Miracle-dz/UniFAR-FTUs huggingface dataset:
Euler polynomials and alternating sums of powers of integers

In this note, we consider the alternating sum of the mth powers of the first n positive integers . In 1989, Gessel and Viennot showed that, for even m = 2k, can be expressed as a polynomial of degree k in the triangular number without constant term. Here, we offer an alternative demonstration of this result that can be made suitable for first-year undergraduate students by using some basic properties of the Euler numbers and polynomials. We also give the corresponding closed formula for in the case of odd powers m = 2k + 1. In addition, we express both and as polynomials in n and give their coefficients in terms of the Bernoulli numbers. Finally, we give yet another representation for and involving the Stirling numbers of the second kind.
‘Body on the line’: experiences of tackle injury in women’s rugby union – a grounded theory study

Objectives Tackle-related injuries account for up to 67% of all match injuries in women’s rugby union. The perspective of women players on tackle injury can help key stakeholders understand psychosocial determinants of tackle injury risk and prevention. We aimed to capture psychosocial processes that explain tackle injury experiences and behaviours in women’s rugby union. Methods We conducted a qualitative study using a grounded theory approach. Adult women players, with at least 1-year senior level experience, were recruited from Europe, South Africa and Canada between December 2021 and March 2022. Data were collected through semistructured interviews and analysed in line with grounded theory coding procedures. Results Twenty-one players, aged 20–48 years with a mean 10.6 years of rugby playing experience, participated. In our analysis, we identified three categories central to participants’ experiences of tackle injury: (1) embodied understandings of tackle injury, (2) gender and tackle injury risk and (3) influences on tackle injury behaviours. Participants reported a sense of fear in their experience of tackling but felt that tackle injuries were an inevitable part of the game. Tackle injury was described based on performance limitations. Tackle injury risks and behaviours were influenced by gendered factors perpetuated by relations, practices and structures within the playing context of women’s rugby union. Conclusion Women’s tackle injury experiences were intertwined with the day-to-day realities of marginalisation and under preparedness. Grounded in the voices of women, we have provided recommendations for key stakeholders to support tackle injury prevention in women’s rugby.
A new painting process for vessel radiators of transformer: wet-on-wet

The painting process of corrugated wall radiators of a distribution transformer is performed by a flow-down painting technique in the industrial field. This study has been prepared in accordance with ISO 12944-5. Correspondingly, this work is motivated by Epoxy 2-pack paints (4.3.4.2) to obtain minimum requirements for C3 atmospheric corrosivity categories (5.1.1). This standard requires from the vertical surface of the vessel of the transformer to be painted with epoxy paints that contain anti-corrosive pigments with a minimum of 100 µm dry film thickness. In the present study, a new production methodology called wet-on-wet (WOW) painting is developed which has never been used in industry. In addition, a modified response surface methodology (RSM) is proposed for designing, modeling, and optimizing the proposed process under unsteady environmental effects. The results indicate that the WOW painting can be applied to real industrial systems successfully by the aid of the proposed new RSM algorithm and provide remarkable time and cost savings.
Spatio-temporal dynamics and drivers of Highly Pathogenic Avian Influenza H5N1 in Chile

Highly pathogenic avian influenza A H5N1 clade 2.3. 4.4b (hereafter H5N1) is causing vast impacts on biodiversity and poultry around the globe. In Chile it was first reported on December 7th, 2022, in a pelican (Pelecanus thagus) found dead in the northern city of Arica. In the following months, lethal H5N1 cases were reported in a wide range of wild bird species, marine mammals, backyard and industrial poultry, and in a human. Despite its high impact and spread, it is not well-known what environmental factors are associated with outbreaks. This study describes the spatio-temporal patterns of the current epizootic of H5N1 in Chile and test ecological and anthropogenic drivers that could be associated with outbreak occurrence. We used H5N1 cases reported by the Chilean national animal health authority to the World Animal Health Information System (WAHIS) from December 9th, 2022, to March 3rd, 2023. These included bird cases confirmed through avian influenza specific real-time PCR assay (qPCR), obtained from passive and active surveillance. Data was analyzed to detect the presence of H5N1 clusters under space-time permutation probability modelling, H5N1 association between distance and days since first outbreak through linear regression, and correlation between H5N1 presence with a range of ecological and anthropogenic variables by general linear modelling. From the 197 H5N1 identified outbreaks, involving 478 individual cases among wild and domestic birds, a wave-like steady spread of H5N1 from north to south was identified, that can help predict hotspots of outbreak risk and establish targeted preventive measures. For instance, 14 statistically significant clusters were identified, with the largest located in central Chile (18-29 km in radius) where poultry production is concentrated. Also, one of the clusters was identified in Tocopilla, location where the H5N1 human case occurred time later. In addition, the presence of H5N1 outbreaks was positively correlated with bird richness, human footprint, precipitation of the wettest month, minimum temperature of the coldest month, and mean diurnal temperature. In contrast, presence of H5N1 was negatively correlated to distance to the closest urban center, precipitation seasonality and isothermality. Preventive actions based on our modeling approach include developing wildlife surveillance diagnostic capabilities in Chilean regions concentrating outbreaks. It is urgent that scientists, the poultry sector, local communities and national health authorities co-design and implement science-based measures from a One Health perspective to avoid further H5N1 spillover from wildlife to domestic animals and humans, including rapid removal and proper disposal of wild dead animals, and the closure of public areas (i.e., beaches) reporting high wildlife mortalities.
Isoform-specific C-terminal phosphorylation drives autoinhibition of Casein Kinase 1

Casein kinase 1 δ (CK1δ) controls essential biological processes, including circadian rhythms and Wnt signaling, but how its activity is regulated is not well understood. CK1δ is inhibited by autophosphorylation of its intrinsically disordered C-terminal tail. Two CK1 splice variants, δ1 and δ2, differ only in the last 16 residues of the tail and have different activity in vivo, suggesting that the extreme C-terminus (XCT) of CK1 plays a role in autoinhibition. Using NMR and HDX-MS, we show that the δ1 XCT is preferentially phosphorylated by the kinase and the δ1 tail makes more extensive interactions across the kinase domain. Mutation of δ1-specific XCT phosphorylation sites disrupts its interaction with the kinase domain and increases kinase activity in vitro and in cells. δ1 autoinhibition relies on conserved anion binding sites around the CK1 active site, demonstrating a common mode of product inhibition of CK1δ. These findings demonstrate how a phosphorylation cycle controls the activity of this essential kinase.
Learning to Express Reward Prediction Error-like Dopaminergic Activity Requires Plastic Representations of Time

The dominant theoretical framework to account for reinforcement learning in the brain is temporal difference (TD) reinforcement learning. The normative motivation for TD theory is that the brain needs to learn about expected future rewards in order to learn how to maximize these rewards. The TD framework predicts that some neuronal elements should represent the reward prediction error (RPE), which means they signal the difference between the expected future rewards and the actual rewards. What makes the TD learning theory so prominent is that the firing properties of dopaminergic neurons in the ventral tegmental area (VTA) appear similar to those of RPE model-neurons in TD learning. Biologically plausible implementations of TD learning assume a fixed temporal basis for each stimulus that might eventually predict a reward. Here we show on the basis of first principles that such a fixed temporal basis is implausible. We also show that certain predictions of TD learning are inconsistent with experimental data. We propose instead an alternative theoretical framework, coined FLEX (Flexibly Learned Errors in Expected Reward). In FLEX, feature specific representations of time are learned, allowing for neural representations of stimuli to adjust their timing and relation to rewards in an online manner. As an indirect consequence, dopamine in FLEX resembles, but is not equivalent to RPE. In FLEX dopamine acts as an instructive signal which helps build temporal models of the environment. FLEX is a general theoretical framework that has many possible biophysical implementations. In order to show that FLEX is a feasible approach, we present a specific biophysically plausible model which implements the principles of FLEX. We show that this implementation can account for various reinforcement learning paradigms, and that its results and predictions are consistent with a preponderance of both existing and reanalyzed experimental data.
Contributions of attention to learning in multi-dimensional reward environments

Real-world choice options have many features or attributes, whereas the reward outcome from those options only depends on a few features/attributes. It is currently unclear how humans learn and make decisions when multiple features and conjunctions of features are predictive of reward, and moreover, how selective attention contributes to these processes. Here, we examined human behavior during a three-dimensional learning task in which reward outcomes for different stimuli could be predicted based on a combination of an informative feature and conjunction. Using multiple approaches, we found that choice behavior and reward probabilities estimated by participants were best described by a model that learned the predictive values of both the informative feature and the informative conjunction. Moreover, attention was controlled by the difference in these values in a cooperative manner such that attention depended on the integrated feature and conjunction values, and the resulting attention weights modulated learning by increasing the learning rate on attended features and conjunctions. However, there was little effect of attention on decision making. These results suggest that in high-dimensional environments, humans direct their attention not only to selectively process reward-predictive attributes, but also to find parsimonious representations of the reward contingencies to achieve more efficient learning.
hipFG: high-throughput harmonization and integration pipeline for functional genomics data

Summary Preparing functional genomic (FG) data with diverse assay types and file formats for integration into analysis workflows that interpret genome-wide association and other studies is a significant and time-consuming challenge. Here we introduce hipFG, an automatically customized pipeline for efficient and scalable normalization of heterogenous FG data collections into standardized, indexed, rapidly searchable analysis-ready datasets while accounting for FG datatypes (e.g., chromatin interactions, genomic intervals, quantitative trait loci). Availability and Implementation hipFG is freely available at https://bitbucket.org/wanglab-upenn/hipFG. Docker container is available at https://hub.docker. com/r/wanglab/hipfg. Contact lswang@pennmedicine.upenn. edu Supplementary information Supplementary data are available as BioRxiv supplemental files.
Turicibacterales protect mice from severe Citrobacter rodentium infection

One of the major contributors to child mortality in the world is diarrheal diseases, with an estimated 800,000 deaths per year. Many pathogens are causative agents of these illnesses, including the enteropathogenic (EPEC) or enterohemorrhagic (EHEC) forms of Escherichia coli. These bacteria are characterized by their ability to cause attaching and effacing lesions in the gut mucosa. Although much has been learned about the pathogenicity of these organisms and the immune response against them, the role of the intestinal microbiota during these infections is not well characterized. Infection of mice with E. coli requires pre-treatment with antibiotics in most mouse models, which hinders the study of the microbiota in an undisturbed environment. Using Citrobacter rodentium as a murine model for attaching and effacing bacteria, we show that C57BL/6 mice deficient in granzyme B expression are highly susceptible to severe disease caused by C. rodentium infection. Although a previous publication from our group shows that granzyme B-deficient CD4+ T cells are partially responsible for this phenotype, in this report we present data demonstrating that the microbiota, in particular members of the order Turicibacterales, have an important role in conferring resistance. Mice deficient in Turicibacter sanguinis have increased susceptibility to severe disease. However, when these mice are co-housed with resistant mice, or colonized with T. sanguinis, susceptibility to severe infection is reduced. These results clearly suggest a critical role for this commensal in the protection against entero-pathogens.
Derrick: A Three-layer Balancer for Self-managed Continuous Scalability

Data arrangement determines the capacity, resilience, and performance of a distributed storage system. A scalable self-managed system must place its data efficiently not only during stable operation but also after an expansion, planned downscaling, or device failures. In this article, we present Derrick, a data balancing algorithm addressing these needs, which has been developed for HYDRAstor, a highly scalable commercial storage system. Derrick makes its decisions quickly in case of failures but takes additional time to find a nearly optimal data arrangement and a plan for reaching it when the device population changes. Compared to balancing algorithms in two other state-of-the-art systems, Derrick provides better capacity utilization, reduced data movement, and improved performance. Moreover, it can be easily adapted to meet custom placement requirements.
Event2Graph: Event-driven Bipartite Graph for Multivariate Time Series Forecasting and Anomaly Detection

Modeling inter-dependencies between time series is the key to achieve high performance in anomaly detection for multivariate time series data. The de-facto solution to model the dependencies is to feed the data into a recurrent neural network (RNN). However, the fully connected network structure underneath the RNN (either GRU or LSTM) assumes a static and complete dependency graph between time series, which may not hold in many real-world applications. To alleviate this assumption, we propose a dynamic bipartite graph structure to encode the inter-dependencies between time series. More concretely, we model time series as one type of nodes, and the time series segments (regarded as event) as another type of nodes, where the edge between two types of nodes describe a temporal pattern occurred on a specific time series at a certain time. Based on this design, relations between time series can be explicitly modeled via dynamic connections to event nodes, and the multivariate time series anomaly detection problem can be formulated as a self-supervised, edge stream prediction problem in dynamic graphs. We conducted extensive experiments to demonstrate the effectiveness of the design.
An empirical investigation of geodesic Gaussian bases for value function approximation

Diffusion wavelets, Laplacian eigenfunctions and geodesic Gaussians are basis functions recently proposed as useful for value function approximation within reinforcement learning. This thesis gives an empirical evaluation of geodesic Gaussian basis functions in comparison to the other two methods when applied to simple discrete grid world problems and more complex continuous problems using the LSPI algorithm. The geodesic Gaussian bases are shown to perform well on both problems.
Impact of Artificial Intelligence on Knowledge Sharing in the Workplace

The increasing use of digital communication tools in the workplace coupled with the ability of AI gives rise to new ways to capture knowledge from everyday communications such as work email and online meetings, and share this knowledge with others. While this has benefits for organisations, little is known of how employees may respond. The aim of this study is to examine factors that influence employees' willingness to share their knowledge knowing that their communications may be analysed, and the knowledge shared with others. Drawing on the Theory of Reasoned Action (TRA), this study examines the impact of motivating and inhibiting factors on knowledge sharing. The findings point to the importance of self-efficacy, reciprocity, and reputation for enhancing knowledge sharing in this context. However, concerns about being monitored may hinder knowledge sharing.
Bright-light distractions and visual performance

Visual distractions pose a significant risk to transportation safety, with laser attacks against aircraft pilots being a common example. This study used a research-grade High Dynamic Range (HDR) display to produce bright-light distractions for 12 volunteer participants performing a combined visual task across central and peripheral visual fields. The visual scene had an average luminance of 10 cd∙m−2 with targets of approximately 0.5° angular size, while the distractions had a maximum luminance of 9,000 cd∙m−2 and were 3.6° in size. The dependent variables were the mean fixation duration during task execution (representative of information processing time), and the critical stimulus duration required to support a target level of performance (representative of task efficiency). The experiment found a statistically significant increase in mean fixation duration, rising from 192 ms without distractions to 205 ms with bright-light distractions (p = 0.023). This indicates a decrease in visibility of the low contrast targets or an increase in cognitive workload that required greater processing time for each fixation in the presence of the bright-light distractions. Mean critical stimulus duration was not significantly affected by the distraction conditions used in this study. Future experiments are suggested to replicate driving and/or piloting tasks and employ bright-light distractions based on real-world data, and we advocate the use of eye-tracking metrics as sensitive measures of changes in performance.
Response to primary chemoradiotherapy of locally advanced oropharyngeal carcinoma is determined by the degree of cytotoxic T cell infiltration within tumor cell aggregates

Background Effective anti-tumor immune responses are mediated by T cells and require organized, spatially coordinated interactions within the tumor microenvironment (TME). Understanding coordinated T-cell-behavior and deciphering mechanisms of radiotherapy resistance mediated by tumor stem cells will advance risk stratification of oropharyngeal cancer (OPSCC) patients treated with primary chemoradiotherapy (RCTx). Methods To determine the role of CD8 T cells (CTL) and tumor stem cells for response to RCTx, we employed multiplex immunofluorescence stains on pre-treatment biopsy specimens from 86 advanced OPSCC patients and correlated these quantitative data with clinical parameters. Multiplex stains were analyzed at the single-cell level using QuPath and spatial coordination of immune cells within the TME was explored using the R-package Spatstat. Results Our observations demonstrate that a strong CTL-infiltration into the epithelial tumor compartment (HR for overall survival, OS: 0.35; p<0.001) and the expression of PD-L1 on CTL (HR: 0.36; p<0.001) were both associated with a significantly better response and survival upon RCTx. As expected, p16 expression was a strong predictor of improved OS (HR: 0.38; p=0.002) and correlated with overall CTL infiltration (r: 0.358, p<0.001). By contrast, tumor cell proliferative activity, expression of the tumor stem cell marker CD271 and overall CTL infiltration, regardless of the affected compartment, were not associated with response or survival. Conclusion In this study, we could demonstrate the clinical relevance of the spatial organization and the phenotype of CD8 T cells within the TME. In particular, we found that the infiltration of CD8 T cells specifically into the tumor cell compartment was an independent predictive marker for response to chemoradiotherapy, which was strongly associated with p16 expression. Meanwhile, tumor cell proliferation and the expression of stem cell markers showed no independent prognostic effect for patients with primary RCTx and thus requires further study.
Novel diagnostic techniques in interstitial lung disease

Research into novel diagnostic techniques and targeted therapeutics in interstitial lung disease (ILD) is moving the field toward increased precision and improved patient outcomes. An array of molecular techniques, machine learning approaches and other innovative methods including electronic nose technology and endobronchial optical coherence tomography are promising tools with potential to increase diagnostic accuracy. This review provides a comprehensive overview of the current evidence regarding evolving diagnostic methods in ILD and to consider their future role in routine clinical care.
Recent progress in fiber-based soft electronics enabled by liquid metal

Soft electronics can seamlessly integrate with the human skin which will greatly improve the quality of life in the fields of healthcare monitoring, disease treatment, virtual reality, and human-machine interfaces. Currently, the stretchability of most soft electronics is achieved by incorporating stretchable conductors with elastic substrates. Among stretchable conductors, liquid metals stand out for their metal-grade conductivity, liquid-grade deformability, and relatively low cost. However, the elastic substrates usually composed of silicone rubber, polyurethane, and hydrogels have poor air permeability, and long-term exposure can cause skin redness and irritation. The substrates composed of fibers usually have excellent air permeability due to their high porosity, making them ideal substrates for soft electronics in long-term applications. Fibers can be woven directly into various shapes, or formed into various shapes on the mold by spinning techniques such as electrospinning. Here, we provide an overview of fiber-based soft electronics enabled by liquid metals. An introduction to the spinning technology is provided. Typical applications and patterning strategies of liquid metal are presented. We review the latest progress in the design and fabrication of representative liquid metal fibers and their application in soft electronics such as conductors, sensors, and energy harvesting. Finally, we discuss the challenges of fiber-based soft electronics and provide an outlook on future prospects.