Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantifying Sparsity of Underwater Acoustic Channel: Field Measurement and Analysis

The inherent sparsity intrinsic to the underwater acoustic (UWA) channel has been a driving force behind substantial efforts toward improving UWA communication, i.e., exploring the sparsity characteristic in crucial aspects such as UWA channel estimation and UWA channel equalization. While extensive empirical evidence obtained from comprehensive sea trial observations supports the recognition that assuming sparsity as a fundamental attribute of the UWA channel is well-founded, the current evaluation measures used to assess the sparsity of UWA channel primarily rely on subjective analysis, lacking a comprehensive analysis and evaluation of measurement indicators tailored specifically for quantifying sparsity in such channel. In this article, the issue of measuring UWA channel sparsity is addressed from the perspective of real-world experimental observation. We evaluate three measures for analyzing UWA channel sparsity: the number of multipath components (MPCs), the Gini index, and the Ricean ${K}$ factor. Although these measures have been used individually in studies related to radio or UWA wireless channel, a comprehensive comparison for quantifying the sparsity of UWA channel is yet to be established. To bridge this gap, we conduct a measurement and analysis of UWA channel sparsity in a shallow water acoustic communication scenario in the real world. Using real-world data collected at a center frequency of 15.5 kHz in Xiamen Harbor, we assess the performance of the aforementioned measures in quantifying UWA channel sparsity with respect to marine environmental behaviors. Our findings demonstrate that these sparsity measures show consistent and reliable results in terms of UWA channel sparsity quantification, which also points to the Gini index as the most suitable sparsity indicator from a practical point of view. Moreover, the relationship between the UWA channel sparsity and environmental behaviors, i.e., wind, tide, and wave, is analyzed and validated.
PTC596-Induced BMI-1 Inhibition Fights Neuroblastoma Multidrug Resistance by Inducing Ferroptosis

Neuroblastoma (NB) is a paediatric cancer with noteworthy heterogeneity ranging from spontaneous regression to high-risk forms that are characterised by cancer relapse and the acquisition of drug resistance. The most-used anticancer drugs exert their cytotoxic effect by inducing oxidative stress, and long-term therapy has been demonstrated to cause chemoresistance by enhancing the antioxidant response of NB cells. Taking advantage of an in vitro model of multidrug-resistant (MDR) NB cells, characterised by high levels of glutathione (GSH), the overexpression of the oncoprotein BMI-1, and the presence of a mutant P53 protein, we investigated a new potential strategy to fight chemoresistance. Our results show that PTC596, an inhibitor of BMI-1, exerted a high cytotoxic effect on MDR NB cells, while PRIMA-1MET, a compound able to reactivate mutant P53, had no effect on the viability of MDR cells. Furthermore, both PTC596 and PRIMA-1MET markedly reduced the expression of epithelial–mesenchymal transition proteins and limited the clonogenic potential and the cancer stemness of MDR cells. Of particular interest is the observation that PTC596, alone or in combination with PRIMA-1MET and etoposide, significantly reduced GSH levels, increased peroxide production, stimulated lipid peroxidation, and induced ferroptosis. Therefore, these findings suggest that PTC596, by inhibiting BMI-1 and triggering ferroptosis, could be a promising approach to fight chemoresistance.
Gender and Age Influence on Emergency Department Visits for Non-Suicidal Self-Injuries in School Aged Children in Italy: An 11 Years Retrospective Cross-Sectional Study

Objectives: Non-suicidal self-injury (NSSI) poses a threat in developmental ages, yet there is a scarcity of studies on NSSI trends, especially those in emergency departments (ED). Methods: The aim of this cross-sectional study is to describe trends in ED visits for NSSI among young people aged between 5 and 19 years in Italy from 2011 to 2021 in Piedmont. From the ministerial ED discharge information system, all occurring NSSIs were identified by medical report and/or ICD9CM code and reported as a population rate and a visit rate on all ED requests. Results: The general rate of ED visits remained stable, with around 210,000 (55% males) visits each year, along the whole period from 2011 to 2019, then halved during 2020 and 2021. The NSSI population and visits rates increased from 2013, peaking in 2019 at a rate of around 25 and 23 NSSI visits (girls) and 76 and 69 NSSI (boys) per 100,000 ED visits. In 2020 and 2021, the rate of NSSI visits increased, particularly in girls and among older adolescents. Conclusion: The gradual increase of NSSI over the last decade is a rising public health issue, which deserves wider attention to ensure early detection and prevention.
The relationship between locus of control, performance in earth/environmental science class, and responsible environmental behavior

This study explored the relationship between students’ locus of control, performance in earth/environmental science class and responsible environmental behavior in the context of small schools. Eighty three high school students in earth/environmental science classes in eastern Wake County were administered the 21-question Nowicki-Strickland locus of control scale and ten-question environmental stewardship scale. Students represented six different small school environments including charter, early college and redesigned theme schools. Four of the schools (one early college and three redesigned) were designated STEM schools. Performance data of grade in course, grade on standardized test and attendance were collected. Data were analyzed in the correlations/ regressions of their locus of control, performance and responsible environmental behavior. Implications for schools were discussed.
Stance-Based Fake News Identification on Social Media with Hybrid CNN and RNN-LSTM Models

Today, fake news can be readily generated and disseminated via social media platforms. Misinformation and hoaxes propagated via online social media or traditional news media are commonly referred to as fake news. Stance-based fake news is based on the opinions of an audience rather than providing correct facts. This study presents a hybrid model focusing on the CNN model and RNN-LSTM model to identify fake news. A balanced dataset of 216k news items called ‘SherLock-FakeNewsNet’ is explored throughout the study resulting in the proposed hybrid model. The NLTK toolkit is utilized to perform some noise reduction. After that, the Keras tokenizer and pre-processor are used for the tokenization and pre-processing steps. Next, the text data is fitted and represented using pre-trained GloVe word embeddings. CNN model is applied with Conv1D layers and MaxPooling layers to extract higher-level features of the text. Following this, to detect the longer context of the given text and to capture interdependencies among word sequences LSTM units are employed in the RNN model. Dropout layers are carefully chosen to reduce overfitting in the final hybrid model. The proposed hybrid model achieves the highest accuracy rate of 92% by outperforming most of the conventional models today with an average Precision of 91%, Recall of 91%, and F1-Score of 91% using an Adam optimizer and a Binary Cross-Entropy loss function. Based on the five experiments performed in the study, we have presented the results by comparing our proposed hybrid model with five related datasets.
Psychosocial Work Conditions as Determinants of Well-Being in Jamaican Police Officers: The Mediating Role of Perceived Job Stress and Job Satisfaction

Policing is considered a high-stress occupation due to the demanding nature of the job. Addressing police stress requires a detailed understanding of how psychosocial risk factors influence various aspects of their well-being. Moreover, an analysis of the direct effects of work conditions and the mediating effects of cognitive appraisals is also warranted. Using the Demands–Resources–Individual Effects (DRIVE) model of work-related stress this study investigated the direct effects of work conditions on well-being and also examined the intermediate role of perceived job stress and job satisfaction in the relationship between work conditions and well-being. Five hundred and seventy-eight police officers from the Jamaica Constabulary Force (J.C.F.) completed the questionnaire. Data were analyzed using hierarchical regressions and the Hayes Process tool for mediation analysis. Both perceived job stress and satisfaction mediated the relationship between work conditions and general physical health. Perceived job stress was an indirect pathway through which work conditions influenced psychological distress, whereas job satisfaction was not a significant mediator. In contrast, job satisfaction mediated the relationship between work conditions and positive well-being, but perceived job stress did not. These findings provide significant evidence for periodically monitoring and auditing perceptions of stress and job satisfaction, as they are likely precursors to subsequent health problems.
Investigating Windowing Techniques in Emotion Classification with ECG and Machine Learning

Automated emotion recognition using physiological signals, particularly Electrocardiogram (ECG), has diverse applications in human-computer interaction, healthcare, and psychology. This study proposes a novel ECG-based emotion recognition approach, utilizing time-series to image encoding, texture-based features, and machine-learning algorithms. The Continuously Annotated Signals of Emotion dataset is used, and emotional states are categorized based on arousal and valence annotations. ECGs are segmented into 5 and 7-window segments and transformed into 2D representations using Markov Transition Field (MTF). Extracting 43 features from the Gray-Level Co-occurrence Matrix and Gray-Level Run Length Matrix (GLRLM), three classifiers, including Random Forest (RF), Support Vector Machine, and eXtreme Gradient Boosting (XGB), are employed for emotion classification. The 7-window approach yields superior results, achieving a peak accuracy of 76.69% with XGB. High-Valence Low-Arousal emotional states are recognized best, with the highest F-measure of 61.9%. The findings suggest the potential for accurate and efficient emotion recognition using ECG, MTF, and machine-learning classifiers.
The Role of the Gut Microbiota in Anorexia Nervosa in Children and Adults—Systematic Review

Among the factors incriminated in the appearance of eating disorders, intestinal microbiota has recently been implicated. Now there is evidence that the composition of gut microbiota is different in anorexia nervosa. We gathered many surveys on the changes in the profile of gut microbiota in patients with anorexia nervosa. This review comprehensively examines the contemporary experimental evidence concerning the bidirectional communication between gut microbiota and the brain. Drawing from recent breakthroughs in this area of research, we propose that the gut microbiota significantly contributes to the intricate interplay between the body and the brain, thereby contributing to overall healthy homeostasis while concurrently impacting disease risk, including anxiety and mood disorders. Particular attention is devoted to elucidating the structure and functional relevance of the gut microbiota in the context of Anorexia Nervosa.
Visualization of Amyloid Oligomers in the Brain of Patients with Alzheimer’s Disease

In the pathogenesis of Alzheimer’s disease (AD), highly neurotoxic amyloid-β (Aβ) oligomers appear early, they are thus considered to be deeply involved in the onset of Alzheimer’s disease. However, Aβ oligomer visualization is challenging in human tissues due to their multiple forms (e.g., low- and high-molecular-weight oligomers, including protofibrils) as well as their tendency to rapidly change forms and aggregate. In this review, we present two visualization approaches for Aβ oligomers in tissues: an immunohistochemical (using the monoclonal antibody TxCo1 against toxic Aβ oligomer conformers) and imaging mass spectrometry using the small chemical Shiga-Y51 that specifically binds Aβ oligomers. TxCo1 immunohistochemistry revealed Aβ oligomer distributions in postmortem human brains with AD. Using Shiga-Y51, imaging mass spectrometry revealed Aβ oligomer distributions in the brain of a transgenic mouse model for AD. These two methods would potentially contribute to elucidating the pathological mechanisms underlying AD.
Sierra Nevada Bioregion

The Sierra Nevada is one of the most striking features of the state of California, extending from the southern Cascade Mountains in the north to the Tehachapi Mountains and Mojave Desert 620 km (435 mi) to the south (Map14.1). The Central Valley forms the western boundary of the Sierra Nevada bioregion, and the Great Basin is on the east. The bioregion includes the central mountains and foothills of the Sierra Nevada Section and the Sierra Nevada Foothills Section of Miles and Goudey (1997). The area of the bioregion is 69,560 km2 (26,442 mi2), approximately 17% of the state. Significant features along the length of the range include Lake Tahoe, Yosemite Valley, and Mount Whitney.
DNA barcoding and comparative RNA-Seq analysis provide new insights into leaf formation using a novel resource of high-yielding Epimedium koreanum

Epimedium koreanum Nakai, a well-known traditional Chinese medicinal herb, has been widely used to treat osteoporosis and sexual dysfunction for thousands of years. However, due to the decreasing population of East Asian natural resources, yearly output of Epimedium crude herb has been in low supply year by year. In this study, an unusual variety of E. koreanum was discovered in Dunhua, Jilin Province, the northernmost area where this variety was found containing 6 individuals, with three branches that had 27 leaflets, which is much more than the typical leaflet number of 9. Firstly, the novel E. koreanum varety was identified using DNA barcodes. Then, 1171 differentially expressed genes (DEGs) were discovered through parallel RNA-seq analysis between the newly discovered variety and wild type (WT) E. koreanum plant. Furthermore, the results of bioinformatics investigation revealed that 914 positively and 619 negatively correlated genes associated with the number of leaflets. Additionally, based on RNA-Seq and qRT-PCR analysis, two homologous hub TCP genes, which were commonly implicated in plant leaf development, and shown to be up regulated and down regulated in the discovered newly variety, respectively. Thus, our study discovered a novel wild resource for leaf yield rewarding medicinal Epimedium plant breeding, provided insights into the relationship between plant compound leaf formation and gene expression of TCPs transcription factors and other gene candidates, providing bases for creating high yield cultivated Epimedium variety by using further molecular selection and breeding techniques in the future.
Factors associated with grazing behavior in candidates for bariatric surgery at a hospital in the Amazon

Blackground To assess grazing behavior and associated factors in candidates for bariatric surgery monitored at a public hospital that is a reference in the care of people with severe obesity. Methods Cross-sectional analytical study, with candidates for bariatric surgery of both genders, treated in a public hospital in the Amazon. To assess grazing behavior, the Repetitive Eating Questionnaire was used, and to investigate patterns of eating behavior, the Three Factor Eating Questionnaire was used, which assesses: Emotional Eating, Cognitive Restriction and Uncontrolled Eating. Sociodemographic information was obtained through self-report and the description of medication use through the medical record. Body mass index (BMI) was also calculated by measuring weight and height. The SPSS program, v. 21.0 was used. The study was approved by the Research Ethics Committee. Results A total of 205 participants were evaluated, with a mean age of 37.5 ± 8.6 years, the majority (93.7%) being women and the majority (59.5%) was not also using medication to lose weight. About 66.3% of the participants had compulsive grazing. The factor with the highest score was cognitive restriction (p < 0.001). Individuals who used weight loss drugs had higher scores in the cognitive restriction factor (p = 0.015) and lower scores for uncontrolled eating (p = 0.008), compulsive grazing (p = 0.021) and non-compulsive grazing (p = 0.034). Conclusion Linear regression showed that emotional eating and uncontrolled eating were predictors of both compulsive grazing and non-compulsive grazing behavior. It was observed that grazing behavior, cognitive restriction, emotional eating and uncontrolled eating are present and correlated in the studied patients. In addition, the use of weight loss drugs seems to help reduce dysfunctional eating behaviors in patients with severe obesity.
Adoption of Wearable Insulin Biosensors for Diabetes Management: A Cross-Sectional Study

Background: Wearable insulin biosensors represent a novel approach that combines the benefits of real-time glucose monitoring and automated insulin delivery, potentially revolutionizing how individuals with diabetes manage their condition. Study purpose: To analyze the behavioral intentions of wearable insulin biosensors among diabetes patients, the factors that drive or hinder their usage, and the implications for diabetes management and healthcare outcomes. Methods: A cross-sectional survey design was adopted in this study. The validated questionnaire included 10 factors (Performance expectancy, effort expectancy, social influence, facilitating conditions, behavioral intention, trust, perceived privacy risk, and personal innovativeness) affecting the acceptance of wearable insulin sensors. A total of 248 diabetic patients who had used wearable sensors participated in the study. Results: Performance expectancy was rated the highest (Mean = 3.84 out of 5), followed by effort expectancy (Mean = 3.78 out of 5), and trust (Mean = 3.53 out of 5). Statistically significant differences (p < 0.05) were observed with respect to socio-demographic variables including age and gender on various influencing factors and adoption intentions. PE, EE, and trust were positively associated with adoption intentions. Conclusion: While wearable insulin sensors are positively perceived with respect to diabetes management, issues like privacy and security may affect their adoption.
Search For Gas Giants Around Late-m Dwarfs

We carried out a near-infrared radial velocity search for Jupiter-mass planets around 36 late M dwarfs. This survey was the first of its kind undertaken to monitor radial velocity variability of these faint dwarfs. For this unique survey we employed the 10-m Keck II on Mauna Kea in Hawaii. With a resolution of 20,000 on the near-infrared spectrograph, NIRSPEC, we monitored these stars over four epochs in 2007. In addition to the measurement of relative radial velocity we established physical properties of these stars. The physical properties of M dwarfs we determined included the identification of neutral atomic lines, the measurement of pseudo-equivalent widths, masses, surface gravity, effective temperature, absolute radial velocities, rotational velocities and rotation periods. The identification of neutral atomic lines was carried out using the Vienna Atomic line Database. We were able to confirm these lines that were previously identified. We also found that some of the lines observed in the K-type stars, such as Mg I though weak, still persist in late M dwarfs. Using the measurement of pseudo-equivalent widths (p-EW) of 13 neutral atomic lines, we have established relations between p-EW and spectral type. Such relations serve as a tool in determining the spectral type of an unknown dwarf star by means of measuring its p-EW. We employed the mass-luminosity relation to compute the masses of M dwarfs. Our calculations indicate these dwarfs to be in the range of 0.1 to 0.07 solar masses. This suggests that some of the late M dwarfs appear to be in the Brown dwarf regime. Assuming their radii of 0.1 solar radii, we calculated their surface gravity. The mean surface gravity is, log g = 5.38. Finally their effective temperature was determined by using the spectral-type iii temperature relationship. Our calculations show effective temperatures in the range of 300
Risk governance and financial performance of public commercial banks of the OECD

This study investigates a relationship between risk governance characteristics and financial performance in public commercial banks across the Organization for Economic Co-operation and Development (OECD) countries. Drawing on the upper echelons theory (UET) (Hambrick & Mason, 1984), it hypothesizes a positive relationship between risk governance characteristics and financial performance. An econometric model is applied to a comprehensive dataset of bank-director years spanning from 2001 to 2019. The empirical findings provide robust evidence supporting a positive and statistically significant relationship between risk governance characteristics of bank directors and financial performance in public commercial banks (Adams et al., 2010). Banks with stronger risk governance structures and characteristics exhibit significantly higher financial performance outcomes. The implications of this study are twofold. Firstly, it highlights the crucial role of efficient and effective risk governance practices in boosting financial performance in the banking sector. The research suggests that banks can greatly benefit from robust risk management systems, enhanced board independence, and expanded director expertise. Additionally, the findings provide actionable guidance for bank directors, regulators, and policymakers in shaping risk governance frameworks and policies. These insights indicate that effective risk governance indirectly improves financial performance and bank stability.
Combination of Local Ablative Techniques with Radiotherapy for Primary and Recurrent Lung Cancer: A Systematic Review

Simple Summary The aim of this review was to evaluate the feasibility and the effectiveness of radiation therapy combined with local tumor ablation therapy in the treatment of primary and recurrent lung cancer in terms of toxicity profile and local control rate. Six studies featuring a total of 115 patients and 119 lesions were selected, showing encouraging outcomes that appear to be promising in terms of toxicity profile. Further prospective studies are need to better delineate combining LTA-RT treatment benefits in this setting. Abstract In patients with early-stage or recurrent NSCLC who are unable to tolerate surgery, a benefit could derive only from a systemic therapy or another few forms of local therapy. A systematic review was performed to evaluate the feasibility and the effectiveness of radiotherapy combined with local ablative therapies in the treatment of primary and recurrent lung cancer in terms of toxicity profile and local control rate. Six studies featuring a total of 115 patients who met eligibility criteria and 119 lesions were included. Three studies evaluated lung cancer patients with a medically inoperable condition treated with image-guided local ablative therapies followed by radiotherapy: their local control rate (LC) ranged from 75% to 91.7% with only 15 patients (19.4%) reporting local recurrence after combined modality treatment. The other three studies provided a salvage option for patients with locally recurrent NSCLC after RT: the median follow-up period varied from 8.3 to 69.3 months with an LC rate ranging from 50% to 100%. The most common complications were radiation pneumonitis (9.5%) and pneumothorax (29.8%). The proposed intervention appears to be promising in terms of toxicity profile and local control rate. Further prospective studies are need to better delineate combining LTA-RT treatment benefits in this setting.