Miracle-dz/UniFAR-FTUs huggingface dataset:
A Generic NLI approach for Classification of Sentiment Associated with Therapies

This paper describes our system for addressing SMM4H 2023 Shared Task 2 on"Classification of sentiment associated with therapies (aspect-oriented)". In our work, we adopt an approach based on Natural language inference (NLI) to formulate this task as a sentence pair classification problem, and train transformer models to predict sentiment associated with a therapy on a given text. Our best model achieved 75.22\% F1-score which was 11\% (4\%) more than the mean (median) score of all teams' submissions.
History of LiDAR

LiDAR has a rich history of over 50 years. It started most of its development in the early 1960s, shortly after the invention of the laser. There had been some earlier LiDAR development prior to the invention of the laser, but the laser has been a critical enabler for LiDAR development. Wind sensing and laser designation were developed starting in the 1960s. I call laser designation a form of bistatic LiDAR because we have an illuminator, which is called the designator, and receiver, which is on the seeker. The illuminator and receiver are separated, so it is a bistatic system. Admittedly, the term LiDAR stands for light detection and ranging, and in a designator there is no ranging, but a designator does use a laser for illumination and a receiver for detection, so we will include it in the discussion of history. LiDAR has become relatively inexpensive and reliable, and has very rich phenomenology, making it competitive compared to alternative sensor technologies, such as passive EO sensing or microwave radar. LiDAR started operating in the visible region (ruby laser), then appeared in the near infrared (Nd:YAG lasers), and next in the thermal infrared (CO2 laser). Many LiDARs are now being developed in the eye-safe, short-wave infrared (SWIR) region (~1.5 μm and beyond).
Cadmium pollution caused by artisanal zinc-smelting in Hezhang county

Objective To investigate the current situation of cadmium pollution and environmental problems caused by artisanal zinc-smelting.Methods The urine samples of the residents,the samples of soil,eight kinds of common crops,four kinds of animal offal,and domestic water in polluted and control area were collected.The contents of cadmium in all samples were measured.The information on demographics and living behovior were collected with a questionnaire among 54 residents in polluted area and 40 residents in control area.Results The contents of cadmium in soil and domestic water from polluted area were 15.3314±8.0221 μg/g and 0.6485±0.2301 μg/L,and significantly higher than those from control area(2.0675±2.3716 μg/g and 0.0022±0.0009 μg/L,P0.01). The contents of cadmium in eight kinds of common crops and three kinds of animal offal from polluted area were higher than those from control area(P0.05). The level of uninary cadmium in exposure group was 9.57(2.55-47.75) μg/g Cr and significantly higher than that in control group(2.55[0.68-9.86]μg/gCr,P0.01). Conclusion The background level of cadmium in soil in the polluted area is higher than that of control area,and the level of cadmium is aggravated by artisanal zinc-smelting.The contents of cadmium in common crops,animal offal,domestic water and in the urine of the residents in polluted area are higher than those in control area.
Gas emission in the poultry production

Among the greenhouse gases produced in broiler chicken production environments, ammonia stands out for being present in higher concentrations and for significantly affecting human and animal health. Thus, this review evaluates the various sources of ammonia generation in animal production facilities, the damages caused by ammonia emissions in broiler chicken production facilities, and the accompanying economic losses. The main source of ammonia in broiler production is the nitrogen ingested in the diet, which is broken down into uric acid and, eventually, into ammonia that is volatilized from the bed to the environment. High ammonia concentrations in such facilities can affect productivity and result in economic losses. The effects on the environment are eutrophication of water bodies and ground water contamination. Ammonia emission control in poultry production facilities is therefore inevitable to avoid economic losses, prevent environmental damage, and increase feed efficiency
Evaluation of cloud computing modelling tools: simulators and predictive models

Experimenting with novel algorithms and configurations for the automatic management of Cloud Computing infrastructures is expensive and time consuming on real systems. Cloud computing delivers the benefits of using virtualisation techniques to data centers instead of physical servers for customers. However, it is still complex for researchers to test and run their experiments on data center due to the cost for repeating the experiments. To address this, various tools are available to enable simulators, emulators, mathematical models, statistical models and benchmarking. Despite this, there are different methods used by researchers to avoid the difficulty of conducting Cloud Computing research on actual large data centre infrastructure. However, it is still difficult to chose the best tool to evaluate the proposed research. This research focuses on investigating the level of accuracy of existing known simulators in the field of cloud computing. Simulation tools are generally developed for particular experiments, so there is little assurance that using them with different workloads will be reliable. Moreover, a predictive model based on a data set from a realistic data center is delivered as an alternative model of simulators as there is a lack of their sufficient accuracy. So, this work addresses the problem of investigating the accuracy of different modelling tools by developing and validating a procedure based on the performance of a target micro data centre. Key insights and contributions are: Involving three alternative models for Cloud Computing real infrastructure showing the level of accuracy of selected simulation tools. Developing and validating a predictive model based on a Raspberry Pi small scale data centre. The use of predictive model based on Linear Regression and Artificial Neural Net- works models based on training data set drawn from a Raspberry Pi Cloud infrastructure provides better accuracy.
Towards ultra-low-cost smartphone microscopy

The outbreak of COVID-19 exposed the inadequacy of our technical tools for home health surveillance, and recent studies have shown the potential of smartphones as a universal optical microscopic imaging platform for such applications. However, most of them use laboratory-grade optomechanical components and transmitted illuminations to ensure focus tuning capability and imaging quality, which keeps the cost of the equipment high. Here we propose an ultra-low-cost solution for smartphone microscopy. To realize focus tunability, we designed a seesaw-like structure capable of converting large displacements on one side into small displacements on the other (reduced to ∼9.1%), which leverages the intrinsic flexibility of 3D printing materials. We achieved a focus-tuning accuracy of ∼ 5 µm, which is 40 times higher than the machining accuracy of the 3D-printed lens holder itself. For microscopic imaging, we use an off-the-shelf smartphone camera lens as the objective and the built-in flashlight as the illumination. To compensate for the resulting image quality degradation, we developed a learning-based image enhancement method. We use the CycleGAN architecture to establish the mapping from smartphone microscope images to benchtop microscope images without pairing. We verified the imaging performance on different biomedical samples. Except for the smartphone, we kept the full costs of the device under 4 USD. We think these efforts to lower the costs of smartphone microscopes will benefit their applications in various scenarios, such as point-of-care testing, on-site diagnosis, and home health surveillance. Research highlights We propose a solution for ultra-low-cost smartphone microscopy. Utilizing the flexibility of 3D-printed material, we can achieve focusing accuracy of ∼ 5 µm. Such a low-cost device will benefit point-of-care diagnosis and home health surveillance.
A naturally occurring G11S mutation in the 3C‐like protease from the SARS‐CoV‐2 virus dramatically weakens the dimer interface

The 3C‐like protease (3CLpro) is crucial to the replication of SARS‐CoV‐2, the causative agent of COVID‐19, and is the target of several successful drugs including Paxlovid and Xocova. Nevertheless, the emergence of viral resistance underlines the need for alternative drug strategies. 3CLpro only functions as a homodimer, making the protein–protein interface an attractive drug target. Dimerization is partly mediated by a conserved glycine at position 11. However, some naturally occurring SARS‐CoV‐2 sequences contain a serine at this position, potentially disrupting the dimer. We have used concentration‐dependent activity assays and mass spectrometry to show that indeed the G11S mutation reduces the stability of the dimer by 600‐fold. This helps to set a quantitative benchmark for the minimum potency required of any future protein–protein interaction inhibitors targeting 3CLpro and raises interesting questions regarding how coronaviruses bearing such weakly dimerizing 3CLpro enzymes are capable of replication.
Conjectural criteria for the most singular points of the Hilbert schemes of points

We provide conjectural necessary and (separately) sufficient conditions for the Hilbert scheme of points of a given length to have the maximum dimension tangent space at a point. The sufficient condition is claimed for 3D and reduces the original problem to a problem in convex geometry. Proving either of the two conjectural statements will in particular resolve a long-standing conjecture by Brian\c{c}on and Iarrobino back in the '70s for the case of the powers of the maximal ideal. Furthermore, for specific classes of lengths, we conjecturally classify points satisfying the conjectural sufficient conditions. This in particular (conjecturally) provides many new explicit families of examples of maximum dimension tangent space at a point of the Hilbert schemes of points of lengths strictly between two consecutive tetrahedral numbers ${3+k \choose 3}$.
Cardiorespiratory fitness is associated with neuroelectric activity complexity in children with overweight or obesity

Cardiorespiratory fitness is one of the most important markers of health. Several studies have demonstrated the relationship between cardiorespiratory fitness and brain functioning in healthy children. Some of these works suggested that cardiorespiratory fitness may have a protective role on the executive function, which represents a set of cognitive mechanisms used to control and coordinate other cognitive abilities. This is particularly relevant in children with overweight or obesity. In these studies, neuroelectric activity is recorded using medical imaging techniques or electroencephalography (EEG). Among the EEG studies, analyses based on the P3 event related potential stand out. However, complementary analyses are necessary to understand the neural mechanisms underlying the associations between cardiorespiratory fitness and brain functioning. EEG complexity, a useful feature that measures the regularity of neuroelectric activity, has been previously associated with cardiorespiratory fitness in adolescents. In this work, we evaluate this association in a group of 87 Caucasian children with overweight/obesity. Our results reveal that the children with higher cardiorespiratory fitness present less EEG complexity while performing a cognitive task that challenges the executive function. In addition, they suggest that the line length, the metric that we used to estimate EEG complexity, performs equally well as those metrics based on the P3 and better than other complexity metrics like sample entropy, as an indicator of cardiorespiratory fitness. Finally, the line length has advantages over the P3: more consistency across EEG regions and cognitive loads, lower experimental complexity, lower computational cost, and higher automatization capability.
Nonlocal quantum differentiation between polarization objects using entanglement

For a wide range of applications a fast, non-destructive, remote, and sensitive identification of samples with predefined characteristics is preferred instead of their full characterization. Here, we report on the experimental implementation of a nonlocal quantum measurement scheme enabling to distinguish different transparent and birefringent samples by means of polarization-entangled photon pairs and remote state preparation. On an example set of more than 80 objects with varying Mueller matrices we show that only two coincidence measurements are already sufficient for successful discrimination in contrast to at least 8 required for a comprehensive inspection. The decreased number of measurements and the sample set significantly exceeding a typical set size for various problems demonstrate the high potential of the method for applications aiming at biomedical diagnostics, remote sensing, and other classification/detection tasks.
Prognostic value of isolated tumor cells in sentinel lymph nodes in low risk endometrial cancer: results from an international multi-institutional study

Objective The prognostic significance of isolated tumor cells (≤0.2 mm) in sentinel lymph nodes (SLNs) of endometrial cancer patients is still unclear. Our aim was to assess the prognostic value of isolated tumor cells in patients with low risk endometrial cancer who underwent SLN biopsy and did not receive adjuvant therapy. Outcomes were compared with node negative patients. Methods Patients with SLNs–isolated tumor cells between 2013 and 2019 were identified from 15 centers worldwide, while SLN negative patients were identified from Mayo Clinic, Rochester, between 2013 and 2018. Only low risk patients (stage IA, endometrioid histology, grade 1 or 2) who did not receive any adjuvant therapy were included. Primary outcomes were recurrence free, non-vaginal recurrence free, and overall survival, evaluated with Kaplan–Meier methods. Results 494 patients (42 isolated tumor cells and 452 node negative) were included. There were 21 (4.3%) recurrences (5 SLNs–isolated tumor cells, 16 node negative); recurrence was vaginal in six patients (1 isolated tumor cells, 5 node negative), and non-vaginal in 15 (4 isolated tumor cells, 11 node negative). Median follow-up among those without recurrence was 2.3 years (interquartile range (IQR) 1.1–3.0) and 2.6 years (IQR 0.6–4.2) in the SLN–isolated tumor cell and node negative patients, respectively. The presence of SLNs-isolated tumor cells, lymphovascular space invasion, and International Federation of Obstetrics and Gynecology (FIGO) grade 2 were significant risk factors for recurrence on univariate analysis. SLN–isolated tumor cell patients had worse recurrence free survival (p<0.01) and non-vaginal recurrence free survival (p<0.01) compared with node negative patients. Similar results were observed in the subgroup of patients without lymphovascular space invasion (n=480). There was no difference in overall survival between the two cohorts in the full sample and the subset excluding patients with lymphovascular space invasion. Conclusions Patients with SLNs–isolated tumor cells and low risk profile, without adjuvant therapy, had a significantly worse recurrence free survival compared with node negative patients with similar risk factors, after adjusting for grade and excluding patients with lymphovascular space invasion. However, the presence of SLNs–isolated tumor cells was not associated with worse overall survival.
Merging by Matching Models in Task Subspaces

Model merging aims to cheaply combine individual task-specific models into a single multitask model. In this work, we view past merging methods as leveraging different notions of a ''task subspace'' in which models are matched before being merged. We connect the task subspace of a given model to its loss landscape and formalize how this approach to model merging can be seen as solving a linear system of equations. While past work has generally been limited to linear systems that have a closed-form solution, we consider using the conjugate gradient method to find a solution. We show that using the conjugate gradient method can outperform closed-form solutions, enables merging via linear systems that are otherwise intractable to solve, and flexibly allows choosing from a wide variety of initializations and estimates for the ''task subspace''. We ultimately demonstrate that our merging framework called ''Matching Models in their Task Subspace'' (MaTS) achieves state-of-the-art results in multitask and intermediate-task model merging. We release all of the code and checkpoints used in our work at https://github.com/r-three/mats.
A Masked Pruning Approach for Dimensionality Reduction in Communication-Efficient Federated Learning Systems

Federated Learning (FL) represents a growing machine learning (ML) paradigm designed for training models across numerous nodes that retain local datasets, all without directly exchanging the underlying private data with the parameter server (PS). Its increasing popularity is attributed to notable advantages in terms of training deep neural network (DNN) models under privacy aspects and efficient utilization of communication resources. Unfortunately, DNNs suffer from high computational and communication costs, as well as memory consumption in intricate tasks. These factors restrict the applicability of FL algorithms in communication-constrained systems with limited hardware resources. In this paper, we develop a novel algorithm that overcomes these limitations by synergistically combining a pruning-based method with the FL process, resulting in low-dimensional representations of the model with minimal communication cost, dubbed Masked Pruning over FL (MPFL). The algorithm operates by initially distributing weights to the nodes through the PS. Subsequently, each node locally trains its model and computes pruning masks. These low-dimensional masks are then transmitted back to the PS, which generates a consensus pruning mask, broadcasted back to the nodes. This iterative process enhances the robustness and stability of the masked pruning model. The generated mask is used to train the FL model, achieving significant bandwidth savings. We present an extensive experimental study demonstrating the superior performance of MPFL compared to existing methods. Additionally, we have developed an open-source software package for the benefit of researchers and developers in related fields.
Jurnal Pendidikan Jasmani dan Olahraga

Emotional intelligence measurement is a potentially important construct and has become one of the most exciting issues in psychological research. This study aimed to test the construct validity of the emotional intelligence scale developed for sports students. The research employed a quantitative approach using a survey method. Participants involved in this study were 280 active sports students. Data were collected through an emotional intelligence scale and analyzed using factor analysis, namely exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) methods on Structural Equation Modeling (SEM) using AMOS 22 software. The fit index test model was based on three categories: absolute fit indices, incremental fit indices, and parsimony fit indices. It indicates that the scale met the valid and reliable criteria for measuring the emotional intelligence of sports students. There were 27 question items declared valid, meaning that all of these items measured the five components, including 14 indicators constructed according to the Bar - on conceptual model.
Canvi ambiental global al municipi de Viladrau

Global environmental change in the municipality of Viladrau The main aim of this study was to evaluate environmental change in the municipality of Viladrau. To this end, climate change was analysed through its effect on biodiversity, hydrology, vegetation cover and land use, and logging systems. Each of the points was dealt with from a different perspective. Vegetation cover and land use were analysed on the basis of the information drawn from S. Llobet’s map (1947), the DARP (1995), cadastral registers for Viladrau (1905, 1953 and 2002) and records kept by Viladrau Town Council on logging for the periods 19391943 and 1979-1983. The other variables studied to demonstrate the existence of global change confirmed the changes detected. The environmental changes observed in the municipality of Viladrau were as follows: a trend towards higher average annual temperatures; change in the altitudinal distribution of the land cover (Mediterraneanisation) with beech forests left isolated by expanding holm oak forests; reduction of animal biodiversity; disappearance of native species such as the southwestern water vole (Arvicola sapidus); appearance of non-native species, some of them bioinvasive, such as the Douglas fir; increase in the area covered by deciduous oak at the expense of holm oak, due to a cultural and economic change; and generally a sharp increase in coppice forest, less farmland and more pine. The interpretation of the results comes as a combination of all the factors for environmental change analysed in the study, as they cannot be analysed independently. It is the interaction of all of them that highlights the existence of environmental change. The switch from an economy based on the primary sector to one that is totally dependent on the tertiary sector can be considered as the catalyst of all these changes.
The evolution and convergence of mutation spectra across mammals

Despite the key role genetic mutations play in shaping phenotypic differences between species, little is currently known about the evolution of germline mutation spectra across mammals. Domesticated species are likely particularly interesting case studies because of their high mutation rates and complex evolutionary histories, which can span multiple founding events and genetic bottlenecks. Here we have developed a new reusable workflow, nSPECTRa, that can undertake the key steps in characterising mutation spectra, from determining ancestral alleles to characterising multiple forms of variation. We apply nSPECTRa to seven species, including several that have undergone domestication, and highlight how nSPECTRa can provide important novel insights into mutation rate evolution. While mutation spectra most often show marked differences between species and even breeds, certain mutation types have risen to a high frequency in subpopulations of different species, indicative of convergent evolution in mutation rates. This includes the previously characterized TCC->TTC change enriched among European humans, which is also enriched among East Asian cattle. We show Indicine cattle are particularly interesting examples of how different mutation spectra segregate within a population and subsequently spread across the globe. Together, this work has important implications for understanding the control and evolution of mammalian mutation rates.