Miracle-dz/UniFAR-FTUs huggingface dataset:
Thermal Conductivity of Water at Extreme Conditions

Measuring the thermal conductivity (κ) of water at extreme conditions is a challenging task, and few experimental data are available. We predict κ for temperatures and pressures relevant to the conditions of the Earth mantle, between 1,000 and 2,000 K and up to 22 GPa. We employ close to equilibrium molecular dynamics simulations and a deep neural network potential fitted to density functional theory data. We then interpret our results by computing the equation of state of water on a fine grid of points and using a simple model for κ. We find that the thermal conductivity is weakly dependent on temperature and monotonically increases with pressure with an approximate square-root behavior. In addition, we show how the increase of κ at high pressure, relative to ambient conditions, is related to the corresponding increase in the sound velocity. Although the relationships between the thermal conductivity, pressure and sound velocity established here are not rigorous, they are sufficiently accurate to allow for a robust estimate of the thermal conductivity of water in a broad range of temperatures and pressures, where experiments are still difficult to perform.
Generating Phishing Attacks using ChatGPT

The ability of ChatGPT to generate human-like responses and understand context has made it a popular tool for conversational agents, content creation, data analysis, and research and innovation. However, its effectiveness and ease of accessibility makes it a prime target for generating malicious content, such as phishing attacks, that can put users at risk. In this work, we identify several malicious prompts that can be provided to ChatGPT to generate functional phishing websites. Through an iterative approach, we find that these phishing websites can be made to imitate popular brands and emulate several evasive tactics that have been known to avoid detection by anti-phishing entities. These attacks can be generated using vanilla ChatGPT without the need of any prior adversarial exploits (jailbreaking).
Binary neutron star populations in the Milky Way

Galactic binary neutron stars (BNSs) are a unique laboratory to probe the evolution of BNSs and their progenitors. Here, we use a new version of the population synthesis code SEVN to evolve the population of Galactic BNSs, by modeling the spin up and down of pulsars self-consistently. We analyze the merger rate $\mathcal{R}_{\rm MW}$, orbital period $P_{\rm orb}$, eccentricity $e$, spin period $P$, and spin period derivative $\dot{P}$ of the BNS population. Values of the common envelope parameter $\alpha=1 - 3$ and an accurate model of the Milky Way star formation history best reproduce the BNS merger rate in our Galaxy ($\mathcal{R}_{\rm MW}\approx{}30$ Myr$^{-1}$). We apply radio-selection effects to our simulated BNSs and compare them to the observed population. Using a Dirichlet process Gaussian mixture method, we evaluate the four-dimensional likelihood in the $(P_{\rm orb}, e, P, \dot{P})$ space, by comparing our radio-selected simulated pulsars against Galactic BNSs. Our analysis favours an uniform initial distribution for both the magnetic field ($10^{10-13}$ G) and the spin period ($10-100$ ms). The implementation of radio selection effects is critical to match not only the spin period and period derivative, but also the orbital period and eccentricity of Galactic BNSs. According to our fiducial model, the Square Kilometre Array will detect $\sim 20$ new BNSs in the Milky Way.
CPMA: An Efficient Batch-Parallel Compressed Set Without Pointers

This paper introduces the batch-parallel Compressed Packed Memory Array (CPMA), a compressed, dynamic, ordered set data structure based on the Packed Memory Array (PMA). Traditionally, batch-parallel sets are built on pointer-based data structures such as trees because pointer-based structures enable fast parallel unions via pointer manipulation. When compared with cache-optimized trees, PMAs were slower to update but faster to scan. The batch-parallel CPMA overcomes this tradeoff between updates and scans by optimizing for cache-friendliness. On average, the CPMA achieves 3x faster batch-insert throughput and 4x faster range-query throughput compared with compressed PaC-trees, a state-of-the-art batch-parallel set library based on cache-optimized trees. We further evaluate the CPMA compared with compressed PaC-trees and Aspen, a state-of-the-art system, on a real-world application of dynamic-graph processing. The CPMA is on average 1.2x faster on a suite of graph algorithms and 2x faster on batch inserts when compared with compressed PaC-trees. Furthermore, the CPMA is on average 1.3x faster on graph algorithms and 2x faster on batch inserts compared with Aspen.
Multi-Teacher Knowledge Distillation For Text Image Machine Translation

Text image machine translation (TIMT) has been widely used in various real-world applications, which translates source language texts in images into another target language sentence. Existing methods on TIMT are mainly divided into two categories: the recognition-then-translation pipeline model and the end-to-end model. However, how to transfer knowledge from the pipeline model into the end-to-end model remains an unsolved problem. In this paper, we propose a novel Multi-Teacher Knowledge Distillation (MTKD) method to effectively distillate knowledge into the end-to-end TIMT model from the pipeline model. Specifically, three teachers are utilized to improve the performance of the end-to-end TIMT model. The image encoder in the end-to-end TIMT model is optimized with the knowledge distillation guidance from the recognition teacher encoder, while the sequential encoder and decoder are improved by transferring knowledge from the translation sequential and decoder teacher models. Furthermore, both token and sentence-level knowledge distillations are incorporated to better boost the translation performance. Extensive experimental results show that our proposed MTKD effectively improves the text image translation performance and outperforms existing end-to-end and pipeline models with fewer parameters and less decoding time, illustrating that MTKD can take advantage of both pipeline and end-to-end models.
Feynman-Hellmann approach to transition matrix elements and quasidegenerate energy states

The Feynman--Hellmann approach to computing matrix elements in lattice QCD by first adding a perturbing operator to the action is described using the transition matrix and the Dyson expansion formalism. This perturbs the energies in the two-point baryon correlation function, from which the matrix element can be obtained. In particular at leading order in the perturbation we need to diagonalise a matrix of near-degenerate energies. While the method is general for all hadrons, we apply it here to a study of a Sigma to Nucleon baryon transition vector matrix element.
Exploring methods for creation of Boron-vacancies in hexagonal Boron Nitride exfoliated from bulk crystal

Boron vacancies (VB${^-}$) in hexagonal boron-nitride (hBN) have sparked great interest in recent years, due to their electronic spin properties. Since hBN can be readily integrated into devices where it interfaces a huge variety of other 2D materials, boron vacancies may serve as a precise sensor which can be deployed at very close proximity to many important materials systems. Boron vacancy defects may be produced by a number of existing methods, the use of which may depend on the final application. Any method should reproducibly generate defects with controlled density and desired pattern. To date, however, detailed studies of such methods are missing. In this paper we study various techniques, focused ion beam (FIB), electron irradiation and ion implantation, for the preparation of hBN flakes from bulk crystals, and relevant post-processing treatments to create VB${^-}$s as a function of flake thickness and defect concentrations. We find that flake thickness plays an important role when optimising implantation parameters, while careful sample cleaning proved important to achieve best results.
Utilization of a novel mobile application, “HBB Prompt”, to reduce Helping Babies Breathe skills decay

Background Helping Babies Breathe (HBB) is a newborn resuscitation training program designed to reduce neonatal mortality in low- and middle-income countries. However, skills decay after initial training is a significant barrier to sustained impact. Objective To test whether a mobile app, HBB Prompt, developed with user-centred design, helps improve skills and knowledge retention after HBB training. Methods HBB Prompt was created during Phase 1 of this study with input from HBB facilitators and providers from Southwestern Uganda recruited from a national HBB provider registry. During Phase 2, healthcare workers (HCWs) in two community hospitals received HBB training. One hospital was randomly assigned as the intervention hospital, where trained HCWs had access to HBB Prompt, and the other served as control without HBB Prompt (NCT03577054). Participants were evaluated using the HBB 2.0 knowledge check and Objective Structured Clinical Exam, version B (OSCE B) immediately before and after training, and 6 months post-training. The primary outcome was difference in OSCE B scores immediately after training and 6 months post-training. Results Twenty-nine HCWs were trained in HBB (17 in intervention, 12 in control). At 6 months, 10 HCW were evaluated in intervention and 7 in control. In intervention and control respectively, the median OSCE B scores were: 7 vs. 9 immediately before training, 17 vs. 21 immediately after training, and 12 vs. 13 at 6 months after training. Six months after training, the median difference in OSCE B scores was -3 (IQR -5 to -1) in intervention and -8 (IQR -11 to -6) in control (p = 0.02). Conclusion HBB Prompt, a mobile app created by user-centred design, improved retention of HBB skills at 6 months. However, skills decay remained high 6 months after training. Continued adaptation of HBB Prompt may further improve maintenance of HBB skills.
Myocardial Infarction in Young Individuals: A Review Article

Although myocardial infarction (MI) primarily affects patients over the age of 45, it can also affect young women and men. Still, when it occurs at an early age, it has severe morbidity and psychological and financial burdens for the patient and his or her relatives. Four classes can be used to categorize the causes of MI in individuals below the age of 45. These are drug abuse-related MI, hyper-coagulable conditions, atheromatous coronary artery disease (CAD), and non-atheromatous CAD. There is a significant overlap between each category. Elevated blood pressure, smoking, diabetes, obesity, high cholesterol, inactivity, an unbalanced diet, binge drinking alcohol, and related substances are all risk factors. The primary mechanism of an MI is typically the total obstruction of a vessel caused by breaking an atheromatous plaque. This article covers the research and focuses on the practical concerns related to young adults with MI.
Localization on a-priori information of plane extraction

Localization constitutes a critical challenge for autonomous mobile robots, with flattened walls serving as a fundamental reference for indoor localization. In numerous scenarios, prior knowledge of a wall’s surface plane is available, such as planes in building information modeling (BIM) systems. This article presents a localization technique based on a-priori plane point cloud extraction. The position and pose of the mobile robot are estimated through real-time multi-plane constraints. An extended image coordinate system is proposed to represent any planes in space and establish correspondences between visible planes and those in the world coordinate system. Potentially visible points representing the constrained plane in the real-time point cloud are filtered using the filter region of interest (ROI), derived from the theoretical visible plane region within the extended image coordinate system. The number of points representing the plane influences the calculation weight in the multi-plane localization approach. Experimental validation of the proposed localization method demonstrates its allowance for redundancy in initial position and pose error.
Gender invariance in the relationship between social support and glycemic control

Background Social support (SS) is important in diabetes self-management; however, little is known about how different types of SS influence diabetes outcomes in men and women with type 2 diabetes mellitus (T2DM). Therefore, the aims of this study were to investigate the relationships between types of SS and glycemic control and self-care behaviors and assess whether the relationships differ by gender. Methods Cross-sectional study of 615 adults from two primary care clinics in the southeastern U.S. Outcomes were hemoglobin A1c (HbA1c) extracted from the medical records, and self-management behaviors (general diet, specific diet, exercise, blood glucose testing, foot care) measured using the Summary of Diabetes Self-Care Activities (SDSCA). Independent variable was SS (emotional/informational, tangible, affectionate, positive social interaction) measured using the Medical Outcomes Study (MOS) SS Scale. Structural equation modeling (SEM) was used to understand pathways between SS and glycemic control based on a theoretical model. Results Tangible support was significantly associated with self-care (r = 0.16; p = 0.046) and affectionate support was marginally associated with glycemic control (r = 0.15; p = 0.08) for both men and women. Using SEM to test gender invariance, there was no statistically significant difference in the meaning of SS between men and women. However, unique invariances in responses occurred, including a stronger relationship between tangible support and self-care for women (r = 0.24; p = 0.061). Conclusions Of the four components of SS, tangible and affectionate support had the strongest influence on glycemic control. While affectionate support will improve glycemic control in both men and women, tangible support will improve self-care management, particularly in women.
Bending self-collimated one-way light by using gyromagnetic photonic crystals

We theoretically demonstrate that electromagnetic waves can self-collimate and propagate unidirectionally in photonic crystals fabricated using semicylindrical ferrite rods in magnetized states. The parity and time-reversal symmetries of such photonic crystals are broken, resulting in a self-collimated one-way body wave within the photonic crystals. By applying the bias magnetic field in a complex configuration, the self-collimated one-way wave beam can be bent into arbitrary trajectories within the photonic crystal, providing an avenue for controlling wave beams.
Effect of postruminal supply of linseed oil in dairy cows: 2. Milk fatty acid profile and oxidative stability

Abstract Our objective was to study the effect of increasing postruminal supply of linseed oil (L-oil), as a source of cis-9, cis-12, cis-15 18:3, on milk fatty acid profile and to assess the resulting impact on the development of volatile degradation products during the storage of homogenized milk. Five Holstein dairy cows fitted with a rumen cannula were randomly distributed in a 5 × 5 Latin square design. Abomasal infusion of L-oil was performed at the rate of 0, 75, 150, 300, and 600 ml/d during periods of 14 d. The concentration of cis-9, cis-12, cis-15 18:3 in milk fat increased linearly with L-oil dose. Concentrations of primary (conjugated diene and triene hydroperoxides) and secondary oxidation products (1-octen-3-one, propanal, hexanal, trans-2 + cis-3-hexenals, cis-4-heptenal, trans-2, cis-6-nonadienal trans-2, trans-4-nonadienal) increased during 11 d of storage at 4°C of homogenized milk under fluorescent light. The magnitude of the increase (difference between final and initial measurements) was linearly greater for all nine lipid oxidation products evaluated in response to increasing level of infusion. Results of the current experiment have shown that milk enriched in cis-9, cis-12, cis-15 18:3 via postruminal supply of L-oil is highly prone to oxidative degradation. This low oxidative stability, exposed under controlled experimental conditions, would represent a major obstacle to those who aim to market milk enriched in polyunsaturated fatty acids.
Studies pertaining to language impairment in school-age autistic individuals underreport participant socio-demographics: A systematic review

Autism research tends to exclude racially and ethnically minoritized autistic individuals, limiting the quality of the evidence base for characterizing and diagnosing language impairment in racially and ethnically minoritized autistic individuals. This systematic review examines reporting practices for participant socio-demographics in studies pertaining to language impairment in autistic school-age individuals using age-referenced assessments. This review was preregistered (PROSPERO: CRD42021260394) and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol. Database searches took place in August of 2021 in Linguistics and Language Behavior Abstracts, PsycINFO, PubMed, and the Directory of Open Access Journals, for publications during 1980–2021. Search terms included three essential concepts: autism, language, and age. Two coders independently screened and evaluated articles. Of qualifying studies (n = 59), 17 (29%) reported any information on participant race and ethnicity; in these studies, participants were at least 77% white. Thirty-two studies (54%) reported gender or sex; just 10 studies (17%) reported socio-economic status using multiple indicators. These findings indicate insufficient adherence to reporting guidelines and systematic exclusion of racially and ethnically minoritized. Future work must address replicable reporting and inclusion in autism research. Lay abstract Although exclusion of racially and ethnically minoritized autistic individuals from research is a long-standing issue, we have yet to determine how exclusion impacts areas of autism research important for identifying language impairment. Diagnosis depends on the quality of the evidence (i.e. research) and is often the pathway to gaining access to services. As a first step, we examined how research studies related to language impairment in school-age autistic individuals report participant socio-demographics. We analyzed reports using age-referenced assessments in English (n = 60), which are commonly used by both practitioners and researchers to diagnose or identify language impairment. Findings showed only 28% of studies reported any information on race and ethnicity; in these studies, most (at least 77%) of the participants were white. In addition, only 56% of studies reported gender or sex and specified what they were reporting (gender, sex, or gender identity). Just 17% reported socio-economic status using multiple indicators. Altogether, findings indicate broad issues with underreporting and exclusion of racially and ethnically minoritized individuals, which might overlay with other aspects of identity including socio-economic status. It is impossible to determine the extent and precise nature of exclusion without intersectional reporting. To ensure that language in autism research is representative of the autistic population, future research must implement reporting guidelines and broaden inclusion of who participates in research studies.
Patterns of health-promoting behaviors and associated factors in family caregivers of people receiving cancer treatment: A latent class profile analysis

Family caregivers tend to neglect their health while prioritizing the needs of their care recipients. Identifying subgroups of caregivers based on the patterns of health‐promoting behaviors (HPBs) may help develop tailored interventions for them, yet little is known. The purpose of this study was: (1) to identify latent classes with distinct patterns of HPBs in family caregivers of people with cancer; and (2) to investigate factors associated with the latent class membership.
Poroscopy: A method of personal identification revisited

Poroscopy, a little studied aspect of personal identification has been undertaken in the present work. Rolled and plain finger prints of one hundred individuals along with their palm prints were obtained to study shape, size, position, inter-spacing and number per unit area of pores etc. These findings were compared with the findings obtained from the latent prints of same number of individuals to see the practical feasibility of the poroscopy in personal identification. It is found that though the study of pores due to their microscopic nature is somewhat difficult as compared to the study of ridge characteristics, but the results achieved in the present study indicate that identification with the help of poroscopy is as reliable and accurate as ridge characteristics and can be compared with the results obtained through the study of ridge characteristics.
Construction of the "Last Mile" Service Quality Evaluation Index System for E-commerce Logistics ——Analysis of Questionnaire Based on Consumer Perception

The “last mile” of logistics is in the terminal link of the logistics supply chain, which restricts the development of the logistics industry. Studying this link is of great significance for improving the logistics operation level and logistics service level. The “last mile” is also the only part of logistics distribution that can face consumers. Consumers play decisive roles in it, and consumer satisfaction is closely related to consumer’s perception. Using Kaizhou District of Chongqing for empirical research, the paper summarized many indicators that influence the consumer’s perception in the “last mile” of e-commerce logistics based on an in-depth interview and literature review. Employing the exploratory factor analysis, the main indicators of service quality evaluation were obtained. After testing the reliability and validity of the survey data, the 5-dimensional logistics service quality thus, order quality, delivery quality, reliability, personnel quality and product quality evaluation index system which conformed to the Chinese situation is finally revised and constructed. The corresponding suggestions for logistics enterprises were put forward based on the findings. Keywords—Last mile; consumer perception; e-commerce logistics; service quality evaluation
ELICITATION OF INFRARED RADIANT TRACK ALONG MERIDIAN COURSES OVER HUMAN BODY SURFACE BY LOCAL HEATING

The infrared radiant track along meridian course(IRRTM)over human body surface could be elicited by local heating acupoint or non-acupoint along meridian course. The thermal conductivity of the corresponding tissues along meridian course was better than that of nonmeridain area. The physical character between the two was really different in certain aspect. This discovery provided an important basis for further clarifying the mechanism of the appearance of IRRTM and the substantiality of its formation.
Methicillin resistant Staphylococcus aureus isolated from surgical patients in Cambodia over a 10-year period

Methicillin-resistant Staphylococcus aureus (MRSA) related surgical infections are a global challenge. The burden of antimicrobial resistance is high throughout South-East Asia, and this is reflected in our local institution in Cambodia. Between 2011 and 2013, we analysed 251 wound swab samples at the Children's Surgical Centre, Phnom Penh; 52.5% of the Staphylococcus aureus isolates (n = 52/99) were MRSA positive. Ten years on, we have sought to investigate whether there is a difference in MRSA rates within our adult and paediatric patient population. Between 2020 and 2022, MRSA rates in our patient population have remained similar at 53.8% (n = 42/78). Resistance profiles of MRSA isolates have also remained similar with a significant proportion of MRSA still showing sensitivity to trimethoprim-sulfamethoxazole and tetracycline. We also find that patients presenting with wound infection secondary to trauma or orthopaedic implants had greater propensity to yield MRSA.