Miracle-dz/UniFAR-FTUs huggingface dataset:
Active Factor Graph Network for Group Activity Recognition

Group activity recognition aims to identify a consistent group activity from different actions performed by respective individuals. Most existing methods focus on learning the interaction between each two individuals (i.e., second-order interaction). In this work, we argue that the second-order interactive relation is insufficient to address this task. We propose a third-order active factor graph network, which models the third-order interaction in each pair of three active individuals. At first, to alleviate the noisy individual actions, we select active individuals by measuring each individual’s influence. The individuals with the top-k largest influence weights are selected as active individuals. Then, for each three-individuals pair, we build a new factor node and contact the factor node with these individual nodes. In other words, we extend the base second-order interactive graph to a new third-order interactive graph, which is defined as factor graph. Next, we design a two-branch factor graph network, in which one branch is to consider all individuals (denoted as full factor graph) and the other one takes the active individuals into consideration (denoted as active factor graph). We leverage both the active and full factor graphs comprehensively for group activity recognition. Besides, to enforce group consistency, a consistency-aware reasoning module is designed with two penalty terms, which describe the inconsistency between individual actions and group activity respectively. Extensive experiments demonstrate that our method achieves state-of-the-art performance on four benchmark datasets, i.e., Volleyball, Collective Activity, Collective Activity Extended, and SoccerNet-v3 datasets. Visualization results further validate the interpretability of our method.
pycofitness—Evaluating the fitness landscape of RNA and protein sequences

Abstract Motivation The accurate prediction of how mutations change biophysical properties of proteins or RNA is a major goal in computational biology with tremendous impacts on protein design and genetic variant interpretation. Evolutionary approaches such as coevolution can help solving this issue. Results We present pycofitness, a standalone Python-based software package for the in silico mutagenesis of protein and RNA sequences. It is based on coevolution and, more specifically, on a popular inverse statistical approach, namely direct coupling analysis by pseudo-likelihood maximization. Its efficient implementation and user-friendly command line interface make it an easy-to-use tool even for researchers with no bioinformatics background. To illustrate its strengths, we present three applications in which pycofitness efficiently predicts the deleteriousness of genetic variants and the effect of mutations on protein fitness and thermodynamic stability. Availability and implementation https://github.com/KIT-MBS/pycofitness.
Targeting MYC induces lipid droplet accumulation by upregulation of HILPDA in clear cell renal cell carcinoma

Significance Lipid droplet (LD) accumulation is common in clear cell renal cell carcinoma (ccRCC), providing survival advantage and association with aggressiveness. However, the mechanisms controlling their biogenesis remain poorly known. Understanding their formation is crucial for developing targeted strategies. We show that MYC inhibition in ccRCC resulted in increased triglyceride accumulation in LDs in a glutamine-dependent process driven by enhanced HILPDA expression. Downregulation of HILPDA reduced tumor growth, and it was only highly expressed in ccRCC in comparison with other tumors or healthy renal tissue. Collectively, we highlight the role of MYC expression and glutamine metabolism in LD biogenesis and propose HILPDA as a specific target for precision medicine, providing an attractive therapeutic approach for this aggressive malignancy.
Wearable functional near‐infrared spectroscopy for measuring dissociable activation dynamics of prefrontal cortex subregions during working memory

Abstract The prefrontal cortex (PFC) has been extensively studied in relation to various cognitive abilities, including executive function, attention, and memory. Nevertheless, there is a gap in our scientific knowledge regarding the functionally dissociable neural dynamics across the PFC during a cognitive task and their individual differences in performance. Here, we explored this possibility using a delayed match‐to‐sample (DMTS) working memory (WM) task using NIRSIT, a high‐density, wireless, wearable functional near‐infrared spectroscopy (fNIRS) system. First, upon presentation of the sample stimulus, we observed an immediate signal increase in the ventral (orbitofrontal) region of the anterior PFC, followed by activity in the dorsolateral PFC. After the DMTS test stimulus appeared, the orbitofrontal cortex activated once again, while the rest of the PFC showed overall disengagement. Individuals with higher accuracy showed earlier and sustained activation of the PFC across the trial. Furthermore, higher network efficiency and functional connectivity in the PFC were correlated with individual WM performance. Our study sheds new light on the dynamics of PFC subregional activity during a cognitive task and its potential applicability in explaining individual differences in experimental, educational, or clinical populations. Practitioner Points Wearable functional near‐infrared spectroscopy (fNIRS) captured dissociable temporal dynamics across prefrontal subregions during a delayed match‐to‐sample task. Anterior regions of the orbitofrontal cortex (OFC) activated first during the delay period, followed by the dorsolateral prefrontal cortex (PFC). PFC disengaged overall after the delay, but the OFC reactivated to the test stimulus. Earlier and sustained activation of PFC was associated with better accuracy. Functional connectivity and network efficiency also varied with task performance.
Decomposition of Healthcare Utilization Inequality in Iran: The Prominent Role of Health Literacy and Neighborhood Characteristics

Unequal utilization in healthcare can potentially affect the right to health. Access to healthcare services and achieving positive health outcomes and health equity are essential principles in promoting human rights. This study aims to assess and analyze socioeconomic-related inequalities in outpatient health services utilization (OHSU) among various socio-demographic subgroups to inform policies that foster health equity. Data were collected through a cross-sectional survey of 1200 households in Tehran, Iran. Inequality in OHSU among the socio-demographic subgroups was calculated by concentration, Wagstaff, and Erigers indices. Decomposition was used to identify the factors contributing to inequality in OHSU. Marginal effect and elasticity were used to calculate the relative absolute shares of socio-demographic variables in the inequality. The rate of OHSU was 63.61% (CI: 60-66.80) which concentrated among households with better socioeconomic status. Based on the results, living in an affluent neighborhood (Relative share (RS): 85.48) and having a disabled member in the household (RS: 6.58) were the most important factors in the concentration of OHSU in favor of the privileged groups. In contrast, very low levels of health knowledge (RS: −83.79) and having basic insurance coverage (RS: −3.92) concentrated OHSU in favor of the lower socioeconomic households. The study was conducted based on survey data, and this may lead to some limitations. Given that this study was a cross-sectional study, we were unable to establish causal relationships between explanatory variables and outpatient health service utilization and its relevant predictors. Households with disabled member(s), as well as a member(s) with chronic diseases, may experience severe inequalities in access to healthcare services. Policies that facilitate access to health services for these households can play a significant role in improving health equity.
Predictive value of stromal tumor-infiltrating lymphocytes in patients with breast cancer treated with neoadjuvant chemotherapy: A meta-analysis

Background: The predictive value of tumor-infiltrating lymphocytes (TILs) in response to neoadjuvant chemotherapy (NAC) for breast cancer (BC) has received increasing attention. Here, a meta-analysis was conducted to evaluate the correlation between the expression of stromal TILs and pathological complete response (pCR) after NAC in BC patients. Methods: The PubMed, Embase, Cochrane Library, and Web of Science databases were searched online by using a combination of keywords and free words to screen literature on the expression of stromal TILs and pCR after NAC in patients with BC. The data were extracted and evaluated for quality. Relative risk (RR) was used to evaluate the relationship between the expression of stromal TILs before NAC and pCR in BC patients. Meta-analysis was performed with Review Manager 5.3 and STATA 14.0 software. Results: Eleven studies involving 6039 BC patients were included in the meta-analysis. The results showed a generally high expression of stromal TILs in BC patients, and the pCR rate after NAC in BC patients with a high expression of stromal TILs was significantly higher than that in BC patients with a low expression of stromal TILs [RR = 1.83, 95% confidence interval (CI): 1.69–1.97]. Subgroup analysis based on the molecular subtypes of BC showed that the pCR rate was significantly higher in patients with a high expression of stromal TILs in hormone receptor (HR)-positive BC [RR = 3.23, 95% CI: 2.43–4.30], human epidermal growth factor receptor 2 (HER-2)-positive BC [RR = 1.41, 95% CI: 1.25–1.60], and triple-negative BC [RR = 1.70, 95% CI: 1.53–1.90] than in those with a low expression of stromal TILs. Subgroup analysis based on expression threshold showed that the pCR rate was higher in patients with a high expression of stromal TILs than in patients with a low expression of stromal TILs at different expression thresholds (10% [RR = 1.99, 95% CI: 1.55–2.55], 20%/30% [RR = 1.57, 95% CI: 1.37–1.81], 50%/60% [RR = 1.91, 95% CI: 1.73–2.11]. Conclusion: TILs can be used as a predictor of pCR after NAC in patients with BC, and the appropriate high expression threshold of stromal TILs should be selected as the predictive value according to the molecular subtype of BC.
Online Reinforcement Learning for Flight Control: An Adaptive Critic Design without prior model knowledge

Online Reinforcement Learning is a possible solution for adaptive nonlinear flight control. In this research an Adaptive Critic Design (ACD) based on Dual Heuristic Dynamic Programming (DHP) is developed and implemented on a simulated Cessna Citation 550 aircraft. Using an online identified system model approximation, the method is independent of prior model knowledge. The agent consists of two Artificial Neural Networks (ANNs) which form the Adaptive Critic Design and is supplemented with a Recursive Least Squares (RLS) online model estimation. The implemented agent is demonstrated to learn a near optimal control policy for different operating points, which is capable of tracking pitch and roll rate while actively minimizing the sideslip angle in a faster than real-time simulation. Providing limited model knowledge is shown to increase the learning, performance and robustness of the controller.
Age‐related positive emotional reactivity decline associated with the anterior insula based resting‐state functional connectivity

Abstract Recent studies have suggested that emotional reactivity changes with age, but the neural basis is still unclear. The insula may be critical for the emotional reactivity. The current study examined how ageing affects emotional reactivity using the emotional reactivity task data from a human sample (Cambridge Center for Age and Neuroscience, N = 243, age 18–88 years). The resting‐state magnetic resonance measurements from the same sample were used to investigate the potential mechanisms of the insula. In the initial analysis, we conducted partial correlation assessments to examine the associations between emotional reactivity and age, as well as between the gray matter volume (GMV) of the insula and age. Our results revealed that emotional reactivity, especially positive emotional reactivity, decreased with age and that the GMV of the insula was negatively correlated with age. Subsequently, the bilateral insula was divided into six subregions to calculate the whole brain resting‐state functional connectivity (rsFC). The mediating effect of the rsFC on age and emotional reactivity was then calculated. The results showed that the rsFC of the left anterior insula (AI) with the right hippocampus, and the rsFCs of the right AI with the striatum and the thalamus were mediated the relationship between positive emotional reactivity and age. Our findings suggest that attenuating emotional reactivity with age may be a strategic adaptation fostering emotional stability and diminishing emotional vulnerability. Meanwhile, the findings implicate a key role for the AI in the changes in positive emotional reactivity with age.
Distribution and vicissitude of gibbons(Hylobatidae)in China during the last 500 years

Gibbon(Hylobatidae spp.)is the only hominoid inhabiting China,and it is the genus which has died out most rapidly in the modern history of China.Research on the historical distribution of gibbons and the factors affecting their distribution,however,are rather limited.Based on ancient literature,in this paper we probe into regional changes in the distribution of gibbons in China dating back to Ming Dynasty(1368-1644). Our results show that the distribution area of gibbons not only shrank towards the southwest,but also in other several regions until gibbons now can be found.Gibbons now survive only in southwestern China and Hainan Island.Although reasons of for the habitat decrease are multiple,among them,the human disturbance matters significantly.
The impact of bilateral versus unilateral anterior temporal lobe damage on face recognition, person knowledge and semantic memory

In recent years, the functional importance of the anterior temporal lobes (ATLs) has come to prominence in two active, albeit unconnected branches of the literature. In one branch, neuropsychology and functional neuroimaging evidence emphasises the role of the ATLs in face recognition and linking faces to biographical knowledge. In the other, cognitive and clinical neuroscience investigations have shown that the ATLs are critical to all forms of semantic memory. To draw these literatures together and generate a unified account of ATL function, we test the predictions arising from each literature and examine the effects of bilateral versus unilateral ATL damage on face recognition, person knowledge and semantic memory. Sixteen people with bilateral ATL atrophy from semantic dementia (SD), 17 people with unilateral ATL resection for temporal lobe epilepsy (TLE; left=10, right=7), and 14 controls completed a test battery encompassing general semantic processing, person knowledge and perceptual face matching. SD patients were severely impaired across all semantic tasks, including person knowledge. Despite commensurate total ATL damage, unilateral resection generated mild impairments, with minimal differences between left- and right-ATL resection. Face matching performance was largely preserved but slightly reduced in SD and right TLE. All groups displayed the classic familiarity effect in face matching; however, this benefit was reduced in SD and right TLE groups and was aligned with the level of item-specific semantic knowledge in all participants. We propose a unified neurocognitive framework whereby the ATLs underpin a resilient bilateral representation system that supports semantic memory, person knowledge and face recognition.
Exploring the community phylogenetic structure along the slope aspect of subalpine meadows in the eastern Qinghai–Tibetan Plateau, China

Abstract Exploring the community assembly has been important for explaining the maintenance mechanisms of biodiversity and species coexistence, in that it is a central issue in community ecology. Here, we examined patterns of the community phylogenetic structure of the subalpine meadow plant community along the slope gradient in the Qinghai–Tibetan Plateau of China. We surveyed all species and constructed the phylogenetic tree of the plant community based on data from the Angiosperm Phylogeny Group III. We selected the net relative index (NRI) and evaluated the community phylogenetic structure along the five slope plants communities. We found that the phylogenetic structure varied from phylogenetic clustering to phylogenetic overdispersion with the slope aspect from north to south. In the north slope, the community phylogenetically cluster indicated that the limiting similarity played a leading role in the community assembly and the maintenance of biodiversity. Community phylogenetic overdispersion in the east, southeast, and south slopes indicated that habitat filtration was the driving force for community assembly. The NRI index of the northeast slope was close to zero, implying random dispersion. But it may be driven by the neutral process or limiting similarity, in that the community assembly process was the result of a combination of several ecological factors and thus required further study.
Made to Be a Woman: A case study on the categorization of gender using an individuation-based approach in the analysis of literary texts

In this article we analyze Simone de Beauvoir’s The Second Sex in order to come up with a category system including gender categories that do not only represent a binary notion but also include non-binary forms of gender. By manually annotating and then visualizing features of gender roles as a networked graph and analyzing the resulting “gender sphere” we come up with two category systems, one containing five, the other one four gender categories, each of which contain a number of gender roles. We compare the gender sphere Beauvoir creates in her text with one resulting from the analysis of narrative texts that she used as references for her analysis of gender roles. In this fiction corpus, we annotated character features, clothes and gender roles, evaluated them quantitatively and then matched them with the gender sphere. Thus it becomes visible that the literary corpus creates a scalar notion of gender ranging from a female to a male pole with a neutral center. Roles relevant for and characters showing traits of gender-diversity are set at the margins. Unlike this scalar notion Beauvoir works towards a more spherical understanding of gender where roles relevant for gender-diversity are well integrated into the center of the gender sphere. Although Beauvoir’s gender sphere cannot be mapped onto the graph data of the fiction corpus, it does offer a good starting point for macro-and microanalysis of literary characters, the features, clothes and roles that are used to describe them and the resulting gender specific profiling.
A New Radiocarbon Sequence from Lamanai, Belize: Two Bayesian Models from One of Mesoamerica’s Most Enduring Sites

Abstract The ancient Maya community of Lamanai, Belize, is well known for its span of occupation from the Early Preclassic (before 1630 BC) to the present. Although most centers in the central and southern Maya Lowlands were abandoned during the Terminal Classic period (AD 750–1000), ceramic and stratigraphic evidence at Lamanai has shown continuous occupation from the start of the Early Preclassic to the Spanish Conquest. In this paper, we present the first complete set of radiocarbon dates from this important site, including 19 new accelerator mass spectrometry (AMS) 14C dates. We use these dates to build Bayesian models for a Terminal Classic structure and an Early Postclassic structure in the site center. This method assists in the refinement of older, conventional dates and provides key chronological information about the site during this volatile time. Adjustments to the standard, uniform distribution model are made using exponential, long-tail, and trapezoidal distributions to incorporate outlier samples and more accurately portray ceramic phases. Because of changes in construction behavior in the Terminal Classic, it is difficult to acquire primary samples from this period, but there remains enough overlap between dates and ceramic phases to deduce persistent occupation at Lamanai during the transition from Late Classic to Postclassic times.
The use of predictive analytics for hydrocarbon exploration in the Denver-Julesburg Basin

We present an approach to predict spatial distribution of a variable from a set of geophysical and interpreted grids using alternating conditional expectations (ACE). This technique is based on nonparametric transformations of the predictor and response variables in order to maximize the linear correlation of the transformed predictors with the transformed response. ACE provides a powerful method to detect underlying relationships between the variables and use them in a regression framework to predict the response variable. A case study is presented that illustrates the approach using a set of grids derived from geophysical attributes (gravity, magnetic, electromagnetic) and interpreted grids (isopach, total organic carbon) as predictor variables to estimate early hydrocarbon production.
Postglacial tectonic structures and mass wasting in Lake Vättern, southern Sweden

Deformation of the Earth's crust by glacial loading and unloading was first recognized more than a century ago (De Geer 1888). This deformation is expressed by postglacial isostatic rebound and is ongoing in large parts of glaciated regions. It is typically a process with uplift rates of millimetres per year (Johansson et al. 2002). The crustal rebound which initially followed deglaciation was, however, faster and therefore caused large earthquakes under certain conditions (Lundqvist & Lagerback 1976; Steffen et al. 2014). In Lake Vattern, southern Sweden, mass wasting and deformation structures have been mapped in the sediment accumulated on the lake floor (Jakobsson et al. 2014). Along an 80 km stretch of the lake, deformation structures seen in sediments reveal up to 13 m of vertical displacement in the underlying bedrock. From this displacement, an earthquake with seismic magnitude up to 7.5 was interpreted to have occurred in Lake Vattern shortly after the Scandinavian Ice Sheet had retreated …
Comparing Australian heat waves in the CMIP5 models through cluster analysis

Quantitative projections of climate extremes on local to regional scales are highly valuable for planners and decision makers and necessary for effective local climate change adaptation. However, in contrast to the model robustness of simulated extremes at the global scale, the robustness in simulating past and future extremes often diminishes over finer spatial scales. In this study we analyze heat waves simulated by state‐of‐the‐art global climate models over the Australian region. For the first time we present results explicitly detailing the model spread in simulated heat wave trends and climatology for this region for the recent past (1958–2005). As expected, large intermodel spread is observed at the local to regional scale for both heat wave trends and climatology. By analyzing multiple initial condition runs from individual models, we show that model internal variability strongly influences the spatial patterns of heat wave trends, while intermodel differences in heat wave climatology appear more influenced by model uncertainty. From a model evaluation perspective, cluster analysis is shown to be useful in characterizing robust spatial features of heat waves simulated by the models. In contrast to the multimodel mean, where uncorrelated spatial features tend to be averaged out, cluster composites preserve these features. Since previous examinations have tended to focus on the multimodel mean the extent of model spread may have been overlooked. Further examination of the processes that lead to model differences and biases is needed.