Miracle-dz/UniFAR-FTUs huggingface dataset:
Deletion of an enhancer in FGF5 is associated with ectopic expression in goat hair follicles and the cashmere growth phenotype

Research on cashmere growth has a significant effect on the production of cashmere and a profound influence on cashmere goat breeding. Whole-genome sequencing is a powerful platform to rapidly gain novel insights into the identification of genetic mechanisms underlying cashmere fiber growth. Here, we generated whole-genome sequences of 115 domestic goats from China, Nepal and Pakistan, including 51 cashmere goats and 64 non-cashmere goats. We found genetically distinct clusters according to their geographic locations but genetic admixture or introgression may have occurred between the Chinese and Nepalese goats. We identified that the fibroblast growth factor 5 gene (FGF5) shows a strong signature for positive selection in the cashmere goat. The 505-bp indel variant at the FGF5 gene locus appeared to be strongly associated with cashmere growth. Functional validation showed that the insertion variant may serve as an enhancer for transcription factor binding, resulting in increased transcription of the upstream FGF5 gene in non-cashmere goats. Our study provides useful information for the sustainable utilization and improved conservation of goat genetic resources and demonstrates that the indel mutation in the FGF5 gene could potentially serve as a molecular marker of cashmere growth in cashmere goat breeding. Author summary Cashmere goats have been selected for thousands of years and have become economically significant livestock in China and other central Asian countries. The mechanism of cashmere growth is not well understood because most studies have focused on the investigation of candidate genes. Here, we conducted a comprehensive whole-genome analysis for selection signatures in a total of 115 goats from 15 genetically diverse goat breeds. The results revealed a strong selection signature at the FGF5 gene locus associated with the cashmere growth phenotype. A 505-bp indel was located in the downstream region of FGF5 and significantly separated in the cashmere goats versus non-cashmere goats. Functional effect analysis of the indel revealed that it may act as an enhancer by specifically binding transcription factors to mediate quantitative changes in FGF5 mRNA expression. Our study illustrates how a structural mutation of the FGF5 gene has contributed to the cashmere growth phenotype in domestic goats.
Transport Mechanism of Class-3 P4 ATPase Lipid Flippases

The P4 ATPases are a large family of membrane-embedded enzymes that use ATP hydrolysis to transport large lipid substrates across lipid bilayers. P4 ATPases differ in their cellular membrane location and their substrates. The structures of the endosome- and Golgi-localized class-1 phosphatidylserine flippases—such as the yeast Drs2 and human ATP8A1—have recently been reported, revealing a substrate binding site on the lumenal side and several transport states. However, a substrate binding site on the cytosolic side has not been found, and the transport mechanisms of P4 ATPases in other classes are still unknown. Here we report a systematic structural and functional study on two plasma-membrane localized, class-3 P4 ATPases that have broader substrate specificity, the S. cerevisiae Dnf1–Lem3 and Dnf2–Lem3 complexes. We have captured substrate lipids on both the exoplasmic and cytosolic sides, and we found that these two enzymes have very similar structures, consistent with their high sequence identity and redundant function. Unexpectedly, Lem3 contributes to substrate binding near the cytosolic surface. We found that the conformational transitions through the substrate transport cycle of these two class-3 enzymes match those of the class-1 enzymes, suggesting a conserved lipid-flipping mechanism among all classes of the P4 ATPases. Our study also revealed a helix-turn-helix insertion in the cytosolic P domain that is unique to the class-3 enzymes and plays a crucial role in their function. Therefore, the P4 ATPases may have retained an overall transport mechanism while evolving distinct features for cellular membrane localization, regulatory mechanisms, and transporting different lipid substrates.
Scanning ion conductance microscopy reveals differences in the ionic environments of gram positive and negative bacteria

This paper reports on the use of scanning ion conductance microscopy (SICM) to locally map the ionic properties and charge environment of two live bacterial strains: the gramnegative Escherichia coli and the gram-positive Bacillus subtilis. SICM results find heterogeneities across the bacterial surface, and significant differences among the grampositive and -negative bacteria. The bioelectrical environment of the B. subtilis was found to be considerably more negatively charged compared to E. coli. SICM measurements, fitted to a simplified finite element method (FEM) model, revealed surface charge values of −80 to −140 mC m−2 for the gram-negative E. coli. The gram-positive B. subtilis show a much higher conductivity around the cell wall, and surface charge values between −350 and −450 mC m−2 were found using the same simplified model. SICM was also able to detect regions of high negative charge near B. subtilis, not detected in the topographical SICM response and attributed to extracellular polymeric substance. To further explore how the B. subtilis cell wall structure can influence the SICM current response, a more comprehensive FEM model, accounting for the physical properties of the gram-positive cell wall, was developed. The new model provides a more realistic description of the cell wall and allowed investigation of the relation between its key properties and SICM currents, building foundations to further investigate and improve understanding of the gram-positive cellular microenvironment.
Automatically identifying potential regressions in the layout of responsive web pages

SUMMARY Providing a good user experience on the ever-increasing number and variety of devices being used to browse the web is a dif ﬁ cult, yet critical, task. With responsive web design, front-end web developers design web pages so that they dynamically resize and rearrange content to best ﬁ t the dimensions of a device ’ s screen. However, when making code modi ﬁ cations to a responsive page, developers can easily introduce regressions from the correct layout that have detrimental effects at unpredictable screen sizes. For instance, the source code change that a developer makes to improve the layout at one screen size may obscure a page ’ s content at other sizes. Current approaches to testing are often insuf ﬁ cient because they rely on limited tools and error-prone manual inspections of web pages. As such, many unintended regressions in web page layout often go undetected and ultimately manifest in production websites. To address the challenge of detecting regressions in responsive web pages, this paper presents an automated approach that extracts the responsive layout of two versions of a page and compares them, alerting developers to the differences in layout that they may wish to investigate further. We implemented the approach and empirically evaluated it on 15 real-world responsive web pages. Leveraging code mutations that a tool automatically injected into the pages as a systematic simulation of developer changes, the experiments show that the approach was highly effective. When compared with manual and automated baseline testing techniques, it detected 12.5% and 18.75% more injected changes, respectively. Along with identifying the best parameters for the method that extracts the responsive layout, the experiments show that the approach surpasses the baselines across changes that vary in their impact, but works particularly well for subtle, hard-to-detect mutants, showing the bene ﬁ ts of automatically identifying regressions in web page layout. © 2020 John Wiley & Sons, Ltd.
On What to Learn: Train or Adapt a Deeply Learned Profile?

In recent years, many papers have shown that deep learning can be beneﬁcial for proﬁled side-channel analysis. However, in order to obtain good performances with deep learning, an attacker needs a lot of data for training. The training data should be as similar as possible to the data that will be obtained during the attack, a condition that may not be easily met in real world scenarios. It is thus of interest to analyse diﬀerent scenarios where the attack makes use of “imperfect” training data. The typical situation in side-channel is that the attacker has access to an unlabelled dataset of measurements from the target device (obtained with the key he actually wants to recover) and, depending on the context, he may also take proﬁt of a labelled dataset (say proﬁling data) obtained on the same device (with known or chosen key(s)). In this paper, we extend the attacker models and investigate the situation where an attacker additionally has access to a neural network that has been pre-trained on some other dataset not fully corresponding to the attack one. The attacker can then either directly use the pre-trained network to attack, or if proﬁling data is available, train a new network, or adapt a pre-trained one using transfer learning. We made many experiments to compare the attack metrics obtained in both cases on various setups (diﬀerent probe positions, channels, devices, size of datasets). Our results show that in many cases, a lack of training data can be counterbalanced by additional ”imperfect” data coming from another setup.
The Problem of Entangled Material Properties in SVBRDF Recovery

SVBRDF (spatially varying bidirectional reﬂectance distribution function) recovery is concerned with deriving the material properties of an object from one or more images. This problem is particularly challenging when the images are casual rather than calibrated captures. It makes the problem highly under speciﬁed, since an object can look quite different from different angles and from different light directions. Yet many solutions have been attempted under varying assumptions, and the most promising solutions to date are those which use supervised deep learning techniques. The network is ﬁrst trained with a large number of synthetically created images of surfaces, usually planar, with known values for material properties and then asked to predict the properties for image(s) of a new object. While the results obtained are impressive as shown through renders of the input object using recovered material properties, there is a problem in the accuracy of the recovered properties. Material properties get entangled, speciﬁcally the diffuse and specular reﬂectance behaviors. Such inaccuracies would hinder various down stream applications which use these properties. In this position paper we present this property entanglement problem. First, we demonstrate the problem through various property map outputs obtained by running a state of the deep learning solution. Next we analyse the present solutions, and argue that the main reason for this entanglement is the way the loss function is deﬁned when training the network. Lastly, we propose potential directions that could be pursued to alleviate this problem.
Constructing the Cryptographic Boundaries for Lattice-based Cryptography on Hardware Security Module

: Post-Quantum Cryptography (PQC) is regarded as an eﬀective way to resist attacks with quantum computers. Since National Institute of Standards and Technology (NIST) proposed its PQC standardization project in 2016, many candidates have been submitted and their quantum-resistant capability has been measuring by researchers. Besides this research, this paper evaluates the separation of hash and asymmetric operations in PQC operations. This paper is relatively focused on encryption of large data (e.g. document signing or code signing), instead of small data (e.g. key encryption, authentication). Regardless of the size of the data, it is desirable to be able to use Hardware Security Module (HSM) in the key management of PQC. In addition, it is desirable that the encryption processing API is the same regardless of the size of the data, the presence or absence of HSM, use case, key usage, etc. This document describes that, for a given device (such as HSM) and usecase, the same API may not be available. For a usecase with a small message size, people may input a plain message into the PQC operation, for another use case with a large message size, people may input a hash of plain message into the PQC operation. In theory, this issue can be easily solved by adding a hash function to each of the current PQC candidates and construct an API for that. In that case, the input to the PQC calculation cannot be a plain message, and will always be the hash of message. However, such an approach seems to be outside the scope of the current PQC evaluation, and there is a possibility that diﬃculties in cryptographic boundaries handling, theoretical proof, or patents may occur. If that approach meets such a diﬃculty, then there is a possibility that the API of the encryption processing cannot be uni(cid:12)ed with regard to the size of the data, the presence or absence of HSM, use case, or key usage. We believe this is an undesirable results for PQC user, so we call for the need for integration of API, regardless of any conditions.
The Effect of Cortisol on Recovery from Exhaustive Exercise in Rainbow Trout (Oncorhynchus mykiss): Potential Mechanisms of Action

The effects of cortisol on metabolic recovery from exhaustive exercise in rainbow trout (Oncorhynchus mykiss) and potential mechanisms of action were investigated. When the postexercise rise in cortisol is prevented in fish by blocking either cortisol synthesis with metyrapone or cortisol release with dexamethasone, there is a faster recovery of blood and muscle metabolites and acid-base status in those fish than in control fish. To investigate whether preventing the rise in plasma cortisol is responsible for these effects, two experiments were done. Cortisol infused intofish treated with metyrapone returned the rate of recovery to that of control fish. Treatment with 11-deoxycortisol or deoxycorticosterone, intermediates in the cortisol biosynthetic pathway, the levels of which are possibly increased by metyrapone treatment, did not increase the rate of recovery; indeed, plasma cortisol was elevated and recovery prolonged in fish treated with 11-deoxycortisol. These experiments indicate that preventing the postexercise rise in plasma cortisol is associated with decreasing the time required for metabolic and acid-base recovery. The mechanism of cortisol action is not alteration of net acid excretion at the gills or mediated by some action at the RU486-sensitive cortisol receptor. It is suggested that cortisol may play an adaptive role in recovery from exhaustive exercise by providing lactate as a postexercise aerobic fuel.
RandRunner: Distributed Randomness from Trapdoor VDFs with Strong Uniqueness

—Generating randomness collectively has been a long standing problem in distributed computing. It plays a critical role not only in the design of state-of-the-art BFT and blockchain protocols, but also for a range of applications far beyond this ﬁeld. We present RandRunner, a random beacon protocol with a unique set of guarantees that targets a realistic system model. Our design avoids the necessity of a (Byzantine fault-tolerant) consensus protocol and its accompanying high complexity and communication overhead. We achieve this by introducing a novel extension to veriﬁable delay functions (VDFs) in the RSA setting that does not require a trusted dealer or distributed key generation (DKG) and only relies on well studied cryptographic assumptions. This design allows RandRunner to tolerate adversarial or failed leaders while guaranteeing safety and liveness of the protocol despite possible periods of asynchrony.
Coping Strategies and Anxiety and Depressive Symptoms in Young Adult Victims of Cyberstalking: A Questionnaire Survey in an Italian Sample

Aims: In the last decade, the use of smartphones, computers and devices has progressively increased, and prolonged use of technology and the internet has generated new arenas (and tools) for victimization. The first aim of this study was to analyze the use of coping strategies in young adult self-declared victims of cyberstalking. The coping strategies were categorized as proactive behavior, avoidance tactics and passivity. To better understand these strategies, they were analyzed in light of the experience of victimization in terms of incurred misconduct. The second aim was to analyze the coping strategies and the consequences (in terms of depression and anxiety) that occurred in victims; a comparison was made between males and females. Methods: A self-administered questionnaire was distributed to over 433 young adults living in Italy. The questionnaires were filled out by 398 (92%) subjects, 41% males and 59% females. Their ages ranged from 18 to 30 years (M = 23.5, SD = 2.76). Respondents took part on a voluntary basis and did not receive any compensation (or extra credit) for their participation. Results: Findings from this investigation confirmed that among victims, females were more prone than males to experience cyberstalking (respectively, 65% and 35%), with females experiencing a higher percentage of more than one form of cyberstalking behavior than males. Young adult male victims used the internet principally for online gaming, and for this activity, they experienced more cyberstalking behavior than females. In most cases, the perpetrator was a male, and the victim–cyberstalker relationship was a friendship or an acquaintance. For the coping strategies adopted, the findings indicated that the victims were more prone to use avoidance tactics than proactivity behavior and passivity strategies. Young adults involved in this investigation mainly used avoidance tactics to cope with the stressful situation, which implies that they preferred to decrease the use of the internet or stop online contact than collect evidence and try to contact and reason with the cyberstalker or increase the misuse of alcohol of psychotropic substances. Moreover, females were less prone to use proactive behavior than expected. Our findings suggested that males were more prone than females to adopt passivity strategies, while females were more prone to adopt avoidance tactics. Moreover, the data showed that proactivity behavior was adopted more in the case of online contacts and online identity fraud, while passivity strategies were adopted in the case of online threats. Conclusion: Findings from this investigation show the importance of improving the knowledge about the coping strategies that could be suggested to victims and the impact on their psychological health.
High-performance work systems and open innovation: moderating role of IT capability

This study aims to explore the impact of high-performance work systems (HPWS) on open innovation and the moderating role of information technology (IT) capability on the relationship between HPWS and open innovation. ,This study conducted a questionnaire survey in the industrial parks of the Yangzi River Delta in China and obtained 108 useful responses. ,HPWS positively impacts open innovation. IT exploration capability strengthens the relationship between HPWS and open innovation, whereas IT exploitation capability and ambidexterity do not strengthen such relationship. ,Firms should use HPWS to improve employees' motivation of external learning and searching for enhancing innovation openness. They should acknowledge the enabling role of IT exploration capability in facilitating employees' learning and searching toward open innovation and discreetly develop IT exploitation capability and ambidexterity during external knowledge searching, which may not achieve the desired facilitation purpose. ,This study contributes to human resource management (HRM) by suggesting that a new antecedent, which is HPWS in our case, should be taken into account when considering the influence of HRM in the process of open innovation. This study has important implications for HPWS, IT capability and open innovation; open innovation can be improved by using HPWS and IT capability. This study also expands IT ambidexterity to HRM and innovation studies.
Fluctuating Asymmetry in Morphological Characteristics of Betula Pendula Roth Leaf under Conditions of Urban Ecosystems: Evaluation of the Multi-Factor Negative Impact

The fluctuating asymmetry (FA) in Betula pendula Roth was estimated as an integrated measure of five morphometric characteristics of a lamina. Samples were collected in seven cities that differ both in climatic conditions, moderately to sharply continental. In total, 33 ecotopes were distinguished with various level of anthropogenic load. The statistical data processing involved correlation, one-way and factorial ANOVA, regression analyses, and principal component analysis (PCA). The impact of 25 climatic and anthropogenic factors on the FA value was considered. In most urban ecotopes, the integrated fluctuating asymmetry (IFA) value was higher than in natural biotopes of the same region. No significant inter-annual differences in IFA values were found. FA dependence on traffic load is noted to be statistically significant. The covariation analysis of IFA, climatic, and anthropogenic variables in various urban ecotopes revealed the impact of three groups of factors that together explain 93% of the variance in environmental parameters. The complex analysis clearly arranged the studied ecotopes by pollution gradient and climatic patterns. The primary effect of the total anthropogenic load on the developmental stability of B. pendula results in an IFA increase. IFA can play a key role in bioindication assessment of environmental quality. The climatic factors have no significant effect on the developmental stability of B. pendula in urban conditions.
GANRED: GAN-based Reverse Engineering of DNNs via Cache Side-Channel

In recent years, deep neural networks (DNN) have become an important type of intellectual property due to their high performance on various classification tasks. As a result, DNN stealing attacks have emerged. Many attack surfaces have been exploited, among which cache timing side-channel attacks are hugely problematic because they do not need physical probing or direct interaction with the victim to estimate the DNN model. However, existing cache-side-channel-based DNN reverse engineering attacks rely on analyzing the binary code of the DNN library that must be shared between the attacker and the victim in the main memory. In reality, the DNN library code is often inaccessible because 1) the code is proprietary, or 2) memory sharing has been disabled by the operating system. In our work, we propose GANRED, an attack approach based on the generative adversarial nets (GAN) framework which utilizes cache timing side-channel information to accurately recover the structure of DNNs without memory sharing or code access. The benefit of GANRED is four-fold. 1) There is no need for DNN library code analysis. 2) No shared main memory segment between the victim and the attacker is needed. 3) Our attack locates the exact structure of the victim model, unlike existing attacks which only narrow down the structure search space. 4) Our attack efficiently scales to deeper DNNs, exhibiting only linear growth in the number of layers in the victim DNN.