Miracle-dz/UniFAR-FTUs huggingface dataset:
Jurnal Akuntansi & Ekonomika Bias Kognitif dalam Keputusan Investasi di Pekanbaru Cognitive Bias in Investment Decisions in Pekanbaru

terhadap informasi tersebut. This study aims to analyze the financial behavior of investors in terms of cognitive bias towards receiving information when making investment decisions in various financial securities. The method used is descriptive analysis with investors in Pekanbaru as a sample. The results of the study prove that in general, investors will behave normally. However, when faced with a variety of information, decision making will be quite biased when faced with a heuristic group. The level of investor bias will be very high in the reaction bias group. This group considers the existence of experience, different types of investment, as well as the delivery of information and a certain time will change investment needs after adjustments are made to the information.
A new model based on the in-plane deformation for the conformal piezoelectric systems for characterization of soft tissue modulus

Mechanical assessment of the human skin is critically important for clinical diagnosis and treatment of disease. Past works developed a conformal piezoelectric system (CPS) that enables the noninvasive in vivo measurement of the elasticity modulus of the skin, and a mechanical model based on the mechanism of out-of-plane extension of the capacitor-type structures. Here, we present a new theoretical model that is established based on the mechanism of the in-plane deformation. The study on both the free-standing CPS and the CPS mounting to the polydimethylsiloxane (PDMS) target substrates verified the universality of the new model. The experimental and theoretical results consistently show that the output voltage of the first sensor approximately linearly increases with the increase of not only the applied voltage but also the modulus of the PDMS. The optimal usage mode of the CPS, in which the voltage is applied to all actuators simultaneously, is proposed for the measurement of the elastic modulus of target substrates such as skin.
Learning to Separate Voices by Spatial Regions

We consider the problem of audio voice separation for binaural applications, such as earphones and hearing aids. While today's neural networks perform remarkably well (separating $4+$ sources with 2 microphones) they assume a known or fixed maximum number of sources, K. Moreover, today's models are trained in a supervised manner, using training data synthesized from generic sources, environments, and human head shapes. This paper intends to relax both these constraints at the expense of a slight alteration in the problem definition. We observe that, when a received mixture contains too many sources, it is still helpful to separate them by region, i.e., isolating signal mixtures from each conical sector around the user's head. This requires learning the fine-grained spatial properties of each region, including the signal distortions imposed by a person's head. We propose a two-stage self-supervised framework in which overheard voices from earphones are pre-processed to extract relatively clean personalized signals, which are then used to train a region-wise separation model. Results show promising performance, underscoring the importance of personalization over a generic supervised approach. (audio samples available at our project website: https://uiuc-earable-computing.github. io/binaural/. We believe this result could help real-world applications in selective hearing, noise cancellation, and audio augmented reality.
Advances in lithium niobate photonics: development status and perspectives

Abstract. Lithium niobate (LN) has experienced significant developments during past decades due to its versatile properties, especially its large electro-optic (EO) coefficient. For example, bulk LN-based modulators with high speeds and a superior linearity are widely used in typical fiber-optic communication systems. However, with ever-increasing demands for signal transmission capacity, the high power and large size of bulk LN-based devices pose great challenges, especially when one of its counterparts, integrated silicon photonics, has experienced dramatic developments in recent decades. Not long ago, high-quality thin-film LN on insulator (LNOI) became commercially available, which has paved the way for integrated LN photonics and opened a hot research area of LN photonics devices. LNOI allows a large refractive index contrast, thus light can be confined within a more compact structure. Together with other properties of LN, such as nonlinear/acousto-optic/pyroelectric effects, various kinds of high-performance integrated LN devices can be demonstrated. A comprehensive summary of advances in LN photonics is provided. As LN photonics has experienced several decades of development, our review includes some of the typical bulk LN devices as well as recently developed thin film LN devices. In this way, readers may be inspired by a complete picture of the evolution of this technology. We first introduce the basic material properties of LN and several key processing technologies for fabricating photonics devices. After that, various kinds of functional devices based on different effects are summarized. Finally, we give a short summary and perspective of LN photonics. We hope this review can give readers more insight into recent advances in LN photonics and contribute to the further development of LN related research.
American Sign Language alphabet recognition using Microsoft American Sign Language alphabet recognition using Microsoft Kinect Kinect

American Sign Language (ASL) fingerspelling recognition using marker-less vision sensors is a challenging task due to the complexity of ASL signs, self-occlusion of the hand, and limited resolution of the sensors. This thesis describes a new method for ASL fingerspelling recognition using a low-cost vision camera, which is Microsoft’s Kinect. A segmented hand configuration is first obtained by using a depth contrast feature based per-pixel classification algorithm. Then, a hierarchical mode-finding method is developed and implemented to localize hand joint positions under kinematic constraints. Finally, a Random Decision Forest (RDF) classifier is built to recognize ASL signs according to the joint angles. To validate the performance of this method, a dataset containing 75,000 samples of 24 static ASL alphabet signs is used. The system is able to achieve a mean accuracy of 92%. We have also used a publicly available dataset from Surrey University to evaluate our method. The results have shown that our method can achieve higher accuracy in recognizing ASL alphabet signs in comparison to the previous benchmarks.
Social Media Security and Attacks

The advent of social media has revolutionized the speed of communication between millions of people around the world in various cultures and disciplines. Social media is the best platform for exchanging opinions and ideas, interacting with other users of similar interests and sharing different types of media and files. With the phenomenal increase in the use of social media platforms, the need to pay attention to protection and security from attacks and misuse has also increased. The present study conducts a comprehensive survey of the latest and most important research studies published from 2018-20 on security and privacy on social media and types of threats and attacks that affect the users. We have also reviewed the recent challenges that affect security features in social media. Furthermore, this research pursuit also presents effective and feasible solutions that address these threats and attacks and cites recommendations to increase security and privacy for the users of social media.
2019-2020 JSA GRADUATE FELLOWSHIP FINAL REPORT

This report summarizes the work and the accomplishments I have made during 2019-2020 under the JSA/JLab Graduate fellowship. To begin with, I would like to thank the JSA/JLab Graduate Fellowship Program committee for awarding me the fellowship. During this time period I worked on re-modelling the DC high voltage photo-gun used as the magnetized electron source at Gun Test Stand (GTS) at Jeﬀerson Lab to deliver high bunch charge (a few nC) electron beam.
Herpes Simplex Virus 1 Expressing GFP-Tagged Virion Host Shutoff (vhs) Protein Uncouples the Activities of RNA Degradation and Differential Nuclear Retention of the Virus Transcriptome

Like many viruses, herpes simplex virus 1 (HSV1) expresses an endoribonuclease, the virion host shutoff (vhs) protein, which regulates the RNA environment of the infected cell and facilitates the classical cascade of virus protein translation. It does this by causing the degradation of some mRNA molecules and the nuclear retention of others. ABSTRACT Virion host shutoff (vhs) protein is an endoribonuclease encoded by herpes simplex virus 1 (HSV1). vhs causes several changes to the infected cell environment that favor the translation of late (L) virus proteins: cellular mRNAs are degraded, immediate early (IE) and early (E) viral transcripts are sequestered in the nucleus with polyA binding protein (PABPC1), and dsRNA is degraded to help dampen the PKR-dependent stress response. To further our understanding of the cell biology of vhs, we constructed a virus expressing vhs tagged at its C terminus with GFP. When first expressed, vhs-GFP localized to juxtanuclear clusters, and later it colocalized and interacted with its binding partner VP16, and was packaged into virions. Despite vhs-GFP maintaining activity when expressed in isolation, it failed to degrade mRNA or relocalise PABPC1 during infection, while viral transcript levels were similar to those seen for a vhs knockout virus. PKR phosphorylation was also enhanced in vhs-GFP infected cells, which is in line with a failure to degrade dsRNA. Nonetheless, mRNA FISH revealed that as in Wt but not Dvhs infection, IE and E, but not L transcripts were retained in the nucleus of vhs-GFP infected cells at late times. These results revealed that the vhs-induced nuclear retention of IE and E transcripts was dependent on vhs expression but not on its endoribonuclease activity, uncoupling these two functions of vhs. IMPORTANCE Like many viruses, herpes simplex virus 1 (HSV1) expresses an endoribonuclease, the virion host shutoff (vhs) protein, which regulates the RNA environment of the infected cell and facilitates the classical cascade of virus protein translation. It does this by causing the degradation of some mRNA molecules and the nuclear retention of others. Here, we describe a virus expressing vhs tagged at its C terminus with a green fluorescent protein (GFP) and show that the vhs-GFP fusion protein retains the physical properties of native vhs but does not induce the degradation of mRNA. Nonetheless, vhs-GFP maintains the ability to trap the early virus transcriptome in the nucleus to favor late protein translation, proving for the first time that mRNA degradation is not a prerequisite for vhs effects on the nuclear transcriptome. This virus, therefore, has uncoupled the nuclear retention and degradation activities of vhs, providing a new understanding of vhs during infection.
A Revisiting Study of Appropriate Offline Evaluation for Top-N Recommendation Algorithms

In recommender systems, top-N recommendation is an important task with implicit feedback data. Although the recent success of deep learning largely pushes forward the research on top-N recommendation, there are increasing concerns on appropriate evaluation of recommendation algorithms. It therefore is important to study how recommendation algorithms can be reliably evaluated and thoroughly verified. This work presents a large-scale, systematic study on six important factors from three aspects for evaluating recommender systems. We carefully select 12 top-N recommendation algorithms and eight recommendation datasets. Our experiments are carefully designed and extensively conducted with these algorithms and datasets. In particular, all the experiments in our work are implemented based on an open sourced recommendation library, Recbole [139], which ensures the reproducibility and reliability of our results. Based on the large-scale experiments and detailed analysis, we derive several key findings on the experimental settings for evaluating recommender systems. Our findings show that some settings can lead to substantial or significant differences in performance ranking of the compared algorithms. In response to recent evaluation concerns, we also provide several suggested settings that are specially important for performance comparison.
How to use Evolutionary Game Theory to study evolutionary aspects of grammar

This chapter is a short tutorial for a game-theoretic approach to study the evolutionary aspects of grammar. Such an approach is very useful to better understand the nature of language change, for at least two reasons: On the one hand, game-theoretic models of grammatical systems make it possible to quantify how useful a grammar is in terms of speaker/hearer economy, where such a quantification serves to compare different grammars regarding being better or worse. On the other hand, Evolutionary Game Theory (EGT) provides tools for studying the evolutionary aspects of grammars, such as their stability as well as the transition probabilities among them. As I will show, EGT supplies useful methods to study aspects of language change that might drive a grammatical system for better or worse.
Knowledge and attitudes regarding HIV/AIDS and its prevention among Ghanaian women [version 1; peer review: awaiting peer review]

Background : HIV/AIDS is still a major public health issue around the world, especially in Sub-Saharan Africa (SSA), where this has resulted in unquantifiable human suffering, social and cultural disruption, and enormous economic losses. Methods : This study aims to assess women’s knowledge and attitude toward HIV/AIDS and its prevention in Ghana. To perform an analytic cross-sectional study, this study used data (the women in reproductive age 15-49 years dataset) from the Ghana Multiple Indicator Cluster Survey (MICS) 2017/18. Bivariate analysis was done using chi-square and predictor variables were identified using binary logistics regression. Results : This study recorded good HIV knowledge and attitude levels of 81.9% and 10.5%. Factors that predicted only good HIV knowledge levels were ethnicity, and disability status. Also, predictors of only good attitude level were type of residence and marital status. Factors implicated in the prediction of both good knowledge and attitude levels were age, educational status, region of orientation, health insurance status, economic status, and media exposure. Conclusions : This study recorded a good HIV knowledge level among the majority of the women, but recorded most respondents having a poor attitude toward HIV.
Green Patents in an Oligopolistic Market with Green Consumers

We develop a theoretical framework to investigate the impact of patent policies and emission taxes on green innovation that reduces the emission output ratio, and on the emission level. We allow strategic interaction of (cid:133)rms in a duopolistic market. A key (cid:133)nding of the paper is that the greater the proportion of consumers that are green conscious, the less likely that (cid:133)rms are to engage in licensing the green innovation which results in higher levels of emissions such that policy-makers may consider implementing technology standards in order to e⁄ectively force licensing. For su¢ ciently large proportions of green conscious consumers, increasing the emission tax beyond a certain threshold induces licensing in equilibrium, thereby causing emissions to fall discretely. Finally, we (cid:133)nd that there exists a second threshold level of the tax beyond which increasing the emission tax leads to increasing the emission level. This paradox can be mitigated by decreasing patenting costs and/or making the patentability requirement stricter.
A Multiple-Model Particle Filter Fusion Algorithm for GNSS/DR Slide Error Detection and Compensation

Continuous accurate positioning is a key element for the deployment of many advanced driver assistance systems (ADAS) and autonomous vehicle navigation. To achieve the necessary performance, global navigation satellite systems (GNSS) must be combined with other technologies. A common onboard sensor-set that allows keeping the cost low, features the GNSS unit, odometry, and inertial sensors, such as a gyro. Odometry and inertial sensors compensate for GNSS flaws in many situations and, in normal conditions, their errors can be easily characterized, thus making the whole solution not only more accurate but also with more integrity. However, odometers do not behave properly when friction conditions make the tires slide. If not properly considered, the positioning perception will not be sound. This article introduces a hybridization approach that takes into consideration the sliding situations by means of a multiple model particle filter (MMPF). Tests with real datasets show the goodness of the proposal.
AIS Electronic Library (AISeL) AIS

Data-driven disciplines like data mining and knowledge management already provide process-based frameworks for data analysis projects, such as the well-known cross-industry standard process for data mining (CRISP-DM) or knowledge discovery in databases (KDD). Although the domain of data science addresses a much broader problem space, i.e., also considers economic, social, and ecological impacts of data-driven projects, a corresponding domain-specific process model is still missing. Consequently, based on a total of four identified meta requirements and 17 corresponding requirements that were collected from experts of theory and practice, this contribution proposes the empirically grounded data science process model (DASC-PM)—a framework that maps a data science project as a four-step process model and contextualizes it among scientific procedures, various areas of application, IT infrastructures, and impacts. To illustrate the phase-oriented specification capabilities of the DASC-PM, we exemplarily present competence and role profiles for the analysis phase of a data science project.
On a semigroup of closed connected partial homeomorphisms of the unit interval with a ﬁxed point

In this paper we study the semigroup IC ( I, [ a ]) ( IO ( I, [ a ]) ) of closed (open) connected partial homeomorphisms of the unit interval I with a ﬁxed point a ∈ I . We describe left and right ideals of IC ( I, [0]) and the Green’s relations on IC ( I, [0]) . We show that the semigroup IC ( I, [0]) is bisimple and every non-trivial congruence on IC ( I, [0]) is a group congruence. Also we prove that the semigroup IC ( I, [0]) is isomorphic to the semigroup IO ( I, [0]) and describe the structure of a semigroup II ( I, [0]) = IC ( I, [0]) ⊔ IO ( I, [0]) . As a corollary we get structures of semigroups IC ( I, [ a ]) and IO ( I, [ a ]) for an interior point a ∈ I .
Towards a Shared Services Model to support e-Government implementation in Developing Countries: Findings from Liberia

The e-Government program in many developing countries is an emerging concept and at the formative stage. This paper focuses on Liberia, a developing country in sub-Saharan Africa faced with many challenges impeding government efforts to harness ICT to deliver quality services. Key among the challenges is the fragmentation of government information systems causing inoperability among government ministries and agencies. This paper describes a project in which we develop a shared services model to transform e-government implementation in Liberia by determining key services that will allow the government to share and leverage finite ICT resources. Few academic studies have been carried out to investigate approaches and ways of combining e-government services in order to implement shared services in a developing country. Through a case study approach, we propose electronic government services that have the potential to promote Shared Services Model implementation in sub-Saharan African countries.
Optically Transparent Nano-Patterned Antennas: A Review and Future Directions

Transparent antennas have been continuously developed for integration with solar cells, vehicular communications, and ultra-high-speed communications such as 5G in recent years. A transparent antenna takes advantage of spatial extensibility more so than all other antennas in terms of wide range of usable area. In addition, the production price of transparent antennas is steadily decreasing due to the development of nano-process technology. This paper reviews published studies of transparent antennas classified by various materials in terms of optical transmittance and electrical, sheet resistance. The transparent electrodes for the transparent antenna are logically classified and the transparent antennas are described according to the characteristics of each electrode. Finally, the contributions transparent antennas can make toward next-generation 5G high-speed communication are discussed.
Liquid biopsy derived circulating tumor cells and circulating tumor DNA as novel biomarkers in hepatocellular carcinoma

ABSTRACT Introduction The diagnosis of hepatocellular carcinoma (HCC) is made at a relatively advanced stage resulting in poor prognosis. Alpha-fetoprotein and liver ultrasound have limited accuracy as biomarkers in HCC. Liver biopsy provides information on tumor biology; however, it is invasive and holds high threat of tumor seeding. Thus, more accurate and less invasive approaches are needed Areas Covered Highly sensitive liquid biopsy assays have made possible the detection and analysis of cells or organelles such as circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and tumor-derived exosomes. Here, we focus on CTCs and ctDNA components of liquid biopsy and their clinical application as diagnostic, prognostic, and predictive biomarkers in HCC. Unlike tissue biopsy, liquid biopsy involves attaining a sample at several time frames in an easy and a non-invasive manner. They have been efficacious in detecting and classifying cancer, in predicting treatment response, in monitoring disease relapse and in identifying mechanisms of resistance to targeted therapies. Expert Opinion Although interesting and highly promising, liquid biopsy techniques still have many obstacles to overcome before their wide spread clinical application sees the light. It is expected that these techniques will be incorporated into traditional methodologies for better diagnostic, predictive and prognostic results.
A high‐gain linear array of cross slots substrate integrated waveguide leaky‐wave antenna with defective ground structure

This letter provides a detailed explanation of a novel high‐gain cross slot substrate integrated waveguide (SIW) rectangular cavity‐backed antenna. The main SIW cavity is further divided into seven small linearly placed cavities at a distance of 0.9 λg ${{\rm{\lambda }}}_{{\rm{g}}}$ . Each cavity contains a cross‐slot at an equal distance from each other. The defective ground structure is placed at the bottom layer of an antenna with two metallic vias to divert the wave towards edge slots for further gain improvement. The antenna shows a measured gain of approximately 12 dBi from 11.37 to 11.78 GHz. The radiation efficiency of 92% and the front‐to‐back ratio of 28 dB is achieved. The proposed antenna provides a very high directive fan‐like pattern which can be utilized for satellite and radar applications in the X‐band.