Miracle-dz/UniFAR-FTUs huggingface dataset:
PROLEAD_SW - Probing-Based Software Leakage Detection for ARM Binaries

A decisive contribution to the all-embracing protection of cryptographic software, especially on embedded devices, is the protection against Side-Channel Analysis (SCA) attacks. Masking countermeasures can usually be integrated into the software during the design phase. In theory, this should provide reliable protection against such physical attacks. However, the correct application of masking is a non-trivial task that often causes even experts to make mistakes. In addition to human-caused errors, micro-architectural Central Processing Unit (CPU) effects can lead even a seemingly theoretically correct implementation to fail to satisfy the desired level of security in practice. This originates from different components of< the underlying CPU which complicates the tracing of leakage back to a particular source and hence avoids making general and device-independent statements about its security.PROLEAD has recently been presented at CHES 2022 and has originally been developed as a simulation-based tool to evaluate masked hardware designs. In this work, we adapt PROLEAD for the evaluation of masked software, and enable the transfer of the already known benefits of PROLEAD into the software world. These include (1) evaluation of larger designs compared to the state of the art, e.g. a full Advanced Encryption Standard (AES) masked implementation, and (2) formal verification under our new generic leakage model for CPUs. Concretely, we formalize leakages, observed across different CPU architectures, into a generic abstraction model that includes all these leakages and is therefore independent of a specific CPU design. Our resulting tool PROLEAD_SW allows to provide a formal statement on the security based on the derived generic model. As a concrete result, using PROLEAD_SW we evaluated the security of several publicly available masked software implementations in our new generic leakage model and reveal multiple vulnerabilities.
Sequencing to identify pathogens in Tenebrio molitor: Implications in insects farmed for food and feed

Introduction The farmed insect industry is increasing in number and size to meet the demand for sustainably-produced protein. Larger insect farms are prone to losses due to pathogens, and more information is needed regarding the health of insects reared for food and feed. Methods In this study, high throughput sequencing was used to identify potential pathogens in a colony of Tenebrio molitor (yellow mealworm, Coleoptera: Tenebrionidae) that exhibited increased mortality in immature stages with eventual colony collapse. Sequences also were obtained from a healthy new colony of T. molitor, as well as a recovered individual from the collapsed colony. Results Screening of sequences obtained from the colonies and their rearing diet indicated that the collapsed colony had low diversity in microbial taxa, with predominantly sequences from the families Staphylococcaeceae and Streptococcaceae constituting from 53 to 88% of the total microbial reads. Conversely, in the new colony and their rearing diet, microbial sequences were from more than 15 different taxa, with Lactobacilleceae the most prevalent but representing only 21% of the total microbial reads. Evidence indicates that Bacillus thuringiensis may have been involved in the collapse of the colony, leading to sepsis and microbial dysbiosis, although the source of the bacteria was not identified. Sequences from the recovered individual reflected a microbial flora profile that was intermediate between those of the diseased collapsed and new colonies. Discussion These findings have implications for insects reared in confined environments and provide a rapid method to screen insect colonies by sequencing healthy and potentially diseased individuals.
Grounding human-object interaction to affordance behavior in multimodal datasets

While affordance detection and Human-Object interaction (HOI) detection tasks are related, the theoretical foundation of affordances makes it clear that the two are distinct. In particular, researchers in affordances make distinctions between J. J. Gibson's traditional definition of an affordance, “the action possibilities” of the object within the environment, and the definition of a telic affordance, or one defined by conventionalized purpose or use. We augment the HICO-DET dataset with annotations for Gibsonian and telic affordances and a subset of the dataset with annotations for the orientation of the humans and objects involved. We then train an adapted Human-Object Interaction (HOI) model and evaluate a pre-trained viewpoint estimation system on this augmented dataset. Our model, AffordanceUPT, is based on a two-stage adaptation of the Unary-Pairwise Transformer (UPT), which we modularize to make affordance detection independent of object detection. Our approach exhibits generalization to new objects and actions, can effectively make the Gibsonian/telic distinction, and shows that this distinction is correlated with features in the data that are not captured by the HOI annotations of the HICO-DET dataset.
Correlation of microbiomes in “plant-insect-soil” ecosystem

Introduction Traditional chemical control methods pose a damaging effect on farmland ecology, and their long-term use has led to the development of pest resistance. Methods Here, we analyzed the correlations and differences in the microbiome present in the plant and soil of sugarcane cultivars exhibiting different insect resistance to investigate the role played by microbiome in crop insect resistance. We evaluated the microbiome of stems, topsoil, rhizosphere soil, and striped borers obtained from infested stems, as well as soil chemical parameters. Results and Discussion Results showed that microbiome diversity was higher in stems of insect-resistant plants, and contrast, lower in the soil of resistant plants, with fungi being more pronounced than bacteria. The microbiome in plant stems was almost entirely derived from the soil. The microbiome of insect-susceptible plants and surrounding soil tended to change towards that of insect-resistant plants after insect damage. Insects’ microbiome was mainly derived from plant stems and partly from the soil. Available potassium showed an extremely significant correlation with soil microbiome. This study validated the role played by the microbiome ecology of plant–soil-insect system in insect resistance and provided a pre-theoretical basis for crop resistance control.
Evaluation of the role of clathrin and bacterial viability in the endocytosis of Lawsonia intracellularis

Lawsonia intracellularis is an obligate intracellular bacterium and causative agent of proliferative enteropathy. The pathogenesis of L. intracellularis is not completely understood, including the endocytic mechanisms to access the host cell cytoplasm. In this study, we evaluated the mechanisms involved in endocytosis of L. intracellularis in vitro using intestinal porcine epithelial cells (IPEC-J2). Confocal microscopy was used to co-localize L. intracellularis and clathrin. Clathrin gene knockdown was then applied to verify whether L. intracellularis endocytosis is clathrin-dependent. Finally, internalization of viable and non-viable (bacteria were inactivated by heat) L. intracellularis organisms were assessed to study the role of the host cell during bacterial endocytosis. L. intracellularis organisms were observed co-localized with clathrin by confocal microscopy but the amount of L. intracellularis internalized in cells, with and without clathrin knockdown, did not differ statistically. The internalization of non-viable L. intracellularis showed a decrease in the internalization in cells with less clathrin synthesis (P<0.05). The present study is the first to elucidate the involvement of clathrin in the endocytosis of L. intracellularis. Clathrin-mediated endocytosis was shown to be an important, but not required, process for L. intracellularis internalization in porcine intestinal epithelial cells. Independence of bacterial viability for host cell internalization was also confirmed.
High-fiber diet ameliorates gut microbiota, serum metabolism and emotional mood in type 2 diabetes patients

Previous studies have demonstrated that patients with type 2 diabetes mellitus (T2DM) often had the problems of fecal microbiota dysbiosis, and were usually accompanied with psychiatric comorbidities (such as depression and anxiety). Here, we conducted a randomized clinical study to analyze the changes in gut microbiota, serum metabolism and emotional mood of patients with T2DM after consumption of a high-fiber diet. The glucose homeostasis of participants with T2DM was improved by the high-fiber diet, and the serum metabolome, systemic inflammation and psychiatric comorbidities were also altered. The increased abundances of Lactobacillus, Bifidobacterium and Akkermansias revealed that the proportions of beneficial gut microbes were enriched by the high-fiber diet, while the abundances of Desulfovibrio, Klebsiella and other opportunistic pathogens were decreased. Therefore, the current study demonstrated that the intestinal microbiota alterations which were influenced by the high-fiber diet could improve the serum metabolism and emotional mood of patients with T2DM.
Transcriptomics analysis of ethanol treatment of male Aedes aegypti reveals a small set of putative radioprotective genes

Introduction: Sterile Insect Technique (SIT) is based on releasing sterilized male insects into wild insect populations to compete for mating with wild females. Wild females mated with sterile males will produce inviable eggs, leading to a decline in population of that insect species. Sterilization with ionizing radiation (x-rays) is a commonly used mechanism for sterilization of males. Since irradiation can cause damage to both, somatic and germ cells, and can severely reduce the competitiveness of sterilized males relative to wild males, means to minimize the detrimental effects of radiation are required to produce sterile, competitive males for release. In an earlier study, we identified ethanol as a functional radioprotector in mosquitoes. Methods: Here, we used Illumina RNA-seq to profile changes in gene expression of male Aedes aegypti mosquitoes fed on 5% ethanol for 48 hours prior to receiving a sterilizing x-ray dose, compared to males fed on water prior to sterilization. Results: RNA-seq revealed a robust activation of DNA repair genes in both ethanol-fed and water-fed males after irradiation, but surprisingly few differences in gene expression between ethanol-fed and water-fed males regardless of radiation treatment. Discussion: While differences in gene expression due to ethanol exposure were minimal, we identified a small group of genes that may prime ethanol-fed mosquitoes for improved survivability in response to sterilizing radiation.
The evolution of personality disorders: A review of proposals

Personality disorders (PDs) are currently considered dysfunctions. However, personality differences are older than humanity and are ubiquitous in nature, from insects to higher primates. This suggests that a number of evolutionary mechanisms—other than dysfunctions—may be able to maintain stable behavioral variation in the gene pool. First of all, apparently maladaptive traits may actually improve fitness by enabling better survival or successful mating or reproduction, as exemplified by neuroticism, psychopathy, and narcissism. Furthermore, some PDs may harm important biological goals while facilitating others, or may be globally beneficial or detrimental depending on environmental circumstances or body condition. Alternatively, certain traits may form part of life history strategies: Coordinated suites of morphological, physiological and behavioral characters that optimize fitness through alternative routes and respond to selection as a whole. Still others may be vestigial adaptations that are no longer beneficial in present times. Finally, variation may be adaptative in and by itself, as it reduces competition for finite resources. These and other evolutionary mechanisms are reviewed and illustrated through human and non-human examples. Evolutionary theory is the best-substantiated explanatory framework across the life sciences, and may shed light on the question of why harmful personalities exist at all.
Exploring the challenges of virtual internships during the COVID-19 pandemic and their potential influence on the professional identity of health professions students: A view from Qatar University

Introduction COVID-19 has imposed many shared limitations on medical and health education. Just like other health professions programs at most institutions, the Qatar University health cluster (QU Health) applied a containment approach and shifted all learning online, and onsite training was replaced by virtual internships (VIs) during the first wave of the pandemic. Our study aims to explore the challenges of virtual internships during the COVID-19 pandemic and their influence on the professional identity (PI) of the health cluster students from the College of Medicine, the College of Health Sciences, and the College of Pharmacy at Qatar University. Methods A qualitative approach was employed. In total, eight focus groups with students (N = 43) and 14 semi-structured interviews with clinical instructors from all the health cluster colleges were conducted. Transcripts were analyzed following the inductive approach. Results The major challenges reported by students were mainly related to the lack of the required skills for navigating the VI, professional and social stressors, the nature of VIs and the quality of learning, technical and environmental issues, and the development of students' professional identity in an alternative internship environment. The challenges relating to the development of professional identity included: limited clinical (practical) experience, a lack of experience in fighting a pandemic, a lack of communication and feedback, and a lack of confidence in meeting the internship's goals. A model was constructed to represent these findings. Discussion The findings are important in identifying the inevitable barriers to virtual learning for health professions students and provide a better understanding of how such challenges and different experiences would be affecting the development of their PI. Hence, students, instructors, and policymakers alike should strive to minimize these barriers. Since physical interactions and patient contact are indispensable components of clinical teaching, these extraordinary times demand innovations involving technology and simulation-based teaching. There is a need for more studies that are focused on determining and measuring the short- and long-term effects of the VI on students' PI development.
Autonomic nervous system and cardiac neuro-signaling pathway modulation in cardiovascular disorders and Alzheimer’s disease

The heart is a functional syncytium controlled by a delicate and sophisticated balance ensured by the tight coordination of its several cell subpopulations. Accordingly, cardiomyocytes together with the surrounding microenvironment participate in the heart tissue homeostasis. In the right atrium, the sinoatrial nodal cells regulate the cardiac impulse propagation through cardiomyocytes, thus ensuring the maintenance of the electric network in the heart tissue. Notably, the central nervous system (CNS) modulates the cardiac rhythm through the two limbs of the autonomic nervous system (ANS): the parasympathetic and sympathetic compartments. The autonomic nervous system exerts non-voluntary effects on different peripheral organs. The main neuromodulator of the Sympathetic Nervous System (SNS) is norepinephrine, while the principal neurotransmitter of the Parasympathetic Nervous System (PNS) is acetylcholine. Through these two main neurohormones, the ANS can gradually regulate cardiac, vascular, visceral, and glandular functions by turning on one of its two branches (adrenergic and/or cholinergic), which exert opposite effects on targeted organs. Besides these neuromodulators, the cardiac nervous system is ruled by specific neuropeptides (neurotrophic factors) that help to preserve innervation homeostasis through the myocardial layers (from epicardium to endocardium). Interestingly, the dysregulation of this neuro-signaling pathway may expose the cardiac tissue to severe disorders of different etiology and nature. Specifically, a maladaptive remodeling of the cardiac nervous system may culminate in a progressive loss of neurotrophins, thus leading to severe myocardial denervation, as observed in different cardiometabolic and neurodegenerative diseases (myocardial infarction, heart failure, Alzheimer’s disease). This review analyzes the current knowledge on the pathophysiological processes involved in cardiac nervous system impairment from the perspectives of both cardiac disorders and a widely diffused and devastating neurodegenerative disorder, Alzheimer’s disease, proposing a relationship between neurodegeneration, loss of neurotrophic factors, and cardiac nervous system impairment. This overview is conducive to a more comprehensive understanding of the process of cardiac neuro-signaling dysfunction, while bringing to light potential therapeutic scenarios to correct or delay the adverse cardiovascular remodeling, thus improving the cardiac prognosis and quality of life in patients with heart or neurodegenerative disorders.
Unconventional Cooper pairing in the superconducting state of UPd2Al3

A possible type of Cooper pairing in an anisotropic superconducting state of ${\mathrm{UPd}}_{2}{\mathrm{Al}}_{3}$ is discussed on the basis of the recent measurement of magnetic exciton modes which are expected to mediate the pairing interaction. The most likely gap is one with ${A}_{\mathrm{g}}$ symmetry with the line node on the plane very close to the zone boundary of the folded Brillouin zone in the antiferromagnetically ordered state.
Fusion of multi-level image features for image-text matching

: The existing mainstream methods use the pre-trained convolutional neural networks to extract image features and usually have the following limitations: a ） Only using a single layer of pre-trained features to represent image; b ） Inconsistency between the pre-trained task and the actual research task. These limitations result in that the existing methods of image-text matching cannot make full use of image features and is easily influenced by the noises. To solve the above limitations, this paper used multi-layer features from a pre-trained network and proposed a fusion algorithm of multi-level image features accordingly. Under the guidance of the image-text matching objective function, the proposed algorithm fused the multi-level pre-trained image features and reduced their dimensionality using a multi-layer perceptron to generate fusion features. It is able to make full use of pre-trained features and successfully reduce the influences of noises. The experimental results show that the proposed fusion algorithm makes better use of pre-trained image features and outperforms the methods using single-level features in the image-text matching task.
Rapidity and energy dependence of thermal parameters

For beam energies from SPS to RHIC, the transverse energy per charged particle, ET/Nch, saturates at a value of approximately 0.8 GeV. A direct connection between this value and the freeze-out criterium E/N ≈ 1 GeV for the primordial energy and particle number in the hadronic resonance gas model is established. The rapidity dependence of the chemical freeze-out thermal parameters T and μB is determined at the highest RHIC and SPS energies. These show a systematic increase in μB away from mid-rapidity and a corresponding decrease in the temperature T.
Analytical approximate solutions of Riesz fractional diffusion equation and Riesz fractional advection–dispersion equation involving nonlocal space fractional derivatives

In this paper, we consider the analytical solutions of fractional partial differential equations (PDEs) with Riesz space fractional derivatives on a finite domain. Here we considered two types of fractional PDEs with Riesz space fractional derivatives such as Riesz fractional diffusion equation (RFDE) and Riesz fractional advection–dispersion equation (RFADE). The RFDE is obtained from the standard diffusion equation by replacing the second‐order space derivative with the Riesz fractional derivative of order α∈(1,2]. The RFADE is obtained from the standard advection–dispersion equation by replacing the first‐order and second‐order space derivatives with the Riesz fractional derivatives of order β∈(0,1] and of order α∈(1,2] respectively. Here the analytic solutions of both the RFDE and RFADE are derived by using modified homotopy analysis method with Fourier transform. Then, we analyze the results by numerical simulations, which demonstrate the simplicity and effectiveness of the present method. Here the space fractional derivatives are defined as Riesz fractional derivatives. Copyright © 2015 John Wiley & Sons, Ltd.
Lossless image coding using adaptive, switching algorithm with automatic fuzzy context modelling

A switching adaptive predictor (SWAP) with automatic fuzzy context modelling is proposed for lossless image coding. Depending on the context of the coding pixel, the SWAP encoder switches between two predictors: the adaptive neural predictor (ANP) and the texture context matching (TCM) predictor. The ANP is known to perform well and gives small prediction errors except for pixels around edges. For areas with edges, TCM is used. To decide which is to be used, a switching criterion is proposed to pick out pixels around edges effectively. With the switching predictor structure, small prediction errors can be achieved in both slowly varying areas and edges. Furthermore, the use of the so-called fuzzy context clustering for prediction error refinement is proposed. The proposed compensation mechanism is proved to be very useful through experiments. It further improves the bit rates by, on average, 0.2 bpp in test images. The experiments also show that an average improvement of 0.3 and 0.05 bpp in first-order entropy can be achieved when the proposed switching predictor is compared with the gradient adjusted predictor and a six-order edge directed predictor, respectively. Moreover, the lossless image coder built upon the proposed algorithm also provides lower bit rates than the state-of-the-art context-based, adaptive, lossless image coding (CALIC) system and is comparable to that obtained by the highly complex two-pass coder called TMW.
A Note on the Normalized Errors in ARCH and Stochastic Volatility Models

It is well-known that conditional heteroskedasticity thickens the tails of the unconditional distribution of an error term relative to its conditional distribution. To what extent do imperfect forecasts of the conditional variance undo this tail thickening? This note considers the effect of changing the quality of the information embodied in a forecast of a conditional variance. Adding noise of a certain form thickens the tails of the normalized errors, but decreasing the amount of information used in the forecast may or may not thicken the tails. We also explore the relation between tail thickness and various notions of “optimal” volatility forecasts. The relationship is surprisingly complicated.
A Search for Environmental Influence on Stellar Mass

The positions and local projected densities of the protostellar continuum sources in Ophiuchus and Serpens are investigated as a function of their masses in order to search for possible environmental effects during star formation. There is a slight trend toward mass segregation for the 850 μm sources found by Johnstone and coworkers in Ophiuchus, but there is no obvious mass segregation for the 1.3 mm sources in Ophiuchus or Serpens. There is also no systematic change in the local projected source density with source mass, as might be expected if clump collisions or gas clearing are involved.