Optimal Site Research Articles

Identifying optimal locations for the development of health facilities towards the attainment of universal health coverage using geospatial techniques in Kishapu district, Tanzania

Two hours of travel time specified by the World Health Organization (WHO) to access quality health services is among the most important criteria for the Universal Health Coverage. However, locations of health facilities (HF) in many developing countries fail to realise this target due to a lack of appropriate models considering the local environment. This work used the central-place theory to explore locations of HF in Kishapu and their accessibility status based on two means of transport in the AccessMod tool: walking only and the combination of walking-and-motor devices. The results of the walking scenario indicated that the travel times to the health centres and hospitals exceeded 2 hours, and a direct relationship existed between the facility level and the travel time spent to access it. The combined transport (walking and motorized) showed that dispensaries are easily accessible (14.5 minutes) compared to health centres (42.8 minutes) and hospitals (67.3 minutes). To address the challenge, we have developed a model revealing optimal sites with quick access for HF construction and improvement using Multi-Criteria-Evaluation and Analytical-Hierarchy Process methods weighting five criteria including distance from settlements (44% weight), roads (26% weight), existing health facilities (16% weight), rivers (9% weight) and railway (5% weight). A test of the model with both means of transport shows that at all places proposed to be optimal allow patitents to travel in less than two hours, indicating that the proposed model can effectively and efficiently solve the challenge of allocating HF in society.

Computational Fluid Dynamics (CFD) in Arteriovenous (AV) Graft Implantation Through End-to-Side Anastomosis with Varying Tube Diameters Across Different Vascular Access Locations for Dialysis Treatment.

Background/Objectives: Arteriovenous (AV) graft is a procedure for hemodialysis performed in the arm. Optimizing AV graft design is vital to enhance haemodialytic efficiency in patients with kidney disease. Despite being a standard procedure, making it work optimally is still difficult due to various graft diameters and anastomosis configurations, which have limited studies. This research aims to find the ideal AV graft tube diameter on blood flow and pressure gradients and the ideal body site for AV graft implantation and to study their angles for dialysate flow. Methods: Nine models were designed in Autodesk Fusion 360 with 40°, 50°, and 60° angles each having 2 mm, 5.1 mm, and 14.5 mm diameters, all following specific equations on continuity, momentum (Navier-Stokes Equation)), and the Reynolds Stress Model (RSM). The CFD simulation of these models was performed in ANSYS Fluent with an established parameter of 0.3 m/s inlet velocity and stiff/no-slip graft and artery wall boundary condition. Results: As a result, the design with a diameter of 14.5 mm and a 40° angle was overall the most ideal in terms of minimal wall shear stress and turbulence. Conclusions: Thus the brachiocephalic area or the forearm is calculated to be the most optimal implantation site. Additionally, varying angles do affect dialysate flow, as smaller values cause less stress.

Recycling Valuable Phenol from Polycarbonate Plastic Waste Via Direct Depolymerization and Csp2-Csp3 Bond Cleavage Under Mild Conditions.

Upcycling plastic waste into commodity chemicals is recognized as an environmentally benign solution and beneficial for the sustained growth of humanity. Nevertheless, transition metal-free catalysts and energy-efficient conditions pose significant challenges due to the robust mechanical properties of plastics. Here, a strategy for selective production of phenol by upcycling polycarbonate waste via direct depolymerization and Csp2-Csp3 bond cleavage in an aqueous medium under mild conditions is reported. The commercial zeolites efficiently catalyze the depolymerization, Csp2-Csp3 bond hydrolysis, and direct Csp2-Csp3 bond scission at Cα of PC. Among all evaluated zeolites, HY (Si/Al=15) showed excellent catalytic performance, attributed to the ~75 % yield of phenol and ~15 % of acetone. The approach also employs different municipal waste PC for upcycling. Studies reveal that HY (15) exhibits high catalytic efficiency and phenol yield due to its optimum acid sites and textual properties. A scale-up experiment demonstrated that 3.1 g of phenol was produced from 5.0 g of PC, and the mass balance was 90 %. A combination of control experiments, NMR analysis, and DFT studies proposed the reaction pathway. Our findings present a sustainable avenue for upcycling PC waste and offer a new way to produce phenol, contributing to the advancement of a circular economy.

Can bone SPECT/CT determine optimal sites for microbiological identification in post-traumatic or chronic osteomyelitis of extremities?

IntroductionAccurate microbiological identification is crucial when managing chronic osteomyelitis (COM) and post-traumatic osteomyelitis (PTO). Although bone single photon emission computed tomography/computed tomography (SPECT/CT) has helped in localizing osteomyelitis lesions, its effectiveness in guiding microbiological sampling remains unclear. This study aimed to determine whether bone SPECT/CT can improve microbiological identification rates in COM or PTO of the extremities. Patients and methodsFrom February 2020 to August 2024, 53 patients with suspected COM or PTO in the extremities were retrospectively analyzed. All patients underwent bone SPECT/CT, followed by microbiological sampling during surgery. Tissue samples were taken from the areas of high SPECT/CT uptake or based on intraoperative findings where no uptake was observed. Microorganism identification rates were analyzed, including a sub-group analysis based on antibiotic discontinuation. ResultsOf the 53 patients, 42 had positive bone SPECT/CT scan findings, with pathogen identification in 30 patients (71.4 %). In contrast, pathogen identification occurred in one out of twelve patients (9.1 %) with negative findings (odds ratio 25, p< 0.001). Bone SPECT/CT demonstrated a sensitivity of 96.8 % and an overall accuracy of 75.5 %. When antibiotics had been discontinued for ≥2 weeks, the pathogen identification rate increased to 90 %, compared with 50 % for <2 weeks of discontinuation (odds ratio 10.0, p= 0.006). In a sub-group of 30 patients with adequate antibiotic discontinuation duration, a positive bone SPECT/CT scan yielded a pathogen identification rate of 90.1 % (odds ratio 60.0, p= 0.001). ConclusionBone SPECT/CT effectively identifies optimal sites for microbiological sampling in COM and PTO of the extremities, particularly when antibiotics have been discontinued for ≥2 weeks, enhancing pathogen detection rates.

Application of a GIS-Based Multi-Criteria Decision-Making Approach to the Siting of Ocean Thermal Energy Conversion Power Plants: A Case Study of the Xisha Sea Area, China

In order to achieve the goals of carbon neutrality and reduced carbon emissions, China is increasingly focusing on the development and utilization of renewable energy sources. Among these, ocean thermal energy conversion (OTEC) has the advantages of small periodic fluctuations and large potential reserves, making it an important research field. With the development of the “Maritime Silk Road”, the Xisha Islands in the South China Sea will see a growing demand for electricity, providing the potential for OTEC development in this region. Optimal site selection of OTEC power plants is a prerequisite for developing thermal energy provision, affecting both the construction costs and future benefits of the power plants. This study establishes a scientific evaluation model based on the decision-making frameworks of geographic information systems (GISs) and multi-criteria decision-making (MCDM) methods, specifically the analytic hierarchy process (AHP) for assigning weights, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to reclassify the factors, and weighted linear combination (WLC) to compute the suitability index. In addition to commonly considered factors such as temperature difference and marine usage status, this study innovatively incorporates geological conditions and maximum offshore distances of cold seawater based on cost control. The final evaluation identifies three suitable areas for OTEC development near the Xuande Atoll and the Yongle Atoll in the Xisha Sea Area, providing valuable insights for energy developers and policymakers.

Synergistic Coordination Effect and Metal-Support Interaction Engineering of Single-Atom Mn-N2 Sites for Boosting Sensitive and Selective Dopamine Biosensing in Human Serum.

Coordination environment of metal atoms is core for designing high-performance single-atom catalysts (SACs), while metal-support interaction also has an important effect on structure-function relationship. Nevertheless, the interaction effect of metal-support is mostly ignored. Through synergistic regulation of coordination environment and metal-support interaction, Mn SAC with atom-dispersed Mn-N2 sites on dopamine (DA) support is synthesized for sensitive and selective DA oxidation based on theoretical calculations and experimental explorations. MnN2 presents the more optimal catalytic site for DA oxidation than other coordination conditions, enhancing sensitivity including a wide range, a low limit of detection, and particularly a very low catalytic potential. The construction of Mn-N2 active sites on DA carbon promotes the coupling between Mn metal atoms and DA support, decreasing work function, facilitating electron exchange, shortening response time, and boosting selectivity. Both the catalytic mechanism of Mn SAC toward DA and the relation construction of catalyst's structure and catalytic function are established.

Towards advanced sustainable criteria for choosing the best site for collecting solar energy in cities using multi-criteria GIS

Solar energy has become a prominent and crucial source of clean energy due to the increasing global demand for electricity. There is a prevailing global trend towards the construction of solar farms as a means of energy generation. This study aims to assess multiple criteria encompassing urban, environmental, and social aspects in order to ascertain the optimal site for constructing solar farms. The evaluation primarily focuses on characteristics such as topography, solar radiation, accessibility, land use, and proximity to roads and power stations. In order to acquire the necessary spatial fit model, the data was evaluated utilizing a Geographic Information System (GIS) program, and the criteria were subsequently consolidated into an integrated geographic information system. A comprehensive review of the existing body of literature reveals that environmental factors, specifically solar radiation and aspect, play a crucial role in determining the suitable places for the establishment of solar energy collection projects (Merrouni et al. in Energy Procedia 49:2270-2279, 2013; McKinney in J Student Res Environ Sci Appalac 4:1-14, 2014). Furthermore, other analysis factors such as proximity to built-up regions, closeness to power lines, and proximity to roadways are taken into account (Hott et al. in GIS-based Spatial Analysis For LargeScale Solar Power And Transmission Line Issues: Case Study of Wyoming, U.S. In: Proceedings of the 41st American Solar Energy Society Meeting, 2012; Effat in Int J Adv Remote Sens GIS 2:205-220, 2013). These criteria have an impact on the cost of solar farms. The objective of this study was to assess several aspects influencing the selection of an optimal location for a solar energy farm, taking into consideration the aforementioned criteria. The study was carried out in New Aswan city, utilizing data obtained from the Urban Planning Authority within the Ministry of Housing and Urban Development, as well as the New Aswan City AuthorityI generated cartographic representations and compiled quantitative data, which informed our selection of places that met the established criteria through the utilization of a Geographic Information System (GIS) software. Upon the conclusion of the study, numerous locations that satisfied the established criteria were selected. The present study focuses on regions with high capacity, and the findings are depicted in the form of spatial and objective maps. One of the primary benefits associated with the utilization of this methodology lies in its versatility, as it can be implemented across several domains. Furthermore, a straightforward adjustment of the criteria facilitates its application in the selection of optimal locations for wind farms.

Assessment of Wind Energy Potential and Optimal Site Selection for Wind Energy Plant Installations in Igdir/Turkey

Wind energy is an eco-friendly, renewable, domestic, and infinite resource. These factors render the construction of wind turbines appealing to nations, prompting numerous governments to implement incentives to augment their installed capacity of wind turbines. Alongside augmenting the installed capacity of wind turbines, identifying suitable locations for their installation is crucial for optimizing turbine performance. This study aims to evaluate potential sites for wind power plant installation via a GIS, a mapping technique. The Analytic Hierarchy Process (AHP) was employed to assess the locations, including both quantitative and qualitative aspects that significantly impact the wind farm suitability map. Utilizing the GIS methodology, all datasets were examined through height and raster transformations of land surface temperature, plant density index, air pressure, humidity, wind speed, air temperature, land cover, solar radiation, aspect, slope, and topographical characteristics, resulting in the creation of a wind farm map. The correlation between the five-year meteorological data and environmental parameters (wind direction, daily wind speed, daily maximum and minimum air temperatures, daily relative humidity, daily average air temperature, solar radiation duration, daily cloud cover, air humidity, and air pressure) influencing the wind power plant in Iğdır province, including Iğdır Airport, Karakoyunlu, Aralık, and Tuzluca districts, was analyzed. If wind energy towers are installed at 1 km intervals across an area of roughly 858,180 hectares in Igdir province, an estimated 858,180 GWh of wind energy can be generated. The GIS-derived wind power plant map indicates that the installation sites for wind power plants are located in regions susceptible to wind erosion.

Optimal Site Selection for Solar PV Systems in the Colombian Caribbean: Evaluating Weighting Methods in a TOPSIS Framework

Optimal Site Selection for Solar PV Systems in the Colombian Caribbean: Evaluating Weighting Methods in a TOPSIS Framework

Experimental and DFT studies of mercury adsorption and oxidation on CuCo2O4(110) surface

Elemental mercury (Hg0) is a typical toxic pollutant in flue gas from coal-fired power plants. The specific role of oxygen transfer on Hg0 oxidation over CuCo2O4 oxygen carrier and the involved reaction mechanisms were systematically studied by experimental and theoretical methods. In this study, the CuCo2O4 oxygen carrier with spinel-structure was prepared with salt-assisted combustion method. To reduce the grain size and increase the specific surface area of the oxygen carrier, the optimal KCl: CuCo2O4 ratio of 1:1 was obtained. Oxygen uncoupling ability of CuCo2O4 oxygen carrier was very strong, and the oxygen-releasing performance was slightly decreased after ten cyclic processes. Simulation based on density functional theory (DFT) shows that CuCo2O4 has relative low oxygen vacancy formation energy and oxygen transport energy barrier, and the oxygen vacancy is the preferred O2 adsorption site. Hg0 removal experiments show that CuCo2O4 has a strong ability to remove Hg0. The proportion of Hg2+ increases with the temperature, and the proportion of HgP decreases accordingly. Simulation shows that the 3-Co site on the surface of the CuCo2O4 oxygen carrier is the optimum Hg0 adsorption site. CuCo2O4 is found as a strong oxygen-releasing oxygen carrier, which can effectively promote the oxidation of Hg0.

Highly Efficient Separation of Intermediate-Size m-Xylene from Xylenes via a Length-Matched Metal-Organic Framework with Optimal Oxygen Sites Distribution.

Xylene separation is crucial but challenging, especially for the preferential separation of the intermediate-size m-xylene from xylene mixtures. Herein, exploiting the differences in molecular length and alkyl distribution among xylenes, we present a length-matched metal-organic framework, formulated as Al(OH)[O2C-C4H2O-CO2], featuring an effective pore size corresponding to m-xylene molecular length combined with multiple negative O hydrogen bond donors distribution, can serve as a molecular trap for efficient preferential separation of the intermediate-size m-xylene. Benchmark separation performance was achieved for separating m-xylene from a ternary mixture of m-xylene/o-xylene/p-xylene, with simultaneous record-high m-xylene uptake (1.3 mmol g-1) and m-xylene/p-xylene selectivity (5.3) in the liquid-phase competitive adsorption. Both vapor- and liquid-phase fixed-bed tests confirmed its practical separation capability with benchmark dynamic m-xylene/p-xylene and m-xylene/o-xylene selectivities, as well as excellent regenerability. The selective and strong m-xylene binding affinity among xylene molecules was further elucidated by simulations, validating the effectiveness of such a pore environment for the separation of intermediate-size molecules.

Highly Efficient Separation of Intermediate‐Size m‐Xylene from Xylenes via a Length‐Matched Metal–Organic Framework with Optimal Oxygen Sites Distribution

AbstractXylene separation is crucial but challenging, especially for the preferential separation of the intermediate‐size m‐xylene from xylene mixtures. Herein, exploiting the differences in molecular length and alkyl distribution among xylenes, we present a length‐matched metal–organic framework, formulated as Al(OH)[O2C−C4H2O−CO2], featuring an effective pore size corresponding to m‐xylene molecular length combined with multiple negative O hydrogen bond donors distribution, can serve as a molecular trap for efficient preferential separation of the intermediate‐size m‐xylene. Benchmark separation performance was achieved for separating m‐xylene from a ternary mixture of m‐xylene/o‐xylene/p‐xylene, with simultaneous record‐high m‐xylene uptake (1.3 mmol g−1) and m‐xylene/p‐xylene selectivity (5.3) in the liquid‐phase competitive adsorption. Both vapor‐ and liquid‐phase fixed‐bed tests confirmed its practical separation capability with benchmark dynamic m‐xylene/p‐xylene and m‐xylene/o‐xylene selectivities, as well as excellent regenerability. The selective and strong m‐xylene binding affinity among xylene molecules was further elucidated by simulations, validating the effectiveness of such a pore environment for the separation of intermediate‐size molecules.

Oxygen Saturation Endoscopic Imaging as a Novel Alternative to Assess Tissue Perfusion During Esophagectomy.

Assessment of gastric conduit perfusion during esophagectomy is crucial to determine its viability and identify the optimal site for anastomosis. Indocyanine green (ICG) fluorescence imaging is commonly used for this purpose, but it is contraindicated in patients with hypersensitivity to ICG, iodine, or shellfish. Oxygen saturation endoscopic imaging (OXEI) is a newer, non-pharmacologic technique for assessing perfusion. We report our experience with OXEI in 3 esophagectomy patients who had contraindications to ICG. All 3 patients underwent robot-assisted esophagectomies. None of the conduits had ischemic areas identified by white light. Using a 5mm laparoscopic specialized camera (ELUXEO Vision, FUJIFILM Healthcare Americas Corp., USA), OXEI was deployed for intracorporeal assessment of gastric conduit perfusion after pull-up into the chest. Postoperative outcomes including anastomotic leaks and complications were recorded. In two patients, OXEI revealed ischemic zones, which were resected to ensure optimal conduit viability. In the remaining patient, OXEI indicated robust vascularity throughout the conduit. All three patients experienced uneventful postoperative courses and were discharged within 10 days. There were no instances of anastomotic leaks or other major complications. In our experience, OXEI is a viable method for intraoperative assessment of gastric conduit perfusion in patients with contraindications to ICG. Prospective studies are needed to validate its efficacy in preventing anastomotic complications and to compare it with other methods of perfusion assessment including gross visual and ICG dye in a larger patient population.

One-pot synthesis of Ir subnanosized clusters supported on MWW nanosheets as effective catalysts for C-C bond hydrogenolysis

The rational design synthesis of metal catalysts with high dispersion and ordered structure is a challenging subject in materials chemistry and heterogeneous catalysis. In this study, we report one-pot synthesis of Ir subnanosized particles supported on MWW nanosheets and their application in hydrogenolysis of decalin. Here, it has been found that C-C bond cleavage occurs via a synergistic carbocation and carbene mechanism on Ir-containing catalysts, and via carbocation in the case of solid acids. The combination of optimal acidic and metallic site characteristics in the subnanosized Ir supported on MWW nanosheets Pill_Ir-ZN_150 sample contributes to the high activity of the final catalysts. We expect that these Ir catalytic systems will open up more opportunities for hydrogenolysis of naphthenics to high-value products.

One techno-economic analysis to rule them all: Instant prediction of hydrothermal liquefaction economic performance with a machine learned analytic equation

Hydrothermal liquefaction (HTL) has remarkable potential for efficient conversion of abundant, decentralized organic wastes into renewable fuels. Because waste is a highly distributed resource with context-dependent economic viability, selection of optimal deployment sites is slowed by the need to develop detailed techno-economic analyses (TEA) for the thousands of potential deployment locations, each with their own unique combinates of scale, proximity to infrastructure/markets, and feedstock properties. An economic modeling framework that requires only easily obtainable inputs for assessing economic performance would therefore allow multiplexed analysis of many thousands of cases, whereas traditional TEA would not be possible for more than a handful of cases. Within such a context, the present study uses machine learning to guide development of a TEA and modeling framework which provides accurate cost predictions using three key inputs – feedstock cost, biocrude yield, and process scale – to estimate the minimum fuel selling price (MFSP) that an HTL process can achieve. The structure of the proposed framework is informed and based on empirical observations of cost projections made by a detailed TEA over a wide range of feedstock costs, biocrude yields, and process scales. A machine learning guided process was used to identify, train, and test a series of models using auto-generated data for training and independently reported data for testing. The most accurate model consists of three terms and requires 6 adjustable parameters to predict independently published values of MFSP (N = 28) to within an average value of ± 20.4%. It is demonstrated that the reduced-order model’s predictions fall within 40% of the corresponding published values 95% of the time, and in the worst case, the associated discrepancy is 45.9%, suggesting that the accuracy of the machine learned model is indeed comparable to the TEAs that were used to build it. Moreover, the terms in the model are physically interpretable, conferring greater reliability to the use of its predictions. The model can be used to predict the dependence of MSFP on biocrude yield, scale, and feedstock cost; interestingly, MFSP is insensitive to biocrude yield and/or scale under many situations of interest and identifying the critical value for a given application is crucial to optimizing economic performance. The proposed model can be also extended to evaluate economic performance of newly developed HTL-based processes, including catalytic HTL, and the methodological framework used in this study is deemed appropriate for the development of machine learned TEA models in cases of other similar waste-to-energy technologies.

Multi-criteria site selection for wastewater treatment plant in Bent Saidane, Tunisia

Optimal site selection for the establishment of a municipal waste-water-treatment plant (WWTP) is an amazingly complex task that involves several factors such as regulations, as well as environmental, economic and social considerations. This paper presents the criteria and applied methods (geographic information system (GIS)/fuzzy analytical hierarchy process (AHP)) used in the screening of potential sites for the WWTP of the Bent Saidane rural locality (northern Tunisia). For this reason, nine factors accompanied by three sets of site selection criteria were used. GIS-based multi-criteria analysis techniques based on the standardised fuzzy logic concept and weighted overlay were applied for generation of all maps in the Universal Transverse Mercator coordinate system. Multiscale evaluations based on the weighted linear combination method were also assessed. The study indicated that 0.14 and 0.11% of the total area of the Bent Saidane locality were found to be highly suitable and very highly suitable, respectively. According to these results, the GIS followed by the fuzzy AHP method could pinpoint the optimal sites selected as the most suitable, due to their minimum impact on the environment, as well as on public health, for the construction of a future WWTP in the Bent Saidane rural area.

Vein Visualisation Technology for Peripheral Intravenous Access in Paediatric Patients: A Clinical Decision-Making Tool.

The aim of this study is to develop a clinical decision-making tool to guide utilisation of vein visualisation technologies and enhance chances of successful peripheral intravenous catheter (PIVC) insertion, using data collected from a vascular access team in a large paediatric medical centre in the United States. Quantitative two-phase, cluster analysis design. The study consisted of the following two phases: (1) a quantitative retrospective chart review to evaluate clinician utilisation and preference for vein visualisation technologies and (2) a quantitative prospective design, including a post-discharge retrospective chart review, to confirm utilisation of vein visualisation technologies and factors influencing clinician decision-making. A total of 16 groups were created based on the cluster analysis and expert clinician input. The results of first-attempt success analyses identified optimal device recommendations for each of the 16 patient groups. For patients older than 2 years old, the NIR device was more likely to result in first-attempt success regardless of BMI or access site and the NIR device was most optimal for almost all categories of paediatric patients regardless of BMI or access site. The transilluminator was found to be the most optimal device to use with younger patients (< 2 years old) who are underweight. Vein visualisation technology is recommended by professional nursing organisations to improve PIV access. Yet, adoption of this useful technology to aid selection of an optimal vein for insertion and visualisation during insertion is limited. This is the first study to develop a clinical decision-making tool for vein visualisation technology in PIVC insertion. Vein visualisation technology allows for a rapid, thorough assessment of patients' vasculature to determine an optimal site for PIVC placement beyond what is visible to the naked eye or achievable using traditional methods. The tool was designed to guide healthcare professionals towards successful first attempt PIVC insertions, thereby improving patient outcomes and efficiency of care. None.

Framework for strategic deployment of hybrid offshore solar and wind power plants: A case study of India

Renewable energy sources are gaining prominence as eco-friendly and sustainable alternatives to fossil fuels due to their availability and minimal greenhouse gas emissions. Nonetheless, the critical challenge is the availability of renewable resources, which fluctuates with changes in climatic conditions. This limitation poses a consistent challenge to generating base load power if it relies solely on a single type of renewable resource. Addressing this, integrating multiple renewable sources into hybrid systems has emerged as a viable solution. This study presents a framework, integrating Geographic Information Systems (GIS) and Hybrid Multi-Criteria Decision Making (MCDM) techniques to identify plausible locations for the deployment of Hybrid Offshore Solar and Wind Power Plants (HOSWPP) and the developed framework is demonstrated considering Indian Exclusive Economic Zone (EEZ) as a study area. Using the proposed approach, Indian EEZ region is classified into five suitability classes. The effectiveness of regions within each class is further assessed in terms of complementarity measured using Kendall's coefficient. Findings suggested that Kendall's coefficient for highly suitable class is −0.41 indicating the regions identified in this study are the prime locations for installing HOSWPP. A total of twenty optimal sites for HOSWPP deployment, predominantly in the offshore regions of Tamil Nadu and Gujarat. Eighteen sites are located along Kanyakumari to Thisayanvilai in Tamil Nadu, including areas in the Gulf of Mannar and near Valinokkam are found plausible. The rest of the two sites are in the offshore regions of Gujarat. This study provides a strategic roadmap to increase the renewable footprint, contributing to the global transition towards cleaner energy sources.

Integration of Photovoltaic and DSTATCOM In the Distribution Network Using Rat Swarm Optimization Technique

Power loss minimization and improved voltage profile have been major challenges faced by the electrical distribution network (DN) mainly because of the long length of the feeders and the high resistance to reactance (R/X) ratio of the DN. A lot of techniques have been investigated to solve these problems. One of the most prominent is the optimal integration of distributed generation (DG) such as photovoltaic (PV) as well as the integration of Distribution Static Synchronous Compensator (DSTATCOM) into the network. The main challenge with this solution has been the determination of the optimal sizes and sites of the DG and/or DSTATCOM. This paper seeks to optimize the simultaneous allocation of multiple DSTATCOMs and PVs in the DN for power loss reduction and voltage profile improvement using the rat swarm optimization (RSO) technique, which is a simple, yet robust optimization technique. The optimization problem is formulated to minimize power loss, voltage deviation index, and maximize the voltage stability index. The IEEE 33 node DN is used as a test network and the simulation results show the effectiveness of the RSO technique in finding the best sizes and locations of the PVs and the DSTATCOMs. The power losses of the network are reduced from 210.996 kW, and 143.129 kVAr when there is no DSTATCOM nor PVs in the network to 26.155 kW, and 19.128 kVAr when DSTATCOM and PVs are simultaneously allocated into the network. A remarkable improvement in the voltage profile of the network is also observed with the minimum node voltage being 0.98 p.u. compared to 0.9038 p.u. when there are no DSTATCOMs or PVs. The RSO results were compared with other techniques from the literature, and it proved its superiority.

Improving transient gene expression and agroinfiltration‐based transformation effectiveness in Indonesian orchid Phalaenopsis amabilis (L.) Blume

Transient gene expression is an approach used to study transient genes across various species, with infiltration by Agrobacterium tumefaciens (agroinfiltration) being a commonly used method. Agroinfiltration offers a simple and effective means of delivering transgenes into the plant genome. An alternative method for enhancing the quality and productivity of orchids as ornamental plants is genetic modification through agroinfiltration. Although Agrobacterium‐mediated genetic transformation by immersion has been used on the Phalaenopsis amabilis (L.) Blume species of orchid, transformation efficiency using the immersion technique remains relatively low and the method itself is challenging due to its requirement for aseptic handling. The application of agroinfiltration in P. amabilis has not previously been reported. This study investigates the impact of the injection site, acetosyringone concentration, bacterial density (OD600), and injection volume to determine the optimum conditions for agroinfiltration on P. amabilis. The results demonstrated that injection site had a noticeably distinct impact on transformation effectiveness, with the abaxial position of the leaf being the optimal site for Agrobacterium culture suspension injection. While adjustments in acetosyringone concentration, bacterial density (OD600), and injection volume did not significantly affect transformation efficiency, they did influence the peak time of GFP fluorescence. Acetosyringone at a concentration of 200 µM, an OD600 of 1.0 for Agrobacterium culture, and an injection volume of 500 µL effectively accelerated GFP expression duration.