High Cost Research Articles

Bio-plausible reconfigurable spiking neuron for neuromorphic computing.

Biological neurons use diverse temporal expressions of spikes to achieve efficient communication and modulation of neural activities. Nonetheless, existing neuromorphic computing systems mainly use simplified neuron models with limited spiking behaviors due to high cost of emulating these biological spike patterns. Here, we propose a compact reconfigurable neuron design using the intrinsic dynamics of a NbO2-based spiking unit and excellent tunability in an electrochemical memory (ECRAM) to emulate the fast-slow dynamics in a bio-plausible neuron. The resistance of the ECRAM was effective in tuning the temporal dynamics of the membrane potential, contributing to flexible reconfiguration of various bio-plausible firing modes, such as phasic and burst spiking, and exhibiting adaptive spiking behaviors in changing environment. We used the bio-plausible neuron model to build spiking neural networks with bursting neurons and demonstrated improved classification accuracies over simplified models, showing great promises for use in more bio-plausible neuromorphic computing systems.

Digital transformation of tourism education: Technologies, opportunities, challenges, and future research agenda

This study explores the integration of these technologies into tourism curricula, highlighting both opportunities and challenges. While digital tools enhance experiential learning, accessibility, and industry relevance, their adoption is hindered by high costs, faculty training, and resistance to change. The study employs qualitative research through semi-structured interviews with tourism educators to examine the effectiveness of digital tools and their impact on student learning. Findings indicate immersive technologies improve engagement, while cloud computing and AI facilitate data-driven decision-making. However, further research is needed to address institutional barriers and ensure equitable access to digital education. The study concludes with a future research agenda to optimize digital transformation strategies in tourism education.

Point-of-care ultrasound in the diagnosis and management of community-acquired Pneumonia in out-of-hospital care: a narrative review

The article reviews the use of Point-of-Care Ultrasound (POCUS) in the diagnosis and management of community-acquired pneumonia (CAP) in extra-hospital settings, such as primary healthcare, outpatient clinics, and home care. CAP is one of the main causes of morbidity and mortality across different age groups, including children and the elderly, requiring quick and accurate diagnoses to improve clinical outcomes. Traditionally, methods such as chest X-rays (CXR) and computed tomography (CT) scans are used to diagnose CAP, but they have limitations such as high cost, the need for specialized infrastructure, and radiation exposure. POCUS emerges as an effective alternative, offering high accuracy and being feasible for use by healthcare professionals who are not specialists in imaging diagnosis. Its portability and accessibility make it especially useful in remote or underserved areas. The absence of radiation makes POCUS particularly beneficial for sensitive populations, such as pregnant women. The review analyzed 27 studies published between 2015 and 2024, highlighting that POCUS not only competes with traditional methods in terms of accuracy but also provides additional advantages, such as the possibility of repeating exams for continuous clinical monitoring. In pediatrics and geriatrics, POCUS has proven particularly effective, surpassing chest X-rays in some diagnostic aspects. Moreover, the implementation of POCUS in primary care can reduce healthcare costs by decreasing the need for conventional imaging exams and hospital admissions. The tool has also proven to be valuable in public health emergencies, such as the COVID-19 pandemic, where it facilitated rapid diagnoses and monitoring of pulmonary complications. However, challenges persist, such as interobserver variability and the need for adequate training to maximize the reproducibility of the findings. The integration of artificial intelligence and the development of specific protocols for primary care are future perspectives that can further enhance the effectiveness of POCUS. It is concluded that POCUS has great potential to transform the diagnosis and management of CAP in out-of-hospital settings, promoting faster, more accurate, and accessible diagnoses, as well as contributing to greater equity in access to healthcare.

Progress in 2D MoS2-Based Advanced Materials for Hydrogen Evolution and Energy Storage Applications

The increasing energy demand for and fast depletion of fossil fuels have driven the need to explore renewable and clean energy sources. Hydrogen production via water electrocatalysis is considered a promising green fuel technology for addressing global energy and environmental challenges while supporting sustainable development. Molybdenum disulfide (MoS2) has emerged as a potential electrocatalyst for hydrogen evolution reactions (HERs) and super-capacitor (SC) applications due to its high electrochemical activity, low cost, and abundance. However, compared to noble metals like platinum (Pt), MoS2 exhibit lower HER activity in water electrocatalysis. Therefore, further modification is needed to enhance its catalytic performance. To address this, MoS2 has been effectively modified with materials such as reduced graphene oxide (rGO), carbon nanotubes (CNTs), polymers, metal oxides, and MXenes. These modifications significantly improve the electrochemical properties of MoS2, enhancing its performance in HER and SC applications. In this review article, we have compiled recent reports on the fabrication of MoS2-based hybrid materials for HER and SC applications. The challenges, advantages, and future perspectives of MoS2-based materials for HERs and SCs have been discussed. It is believed that readers may benefit from the recent updates on the fabrication of MoS2-based hybrid materials for HER and SC applications.

Electric Vehicle Charging Stations in India: Challenges, Business Prospects, and Future Opportunities

The significant transition to Electric Vehicles (EVs) has been prompted by the increasing concern about environmental sustainability, the accumulation of carbon emissions, and a heavy reliance on fossil fuels. EVs have emerged as a potential alternative to Internal Combustion Engine (ICE) vehicles. The development of a comprehensive and accessible charging infrastructure is a critical component of this transition, necessitating the installation of Electric Vehicle Charging Stations (EVCS). Establishing EVCS presents numerous obstacles. The critical issue of load forecasting has arisen as a result of the rapid increase in the number of electric vehicles (EVs), particularly in order to prevent grid overloads. Additionally, the regulatory requirements may complicate the process of locating an appropriate location for charging stations, particularly in urban areas that have been developed. High upfront investment costs and uncertain returns compound financial challenges. Additionally, it alleviates congestion during prime station hours and minimizes the time required for drivers to recharge their batteries. It is imperative to address these obstacles in order to reduce the likelihood of prospective obstacles to the equitable implementation of EVCS. The paper's examination of the challenges associated with the establishment of EVCS in India is discussed, as well as the potential opportunities for entrepreneurs and enterprises to enter this emerging market. It also examines the current regulations regarding charging stations, including those that are either rapid or slow. The installation of EVCS is facilitated by financial resources provided by the government and local authorities. The section concludes with a prospective examination of emerging technologies, including renewable energy integration and smart charging solutions, which have the potential to enhance the charging infrastructure. In addition, the paper explores a variety of business models and strategies for the establishment of successful charging station businesses, such as pricing structures, strategic alliances, and customer service. The study examines the overall feasibility of various configurations of EVCS, consumers' demand trends, and the impact on the power grid using simulated primary data, among other business viability indicators. These suggestions will be beneficial in expediting the development of a more sustainable and energy-efficient EV transition ecosystem in India. Stakeholders can assist in the development of a more environmentally friendly transportation ecosystem by addressing multifaceted obstacles and seizing new opportunities. Keywords—Electric Vehicle (EV), Electric Vehicle Charging Station (EVCS), Renewable Energy Sources (RES), Smart Grid, Battery Swapping Station (BSS), Intelligent Transport System (ITS), Vehicle-to-Grid (V2G), Business Model, Charging Infrastructure, Simulated Data Analysis.

Societal impacts and opportunities of federated learning

Artificial intelligence (AI) systems have the potential to significantly enhance various aspects of human life, including healthcare, employment, energy management, finance, and creative endeavors. However, the rise of larger, computationally intensive AI models has also led to concerns about their negative societal impacts, such as increasing economic concentration, higher energy emissions, and threats to data privacy. In this paper, we examine the societal implications of a promising machine learning approach called federated learning. We begin by reviewing ongoing research challenges, noting that federated learning is often promoted as a potential solution to mitigate issues of economic concentration, environmental harm, and privacy concerns associated with AI. While federated learning systems hold significant promise, they are currently at an early stage of development and face critical technical challenges, including data leakage risks and high communication costs, which need to be addressed before widespread adoption can occur.

Advanced theoretical modeling methodologies for electrocatalyst design in sustainable energy conversion

Electrochemical reactions are pivotal for energy conversion and storage to achieve a carbon-neutral and sustainable society, and optimal electrocatalysts are essential for their industrial applications. Theoretical modeling methodologies, such as density functional theory (DFT) and molecular dynamics (MD), efficiently assess electrochemical reaction mechanisms and electrocatalyst performance at atomic and molecular levels. However, its intrinsic algorithm limitations and high computational costs for large-scale systems generate gaps between experimental observations and calculation simulation, restricting the accuracy and efficiency of electrocatalyst design. Combining machine learning (ML) is a promising strategy to accelerate the development of electrocatalysts. The ML-DFT frameworks establish accurate property–structure–performance relations to predict and verify novel electrocatalysts' properties and performance, providing a deep understanding of reaction mechanisms. The ML-based methods also accelerate the solution of MD and DFT. Moreover, integrating ML and experiment characterization techniques represents a cutting-edge approach to providing insights into the structural, electronic, and chemical changes under working conditions. This review will summarize the DFT development and the current ML application status for electrocatalyst design in various electrochemical energy conversions. The underlying physical fundaments, application advancements, and challenges will be summarized. Finally, future research directions and prospects will be proposed to guide novel electrocatalyst design for the sustainable energy revolution.

Integrating Fiber Broadband and 5G Network: Synergies and Challenges

The integration of fiber broadband and 5G networks represents a significant leap forward in telecommunications, promising to revolutionize connectivity and enable a plethora of advanced applications. This research paper delves into the synergy between fiber broadband and 5G, examining the technological, economic, and societal impacts of this convergence. By leveraging the high bandwidth and low latency of fiber optics alongside the ultra-fast wireless capabilities of 5G, this integration offers unprecedented network performance and reliability.[1] We explore the key components that make this integration possible, including the deployment of fiber optic infrastructure, the utilization of 5G technology, and the role of edge computing in reducing latency. The paper highlights the numerous benefits of fiber-5G integration, such as enhanced connectivity, increased network reliability, and support for emerging technologies like IoT and smart cities.[2] However, the integration also presents several challenges, including the high costs and logistical complexities of infrastructure deployment, technological compatibility issues, and security concerns. Through detailed case studies, we illustrate real-world implementations of fiber-5G integration, showcasing the practical benefits and solutions to these challenges.[3] Looking ahead, the paper discusses future prospects for fiber-5G integration, emphasizing the potential of AI-driven network management, advanced edge computing, and network slicing to further enhance network capabilities. Ultimately, this research underscores the transformative potential of fiber broadband and 5G integration in shaping the future of telecommunications and driving innovation across various sectors. Keywords: Fiber Optics, 5G, Network Integration, Fiber- Wireless convergence, Edge Computing

An Analysis of Banana Cultivation in Wayanad District, Kerala

Objective: analyse area and production, to examine the production, cost performance and socio-economic problems of banana cultivation in Wayanad district in Kerala. Methods/statistical analysis: This study relies completely primary information obtained from the banana cultivators from the selected study area. The research design of the present study included in selection of study areas, selection of sample farmers, collection of data, analysis of data and presenting findings selection of study area purposive sampling procedure was followed for the selection of the study area. First the data of Krishi bhavan under all four blocks of Wayanad were selected, through Krishi bhavan officers, information about banana cultivators was selected. Then 100 farmers were randomly selected from among them. Findings: From the income analysis it seen that majority of the cultivators are earn 1lakh to 3 lakhs. Nendran variety is more profitable than other varieties followed by robusta variety. Among the main problem faced by the banana cultivators most of the respondents are reported natural calamities are main reason. high cost of production is the second most problem faced by banana cultivators. Many of those who had previously taken crop insurance are not now willing to take insurance because of the amount due is not received on time. When the price of bananas falls, farmers incur higher costs to get them to VFPCK stores to get the support price given by the government. Application/improvement: It is suggested that casuarina may be planted around the banana’s place of cultivation as a windbreaker to save the banana plants from lodging due to heavy wind. The banks and co-operatives should make necessary arrangements to increase the loan amount to meet the requirement of the cultivators. set up more VFPCK stores where banana farmers can easily access them.

Oyster Mushroom (Pleurotus ostreatus) and Okara Flour as Nutritional Enhancers in Wheat Biscuits: A Study on Storage Stability

In response to the scarcity and high cost of wheat in Nigeria, this study investigates the potential of oyster mushroom (Pleurotus ostreatus) and okara flour to enhance the nutritional quality and storage stability of wheat biscuits. By incorporating 10–50% oyster mushroom powder into wheat flour, this study observed significant increases in the nutritional profile of the biscuits. The protein content notably increased from 8.26% to 16.12%, while the crude fibre and ash content also saw over a 50% increment. Storage studies revealed that biscuits (baked for 18 min at 180 °C) packaged in cartons within polyethene were more shelf-stable than those in low-density polyethylene (LDPE) bags, maintaining quality over two months at ambient temperature. The inclusion of oyster mushroom and okara flour in wheat biscuits significantly enhances their nutritional value and shelf life, presenting a viable solution to the challenges of wheat scarcity and global malnutrition. The optimal mushroom flour enrichment level was identified at 20% to maintain consumer appeal.

High cost of governance and socio-economic development in Nigeria

High cost of governance and socio-economic development in Nigeria

Current Use, Challenges, Barriers, and Chances of Telemedicine in the Ambulatory Sector in Germany-A Survey Study Among Practicing Cardiologists, Internists, and General Practitioners.

Introduction: Digital technologies, such as telemedicine and wearable devices, are transforming health care by enhancing cross-sectoral care and targeted health responses. Despite these advancements, challenges such as data protection, lack of interoperability, reimbursement, and financial costs hinder telemedicine's broader implementation, especially within the German health care system. This study explores the use, acceptance, and barriers of telemedicine among cardiologists, internists, and general practitioners in Germany. Methods: A web-based survey was conducted from October 2023 to January 2024, targeting cardiologists, internists, and general practitioners. The survey assessed current telemedicine usage, acceptance, and barriers. Data analysis included descriptive statistics and exploratory cluster analysis. Results: Of the 172 physicians analyzed, 76.2% were cardiologists. Telemonitoring (45.9%) and wearable devices (26.2%) were the most used telemedicine applications, whereas video consultations (11.0%) and apps (19.2%) were less common. Despite high costs (57.7%), insufficient technical expertise (20.8%), and lack of system interoperability (45.8%), respondents rated telemedicine positively and saw several chances and potentials. Cluster analysis identified four user groups: The pioneers, the focused practitioners, the using skeptics, and the uninformed distanced, each with unique needs and challenges. Discussion: The acceptance of elemedicine among physicians indicates recognition of its benefits for patient care. Only half of the respondents felt reasonably well informed about telemedicine. Overall, our study shows the current use of telemedicine as well as the acceptance, barriers, and challenges perceived in the German ambulatory sector. It underlines the increasing importance of telemedicine for patient care and highlights existing barriers to enable wider implementation in the outpatient sector. The results show that telemedicine in Germany is on a promising path. The biggest obstacles still appear to be reimbursement and the technical infrastructure.

Influence of different extraction methods on the cannabinoid profile in Cannabis sativa oil

The research focuses on optimizing extraction methods for Cannabis sativa to ensure the production of high-quality oils with consistent cannabinoid profiles, critical for therapeutic applications. The study highlights the plant’s medicinal potential, driven by bioactive compounds such as cannabidiol (CBD) and tetrahydrocannabinol (THC), which are effective against various conditions, including epilepsy and chronic pain. The objective is to evaluate and compare advanced extraction techniques like supercritical CO₂, ethanol-based, and microwave-assisted extraction to identify methods that balance efficiency, yield, and sustainability. Upon exploration, the study reviewed scientific literature, analyzing efficiency metrics and cost-effectiveness across methods. Results underscore the superiority of supercritical CO₂ extraction for purity and pharmaceutical-grade standards but note its high cost. Ethanol-based techniques are cost-effective but require additional refinement. Microwave-assisted methods offer terpene preservation but lack scalability. These findings stress the need for hybrid techniques that integrate advantages while addressing limitations. The research concludes that standardization and technological innovations are essential to overcome inconsistencies in cannabinoid profiles, enhancing clinical and industrial viability. It advocates for interdisciplinary collaboration to improve extraction protocols, ensuring sustainable and effective use of Cannabis sativa in medicine.

Feasibility and efficiency of microalgae cultivation for nutrient recycling and energy recovery from food waste filtrate.

With the continuous growth of economic and population, the generation of food waste has significantly increased in recent years. The disposition of food waste, typically through incineration or landfill, can lead to severe health and environmental problems, accompanied by high additional costs. However, the leachate produced from food waste during collection, transportation and landfill operations predominantly contains high levels of nutrients necessary for microalgae growth. The integration of microalgae cultivation into waste treatment for nutrient recycling presents a potential route for energy recovery from food waste. Therefore, this study was conducted to evaluate the feasibility of microalgae cultivation for food waste filtrate treatment. In addition, the optimal cultivation conditions and nutrient removal efficiency for microalgae in food waste filtrate treatment were investigated. The results indicated that Cyanobacterium aponinum exhibited the highest growth rate (0.530 cells d-1) and maximum cell density (9.6 × 106 cells mL-1) among eight potential microalgal species in 10% food waste filtrate treatment under 10,000 lux and 32°C. It was also observed that C. aponinum had significantly higher biomass productivity and nutrient removal efficiency under a 5% CO2 concentration. The successful cultivation of C. aponinum demonstrated that food waste filtrate could be a promising growth medium, reducing the high cost of cultivation with synthetic medium. However, further efforts should be made to utilize microalgae in food waster filtrate treatment, transitioning from laboratory condition to a pilot scale.

Enhancing anatomy education using anatomical sign language: expanding its expressive capabilities to the upper and lower extremities, face, and brain structures.

Various information technologies have been introduced for anatomy education in the current digital era, including three-dimensional (3D) virtual reality, mobile augmented reality, and 3D printing. While these technologies enhance educational effectiveness, their high cost often restricts their accessibility. Conversely, low-cost methods using everyday items have proven effective in anatomy education. The anatomical sign language (ASL) method has been introduced, and uses the fingers, hands, and arms to represent anatomical structures to leverage muscle memory to aid the retention and understanding of complex anatomical structures and provide a comprehensive and interactive approach to anatomy education. This study was performed to expand ASL to include the expressive capabilities of the upper and lower extremities, and the face and brain. The results indicate that ASL effectively illustrates the anatomy of various structures. The educational benefits of ASL for anatomy and radiologic anatomy education are discussed.

A review on enhancing water productivities adaptive to the climate change

ABSTRACT Crop water requirements depend on climate, soil, and plant characteristics, necessitating responsive and adaptive irrigation systems for efficient water use. The objectives of this study include assessing the implementation of irrigation technology and its impact on water use efficiency, reviewing smart irrigation systems employed as irrigation management systems, and introducing evapotranspirative irrigation technology as a straightforward smart irrigation approach. Globally, research on irrigation technologies highlights significant potential for water conservation. Smart irrigation system, as a facet of irrigation system management, is considered strategic approach for effective irrigation implementation. The adoption of micro-irrigation systems in cultivated crops has shown promising results in enhancing water productivity and significantly increasing yield rates, but smallholder farmers resist due to high costs. This study introduces innovative approaches using simple automatic technology based on the principle of evapotranspiration, aiming to mitigate high costs. This technology is designed to distribute water optimally at the highest evapotranspiration rate during prolonged dry periods. The key success indicators focus on water productivity, encompassing crop water, irrigation water, and total water. The evapotranspirative irrigation system is pivotal in regulating evapotranspiration rates, resulting in reduced water evaporation and increased land and water productivities, making it adaptive to the impacts of climate change.

Pyridylboronic Acid- and Poly(ethylene glycol)-Functionalized PEDOT Copolymers for Electrochemical Detection of Sialic Acid-Rich Cancer Biomarkers in Serum.

The detection of carbohydrate antigen 19-9 (CA199), a critical biomarker for pancreatic, colorectal, and gastric cancers, is essential for early diagnosis and disease monitoring. Traditional antibody-based assays for CA199 detection are limited by high costs, time-consuming procedures, and susceptibility to nonspecific interference. This study presents an electrochemical biosensor based on a multifunctional poly(EDOT-PyBA-co-EDOT-PEG) copolymer designed to overcome these limitations. The biosensor integrates pyridylboronic acid (PyBA) moieties for specific recognition of sialic acid residues and poly(ethylene glycol) (PEG) chains for antifouling properties within a conductive PEDOT framework. By eliminating antibody dependency, the biosensor reduces costs, enhances stability, and simplifies the diagnostic process. Surface characterization confirmed the successful incorporation of PyBA and PEG units, while electrochemical impedance spectroscopy enabled sensitive detection of CA199 with a limit of detection of 0.05 U·mL-1 and a linear response range from 0.05 to 40 U·mL-1. Recovery tests in spiked human serum samples demonstrated excellent accuracy (97-109% recovery), validating the biosensor's reliability in complex biological matrices. The rationally designed copolymer provides both high sensitivity and specificity while maintaining resistance to biofouling in serum samples. This work establishes a scalable, cost-effective platform for glycoprotein biomarker detection, advancing the field of clinical diagnostics and cancer monitoring.

Microfluidic digital focus assays for the quantification of infectious influenza virus.

Quantifying infectious virus is essential for vaccine development, clinical diagnostics, and infectious disease research, but current assays are constrained by long turnaround times, high costs, and laborious procedures. To address these limitations, we present a digital focus assay employing an array of independent nanoliter cell cultures. The microfluidic platform allows cells in each nanowell to be inoculated with virus, followed by oil discretization to prevent cross-contamination. After incubation, infected cells are visualized through immunofluorescence staining, and a binary map of wells positive for viral antigen is generated by automated image analysis, allowing infectious viral titer to be calculated by statistical analysis. The platform requires significantly smaller sample and reagent volumes than conventional focus assays while enhancing assay automation and endpoint time flexibility. The technology is applied to the quantification of infectious influenza A using both model virus and clinical specimens, demonstrating the digital platform as an accurate, rapid, cost-effective, and convenient tool for viral load quantification with broad utility in clinical, pharmaceutical, and research applications.

Near infrared-emitting carbon dots for the detection of glial fibrillary acidic protein (GFAP): a non-enzymatic approach for the early identification of stroke and glioblastoma.

Immunoassay techniques are widely recognized for their sensitivity and selectivity in biomarker detection; however, their high cost, time-consuming protocols and limited stability often pose significant limitations. In this study, we address these challenges by developing an antibody-free fluorescent platform for the detection of glial fibrillary acidic protein (GFAP), a biomarker released from astrocytes, which plays a critical role in neurological diseases such as ischemic stroke and glioblastoma (GBM). Glutamic acid (GA), a neurotransmitter prevalent in the brain, was selected to quench a near-infrared (NIR) emitting carbon dot-based probe, exploiting the potential interaction between GA and GFAP. The probe demonstrated a turn-on response towards GFAP in the presence of various co-existing biomolecules and ions with a detection limit of 1.8 pg mL-1. A real sample assay conducted in human serum further validated the performance of the probe, achieving a recovery rate of 85% to 97%, underscoring the potential of the probe as a reliable and cost-effective tool for GFAP detection in clinical settings.

Preclinical research models for endometrial cancer: development and selection of animal models

Endometrial cancer (EC) is the most common gynecological malignancy in developed countries, with rising incidence in recent years. Experimental animal models are crucial for studying the pathogenesis, advancing diagnostic methods, and developing new treatments. We review five main EC animal models. The use of spontaneous and chemically-induced models has decreased, with transgenic mouse and xenograft models becoming the most widely used. These models better simulate tumor molecular mechanisms and treatments, with the organoid-based patient-derived xenograft model (O-PDX) showing great promise in drug screening and personalized therapy. The application of humanized models remains limited due to technical challenges and high costs. In this review, we highlight the strengths and limitations of each model to guide researchers in their selection.