Miracle-dz/UniFAR-FTUs huggingface dataset:
Is Digital Treatment the Holy Grail? Literature Review on Computerized and Blended Treatment for Depressive Disorders in Youth

Computerized and blended treatments seem to be an attractive treatment for adolescents as an alternative to face-to-face treatment, but mental health professionals seem hesitant to use these treatment modalities. This review provides an overview of factors contributing to and withholding from using computerized or blended treatment in routine care. Three databases were searched with terms related to (1) adolescents, (2) depression, (3) computerized or blended, and (4) treatment. Of the 33 articles identified, 10 focused on unguided computerized treatments, six on guided, two on blended, two compared unguided, blended- and face-to-face treatment to no treatment, and eight studies on games. Further, two articles that were focused on an online monitoring tool and three on intervention characteristics or preferred modes of help-seeking. Evidence for effectiveness, adherence, drop-out, and forming therapeutic relations were suspected to be barriers, but are no reason to reject computerized or blended treatment. Improvement in mental health literacy and the possibility to tailor the intervention are facilitators. However, adolescents’ intention to seek help, acceptability of computerized treatment, symptom severity, time spent by therapist, and other facilities are identified as barriers and they need to be taken into account when using computerized or blended interventions. Nevertheless, computerized and blended are promising treatments for depressed youth.
One View Per City for Buildings Segmentation in Remote-Sensing Images via Fully Convolutional Networks: A Proof-of-Concept Study

The segmentation of buildings in remote-sensing (RS) images plays an important role in monitoring landscape changes. Quantification of these changes can be used to balance economic and environmental benefits and most importantly, to support the sustainable urban development. Deep learning has been upgrading the techniques for RS image analysis. However, it requires a large-scale data set for hyper-parameter optimization. To address this issue, the concept of “one view per city” is proposed and it explores the use of one RS image for parameter settings with the purpose of handling the rest images of the same city by the trained model. The proposal of this concept comes from the observation that buildings of a same city in single-source RS images demonstrate similar intensity distributions. To verify the feasibility, a proof-of-concept study is conducted and five fully convolutional networks are evaluated on five cities in the Inria Aerial Image Labeling database. Experimental results suggest that the concept can be explored to decrease the number of images for model training and it enables us to achieve competitive performance in buildings segmentation with decreased time consumption. Based on model optimization and universal image representation, it is full of potential to improve the segmentation performance, to enhance the generalization capacity, and to extend the application of the concept in RS image analysis.
A Multi-Scale Spatial-Temporal Attention Model for Person Re-Identification in Videos

In this paper, we propose a novel deep neural network based attention model to learn the representative local regions from a video sequence for person re-identification. Specifically, we propose a multi-scale spatial-temporal attention (MSTA) model to measure the regions of each frame in different scales from the perspective of whole video sequence. Compared to traditional temporal attention models, MSTA focuses on exploiting the importance of local regions of each frame to the whole video representation in both spatial and temporal domains. A new training strategy is designed for the proposed model by incorporating the image-to-image mode with the video-to-video mode. Extensive experiments on benchmark datasets demonstrate the superiority of the proposed model over state-of-the-art methods.
Experimental and Prediction Study of Displacement-Rate Effects on Flexural Behaviour in Nano and Micro TiO2 Particles-Epoxy Resin Composites

Epoxy resin composites with different weight fractions of TiO2 microparticles (1%, 5%, 10%, 15%, 20%) and of TiO2 nanoparticles (0.5%, 1%, 2%, 3%) were prepared. The particle size of the nanoparticles was averaged around 21 nm while the particle size of the micro TiO2 particles was averaged around 0.2 μm. The morphology of the manufactured particulate composites was studied by means of scanning electron microscopy (SEM). The mechanical properties of both nanocomposites (21 nm) and microcomposites (0.2 μm) were investigated and compared through flexural testing. Furthermore, the effect of displacement-rate on the viscoelastic behavior of composite materials was investigated. The flexural tests were carried out at different filler weight fractions and different displacement-rates (0.5, 5, 10, 50 mm/min). The influence of TiO2 micro- and nanoparticles on the mechanical response of the manufactured composites was studied. For micro TiO2 composites, a maximum increase in flexural modulus on the order of 23% was achieved, while, in the nanocomposites, plastification of the epoxy matrix due to the presence of TiO2 nanoparticles was observed. Both behaviors were predicted by the Property Prediction Model (PPM), and a fair agreement between experimental results and theoretical predictions was observed.
Fingerprint Identification With Shallow Multifeature View Classifier

This article presents an efficient fingerprint identification system that implements an initial classification for search-space reduction followed by minutiae neighbor-based feature encoding and matching. The current state-of-the-art fingerprint classification methods use a deep convolutional neural network (DCNN) to assign confidence for the classification prediction, and based on this prediction, the input fingerprint is matched with only the subset of the database that belongs to the predicted class. It can be observed for the DCNNs that as the architectures deepen, the farthest layers of the network learn more abstract information from the input images that result in higher prediction accuracies. However, the downside is that the DCNNs are data hungry and require lots of annotated (labeled) data to learn generalized network parameters for deeper layers. In this article, a shallow multifeature view CNN (SMV-CNN) fingerprint classifier is proposed that extracts: 1) fine-grained features from the input image and 2) abstract features from explicitly derived representations obtained from the input image. The multifeature views are fed to a fully connected neural network (NN) to compute a global classification prediction. The classification results show that the SMV-CNN demonstrated an improvement of 2.8% when compared to baseline CNN consisting of a single grayscale view on an open-source database. Moreover, in comparison with the state-of-the-art residual network (ResNet-50) image classification model, the proposed method performs comparably while being less complex and more efficient during training. The result of classification-based fingerprint identification has shown that the search space is reduced by over 50% without degradation of identification accuracies.
Sexual Dimorphism and Breed Characterization of Creole Hens through Biometric Canonical Discriminant Analysis across Ecuadorian Agroecological Areas

Simple Summary The first step towards the protection and valorization of the genetic resources of a country is their definition. Although Ecuadorian zootechnical species are very diverse, they are scarcely characterized, and hence the efforts towards their protection are not as fruitful as they could be. The present paper approaches the biometric characterization of the Creole hen population in Ecuador through the study of sexual dimorphism and the differentiation of an agroecologically-based structured population using fourteen zoometric measures as differentiation criteria. Highlands region provinces of Cotopaxi and Tungurahua were the most zoometrically distant from the rest. However, Morona Santiago province population in the Amazonian region slightly differs from those in Guayas, Chimborazo and Bolívar in the Coastal and Highlands regions, respectively. The dual-purpose nature of Ecuadorian Creole hen resources enables the implementation of breeding programs that seek meeting a wider scope of public demands, through the definition of the agroecologically-based breed differentiated production of local hen eggs and meat. Abstract Despite Ecuador having a wide biodiversity of zootechnical species, characterization studies of these genetic resources are scarce. The objective of this research was to perform the biometric characterization of the Creole hen population through 14 quantitative zoometric measures. We evaluated 207 hens and 37 roosters from Ecuador’s three agro-ecological regions: the Sierra (highlands) region (Bolivar, Chimborazo, Tungurahua and Cotopaxi provinces); the Costa (coastal) region (Guayas); and the Oriente Amazonian region (Morona Santiago). Sexual dimorphism was assessed using one-way analysis of variance (ANOVA). Body dimensions were generally significantly higher for males (p < 0.05), especially for length of head, beak, neck, dorsum, tarsus, thigh, leg, and middle finger. Then, individuals were biometrically clustered into populations after a stepwise canonical discriminant analysis (CDA) computing interpopulation Mahalanobis distances. Agroecologically-based structured populations were identified when zoometrical criteria were used to classify the animals. Cotopaxi and Tungurahua provinces were reported to be the most distant from the rest, with a slight differentiation of the Morona Santiago province population from those in Guayas, Chimborazo and Bolívar. Conclusively, Ecuadorian Creole hens were higher than longer contrasting light hen breeds, which favors their dual-purpose aptitude. Hence, the development of selection programs aimed at Ecuadorian differentiated entity of production of eggs and meat across agro-ecological areas is feasible.
The impact of home‐based pulmonary rehabilitation on people with mild chronic obstructive pulmonary disease: A randomised controlled trial

People with mild chronic obstructive pulmonary disease (COPD) experience exercise intolerance, dyspnoea and poor quality of life. However, the role of pulmonary rehabilitation (PR) in this group is unclear. Objectives: This randomised controlled trial aimed to explore the effects of home‐based PR in people with mild COPD.
The current use of telehealth in ALS care and the barriers to and facilitators of implementation: a systematic review

Abstract Objective: We aimed to provide an overview of telehealth used in the care for patients with amyotrophic lateral sclerosis (ALS), and identify the barriers to and facilitators of its implementation. Methods: We searched Pubmed and Embase to identify relevant articles. Full-text articles with original research reporting on the use of telehealth in ALS care, were included. Data were synthesized using the Consolidation Framework for Implementation Research. Two authors independently screened articles based on the inclusion criteria. Results: Sixteen articles were included that investigated three types of telehealth: Videoconferencing, home-based self-monitoring and remote NIV monitoring. Telehealth was mainly used by patients with respiratory impairment and focused on monitoring respiratory function. Facilitators for telehealth implementation were a positive attitude of patients (and caregivers) toward telehealth and the provision of training and ongoing support. Healthcare professionals were more likely to have a negative attitude toward telehealth, due to the lack of personal evaluation/contact and technical issues; this was a known barrier. Other important barriers to telehealth were lack of reimbursement and cost-effectiveness analyses. Barriers and facilitators identified in this review correspond to known determinants found in other healthcare settings. Conclusions: Our findings show that telehealth in ALS care is well-received by patients and their caregivers. Healthcare professionals, however, show mixed experiences and perceive barriers to telehealth use. Challenges related to finance and legislation may hinder telehealth implementation in ALS care. Future research should report the barriers and facilitators of implementation and determine the cost-effectiveness of telehealth.
Development of a Smartphone-Based Balance Assessment System for Subjects with Stroke

Stroke is a cerebral artery disease that negatively affects activities of daily living (ADLs) and quality of life (QoL). Smartphones have demonstrated strong potential in assessing balance performance. However, such smartphone-based tools have thus far not been applied to stroke survivors. The purpose of this study was to develop a smartphone-based balance assessment system for subjects who have experienced strokes and evaluate the system feasibility. The smartphone-based balance assessment application was developed with Android Studio, and reliability and validity tests were conducted. The smartphone was used to record data using a built-in accelerometer and gyroscope, and increased changes represented greater instability. Six postures were tested for 30 s each. Ten healthy adults were recruited in the reliability test, and the intraclass correlation coefficient (ICC) was used to analyze the within-day and between-day reliabilities. Eight subjects with chronic stroke and eight healthy adults were recruited for the validity test, in which balance performance was compared to represent the application validity. The ICC values of the reliability tests were at least 0.76 (p = 0.00). The acceleration data exhibited no difference between individuals who have experienced stroke and healthy subjects; however, all six postures were found to differ significantly between the two groups in the gyroscope data. The study demonstrates that the smartphone application provides a convenient, reliable, and valid tool for the balance assessments of subjects who have experienced chronic stroke.
Prevalence of Salmonella by Serological and Direct Detection Methods in Piglets from Inconspicuous, Conspicuous, and Vaccinated Sow Herds

Simple Summary Salmonella is one of the most important bacterial zoonotic pathogens worldwide that can lead to infections in humans, particularly through the consumption of contaminated food. The percentage of diarrhoeal diseases attributable to the consumption of pork products has risen in recent years, whereas cases associated with poultry meat have considerably decreased. In the present study, the Salmonella prevalence on piglet-producing farms was determined on the basis of environmental samples and blood samples on 24 pig farms previously classified as Salmonella-inconspicuous (SI) and Salmonella-conspicuous (SC). In addition, the effects of sow vaccination against Salmonella prevalence in piglets on SC farms were investigated. The evaluation confirmed the previous classification into SC and SI farms—SC-farms showed significantly higher Salmonella prevalence in environmental samples and significantly higher OD% values in blood samples from piglets. Furthermore, vaccination of sows on SC farms was accompanied by the highest Salmonella prevalence in the environment, and by the highest antibody titer values in piglets, and therefore cannot influence the Salmonella prevalence solely at the farm level. Abstract Due to the zoonotic potential of Salmonella, the high prevalence of Salmonella on pig farms deserves particular attention. Because there is limited precise data on piglet-producing farms, this survey evaluated the Salmonella status of 24 different pig farms that had previously been divided into 12 Salmonella-conspicuous (SC) and 12 Salmonella-inconspicuous (SI) farms on the basis of the serological status of their piglets (25 kg). The evaluation was based on 498 environmental samples and 2641 blood samples, as well as on a biosecurity screening. SC farms were subdivided into farms with sow vaccination against Salmonella (n = 3) and those without vaccination (n = 9). In accordance with the previous classification, both the highest Salmonella prevalence in the environment and the highest antibody titers of the examined piglets were determined on SC farms at both defined time points. Piglets from vaccinated sows showed the highest OD% values, before and after vaccination. On SC farms, most Salmonella-positive samples could be obtained in rearing areas (2017: 40.8%, 2019: 26.0%). The results of this study indicate that sow vaccination alone cannot influence Salmonella prevalence at the farm level. Above all, general infection pressure seems to play a major role for Salmonella prevalence in the environment and for high OD% values of related pigs.
Pretreatment with Yeast-Derived Complex Dietary Polysaccharides Suppresses Gut Inflammation, Alters the Microbiota Composition, and Increases Immune Regulatory Short-Chain Fatty Acid Production in C57BL/6 Mice.

BACKGROUND β-Glucans (BGs), a group of complex dietary polysaccharides (CDPs), are available as dietary supplements. However, the effects of orally administered highly purified BGs on gut inflammation are largely unknown. OBJECTIVES The aim of this study was to investigate the impact of orally administering highly purified, yeast-derived BG (YBG; β-1,3/1,6-d-glucan) on susceptibility to colitis. METHODS Eight-week-old C57BL/6 (B6) mice were used in a series of experiments. Experiment (Expt) 1: male and female mice were treated every day, for 40 d, with saline (control) or 250 μg YBG, followed by 2.5% (wt:vol) dextran sulfate sodium (DSS) in drinking water during days 30-35; and colitis severity and intestinal immune phenotype were determined. Expt 2: female B6 mice were treated with saline or YBG for 30 d and intestinal immune phenotype, gut microbiota composition, and fecal SCFA concentrations were determined. Expt 3: female B6 mice were treated as in Expt 2, given drinking water with or without antibiotics [Abx; ampicillin (1 g/L), vancomycin (0.5 g/L), neomycin (1 g/L), and metronidazole (1 g/L)] during days 16-30, and gut immune phenotype and fecal SCFA concentrations were determined. Expt 4: female B6 Foxp3-green fluorescent protein (-GFP) reporter mice were treated as in Expt 3, and intestinal T-regulatory cell (Treg) frequencies and immune phenotypes were determined. Expt 5: female mice were treated as in Expt 1, given drinking water with or without antibiotics during days 16-40, and colitis severity and intestinal cytokine production were determined. RESULTS Compared with controls, the YBG group in Expt 1 exhibited suppressive effects on features of colitis, such as loss of body weight (by 47%; P < 0.001), shortening of colon (by 24%; P = 0.016), and histopathology severity score (by 45%; P = 0.01). The YBG group of Expt 2 showed a shift in the abundance of gut microbiota towards Bacteroides (by 16%; P = 0.049) and Verrucomicrobia (mean ± SD: control = 7.8 ± 0.44 vs. YBG = 21.0 ± 9.6%) and a reduction in Firmicutes (by 66%; P < 0.001). The YBG group also showed significantly higher concentrations of fecal SCFAs such as acetic (by 37%; P = 0.016), propionic (by 47%; P = 0.026), and butyric (by 57%; P = 0.013) acids. Compared with controls, the YBG group of Expt 2 showed higher frequencies of Tregs (by 32%; P = 0.043) in the gut mucosa. Depletion of gut microbiota in the YBG group of mice caused diminished fecal SCFA concentrations (Expt 3) and intestinal Treg frequencies (Expt 4). Compared with the YBG group, the YBG-(Abx) group of Expt 5 showed aggravated colitis features including loss of body weight (by >100%; P < 0.01) and colonic inflammation score (by 42%; P = 0.04). CONCLUSIONS Studies using B6 mice show that dietary BGs are beneficial for promoting intestinal health when the gut microbiota is intact. However, these CDPs may produce adverse effects if gut microbiota is compromised.
Dose Intensity/Body Surface Area Ratio is a Novel Marker Useful for Predicting Response to Lenvatinib against Hepatocellular Carcinoma

Lenvatinib was recently approved as a novel first-line molecular targeted agent (MTA) for treating hepatocellular carcinoma (HCC). The importance of relative dose intensity (RDI) has been shown in the treatment of various types of cancers. However, RDI may not accurately reflect the treatment intensity of lenvatinib, as it is the first oral MTA where the dose is based on the patient’s weight. We aimed to evaluate the utility of 2M-DBR (the delivered dose intensity/body surface area ratio at 60 days) by comparing the relationship between 2M-DBR, 2M-RDI (RDI at 60 days), and the therapeutic response. The therapeutic response to lenvatinib was evaluated in 45 patients who underwent computed tomography 8–12 weeks after treatment initiation. We also investigated the clinical factors associated with high 2M-DBR. The area under the receiver operating characteristic of 2M-DBR that predicts the response to lenvatinib was higher than that of 2M-RDI (0.8004 vs. 0.7778). Patients with high 2M-DBR achieved significantly better objective responses and disease control rates than those with low 2M-DBR (p < 0.0001 and 0.0008). Patients with high 2M-DBR experienced significantly longer progression-free survival (PFS) than those with low 2M-DBR (p = 0.0001), while there was no significant correlation between 2M-RDI levels and PFS (p = 0.2198). Patients who achieved higher levels of 2M-DBR had a significantly better modified ALBI grade (p = 0.0437), better CONUT score (p = 0.0222), and higher BTR (p = 0.0281). Multivariate analysis revealed that high 2M-DBR was the only significant factor associated with longer PFS. In conclusion, 2M-DBR could be an important factor that reflects treatment intensity and useful for predicting the response to lenvatinib against HCC, instead of 2M-RDI.
MicroRNA-506 Is Involved in Regulation of the Occurrence of Lipopolysaccharides (LPS)-Induced Pulpitis by Sirtuin 1 (SIRT1)

Background Toothache often occurs with pulpitis. Lipopolysaccharide (LPS) is produced by gram-negative bacteria, and its accumulation is related to clinical symptoms of pain. MicroRNAs (miRNAs) display anti-inflammatory potential due to their direct regulation of cellular protein expression, which can promote inflammatory changes in dental pulp tissues. However, the mechanism of LPS-induced pulpitis is still unclear. Material/Methods In this study, dental pulp stem cells (DPSCs) were separated and cultured from rat dental pulp tissues; then, LPS was administered to induce inflammation and activate the TLR4 pathway. Results It was found that miR-506 was upregulated following LPS treatment in DPSCs. The inhibition of miR-506 in LPS-treated DPSCs led to attenuated inflammation and deactivation of the TLR4 pathway. Furthermore, the bioinformatic analysis and dual-luciferase reporter gene assay indicated that miR-506 could target the 3′-UTR of sirtuin 1 (SIRT1). Additionally, SIRT1 decreased in LPS-treated DPSCs, and miR-506 transfection resulted in SIRT1 upregulation. SIRT1 overexpression showed a similar inhibitory effect as that of miR-506 downregulation on inflammation and TLR4 activation in DPSCs. Conclusions In brief, miR-506 can protect dental pulp in LPS-induced inflammation by inhibiting the SIRT1-mediated TLR4 pathway.
TRPS1 acts as a context-dependent regulator of mammary epithelial cell growth/differentiation and breast cancer development

In this study, Cornelissen et al. set out to elucidate the role of the GATA-type zinc finger transcription factor TRPS1 in breast cancer. Using in vitro and in vivo loss-of-function approaches, the authors demonstrate that TRPS1 can function as a context-dependent tumor suppressor in breast cancer, while being essential for growth and differentiation of normal mammary epithelial cells.