Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling and Analysis of Queuing Systems in Banks: (A Case Study of Banque Commerciale du Congo-BCDC/Mbujimayi)

This study examined the application of queue theory in the banking system in Democratic Republic of Congo, with particular reference to BCDC (Banque Commerciale du Congo)/Mbujimayi. The queuing characteristics of the bank were analyzed using a Multi-Server Queuing Model. The obvious implication of customers waiting in long and winding queues could result to prolonged discomfort and economic cost to them; however increasing the service rate will require additional number of tellers which implies extra cost to management. Data for this study was collected at BCDC bank for one week through observations and was formulated as multi-server single line queuing model. The data was analyzed using TORA optimization Software as recommended software for operational research. The performance measures of different queuing systems were evaluated and analyzed. The results of the analysis showed using a six-teller system was better than a five in terms of average waiting time.
Reconfiguring the Imaging Pipeline for Computer Vision : Supplemental Material

For readers unfamiliar with the ISP pipeline, we describe the standard pipeline found in any modern camera, from DSLRs to smartphones. This expands on Section 3.1 in the main paper. We consider a complete system including a computer vision algorithm that processes images and produces vision results. Figure 1a in the main paper depicts the traditional pipeline. The main components are an image sensor, which reacts to light and produces a RAW image signal; an image signal processor (ISP) unit, which transforms, enhances, and compresses the signal to produce a complete image, usually in JPEG format; and the vision application itself.
A cell-permeant peptide corresponding to the cUBP domain of USP5 reverses inflammatory and neuropathic pain

Background Cav3.2 T-type calcium currents in primary afferents are enhanced in various painful pathological conditions, whereas inhibiting Cav3.2 activity or expression offers a strategy for combating the development of pain hypersensitivity. We have shown that Cav3.2 channel surface density is strongly regulated by the ubiquitination machinery and we identified the deubiquitinase USP5 as a Cav3.2 channel interacting protein and regulator of its cell surface expression. We also reported that USP5 is upregulated in chronic pain conditions. Conversely, preventing its binding to the channel in vivo mediates analgesia in inflammatory and neuropathic pain models. Results To identify which USP5 domain is responsible for the interaction, we used a series of USP5-derived peptides corresponding to different regions in nUBP, cUBP, UBA1, and UBA2 domains to outcompete full length USP5. We identified a stretch of amino acid residues within the cUBP domain of USP5 as responsible for binding to Cav3.2 calcium channels. Based on this information, we generated a TAT-cUBP1-USP5 peptide that could disrupt the Cav3.2/USP5 interaction in vitro and tested its physiological effect in well-established models of persistent inflammatory pain (CFA test) and chronic mononeuropathy and polyneuropathy in mice (partial sciatic nerve injury and the (ob/ob) diabetic spontaneous neuropathic mice). Our results reveal that the TAT-cUBP1-USP5 peptide attenuated mechanical hyperalgesia induced by both Complete Freund’s Adjuvant and partial sciatic nerve injury, and thermal hyperalgesia in diabetic neuropathic animals. In contrast, Cav3.2 null mice were not affected by the peptide in the partial sciatic nerve injury model. Cav3.2 calcium channel levels in diabetic mice were reduced following the administration of the TAT-cUBP1-USP5 peptide. Conclusions Our findings reveal a crucial region in the cUBP domain of USP5 that is important for substrate recognition and binding to the III-IV linker of Cav3.2 channels. Targeting the interaction of this region with the Cav3.2 channel can be exploited as the basis for therapeutic intervention into inflammatory and neuropathic pain.
Initial evaluation of the Older Adult Social-Evaluative Situations Questionnaire: a measure of social anxiety in older adults

ABSTRACT Background: The assessment of social anxiety in late life has been examined in few studies (e.g. Gretarsdottir et al., 2004; Ciliberti et al., 2011). The present study describes the creation and initial psychometric evaluation of a new, content valid measure of social anxiety for older adults, the Older Adult Social-Evaluative Situations Questionnaire (OASES). Methods: Psychometric properties of the OASES were evaluated in a community dwelling sample of older adults (N = 137; 70.8% female). Convergent validity was established by examining the relation between the OASES and the Liebowitz Social Anxiety Scale (LSAS), Social Phobia and Anxiety Inventory (SPAI), and Beck Anxiety Inventory (BAI). Discriminant validity was established by examining the relation between the OASES and measures of depression (Geriatric Depression Scale, GDS), perceived health status (Short Form Health Survey, SF-12), and demographic variables. The validity analyses of the OASES were based on a smaller sample with n values ranging from 98 to 137 depending on missing data on each questionnaire. Results: Internal consistency, measured by Cronbach's α, for the OASES total score was 0.96. All items on the OASES were endorsed by participants. Convergent validity was demonstrated by medium to large correlations with the SPAI, LSAS, and BAI. Support for discriminant validity was evidenced by small to medium correlations between the OASES and GDS, SF-12, and demographic variables. Conclusions: Evidence in support of convergent and discriminant validity of the OASES is discussed. Although the results from the present study suggest that this measure may assess anxiety in and avoidance of social situations salient to older adults, future studies are needed to further examine the psychometric properties of the OASES and replicate these results in both clinical and more diverse samples of older adults.
Longer longitudinal atrial dimension in patients with idiopathic paroxysmal atrial fibrillation: A possible cause of atrial fibrillation.

BACKGROUND The ostium of the superior pulmonary veins or superior vena cava has been reported to be an important source of the ectopic beats that initiate paroxysmal atrial fibrillation (PAF). The structural details of the atria in patients with idiopathic PAF, however, remain unknown. METHODS We studied 113 patients (92 men and 21 women) with idiopathic PAF and 128 normal control subjects (100 men and 28 women). None of the subjects in either group were found to have any evidence of structural cardiac disease. The echocardiographic measurements were performed in the apical 4-chamber view during end-systole of sinus rhythm. RESULTS The longitudinal dimension of the left and right atria was longer in patients with PAF who were not administered any drugs (non-drug-taking patients) than in the control subjects (P <.001 and P <.01, respectively). However, there were no significant differences in the transverse dimension of either atrium between such patients and control subjects. The longitudinal and transverse dimensions and volume determinations of atria were greater in the patients with idiopathic PAF who were administered class 1 antiarrhythmic drugs than in non-drug-taking patients (P <.05 to.001). In non-drug-taking patients, prolongation of the atrial longitudinal dimension did not depend on either age, the total frequency of PAF, or the interval from the first episode of PAF. The longitudinal dimension of the left and right atria was longer even in the patients with a short history of PAF (<1 month) as compared with control subjects (P <.001 and.05, respectively). CONCLUSIONS These observations suggest that there is prolongation of the longitudinal dimension in patients with idiopathic PAF independent of PAF frequency and age (and that PAF is probably a consequence of the prolongation).
Feature Selective Projection with Low-Rank Embedding and Dual Laplacian Regularization

Feature extraction and feature selection have been regarded as two independent dimensionality reduction methods in most of the existing literature. In this paper, we propose to integrate both approaches into a unified framework and design an unsupervised linear feature selective projection (FSP) for feature extraction with low-rank embedding and dual Laplacian regularization, with the aim to exploit the intrinsic relationship among data and suppress the impact of noise. Specifically, a projection matrix with an <inline-formula><tex-math notation="LaTeX">$l_{2,1}$</tex-math><alternatives><mml:math><mml:msub><mml:mi>l</mml:mi><mml:mrow><mml:mn>2</mml:mn><mml:mo>,</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msub></mml:math><inline-graphic xlink:href="liu-ieq1-2911946.gif"/></alternatives></inline-formula>-norm regularization is introduced to project original high dimensional data points into a new subspace with lower dimension, where the <inline-formula><tex-math notation="LaTeX">$l_{2,1}$</tex-math><alternatives><mml:math><mml:msub><mml:mi>l</mml:mi><mml:mrow><mml:mn>2</mml:mn><mml:mo>,</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msub></mml:math><inline-graphic xlink:href="liu-ieq2-2911946.gif"/></alternatives></inline-formula>-norm regularization can endow the projection with good interpretability. We deploy a coefficient matrix with low rank constraint to reconstruct the data points and the <inline-formula><tex-math notation="LaTeX">$l_{2,1}$</tex-math><alternatives><mml:math><mml:msub><mml:mi>l</mml:mi><mml:mrow><mml:mn>2</mml:mn><mml:mo>,</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msub></mml:math><inline-graphic xlink:href="liu-ieq3-2911946.gif"/></alternatives></inline-formula>-norm is imposed to regularize the data reconstruction errors in the low-dimensional subspace and make FSP robust to noise. Furthermore, a dual graph Laplacian regularization term is imposed on the low dimensional data and data reconstruction matrix for preserving the local manifold geometrical structure of data. Finally, an alternatively iterative algorithm is carefully designed for solving the proposed optimization model. Theoretical convergence and computational complexity analysis of the algorithm are also provided. Comprehensive experiments on various benchmark datasets have been carried out to evaluate the performance of the proposed FSP. As indicated, our algorithm significantly outperforms other state-of-the-art methods for feature extraction.
Microstrip Filters for RF/Microwave Applications [Book Review]

Time-Domain Computer Analysis of Nonlinear Hybrid Systems by Wenquan Sui My first thought upon picking up Time-Domain Computer Analysis of Nonlinear Hybrid Systems by Wenquan Sui was wondering just what kind of hybrid he was going to discuss. Dr. Sui’s hybrid world consists of bringing together finite difference time domain (FDTD) electromagnetic simulators with circuit level nonlinear device simulators. In spite of the fact that analyzing even a fraction of a printed circuit board can bring an electromagnetic simulator to its knees, there is a continuing drive to create simulators that will reduce more and more of our problems to a number. The bottom line is that we live in an age where we can join the circuit laws of Kirchoff to the electromagnetic formulations of Maxwell and the nonlinear physics of semiconductors and solve the lot on a desktop computer. Dr. Sui’s book takes on the formidable task of joining FDTD electromagnetic analysis with nonlinear circuit analysis. His treatment is application oriented rather than theoretical or historical. Working at Bell Labs, IBM Microelectronics, and Conexant has obviously motivated Dr. Sui toward the practical side of computer-aided design (CAD). This book appears targeted at the professional who uses CAD or develops CAD programs. Each topic is handled in depth, and the book covers a wide range of subjects quickly. This book is not oriented toward classroom
The impact of CD34+ cell dose on platelet engraftment in pediatric patients following unmanipulated haploidentical blood and marrow transplantation

Unmanipulated haploidentical blood and marrow transplantation has been developed as an alternative transplant strategy for pediatric patients with hematological diseases. The aim of this study was to investigate the effects of donor and recipient characteristics on hematopoietic recovery in pediatric patients following unmanipulated haploidentical transplantation.
A deliberation layer for instantiating robot execution plans from abstract task descriptions

We present an application of Hierarchical Task Network (HTN) planning to create robot execution plans, that are adapted to the environment and the robot hardware from abstract task descriptions. Our main intention is to show that different robotic platforms can make use of the same high level symbolic task description. As an off-the-shelf planning component, the SHOP2 HTN planner is adopted. All the domain knowledge is encoded in the Web Ontology Language (OWL) and stored in a world wide accessible database, which allows multiple systems to reuse and improve upon this knowledge. For task execution, the execution plan is generated using the CRAM plan language (CPL). We demonstrate the functionality of the system in executing a pick-and-place task in a simulated environment with two different service robots, the TU/e Amigo robot prototype and the Fraunhofer IPA Care-O-Bot 3. The experiment shows that although the robots differ in hardware capabilities, the use of HTN planning adds information that is crucial for successful task execution and enables both systems to successfully execute the instructed task.
Performance and cost optimization for multiple large-scale grid workflow applications

Scheduling large-scale applications on the Grid is a fundamental challenge and is critical to application performance and cost. Large-scale applications typically contain a large number of homogeneous and concurrent activities which are main bottlenecks, but open great potentials for optimization. This paper presents a new formulation of the well-known NP-complete problems and two novel algorithms that addresses the problems. The optimization problems are formulated as sequential cooperative games among workflow managers. Experimental results indicate that we have successfully devised and implemented one group of effective, efficient, and feasible approaches. They can produce soultuins of significantly better performance and cost than traditional algorithms. Our algorithms have considerably low time complexity and can assign 1,000,000 activities to 10,000 processors within 0.4 second on one Opteron processor. Moreover, the solutions can be practically performed by workflow managers, and the violation of QoS can be easily detected, which are critical to fault tolerance.
Optimization and Human Movement

Human movement is an ongoing optimization process. A baseball player attempts to contact a ball with a bat so as to propel the latter as far as possible; a rower tries to impart the maximum possible force to the water through an oar, while at the same time avoiding any disturbance to the boat’s forward motion. The cost functions involved are complex, implicit, nonunique, fuzzy, and often subjective. Hundreds of muscles—most of which are not under conscious control—are involved in every motion, and different body geometries, coaches, choreographers, etc., prescribe different criteria for optimal movement. At the same time, the results are unmistakeable: the difference between breakdancing and ballet is patently obvious, even to the untrained eye. Automatic generation of motion sequences is an interesting problem that has applications in graphics and animation, in training sequence generation, in gait analysis, and even in artistic innovation[2, 3, 7]. The moving picture industry, needless to say, has devoted tremendous numbers of cycles to this problem, but the algorithms involved rely on human animators to specify “keyframes” that act as skeletons for the movement. One can use mathematical interpolation techniques like splines to move individual body parts from one keyframe to another, but these kinds of methods do not address the problem of kinesiological illegality (e.g., that the knee only bends 180 degrees, or that arms cannot pass through ribcages). Many animation packages, such as Life Forms or Poser, use an augmented spline approach that relies on a table
A Glycosaminoglycan Extract from Portunus pelagicus Inhibits BACE1, the β Secretase Implicated in Alzheimer’s Disease

Therapeutic options for Alzheimer’s disease, the most common form of dementia, are currently restricted to palliative treatments. The glycosaminoglycan heparin, widely used as a clinical anticoagulant, has previously been shown to inhibit the Alzheimer’s disease-relevant β-secretase 1 (BACE1). Despite this, the deployment of pharmaceutical heparin for the treatment of Alzheimer’s disease is largely precluded by its potent anticoagulant activity. Furthermore, ongoing concerns regarding the use of mammalian sourced heparins, primarily due to prion diseases and religious beliefs, hinder the deployment of alternative heparin based therapeutics. A marine-derived, heparan sulphate-containing glycosaminoglycan extract isolated from the crab Portunus pelagicus, was identified to inhibit human BACE1 with comparable bioactivity to that of mammalian heparin (IC50 = 1.85 μg.mL-1 (R2 = 0.94) and 2.43 μg. mL-1 (R2 = 0.93), respectively) possessing highly attenuated anticoagulant activities. The results from several structural techniques suggest that the interactions between BACE1 and the extract from P. pelagicus are complex and distinct from those of heparin.
Human NK Cells Selective Targeting of Colon Cancer–Initiating Cells: A Role for Natural Cytotoxicity Receptors and MHC Class I Molecules

Tumor cell populations have been recently proposed to be composed of two compartments: tumor-initiating cells characterized by a slow and asymmetrical growth, and the “differentiated” cancer cells with a fast and symmetrical growth. Cancer stem cells or cancer-initiating cells (CICs) play a crucial role in tumor recurrence. The resistance of CICs to drugs and irradiation often allows them to survive traditional therapy. NK cells are potent cytotoxic lymphocytes that can recognize tumor cells. In this study, we have analyzed the NK cell recognition of tumor target cells derived from the two cancer cell compartments of colon adenocarcinoma lesions. Our data demonstrate that freshly purified allogeneic NK cells can recognize and kill colorectal carcinoma–derived CICs whereas the non-CIC counterpart of the tumors (differentiated tumor cells), either autologous or allogeneic, is less susceptible to NK cells. This difference in the NK cell susceptibility correlates with higher expression on CICs of ligands for NKp30 and NKp44 in the natural cytotoxicity receptor (NCR) group of activating NK receptors. In contrast, CICs express lower levels of MHC class I, known to inhibit NK recognition, on their surface than do the “differentiated” tumor cells. These data have been validated by confocal microscopy where NCR ligands and MHC class I molecule membrane distribution have been analyzed. Moreover, NK cell receptor blockade in cytotoxicity assays demonstrates that NCRs play a major role in the recognition of CIC targets. This study strengthens the idea that biology-based therapy harnessing NK cells could be an attractive opportunity in solid tumors.
Recognition of sign language using neural networks

This thesis details the development of a computer system (labelled the SLARTI system) capable of recognising a subset of signs from Auslan (the sign language of the Australian Deaf community), based on the pattern classification paradigm of artificial neural networks. The research discussed in this work has two main streams. The first is the creation of a practical sign classification system, suitable for use within a sign language training system or other applications based on hand gestures. The second is an exploration of the suitability of neural networks for the creation of a real-time classification system with the ability to process temporal patterns. Sign languages such as Auslan are the primary form of communication between members of the Deaf community. However these languages are not widely known outside of these communities, and hence a communications barrier can exist between Deaf and hearing people. The techniques for recognising signs developed in this research allow the creation of systems which can help to eliminate this barrier, either by providing computer tools to assist in the learning of sign language, or potentially the creation of portable sign-language-to-speech translation systems. Artificial neural networks have proved to be an extremely useful approach to pattern classification tasks, but much of the research in this field has concentrated on relatively simple problems. Attempting to apply these networks to a complex real-world problem such as sign language recognition exposed a range of issues affecting this classification technique. The development of the SLARTI system inspired the creation of several new techniques related to neural networks, which have general applicability beyond this particular application. This thesis includes discussion of techniques related to issues such as input encoding, improving network generalisation, training recurrent networks and developing modular, extensible neural systems.
Information Splitting Using Crypto-biometrics Approach

In this paper will be described a new idea and algorithm for secure information sharing using individual biometric patterns. Threshold schemes are classical cryptographic algorithms used for secret splitting or sharing. Those schemes aren't any connection between generated shares and owners of information shadows. Sometimes it may be worth to generate personalized shadows, which allow not only recovery the original information, but also to identify who exactly took part in the secret reconstruction procedure. Below authors describe algorithm for extraction of some personal or biometric characteristics (personal features) using intelligent information systems like cognitive systems, as well as the algorithm of application such personal information for shadow generation in threshold schemes. New approach of information splitting using crypto-biometrics may play a great role in intelligent information systems and secure information management.
Development and Psychometric Evaluation of the Ostomy Adjustment Inventory‐23

PURPOSE This article describes the development of the Ostomy Adjustment Inventory-23 (OAI-23), a self-report, multidimensional scale designed to assess psychosocial adjustment in patients with ostomy. SUBJECTS AND SETTING Five hundred seventy persons with a colostomy, ileostomy, or urostomy, who were randomly selected from 3 national databases, provided assessable data. RESULTS The results indicate that the OAI-23 is reliable (the Cronbach α = .93, split-half = 0.91, and test-retest (r) = 0.83) and valid, correlating positively with Felton's Acceptance of Illness Scale (r = 0.72) and confirming expected improvements in adjustment consistent with increasing time since surgery (F5,531 = 5.22, P < .001). Four factors (eigenvalue ≥ 1) that accounted for 55.4% of the total variance emerged from factor analysis. CONCLUSION The OAI-23 is a valid and reliable measure of psychosocial adjustment that will be of interest to both researchers investigating life after stoma surgery and clinicians making objective assessments of their patients' progress.