Miracle-dz/UniFAR-FTUs huggingface dataset:
The new approach for infrared target tracking based on the particle filter algorithm

Target tracking on the complex background in the infrared image sequence is hot research field. It provides the important basis in some fields such as video monitoring, precision, and video compression human-computer interaction. As a typical algorithms in the target tracking framework based on filtering and data connection, the particle filter with non-parameter estimation characteristic have ability to deal with nonlinear and non-Gaussian problems so it were widely used. There are various forms of density in the particle filter algorithm to make it valid when target occlusion occurred or recover tracking back from failure in track procedure, but in order to capture the change of the state space, it need a certain amount of particles to ensure samples is enough, and this number will increase in accompany with dimension and increase exponentially, this led to the increased amount of calculation is presented. In this paper particle filter algorithm and the Mean shift will be combined. Aiming at deficiencies of the classic mean shift Tracking algorithm easily trapped into local minima and Unable to get global optimal under the complex background. From these two perspectives that "adaptive multiple information fusion" and "with particle filter framework combining", we expand the classic Mean Shift tracking framework . Based on the previous perspective, we proposed an improved Mean Shift infrared target tracking algorithm based on multiple information fusion. In the analysis of the infrared characteristics of target basis, Algorithm firstly extracted target gray and edge character and Proposed to guide the above two characteristics by the moving of the target information thus we can get new sports guide grayscale characteristics and motion guide border feature. Then proposes a new adaptive fusion mechanism, used these two new information adaptive to integrate into the Mean Shift tracking framework. Finally we designed a kind of automatic target model updating strategy to further improve tracking performance. Experimental results show that this algorithm can compensate shortcoming of the particle filter has too much computation, and can effectively overcome the fault that mean shift is easy to fall into local extreme value instead of global maximum value . Last because of the gray and fusion target motion information, this approach also inhibit interference from the background, ultimately improve the stability and the real-time of the target track.
Exploring Orthogonality between Halogen and Hydrogen Bonding Involving Benzene

The concept of orthogonality between halogen and hydrogen bonding, brought out by Ho and coworkers some years ago, has become a widely accepted idea within the chemists’ community. While the original work was based on a common carbonyl oxygen as acceptor for both interactions, we explore here, by means of M06-2X, M11, ωB97X, and ωB97XD/aug-cc-PVTZ DFT calculations, the interdependence of halogen and hydrogen bonding with a shared π-electron system of benzene. The donor groups (specifically NCBr and H2O) were placed on either or the same side of the ring, according to a double T-shaped or a perpendicular geometry, respectively. The results demonstrate that the two interactions with benzene are not strictly independent on each other, therefore outlining that the orthogonality between halogen and hydrogen bonding, intended as energetical independence between the two interactions, should be carefully evaluated according to the specific acceptor group.
Positioning accuracy measurement method of bucket-wheel reclaimer based on 3D lidar

Three-Dimensional LiDAR is one of the sensors used for Simultaneous Localization and Mapping (SLAM) algorithms. SLAM algorithms are widely applied in the field of autonomous driving and mobile robotics, providing a framework for autonomous motion by incorporating data acquisition, front-end odometry, loop detection, back-end optimization, and accuracy evaluation. Accuracy evaluation in SLAM algorithms typically involves comparing the measured trajectory obtained from SLAM with a reference trajectory computed using higher-precision sensors such as motion capture systems or laser total stations. In this study, to achieve unmanned operation of bucket-wheel reclaimer in material yards, a three-dimensional LiDAR sensor is utilized for SLAM algorithms to achieve precise positioning of the wheel loader and establish a three-dimensional digital model of the material pile. To verify the positioning accuracy of the SLAM algorithms in a dusty environment of the material yard, a least squares method is employed to calculate the actual trajectory of the bucket-wheel reclaimer (make its arm performing a circular motion This actual trajectory serves as the reference for evaluation of SLAM), thereby avoiding the need for expensive high-precision sensors. By utilizing this approach, the accuracy of the SLAM algorithms in material yard environments is obtained. To validate the reliability of this method and the accuracy evaluation, this study first verifies the fitting performance of the reference trajectory using the mechanical dimensions of the bucket-wheel reclaimer itself. Furthermore, the accuracy evaluated through this method is validated by assessing the mapping results (mapping and Positioning is Simultaneous for SLAM. Positioning accuracy is same with Mapping).
VLSI interconnects and their testing: prospects and challenges ahead

Purpose – The purpose of this paper is to explore the functioning of very‐large‐scale integration (VLSI) interconnects and modeling of interconnects and evaluate different approaches of testing interconnects.Design/methodology/approach – In the past, on‐chip interconnect wires were not considered in circuit analysis except in high precision analysis. Wiring‐up of on‐chip devices takes place through various conductors produced during fabrication process. The shrinking size of metal‐oxide semiconductor field effect transistor devices is largely responsible for growth of VLSI circuits. With deep sub‐micron (DSM) technology, the interconnect geometry is scaled down for high wiring density. The complex geometry of interconnects and high operational frequency introduce wire parasitics and inter‐wire parasitics. These parasitics causes delay, power dissipation, and crosstalk that may affect the signal integrity in VLSI system. Accurate analysis, sophisticated design, and effective test methods are the requiremen.
Screening Life Cycle Environmental Impacts and Assessing Economic Performance of Floating Wetlands for Marine Water Pollution Control

The growing environmental awareness of society, the advancement of nature-based solutions (NbSs), and the need for reliable and cost-effective solutions create a favorable environment of opportunities for floating wetlands as alternative solutions for marine water pollution control. The aim of this work was to screen, through OpenLCA, the environmental impacts of floating wetlands for marine water pollution control at various life cycle stages of the system, and assess its economic performance and contribution to the welfare of society. The stage of raw materials production and acquisition was found to be responsible for the main environmental impacts of the floating wetlands, especially on global warming potential, whereas the main impact of the operational stage was related to the eutrophication potential due to N and P residuals in the effluent. The economic performance indicators of economic net present value (ENPV), economic rate of return (ERR), and benefits/costs ratio (B/C ratio) indicate, although marginally, that floating wetlands may constitute a viable investment with potential positive socioeconomic impacts. However, there are still several scientific challenges and technical issues to be considered for the operational application of such systems at full-scale in marine environments.
Modeling and Predicting Commuters' Travel Mode Choice in Lahore, Pakistan

The travel mode preference exists in both culture and theenvironment. The wide scale of people's mobility makesour cities more polluted and congested, eventually affecting urban assets.Understanding people’s mode choice is important to develop urbantransportation planning policies effectively. This study aims to model andpredict the commuter’s mode choice behaviour in Lahore, Pakistan. A surveywas conducted, and the data was used for model validation. Thecomparative study was further done among multinomial logit model (MNL),Random Forest (RF), and K-Nearest Neighbor (KNN) classificationapproaches. It’s common in existing studies that vehicle ownership is rankedas the most important among all features impacting commuters’ travel modechoice. Since many commuters in Lahore own no vehicle, it’s unclear whatthe rank of factors impacting non-vehicle owners is. Other than thecomparison of predicting the performance of the methods, our contributionis to do more analysis of the rank of factors impacting the different types ofcommuters. It was observed that occupation is ranked as the most importantamong all features for non-vehicle owners.
Spectrophotometric estimation of para-aminophenol via oxidative coupling reaction with 4-chlororesorcinol –Application to paracetamol

A simple and sensitive spectrophotometric method has been suggested for the estimation of pure paminophenol(p-AMPL), and p-AMPL results from the hydrolysis of paracetamol (PARL). The suggested method is based on oxidative coupling reaction of p-AMPL with 4-chlororesorcinol and potassium periodate to produce a stable, and water-soluble colored product with maximum absorption at wavelength 556 nm. Beer's law is followed over the range of concentration from 2 to 20 μg. ml-1. The molar absorptivity value is equal to 1.0356×104 l.mol-1cm-1. All factors responsible for the completed reaction and highest intensity of the product have been studied, and the optimal of each factor has been selected. The suggested method was applied in an indirect method for the determination of paracetamol in tablets and injection after acidic hydrolysis to p-AMPL. The common excipients added did not interfere in the estimation of paracetamol.
Examining Motivator Factors of STEM Undergraduate Persistence through Two-Factor Theory

ABSTRACT This study investigates undergraduate STEM persistence through two-factor theory. Using nationally representative data and multinomial regression, we conceptualize known determinants of persistence as hygiene and motivator factors to test the persistence outcomes among college students who majored in STEM: earning a STEM degree, non-STEM degree, and degree non-completion. We propose that hygiene factors provide a baseline means of persistence in higher education, whereas the motivator factors improve the probability of student persistence in STEM majors. Our findings demonstrated that motivator factors improve the persistence model when added to hygiene factors. Hygiene factors were generally associated with STEM persistence by staying in college, while motivator factors mostly predicted persistence by remaining in the STEM major. Given the importance of motivator factors, we also tested the differential relationship between motivator factors and student persistence in STEM majors by gender and race/ethnicity due to underrepresentation in STEM fields.
A survey of today's CVT controls

For over one hundred years, the principle of continuously and infinitely variable transmissions (C/IVT) has eluded practical automotive utility. With the advent of durable materials, sophisticated electronic controls, and improved lubricants, a viable assortment of C/IVT powertrain systems with innovative ratio shift control strategies is now feasible. A few of these progressive system designs are described in this survey. Pertinent fundamental relationships of C/IVT powertrains are also discussed.
Designing smart living for ageing Alice – and the persons next door

ABSTRACT This article presents the co-design and development process for a home control system in the context of a healthcare ecology for older people accessing care home services. The contribution of this article is threefold: (1) it presents a design-oriented, user-centred approach for studying intelligent environments (IE); (2) it describes an ontology-based architecture that provides the foundation for the system, and (3) it introduces a proof-of-concept tool for creating and customizing IE services. The article dedicates the system to ‘Alice’, a central persona created for the initial research scenarios, representing a new arrival at a residential care home. This article illustrates the multifaceted design process and considers the challenges of linking Alice's ‘intelligent apartment’ to all the other apartments next to, and beyond, hers.
Supervisory control and data acquisition data-based non-linear state estimation technique for wind turbine gearbox condition monitoring

Offshore wind energy is catching increasing worldwide interest. However, access and maintenance offshore can be difficult and will be more costly than onshore, and hence, availability is correspondingly lower. As a result, there is a growing interest in wind turbine condition monitoring with condition-based rather than responsive and scheduled maintenance. A non-linear state estimation technique (NSET) model is presented here to model a healthy wind turbine gearbox using stored historical data. These data capture the inter-relationship between the model input and output parameters. The state vectors comprising the data should cover as much as turbine operational range, including the extreme conditions in order to obtain an accurate model performance. A model so constructed can be applied to assess the operational data. Welch's t-test is employed in the fault detection algorithm, together with suitable time series filtering, to identify incipient anomalies in the turbine gearbox before they develop into catastrophic faults. Two case studies based on 10-minute supervisory control and data acquisition data from a commercial wind farm are presented to demonstrate the model's effectiveness. Comparison is made with neural network modelling, and the NSET approach is demonstrated to be superior.
An Importin-β-like Protein from Nicotiana benthamiana Interacts with the RNA Silencing Suppressor P1b of the Cucumber Vein Yellowing Virus, Modulating Its Activity

During a plant viral infection, host–pathogen interactions are critical for successful replication and propagation of the virus through the plant. RNA silencing suppressors (RSSs) are key players of this interplay, and they often interact with different host proteins, developing multiple functions. In the Potyviridae family, viruses produce two main RSSs, HCPro and type B P1 proteins. We focused our efforts on the less known P1b of cucumber vein yellowing virus (CVYV), a type B P1 protein, to try to identify possible factors that could play a relevant role during viral infection. We used a chimeric expression system based on plum pox virus (PPV) encoding a tagged CVYV P1b in place of the canonical HCPro. We used that tag to purify P1b in Nicotiana-benthamiana-infected plants and identified by mass spectrometry an importin-β-like protein similar to importin 7 of Arabidopsis thaliana. We further confirmed the interaction by bimolecular fluorescence complementation assays and defined its nuclear localization in the cell. Further analyses showed a possible role of this N. benthamiana homolog of Importin 7 as a modulator of the RNA silencing suppression activity of P1b.
Brown Fat Dnmt3b Deficiency Ameliorates Obesity in Female Mice

Obesity results from a chronic energy imbalance due to energy intake exceeding energy expenditure. Activation of brown fat thermogenesis has been shown to combat obesity. Epigenetic regulation, including DNA methylation, has emerged as a key regulator of brown fat thermogenic function. Here we aimed to study the role of Dnmt3b, a DNA methyltransferase involved in de novo DNA methylation, in the regulation of brown fat thermogenesis and obesity. We found that the specific deletion of Dnmt3b in brown fat promotes the thermogenic and mitochondrial program in brown fat, enhances energy expenditure, and decreases adiposity in female mice fed a regular chow diet. With a lean phenotype, the female knockout mice also exhibit increased insulin sensitivity. In addition, Dnmt3b deficiency in brown fat also prevents diet-induced obesity and insulin resistance in female mice. Interestingly, our RNA-seq analysis revealed an upregulation of the PI3K-Akt pathway in the brown fat of female Dnmt3b knockout mice. However, male Dnmt3b knockout mice have no change in their body weight, suggesting the existence of sexual dimorphism in the brown fat Dnmt3b knockout model. Our data demonstrate that Dnmt3b plays an important role in the regulation of brown fat function, energy metabolism and obesity in female mice.
Skeletal Ryanodine Receptors Are Involved in Impaired Myogenic Differentiation in Duchenne Muscular Dystrophy Patients

Duchenne muscular dystrophy (DMD) is characterized by progressive muscle wasting following repeated muscle damage and inadequate regeneration. Impaired myogenesis and differentiation play a major role in DMD as well as intracellular calcium (Ca2+) mishandling. Ca2+ release from the sarcoplasmic reticulum is mostly mediated by the type 1 ryanodine receptor (RYR1) that is required for skeletal muscle differentiation in animals. The study objective was to determine whether altered RYR1-mediated Ca2+ release contributes to myogenic differentiation impairment in DMD patients. The comparison of primary cultured myoblasts from six boys with DMD and five healthy controls highlighted delayed myoblast differentiation in DMD. Silencing RYR1 expression using specific si-RNA in a healthy control induced a similar delayed differentiation. In DMD myotubes, resting intracellular Ca2+ concentration was increased, but RYR1-mediated Ca2+ release was not changed compared with control myotubes. Incubation with the RYR-calstabin interaction stabilizer S107 decreased resting Ca2+ concentration in DMD myotubes to control values and improved calstabin1 binding to the RYR1 complex. S107 also improved myogenic differentiation in DMD. Furthermore, intracellular Ca2+ concentration was correlated with endomysial fibrosis, which is the only myopathologic parameter associated with poor motor outcome in patients with DMD. This suggested a potential relationship between RYR1 dysfunction and motor impairment. Our study highlights RYR1-mediated Ca2+ leakage in human DMD myotubes and its key role in myogenic differentiation impairment. RYR1 stabilization may be an interesting adjunctive therapeutic strategy in DMD.
An IoT-Oriented Privacy-Preserving Fingerprint Authentication System

Identity authentication has become an essential component for access control in the Internet of Things (IoT) environment. To overcome the inherent weakness of password-based authentication, many present IoT devices (e.g., commercial banking smart cards) are equipped with the fingerprint authentication mechanism. However, due to the resource constraints of IoT devices, oversimplified authentication schemes are deployed, which compromise system performance significantly. Moreover, fingerprint templates in these existing schemes are unprotected. To address these issues, we propose an IoT-oriented privacy-preserving fingerprint authentication system. The proposed system is composed of four main components: 1) minutiae extraction; 2) the minutia cylinder-code (MCC)-based cancelable binary template, generated by the proposed normalized random projection; 3) the lightweight, privacy-preserving template, built by novel pairwise Boolean operations; and 4) fingerprint matching. Our system can effectively mitigate preimage and hill-climbing attacks. A prototype of the proposed system is developed using a popular open-source platform (i.e., Open Virtual Platforms). Comprehensive experimental results on eight benchmark data sets validate the effectiveness of the proposed IoT-oriented fingerprint authentication system. Our system also achieves equivalent authentication accuracy to that of the unprotected fingerprint authentication systems deployed in the resource-rich, non-IoT environment. More importantly, our system prototype is deployable to commercially available low-cost smart cards, such as Atmel AT24C256C Memory Smart Card 256K Bits. To the best of our knowledge, the proposed system is the first privacy-preserving, cancelable fingerprint authentication system developed in such a resource-constrained IoT setting.
Methods for dehulling of pulses: A critical appraisal

Pulses are dehulled into dhal (decorticated dry split cotyledons) for use as human food. Dehulling reduces cooking time, antinutritional factors, and improves protein quality, palatability, and digestibility of pulses. An efficient and improved method of dehulling pulses is of vital importance in reducing dehulling losses. Dhal yield, which is a function of dehulling efficiency, is highest in chickpeas and lowest in pigeonpeas in the case of both small scale (stone chakki) and large scale (dhal mill) operations. Mean dehulling loss is nearly 33% in stone chakki and 25% in dhal mills. Of the various pretreatments, heating of seed before dehulling appears to improve the dhal yield in pulses, particularly in pigeonpeas. Pulse varieties with uniform and round seeds are preferred for higher dhal yields. Genotypic differences exist in the dehulling characteristics of different pulses. Several aspects of dehulling are reviewed, such as methodology, pretreatments, physical, morphological and chemical characteristics of seed, with respect to dehulling characteristics, nutrient losses and varietal differences in dehulling quality.
Conducting Language Production Research Online: A Web-based Study of Semantic Context and Name Agreement Effects in Multi-Word Production

Few web-based experiments have explored spoken language production, perhaps due to concerns of data quality, especially for measuring onset latencies. The present study highlights how speech production research can be done outside of the laboratory by measuring utterance durations and speech fluency in a multiple-object naming task when examining two effects related to lexical selection: semantic context and name agreement. A web-based modified blocked-cyclic naming paradigm was created, in which participants named a total of sixteen simultaneously presented pictures on each trial. The pictures were either four tokens from the same semantic category (homogeneous context), or four tokens from different semantic categories (heterogeneous context). Name agreement of the pictures was varied orthogonally (high, low). In addition to onset latency, five dependent variables were measured to index naming performance: accuracy, utterance duration, total pause time, the number of chunks (word groups pronounced without intervening pauses), and first chunk length. Bayesian analyses showed effects of semantic context and name agreement for some of the dependent measures, but no interaction. We discuss the methodological implications of the current study and make best practice recommendations for spoken language production research in an online environment.