Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on key technologies of random stacking components automatically crawl

Given the growing demand for intelligence in industrial production, the key technology of robotic arm automatically crawling is being studied and realized using random stacking components as the research object. To begin, the global feature descriptor PPF algorithm is used to extract part features. The visible points that meet the conditions are then combined pairwise in the off-line training stage, and the characteristics of point pairs are calculated to obtain the model describing the object's global information. The components are identified during the online matching stage by employing a voting strategy based on the Hough transform. The RANSAC algorithm is then used for rough pose estimation, and the ICP algorithm is used to fine-tune the pose result to obtain the target's optimal pose estimation. Finally, the transformation matrix after hand-eye calibration based on differential evolution algorithm determines the position and posture of the parts in the real world coordinate system, guiding the manipulator to accurately grab and place the stacked parts. A grab system was built to test it as part of a water pump production line reconstruction project. Using the pump body as an example, the results show that the number of features of the selected point pair is 730,830, the matching accuracy can reach 94.64%, and the matching time consumption is 1.1424 s; the overall average grabbing success rate is 92.3%, which is practical.
Feature Extraction with Ordered Mean Values for Content Based Image Classification

Categorization of images into meaningful classes by efficient extraction of feature vectors from image datasets has been dependent on feature selection techniques. Traditionally, feature vector extraction has been carried out using different methods of image binarization done with selection of global, local, or mean threshold. This paper has proposed a novel technique for feature extraction based on ordered mean values. The proposed technique was combined with feature extraction using discrete sine transform (DST) for better classification results using multitechnique fusion. The novel methodology was compared to the traditional techniques used for feature extraction for content based image classification. Three benchmark datasets, namely, Wang dataset, Oliva and Torralba (OT-Scene) dataset, and Caltech dataset, were used for evaluation purpose. Performance measure after evaluation has evidently revealed the superiority of the proposed fusion technique with ordered mean values and discrete sine transform over the popular approaches of single view feature extraction methodologies for classification.
The processes with fractional order delay and PI controller design using particle swarm optimization

In this study, the stability analysis of systems with fractional order delay is presented. Besides, PI controller design using particle swarm optimization (PSO) technique for such systems is also presented. The PSO algorithm is used to obtain the controller parameters within the stability region. As it is known that it is not possible to investigate the stability of systems with fractional order delay using analytical methods such as the Routh-Hurwitz criterion. Furthermore, stability analysis of such systems is quite difficult. In this study, for stability testing of such systems, an approximation method previously introduced in the literature by the corresponding author is used. In addition, the unit step responses have been examined to evaluate the systems' performances. It should be noted that examining unit step responses of systems having fractional-order delay is not possible due to the absence of analytical methods. One of the aims of this study is to overcome this deficiency by using the proposed approximation method. Besides, a solution to the question of which controller parameter values should be selected in the stability region, which provides the calculation of all stabilizing PI controllers, is proposed using the PSO algorithm.
Results of a search for double positron decay and electron positron conversion of Kr-78

The results of a search for the 2[beta][sup +] and [ital K][beta][sup +] decay modes of [sup 78]Kr, in a coincidence experiment using a high pressure ionization chamber of enriched [sup 78]Kr inside an array of sodium iodine scintillators, are presented. After 4434 h of counting time, the half-life lower limits obtained are [ital T][sub 1/2]([ital K][beta][sup +])[sub 0[nu]][ge]5.1[times]10[sup 21] yr and [ital T][sub 1/2](2[beta][sup +])[sub 0[nu]+2[nu]][ge]2.0[times]10[sup 21] yr at 68% C.L.
Stability Analysis for a Class of Linear Switched Positive Systems

This paper addresses stability properties of linear switched positive systems composed of continuous-time subsystems and discrete-time subsystems. Based on the common linear copositive Lyapunov functions, stability of the positive systems is discussed under arbitrary switching. Moreover, a sufficient condition on the minimum dwell time that guarantees the stability of linear switched positive systems. The dwell time analysis interprets the stability of linear switched positive systems through the distance between the eigenvector sets. Thus, an explicit relation in view of stability is obtained between the family of the involved subsystems and the set of admissible switching signals.
A relevance-theoretic account of the way we use and understand the English temporal adverb again and its Norwegian counterpart igjen

The English temporal adverb again and the corresponding adverb igjen in Norwegian are words which do not encode a concept but rather an instruction to the audience to let the inferential phase of their comprehension process be guided by a specific contextual assumption. These adverbs have a procedural semantics in the sense of Relevance Theory, which distinguishes them semantically from an expression like once more or the prefix re-, both of which encode a conceptual meaning. English has a single lexical entry again whose encoded meaning is temporal yet not truth-conditional, and there is an exact correspondent igjen in the Norwegian lexicon, though Norwegian igjen in addition appears as two distinct non-temporal words encoding a concept and as a verbal particle forming a lexical entry together with a preceding verb. The full use range of the form igjen is found to be very similar to that of the Latin(ate) prefix re- as well as to the complex meaning of the verbal prefix ga- in the Niger-Congo language Ewe.
Attenuation compensation in mesh-domain OSEM SPECT reconstruction

A new method for attenuation compensation (AC) in mesh-domain SPECT OSEM reconstruction using strip-area approximation (SAAC) is introduced and compared to single-ray AC (SRAC). SAAC uses the polygonal area of the intersection of a mesh element (ME) and a tube-of-response (TOR) for defining an effective length of photon transit and an effective attenuation coefficient. This approach to AC is compared to SRAC, which defines the effective length of photon transit as the intersection of a single ray and a ME and the effective attenuation coefficient as the mean along the ray path. Comparative quantitative and qualitative analysis demonstrated that SAAC outperformed SRAC in terms of reconstruction image accuracy and quality.
Prospect of the search for W ′ in vector boson fusion at the high‑luminosity large hadron collider

A search for a new heavy charged gauge boson W ′ produced via a vector boson fusion process with two hard jets in pp collisions in the high-luminosity Large hadron collider (HL-LHC) environment is presented. The HL-LHC will increase the peak instantaneous luminosity to 7.5 × 10 34 cm − 2 s − 1 and the center of mass energy of 14 TeV to collect integrated luminosities up to 3 ab − 1 , which will significantly improve sensitivity for the observation of new heavy particles via rare processes. In this paper, to investigate the signal sensitivity for a W ′ we use the heavy vector triplet model, in the context of a simplified phenomenological approach, under Monte-Carlo simulations. The search targets events with one energetic electron and large missing transverse momentum, as well as two jets with a large separation in pseudorapidity. The expected upper limit for the mass of W ′ and exclusion limit contour on coupling parameters are presented at the 95% confidence level for an integrated luminosity of 3 ab − 1 .
Statistical Exploration from SARS

The outbreak of Severe Acute Respiratory Syndrome (SARS) posed a threat to people in many parts of the world, particularly Toronto, Singapore, Beijing, Hong Kong, and Taiwan. Most cities were totally unprepared for this disease. In this article, we provide several statistical problems on SARS based on publicly available data. Students can learn various statistical methods by use of this application and thus enhance their skill in statistical reasoning.
Formulation of Wave Equation for Calculating Velocity of Sound in Suspensions

A wave equation for the propagation of sound in suspensions or emulsions has been formulated from the simple considerations of mass and momentum balances on a sufficiently small homogeneous and compressible volume element of the suspension in the sound field. The induced masses of the non‐neutrally buoyant oscillating particles and the adiabatic compressibilities of suspension components have been shown to modify the equations of continuity and momentum and thereby the wave equation, with respect to those equations for the single‐phase suspending fluid. A formula for the velocity of sound in suspensions has been deduced, which agrees with that derived from the scattering theory.
Binding elucidation of azo dyes with human serum albumin via spectroscopic approaches and molecular docking techniques

Abstract The large number of synthesized azo dyes is widely applied in the food, pharmaceutical, cosmetic, textile, and leather industries. In this study, the binding mechanism of two synthesized dyes with human serum albumin (HSA); as the most abundant protein in plasma; was elucidated by fluorescence spectroscopy, Fourier-transform infrared spectroscopy and molecular modeling methods. The fluorescence quenching measurements showed that each dye can quench the intrinsic fluorescence of HSA via a dynamic quenching mechanism with an increase in concentration. From the thermodynamic data observations, revealed that the binding process is a spontaneous molecular force for each dye with HSA due to hydrophobic interactions and hydrogen bonding. FT-IR spectra showed that the secondary structure of the protein changes due to interaction of each dye with HSA. Furthermore, docking simulation demonstrated that the probable binding location of both dyes is subdomain IIA of HSA (Sudlow site I) and that complex formed is stabilized by hydrophobic interactions and hydrogen bonding. Communicated by Ramaswamy H. Sarma
In vitro characterization on the role of APOE polymorphism in human hippocampal neurogenesis

Hippocampal neurogenesis (HN) is considered an important mechanism underlying lifelong brain plasticity, and alterations in this process have been implicated in early Alzheimer's disease progression. APOE polymorphism is the most common genetic risk factor for late‐onset Alzheimer's disease where the ε4 genotype is associated with a significantly earlier disease onset compared to the neutral ε3 allele. Recently, APOE has been shown to play an important role in the regulation of HN. However, the time‐dependent impact of its polymorphism in humans remains elusive, partially due to the difficulties of studying human HN in vivo. To bridge this gap of knowledge, we used an in vitro cellular model of human HN and performed a time course characterization on isogenic induced pluripotent stem cells with different genotypes of APOE. We found that APOE itself was more highly expressed in ε4 at the stem cell stage, while the divergence of differential gene expression phenotype between ε4 and ε3 became prominent at the neuronal stage of differentiation. This divergence was not associated with the differential capacity to generate dentate gyrus granule cell‐like neurons, as its level was comparable between ε4 and ε3. Transcriptomic profiling across different stages of neurogenesis indicated a clear “maturation of functional neurons” phenotype in ε3 neural progenitors and neurons, while genes differentially expressed only in ε4 neurons suggested potential alterations in “metabolism and mitochondrial function. ” Taken together, our in vitro investigation suggests that APOE ε4 allele can exert a transcriptome‐wide effect at the later stages of HN, without altering the overall level of neurogenesis per se.
Efficacy and Safety of Vernonia cinerea for Smoking Cessation: An Open-Label Randomized Controlled Trial

This study aimed to compare the efficacy and safety of Vernonia cinerea (VC) and nortriptyline for smoking cessation. A randomized, active-comparator, open-label trial was conducted in 2019. A total of 84 patients participated in the study, and equally randomized with 42 participants in each group. Overall, there was no statistically significant difference of continuous abstinence rate (CAR) between VC and nortriptyline group (Odd ratio 0.68, 95%CI 0.25-1.85, P=0.451). After week 12, the end of treatment, CAR between both groups was not different (44.44% vs 45.95%, Odd ratio 0.77, 95%CI 0.23–2.54, P>0.999). After follow up by the end of research at week 24, the CAR in both groups was not different (41.67% vs 43.24%, Odd ratio 0.76, 95%CI 0.23–2.55, P>0.999). After week 24, relapse rate between VC and nortriptyline group was not different (13.89% vs 10.81%, P=0.923). In addition, both groups were effective in reducing the number of cigarettes per day compared to baseline. However, there was no difference between the groups. Overall, the VC group had an 8% smoking rate less than nortriptyline group, but not statistically significant (IRR 0.92, 95%CI 0.59-1.43, P=0.702). They also resulted in reducing the exhaled CO level at treatment period and wash out period (at week 12; 7(-17-20) vs 7(-12-16), mean difference 0.78, 95%CI -3.07-4.63, P>0.999, at week 24; 8(-5-22) vs 8.5(-5-17), mean difference 0.39, 95%CI -3.46-4.24, P>0.999). Overall, there was no difference between either group (mean difference -0.31, 95%CI -3.10-2.47). For safety data, adverse events including tongue bitter taste or numbness were found in VC group to be greater than in nortriptyline group (61.9% vs 30.95%, P=0.004), whereas dry mouth and drowsiness were greater found in nortriptyline group (35.71% vs 90.48%, P<0.001 and 16.67% vs 90.48%, P<0.001, respectively). Serious adverse events were not found. In smoking cessation, efficacy and safety of either VC or nortriptyline showed no difference.
Community and Policy Factors Influencing the Decision to Undergo Screening Mammography amongst Indian Women in the United Arab Emirates

Objective: This study explored the expectations, requirements, and recommendations and identifies the socio-ecological determinants for the informed uptake of screening mammography amongst expatriate women residing in the UAE. Methodology: A qualitative research approach was adopted using five focus group discussions. The study comprised two populations- those who had undergone screening mammography and those who had not. Thematic analysis- the six-phase model was adopted and modified for data analysis. Results: The factors that influence the rate of uptake of screening mammography by the participants were multifactorial and reciprocal. The community determinants identified are cultural beliefs, medical professionals, breast cancer survivors, community organizations, and media. The health policies in an expatriate’s home country and adopted country were found to have a considerable influence on the health behaviors of the participants. A comprehensive approach to change in health behavior is required to increase the informed uptake of screening mammography by expatriate women residing in the UAE. Conclusion: The study identified the need of developing migrant health units with community navigators, international health collaboration, migrant health directory, risk assessment team, automatic invitation system for screening, referral system, migrant cancer registry, and psychological support team in UAE. However, further studies are expected to give a wider perspective.
Influence of soil-transmitted helminth infections on physical activity, physical fitness, and cardiovascular disease risk in primary schoolchildren in Gqeberha, South Africa

Background/Aim: School-aged children in low- and middle-income countries carry the highest burden of intestinal helminth infections, such as soil-transmitted helminths (STH). STH infections have been associated with negative consequences for child physical and cognitive development and wellbeing. Thus, the aim of this study was to determine the association of STH infections in schoolchildren from Gqeberha, focusing on physical activity, physical fitness, and clustered cardiovascular disease (CVD) risk score. Methods: This cross-sectional study involved 680 schoolchildren (356 girls and 324 boys; mean age 8.19 years, SD 1.4) from disadvantaged communities in Gqeberha (formerly, Port Elizabeth), South Africa. Stool samples were collected and examined for STH infections using the Kato-Katz method. Physical activity (accelerometer) and physical fitness (grip strength, 20 m shuttle run) were measured using standard procedures. Furthermore, anthropometry, blood pressure, as well as glycated haemoglobin and lipid profile from capillary blood samples were assessed. We employed one-way ANOVAs to identify the associations of STH infections in terms of species and infection intensity with physical activity, physical fitness, and clustered CVD risk score. Results: We found a low STH infection prevalence (7.2%) in our study, with participants infected with at least one intestinal helminth species. In comparison to their non-infected peers, children infected with STH had lower mean grip strength scores, but higher mean VO2max estimation and higher levels of MVPA (p<.001). When considering type and intensity of infection, a positive association of A. lumbricoides infection and MVPA was found. In contrast, light T. trichiura-infected children had significantly lower grip strength scores compared to non-infected children. VO2max and MVPA were positively associated with light T. trichiura infection. No significant association between the clustered CVD risk score and infection with any STH species was evident. Conclusions: STH-infected children had lower grip strength scores than their non-infected peers, yet, achieved higher VO2max and MVPA scores. Our study highlights that the type and intensity of STH infection is relevant in understanding the disease burden of STH infections on childrens health. The findings of our study must be interpreted cautiously due to the low infection rate, and more research is needed in samples with higher prevalence rates or case-control designs.
Biomedical Image Reconstruction: A Survey

Biomedical image reconstruction research has been developed for more than five decades, giving rise to various techniques such as central and filtered back projection. With the rise of deep learning technology, biomedical image reconstruction field has undergone a massive paradigm shift from analytical and iterative methods to deep learning methods To drive scientific discussion on advanced deep learning techniques for biomedical image reconstruction, a workshop focusing on deep biomedical image reconstruction, MLMIR, is introduced and is being held yearly since 2018. This survey paper is aimed to provide basic knowledge in biomedical image reconstruction and the current research trend in biomedical image reconstruction based on the publications in MLMIR. This survey paper is intended for machine learning researchers to grasp a general understanding of the biomedical image reconstruction field and the current research trend in deep biomedical image reconstruction.
Strain-balanced GaAsP/InGaAs quantum well solar cells

A strain-balance multiquantum well (MQW) approach to enhance the GaAs solar cell efficiency is reported. Using a p-i-n diode structure, the strain-balanced GaAsP/InGaAs MQW is grown on a GaAs substrate and equals a good GaAs cell in terms of power conversion efficiency. The cell design is presented together with measurements of the forward bias dark current density, quantum efficiency, and 3000 K light-IV response. Cell efficiencies under standard air mass (AM) 1.5 and AM 0 illumination are projected from experimental data and the suitability of this cell for enhancing GaInP/GaAs tandem cell efficiencies is discussed.
Robust variance-regularized risk minimization with concomitant scaling

Under losses which are potentially heavy-tailed, we consider the task of minimizing sums of the loss mean and standard deviation, without trying to accurately estimate the variance. By modifying a technique for variance-free robust mean estimation to fit our problem setting, we derive a simple learning procedure which can be easily combined with standard gradient-based solvers to be used in traditional machine learning workflows. Empirically, we verify that our proposed approach, despite its simplicity, performs as well or better than even the best-performing candidates derived from alternative criteria such as CVaR or DRO risks on a variety of datasets.
Neural Wasserstein Gradient Flows for Maximum Mean Discrepancies with Riesz Kernels

Wasserstein gradient flows of maximum mean discrepancy (MMD) functionals with non-smooth Riesz kernels show a rich structure as singular measures can become absolutely continuous ones and conversely. In this paper we contribute to the understanding of such flows. We propose to approximate the backward scheme of Jordan, Kinderlehrer and Otto for computing such Wasserstein gradient flows as well as a forward scheme for so-called Wasserstein steepest descent flows by neural networks (NNs). Since we cannot restrict ourselves to absolutely continuous measures, we have to deal with transport plans and velocity plans instead of usual transport maps and velocity fields. Indeed, we approximate the disintegration of both plans by generative NNs which are learned with respect to appropriate loss functions. In order to evaluate the quality of both neural schemes, we benchmark them on the interaction energy. Here we provide analytic formulas for Wasserstein schemes starting at a Dirac measure and show their convergence as the time step size tends to zero. Finally, we illustrate our neural MMD flows by numerical examples.
Learning Vortex Dynamics for Fluid Inference and Prediction

We propose a novel differentiable vortex particle (DVP) method to infer and predict fluid dynamics from a single video. Lying at its core is a particle-based latent space to encapsulate the hidden, Lagrangian vortical evolution underpinning the observable, Eulerian flow phenomena. Our differentiable vortex particles are coupled with a learnable, vortex-to-velocity dynamics mapping to effectively capture the complex flow features in a physically-constrained, low-dimensional space. This representation facilitates the learning of a fluid simulator tailored to the input video that can deliver robust, long-term future predictions. The value of our method is twofold: first, our learned simulator enables the inference of hidden physics quantities (e.g., velocity field) purely from visual observation; secondly, it also supports future prediction, constructing the input video's sequel along with its future dynamics evolution. We compare our method with a range of existing methods on both synthetic and real-world videos, demonstrating improved reconstruction quality, visual plausibility, and physical integrity.