Search results for: innovative teaching-learning techniques

Authors: Mirian Graciella Dalla Porta, Humberto Jorge José, Danielle de Bem Luiz, Regina de F. P. M.Moreira

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Similar to most processing industries, fish processing produces large volumes of wastewater, which contains especially organic contaminants, salts and oils dispersed therein. Different processes have been used for the treatment of fishery wastewaters, but the most commonly used are chemical coagulation and flotation. These techniques are well known but sometimes the characteristics of the treated effluent do not comply with legal standards for discharge. Electrocoagulation (EC) is an electrochemical process that can be used to treat wastewaters in terms of both organic matter and nutrient removal. The process is based on the use of sacrificial electrodes such as aluminum, iron or zinc, that are oxidized to produce metal ions that can be used to coagulate and react with organic matter and nutrients in the wastewater. While EC processes are effective to treatment of several types of wastewaters, applications have been limited due to the high energy demands and high current densities. Generally, the for EC process can be performed without additional chemicals or pre-treatment, but the costs should be reduced for EC processes to become more applicable. In this work, we studied the treatment of a real wastewater from fishmeal industry by electrocoagulation process. Removal efficiencies for chemical oxygen demand (COD), total organic carbon (TOC) turbidity, phosphorous and nitrogen concentration were determined as a function of the operating conditions, such as pH, current density and operating time. The optimum operating conditions were determined to be operating time of 10 minutes, current density 100 A.m-2, and initial pH 4.0. COD, TOC, phosphorous concentration, and turbidity removal efficiencies at the optimum operating conditions were higher than 90% for aluminum electrode. Operating costs at the optimum conditions were calculated as US$ 0.37/m3 (US$ 0.038/kg COD) for Al electrode. These results demonstrate that the EC process is a promising technology to remove nutrients from fishery wastewaters, as the process has both a high efficiency of nutrient removal, and low energy requirements.

Keywords: electrocoagulation, fish, food industry, wastewater

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Authors: Ganeshkumar, Ashika, Valavan, Ramesh, Thangam, Chirayu

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MSCs are found in much higher concentration in the Wharton’s jelly compared to the umbilical cord blood, which is a rich source of hematopoietic stem cells. Umbilical cord tissue is collected at the time of birth; it is processed and stored in liquid nitrogen for future therapeutical purpose. The source of contamination might be either from vaginal tract of mother or from hospital environment or from personal handling during cord tissue sample collection. If the sample were contaminated, decontamination procedure will be done with 70% ethanol (1 minute) in order to avoid sample rejection. Ethanol is effective against a wide range of bacteria, protozoa and fungi and has low toxicity to humans. Among the 1954 samples taken for the study, 24 samples were found to be contaminated with microorganism. The organisms isolated from the positive samples were found to be E. coli, Stenotrophomonas maltophilia, Pseudomonas aueroginosa, Enterococcus fecalis, Acinetobacter bowmani, Staphylococcus epidermidis, Enterobacter cloacae, and Proteus mirabilis. Among these organisms 70% ethanol successfully eliminated E. coli, Enterococcus fecalis, Acinetobacter bowmani, Staphylococcus epidermidis, and Proteus mirabilis. 70% ethanol was unsuccessful in eliminating Stenotrophomonas maltophilia, Pseudomonas aueroginosa, and Enterobacter cloacae. Stenotrophomonas maltophilia and Pseudomonas aueroginosa have the ability to form biofilm that make them resistant to alcohol. Biofilm act as protective layer for bacteria and which protects them from host defense and antibiotic wash. Finally it was found 70% ethanol wash saved 58.3% cord tissue samples from rejection and it is ineffective against 41% of the samples. The contamination rate can be reduced by maintaining proper aseptic techniques during sample collection and processing.

Keywords: umblical cord tissue, decontamination, 70% ethanol effectiveness, contamination

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Authors: Jeisson A. Estrella, Laura C. Herrera, Cristian A. Arenas

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The Colombian electricity sector has been transforming through the insertion of new energy sources to generate electricity, one of them being solar energy, which is being promoted by companies interested in photovoltaic technology. The study of this technology is important for electricity generation in general and for the planning of the sector from the perspective of energy complementarity. Precisely in this last approach is where the project is located; we are interested in answering the concerns about the reliability of the electrical system when climatic phenomena such as El Niño occur or in defining whether it is viable to replace or expand thermoelectric plants. Reliability of the electrical system when climatic phenomena such as El Niño occur, or to define whether it is viable to replace or expand thermoelectric plants with renewable electricity generation systems. In this regard, some difficulties related to the basic information on renewable energy sources from measured data must first be solved, as these come from automatic weather stations. Basic information on renewable energy sources from measured data, since these come from automatic weather stations administered by the Institute of Hydrology, Meteorology and Environmental Studies (IDEAM) and, in the range of study (2005-2019), have significant amounts of missing data. For this reason, the overall objective of the project is to complete the global solar irradiance datasets to obtain time series to develop energy complementarity analyses in a subsequent project. Global solar irradiance data sets to obtain time series that will allow the elaboration of energy complementarity analyses in the following project. The filling of the databases will be done through numerical and statistical methods, which are basic techniques for undergraduate students in technical areas who are starting out as researchers technical areas who are starting out as researchers.

Keywords: time series, global solar irradiance, imputed data, energy complementarity

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Authors: Waldir Roque, Gustavo Oliveira, Moises Santos, Tatiana Simoes

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Increasing the oil recovery factor of an oil reservoir has been a concern of the oil industry. Usually, the production placement zones are defined after some analysis of geological and petrophysical parameters, being the rock porosity, permeability and oil saturation of fundamental importance. In this context, the determination of hydraulic flow units (HFUs) renders an important step in the process of reservoir characterization since it may provide specific regions in the reservoir with similar petrophysical and fluid flow properties and, in particular, techniques supporting the placement of production zones that favour the tracing of directional wells. A HFU is defined as a representative volume of a total reservoir rock in which petrophysical and fluid flow properties are internally consistent and predictably distinct of other reservoir rocks. Technically, a HFU is characterized as a rock region that exhibit flow zone indicator (FZI) points lying on a straight line of the unit slope. The goal of this paper is to provide a trustful indication for oil production placement zones for the best-fit HFUs. The FZI cloud of points can be obtained from the reservoir quality index (RQI), a function of effective porosity and permeability. Considering log and core data the HFUs are identified and using the discrete rock type (DRT) classification, a set of connected cell clusters can be found and by means a graph centrality metric, the maximum closeness (MaxC) cell is obtained for each cluster. Considering the MaxC cells as production zones, an extensive analysis, based on several oil recovery factor and oil cumulative production simulations were done for the SPE Model 2 and the UNISIM-I-D synthetic fields, where the later was build up from public data available from the actual Namorado Field, Campos Basin, in Brazil. The results have shown that the MaxC is actually technically feasible and very reliable as high performance production placement zones.

Keywords: hydraulic flow unit, maximum closeness centrality, oil production simulation, production placement zone

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Authors: Neelma Ashraf

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Actinomycetes, particularly genus Streptomyces is of great importance due to their role in the discovery of new natural products, particularly antimicrobial secondary metabolites in the medicinal science and biotechnology industry. Different Streptomyces strains were isolated from Helianthus annuus plants and tested for antibacterial and antifungal activities. The most promising five strains were chosen for further investigation, and growth conditions for antibiotic synthesis were optimised. The supernatants were extracted in different solvents, and the extracted products were analyzed using liquid chromatography-mass spectrometry (LC-MS) and biological testing. From one of the potent strains Streptomyces globusus sp. BR123, a compound lavendamycin was identified using these analytical techniques. In addition, this potent strain also produces a strong antifungal polyene compound with a quasimolecular ion of 2072. Streptomyces sp. BR123 was genome sequenced because of its promising antimicrobial potential in order to identify the gene cluster responsible for analyzed compound “lavendamycin”. The genome analysis yielded candidate genes responsible for the production of this potent compound. The genome sequence of 8.15 Mb of Streptomyces sp. isolate BR123 with a GC content of 72.63% and 8103 protein coding genes was attained. Many antimicrobial, antiparasitic, and anticancerous compounds were detected through multiple biosynthetic gene clusters predicted by in-Silico analysis. Though, the novelty of metabolites was determined through the insignificant resemblance with known biosynthetic gene clusters. The current study gives insight into the bioactive potential of Streptomyces sp. isolate BR123 with respect to the synthesis of bioactive secondary metabolites through genomic and spectrometric analysis. Moreover, the comparative genome study revealed the connection of isolate BR123 with other Streptomyces strains, which could expand the knowledge of this genus and the mechanism involved in the discovery of new antimicrobial metabolites.

Keywords: streptomyces, secondary metabolites, genome, biosynthetic gene clusters, high performance liquid chromatography, mass spectrometry

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Authors: Wisam Ismail, Brendan Wooler, Penelope McManus

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Introduction: The public perception of implants has been damaged in the wake of recent negative publicity and increasingly we are finding patients wanting to avoid them. Planned lipo-modelling to enhance the volume of a Latissimus dorsi flap is a viable alternative to silicone implants and maintains a Totally Autologous Technique (TAT). Here we demonstrate that when compared to an Implant Assisted Technique (IAT), a TAT offers patients many benefits that offset the requirement of more operations initially, with reduced short and long term complications, reduced symmetrisation surgery and reduced revision rates. Methods. Data was collected prospectively over 7 years. The minimum follows up was 3 years. The technique was generally standardized in the hand of one surgeon. All flaps were extended LD flaps (ELD). Lipo-modelling was performed using standard techniques. Outcome measures were unplanned secondary procedures, complication rates, and contralateral symmetrisation surgery rates. Key Results Were: Lower complication rates in the TAT group (18.5% vs. 33.3%), despite higher radiotherapy rates (TAT=49%, IAT=36.8%), TAT was associated with lower subsequent symmetrisation rates (30.6% vs. 50.9%), IAT had a relative risk of 3.1 for subsequent unplanned procedure, Autologous patients required an average of 1.76 sessions of lipo-modelling, Conclusions: Using lipo-modelling to enable totally autologous LD reconstruction offers significant advantages over an implant assisted technique. We have shown a lower subsequent unplanned procedure rate, lower revision surgery, and less contralateral symmetrisation surgery. We anticipate that a TAT will be supported by patient satisfaction surveys and long-term patient-reported cosmetic outcome data and intended to study this.

Keywords: breast, Latissimus dorsi, lipomodelling, reconstruction

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Authors: K. R. Roopesh Bharatwaj, Avinash Maharana, Favour Tobi Aborisade, Roger Young

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Presently, there are few cases of complete automation of drones and its allied intelligence capabilities. In essence, the potential of the drone has not yet been fully utilized. This paper presents feasible methods to build an intelligent drone with smart capabilities such as self-driving, and obstacle avoidance. It does this through advanced Reinforcement Learning Techniques and performs object detection using latest advanced algorithms, which are capable of processing light weight models with fast training in real time instances. For the scope of this paper, after researching on the various algorithms and comparing them, we finally implemented the Deep-Q-Networks (DQN) algorithm in the AirSim Simulator. In future works, we plan to implement further advanced self-driving and object detection algorithms, we also plan to implement voice-based speech recognition for the entire drone operation which would provide an option of speech communication between users (People) and the drone in the time of unavoidable circumstances. Thus, making drones an interactive intelligent Robotic Voice Enabled Service Assistant. This proposed drone has a wide scope of usability and is applicable in scenarios such as Disaster management, Air Transport of essentials, Agriculture, Manufacturing, Monitoring people movements in public area, and Defense. Also discussed, is the entire drone communication based on the satellite broadband Internet technology for faster computation and seamless communication service for uninterrupted network during disasters and remote location operations. This paper will explain the feasible algorithms required to go about achieving this goal and is more of a reference paper for future researchers going down this path.

Keywords: convolution neural network, natural language processing, obstacle avoidance, satellite broadband technology, self-driving

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Authors: Jean Paul Hategekimana, Dukuzumuremyi Yvonne, Mukeshimana Marthe, Alexandre Niyonshima

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Sweet potato (Ipomoea batatas) is a very important staple food crop in Rwanda due to its high growth and consumption in all parts of the country. The effect of seven different storage conditions on the quality and nutritional composition of the three most grown and consumed varieties of orange-fleshed sweet potato (OFSP), namely Kabode, Terimbere, and Vita, were studied over a period of six weeks at Postharvest Service and Training Center of University Rwanda, Busogo Campus. The potato stored under the following conditions (zero energy cooling chamber, ground washed sweet potato, ground unwashed sweet potato, perforated washed sweet potato, perforated unwashed sweet potato, non-perforated washed sweet potato, and non-perforated unwashed sweet potato) were assessed in this study. These storage conditions are the modifications of existing methods currently used in Rwanda for suitable local climatic conditions. Hence, 30kgs of freshly harvested OFSP for each variety were bought from farmers of Gakenke and Rulindo districts and then transported to the postharvest training and service center UR-CAVM, Busogo Campus. 2.5kg of each potato sample was selected and stored under the above-mentioned storage conditions after pretreatment. Data were collected for six weeks on percent weight loss, shrinkability and the general appearance at interval of three days. The stored samples were also analyzed for moisture, crude ash, crude fiber, and reduced sugar levels during the entire storage period. Results showed the difference among the various storage conditions. It was shown that ZECC and non-perforated sacs (in the open air) storage techniques had good potential for storage of orange flesh sweet potato for up to six weeks without considerable change in physical and nutritional parameters compared to other considered conditions and, therefore, can be recommended as more useful for OSFP at farm level and during transport and market storage.

Keywords: ZECC, orange fleshed sweet potato, perforated sacs, storage conditions

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Authors: B. Hammouti, H. Oudda, A. Benabdellah, A. Benayada, A. Aouniti

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Corrosion behaviour of carbon steel was studied in various concentrated HClO4 solutions. To explain the acid attack in relation of H+ activity, new sensor was realised: two carbon paste electrodes (CPE) were constructed by incorporating ferrocene (Fc) and orthoquinone into the carbon paste matrix and crossed by weak current to stabilize potential difference. The potentiometric method at imposed weak current between these two electrodes permits the in situ determination of both concentration and acidity level of various concentrated HClO4 solutions. The different factors affecting the potential at imposed current as current intensity, temperature and H+ ion concentration are studied. The potentials measured between ferrocene and chloranil electrodes are directly linked to the acid concentration. The acidity Ri(H) function defined represents the determination of the H+ activity and constitutes the extend of pH is concentrated acid solutions. Ri(H) has been determined and compared to Strehlow Ro(H), Janata HGF and Hammett Ho functions. The collected data permit to give a scale of strength of mineral concentrated acids at a given concentration. Ri(H) is numerically equal to the thermodynamic Ro(H), but deviated from Hammett functions based on indicator determination. The CPE electrode with inserted ferrocene in presence of ferricinium (Fc+) ion in concentrated HClO4 at various concentrations is realized without junction potential and may plays the role of a practical reference electrode (FRE) in concentrated acids. Fc+ was easily prepared in biphasic medium HClO4-acid by the quantitative oxidation of ferrocene by the ortho-chloranil (oQ). Potential of FRE is stable with time. The variation of equilibrium potential of the interface Fc/ Fc+ at various concentrations of Fc+ (10-4 - 2 10-2 M) obeyed to the Nernst equation with a slope 0.059 Volt per decade. Corrosion rates obtained by weight loss and electrochemical techniques were then easily linked to acidity level.

Keywords: ferrocene, strehlow, concentrated acid, corrosion, Generalised pH, sensor carbon paste electrode

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Authors: Jorn Fricke, Frans Melissen

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Citizens in urban areas are prone to increased levels of stress due to urbanization, inadequate and overburdened infrastructure and services, and environmental degradation. Moreover, communities are fragile and subject to shocks and stresses through various social and political processes. A loss of (a sense of) community is often seen as related to increasing political and civic disintegration. Feelings of community can manifest themselves in various ways but underlying all these manifestations is the need for trust between people. One of the main drivers of trust between individuals is (shared) experiences. It is these shared experiences that may play an important role in building resilience, i.e., the ability of a community and its members to adapt to and deal with stresses, as well as ensure the ongoing development of a community. So far, experience design, as a discipline and academic field, has mainly focused on designing products or services. However, people-to-people experiences are the ones that play a pivotal role in building inclusiveness, safety, and resilience in communities. These experiences represent challenging objects of design as they develop in an interactive space of spontaneity, serendipity, and uniqueness that is based on intuition, freedom of expression, and interaction. Therefore, there is a need for research to identify which elements are required in designing the social and physical environment (or ‘experience scape’) to increase the chance for people-to-people experiences to be successful and what elements are required for these experiences to help in building resilience in urban communities that can resist shocks and stresses. By means of a comparative case study approach in urban areas in Germany and the Netherlands, using a range of qualitative research methods such as in-depth interviews, focus groups, participant observation, storytelling techniques, and life stories, this research identifies relevant actors and their roles in creating building blocks of optimal experience scrapes for building resilience in communities.

Keywords: community development, experiences, experience scapes, resilience

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Authors: Samuel O. Akande

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The human-induced climate change is likely to have severe consequences on forest ecosystems in Nigeria. Recent discussions and emphasis on issues concerning the environment justify the need for this research which examined deforestation monitoring in Oban Forest, Nigeria using Remote Sensing techniques. The Landsat images from TM (1986), ETM+ (2001) and OLI (2015) sensors were obtained from Landsat online archive and processed using Erdas Imagine 2014 and ArcGIS 10.3 to obtain the land use/land cover and Normalized Differential Vegetative Index (NDVI) values. Ground control points of deforested areas were collected for validation. It was observed that the forest cover decreased in area by about 689.14 km² between 1986 and 2015. The NDVI was used to determine the vegetation health of the forest and its implications on agricultural sustainability. The result showed that the total percentage of the healthy forest cover has reduced to about 45.9% from 1986 to 2015. The results obtained from analysed questionnaires shown that there was a positive correlation between the causes and effects of deforestation in the study area. The coefficient of determination value was calculated as R² ≥ 0.7, to ascertain the level of anthropogenic activities, such as fuelwood harvesting, intensive farming, and logging, urbanization, and engineering construction activities, responsible for deforestation in the study area. Similarly, temperature and rainfall data were obtained from Nigerian Meteorological Agency (NIMET) for the period of 1986 to 2015 in the study area. It was observed that there was a significant increase in temperature while rainfall decreased over the study area. Responses from the administered questionnaires also showed that futile destruction of forest ecosystem in Oban forest could be reduced to its barest minimum if fuelwood harvesting is disallowed. Thus, the projected impacts of climate change on Nigeria’s forest ecosystems and environmental stability is better imagined than experienced.

Keywords: deforestation, ecosystems, normalized differential vegetative index, sustainability

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Authors: Surya Prakash Gajagouni, Akram Alfantazi, Imad Barsoum

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Austenitic stainless steels are widely recognized for their exceptional corrosion resistance and mechanical properties, rendering them indispensable materials across various industries from construction to biomedical applications. However, in chloride and high temperature atmosphere it to further enhance their surface properties, anodization has emerged as a promising surface treatment technique. Anodization modifies the surface of stainless steels by creating a protective oxide layer, improving corrosion resistance and imparting additional functional characteristics. This paper explores the structural and corrosion characteristics of anodized austenitic stainless steels (AISI 304) using a two-step anodic technique. We utilized a perchloric acid-based electrolyte followed by an ammonium fluoride-based electrolyte. This sequential approach aimed to cultivate deeper and intricately self-ordered nanopore oxide arrays on a substrate made of 304 stainless steel. Electron Microscopic (SEM and TEM) images revealed nanoporous layered structures with increased length and crack development correlating with higher voltage and anodization time. Surface composition and chemical oxidation state of surface-treated SS were determined using X-ray photoelectron spectroscopy (XPS) techniques, revealing a surface layer rich in Ni and suppressed Cr, resulting in a thin film composed of Ni and Fe oxide compared to untreated SS. Electrochemical studies demonstrated enhanced corrosion resistance in a strong alkaline medium compared to untreated SS. Understanding the intricate relationship between the structural features of anodized stainless steels and their corrosion resistance is crucial for optimizing the performance of these materials in diverse applications. This study aims to contribute to the advancement of surface engineering strategies for enhancing the durability and functionality of austenitic stainless steels in aggressive environments.

Keywords: austenitic stainless steel, anodization, nanoporous oxides, marine corrosion

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Authors: Vistorina Amputu, Katja Tielboerger, Nichola Knox

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Primary productivity in dry savannahs is constraint by moisture availability and under increasing anthropogenic pressure. Thus, considering climate change and the unprecedented pace and scale of rangeland deterioration, methods for assessing the status of such rangelands should be easy to apply, yield reliable and repeatable results that can be applied over large spatial scales. Global and local scale monitoring of rangelands through satellite data and labor-intensive field measurements respectively, are limited in accurately assessing the spatiotemporal heterogeneity of vegetation dynamics to provide crucial information that detects degradation in its early stages. Fortunately, newly emerging techniques such as unmanned aerial vehicles (UAVs), associated miniaturized sensors and improving digital photogrammetric software provide an opportunity to transcend these limitations. Yet, they have not been extensively calibrated in natural systems to encompass their complexities if they are to be integrated for long-term monitoring. Limited research using drone technology has been conducted in arid savannas, for example to assess the health status of this dynamic two-layer vegetation ecosystem. In our study, we fill this gap by testing the relationship between UAV-estimated cover of rangeland functional attributes and field data collected in discrete sample plots in a Namibian dryland savannah along a degradation gradient. The first results are based on a supervised classification performed on the ultra-high resolution multispectral imagery to distinguish between rangeland functional attributes (bare, non-woody, and woody), with a relatively good match to the field observations. Integrating UAV-based observations to improve rangeland monitoring could greatly assist in climate-adapted rangeland management.

Keywords: arid savannah, degradation gradient, field observations, narrow-band sensor, supervised classification

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Authors: J. Ritonja, R. Brezovnik, M. Petrun, B. Polajžer

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Many modern synchronous generators in power systems are extremely weakly damped. The reasons are cost optimization of the machine building and introduction of the additional control equipment into power systems. Oscillations of the synchronous generators and related stability problems of the power systems are harmful and can lead to failures in operation and to damages. The only useful solution to increase damping of the unwanted oscillations represents the implementation of the power system stabilizers. Power system stabilizers generate the additional control signal which changes synchronous generator field excitation voltage. Modern power system stabilizers are integrated into static excitation systems of the synchronous generators. Available commercial power system stabilizers are based on linear control theory. Due to the nonlinear dynamics of the synchronous generator, current stabilizers do not assure optimal damping of the synchronous generator’s oscillations in the entire operating range. For that reason the use of the robust power system stabilizers which are convenient for the entire operating range is reasonable. There are numerous robust techniques applicable for the power system stabilizers. In this paper the use of sliding mode control for synchronous generator stability improvement is studied. On the basis of the sliding mode theory, the robust power system stabilizer was developed. The main advantages of the sliding mode controller are simple realization of the control algorithm, robustness to parameter variations and elimination of disturbances. The advantage of the proposed sliding mode controller against conventional linear controller was tested for damping of the synchronous generator oscillations in the entire operating range. Obtained results show the improved damping in the entire operating range of the synchronous generator and the increase of the power system stability. The proposed study contributes to the progress in the development of the advanced stabilizer, which will replace conventional linear stabilizers and improve damping of the synchronous generators.

Keywords: control theory, power system stabilizer, robust control, sliding mode control, stability, synchronous generator

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Authors: Kanik Sharma

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In the year of 2011, the global production of carbon nano-materials (CNMs) was around 3,500 tons, and it is projected to expand at a compound annual growth rate of 30.6%. Expanding markets for applications of CNMs, such as carbon nano-tubes (CNTs) and carbon nano-fibers (CNFs), place ever-increasing demands on lowering their production costs. Current technologies for CNM generation require intensive premium feedstock consumption and employ costly catalysts; they also require input of external energy. Industrial-scale CNM production is conventionally achieved through chemical vapor deposition (CVD) methods which consume a variety of expensive premium chemical feedstocks such as ethylene, carbon monoxide (CO) and hydrogen (H2); or by flame synthesis techniques, which also consume premium feedstock fuels. Additionally, CVD methods are energy-intensive. Renewable and replenishable feedstocks, such as those found in municipal, industrial, agricultural recycling streams have a more judicious reason for usage, in the light of current emerging needs for sustainability. Agricultural sugarcane bagasse and corn residues, scrap tire chips as well as post-consumer polyethylene (PE) and polyethylene terephthalate (PET) bottle shreddings when either thermally treated by sole pyrolysis or by sequential pyrolysis and partial oxidation result in the formation of gaseous carbon-bearing effluents which when channeled into a heated reactor, produce CNMs, including carbon nano-tubes, catalytically synthesized therein on stainless steel meshes. The structure of the nano-material synthesized depends on the type of feedstock available for pyrolysis, and can be determined by analysing the feedstock. These feedstocks could supersede the use of costly and often toxic or highly-flammable chemicals such as hydrocarbon gases, carbon monoxide and hydrogen, which are commonly used as feedstocks in current nano-manufacturing process for CNMs.

Keywords: nanomaterials, waste plastics, sugarcane bagasse, pyrolysis

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Authors: Daniele Lerede, Gianvito Colucci, Matteo Nicoli, Laura Savoldi

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The European Green Deal is the first internationally agreed set of measures to contrast climate change and environmental degradation. Besides the main target of reducing emissions by at least 55% by 2030, it sets the target of accompanying European countries through an energy transition to make the European Union into a modern, resource-efficient, and competitive net-zero emissions economy by 2050, decoupling growth from the use of resources and ensuring a fair adaptation of all social categories to the transformation process. While the general purpose to allow the realization of the purposes of the Green Deal already dates back to 2019, strategies and policies keep being developed coping with recent circumstances and achievements. However, general long-term measures like the Circular Economy Action Plan, the proposals to shift from fossil natural gas to renewable and low-carbon gases, in particular biomethane and hydrogen, and to end the sale of gasoline and diesel cars by 2035, will all have significant effects on energy supply and demand evolution across the next decades. The interactions between energy supply and demand over long-term time frames are usually assessed via energy system models to derive useful insights for policymaking and to address technological choices and research and development. TEMOA-Europe is a newly developed energy system optimization model instance based on the minimization of the total cost of the system under analysis, adopting a technologically integrated, detailed, and explicit formulation and considering the evolution of the system in partial equilibrium in competitive markets with perfect foresight. TEMOA-Europe is developed on the TEMOA platform, an open-source modeling framework totally implemented in Python, therefore ensuring third-party verification even on large and complex models. TEMOA-Europe is based on a single-region representation of the European Union and EFTA countries on a time scale between 2005 and 2100, relying on a set of assumptions for socio-economic developments based on projections by the International Energy Outlook and a large technological dataset including 7 sectors: the upstream and power sectors for the production of all energy commodities and the end-use sectors, including industry, transport, residential, commercial and agriculture. TEMOA-Europe also includes an updated hydrogen module considering its production, storage, transportation, and utilization. Besides, it can rely on a wide set of innovative technologies, ranging from nuclear fusion and electricity plants equipped with CCS in the power sector to electrolysis-based steel production processes and steel in the industrial sector – with a techno-economic characterization based on public literature – to produce insightful energy scenarios and especially to cope with the very long analyzed time scale. The aim of this work is to examine in detail the scheme of measures and policies for the realization of the purposes of the Green Deal and to transform them into a set of constraints and new socio-economic development pathways. Based on them, TEMOA-Europe will be used to produce and comparatively analyze scenarios to assess the consequences of Green Deal-related measures on the future evolution of the energy mix over the whole energy system in an economic optimization environment.

Keywords: European Green Deal, energy system optimization modeling, scenario analysis, TEMOA-Europe

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Authors: Fatemeh Modirzare

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Smart interior design represents a transformative approach to creating living spaces that integrate technology seamlessly into our daily lives, enhancing comfort, convenience, and sustainability. This paper explores the concept of smart interior design, its principles, benefits, challenges, and future prospects. It also highlights various examples and applications of smart interior design to illustrate its potential in shaping the way we live and interact with our surroundings. In an increasingly digitized world, the boundaries between technology and interior design are blurring. Smart interior design, also known as intelligent or connected interior design, involves the incorporation of advanced technologies and automation systems into residential and commercial spaces. This innovative approach aims to make living environments more efficient, comfortable, and adaptable while promoting sustainability and user well-being. Smart interior design seamlessly integrates technology into the aesthetics and functionality of a space, ensuring that devices and systems do not disrupt the overall design. Sustainable materials, energy-efficient systems, and eco-friendly practices are central to smart interior design, reducing environmental impact. Spaces are designed to be adaptable, allowing for reconfiguration to suit changing needs and preferences. Smart homes and spaces offer greater comfort through features like automated climate control, adjustable lighting, and customizable ambiance. Smart interior design can significantly reduce energy consumption through optimized heating, cooling, and lighting systems. Smart interior design integrates security systems, fire detection, and emergency response mechanisms for enhanced safety. Sustainable materials, energy-efficient appliances, and waste reduction practices contribute to a greener living environment. Implementing smart interior design can be expensive, particularly when retrofitting existing spaces with smart technologies. The increased connectivity raises concerns about data privacy and cybersecurity, requiring robust measures to protect user information. Rapid advancements in technology may lead to obsolescence, necessitating updates and replacements. Users must be familiar with smart systems to fully benefit from them, requiring education and ongoing support. Residential spaces incorporate features like voice-activated assistants, automated lighting, and energy management systems. Intelligent office design enhances productivity and employee well-being through smart lighting, climate control, and meeting room booking systems. Hospitals and healthcare facilities use smart interior design for patient monitoring, wayfinding, and energy conservation. Smart retail design includes interactive displays, personalized shopping experiences, and inventory management systems. The future of smart interior design holds exciting possibilities, including AI-powered design tools that create personalized spaces based on user preferences. Smart interior design will increasingly prioritize factors that improve physical and mental health, such as air quality monitoring and mood-enhancing lighting. Smart interior design is revolutionizing the way we interact with our living and working spaces. By embracing technology, sustainability, and user-centric design principles, smart interior design offers numerous benefits, from increased comfort and convenience to energy efficiency and sustainability. Despite challenges, the future holds tremendous potential for further innovation in this field, promising a more connected, efficient, and harmonious way of living and working.

Keywords: smart interior design, home automation, sustainable living spaces, technological integration, user-centric design

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Authors: Kehinde Agbele, Longe Olumide, Daniel Ekong, Dele Seluwa, Akintoye Onamade

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One major problem of most existing information retrieval systems (IRS) is that they provide even access and retrieval results to individual users specially based on the query terms user issued to the system. When using IRS, users often present search queries made of ad-hoc keywords. It is then up to IRS to obtain a precise representation of user’s information need, and the context of the information. In effect, the volume and range of the Internet documents is growing exponentially and consequently causes difficulties for a user to obtain information that precisely matches the user interest. Diverse combination techniques are used to achieve the specific goal. This is due, firstly, to the fact that users often do not present queries to IRS that optimally represent the information they want, and secondly, the measure of a document's relevance is highly subjective between diverse users. In this paper, we address the problem by investigating the optimization of IRS to individual information needs in order of relevance. The paper addressed the development of algorithms that optimize the ranking of documents retrieved from IRS. This paper addresses this problem with a two-fold approach in order to retrieve domain-specific documents. Firstly, the design of context of information. The context of a query determines retrieved information relevance using personalization and context-awareness. Thus, executing the same query in diverse contexts often leads to diverse result rankings based on the user preferences. Secondly, the relevant context aspects should be incorporated in a way that supports the knowledge domain representing users’ interests. In this paper, the use of evolutionary algorithms is incorporated to improve the effectiveness of IRS. A context-based information retrieval system that learns individual needs from user-provided relevance feedback is developed whose retrieval effectiveness is evaluated using precision and recall metrics. The results demonstrate how to use attributes from user interaction behavior to improve the IR effectiveness.

Keywords: context, document relevance, information retrieval, personalization, user search behaviors

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Authors: B. M. Pardeshi

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Introduction: Minerals and trace elements are chemical elements required by our bodies for numerous biological and physiological processes that are necessary for the maintenance of health. Medicinal plants are highly beneficial for the maintenance of good health and prevention of diseases. They are known as potential sources of minerals and vitamins. 30 to 40% of today’s conventional drugs used in the medicinal and curative properties of various plants are employed in herbal supplement botanicals, nutraceuticals and drug. Aim: The authors explored the mineral element content of some herbs, because mineral elements may have significant role in the development and treatment of gastrointestinal diseases, and a close connection between the presence or absence of mineral elements and inflammatory mediators was noted. Methods: Present study deals with the elemental analysis of medicinal plants by Instrumental Neutron activation Analysis and Atomic Absorption Spectroscopy. Medicinal herbals prescribed for skin diseases were purchased from markets and were analyzed by Instrumental Neutron Activation Analysis (INAA) using 252Cf Californium spontaneous fission neutron source (flux * 109 n s-1) and the induced activities were counted by γ-ray spectrometry and Atomic Absorption Spectroscopy (AAS) techniques (Perkin Elmer 3100 Model) available at Department of Chemistry University of Pune, INDIA, was used for the measurement of major, minor and trace elements. Results: 15 elements viz. Al, K, Cl, Na, Mn by INAA and Cu, Co, Pb, Ni, Cr, Ca, Fe, Zn, Hg and Cd by AAS were analyzed from different medicinal plants from India. A critical examination of the data shows that the elements Ca , K, Cl, Al, and Fe are found to be present at major levels in most of the samples while the other elements Na, Mn, Cu, Co, Pb, Ni, Cr, Ca, Zn, Hg and Cd are present in minor or trace levels. Conclusion: The beneficial therapeutic effect of the studied herbs may be related to their mineral element content. The elemental concentration in different medicinal plants is discussed.

Keywords: instrumental neutron activation analysis, atomic absorption spectroscopy, medicinal plants, trace elemental analysis, mineral contents

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Authors: Michael A. Sprayberry, Vincent C. Paquit

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Process parameter optimization in metal powder bed electron beam melting (MPBEBM) is crucial to ensure the technology's repeatability, control, and industry-continued adoption. Despite continued efforts to address the challenges via the traditional design of experiments and process mapping techniques, there needs to be more successful in an on-the-fly optimization framework that can be adapted to MPBEBM systems. Additionally, data-intensive physics-based modeling and simulation methods are difficult to support by a metal AM alloy or system due to cost restrictions. To mitigate the challenge of resource-intensive experiments and models, this paper introduces a Multi-Objective Reinforcement Learning (MORL) methodology defined as an optimization problem for MPBEBM. An off-policy MORL framework based on policy gradient is proposed to discover optimal sets of beam power (P) – beam velocity (v) combinations to maintain a steady-state melt pool depth and phase transformation. For this, an experimentally validated Eagar-Tsai melt pool model is used to simulate the MPBEBM environment, where the beam acts as the agent across the P – v space to maximize returns for the uncertain powder bed environment producing a melt pool and phase transformation closer to the optimum. The culmination of the training process yields a set of process parameters {power, speed, hatch spacing, layer depth, and preheat} where the state (P,v) with the highest returns corresponds to a refined process parameter mapping. The resultant objects and mapping of returns to the P-v space show convergence with experimental observations. The framework, therefore, provides a model-free multi-objective approach to discovery without the need for trial-and-error experiments.

Keywords: additive manufacturing, metal powder bed fusion, reinforcement learning, process parameter optimization

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Authors: Dongping Fang, Lian Duan, Xiaojing Yuan, Mike Xu, Allyn Klunder, Kevin Tan, Suiting Cao, Yeqing Ji

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Accurate prediction of a medical condition with straight clinical evidence is a long-sought topic in the medical management and health insurance field. Although great progress has been made with machine learning algorithms, the medical community is still, to a certain degree, suspicious about the model's accuracy and interpretability. This paper presents an innovative hierarchical attention deep learning model to achieve good prediction and clear interpretability that can be easily understood by medical professionals. This deep learning model uses a hierarchical attention structure that matches naturally with the medical history data structure and reflects the member’s encounter (date of service) sequence. The model attention structure consists of 3 levels: (1) attention on the medical code types (diagnosis codes, procedure codes, lab test results, and prescription drugs), (2) attention on the sequential medical encounters within a type, (3) attention on the medical codes within an encounter and type. This model is applied to predict the occurrence of stage 3 chronic kidney disease (CKD3), using three years’ medical history of Medicare Advantage (MA) members from a top health insurance company. The model takes members’ medical events, both claims and electronic medical record (EMR) data, as input, makes a prediction of CKD3 and calculates the contribution from individual events to the predicted outcome. The model outcome can be easily explained with the clinical evidence identified by the model algorithm. Here are examples: Member A had 36 medical encounters in the past three years: multiple office visits, lab tests and medications. The model predicts member A has a high risk of CKD3 with the following well-contributed clinical events - multiple high ‘Creatinine in Serum or Plasma’ tests and multiple low kidneys functioning ‘Glomerular filtration rate’ tests. Among the abnormal lab tests, more recent results contributed more to the prediction. The model also indicates regular office visits, no abnormal findings of medical examinations, and taking proper medications decreased the CKD3 risk. Member B had 104 medical encounters in the past 3 years and was predicted to have a low risk of CKD3, because the model didn’t identify diagnoses, procedures, or medications related to kidney disease, and many lab test results, including ‘Glomerular filtration rate’ were within the normal range. The model accurately predicts members A and B and provides interpretable clinical evidence that is validated by clinicians. Without extra effort, the interpretation is generated directly from the model and presented together with the occurrence date. Our model uses the medical data in its most raw format without any further data aggregation, transformation, or mapping. This greatly simplifies the data preparation process, mitigates the chance for error and eliminates post-modeling work needed for traditional model explanation. To our knowledge, this is the first paper on an interpretable deep-learning model using a 3-level attention structure, sourcing both EMR and claim data, including all 4 types of medical data, on the entire Medicare population of a big insurance company, and more importantly, directly generating model interpretation to support user decision. In the future, we plan to enrich the model input by adding patients’ demographics and information from free-texted physician notes.

Keywords: deep learning, interpretability, attention, big data, medical conditions

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Authors: Mohsin Ejaz, Shiao-Wei Kuo

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The growing production and exploitation of fossil fuels have placed human society in serious environmental issues. As a result, it's critical to design efficient and eco-friendly energy production and storage techniques. Porous organic polymers (POPs) are multi-dimensional porous network materials developed through the formation of covalent bonds between different organic building blocks that possess distinct geometries and topologies. POPs have tunable porosities and high surface area making them a good candidate for an effective electrode material in energy storage applications. Herein, we prepared a fully benzoxazine-based porous organic polymers (TPA–DHTP–BZ POP) through sonogashira coupling of dihydroxyterephthalaldehyde (DHPT) and triphenylamine (TPA) containing benzoxazine (BZ) monomers. Firstly, both BZ monomers (TPA-BZ-Br and DHTP-BZ-Ea) were synthesized by three steps, including Schiff base, reduction, and mannich condensation reaction. Finally, the TPA–DHTP–BZ POP was prepared through the sonogashira coupling reaction of brominated monomer (TPA-BZ-Br) and ethynyl monomer (DHTP-BZ-Ea). Fourier transform infrared (FTIR) and solid-state nuclear magnetic resonance (NMR) spectroscopy confirmed the successful synthesis of monomers as well as POP. The porosity of TPA–DHTP–BZ POP was investigated by the N₂ absorption technique and showed a Brunauer–Emmett–Teller (BET) surface area of 196 m² g−¹, pore size 2.13 nm and pore volume of 0.54 cm³ g−¹, respectively. The TPA–DHTP–BZ POP experienced thermal ring-opening polymerization, resulting in poly (TPA–DHTP–BZ) POP having strong inter and intramolecular hydrogen bonds formed by phenolic groups and Mannich bridges, thereby enhancing CO₂ capture and supercapacitive performance. The poly(TPA–DHTP–BZ) POP demonstrated a remarkable CO₂ capture of 3.28 mmol g−¹ and a specific capacitance of 67 F g−¹ at 0.5 A g−¹. Thus, poly(TPA–DHTP–BZ) POP could potentially be used for energy storage and CO₂ capture applications.

Keywords: porous organic polymer, benzoxazine, sonogashira coupling, CO₂, supercapacitor

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Authors: Ben Nadler

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Cell adhesion plays a vital role in many cell activities. The motivation to model cell adhesion is to study important biological processes, such as cell spreading, cell aggregation, tissue formation, and cell adhesion, which are very challenging to study by experimental methods alone. This study provides important insight into cell adhesion, which can lead to improve regenerative medicine and tissue formation techniques. In this presentation the biological cells adhesion is mediated by receptors–ligands binding and the diffusivity of the receptor on the cell membrane surface. The ability of receptors to diffuse on the cell membrane surface yields a very unique and complicated adhesion mechanism, which is exclusive to cells. The phospholipid bilayer, which is the main component in the cell membrane, shows fluid-like behavior associated with the molecules’ diffusivity. The biological cell is modeled as a fluid-like membrane with negligible bending stiffness enclosing the cytoplasm fluid. The in-plane mechanical behavior of the cell membrane is assumed to depend only on the area change, which is motivated by the fluidity of the phospholipid bilayer. In addition, the presence of receptors influences on the local mechanical properties of the cell membrane is accounted for by including stress-free area change, which depends on the receptor density. Based on the physical properties of the receptors and ligands the attraction between the receptors and ligands is modeled as a charged-nonpolar which is a noncovalent interaction. Such interaction is a short-range type, which decays fast with distance. The mobility of the receptor on the cell membrane is modeled using the diffusion equation and Fick’s law is used to model the receptor–receptor interactions. The resultant interaction force, which includes receptor–ligand and receptor–receptor interaction, is decomposed into tangential part, which governs the receptor diffusion, and normal part, which governs the cell deformation and adhesion. The formulation of the governing equations and numerical simulations will be presented. Analysis of the adhesion characteristic and properties are discussed. The roles of various thermomechanical properties of the cell, receptors and ligands on the cell adhesion are investigated.

Keywords: cell adhesion, cell membrane, receptor-ligand interaction, receptor diffusion

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Authors: Aldé Belgard Tchicaya Loemba, Baraka Kichonge, Thomas Kivevele, Juma Rajabu Selemani

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Plants used for medicinal purposes are extremely perishable, owing to moisture-enhanced enzymatic and microorganism activity, climate change, and improper handling and storage. Experiments have shown that drying the medicinal plant without affecting the active nutrients and controlling the moisture content as much as possible can extend its shelf life. Different traditional and modern drying techniques for preserving medicinal plants have been developed, with some still being improved in Sub-Saharan Africa. However, many of these methods fail to address the most common issues encountered when drying medicinal plants, such as nutrient loss, long drying times, and a limited capacity to dry during the evening or cloudy hours. Heat pump drying is an alternate drying method that results in no nutritional loss. Furthermore, combining a heat pump dryer with a solar energy storage system appears to be a viable option for all-weather drying without affecting the nutritional values of dried products. In this study, a solar-assisted heat pump dryer integrated with thermal energy storage is developed for drying moringa leaves. The study also discusses the performance analysis of the developed dryer as well as the proximate analysis of the dried moringa leaves. All experiments were conducted from 11 a.m. to 4 p.m. to assess the dryer's performance in “daytime mode”. Experiment results show that the drying time was significantly reduced, and the dryer demonstrated high performance in preserving all of the nutrients. In 5 hours of the drying process, the moisture content was reduced from 75.7 to 3.3%. The average COP value was 3.36, confirming the dryer's low energy consumption. The findings also revealed that after drying, the content of protein, carbohydrates, fats, fiber, and ash greatly increased.

Keywords: heat pump dryer, efficiency, moringa leaves, proximate analysis

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Authors: Ghulam Mustafa Halepota, Zaib Dahar

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Background: Low acceptance of FP services, particularly in hard to reach areas where geographic, economic, or social barriers limit-service uptake. Moreover, limited resources appeared to be a reflection of dismal contraceptive use in Pakistan. People’s Primary Health Care Initiative (PPHI) is a Public Private Partnership Program of Government of Sindh which aims to improve maternal child health through accessible family planning services in far flung areas. In 2015 PPHI launched special family planning camps to have achieved a rapid improvement in CPR. On quarterly basis, these camps focus on Long Acting Reversible Contraceptives (LARC). These camps are arranged at 250 BHU Plus (24/7 MCHCs). The Organization manages 1140 primary health care facilities all over Sindh province and focuses on maternal, newborn and child health which includes antenatal care, labor/delivery, postnatal care, family planning, immunization, nutrition, BEmONC, CEmONC, diagnostic laboratories, ambulance services. Under the FPRH program, the organization launched special family planning camps in far flung areas to achieve a rapid improvement in CPR-committed to FP 2020 goal. Objective: To assess the performance of special FP camps for the improvement of long acting reversible contraceptive in hard to reach areas. Methodology: Outreach camps are organized on quarterly basis in 250 BHUs and maternal and child health centers (available-24/7). Using observational study design, the study reports 2 years data of special FP camps conducted in 23 various districts of Sindh during April 2015-April 2017. These special camps served a range of modern contraceptive methods including IUCDs, implants, condoms, pills, and injections. Moreover, 125 male medical officers are trained across Sindh in LARC and 554 female have been trained in implants and IUCD insertions. MSI Impact calculator was used to determine health and demographic impact of services. Results: This intervention has brought exceptional results, and the response has been overwhelming in time. Total 2048 special camps during 2015 till April 2017 have been carried out. 231796 MWRAs visited camps 91% opted modern FP, of which 45% opted Implants, 6% selected IUCDs from LARC (long term reversible contraceptive) from short term, 17% opted injectable 18% choose pills, and 12% used condoms. This intervention created a high contraceptive impact in rural Sindh an estimated 125048 FP users have been created, of this 111846 LARC users and 13498 are SARC users, through this intervention an estimated 55774 unintended pregnancies, 36299 live births, 9394, 80 maternal deaths, 926 and 6077 unsafe abortion have been averted. Moreover, the intervention created an economic impact and saved 2,409,563 direct health expenditure on each woman with reproductive age. Conclusion: Special FP Camps along with routine services is an effective and acceptable model for increase in provision of long-acting and permanent methods in hard to reach areas. This innovative approach by PHHI-Sindh has also been adopted in other provinces of Pakistan.

Keywords: inequalities, special camps, family planning services, hard to reach areas

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Authors: I. Kamika, S. Azizi, M. Tekere

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Nanotechnology promises significant improvements of advanced materials and manufacturing techniques with a vast range of applications, which are critical for the future competitiveness of national industries. The manipulations and productions of materials, whilst, controlling the optical properties and surface area to a nanosize scale enabled a birth of a new field known as nanotechnology. However, their rapidly developing industry raises concerns about the environmental impacts of nanoparticles, as their effects on functional bacterial community in wastewater treatment remain unclear. The present research assessed the impact of cerium Oxide nanoparticles (nCeO) on the bacterial microbiome of an activated sludge system, which influenced its performance of this system on nutrient removal. Out of 15875 reads sequenced, a total of 13133 reads were non-chimeric. The wastewater samples were more dominant to the unclassified bacteria (51.07% of bacteria community) followed with the classified bacteria (48.93). Proteobacteria was the most dominant phylum in both classified and unclassified bacteria, whereas 18% of bacteria could even not be assigned a phylum and remained unclassified suggesting hitherto vast untapped microbial diversity. The bacterial operational taxonomic units (OTUs) ranged from 1014 to 2629 over the experimental period. The denitrification related species including Diaphorobacter species, Thauera species and those in the Sphaerotilus and Leptothrix group were found to be inhibited in a high concentration of CeO-NP. The diversity indices suggested that the bacterial community inhabiting the wastewater samples were less diverse as the concentration of CeO increases. The canonical correspondence analysis (CCA) results highlighted that the bacterial community variance had the strongest relationship with water temperature, conductivity, pH, and dissolved oxygen (DO) content as well as nCeO. The results provided the relationships between the microbial community and environmental variables in the wastewater samples.

Keywords: bacterial community, next generation, cerium oxide, wastewater, activated sludge, nanoparticles, nanotechnology

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Authors: Velimir "monty" Vesselinov, Trais Kliplhuis, Hope Jasperson

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Artificial intelligence (AI) is a powerful tool in the geothermal energy sector, aiding in both exploration and utilization. Identifying promising geothermal sites can be challenging due to limited surface indicators and the need for expensive drilling to confirm subsurface resources. Geothermal reservoirs can be located deep underground and exhibit complex geological structures, making traditional exploration methods time-consuming and imprecise. AI algorithms can analyze vast datasets of geological, geophysical, and remote sensing data, including satellite imagery, seismic surveys, geochemistry, geology, etc. Machine learning algorithms can identify subtle patterns and relationships within this data, potentially revealing hidden geothermal potential in areas previously overlooked. To address these challenges, a SIML (Science-Informed Machine Learning) technology has been developed. SIML methods are different from traditional ML techniques. In both cases, the ML models are trained to predict the spatial distribution of an output (e.g., pressure, temperature, heat flux) based on a series of inputs (e.g., permeability, porosity, etc.). The traditional ML (a) relies on deep and wide neural networks (NNs) based on simple algebraic mappings to represent complex processes. In contrast, the SIML neurons incorporate complex mappings (including constitutive relationships and physics/chemistry models). This results in ML models that have a physical meaning and satisfy physics laws and constraints. The prototype of the developed software, called GeoTGO, is accessible through the cloud. Our software prototype demonstrates how different data sources can be made available for processing, executed demonstrative SIML analyses, and presents the results in a table and graphic form.

Keywords: science-informed machine learning, artificial inteligence, exploration, utilization, hidden geothermal

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Authors: A. Calabrese, V. F. Uricchio, D. di Noia, S. Favale, C. Caiati, G. P. Maggi, G. Donvito, D. Diacono, S. Tangaro, A. Italiano, E. Riezzo, M. Zippitelli, M. Toriello, E. Celiberti, D. Festa, A. Colaianni

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Climate change has a severe impact on human health. There is a vast literature demonstrating temperature increase is causally related to cardiovascular problem and represents a high risk for human health, but there are not study that improve a solution. In this work, it is studied how the clime influenced the human parameter through the analysis of climatic conditions in an area of the Apulia Region: Capurso Municipality. At the same time, medical personnel involved identified a set of variables useful to define an index describing health condition. These scientific studies are the base of an innovative alert system, IPPOCRATE, whose aim is to asses climate risk and share information to population at risk to support prevention and mitigation actions. IPPOCRATE is an e-health system, it is designed to provide technological support to analysis of health risk related to climate and provide tools for prevention and management of critical events. It is the first integrated system of prevention of human risk caused by climate change. IPPOCRATE calculates risk weighting meteorological data with the vulnerability of monitored subjects and uses mobile and cloud technologies to acquire and share information on different data channels. It is composed of four components: Multichannel Hub. Multichannel Hub is the ICT infrastructure used to feed IPPOCRATE cloud with a different type of data coming from remote monitoring devices, or imported from meteorological databases. Such data are ingested, transformed and elaborated in order to be dispatched towards mobile app and VoIP phone systems. IPPOCRATE Multichannel Hub uses open communication protocols to create a set of APIs useful to interface IPPOCRATE with 3rd party applications. Internally, it uses non-relational paradigm to create flexible and highly scalable database. WeHeart and Smart Application The wearable device WeHeart is equipped with sensors designed to measure following biometric variables: heart rate, systolic blood pressure and diastolic blood pressure, blood oxygen saturation, body temperature and blood glucose for diabetic subjects. WeHeart is designed to be easy of use and non-invasive. For data acquisition, users need only to wear it and connect it to Smart Application by Bluetooth protocol. Easy Box was designed to take advantage from new technologies related to e-health care. EasyBox allows user to fully exploit all IPPOCRATE features. Its name, Easy Box, reveals its purpose of container for various devices that may be included depending on user needs. Territorial Registry is the IPPOCRATE web module reserved to medical personnel for monitoring, research and analysis activities. Territorial Registry allows to access to all information gathered by IPPOCRATE using GIS system in order to execute spatial analysis combining geographical data (climatological information and monitored data) with information regarding the clinical history of users and their personal details. Territorial Registry was designed for different type of users: control rooms managed by wide area health facilities, single health care center or single doctor. Territorial registry manages such hierarchy diversifying the access to system functionalities. IPPOCRATE is the first e-Health system focused on climate risk prevention.

Keywords: climate change, health risk, new technological system

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Authors: Rajkumar Ghosh

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India faces a critical task of water shortage, specifically during dry seasons, which adversely impacts agricultural productivity and food protection. Natural farming, specializing in sustainable practices, demands green water management in smart cities in India. This paper examines how rooftop rainwater harvesting (RRWH) can alleviate water scarcity and support sustainable organic farming practices in India. RRWH emerges as a promising way to increase water availability for the duration of dry intervals and decrease reliance on traditional water sources in smart cities. The look at explores the capacity of RRWH to enhance water use performance, help crop growth, enhance soil health, and promote ecological stability inside the farming ecosystem. The medical paper delves into the advantages, challenges, and implementation techniques of RRWH in organic farming. It addresses demanding situations, including seasonal variability of rainfall, limited rooftop vicinity, and monetary concerns. Moreover, it analyses broader environmental and socio-economic implications of RRWH for sustainable agriculture, emphasizing water conservation, biodiversity protection, and the social properly-being of farming communities. The belief underscores the importance of RRWH as a sustainable solution for reaching the aim of sustainable agriculture in natural farming in India. It emphasizes the want for further studies, policy advocacy, and capacity-building initiatives to promote RRWH adoption and assist the transformation in the direction of sustainable organic farming systems. The paper proposes adaptive strategies to triumph over demanding situations and optimize the advantages of RRWH in organic farming. By way of doing so, India can make vast development in addressing water scarcity issues and making sure a greater resilient and sustainable agricultural future in smart cities.

Keywords: rooftop rainwater harvesting, organic farming, green water management, food protection, ecological stabilty

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Authors: Nemat Sokhandan Bashir

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Threats from viruses to agricultural crops could be even larger than the losses caused by the other pathogens because, in many cases, the viral infection is latent but crucial from an epidemic point of view. Wild vegetation can be a source of many viruses that eventually find their destiny in crop plants. Although often asymptomatic in wild plants due to adaptation, they can potentially cause serious losses in crops. Therefore, exploring viruses in wild vegetation is very important. Recently, omics have been quite useful for exploring plant viruses from various plant sources, especially wild vegetation. For instance, we have discovered viruses such as Ambrossia asymptomatic virus I (AAV-1) through the application of metagenomics from Oklahoma Prairie Reserve. Accordingly, extracts from randomly-sampled plants are subjected to high speed and ultracentrifugation to separated virus-like particles (VLP), then nucleic acids in the form of DNA or RNA are extracted from such VLPs by treatment with phenol—chloroform and subsequent precipitation by ethanol. The nucleic acid preparations are separately treated with RNAse or DNAse in order to determine the genome component of VLPs. In the case of RNAs, the complementary cDNAs are synthesized before submitting to DNA sequencing. However, for VLPs with DNA contents, the procedure would be relatively straightforward without making cDNA. Because the length of the nucleic acid content of VPLs can be different, various strategies are employed to achieve sequencing. Techniques similar to so-called "chromosome walking" may be used to achieve sequences of long segments. When the nucleotide sequence data were obtained, they were subjected to BLAST analysis to determine the most related previously reported virus sequences. In one case, we determined that the novel virus was AAV-l because the sequence comparison and analysis revealed that the reads were the closest to the Indian citrus ringspot virus (ICRSV). AAV—l had an RNA genome with 7408 nucleotides in length and contained six open reading frames (ORFs). Based on phylogenies inferred from the replicase and coat protein ORFs of the virus, it was placed in the genus Mandarivirus.

Keywords: wild, plant, novel, metagenomics

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