Miracle-dz/UniFAR-FTUs huggingface dataset:
Operation Modes Can Affect the Activity of Immobilized Enzyme onto Silk Fibroin Nanofibrous Membrane

Note ] Int. J. Indust. Entomol. Vol. 27, No. (2), pp. 322-325 (2013) 322 323 Immobilization of CT on SF nanofibrous membrane In order to immobilize CT on the SF, the amine groups of SF were activated with glutaraldehye (GA). To one piece of SF nanofibrous membrane, 10% (v/v) GA in 0.2 M sodium carbonate buffer (pH 9.2) was added to activate the SF. The reaction was continued for 1 h at 25oC. The activated SF was washed 2 times with distilled water and 3 times with 0.1 M sodium phosphate buffers (pH 7.4). The activated SF was mounted on the membrane holder and an ice-cold buffer solution of CT (1 mg/mL) in 0.1 M sodium phosphate buffer (pH 7.4) was circulated overnight at 4oC. The unbound CT was washed out 20 mL of ice-cold 0.5 M of NaCl in 0.1 M sodium phosphate buffer (pH 7.4). Further it was washed 30 mL of the same buffer but without NaCl. Quantification and Activity Test of CT The bound CT was measured by bicinchoninic acid assay methods using bovine serum albumin as standard. The amount of bound CT was calculated by subtracting the amount of remaining CT from the initial amount of CT. N-benzoyl-DLtyrosine-p-nitroanilide hydrochloride (BTPNA) was used as substrate of CT. For general purpose, the substrate solution were prepared by mixing 5 mM BTPNA in DMSO, distilled water and 0.1 M sodium phosphate buffer (pH 7.4) in a ratio of 10:15:3, respectively. In order to measure the activity of the immobilized CT, the increase of absorbance at 400 nm was measured using UV spectrometer (UVICON 923, Kontron Instruments, USA). If the value of absorbance exceeded 2 then it was diluted until it reached below 1.5. The activity of immobilized CT was defined as μmol BTPNA hydrolyzed in 1 min by 1 mg of immobilized CT applying an absorbance coefficient of e400 = 9520 M -1 cm -1 . The Michaelis-Menten parameters was calculated by the Lineweaver– Burk plot after reacting enzyme immobilized SF nanofibrous membrane with the substrate solution having different BTPNA concentration. In this case, the final concentration of BTPNA was 0.0625, 0.125, 0.25, 0.5, 1.0 and 2.0 mM. Operation modes of immobilized CT The substrate solution was reacted with enzyme immobilized SF nanofibrous membrane in two modes. For the batch reactor mode, the enzyme immobilized SF nanofibrous membrane nanofibrous membrane and operated in two different systems. First, it was operated like a batch-type reactor, where the enzyme immobilized SF nanofibrous membrane was immersed into the substrate solution. Secondly, the enzyme immobilized SF nanofibrous membrane was mounted on the membrane holder and the substrate solution was passed through the membrane. We compared the Michaelis-Menten parameters of both operations and examined the effectiveness of the membrane reactor. Materials and Methods
exPeriMental inVestigations oF the ParaMeters oF the Jet MilK hoMogeniZer With seParate creaM suPPly

Визначено, що зменшення розміру жирових кульок до рівня клапанних гомогенізаторів забезпечується при діаметрі каналу подавання вершків 0,6 мм і розмірі центрального каналу 2 мм. Встановлено, що основним фактором, що визначає процес диспергування жирової фази молока, є швидкість потоку. Причому зменшення розмірів часток при зростанні швидкості потоку має прямо пропорційний характер. ключові слова: струминний гомогенізатор, роздільна подача вершків, канал подавання вершків, діаметр жирової кульки. Kovalyov a. , samoichuk K. , Palyanychka n. , Verkholantseva V. , yanakov V.
ACREAGE EFFECTS OF DECOUPLED PROGRAMS AT THE EXTENSIVE MARGIN

This analysis utilizes farm-level data to evaluate the extent to which U.S. farm program benefits, particularly the Agricultural Market Transition Act (AMTA) and market loss assistance payments, bring about distortions in production for wheat and barley production in the Northern Great Plains. The issue is important in light of the upcoming WTO negotiations and debate over the distortionary effects of such decoupled ("green-box") payments. Our results suggest that a modest, though statistically significant effect on acreage may have been evoked by AMTA payments. In particular,if the over $45 billion allocated to AMTA payments and market loss assistance had been doubled, wheat acreage may have been 7% greater and barley acreage may have been 12.8% higher. Models of land idling suggest that AMTA payments have a very modest effect on land idling in this region. We note that the nature of our data may result in an upward bias in AMTA and MLA payment effects, such that our analysis provides conservative estimates.
Prevalence of Entamoeba histolytica and Giardia lamblia in District Hangu of Khyber Pakhtunkhwa, Pakistan

Giardia lamblia and Entamoeba histolytica are two important parasites of the gastrointestinal tract causing gastroenteritis in human population. The present study is carried out to check the prevalence of these two parasites in the stream and open well water of district Hangu of Khyber Pakhtunkhwa.200/two hundred sample were examined through PCR which showed 26.5% (53/200) and 22.5%(45\200) positive results for Giardia lamblia and E.histolytica respectively. The PCR product for Giardia lamblia was 163bp HSP (heat shock protein) and for Entamoeba histolytica was135bp small fragment of DNA.
A Broadband Printed Quadrifilar Helical Antenna with a Novel Compact Broadband Feeding Network

A broadband printed quadrifllar helical antenna (BPQHA) integrated with a broadband feeding network for satellite communications is proposed. Using a multiple arm technique, satisfactory antenna characteristics over a wide bandwidth are realized. To feed the antenna, a novel compact broadband feeding network composed of a frequency independent 180 - out-of-phase power divider, two Wilkinson power dividers and two broadband 90 - phase shifters is designed. The measured boresight gain remains positive with a re∞ection coe-cient lower than i11dB over a bandwidth of approximately 26%. The axial ratio is below 1.7dB and the half-power beamwidth is more than 120 - over the same bandwidth. Details of the proposed antenna design are provided and discussed, as well as the experimental results.
MCADNNet: Recognizing Stages of Cognitive Impairment Through Efficient Convolutional fMRI and MRI Neural Network Topology Models

Mild cognitive impairment (MCI) represents the intermediate stage between normal cerebral aging and dementia associated with Alzheimer’s disease (AD). Early diagnosis of MCI and AD through artificial intelligence has captured considerable scholarly interest; researchers hope to develop therapies capable of slowing or halting these processes. We developed a state-of-the-art deep learning algorithm based on an optimized convolutional neural network (CNN) topology called MCADNNet that simultaneously recognizes MCI, AD, and normally aging brains in adults over the age of 75 years, using structural and functional magnetic resonance imaging (fMRI) data. Following highly detailed preprocessing, four-dimensional (4D) fMRI and 3D MRI were decomposed to create 2D images using a lossless transformation, which enables maximum preservation of data details. The samples were shuffled and subject-level training and testing datasets were completely independent. The optimized MCADNNet was trained and extracted invariant and hierarchical features through convolutional layers followed by multi-classification in the last layer using a softmax layer. A decision-making algorithm was also designed to stabilize the outcome of the trained models. To measure the performance of classification, the accuracy rates for various pipelines were calculated before and after applying the decision-making algorithm. Accuracy rates of 99.77% ± 0.36% and 97.5% ± 1.16% were achieved for MRI and fMRI pipelines, respectively, after applying the decision-making algorithm. In conclusion, a cutting-edge and optimized topology called MCADNNet was designed and preceded a preprocessing pipeline; this was followed by a decision-making step that yielded the highest performance achieved for simultaneous classification of the three cohorts examined.
A Survey on the Role of IoT in Agriculture for the Implementation of Smart Farming

Internet of things (IoT) is a promising technology which provides efficient and reliable solutions towards the modernization of several domains. IoT based solutions are being developed to automatically maintain and monitor agricultural farms with minimal human involvement. The article presents many aspects of technologies involved in the domain of IoT in agriculture. It explains the major components of IoT based smart farming. A rigorous discussion on network technologies used in IoT based agriculture has been presented, that involves network architecture and layers, network topologies used, and protocols. Furthermore, the connection of IoT based agriculture systems with relevant technologies including cloud computing, big data storage and analytics has also been presented. In addition, security issues in IoT agriculture have been highlighted. A list of smart phone based and sensor based applications developed for different aspects of farm management has also been presented. Lastly, the regulations and policies made by several countries to standardize IoT based agriculture have been presented along with few available success stories. In the end, some open research issues and challenges in IoT agriculture field have been presented.
A Mechanism to Improve Effectiveness and Privacy Preservation for Review Publication in LBS

Local business service systems (LBSS), as an essential role of location-based service (LBS), have been gaining tremendous popularity in our daily life. Individuals’ reviews in these systems are very important as they not only contribute to building reputations for businesses but also play a guiding role for consumers. However, users’ privacy disclosure and the effectiveness of reviews are the urgent problems to be solved for the further development of LBSS. This paper proposes a mechanism to improve effectiveness and privacy preservation for review publication. In users’ privacy protection, the mechanism firstly formalizes the model of attackers, then focuses on the identification or inference attack caused by reviews. For improving the effectiveness of reviews, the mechanism introduces users’ reputation scores to rank the reviews. We evaluate our mechanism thoroughly by extensive experiments, and the results validate that our mechanism can achieve a better performance.
Investigations of the properties of solutions of impulsive differential systems in the linear approximation

In work [1], two-parametric scale increasing functions were first considered to investigate the problem of stability of solutions of the nonlinear system dx/dt = A(t)x + F (t, x) in the linear approximation dy/dt = A(t)y (shorted system). The Cauchy matrix of the shorted system satisfies such an estimate: ‖C(t, τ)‖ 6 c exp[α(t − τ)][t/τ ] , for τ > 1, where α > α + ε, ε > 0, α = max k αk(k = 1, 2, . . . , n), αk = lim t→∞ t ln ‖yk(t)‖, k = 1, n, (αk is the characteristic index of a Lyapunov nontrivial solution yk(t) of the shorted system), β > β = max k βk, k = 1, n, where the characteristic degree by Lyapunov βk = lim t→∞ [(ln t) ln{‖yk(t)‖ exp[−αkt]}], k = 1, n. In work [2], the author investigated the problem of stability by Lyapunov of solutions of a nonlinear system in the linear approximation by using an estimate of the Cauchy matrix of the shorted system of such a type: ‖C(t, τ)‖ 6 η(t)l(τ), η(t) : R → R, η(t) ∈ C(R), l(τ) ∈ C(R). Later on, Borysenko and Martynyuk (Mat. Fizika, 1980, N 2) used this estimate to investigate, in the linear approximation, the problem of practical stability (by Chetaev; uniform, attractive) of solutions of a nonlinear regular system with nonlinearities on the right-hand side of the system either the Lipschitz or Hölder type (the evolution of processes which describe the system can be either finite or infinite). The estimate from [2] was also used to estimate the Cauchy matrix of a system of variations and to investigate the problem of stability of solutions of a nonlinear system in the nonlinear approximation [see Mat. Fizika, 1981, N 1 (Borysenko)]. These results are generally based on the method of integral inequalities for continuous functions [3] and its applications. In 1983 (Ukr. Math. Journ., N 2), Borysenko considered a generalization of the idea of Demidovich [1] by using the two-parametric scale of increasing functions to investigate the properties of solutions of nonlinear impulsive differential systems in the linear approximation (linear impulsive differential systems) and used the following estimate of the Cauchy matrix of an impulsive shorted system: ‖C(t, t0)‖ 6 ce [t/t0] , where c, α, and β are some constants, and t > t0 > 1. In the monograph by Lakshmikantham, Bainov, Simeonov [4], the problem of stability by Lyapunov of solutions of the impulsive nonlinear differential system under a pulse influence at fixed time moments,
CONSERVATION TILLAGE TOMATO AND COTTON PRODUCTION SYSTEMS IN CALIFORNIA

Despite increases in conservation tillage (CT) pr oduction in other regions of the US during the past decade, less than 0.3% of the acr eage in California’s San Joaquin Valley is curr ently farmed using CT practices. Preplant tillage operations typically account for 18 – 24% of overall production costs for annual cr ops grown in the
Remote Monitoring of Biomedical Signal

The remote monitoring of the biomedical signal is an important tool for assessing the quality of life, control and prevention of diseases. In this research, we developed and validated a remote monitoring system for prevention and health promotion. The system architecture is composed of 3 main modules: a) interface for recording food intake and monitoring physical activity and heart rate frequency by a mobile application; b) interface for insert anthropometric assessment data of patient; c) web interface where all data is remotely shown through reports with information that can assist in preventive health actions. The study involved 70 children aged between 8 and 12 years. They were monitored for 4 months by the app installed in the children's own smartphones. Significant differences were observed in the frequency domain and nonlinear heart rate variability variables between each anthropometric group. Moreover, within the same group, there were also differences between night-morning and afternoon/evening time. Being the biggest variation in the frequency domain parameters during afternoon/evening time for the obese group.
Forecasting with Factor Models: A Subset Problem

This paper evaluates a modification done on the DI framework of Stock and Watson (2002). The regressors used for PCA are first evaluated for their predictive power. As there are several techniques to create such subsets, five are used of which two are hard thresholding and three are soft thresholding methods. The 1, 6, 12 and 24 month ahead point-forecasts are then compared to a 3 factor benchmark with factors constructed from the complete dataset. Results show that selecting relevant predictors before applying principal component analysis yields improved forecasts.
On the Timing of Separatist Conflict

We study the endogenous timing of separatist conflict, that is, a situation in which two regions fight against each other in order to force the border configuration they prefer. Assuming that incentives for secession are driven by the traditional trade-off between economies of scale and heterogeneity of preferences, we show that the only equilibrium timing of the conflict game is a sequential one, and is such that both regions are active in the conflict (i.e. there is no deterrence in equilibrium). More specifically, the separatists take the lead in an efficient union, whereas the unionists take the lead when seceding is the socially efficient outcome. In turn, the properties of total conflict intensity are very different depending on whether the union is efficient or not. The equilibrium timing of the conflict is also the one that maximizes welfare.
Bayesian inference for stochastic volatility models using the generalized skew-$t$ distribution with applications to the Shenzhen Stock Exchange returns

In this paper, we propose a new stochastic volatility model based on a generalized skew-Student-t distribution for stock returns. This new model allows a parsimonious and flexible treatment of the skewness and heavy tails in the conditional distribution of the returns. An efficient Markov chain Monte Carlo (MCMC) sampling algorithm is developed for computing the posterior estimates of the model parameters. Value-at-Risk (VaR) and Expected Shortfall (ES) forecasting via a computational Bayesian framework are considered. The MCMC-based method exploits a skewnormal mixture representation of the error distribution. The proposed methodology is applied to the Shenzhen Stock Exchange Component Index (SZSE-CI) daily returns. Bayesian model selection criteria reveal that there is a significant improvement in model fit to the SZSE-CI returns data by using the SV model based on a generalized skew-Student-t distribution over the usual normal and Student-t models. Empirical results show that the skewness can improve VaR and ES forecasting in comparison with the normal and Student-t models. We demonstrate that the generalized skew-Studentt tail behavior is important in modeling stock returns data.
Modeling of Heat Source inside MOSFET Under HPEMP Based on Electro-thermal Analysis

The electro-thermal coupled process inside semiconductor device under high power electromagnetic pulse (HPEMP) is an important cause which leads electronic circuits to failure. The parameters of position and structure of heat source inside a real device play key roles in the analysis of thermal failure. In this paper, the parameters of heat source inside an 180 nm n-type metal-oxide-semiconductor field-effect transistor (MOSFET) under HPEMP are analyzed by an electro-thermal coupled method. Distributions of temperature, electric field and carrier concentration inside MOSFET are analyzed quantitatively, and the position and structure parameters of heat source are derived. This analysis is useful for further failure estimating of MOSFET under HPEMP.
Particle-Crushing Characteristics and Acoustic-Emission Patterns of Crushing Gangue Backfilling Material under Cyclic Loading

In solid backfilling coal mining (SBCM), the crushed gangue backfilling material (CGBM) is generally compacted circularly by a compaction machine in order to reduce its compressibility. In this cyclic compaction process, the particles are crushed, which has a significant effect on the deformation resistance of CGBM. However, the deformation resistance of CGBM is critical for controlling overburden strata movement and ground surface subsidence. This study implemented an experimental approach to investigate the particle-crushing characteristics and acoustic-emission (AE) characteristics of CGBM during constant-amplitude cyclic loading (CACL). At the same time, the relationship between particle crushing and AE signals was established. The results showed that the gangue particles were generally in the shape of irregular convex polyhedrons with more edges and angles that were prone to breakage. It also demonstrated that both the crushing ratio (Bg) and the newly produced fine granule content increased with the cyclic loading times. The content of newly generated fine particles can reflect the particle-crushing conditions to a certain extent. What is more, it was found that the CGBM samples exhibited an apparent Felicity effect during CACL, and AE signals were the most active during the first loading cycle. The crushing ratio of CGBM was highly correlated to the AE signals, which indicated that AE signals can be used to reflect the particle-crushing situation of CGBM. This study is of great significance for obtaining an in-depth understanding of the mechanical properties of CGBM, as well as providing guidance for the engineering practice of SBCM.
HDMI Cable Modeling and Analysis with TDR Data

This paper describes HDMI cable modeling process based on TDR/T data. Frequency domain transmission parameters can either measured directly using TDT or can be approximated from TDR data using a measurement-based model. With the TDR approach, after good correlation is achieved between measured and HSPICE circuit simulation data for both time and frequency domains in open-ended structure, the circuit model then can be terminated with 50Ohm terminations to approximate S-parameters. The transmission characteristics of the HDMI cable assembly can be effectively obtained from the circuit model and then analyzed with an eye diagram. A measurement-based model for a short cable can be used to predict behavior of a longer cable.
Minimizing Energy for Caching Resource Allocation in Information-Centric Networking with Mobile Edge Computing

Cache resource allocation is the main challenging and practically important issues of Information-Centric Networking (ICN). Although many studies have exploited optimized cache resource allocation to enhance the caching efficiency and the performance of the network, little attention has been paid to the minimization of user energy consumption. To fill in this gap, this study focuses on optimized allocating cache resource to closer user and form a connected network with minimum time delay and energy consumption. To this end, the caching resource allocation (CRA) problem is decomposed into two sub-problems: BS caching capacity (BSCC) problem and Request MATching (RMAT) problem. We then solve BSCC and RMAT one by one and combine their solutions to address the CRA problem.
In vitro antiviral activity of seeds from Guettarda angelica against avian viruses

2003); and still are source of compounds with the most diverse biological activities including antivirals (Jassim & Naji, 2003; Chattopadhyay & Naik, 2007). The most effective strategy to prevent the viral diseases is the vaccination, which provides resistance to infections, and the use of synthetic antiviral drugs is applied in treatment (Jassim & Naji, 2003; Chattopadhyay & Naik, 2007). However, there is still great need to develop new antiviral drugs that can substitute for or complement the therapy with the currently available drugs. Thus, new antiviral agents from natural sources, especially those that have high efficacy on resistant mutant viral strains and low toxicity to host, are considered to be most promising.
The Fusion of Electroencephalography and Facial Expression for Continuous Emotion Recognition

Recently, the study of emotion recognition has received increasing attentions by the rapid development of noninvasive sensor technologies, machine learning algorithms and compute capability of computers. Compared with single modal emotion recognition, the multimodal paradigm introduces complementary information for emotion recognition. Hence, in this work, we presented a decision level fusion framework for detecting emotions continuously by fusing the Electroencephalography (EEG) and facial expressions. Three types of movie clips (positive, negative, and neutral) were utilized to elicit specific emotions of subjects, the EEG and facial expression signals were recorded simultaneously. The power spectrum density (PSD) features of EEG were extracted by time-frequency analysis, and then EEG features were selected for regression. For the facial expression, the facial geometric features were calculated by facial landmark localization. Long short-term memory networks (LSTM) were utilized to accomplish the decision level fusion and captured temporal dynamics of emotions. The results have shown that the proposed method achieved outstanding performance for continuous emotion recognition, and it yields 0.625± 0.029 of concordance correlation coefficient (CCC). From the results, the fusion of two modalities outperformed EEG and facial expression separately. Furthermore, different numbers of time-steps of LSTM was applied to analyze the temporal dynamic capturing.