This paper presents the T-RexNet approach to detect small moving objects in videos by using a deep neural network. T-RexNet combines the advantages of Single-Shot-Detectors with a specific feature-extraction network, thus overcoming the known shortcomings of Single-Shot-Detectors in detecting small objects. The deep convolutional neural network includes two parallel paths: the first path processes both the original picture, in gray-scale format, and differences between consecutive frames; in the second path, differences between a set of three consecutive frames is only handled. As compared with generic object detectors, the method limits the depth of the convolutional network to make it less sensible to high-level features and easier to train on small objects. The simple, Hardware-efficient architecture attains its highest accuracy in the presence of videos with static framing. Deploying our architecture on the NVIDIA Jetson Nano edge-device shows its suitability to embedded systems. To prove the effectiveness and general applicability of the approach, real-world tests assessed the method performances in different scenarios, namely, aerial surveillance with the WPAFB 2009 dataset, civilian surveillance using the Chinese University of Hong Kong (CUHK) Square dataset, and fast tennis-ball tracking, involving a custom dataset. Experimental results prove that T-RexNet is a valid, general solution to detect small moving objects, which outperforms in this task generic existing object-detection approaches. The method also compares favourably with application-specific approaches in terms of the accuracy vs. speed trade-off. The recent growth of industrial applications for object detection stimulates the research community toward novel solutions. Intelligent video analysis is the core of several industry applications such as transportation , sentimeDeep learning lies today at the core of state-of-the-art techniques for object detection, such as Faster RCNN , YOLO 66 and SSDThis paper addresses the detection of small objects, which typically take up a few tens of pixels. State-of-the-art approaches often exhibit poor performances when dealing with very small objects, due to the apparent difficulty in discriminating these features from one another and from the background . Figure Human observers face a similar challenge when looking for tiny objects in a wide scene. The detection task, in fact, gets simpler if the target moves with respect to a still background, since the human vision system can combine motion information with the visual aspect of the object. The approach presented here deploys the detection of tiny moving objects in wide scenes on limited hardware resources. The method adjusts the basic building blocks of resource-constrained computer vision, and proposes a custom deep neural network for the recognition task. The T-RexNet framework improves over generic hardware-aware detectors, which only rely on visual features, and combines those features with motion information. The framework processes three consecutive frames from the video source, and prompts a set of bounding boxes around the detected objects. The overall architecture includes two stacked blocks, for feature extraction and subsequent object detection.The dedicated pair of parallel convolutional paths in the network support that image/motion fusion process. As compared to generic object detectors, the computational overhead brought about by the two-tiered feature-extraction network is mitigated by reducing the network depth. As a matter of fact, focusing on tiny objects allows to leave out the deep layers operating at low resolution.Single-Shot-Detector (SSD) architectures are quite popular for resource-constrained object detection. The custom feature-extraction module overcomes the well-known limitations of SSD in detecting tiny objects. The resulting feature-extraction architecture is quite shallow, and the object detection block relies on one of the least demanding available State-of-Art (SoA) solutions. In summary, the integration of these two features yields a viable solution for the real-time detection of small objects by constrained devices.Experimental results prove that, in that context, T-RexNet improves significantly over state-of-the-art methods for generic object detection. As compared to application-specific solutions, T-RexNet exhibits a satisfactory accuracy vs/speed balance in several complex scenarios such as aerial and/or civilian surveillance and high-speed detection, tackling medium-sized to tiny objects, and varying target densities. In other words, it manages to achieve high detection rates without sacrificing accuracy too much.http://sealab.diten.unige.it/ accessed on 8 June 2020.The paper is organised as follows. The identification of small moving objects is a subset of a wider research field in object detection. Existing solutions and techniques can be arranged into three main groups, namely, Single-image solutions, Background-subtraction solutions, and Spatio-temporal CNNs.Typical object-detection models handle one image at a time, even when spatio-temporal information might be available. State-of-the art approaches, relying on deep learning, can be divided into region-based and single-shot detectors.In the former models, such as R-FCN  and FastThese methods apply a library of predefined bounding boxes (anchor boxes), which have various shapes and sizes and cover the likely locations of objects in the image. The inference phase takes care of fine tuning each anchor box in terms of size and position. Region-based detectors usually prove more accurate that single-shot detectors, but are computationally demanding, as they require a loop for each single ROI .Multi-scale representation: high- and low- resolution feature maps stem from different levels of a feature-extraction network; after super-sampling low-resolution maps, features fuse together by applying either element-wise sum  ) or concContextual information: the network takes into account explicitly the contextual information around a candidate object. For example, ContextNet  applies Super resolution: generative adversarial networks generate a higher-resolution version of the candidate object, thus improving accuracy in the detection of small objects ) ).Mixed methods: features with distinct scales are extracted from different layers of a convolutional neural network; they are concatenated together, and then used to generate a series of pyramid features .In the case of small objects at low resolutions, both region-based detectors and single shot detectors tend to exhibit poor performances. Several techniques have been proposed recently to overcome that issue :Multi-scThese methods all exhibit an increase in both computational and memory load. This brings about lower update frequency, higher latency, and ultimately might compromise implementations on resource-constrained devices for embedded applications.In complex applications such as aerial surveillance, camera views can cover wide areas. Target objects  usually span just a few tens of pixels, and the detection techniques discussed above  are inefMethods differ in terms of computational cost, robustness and accuracy—Mixture of Gaussians (MOG)  approachSince these methods typically process gray-scale (or even B/W after threshold) images that highlight changes at a given time, the actual detection of moving objects requires some post-processing. This might possibly include morphological transformations, blob detection , or moreThe literature witnesses the growth of spatio-temporal CNNs, which take into account both visual and motion data. In MODNet , the autA spatio-temporal CNN supported the detection of vehicles in Wide Area Motion Imagery (WAMI) . In the Spatio-temporal CNNs for object detection can prove effective, but also exhibit some drawbacks: they are often computationally heavy; the various approaches are normally tailored to specific applications, and application-independent detection of small objects has not been proved yet.The methods discussed above all exhibit some features that make them unsuitable to support the Real-Time detection of small moving objects on resource-constrained devices; specific shortcomings possibly include the inability to recognize tiny objects, impractical computational loads, or lack of general applicability. The approach described in this paper can perform detection of small moving objects by maintaining some crucial features—it is lightweight and suitable for embedded devices, accuracy keeps comparable to SoA approaches and improves over them in particularly challenging conditions, the system is end-to-end trainable, and finally the method is application independent, as it performs satisfactorily in different scenarios.T-RexNet combines several of the techniques mentioned above to detect small moving objects in a fast, lightweight manner. The system benefits from the versatility of an end-to-end fully convolutional neural network, it processes differences between frames to involve motion information, and relies on the efficiency of MobileNet-based convolutions to integrate visual and motion data. Single-shot detectors attain real-time performances. Thus T-RexNet can be regarded as a spatio-temporal, single-shot, fully convolutional deep neural network, as per M and K, which undergo a feature-extraction process based on two separate parallel convolutional paths. The actual object-detection results stem from the third SSD-based step.M, K} of motion-augmented images, as explained in the following.This module received in input three gray-scale input frames, M includes three channels that are worked out as:The image K is the concatenation of the first and the last channels of M, hence it only holds motion data without any visual feature.The image Feature-extraction networks typically include stacks of convolutional layers and pooling layers, in which lower layers involve the details of the image, whereas the topmost layers extract object-related information . From a M), and only motion-related data (image K), respectively.T-RexNet aims to detect small objects, hence high level information can be disregarded, and the number of stacked layers in the feature extraction network reduces accordingly. This feature also entails a beneficial effect on latency. In principle, high-level features might provide context information and therefore help localise small objects; at the same time, reducing contextual information makes the feature extractor more independent of any specific scenario and therefore maximally flexible. Feature extraction in T-RexNet involves two convolutional paths that process visual-motion mixed data . This tI is a squared input image and T-RexNet associates each element of the feature map  with the dimension/position information and the classification (car/pedestrian/background etc.) of the corresponding anchors. The anchor size is set to Three heterogeneous scenarios formed the test-bench for assessing the performances of T-RexNet, namely, aerial surveillance, civilian surveillance, and fast object tracking. (1)the research community proved the comparison’s effectiveness in object detection and its implementation on embedded devices; the experiments focused on each method’s ability to detect small moving objects;(2)the various methods had been targeted to their specific test scenario, hence comparisons with T-RexNet could highlight the latter’s balance between accuracy and speed.To ensure fair tests, comparisons included methods with the following features:The Aerial-surveillance tests addressed the Wright-Patterson Air Force Base (WPAFB) 2009 dataset, which is a well-established benchmark in Wide-Area-Motion-Imagery (WAMI). Surveillance relies on powerful camera set-ups (and software) to detect and track hundreds of targets, usually people and vehicles, possibly over areas of several squared kilometres. This typically calls for airborne systems. Targets can be so small that motion information is required to distinguish them from the background or noise. Background-subtraction techniques are therefore popular for object detection in this field .The WPAFB dataset holds images taken by an airborne system and focuses on moving vehicles. Each frame roughly includes 315 million pixels and merges the shots by six, partially overlapping, gray-scale camera sensors .The tests presented in this paper involved AOI 1, 2 and 3, as they covered a variety of layouts with different intensities of traffic. The size of each AOI was 2000 × 2000 pixels. The WPAFB dataset gave the position of a vehicle within an AOI by means of the target coordinates, T-RexNet was trained on AOIs 1 and 3, which covered high-intensity and low-intensity traffic situations, respectively. The images were taken from a moving camera, and the test phase involved the remaining set, AOI 2. To ensure fair comparisons with other approaches, time-consecutive images were recorded to support frame differencing. Due to the excessive size of input images (for T-RexNet as well as other object detectors), in compliance with the approach  each 200The CUHK Square dataset  addresseThe quasi-horizontal inclination of the camera affected the depth of the scene and the perspective; as a consequence, people close to the camera appeared much bigger than people on the background. Thus CUHK also allowed to test the effectiveness of T-RexNet in detecting medium-sized objects.At 30 FPS, the slow advance of walking people resulted in minimal changes between time-consecutive frames, hence the input videos were downsampled to 1 Frame-Per-Second (FPS), and the spatial resolution was resized to 512 × 512 pixels. That downsampling factor set the trade-off between the amount of motion data captured and the update frequency of the detections.The experiments only considered valid detections when an IoU exceeded the This setup only included one target object per frame. The example presented in Tennis ball tracking lacks publicly available benchmarks, hence the training set collected 18,220 labeled frames extracted from videos of various matches and recorded at 30 FPS. To avoid overfitting, the test set included 5160 frames taken from three videos taken in different courts and with the camera placed at different heights, as per This scenario aimed to assess the suitability of T-RexNet for fast, real-time detections; in both the training and the test set, the frames were downsampled to 300 × 300 pixels. Only the detected boxes whose center was closer than 16 pixels to the ground truth location were considered as true positives.To allow a fair comparison with other methods in the literature and make the repeatibility of our experiments easier, we first performed our tests on a Desktop PC provided with an NVIDIA GTX 1080 Ti graphic card.Then, to prove the suitability of our method to embedded edge-AI devices, we deployed it on an NVIDIA Jetson Nano , using iUsers can set hardware utilization using a software interface. Two optimized configurations called 5 W and Max-N are available. The first one limits power consumption setting a clock frequency of CPU and GPU to 0.90 and 0.64 GHz, respectively. In addition, two cores of the CPU are turned off. In Max-N configuration all the hardware resources are set to maximize performance, at the expense of power consumption.NVIDIA provides a toolchain based on TensorTRT. This tool provides an optimized implementation of common deep learning layers for Jetson devices. For the case of TF models, the output of TensorTRT is again a TF frozen graph where the computed layers are replaced with optimized versions. TensorTRT can adopt different data sizes when deploying a network: standard floating-point representation (FP32), half-precision floating point (FP16) and 8-bit integer representation (INT8). The experiments were conducted with the FP16 format since this provides a good trade-off between accuracy and power consumption . In addiThe code was developed in Python using the CV2 module and TensorFlow. The computed latency considered only network processing. Each frame was elaborated in real-time when acquired without the use of any batching strategy. The measures involved 100 images. The tests involved two versions of T-RexNet, one with input size 300 × 300 and another with input size 512 × 512. The networks were optimized using tensorRT with FP16 representation. The results measured the average inference time for optimized and non-optimized models, using the Jetson Nano with different power settings and different input sizes.This section illustrates the results of the experiments performed in the three test scenarios. According to our previous findings  we obserT-RexNet outperformed the other comparisons in terms of accuracy, with the exception of ClusterNet , which sThe ROC curves in Experimental outcomes prove that T-RexNet featured a remarkable improvement over State-of-the-Art, application-independent approaches. When considering application-specific solutions, TrackNet  had geneThis section presents the results of the deployment on Jetson Nano. The results reveal that T-RexNet can be deployed in embedded systems with real-time performances. In Max-N configuration, the network can process a frame in 70.28 ms. In other words, the device could elaborate 13 FPS, which is acceptable for many applications. The comparison with native TensorFlow solutions highlights the importance of optimization combined with FP16. A similar observation holds for 5W power mode.pb file, that is the TensorFlow’s ProtoBuf file containing the description of the network, measures around 3.0 MB. The memory strategy implemented on Jetson Nano allocates a large amount of memory that is not directly dependent on the model size. Accordingly, a direct measure would yield biased results. Indeed, literature proves that similar models can be deployed in devices using a smaller memory footprint [Memory requirements for this network are quite limited. The ootprint .The T-RexNet approach involves a deep neural network for the detection of small moving objects. It uses motion data as a discriminant contribution whenever visual-only information is limited due to the small target sizes. The T-RexNet architecture includes a two-path network, while keeping computational costs low. The method’s relevant features consist in limiting computational and memory costs, allowing real-time execution, ensuring reuse in several applications with an end-to-end approach, and yielding remarkable accuracy performances that favourably compare with SoA approaches. T-RexNet was tested in three real-world scenarios covering a wide range of applications. Accuracy results confirmed that the proposed method outperformed most of SoA approaches; conversely, when considering execution speed, T-RexNet improved over the most accurate methods. Tests performed on an NVIDIA Jetson Nano proved that our solution is suitable for deployment on embedded edge devices. In conclusion, we believe T-RexNet can be regarded as an easy-to-use alternative, suitable for embedded to high-end devices, to deal with tiny moving targets.


Anxiety disorder is the most prevalent mental disorder among children and adolescents, causing significant psychosocial problems and physical health conditions. Cognitive behavioral therapy (CBT) is an effective treatment for anxiety disorder in children and adolescents. And parent-only CBT is an alternative treatment for childhood anxiety disorder, which includes psychologists and parents rather than children in the treatment. As a new type of CBT, parent-only CBT has some advantages. However, it remains unclear whether parent-only CBT interventions are effective for treating children and adolescents with anxiety disorder.In this study, we evaluated the efficacy  and acceptability  of parent-only cognitive behavioral therapy (CBT) for children and adolescents with anxiety disorder. We searched electronic databases, including PubMed, Cochrane Library, Embase, Web of Science, ProQuest, and PsycINFO from inception to June 2019. We included randomized controlled trials (RCTs) comparing parent-only CBT either with waitlist (WL), or CBT with parents in children and adolescents with anxiety disorder.p = 0.04), and more remission rate with RR of 4.33  at post-treatment. And our analyses showed no evidence that parent-only CBT had significantly greater efficacy than CBT with parents with SMD of 0.21 . Acceptability in the parent-only CBT group was not significantly different to the WL group with RR of 0.92 , and was significantly worse than in the CBT with parents group with RR of 1.93 .Finally, six RCTs with 407 participants were included in the meta-analyses. In terms of efficacy, pooled analyses indicated that parent-only CBT was significantly more effective than WL for reducing anxiety symptoms with SMD of − 0.72 (95% CI − 1.41 to − 0.03, Current evidence indicates that parent-only CBT can be an alternative and acceptable intervention for treating children and adolescents with anxiety disorder.The online version contains supplementary material available at 10.1186/s12888-020-03021-0. Anxiety disorder is the most prevalent mental disorder among children and adolescents. Internationally, 6.5% of all children and adolescents meet the diagnostic criteria for anxiety disorder at least once in their life . AnxietyCognitive behavioral therapy (CBT) is an effective treatment for childhood anxiety disorder. And parent-only CBT is an alternative treatment for childhood anxiety disorder, which includes psychologists and parents rather than children in the treatment. By previous study, we reported meta-analysis about child-CBT for anxiety disoder and noticed parent-only CBT for children anxiety is an interesting treatment which have unique advantages, especially for young children. So on the basis, we did this research focused on parent-only CBT –10. As oTo respond to these challenges, research into parent-focused interventions for childhood anxiety disorder is increasing. This type of intervention has the potential to avoid the problems mentioned above. However, it remains unclear whether parent-only CBT interventions are effective for treating children and adolescents with anxiety disorder, and previous studies have produced conflicting findings , 16–18. PRISMA guidelines  were useTo determine appropriate studies for our meta-analysis exploring the efficacy and acceptability for treatment of children and adolescents with anxiety disorder, we selected studies according to the following criteria: (1) we included any RCTs investigating the application of parent-only CBT for the treatment of anxiety disorder in children and adolescents, and comparing parenr-only CBT with WL or CBT with parents; (2) we included studies with children and adolescents who were under the age of 18; (3) All participants met a primary diagnosis of a current anxiety disorder, conforming to standardized diagnostic criteria (DSM-IV and K-SADS-PL) –22. to eThe inclusion process was conducted by two independent reviewers (BY and TT). First, the reviewers scanned the abstract and title of potential papers, and identified studies to be read in full text. The final selection of studies was conducted by both reviewers. If there was any disagreement between the two reviewers, another reviewer was consulted to resolve the discrepancy (XZ).The primary outcome of efficacy was the mean change scores of the anxiety rating scale from baseline to post-treatment. When there was more than one available anxiety rating scale in one study, we used the scores from the anxiety rating scale according to a predefined hierarchy , based oThe second efficacy outcome was remission rate measured by the proportion of participants who did not meet the standardized diagnostic criteria for anxiety disorder after treatment.The outcome of acceptability was all-cause discontinuation, defined as the proportion of patients in the treatment group who withdrew from treatment early for any reason.Two independent reviewers (BY and TT) used standardized data extraction forms to extract data of the main characteristics of all trials, and the methodological qualities of trials were also assessed. Standardized data extraction forms included data on study characteristics , intervention details , patients’ characteristics , and outcome measures . The risk of bias among all studies was assessed according to the Cochrane Collaboration Risk of bias tool described in the Cochrane Handbook for Systematic Reviews of Intervention . If therWe compared the relative efficacy and acceptability by performing a meta-analysis using Review Manager 5.3 (The Cochrane Collaboration of The Nordic Cochrane Center in Copenhagen). Because of various anxiety rating scales among included studies, there maybe exist underlying heterogeneity and the difference in the true treatment effect among studies. So the DerSimonian and Laird random-effects models were adopted for all meta-analyses .p-values of the Q statistic and I2 statistic. For the primary outcome of efficacy(parent-only CBT compared with WL), we realized significant heterogeneity. Then we performed sensitivity analysis by excluding the outlier, the study of Cartwright-Hatton (2011) in forest plot Fig. Pooled estimates of standardized mean difference (SMD) were calculated with 95% confidence intervals (CIs) for continuous outcomes. An SMD of more than 0 indicates that the comparison conditions (WL or CBT with parents) were more effective. Conversely, an SMD value of less than 0 indicates that the parent-only CBT condition was more effective. Regarding the risk ratios (RRs), we calculated 95% confidence intervals for discontinuous outcomes. Values of more or less than 1 indicate that the comparison groups or parent-only CBT group more frequently involved events of concern, respectively. Additionally, heterogeneity of both effects among studies was assessed using the To test significant differences in primary efficacy between the different categories of studies, we also performed subgroup analyses. The studies were divided into different categories based on the following factors: male to female ratio (more than 1 or not more than 1), the risk of bias according to the Cochrane Collaboration Risk of bias tool (high bias risk or unclear risk) and the anxiety rating scale , respectively.As for publication bias, we performed Egger’s teston STATA.After searching six electronic databases, we identified 6878 potentially relevant studies. Then, 118 full-text articles were identified for review. Finally, six RCTs with 407 participants were included in our meta-analyses. A flow diagram showing the details of the inclusion and exclusion of studies is presented in Fig. Detailed information about the included studies is presented in Table p = 0.04, 4 studies including 206 patients, Egger’s test P = 0.787) and high heterogeneity  and low heterogeneity  and low heterogeneity  with low heterogeneity  with low heterogeneity  for the parent-only intervention group (4 studies), and 20/114 (17.54%) for the WL group (4 studies). There was no significant difference between the two groups. The RR value was 0.92 , with low heterogeneity, where the effect size greatly changed . Studies with more girls  did not show a greater effect size than WL , but studies with more boys  showed a significant difference between two groups . When we compared parent-only CBT with WL. Studies that included patients measured with other-rated scales  still appeared to be more effective. Studies that recruited patients measured with self-rated measures exhibited no significant differences  between studies with high risk  and unclear risk . We found no significant differences . we found that the children relatively young and MASC was adopted. But MASC was developed for children 8 years and older. The self-rated scale MASC may do not inappropriate to anxiety in young children. For example, the studies (Waters 2009 and Monga 2015) included young children adopted other-rated scale.Interestingly, for the primary outcome of efficacy(parent-only CBT compared with WL), we realized significant heterogeneity. Then we performed sensitivity analysis. We excluded the study of Cartwright-Hatton (2011), which made heterogeneity fromdwon to and Regarding acceptability, we found no significant differences between the parent-only CBT and WL conditions. However, more families tended to drop out of treatment in the parent-only group compared with the CBT with parents group. This result is similar to those of other studies investigating internet-based delivery and bibliotherapy as alternative modes of CBT treatment –37. It iIn the current study, we did not investigate the effects of parent-only CBT in young children and older children, respectively, due to a lack of studies. According to previous studies of CBT with parents in young children , family-The current study involved several limitations that should be considered. First, the sample size was not sufficient to ensure reliable statistical power, particularly in subgroup analyses. In addition, the unsatisfactory quality of some of the included studies limited the reliability of the conclusions, and the studies included in the review exhibited substantial heterogeneity. Therefore, caution is required when interpreting the current findings. Moreover, other types of CBT involving parental participation were not taken into consideration, such as parent-delivered CBT, internet-delivered CBT with parents, and telephone-delivered CBT with parents. We did not investigate the efficacy of parent-only CBT for specific types of anxiety in children. Elucidating these issues will require further investigation. Due to a lack of data in the included studies, we did not examine follow-up assessment results. Resolving this shortcoming will require future studies.Our meta-analysis suggests that parent-only CBT is one of effective interventions for children with anxiety disorder. Although parent-only CBT increased the rate of all-cause discontinuation compared with CBT with parents, it did not lead to more patients dropping out compared with the WL control group. Current evidence indicates that parent-only CBT is both an acceptable and alternative treatment compared with a control condition for children and adolescents with anxiety disorder.Additional file 1: Table S1-S6. Literature search report: Cochrane (613), Embase (386), ProQuest (810), PsycINFO (559), PubMed (1393), Web of Science (3118) and Additional file 2Additional file 2. 112 excluded studies, and the reasons they were excluded.Additional file 3. Data extraction forms.Additional file 4. Graphical overview of the methodological quality of included studies.


Improved insight into the molecular mechanisms of head and neck squamous cell carcinoma (HNSCC) is required to predict prognosis and develop a new therapeutic strategy for targeted genes. The aim of this study is to identify significant genes associated with HNSCC and to further analyze its prognostic significance. In our study, the cancer genome atlas (TCGA) HNSCC database and the gene expression profiles of GSE6631 from the Gene Expression Omnibus (GEO) were used to explore the differential co-expression genes in HNSCC compared with normal tissues. A total of 29 differential co-expression genes were screened out by Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis methods. As suggested in functional annotation analysis using the R clusterProfiler package, these genes were mainly enriched in epidermis development and differentiation , apical plasma membrane and cell-cell junction (cellular component), and enzyme inhibitor activity (molecular function). Furthermore, in a protein-protein interaction (PPI) network containing 21 nodes and 25 edges, the ten hub genes  were identified using the CytoHubba plugin of Cytoscape. The expression of the ten hub genes were all downregulated in HNSCC tissues compared with normal tissues. Based on survival analysis, the lower expression of CSTA was associated with worse overall survival (OS) in patients with HNSCC. Finally, the protein level of CSTA, which was validated by the Human Protein Atlas (HPA) database, was down-regulated consistently with mRNA levels in head and neck cancer samples. In summary, our study demonstrated that a survival-related gene is highly correlated with head and neck cancer development. Thus, CSTA may play important roles in the progression of head and neck cancer and serve as a potential biomarker for future diagnosis and treatment. Head and neck squamous cell carcinoma (HNSCC) is one of most common types of cancer in the world. HNSCC includes several malignancies that originate in the mouth, nasopharynx, oropharynx, hypopharynx, larynx, and neck . AccordiWith the development of genomic technologies, bioinformatics has become increasingly popular for gene expression profiles analysis to study the molecular mechanisms of diseases and discover disease-specific biomarkers . One impIn this study, the mRNA expression data of HNSCC from the TCGA and GEO databases were analyzed by WGCNA and differential gene expression analysis to obtain differential co-expression genes. We further explored HNSCC development through functional enrichment and protein-protein interaction (PPI) analysis combined with survival analysis. The study provides a potential basis to understand the cause and potential molecular events of HNSCC by analyzing differential co-expression genes for clinical diagnosis or treatment.The workflow of the analysis hub gene extraction curation pipeline is shown in We elaborate on each step in the following sub-sections.https://portal.gdc.cancer.gov/) and GEO (https://www.ncbi.nlm.nih.gov/gds). In the TCGA database, all data on HNSCC and corresponding clinical information were freely downloaded by R package TCGAbiolinks , and was transformed into a topological overlap matrix (TOM) as well as the corresponding dissimilarity (1-TOM). Afterwards, a hierarchical clustering dendrogram of the 1-TOM matrix was constructed to classify the similar gene expressions into different gene co-expression modules. To further identify functional modules in a co-expression network, the module-trait associations between modules, and clinical trait information were calculated according to the previous study  provides an integrated solution for differential expression analyses on RNA-Sequencing and microarray data . Genes with the cut-off criteria of |logFC| ≥ 1.0 and adj. P < 0.05 were regarded as DEGs. The DEGs of the TCGA-HNSCC and GSE6631 dataset were visualized as a volcano plot by using the R package ggplot2 , cellular component (CC), and molecular function (MF)—can identify the biological properties of genes and gene sets for all organisms (To explore Gene Ontology (GO) of selected genes, R package clusterProfiler package  was usedrganisms .In our study, we used the STRING  online tool, which is designed for predicting protein–protein interactions (PPI), to construct a PPI network of selected genes . Using tsurvival package in R software to explore the relationship between overall survival (OS) and hub genes in patients. Moreover, the association between disease-free survival (DFS) and hub genes expressed in HNSCC patients was determined using the online tool GEPIA2 . HPA is a valuable database that provides a large amount of transcriptomics and proteomics data in specific human tissues and cells for researchers  from the Human Protein Atlas database .In order to find the functional clusters in HNSCC patients, the gene co-expression networks were constructed from the TCGA-HNSCC and GSE6631 datasets with the GA-HNSCC  and nineGA-HNSCC  were ideP < 0.05, a total of 3,728 DEGs in the TCGA dataset  (P < 0.05)  were screened out by CytoHubba plugin, we verified the expression levels of the hub genes among the patients of the TCGA database. As shown in  package  and the  package  for inve < 0.05) , while w < 0.05) . Further < 0.05) . All theclusterProfiler package, these genes were mainly enriched in epidermis development and differentiation, which are basic processes in cell proliferation. Furthermore, according to MCC scores from the CytoHubba plugin in Cytoscape, the top 10 HNSCC-related genes were screened out  and all their expression patterns were found be downregulated in HNSCC tissues compared with the normal controls. Among them, CSTA downexpression was significantly associated with poor overall survival in head and neck cancers. Finally, survival and immunohistochemical analysis for CSTA was carried out.Head and neck squamous cell carcinomas (HNSCC) are a group of cancers found in several regions, including the mouth, nose, throat, larynx, sinuses, or salivary glands. Although the treatment of head and neck cancer has improved, the prognosis of patients is generally poor due to the lack of precise molecular targets. Therefore, better biomarkers for specific prognosis and progression of HNSCC are demanded. In this study, a total of 29 significant genes with the same expression trends were identified in the TCGA and GSE6631 databases using integrated bioinformatic analysis. As suggested in functional annotation analysis by the CSTA, also known as Cystatin A or stefin A, is a member of the cystatin superfamily. It is an intracellular inhibitor regulating the activities of cystatin proteinase and has an important role in desmosome-mediated cell-cell adhesion , 30. FurAs with all research, our study also had limitations about the classification of tumors to different subtypes. Although we provided a comprehensive bioinformatics analysis to identify potential diagnostic genes between cancer and normal tissues, it may not be very accurate for each patient with HNSCC subtypes. Moreover, the molecular mechanisms involved in the survival-related genes that affected the prognosis of HNSCC patients should be further validated through a series of experiments.In summary, by integrating WGCNA with differential gene expression analysis, our study generated the significant survival-related gene CSTA that has potential for prognosis prediction in HNSCC.https://portal.gdc.cancer.gov/), GEO (https://www.ncbi.nlm.nih.gov/gds), and HPA (https://www.proteinatlas.org/).All available data were analyzed in this study. Those can be found here: TCGA (J-HC, CW, and CL: conceptualization and methodology. CW and J-HC: software and data curation. JT and CL: validation. J-HC and CL: writing—original draft preparation. CW and JT: writing—review, editing, and supervision.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.


Rho = 0.487; 2017 Rho = 0.439 p < 0.05). Distinct regional and gender correlation patterns between age-adjusted DALYs due to MSK and mental disorders were reported. No correlation was reported between DALYs due to MSK and all mental disorders collectively, among Low- or Middle-income countries. However, in High-income countries (HICs), the correlation was strong and consistent between 1990 and 2017 . Conclusions: The reported correlation patterns call for targeted preventive strategies and intervention policies for mental and MSK disorders internationally. Special attention is needed among HICs.Background: The aim of the present study was to use the extensive Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) database from 1990–2017 to evaluate the levels and temporal correlation trends between disability adjusted life years (DALYs) attributed to musculoskeletal (MSK) disorders, all mental disorders collectively and by mental disorder sub-category. Methods: We utilized results of the GBD 2017 to describe the correlation patterns between DALYs due to MSK disorders, mental disorders and other diseases among 195 countries. Mixed model analysis was also applied. Results: A consistent relation was reported between age-adjusted DALYs attributed to MSK and mental disorders  among the 195 countries, in both sexes, for 1990 to 2017 (1990  Recent evidence from 63 different countries has shown that 29% of the population suffer from a mental disorder at least once during their lifetime . Recentlhttps://vizhub.healthdata.org/gbd-compare/). MSK disorders include, among others, low back pain, gout, osteoarthritis and rheumatoid arthritis and are related with a variety of environmental and psychosocial factors . Musculoskeletal impairments and mental disorders are both severe and persistent conditions causing low levels of self-perceived health and quality of life [Mental disorders have been associated with musculoskeletal (MSK) disorders ,3,4,5, w of life ,7. In ad of life ,9. Even  of life , both of of life . Further of life .While MSK and mental disorder burden is analogous to that of cardiovascular diseases, to date, there are no global epidemiological data analyzing the relation among these disorders . SpecifiThus, the aim of the present study was to use the extensive GBD database from 1990 to 2017 to evaluate geographical, socio-demographic and temporal trends of the correlation between MSK and mental disorders. First, we hypothesized that mental and MSK disorders and their subcategories (expressed as age-adjusted DALYs estimates) will be correlated consistently between 1990 and 2017 among 195 countries. Secondly, we hypothesized that this correlation will be different by sex and by country-income levels . In terms of comparisons, the correlation between YLDs due to MSK disorders and other disorders, such as cardiovascular diseases, neoplasms, neurological disorders and injuries is also presented.The GBD is among the few global health studies that apply standard design and procedures across all populations of the world (195 countries). To the best of our knowledge, except for this dataset, there are no other multi-country studies on MSK and mental disorders that allow comparisons by sex and between different settings and/or country-income levels.http://vizhub.healthdata.org/gbd-compare) and for download .GBD 2017 quantified multiple measures of health loss for 359 causes and 84 risk factors for 195 countries and territories, from 1990 to 2017. For the present analysis, we compared all available 195 locations. Our comparisons are primarily for both sexes combined, by males and females and by country-income level. GBD results are available publicly for visualization (The GBD study’s protocol has been approved by the research ethics board at the University of Washington (UW). The GBD shall be conducted in full compliance with UW policies and procedures, as well as applicable federal, state and local laws.https://vizhub.healthdata.org/epi/). Mental and MSK disorders sub-categories were defined based on specific GBD criteria. For example, in GBD, anxiety disorders were classified as all the experiences of intense fear and distress, typically in combination with other physiological symptoms [As presented in symptoms . More insymptoms . Excludesymptoms ,17. The symptoms ,17.http://www.healthdata.org/terms-defined). Annualized rate of change (ARC%) was computed as natural log-transformed  divided by the number of years and was used to compare trends among age-standardized DALYs. No specific ARC threshold was used to classify a negative or positive change. Detailed methods for the overall study and for specific causes and risks are available in GBD 2017 summary publications, [In this study, we used specific GBD metrics. We compared DALYs rates across locations with age-standardization to control for age structure, and correlation analysis was conducted to examine specific interrelations between MSK and mental disorders , the existing GBD model life table system  was used. Using this updated dataset, the LE estimated the life expectancy at birth for the all the available populations .Cause-specific deaths and YLLs were estimated for underlying causes of mortality, ensuring that the sum of all specific causes is equal to all-cause mortality. Each death was assigned to a single cause. Vital registration and census death data were adjusted for incompleteness and misclassification ; non-specific and intermediate codes  were redistributed using age-, sex- and geography-specific statistical redistribution methods prior to modelling. The most commonly used estimation method was cause of death ensemble modelling (CODEm). CODEm uses a train-test-test approach, first testing all combinations of selected country-level covariates and their relationship to in-sample data, then ranking those component models based on out-of-sample predictive validity to construct weighted ensembles. All ensemble models are again ranked on a second round of out-of-sample predictive validity to select a final model. Cause-specific fractions were multiplied by all-cause mortality estimates to calculate cause-specific deaths, then scaled with all other causes to match all-cause mortality. YLLs were calculated by multiplying age-specific deaths by global standard life expectancy at age of death.For this analysis, age-standardized YLLs for MSK disorders and mental disorders, cardiovascular diseases, neoplasms, neurological disorders and injuries were estimated, for all locations, for both sexes combined as well as by males and females and by country-income level. Information on the YLLs due to cardiovascular diseases (CVDs) , neoplasms , neurological disorders  and injuries  definition is available in detail elsewhere ,13.Epidemiologic data from systematic literature review, health surveys, surveillance systems, disease registries and hospital and claims databases were used to generate cause- and sequela-specific prevalence and incidence estimates using a variety of modelling approaches, of which Bayesian meta-regression compartmental modelling in DisMod-MR 2.1 was the most common . DisabilThe disability-adjusted life-years (DALYs) is a summary measure of health that was calculated for each age-sex-year-state-cause strata by summing the fatal (YLL) and nonfatal (YLD) components . DALYs iTo further assess the effects of socioeconomic factors and health system performance on global and regional health metrics, we employed the Socio-demographic Index (SDI) and the Healthcare Access and Quality (HAQ) Index, respectively. SDI is a composite indicator that uses as components the country-level income per capita, average educational attainment among individuals over age 15 and total fertility rate among women under 25. The SDI ranges from 0 to 100 .HAQ Index is a GBD composite metric that is based on comparative mortality rates for health-care-sensitive diseases and standardized to risk exposure level and is meant to quantify the overall performance of health systems. The HAQ Index ranges from 0 to 1 .p-values are based on two-sided tests. p value ≤ 0.05 was considered as significant. We followed previously reported criteria to classify a correlation as weak (0.3≤), moderate (0.4–0.6), and strong (≥0.7)  [Associations, primarily between age-standardized DALYs and YLDs for MSK and mental disorders  and secondarily between MSK disorders and cardiovascular diseases, neoplasms, neurological disorders and injuries (age-standardized DALYs and YLDs), were tested by the Spearman’s rho coefficients. The associations were tested for the years 1990, 1995, 2000, 2005, 2010, 2015 and 2017 among all 195 countries, for both sexes, by males and females and by country-income level based on the World Bank classification (high-income countries (HICs), lower and upper middle-income countries (LMICs), low-income countries (LICs)) . All p-v values) . When a Mixed-effect multilevel linear regression models were carried out to assess whether MDT (outcome) and MSK disorders (independent variable) (as DALYs) were related between 1990 and 2017, after adjustment for various factors. Specifically, the mixed-effect multilevel model  was condCorrelation analyses were performed with the Statistical Package for Social Sciences version 22  and linear mixed model analysis with the R package lme4.Analysis of the ARC% of age-standardized DALYs attributed to mental and MSK disorders, between 1990 and 2017, in both sexes and by country is presented in Rho = 0.487; 2017 Rho = 0.439 p < 0.05). These correlations at 5-year intervals are also available in Rho = 0.548; 2017 Rho = 0.503 p < 0.05), eating disorders , the category of other mental disorders and schizophrenia (p < 0.05) was shown. A weak consistent positive correlation was observed between DALYs attributed to dysthymia and bipolar, autism (p < 0.05) and MSK disorders, while no association was shown with depressive disorders or major depressive disorders (MDD). In addition, a consistent inverse correlation was shown for attention-deficit/hyperactivity disorders and MSK conditions . No association was found between DALYs attributed to MSK disorders and major depressive disorders, conduct disorders, idiopathic developmental intellectual disability or with neoplasms and neurological disorders. Consistent weak to moderate inverse relations were shown between DALYs attributed to musculoskeletal disorders and cardiovascular diseases as well as with injuries.Rho = 0.484; 2017 Rho = 0.541 p < 0.05), osteoarthritis , low back pain (p < 0.05) and the sub-category of gout  was shown.In terms of the sub-categories of MSK disorders, a consistent and moderate positive correlation between DALYs attributed to MDT and rheumatoid arthritis (p < 0.05). Between 1990 and 2017, MSK disorders were inversely related with conduct disorders in females but positively related in males . Moreover, only in males, autism disorders were positively related with MSK disorders (p < 0.05). Similar trends were shown for analyses between MDT, and all subcategories of MSK disorders (p < 0.05).Correlation coefficients between MSK disorders, mental disorders and age standardized DALYs of other health outcomes for 195 countries, in males and females, between 1990 and 2017 are shown in isorders . Correlap < 0.001). In Model II, after adjusting for the abovementioned covariates plus CVDs, neoplasms, neurological disorders and injuries, a similar positive relation between mental and MSK disorders was found  (data shown only in text).In order to further explore whether mental and MSK disorders are related across time and go beyond univariate correlation analysis, a mixed-effect multilevel regression analysis was conducted, adjusting for various factors and taking into account the time effect. Specifically, in Model I, after adjusting for SDI, SDIxHAQ index and time (year), MSK disorders were positively related with mental disorders (MDT) for both sexes . p < 0.05). Schizophrenia was moderately correlated with MSK disorders among LICs but this relation was weak among LMICs and HICs (p < 0.05). No correlation between DALYs due to conduct and MSK disorders was observed among all regions (HICs and LMICs).A comparison by country-income level of the correlation trends between age-standardized DALYs attributed to MSK and mental disorders from 1990 to 2017 helps to identify different regional patterns . It was p < 0.05). However, the rest of the MSK sub-categories  were associated moderately with mental disorders (MDT) only among HICs. No relation was observed among LICs and MICs . The YLDs attributed to mental and MSK disorders correlation coefficients when analyzed by gender and by country-income level showed a stable and consistent pattern comparable with the previous one reported for DALYs.Correlation coefficient trends between age-standardized YLDs attributed to mental and MSK disorders in both sexes by males and females and by country-income level followed similar patterns with the previously presented DALYs . HoweverThe present work analyzed the geographical and temporal burden of mental and MSK disorders and their correlation between 1990 and 2017. We found that 75 countries around the world had concomitant positive ARC% for mental and MSK disorders during 1990–2017. Second, a consistent relation between age-adjusted DALYs attributed to MSK and mental disorders (as reflected by MDT), among the 195 GBD countries, in both sexes, for 1990 to 2017 was shown. This finding was also confirmed when applying mixed models analysis adjusting for various confounders. Anxiety, eating disorders, all mental disorders except anxiety and depressive disorders and other mental disorders had the strongest correlation with MSK disorders, between 1990 and 2017, while no relation was observed with depressive disorders. In addition, MDT was moderately related with rheumatoid arthritis, osteoarthritis, low back pain, neck pain and gout. Third, analysis stratified by gender showed that the aforementioned relations followed similar correlation patterns among males and females between 1990 and 2017. However, DALYs attributed to dysthymia and eating disorders reported higher correlation coefficients with DALYs due to MSK disorders in females. Fourth, when country income was taken into account, there was a clear correlation pattern between DALYs due to MSK disorders and all the categories of mental disorders across HICs. A similar and consistent pattern was shown between DALYs due to MDT and all the categories of MSK disorders, across HICs, while a positive correlation with rheumatoid arthritis was observed across all regions.It is well known that musculoskeletal disorders coexist with chronic conditions  and normAs aforementioned, MSK and mental health have a complex interrelation that can potentially exacerbate or cause the other . The maiAdditional analysis by gender showed similar trends in the correlation patterns between age-adjusted DALYs due to MSK and mental disorders (MDT), although the coefficients were attenuated in males. This could be attributed to the fact that mental disorders  and MSK are more pronounced in females, as has been reported in the literature , but alsSome distinct correlation trends between MSK and mental disorders were found in HICs and LMICs . Interestingly, no relation was evident from 1990 to 2017, between MSK and mental disorders , depressive disorders and MDD in LMICs, while moderate/strong correlations were observed in HICs. Furthermore, although no relation between age-adjusted DALYs due to anxiety and MSK was shown among LICs, moderate positive correlations were found in MICs and strong correlations in HICs. Based on the aforementioned findings, it should be noted that mental and MSK disorders are relatively highly prevalent among HICs , a fact Currently, individuals around the world and mostly among high-income regions are experiencing high burden of disability due to mental and MSK disorders ,13,41, aThe present study has several strengths. To the best of our knowledge, this is the first global study to evaluate the association between age-standardized DALYs attributed to MSK and any mental disorders, as well as by mental and MSK disorder categories using the GBD 2017 platform with standardized data that allow global comparisons of different settings, which has not been done previously. These results could help policy makers develop prevention, intervention and treatment programs for MSK and mental disorders. However, the present analysis shares the limitations of other GBD studies, mostly the challenges of capturing all sources of uncertainty, lags in data availability, variation in coding practices , DALYs construct and other biases and limitations of existing analytical tools, which may not fully capture temporal trends in mortality, incidence and prevalence . MoreoveWe found a consistent and positive association between age-adjusted DALYs of mental and MSK disorders from 1990 to 2017, in 195 countries. Among mental disorder sub-categories, anxiety showed the highest correlation with MSK disorders. This association was more pronounced among females and in HICs. Depressive disorders were related with MSK disorders only among HICs. Among MSK disorders, rheumatoid arthritis was related with MDT across all regions. The gender-dependent and regional correlations call for implementation of context- or population-specific direct and simultaneous preventive policies for both mental and MSK disorders. In particular, addressing these conditions in the context of HICs would be important. Policymakers should consider a health care system where mental and musculoskeletal healthcare services could address patient’s physio-psychosocial aspects jointly.


Genitourinary (GU) cancers are among the most common malignant diseases in men. In the United States, prostate, bladder, and kidney cancers are the first, fourth, and sixth most common cancers in men, respectively . RecentlMSN significantly decreased invasiveness in BC cell lines, suggesting that MSN may be a potential diagnostic marker for cancer invasion in BC. DNA methylation analysis of urine samples has been used for the purpose of detection and surveillance in BC. Hentschel et al. investigated DNA methylation of urine supernatant (cell-free DNA) in comparison with full void urine and urine pellets [FGFR3-mutated, PD-L1-negative tumor, but FGFR3 mutations are rare in mixed LNUC, suggesting a different pathway of tumor development. BC is extremely rare in patients under the age of 20 years; Im et al. studied 29 patients with young-onset bladder cancer (YBC) and found that almost all YBCs were low-grade, noninvasive, papillary tumors [Bladder cancer (BC) is the focus of this Special Issue, with eight articles investigating various biomarkers that may have diagnostic, prognostic, and therapeutic value in BC. Small non-coding RNAs (sncRNAs) in urine have been used as noninvasive biomarkers for BC, but their use in plasma has not yet been well studied. Sabo AA et al. analyzed the expression of sncRNAs in plasma extracellular vesicles (EVs) in BC by next-generation sequencing . They fo pellets . They fo pellets . Pure LNy tumors . Whole-ey tumors . In addiy tumors . De Olivy tumors .Other GU cancers, including prostate and kidney cancers, are also investigated by various researchers in this issue. MRI imaging is a valuable tool that facilitates the selection of clinically significant or high-grade prostate cancer (PC). Roumiguié et al. investigated the respective predictive values of a biomarker-based model MDx-2 as well as clinical variables in upfront MRI image-guided prostate biopsies . They foThis Special Issue presents a diverse body of research that aims to address some urgent issues in the diagnosis, prognosis, and treatment of GU cancers. A number of investigative studies evaluated new biomarkers using innovative in vivo and in intro models, which may have potential value in the management of BCs and PCs. Several researchers updated the new biomarkers in BC and PCs and proposed a new approach to the diagnosis of pediatric renal cancers. We hope this issue will provide a new perspective which will lead to an improved understanding of the complex molecular and genomic mechanisms underlying the oncogenesis and progression of GU cancers.


Aedes aegypti mosquito collected in Aracajú, Sergipe State, Brazil. The coding-complete genome of the PCLV is described in this report.Insect-specific viruses do not replicate in vertebrates. Here, we report the genome sequence of a novel strain of a Phasi Charoen-like virus (PCLV) that was isolated from a wild  Aedes aegypti mosquito collected in Aracajú, Sergipe State, Brazil. The coding-complete genome of the PCLV is described in this report.Insect-specific viruses do not replicate in vertebrates. Here, we report the genome sequence of a novel strain of a Phasi Charoen-like virus (PCLV) that was isolated from a wild  Aedes aegypti mosquito is the main vector of several arboviruses. Although this species can be infected by viruses that circulate among invertebrate and vertebrate hosts, finding an infected wild mosquito is frequently challenging. Studies of the mosquito microbiome using metagenomics led to the discovery of a growing number of insect-specific viruses (ISVs) (The s (ISVs) , 2. ISVss (ISVs) .Bunyaviridae family that was obtained from an A. aegypti mosquito, which was naturally infected by chikungunya virus (CHIKV), as part of a surveillance study of arboviruses in urban mosquitoes , purified (treated with DNase I), and concentrated using the RNA Clean and Concentrator-5 kit . The RNA was subjected to next-generation genomic sequencing. Briefly, paired-end RNA libraries were constructed using the TruSeq stranded total RNA HT sample preparation kit, and sequencing was performed using the Illumina NextSeq platform.Here, we describe the coding-complete genome of a member of the squitoes . To ideneviously . The RNAArchaea and Bacteria , with complete sizes (including coding and noncoding regions) similar to those of the RefSeq PCLV genome and those reported for this virus in the literature . Genomic coverage was recovered for all sites using a map-to-reference strategy  79.15%), followed by the presence of CHIKV (1.99%), as previously reported for the same PCLV-positive mosquito . All of Bacteria . Taxonomstrategy  to D. Ph5%, folloAlthough PCLV has very often been found in other metagenomic studies , 5, 7, w8–MN692603 (segment L), MN692604 (segment M), and MN692605 (segment S). The raw sequencing reads are available in the Sequence Read Archive (SRA) under the accession number PRJNA641154.Genome data for the PCLV isolate C302F have been deposited in GenBank under the accession numbers


Spacecraft formation flying (SFF) in highly elliptical orbit (HEO) has attracted a great deal of attention in many space exploration applications, while precise guidance, navigation, and control (GNC) technology—especially precise ranging—are the basis of success for such SFF missions. In this paper, we introduce a novel K-band microwave ranging (MWR) equipment for the on-orbit verification of submillimeter-level precise ranging technology in future HEO SFF missions. The ranging technique is a synchronous dual one-way ranging (DOWR) microwave phase accumulation system, which achieved a ranging accuracy of tens of microns in the laboratory environment. The detailed design and development process of the MWR equipment are provided, ranging error sources are analyzed, and relative orbit dynamic models for HEO formation scenes are given with real perturbations considered. Moreover, an adaptive Kalman filter algorithm is introduced for SFF relative navigation design, incorporating process noise uncertainty. The performance of SFF relative navigation while using MWR is tested in a hardware-in-the-loop (HIL) simulation system within a high-precision six degrees of freedom (6-DOF) moving platform. The final range estimation errors from MWR using the adaptive filter were less than 35  Spacecraft formation flying (SFF) has attracted a great deal of attention, since it can perform space missions with more reliability, adaptability, and low life-cycle cost, compared with traditional monolithic spacecraft . SeveralWith the development of space technologies in recent decades, scientists have attempted to explore outer space far beyond Earth, which has turned their eyes toward highly elliptical orbit (HEO) SFF technologies. The most famous examples include the Magnetospheric Multiscale mission (MMS) launched by the National Aeronautics and Space Administration (NASA), a Solar Terrestrial Probes mission that studies the Earth’s magnetosphere . The CluThe realization of precise SFF GNC technologies requires the development of actuators, metrologies, and algorithms, where the metrologies system conducts the baseline of GNC, since it provides the direct relative-states measurement between the spacecrafts in formation. Typically, the metrologies system will cover both radio frequency (RF) and optical metrologies. The RF terminal receives signals from other spacecraft, and processes time-of-flight spread-spectrum code and carrier phase that allow for the retrieval of distance and line-of-sight (LOS) measurement with an accuracy of 1 cm (distance) and 1° (LOS). The optical metrologies can be conducted using geometric and interferometric concepts, achieving different ranges and accuracies. Optical position metrology for XEUS is reported as a coarse and fine sensor, which achieves accuracy of tens of microns, with a maximum relative distance of 120 m ,10. The distance ,12.China’s space agency has recently approved an HEO SFF mission, called the Highly Elliptical Formation Flying Demonstration (HEFFD) mission, consisting of two spacecraft for science observation, quite similar to the Proba-3 mission ,14. The In addition to optical metrology, (a) MWR can provide precise ranging results as backup equipment, during the science observation period around apogee; and (b) can avoid sunlight disturbance which occurs in the optical spectrum, for specific space science missions such as solar corona observation.Microwave ranging relies on a carefully designed transceiver antenna with relatively wider main lobe angle of a few degrees, which greatly reduces the burden of the high-precision pointing mechanism used for optical metrology. At the same time, microwave ranging can operate in pseudo-code mode or carrier mode for coarse/precise ranging if necessary, as required by mission control, providing flexible solutions to the GNC system.We have inherited a great deal of microwave ranging technology from existing space experience. MWR has been developed and tested previously, and successfully verified in one LEO formation mission .As an essential supplement to the MWR system, BeiDou III B1C/B2a dual-frequency new-generation navigation signal receive and process technology can be fully tested and verified in HEO formation missions. The B1C/B2a dual-frequency receiver on-board can provide highly precise time synchronization solutions with nanosecond precision, which serves as a time-scale benchmark between formation spacecrafts. Moreover, the receiver can provide precise stand-alone navigation solutions while using a precise orbit determination algorithm.Microwave can also be used for real-time data transmission between spacecraft for original scientific data exchange, differential GPS measurement data transmission for relative navigation, etc.Moreover, a K-band microwave ranging (MWR) payload is developed particularly for this HEO formation mission for the following reasons:This paper focuses on the principle, design, development, and testing of MWR equipment that will be deployed in the HEFFD mission. The following content is organized as follows: Correction of ionospheric influence by dual-frequency measurement during space flight around perigee;Synchronous bidirectional ranging comparison that cancels the long-term instability of the oscillator source; and,Carrier phase measurement by frequency difference to improve the accuracy.MWR measures the biased distance between the antenna phase centers of two satellites through microwave carrier phase accumulation and Doppler drift, and then derives the distance variation and its rate between two satellites. Basically, the whole system is a synchronous dual one-way ranging (DOWR) microwave phase accumulation ranging system . Three ti at time t can be modeled as:i, j, The dual-way phase measurement is defined as the summation of one-way ranging:j to i.Substitute the receiving phase to sending phaseEach phase Dual ranging Subsequently, we haveThe one-way phase measurement of The principle of differential frequency phase measurement is to change the reference signal and measured signal into intermediate frequency (IF), or lower frequency, by mixing the radio frequency (RF) and local frequency, followed by a phase comparison. Because the IF signal entering the phase measurement system is much lower than the RF, the phase period is expanded, which greatly improves the phase measurement accuracy.Carrier phase measurement errors are mainly caused by the following reasons: local oscillator phase noise, system noise, and dynamic stress error.Carrier phase measurement error due to system noiseThe carrier phase measurement error due to system noise can be given as  introduced by the local oscillator’s Allan variance can be given by the following empirical formula:With calculation, the phase measurement errors due to local oscillator Allan variance are Phase measurement error due to dynamic stressDynamic stress error is closely related to the tracking loop order. For three-order PLL, the dynamic stress is given as:Summary of phase measurement errorThe total measurement error while using three-order PLL can be modeled as:K band: Ka band: The MWR system payload has been carefully designed and developed, with the diagram of one spacecraft shown in Currently, MWR system payload prototypes have been developed that consist of two sets of identical equipment, mainly including (a) a K/Ka-band transceiving antenna: a single corrugated horn antenna that transmits–receives K/Ka-band dual-frequency microwave signals; (b) a frequency reference unit: an ultra-stable oscillator (USO) is used as the frequency reference source of the whole system; (c) a K/Ka-band microwave channel: up-converts the reference frequency to transmission carrier frequency (TCF) and down-converts the TCF received from another satellite to a single-carrier signal that completes the amplification process and reception mixing; and (d) a digital signal processing unit: conducts sampling and digital processing of the down-converted K/Ka-band carrier phase signal and BeiDou signal to complete the high-precision carrier phase extraction. Here, we provide a brief introduction of these four components, as:The MWR antenna is composed of a K/Ka dual-frequency corrugated horn and a dual polarization quadrature coupler, as shown in The frequency reference units include an USO and a frequency multiplier, which provides a frequency reference for the microwave channel, signal processing unit of the MWR, and the BeiDou receiver.The USO is achieved by a high-stability/low-phase-noise constant-temperature oscillator design, which includes (1) an oscillator circuit and (2) a temperature control circuit. The oscillator circuit is used in order to realize low phase noise function, and includes the main Pierce oscillator circuit, amplification, a spectrum purity filter, and a power supply circuit. A continuous temperature control circuit is adopted, since it guarantees the best short-term oscillator stability , and then sends it to the digital signal processing unit for carrier phase measurement.The MWR microwave channel consists of an RF module, a local oscillator, and a secondary power supply. (a) The RF module uses a local oscillator signal to convert the 32.7 GHz RF signal to an 600.098 kHz intermediate frequency (IF) signal with a certain gain. The RF module gain can be adjusted by telecontrol command, with gain state parameters telemetry output. (b) The local oscillator uses the input reference signal in order to generate the local oscillator signal for RF module frequency down-conversion. (c) The secondary power provides the required secondary voltage for the RF module, and it controls the ON/OFF switch of the equipment through the telecontrol command, and it provides telemetry information on the switch state.Fundamental wave mixing is adopted for the RF module’s down-conversion, which has the advantages of low frequency conversion loss  and low noise coefficient. Moreover, it can better suppress high-order mixing by-products when a single-balance or double-balance method is used. The central frequency of the fundamental mixing local oscillator signal is chosen as 32.7 GHz, according to the frequency relationship between input and output signals.The digital signal processing unit is the most important in the whole MWR system, since it processes both K/Ka dual-frequency signals and BeiDou dual-frequency navigation signals in high quality. New-generation BeiDou III B1C/B2a navigation signals are chosen, and dual-frequency receiver development is adopted, with the aim of providing high-precision time synchronization between satellites to the less than 0.3 ns that is required by MWR DOWR measurement.In order to ensure the time synchronization accuracy of 0.3 ns that is required by MWR, the dual-frequency navigation receiver is integrated with a K/Ka signal processing hardware platform that shares a unique USO frequency source. The hardware platform includes the MWR measurement processing module, the BeiDou measurement processing module, and the external interface module, as shown in The ADC1 component of the hardware platform, as shown in x: radial, y: in-track and z: cross-track (RIC), with the origin located in the master spacecraft [Unlike the traditional relative orbit motion equation expressed in the directions acecraft ,18, hereacecraft  by variaormed to :(14)η¨=fThe denotations of variables/matrix found in , and areThe formation flying orbit analyzed here, quite similar to that in PROBA-3, is a virtual structure SFF mission that will perform in HEO, which we previously referred to as the HEFFD mission. The HEFFD mission is initially designed as an on-orbit development, verification, and validation platform for multiple task forces. The main objective is to test guidance, navigation, and control (GNC) technology in space flight, especially for accurate ranging metrology units and high-performance propulsion systems that enable fine formation maneuvers.The HEFFD mission orbit design is a trade-off analysis process that considers the requirements of: (a) high altitude during the formation flying stage since it is a low-gravity-gradient environment; (b) simple Sun–Earth geometry when SFF during Solar observation phase; (c) launch capability; and (d) ground station location.Here, we provide the baseline orbit for the HEFFD mission in and the slave spacecraft is supposed to be performing follow-on flight relative to the master spacecraft, with a minimal distance of 10 km around apogee.Some preliminary design parameters of master/slave spacecrafts include: mass: 200 kg/400 kg; reference area: 1.81 m1.2/3.27 ,22.According to According to the relative orbit model (11)–(17), the class of systems considered here is given asThe traditional Kalman filter provides the optimal estimation of states by using a recursive scheme of propagating states and measurement update. The filter optimally blends the prior state and information update through a gain matrix which balances uncertainty in both the measurements and dynamics model.However, for HEO SFF missions, the real relative orbit drifted gradually away from the designed model, as in Here, we use a recursive adaptive algorithm dealing with process noise uncertainty by minimizing a function in real time, which is determined by the difference of residual covariance computed by the filter and residual sequence generated by the filter. The adaptive approach can be summarized as follows:Suppose that we have the predicted state error covariance matrix l system ,24. The l system .Extensive tests of the MWR payload were done in the laboratory environment, conducted in a precise moving platform, as shown in With extensive tests of MWR that were conducted in the 6-DOF platform, the results verified the micron-level high-accuracy specifications that could be applied to real space formation missions in the future. A hardware-in-the-loop (HIL) simulation was conducted, with all of the deployed payloads fixed in the 6-DOF platform, aiming for an in-depth analysis of the relative navigation filter performance using real MWR equipment.When considering the sharp orbit drift during perigee time, mission designers proposed a mature S-band ranging (SBR) equipment, in addition to a BeiDou dual-frequency receiver, as a backup payload for both relative measurement data transfer and TT&C payloads. SBR is a reliable medium-accuracy measurement payload that operates at the amateur frequency of 2450 MHz ± 50 Hz. The ranging accuracy of SBR is 1 mThe platform was precisely installed with transmitting/receiving payloads and antennas of SBR, MWR, and optical equipment, with a guaranteed accuracy of a fixed position deviation within two microns. Some of the parameters used in this simulation were as follows: initial date of simulation: 8 April 2021, 14:15:00 (GMT+08:00), sample time interval: 1 s. The spectral densities of the process noise components Equation , which aClearly, this is not an optimal result for engineering application. The reason for the filter divergence is that the formation dynamic model used in the filter  is not sufficiently accurate for the prediction of states through recursive calculation at each sampling time. The process noise values of However, centimeter-level ranging accuracy is not sufficient for the real HEFFD mission. The black lines in In this study, we presented a novel submillimeter-level accuracy K-band microwave ranging (MWR) payload, used for the on-orbit demonstration of precise ranging technology for a future HEO SFF mission, which we have named the highly elliptical formation flying demonstration (HEFFD) mission. The MWR uses DOWR microwave phase accumulation, and details on the development of MWR are introduced, including a K/Ka-band dual-frequency corrugated horn antenna, frequency reference unit, microwave channel, and signal processing platform. Relative orbit models with perturbations and an improved adaptive filter algorithm that incorporates process noise uncertainty are presented, and are used for the SFF relative navigation system design.The MWR equipment was tested in two stages: an assessment of the ranging accuracy, and an HIL simulation within the SFF GNC system. First, the MWR payload was fixed in a high-precision 6-DOF moving platform and extensively tested under a relative velocity of 5


Self-isolation/quarantine was associated with higher depressive and anxiety symptoms compared to social distancing (p < 0.001). Maintaining and enhancing physical activity participation and limiting screen time increases during abrupt societal changes may mitigate the mental health consequences.The COVID-19 pandemic altered many facets of life. We aimed to evaluate the impact of COVID-19-related public health guidelines on physical activity (PA), sedentary behavior, mental health, and their interrelations. Cross-sectional data were collected from 3052 US adults 3–8 April 2020 . Participants self-reported pre- and post-COVID-19 levels of moderate and vigorous PA, sitting, and screen time. Currently-followed public health guidelines, stress, loneliness, positive mental health (PMH), social connectedness, and depressive and anxiety symptoms were self-reported. Participants were grouped by meeting US PA guidelines, reporting ≥8 h/day of sitting, or ≥8 h/day of screen time, pre- and post-COVID-19. Overall, 62% of participants were female, with age ranging from 18–24 (16.6% of sample) to 75+ (9.3%). Self-reported PA was lower post-COVID among participants reporting being previously active  but largely unchanged among previously inactive participants . No longer meeting PA guidelines and increased screen time were associated with worse depression, loneliness, stress, and PMH ( The novel coronavirus COVID-19) has rapidly altered many facets of life globally. In the US, all 50 states and the federal government had made emergency declarations by 16 March 2020. In response to this global pandemic, governments have introduced diverse measures ) and increase in sitting (g = 0.698 [0.526 to 0.869]) and screen time (g = 0.653 [0.482 to 0.823]). Among those with stay-at-home and social distancing restrictions, changes in physical activity , sitting time , and screen time  were comparable.Among active participants pre-COVID-19 restrictions, those in social isolation showed the largest  drop in physical activity (g = 0.565 [0.393 to 0.735]) and screen time (g = 0.589 [0.417 to 0.760]). Among those with stay-at-home and social distancing restrictions, changes in sitting  and screen time  were comparable. In contrast to the active participants, no change in physical activity was observed in the previously inactive participants .Among inactive participants pre-COVID-19 restrictions, those in social isolation also self- reported the largest and clinically meaningful increases in sitting (p < 0.001), loneliness , and stress , and lower PMH . Those who maintained low physical activity levels had lower levels of social network  and PMH  and higher levels of stress .Associations between changes in physical activity, sitting time, and screen time pre-/post- COVID-19 related public health restrictions and mental health outcomes in the total population are presented in p < 0.001), loneliness , and stress , and lower PMH . Sitting time was not significantly associated with any outcome.Results were similar for screen time. Compared to those who maintained screen time <8 h/day , those who increased had higher depressive symptoms  and anxiety symptoms  large reductions of physical activity and increases in sedentary time across the population and particularly among previously physically active and self-isolated/quarantined individuals; (2) consistent associations between reductions in physical activity and increases in screen time with higher negative mental health and lower positive mental health; and, (3) more severe anxiety and depressive symptoms for those in self-isolation compared to less restrictive situations, which were not moderated by changes in physical activity or sedentary behavior. Some models suggest persistent physical distancing may be required for three months, and possibly for eighteen months, to mitigate the peak effects of COVID-19 on health systems . Recent Participants who met the physical activity guidelines prior to COVID-19-related restrictions decreased their physical activity by 32%, on average, with those in self-isolation reported the greatest decrease of 43%. The magnitude of changes in physical activity and screen time found here are potentially meaningful based on a commonly utilized important difference of 0.5 standard deviation unit . UnsurprPhysical activity has well-established inverse associations with anxiety and depressive symptoms ,11,12,29The lack of behavior by public health restriction interactions on mental health was not unexpected. This indicates that the way that people’s behavior changed did not significantly alter the association of public health restrictions with mental health. It is possible that self-isolation/quarantine was associated with consistently lower mental health regardless of behavior changes, or that the effects of self-isolation/quarantine on sitting, screen or active time were consistent enough across people so that potential interactions were not found. Overall, the associations between mental health and changing physical activity and screen time underline the importance of these behaviors regardless of the specific public health restrictions that are in place.Much past research has conceptualized mental health based on the presence/absence of negative symptoms ; the positive mental health benefits of physical activity are currently understudied. A recent study of 5090 Finnish adults reported that physical inactivity overall  and long screen time at home, were associated with higher odds of low positive mental health . The preSimilarly, substantial increases in sitting and screen time were observed. Evidence regarding the mental health impacts of sitting and screen time is mixed, and the effects of such large, acute increases in sedentary behaviors are unknown. Presently, participants who increased their screen time reported higher negative mental health and lower positive mental health across almost all evaluated dimensions compared to those who maintained lower levels. However, no associations between sitting time and mental health were observed. It is plausible that the differing mental health effects of mentally-active and mentally-passive sedentary behaviors explain this distinction. In a cohort of 24,000 Swedish adults, substituting mentally-active sedentary behavior for mentally-passive behavior was associated with a reduced risk of developing major depression over thirteen years . Screen These findings should be considered in the context of their strengths and limitations. Strengths include data on physical activity and sedentary behavior pre- and post-COVID-19 public health restrictions, evaluation of both physical activity and sedentary behavior, and the use of well- validated measures of mental health in a large sample of US males and females across broad age demographics. Nonetheless, the cross-sectional design precludes inference of causality and the sample is predominantly well-educated and white. In particular, as this study sample is not representative of the entire US population, generalizations should be limited based on the sample characteristics. All behaviors and currently followed public health guidelines were self-reported and included a recall of pre-COVID-19 activity, which is potentially subject to misreporting. The self- selection and convenience sampling of participants to complete the survey may also affect the results, although a >70% completion rate for those who began the survey is high. Further, while it was expected that certain demographic factors  were associated with mental health, the influence of changing employment status should be further explored. Finally, how these behaviors change across time and the prospective relationships between health behaviors and mental health are of public health interest, but the current cross-sectional and retrospective design preclude their evaluation.The current findings strongly support the mental health benefits of implementing measures that promote physical activity while limiting screen time during periods of societal modification due to a pandemic. Potentially effective methods to do so may be through enhanced telehealth or public broadcasting time devoted to promotion/implementation of home-based physical activity. Future research should replicate these findings in other large samples, investigate potential cross-national differences, longitudinally assess dynamic relationships between these factors, and integrate device- based measures.