Miracle-dz/UniFAR-FTUs huggingface dataset:
The Influence of Transformational and Transactional Leadership on Employee Performance: Empirical Study on Employee of Banking Company at North Sulawesi

Transformational leadership style is an activity that influences people to working together in order to achieve the organization goals. Leadership can occur anywhere, provided that someone shows his ability to influence the behavior of others towards achieving a certain goal. Transformational leadership as a leader who has the power to influence subordinates in certain ways. The intent of transformational leadership is to encourage employee performance in the Banking business in North Sulawesi, Indonesia. The object of the study was Bank BRI, BNI and SulutGo, which have branches throughout the North Sulawesi region. The number of respondents was 176 employees. The collected data were then analysed by using a variant-based structural equation model or Partially Least Square (PLS-SEM). The data analysis results provide empirical evidence that a transformational leadership style, particularly in the individual consideration and individual inspirational dimensions, positively impacts employee performance. However, other dimensions, namely, intellectual stimulation and inspirational motivation, do not significantly encourage activities related to performance. Moreover, transactional leadership on the contingent reward dimension does not significantly impact knowledge sharing. Keywords: employee performance, transformational leadership, banking company
Spontaneous Hypoglycemia Associated With Autoimmunity Specific to Human Insulin

A 55-yr-old woman with a history of Graves'; disease experienced attacks of postprandial hypoglycemia for 6 yr. An insulinoma could not be confirmed by repeated fasting tests and by surgical pancreas revision. Extracted pancreatic insulin was chemically normal. Fasting plasma total insulin (1.22 nM = 183 μU/ml) and proinsulin (0.48 nM) were elevated and greatly increased after oral glucose. Glucoseclamp studies revealed delayed insulin clearance. Plasma free-insulin levels were normal. Insulin-binding antibodies were detected by enzyme-linked immunosorbent assay (ELISA) and radioimmunoassay with human insulin as ligand but not with pork or beef insulins. Analysis with a modified ELISA suggested a monotypic and monoclonal human insulin autoantibody, which showed a restriction to the λ-light chain. T-lymphocytes (predominantly helper) demonstrated increased responsiveness to beef, pork, and human insulins by proliferation assay. A T-lymphocyte line showed exclusively human insulin specificity. All this indicated cellular and humoral anti-human insulin autoimmunities. Clinically, the cause of hypoglycemia associated with elevated total insulin and proinsulin was misdiagnosed as atypical insulinoma. The study of total and free plasma insulin levels and sensitive antibody assays specific to human insulin were necessary to correctly diagnose autoimmune hypoglycemia.
Historical and contingent factors affect re‐evolution of a complex feature lost during mass extinction in communities of digital organisms

Re‐evolution of complex biological features following the extinction of taxa bearing them remains one of evolution’s most interesting phenomena, but is not amenable to study in fossil taxa. We used communities of digital organisms (computer programs that self‐replicate, mutate and evolve), subjected to periods of low resource availability, to study the evolution, loss and re‐evolution of a complex computational trait, the function EQU (bit‐wise logical equals). We focused our analysis on cases where the pre‐extinction EQU clade had surviving descendents at the end of the extinction episode. To see if these clades retained the capacity to re‐evolve EQU, we seeded one set of multiple subreplicate ‘replay’ populations using the most abundant survivor of the pre‐extinction EQU clade, and another set with the actual end‐extinction ancestor of the organism in which EQU re‐evolved following the extinction episode. Our results demonstrate that stochastic, historical, genomic and ecological factors can lead to constraints on further adaptation, and facilitate or hinder re‐evolution of a complex feature.
Nonlinear Antiswing Control of Offshore Cranes With Unknown Parameters and Persistent Ship-Induced Perturbations: Theoretical Design and Hardware Experiments

In practical applications, offshore cranes are widely utilized on large scale ships to accomplish the tasks of transferring cargos from one ship to another or between ships and harbors. Compared with traditional land-fixed cranes, offshore cranes work in noninertial (ship) frames and their movements are significantly influenced by such complicated disturbances as sea waves, etc. Hence, the control issue of offshore cranes presents much more challenges. At present, existing controllers for offshore cranes are designed based upon linearized dynamics, and they need the accurate values of the plant parameters. However, the values of the parameters, including cargo/jib masses, are usually difficult to measure or even unknown, which makes exact gravitational force compensation difficult and unavoidably results in positioning errors for luffing and hoisting/lowering control. To deal with these practical issues, we suggest a novel model-parameter-free control approach to achieve effective control for underactuated offshore crane systems. By constructing an elaborate storage function, we provide a complete Lyapunov-based stability analysis. As far as we know, this paper provides the first control strategy to asymptotically regulate an offshore crane system subject to parametric uncertainties and ship-induced perturbations, which is developed without simplifying the original nonlinear dynamic equations. At last, a series of experimental results, carried out on a self-built offshore crane hardware platform, are presented to validate the effectiveness and robustness of the presented control scheme.
NCAA Graduation Rates: A Quarter-Century of Re-branding Academic Success

Asserting “[t]he goal of the NCAA is to integrate athletics with academics” (O’Bannon v. NCAA, November 14, 2014, p. 26), NCAA chief legal officer Donald Remy cautioned the U.S. Court of Appeals for the Ninth Circuit to not allow “the plaintiffs and the district court to untether college athletics from the academic experience” (Solomon, 2014, para. 19) In their brief, the NCAA claimed college athletes are just like any other college students, fully integrated into the academic community and enjoying greater academic success than regular students:
Multivariate t nonlinear mixed‐effects models for multi‐outcome longitudinal data with missing values

The multivariate nonlinear mixed‐effects model (MNLMM) has emerged as an effective tool for modeling multi‐outcome longitudinal data following nonlinear growth patterns. In the framework of MNLMM, the random effects and within‐subject errors are assumed to be normally distributed for mathematical tractability and computational simplicity. However, a serious departure from normality may cause lack of robustness and subsequently make invalid inference. This paper presents a robust extension of the MNLMM by considering a joint multivariate t distribution for the random effects and within‐subject errors, called the multivariate t nonlinear mixed‐effects model. Moreover, a damped exponential correlation structure is employed to capture the extra serial correlation among irregularly observed multiple repeated measures. An efficient expectation conditional maximization algorithm coupled with the first‐order Taylor approximation is developed for maximizing the complete pseudo‐data likelihood function. The techniques for the estimation of random effects, imputation of missing responses and identification of potential outliers are also investigated. The methodology is motivated by a real data example on 161 pregnant women coming from a study in a private fertilization obstetrics clinic in Santiago, Chile and used to analyze these data. Copyright © 2014 John Wiley & Sons, Ltd.
Operationalizing the Continuum between Well-Defined and Ill-Defined Problems for Educational Technology

One of the most effective ways to learn is through problem solving. Recently, researchers have started to develop educational systems which are intended to support solving ill-defined problems. Most researchers agree that there is no sharp distinction but rather a continuum between well-definedness and ill-definedness. However, positioning a problem within this continuum is not always easy, which may lead to difficulties in choosing an appropriate educational technology approach. We propose a classification of the degree of ill-definedness of educational problems based on the existence of solution strategies, the implementation variability for each solution strategy, and the verifiability of solutions. The classification divides educational problems into five classes: 1) one single solution, 2) one solution strategy with different implementation variants, 3) a known number of typical solution strategies, 4) a great variety of solution strategies beyond the anticipation of a teacher where solution correctness can be verified automatically, and 5) problems whose solution correctness cannot be verified automatically. The benefits of this problem classification are twofold. First, it helps researchers choose or develop an appropriate modeling technique for educational systems. Second, it offers the learning technology community a communication means to talk about sorts of more or less ill-defined educational problems more precisely.
iQuant: A fast yet accurate GUI tool for transcript quantification

Transcript quantification using RNA-seq is central to contemporary and future transcriptomics research. The existing tools are useful but have much room for improvement. We present a new statistical model, a fast yet accurate transcript quantification algorithm. Our tool takes RNA-seq reads in fasta or fastq format as input and output transcript abundance through a few mouse clicks. Our method compares favorably with the existing GUI tools in terms of both time complexity and accuracy. Availability: Both simulation data used for method comparisons and the GUI tool are freely available at http://asammate.sourceforge. net/.
Can clock drawing differentiate Alzheimer's disease from other dementias?

ABSTRACT Background: Studies have shown the clock-drawing test (CDT) to be a useful screening test that differentiates between normal, elderly populations, and those diagnosed with dementia. However, the results of studies which have looked at the utility of the CDT to help differentiate Alzheimer's disease (AD) from other dementias have been conflicting. The purpose of this study was to explore the utility of the CDT in discriminating between patients with AD and other types of dementia. Methods: A review was conducted using MEDLINE, PsycINFO, and Embase. Search terms included clock drawing or CLOX and dementia or Parkinson's Disease or AD or dementia with Lewy bodies (DLB) or vascular dementia (VaD). Results: Twenty studies were included. In most of the studies, no significant differences were found in quantitative CDT scores between AD and VaD, DLB, and Parkinson's disease dementia (PDD) patients. However, frontotemporal dementia (FTD) patients consistently scored higher on the CDT than AD patients. Qualitative analyses of errors differentiated AD from other types of dementia. Conclusions: Overall, the CDT score may be useful in distinguishing between AD and FTD patients, but shows limited value in differentiating between AD and VaD, DLB, and PDD. Qualitative analysis of the type of CDT errors may be a useful adjunct in the differential diagnosis of the types of dementias.
Image completion with global structure and weighted nuclear norm regularization

Structure and nonlocal patch similarity have been used successfully to enhance the performance of image restoration. However, these techniques can often remove textures and edges, or introduce artifacts. In this paper, we propose a novel image completion method that leverages the redundancy of nonlocal image patches via the low-rank regularization of similar patch groups. The textures and edges in these patches are preserved using an adaptive regularization technique based on the weighted nuclear norm. Furthermore, a new global structure regularization strategy, imposing ℓ1-norm sparsity on the image's high-frequency residual component, is presented to recover missing pixels while preserving structural information in the image. An efficient optimization technique, based on the Alternating Direction Method of Multipliers (ADMM) algorithm, is used to solve the proposed model. Experimental results show our method to outperform state-of-the-art image completion approaches, for various text-corrupted images and different ratios of missing pixels.
Low-dose CT detects more progression of bone formation in comparison to conventional radiography in patients with ankylosing spondylitis: results from the SIAS cohort

Objectives To compare the CT Syndesmophyte Score (CTSS) for low-dose CT (ldCT) with the modified Stoke Ankylosing Spondylitis Spine Score (mSASSS) for conventional radiographs (CR) in patients with ankylosing spondylitis (AS). Methods Patients with AS in the Sensitive Imaging in Ankylosing Spondylitis cohort had lateral cervical and lumbar spine CR and whole spine ldCT at baseline and 2 years. CR and ldCT images were scored by two readers, paired by patient, blinded to time order, per imaging modality. For the total score analysis, we used average scores of readers per corner on CR or quadrant on ldCT. For the syndesmophyte analysis we used individual reader and consensus scores, regarding new or growing syndesmophyte at the same corner/quadrant. Results 50 patients were included in the syndesmophyte analysis and 37 in the total score analysis. Mean (SD) status scores for mSASSS (range 0–72) and CTSS (range 0–552) at baseline were 17.9 (13.8) and 161.6 (126.6), and mean progression was 2.4 (3.8) and 17.9 (22.1). Three times as many patients showed new or growing syndesmophytes at ≥3 quadrants on ldCT compared with ≥3 corners on CR for individual readers; for consensus this increased to five times. In 50 patients, 36 new or growing syndesmophytes are seen on CR compared with 151 on ldCT, most being found in the thoracic spine. Conclusions ldCT, covering the whole spine, detects more progression in the form of new and growing syndesmophytes in patients with AS compared with CR, which is limited to the cervical and lumbar spine. Most progression occurred in the thoracic spine.
Chemical synthesis and biotinylation of the thrombospondin domain TSR2

The type 1 repeat domain from thrombospondin has potent antiangiogenic activity and a structurally interesting fold, making it an attractive target for protein engineering. Chemical synthesis is an attractive approach for studying protein domains because it enables the use of unnatural amino acids for site‐specific labeling and detailed structure‐function analysis. Here, we demonstrate the first total chemical synthesis of the thrombospondin type 1 repeat domain by native chemical ligation. In addition to the natural domain, five sites for side chain modification were evaluated and two were found to be compatible with oxidative folding. Several challenges were encountered during peptide synthesis due to the functional complexity of the domain. These challenges were overcome by the use of new solid supports, scavengers, and the testing of multiple ligation sites. We also describe an unusual sequence‐specific protecting group migration observed during cleavage resulting in +90 Da and +194 Da adducts. Synthetic access to this domain enables the synthesis of a number of variants that can be used to further our understanding of the biochemical interaction network of thrombospondin and provide insight into the structure and function of this important antitumorogenic protein domain.
Correlations Between B‐Mode Ultrasonic Image Texture Features and Tissue Temperature in Microwave Ablation

Objective. The purpose of this study was to find the correlations between B‐mode ultrasonic tissue texture features and tissue temperature in microwave ablation. Methods. A total of 20 in vitro porcine liver samples were used for microwave ablation experiments. B‐mode ultrasonic images under various temperatures were acquired. The texture features of the differential images based on the gray level histogram, including the mean of the gray scale (MGS), standard deviation of the gray scale, and entropy of the gray scale (ENT), and those based on the gray level co‐occurrence matrix, including the contrast (CON), angular second moment (ASM), inverse difference moment (IDM), and correlation, were extracted. Correlations between the features and liver sample temperature were analyzed. In addition, water bath heating experiments were also performed on 15 in vitro porcine liver samples for analysis validation. Results. The correlation coefficients across the MGS, ENT, and ASM in 4 directions (0°, 45°, 90°, and 135°), the CON and IDM in 3 directions (45°, 90°, and 135°), and a temperature range of 15°C to 90°C were high and greater than 0.9 during microwave ablation. All texture features of the differential B‐mode ultrasonic images changed with rising temperature from 25°C to 60°C during water bath heating. Conclusions. Changes in image features reflect changes in tissue temperature during microwave ablation.
Survival Analysis for Truncated Data and Competing Risks

The purpose of this project is to consider the problems of left truncation and competing risks in analyzing censored survival data, and to compare and contrast various approaches for handling these problems. The motivation for this work comes from an analysis of data from the Cache County Memory Study. Study investigators were interested in the association between early-life psychologically stressful events (e.g., parental or sibling death, or parental divorce, among others) and late-life risk of Alzheimer's disease (AD). While conventional methods for censored survival data can be applied, the presence of left truncation and competing risks (i.e., other adverse events such as death that may lead to censoring with respect to AD) may require some consideration in order to avoid potential bias in terms both of estimation and inference. In this paper we briefly summarize the issues of truncation and competing risks in the context of survival analysis, and apply and compare several approaches suggested in the literature to the Cache County Data.
Political Institutions and Corporate Governance Reforms in Southeast Asia

While the weak corporate governance has been identified as among the leading contributing factors that led to the Asian financial crisis, the progress in restructuring corporate governance has been rather modest in Southeast Asia following the crisis. Some common features of corporate governance in Southeast Asian countries, such as high concentration of ownership and lack of adequate disclosure, have been remarkably resilient to the frustration of the reformers. In this paper, we argue that the observed rigidities in corporate governance structure in Southeast Asia may be due to the political institutions as well as the interaction between these institutions and the corporate sectors. Our analysis also finds that there are substantive variations in corporate governance across Southeast Asian countries, and that the differences in political institutions among these countries may account for much of the variations.
OpenBMI: A real-time data analysis toolbox for Brain-Machine Interfaces

Recently, there has been an increased demand for Brain-Machine Interface (BMI) toolboxes for neuroscientifc research. In many BMI applications, speller systems can provide an efficient communication channel for users with disabilities. Here, we introduce an open-source BMI toolbox termed ‘OpenBMI’, which supports the various signal processing chains for common BMI paradigms, such as event-related potentials (ERPs) and steady-state visual evoked potentials (SSVEP). The OpenBMI framework consists of ready-to-use experimental paradigms, offline data analysis techniques, online feedback as well as evaluation modules. The data analysis modules provide essential pre-processing steps (segmentation, baseline correction, etc.) as well as signal processing algorithms such as temporal and spatial filtering, artifact rejection, among others. The experimental paradigms of ERP and SSVEP are available with fully open-sourced demo scripts. Users can easily modify or extend the demo scripts for their needs. In this article, the OpenBMI framework, its features as well as its future development plan is introduced.
Artificial-Noise-Aided Secure Channel with a Full-duplex Source

This paper consider a new secure communication scene where a full-duplex transmitter (Alan) need to transmit confidential information to a half-duplex receiver (Bob), with a silent eavesdropper (Eve) that tries to eavesdrop the confidential information. For realizing secure communication between Alan and Bob, a novel two phases communication scheme is proposed: in Phase 1, Alan and Bob send artificial noises (AN) simultaneously, while in Phase 2, Alan superimposes the AN received in Phase 1 with its confidential signal and sends the mixed signalto Bob. Since the mixed AN could degrade the SINR (Signal to Interference and Noise Ratio) of Eve, but does not affect the SINR of Bob, a secrecy capacity can be achieved. We also derive the conditions that the secrecy capacity of the proposed scheme exists, and analyze the secrecy outage probability under Rayleigh fading channel. Numerical results show that the secrecy capacity is about two times higher than without AN, even though in the proposed scheme half of the time is used to transmit ANs, and the outage probability is about five times lower than that without AN.
Does slum formalisation without title provision stimulate housing improvement? A case of slum declaration in Pune, India

Though previous studies have examined how formalising land tenure affects housing improvements in informal settlements, the role of tenure security and its long-term influence remain unclear. In response, this paper quantitatively examines the extent to which formalising land tenure by way of slum declaration has stimulated housing improvements during the last three decades in the slums of Pune, India. Since slum declaration guarantees residents occupancy but not full property rights, this study focuses on how tenure security contributes to housing outcomes, such as materials, size, the number of floors and the amount of money spent for the improvements. Using original household survey data, analysis involving propensity score matching and difference-in-differences methods reveals that slum declaration has tripled a household’s likelihood of having added a second floor and, albeit less clear, increased the average amount of money spent on housing improvements. At the same time, slum declaration has not induced any improvement in housing materials, largely since many residents of non-formalised slums have also replaced materials. These results indicate that slum declaration, even in the long run, has continued to influence housing investments in Pune’s slums, in terms of both type and amount spent, though residents of non-formalised slums have also come to enjoy certain de facto tenure security. Among other implications for policy, these findings underscore that governments should at least provide legal assurance of occupancy rights in informal settlements, even if active interventions such as slum upgrading and titling are currently difficult.