Miracle-dz/UniFAR-FTUs huggingface dataset:
Magnetic field-induced intermediate quantum spin liquid with a spinon Fermi surface

Significance In a quantum spin liquid, the spins remain disordered down to zero temperature, and yet, it displays topological order that is stable against local perturbations. The Kitaev model with anisotropic interactions on the bonds of a honeycomb lattice is a paradigmatic model for a quantum spin liquid. We explore the effects of a magnetic field and discover an intermediate gapless spin liquid sandwiched between the known gapped Kitaev spin liquid and a polarized phase. We show that the gapless spin liquid harbors fractionalized neutral fermionic excitations, dubbed spinons, that remarkably form a Fermi surface in a charge insulator. The Kitaev model with an applied magnetic field in the H∥[111] direction shows two transitions: from a nonabelian gapped quantum spin liquid (QSL) to a gapless QSL at Hc1≃0.2K and a second transition at a higher field Hc2≃0.35K to a gapped partially polarized phase, where K is the strength of the Kitaev exchange interaction. We identify the intermediate phase to be a gapless U(1) QSL and determine the spin structure function S(k) and the Fermi surface ϵFS(k) of the gapless spinons using the density matrix renormalization group (DMRG) method for large honeycomb clusters. Further calculations of static spin-spin correlations, magnetization, spin susceptibility, and finite temperature-specific heat and entropy corroborate the gapped and gapless nature of the different field-dependent phases. In the intermediate phase, the spin-spin correlations decay as a power law with distance, indicative of a gapless phase.
From Low Initial Interest to Electric Vehicle Adoption: “EV Converts” in New York State’s Rebate Program

To meet aggressive transportation-electrification goals, electric-vehicle (EV) sales must expand beyond enthusiastic early adopters and deeper into mainstream markets. To support that expansion, this research examined a strategic market segment that points the way: EV adopters who had little to no interest in adopting an EV when they started looking for a new car—or “EV Converts. ” It utilized survey responses from 5,216 recipients of New York State’s Drive Clean Rebate, separately examining consumers of plug-in hybrid EVs, Teslas, and non-Tesla battery EVs. Weighted descriptive statistics and logistic regressions were used to identify factors that predict EV Convert status, and dominance analysis was used to rank factors for prioritization. The results were combined into summary profiles for each vehicle category, summarizing their current characteristics and describing top opportunities for reinforcing each segment. Across categories, high-ranking factors associated with increased odds of being an EV Convert included giving relatively less importance to societal factors like energy independence or environmental impacts, lack of consumer awareness of the rebate before the first dealership visit, the essentiality of the rebate to the EV purchase/lease, having no plans to install solar, giving no importance to the desire for the newest technology, and/or identifying as female. Significant factors were ranked and compared across vehicle categories. Recommendations for program design, outreach, and dealer education are provided.
The large area radio galaxy evolution spectroscopic survey (LARGESS)

© 2016 The Authors. We present the Large Area Radio Galaxy Evolution Spectroscopic Survey (LARGESS), a spectroscopic catalogue of radio sources designed to include the full range of radio AGN populations out to redshift z ~ 0.8. The catalogue covers ~800 deg 2 of sky, and provides optical identifications for 19 179 radio sources from the 1.4 GHz Faint Images of the Radio Sky at Twenty-cm (FIRST) survey down to an optical magnitude limit of i mod < 20.5 in Sloan Digital Sky Survey (SDSS) images. Both galaxies and point-like objects are included, and no colour cuts are applied. In collaboration with the WiggleZ and Galaxy And Mass Assembly (GAMA) spectroscopic survey teams, we have obtained new spectra for over 5000 objects in the LARGESS sample. Combining these new spectra with data from earlier surveys provides spectroscopic data for 12 329 radio sources in the survey area, of which 10 856 have reliable redshifts. 85 per cent of the LARGESS spectroscopic sample are radio AGN (median redshift z = 0.44), and 15 per cent are nearby star-forming galaxies (median z = 0.08). Low-excitation radio galaxies (LERGs) comprise the majority (83 per cent) of LARGESS radio AGN at z < 0.8, with 12 per cent being high-excitation radio galaxies (HERGs) and 5 per cent radioloud QSOs. Unlike the more homogeneous LERG and QSO sub-populations, HERGs are a heterogeneous class of objects with relatively blue optical colours and a wide dispersion in mid-infrared colours. This is consistent with a picture in which most HERGs are hosted by galaxies with recent or ongoing star formation as well as a classical accretion disc.
Differences in the effectiveness of audiovisual sex education by nurse and peer education on prevention of premarital sex

The trend issue of premarital sexual experiences in Indonesia is a serious problem and more pay attention. The consequences of premarital sex are family stigma and social sanctions that has an impact on teenagers choosing kill their newborn babies. One of the most effective educate youth about sexual health issues is through peer educator groups and audiovisual sex education. The aims of this study to analyze differences in the effectiveness of sex education in adolescents based on audiovisual and peer education on the prevention of pre-marital sex. A quasy-experimental design method with pretest-posttest with control group design was conducted. A total of 32 adolescents were included. In this study there is a significant difference in the level of knowledge (p= 0.000) and premarital sexual behavior (p= 0.001) before and after being given audiovisual sex education by nursing. Meanwhile, there is a significant difference in the level of knowledge before and after being given peer education (p= 0.006) but there is no significant difference in the level of premarital sexual behavior before and after given peer education (p= 0.057). Audiovisual sex education is more effective than peer education on prevention of pre-marital sex.
Trajectories towards affirmation: Gender identity in mental health services after the ICD-11

Depathologisation of gender diversity in the ICD-11 marks a shift in psychological services for transgender and gender nonconforming people. Even though the stipulated changes are only practically applicable ever since early 2022, a general move towards affirmative psychotherapeutic and counselling practice has been noticed ever since 2018. The present paper covers three main models of mental health care for gender minorities, namely the conversion therapy model, the transsexual gatekeeping model, and the affirmative model, in order to view them under a novel lens. Drawing on Science, Technology and Society Studies, the universalist presumptions and rigid gender roles of the traditional models are brought under scrutiny. Moreover, the itinerary reveals the need for situated narratives that encourage self-determination and renovate the therapeutic relationship as a means of self-exploration instead of an institutional control mechanism. Concluding, it is remarked that intersectional knowledge is crucial in compensating for micro-aggressive practices and dynamics historically promoted by psychologists and other mental health providers.
Simple Inference for Constrained Optima ∗

where the vector p is known and well-behaved estimators of the (vector valued) constraint functions f and g are available; in particular these could be moment (in)equalities. A leading application is projection of partially identified vectors, notably inference on their components. We call the method “simple” because a critical value is computed at most once per direction of inference, i.e. at most twice for a two-sided test. This is in contrast to very generally valid methods like Bugni, Canay, and Shi (2017), Kaido, Molinari, and Stoye (2017), or also projection of confidence regions defined in Andrews and Soares (2010), all of which recompute critical values many times. The price is that assumptions became stronger. Compared to other approaches with similar computational cost, however, assumptions are still rather weak. Similarly to Kaido, Molinari, and Stoye (2017), the basic idea is to relax sample analogs of studentized constraints by an amount ĉn calibrated so that the problem’s optimal value is covered (uniformly asymptotically) with pre-assigned probability. This can be computationally demanding if –as is the case in the most general settings– the limit of ĉn depends on the parameter value θ at which it is evaluated, so that ĉn must be computed many times. We show that, under arguably reasonable assumptions, it suffices to compute ĉn once. The main theoretical insights are as follows:
Science Teachers’ Level of Concern on Dual Language Programme (DLP) in Primary Schools in Sri Aman District

This study aims to identify the Science teachers’ level of concern towards the implementation of Dual Language Programme (DLP) in primary schools in Sri Aman District. Concern Based Adaptation Model (CBAM) is applied as the theoretical framework. Meanwhile, the adapted Stage of Concern Questionnaire (SoCQ) is used as a research instrument to determine the level of teacher’s concern. A total of 45 Science teachers were selected by using purposive sampling method. Descriptive data analysis was conducted to generate demographic group profiles as well as general profiles of teachers’concerns based on the SoCQ Quick Scoring Device guidelines. The results of the study found both types of profiles; general and demographic, showed high concern for awareness (Stage 0), information (Stagel 1) and personal (Stage 2), whereas, low concern intensity scores for collaboration (Stage 5) and refocusing (Stage 6). Such concern level profiles reflect that teachers show little involvement with, general awareness of and uncertain feeling towards the DLP. The results are important for the stakeholders to provide intervention programmes to support teachers to undergo the curriculum innovation.
A Deep Dive: Does Big Data Improve Maturity in the Developed Capital Markets?

Over this decade, the concept of big data has been applied to industries but the capital markets have been traditionally laggard to adoption. Within the financial services’ sector, Big Data has gained far more traction within retail banking and insurance due to the increasing desire of these financial institutions to profile and analyze their customers in a similar manner to early adopters of Big Data strategy such as Amazon, Baidu or Google. However, Big Data strategies have begun to make some impacts on few selected areas of the capital markets, including the social media sentiment analysis on the structured and unstructured data for trading, growth in volume, risk analytics, fraud prevention, market surveillance, predictability and forecasting of the equity prices; those are the early sign of the maturity of the capital markets. Technical and theoretical measures have evolved, but still these dimensions of the capital markets have been a mystery for the human beings till now. The Big Data in the form of structured, semi-structured and unstructured socio-economic and demographic information from social media and blogs from consumers has started indicating impacts on the capital markets which can lead to improving the real-time systems and transaction processing, and improving operational efficiency and maturity. The intent of this paper is threefold. First, it aims to bring the clear inference from the past researches to take a holistic analysis of the work done in the emerging area of Big Data and its implications on capital markets. Second, it’s to perform a deep analysis on how the influences of Big Data affect the assumptions in connection with Random Walk theory and Efficient Market Hypothesis. Third, it will provide a conclusive theoretical analysis of past research work by the scholars, which can establish the model to refine the nexus between investors’ sentiments and assets’ prices with advanced techniques in the Big Data. The paper has been divided into 4 broad sections. In the first section, the paper sets the introduction of connecting the dots and setting the context for the two different fields like Big Data and its influences on the capital markets. The second section explains the theoretical premises and frameworks needed for this research and does deep studies of the previous works in this area to establish conclusive references for the future study. The third section carries out the studies of emerging social media and technologies, analysis of the previous research works from the social media and the capital markets perspective. Finally, the fourth section concludes findings with recommendations.
A study of two domain decomposition preconditioners.

Large-scale finite element analysis often requires the iterative solution of equations with many unknowns. Preconditioners based on domain decomposition concepts have proven effective at accelerating the convergence of iterative methods like conjugate gradients for such problems. A study of two new domain decomposition preconditioners is presented here. The first is based on a substructuring approach and can viewed as a primal counterpart of the dual-primal variant of the finite element tearing and interconnecting method called FETI-DP. The second uses an algebraic approach to construct a coarse problem for a classic overlapping Schwarz method. The numerical properties of both preconditioners are shown to scale well with problem size. Although developed primarily for structural mechanics applications, the preconditioners are also useful for other problems types. Detailed descriptions of the two preconditioners along with numerical results are included.
Lateral cephalometric radiograph analysis on obstructive sleep apnea patients

Objectives: This review article is aimed to investigate changes in anatomical factors in Obstructive Sleep Apnea (OSA) patients through means of a cephalometric radiograph, which covers relation and size. Review: This literature review used online databases (PubMed and Scopus) discussing obstructive sleep apnea (OSA) in adults aged 18-80 years, using cephalometric analysis, and several keywords such as “obstructive sleep apnea and cephalometry” were employed to do the literature search. The search was limited to full-text articles written in English and published during the 2011-2021 period. Articles were selected by complying with literature review guidelines. Conclusion: Dentists can detect OSA early through lateral radiograph, which is originally an early screening tool, by paying attention to patients’ position during exposure, irradiation condition (kV, mA and Sec) and patient position in OSA diagnosis in regards to hard and soft tissue being evaluated. The specific craniofacial morphological variable could be a reliable parameter in determining the existence of OSA.
An Efficient Load Balancing Technique for Mutation based Particle Swarm Optimization

: Load balancing techniques play significant role in cloud computing environment because it directly af-fects the performance of cloud data centers. An efficient load balancing technique not only provides high availability of resources to cloud users, but also enhances the performance of cloud data centers. Load balancing techniques are a typical NP-hard problem. Currently, many researchers have solved load bal-ancing problem by considering well-known metaheuristic techniques. However, these techniques suffer from one of these issues: premature convergence, poor convergence speed, initially selected random so-lutions and stuck in local optima. To handle the issues associated with existing metaheuristic techniques, in this paper, a mutation based particle swarm optimization based load balancing technique is proposed. The proposed technique has an ability to overcome several issues associated with existing techniques such as premature convergence, poor convergence speed, initially selected random solutions and stuck in local optima issues. Also, multi-objective fitness function is designed as a minimization problem. Multi-objective fitness function considers energy consumption, makespan and load imbalance rate parameters. The proposed technique outperforms existing load balancing techniques in terms of makespan, speedup, communication overheads, efficiency, utilization, mean gain time, load imbalance rate and energy consumption.
Is flood to drip irrigation a solution to groundwater depletion in the Indo-Gangetic plain?

Indian river basins are intensively managed with country-specific agricultural practices of cultivating submerged paddy and uncontrolled groundwater (GW) irrigation. Numerical experiments with the state-of-the-art land surface models, such as variable infiltration capacity (VIC), without incorporating region-specific practices, could be misleading. Here, we coupled VIC with 2D GW model AMBHAS, incorporating India-specific irrigation practices and crop practices, including submerged paddy fields. We performed numerical experiments to understand the causal factors of GW depletion in the northwest Indo-Gangetic plain (IGP). We identify widespread flood irrigation and cultivation of water-intensive paddy as critical drivers of the declining GW scenario. Our numerical experiments suggest that the introduction of drip irrigation reduces GW depletion in the northwest, but does not change the sign of GW level trends. The GW levels in the non-paddy fields of the middle IGP are less sensitive to irrigation practices due to the high return flow to GW for flood irrigation.
IMPACT OF LEVERAGE AND FINANCIAL DISTRESS ON ACCOUNTING CONSERVATISM

This study objective is to determine whether and how exposure to financial stress and leverage can prompt accountants to exercise greater caution when working with numerical data. The investigation covered 165 manufacturing companies that were scheduled to be listed on the Indonesia Stock Exchange in 2020. For the purpose of this study, a purposive sampling technique was utilized to select a total of 52 different companies at random. The records of the company's finances that have been audited are the source of the secondary data. The approach taken in this study is primarily based on the use of quantitative methods. SPSS version 26's descriptive statistics, multiple linear regression, analysis requirements, classical assumption, and hypothesis testing features were utilized in order to conduct the analysis on the collected data. According to the findings of the study, there is no statistically significant connection between financial hardship and conservative accounting practices. Leverage does not significantly alter the cautious nature of accounting. Moreover, the combined effects of financial distress and leverage have little to no visible influence on the conservative accounting process.
Barriers and facilitators to implementing the Activate injury prevention exercise programme – A qualitative study of schoolboy rugby coaches

The rugby-specific Activate injury prevention exercise programme was deemed efficacious in a randomised controlled trial and subsequently disseminated nationwide by the Rugby Football Union (English rugby union governing body) in 2017. However, no assessment has been made of the factors influencing Activate implementation in an applied setting. Consequently, this study sought to assess the barriers and facilitators to coaches implementing Activate in English schoolboy rugby. This qualitative study adopted a framework approach, using four a-priori themes influencing injury prevention implementation: awareness, motivational determinants, volitional determinants and socio-environmental factors. A purposive sample of schoolboy rugby coaches were recruited from schools nationwide, participating in semi-structured, one-on-one interviews (n = 10). Transcripts were thematically coded. Participants had positive perceptions towards Activate, although only six adopted the programme. Participants reported that players were generally unaware of the programme, with some suggesting this was not an issue as coaches made the decision to adopt Activate. Participants focused heavily upon the use of resources to develop coaches’ awareness, knowledge and confidence. No participant implemented Activate as initially designed, influenced by time and engagement, instead incorporating it within training drills rather than as a block at the beginning of the session. Participants adapted the programme to make it suitable for multiple sports. Some participants reported asking players to deliver Activate, despite their lack of awareness, raising concerns around implementation. Participants heavily adapted Activate delivery to suit their contexts. How this affects the effectiveness of Activate to reduce injury risk is unknown and should be investigated. Player-specific dissemination strategies should be considered if these individuals act as delivery-agents.
Evaluation of the Physicochemical and Thermal Properties of Folic Acid: Influence of the Energy of Consciousness Healing Treatment

Folic acid is vitamin B9, which is a water-soluble vitamin that plays an important role in cell growth, production of DNA and replication. This study was aimed to determine the influence of the Trivedi Effect® Consciousness Energy Healing Treatment on the various physicochemical and thermal properties of folic acid by using the different analytical techniques. The study was done by dividing the folic acid sample into the control and treated parts; in which, no treatment was given to control, while the treated part received the Consciousness Energy Healing Treatment remotely by a renowned Biofield Energy Healer, Dahryn Trivedi. The analysis indicated that the particle sizes of the treated sample were reduced by 3.80% (d10), 5.18% (d50), 6.33% (d90), and 4.79% {D (4,3)}, respectively, which resulted in the increase in surface area by 4.60% compared with the control sample. The PXRD analysis indicated the changes in the peak intensities of the characteristic peaks of the treated sample and their corresponding crystallite sizes in the range from -45.76% to 277.50% and -87.55% to 15.88%, respectively, in comparison to the control folic acid sample. The treated sample also showed a significant reduction in the average crystallite size by 19.37% compared with the control sample. The weight loss of the treated sample was increased during thermal degradation by 9.11% and therefore, the decreased residual mass by 36.56%, in comparison to the untreated sample. The DSC analysis of the treated sample revealed the increase in melting and degradation temperature by 10.48% and 7.32%, respectively; while the latent heat of fusion and decomposition were reduced by 2.27% and 34.35%, respectively, compared to the untreated sample. The overall study indicated that the Trivedi Effect®Consciousness Energy Healing Treatment has the significant impact of on the folic acid, which might be used as a novel approach for introducing some new polymorph of folic acid and thereby improving its solubility, bioavailability, and melting and degradation profile in comparison to the untreated sample. Hence, the Trivedi Effect® could be used as a useful approach in developing the nutraceutical/pharmaceutical formulations of folic acid with improved performance and efficacy.