Miracle-dz/UniFAR-FTUs huggingface dataset:
Temporal prediction of oxygen uptake dynamics from wearable sensors during low-, moderate-, and heavy-intensity exercise

Oxygen consumption (V̇O2) provides established clinical and physiological indicators of cardiorespiratory function and exercise capacity. However, V̇O2 monitoring is largely limited to specialized laboratory settings, making its widespread monitoring elusive. Here, we investigate temporal prediction of V̇O2 from wearable sensors during cycle ergometer exercise using a temporal convolutional network (TCN). Cardiorespiratory signals were acquired from a smart shirt with integrated textile sensors alongside ground-truth V̇O2 from a metabolic system on twentytwo young healthy adults. Participants performed one rampincremental and three pseudorandom binary sequence exercise protocols to assess a range of V̇O2 dynamics. A TCN model was developed using causal convolutions across an effective history length to model the time-dependent nature of V̇O2. Optimal history length was determined through minimum validation loss across hyperparameter values. The best performing model encoded 218 s history length (TCN-VO2 A), with 187 s, 97 s, and 76 s yielding less than 3% deviation from the optimal validation loss. TCN-VO2 A showed strong prediction accuracy (mean, 95% CI) across all exercise intensities (−22 ml·min−1, [−262, 218]), spanning transitions from low-moderate (−23 ml·min−1, [−250, 204]), low-heavy (14 ml·min−1, [−252, 280]), ventilatory thresholdheavy (−49 ml·min−1, [−274, 176]), and maximal (−32 ml·min−1, [−261, 197]) exercise. Second-by-second classification of physical activity across 16090 s of predicted V̇O2 was able to discern between vigorous, moderate, and light activity with high accuracy (94.1%). This system enables quantitative aerobic activity monitoring in non-laboratory settings across a range of exercise intensities using wearable sensors for monitoring exercise prescription adherence and personal fitness.
Revisiting the Negative Data of Distantly Supervised Relation Extraction

Distantly supervision automatically generates plenty of training samples for relation extraction. However, it also incurs two major problems: noisy labels and imbalanced training data. Previous works focus more on reducing wrongly labeled relations (false positives) while few explore the missing relations that are caused by incompleteness of knowledge base (false negatives). Furthermore, the quantity of negative labels overwhelmingly surpasses the positive ones in previous problem formulations. In this paper, we first provide a thorough analysis of the above challenges caused by negative data. Next, we formulate the problem of relation extraction into as a positive unlabeled learning task to alleviate false negative problem. Thirdly, we propose a pipeline approach, dubbed ReRe, that first performs sentence classification with relational labels and then extracts the subjects/objects. Experimental results show that the proposed method consistently outperforms existing approaches and remains excellent performance even learned with a large quantity of false positive samples. Source code is available online at https://github.com/redreamality/RERE-relation-extraction.
Pseudo Pixel-level Labeling for Images with Evolving Content

Annotating images for semantic segmentation requires intense manual labor and is a time-consuming and expensive task especially for domains with a scarcity of experts, such as Forensic Anthropology. We leverage the evolving nature of images depicting the decay process in human decomposition data to design a simple yet effective pseudo-pixel-level label generation technique to reduce the amount of effort for manual annotation of such images. We first identify sequences of images with a minimum variation that are most suitable to share the same or similar annotation using an unsupervised approach. Given one user-annotated image in each sequence, we propagate the annotation to the remaining images in the sequence by merging it with annotations produced by a state-of-the-art CAM-based pseudo label generation technique. To evaluate the quality of our pseudo-pixel-level labels, we train two semantic segmentation models with VGG and ResNet backbones on images labeled using our pseudo labeling method and those of a state-of-the-art method. The results indicate that using our pseudo-labels instead of those generated using the state-of-the-art method in the training process improves the mean-IoU and the frequency-weighted-IoU of the VGG and ResNet-based semantic segmentation models by 3.36%, 2.58%, 10.39%, and 12.91% respectively.
Non-local Lagrangian mechanics: Noether’s theorem and Hamiltonian formalism

Lagrangian systems with a finite number of degrees of freedom that are non-local in time are studied. We obtain an extension of Noether’s theorem and Noether identities to this kind of Lagrangians. A Hamiltonian formalism has then been set up for these systems. n-order local Lagrangians can be treated as a particular case of non-local ones and standard results are recovered. The method is then applied to several other cases, namely two examples of non-local oscillators and the p-adic particle.
Generalization Error Bound for Hyperbolic Ordinal Embedding

Hyperbolic ordinal embedding (HOE) represents entities as points in hyperbolic space so that they agree as well as possible with given constraints in the form of entity i is more similar to entity j than to entity k. It has been experimentally shown that HOE can obtain representations of hierarchical data such as a knowledge base and a citation network effectively, owing to hyperbolic space's exponential growth property. However, its theoretical analysis has been limited to ideal noiseless settings, and its generalization error in compensation for hyperbolic space's exponential representation ability has not been guaranteed. The difficulty is that existing generalization error bound derivations for ordinal embedding based on the Gramian matrix do not work in HOE, since hyperbolic space is not inner-product space. In this paper, through our novel characterization of HOE with decomposed Lorentz Gramian matrices, we provide a generalization error bound of HOE for the first time, which is at most exponential with respect to the embedding space's radius. Our comparison between the bounds of HOE and Euclidean ordinal embedding shows that HOE's generalization error is reasonable as a cost for its exponential representation ability.
THERMODYNAMIC OPTIMIZATION AND CALCULATION OF THE ErCl3-CaCl2 SYSTEM

From measured phase diagram,the system of ErCl3-CaCl2 was optimized and calculated by the CALPHAD approach.The calculated phase diagram is eutectic and the eutectic point is 850.92K,46.0%(mole fraction)ErCl3.Enthalpy of mixing in liquid and interaction parameter of mixing enthalpy have been optimized and calculated in the system.These thermodynamic functions are important for fusion of rare-earth metal and their alloy.
Tropical Stratospheric Circulation and Ozone Coupled to Pacific Multi‐Decadal Variability

Observational and modeling evidence suggest a recent acceleration of the stratospheric Brewer‐Dobson circulation (BDC), driven by climate change and stratospheric ozone depletion. However, slowly varying natural variability can compromise our ability to detect such forced changes over the relatively short observational record. Using observations and chemistry‐climate model simulations, we demonstrate a link between multi‐decadal variability in the strength of the BDC and the Interdecadal Pacific Oscillation (IPO), with knock‐on impacts for composition in the stratosphere. After accounting for the IPO‐like variability in the BDC, the modeled trend is approximately 7%–10% dec−1 over 1979–2010. Furthermore, we find that sea surface temperatures explain up to 50% of the simulated decadal variability in tropical mid‐stratospheric ozone. Our findings demonstrate strong links between low‐frequency variability in the oceans, troposphere and stratosphere, as well as their potential importance in detecting structural changes in the BDC and future ozone recovery.
Simulation of wheat yield , water and nitrogen use efficiencies across Europe and North Africa

Arable farming systems in the Netherlands exhibit small yield gaps due to the use of upto-date technologies and of substantial amounts of inputs. In this context, it is important to understand the scope to increase/maintain crop yields while improving resource use efficiency (and reducing environmental footprint) through reductions in input use. The objective of this report is to quantify the magnitude, and to identify the biophysical and management determinants, of on-farm radiation (RUE), water (WUE) and nitrogen use efficiencies (NUE) for the main arable crops in the Netherlands. Individual field data from Dutch farms during the period 2015 2017 were used. The database was compiled through a commercial crop management software used by farmers. The sample used in this study was selected from a database of ca. 350.000 farm x field x crop x year combinations using as criteria the crop species (i.e., ware potato, seed potato, starch potato, sugar beet, spring onion, winter wheat and spring barley) and the completeness of the crop cycle, water and nutrient management information. A framework based on crop coefficients (kc) was used to estimate the potential yield (Yp), radiation intercepted and potential evapotranspiration (ETP) for each crop. Quantile regressions were used to identify ’best’ performing fields and multiple regressions were used to identify the biophysical and management determinants of on-farm crop yields and resource use efficiencies. Yield gaps ranged between 20% Yp for sugar beet and 55% for spring onion and were between 30 40% Yp for ware potato and cereal crops. The drivers of Ya were mostly related with water availability and sowing or harvest dates. The field-to-field variation observed in Ya and seasonal water available suggest there is scope to improve WUE, which can be best achieved through increases in Ya. The lack of yield responses to N indicate there is a large scope to further increase NUE and decrease N surplus, especially for ware potato and winter wheat crops. This is best achieved through decreases in N applied rather than through increases in Ya. Although these findings are only relevant to similar production systems in NW Europe, the underlying methods are generic and can be applied to similar datasets in other production systems.
The Costs and Benefits of a Child Allowance

This paper conducts a cost benefit analysis of making the $2,000 Child Tax Credit in the federal income tax fully refundable and the more generous child allowance in the American Family Act (AFA) of $3600 per child age 0-5 and $3000 per child age 6-17. We estimate costs with a micro-simulation analysis. We estimate benefits with a systematic literature review of the highest quality evidence on the causal effects of cash and near-cash transfers. We found 20 studies that met our stringent criteria; all but one found positive effects. For child beneficiaries we examine future earnings and taxes paid, education attainment, and four health outcomes: birth weight, neo-natal mortality, health between age one and death, and longevity. For parent beneficiaries, we examine effects on their health, mental health, and longevity. We also estimate the declines in health expenditures that are associated with the improvements in both child and parent health and declines in expenditures on other transfer programs, child protective services, and the criminal justice system. Our baseline estimates suggest that making the $2000 per Child Tax Credit fully refundable and increasing its generosity are both remarkably good investments. The initial investment of making the $2000 Child Tax Credit fully refundable is roughly $25 billion per year and the benefits for society are nearly $300 billion. The cost of the more generous child allowance in the American Family Act is $100 billion per year and the social benefits are over $800 billion. We also conducted several sensitivity analyses. The sensitivity analyses indicate that there is a fair range of uncertainty about precisely how good an investment the AFA is. The most plausible estimates range from being a very good to an extraordinarily good investment in our Nation’s future. The Costs and Benefits of a Child Allowance 2 | P a g e
A chemometrics approach to analyze volatile molecules released by post-mortem bovine fast-twitch muscles

ABSTRACT It is well known that beef produces volatile molecules. In this work, the detection of volatiles released by post-mortem bovine fast-twitch muscles (Musculus longissimus dorsi and Musculus cutaneus trunci) was done using GC/MS–SPME (gas chromatography/mass spectrum–solid-phase microextraction). The releases of volatile molecules were modeled against three factors (rigor-mortis, animal age and oxidative capacity) using a chemometrics approach (experimental design and partial least squares regression). The GC/MS–SPME technique produced more than 30 reproducible chromatographic peaks, but only 13 were associated significantly with two factors (rigor-mortis and animal age). The volatile profile was composed mainly of alcohols, aldehydes and alkanes. The factor “animal age” was the main variable related to the release of volatile molecules. The results strongly suggest that the release of volatile molecules change according to post-mortem metabolism and the animal age.
How do you socialize newcomers during a pandemic?

[ ]the frequency of interactions with insiders is the primary mechanism for transforming newcomers into insiders (Reichers, 1987) In one of the few studies that compared a traditional, face-to-face (social-based) orientation program with a computer-based orientation program (a self-guided, 2- to 3-day program that covered all of the same material as the traditional orientation through the use of multimedia technologies), Wesson and Gogus (2005) found that newcomers who participated in the computer-based orientation scored significantly lower on socially oriented socialization content areas [ ]participation in the computer-based orientation had a significant negative effect on job satisfaction and organizational commitment The way their organization conducts its business and functions might have changed;how it interacts with customers, clients, and patients will be different;jobs and roles might change;and new human resource policies and guidelines about the use of personal protective equipment and physical distancing will have
Fighting two pandemics at once: When COVID-19 meets racism

The Centers for Disease Control also suggest that racial/ethnic disparities in living and working conditions during the pandemic have led to increased health risks for these racial/ethnic minorities The self-determination theory includes the need for autonomy as one of the most important human needs to be fulfilled in order to ensure intrinsic motivation on the job (Deci & Ryan, 2000) [ ]under stressful situations, lacking control can influence the likelihood of counterproductive work behavior (Tucker etal , 2009) In the United States, because of the stigma associated with COVID-19, the two million small businesses owned by Asians are at particular risk of losing customers (Kwon, 2020) Since the U S declared a national emergency on March 13, Asian-owned businesses saw a 60% decrease in revenue (JP Morgan Chase and Company, 2020) [ ]although the COVID-19 pandemic may be contained one day, its influence on workers and organizations can be long lasting
Preparation and labeling of surface-modified magnetoferritin protein cages with a rhenium(I) carbonyl complex for magnetically targeted radiotherapy

New rhenium radiolabeled compounds are of general interest due to their nuclear characteristics which allow radiotherapy and in situ monitoring of tumor uptake. Biocompatible magnetic nanoparticles capable of transporting radionuclides, providing MRI contrast agent properties for imaging and a therapeutic effect in the target tissue simultaneously, are highly desirable. Herein we describe the preparation of magnetoferritin samples, and their labeling with rhenium in the form of the low oxidation state rhenium(I)–tricarbonyl complex, [Re(CO)3(H2O)3]+. A non-radioactive rhenium isotope (187Re) was used in all studies. The rhenium complex was conjugated covalently to the surface lysine groups of the protein cage via glutaraldehyde crosslinker and histidine modification. The analyses of conjugates were performed by inductively coupled plasma mass spectroscopy (ICP-MS) and size exclusion chromatography (SEC). Labeling efficiency was calculated as 22 ± 2 rhenium per protein cage. The in vitro stability of the rhenium carbonyl label was evaluated at room temperature and in human serum medium. It was found that 91.1 ± 1.8% rhenium was retained on the surface of the magnetoferritin cage following 72 h of dialysis. Prussian blue staining revealed the uptake of rhenium labeled nanocages preferentially into the human breast metastatic adenocarcinoma, MDA-MB-231 cells lines. The cytotoxicity assay carried out with the same cell lines showed that there is no significant cytotoxic effect up to 72 hours of incubation with 1 mg of labeled nanocages per mL (IC50 value).
AROMATIC POLYIMIDES CONTAINING POLAR NITRILE GROUPS

A series of polyimides containing nitrile groups has been synthesized by solution polycondensation reaction of two aromatic diamines having nitrile group and two ether linkages with various aromatic dianhydrides, namely 4,4'-oxidiphthalic dianhydride, benzophenonetetracarboxylic dianhydride and hexafluoroisopropylidene-diphthalic dianhydride. The polymers were easily soluble in polar organic solvents, such as N-methylpyrrolidone, N,N-dimethylfonnamide and N,N-dimethylacetamide, and gave flexible thin films by casting their solution. They present high thermal stability, with decomposition temperature being above 438°C. The polymers exhibited a glass transition temperature in the range of 203-284°C, with reasonable interval between glass transition and decomposition temperature.
Passionate Speech: On the Uses and Abuses of Anger in Public Debate

Abstract Anger dominates debates in the public sphere. In this article I argue that there are diverse forms of anger that merit different responses. My focus is especially on two types of anger that I label respectively arrogant and resistant. The first is the characteristic defensive response of those who unwarrantedly arrogate special privileges for themselves. The second is often a source of insight and a form of moral address. I detail some discursive manifestations of these two types of anger. I show that arrogant anger is responsible for attempts to intimidate and humiliate others with whom one disagrees. Whilst resistant anger can be intimidating, it is also essential in communicating moral demands.
Neural Representations of Task-relevant and Task-irrelevant Features of Attended Objects

Visual attention plays an essential role in selecting task-relevant and ignoring task-irrelevant information, for both object features and their locations. In the real world, multiple objects with multiple features are often simultaneously present in a scene. When spatial attention selects an object, how are the task-relevant and task-irrelevant features represented in the brain? Previous literature has shown conflicting results on whether and how irrelevant features are represented in visual cortex. In an fMRI task, we used a modified inverted encoding model (IEM, e.g., Sprague & Serences, 2015) to test whether we can reconstruct the task-relevant and task-irrelevant features of spatially attended objects in a multi-feature (color + orientation), multi-item display. Subjects were briefly shown an array of three colored, oriented gratings. Subjects were instructed as to which feature (color or orientation) was relevant before each block, and on each trial were asked to report the task-relevant feature of the object that appeared at a spatially pre-cued location, using a continuous color or orientation wheel. By applying the IEM, we achieved reliable feature reconstructions for the task-relevant features of the attended object from visual ROIs (V1 and V4v) and Intraparietal sulcus. Preliminary searchlight analyses showed that task-irrelevant features of attended objects could be reconstructed from activity in some intraparietal areas, but the reconstructions were much weaker and less reliable compared with task-relevant features. These results suggest that both relevant and irrelevant features may be represented in visual and parietal cortex but in different forms. Our method provides potential tools to noninvasively measure unattended feature representations and probe the extent to which spatial attention acts as a “glue” to bind task-relevant and task-irrelevant features.
Deamidation drives molecular aging of the SARS-CoV-2 spike receptor-binding motif

The spike is the main protein component of the SARS-CoV-2 virion surface. The spike receptor binding motif mediates recognition of the hACE2 receptor, a critical infection step, and is the preferential target for spike-neutralizing antibodies. Post-translational modifications of the spike receptor binding motif can modulate viral infectivity and immune response. We studied the spike protein in search for asparagine deamidation, a spontaneous event that leads to the appearance of aspartic and isoaspartic residues, affecting both the protein backbone and its charge. We used computational prediction and biochemical experiments to identify five deamidation hotspots in the SARS-CoV-2 spike. Similar deamidation hotspots are frequently found at the spike receptor-binding motifs of related sarbecoviruses, at positions that are mutated in emerging variants and in escape mutants from neutralizing antibodies. Asparagine residues 481 and 501 from the receptor-binding motif deamidate with a half-time of 16.5 and 123 days at 37 °C, respectively. This process is significantly slowed down at 4 °C, pointing at a strong dependence of spike molecular aging on the environmental conditions. Deamidation of the spike receptor-binding motif decreases the equilibrium constant for binding to the hACE2 receptor more than 3.5-fold. A model for deamidation of the full SARS-CoV-2 virion illustrates that deamidation of the spike receptor-binding motif leads to the accumulation in the virion surface of a chemically diverse spike population in a timescale of days. Our findings provide a mechanism for molecular aging of the spike, with significant consequences for understanding virus infectivity and vaccine development.
Decoding the effects of synonymous variants

Synonymous single nucleotide variants (sSNVs) are common in the human genome but are often overlooked. However, sSNVs can have significant biological impact and may lead to disease. Existing computational methods for evaluating the effect of sSNVs suffer from the lack of gold-standard training/evaluation data and exhibit over-reliance on sequence conservation signals. We developed synVep (synonymous Variant effect predictor), a machine learning-based method that overcomes both of these limitations. Our training data was a combination of variants reported by gnomAD (observed) and those unreported, but possible in the human genome (generated). We used positive-unlabeled learning to purify the generated variant set of any likely unobservable variants. We then trained two sequential extreme gradient boosting models to identify subsets of the remaining variants putatively enriched and depleted in effect. Our method attained 90% precision/recall on a previously unseen set of variants. Furthermore, although synVep does not explicitly use conservation, its scores correlated with evolutionary distances between orthologs in cross-species variation analysis. synVep was also able to differentiate pathogenic vs. benign variants, as well as splice-site disrupting variants (SDV) vs. non-SDVs. Thus, synVep provides an important improvement in annotation of sSNVs, allowing users to focus on variants that most likely harbor effects.