Miracle-dz/UniFAR-FTUs huggingface dataset:
Is Mate Preference Recognizable Based on Electroencephalogram Signals? Machine Learning Applied to Initial Romantic Attraction

Initial romantic attraction (IRA) refers to a series of positive reactions toward potential ideal partners based on individual preferences; its evolutionary value lies in facilitating mate selection. Although the EEG activities associated with IRA have been preliminarily understood; however, it remains unclear whether IRA can be recognized based on EEG activity. To clarify this, we simulated a dating platform similar to Tinder. Participants were asked to imagine that they were using the simulated dating platform to choose the ideal potential partner. Their brain electrical signals were recorded as they viewed photos of each potential partner and simultaneously assessed their initial romantic attraction in that potential partner through self-reported scale responses. Thereafter, the preprocessed EEG signals were decomposed into power-related features of different frequency bands using a wavelet transform approach. In addition to the power spectral features, feature extraction also accounted for the physiological parameters related to hemispheric asymmetries. Classification was performed by employing a random forest classifier, and the signals were divided into two categories: IRA engendered and IRA un-engendered. Based on the results of the 10-fold cross-validation, the best classification accuracy 85.2% (SD = 0.02) was achieved using feature vectors, mainly including the asymmetry features in alpha (8–13 Hz), beta (13–30 Hz), and theta (4–8 Hz) rhythms. The results of this study provide early evidence for EEG-based mate preference recognition and pave the way for the development of EEG-based romantic-matching systems.
Comparing Adherence of Continuous and Automatic Positive Airway Pressure (CPAP and APAP) in Obstructive Sleep Apnea (OSA) Children

Objectives The treatment outcomes of pediatric obstructive sleep apnea (OSA) are affected by positive airway pressure (PAP) therapy adherence, which may be affected by the type of device used. Continuous PAP (CPAP) devices deliver a continuous and fixed air pressure level, whereas automatic PAP (APAP) devices automatically adjust the pressure to meet changing needs during sleep. The adherence, tolerance and consistency of OSA-children's use of CPAP and APAP devices were compared. Study design One-year, observational cohort study. Methods Twenty-seven OSA-children were enrolled. Fourteen (52%) used CPAP, and 13 (48%) used APAP. The adherence, tolerance, and consistency of the PAP usage by the two groups were compared. Results Overall, 11 of the 27 children (41%) showed good PAP adherence. The CPAP patients averaged 4.9 h of device usage on the days used, for 60% of days, with 6 of 14 (43%) demonstrating good adherence. In comparison, the APAP patients averaged 3.2 h for 55% of days, with 5 of 13 (38%) exhibiting good adherence. The 2 groups showed no differences in their adherence, tolerance, or consistency of device usage (P values, 0.816, 0.609, and 0.720, respectively). Although the adherence of both groups improved in the second 6 months, it was without statistical significance (P values, 0.400 and 0.724). Age, sex, baseline apnea-hypopnea index, comorbidities, prescribed period, device type, mask type, and caregiver education-level were not risk factors for poor PAP adherence. Conclusions No differences in the adherence, tolerance, or consistency of the children's use of CPAP and APAP were revealed in this small inhomogeneous cohort study with limited resources.
Anxiety, Depression, and Stress Are Associated With Internet Gaming Disorder During COVID-19: Fear of Missing Out as a Mediator

Background Many teenagers suffered negative emotional states, especially anxiety and depression, during the COVID-19 outbreak, and most teenagers choose Internet games to cope with negative emotion. Previous evidence indicated that fear of missing out is related with anxiety and depression in teenagers with Internet gaming disorder, but it is unclear how fear of missing out influences depression, anxiety, or stress. Methods Based on an I-PACE model, using Depression, Anxiety, Stress Scale (DASS-21), Fear of Missing Out Scale, and Internet Gaming Addiction Scale, and 324 middle school students as participants, this study explored the mediating effect of fear of missing out on depression, anxiety, or stress and Internet gaming disorder. Results The results showed that depression and stress are significantly related to Internet gaming disorder through the partial mediating of fear of missing out. Anxiety is not significantly related to Internet gaming disorder through the full mediating of fear of missing out, and anxiety and stress have a greater predictive effect on Internet gaming disorder through fear of missing out. Results also demonstrated that students who play Honor of Kings or Player Unknown's Battlegrounds have more risk to develop Internet gaming disorder. Conclusions The results indicated that fear of missing out as a mediator regulates the relationship among depression, anxiety, and stress and Internet game disorder. Specifically, under the mediation of fear of missing out, teenagers with anxiety are more likely to develop Internet gaming disorder, while teenagers with depression or stress might be prone to other types of Internet use disorders.
Deep Convolutional Neural Networks for Weeds and Crops Discrimination From UAS Imagery

Weeds are among the significant factors that could harm crop yield by invading crops and smother pastures, and significantly decrease the quality of the harvested crops. Herbicides are widely used in agriculture to control weeds; however, excessive use of herbicides in agriculture can lead to environmental pollution as well as yield reduction. Accurate mapping of crops/weeds is essential to determine weeds’ location and locally treat those areas. Increasing demand for flexible, accurate and lower cost precision agriculture technology has resulted in advancements in UAS-based remote sensing data collection and methods. Deep learning methods have been successfully employed for UAS data processing and mapping tasks in different domains. This research investigate, compares and evaluates the performance of deep learning methods for crop/weed discrimination on two open-source and published benchmark datasets captured by different UASs (field robot and UAV) and labeled by experts. We specifically investigate the following architectures: 1) U-Net Model 2) SegNet 3) FCN (FCN-32s, FCN-16s, FCN-8s) 4) DepLabV3+. The deep learning models were fine-tuned to classify the UAS datasets into three classes (background, crops, and weeds). The classification accuracy achieved by U-Net is 77.9% higher than 62.6% of SegNet, 68.4% of FCN-32s, 77.2% of FCN-16s, and slightly lower than 81.1% of FCN-8s, and 84.3% of DepLab v3+. Experimental results showed that the ResNet-18 based segmentation model such as DepLab v3+ could precisely extract weeds compared to other classifiers.
Immune Checkpoint and Telomerase Crosstalk Is Mediated by miRNA-138 in Bladder Cancer

Background Tumor recurrence and progression in non-muscle invasive bladder cancer (NMIBC), therapy failure, and severe side effects in muscle invasive bladder cancer (MIBC) are the major challenges in the clinical management of bladder cancer (BC). Here, we identify new molecular targetable signatures to improve BC patients’ stratification and the outcome of current immunotherapies. Material and Methods In a prospective cohort of 70 BC patients, we assessed the genetic and molecular regulation of TERT in maintaining telomere length in parallel to immune checkpoint and microRNA expression. Results TERT was undetectable in healthy bladder tissues but upregulated in invasive BC stages and high tumor grade. Its expression was linked with the combined effect of the C250T mutation and THOR hypermethylation, associated with progressing tumors and maintaining of telomere length. In the same cohort, PD-L1 scored highest in NMIBC, while PD-L2 was upregulated in MIBC. We also show that miR-100-5p and 138-5p were highly expressed in healthy bladder specimens and cell line, while expression decreased in the BC tissues and BC cell lines. In line with the binding prediction for these miRNAs on target genes, miRs 100-5p and 138-5p expression strongly inverse correlated with TERT, PD-L1, and PD-L2 expression, but not PD1. Conclusion We identify a loop involving TERT, PD1-ligands, and miR-138-5p in BC, that might represent not only a useful biomarker for improved diagnosis and patients’ stratification but also as a promising axis that might be therapeutically targeted in situ.
Publication Trends for Sarcopenia in the World: A 20-Year Bibliometric Analysis

Background Sarcopenia, an age-related degenerative disease, seriously affects the health and quality of life of the elder. The research of sarcopenia has changed dramatically around the world. This article aims to analyze global trends in this field over the past 20 years. Methods “Sarcopenia” was used as the search term to retrieve relevant publications from the WOS and PubMed databases. Co-occurrence, literature coupling, co-citation, and co-author analysis were performed by using the software VOS viewer. We analyzed the trends of sarcopenia research over the last 20 years from different aspects, such as the number of papers, total citations, average citations per item, h-index, research area, article types, institutions, country, journals, and funding. Results We retrieved 13,421 research articles published on sarcopenia between 2001 and 2020. The results showed that the USA made the highest contributions to this field. Geriatrics gerontology is the most study classification of sarcopenia. Basic research on sarcopenia in geriatric gerontology accounts for approximately 16.496% of global publications. The Osteoporosis International published the largest number of sarcopenia-related studies. The United States Department of Health Human Services was the leading funding organization, which sponsored 1,604 articles. Conclusion Global sarcopenia research increased rapidly from 2001 to 2020, especially recently. The research leader of sarcopenia is the USA. In the future, the study of sarcopenia will continue to focus on aging, nutrition, and exercise and will delve deeper into molecular mechanisms. On the other hand, revealing the link between sarcopenia and other diseases will be the next research hotspot.
EasyFlyTracker: A Simple Video Tracking Python Package for Analyzing Adult Drosophila Locomotor and Sleep Activity to Facilitate Revealing the Effect of Psychiatric Drugs

The mechanism of psychiatric drugs (stimulant and non-stimulant) is still unclear. Precision medication of psychiatric disorders faces challenges in pharmacogenetics and pharmacodynamics research due to difficulties in recruiting human subjects because of possibility of substance abuse and relatively small sample sizes. Drosophila is a powerful animal model for large-scale studies of drug effects based on the precise quantification of behavior. However, a user-friendly system for high-throughput simultaneous tracking and analysis of drug-treated individual adult flies is still lacking. It is critical to quickly setup a working environment including both the hardware and software at a reasonable cost. Thus, we have developed EasyFlyTracker, an open-source Python package that can track single fruit fly in each arena and analyze Drosophila locomotor and sleep activity based on video recording to facilitate revealing the psychiatric drug effects. The current version does not support multiple fruit fly tracking. Compared with existing software, EasyFlyTracker has the advantages of low cost, easy setup and scaling, rich statistics of movement trajectories, and compatibility with different video recording systems. Also, it accepts multiple video formats such as common MP4 and AVI formats. EasyFlyTracker provides a cross-platform and user-friendly interface combining command line and graphic configurations, which allows users to intuitively understand the process of tracking and downstream analyses and automatically generates multiple files, especially plots. Users can install EasyFlyTracker, go through tutorials, and give feedback on http://easyflytracker.cibr. ac.cn. Moreover, we tested EasyFlyTracker in a study of Drosophila melanogaster on the hyperactivity-like behavior effects of two psychiatric drugs, methylphenidate and atomoxetine, which are two commonly used drugs treating attention-deficit/hyperactivity disorder (ADHD) in human. This software has the potential to accelerate basic research on drug effect studies with fruit flies.
Diversity and Ecological Guild Analysis of the Oil Palm Fungal Microbiome Across Root, Rhizosphere, and Soil Compartments

The rhizosphere microbiome is a major determinant of plant health, which can interact with the host directly and indirectly to promote or suppress productivity. Oil palm is one of the world’s most important crops, constituting over a third of global vegetable oil production. Currently there is little understanding of the oil palm microbiome and its contribution to plant health and productivity, with existing knowledge based almost entirely on culture dependent studies. We investigated the diversity and composition of the oil palm fungal microbiome in the bulk soil, rhizosphere soil, and roots of 2-, 18-, and 35-year old plantations in Selangor, Malaysia. The fungal community showed substantial variation between the plantations, accounting for 19.7% of community composition, with compartment (root, rhizosphere soil, and bulk soil), and soil properties (pH, C, N, and P) contributing 6.5 and 7.2% of community variation, respectively. Rhizosphere soil and roots supported distinct communities compared to the bulk soil, with significant enrichment of Agaricomycetes, Glomeromycetes, and Lecanoromycetes in roots. Several putative plant pathogens were abundant in roots in all the plantations, including taxa related to Prospodicola mexicana and Pleurostoma sp. The mycorrhizal status and dependency of oil palm has yet to be established, and using 18S rRNA primers we found considerable between-site variation in Glomeromycotinian community composition, accounting for 31.2% of variation. There was evidence for the selection of Glomeromycotinian communities in oil palm roots in the older plantations but compartment had a weak effect on community composition, accounting for 3.9% of variation, while soil variables accounted for 9% of community variation. While diverse Mucoromycotinian fungi were detected, they showed very low abundance and diversity within roots compared to bulk soil, and were not closely related to taxa which have been linked to fine root endophyte mycorrhizal morphology. Many of the fungal sequences showed low similarity to established genera, indicating the presence of substantial novel diversity with significance for plant health within the oil palm microbiome.
Quantification of Tissue Microstructure Using Tensor-Valued Diffusion Encoding: Brain and Body

Diffusion-weighted magnetic resonance imaging (DW-MRI) is a non-invasive technique to probe tissue microstructure. Conventional Stejskal–Tanner diffusion encoding (i.e., encoding along a single axis), is unable to disentangle different microstructural features within a voxel; If a voxel contains microcompartments that vary in more than one attribute (e.g., size, shape, orientation), it can be difficult to quantify one of those attributes in isolation using Stejskal–Tanner diffusion encoding. Multidimensional diffusion encoding, in which the water diffusion is encoded along multiple directions in q-space (characterized by the so-called “b-tensor”) has been proposed previously to solve this problem. The shape of the b-tensor can be used as an additional encoding dimension and provides sensitivity to microscopic anisotropy. This has been applied in multiple organs, including brain, heart, breast, kidney and prostate. In this work, we discuss the advantages of using b-tensor encoding in different organs.
Brain Oxygen Extraction and Metabolism in Pediatric Patients With Sickle Cell Disease: Comparison of Four Calibration Models

Sickle cell disease (SCD) is an inherited hemoglobinopathy with an increased risk of neurological complications. Due to anemia and other factors related to the underlying hemoglobinopathy, cerebral blood flow (CBF) increases as compensation; however, the nature of alterations in oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO2) in SCD remains controversial, largely attributed to the different calibration models. In addition, limited studies have been done to investigate oxygen metabolism in pediatric patients. Thus, this study used a non-invasive T2-based MR oximetry, T2-Relaxation-Under-Spin-Tagging (TRUST) MRI, to measure oxygen homeostasis in pediatric patients with SCD using four different calibration models and examined its relationship to hematological measures. It was found that, compared with controls, SCD patients showed an increased CBF, unchanged total oxygen delivery and increased venous blood T2. The results of OEF and CMRO2 were dependent on the calibration models used. When using sickle-specific, hemoglobin S (HbS) level-dependent calibration, there was a decreased OEF and CMRO2, while the bovine model showed an opposite result. OEF and CMRO2 were also associated with hemoglobin and HbS level; the direction of the relationship was again dependent on the model. Future studies with in vivo calibration are needed to provide more accurate information on the T2-Yv relationship.
Association Between Graphic Health Warning Labels on Cigarette Packs and Smoking Cessation Attempts in Korean Adolescent Smokers: A Cross-Sectional Study

Graphic health warning labels on cigarette packs inform smokers about the health risks associated with tobacco smoking. Adolescents are generally the main targets to influence by graphic health warning labels. This study investigated the association between graphic health warning labels on cigarette packs and attempts to quit smoking in South Korean adolescents. This cross-sectional study used data from the 2017 to 2019 Korea Youth Risk Behavior Web-based Survey, using multiple logistic regression for the analysis. The study population comprised 11,142 adolescents aged 12–18 years. The outcome variable was attempts to quit smoking among adolescent smokers who had seen graphic health warning labels. Attempts to quit smoking were higher among adolescent smokers who had seen graphic health warning labels compared to those who had not {boys, odds ratio (OR) = 1.72 [95% confidence interval (CI), 1.48–2.00]; girls, OR = 1.74 (95% CI, 1.33–2.28)}. The correlation was greater for adolescents who thought about the harm of smoking [boys, OR = 1.86 (95% CI, 1.60–2.16); girls, OR = 1.85 (95% CI, 1.41–2.43)] and the willingness to quit [boys, OR = 2.03 (95% CI, 1.74–2.36); girls, OR = 2.04 (95% CI, 1.55–2.68)] after seeing graphic health warning labels. Our findings indicate that graphic health warning labels on cigarette packs have the potential to lower smoking intentions of adolescents. We suggest that the use of graphic health warning labels is an effective policy-related intervention to reduce smoking in South Korean adolescents.
Clinical Features, Diagnostic Test Performance, and Prognosis in Different Subtypes of Chronic Pulmonary Aspergillosis

Objective The aim of this study was to describe clinical features in different subtypes of chronic pulmonary aspergillosis (CPA)-simple aspergilloma (SA), chronic cavitary pulmonary aspergillosis (CCPA), chronic fibrosing pulmonary aspergillosis (CFPA), aspergillus nodule (AN), and subacute invasive aspergillosis (SAIA), respectively, and identify long-term prognosis of CPA. Methods We reviewed patients diagnosed with different subtypes of CPA from 2002 to 2020 at Nanjing Jinling Hospital, China. We analyzed the clinical and survival information of five different subgroups. A Cox regression model was used to explore proper antifungal duration and long-term survival factors of CCPA and SAIA. Results A total of 147 patients with CPA were included, consisting of 11 SA, 48 CCPA, 5 CFPA, 12 AN, and 71 SAIA. The most common underlying pulmonary disease was pulmonary tuberculosis (n = 49, 33%), followed by bronchiectasis (n = 46, 31.3%) and chronic obstructive pulmonary disease (COPD) or emphysema (n = 45, 30.6%), while in SAIA and CFPA groups, the most common was COPD or emphysema (45.1 and 100%). Cough (85%), expectoration (70.7%), hemoptysis (54.4%), and fever (29.9%) were common symptoms, especially in CCPA, CFPA, and SAIA groups. The common imaging manifestations included cavitation (n = 94, 63.9%), fungal ball (n = 54, 36.7%), pleural thickening (n = 47, 32.0%), and bronchiectasis (n = 46, 31.3%). SAIA and CFPA groups had a lower value of hemoglobin (HB) and serum albumin (ALB) with higher C-reactive protein and erythrocyte sedimentation rate. The positive rate of sputum culture, serum galactomannan (GM), and bronchoalveolar lavage fluid GM was 32.7% (36/110), 18.4% (18/98), and 48.7% (19/39), respectively. There were 64.6% (31/48) patients with CCPA and 25.4% (18/71) patients with SAIA who received surgery and the 5-year cumulative survival rate was 92.1 and 66.6%, respectively. SAIA, old age, male, low body mass index (BMI), COPD or emphysema, multiple distribution, low serum ALB, and positive sputum culture were adverse prognosis factors for SAIA and CCPA group, and BMI ≤ 20.0 kg/m2 was independently associated with increased mortality (hazard ratio (HR) 5.311, 95% CI 1.405–20.068, p = 0.014). Multivariable Cox regression indicated that surgery (HR 0.093, 95% CI 0.011–0.814, p = 0.032) and antifungal duration >6 months (HR 0.204, 95% CI 0.060–0.696 p = 0.011) were related to improved survival. Conclusion The clinical features and laboratory test performance are different among SA, CCPA, CFPA, AN, and SAIA. Low BMI was an independent risk factor for survival. Selective surgery and antifungal duration over 6 months were associated with improved survival.
Impact of Dose of Combined Conventional and Robotic Therapy on Upper Limb Motor Impairments and Costs in Subacute Stroke Patients: A Retrospective Study

Introduction Robot-based training integrated into usual care might optimize therapy productivity and increase treatment dose. This retrospective study compared two doses of an upper limb rehabilitation program combining robot-assisted therapy and occupational therapy on motor recovery and costs after stroke. Methods Thirty-six subacute stroke patients [Fugl-Meyer Assessment (FMA) score 32 ± 12 points; mean ± SD] underwent a combined program of 29 ± 3 sessions of robot-assisted therapy and occupational therapy. Scheduled session time for the higher dose group (HG) was 90 min (two 45-min sessions; n = 14) and for the lower dose group (LG) was 60 min (two 30-min sessions; n = 22). Pre-/post-treatment change in FMA score (ΔFMA, %), actual active time (min), number of movements and number of movements per minute per robot-assisted therapy session were compared between groups. The costs of the combined programs were also analyzed. Results ΔFMA did not differ significantly between groups; the HG improved by 16 ± 13 % and the LG by 11 ± 8%. A between-group difference was found for actual active time (p = 1.06E−13) and number of movements (p = 4.42E−2) but not for number of movements per minute during robot-assisted therapy: the HG performed 1,023 ± 344 movements over 36 ± 3 min and the LG performed 796 ± 301 movements over 29 ± 1 min. Both groups performed 28 movements per minute. The combined program cost was €2017 and €1162 for HG and LG, respectively. Conclusions Similar motor improvements were observed following two doses of movement-based training. The reduction in scheduled session time did not affect the intensity of the practice and met economic constraints.