Search results for: average cycle time

Authors: Andrey V. Timofeev

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The practical efficient approach is suggested to estimate the high-speed objects instant bounds in C-OTDR monitoring systems. In case of super-dynamic objects (trains, cars) is difficult to obtain the adequate estimate of the instantaneous object localization because of estimation lag. In other words, reliable estimation coordinates of monitored object requires taking some time for data observation collection by means of C-OTDR system, and only if the required sample volume will be collected the final decision could be issued. But it is contrary to requirements of many real applications. For example, in rail traffic management systems we need to get data off the dynamic objects localization in real time. The way to solve this problem is to use the set of statistical independent parameters of C-OTDR signals for obtaining the most reliable solution in real time. The parameters of this type we can call as 'signaling parameters' (SP). There are several the SP’s which carry information about dynamic objects instant localization for each of C-OTDR channels. The problem is that some of these parameters are very sensitive to dynamics of seismoacoustic emission sources but are non-stable. On the other hand, in case the SP is very stable it becomes insensitive as a rule. This report contains describing the method for SP’s co-processing which is designed to get the most effective dynamic objects localization estimates in the C-OTDR monitoring system framework.

Keywords: C-OTDR-system, co-processing of signaling parameters, high-speed objects localization, multichannel monitoring systems

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Authors: Abderrahmane Diaf, Kamel Benabdellaziz

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Remote arid areas of the vast expanses of the African deserts hold huge subterranean reserves of brackish water resources waiting for economic development. This work presents design guidelines as well as initial performance data of new autonomous solar desalination equipment which could help local communities produce their own fresh water using solar energy only and, why not, contribute to transforming desert lands into lush gardens. The output of solar distillation equipment is typically low and in the range of 3 l/m2/day on the average. This new design with an integrated, water-based, environmentally-friendly solar heat storage system produced 5 l/m2/day in early spring weather. Equipment output during summer exceeded 9 liters per m2 per day.

Keywords: multiple trough distillation, solar desalination, solar distillation with heat storage, water based heat storage system

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Authors: Muhammad Farid, Jen Der Day

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The purpose of this study is to explore the construct of service innovation model for Small and medium-sized enterprises (SMEs) in automotive service industries. A case study of repair shop of the motorcycle at Makassar city illustrates measure innovation implementation, the degree of innovation, and identifies the type of innovation by the service innovation model for SMEs. In this paper, we interview 10 managers of SMEs and analyze their answers. We find that innovation implementation has been slowly; only producing new service innovation 0.62 unit average per year. Incremental innovation is the present option for SMEs, because they choose safer roads to improve service continuously. If want to create radical innovation, they still consider the aspect of cost, system, and readiness of human resources.

Keywords: service innovation, incremental innovation, SMEs, automotive service industries

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Authors: Chia-Jung Li, Kuan-Hao Tsui

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As women age, the quality of their oocytes deteriorates irreversibly, leading to reduced fertility. To better understand the role of Ferroptosis-related genes in ovarian aging, we employed a multi-omics analysis approach, including spatial transcriptomics, single-cell RNA sequencing, human ovarian pathology, and clinical biopsies. Our study identified excess lipid peroxide accumulation in aging germ cells, metal ion accumulation via oxidative reduction, and the interaction between ferroptosis and cellular energy metabolism. We used multi-histological prediction of ferroptosis key genes to evaluate 75 patients with ovarian aging insufficiency and then analyzed changes in hub genes after supplementing with DHEA, Ubiquinol CoQ10, and Cleo-20 T3 for two months. Our results demonstrated a significant increase in TFRC, GPX4, NCOA4, and SLC3A2, which were consistent with our multi-component prediction. We theorized that these supplements increase the mitochondrial tricarboxylic acid cycle (TCA) or electron transport chain (ETC), thereby increasing antioxidant enzyme GPX4 levels and reducing lipid peroxide accumulation and ferroptosis. Overall, our findings suggest that supplementation intervention significantly improves IVF outcomes in senescent cells by enhancing metal ion and energy metabolism and enhancing oocyte quality in aging women.

Keywords: multi-omics, nutrients, ferroptosis, ovarian aging

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Authors: C. N. Okafor, M. Maaza, T. A. E. Mokrani

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A proton exchange membrane has been developed for Direct Methanol Fuel Cell (DMFC). The nanofiber network composite membranes were prepared by interconnected network of Nafion (perfuorosulfonic acid) nanofibers that have been embedded in an uncharged and inert polymer matrix, by electro-spinning. The spinning solution of Nafion with a low concentration (1 wt. % compared to Nafion) of high molecular weight poly(ethylene oxide), as a carrier polymer. The interconnected network of Nafion nanofibers with average fiber diameter in the range of 160-700nm, were used to make the membranes, with the nanofiber occupying up to 85% of the membrane volume. The matrix polymer was cross-linked with Norland Optical Adhesive 63 under UV. The resulting membranes showed proton conductivity of 0.10 S/cm at 25°C and 80% RH; and methanol permeability of 3.6 x 10-6 cm2/s.

Keywords: composite membrane, electrospinning, fuel cell, nanofibers

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Authors: Mohammadreza Hedyehzadeh, Mahdi Yousefi

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Colon cancer is one of the most common cancer, which predicted to increase its prevalence due to the bad eating habits of peoples. Nowadays, due to the busyness of people, the use of fast foods is increasing, and therefore, diagnosis of this disease and its treatment are of particular importance. To determine the best treatment approach for each specific colon cancer patients, the oncologist should be known the stage of the tumor. The most common method to determine the tumor stage is TNM staging system. In this system, M indicates the presence of metastasis, N indicates the extent of spread to the lymph nodes, and T indicates the size of the tumor. It is clear that in order to determine all three of these parameters, an imaging method must be used, and the gold standard imaging protocols for this purpose are CT and PET/CT. In CT imaging, due to the use of X-rays, the risk of cancer and the absorbed dose of the patient is high, while in the PET/CT method, there is a lack of access to the device due to its high cost. Therefore, in this study, we aimed to estimate the tumor size and the extent of its spread to the lymph nodes using MR images. More than 1300 MR images collected from the TCIA portal, and in the first step (pre-processing), histogram equalization to improve image qualities and resizing to get the same image size was done. Two expert radiologists, which work more than 21 years on colon cancer cases, segmented the images and extracted the tumor region from the images. The next step is feature extraction from segmented images and then classify the data into three classes: T0N0، T3N1 و T3N2. In this article, the VGG-16 convolutional neural network has been used to perform both of the above-mentioned tasks, i.e., feature extraction and classification. This network has 13 convolution layers for feature extraction and three fully connected layers with the softmax activation function for classification. In order to validate the proposed method, the 10-fold cross validation method used in such a way that the data was randomly divided into three parts: training (70% of data), validation (10% of data) and the rest for testing. It is repeated 10 times, each time, the accuracy, sensitivity and specificity of the model are calculated and the average of ten repetitions is reported as the result. The accuracy, specificity and sensitivity of the proposed method for testing dataset was 89/09%, 95/8% and 96/4%. Compared to previous studies, using a safe imaging technique (MRI) and non-use of predefined hand-crafted imaging features to determine the stage of colon cancer patients are some of the study advantages.

Keywords: colon cancer, VGG-16, magnetic resonance imaging, tumor size, lymph node metastasis

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Authors: Ronal Muresano, Andrea Pagano

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Nowadays, the mathematical/statistical applications are developed with more complexity and accuracy. However, these precisions and complexities have brought as result that applications need more computational power in order to be executed faster. In this sense, the multicore environments are playing an important role to improve and to optimize the execution time of these applications. These environments allow us the inclusion of more parallelism inside the node. However, to take advantage of this parallelism is not an easy task, because we have to deal with some problems such as: cores communications, data locality, memory sizes (cache and RAM), synchronizations, data dependencies on the model, etc. These issues are becoming more important when we wish to improve the application’s performance and scalability. Hence, this paper describes an optimization method developed for Systemic Model of Banking Originated Losses (SYMBOL) tool developed by the European Commission, which is based on analyzing the application's weakness in order to exploit the advantages of the multicore. All these improvements are done in an automatic and transparent manner with the aim of improving the performance metrics of our tool. Finally, experimental evaluations show the effectiveness of our new optimized version, in which we have achieved a considerable improvement on the execution time. The time has been reduced around 96% for the best case tested, between the original serial version and the automatic parallel version.

Keywords: algorithm optimization, bank failures, OpenMP, parallel techniques, statistical tool

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Authors: Dimakatso Machetele, Kowiyou Yessoufou

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Whilst several studies indicated that road accident events might be more complex than thought, we have a limited scientific understanding of this complexity in South Africa. The present project proposes and tests a more comprehensive metamodel that integrates multiple causality relationships among variables previously linked to road accidents. This was done by fitting a structural equation model (SEM) to the data collected from various sources. The study also fitted the GARCH Model (Generalized Auto-Regressive Conditional Heteroskedasticity) to predict the future of road accidents in the country. The analysis shows that the number of road accidents has been increasing since 1935. The road fatality rate follows a polynomial shape following the equation: y = -0.0114x²+1.2378x-2.2627 (R²=0.76) with y = death rate and x = year. This trend results in an average death rate of 23.14 deaths per 100,000 people. Furthermore, the analysis shows that the number of crashes could be significantly explained by the total number of vehicles (P < 0.001), number of registered vehicles (P < 0.001), number of unregistered vehicles (P = 0.003) and the population of the country (P < 0.001). As opposed to expectation, the number of driver licenses issued and total distance traveled by vehicles do not correlate significantly with the number of crashes (P > 0.05). Furthermore, the analysis reveals that the number of casualties could be linked significantly to the number of registered vehicles (P < 0.001) and total distance traveled by vehicles (P = 0.03). As for the number of fatal crashes, the analysis reveals that the total number of vehicles (P < 0.001), number of registered (P < 0.001) and unregistered vehicles (P < 0.001), the population of the country (P < 0.001) and the total distance traveled by vehicles (P < 0.001) correlate significantly with the number of fatal crashes. However, the number of casualties and again the number of driver licenses do not seem to determine the number of fatal crashes (P > 0.05). Finally, the number of crashes is predicted to be roughly constant overtime at 617,253 accidents for the next 10 years, with the worse scenario suggesting that this number may reach 1 896 667. The number of casualties was also predicted to be roughly constant at 93 531 overtime, although this number may reach 661 531 in the worst-case scenario. However, although the number of fatal crashes may decrease over time, it is forecasted to reach 11 241 fatal crashes within the next 10 years, with the worse scenario estimated at 19 034 within the same period. Finally, the number of fatalities is also predicted to be roughly constant at 14 739 but may also reach 172 784 in the worse scenario. Overall, the present study reveals the complexity of road accidents and allows us to propose several recommendations aimed to reduce the trend of road accidents, casualties, fatal crashes, and death in South Africa.

Keywords: road accidents, South Africa, statistical modelling, trends

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Authors: Marwa Hussien Mohamed, Mohamed Helmy Khafagy

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Map-Reduce is a programming model which is widely used to extract valuable information from enormous volumes of data. Map-reduce designed to support heterogeneous datasets. Apache Hadoop map-reduce used extensively to uncover hidden pattern like data mining, SQL, etc. The most important operation for data analysis is joining operation. But, map-reduce framework does not directly support join algorithm. This paper explains and compares two-way and multi-way map-reduce join algorithms for map reduce also we implement MR join Algorithms and show the performance of each phase in MR join algorithms. Our experimental results show that map side join and map merge join in two-way join algorithms has the longest time according to preprocessing step sorting data and reduce side cascade join has the longest time at Multi-Way join algorithms.

Keywords: Hadoop, MapReduce, multi-way join, two-way join, Ubuntu

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Authors: Hieu Duy Nguyen, Chitsan Lin Jr., Dung Duc Tran

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Nowadays, drought and salinity intrusion becomes a severe problem in the Lower Mekong region due to climate change, especially in coastal provinces. Freshwater resources are decreased due to sea-level rise and the decline in water flow from upstream in the dry season. The combination of the above issues can lead to many effects on the environment and human health in affected areas such as the pathological of digestive or decreased the immune system. Tidal cycle and upstream flows are the two main factors affecting the saline intrusion process and the former salt-wedge in the estuary. Under suitable conditions, salt-wedge can be going further upstream under the water surface and affected groundwater. In order to have a proper plan for the mitigation of the above adverse effects, we need to understand the characteristics of this process. In this study, 3D model is used to investigate the movement of salt-wedge under different conditions of tidal and flow discharge. The salinity in the vertical profile is also measured in the dry season of 2017 and 2018 for model calibrating. The data has proved that there is the presence of salt-wedge in the study area. The obtained results will help strategic planners to use and preserve water resources more effectively and serve as a basis for new research directions on saline intrusion and human health.

Keywords: salt-wedge, salinity intrusion, human health, 3D model

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Authors: Jianqin Qu

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This paper proposes a rigid point set matching algorithm in arbitrary dimensions based on the idea of symmetric covariant function. A group of functions of the points in the set are formulated using rigid invariants. Each of these functions computes a pair of correspondence from the given point set. Then the computed correspondences are used to recover the unknown rigid transform parameters. Each computed point can be geometrically interpreted as the weighted mean center of the point set. The algorithm is compact, fast, and dimension free without any optimization process. It either computes the desired transform for noiseless data in linear time, or fails quickly in exceptional cases. Experimental results for synthetic data and 2D/3D real data are provided, which demonstrate potential applications of the algorithm to a wide range of problems.

Keywords: covariant point, point matching, dimension free, rigid registration

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Authors: Ayodele James Akinola

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This study examines how social and linguistic variables influenced communication between neurologists and patients in selected university teaching hospitals (UTHs) in southwestern Nigeria. Jacob Mey’s Pragmatic Acts, complemented by Emanuel and Emanuel’s model of doctor-patient relationship, served as the theoretical framework. Data comprising 22 audio-recorded neurologist-patient interactions were collected from two UTHs in the southwestern region of Nigeria. Data revealed that educational attainment of patients has insignificant influence on the interaction where the linguistic prowess of the patient has been impaired for consultative communication. However, the status influenced the degree of attention paid to patients by neurologists and determines the amount of time 'trying to help patients to communicate'. Patients with lower educational status and who could not communicate in English spent more time narrating their ailment to neurologists. Patients with higher educational status and could communicate in English saves consultation time as they express themselves briefly unlike those who were of little or no education in the clinics. Through this, diagnoses and therapeutic processes took eight to 12 minutes. 20 minutes was the longest duration recorded. Neurologist-patient interaction in the observed hospitals is shaped by neurologists’ experience, patients’ social variables and language.

Keywords: medical pragmatics, neurologist-patient interaction, nigeria, socio-linguistic influence

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Authors: Pavel E. Mikriukov

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The demand for natural gas (NG) is increasing every year around the world, so it is necessary to produce and transport NG in large quantities. To solve this problem, liquefied natural gas (LNG) plants are used, using different equipment and different technologies to achieve the required LNG quality. To determine the best efficiency of the LNG liquefaction plant, it is necessary to analyze the equipment used in this process and identify other technological solutions for LNG production using more productive and energy-efficient equipment. Based on this, mathematical models of the technological process of the LNG plant were created, which are based on a two-circuit system of heat exchange equipment and a nitrogen isolated cycle for NG cooling. The final liquefaction of natural gas is performed on the construction of the basic principle of the Joule-Thompson effect. The pressure and temperature drop are considered on different types of equipment such as throttle valve, which was used in the basic scheme; turbo expander and supersonic separator, which act as new equipment, to be compared with the efficiency of the basic scheme of the unit. New configurations of LNG plants are suggested, which can be used in almost all LNG facilities. As a result of the analysis, it turned out that the turbo expander and the supersonic separator have comparatively equal potential in comparison with the baseline scheme execution on the throttle valve. A more rational method of selecting the technology and the equipment used for natural gas liquefaction can improve the efficiency of low-tonnage plants and reduce the cost of gas for own needs.

Keywords: gas liquefaction, gas, Joule-Thompson effect, LNG, low-tonnage LNG, supersonic separator, Throttle valve, turbo expander

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Authors: C. C. Kruger, P. Van Tonder

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Concrete deteriorates over time and the deterioration can be escalated due to multiple factors. When deteriorations are beneath the concrete’s surface, they could be unknown, even more so when they are located at high elevations. Establishing the severity of such defects could prove difficult and therefore the need to find efficient, safe and economical methods to find these defects becomes ever more important. Current methods using thermography to find defects require equipment such as scaffolding to reach these higher elevations. This could become time- consuming and costly. The risks involved with personnel scaffold or abseil to such heights are high. Accordingly, by combining the technologies of a thermal camera and a Remotely Piloted Aerial System it could be used to find better diagnostic methods. The data could then be constructed into a 3D thermal model to easy representation of the results

Keywords: concrete, infrared thermography, 3D thermal models, diagnostic

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Authors: John Battersby, Rhys Ball

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After the 15 March 2019 Mosque attacks in Christchurch, the New Zealand security sector has had to address its training and preparedness levels for dealing with contemporary terrorist threats as well as potential future manifestations of terrorism. From time to time, members of the academic community from Australia and New Zealand have been asked to assist agencies in this endeavour. In the course of 2018, New Zealand security sector professionals working in the counter-terrorism area were interviewed about how they regarded academic contributions to understanding terrorism and counter-terrorism. Responses were mixed, ranging from anti-intellectualism, a belief that the inability to access classified material rendered academic work practically useless - to some genuine interest and desire for broad based academic studies on issues practitioners did not have the time to look at. Twelve months later, researchers have revisited those spoken to prior to the Brenton Tarrant 15 March shooting to establish if there has been a change in the way academic research is perceived, viewed and valued, and what key factors have contributed to this shift in thinking. This paper takes this data, combined with a consideration of the literature on higher education within professional police and intelligence forces, and on the general perception of academics by practitioners, to present a series of findings that will contribute to a more proactive and effective set of engagements, between two distinct but important security sectors, that reflect more closely with international practice.

Keywords: academic, counter terrorism, intelligence, practitioner, research, security

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Authors: Hamid Reza Goshayeshi

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The effect of ɑ(alpha) Fe2O3 and ɤ(gamma)Fe2O3 particles on the heat transfer performance of an oscillating heat pipe was investigated experimentally. Kerosene was used as the base fluid for the OHP. Six size particles with average diameters of 10 nm, 20 nm, and 30 nm ɑFe2O3 and ɤFe2O3 were investigated, respectively. Experimental results show that the ɤFe2O3 particles added in the OHP significantly affect the heat transfer performance. When the OHP was charged with kerosene and 20 nm ɤ Fe2O3 particles, the OHP can achieve the best heat transfer performance among six particles investigated in this research.

Keywords: copper oscillating heat pipe, heat transfer, flow, comparison of ɑ(alpha)Fe2O3 and ɤ(gamma)Fe2O3, increase heat transfer

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Authors: Desissa Yadeta Muleta

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Purely organic long-persistent luminescence materials (OLPLMs) have been developed as emerging organic materials due to their simple production process, low preparation cost and better biocompatibilities. Notably, OLPLMs with afterglow-time-tunable long-persistent luminescence (LPL) characteristics enable higher-level protection applications and have great prospects in biological applications. The realization of these advanced performances depends on our ability to gradually tune LPL duration under ambient conditions, however, the strategies to achieve this are few due to the lack of unambiguous mechanisms. Here, we propose a two-step strategy to gradually tune LPL duration of OLPLMs over a wide range of seconds in water and air, by using derivatives as the guest and introducing a third-party material into the host-immobilized host–guest doping system. Based on this strategy, we develop an analysis method for deoxyribonucleic acid (DNA) content detection without DNA separation in aqueous samples, which circumvents the influence of the chromophore, fluorophore and other interferents in vivo, enabling a certain degree of in situ detection that is difficult to achieve using today’s methods. This work will expedite the development of afterglow-time-tunable OLPLMs and expand new horizons for their applications in data protection, bio-detection, and bio-sensing

Keywords: deoxyribonucliec acid, long persistent luminescent materials, water, air

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Authors: M. G. Talasbayen, N. N. Dyussenbayev, Y. D. Kali, R. A. Zholbarysov, Y. N. Duissenbayev, I. Z. Mammadinova, S. M. Nuradilov

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Background. Hemorrhagic stroke is an acute cerebrovascular accident resulting from rupture of a cerebral vessel or increased permeability of the wall and imbibition of blood into the brain parenchyma. Arterial hypertension is a common cause of hemorrhagic stroke. Male gender and age over 55 years is a risk factor for intracerebral hemorrhage. Treatment of intracerebral hemorrhage is aimed at the primary pathophysiological link: the relief of coagulopathy and the control of arterial hypertension. Early surgical treatment can limit cerebral compression; prevent toxic effects of blood to the brain parenchyma. Despite progress in the development of neuroimaging data, the use of minimally invasive techniques, and navigation system, mortality from intracerebral hemorrhage remains high. Materials and methods. The study included 78 patients (62.82% male and 37.18% female) with a verified diagnosis of hemorrhagic stroke in the period from 2019 to 2021. The age of patients ranged from 25 to 80 years, the average age was 54.66±11.9 years. Demographic, brain CT data (localization, volume of hematomas), methods of treatment, and disease outcome were analyzed. Results. The retrospective analyze demonstrate that 78.2% of all patients underwent surgical treatment: decompressive craniectomy in 37.7%, craniotomy with hematoma evacuation in 29.5%, and hematoma draining in 24.59% cases. The study of the proportion of deaths, depending on the volume of intracerebral hemorrhage, shows that the number of deaths was higher in the group with a hematoma volume of more than 60 ml. Evaluation of the relationship between the time before surgery and mortality demonstrates that the most favorable outcome is observed during surgical treatment in the interval from 3 to 24 hours. Mortality depending on age did not reveal a significant difference between age groups. An analysis of the impact of the surgery type on mortality reveals that decompressive craniectomy with or without hematoma evacuation led to an unfavorable outcome in 73.9% of cases, while craniotomy with hematoma evacuation and drainage led to mortality only in 28.82% cases. Conclusion. Even though the multimodal approaches, the development of surgical techniques and equipment, and the selection of optimal conservative therapy, the question of determining the tactics of managing and treating hemorrhagic strokes is still controversial. Nevertheless, our experience shows that surgical intervention within 24 hours from the moment of admission and craniotomy with hematoma evacuation improves the prognosis of treatment outcomes.

Keywords: hemorragic stroke, Intracerebral hemorrhage, surgical treatment, stroke mortality

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Authors: Reena Behal, D. P. Shukla

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In this paper, we investigate Bulk Viscous Bianchi Type V Cosmological Model with Time dependent gravitational constant and cosmological constant in general Relativity by assuming ξ(t)=ξ_(0 ) p^m where ξ_(0 ) and m are constants. We also assume a variation law for Hubble parameter as H(R) = a (R^(-n)+1), where a>0, n>1 being constant. Two universe models were obtained, and their physical behavior has been discussed. When n=1 the Universe starts from singular state whereas when n=0 the cosmology follows a no singular state. The presence of bulk viscosity increase matter density’s value.

Keywords: Bulk Viscous Bianchi Type V Cosmological Model, hubble constants, gravitational constant, cosmological constants

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Authors: Sam Bahreini, Payam Hayati

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Metal-organic coordination [Cu(L)₄(SCN)₂] was synthesized applying ultrasonic irradiation, and its photocatalytic performance for the degradation of Remdesivir (RS) under sunlight irradiation was systematically explored for the first time in this study. The physicochemical properties of the synthesized photocatalyst were investigated using Fourier-transform infrared (FT-IR), field emission scanning electron microscopy (FE-SEM), powder x-ray diffraction (PXRD), energy-dispersive x-ray (EDX), thermal gravimetric analysis (TGA), diffuse reflectance spectroscopy (DRS) techniques. Systematic examinations were carried out by changing irradiation time, temperature, solution pH value, contact time, RS concentration, and catalyst dosage. The photodegradation kinetic profiles were modeled in pseudo-first order, pseudo-second-order, and intraparticle diffusion models reflected that photodegradation onto [Cu(L)₄(SCN)₂] catalyst follows pseudo-first order kinetic model. The fabricated [Cu(L)₄(SCN)₂] nanostructure bandgap was determined as 2.60 eV utilizing the Kubelka-Munk formula from the diffuse reflectance spectroscopy method. Decreasing chemical oxygen demand (COD) (from 70.5 mgL-1 to 36.4 mgL-1) under optimal conditions well confirmed mineralizing of the RS drug. The values of ΔH° and ΔS° was negative, implying the process of adsorption is spontaneous and more favorable in lower temperatures.

Keywords: Photocatalytic degradation, COVID-19, density functional theory (DFT), molecular electrostatic potential (MEP)

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Authors: Young Gyu Kim, Sangguk Ahn, Gyoutae Park, Hiesik Kim

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In the gas industrial fields, there are many problems to detect extremely small amounts of combustible gas (CH₄) if a conventional semiconductor is used. Those reasons are that measuring is difficult at the low concentration level, the stabilization time is long, and an initial response time is slow. In this study, we propose a method to solve these issues using two specific sensors to overcome the circumstances of temperature and humidity. This idea is to combine a catalytic and a semiconductor type sensor and to utilize every advantage from every sensor’s characteristic. In order to achieve the goal, we reduced fluctuations of a gas sensor for temperature and humidity by applying designed circuits for sensing temperature and humidity. And we induced the best calibration line of gas sensors through adjusting a weight value corresponding to changeable patterns of temperature and humidity after their data are previously acquired and stored. We proposed and developed the gas leak detector using two sensor modules, which is first operated by a semiconductor sensor for measuring small gas quantities and second a catalytic type sensor is detected if measuring range of the first sensor is beyond. We conclusively verified characteristics of sharp sensitivity and fast response time against even at lower gas concentration level through experiments other than a conventional gas sensor. We think that our proposed idea is very useful if another gas leak is developed to enable measuring extremely small quantities of toxic and flammable gases.

Keywords: gas sensor, leak detector, lower concentration, and calibration

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Authors: Henry O. Udeha, Kwaku G. Duodub, Afam I. O. Jideanic

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Finger millet (FM) [Eleusine coracana] is considered as a potential ‘‘super grain’’ by the United States National Academies as one of the most nutritious among all the major cereals. The regular consumption of FM-based diets has been associated with reduced risk of diabetes, cataract and gastrointestinal tract disorder. Hyperglycaemic, hypocholesterolaemic and anticataractogenic, and other health improvement properties have been reported. This study examined the effect of fermentation time and microbial source on physicochemical properties, phenolic compounds and antioxidant activity of two finger millet (FM) malt flours. Sorghum was used as an external reference. The grains were malted, mashed and fermented using the grain microflora and Lactobacillus fermentum. The phenolic compounds of the resulting beverage were identified and quantified using ultra-performance liquid chromatography (UPLC) and mass spectrometer system (MS). A fermentation-time dependent decrease in pH and viscosities of the beverages, with a corresponding increase in sugar content were noted. The phenolic compounds found in the FM beverages were protocatechuic acid, catechin and epicatechin. Decrease in total phenolics of the beverages was observed with increased fermentation time. The beverages exhibited 2, 2-diphenyl-1-picrylhydrazyl, 2, 2՛-azinobis-3-ethylbenzthiazoline-6-sulfonic acid radical scavenging action and iron reducing activities, which were significantly (p < 0.05) reduced at 96 h fermentation for both microbial sources. The 24 h fermented beverages retained a higher amount of total phenolics and had higher antioxidant activity compared to other fermentation periods. The study demonstrates that FM could be utilised as a functional grain in the production of non-alcoholic beverage with important phenolic compounds for health promotion and wellness.

Keywords: antioxidant activity, eleusine coracana, fermentation, phenolic compounds

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Authors: Hee-Choul Kwon, Heeyong Kwon

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Image rotation is one of main pre-processing steps for image processing or image pattern recognition. It is implemented with a rotation matrix multiplication. It requires a lot of floating point arithmetic operations and trigonometric calculations, so it takes a long time to execute. Therefore, there has been a need for a high speed image rotation algorithm without two major time-consuming operations. However, the rotated image has a drawback, i.e. distortions. We solved the problem using an augmented two-step shear transform. We compare the presented algorithm with the conventional rotation with images of various sizes. Experimental results show that the presented algorithm is superior to the conventional rotation one.

Keywords: high-speed rotation operation, image rotation, transform matrix, image processing, pattern recognition

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Authors: Yen-Hui Chen, Terry Walker

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As the world experiences an energy crisis, investing in sustainable energy resources is a pressing mission for many countries. Microalgae-derived biodiesel has attracted intensive attention as an important biofuel, and microalgae Chlorella protothecoides lipid is recognized as a renewable source for microalgae-derived biodiesel production. Supercritical carbon dioxide (SC-CO₂) is a promising green solvent that may potentially substitute the use of organic solvents for lipid extraction; however, the efficiency of SC-CO₂ extraction may be affected by many variables, including temperature, pressure and extraction time individually or in combination. In this study, response surface methodology (RSM) was used to optimize the process parameters, including temperature, pressure and extraction time, on C. protothecoides lipid yield by SC-CO₂ extraction. A second order polynomial model provided a good fit (R-square value of 0.94) for the C. protothecoides lipid yield. The linear and quadratic terms of temperature, pressure and extraction time—as well as the interaction between temperature and pressure—showed significant effects on lipid yield during extraction. The optimal lipid yield from the model was predicted as the temperature of 59 °C, the pressure of 350.7 bar and the extraction time 2.8 hours. Under these conditions, the experimental lipid yield (25%) was close to the predicted value. The principal fatty acid methyl esters (FAME) of C. protothecoides lipid-derived biodiesel were oleic acid methyl ester (60.1%), linoleic acid methyl ester (18.6%) and palmitic acid methyl ester (11.4%), which made up more than 90% of the total FAMEs. In summary, this study indicated that RSM was useful to characterize the optimization the SC-CO₂ extraction process of C. protothecoides lipid yield, and the second-order polynomial model could be used for predicting and describing the lipid yield very well. In addition, C. protothecoides lipid, extracted by SC-CO₂, was suggested as a potential candidate for microalgae-derived biodiesel production.

Keywords: Chlorella protothecoides, microalgal lipids, response surface methodology, supercritical carbon dioxide extraction

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Authors: S. Sharma, U. Batra, S. Kapoor, A. Dua

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In this study, the effects and interactions of reaction time and capping agent assistance during sol-gel synthesis of magnesium substituted hydroxyapatite nanopowder (MgHA) on hydroxyapatite (HA) to β-tricalcium phosphate (β-TCP) ratio, Ca/P ratio and mean crystallite size was examined experimentally as well as through statistical analysis. MgHA nanopowders were synthesized by sol-gel technique at room temperature using aqueous solution of calcium nitrate tetrahydrate, magnesium nitrate hexahydrate and potassium dihydrogen phosphate as starting materials. The reaction time for sol-gel synthesis was varied between 15 to 60 minutes. Two process routes were followed with and without addition of triethanolamine (TEA) in the solutions. The elemental compositions of as-synthesized powders were determined using X-ray fluorescence (XRF) spectroscopy. The functional groups present in the as-synthesized MgHA nanopowders were established through Fourier Transform Infrared Spectroscopy (FTIR). The amounts of phases present, Ca/P ratio and mean crystallite sizes of MgHA nanopowders were determined using X-ray diffraction (XRD). The HA content in biphasic mixture of HA and β-TCP and Ca/P ratio in as-synthesized MgHA nanopowders increased effectively with reaction time of sols (p < 0.0001, two way Anova), however, these were independent of TEA addition (p > 0.15, two way Anova). The MgHA nanopowders synthesized with TEA assistance exhibited 14 nm lower crystallite size (p < 0.018, 2 sample t-test) compared to the powder synthesized without TEA assistance.

Keywords: capping agent, hydroxyapatite, regression analysis, sol-gel, 2- sample t-test, two-way analysis of variance (ANOVA)

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Authors: Barnali Thakuria, Labananda Choudhury

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Gender equality and women’s empowerment is one of the components of eight Millennium Development Goal (MDG).Literacy and employment are the parameters which reflect the empowerment of women. But in a developing country like India, literacy and working status among the females are not satisfactory. Both literacy and employment technically can be measured by Literate Life Expectancy (LLE) and Working Life Expectancy (WLE).One can also combine both the factors literacy and working to get a better new measure. The proposed indicator can be called literate-working life expectancy (LWLE). LLE gives an average number of years a person lives in a literate state under current mortality and literacy conditions while WLE defined as average number of years a person lives in a working state if current mortality and working condition prevails. Similarly, LWLE gives number of expected years by a person living under both literate and working state. The situation of females cannot be figured out without comparing both the sexes. In the present paper an attempt has been made to estimate LLE and WLE in India along with some selected states from various zones of India namely Assam from the North-East, Gujarat from the West, Kerala from the South, Rajasthan from the North, Uttar Pradesh from the Central and West Bengal from the East respectively for both the sexes based on 2011 census. Furthermore, we have also developed a formula for a new indicator namely Literate-Working Life Expectancy (LWLE) and the proposed index has been applied in India and the selected states mentioned above for both males and females. Data has been extracted from SRS(Sample Registration System) based Abridged Life Table and Census of India. The computation of LLE follows the method developed by Lutz while WLE has followed the method developed by Saw Swee Hock. By combining both the factors literacy and employment, the new indicator LWLE also follows the method like LLE and WLE. Contrasted results have been found in different parts of India. The result shows that LLE at birth is highest(lowest) in the state Kerala(Uttar Pradesh) with 61.66 (39.51) years among the males. A similar situation is also observed among the females with 62.58 years and 25.11 years respectively. But male WLE at birth is highest (lowest) in Rajasthan(Kerala) with 37.11 (32.64) years. Highest female WLE at birth is also observed in Rajasthan with 23.51 years and the lowest is concentrated in Uttar Pradesh with 11.76 years. It is also found that Kerala’s performance is exceptionally good in terms of LWLE at birth while the lowest LWLE at birth prevails in the state Uttar Pradesh among the males. Female LWLE at birth is highest(lowest) in Kerala(Uttar Pradesh) with 19.73(4.77)years. The corresponding value of the index increases as the number of factors involved in the life expectancy decrease. It is found that women are lagging behind in terms of both literacy and employment. Findings of the study will help the planners to take necessary steps to improve the position of women.

Keywords: life expectancy, literacy, literate life expectancy, working life expectancy

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Authors: T. Ewetumo, K. D. Adedayo, Festus Ben

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Knowledge of the thermal properties of foods is of fundamental importance in the food industry to establish the design of processing equipment. However, for tropical fruit juice, there is very little information in literature, seriously hampering processing procedures. This research work describes the development of an instrument for automated thermal conductivity and thermal diffusivity measurement of tropical fruit juice using a transient thermal probe technique based on line heat principle. The system consists of two thermocouple sensors, constant current source, heater, thermocouple amplifier, microcontroller, microSD card shield and intelligent liquid crystal. A fixed distance of 6.50mm was maintained between the two probes. When heat is applied, the temperature rise at the heater probe measured with time at time interval of 4s for 240s. The measuring element conforms as closely as possible to an infinite line source of heat in an infinite fluid. Under these conditions, thermal conductivity and thermal diffusivity are simultaneously measured, with thermal conductivity determined from the slope of a plot of the temperature rise of the heating element against the logarithm of time while thermal diffusivity was determined from the time it took the sample to attain a peak temperature and the time duration over a fixed diffusivity distance. A constant current source was designed to apply a power input of 16.33W/m to the probe throughout the experiment. The thermal probe was interfaced with a digital display and data logger by using an application program written in C++. Calibration of the instrument was done by determining the thermal properties of distilled water. Error due to convection was avoided by adding 1.5% agar to the water. The instrument has been used for measurement of thermal properties of banana, orange and watermelon. Thermal conductivity values of 0.593, 0.598, 0.586 W/m^o C and thermal diffusivity values of 1.053 ×〖10〗^(-7), 1.086 ×〖10〗^(-7), and 0.959 ×〖10〗^(-7) 〖m/s〗^2 were obtained for banana, orange and water melon respectively. Measured values were stored in a microSD card. The instrument performed very well as it measured the thermal conductivity and thermal diffusivity of the tropical fruit juice samples with statistical analysis (ANOVA) showing no significant difference (p>0.05) between the literature standards and estimated averages of each sample investigated with the developed instrument.

Keywords: thermal conductivity, thermal diffusivity, tropical fruit juice, diffusion equation

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Authors: Wei Li, Tuo Yang

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In order to satisfy the real-time and accurate requirements of cigarette smoke detection in complex scenes, a cigarette smoke detection technology based on the combination of deep learning and color features was proposed. Firstly, based on the color features of cigarette smoke, the suspicious cigarette smoke area in the image is extracted. Secondly, combined with the efficiency of cigarette smoke detection and the problem of network overfitting, a network model for cigarette smoke detection was designed according to YOLOV3 algorithm to reduce the false detection rate. The experimental results show that the method is feasible and effective, and the accuracy of cigarette smoke detection is up to 99.13%, which satisfies the requirements of real-time cigarette smoke detection in complex scenes.

Keywords: deep learning, computer vision, cigarette smoke detection, YOLOV3, color feature extraction

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Authors: Melody Yin

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Concussions impact a large amount of adolescents; they make up as much as half of the diagnosed concussions in America. This research proposes a hybrid machine learning model based on the combination of human/knowledge-based domains and computer-generated feature rankings to improve the accuracy of diagnosing sports related concussion (SRC). Using a data set of symptoms collected on the sideline post-SRC events, the symptom selection criteria method has been developed by using Google AutoML's important score function to identify the top 10 symptom features. In addition, symptom domains have been introduced as another parameter, categorizing the symptoms into physical, cognitive, sleep, and emotional domains. The hybrid machine learning model has been trained with a combination of the top 10 symptoms and 4 domains. From the results, the hybrid model was the best performer for symptom resolution time prediction in 2 and 4-week thresholds. This research is a proof of concept study in the use of domains along with machine learning in order to improve concussion prediction accuracy. It is also possible that the use of domains can make the model more efficient due to reduced training time. This research examines the use of a hybrid method in predicting sports-related concussion. This achievement is based on data preprocessing, using a hybrid method to select criteria to achieve high performance.

Keywords: hybrid model, machine learning, sports related concussion, symptom resolution time

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Authors: Srijitra Khanpakdee, Teera Butburee, Jung-Ho Yun, Miaoqiang Lyu, Supphasin Thaweesak, Piangjai Peerakiatkhajohn

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The synthesis of titanium dioxide (TiO₂) nanorods (NRs) on fluorine-doped tin oxide (FTO) glass via hydrothermal methods was investigated to determine the optimal reaction time for enhanced photocatalytic and optical performance. Reaction times of 4, 6, and 8 hours were studied. Characterization through SEM, UV-vis, XRD, FTIR, Raman spectroscopy and photoelectrochemical (PEC) techniques revealed significant differences in the properties of the TiO₂ NRs based on the reaction duration. XRD and Raman spectroscopy analysis confirmed the formation of the rutile phase of TiO₂. As photoanodes in PEC cells, TiO₂ NRs synthesized for 4 hours exhibited the best photocatalytic activity, with the highest photocurrent density and superior charge transport properties, attributed to their densely packed vertical structure. Longer reaction times resulted in less optimal morphological and photoelectrochemical characteristics. The bandgap of the TiO₂ NRs remained consistent around 3.06 eV, with only slight variations observed. This study highlights the critical role of reaction time in hydrothermal synthesis, identifying 4 hours as the optimal duration for producing TiO₂ NRs with superior photoelectrochemical performance. These findings provide valuable insights for optimizing TiO₂-based materials for solar energy conversion and renewable energy applications.

Keywords: titanium dioxide, nanorods, hydrothermal, photocatalytic, photoelectrochemical

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