Miracle-dz/UniFAR-FTUs huggingface dataset:
Challenges of English Language Learners towards Remote Independent Study: Developing a Theory

English language is considered as the universal language in the world, yet one of the most difficult subjects to learn for many reasons. There are numerous factors that learners are fumbling with in spelling, grammar, and phonological structures. However, the benefits of understanding the language far outweigh the inconveniences of learning it. One of the most affected groups of students since the pandemic is English Language Learners. These learners encounter numerous challenges throughout the autonomous learning process and exhibit a negative attitude towards learning. The purpose of this study is to identify the difficulties faced by English language learners at Jefferson Union High School District in Daly City, California. Specifically, this research studies (i) the challenges of English Language learners towards remote independent study, (ii) the significant themes that can be drawn from their challenges, and (iii) the theory that may be developed based on the significant themes. To further comprehend this phenomenon, this study takes a qualitative approach that employs interviews as a data collection instrument and uses Interpretative Phenomenological Analysis in the analysis of qualitative data. Participants in this study are English language learners who struggle with learning remotely during the pandemic. The sample of this study consisted of 6 students from 4 different grade levels in high school: Grades 9, 10, 11, and 12. The results show that there are a variety of challenges that students face, which can be categorized into time management, sustained attention, and motivation. The participants employed a variety of techniques to address the issues, including family and friends support, and technology throughout the pandemic and this resulted in remote independent study for autonomous and self-directed learning.
A Deterministic Heuristic Algorithm Based on Euclidian Distance for Solving the Rectangles Packing Problem

Solving NP hard problem is the bottleneck task for computer science and technology nowadays. In recent years, investigations show that for NP hard problems, there may not exist an algorithm that is both complete and rigorous and not too slow. So its solution methods are usually heuristic. The rectangles Packing problem is NP hard. Given a set of rectangles with fixed width and height and a larger rectangle, the rectangles Packing problem is to find a good layout by Packing these rectangles without overlapping entirely inside a larger rectangle. In this paper, based on the quasi-human strategy, the authors propose the so-called corner-occupying and largest hole degree first placement policy based on Euclidian distance. An effective heuristic algorithm is presented, and the solution to the rectangles Packing problem can be obtained quickly by applying this algorithm. Experimental results on MCNC and GSRC benchmark circuits demonstrate that the algorithm is quite effective in solving the problem.
Wireless Network Security

Wireless networking is becoming increasingly prevalent in modern networked environments. This paper examined methods used to secure wireless networks from intrusion and eavesdropping. WEP, WPA and RSN were examined to see the progression from weak to much stronger security for wireless LANs. WEP was incredibly insecure, but these vulnerabilities were addressed to produce significantly more secure networks.
Fast Incremental Updating of Frequent Itemsets

Mining frequent itemsets is a major problem in the data mining field with numerous practical appilcations. Efficient incremental updating of discovered frequent itemsets is the key problem. The existing incremental updating algorithms employ the same framework as Apriori, which need to generate a lots of candidate sets and repeatedly scan the database, especially when there exist many patterns and/or long patterns. In this paper, we propose an incremental updating algorithm of frequent itemsets (FIUA) mainly for the updating of frequent itemsets as a time when the minimum support threshold adjusts dynamically. In worst case, FIUA only scans transaction database once and need not generate candidate sets, which saves effectively storage space. Therefore, FIUA is efficient and effective. 
Maximum likelihood inference of molecular phylogeny

The evolutionary history of organisms is inscribed in the DN A of living organisms. Since the nucleotide substitution of DNA in evolut卲n is best regarded as stochastic, statistical methods based on probabilistic models are required for inferring the history 叝om the DN A sequences. Among these, a maximum likelihood method is on a 五rm theoretical basis o � probability theory. It requ叝es an explicit probabil﨎tic model of nucleotide subst咜ution to calculate the likel劜ood funct卲n and helps to make the assumptions clear. In molecuar phylogenetics, we want to solve two problems; (1) inference o �branch匤g order, and (2) est匇ation of branching dates, and the two problems are interrelated. The estimation of branching dates has been based on an approximate constancy of the molecular evolutionary rate, that is called a molecular clock. However, it has recently been suggested that the rate sometimes differs among taxonomic units. A relative rate test is applicable to examine whether the rate differs among linea伊s (Hasegawa et aJ., 1987). The test, however, depends on the branching order. To avoide the circularity we should infer the branching order at 五rst w咜hout assuming constancy of the rate. A maximum likelihood method developed by Felsenstein (1982) is suitable for this purpose (Hasegawa and Yano, 1984) and the method has been applied to a wide range of phylogenetic problems (Hasegawa et al. , 1985a; Hasegawa and Kishino, 1989; Kishino and Hasegawa, 1989). Kishino et al . (1990) have developed a simple method for estimating a bootstrap probability of being the ma.ximum likelihood tree among alternatives without performing maximum likelihood estimation for each resampled data. After establish匤g the branching order, we shall est匇ate the branch匤g dates by a method developed by Kish匤o and Hasegawa (1990) which is desc副)ed briefly below. This is an extension of our earlier method based on the 出sumption o �the rate constancy (Has坦gawa et al. , 1984, 1985b). The rate variation does not itselfinvalidate the molecular clock ana.lysis, provided the variation can be incorporated into the modeJ. The method has been applied to phylogenetic problems on man's place in the evolution of primates (長 谷川 , 1989a, 1989b; Hasegawa 1990; Hasegawa a.nd Kishino 1990; Hasegawa et al., 1989, 1990a) and on the root for polymorphisms of mitochondrial DNA in the present human population (Hasegawa and Horai, 1990). Furthermore, we have developed a ma口xim 訂mum likelihood method for in冾rring prot伐凶 ein phylogeny from a.mi 討ino acid s 田eq 中1悶nces (Kisl 油hinoetal. 1990吋). The method has be町閃 f引n ap河耶 p 凶〉汁lie 佼吋d l tωo pμ 〉汁hylogcnetic problems on the origil1 of chloroplasLs (Kishino et al. 1990) and 011 thc relatiol1s1句 among eul叩yotes , archa.ebacteria and e山
Efficient Platform for Flexible Engineering of Superradiant, Fano-Type, and Subradiant Resonances

Delicate control of the surface plasmon resonance (SPR) line shapes is crucial for the development of nanoplasmonics with dedicated applications. In this paper, we develop a method to fabricate large-scale periodic structures with significantly different plasmonic properties by the holographic lithography method. We show that SPR line shapes can be controllably engineered from a broad superradiant line shape to an asymmetrical Fano-type resonance, as well as an ultranarrow subradiant mode, which are clearly correlated with the structural parameter (morphology) of the fabricated structures. The wavelength of the SPR band can be tuned from the visible to near-infrared region by changing the incident angle. The nanostructures fabricated by the present method show a clear correlation between the morphology of plasmonic structures and SPR line shapes, which can serve as an efficient platform for engineering SPR line shapes for specific applications. Most importantly, the capability to produce structures of lar.
LAMBDA CYHALOTHRIN INDUCED OXIDATIVE STRESS ON BRAIN TISSUES OF RATTUS NORVEGICUS AND ITS AMELIORATION BY GREEN TEA EXTRACT

Lambda cyhalothrin is one of the most important agricultural pesticides extensively used around the world. Pyrethroids are specially recommended insecticides as they have low mammalian toxicity, but they are known to cause an alteration in biochemical parameters and affect the oxidative status of the body through producing free radicals. However, it has been found that some herbal extracts can ameliorate the toxicity induced by the pesticides and other chemicals but the search for such compounds will always be an urgent need to achieve the optimum degree of amelioration. For this purpose, the present study was designed to evaluate the oxidative stress produced by lambda cyhalothrin, a synthetic type-II pyrethroid and ameliorating effect of green tea extract in albino rats.
Entertainment journalism as a resource for public connection: A qualitative study of digital news audiences

Entertainment journalism has long been a marginal object of academic inquiry due to its reputation as a trivial distraction from public affairs journalism, yet this view has since been challenged by scholars who emphasize its substantive role in political discourse. Although previous research has disputed the idea that entertainment news helps audiences forge connections with public issues, the present study renews this line of inquiry at a time when this journalism has increasingly become a driver of political reporting and opinion, particularly in tandem with activism efforts addressing the media representation of marginalized identity groups as well as celebrity-fueled public advocacy. In-depth interviews are used to illuminate the interpretive processes of US audience members who engage online with this news, outlining how it is used as a resource for navigating the politics of media representation, for making political meanings from celebrity culture, and for fulminating right-wing backlash to cultural institutions.
Smart Agriculture: A Review of IoT Technologies for Sustainable Farming

— The climate, topography, soil and biology are highly dependent on agriculture. In which land plays a significant role. Despite considerable progress in the service sector, agriculture remains India's primary source of employment and income, and price fluctuations in agricultural commodities have a significant impact on people's daily lives as well as agricultural inputs and outputs. In order to overcome all this, soil test values are used in the current study to classify several important soil characteristics, such as the Available Phosphorus (P), Potassium (K), Organic Carbon (OC) and Boron (B) village-wise soil fertility indices, as well as the Soil Reaction parameter (pH). We have addressed various algorithms related to data mining and machine learning (ML) classification techniques in this paper along with IOT hardware that used in agriculture. These algorithms are developed on a data set for yield prediction of crops that have been collected over the years. In addition, a comparative study is carried out to show which classification algorithm is better suited for classification techniques success prediction.
Peanut yield prediction with UAV multispectral imagery using a cooperative machine learning approach

The unmanned aerial vehicle (UAV), as a remote sensing platform, has attracted many researchers in precision agriculture because of its operational flexibility and capability of producing high spatial and temporal resolution images of agricultural fields. This study proposed machine learning (ML) models and their ensembles for peanut yield prediction using UAV multispectral data. We utilized five bands (red, green, blue, near-infra-red (NIR) and red-edge) multispectral images acquired at various growth stages of peanuts using UAV. The correlation between spectral bands and yield was analyzed for each growth stage, which showed that the maturity stages had a significant correlation between peanut yield and spectral bands: red, green, NIR and red edge (REDE). Using these four bands spectral data, we assessed the potential for peanut yield prediction using multiple linear regression and seven non-linear ML models whose hyperparameters were optimized using simulated annealing (SA). The best three ML models, random forest (RF), support vector machine (SVM) and XGBoost, were then selected to construct a cooperative yield prediction framework with both the best ML model and the ensemble scheme from the best three as comparable recommendations to the farmers.
Knapsack constraint reformulation: A new approach that significantly reduces the number of sub-problems in the branch and bound algorithm

The paper presents a new approach to significantly reduce the number of sub-problems required to verify optimality in the branch and bound algorithm. The branch and bound algorithm is used to solve linear integer models and these models have application in areas such as scheduling, resource allocation, transportation, facility allocation and capital budgeting. The single constraint of the knapsack linear integer problem (KLIP) is reformulated in such a way that the number of standard branch and bound sub-problems required to verify optimality is significantly reduced. Computational results of the proposed approach on randomly generated KLIPs are also presented.
Genetic diversity of mitochondrial DNA D-loop in wild and domestic pigs (Sus scrofa) in East Asia

Chinese domestic pig breeds have abundant genetic resources, but definite information about the geographic specificity and genetic structure is lacking. In this study, we analysed 359 mitochondrial D-loop sequences, including 86 sequences from Chinese domestic pigs and the rest downloaded from GenBank. The haplotype and nucleotide diversity indices ranged from 0.467 ±0.132 (Duroc) to 1.000 ±0.500 (Thailand, North Korea and Cambodia) and 0.00067 ±0.00019 (Duroc) to 0.02000 ±0.01000 (Thailand), respectively. The neighbour-joining tree revealed two clads in the individual pigs, with a Chinese domestic breed distributed discontinuously among several breeds. The network data indicated that the gene pools of Chinese domestic pigs are likely related to Chinese, Japanese and some other Southeast Asian wild boars.
Online generation of time- optimal trajectories for industrial robots in dynamic environments

In the field of industrial robots, there is a growing need for having cooperative robots that interact with each other and share work spaces. Currently, industrial robotic systems still rely on hard coded motions with limited ability to react autonomously to dynamic changes in the environment. This thesis focuses on providing a novel framework to deal with real-time collision avoidance for robots performing tasks in a dynamic environment. We develop a reactive trajectory generation algorithm that reacts in real time, removes the fastidious optimization process which is traditionally executed by hand by handling it automatically, and provides a practical way of generating locally time optimal solutions.The novelty in this thesis is in the way we integrate the proposed time optimality problem in a task priority framework to solve a nonlinear optimization problem efficiently in real time using an embedded system with limited resources. Our approach is applied in a Model Predictive Control (MPC) setting, which not only improves reactivity of the system but presents a possibility to obtain accurate local linear approximations of the collision avoidance constraint. The control strategies presented in this thesis have been validated through various simulations and real-world robot experiments. The results demonstrate the effectiveness of the new control structure and its reactivity and robustness when working in dynamic environments.
Integral stellar-nebular model of NGC 7009

Abstract We developed a self-consistent stellar-nebular model for NGC 7009. This model reproduces the available observations ranging from optical to UV. The combined approach to the modeling process produces more constraints and thus more trustworty results. After obtaining the model, we perform a comparative study of the chemical composition of He, N, O, Ne, Cl, and S in the nebula and its central star. Concluding that the stellar composition agrees with the nebular composition with t 2 ≠ 0.00.
Multi-Group Generalizations of SIBTEST and Crossing-SIBTEST

ABSTRACT This article presents generalizations of SIBTEST and crossing-SIBTEST statistics for differential item functioning (DIF) investigations involving more than two groups. After reviewing the original two-group setup for these statistics, a set of multigroup generalizations that support contrast matrices for joint tests of DIF are presented. To investigate the Type I error and power behavior of these generalizations, a Monte Carlo simulation study was then explored. Results indicated that the proposed generalizations are reasonably effective at recovering their respective population parameter definitions, maintain optimal Type I error control, have suitable power to detect uniform and non-uniform DIF, and in shorter tests are competitive with the generalized logistic regression and generalized Mantel–Haenszel tests for DIF.
The effectiveness of image augmentation in pneumonia diagnosis using convolutional neural network

In human history, pneumonia has resulted several disasters, including the COVID-19. How to diagnosis a pneumonia timely and efficiently becomes a problem. A Computer-Aided Diagnosis (CAD) system with classification algorithms based on convolutional neural network are considered to be the most potential methods. But lack of data to train the network is a great challenge in its popularity. To help relieve the phenomenon, this paper is to explore some traditional methods in data augmentation to let a Convolutional Neural Network (CNN) trained well with less data. In this paper, two different models are applied, and both will employ five datasets with different way of data augmentation. The five datasets include the original one, the one with oversampling, the one with geometric augmentation, the one with color space transformation and the one with both geometric augmentation and color spacer transformation (it will be called the mixed method in the paper). The results show that oversampling has a limited improvement in accuracy, geometric augmentation has a great effect in the accuracy, color space transformation has a bad result, the mixed method performs as awful as color space transformation does and the second model with batch normalization perform well in all five datasets. Finally, an 80.34% accuracy is achieved. It can be concluded that, oversampling can balance the dataset and provide a limited increase, geometric augmentation is a good strategy while color space transformation is not and model with batch normalization can exclude the influence of extreme data and perform well and stable.
Affine Invariance of Central Projection Transformation

A method is proposed by combining contour-based methods with region-based methods.A closed contour is derived from the object by central projection transformation,and invariant features are extracted from this closed contour.The affine invariance of the closed curve derived by central projection transformation has been proved.An algorithm is provided to extract affine invariant features by employing stationary wavelet transform.Some Chinese characters and 26 capital letters are used to evaluate the proposed method.Experimental results show that the proposed method can efficiently extract invariant features.Compared to traditional methods,the proposed method is robust to noise.
Substantiation of the Priestley and Taylor Parameter α = 1.26 for Potential Evaporation in High Latitudes

Abstract Summertime latent heat flux values determined by the energy budget approach are compared to equilibrium model estimates for two shallow lakes and two sedge meadow surfaces in northern Canada. Comparison of energy budget values with equilibrium estimates for each surface show that the latent heat flux can be accurately determined by the Priestley and Taylor (1972) model, where α the ratio of actual to equilibrium evaporation equals 1.26. Results suggest that the Priestley and Taylor parameter is generally applicable to saturated surfaces in high latitudes.
Mosunetuzumab monotherapy is active and tolerable in patients with relapsed/refractory diffuse large B-cell lymphoma

Key Points • Mosunetuzumab is active as a single agent and yields CRs in 24% of heavily pretreated patients with R/R DLBCL. • Step-up dosing mitigated CRS events with mosunetuzumab, which has a manageable tolerability profile in R/R DLBCL.
Impact of using the International Risk Scoring Tool on the cost-utility of palivizumab for preventing severe respiratory syncytial virus infection in Canadian moderate-to-late preterm infants

Abstract Background and objective To assess the cost-utility of palivizumab versus no prophylaxis in preventing severe respiratory syncytial virus (RSV) infection in Canadian moderate-to-late preterm (32–35 weeks’ gestational age) infants using an (i) International Risk Scoring Tool (IRST) and (ii) Canadian RST (CRST). Methods A decision tree was developed to assess cost-utility. Infants assessed at moderate- and high-risk of RSV-related hospitalization (RSVH) by the IRST or CRST received palivizumab or no prophylaxis and then progressed to either (i) RSVH; (ii) emergency room/outpatient medically attended RSV-infection (MARI) or (iii) were uninfected/non-medically attended. Infants admitted to intensive care could incur mortality (0.43%). Respiratory morbidity was accounted in all uninfected surviving infants for 6 years or 18 years (RSVH/MARI). Palivizumab efficacy (72.2% RSVH reduction) and hospital outcomes were from the Canadian CARESS, PICNIC and RSV-Quebec studies. Palivizumab costs (50 mg: CAN$752; 100 mg: $1,505) were calculated from Canadian birth statistics combined with a growth algorithm. Healthcare/payer and societal costs (May 2022; 1.5% discounting) were included. Results Cost per quality-adjusted life year (QALY) was $29,789 with the IRST (0.79 probability of being <$50,000) and $15,833 with the CRST (0.96 probability). The model was most sensitive to utility scores, long-term sequelae and palivizumab cost. Vial sharing improved the incremental cost-utility ratio (IRST: $22,319; CRST: $9,231). Conclusions Palivizumab was highly cost-effective (vs no prophylaxis) in Canadian moderate-to-late preterm infants using either the IRST or CRST. The IRST has fewer risk factors than the CRST (3 vs 7, respectively), captures more potential RSVHs (85% vs 54%) and provides another option to guide cost-effective RSV prophylaxis in Canada. Graphical Abstract
Complete Genome Sequence of a Canadian Strain of Escherichia coli with Multiple Metal and Antimicrobial Resistance Genes That Was Isolated from Municipal Biosolids

This announcement reports the complete genome sequence of a non-Shiga toxin-producing Escherichia coli strain that was isolated from municipal biosolids collected from a Canadian wastewater treatment plant. This strain contains multiple metal, antimicrobial, and heat resistance genes, as determined by genome sequencing, and could be a useful bacterial model for future studies. ABSTRACT This announcement reports the complete genome sequence of a non-Shiga toxin-producing Escherichia coli strain that was isolated from municipal biosolids collected from a Canadian wastewater treatment plant. This strain contains multiple metal, antimicrobial, and heat resistance genes, as determined by genome sequencing, and could be a useful bacterial model for future studies.