Search results for: multi junction solar cells

Authors: Dake Xiong, Ben Hankamer, Ian Ross

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The most urgent challenge of our time is to replace the depleting resources of fossil fuels by sustainable environmentally friendly alternatives. Hydrogen is a promising CO2-neutral fuel for a more sustainable future especially when produced photo-biologically. Hydrogen can be photosynthetically produced in unicellular green alga like Chlamydomonas reinhardtii, catalysed by the inducible highly active and bidirectional [FeFe]-hydrogenase enzymes (HydA). However, evolutionary and physiological constraints severely restrict the hydrogen yield of algae for industrial scale-up, mainly due to its competition among other metabolic pathways on photosynthetic electrons. Among them, a major challenge to be resolved is the inferior competitiveness of hydrogen production (catalysed by HydA) with NADPH production (catalysed by ferredoxin-NADP+-reductase (FNR)), which is essential for cell growth and takes up ~95% of photosynthetic electrons. In this work, the in vivo hydrogen production efficiency of mutants with ferredoxin-hydrogenase (Fd*-HydA1*) fusion protein construct, where the electron donor ferredoxin (Fd*) is fused to HydA1* and expressed in the model organism C. reinhardtii was investigated. Once Fd*-HydA1* fusion gene is expressed in algal cells, the fusion enzyme is able to draw the redistributed photosynthetic electrons and use them for efficient hydrogen production. From preliminary data, mutants with Fd*-HydA1* transgene showed a ~2-fold increase in the photosynthetic hydrogen production rate compared with its parental strain, which only possesses the native HydA in vivo. Therefore, a solid method of having more efficient hydrogen production in microalgae can be achieved through the expression of the synthetic enzymes.

Keywords: Chlamydomonas reinhardtii, ferredoxin, fusion protein, hydrogen production, hydrogenase

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Authors: Hossein Nikandam Kermanshah, Babak Samavatian, Akbar Hemmati Sabet, Mohammad Ahmadpanah

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This is a quasi-experimental study that has been conducted in order to compare the effectiveness of social skills training and stress management training on self-esteem and aggression in first grade high school students. Forty-five people were selected from research community and were put randomly in there groups of social skills training, stress management training and control ones. Collecting data tools in this study was devise, self-esteem and AGQ aggression questionnaire. Self-esteem and aggression questionnaires has been conducted as the pre-test and post-test. Social skills training and stress management groups participated in eight 1.5 hour session in a week. But control group did not receive any therapy. For descriptive analysis of data, statistical indicators like mean, standard deviation were used, and in inferential statistics level multi variable covariance analysis have been used. The finding result show that group training social skills and stress management is significantly effective on the self-esteem and aggression, there is a meaningful difference between training social skills and stress management on self-esteem that the preference is with group social skills training, in the difference between group social skills training and stress management on aggression, the preference is with group stress management.

Keywords: social skill training, stress management training, self-esteem aggression, psychological sciences

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Authors: Parul Bhalla, Sarvesh Palria

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Wetlands are areas of land that are either temporarily or permanently covered by water. Wetlands exhibit enormous diversity according to their genesis, geographical location, water regime and chemistry, dominant plants and soil or sediment characteristics. The spatial and temporal characteristics of wetland in terms of turbidity and aquatic vegetation could serve as guiding tool, in conservation prioritization of wetlands. The aquatic vegetation in the wetland is an indicator of the trophic status of the wetland which has a bearing on the water quality, the turbidity level in any wetland is indicative of the quality of the water in it. To conserve and manage wetland resources, it is important to have inventory of wetland and its catchment. Fateh Sagar wetland in Udaipur city is the one of the important wetland for tourism industry and other economic activities in the region. Realizing the importance of the wetland, the present study has been taken up with the specific objective of delineation and characterization of Fateh Sagar wetland in terms of turbidity and aquatic vegetation, using high resolution satellite data such as Cartosat and LISS IV multi-temporal data, which will efficiently bring out the changes in water spread and quality parameters. The catchment of wetland has been also characterized for various features. The study leads in to takes necessary steps to conserve the wetland and its resources.

Keywords: aquatic vegetation, catchment, turbidity status, wetland

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Authors: Hye Kyung Kim, Myung-Gyou Kim, Kang-Hyun Leem

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The prickly pear cactus (Opuntia ficus-indica) has a global distribution and has been used for medicinal benefits such as artherosclerosis, diabetes, gastritis, and hyperglycemia. The prickly pear variety Opuntia ficus-indica var. Saboten (OFS) is widely cultivated in Cheju Island, the southwestern region of Korea, and used as a functional food. The present study investigated the effects of OFS on adipogenesis, lipolysis, glucose uptake, and glucose transporter (GLUT4) expression using preadipocyte 3T3-L1 cells. Adipogenesis was determined by preadipocyte differentiation and triglyceride accumulation assessed by Oil Red O staining. Lipolysis was determined as the rate of glycerol release. Insulin-stimulated glucose uptake and GLUT4 expression were measured using fluorescent glucose analogue, 2-NBDG, and ELISA, respectively. Quantitative real-time RT-PCR was performed to investigate the effects of OFS on the mRNA expression of peroxisome proliferator-activated receptor γ (PPARγ), a regulator of adipocyte differentiation. Ethanol extracts of OFS dose-dependently enhanced adipocyte differentiation and cellular triglyceride levels indicating the enhancement of the differentiation of preadipocytes into adipocytes. Insulin-stimulated glucose uptake and GLUT4 expression were also dose-dependently increased by OFS treatment. Furthermore, OFS treatment also increased the mRNA levels of PPARγ. These effects of OFS on adipocytes suggest that OFS is potentially beneficial for type 2 diabetes by due to its enhanced glucose uptake and balanced adipogenesis and lipolysis properties.

Keywords: 3T3-L1 preadipocyte cell, adipogenesis, GLUT4, lipolysis, Opuntia ficus-indica var. Saboten, PPARγ, prickly pear cactus

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Authors: Afifa Hafidh, Hedia Chaabane

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This work mainly focused on the synthetic strategies and biological activities associated with pyrazoles. Pyrazole derivatives have been successfully synthesized by simple and facile method and studied for their antibacterial activity. These compounds were prepared from pyrazolic difunctional compounds as starting materials, by reaction with salicylic acid, paracetamol and thiosemicarbazide respectively. Structure of all the prepared compounds confirmation were proved using (FT-IR), (1H-NMR) and (13C-NMR) spectra in addition to melting points. The screening of the antimicrobial activity of the pyrazolic derivatives was examined against different microorganisms in the present study. They were screened for their antimicrobial activities against gram positive bacteria, gram negative bacteria and Candida albicans. The synthesized compounds were found to exhibit high antibacterial and antifungal efficiency against several tested bacterial strains, using agar diffusion method and filter paper disc-diffusion method. Ampicillin was used as positive control for all strains except Candida albicans for which Nystatin was used. The obtained results reveal that the antibacterial activity of some pyrazolic derivatives is comparable to that observed for the control samples (Ampicilin and Nystatin), suggesting a strong antibacterial activity. The analysis of these results shows that synthesized products react on the surfaces cell walls that are disrupted. When these products are in contact with the bacteria, they damage the membrane, leading to the perturbation of different cellular processes and then leakage of cytoplasm, resulting in the death of the cells. The results will be presented in details. The obtained products constitute effective antibacterial agents and important compounds for biological systems.

Keywords: salicylic acid, antimicrobial activities, antioxidant activity, paracetamol, pyrazole, thiosemicarbazide

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Authors: Norah Al Hokbany, Ibrahim Al Jammaz, Basem Al Otaibi, Yousif Al Malki, Subhani M. Okarvi

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Objective: The folate receptor is over-expressed in a wide variety of human tumors. Conjugates of folate have been shown to be selectively taken up by tumor cells via the folate receptor. In an attempt to develop new folate radiotracers with favorable biochemical properties for detecting folate receptor-positive cancers. Methods: we synthesized ⁶⁴Cu-NOTA- and ⁶⁴Cu-NOTAM-folate conjugates using a straightforward and simple one-step reaction. Radiochemical yields were greater than 95% (decay-corrected) with a total synthesis time of less than 20 min. Results: Radiochemical purities were always greater than 98% without high-performance liquid chromatography (HPLC) purification. These synthetic approaches hold considerable promise as a rapid and simple method for ⁶⁴Cu-folate conjugate preparation with high radiochemical yield in a short synthesis time. In vitro tests on the KB cell line showed that significant amounts of the radio conjugates were associated with cell fractions. Bio-distribution studies in nude mice bearing human KB xenografts demonstrated a significant tumor uptake and favorable bio-distribution profile for ⁶⁴Cu-NOTA- and ⁶⁴Cu-NOTAM-folate conjugate. The uptake in the tumors was blocked by the excess injection of folic acid, suggesting a receptor-mediated process. Conclusion: These results demonstrate that the ⁶⁴Cu-NOTAM-folate conjugate may be useful as a molecular probe for the detection and staging of folate receptor-positive cancers, such as ovarian cancer and their metastasis, as well as monitoring tumor response to treatment.

Keywords: folate, receptor, tumor imaging, ⁶⁴Cu-NOTA-folate, PET

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Authors: Rong-Terng Juang

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Autonomous vehicles offer the possibility of significant benefits to social welfare. However, fully automated cars might not be going to happen in the near further. To speed the adoption of the self-driving technologies, many governments worldwide are passing laws requiring data recorders for the testing of autonomous vehicles. Currently, the self-driving vehicle, (e.g., shuttle bus) has to be monitored from a remote control center. When an autonomous vehicle encounters an unexpected driving environment, such as road construction or an obstruction, it should request assistance from a remote operator. Nevertheless, large amounts of data, including images, radar and lidar data, etc., have to be transmitted from the vehicle to the remote center. Therefore, this paper proposes a data compression method of in-vehicle networks for remote monitoring of autonomous vehicles. Firstly, the time-series data are rearranged into a multi-dimensional signal space. Upon the arrival, for controller area networks (CAN), the new data are mapped onto a time-data two-dimensional space associated with the specific CAN identity. Secondly, the data are sampled based on differential sampling. Finally, the whole set of data are encoded using existing algorithms such as Huffman, arithmetic and codebook encoding methods. To evaluate system performance, the proposed method was deployed on an in-house built autonomous vehicle. The testing results show that the amount of data can be reduced as much as 1/7 compared to the raw data.

Keywords: autonomous vehicle, data compression, remote monitoring, controller area networks (CAN), Lidar

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Authors: Bowei Yuan, Shi Li, Liuyang Song, Huaqing Wang, Lingli Cui

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Convolutional neural networks (CNN) have received extensive attention in the field of fault diagnosis. Many fault diagnosis methods use CNN for fault type identification. However, when the amount of raw data collected by sensors is massive, the neural network needs to perform a time-consuming classification task. In this paper, a mechanical fault diagnosis method based on vibration signal down-sampling and the improved one-dimensional convolutional neural network is proposed. Through the robust principal component analysis, the low-rank feature matrix of a large amount of raw data can be separated, and then down-sampling is realized to reduce the subsequent calculation amount. In the improved one-dimensional CNN, a smaller convolution kernel is used to reduce the number of parameters and computational complexity, and regularization is introduced before the fully connected layer to prevent overfitting. In addition, the multi-connected layers can better generalize classification results without cumbersome parameter adjustments. The effectiveness of the method is verified by monitoring the signal of the centrifugal pump test bench, and the average test accuracy is above 98%. When compared with the traditional deep belief network (DBN) and support vector machine (SVM) methods, this method has better performance.

Keywords: fault diagnosis, vibration signal down-sampling, 1D-CNN

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Authors: Anita Sadat Sadati Rostami, Reza Almasi Ghaleh

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Surface electromyography (sEMG) offers important insights into muscle activation and has applications in fields including rehabilitation and human-computer interaction. The purpose of this work is to predict the degree of activation of two joints in the index finger using an LSTM-Transformer architecture trained on sEMG data from the Ninapro DB8 dataset. We apply advanced preprocessing techniques, such as multi-band filtering and customizable rectification methods, to enhance the encoding of sEMG data into features that are beneficial for regression tasks. The processed data is converted into spike patterns and simulated using Leaky Integrate-and-Fire (LIF) neuron models, allowing for neuromorphic-inspired processing. Our findings demonstrate that adjusting filtering parameters and neuron dynamics and employing the LSTM-Transformer model improves joint angle prediction performance. This study contributes to the ongoing development of deep learning frameworks for sEMG analysis, which could lead to improvements in motor control systems.

Keywords: surface electromyography, LSTM-transformer, spiking neural networks, hand kinematics, leaky integrate-and-fire neuron, band-pass filtering, muscle activity decoding

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Authors: Endalamaw Ewnu Kassa, Ade Kurniawan, Ya-Fen Wu, Sajal Biring

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Perovskite-based gas sensors represent a highly promising materials within the realm of gas sensing technology, with a particular focus on detecting ammonia (NH3) due to its potential hazards. Our work conducted thorough comparison of various solvents, including dimethylformamide (DMF), DMF-dimethyl sulfoxide (DMSO), dimethylacetamide (DMAC), and DMAC-DMSO, for the preparation of our perovskite solution (MAPbI3). Significantly, we achieved an exceptional response at 10 ppm of ammonia gas by employing a binary solvent mixture of DMAC-DMSO. In contrast to prior reports that relied on single solvents for MAPbI3 precursor preparation, our approach using mixed solvents demonstrated a marked improvement in gas sensing performance. We attained enhanced surface coverage, a reduction in pinhole occurrences, and precise control over grain size in our perovskite films through the careful selection and mixtures of appropriate solvents. This study shows a promising potential of employing binary and multi-solvent mixture strategies as a means to propel advancements in gas sensor technology, opening up new opportunities for practical applications in environmental monitoring and industrial safety.

Keywords: sensors, binary solvents, ammonia, sensitivity, grain size, pinholes, surface coverage

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Authors: Mesfin Angaw Tesfay

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L-Xylulose is a potentially valuable rare sugar used as starting material for antiviral and anticancer drug development in pharmaceutical industries. L-Xylulose exist in a very low concentration in nature and have to be synthesized from cheap starting materials such as xylitol through biotechnological approaches. In this study, cofactor engineering and deep eutectic solvent were applied to improve the efficiency of L-xylulose production from xylitol. A water-forming NAD+ regeneration enzyme (NADH oxidase) from Streptococcus mutans ATCC 25175 was introduced into E. coli with xylitol-4-dehydrogenase (XDH) of Pantoea ananatis resulting in recombinant cells harboring the vector pETDuet-xdh-SmNox. Further, three deep eutectic solvents (DES) including, Choline chloride/glycerol (ChCl/G), Choline chloride/urea (ChCl/U), and Choline chloride/ethylene glycol (ChCl/EG) have been employed to facilitate the conversion efficiency of L-xylulose from xylitol. The co-expression system exhibited optimal activity at a temperature of 37 ℃ and pH 8.5, and the addition of Mg2+ enhanced the catalytic activity by 1.19-fold. Co-expression of NADH oxidase with XDH enzyme resulted in increased L-xylulose concentration and productivity from xylitol as well as the intracellular NAD+ concentration. Two of the DES used (ChCl/U and ChCl/EG) show positive effects on product yield and the ChCl/G has inhibiting effects. The optimum concentration of ChCl/U was 2.5%, which increased the L-xylulose yields compared to the control without DES. In a 1 L fermenter the final concentration and productivity of L-xylulose from 50 g/L of xylitol reached 48.45 g/L, and 2.42 g/L.h respectively, which was the highest report. Overall, this study is a suitable approach for large-scale production of L-xylulose from xylitol using the engineered E. coli cell.

Keywords: Xylitol-4-dehydrogenase, NADH oxidase, L-xylulose, Xylitol, Coexpression, DESs

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Authors: Eldar Mammadov, Konul Mammadova, Aytaj Ilyaszada

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Background: According to many studies, it is known that H. pylori transform into the coccoid form, which cannot be cultured and has poor metabolic activity.In this study, we succeeded in preserving the spiral shape of H.pylori for a long time by preparing a biphase transport medium with a hard bottom (Muller Hinton with 7% HRBC (horse red blood cells) agar 5ml) and liquid top part (BH (brain heart) broth + HS (horse serum)+7% HRBC+antibiotics (Vancomycin 5 mg, Trimethoprim lactate 25 mg, Polymyxin B 1250 I.U.)) in cell culture flasks with filter caps. For comparison, we also used a BH broth medium with 7% HRBC used for the transport of H.pylori. Methods: Rapid urease test positive 7 biopsy specimens were also inoculated into biphasic and BH broth medium with 7% HRBC, then put in CO2 Gaspak packages and sent to the laboratory. Then both mediums were kept in the thermostat at 37 °C for 1 day. After microscopic, PCR and urease test diagnosis, they were transferred to Columbia Agar with 7% HRBC. Incubated at 37°C for 5-7 days, cultures were examined for colony characteristics and bacterial morphology. E-test antimicrobial susceptibility test was performed. Results: There were 3 growths from biphasic transport medium passed to Columbia agar with 7% HRBC and only 1 growth from BH broth medium with 7% HRBC. It was also observed that after the first 3 days in BH broth medium with 7%, H.pylori passed into coccoid form and its biochemical activity weakened, while its spiral shape did not change for 2-3 weeks in the biphase transport medium. Conclusions: By using the biphase transport medium we have prepared; we can culture the bacterium by preventing H.pylori from spiraling into the coccoid form. In our opinion, this may result in the wide use of culture method for diagnosis of H.pylori, study of antibiotic susceptibility and molecular genetic analysis.

Keywords: clinical trial, H.pylori, coccoid form, transport medium

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Authors: Abdullah Mohammad, Abdullah Alshemali, Esmaeil Alsaleh

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The chemical composition of desalinated water is modified to make it more acceptable to the end-user. Sometimes, this modification is approached by mixing with brackish water that is known to contain a variety of minerals. Expectedly, besides minerals, brackish water indigenous bacterial communities access the final mixture hence reaching the end consumer. The current project examined the safety of using brackish water as an ingredient in potable water. Pseudomonas aeruginosa strains were detected in potable and brackish water samples collected from storage facilities in residential areas as well as from main water distribution and storage tanks. The application of molecular and biochemical fingerprinting methods, including phylogeny, RFLP (restriction fragment length polymorphism), MLST (multilocus sequence typing) and substrate specificity testing, suggested that the potable water P. aeruginosa strains were most probably originated from brackish water. Additionally, all the sixty-four isolates showed multi-drug resistance (MDR) phenotype and harboured the three genes responsible for biofilm formation. These virulence factors represent serious health hazards compelling the scientific community to revise the WHO (World Health Organization) and USEP (US Environmental Protection Agency) A potable water quality guidelines, particularly those related to the types of bacterial genera that evade the current water quality guidelines.

Keywords: potable water, brackish water, pseudomonas aeroginosa, multidrug resistance

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Authors: Pranav Gunhal., Krish Jhurani

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This study tackles the significant computational challenge of predicting excited state dynamics in organic photovoltaic (OPV) materials—a pivotal factor in the performance of solar energy solutions. Time-dependent density functional theory (TDDFT), though effective, is computationally prohibitive for larger and more complex molecules. As a solution, the research explores the application of transformer neural networks, a type of artificial intelligence (AI) model known for its superior performance in natural language processing, to predict excited state dynamics in OPV materials. The methodology involves a two-fold process. First, the transformer model is trained on an extensive dataset comprising over 10,000 TDDFT calculations of excited state dynamics from a diverse set of OPV materials. Each training example includes a molecular structure and the corresponding TDDFT-calculated excited state lifetimes and key electronic transitions. Second, the trained model is tested on a separate set of molecules, and its predictions are rigorously compared to independent TDDFT calculations. The results indicate a remarkable degree of predictive accuracy. Specifically, for a test set of 1,000 OPV materials, the transformer model predicted excited state lifetimes with a mean absolute error of 0.15 picoseconds, a negligible deviation from TDDFT-calculated values. The model also correctly identified key electronic transitions contributing to the excited state dynamics in 92% of the test cases, signifying a substantial concordance with the results obtained via conventional quantum chemistry calculations. The practical integration of the transformer model with existing quantum chemistry software was also realized, demonstrating its potential as a powerful tool in the arsenal of materials scientists and chemists. The implementation of this AI model is estimated to reduce the computational cost of predicting excited state dynamics by two orders of magnitude compared to conventional TDDFT calculations. The successful utilization of transformer neural networks to accurately predict excited state dynamics provides an efficient computational pathway for the accelerated discovery and design of new OPV materials, potentially catalyzing advancements in the realm of sustainable energy solutions.

Keywords: transformer neural networks, organic photovoltaic materials, excited state dynamics, time-dependent density functional theory, predictive modeling

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Authors: Azza H. El-Medany, Hanan H. Hagar, Omnia A. Nayel, Jamila H. El-Medany

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In search for drugs that can target cancer cell micro-environment in as much as being able to halt malignant cellular transformation, the natural dietary phytochemical curcumin was currently assessed in DMH-induced colorectal cancer rat model. The study enrolled 50 animals divided into a control group (n=10) and DMH-induced colorectal cancer control group (n=20) (20mg/kg-body weight for 28 weeks) versus curcumin-treated group (n=20) (160 mg/kg suspension daily oral for further 8 weeks). Treatment by curcumin succeeded to significantly decrease the percent of ACF and tended to normalize back the histological changes retrieved in adenomatous and stromal cells induced by DMH. The drug also significantly elevated GSH and significantly reduced most of the accompanying biochemical elevations (namely MDA, TNF-α, TGF-β and COX2) observed in colonic carcinomatous tissue, induced by DMH, thus succeeding to revert that of MDA, COX2 and TGF-β back to near normal as justified by being non-significantly altered as compared to normal controls. The only exception was PAF that was insignificantly altered by the drug. When taken together, it could be concluded that curcumin possess the potentiality to halt some of the orchestrated cross-talk between cancerous transformation and its micro-environmental niche that contributes to cancer initiation, progression and metastasis in this experimental cancer colon model. Envisioning these merits to a drug with already known safety preferentiality, awaits final results of current ongoing clinical trials, before curcumin can be added to the new therapeutic armamentarium of anticancer therapy.

Keywords: curcumin, dimethyl hydralazine, aberrant crypt foci, malondialdehyde, reduced glutathione, cyclooxygenase-2, tumour necrosis factor-alpha, transforming growth factor-beta, platelet activating factor

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Authors: Samir El-Gendy, Doaa Zaghloul

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The current study dealt with the gross and microscopic anatomy of the integument of male ostrich in addition to the histological features of different areas of skin by light and SEM. The ostrich skin is characterized by prominent feather follicles and bristles. The number of feather follicles was determined per cm2 in different regions. The integument of ostrich had many modifications which appeared as callosities and scales, nail and toe pads. They were sternal, pubic and Achilles tendon callosities. The vacuolated epidermal cells were seen mainly in the skin of legs and to a lesser extent in the skin of back and Achilles areas. Higher lipogenic potential was expressed by epidermis from glabrous areas of ostrich skin. The dermal papillae were found in the skin of feathered area of neck and back and this was not a common finding in bird's skin which may give resistance against shearing forces in these regions of ostrich skin. The thickness of the keratin layer of ostrich varied, being thick and characteristically loose in the skin at legs, very thin and wavy at neck, while at Achilles skin area, scale and toe pad were thick and more compact, with the thickest very dense and wavy keratin layer at the nail. The dermis consisted of superficial layer of dense irregular connective tissue characterized by presence of many vacuoles of different sizes just under the basal lamina of the epithelium of epidermis and deep layer of dense regular connective tissue. This result suggested presence of fat droplets in this layer which may be to overcome the lack of good barrier of cutaneous water loss in epidermis.

Keywords: ostrich, light microscopy, scanning electron microscopy, integument, skin modifications

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Authors: Mona Francesca B. Dela Cruz, Katrina Marie R. Mamaril, Mariah Hannah Kassandra Salazar, Emerald Jay D. Ilac

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One key factor that should be considered when determining sustainable solutions to various environmental problems is the potential impact of individual human beings. In order to understand an individual, there is a need to examine cognitive, emotional, dispositional, and behavioral factors which are all indicative of one’s environmental consciousness. This quantitative study explored the moderated mediation between environmental consciousness, socio-economic status, social norms as a mediator, and the perceived role of government as a moderator for 381 Filipinos, aged 25 to 65, in urban and suburban settings. Results showed social norms do not have a mediating effect between socio-economic status and environmental consciousness. This may be influenced by the collectivist culture of the Philippines and the tendency for people to copy behaviors according to the descriptive norm effect. Meanwhile, there exists a moderating effect of the perceived role of government between the relationship of social norms and environmental consciousness which can be explained by the government’s ability to impose social norms that can induce a person to think and act pro-environmentally. Practical applications of this study can be used to tap the ability of the government to strengthen their influence and control over environmental protection and to provide a basis for the development of class-specific environmental solutions that can be done by individuals depending on their socioeconomic status.

Keywords: environmental consciousness, role of government, social norms, socio-economic status

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Authors: Dinoo Kirthinanda, Sujani Wijeratne

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

Keywords: patient safety, pseudohyperkalaemia, haemolysis, myeloproliferative disorder

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Authors: Keshab Shrestha, Hung-Suck Park

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Emergy accounting of the systems networks is guided by a definite rule called ‘emergy algebra’. The systems networks consist of two types of branching. These are the co-product branching and split branching. The emergy accounting procedure for both the branching types is different. According to the emergy algebra, each branch in the co-product branching has different transformity values whereas the split branching has the same transformity value. After the transformity value of each branch is determined, the emergy is calculated by multiplying this with the energy. The aim of this research is to solve the problems in determining the transformity values in the co-product branching through the introduction of a new methodology, the modified physical quantity method. Initially, the existing methodologies for emergy accounting in the co-product branching is discussed and later, the modified physical quantity method is introduced with a case study of the Eucalyptus pulp production. The existing emergy accounting methodologies in the co-product branching has wrong interpretations with incorrect emergy calculations. The modified physical quantity method solves those problems of emergy accounting in the co-product branching systems. The transformity value calculated for each branch is different and also applicable in the emergy calculations. The methodology also strictly follows the emergy algebra rules. This new modified physical quantity methodology is a valid approach in emergy accounting particularly in the multi-production systems networks.

Keywords: co-product branching, emergy accounting, emergy algebra, modified physical quantity method, transformity value

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Authors: YingWei Tan, XueFeng Ding

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Attention-based voice activity detection models have gained significant attention in recent years due to their fast training speed and ability to capture a wide contextual range. The inclusion of multi-head style and position embedding in the attention architecture are crucial. Having multiple attention heads allows for differential focus on different parts of the sequence, while position embedding provides guidance for modeling dependencies between elements at various positions in the input sequence. In this work, we propose an approach by considering each head as a node, enabling the application of graph neural networks (GNN) to identify correlations among the different nodes. In addition, we adopt an implementation named rotary position embedding (RoPE), which encodes absolute positional information into the input sequence by a rotation matrix, and naturally incorporates explicit relative position information into a self-attention module. We evaluate the effectiveness of our method on a synthetic dataset, and the results demonstrate its superiority over the baseline CRNN in scenarios with low signal-to-noise ratio and noise, while also exhibiting robustness across different noise types. In summary, our proposed framework effectively combines the strengths of CNN and RNN (LSTM), and further enhances detection performance through the integration of graph neural networks and rotary position embedding.

Keywords: voice activity detection, CRNN, graph neural networks, rotary position embedding

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Authors: Saji George, Eng Khuan Seng, Christof Luda

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Nanotechnology has been recognized as an important tool for modern agriculture and has the potential to overcome some of the pressing challenges faced by aquaculture industry. A strategy for optimizing nanotechnology-based therapeutic delivery platform for immunizing farmed fish was developed. Accordingly, a compositional library of nanomaterials of natural chemistry (Halloysite (clay), Chitosan, Hydroxyapatite, Mesoporous Silica and a composite material of clay-chitosan) was screened for their toxicity and efficiency in delivering models antigens in cellular and zebrafish embryo models using high throughput screening platforms. Through multi-parametric optimization, chitosan modified halloysite (clay) nanomaterial was identified as an optimal vaccine delivery platform. Further, studies conducted in juvenile seabass showed the potential of clay-chitosan in delivering outer membrane protein of Tenacibaculum maritimum- TIMA (pathogenic bacteria) to and its efficiency in eliciting immune responses in fish. In short, as exemplified by this work, the strategy of using compositional nanomaterial libraries and their biological profiling using high-throughput screening platform could fasten the discovery process of nanomaterials with potential applications in food and agriculture.

Keywords: nanotechnology, fish-vaccine, drug-delivery, halloysite-chitosan

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Authors: Driss Cherqaoui, Nouhaila Ait Lahcen, Ismail Hdoufane, Mehdi Oubahmane, Wissal Liman, Christelle Delaite, Mohammed M. Alanazi

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The Ebola virus is a highly contagious and deadly pathogen that causes Ebola virus disease. The Ebola virus glycoprotein (EBOV-GP) is a key factor in viral entry into host cells, making it a critical target for therapeutic intervention. Using a combination of computational approaches, this study focuses on the identification of natural compounds that could serve as potent inhibitors of EBOV-GP. The 3D structure of EBOV-GP was selected, with missing residues modeled, and this structure was minimized and equilibrated. Two large natural compound databases, COCONUT and NPASS, were chosen and filtered based on toxicity risks and Lipinski’s Rule of Five to ensure drug-likeness. Following this, a pharmacophore model, built from 22 reported active inhibitors, was employed to refine the selection of compounds with a focus on structural relevance to known Ebola inhibitors. The filtered compounds were subjected to virtual screening via molecular docking, which identified ten promising candidates (five from each database) with strong binding affinities to EBOV-GP. These compounds were then validated through molecular dynamics simulations to evaluate their binding stability and interactions with the target. The top three compounds from each database were further analyzed using ADMET profiling, confirming their favorable pharmacokinetic properties, stability, and safety. These results suggest that the selected compounds have the potential to inhibit EBOV-GP, offering new avenues for antiviral drug development against the Ebola virus.

Keywords: EBOV-GP, Ebola virus glycoprotein, high-throughput drug screening, molecular docking, molecular dynamics, natural compounds, pharmacophore modeling, virtual screening

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Authors: Shahla Ali

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In the context of promoting green infrastructure development, new opportunities are emerging to re-examine sustainable development practices. This paper presents an initial exploration of the development of community-investor dispute prevention and facilitation mechanisms in the context of the Belt and Road Initiative (BRI) spanning Asia, Africa, and Europe. Given the widescale impact of China’s multi-jurisdictional development initiative, learning how to coordinate with local communities is vital to realizing inclusive and sustainable growth. In the 20 years since the development of the first multilateral community-investor dispute resolution mechanism developed by the International Finance Centre/World Bank, much has been learned about public facilitation, community engagement, and dispute prevention during the early stages of major infrastructure development programs. This paper will explore initial findings as they relate to initiatives underway along the BRI within the Asian Infrastructure Investment Bank and the Asian Development Bank. Given the borderless nature of sustainability concerns, insights from diverse regions are critical to deepening insights into best practices. Drawing on a case-based methodology, this paper will explore the achievements, challenges, and lessons learned in community-investor dispute prevention and resolution for major infrastructure projects in the greater China region.

Keywords: law and development, dispute prevention, sustainable development, mitigation

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Authors: Chigozirim Onwusiribe, Jude Mbanasor

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Egusi Melon (Citrullus Lanatus Thunb. Mansf ) is a very important oil seed that serves a major ingredient in the diet of most of the households in Nigeria. Egusi Melon is very nutritious and very important in meeting the food security needs of Nigerians. Egusi Melon is cultivated in most farm enterprise in South East Nigeria but the profitability of its value chain needs to be investigated. This study analyzed the profitability of the Egusi Melon value chain. Specifically this study developed a value chain map for Egusi Melon, analysed the profitability of each stage of the Egusi Melon Value chain and analysed the determinants of the profitability of the Egusi Melon at each stage of the value chain. Multi stage sampling technique was used to select 125 farm enterprises with similar capacity and characteristics. Questionnaire and interview were used to elicit the required data while descriptive statistics, Food and Agriculture Organization Value Chain Analysis Tool, profitability ratios and multiple regression analysis were used for the data analysis. One of the findings showed that the stages of the Egusi Melon value chain are very profitable. Based on the findings, we recommend the provision of grants by government and donor agencies to the farm enterprises through their cooperative societies, this will provide the necessary funds for the local fabrication of value addition and processing equipment to suit their unique value addition needs not met by the imported equipment.

Keywords: value, chain, melon, farm, enterprises

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Authors: Songul Cinaroglu

Abstract:

Background: Random Forest is an efficient, multi-class machine learning method using for classification, regression and other tasks. This method is operating by constructing each tree using different bootstrap sample of the data. Determining the number of trees in random forests is an open question in the literature for studies about improving classification performance of random forests. Aim: The aim of this study is to analyze whether there is an optimal number of trees in Random Forests and how performance of Random Forests differ according to increase in number of trees using sample health data sets in R programme. Method: In this study we analyzed the performance of Random Forests as the number of trees grows and doubling the number of trees at every iteration using “random forest” package in R programme. For determining minimum and optimal number of trees we performed Mc Nemar test and Area Under ROC Curve respectively. Results: At the end of the analysis it was found that as the number of trees grows, it does not always means that the performance of the forest is better than forests which have fever trees. In other words larger number of trees only increases computational costs but not increases performance results. Conclusion: Despite general practice in using random forests is to generate large number of trees for having high performance results, this study shows that increasing number of trees doesn’t always improves performance. Future studies can compare different kinds of data sets and different performance measures to test whether Random Forest performance results change as number of trees increase or not.

Keywords: classification methods, decision trees, number of trees, random forest

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Authors: Huilei Wang, Yuanfeng Wang

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In the early period of China, economy developed rapidly at the cost of environment. Recently, it is generally recognized that the heavily polluted environment not only puts a brake on economic development but also paces negative impact on people’ health as well as probably next decades of generations. Accordingly, the latest Environmental Protection Law revised in 2014 makes a clear-cut division of environmental responsibility and regulates stricter penalties of breaching law. As the new environmental law is enforced gradually, environmental forensic is increasingly required in the process of ascertaining facts in judicial proceedings of environmental cases. Based on the outcomes of documentary analysis for all environmental cases judged on the basis of new environmental law, it is concluded that there still exists problems in present system of environmental forensic. Thus, this paper is aimed to make proposition on improving Chinese environmental forensic system, which involves: (i) promoting capability of environmental forensic system (EFS) to handle professional questions; (ii) develop price mechanism; (iii) multi-departments cooperate to establish unifying and complete EFS system;(iv) enhance the probative value of results of EFS. Such protocol for amending present regulation on environmental forensic is of significant importance because a quality report of environmental forensic will contributes to providing strong probative evidence of culprits’ activity of releasing contaminant into environment, degree of damages for victims and above all, causality between the behavior of public nuisance and damages.

Keywords: China, environmental cases, environmental forensic system, proposition

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Authors: Sarah Elmammeri

Abstract:

This paper will represent the postcolonial every day in the journey of asylum seekers through the asylum process in the UK. It represents everyday borders, which are defined as everyday barriers, and obstacles facing asylum seekers and refugees in the host country. These everyday barriers can be legal, financial, social and educational under the umbrella of the racialized administrative border creating a package. The arguments build on a set of 21 semi-structured interviews in English and Arabic. The interviews were conducted in the UK, online via zoom lasting between 25 minutes and 2 hours with asylum seekers, refugees, Non-governmental organisations workers and volunteers. The interviews focus on the meaning of borders both physical and metaphorical and ways to challenge the ongoing postcolonial everyday border practices. The findings conclude that these barriers are there deliberately and intentionally to target asylum seekers and limit their legal right to claim asylum in a form of policy and regulations. People in the asylum process, NGO workers, and refugees relate to this aspect of the everyday borders. Second, these barriers come intertwined together creating a structure that interferes with the daily life of an asylum seeker and later affects people with refugee status creating racialised barriers starting with the structural and official form of it: the asylum process. These structural barriers will be linked forming a multi-level barrier enhancing the racialisation of people who are categorised and selected.

Keywords: everyday borders, asylum policies, inclusion and exclusion, refugees and asylum seekers

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Authors: Wenhao Wang, Xinzhi Xu, Limin Feng, Wei Cong

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This paper comprehensively investigates current development status of global power grids and fossil energy pipelines (oil and natural gas), proposes a standard visual platform of global power and fossil energy based on Geographic Information System (GIS) technology. In this visual platform, a series of systematic visual models is proposed with global spatial data, systematic energy and power parameters. Under this visual platform, the current Global Power Grids Map and Global Fossil Energy Pipelines Map are plotted within more than 140 countries and regions across the world. Using the multi-scale fusion data processing and modeling methods, the world’s global fossil energy pipelines and power grids information system basic database is established, which provides important data supporting global fossil energy and electricity research. Finally, through the systematic and comparative study of global fossil energy pipelines and global power grids, the general status of global fossil energy and electricity development are reviewed, and energy transition in key areas are evaluated and analyzed. Through the comparison analysis of fossil energy and clean energy, the direction of relevant research is pointed out for clean development and energy transition.

Keywords: energy transition, geographic information system, fossil energy, power systems

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Authors: Igbozuruike Chigozie Jude, Agwu Agwu Ejem

Abstract:

This research examines the comparative influence of social media and TV campaigns on youth participation in the 2023 general elections in Nigeria. It interrogates the roles played by these two media in influencing youth participation, especially youths in Nigeria, while revealing the factors that influenced their exposure to the media and their participation. The study employed a survey design of quantitative research method to gather the data for this study. Data was collected through a questionnaire from 300 youths in Lagos. The sample size was selected using a multi-stage cluster sampling technique. Social media was the most media that was rated to have had the most impact on youth participation during the election period with its political campaigns. The elaborate likelihood model was used to underpin the study. The study concluded that social media campaigns played a major role in political participation among the youth during the 2023 general election. It revealed how social media contributed to the youths' participation and influenced them to engage in common forms of political participation. The main recommendation of this study is that since the majority of the youths are between the ages of 18 to 35, the media should work on coming up with more content around the year to sensitize them about their political rights and enlighten them socio-politically so that they grow up to become responsible citizens in the country both politically and socially.

Keywords: social media, general election, Nigeria, political apathy, youth

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Authors: Balamurali Gunji, B. B. V. L. Deepak, B. B. Biswal, Amrutha Rout, Golak Bihari Mohanta

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Robots play an important role in the operations like pick and place, assembly, spot welding and much more in manufacturing industries. Out of those, assembly is a very important process in manufacturing, where 20% of manufacturing cost is wholly occupied by the assembly process. To do the assembly task effectively, Assembly Sequences Planning (ASP) is required. ASP is one of the multi-objective non-deterministic optimization problems, achieving the optimal assembly sequence involves huge search space and highly complex in nature. Many researchers have followed different algorithms to solve ASP problem, which they have several limitations like the local optimal solution, huge search space, and execution time is more, complexity in applying the algorithm, etc. By keeping the above limitations in mind, in this paper, a new automated optimal robotic assembly sequence planning using Artificial Bee Colony (ABC) Algorithm is proposed. In this algorithm, automatic extraction of assembly predicates is done using Computer Aided Design (CAD) interface instead of extracting the assembly predicates manually. Due to this, the time of extraction of assembly predicates to obtain the feasible assembly sequence is reduced. The fitness evaluation of the obtained feasible sequence is carried out using ABC algorithm to generate the optimal assembly sequence. The proposed methodology is applied to different industrial products and compared the results with past literature.

Keywords: assembly sequence planning, CAD, artificial Bee colony algorithm, assembly predicates

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