Miracle-dz/UniFAR-FTUs huggingface dataset:
Diversity effects in subjective probability judgment

Abstract Previous research has shown that the judged probability of an event depends on whether its description mentions examples (“What is the probability that a randomly chosen Italian businessman will travel during the next month to Warsaw, Budapest, Prague or some other European city? ”) or does not mention examples (“What is the probability that a randomly chosen Italian businessman will travel during the next month to a European city? ”). Here, we examined descriptions that mention examples and manipulated whether these are relatively similar (e.g., Warsaw, Budapest, Prague) or diverse (e.g., Warsaw, Marseilles, Helsinki). Four experiments (N = 1112) revealed a diversity effect: Overall, descriptions with diverse examples received higher probability judgments than descriptions with similar examples. We discuss several possible mechanisms for this effect, such as that descriptions with diverse examples prompt fuller representations of the target category or that the effect is driven by a representativeness or proximity heuristic.
Minimizing a Low-Dimensional Convex Function Over a High-Dimensional Cube

For a matrix $W \in \mathbb{Z}^{m \times n}$, $m \leq n$, and a convex function $g: \mathbb{R}^m \rightarrow \mathbb{R}$, we are interested in minimizing $f(x) = g(Wx)$ over the set $\{0,1\}^n$. We will study separable convex functions and sharp convex functions $g$. Moreover, the matrix $W$ is unknown to us. Only the number of rows $m \leq n$ and $\|W\|_{\infty}$ is revealed. The composite function $f(x)$ is presented by a zeroth and first order oracle only. Our main result is a proximity theorem that ensures that an integral minimum and a continuous minimum for separable convex and sharp convex functions are always"close"by. This will be a key ingredient to develop an algorithm for detecting an integer minimum that achieves a running time of roughly $(m \| W \|_{\infty})^{\mathcal{O}(m^3)} \cdot \text{poly}(n)$. In the special case when $(i)$ $W$ is given explicitly and $(ii)$ $g$ is separable convex one can also adapt an algorithm of Hochbaum and Shanthikumar. The running time of this adapted algorithm matches with the running time of our general algorithm.
Cryptic Genes for Interbacterial Antagonism Distinguish Rickettsia Species Infecting Blacklegged Ticks From Other Rickettsia Pathogens

Background The genus Rickettsia (Alphaproteobacteria: Rickettsiales) encompasses numerous obligate intracellular species with predominantly ciliate and arthropod hosts. Notable species are pathogens transmitted to mammals by blood-feeding arthropods. Mammalian pathogenicity evolved from basal, non-pathogenic host-associations; however, some non-pathogens are closely related to pathogens. One such species, Rickettsia buchneri, is prevalent in the blacklegged tick, Ixodes scapularis. While I. scapularis transmits several pathogens to humans, it does not transmit Rickettsia pathogens. We hypothesize that R. buchneri established a mutualism with I. scapularis, blocking tick superinfection with Rickettsia pathogens. Methods To improve estimates for assessing R. buchneri infection frequency in blacklegged tick populations, we used comparative genomics to identify an R. buchneri gene (REIS_1424) not present in other Rickettsia species present throughout the I. scapularis geographic range. Bioinformatic and phylogenomics approaches were employed to propose a function for the hypothetical protein (263 aa) encoded by REIS_1424. Results REIS_1424 has few analogs in other Rickettsiales genomes and greatest similarity to non-Proteobacteria proteins. This cohort of proteins varies greatly in size and domain composition, possessing characteristics of Recombination hotspot (Rhs) and contact dependent growth inhibition (CDI) toxins, with similarity limited to proximal C-termini (~145 aa). This domain was named CDI-like/Rhs-like C-terminal toxin (CRCT). As such proteins are often found as toxin-antidote (TA) modules, we interrogated REIS_1423 (151 aa) as a putative antidote. Indeed, REIS_1423 is similar to proteins encoded upstream of CRCT domain-containing proteins. Accordingly, we named these proteins CDI-like/Rhs-like C-terminal toxin antidotes (CRCA). R. buchneri expressed both REIS_1423 and REIS_1424 in tick cell culture, and PCR assays showed specificity for R. buchneri over other rickettsiae and utility for positive detection in three tick populations. Finally, phylogenomics analyses uncovered divergent CRCT/CRCA modules in varying states of conservation; however, only R. buchneri and related Tamurae/Ixodes Group rickettsiae carry complete TA modules. Conclusion We hypothesize that Rickettsia CRCT/CRCA modules circulate in the Rickettsia mobile gene pool, arming rickettsiae for battle over arthropod colonization. While its functional significance remains to be tested, R. buchneri CRCT/CRCA serves as a marker to positively identify infection and begin deciphering the role this endosymbiont plays in the biology of the blacklegged tick.
Conceptual Model for Adoption Cloud-Based ERP in SMEs: Case Study Iraq

Cloud based Enterprise Resource Planning (ERP) frameworks showed up the responses to every one of the issues looked customary ERP framework. Versatility, adaptability, and cost proficiency. Fast sending and low forthright ventures are its highlights. Cloud based ERP goes about as a substitute to on-premises ERP frameworks. The execution of cloud-based ERP framework is looked with numerous impediments. The usage of ERP framework is exceptionally perplexing, dreary, and tedious and a gigantic need of progress is produced in ERP structure to improve ERP frameworks foundation and usefulness. The built up nations' SMEs have officially executed cloud-based ERP. Be that as it may, then again, the cloud-based ERP usage is extremely constrained and relatively few examinations have been done dependent on it. This present paper's motivation is to explore the issues that impact the cloud-based ERP reception in Iraq SMEs. Also, different elements will be inspected by us that influence the cloud-based ERP appropriation in various SMEs in Iraq by consolidating Technology-Organization-Environment (TOE) system and Diffusion of Innovation hypothesis. Proposals of future work research will likewise be given .
The Role of Entrepreneur Characteristics and Entrepreneur Motivation has a significant effect on SMEs' Business Performance During Digital Era

The purpose of this study was to analyze the relationship between Entrepreneur Characteristics and Business Performance variables, the relationship between entrepreneurial motivation variables and MSME business performance. In this study using quantitative methods. This is because the research data is in the form of numbers and analysis uses statistics, in collecting data using research instruments, data analysis is quantitative, with the aim of testing the established hypothesis, is experimental/survey, if the problem is clear. This type of research uses associative research. serves to explain, predict and control a symptom. This method is used to answer the formulation of the problem, namely knowing the effect of entrepreneurial characteristics and motivation on SMEs business performance. In this study, researchers used a questionnaire data collection technique (questionnaire). Questionnaire is a data collection technique which is done by giving a set of questions or written statements to respondents to answer. The statement questionnaire in this study was measured using a Likert 5 scale. The data analysis of this study used the smartPLS 4.0 software (Purwanto et al., 2020) and the data was obtained through the distribution of online questionnaires with social media to 300 respondents who were selected using a simple random sampling method. Based on the results of data processing and analysis that has been done, the conclusions of this study are: 1. Entrepreneurial Characteristics Affect Business Performance. In this case the characteristics of entrepreneurs are very good. Entrepreneurial characteristics can be seen from the spirit of work and hard work to realize desires. 2. Entrepreneur motivation influences business performance. In this case the motivation of entrepreneurs is very high. Entrepreneur motivation can be seen from being an entrepreneur because he has a desire to be rich. The business performance variable is also very high. This is evident from my business has the ability to compete.
General Cutting Planes for Bound-Propagation-Based Neural Network Verification

Bound propagation methods, when combined with branch and bound, are among the most effective methods to formally verify properties of deep neural networks such as correctness, robustness, and safety. However, existing works cannot handle the general form of cutting plane constraints widely accepted in traditional solvers, which are crucial for strengthening verifiers with tightened convex relaxations. In this paper, we generalize the bound propagation procedure to allow the addition of arbitrary cutting plane constraints, including those involving relaxed integer variables that do not appear in existing bound propagation formulations. Our generalized bound propagation method, GCP-CROWN, opens up the opportunity to apply general cutting plane methods for neural network verification while benefiting from the efficiency and GPU acceleration of bound propagation methods. As a case study, we investigate the use of cutting planes generated by off-the-shelf mixed integer programming (MIP) solver. We find that MIP solvers can generate high-quality cutting planes for strengthening bound-propagation-based verifiers using our new formulation. Since the branching-focused bound propagation procedure and the cutting-plane-focused MIP solver can run in parallel utilizing different types of hardware (GPUs and CPUs), their combination can quickly explore a large number of branches with strong cutting planes, leading to strong verification performance. Experiments demonstrate that our method is the first verifier that can completely solve the oval20 benchmark and verify twice as many instances on the oval21 benchmark compared to the best tool in VNN-COMP 2021, and also noticeably outperforms state-of-the-art verifiers on a wide range of benchmarks. GCP-CROWN is part of the $\alpha,\! \beta$-CROWN verifier, the VNN-COMP 2022 winner. Code is available at http://PaperCode.cc/GCP-CROWN
Mass ratio from Doppler beaming and Rømer delay versus ellipsoidal modulation in the Kepler data of KOI-74

We present a light curve analysis and radial velocity study of KOI-74, an eclipsing A star\(+\) white dwarf binary with a 5.2 day orbit. Aside from new spectroscopy covering the orbit of the system, we used 212 days of publicly available Kepler observations and present the first complete light curve fitting to these data, modelling the eclipses and transits, ellipsoidal modulation, reflection, and Doppler beaming. Markov Chain Monte Carlo simulations are used to determine the system parameters and uncertainty estimates. Our results are in agreement with earlier studies, except that we find an inclination of \(87.0\pm 0.4^\circ \), which is significantly lower than the previously published value. The altered inclination leads to different values for the relative radii of the two stars and therefore also the mass ratio deduced from the ellipsoidal modulations seen in this system. We find that the mass ratio derived from the radial velocity amplitude (\(q=0.104\pm 0.004\)) disagrees with that derived from the ellipsoidal modulation (\(q=0.052\pm 0.004\) assuming corotation). This mismatch was found before, but with our smaller inclination, the discrepancy is even larger than previously reported. Accounting for the rapid rotation of the A-star, instead of assuming corotation with the binary orbit, is found to increase the discrepancy even further by lowering the mass ratio to \(q=0.047\pm 0.004\). These results indicate that one has to be extremely careful in using the amplitude of an ellipsoidal modulation signal in a close binary to determine the mass ratio, when a proof of corotation is not firmly established. The same problem could arise whenever an ellipsoidal modulation amplitude is used to derive the mass of a planet orbiting a host star that is not in corotation with the planet’s orbit. The radial velocities that can be inferred from the detected Doppler beaming in the light curve are found to be in agreement with our spectroscopic radial velocity determination. We also report the first measurement of Romer delay in a light curve of a compact binary. This delay amounts to \(-56\pm 17\) s and is consistent with the mass ratio derived from the radial velocity amplitude. The firm establishment of this mass ratio at \(q=0.104\pm 0.004\) leaves little doubt that the companion of KOI-74 is a low mass white dwarf.
MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization

Training graph neural networks (GNNs) on large graphs is complex and extremely time consuming. This is attributed to overheads caused by sparse matrix multiplication, which are sidestepped when training multi-layer perceptrons (MLPs) with only node features. MLPs, by ignoring graph context, are simple and faster for graph data, however they usually sacrifice prediction accuracy, limiting their applications for graph data. We observe that for most message passing-based GNNs, we can trivially derive an analog MLP (we call this a PeerMLP) with an equivalent weight space, by setting the trainable parameters with the same shapes, making us curious about \textbf{\emph{how do GNNs using weights from a fully trained PeerMLP perform? }} Surprisingly, we find that GNNs initialized with such weights significantly outperform their PeerMLPs, motivating us to use PeerMLP training as a precursor, initialization step to GNN training. To this end, we propose an embarrassingly simple, yet hugely effective initialization method for GNN training acceleration, called MLPInit. Our extensive experiments on multiple large-scale graph datasets with diverse GNN architectures validate that MLPInit can accelerate the training of GNNs (up to 33X speedup on OGB-Products) and often improve prediction performance (e.g., up to $7.97\%$ improvement for GraphSAGE across $7$ datasets for node classification, and up to $17.81\%$ improvement across $4$ datasets for link prediction on metric Hits@10). The code is available at \href{https://github.com/snap-research/MLPInit-for-GNNs}.
Medical Resident Awareness of Predatory Journal Practices in an International Medical Education System

ABSTRACT Introduction Learning research methodology is increasingly becoming an essential part of graduate medical education worldwide, with many regulatory and accreditation bodies requiring residents to participate in scholarship. Research methodology workshops have become a standard part of medical curricula; however, there is limited data on how much training on journal selection and the publication process trainees receive. The alarming growth of predatory journals has made it increasingly difficult for researchers, especially trainees and early career physicians, to distinguish these publications from reputable journals. The purpose of this study is to assess the knowledge of reputable and predatory publishing practices amongst medical trainees in an international medical education setting in the United Arab Emirates. Methods A survey on credible journal practices based on the ‘Think. Check. Submit’ initiative was sent to all graduate medical education trainees at two large academic medical centers in Abu Dhabi, United Arab Emirates. Descriptive statistics were used to tabulate variable frequencies. Results Over half of the 160 respondents reported receiving prior research methodology training and 42.5% had at least one publication. The majority of the trainees selected impact factor and the quality of the peer-review process as characteristics of reputable journals. Ambiguous editorial board and rapid publication process were recognized as characteristics of predatory journals by >65% of trainees, however, 95% of all trainees were unaware of Beall’s list or other resources to help select a journal for publication. 15.2% of trainees who received unsolicited emails from publishers submitted their manuscripts to the unfamiliar journals, citing peer recommendation and pressure to publish from their training programs as reasons. Conclusion Trainees in the United Arab Emirates were mostly unaware of reputable publication practices and are vulnerable to publishing in predatory journals. Policy and educational reform are necessary to maintain the credibility and integrity of the scientific process.
Enhancing Reliability and Security: A Configurable Poisoning PUF Against Modeling Attacks

Physically unclonable functions (PUFs) have been widely proposed as hardware primitives for device identification and cryptographic key generation. While strong PUFs provide an exponential number of challenge–response pairs (CRPs) for device authentication, most are vulnerable to machine-learning (ML)-based modeling attacks. Regarding the inherent hard learning problem, adversarial-based PUFs pseudo-randomly switch between several predefined internal states to poison the ML algorithms. However, existing adversarial-based PUFs sacrifice reliability or security against ML attacks. Furthermore, most works only evaluated the ML resistance by empirical experiments, which provides limited evidence for ML resistance. This work explored a novel adversarial-based PUF, Configurable Poisoning PUF (CP PUF), that simultaneously maintains reliability and protects the internal state by a reliability trapdoor. We then connect the proposed CP PUF with the learning parity with noise (LPN) problem to provide a theoretical security guarantee. Experiments show that the reliability of our proposed CP PUF keeps at least 88.9% and outperforms the existing adversarial-based PUFs under different levels of noisy environments. Moreover, the proposed CP PUF achieved a 50.16% accuracy under empirical ML attacks, a near-optimal performance.
Thermopower of quantum Hall states in Corbino geometry as a measure of quasiparticle entropy

Using the Onsager relation between electric and heat transport coefficients, and considering the very different roles played by the quantum Hall condensate and quasiparticles in transport, we argue that near the center of a quantum Hall plateau thermopower in a Corbino geometry measures {\it "entropy per quasiparticle per quasiparticle charge"}. This relation indicates that thermopower measurement in a Corbino setup is a more direct measure of quasiparticle entropy than in a Hall bar. Treating disorder within the self-consistent Born approximation, we show through an explicit microscopic calculation that this relation holds on an integer quantum Hall plateau at low temperatures. Applying this to non-Abelian quantum Hall states, we argue that Corbino thermopower at sufficiently low temperature becomes temperature-independent, and measures the quantum dimension of non-Abelian quasiparticles that determines the topological entropy they carry.
How much data do we need? Reliability and data deficiency in global vertebrate biodiversity trends

Global biodiversity is facing a crisis, which must be solved through effective policies and on-the-ground conservation. But governments, NGOs, and scientists need reliable indicators to guide research, conservation actions, and policy decisions. Developing reliable indicators is challenging because the data underlying those tools is incomplete and biased. For example, the Living Planet Index tracks the changing status of global vertebrate biodiversity, but taxonomic, geographic and temporal gaps and biases are present in the aggregated data used to calculate trends. But without a basis for real-world comparison, there is no way to directly assess an indicator’s accuracy or reliability. Instead, a modelling approach can be used. We developed a model of trend reliability, using simulated datasets as stand-ins for the "real world", degraded samples as stand-ins for indicator datasets (e.g. the Living Planet Database), and a distance measure to quantify reliability by comparing sampled to unsampled trends. The model revealed that the proportion of species represented in the database is not always indicative of trend reliability. Important factors are the number and length of time series, as well as their mean growth rates and variance in their growth rates, both within and between time series. We found that many trends in the Living Planet Index need more data to be considered reliable, particularly trends across the global south. In general, bird trends are the most reliable, while reptile and amphibian trends are most in need of additional data. We simulated three different solutions for reducing data deficiency, and found that collating existing data (where available) is the most efficient way to improve trend reliability, and that revisiting previously-studied populations is a quick and efficient way to improve trend reliability until new long-term studies can be completed and made available.