Search results for: distribution patterns

Authors: Vichayada Laohapiboolkul

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Introduction: As the legal use of cannabis is being widely accepted throughout the world, medical cannabis has been explored in order to become an alternative cure for patients. Tetrahydrocannabinol (THC) and Cannabidiol (CBD) are natural cannabinoids found in the Cannabis plant which is proved to have positive treatment for various diseases and symptoms such as chronic pain, neuropathic pain, spasticity resulting from multiple sclerosis, reduce cancer-associated pain, autism spectrum disorders (ASD), dementia, cannabis and opioid dependence, psychoses/schizophrenia, general social anxiety, posttraumatic stress disorder, anorexia nervosa, attention-deficit hyperactivity disorder, and Tourette's disorder. Regardless of all the medical benefits, THC, if not metabolized, can lead to mild up to severe adverse drug reactions (ADR). The enzyme CYP2C19 was found to be one of the metabolizers of THC. However, the suballele CYP2C19*2 manifests as a poor metabolizer which could lead to higher levels of THC than usual, possibly leading to various ADRs. Objective: The aim of this study was to investigate the distribution of CYP2C19, specifically CYP2C19*2, genes in Thai patients treated with medical cannabis along with adverse drug reactions. Materials and Methods: Clinical data and EDTA whole blood for DNA extraction and genotyping were collected from patients for this study. CYP2C19*2 (681G>A, rs4244285) genotyping was conducted using the Real-time PCR (ABI, Foster City, CA, USA). Results: There were 42 medical cannabis-induced ADRs cases and 18 medical cannabis tolerance controls who were included in this study. A total of 60 patients were observed where 38 (63.3%) patients were female and 22 (36.7%) were male, with a range of age approximately 19 - 87 years. The most apparent ADRs for medical cannabis treatment were dry mouth/dry throat (76.7%), followed by tachycardia (70%), nausea (30%) and a few arrhythmias (10%). In the total of 27 cases, we found a frequency of 18 CYP2C19*1/*1 alleles (normal metabolizers, 66.7%), 8 CYP2C19*1/*2 alleles (intermediate metabolizers, 29.6%) and 1 CYP2C19*2/*2 alleles (poor metabolizers, 3.7%). Meanwhile, 63.6% of CYP2C19*1/*1, 36.3% and 0% of CYP2C19*1/*2 and *2/*2 in the tolerance controls group, respectively. Conclusions: This is the first study to confirm the distribution of CYP2C19*2 allele and the prevalence of poor metabolizer genes in Thai patients who received medical cannabis for treatment. Thus, CYP2C19 allele might serve as a pharmacogenetics marker for screening before initiating treatment.

Keywords: medical cannabis, adverse drug reactions, CYP2C19, tetrahydrocannabinol, poor metabolizer

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Authors: M. Linek

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This article presents the comparison of selected evaluation methods regarding microstructure modification of hardened cement concrete intended for airfield pavements. Basic test results were presented for two pavement quality concrete lots. Analysis included standard concrete used for airfield pavements and modern material solutions based on concrete composite modification. In case of basic grain size distribution of concrete cement CEM I 42,5HSR NA, fine aggregate and coarse aggregate fractions in the form of granite chippings, water and admixtures were considered. In case of grain size distribution of modified concrete, the use of modern modifier as substitute of fine aggregate was suggested. Modification influence on internal concrete structure parameters using scanning electron microscope was defined. Obtained images were compared to the results obtained using computed tomography. Opportunity to use this type of equipment for internal concrete structure diagnostics and an attempt of its parameters evaluation was presented. Obtained test results enabled to reach a conclusion that both methods can be applied for pavement quality concrete diagnostics, with particular purpose of airfield pavements.

Keywords: scanning electron microscope, computed tomography, cement concrete, airfield pavements

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Authors: Nji Queenta Ngum, Mwanza Mulunda

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Introduction Most African research reports on the frequent aflatoxin contamination of various foodstuffs, with researchers rarely specifying which of the Aspergillus species are present in these commodities. Numerous research works provide evidence of the ability of fungi to grow, thrive, and interact with other crop species and focus on the fact that these processes are largely affected by climatic variables. South Africa is a water-stressed country with high spatio-temporal rainfall variability; moreover, temperatures have been projected to rise at a rate twice the global rate. This weather pattern change may lead to crop stress encouraging mold contamination with subsequent mycotoxin production. In this study, the biodiversity and distribution of Aspergillus species with their corresponding toxins in maize from six distinct maize producing regions with different weather patterns in South Africa were investigated. Materials And Methods By applying cultural and molecular methods, a total of 1028 maize samples from six distinct agro-climatic regions were examined for contamination by the Aspergillus species while the high performance liquid chromatography (HPLC) method was applied to analyse the level of contamination by aflatoxins. Results About 30% of the overall maize samples were contaminated by at least one Aspergillus species. Less than 30% (28.95%) of the 228 isolates subjected to the aflatoxigenic test was found to possess at least one of the aflatoxin biosynthetic genes. Furthermore, almost 20% were found to be contaminated with aflatoxins, with mean total aflatoxin concentration levels of 64.17 ppb. Amongst the contaminated samples, 59.02% had mean total aflatoxin concentration levels above the SA regulatory limit of 20ppb for animals and 10 for human consumption. Conclusion In this study, climate variables (rainfall reduction) were found to significantly (p<0.001) influence the occurrence of the Aspergillus species (especially Aspergillus fumigatus) and the production of aflatoxin in South Africa commercial maize by maize variety, year of cultivation as well as the agro-climatic region in which the maize is cultivated. This included, amongst others, a reduction in the average annual rainfall of the preceding year to about 21.27 mm, and, as opposed to other regions whose average maximum rainfall ranged between 37.24 – 44.1 mm, resulted in a significant increase in the aflatoxin contamination of maize.

Keywords: aspergillus species, aflatoxins, diversity, drought, food safety, HPLC and PCR techniques

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Authors: Natalia Moreno-Castellanos, Amaia Rodriguez, Gema Frühbeck

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Introduction: In adipocytes, the cytoskeleton undergoes important expression and distribution in adipocytes rearrangements during adipogenesis and in obesity. Indeed, a role for these proteins in the regulation of adipocyte differentiation and response to insulin has been demonstrated. Recently, septins have been considered as new components of the cytoskeletal network that interact with other cytoskeletal elements (actin and tubulin) profoundly modifying their dynamics. However, these proteins have not been characterized as yet in adipose tissue. In this work, were examined the cellular, molecular and functional features of a member of this family, septin 11 (SEPT11), in adipocytes and evaluated the impact of obesity on the expression of this protein in human adipose tissue. Methods: Adipose gene and protein expression levels of SEPT11 were analysed in human samples. SEPT11 distribution was evaluated by immunocytochemistry, electronic microscopy, and subcellular fractionation techniques. GST-pull down, immunoprecipitation and a Yeast-Two Hybrid (Y2H) screening were used to identify the SEPT11 interactome. Gene silencing was employed to assess the role of SEPT11 in the regulation of insulin signaling and lipid metabolism in adipocytes. Results: SEPT11 is expressed in human adipocytes, and its levels increased in both omental and subcutaneous adipose tissue in obesity, with SEPT11 mRNA content positively correlating with parameters of insulin resistance in subcutaneous fat. In non-stimulated adipocytes, SEPT11 immunoreactivity showed a ring-like distribution at the cell surface and associated to caveolae. Biochemical analyses showed that SEPT11 interacted with the main component of caveolae, caveolin-1 (CAV1) as well as with the fatty acid-binding protein, FABP5. Notably, the three proteins redistributed and co-localized at the surface of lipid droplets upon exposure of adipocytes to oleate. In this line, SEPT11 silencing in 3T3-L1 adipocytes impaired insulin signaling and decreased insulin-induced lipogenesis. Conclusions: Those findings demonstrate that SEPT11 is a novel component of the adipocyte cytoskeleton that plays an important role in the regulation of lipid traffic, metabolism and can thus represent a potential biomarker of insulin resistance in obesity in adipocytes through its interaction with both CAV1 and FABP5.

Keywords: caveolae, lipid metabolism, obesity, septins

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Authors: B. Paygozar, S.A. Dizaji

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Adhesive bonding is a highly valued type of fastening mechanical parts in complex structures, where joining some simple components is always needed. This method is of several merits, such as uniform stress distribution, appropriate bonding strength, and fatigue performance, and lightness, thereby outweighing other sorts of bonding methods. This study is to investigate the failure load of adhesive single-strap joints, including adherends of different sizes and materials. This kind of adhesive joint is very practical in different industries, especially when repairing the existing joints or attaching substrates of dissimilar materials. In this research, experimentally validated numerical analyses carried out in a commercial finite element package, ABAQUS, are utilized to extract the failure loads of the joints, based on the cohesive zone model. In addition, the stress analyses of the substrates are performed in order to acquire the effects of lowering the thickness of the substrates on the stress distribution inside them to avoid designs suffering from the necking or failure of the adherends. It was found out that this method of bonding is really feasible in joining dissimilar materials which can be utilized in a variety of applications. Moreover, the stress analyses indicated the minimum thickness for the adherends so as to avoid the failure of them.

Keywords: cohesive zone model, dissimilar materials, failure load, single strap joint

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Authors: Benjamin Glasner, Carlos Henriquez, Fernando Alfaro, Nicole Trefault, Santiago Andrade, Rodrigo De La Iglesia

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A central question in ecology refers to the relative importance that local-scale variables have over community composition, when compared with regional-scale variables. In coastal environments, strong seasonal abiotic influence dominates these systems, weakening the impact of other parameters like micronutrients. After the industrial revolution, micronutrients like trace metals have increased in ocean as pollutants, with strong effects upon biotic entities and biological processes in coastal regions. Coastal picoplankton communities had been characterized as a cyanobacterial dominated fraction, but in recent years the eukaryotic component of this size fraction has gained relevance due to their high influence in carbon cycle, although, diversity patterns and responses to disturbances are poorly understood. South Pacific upwelling coastal environments represent an excellent model to study seasonal changes due to a strong influence in the availability of macro- and micronutrients between seasons. In addition, some well constrained coastal bays of this region have been subjected to strong disturbances due to trace metal inputs. In this study, we aim to compare the influence of seasonality and trace metals concentrations, on the community structure of planktonic picoeukaryotes. To describe seasonal patterns in the study area, satellite data in a 6 years time series and in-situ measurements with a traditional oceanographic approach such as CTDO equipment were performed. In addition, trace metal concentrations were analyzed trough ICP-MS analysis, for the same region. For biological data collection, field campaigns were performed in 2011-2012 and the picoplankton community was described by flow cytometry and taxonomical characterization with next-generation sequencing of ribosomal genes. The relation between the abiotic and biotic components was finally determined by multivariate statistical analysis. Our data show strong seasonal fluctuations in abiotic parameters such as photosynthetic active radiation and superficial sea temperature, with a clear differentiation of seasons. However, trace metal analysis allows identifying strong differentiation within the study area, dividing it into two zones based on trace metals concentration. Biological data indicate that there are no major changes in diversity but a significant fluctuation in evenness and community structure. These changes are related mainly with regional parameters, like temperature, but by analyzing the metal influence in picoplankton community structure, we identify a differential response of some plankton taxa to metal pollution. We propose that some picoeukaryotic plankton groups respond differentially to metal inputs, by changing their nutritional status and/or requirements under disturbances as a derived outcome of toxic effects and tolerance.

Keywords: Picoeukaryotes, plankton communities, trace metals, seasonal patterns

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Authors: Rajat Raj, Rohini S. Hallikar

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The ever-increasing integration of renewable energy sources in the power grid necessitates the development of efficient and reliable microgrid systems. Photovoltaic (PV) systems coupled with energy storage technologies, such as batteries, offer promising solutions for sustainable and resilient power generation. This paper proposes an adaptive power control topology for a PV-battery microgrid system, aiming to optimize the utilization of available solar energy and enhance the overall system performance. In order to provide a smooth transition between the OFF-GRID and ON-GRID modes of operation with proportionate power sharing, a self-adaptive control method for a microgrid is proposed. Three different modes of operation are discussed in this paper, i.e., GRID connected, the transition between Grid-connected and Islanded State, and changing the irradiance of PVs and doing the transitioning. The simulation results show total harmonic distortion to be 0.08, 1.43 and 2.17 for distribution generation-1 and 4.22,3.92 and 2.10 for distribution generation-2 in the three modes, respectively which helps to maintain good power quality. The simulation results demonstrate the superiority of the adaptive power control topology in terms of maximizing renewable energy utilization, improving system stability and ensuring a seamless transition between grid-connected and islanded modes.

Keywords: islanded modes, microgrids, photo voltaic, total harmonic distortion

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Authors: Spandan Sahu, Amiya Kumar Pati, Kishanjit Kumar Khatua

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The river is our main source of water which is a form of open channel flow and the flow in the open channel provides with many complex phenomena of sciences that need to be tackled such as the critical flow conditions, boundary shear stress, and depth-averaged velocity. The development of society, more or less solely depends upon the flow of rivers. The rivers are major sources of many sediments and specific ingredients which are much essential for human beings. During floods, part of a river is carried by the simple main channel and rest is carried by flood plains. For such compound asymmetric channels, the flow structure becomes complicated due to momentum exchange between the main channel and adjoining flood plains. Distribution of boundary shear in subsections provides us with the concept of momentum transfer between the interface of the main channel and the flood plains. Experimentally, to get better data with accurate results are very complex because of the complexity of the problem. Hence, CES software has been used to tackle the complex processes to determine the shear stresses at different sections of an open channel having asymmetric flood plains on both sides of the main channel, and the results are compared with the symmetric flood plains for various geometrical shapes and flow conditions. Error analysis is also performed to know the degree of accuracy of the model implemented.

Keywords: depth average velocity, non prismatic compound channel, relative flow depth, velocity distribution

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Authors: Vijay Meena, Arup Kumar Sarma, Chandan Mahanta

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The environment has been getting contaminated by anthropogenic processes including those that discharge heavy metals to air, soil and water. The present work emphasizes the spatial distribution and vertical profile of six heavy metals (Cu, Zn, Mn, Ni, Fe, Cr) in three layers of mid sand bars (bed surface layer, 50 cm and 100 cm depth) at 42 sampling stations covering around 600 km stretch of the Brahmaputra River, India. Heavy metal analysis was conducted on the sample collected from mid-sand bars in the river stretch to examine the impact of dredging for various hydrological operations in the future. Sediment quality was assessed by calculating six different indices viz., EF, CF, CD, PLI, Igeo, and PERI. In all sediment layers, heavy metal concentrations have been observed to be the same as listed, Fe > Mn > Zn > Ni > Cr > Cu in μg/g. The average concentration of Cu, Mn, and Fe was found in the middle layer while Zn, Ni, and Cr were in the Surface layer. EF indicates higher enrichment in reach 2 which is likely to be due to anthropogenic sources of industrial and urbanized effluents. The sediment of the mid-sand bar was generally found moderately polluted possessing low risk to aquatic lives and the environment. Suggesting, Dredging can be possible in the future. An examination of correlation matrices, principal components analysis, and cluster analyses indicated that these heavy metals possess similar anthropogenic origins for their enrichment.

Keywords: heavy metal contamination, risk assessment, anthropogenic impacts, sediment

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Authors: Mohamed Hamed Mohamed Ahmed Alameer

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Population studies, essentially deals with the size, growth, and distribution of the population in a given area. Size, growth, and distribution are determined by three major factors, which are fertility mortality, and migration. Of these factors, fertility- as a number of live births a woman has actually had- is a potent socio-demographic force in vital process of population growth. So, fertility is a major component of population growth. It is one of the main determinants of population growth and has crucial role in population dynamic, because it measures the rate at which a population increased. In fact the levels of fertility are vary widely among nations, countries, geographic regions, ethnic, socio- economic groups, and religious groups. Fertility differential by religion have been empirically documented in a large numbers of countries. For instance, many researchers in developing and developed countries investigated the differential of fertility among Muslims and Non- Muslims. Most of them have found that fertility of Muslims is higher than fertility of non Muslims. And Muslims have a tendency for large families comparing to non- Muslims population. On the basis of this; Islam by it itself could play an important role in shaping attitudes and values of fertility, such as: sustainability of human kind, developmental reasons, religious Motivations, socioeconomic Motivations, and Psychological Motivation. Therefore, this paper investigates socio-economic values of fertility in Islam and compare it to Malthusian and neo Malthusian functionalists and conflict perspectives.

Keywords: islam, fertility, socioeconomic values, social sciences

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Authors: Amandeep Kaur, Ns Atri, Munruchi Kaur

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Mushrooms have shaped our environment in ways that we are only beginning to understand. The weather patterns, topography, flora and fauna of Punjab state in India create favorable growing conditions for thousands of species of mushrooms, but the complete region was unexplored when it comes to coprophilous mushrooms growing on herbivorous dung. Coprophilous mushrooms are the most specialized fungi ecologically, which germinate and grow directly on different types of animal dung or on manured soil. In the present work, the diversity of coprophilous mushrooms' of Family Psathyrellaceae of the order Agaricales is explored, their relationship to the human world is sketched out, and their supreme significance to life on this planet is revealed. During the investigation, different dung localities from 16 districts of Punjab state have been explored for the collection of material. The macroscopic features of the collected mushrooms were documented on the Field key. The hand cut sections of the various parts of carpophore, such as pileus, gills, stipe and the basidiospores details, were studied microscopically under different magnification. Various authentic publications were consulted for the identification of the investigated taxa. The classification, authentic names and synonyms of the investigated taxa are as per the latest version of Dictionary of Fungi and the MycoBank. The present work deals with the taxonomy of 81 collections belonging to 39 species spread over 05 coprophilous genera, namely Psathyrella, Panaeolus, Parasola, Coprinopsis, and Coprinellus of family Psathyrellaceae. In the text, the investigated taxa have been arranged as they appear in the key to the genera and species investigated. In this work, have been thoroughly examined for their macroscopic, microscopic, ecological, and chemical reaction details. The authors dig deeper to give indication of their ecology and the dung type where they can be obtained. Each taxon is accompanied by a detailed listing of its prominent features and an illustration with habitat photographs and line drawings of morphological and anatomical features. Taxa are organized as per their status in the keys, which allow easy recognition. All the taxa are compared with similar taxa. The study has shown that dung is an important substrate which serves as a favorable niche for the growth of a variety of mushrooms. This paper shows an insight what short-lived coprophilous mushrooms can teach us about sustaining life on earth!

Keywords: abundance, basidiomycota, biodiversity, seasonal availability, systematics

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Authors: Dorota Miroslaw-Swiatek, Mateusz Grygoruk, Sylwia Szporak

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We applied a two-dimensional surface water flow model with irregular wet boundaries. In this model, flow equations are in the form of a 2-D, non-linear diffusion equations which allows to account spatial variations in flow resistance and topography. Calculation domain to simulate the flow pattern in the floodplain is congruent with a Digital Elevation Model (DEM) grid. The rate and direction of sheet flow in wetlands is affected by vegetation type and density, therefore the developed model take into account spatial distribution vegetation resistance to the water flow. The model was tested in a part of the Biebrza Valley, of an outstanding heterogeneity in the elevation and flow resistance distributions due to various ecohydrological conditions and management measures. In our approach we used the highest-possible quality of the DEM in order to obtain hydraulic slopes and vegetation distribution parameters for the modelling. The DEM was created from the cloud of points measured in the LiDAR technology. The LiDAR reflects both the land surface as well as all objects on top of it such as vegetation. Depending on the density of vegetation cover the ability of laser penetration is variable. Therefore to obtain accurate land surface model the “vegetation effect” was corrected using data collected in the field (mostly the vegetation height) and satellite imagery such as Ikonos (to distinguish different vegetation types of the floodplain and represent them spatially). Model simulation was performed for the spring thaw flood in 2009.

Keywords: floodplain flow, Biebrza valley, model simulation, 2D surface flow model

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Authors: Andrea Cretu, Calin Cadar, Maria Miclaus, Lucian Barbu-Tudoran, Siegfried Stapf, Ioan Ardelean

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Additives and mineral admixtures have become an integral part of cement-based materials. It is common practice to add silica fume to cement based mixes in order to produce high-performance concrete. There is still a lack of scientific understanding regarding the effects that silica fume has on the microstructure of hydrated cement paste. The aim of the current study is to develop high-performance materials with low permeability and high resistance to flexural stress using silica fume and an organosilane. Organosilane bonds with cement grains and silica fume, influencing both the workability and the final properties of the mix, especially the pore size distributions and pore connectivity. Silica fume is a known pozzolanic agent which reacts with the calcium hydroxide in hydrated cement paste, producing more C-S-H and improving the mechanical properties of the mix. It is believed that particles of silica fume act as capillary pore fillers and nucleation centers for C-S-H and other hydration products. In order to be able to design cement-based materials with added silica fume and organosilane, it is necessary first to understand the formation of the porous network during hydration and to observe the distribution of pores and their connectivity. Nuclear magnetic resonance (NMR) methods in low-fields are non-destructive and allow the study of cement-based materials from the standpoint of their porous structure. Other methods, such as XRD and SEM-EDS, help create a comprehensive picture of the samples, along with the classic mechanical tests (compressive and flexural strength measurements). The transverse relaxation time (T₂) was measured during the hydration of 16 samples prepared with two water/cement ratios (0.3 and 0.4) and different concentrations or organosilane (APTES, up to 2% by mass of cement) and silica fume (up to 6%). After their hydration, the pore size distribution was assessed using the same NMR approach on the samples filled with cyclohexane. The SEM-EDS and XRD measurements were applied on pieces and powders prepared from the samples that were used in mechanical testing, which were kept under water for 28 days. Adding silica fume does not influence the hydration dynamics of cement paste, while the addition of organosilane extends the dormancy stage up to 10 hours. The size distribution of the capillary pores is not influenced by the addition of silica fume or organosilane, while the connectivity of capillary pores is decreased only when there is organosilane in the mix. No filling effect is observed even at the highest concentration of silica fume. There is an apparent increase in flexural strength of samples prepared only with silica fume and a decrease for those prepared with organosilane, with a few exceptions. XRD reveals that the pozzolanic reactivity of silica fume can only be observed when there is no organosilane present and the SEM-EDS method reveals the pore distribution, as well as hydration products and the presence or absence of calcium hydroxide. The current work was funded by the Romanian National Authority for Scientific Research, CNCS – UEFISCDI, through project PN-III-P2-2.1-PED-2016-0719.

Keywords: cement hydration, concrete admixtures, NMR, organosilane, porosity, silica fume

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Authors: Ghufran Ahmed, Muhammad Osama Siddiqui, Shahbaz Siddiqui, Rauf Ahmad Shams Malick, Faisal Khan, Mubashir Khan

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In this paper, a machine learning-based approach for early prediction of diseases in cows is proposed. Different ML algos are applied to extract useful patterns from the available dataset. Technology has changed today’s world in every aspect of life. Similarly, advanced technologies have been developed in livestock and dairy farming to monitor dairy cows in various aspects. Dairy cattle monitoring is crucial as it plays a significant role in milk production around the globe. Moreover, it has become necessary for farmers to adopt the latest early prediction technologies as the food demand is increasing with population growth. This highlight the importance of state-ofthe-art technologies in analyzing how important technology is in analyzing dairy cows’ activities. It is not easy to predict the activities of a large number of cows on the farm, so, the system has made it very convenient for the farmers., as it provides all the solutions under one roof. The cattle industry’s productivity is boosted as the early diagnosis of any disease on a cattle farm is detected and hence it is treated early. It is done on behalf of the machine learning output received. The learning models are already set which interpret the data collected in a centralized system. Basically, we will run different algorithms on behalf of the data set received to analyze milk quality, and track cows’ health, location, and safety. This deep learning algorithm draws patterns from the data, which makes it easier for farmers to study any animal’s behavioral changes. With the emergence of machine learning algorithms and the Internet of Things, accurate tracking of animals is possible as the rate of error is minimized. As a result, milk productivity is increased. IoT with ML capability has given a new phase to the cattle farming industry by increasing the yield in the most cost-effective and time-saving manner.

Keywords: IoT, machine learning, health care, dairy cows

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Authors: S. Benkraouda, Z. Djelloul-Khedda, B. Yagoubi

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we present a method for early detection of forest fires from a thermal infrared satellite image, using the image matrix of the probability of belonging. The principle of the method is to compare a theoretical mathematical model to an experimental model. We considered that each line of the image matrix, as an embodiment of a non-stationary random process. Since the distribution of pixels in the satellite image is statistically dependent, we divided these lines into small stationary and ergodic intervals to characterize the image by an adequate mathematical model. A standard deviation was chosen to generate random variables, so each interval behaves naturally like white Gaussian noise. The latter has been selected as the mathematical model that represents a set of very majority pixels, which we can be considered as the image background. Before modeling the image, we made a few pretreatments, then the parameters of the theoretical Gaussian model were extracted from the modeled image, these settings will be used to calculate the probability of each interval of the modeled image to belong to the theoretical Gaussian model. The high intensities pixels are regarded as foreign elements to it, so they will have a low probability, and the pixels that belong to the background image will have a high probability. Finally, we did present the reverse of the matrix of probabilities of these intervals for a better fire detection.

Keywords: forest fire, forest fire detection, satellite image, normal distribution, theoretical gaussian model, thermal infrared matrix image

Procedia PDF Downloads 136

Authors: Luvindran Sugumaran, Mohd Nashrul Mohd Zubir, Kazi Md Salim Newaz, Tuan Zaharinie Tuan Zahari, Suazlan Mt Aznam, Aiman Mohd Halil

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With reference to Energy Roadmap 2050, the minimization of greenhouse gas emissions and the enhancement of energy efficiency are the two key factors that could facilitate a radical change in the world's energy infrastructure. However, the energy demands of electronic devices skyrocketed with the advent of the digital age. Currently, the two-phase cooling technique based on phase change pool boiling heat transfer has received a lot of attention because of its potential to fully utilize the latent heat of the fluid and produce a highly effective heat dissipation capacity while keeping the equipment's operating temperature within an acceptable range. There are numerous strategies available for the alteration of heating surfaces, but finding the best, simplest, and most dependable one remains a challenge. Lately, surface texturing via laser ablation has been used in a variety of investigations, demonstrating its significant potential for enhancing the pool boiling heat transfer performance. In this research, the nucleate pool boiling heat transfer performance of laser-structured copper surfaces of different patterns was investigated. The bare copper surface serves as a reference to compare the performance of laser-structured surfaces. It was observed that the heat transfer coefficients were increased with the increase of surface area ratio and the ratio of the peak-to-valley height of the microstructure. Laser machined grain structure produced extra nucleation sites, which ultimately caused the improved pool boiling performance. Due to an increase in nucleation site density and surface area, the enhanced nucleate boiling served as the primary heat transfer mechanism. The pool boiling performance of the laser-structured copper surfaces is superior to the bare copper surface in all aspects.

Keywords: heat transfer coefficient, laser structuring, micro structured surface, pool boiling

Procedia PDF Downloads 77

Authors: Luvindran Sugumaran, Mohd Nashrul Mohd Zubir, Kazi Md Salim Newaz, Tuan Zaharinie Tuan Zahari, Suazlan Mt Aznam, Aiman Mohd Halil

Abstract:

With reference to Energy Roadmap 2050, the minimization of greenhouse gas emissions, and the enhancement of energy efficiency are the two key factors that could facilitate a radical change in the world's energy infrastructure. However, the energy demands of electronic devices skyrocketed with the advent of the digital age. Currently, the two-phase cooling technique based on phase change pool boiling heat transfer has received a lot of attention because of its potential to fully utilize the latent heat of the fluid and produce a highly effective heat dissipation capacity while keeping the equipment's operating temperature within an acceptable range. There are numerous strategies available for the alteration of heating surfaces, but to find the best, simplest, and most dependable one remains a challenge. Lately, surface texturing via laser ablation has been used in a variety of investigations, demonstrating its significant potential for enhancing the pool boiling heat transfer performance. In this research, the nucleate pool boiling heat transfer performance of laser-structured copper surfaces of different patterns was investigated. The bare copper surface serves as a reference to compare the performance of laser-structured surfaces. It was observed that the heat transfer coefficients were increased with the increase of surface area ratio and the ratio of the peak-to-valley height of the microstructure. Laser machined grain structure produced extra nucleation sites, which ultimately caused the improved pool boiling performance. Due to an increase in nucleation site density and surface area, the enhanced nucleate boiling served as the primary heat transfer mechanism. The pool boiling performance of the laser-structured copper surfaces is superior to the bare copper surface in all aspects.

Keywords: heat transfer coefficient, laser structuring, micro structured surface, pool boiling

Procedia PDF Downloads 75

Authors: Luvindran Sugumaran, Mohd Nashrul Mohd Zubir, Kazi Md. Salim Newaz, Tuan Zaharinie Tuan Zahari, Suazlan Mt Aznam, Aiman Mohd Halil

Abstract:

With reference to Energy Roadmap 2050, the minimization of greenhouse gas emissions and the enhancement of energy efficiency are the two key factors that could facilitate a radical change in the world's energy infrastructure. However, the energy demands of electronic devices skyrocketed with the advent of the digital age. Currently, the two-phase cooling technique based on phase change pool boiling heat transfer has received a lot of attention because of its potential to fully utilize the latent heat of the fluid and produce a highly effective heat dissipation capacity while keeping the equipment's operating temperature within an acceptable range. There are numerous strategies available for the alteration of heating surfaces, but to find the best, simplest, and most dependable one remains a challenge. Lately, surface texturing via laser ablation has been used in a variety of investigations, demonstrating its significant potential for enhancing the pool boiling heat transfer performance. In this research, the nucleate pool boiling heat transfer performance of laser-structured copper surfaces of different patterns was investigated. The bare copper surface serves as a reference to compare the performance of laser-structured surfaces. It was observed that the heat transfer coefficients were increased with the increase of surface area ratio and the ratio of the peak-to-valley height of the microstructure. Laser-machined grain structure produced extra nucleation sites, which ultimately caused the improved pool boiling performance. Due to an increase in nucleation site density and surface area, the enhanced nucleate boiling served as the primary heat transfer mechanism. The pool boiling performance of the laser-structured copper surfaces is superior to the bare copper surface in all aspects.

Keywords: heat transfer coefficient, laser structuring, micro structured surface, pool boiling

Procedia PDF Downloads 78

Authors: Godwin Chigozie Okpara

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This paper using standard GARCH, EGARCH, and TARCH models on day of the week return series (of 246 days) from the Nigerian Stock market estimated the model variants’ VaR. An asymmetric return distribution and fat-tail phenomenon in financial time series were considered by estimating the models with normal, student t and generalized error distributions. The analysis based on Akaike Information Criterion suggests that the EGARCH model with student t innovation distribution can furnish more accurate estimate of VaR. In the light of this, we apply the likelihood ratio tests of proportional failure rates to VaR derived from EGARCH model in order to determine the short and long positions VaR performances. The result shows that as alpha ranges from 0.05 to 0.005 for short positions, the failure rate significantly exceeds the prescribed quintiles while it however shows no significant difference between the failure rate and the prescribed quantiles for long positions. This suggests that investors and portfolio managers in the Nigeria stock market have long trading position or can buy assets with concern on when the asset prices will fall. Precisely, the VaR estimates for the long position range from -4.7% for 95 percent confidence level to -10.3% for 99.5 percent confidence level.

Keywords: downside risk, value-at-risk, failure rate, kupiec LR tests, GARCH models

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Authors: R. Daira

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The electronic speckle interferometry technique used to measure the deformations of scatterers process is based on the subtraction of interference patterns. A speckle image is first recorded before deformation of the object in the RAM of a computer, after a second deflection. The square of the difference between two images showing correlation fringes observable in real time directly on monitor. The interpretation these fringes to determine the deformation. In this paper, we present experimental results of deformation out of the plane of two samples in aluminum, electronic boards and stainless steel.

Keywords: optical method, holography, interferometry, deformation

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Authors: Laxuman Thakuri

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Despite the large number of in-depth case studies focused on policy analysis, institutional arrangement, and collective action of common property resource management; how the local institutions take the pricing decision of forest products in community forest management and what kinds of effects produce it, the answers of these questions are largely silent among the policy-makers and researchers alike. The study examined how the local institutions take the pricing decision of forest products in the lowland community forestry of Nepal and how the decisions affect to equitable distribution of benefits and livelihood improvement which are also objectives of Nepalese community forestry. The study assumes that forest products pricing decisions have multiple effects on equitable distribution and livelihood improvement in the areas having heterogeneous socio-economic conditions. The dissertation was carried out at four community forests of lowland, Nepal that has characteristics of high value species, matured-experience of community forest management and better record-keeping system of forest products production, pricing and distribution. The questionnaire survey, individual to group discussions and direct field observation were applied for data collection from the field, and Lorenz curve, gini-coefficient, χ²-text, and SWOT (Strong, Weak, Opportunity, and Threat) analysis were performed for data analysis and results interpretation. The dissertation demonstrates that the low pricing strategy of high-value forest products was supposed crucial to increase the access of socio-economically weak households, and to and control over the important forest products such as timber, but found counter productive as the strategy increased the access of socio-economically better-off households at higher rate. In addition, the strategy contradicts to collect a large-scale community fund and carry out livelihood improvement activities as per the community forestry objectives. The crucial part of the study is despite the fact of low pricing strategy; the timber alone contributed large part of community fund collection. The results revealed close relation between pricing decisions and livelihood objectives. The action research result shows that positive price discrimination can slightly reduce the prevailing inequality and increase the fund. However, it lacks to harness the full price of forest products and collects a large-scale community fund. For broader outcomes of common property resource management in terms of resource sustainability, equity, and livelihood opportunity, the study suggests local institutions to harness the full price of resource products with respect to the local market.

Keywords: community, equitable, forest, livelihood, socioeconomic, Nepal

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Authors: Muhammad Munir, Riffat Mehboob, Samina Naeem, Muhammad Salman, Shehryar Ahmed, Irshad Hussain Qureshi, Tahira Murtaza Cheema, Ashraf Sultan, Akmal Laeeq, Nakhshab Choudhry, Asad Aslam Khan, Fridoon Jawad Ahmad

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A dengue outbreak in Lahore, Pakistan during 2011 was unprecedented in terms of severity and magnitude. This research aims to determine the serotype distribution of dengue virus during this outbreak and classify the patients demographically. 5ml of venous blood was drawn aseptically from 166 patients with dengue-like signs to test for the virus between the months of August to November 2011. The samples were sent to the CDC, Atlanta, Georgia for the purpose of molecular assays to determine their serotype. RT-PCR protocol was performed targeting at the 4 dengue serotypes. Out of 166 cases, dengue infection was detected with RT-PCR in 95 cases, all infected with same serotype DEN-2. 75% of positive cases were males while 25% were females. Most positive patients were in the age range of 16-30 years. 33% positive cases had accompanying bleeding. This is first study during the 2011 dengue epidemic in Lahore that reports DEN-2 as the only prevalent serotype. It also indicates that more infected patients were males, adults, within age range of 16-30 years, peaked in the month of November, Dengue hemorrhagic fever (DHF) is manifested more in females, Ravi town was heavily hit by dengue virus infection.

Keywords: dengue, serotypes, Pakistan, DEN 2, Lahore, demography, serotype distrbution, 2011 epidemic

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Authors: A. J. S. P. Nileema, S. Kulatunga , S. H. Palihawadana

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Computer aided detection (CAD) system was developed for the diagnosis of pulmonary tuberculosis using digital chest X-rays with MATLAB image processing techniques using a statistical approach. The study comprised of 200 digital chest radiographs collected from the National Hospital for Respiratory Diseases - Welisara, Sri Lanka. Pre-processing was done to remove identification details. Lung fields were segmented and then divided into four quadrants; right upper quadrant, left upper quadrant, right lower quadrant, and left lower quadrant using the image processing techniques in MATLAB. Contrast, correlation, homogeneity, energy, entropy, and maximum probability texture features were extracted using the gray level co-occurrence matrix method. Descriptive statistics and normal distribution analysis were performed using SPSS. Depending on the radiologists’ interpretation, chest radiographs were classified manually into PTB - positive (PTBP) and PTB - negative (PTBN) classes. Features with standard normal distribution were analyzed using an independent sample T-test for PTBP and PTBN chest radiographs. Among the six features tested, contrast, correlation, energy, entropy, and maximum probability features showed a statistically significant difference between the two classes at 95% confidence interval; therefore, could be used in the classification of chest radiograph for PTB diagnosis. With the resulting value ranges of the five texture features with normal distribution, a classification algorithm was then defined to recognize and classify the quadrant images; if the texture feature values of the quadrant image being tested falls within the defined region, it will be identified as a PTBP – abnormal quadrant and will be labeled as ‘Abnormal’ in red color with its border being highlighted in red color whereas if the texture feature values of the quadrant image being tested falls outside of the defined value range, it will be identified as PTBN–normal and labeled as ‘Normal’ in blue color but there will be no changes to the image outline. The developed classification algorithm has shown a high sensitivity of 92% which makes it an efficient CAD system and with a modest specificity of 70%.

Keywords: chest radiographs, computer aided detection, image processing, pulmonary tuberculosis

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Authors: Sakshi Dhumale, Madhushree C., Amba Shetty

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The effect of station density on the geostatistical prediction of groundwater levels is of critical importance to ensure accurate and reliable predictions. Monitoring station density directly impacts the accuracy and reliability of geostatistical predictions by influencing the model's ability to capture localized variations and small-scale features in groundwater levels. This is particularly crucial in regions with complex hydrogeological conditions and significant spatial heterogeneity. Insufficient station density can result in larger prediction uncertainties, as the model may struggle to adequately represent the spatial variability and correlation patterns of the data. On the other hand, an optimal distribution of monitoring stations enables effective coverage of the study area and captures the spatial variability of groundwater levels more comprehensively. In this study, we investigate the effect of station density on the predictive performance of groundwater levels using the geostatistical technique of Ordinary Kriging. The research utilizes groundwater level data collected from 121 observation wells within the semi-arid Berambadi watershed, gathered over a six-year period (2010-2015) from the Indian Institute of Science (IISc), Bengaluru. The dataset is partitioned into seven subsets representing varying sampling densities, ranging from 15% (12 wells) to 100% (121 wells) of the total well network. The results obtained from different monitoring networks are compared against the existing groundwater monitoring network established by the Central Ground Water Board (CGWB). The findings of this study demonstrate that higher station densities significantly enhance the accuracy of geostatistical predictions for groundwater levels. The increased number of monitoring stations enables improved interpolation accuracy and captures finer-scale variations in groundwater levels. These results shed light on the relationship between station density and the geostatistical prediction of groundwater levels, emphasizing the importance of appropriate station densities to ensure accurate and reliable predictions. The insights gained from this study have practical implications for designing and optimizing monitoring networks, facilitating effective groundwater level assessments, and enabling sustainable management of groundwater resources.

Keywords: station density, geostatistical prediction, groundwater levels, monitoring networks, interpolation accuracy, spatial variability

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Authors: Haftay Abraha Tadesse, Atsebaha Gebrekidan Kahsay, Mahumd Abdulkader

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Background: Salmonella species and Escherichia coli are important foodborne pathogens affecting humans and animals. They are among the most important causes of infection that are associated with the consumption of contaminated food. This study was aimed to determine the prevalence, antimicrobial susceptibility patterns and associated risk factors for Salmonella species and E. coli in raw meat from butchery houses of Mekelle, Northern Ethiopia. Methodology: A cross-sectional study was conducted from January to September 2019. Socio-demographic data and risk factors were collected using a predesigned questionnaire. Meat samples were collected aseptically from the butchery houses and transported using icebox to Mekelle University, College of Veterinary Sciences for the isolation and identification of Salmonella species and E. coli, Antimicrobial susceptibility patterns were determined using Kirby disc diffusion method. Data obtained were cleaned and entered into Statistical Package for the Social Sciences version 22 and logistic regression models with odds ratio were calculated. P-value < 0.05 was considered as statistically significant. Results: A total of 153 out of 384 (39.8%) of the meat specimens were found to be contaminated. The contamination of Salmonella species and E. coli were 15.6% (n=60) and 20.8%) (n=80), respectively. Mixed contamination (Salmonella species and E. coli) was observed in 13 (3.4 %) of the analyzed. Poor washing hands regularly (AOR = 8.37; 95% CI: 2.75-25.50) and not using gloves during meat handling (AOR=11. 28; 95% CI: (4.69 27.10) were associated with an overall bacterial contamination.About 95.5% of the tested isolates were sensitive to chloramphenicol and norfloxacin while the resistance of amoxyclav_amoxicillin and erythromycin were both isolated bacteria species. The overall multidrug resistance pattern for Salmonella and E. coli were 51.4% (n=19) and 31.8% (14), respectively. Conclusion: Of the 153 (153/384) contaminated raw meat, 60 (15.6%) and 80 (20.8%) were contaminated by Salmonella species and E. coli, respectively. Poor hand washing practice and not using glove during meat handling showed significant association with bacterial contamination. Multidrug-resistant showed in Salmonella species and E. coli were 19 (51.4%) and 14 (31.8%), respectively.

Keywords: antimicrobial susceptibility test, butchery houses, e. coli, salmonella species

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Authors: M. Zafar, S. Rasheed, Imran Hashmi

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Very little is concerned about the bacterial contamination in drinking water biofilm which provide a potential source for bacteria to grow and increase rapidly. So as to understand the microbial density in DWDs, a three-month study was carried out. The aim of this study was to examine biofilm in three different pipe materials including PVC, PPR and GI. A set of all these pipe materials was installed in DWDs at nine different locations and assessed on monthly basis. Drinking water quality was evaluated by different parameters and characterization of biofilm. Among various parameters are Temperature, pH, turbidity, TDS, electrical conductivity, BOD, COD, total phosphates, total nitrates, total organic carbon (TOC) free chlorine and total chlorine, coliforms and spread plate counts (SPC) according to standard methods. Predominant species were Bacillus thuringiensis, Pseudomonas fluorescens , Staphylococcus haemolyticus, Bacillus safensis and significant increase in bacterial population was observed in PVC pipes while least in cement pipes. The quantity of DWDs bacteria was directly depended on biofilm bacteria and its increase was correlated with growth and detachment of bacteria from biofilms. Pipe material also affected the microbial community in drinking water distribution network biofilm while Similarity in bacterial species was observed between systems due to same disinfectant dose, time period and plumbing pipes.

Keywords: biofilm, DWDs, pipe material, bacterial population

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Authors: Attila Kiss, Erzsébet Némedi, Zoltán Naár

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As natural prebiotic (non-digestible) carbohydrates stimulate the growth of colon microflora and contribute to maintain the health of the host, analytical studies aiming at revealing the chemical behavior of these beneficial food components came to the forefront of interest. Food processing (especially baking) may lead to a significant conversion of the parent compounds, hence it is of utmost importance to characterize the transformation patterns and the plausible decomposition products formed by thermal degradation. The relevance of this work is confirmed by the wide-spread use of these carbohydrates (fructo-oligosaccharides, cyclodextrins, raffinose and resistant starch) in the food industry. More and more functional foodstuffs are being developed based on prebiotics as bioactive components. 12 different types of oligosaccharides have been investigated in order to reveal their thermal degradation characteristics. Different carbohydrate derivatives (D-fructose and D-glucose oligomers and polymers) have been exposed to elevated temperatures (150 °C 170 °C, 190 °C, 210 °C, and 220 °C) for 10 min. An advanced HPLC method was developed and used to identify the decomposition products of carbohydrates formed as a consequence of thermal treatment. Gradient elution was applied with binary solvent elution (acetonitrile, water) through amine based carbohydrate column. Evaporative light scattering (ELS) proved to be suitable for the reliable detection of the UV/VIS inactive carbohydrate degradation products. These experimental conditions and applied advanced techniques made it possible to survey all the formed intermediers. Change in oligomer distribution was established in cases of all studied prebiotics throughout the thermal treatments. The obtained results indicate increased extent of chain degradation of the carbohydrate moiety at elevated temperatures. Prevalence of oligomers with shorter chain length and even the formation of monomer sugars (D-glucose and D-fructose) might be observed at higher temperatures. Unique oligomer distributions, which have not been described previously are revealed in the case of each studied, specific carbohydrate, which might result in various prebiotic activities. Resistant starches exhibited high stability when being thermal treated. The degradation process has been modeled by a plausible reaction mechanism, in which proton catalyzed degradation and chain cleavage take place.

Keywords: prebiotics, thermal degradation, fructo-oligosaccharide, HPLC, ELS detection

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Authors: Said Abdirasak Abidrahman, Ibrahim Mohamed

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Background: Urinary Tract Infections (UTIs) are the commonest infections described among diabetes mellitus patients. More often, empirical antimicrobial therapy is initiated before the laboratory results are made available with minimal treatment success. The knowledge of the etiology and antibiotic susceptibility patterns of the organisms causing urinary tract infections among diabetes mellitus patients remains scarce, despite its vitality. This study sought to determine the prevalence, bacteria species, and drug susceptibility patterns of common causes of urinary tract infections among diabetes mellitus patients attending Bosaso health centers. Materials and methods: We conducted a cross-sectional study involving adult diabetic patients at Bosaso health centers between the months of May and July 2020. Laboratory assay of mid-stream urine samples was done to isolate bacteria causes of UTIs. These were biochemically identified using Gram stain, Kligler iron agar (KIA), Indole test, citrate, urea, coagulase, catalase, motility agar, and lysine iron agar. Their antibiotic susceptibility pattern for the isolated organisms was made for Ampicillin 10μg, Ciprofloxacin 5μg, Cotrimoxazole 25μg, Gentamycin 10μg, Ceftriaxone 10μg, and determined using the Kirby Bauer Disc Diffusion method. Results: Of 177 participants, 69 (39.0%) were males and 108 (61.0%) were females. Their mean age was 33.1 years (range; 18-67 years). Of these, 14.7% (26/177) of the samples revealed significant growth (>= 105 CFU/mL) giving a prevalence of 14.9 % (95% CI: 10.6 to 16.3). The organisms isolated were Escherichia coli -50% (N=13), Klebsiella pneumonia 30.8% (N=8), Staphylococcus aureus 15.4% (N=4), and unidentified organism 3.8% (N=1), and these were associated with such socio-demographic factors like history of catheterization and sexual activity. Antibiotic susceptibility to the commonly used agents for treating UTIs indicated higher sensitivity to Gentamicin and Ceftriaxone.

Keywords: antimicrobials, bacteria, urinary tract infections, diabetes

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Authors: Siriporn Okonogi, Temsiri Suwan, Sakornrat Khongkhunthian, Jakkapan Sirithunyalug

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In this study, silver nanoparticles (AgNPs) were prepared using ascorbic acid as a reducing agent and silver nitrate as a precursor. The effects of gelatin (G) on particle characteristics and dental pathogen inhibition were investigated. The spectra of AgNPs and G-AgNPs were compared using UV-Vis and Energy-dispersive X-ray (EDX) spectroscopy. The obtained AgNPs and G-AgNPs showed the maximum absorption at 410 and 430 nm, respectively, and EDX spectra of both systems confirmed Ag element. Scanning electron microscope showed that AgNPs and G-AgNPs were spherical in shape. Particles size, size distribution, and zeta potential were determined using dynamic light scattering approach. The size of AgNPs and G-AgNPs were 56 ± 2.4 and 67 ± 3.6 nm, respectively with a size distribution of 0.23 ± 0.03 and 0.19 ± 0.02, respectively. AgNPs and G-AgNPs exhibited negative zeta potential of 24.1 ± 2.7 mV and 32.7 ± 1.2 mV, respectively. Minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of the obtained AgNPs and G-AgNPs against three strains of dental pathogenic bacteria; Streptococcus gordonii, Streptococcus mutans, and Staphylococcus aureus were determined using broth dilution method. AgNPs and G-AgNPs showed the strongest inhibition against S. gordonii with the MIC of 0.05 and 0.025 mg/mL, respectively and the MBC of 0.1 and 0.05 mg/mL, respectively. Cytotoxicity test of AgNPs and G-AgNPs on human breast cancer cells using MTT assay indicated that G-AgNPs (0.1 mg/mL) was significantly stronger toxic than AgNPs with the cell inhibition of 91.1 ± 5.4%. G-AgNPs showed significantly less aggregation after storage at room temperature for 90 days than G-AgNPs.

Keywords: antipathogenic activity, ascorbic acid, cytotoxicity, stability

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Authors: Oleg Vlasovets, Fabian Schaipp, Christian L. Mueller

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we conduct a network analysis and predict the sex of 1000 participants based on ”connectome” - pairwise Pearson’s correlation across 436 brain parcels. We solve the non-smooth convex optimization problem, known under the name of Graphical Lasso, where the solution includes a low-rank component. With this solution and machine learning model for a sex prediction, we explain the brain parcels-sex connectivity patterns.

Keywords: network analysis, neuroscience, machine learning, optimization

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