Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on Online Impulsive Buying and Post-Purchase Dissonance

With the popularized of Internet and smart mobile devices, people nowadays can complete shopping process in seconds. Hence, consumers’ reliance toward online shopping is getting stronger. Yet, contrasting to the shopping experience in physical store, the chance of impulse buying and product return increases when consumers shops online. Subsequently, problems like post-purchase dissonance (e.g. emotion dissonance, product dissonance) arise as well. Therefore, in order to Figure out what causes impulse buying behavior and the relationship with cognitive dissonance, we adopt the concept from Powers and Jacks [1]. Also, despite of two shopping values as antecedents for impulse buying, we supplement time pressure from Tıgli and Kaytaz Yigit [2] as well. Consequently, we attach return tendency, which are to explore the effect of post-purchase dissonance. In this study, we conduct a survey and receive 155 valid response in total, and the result shows that time pressure and emotion dissonance are the main factors influence impulse buying. To sum up. our findings may be useful for retailers attempting to operate websites in e-commerce.
Latent Feature Modelling for Recommender Systems

Matrix factorization is one of the most successful model-based collaborative filtering approaches in recommender systems. Nevertheless, useful latent user features can lead to a more accurate recommendation. However, user privacy and cross-domains access restrictions challenge collection and analysis of such information. In this study, we propose a feature extraction method (WAFE) which leverages user-item interaction history to extract useful latent user features. We also propose a rating prediction approach that incorporates the local mean of users’ and items’ ratings. We evaluate our proposed model using two real-world benchmark datasets and compare its performance against the state-of-the-art matrix factorization collaborative filtering methods. Evaluation results show that proposed method outperforms the existing methods.
Differential Analysis of Intestinal Microflora in Pigs with Different Growth Performance

This experiment was conducted to analysis the differences of intestinal microbial composition in pigs with different growth performances by polymerase chain reaction-denaturing gradient gel electrophoresis( PCRDGGE). Thirty-six barrows( Duroc × Landrace × Yorkshire) with a starting body weight of( 26. 6 ± 2. 6) kg were raised for 42 days( ad libitum) within single bar. Feed intake and body weight of each pig were recorded every week to calculate feed conversion rate and average daily gain. At the end of the experiment,feed conversion ratio and average daily gain were integrated to divide the pigs into 3 groups,namely,high growth performance group,middle growth performance group and lowgrowth performance group. Three selected pigs from each group were killed to collect gut contents and feces. The results showed that the DGGE band numbers of ileum,colon,cecum and fecal samples were increased with the improvement of growth performance. Specifically,the abundance of Coprococcus sp. in cecum,Roseburia sp. in colon and fecal samples were higher in high growth performance group than those in the lowgrowth performance group,while Roseburia sp. and Lactobacillus sp. were abundant in the gut of some high growth performance pigs. In summary,there is a correlation between pig gut microbiota composition and the growth performance of pigs. Bacteria belong to the genus of Coprococcus,Roseburia,Lactobacillus can serve as target for improving the health and growth performance of pigs.
Protein stability in mixed solvents: From transfer thermodynamics to the denaturation by urea and back

The conformational equilibrium between folded and unfolded protein structures is sensitive to the presence of cosolvents in the surrounding solution, and several small organic molecules are known to modulate the functioning of proteins in cells by shifting the equilibrium toward folded (stabilizers) or unfolded states (denaturants). The molecular mechanisms behind these effects are not yet fully understood and are a matter of intense research. In the past, successful models have been devised which predict the effects of cosolvents on proteins on the basis of their effects on small model compounds. E. g. , in the popular transfer model (TM) the latter are quantified by the free energies of the transfer (TFEs) of the model compounds between water and cosolvent solutions. In this thesis, we examine and discuss the interpretation and measurement of TFEs. Moreover, we deal with the application of TFE-based bottom-up approaches in the study of the denaturing mechanism of urea—the probably most studied and nonetheless most controversially discussed cosolvent. The highlights of this work are: • We present a detailed and comprehensible explanation for the role of the concentration scale in the definition of TFEs and show that only the TFE that is defined in the molarity scale can be interpreted directly in terms of favorable or unfavorable solute-solvent interactions. • We uncover an inconsistency and a compensating error in the nowadays established implementation of the TM. After their revision, the TM predicts that both the protein backbone and the side chains play a role in denaturation by urea. This is in line with many recent studies and thus paves the way toward a unified understanding of urea’s denaturing mechanism. Previous applications of the TM predicted a contrasting mode of action and this discrepancy was considered a major concern. • We present a molecular dynamics study which provides further insight into urea’s denaturing mechanism. It suggests that protein denaturation by urea is the resultant of a complex and subtle interplay of various types of interactions between all solution components, being the protein, urea, and water. • We propose a new measuring method for the determination of TFEs for transfers between pure and mixed solvents and point out that it is necessary to reassess the accuracies of currently employed measuring approaches. First steps into that direction suggest that some currently used measuring methods might not be as accurate as presumed so far.
Interface Density Effects on Cross-Plane Thermal Conductance of Nanolaminate Thin Films

Thermal resistance arises at the interface of two different materials. However, developers of sensors, electronics, and power conversion devices often ignore this effect. The additional thermal resistance imposed due to interface can enhance sensitivity of thermal sensors, and efficiency of thermal energy harvesting devices such as thermoelectrics. This work demonstrates that the effect of interfaces cannot, and should not, be ignored when dealing with many interfaces in a system. We use frequency-domain thermoreflectance to demonstrate that nanolaminate thin films significantly reduce the overall thermal conductance of the film stack. As an example, with 500nm total film thickness, a repeated period of 10nm each of high thermal conductivity aluminum (kbulk,Al = 212 Wm-1K-1) and silicon dioxide (kbulk,SiO2 = 1.4 Wm-1K-1) have measured effective thermal conductivity less than that of silicon dioxide alone (1.20 Wm-1K-1 vs 1.38 Wm-1K-1). While this is substantial, the diffuse mismatch model (which often over-predicts thermal conductance of single interfaces) predicts an even lower value of effective thermal conductivity (0.56 Wm-1K-1), meaning much lower nanolaminate thermal conductivity could be realized with appropriate treatment of the surface where an interface will form.
The Seed Germination And The Developmental of the Seeding Study of Gentiana macrophylla

This paper studies the effects of the different store ways and the gibberellins of varying concentration on the seed germination,and observed the seeding development of Gentiana macrophylla.Our results show the promoting effect is significant to the germination energy and germination rate of the seeding by 200mg/L gibberellin at the 22±1℃ temperature.Because the seeds are ephemeral,The seed germination rate decreased significantly at the natural conditions of storage after 1 year.The way at subzero cryopreservation may increase the seed longevity although the seed longevity of Gentiana macrophylla is one year.The root collar and hypocotyl hairs appear on the early developing of the seeding.The leaves of the one-year seedling arrange rosulate.
Analysis of Resource Allocation Overheads in Vehicle Ad Hoc Network Considering CSI

The problem of overheads caused by resource allocation in vehicle ad hoc network (VANET) has become an issue attracting more and more attention. Recently, 3GPP has introduced channel state information (CSI) report into NR V2X as a new and important technical feature. Therefore, by considering the channel state of the vehicle nodes, this paper proposes an improved permutation model based on our previous work where the overheads related to channel state were not treated in a differentiated manner. It is assumed that the nodes in good channel state would have priority to occupy resources first, while the nodes in bad channel state are not allowed to participate in resource allocation, and the CSIs representing bad channel state are assumed to be compressed or saved. In this way, the overheads of resource allocation in VANET can be reduced, thus leading to the potential performance improvement of the overall system. This result is verified by simulation experiments, which show the proposed model may work as a better optimizing guideline for achieving good performance gain.
Configurable Ring Oscillator PUF Using Hybrid Logic Gates

Physical unclonable function (PUF), a hardware that can extract the differences of the same implementations and provide unique secret keys without the utilization of non-volatile memory, is regarded as a promising security primitive in the near future. Ring Oscillator (RO) PUF is one of its easy silicon implementations, which exploits the frequency difference between a pair of structurally identical ring oscillators. However, a large number of ROs must be constructed if multiple stable output bits are required, which means unacceptable area overhead for lightweight applications. To solve this problem, configurable ROs using multiplexers and different delay units were proposed in previous papers. Unfortunately, most of them take advantage of the specific structure of a certain type of field-programmable gate arrays (FPGAs), thus not cost-saving for application-specific integrated circuit (ASIC). In this paper, we propose a configurable RO using only two hybrid logic gates in each stage for ASIC, which costs less area and power compared with previous proposals. Experiment on 50 FPGAs and one self-designed printed circuit board demonstrates satisfactory uniformity and uniqueness of this novel RO PUF. Furthermore, our proposal is proved to be reliable in a wide variety of environment conditions.
BusinessDetect: An Advanced Business Information Mining Application for Intelligent Marketing

With the arrival of the era of big data, information technology is widely applied in almost all industries. Traditional marketing is largely dependent on manpower, which is quite inefficient. Data mining combined with big data technology has become an effective solution for intelligent marketing. However, the existing marketing applications mainly concentrate on providing business information retrieval but have limited capability to discover business insights. Hence, in this paper, we propose BusinessDetect, a business information mining application that integrates complete business information and extracts appropriate knowledge to support intelligent marketing. Furthermore, we design different interfaces to display information and interact with users. The evaluation results show that BusinessDetect can provide comprehensive support for developing customers and making decisions more efficiently.
Quiet Revolutions: How Advanced Microelectronics Packaging Continues to Drive Heterogeneous Integration1

The past few years have seen increasing interest in advanced package architectures as compact, high performance platforms for heterogeneous integration across a wide variety of applications [1]. Interest in advanced packaging is driven by the need for increased on-package bandwidth, the need to integrate diverse IP from multiple foundries and the need for improved yield resiliency [2]. A number of innovative package architectures that enable power-efficient on-package bandwidth interconnects [3]-[8] have made major advances in microelectronics performance possible [9]-[11]. Focus on heterogeneous integration makes visible to broader audiences, the packaging community that in a quiet, systematic and largely unheralded manner continues to drive momentous changes in packaging, assembly and associated test technologies. In this paper, I will attempt to describe some of these changes and more importantly offer a perspective for how packaging should evolve and what this means to the thermal management community.
Scientific Workflow Recommendation Based on Service Knowledge Graph

With the dramatically increasing emerging of external Web services, automatically creating workflows to satisfy the sophisticated requirements of users has become a significant issue. Most scientific workflow recommendation focus on mining association patterns between services in historical portfolios, including positive and negative rules, and recommending appropriate workflows based on derived patterns. However, due to the development of social network, several key social interactions are ignored which can enrich implicit associations of items and guide workflow recommendation. To tackle these problems, a Service Social Knowledge Graph (SSKG), including two types of entities service and developer and three types of relations isInk, isDlp and isFrd, is proposed to visually integrate and manage vital information which can facilitate workflows construction. Respectively, isInk shows the data flow between services, isDlp means the relation between a developer and his services and isFrd presents the friend relationships between developers. SSKG supplies indirect relations of services which inferred from isDlp and isFrnd. From SSKG, we extract several positive and negative rules to estimate the feasibility of composing services that the positive rules promote service composition and negative rules hinder the cooperation of services. According to the overall effects of rules, the $A^{*}$ and the Yen’s method are used to recommend workflows to users. We have conducted extensive experiments with real-world data. Results indicate that the accuracy and efficiency of our proposed method outperform the classical and state-of-the-art methods.
Preliminary study on growth characteristics of cage-cultured Nibea albiflora(Richardson)

As a newly developing species,the spotted maigre,Nibea albiflora(Richardson) exhibited great potential for aquaculture.To investigate the cultured ecology characteristics of the spotted maigre,the growth performance were monitored regularly,and the growth differences between males and females were also compared.During June of 2009 and June of 2010,the environmental factors were monitored regularly and the total length,body length and body weight were measured at fixed periods every month.The growth performance was compared between female and male individuals since the spotted maigre was 7 months old.The results showed that the spotted maigre grew fast during summer cultured period while grew slowly during winter cultured period.The mean growth rate was 0.72 g/d in body weight and 0.048 cm/d in total length.The body weight reached 288.32±38.56 g when the spotted maigre was 15 months old.The female and male individuals had significant differences in body weight since 7 months old.The differences enlarged as the age increased,and the body weight of female individuals was 1.31 times larger than that of the male individuals.
Multiple Cues Based Particle Filter for Robust Tracking

The main goal of this paper is to develop a robust visual tracking algorithm with particle filtering. Visual Tracking with particle filter technique is not easy task due to cluttered environment, illumination changes. To deal with these problems, we develop an efficient observation model for target tracking with particle filter. We develop a robust phase correlation combined with motion information based observation model for particle filter framework. Phase correlation provides straight-forward estimation of rigid translational motion between two images, which is based on the well-known Fourier shift property. Phase correlation has the advantage that it is not affected by any intensity or contrast differences between two images. On the other hand, motion cue is also very well known technique and widely used due to its simplicity. Therefore, we apply the phase correlation integrated with motion information in particle filter framework for robust tracking. In experimental results, we show that tracking with multiple cues based model provides more reliable performance than single cue.
Bias in machine learning - what is it good for?

In public media as well as in scientific publications, the term \emph{bias} is used in conjunction with machine learning in many different contexts, and with many different meanings. This paper proposes a taxonomy of these different meanings, terminology, and definitions by surveying the, primarily scientific, literature on machine learning. In some cases, we suggest extensions and modifications to promote a clear terminology and completeness. The survey is followed by an analysis and discussion on how different types of biases are connected and depend on each other. We conclude that there is a complex relation between bias occurring in the machine learning pipeline that leads to a model, and the eventual bias of the model (which is typically related to social discrimination). The former bias may or may not influence the latter, in a sometimes bad, and sometime good way.
Towards Privacy Preserving Data Centric Super App

The number of smartphone users recently surpassed the numbers of desktop users on Internet, and opened up countless development challenges and business opportunities. Not only the fact that the majority of users are connected using their smartphones, but the number of Internet users in general has popularized the massive use of data-driven applications. In this context, the concept of super apps seems to be the next game-changer for the mobile apps industry, and the challenges related to security and privacy are key aspects for keeping user data safe. Thus, by combining different components for provisioning, authentication, membership and others, we propose a novel framework that enables the creation of a super app using privacy by design principles.
High Performance Operational Amplifier with 90dB Gain in SCL 180nm Technology

This paper presents the design and implementation of a high-speed, high-gain fully differential opamp. The architecture consists of a telescopic cascode differential amplifier followed by a modified common-source second stage that includes an intermediate push-pull stage, individual CMFB circuits including frequency compensation for the first and second stages, RC Miller compensation for the main op-amp, and dc bias circuit blocks. The circuit is implemented in SCL 180nm technology, including layout and post-layout extracted characterization. It achieves a DC gain of 90dB with phase margin of 58° at 530MHz for a load of 1pF. Output voltage swing is +/-600mV for a +/-900mV supply. A sample-and-hold circuit built with the op-amp gives an accuracy of 60µV at 40MHz.
Research on Dimension Reduction Method of Public Opinion Short Text Representation Model Based on Combined Neural Network

With the rapid development of the Internet and the popularization of social software such as Twitter and Weibo, online public opinion has an increasing influence on public opinion in the entire society. In order to effectively prevent and control vicious incidents, real-time monitoring of online public opinion is becoming increasingly important. important. According to the characteristics of short-sentence information in public opinion, this paper proposes an automatic clustering method based on combinatorial neural network to construct a short-sentence representation model of public opinion, and construct word clusters based on the semantic similarity of characteristic words. The test results show that: in the process of mass text analysis and public opinion discovery, this method can effectively reduce the accuracy of the short text public opinion construction representation model by reducing the dimension of the text representation model, while ensuring the real-time acquisition of public opinion while greatly improving Public opinion finds efficiency.
Investing in Applications Based on Predictive Modeling

Since 1983, the start of the mobile industry has led to some great inventions. Due to the rapid increase in technology, the world of mobile applications has grown stupendously. While some applications achieve great success both from rating and financial perspective, several applications do not perform well in the application store. This research attempts to develop a model for the prediction of app ratings based on several data points collected from multiple sources. The research is restricted to Android apps, and the ratings are predicted using Linear Regression and Logistic Regression. The study brings in a new perspective of review sentiment and analyzes the impact of various parameters on the successful ratings of mobile applications.
The Degradation Mechanisms of Underfills Subjected to High Temperature Long Term Aging

Much of automotive electronics used to support power systems and enable safety systems resides underhood. Underhood electronics may be subjected to sustained temperatures of 125-150°C for prolonged periods during operation. Majority of the available plastic encapsulated electronic components are designed for operation at 55-100°C and lower lifetimes about 3-5 years. There is dearth of commercially available components designed to operate reliably above 150°C for extended periods-of-time. The insufficient information on materials, interconnects, and packaging systems capable of surviving high temperatures for long periods (>100,000 hours), which are compatible with and protect the electronics. In this paper, 4 different types of underfills has been cured and ageing. Mechanical tests have been performed for 4 types of underfills. Uniaxial tensile tests are conducted to study the elastic modulus, ultimate tensile strength and percentage elongation of 4 types of underfills. SEM and EDX are applied to study the microstructure behaviors of 4 types of underfills. The raw data on packaging material is collected. The experimental results are compared before and after aging tests, including pristine, 30 days, 60 days and 90days. The research focuses on microstructure-property-processing-performance relationships. Reliability physics of high temperature degradation of packaging material is studied.