Miracle-dz/UniFAR-FTUs huggingface dataset:
Satisfaction with Care in Late Stage Parkinson's Disease

In late stage Parkinson's disease (PD) (i.e., Hoehn and Yahr (HY) stages IV-V), both motor and nonmotor symptoms (NMS) are pronounced, and the patients become increasingly dependent on help in their daily life. Consequently, there is an increasing demand on health-care and social care resources for these patients and support for their informal caregivers. The aim of this study was to assess satisfaction with care in late stage PD patients and to identify factors associated with satisfaction with care. Moreover, to assess their informal caregivers' satisfaction with support and to identify factors associated with caregivers' satisfaction with support. Factors potentially associated with satisfaction with care/support were assessed in 107 late stage PD patients and their informal caregivers (n=76) and entered into multivariable logistic regression analyses. Fifty-eight (59%) of the patients and 45 (59%) of the informal caregivers reported satisfaction with their overall care/support. Patients satisfied with their care reported higher independence in activities of daily living (ADL) (Katz ADL index; P=0.044), less depressive symptoms (Geriatric Depression Scale, GDS-30; P=0.005), and higher individual quality of life (QoL) (Schedule for the Evaluation of Individual Quality of Life Questionnaire, SEIQoL-Q; P=0.036). Multivariable logistic regression analyses identified depressive symptoms (P=0.015) and independence in ADL (P=0.025) as independently associated with satisfaction with care. For informal caregivers, the analyses identified patients' HY stage (P=0.005) and caregivers' QoL (Alzheimer's Carers Quality of Life Inventory, ACQLI; P=0.012) as independently associated with satisfaction with caregiver support. The results indicate that an effective both pharmacological and nonpharmacological PD therapy is important, to adequately treat motor and NMS (e.g., depressive symptoms) in order to improve depressive symptoms and patient independence in ADL. This may benefit not only the patients, but also their informal caregivers.
Nanotecnología para textiles funcionales

Fil: Abraham, Gustavo Abel. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Mar del Plata. Instituto de Investigaciones en Ciencia y Tecnologia de Materiales. Universidad Nacional de Mar del Plata. Facultad de Ingenieria. Instituto de Investigaciones en Ciencia y Tecnologia de Materiales; Argentina
Design of a patch antenna with square ring-shaped-coupled ground for on-/off body communication

ABSTRACT Bio-telemetry is an advanced area of research that enables the transmission of biomedical parameters from human body to external monitoring device. Wearable antennas showing robust performance are attaining attention for RF bio-telemetry. A square ring-shaped ground antenna with a truncated patch is investigated for dual mode, on-body and off-body communication. The proposed antenna structure is analysed and optimised on a multi-layered flat tissue phantom. Proposed design resonates at 2.6 GHz with |S11| −22 dB and at 5.2 GHz with |S11| −35 dB on the phantom gel. Wide bandwidth of 520 MHz (2.33–2.85 GHz) and 620 MHz (4.78–5.4 GHz) efficiently covers ISM, LTE and WLAN bands and enables the antenna to withstand frequency detuning due to different body postures. Antenna shows maximum radiation efficiency of 15% at 2.45 GHz band when placed close to the tissue. Low specific absorption rate (SAR) value of 0.459/0.523/0.303 W/Kg at 2.45/2.6/5.2 GHz ensures the tissue safety.
Avaliação in vitro e in vivo de dentifrício contendo hidrocolóide como sistema de liberação controlada de flúor

Objective: To evaluable the retention of intraoral fluoride in biofilm and saliva by the use of experimental dentifrice containing hydrocolloid (tara gum) as a controlled release system of fluoride (F). Design: It was a crossover randomized triple-blind trial in which eigthteen individuals used different dentifrices during a week: 100-TGF (NaF associate to tara gum 1100 mg/mL); 50-TGF (50% NaF associate to tara gum + 50% free NaF 1100 mg/mL); CD (free NaF 1100 mg/mL); TG (with tara gum and without F); placebo (without F and tara gum). After 7th day, it was collected biofilm and saliva samples with 1 and 12 hours after the last toothbrusing. The F concentrations was determined by physico-chemical analysis of fluoride by the hexamethyldisiloxane-facilitated diffusion technique. Data were submitted to twoway ANOVA (repeated measures) and Sperman correlation coefficient (p <0.05). Results: Biofilm and salivary F levels were highter after the use of fluoride dentifrices when compared to values for placebo and TG. Not found statistical difference between F retention on biofilm at 1h and 12h after the toothbrushing for the 100-TGF, placebo and TG (p>0.05). The highest AUC values were for 50TGF, 100-TGF and CD, respectively. Conclusion: The outcomes indicates the efficacy of the dentifrice containing tara gum as a controlled release system of F in promoting F retention on the oral cavity even after 12 hours of brushing. Key-words: Dentifrice, Fluoride, Natural Product, Tara gum.
Assessment of Grid-Feeding Converter Voltage Stability

This letter applies voltage stability analysis to grid feeding converters in the presence of the converter stability versus the grid state and its operation. By applying this analysis, it is shown that the converter may become unstable if the converter reference power or current exceeds the line capacity. This letter proposes to use a conventional PV curve to determine the stability of the dynamic response of grid-feeding converters considering both power and current limits.
Optimal learning algorithm in bidirectional associative memories

The authors present an optimal learning algorithm in a discrete bidirectional associative memory (BAM). According to the cost function that measures the goodness of BAM, the authors transform the problem of specifying the connection matrix into a global optimization, solved by a gradient descent method. This learning algorithm guarantees to store all trained patterns whenever it is allowable. Experimental results are reported to demonstrate the power of the algorithm. <<ETX>>
Analysis of meiosis in Pristionchus pacificus reveals plasticity in homolog pairing and synapsis in the nematode lineage

Meiosis is conserved across eukaryotes yet varies in the details of its execution. Here we describe a new comparative model system for molecular analysis of meiosis, the nematode Pristionchus pacificus, a distant relative of the widely studied model organism Caenorhabditis elegans. P. pacificus shares many anatomical and other features that facilitate analysis of meiosis in C. elegans. However, while C. elegans has lost the meiosis-specific recombinase Dmc1 and evolved a recombination-independent mechanism to synapse its chromosomes, P. pacificus expresses both DMC-1 and RAD-51. We find that SPO-11 and DMC-1 are required for stable homolog pairing, synapsis, and crossover formation, while RAD-51 is dispensable for these key meiotic processes. RAD-51 and DMC-1 localize sequentially to chromosomes during meiotic prophase and show nonoverlapping functions. We also present a new genetic map for P. pacificus that reveals a crossover landscape very similar to that of C. elegans, despite marked divergence in the regulation of synapsis and crossing-over between these lineages.
Churn Prediction in Telecommunication Using Data Mining Technology

Since its inception, the field of Data Mining and Knowledge Discovery from Databases has been driven by the need to solve practical problems. In this paper an attempt is made to build a decision support system using data mining technology for churn prediction in Telecommunication Company. Telecommunication companies face considerable loss of revenue, because some of the customers who are at risk of leaving a company. Increasing such customers, becoming crucial problem for any telecommunication company. As the size of the organization increases such cases also increases, which makes it difficult to manage, such alarming conditions by a routine information system. Hence, needed is highly sophisticated customized and advanced decision support system. In this paper, process of designing such a decision support system through data mining technique is described. The proposed model is capable of predicting customers churn behavior well in advance.
Random graphs as model of Peer-to-Peer social networks

This thesis will present a study of using different types of random graphs to model real-world networks. Three random graph models are examined with various properties, such as growing graphs and preferential attachment. The resulting degree distribution for each model is investigated, and some numerical simulations are done on Matlab to study the average values of degrees, shortest path lengths and clustering coefficients. These results will be then compared between the models and corresponding data collected from observations done on social connections between peers in a Peer-to-Peer network. Sammanfattning Rapporten kommer att presentera en studie av olika typer av slumpgrafer som modeller for riktiga natverk. Tre olika slumpgraf modeller kommer att studeras med egenskaper som vaxande grafer och preferentiell kantsannolikhet. Den resulterande gradfordelningen undersoks hos varje modell, och nagra numeriska simuleringar utfors pa Matlab for att studera medelvarden av grader, distanser mellan noder och klustringskoefficienter. Slutligen kommer dessa resultat att jamforas mellan modeller och motsvarande data fran observationer som gjorts pa sociala kontakter mellan peers i ett Peer-to-Peer natverk.
Sonific ation Report: Status of the Field and Research Agenda

The purpose of this paper is to provide an overview of sonification research, including the current status of the field and a proposed research agenda. This paper was prepared by an interdisciplinary group of researchers gathered at the request of the National Science Foundation in the fall of 1997 in association with the International Conference on Auditory Display (ICAD).
Proposal and Analysis of Distributed Reflector‐Laser Diode Integrated with an Electroabsorption Modulator

A novel integrated laser, that is, a distributed reflector laser diode integrated with an electroabsorption modulator, is proposed to improve the output efficiency, single‐mode stability, and chirp. The proposed laser can be realized using the selective metalorganic vapor phase epitaxy technique (that is, control of the width of the insulating mask), and its fabrication process is almost the same as the conventional electroabsorption modulated laser (EML) process except for the asymmetric coupling coefficient structure along the cavity. For our analysis, an accurate time‐domain transfer‐matrix‐based laser model is developed. Based on this model, we perform steady‐state and large‐signal analyses. The performances of the proposed laser, such as the output power, extinction ratio, and chirp, are compared with those of the EML. Under 10‐Gbps NRZ modulation, we can obtain a 30% higher output power and about 50% lower chirp than the conventional EML. In particular, the simulation results show that the chirp provided by the proposed laser can appear to have a longer wavelength side at the leading edge of the pulse and a shorter wavelength side at the falling edge.
Distributed power control in cellular mobile radio systems with time-varying link gains

A simple distributed power control algorithm for communication systems with mobile users and unknown time-varying link gains is proposed. We prove that the proposed algorithm is exponentially converging. Furthermore, we show that the algorithm significantly outperforms the well-known Foschini and Miljanic algorithm in the case of quickly moving mobile users
Simple approach to nonlinear prediction

A simple procedure for improving linear prediction is presented. A zero memory nonlinear step at the output of the linear predictor may be adequate to obtain significant improvements. Two techniques are proposed for designing the nonlinearity, the object of each being to achieve the conditional mean of the nonlinear prediction given the linear one. The technique is applied to improve the signal-to-noise ratio in the automatic detection of fire by infrared signal processing.
Prevalence and co-variates of left ventricular dysfunction among patients with chronic kidney disease attending Muhimbili National Hospital.

Background: Chronic kidney disease (CKD) is at least 3–4 times more frequent in sub Saharan Africa than in developed countries, affecting mainly young adults in their productive years. The disease is a significant cause of mortality in the region, which may be a result of death from kidney failure or from congestive heart failure a frequent complication of CKD. There is however scarcity of documented literature on the magnitude of LV dysfunction among CKD patients in Tanzania. Objective: To determine the prevalence and covariates of LV dysfunction in patients with CKD attending Muhimbili National Hospital. Methodology: A descriptive cross-sectional study was conducted between March and October 2014 at the Nephrology Unit, Muhimbili National Hospital. Patients with CKD were consecutively enrolled into the study, if they fulfilled the inclusion criteria and had consented to take part in the study. A structured questionnaire was used to gather information on patient’s clinical characteristics as well as cardiovascular risk profile. Laboratory tests included a blood sample for serum creatinine, urea, and cholesterol levels. A urine dipstick was tested for proteinuria. Echocardiograms were performed to assess the LV systolic and diastolic functions. LV systolic dysfunction was defined as ejection fraction <55% and LV diastolic dysfunction as mild (impaired relaxation), moderate (pseudonormal pattern) and severe (restrictive pattern), based on transmitral pulsed-wave Doppler inflow recordings and tissue Doppler imaging of the medial mitral annulus. Data management and analysis was performed using SPSS software, version 18. A p-value of <0.05 was considered to indicate a significant statistical difference. Results: In total 197 CKD patients were enrolled but only 191 (96.9%) had complete data and were analyzed. The mean±SD age was 48±13 years, and 45.5% were females. The mean blood pressure was 154±24/92±14mmHg and 98.4% were hypertensive, with a mean duration of hypertension of 4.7years. Diabetes was present in 22.8%, smoking in 10.7% and 3.7% were obese. The mean serum creatinine levels were very high (1173±688 μmol/l) and 97.9% had end stage renal disease. The prevalence of LV
Neural network approach to locating acoustic emission sources in nondestructive evaluation

Many methods have been proposed for the nondestructive evaluation (NDE) of objects or structures. The analysis of acoustic emission (AE) signals produced during cracking in a material is a promising approach for NDE. We discuss the advantages and disadvantages of AE testing and describe some of the difficulties in applying classical signal processing (deconvolution) techniques to AE analysis of a complex system. In particular, determining the location of the source of an AE is a highly nonlinear inversion problem for which classical deconvolution approaches are inapplicable. We present a neural network (NN) approach that has the potential to overcome many of the difficulties in nonlinear inversion. The approach is demonstrated on a steel I-beam. Although work remains in taking the concept to a large-scale practical implementation, the approach seems in principle to address some of the most vexing aspects of this challenging problem.
Effective permittivity of a random mixture with spherical inclusions

The paper reports the results of a numerical analysis of electric field in random dielectric materials. The effective permittivity of a three-dimensional mixture is calculated by the finite difference method. The studied mixture is a two-component mixture with a homogeneous background in which spheres of another material are embedded in random positions. A new technique to derive difference equations in the neighborhood of material interfaces is considered. Hundreds of mixture samples with different random inclusion distributions are analysed to get a good insight into average characteristics of the mixture material. The calculated permittivity distributions are also compared with well-known theoretical models such as Maxwell Garnett and Bruggeman models.
Low-volatility compounds contribute significantly to isoprene secondary organic aerosol (SOA) under high-NOx conditions

Abstract. Recent advances in our knowledge of the gas-phase oxidation of isoprene, the impact of chamber walls on secondary organic aerosol (SOA) mass yields, and aerosol measurement analysis techniques warrant reevaluating SOA yields from isoprene. In particular, SOA from isoprene oxidation under high-NOx conditions forms via two major pathways: (1) low-volatility nitrates and dinitrates (LV pathway) and (2) hydroxymethyl-methyl-α-lactone (HMML) reaction on a surface or the condensed phase of particles to form 2-methyl glyceric acid and its oligomers (2MGA pathway). These SOA production pathways respond differently to reaction conditions. Past chamber experiments generated SOA with varying contributions from these two unique pathways, leading to results that are difficult to interpret. This study examines the SOA yields from these two pathways independently, which improves the interpretation of previous results and provides further understanding of the relevance of chamber SOA yields to the atmosphere and regional or global modeling. Results suggest that low-volatility nitrates and dinitrates produce significantly more aerosol than previously thought; the experimentally measured SOA mass yield from the LV pathway is ∼0.15. Sufficient seed surface area at the start of the reaction is needed to limit the effects of vapor wall losses of low-volatility compounds and accurately measure the complete SOA mass yield. Under dry conditions, substantial amounts of SOA are formed from HMML ring-opening reactions with inorganic ions and HMML organic oligomerization processes. However, the lactone organic oligomerization reactions are suppressed under more atmospherically relevant humidity levels, where hydration of the lactone is more competitive. This limits the SOA formation potential from the 2MGA pathway to HMML ring-opening reactions with water or inorganic ions under typical atmospheric conditions. The isoprene SOA mass yield from the LV pathway measured in this work is significantly higher than previous studies have reported, suggesting that low-volatility compounds such as organic nitrates and dinitrates may contribute to isoprene SOA under high-NOx conditions significantly more than previously thought and thus deserve continued study.
Real time implementation of MPEG-4 video decoder on ARM7TDMI

MPEG-4 simple profile is being used as the video compression standard in mobile video communications. Video compression requires a significant amount of processing power. Currently, ARM cores are widely used in mobile applications because of their low power consumption. As the processing power available is limited, optimization of the applications is inevitable. This paper describes in detail the implementation of MPEG-4 simple profile video decoder on ARM7TDMI.
Research report on Bangla optical character recognition using Kohonen network

This report discusses the theory and implementation of an Optical Character Recognition (OCR) for Bangla. The principal idea is to convert images of text documents such as those obtained from scanning a document into editable texts. This report does not address the pre-processing steps such as skew correction and noise reduction (which is handled in a previous report), so the documents are assumed to pre-processed by another tool in the pipeline. For training and recognition, the input is then first converted to a binary image, and then into to a 25x25 pixel2 image; the only feature extracted from the images is a 625-bit long vector, which is then trained or classified using a Kohonen neural network. The OCR shows excellent performance for documents with single typeface. The work in progress is extending it to handle multiple typefaces.
Context dependency effect in the formation of image concepts and its application

For the human brain, context dependency was studied in successive presentation of image stimuli to examine the influence of formerly presented stimuli. It is shown that concept formation is influenced by the context of successively presented stimuli. These conclusions were reached after three psychological experiments. Based on the results, a new retrieval mechanism for an image database is proposed, and the merit of supporting the retriever's decision making is discussed. <<ETX>>
A Network Simulation Tool for User Traffic Modeling and Quality of Experience Analysis in a Hybrid Access Architecture

A Hybrid Access Architecture, where network users can be simultaneously served by different technologies, has been envisioned in order to increase the achievable data rates and enhance the user experience. This proposed access is promising to users where the costs of replacing existing technology are unmanageable and the complementary technology is underused. In order to understand the implications of a Hybrid Access between Digital Subscriber Line (DSL) and Long Term Evolution (LTE) in Downlink (DL) operation, a Network Simulation Tool has been developed, where the services demanded by the users are defined and modeled. Additionally, the Traffic and QoE Simulator (TQoES) establishes an algorithm to select the kind of access to be used by specific services, and reliably simulates the behavior of users within an LTE network based on 3GPP recommendations.
Fast tissue segmentation based on a 3D and 4D feature map: comparison study

The aim of this work was to develop a fast and accurate method for tissue segmentation in MRI based on 4D feature map and compare it with that derived from the 3D feature map. High resolution MR imaging was performed in 5 normals, 6 patients with brain MS, and 6 with malignant brain tumors. Three inputs: proton density, or weighted fast spin-echo, T1-weighted spin echo MR images were routinely utilized. As a fourth input, either magnetization transfer MRI was used in normals and some patients or Tl weighted post contract MRI in other patients. Modified k-Nearest Neighbor segmentation algorithm was optimized for maximum computation speed and high quality segmentation. In that regard: 1) the authors discarded the redundant seed points, 2) discarded the points within 0.5 standard deviation from the cluster center that were non overlapping with other tissue classes, 3) they removed outlying seed points outside 5 times the standard deviation from the cluster center of each tissue class. Their new technique utilizing all 4 MRI inputs provided better segmentation than that based on three inputs. (p<0.001) The tissues were smoother and the delineation of the tissues was increased. Details that were previously blurred or invisible now became apparent. In normals, detailed depiction of deep gray matter nuclei was obtained. In malignant tumors, up to 5 abnormal tissues were identified: 1) solid tumor core, 2) cyst, 3) edema in white matter 4) edema in gray matter and 5) necrosis. Delineation of MS plaque in different stages of demyelination, became much sharper. In conclusion, proposed methodology warrants further development and clinical evaluation.