Miracle-dz/UniFAR-FTUs huggingface dataset:
Mean scatterer space estimation from ultrasound signals combining singular spectral analysis and entropy

Introduction: Ultrasound (US) is a nonionizing radiation capable of real time imaging at low cost. Its most attractive application is quantitative tissue characterization with the objective of differentiating normal tissues from diseased tissues. In this study, an automated method using singular spectrum analysis (SSA) to estimate the mean scatterer space (MSS) of US signals is proposed. Methods: Entropy was used to determine the optimal number of components for the SSA. Subsequently, this number was compared with the results using a fixed number of components. A method based on the spectrum of the original signal was also used for comparison. The method was evaluated by using 24,000 simulated US signals, i.e., echoes and jitters backscattered from samples with different ratios of regular-to-irregular structure, as well as with 152 signals obtained from a phantom made of nylon wires. Results: For the simulated signals, the proposed method for estimating the MSS presented results similar to the other methods that were tested. However, the magnitude-of-the-spectrum method loses the phase information, and hence, does not allow the characterization of irregular structures. For the signals recorded from the phantom, the methods using SSA and entropy achieved better results. Conclusion: In this study, the combination of SSA with entropy to estimate the MSS of a periodic or quasi-periodic medium was proposed. The proposed method achieved similar or better results compared with two other methods found in the scientific literature. The novelty of the proposed method is the application of entropy as a quantitative criterion for selecting the SSA periodic components, allowing it to become independent of heuristic criteria.
Differential protein expression between normal and degenerated human nucleus pulposus cells by proteomic and bioinformatics analyses

Low back pain is a chronic disease associated with the degeneration of lumbar intervertebral disc (IVD). The molecular and cellular basis of degenerate IVD disorder remains largely unclear. Using 2-D electrophoresis, mass spectrometric analyses, database searching and western blot assay, we examined differential protein expression between normal surrogates and degenerated human nucleus pulposus (NP) cells. Ten protein spots with most altered differential expression levels between normal surrogates and degenerated NP cells were identified. Among these, five proteins showed decreased expression in degenerated NP cells, including SID 1 transmembrane family member 2, isoform 1 of proteasome activator complex subunit 3, transaldolase 1, isoform 1 of 26S protease regulatory subunit 8 and guanylate cyclase soluble subunit beta-1. Conversely, five proteins showed increased expression in degenerated NP cells including peroxiredoxin 2, superoxide dismutase, isoform 2 of neutrophil gelatinase-associated lipocalin, peroxiredoxin-4 and isoform 4 of Calumenin. Further, bioinformatics analysis hints that these differentially expressed proteins bear characteristics of membrane-like molecules with antioxidant function. Collectively, differentially expressed proteins might serve as biomarkers of the degenerate IVD and help us to understand the pathogenesis of IVD.
An Approach for Assessing Logs by Software Fault Injection

Nowadays, an increasing number of systems needs to be kept running for long periods without showing failures, but several factors compromise their correct behavior during the operational phase. Logs play a key role to address dependability issues of current systems and to enable proactive actions against failures (e.g., proactive maintenance, failure prediction). Nevertheless, they may lack any information in case of software faults, which escape the testing phase and are activated on the field by complex environmental conditions. In this paper, we evaluate built-in logging capabilities of a software system, namely the Apache Web Server, by means of an extensive software fault injection campaign. We experience that, in most of cases, software faults lead to failures without leaving any information in Apache logs. For this reason, we provide a few guidelines for developers that can be used during the development cycle, in order to improve the effectiveness of logs during the operational phase.
45 22 v 1 [ he pph ] 1 6 A pr 2 01 3 Mass Spectrum of Heavy Quarkonium Hybrids

We have extended the calculation of the correlation functions of heavy quarkonium hybrid operators with various J quantum numbers to include QCD condensates up to dimension six. In contrast to previous analyses which were unable to optimize the QCD sum-rules for certain J , recent work has shown that inclusion of dimension six condensates stabilizes the hybrid sum rules and permits reliable mass predictions. In this work we have investigate the effects of the dimension six condensates on remaining channels. After performing the QCD sum rule analysis, we update the mass spectra of charmonium and bottomonium hybrids with exotic and non-exotic quantum numbers. We identify that the negative-parity states with J = (0, 1, 2), 1 form the lightest hybrid supermultiplet while the positive-parity states with J = (0, 1), (0, 1, 2) belong to a heavier hybrid supermultiplet, confirming the supermultiplet structure found in other approaches. The hybrid with J = 0 has a much higher mass which may suggest a different excitation of the gluonic field compared to other channels. In agreement with previous results, we find that the J = 1 charmonium hybrid is substantially heavier than the X(3872), which seems to preclude a pure charmonium hybrid interpretation for this state.
An auditory model for coding speech into nerve-action potentials

In this paper we present a model for coding arbitrary acoustic stimuli into auditory nerve action potentials. The model consists of an inner ear model with high dynamic compression, and an existing inner hair-cell and auditory nerve-synapse model. For this study, we have tuned the model to recent psychophysical data [3]. As the dynamic range of the sensory cells is limited, the challenge lies in the inner ear providing appropriate compression so that sound signals can be coded into action potentials without loss of information.
Depression and Its Associated Factors among Lower Limb Amputees at Hospital Kuala Lumpur and Hospital Sultanah Bahiyah: A Cross Sectional Study

Introduction: Clinical reports have indicated that a significant number of lower limb amputees are experiencing psychological adjustment problems. To date, there is a dearth of studies documenting depression among lower limb amputees (LLA) in Malaysia. Objective: The objective of this study is to determine the prevalence of depression among LLA and its associated factors. Methods: This is a cross-sectional study involving 196 LLA who attended the Rehabilitation Medicine Clinics at Hospital Kuala Lumpur and Hospital Sultanah Bahiyah, Alor Setar. Beck Depression (BDI), Multi-Dimensional Perceived Social Support (MSPSS), World Health Organisation Quality of Life Brief Scale (WHOQOL-BREF) and Mini-International Neuropsychiatric Interview (MINI) were used. Results: 47.4% of LLA had depressive symptoms. 24.5% of these patients were diagnosed to have major depression. The findings revealed depression was associated with younger age, being single, low educational, bilateral side of amputation, trauma as a reason for amputation, absence of prosthesis as type of walking aid, shorter duration of amputation absence of medical co-morbidity among amputees, low social support and poor quality of life. Low perceived social supports and absence of medical comorbidities among amputees emerged as a significant predictor of depression among LLA in multivariate analysis. Conclusion: Present study demonstrated high percentage of clinical depression in amputees. These findings should encourage those in rehabilitation services to screen for depression in those attending their services to ensure a holistic management in these patients.
La transplantation rénale pédiatrique Pediatric Kidney Transplantation

The pediatric population represents a small part of the patients on waiting list for kidney transplantation or transplanted each year (~ 3 to 5% according to the country). In France, more than 3,000 kidney transplantations were yearly performed in the last years, including 100 to 120 grafts in pediatric recipients (less than 18 years at registration on waiting list). The level of priority given to pediatric recipients varies in relation to the country. In France, good access to transplantation for children and adolescents is provided with a median duration on waiting list of 7 versus 25 months in adult patients with one third of preemptive transplantations. Graft survival has progressively increased over time with decreasing of early graft losses according to better prevention of thrombosis and acute rejection. In the recent cohorts, actuarial graft survival is over 80% at 5 years and close to 70% at 10 years. Living donor transplantation is responsible for a better graft survival but remains underdeveloped in France compared to other countries. Graft with kidney from small donors and young recipients presents an increasing risk of early graft loss. Adolescents and young adults have a worse long-term survival due to poor adherence to treatment. Survival, growth, social and professional life and quality of life are improved in pediatric recipients after kidney transplantation in comparison to dialysis period. This treatment should be offered as soon as possible to all children with end-stage renal disease.
An Energy Efficient Environmental Sensor Network for Data Collection

Wireless sensor networks allow real-time, environmental data collection but are limited by unreliable communication links, node failures, and battery life. A robust network must handle failure of nodes and adapt its behavior to conserve energy by powering off nodes when not in use. This leads to the problem of node synchronization, as messages cannot be sent or received during power down mode. This research constructed a complete wireless sensor network that allowed data from any number of distributed sensor nodes to be collected and displayed. Challenges tackled include power management, node failures, synchronization, and adaptive routing of data messages. The system uses reference broadcasts to maintain synchronization, and gradient-based routing to send data towards the sink. In neither of these protocols do nodes need to have knowledge of the network beyond the nodes they can contact directly. This allows the network to be more adaptable to changes due to nodes entering and leaving the network. The developed system will greatly reduce the cost and complexity of environmental monitoring and data collection.
Crystal Graph Neural Networks for Data Mining in Materials Science

Machine learning methods have been employed for materials prediction in various ways. It has recently been proposed that a crystalline material is represented by a multigraph called a crystal graph. Convolutional neural networks adapted to those graphs have successfully predicted bulk properties of materials with the use of equilibrium bond distances as spatial information. An investigation into graph neural networks for small molecules has recently shown that the no distance model performs almost as well as the distance model. This paper proposes crystal graph neural networks (CGNNs) that use no bond distances, and introduces a scale-invariant graph coordinator that makes up crystal graphs for the CGNN models to be trained on the dataset based on a theoretical materials database. The CGNN models predict the bulk properties such as formation energy, unit cell volume, band gap, and total magnetization for every testing material, and the average errors are less than the corresponding ones of the database. The predicted band gaps and total magnetizations are used for the metalinsulator and nonmagnet-magnet binary classifications, which result in success. This paper presents discussions about high-throughput screening of candidate materials with the use of the predicted formation energies, and also about the future progress of materials data mining on the basis of the CGNN architectures.
THE IMPACT OF NON-CONFORMANCES ON PATIENT CARE AT A PATHOLOGY TERTIARY CARE LABORATORY IN SOUTH AFRICA

Introduction Although several studies have reported that laboratory errors may have some effect on patient care, few have studied non-conformance reports specifically. Clinical governance is a framework through which laboratories can improve the quality of their service and boost high standards of patient care. One of the measures of achieving this is by the identification and control of errors. For the purpose of this publication, non-conformances will refer to the recognition and documentation of laboratory errors. They are activities that fail to conform to specified standards. Methods This was a retrospective study of the non-conformance reports for five accredited pathology divisions (Chemical Pathology, Haematology, Medical Microbiology, Immunology, and Virology) at an academic tertiary laboratory of the National Health Laboratory Service, Tygerberg Hospital over a three year period. The medical records of patients that were directly implicated by the non-conformances were reviewed to determine the impact to their healthcare. Results Five hundred and eighty-three non-conformance reports were recorded across the divisions with chemistry having 140 (24%), haematology 65 (11%), medical microbiology 122 (21%), virology 211 (36%) and immunology 45 (8%). Three hundred and sixty-eight (63%) non-conformances had a major impact on patient care such as: delay in treatment in 52 (20%) cases, specimen recollection in 27 (11%) cases, inappropriate or unnecessary therapy in 44 (17%) cases, and inadequate patient care in 56 (22%) cases. Conclusion Although the data was limited by poor adherence to documentation, this could serve as a pilot study where laboratories can be encouraged to document non-conformance reports better so that the appropriate impact of non-conformances on patient care can be ascertained subsequently. With continuous quality improvement measures in the laboratory, more favorable patient outcomes are expected.
ON DESIGNING H ∞ FAULT DETECTION FILTER FOR MARKOVIAN JUMP LINEAR SYSTEMS WITH POLYTOPIC UNCERTAINTIES

This paper deals with the problem of robust fault detection for Markovian jump linear systems with polytopic uncertainties. Using a generalized form of observerbased fault detection filter (FDF) as a residual generator, the design of robust FDF is formulated in the framework of stochastic H∞ filtering. Based on analyzing the robust mean square stability and stochastic H∞ performance of the FDF, sufficient conditions on the existence of both mode-dependent and mode-independent H∞ FDFs are respectively derived and solutions to the H∞ FDFs are given in terms of linear matrix inequalities. A numerical example is given to show the effectiveness of the proposed method.
KINEMATICAL AND LOAD SHARING EFFECT OF A NOVEL POSTERIOR DYNAMIC STABIIZATION SYSTEM IMPLNATED IN LUMBAR SPINE

INTRODUCTION Posterior dynamic stabilization systems (PDS) has been proposed as an alternative solution for treatment of degenerative disc disease. PDS systems are designed to restore the kinematics of destabili zed segment to its intact state. The objective of this study was to investigate the biomechanical effect of a novel PDS system on lumbar spine. A cadaveric experiment followed by a Finite Element (FE) modeling approach were used for this purpose.
P63, a marker of the proliferative basal layers of skin epithelia and the hair follicle

In this experiment, we investigated that the P63 protein varied in normal hair cycle and hair regeneration process after hair follicles were thoroughly destroyed by cyclophosphamide. Regeneration of the destroyed cells is an optimal model for the research of cell proliferation. BrdU was used to identify which part of skin was destroyed and the new cells regenerated (without or with new cells) in this CYP-injection induced dystrophy. The new cells in hair cycle were also labeled by BrdU. P63-positive cells and new cells were identified at basal layers of skin epithelia and outer root sheath of hair, which provided an evidence for the research result that the p63 is a marker of the proliferative basal layers of skin epithelia. IHC results showed that less p63-positive cells appeared in the in the resting phase (telogen), and new cells also significantly decreased in this phase. Much more p63-positive cells appeared in later anagen than early anagen, but reverse situation happened to the high proliferative cells (marked by BrdU). Most p63-positive cells congregated along the inner side of the hair matrix, whereas the new cells scattered in the hair matrix at anagen phase. These results suggested that p63 is not sufficient to be a marker of high proliferative cells of the hair follicles.
Characterizing Urban Growth and Peri-Urban Landscape Change in Rondônia using Multiple Endmember Spectral Mixture Analysis

This study explored the utility of multiple endmember spectral mixture analysis (MESMA) to capture patterns of change in urban and peri-urban land cover through time. MESMA models measured spectra as the linear sum of spectrally pure endmembers and allows endmembers to vary on a per-pixel basis. We analyzed ten urban centers in the state of Rondônia using Landsat TM/ETM+ imagery corresponding to the years 1985, 1990, 1995, and 2000. MESMA was applied to each sample, and two categories of maps were generated: (a) maps of the sub-pixel abundance of generalized urban materials (impervious surfaces, vegetation, and soil), and (b) maps of model complexity (i.e., the number of endmembers required to adequately model each pixel). Model complexity was found to be highly correlated with degree of human impact on the landscape. The relationships between model complexity, urban growth, and changes in the peri-urban landscape were explored in the context of this tropical forest frontier environment.
Guarantee of Service Processing Time of Process Group for Multimedia Application

Computer performance has improved year by year. As a result, multimedia applications can be executed on a computer simultaneously. However multimedia applications sometimes can not provide a good service because multimedia applications compete with themselves to get computer resources. For this reason, computer resources need to be reserved for multimedia applications to provide a good service. Besides, there are a lot of service applications that consist of multi process. Thus multi process need to be a unit of resource reservation to provide a service of appropriate quality. We call multi process a process group. In this paper, we propose execution that is a unit of processor time assignment. In addition we propose a mechanism for guaranteeing processing time of process groups by ex-ecutions .
Criteria for Evaluating a Game-Based CALL Platform.

Game-based Computer-Assisted Language Learning (CALL) is an area that currently warrants attention, as task-based, interactive, multimodal games increasingly show promise for language learning. This area is inherently multidisciplinary – theories from second language acquisition, games, and psychology must be explored and relevant concepts from each drawn together. Based on extensive research in these three areas and on subsequent evaluation in the context of a newly developed immersive language learning game (Digichaint), this paper proposes nine criteria that should be taken into account both at the design and evaluation stages of game-based CALL platforms.
Towards Model-adaptive Control in Online Service Environments

There is a growing interest in implementing online control frameworks that manage distributed computing systems for power and performance objectives. While such frameworks continuously manage the system to optimize resource allocation and respond to dynamic environment input, they often rely upon static models of application behavior that do not adapt to slow behavior changes that occur during normal operation. By introducing adaptive models that dynamically adjust to the changing performance profile of an application, a robust controller can maintain performance objectives through normal changes that can occur in production and those introduced by software errors. In this paper, we characterize the effects of events that change an application’s performance profile over time. Such studies motivate the need for model-adaptive control to maintain system power and performance objectives over time under dynamic operating conditions.
Combining Wavelets and 2 D Gabor Descriptors for Iris Recognition in Noncooperative Environments

Nowadays, there are many open issues related to iris recognition in noncooperative environments. This work explores the fusion of Wavelet and 2D Gabor descriptors, two well successful feature descriptors used in the iris recognition literature. The main contribution of this work is how the fusion of Wavelet and 2D Gabor filter descriptors is made, resulting in a powerful iris descriptor. We conducted experiments on two widely used databases, CASIA-IrisV4, in which the iris images are acquired in a well constrained environment, and UBIRIS.v2, where the iris images were captured in unconstrained conditions, representing more realistic situations. The experiments show that our implementation of combined descriptors achieves Equal Error Rate (EER) of 1.46% for the CASIA-Iris.v4 database, which are very close to the state-of-the-art, and EER of about 15% for the UBIRIS-V2 database (decreasing the error in 25%). Keywords—Iris recognition; Wavelet descriptor; 2D Gabor descriptor; CASIA and UBIRIS databases
Walking assist effects based on rhythm input on upper limbs by the wearable robot

With recently rapid aging in Japan, it becomes important to conduct walking support for the elderly person whom walking function decreased gradually with increase of aging. On the other hand, it became clear the importance of the cooperative relationship between upper and lower limbs in walking. This study aims to promotion of walking function of elderly person by rhythm input to upper limbs. Specifically, we inspected a walk assist effect using wearable robot which let upper limbs drive by rhythm input. The rhythm to input was generated based on swing movement of upper limbs in walking. In this experiment, the wearable robot was applied to normal elderly person under three conditions with different drive timings of the wearable robot. We analyzed the data on their walking measured by the encoder and accelerator sensor. Finally, we obtained positive results on the evaluation of stride lengths and upper and lower swing degrees.
Mathematical model of workforce scheduling problem in flow shop with makespan minimization

We study a hand-intensive production flow-shop with variable workers’ productivity. Actual processing times of jobs are assumed to vary depending on their position on the schedule. A mathematical model is proposed. Computational experiments are run using different datasets in order to evaluate the power of the model in terms of efficiency and efficacy to solve the problem.