Miracle-dz/UniFAR-FTUs huggingface dataset:
INVESTIGATING THE EFFECTS OF DIFFERENT SOFTENERS ON PILLING PROPERTIES AND DURABILITY TO WASHING OF BAMBOO KNITTED FABRICS

Havlanma ve boncuklanma problemleri, orme kumaslarin baslica problemlerinden birisidir. Kumaslardaki boncuklanmayla ilgili olarak yumusaticilarin cesitli etkileri bulunmaktadir. Bu calismanin amaci, bambu orme kumaslarda farkli yumusaticilarin boncuklanma ozellikleri uzerine etkisini sistematik bir sekilde arastirmaktir. Ayrica, 5, 10 ve 20 kez yikamalardan sonra kullanilan yumusaticilarin yikamaya karsi dayanikliliklari da incelenmistir. Bu amacla, oncelikle % 100 bambu orme kumaslar uretilmistir. On terbiye islemleri ve boyamadan sonra yedi farkli yumusatici emdirme yontemiyle kumaslara aktarilmistir. Daha sonra, tum islem gormemis ve islem gormus kumaslar Wascator’de yikanmistir. Yikama donguleri 5, 10 ve 20 olarak secilmistir. Sonuc olarak, yumusaticilarin genel olarak bambu orme kumaslarda boncuk olusumunu azalttigi ve yumusaticilarin etkisinin olumlu oldugu bulunmustur. Yikama oncesinde yumusaticilar arasinda yumusatici S4 (katyonik yumusatici) ve yumusatici S6 (karbamino turevi ve mikro silikon karisimi) en iyi sonuclari vermistir. Bambu orme kumaslarda yikama sirasindaki yogun mekaniksel etki sebebiyle coklu yikamalar, boncuk olusumunda artisa sebep olmustur.
Phytoplankton communities in aquaculture system (integration of shrimp and seaweed)

ABSTRACT Knowledge about phytoplankton communities is important for aquaculture due to their influence on environmental variables. The goal of the study was to evaluate the ecological effect of seaweed Gracilaria birdiae at three different densities: 2.5 (LG2.5); 5.0 (LG5.0) and 7.5 kg m−3 (LG7.5), on water quality variables and the phytoplankton communities in integrated aquaculture systems (shrimp and seaweed) with a control (without seaweed) (LB) using biofloc technology. Settleable and total suspended solids were significantly correlated with the phytoplankton groups. In addition, orthophosphate was the main variable controlling phytoplankton growth and gross primary production. No significant differences were identified among the treatments in terms of the phytoplankton assemblages (p > 0.05) but differences were found between the communities (ANOSIM, R global = 0.873) in relation to the days of the experiment. However, the LG2.5 treatment had higher diversity and lower species dominance, as well as higher productivity and final shrimp weight. The results indicate that seaweed inhibit phytoplankton growth, mainly of toxic species. They suggest that phytoplankton composition in integrated aquaculture systems in the presence of seaweed at a density of 2.5 kg m−3 is more diversified and provides better water quality and shrimp performance by inhibiting the abundance of harmful species.
Fast and Simultaneous Determination of Soil Properties Using Laser-Induced Breakdown Spectroscopy (LIBS): A Case Study of Typical Farmland Soils in China

Accurate management of soil nutrients and fast and simultaneous acquisition of soil properties are crucial in the development of sustainable agriculture. However, the conventional methods of soil analysis are generally labor-intensive, environmentally unfriendly, as well as time- and cost-consuming. Laser-induced breakdown spectroscopy (LIBS) is a “superstar” technique that has yielded outstanding results in the elemental analysis of a wide range of materials. However, its application for analysis of farmland soil faces the challenges of matrix effects, lack of large-scale soil samples with distinct origin and nature, and problems with simultaneous determination of multiple soil properties. Therefore, LIBS technique, in combination with partial least squares regression (PLSR), was applied to simultaneously determinate soil pH, cation exchange capacity (CEC), soil organic matter (SOM), total nitrogen (TN), total phosphorus (TP), total potassium (TK), available phosphorus (AP), and available potassium (AK) in 200 soils from different farmlands in China. The prediction performances of full spectra and characteristic lines were evaluated and compared. Based on full spectra, the estimates of pH, CEC, SOM, TN, and TK achieved excellent prediction abilities with the residual prediction deviation (RPDV) values > 2.0 and the estimate of TP featured good performance with RPDV value of 1.993. However, using characteristic lines only improved the predicted accuracy of SOM, but reduced the prediction accuracies of TN, TP, and TK. In addition, soil AP and AK were predicted poorly with RPDV values of < 1.4 based on both full spectra and characteristic lines. The weak correlations between conventionally analyzed soil AP and AK and soil LIBS spectra are responsible for the poor prediction abilities of AP and AK contents. Findings from this study demonstrated that the LIBS technique combined with multivariate methods is a promising alternative for fast and simultaneous detection of some properties (i.e., pH and CEC) and nutrient contents (i.e., SOM, TN, TP, and TK) in farmland soils because of the extraordinary prediction performances achieved for these attributes.
A Study on Product Search Service using Feature Point Information based on Image

With the development of ICT technology and the promotion of smartphone penetration, purchasing services that purchase various products through online market are being activated. In particular, due to advances in storage and delivery technology, sales of short food materials can be purchased online. Therefore, in this paper, we propose an integrated solution that enables advertisement effect, ordering and delivery through a purchase service even if there is no sales knowledge and sales network in a small shopping mall where only offline sales can be performed. The proposed system is able to efficiently view the product information by category through image search for the product that the user desires, so that the seller of the registered product can efficiently sell without any additional advertisement.
Smartphone interventions for long-term health management of chronic diseases: an integrative review.

INTRODUCTION Long-term health management is challenging for the rapidly growing number of patients with chronic diseases. Smartphone interventions offer promising solutions. This article presents features of smartphone interventions for long-term chronic condition management, illustrating how these applications benefit patients with chronic diseases. MATERIALS AND METHODS Systematic searches for smartphone health interventions were conducted in five publication databases. Articles were included only if (1) the smartphone application (app) was exclusively developed for patients with chronic diseases and (2) the article incorporated a defined outcome measurement to evaluate the effects of the implemented intervention. Sixteen articles were included in the final review, including studies in diabetes, mental health problems, overweight, cancer, and chronic obstructive pulmonary disease. RESULTS These studies found that the smartphone intervention was a completely or at least partially effective tool to assist in managing some chronic diseases. With the help of health-related smartphone apps, patients with chronic conditions (1) felt secure in the knowledge that their illnesses were closely monitored, (2) participated in their own health management more effectively, and (3) felt that they had not been forgotten by their doctors and were taken good care of even outside the hospital/clinic. CONCLUSIONS However, there are limited smartphone apps for the long-term health management of chronic diseases. More smartphone apps need to be developed to help people manage chronic diseases.
A Review of Asphalt Binders Characterized by X-ray Diffraction

Asphalt binder research papers characterized by X-ray diffraction are reviewed. The Xray results reveal the aromaticity and crystallite size parameters of asphaltene in asphalt binders as reported in the research literature. The research data is discussed in terms of asphalt molecular structure on a length scale, methodology, and petroleum oil fields. Box plots and summary statistics created for each parameter are compared and discussed as they relate to eleven data sets from various asphaltene-crude-oil-geological-regions.
Influence of nitrogen sources on growth of thraustochytrids in waste water from the demineralization of cheese whey

An experimental design was ued to optimize the growth of two thraustochytrids, (Schizochytrium limacinum PA-968 and Japonochytrium marinum AN-4), on different nitrogen sources (yeast extract, corn steep liquor, ammonium sulphate) supplemented into saline waste water from the demineralization of cheese whey. Yeast extract was found to be the most suitable complex nutrient source. Nitrogen limitation was found to increase the lipid content in shake flask cultures of thraustochytrids by 12.7–22.4% w/w. The maximum total lipid content (79.1% w/w) and docosahexaenoic acid productivity (0.465 g/l per day) were achieved by J. marinum AN-4 in shake flask cultures. Fed-batch cultures of J. marinum AN-4, under conditions of nitrogen limitation, yielded biomass with a lower lipid content (72.1% wt.) but higher docosahexaenoic acid productivity (1.43 g/l per day). These results provide proof of concept that fed-batch cultivation of thraustochytrids, combined with nitrogen limitation, can be an appropriate strategy for the productive use of saline waste water from the dairy industry.
How You Learn Depends on When You Learn: Experimental Evidence From Cournot Contests

We conducted controlled laboratory experiments to investigate how humans adapt the decision rule (DR) they use in repeated strategic interactions in light of new information becoming available. We do so by providing -- along different paths -- more and more information over time, so as to trigger adoption and abandonment of different DRs along the way. We focus on 'Cournot contest' games and consider the three leading DRs in game theory: payoff-based learning, best-response, and imitation. Our study reveals path dependence in how people use heuristics in strategic decision-making, falsifying the salient assumption that DRs are triggered by the available information alone.
Optical and computational approaches for mapping brain activity and structure

Neuroscience always has been a heavily technology-starved field that has been often revolutionized with the rise of a new technology; and arguably the future advancement of neuroscience will also depend largely on the development of new technologies that allow acquiring new data sets that can provide deeper insights into the brain. While there is no universal agreement as to what data sets are needed to fully reveal the underlying principles of brain computation, neurons will certainly serve as an important layer to study the brain considering their discreteness and electrical characteristics. In other words, seeing a brain as a circuitry that is made of the neurons, it is important to study the relation between the brain's structure and its function at the neuronal level. Unfortunately, a brain is a huge network that consists of a huge number of neurons which makes it difficult to see the "big picture" while retaining the single neuron resolution. The aim of this study is to the develop such technologies that allow to see and analyze the large network's structure and dynamics with the single neuron resolution. The core strategy is to use optical microscopy to acquire the raw data and to infer the information of our interests with computational techniques with designing both optical and computational parts with each other in mind to maximize the synergy. The first part of the thesis describes the development and application of computational imaging techniques to monitor the brain activity in 3-D which allowed us to see how the neurons interact at an unprecedented speed. The second part describes a computational approach to extract a wiring diagram of a brain from an optical image of the brain rather than an electron microscopy image, as optical microscopy is undergoing rapid development and is likely to outperform electron microscopy in terms of scalability which will be an important criterion to map the whole brain. These will be the tools of great utility in neuroscience that can generate rich data sets that will be of wide interests to system neuroscientists as well as cellular/molecular neuroscientists.
INDOOR/OUTDOOR CORRELATIONS REGARDING INDOOR AIR POLLUTION WITH PARTICULATE MATTER

This paper presents the results of a case study conducted between 2.04 and 24.04. 2013 in order to establish the most relevant indicators that characterize the influence of outdoor air pollution, with particulate matter having a nominal diameter less than 2.5 m (PM2.5), on the quality of indoor air from a new building. The tests consisted in simultaneous determination of the daily average PM2.5 concentrations at four indoor sites and at one outside, nearby the building. The average PM2.5 concentration was 38.41 7.4 g/m3, but only 70% of the outdoor performed tests were above the daily limit of 35 g/m3, set by the U.S. Environmental Protection Agency. The indoor air pollution with PM2.5 was lower than outdoor with an average concentration of 21.78 6.22 g/m3. Both Pearson s statistical correlation analysis and linear regression analysis showed a good direct correlation between indoor and outdoor PM2.5 concentrations, the proper insulation of the building and the absence of major indoor sources of PM2.5 particles. The results of this study demonstrated that for a new building the indoor/outdoor (I/O) ratio and infiltration factor (Fin) could give a correct estimation of the outdoor air pollution influence on the indoor air quality. Further information could be provided by statistical correlation and linear regression analysis; the value of the intercept could be a good indicator of the presence of indoor sources.
Monte Carlo Study of Slot-waveguide Liquid Crystal Phase Shifters

Abstract We present detailed Monte Carlo simulations of a simple model of a nematic liquid crystal slot waveguide shifter, investigating the effect of an applied electric external field. The simulations are based on the Lebwohl-Lasher lattice spin model with boundary conditions chosen to mimic the planar alignment as in Silicon Organic Hybrid waveguides and the homeotropic anchoring appropriate for Polydimethylsiloxane polymer walls. The external field is modeled by adding a term to the Hamiltonian which describes its coupling to the mesogenic molecules. We have investigated the effect of the external field on the optical transmission and the ordering across the cell.
Channel Selection Method for EEG Emotion Recognition Using Normalized Mutual Information

Electroencephalography (EEG) signals can reflect activities of the human brain and represent different emotional states. However, recognizing emotions based on full-channel EEG signals will lead to redundant data and hardware complexity, thus it is not suitable for designing wearable devices for daily-life emotion recognition. This paper proposes a channel selection method to select an optimal subset of EEG channels by using normalized mutual information (NMI). Compared with other methods, the proposed method solves the problem of obtaining a higher recognition rate while reducing EEG channels sharply. First, EEG signals are sliced into fixed-length pieces with a sliding window, and short-time Fourier transform is adopted to capture EEG spectrogram. Then inter-channel connection matrix is calculated based on NMI, and channel reduction is conducted by using thresholding and connection matrix analysis. The experiments are based on the widely-used emotion recognition database DEAP. It can be derived from the experimental results that the proposed method can select optimal EEG channel subsets to a certain number while maintaining high accuracy of 74.41% for valence and 73.64% for arousal with support vector machines. Further analysis also reveals that the distribution of the selected channels is consistent with cortical areas for general emotion tasks.
Lignin-KMC: A Toolkit for Simulating Lignin Biosynthesis

Lignin is an abundant biopolymer of phenylpropanoid monomers that is critical for plant structure and function. Based on the abundance of lignin in the biosphere and interest in lignin valorization, a more comprehensive understanding of lignin biosynthesis is imperative. Here we present an open-source software toolkit, LIGNIN-KMC, that combines kinetic Monte Carlo and first-principles calculations of radical coupling events, which enables modeling of lignin biosynthesis in silico. Specifically, lignification is simulated using the Gillespie algorithm with a graph representation of the lignin fragments and with rates derived from density functional theory calculations of individual fragment couplings. Using this approach, we confirm experimental findings regarding the impact of lignification conditions on final polymer structure and identify new features of fundamental interest to plant cell wall biosynthesis including (1) the monolignol supply rate under in planta lignification conditions likely varies as a function of evolutionary stresses; (2) under conditions of low monolignol supply rates, increasing the fraction of sinapyl alcohol increases the depolymerization yield of monomers upon ether bond cleavage; and (3) by including calculated energetics of caffeyl alcohol homopolymers, the model accurately predicts C-lignin structures. These examples not only highlight the robustness of our modeling framework, but also motivate future studies of new lignin types, unexplored monolignol chemistries, and lignin structure predictions, all with an overarching aim of developing a more comprehensive, molecular understanding of native lignin, which, in turn, can advance the biological and chemistry communities interested in this important biopolymer.
A Robotic System With Multichannel Flexible Parallel Manipulators for Single Port Access Surgery

Robot-assisted single port access surgery (SPAS) brings significant benefits to the patients. However, it is challenging due to the limited incision size and requirements in precision, load capacity, and dexterity. To address these challenges, this paper presents a multichannel SPAS robotic system consisting of two channels of 5-degree-of-freedom (DOF) flexible manipulators and an endoscope channel. Each channel of the manipulators is designed based on a 3-DOF parallel mechanism with three sets of super-elastic Ni–Ti rods and universal joints. This design optimizes the structure for flexibility and safety considerations with a simplified structure compared with conventional parallel mechanisms. Flexible shafts are used for torque transmission from the actuation unit, allowing the motors to be farther away from the patient-side robotic system. The kinematics of the manipulator is derived, and then the reachable workspace and dexterity are analyzed. Furthermore, a prototype of the proposed robotic system is presented and evaluated through adequate experiments. The flexibility of the manipulator is verified via stiffness characterization test. The results of the accuracy tests confirmed that the robotic system can implement manipulation arm with acceptable accuracy. The feasibility and effectiveness of applying the robotic system to the practical operation are also demonstrated through experimentations.
Mapping ACL/VF to a Java Environment: A Feasibility Study

In this thesis we focus on an alternative approach to MBT, namely scenario based testing, which we consider in the context of runtime validation. More specifically, we address scenario monitoring and validation in ACL/VF. The two current versions of the ACL/VF have a number of issues that prevent them being usable solutions. Upgrading the original version to a more recent version of . NET would amount to a complete rewrite. A second version was implemented and tested with the JavaMOP framework. Experimentation with this second solution however revealed it cannot manage and monitor multiple scenarios running simultaneously! Due to these difficulties, the immediate research question for ACL/VF is to determine whether it can be implemented in a commonly-used environment such as the core Java/J2EE framework. This thesis provides an affirmative answer to this question: a case study is used to illustrate the proposed approach to monitoring ACL scenarios using Java threads
ESTIMATION OF STABILITY PARAMETERS OF POTATO GENOTYPES UNDER DIFFERENT SOWING SEASONS

This investigation was carried out in Vegetable Private Farm at Al-Salhyia, Fakous District, Sharkia Governorate, Egypt. Eight potato genotypes were evaluated for tuber yield and its components as well as tuber dry matter (%) under six varied environments which are the combination between three years 2013/2014, 2014/2015 and 2015/2016 and two sowing seasons i.e., fall and summer. The combined analysis of variance showed highly significant differences between genotypes, environments as well as G×E for all studied traits except for aerial stem No./plant which was insignificant, Phenotypic stability parameters revealed that potato genotypes Horaizon and Spunta were highly adapted to favorable environment. These results reflected the importance of environmental factors on the performance of genotype. According to phenotypic stability, the best cultivars were Horaizon and Caruso in most traits. For genotypic stability parameters, most cultivars considered stable in different studied traits. Horaizon, Hermus, Spunta and Inova were the most desired and stable for additive main effects and multiplicative interaction methods stability value (ASV) and regression coeffient (R) in most traits. The ideal potato culturar was Carus for tuber number/plant, while Hermus was the ideal for average tuber weight, tuber yield/plant, tuber yield/fad. , and tuber dry matter according to genotype + genotype x environment.
Angular momentum regulation may dictate the slip severity in young adults

Falls vastly affect the economy and the society with their high cost, injuries, and mortalities. Slipping is the main trigger for falling. Yet, individuals differ in their ability to recover from slips. Mild slippers can accommodate slips without falling, whereas severe slippers indicate inadequate or slow pre-or post-slip control that make them more prone to fall after a slip. Knowing the discrepancies in different kinematic and kinetic variables in mild and severe slippers helps pinpoint the adverse control responsible for severe slipping and falling. This study examined Center of Mass (COM) height, sagittal angular momentum (H), upper body kinematics, and the duration of single/double phase in mild and severe slippers for both normal walking and slipping to identify their differences and possible relationships. Possible causality of such relationships were also studied by observing the time-lead of the deviations. Twenty healthy young adults walked in a long walkway for several trials and were slipped unexpectedly. They were classified into mild and severe slippers based on their slip severity. No inter-group differences were observed in the upper extremity kinematics. It was found that mild and severe slippers do not differ in the studied variables during normal gait; however, they do show significant differences through slipping. Compared to mild slippers, sever slippers lowered their COM height following a slip, presented higher H, and shortened their single support phase (p-value<0.05 for all). Based on the time-lead observed in H over all other variables suggests that angular momentum may be the key variable in controlling slips.