Search results for: erosivity potential

Authors: Fnu Asina, Ivana Brzonova, Keith Voeller, Yun Ji, Alena Kubatova, Evguenii Kozliak

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Lignin, a heterogeneous three-dimensional biopolymer, is one of the building blocks of lignocellulosic biomass. Due to its limited chemical reactivity, lignin is currently processed as a low-value by-product in pulp and paper mills. Among various industrial lignins, Kraft lignin represents a major source of by-products generated during the widely employed pulping process across the pulp and paper industry. Therefore, valorization of Kraft lignin holds great potential as this would provide a readily available source of aromatic compounds for various industrial applications. Microbial degradation is well known for using both highly specific ligninolytic enzymes secreted by microorganisms and mild operating conditions compared with conventional chemical approaches. In this study, the degradation of Indulin AT lignin was assessed by comparing the effects of Basidiomycetous fungi (Coriolus versicolour and Trametes gallica) and Actinobacteria (Mycobacterium sp. and Streptomyces sp.) to two commercial laccases, T. versicolour ( ≥ 10 U/mg) and C. versicolour ( ≥ 0.3 U/mg). After 54 days of cultivation, the extent of microbial degradation was significantly higher than that of commercial laccases, reaching a maximum of 38 wt% degradation for C. versicolour treated samples. Lignin degradation was further confirmed by thermal carbon analysis with a five-step temperature protocol. Compared with commercial laccases, a significant decrease in char formation at 850ºC was observed among all microbial-degraded lignins with a corresponding carbon percentage increase from 200ºC to 500ºC. To complement the carbon analysis result, chemical characterization of the degraded products at different stages of the delignification by microorganisms and commercial laccases was performed by Pyrolysis-GC-MS.

Keywords: lignin, microbial degradation, pyrolysis-GC-MS, thermal carbon analysis

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Authors: Rajnarayan Damor, Gayatri Swarnakar

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Fasciola gigantica are present in the biliary ducts of liver and gall bladder of domestic buffaloes. They are very harmful and causes significant lose to live stock owners, on account of poor growth and lower productivity of domestic buffaloes. Synthetic veterinary drugs have been used to eliminate parasites from cattle but these drugs are unaffordable and inaccessible for poor cattle farmers. The in vitro anthelmintic effect of Citrullus colocynthis fruit extract against Fasciola gigantica parasites were observed by light and scanning electron microscopy. Fruit extracts of C. colocynthis exhibit highest mortality 100% at 50 mg/ml in 15th hour of exposure. The oral and ventral sucker appeared to be slightly more swollen than control and synthetic drug albendazole. The tegument showed submerged spines by the swollen tegument around them. The tegument of the middle region showed deep furrows, folding and submerged spines which either lied very flat against the surface or had become submerged in the tegument by the swollen tegument around them leaving deep furrows. Posterior region showed with deep folding in the tegument, completely disappearance of spines and swelling of the tegument led to completely submerged spines leaving spine socket. The present study revealed that fruit extracts of Citrullus colocynthis found to be potential sources for novel anthelmintic and justify their ethno-veterinary use.

Keywords: anthelmintic, buffalo, Citrullus colocynthis, Fasciola gigantica, mortality, tegument

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Authors: Muhammad Bilal Qadir, Danish Umer, Amir Shahzad

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The use of conductive materials in smart and interactive textiles is gaining significant importance for creating value addition, innovation, and functional product development. These products find their potential applications in health monitoring, military, protection, communication, sensing, monitoring, actuation, fashion, and lifestyles. The materials which are most commonly employed in such type of interactive textile include intrinsically conducting polymers, conductive inks, and metallic coating on textile fabrics and inherently conducting metallic fibre yarns. In this study, silver coated polyester filament yarn is explored for the development of multifunctional interactive gloves. The composite yarn was developed by covering the silver coated polyester filament around the polyester spun yarn using hollow spindle technique. The electrical and tensile properties of the yarn were studied. This novel yarn was used to manufacture a smart glove to explore the antibacterial, functional, and interactive properties of the yarn. The change in electrical resistance due to finger movement at different bending positions and antimicrobial properties were studied. This glove was also found useful as an interactive tool to operate the commonly used touch screen devices due to its conductive nature. The yarn can also be used to develop the sensing elements like stretch, strain, and piezoresistive sensors. Such sensor can be effectively used in medical and sports textile for performance monitoring, vital signs monitoring and development of antibacterial textile for healthcare and hygiene.

Keywords: conductive yarn, interactive textiles, piezoresistive sensors, smart gloves

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Authors: Farhad Eizakshiri

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The potential for groupthink to explain the issues contributing to deterioration of decision-making ability within the unitary team and so to cause poor outcomes attracted a great deal of attention from a variety of disciplines, including psychology, social and organizational studies, political science, and others. Yet what remains unclear is how and why the team members’ strivings for unanimity and cohesion override their motivation to realistically appraise alternative courses of action. In this paper, the findings of a sequential explanatory mixed-methods research containing an experiment with thirty groups of three persons each and interviews with all experimental groups to investigate this issue is reported. The experiment sought to examine how individuals aggregate their views in order to reach a consensual group decision concerning the completion time of a task. The results indicated that groups made better estimates when they had no interaction between members in comparison with the situation that groups collectively agreed on time estimates. To understand the reasons, the qualitative data and informal observations collected during the task were analyzed through conversation analysis, thus leading to four reasons that caused teams to neglect divergent viewpoints and reduce the number of ideas being considered. Reasons found were the concurrence-seeking tendency, pressure on dissenters, self-censorship, and the illusion of invulnerability. It is suggested that understanding the dynamics behind the aforementioned reasons of groupthink will help project teams to avoid making premature group decisions by enhancing careful evaluation of available information and analysis of available decision alternatives and choices.

Keywords: groupthink, group decision, cohesiveness, project teams, mixed-methods research

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Authors: Temesgen Kassa Getahun, Gezahegn Mamo, Beksisa Urge

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A cross-sectional study was conducted from December 2019 to May 2020 with the aim of determining the seroprevalence of brucellosis in dairy cows and their owners in the central highland of Oromia, Ethiopia. A total of 352 blood samples from dairy cattle, 149 from animal owners, and 17 from farm workers were collected and initially screened using the Rose Bengal Plate test and confirmed by the Complement Fixation test. Overall seroprevalence was 0.6% (95% CI: 0.0016–0.0209) in bovines and 1.2% (95% CI: 0.0032–0.0427) in humans. Market-based stock replacement (OR=16.55, p=0.002), breeding by artificial insemination (OR=7.58, p=0.05), and parturition pen (OR = 11.511, p=0.027) were found to be significantly associated with the seropositivity for Brucella infection in dairy cattle. Human housing (OR=1.8, p=0.002), contact with an aborted fetus (OR=21.19, p=0.017), drinking raw milk from non-aborted (OR=24.99, p=0.012), aborted (OR=5.72, p=0.019) and retained fetal membrane (OR=4.22, p=0.029) cows had a significant influence on human brucellosis. A structured interview question was administered to 284 respondents. Accordingly, most respondents had no knowledge of brucellosis (93.3%), and in contrast, 90% of them consumed raw milk. In conclusion, the present seroprevalence study revealed that brucellosis was low among dairy cattle and exposed individuals in the study areas. However, since there were no control strategies implemented in the study areas, there is a potential risk of transmission of brucellosis in dairy cattle and the exposed human population in the study areas. Implementation of a test and slaughter strategy with compensation to farmers is recommended, while in the case of human brucellosis, continuous social training and implementing one health approach framework must be applied.

Keywords: abortion, bovine brucellosis, human brucellosis, risk factors, seroprevalence

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Authors: A. Sewell

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The paper reports a research project which investigated the social interactions of nine to ten-year-olds in a mainstream primary school. The project implemented an adaption of a whole class, behavioural intervention known as 'The Good Behaviour Game (TGBG)'. TGBG is an evidence-based intervention traditionally used to reduce low-level disruptive behaviours in a classroom setting. TGBG was adapted to encourage pupil’s engagement in pro-social behaviour during lessons. A mixed methods research design was employed to evaluate intervention effects and pupil’s perceptions of their social interactions and relationships with others. Single-case research design was used to evaluate behaviour change, and Personal Construct Psychology (PCP) repertory grids were used to explore pupil’s perceptions. The findings demonstrated that TGBG could be successfully adapted to positively influence pupil’s engagement in pro-social behaviours. The findings from the PCP repertory grid interviews revealed the complexities of how children construct their social interactions and relationships with others, and how an understanding of these could be used to design better social skills interventions. It is concluded that TGBG is a cost-effective, simple to implement intervention for promoting positive social interactions and relationships at the whole class level. The paper presents the aims, design, findings, and conclusions of the study in further detail and relates limitations and potential future extensions of the research. The outcomes have direct application and relevance for practitioners interested in children’s social development and how to promote positive outcomes in this critical aspect of childhood.

Keywords: social skills, social development, social competency, the good behaviour game

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Authors: Kyu Bum Han, Eunjin Jeon, Kimberly Watts, Brenda Payan Medina

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Gen3 Concentrating Solar Power (CSP) high-temperature thermal systems have the potential to lower the cost of a CSP system. When compared to the other systems (chloride salt blends and supercritical fluids), the particle transport system can avoid many of the issues associated with high fluid temperature systems at high temperature because of its ability to operate at ambient pressure with limited corrosion or thermal stability risk. Furthermore, identifying and demonstrating low-cost particles that have excellent optical properties and durability can significantly reduce the levelized cost of electricity (LCOE) of particle receivers. The currently available thermal transfer particle in the study and market is oxidized at about 700oC, which reduces its durability, generates particle loss by high friction loads, and causes the color change. To meet the CSP SunShot goal, the durability of particles must be improved by identifying particles that are less abrasive to other structural materials. Furthermore, the particles must be economically affordable and the solar absorptance of the particles must be increased while minimizing thermal emittance. We are studying a novel thermal transfer particle, which has low cost, high durability, and high solar absorptance at high temperatures. The particle minimizes thermal emittance and will be less abrasive to other structural materials. Additionally, the particle demonstrates reusability, which significantly lowers the LCOE. This study will contribute to two principal disciplines of energy science: materials synthesis and manufacturing. Developing this particle for thermal transfer will have a positive impact on the ceramic study and industry as well as the society.

Keywords: concentrating solar power, thermal energy storage, particle, reusability, economics

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Authors: Bachir Redouane, Dib Nihel, Bedrane Sumeya, Blanco Ginesa, Calvino José Juan

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Furfural, a key biomass-derived platform compound, holds significant potential for biofuel production and the synthesis of high-value intermediates. This study investigates the hydrogenation-condensation reaction of furfural issued from lignocellulosique biomass with isopropyl alcohol to produce isopropylfurfuryl ether (iPFE), a next-generation synfuel with a high-octane number. iPFE’s water stability and resistance to methanol absorption make it a sustainable alternative to conventional gasoline additives, offering comparable performance. The catalyst used in this reaction is based on NiAl layered double hydroxides (LDH), with zirconium incorporated to enhance the distribution and structure of active sites. Gold (Au) was deposited on the NiAlZr-LDH support to improve selectivity and yield. The addition of Zr improved the thermal and mechanical stability of the catalyst, while the Au modification further increased selectivity toward iPFE. Extensive catalytic experiments were conducted to optimize reaction conditions, including temperature, hydrogen pressure, and Au loading, to maximize iPFE yield. The results demonstrate a high conversion rate of furfural, exceeding 90% under optimal conditions, with enhanced selectivity toward iPFE. Moreover, iPFE was shown to have a higher-octane number compared to traditional furfuryl ethers, making it a highly promising candidate for advanced fuel applications.

Keywords: Au-NiAlZr-LDH, biofuels, furfural, green chemistry, hydrogenation, isopropylfurfuryl ether, octane number.

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Authors: Mehrnoosh Abouzari, Shahrokh Shahraei

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With the development of artificial intelligence in the present age, intelligent machines and systems have proven their actual and potential capabilities and are mindful of increasing their presence in various fields of human life in the fields of industry, financial transactions, marketing, manufacturing, service affairs, politics, economics and various branches of the humanities .Therefore, despite the conservatism and prudence of law enforcement, the traces of artificial intelligence can be seen in various areas of law. Including judicial robotics capability estimation, intelligent judicial decision making system, intelligent defender and attorney strategy adjustment, dissemination and regulation of different and scattered laws in each case to achieve judicial coherence and reduce opinion, reduce prolonged hearing and discontent compared to the current legal system with designing rule-based systems, case-based, knowledge-based systems, etc. are efforts to apply AI in law. In this article, we will identify the ways in which AI is applied in its laws and regulations, identify the dominant concerns in this area and outline the relationship between these two areas in order to answer the question of how artificial intelligence can be used in different areas of law and what the implications of this application will be. The authors believe that the use of artificial intelligence in the three areas of legislative, judiciary and executive power can be very effective in governments' decisions and smart governance, and helping to reach smart communities across human and geographical boundaries that humanity's long-held dream of achieving is a global village free of violence and personalization and human error. Therefore, in this article, we are going to analyze the dimensions of how to use artificial intelligence in the three legislative, judicial and executive branches of government in order to realize its application.

Keywords: artificial intelligence, law, intelligent system, judge

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Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

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In this work, we use machine learning and novel data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. To the best of our knowledge, this is the first work to apply modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

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Authors: Ahlem Nefzi, Rania Aydi Ben Abdallah, Hayfa Jabnoun-Khiareddine, Nawaim Ammar, Sined Medimagh-Saidana, Mejda Daami-Remadi

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In the present study, leaf, stem, and fruit aqueous extracts of native wild Solanum linnaeanum L. were screened for their ability to suppress Fusarium Crown and Root Rot disease and to enhance tomato (Solanum lycopersicum L.) growth under greenhouse conditions. Leaf extract used at 30% w/v was the most effective in reducing leaf and root damage index by 92.3% and the extent of vascular discoloration by 97.56% compared to Fusarium oxyxporum f. sp radicis lycopersici -inoculated and untreated control. A significant promotion of growth parameters (root length, shoot height, root and shoot biomass and stem diameter) was recorded on tomato cv. Rio Grande seedlings by 40.3-94.1% as compared to FORL inoculated control and by 9.6-88.8% over pathogen-free control. All S. linnaeanum aqueous extracts tested significantly stimulated the germination by 10.2 to 80.1% relative to the untreated control. FORL mycelial growth, assessed using the poisoned food technique, varied depending on plant organs, extracts, and concentrations used. Butanolic extracts were the most active, leading to 60.81% decrease in FORL mycelial growth. HPLC analysis of butanolic extract revealed the presence of thirteen phenolic compounds. Thus, S. linnaeanum can be explored as a potential natural source of antifungal and biofertilizing compounds.

Keywords: antifungal activity, HPLC-MS analysis, Fusarium oxysporum f. sp. radicis-lycopersici, tomato growth

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Authors: Abdul Muqsit Abbasi, Ibrahim Chhipa, Asad Anwer, Saad Farooq, Hassan Berry, Sonu Kumar, Sundar Ali, Muhammad Owais Mahmood, Areeb Ur Rehman, Bahram Baloch

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Accurate translation between structurally diverse languages, such as Arabic and English, presents a critical challenge in natural language processing due to significant linguistic and cultural differences. This paper investigates the effectiveness of Facebook’s mBART model, fine-tuned specifically for sequence-tosequence (seq2seq) translation tasks between Arabic and English, and enhanced through advanced refinement techniques. Our approach leverages the Alef Dataset, a meticulously curated parallel corpus spanning various domains to capture the linguistic richness, nuances, and contextual accuracy essential for high-quality translation. We further refine the model’s output using advanced language models such as GPT-3.5 and GPT-4, which improve fluency, coherence, and correct grammatical errors in translated texts. The fine-tuned model demonstrates substantial improvements, achieving a BLEU score of 38.97, METEOR score of 58.11, and TER score of 56.33, surpassing widely used systems such as Google Translate. These results underscore the potential of mBART, combined with refinement strategies, to bridge the translation gap between Arabic and English, providing a reliable, context-aware machine translation solution that is robust across diverse linguistic contexts.

Keywords: natural language processing, machine translation, fine-tuning, Arabic-English translation, transformer models, seq2seq translation, translation evaluation metrics, cross-linguistic communication

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Authors: Saqib Ali

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Sources are classified into two depending upon the factor of reviving. These sources, which cannot be revived into their original shape once they are consumed, are considered as nonrenewable energy resources, i.e., (coal, fuel) Moreover, those energy resources which are revivable to the original condition even after being consumed are known as renewable energy resources, i.e., (wind, solar, hydel) Renewable energy is a cost-effective way to generate clean and green electrical energy Now a day’s majority of the countries are paying heed to energy generation from RES Pakistan is mostly relying on conventional energy resources which are mostly nonrenewable in nature coal, fuel is one of the major resources, and with the advent of time their prices are increasing on the other hand RES have great potential in the country with the deployment of RES greater reliability and an effective power system can be obtained In this thesis, a similar concept is being used and a hybrid power system is proposed which is composed of intermixing of renewable and nonrenewable sources The Source side is composed of solar, wind, fuel cells which will be used in an optimal manner to serve load The goal is to provide an economical, reliable, uninterruptable power supply. This is achieved by optimal controller (PI, PD, PID, FOPID) Optimization techniques are applied to the controllers to achieve the desired results. Advanced algorithms (Particle swarm optimization, Flower Pollination Algorithm) will be used to extract the desired output from the controller Detailed comparison in the form of tables and results will be provided, which will highlight the efficiency of the proposed system.

Keywords: distributed generation, demand-side management, hybrid power system, micro grid, renewable energy resources, supply-side management

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Authors: Aymen Laadhari

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The cardiovascular system is centered on the heart and is characterized by a very complex structure with different physical scales in space (e.g. micrometers for erythrocytes and centimeters for organs) and time (e.g. milliseconds for human brain activity and several years for development of some pathologies). The development and numerical implementation of mathematical models of the cardiovascular system is a tremendously challenging topic at the theoretical and computational levels, inducing consequently a growing interest over the past decade. The accurate computational investigations in both healthy and pathological cases of processes related to the functioning of the human cardiovascular system can be of great potential in tackling several problems of clinical relevance and in improving the diagnosis of specific diseases. In this talk, we focus on the specific task of simulating three particular phenomena related to the cardiovascular system on the macroscopic, mesoscopic and microscopic scales, respectively. Namely, we develop numerical methodologies tailored for the simulation of (i) the haemodynamics (i.e., fluid mechanics of blood) in the aorta and sinus of Valsalva interacting with highly deformable thin leaflets, (ii) the hyperelastic anisotropic behaviour of cardiomyocytes and the influence of calcium concentrations on the contraction of single cells, and (iii) the dynamics of red blood cells in microvasculature. For each problem, we present an appropriate fully Eulerian finite element methodology. We report several numerical examples to address in detail the relevance of the mathematical models in terms of physiological meaning and to illustrate the accuracy and efficiency of the numerical methods.

Keywords: finite element method, cardiovascular system, Eulerian framework, haemodynamics, heart valve, cardiomyocyte, red blood cell

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Authors: Rajani Kant Rai, Jayakrishnan Athipet

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There have been several attempts to prepare polymers with antimicrobial properties by doping with various N-halamines. Hydantoins (Cyclic N-halamine) is of importance due to their stability rechargeable chloroamide function, broad-spectrum anti-microbial action and ability to prevent resistance to the organisms. Polymerizable hydantoins are synthesized by tethering vinyl moieties to 5,5,-dialkyl hydantoin sacrificing the imide hydrogen in the molecule thereby restricting the halogen capture only to the amide nitrogen that results in compromised antibacterial activity. In order to increase the activity of the antimicrobial polymer, we have developed a scheme to maximize the attachment of chlorine to the amide and the imide moieties of hydantoin. Vinyl hydantoin monomer, (Z)-5-(4-((3-methylbuta-1,3-dien-2-yl)oxy)benzylidene)imidazolidine-2,4-dione (MBBID) was synthesized and copolymerized with a commercially available monomer, methyl methacrylate, by free radical polymerization. The antimicrobial activity of hydantoin is strongly dependent on their surface area and hence their microbial activity increases when incorporated in microspheres or nanoparticles as compared to their bulk counterpart. In this regard, smooth and rough surface microsphere of the vinyl monomer (MBBID) with commercial monomer was synthesized. The oxidative chlorine content of the copolymer ranged from 1.5 to 2.45 %. Further, to demonstrate the water purification potential, the thin column was packed with smooth or rough microspheres and challenged with simulated contaminated water that exhibited 6 log kill (total kill) of the bacteria in 20 minutes of exposure with smooth (25 mg/ml) and rough microsphere (15.0 mg/ml).

Keywords: cyclic N-halamine, vinyl hydantoin monomer, rough surface microsphere, simulated contaminated water

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Authors: T. Hopkin, S. Lu, P. Rogers, M. Sexton

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Housing Associations (HAs) contribute circa 20% of the UK’s housing supply. HAs are however under increasing pressure as a result of funding cuts and rent reductions. Due to the increased pressure, a number of processes are currently being reviewed by HAs, especially how they manage and learn from defects. Learning from defects is considered a useful approach to achieving defect reduction within the UK housebuilding industry. This paper contributes to our understanding of how HAs learn from defects by undertaking an initial round table discussion with key HA stakeholders as part of an ongoing collaborative research project with the National House Building Council (NHBC) to better understand how house builders and HAs learn from defects to reduce their prevalence. The initial discussion shows that defect information runs through a number of groups, both internal and external of a HA during both the defects management process and organizational learning (OL) process. Furthermore, HAs are reliant on capturing and recording defect data as the foundation for the OL process. During the OL process defect data analysis is the primary enabler to recognizing a need for a change to organizational routines. When a need for change has been recognized, new options are typically pursued to design out defects via updates to a HAs Employer’s Requirements. Proposed solutions are selected by a review board and committed to organizational routine. After implementing a change, both structured and unstructured feedback is sought to establish the change’s success. The findings from the HA discussion demonstrates that OL can achieve defect reduction within the house building sector in the UK. The paper concludes by outlining a potential ‘learning from defects model’ for the housebuilding industry as well as describing future work.

Keywords: defects, new homes, housing association, organizational learning

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Authors: Balakrishna Valluru, Ruth Suckling

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A 16 year old male was found collapsed on the road following stab injuries to the chest and abdomen and was transported to the emergency department by ambulance. On arrival in the emergency department the patient was breathless and appeared pale. He was maintaining his airway with spontaneous breathing and had a heart rate of 122 beats per minute with a blood pressure of 83/63 mmHg. He was resuscitated initially with three units of packed red cells. Clinical examination identified three incisional wounds each measuring 2 cm. These were in the left para-sternal region, right infra-scapular region and left upper quadrant of the abdomen. The chest wound over the left parasternal area at the level of 4tth intercostal space was bleeding intermittently on leaning forwards and was relieving his breathlessness intermittently. CT imaging was performed to characterize his injuries and determine his management. CT scan of chest and abdomen showed moderate size haemopericardium with left sided haemopneumothorax. The patient underwent urgent surgical repair of the left ventricle and left anterior descending artery. He recovered without complications and was discharged from the hospital. This case highlights the fact that the potential to develop a life threatening cardiac tamponade was mitigated by the left parasternal stab wound. This injury fortuitously provided a pericardial window through which the bleeding from the injured left ventricle and left anterior descending artery could drain into the left hemithorax providing an opportunity for timely surgical intervention to repair the cardiac injuries.

Keywords: stab, incisional, haemo-pericardium, haemo-pneumothorax

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Authors: Oluseyi O. Ajayi, Ohiose D. Ohijeagbon, Mercy Ogbonnaya, Ameh Attabo

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The study assessed the potential and economic viability of stand-alone wind systems for embedded generation, taking into account its benefits to small off-grid rural communities at 40 meteorological sites in Nigeria. A specific electric load profile was developed to accommodate communities consisting of 200 homes, a school and a community health centre. This load profile was incorporated within the distributed generation analysis producing energy in the MW range, while optimally meeting daily load demand for the rural communities. Twenty-four years (1987 to 2010) of wind speed data at a height of 10m utilized for the study were sourced from the Nigeria Meteorological Department, Oshodi. The HOMER® software optimizing tool was engaged for the feasibility study and design. Each site was suited to 3MW wind turbines in sets of five, thus 15MW was designed for each site. This design configuration was adopted in order to easily compare the distributed generation system amongst the sites to determine their relative economic viability in terms of life cycle cost, as well as levelised cost of producing energy. A net present value was estimated in terms of life cycle cost for 25 of the 40 meteorological sites. On the other hand, the remaining sites yielded a net present cost; meaning the installations at these locations were not economically viable when utilizing the present tariff regime for embedded generation in Nigeria.

Keywords: wind speed, wind power, distributed generation, cost per kilowatt-hour, clean energy, Nigeria

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Authors: Shetie Gatew

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Current soil maps of Ethiopia do not represent accurately the soils of Nech Sar National Park. In the framework of studies on the ecology of the park, we prepared a soil map based on field observations and a digital terrain model derived from SRTM data with a 30-m resolution. The landscape comprises volcanic cones, lava and basalt outflows, undulating plains, horsts, alluvial plains and river deltas. SOTER-like terrain mapping units were identified. First, the DTM was classified into 128 terrain classes defined by slope gradient (4 classes), relief intensity (4 classes), potential drainage density (2 classes), and hypsometry (4 classes). A soil-landscape relation between the terrain mapping units and WRB soil units was established based on 34 soil profile pits. Based on this relation, the terrain mapping units were either merged or split to represent a comprehensive soil and terrain map. The soil map indicates that Leptosols (30 %), Cambisols (26%), Andosols (21%), Fluvisols (12 %), and Vertisols (9%) are the most widespread Reference Soil Groups of the park. In contrast, the harmonized soil map of Africa derived from the FAO soil map of the world indicates that Luvisols (70%), Vertisols (14%) and Fluvisols (16%) would be the most common Reference Soil Groups. However, these latter mapping units are not consistent with the topography, nor did we find such extensive areas occupied by Luvisols during the field survey. This case study shows that with the now freely available SRTM data, it is possible to improve current soil information layers with relatively limited resources, even in a complex terrain like Nech Sar National Park.

Keywords: andosols, cambisols, digital elevation model, leptosols, soil-landscaps relation

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Authors: Rabih Ghostine, Craig Kapfer, Viswanathan Kannan, Ibrahim Hoteit

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Urban flooding resulting from a sudden release of water due to dam-break or excessive rainfall is a serious threatening environment hazard, which causes loss of human life and large economic losses. Anticipating floods before they occur could minimize human and economic losses through the implementation of appropriate protection, provision, and rescue plans. This work reports on the numerical modelling of flash flood propagation in urban areas after an excessive rainfall event or dam-break. A two-dimensional (2D) depth-averaged shallow water model is used with a refined unstructured grid of triangles for representing the urban area topography. The 2D shallow water equations are solved using a second-order well-balanced discontinuous Galerkin scheme. Theoretical test case and three flood events are described to demonstrate the potential benefits of the scheme: (i) wetting and drying in a parabolic basin (ii) flash flood over a physical model of the urbanized Toce River valley in Italy; (iii) wave propagation on the Reyran river valley in consequence of the Malpasset dam-break in 1959 (France); and (iv) dam-break flood in October 1982 at the town of Sumacarcel (Spain). The capability of the scheme is also verified against alternative models. Computational results compare well with recorded data and show that the scheme is at least as efficient as comparable second-order finite volume schemes, with notable efficiency speedup due to parallelization.

Keywords: dam-break, discontinuous Galerkin scheme, flood modeling, shallow water equations

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Authors: Kalangi Rodrigo

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The term Neuroecology elucidates the study of customizable variation in cognition and the brain. Subject marked the birth since 1980s, when researches began to apply methods of comparative evolutionary biology to cognitive processes and the underlying neural mechanisms of cognition. In Archaeology and Anthropology, we observe behaviors such as social learning skills, innovative feeding and foraging, tool use and social manipulation to determine the cognitive processes of ancient mankind. Depending on the brainstem size was used as a control variable, and phylogeny was controlled using independent contrasts. Both disciplines need to enriched with comparative literature and neurological experimental, behavioral studies among tribal peoples as well as primate groups which will lead the research to a potential end. Neuroecology examines the relations between ecological selection pressure and mankind or sex differences in cognition and the brain. The goal of neuroecology is to understand how natural law acts on perception and its neural apparatus. Furthermore, neuroecology will eventually lead both principal disciplines to Ethology, where human behaviors and social management studies from a biological perspective. It can be either ethnoarchaeological or prehistoric. Archaeology should adopt general approach of neuroecology, phylogenetic comparative methods can be used in the field, and new findings on the cognitive mechanisms and brain structures involved mating systems, social organization, communication and foraging. The contribution of neuroecology to archaeology and anthropology is the information it provides on the selective pressures that have influenced the evolution of cognition and brain structure of the mankind. It will shed a new light to the path of evolutionary studies including behavioral ecology, primate archaeology and cognitive archaeology.

Keywords: Neuroecology, Archaeology, Brain Evolution, Cognitive Archaeology

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Authors: Meng Su

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High-dimensional data analysis often presents challenges in capturing the complex, nonlinear relationships and manifold structures inherent to the data. This article presents a novel approach that leverages the strengths of two powerful techniques, Diffusion Maps and Diffusion Probabilistic Models (DPMs), to address these challenges. By integrating the dimensionality reduction capability of Diffusion Maps with the data modeling ability of DPMs, the proposed method aims to provide a comprehensive solution for analyzing and generating high-dimensional data. The Diffusion Map technique preserves the nonlinear relationships and manifold structure of the data by mapping it to a lower-dimensional space using the eigenvectors of the graph Laplacian matrix. Meanwhile, DPMs capture the dependencies within the data, enabling effective modeling and generation of new data points in the low-dimensional space. The generated data points can then be mapped back to the original high-dimensional space, ensuring consistency with the underlying manifold structure. Through a detailed example implementation, the article demonstrates the potential of the proposed hybrid approach to achieve more accurate and effective modeling and generation of complex, high-dimensional data. Furthermore, it discusses possible applications in various domains, such as image synthesis, time-series forecasting, and anomaly detection, and outlines future research directions for enhancing the scalability, performance, and integration with other machine learning techniques. By combining the strengths of Diffusion Maps and DPMs, this work paves the way for more advanced and robust data analysis methods.

Keywords: diffusion maps, diffusion probabilistic models (DPMs), manifold learning, high-dimensional data analysis

Procedia PDF Downloads 108

Authors: Subhasree Majumdar, Sovan Dey, Sayari Mukherjee, Sourav Dutta, Dalia Dasgupta Mandal

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Bacterial isolates from Planococcus genus are known for the production of yellowish orange pigment that belongs to the carotenoid family. These pigments are of immense pharmacological importance as antioxidant, anticancer, eye and liver protective agent, etc. The production of this pigment in a cost effective manner is a challenging task. The present study explored paper mill sludge (PMS), a solid lignocellulosic waste generated in large quantities from pulp and paper mill industry as a substrate for carotenoid pigment production by Planococcus sp. TRC1. PMS was compared in terms of efficacy with sugarcane bagasse, which is a highly explored substrate for valuable product generation via solid state fermentation. The results showed that both the biomasses yielded the highest carotenoid during 48 hours of incubation, 31.6 mg/gm and 42.1 mg/gm for PMS and bagasse respectively. Compositional alterations of both the biomasses showed reduction in lignin, hemicellulose and cellulose content by 41%, 15%, 1% for PMS and 38%, 25% and 6% for sugarcane bagasse after 72 hours of incubation. Structural changes in the biomasses were examined by FT-IR, FESEM, and XRD which further confirmed modification of solid biomasses by bacterial isolate. This study revealed the potential of PMS to act as cheap substrate for carotenoid pigment production by Planococcus sp. TRC1, as it showed a significant production in comparison to sugarcane bagasse which gave only 1.3 fold higher production than PMS. Delignification of PMS by TRC1 during pigment production is another important finding for the reuse of this waste from the paper industry.

Keywords: carotenoid, lignocellulosic, paper mill sludge, Planococcus sp. TRC1, solid state fermentation, sugarcane bagasse

Procedia PDF Downloads 235

Authors: Iftikhar A. Tayubi, Tabrej Khan, Mansoor M. Alsubei, Fahad A. Alsaferi

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LIZTOXD provides a single source of high-quality information about proteinaceous lizard toxins that will be an invaluable resource for pharmacologists, neuroscientists, toxicologists, medicinal chemists, ion channel scientists, clinicians, and structural biologists. We will provide an intuitive, well-organized and user-friendly web interface that allows users to explore the detail information of Lizard and toxin proteins. It includes common name, scientific name, entry id, entry name, protein name and length of the protein sequence. The utility of this database is that it can provide a user-friendly interface for users to retrieve the information about Lizard, toxin and toxin protein of different Lizard species. These interfaces created in this database will satisfy the demands of the scientific community by providing in-depth knowledge about Lizard and its toxin. In the next phase of our project we will adopt methodology and by using A MySQL and Hypertext Preprocessor (PHP) which and for designing Smart Draw. A database is a wonderful piece of equipment for storing large quantities of data efficiently. The users can thus navigate from one section to another, depending on the field of interest of the user. This database contains a wealth of information on species, toxins, toxins, clinical data etc. LIZTOXD resource that provides comprehensive information about protein toxins from lizard toxins. The combination of specific classification schemes and a rich user interface allows researchers to easily locate and view information on the sequence, structure, and biological activity of these toxins. This manually curated database will be a valuable resource for both basic researchers as well as those interested in potential pharmaceutical and agricultural applications of lizard toxins.

Keywords: LIZTOXD, MySQL, PHP, smart draw

Procedia PDF Downloads 162

Authors: Ankit Sharma, Mudit Sachan, Anurag Prakash

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Rapid growth in data acquisition technologies through drones, have led to advances and interests in collecting high-resolution images of geological fields. Being advantageous in capturing high volume of data in short flights, a number of challenges have to overcome for efficient analysis of this data, especially while data acquisition, image interpretation and processing. We introduce a method that allows effective mapping of geological fields using photogrammetric data of surfaces, drainage area, water bodies etc, which will be captured by airborne vehicles like UAVs, we are not taking satellite images because of problems in adequate resolution, time when it is captured may be 1 yr back, availability problem, difficult to capture exact image, then night vision etc. This method includes advanced automated image interpretation technology and human data interaction to model structures and. First Geological structures will be detected from the primary photographic dataset and the equivalent three dimensional structures would then be identified by digital elevation model. We can calculate dip and its direction by using the above information. The structural map will be generated by adopting a specified methodology starting from choosing the appropriate camera, camera’s mounting system, UAVs design ( based on the area and application), Challenge in air borne systems like Errors in image orientation, payload problem, mosaicing and geo referencing and registering of different images to applying DEM. The paper shows the potential of using our method for accurate and efficient modeling of geological structures, capture particularly from remote, of inaccessible and hazardous sites.

Keywords: digital elevation model, mapping, photogrammetric data analysis, geological structures

Procedia PDF Downloads 686

Authors: Huimin Zhao, Xiaoquan Liu, Haochen Liu

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The major challenge facing Alzheimer's Disease (AD) drug development is how to effectively improve cognitive function in clinical practice. Growing evidence indicates that stimulating hippocampal neurogenesis is a strategy for restoring cognition in animal models of AD. The mitogen-activated protein kinase (MAPK) pathway is a crucial factor in neurogenesis, which is negatively regulated by Dual-specificity phosphatase 16 (DUSP16). Transcriptome analysis of post-mortem brain tissue revealed up-regulation of DUSP16 expression in AD patients. Additionally, DUSP16 was involved in regulating the proliferation and neural differentiation of neural progenitor cells (NPCs). Nevertheless, whether the effect of DUSP16 on ameliorating cognitive disorders by influencing NPCs differentiation in AD mice remains unclear. Our study demonstrates an association between DUSP16 SNPs and clinical progression in individuals with mild cognitive impairment (MCI). Besides, we found that increased DUSP16 expression in both 3×Tg and SAMP8 models of AD led to NPC differentiation impairments. By silencing DUSP16, cognitive benefits, the induction of AHN and synaptic plasticity, were observed in AD mice. Furthermore, we found that DUSP16 is involved in the process of NPC differentiation by regulating c-Jun N-terminal kinase (JNK) phosphorylation. Moreover, the increased DUSP16 may be regulated by the ETS transcription factor (ELK1), which binds to the promoter region of DUSP16. Loss of ELK1 resulted in decreased DUSP16 mRNA and protein levels. Our data uncover a potential regulatory role for DUSP16 in adult hippocampal neurogenesis and provide a possibility to find the target of AD intervention.

Keywords: alzheimer's disease, cognitive function, DUSP16, hippocampal neurogenesis

Procedia PDF Downloads 72

Authors: Andrea Treviño Gavito, Diego Klabjan, Sanjiv J. Shah

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Echocardiograms serve as pivotal resources for clinicians in diagnosing cardiac conditions, offering non-invasive insights into a heart’s structure and function. When echocardiographic studies are conducted, no standardized labeling of the acquired views is performed. Employing machine learning algorithms for automated echocardiogram view detection has emerged as a promising solution to enhance efficiency in echocardiogram use for diagnosis. However, existing approaches predominantly rely on supervised learning, necessitating labor-intensive expert labeling. In this paper, we introduce a fully unsupervised echocardiographic view detection framework that leverages convolutional autoencoders to obtain lower dimensional representations and the K-means algorithm for clustering them into view-related groups. Our approach focuses on discriminative patches from echocardiographic frames. Additionally, we propose a trainable inverse average layer to optimize decoding of average operations. By integrating both public and proprietary datasets, we obtain a marked improvement in model performance when compared to utilizing a proprietary dataset alone. Our experiments show boosts of 15.5% in accuracy and 9.0% in the F-1 score for frame-based clustering, and 25.9% in accuracy and 19.8% in the F-1 score for view-based clustering. Our research highlights the potential of unsupervised learning methodologies and the utilization of open-sourced data in addressing the complexities of echocardiogram interpretation, paving the way for more accurate and efficient cardiac diagnoses.

Keywords: artificial intelligence, echocardiographic view detection, echocardiography, machine learning, self-supervised representation learning, unsupervised learning

Procedia PDF Downloads 33

Authors: Nana Segu Acquaah-Harrison, James Osei Mensah, Richard Aidoo, David Amponsah, Amy Buah, Gilbert Aboagye

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The study aimed at assessing the feasibility of commercial meat rabbit production in the Kumasi Metropolis of Ghana. Structured and unstructured questionnaires were utilized in obtaining information from two hundred meat consumers and 15 meat rabbit farmers. Data were analyzed using Net Present Value (NPV), Internal Rate of Return (IRR), Benefit Cost Ratio (BCR)/Profitability Index (PI) technique, percentages and chi-square contingency test. The study found that the current demand for rabbit meat is low (36%). The desirable nutritional attributes of rabbit meat and other socio economic factors of meat consumers make the potential demand for rabbit meat high (69%). It was estimated that GH¢5,292 (approximately $ 2672) was needed as a start-up capital for a 40-doe unit meat rabbit farm in Kumasi Metropolis. The cost of breeding animals, housing and equipment formed 12.47%, 53.97% and 24.87% respectively of the initial estimated capital. A Net Present Value of GH¢ 5,910.75 (approximately $ 2984) was obtained at the end of the fifth year, with an internal rate return and profitability index of 70% and 1.12 respectively. The major constraints identified in meat rabbit production were low price of rabbit meat, shortage of fodder, pest and diseases, high cost of capital, high cost of operating materials and veterinary care. Based on the analysis, it was concluded that meat rabbit production is feasible in the Kumasi Metropolis of Ghana. The study recommends embarking on mass advertisement; farmer association and adapting to new technologies in the production process will help to enhance productivity.

Keywords: feasibility, commercial meat rabbit, production, Kumasi, Ghana

Procedia PDF Downloads 133

Authors: Michael Karnes, Alper Yilmaz

Abstract:

This paper presents the application of the omni-modeler towards pedestrian redetection. The pedestrian redetection task creates several challenges when applying deep neural networks (DNN) due to the variety of pedestrian appearance with camera position, the variety of environmental conditions, and the specificity required to recognize one pedestrian from another. DNNs require significant training sets and are not easily adapted for changes in class appearances or changes in the set of classes held in its knowledge domain. Pedestrian redetection requires an algorithm that can actively manage its knowledge domain as individuals move in and out of the scene, as well as learn individual appearances from a few frames of a video. The Omni-Modeler is a dynamically learning few-shot visual recognition algorithm developed for tasks with limited training data availability. The Omni-Modeler adapts the knowledge domain of pre-trained deep neural networks to novel concepts with a calculated localized language encoder. The Omni-Modeler knowledge domain is generated by creating a dynamic dictionary of concept definitions, which are directly updatable as new information becomes available. Query images are identified through nearest neighbor comparison to the learned object definitions. The study presented in this paper evaluates its performance in re-identifying individuals as they move through a scene in both single-camera and multi-camera tracking applications. The results demonstrate that the Omni-Modeler shows potential for across-camera view pedestrian redetection and is highly effective for single-camera redetection with a 93% accuracy across 30 individuals using 64 example images for each individual.

Keywords: dynamic learning, few-shot learning, pedestrian redetection, visual recognition

Procedia PDF Downloads 76

Authors: Michael Williams

Abstract:

The ability to control a flowing well is of the utmost important. During the kill phase, heavy weight kill mud is circulated around the well. While increasing bottom hole pressure near wellbore formation, the damage is increased. The addition of high density spherical objects has the potential to minimise this near wellbore damage, increase bottom hole pressure and reduce operational time to kill the well. This operational time saving is seen in the rapid deployment of high density spherical objects instead of building high density drilling fluid. The research aims to model the well kill process using a Computational Fluid Dynamics software. A model has been created as a proof of concept to analyse the flow of micron sized spherical objects in the drilling fluid. Initial results show that this new methodology of spherical objects in drilling fluid agrees with traditional stream lines seen in non-particle flow. Additional models have been created to demonstrate that areas of higher flow rate around the bit can lead to increased probability of wash out of formations but do not affect the flow of micron sized spherical objects. Interestingly, areas that experience dimensional changes such as tool joints and various BHA components do not appear at this initial stage to experience increased velocity or create areas of turbulent flow, which could lead to further borehole stability. In conclusion, the initial models of this novel well control methodology have not demonstrated any adverse flow patterns, which would conclude that this model may be viable under field conditions.

Keywords: well control, fluid mechanics, safety, environment

Procedia PDF Downloads 171