Miracle-dz/UniFAR-FTUs huggingface dataset:
eNose breath prints as a surrogate biomarker for classifying patients with asthma by atopy

Mahmoud I. Abdel-Aziz, MSc, Paul Brinkman, PhD, Susanne J. H. Vijverberg, PhD, Anne H. Neerincx, PhD, Rianne de Vries, MSc, Yennece W. F. Dagelet, RN, John H. Riley, PhD, Simone Hashimoto, MD, PhD, Paolo Montuschi, MD, Kian Fan Chung, MD, DSc, Ratko Djukanovic, MD, PhD, Louise J. Fleming, MD, Clare S. Murray, MD, Urs Frey, MD, PhD, Andrew Bush, MD, FRCP, FRCPCH, Florian Singer, MD, PhD, Gunilla Hedlin, MD, PhD, Graham Roberts, MD, PhD, Sven-Erik Dahl en, MD, PhD, Ian M. Adcock, PhD, Stephen J. Fowler, MD, PhD, Karen Knipping, MSc, Peter J. Sterk, MD, PhD, Aletta D. Kraneveld, PhD, and Anke H. Maitland-van der Zee, PharmD, PhD, on behalf of the U-BIOPRED Study Group, and the Amsterdam UMC Breath Research Group Amsterdam, Utrecht, and Reeuwijk, The Netherlands; Assiut, Egypt; Stockley Park, London, Southampton, and Manchester, United Kingdom; Rome, Italy; Basel and Bern, Switzerland; and Stockholm, Sweden
L2BEC2: Local Lightweight Bidirectional Encoding and Channel Attention Cascade for Video Frame Interpolation

Video frame interpolation (VFI) is of great importance for many video applications, yet it is still challenging even in the era of deep learning. Some existing VFI models directly exploit existing lightweight network frameworks, thus making synthesized in-between frames blurry and creating artifacts due to imprecise motion representation. The other existing VFI models typically depend on heavy model architectures with a large number of parameters, preventing them from being deployed on small terminals. To address these issues, we propose a local lightweight VFI network (L2BEC2) that leverages bidirectional encoding structure with channel attention cascade. Specifically, we improve visual quality by introducing a forward and backward encoding structure with channel attention cascade to better characterize motion information. Furthermore, we introduce a local lightweight strategy into the state-of-the-art Adaptive Collaboration of Flows (AdaCoF) model to simplify its model parameters. Compared with the original AdaCoF model, the proposed L2BEC2 obtains performance gain at the cost of only one-third of the number of parameters and performs favorably against the state-of-the-art works on public datasets. Our source code is available at https://github.com/Pumpkin123709/LBEC.git.
uantized Sparse Training: A Unified Trainable Framework for Joint Pruning and uantization in DNNs

Deep neural networks typically have extensive parameters and computational operations. Pruning and quantization techniques have been widely used to reduce the complexity of deep models. Both techniques can be jointly used for realizing signiicantly higher compression ratios. However, separate optimization processes and diiculties in choosing the hyperparameters limit the application of both the techniques simultaneously. In this study, we propose a novel compression framework, termed as quantized sparse training, that prunes and quantizes networks jointly in a uniied training process. We integrate pruning and quantization into a gradient-based optimization process based on the straight-through estimator. Quantized sparse training enables us to simultaneously train, prune, and quantize a network from scratch. The empirical results validate the superiority of the proposed methodology over the recent state-of-the-art baselines with respect to both the model size and accuracy. Speciically, quantized sparse training achieves a 135KB model size in case of VGG16, without any accuracy degradation, which is 40% of the model size feasible based on the state-of-the-art pruning and quantization approach.
SUPERRESOLUTION OF IMAGES WITH LEARNED MULTIPLE RECONSTRUCTION KERNELS

This chapter develops a superresolution methodology and specifies an architecture to magnify and make clear small-sized and/or low-fidelity images. Superresolution is particularly relevant for multimedia applications due to the poor quality of images imposed by low bandwidth requirements. The method is based on the fact that data dependent bases are able to reconstruct signals with a resolution above the one imposed by the Shannon sampling theorem, provided that statistical information about the signals is utilized to specify the bases. Here we propose to learn the bases and the reconstruction kernels using the information available in local neighborhoods and across scales. First, local neighborhoods of a training image are clustered based on local features. Each cluster is assigned to a reconstruction kernel that is designed as an optimal mapping relating homologous neighborhoods across scales. A superresolved image is obtained by feeding an image through the architecture, or equivalently, by convolving the image with the learned family of kernels. Several examples are presented demonstrating the effectiveness of the approach.
Interaction of the Clostridium difficile Binary Toxin CDT and its Host Cell Receptor LSR*

Background: Clostridium difficile binary toxin CDT enters host cells via its receptor LSR. Results: Regions responsible for the CDT-LSR interaction were identified. Conclusion: An immunoglobulin-like domain of LSR and amino acids 757 to 866 of the binding component of CDT determine the toxin-receptor interaction. Significance: Knowledge of the toxin-receptor interaction is key to the development of anti-toxin strategies. ABSTRACT CDT ( Clostridium difficile transferase) is a binary, actin ADP-ribosylating toxin frequently associated with hypervirulent strains of the human enteric pathogen C.
Limb edema in critically ill patients: Comparing intermittent compression and elevation

Intensive care unit (ICU) patients are at high risk for limb edema, which caused complications such as pain, joint contracture, limited range of motion and atrophy of the limbs. Thus, this study was conducted to compare ICU patients' upper limb edema between two groups with the intervention of limb elevation and intermittent pneumatic compression (IPC). In this quasi‐experimental before and after study, 40 patients were recruited. One upper limb was randomly assigned to the upper limb elevation (ULE) group and the other one was assigned to the IPC group. The circumference of the wrist and the middle of the arm were compared between and within groups. Results showed that in both groups of IPC and ULE and all five sessions (unless the second session of ULE), participants' arm and wrist edema were reduced significantly after the interventions (arm: P < .01; wrist: P < .0001). The differences between the two groups of ULE and IPC in regards to limb edema reduction were not significant. Although there was no significant difference between IPC and ULE intervention in the removal of edema, ULE seems to be more feasible and practical, which should be assessed in future studies.
Delineation of nutrient management zones for precise fertilizer management in wheat crop using geo‐statistical techniques

Understanding the variability in crop yield in relation to the spatial variations in soil properties can help to more efficiently apply agricultural inputs on a site‐specific basis. This study was designed to characterize and quantify the spatial variation in soil properties and wheat yield and to delineate prescription maps for site‐specific fertilization. A wheat field was selected at the research farm of the University of Agriculture, Faisalabad, Pakistan, and a grid pattern (30 m * 30 m) was established at the experimental sites to collect soil and crop yield samples at two sampling depths (0–15 & 15–30 cm). The soil samples were analysed for soil nitrogen (N), phosphorus (P), potassium (K), pH, electrical conductivity (EC), soil organic matter (SOM) and saturation (S) at both sampling depths. The locations of the sampling points and field boundary were marked with a GPS receiver. Results of classical, geo‐statistical and interpolated maps revealed significant spatial variability in soil properties and crop yield, demanding for site‐specific nutrient management. The cluster analysis was performed to group the soil and yield data into five productivity zones termed as ‘very low’, ‘low’, ‘medium’, ‘high’ and ‘very high’ without prior knowledge of productivity potential with the internal homogeneity and external heterogeneity at a similarity level of greater than 70%. Results of correlation matrix suggested significant relationships among the crop yield and the soil properties. Results of means comparison in different productivity zones indicated that the crop yield and soil properties were significantly different in developed management zones except ‘low’ and ‘very low’ zones. Significant variation of soil nutrients in very low‐to‐very high productivity zones at both sampling depths suggested that the soil nutrients in combination with soil pH and organic matter can be used to develop prescription maps for site‐specific fertilization. Furthermore, the results of this study emphasize the need to predict soil and crop variables using sensors, in future studies, to delineate prescription maps, as soil sampling and analysis is expansive and time consuming. Site‐specific fertilization based on soil and crop needs can improve economic and environmental efficiency.
Increased phosphorus availability from sewage sludge ashes to maize in a crop rotation with clover

A recycling of Phosphorus (P) from the human food chain is mandatory to secure the future P supply for food production. However, many available recycled P fertilizers from sewage sludge do not have an adequate P bioavailability and, thus, are not suitable for their application in soils with pH >5.5–6.0, unless being combined with efficient mobilization measures. The aim of the study was to test the P mobilization ability of red clover (Trifolium pratense L.) from two thermally recycled P fertilizers for a subsequently grown maize. Two sewage sludge ashes (SSA) were investigated in a pot experiment at soil pH 7.5 with red clover differing in its nitrogen (N) supply (added N fertilizer or biological N2 fixation (BNF)), followed by maize (Zea maize L.). Shoot dry matter of maize was almost doubled when N supply of previous grown clover was covered by BNF, instead of receiving added N fertilizer. Similarly, shoot P removal of maize following clover with BNF was significantly increased. It is suggested that the P mobilization is related to the BNF, and a proton release of N2 fixing clover roots led to the measured decrease in soil pH and thereby increased P availability of the tested fertilizers.
Corporate Entrepreneurship and Organizational Performance

The aim of this study is to investigate the effect of corporate entrepreneurship on organizational performance in Dangote group. Descriptive survey research design was used while a sample size of two hundred and thirty eight (238) respondents using Slovene’s formula were selected out of 592 management staff of Dangote group using stratified-proportionate sampling. A Closed-ended questionnaire using 4 Likert’s rating scale was distributed, the instrument was tested using face validity, and to check the internal consistence, test and retest method was employed. Pearson Linear Correlation and Multiple Regression analysis was use to analyze the data using Statistical Package for Social Science (SPSS) version 21. The overall results of the study revealed that innovativeness and risk taking have no positive relationship with organizational performance, while pro-activeness has positive and significant effect on organizational performance in Dangote Group Nigeria. The study recommends that the management should pay attention to proacativeness when increasing organizational performance in Dangote Group.
HP1-driven phase separation recapitulates the thermodynamics and kinetics of heterochromatin condensate formation

The spatial segregation of pericentromeric heterochromatin (PCH) into distinct, membrane-less nuclear compartments involves the binding of Heterochromatin Protein 1 (HP1) to H3K9me2/3-rich genomic regions. While HP1 exhibits liquid-liquid phase separation properties in vitro, its mechanistic impact on the structure and dynamics of PCH condensate formation in vivo remains largely unresolved. Here, using biophysical modeling, we systematically investigate the mutual coupling between self-interacting HP1-like molecules and the chromatin polymer. We reveal that the specific affinity of HP1 for H3K9me2/3 loci facilitates coacervation in nucleo, and promotes the formation of stable PCH condensates at HP1 levels far below the concentration required to observe phase separation in purified protein assays in vitro. These heterotypic HP1-chromatin interactions give rise to a strong dependence of the nucleoplasmic HP1 density on HP1-H3K9me2/3 stoichiometry, consistent with the thermodynamics of multicomponent phase separation. The dynamical crosstalk between HP1 and the viscoelastic chromatin scaffold also leads to anomalously-slow equilibration kinetics, which strongly depend on the genomic distribution of H3K9me2/3 domains, and result in the coexistence of multiple long-lived, microphase-separated PCH compartments. The morphology of these complex coacervates is further found to be governed by the dynamic establishment of the underlying H3K9me2/3 landscape, which may drive their increasingly abnormal, aspherical shapes during cell development. These findings compare favorably to 4D microscopy measurements of HP1 condensates that we perform in live Drosophila embryos, and suggest a general quantitative model of PCH formation based on the interplay between HP1-based phase separation and chromatin polymer mechanics. SIGNIFICANCE STATEMENT The compartmentalization of pericentromeric heterochromatin (PCH), the highly-repetitive part of the genome, into membrane-less organelles enriched in HP1 proteins, is critical to both genetic stability and cell fate determination. While HP1 can self-organize into liquid-like condensates in vitro, the roles of HP1 and the polymer chromatin in forming 3D PCH domains in vivo are still unclear. Using molecular simulations, we show that key kinetic and thermodynamic features of PCH condensates are consistent with a phase-separation mode of organization driven by the genomic distribution of methylated domains and HP1 self-attraction and affinity for heterochromatin. Our predictions are corroborated by live-microscopy performed during early fly embryogenesis, suggesting that a strong crosstalk between HP1-based phase separation and chromosome mechanics drive PCH condensate formation.
Welcome Program and Tutoring Plan for New Students at the Faculty of Engineering of Vitoria-Gasteiz

The main objective of this paper is to describe two innovative experiences that are being developed at the Faculty of Engineering of Vitoria-Gasteiz (Basque Country University, Spain). The first one is being carried out during the last three years, and in short it is a Welcome Program for the new students. Its objective is to improve the adaptation of this group to its entrance to the university, as well as to try to reduce the dropping out rate of studies during their first academic year. This is the unique initiative of the type at the University of the Basque Country - Euskal Herriko Unibertsitatea (UPV/EHU). The second experience is developed once that the course has begun, offering to these same students a Tutoring Plan, where they can be guided and advised by teachers of the Faculty in order to maximize their academic achievements.
The Effect of Developmental Pleiotropy on the Evolution of Insect Immune Genes

The pressure to survive relentless pathogen exposure explains the frequent observation that immune genes are among the fastest-evolving in the genomes of many taxa, but an intriguing proportion of immune genes also appear to be under purifying selection. Though variance in evolutionary signatures of immune genes is often attributed to differences in gene-specific interactions with microbes, this explanation neglects the possibility that immune genes participate in other biological processes that could pleiotropically constrain adaptive selection. In this study, we analyzed available transcriptomic and genomic data from Drosophila melanogaster and related species to test the hypothesis that there is substantial pleiotropic overlap in the developmental and immunological functions of genes involved in immune signaling and that pleiotropy would be associated with stronger signatures of evolutionary constraint. Our results suggest that pleiotropic immune genes do evolve more slowly than those having no known developmental functions, and that signatures of constraint are particularly strong for pleiotropic immune genes that are broadly expressed across life stages. However, pleiotropic immune genes also contain a significantly higher proportion of positively selected sites and substitutions are more likely to be under positive selection, suggesting a mechanism to circumvent evolutionary constraint. These results support the general yet untested hypothesis that pleiotropy can constrain immune system evolution, raising new fundamental questions about the benefits of maintaining pleiotropy in systems that need to rapidly adapt to changing pathogen pressures.
Homeostatic responses to hypoxia by the carotid body and adrenal medulla are based on mutual antagonism between HIF-1α and HIF-2α

Respiration and blood pressure (BP) are regulated to maintain optimal delivery of O2 to every cell in the body. Arterial hypoxemia is sensed by the carotid body (CB), which initiates sympathetic reflex arcs to the diaphragm to increase ventilation, and to the adrenal medulla (AM) to increase catecholamine secretion and thereby increase BP. However, the underlying molecular mechanisms have not been fully delineated. Here, we report that the relative activities of hypoxia-inducible factor-1 (HIF-1) and HIF-2 determine the set point for the CB and AM, with respect to their maintenance of BP and respiration. In Hif2a+/- mice, which are heterozygous for a knockout allele at the locus encoding HIF-2α, expression of HIF-1α and NADPH oxidase 2 was increased in the CB and AM, resulting in an oxidized intracellular redox state with augmented sensitivity to hypoxia, increased BP, and respiratory abnormalities, which were all normalized by treatment with a HIF-1α inhibitor or a superoxide anion scavenger. By contrast, in Hif1a+/- mice, which are heterozygous for a knockout allele at the locus encoding HIF-1α, the expression of HIF-2α and superoxide dismutase 2 was increased in the CB and AM, resulting in a reduced intracellular redox state with impaired CB and ventilatory responses to chronic hypoxia, which were normalized by treatment with a HIF-2α inhibitor. None of the abnormalities that were observed in Hif1a+/- or Hif2a+/- mice were observed in Hif1a+/-; Hif2a+/- double- heterozygous mice. Our results demonstrate that redox balance in the CB and AM, which is determined by mutual antagonism between HIF-α isoforms, establishes the set point for responses of the CB and AM to hypoxia, and is required for the maintenance of normal BP and respiration.
Interrogating the effect of enzyme kinetics on metabolism using differentiable constraint-based models

Metabolic models are typically characterized by a large number of parameters. Traditionally, metabolic control analysis is applied to differential equation-based models to investigate the sensitivity of predictions to parameters. A corresponding theory for constraint-based models is lacking, due to their formulation as optimization problems. Here, we show that optimal solutions of optimization problems can be efficiently differentiated using constrained optimization duality and implicit differentiation. We use this to calculate the sensitivities of predicted reaction fluxes and enzyme concentrations to turnover numbers in an enzyme-constrained metabolic model of Escherichia coli. The sensitivities quantitatively identify rate limiting enzymes and are mathematically precise, unlike current finite difference based approaches used for sensitivity analysis. Further, efficient differentiation of constraint-based models unlocks the ability to use gradient information for parameter estimation. We demonstrate this by improving, genome-wide, the state-of-the-art turnover number estimates for E. coli. Finally, we show that this technique can be generalized to arbitrarily complex models. By differentiating the optimal solution of a model incorporating both thermodynamic and kinetic rate equations, the effect of metabolite concentrations on biomass growth can be elucidated. We benchmark these metabolite sensitivities against a large experimental gene knockdown study, and find good alignment between the predicted sensitivities and in vivo metabolome changes. In sum, we demonstrate several applications of differentiating optimal solutions of constraint-based metabolic models, and show how it connects to classic metabolic control analysis.
Individual tree-based vs pixel-based approaches to mapping forest functional traits and diversity by remote sensing

Trait-based approaches, focusing on the functional characteristics of vascular plants in a community, have been increasingly used in plant ecology and biodiversity research. Compared with traditional field survey (which typically samples individual trees), remote sensing enables quantifying functional traits over large contiguous areas, but assigning trait values to biological units such as species and individuals is difficult with pixel-based approaches. We used a subtropical forest landscape in China to compare an approach based on LiDAR-delineated individual tree crowns (ITCs) with a pixel-based approach for assessing functional traits from remote sensing data. We compared trait distributions, trait–trait relationships and functional diversity metrics obtained by the two approaches at changing grain and extent. We found that morphological traits derived from airborne laser scanning showed more differences between ITC- and pixel-based approaches than physiological traits estimated by imaging spectroscopy data. Pixel sizes approximating average tree crowns yielded similar results as ITCs, but 95th quantile height and foliage height diversity tended to be overestimated and leaf area index underestimated relative to ITC-based values. With increasing pixel size, the differences to ITC- based trait values became larger and less trait variance was captured, indicating information loss. The consistency of ITC- and pixel-based functional richness measures also decreased with increasing pixel grain, and changed with the observed extent for functional diversity monitoring. We conclude that whereas ITC-based approaches in principle allow partitioning of variation between individuals, genotypes and species, at high resolution, pixel-based approaches come close to this and can be suitable for assessing ecosystem-scale trait variation by weighting individuals and species according to coverage.