Miracle-dz/UniFAR-FTUs huggingface dataset:
Global expectations mediate local constraint: evidence from concessive structures

ABSTRACT Numerous studies have found facilitation for lexical processing in highly constraining contexts. However, less is known about cases in which immediately preceding (local) and broader (global) contextual constraint conflict. In two eye-tracking while reading experiments, local and global context were manipulated independently, creating a critical condition where local context biases towards a word that is incongruent with global context. Global context consisted of a clause introduced by a concessive marker generating broad expectations about upcoming material. Experiment 1 compared high- and low-predictability critical words, whereas Experiment 2 held the critical word constant and manipulated the preceding verb to impose different levels of local constraint. Facilitation from local context was reduced when it was incongruent with global context, supporting models in which information from global and local context is rapidly integrated during early lexical processing over models that would initially prioritise only local or only global context.
Network Pruning for Bit-Serial Accelerators

Bit-serial architectures (BSAs) are becoming increasingly popular in low-power neural network processor (NNP) designs for edge scenarios. However, the performance and energy efficiency of state-of-the-art BSA NNPs heavily depends on both the proportion and distribution of ineffectual weight bits in neural networks (NNs). To boost the performance of typical BSA accelerators, we present Bit-Pruner, a software approach to learn BSA-favored NNs without resorting to hardware modifications. Bit-Pruner not only progressively prunes but also restructures the nonzero bits in weights so that the number of nonzero bits in the model can be reduced and the corresponding computing can be load-balanced to suit the target BSA accelerators. On top of Bit-Pruner, we further propose a Pareto frontier optimization algorithm to adjust the bit-pruning rate across network layers and fulfill diverse NN processing requirements in terms of performance and accuracy for various edge scenarios. However, an aggressive Bit-Pruner can lead to nontrivial accuracy loss, especially for lightweight NNs and complex tasks. To this end, the alternating direction method of multipliers (ADMMs) is adapted to the retraining phase in Bit-Pruner to smooth the abrupt disturbance due to bit-pruning and enhance the resulting model accuracy. According to the experiments, Bit-Pruner increases the bit-sparsity up to 94.4% with negligible accuracy degradation and achieves an optimized tradeoff between NN accuracy and energy efficiency even under very-aggressive performance constraints. When pruned models are deployed onto typical BSA accelerators, the average performance is $2.1\times $ and $1.6\times $ higher than the baseline networks without pruning and those with classical weight pruning, respectively.
Epileptic Disorder Detection of Seizures Using EEG Signals

Epilepsy is a nervous system disorder. Encephalography (EEG) is a generally utilized clinical approach for recording electrical activity in the brain. Although there are a number of datasets available, most of them are imbalanced due to the presence of fewer epileptic EEG signals compared with non-epileptic EEG signals. This research aims to study the possibility of integrating local EEG signals from an epilepsy center in King Abdulaziz University hospital into the CHB-MIT dataset by applying a new compatibility framework for data integration. The framework comprises multiple functions, which include dominant channel selection followed by the implementation of a novel algorithm for reading XLtek EEG data. The resulting integrated datasets, which contain selective channels, are tested and evaluated using a deep-learning model of 1D-CNN, Bi-LSTM, and attention. The results achieved up to 96.87% accuracy, 96.98% precision, and 96.85% sensitivity, outperforming the other latest systems that have a larger number of EEG channels.
How Artificial Intelligence in Imaging Can Better Serve Patients with Bronchial and Parenchymal Lung Diseases?

With the rapid development of computing today, artificial intelligence has become an essential part of everyday life, with medicine and lung health being no exception. Big data-based scientific research does not mean simply gathering a large amount of data and letting the machines do the work by themselves. Instead, scientists need to identify problems whose solution will have a positive impact on patients’ care. In this review, we will discuss the role of artificial intelligence from both physiological and anatomical standpoints, starting with automatic quantitative assessment of anatomical structures using lung imaging and considering disease detection and prognosis estimation based on machine learning. The evaluation of current strengths and limitations will allow us to have a broader view for future developments.
Basics of Sustainable Diets and Tools for Assessing Dietary Sustainability: A Primer for Researchers and Policy Actors

Climate change can have economic consequences, affecting the nutritional intake of populations and increasing food insecurity, as it negatively affects diet quality parameters. One way to mitigate these consequences is to change the way we produce and consume our food. A healthy and sustainable diet aims to promote and achieve the physical, mental, and social well-being of the populations at all life stages, while protecting and safeguarding the resources of the planet and preserving biodiversity. Over the past few years, several indexes have been developed to evaluate dietary sustainability, most of them based on the EAT-Lancet reference diet. The present review explains the problems that arise in human nutrition as a result of climate change and presents currently available diet sustainability indexes and their applications and limitations, in an effort to aid researchers and policy actors in identifying aspects that need improvement in the development of relevant indexes. Overall, great heterogeneity exists among the indicators included in the available indexes and their methodology. Furthermore, many indexes do not adequately account for the diets’ environmental impact, whereas others fall short in the economic impact domain, or the ethical aspects of sustainability. The present review reveals that the design of one environmentally friendly diet that is appropriate for all cultures, populations, patients, and geographic locations is a difficult task. For this, the development of sustainable and healthy diet recommendations that are region-specific and culturally specific, and simultaneously encompass all aspects of sustainability, is required.
CHEMICAL AND TECHNOLOGICAL STUDIES ON KHALAS DATE SEEDS POWDER

: This study was aimed to estimate the nutritional value of khalas date seed powder and pita bread, prepared by replacing 5, 10, 15 and 20% of wheat flour by khalas date seed powder. Results indicated that the content of carbohydrate (%), protein (%), crude fibre (%), crude oil (%), ash (%), of khalas date seeds were 64.3, 4.69, 17.12, 4.62, and 1.09%, respectively. The total phenolic content (TPC), total flavonoids and radical scavenging activity (%RSA) were 430.43±1.2 mg GAE/100 g, 346. 13 mg RE/100 g and 79.12±1.9%, respectively. The seed oils contained 51.42% saturated fatty acids and 48.58% unsaturated fatty acids. Fiber content of whole wheat pita bread was higher compared to regular pita bread. It remained lower in 5% date seed powder bread, was quite similar in 10% date seed powder bread, and increased to 9.08% in 20% date seed powder bread compared to whole wheat pita bread. The total phenols, total flavonoids and radical scavenging activity content of pita bread fortified with date seeds increased as the amount of date seeds increased. The pita bread with20% date seeds had the highest percent for each of total phenols, total flavonoids and radical scavenging activity which valued 187.11 mg/100g, 235.45 mg RE/100 g and 43.38%, respectively. While control regular pita contained 72.31 mg/100g, 41.42 mg RE/100 g and 3.53%, respectively. Pita bread supplemented with 15% date seeds, showed high score in overall acceptability when compared to control pita bread and other various concentrations of pits. Generally, changes in dough properties were greater using different concentrations of date seeds with differences for overall acceptability and had high acceptability compared to control pita bread .
How South Africa Governing Their Services Contract in Public Private Partnership: A Systemic Review Study

Governance is very important in the commitment to continue cooperation in the public-private partnership (PPP). By using the literature study method, this research tries to explain the forms of partnerships that exist in the South African country. Based on research with the theme of PPP in the South African country. Based on the information gathered in this article, there are 3 issues found in PPP in South Africa: health, food security, and public services. This study also explains the variables that exist in PPP management such as actors, regulations, and service arrangements. In general, the government still plays an important role in partnerships with the private sector, so it is still difficult to clarify the pattern of work contracts.
Hybrid-mixed finite elements on polytopal meshes for two-scale elasticity models with relaxed symmetry

The focus is on two-scale ﬁnite element spaces for stable stress mixed formulations of linear elasticity problems with relaxed symmetry. For that, we consider ﬁnite element H(div)-conforming tensor approximations for the discretization of the stress variable based on general polyhedral meshes with ﬂat faces (polytopes). Tensor normal trace components (traction) are kept constrained to a given coarse ﬁnite dimensional space, piecewise deﬁned over a partition of the mesh skeleton (facets). Internal tensor components are piecewise deﬁned over partitions of the subdomains, and they may be enriched in diﬀerent extents: with respect to internal mesh size, internal polynomial degree, or both. The subdomain grids do not have to match across the interfaces, but a mild compatibility constraint is required. The method is designed in a hybrid mixed framework, where displacement and rotation ﬁelds are introduced to impose divergence and symmetry constraints. Their approximations should be compatible with the tensor spaces in the sense of the inf-sup stability condition. In a local-global context, a global problem is solved at the coarser level for the traction ﬁeld and for piecewise rigid motions. The ﬁne details of the solution are obtained by local Neumann problems in each polytopal subdomain, the traction playing the role of boundary data. Stability and error estimates are proved for the method based on two-scale versions of a variety of known stable single-scale space settings used to solve the local Neumann problems. The approximate stress and displacement are row-wise formed by standard Poisson-compatible ﬁnite element pairs. The analysis also holds when the tensor spaces are enriched by some extra divergence-free bubble matrices. Enhanced accuracy rates for displacement and super-convergent divergence of the stress can be obtained. Stress, rotation, and stress symmetry errors keep the same accuracy order determined by the traction discretisation.
Severe Complications after General Anesthesia versus Sedation during Pediatric Diagnostic Cardiac Catheterization for Ventricular Septal Defect

Pediatric cardiac catheterization requires unconsciousness and immobilization through general anesthesia or sedation. This study aimed to compare the occurrence of severe complications in pediatric diagnostic cardiac catheterization for ventricular septal defect between general anesthesia and sedation performed under similar institutional environments. Using the Japanese Diagnosis Procedure Combination database, we retrospectively identified pediatric patients (aged <2 years) who underwent diagnostic cardiac catheterization for ventricular septal defect between July 2010 and March 2019. The composite outcome was the occurrence of severe complications, including catecholamine use and intensive care unit admission, within seven days after catheterization. Overlap weighting based on propensity scores was used to adjust for patient- and hospital-level confounding factors. We identified 3159 patients from 87 hospitals, including 930 under general anesthesia and 2229 under sedation. The patient- and hospital-level baseline characteristics differed between the groups. After adjustment, the proportion of patients with severe complications was significantly higher in the general anesthesia group than in the sedation group (2.4% vs. 0.6%; risk difference, 1.8% [95% confidence interval, 0.93–2.6%]). Severe complications occurred more frequently in the general anesthesia group than in the sedation group. Further research on anesthetic methods is necessary to assess the safety and accuracy of pediatric diagnostic cardiac catheterization.
Hepatitis B Virus Research in South Africa

Despite being vaccine-preventable, hepatitis B virus (HBV) infection remains the seventh leading cause of mortality in the world. In South Africa (SA), over 1.9 million people are chronically infected with HBV, and 70% of all Black chronic carriers are infected with HBV subgenotype A1. The virus remains a significant burden on public health in SA despite the introduction of an infant immunization program implemented in 1995 and the availability of effective treatment for chronic HBV infection. In addition, the high prevalence of HIV infection amplifies HBV replication, predisposes patients to chronicity, and complicates management of the infection. HBV research has made significant progress leading to better understanding of HBV epidemiology and management challenges in the SA context. This has led to recent revision of the national HBV infection management guidelines. Research on developing new vaccines and therapies is underway and progress has been made with designing potentially curative gene therapies against HBV. This review summarizes research carried out in SA on HBV molecular biology, epidemiology, treatment, and vaccination strategies.
Recombinant Viral Vectors for Therapeutic Programming of Tumour Microenvironment: Advantages and Limitations

Viral vectors have been widely investigated as tools for cancer immunotherapy. Although many preclinical studies demonstrate significant virus-mediated tumour inhibition in synergy with immune checkpoint molecules and other drugs, the clinical success of viral vector applications in cancer therapy currently is limited. A number of challenges have to be solved to translate promising vectors to clinics. One of the key elements of successful virus-based cancer immunotherapy is the understanding of the tumour immune state and the development of vectors to modify the immunosuppressive tumour microenvironment (TME). Tumour-associated immune cells, as the main component of TME, support tumour progression through multiple pathways inducing resistance to treatment and promoting cancer cell escape mechanisms. In this review, we consider DNA and RNA virus vectors delivering immunomodulatory genes (cytokines, chemokines, co-stimulatory molecules, antibodies, etc.) and discuss how these viruses break an immunosuppressive cell development and switch TME to an immune-responsive “hot” state. We highlight the advantages and limitations of virus vectors for targeted therapeutic programming of tumour immune cell populations and tumour stroma, and propose future steps to establish viral vectors as a standard, efficient, safe, and non-toxic cancer immunotherapy approach that can complement other promising treatment strategies, e.g., checkpoint inhibitors, CAR-T, and advanced chemotherapeutics.
Design, Synthesis, DFT, TD-DFT/PCM Calculations, and Molecular Docking Studies on the Anti-COVID-19, and Anti-SARS Activities of Some New Bis-Thiazoles and Bis-Thiadiazole

Abstract A novel synthesis of bis(thiazoles) and bis(thiadiazole), each connected to a thienothiophene moiety, is described. The DFT calculations support the favored synthesis of one of the anticipated bis(thiazole) regioisomers. The B3LYP/6-311G** level of theory was used to optimize quantum mechanical calculations of geometrical characteristics and energy of new compounds under study. The electronic absorption of the new compounds in ethanol solvent was handled and finished using time-dependent-density functional theory (TD-DFT) at the B3LYP/6-31G(d,p) level with the addition of the polarizable continuum solvation technique TD-DFT/PCM. The permissible singlet transitions are identified, and their involvements in the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) are described. Natural bond orbital (NBO) analysis was used to investigate hyper conjugative partnerships, molecular stability, and bond strength. Mean polarizability, total static dipole moment, anisotropy of polarizability, and mean first-order hyperpolarizability have all been computed. The results reveal that the compounds are promising contenders for non-linear optical materials. The molecular docking mechanism between ligands 8a–8c and COVID-19/5epw or SARS/5wrg receptors was done to explore the binding modes of these compounds at the active sites. Molecular docking results have shown that the compounds 8a–8c can be considered as a potential agent against COVID-19/5epw and SARS/5wrg receptors. Graphical Abstract
scHOIS: Determining Cell Heterogeneity Through Hierarchical Clustering Based on Optimal Imputation Strategy

Advances in single-cell RNA sequencing (scRNA-seq) technology provide an unbiased and high-throughput analysis of each cell at single-cell resolution, and further facilitate the development of cellular heterogeneity analysis. Despite the promise of scRNA-seq, the data generated by this method are sparse and noisy because of the presence of dropout events, which can greatly impact downstream analyses such as differential gene expression, cell type annotation, and linage trajectory reconstruction. The development of effective and robust computational methods to address both dropout and clustering are thus urgently needed. In this study, we propose a flexible, accurate two-stage algorithm for single cell heterogeneity analysis via hierarchical clustering based on an optimal imputation strategy, called scHOIS. At the first stage, masked non-negative matrix factorization is applied to approximate the original observed scRNA-seq data, with optimal rank determined by variance analysis. At the second stage, hierarchical clustering is applied to group the imputed cells using Pearson correlation to measure similarity, with the optimal number of clusters determined by integrating three classical indexes. We performed extensive experiments on real-world datasets, which showed that scHOIS effectively and robustly distinguished cellular differences and that the clustering performance of this algorithm was superior to that of other state-of-the-art methods.
Absorption and emission line studies of gas in the Milky Way halo

We perform a systematic study of physical properties and distribution of neutral and ionised gas in the halo of the Milky Way (MW). Beside the large neutral intermediate- and high-velocity cloud (IVC, HVC) complexes there exists a population of partly ionised gaseous structures with low-column densities that have a substantial area filling factor. The origin and nature of these structures are still under debate. We analyse the physical parameters of the MW halo gas and the relation to quasar (QSO) metal-absorption line systems at low and high redshifts. For this purpose we combine new HI 21-cm data from the EBHIS and GASS surveys with optical quasar absorption line data to study the filling factor and distribution of these gaseous clouds in the halo at HI densities below 10^19 1/cm^2. This study is important to understand the evolution of the MW in particular and the gas accretion mechanisms of galaxies in general.
Raman scattering in a Heisenberg {\boldmath $S=1/2$} antiferromagnet on the triangular lattice

We investigate two-magnon Raman scattering from the $S=1/2$ Heisenberg antiferromagnet on the triangular lattice, considering both the effect of renormalization of the one-magnon spectrum by 1/S corrections and final-state magnon-magnon interactions. The bare Raman intensity displays two peaks related to one-magnon van-Hove singularities. We find that 1/S self-energy corrections to the one-magnon spectrum strongly modify this intensity profile. The central Raman-peak is significantly enhanced due to plateaus in the magnon dispersion, the high frequency peak is suppressed due to magnon damping, and the overall spectral support narrows considerably. Additionally we investigate final-state interactions by solving the Bethe-Salpeter equation to $O(1/S)$. In contrast to collinear antiferromagnets, the non-collinear nature of the magnetic ground state leads to an irreducible magnon scattering which is retarded and non-separable already to lowest order. We show that final-state interactions lead to a rather broad Raman-continuum centered around approximately twice the 'roton'-energy. We also discuss the dependence on the scattering geometry.
Sunitinib versus Pazopanib Dilemma in Renal Cell Carcinoma: New Insights into the In Vitro Metabolic Impact, Efficacy, and Safety

Sunitinib and pazopanib are tyrosine kinase inhibitors (TKIs) used as first-line therapy for metastatic renal cell carcinoma (RCC). Although these TKIs are associated with similar survival outcomes, some differences have been reported in their safety profiles. In this work, traditional toxicological endpoints (cell viability and growth, oxidative stress, and nuclear morphology) and 1H NMR spectroscopy-based metabolomics analysis were used to provide new insights into the cytotoxicity and metabolic mechanisms underlying sunitinib and pazopanib treatments. Tumoral (Caki-1) and non-tumoral (HK-2) human renal cells were exposed to clinically relevant concentrations of sunitinib (2 µM) or pazopanib (50 µM). Sunitinib showed selectivity for cancer cells, inhibiting proliferation, and inducing apoptotic death of Caki-1 cells, whereas pazopanib had a similar cytotoxic effect in both tumoral and non-tumoral cells. 1H-NMR metabolomics unveiled a higher impact of sunitinib on the levels of intracellular metabolites of Caki-1 cells (seven dysregulated metabolites), suggesting dysregulations on amino acid, glutathione and glycerophospholipid metabolisms. In contrast, pazopanib had a higher impact on the levels of extracellular metabolites of Caki-1 cells (seven dysregulated metabolites in culture medium), unveiling alterations on amino acid and energetic metabolisms. In HK-2 cells, sunitinib caused only a minor increase in intracellular isoleucine levels, whereas pazopanib induced several alterations on the intracellular (three dysregulated metabolites) and extracellular (three dysregulated metabolites) compartments suggesting changes on amino acid, glycerophospholipid, and energy metabolisms. Our results demonstrate that these TKIs elicit distinct cellular and metabolic responses, with sunitinib showing better in vitro efficacy against target RCC cells and lesser nephrotoxic potential than pazopanib.