A large number of low-income residents in industrial neighborhoods rarely engage in recreational and physical activities in green spaces in extremely cold weather. This study mainly explores the relationship between the street environment and physical activities under special industrial properties and extreme cold weather conditions. In addition, we further divide essential physical activity into two categories, life-type and traffic-type physical activity, to explore and refine the related studies.We use principal component analysis to classify the street environment indicators and use multiple linear regression to analyze the impact of each indicator on different physical activities. The conclusions are as follows. For low-income people, the street environment in industrial neighborhoods has a much greater impact on life-type physical activity than traffic-type physical activity, and there is a conflict between the two. In addition, a high greening density is not conducive to either type of physical activity in the street environment. It reduces the paved area of streets and create sports conflicts between people undertaking different physical activities. The findings contribute to the development and optimization of public health research on environmental interventions in industrial neighborhood streets and enable effective recommendations for increasing outside physical activity among low-income people in severe weather conditions. In future studies, we will use the physical environment as a mediator to explore the relationship between the street environment and high-frequency chronic diseases in old industrial neighborhoods.The online version contains supplementary material available at 10.1186/s12889-022-14533-7. The rise of China’s industrial cities mainly occurred in the 1950s, but with the rapid development of information technology in the twenty-first century, the industrial society gradually transitioned to an information society. The industrial city economy entered declined, and the industrial attributes were subsequently diluted. However, there are still many low-income groups, such as factory employees, their families and elderly retired workers, living in industrial neighborhoods, and they maintain their original behavioral habits and life patterns. Old industrial neighborhood green spaces often have difficulty meeting the physical and psychological needs of residents due to problems such as uneven spatial distributions and the poor quality of landscape vignettes.Studies have found that increased access to green space is beneficial to residents’ physical and mental health . HoweverNotably, the built environment is defined as ‘the physical form of communities’, which can include land-use patterns, large- and small-scale built and natural features, and the transport system .CurrentlRecent relevant studies have also targeted specific types of people. A study from Iran explored the relationship between street network configuration in 18 primary schools and walking students. It found that the local morphological variables, integration and comprehensibility around the students’ homes had a direct and substantial relationship with the students’ walking, but the control and local selection indicators were negatively correlated. How children get to school has been found to be closely related to their physical and mental health .Ulrike eScholars from different countries have also verified that the equity of green space use varies across income groups, with lower income residential areas within towns and cities likely to have the least access to green infrastructure such as green space or street trees –26. LoweTherefore, this paper investigates the health status and essential physical activity of low-income people in the street space of an industrial neighborhood in Harbin, an industrial city in China, during the cold season. On the one hand, it is obvious that the urban population density of China is much higher than that of most western countries, so there may be greater contradiction in the allocation of urban green resources. On the other hand, industrial cities often have a range of residential and service areas attached to factories, with a high degree of mixed land use and infrastructure centered on the factories. As a result, residents of industrial cities tend to meet their basic needs on foot and have a higher level of essential physical activity behavior than in other areas, which makes such cities likely to have higher street utilization. Most importantly, there are a large number of low-income groups in industrial communities, and their physical and mental health problems are often more serious than those in emerging urban communities. This research will help fill the gaps in the literature on the existing problems of industrial districts and promote the physical and mental health of low-income groups.The study was conducted in Harbin , a typical industrial city in China. At the end of the nineteenth century, the construction of the Middle East Railway enabled Harbin to develop rapidly from a small frontier fishing village into one of the major transportation hubs in Northeast Asia. The industrial structure of the city was gradually transformed from agriculture, animal husbandry and handicrafts to industry, and a large number of factories began to emerge in the center of the city. To meet the basic needs of factory workers, the old Harbin (now Xiangfang District) first started urban construction around the factories, and numerous industrial neighborhoods with factory unit compounds as the core were formed. However, with the shift in China’s economic development to coastal cities and the impact of new industries, Harbin’s industrial economy grew more slowly, and its industrial attributes declined, with many idle factories appearing in the city center becoming idle.The streets in the industrial area considered in this study are old and mainly used for industrial transportation, and the roads are primarily connected by high-grade expressways connected to low-grade feeder roads. In addition, the neighborhood has a high percentage of low-income people Table , who havLife-type physical activity, such as grocery shopping and dog walking, meets the needs of life, and there is a high level of neighborhood cohesion due to the presence of industrial plants. The neighborhood has a high degree of mixed land use and a wide variety of business types. The spatial structure of small neighborhoods and dense road networks also provides more options for daily travel for physically active crowds. Traffic-type physical activity, such as waiting for cars and other transportation commuting needs, meets the needs of daily work and study. The decay of the industrial plants has made it necessary for some residents to commute by public transportation, but some still walk to their jobs at the plants. According to the World Health Organization’s classification of physical activity intensity, both types of essential physical activity have MET values of less than 6, which is low to moderate intensity physical activity . Eventually, the total amount of physical activity in both categories was determined for different street segments and times.(2)Self-reported mental healthThe total physical activity was measured from October to December 2021 at extremely cold temperatures (− 20 °C to –30 °C) with no snow and no clouds. The extreme season was chosen to maximize the exclusion of physical activity travel for leisure purposes. The data for each sample street included 5 weekdays and 2 weekend days for a total of 7 days, and the different types of physical activity were recorded in units of 0.5 h for each street for a total of 12 time points in the morning (7:30–9:00), midday (11:30–13:00) and evening (16:30–18:00). The researchers used cameras to spot video the crowds passing within the sample streets and automatically extracted the number of physically active people and artificially classified them through Baidu’s foot traffic statistics platform , accessibility of living  and commercial richness ; 70.594% of the total variance can be cumulatively explained. The three principal components affecting traffic-type physical activities were vehicle accessibility , pedestrian accessibility  and destinations available ; 68.232% of the total variance can be explained accumulatively, as shown in Table Within the study of essential physical activities, both types of activities are frequently influenced by accessibility. The accessibility of traffic-type physical activities can be categorized into vehicle accessibility, pedestrian accessibility and destinations available, as shown in Table Figure In this paper, street environment indicators were used as independent variables, the number of people undertaking two types of essential physical activity during the research period was used as a dependent variable, and two multiple linear regression models were constructed using SPSS software. The coefficients of the influencing factors were ranked, and the top 5 street environment indicators in terms of degree of influence were extracted. The VIFs of the 2 models were < 10, and there was no significant covariance problem. The top 5 street environment indicators were ranked in descending order of importance: diversity of commercial businesses along the street, green space accessibility, number of bus stations, greening density and density of traffic-type stores along the street. Table The street environment indicators affecting traffic-type physical activity differed from those affecting life-type physical activity. Plant accessibility had the highest degree of influence, and neighborhood accessibility had the lowest degree of influence. The remaining three indicators were ranked in order of importance: the density of life-type stores along the street, greening density and number of road intersections. Among them, the number of road intersections and neighborhood accessibility were positively correlated. Table The demographic and sociological statistics of this study showed that Sig. > 0.05, indicating that the gender and age of the residents of industrial neighborhoods do not have a significant effect on the duration of their physical activity. This is consistent with the results of Vich et al.  In additBased on the data analysis, the physiological health status of the residents was significantly influenced by their monthly income, where the mean of 3.08 indicated that the residents with a monthly income of ¥8000 or more reported the worst physical health status. As indicated by the mean of 2.52, the residents with a monthly income below ¥2000 exhibited the second worst physical health status. This is different from the results of previous studies due to the specific characteristics of populations in industrial neighborhoods. Most residents in industrial neighborhoods are engaged in manual labor, primarily industrial labor, and higher pay means longer and more intense physical labor, thus increasing the chance of physical pain due to overwork. On the other hand, low-income residents may ignore the dangers of physical illnesses because of their economic constraints. This paper also shows that the mental health status of residents is affected by their marital status. Unmarried, divorced, and widowed residents show worse mental health than married residents, indicating that the married group can better communicate with those around them when psychological problems arise to alleviate mental health problems more efficiently.The findings suggest that the effect of the street environment on physical activity in industrial neighborhoods varies with the type of physical activity. We followed the recommendations of previous related studies and classified the physical activities of the residents within the study area according to the purpose of use. This differs from previous studies, which often classified activities according to their intensity . We founIn addition, there is some conflict between the effects of the street environment on the two types of essential physical activity in the study area. In other words, characteristics of the street environment that are conducive to life-type physical activity may inhibit traffic-type physical activity. Therefore, the layout of the street environment in industrial areas should be effectively classified according to the physical activity needs of users, and the two types of physical activity paths should avoid overlapping. The hard and blind placement of street space elements does not necessarily play a positive role in promoting the behavioral needs of a neighborhood. Therefore, in the process of reconstructing old industrial streets, properly screening the ineffective space elements may create more efficient behavior paths for the two types of sports activity groups. This spatial environment will encourage the occurrence of physical activity behaviors in industrial neighborhoods, consciously distinguishe between the two types of behavioral path, guide the population to conduct physical activities in an orderly manner, and promote users’ physiological and psychological health levels in the process of engaging in physical activities.The analysis in this paper finds that life-type physical activity in industrial neighborhoods is frequently influenced by commercial richness. A diversity of commercial businesses along the street is more likely to help people undertake life-type physical activity to meet multiple needs in their daily lives because low-income groups are more likely to choose to buy goods from affordable stores along the street than from commercially integrated groups. In terms of greening density, this paper also verifies the specificity of the low-income group. Contrary to the findings of previous studies, the density of trees exposed to the street and the daily walking time of individuals were positively correlated . High grIn summary, indicators such as enhanced greening density, greening ratio and greening coverage area do not meet the actual needs of users. Future design and renovation are needed based on the practicality of use. In addition, an increase in the density of traffic-type stores along the street and high green space accessibility also inhibit the life-type physical activities available to residents to some extent. The demand for traffic-type stores in older neighborhoods with declining industrial attributes is greatly reduced. Too many traffic-type stores along the streets reduces the number of life-type stores, which are in greater demand, and the number of people will be reduced as a result. Our recommendation is to consolidate the production-type stores along the street, so as to increase the number of life-type stores along the street, which are in greater demand. This effectively increases the chances that residents will leave their homes and maintain a high state of physical function. Streets with high green space accessibility tend to be perceived as having more people using them, but such green spaces are obviously more attractive than streets with less privacy and limited functions. Thus, streets with high green space accessibility tend to have a traffic-only function. This discovery will help the public to break the old impression and provide them with real street use in old industrial districts. During the study, the conclusion is that an increase in the number of bus stops will generate large numbers of people and lead to traffic flow confusion. It is recommended that separate public transport waiting areas be designated to ensure effective traffic flow. A reasonable street space layout can improve the efficiency of access for people engaged in essential physical activities, reduce the probability that the street space will be used less due to poor traffic, and enhance public walking opportunities.In the study of residents undertaking traffic-type physical activity, greening density showed the same results as for life-type physical activity. A high greening density is not conducive to various types of physical activities on streets. This differs from previous findings that high greenery promotes the occurrence of physical activity , 16. ThiAn increase in the density of life-type stores along the street and high plant accessibility will inhibit traffic-type physical activities because an increase in the density of life-type stores along the street increases the amount of life-type physical activity. The conflicting nature of the two types of activity was mentioned in the previous section, and an increase in such conflict would have a negative impact on traffic-type physical activity. Therefore, in the process of street renewal, a reduction in the number of life-type stores along such streets should be considered Fig. . In the This study focuses on the effects of the street environment on essential physical activity  in the industrial neighborhoods of Harbin, an old industrial city in China. It was found that the high- and low-income groups showed worse physical health and that the married group had better mental health than the single group . This indicates that high- and low-income groups in industrial neighborhoods with lower overall income levels experience more life stress. Life-type physically active groups tend to be more active in peri-urban areas because the centers tend to have higher levels of consumption, while neighborhood residents prefer markets and fairs in nonurban centers. Traffic-type physical activity is strongly and positively correlated with the width of a carriageway, as wider carriageways facilitate the movement of vehicles. This helps meet the transportation needs of residents.However, our study is limited in several ways. First, the streetscape data collection took place during the severe cold season, and the choice of season limited the availability of data on street vegetation after leaf fall , which may have produced discrepancies with the results of the summer study. Second, the linear nature of the street itself may lead to bias when researchers obtain users’ physical activity data. Third, some of the reports in the study were based on subjects’ self-reported responses, and self-reported measures are subject to subjective choices that may be unreliable due to self-report bias. Finally, the relatively small sample size cannot fully reflect the street space use needs of the entire population in the industrial district. Nevertheless, self-reported data can still provide a wider range of responses and be beneficial in obtaining the views, perspectives and opinions of participants.Therefore, according to the problems identified in the above article, we should consider the impact of seasons on data collection and increase the number of sample studies in future research to reduce the deviation of data caused by small sample size. In the selection of the study space, future studies should also consider broadening the type of green space studied; they should also consider including public green space and urban parks in comprehensive research experiments. At the same time, more efficient and objective measurement tools  should be explored for the acquisition of data on subjects’ conditions. In the future, we will try to explore the preference for green space in people suffering from high-frequency chronic diseases in China such as hypertension and diabetes. We hope to obtain green space configuration methods that can effectively alleviate residents’ chronic diseases and improve the physical and mental health of typical low-income residents in old industrial neighborhoods.Additional file 1. Street environment index data.Additional file 2. Measurement of physical activity indicators of users.Additional file 3. Supplementary data for data analysis.


This study examines the feasibility of using a robot-assisted therapy methodology based on the Bobath concept to perform exercises applied in conventional therapy for gait rehabilitation in stroke patients. The aim of the therapy is to improve postural control and movement through exercises based on repetitive active-assisted joint mobilization, which is expected to produce strength changes in the lower limbs. As therapy progresses, robotic assistance is gradually reduced and the patient's burden increases with the goal of achieving a certain degree of independence. The relationship between force and range of motion led to the analysis of both parameters of interest. The study included 23 volunteers who performed 24 sessions, 2 sessions per week for 12 weeks, each lasting about 1 h. The results showed a significant increase in hip abduction and knee flexion strength on both sides, although there was a general trend of increased strength in all joints. However, the range of motion at the hip and ankle joints was reduced. The usefulness of this platform for transferring exercises from conventional to robot-assisted therapies was demonstrated, as well as the benefits that can be obtained in muscle strength training. However, it is suggested to complement the applied therapy with exercises for the maintenance and improvement of the range of motion. Stroke is a leading cause of death and disability worldwide, with an incidence of nearly 14 million new cases each year , a resource provided by the U.S. National Library of Medicine. The protocol (Code: CRCS_UID_210619) was approved by the Institutional Review Board of the Rehabilitation Center Club de Leones Cruz del Sur.A total of 23 patients  with a mean age of 53.9 ± 9.7 years, mean weight of 77.7 ± 14.2 kg, and mean height of 163.8 ± 7.7 cm participated in this clinical study. All the participants were recruited from the Outpatient Rehabilitation Program of the Rehabilitation Center Club de Leones Cruz del Sur.All the patients included in the present study had unilateral lower extremity paresis resulting from a stroke occurring at least 6 months prior to the study. Furthermore, patients had full passive range of motion in the lower extremities or at least reached a neutral joint position; they were also able to stand freely and walk with or without assistance for at least 20 m in <2 min. Exclusion criteria were peripheral nervous system pathology, epilepsy, weight over 100 kg, difficulty following the study instructions, pregnancy, use of implanted devices, and unstable lower extremity joints or fixed contracture. The co-researchers obtained written informed consent from all participants. All enrolled participants were informed of their responsibility to attend all scheduled sessions.A rehabilitation platform was developed consisting of a powered lower limb exoskeleton , a control software and a weight-bearing system  was designed to control the position of each joint of the exoskeleton independently, adjust the assistance and record data from each rehabilitation session. The control diagram can be found in the supplementary material provided . This soThe assistance level can be set in percentage values between 50 and 100% , the latIn short, the new platform allows to control the movement of each joint, facilitating normal movement and avoiding the use of compensatory movement strategies that patients use due to muscle weakness. Additionally, the software allows the modification of variables such as speed, repetitions and rest time between each exercise, facilitating the application of adjustments in each session to personalize the therapy according to the patient's progress.Participants were assessed at baseline and after the robotic therapy through standardized clinical tests to measure the strength and PROM of each joint. Lower limbs PROM assessment was performed using a six-piece goniometer set . Strength assessment was carried out using a digital handheld dynamometer  in which maximum and average muscle strength of hip flexion, hip extension, hip abduction, knee extension, knee flexion, dorsiflexion and plantar flexion of the ankle were assessed. The assessment was performed using the evaluation protocols available in the literature to reach positions with higher reliability to test isometric strength  and then gradually decreased their assistance by 5% every 4 sessions based on clinical judgment. Each session was subdivided into preparatory activities, robotic therapy and post-therapy activities. Preparatory activities included securing the patient by installing a harness connected to a non-movable weight-bearing system whose sole purpose is to secure the patient and prevent falls, but without supporting a fixed percentage of weight; installing and adjusting the exoskeleton; connecting the software; selecting the exercise to be performed, and setting the percentage of assistance per joint. In addition, vital parameters as blood pressure and heart rate were measured before and after each session with the SureSingVS2+ multiparametric device  to ensure that the patient performed the training in perfect condition and that no adverse effects occurred after the session.The therapy design included 5 gait training exercises  based onOnce the training session was over, the system was switched off and the equipment was uninstalled. A skin inspection was carried out in the areas where pressure was applied with the exoskeleton and the patient was consulted about his or her comfort and experience during the session. In addition, at the end of each session the therapist monitored established criteria for discontinuing the study: (1) Participant requests to leave the study; (2) Follow-up assessment reveals evidence of unexpected contraindication to the intervention, such as skin problems or pain. In addition, participants' adherence to the program was monitored and encouraged throughout the trial. In addition, all patients were informed about permitted and prohibited concomitant interventions during the trial.After 12 weeks of training, assessment tests were repeated for comparison with the baseline condition. In addition, post-trial care of the study included: (1) All patients enrolled in the study were scheduled for clinical follow-up; (2) Implementation of a telephone line for patients in case of post-trial complications.Only institution employees, co-researchers, and ethics committees get access to the participants' records. Participants' identities are concealed in any research related publications.−1. The results presented in relation to the PROM are in degrees. Descriptive statistics, such as mean (M) and standard deviation (SD), were calculated. An analysis of the classical assumptions was performed, i.e., normality tests (Shapiro Wilks test). The results obtained from these tests conditioned the use of a parametric (Student's t-test) or non-parametric (Wilcoxon test) test for related samples at 5% confidence. In addition, a statistical power study was performed with GPower v3.1 software to confirm the reliability of the results obtained with the proposed statistical analysis. For this purpose, it was established that the statistical power should be equal to or >80%. Due to the multiple comparisons made to identify significant differences in the variables measured for strength and PROM, the familywise error rate increases. That is, the probability of making a type I error increases. To control this effect, a Holm-Bonferroni adjustment was applied to the strength and PROM family variables separately. This allowed us to identify the significant differences for each of the groups of variables studied.The data collected with the pre- and post-therapy assessments were analyzed with SPSS Statistics 26 software. The results obtained in the dynamometry tests were normalized by the weight of each subject in order to carry out the statistical study, so the units of the strength results presented in this study are kgf·kgFinally, to assess the possible relationships between the significant changes detected, the percentage of change that occurred between the pre- and post-variables was calculated. For this purpose, the following equation was applied:Subsequently, the relationships between these newly calculated variables were evaluated for two different scenarios. Variations of the variables on the paretic side and on the non-paretic side were analyzed separately. In a first scenario, the relationship was studied for the variations of the maximum strength measures. They were only examined for maximum strength, as maximum strength and average strength were considered to be linearly dependent. Furthermore, clinically, maximum strength is more relevant than average strength. This helps to simplify and interpret the results in the sense that the aim is to explore whether the strength variations experienced after therapy are in the same direction and with the same intensity. In a second scenario, the same analysis was performed with respect to PROM variations. Finally, the relationships between the variations of the variables that underwent significant changes on both sides were analyzed in order to study whether these changes were similar.For the statistical analysis of the last two hypotheses involving multiple comparisons, partial approximations have been made. A principal component analysis (PCA) was applied in order to reduce dimensionality and describe the dataset in terms of new uncorrelated variables that help to understand the main relationships between the study variables. Loadings allow us to interpret the distribution of our variables with respect to these principal components. A loading is large when its absolute value is >0.5. The sign will indicate whether the correlation between the variable and the component is positive or negative, resulting in a direct or inversely proportional relationship, respectively. As for the relationships of maximum strength and the relationships of the same variable comparing different sides, the comparisons were bivariate. Therefore, Pearson's or Spearman's correlation was applied depending on whether or not the normality criterion previously analyzed was met for the variables used to calculate the variation.p < 0.05) which seem to indicate that this training therapy promotes strength gain mainly at the hip and knee joint level . MCID is defined as “the smallest difference in score in the domain of interest which patients perceive as beneficial and which would mandate, in the absence of troublesome side effects and excessive cost, a change in the patient's management”  and by the Rehabilitation Center “Club de Leones Cruz del Sur”, Punta Arenas, Chile. This work has been also partially funded by CSIC Interdisciplinary Thematic Platform (PTI+) NEURO-AGING+ (PTI-NEURO-AGING+).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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


A dermal interstitial lymphocytic infiltrate may represent a diagnostic challenge, particularly if the clinical history is not provided. We present three cases within the histological spectrum of morphea in which the immunohistochemical marker CD34 was helpful in confirming the diagnosis.  Morphea is an autoimmune disorder that causes fibrosis of the skin and is most frequently seen in young girls. The pathogenesis is not fully elucidated; however, it appears that the fibroblasts are activated by various environmental stimuli in the presence of genetic predisposition . The most common histological features are collagen homogenization, sclerosis and thickening of the dermis, and loss of peri-adnexal fat or reduced appendages of the skin . Other pHowever, the diagnosis of morphea histologically can be challenging, particularly in the early inflammatory stage when it might lack the characteristic stromal changes and manifest with a non-specific perivascular and interstitial lymphocytic cell infiltrate. Accordingly, about half of the biopsies may be non-diagnostic ,3. In adA negative CD34 staining in the reticular dermis has been previously demonstrated in biopsies from morphea lesions . We presA nine-year-old girl presented with a ten-month history of a linear erythematous rash with mild pruritus on both her forearms A. The chA punch biopsy from a 57-year-old female was received for evaluation. The biopsy was sent from general practice with the minimal clinical detail of a rash on the left hip. Microscopic evaluation revealed hyperkeratosis with follicular plugging and acanthosis of the epidermis. There was homogenization of the collagen in the superficial dermis, while the mid-to-deep dermis showed a mild interstitial lymphoid cell infiltrate with some thickening of the collagen bundles A–C. LossA 58-year-old female presented with a one-year history of a patch of hyperpigmentation on the left upper inner arm A. The paCD34+ Dermal dendritic cells (DDCs) are normally distributed in the reticular dermis and around the adnexa. They are postulated to have functions in wound healing and the maintenance of dermal architecture [Multiple studies have noted that there is a reduction of dermal dendritic cells in morphea. Skobieranda et al.  demonstrA similar study, conducted on a larger population (50 patients and 50 controls), was concluded with similar results. In addition, they found elevated SMA expression, which they explained as a phenotypic shift from CD34 DDCs to myofibroblasts [Reduction or loss of CD34 expression has also been described in similar sclerosing disorders such as lichen sclerosus, systemic sclerosis, lipodermatosclerosis, and sclerodermoid graft-versus-host disease, as well as scars ,6,7,8. AThe differential diagnosis of lymphocyte-predominant interstitial inflammatory cell infiltrate is broad and varies from Schamberg’s disease to interstitial mycosis fungoides (IMF) . Indeed,In this setting, loss of CD34 expression and plasma cells in the infiltrate point towards the diagnosis of morphea .In Schamberg’s disease, extravasation of erythrocytes and hemosiderin deposition are helpful findings . Early eIt is important to emphasize that the loss of CD34 staining in the dermis is not entirely diagnostic and should not be used in differentiating morphea from scars and other cutaneous diseases in which sclerosis is the main pathology.However, in the appropriate clinical setting, we underscore that this can be a very valuable clue for differentiating morphea from other lymphocytic-predominant interstitial infiltrates, especially in early and subtle clinical cases such as our first case or in cases with minimal clinical information as in our second case. In the former, the absence of CD34 positivity was mainly in the lower reticular dermis, while in the second and third cases, the reticular dermis was diffusely negative for CD34. This may be explained by the previous observation that the degree of CD34 expression is inversely correlated to the degree of dermal sclerosis in morphea [Future studies are necessary to determine the sensitivity of CD34 loss in morphea cases and whether there is a pattern that can be correlated with the stage of the disease.


Temporal variations in the configuration of the flowing portion of stream networks are observed in the large majority of rivers worldwide. However, the ecological implications of river network expansions/retractions remain poorly understood, owing to the lack of computationally efficient modelling tools conceived for the long-term simulation of river network dynamics. Here, we couple a stochastic approach for the simulation of channel network expansion and retraction (described in a companion paper) with a dynamic version of a stochastic occupancy metapopulation model. The coupled eco-hydrological model is used to analyse the impact of pulsing river networks on species persistence under different hydroclimatic scenarios. Our results unveil the existence of a climate-dependent detrimental effect of network dynamics on species spread and persistence. This effect is enhanced by dry climates, where flashy expansions and retractions of the flowing channels induce metapopulation extinction. Survival probabilities are particularly reduced in settings where the spatial heterogeneity of network connectivity is pronounced. The analysis indicates that accounting for the temporal variability of the flowing river network and its connectivity is a fundamental prerequisite for analysing in-stream metapopulation dynamics. In frWhile the spatial dimension of stream networks has been extensively analysed, their temporal dynamics, implied by the ever-changing wetness condition in the surrounding landscape, has received less attention by the ecological community. Fluctuations in streamflows along the network are the primary form of environmental variability in riverine ecosystems , owing tWhile the ecological implications of spatio-temporal variability in habitat suitability and connectivity have been already analysed in the eco-hydrological literature ,27–36, tTo answer this question, we leverage the hydrological model proposed in a companion paper , and we . 2In what follows, we describe the proposed dynamic metapopulation model, and we summarize the key features of the underlying dynamic stream network model. For more details about the physical and theoretical hydrological set-up, the reader is referred to our companion paper .. 2.1Xi(t) that could be either 0 (dry) or 1 (active). Each node (i) is representative of the hydrological conditions in a uniform stream reach of length Δli containing the node i. Temporal changes in the spatial configuration of the active network are simulated by assigning the status of each node in the network during a sequence of time steps. The time variability of the status of each node can be summarized by its local persistency, Pi, which represents the marginal probability of node i being active.In our mathematical framework, a dynamic stream network is represented by a set of nodes with arbitrary spatial coordinates and a binary state L(t) and streamflow at the outlet Q(t)  decreases  m−2 d−1 and e ∈  m2 d−1. In what follows, we first report the full results of the sensitivity analysis on species survival for a set of virtual species spanning the entire range of the colonization and extinction rates. We ran the static and dynamic metapopulation model for each combination of the parameters, performing a set of 50 Monte Carlo simulations each and computing the number of times the species survived until the end of the simulation (365 days). Then, we show the results for a representative virtual species characterized by c = 0.015 m−2 d−1, e = 20 m2 d−1 and δ = 4 NND. While the former analysis allowed us to explore which type of species may or may not survive under different hydroclimatic conditions, the latter enabled us to improve our understanding of the different temporal dynamics in species occupancy variability between the static and dynamic metapopulation model. As such, the combination of c, e and δ values of the focus species was specifically selected to highlight the different behaviour of the metapopulation model under different hydroclimatic conditions.Our analyses comprise nine different scenarios, which arise from the combination of three possible climates  and species attributes . While our companion paper  investige/c can be identified in the pseudocolour maps. For high values of e/c (top-left corner), the survival probability tended to zero, preventing metapopulation survival. Indeed, in this case the extinction process dominated and impeded species colonization even if the habitat might still have been suitable. On the other end, for low values of the e/c ratio (bottom-right corner) the probability of survival tended to one, mirroring a scenario where the given species were able to colonize the entire habitat, and thus survive. Finally, for intermediate e/c ratios (top-right and bottom-left corner) the individual values of e and c did play a role in defining the survival or extinction of the species. As the hydroclimatic conditions changed from wet to intermediate the different zonation tended to fade, with an overall decrease in the probability of survival which eventually collapsed to zero under dry hydroclimatic regimes, where the habitat suitability was too limited to promote successful colonization.Overall, the pseudocolour maps reported in figures e and c, the probability of metapopulation survival under dynamic conditions was always lower than that observed under steady conditions. Indeed, the dynamic version of the metapopulation model predicted a lower value of occupancy for all the investigated scenarios. This was particularly evident when we compared the two dry cases. Here, for certain combinations of the colonization and extinction rates we still observed some viable metapopulation in the static case, while the dynamic model went to extinction in all cases.Another important result shown by the plots in figures The results presented above show what subset of species might survive given the hydrological regime of the river network. However, they do not give information about the temporal occupancy dynamics at the local scale, which is investigated in the following section, where we assumed a given combination of the colonization and extinction parameters (see the red circle in figures . 3.2I1 and D1) had a lower mean occupancy than the others.The time series of river network occupancy resulting from the application of the dynamic metapopulation model on the nine scenarios described above are shown in a,d,g), and in the contributing area and TWI scenarios of the intermediate cases , the majority of the simulations predicted metapopulation extinction for scenario I1, and metapopulation survival was null for the dry regime .In all cases, the mean occupancy of the dynamic networks was lower than that of their static counterparts. This was particularly evident in the dry regimes, where the metapopulation survived only in static conditions, while the dynamic simulations all led to extinction. The lower mean occupancy was also accompanied by a higher temporal variability of the occupancy in all dynamic networks, as compared with the static scenarios. Accordingly, the coefficient of variation of network occupancy , instead, a number of disconnections arose along the network, and several small active branches were disconnected from the outlet. However, in spite of the presence of these disconnections and the ensuing lower values of the LCP length, the mean LCP was only slightly smaller than the mean active length of the network. Consequently, the few disconnections only weakly hindered species dispersal, as compared with the previous case. Interestingly, in scenarios W1, I1, D1, when the local persistencies were spatially uncorrelated, significant sizes of the LCP were observed for very short durations even in the case of wet hydroclimatic conditions. In this case, the mean LCP was much smaller than the mean network length and, consequently, metapopulation dispersal was significantly hindered by the fragmentation of the active network. As climate varied from wet to dry, the curves in The different occupancy dynamics observed under the nine scenarios analysed in Pi. The observed patterns of metapopulation occupancy only in part resembled the local persistency maps. The headwaters represented the portions of the river network with, on average, the lowest level of occupancy due to their highly intermittent dynamics and the more limited habitat suitability due to the reduced stream bed area. On the other hand, the main stream was characterized by the largest value of occupancy in all the scenarios, especially in the most downstream region of the stream network. Nevertheless, the random scenario (W1 and I1) represented the least favourable ones to maintain a viable metapopulation, due to the large number of disconnections that arose along the stream network.The different hydrological dynamics experienced by the river network also affected the chances of metapopulation survival along the network, as shown in . 4. 4.1The synthetic dynamic networks generated in the companion paper were used as domains for a network-scale ecological model devoted to the simulation of metapopulation dynamics in riverine environments. The application not only demonstrated the versatility of the proposed framework for eco-hydrological studies, but also provided novel insights on the role of network dynamics on species spread and survival in fluvial environments. Dynamic river networks, in fact, increase the temporal variability of network occupancy as compared with static streams. This is explained by the enhanced time variability of the portion of network that can be colonized by the target species: when the active network expands, additional nodes become available for colonization, and network occupancy generally increases. Conversely, when the network contracts, network occupancy is bound to shrink as more and more nodes dry out. However, a smaller mean network occupancy is observed in dynamic networks, with respect to the corresponding static streams with a constant, equivalent active length. This is related to the ephemeral nature of the nodes that are active when the network is relatively expanded, which makes them unsuitable for colonization, owing to the ecological lag between the node activation and the following node colonization. As such, the reduction of mean occupancy is more evident in dry climates, where only a limited number of nodes can sustain the metapopulation for prolonged time periods. These nodes act as starting points for species dispersal during the time periods in which the network is more expanded. The lower mean and the higher variability of network occupancy associated to dynamic networks is also reflected into a higher probability of extinction of the metapopulation in a dynamic setting, in accordance with previous studies .Alterations to the spatial configuration of habitats and the temporal fluctuations in river flow may reduce the connectivity between temporary and permanent aquatic habitats and therefore could potentially limit their ecological use by aquatic organisms. Our analysis also revealed that enhanced stream disconnections appearing along the active network bear a significant signature on metapopulation dynamics, preventing species dispersal and promoting extinction. In dynamic streams, such disconnections may temporarily disappear during the network expansion, thereby creating ephemeral connectivity windows for species propagation along the network, with potentially relevant network-scale effect on metapopulation dynamics ,29. Alth. 4.2Our study showed the importance of coupling dynamic hydrological and ecological models to predict the patterns of species occupancy in dynamic stream networks. Here, the coupling was expressed based on habitat suitability, which linked the stream bed area that dynamically expands and contracts based on the hydroclimatic forcing to the probability of species colonization and extinction. This function was selected because the stream bed area is the zone where the primary production, which is an essential process at the basis of the food chain, takes place . HoweverAnother potential limitation of our approach is represented by the assumption of unbiased dispersal, for which the direction of water velocity did not affect the movement of the target species. This assumption has been demonstrated to be valid for multiple fish species ,56, but Furthermore, the ecological model could be made more general by relaxing some of its assumptions , thus allowing the description of various target species with different general traits. For example, for some species larger streams may not provide preferred habitat, requiring a different specification of the habitat suitability in our model. An additional improvement could be that of adding the possibility for the target species to survive on a given node for a certain period of time after the node had dried out, thereby allowing the model to describe species that can temporarily survive also in lentic habitats.c, e, δ) was also neglected in our analysis. This assumption is likely to be violated when evolution modifies species response to environmental variables. However, the timescale of the process is far beyond those covered in the proposed work.Finally, non-stationarity in species traits .e/c ratio, since they can quickly colonize those limited suitable habitats still present along the river network.As network dynamics were driven by climate, a strong climatic signature can also be found in the observed temporal patterns of species persistency. Temporary streams characterized by wet climates, in fact, were associated with higher but more stable degrees of occupancy of the target species. Conversely, the driest scenarios displayed more variable degrees of network occupancy and smaller survival probabilities. The metapopulation survival in these harsh hydroclimatic conditions is limited to those species who are characterized by smaller values of the


The advantages of an event camera, such as low power consumption, large dynamic range, and low data redundancy, enable it to shine in extreme environments where traditional image sensors are not competent, especially in high-speed moving target capture and extreme lighting conditions. Optical flow reflects the target’s movement information, and the target’s detailed movement can be obtained using the event camera’s optical flow information. However, the existing neural network methods for optical flow prediction of event cameras has the problems of extensive computation and high energy consumption in hardware implementation. The spike neural network has spatiotemporal coding characteristics, so it can be compatible with the spatiotemporal data of an event camera. Moreover, the sparse coding characteristic of the spike neural network makes it run with ultra-low power consumption on neuromorphic hardware. However, because of the algorithmic and training complexity, the spike neural network has not been applied in the prediction of the optical flow for the event camera. For this case, this paper proposes an end-to-end spike neural network to predict the optical flow of the discrete spatiotemporal data stream for the event camera. The network is trained with the spatio-temporal backpropagation method in a self-supervised way, which fully combines the spatiotemporal characteristics of the event camera while improving the network performance. Compared with the existing methods on the public dataset, the experimental results show that the method proposed in this paper is equivalent to the best existing methods in terms of optical flow prediction accuracy, and it can save 99% more power consumption than the existing algorithm, which is greatly beneficial to the hardware implementation of the event camera optical flow prediction., laying the groundwork for future low-power hardware implementation of optical flow prediction for event cameras. The estimation of motion patterns corresponding to spatio-temporal variations of structured illumination commonly referred to as optical flow, provides vital information for estimating ego-motion and perceiving the environment . In the t is greater than the event trigger threshold Therefore, the event camera emerged as the times required, and is also called a dynamic vision sensor, bio-inspired sensor, or neurological sensor ,3,4,5. T, an ON or OFF event is generated.Combined with the characteristics of the event camera, The set of output events in the spatiotemporal domain is known as the spatiotemporal event stream. The spatiotemporal event stream can be defined as the following .(1)E=∑iHigh temporal resolution (in the unit of microseconds), low power consumption, and high dynamic range compared with frame-based cameras make event cameras suitable for estimating high-speed and low-light visual motion in an energy-efficient manner. Hence, event cameras have been gradually applied to object tracking ,9, surveEvent cameras are also suitable for optical flow estimation since the precise timestamp at pixel-level intensity changes directly encodes fine-grain motion information. However, the event camera represents a paradigm shift in computer vision because of its principle of operation and unconventional output . BecauseIn recent years, many researchers have proposed optical flow estimation based on event cameras to promote the application of event cameras in machine vision. According to the working principle of their algorithms, these optical flow estimation methods can be roughly divided into two categories. One is the optical flow estimation algorithm based on traditional methods. The other is the modified version of the optical flow estimation algorithm based on the neural network.In the basic algorithm of event camera optical estimation, the gradient method, plane fitting method, and frequency method have all achieved perfect optical flow estimation results. Benosman, R. and Brosch, T. used the gradient-based Lucas–Kanade algorithm to estimate the optical flow of discrete spatiotemporal data ,15. The For neural network algorithms for the event camera’s optical flow estimation, supervised training, self-supervised training, and unsupervised training are all applied to the event camera’s optical flow estimation by researchers. EV-FlowNet  proposedAlthough the above-mentioned neural network method has made optical flow prediction on the spatiotemporal data of the event camera possible, most of the methods mentioned above slice the spatiotemporal data stream according to a fixed number of events or a fixed time interval and then convert it into image frames, sending the image frames into the traditional convolutional neural network for training. The spatiotemporal data stream is sliced by the fixed number of events or the fixed time interval. Then, the event slice is converted into image frames and sent into the traditional convolutional neural network for training. However, the method of slicing with a fixed number of events or a fixed time interval and then converting to an image frame will result in motion blur or information loss in the image frame. Moreover, the network will calculate every pixel in the image frame, significantly increasing the amount of calculation and losing the advantage of the low data volume of the event camera.This paper also uses the learning method to predict optical flow, but it is different from the above methods. First, this paper uses the method in  to adaptBuild a spike neural network architecture that is more suitable for discrete spatiotemporal data stream so that it can directly process discrete spatiotemporal data of the event camera, reduce the amount of computation, and retain the advantage of the low data volume of event cameras;Aiming at the problem that the existing training methods of the spike neural network mainly focus on the spatial domain but pay less attention to the time domain, the network is trained using high-performance spatial temporal backpropagation combined with the spatiotemporal information of the event camera to improve the accuracy of optical flow prediction.In a word, the main contributions of this paper are as follows:Because the output data of the event camera is an asynchronous and discrete spatiotemporal data stream, which is not compatible with the existing convolutional neural network model, many researchers construct spatiotemporal data into image frames with various methods and then use existing convolutional neural networks to predict the optical flow.The most commonly used representation is multiple discretized frames of event counts ,24,26,27Spike neural network is a new generation of artificial neural network model inspired by biology, which has strong spatiotemporal information representation and asynchronous event information processing capabilities. Spike neural network has many neuron representation models, but leaky-integrate-and-fire (LIF) is the most widely used model, which can be simply expressed by the following formula:When the membrane potential Wu, Y. optimized the traditional LIF and built an iterative LIF mode . When weEquation (4) shows that the membrane potential at time t is related to the membrane potential at j-th neuron in the pre-layer  can be changed to:i-th neuron in the layer(n) at time t:Next, we combine the fire reset mechanism in Equation (7). Considering the accumulation of the presynaptic input in the spatial domain and the decay of the membrane potential in the time domain, we iteratively update the LIF model to obtain the membrane potential of the Equation (8) is the iterative LIF model that is more consistent with the firing activity of the neuron. The model of spike iteration is shown in Our network architecture is similar to that in SpikeMS . The endλ is the weight factor.Compared with the traditional optical flow datasets based on frame-based cameras, the number of optical flow datasets with ground truth that can be used for optical flow estimation of event cameras is relatively small. Therefore, we use a self-supervised learning method, which uses the gray image generated together with the asynchronous event stream of the event camera to train the spike neural network . We combWe send the event slice The photometric reconstruction loss ∂L∂oa is the width of rectangular function.In the process of backpropagation, we need to solve the presynaptic output activity :(16)hu=1We use the public dataset Multi Vehicle Stereo Event Camera dataset (MVSEC)  to trainN-th and N + 1-th (dt = 1) gray images, and the other is generated between the N-th and N + 4-th (dt = 4) gray images. Since we use adaptive slicing, we only use the dataset of dt = 1 to train the network and conduct comparative experiments. When using the gray image for self-supervised training, there may be optical flow information predicted by multiple event slices between two gray images. Therefore, it is necessary to map the predicted optical flow of all event slices in the two gray image frames to ensure the accuracy of loss function calculation.We use the outdoor day2 in the MVSEC dataset to train the network model. There are two types of ground truths of optical flow in the dataset, one is generated between the λ in Equation (10) is set to 0.5. For the Charbonnier loss (12), we set α to be 0.45 and Our framework is implemented in PyTorch. We use the Adam optimizer  and a leEquation 0 is set milar to . The thrm is the number of pixels with optical flow information, In this paper, Average End point Error (AEE), which is commonly used in the field of optical flow prediction, is selected as the evaluation index of optical flow quality predicted by different methods. AEE mainly calculates the average European distance between the predicted optical flow of each pixel and the ground truth. The AEE calculation equation is as follows:Our method compares with ,22,24,37In ,37, the FLOPs) and the theoretical power consumption between SNN and CNN with the same network architecture.In order to verify that the spike neural network proposed in this paper can better handle the event camera’s discrete data and reduce the network’s computational load, in this section, we analyze the computational complexity of our approach in terms of the float point operations FLOPA “Multi-Add” is often regarded as a float point operation in computer vision papers. Therefore, the operation amount of the single-layer network is:The number of floating point operations in the entire CNN network is:Because of the binary nature of spike events, SNN performs only an accumulation (AC) per synaptic operation. Compared with the addition operation (0.9 pJ), the power consumption of the multiply-accumulate operation (4.6 pJ) is 5.1 times that of the add operation . Thus, iBefore optical flow prediction, the event flow needs to be cut into event slices and then input into the optical flow prediction network in various forms. The existing event slicing methods will lead to motion blur or information loss of the target in the scene, affecting the accuracy of optical flow prediction. Therefore, in this experiment, only the event slicing method is changed, and optical flow prediction is conducted on the SNN proposed in this paper with the same dataset. For the convenience of comparison, we choose a fixed time window (dt = 1) as the slicing method for the comparison experiment. The experimental results are shown in The optical flow prediction results after slicing by different methods are shown in In this paper, we construct an end-to-end spike neural network model for the event camera’s optical flow prediction more suitable for the discrete spatiotemporal event stream. Unlike the current neural network for optical flow prediction, we can directly handle the discrete spatiotemporal event stream output by the event camera, reducing the network computation. Compared with the convolutional neural network with the same network structure during hardware implementation, the proposed algorithm can save 99% more power consumption than the existing CNN algorithm, which is greatly beneficial to the hardware implementation of the event camera optical flow prediction. At the same time, the network is trained in the space domain and time domain by using spatial-temporal backpropagation in a self-monitoring way, which makes full use of the spatiotemporal information of spatiotemporal data flow and greatly improves the network performance. Moreover, to avoid motion blur or information loss, we adaptively slice the spatiotemporal data stream, and send event slices into the network, improving the accuracy of optical flow information. Finally, compared with other existing methods on the public dataset, the accuracy of optical flow information predicted by our method is not inferior to that of existing methods.


In recent years, multispectral imaging systems are considerably expanding with a variety of multispectral demosaicking algorithms. The most crucial task is setting up an optimal multispectral demosaicking algorithm in order to reconstruct the image with less error from the raw image of a single sensor. In this paper, we presented a four-band multispectral filter array (MSFA) with the dominant blue band and a multispectral demosaicking algorithm that combines the linear minimum mean square error (LMMSE) and the adaptive kernel regression methods. To estimate the missing blue bands, we used the LMMSE algorithm and for the other spectral bands, the directional gradient method, which relies on the estimated blue bands. The adaptive kernel regression is then applied to each spectral band for their update without persistent artifacts. The experiment results demonstrate that our proposed method outperforms other existing approaches both visually and quantitatively in terms of peak signal-to-noise-ratio (PSNR), structural similarity index (SSIM) and root mean square error (RMSE). Digital color cameras generally sensitive to three bands of the visible electromagnetic spectrum are used to capture digital color images representing the reflectance of the observed object. Nowadays, technological advancement has made it possible to overcome this three-band limitation with the development of multispectral digital cameras to acquire multispectral images with more than three spectral bands per pixel. There are several types of multispectral image acquisition systems including single-sensor one-shot cameras which are equipped with a multispectral filter mosaic. However, in the raw image from the sensor, each pixel is characterized by a single available spectral band. We will have to reconstruct the missing spectral bands by the demosaicking method. The reconstruction performance depends on the optimal choice of MSFA and the multispectral demosaicking algorithm.Several MSFA patterns are proposed in the literature. To our knowledge, Miao et al.  are the Many multispectral demosaicking algorithms using the designed MSFAs have been implemented in the literature . Miao etMultispectral images demosaicked using the previous algorithms suffer from severe artefacts in edge regions. To overcome these limitations, a new avenue of multispectral demosaicking called the LMMSE method is being explored. Zhang and Wu , in the The contributions of our paper focused on the LMMSE method in  and the The identified four-band MSFA is based on the generic method of Miao et al.  based onAfter balancing the energies of the different spectral bands according to the proposed MSFA pattern, their spectral sensitivities are shown in The LMMSE method as used for RGB images obeys two assumptions. Firstly, in natural images, the different spectral bands are strongly correlated. Then, the gradient of the different bands remains constant and constitutes a smooth process (low pass) . To veriG bands at different pixels. We briefly present here the estimate of the G-band at each spatial position G-band at the red pixels is obtained according to the formula used:In their color image demosaicking algorithm, Zhang and Wu  used theThe gradient Before calculating the gradient, a second order Laplacian interpolation is used beforehand to know at each pixel, the “missing samples”. The noises associated with the directional gradient estimate are determined as:So, we have:The gradient x is defined:The optimal estimate of the minimum mean square error (MMSE) of p(x/y) is rarely known making estimation of MMSE difficult. Therefore, instead of MMSE, the authors used the LMMSE method to estimate x, such as:However, in practice, the probability y. Denoting by For an optimal estimate of With More information is given in .Takeda et al.  proposedThe They are computed by the following optimization problem:K is the kernel function and H the 2 × 2 smoothing matrix of order defined by:The adaptive kernel regression is an extension of the classical kernel regression  and struThe value of a spectral band at a spatial position is determined by:Expressing The steering matrix is defined as:h makes it possible to have a strong denoising effect and the steering kernel is a Gaussian kernel.The The proposed algorithm is subdivided into six main steps. The blue band being the dominant band of our MSFA c, this bWe estimate the blue band missing at the orange pixel by applying the formula:The gradient The green and red bands have identical neighborhoods.sw) and southeast The gradient values rections  northwesEach orange band is then estimated at the green and red pixels by the formula:n), south (s), east (e), and west (w) directions.We apply the same strategies as before but in a wider neighborhood  in the nThe Taking into account the neighborhood of the orange bands for the red and green pixels , originarections b,c for tFrom Therefore, the missing orange band at the blue pixels is estimated by the relation:Similarly, we estimate the red and green bands at the blue pixels such as:Although the previous estimation formulas have worked well for color images as in , their uIn our experiments, we used 26 images from the 32 (the others being resemblances) of the cave dataset , in whicTo evaluate the performance of the proposed algorithm, we compared it with recent four-band multispectral demosaicking methods, namely generic binary tree edge sensing (BTES) , directiFor evaluation purposes, we selected four images with detailed structures as shown in To quantitatively assess the objective performance of our proposed algorithm, we used the PSNR, SSIM, and RMSE metrics as described in ,22 and cA careful analysis of In this study, we identified a four-band MSFA pattern for single-sensor cameras, arranged in a 6 × 6 moxel half filled with the blue band taking into account the properties of the liquid crystal tunable filter with which the sensor surface of the camera used is covered to acquire simulation images of the cave dataset. Based on the existing one, we then proposed a consequent algorithm that combines the LMMSE method and the adaptive kernel regression. In the proposed algorithm, we estimated the missing blue bands by the LMMSE method and the other spectral bands by the directional gradient method which relies on the estimated blue bands. Finally, applying the adaptive kernel regression gradient method to each spectral band refines the band by ridding it of artifacts that can adversely affect the reconstruction performance. In the experiment, we evaluated the proposed algorithm both visually and quantitatively with the existing algorithms BTES, DFWF, ASCD, and N-LMMSE. The results show that our proposed algorithm outperforms the others both visually and in terms of PSNR, SSIM, and RMSE.The future work consists in deepening the algorithm in terms of the number of spectral bands by varying the moxels such as they are of 4 × 4 and 8 × 8 support to fully appreciate the degradation behavior of each spectral band.


The World Federation of Obesity warns that the main health problem of the next decade will be childhood obesity. It is known that factors such as gestational obesity produce profound effects on fetal programming and are strong predictors of overweight and obesity in children. Therefore, establishing healthy eating behaviors during pregnancy is the key to the primary prevention of the intergenerational transmission of obesity. Mobile health  programs are potentially more effective than face-to-face interventions, especially during a public health emergency such as the COVID-19 outbreak.This study aims to evaluate the effectiveness of an mHealth intervention to reduce excessive weight gain in pregnant women who attend family health care centers.The design of the intervention corresponds to a classic randomized clinical trial. The participants are pregnant women in the first trimester of pregnancy who live in urban and semiurban areas. Before starting the intervention, a survey will be applied to identify the barriers and facilitators perceived by pregnant women to adopt healthy eating behaviors. The dietary intake will be estimated in the same way. The intervention will last for 12 weeks and consists of sending messages through a multimedia messaging service with food education, addressing the 3 domains of learning . Descriptive statistics will be used to analyze the demographic, socioeconomic, and obstetric characteristics of the respondents. The analysis strategy follows the intention-to-treat principle. Logistic regression analysis will be used to compare the intervention with routine care on maternal pregnancy outcome and perinatal outcome.The recruitment of study participants began in May 2022 and will end in May 2023. Results include the effectiveness of the intervention in reducing the incidence of excessive gestational weight gain. We also will examine the maternal-fetal outcome as well as the barriers and facilitators that influence the weight gain of pregnant women.Data from this effectiveness trial will determine whether mami-educ successfully reduces rates of excessive weight gain during pregnancy. If successful, the findings of this study will generate knowledge to design and implement personalized prevention strategies for gestational obesity that can be included in routine primary care.ClinicalTrials.gov NCT05114174; https://clinicaltrials.gov/ct2/show/NCT05114174DERR1-10.2196/44456 The World Obesity Federation warns that the main health problem of the next decade will be childhood obesity ,2. ObesieGWG during early pregnancy has been repeatedly associated with increased adiposity in childhood and adolescence -15. ThusNew strategies to engage the target population are required to maintain nutritional recommendations as a priority in the daily decision-making (top of mind) of pregnant women . Interve2) and body weight (−1.07 kg) in the intervention group [mHealth programs are potentially more effective than face-to-face interventions since they make it possible to cover a larger part of the population; moreover, face-to-face interventions are more labor-intensive, time-consuming, and expensive. Furthermore, they are especially useful during public health emergencies, like the recent COVID-19 pandemic . Accordion group . A recenon group  demonstron group . Hence, on group . Thus, ton group . In thisThe design of the intervention corresponds to a classic RCT, a design that allows us to prospectively study pregnant women, in which it is intended to compare the effect of the intervention versus the control condition, to establish a cause-and-effect relationship. This design allows us to reduce the risk of comparability bias. The study will be carried out with pregnant women who control their pregnancy in Family Health Centers (CESFAM) of the Metropolitan Region  and the Aconcagua Valley, Valparaiso Region . The CESFAM work under the Comprehensive Health Model with a Family and Community Approach, focusing on prevention and health promotion, and are responsible for basic health care, including home care and health rehabilitation actions. These centers focus on families and communities, give importance to community participation, and work with a primary health team that attends to the whole family in health and sickness throughout the life cycle.Pregnant women enrolled in the prenatal control program receive routine care at the CESFAM.Pregnant women enrolled in the prenatal control program receive routine care at the CESFAM and messages on nutrition (intervention).Chilean- or Spanish-speaking immigrant pregnant women older than 18 years who receive care at the 6 CESFAM in El Bosque, Metropolitan Region and in Segismundo Iturra CESFAM in San Felipe, Aconcagua Valley, Valparaiso Region; who have gestational ages ≤12 weeks (first trimester); who have a single pregnancy; who declare to have a normal pregnancy at the time of starting the intervention; who agree to be randomized; and who have voluntarily signed the informed consent can participate in this study. The pregnant women who participate in the study must have a mobile device that allows the use of MMS.Exclusion criteria include multiple pregnancies, conditions requiring a special diet, participants with psychiatric illnesses or other prepregnancy pathology, and a history of recurrent miscarriages.The total sample consists of 511 participants, which will be divided into 2 groups. In the El Bosque CESFAM, 280 pregnant women were recruited, with an estimated dropout rate of 30% (based on the pilot study carried out) to guarantee the required sample size of 210 pregnant women with a confidence level of 90% and a 5% error. At Segismundo Iturra CESFAM, 231 pregnant women were recruited, with the same estimated dropout rate, to ensure a sample size of 178 pregnant women with a confidence level of 90% and a 5% error. For the calculation of the sample size, the official records of the DEIS regarding the number of pregnant women between 20 and 44 years of age who were treated for prenatal control in the CESFAM of the El Bosque commune and Segismundo Iturra were considered. The recruitment period will be 6 months.2), normal weight (BMI 18.5-24.9 kg/m2), overweight (25-29.9 kg/m2), and obese (BMI≥30 kg/m2). Simple random selection will be carried out then by generating a table of random numbers without repetition, from 1 to n, and deciding a priori that it will be read from left to right, with even numbers assigned to the control group and odd numbers to the intervention group.The pregnant women who meet the inclusion criteria are invited to participate in the study, as are those who accept and sign the informed consent form. These pregnant women receive the link to the diagnostic survey on their telephones and are then randomized to be included in the intervention. At the end of each month of the recruitment period, the researchers will randomize the pregnant women who were recruited during that month. A stratified randomization will be carried out to ensure a sample that is as balanced as possible. The sample will be divided into 4 strata according to their pregestational weight, classifying them as underweight , and the perinatal outcomes (prematurity and birth weight) of the pregnant women in the control and intervention groups.2), comparing the intervention group with the control group in terms of the percentage of women who are classified as having excessive weight gain at the end of pregnancy. To confirm the effectiveness of the intervention, a significant decrease (P<.001) of women with eGWG in the intervened group will be expected. For data analysis, the statistical software GraphPad Instat 3.0b and GraphPad Prism 6.0f (GraphPad Software Inc) will be used. P<.001 (determined by a 2-sided test) will be considered statistically significant.The data analysis plan will be governed by the intention-to-treat principle, as we will include all participants who were randomly assigned after recruitment, assuming that participants who drop out are treatment failures. The effectiveness of the treatment will be measured using the chi-square test  and the Scientific Ethics Committees of the South Metropolitan Health Service . Informed consent will be obtained from all participants invited to participate in the study before proceeding with the initial survey. The data will be treated respecting the ethical principles that guarantee the anonymity of the participants.The study was funded by the National Research and Development Agency of Chile in December 2021. The data collection began on May 2, 2022. Study staff have been engaged in activities associated with study including enrollment and data collection. As of November 30, 2022, a total of 222 pregnant women have been admitted for the first prenatal appointment, 127 meet the inclusion criteria, and 76 agree to participate and answered the diagnostic survey. The expected timeframe for completing recruitment and data analysis is November 2023.It is well known that pregestational obesity has been recognized as a risk factor for several perinatal complications, such as fetal macrosomia, gestational diabetes, hypertensive disorders, failed induction, premature rupture of membranes, and cesarean section . NeverthThe results of this study may serve to implement evidence-based primary prevention strategies and help a broader group of pregnant women maintain adequate weight gain during pregnancy and prevent pregnancy pathologies associated with obesity. This would ultimately influence health care costs. In Chile, it has been described that the cost of overweight and obesity increases to US $455 million by year, representing 2% of the total health budget, which means that obesity costs 4-fold higher than normal weight health care . ThroughA limitation of this study is the reliance on smartphones to access interventions. In addition, the recruitment of pregnant women must occur during the first trimester of gestation, and this may be hindered because some pregnant women begin prenatal care in the second trimester. Another limitation is that the pregnant woman may decide not to interact with the messages by blocking the number of the intervention.


Viscous dissipation causes significant energy losses in fluid flows; in ducts, laminar flows provide the minimum resistance to the motion, whereas turbulence substantially increases the friction at the wall and the consequent energy requirements for pumping. Great effort is currently being devoted to find new strategies to reduce the energy losses induced by turbulence. Here we propose a simple and novel drag-reduction technique which achieves substantial energy savings in internal flows. Our approach consists in driving the flow with a temporally intermittent pumping, unlike the common practice of a constant pumping. We alternate “pump on” phases where the flow accelerates, and “pump off” phases where the flow decays freely. The flow cyclically enters a quasi-laminar state during the acceleration, and transitions to a more classic turbulent state during the deceleration. Our numerical results demonstrate that important energy savings can be achieved by simply modulating the power injection into the system over time. The physical understanding of this process can help the industry in reducing the waste of energy, creating economical benefits and preserving the environment by reducing harmful emissions. Meeting the increasing demand for energy while reducing our dependence from fossil fuels is a complex and multi-faceted problem, challenging researchers3, and international organisations like the International Energy Agency4. While some countries are able to trade part of their wealth for a more sustainable energy production, others do not have such a possibility. Due to the recent growth of the oil price, in facts, the latter are left with the only option of dramatically increasing their reliance on firewood. Such trend clearly contrasts with the guidelines drawn by the Glasgow Climate Pact5, enhancing both deforestation and global warming. In order to interrupt this escalation, it is necessary to reduce the price of liquid fuels. Cheaper access to natural oil and gas can facilitate the economic growth of developing countries, later allowing them to face the transition towards greener energy sources. At the same time, a lower cost of innovative fuels, like hydrogen, can further promote the transition, also making it easier for those nations already undergoing it.The world is facing an unprecedented energy problem6. As recently estimated7, the cost of energy transport may vary by more than two orders of magnitude when comparing different carriers and energy sources. Transferring oil and gas in tankers, for example, is significantly more convenient than displacing liquid hydrogen in pipelines. Oil and gas, in fact, have a significantly higher energy density than liquid hydrogen, therefore less fluid needs to be transported in order to store the same amount of energy. Nevertheless, all these fuels remain unaffordable for many developing countries, and their transport cost needs to be reduced.Various factors contribute to the final cost of fuels, as frequently discussed in heterogeneous contexts, but the non-negligible share coming from transport is often overlooked11 and have categorised them as active or passive, depending on whether they require a power supply. Special surface treatments such as the carving of microscopic riblets on the wall12 or the addition of polymers to the flow13 belong to the second category, while for example a predetermined motion at the wall15 belongs to the first. Some techniques are extremely efficient in the context of duct flows , but most of them bring disadvantages like the contamination of the fluid with spurious substances, the introduction of complex control mechanisms with moving parts, or the need for regular maintenance.The sizes and operative flow-rates of conventional pipelines determine an highly turbulent motion of the fluid at their interior. Its chaotic behaviour dissipates a significant amount of the energy supplied to the flow intended to displace it, hence inducing significant drag penalties and decreasing the energetic efficiency of the process. Over the years, many researchers have studied various approaches to control the flow17, our approach exploits an unsteady power delivery, inspired by the work of Iwamoto, Sasou and Kawamura18 and Kobayashi et al.19, designed to move the flow smartly back and forth between the turbulent regime and a quasi-laminar one. In the following, we describe in detail our innovative forcing technique, and discuss the results of the demanding numerical simulations we performed. The potential of this control and the need for further investigations are highlighted.In this paper, we demonstrate the success of a simple and feasible approach that circumvents such issues. The periodic power-on and shutdown of the pump feeding a turbulent pipe flow can reduce the energy needed to transfer a fixed amount of fluid in a given time from one point to another, regardless of the power peaks required to repeatedly accelerate the fluid. This constitutes a hybrid form of control, in which no additional devices are required (as in passive techniques), and the active pumping phase is employed to increase the overall efficiency of the system (as in active techniques). Building upon recent progresses made in understanding the transient nature of turbulent flows and the effects of a time-varying pumpinga of Fig. 20, where h its half-width, T and the relative length of the active pumping phase, the duty-cycle nth pulsation we prescribe:Our numerical experiments are carried out in an indefinite channel, bounded by two smooth planar walls. An incompressible Newtonian fluid flows through the domain as described by the incompressible Navier–Stokes equations, under the influence of a volumetric forcing of choice. In such simulations, this forcing is either set to a constant pressure gradient, or adjusted in time to ensure a constant flow rate. Here, instead, we prescribe an homogeneous streamwise pressure gradient mentclass2pt{minim19, who employed machine learning to devise and test different waveforms. In our numerical study, however, we employ a simpler and more realistic waveform, and aim at verifying the robustness of the approach with respect to the investigation method and the control parameters, establishing that the advantage is not limited to reductions in drag, but extends to savings in energy.A similar control strategy was recently studied experimentally by Kobayashi et al.20 to obtain reliable statistics of the channel flow at the same Reynolds number. Moreover, for each Within this study, we have considered different values of the period  starts to grow and the pumping power  associated to the cross-stream velocity fluctuations: an efficient indicator of the turbulent state of the flow. The value of K is extremely small at the beginning of every period, and remains such during the acceleration. The forcing is then switched off setting Q starts decreasing (due to viscous losses) and so does K. At a random instant of the deceleration, however, the decay rate of Q suddenly increases, producing a kink in the curve of panel b. This coincides with a peak in K and, shortly thereafter, also Q and K is again almost zero.Figure 23, which extend towards the centre of the channel before the activation of the forcing, are stretched and initially stabilised. The sudden, intense and brief nature of the acceleration prevents the appearance of turbulent spots, and no new turbulence is therefore generated during this phase. At the end of the acceleration, what remains of the classic streaks is a quasi-2D perturbation  of the laminar flow: the streaks extend indefinitely in the streamwise direction. After switching the forcing off, they do not become immediately unstable, but rather keep growing while the flow progressively slows down, and organise themselves in a regular alternating low- and high-speed pattern (as in panel c), which sometimes extends up to the centreline, while the mean velocity profile assumes the typical parabolic shape reminiscent of the laminar regime. Such streaks differ from those of a conventional turbulent channel flow with comparable wall friction, and are observed here for the first time. This picture comes to an end when a flow instability sets in and destroys the streaks, making the flow turbulent as in panel d: perturbations suddenly grow in magnitude, and an abrupt transition drives the channel towards a fully chaotic regime.In Fig. Once new turbulence is generated, the wall friction undergoes a sudden increase: this induces a faster decay of the flow rate, corresponding to the kink in Fig. https://en.wikipedia.org/wiki/Keystone_Pipeline,https://en.wikipedia.org/wiki/Petroleum_transport).Our work demonstrates how the energetic efficiency of a fluid transport system can be effectively improved by modulating in time the pumping power. By employing a simple periodic sequence of on–off pulses, described by the duration of the period and the duty-cycle, our numerical study proves that intense accelerations followed by long relaxation phases yield significant energetic savings, up to 22% in the parameter range considered. For example, assuming an average transport cost of up to 5 US dollars per barrel of crude oil, the Keystone pipeline in North America operating at full regime  can save about 0.5 million US dollars per day , capable of second-order accuracy thanks to central finite-differences in space and Adams–Bashfort’s method in time. Time integration is performed according to a fractional-step method, under a bounding constraint on the maximum value of the CFL number. The Poisson pressure equation is dealt with by means of an efficient spectral solver. Mass, momentum and energy are therefore conserved exactly. The discretisation points are uniformly distributed along the homogeneous directions, while an hyperbolic tangent stretching function is employed in the wall-normal one.We numerically solve via direct numerical simulation (DNS) the discretised incompressible mass and momentum balance equations with an efficient in-house code (Several resolutions and sizes of the computational domain have been tested to ensure that our conclusions are independent from discretisation effects. The fully-resolved DNS discussed here have been carried out on a computational grid characterised by a streamwise spacing of Viscous, or “plus” units are defined for the reference turbulent channel flow under steady forcing at 25.Computations were executed by running the program in parallel on 8192 cores in the supercomputer Deigo at OIST and in Fugaku at RIST. The present results have also been validated against a well tested spectral codeSupplementary Information 1.Supplementary Information 2.Supplementary Video 1.Supplementary Video 2.