Miracle-dz/UniFAR-FTUs huggingface dataset:
Preparedness against floods in nearly pristine socio-hydrological systems

ABSTRACT The relations between preparedness and psycho-social attributes of people and communities exposed to river floods in a nearly pristine socio-hydrological system were investigated, applying a hydrological-hydraulic analysis of flood risk in combination with results from a survey, social cartography, semi-structured non-participant observation, and semi-structured interviews. Results show that preparedness in nearly pristine systems is noticeably different to that reported for altered systems. People adopt innovative and simple but efficient measures against floods, conditioned by (1) damage suffered during past floods, (2) perceived exposure to floods, and (3) the number of dependent people in the household. The studied system proved to be well adapted to floods but not resilient. Studying attributes that explain preparedness as part of flood risk management plans would contribute towards uncertainty reduction in risk calculations and increase the safety of goods and people from floods.
Transition of Female Pakistani Students to both the UK and Postgraduate Education Context: Constructing Hybrid Identities through a modicum of control

ABSTRACT The article explores female Pakistani students’ narratives of transition on moving to the UK and into post-graduate higher education. It draws on a qualitative longitudinal study with six female Pakistani students at one university to reveal the complex ongoing transformation of their thinking, feeling and believing. An analysis of troubles of identity during the year are suggestive of their seizing a ‘modicum of control’: a kind of agency that doesn’t resist power structures, but does make an individual feel that they are choosing. As a result our participants went on to make profound changes to some of the ways they thought about and lived their lives. The results have implications for Universities, policy makers and tutors to transcend an institutional focus into a broader enculturated view that highlights an irreversible change to their past identities, which needs support both for students’ transitioning to the UK University and on their return.
Further Exploiting c-Closure for FPT Algorithms and Kernels for Domination Problems

For a positive integer c , a graph G is said to be c -closed if every pair of non-adjacent vertices in G have at most c − 1 neighbours in common. The closure of a graph G , denoted by cl ( G ), is the least positive integer c for which G is c -closed. The class of c -closed graphs was introduced by Fox et al. [ICALP ‘18 and SICOMP ‘20]. Koana et al. [ESA ‘20] started the study of using cl ( G ) as an additional structural parameter to design kernels for problems that are W -hard under standard parameterizations. In particular, they studied problems such as Independent Set , Induced Matching , Irredundant Set and (Threshold) Dominating Set , and showed that each of these problems admits a polynomial kernel, either w.r. t. the parameter k + c or w.r. t. the parameter k for each fixed value of c . Here, k is the solution size and c = cl ( G ). The work of Koana et al. left several questions open, one of which was whether the Perfect Code problem admits a fixed-parameter tractable ( FPT ) algorithm and a polynomial kernel on c -closed graphs. In this paper, among other results, we answer this question in the affirmative. Inspired by the FPT algorithm for Perfect Code , we further explore two more domination problems on the graphs of bounded closure. The other problems that we study are Connected Dominating Set and Partial Dominating Set . We show that Perfect Code and Connected Dominating Set are fixed-parameter tractable w.r. t. the parameter k + cl ( G ), whereas Partial Dominating Set , parameterized by k is W [1]-hard even when cl ( G ) = 2. We also show that for each fixed c , Perfect Code admits a polynomial kernel on the class of c -closed graphs. And we observe that Connected Dominating Set has no polynomial kernel even on 2-closed graphs, unless NP ⊆ co-NP /poly.
Psychological Distress in the Galapagos Islands During the COVID-19 Pandemic

Objectives: to explore the emotional impact of the COVID-19 pandemic in the Galapagos Islands. Methods: an online survey of 369 participants, conducted on October of 2020, was used to assess levels of depression, anxiety, and stress, as well as specific behavioral and emotional reactions to the pandemic. Results: the prevalence of anxiety was 4% and depression 3.65%. Perceived stress level was higher, with 52% of the sample reporting moderate amounts. Women had higher levels of depression and perceived stress. Financial distress, interpersonal conflicts, feelings of isolation and fear of contagion of COVID-19 were all associated with higher levels of anxiety, depression, and stress. Conclusion: prevalence of anxiety and depression is lower in the Galápagos Islands during the pandemic compared to other regions, while stress levels are more significant and may warrant intervention. Despite being low, anxiety and depression were associated with potentially problematic behaviors and emotional reactions.
Exploring Unsupervised Machine Learning Classification Methods for Physiological Stress Detection

Over the past decade, there has been a significant development in wearable health technologies for diagnosis and monitoring, including application to stress monitoring. Most of the wearable stress monitoring systems are built on a supervised learning classification algorithm. These systems rely on the collection of sensor and reference data during the development phase. One of the most challenging tasks in physiological or pathological stress monitoring is the labeling of the physiological signals collected during an experiment. Commonly, different types of self-reporting questionnaires are used to label the perceived stress instances. These questionnaires only capture stress levels at a specific point in time. Moreover, self-reporting is subjective and prone to inaccuracies. This paper explores the potential feasibility of unsupervised learning clustering classifiers such as Affinity Propagation, Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH), K-mean, Mini-Batch K-mean, Mean Shift, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Ordering Points To Identify the Clustering Structure (OPTICS) for implementation in stress monitoring wearable devices. Traditional supervised machine learning (linear, ensembles, trees, and neighboring models) classifiers require hand-crafted features and labels while on the other hand, the unsupervised classifier does not require any labels of perceived stress levels and performs classification based on clustering algorithms. The classification results of unsupervised machine learning classifiers are found comparable to supervised machine learning classifiers on two publicly available datasets. The analysis and results of this comparative study demonstrate the potential of unsupervised learning for the development of non-invasive, continuous, and robust detection and monitoring of physiological and pathological stress.
The Theoretical Study of Unexpected Magnetism in 2D Si-Doped AlN

In this study, the structural and magnetic properties of Si-doped bulk and 2D AlN were systematically investigated by first-principles calculations. Si atoms prefer to substitute Al atoms in both bulk and 2D AlN under N-rich growth conditions. In bulk AlN, Si dopants exhibit a non-magnetic state, uniform distribution, and a strong anisotropic diffusion energy barrier. In contrast to that, Si dopants prefer to form a buckling structure and exhibit a magnetic moment of 1 μ B in 2D AlN. At a low Si concentration, Si atoms tend to get together with antiferromagnetic coupling between each other. However, the magnetic coupling among Si atoms changes to ferromagnetic coupling as Si concentration increases, due to the enhanced exchange splitting and delocalized impurity states. At the extreme doping limit, monolayer SiN, along with its analogs GeN and SnN, is a ferromagnetic semiconductor with a large band gap and high Curie temperature. These results indicate that 2D AlN doped by group IV atoms has potential applications in spintronic devices.
Comprehensive Analysis of the Differential Expression and Prognostic Value of Histone Deacetylases in Glioma

Gliomas are the most common and aggressive malignancies of the central nervous system. Histone deacetylases (HDACs) are important targets in cancer treatment. They regulate complex cellular mechanisms that influence tumor biology and immunogenicity. However, little is known about the function of HDACs in glioma. The Oncomine, Human Protein Atlas, Gene Expression Profiling Interactive Analysis, Broad Institute Cancer Cell Line Encyclopedia, Chinese Glioma Genome Atlas, OmicShare, cBioPortal, GeneMANIA, STRING, and TIMER databases were utilized to analyze the differential expression, prognostic value, and genetic alteration of HDAC and immune cell infiltration in patients with glioma. HDAC1/2 were considerable upregulated whereas HDAC11 was significantly downregulated in cancer tissues. HDAC1/2/3/4/5/7/8/11 were significantly correlated with the clinical glioma stage. HDAC1/2/3/10 were strongly upregulated in 11 glioma cell lines. High HDCA1/3/7 and low HDAC4/5/11 mRNA levels were significantly associated with overall survival and disease-free survival in glioma. HDAC1/2/3/4/5/7/9/10/11 are potential useful biomarkers for predicting the survival of patients with glioma. The functions of HDACs and 50 neighboring genes were primarily related to transcriptional dysregulation in cancers and the Notch, cGMP-PKG, and thyroid hormone signaling pathways. HDAC expression was significantly correlated with the infiltration of B cells, CD4+ T cells, CD8+ T cells, macrophages, neutrophils, and dendritic cells in glioma. Our study indicated that HDACs are putative precision therapy targets and prognostic biomarkers of survival in glioma patients.
Oral Health Knowledge, Attitudes, and Behaviors (KAB) of German Dental Students: Descriptive Cross-Sectional Study

Germany's 2030–oral health agenda incorporates behavioral targets such as twice-daily toothbrushing and routine dental check-ups. Given the professional and social roles of dentists in oral health promotion, the oral health-related knowledge, attitudes, and behaviors (KAB) of dentists and dental students became worth investigation. The present study was designed as a descriptive cross-sectional study that aimed to evaluate oral health KAB of German dental students using the Hiroshima University – Dental Behavioral Inventory (HU-DBI). A total of 508 dental students filled in the questionnaire, out of which 74.2% were females, 38.8% were clinical students, 11.4% reported tobacco smoking at least once week, 26.6% reported drinking alcohol at least once a week, and 82.9% reported suffering from problematic internet use. The overall HU-DBI score was high (7.67 ± 1.32), and it was slightly higher among females (7.70 ± 1.33) than males (7.59 ± 1.29), and gender-diverse students (7.33 ± 1.37). Clinical students (7.88 ± 1.26) had a significantly higher HU-DBI score, especially in the domain of oral health behaviors, compared with preclinical students (7.53 ± 1.34). A significant improvement in oral health behaviors and HU-DBI score was found between the third- vs. the fourth year, which corresponds to the period when prophylaxis, hygiene, and periodontology courses are delivered. Tobacco smoking was significantly associated with poor oral health knowledge, behaviors, and overall HU-DBI score. Problematic internet use and alcohol drinking had slightly lower HU-DBI scores. The findings of the present study call for early implementation of preventive dentistry elements in German curricula and addressing oral health needs of gender minorities in Germany by future epidemiologic studies.
Aldosterone-Induced Sarco/Endoplasmic Reticulum Ca2+ Pump Upregulation Counterbalances Cav1.2-Mediated Ca2+ Influx in Mesenteric Arteries

In mesenteric arteries (MAs), aldosterone (ALDO) binds to the endogenous mineralocorticoid receptor (MR) and increases the expression of the voltage-gated L-type Cav1.2 channel, an essential ion channel for vascular contraction, sarcoplasmic reticulum (SR) Ca2+ store refilling, and Ca2+ spark generation. In mesenteric artery smooth muscle cells (MASMCs), Ca2+ influx through Cav1.2 is the indirect mechanism for triggering Ca2+ sparks. This process is facilitated by plasma membrane-sarcoplasmic reticulum (PM-SR) nanojunctions that drive Ca2+ from the extracellular space into the SR via Sarco/Endoplasmic Reticulum Ca2+ (SERCA) pump. Ca2+ sparks produced by clusters of Ryanodine receptors (RyRs) at PM-SR nanodomains, decrease contractility by activating large-conductance Ca2+-activated K+ channels (BKCa channels), which generate spontaneous transient outward currents (STOCs). Altogether, Cav1.2, SERCA pump, RyRs, and BKCa channels work as a functional unit at the PM-SR nanodomain, regulating intracellular Ca2+ and vascular function. However, the effect of the ALDO/MR signaling pathway on this functional unit has not been completely explored. Our results show that short-term exposure to ALDO (10 nM, 24 h) increased the expression of Cav1.2 in rat MAs. The depolarization-induced Ca2+ entry increased SR Ca2+ load, and the frequencies of both Ca2+ sparks and STOCs, while [Ca2+]cyt and vasoconstriction remained unaltered in Aldo-treated MAs. ALDO treatment significantly increased the mRNA and protein expression levels of the SERCA pump, which counterbalanced the augmented Cav1.2-mediated Ca2+ influx at the PM-SR nanodomain, increasing SR Ca2+ content, Ca2+ spark and STOC frequencies, and opposing to hyperpolarization-induced vasoconstriction while enhancing Acetylcholine-mediated vasorelaxation. This work provides novel evidence for short-term ALDO-induced upregulation of the functional unit comprising Cav1.2, SERCA2 pump, RyRs, and BKCa channels; in which the SERCA pump buffers ALDO-induced upregulation of Ca2+ entry at the superficial SR-PM nanodomain of MASMCs, preventing ALDO-triggered depolarization-induced vasoconstriction and enhancing vasodilation. Pathological conditions that lead to SERCA pump downregulation, for instance, chronic exposure to ALDO, might favor the development of ALDO/MR-mediated augmented vasoconstriction of mesenteric arteries.
Fusobacterium nucleatum Accelerates Atherosclerosis via Macrophage-Driven Aberrant Proinflammatory Response and Lipid Metabolism

Periodontitis, an oral chronic inflammatory disease, is reported to show an association with atherosclerotic vascular disease. Fusobacterium nucleatum is an oral commensal bacterium that is abundantly implicated in various forms of periodontal diseases; however, its role in the pathogenesis of atherosclerosis is unclear. This study aimed to elucidate the underlying pathogenic mechanisms of atherosclerosis induced by F. nucleatum to provide new insight on the prevention and treatment of atherosclerosis. We used an animal model, that is, ApoE–/– mice were infected with F. nucleatum by oral gavage, and in vitro co-culture models to assess the pathogenicity of F. nucleatum. The results indicate that F. nucleatum ATCC 25586 invaded aortic tissues and substantially increased the progression of atherosclerotic lesions. In addition, F. nucleatum changed plaque composition into a less-stable phenotype, characterized with increased subcutaneous macrophage infiltration, M1 polarization, lipid deposition, cell apoptosis, and reduced extracellular matrix and collagen content. The serum levels of pro-atherosclerotic factors, such as interleukin (IL)-6, IL-1β, tumor necrosis factor (TNF)-α, monocyte chemoattractant protein-1 (MCP-1), c-reactive protein, and oxidized low-density lipoprotein (ox-LDL) and microRNAs (miR-146a, miR-155, and miR-23b) were considerably increased after F. nucleatum stimulation, whereas HDL-c level was reduced. F. nucleatum induced in vitro macrophage apoptosis in a time- and dose-dependent manner. F. nucleatum facilitated ox-LDL–induced cholesterol phagocytosis and accumulation by regulating the expression of lipid metabolism-related genes (AR-A1, ACAT1, ABCA1, and ABCG1). F. nucleatum further worsened the atherosclerotic plaque microenvironment by considerably increasing the levels of IL-6; IL-1β; TNF-α; MCP-1; and MMP-2, 8, and 9 and by suppressing fibronectin (FN) 1 levels during foam cell formation. This study shows that F. nucleatum ATCC 25586 is implicated in atherosclerosis by causing aberrant activation and lipid metabolism in macrophage. Graphical Abstract Schematic diagram depicting the process of F. nucleatum inducing atherosclerosis. As one of the oral commensal bacteria, F. nucleatum is abundant in periodontitis sites and can enter blood circulation through damaged periodontal tissue. Subsequently, there is an increase in risk factors (dyslipidemia and inflammatory mediators) in the blood circulation. In addition, it has high invasiveness and can invade into the vascular intima, promoting macrophages M1 polarization, aberrant lipid metabolism, and cell apoptosis, thereby increasing the release of inflammatory mediators, and the degradation of extracellular matrix in the atherosclerotic plaque microenvironment. By then, plaques are prone to rupture.
A New Technique to Quantify the Local Predictability of Extreme Events: The Backward Nonlinear Local Lyapunov Exponent Method

Extreme weather events have a large impact on society, but are challenging to forecast accurately. In this study, we carried out a theoretical investigation of the local predictability of extreme weather events using the Lorenz model. We introduce a new method using the backward nonlinear local Lyapunov exponent to quantitatively estimate the local predictability limits of extreme events. The local predictability limits of extreme events on an individual orbit of a dynamical trajectory are broadly the same, whereas this is not the case if they are on different orbits. The specific structure of the Lorenz attractor is responsible for this phenomenon. Our results show that the local predictability limits of extreme events do not decrease or increase monotonically as the events increase in magnitude. This indicates that the magnitude of extreme events is not the only factor that affects the local predictability. The dynamical flow, initial error size, and structure of an attractor may also affect the local predictability. We also quantitatively compared the local predictability of extreme warm and cold events. This showed that the local predictability limits of extreme warm events are higher than extreme cold events at the same probability. A statistical analysis (i.e., the minimum, first quartile, median, third quartile, and maximum) also suggests that the extreme warm events have higher local predictability limits. In general, extreme warm events are more predictable than extreme cold events.
Viral Vector Vaccines Against ASF: Problems and Prospectives

African swine fever (ASF) is a highly contagious viral disease affecting pigs, with mortality rates a primary focus as they can reach up to 100%. The widespread and colossal economic losses from ASF have impacts on the development of animal husbandry practices in most countries within Africa, Asia, and Europe. Currently, a variety of approaches toward the development of vaccines against ASF are being employed. A promising new concept centered around more economical and time-consuming vaccine production is based on the use of viral vectors to deliver selected immunogens. This review discusses the results obtained from testing various viral vectors as carriers of targeted ASF virus genes. The safety and prospects of viral vectors, the possibilities around modulating cellular and humoral immune responses by choosing genes expressing immunodominant antigens, and the degree of protection in experimental animals from infection with a lethal dose of virulent ASF virus strains have been shown and discussed.
Modeling Functional Flows in California’s Rivers

Environmental flows are critical to the recovery and conservation of freshwater ecosystems worldwide. However, estimating the flows needed to sustain ecosystem health across large, diverse landscapes is challenging. To advance protections of environmental flows for streams in California, United States, we developed a statewide modeling approach focused on functional components of the natural flow regime. Functional flow components in California streams—fall pulse flows, wet season peak flows and base flows, spring recession flows, and dry season baseflows—support essential physical and ecological processes in riverine ecosystems. These functional flow components can be represented by functional flow metrics (FFMs) and quantified by their magnitude, timing, frequency, duration, and rate-of-change from daily streamflow records. After calculating FFMs at reference-quality streamflow gages in California, we used machine-learning methods to estimate their natural range of values for all stream reaches in the state based on physical watershed characteristics, and climatic factors. We found that the models performed well in predicting FFMs in streams across a diversity of landscape and climate contexts, according to a suite of model performance criteria. Using the predicted FFM values, we established initial estimates of ecological flows that are expected to support critical ecosystem functions and be broadly protective of ecosystem health. Modeling functional flows at large regional scales offers a pathway for increasing the pace and scale of environmental flow protections in California and beyond.