Search results for: cardiac output

Authors: Lopamudra D. Satpathy, Bani Chatterjee, Jitendra Mahakud

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The rapid economic growth in terms of output and investment necessitates a substantial growth of Total Factor Productivity (TFP) of firms which is an indicator of an economy’s technological change. The strong empirical relationship between financial sector development and economic growth clearly indicates that firms financing decisions do affect their levels of output via their investment decisions. Hence it establishes a linkage between the financial factors and productivity growth of the firms. To achieve the smooth and continuous economic growth over time, it is imperative to understand the financial channel that serves as one of the vital channels. The theoretical or logical argument behind this linkage is that when the internal financial capital is not sufficient enough for the investment, the firms always rely upon the external sources of finance. But due to the frictions and existence of information asymmetric behavior, it is always costlier for the firms to raise the external capital from the market, which in turn affect their investment sentiment and productivity. This kind of financial position of the firms puts heavy pressure on their productive activities. Keeping in view this theoretical background, the present study has tried to analyze the role of both external and internal financial factors (leverage, cash flow and liquidity) on the determination of total factor productivity of the firms of manufacturing industry and its sub-industries, maintaining a set of firm specific variables as control variables (size, age and disembodied technological intensity). An estimate of total factor productivity of the Indian manufacturing industry and sub-industries is computed using a semi-parametric approach, i.e., Levinsohn- Petrin method. It establishes the relationship between financial factors and productivity growth of 652 firms using a dynamic panel GMM method covering the time period between 1997-98 and 2012-13. From the econometric analyses, it has been found that the internal cash flow has a positive and significant impact on the productivity of overall manufacturing sector. The other financial factors like leverage and liquidity also play the significant role in the determination of total factor productivity of the Indian manufacturing sector. The significant role of internal cash flow on determination of firm-level productivity suggests that access to external finance is not available to Indian companies easily. Further, the negative impact of leverage on productivity could be due to the less developed bond market in India. These findings have certain implications for the policy makers to take various policy reforms to develop the external bond market and easily workout through which the financially constrained companies will be able to raise the financial capital in a cost-effective manner and would be able to influence their investments in the highly productive activities, which would help for the acceleration of economic growth.

Keywords: dynamic panel, financial factors, manufacturing sector, total factor productivity

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Authors: Dawit Burusie Abdi, Mamidala Jagadesh Kumar

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In this paper, using 2D TCAD simulations, the application of a dual material gate (DMG) for suppressing ambipolar conduction in a tunnel field effect transistor (TFET) is demonstrated. Using the proposed DMG concept, the ambipolar conduction can be effectively suppressed even if the drain doping is as high as that of the source doping. Achieving this symmetrical doping, without the ambipolar conduction in TFETs, gives the advantage of realizing both n-type and p-type devices with the same doping sequences. Furthermore, the output characteristics of the DMG TFET exhibit a good saturation when compared to that of the gate-drain underlap approach. This improved behavior of the DMG TFET makes it a good candidate for inverter based logic circuits.

Keywords: dual material gate, suppressing ambipolar current, symmetrically doped TFET, tunnel FETs, PNPN TFET

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Authors: Noha Al Majid, Said Mazer, Moulhime El Bekkali, Catherine Algani, Mahmoud Mehdi

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A low noise figure (NF) and high linearity V-band Low Noise Amplifier (LNA) is reported in this article. The LNA compromises a three-stage cascode configuration. This LNA will be used as a part of a WPAN (Wireless Personal Area Network) receiver in the millimeter-wave band at 60 GHz. It is designed according to the MMIC technology (Monolithic Microwave Integrated Circuit) in PH 15 process from UMS foundry and uses a 0.15 μm GaAs PHEMT (Pseudomorphic High Electron Mobility Transistor). The particularity of this LNA compared to other LNAs in literature is its very low noise figure which is equal to 1 dB and its high linearity (IIP3 is about 22 dB). The LNA consumes 0.24 Watts, achieving a high gain which is about 23 dB, an input return loss better than -10 dB and an output return loss better than -8 dB.

Keywords: low noise amplifier, V-band, MMIC technology, LNA, amplifier, cascode, pseudomorphic high electron mobility transistor (PHEMT), high linearity

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Authors: Chang-Hsing Lee, Cheng-Chang Lien, Chin-Chuan Han

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In this paper, an edge-strength guided multiscale retinex (EGMSR) approach will be proposed for color image contrast enhancement. In EGMSR, the pixel-dependent weight associated with each pixel in the single scale retinex output image is computed according to the edge strength around this pixel in order to prevent from over-enhancing the noises contained in the smooth dark/bright regions. Further, by fusing together the enhanced results of EGMSR and adaptive multiscale retinex (AMSR), we can get a natural fused image having high contrast and proper tonal rendition. Experimental results on several low-contrast images have shown that our proposed approach can produce natural and appealing enhanced images.

Keywords: image enhancement, multiscale retinex, image fusion, EGMSR

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Authors: Dinoo Kirthinanda, Sujani Wijeratne

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Pseudohyperkalaemia is a common benign in vitro phenomenon caused by the release of potassium ions (K+) from cells during specimen processing. Analysis of haemolysed blood samples for predominantly intracellular electrolytes may lead to re-investigation and potentially harmful interventions. We report a case of a 52-year male with myeloproliferative disease manifested as Polycythaemia Rubra Vera, Hypertension and hypertensive nephropathy with stage 3 chronic kidney disease admitted to Neuro-intensive care unit (NICU) with an intra-cerebral haemorrhage secondary to hypertensive bleed. His initial blood investigations showed hyperkalemia with serum K+ 6.2 mmol/L yet the bedside arterial blood gas analysis yielded K+ of 4.6 mmol/L. The patient was however given hyperkalemia regime twice based on venous electrolyte analysis. The discrepancy between the bedside electrolyte analysis using arterial blood and venous blood prompted further evaluation. The 12 lead Electrocardiogram showed U waves and sinus bradycardia corresponding to the serum K+ of 2.8 mmol/L on arterial blood gas analysis. Immediate K+ replacement ensured the patient did not develop life-threatening cardiac complications. Pseudohyperkalaemia may pose diagnostic challenges in the absence of detectable haemolysis and should be suspected in susceptible patients with normal Electrocardiogram and Glomerular Filtration Rate to avoid potentially life-threatening interventions. When in doubt, rapid analysis of arterial blood gas may be useful for accurate quantification of potassium.

Keywords: patient safety, pseudohyperkalaemia, haemolysis, myeloproliferative disorder

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Authors: S. Ghorbani, N. I. Polushin

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Vibration during machining process is crucial since it affects cutting tool, machine, and workpiece leading to a tool wear, tool breakage, and an unacceptable surface roughness. This paper applies a nonparametric statistical method, single decision tree (SDT), to identify factors affecting on vibration in machining process. Workpiece material (AISI 1045 Steel, AA2024 Aluminum alloy, A48-class30 Gray Cast Iron), cutting tool (conventional, cutting tool with holes in toolholder, cutting tool filled up with epoxy-granite), tool overhang (41-65 mm), spindle speed (630-1000 rpm), feed rate (0.05-0.075 mm/rev) and depth of cut (0.05-0.15 mm) were used as input variables, while vibration was the output parameter. It is concluded that workpiece material is the most important parameters for natural frequency followed by cutting tool and overhang.

Keywords: cutting condition, vibration, natural frequency, decision tree, CART algorithm

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Authors: A. M. Al-Sabagh, M. A. Deyab, M. N. Kroush

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The present study focused on critical and detailed approach for using aluminum electrode as impressed current anode for cathodic protection of X65 steel tank containing fresh water. The impressed current design calculation showed 0.6 A of current demand and voltage of 0.33 V required to adequately protect the X65 steel tank with internal surface area of 421 m². We used here one transformer rectifier with current and voltage output of 25 A and 25 V, respectively. The data showed that the potentials ranged from -0.474 to -0.509 V (vs. Cu/CuSO₄), prior to the application of cathodic protection. When the potential was measured 1 h after the application of cathodic protection, the potential values showed considerable shift within protection range (-0.950 V vs. Cu/CuSO₄). The results confirmed that aluminum anode can be used in freshwater applications with high efficiency (current capacity) and low consumption rate.

Keywords: cathodic protection, aluminum, steel, fresh water

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Authors: Bahar Tunctan, Sefika Pinar Kucukkavruk, Meryem Temiz-Resitoglu, Demet Sinem Guden, Ayse Nihal Sari, Seyhan Sahan-Firat, Mahesh P. Paudyal, John R. Falck, Kafait U. Malik

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We hypothesized that 20-hydroxyeicosatetraenoic acid (20-HETE) mimetics such as N-(20-hydroxyeicosa-5[Z],14[Z]-dienoyl)glycine (5,14-HEDGE) may be beneficial for preventing mortality due to inflammation induced by lipopolysaccharide (LPS). This study aims to assess the effect of 5,14-HEDGE on the LPS-induced changes in nucleotide binding domain and leucine-rich repeat protein 3 (NLRP3)/apoptosis-associated speck-like protein containing a caspase activation and recruitment domain (ASC)/pro-caspase-1 inflammasome. Rats were injected with saline (4 ml/kg) or LPS (10 mg/kg) at time 0. Blood pressure and heart rate were measured using a tail-cuff device. 5,14-HEDGE (30 mg/kg) was administered to rats 1 h after injection of saline or LPS. The rats were sacrificed 4 h after saline or LPS injection and kidney, heart, thoracic aorta, and superior mesenteric artery were isolated for measurement of caspase-1/11 p20, NLRP3, ASC, and β-actin proteins as well as interleukin-1β (IL-1β) levels. Blood pressure decreased by 33 mmHg and heart rate increased by 63 bpm in the LPS-treated rats. In the LPS-treated rats, tissue protein expression of caspase-1/11 p20, NLRP3, and ASC in addition to IL-1β levels were increased. 5,14-HEDGE prevented the LPS-induced changes. Our findings suggest that inhibition of renal, cardiac, and vascular formation/activity of NLRP3/ASC/pro-caspase-1 inflammasome involved in the protective effect of 5,14-HEDGE on LPS-induced septic shock in rats. This work was financially supported by the Mersin University (2015-AP3-1343) and USPHS NIH (PO1 HL034300).

Keywords: 5, 14-HEDGE, lipopolysaccharide, NLRP3, inflammasome, septic shock

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Authors: Abraham J. Rizkalla, Tristan D. Yan

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Purpose: Durable mitral valve repair is preferred to a replacement, avoiding the need for anticoagulation or re-intervention, with a reduced risk of endocarditis. Robotic mitral repair has been gaining favour globally as a safe, effective, and reproducible method of minimally invasive valve repair. In this work, we showcase the use of the Davinci© Xi robotic platform to perform several advanced techniques, working synergistically to achieve successful mitral repair in advanced mitral disease. Techniques: We present the case of a Barlow type mitral valve disease with a tall and redundant posterior leaflet resulting in severe mitral regurgitation and systolic anterior motion. Firstly, quadrangular resection of P2 is performed to remove the excess and redundant leaflet. Secondly, a sliding leaflet plasty of P1 and P3 is used to reconstruct the posterior leaflet. To anchor the newly formed posterior leaflet to the papillary muscle, CV-4 Goretex neochordae are fashioned using the innovative string, ruler, and bulldog technique. Finally, mitral valve annuloplasty and closure of a patent foramen ovale complete the repair. Results: There was no significant residual mitral regurgitation and complete resolution of the systolic anterior motion of the mitral valve on post operative transoesophageal echocardiography. Conclusion: This work highlights the robotic approach to complex repair techniques for advanced mitral valve disease. Familiarity with resection and sliding plasty, neochord implantation, and annuloplasty allows the modern cardiac surgeon to achieve a minimally-invasive and durable mitral valve repair when faced with complex mitral valve pathology.

Keywords: robotic mitral valve repair, Barlow's valve, sliding plasty, neochord, annuloplasty, quadrangular resection

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Authors: Zineb Jibraili, Said Ouhadi, Jorge Arana

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Introduction: Organizational performance is recognized by some theorists as one-dimensional concept, and by others as multidimensional. This concept, which is already difficult to apply in traditional companies, is even harder to identify, to measure and to manage when voluntary organizations are concerned, essentially because of the complexity of that form of organizations such as sport clubs who are characterized by the multiple goals and multiple constituencies. Indeed, the new culture of professionalization and modernization around organizational performance emerges new pressures from the state, sponsors, members and other stakeholders which have required these sport organizations to become more performance oriented, or to build their capacity in order to better manage their organizational performance. The evaluation of performance can be made by evaluating the input (e.g. available resources), throughput (e.g. processing of the input) and output (e.g. goals achieved) of the organization. In non-profit organizations (NPOs), questions of performance have become increasingly important in the world of practice. To our knowledge, most of studies used the same methods to evaluate the performance in NPSOs, but no recent study has proposed a club-specific model. Based on a review of the studies that specifically addressed the organizational performance (and effectiveness) of NPSOs at operational level, the present paper aims to provide a multidimensional framework in order to understand, analyse and measure organizational performance of sport clubs. This paper combines all dimensions founded in literature and chooses the most suited of them to our model that we will develop in Moroccan sport clubs case. Method: We propose to implicate our unified model of evaluating organizational performance that takes into account all the limitations found in the literature. On a sample of Moroccan sport clubs ‘Football, Basketball, Handball and Volleyball’, for this purpose we use a qualitative study. The sample of our study comprises data from sport clubs (football, basketball, handball, volleyball) participating on the first division of the professional football league over the period from 2011 to 2016. Each football club had to meet some specific criteria in order to be included in the sample: 1. Each club must have full financial data published in their annual financial statements, audited by an independent chartered accountant. 2. Each club must have sufficient data. Regarding their sport and financial performance. 3. Each club must have participated at least once in the 1st division of the professional football league. Result: The study showed that the dimensions that constitute the model exist in the field with some small modifications. The correlations between the different dimensions are positive. Discussion: The aim of this study is to test the unified model emerged from earlier and narrower approaches for Moroccan case. Using the input-throughput-output model for the sketch of efficiency, it was possible to identify and define five dimensions of organizational effectiveness applied to this field of study.

Keywords: organisational performance, model multidimensional, evaluation organizational performance, sport clubs

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Authors: Roman Snytsar

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Pseudo-random numbers are often used in scientific computing such as the Monte Carlo Simulations or the Quantum Inspired Optimization. Requirements for a parallel random number generator running in the modern multi-core vector environment are more stringent than those for sequential random number generators. As well as passing the usual quality tests, the output of the parallel random number generator must be verifiable and reproducible throughout the concurrent execution. We propose a family of vectorized Permuted Congruential Generators. Implementations are available for multiple modern vector modern computer architectures. Besides demonstrating good single core performance, the generators scale easily across many processor cores and multiple distributed nodes. We provide performance and parallel speedup analysis and comparisons between the implementations.

Keywords: pseudo-random numbers, quantum optimization, SIMD, parallel computing

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Authors: G. Rajapakse, S. Jayasinghe, A. Fleming

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This paper aims to experimentally validate the control strategy used for electrical power converters in grid integrated oscillating water column (OWC) wave energy converter (WEC). The particular OWC’s unidirectional air turbine-generator output power results in discrete large power pulses. Therefore, the system requires power conditioning prior to integrating to the grid. This is achieved by using a back to back power converter with an energy storage system. A Li-Ion battery energy storage is connected to the dc-link of the back-to-back converter using a bidirectional dc-dc converter. This arrangement decouples the system dynamics and mitigates the mismatch between supply and demand powers. All three electrical power converters used in the arrangement are controlled using finite control set-model predictive control (FCS-MPC) strategy. The rectifier controller is to regulate the speed of the turbine at a set rotational speed to uphold the air turbine at a desirable speed range under varying wave conditions. The inverter controller is to maintain the output power to the grid adhering to grid codes. The dc-dc bidirectional converter controller is to set the dc-link voltage at its reference value. The software modeling of the OWC system and FCS-MPC is carried out in the MATLAB/Simulink software using actual data and parameters obtained from a prototype unidirectional air-turbine OWC developed at Australian Maritime College (AMC). The hardware development and experimental validations are being carried out at AMC Electronic laboratory. The designed FCS-MPC for the power converters are separately coded in Code Composer Studio V8 and downloaded into separate Texas Instrument’s TIVA C Series EK-TM4C123GXL Launchpad Evaluation Boards with TM4C123GH6PMI microcontrollers (real-time control processors). Each microcontroller is used to drive 2kW 3-phase STEVAL-IHM028V2 evaluation board with an intelligent power module (STGIPS20C60). The power module consists of a 3-phase inverter bridge with 600V insulated gate bipolar transistors. Delta standard (ASDA-B2 series) servo drive/motor coupled to a 2kW permanent magnet synchronous generator is served as the turbine-generator. This lab-scale setup is used to obtain experimental results. The validation of the FCS-MPC is done by comparing these experimental results to the results obtained by MATLAB/Simulink software results in similar scenarios. The results show that under the proposed control scheme, the regulated variables follow their references accurately. This research confirms that FCS-MPC fits well into the power converter control of the OWC-WEC system with a Li-Ion battery energy storage.

Keywords: dc-dc bidirectional converter, finite control set-model predictive control, Li-ion battery energy storage, oscillating water column, wave energy converter

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Authors: Ashiq Rahman, Sunil Thapa, Shunyao Fan, Niloy K. Dutta

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A 20-GHz and a 50-GHz pulse train are generated using a fiber ring laser setup that incorporates Rational Harmonic Mode Locking. Two separate experiments were carried out using charcoal nanoparticles and graphene nanoparticles acting as saturable absorbers to reduce the pulse width generated from rational harmonic mode-locking (RHML). Autocorrelator trace shows that the pulse width is reduced from 5.6-ps to 3.2-ps using charcoal at 20-GHz, and to 2.7-ps using graphene at 50-GHz repetition rates, which agrees with the simulation findings. Numerical simulations have been carried out to study the effect of varying the linear and nonlinear absorbance parameters of both absorbers on output pulse widths. Experiments closely agree with the simulations.

Keywords: fiber optics, fiber lasers, mode locking, saturable absorbers

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Authors: N. Hiranmai, M. L. S. Deva Kumar

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In this project, it is planned to carry out an experimental investigation on 4- stroke Direct Injection Diesel Engine, which is a single-cylinder, four-stroke, water-cooled, and constant speed engine capable of developing a power output of 3.7 kW at 1500 rpm, run with diesel fuel and also with different proportions of Safflower oil methyl esters, with a piston having five number of grooves on its crown to create turbulence. Various performance parameters, such as brake power, specific fuel consumption, and thermal efficiency, are calculated. At all the load conditions, the performance of the engine is obtained better for blend B40 (40% Safflower oil + 60% of Diesel). At different load conditions, Brake thermal Efficiency (ηbth) is comparatively more for all blends than that for Diesel. At different load conditions, ηith is less for blend B40.

Keywords: four-stroke engine, diesel, safflower oil, engine performance, emissions.

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Authors: Diego Aguirre, Olac Fuentes

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In this paper, we present a taxonomy of weight initialization schemes used in deep learning. We survey the most representative techniques in each class and compare them in terms of overhead cost, convergence rate, and applicability. We also introduce a new weight initialization scheme. In this technique, we perform an initial feedforward pass through the network using an initialization mini-batch. Using statistics obtained from this pass, we initialize the weights of the network, so the following properties are met: 1) weight matrices are orthogonal; 2) ReLU layers produce a predetermined number of non-zero activations; 3) the output produced by each internal layer has a unit variance; 4) weights in the last layer are chosen to minimize the error in the initial mini-batch. We evaluate our method on three popular architectures, and a faster converge rates are achieved on the MNIST, CIFAR-10/100, and ImageNet datasets when compared to state-of-the-art initialization techniques.

Keywords: deep learning, image classification, supervised learning, weight initialization

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Authors: Noura Al-Ajmi, Mohammed A. Almulla

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With the increased utilization of technology devices around the world, healthcare and medical diagnosis are critical issues that people worry about these days. Doctors are doing their best to avoid any medical errors while diagnosing diseases and prescribing the wrong medication. Subsequently, artificial intelligence applications that can be installed on mobile devices such as rule-based expert systems facilitate the task of assisting doctors in several ways. Due to their many advantages, the usage of expert systems has increased recently in health sciences. This work presents a backward rule-based expert system that can be used for a headache diagnosis and medication recommendation system. The structure of the system consists of three main modules, namely the input unit, the processing unit, and the output unit.

Keywords: headache diagnosis system, prescription recommender system, expert system, backward rule-based system

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Authors: Ni Luh Putu Harta Wedari

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Background: Clostridium difficile has two main virulence factors, namely TcdA and TcdB. TcdA encoded by the tcdA gene acts as an enterotoxin, pro-inflammatory and fluid accumulation, while TcdB encoded by the tcdB gene is cytotoxic, causes disruption of the actin cytoskeleton, and causes disruption of tight junctions in colon cells. This study aims to explore the relationship between the tcdA and tcdB genes and the duration of diarrhea in elderly patients. Method: This research was an observational analytic with a prospective cross-sectional with samples of elderly diarrhea patients who met the inclusion criteria in Denpasar City health service facilities from 1 December 2022 until 30 June 2023, and then their feces were analyzed using the real-time PCR method. Results: In this study, 40 elderly diarrhea patients met the inclusion criteria and in accordance with the minimum sample size, 28 (70%) men and 12 (30%) women. 5 patients (12.5%) had a history of azithromycin, 4 (10%) levofloxacin, 17 (42.5%) ciprofloxacin, 8 (20%) metronidazole, 1 (2.5%) cefoperazone, 5 (12, 5%) doxycycline. Comorbids, namely 13 (32.5%) type II diabetes mellitus, 4 (10%) chronic kidney disease, 10 (25%) malignancies, 7 (17.5%) urinary tract infections, 3 (7.5%) %) immunocompromised, 2 (5%) cardiac heart failure, and 1 (2.5%) acute on chronic kidney disease. The overall diarrhea duration average was 5 days. 8 samples (20%) were positive for 16s rRNA, and there was no significant difference in diarrhea duration with negative samples (p=0.166). The relationship between the tcdA gene and the duration of diarrhea could not be performed because all samples were negative. Likewise, relationship analysis between the coexistence of tcdA and tcdB could not be performed. There was no significant difference between tcdB positive 3 (7.5%) and negative with diarrhea duration (p=0.739). Conclusion: There is no significant relationship between the presence of the 16s rRNA and tcdB C. difficile genes with the duration of diarrhea in elderly patients.

Keywords: clostridium, difficile, diarrhea, elderly, tcdA, tcdB

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Authors: Misbahuddin Mahammad, P. Chandra Sekhar, Metuku Shyamsunder

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The oversampled output of a sigma-delta modulator is decimated to Nyquist sampling rate by decimation filters. The decimation filters work twofold; they decimate the sampling rate by a factor of OSR (oversampling rate) and they remove the out band quantization noise resulting in an increase in resolution. The speed, area and power consumption of oversampled converter are governed largely by decimation filters in sigma-delta A/D converters. The scope of the work is to design a decimation filter for sigma-delta ADC and simulation using MATLAB. The decimation filter structure is based on cascaded-integrated comb (CIC) filter. A second decimation filter is using CIC for large rate change and cascaded FIR filters, for small rate changes, to improve the frequency response. The proposed structure is even more hardware efficient.

Keywords: sigma delta modulator, CIC filter, decimation filter, compensation filter, noise shaping

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Authors: Austin Jiang, Richard M. Salmon, Nicholas W. Morrell, Wei Li

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BMP10 is highly expressed in the developing heart and plays essential roles in cardiogenesis. BMP10 deletion in mice results in embryonic lethality due to impaired cardiac development. In adults, BMP10 expression is restricted to the right atrium, though ventricular hypertrophy is accompanied by increased BMP10 expression in a rat hypertension model. However, reports of BMP10 activity in the circulation are inconclusive. In particular it is not known whether in vivo secreted BMP10 is active or whether additional factors are required to achieve its bioactivity. It has been shown that high-affinity binding of the BMP10 prodomain to the mature ligand inhibits BMP10 signaling activity in C2C12 cells, and it was proposed that prodomain-bound BMP10 (pBMP10) complex is latent. In this study, we demonstrated that the BMP10 prodomain did not inhibit BMP10 signaling activity in multiple endothelial cells, and that recombinant human pBMP10 complex, expressed in mammalian cells and purified under native conditions, was fully active. In addition, both BMP10 in human plasma and BMP10 secreted from the mouse right atrium were fully active. Finally, we confirmed that active BMP10 secreted from mouse right atrium was in the prodomain-bound form. Our data suggest that circulating BMP10 in adults is fully active and that the reported vascular quiescence function of BMP10 in vivo is due to the direct activity of pBMP10 and does not require an additional activation step. Moreover, being an active ligand, recombinant pBMP10 may have therapeutic potential as an endothelial-selective BMP ligand, in conditions characterized by loss of BMP9/10 signaling.

Keywords: bone morphogenetic protein 10 (BMP10), endothelial cell, signal transduction, transforming growth factor beta (TGF-B)

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Authors: S. Jimenez, R.Duarte, J.Sanchez-Choliz, I. Villanua

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There is a certain consensus in economic literature about the factors that have influenced in historical differences in growth rates observed between developed and developing countries. However, it is less clear what elements have marked different paths of growth in developed economies in recent decades. R&D has always been seen as one of the major sources of technological progress, and productivity growth, which is directly influenced by technological developments. Following recent literature, we can say that ‘innovation pushes the technological frontier forward’ as well as encourage future innovation through the creation of externalities. In other words, productivity benefits from innovation are not fully appropriated by innovators, but it also spread through the rest of the economies encouraging absorptive capacities, what have become especially important in a context of increasing fragmentation of production This paper aims to contribute to this literature in two ways, first, exploring alternative indexes of R&D flows embodied in inter-country, inter-sectorial flows of good and services (as approximation to technology spillovers) capturing structural and technological characteristic of countries and, second, analyzing the impact of direct and embodied R&D on the evolution of labor productivity at the country/sector level in recent decades. The traditional way of calculation through a multiregional input-output framework assumes that all countries have the same capabilities to absorb technology, but it is not, each one has different structural features and, this implies, different capabilities as part of literature, claim. In order to capture these differences, we propose to use a weight based on specialization structure indexes; one related with the specialization of countries in high-tech sectors and the other one based on a dispersion index. We propose these two measures because, as far as we understood, country capabilities can be captured through different ways; countries specialization in knowledge-intensive sectors, such as Chemicals or Electrical Equipment, or an intermediate technology effort across different sectors. Results suggest the increasing importance of country capabilities while increasing the trade openness. Besides, if we focus in the country rankings, we can observe that with high-tech weighted R&D embodied countries as China, Taiwan and Germany arose the top five despite not having the highest intensities of R&D expenditure, showing the importance of country capabilities. Additionally, through a fixed effects panel data model we show that, in fact, R&D embodied is important to explain labor productivity increases, in fact, even more that direct R&D investments. This is reflecting that globalization is more important than has been said until now. However, it is true that almost all analysis done in relation with that consider the effect of t-1 direct R&D intensity over economic growth. Nevertheless, from our point of view R&D evolve as a delayed flow and it is necessary some time to be able to see its effects on the economy, as some authors have already claimed. Our estimations tend to corroborate this hypothesis obtaining a gap between 4-5 years.

Keywords: economic growth, embodied, input-output, technology

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Authors: Young-San Shin, Seongsoo Lee

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Hall sensor is widely used to measure rotation angle. When the Hall voltage is measured for linear displacement, it is converted to angular displacement using arctangent function, which requires a large lookup table. In this paper, a lookup table reduction technique is presented for angle measurement. When the input of the lookup table is small within a certain threshold, the change of the outputs with respect to the change of the inputs is relatively small. Thus, several inputs can share same output, which significantly reduce the lookup table size. Its error analysis was also performed, and the threshold was determined so as to maintain the error less than 1°. When the Hall voltage has 11-bit resolution, the lookup table size is reduced from 1,024 samples to 279 samples.

Keywords: hall sensor, angle measurement, lookup table, arctangent

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Authors: Jana Ismail, Layla Fallatah, Maha Alshmaisi

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ChatGPT, a cutting-edge language model built on the GPT-3.5 architecture, has garnered attention for its profound natural language processing capabilities, holding promise for transformative applications in customer service and content creation. This study delves into ChatGPT's architecture, aiming to comprehensively understand its strengths and potential limitations. Through systematic experiments across diverse domains, such as general knowledge and creative writing, we evaluated the model's coherence, context retention, and task-specific accuracy. While ChatGPT excels in generating human-like responses and demonstrates adaptability, occasional inaccuracies and sensitivity to input phrasing were observed. The study emphasizes the impact of prompt design on output quality, providing valuable insights for the nuanced deployment of ChatGPT in conversational AI and contributing to the ongoing discourse on the evolving landscape of natural language processing in artificial intelligence.

Keywords: artificial Inelegance, chatGPT, open AI, NLP

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Authors: Osama Mohamed Elrajubi, Idris El-Feghi, Mohamed Abu Baker Saghayer

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This paper describes an identification of specific shapes within binary images using the morphological Hit-or-Miss Transform (HMT). Hit-or-Miss transform is a general binary morphological operation that can be used in searching of particular patterns of foreground and background pixels in an image. It is actually a basic operation of binary morphology since almost all other binary morphological operators are derived from it. The input of this method is a binary image and a structuring element (a template which will be searched in a binary image) while the output is another binary image. In this paper a modification of Hit-or-Miss transform has been proposed. The accuracy of algorithm is adjusted according to the similarity of the template and the sought template. The implementation of this method has been done by C language. The algorithm has been tested on several images and the results have shown that this new method can be used for similar shape detection.

Keywords: hit-or-miss operator transform, HMT, binary morphological operation, shape detection, binary images processing

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Authors: Muhammad Farooq, Ahtasham Gul

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To meet the desired standard, it is important to monitor and analyze different engineering processes to get desired output. The bivariate distributions got a lot of attention in recent years to describe the randomness of natural as well as artificial mechanisms. In this article, a bivariate model is constructed using two independent models developed by the nesting approach to study the effect of each component on reliability for better understanding. Further, the Bayes analysis of system availability is studied by considering prior parametric variations in the failure time and repair time distributions. Basic statistical characteristics of marginal distribution, like mean median and quantile function, are discussed. We use inverse Gamma prior to study its frequentist properties by conducting Monte Carlo Markov Chain (MCMC) sampling scheme.

Keywords: reliability, system availability Weibull, inverse Lomax, Monte Carlo Markov Chain, Bayesian

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Authors: Hassan Masoumi, Ahad Salimi, Nazanin Barhemmat, Babak Gholami

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Artificial neural networks have gained a lot of interest as empirical models for their powerful representational capacity, multi input and output mapping characteristics. In fact, most feed-forward networks with nonlinear nodal functions have been proved to be universal approximates. In this paper, we propose a new supervised method for color image classification based on self organizing feature maps (SOFM). This algorithm is based on competitive learning. The method partitions the input space using self-organizing feature maps to introduce the concept of local neighborhoods. Our image classification system entered into RGB image. Experiments with simulated data showed that separability of classes increased when increasing training time. In additional, the result shows proposed algorithms are effective for color image classification.

Keywords: classification, SOFM algorithm, neural network, neighborhood, RGB image

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Authors: E. M. S. Azzam, S. A. Ahmed, H. H. Mohamed, M. A. Adly, E. A. M. Gad

Abstract:

In this work we prepared 3-(p-methyl) phenyl-5-thionyl-1,2,4-triazoline (C1). The nanostructure of the prepared C1 compound was fabricated by assembling on silver nanoparticles. The UV and TEM analyses confirm the assembling of C1 compound on silver nanoparticles. The effect of C1 compound on the removal of Iron (II) from Iron contaminated samples and industrial wastewater samples (produced water from oil processing facility) were studied before and after their assembling on silver nanoparticles. The removal of Iron was studied at different concentrations of FeSO4 solution (5, 14 and 39 mg/l) and field sample concentration (661 mg/l). In addition, the removal of Iron (II) was investigated at different times. The Prepared compound and its nanostructure with AgNPs show highly efficient in removing the Iron ions. Quantum chemical descriptors using DFT was discussed. The output of the study pronounces that the C1 molecule can act as chelating agent for Iron (II).

Keywords: triazole derivatives, silver nanoparticles, iron (II), oil field

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Authors: M. Otrusinova, E. Pastuszkova

Abstract:

The article is addressing the currently ongoing reform processes of transforming the public finance accounting based on cash flow principle to accrual principle. The presented analysis concerns the issues associated with the introduction of the state accounting from the perspective of municipal employees in compiling the opinions of financial experts in conditions of the Czech Republic. The aim of this paper is to present outcomes of analysis focused on currently discussed topics which are related to introducing the accrual principle into accounting of selected entities, especially municipalities and municipality-funded institutions. The output of the paper consists of comparing the application of the accrual principle in the financial reporting of municipalities in the Czech Republic and Slovakia. In conclusion and based on the survey, respondents from Slovak municipalities that have already adopted the accrual accounting principle show better opinion than Czech municipalities.

Keywords: accrual principle, accounting, accounting reform, Czech Republic, municipalities, public finance

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Authors: Hamza Nejib, Okba Taouali

Abstract:

This paper presents two of the most knowing kernel adaptive filtering (KAF) approaches, the kernel least mean squares and the kernel recursive least squares, in order to predict a new output of nonlinear signal processing. Both of these methods implement a nonlinear transfer function using kernel methods in a particular space named reproducing kernel Hilbert space (RKHS) where the model is a linear combination of kernel functions applied to transform the observed data from the input space to a high dimensional feature space of vectors, this idea known as the kernel trick. Then KAF is the developing filters in RKHS. We use two nonlinear signal processing problems, Mackey Glass chaotic time series prediction and nonlinear channel equalization to figure the performance of the approaches presented and finally to result which of them is the adapted one.

Keywords: online prediction, KAF, signal processing, RKHS, Kernel methods, KRLS, KLMS

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Authors: Osama Madkhali

Abstract:

GdAl₃(BO₃)₄ phosphors, incorporating Dy³+ and Dy³+/Eu³+ activators, were successfully synthesized via the gel combustion method. Powder X-ray diffraction (XRD) was utilized to ascertain phase purity and assess the impact of dopant concentration on the crystallographic structure. Photoluminescence (PL) measurements revealed that luminescence properties' intensity and lifetime varied with Dy³+ and Eu³+ ion concentrations. The relationship between luminescence intensity and doping concentration was explored in the context of the energy transfer process between Eu³+ and Dy³+ ions. An increase in Eu³+ co-doping concentrations resulted in a decrease in luminescence lifetime. Energy transfer efficiency was significantly enhanced from 26% to 84% with Eu³+ co-doping, as evidenced by decay curve analysis. These findings position GdAl₃(BO₃)4: Dy³+, Eu³+ phosphors as promising candidates for LED applications in solid-state lighting and displays.

Keywords: GdAl₃(BO₃)₄ phosphors, Dy³+/Eu³+ co-doping, photoluminescence (PL) measurements, luminescence properties, LED applications, solid-state lighting

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Authors: Rita Chattopadhyay, Vivek Anand Thoutam

Abstract:

Speech is the most acceptable means of communication where we can quickly exchange our feelings and thoughts. Quite often, people can communicate orally but cannot interact or work with computers or devices. It’s easy and quick to give speech commands than typing commands to computers. In the same way, it’s easy listening to audio played from a device than extract output from computers or devices. Especially with Robotics being an emerging market with applications in warehouses, the hospitality industry, consumer electronics, assistive technology, etc., speech-based human-machine interaction is emerging as a lucrative feature for robot manufacturers. Considering this factor, the objective of this paper is to design the “Audio-Visual Co-Data Processing Pipeline.” This pipeline is an integrated version of Automatic speech recognition, a Natural language model for text understanding, object detection, and text-to-speech modules. There are many Deep Learning models for each type of the modules mentioned above, but OpenVINO Model Zoo models are used because the OpenVINO toolkit covers both computer vision and non-computer vision workloads across Intel hardware and maximizes performance, and accelerates application development. A speech command is given as input that has information about target objects to be detected and start and end times to extract the required interval from the video. Speech is converted to text using the Automatic speech recognition QuartzNet model. The summary is extracted from text using a natural language model Generative Pre-Trained Transformer-3 (GPT-3). Based on the summary, essential frames from the video are extracted, and the You Only Look Once (YOLO) object detection model detects You Only Look Once (YOLO) objects on these extracted frames. Frame numbers that have target objects (specified objects in the speech command) are saved as text. Finally, this text (frame numbers) is converted to speech using text to speech model and will be played from the device. This project is developed for 80 You Only Look Once (YOLO) labels, and the user can extract frames based on only one or two target labels. This pipeline can be extended for more than two target labels easily by making appropriate changes in the object detection module. This project is developed for four different speech command formats by including sample examples in the prompt used by Generative Pre-Trained Transformer-3 (GPT-3) model. Based on user preference, one can come up with a new speech command format by including some examples of the respective format in the prompt used by the Generative Pre-Trained Transformer-3 (GPT-3) model. This pipeline can be used in many projects like human-machine interface, human-robot interaction, and surveillance through speech commands. All object detection projects can be upgraded using this pipeline so that one can give speech commands and output is played from the device.

Keywords: OpenVINO, automatic speech recognition, natural language processing, object detection, text to speech

Procedia PDF Downloads 80