Miracle-dz/UniFAR-FTUs huggingface dataset:
Phytochemical Composition and Cytotoxic Effects on Liver Hepatocellular Carcinoma Cells of Different Berries Following a Simulated In Vitro Gastrointestinal Digestion

Berry fruits are rich in nutrients and polyphenols, providing potential health benefits. Understanding the factors that affect their bioavailability is becoming of utmost importance for evaluating their biological significance and efficacy as functional food. In this study, the phytochemical composition and the total antioxidant capacity of different varieties of five berries (blackberry, blackcurrant, blueberry, raspberry, and strawberry) were evaluated after an in vitro gastrointestinal digestion process. The cultivar of each berry that showed the higher content of total phenols and flavonoids was selected to study its cytotoxic effect on human hepatoma cells. Digestion resulted in a high reduction (p ˂ 0.05) of total phenolic, flavonoid and anthocyanin contents and total antioxidant capacity, in the “IN” samples compared to the “OUT” extracts, which represent the “serum-available” and the “colon-available” fractions, respectively. Incubation of the digested fraction for 24 h didn’t exert any effect on cellular viability, while a dose- and time-dependent cytotoxicity was observed after 48 h and 72 h of incubation for all the berries analyzed. Our results suggest that the approach proposed in this work may represent a rapid tool for evaluating and identifying new berries with increased phytochemical bioavailability, highlighting their antiproliferative agents after an in vitro digestion.
Development of an Interactive Dashboard to Analyze Cognitive Workload of Surgical Teams During Complex Procedural Care

In the surgical setting, team members constantly deal with a high-demand operative environment that requires simultaneously processing a large amount of information. In certain situations, high demands imposed by surgical tasks and other sources may exceed team member’s cognitive capacity, leading to cognitive overload which may place patient safety at risk. In the present study, we describe a novel approach to integrate an objective measure of team member’s cognitive load with procedural, behavioral and contextual data from real-life cardiac surgeries. We used heart rate variability analysis, capturing data simultaneously from multiple team members (surgeon, anesthesiologist and perfusionist) in a real-time and unobtrusive manner. Using audio-video recordings, behavioral coding and a hierarchical surgical process model, we integrated multiple data sources to create an interactive surgical dashboard, enabling the analysis of the cognitive load imposed by specific steps, substeps and/or tasks. The described approach enables us to detect cognitive load fluctuations over time, under specific conditions (e.g., emergencies, teaching) and in situations that are prone to errors. This in-depth understanding of the relationship between cognitive load, task demands and error occurrence is essential for the development of cognitive support systems to recognize and mitigate errors during complex surgical care in the operating room.
Data Augmentation for Robust Keyword Spotting under Playback Interference

Accurate on-device keyword spotting (KWS) with low false accept and false reject rate is crucial to customer experience for far-field voice control of conversational agents. It is particularly challenging to maintain low false reject rate in real world conditions where there is (a) ambient noise from external sources such as TV, household appliances, or other speech that is not directed at the device (b) imperfect cancellation of the audio playback from the device, resulting in residual echo, after being processed by the Acoustic Echo Cancellation (AEC) system. In this paper, we propose a data augmentation strategy to improve keyword spotting performance under these challenging conditions. The training set audio is artificially corrupted by mixing in music and TV/movie audio, at different signal to interference ratios. Our results show that we get around 30-45% relative reduction in false reject rates, at a range of false alarm rates, under audio playback from such devices.
Novel Interference Modelling in Multicellular D2D Network

Device-to-device (D2D) communication has been considered as an integral part of future 5G networks that enables direct communication between user equipments (UEs) without unnecessary routing via network infrastructure. However, D2D communications can generate significant interference to cellular communications during resource sharing. In this paper, we consider a realistic multi-cell scenario where the interferers are scattered according to a homogeneous Poisson point process and operating asynchronously in a wireless environment subject to path loss and multipath fading. Our framework accounts for all the essential physical parameters that affects the interference, such as success probability (for cellular and D2D), distance-based mode selection scheme and Spatial Average Rate(SAR) of the interferers.
Web Analytics Support System for Prediction of Heart Disease Using Naive Bayes Weighted Approach (NBwa)

Datamining is a technique that uses several methods to find patterns or getting required information from database which can be used in decision support and predictions areas. In this research work an intelligent and effective system using Naïve Bayes modeling technique is analyzed for prediction of heart disease. User need to provide required values to the attributes for the application that is implemented as web based. The data is taken from database and relates trained data with user input value. Traditional systems cannot accurately find heart disease but this work can assist doctors to take correct decisions. Naïve Bayes for classification purpose to detect heart disease is used and this approach classifies output data as no, low, average, high and very high. Hence two basic functions namely classification and prediction is be performed. Accuracy of the system depends on algorithm and database used and with the Naïve Bayes Weighted Approach (NBwa) an accuracy of 86% is obtained.
Wavelet Sparse Regularization for Manifold-Valued Data

In this paper, we consider the sparse regularization of manifold-valued data with respect to an interpolatory wavelet/multiscale transform. We propose and study variational models for this task and provide results on their well-posedness. We present algorithms for a numerical realization of these models in the manifold setup. Further, we provide experimental results to show the potential of the proposed schemes for applications.
A Heterogeneous Multicore System on Chip for Energy Efficient Brain Inspired Computing

Convolutional neural networks (CNNs) have revolutionized computer vision, speech recognition, and other fields requiring strong classification capabilities. These strengths make CNNs appealing in edge node Internet-of-Things (IoT) applications requiring near-sensors processing. Specialized CNN accelerators deliver significant performance per watt and satisfy the tight constraints of deeply embedded devices, but they cannot be used to implement arbitrary CNN topologies or nonconventional sensory algorithms where CNNs are only a part of the processing stack. A higher level of flexibility is desirable for next generation IoT nodes. Here, we present Mia Wallace, a 65-nm system-on-chip integrating a near-threshold parallel processor cluster tightly coupled with a CNN accelerator: it achieves peak energy efficiency of 108 GMAC/s/W at 0.72 V and peak performance of 14 GMAC/s at 1.2 V, leaving 1.2 GMAC/s available for general-purpose parallel processing.
Systematic Functional Analysis of Sigma (σ) Factors in the Phytopathogen Xanthomonas campestris Reveals Novel Roles in the Regulation of Virulence and Viability

The black rot pathogen Xanthomonas campestris pv. campestris (Xcc) is a model organism for the study of plant bacterial pathogenesis mechanisms. In bacteria, σ factors serve as important regulatory elements that respond to various environmental signals and cues. Though Xcc encodes 15 putative σ factors little is known about their roles. As an approach to identify the potential role of each σ factor, we constructed mutations in each of the σ-factor genes as well as generating mutants deficient in multiple σ factors to assess these regulators potential additive functions. The work identified two σ70 factors essential for growth. Furthermore, the work discovered a third σ70 factor, RpoE1, important for virulence. Further studies revealed that RpoE1 positively regulates the expression of the hrp gene cluster that encodes the type III secretion system (T3SS) which determines the pathogenicity and hypersensitive response of Xcc on plants. In vivo and in vitro studies demonstrated that RpoE1 could bind to the promoter region and promote transcription of hrpX, a gene encoding a key regulator of the hrp genes. Overall, this systematic analysis reveals important roles in Xcc survival and virulence for previously uncharacterized σ70 factors that may become important targets for disease control.
Development of an Internet of Things (IoT) Based Introductory Laboratory for Undergraduate Engineering Students

Internet of Things (IoT) is a fast emerging concept which is going to affect our life style in a big way. There is a need to include IoT in the under graduate engineering curriculum following the global trend for outcome based education. In this paper, details of various stages of development of an introductory laboratory based on IoT are presented. It starts with tackling the challenges and designing laboratory experiments with limited resources available. Project based learning approach is adopted to develop this laboratory through students. The students' feedback on learning experience is also included.
Xerox Day Vulnerability

In the area of espionage between countries, an infiltration covert channel used to trigger a silent malware installed on a network of a critical organization (such as 911 services and missile launching facility) from the outside world is extremely dangerous to the target country’s security. In order to prevent attackers from establishing such a channel, these organizations take various steps to secure their networks, to make the establishment of this type of covert channel very challenging and almost impractical to achieve; the current state of the art methods are very limited and ineffective. In this paper, we show that even a strong isolation technique, such as air-gapping the network, can be circumvented by using an organizational multifunction printer (MFP) to establish an infiltration covert channel in order to communicate with a malware installed on an isolated organization from the outside. We show how an attacker can leverage the light sensitivity of an MFP and use different light sources to infiltrate commands to the malware in the organization. We analyze the influence of light intensity, distance, transmission rate, ambient light, and wavelength on the covert channel. In addition we demonstrate the attack on a real organization using: 1) a laser attached to a tripod stand; 2) a laser carried by a drone; and 3) a hijacked smart bulb that is not even connected to the organization’s network and is accessed and controlled by an attacker in a passing car. We prove that locating the scanner in an inner room inside an organization does not prevent an attacker from establishing the covert channel. We show how our covert channel can be established from a greater distance (900 m) and at a higher transmission rate of 200 bits/s than other methods used to infiltrate data to an organization, even using invisible light (covertly).
Gray Matter Volume and Cognitive Performance During Normal Aging. A Voxel-Based Morphometry Study

Normal aging is characterized by decline in cognitive functioning in conjunction with extensive gray matter (GM) atrophy. A first aim of this study was to determine GM volume differences related to aging by comparing two groups of participants, middle-aged group (MAG, mean age 41 years, N = 16) and older adults (OG, mean age 71 years, N = 14) who underwent an magnetic resonance images (MRI) voxel-based morphometry (VBM) evaluation. The VBM analyses included two optimized pipelines, for the cortex and for the cerebellum. Participants were also evaluated on a wide range of cognitive tests assessing both domain-general and language-specific processes, in order to examine how GM volume differences between OG and MAG relate to cognitive performance. Our results show smaller bilateral GM volume in the OG relative to the MAG, in several cerebral and right cerebellar regions involved in language and executive functions. Importantly, our results also revealed smaller GM volume in the right cerebellum in OG relative to MAG, supporting the idea of a complex cognitive role for this structure. This study provides a broad picture of cerebral, but also cerebellar and cognitive changes associated with normal aging.
Psychometric evaluation and cultural adaptation of the Spanish version of the “Scale for End-of Life Caregiving Appraisal”

Abstract Objective To translate, culturally adapt, and psychometrically evaluate the Spanish version of the “Scale for End-of Life Caregiving Appraisal” (SEOLCAS). Method Observational cross-sectional study. Convenience sample of 201 informal end-of-life caregivers recruited in a southern Spanish hospital. The reliability of the questionnaire was assessed through its internal consistency (Cronbach's α) and temporal stability (Pearson's correlation coefficient [r] between test-retest). The content validity index of the items and the scale was calculated. Criterion validity was explored through performing a linear regression analysis to evaluate the SEOLCAS’ predictive validity. Exploratory factor analysis was used to examine its construct validity. Results The SEOLCAS’ reliability was very high (Cronbach's α = 0.92). Its content validity was excellent (all items’ content validity index = 0.8–1; scale's validity index = 0.88). Evidence of the SEOLCAS’ criterion validity showed that the participants’ scores on the SEOLCAS explained approximately 79.3% of the between-subject variation of their results on the Zarit Burden Interview. Exploratory factor analysis provided evidence of the SEOLCAS’ construct validity. This analysis revealed that two factors (“internal contingencies” and “external contingencies”) explained 53.77% of the total variance found and reflected the stoic Hispanic attitude toward adversity. Significance of results The Spanish version of the SEOLCAS has shown to be an easily applicable, valid, reliable, and culturally appropriate tool to measure the impact of end-of-life care provision on Hispanic informal caregivers. This tool offers healthcare professionals the opportunity to easily explore Hispanic informal end-of-life caregivers’ experiences and discover the type of support they may need (instrumental or emotional) even when there are communicational and organizational constraints.
Compact, Low-Profile, Bandwidth-Enhanced Substrate Integrated Waveguide Filtenna

In this letter, a compact, low-profile, bandwidth-enhanced, dual-cavity substrate integrated waveguide (SIW) filtenna is demonstrated. Two SIW cavities are stacked vertically on top of each other. A complementary split-ring resonator slot is etched in the top surface of the uppermost cavity, causing the top surface to act as a patch antenna. The operational impedance bandwidth is significantly enhanced by merging the three resonances that arise from this configuration. One is introduced by the patch, and the other two are inherently generated by the two cavities. A metallized coupling post is introduced from the ground plane through both cavities to the upper surface to excite the fundamental resonant mode of the patch, as well as to electromagnetically couple the two cavities. The optimized filtenna was fabricated by a standard printed circuit board technology and tested. It has a low profile <inline-formula><tex-math notation="LaTeX">${\text{0.03}}\lambda _{0}$</tex-math></inline-formula> and a compact size <inline-formula><tex-math notation="LaTeX">${\text{0.62}}\,\lambda _{0}\,\times {\text{0.62}}\,\lambda _{0}$</tex-math> </inline-formula> at its center frequency, <inline-formula><tex-math notation="LaTeX">$f_{0}= {\text{2.95}}\,{\text{ GHz}}$</tex-math></inline-formula>. The measured results agree well with their simulated values. They demonstrate a 6.3% fractional bandwidth, a maximum realized gain of 6.73 dBi, a flat gain profile within its passband, and an excellent out-of-band selectivity.
Measurement and Analysis of Input-Signal Dependent Flicker Noise Modulation in Chopper Stabilized Instrumentation Amplifier

This letter presents measurement results and an analysis of an input-signal dependent flicker noise modulation in chopper stabilized current balancing instrumentation amplifier. Although the chopping is well known and often used for its effectiveness in flicker noise mitigation, measurement results show an increased effect of the 1/ $f$ noise proportional to input signal amplitude. This effect is often ignored in most publications and will also not be apparent in traditional noise measurements (due to the lack of input signal when doing noise measurements). The unexpected operation was confirmed by a Spectre simulation and the main cause can be attributed to a flicker noise modulation by input signals of large amplitude. Because of the signal-dependency of the effect, flicker noise remains (and can be significant) even when chopping is applied.
Deliberation and Procedural Automation on a Two-Step Task for Rats

Current theories suggest that decision-making arises from multiple, competing action-selection systems. Rodent studies dissociate deliberation and procedural behavior, and find a transition from procedural to deliberative behavior with experience. However, it remains unknown how this transition from deliberative to procedural control evolves within single trials, or within blocks of repeated choices. We adapted for rats a two-step task which has been used to dissociate model-based from model-free decisions in humans. We found that amixture ofmodel-based andmodel-free algorithms was more likely to explain rat choice strategies on the task than either model-based or model-free algorithms alone. This task contained two choices per trial, which provides a more complex and non-discrete per-trial choice structure. This task structure enabled us to evaluate how deliberative and procedural behavior evolved within-trial and within blocks of repeated choice sequences. We found that vicarious trial and error (VTE), a behavioral correlate of deliberation in rodents, was correlated between the two choice points on a given lap. We also found that behavioral stereotypy, a correlate of procedural automation, increased with the number of repeated choices. While VTE at the first choice point decreased with the number of repeated choices, VTE at the second choice point did not, and only increased after unexpected transitions within the task. This suggests that deliberation at the beginning of trialsmay correspond to changes in choice patterns, while mid-trial deliberation may correspond to an interruption of a procedural process.
Brief Announcement: MUSIC: Multi-Site Entry Consistencyfor Geo-Distributed Services

Geo-distributed services that are executed across multiple sites at a global scale are increasingly prevalent, and are at the core of the control plane tasked with managing the Virtual Network Functions (VNFs) of next-generation network infrastructure. A key building block of any replicated service of this type is logically shared state, an abstraction that is often implemented by having multiple copies of each data element and using one of any number of distributed protocols to enforce consistency with guarantees ranging from eventual to causal to sequential consistency. These solutions fail to meet the real needs of geo-distributed services found in a VNF control plane (and elsewhere), which are to provide guarantees strong enough to be useful, yet still efficiently implementable in a global network with larger latencies and a wider range of failure modes. Here, we propose a new solution to state consistency based on extending entry consistency, a paradigm originally developed for failure-free multi-processor systems, for use in geo-distributed services with failures. We outline the challenges associated with state consistency in such services, and describe a data-store called MUSIC (MUlti-SIte entry Consistency) that combines an eventually consistent key-value store with locking primitives to implement entry-consistent semantics.
fPADnet: Small and Efficient Convolutional Neural Network for Presentation Attack Detection

The rapid growth of fingerprint authentication-based applications makes presentation attack detection, which is the detection of fake fingerprints, become a crucial problem. There have been numerous attempts to deal with this problem; however, the existing algorithms have a significant trade-off between accuracy and computational complexity. This paper proposes a presentation attack detection method using Convolutional Neural Networks (CNN), named fPADnet (fingerprint Presentation Attack Detection network), which consists of Fire and Gram-K modules. Fire modules of fPADnet are designed following the structure of the SqueezeNet Fire module. Gram-K modules, which are derived from the Gram matrix, are used to extract texture information since texture can provide useful features in distinguishing between real and fake fingerprints. Combining Fire and Gram-K modules results in a compact and efficient network for fake fingerprint detection. Experimental results on three public databases, including LivDet 2011, 2013 and 2015, show that fPADnet can achieve an average detection error rate of 2.61%, which is comparable to the state-of-the-art accuracy, while the network size and processing time are significantly reduced.
Genetic Association of Single Nucleotide Polymorphisms with Acetaminophen-Induced Hepatotoxicity

Acetaminophen is commonly used to reduce pain and fever. Unfortunately, overdose of acetaminophen is a leading cause of acute liver injury and failure in many developed countries. The majority of acetaminophen is safely metabolized in the liver and excreted in the urine; however, a small percentage is converted to the highly reactive N-acetyl-p-benzoquinone imine (NAPQI). At therapeutic doses, NAPQI is inactivated by glutathione S-transferases, but at toxic levels, excess NAPQI forms reactive protein adducts that lead to hepatotoxicity. Individual variability in the response to both therapeutic and toxic levels of acetaminophen suggests a genetic component is involved in acetaminophen metabolism. In this review, we evaluate the genetic association studies that have identified 147 single nucleotide polymorphisms linked to acetaminophen-induced hepatotoxicity. The identification of novel genetic markers for acetaminophen-induced hepatotoxicity provides a rich resource for further evaluation and may lead to improved prognosis, prevention, and treatment.