Miracle-dz/UniFAR-FTUs huggingface dataset:
Promoting Well-Being in Old Age: The Psychological Benefits of Two Training Programs of Adapted Physical Activity

In the last few decades, the relationship between physical conditions and mental health has increasingly attracted the interest of researchers and professionals across disciplines. This relationship is especially relevant in old age, as the challenges posed by aging at various levels represent crucial concerns for policy makers. Due to the remarkable increase in life expectancy across countries, sustainable prevention strategies are needed to help individuals preserve psychophysical well-being in old age. In particular, the regular practice of a moderately intense physical activity is recommended by the World Health Organization to enhance balance, prevent falls, strengthen muscles, and promote psychophysical well-being. Daily physical exercise represents a beneficial and low-cost strategy, easily accessible to the general population and potentially customizable to specific needs through brief training programs. Based on these premises, the present research aimed at longitudinally evaluating mental well-being among 58 Italian people aged 67–85, who were involved in two Adapted Physical Activity (APA) training programs. Inclusion criteria for participation comprised high autonomy levels in daily activities, no cognitive impairment, sedentary habits or only occasional performance of moderate physical activity. Based on physical and functional assessment, 39 participants joined a program of adapted motor activity (PoliFit; Study 1), while 19 participants attended a variant program specifically designed for people with osteoporosis (OsteoFit; Study 2). Well-being dimensions were assessed through the Mental Health Continuum-Short Form, the Emotion Regulation Questionnaire and the Satisfaction with Life Scale. Physical functioning were evaluated before and after the programs through the Short Physical Performance Battery and the Handgrip Dynamometer Jamar Test. Findings highlighted that, besides physical benefits, participants reported significantly more adaptive emotion regulation strategies after both training programs; in addition, participants attending OsteoFit reported significantly higher levels of emotional well-being. Results suggest the potential of moderate physical activity in promoting mental health, emphasizing the additional role of training programs as cost-effective opportunities for elderly people to socialize and improve emotional functioning. Overall, the findings support the view of old age as a stage of competence development and adaptive adjustment, rather than a phase of mere psychophysical decline.
A Review of Automatic Drum Transcription

In Western popular music, drums and percussion are an important means to emphasize and shape the rhythm, often defining the musical style. If computers were able to analyze the drum part in recorded music, it would enable a variety of rhythm-related music processing tasks. Especially the detection and classification of drum sound events by computational methods is considered to be an important and challenging research problem in the broader field of music information retrieval. Over the last two decades, several authors have attempted to tackle this problem under the umbrella term automatic drum transcription (ADT). This paper presents a comprehensive review of ADT research, including a thorough discussion of the task-specific challenges, categorization of existing techniques, and evaluation of several state-of-the-art systems. To provide more insights on the practice of ADT systems, we focus on two families of ADT techniques, namely methods based on non-negative matrix factorization and recurrent neural networks. We explain the methods’ technical details and drum-specific variations and evaluate these approaches on publicly available data sets with a consistent experimental setup. Finally, the open issues and underexplored areas in ADT research are identified and discussed, providing future directions in this field.
Inefficient Metabolism of the Human Milk Oligosaccharides Lacto-N-tetraose and Lacto-N-neotetraose Shifts Bifidobacterium longum subsp. infantis Physiology

Human milk contains a high concentration of indigestible oligosaccharides, which likely mediated the coevolution of the nursing infant with its gut microbiome. Specifically, Bifidobacterium longum subsp. infantis (B. infantis) often colonizes the infant gut and utilizes these human milk oligosaccharides (HMOs) to enrich their abundance. In this study, the physiology and mechanisms underlying B. infantis utilization of two HMO isomers lacto-N-tetraose (LNT) and lacto-N-neotetraose (LNnT) was investigated in addition to their carbohydrate constituents. Both LNT and LNnT utilization induced a significant shift in the ratio of secreted acetate to lactate (1.7–2.0) in contrast to the catabolism of their component carbohydrates (~1.5). Inefficient metabolism of LNnT prompts B. infantis to shunt carbon toward formic acid and ethanol secretion. The global transcriptome presents genomic features differentially expressed to catabolize these two HMO species that vary by a single glycosidic linkage. Furthermore, a measure of strain-level variation exists between B. infantis isolates. Regardless of strain, inefficient HMO metabolism induces the metabolic shift toward formic acid and ethanol production. Furthermore, bifidobacterial metabolites reduced LPS-induced inflammation in a cell culture model. Thus, differential metabolism of milk glycans potentially drives the emergent physiology of host-microbial interactions to impact infant health.
Regulation of lipid peroxidation and ferroptosis in diverse species

This review by Conrad et al. reviews the functions and regulation of lipid peroxidation, ferroptosis, and the antioxidant network in diverse species, including humans, other mammals and vertebrates, plants, invertebrates, yeast, bacteria, and archaea, and discusses the potential evolutionary roles of lipid peroxidation and ferroptosis.
Oxaliplatin-induced blood brain barrier loosening: a new point of view on chemotherapy-induced neurotoxicity

Oxaliplatin is a key drug in the treatment of advanced metastatic colorectal cancer. Despite its beneficial effects in tumor reduction, the most prevalent side-effect of oxaliplatin treatment is a chemotherapy-induced neuropathy that frequently forces to discontinue the therapy. Indeed, along with direct damage to peripheral nerves, the chemotherapy-related neurotoxicity involves also the central nervous system (CNS) as demonstrated by pain chronicity and cognitive impairment (also known as chemobrain), a newly described pharmacological side effect. The presence of the blood brain barrier (BBB) is instrumental in preventing the entry of the drug into the CNS; here we tested the hypothesis that oxaliplatin might enter the endothelial cells of the BBB vessels and trigger a signaling pathway that induce the disassembly of the tight junctions, the critical components of the BBB integrity. By using a rat brain endothelial cell line (RBE4) we investigated the signaling pathway that ensued the entry of oxaliplatin within the cell. We found that the administration of 10 μM oxaliplatin for 8 and 16 h induced alterations of the tight junction (TJs) proteins zonula occludens-1 (ZO-1) and of F-actin, thus highlighting BBB alteration. Furthermore, we reported that intracellular oxaliplatin rapidly induced increased levels of reactive oxygen species and endoplasmic reticulum stress, assessed by the evaluation of glucose-regulated protein GRP78 expression levels. These events were accompanied by activation of caspase-3 that led to extracellular ATP release. These findings suggested a possible novel mechanism of action for oxaliplatin toxicity that could explain, at least in part, the chemotherapy-related central effects.
Who Benefits From Humor-Based Positive Psychology Interventions? The Moderating Effects of Personality Traits and Sense of Humor

The evidence for the effectiveness of humor-based positive psychology interventions (PPIs; i.e., interventions aimed at enhancing happiness and lowering depressive symptoms) is steadily increasing. However, little is known about who benefits most from them. We aim at narrowing this gap by examining whether personality traits and sense of humor moderate the long-term effects of humor-based interventions on happiness and depressive symptoms. We conducted two placebo-controlled online-intervention studies testing for moderation effects. In Study 1 (N = 104) we tested for moderation effects of basic personality traits (i.e., psychoticism, extraversion, and neuroticism) in the three funny things intervention, a humor-based PPI. In Study 2 (N = 632) we tested for moderation effects of the sense of humor in five different humor-based interventions. Happiness and depressive symptoms were assessed before and after the intervention, as well as after 1, 3, and 6 months. In Study 2, we assessed sense of humor before and 1 month after the intervention to investigate if changes in sense of humor go along with changes in happiness and depressive symptoms. We found moderating effects only for extraversion. Extraverts benefitted more from the three funny things intervention than introverts. For neuroticism and psychoticism no moderation effects were found. For sense of humor, no moderating effects were found for the effectiveness of the five humor-based interventions tested in Study 2. However, changes in sense of humor from pretest to the 1-month follow-up predicted changes in happiness and depressive symptoms. Taking a closer look, the playful attitude- and sense of humor-subscales predicted changes in happiness and depression for up to 6 months. Overall, moderating effects for personality (i.e., extraversion) were found, but none for sense of humor at baseline. However, increases in sense of humor during and after the intervention were associated with the interventions’ effectiveness. Thus, we found humor-based interventions to be equally suited for humorous and non-humorous people, but increases in the sense of humor during the intervention phase could serve as an indicator whether it is worth continuing the intervention in the long-term.
Progress and challenges with CdTe cell efficiency

CdTe solar-cell efficiency at Colorado State has now been independently verified above 18% on commercial glass. The parameters for the highest-efficiency cell are 863 mV for VOC, 26.8 mA/cm2 for JSC, and 79.2% for fill-factor, combining for 18.3% efficiency. The cell features that allowed the increases include higher-temperature pre-heating before CdTe deposition, a Te layer to facilitate the back contact, MgZnO for the buffer layer, and an anti-reflective coating. The current and fill-factor have achieved large fractions of their ideal values for the CdTe band gap, but as is typical for CdTe cells, the voltage has not. Two general strategies to address the voltage deficit are described. One of these, electron reflection with fully-depleted CdTe, has achieved voltage increases of 60 mV with 1-μm CdTe and higher with sub-micron absorbers.
Computer vision based approach to detect rice leaf diseases using texture and color descriptors

One of the major reason behind degradation of quality and quantity of rice crop is pest. The lack of technical and scientific knowledge to prevent pest diseases is the main reason for low production of these commodities. This article aims to develop a computer vision based automatic system for the diagnosis of diseases caused by pests in the rice plants. Automatic disease detection using computer vision approach involves three types of feature extraction in this experiment. Diseased area of the leaf, textural descriptors using gray level co-occurrence matrix (GLCM) and color moments are extracted from diseased and non-diseased leaf images resulting in 21-D feature vector. Genetic algorithm based feature selection approach is employed to select relevant features and to discard redundant features, generating a 14-D feature vector that reduces the complexity. Artificial neural network (ANN) and support vector machine (SVM) is used for classification. The proposed algorithm results in classification accuracy of 92.5% using SVM and 87.5% using ANN.
IP-10 Promotes Blood–Brain Barrier Damage by Inducing Tumor Necrosis Factor Alpha Production in Japanese Encephalitis

Japanese encephalitis is a neuropathological disorder caused by Japanese encephalitis virus (JEV), which is characterized by severe pathological neuroinflammation and damage to the blood–brain barrier (BBB). Inflammatory cytokines/chemokines can regulate the expression of tight junction (TJ) proteins and are believed to be a leading cause of BBB disruption, but the specific mechanisms remain unclear. IP-10 is the most abundant chemokine produced in the early stage of JEV infection, but its role in BBB disruption is unknown. The administration of IP-10-neutralizing antibody ameliorated the decrease in TJ proteins and restored BBB integrity in JEV-infected mice. In vitro study showed IP-10 and JEV treatment did not directly alter the permeability of the monolayers of endothelial cells. However, IP-10 treatment promoted tumor necrosis factor alpha (TNF-α) production and IP-10-neutralizing antibody significantly reduced the production of TNF-α. Thus, TNF-α could be a downstream cytokine of IP-10, which decreased TJ proteins and damaged BBB integrity. Further study indicated that JEV infection can stimulate upregulation of the IP-10 receptor CXCR3 on astrocytes, resulting in TNF-α production through the JNK-c-Jun signaling pathway. Consequently, TNF-α affected the expression and cellular distribution of TJs in brain microvascular endothelial cells and led to BBB damage during JEV infection. Regarding regulation of the BBB, the IP-10/TNF-α cytokine axis could be considered a potential target for the development of novel therapeutics in BBB-related neurological diseases.
Deep CT to MR Synthesis Using Paired and Unpaired Data

Magnetic resonance (MR) imaging plays a highly important role in radiotherapy treatment planning for the segmentation of tumor volumes and organs. However, the use of MR is limited, owing to its high cost and the increased use of metal implants for patients. This study is aimed towards patients who are contraindicated owing to claustrophobia and cardiac pacemakers, and many scenarios in which only computed tomography (CT) images are available, such as emergencies, situations lacking an MR scanner, and situations in which the cost of obtaining an MR scan is prohibitive. From medical practice, our approach can be adopted as a screening method by radiologists to observe abnormal anatomical lesions in certain diseases that are difficult to diagnose by CT. The proposed approach can estimate an MR image based on a CT image using paired and unpaired training data. In contrast to existing synthetic methods for medical imaging, which depend on sparse pairwise-aligned data or plentiful unpaired data, the proposed approach alleviates the rigid registration of paired training, and overcomes the context-misalignment problem of unpaired training. A generative adversarial network was trained to transform two-dimensional (2D) brain CT image slices into 2D brain MR image slices, combining the adversarial, dual cycle-consistent, and voxel-wise losses. Qualitative and quantitative comparisons against independent paired and unpaired training methods demonstrated the superiority of our approach.
The interplay between resource supply and demand determines the influence of predation on prey body size1

Predation has been shown to either increase or decrease the body mass of fish, as well as cause variable changes in growth rate. The mechanisms underlying these contrasting responses are not well understood. Here we compared intraspecific body size and growth responses to predation against a backdrop of 2006 estimates of asymptotic mass and growth constants (i.e., von Bertalanffy parameters) across species. We show that intraspecific responses can be quite large relative to interspecific variation and confirm that the magnitude and direction of body size responses is variable. We then employed the supply–demand (SD) model of body mass evolution to explore how predator-induced changes in resource demand or supply could alter body mass. The SD model predicts that any combination of increasing or decreasing body mass and increasing or decreasing growth rate is possible when predation risk is increased, which is consistent with the literature. Finally, we use three case studies to illustrate how the interplay.
STABLE ISOTOPE RATIOS (δ15N AND δ13C) OF SYNTOPIC SHREWS (SOREX)

Abstract Local species richness in shrew (Soricidae) assemblages is often high, and the mechanisms of ecological separation remain relatively unexplored. In this study, hair samples from 6 species of Sorex in 3 separate assemblages were analyzed for stable carbon (13C/12C) and nitrogen (15N/14N) isotope ratios to investigate dietary differences. At each locality, common species exhibited a broad range in δ15N and, to a lesser extent, δ13C, whereas non-overlapping signatures characterized the less abundant species. Because the naturally occurring stable isotope ratios of carbon and nitrogen vary with microenvironment and trophic level, the results support the idea that shrews achieve coexistence through resource partitioning. This study is the first to report stable isotope data on syntopic shrews and provides a direction for future research into resolving the mechanisms of ecological separation in shrew communities.
Vicky Prefers Voltaire to Vogue: Obstacles to the Self-Actualisation of Gifted Women Within Social Systems

Giftedness is characterized by high intellectual capabilities and ambitions, unconventional thinking, and a drive to learn and be creative. We argue that gifted women face specific obstacles that, for many, have precluded their ability to develop their gifts, hindered their educational development and career, and made them feel frustrated and unfulfilled. We analyse testimonies of gifted women that we collected from across the globe to provide concrete evidence of these hurdles, thereby highlighting their struggles, while noting in particular their experiences of shame, guilt, fear and self-doubt. A full understanding of these issues requires a deconstruction of the symbolic paradigm that underpins the social system we live in. As gifted women are by nature drawn to creative, independent, intellectual pursuits, they deviate from the norms imposed by the social system. The resulting negative reactions frequently lead them to believe there is something intrinsically wrong with them. This produces the painful emotion of shame, which potently suppresses selfactualization.
Heart Rate Monitoring in Team Sports—A Conceptual Framework for Contextualizing Heart Rate Measures for Training and Recovery Prescription

A comprehensive monitoring of fitness, fatigue, and performance is crucial for understanding an athlete's individual responses to training to optimize the scheduling of training and recovery strategies. Resting and exercise-related heart rate measures have received growing interest in recent decades and are considered potentially useful within multivariate response monitoring, as they provide non-invasive and time-efficient insights into the status of the autonomic nervous system (ANS) and aerobic fitness. In team sports, the practical implementation of athlete monitoring systems poses a particular challenge due to the complex and multidimensional structure of game demands and player and team performance, as well as logistic reasons, such as the typically large number of players and busy training and competition schedules. In this regard, exercise-related heart rate measures are likely the most applicable markers, as they can be routinely assessed during warm-ups using short (3–5 min) submaximal exercise protocols for an entire squad with common chest strap-based team monitoring devices. However, a comprehensive and meaningful monitoring of the training process requires the accurate separation of various types of responses, such as strain, recovery, and adaptation, which may all affect heart rate measures. Therefore, additional information on the training context (such as the training phase, training load, and intensity distribution) combined with multivariate analysis, which includes markers of (perceived) wellness and fatigue, should be considered when interpreting changes in heart rate indices. The aim of this article is to outline current limitations of heart rate monitoring, discuss methodological considerations of univariate and multivariate approaches, illustrate the influence of different analytical concepts on assessing meaningful changes in heart rate responses, and provide case examples for contextualizing heart rate measures using simple heuristics. To overcome current knowledge deficits and methodological inconsistencies, future investigations should systematically evaluate the validity and usefulness of the various approaches available to guide and improve the implementation of decision-support systems in (team) sports practice.
Image-to-image translation for cross-domain disentanglement

Deep image translation methods have recently shown excellent results, outputting high-quality images covering multiple modes of the data distribution. There has also been increased interest in disentangling the internal representations learned by deep methods to further improve their performance and achieve a finer control. In this paper, we bridge these two objectives and introduce the concept of cross-domain disentanglement. We aim to separate the internal representation into three parts. The shared part contains information for both domains. The exclusive parts, on the other hand, contain only factors of variation that are particular to each domain. We achieve this through bidirectional image translation based on Generative Adversarial Networks and cross-domain autoencoders, a novel network component. Our model offers multiple advantages. We can output diverse samples covering multiple modes of the distributions of both domains, perform domain-specific image transfer and interpolation, and cross-domain retrieval without the need of labeled data, only paired images. We compare our model to the state-of-the-art in multi-modal image translation and achieve better results for translation on challenging datasets as well as for cross-domain retrieval on realistic datasets.
Lipid and fatty acid compositions of Symbiodinium strains

Many marine invertebrates including corals that live in tropical and subtropical regions form symbioses with dinoflagellates (zooxanthellae). These symbioses are thought to cope with environmental stress by changing the membrane lipid and fatty acid compositions of their zooxanthellae, but details of these compositions have not been reported. To evaluate how the symbiosis withstands stress, we examined the lipid and fatty acid content of the symbiont’s membranes. We chose two strains, KB8 and Y106, of Symbiodinium which were isolated from a jellyfish Cassiopea ornata and a mantle lobe of the giant clam Tridacna crocea, respectively. These dinoflagellate strains were cultured in f/2 medium for 21 days at 24oC. Lipids were extracted from the cells, and separated by two-dimensional thin-layer chromatography. Each lipid was then scraped from the silica plates and co-chromatographed with standard lipids. In both strains, three glycolipids, monogalactosyldiacylglycerol, digalactosyldiacylglycerol and sulfoquinovosyldiacylglycerol, were found. These are typical lipids of photosynthetic membranes, indicating that the strains are photosynthetically active. With respect to phospholipids, phosphatidylcholine was the major lipid. This phospholipid is typical of organelles other than the plastids. These dinoflagellates were also found to have long-chain unsaturated fatty acids, e.g., octadecatetraenoic acid, octadecapentaenoic acid, octadecapentaenoic acid, and docosahexaenoic acid. The data presented here provide baseline information to analyze the effects of environmental stress on lipid and fatty acid compositions.