Miracle-dz/UniFAR-FTUs huggingface dataset:
Retrospective study of 20 cats surgically treated for insulinoma

Abstract Objective To report the clinical signs, histopathology results, and prognostic factors for outcomes following excision for feline insulinoma (INS). Study design Retrospective study. Sample population Twenty client‐owned cats. Methods Medical records from 2006 to 2020 were reviewed by Veterinary Society of Surgical Oncology members for cats with hypoglycemia resulting from INS, with surgical excision and follow up. Clinical signs and histopathology results were summarized. Factors potentially related to disease‐free interval (DFI), disease‐related death (DRD), and overall survival time (OST) were analyzed with a Cox proportional hazards regression analysis. Results All cats were hypoglycemic on presentation with neurologic signs in 18 out of 20 and inappropriate insulin levels in 12/13. Excision of insulinomas resulted in immediate euglycemia or hyperglycemia in 18 cats. Eighteen cats survived to hospital discharge. The median time to death or last postoperative follow up was 664 days (range: 2‐1205 days). Prognostic factors included age at presentation (for DFI); time to postoperative euglycemia (for DRD); preoperative and postoperative serum blood glucose concentrations; metastasis at the time of surgery (DFI and DRD), and histopathologic tumor invasion (for OST). The median OST for all cats was 863 days. The 1‐, 2‐ and 3‐year survival rates were 75%, 51%, and 10%, respectively. Conclusion Excision of insulinoma resulted in euglycemia or hyperglycemia in most cats. Negative prognostic factors included young age, low serum glucose concentrations, metastasis at time of surgery, tumor invasion, and shorter time to euglycemia. Clinical significance Surgical excision resulted in survival times comparable to those of canine INS.
A Naturalistic Actigraphic Assessment of Changes in Adolescent Sleep, Light Exposure, and Activity Before and During COVID-19

The majority of high school–aged adolescents obtain less than the recommended amount of sleep per night, in part because of imposed early school start times. Utilizing a naturalistic design, the present study evaluated changes in objective measurements of sleep, light, and physical activity before (baseline) and during the first wave of the COVID-19 pandemic (during COVID-19) in a group of US adolescents. Sixteen adolescents (aged 15.9 ± 1.2 years, 68.8% female) wore an actigraphy monitor for 7 consecutive days during an in-person week of school before the pandemic (October 2018-February 2020) and again during the pandemic when instruction was performed virtually (May 2020). Delayed weekday sleep onset times of 1.66 ± 1.33 h (p < 0.001) and increased sleep duration of 1 ± 0.87 h (p < 0.001) were observed during COVID-19 compared with baseline. Average lux was significantly higher during COVID-19 compared with baseline (p < 0.001). Weekday physical activity parameters were not altered during COVID-19 compared with baseline, except for a delay in the midpoint of the least active 5 h (p value = 0.044). This analysis provides insight into how introducing flexibility into the traditional school schedule might influence sleep in adolescents.
Molecular mechanisms, physiological roles, and therapeutic implications of ion fluxes in bone cells: Emphasis on the cation‐Cl− cotransporters

Bone turnover diseases are exceptionally prevalent in human and come with a high burden on physical health. While these diseases are associated with a variety of risk factors and causes, they are all characterized by common denominators, that is, abnormalities in the function or number of osteoblasts, osteoclasts, and/or osteocytes. As such, much effort has been deployed in the recent years to understand the signaling mechanisms of bone cell proliferation and differentiation with the objectives of exploiting the intermediates involved as therapeutic preys. Ion transport systems at the external and in the intracellular membranes of osteoblasts and osteoclasts also play an important role in bone turnover by coordinating the movement of Ca2+, PO42−, and H+ ions in and out of the osseous matrix. Even if they sustain the terminal steps of osteoformation and osteoresorption, they have been the object of very little attention in the last several years. Members of the cation‐Cl− cotransporter (CCC) family are among the systems at work as they are expressed in bone cells, are known to affect the activity of Ca2+‐, PO42−‐, and H+‐dependent transport systems and have been linked to bone mass density variation in human. In this review, the roles played by the CCCs in bone remodeling will be discussed in light of recent developments and their potential relevance in the treatment of skeletal disorders.
Bystanders of intimate partner violence against women and their willingness to intervene: An analysis of secondary data in Spain (2005–2020)

Recent decades have seen a growing acknowledgement of violence against women (VAW) as a serious social and public health problem of epidemic proportions. The prevention of VAW and intimate partner violence against women (IPVAW) has become a priority within this context, and includes various prevention strategies such as social participation and helping behaviors. In different countries, conducting research on help-seeking behavior and bystander intervention in cases of VAW is a common practice, but addressing these issues is much less common in Spain. In this context, the objective of this study is to provide a preliminary estimation of the volume of bystanders in cases of IPVAW in Spain between 2005 and 2020 (since the entry into force of Organic Law 1/2004), their willingness to intervene and, in the case of intervention, the type of helping behavior (real or hypothetical) preferred, using the sources (secondary data) available (specifically, survey data, as the surveys of social perception of gender violence and the 2014 and 2019 macro-surveys, and also administrative data, as the database of reports filed). The data analyzed allow us to determine that, in fact, in the cases of IPVAW there are usually persons within the victim’s inner circle who are firsthand witnesses or have been informed by the victim of the existence of this type of violence, but, although the bystanders generally claim they would engage in an active and supportive response, this is in fact not always the case. These results underscore the need to develop intervention programs aimed at IPVAW bystanders to improve their reaction and contribute to the development of helpful and efficient active responses.
Analytical methods for correlated data arising from multicenter hearing studies

In epidemiological hearing studies, estimating the association between exposures and hearing loss using audiometrically‐assessed hearing measurements is challenging due to the complex correlation structure in the clustered data, with clusters formed by the two ears of the same individual and the testing site and audiologist. We propose a linear mixed‐effects model to take into account the multilevel correlation structures of the data. Both theoretically and in simulation studies, we compare single‐ear linear regression models commonly used in published hearing loss studies with the proposed both‐ears linear mixed models properly accounting for the multi‐level correlations. Our findings include (1) when there are only participant‐level covariates, the worse‐ear linear regression models produce unbiased but typically less efficient estimators than the both‐ear and average‐ear approaches; (2) when there are ear‐level confounders, the worse‐ear method may lead to biased estimators and the average‐ear method produces unbiased but typically less efficient estimators than the both‐ear method; (3) the both‐ear method may gain efficiency when additionally adjusting for testing sites and audiologists. As an illustrative example, we applied the single‐ear and both‐ear methods to assess aspirin‐hearing association in the Nurses' Health Study II.
Hydrogen Intake Relieves Alcohol Consumption and Hangover Symptoms in Healthy Adults: a Randomized and Placebo-Controlled Crossover Study.

BACKGROUND Alcohol-induced hangover represents a significant, yet understudied, global hazard and a large socio-economic burden. OBJECTIVES The aim of this study was to investigate the effects of hydrogen (H2) on relieving drinking and hangover symptoms in 20 healthy volunteers. METHODS In this pilot, randomized, double-blinded, placebo-controlled, matched, crossover interventional trial, participants were matched into pairs and randomly assigned. Study group 1 inhaled placebo air for 1 hr, followed by drinking 100 ml of liquor (40% alcohol) within 10 min, and then pure water. Study group 2 inhaled a mixture of H2 and O2 gas for 1 hr, followed by drinking 100 ml of liquor within 10 min, and then H2 dissolved in water. On a second intervention day (crossover) ≥1 wk later, study-group subjects were switched to the opposite order. Breath alcohol concentration (BrAC), hangover severity, and cognitive scores were measured. RESULTS The BrACs within the H2 group were significantly lower than those within the placebo group after 30 min, 60 min, and 90 min (P < 0.05). The H2 group reported having fewer hangover symptoms compared with the placebo group (Placebo: 77% of symptoms absent, 19.7% of mild symptoms, 2.7% of moderate symptoms, 0.7% of severe symptoms; H2: 88.6% of symptoms absent, 10% of mild symptoms, 1.3% of moderate symptoms, 0% of severe symptoms; P < 0.001). H2 treatment improved cognitive testing scores (P < 0.05), including attention and executive functions. Furthermore, consumption of H2 was negatively (β = -13.016; 95% CI: -17.726, -8.305; P < 0.001) and female sex was positively (β = 22.611; 95% CI: 16.226, 28.997; P < 0.001) correlated with increased BrACs. Likewise, the consumption of H2 was negatively (OR: 0.035; 95% CI: 0.007, 0.168; P < 0.001) while female sex was positively (OR: 28.838; 95% CI: 5.961, 139.506; P < 0.001) correlated with the severity of hangover symptoms. CONCLUSIONS H2 decreases BrACs and relieves the symptoms of hangovers.This trial was registered at China Clinical Trial Registry as ChiCTR2200059988. URL of registration: http://www.chictr. org.cn/showproj.aspx? proj=58359.
Worldwide prevalence of DSM-5 eating disorders among young people

Purpose of review Eating disorders (anorexia nervosa, bulimia nervosa, binge eating disorder, and other eating disorders) affect young people worldwide. This narrative review summarizes key studies conducted on the prevalence of Diagnostic and Statistical Manual of Mental Disorders (DSM-5) eating disorders among young people in 2013-22. Recent findings In Western settings, a substantial proportion of young people have reported an eating disorder. Overall, 5.5--17.9% of young women and 0.6–2.4% of young men have experienced a DSM-5 eating disorder by early adulthood. Lifetime DSM-5 anorexia nervosa was reported by 0.8–6.3% of women and 0.1–0.3% of men, bulimia nervosa by 0.8–2.6% of women and 0.1–0.2% of men, binge eating disorder by 0.6–6.1% of women and 0.3–0.7% of men, other specified feeding or eating disorders by 0.6–11.5% of women and 0.2–0.3% of men, and unspecified feeding or eating disorders 0.2–4.7% of women and 0–1.6% of men. Gender and sexual minorities were at particularly high risk. Emerging studies from Eastern Europe, Asia, and Latin America show similar high prevalences. During the COVID-19 pandemic, the incidence of eating disorders has still increased. Summary Eating disorders are a global health concern among young people. Improved detection, management, and prevention methods are urgently needed.
Association of Modified Systemic Lupus Erythematosus Responder Index Attainment With Long‐Term Clinical Outcomes: A Five‐Year Prospective Study

In trials of systemic lupus erythematosus (SLE), the SLE Responder Index (SRI) is the most commonly used primary efficacy end point but has limited validation against long‐term outcomes. We aimed to investigate associations of attainment of a modified version of the SRI (mSRI) with key clinical outcomes in SLE patients with up to 5 years of follow‐up.
A chemometrics toolbox based on projections and latent variables

A personal view is given about the gradual development of projection methods—also called bilinear, latent variable, and more—and their use in chemometrics. We start with the principal components analysis (PCA) being the basis for more elaborate methods for more complex problems such as soft independent modeling of class analogy, partial least squares (PLS), hierarchical PCA and PLS, PLS‐discriminant analysis, Orthogonal projection to latent structures (OPLS), OPLS‐discriminant analysis and more.
GAMA: Generative Adversarial Multi-Object Scene Attacks

The majority of methods for crafting adversarial attacks have focused on scenes with a single dominant object (e.g., images from ImageNet). On the other hand, natural scenes include multiple dominant objects that are semantically related. Thus, it is crucial to explore designing attack strategies that look beyond learning on single-object scenes or attack single-object victim classifiers. Due to their inherent property of strong transferability of perturbations to unknown models, this paper presents the first approach of using generative models for adversarial attacks on multi-object scenes. In order to represent the relationships between different objects in the input scene, we leverage upon the open-sourced pre-trained vision-language model CLIP (Contrastive Language-Image Pre-training), with the motivation to exploit the encoded semantics in the language space along with the visual space. We call this attack approach Generative Adversarial Multi-object scene Attacks (GAMA). GAMA demonstrates the utility of the CLIP model as an attacker's tool to train formidable perturbation generators for multi-object scenes. Using the joint image-text features to train the generator, we show that GAMA can craft potent transferable perturbations in order to fool victim classifiers in various attack settings. For example, GAMA triggers ~16% more misclassification than state-of-the-art generative approaches in black-box settings where both the classifier architecture and data distribution of the attacker are different from the victim. Our code is available here: https://abhishekaich27.github. io/gama.html
Vanishing results in Chow groups for the modified diagonal cycles

We prove a suﬃcient condition for the vanishing of the modiﬁed diagonal cycle in the Chow group (with Q -coeﬃcients) of the triple product of a curve over C . We exhibit inﬁnitely many non-hyperelliptic curves, including the Fricke–Macbeath curve, the Bring curve, and two 1-dimensional families parameterized by certain Hurwitz spaces, for which our condition is satisﬁed.
SleePyCo: Automatic Sleep Scoring with Feature Pyramid and Contrastive Learning

Automatic sleep scoring is essential for the diagnosis and treatment of sleep disorders and enables longitudinal sleep tracking in home environments. Conventionally, learning-based automatic sleep scoring on single-channel electroencephalogram (EEG) is actively studied because obtaining multi-channel signals during sleep is difficult. However, learning representation from raw EEG signals is challenging owing to the following issues: 1) sleep-related EEG patterns occur on different temporal and frequency scales and 2) sleep stages share similar EEG patterns. To address these issues, we propose a deep learning framework named SleePyCo that incorporates 1) a feature pyramid and 2) supervised contrastive learning for automatic sleep scoring. For the feature pyramid, we propose a backbone network named SleePyCo-backbone to consider multiple feature sequences on different temporal and frequency scales. Supervised contrastive learning allows the network to extract class discriminative features by minimizing the distance between intra-class features and simultaneously maximizing that between inter-class features. Comparative analyses on four public datasets demonstrate that SleePyCo consistently outperforms existing frameworks based on single-channel EEG. Extensive ablation experiments show that SleePyCo exhibits enhanced overall performance, with significant improvements in discrimination between the N1 and rapid eye movement (REM) stages.
MAC: A Meta-Learning Approach for Feature Learning and Recombination

Optimization-based meta-learning aims to learn an initialization so that a new unseen task can be learned within a few gradient updates. Model Agnostic Meta-Learning (MAML) is a benchmark algorithm comprising two optimization loops. The inner loop is dedicated to learning a new task and the outer loop leads to meta-initialization. However, ANIL (almost no inner loop) algorithm shows that feature reuse is an alternative to rapid learning in MAML. Thus, the meta-initialization phase makes MAML primed for feature reuse and obviates the need for rapid learning. Contrary to ANIL, we hypothesize that there may be a need to learn new features during meta-testing. A new unseen task from non-similar distribution would necessitate rapid learning in addition reuse and recombination of existing features. In this paper, we invoke the width-depth duality of neural networks, wherein, we increase the width of the network by adding extra computational units (ACU). The ACUs enable the learning of new atomic features in the meta-testing task, and the associated increased width facilitates information propagation in the forwarding pass. The newly learnt features combine with existing features in the last layer for meta-learning. Experimental results show that our proposed MAC method outperformed existing ANIL algorithm for non-similar task distribution by approximately 13% (5-shot task setting)
Two Piggybacking Codes with Flexible Sub-Packetization to Achieve Lower Repair Bandwidth

As a special class of array codes, $(n,k,m)$ piggybacking codes are MDS codes (i.e., any $k$ out of $n$ nodes can retrieve all data symbols) that can achieve low repair bandwidth for single-node failure with low sub-packetization $m$. In this paper, we propose two new piggybacking codes that have lower repair bandwidth than the existing piggybacking codes given the same parameters. Our first piggybacking codes can support flexible sub-packetization $m$ with $2\leq m\leq n-k$, where $n - k>3$. We show that our first piggybacking codes have lower repair bandwidth for any single-node failure than the existing piggybacking codes when $n - k = 8,9$, $m = 6$ and $30\leq k \leq 100$. Moreover, we propose second piggybacking codes such that the sub-packetization is a multiple of the number of parity nodes (i.e., $(n-k)|m$), by jointly designing the piggyback function for data node repair and transformation function for parity node repair. We show that the proposed second piggybacking codes have lowest repair bandwidth for any single-node failure among all the existing piggybacking codes for the evaluated parameters $k/n = 0.75, 0.8, 0.9$ and $n-k\geq 4$.
GANet: Goal Area Network for Motion Forecasting

Predicting the future motion of road participants is crucial for autonomous driving but is extremely challenging due to staggering motion uncertainty. Recently, most motion forecasting methods resort to the goal-based strategy, i.e., predicting endpoints of motion trajectories as conditions to regress the entire trajectories, so that the search space of solution can be reduced. However, accurate goal coordinates are hard to predict and evaluate. In addition, the point representation of the destination limits the utilization of a rich road context, leading to inaccurate prediction results in many cases. Goal area, i.e., the possible destination area, rather than goal coordinate, could provide a more soft constraint for searching potential trajectories by involving more tolerance and guidance. In view of this, we propose a new goal area-based framework, named Goal Area Network (GANet), for motion forecasting, which models goal areas as preconditions for trajectory prediction, performing more robustly and accurately. Specifically, we propose a GoICrop (Goal Area of Interest) operator to effectively aggregate semantic lane features in goal areas and model actors' future interactions as feedback, which benefits a lot for future trajectory estimations. GANet ranks the 1st on the leaderboard of Argoverse Challenge among all public literature (till the paper submission). Code will be available at https://github.com/kingwmk/GANet.
High Order Asymptotic Preserving and Classical Semi-implicit RK Schemes for the Euler-Poisson System in the Quasineutral Limit

In this paper, the design and analysis of high order accurate IMEX ﬁnite volume schemes for the compressible Euler-Poisson (EP) equations in the quasineutral limit is presented. As the quasineutral limit is singular for the governing equations, the time discretisation is tantamount to achieving an accurate numerical method. To this end, the EP system is viewed as a diﬀerential algebraic equation system (DAEs) via the method of lines. As a consequence of this vantage point, high order linearly semi-implicit (SI) time discretisation are realised by employing a novel combination of the direct approach used for implicit discretisation of DAEs and, two diﬀerent classes of IMEX-RK schemes: the additive and the multiplicative. For both the time discretisation strategies, in order to account for rapid plasma oscillations in quasineutral regimes, the nonlinear Euler ﬂuxes are split into two diﬀerent combinations of stiﬀ and non-stiﬀ components. The high order scheme resulting from the additive approach is designated as a classical scheme while the one generated by the multiplicative approach possesses the asymptotic preserving (AP) property. Time discretisa-tions for the classical and the AP schemes are performed by standard IMEX-RK and SI-IMEX-RK methods, respectively so that the stiﬀ terms are treated implicitly and the non-stiﬀ ones explicitly. In order to discretise in space a Rusanov-type central ﬂux is used for the non-stiﬀ part, and simple central diﬀerencing for the stiﬀ part. AP property is also established for the space-time fully-discrete scheme obtained using the multiplicative approach. Results of numerical experiments are presented, which conﬁrm that the high order schemes based on the SI-IMEX-RK time discretisation achieve uniform second order convergence with respect to the Debye length and are AP in the quasineutral limit.
On the dimension of non-abelian tensor square of Lie superalgebras

In this paper, we determine upper bound for the non-abelian tensor product of ﬁnite dimensional Lie superalgebra. More precisely, if L is a non-abelian nilpotent Lie superalgebra of dimension ( k | l ) and its derived subalgebra has dimension ( r | s ), then dim( L ⊗ L ) ≤ ( k + l − ( r + s ))( k + l − 1) + 2. We discuss the conditions when the equality holds for r = 1 , s = 0 explicitly.