Miracle-dz/UniFAR-FTUs huggingface dataset:
Microbial quality and emerging pollutants in freshwater systems of Mega Manila, Philippines: a scoping review

ABSTRACT Microbial and chemical qualities of drinking water and freshwater bodies in highly urbanized regions of developing countries remain as global knowledge gaps. This current scoping review addressed this issue in the case of Mega Manila, Philippines. Quantitative and qualitative analyses of literature were done to support syntheses and identify gaps in water quality monitoring and management. The microbial quality of freshwater bodies and drinking water within the region is indicated by the detected microbial communities, bacterial species, and genetic elements associated with drug resistance, through culture-dependent and -independent approaches. Heavy metals were found to contaminate freshwater bodies but were absent in the drinking water supply. Overall, our findings highlight the need for harmonizing monitoring tools and data to assess water safety. Outside Mega Manila, freshwater bodies and drinking water supply must be monitored. Research focusing on environmental and public health as impacted by drinking water and resources must also be prioritized.
A PHENOMENOLOGICAL MODEL OF NANOCRYSTALLINE COATING PRODUCTION USING THE PLASMA ELECTROLYTIC SATURATION (PES) TECHNIQUE

Abstract. Railway managers have a strong economic incentive to minimize track maintenance costs, while maintaining safety standards and providing adequate service levels to train operators. The objective of this study is to apply a procedure for making optimal maintenance decisions in Iranian Railways. This study consists of two parts. First, a cumulative damage model, based on a Markov process, is applied to model the deterioration of the track. For this reason, tracks are categorized into six classes, so that those tracks with similar trac loads and geographical location are collected into one class. The track survey data from 215 blocks (4,228 km) of the ten divisions of the Iranian Railway system, during 2002-2004, is used to identify the transition matrix. Secondly, probabilistic dynamic programming is used to nd the optimal repair for each possible track state in the planning horizon. This approach allows an optimal maintenance decision to be determined for the track at any point in time within the planning horizon.
Asymptotic Methods in Queueing Theory.

places strong emphasis on developing the reader's intuition. On the other hand, both books are hard to skim. If the level is not right for the course, then one must reluctantly treat the book as recommeded reading and choose a more efficient textbook. One final remark. It seems to me that information theory is a more mathematical subject in the Soviet Union than it is in the United States. Nonetheless, as evidenced by this book, the cultures are developing along parallel lines.
A novel approach for shaken image deblurring

Blurry images are the bane of many photographers. Although sometimes these images could be retaken in the hope that the next exposure will not be blurred, but frequently they are of some unique event that could only be captured once. The most common cause of blurry images is camera shake. Camera shake means that during the exposure the camera moved. This movement may be very small but still creates blurry images. In this paper, a novel blind-deblurring approach for removing the effect of camera shake from blurry image is proposed. Starting with an image that has been blurred by camera shake, we recover the unknown shape image in two phases: (i) a kernel estimation phase using Radon transform method, and (ii) the shape image recovery based on EM algorithm. Comprehensive comparisons on a number of blurry images show that our approach is not only substantially faster, but it also leads to better deblurring results. Our experimental results are also shown for comparisons. Visually, we find that the restored images are better than those given by the algorithm in other methods from previous works. 2014 SERSC.
Cooperative caching strategy based mobile vehicle social‐aware in internet of vehicles

The dramatic growth of smart in‐vehicle applications in the Internet of Vehicles and the increasing quality of experience for vehicle users have put a huge traffic load on the mobile core network. Mobile edge caching has been proposed to place content at the edge of the network to serve users in close proximity to them. However, the dynamic topology of existing edge networks and the inherent storage limitations of edge devices pose a serious challenge to vehicular edge caching. Therefore, in this article, we propose a cooperative caching strategy based on mobile prediction and social awareness that allows collaborative content decision making among edge devices. Specifically, the long short‐term memory network is used to predict vehicle trajectories, social relationships are computed using content similarity and contact rates among vehicle users to select vehicles that can serve as caching nodes, and deep reinforcement learning is employed to achieve the final caching decision. Simulation results show that the caching strategy proposed in this article achieves up to 7.7%, 24.2%, and 27.3% gains, respectively, in terms of content acquirement delay compared to the reinforcement learning algorithm, the algorithm without considering mobility, and the non‐cooperative algorithm.
Absolute air refractive index measurement and tracking based on variable length vacuum cell

Abstract. A refractometer system using four modified Wu-type heterodyne interferometers with a variable length vacuum cell is presented. The proposed system has two working modes: (1) a moving mode for measuring the absolute air refractive index at the start of a measurement and (2) a static mode for monitoring the air refractive index fluctuation with the same bandwidth as a traditional displacement interferometer. The system requires no gas filling or pumping during the measurement and can be used for real-time refractive index compensation. Comparison experiments with empirical equations are conducted to investigate the feasibility and performance of the proposed system. The standard deviation of the measurement difference between the proposed system and empirical equation is 2.8 parts in 107, which is close to the uncertainty of our refractive index reference based on the accuracy of the environmental sensors. The relative refractive index tracking is a few parts in 108 with a bandwidth of 10 Hz, but high bandwidths are readily achievable.
Appressoria Formation in Phytopathogenic Fungi Suppressed by Antimicrobial Peptides and Hybrid Peptides from Black Soldier Flies

Antimicrobial peptides (AMPs) from black solider flies (Hermetia illucens, BSF) exhibiting broad-spectrum antimicrobial activity are the most promising green substitutes for preventing the infection of phytopathogenic fungi; therefore, AMPs have been a focal topic of research. Recently, many studies have focused on the antibacterial activities of BSF AMPs against animal pathogens; however, currently, their antifungal activities against phytopathogenic fungi remain unclear. In this study, 7 AMPs selected from 34 predicted AMPs based on BSF metagenomics were artificially synthesized. When conidia from the hemibiotrophic phytopathogenic fungi Magnaporthe oryzae and Colletotrichum acutatum were treated with the selected AMPs, three selected AMPs—CAD1, CAD5, and CAD7—showed high appressorium formation inhibited by lengthened germ tubes. Additionally, the MIC50 concentrations of the inhibited appressorium formations were 40 μM, 43 μM, and 43 μM for M. oryzae, while 51 μM, 49 μM, and 44 μM were observed for C. acutatum, respectively. A tandem hybrid AMP named CAD-Con comprising CAD1, CAD5, and CAD7 significantly enhanced antifungal activities, and the MIC50 concentrations against M. oryzae and C. acutatum were 15 μM and 22 μM, respectively. In comparison with the wild type, they were both significantly reduced in terms of virulence when infection assays were performed using the treated conidia of M. oryzae or C. acutatum by CAD1, CAD5, CAD7, or CAD-Con. Meanwhile, their expression levels of CAD1, CAD5, and CAD7 could also be activated and significantly increased after the BSF larvae were treated with the conidia of M. oryzae or C. acutatum, respectively. To our knowledge, the antifungal activities of BSF AMPs against plant pathogenic fungi, which help us to seek potential AMPs with antifungal activities, provide proof of the effectiveness of green control strategies for crop production.
Ionized Gas in Sgr B2 Main on Scales of 0.065 Arcsecond (600 Au)

The ionized gas in the Sagittarius B2 Main star-forming region has been imaged with ~65 mas (600 AU) resolution using the Very Large Array (VLA) at 7 mm in the A configuration. These observations have ~4-5 times the resolution of the previous highest resolution images of this source. These VLA observations show that the central four ultracompact H II (UC H II) regions in Sgr B2 Main (F1, F2, F3, and F4) break up into ~20 separate UC H II regions. The individual sources have small resolved sizes (~10-3 pc), high derived emission measures (EM ~ 109 pc cm-6), and high rms electron densities (ne ~ 106 cm-3). We compare the observed radius and derived emission measure of each of these regions with those expected for a UC H II region in pressure equilibrium with its environment, using previously published temperatures and densities for the Sgr B2 molecular core (nH2=2×107 cm-3). We find that the observed emission measures are in fact higher than those predicted in a simple pressure-confinement model, suggesting that the molecular densities on scales that confine the UC H II regions may be higher than 2 × 107 cm-3.
Algorithmically random closed sets and probability

Algorithmic randomness in the Cantor space, 2ω, has recently become the subject of intense study. Originally defined in terms of the fair coin measure, algorithmic randomness has since been extended, for example in Reimann and Slaman [22, 23], to more general measures. Others have meanwhile developed definitions of algorithmic randomness for different spaces, for example the space of continuous functions on the unit interval (Fouche [8, 9]), more general topological spaces (Hertling and Weihrauch [12]), and the closed subsets of 2ω (Barmpalias et al. [1], Kjos-Hanssen and Diamondstone [14]). Our work has also been to develop a definition of algorithmically random closed subsets. We take a very different approach, however, from that taken by Barmpalias et al. [1] and Kjos-Hanssen and Diamondstone [14]. One of the central definitions of algorithmic randomness in Cantor space is Martin-Lof randomness. We use the probability theory of random closed sets (RACS) to prove that Martin-Lof randomness can be defined in the space of closed subsets of any locally compact, Hausdorff, second countable space. We then explore the Martin-Lof random closed subsets of the spaces N , 2ω, and R under different measures. In the case of 2ω we prove that the definitions of Barmpalias et al. [1] and Kjos-Hanssen and Diamondstone [14] are compatible with our approach. In the case of N we prove that the Martin-Lof random subsets are exactly those with Martin-Lof random characteristic functions. In the case of R we investigate the Martin-Lof random closed sets under generalized Poisson processes. This leads to a characterization of the Martin-Lof random elements of R as exactly the reals contained in some Martin-Lof random closed subset of R .
Deep Learning Model for Recognition of Handwritten Devanagari Numerals With Low Computational Complexity and Space Requirements

The broad application area and accompanying challenges make machine learning-based recognition of handwritten scripts a demanding field. Individuals’ writing practices and inherent variations in the size, shape, and tilt of characters may increase the difficulty level. Deep convolutional neural network (DCNN) models have been successful in solving pattern recognition problems, but at the expense of a considerable number of trainable parameters and heavy computational loads. The proposed work addresses these problems by using the shifted window (SWIN) transformer method to recognize handwritten Devanagari numerals for the first time. In the presented model, the SWIN transformer is finely tuned to withstand popular DCNN models, such as VGG-16Net, ResNet-50, and DenseNet-121, in terms of recognition accuracy, space requirement, and computational complexity. The model successfully attained a recognition accuracy of 99.20% with only 0.218 million trainable parameters and 0.0912 giga floating-point operations per second (FLOPs). This indicates the validity and soundness of the proposed model for recognizing handwritten Devanagari numerals.
APPLY BOLTZMANN EQUATION ANALYSIS TO ADVANCED TECHNIQUES

Some of advanced techniques exhibit many different types of spatial and temporal behavior,typically the analysis of such phenomena is based on a Boltzmann equation (BE). This paper presents some examples to explain that adopt Boltzmann equation description the phenomena of interest will be adequate. The elucidation consists of five separate parts,and each focuses on one aspect just as subtitle shows:1)Effect of BE analysis in ion motor.2)Apply BE analysis to gas laser.3)Utilizing lattice Boltzmann models to study diffusive properties.4)Using discrete BE to explore nonlinear chemically reacting systems.5)Apply BE analysis to explore the existence of antimatter.
A new parametric family for modelling cumulative incidence functions: application to breast cancer data

Summary. Competing risks situations can be encountered in many research areas such as medicine, social science and engineering. The main stream of analyses of those competing risks data has been nonparametric or semiparametric in the statistical literature. We propose a new parametric family to parameterize the cumulative incidence function completely. The new distribution is sufficiently flexible to fit various shapes of hazard patterns in survival data and increases the efficiency of the cumulative incidence estimates over the distribution‐free approaches. A simple two‐sample parametric test statistic is also proposed to compare the cumulative incidence functions between two groups at a given time point. The new parametric approach is illustrated by using breast cancer data sets from the National Surgical Adjuvant Breast and Bowel Project.
Reciprocal Effect of Environmental Stimuli to Regulate the Adipogenesis and Osteogenesis Fate Decision in Bone Marrow-Derived Mesenchymal Stem Cells (BM-MSCs)

Mesenchymal stem cells derived from bone marrow (BM-MSCs) can differentiate into adipocytes and osteoblasts. Various external stimuli, including environmental contaminants, heavy metals, dietary, and physical factors, are shown to influence the fate decision of BM-MSCs toward adipogenesis or osteogenesis. The balance of osteogenesis and adipogenesis is critical for the maintenance of bone homeostasis, and the interruption of BM-MSCs lineage commitment is associated with human health issues, such as fracture, osteoporosis, osteopenia, and osteonecrosis. This review focuses on how external stimuli shift the fate of BM-MSCs towards adipogenesis or osteogenesis. Future studies are needed to understand the impact of these external stimuli on bone health and elucidate the underlying mechanisms of BM-MSCs differentiation. This knowledge will inform efforts to prevent bone-related diseases and develop therapeutic approaches to treat bone disorders associated with various pathological conditions.
Renewable Carbon Materials as Electrodes for High-Performance Supercapacitors: From Marine Biowaste to High Specific Surface Area Porous Biocarbons

Waste, in particular, biowaste, can be a valuable source of novel carbon materials. Renewable carbon materials, such as biomass-derived carbons, have gained significant attention recently as potential electrode materials for various electrochemical devices, including batteries and supercapacitors. The importance of renewable carbon materials as electrodes can be attributed to their sustainability, low cost, high purity, high surface area, and tailored properties. Fish waste recovered from the fish processing industry can be used for energy applications and prioritizing the circular economy principles. Herein, a method is proposed to prepare a high surface area biocarbon from glycogen extracted from mussel cooking wastewater. The biocarbon materials were characterized using a Brunauer–Emmett–Teller surface area analyzer to determine the specific surface area and pore size and by scanning electron microscopy coupled with energy-dispersive X-ray analysis, Raman analysis, attenuated total reflectance Fourier transform infrared spectroscopy, X-ray diffraction, X-ray photoelectron spectroscopy, and transmission electron microscopy. The electrochemical characterization was performed using a three-electrode system, utilizing a choline chloride-based deep eutectic solvent (DES) as an eco-friendly and sustainable electrolyte. Optimal time and temperature allowed the preparation of glycogen-based carbon materials, with a specific surface area of 1526 m2 g–1, a pore volume of 0.38 cm3 g–1, and an associated specific capacitance of 657 F g–1 at a current density of 1 A g–1, at 30 °C. The optimal material was scaled up to a two-electrode supercapacitor using a DES-based solid-state electrolyte (SSE@DES). This prototype delivered a maximum capacitance of 703 F g–1 at a 1 A g–1 of current density, showing 75% capacitance retention over 1000 cycles, delivering the highest energy density of 0.335 W h kg–1 and power density of 1341 W kg–1. Marine waste can be a sustainable source for producing nanoporous carbon materials to be incorporated as electrode materials in energy storage devices.
Simultaneous low extinction and high local field enhancement in Ag nanocubes

We theoretically investigate surface plasmon resonance properties in Au and Ag cubic nanoparticles and find a novel plasmonic mode that exhibits simultaneous low extinction and high local field enhancement properties. We analyse this mode from different aspects by looking at the distribution patterns of local field intensity, energy flux, absorption and charge density. We find that in the mode the polarized charge is highly densified in a very limited volume around the corner of the nanocube and results in very strong local field enhancement. Perturbations of the incident energy flux and light absorption are also strongly localized in this small volume of the corner region, leading to both low absorption and low scattering cross section. As a result, the extinction is low for the mode. Metal nanoparticles involving such peculiar modes may be useful for constructing nonlinear compound materials with low linear absorption and high nonlinearity.
Experimental study of the friction torque on a disc rotating in viscous fluid around its horizontal diameter

If a disc is rotated in a fluid around its diameter, a reaction torque arises due to the viscosity of the fluid. In this study, we present the results of an experimental analysis of such a motion. Discs of several diameter have been rotated in water, while the torque and revolutionary speed has been recorded. The data sets are interpreted with the help of dimensionless quantities. Based on the experimental data, analytical formulae are given for the torque-angular velocity relationship and for the critical Reynolds number at which the laminar-turbulent transition occurs.
FLAME GPU 2: A framework for flexible and performant agent based simulation on GPUs

Agent based modelling (ABM) offers a powerful abstraction for scientific study in a broad range of domains. The use of agent based simulators encourages good software engineering design such as separation of concerns, that is, the uncoupling of the model description from its implementation detail. A major limitation in current approaches to ABM simulation is that of the trade off between simulator flexibility and performance. It is common that highly optimised simulations, such as those which target graphics processing units (GPU) hardware, are implemented as standalone software. This work presents a software framework (FLAME GPU 2) which balances flexibility with performance for general purpose ABM. Methods for ensuring high computational efficacy are demonstrated by, minimising data movement, and ensuring high device utilisation by exploiting opportunities for concurrent code execution within a model and through the use of ensembles of simulations. A novel hierarchical sub‐modelling approach is also presented which can be used to model certain types of recursive behaviours. This feature is shown to be essential in providing a mechanism to resolve competition for resources between agents within a parallel environment which would otherwise introduce race conditions. To understand the performance characteristics of the software, a benchmark model with millions of agents is used to explore the use of simulation ensembles and to parametrically investigate concurrent code execution within a model. Performance speedups are demonstrated of 3.5 ×$$ \times $$ and 10 ×$$ \times $$ respectively over a baseline GPU implementation. Our hierarchical sub‐modelling approach is used to demonstrate the implementation of a recursive algorithm to resolve competition of agent movement which occurs as a result of agent desire to simultaneously occupy discrete areas high in a ‘resource’. The algorithm is used to implement a classical socio‐economics model, Sugarscape, with populations of up to 16M agents.
L’effet de la rémunération monétaire et non monétaire sur la détresse psychologique : le cas du salaire, des augmentations de salaire et de la reconnaissance du superviseur

L’objectif de cette étude consiste à déterminer dans quelle mesure et de quelle manière les types de rétributions monétaires et non monétaires influencent le niveau de détresse psychologique. Les données ont été collectées auprès de 320 employés provenant d’établissements du secteur des finances et des assurances. Un test de médiation selon la méthode « bootstrap » a été effectué. Les résultats montrent que les perceptions d’équité des rétributions (sécurité d’emploi, salaire, reconnaissance, augmentation de salaire basée sur le rendement) agissent sur la détresse psychologique parce qu’elles signalent aux employés leur valeur (perception de justice distributive). De plus, les rétributions basées sur le rendement agissent également à travers l’interprétation que font les employés des objectifs à atteindre (ex. valeur et estime ; risques d’échec).
PRODUCTION OF HIGH GEOMETRIC RESOLUTION ORTHOPHOTOS BY PHOTOGRAMMETRIC APPROACH FOR THE ROYAL RACCONIGI CASTEL PARK DOCUMENTATION

: The aim of this work concerns the development of a simple and rigorous procedure for the construction of metric orthophotos in high geometric resolution and rich in detail through the use of terrestrial and UAV photogrammetry techniques. This approach has been tested on various datasets relating to the Racconigi Castle (Italy) and has allowed the state of the sites to be documented. All the orthophotos produced made it possible to identify the critical areas from a conservation point of view and, at the same time, to create a support tool that makes it possible to identify, with high precision, the damaged areas in a short time thanks to the georeferencing of the processed models.
Efficient Alternative for Construction of the Linear System Stemming from Numerical Solution of Heat Transfer Problems via FEM

This paper proposes an efficient alternative to construction of the linear system coming from a solution via the Finite Element Method that is able to significantly decrease the time of construction of this system. From the presentation of the methodology used and a numerical application it will be clear that the purpose of this work is to be able to decrease 6-7 times (on average) the linear system building time.