Vein puncture is commonly used for blood sampling, and accurately locating the blood vessel is an important challenge in the field of diagnostic tests. Imaging systems based on near-infrared (NIR) light are widely used for accurate human vein puncture. In particular, segmentation of a region of interest using the obtained NIR image is an important field, and research for improving the image quality by removing noise and enhancing the image contrast is being widely conducted. In this paper, we propose an effective model in which the relative total variation (RTV) regularization algorithm and contrast-limited adaptive histogram equalization (CLAHE) are combined, whereby some major edge information can be better preserved. In our previous study, we developed a miniaturized NIR imaging system using light with a wavelength of 720–1100 nm. We evaluated the usefulness of the proposed algorithm by applying it to images acquired by the developed NIR imaging system. Compared with the conventional algorithm, when the proposed method was applied to the NIR image, the visual evaluation performance and quantitative evaluation performance were enhanced. In particular, when the proposed algorithm was applied, the coefficient of variation was improved by a factor of 15.77 compared with the basic image. The main advantages of our algorithm are the high noise reduction efficiency, which is beneficial for reducing the amount of undesirable information, and better contrast. In conclusion, the applicability and usefulness of the algorithm combining the RTV approach and CLAHE for NIR images were demonstrated, and the proposed model can achieve a high image quality. In the medical field, venipuncture is one of the critical and fundamental approaches for examination of health conditions and precise treatment monitoring of diseases, and involves blood sampling analysis or intravenous medication administration through intravenous catheterization . ImpropeMany methods of identification of the veins have been investigated for the automatic insertion of a catheter into the vein, most of which are based on either the preprocessing method or the vein extraction method ,11. SeveThe objective of applying preprocessing techniques before vein feature extraction is to improve the poor contrast for distinguishing veins from other features. Contrast-limited adaptive histogram equalization (CLAHE)  is dividIn this study, we developed a cost-effective, miniaturized vein imaging system using a relative total variation (RTV) regularization -based veTwo NIR LEDs centered at a wavelength of 940 nm were employed as light sources to illuminate the target samples, such as the veins located at the dorsum of a hand and at the cubital fossa. The examined veins were positioned below the heart level of a human to make veins fill with blood as in the practical environment. The imaging target models had standard Korean skin characteristics of a bright yellow color, little hair, little fat, etc. The reflected light from the vein blood vessels and the surrounding tissues in the region of interest (ROI) was detected by the IR CMOS sensor module  after passing through a dichroic filter. The dichroic filter had an edge wavelength of 757 nm and a transmission efficiency of >93% in the range of 768–1100 nm; thus, it played the important role of an optical long-pass filter. The visible light coming from the DLP projector   was reflected at the dichroic filter and incident onto the imaging target area for clearly visualizing the invisible vein while the IR light was passing through. Commercial components of NIR LEDs  and IR CMOS sensors  (3280 × 2464 pixels) without IR-CUT filters were used to construct a cost-effective miniaturized vein viewer system. The center wavelength of an NIR light source was selected by a specification of the IR CMOS sensor sensitivity for the optical wavelength. The image quality-based system performance was evaluated and optimized with regard to the light angle, number of NIR LEDs, optical power, LED position, etc. An optical long-pass filter centered at 720 nm was placed in front of a detection sensor to enhance the SNR of the vein pattern image, because unnecessary visible light can be completely rejected by a long-pass filter . A commercialized focusing lens was inserted in front of the IR sensor after calculating the imaging range, view angle, focal length, and image display size of the DLP projector. The DLP working distance was slightly mechanically adjusted using three-dimensional (3D) micro-stages to match the DLP illumination area with the ROI size of the NIR light, because the size of the DLP illumination area and the ROI of the NIR light can change according to the respective optical paths. When the IR LED light was incident on the imaging samples, the reflected light from the ROI was detected by the IR sensor module and transferred to the main control processor (Raspberry Pi3 compute tool kit) with a 1.2-GHz quad cortex A53 and 400-MHz video core graphics processing unit (GPU). After image-processing algorithms were applied, the final image was displayed on the surface of the ROI of the imaging tissue by a DLP projector in a real-time display of approximately 60 frames/s.To analyze the performance of the modified RTV algorithm for a system with an optical difference, we acquired the image results for two systems that differed only in the wavelength to replace the NIR LEDs, having a center wavelength of 850 nm with the NIR LEDs having a center wavelength of 940 nm. The acquired images were post-processed using the proposed algorithm. Furthermore, a color image sensor was added and positioned next to the DLP to obtain real images of the target samples. The color images could be acquired while the DLP was turned off. The ROIs of the color image sensor and IR sensors were mechanically adjusted to be identical even if they did not perfectly match from the center to the edge region.The total variation (TV) regularization method for preserving a large-scale edge during smoothing was introduced by Rudin et al. ,31,32 ann et al.  solved ti et al.  introducariation ,35,36. IMedian filtering is a nonlinear technique that effectively removes noise while preserving contours. We set the size of the median mask (or window) to align each pixel of the degraded image  algorithm [ts in mk ,39. k-melgorithm ,41, whick-means clustering algorithm was blended with the optical image captured at the same position as the NIR image. Here, k was 3, corresponding to the background, tissue area, and subcutaneous veins.Herein, an RTV regularization-based framework is proposed as a dorsal vein recognition algorithm. TM , with the following computer specifications: central processing unit—Intel , Xeon Platinum 8168 @ 2.70 GHz; random-access memory—Samsung, South Korea, 8 G × 4 DDR4 21300; GPU: NVIDIA, USA, GTX 1080 11 GB. The utility of the proposed image-processing method for practical applications was confirmed.Image processing was performed using MATLABThe objective of this study was to extract veins accurately, and to achieve this goal, we performed effective smoothing to compare veins with noise and foreign objects to distinguish them from grayscale and morphologically. Therefore, with a smaller amount of residue remaining after vein extraction, the smoothing method is more effective.We evaluated the applicability of the designed framework for dorsal vein recognition with regard to the profile and coefficient of variation (COV) ,43. In tIn our previous study, we developed a cost-effective, miniaturized, handheld vein imaging system. The system comprises two NIR LEDs centered at 940 nm wavelength and uses the principle of obtaining an image from a CMOS detector through a dichroic filter and a long-pass filter by exposing an IR light source to the hand. In this study, a vein adaptive smoothing approach based on RTV regularization was applied to an established imaging system to obtain more accurate blood-vessel extraction images.A to D in the yellow-box regions. The ROIs were set as boxes A to D because these parts quantitatively determined the amount of additional noise relative to the manicured vein. A smaller amount of noise indicated more successful vein extraction. The evaluated COV factor of the vein segmentation image with the proposed filtering using RTV regularization was relatively low compared with the COV factors for image-processing methods ①to ③. The average COV factors of image-processing methods ① to ④ were 0.86, 0.60, 0.35, and 0.05, respectively. Here, the average COV factors represent the mean value of the calculated COV in each region. When the proposed algorithm was used, the quantitative average COV value was improved by a factor of approximately 15.77 compared with the case where the algorithm was not used. Additionally, the COV result obtained by applying the proposed algorithm was improved by factors of 11.03 and 6.39, respectively, compared with the result obtained by applying the median and Wiener filter to the obtained image. This result indicates that the proposed algorithm can effectively extract the vein lines while minimizing the distorted extraction in an NIR image of 850 nm.In this study, the results were analyzed focusing on the effective use and usefulness of the developed imaging system and algorithm when applied to venous blood vessels. The applicability to radial blood vessels was proved, and the results in arteries were not analyzed. However, the field in which this system can be used more effectively is percutaneous coronary intervention (PCI), which is closely related to the arterial system. In a study of Cesaro et al., the comparison of transfemoral and transradial-based methods when performing PCI provided scientific evidence that the use of the radial artery is effective in terms of bleeding risk and time required . TherefoFor efficiently applying the blood-vessel image acquired using NIR light to the field of medical diagnosis, segmentation of the target blood vessel is important. In the study of Jang et al., the noise reduction efficiency was significantly improved as a result of visually evaluating the accuracy of blood-vessel extraction by applying an algorithm using the CLAHE approach based on adaptive histogram equalization to NIR images . HoweverIn this study, a vein viewer system based on NIR light developed by our research team was used to acquire an image of a blood vessel, and the possibility and effect were quantitatively analyzed by applying an algorithm that can achieve both a smoothing effect and contrast enhancement. However, based on the results of this study, it is considered that the improved blood vessel images acquired using light will need to be evaluated in the future with diagnostic angiography or ultrasound images that were objectively used. In addition, we plan to conduct additional studies for various clinical variables , not just using a single blood vessel image.The results of the study indicated that the proposed filtering method using RTV regularization for vein extraction is effective for improving the imaging performance of NIR images. This technique is expected to facilitate accurate and stable venipuncture through clear visualization of the invisible dorsal vein.


In this work, we investigate the effect of the cation structure on the structure and dynamics of the electrode–electrolyte interface using molecular dynamics simulations. A constant potential method is used to capture the behaviour of 1-ethyl-3-methylimidazolium bis (trifluoromethane)sulfonimide ([C In today’s modern society, a wide range of electronic products, including mobile phones, laptops, cameras, pacemakers, hearing aids and electric vehicles, heavily rely on the energy storage technology behind them. Among promising candidates as future energy storage devices are batteries and electric double-layer supercapacitors (EDLSC). A striking difference between these two systems is that no chemical reactions occur on the electrodes of an EDLSC and energy is stored via ion adsorption on the electrodes, whereas energy is generated through chemical reactions involving the electrodes of a battery. Batteries are suitable for long-term energy storage whereas EDLSCs are ideal for repeated short-term power delivery, such as repetitive breaking in electric vehicles. In general, batteries possess high energy density whereas EDLSCs have high power density. However, energy storage devices often need to meet both power density and energy density requirements, so developing devices that achieve both is of importance. To advance the utility of EDLCS, it is vital to understand the molecular-level formation of charge layers in the vicinity of electrodes, or the electric double layers (EDLs) as this is a key factor for their performance. We will refer to EDLSCs as supercapacitors in the rest of this paper since we are not considering pseudocapacitors.As well as modifications of the surface chemistry and topological characteristics of electrode materials, the electrolyte can be altered to improve a supercapacitor’s performance. Supercapacitor technologies rely on the EDL that forms at the electrode–electrolyte interface . In 1853Room temperature ionic liquids (ILs) are liquids consisting of only cations and anions. They are of particular interest for use in supercapacitors due to their low volatility, high ion density and wide electrochemical window. Interesting structures can form in the EDL of ILs due to the different size and structure of the anions, their interaction with the electrodes and with each other. This means that even without charge applied to the electrodes, distinct layers of charge can form near the electrode surface in many IL electrolytes. On application of a potential, over-screening and crowding of ions are observed. In general, the classical models described above do not represent the structures in ILs well. In addition, the high viscosity and charge density of ILs mean that the charge/discharge mechanism is likely to differ from that in lower viscosity electrolytes where the ion density is lower and mobility is higher.The structure of the EDL and its change on charge/discharge is one key factor determining the ultimate performance  of a supercapacitor. Because extensions to the standard model are necessary to gain a molecular-level understanding of the formation of the EDL, further work is required . To thisThe structure of the EDL influences the performance of a supercapacitor. However, the mobility of ions, which are related to the electrolyte viscosity or diffusivity, also plays a role, particularly on the charge/discharge rate. Computer simulations, such as molecular dynamics (MD) simulations, can be used to gain an insight into the atomic-level formation of layers in EDLs. In MD simulations, two techniques have been commonly used to model the charged electrodes: a fixed charge method (FCM) and a constant potential method (CPM) ,13,14. IRecently, various groups have reported the use of the CPM to investigate the molecular-level formation of EDLs in the vicinity of electrodes. For example, Noh and Jung  studied yanitsky  studied In this work, we investigate the effect of the cation structure and dynamics on the layering in the electrode-to-electrolyte interface (or EDLs) using molecular dynamics (MD) simulations by studying two ionic liquid electrolytes with planar graphene electrodes. The ionic liquids are 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([Cat 298 K ). We useat 298 K  to captuAll-atom molecular dynamics (MD) simulations were carried out using the OPLS force field for the [CTf2] ILs ,20,21. Tterature  and haveterature . The eleterature . Followi) solver  with a s) solver . We repoWe then used a simulated annealing (SA) procedure to ensure that the IL ions were mixed properly ,27. In tlammps.sandia.gov).In the simulations of pure ILs, the temperature and pressure were controlled via a Nosé–Hoover thermostat ,29 with The size of our atomic-level models of supercapacitors are large compared to most similar systems in the literature in terms of both the number of atoms making up the graphene electrode and the number of ion-pairs for the electrolyte. To ensure that our results are reliable we also consider three independently generated samples for each system, averaging these to obtain representative results or comparing the results of the three samples to give an indication of the reliability of the results. We also monitored how the charge density developed on the electrode with time and how the density profiles evolved with time to ensure that appropriate simulation times were used to determine averages. This is particularly important for ILs that are even more viscous than those studied here, since they are likely to become kinetically trapped within the relatively short timescales of the simulations. The development of symmetric profiles at Once we achieved equilibration of the IL in the presence of graphene electrodes, we applied a potential difference across the simulation cell  using the CPM ,13,14 imPrior to testing our supercapacitor models under varying applied potentials, we tested the force field parameters on pure ILs to ensure that we reproduced the experimental density of the ILs ,32. We gWe equilibrated our samples using a SA procedure ,34. We tThe equilibrated systems were used as the initial states to which we applied a potential difference . The results for [SCN] ) whereasim][SCN] .The distribution of charges on the carbon atoms of the electrodes can also be determined from the simulations. Our results also indicate that, with an increase in m][NTf2]  and theyThe change in the amplitude of the normalised population with applied voltage is less pronounced with the +) see . The volWe report the normalised mass density distribution of each ion in  IL a,b. This] IL  curves of each ion type.Our simulation results indicate that 10 m2 s−1. When we surface , giving Considering the second issue, Simonnin et al.  investigIn this work, we also studied the response of ions to an applied potential in a supercapacitor model where we set the electrode-to-electrode distance to ∼10 nm and ∼11 nm for [Ce et al.  investigOur MSD curves reported in t. This means that the ions do not have to be in the first layer at time We also calculated a local MSD in the EDL only . The loc is zero .We investigated the dynamics of two ionic liquids with different viscosities as electrolytes in a supercapacitor model where flat graphene was used as the electrode and the temperature was 294 K. A constant potential difference was applied across the supercapacitor model to observe the behaviour of ions in response to electrode surface polarisation. The partial atomic charges of electrode atoms, which fluctuated during the constant potential simulations, caused ions in the EDL to readjust their configurations. Our simulations revealed that the ring of the [COverall, the results showed significant differences in the double layer structure and orientation of the molecules with a change in the cation and the applied potential. The dynamics were also significantly affected by the cation, which will influence the power density of the supercapacitor; however, it did not change greatly with the applied potential. Moreover, the overall charge distribution was not strongly influenced by the cation or potential and hence, there, the capacitance remained similar for the systems considered.On charging, the ions rearranged and reoriented within a region of ∼1 nm from the electrode until a steady charge on the electrode and steady charge density profile developed. This occurred on timescales of Our computational procedure will enable us to capture the molecular-level interactions between ionic liquid and electrode materials in supercapacitors to assist in obtaining a better performance . In addition, our computational procedure can be exploited to screen numerous ionic liquids as electrolytes, and the outcomes of simulations could be input to a machine learning pipeline to explore pure or mixed ionic liquids for the ultimate optimised performance.


P < 0.05), respectively. Moreover, the average VAS score was 1.73 ± 0.27 , demonstrating obvious improvement after the operation. To our best knowledge, this is the first time to perform the resection of the distal tibial interosseous osteochondroma involving the fibula without interrupting the inferior syndesmotic complex especially the AITFL and PITFL. We believe that this strategy may pave a new way for optimized clinical outcome for these patients with distal tibiofibular interosseous osteochondroma. This clinical trial study is registered with number ChiCTR1900024690.Osteochondroma is one of the most common benign bone tumor; however, the surgical treatment still remains a challenge for those that occur at the distal tibiofibular interosseous location. Previously, the transfibular approach has been successfully described, but the potential damage of the syndesmosis would give rise to the instability of the ankle joint and thus may result in the unfavorable long-term outcome. Here, a revised strategy which can protect the syndesmotic complex is introduced. From 2010 to 2017, eleven patients with the distal tibiofibular interosseous osteochondroma who underwent the revised surgery were collected. The distal fibular osteotomy and posterior tibial osteotomy were performed to keep the inferior syndesmosis intact for better stability of the ankle joint. Both the anterior tibiofibular ligaments (AITFL) and posterior tibiofibular ligaments (PITFL) have been preserved successfully, and thus, the stability of the ankle joint has been maintained due to our strategy. The VAS and AOFAS scores were utilized to assess the clinical outcome and function. Postoperatively, all the patients were pain-free and were able to wear the appropriate shoes at the last follow-up. Preoperative and postoperative AOFAS scores were 93.63 ± 6.91 and 47.27 ± 5.27 ( Osteochondroma is defined as a benign lesion with a bony structure covered by a cartilaginous cap . It is rSo far, the clinical outcome after the surgery is not favorable both for the surgeon and patients. Notably, the poor outcome may be attributed to its disruption for the ankle joint, especially, the inferior tibiofibular syndesmosis . In otheNormally, the anterior tibiofibular inferior ligament (AITFL) is the weakest one of the four syndesmotic ligaments and is the first to yield to forces that create an external rotation of the fibula around its longitudinal axis . Thus, iIn this study, for the first time, we introduced a revised strategy to remove the osteochondroma without disturbing the inferior syndesmosis by using distal fibular osteotomy and posterior tibial osteotomy to keep the syndesmostic complex, especially AITFL and PITFL, intact during the surgical procedure. We evaluated the clinical functional outcome of the patients and proved that this new surgical technique could accomplish the thorough resection of tumor as well as preserve the inferior tibiofibular syndesmosis complex, thus significantly improving the stability of the ankle joint for the better long-term function of the ankle joint and clinical prognosis.From October 2010 to January 2017, a total of 11 patients with distal tibiofibular interosseous osteochondroma who were admitted to the China Three Gorges University & Yichang Central People's Hospital were collected. There were 7 male and 4 female patients with an average of 27.52 ± 11.36 years , and all the demographic and clinical data including age, gender, the affected side, symptoms were recorded . The incAll the patients performed X-ray with anteroposterior (AP view) and lateral position preoperatively, including a mortise view as well. Radiographs were evaluated by an experienced orthopaedic surgeon to determine the radiographic finding. In addition, a computed tomography (CT) plain scan with three-dimensional reconstruction and magnetic resonance imaging (MRI) examination were also acquired if necessary to assess the involvement of the lesion. All the procedures were approved by the Ethics Committee of our hospital, and all the patients signed a written consent before the surgery.After the lateral approach was performed, the peroneus muscle was retracted away to expose the distal fibula. The locking plate was placed and every hole of screw was prepared prior to the distal fibular osteotomy to ensure the later anatomical reduction of the fibular fragment when the lesion resection was achieved. Then the osteotomy of distal fibula was performed right above the level of the inferior syndesmosis or according to the location of tumor mass, preventing the damage brought to the syndesmosis complex. Next, the distal fragment of fibula was rotated anteromedially to expose the tumor mass. If the tumor mass encroached the lateral side of tibia, the posterior osteotomy of the distal tibia (osteotomy of Volkmann's tuberosity) was performed to expose the intact margin of the lump, and the Kirschner wires were used to fix the retracted Volkmann tuberosity back; thus, the inferior tibiofibular syndesmosis complex especially the AITFL was successfully preserved. After the tumor mass was removed thoroughly, the fragment of fibula was placed back to its original location to achieve the anatomical reduction. If necessary, the cannulated screw (diastasis screw) was utilized to stabilize the inferior tibiofibular joint. Autologous iliac bony grafting would be taken into account when the remaining cave was too large to prevent the nonunion or malunion. Further histology was performed to confirm the diagnosis of osteochondroma with no malignant transformation .Postoperatively, the patient was mobilized with plaster for nonweight bearing for 4-6 weeks. Next, the patients were encouraged to commence active exercises with a full range of motion at the ankle joint. Meanwhile, gradual transition from partial to full weight bearing was performed under proper protection. At final routine clinical follow-up, the functional outcome and the range of motion were recorded.The scoring system of the American Orthopaedic Foot and Ankle Society (AOFAS)  [P value < 0.05 was regarded as statistically significant.All values were presented as mean ± standard deviation (SD) and analyzed by repeated measures (ANOVA). A In this study, all 11 patients were successfully followed-up with average of 1.9 ± 0.4 years. All patients were shown to resume with full activities at the last follow-up, and no evidence of recurrence was observed. Moreover, all the patients were pain-free and were able to wear the appropriate shoes such as casual shoes or sneakers; however, they complained no proper shoes were available for them before the operation.All the lesion in this study was further confirmed as osteochondroma, which have been previously proved to be benign . All theP < 0.05). The good rate was 54.5% with 6 cases rated as good, 4 as fair, and only 1 as poor , indicating the favorable outcome with long-term observation  infection with superficial tissue and 9.09% (1/11) nonunion rate . The infections were solved with enhanced wound dressing accompanied with the application of antibiotics. No deep tissue infection or osteomyelitis was observed. The fibular nonunion patient was managed with revision surgery by replacing the internal fixation coupled with autologous bone graft, and the ultimate union was observed at 6 months after the revision surgery. The typical cases are shown in Figures The osteochondromas discussed here were referred as those located at either the metaphysis or the junction of the metaphysis of the tibia and fibula. Although these has been explored by several studies for the last decades , 11, fewIt has been reported that osteochondromas are considered as the most common benign bone tumors . They arIn our study, we introduced a revised strategy to keep the syndesmostic complex intact during the surgical procedure by distal fibular osteotomy and distal anterolateral tibial osteotomy to preserve the distal anterior tibiofibular ligament (AITFL). Normally, the AITFL is the weakest one of the four syndesmotic ligaments and is the first to yield to forces that create an external rotation of the fibula around its longitudinal axis . Thus, iIn a word, our findings proved that the new strategy by using the distal tibial osteotomy was able to achieve the preservation of the inferior tibiofibular syndesmosis especially the AITFL, leading to the better functional outcome and favorable prognosis for the patients.Herein, we introduced a new strategy to maintain the distal anterior tibiofibular ligament intact, thus protecting the integrity of the syndesmosis complex, which is believed to be the keystone of the stability of the ankle joint. With the help of this revised modified surgical procedure, the syndesmosis complex was successfully preserved after the tumor resection was achieved. The observation of the clinical outcome in this study proved that this new surgical technique is able to significantly improve the stability of the ankle joint and the long-term function. To our knowledge, this is the first time to perform the excision of the distal tibial interosseous osteochondroma involving the fibula without interrupting the inferior syndesmotic complex especially the AITFL. We believe that this strategy may pave a new way for the further clinical application for these patients with distal tibiofibular interosseous osteochondroma to obtain a more stable ankle joint after surgery.


This paper describes the process of adapting an early childhood development programme, with proven effectiveness in Bangladesh, for integration into government health services in rural Bangladesh. Through a three-stage process, we adapted an evidence-based, home-visiting, programme (Reach-Up and Learn) for delivery in government health clinics by government health staff as part of their regular duties. Stage one involved preparing an initial draft of two parenting interventions for use with: (1) pairs of mother/child dyads, and (2) small groups of mother/child dyads. In stage two, we piloted the adapted interventions in nine clinics with a total of twenty-seven health staff and 357 mother/child dyads. We used data from mothers' attendance, feedback from participating mothers and health staff and observations of parenting sessions by the research team to revise the interventions. Stage three involved piloting the revised interventions in six clinics with eighteen health staff and 162 mother/child dyads. We gathered additional data on mothers' attendance and used observations by the research team to finalize the interventions. Through this three-stage process, adaptations were made to the intervention content, process of delivery, materials, and engagement strategies used. The largest challenges were related to incorporating the parenting programme into health staff's existing workload and promoting mothers' engagement in the programme. We also simplified the content and structure of the curriculum to make it easier for health staff to deliver and to ensure mothers understood the activities introduced. This iterative piloting was used prior to implementing and evaluating the interventions through an effectiveness trial. Worldwide 43% (250 million) children under-5 years of age in low- and middle- income countries (LMIC) are at risk of not attaining their full developmental potential due to poverty, malnutrition, and lack of appropriate early stimulation . There iPoor Bangladeshi children show a significant cognitive deficit as early as 7 months of age compared to their more affluent peers, and the deficit grows larger as children reach 5 years of age . These dThe Bangladeshi government delivers primary health care through community clinics (CCs) in rural areas across the country. The CC is the lowest tier of the health facilities providing primary health care, family planning and nutritional services. There are over 13,000 CCs and they are established in all rural areas including remote and hard to reach areas. Each CC is staffed by three health workers: a Community Health Care Provider (CHCP), a Health Assistant (HA) and a Family Welfare Assistant (FWA). The CHCP works full-time in the clinic, and the HA and FWA spend 2–3 days at the clinic and the remaining days work in the community. CCs provide services for 6 days a week with operating hours from 9 a.m. to 3 p.m. The majority of CHCPs and HAs have Masters degrees and the FWAs have usually completed secondary (grade 10) level education. Most patients attend clinic in the morning and CC staff generally finish their regular schedule work around noon. Given the reach, structure and staffing levels of the community clinics, they provide a logical service for integrating parenting sessions within the routine work of the clinic.The aim of this study was to adapt the Reach-Up and Learn home-visiting programme so that it could be implemented through the CCs with sessions conducted by government health staff as part of their routine duties. The beneficiary target group was mothers of undernourished children aged 6–36 months. We targeted undernourished children as undernutrition is an important risk factor for poor development, is relatively easy to measure, and has high prevalence in Bangladesh , 11.We developed two adapted versions of the Reach-Up and Learn home visiting programme for integration into the community clinic services including curricula for use with: (1) pairs of mother/child dyads, and (2) groups of four to five mother/child dyads. Both curricula have potential to extend the reach of the intervention, which was previously delivered with one mother/child dyad. The intervention development approaches used included: (1) the “target population centred” approach that involves incorporating the views and actions of the participants and delivery agents, and (2) the “implementation-based” approach that involves maximizing the likelihood that the intervention will be used in the real world . The stuReach-Up and Learn is a home-visiting, play-based intervention for mothers of children aged 6 months to 4 years that was developed from the Jamaican early stimulation programme . This prThe aim of stage two was to identify the enablers and barriers to implementing the adapted pair and group curricula within the community clinic network, using the existing health staff. This included factors relating to the content, structure, materials, and process of delivery of the curricula, the strategies used to recruit and engage the mothers in the session and the challenges faced by health staff in integrating the sessions into their regular workload.The study was conducted in the Sonargaon sub-district, under Narayanganj district, located 80 km from Dhaka city. Sonargaon consists of 30 community clinics and nine clinics were purposively selected for easy accessibility and availability of transportation facilities. We screened all households with children aged between 6 and 33 months old living within 45 min walking distance from the selected clinics. All children were weighed and those with weight-for-age z-score of ≤-2SDs of the WHO growth standards were eligible to participate in the study. We enrolled up to 40 children in each clinic; when more than 40 children were identified, we randomly selected 40 children to participate. The programme was discussed with the mother and other members of the household who were present and the mother was invited to participate in the parenting sessions. Children with severe malnutrition (<-3SDs weight for age z-score) and children with disabilities were referred for specialist services and excluded from the study. Details of the number of clinics, health staff, and mother/child dyads participating in the piloting activities are shown in The research team provided 2 weeks training in how to conduct the parenting sessions to the Community Health Care Provider (CHCP), Family Welfare Assistant (FWA) and Health Assistant (HA) from each of the selected nine clinics. Training was conducted in two waves: health staff from five clinics were trained in the pair curriculum and health workers from four clinics were trained in the group curriculum. A member of the research team supervised the parenting sessions with a minimum of two visits per week to each clinic. During each visit, the supervisor assisted the health staff in preparing for the session, provided ongoing support during the session, and completed a monitoring form with input from the health staff to record enablers and barriers to programme implementation. During this pilot study, mothers attending clinics implementing the pair curriculum were offered a total of six parenting sessions, while five parenting sessions were offered to mothers attending clinics delivering the group curriculum. Each mother-child dyad attended fortnightly sessions. Health staff in pair clinics conducted 9–11 sessions/week and staff in group clinics delivered 4–6 sessions/week.We collected data on parent attendance at each session and conducted semi-structured interviews with health care staff and a subsample of participating mothers. Twenty-three mothers were selected from two of the pair clinics based on session attendance to identify the enablers and barriers to attendance from the perspective of the mothers. The sample included five mothers who attended all six sessions, ten mothers who attended three sessions, four mothers who attended one session and four mothers who attended zero sessions. Nineteen mothers who had attended three or more sessions were selected from two of the group clinics to investigate the extent to which the mothers understood the activities that were introduced in the sessions. Mothers were asked to show the interviewer the toy, book, and language activity that had been introduced in the previous session and to describe the developmental and nutritional message. This data was used to assess if mothers remembered and understood the activities and messages from the session. Mothers were also asked how many times a week they conducted the activities at home. Mothers were interviewed at their home by a female member of the research team using a semi-structured questionnaire. Mothers' responses were written verbatim. Each interview lasted ~30 min. We also conducted two group discussions with clinic staff to explore the enablers and barriers to implementing the parenting sessions from their perspective. A semi-structured interview was used and covered enablers and barriers relating to the curriculum content, the materials used, the process of delivering the sessions, mother engagement, and integrating the sessions into the regular clinic activities. Nine health staff from pair clinics and eight health staff from the group clinics participated in these discussions. Two researchers conducted these interviews with one moderating the discussion and the second keeping detailed notes.Mothers' attendance declined over time in both pilot studies . Table 3The session is very much and he enjoyed the sessions. But the clinic does not provide any vitamin syrup. If the clinic gives medicine, nutritious food and advice about nutrition and sickness then I will come to the sessions.” (Mother from pair clinic)“In the group clinics, the majority of mothers (95%) reported doing the activities at home frequently with their child. However, the activities reported were not always age-appropriate, indicating that more clarity was needed during session delivery.Key enablers and barriers from the perspective of the clinic staff and core observations from the supervisors are also given in I personally think the program is good. Sometimes I feel it is an extra work but not always. If children play well and do better then I feel good to see that the children are improving.” “Other barriers to intervention implementation were related to the complexity of the curricula. For example, there were too many activities included in each session, the curriculum manuals were hard to use, and health workers spent insufficient time on some activities. Health staff were also overly didactic during the parts of the session that involved discussion. Based on the data collected, we made revisions to both the pair and group curriculum to make the sessions easier to conduct and to encourage more participatory and interactive delivery methods, and we adapted the process of implementation to ensure the programme could be managed within the staff workload see . In addiThe main aim of the stage three was to evaluate the effectiveness of two different engagement strategies on mothers' attendance. We also continued to monitor the quality of the parenting sessions to identify if the changes made to the curricula led to more successful implementation.For financial and logistical reasons, the pilot studies in stage three were conducted in only six of the nine selected clinics. From the original sample of 40 parent-child dyads/clinic, we excluded parents who lived more than a 30-min walk from the clinic and then randomly selected 20 parent-child dyads from pair clinics and 30 parent-child dyads from group clinics to continue in the programme .In community clinics conducting the pair sessions, we organized community motivational meetings that were attended by village elites, local leaders, school teachers, health care staff and the selected mothers and their families. We provided psychoeducation around the importance of play and stimulation for child development and introduced the play materials used in the programme. The village leader also delivered a speech encouraging families to engage with the programme. In the community clinics conducting the group sessions, we offered mothers an incentive of half a liter of cooking oil for every session attended.A further four parenting sessions were offered to mother-child dyads in all six clinics participating in the stage three piloting activities. Mothers attended sessions once a fortnight and a total of 4–5 parenting sessions/week were conducted in pair clinics and 2–3 parenting sessions a week were conducted in group clinics. Supervisors continued to attend a minimum of two sessions per week in each community clinic to provide ongoing support to the health staff and to document the quality of the sessions.Mothers' attendance at the sessions was recorded. Supervisors completed record forms on the enablers and barriers to implementation after each session.The adaptations to the curricula, including adaptations to the content, materials, and structure as shown in Mothers' attendance was greatly improved with both engagement strategies used . The incThe final version of the curricula consisted of 12 fortnightly parenting sessions, suitable for children aged 6–36 months that were repeated every 6 months. Activities were divided into child age months for the pair curriculum and either 6- or 12-month age bands in the group curricula. Hence, when the sessions were repeated, most children would be introduced to activities in the higher age range. Each session included the following: (1) feedback from the previous session, (2) a song, (3) demonstration and practice of the toy, book and language activities, (4) developmental and/or nutritional message(s), and (5) review and reminder of home activities. Mothers were given at least one book and one toy during each session and these were swapped for a different book and toy at the next session. Given the cost and the logistical challenges associated with providing oil and the success of the community motivational meetings, we chose the latter strategy as the key engagement strategy to be used in the effectiveness trial. We also planned for quarterly refresher meetings within the community with small gifts provided to mothers with high attendance at the sessions to sustain mothers' engagement in the programme. We also decided to only recruit eligible mothers who lived within a 30-min walking distance from the community clinic. The revised curricula have since been evaluated with large benefits found for child cognition, language, motor development and behavior in addition to home stimulation, maternal knowledge of child rearing and maternal depression . InteresIn this brief research report, we describe the process of adapting an early childhood parenting intervention with proven effectiveness in the Bangladeshi context for integration into the government health service including delivery by existing health staff. Adaptations were required to take into account differences in the delivery location (clinic vs. home), delivery agents used , and the intended reach (higher number of mothers reached per delivery agent) of the intervention. The adaptation process involved two rounds of piloting and during the piloting process we (1) measured mothers' attendance at the sessions, (2) incorporated feedback from the intended beneficiaries (mothers) and the delivery agents , and (3) documented enablers and barriers to implementation through ongoing observations of the research team. Adaptations were made to the content of the curriculum, the materials used, the process of delivery, and the engagement strategies used. The paper illustrates the importance of thorough piloting of all aspects of an intervention, when moving from smaller-scale implementation in an efficacy trial to large scale implementation through an existing service. The value of investing resources to iteratively field test an adapted intervention in the context in which it is to be implemented is demonstrated by the large and wide-ranging benefits to children and mothers who later participated in an effectiveness trial .There are examples in the literature relating to (1) transporting evidence-based parenting interventions across countries –20, (2) Firstly, attention to staff workload is important, especially when integrating into an existing service. Through the piloting process, we aimed to incorporate the additional responsibilities into staff's existing duties without reducing their effectiveness in other aspects of their role, and without leading to staff demotivation. Other early childhood parenting interventions have reported that staff workload is problematic leading to high staff turnover  and/or aSecondly, it is important to develop a feasible and effective strategy for engaging participants in the intervention. We found the strategies that we had previously used to engage mothers in a home-visiting intervention, were less effective at engaging mothers in a clinic-based intervention. The lack of an incentive and family members discouraging attendance were the most frequent barriers to mothers' engagement. These barriers have also been reported in a recent study in Bangladesh . We trieThirdly, it is important to ensure sessions are simple for staff to deliver and the messages and activities are easy for mothers to understand. We found the curricula manuals were too complex for the health staff to use during the sessions, particularly for the group sessions. Navigating through the different sections of the manual took their attention away from the mothers and children, leading to lower participation and interest. We therefore designed a laminated summary card for use during the session. Also, when many activities were introduced during the session, mothers were unable to recall the content. A simple, streamlined intervention with user-friendly manuals is recommended to maintain the interest and engagement of participants and to maximize the likelihood that the intervention will be delivered with fidelity . ReducinFourthly, using active learning and evidence-based behavior change techniques  are key characteristics of effective early childhood programmes , 27. ThrFifthly, it is important to decide on the target population for the intervention as it may not be feasible to offer a parenting intervention for all families in need. For example, in Malawi, health staff were only able to reach 14.2% of eligible children, with an early childhood development intervention . We targFinally, incorporating participant feedback including feedback from potential beneficiaries and from the delivery agents is an important part of the adaptation process –23, in afardina.mehrin@iccdrb.org.The datasets generated in this article are not readily available because most of the data is not suitable for sharing as it is not fully anonymised. Requests to access the datasets should be directed to The studies involving human participants were reviewed and approved by Institutional Review Board of the International Center for Diarrhoeal Disease Research, Bangladesh . Informed consent was provided by all health staff and mothers participating in the study.JDH and HB-H contributed to the conceptualization of the study and funding acquisition. SM, N-ES, JDH, MH, and SH contributed to project administration. SM, JDH, HB-H, N-ES, MH, and SH contributed to investigation. SM, HB-H, and JDH were responsible for data curation and data analysis. SM and HB-H were responsible for writing the original draft. All authors reviewed and edited the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Most ultrasonic flowmeters utilize several wedge sensors for transmission and reception. Thus, the location and alignment of the sensors are critical factors that determine the performance of the ultrasonic flowmeter. In this study, we proposed an ultrasound liquid flowmeter utilizing a 128-element linear array transducer with a transmit delay control for varying the incidence angles of ultrasound wave transmission. The performance of the flowmeter was evaluated at flow rates of 0–50 L/min in a specially designed pipe system. Flow estimation was performed with the transit-time method using cross-correlation with phase zero-crossing for sub-sample estimation. While a single plane wave approach performed invasive electromagnetic measurements with only 74% accuracy as a reference, a multiple angular compensation method with 24 angles was proposed to increase the accuracy of measurements up to 93%. This study demonstrated the capability of the non-invasive single-sided ultrasonic flowmeter with a linear array transducer for liquid flow measurements in the metal pipe system. Flowmeters  have beeThe performance of the transit-time ultrasonic flowmeter can be degraded for various reasons, including the misalignment of transmitter and receiver sensors, irregular pipe surface conditions, errors in time difference estimation, and non-invasive  installation of transmitter and receiver sensors ,17. To mAs employing more sensors with several wave traveling paths can increase the accuracy of the flowmeter, previous studies have tried to use array sensors for the flowmeter ,20,21. OBy utilizing the delay control of the ultrasound system, an array transducer can replace multiple wedge sensors. When the transmit delays for wave transmission are controlled, the incidence angle can be adaptively modified without varying the physical position and wedge angle of the transducer. Hence, both the transmission and reception of ultrasound waves can be achieved by one flat array transducer. Ultrasonic radio frequency (RF) signals from multiple receiver channels will include all possible reflective paths from the pipe wall. Therefore, ultrasonic signals from the appropriate transducer receiver sensors can be used to calculate the flow rate.In this study, a single-sided non-invasive ultrasonic flowmeter is proposed for liquids flowing through a metal pipe to obtain more accurate and precise flow estimates. The flowmeter was implemented by utilizing the delay control function of an ultrasound imaging system and array sensors. Afterward, the performance was evaluated using the ultrasound data acquired from the specially designed pipe system. We performed a thorough analysis of the experimental results for non-invasive liquid flow measurements using an ultrasound array transducer. Multi-angle based liquid fluid measurements were also suggested for further improvement.fs) for system data acquisition was four times the transmission frequency. The transmitted signal was a pulsed wave with 2–3 cycles of sinusoidal waves to avoid any overlap between multiple reflections. The width of the transducer was aligned in the vertical direction of the pipe. Then, the height of the transducer was small enough to fit on the surface of the circular pipe (outer diameter is 34 mm). Thus, the flat linear transducer was coupled well on the pipe surface. Ultrasound gel was applied as a couplant agent to match the impedance between the pipe and the ultrasound transducer.Two-dimensional (2D) ultrasonic signals were acquired by an ultrasound imaging system  with a linear array transducer . The ultrasound imaging system consists of a hardware for controlling wave transmission and data acquisition, and a host computer that controls all actions of the hardware and software environments using the Matlab software. Ultrasound waves were generated and received by the ultrasound imaging system with the linear array transducer. The system has 64 independently controlled transmitter channels and 32 receiver channels. The array transducer contains 128 elements with a frequency range of 4–7 MHz and a transducer size of 38 mm × 7 mm . The transducer transmission frequency was set at 5.2 MHz. The sampling frequency . In this study, two types of ultrasound waveforms were investigated: focused beam with a focal position at the surface of the pipe , and plaθi) is the same as the reflection angle (rθ). Considering the incidence and reflective angles, the matching receiver elements for the transmitter elements were calculated  of 20.13° are 90 and 39 for the downstream and upstream, respectively).When ultrasonic waves travel through the pipe and water and then impinge on the opposite side of the pipe, a portion of the incident acoustic energy is transmitted through the pipe, while the rest is reflected from the pipe, as shown in Most of the transmit-time ultrasonic flowmeters performed time estimation using the conventional zero-crossing approach, which detects the zero-crossing time of the received ultrasonic signals ,25. AfteL is the ultrasonic path length through the fluid, c is the speed of sound in the fluid, beamV is the average flow velocity along the ultrasonic beam, and θ is the angle of the propagating ultrasonic wave. As liquid flow velocity is much lower than the speed of sound in general, the flow velocity equation was derived as follows:The time difference between the upstream and downstream  was theoretically calculated using the Reynolds number [Therefore, the flow rate s number . In addiBecause bubbles in the fluid can significantly affect the time estimation performance, bubble concentrations in the pipe were monitored using ultrasound imaging. Ultrasound images of the pipe cross-section  were generated by transmitting plane waves using the 64 array elements (elements 1–64) placed on the pipe surface and collecting the received signals from 32 array elements (elements 33–64). No beamforming was applied for imaging. The imaging region measured 9.5 mm in width by 9.5 mm in height, and the center of the region was at 15 mm depth of the fluids in the pipe. Ultrasound images of the fluid were acquired at different flow rates. As bubbles are strong reflectors of ultrasound waves in the fluid owing to the high impedance mismatch between the fluid and air, the strength of the reflected ultrasound signals in the water was measured from the acquired ultrasound images. When the signal strength is higher, the concentration of the bubbles can be interpreted to be higher. Thus, the relative change in bubble concentration was measured by averaging the signal strength in the imaging region at different flow rates.Angular compensation from various plane wave angles was applied to improve the accuracy of flow measurement using the linear array transducer. To control the incidence angle by delaying the transmission time of each element of the array transducer, multi-angle transmission was used. In this study, 24 incidence angles were applied for both upstream and downstream transmissions. Then, the estimated flow rates were averaged, which is a similar concept as the spatial averaging method . To meas2 was also evaluated to determine the goodness-of-fit.To compare the performance of flow rate estimates, linear regression using the least-squares method was performed between the reference measurements using the electromagnetic flowmeter  and the measurements using various approaches in our study . In the linear regression, the slope  and intercept values were calculated to determine the accuracy of the measurements . The coefficient of determination RUltrasound data acquired from the array transducer at a flow rate of 35 L/min is shown in Ideally, the flowmeter should estimate the zero flow rate when there is no fluid flow in the pipe. However, the flow rate estimation can be affected by the properties of the pipe, the impedance matching of the transducer, and the flow condition. Hence, zero-flow calibration was applied by subtracting the estimated flow rate at no flow . UltrasoThe current study demonstrated the feasibility of using the single-sided non-invasive ultrasonic liquid flowmeter with a linear array transducer. The ultrasound array transducer was used as the transmitter and receiver sensors. As shown in Moreover, it was shown that the accuracy of flow rate measurements using the ultrasound array transducer was lower than that of invasive reference measurements . The possible factors degrading the accuracy of our transit-time ultrasonic flowmeter were the small inner diameter and pipe roughness, as well as the velocity distribution in the pipe ,13. To iK was calculated using theoretical calculation considering the Reynolds number only. The correction factor K can be further validated through an experiment quantifying flow rates, such as liquid collection and measurement methods, to consider other factors affecting K such as pipe radius and roughness [As this study uses a flat linear array, the irregular condition of the pipe surface can disturb the incident waves and eventually lead to measurement errors. Thus, it is expected to have an even surface for at least the length of the flat linear array or that a special measuring window with an even surface can be designed. In a previous study, a Plexiglass viewing window was installed on the metal pipe for the linear array transducer to provide a regular condition of the pipe . Althougoughness ,13,30.For the transit-time ultrasonic flowmeter, the time-shift estimation method plays an important role in determining the quality of measurements. In this study, we performed experiments to compare two estimation methods, i.e., the conventional zero-crossing method and cross-correlation with phase zero-crossing method. As shown in For ultrasound flow measurements in the pipe, bubble concentration has a great impact, as bubbles are strong ultrasonic reflectors. At a higher pump speed, more bubbles were generated as shown in In this study, the performance of a single-sided non-invasive ultrasonic flowmeter with an array transducer was evaluated. The experimental results of multiple angular compensation confirmed that our approach can be applied to increase the accuracy of the ultrasonic flowmeter using the linear array transducer. It can also help monitor liquid flow non-invasively with reliable measurement accuracy.


Coronavirus disease 2019 (COVID-2019) has been recognized as a global threat, and several studies are being conducted using various mathematical models to predict the probable evolution of this epidemic. These mathematical models based on various factors and analyses are subject to potential bias. Here, we propose a simple econometric model that could be useful to predict the spread of COVID-2019. We performed Auto Regressive Integrated Moving Average (ARIMA) model prediction on the Johns Hopkins epidemiological data to predict the epidemiological trend of the prevalence and incidence of COVID-2019. For further comparison or for future perspective, case definition and data collection have to be maintained in real time. The AugParameters of the ARIMA model were estimated by autocorrelation function (ACF) graph and partial autocorrelation (PACF) correlogram. To determine the prevalence of COVID-2019, ARIMA  was selected as the best ARIMA model, while ARIMA  was selected as the best ARIMA model for determining the incidence of COVID-2019. Gretl2019d statistical software  was usedLogarithmic transformation was performed to evaluate the influence of seasonality on the forecast. The correlogram reporting the ACF and PACF showed that both prevalence and incidence of COVID-2019 are not influenced by the seasonality. The forecast of prevalence and incidence data with relative 95% confidence intervals are reported in Although more data are needed to have a more detailed prevision, the spread of the virus seems to be slightly decreasing. Moreover, although the number of confirmed cases is still increasing, the incidence is slightly decreasing. If the virus does not develop new mutations, the number of cases should reach a plateau , Fig. 2.


In recent years, human–machine interactions encompass many avenues of life, ranging from personal communications to professional activities. This trend has allowed for person identification based on behavior rather than physical traits to emerge as a growing research domain, which spans areas such as online education, e-commerce, e-communication, and biometric security. The expression of opinions is an example of online behavior that is commonly shared through the liking of online images. Visual aesthetic is a behavioral biometric that involves using a person’s sense of fondness for images. The identification of individuals using their visual aesthetic values as discriminatory features is an emerging domain of research. This paper introduces a novel method for aesthetic feature dimensionality reduction using gene expression programming. The proposed system is capable of using a tree-based genetic approach for feature recombination. Reducing feature dimensionality improves classifier accuracy, reduces computation runtime, and minimizes required storage. The results obtained on a dataset of 200 Flickr users evaluating 40,000 images demonstrate a 95% accuracy of identity recognition based solely on users’ aesthetic preferences. Human–machine interactions rely on human behavior . BehavioAs a relatively new domain of research, visual aesthetic identification shows very high potential. Human–machine interaction often includes not only work-related tasks but also online social activities, interactions with family members, recreation and more. Among them, sharing photographs, discussing art, and expressing the liking of posted images are common expressions of human behavior. However, understanding these behaviors has been notoriously difficult due to the numerous visual features that are present in the images. During the creation of user authentication templates, it is important to use the most discriminatory features for classification. In pattern recognition, a feature is a characteristic that represents some data of an observation. Although what are considered good feature characteristics depends heavily on the problem domain, many common techniques aim to improve the efficacy of feature data such as normalization, selection, extraction, and expansion. Highly correlated or otherwise non-discriminatory features can decrease the accuracy and speed of the classifier, with intensity varying depending on the model. The most recent work  used 861In this paper, we apply Gene Expression Programming (GEP) to reduce feature dimensionality and increase classifier accuracy in a new identification model for visual aesthetic identification. Gene expression programming is a stochastic, meta-heuristic approach that utilizes structured gene trees to represent generated candidate solutions. The general structure of a GEP model follows other genetic approaches that use the fundamental principles of evolution: selection, mutation, and crossover . Through the use of program generations, unique candidates are generated based on random mutation and crossover with the previous generation to maintain a population of programs ,14. The A modified GEP-based approach to feature extraction is proposed in this paper to improve aesthetic-based person identification accuracy and reduce enrollment times. This approach transforms the original feature set into a smaller set of complex features through structured program evolution. We establish that these complex features can increase accuracy due to the reduction of noise introduced into the classifier system. A smaller feature vector with higher discriminatory ability also results in fewer computations during classification and a lower amount of memory required to store an authentication template. The proposed approach can be applied to other domains and lead to integration into more complex systems. In proposing such a model, the paper aims to improve the current state-of-the-art visual aesthetic identification and test the efficacy of a GEP approach given a large feature set in this domain. Results surpass the state-of-the-art methods for visual aesthetic identification.A novel visual aesthetic-based identification model is introduced that achieves higher accuracy over the most recently reported results.The investigation of utilizing gene expression programming to construct complex features is conducted for the first time in the aesthetic research domain.The proposed model reduces the dimensionality of the feature data required for identification, which achieves an improvement in both computation speed and system robustness of the visual aesthetic-based identification system.A comparison with the proposed model and previous works is performed on the benchmark dataset.Very preliminary research on this topic has been published as a conference paper . In the The research on visual aesthetics presented in this paper is introduced in the context of social biometrics ,6, an arA more sophisticated approach was developed by Segalin et al., which utilized a multi-resolution counting grid to categorize similar images . FeatureThe more recent work performed by Azam and Gavrilova presented a larger feature set of 861 that consisted of local perceptual features, global perceptual features, histogram of gradients (HOG) features, and content features . The metIn solving this identification problem, the classification techniques used in the previous works consisted of a mixture of traditional machine learning and feature engineering. As a general trend, more features are extracted to improve identification accuracy, with 861 features introduced in the most recent work  comparedThe recently introduced GEP methodology has proven highly beneficial in a variety of applications . Like otThe proposed system is a visual aesthetic-based identification system that utilizes GEP-based feature construction and an SVM to classify individuals. Given a collection of favorite images from a user, the model first extracts pertinent perceptual and content features. This high dimensionality feature vector is then inputted into the GEP constructed tree structure to reduce dimensionality, before being used to train the SVM in the enrollment phase. During identification, the features from the set of images from an unknown user will be extracted and transformed using the same GEP structure to a lower dimensionality. The trained SVM will then be consulted and the stored template of the closest user will be returned as the prediction. A figure illustrating the enrollment and identification phases of the system is shown in The illustration of a conceptual flowchart using the proposed aesthetic identification system is shown in The database of 200 users labeled to 200 of their favorite images is used , with a Perceptual features describe direct properties of the image such as mean hue, saturation, and value (HSV), colorfulness, and entropy of pixel intensities. The further distinction between global and local perceptual features is the applied space—global perceptual features are taken from the entire image, while local perceptual features are taken from each of nine evenly split partition cells of the image in a grid fashion. Content features describe the count and average area of detected faces and objects in the image . Lastly, the HOG features are generated using gradient values returned from point locations of the image based on the corresponding angle and magnitude maps. All feature values are normalized with zero mean/unit standard deviation and largely operate on the pixel properties (color space) of the image. The feature categorization is shown in After the concatenation of these features into a combined high dimensional feature vector, it is preprocessed before undergoing feature extraction. The GEP module takes as input the original feature set of size 924 and performs various logical and arithmetic recombinations to produce an evolving complex feature set. A large portion of the implementation is in the GEP module, with the classifier system serving as a wrapper function to direct the evolutionary fitness of each generated feature. Each candidate solution is evaluated using the classifier prediction accuracy with 5-fold random split cross-validation.After a pre-determined number of generations, the GEP module outputs a lower-dimensional feature vector of complex features which is subsequently used to generate visual aesthetic templates for every user in the training set. A similar process is followed for user identification, where the complex feature score for the user to be identified is calculated and compared to the stored templates in the template database. The user corresponding to the stored visual aesthetic template generated at enrollment which matches most with the provided template is chosen as the system prediction.As a genetic-based algorithm, the genetic operators of selection, mutation, and recombination are used to generate new complex features. These complex features take the form of tree-based structures, where leaf nodes are called terminals and branch nodes are called functions. Terminals are selected from the pool of features from the original feature set, while functions are selected from a pool of available mathematical and logical functions. A candidate solution is called a chromosome, which is composed of subtrees called genes. Collectively, a generation is composed only of a pre-determined number of chromosomes called the population, which shifts every iteration of the algorithm simulating evolution. A small process map of the GEP algorithm is shown in Each of these tree expressions is evaluated given the corresponding values in the original feature set to create a transformed feature vector. To store a multi-dimensional complex feature, an individual complex feature is defined as a gene subtree of the candidate chromosome. Each gene encodes one complex feature, with the combined feature vector represented as a multi-dimensional vector of its composite gene values over all observations. These candidate solution vectors are the structures that are ultimately optimized for accuracy using classifier accuracy as a fitness function.Most model parameters of GEP affect the genetic operation phases directly. The number of genes and the head length afforded to each chromosome is determined at the construction of the model, which is fixed throughout the program after definition. This determines the overall complexity and number of generated features. A gene number of 150 and a head length of 30 was used. The values of 150 complex features and 30 head length were determined empirically, showing the most sustained improvement and faster convergence to the solution. These values are subject to variation between problem domains as the number of original features, the complexity of the problem and the nature of the problem are vital considerations for determining the complex feature structure.The population of each generation is also an important consideration, where a small population can result in higher probabilities of model stagnation and a large population results in longer generation times on average. A balance between computational load and model efficacy was sought in this research. A population of 30 was used, which proved to be a large enough population to avoid most cases of homogeneity among the active population while taking time and computational restraints into consideration.The initialization of the starting population is randomly selected by drawing within the pool of available terminals and functions. Although there is a scaled fitness selection method, the initial population will always be independently random, due to the absence of fitness direction. The head and gene counts of the candidates are fixed, meaning that, even at initialization, all complex features generated will exhibit syntactic correctness . The pool of available terminals and functions used in the project are included in The fitness of every complex feature vector in the population is evaluated every generation. A wrapper-based approach to fitness is applied, where the complex feature vector is tested with the classifier for every candidate. The fitness value is produced through 5-fold cross-validation using random splitting. The stratified and randomized test/training set pairs avoid the selection of an overfitted set of complex features that can only successfully classify for very limited cases. Any candidates that are unviable due to mathematical/logical errors are automatically assigned a fitness value of 0 and effectively discarded due to the nature of evolutionary bias. The combination that generates the highest classification accuracy is then chosen to persist to the next generation as a simple form of elitism. The best candidate of the population will not be mutated or recombined (but can be recombined with) to preserve its discriminatory ability.The termination condition used in the model was 300 generations. The time required per generation increases significantly based on training and testing sample dimensionality; therefore, the number of generations in this implementation may be smaller than other GEP implementations. Maintaining 300 generations proved to capture a sufficient period for growth and usually led to indicators of convergence to a solution. For larger user datasets, the number of generations will likely need to increase, as it will take the system more evolutionary generations to converge on a larger solution space.Mutation in the GEP implementation operates by selecting a random index with probability based on the pre-determined mutation rate. This implementation uses a base adaptive mutation rate that decreases proportionally to classifier accuracy, with an increasing mutation rate of 0.05 per generation without improvement compared to the last best accuracy. When an improvement is experienced, the mutation rate will return to the base adaptive mutation rate.A base adaptive mutation rate allows for the system to adjust the minimum amount of mutations every generation. The intuition behind this is to restrict the explorable solution space as smaller changes to the existent solution are required. By allowing the mutation rate to increase above the base adaptive rate during periods of non-improvement, the model increases the explorable solution space to potentially escape local maxima. This will allow the model to restrict and release the solution space by manipulating the probability of random changes to every node of every solution tree, which produces a more robust searching model. This is especially significant when the population has reached an over homogeneous state or has difficulty converging onto a smaller solution space.A be the accuracy as a decimal value. Then, the computation is carried out as: Let The value of the denominator of 10 was used to restrict the mutation rate to values within a range of 0.0 to 0.1, or 0% to 10%. Regardless of the initialization of the population, the best solution at any given generation is typically higher than 50%, as even non-optimal complex features carry some discriminatory ability. The increment of 0.05 acts as an increased weight to the mutation rate, which was determined empirically to ensure the impact is significant yet controlled. This increment is then multiplied with the period of non-improvement, denoted by n-point crossover denotes Crossover is the random exchange of a set of genes between two candidate features. The number and location of these exchanges are random and can occur multiple times throughout a single gene crossover. This implementation uses a unique variable uniform, one-point, and two-point crossover rates based on current best classifier accuracy. A uniform gene crossover is a default rate at which every node of either candidate solution can be chosen, while an A be the accuracy as a decimal value. Then, the computation is carried out as:Let The denominator of 4 was used to ensure the crossover rate did not exceed 0.25 but maintained a high chance per node to be exchanged. In addition, the one-point and two-point crossover rates increase in proportion to the uniform crossover rate. This allows for an increased rate of diverse crossover, which contributes to a more varied resulting population.The selection phase collects the resultant, evolved population and iterates back to the evaluation phase. During this stage, the GEP model uses simple elitism by automatically carrying and saving the best candidate from the previous generation into the next. This maintains at least one complex feature combination with the best current accuracy, allowing the other candidate solutions in the next generation the opportunity to crossover. A bias is applied through a scaled roulette wheel that favors candidates with higher accuracy. These solutions will be allowed an increased chance of reproduction with other solutions.The evaluation of the fitness of each candidate solution vector is handled by a linear support vector machine (SVM) classifier. Each evaluation score is generated from the mean of 5-fold cross-validations on the train and test sets, with a random splitting of sample indices. When performing multi-class prediction, the classifier adopts the One-Versus-Rest (OVR) approach by constructing a binary classifier for each class, with samples from that corresponding class marked as positive, while all other classes are negative. The combination stage takes the classifier result with the highest confidence score. Preprocessing is vital due to the potential distribution of the complex features produced. The complex features are preprocessed through standardization and a power transform to resemble more Gaussian-distributed data. Hyperparameters for the classifier favored classifier accuracy and speed of classification, as the speed of the classifier is directly correlated to the efficacy of the gene expression model. A reduced classification time can allow for more extensive feature combinations, a higher candidate population, and additional generations. Classifier hyperparameters are evaluated before the GEP implementation.The classification system was implemented in Python 3.5, using the open-source PyGEP 3.5 port library for the base GEP framework. All experiments were run on a Windows distribution using an Intel Core i7-8700 @ 3.20 GHz CPU and an Nvidia GeForce GTX 1080 GPU. Six cores, 12 logical processors, and 16 GB RAM are available to the machine.The system is tested on a 40,000 Flickr benchmark dataset consisting of 200 users each with 200 labeled favorite images . An overTo evaluate the strength of the computed complex features, the GEP approach was used with a gene number or complex feature count of 150 on the same classification problem. A termination condition of 300 generations was used, as the improvement of the produced solution was found to become stable after this generation count.The experiments were designed to verify the system’s ability to perform highly accurate identification reliably and efficiently. The experiments begin with the testing of the optimal generation and gene count. This configuration is then used to compare the performance of different classifiers, where SVM produces the best result. Performance metrics for the system including the cumulative matching characteristic, receiver operating characteristic, and the false positive/negative graphs are shown. These results are compared to the current state-of-the-art methods, with the proposed system outperforming the most recent published model in  and its The choice of gene count was determined empirically, with the results of the experiments shown in A comparison of the different classifiers is shown in The Cumulative Matching Characteristic (CMC) curve is shown in Given the prediction probabilities for the test samples, a CMC curve is constructed by calculating the rank N recognition rate for each rank. As the system identifies individuals, there are 200 ranks. This is depicted in the following formula:The Receiver Operating Characteristic (ROC) curve in The equal error rate is the point at which the false positive rate and the false negative rate intercept. In the context of this multiclass problem, a micro-mean approach is taken, where the ROC and EER metrics were averaged for all binary class scenarios using the one-versus-rest strategy. The relationship between the ROC and EER metrics are depicted in the following formula:Three of the referenced models are compared to the proposed model, with data shown in n evaluations, along with evaluations required for refitting the classifier. Further tests with higher generation count, higher population size, or additional complex features can potentially increase accuracy rates further.As more improvements are made throughout the generations, the growth in classifier accuracy decreases as it becomes more difficult to generate further discriminating features without overlap. More generations are required to fine-tune smaller changes to the feature trees due to the random nature of the evolutionary operations. It is also important to consider 300 generations as a low count for typical genetic-based algorithms. The largest expense to the model is the evaluation of every individual complex feature vector, which takes on average under 10 s. Each generation requires at most In addition, the state-of-the-art approach presented in  has beenThe proposed model is shown in In addition, the proposed model is compared with the most recent state-of-the-art methods in Additional tests are shown in Summarizing the performed experiments, both the rationale and the performance of the system have been validated. First, it was discovered that a gene count of 150 performed the best among a set range of different gene counts. This gene count translates to 150 complex features, as each gene subtree encodes one complex feature. Using 150 complex features, the GEP model outperformed common dimensionality reduction techniques such as Independent Component Analysis, Factor Analysis, and Principal Component Analysis when applied to the same feature space. Different classifier configurations are tested with the model, with a Support Vector Machine-based classification outperforming K-Nearest Neighbor, Naive Bayes, and Stochastic Gradient Descent. The Cumulative Matching Characteristic curve establishes the system’s consistently accurate performance across ranks and a normalized Area-Under-the-Curve of 0.9987. A Receiver Operating Characteristic Area-Under-the-Curve of 0.9964 and an Equal Error Rate of 0.0303 proves the system’s robustness and low chance of misidentification. The proposed system achieves a rank 1 accuracy of 95.1% and a rank 5 accuracy of 98.9%. The time and memory required for this system are much lower than the reimplementation of the most recent state-of-the-art method. The results prove that the proposed model outperforms the state-of-the-art visual aesthetic identification methods in accuracy, speed, and storage required.This article presents the most comprehensive study to date on the use of aesthetic-based human traits expressed through human–machine interaction for biometric identification. It answers the research question of whether a new algorithm can be developed based on gene expression programming that can significantly outperform previous approaches for aesthetic-based human identification. The research demonstrated on a large dataset through extensive experimentation that GEP is an effective method for feature extraction in visual aesthetic identification and that the proposed model reduces the number of features required for identification while also increasing the overall recognition rate. The method reduced the dimensionality of the large original feature set while achieving rank 1 and rank 5 accuracies of 95.1% and 98.9%, respectively. The time and memory requirements have also been shown to be lower than in the previous methods.This study opens new avenues in harvesting rich information provided during human–machine interaction, where human aesthetics plays a vital role in selecting favorite images. A more thorough investigation into the model implementation may allow the opportunity for further optimizations in system performance through the use of extensive parallelism. In addition to system complexity, the selection, mutation, and crossover strategies can be further developed to increase the robustness and the accuracy of the converged solution. On a broader level, the exploration of alternative ways of human–machine interaction based on other aesthetics, such as music and touch, can be performed for the development of more comprehensive human–machine interfaces as well as more versatile security systems.


High-resolution synthetic aperture radar (SAR) images are mostly used in the current field of ship classification, but in practical applications, moderate-resolution SAR images that can offer wider swath are more suitable for maritime surveillance. The ship targets in moderate-resolution SAR images occupy only a few pixels, and some of them show the shape of bright spots, which brings great difficulty for ship classification. To fully explore the deep-level feature representations of moderate-resolution SAR images and avoid the “dimension disaster”, we innovatively proposed a feature fusion framework based on the classification ability of individual features and the efficiency of overall information representation, called maximum-information-minimum-redundancy (MIMR). First, we applied the Filter method and Kernel Principal Component Analysis (KPCA) method to form two feature subsets representing the best classification ability and the highest information representation efficiency in linear space and nonlinear space. Second, the MIMR feature fusion method is adopted to assign different weights to feature vectors with different physical properties and discriminability. Comprehensive experiments on the open dataset OpenSARShip show that compared with traditional and emerging deep learning methods, the proposed method can effectively fuse non-redundant complementary feature subsets to improve the performance of ship classification in moderate-resolution SAR images. Synthetic aperture radar (SAR) is widely used in maritime surveillance and ship monitoring due to its all-time and all-weather observing ability that covers wide areas . KnowledSince the swath of SAR images is inversely proportional to image resolution, high-resolution SAR images are usually obtained at the expense of narrow swath. A high-resolution SAR image at the resolution of about 1 m usually corresponds to a swath of 5 km. Such narrow swath may be suitable to inspect specific locations on Earth, but are unsuitable for maritime surveillance. The current satellite-borne SAR can provide swaths of 100–450 km at image resolution of 10–30 m [Unlike optical images, SAR images are essentially the spatial distribution of electromagnetic wave reflection intensity. The challenges and difficulties of ship target recognition in satellite-borne SAR images are summarized as follows : first, The typical SAR image ship target recognition is mainly divided into four stages: pre-processing, target detection, feature extraction, and target classification. Among them, feature extraction is a key factor that affects the ship classification in SAR images, and the selection of features directly determines the accuracy of classification. The widely used features in moderate-resolution SAR images are physical features, such as geometric structure features , gray-scThese algorithms are intuitive and efficient, and they do not change the essential attributes of features, but rely on the accuracy and stability of feature evaluation criteria. Therefore, more nonlinear dimensionality reduction methods have emerged, such as the kernel principal component analysis (KPCA) method . KPCA isWith the rapid development of artificial intelligence technology, numerous deep learning (DL) methods have been developed for SAR target recognition. The most commonly used is convolutional neural network (CNN), but it heavily relies on the quality and quantity of training data , which iBased on the above analysis, we consider the feature extraction problem from two perspectives, one is to extract the most separable features, and the other is to extract the most robust and effective features. Therefore, the Filter method is applied to evaluate features and the features with better classification capabilities are selected into the feature subset. And the KPCA method is applied to retain the principal components of the original features and maximize the information representation efficiency of the feature subset to the target. Then, the maximum-information-minimum-redundancy (MIMR) method is utilized to perform reliable feature fusion to maximize information representation and minimize feature redundancy, and different classifiers are selected for ship classification. In The overview of the basic framework is shown in Geometric structure features : area x1Brightness features : qualityTexture features : energy Moment invariant features : 7 Hu moGenerally, the original feature value has a large range. For example, In the Filter method, evaluation criteria based on distance measurement, information measurement, and dependency measurement are applied to feature evaluation. In this article, we evaluate original features by three evaluation criteria and the comprehensive ranking method is utilized to select several better features as a candidate feature subset.SeparabilityThe separability metric uses the distance between samples to measure the separability of features for different types of samples. The most commonly used distance measures are intra-class distance and inter-class distance. The definition of these two distance measures is expressed as (1)SWi=∑fined as :(3)Ji=SBWe hope that features can effectively distinguish different target categories, that is, the smaller the intra-class distance is, the better, and the larger the inter-class distance is, the better. Therefore, the larger StabilityA subset of features for which a classifier obtains the best results may not necessarily be applicable to other classifiers. Therefore, the stability of the feature itself is also a factor that must be paid attention to in feature selection. The normalized coefficient of variance is used to measure the stability of the target feature, which is defined as:ature is .Pearson correlation coefficientIn statistics, the Pearson correlation coefficient is often used to measure the degree of linear correlation of variables, which is defined as the ratio of covariance to standard deviation. The greater the absolute value of the correlation coefficient, the stronger the correlation, that is, the closer the correlation coefficient is to 1 or −1, the stronger the correlation; the closer the correlation coefficient is to 0, the weaker the correlation, which is defined as:Obviously, the lower the After feature extraction, we first analyze the separability, stability and Pearson correlation coefficient of features. Then we comprehensively evaluate the features according to their separability and stability, and subtract the features when the separability is lower than a certain threshold and the stability is higher than a certain threshold. Next we analyze the correlation coefficients of the remaining features, and select the features with lower correlation with other features into the feature subset. Finally, a feature vector is constructed for each ship chip: An initial motivation of KPCA is to perform PCA in the high-dimensional feature space. As we know, PCA minimizes the distance between the data and the linear principal component; while KPCA first selects a suitable nonlinear mapping, and then maps the original data into a high-dimensional nonlinear feature space omponent . KPCA coGiven the sample set Kernel techniques are introduced to avoid huge calculations. The covariance matrix on the feature space The corresponding eigenvalue equation is:The principal components are decided by the eigenvalue Therefore, Equation (9) can be transformed to:The kernel function provides a connection from linear to nonlinear and any algorithm that can represent the dot product between two vectors. The specific representation of mapping In addition to using a certain feature alone, the rational use of different types of features combined with each other can achieve complementary effects. The most important problem to be solved is how to effectively combine different types of features, which is called feature-level fusion . FeatureThe idea of the MIMR method is to consider the information representation efficiency of the target feature subsets with different physical attributes while minimizing the redundancy between feature vectors Given the feature set Furthermore, it has been recognized that the combinations of individually good features do not necessarily lead to good classification performance. In other words, there may be redundancy between “good” features. Here we utilize mutual information (MI) to represent redundancy, and minimum redundancy represents the smallest correlation between features, that is, the smallest MI between features. Given two random variables Therefore, the optimization model can be established asfunction . The ideTo further improve efficiency, we first adopted the Fisher Score method  to make fined as :(14)FSi=In terms of classifier selection, we consider several mature classifiers including: k-Nearest Neighbor (KNN) classifier based on Euclidean distance, support vector machine (SVM) classifier based on kernel function, and neural network classifier based on artificial intelligence ,32,33. KConsidering that the number of samples between the categories of experimental data in this article is extremely unbalanced, it is difficult for neural network classifiers to train a good network model, so here we choose KNN classifier and SVM classifier to ensure the classification accuracy and the speed of the algorithm, and we use LibSVM  implemenThe detailed process to obtain the weight coefficients Algorithm 1 The process of the MIMR algorithmStep 2. Utilize the Fisher Score method to evaluate the Step 3. For the remaining Step 4. Calculate the mutual information between the Step 5. Utilize iterative optimization method to find the local minimum that satisfies the constraints. Compare the objective function Step 6. When objective function Step 1. After normalizing the feature vectors In this article, the experimental dataset selected is the OpenSARShip  dataset,After feature extraction and analysis, the separability, stability, and Pearson correlation coefficient analysis result are shown in From the result, it can be seen intuitively that different features have different properties and distinguishability. For example, the width In each experiment, we randomly selected 200 container ships, 200 bulk carriers, and 100 tankers as the training set, and the rest as the test set. In order to eliminate the bias caused by random sampling to a single experimental data, the above experiments were carried out 50 times. The performance of the classifier is finally reported as the average classification accuracy. KNN classifier and SVM classifier are selected to perform classification tasks to comprehensively evaluate the method. The recognition result is shown in Where Feature-fusion is the feature vector We also found that the same feature vector performs differently on different classifiers. The feature vector In addition, we compared the performance of the proposed method with other methods for ship classification in moderate-resolution SAR images, including naive geometric features (NGFs) , GeometrThis article aims to provide a reliable and operable method for ship classification in moderate-resolution SAR images. We extract the motivation of the target classification problem from multi-dimensional feature selection and fusion and correct classification rate. A novel multi-feature fusion framework based on the MIMR method is proposed, which not only considers the classification ability of a single feature, but also considers the information representation efficiency of the overall feature subset to the target, while ensuring that the redundancy is minimized. The results of the comparative experiments show that the proposed method effectively reduces the redundancy between features, and has a fairly good performance for ship targets classification in moderate-resolution SAR images.The preliminary analysis we presented here can be extended in many ways. We intend to conduct extensive experiments in combination with feature fusion under different polarization channels. In addition, we will continue to study other more advanced classifiers.