Miracle-dz/UniFAR-FTUs huggingface dataset:
Context-Aware Ranking Approaches for Search-based Query Rewriting

Query rewriting (QR) is an increasingly im-001 portant technique for reducing user friction 002 in large-scale conversational AI agents. Re-003 cently, the search based query rewriting sys-004 tem has been proven effective and achieved 005 promising results. It is a multi-stage system 006 that consists of two components orderly: re-007 trieval and ranking. Specifically, given a query, 008 a dual-encoder model retrieves top N rewrite 009 candidates. Then a Gradient Boosted Decision 010 Trees (GBDT) re-ranks the candidates by con-011 sidering semantic and information retrieval (IR) 012 features. However, although there is still a de-013 bate for the effectiveness of the neural ranking 014 model on traditional Learning-to-Rank (LTR) 015 problems, the neural LTR models for the QR 016 task have not been explored. To this end, we 017 first explore preliminary ranking models, in-018 cluding both tree-based (e.g., LambdaMART) 019 and neural-based (e.g., point-wise, list-wise) 020 ranking models. Furthermore, we propose a 021 context-aware ranking approach by integrating 022 the dialog context information into the rank-023 ing models. Experimental results demonstrate 024 that the proposed context-aware ranking model 025 outperforms the baselines significantly. 026
Fraud news identification: A Survey

Fraud news identification might be a basic yet testing issue. The quick ascent of person to person communication stages has not just yielded a colossal increment in data openness however has additionally quickened the spread of fake news. Given the enormous measure of site page, programmed Fraud news identification might be a reasonable NLP issue required by all online substance suppliers. This paper presents a study on Fraud news identification. Our review presents the difficulties of programmed Fraud news location. We deliberately audit the datasets and NLP arrangements that are produced for this errand. We likewise talk about the limits of those datasets and issue details, our bits of knowledge, and suggested arrangements.
PSYCHOLOGICAL FACTORS CONTRIBUTING TOWARDS PEAK PERFORMANCE AMONG ELITE INDIAN TRACK AND FIELD ATHLETES Athletic Coping skills among athletes of both the Genders

: The objective of the study was to identify and organize training, preparation and the development of an athlete from psychological point of view. The outcome of the study would aid in identifying an appropriate intervention strategy whenever required and maximize the athlete's motivation and adherence to the training program. The subjects for the study were 10 track & field athletes attending Indian camp. The test items selected for psychological parameters for assessing in this study were Athletic coping skills inventory “To measure individual differences in Psychological Skills within a sports context” (Smith, Schutz, Smoll and Ptacek, 1995) Task and Ego Orientation in Sport (TEOSQ): “TEOSQ is to assess individual differences in goal perspectives in sport settings. It also assesses whether the individual is prone to being task or ego orientated in the sporting context. This relates also to the extent that an individual defines success as mastery (task) or outperforming others (ego) and Competitive State Anxiety Inventory – 2. The CSAI-2 is an instrument used to measure state cognitive state anxiety, somatic state anxiety and state self-confidence in competitive situations. The outcomes of the study are discussed inline with the research outcomes of various contemporary researches. They also that perfectionism, dispositional hope, and high levels of are new variables to consider. Results are also relative to Bloom's Côtè's (1999) and Csikzentmihalyi, Rathunde, and Wong's (1993) talent development research. Practical implications focus on implementing parenting and coaching practices related to the development of psychological characteristics associated with athletic success.
FoSSA Optimization-Based SVM Classifier for the Recognition of Partial Discharge Patterns in HV Cables

In order to enhance the classification accuracy and the generalization performance of the SVM classifier in cable partial discharge (PD) pattern recognition, a firefly optimized sparrow search algorithm (FoSSA) is proposed to optimize its kernel function parameters and penalty factors. First, the Circle-Gauss hybrid mapping model is employed in the population initialization stage of the sparrow search algorithm (SSA) to eliminate the uneven population distribution of random mapping. Sparrows tend to fall into local extremums during the search process, while the firefly algorithm has a fast optimization speed and strong local search ability. Thus, a firefly disturbance is added in the sparrow search process, and the fitness value is recalculated to update the sparrow position to enhance the sparrow's local optimization ability and accuracy. Finally, based on the SSA, a dynamic step-size strategy is adopted to make the step size dynamically decrease with the number of iterations and improve the accuracy of convergence. Six benchmark functions are employed to evaluate the optimization performance of the FoSSA quantitatively. Experiment results show that the recognition accuracy of the PD patterns using the SVM optimized by the FoSSA could reach 97.5%.
Performance Evaluation of STF codes with Pre-DFT processing of MIMO-OFDM Systems

: The main aim of this paper is to propose an approach to reduce the system complexity of the conventional MIMO-OFDM system by reducing the number of DFT processing blocks corresponding to the receiver antennas at the receiver side. This is going to be achieved by processing the received data bits even before it is sent for processing by the space-time-frequency (STF) decoder. This results in the size reduction of the MIMO-OFDM system. Here we use a weighting coefficients calculation algorithm unlike others which are more relevant to STF coding used, this algorithm can be used for most of the STF schemes in the real time applications which is the main advantage for MIMO systems. In the proposed technique, there is no restriction on the number of the DFT processing blocks which can be used at the receiver side. They can range from one to total receiver antennas. This leads to the complexity reduction and cost minimization.
Compositional Generalization and Neuro-Symbolic Architectures

Compositional generalization is the ability to understand novel combinations of known concepts. Although it is considered as an innate skill for humans, recent studies have shown that neural networks lack this characteristic. In this paper, we focus on compositional generalization with respect to the two speciﬁc tasks of word problem solving and visual relation recognition and propose a neuro-symbolic solution, using DeepProbLog, that addresses the problem of compositionality in state-of-the-art neural systems for these tasks.
The COVID-19 pandemic disclosure: A case of the banking sector in an African developing economy

This research aims to explore the extent of COVID-19 reporting by the banking sector in a developing economy after the 2020 experience in the absence of known pandemic standards. The subject of this research is the 2021 top six banks from South Africa, a country classified as a developing economy. An unobtrusive research method was employed. Data were collected from the banks’ integrated reports for 2020/2021 depending on the banks’ financial year period. Document analysis was done and a technique of counting and recording the number of mentions for each COVID-19 content or capital category was employed. Findings indicated that Standard Bank, which was ranked top of the six, took the lead in the extent of COVID-19 reporting based on a recently suggested reporting framework that has not yet been contrasted by the rest of the researchers. A correlation analysis showed a significant positive relationship between the bank size and the extent of COVID-19 disclosure by the sampled banks. The study indicated that the top South African banks significantly reported on the COVID-19 pandemic despite the absence of guiding reporting standards. However, there is a need for another study to develop an index that will show different levels of disclosure extent. © 2022 by the authors. Licensee SSBFNET, Istanbul, Turkey. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Less is More: Learning to Refine Dialogue History for Personalized Dialogue Generation

Personalized dialogue systems explore the problem of generating responses that are consistent with the user’s personality, which has raised much attention in recent years. Existing personalized dialogue systems have tried to extract user profiles from dialogue history to guide personalized response generation. Since the dialogue history is usually long and noisy, most existing methods truncate the dialogue history to model the user’s personality. Such methods can generate some personalized responses, but a large part of dialogue history is wasted, leading to sub-optimal performance of personalized response generation. In this work, we propose to refine the user dialogue history on a large scale, based on which we can handle more dialogue history and obtain more abundant and accurate persona information. Specifically, we design an MSP model which consists of three personal information refiners and a personalized response generator. With these multi-level refiners, we can sparsely extract the most valuable information (tokens) from the dialogue history and leverage other similar users’ data to enhance personalization. Experimental results on two real-world datasets demonstrate the superiority of our model in generating more informative and personalized responses.
A Tale of Two Taphonomies: Assessing the Contribution of Taphonomic Analysis to our Understanding of Neolithic Sudanese Burial Sites using both the Standard Anglophone and Francophone Definitions

The Kadruka concession represents an area of study grouping together a large number of funerary (as well as habitat) sites located in Upper Nubia in modern day Sudan. Five of these sites (KDK1, KDK2, KDK18, KDK21 and KDK23) served as the basis for a doctoral thesis that provided a new perspective on the identity and practices of these populations. These results are part of a larger and ongoing project, which aims to expand our understanding of the Kadruka area, how the different sites relate to one another and to the surrounding region more broadly. Initially excavated and studied by J. Reinold and C. Simon from the 1980s to the early 2000s, the vast documentation made available by this work served as an important means to perform a taphonomic analysis on this collection of burials a posteriori. Traditionally, the term taphonomy possesses two different meanings within its use in archaeology. On the one hand there is the widely used English language definition and on the other there is its meaning and scope in French. Both uses contribute significantly to an improved understanding of the diversity of methods of disposal of the dead, of deposition practices for gravegoods and of the way in which a cemetery may have functioned within a specific environment.
Analysis of a Direct Current Compressor for Solar Cooler

Abstract: Refrigeration systems have higher electricity consumption ratio in overall energy consumption especially in household utilization. On the other hand, these systems have an advantage of being powered by renewable energy sources such as solar or solar-wind hybrid systems because of their lower power demand. Since the efficiency improvement of refrigeration systems is crucial for domestic and industrial systems in the present study, solar energy powered compressor for vapour compression refrigeration systems have been investigated. Compressor is the most important part and often the costliest component of any refrigerant system. There are two different options for powering the compressor such as alternative current (AC) and direct current (DC).
Proximal JunctionKyphosis inAdultScoliosis:BestPostoperative Radiological Predictors—A Retrospective Cohort Study

Background. Proximal junction kyphosis (PJK) is the postsurgical radiographic event seen in the surgical plane after the fusion of a spinal deformity. Unfavorable health outcomes have been reported in symptomatic PJK patients compared to non-PJK patients. Methods. -e data for adult scoliosis patients who underwent curve correction were extracted from the hospital database. Pelvic and spinal parameters were measured and calculated to compare four predictive formulae for occurrences of PJK. Formula 1. Restoration of hypothetical values of lumbar lordosis (LL) and thoracic kyphosis (TK) according to pelvic incidence (PI). Formula 2. Evaluation of global sagittal alignment. Formula 3. Restoration of the apex of LL to its hypothetical position according to the spine shape. Formula 4. Evaluation of positive-sum and negative-sum of (LL +TK). Results. A total number of cases were 52. -ere were 14 cases of PJK. -e incidence of PJK was 26.9%, and the mean age for PJK cases was 63.2± 5.2. -e excellent predictor for occurrences of PJK was formula 3. Postsurgical sagittal apexes of lumbar lordosis were located in their hypothetical position in 24 cases, and 12.5% of these cases developed PJK. While sagittal apexes were not located in their hypothetical position in 28 patients, PJK occurred in 39.3% of them (P � 0.03, OR: 4.53, (95% CI: 1.09–18.9)). -e second good predictor for occurrences of PJK was formula 2 (GSA >45° versus GSA <45° OR� 2.5, (95% CI: 0.67–9.38), P � 0.17). -e other two formulae (1 and 4) were not good predictors for occurrences of PJK. Conclusion. Among the four proposed formulae for predicting occurrences of PJK, the position of the sagittal apex of lumbar lordosis is an excellent predictor of the development of PJK, followed by GSA. Hypothetical values of LL and TK, and positive or negative-sum of (LL +TK), are weak predictors for occurrences of PJK.
Genetic variation of coxsackie virus B5 strains associated with aseptic meningitis in Greece

In order to explore the genetic relationships among coxsackie virus B5 strains in Greece, the nucleotide sequences of the partial VP1 gene in strains isolated from aseptic cases of meningitis were determined and compared with those of strains isolated from other countries. Phylogenetic analysis showed a high degree of divergence (25%) among Greek strains isolated in different years, which clustered with high bootstrap values in a different subgroup of viruses, suggesting that enterovirus types vary with time rather than geographical distribution. A non-synonymous mutation present in the strains of this study was not observed in other coxsackie virus B5 strains. Corresponding author and reprint requests: A. Papa, A¢ Department of Microbiology, School of Medicine, Aristotle University of Thessaloniki, 54006 Thessaloniki, Greece E-mail: annap@med.auth. gr 688 Clinical Microbiology and Infection, Volume 12 Number 7, July 2006 2006 Copyright by the European Society of Clinical Microbiology and Infectious Diseases, CMI, 12, 672–694
ProKnow : Dataset and Method for Process-guided, Safety-Contrained, and Explainable Mental Health Diagnostic Assistance Anonymous ACL submission

Current Virtual Mental Health Assistants (VMHAs) provide counseling and suggestive care. They refrain from patient diagnostic assistance because of a lack of training on safety-constrained and specialized clinical process knowledge ( ProKnow ). In this work, we introduce a new dataset of diagnostic conversations guided by safety constraints and ProKnow that healthcare professionals use ( ProKnow - data ). We develop a method for natural language generation (NLG) that collects diagnostic information from the patient interactively ( ProKnow - algo ). We demonstrate the limitations of using state-of-the-art large-scale language models on this dataset. ProKnow - algo models the process knowledge through explictly modeling safety, knowledge capture, and explainability and achieves an 82% improvement. Through both our dataset and our language generation pipeline, we introduce a novel knowledge intensive learning task that shows how such data and pipelines can be integrated. For reproducibility we will make ProKnow - data and code repository of ProKnow - algo publicly available upon acceptance.
Exploring Potential of Sketchnoting as a Tool for Constructing Learner ́s Knowledge in Geography

In the paper, we explore the potential of sketchnoting as a tool for constructing learner ́s knowledge. Sketchnoting is nonlinear note-taking method that combines text and visual elements to express knowledge in a complex form, and is represented by text, symbols, arrows, frames, and other visual elements. Drawing on theory of dual coding and theory of multimedia learning, it is argued that a learner retains information more permanently if they process it verbally and visually at the same time. Sketchnoting can be effectively implemented in a learning process. We illustrate sketchnoting as a supportive learning tool by empirical study with learners at geography lessons in a secondary grammar school. We assessed twenty students ́ first sketchnotes and found out most of them focused on facts rather than relations. It is therefore suggested that teachers draw more attention to organisation, structure and interrelations of the elements of knowledge in sketchnote when introducing it first to learners.
TRUE: Re-evaluating Factual Consistency Evaluation

Grounded text generation systems often generate text that contains factual inconsistencies, hindering their real-world applicability. Automatic factual consistency evaluation may help alleviate this limitation by accelerating evaluation cycles, filtering inconsistent outputs and augmenting training data. While attracting increasing attention, such evaluation metrics are usually developed and evaluated in silo for a single task or dataset, slowing their adoption. Moreover, previous meta-evaluation protocols focused on system-level correlations with human annotations, which leave the example-level accuracy of such metrics unclear.In this work, we introduce TRUE: a comprehensive survey and assessment of factual consistency metrics on a standardized collection of existing texts from diverse tasks, manually annotated for factual consistency. Our standardization enables an example-level meta-evaluation protocol that is more actionable and interpretable than previously reported correlations, yielding clearer quality measures. Across diverse state-of-the-art metrics and 11 datasets we find that large-scale NLI and question generation-and-answering-based approaches achieve strong and complementary results. We recommend those methods as a starting point for model and metric developers, and hope TRUE will foster progress towards even better evaluation methods.
Advanced nonlinear equalizer for Filter Bank Multicarrier‐based Long Reach‐Passive Optical Network system

The performance of the intensity‐modulated Filter Bank Multicarrier (FBMC) system using direct detection with advanced nonlinear equalizer in Long Reach‐Passive Optical Network (LR‐PON) is presented in this paper. First, the performance of the FBMC system and its nonlinearity in the channel are analyzed. We introduce two nonlinear equalizers, namely, Artificial Neural Networks–Nonlinear Feed‐Forward Equalizer (ANN‐NFFE) and Deep Neural Network–Nonlinear Equalizer (DNN‐NLE). Both the equalizers can mitigate the nonlinearities in the signal. Also, the impact of the system in downlink is analyzed using simulation by varying the data rates for various fiber lengths. The FBMC using SMT provides better spectral efficiency. The performance of both equalizers is compared. The addition of the DNN‐NLE equalizer provides a better OSNR, good accuracy, and better BER compared with ANN‐NFFE.
An Efficient 5‐Input Exclusive‐OR Circuit Based on Carbon Nanotube FETs

The integration of digital circuits has a tight relation with the scaling down of silicon technology. The continuous scaling down of the feature size of CMOS devices enters the nanoscale, which results in such destructive effects as short channel effects. Consequently, efforts to replace silicon technology with efficient substitutes have been made. The carbon nanotube field‐effect transistor (CNTFET) is one of the most promising replacements for this purpose because of its essential characteristics. Various digital CNTFET‐based circuits, such as standard logic cells, have been designed and the results demonstrate improvements in the delay and energy consumption of these circuits. In this paper, a new CNTFET‐based 5‐input XOR gate based on a novel design method is proposed and simulated using the HSPICE tool based on the compact SPICE model for the CNTFET at the 32‐nm technology node. The proposed method leads to improvements in performance and device count compared to the conventional CMOS‐style design.
Psychological biases abilities on constructing weekend anomaly 1

Even though many researchers have proposed trading behavior as the explanation of the Monday Irrationality or Day-of-the Week anomaly, yet, it has still left without empirical evidence. This research aims to investigate empirically by gauging psychological approach whereas the affection bias (weather-induced mood, and moon-induced mood), and cognition bias (attention bias, and cognitive dissonance) are the factors. Our results report that investor’s Monday irrationality is caused by those psychological biases. Employing one traditional dummy interaction model and an innovation model with market index returns and size-based portfolio returns as our constructs, we found the psychological biases are the explanations beyond the DOWA over the period of 1 January 1999 until 22 March 2010. This research found size does matter in this case as the intuitive judgment of investor plays role on investment decision. Our findings support the conclusion that psychology of investor does play important role on investment decision and resulting DOWA.
Dual‐band balanced‐to‐unbalanced out‐of‐phase equal power divider

This article proposes a Gysel type dual‐band balanced‐to‐unbalanced (BTU) power divider (PD) for equal power division. The proposed PD has out‐of‐phase (phase difference between two output signal is 180°) characteristic. Standard [S] matrix for the dual‐band PD is derived from mixed mode [S] matrix. Analysis is carried out to obtain design equations of the PD. The proposed PD is designed for a frequency ratio of 1.91. The two design frequencies are 2.2 and 4.2 GHz. A prototype is fabricated to validate theory and design equations. Measurement results show the dual‐band nature and out‐of‐phase characteristic of PD. Size of the fabricated prototype is 0. 52λg × 0. 29λg. The proposed PD configuration can also be used for high power application.
Quasi‐carousel tournaments

A tournament is called locally transitive if the outneighborhood and the inneighborhood of every vertex are transitive. Equivalently, a tournament is locally transitive if it avoids the tournaments W4 and L4, which are the only tournaments up to isomorphism on four vertices containing a unique 3‐cycle. On the other hand, a sequence of tournaments (Tn)n∈N with V(Tn)=n is called almost balanced if all but o(n) vertices of Tn have outdegree (1/2+o(1))n . In the same spirit of quasi‐random properties, we present several characterizations of tournament sequences that are both almost balanced and asymptotically locally transitive in the sense that the density of W4 and L4 in Tn goes to zero as n goes to infinity.