Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Continuous Glucose Monitoring to Prescribe a Time to Exercise for Individuals with Type 2 Diabetes

This study examines the potential utility of using continuous glucose monitoring (CGM) to prescribe an exercise time to target peak hyperglycaemia in people with type 2 diabetes (T2D). The main aim is to test the feasibility of prescribing an individualised daily exercise time, based on the time of CGM-derived peak glucose, for people with T2D. Thirty-five individuals with T2D (HbA1c: 7.2 ± 0.8%; age: 64 ± 7 y; BMI: 29.2 ± 5.2 kg/m2) were recruited and randomised to one of two 14 d exercise interventions: i) ExPeak (daily exercise starting 30 min before peak hyperglycaemia) or placebo active control NonPeak (daily exercise starting 90 min after peak hyperglycaemia). The time of peak hyperglycaemia was determined via a two-week baseline CGM. A CGM, accelerometer, and heart rate monitor were worn during the free-living interventions to objectively measure glycaemic control outcomes, moderate-to-vigorous intensity physical activity (MVPA), and exercise adherence for future translation in a clinical trial. Participation in MVPA increased 26% when an exercise time was prescribed compared to habitual baseline (p < 0.01), with no difference between intervention groups (p > 0.26). The total MVPA increased by 10 min/day during the intervention compared to the baseline (baseline: 23 ± 14 min/d vs. intervention: 33 ± 16 min/d, main effect of time p = 0.03, no interaction). The change in peak blood glucose (mmol/L) was similar between the ExPeak (−0.44 ± 1.6 mmol/L, d = 0.21) and the NonPeak (−0.39 ± 1.5 mmol/L, d = 0.16) intervention groups (p = 0.92). Prescribing an exercise time based on CGM may increase daily participation in physical activity in people with type 2 diabetes; however, further studies are needed to test the long-term impact of this approach.
Density-Based Classification Network Control Approach for a Single Stoplight Traffic System on a Simplified Traffic Simulation using MATLAB

A more dynamic method of improving traffic flow on a road network is made possible by intelligent traffic management systems (ITMS). This is done by determining the optimal routing configuration of a stoplight system to maximize vehicle throughput. One such algorithm is the classification network which uses a deep neural network to approximate a function that determines the optimal routing state by projecting it as a classification task. This paper uses a classification network-based control algorithm for a single smart traffic light module implemented through the MATLAB software. The proposed system was able to route vehicles 15.1% faster than a static system on a single intersection road network. The classification network control scheme was able to determine the best routing configuration for the stoplight system in real time to optimize traffic flow. Thus, the system is a feasible improvement in stoplight control as it can reduce traffic congestion by increasing vehicle throughput in the system.
Tunable thermal conductivity in silicon twinning superlattice nanowires

Shiyun Xiong,1,2 Yuriy A. Kosevich,1,2,3 K. Saaskilahti,1,2,4 Yuxiang Ni,1,2,* and Sebastian Volz1,2,† 1CNRS, UPR 288 Laboratoire d’Energetique Moleculaire et Macroscopique, Combustion (EM2C), Grande Voie des Vignes, 92295 Châtenay-Malabry, France 2Ecole Centrale Paris, Grande Voie des Vignes, 92295 Châtenay-Malabry, France 3Semenov Institute of Chemical Physics, Russian Academy of Sciences, 119991 Moscow, Russia 4Department of Biomedical Engineering and Computational Science, Aalto University, FI-00076 Aalto, Finland (Received 17 September 2014; revised manuscript received 29 October 2014; published 24 November 2014)
Monte Carlo Study of Phonon Transport in Solid Thin Films Including Dispersion and Polarization

The Boltzmann Transport Equation (BTE) for phonons best describes the heat flow in solid nonmetallic thin films. The BTE, in its most general form, however, is difficult to solve analytically or even numerically using deterministic approaches. Past research has enabled its solution by neglecting important effects such as dispersion and interactions between the longitudinal and transverse polarizations of phonon propagation. In this article, a comprehensive Monte Carlo solution technique of the BTE is presented. The method accounts for dual polarizations of phonon propagation, and non-linear dispersion relationships. Scattering by various mechanisms is treated individually. Transition between the two polarization branches, and creation and destruction of phonons due to scattering is taken into account. The code has been verified and evaluated by close examination of its ability or failure to capture various regimes of phonon transport ranging from diffusive to the ballistic limit. Validation results show close agreement with experimental data for silicon thin films with and without doping. Simulation results show that above 100 K, transverse acoustic phonons are the primary carriers of energy in silicon.
Determining the Ripeness of Edible Fruits using YOLO and the OVA Heuristic Model

The freshness of fruit can be determined in various ways. And some do it by smelling, some by using touch, others visually, while others even predict the freshness through sound. Among these, the most common and accurate way of determining the freshness of the fruit is by looking at it. Therefore, the authors of this paper made a system with the general objective of automating the prediction of the freshness of two types of fruits which are the Cavendish banana and Carabao mango, by using the You Only Look Once (YOLO) algorithm for object detection and a Support Vector Machine (SVM) classifier that will classify whether the fruit subject is unripe, ripe, or spoiled. Given that the classification problem presented here is multiclass, the One Versus All (OVA) heuristic model is needed to extend the SVM classifier. The YOLO classifier was trained with a dataset that contains more than 100 images, and it was able to detect fruit samples that were invalid and valid. Furthermore, with 33 test fruit subjects, the system’s overall accuracy regarding its classification of freshness to the fruit subjects is 90.9%.
Soybean Oil Regulates the Fatty Acid Synthesis II System of Bacillus amyloliquefaciens LFB112 by Activating Acetyl-CoA Levels

[Background] Bacillus LFB112 is a strain of Bacillus amyloliquefaciens screened in our laboratory. Previous studies found that it has a strong ability for fatty acid metabolism and can improve the lipid metabolism of broilers when used as feed additives. [Methods] This study aimed to confirm the fatty acid metabolism of Bacillus LFB112. Sterilized soybean oil (SSO) was added to the Beef Peptone Yeast (BPY) medium, and its effect on fatty acid content in the supernatant and bacteria, as well as expression levels of genes related to fatty acid metabolism, were studied. The control group was the original culture medium without oil. [Results] Acetic acid produced by the SSO group of Bacillus LFB112 decreased, but the content of unsaturated fatty acids increased. The 1.6% SSO group significantly increased the contents of pyruvate and acetyl-CoA in the pellets. Furthermore, the mRNA levels of enzymes involved in the type II fatty acid synthesis pathway of FabD, FabH, FabG, FabZ, FabI, and FabF were up-regulated. [Conclusions] Soybean oil increased the content of acetyl-CoA in Bacillus LFB112, activated its type II fatty acid synthesis pathway, and improved the fatty acid metabolism level of Bacillus LFB112. These intriguing results pave the way for further investigations into the intricate interplay between Bacillus LFB112 and fatty acid metabolism, with potential applications in animal nutrition and feed additive development.
A Novel Approach to Avoid Singularities of PUMA-type Manipulators

Existing methods to avoid the kinematic singularities are complex.A novel approach(named"singularity separation plus damped reciprocal"method)is proposed for PUMA-type manipulators.Firstly,we analyze the singularity conditions and separate the singularity parameters from the Jacobian inverse.Then,the damped reciprocals are used to avoid the singularities by replacing their reciprocals.Since the SVD decomposition and the estimate of the minimum singularity value are not required,the algorithm is more efficient and fit for real-time application.And not all components of the end-effector velocities are sacrificed in accuracy.The method can be used for prescribed or real-time trajectory tracking.Simulation and experiment results verify the method.
Genes Participating in the Ensheathment of Neurons Are Affected by Postnatal Stress and Maternal Immune Activation in the Pituitary Gland

Immune challenges during gestation are associated with neurodevelopmental disorders and can interact with stress later in life. The pituitary gland participates in endocrine- and immune-related processes that influence development, growth, and reproduction and can modulate physiological and behavioral responses to challenges. The objective of this study was to investigate the effect of stressors at different time points on the molecular mechanisms of the pituitary gland and detect sex differences. RNA sequencing was used to profile the pituitary glands of female and male pigs exposed to weaning stress and virally induced maternal immune activation (MIA), relative to unchallenged groups. Significant effects (FDR-adjusted p-value < 0.05) of MIA and weaning stress were detected in 1829 and 1014 genes, respectively. Of these, 1090 genes presented significant interactions between stressors and sex. The gene ontology biological process of the ensheathment of neurons (GO:0007272), substance abuse, and immuno-related pathways, including the measles disease (ssc05162), encompasses many genes with profiles impacted by MIA and weaning stress. A gene network analysis highlighted the under-expression of myelin protein zero (Mpz) and inhibitors of DNA binding 4 (Id4) among the non-stressed males exposed to MIA, relative to the control and non-MIA males exposed to weaning stress, relative to non-stressed pigs. The detection of changes in the molecular mechanisms of the pituitary gland could advance our understanding of disruptions in the formation of the myelin sheath and the transmission of neuron-to-neuron signals in behavioral disorders associated with maternal immune activation and stress.
Traffic Assignment and Gibbs-Maslov Semirings

The Traffic Assignment problem consists in determining the routes used by sets of network users taking into account the link congestions. In deterministic modelling, Wardrop Equilibriums are computed. They can be reduced to huge non-linear multiflow problems in the simplest cases. In stochastic modelling, Logit Assignments are used. They are obtained, mainly, by substituting the minplus semiring by the «Gibbs-Maslov semirings»[ ], in the deterministic assignment computations.
Leveraging Integrated Primary Care to Enhance the Health System Response to IPV: Moving toward Primary Prevention Primary Care

Intimate partner violence (IPV) is a prominent public health problem in the United States, with significant health impacts that are often severe and persistent. Healthcare systems have been called upon to improve both the systematic identification and treatment of IPV largely by adopting secondary and tertiary prevention efforts. Research to date demonstrates both benefits and challenges with the current strategies employed. In this paper, we summarize current knowledge about the healthcare system’s response to IPV and evaluate the strengths, limitations, and opportunities. We offer recommendations to broaden the continuum of healthcare resources to address IPV, which include a population health approach to primary prevention.
Evaluation of the Autologous Genetically Enriched Leucoconcentrate on the Lumbar Spinal Cord Morpho-Functional Recovery in a Mini Pig with Thoracic Spine Contusion Injury

Background: Pathological changes associated with spinal cord injury (SCI) can be observed distant, rostral, or caudal to the epicenter of injury. These remote areas represent important therapeutic targets for post-traumatic spinal cord repair. The present study aimed to investigate the following in relation to SCI: distant changes in the spinal cord, peripheral nerve, and muscles. Methods: The changes in the spinal cord, the tibial nerve, and the hind limb muscles were evaluated in control SCI animals and after intravenous infusion of autologous leucoconcentrate enriched with genes encoding neuroprotective factors (VEGF, GDNF, and NCAM), which previously demonstrated a positive effect on post-traumatic restoration. Results: Two months after thoracic contusion in the treated mini pigs, a positive remodeling of the macro- and microglial cells, expression of PSD95 and Chat in the lumbar spinal cord, and preservation of the number and morphological characteristics of the myelinated fibers in the tibial nerve were observed and were aligned with hind limb motor recovery and reduced soleus muscle atrophy. Conclusion: Here, we show the positive effect of autologous genetically enriched leucoconcentrate-producing recombinant neuroprotective factors on targets distant to the primary lesion site in mini pigs with SCI. These findings open new perspectives for the therapy of SCI.
Deep Learning for Automatic Vision-Based Recognition of Industrial Surface Defects: A Survey

Automatic vision-based inspection systems have played a key role in product quality assessment for decades through the segmentation, detection, and classification of defects. Historically, machine learning frameworks, based on hand-crafted feature extraction, selection, and validation, counted on a combined approach of parameterized image processing algorithms and explicated human knowledge. The outstanding performance of deep learning (DL) for vision systems, in automatically discovering a feature representation suitable for the corresponding task, has exponentially increased the number of scientific articles and commercial products aiming at industrial quality assessment. In such a context, this article reviews more than 220 relevant articles from the related literature published until February 2023, covering the recent consolidation and advances in the field of fully-automatic DL-based surface defects inspection systems, deployed in various industrial applications. The analyzed papers have been classified according to a bi-dimensional taxonomy, that considers both the specific defect recognition task and the employed learning paradigm. The dependency on large and high-quality labeled datasets and the different neural architectures employed to achieve an overall perception of both well-visible and subtle defects, through the supervision of fine or/and coarse data annotations have been assessed. The results of our analysis highlight a growing research interest in defect representation power enrichment, especially by transferring pre-trained layers to an optimized network and by explaining the network decisions to suggest trustworthy retention or rejection of the products being evaluated.
Structure and Performance of All-Green Electrospun PHB-Based Membrane Fibrous Biomaterials Modified with Hemin

This work addresses the challenges concerning the development of “all-green” high-performance biodegradable membrane materials based on poly-3-hydroxybutyrate (PHB) and a natural biocompatible functional additive, iron-containing porphyrin, Hemin (Hmi) via modification and surface functionalization. A new facile and versatile approach based on electrospinning (ES) is advanced when modification of the PHB membranes is performed by the addition of low concentrations of Hmi (from 1 to 5 wt.%). Structure and performance of the resultant {HB/Hmi membranes were studied by diverse physicochemical methods, including differential scanning calorimetry, X-ray analysis, scanning electron microscopy, etc. Modification of the PHB fibrous membranes with Hmi allows control over their quality, supramolecular structure, morphology, and surface wettability. As a result of this modification, air and liquid permeability of the modified electrospun materials markedly increases. The proposed approach provides preparation of high-performance all-green membranes with tailored structure and performance for diverse practical applications, including wound healing, comfort textiles, facial protective masks, tissue engineering, water and air purification, etc.
Inverse Mapping of Pulsar Magnetospheres: Optical Emission Comes From 300 km Above the Surface

Abstract In order to determine the emission height of the optical photons from pulsars we present an inverse mapping approach, which is directly constrained by empirical data. The model discussed is for the case of the Crab pulsar. Our method, which uses the optical Stokes parameters, determines the most likely geometry for emission including the magnetic-field inclination angle (α), the observer's line-of-sight angle (χ) and emission height. We discuss the computational implementation of the approach, and the physical assumptions made. We find that the most likely emission altitude is at 20% of the light-cylinder radius above the stellar surface in the open field region.
Pathogenesis of Alkali Injury-Induced Limbal Stem Cell Deficiency: A Literature Survey of Animal Models

Limbal stem cell deficiency (LSCD) is a debilitating ocular surface disease that eventuates from a depleted or dysfunctional limbal epithelial stem cell (LESC) pool, resulting in corneal epithelial failure and blindness. The leading cause of LSCD is a chemical burn, with alkali substances being the most common inciting agents. Characteristic features of alkali-induced LSCD include corneal conjunctivalization, inflammation, neovascularization and fibrosis. Over the past decades, animal models of corneal alkali burn and alkali-induced LSCD have been instrumental in improving our understanding of the pathophysiological mechanisms responsible for disease development. Through these paradigms, important insights have been gained with regards to signaling pathways that drive inflammation, neovascularization and fibrosis, including NF-κB, ERK, p38 MAPK, JNK, STAT3, PI3K/AKT, mTOR and WNT/β-catenin cascades. Nonetheless, the molecular and cellular events that underpin re-epithelialization and those that govern long-term epithelial behavior are poorly understood. This review provides an overview of the current mechanistic insights into the pathophysiology of alkali-induced LSCD. Moreover, we highlight limitations regarding existing animal models and knowledge gaps which, if addressed, would facilitate development of more efficacious therapeutic strategies for patients with alkali-induced LSCD.
Accurate and O(1)-Time Query of Per-Flow Cardinality in High-Speed Networks

On a high-speed link, there may be tens of millions of IP packets per second and millions of active flows. Maintaining the state of each flow is a fundamental task underlying many network functions, such as load balancing and network anomaly detection. There are two important kinds of per-flow states: per-flow size (e.g., the number of packets received by an arbitrary destination IP) and per-flow cardinality (e.g., the number of distinct source IP addresses that contacted each destination IP). In this paper, we focus on the latter kind of states, and define a new problem: online query of per-flow cardinality, in which we query any given flow’s cardinality entirely on the data plane with low time complexity. For this problem, we propose three solutions named On-vHLL, Ton-vHLL and Aton-vHLL, whose time cost are $O(1)$ even for the query operation. Our proposed techniques are three folds. First, we redesign the traditional vHLL with new supplementary data structures called incremental update units (IUUs). When a certain flow’s cardinality is queried, these IUUs can avoid scanning the whole data structure and reduce the time complexity to $O(1)$ . Second, we apply a HLL register compression technique called TailCut to the On-vHLL sketch, which can save memory cost by 50%. Third, we add a prefilter based on min-heap, alongside the Ton-vHLL sketch. The prefilter is to give each currently sampled top- $k$ superspreader a dedicated HyperLogLog estimator for better accuracy. It can also absorb the superspreaders’ packets bypassing the sketch. We evaluate our new sketches by simulation with CAIDA traces. The results show that our On-vHLL, Ton-vHLL and Aton-vHLL sketches need about 5 memory accesses per packet. The time cost of query operation decreases by hundreds of times than the traditional vHLL that can only be queried offline. Meanwhile, the estimation error of flow spread by our Aton-vHLL is comparable to vHLL.
Improving Jellyfish Swarm Algorithm for Solving Unconstrained Optimization Problems

Many real-world optimization issues have been resolved with the help of Jellyfish Search Optimizer (JSO Jellyfish search behavior may be simulated by considering their active and passive movements within a swarm, as well as their direction relative to the ocean current. To enhance the movement and trajectory of a swarm of jellyfish, the authors of this study create a novel Quasi-technique of Newton's matrix that they refer to as JSO-QNH1. Ten standard functions were used to demonstrate and evaluate our algorithm's effectiveness. It has been proven that the proposed algorithm is superior to the standard and well-known algorithms by using more than one comparison measure.
Assessment of the NCEP-DOE Reanalysis-2 and TOVS Pathfinder A Moisture Fields and Their Use in Antarctic Net Precipitation Estimates

Abstract Moisture fields from the NCEP–DOE reanalysis-2 (R-2) and Television Infrared Observational Satellite (TIROS) Operational Vertical Sounder (TOVS) Pathfinder A are validated using the Special Sensor Microwave Imager (SSM/I) retrievals over the Southern Ocean. It is shown that the spatial distributions of the annual mean statistics of the total precipitable water are similar among SSM/I, R-2, and TOVS Pathfinder A for both the eddy and mean components. However, transient statistics show that the R-2 total precipitable water agrees with SSM/I with a correlation of 0.77 over the Southern Ocean while the TOVS Pathfinder A moisture is almost uncorrelated with the SSM/I data. Total moisture transport convergence for 1988 over the Antarctic continent is further examined using the R-2 wind and moisture data as well as the moisture retrievals from TOVS Pathfinder A. To gain a better understanding of transient and mean processes on moisture transport, the total moisture transport was decomposed into mean and.
Biosynthesis of nisin, antimicrobial mechanism and its applications as a food preservation: A review

This review examines the biosynthesis of nisin, its antimicrobial mechanism, and its applications in food preservation. Nisin is synthesized withinside the ribosome as a pre-peptide which undergoes amendment withinside the post-translational level as a number one metabolite from lactic acid bacteria. Nisin secretion occurs in the exponential phase and is maximally produced at the end of the exponential phase or the beginning of the stationary phase. As an antibiotic in the form of a peptide molecule, nisin is characterized by the presence of lanthionine-type thioester bonds. Nisin has been reported to have the ability to inhibit bacteria, especially Gram-positive bacteria such as Bacillus subtilis, Bacillus stearothermophilus, Clostridium botulinum, Streptococcus hemolyticus, Staphylococcus aureus, and Listeria monocytogenes. Nevertheless, nisin is less effective against Gram-negative bacteria, yeast, and molds. Based on its ability to inhibit bacteria plus the non-toxic nature of nisin, Nisin can be used as bio preservation in food products. Besides being non-toxic, several other factors that can be considered for nisin as bio preservation are that nisin is readily biodegradable. It is a protein compound that does not harm the intestinal flora as it is easily digested by enzymes in the gastrointestinal tract and does not cause bacterial resistance as therapeutic antibiotics are safe for humans.