Miracle-dz/UniFAR-FTUs huggingface dataset:
Let's Take it Offline: Boosting Brute-Force Attacks on iPhone's User Authentication through SCA

In recent years, smartphones have become an increasingly important storage facility for personal sensitive data ranging from photos and credentials up to financial and medical records like credit cards and person’s diseases. Trivially, it is critical to secure this information and only provide access to the genuine and authenticated user. Smartphone vendors have already taken exceptional care to protect user data by the means of various software and hardware security features like code signing, authenticated boot chain, dedicated co-processor and integrated cryptographic engines with hardware fused keys. Despite these obstacles, adversaries have successfully broken through various software protections in the past, leaving only the hardware as the last standing barrier between the attacker and user data. In this work, we build upon existing software vulnerabilities and break through the final barrier by performing the first publicly reported physical Side-Channel Analysis (SCA) attack on an iPhone in order to extract the hardware-fused devicespecific User Identifier (UID) key. This key – once at hand – allows the adversary to perform an offline brute-force attack on the user passcode employing an optimized and scalable implementation of the Key Derivation Function (KDF) on a Graphics Processing Unit (GPU) cluster. Once the passcode is revealed, the adversary has full access to all user data stored on the device and possibly in the cloud.As the software exploit enables acquisition and processing of hundreds of millions oftraces, this work further shows that an attacker being able to query arbitrary many chosen-data encryption/decryption requests is a realistic model, even for compact systems with advanced software protections, and emphasizes the need for assessing resilience against SCA for a very high number of traces.
SmarT: Uso de Aprendizado de Máquina para Filtragem e Recuperação Eficiente de Dados Espaciais e Temporais em Big Data

With the tremendous growth of big data time series, the efficient filtering and retrieval of large volumes of spatial and temporal data have become one of the biggest challenges for big data time series processing. Although some big data systems have been proposed to tackle these problems, none of them is considered a clear winner for all possible scenarios. This paper presents the SmarT search engine, a machine learning based solution that chooses the best big data system for filtering and retrieval of spatial and temporal data on the fly. In a detailed experimental evaluation, considering the Apache Spark, Elasticsearch, and SciDB big data systems, SmarT was able to reduce the response time in up to 22%. Resumo. Com o aumento do volume de dados de séries temporais na era de Big Data, a filtragem e recuperação eficiente de um grande volume de dados, utilizados como entrada no processamento de séries temporais, são uns dos maiores desafios da área. Diversos sistemas de Big Data foram criados para lidar com estes desafios, mas nenhum possui o melhor desempenho de filtragem e recuperação de dados em todos os cenários com filtros espaciais e temporais. Este trabalho apresenta o motor de busca SmarT que utiliza algoritmos de aprendizado de máquina para escolher, em tempo real, o melhor sistema Big Data para filtrar e recuperar os dados de séries temporais. O trabalho avalia o Apache Spark, Elasticsearch e SciDB e mostra uma redução de quase 22% do tempo de resposta utilizando o SmarT.
Reference Measurements in Developing UAV Systems for Detecting Pests, Weeds, and Diseases

The development of UAV (unmanned aerial vehicle) imaging technologies for precision farming applications is rapid, and new studies are published frequently. In cases where measurements are based on aerial imaging, there is the need to have ground truth or reference data in order to develop reliable applications. However, in several precision farming use cases such as pests, weeds, and diseases detection, the reference data can be subjective or relatively difficult to capture. Furthermore, the collection of reference data is usually laborious and time consuming. It also appears that it is difficult to develop generalisable solutions for these areas. This review studies previous research related to pests, weeds, and diseases detection and mapping using UAV imaging in the precision farming context, underpinning the applied reference measurement techniques. The majority of the reviewed studies utilised subjective visual observations of UAV images, and only a few applied in situ measurements. The conclusion of the review is that there is a lack of quantitative and repeatable reference data measurement solutions in the areas of mapping pests, weeds, and diseases. In addition, the results that the studies present should be reflected in the applied references. An option in the future approach could be the use of synthetic data as reference.
Unified Low-Rank Subspace Clustering with Dynamic Hypergraph for Hyperspectral Image

Low-rank representation with hypergraph regularization has achieved great success in hyperspectral imagery, which can explore global structure, and further incorporate local information. Existing hypergraph learning methods only construct the hypergraph by a fixed similarity matrix or are adaptively optimal in original feature space; they do not update the hypergraph in subspace-dimensionality. In addition, the clustering performance obtained by the existing k-means-based clustering methods is unstable as the k-means method is sensitive to the initialization of the cluster centers. In order to address these issues, we propose a novel unified low-rank subspace clustering method with dynamic hypergraph for hyperspectral images (HSIs). In our method, the hypergraph is adaptively learned from the low-rank subspace feature, which can capture a more complex manifold structure effectively. In addition, we introduce a rotation matrix to simultaneously learn continuous and discrete clustering labels without any relaxing information loss. The unified model jointly learns the hypergraph and the discrete clustering labels, in which the subspace feature is adaptively learned by considering the optimal dynamic hypergraph with the self-taught property. The experimental results on real HSIs show that the proposed methods can achieve better performance compared to eight state-of-the-art clustering methods.
Resveratrol Improves Mitochondrial Biogenesis Function and Activates PGC-1α Pathway in a Preclinical Model of Early Brain Injury Following Subarachnoid Hemorrhage

Peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α) has been shown to play a pivotal role in the regulation of mitochondrial biogenesis in diseases. Resveratrol (RSV), a natural polyphenolic reagent, has powerful antioxidant properties and the ability to scavenge mitochondrial reactive oxygen species (ROS) in a variety of central nervous system diseases. However, the underlying molecular mechanisms of RSV on mitochondrial biogenesis in early brain injury (EBI) following subarachnoid hemorrhage (SAH) remain poorly understood. This study aimed to explore the potential neuroprotective effects of RSV on mitochondrial biogenesis and function by activation of the PGC-1α signaling pathway in a prechiasmatic cistern SAH model. PGC-1α expression and related mitochondrial biogenesis were detected. Amounts of nuclear respiratory factor 1 (NRF1) and mitochondrial transcription factor A (TFAM) were determined to evaluate the extent of mitochondrial biogenesis. Increased PGC-1α and mitochondrial biogenesis after SAH were observed in the temporal cortex. Resveratrol increased the expression of PGC-1α, NRF1, and TFAM, and promoted PGC-1α nuclear translocation. Moreover, RSV could scavenge excess ROS, increase the activity of superoxide dismutase (SOD), enhance the potential of mitochondrial membrane and ATP levels, reduce the number of mitochondrial DNA copy, and decrease the level of malondialdehyde (MDA). RSV significantly ameliorated the release of apoptosis-related cytokines, namely P53, cleaved caspase-3, cytochrome c, and BAX, leading to the amelioration of neuronal apoptosis, brain edema, and neurological impairment 24 h after SAH. These results indicate that resveratrol promotes mitochondrial biogenesis and function by activation of the PGC-1α signaling pathway in EBI following SAH.
Turbulent heat transfer enhancement in an air-to-water heat exchanger

Hydrothermal behavior in a water-to-air double-pipe heat exchanger is studied experimentally and numerically. To achieve fully developed conditions, the heat exchanger was built with additional lengths before and after the test section. Commercial code (ANSYS 14) is used for numerical section. In order to enhance rate of heat transfer, discontinuous helical fins is utilized. Results show that Nusselt number augments with the enhancement of Reynolds number and Prandtl number, which are calculated at bulk temperature. The use of square section helical fins also shows a higher heat transfer enhancement rate than that of the circular one. Thermal performance factor is an increasing function of the open area ratio.
Quantitative Phosphoproteomic Analysis Reveals Dendritic Cell- Specific STAT Signaling After α2-3–Linked Sialic Acid Ligand Binding

Dendritic cells (DCs) are key initiators of the adaptive immunity, and upon recognition of pathogens are able to skew T cell differentiation to elicit appropriate responses. DCs possess this extraordinary capacity to discern external signals using receptors that recognize pathogen-associated molecular patterns. These can be glycan-binding receptors that recognize carbohydrate structures on pathogens or pathogen-associated patterns that additionally bind receptors, such as Toll-like receptors (TLRs). This study explores the early signaling events in DCs upon binding of α2-3 sialic acid (α2-3sia) that are recognized by Immune inhibitory Sialic acid binding immunoglobulin type lectins. α2-3sias are commonly found on bacteria, e.g. Group B Streptococcus, but can also be expressed by tumor cells. We investigated whether α2-3sia conjugated to a dendrimeric core alters DC signaling properties. Through phosphoproteomic analysis, we found differential signaling profiles in DCs after α2-3sia binding alone or in combination with LPS/TLR4 co-stimulation. α2-3sia was able to modulate the TLR4 signaling cascade, resulting in 109 altered phosphoproteins. These phosphoproteins were annotated to seven biological processes, including the regulation of the IL-12 cytokine pathway. Secretion of IL-10, the inhibitory regulator of IL-12 production, by DCs was found upregulated after overnight stimulation with the α2-3sia dendrimer. Analysis of kinase activity revealed altered signatures in the JAK-STAT signaling pathway. PhosphoSTAT3 (Ser727) and phosphoSTAT5A (Ser780), involved in the regulation of the IL-12 pathway, were both downregulated. Flow cytometric quantification indeed revealed de- phosphorylation over time upon stimulation with α2-3sia, but no α2-6sia. Inhibition of both STAT3 and -5A in moDCs resulted in a similar cytokine secretion profile as α-3sia triggered DCs. Conclusively, this study revealed a specific alteration of the JAK-STAT pathway in DCs upon simultaneous α2-3sia and LPS stimulation, altering the IL10:IL-12 cytokine secretion profile associated with reduction of inflammation. Targeted control of the STAT phosphorylation status is therefore an interesting lead for the abrogation of immune escape that bacteria or tumors impose on the host.
Pro-Resolving Mediator Annexin A1 Regulates Intracellular Ca2+ and Mucin Secretion in Cultured Goblet Cells Suggesting a New Use in Inflammatory Conjunctival Diseases

The amount of mucin secreted by conjunctival goblet cells is regulated to ensure the optimal level for protection of the ocular surface. Under physiological conditions lipid specialized pro-resolving mediators (SPM) are essential for maintaining tissue homeostasis including the conjunctiva. The protein Annexin A1 (AnxA1) can act as an SPM. We used cultured rat conjunctival goblet cells to determine if AnxA1 stimulates an increase in intracellular [Ca2+] ([Ca2+]i) and mucin secretion and to identify the signaling pathways. The increase in [Ca2+]i was determined using fura2/AM and mucin secretion was measured using an enzyme-linked lectin assay. AnxA1 stimulated an increase in [Ca2+]i and mucin secretion that was blocked by the cell-permeant Ca2+ chelator BAPTA/AM and the ALX/FPR2 receptor inhibitor BOC2. AnxA1 increased [Ca2+]i to a similar extent as the SPMs lipoxin A4 and Resolvin (Rv) D1 and histamine. The AnxA1 increase in [Ca2+]i and mucin secretion were inhibited by blocking the phospholipase C (PLC) pathway including PLC, the IP3 receptor, the Ca2+/ATPase that causes the intracellular Ca2+ stores to empty, and blockade of Ca2+ influx. Inhibition of protein kinase C (PKC) and Ca2+/calmodulin-dependent protein kinase also decreased the AnxA1-stimulated increase in [Ca2+]i and mucin secretion. In contrast inhibitors of ERK 1/2, phospholipase A2 (PLA2), and phospholipase D (PLD) did not alter AnxA1-stimulated increase in [Ca2+]i, but did inhibit mucin secretion. Activation of protein kinase A did not decrease either the AnxA1-stimulated rise in [Ca2+]i or secretion. We conclude that in health, AnxA1 contributes to the mucin layer of the tear film and ocular surface homeostasis by activating the PLC signaling pathway to increase [Ca2+]i and stimulate mucin secretion and ERK1/2, PLA2, and PLD to stimulate mucin secretion from conjunctival goblet cells.
Validation of a Modified Submaximal Balke Protocol to Assess Cardiorespiratory Fitness in Individuals at High Risk of or With Chronic Health Conditions—A Pilot Study

Objectives: This study aims to validate a submaximal treadmill walking test for estimation of maximal oxygen consumption (VO2max) in individuals at high risk of or with chronic health conditions. Method: Eighteen participants (age 62 ± 16 years; VO2max 31.2 ± 5.9 ml kg−1 min−1) at high risk of getting or with established chronic diseases performed two valid modified Balke treadmill walking protocols, one submaximal protocol, and one maximal protocol. Test duration, heart rate (HR), and rate of perceived exertion (RPE) were measured during both tests. VO2max was measured during the maximal test. VO2max was estimated from the submaximal test by multiple regression using time to RPE ≥ 17, gender, age, and body mass as independent variables. Model fit was reported as explained variance (R2) and standard error of the estimate (SEE). Results: The model fit for estimation of VO2max from time to RPE ≥ 17 at the submaximal test, body mass, age, and gender was R2 = 0.78 (SEE = 3.1 ml kg−1 min−1, p ≤ 0.001). Including heart rate measurement did not improve the model fit. Conclusions: The submaximal walking test is feasible and valid for assessing cardiorespiratory fitness in individuals with high risk of or chronic health conditions.
Effects of a Multi-Component Training Program on Healthy Older Adults' Prospective Memory Performance: Assessing Change Over Time

Prospective Memory (PM) is a cognitive function affected by aging. PM is the memory of future intentions and is significantly involved in everyday life, especially among older adults. Nevertheless, there are a few studies focused on PM training among healthy older adults and these studies did not report the optimal duration of training regarding improving PM performance among older adults. The present study aimed to determine the effective duration for training PM performance among healthy older adults. The current study was a randomized, controlled, single-blind, within-participants crossover trial including a training program with a duration of 12 h. The sample of 25 older adults aged 55 to 74 years recruited from the active members of the University of the Third Age (U3A), Kuala Lumpur/Selangor, their family members, and friends. The study design ensured some participants would receive the training after baseline while others would wait for 6 weeks after the baseline before receiving the training. All participants were evaluated five times: at baseline, 6, 12, 16, and at 24 weeks post-baseline. Moreover, the training program ensured all participants were assessed after each training session. The minimum number of hours to achieve training effects for this multi-component training program was eight. Results supported the efficacy of the training program in improving PM performance among healthy older adults. Also, the optimal duration for the multicomponent training program on PM performance among healthy older adults was obtained. This trial is registered at isrctn.com (#ISRCTN57600070).
Identification of Long Non-coding RNA Isolated From Naturally Infected Macrophages and Associated With Bovine Johne's Disease in Canadian Holstein Using a Combination of Neural Networks and Logistic Regression

Mycobacterium avium ssp. paratuberculosis (MAP) causes chronic enteritis in most ruminants. The pathogen MAP causes Johne's disease (JD), a chronic, incurable, wasting disease. Weight loss, diarrhea, and a gradual drop in milk production characterize the disease's clinical phase, culminating in death. Several studies have characterized long non-coding RNA (lncRNA) in bovine tissues, and a previous study characterizes (lncRNA) in macrophages infected with MAP in vitro. In this study, we aim to characterize the lncRNA in macrophages from cows naturally infected with MAP. From 15 herds, feces and blood samples were collected for each cow older than 24 months, twice yearly over 3–5 years. Paired samples were analyzed by fecal PCR and blood ELISA. We used RNA-seq data to study lncRNA in macrophages from 33 JD(+) and 33 JD(–) dairy cows. We performed RNA-seq analysis using the “new Tuxedo” suite. We characterized lncRNA using logistic regression and multilayered neural networks and used DESeq2 for differential expression analysis and Panther and Reactome classification systems for gene ontology (GO) analysis. The study identified 13,301 lncRNA, 605 of which were novel lncRNA. We found seven genes close to differentially expressed lncRNA, including CCDC174, ERI1, FZD1, TWSG1, ZBTB38, ZNF814, and ZSCAN4. None of the genes associated with susceptibility to JD have been cited in the literature. LncRNA target genes were significantly enriched for biological process GO terms involved in immunity and nucleic acid regulation. These include the MyD88 pathway (TLR5), GO:0043312 (neutrophil degranulation), GO:0002446 (neutrophil-mediated immunity), and GO:0042119 (neutrophil activation). These results identified lncRNA with potential roles in host immunity and potential candidate genes and pathways through which lncRNA might function in response to MAP infection.
QDECR: A Flexible, Extensible Vertex-Wise Analysis Framework in R

The cerebral cortex is fundamental to the functioning of the mind and body. In vivo cortical morphology can be studied through magnetic resonance imaging in several ways, including reconstructing surface-based models of the cortex. However, existing software for surface-based statistical analyses cannot accommodate “big data” or commonly used statistical methods such as the imputation of missing data, extensive bias correction, and non-linear modeling. To address these shortcomings, we developed the QDECR package, a flexible and extensible R package for group-level statistical analysis of cortical morphology. QDECR was written with large population-based epidemiological studies in mind and was designed to fully utilize the extensive modeling options in R. QDECR currently supports vertex-wise linear regression. Design matrix generation can be done through simple, familiar R formula specification, and includes user-friendly extensions for R options such as polynomials, splines, interactions and other terms. QDECR can handle unimputed and imputed datasets with thousands of participants. QDECR has a modular design, and new statistical models can be implemented which utilize several aspects from other generic modules which comprise QDECR. In summary, QDECR provides a framework for vertex-wise surface-based analyses that enables flexible statistical modeling and features commonly used in population-based and clinical studies, which have until now been largely absent from neuroimaging research.
Non-Coding RNAs Regulate Placental Trophoblast Function and Participate in Recurrent Abortion

Recurrent spontaneous abortion (RSA) is a serious pregnancy complication with an increasing clinical incidence. The various causes of recurrent abortion are complicated. Developments in genetics, immunology, and cell biology have identified important roles of non-coding RNAs (ncRNAs) in the occurrence and progress of recurrent abortion. NcRNAs can affect the growth, migration, and invasion of placental trophoblasts by regulating cell processes such as the cell cycle, apoptosis, and epithelial-mesenchymal transformation. Therefore, their abnormal expression might lead to the occurrence and development of RSA. NcRNAs include small nuclear RNA (snRNA), small nucleolar RNA (snoRNA), ribosomal RNA (rRNA), transfer, RNA (tRNA), circular RNA (cRNA), and Piwi-interacting RNA (piRNA). In this review, we discuss recent research that focused on the function and mechanism of microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNA (circRNA) in regulating placental trophoblasts. The use of ncRNAs as potential diagnostic and predictive biomarkers in RSA is also discussed to provide future research insights.
Effect of Lactic Acid Bacteria Strains on the Growth and Aflatoxin Production Potential of Aspergillus parasiticus, and Their Ability to Bind Aflatoxin B1, Ochratoxin A, and Zearalenone in vitro

The increased consumption of plant-based foods has intensified the concern related to mycotoxin intoxication. This study aimed to investigate the effect of selected lactic acid bacteria (LAB) strains on the growth of Aspergillus parasiticus NRRL 2999 and its production of aflatoxin (AF). The ability of the heat-killed (100°C for 1 h) LAB strains to bind aflatoxin M1 (AFM1) in milk and aflatoxin B1 (AFB1), ochratoxin A (OTA), and zearalenone (ZEN) in potassium phosphate buffer (PPB) was also evaluated in vitro. Ten LAB strains were tested individually, by inoculating them simultaneously with the fungus or after incubation of the fungus for 24 or 48 h at 25°C. Double layer yeast extract sucrose (YES) agar, de Man Rogosa and Sharpe (MRS) agar, and YES broth were incubated for 7 days at 25°C to follow the development of the fungus. Levilactobacillus spp. 3QB398 and Levilactobacillus brevis 2QB422 strains were able to delay the growth of A. parasiticus in YES broth, even when these strains were inoculated 24 h after the fungus. The inhibitory effect of these LAB strains was confirmed by the reduction of fungus colony size, suggesting dominance of LAB by competition (a Lotka-Voltera effect). The production of AFB1 by A. parasiticus was inhibited when the fungus was inoculated simultaneously with Lactiplantibacillus plantarum 3QB361 or L. plantarum 3QB350. No AFB1 was found when Levilactobacillus spp. 2QB383 was present, even when the LAB was inoculated 48 h after the fungus. In binding studies, seven inactivated LAB strains were able to promote a reduction of at least 50% the level of AFB1, OTA, and ZEN. This reduction varied depending on the pH of the PPB. In milk, however, only two inactivated LAB strains were able to reduce AFM1, with a reduction of 33 and 45% for Levilactobacillus spp. 3QB398 (Levilactobacillus spp.) and L. brevis 2QB422, respectively. Nevertheless, these results clearly indicate the potential of using LAB for mycotoxin reduction.