Miracle-dz/UniFAR-FTUs huggingface dataset:
Fluctuations of Functions of Wigner Matrices

We show that matrix elements of functions of N ×N Wigner matrices fluctuate on a scale of order N−1/2 and we identify the limiting fluctuation. Our result holds for any function f of the matrix that has bounded variation thus considerably relaxing the regularity requirement imposed in [7, 11].
The contribution of the components of self-compassion and self-judgment in depressive symptomatology and psychological health in patients with chronic physical disease

ABSTRACT The current study aimed at examining the potential role of self-compassion and self-judgment components on depressive symptomatology and psychological health in people with a diagnosis of chronic physical disease. The sample included 223 participants with a diagnosis of chronic physical disease, aged between 18 and 45 years, who completed an online survey. The tested model showed an excellent fit to the empirical data and path analysis results indicated that mindfulness, self-judgment, and isolation have a significant impact on depressive symptomatology (explaining 40% of its variance) and also on psychological health (explaining 45% of its variance). This study shed some light on the role of both self-compassion and self-judgment components, suggesting the importance of the promotion of mindfulness skills and the reduction of self-judgment and feelings of isolation in people with chronic physical disease. These findings seem to support the development of more effective interventions for the promotion of psychological health and reduction of depressive symptoms in people diagnosed with a chronic physical disease.
A meta‐analysis examined the effect of intrawound vancomycin on surgical site wound infections in non‐spinal neurosurgical operation

To assess the impact of intrawound vancomycin on surgical site wound infections in non‐spinal neurosurgical operations, we conducted a meta‐analysis. A thorough review of the literature up to September 2022 showed that 4286 participants had a non‐spinal neurosurgical operation at the start of the investigations; 1975 of them used intrawound vancomycin, while 2311 were control. Using dichotomous or contentious methods and a random or fixed‐effect model, odds ratios (OR) and mean difference (MD) with 95% confidence intervals (CIs) were estimated to evaluate the impact of intrawound vancomycin on surgical site wound infections in non‐spinal neurosurgical operation. The intrawound vancomycin had significantly lower surgical site wound infections (OR, 0.28; 95% CI, 0.19‐0.40; P < .001) with low heterogeneity (I2 = 32%) compared with the control in non‐spinal neurosurgical operation. The intrawound vancomycin had significantly lower surgical site wound infections compared with control in non‐spinal neurosurgical operation. The low sample size of 2 out of 13 researches in the meta‐analysis calls for care when analysing the results.
Hematological and Plasma Biochemical Reference Values for Captive White-Fronted Parrots (Amazona albifrons) in México

Abstract: The objective of this study was to establish hematological and plasma biochemical reference values in captive white-fronted Amazon parrots (Amazona albifrons), as well as to determine whether sex effects the reference values. To our knowledge, hematological and plasma biochemical data have not been reported in this species. Thirty-seven clinically healthy adult individuals (21 males, 16 females) from El Nido Bird Sanctuary, Ixtapaluca, Estado de México, were the subject birds for this study. Complete blood count and selected plasma biochemical parameters, including uric acid, glutamate dehydrogenase, aspartate aminotransferase, total protein, and albumin, were evaluated. Blood samples were collected in the winter (January), outside of the birds' breeding season. Many hematological and plasma biochemical analytes had large coefficients of variation, and there were no statistically significant sex differences identified.
Production aspects of hay of tropical pasture of Urochloa brizantha, Megathyrsus maximus and Andropogon gayanus: forage mass yield characteristics, evaluation of losses, dehydration and nutritional value of hays

ABSTRACT Context. Tropical pasture have been little explored for haymaking, due to lack of information regarding loss of nutrients and of forage dehydration. Aims. This study aimed to evaluate the production aspects of tropical pasture hays. Methods. To characterise forage dry mass yield and dehydration rate, we studied the grasses Marandú, Xaraés, Massai, Paredão, Planaltina and Tupã. The water soluble carbohydrates concentration curve, chemical composition and in situ rumen degradability of dry mass, crude protein and neutral detergent fibre were also determined. Key results. The highest forage dry mass yield was observed in 2018, when Planaltina and Paredão performed best (6.28 and 5.26 ± 0.41 t of dry matter ha−1, respectively). There was no genotype × dehydration time interaction (P = 0.81) on water soluble carbohydrates. Exposure to sun resulted in a linear decreasing effect (P < 0.01) on water soluble carbohydrates content, with loss of 5.03 g kg−1 for each hour of exposure to the sun during the haymaking process. There was an interaction effect (P < 0.01) between type of material and genotype on the content of dry matter, mineral matter, crude protein and neutral detergent fibre (P < 0.01). In situ degradability of Massai grass dry mass was higher for the hay (758.0 and 253.8 ± 7.9 g kg−1 for hay and in natura material, respectively). Conclusions and implications. The greater amount of leaves in relation to stem indicates that Massai grass is more efficient in dehydration during the first hours of exposure to the sun, as well as sustaining lower losses.
Gender Inequality, Bargaining, and Pay in Care Services in the United States

The authors argue that paid providers of care services in the United States (in health, education, and social service industries) are less able than providers of business services to capture value-added or to extract rents because limited consumer sovereignty, incomplete information regarding quality, and large positive externalities reduce their relative market power. In addition, many care jobs enforce normative responsibility for others and require specific skills that limit cross-industry mobility. Analysis of Current Population Survey data for 2014 to 2019 reveals significant pay penalties in care services relative to business services, controlling for factors such as gender, education, occupation, and public or private employment. Women’s concentration in care services explains a significant proportion of the gender wage gap and raises the possibility of significant potential benefits from industry-level bargaining strategies.
EXPANDER GRAPHS AND SIEVING IN COMBINATORIAL STRUCTURES

We prove a general large-sieve statement in the context of random walks on subgraphs of a given graph. This can be seen as a generalization of previously known results where one performs a random walk on a group enjoying a strong spectral gap property. In such a context the point is to exhibit a strong uniform expansion property for a suitable family of Cayley graphs on quotients. In our combinatorial approach, this is replaced by a result of Alon–Roichman about expanding properties of random Cayley graphs. Applying the general setting we show, for instance, that with high probability (in a strong explicit sense) random coloured subsets of integers contain monochromatic (nonempty) subsets summing to $0$ , and that a random colouring of the edges of a complete graph contains a monochromatic triangle.
The characterization of tumor microenvironment infiltration and the construction of predictive index based on cuproptosis-related gene in primary lung adenocarcinoma

Objective We aimed to use the cancer genome atlas and gene expression omnibus databases to explore the characterization of tumor microenvironment (TME) infiltration and construct a predictive index of prognosis and treatment effect based on cuproptosis-related genes (CRGs) in primary lung adenocarcinoma (LUAD). Methods We described the alterations of CRGs in 954 LUAD samples from genetic and transcriptional fields and evaluated their expression patterns from three independent datasets. We identified two distinct molecular subtypes and found that multi-layer CRG alterations were correlated with patient clinicopathological features, prognosis, and TME cell infiltrating characteristics. Then, a cuproptosis scoring system (CSS) for predicting the prognosis was constructed, and its predictive capability in LUAD patients was validated. Results Two molecular subtypes of cuproptosis (Copper Genes cluster A and cluster B) in LUAD were identified. Copper Genes cluster B had better survival than those with Copper Genes cluster A (p <0.01). Besides, we found that the infiltration of activated CD4+ T cells, natural killer T cells, and neutrophils was stronger in cluster A than in cluster B. Then, we constructed a highly accurate CSS to predict the prognosis, targeted therapy effect, and immune response. Compared with the low-CSS subgroup, the mutations of the TP53, MUC16, and TTN genes were more common in the high-CSS subgroup, while the mutation of TP53, TTN, and CSMD3 genes were more common in the low-CSS subgroup than in high-CSS subgroup. The low-score CSS group had an inferior survival than high-score CSS group (p <0.01). In addition, CSS presented good ability to predict the immune response (area under curve [AUC], 0.726). Moreover, AZD5363 and AZD8186 were the inhibitors of AKT and PI3K, respectively, and had lower IC50 and AUC in the low-score CSS group than it in the high-score CSS group. Conclusions CRGs are associated with the development, TME, and prognosis of LUAD. Besides, a scoring system based on CRGs can predict the efficacy of targeted drugs and immune response. These findings may improve our understanding of CRGs in LUAD and pave a new path for the assessment of prognosis and the development of more effective targeted therapy and immunotherapy strategies.
Examining physical activity participation barriers among adults 50 years and older: a scoping review protocol

Abstract Background Despite the benefits of physical activity (PA), 61% of adults 50 years and older do not meet the recommended levels of PA. One method of increasing PA participation is assessing and addressing PA participation barriers. Currently, no guidance on methodologies for assessing PA participation barriers exist. Objective The primary objective of this scoping review is to map the methodologies used to examine potential PA participation barriers faced by community-dwelling adults 50 years and older. A secondary objective is to evaluate the clinimetric properties of these methodologies. Methods This scoping review protocol is registered with Open Science Framework (https://osf.io/wd2hx). A systematic search of the following databases will be performed: PubMed, PsycINFO, CINAHL, Web of Science, and PEDro. Included studies will 1) present either a) data on development or clinimetric properties of PA participation barrier tool (s); or b) relative risk or odds ratios of PA participation barrier(s); 2) compare PA participation barriers or PA participation barrier tool(s) to either subjective or objective measures of PA; and 3) comprise of community-dwelling participants with a mean age of 50 years and older. A two-phase blinded independent screening process will be conducted to select the included publications. Data will be extracted using a standardized form and cross-checked by the first author. A narrative summary will accompany the results presented in tables and figures. Conclusion This scoping review will provide a comprehensive understanding of current literature and gaps related to PA participation barrier methodologies used with adults 50 years and older.
Rasputin/G3BP mediates o’nyong-nyong virus subversion of antiviral immunity in Anopheles coluzzii

The G3BP proteins in vertebrates and Aedes mosquito ortholog, Rasputin, are essential for alphavirus infection, but the underlying mechanism of Rasputin/G3BP proviral activity is poorly understood. It has been suggested that G3BP could influence host immune signaling, but this has not been functionally demonstrated. Here, we find that depletion of Rasputin activity in Anopheles mosquitoes, the primary vectors of the alphavirus o’nyong-nyong (ONNV), provokes dysregulation of the antiviral Imd, JAK/STAT and RNAi pathways, indicating that Rasputin is required for expression of normal basal immunity in uninfected mosquitoes. Depletion of Rasputin during ONNV bloodmeal infection causes increased transcript abundance of genes in the Imd pathway including positive regulator Rel2, and decreases ONNV infection in mosquitoes. Loss of Rasputin is complemented by co-depletion of Imd pathway positive regulator, Rel2, which restores normal ONNV infection levels. Thus, the presence of Rasputin is required for ONNV inhibition of Imd activity, and viral inhibition of Imd explains much of the Rasputin proviral activity. The viral non-structural protein 3 (nsP3) binds to Rasputin and alters the profile of cellular proteins binding to Rasputin. In the presence of nsP3, 48 Rasputin-binding proteins are unchanged but seven binding proteins are excluded and eight new proteins bind Rasputin. The Rasputin binding partners altered by nsP3 are candidate factors for ONNV immune manipulation and subversion through Rasputin. Overall, these results are consistent with and strongly suggest a mechanism in which ONNV, probably nsP3, co-opts the normal Rasputin function assuring basal cellular immune activity in order to inhibit antiviral immunity and promote infection. These observations may be generalizable for Rasputin function during alphavirus infection of other mosquitoes, as well as for G3BP function in the mammalian host, and could offer a target for vector-based control of arbovirus transmission.
Modulatory effect of non-invasive prefrontal brain stimulation on risk-taking behaviours in humans: preliminary insight on the influence of personality traits

We investigated the modulatory effects of cathodal High-Definition transcranial Direct Current Stimulation (HD-tDCS) on the left dorsolateral prefrontal cortex (DLPFC) and the left ventrolateral prefrontal cortex (VLPFC) on risk-taking. Methods Thirty-four healthy adults underwent 3 independent cathodal HD-tDCS interventions (DLPFC, VLPFC, sham) delivered in counterbalanced order during the performance of the balloon analogue risk task (autoBART). Participants were clustered post-hoc in 3 separate personality profiles according to the HEXACO-60 and the Dark Triad dirty dozen and we reanalysed the data. Results Dorsal prefrontal cathodal HD-tDCS significantly modulated autoBART performance rendering participants less prone to risk-taking (i.e., more conservative) under left DLPFC HD-tDCS compared to left VLPFC or sham stimulation. The re-analysis of the same dataset, taking into consideration personality traits, suggested specific effects in impulsive-disinhibited and normative participants for DLPFC and VLPFC stimulation, respectively. Specifically, we saw that participants classified as impulsive-disinhibited were more affected by HD-tDCS left DLPFC stimulation than other profiles. Conclusions Both, dorsal and ventral prefrontal active HD-tDCS decrease risk-taking behaviour compared to sham stimulation. Importantly, such effects are likely influenced by personality traits (impulsive disinhibited vs normative) exhibited by the participants. Highlights We investigated the effect of dorsal and ventral prefrontal HD-tDCS on risk-taking. We considered post-hoc, the influence of individual personality differences. Dorsal and ventral Prefrontal cathodal HD-tDCS decreased risk-taking behaviour. Left cathodal DLPFC HD-tDCS decreased risk propensity in impulsive-disinhibited participants. Left cathodal VLPFC HD-tDCS decreased risk propensity in normative personality participants.
Low-dimensional representations of the three component loop braid group

Motivated by physical and topological applications, we study representations of the group $\mathcal{LB}_3$ of motions of $3$ unlinked oriented circles in $\mathbb{R}^3$. Our point of view is to regard the three strand braid group $\mathcal{B}_3$ as a subgroup of $\mathcal{LB}_3$ and study the problem of extending $\mathcal{B}_3$ representations. We introduce the notion of a \emph{standard extension} and characterize $\mathcal{B}_3$ representations admiting such an extension. In particular we show, using a classification result of Tuba and Wenzl, that every irreducible $\mathcal{B}_3$ representation of dimension at most $5$ has a (standard) extension. We show that this result is sharp by exhibiting an irreducible $6$-dimensional $\mathcal{B}_3$ representation that has no extensions (standard or otherwise). We obtain complete classifications of (1) irreducible $2$-dimensional $\mathcal{LB}_3$ representations (2) extensions of irreducible $3$-dimensional $\mathcal{B}_3$ representations and (3) irreducible $\mathcal{LB}_3$ representations whose restriction to $\mathcal{B}_3$ has abelian image.
Matlis' semi-regularity in trivial ring extensions issued from integral domains

This paper contributes to the study of homological aspects of trivial ring extensions (also called Nagata idealizations). Namely, we investigate the transfer of the notion of (Matlis') semi-regular ring (also known as IF-ring) along with related concepts, such as coherence, in trivial ring extensions issued from integral domains. All along the paper, we put the new results in use to enrich the literature with new families of examples subject to semi-regularity.
Multi-Granularity Perceptual Ensemble Learning Model with An Application

For the multi-granularity perceptual problem of structured data and its machine learning tasks, proposing a new ensemble learning framework, multi-granularity perceptual ensemble learning model (GEL), which introduced the concepts of granularity, granule and granular layer. GEL mainly includes multi-granularity perceptual data derivation algorithm (MPDDA), selection and training of base learners, and granule weighted ensemble strategy (GWES). GEL is a supervised learning model, in which the MPDDA provides it with multi-level and perspective on data and to solve problems, this enhanced the interpretability of the model. In GEL, it mainly adopts algorithm of decision tree type as the base to study, GWES will improve the ensemble effect. Finally, a user online behavior abnormal detection task is taken as the experimental application object to prove the effectiveness of GEL model. The experimental results showed that GEL model can improve the prediction effect to a certain extent, and its interpretability is significantly better than that of traditional ensemble learning methods. It can provide decision-makers with a reference of multi-granularity perspective and reduce the cognitive bias and prediction error caused by machine learning model viewing things from a single perspective.
Single-Frequency-Driven Multi-Resonant Fsk: An Easy-to-Operate Wideband Modulation Scheme for Magnetic (Underwater) Communication

In this short paper, an innovative wideband hardware-based frequency shift keying modulation technique for magnetic communication is presented. The easy-to-operate transmitter circuit is designed to switch between two configurable resonant frequencies with precise timing, with data symbols mapped to those frequencies. The implementation of a zero voltage crossing detector ensures precise timing for ideal symbol changes, which retains most of the system's energy. This largely eliminates the transient response and unwanted amplitude fluctuations, so that the symbol rate can be significantly increased in conjunction with a wideband receiver. Due to the efficient operation, the resonant circuit needs to be driven by just one of the data symbol frequencies, which simplifies the signal generation for transmitter operation.
Human Position Classification Based On Channel State Information In Wi-Fi Networks

The given work is devoted to the construction of a human position classifier based on channel state information in Wi-Fi networks. During the last decade, many researchers have been developing various monitoring systems such as human activity recognition, activity counting and activity classification based on the Wi-Fi system. This approach is attractive because Wi-Fi wireless technology is used everywhere today, therefore it does not require expensive equipment, special devices and sensors, and is also convenient to use. In this study, to implement the classifier, channel state information (CSI) is used, which describes the singularities of the signal propagation from transmitter to receiver. Based on it, classifiers are built using supervised machine learning algorithms: $k$ nearest neighbors algorithm, logistic regression method, linear support vector machine. After preliminary work with CSI data and fine tuning of the classifiers, the obtained accuracy of correct human position classification in the Wi-Fi channel was 96.1% for the $k$ nearest neighbors algorithm, 95.1% for the logistic regression method, and 94.6% for the linear support vector machine.
DECONN: Combining Minimum and Neutral Energy Consumption Strategies in IoT Networks

In Low-Power Internet-of-Things (IoT), energy provisioning is often heterogeneous, meaning that nodes with rechargeable and non-rechargeable batteries coexist and collaborate to support data communication. Non-rechargeable nodes pose the requirement of minimum energy consumption for maximizing their network lifetime. Nodes powered by rechargeable batteries, in turn, must foster neutral energy consumption to avoid battery depletion and overflow. In this context, keeping one subset of nodes in neutral consumption and another subset in minimum consumption while maintaining proper network operation is a complex challenge to solve. To tackle this problem, we propose in this paper the Dual Energy COnsumption for interNet-of-thiNgs (DECONN). DECONN is a distributed solution designed to combine minimum and neutral consumption for IoT networks with heterogeneous energy provision. Using DECONN, nodes with the lowest amount of energy determine the energy consumption of the nodes located in the communication path. We compare DECONN with current IoT low-power standard protocols, such as RPL and CoAP. The results achieved provide evidence that DECONN may outperform standard protocols regarding the amount of saved energy for non-rechargeable and time in neutral operation for rechargeable nodes.
UAV Cooperative Search based on Multi-agent Generative Adversarial Imitation Learning

The multi-UAV cooperative search problem in an unknown environment is a complex decision-making optimization problem. This paper proposes a multi-agent PPO-based generative adversarial imitation learning algorithm to solve the multi-UAV cooperative search task oriented to target search scenarios. In this work, we propose a generative adversarial imitation learning algorithm framework for centralized training and distributed environment interaction, and use multi-threaded interactive environment to sample training data in parallel to improve the utilization efficiency of generated samples. The experimental results show that the algorithm proposed in this paper effectively completes the multi-UAV cooperative search target task, and achieves the effect similar to that of the expert demonstration.