Low Cost Operation Research Articles

Enhancement of effluent degradation by zinc oxide, carbon nitride, and carbon xerogel trifecta on brass monoliths.

In recent years, heterogeneous photocatalysis has emerged as a promising alternative for the treatment of organic pollutants. This technique offers several advantages, such as low cost and ease of operation. However, finding a semiconductor material that is both operationally viable and highly active under solar irradiation remains a challenge, often requiring materials of nanometric size. Furthermore, in many processes, photocatalysts are suspended in the solution, requiring additional steps to remove them. This can render the technique economically unviable, especially for nanosized catalysts. This work demonstrated the feasibility of using a structured photocatalyst (ZnO, g-C3N4, and carbon xerogel) optimized for this photodegradation process. The synthesized materials were characterized by nitrogen adsorption and desorption, X-ray diffraction (XRD), and diffuse reflectance spectroscopy (DRS). Adhesion testing demonstrated the efficiency of the deposition technique, with film adhesion exceeding 90%. The photocatalytic evaluation was performed using a mixture of three textile dyes in a recycle photoreactor, varying pH (4.7 and 10), recycle flow rate (2, 4, and 6 L h-1), immobilized mass (1, 2, and 3mgcm-2), monolith height (1.5, 3.0, and 4.5cm), and type of radiation (solar and visible artificials; and natural solar). The structured photocatalyst degraded over 99% of the dye mixture under artificial radiation. The solar energy results are highly promising, achieving a degradation efficiency of approximately 74%. Furthermore, it was possible to regenerate the structured photocatalyst up to seven consecutive times using exclusively natural solar light and maintain a degradation rate of around 70%. These results reinforce the feasibility and potential application of this system in photocatalytic reactions, highlighting its effectiveness and sustainability.

Evaluation and Optimization of Hybrid Renewable Energy Systems for Sustainable Farm Machinery Operations in Northern Nigeria

This study aimed to assess and optimize hybrid renewable energy systems (HRES) integrating solar and wind energy for sustainable farm machinery operations in Northern Nigeria. A purposive sampling technique was used to select representative farms and agricultural sites within the Kaduna region. Qualitative data were collected through interviews and surveys with farm owners and operators to gain insights into energy use practices, challenges, and perceptions regarding renewable energy adoption. The comparative analysis of different HRES configurations revealed that Configuration C, with the highest solar (20 kW) and wind capacities (15 kW), achieved the highest renewable energy fraction of 90% and the lowest annual cost of $14,800. Configuration B, with increased capacities (15 kW solar and 10 kW wind) and a battery capacity of 200 kWh, achieved an 85% renewable fraction and reduced the annual cost to $16,200. The cost-benefit analysis confirmed that HRES are economically viable and offer significant environmental advantages compared to conventional diesel generators. These findings underscore the potential for optimizing energy resources to achieve higher renewable energy fractions and lower operational costs. The study provides practical recommendations for promoting HRES adoption, highlighting the necessity for financial support, technical training, and robust policy frameworks to facilitate the transition towards sustainable energy solutions in agriculture.

Innovative Resource Distribution Through Multi-Agent Supply Chain Scheduling Leveraging Honey Bee Optimization Techniques

Many people and things involved in the supply chain can be represented by a network of linked agents in a multi-agent system. To achieve distribution and manufacturing targets efficiently, actions in a supply chain must be scheduled by tracking and organizing the allocation of resources. Healthcare, energy, aerospace, agriculture, and manufacturing are some of the industries that make use of it to better allocate and coordinate resources in complex networks. The goal of multi-agent supply chains is to lower costs and meet demand in dynamic contexts through efficient resource allocation and planning. Traditional approaches, such as linear programming and heuristic algorithmic approaches, have problems with adaptation and scalability. This study offers a novel scheduling method, Resource Distribution by Honey Bee Optimization (RDHBO), to circumvent these issues. It is based on a tactic that the honey bee uses when foraging. In this model, scout bees and foragers take on the role of actors, investigating and making the most of potential new ways to divide up resources by employing HBO strategies. The foraging agents look for places that have been profitable in the past, and the scouting agents carefully examine the supply chain to find places where resources might be available. The proposed RDHBO architecture allows for better supply chain scheduling by encouraging effective utilization and investigation, better communication, dynamic adaptability, autonomous decision-making, and efficiency of complicated systems. This method leads to an adaptable supply chain, lower operational costs, and more scalability and adaptability. This paper presents a formidable alternative to conventional optimization methods by demonstrating an efficient approach to dealing with complicated supply chain challenges.

Efficient electrochemical removal of ammoniacal nitrogen from livestock wastewater: The role of the electrode material

Wastewater from livestock farms contains high concentrations of suspended solids, organic contaminants, and nitrogen compounds, such as ammoniacal nitrogen. Discharging livestock effluents into water bodies without appropriate treatment leads to severe environmental pollution. Compared to conventional treatment methods, electrochemical oxidation exhibits higher nitrogen removal efficiencies. In the present work, the electrochemical removal of ammoniacal nitrogen from real livestock wastewater was investigated through a lab-scale reactor. Preliminary experiments were carried out to investigate the effects of different anode materials, including boron-doped diamond and iridium/ruthenium-coated titanium, on the total nitrogen removal efficiency using synthetic wastewater. Boron-doped diamond, a well-known non-active electrode, allowed to obtain 63.7 ± 1.21 % of total nitrogen degradation efficiency. However, the iridium/ruthenium-coated titanium electrode, belonging to the class of active anodes, showed a higher performance, achieving 78.8 ± 0.76 % contaminant degradation. Coupling iridium/ruthenium-coated titanium anode with a stainless-steel cathode improved the performance of the system, achieving even 96.2 ± 2.73 % of total nitrogen removal. The optimized cell configuration was used to treat livestock wastewater, resulting in the degradation of 67.0 ± 2.25 % of total nitrogen and 37.3 ± 0.68 % of total organic carbon when sodium chloride was added. At the end of the process, the ammonium content was completely removed, and only 17.7 ± 0.51 % of the initial nitrogen turned into nitrate. The results show that the proposed system is a promising approach to treating livestock wastewater by coupling high contaminant removal efficiencies with low operational costs. Anyway, further studies on process optimization with an emphasis on power requirements and electrode costs need to be carried out.

Countercurrent chromatography isolation of green propolis biomarkers: Potential blockers of SARS-COV-2 RBD and ACE2 interaction

Propolis is a natural resinous mixture produced by honeybees with numerous biological activities. Considering the recently reported potential of propolis as an adjuvant in COVID-19 treatment, a methodology for the fractionation of the hexane extract of Brazilian green propolis (HEGP) was developed for the obtention of prenylated biomarkers by countercurrent chromatography. The inhibition of the interaction between the receptor binding domain (RBD) of spike and ACE2 receptor was evaluated by the Lumitᵀᴹ immunoassay. Fractionation of HEGP was performed by both normal (CCC1 and CCC2, with extended elution) and reversed (CCC3) phase elution-extrusion modes with the solvent system hexane–ethanol–water 4:3:1. The normal elution mode of CCC1 (471 mg HEGP in a 80 mL column volume, 1.6 mm id) was scaled-up (CCC5, 1211 mg HEGP in a 112 mL column volume, 2.1 mm id), leading to the isolation of 89.9 mg of artepillin C, 1; 52.7 mg of baccharin, 2; and 26.6 mg of chromene, with purities of 93 %, 83 % and 88 %, respectively, by HPLC-PDA. Among the isolated compounds, artepillin C, 1, and baccharin, 2, presented the best results in the Lumitᵀᴹ immunoassay, showing 67% and 51% inhibition, respectively, at the concentration of 10 μM. This technique proved to be of low operational cost and excellent reproducibility.

Renewable regeneration optic fiber glucose sensor based on succinylaminobenzenoboronic acid modified excessively tilted fiber grating

BackgroundOptical fiber sensors have been used to detect glucose owing to advantages such as low cost, small size, and ease of operation etc. phenylboronic acid is one of the commonly used receptors for glucose detection, however phenylboronic acid based regenerative optical fiber sensors are commonly cumulative regeneration, renewable regeneration sensor has been missing from the literature. ResultsIn this work, instead of using phenylboronic acid, we synthesized succinylaminobenzenoboronic acid molecule (BPOA) by introducing a short chain containing carboxyl group at the other end of phenylboronic acid then covalently bonded BPOA on the surface of excessively tilted fiber grating (Ex-TFG). This provides a very stable platform for renewable regeneration and the regenerative buffer was also optimized. The proposed renewable regeneration method exhibited higher linearity and sensitivity (R2 = 0.9992, 8 pm/mM) in relative to the conventional cumulative regeneration method (R2 = 0.9718, 4.9 pm/mM). The binding affinity between BPOA and glucose was found to be almost constant over 140 bind/release cycles with a variation of less than 0.3 % relative standard deviation. SignificanceThe regenerative and label-free sensing capacity of the proposed device provides a theoretical foundation for label-free saccharide detection and the development of wearable glucose monitoring devices based on fiber optic sensors.

Triboelectric Nanosensor Fabricated on Robotic Platform for Self-Powered Detection of Heavy Metal Ions in Aquatic Environments

The escalation of heavy metal ions pollution, caused by the natural processes as well as human activities has emerged as a significant global challenge. The accumulation of heavy metal ions in the human body primarily occurs through water and food consumption which poses a severe threat leading to irreversible health damage. To address this issue, the World Health Organization (WHO) has established permissible limits for various heavy metal ions in drinking water, ranging from 0.003 to 3 ppm. When these limits are exceeded, water is deemed contaminated which necessitates effective monitoring and detection strategies. Robotic chemical sensing platforms have become indispensable for tackling chemical threats by detecting harmful pollutants in toxic environments. However, chemical sensors integrated with robotic platforms encounter drawback such as reliance on external power sources. In response to this challenge, our approach integrates a highly sensitive, self-powered triboelectric nanosensor (TENS) into a robotic platform charged by a thermoelectric generator (TEG) and equipped with wireless transmission capabilities. This integration enables the rapid on-site detection of heavy metal ions. The system employs copper electrodes modified with ion-selective membranes (ISM) as sensing probes and solid triboelectric contact materials. Through periodic contact-separation cycles with ionic solutions, the system generates electrical output, facilitating the detection of various concentrations of Pb2+, As3+, and Cr6+ ions. The ionophores in the respective ISMs contribute to the selective binding capacity of the sensing probe to the particular ion. This self-powered robotic platform provides an innovative and cost-effective solution for automated chemical sensing in water environments. Its advantages include the avoidance of external power sources, low-cost operation, and the elimination of the need for frequent battery replacements. With its capability for remote monitoring and detection, this system emerges as an ideal tool for preventing and controlling heavy metal ions pollution, ultimately contributing to the intelligent monitoring of heavy metal ions in aquatic environments. Keywords: Heavy metal ions, Solid-liquid triboelectric nanosensor, Robotic platform, Self-powered detection, Copper electrodes.

The Resurgence of Hydrogen Depolarized Anodes: A Catalyst for Change in Industrial Electrochemistry

This presentation delves into the remarkable history of Hydrogen Depolarized Anodes (HDAs) and their relevance to modern industrial electrochemistry. HDAs were originally developed in the early 1970s, but their use has been confined to fuel cell technology and power generation. In the wake of a growing green hydrogen economy and the escalating price of precious metal catalysts, this technology is now emerging as a useful tool to boost the energy efficiency and lower both capital and operational costs of electrified chemical manufacturing processes. Our discussion recounts the evolution of HDA technology, from its conceptual beginnings to its current role as an innovative solution in electrochemical processes.The recent renaissance of HDAs is driven largely by economic and environmental factors. As chemical industries strive to electrify their processes, they also grapple with the rising cost of conventional anode materials. The increasing affordability and availability of hydrogen presents HDAs as a viable and efficient alternative. This shift is not just about cost-saving; it's about embracing a technology that aligns with the principles of sustainability and circular economy.We will explore various applications where HDAs are making a significant impact, such as in the manufacturing of acids and bases, the production of metals such as iron, copper, and zinc, and more experimental processes such as cement production. These examples not only demonstrate the versatility of HDAs, but also underscore their potential in achieving higher energy efficiency than conventional technologies and reducing environmental footprint of a range of industrial operations.Furthermore, our talk will illuminate how HDAs are a stepping stone towards a broader adoption of hydrogen as a cornerstone of industrial electrochemistry. The implementation of HDA technology is more than an innovation; it's a transformative step forward, signaling a new era in chemical manufacturing where sustainability and efficiency go hand in hand.

Real-time hardware emulation of neural cultures: A comparative study of in vitro, in silico and in duris silico models

Biological neural networks are well known for their capacity to process information with extremely low power consumption. Fields such as Artificial Intelligence, with high computational costs, are seeking for alternatives inspired in biological systems. An inspiring alternative is to implement hardware architectures that replicate the behavior of biological neurons but with the flexibility in programming capabilities of an electronic device, all combined with a relatively low operational cost. To advance in this quest, here we analyze the capacity of the HEENS hardware architecture to operate in a similar manner as an in vitro neuronal network grown in the laboratory. For that, we considered data of spontaneous activity in living neuronal cultures of about 400 neurons and compared their collective dynamics and functional behavior with those obtained from direct numerical simulations (in silico) and hardware implementations (in duris silico). The results show that HEENS is capable to mimic both the in vitro and in silico systems with high efficient-cost ratio, and on different network topological designs. Our work shows that compact low-cost hardware implementations are feasible, opening new avenues for future, highly efficient neuromorphic devices and advanced human–machine interfacing.

Efficient removal of direct dyes by SA-Er biopolymer gel spheres: Equilibrium isotherms, kinetics and regeneration performance study

Biomass-based adsorbent materials are characterized by their low cost, environmental friendliness, and ease of design and operation. In this study, biomass-based hydrogel microspheres erbium alginate (SA/Er) with high stability and adsorption properties were prepared by a one-step synthesis method. The prepared materials were characterized and analyzed by SEM-EDS, XRD, TGA, FT-IR, UV–Vis, BET-BJH and XPS, and the adsorption performance of SA/Er was investigated for high concentrations of azo dyes in water. The results showed that the adsorption performance of SA/Er on the azo dyes of direct violet N (DV 1) and direct dark green NB (DG 6) with concentrations of 850 mg/L and 1100 mg/L under the optimal conditions was very high, and the adsorption amount could be up to 692 mg/g and 864 mg/g, respectively. The adsorption process was in accordance with the quasi-secondary kinetic model, which was accomplished by physical and chemical adsorption; the Langmuir isothermal model was able to better respond to the adsorption equilibrium, and the adsorption was dominated by the adsorption of surface monolayers; after seven desorption cycles, the removal of both azo dyes by the adsorbent material could reach >79.7 %. Combined with the results of FT-IR, UV–vis and XPS analysis before and after the adsorption, it was revealed that the adsorption of SA/Er with the dye molecules mainly consisted of hydrogen bonding, electrostatic adsorption and surface complexation, which resulted in the significant adsorption effect on the two azo dyes, and the above results can provide a reference for the treatment of dye wastewater.

The future of Ni-Cu smelting in Botswana: the choice between flash-smelting and top-submerged lance furnaces

The BCL furnace is scheduled to restart operations after being placed on care and maintenance in 2016 due to depressed nickel prices. The decision to start operations after such a stoppage ought to be led by a techno-economic evaluation of process options to make operations more resilient. For BCL, the decision lies between using the existing flash-smelting furnace (FSF) or a top-submerged lance (TSL) furnace. Available studies show that the FSF combined with other converting technologies is cheaper to operate; however, such studies are based on flowsheet simulation results of single copper concentrates and therefore do not provide a full scope of practical capabilities based on smelter operator skills. Using a t-test on normalized prior operational data from three Cu FSF and two Cu TSL, it was found that the only statistical differences between the operating costs of the FSF and TSL technologies are in the coal use for heating the feed blow and number of rebuilds: the FSF consumes coal to heat the feed blow and the TSL requires 2.4 rebuilds during a course of a single FSF campaign. A summative operating cost comparison over the existing BCL FSF 11-year life shows that BCL can decrease operational costs by some BWP 55.5 million if the operation were to change to the newer TSL technology. The savings derive from reduced coal use, which is normally associated with heating the blow when using the FSF. Despite the TSL carrying added costs of 2.4 rebuilds during a life time of one FSF furnace campaign, the cost associated with the TSL rebuilds of approximately BWP 1.3 million is minimal compared with the overall operational expenditure decrease that BCL will incur on using the TSL technology. In terms of the technology, BCL can have higher Ni-Cu recoveries at lower operational costs by elimination of Ni-Cu losses and eliminating the slag-cleaning furnace by converting to a TSL furnace.

Study on energy-saving applications of vacuum ejectors across various operational demands

Vacuum suction technology is a pivotal innovation within the Industry 4.0 revolution. Ejectors serve as the core of vacuum systems with distinct advantages such as simple structure, low cost, and ease of operation. However, traditional fixed ejectors suffer from low efficiency, energy waste, and poor adaptability. This study aims to optimize the design of vacuum ejectors to meet various requirements, achieving energy efficiency and high performance in automated production. On this basis, an energy-saving vacuum system based on dual ejectors is proposed, which can switch between single and dual ejectors depending on different working stages. When the vacuum reaches 90 kPa, the required motive pressure and the entrainment ratio are selected as the screening indicators for the vacuum ejector. A two-dimensional axisymmetric model is established and verified through experimentation. The key parameters are identified through a single-factor analysis. A multi-factor analysis is employed to determine the recommended values for each parameter and their respective applications. The energy-saving effects of the optimized ejectors are evaluated in conjunction with the automated processes. The findings indicate that the vacuum system based on dual ejectors can achieve rapid response and low air consumption. This paper contributes to advancing the research on energy-saving applications of ejectors.

Hyperthermophilic composting of livestock waste drastically reduces antimicrobial resistance

Composting is the most common method for managing livestock waste. However, it often fails to effectively eliminate antimicrobial resistance, resulting in potential antimicrobial resistance in livestock waste. Hence, a more effective livestock waste management strategy is warranted. The hyperthermophilic composting method uses recycled compost containing hyperthermophilic microbes to raise the compost temperature up to approximately 100 °C (compost temperature in normal composting: 50–70 °C). This study clarifies the effectiveness of hyperthermophilic composting method in attenuating antimicrobial resistance during livestock waste composting in both a composting simulator and on a field dairy farm. We analyzed bacterial abundance and community composition, performed PCR analysis, and evaluated the concentration of residual antimicrobials in the compost. Hyperthermophilic composting significantly reduced the abundance of culturable bacteria and Escherichia coli including that of antimicrobial-resistant culturable bacteria and E. coli in both the simulated and field dairy farms. The copy numbers of the tested antimicrobial resistance genes (tetA, tetB, blaTEM, and blaCTX-M) decreased substantially. Residual antimicrobials (tetracyclines and β-lactams) were not detected in the field dairy farms, and network analysis showed that potential hosts of antimicrobial-resistance genes were eliminated. These results indicate that hyperthermophilic composting significantly reduces the abundance of antimicrobial-resistant bacteria, antimicrobial-resistance genes, and residual antimicrobials at low cost and easy operation while generating valuable agricultural resource as the final output.

Determining the Location of Solar Power Plant in Indonesia Using Fuzzy-AHP TOPSIS

Solar is a promising renewable energy source for Indonesia's increasing electricity demand, which grows at the rate of 3.3% annually. However, high investment costs and unclear policies hinder Solar Power Plant (SPP) development. Considering the potential for growth in energy demand and the low long-term operational costs, it is imperative to foster SPP expansion in Indonesia. This study aims to identify location criteria and potential SPP development sites in Indonesia. We employ Multi-Criteria Decision-Making (MCDM) combining Fuzzy-AHP and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodologies to assign criteria weights and prioritize alternative SPP locations. Results show that, from all respondents using the geometric mean in the Fuzzy Analytic Hierarchy Process (AHP), it is found that the Economic criteria give the highest weight at 31%, and subcriteria of Land Availability, Peak Sun Hours, Geographic Location, Distance from Transportation Networks, Construction Costs, and Government Regulations contribute significantly. The ranking of alternative solutions indicates that South Sumatra Province holds the highest priority for SPP development with a 0.572 score, closely followed by North Sumatra at 0.571

Integration of Information Technology and Machine Learning to Improve the Efficiency of IoT-Based Logistics Systems

In today's digital era, efficiency in supply chain management and logistics is the main key to maintaining business competitiveness. This article discusses the integration of Information Technology (IT) and Machine Learning (ML) in Internet of Things (IoT)-based logistics systems to improve operational efficiency. By leveraging IoT sensors for real-time data collection and ML algorithms for predictive analysis, the system is able to optimize inventory management, route planning, and preventive maintenance. The case studies discussed in this article show that the use of ML in IoT-based logistics systems can reduce delivery times, lower operational costs, and increase responsiveness to changes in market demand. The results of this study are expected to provide insight for system developers and logistics managers in implementing advanced technologies to address challenges in the modern logistics industry.

A multi-agent deep reinforcement learning paradigm to improve the robustness and resilience of grid connected electric vehicle charging stations against the destructive effects of cyber-attacks

The rising deployment of electric vehicle charging stations (EVCS) in existing power grids and their integration with electric vehicles through communication systems are increasingly vulnerable to cyber-attacks, such as false data injection (FDI) and uncertainties of communication system. This research introduces an EVCS evaluation from a techno-economic standpoint, utilizing the developed and data-oriented TSKFS&MADRL technique to identify and rectify inaccuracies stemming from cyber-attacks like FDI and communication system delays. This method aims to enhance the resilience of EVCSs against sabotage attacks by ensuring fast dynamic responses. Initially, the study models the potential targets of hackers, such as communication systems and transducer sensors, and employs the Euclidean norm theory, weighted least square error method, and residual error technique to identify cyber-attacks resulting from FDI through the comparison of measured data with reference values based on probability distribution functions. Subsequently, the network control and recovery requirements are facilitated by the proposed controller. The proposed approach application has been demonstrated in the IEEE 33 bus, showcasing a 7.33 % lower experimental operation cost compared to the RL method and 12.15 % lower than the CNN method. Additionally, the FDI detection time is observed to be 40 % quicker than alternative methods based on the experimental outcomes.

On the selection of aircraft-engine pairs for medium-haul Low-Cost Carriers operations

The selection of aircraft and engine models poses a significant challenge for Low-Cost Carriers (LCCs) striving for profitability. This decision is compounded by numerous subjective and objective variables and the vast array of available aircraft and engine configurations. Current methodologies, utilizing Multi-Criteria Decision Making (MCDM) and fuzzy logic, often simplify the problem, neglecting the engine consideration and limiting variables and alternatives. In this paper, we propose a novel methodology that circumvents these simplifications, considering engine configurations within the aircraft selection and addressing this problem for 27 parameters and real 51 selection alternatives. Through the consultation of different experts in the aeronautic field, we establish a comprehensive approach to assess the relative and overall performance of multiple variables, as well as their weights and hierarchy in the selection scheme. We apply this methodology to the aircraft selection problem in the medium-haul market, providing a framework and a solution for this currently unexplored literature domain. The results provide valuable insights for validating the devised methodology and providing relevant insights on the characteristics of the medium-haul market for LCCs.

Evaluation of industrial and consumer 3-D resin printer fabrication of microdevices for quality management of genetic resources in aquatic species

Aquatic germplasm repositories can play a pivotal role in securing the genetic diversity of natural populations and agriculturally important aquatic species. However, existing technologies for repository development and operation face challenges in terms of accuracy, precision, efficiency, and cost-effectiveness, especially for microdevices used in gamete quality evaluation. Quality management is critical throughout genetic resource protection processes from sample collection to final usage. In this study, we examined the potential of using three-dimensional (3-D) stereolithography resin printing to address these challenges and evaluated the overall capabilities and limitations of a representative industrial 3-D resin printer with a price of US$18,000, a consumer-level printer with a price <US$700, and soft lithography, a conventional microfabrication method. A standardized test object, the Integrated Geometry Sampler (IGS), and a device with application in repository quality management, the Single-piece Sperm Counting Chamber (SSCC), were printed to determine capabilities and evaluate differences in targeted versus printed depths and heights. The IGS design had an array of negative and positive features with dimensions ranging from 1 mm to 0.02 mm in width and depth. The SSCC consisted of grid and wall features to facilitate cell counting. The SSCC was evaluated with polydimethylsiloxane (PDMS) devices cast from a typical photoresist and silicon mold. Fabrication quality was evaluated by optical profilometry for parameters such as dimensional accuracy, precision, and visual morphology. Fabrication time and cost were also evaluated. The precision, reliability, and surface quality of industrial-grade 3-D resin printing were satisfactory for operations requiring depths or heights larger than 0.1 mm due to a low discrepancy between targeted and measured dimensions across a range of 1 mm to 0.1 mm. Meanwhile, consumer-grade printers were suitable for microdevices with depths or heights larger than 0.2 mm. While the performance of either of these printers could be further optimized, their current capabilities, broad availability, low cost of operation, high throughput, and simplicity offer great promise for rapid development and widespread use of standardized microdevices for numerous applications, including gamete quality evaluation and “laboratory-on-a-chip” applications in support of aquatic germplasm repositories.

Comparison of Four Tests for the Diagnosis of Helicobacter pylori Infection.

Due to lower operational costs, health maintenance organizations (HMOs) may prioritize Helicobacter pylori stool antigen testing (HpStAg) for the non-invasive diagnosis of H. pylori infection over 13C-urea breath tests (13C-UBTs). The aim of our study was to compare the accuracy of the diagnostic tests for H. pylori. We performed histology, rapid urease test (RUT), 13C-UBT and HpStAg on consecutive patients referred for gastroscopy. Monoclonal stool antigen test was performed using the LIAISON Meridian chemiluminescent immunoassay. Histology was examined with hematoxylin and eosin, and additional stains were performed at the pathologist's discretion. For the assessment of 13C-UBT, we compared concordant histology and RUT. HpStAg was compared to the concordant results of two of the three remaining tests. 103 patients were included (36 males (35.0%), age 50.1 ± 18.4 years). The indication for gastroscopy was dyspepsia in 63 (61.2%). Agreement between RUT and histology was 95.9%. For 13C-UBT and HpStAg, respectively, H. pylori positivity was 30% (30/100) and 27.16% (22/81); sensitivity was 97% and 70%; specificity was 100% and 94.4%; accuracy was 98% and 86%; positive predictive value (PPV) was 100% and 86.4%; negative predictive value (NPV) was 93% and 86%. No demographic, clinical, or endoscopic predictors of HpStAg accuracy were identified using logistic regression. 13C-UBT performs better than HpStAg at our institution. When interpreting results, clinicians should consider test limitations.

Feasibility analysis of hybrid photovoltaic, wind, and fuel cell systems for on–off‐grid applications: A case study of housing project in Bangladesh

AbstractThis study investigates the viability of hybrid photovoltaic (PV), wind, and fuel cell (FC) systems for on‐grid and off‐grid operations for the Ashrayan‐3 housing project in Bangladesh, with an increased focus on sustainable energy solutions. Motivated by the issue of the delivery of proper and sustainable energy services to remote locations, we conducted an extensive analysis of load demand and found that an average daily demand of 46,176.65 kWh exists, with a peak load of 4852.8 kW. In this research, the HOMER software has been used to make a simulation of five different hybrid system configurations with differing mixes of renewable technologies. From the analyses, the systems based 100% on renewable resources suffer more initial capital costs, with a total net present cost increase of up to 20%, in comparison to conventional systems. On the other hand, the systems give much lower operational costs and cost of energies (COEs) of a minimum of $0.0253/kWh, reported from the on‐grid PV‐based system. On the other hand, the off‐grid PV–FC–wind turbine system showed a COE of $0.286/kWh, along with a decrease in CO2 emissions by about 15,000 kg/year, showing a 30% decrease, compared with on‐grid systems. The results form a basis for the conclusion that such hybrid renewable energy systems are both economically and environmentally feasible. They can reduce COEs by up to 70% in off‐grid systems. This proves that the quality of life and energy security in developing regions will be highly increased, supporting the goals of sustainable development.