Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Microbial Transglutaminase and Fermentation Type on Improvement of lysine Availability in Wheat Bread: A Response Surface Methodology

Background and objective: Lysine-glutamine crosslink formation catalyzed by microbial transglutaminase is supposed to affect improvement of lysine availability in wheat bread. Present study is done to investigate the effect of microbial transglutaminase and fermentation type in improvement of the lysine availability of wheat bread. Material and methods: Lysine-fortified wheat breads were formulated using response surface methodology with composite-face central design. Statistical models were used to predict the impact of defatted soy flour level (0-50% w w -1 ), microbial transglutaminase level (0-1.6% w w -1 ) and fermentation type (yeast or mixed fermentation based on sourdough). Further information was provided on the individual role of independent variables in nutritional and structural characteristics of optimized formulation and blank and control samples. Experiments were carried out in triplicate and the mean values were analyzed using one-way analysis of variance and Tukey’s test. Results and conclusion: The suggested formula contained 26.64% w w -1 of defatted soy flour and 0.55% w w -1 of microbial transglutaminase, which was fermented using sourdough-based mixed fermentation and provided 0.16 mg 100 g -1 of available lysine and 2.09 cm 3 g -1 of specific volume. The highest lysine chemical score (22.79±0.16), essential amino acid index (35.31±0.37) and biological value (26.79±0.02) and the lowest lysine loss during the baking process seen in optimized formulation verified the effectiveness of microbial transglutaminase in lysine fortification of defatted soy flour/wheat breads (P≤0.05). Considering rheology parameters and textural analysis, microbial transglutaminase treatment increased elastic modulus and β-sheet structure. These structural changes decreased final products digestibility, which can increase using mixed fermentation based on sourdough. Conflict of interest: The authors declare no conflict of interest.
Cortactin Phosphorylation by Casein Kinase 2 Regulates Actin Related Protein 2/3 Complex Activity and Invadopodia Function

Cortactin Phosphorylation by Casein Kinase 2 Regulates Actin Related Protein 2/3 Complex Activity and Invadopodia Function Steven Michael Markwell Malregulation of the actin cytoskeleton enhances tumor cell motility and invasion. The actinbinding protein cortactin facilitates branched actin network formation through activation of the actin-related protein (Arp) 2/3 complex. Arp2/3 complex activation is responsible for driving increased migration and extracellular matrix (ECM) degradation by governing invadopodia formation and activity. While cortactin-mediated activation of Arp2/3 complex and invadopodia regulation has been well established, signaling pathways responsible for governing cortactin binding to Arp2/3 are unknown. In this dissertation we identify casein kinase (CK) 2α phosphorylation of cortactin as a negative regulator of Arp2/3 binding. CK2α directly phosphorylates cortactin at a conserved threonine (T24) adjacent to the canonical Arp2/3 binding motif. Phosphorylation of cortactin T24 by CK2α impairs the ability of cortactin to bind Arp2/3 and activate actin nucleation. Decreased invadopodia activity is observed in HNSCC cells with expression of CK2α phosphorylation-null cortactin mutants, shRNA-mediated CK2α knockdown, and with the CK2α inhibitor Silmitasertib. Silmitasertib inhibits HNSCC collective invasion in tumor spheroids and orthotopic tongue tumors in mice. Although overall cancer incidence rates are declining across the United States, the incidence of head and neck squamous cell carcinoma (HNSCC) continues to increase within the Appalachian region. To better understand the underlying factors leading to disproportionate outcomes, our group has established an Appalachian-specific HNSCC patient tissue cohort from surgically-resected tumors. This cohort represents all HNSCC stages, lesion types and morphologies, as well as cases that contain human papillomavirus (HPV) and/or tobacco and alcohol use. Moreover, we have generated several patient derived xenografts (PDXs) from these tissues, allowing further cellular, biochemical and preclinical therapeutic evaluation. Utilization of PDX tumors from this cohort will allow examination of critical steps in the development and potential treatment of invasive, metastatic, and recurrent Appalachian-associated disease. Matched patient and PDX sample availability enables personalized medicine and co-clinical trials aimed at reversing this Appalachian cancer health disparity and ultimately improving regional HNSCC patient care.
STARD3: A Swiss Army Knife for Intracellular Cholesterol Transport

Intracellular cholesterol transport is a complex process involving specific carrier proteins. Cholesterol-binding proteins, such as the lipid transfer protein steroidogenic acute regulatory-related lipid transfer domain-3 (STARD3), are implicated in cholesterol movements between organelles. Indeed, STARD3 modulates intracellular cholesterol allocation by reducing it from the plasma membrane and favoring its passage from the endoplasmic reticulum (ER) to endosomes, where the protein is localized. STARD3 interacts with ER-anchored partners, notably vesicle-associated membrane protein-associated proteins (VAP-A and VAP-B) and motile sperm domain-containing 2 (MOSPD2), to create ER–endosome membrane contacts. Mechanistic studies showed that at ER–endosome contacts, STARD3 and VAP proteins build a molecular machine able to rapidly transfer cholesterol. This review presents the current knowledge on the molecular and cellular function of STARD3 in intracellular cholesterol traffic.
An Improved Pre-pruning Algorithm Based on ID3

As a popular algorithm of decision tree,ID3 is widely used because of its simple idea and facile realization.However,the structure of the tree produced by this algorithm is usually too large and complex,thus the performance of the algorithm is restricted.In order to enhance the efficiency of the tree-producing process and avoid "overfitting",we take the classification effect of each classifying attribute into account,that is,if the classification effect reaches a certain level,the process of classification of that branch will be terminated,and propose an improved algorithm by using the maximum support and adopting pre-pruning strategy.The experiment results show that the improved algorithm can make decision tree simpler without reducing precise.
Intelligent Access Selection in Cognitive Networks: A Fuzzy Neural Network Approach

AbstractTraditional single attribute access selection scheme can’t meet the requirements of new service and userexperience in cognitive networks. In this paper, we present a novel multi-attributes intelligent accessselection scheme based on fuzzy neural network. By means of considering network side, terminal side anduser preference as access elements, we get the optimal access network by using fuzzy neural network.Parameter learning makes the scheme adapt network environment variation dynamically. Simulationresults show the advantages comparing to the existing schemes. Keywords : Cognitive Networks; Access Selection; Fuzzy Neural Network; Particle Swarm Optimization 1 Introduction Cognitive network (CN) is a type of intelligent network that has a cognitive process can perceivecurrent network conditions, and then plan, decide and act on those conditions, then learn fromthese adaptations and use them to make future decisions, all while taking into account end-to-endgoals [1]. Because of its self-management attributions, CN is considered as a key approach toachieve the goals of intelligence thereupon then attract more attention, and become a hotspotthat academia concerned rapidly [2]. As one of the key technologies, network access selection plays an important role in CN studies.In CNs, it’s diﬃcult for terminals to select the optimal network rapidly and accurately becauseof networks’ heterogeneous. From recent researches, we can conclude that there are mainly twomajor aspects:1) access selection based on single attribute; 2) access selection based on multi-attributes. Single attribute access selection manner can improve access performance for terminalside and network side at one area. E.g. load balance manner uses load metric parametersto quantify the load degree, and selects access network with lower load [3]. User preferencemanner selects the optimal network according to user preference model, it can improve access
Auditory displays and assistive technologies : the use of head movements by visually impaired individuals and their implementation in binaural interfaces

Visually impaired people rely upon audition for a variety of purposes, among these are the use of sound to identify the position of objects in their surrounding environment. This is limited not just to localising sound emitting objects, but also obstacles and environmental boundaries, thanks to their ability to extract information from reverberation and sound reflectionsall of which can contribute to effective and safe navigation, as well as serving a function in certain assistive technologies thanks to the advent of binaural auditory virtual reality. It is known that head movements in the presence of sound elicit changes in the acoustical signals which arrive at each ear, and these changes can improve common auditory localisation problems in headphone-based auditory virtual reality, such as front-to-back reversals. The goal of the work presented here is to investigate whether the visually impaired naturally engage head movement to facilitate auditory perception and to what extent it may be applicable to the design of virtual auditory assistive technology. Three novel experiments are presented; a field study of head movement behaviour during navigation, a questionnaire assessing the self-reported use of head movement in auditory perception by visually impaired individuals (each comparing visually impaired and sighted participants) and an acoustical analysis of inter-aural differences and crosscorrelations as a function of head angle and sound source distance. It is found that visually impaired people self-report using head movement for auditory distance perception. This is supported by head movements observed during the field study, whilst the acoustical analysis showed that interaural correlations for sound sources within 5m of the listener were reduced as head angle or distance to sound source were increased, and that interaural differences and correlations in reflected sound were generally lower than that of direct sound. Subsequently, relevant guidelines for designers of assistive auditory virtual reality are proposed.
Image Restoration Network with Adaptive Channel Attention Modules for Combined Distortions

The image obtained from systems such as autonomous driving cars or fire-fighting robots often suffer from several degradation such as noise, motion blur, and compression artifact due to multiple factor. It is difficult to apply image recognition to these degraded images, then the image restoration is essential. However, these systems cannot recognize what kind of degradation and thus there are difficulty restoring the images. In this paper, we propose the deep neural network, which restore natural images from images degraded in several ways such as noise, blur and JPEG compression in situations where the distortion applied to images is not recognized. We adopt the channel attention modules and skip connections in the proposed method, which makes the network focus on valuable information to image restoration. The proposed method is simpler to train than other methods, and experimental results show that the proposed method outperforms existing state-of-the-art methods. 키워드: 영상복원,딥러닝,채널어텐션,합성곱신경망
Split/Merge and Chromosome Encoding Model of Genetic Algorithm For Image Segmentation & Optimization

The present paper focuses on image segmentation by the implementation of the split/merge approach which involves k-means clustering algorithm and proficient chromosome encoding model of Genetic Algorithm for merging. The input for a segmentation algorithm is an image that is converted to a gray-level intensity image through the preprocessing techniques and optimized according to some predefined quality measures. In order to optimize the image, an evolutionary computation algorithm is utilized. Keywords: Image Segmentation, Genetic Optimization, Genetic Algorithm, K-means Clustering Algorithm and Split/Merge approach
Effect of Indian spices on lasR mutant of Pseudomonas aeruginosa PAO1 biofilm

The study was undertaken to analyse the impact of bark of cinnamon (Cinnamomum zeylanicum), seeds of mustard (Brassica nigra) and nutmeg fruit (Myristica fragrans) on the biofilm by lasR mutant of Pseudomonas aeruginosa PAO1. The analysis of the phytoextracts showed that the test culture is inhibited to varying degrees by different phytoextracts. Aqueous and methanolic extracts were prepared and its phenolic content and antioxidant properties were assessed. The effect of the extract was further studied for the biofilm formation by the lasR mutant. Different phytoextract cause varying degree of structural changes in biofilm architecture of wild type and lasR mutant. The finding indicates involvement of lasR during biofilm development in presence any antimicrobial compound of plant origin.
Task Execution Cost Minimization-Based Joint Computation Offloading and Resource Allocation for Cellular D2D MEC Systems

The rapid proliferation of new applications poses great challenges to the computation capability of mobile devices. To tackle this problem, computation offloading was proposed as a promising paradigm. In this paper, we consider a cellular device-to-device (D2D) mobile edge computing (MEC) system consisting of one base station (BS) deployed with an MEC server and users. We assume that a portion of users have task computation requirements and may perform local computing, MEC offloading, or D2D offloading. Further assuming that tasks can be partitioned into small-sized data and can be executed simultaneously via various computation modes, we jointly study computation offloading and resource allocation problem. To achieve efficient information interaction and task management, we first propose a joint task management architecture. Defining task execution cost as the weighted sum of task execution latency and energy consumption, we then formulate the joint optimization problem as a task execution cost minimization problem. As the formulated problem is a mixed integer nonlinear problem, which cannot be solved conveniently, we propose a heuristic algorithm that successively solves computation offloading subproblem and resource allocation subproblem by Kuhn–Munkres algorithm and Lagrangian dual method, respectively. Numerical results demonstrate the effectiveness of the proposed algorithm.
Inulinase immobilization on polyethylene glycol/polypyrrole multiwall carbon nanotubes producing a catalyst with enhanced thermal and operational stability

This paper describes the development of a simple method for mixed non‐covalent and covalent bonding of partially purified inulinase on functionalized multiwall carbon nanotubes (f‐MWCNTs) with polypyrrole (PPy). The pyrrole (Py) was electrochemically polymerized on MWCNTs in order to fabricate MWCNTs/PPy nanocomposite. Two multiple forms of enzyme were bound to N‐H functional groups from PPy and ‐COO− from activated MWCNTs to yield a stable MWCNTs/PPy/PEG immobilized preparation with increased thermal stability. Fourier transform infrared (FTIR) spectroscopy and scanning electron microscopy (SEM) were used to confirm functionalization of nanoparticles and immobilization of the enzyme. The immobilization yield of 85% and optimal enzyme load of 345 μg protein onto MWCNTs was obtained. The optimum reaction conditions and kinetic parameters were established using the UV‐Vis analytical assay. The best functional performance for prepared heterogeneous catalyst has been observed at pH 3.6 and 10, and at the temperatures of 60 and 80ºC. The half‐life (t1/2) of the immobilized inulinase at 60 and 80ºC was found to be 231 and 99 min, respectively. The reusability of the immobilized formulation was evaluated based on a method in which the enzyme retained 50% of its initial activity, which occurred after the eighteenth operation cycle.
Integrated information systems: The influence on process performance in management accounting

The main argument within management accounting for why integrated information systems create value has been that they increase process efficiency. However, the implementation of more sophisticated information systems also changes the relation-ship between the manager and the management accountant. The aim of this thesis is to determine if improved relationship quality between the manager and the management accountant is one mechanism by which integrated information systems improve the process performance in management accounting. I used structural equation modeling for a sample of 406 valid respondents consisting of management accountants from various industries. The analysis shows that integrated information systems indeed also create value through a better relationship quality between the manager and the management accountant.Keywords: Integrated information systems, Management accounting, Process performance, Structural equation modelling
The Influence Model of Online Social Interactions and its Learning Algorithms

This paper models the sequential states of each interaction participant and their corresponding information seeking actions with a Hidden Markov Model (HMM), and then proposes a common framework with the Influence Model to analyze the dynamic inter influencing relationships of all participants on selecting material or seeking desired information from digital libraries. Furthermore, an incremental gradient based algorithm is presented in this paper for the training problem of the above model. The experimental results show that authors’ model and its learning algorithm can effectively characterize the influences people have on each other during online social interactions.
Improving SRAM FPGA Radiation Reliability Through Low-Level TMR Implementation

—Mitigation techniques, such as TMR with repair, are used to reduce the negative effects of radiation on FPGAs deployed in space environments. While these techniques increase the robustness of the device, there is still room for improvement in the range of 100 to 1,000x. These improvements can be realized through the low-level implementation of the placement and routing on the device. This work has implemented a wide variety of techniques to realize these gains, achieving an overall improvement of 57,443x through fault-injection testing and an improvement of 350x in radiation testing.
Identifying and Prediction of Events of Critical Public Domain using Social Sensor Big Data

- Public infrastructure systems provide many of the services that are critical to the health, functioning, and security of society. Many of these infrastructures, however, lack continuous physical sensor monitoring to be able to detect failure events or damage that has occurred to these systems. We propose the use of social sensor big data to detect these events. We focus on two main infrastructure systems, transportation and energy, and use data from Twitter streams to detect damage to bridges, highways, gas lines, and power infrastructure. Through a three-step filtering approach and assignment to geographical cells, we are able to filter out noise in this data to produce relevant geo-located tweets identifying failure events. Applying the strategy to real-world data, we demonstrate the ability of our approach to utilize social sensor big data to detect damage and failure events in these critical public infrastructures.
Hetero-N-Coordinated Co Single Sites with High Turnover Frequency for Efficient Electrocatalytic Oxygen Evolution in an Acidic Medium

The development of noble-metal-free, acid-compatible oxygen electrocatalysts and monitoring their active sites’ evolution under working conditions are crucial for global renewable energy storage and conversion. Here, we present a new type of hetero-N-coordinated Co (HNC-Co) single sites, with Co active centers bonding to hetero pyridinic- and amino-N ligands, as an efficient oxygen evolution reaction (OER) electrocatalyst in an acidic medium. The atomically dispersed HNC-Co electrocatalyst could effectively oxidize water at a quite low overpotential of 265 mV at 10 mA cm–2 in 0.5 M H2SO4 solution with an ultrahigh turnover frequency of 2.8 s–1 and a huge mass activity of 7.6 A mg–1, ∼80–240 times that of commercial IrO2. By using operando synchrotron infrared spectroscopy, a potential-driven active site evolution of H2N–(*O–Co)–N4 is observed for the first time during the OER process, which greatly promotes the surface oxo-species transformation for efficient acidic OER catalysis.
Application of General Item Bank in Auto-generating Paper Based on GA

This paper analyses the problem of auto generating paper and discusses the multi-object parameter optimizing problem with restrictions which solved with genetic algorithm,It also makes some improvements to the tradition genetic algorithm.The result of the experiment shows that the improved genetic algorithm has high quality and efficiency.It matches the thought of the tiny evolution; It is an applicable method with satisfactory performance.
EVALUATION OF FREE PLATFORMS FOR DELIVERY OF MASSIVE OPEN ONLINE COURSES (MOOCS)

For the hosting, management and delivery of Massive Open Online Courses (MOOC) it is necessary a technological infrastructure that supports it. Various educational institutions do not have or do not wish to invest in such a structure, possibly because MOOCs are not yet part of official programs of universities, but initiatives by a particular teacher or a research group. Focusing on this problem, this study seeks to identify platforms that make it possible to create, host and provide courses free of charges for the offeror; find in the respective literature, the basic requirements for MOOC platforms and to evaluate the platforms based on the raised requirements. In order to identify the platforms, information was sought in scientific articles and websites dealing with the comparison of platforms and listing the existing MOOC providers. For the definition of evaluation requirements, there was a search in the Web of Science and Scopus databases, looking for the term "Massive Open Online Courses". After applying some filters, 62 works that address platforms and technology were selected for analysis. As a result there is the identification of six platforms that allow the free supply of courses, the proposal for 14 requirements for reviewing them and a frame containing the evaluation of the identified platforms. This assessment is important since it brings knowledge as a basis for selecting a platform that is the most suitable one in terms of the chosen structure and method to store, manage and deliver courses in MOOC format.
Contributions of single and double joint stiffness of human arm during force control

To investigate the motion control mechanism of human arm during force control, shoulder, elbow, and double-joint stiffness were measured by applying a small perturbation, and their contributions to joint torques were estimated. Each joint stiffness greatly altered for the different force direction at hand, and shoulder and elbow single joint stiffness were linearly correlated to each joint torques. By assuming a linear joint stiffness, generated torques were decomposed into torques produced by each stiffness component. This analysis has revealed that the elbow torque was produced complementary by the single and double-joint stiffness, and that the shoulder torque was mainly produced by the shoulder single joint stiffness. Additionally, the double-joint stiffness was linearly correlated to the decomposed elbow joint torques produced by double-joint stiffness. These results suggest that shoulder and elbow torques are separately controlled by different muscles in this task.