Miracle-dz/UniFAR-FTUs huggingface dataset:
Protective Effects of Anti-IL17 on Acute Lung Injury Induced by LPS in Mice

Introduction: T helper 17 (Th17) has been implicated in a variety of inflammatory lung and immune system diseases. However, little is known about the expression and biological role of IL-17 in acute lung injury (ALI). We investigated the mechanisms involved in the effect of anti-IL17 in a model of lipopolysaccharide (LPS)-induced acute lung injury (ALI) in mice. Methods: Mice were pre-treated with anti-IL17, 1h before saline/LPS intratracheal administration alongside non-treated controls and levels of exhaled nitric oxide (eNO), cytokine expression, extracellular matrix remodeling and oxidative stress, as well as immune cell counts in bronchoalveolar lavage fluid (BALF), and respiratory mechanics were assessed in lung tissue. Results: LPS instillation led to an increase in multiple cytokines, proteases, nuclear factor-κB, and Forkhead box P3 (FOXP3), eNO and regulators of the actomyosin cytoskeleton, the number of CD4+ and iNOS-positive cells as well as the number of neutrophils and macrophages in BALF, resistance and elastance of the respiratory system, ARG-1 gene expression, collagen fibers, and actin and 8-iso-PGF2α volume fractions. Pre-treatment with anti-IL17 led to a significant reduction in the level of all assessed factors. Conclusions: Anti-IL17 can protect the lungs from the inflammatory effects of LPS-induced ALI, primarily mediated by the reduced expression of cytokines and oxidative stress. This suggests that further studies using anti-IL17 in a treatment regime would be highly worthwhile.
Brain MR Image Analysis using Discrete wavelet Transform with Fractal Feature Analysis

Magnetic resonance image analysis for detection of some neurodegenerative diseases are investigated and reported in this work. It is based on discrete wavelet transform in combination with different fractal analysis. The proposed action consists of two stages. In the first stage consists of image preprocessing which includes image enhancement, the region of extraction and skull stripping. In the second stage, the preprocessed image is converted to wavelet domain, and the following study is performed for feature extraction using fractal analysis. Finally proposed work has experimented with a publically available dataset of images having the mild cognitive impairment, Alzheimer's and healthy patient. The support vector machine based classifier has achieved the classification accuracy of 89.7 +- 0.6. This work will pave to develop a system for computer-aided diagnosis of some neurological diseases.
Critical Role for Saccharomyces cerevisiae Asc1p in Translational Initiation at Elevated Temperatures

The eukaryotic ribosomal protein RACK1/Asc1p is localized to the mRNA exit channel of the 40S subunit but lacks a defined role in mRNA translation. Saccharomyces cerevisiae deficient in ASC1 exhibit temperature‐sensitive growth. Using this null mutant, potential roles for Asc1p in translation and ribosome biogenesis are evaluated. At the restrictive temperature the asc1Δ null mutant has reduced polyribosomes. To test the role of Asc1p in ribosome stability, cryo‐EM is used to examine the structure of 80S ribosomes in an asc1Δ yeast deletion mutant at both the permissive and nonpermissive temperatures. CryoEM indicates that loss of Asc1p does not severely disrupt formation of this complex structure. No defect is found in rRNA processing in the asc1Δ null mutant. A proteomic approach is applied to survey the effect of Asc1p loss on the global translation of yeast proteins. At the nonpermissive temperature, the asc1Δ mutant has reduced levels of ribosomal proteins and other factors critical for translation. Collectively, these results are consistent with recent observations suggesting that Asc1p is important for ribosome occupancy of short mRNAs. The results show the Asc1 ribosomal protein is critical in translation during heat stress.
Sensitivity of Shoulder Musculoskeletal Model Predictions to Muscle–Tendon Properties

Objective: While the sensitivity of estimated muscle forces to muscle–tendon properties is well documented for the lower limbs, little is known about the shoulder and upper limbs. The purpose of this study was to assess the sensitivity of estimated shoulder muscle forces and scapulohumeral joint force to muscle–tendon properties. Methods: One healthy male participant performed arm flexions and simulated throwing maneuvers. Kinematics were recorded using intra-cortical pins. Muscle forces were estimated using static optimization with the generic delft shoulder and elbow in OpenSim, and scapulohumeral joint forces were calculated from the estimated forces. Then, variations from –25% to +25% of the nominal values of the tendon slack length, the optimal fiber length, the maximal isometric force, and the pennation angle were applied to the musculoskeletal model to compute affected muscle forces and scapulohumeral joint force. Results: The variations in muscle–tendon properties led to changes up to 9.6 N or 174% in the muscle nominal forces. The more sensitive muscles were those that produced the greatest force: the rotator cuff muscles and the prime movers specific to the task. Among the four muscle–tendon properties, the maximal isometric force and the optimal fiber length had the greatest influence on the muscle force variability. Glenohumeral force was slightly influenced by muscle–tendon properties (<8%). Conclusion: Generic models (i.e., those without personalization of muscle–tendon properties) can lead to misinterpretations of muscle force. Efforts should focus on the maximal isometric force and the optimal fiber length of the rotator cuff muscles and prime movers.
An Efficient Multiobjective Design Optimization Method for a PMSLM Based on an Extreme Learning Machine

This paper focuses on the multiobjective design optimization of the permanent magnet synchronous linear motors (PMSLMs), which are applied to a high-precision laser engraving machine. A novel efficient multiobjective design optimization method for a PMSLM is proposed to achieve optimal performances as indicated by high average thrust, low thrust ripple, and low total harmonic distortion at different running speeds. First, based on the finite-element analysis (FEA) data, a regression machine learning algorithm, called an extreme learning machine (ELM), is introduced to solve the calculation modeling problem by mapping out the nonlinear and complex relationship between input structural factors and output motor performances. Comparative simulation experiments conducted using the traditional analytical modeling method and another machine learning modeling method, i.e., support vector machine, confirm the superiority of the ELM. Then, a new bionic intelligent optimization algorithm, called the gray wolf optimizer algorithm, is used to search the best optimization performances and structural parameters by performing iteration optimization calculation for multiobjective functions. Finally, FEA and prototype motor experiments prove the effectiveness and validity of the proposed method.
Multiuser MIMO for Underwater Visible Light Communication

Underwater visible light communication (UVLC) is a newly emerging technique in the field of wireless communication. Numerous studies indicated that it can achieve high data rate (on the order of Gbps) over tens of meters of communication link. Multiuser multiple-input multiple-output (MU-MIMO) systems have a potential to provide high capacity, interference suppression and space division multiple access. In this paper the performance of an orthogonal frequency division multiplexing (OFDM)-based MU-MIMO system for underwater visible light communication (VLC) is investigated. It is worth to note that MU-MIMO OFDM has been applied for indoor optical communication, however, to the best of our knowledge, it has not been studied for underwater environment yet. The system is considered to be $2\mathrm {x}2$ and the channel gain for each path is calculated with the closed-form expression for weighted double gamma function (WDGF). Zero-forcing precoding scheme is implemented to eliminate multiuser interference.
Investigation of Surface Temperature Differentiation of Fagus and Quercus Stands by Using Landsat Images

Bolgelerin iklimsel ozelliklerinin, agac turlerinin cesitliligini ve yapisal ozelliklerini etkilemesine karsin bitki ortusu yapisi da mikro iklim uzerinde etkili olmaktadir. Bu calismada, bu bilgiye dayanarak, Şile’nin Mercankosk Orman Isletme Şefligi siniri icerisinde kalan ve homojen yapi sergileyen kayin ve mese mescereleri ele alinarak yuzey sicakligi farkliliklari ortaya konulmaya calisilmistir 2011 Landsat TM-5 ve 2013, 2014 ve 2015 yillarina ait Landsat 8 - ETM termal goruntuleri uzerinden elde edilen yuzey sicakligi bilgileri, mescere verisi ile iliskilendirilerek istatistiksel olarak karsilastirilmistir . Elde edilen sonuclara gore, iki agac turune ait homojen mescere alanlari arasinda 2.4°C’ye varan yuzey sicakligi farklarinin olustugu tespit edilmistir. Bolgesel ozelliklerin hemen hemen benzer oldugu seflik sinirlari icerisinde olusan bu sicaklik farki, iklimsel acidan gozardi edilemeyecek bir etki yaratmaktadir. Ozellikle kuresel isinmayla mucadele kapsaminda yapilan hazirlik calismalarinda, bu bilgilerin bolgesel envanter olarak kullanilmasinin, elde edilecek basari uzerinde etkili olacagi dusunulmektedir.
Wireless Power Transfer—An Overview

Due to limitations of low power density, high cost, heavy weight, etc., the development and application of battery-powered devices are facing with unprecedented technical challenges. As a novel pattern of energization, the wireless power transfer (WPT) offers a band new way to the energy acquisition for electric-driven devices, thus alleviating the over-dependence on the battery. This paper presents an overview of WPT techniques with emphasis on working mechanisms, technical challenges, metamaterials, and classical applications. Focusing on WPT systems, this paper elaborates on current major research topics and discusses about future development trends. This novel energy transmission mechanism shows significant meanings on the pervasive application of renewable energies in our daily life.
Corporate Volunteering: Relationship to Job Resources and Work Engagement

Employers are increasingly including volunteer activities in their social responsibility programs. At companies at which this is done in a planned manner, we can speak of the development of a corporate volunteering, which correlates with numerous positive psychological outcomes at both the individual and the organizational level. The aim of the study was to investigate the relationship between the corporate volunteering programs and job characteristics, connected with work engagement. In our study we were interested in identifying the role of the corporate volunteering in the evaluation of job resources and work engagement. The study included 274 employees from 15 Slovenian companies, of whom 62% participate in their organizations’ volunteer activities. They filled out the Job demands and resources questionnaire, the Utrecht Work Engagement Scale (UWES-17) and a scale for measuring the corporate volunteering climate. The results indicate that the carrying out of volunteer activities correlates with the perception of the corporate volunteering climate. Employees whose employers implement volunteering programs are more engaged and report higher levels of both autonomy and support from their co-workers and supervisors. Theoretical and practical implications are discussed.
Shielding Performance Monitor Counters: a double edged weapon for safety and security

Recent years have witnessed the growth of the adoption of Cyber-Physical Systems (CPSs) in many sectors such as automotive, aerospace, civil infrastructures and healthcare. Several CPS applications include critical scenarios, where a failure of the system can lead to catastrophic consequences. Therefore, anomalies due to failure or malicious attacks must be timely detected. This paper focuses on two relevant aspects of the design of a CPS: safety and security. In particular, it studies how performance monitor counters (PMCs) available in modern microprocessors can be from the one hand a valuable tool to enhance the safety of a system and, on the other hand, a security backdoor. Starting from the example of a PMC based safety mechanism, the paper shows the implementation of a possible attack and eventually proposes a strategy to mitigate the effectiveness of the attack while preserving the safeness of the system.
Secure Complaint bot using Onion Routing Algorithm Concealing identities to increase effectiveness of complain bot

The more traditional approach towards launching a complaint is through written complaints that would be dropped into the complaint boxes available in some sectors, which has a lot of problems associated with it such as loss of complaints, security issues, etc. The proposed model that is structured towards replacement of this approach is an online complaint bot that would accept complaints through the onion routing algorithm. This would indeed secure complainant's identity and the bot would also use NLP to prioritize the complaints based on keywords. It would also direct it towards concerned authorities with a timestamp associated with each complaint and this complaint would have an id being sent back to the complainant for tracking of the issue on an online portal. These traits would in turn result into a system where data flows faster than the traditional approach and effective results a shorter time interval.
Evaluating the Progression and Orientation of Scratches on Outer-Raceway Bearing Using a Pattern Recognition Method

Bearing faults are a major source of failure in an induction motor, and early detection of fault becomes necessary because of its industrial application. A range of analytical methods has been used to detect, identify, and diagnose bearing faults, including vibrational analysis. Most analyses have used pitting as the fault, whereas in the industrial environment, scratches are a more common problem. This paper investigates such scratches, applying two types of fault analysis: fault progression and fault orientation. A support vector machine (SVM) algorithm is used to classify and diagnose the different types of bearing fault. The frequency-domain features obtained from a fast Fourier transform of the load current is used to train the SVM algorithm. The proposed diagnostic method is tested experimentally using induced outer race faults under different load conditions. The method is shown to be successful in diagnosing faults, suggesting potential applications in real industrial settings.
Robust vehicle-infrastructure localization using factor graph and probability data association

This paper presents a robust graph-based optimization framework for vehicle-infrastructure cooperative localization. Compared to the state-of-the-art approaches, the proposed solution keeps high performance in presence of unknown data association environments. In this paper, the association probability of each measurement is calculated, and then assigned to the corresponding edges on the graph, in which the nonlinear least square method is utilized to optimize the state. Thus the proposed approach presents a robust framework in the presence of high association uncertainty during vehicle-infrastructure cooperative localization, in which the corresponding weights from outliers are lower than the true vehicles. The experimental results demonstrate the good robustness in simulated data.
Project-oriented Problem Based Learning to build skills linked with industrial controllers

Active learning is a strategy to improve students’ analytical and interpretative skills to solve problems linked with industrial controllers. This implementation of active learning consists of the acquisition of knowledge with seminars taught by students, and latterly developing a project to solve a real technical problem. This way of learning requires support and continuous monitoring by academic staff, and an assessing model that contemplates the level of the skills acquired by each student.
Input to State Stability of Bipedal Walking Robots: Application to DURUS

Bipedal robots are a prime example of systems which exhibit highly nonlinear dynamics, underactuation, and undergo complex dissipative impacts. This paper discusses methods used to overcome a wide variety of uncertainties, with the end result being stable bipedal walking. The principal contribution of this paper is to establish sufficiency conditions for yielding input to state stable (ISS) hybrid periodic orbits, i.e., stable walking gaits under model-based and phase-based uncertainties. In particular, it will be shown formally that exponential input to state stabilization (e-ISS) of the continuous dynamics, and hybrid invariance conditions are enough to realize stable walking in the 23-DOF bipedal robot DURUS. This main result will be supported through successful and sustained walking of the bipedal robot DURUS in a laboratory environment.
Improved Feng Binarization Based on Max-Mean Technique on Document Image

Many valuable documents stored on the libraries and to keep the historical document content safe, a binarization approach on document images must be applied. In this study, a modification of Feng algorithm using Max-Mean was proposed. Feng method produced a blurred image and introduced a noise in the resulting image. The proposed method successfully to overcome the Feng method problem by suggesting a maximum threshold value. Based on the result, Max-Mean method able to improve the image quality and reduced the noise. Based on IQA, the proposed method achieved F-measure (74.901), PSNR (16.104), NRM (0.153) and MPM (1.371). Accuracy also shows the increment compare to the Feng result.
Single Phase Grid Interactive Solar Photovoltaic Inverters: A Review

Nowadays, single phase inverters are extensively being implemented for small scale grid-tied photovoltaic (PV) system. Small size PV inverters are replacing the central inverters. These inverters convert and transfer the power supplied by the single or a string of modules to the grid. Following this trend, various single phase inverters from conventional full bridge (H4) to more complex topologies have been introduced in the past few years. In this paper, single phase PV inverter topologies are classified and reviewed. First, the topologies are classified on the basis of PV module configurations, galvanic isolation and power conversion stages. Then, each topology is discussed in detail, addressing their merits and demerits. Finally, the recent development and future prospects of grid connected PV systems are discussed.
Haptic Assistance Improves Tele-Manipulation With Two Asymmetric Slaves

Tele-manipulation of heavy loads typically requires the simultaneous use of two asymmetric slaves: a crane for vertical weight support and a robot for accurate lateral positioning. The industrial standard prescribes a pair of operators for such tasks (one operator to control each slave), although in principle one operator might control both slaves with a single, hybrid interface. Accurate and safe co-operative handling of the expensive and fragile heavy components is difficult, presumably due to problems in the coordination of the subtasks and the lack of mutual awareness between the two operators. This study proposes a novel haptic assistance system to improve subtask coordination and task performance. Its novelty consists of haptically linking operators/interfaces through the joint task environment. The system's efficacy is evaluated with 15 pairs of co-operators and 15 individual uni-manual operators who maneuvered a heavy load through a bounded path in Virtual Reality. Haptic assistance improves task completion time for both groups. It also reduces control activity and self-reported workload without affecting a number of critical errors made by the operators. Moreover, without haptic assistance, uni-manual operators perform worse than co-operators, but this difference between the interfaces was not found with haptic assistance.
Comparison of ultrasound imaging and cone-beam computed tomography for examination of the alveolar bone level: A systematic review

Background and objective The current methods to image alveolar bone in humans include intraoral 2D radiography and cone-beam computed tomography (CBCT). However, these methods expose the subject to ionizing radiation. Therefore, ultrasound imaging has been investigated as an alternative technique, as it is both non-invasive and free from ionizing radiation. In order to assess the validity and reliability of ultrasonography in visualizing alveolar bone, a systematic review was conducted comparing ultrasound imaging to CBCT for examination of the alveolar bone level. Study design Seven databases were searched. Studies addressing examination of alveolar bone level via CBCT and ultrasound were selected. Risk of bias under Cochrane guidelines was used as a methodological quality assessment tool. Results All the four included studies were ex vivo studies that used porcine or human cadaver samples. The alveolar bone level was measured by the distance from the alveolar bone crest to certain landmarks such as cemento-enamel junction or gingival margin. The risk of bias was found as low. The mean difference between ultrasound and CBCT measurements ranged from 0.07 mm to 0.68 mm, equivalent to 1.6% - 8.8%. Conclusions There is currently preliminary evidence to support the use of ultrasonography as compared to CBCT for the examination of alveolar bone level. Further studies comparing ultrasound to gold standard methods would be necessary to help validate the accuracy of ultrasonography as a diagnostic technique in periodontal imaging.
Current Sense Amplifier Design with CMOS-Memristive Circuits

In recent years, the increase of processing speed requirements led to the demand to increase speed and reduce power consumption of memory devices, where sense amplifier is one of the most important components. This work provides the design idea and preliminary results of CMOS-memristive sense amplifier. The main objective of the paper is to modify $180 nm$ CMOS sense amplifier design by using memristive devices and improve the design in terms of on-chip area, power efficiency, temperature variation and speed. In the proposed design, NOT gates in the circuit were designed with memristors. The main aim of the paper is to check the effect of memristors on sense amplifier performance. The power consumption, on-chip area reduction, sensing delay and offset are reported in the paper.