Miracle-dz/UniFAR-FTUs huggingface dataset:
The Influence of a Witness ’ Familiarity with the Perpetrator and Gender-Specific Stereotype Consistency on Witness Identification Accuracy

The present study examined the influence of an eyewitness’ familiarity with the perpetrator in conjunction with gender-specific stereotype consistency on eyewitness identification accuracy (N = 105). Neither eyewitness familiarity with the perpetrator nor stereotype consistency was significantly influential on overall eyewitness identification accuracy. Following a simultaneous, target-absent lineup procedure composed of four foils, participants who were familiar with the target provided more correct rejections when compared to those not familiar with the target; however, this was not significant. Similarly, more correct rejections were made by participants faced with an inconsistent gender-specific stereotype when compared to those effaced with a consistent stereotype; however, this also was not significant. No differences in foil identification decisions were observed. Implications and directions for future research are discussed.
Knee–Hip–Spine Syndrome: Improvement in Preoperative Abnormal Posture following Total Knee Arthroplasty

An ergonomic upright body posture is maintained by the alignment of the spine, pelvis, and lower extremities, and the muscle strength of body trunk and lower extremities. The posture varies with age because of the degenerative changes in the involved structures and the weakening of the muscles. The compensatory mechanisms underlying these changes have recently been evaluated, and the loss of lumbar lordosis results in spinal kyphosis, pelvic retroversion, hip extension, knee flexion, and ankle dorsiflexion. These mechanisms are referred to as the hip–spine and knee–spine syndromes. The spine, hip, and knee are anatomically connected, and the pain and discomfort of the lower back, hip, and knee frequently arise due to degenerative changes of these structures. Thus, these mechanisms are considered as the knee–hip–spine syndrome. Spinal fusion, total hip arthroplasty, and total knee arthroplasty are the surgical procedures for severe degeneration, and their clinical outcomes for the affected sites are promising. However, despite surgeries, other structures may degenerate and result in complications, such as proximal junctional kyphosis and hip dislocation, following spinal fusion. Therefore, it is necessary to evaluate each patient under specific conditions and to treat each section while considering associations between the target structure and entire body. The purpose of this article is to introduce postural maintenance, variations with age, and improvements with surgical interventions of spine, hip, and knee as the knee–hip–spine syndrome.
Phylogeny Simulation and Diversification Rate Analysis with TESS

This tutorial describes statistical approaches for inferring rates of lineage diversification (speciation – extinction) from empirical (i.e., estimated) phylogenetic trees—and for generating simulated phylogenetic trees—under various stochasticbranching process models using the R package TESS. TESS provides a flexible framework for specifying diversification models—where diversification rates are constant, vary continuously, or change episodically through time (including explicit models of mass-extinction events)—and implements numerical methods to estimate parameters of these models from estimated phylogenies. A major feature of TESS is the ability to include various methods of incomplete taxon sampling. Additionally, we provide robust Bayesian methods for assessing the relative fit of these models of lineage diversification to a given study tree—e.g., where steppingstone simulation is used to estimate the marginal likelihoods of competing models, which can then be compared using Bayes factors. We also provide Bayesian methods for evaluating the absolute fit of these branching-process models to a given study tree—i.e., where posterior-predictive simulation is used to assess the ability of a candidate model to generate the observed phylogenetic data. Finally, we show how TESS can be used to efficiently simulate phylogenies, and how these simulations can provide invaluable null hypotheses.
Comparison of platelet count , platelet indices and coagulation profile in preeclampsia and normal pregnancy

Aim: To compare platelet count, platelet volume indices (MPV and PDW) and coagulation profile in preeclampsia and normal pregnancy. Method: This comparative cross sectional study was performed at King Edward Medical University, Lahore and its affiliated hospitals. Study was conducted for six months after approval of synopsis.The patients fulfilling inclusion and exclusion criteria were enrolled after informed consent. Venous blood sample was properly taken in dipotassium EDTA (Ethylene diamine tetra acetic acid) vacutainer for platelet count and platelet volume indices. In sodium citrate vial the sample was taken from both groups (i.e.; normal pregnant woman and preeclamptic patients) for PT, APTT, FDPs, D-Dimers and fibrinogen level and tested within six hours of collection to minimize variations due to sample aging. Improperly collected samples (hemolysed and clotted samples) were discarded. Samples were stored at room temperature. Results: The mean age of patients with preeclampsia was 26.19±5.02 years and with normal pregnancy was 25.17±5.68 years. The mean platelets count in preeclampsia and normotensive pregnant female was 219.43±100.58 and 254.43±70.35 respectively. The mean platelet volume in preeclampsia and normotensive pregnant female was 9.78±0.96 and 9.34±1.30 respectively. The mean platelet distribution width (PDW) in preeclampsia and normotensive pregnant female was 12.43 ±3.45 and 11.98±3.45 respectively. The mean prothrombin time (PT) in preeclampsia and normotensive pregnancy was 14.52±3.16 and 13.60±1.75 respectively. The mean Activated partial thromboplastin time (APTT) in preeclampsia and normotensive pregnancy was 38.67±18.52 and 35.31±11.88 respectively. The mean Fibrinogen level in preeclampsia and normotensive pregnant female was 247.79±392.10 and 261.93±57.89 respectively. Among women with preeclampsia, the FDP of 35 (83.3%) women was <10 and of 7 (16.7%) was >10 whereas, among women with normal pregnancy group, all females (100%) had FDP <10. Conclusions:Current study shows that the hematological parameters such as platelet count, Mean platelet volume (MPV), Platelet Distribution Width (PDW), fibrinogen, FDPs and D-Dimers were differing in women with preeclampsia compared to normal pregnancy but were not statistically significant.
Evaluating the Effect of Online Compression on the Disk Cache of Storage System

A trace driven simulation of the disk cache of a mass storage system was used to evaluate the effect of an online compression algorithm on various performance measures. Traces from the system at NASA's Center for Computational Sciences were used to run the simulation and disk cache hit ra-tios, number of files and bytes migrating to tertiary storage were measured. The measurements were performed for both an LRU and a size based migration algorithm. In addition to seeing the effect of online data compression on the disk cache performance measure, the simulation provided insight into the characteristics of the interactive references, suggesting that hint based prefetching algorithms are the only alternative for any future improvements to the disk cache hit ratio.
Seismic Imaging of Supercritical Geothermal Reservoir Using Full-waveform Inversion Method

To examine the imaging capability of the supercritical water reservoirs as one of the future geothermal energies, we conducted simulations using full-waveform inversion (FWI) method. We studied two cases: one for active source, one for nearby natural earthquakes. For the first case, we assumed borehole active seismic source at the 2 km depth combined with seismic arrays at surface, borehole, observation well and horizontal well. The distributed acoustic sensor (DAS) is assumed as the array sensor in the borehole providing extremely dense seismic data. The result of full-waveform inversion showed very precise location, shape and physical properties (Vp, Vs and density) of the reservoir model. For the second case, we examined the use of near-by natural earthquakes as passive seismic sources. This case showed reasonable location, a shape of an igneous intrusion, but physical properties inside of intrusion are not well retrieved probably due to the limited locations of assumed natural earthquakes. In the future field study, we will use both of active and passive sources to obtain better imaging for the supercritical reservoirs. We think that supercritical water zone can be well imaged by the combination of the full-waveform method, active seismic sources and/or appropriated natural earthquakes, and the DAS seismic array(s) in the borehole and surface seismic array.
Improved HDR image reconstruction method

Recently, the importance of information enhancement methods in digital image processing has increased significantly. A large amount of research has been focused on information retrieval and image understanding. High dynamic range (HDR) of illumination may cause serious distortions and other problems in viewing and further processing of digital images. This paper describes a new algorithm for HDR image creation based on merging images taken with different exposure time.
Hypoxia Gene-expression Signature for Breast Cancer : Patient Survival Prediction and New Hypoxia-genes

Breast cancer is a heterogeneous disease characterized by different subtypes, age, clinical course and responsiveness to treatment. Although currently used prognostic and treatment-predictive markers have distinctly improved treatment decisions, additional markers are required to further tailor treatment for individual patients. Among the variety of factors contributing for cancer aggressiveness, hypoxia is a leading one in terms of lethal prognosis, by driving more than 60 genes related with cell survival and adaptation. In this work, a hypoxia gene signature was created based on available clinical data from breast cancer patients. Afterwards, this signature was validated and improved by comparison with the gene expression of 20 breast cancer cell lines. The final signature, composed of 18 genes, was then applied in the clinical data, and it showed a very remarkable distribution of the patients within 3 scores: [0-4], [5-13], and [1418] expressed genes out of the total. Moreover, the created hypoxia signature was used to find new hypoxia-related genes. Genes that are co-expressed with each one of the 18-selected genes were verified, and MFAP2 and TUBB6 demonstrated to be promising. TUBB6 was followed-up, and its expression is significantly higher in the mRNA level in 8 different cell lines. Moreover, HIF1 and HIF-2 knockdowns were used to further investigate hypoxia-regulation, and HIF-1 seems to be the primary regulator of TUBB6. A knockdown study of TUBB6 was also conducted and it confirmed its functionality by showing less chemoresistance to Paclitaxel.
Crabp1 Regulation of FAS RNA in Mouse Mammary Gland ASCs

4 Introduction: . 5 Methods: . 11 Results: . 14 Discussion: . 18 References: . 21 Figures: . 23
Enhancing Performance of Iris Recognition Algorithm through Time Reduction

Nowadays, for providing the secure facilities and services to the user, the accurate identification is necessary. The Iris recognition is one of the attractive approach for user’s identification, provides high level of security and convenience then the other methods of identification like traditional ID and password, which can be lost or transferred. However, the iris recognition algorithms are implemented on general purpose sequential processing systems, such as generic central processing units (CPUs). Parallel processing is an alternative offers an opportunity to enhance the performance of system by increasing the speed. The most time consuming part of Iris recognition algorithm is matching part, which is implemented using Verilog HDL through ISE Design suit (14.2), achieved significantly reduction in execution time. The proposed design is suitable for integration either in ASIC or FPGA.
Millennials’ Career Attitudes: The roles of Career Anchors and Psychological Empowerment

This study examines the mediating effect Millennials’ psychological empowerment perceptions on the relationship between their career anchors (technical/functional competence, general managerial competence, autonomy/independence, security/stability, entrepreneurial creativity, service/dedication to a cause, pure challenge and life style) and career attitudes. Participants were 492 engineers who are working in different Information Technology companies. The results indicate a significant relationship between Millennials’ psychological empowerment and their protean career attitudes. Hierarchical regression analyses show that the relationships between career anchors (autonomy, security, entrepreneurial creativity, service and pure challenge) and Millennials’ protean career attitudes are partially mediated by their psychological empowerment perceptions. The findings reveal that organizations should focus more on giving importance to empowerment mechanisms for Millennials that is the underlying effect between their career anchors and career attitudes.
Gradual Typing with Unification-Based Inference ; CU-CS-1039-08

Static and dynamic type systems have well-known strengths and weaknesses. Gradual typing provides the benefits of both in a single language by giving the programmer control over which portions of the program are statically checked based on the presence or absence of type annotations. This paper studies the combination of gradual typing and unification-based type inference, with the goal of developing a system that helps programmers increase the amount of static checking in their program. The key question in combining gradual typing and inference is how should the dynamic type of a gradual system interact with the type variables of an inference system. This paper explores the design space and shows why three straightforward approaches fail to meet our design goals. In particular, the combined system should satisfy the criteria for a gradual type system: 1) when a program is unannotated, only a few type errors are detected at compile-time and the rest are detected at run-time, and 2) when the program does not contain dynamic type annotations (implicitly or explicitly), the type system should statically detect all type errors. This paper presents a new type system based on the idea that a solution for a type variable should be as informative as any type that constrains the variable. We prove that the new type system satisfies the above criteria for a gradual type system. The paper also develops an efficient inference algorithm and proves it sound and complete with respect to the type system.
Sparse principal component analysis via axis‐aligned random projections

We introduce a new method for sparse principal component analysis, based on the aggregation of eigenvector information from carefully selected axis‐aligned random projections of the sample covariance matrix. Unlike most alternative approaches, our algorithm is non‐iterative, so it is not vulnerable to a bad choice of initialization. We provide theoretical guarantees under which our principal subspace estimator can attain the minimax optimal rate of convergence in polynomial time. In addition, our theory provides a more refined understanding of the statistical and computational trade‐off in the problem of sparse principal component estimation, revealing a subtle interplay between the effective sample size and the number of random projections that are required to achieve the minimax optimal rate. Numerical studies provide further insight into the procedure and confirm its highly competitive finite sample performance.
Searching for Optimal Models: Comparing Two Encoding Approaches

Search-Based Software Engineering (SBSE) is about solving software development problems by formulating them as optimization problems. In the last years, combining SBSE and Model-Driven Engineering (MDE), where models and model transformations are treated as key artifacts in the development of complex systems, has become increasingly popular. While search-based techniques have often successfully been applied to tackle MDE problems, a recent line of research investigates how a model-driven design can make optimization more easily accessible to a wider audience. In previous model-driven optimization efforts, a major design decision concerns the way in which solutions are encoded. Two main options have been explored: a model-based encoding representing candidate solutions as models, and a rule-based encoding representing them as sequences of transformation rule applications. While both encodings have been applied to different use cases, no study has yet compared them systematically. To close this gap, we evaluate both approaches on a common set of optimization problems, investigating their impact on the optimization performance. Additionally, we discuss their differences, strengths, and weaknesses laying the foundation for a knowledgeable choice of the right encoding for the right problem.
THE ROLE OF INFORMATION TECHNOLOGY IN KNOWLEDGE MANAGEMENT IN SMALL MEDIUM ENTERPRISE

The existence of Small Medium Enterprise (SME) has become a support and has a major influence on Indonesia's economic growth. Furthermore, the general problems and challenges of SMEs in several cities in Indonesia are lack of knowledge and low competitiveness. There were 57.8 million SME practitioners in Indonesia, with employment of 114 million people. Therefore, the purpose of this study was to determine the role of information technology (IT) on knowledge management applied by SME actors in Batam City, Riau Islands, Indonesia. This study involved 30 of 1006 SMEs in the entire city of Batam Kepri, Indonesia with 5 types of businesses including industry, services, trade, fisheries, plantations, agriculture, and livestock. The method used is multiple regression analysis with T-Test and F Model Test. Researchers want to assess the influence of information technology variables through IT knowledge, IT Operations, and IT Infrastructure variables on knowledge management in SME. The results of this study show at the 0.05 level of significance IT knowledge, IT Operations, and IT Infrastructure has a positive and significant effect on knowledge management. The results of the descriptive analysis state that the Acquisition and/or development of knowledge provides the largest contribution in the application of knowledge management for SMEs in Batam City.
Learning algorithm for nearest-prototype classifiers

Incremental learning algorithms are presented for nearest prototype (NP) classifiers. Fuzzification of the 1-NP and K-NP classification rules provides an explicit analytical expression of the membership of data to categories. This expression enables formulation of the protoype placement problem as mathematical programming which can be solved by using a gradient descent algorithm. In addition to the learning algorithm, analog electronic circuits are configured, which implement the 1-NP and k-NP classifiers.
Changing Semantic Role Representations with Holographic Memory 1

Semantic roles describe “who did what to whom” and as such are central to many subfields of AI and cognitive science. Each subfield or application tends to use its own “flavor” of roles. For analogy processing, logical deduction, and related tasks, roles are usually specific to each predicate: for loves there is a LOVER and a BELOVED, for eats an EATER and an EATEN, etc. Language modeling, on the other hand, requires more general roles like AGENT and PATIENT in order to relate form to meaning in a parsimonious way. Commitment to a particular type of role makes it difficult to model processes of change, for example the change from specific to general roles that seems to take place in language learning. The use of semantic features helps solve this problem, but still limits the nature and number of changes that can take place. This paper presents a new model of semantic role change that addresses this problem. The model uses an existing technique, Holographic Reduced Representation (HRR) for representing roles and their fillers. Starting with specific roles, the model learns to generalize roles through exposure to language data. The learning mechanism is simple and efficient, and is scaling properties are well-understood. The model is able to learn and exploit new representations without losing the information from existing ones. We present experimental data illustrating these principles, and conclude with by discussing some implications of the model for the issues of changing representations as a whole.
IDETC 2016-60053 ADAPTABILITY TRADEOFFS IN THE DESIGN OF SELF-ORGANIZING SYSTEMS

Self-organizing systems have great potential for adaptability, but as complex systems, they can also be prone to unpredictable behavior, cascading failures, and sensitivity to perturbations. Also, designing systems for adaptability may introduce overhead that reduces their performance. This paper investigates the design tradeoffs between adaptability and performance in the context of a box-pushing task. Using a genetic algorithm to optimize a parametric behavioral model, we are able to test systems optimized under different conditions for performance and reliability. It was found that a system optimized in the face of random initial conditions and internal perturbations was more robust than a system optimized without these perturbations, showing a higher overall fitness over diverse trials, but it could not take advantage of particular initial conditions that would have allowed it to achieve a one-off high fitness in a repeatable environment. A system optimized with predesigned initial conditions was found to achieve a very high fitness, but when it was retested with random initial conditions, its performance plummeted, indicating that it was fit to the ideal initial conditions but not robust.
0 N ov 2 01 8 Two-Dimensional Elliptic Determinantal Point Processes and Related Systems

We introduce new families of determinantal point processes (DPPs) on a complex plane C, which are classified into seven types following the irreducible reduced affine root systems, RN = AN−1, BN , B ∨ N , CN , C ∨ N , BCN , DN , N ∈ N. Their multivariate probability densities are doubly periodic with periods (L, iW ), 0 < L,W < ∞, i = √ −1. The construction is based on the orthogonality relations with respect to the double integrals over the fundamental domain, [0, L)× i[0,W ), which are proved in this paper for the RN -theta functions introduced by Rosengren and Schlosser. In the scaling limit N → ∞, L → ∞ with constant density ρ = N/(LW ) and constant W , we obtain four types of DPPs with an infinite number of points on C, which have periodicity with period iW . In the further limit W → ∞ with constant ρ, they are degenerated into three infinite-dimensional DPPs. One of them is uniform on C and equivalent with the Ginibre point process studied in random matrix theory, while other two systems are rotationally symmetric around the origin, but non-uniform on C. We show that the elliptic DPP of type AN−1 is identified with the particle section, obtained by subtracting the background effect, of the two-dimensional exactly solvable model for one-component plasma studied by Forrester. Other two exactly solvable models of one-component plasma are constructed associated with the elliptic DPPs of types CN and DN . Relationship to the Gaussian free field on a torus is discussed for these three exactly solvable plasma models.