Miracle-dz/UniFAR-FTUs huggingface dataset:
Two new species of the genus Cylindrophis Wagler, 1828 (Squamata: Cylindrophiidae) from Southeast Asia

© 2015 Amarasinghe et al. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercialNoDerivatives 4.0 International License, which permits unrestricted use for non-commercial and education purposes only, in any medium, provided the original author and the official and authorized publication sources are recognized and properly credited. The official and authorized publication credit sources, which will be duly enforced, are as follows: official journal title Amphibian & Reptile Conservation; official journal website . The attached file is the published version of the article.
An Unsupervised Machine Learning Scheme for Index-Based CSI Feedback in Wi-Fi

With the ever-increasing demand for high-speed wireless data transmission, beamforming techniques have been proven to be crucial in improving the data rate and the signal-to-noise ratio (SNR) at the receiver. However, they require feedback mechanisms that need an overhead of information and increase the system complexity, potentially challenging the efficiency and capacity of modern wireless networks. This paper investigates novel index-based feedback mechanisms that aim at reducing the beamforming feedback overhead in Wi-Fi links. The proposed methods mitigate the overhead by generating a set of candidate beamforming vectors using an unsupervised learning-based framework. The amount of feedback information required is thus reduced by using the index of the candidate as feedback instead of transmitting the entire beamforming matrix. We explore several methods that consider different representations of the data in the candidate set. In particular, we propose five different ways to generate and represent the candidate sets that consider the covariance matrices of the channel, serialize the feedback matrix, and account for the effective distance, among others. Additionally, we also discuss the implications of using partial information in the compressed beamforming feedback on the link performance and compare it with the newly proposed index-based methods. Extensive IEEE 802.11 standard-compliant simulation results show that the proposed methods effectively minimize the feedback overhead, enhancing the throughput while maintaining an adequate link performance.
Davemaoite as the mantle mineral with the highest melting temperature

Knowledge of high-pressure melting curves of silicate minerals is critical for modeling the thermal-chemical evolution of rocky planets. However, the melting temperature of davemaoite, the third most abundant mineral in Earth’s lower mantle, is still controversial. Here, we investigate the melting curves of two minerals, MgSiO3 bridgmanite and CaSiO3 davemaoite, under their stability field in the mantle by performing first-principles molecular dynamics simulations based on the density functional theory. The melting curve of bridgmanite is in excellent agreement with previous studies, confirming a general consensus on its melting temperature. However, we predict a much higher melting curve of davemaoite than almost all previous estimates. Melting temperature of davemaoite at the pressure of core-mantle boundary (~136 gigapascals) is about 7700(150) K, which is approximately 2000 K higher than that of bridgmanite. The ultrarefractory nature of davemaoite is critical to reconsider many models in the deep planetary interior, for instance, solidification of early magma ocean and geodynamical behavior of mantle rocks.
Further Evidence of Coal Fly Ash Utilization in Tropospheric Geoengineering: Implications on Human and Environmental Health

We disclose a fourth independent line of evidence, based on the co-precipitation technique, pointing to coal fly ash as the material utilized in tropospheric geoengineering, and describe some of the adverse environmental and public health risks associated with its persistent application. During a snow storm, the fluffy snow traps geoengineering-aerosol-particulates and brings them down with the snow. The results of the ICP-MS analytical measurements of the snow-melt particulates we tested are consistent with three independent lines of evidence that coal fly ash is the main aerosolized particulate used for tropospheric geoengineering. Coal fly ash tropospheric geoengineering inhibits rainfall to change weather/climate which disrupts habitats, including arable habitats. Long periods of artificially induced drought can wreak economic disaster on farmers, and shift the delicate balance in nature, weakening natural defenses and giving a boost to aggressive Short Communication Herndon and Whiteside; JGEESI, 9(1): 1-8, 2017; Article no.JGEESI. 31417 2 pathogens. Coal fly ash when exposed to water or body fluids can release a host of toxic chemicals including neuro-toxic aluminum in a chemically mobile form and carcinogens such as arsenic, hexavalent chromium, and the radioactive elements, uranium, thorium and their daughter products. The only safe geoengineering is no geoengineering at all.
On the Progenitors of Two Type II-P Supernovae in the Virgo Cluster

Direct identification of the progenitors of supernovae (SNe) is rare because of the required spatial resolution and depth of the archival data prior to the SN explosions. Here we report on the identification of the progenitors of two nearby SNe in the Virgo Cluster: SN 2006my in NGC 4651 and SN 2006ov in M61. We obtained high-quality ground-based images of SN 2006my with the Canada-France-Hawaii Telescope, and are able to locate the site of the SN on pre-SN Hubble Space Telescope (HST) Wide Field Planetary Camera 2 images to a high precision (1 σ uncertainty of ±0.05''). We pinpoint the site of SN 2006ov to within 0.02'' from HST Advanced Camera for Surveys images of the SN. We detected a red supergiant progenitor for each SN within the error circles, with an inferred zero-age main-sequence mass (Mzams) of 10 and 15 M☉ for the progenitors of SNe 2006my and 2006ov, respectively. The mass estimates for the progenitors of both SNe confirm a suggested trend that the most common Type II-plateau SNe originate from low-mass supergiants with Mzams ≈ 8-20 M☉.
Series2Vec: Similarity-based Self-supervised Representation Learning for Time Series Classification

We argue that time series analysis is fundamentally different in nature to either vision or natural language processing with respect to the forms of meaningful self-supervised learning tasks that can be defined. Motivated by this insight, we introduce a novel approach called \textit{Series2Vec} for self-supervised representation learning. Unlike other self-supervised methods in time series, which carry the risk of positive sample variants being less similar to the anchor sample than series in the negative set, Series2Vec is trained to predict the similarity between two series in both temporal and spectral domains through a self-supervised task. Series2Vec relies primarily on the consistency of the unsupervised similarity step, rather than the intrinsic quality of the similarity measurement, without the need for hand-crafted data augmentation. To further enforce the network to learn similar representations for similar time series, we propose a novel approach that applies order-invariant attention to each representation within the batch during training. Our evaluation of Series2Vec on nine large real-world datasets, along with the UCR/UEA archive, shows enhanced performance compared to current state-of-the-art self-supervised techniques for time series. Additionally, our extensive experiments show that Series2Vec performs comparably with fully supervised training and offers high efficiency in datasets with limited-labeled data. Finally, we show that the fusion of Series2Vec with other representation learning models leads to enhanced performance for time series classification. Code and models are open-source at \url{https://github.com/Navidfoumani/Series2Vec. }
Spheroidal Molecular Communication via Diffusion: Signaling Between Homogeneous Cell Aggregates

Recent molecular communication (MC) research has integrated more detailed computational models to capture the dynamics of practical biophysical systems. This paper focuses on developing realistic models for MC transceivers inspired by spheroids – three-dimensional cell aggregates commonly used in organ-on-chip experimental systems. Potential applications that can be used or modeled with spheroids include nutrient transport in organ-on-chip systems, the release of biomarkers or reception of drug molecules by cancerous tumor sites, or transceiver nanomachines participating in information exchange. In this paper, a simple diffusive MC system is considered where a spheroidal transmitter and spheroidal receiver are in an unbounded fluid environment. These spheroidal antennas are modeled as porous media for diffusive signaling molecules, then their boundary conditions and effective diffusion coefficients are characterized. Furthermore, for either a point source or spheroidal transmitter, the Green’s function for concentration (GFC) outside and inside the receiving spheroid is analytically derived and formulated in terms of an infinite series and confirmed with a particle-based simulator (PBS). The provided GFCs enable computation of the transmitted and received signals in the proposed spheroidal communication system. This study shows that the porous structure of the receiving spheroid amplifies diffusion signals but also disperses them, thus there is a trade-off between porosity and information transmission rate. Furthermore, the results reveal that the porous arrangement of the transmitting spheroid not only disperses the received signal but also attenuates it in comparison to a point source transmitter. System performance is also evaluated in terms of the bit error rate (BER). Decreasing the porosity of the receiving spheroid is shown to enhance the system performance. Conversely, reducing the porosity of the transmitting spheroid can adversely affect system performance.
Model-Based Epistemic Variance of Values for Risk-Aware Policy Optimization

We consider the problem of quantifying uncertainty over expected cumulative rewards in model-based reinforcement learning. In particular, we focus on characterizing the variance over values induced by a distribution over MDPs. Previous work upper bounds the posterior variance over values by solving a so-called uncertainty Bellman equation (UBE), but the over-approximation may result in inefficient exploration. We propose a new UBE whose solution converges to the true posterior variance over values and leads to lower regret in tabular exploration problems. We identify challenges to apply the UBE theory beyond tabular problems and propose a suitable approximation. Based on this approximation, we introduce a general-purpose policy optimization algorithm, Q-Uncertainty Soft Actor-Critic (QU-SAC), that can be applied for either risk-seeking or risk-averse policy optimization with minimal changes. Experiments in both online and offline RL demonstrate improved performance compared to other uncertainty estimation methods.
CLadder: Assessing Causal Reasoning in Language Models

The ability to perform causal reasoning is widely considered a core feature of intelligence. In this work, we investigate whether large language models (LLMs) can coherently reason about causality. Much of the existing work in natural language processing (NLP) focuses on evaluating commonsense causal reasoning in LLMs, thus failing to assess whether a model can perform causal inference in accordance with a set of well-defined formal rules. To address this, we propose a new NLP task, causal inference in natural language, inspired by the"causal inference engine"postulated by Judea Pearl et al. We compose a large dataset, CLadder, with 10K samples: based on a collection of causal graphs and queries (associational, interventional, and counterfactual), we obtain symbolic questions and ground-truth answers, through an oracle causal inference engine. These are then translated into natural language. We evaluate multiple LLMs on our dataset, and we introduce and evaluate a bespoke chain-of-thought prompting strategy, CausalCoT. We show that our task is highly challenging for LLMs, and we conduct an in-depth analysis to gain deeper insights into the causal reasoning abilities of LLMs. Our data is open-sourced at https://huggingface.co/datasets/causalNLP/cladder, and our code can be found at https://github.com/causalNLP/cladder.
Regional Climate Modeling of Vegetation Feedbacks on the Asian-Australian Monsoon Systems

AbstractThis study explores the hypothesis that subtropical and tropical monsoon regions exhibit unique responses to vegetation feedbacks. Using the Community Climate System Model (CCSM), M. Notaro et al. concluded that reduced vegetation cover led to an earlier subtropical Chinese monsoon and a delayed, weaker tropical Australian monsoon, yet significant climate and leaf area index (LAI) biases obfuscated the hypothesis’s reliability. To address these concerns, the Regional Climate Model, version 4 (RegCM4), likewise coupled to the Community Land Model but with “observed” LAI boundary conditions, is applied across China and Australia. The model matches the observed dominance of crops, grass, and evergreen trees in southern China and grass and shrubs in northern Australia. The optimal model configuration is determined and applied in control runs for 1960–2013. Monsoon region LAI is modified in a RegCM4 ensemble, aimed at contrasting vegetation feedbacks between tropical and subtropical regions. Greater LA.
The Emergence of Social Work Practice Research in the Peoples’ Republic of China

Objective: In China where social work is a fledgling profession, practice research is still a novelty. This article aims to provide an overview of the development of social work practice research in mainland China. Methods: This review analyzes the content of 206 Chinese journal articles published in the Peoples’ Republic of China since 1915 using the China National Knowledge Infrastructure database, with a focus on the question “who published what? ” Results: The first social work practice research was published in 1999 and it has been increasing in recent years in China. They are predominantly conducted by academics and the collaboration between academics and practitioners is rare and can be further promoted. Conclusions: Practice research could be stepped up to build a distinctive professional knowledge base for social work in China considering its unique geographical, cultural, socioeconomic, and political contexts.
ScholarWorks ScholarWorks

Research Summary: Several upper echelons studies have found that firms led by female executives are less likely to engage in risky endeavors than those led by male top executives. We argue that conceptualizing female CEOs as universally conservative decision-makers may paint too simplistic a picture and that the impact of CEO gender on strategic decision-making may vary significantly depending on the given situation CEOs are experiencing. We integrate executive job demands and gender research to propose that scrutiny will exhibit differential effects on female and male CEOs' acquisition activity. We show that in high-scrutiny contexts, the difference between male and female CEO acquisition activity disappears. In contrast, in low-scrutiny contexts, the difference between male and female CEOs' acquisition activity is exaggerated. Managerial Summary: Substantial research has shown that female executives acquire at a lower rate than male executives. We argue that viewing female CEOs as universally conservative decision-makers may paint too simplistic a picture and that the impact of CEO gender on strategic decision-making may vary
Smirnov words and the Delta Conjectures

We provide a combinatorial interpretation of the symmetric function $\left. \Theta_{e_k}\Theta_{e_l}\nabla e_{n-k-l}\right|_{t=0}$ in terms of segmented Smirnov words. The motivation for this work is the study of a diagonal coinvariant ring with one set of commuting and two sets of anti-commuting variables, whose Frobenius characteristic is conjectured to be the symmetric function in question. Furthermore, this function is related to the Delta conjectures. Our work is a step towards a unified formulation of the two versions, as we prove a unified Delta theorem at $t=0$.
Contribution à l'étude de l'écologie de la faune vagile profonde de la Méditerranée nord-occidentale. II: Les cumacés (Crustacea)

On traite des cumaces collectes dans des fonds etages approximativement de 60 a 380 m; 32 especes inventoriees. Plusieurs especes nouvelles pour cette mer. Mesolamprops denticulata est nouveau pour la science; 12 des especes n'ont ete trouvees que dans l'etage bathyal qui semble correspondre a la limite superieure de leur extension verticale
Valuations of Elemental Concentrations of Particle Matter in Ulaanbaatar, Mongolia

This study focused on the contents of the air particulate matter pollution in two districts of Ulaanbaatar and determined the chemical composition of air borne samples and the source of those particles. Samples of fine and coarse fractions of PM were collected using a “Gent” stacked filter unit in two fractions of 0 - 2.2 μm and 2.2 - 10 μm sizes in two semi-residential areas from September 2012 to August 2013. This paper points out that fine and coarse concentration varied seasonally with meteorological changes. In sampling site 3, Zuun Ail (Figure 1) combustion generators generate the majority of pollution around 50.6% of household waste furnace to create high-temperature combustion of 21.6%. However, this net contributes to soil contamination near the lower value (5%) that arises around the vacuum environment in substantial amounts (14%), where is open around the buildings and residential areas, and the soil is considered to be due to the construction. But the data point to the highway in the distance, where is 9% of contamination of all vehicles’ smoke, and exhaust is similar to the data collected in Ulaanbaatar. According to analysis of samples of Nuclear Research Center (NRC) sampling site 2, it shows burning source of Particulate Matter 2.5 pollution in the air is around 25.5% of household waste furnace to create high-temperature product of combustion. But here the very high net contribution to the pollution of soil, is 31.6%. Today’s emerging dust is around 15.2%, showing that motor vehicle pollution causes 19.7%. Since the analysis was done on a sample-by-sample basis, it is possible to estimate the daily contributions of pollution sources and provide useful information based on a limited number of samples in order to address air quality management issues in Ulaanbaatar.
The Qualitative Report The Qualitative Report

Abstract Parents’ involvement patterns serve as a catalyst to their children’s moral development (Bandura, 1991). Yet, sport culture may convolute parents’ authentic ability to socialize their children’s moral development within a compliant structure focused on performance excellence (Hughes & Coakley, 1991). The purpose of the current study was to examine how parents conceptualize morality while entrenched in a conformity-driven elite youth ice hockey environment. The following research question was explored: how do parents ascribe meaning to, and learn the behavioral representations of, moral and immoral behaviors in youth ice hockey? Parents’ (N = 8, M age = 53.13) perspectives of morality and immorality were explored within the culture of elite youth hockey through individual semi-structured interviews. A transcendental phenomenological approach was implemented to identify both textural and structural experiences parents used to derive their perceptions of morality and immorality in youth ice hockey (Creswell & Poth, 2018). Results exemplify how normative standards socialized through various dimensions of hockey culture obscured parents’ perceptions of morality and immorality through “relatively conscious” acceptance of socialized norms. Findings highlight the socialization processes that parents use to develop their conceptions of morality by overconforming to the normative standards valorized through the youth hockey sport ethic (Hughes & Coakley, 1991). The “relative consciousness” findings reflected how parents transformed their moral conceptions paralleled with youth hockey culture’s delineation of moral norms and values (Burry & Fiset, 2022; Hughes & Coakley, 1991).
UvA-DARE (Digital Academic Repository) Efficient probabilistic estimation of quasi-identifier uniqueness

This paper proposes a method to quantify anonymity. Anonymity can be quantiﬁed as the probability that each member of a group can be uniquely identiﬁed using a quasi-identiﬁer : a combination of variables which combined can be used to identify an individual within a group. Estimating this uniqueness probability is straightforward when all possible values of a quasi-identiﬁer are equally likely — i.e., when the underlying variable distribution is homogenous. In this paper, we present an approach to estimate anonymity for the more realistic case where the variables composing a quasi-identiﬁer follow a non-uniform distribution. We present an eﬃcient and accurate approximation of the uniqueness probability using a measure of heterogeneity called the Kullback-Leibler distance and the group size. The approach is thoroughly validated by comparing the approximation with re-sults from a simulation using real demographic information from the Netherlands.
Toward the Integration of Personality Theory and Decision Theory in the Explanation of Economic and Health Behavior

Trait-based personality psychology and economics have taken different approaches to understanding individual differences, with the former emphasizing variables derived from the factor analysis of trait assessments, and the latter emphasizing variables derived from formal decision theory. In a data set on trainee truckers in a large US company, we provide a systematic initial assessment of the empirical pattern of relationships between the elements from these two approaches by comparing the predictive power of measurements derived from personality theory and decision theory for several individual characteristics and outcomes, and relating the two sets of measurements to each other. We show that personality traits have a comparable or stronger predictive power than do economic preferences for several dependent variables, including credit score, job persistence, and heavy truck accidents. They also have strong predictive power for Body Mass Index (BMI) and smoking status. Further, decision theory and personality variables are meaningfully related. For example, we confirm that cognitive ability explains a substantial part of time preferences, and find that Neuroticism and cognitive ability together explain attitudes toward risk. In addition, Agreeableness and cognitive ability explain aspects of other-regarding behavior in a strategic setting.