Miracle-dz/UniFAR-FTUs huggingface dataset:
Query Processing Over RelationalCross Model in Uncertain and Probabilistic Databases

In real world, Database stores the information of object. The management of database system provide to load, access, and manipulate the information. Data stored in database is either certain and uncertain. The certain data are those data whose value is known and fixed. If the certain attribute value is not known, then it will have treated as Null value. The uncertain data is data whose value is unknown and not fixed. Its value is uncertain, and its presence is uncertain. In uncertain databases, for particular attribute value is not known so it will be stored alternatives of value with assurance value. There are many existing real-world applications which required uncertain data with assurance value. There are some existing database management systems developed for UPDB like TRIO, ULDB etc. Each system is designed with own organisation and management strategies for organizing uncertain data and its features is suitable for some applications and has some downside also. The center of attention of the paper is towards a new proposed RelationalCross model for organizing uncertain and probabilistic data into database. It expresses, how different types of queries gets processed and transformed using RelationalCross on uncertain databases
Multidimensional TOMBO imaging and its applications

We present a framework of multi-dimensional compound-eye imaging with the thin observation module by bound optics (TOMBO) and its applications. In the system, each of sub-optics equips optical coding elements to shear or to weight the multi-dimensional object information along the axial direction. The encoded information is integrated onto the detectors in the sub-optics. The object is reconstructed by a compressive sensing algorithm. The framework can be applied to various optical information acquisitions. We describe some applications of the framework including spectral imaging, polarization imaging, and so on.
Secondary Controller for Voltage and Frequency Regulation in an Islanded Microgrid System Based on Anti-Windup Loop

This paper presents an anti-windup (AW) proportional-integral (PI) secondary controller for both voltage and frequency restoration and stabilization for a stand-alone Microgrid (MG) system. The MG comprises four distributed generations (DGs) with distributed droop-based primary control systems and a centralized AW based secondary controller. The significance of this research is using a clamping model of the AW proportional-integral (AWPI) controller to suppress the possible overshoot or undershoot of the control signal during the secondary control operation and reduce the settling time of the PI controller. The suggested technique considers the voltage and frequency coupling in the stand-alone MG system. Some load and generation change scenarios are also modelled to approve the plug-and-play capability of this novel control fashion. In the end, the performance of the proposed control system is verified by using MATLAB®/SIMULIMK software.
Pemanfaatan Linkedin Sebagai Digital Marketing PT Vfirst Komunikasi Indonesia Dalam Membangun Brand Awareness di Indonesia

The digital era, provides opportunities for B2B companies to market their products through social media. Social media is one of the digital marketing strategies that are most chosen by business people because it is effective enough to connect with customers so that it can create brand awareness, generate leads, audience conversions, and more. This is the goal of PT. VFirst Communications Indonesia or commonly called VFirst, to implement digital marketing strategies. However, VFirst does not yet have a strong marketing team in doing digital marketing because all marketing activities are still being taken over and regulated by the central marketing team in India. VFirst in Indonesia entrusts Lead Generation to carry out digital marketing strategies by using LinkedIn to build brand awareness. This study was conducted to determine the use of LinkedIn as VFirst digital marketing in building brand awareness. The research method used is qualitative with in-depth interview data collection techniques. The results showed that the implementation of digital marketing through LinkedIn in building brand awareness in accordance with the main concepts used, with the selection of appropriate channels and interesting content as well as an approach to prospective customers carried out by the Lead Generation division succeeded in creating brand awareness from VFirst at the stage of recognition as a digital communication solution company.
Changes in gender differences in household poverty in Kenya

Abstract Gender poverty differences in households are likely to affect female-headed households more than male-headed households. This paper examined the evolution of the gender poverty rate gap and identified the factors that underlie differences in poverty rates between female-headed households and male-headed households using the most recent representative household surveys conducted by the Kenya National Bureau of Statistics in 2005/06 and 2015/16. An extended Blinder-Oaxaca decomposition analysis with nonlinear regression was performed. The findings indicate that poverty rates for female-headed households and male-headed households declined from 38.56 to 32.73% in 2005/06 to 30.23 and 26.04% in 2015/16, respectively. Although female-headed households (1.12) have a higher chance of falling into poverty than male-headed households (0.95), the decline in the poverty rate was higher for female-headed households (8.33%) than for male-headed households (6.69%). Therefore, the results do not support the feminization of poverty hypothesis in Kenya. Factors that have bridged the gender poverty gap include cash transfers that explain 11.02% of the gaps, literacy (53.97%), university education (10.39%), secondary education (40.84%), employment in public and private sectors (26.66%) and business employment (10.58%). Recommended policies include the implementation of the gender policy and affirmative action, enhancing literacy levels, and secondary and university enrolment.
Jellyfishes—Significant Marine Resources with Potential in the Wound-Healing Process: A Review

The wound-healing process is a significant area of interest in the medical field, and it is influenced by both external and patient-specific factors. The aim of this review paper is to highlight the proven wound-healing potential of the biocompounds found in jellyfish (such as polysaccharide compounds, collagen, collagen peptides and amino acids). There are aspects of the wound-healing process that can benefit from polysaccharides (JSPs) and collagen-based materials, as these materials have been shown to limit exposure to bacteria and promote tissue regeneration. A second demonstrated benefit of jellyfish-derived biocompounds is their immunostimulatory effects on growth factors such as (TNF-α), (IFN-γ) and (TGF), which are involved in wound healing. A third benefit of collagens and polysaccharides (JSP) is their antioxidant action. Aspects related to chronic wound care are specifically addressed, and within this general theme, molecular pathways related to tissue regeneration are explored in depth. Only distinct varieties of jellyfish that are specifically enriched in the biocompounds involved in these pathways and live in European marine habitats are presented. The advantages of jellyfish collagens over mammalian collagens are highlighted by the fact that jellyfish collagens are not considered transmitters of diseases (spongiform encephalopathy) or various allergic reactions. Jellyfish collagen extracts stimulate an immune response in vivo without inducing allergic complications. More studies are needed to explore more varieties of jellyfish that can be exploited for their biocomponents, which may be useful in wound healing.
A CNN-Based Wearable System for Driver Drowsiness Detection

Drowsiness poses a serious challenge to road safety and various in-cabin sensing technologies have been experimented with to monitor driver alertness. Cameras offer a convenient means for contactless sensing, but they may violate user privacy and require complex algorithms to accommodate user (e.g., sunglasses) and environmental (e.g., lighting conditions) constraints. This paper presents a lightweight convolution neural network that measures eye closure based on eye images captured by a wearable glass prototype, which features a hot mirror-based design that allows the camera to be installed on the glass temples. The experimental results showed that the wearable glass prototype, with the neural network in its core, was highly effective in detecting eye blinks. The blink rate derived from the glass output was highly consistent with an industrial gold standard EyeLink eye-tracker. As eye blink characteristics are sensitive measures of driver drowsiness, the glass prototype and the lightweight neural network presented in this paper would provide a computationally efficient yet viable solution for real-world applications.
Subgrid-scale modelling for the large-eddy simulation of high-Reynolds-number boundary layers

It has been recognized that the subgrid-scale (SGS) parameterization represents a critical component of a successful large-eddy simulation (LES). Commonly used linear SGS models produce erroneous mean velocity profiles in LES of high-Reynolds-number boundary layer flows. Although recently proposed approaches to solving this problem have resulted in significant improvements, questions about the true nature of the SGS problem in shear-driven high-Reynolds-number flows remain open. We argue that the SGS models must capture inertial transfer effects including backscatter of energy as well as its redistribution among the normal SGS stress components. These effects are the consequence of nonlinear interactions and anisotropy. In our modelling procedure we adopt a phenomenological approach whereby the SGS stresses are related to the resolved velocity gradients. We show that since the SGS stress tensor is not frame indifferent a more general nonlinear model can be applied to the SGS parameterization. We develop a nonlinear SGS model capable of reproducing the effects of SGS anisotropy characteristic for shear-driven boundary layers. The results obtained using the nonlinear model for the LES of a neutral shear-driven atmospheric boundary layer show a significant improvement in prediction of the non-dimensional shear and low-order statistics compared to the linear Smagorinsky-type models. These results also demonstrate a profound effect of the SGS model on the flow structures.
Ground-based synoptic instrumentation for solar observations

We will describe the status of current ground-based solar spectroscopic and imaging instruments used in solar observations. We will describe the advantages and disadvantages of using these two classes of instruments with examples drawn from the Improved Solar Optical Observing Network (ISOON) and Synoptic Long Term Investigations of the Sun (SOLIS) Network. Besides instrumental requirements and lessons learned from existing ground-based instruments, this talk will also focus on the future needs and requirements of ground-based solar optical observations.
Target Capturability Using Agents in Cyclic Pursuit

In the literature, several variants of the conventional cyclic pursuit law have been discussed. In this paper, one such variant, a modified heterogeneous cyclic pursuit scheme, has been proposed to capture a moving target. As a special case, when the target is stationary, the problem of capturing the target becomes the same as the rendezvous problem. The control laws proposed here ensure that such fixed targets (points) can always be collectively captured ( reached) and a maneuvering target can be captured, provided that the agents can rendezvous at its initial position. Agents with double-integrator dynamics have also been considered, and a suitable cyclic pursuit law has been proposed to ensure global reachability and target capturability for bounded target maneuver. The theoretical findings are backed by simulation results.
Moderate Aerobic Exercise Reduces the Detrimental Effects of Hypoxia on Cardiac Autonomic Control in Healthy Volunteers

Physical inactivity increases cardiometabolic risk through a variety of mechanisms, among which alterations of immunological, metabolic, and autonomic control systems may play a pivotal role. Physical inactivity is frequently associated with other factors that may further worsen prognosis. The association between physical inactivity and hypoxia is particularly interesting and characterizes several conditions—whether physiological (e.g., residing or trekking at high altitude and space flights) or pathological (e.g., chronic cardiopulmonary diseases and COVID-19). In this randomized intervention study, we investigated the combined effects of physical inactivity and hypoxia on autonomic control in eleven healthy and physically active male volunteers, both at baseline (ambulatory) conditions and, in a randomized order, hypoxic ambulatory, hypoxic bedrest, and normoxic bedrest (i.e., a simple experimental model of physical inactivity). Autoregressive spectral analysis of cardiovascular variabilities was employed to assess cardiac autonomic control. Notably, we found hypoxia to be associated with an impairment of cardiac autonomic control, especially when combined with bedrest. In particular, we observed an impairment of indices of baroreflex control, a reduction in the marker of prevalent vagal control to the SA node, and an increase in the marker of sympathetic control to vasculature.
Grapho-motor imitation training in children with handwriting difficulties: A single-center pilot study

Abstract Imitation is a crucial process for learning and brain development. It is based on the mirror neuron mechanism and underlies our understanding of actions and the gestures of others. Some researchers hypothesized a possible correlation between a low functioning mirror neuron system (MNS) and developmental coordination disorder, including dysgraphic deficit. However, no studies have verified whether imitation of graphic gestures by exploiting the properties of the MNS could improve handwriting. This study evaluates the effects of imitation training of handwriting in five children with handwriting difficulties aged 8 to 10 years. The training lasted for five months, and was undertaken three times a week, for a total number of 60 sessions for each child. Before and after the training, we evaluated the degree of handwriting impairment using the Concise Evaluation Scale for Children’s Handwriting (BHK). Our results suggest that handwriting imitation training produced a significant qualitative change in the children’s writing, likely due to exercises that stimulated fine motor imitation. Furthermore, the imitation also involved ergonomic and biomechanical aspects relevant to improving imitative writing after observing the model. Each child has therefore reached an adequate level of writing, suggesting the effectiveness of the proposed intervention.
Robust Vision SLAM Based on YOLOX for Dynamic Environments

Simultaneous localization and mapping (SLAM) is used in almost all intelligent robots. Recently, many excellent SLAM systems have been developed with good performance and impressive ideas. However, there are many problems that do not have a good solution. For example, when dynamic objects in the system are so perturbed that the system is unstable. This paper proposes a visual SLAM in a dynamic environment, called YOLOX-SLAM, which has good robustness. In YOLOX-SLAM, four threads run in parallel: tracking, object detection, local mapping, and loop closure. YOLOX-SLAM uses YOLO object detection to detect dynamic objects and eliminate dynamic feature points. Good accuracy is achieved in a dynamic environment, reducing the influence of dynamic objects. Our experiments were validated on the TUM RGB-D dataset. The results show that YOLOX-SLAM has better accuracy than ORB-SLAM2 in highly dynamic scenarios.
Specific Intelligent Traits of a Kind of Quarternary Wavelet Packs with an Integer-Valued Expansive Dilation Matrix

In this work, the notion of orthogonal nonseparable quarternary wavelet packs, which is the generalization of orthogonal univariate wavelet packs, is introduced. The definition for orthogonal nonseparable quarternary wavelet packs is presented by iteration method. The orthogonality characters of quarternary wavelet packs are discussed. Three orthogonality formulas concerning these wavelet packets are estabished. Moreover, it is shown how to obtain new orthogonal bases of space from these wavelet packets.
Influence of Structural Characteristics for Optical Fiber Composite Overhead Ground Wire on Current Density Distribution under Lightning Strikes

When Optical Fiber Composite Overhead Ground Wire (OPGW) is struck by lightning, the damage or rupture accident occur. This is unacceptable for the stable operation of the power system and the safe transmission of the communication system. Therefore, the investigation on the lightning-induced damage mechanism of OPGW is significant for the optimization of lightning protection measures. Combined with the structural characteristics of OPGW, this paper calculated current density distribution of OPGW caused by lightning strike, which provided the data support for the damage mechanism research. Firstly, the magnetohydrodynamics (MHD) models based on OPGW and plate structure were established. Then, the current density distributions of OPGW and plate under lighting strikes were compared. The result shows that the maximum current density on the surface of the OPGW is greater than that on the surface of the plate. Moreover, the distribution range of current density on the surface of the OPGW is smaller than that on the surface of the plate. Therefore, in order to accurately establish the numerical modeling of thermal ablation damage of OPGW, it is necessary to consider the influence of structural characteristics of OPGW on current density distribution.
A mini review of the effect of modified carbon paper, carbon felt, and carbon cloth electrodes on the performance of microbial fuel cell

ABSTRACT Microbial fuel cells (MFCs) have attracted much interest as an alternative energy conversion technology and as a system for recovering and treating wastewater. MFC is a powerful technique for generating energy from various sources, including natural organic matter and renewable biomass. It has several possible applications, including power generation for many small electronic devices, wastewater treatment, and biosensors. However, the restricted power output of MFCs is the most significant impediment to their widespread use and up-scaling in practical applications. The anode electrode is the most critical component of an MFC, where poor anode electrode performance leads to poor MFC efficiency. Therefore, efforts have been made to modify electrodes to improve their performance. While power density is an essential metric in determining MFC efficiency, other parameters such as Coulombic efficiency, current density, cell voltage, and the removal rate of chemical oxygen demand (COD) should also be considered to evaluate the performance of MFC. This study reviews the most recent electrode modification techniques through anode treatments with metal oxides, conductive polymers, carbon nanotubes, and other chemical compounds as well as through cathode modifications. Different modified MFCs are compared in terms of their power density and the type of bacteria and membrane used.
Adaptively Integrative Association between Multivariate Phenotypes and Transcriptomic Data for Complex Diseases

Phenotype–gene association studies can uncover disease mechanisms for translational research. Association with multiple phenotypes or clinical variables in complex diseases has the advantage of increasing statistical power and offering a holistic view. Existing multi-variate association methods mostly focus on SNP-based genetic associations. In this paper, we extend and evaluate two adaptive Fisher’s methods, namely AFp and AFz, from the p-value combination perspective for phenotype–mRNA association analysis. The proposed method effectively aggregates heterogeneous phenotype–gene effects, allows association with different data types of phenotypes, and performs the selection of the associated phenotypes. Variability indices of the phenotype–gene effect selection are calculated by bootstrap analysis, and the resulting co-membership matrix identifies gene modules clustered by phenotype–gene effect. Extensive simulations demonstrate the superior performance of AFp compared to existing methods in terms of type I error control, statistical power and biological interpretation. Finally, the method is separately applied to three sets of transcriptomic and clinical datasets from lung disease, breast cancer, and brain aging and generates intriguing biological findings.
A singularity–induced bifurcation theorem for infinite–dimensional implicit dynamical systems

In this note we study a class of partial differential equations whose formal structure resembles the semi–explicit, index–1 form from the theory of differential–algebraic equations. It is known from the theory of such problems that one can encounter simple poles in the eigenvalue loci of parameter–dependent linearizations, leading to the loss of linear stability without the presence of steady–state bifurcations. We demonstrate how this carries over to implicitly defined problems on a Hilbert space.
Soliton dynamics of an extended phi4 model with dissipation and an external field

The authors present an analytical and numerical study of the dynamics of the nonlinear excitations in an extended phi 4 nonlinear chain with a constant external field including nonlinear inter-particle coupling along the chain. In the absence of damping the kink is accelerated but its velocity is limited by the emission of sound waves, due to narrowing of the kink. The stability of envelope solitons in the presence of the external field and as a function of the potential parameters is examined. With dissipation the kinks move uniformly with a field-dependent velocity except at high fields. For a dimerised interaction between nearest neighbours they obtain small-amplitude 'optical kinks' whose dynamics are studied. Finally, the results are generalised for a diatomic chain and possible extensions and applications for hydrogen-bonded chains are discussed.
The M/M /∞ queue in a random environment

The M/M/∞ queue in a random environment is an infinite-server queue where arrival and service rates are stochastic processes. Here we study the steady-state behavior of such a system. Explicit results are obtained for the factorial moments, the impossibility of a ‘matrix-Poisson' steady-state distribution is demonstrated and two numerical examples are presented.
Self-steepening and intrapulse Raman scattering for supercontinuum generation in optimized photonic crystal fiber at 1.3 μm

In this work, we design a highly nonlinear noncircular core photonic crystal fiber (HNL-PCF) for the generation of a supercontinuum (SC) at 1.3 μm having minimum anomalous dispersion and using many nonlinear effects by introducing self-phase modulation (SPM), self-steepening and Raman effects. The proposed geometry of the HNL-PCF is composed of six rings of air-holes and silica as a background material for the core. Using the vectorial Finite Element method (FEM) with a perfectly matched layer (PML), the proposed HNL-PCF is numerically modeled for determining its characteristics as Group Velocity Dispersion (GVD) and nonlinear properties. After optimizing the properties of the proposed HNL-PCF (GVD= - 0.95 ps2/km; γ= 55.45 [W.km]-1 around 1.3 μm), the SC is generated by solving the nonlinear Schrodinger equation (NLSE), that contains different parameters of the cited nonlinear effects, with split-step Fourier method (SSFM). The introducing of this different effects in our work allows to generate a SC of spectral bandwidth SBW=260 nm at 1,3 μm using only 1.89 mm long of PCF.