Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Aquila Optimization Controlled Deep Convolutional Neural Network for Power Management in Supercapacitors/Battery of Electric Vehicles

Abstract Electric Vehicles (EVs) may be a viable solution to reduce the huge energy consumption and greenhouse emissions of global transportation. However, the cost and range of batteries are two major obstacles for EV. An efficient Power management system for EVs, which includes Supercapacitor (SC) and battery with an optimized converter, is proposed in this paper. An optimal Direct Current (DC)-DC Bi-directional Buck-Boost Converter (BBBC) with a Proportional Integral Derivative (PID) controller is used for the optimal flow of power from the energy source to the drive during EV acceleration. The regenerative braking energy is allowed to return through the same bidirectional converter and retained in the Hybrid Energy Storage System (HESS) during the deceleration mode. A novel optimization is attained in the converter controller circuit using a Deep Convolution Neural Network (DCNN) and Adaptive Aquila Optimization Algorithm (AAqOA). The proposed strategy is validated using the results compared to conventional algorithms. In particular, the settling time of the suggested AAqOA model is 55.44%, 96.94%, 97.03%, and 91.87% better than the extant PI, DA, SSA, and AOA methods, respectively.
New Affordable Methods for Large-Scale Isolation of Major Olive Secoiridoids and Systematic Comparative Study of Their Antiproliferative/Cytotoxic Effect on Multiple Cancer Cell Lines of Different Cancer Origins

Olive oil phenols (OOPs) are associated with the prevention of many human cancers. Some of these have been shown to inhibit cell proliferation and induce apoptosis. However, no systematic comparative study exists for all the investigated compounds under the same conditions, due to difficulties in their isolation or synthesis. Herein are presented innovative methods for large-scale selective extraction of six major secoiridoids from olive oil or leaves enabling their detailed investigation. The cytotoxic/antiproliferative bioactivity of these six compounds was evaluated on sixteen human cancer cell lines originating from eight different tissues. Cell viability with half-maximal effective concentrations (EC50) was evaluated after 72 h treatments. Antiproliferative and pro-apoptotic effects were also assessed for the most bioactive compounds (EC50 ≤ 50 μM). Oleocanthal (1) showed the strongest antiproliferative/cytotoxic activity in most cancer cell lines (EC50: 9–20 μM). The relative effectiveness of the six OOPs was: oleocanthal (1) > oleuropein aglycone (3a,b) > ligstroside aglycone (4a,b) > oleacein (2) > oleomissional (6a,b,c) > oleocanthalic acid (7). This is the first detailed study comparing the bioactivity of six OOPs in such a wide array of cancer cell lines, providing a reference for their relative antiproliferative/cytotoxic effect in the investigated cancers.
Gastro-Intestinal Microbiota in Equines and Its Role in Health and Disease: The Black Box Opens

Horses are large non-ruminant herbivores and rely on microbial fermentation for energy, with more than half of their maintenance energy requirement coming from microbial fermentation occurring in their enlarged caecum and colon. To achieve that, the gastro-intestinal tract (GIT) of horses harbors a broad range of various microorganisms, differing in each GIT segment, which are essential for efficient utilization of feed, especially to use nutrients that are not or little degraded by endogenous enzymes. In addition, like in other animal species, the GIT microbiota is in permanent interplay with the host’s cells and is involved in a lot of functions among which inflammation, immune homeostasis, and energy metabolism. As for other animals and humans, the horse gut microbiome is sensitive to diet, especially consumption of starch, fiber, and fat. Age, breeds, stress during competitions, transportation, and exercise may also impact the microbiome. Because of its size and its complexity, the equine GIT microbiota is prone to perturbations caused by external or internal stressors that may result in digestive diseases like gastric ulcer, diarrhea, colic, or colitis, and that are thought to be linked with systemic diseases like laminitis, equine metabolic syndrome or obesity. Thus, in this review we aim at understanding the common core microbiome -in terms of structure and function- in each segment of the GIT, as well as identifying potential microbial biomarkers of health or disease which are crucial to anticipate putative perturbations, optimize global practices and develop adapted nutritional strategies and personalized nutrition.
ABSOLUTE PHOTODETACHMENT CROSS-SECTION MEASUREMENTS FOR HYDROCARBON CHAIN ANIONS

Absolute photodetachment cross sections have been measured for the hydrocarbon chain anions CnH−, n = 2, 4, and 6, which are relevant for an understanding of molecular clouds in the interstellar medium. Data have been obtained for different photon energies within approximately 1 eV of the detachment threshold. With our recently developed method we have achieved a precision of better than 25% on these absolute cross sections. The experiments have been carried out by means of photodetachment tomography of the mass-selected molecular anions in a multipole radio-frequency ion trap. The measured absolute cross sections are in accordance with the empirical scaling law of Millar et al. and have allowed us to determine its free parameters. These results are important for predicting the photostability and thus the abundance of carbon chain anions in planetary atmospheres, in circumstellar envelopes, and in photon-dominated regions of interstellar molecular clouds.
3D image correction for time of flight (ToF) cameras

The distance image from the ToF camera is affected by errors mainly due to multiple light reflections inside the camera body and by the indirect light illuminating the objects in the scene. These errors can't be avoided and in particular cases can be as great as 50%. The method presented corrects the measured distance errors to objects labeled with a known strong contrast tag. A proposed algorithm determines the integral perturbing light signal and by subtracting it from the measured one we compute the (actual) corrected 3D image. Because the perturbing signal has a slow variation along the image it is computed only in the region of the tag with known contrast but the correction is performed in a wider region. An extension of this method to the entire 3D image can be implemented using amplitude modulated structured light. The method can be useful to other distance measuring devices using the same (ToF) principle.
Dynamic Watermarking for Cybersecurity of Autonomous Vehicles

Autonomous vehicles (AVs) are rapidly proliferating. However, their future adoption is dependent on guarantees of their safety and security. Studies have shown that AVs are vulnerable to malicious cyberattacks with potentially lethal consequences. It is, therefore, imperative to deploy defensive techniques to enhance their cybersecurity. The method of dynamic watermarking (DW) has been proposed as an active technique for cyber-physical systems to detect cyberattacks. In this study, DW is implemented on an actual AV. It is shown that the DW technique is effective for timely detection of different types of attacks on the yaw rate measurement under autonomous operation, and thereby, allows recourse to measures such as stopping or pulling off to the side to prevent collisions.
Taylor-Couette Instabilities in Flows of Newtonian and Power-Law Liquids in the Presence of Partial Annulus Obstruction

The flow inside a horizontal annulus due to the inner cylinder rotation is studied. The bottom of the annular space is partially blocked by a plate parallel to the axis of rotation, thereby destroying the circumferential symmetry of the annular space geometry. This flow configuration is encountered in the drilling process of horizontal petroleum wells, where a bed of cuttings is deposited at the bottom part of the annulus. The velocity field for this flow was obtained both numerically and experimentally. In the numerical work, the equations which govern the three-dimensional, laminar flow of both Newtonian and power-law liquids were solved via a finite-volume technique. In the experimental research, the instantaneous and time-averaged flow fields over two-dimensional meridional sections of the annular space were measured employing the particle image velocimetry (PIV) technique, also both for Newtonian and power-law liquids. Attention was focused on the determination of the onset of secondary flow in the form of distorted Taylor vortices
Feature Based Automatic Text Summarization Methods: A Comprehensive State-of-the-Art Survey

With the advent of the World Wide Web, there are numerous online platforms that generate huge amounts of textual material, including social networks, online blogs, magazines, etc. This textual content contains useful information that can be used to advance humanity. Text summarization has been a significant area of research in natural language processing (NLP). With the expansion of the internet, the amount of data in the world has exploded. Large volumes of data make locating the required and best information time-consuming. It is impractical to manually summarize petabytes of data; hence, computerized text summarization is rising in popularity. This study presents a comprehensive overview of the current status of text summarizing approaches, techniques, standard datasets, assessment criteria, and future research directions. The summarizing approaches are assessed based on several characteristics, including approach-based, document-number-based, Summarization domain-based, document-language-based, output summary nature, etc. This study concludes with a discussion of many obstacles and research opportunities linked to text summarizing research that may be relevant for future researchers in this field.
A Contemporary and Comprehensive Survey on Streaming Tensor Decomposition

Tensor decomposition has been demonstrated to be successful in a wide range of applications, from neuroscience and wireless communications to social networks. In an online setting, factorizing tensors derived from multidimensional data streams is however nontrivial due to several inherent problems of real-time stream processing. In recent years, many research efforts have been dedicated to developing online techniques for decomposing such tensors, resulting in significant advances in streaming tensor decomposition or tensor tracking. This topic is emerging and enriches the literature on tensor decomposition, particularly from the data stream analystics perspective. Thus, it is imperative to carry out an overview of tensor tracking to help researchers and practitioners understand its developments and achievements, summarise the current trends and advances, and identify challenging problems. In this article, we provide a contemporary and comprehensive survey on different types of tensor tracking techniques. We particularly categorize the state-of-the-art methods into three main groups: streaming CP decompositions, streaming Tucker decompositions, and streaming decompositions under other tensor formats (i.e., tensor-train, t-SVD, and BTD). In each group, we further divide the existing algorithms into sub-categories based on their main optimization framework and model architectures. Finally, we present several applications, research challenges, open problems, and potential directions of tensor tracking in the future.
Risk Factors Affecting Muscle Mass Decline in Maintenance Hemodialysis Patients

Objective There is a high prevalence of sarcopenia in maintenance hemodialysis (MHD) patients, which is known to be associated with increased mortality. This study is aimed at analyzing the risk factors affecting muscle mass decline in MHD patients. Methods This retrospective study included MHD patients who underwent two body composition assessments in October 2013 and November 2017. Depending on whether there was muscle loss or not, the patients were divided into a normal muscle mass (NMM) group and a muscle mass decline (MMD) group. According to the muscle mass decline rate, patients in the MMD group were further classified into a low-rate group and a high-rate group. Biochemical variables, serum vitamin concentrations, anthropometric data, SGA, muscle mass, handgrip, and daily steps were assessed. Risk factors for muscle mass decline were screened by multivariate logistic analysis and linear regression analysis. Results Of the 72 MHD patients included in this study, 33 were male and 39 were female with a mean age of 56.80 ± 10.86 years and a mean dialysis duration of 7.50 ± 5.20 years. Age (P = .014) and serum 25(OH)D (P = .040) were found to be associated with a higher risk of muscle mass decline after adjusting for gender, dialysis vintage, albumin, and hs-CRP (P = .040). Further analysis found that dialysis vintage (β = 0.285, P = .030), 25(OH)D (β = −0.351, P = .007), and log NT-proBNP (β = 0.312, P = .020) were risk factors associated with the muscle mass decline rate in MHD patients. Conclusion Age and serum 25(OH)D were associated with a higher risk of muscle mass decline, while 25(OH)D, dialysis vintage, and NT-proBNP were associated with the muscle mass decline rate in MHD patients.
Bioimpedance as a measure of fluids in patients with septic shock. A prospective observational study

Septic shock is often treated with aggressive fluid resuscitation leading to profound fluid overload. The assessment of fluid status relies on suboptimal measures making treatment difficult. Bioelectrical impedance analysis is an alternative but the validity is unclear. The aim of this study was to determine the validity of bioelectrical impedance analysis for fluid measures in patients with septic shock.
A Twelve-Hundred-Year Stable Oxygen Isotope Chronology Constructed Using Subfossil Wood from Schwarzensee Lake, Austrian Alps

ABSTRACT This study presents a new stable oxygen isotope chronology, covering the years 800–2000 AD, constructed using modern and subfossil wood derived from trees growing around Lake Schwarzensee in Austria. The climatic signal imparted in the chronology is conditioned mainly by the direct influence of environmental factors on the isotopic signature of source water, which in turn is regulated by evaporation and condensation mechanisms. The second driver of stable oxygen isotope is the physiological response of trees to changing weather conditions, most importantly rates of transpiration. The chronology of stable oxygen isotopes corresponds well with both temperature (r = 0.485; p < 0.05) and total precipitation (r = −0.548; p < 0.05) during the growing season (May–September). This mixed signal results from the fact that the relationship between the content of stable oxygen isotopes and the influence of climate is multifactorial. Moreover, the effect exerted by meteorological conditions on stable isotope ratio changes over time. This is most probably linked to interannual variation in climatic and environmental factors.
Polaris Scheduler: SLO- and Topology-aware Microservices Scheduling at the Edge

The continuous expansion of Edge computing calls for efficient scheduling techniques for the employed microservices. However, typical container schedulers often fall short when used in an Edge cluster with heterogeneous devices and unstable network connections, because they do not account for any network Quality of Service (QoS) requirements. This makes it hard for applications to fulfill their Service Level Objectives (SLOs). In this paper we present Polaris Scheduler, an SLO-aware scheduler for the Edge that is developed as part of the Linux Foundation Centaurus project. Polaris Scheduler optimizes the placement of an application’s microservices to improve the fulfillment of their SLOs. To this end, it supports modeling of the Edge topology as a Cluster Topology Graph to capture the network quality characteristics and allows users to specify the dependencies among their application’s microservices, as well as the network QoS requirements (bandwidth, latency, jitter, and packet drop) for each of them in the form of a Service Graph. Polaris Scheduler relies on a plugin-based approach to allow support for multiple SLOs. We implement our scheduler with plugins for meeting network QoS SLOs as a Kubernetes scheduler and evaluate it using a realistic traffic analysis and hazard detection use case.
Does Firm Innovativeness Mediate the Relationship between Human Capital and Financial Performance of Insurance Firms in Kenya?

This study investigates the effect of firm innovativeness in mediating the human capital-financial performance link. The research is founded on human capital theory. The data was drawn from employees in all the 49 insurance firms in Kenya. The usable sample for the study comprised 372 employees. Data was gathered via a survey questionnaire and examined using structural equation modelling. The outcomes show that there is an affirmative and substantial association amid human capital and financial performance. Additionally, it has been demonstrated that a company's innovativeness helps to moderate the affiliation between financial performance and human capital.
Novelty detection using extreme value statistics

Extreme value theory is a branch of statistics that concerns the distribution of data of unusually low or high value, i.e. in the tails of some distribution. These extremal points are important in many applications as they represent the outlying regions of normal events against which we may wish to define abnormal events. In the context of density modelling, novelty detection or radial-basis function systems, points that lie outside of the range of expected extreme values may be flagged as outliers. There has been interest in the area of novelty detection, but decisions as to whether a point is an outlier or not tend to be made on the basis of exceeding some (heuristic) threshold. It is shown that a more principled approach may be taken using extreme value statistics.
Heat Transfer From Rectangular Plates Inclined at Different Angles of Attack and Yaw to an Air Stream

Average heat transfer coefficients during forced convection air flow over inclined and yawed rectangular plates have been experimentally determined. Tripping wires at the edges ensured that a turbulent boundary layer prevailed over the plates. The experiments were carried out for a constant surface temperature and covered two plates of different aspect ratios, angles of attack from 0 to 45 deg, angles of yaw from 0 to 30 deg, and Reynolds numbers from 2 times; 104 to 3.5 times; 105 . The results show that the average heat transfer coefficient is essentially insensitive to the aspect ratio and angle of yaw. However, it is a function of Reynolds number and the angle of attack. Correlation equations for various angles of attack are suggested.
Recent developments in GSDIM microscopy

In the presented study we characterized the suitability of 15 conventional fluorescence dyes for GSDIM microscopy. For all dyes involved in the screening labeled secondary antibodies for immunohistochemistry are commercially available. The dye performance was tested after staining to fixed mammalian cells. Chemical environments were chosen to be compatible with the applicative and spectroscopic demands. Investigated watery environments are suitable for TIRF based applications. To the best of our knowledge, we present for the first time systematic screening for configurations of dyes embedded in solid polymer. The polymer mounting matches well to the refractive index of oil immersion optics. This is crucial for applications at high penetration depth into the sample and suitable for long-term sample storage. We rated the final super-resolution image quality additional to quantitative characterization of important spectroscopic parameters. Therefore, this dye screening is optimized for various biological imaging applications. Control of the single molecule blinking rate by 405nm light exposure is quantified, as well. It is shown that this important effect is applicable to numerous fluorescent dyes. Thus, the controlled application of low intensities of 405nm light allows to maximize recording speed. As this option is already included in commercial GSDIM microscopes the results of our study allow optimized super-resolution imaging down to ~20nm with multiple dyes and multi-color staining.
The stability of magnetized protostellar disks with the Hall effect and buoyancy

The stability properties of cool protostellar disks are examined by use of the dispersion relation taking into account the Hall effect and buoyancy. Depending on the conditions, different types of instabilities can arise in different regions of the disk. In very low-ionized regions the instability associated with baroclinic effects of buoyancy is likely most efficient. The shear-Hall instability will be responsible for destabilization of regions with a weak magnetic field (parallel to the rotation axis) and with low conductivity (${\rm \Lambda} a e magnetization parameter of electrons). The magnetorotational instability modified by buoyancy should be the main destabilizing factor in regions with sufficiently strong magnetic fields and/or high conductivity (${\rm \Lambda} > a_{\rm e}$). For a magnetic field amplitude of 1 Gauss the transition between both the regions happens at approximately 1 AU.
An Indoor Pseudolite Positioning Method Based on Measured and Simulated Fingerprints

At present, the indoor positioning method of pseudolite based on fingerprint is restricted by the range and density of fingerprint collection, and its stability, reliability, and accuracy are still technical bottlenecks. Aiming at the shortcomings of existing indoor fingerprint positioning, combined with the advantages of deterministic ray tracing simulation, a new hybrid method of measurement and simulation is proposed to generate the fingerprint feature input set to drive the position prediction model. The feature parameters generated by the simulation calculation are added to the neural network as part of the input, the original artificial neural network structure is improved, and the sample features of the neural network input data set are expanded. Taking the indoor arrival hall of an airport as an example, the static and dynamic positioning tests are carried out by combining the simulation and measured fingerprint construction methods. Compared with the traditional positioning effect based on fingerprint collection alone, the static positioning error of the proposed method is reduced by 42.2%, and the dynamic positioning error is reduced by 46.9%.