Search results for: long range correlations

Authors: Jyothi P. Phatak, L. Venkatesha, C. S. Raviprasad

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The performance improvement of Hybrid Energy Storage System (HESS) in Electric Vehicle (EV) has been in discussion over the last decade. The important issues in terms of performance parameters addressed are, range of vehicle and battery (BA) peak current. Published literature has either addressed battery peak current reduction or range improvement in EV. Both the issues have not been specifically discussed and analyzed. This paper deals with both range improvement in EV and battery peak current reduction by applying a new Karnaugh Map (K-Map) constructed rule based energy management strategy to proposed HESS. The strategy allows Ultracapacitor (UC) to assist battery when the vehicle accelerates there by reducing the burden on battery. Simulation is carried out for various operating modes of EV considering both urban and highway driving conditions. Simulation is done for different values of UC by keeping battery rating constant for each driving cycle and results are presented. Feasible value of UC is selected based on simulation results. The results of proposed HESS show an improvement in performance parameters compared to Battery only Energy Storage System (BESS). Battery life is improved to considerable extent and there is an overall development in the performance of electric vehicle.

Keywords: electric vehicle, PID controller, energy management strategy, range, battery current, ultracapacitor

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Authors: Liangliang Tang, Chang Xu, Xingying Chen

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GaInAsSb cells probably show better performance than GaSb cells in low-temperature thermophotovoltaic systems due to lower bandgap; however, few experiments proved this phenomenon so far. In this paper, numerical simulation is used to evaluate GaInAsSb and GaSb cells with similar structures under different radiation temperatures. We found that GaInAsSb cells with n-type emitters show slightly higher output power densities compared with that of GaSb cells with n-type emitters below 1,550 K-blackbody radiation, and the power density of the later cells will suppress the formers above this temperature point. During the temperature range of 1,000~2,000 K, the efficiencies of GaSb cells are about twice of GaInAsSb cells if perfect filters are used to prevent the emission of the non-absorbed long wavelength photons. Several parameters that affect the GaInAsSb cell were analyzed, such as doping profiles, thicknesses of GaInAsSb epitaxial layer and surface recombination velocity. The non-p junctions, i.e., n-type emitters are better for GaInAsSb cell fabrication, which is similar to that of GaSb cells.

Keywords: thermophotovoltaic cell, GaSb, GaInAsSb, diffused emitters

Procedia PDF Downloads 275

Authors: Riyas Peringattuthodiyil, Mark Taylor, Ian Wallace, Ailish Nugent, Mike Mitchell, Judith Thompson, Allison McKee, Philip C. Johnston

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Aim of Study: The purpose of the study was to screen for diabetes through HbA1c in patients with chronic pancreatitis (CP) within the Belfast Trust. Background: Patients with chronic pancreatitis are at risk of developing diabetes, earlier diagnosis with subsequent multi-disciplinary input has the potential to improve clinical outcomes. Methods: Clinical and laboratory data of patients with chronic pancreatitis were obtained through the Northern Ireland Electronic Healthcare Record (NIECR), specialist hepatobiliary, and gastrointestinal clinics. Patients were invited to have a blood test for HbA1c. Newly diagnosed patients with diabetes were then invited to attend a dedicated Belfast City Hospital (BCH) specialist chronic pancreatitis and diabetes clinic for follow up. Results: A total of 89 chronic pancreatitis patients were identified; Male54; Female:35, mean age 52 years, range 12-90 years. Aetiology of CP included alcohol 52/89 (58%), gallstones 18/89 (20%), idiopathic 10/89 11%, 2 were genetic, 1: post ECRP, 1: IgG autoimmune, 1: medication induced, 1: lipoprotein lipase deficiency 1: mumps, 1: IVDU and 1: pancreatic divisum. No patients had pancreatic carcinoma. Mean duration of CP was nine years, range 3-30 years. 15/89 (16%) of patients underwent previous pancreatic surgery/resections. Recent mean BMI was 25.1 range 14-40 kg/m². 62/89 (70%) patients had HbA1c performed. Mean HbA1c was 42 mmol/mol, range 27-97mmol/mol, 42/62 (68%) had normal HbA1c (< 42 mmol/mol) 13/62 (21%) had pre-diabetes (42-47mmol/mol) and 7/62 (11%) had diabetes (≥ 48 mmol/mol). Conclusions: Of those that participated in the screening program around one-third of patients with CP had glycaemic control in the pre and diabetic range. Potential opportunities for improving screening rates for diabetes in this cohort could include regular yearly testing at gastrointestinal and hepatobiliary clinics.

Keywords: pancreatogenic diabetes, screening, chronic pancreatitis, trust experience

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Authors: Aurora Cerri, Niko Pullojani

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Long-term differential settlement between the bridge structure and the bridge embankment typically results in an abrupt grade change, causing driver discomfort, impairing driver safety, and exerting a potentially excessive impact traffic loading on the abutment. This paper has analysed a case of study showing the effect of an approaching slab realized in a bridge constructed at Tirane-Elbasan Motorway. The layer thickness under the slab is modeled as homogenous, the slab is a reinforced concrete structure and over that the asphaltic layers take place. Analysis indicates that reinforced concrete approaching slab distributes the stresses quite uniformly into the road fill layers and settlements varies in a range less than 2.50 cm in the total slab length of 6.00 m with a maximum slope of 1/240. Results taken from analytical analysis are compared with topographic measurements done on field and they carry great similarities.

Keywords: approach slab, bridge, road pavement, differential settlement

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Authors: Jantakan Jullawateelert, Korakod Haonoo, Sutipong Sananseang, Sarun Torpaiboon, Thanunthon Bowornsakulwong, Lalintip Hocharoen

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Process scale-up is essential for the biological process to increase production capacity from bench-scale bioreactors to either pilot or commercial production. Scale-up based on constant volumetric oxygen mass transfer coefficient (KLa) is mostly used as a scale-up factor since oxygen supply is one of the key limiting factors for cell growth. However, to estimate KLa of culture vessels operated with different conditions are time-consuming since it is considerably influenced by a lot of factors. To overcome the issue, this study aimed to establish correlation equations of KLa and operating parameters in 0.5 L and 5 L bioreactor employed with pitched-blade impeller and gas sparger. Temperature, gas flow rate, agitation speed, and impeller position were selected as process parameters and equations were created using response surface methodology (RSM) based on central composite design (CCD). In addition, the effects of these parameters on KLa were also investigated. Based on RSM, second-order polynomial models for 0.5 L and 5 L bioreactor were obtained with an acceptable determination coefficient (R²) as 0.9736 and 0.9190, respectively. These models were validated, and experimental values showed differences less than 10% from the predicted values. Moreover, RSM revealed that gas flow rate is the most significant parameter while temperature and agitation speed were also found to greatly affect the KLa in both bioreactors. Nevertheless, impeller position was shown to influence KLa in only 5L system. To sum up, these modeled correlations can be used to accurately predict KLa within the specified range of process parameters of two different sizes of bioreactors for further scale-up application.

Keywords: response surface methodology, scale-up, stirred-tank bioreactor, volumetric oxygen mass transfer coefficient

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Authors: Shu-Jun Li, Cheng-Cao Sun, De-Jia Li

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Recently, long noncoding RNAs (lncRNAs) have been emerged as crucial regulators of human diseases and prognostic markers in numerous of cancers, including colorectal carcinoma (CRC). Here, we identified an oncogenetic lncRNA HULC, which may promote colorectal tumorigenesis. HULC has been found to be up-regulated and acts as oncogene in gastric cancer and hepatocellular carcinoma, but its expression pattern, biological function and underlying mechanism in CRC is still undetermined. Here, we reported that HULC expression is also over-expressed in CRC, and its increased level is associated with poor prognosis and shorter survival. Knockdown of HULC impaired CRC cells proliferation, migration and invasion, facilitated cell apoptosis in vitro, and inhibited tumorigenicity of CRC cells in vivo. Mechanistically, RNA immunoprecipitation (RIP) and RNA pull-down experiment demonstrated that HULC could simultaneously interact with EZH2 to repress underlying targets NKD2 transcription. In addition, rescue experiments determined that HULC oncogenic function is partly dependent on repressing NKD2. Taken together, our findings expound how HULC over-expression endows an oncogenic function in CRC.

Keywords: long noncoding RNA, HULC, NKD2, colorectal carcinoma, proliferation, apoptosis

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Authors: Soner Cubuk, Mirgul Kosif, M. Vezir Kahraman, Ece Kok Yetimoglu

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Boron is an essential trace element for the completion of the life circle for organisms. Suitable methods for the determination of boron have been proposed, including acid - base titrimetric, inductively coupled plasma emission spectroscopy flame atomic absorption and spectrophotometric. However, the above methods have some disadvantages such as long analysis times, requirement of corrosive media such as concentrated sulphuric acid and multi-step sample preparation requirements and time-consuming procedures. In this study, a selective and reusable fluorescent sensor for boron based on glycosyloxyethyl methacrylate was prepared by photopolymerization. The response characteristics such as response time, pH, linear range, limit of detection were systematically investigated. The excitation/emission maxima of the membrane were at 378/423 nm, respectively. The approximate response time was measured as 50 sec. In addition, sensor had a very low limit of detection which was 0.3 ppb. The sensor was successfully used for the determination of boron in water samples with satisfactory results.

Keywords: boron, fluorescence, photopolymerization, polymeric sensor

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Authors: Jonathan Olusegun Famoroti, Mathew Ekundayo Rotimi, Mishelle Doorasamy

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This study offers an empirical investigation into some selected macroeconomic drivers of the monetary policy rate in member countries of the West African Monetary Zone (WAMZ), considering both internal and external variables. We employed Autoregressive Distributed Lag (ARDL) to carry out the investigation between monetary policy and some macroeconomic variables in both the long-run and short-run relationship. The results suggest that the drivers of the policy rate in this zone, in the long run, include, among others, global oil price, exchange rate, inflation rate, and gross domestic product, while in the short run, federal fund rate, trade openness, exchange rate, inflation rate, and gross domestic product are core determinants of the policy rate. Therefore, in order to ensure long-run stability in the policy rate among the members’ states, these drivers should be given closer consideration so that the trajectory for effective structure can be designed and fused into the economic structure and policy frameworks accordingly.

Keywords: monetary policy rate, macroeconomic variables, WAMZ, ARDL

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Authors: Qihang Zeng, Wei Xu, Ying Shen, Changyuan Yu

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In this paper, a highly sensitive fiber-optic curvature sensor based on four mode fiber (FMF) is presented and investigated. The proposed sensing structure is constructed by fusing a section of FMF into two standard single mode fibers (SMFs) concatenated with two no core fiber (NCF), i.e., SMF-NCF-FMF-NCF-SMF structure is fabricated. The length of the NCF is very short about 1 millimeter acting as exciting/recoupling the light from/into the core of the SMF, while the FMF is with 3 centimeters long supporting four eigenmodes including LP₀₁, LP₁₁, LP₂₁ and LP₀₂. High core modes in FMF can be effectively stimulated owing to mismatched mode field distribution and the mainly sensing principle is based on modal interferometer spectrum analysis. Different curvatures induce different strains on the FMF such that affecting the modal excitation, resulting spectrum shifts. One can get the curvature value by tracking the wavelength shifting. Experiments have been done to address the sensing performance, which is about 7.8 nm/m⁻¹ within a range of 1.90 m⁻¹~3.18 m⁻¹.

Keywords: curvature, four mode fiber, highly sensitive, modal interferometer

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Authors: Elham Koohikerade, Silvio Jose Gumiere

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In this research, irrigation is highlighted as crucial for improving both the yield and quality of ‎potatoes due to their high sensitivity to soil moisture changes. The study presents a hybrid Long ‎Short-Term Memory (LSTM) model aimed at optimizing irrigation scheduling in potato fields in ‎Quebec City, Canada. This model integrates model-based and satellite-derived datasets to simulate ‎soil moisture content, addressing the limitations of field data. Developed under the guidance of the ‎Food and Agriculture Organization (FAO), the simulation approach compensates for the lack of direct ‎soil sensor data, enhancing the LSTM model's predictions. The model was calibrated using indices ‎like Surface Soil Moisture (SSM), Normalized Vegetation Difference Index (NDVI), Enhanced ‎Vegetation Index (EVI), and Normalized Multi-band Drought Index (NMDI) to effectively forecast ‎soil moisture reductions. Understanding soil moisture and plant development is crucial for assessing ‎drought conditions and determining irrigation needs. This study validated the spectral characteristics ‎of vegetation and soil using ECMWF Reanalysis v5 (ERA5) and Moderate Resolution Imaging ‎Spectrometer (MODIS) data from 2019 to 2023, collected from agricultural areas in Dolbeau and ‎Peribonka, Quebec. Parameters such as surface volumetric soil moisture (0-7 cm), NDVI, EVI, and ‎NMDI were extracted from these images. A regional four-year dataset of soil and vegetation moisture ‎was developed using a machine learning approach combining model-based and satellite-based ‎datasets. The LSTM model predicts soil moisture dynamics hourly across different locations and ‎times, with its accuracy verified through cross-validation and comparison with existing soil moisture ‎datasets. The model effectively captures temporal dynamics, making it valuable for applications ‎requiring soil moisture monitoring over time, such as anomaly detection and memory analysis. By ‎identifying typical peak soil moisture values and observing distribution shapes, irrigation can be ‎scheduled to maintain soil moisture within Volumetric Soil Moisture (VSM) values of 0.25 to 0.30 ‎m²/m², avoiding under and over-watering. The strong correlations between parcels suggest that a ‎uniform irrigation strategy might be effective across multiple parcels, with adjustments based on ‎specific parcel characteristics and historical data trends. The application of the LSTM model to ‎predict soil moisture and vegetation indices yielded mixed results. While the model effectively ‎captures the central tendency and temporal dynamics of soil moisture, it struggles with accurately ‎predicting EVI, NDVI, and NMDI.‎

Keywords: irrigation scheduling, LSTM neural network, remotely sensed indices, soil and vegetation ‎monitoring

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Authors: Beata Wentura-Dudek

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In Sweden the needs of the labor market are regularly monitored. Test results and forecasts translate directly into the education system in this country, which is largely a state system. Sweden is one of the first countries in Europe that has used active labor market policies. It is realized that there is an active unemployment which includes a wide range of activities that can be divided into three groups: Active forms of influencing the creation of new jobs, active forms that affect the labor supply and active forms for people with disabilities. Most of the funding is allocated there for subsidized employment and training. Research conducted in Sweden shows that active forms of counteracting unemployment focused on the long-term unemployed can significantly raise the level of employment in this group.

Keywords: Sweden, research conducted in Sweden, labour market, labour market policies, unemployment, active forms of influencing the creation of new jobs, active forms of counteracting unemployment, employment, subsidized employment education

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Authors: Jinhoa Lee

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The relationships between environmental quality, energy use and economic output have created growing attention over the past decades among researchers and policy makers. Focusing on the empirical aspects of the role of carbon dioxide (CO2) emissions and energy use in affecting the economic output, this paper is an effort to fulfill the gap in a comprehensive case study at a country level using modern econometric techniques. To achieve the goal, this country-specific study examines the short-run and long-run relationships among energy consumption (using disaggregated energy sources: crude oil, coal, natural gas, electricity), CO2 emissions and gross domestic product (GDP) for Egypt using time series analysis from the year 1980-2010. To investigate the relationships between the variables, this paper employs the Augmented Dickey-Fuller (ADF) test for stationarity, Johansen maximum likelihood method for co-integration and a Vector Error Correction Model (VECM) for both short- and long-run causality among the research variables for the sample. The long-run equilibrium in the VECM suggests some negative impacts of the CO2 emissions and the coal and natural gas use on the GDP. Conversely, a positive long-run causality from the electricity consumption to the GDP is found to be significant in Egypt during the period. In the short-run, some positive unidirectional causalities exist, running from the coal consumption to the GDP, and the CO2 emissions and the natural gas use. Further, the GDP and the electricity use are positively influenced by the consumption of petroleum products and the direct combustion of crude oil. Overall, the results support arguments that there are relationships among environmental quality, energy use, and economic output in both the short term and long term; however, the effects may differ due to the sources of energy, such as in the case of Egypt for the period of 1980-2010.

Keywords: CO2 emissions, Egypt, energy consumption, GDP, time series analysis

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Authors: Sofia Mylona, Dale Hume

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The main scope of this work is to compare the experimental thermal conductivity results of fluids between devices using transient techniques. A range of different liquids within a range of viscosities was measured with two or more devices, and the results were compared between the different methods and the reference equations wherever it was available. The liquids selected are the most commonly used in academic or industrial laboratories to calibrate their thermal conductivity instruments having a variety of thermal conductivity, viscosity, and density. Three transient methods (Transient Hot Wire, Transient Plane Source, and Transient Line Source) were compared for the thermal conductivity measurements taken by using them. These methods have been chosen as the most accurate and because they all follow the same idea; as a function of the logarithm of time, the thermal conductivity is calculated from the slope of a plot of sensor temperature rise. For all measurements, the selected temperature range was at the atmospheric level from 10 to 40 ° C. Our results are coming with an agreement with the objections of several scientists over the reliability of the results of a few popular devices. The observation was surprising that the device used in many laboratories for fast measurements of liquid thermal conductivity display deviations of 500 percent which can be very poorly reproduced.

Keywords: accurate data, liquids, thermal conductivity, transient methods.

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Authors: Jianhong Xiang, Hao Xiang, Linyu Wang

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Compressed sensing (CS) has a wide range of applications in sparse signal reconstruction. Aiming at the problems of low recovery accuracy and long reconstruction time of existing reconstruction algorithms in medical imaging, this paper proposes a corrected smoothing L0 algorithm based on compressed sensing (CSL0). First, an approximate hyperbolic tangent function (AHTF) that is more similar to the L0 norm is proposed to approximate the L0 norm. Secondly, in view of the "sawtooth phenomenon" in the steepest descent method and the problem of sensitivity to the initial value selection in the modified Newton method, the use of the steepest descent method and the modified Newton method are jointly optimized to improve the reconstruction accuracy. Finally, the CSL0 algorithm is simulated on various images. The results show that the algorithm proposed in this paper improves the reconstruction accuracy of the test image by 0-0. 98dB.

Keywords: smoothed L0, compressed sensing, image processing, sparse reconstruction

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Authors: Dilip K. Paul

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The most popular mesoporous molecular sieves, Mobil Composition of Matter (MCM) are keenly studied by researchers because of these materials possess amorphous silica wall and have a long range of ordered framework with uniform mesopores. These materials also possess large surface area, which can be up to more than 1000 m2g−1. Herein the investigation is focused upon the synthesis and characterization of chromium and aluminum doped MCM-41 using XRD and FTIR. Acid-base properties of Cr-Al-MCM 41 was investigated by molecularly sensitive transmission FT-IR spectroscopy by adsorbing pyridine. In addition, these MCM nanomaterial was used to catalyze C-C bond formation from acetaldehyde adsorption. The assignment of all infrared peaks during adsorption of pyridine provided detail information on the presence of acid-base sites which in turn helped us to explain the roles of these in the condensation reaction of aldehyde. Reaction mechanisms of C-C bond formation is therefore explored to shed some light on this elusive reaction detail.

Keywords: mesoporous nanomaterial, MCM 41, FTIR studies, acid-base studies

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Authors: B. Sabayan, A. Alidadi, S. Ebrahimi, N. M. Bakhshani

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Neuropsychological problems are more common in hemodialysis (HD) patients than in healthy individuals. The aim of this study was to investigate the effect of long term HD on memory types of HD patients. To assess the different type of memory, we used memory parts of the Persian Papers and Pencil Cognitive assessment package (PCAP) and Addenbrooke's Cognitive Examination (ACE-R). Our study included 80 HD patients of whom 39 had less than six months of HD and 41 patients and another group which had a history of HD more than six months. The population had a mean age of 51.60 years old and 27.5% of them were female. The scores of patients who have been hemodialyzed for a long time (median time of HD was up to 4 years) had lower score in anterograde, explicit, visual, recall and recognition memory (5.44±1.07, 9.49±3.472, 22.805±6.6913, 5.59±10.435, 11.02±3.190 score) than the HD patients who underwent HD for a shorter term, where the median time was 3 to 5 months (P<0.01). The regression result shows that, by increasing the HD duration, all memory types are reduced (R2=0.600, P<0.01). The present study demonstrated that HD patients who were under HD for a long time had significantly lower scores in the different types of memory. However, additional researches are needed in this area.

Keywords: hemodialysis patients, duration of hemodialysis, memory types, Zahedan

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Authors: Susan Mwai, Mary Muchane, Peter Wachira, Sheila Okoth, Muchai Muchane, Halima Saado

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Tropical forests harbor a wide range of biodiversity and rich macro-fungi diversity compared to the temperate regions in the World. However, biodiversity is facing the threat of extinction following the rate of forest loss taking place before proper study and documentation of macrofungi is achieved. The present study was undertaken to determine the effect of converting indigenous habitat to plantation forest on macrofungi diversity. To achieve the objective of this study, an inventory focusing on macro-fungi diversity was conducted within Kereita block in Kikuyu Escarpment forest which is on the southern side of Aberdare mountain range. The macrofungi diversity was conducted in the indigenous forest and in more than 15 year old Patula plantation forest , during the wet (long rain season, December 2014) and dry (Short rain season, May, 2015). In each forest type, 15 permanent (20m x 20m) sampling plots distributed across three (3) forest blocks were used. Both field and laboratory methods involved recording abundance of fruiting bodies, taxonomic identity of species and analysis of diversity indices and measures in terms of species richness, density and diversity. R statistical program was used to analyze for species diversity and Canoco 4.5 software for species composition. A total number of 76 genera in 28 families and 224 species were encountered in both forest types. The most represented taxa belonged to the Agaricaceae (16%), Polyporaceae (12%), Marasmiaceae, Mycenaceae (7%) families respectively. Most of the recorded macro-fungi were saprophytic, mostly colonizing the litter 38% and wood 34% based substrates, which was followed by soil organic dwelling species (17%). Ecto-mycorrhiza fungi (5%) and parasitic fungi (2%) were the least encountered. The data established that indigenous forests (native ecosystems) hosts a wide range of macrofungi assemblage in terms of density (2.6 individual fruit bodies / m2), species richness (8.3 species / plot) and species diversity (1.49/ plot level) compared to the plantation forest. The Conversion of native forest to plantation forest also interfered with species composition though did not alter species diversity. Seasonality was also shown to significantly affect the diversity of macro-fungi and 61% of the total species being present during the wet season. Based on the present findings, forested ecosystems in Kenya hold diverse macro-fungi community which warrants conservation measures.

Keywords: diversity, Indigenous forest, macro-fungi, plantation forest, season

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Authors: Jeh Patel, Chandrahas Paidi, Ahmed Hambaba

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Traditional methods for analyzing athlete movement often lack the detail and immediacy required for optimal training. This project aims to address this limitation by developing a Real-time human pose estimation system specifically designed to enhance athlete training across various sports. This system leverages the power of convolutional neural networks (CNNs) to provide a comprehensive and immediate analysis of an athlete’s movement patterns during training sessions. The core architecture utilizes dilated convolutions to capture crucial long-range dependencies within video frames. Combining this with the robust encoder-decoder architecture to further refine pose estimation accuracy. This capability is essential for precise joint localization across the diverse range of athletic poses encountered in different sports. Furthermore, by quantifying movement efficiency, power output, and range of motion, the system provides data-driven insights that can be used to optimize training programs. Pose estimation data analysis can also be used to develop personalized training plans that target specific weaknesses identified in an athlete’s movement patterns. To overcome the limitations posed by outdoor environments, the project employs strategies such as multi-camera configurations or depth sensing techniques. These approaches can enhance pose estimation accuracy in challenging lighting and occlusion scenarios, where pose estimation accuracy in challenging lighting and occlusion scenarios. A dataset is collected From the labs of Martin Luther King at San Jose State University. The system is evaluated through a series of tests that measure its efficiency and accuracy in real-world scenarios. Results indicate a high level of precision in recognizing different poses, substantiating the potential of this technology in practical applications. Challenges such as enhancing the system’s ability to operate in varied environmental conditions and further expanding the dataset for training were identified and discussed. Future work will refine the model’s adaptability and incorporate haptic feedback to enhance the interactivity and richness of the user experience. This project demonstrates the feasibility of an advanced pose detection model and lays the groundwork for future innovations in assistive enhancement technologies.

Keywords: computer vision, deep learning, human pose estimation, U-NET, CNN

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Authors: Leena-Maria Alyedreessy

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Self-esteem is thought to be determined by ones’ own feeling of being included, liked and accepted by others. This research explores whether this concept may also be applied in the virtual world and assesses whether there is any relationship between Twitter users' self-esteem and the amount of interactions they receive. 20 female Arab participants were given a survey asking them about their Twitter interactions and their feelings of having an imagined audience to fill out and a Rosenberg Self-Esteem Assessment to complete. After completion and statistical analysis, results showed a significant correlation between the feeling of being Twitter elite, the feeling of having a lot of people listening to your tweets and having a lot of interactions with high self-esteem. However, no correlations were detected for low-self-esteem and low interactions.

Keywords: twitter, social media, self-esteem, narcissism, interactions

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Authors: Changhong Guo, Shaomei Fang, Yong He

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In this paper, fractional Black-Scholes models for the European option pricing were established based on the fractional G-Brownian motion (fGBm), which generalizes the concepts of the classical Brownian motion, fractional Brownian motion and the G-Brownian motion, and that can be used to be a tool for considering the long range dependence and uncertain volatility for the financial markets simultaneously. A generalized fractional Black-Scholes equation (FBSE) was derived by using the Taylor’s series of fractional order and the theory of absence of arbitrage. Finally, some explicit option pricing formulas for the European call option and put option under the FBSE were also solved, which extended the classical option pricing formulas given by F. Black and M. Scholes.

Keywords: European option pricing, fractional Black-Scholes equations, fractional g-Brownian motion, Taylor's series of fractional order, uncertain volatility

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Authors: Nushrat Khan, Mike Thelwall, Kayvan Kousha

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Making research data openly accessible has been mandated by most funders over the last 5 years as it promotes reproducibility in science and reduces duplication of effort to collect the same data. There are evidence that articles that publicly share research data have higher citation rates in biological and social sciences. However, how and whether shared data is being reused is not always intuitive as such information is not easily accessible from the majority of research data repositories. This study aims to understand the practice of data citation and how data is being reused over the years focusing on biodiversity since research data is frequently reused in this field. Metadata of 38,878 datasets including citation counts were collected through the Global Biodiversity Information Facility (GBIF) API for this purpose. GBIF was used as a data source since it provides citation count for datasets, not a commonly available feature for most repositories. Analysis of dataset types, citation counts, creation and update time of datasets suggests that citation rate varies for different types of datasets, where occurrence datasets that have more granular information have higher citation rates than checklist and metadata-only datasets. Another finding is that biodiversity datasets on GBIF are frequently updated, which is unique to this field. Majority of the datasets from the earliest year of 2007 were updated after 11 years, with no dataset that was not updated since creation. For each year between 2007 and 2017, we compared the correlations between update time and citation rate of four different types of datasets. While recent datasets do not show any correlations, 3 to 4 years old datasets show weak correlation where datasets that were updated more recently received high citations. The results are suggestive that it takes several years to cumulate citations for research datasets. However, this investigation found that when searched on Google Scholar or Scopus databases for the same datasets, the number of citations is often not the same as GBIF. Hence future aim is to further explore the citation count system adopted by GBIF to evaluate its reliability and whether it can be applicable to other fields of studies as well.

Keywords: data citation, data reuse, research data sharing, webometrics

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Authors: Gao Youtao, Zhao Tanran, Jin Bingyu, Xu Bo

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Global navigation satellite system(GNSS) can deliver navigation information for spacecraft orbiting on low-Earth orbits and medium Earth orbits. However, the GNSS cannot navigate the spacecraft on high-Earth orbit or deep space probes effectively. With the deep space exploration becoming a hot spot of aerospace, the demand for a deep space satellite navigation system is becoming increasingly prominent. Many researchers discussed the feasibility and performance of a satellite navigation system on periodic orbits around the Earth-Moon libration points which can be called Lagrangian point satellite navigation system. Autonomous orbit determination (AOD) is an important performance for the Lagrangian point satellite navigation system. With this ability, the Lagrangian point satellite navigation system can reduce the dependency on ground stations. AOD also can greatly reduce total system cost and assure mission continuity. As the elliptical restricted three-body problem can describe the Earth-Moon system more accurately than the circular restricted three-body problem, we study the autonomous orbit determination of Lagrangian navigation constellation using only crosslink range based on elliptical restricted three body problem. Extended Kalman filter is used in the autonomous orbit determination. In order to compare the autonomous orbit determination results based on elliptical restricted three-body problem to the results of autonomous orbit determination based on circular restricted three-body problem, we give the autonomous orbit determination position errors of a navigation constellation include four satellites based on the circular restricted three-body problem. The simulation result shows that the Lagrangian navigation constellation can achieve long-term precise autonomous orbit determination using only crosslink range. In addition, the type of the libration point orbit will influence the autonomous orbit determination accuracy.

Keywords: extended Kalman filter, autonomous orbit determination, quasi-periodic orbit, navigation constellation

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Authors: Yuyun Sri Wahyuni, Fathih Misbahuddin Islam

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Nanggroe Aceh Darussalam is the special district with its long conflict history. The long conflict history started from The Free Aceh Movement’s intentions to implement Islamic principles in Aceh Province, it was actually contradicted with the principles of state. This long conflict was finally ended on 2005. Then, since 2005 Aceh had special authority to administer its local government affairs by applying Islamic principles (syariah), included criminal law matters. To administer it, Aceh Government enacted Law Number 6 of 2014 on the Jinayah. This law consists the criminal act (jarimah) and the punishment (uqubat). Khamr, maisir, khalwat, ikhtilath, zina, sexual harrasment, rape, qadzaf, liwath, and musahaqah are the kinds of the criminal act which are ruled within. Meanwhile, Hudud and Takdzir as the kinds of punishment (uqubat). After 2 years of the issuance of this law inflicting controversy from any sides and being discussed not only locally but also globally. The objectives of this paper are to analyze the fundamental value of the flagellation punishment within this law and Aceh Government review in formulating the law.

Keywords: Aceh province, flagellation punishment, Islamic Principle, Qanun Jinayah

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Authors: F. Zouai, F. Z. Benabid, S. Bouhelal, D. Benachour

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A new route of preparation of compatible blends, based on poly(ethylene terephthalate)(PET)/poly(ethylenenaphthalene2,6-dicarboxylate) (PEN)/clay nanocomposites has been successfully performed in one step by reactive melt extrusion. To achieve this, untreated clay was first purified and functionalized “in situ” with a compound based on an organic peroxide/sulfur mixture and (tetra methyl thiuram disulfide) TMTD as accelerator or activator for sulfur. The PET and PEN materials were first mixed separately in the melt state with different amounts of functionalized clay. It was observed that the compositions PET/4 wt% clay and PEN/7.5 wt% clay showed total exfoliation. These completely exfoliated compositions, called nPET and nPEN, respectively, were used to prepare new nPET/nPEN nanoblends in the same mixing batch. The nPET/nPEN nanoblends were compared to neat blends of PET/PEN. The blends and the nanocomposites were characterized by different techniques: differential scanning calorimetry (DSC) and wide-angle X-ray scattering (WAXS). The micro and nanostructure/properties relationships were investigated. The results of the WAXS measurements study showed that the exfoliation of tetrahedral nanolayers of clay was complete and the octahedral structure disappeared totally. From the different WAXS patterns, it is seen that all samples are amorphous phase. The thermal study showed that there are only one glass transition temperature Tg, one crystallization temperature Tc and one melting temperature Tm for every composition. This indicated that both PET/PEN blends and nPET/nPEN blends were compatible in the entire range of compositions. In addition, nPET/nPEN blends present lower Tc values and higher Tm values than the corresponding neat PET/PEN blends. The obtained results indicate that nPET/nPEN blends are somewhat different from the pure ones in nanostructure and behavior, thus showing the additional effect of nanolayers. The present study allowed establishing good correlations between the different measured properties.

Keywords: PET, PEN, montmorillonite, nanocomposites, exfoliation, reactive melt-mixing

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Authors: Bikis Muhammed, Sehra Sedigh Sarvestani, Ali R. Hurson, Lasanthi Gamage

Abstract:

Vehicular traffic events have overly complex spatial correlations and temporal interdependencies and are also influenced by environmental events such as weather conditions. To capture these spatial and temporal interdependencies and make more realistic vehicular traffic predictions, graph neural networks (GNN) based traffic prediction models have been extensively utilized due to their capability of capturing non-Euclidean spatial correlation very effectively. However, most of the already existing GNN-based traffic prediction models have some limitations during learning complex and dynamic spatial and temporal patterns due to the following missing factors. First, most GNN-based traffic prediction models have used static distance or sometimes haversine distance mechanisms between spatially separated traffic observations to estimate spatial correlation. Secondly, most GNN-based traffic prediction models have not incorporated environmental events that have a major impact on the normal traffic states. Finally, most of the GNN-based models did not use an attention mechanism to focus on only important traffic observations. The objective of this paper is to study and make real-time vehicular traffic predictions while incorporating the effect of weather conditions. To fill the previously mentioned gaps, our prediction model uses a real-time driving distance between sensors to build a distance matrix or spatial adjacency matrix and capture spatial correlation. In addition, our prediction model considers the effect of six types of weather conditions and has an attention mechanism in both spatial and temporal data aggregation. Our prediction model efficiently captures the spatial and temporal correlation between traffic events, and it relies on the graph attention network (GAT) and Bidirectional bidirectional long short-term memory (Bi-LSTM) plus attention layers and is called GAT-BILSTMA.

Keywords: deep learning, real time prediction, GAT, Bi-LSTM, attention

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Authors: Vivian Wu

Abstract:

During the mating season, honeybee drones make mating fights to congregation areas where they face fierce competition to mate with a queen. Drones have developed distinct anatomical and functional features in order to optimize their chances of success. Flight activities of western honeybee (Apis mellifera) drones and foragers were monitored using radio frequency identification (RFID) to test if drones have also developed distinct flight behaviors. Drone flight durations showed a bimodal distribution dividing the flights into short flights and long flights while forager flight durations showed a left-skewed unimodal distribution. Interestingly, the short trips occurred prior to the long trips on a daily basis. The first trips of the day the drones made were primarily short trips, and the distribution significantly shifted to long trips as the drones made more trips. In contrast, forager trips showed no such shift of distribution. In addition, drones made short trips but no long mating trips on days associated with a significant drop in temperature and increase of clouds compared to the previous day. These findings suggest that drones may have developed a unique flight behavior making short trips first to survey the weather conditions before flying out to the congregation area to pursue a successful mating.

Keywords: apis mellifera, drone, flight behavior, weather, RFID

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Authors: Uchenna Egwu, Paul Jonathan Sallis

Abstract:

Perennial ryegrass is an abundant renewable lignocellulosic biofuel feedstock for biomethane production through anaerobic digestion (AD). In this study, six anaerobic continuously stirred tank reactors (CSTRs) were set up in three pairs. Each pair of the CSTRs was then used to study the effects of operating temperatures – psychrophilic, mesophilic, and thermophilic, and optimum pH on the specific methane production (SMP) of the ryegrass during AD under discontinuous daily feeding conditions. The reactors were fed at an organic loading rate (OLR) ranging from 1-1.5 kgVS.L⁻¹d⁻¹ and hydraulic residence time, HRT=20 days for 140 days. The pH of the digesters was maintained at the range of 6.8-7.2 using 1 M NH₄HCO₃ solution, but this was replaced with biomass ash-extracts from day 105-140. The results obtained showed that the mean SMP of ryegrass measured between HRT 3 and 4 were 318.4, 425.4 and 335 N L CH₄ kg⁻¹VS.d⁻¹ for the psychrophilic (25 ± 2°C), mesophilic (40 ± 1°C) and thermophilic (60 ± 1°C) temperatures respectively. It was also observed that the buffering ability of the reactors increased with operating temperature, probably due to an increase in the solubility of ammonium bicarbonate (NH₄HCO₃) with temperature. The reactors also achieved a mean VS destruction of 61.9, 68.5 and 63.5%, respectively, which signifies that the mesophilic reactors achieved the highest specific methane production (SMP), while the psychrophilic reactors achieved the lowest. None of the reactors attained steady-state condition due to the discontinuous daily feeding times, and therefore, such feeding practice may not be the most effective for maximum biogas production over long periods of time. The addition of NH₄HCO₃ as supplement provided a good buffering condition in these AD digesters, but the digesters failed in the long run due to inhibition from the accumulation of free ammonia, which later led to decrease in pH, acidification, and souring of the digesters. However, the addition of biomass ash extracts was shown to potentially revive failed AD reactors by providing an adequate buffering and essential trace nutrient supplements necessary for optimal bacterial growth.

Keywords: anaerobic digestion, discontinuous feeding, perennial ryegrass, specific methane production, supplements, temperature

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Authors: Mohammad Maruf Hasan

Abstract:

Foreign Direct Investment (FDI) has been increased at a remarkable position around the globe in which emerging economies are getting more FDI compared to industrialized economies. This study aims to examine the determinants of inward FDI flows in Bangladesh. To estimate the long and short-run impact of the FDI determinants for 1996-2020, we employed the Autoregressive-Distributed Lag (ARDL) model. Results show that: (1) macroeconomic determinants, such as economic growth, infrastructure, and market size, have a significant and strong positive effect.(2) Inflation exchange rate shows insignificant effects, while trade openness has mixed (short-run negative, long-run positive) effects on FDI inflows in both the long and short run. (3) Current institutional determinants rule of law has a positive effect on FDI inflows but is statistically insignificant, political stability has a negative, and the rule of law has a considerable beneficial impact on inflows of FDI. (4) The macroeconomic factors have been determined to impact Bangladesh's FDI inflows. Finally, a stable macroeconomic climate is more effective at luring FDI, as this study confirms. From a policy perspective, this study will help the government and policymakers to make a new investment policy.

Keywords: determinants, FDI, ARDL, Bangladesh

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Authors: Hee-Young Song

Abstract:

Background and objectives: In 2011, the Global Initiative for Chronic Obstructive Lung Disease (GOLD) recommendations proposed a multidimensional assessment of patients’ conditions that included both functional parameters and patient-reported outcomes, with the aim to provide a comprehensive assessment of the disease, thus meeting both the needs of the patient and the role of the physician. However, few studies have evaluated patient-reported outcomes as well as objective functional assessments among individuals with chronic obstructive pulmonary disease (COPD) in clinical practice in Korea. This study was undertaken to explore the relationship between functional status assessed by the 6-minute walking distance (MWD) test and subjective health status reported by stable patients with COPD residing in community. Methods: A cross-sectional descriptive study was conducted with 118 stable COPD patients aged 69.4 years old and selected by a convenient sampling from an outpatient department of pulmonology in a tertiaryhospitals. The 6-MWD test was conducted according to standardized instructions. Participants also completed a constructed questionnaire including general characteristics, smoking history, dyspnea by modified medical research council (mMRC) scale, and health status by COPD assessment test (CAT). Anthropometric measurements were performed for body mass index (BMI). Medical records were reviewed to obtain disease-related characteristics including duration of the disease and forced expiratory volume in 1 second (FEV1). Data were analyzed using PASW statistics 20.0. Results: Mean FEV1% of participants was 63.51% and mean 6-MWD and CAT scores were 297.54m and 17.7, respectively. The 6-MWD and CAT showed significant negative correlations (r= -.280, p=.002); FEV1 and CAT did as well correlations (r= -.347, p < .001). Conclusions: Findings suggest that the better functional status an individual with COPD has, the better subjective health status is, and provide the support for using patient-reported outcomes along with functional parameters to facilitate comprehensive assessment of COPD patients in real clinical practices.

Keywords: chronic obstructive pulmonary disease, COPD assessment test, functional status, patient-reported outcomes

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Authors: Syahira Ibrahim, Herlina Abdul Rahim

Abstract:

The amylose content is an essential element in determining the texture and taste of rice grains. This paper evaluates the use of VIS-SWNIRS in estimating the amylose content for seven varieties of rice grains available in the Malaysian market. Each type consists of 30 samples and all the samples are scanned using the spectroscopy to obtain a range of values between 680-1000nm. The Savitzky-Golay (SG) smoothing filter is applied to each sample’s data before the Principal Component Regression (PCR) technique is used to examine the data and produce a single value for each sample. This value is then compared with reference values obtained from the standard iodine colorimetric test in terms of its coefficient of determination, R2. Results show that this technique produced low R2 values of less than 0.50. In order to improve the result, the range should include a wavelength range of 1100-2500nm and the number of samples processed should also be increased.

Keywords: amylose content, diffuse reflectance, Malaysia rice grain, principal component regression (PCR), Visible and Shortwave near-infrared spectroscopy (VIS-SWNIRS)

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