Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Online Consumer Review and Online Consumer Rating to Consumer Trust and Purchase Decision on E-Commerce Jakmall.Com

:- This research aims to analyze the effect of Online Consumer Review and Online Consumer Rating variables on Consumer Trust and Purchasing Decisions at Jakmall.com. This research uses quantitative research methods with explanatory and survey approaches. The study population are consumers who have purchased products at E-commerce Jakmall.com and the number of research samples is 150 respondents. The sampling method is done by using the Purposive Sampling method. Hypothesis testing proposed in this study carried out with a Structural Equation Model (SEM) test tool using LISREL 8.8 software. The results of the structural model analysis show that the Online Consumer Review and Online Consumer Rating variables have a positive and significant effect on the Consumer Trust. In addition the Online Consumer Rating variable also has a positive and significant effect on Purchasing Decisions, while the Online Consumer Review variable has a positive and not significant effect on Purchasing Decision at Jakmall.com.
Weighted group sparse compressed sensing for parametric function approximation

Motivated by problems arising in uncertainty quantification and high-dimensional parametric PDEs, we review and combine two fairly recent aspects of model-based compressed sensing: namely weighted compressed sensing and block sparsity. Sparse approximation of generalized polynomial chaos has drawn more and more attention recently [1], [2] for the approximation of quantities of interest in uncertainty quantification. It has been proven [6] that solutions to some elliptic and parabolic parametric PDEs enjoy a sparse (or at least compressible) expansion in some polynomial basis and their numerical approximations has been reviewed by various methods based, among others, on downward closed sets and weighted compressed sensing [8], [3], [7]. On the other hand, group sparsity [5] has been known to help in recovering signals that share a common structure. In this note, we want to combine both approaches with the end goal to approximate the full (numerical) solution to a class of elliptic parametric PDEs [4].
The unintended distributional consequences of the 2012 rise in the Mexican minimum wage

In this paper we use Mexico’s 2012 harmonization of Zone B’s minimum wages to those in Zone A as a natural experiment to analyse the effect on the distribution of real earnings. We estimate the effect of the policy change on different points of the earnings distribution by implementing the unconditional quantile regression developed by Firpo et al. (2009). We find evidence of significant effects at the bottom of the earnings distribution, which suggests a small improvement in earnings for the targeted lowest income workers. Interestingly, the model also shows the existence of important lighthouse, or spillover effects on the top percentiles of the distribution, having the effect of widening the wage dispersion. Our results therefore confirm that minimum wages played also a ‘reference’ role in the Mexican labour market. The presence of spillover effects in the formal and informal labour markets challenges the Welch–Gramlich–Mincer Two Sector Model by the estimation of positive effects on both sectors. JEL Classification: J23, J32
Catastrophic climate change under time-inconsistent preferences

We analyze optimal fossil fuel use in an intergenerational model with the risk of a climate catastrophe. Each generation maximizes a weighted sum of discounted utility (positive) and the probability that a climate catastrophe will occur at any point in the future (negative). The model generates time-inconsistency as generations disagree on the relative weights on consumption and catastrophe prevention. As a consequence, future generations emit too much from the current generation’s perspective and a dynamic game ensues. We consider a sequence of models. If the fossil fuel stock is finite, early generations are more conservationist in Markov equilibrium than under commitment in order to smooth fossil fuel use over time. When fossil fuels are expected to become redundant in the near future, early generations may increase or decrease their fossil fuel consumption in Markov equilibrium depending on the utility and threshold distribution functions. When an abundant fossil fuel will remain essential as a production factor, the catastrophe becomes a self-fulfilling prophecy. JEL-Classification: C73, D83, Q54
Supplier selection: an expert system approach

In this work, an expert system has been designed for selecting suppliers in the supply chain management area. A supply chain management system has been designed and an expert system tool has been developed for supplier selection process. Although supply chain management might be established for almost any sector, the automotive sector has been selected for this research. One of the most crucial steps of supply chain management is to determine supplier selection criteria and weigh factors to use during this process. A questionnaire has been implemented in the region of Sakarya among 19 top managers of medium and large sized factories. According to the results obtained from this work an expert system is a suitable tool for selecting suppliers.
Erratum: Periodic substrate structure suppresses spurious response in coupled line filters

Originally published Microwave Opt Technol Lett 54: 2175–2178, 2012. @ 2012 Wiley Periodicals, Inc. Microwave Opt Technol Lett 54: 2446, 2012; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.27101(Original article DOI 10.1002/mop.26999)
Ada: the Intelligent Room

A multidisciplinary team based at the Institute of Neuroinformatics, ETH, Zurich, was responsible for Ada: the intelligent room, an interactive space conceived of as a human being that responded to visitors at Exp02, the Swiss national exhibition at Neuchatel, where it was launched, writes Lucy Bullivant. Copyright © 2005 John Wiley & Sons, Ltd.
Compressed Sensing of Image Sequences via Multiple Total Variation

—Total variation (TV) norm has been widely used in the context of compressed sensing. In this paper, given multiple measurement vectors (MMVs), we study the alternating direction method of multipliers (ADMM) algorithm to solve the multiple TV (MTV) norm minimization problem. In ADMM-MTV, we derive the closed-form solutions of all subproblems to ease implementation. Moreover, ADMM-MTV is able to reconstruct all image signals simultaneously, which is more efﬁcient than the traditional TV norm minimization problem that conducts sparse recovery individually. In addition to computation complexity analysis and comparison, we also verify that the MTV norm outperforms TV norm in terms of two applications: Magnetic Resonance Imaging (MRI) and general image sequence reconstruction.
Rapid Microbe Detection Using Deep Learning

Microbes are microscopic organisms invisible to the naked eye with a significant role in everyday life. The ability to detect and accurately classify them is essential to discover diseases, prescribe medication, keep a healthy lifestyle in general. The main goal of this thesis is develop a deep learning method that can in a fast and accurate way detect a microbial species from short fragments of that species. The architecture was based on a novel NLP architecture called the Transformer, adapted to the microbe detection task and used to obtain compressed representations of the sequenced DNA fragments. Once the compressed representation were found, different classification methods were applied to output predictions of microbial species.
Si-based ultrasmall multiswitching single-electron transistor operating at room-temperature

An ultrasmall single-electron transistor has been made by scaling the size of a fin field-effect transistor structure down to an ultimate limiting form, resulting in the reliable formation of a sub-5 nm Coulomb island. The charge stability data feature the first exhibition of three and a half clear Coulomb diamonds at 300 K, each showing a high peak-to-valley current ratio. Its charging energy is estimated to be more than one order magnitude larger than the thermal energy at room-temperature. The hybrid literal gate integrated by this single-electron transistor combined with a field-effect transistor displays >5 bit multiswitching behavior at 300 K with a large voltage swing of ∼1 V.
PII: S0304-3835(01)00740-6

To search for possible cancer chemopreventive agents from natural sources, we performed primary screening of ten flavanones isolated from plants belonging to Rutaceae and Leguminosae by examining their possible inhibitory effects on Epstein–Barr virus (EBV) early antigen activation induced by 12-O-tetradecanoylphorbol-13-acetate in Raji cells. All of the flavanones tested in this study showed inhibitory activity against EBV, without showing any cytotoxicity. Amorilin (3), which has three prenyl (3-methyl-2-butenyl) side-chains in the molecule, showed the most potent activity. Furthermore, lupinifolin (5) exhibited a marked inhibitory effect on mouse skin tumor promotion in an in vivo two-stage carcinogenesis test. These results indicate that some of these prenylated flavanones might be valuable as potential cancer chemopreventive agents (anti-tumor promoters). q 2002 Elsevier Science Ireland Ltd. All rights reserved.
Improving the Development and Use of Biologically Based Dose Response Models (BBDR) in Risk Assessment

Biologically based dose-response (BBDR) models predict health outcomes (response) resulting from the presence of a toxicant at a biological target (dose). The benefits of BBDR models are many, and research programs are increasingly focusing on mechanistic research to support model development; however, progress has been slow. Impediments to progress include the complexity of dose response modeling, the need for a multidisciplinary team and consistent funding support, and difficulty in identifying and extracting the needed data. Of immediate concern is the lack of transparency of published models to the supporting data and literature, difficulty in accessing model code and simulation conditions sufficient to allow independent replication of results, and absence of well-defined quality criteria. Suggestions are presented to improve the development and use of BBDR models in risk assessment and to address the above limitations. Examples from BBDR models for methylmercury neurotoxicity and 5-fluorouracil embryotoxicity are presented to illustrate the suggestions including what kinds of databases are needed to support model development and transparency, quality assurance for modeling, and how the internet can advance database development and collaboration within the biological modeling community.
Prevalence of Unmet Healthcare Needs in Adolescents and Associated Factors: Data from the Seventh Korea National Health and Nutrition Examination Survey (2016–2018)

Adolescent health is considered the basis of adult health, and the unmet healthcare needs in adolescents are an important issue to be solved. This study, therefore, aimed to explore the prevalence of unmet healthcare needs, and examine its associated factors among adolescents in Korea based on Andersen’s Behavioral Model of Health Services, using data from the Seventh Korea National Health and Nutrition Examination Survey (2016 to 2018). This survey’s data source comprised 12- to 18-year-old adolescents, of which 1425 provided information on their unmet healthcare needs, as well as their predisposing, enabling, and need factors. For statistical analysis, SPSS version 25.0 was used. Descriptive analyses were performed to assess each variable, whereas multiple logistic regression was used to determine the associated factors. The overall prevalence of unmet healthcare needs was 5.5%. The factors that had statistically significant relationships with adolescents’ unmet healthcare needs were: age; stress perceptions; housing types; and perceived health status. Unlike previous studies that presented related factors on vulnerable groups, this study’s results presented unmet healthcare needs and related factors for all Korean adolescents using a national survey dataset. Hence, its findings could provide feedback on current policies, and guide future studies.
FIELD PERFORMANCE OF FRAXINUS ORNUS BAREROOT PLANTS TO DROUGHT STRESS

In this study an experiment was conducted to find out the influence of drought on Fraxinus ornus plant morphology, biomass allocation, architecture of first-order lateral roots (FOLR) and field survival at the early stages of outplanting. Totally 120 undercut bareroot plants were transplanted to field conditions in a Mediterranean area. After establishment, half of the seedlings were kept well-watered (control) while the rest received no other irrigation except natural rainfall (water stress). In the field, measurements were taken after 6 months (before summer), after 8 months (midsummer) and after 10 months (after summer). The results showed that the root biomass, the seedling quality index and the number of first order lateral roots were significantly greater in watered seedlings. The mean length of FOLR increased over time in watered and stressed seedlings as well. However, after the summer period the stressed seedlings had also significantly lower length of FOLR than watered ones. Similarly, the leaf RWC was highly affected by the treatments applied and was found significantly greater in water seedlings during the summer. The first summer period after outplanting was crucial for stressed and watered seedlings as well. Eight months after outplanting the survival rate of stressed seedlings was 45% while that of well-watered seedlings was 75%. There is much evidence for the positive relationship between root biomass, seedling quality index and number and length of FOLR with seedlings survival.
Machine Learning Techniques for Sentiment Analysis: A Review

– Social media platforms and micro blogging websites are the rich sources of user generated data. Through these resources, users from all over the world express and share their opinions about a variety of subjects. The analysis of such a huge amount of user generated data manually is impossible, therefore an effective and intelligent technique is needed which can analyze and provide the polarity of this textual data. Multiple tools and techniques are available today for automatic sentiment classification for this user generated data. Mostly, three approaches are used for this purpose Lexicon based techniques, Machine Learning based techniques and hybrid techniques (which combines lexicon based and machine learning based approach). Machine Learning approach is effective and reliable for opinion mining and sentiment classification. Many variants and extensions of machine learning techniques and tools are available today. The purpose of this study is to explore the different machine learning techniques to identify its importance as well as to raise an interest for this research area.
Introducing Dynamic Capability in Photovoltaic System Maximum Power Point Tracking Algorithm

Photovoltaic (PV) power has become the most attractive choice among various renewable resources. However, one major challenge associated with PV interfacing is its intermittent output characteristic which varies dramatically with the operating conditions. Thus designing an effective maximum power point tracking (MPPT) algorithm is a key aspect for optimizing PV system performance. Numerous MPPT algorithms have been proposed earlier having their own specific advantages. However, these are found to have two major limitations which have to be essentially addressed. Firstly, they become ineffective in the dynamic conditions where there is rapid change in environmental parameters like insolation and temperature. Secondly, they fail to discriminate between global and local peaks under partial shading conditions. Therefore, to achieve a reliable and efficient system operation, this paper presents an optimized algorithm which enhances the model-based (MB) tracking capability so as to overcome both the above deficiencies. On the basis of modified governing equations and incorporating the precised estimation of parameters, it predetermines the MPP analytically. First simulated results are obtained where it is tested for dynamic variations of all the three parameters. Then the experimental validation is carried out on a 2 KW installed panel where real time data is recorded through CR1000 data logger and environmental parameters are sensed with elements like pyranometer, humidity sensor, etc. Numerous experimental results are analyzed for tracked MPP in the dynamic conditions, which are then summarized in tabular forms. These are finally plotted and compared with simulated results to illustrate the effectiveness of proposed MB algorithm.
Timing jitter in ultrahigh-speed dispersion-managed soliton systems

An analytical theory is presented which demonstrates the timing jitter induced by amplifier noise in ultrahigh-speed dispersion-managed soliton systems when the Raman effect and third-order dispersion (TOD) are considered. The analysis indicates that Raman jitter remains a potential problem for picosecond and subpicosecond pulses. Positive residual TOD can enhance the timing jitter caused by the combined action of TOD and Raman effect, while vice versa for negative residual TOD.
Effect of continuing care in the management of chronic heart failure and improvement of cardiac function

Objective: To explore the effect of continuing care in the management of chronic heart failure and the improvement of patients’ cardiac function. Methods: In this retrospective study, 120 patients with chronic heart failure were randomly divided into the control group (n=60, patients received discharge instructions before hospital discharge but no intervention after discharge) and the research group (n=60, patients received continuing care after discharge). Patients’ cardiac function, self-care ability, medication adherence, mood state and quality of life at discharge were compared to those at 6 months after discharge. Results: Six months after hospital discharge, the patients in both groups had decreased levels of left ventricular end systolic dimension, left ventricular end-diastolic dimension, and N-terminal pro B type natriuretic peptide and increased levels of left ventricular ejection fraction and cardiac output, and the magnitude of the changes in these markers was greater in the research group than in the control group (all P<0.05). Meanwhile, the scores of Morisky Medication Adherence Scale and Self-Care of Heart Failure Index v6.2 of the research group increased at 6 months after discharge and were higher than those in the control group at the same time point (all P<0.001). Also, the scores of Profile of Mood States reduced, and the scores of Generic Quality of Life Inventory-74 increased in both groups at 6 months after discharge, and the magnitude of changes in the research group was greater (all P<0.05). Conclusion: Continuing care for chronic heart failure patients can markedly improve the cardiac function and quality of life of the patients. It can also significantly reduce patients’ negative emotions and improve the medication adherence and the self-care ability.
Design study and fabrication techniques for high power density microtransformers

This paper presents an investigation into the power density and efficiency achievable from microtransformers suitable for integration on silicon. Results from the design study indicate that high aspect ratio conductors and laminated cores are required to achieve high power density. Fabrication techniques, using thick photoresist, which can be used to achieve high aspect ratios, have been developed and results are presented. Initial test results for the inductance and resistance of the coils are also presented.
Using NOMA Scheme for the Management of Interference and the Improvement of Performance in 5G Networks

The new generation of 5G networks, compared to 4G networks, is a very important example of change in achieving very high frequencies in the carrier with huge bandwidth, high densities with a huge number of antennas and improved quality of services, making effective interference management necessary. In this paper, we present the contribution of the Non-Orthogonal Multiple Access (NOMA) scheme to improving the performance of 5G networks. We refer to the technique of sequential interference cancellation applied to some NOMA formats, compare NOMA and Orthogonal Multiple Access (OMA) formats in terms of the capabilities they offer users and NOMA's significant contribution to Multiple-Input Multiple-Output (MIMO) technology and compare three basic NOMA formats in three different resource and user reporting scenarios. Finally, we present the results of the simulations of the above comparisons and analyze the contribution of each scheme to the improvement of the system performance.
Migraine and Stroke: In Search of Shared Pathways, Mechanisms, and Risk Factors

Migraines are one of the emerging causes of disabilities experienced worldwide, and strokes are the second leading cause of death globally. Migraines with aura have been reported to be associated with a higher risk of ischemic strokes, whereas hemorrhagic strokes are more closely associated with migraines without aura, possible mechanisms that link migraines to strokes. These can be categorized into vascular mechanisms such as vasospasm, endothelial and platelet dysfunction, and alteration in the vessel wall seen in migraineurs, further perpetrated by vascular risk factors such as hypertension and hyperlipidemias. Cerebral hypoperfusion that occurs in migraines can cause an electrical aberrance, leading to a phenomenon known as “spreading depression” which can contribute to strokes. In this review, we discuss bloodstream elevation in procoagulants such as antiphospholipid antibodies, homocysteine, von Willebrand factor, and prothrombin. Maintaining pregnant women who actively experience migraines with aura under close observation may be of some value in achieving better outcomes. Women who experience migraines after starting hormonal contraception are at a higher risk of experiencing strokes and stand to benefit from being switched to non-hormonal methods. In this article, we discuss the mechanisms linking migraines and strokes, briefly discuss the pathogenesis, and explore the risk factors contributing to the association therein. In addition, we examine the relationship between migraines and ischemic strokes, as well as hemorrhagic strokes, and review management considerations.