Miracle-dz/UniFAR-FTUs huggingface dataset:
Behavior of Assets Disclosure of Personal Tax Payers on Following Tax Amnesty Program (Phenomenology Study)

Tax amnesty is a large government program in obtaining tax revenue. Considering tax revenues always do not reach the target that has been determined. The tax amnesty program has been planned by President Joko Widodo which will begin on July 1, 2016, but socialization has been carried out directly to Taxpayers to all regions in Indonesia before July 1, 2016. Tax revenues have an important role for a country, especially used to build infrastructure, health , education, and much more. Several policies and programs were launched by the government in relation to safeguarding the achievement of revenue and taxation targets in particular. One of them is the tax amnesty program. The enactment of the tax amnesty program is expected to cover shortages of funds in the short term and can increase public compliance with taxes in the long term.
A process reference model for claims management in construction supply chains: the contractors’ perspective

ABSTRACT Claims are an unavoidable burden for every construction project. They stem from risks that have unfortunately been realized in a project and how they will be pursued is up to company strategy, operational particularities and managers’ skills and experience. Claims, in general, have an adverse effect on a project's supply chain by compromising actors’ relationships, project implementation and project outcomes. It is imperative that all contractors follow a well-designed claims management strategy that is guided by well-defined and accurately documented operational processes outlined in detail. Process models related to claims management are scarcely found in the literature. These models are evaluated and a new process reference model, that attempts to improve the claims management process and rectify the identified shortcomings of existing models, such as a lack of transactions between the contractor and other supply chain actors, is proposed. In doing so, a number of process models are created. The objective of this paper is to prescribe the claims management process as an integral process to the supply chain of a construction project in an effort to raise awareness of this relationship and provide a holistic view to claims management through a supply chain management lens.
700-V asymmetrical 4H-SiC gate turn-off thyristors (GTO's)

Silicon Carbide (4H-SiC), asymmetrical gate turn-off thyristors (GTO's) were fabricated and tested with respect to forward voltage drop (V/sub F/), forward blocking voltage, and turn-off characteristics. Devices were tested from room temperature to 350/spl deg/C in the dc mode. Forward blocking voltages ranged from 600-800 V at room temperature for the devices tested. V/sub F/ of a typical device at 350/spl deg/C was 4.8 V at a current density of 500 A/cm/sup 2/. Turn-off time was less than 1 /spl mu/s. Although no beveling or advanced edge termination techniques were used, the blocking voltage represented approximately 50% of the theoretical value when tested in an air ambient. Also, four GTO cells were connected in parallel to demonstrate 600-V, 1.4 A (800 A/cm/sup 2/) performance.
The African Political Business Cycle: Varieties of Experience

Abstract We seek to understand both the incidence and the impact of the African political business cycle in the light of a literature which has argued that, with major extensions of democracy since the 1990s, the cycle has both become more intense and has made African political systems more fragile. With the help of country case studies, we argue, first, that the African political business cycle is not homogeneous, and occurs relatively infrequently in so-called ‘dominant-party systems’ where a pre-election stimulus confers little political advantage. Secondly, we show that, in those countries where a political cycle does occur, it does not necessarily cause institutional damage. Whether it does or not depends not so much on whether there is an electoral cycle as on whether this cycle calms or exacerbates fears of an unjust allocation of resources. In other words, the composition of the pre-election stimulus, in terms of its allocation between different categories of voter, is as important as its size.
FINANCIAL REPORTS QUALITY AND CORPORATE SOCIAL RESPONSIBILITY

This study explores the correlation between CSR and the quality of financial reports according to Stewardship Theory for 100 Best Corporate Citizens. The empirical results of the overall samples indicated that by practicing CSR, companies can effectively reduce their level of earnings management, providing quality financial reports. The cluster sampling results show that CSR has a mediating effect, reducing the direct effects of corporate governance board structures on the quality of financial reports. This study considers the emergence of Stewardship Theory compensates for the defects and deficiencies of agency theory in explaining the behaviors of managers. This study offers deeper insights to policy makers and investors to understand the association between company CSR performance and their financial reporting quality. The results suggest that company stakeholders should pay more attention when considering the influence of company CSR investment performance.
Learning Probabilistic Kernel from Latent Dirichlet Allocation

Measuring the similarity of given samples is a key problem of recognition, clustering, retrieval and related applications. A number of works, e.g. kernel method and metric learning, have been contributed to this problem. The challenge of similarity learning is to find a similarity robust to intra-class variance and simultaneously selective to inter-class characteristic. We observed that, the similarity measure can be improved if the data distribution and hidden semantic information are exploited in a more sophisticated way. In this paper, we propose a similarity learning approach for retrieval and recognition. The approach, termed as LDA-FEK, derives free energy kernel (FEK) from Latent Dirichlet Allocation (LDA). First, it trains LDA and constructs kernel using the parameters and variables of the trained model. Then, the unknown kernel parameters are learned by a discriminative learning approach. The main contributions of the proposed method are twofold: (1) the method is computationally efficient and scalable since the parameters in kernel are determined in a staged way; (2) the method exploits data distribution and semantic level hidden information by means of LDA. To evaluate the performance of LDA-FEK, we apply it for image retrieval over two data sets and for text categorization on four popular data sets. The results show the competitive performance of our method.
Influenza Vaccine Coverage and Reasons for Non-vaccination in a Sample of People Above 65 Years of Age, in Sweden, 1998-2000

Influenza vaccination for the elderly has been shown to be effective. The Swedish national recommendations are that people over 65 y, and especially those with chronic cardiac and/or pulmonary disease, should be immunized annually. However, implementation of such programmes has often been far from successful. The aims of this study were to estimate vaccine coverage and especially reasons for not being vaccinated in a group of elderly people who were all clearly included in the national recommendations. The study investigated people over the age of 65 y who lived in special apartments, 'service homes', connected to the community care for the elderly in the municipality of Linköping, Sweden. The data were collected from the middle of May to the middle of July during 3 years, 1998, 1999 and 2000. Data were gathered by interviewing a sample of 210 tenants each year. All interviews were conducted using a standard questionnaire. The vaccination coverage for influenza in this population was found to be as low as around 30%. The main reason reported for non-vaccination was a lack of knowledge of the recommendations. The results clearly demonstrate that the single most important factor needed to attain high coverage is information, both to the people defined to be at risk and to health-care professionals.
Strategy for the treatment of multiple myeloma utilizing monoclonal antibodies: A new era begins

Abstract Novel agents, such as immunomodulantory drugs (IMiDs) and proteasome inhibitors (PI), have significantly improved overall survival of multiple myeloma (MM) patients. Yet, MM remains an incurable disease, relapse inevitably occurs and patients tend to become resistant to subsequent treatments. This led to the evaluation of new treatment strategies. The recent development of monoclonal antibodies is changing the treatment algorithm of MM by increasing the therapeutic armamentarium. Elotuzumab and Daratumumab were shown to be very effective and are likely to be soon approved by the FDA. Other antibodies are in pre-clinical or early clinical phases of evaluation and further investigation and more robust data are needed. This review will give an overview of the most active monoclonal antibodies against MM.
Molecular Epidemiology of Norovirus Infections in Children with Acute Gastroenteritis in South Korea in November 2005 through November 2006

ABSTRACT Norovirus infections were detected in 114 of 762 children with acute gastroenteritis in South Korea from November 2005 to November 2006. Seasonality peaks in December, March, and October were also assessed in this study. We identified seven noroviral genotypes (GI-6, GII-2, GII-3, GII-4, GII-5, GII-6, and GII-8) and a C1-120 strain showing low identity (79.3%) with GII-13 and GII-17.
Does CEO Duality affect the Firm Performance? Evidence from Sri Lanka

This article examines the impact of CEO duality on firm performance of listed non financial firms in Sri Lanka. This study uses the ROA as proxy measure for form performance. This study employs a cross sectional ordinary least square analysis of 128 firms listed in Colombo Stock Exchange (CSE) for the financial year ending 2013. The results show that CEO duality is significantly negatively associated with ROA. In the case of control variables, board size and leverage are significantly negatively associated with ROA on the other hand firm size is significantly positively linked with ROA. This paper contributes to the existing literature on corporate governance and firm performance by introducing a framework in identifying and analyzing variables that affect the relationship between CEO duality and firm performance. Keywords: Corporate governance, CEO duality, firm performance, ROA
Evaluation of Osteoporosis in Indian Women and Men using Peripheral Dual-Energy X-ray Absorptiometry ( pDXA )

It has been claimed that osteoporosis is becoming more common in India although its prevalence in the country has not been established. Because of the lack of facilities for measurement of bone mineral density (BMD), very little population-based research on osteoporosis has been done in India. The primary objective of this study was to establish the prevalence of osteoporosis in a group of otherwise normal volunteers using forearm BMD measured by peripheral dual-energy x-ray absorptiometry (pDXA). A total of 179 Indian men and women aged 20 years or more attended a free screening camp; of these, 167 were eligible to participate in the study. Total distal forearm BMD (g cm) was measured using an Osteometer DTX-200 pDXA bone densitometer. Data were analyzed by dividing the participants into sex and age-specific groups and using descriptive statistics. For each participant, the T-score was calculated as the difference between BMD and the mean BMD of a group of young persons of the same sex (peak BMD), divided by the group standard deviation (SD). For both women and men, peak BMD occurred in the 20-29 year age group. The mean (±SD) values were 0.393 (±0.031) and 0.433 (±0.073) g cm respectively; the difference (9.2% relative to the male mean) was significant (p=0.01, unpaired ttest). These Indian total distal forearm peak BMD values were less than published corresponding values for Japanese and Caucasian populations. In Indian women and men aged 60 years or more, mean total distal forearm BMD values were significantly reduced (by 13% and 12% respectively) compared to those obtained for women and men aged 20-40 years. Using published Osteometer DTX-200 pDXA devicespecific T-score thresholds, 31.8% (7/22) of Indian women aged 50 years or more were classified as having osteoporosis (Tscore ≤-2.6) while 36.4% (8/22) were found to be at risk of osteoporosis (T-score between -1.5 and -2.5). Using the same Tscore thresholds, no Indian male was found to have osteoporosis but 16.7% (4/24) of men aged 50 years or more were classified as being at risk of osteoporosis. Keywords-osteoporosis, Indian women, Indian men, peripheral dual energy x-ray absorptiometry (pDXA), T-score, total distal forearm peak BMD, Indian normative forearm BMD
A Data Mining Framework for Constructing Features and Models for Intrusion Detection Systems

Intrusion detection is an essential component of critical infrastructure protection mechanisms. The traditional pure “knowledge engineering” process of building Intrusion Detection Systems (IDSs) is very slow, expensive, and error-prone. Current IDSs thus have limited extensibility in the face of changed or upgraded network configurations, and poor adaptability in the face of new attack methods. This thesis describes a novel framework, MADAM ID, for Mining Audit Data for Automated Models for Intrusion Detection. Classification rules are inductively learned from audit records and used as intrusion detection models. A critical requirement for the rules to be effective detection models is that an appropriate set of features need to be first constructed and included in the audit records. A key contribution of the thesis is thus in automatic “feature construction”. Using MADAM ID, raw audit data is first preprocessed into records with a set of “intrinsic” (i.e., general purposes) features. Data mining algorithms are then applied to compute the frequent activity patterns from the records, which are automatically analyzed to generate an additional set of features for intrusion detection purposes. We introduce several extensions, namely, axis attribute(s), reference attribute(s), level-wise approximate mining, and mining with relative support, to the basic association rules and frequent episodes algorithms. The extended algorithms use the characteristics of audit data to direct the efficient computation of “relevant” patterns. We develop an encoding algorithm so that frequent patterns can be easily visualized, analyzed, and compared. We devise an algorithm that automatically constructs temporal and statistical features according to the semantics of the patterns. The effectiveness and advantages of our algorithms have been objectively evaluated through the 1998 DARPA Intrusion Detection Evaluation program.
The Effects of Automation Transparency and Ethical Outcomes on User Trust and Blame Towards Fully Autonomous Vehicles

THE EFFECTS OF AUTOMATION TRANSPARENCY AND ETHICAL OUTCOMES ON USER TRUST AND BLAME TOWARDS FULLY AUTONOMOUS VEHICLES Nathan Andrew Hatfield Old Dominion University, 2018 Director: Dr. Bryan Porter The current study examined the effect of automation transparency on user trust and blame during forced moral outcomes. Participants read through moral scenarios in which an autonomous vehicle did or did not convey information about its decision prior to making a utilitarian or non-utilitarian decision. Participants also provided moral acceptance ratings for autonomous vehicles and humans when making identical moral decisions. It was expected that trust would be highest for utilitarian outcomes and blame would be highest for non-utilitarian outcomes. When the vehicle provided information about its decision, trust and blame were expected to increase. Results showed that moral outcome and transparency did not influence trust independently. Specifically, trust was highest for non-transparent nonutilitarian outcomes and lowest for non-transparent utilitarian outcomes. Blame was not found to be influenced by either transparency, moral outcome, or their combined effects. Interestingly, acceptance was determined to be higher for autonomous vehicles that made the same utilitarian decision as humans, though no differences were found for non-utilitarian outcomes. This research draws on the importance of active and passive harm and suggests that the type of automation transparency conveyed to an operator may be inappropriate in the presence of actively harmful moral outcomes. Theoretical insights into how ethical decisions are evaluated when different agents (human or autonomous) are responsible for active or passive moral decisions are discussed.
A review of causes of variation order in the construction of terrace housing projects in Malaysia

Variation order refers to any changes from the scope, plan, specification or contract document in the construction project. This changes of work is a common problem in construction projects in Malaysia. It is inevitable in any construction project and this problem can become more serious when variation order causes work progress to be impaired as a results it increased the construction time and cost that affects the construction industry in Malaysia. This paper critically review the causes of variation order in the construction industry on the double-storey terrace housing project in Malaysia. The discussions began with the construction industry in Malaysia and then related parties involved in the construction industry. The extensive local and abroad literature review on the definitions of variation order and analysis of past studies conducted on variation order and the previous study of the prediction model of variation. The extensive literature on variation order in the construction of building project may help to improve the performance in term of time, cost and quality of the construction of building projects in Malaysia.
Spatio-Temporal Scene Graphs for Video Dialog

The Audio-Visual Scene-aware Dialog (AVSD) task requires an agent to indulge in a natural conversation with a human about a given video. Specifically, apart from the video frames, the agent receives the audio, brief captions, and a dialog history, and the task is to produce the correct answer to a question about the video. Due to the diversity in the type of inputs, this task poses a very challenging multimodal reasoning problem. Current approaches to AVSD either use global video-level features or those from a few sampled frames, and thus lack the ability to explicitly capture relevant visual regions or their interactions for answer generation. To this end, we propose a novel spatio-temporal scene graph representation (STSGR) modeling fine-grained information flows within videos. Specifically, on an input video sequence, STSGR (i) creates a two-stream visual and semantic scene graph on every frame, (ii) conducts intra-graph reasoning using node and edge convolutions generating visual memories, and (iii) applies inter-graph aggregation to capture their temporal evolutions. These visual memories are then combined with other modalities and the question embeddings using a novel semantics-controlled multi-head shuffled transformer, which then produces the answer recursively. Our entire pipeline is trained end-to-end. We present experiments on the AVSD dataset and demonstrate state-of-the-art results. A human evaluation on the quality of our generated answers shows 12% relative improvement against prior methods.
Physical activity and diabetes: An application of the theory of planned behaviour to explain physical activity for Type 1 and Type 2 diabetes in an adult population sample

Physical activity (PA) plays a key role in the management of Type 1 (T1D) and Type 2 diabetes (T2D) but there are few theory-based, effective programs to promote PA for individuals with diabetes. The purpose of this study was to investigate the utility of the Theory of Planned Behaviour (TPB) in understanding PA in an adult population with T1D or T2D. A total of 2311 individuals (691 T1D; 1614 T2D) completed self-report TPB constructs of attitude, subjective norms, perceived behavioural control (PBC), intention and PA at baseline and 1717 (524 T1D; 1123 T2D) completed the PA measure again at 6-month follow-up. Multi-group Structural Equation Modelling was conducted to: (1) test the fit of the TPB structure (2) determine the TPB structural invariance between the two types of diabetes and (3) to examine the explained variances in PA and compare the strength of associations of the TPB constructs in the two types of diabetes. The TPB constructs explained ≥40% of the variance in intentions for both diabetes groups. In cross-sectional models, the TPB accounted for 23 and 19% of the variance in PA for T1D and T2D, respectively. In prospective models, the TPB explained 13 and 8% of the variance in PA for T1D and T2D, respectively. When adjusting for past PA behaviour, the impact of PBC and intention on behaviour was reduced in both groups. The findings provide evidence for the utility of the TPB for the design of PA promotion interventions for adults with either T1D or T2D.
Clinical Study on Modified Boron Neutron Capture Therapy for Newly Diagnosed Glioblastoma

Boron neutron capture therapy (BNCT) is based on the nuclear capture and fission reactions that occur when non-radioactive boron-10 (10B) is irradiated with neutrons of the appropriate energy to yield high energy alpha particles (4He) and recoiling lithium-7 (7Li) nuclei. Since these particles have pathlengths of approximately one cell diameter, their lethality primarily is limited to boron containing cells. BNCT, therefore, can be regarded as both a biologically and a physically targeted type of radiation therapy (Fig. 1). Its success is dependent upon the selective delivery of sufficient amounts of 10B to cancer cells with only small amounts localized in the surrounding normal tissues. A wide variety of boron delivery agents have
Analysis of Paschen Curves for air, N2 and SF6 Using the Townsend Breakdown Equation

It has been shown that it is possible to extend the validity of the Townsend breakdown criterion for evaluating the breakdown voltages in the complete pd range in which Paschen curves are available. Evaluation of the breakdown voltages for air (pd=0.0133 to 1400 kPa · cm), N2(pd=0.0313 to 1400 kPa · cm) and SF6 (pd=0.3000 to 1200 kPa · cm) has been done and in most cases the computed values are accurate to ±3% of the measured values. The computations show that it is also possible to estimate the secondary ionization coefficient ¿ in the pd ranges mentioned above.