Miracle-dz/UniFAR-FTUs huggingface dataset:
Excessive respiratory variation in tricuspid regurgitation systolic velocities in patients with severe tricuspid regurgitation.

AIMS Respiratory changes in tricuspid regurgitation (TR) systolic velocities are occasionally demonstrated by Doppler echocardiography in patients with TR. We tested the hypothesis that excessive respiratory changes in TR velocities are diagnostic of severe TR. METHODS AND RESULTS The difference between the maximal (expiratory) and minimal (inspiratory) TR systolic velocities during spontaneous respiration was measured by Doppler echocardiography in 68 patients with severe TR and 68 patients with moderate TR. The diagnostic value of the respiratory changes in TR velocity for detecting severe TR was assessed. The respiratory differences in TR velocities were greater in patients with severe TR (0.72 ± 0.30 m/s), compared with patients with moderate TR (0.28 ± 0.18; P < 0.001). Using receiver-operating characteristics analysis, the area under the curve for the respiratory difference in TR velocities for diagnosing severe TR was 0.92 (95% confidence interval: 0.87-0.96; P < 0.001). A difference in TR velocity ≥0.6 m/s had a sensitivity of 66%, specificity of 94%, positive predictive value of 92%, and a negative predictive value of 74% for diagnosing severe TR. Among patients with severe TR, excessive values of TR velocity difference were associated with signs of more severe TR (greater right ventricular size and malcoaptation of the tricuspid valve leaflets). CONCLUSION Excessive respiratory changes in Doppler measurements of TR systolic velocities are a specific sign of severe TR.
Molecular markers of some tick genera in Egypt based on the internal transcribed spacer (ITS-2): 1- Ixodidae (Boophilus and Hyalomma)

A method for the identification of three ixodid tick species; the cow tick (Boophilus annulatus), the camel tick (Hyalomma dromedarii) and the cattle tick (Hyalomma anatolicum excavatum) based on restriction enzyme analysis of the second internal transcribed spacer (ITS-2) in the nuclear ribosomal DNA was adopted. PCR products with MW 1375 bp, 1650 bp and 1835 bp from B. annulatus, H. dromedarii and H. anatolicum excavatum, respectively were amplified. These products were digested by the restriction enzymes Bgl II, EcoR I, Cfo I and Xmn I and the PCRRFLP patterns of the enzyme Cfo I showed differences among the three tick species. Speciesspecific restriction enzyme patterns were identified for B. annulatus (500bp), H. dromedarii (750 bp) and H. anatolicum excavatum (940 bp). The PCR-RFLP patterns of the enzyme Xmn I showed species-specific restriction enzyme patterns for H. dromedarii species (1000 and 650 bp). Further studies on different ixodid and argasid tick species in Egypt are taken place.
Array Types for a Graph Processing Language

Graphs are frequently represented and manipulated in the form of arrays encoding their adjacency matrices. Programs that operate on these arrays, for example, using linear algebra operations to encode graph algorithm primitives, can benefit from optimization techniques such as operation and loop fusion, data layout tuning, and other classical compilation methods. To support the construction of sound transformations and optimizations we present HAL (Hierarchical Array Language), a typed language for array processing. HAL provides first class index spaces, programming via type-directed transformations, and an expressive type-system that allows for encoding data structure properties. We show laws that can be derived for HAL to establish a basis for many semantics preserving transformations. This work also briefly introduces methods for expressing computations over these types via higher order functions.
WER: Maximizing Parallelism of Irregular Graph Applications Through GPU Warp EqualizeR

Irregular graphs are becoming increasingly prevalent across a broad spectrum of data analysis applications. Despite their versatility, the inherent complexity and irregularity of these graphs often result in the underutilization of Single Instruction, Multiple Data (SIMD) resources when processed on Graphics Processing Units (GPUs). This underutilization originates from two primary issues: the occurrence of inactive threads and intra-warp load imbalances. These issues can produce idle threads, lead to inefficient usage of SIMD resources, consequently hamper throughput, and increase program execution time. To address these challenges, we introduce Warp EqualizeR (WER), a framework designed to optimize the utilization of SIMD resources on a GPU for processing irregular graphs. WER employs both software API and a specifically-tailored hardware microarchitecture. Such a synergistic approach enables workload redistribution in irregular graphs, which allows WER to enhance SIMD lane utilization and further harness the SIMD resources within a GPU. Our experimental results over seven different graph applications indicate that WER yields a geometric mean speedup of $2.52 \times$ and $1.47 \times$ over the baseline GPU and existing state-of-the-art methodologies, respectively.
A Blockchain-Based Security Assessment Framework

Using Blockchain Technology for Security Assessment results in effective monitoring capabilities especially when data analytics components are inbuilt in such a system. At present days, we can see the availability of many Security Information and Event Management (SIEM) tools that follow a client-server model for capturing data from different resources and performing data analysis on the server side. However, such tools serve the purpose of a single institute and depend on the trust level in a multi-institute or multi-center-project kind of environment where they can be used. Another limitation could be that if the server is attacked, the whole exercise would be futile. The lack of trust and concerns about data integrity in such an environment makes performing root cause analysis of security risks difficult. Blockchain technology ensures a tamper-proof, time-stamped, and decentralized storage repository that helps in maintaining data integrity even in complex and untrusted multi-institute or multi-center-project environments while assuring data provenance. This article presents a unified and comprehensive security assessment framework that produces a compliance report along with threat perception level by monitoring and assessing resources across multi-institute or multi-center-project in different geographical locations while supporting data privacy by leveraging Blockchain Technology capabilities.
Guide to the Support for the Enhancement of Security Measures in Agile Projects

This article presents a series of recommendations to integrate techniques of Security Engineering with Agile Methods without compromising agility. Such recommendations are grouped in a guide based on a literature review. To evaluate the guide, specialists with different profiles were interviewed in order to obtain a variety of perspectives on the addressed subject. This way, positive and negative aspects of guide were obtained as a result of a qualitative research.
Establishing Maintainability in Systems Integration: Ambiguity, Negotiations, and Infrastructure

This paper investigates how maintainability can be established in system integration (SI) projects where maintainers have no direct access to the source code of the third-party software being integrated. We propose a model for maintainability in SI focusing on post-release activities, unlike traditional maintainability models where focus is on pre-release activities. Our model describes maintainability as a process characterized by ambiguity and negotiation that is supported through an infrastructure of debugging and coordination tools. Further, we describe how the process going from a software failure to establishing the fault causing the failure can be managed in SI. The results presented in this paper are based on observations from an ethnographic study of the Gentoo open source software (OSS) community, a large distributed volunteer community of over 320 developers developing and maintaining a software system for distributing and integrating third-party OSS software packages with different Unix versions
The presence of active Cdk5 associated with p35 in astrocytes and its important role in process elongation of scratched astrocyte

Cyclin‐dependent kinase 5 (Cdk5) is a unique member of the Cdk family; its kinase activity requires association with its activator, p35 or p39. p35 is the strongest and best characterized activator. Previous studies showed that p35 is a neuron‐specific protein that restricts Cdk5 activity in neurons. However, a high expression level of Cdk5 is found in astrocytes, which raises the possibility that astrocytic Cdk5 is functional. Here we show the presence of functional Cdk5 associated with p35 in astrocytes and demonstrate its important role in process elongation of scratched astrocytes. We found that p35 and glial fibrillary acidic protein (GFAP) were co‐localized in primary cultured and acute isolated brain cells. Cdk5 could form an immunocomplex with p35 and its activity was shown in pure primary cultured astrocytes. p35 was upregulated in astrocytes injured by scratching, concomitantly with upregulation of Cdk5 kinase activity. Pretreatment of the scratched astrocytes with a Cdk5 inhibitor, roscovitine, could delay wound healing by inhibiting the reorganization of tubulin, GFAP, and the extension of hypertrophic processes. Moreover, overexpression of dominant negative Cdk5 could shorten the length of extending protrusion of reactive astrocytes. Thus, our findings demonstrated that functional Cdk5, associated with p35, was expressed in astrocytes and its activity could be upregulated in reactive astrocytes, a new role of Cdk5 that has never been reported in the nervous system. The present study may provide new insight for understanding the multifunctional protein complex Cdk5/p35 in the nervous system. © 2007 Wiley‐Liss, Inc.
Analyzing Correlated Road Accident Count Data Using Zero Truncated Bivariate Poisson Regression Model

This paper aims to determine the significant factors which influence two correlated count responses, namely the total number of cars involved in an accident and the total number of fatalities due to that accident, of United Kingdom (UK) road accident count data. The bivariate Poisson (BVP) of two different forms and zero truncated bivariate Poisson regression (ZTBVP) models are considered to analyze UK road accident count data and the best model is selected based on the AIC and BIC values. From the data analysis, it is observed that the ZTBVP model provides the best fit (AIC value: 20563.26) for the UK road accident count data compared to all two variants of the BVP model (AIC value: >20563.26). From the results obtained from ZTBVP model, it is also observed that sex of driver, area, serious severity, and light condition are the significant covariates for the total number of cars involved in an accident while area, fatal severity, serious severity, light condition and year 2021 are the significant covariates for the total number of fatalities due to that accident. Dhaka Univ. J. Sci. 72(1): 24-29, 2024 (January)
A secured model for Indian e-health system

The inclusion of information technology in health sector has initiated a promising revolution in the area of health care. However, like in all other IT sectors, security issues are of primary concern in e-health care systems. In the present study, considering the Indian e-health scenario we have proposed a model, which integrates the authorization (role based and attribute based) and authentication techniques simultaneously. The suggested model utilizes “Aadhaar” an upcoming identification proof provided by UIDAI (Unique Identification Authority of India) an agency of Government Of India along with spatial &Temporal constraints for the purpose of authentication. Further we have also designed an algorithm for the implementation of same.
Dutch Stress Acquisition : OT and Connectionist Approaches

The task of acquiring phonology is not a simple one; a languageÕs phonological system involves a relatively complex set of patterns made up of abstract grammatical elements such as phonemes, moras, feet and prosodic words. And yet, children are able to acquire a great deal of their languageÕs phonological system relatively quickly and efficiently. How are children able to acquire the sound patterns of language? The generative approach, which dominated much of the early thinking about language acquisition, suggests that children are born with an innate Universal Grammar (UG) which governs the phonological patterns of languages, and allows language learners to quickly and efficiently acquire seemingly complex linguistic systems (Chomsky 1965). Earlier generative theories of phonology specified phonology as the knowledge of words’ constituents (i.e., features and phonemes), and the types of rules that can act upon them (Chomsky and Halle 1968, Smith 1973). More modern theories have recast these ideas within a variety of other frameworks, for example Optimality Theory (Prince & Smolensky 1993), as well as expanding the domain of phonological constituency to include increasingly more abstract units, as in autosegmental phonology (Goldsmith 1990) and feature geometry (Clements 1985, Sagey 1986). Nevertheless, these approaches are faithful to many of the original theories in the generative tradition, such as the assumption that children are born with a relatively extensive amount of phonological knowledge. One principal tenet that is particularly relevant to the present work is the description of grammars as sets of deterministic symbolic mechanisms which act upon a discrete inventory of language tokens. In the case of phonology, generative grammars are described as rules, principles or constraints that act upon the phonemes and words encoded in the mental lexicon. The present work reconsiders generative theories by exploring a radically different approach to how phonology is acquired, one in which children are not born with such a rich set of linguistic knowledge. This work instead considers the possibility that the input that children are exposed to contains a relatively rich set of information, and that children are able to use this information in order to acquire complex linguistic behaviors. This account does not reject the possibility that human language processing involves complex abstract structures such as features, phonemes, syllables, tones, feet and prosodic words. Instead, it suggests that the linguistic input to children is sufficiently rich as to allow them to acquire and use these concepts without the help of a great deal of innate linguistic structure. However, this approach does not include the core mechanics of generative grammars, namely the sets explicit and deterministic rules or constraints, and a lexicon that exists in isolation from such mechanisms.
Imbalanced Data Classification with Fuzzy Logic and Universal Image Fusion for Gearbox Defect Detection

Finding data with different appearance defects and imaging them on a large scale is a laborious and costly affair. In this paper, an image-based model for detecting and classifying defects on various surfaces such as metal, wood, carbon fiber, concrete and fabric structures is provided. The model is designed to work with limited and class-imbalanced data. In this model, the Universal Image Fusion (UIF) block is embedded. This block gives a comprehensive view of the distribution of defects, their dimensions, and their location on the surfaces. To make fake defective images, the defects are cropped from the defective images and fused according to the distribution map, with gradient masks on the defect-free surfaces. Next, extracting texture features from images was improved with the help of Fuzzy Inference Systems (FIS) with Gaussian membership function and Sobel operator. Images were classified into two classes, defective and non-defective, with the participation of three networks, VGG-16, InceptionV3, and Resnet-50. The presented model was implemented on a dataset of gearbox components with imbalance data and was able to achieve 97.87% accuracy, 98.59% precision, 98.55% specificity, 97.90% F1 score, 97.22% sensitivity, and 0.9577 informedness (Youden’s J statistic). The demo is available via https://github.com/DeepCar/Gearbox-Defect-Detection.
Restudying the Artificial Immune Model for Network Intrusion Detection

In order to quicken the affinity maturation process of detector population and improve the efficiency of network intrusion detection, this paper describes detailed vaccine operator, algorithm of adaptive extracting vaccine and Immune Evolutionary Algorithm (IEA), and then design a novel artificial immune model and algorithm for network intrusion detection which integrates Negative Selection Algorithm (NSA) with IEA. This model can also satisfy three requirements of distributed, self-organizing and lightweight. The network intrusion detection experiments based on the novel model and algorithm are designed to compare with Kim’s artificial immune model for network intrusion detection which is based on Clonal Selection Algorithm (CSA) and NSA. Experimental results show that the novel model and its algorithm quickens the affinity maturation process of detector population and stably increases the detection rate along with increasing evolutionary generation; but in Kim’s conceptual mode, the affinity maturation process of detector population takes more time, the detection rate falls into a little degradation and maintains invariant for a long time.
Improve the Resolution of Analog to Digital Converters with Bootstrap Method

The digital integrated circuit technologies operate on a wide variety of continuous-time signals. The reliability of these systems depends on the performances of the analog to digital converters ADC. However, the characteristics of ADC are affected by their resolution. In this paper, a bootstrap method is proposed which enhance the resolution of ADC and retain the desired accuracy.
Steganography in Thai text

Steganography, or communication through covert channels, is desirable when the mere existence of an encrypted message might provide useful information to eavesdroppers. Text is ideal for steganography due to its ubiquity. However, text communication channels do not necessarily provide sufficient redundancy for covert communication. We propose a steganographic scheme for Thai plain text documents that exploits redundancies in the way particular vowel, diacritical, and tonal symbols are composed in TIS-620, the standard Thai character set. The scheme is blind in that the original carrier text is not required for decoding. In an experimental evaluation, we find that the message embedding scheme allows 2.2 bytes of embedded covert text per kilobyte of carrier text on average, and that the document modifications are unnoticeable by casual observers. The method is thus a practical and effective method for covert communication over Thai plain text channels.
An outer gap model of high-energy emission from rotation-powered pulsars

We describe a refined calculation of high-energy emission from rotation-powered pulsars based on the outer gap model of Cheng, Ho, & Ruderman (1986 a, b). In this calculation, vacuum gaps form in regions near the speed-of-light cylinder of the pulsar magnetosphere along the boundary between the closed and open field line zones. We have improved upon previous efforts to model the spectra from these pulsars (e.g., Cheng et al. 1986b; Ho 1989) by following the variation in particle production and radiation properties with position in the outer gap. Curvature, synchotron, and inverse-Compton scattering fluxes vary significantly over the gap, and their interactions via photon-photon pair production build up the radiating charge populations at varying rates. We have also incorporated an approximate treatment of the transport particle and photon fluxes between gap emission zones. These effects, along with improved computations of the particle and photon distribution, provide very important modifications of the model gamma-ray flux. In paticular, we attempt to make specific predictions of pulse profile shapes and spectral variations as a function of pulse phase and suggest further extensions to the model which may provide accurate computations of the observed high-energy emissions.
Investigation of Core Loss in Electric Vehicle Induction Motor Using Finite Element Analysis for Performance Enhancement

Temperature rise in a 3ϕ, Totally Enclosed Fan Cooled (TEFC). , Squirrel Cage Induction Motor (SCIM) used in Electric Vehicles (EV) is effected by core loss. The temperature rise is a function of core loss and other losses. Since, the core loss components eddy current and hysteresis losses are a function of flux and flux density, Finite Element Method (FEM) is used to obtain average maximum flux density at different loads. Core loss is varying with respect to load and hence temperature rise, resistance value, starting torque to maximum torque $(\displaystyle \frac{T_{st}}{T_{\max}})$ ratio and current drawn at $(\displaystyle \frac{T_{st}}{T_{\max}})$ also varies which is so far assumed constant in reality. The analysis is made on the effect of core loss on SCIM used in EV for performance enhancement. The results reveals that when the variable core loss is considered, temperature rise is reduced and the SCIM rating is enhanced for 20%.
Increasing Sulfatide Synthesis in Myelin-Forming Cells of Arylsulfatase A-Deficient Mice Causes Demyelination and Neurological Symptoms Reminiscent of Human Metachromatic Leukodystrophy

Metachromatic leukodystrophy (MLD) is a lysosomal storage disorder caused by the deficiency of arylsulfatase A (ASA). This results in accumulation of sulfated glycosphingolipids, mainly 3-O-sulfogalactosylceramide (sulfatide), in the nervous system and various other organs. In patients, lipid storage causes a progressive loss of myelin leading to various neurological symptoms. The sulfatide storage pattern in ASA-deficient [ASA(−/−)] mice is comparable to humans, but regrettably, the mice do not mimic the myelin pathology. We reasoned that increasing sulfatide storage in this animal model might provoke demyelination. Therefore, we generated transgenic ASA(−/−) [tg/ASA(−/−)] mice overexpressing the sulfatide-synthesizing enzyme galactose-3-O-sulfotransferase-1 in myelinating cells. Indeed, these tg/ASA(−/−) mice displayed a significant increase in sulfatide storage in brain and peripheral nerves. Mice older than 1 year developed severe neurological symptoms. Nerve conduction velocity was significantly reduced in tg/ASA(−/−) mice because of a peripheral neuropathy characterized by hypomyelinated and demyelinated axons. Inhomogeneous myelin thickness in the corpus callosum, increased frequency of hypomyelinated and demyelinated axons in corpus callosum and optic nerve, and substantially reduced myelin basic protein levels are in accordance with loss of myelin in the CNS. Thus, increasing sulfatide storage in ASA(−/−) mice leads to neurological symptoms and morphological alterations that are reminiscent of human MLD. The approach described here may also be applicable to improve other mouse models of lysosomal as well as nonlysosomal disorders.
Reliable key generation for authentication and encryption using RO PUF on FPGA

Physical Unclonable Functions (PUFs) offer a robust solution for fingerprinting integrated circuits (ICs) by using process variations introduced during manufacturing. This paper presents a reliable key generation method for hardware authentication by employing an 8-bit parallel ring oscillator (RO) PUF deployed over a Xilinx Artix-7 Field Programmable Gate Array (FPGA), with seamless integration with a Raspberry Pi 3B+ single board computer for data manipulation. The bit selection and data extraction algorithms developed, result in the generation of a 2048-bit dependable key which is characterized by unique chip properties and is 100% reliable, serving as a means of device authentication and encryption.