Primary Application Research Articles

Techno-economic assessment of the Synthetic Natural Gas production using different electrolysis technologies and product applications

Power to Methane (PtM) systems are considered an attractive alternative for power generation, renewable sources’ potential harnessing, and atmospheric carbon dioxide (CO2) utilization. This study analyzes the potential use of Synthetic Natural Gas (SNG) for electrical power generation or its direct injection into the currently available Natural Gas Transportation infrastructure. A simulation approach using Aspen Plus v14 software was employed to assess various PtM configurations. Six different systems were analyzed for methanation processes, utilizing three types of electrolysis systems: Alkaline (AE), Proton Exchange Membrane (PEME), and Solid Oxide (SOE). Two primary methane applications were considered: integrated into a combined cycle for power generation and a standalone gas treatment stage for grid injection. As a result, the PEME-based system showed the highest generated-to-fed power ratio, larger than SOE (1.45% higher) and AE (20.66% higher). In addition, PEME technology reports the largest generation of SNG per power supply, exceeding 3.4% and 16.4% of those of SOE and AE, respectively. However, the SOE technology showed a larger efficiency than PEME technology by 8.2% and a PtM efficiency larger than PEME by 12.4%. Fixed capital investment for the PtM systems is around 8.6 and 13.9 million USD$, and their total earnings are between −8.2 and 20.9 thousand USD$ a year, depending on the electrolysis technology, methane application, and carbon credits scenario. According to these results, the PEME-based system is the most suitable option regarding technical and economic criteria.

Evaluating the financial reporting quality under changes in accounting standards of the Indian textile sector

Purpose The purpose of this study is to analyze the literature on Lean Management and Lean Six Sigma (LM/LSS) in local government organizations (LGOs). Design/methodology/approach A systematic literature review (SLR) was conducted to extract the most relevant academic publications on LM/LSS in LGOs. ProQuest, Web of Science and Engineering Village were used to obtain the publication set. Studies were then analyzed based on author characteristics, research design characteristics and content characteristics. Findings The SLR yielded 53 academic publications. The primary finding is that this research area has recently received an increase in attention within these types of organizations. While this research area attracts new scholars every year, there remains insufficient collaboration across different research groups. Research methods, outcomes and future research areas were also investigated to comprehensively evaluate the literature and specify new research opportunities. Research limitations/implications Although the SLR is a rigorous research methodology used to gather relevant publications, it is limited to the chosen information sources (i.e. platforms) to obtain the publications. Therefore, the researchers used multiple sources to maximize the likelihood of capturing publications related to this topic. Practical implications The insights presented here provide a foundational reference for researchers interested in investigating and exploring future research opportunities associated with LM/LSS in LGOs. Originality/value This study adds value to the research community through its detailed characterization and analysis of the existing research literature on LM/LSS within LGOs, an area that remains largely unexplored in the academic literature. By providing a rigorous understanding of the current status of this research area, this work responds to a notable gap. The review of the existing literature suggests that this effort represents the first comprehensive examination of the research literature on the evolution of LM/LSS, specifically focusing on LGOs as the primary application unit of interest.

Comparison of the vs30 model and site class based on MASW, microtremor and N-SPT data in the Opak River Basin

Abstract The utilization of vs30 data offers numerous applications within the geotechnical field, with one of its primary applications being the determination of site class and the microzonation of site class. vs30 data can be acquired through various methods, including Multichannel Analysis of Surface Waves (MASW), microtremor measurements, and N-SPT data. This study seeks to compare vs30 data and site class criteria based on measurements obtained from MASW, microtremor, and N-SPT data in the Opak River Basin. For the vs30 data analysis, a total of 27 data points from MASW and microtremor measurements, along with 3 data points from N-SPT measurements, were employed. These measurements were conducted across various geological formations, encompassing the young volcanic deposits of Merapi Volcano, alluvial deposits, and the Nglanggran, Sentolo, Wonosari, and Semilir Formations. It is worth noting that all N-SPT data were specifically collected within the young volcanic deposits of the Merapi Volcano Formation. The results of this analysis revealed vs30 values ranging from 159 to 192 m/s for MASW measurements, 156 to 789 m/s for microtremor measurements, and 241 to 249 m/s for N-SPT measurements. In accordance with the SNI 1726-2019 site class criteria, the site classes determined based on vs30 values from MASW and microtremor data included rock (SB), very dense soil (SC), stiff soil (SD) and soft soil (SE), while the site class based on vs30 N-SPT data fell under the stiff soil (SD) criteria. The correlation between vs30 values obtained from MASW and microtremor measurements yielded a strong correlation coefficient (r) of 0.98, and the correlation between vs30 values from MASW and N-SPT measurements demonstrated a very strong correlation coefficient (r) of 0.99.

From 3D to 5D tracking: SMX ASIC-based double-sided micro-strip detectors for comprehensive space, time, and energy measurements

We present the recent development of a lightweight detector capable of accurate spatial, timing, and amplitude resolution of charged particles. The technology is based on double-sided double-metal p+ – n – n+ micro-strip silicon sensors, ultra-light long aluminum-polyimide micro-cables for the analogue signal transfer, and a custom-developed SMX read-out ASIC capable of measurement of the time (Δt ≲ 5 ns) and amplitude. Dense detector integration enables a material budget > 0.3 % X 0. A sophisticated powering and grounding scheme keeps the noise under control.In addition to its primary application in Silicon Tracking System of the future CBM experiment in Darmstadt, our detector will be utilized in other research applications.

RimabotulinumtoxinB: An Update.

Botulinum type-A toxin is a well established aesthetic and medical treatment. While the usage of type-B toxin is less common, there is a growing interest in using type-B toxin, especially in those who are treatment resistant. To evaluate the primary FDA-approved clinical applications of rimabotulinumtoxinB, along with established and emerging off-label clinical indications. Articles were reviewed from PubMed database and Food and Drug Adminstration guidelines. Facial rhytids tend to use a higher conversion ratio between type A and type B toxin, due to type B toxin's weaker affinity to muscles and higher affinity for sweat glands. Specially, a 1:100 to 1:50 ratio was utilized for glabellar rhytids, a 1:25 to 1:50 ratio for periocular rhytids, a 1:50 to 1:66.6 ratio for cervical dystonia, a 1:20 to 1:50 ratio for hyperhidrosis, and a 1:25 to 30 ratio for sialorrhea. Type B toxin has demonstrated its safety and efficacy in treating facial rhytids, cervical dystonia, sialorrhea and hyperhidrosis, with potential for novel applications under investigation. Regardless of injection location and clinical applications, dry mouth and dysphagia remained the most common side effects. Across all indications, type B toxin appeared to have a faster onset of action, a dose-dependent clinical duration, and a dose-dependent adverse effect profile.

Graph Convolutional Network for Image Restoration: A Survey

Image restoration technology is a crucial field in image processing and is extensively utilized across various domains. Recently, with advancements in graph convolutional network (GCN) technology, methods based on GCNs have increasingly been applied to image restoration, yielding impressive results. Despite these advancements, there is a gap in comprehensive research that consolidates various image denoising techniques. In this paper, we conduct a comparative study of image restoration techniques using GCNs. We begin by categorizing GCN methods into three primary application areas: image denoising, image super-resolution, and image deblurring. We then delve into the motivations and principles underlying various deep learning approaches. Subsequently, we provide both quantitative and qualitative comparisons of state-of-the-art methods using public denoising datasets. Finally, we discuss potential challenges and future directions, aiming to pave the way for further advancements in this domain. Our key findings include the identification of superior performance of GCN-based methods in capturing long-range dependencies and improving image quality across different restoration tasks, highlighting their potential for future research and applications.

A new strategy for efficient detection of triflumuron residues in food: An electrochemical sensor derived from a Cu/Fe-BTC MOF-polymer

Triflumuron is an insect growth regulator belonging to the class of insecticides. It finds its primary application in the agricultural sector for the control of various pests, particularly certain beetles, aphids, locusts, and mites. In this paper, a Cu/Fe-BTC composite was synthesized through a straightforward solvothermal approach, subsequently employed as a precursor for the fabrication of an electrochemical sensor denoted as CuFe2O4@C. The latter exhibited a distinctive core-shell architecture achieved through annealing, and its application was focused on the sensitive detection of triflumuron. The electrochemical behaviour of CuFe2O4@C for the detection of triflumuron was evaluated by differential pulse voltammetry (DPV) under optimal conditions in wide concentrations from 1.0 × 10−4 to 1.0 × 10−12 mol·L−1, where there existed a superior linear relationship between the current and the concentration of triflumuron with R2 being 0.995. Meanwhile, CuFe2O4@C had a low limit of detection (LOD) of 922 fM for triflumuron. The CuFe2O4@C/GCE exhibited remarkable sensitivity, long-term stability, excellent reproducibility, and repeatability, as well as effective anti-interference capabilities. Additionally, CuFe2O4@C demonstrated its applicability for the quantitative determination of triflumuron in diverse real samples with commendable recovery rates. In conclusion, the electrochemical sensor not only displayed exceptional performance in terms of stability, reproducibility, and anti-interference, but also showcased its practical utility in quantifying triflumuron across various real-world samples.

Retrospective of interdisciplinary research on robot services (1954–2023): From parasitism to symbiosis

Social distancing and low-touch services have been fuelled by the COVID-19 pandemic, leading to a paradoxical dilemma for service providers to balance high-quality service and low-touch demand. The introduction of robot services has emerged as a possible solution, yet its full potential in fostering a user-friendly modern society remains underexplored. Our goal is to address this gap via a comprehensive analysis of 16,255 interdisciplinary articles published between 1954 and 2023, elucidating the intellectual, social, and conceptual frameworks underpinning robot service research. Using a parasitical evolutionary lens, which incorporates various stages from low-level parasitism to symbiosis, we investigated the dynamic relationship between robot services and related technologies. Furthermore, we pinpointed six primary application areas for robot services, and charted their historical development, current status, and evolving issues. Additionally, we analysed robot service applications in contemporary society, offering both cross-domain and domain-specific insights. Theoretically, our research combines the integrated interdisciplinary narrative with the evolutionary technological parasitism perspectives on deconstructing robot services research. This contributes to bridging the gap between theory and practice, and expanding the boundaries of applying technology parasitism theory in answering real-world questions. Empirically, this study provides valuable insights for shaping management and innovation policies in this field. Specifically, the opportunities, threats, and future research agendas highlighted in this study can aid the work of policymakers, strategists, and technology implementation teams.

What does terroir mean? A science mapping of a multidimensional concept

AbstractTerroir is a pivotal concept in defining collective quality labels for agricultural products, such as geographical appellations. With climate change likely to significantly impact these appellations' delimitations, an in‐depth understanding of terroir's various dimensions becomes imperative. Yet, the literature presents diverse and multifaceted definitions of terroir, making it a challenging concept to delineate. Utilising 913 articles from 1986 to 2023 sourced from Scopus and adhering to the SPAR‐4‐SLR bibliometric protocol, we conducted a science mapping that includes analysis of document co‐citation, co‐authorship, bibliographical coupling and keyword co‐occurrence to elucidate terroir's definitions, research fields and issues. We propose a bibliometric analysis methodology that enables detailed mapping of the concept by disciplinary fields. The proposed methodology is applicable to systematic literature reviews aimed at studying a domain while incorporating the diversity of scientific disciplines in which it is investigated. Our analysis confirms that, in terms of agri‐food sectors, the literature predominantly focuses on wine. More specifically, within the fields of business, economics and social sciences, the primary applications of the concept are with respect to geographical indications and climate change. Research conducted in agricultural and biological sciences facilitates a better characterisation of terroirs in terms of microbial characteristics. This increasingly enables a distinction to be made between the soil—i.e., the terroir place—and the quality of agri‐food products. Future analysis can make use of this knowledge, as well as that on the cultural dimensions of terroir, to better understand the economic impacts of the different dimensions of terroir.

Unveiling wearables: exploring the global landscape of biometric applications and vital signs and behavioral impact

The development of neuroscientific techniques enabling the recording of brain and peripheral nervous system activity has fueled research in cognitive science. Recent technological advancements offer new possibilities for inducing behavioral change, particularly through cost-effective Internet-based interventions. However, limitations in laboratory equipment volume have hindered the generalization of results to real-life contexts. The advent of Internet of Things (IoT) devices, such as wearables, equipped with sensors and microchips, has ushered in a new era in behavior change techniques. Wearables, including smartwatches, electronic tattoos, and more, are poised for massive adoption, with an expected annual growth rate of 55% over the next five years. These devices enable personalized instructions, leading to increased productivity and efficiency, particularly in industrial production. Additionally, the healthcare sector has seen a significant demand for wearables, with over 80% of global consumers willing to use them for health monitoring. This research explores the primary biometric applications of wearables and their impact on users’ well-being, focusing on the integration of behavior change techniques facilitated by IoT devices. Wearables have revolutionized health monitoring by providing real-time feedback, personalized interventions, and gamification. They encourage positive behavior changes by delivering immediate feedback, tailored recommendations, and gamified experiences, leading to sustained improvements in health. Furthermore, wearables seamlessly integrate with digital platforms, enhancing their impact through social support and connectivity. However, privacy and data security concerns must be addressed to maintain users’ trust. As technology continues to advance, the refinement of IoT devices’ design and functionality is crucial for promoting behavior change and improving health outcomes. This study aims to investigate the effects of behavior change techniques facilitated by wearables on individuals’ health outcomes and the role of wearables in promoting a healthier lifestyle.

Augmented Optoelectronic Quantum Dot‐Enhanced Heterogeneous IGZO‐Te Photodiode for Artificial Synaptic Image Processing Applications

AbstractThis study presents a novel photodiode technology with augmented optoelectronic capabilities through the incorporation of quantum dots (QDs). The photodiode, composed of Indium Gallium Zinc Oxide‐Tellurium (IGZO‐Te), is engineered for enhanced light sensitivity and tailored optoelectronic interactions. The primary application of this advanced photodiode lies in the domain of artificial intelligence and machine learning, where it plays a pivotal role in simulating synaptic connections for image processing tasks. Due to the exceptional optical and electrical properties of the IGZO‐Te‐QDs active material combination, the photodiode demonstrates consistent and dependable optical synaptic functions linked to learning. This is achieved through conduction modulation and time duration modulation of light stimulus. In addition, the opto‐synaptic functionalities such as short‐term and long‐term memory has also been successfully demonstrated not only on single device but also on 6 × 6 photodiodes array device. These findings underscore the significant potential of the hybrid structure of IGZO‐Te with QDs in optical artificial neuromorphic chips.

Deep transfer learning strategy in intelligent fault diagnosis of rotating machinery

Rotating machinery plays an essential part in many engineering fields. It needs prompt solutions to the prognosis and health management to ensure the system reliability. Facilitated by big data and artificial intelligence, intelligent fault diagnosis provides a new approach. As for the insufficient faulty data and complex conditions, deep transfer learning (DTL) presents a possible approach for cross-domain and cross-machine diagnosis. The published reviews thus far mainly emphasize on the analysis of fault diagnosis based on common classes of DTL or industrial application scenarios. This review concentrates on the applications of DTL in rotating machinery. Moreover, present relevant reviews were mainly till the end of 2021. The latest researches are analyzed from then until now. A special main line based on input types is chosen that distinguishes it from other reviews. From this perspective, it is therefore valuable to comprehensively investigate the fault diagnosis of rotating machinery. This survey firstly outlines the fundamental principle and conventional categories of DTL. The primary applications of DTL in fault diagnosis of rotating machinery are then summarized, and more than 100 relative studies have been analyzed. The special perspective of input types is selected and evaluated, including one-dimensional and two-dimensional, on the DTL framework as applied to the rotary machines discussed. Finally, the existing challenges are pointed out and potential future trends of DTL are prospected. This review helps readers to understand the research status and development trends of transfer intelligent fault diagnosis. It serves to the innovative exploration from multiple different scales.

Establishment of a Cleavage-Based Single-Plasmid Dual-Luciferase Surrogate Reporter for the Cleavage Efficiency Evaluation of CRISPR-Cas12a Systems and Its Primary Application.

CRISPR-Cas technology is a widely utilized gene-editing tool that involves gRNA-guided sequence recognition and Cas nuclease-mediated cleavage. The design and evaluation of gRNA are essential for enhancing CRISPR/Cas editing efficiency. Various assays such as single-strand annealing, in vitro cleavage, and T7 endonuclease I (T7EI) are commonly used to assess gRNA-mediated Cas protein cleavage activity. In this study, a firefly luciferase and Renilla luciferase co-expressed and a cleavage-based single-plasmid dual-luciferase surrogate reporter was built to evaluate the gRNA-mediated Cas12a cleavage efficiency. The cleavage activities of CRISPR-Cas12a can be quantitatively determined by the recovery degree of firefly luciferase activity. The cleavage efficiency of CRISPR-Cas12a can be quantitatively measured by the recovery of firefly luciferase activity. By using this system, the cleavage efficiency of CRISPR-Cas12a on hepatitis B virus (HBV)/D expression plasmid was evaluated, revealing a negative correlation between gRNA cleavage efficiency and HBV gene expression measured using an enzyme-linked immunosorbent assay. This simple, efficient, and quantifiable system only requires the dual-luciferase vector and CRISPR-Cas12a vector, making it a valuable tool for selecting effective gRNAs for gene editing.

Innovation waves: Analysis and modeling of patents on ultrasound applications in food processing

AbstractUltrasonication is an innovative green technology with various applications in the food industry. Notably, patent analysis from a technological perspective is essential for monitoring market trends and identifying the technological stage through life cycle modeling. Thus, this study aimed to conduct an investigation using patent documents on the application of ultrasound in the food sector. The Espacenet® database was used with the keywords “Food Processing,” “Ultrasound,” and “Ultrasonication,” along with the code A23. A total of 140 documents were evaluated, with China being the main applicant country. Fruits and vegetables and bioactive compounds were the key technological sectors. Food preservation and extraction processes emerged as the primary applications. The involvement of ultrasound technology in the food industry is entering the maturity stage, as demonstrated by the function adjusted to the BiDoseResp model. This result implies further technological and market development in the food industry in the coming years.Practical applicationsThis review addressed the evolution and the current scenario of ultrasound applications in food processing through patent documents deposited between 1979 and 2022, which are rich technological information sources. This approach identified the main technological sectors of food and applications in which ultrasound is most used, as well as the main institutions, inventors, and patent‐filing countries. The major challenges, impacts of the COVID‐19 pandemic, and market trends were also discussed. Through mathematical modeling of patent mapping, it was detected that ultrasonication is integrated into the food sector while maintaining a highly competitive impact. This development indicates a future with significant advancements in the development of ultrasound in the food industry, with increasing participation of emerging countries in technological monopolies and a trend of associating ultrasound with non‐thermal emerging technologies in patented inventions. Food waste, food printing, and food for people with swallowing difficulties are potential areas for further development.

Dual-energy CT applications on liver imaging: what radiologists and radiographers should know? A systematic review.

This review aims to provide a comprehensive summary of DECT techniques, acquisition workflows, and post-processing methods. By doing so, we aim to elucidate the advantages and disadvantages of DECT compared to conventional single-energy CT imaging. A systematic search was conducted on MEDLINE/EMBASE for DECT studies in liver imaging published between 1980 and 2024. Information regarding study design and endpoints, patient characteristics, DECT technical parameters, radiation dose, iodinated contrast agent (ICA) administration and postprocessing methods were extracted. Technical parameters, including DECT phase, field of view, pitch, collimation, rotation time, arterial phase timing (from injection), and venous timing (from injection) from the included studies were reported, along with formal narrative synthesis of main DECT applications for liver imaging. Out of the initially identified 234 articles, 153 met the inclusion criteria. Extensive variability in acquisition parameters was observed, except for tube voltage (80/140 kVp combination reported in 50% of articles) and ICA administration (1.5mL/kg at 3-4mL/s, reported in 91% of articles). Radiation dose information was provided in only 40% of articles (range: 6-80mGy), and virtual non-contrast imaging (VNC) emerged as a common strategy to reduce the radiation dose. The primary application of DECT post-processed images was in detecting focal liver lesions (47% of articles), with predominance of study focusing on hepatocellular carcinoma (HCC) (27%). Furthermore, a significant proportion of the articles (16%) focused on enhancing DECT protocols, while 15% explored metastasis detection. Our review recommends using 80/140 kVp tube voltage with 1.5mL/kg ICA at 3-4mL/s flow rate. Post-processing should include low keV-VMI for enhanced lesion detection, IMs for tumor iodine content evaluation, and VNC for dose reduction. However, heterogeneous literature hinders protocol standardization.

THE IMPACT OF HEALTH SUPPLY AND DEMAND ON HEALTH OUTCOMES IN PRIMARY HEALTH CARE SERVICES: PANEL DATA ANALYSİS

The aim of this study is to determine the impact of health supply and demand on health outcomes in primary health care services. For this purpose, the population of the study consists of the Eastern Anatolia Region. Sampling was not determined in the study, and data from 14 provinces in the region were evaluated. The dependent variable of the study is the number of deaths, while the independent variables are the number of family medicine units and the number of primary care applications. The research data were tested separately for each province considering the time period 2012-2021. According to the results of the study, the increase in the number of family medicine units leads to a decrease in the number of deaths in Erzurum, Van and Ağrı, as in the whole panel. On the other hand, the increase in the number of primary care visits decreases the number of deaths in Muş and Hakkari, but increases it in Malatya and Bitlis.

Incidence and Outcomes of COVID-19 Vaccine Hypersensitivity Reactions and Success of COVID-19 Vaccine Provocation Tests Post Previous COVID-19 Vaccine Hypersensitivity.

Background: The COVID-19 pandemic has led to high mortality rates. There have been reports of hypersensitivity reactions with mild to severe symptoms. The COVID-19 vaccine provocation test is a vaccination protocol for individuals with a history of hypersensitivity. This study aims to determine the benefits of COVID-19 vaccine provocation tests in patients with a history of hypersensitivity reactions to COVID-19 vaccines and its influencing factors. Objective: To determine the incidence, severity, outcome of hypersensitivity reactions, and success of the COVID-19 vaccine provocation test. Methods: A retrospective cohort study was conducted, using subjects taken from medical record data at the RSCM who had received COVID-19 vaccination with a history of hypersensitivity. Data was taken from the COVID-19 vaccination records at the RSCM, BPJS Health Primary Care application. Results: From a total of 29,036 doses of the COVID-19 vaccine, 44 patients experienced hypersensitivity reactions. As many as 38.64% did not continue vaccination, 2.27% experienced mild hypersensitivity, and 59.44% were successfully vaccinated. Conclusions: People with a history of hypersensitivity reactions to COVID-19 vaccines can still receive subsequent COVID-19 vaccinations at healthcare facilities equipped with anaphylaxis kits and immunology allergists.

Anatomia radiológica do tórax na graduação médica: o que o médico generalista precisa saber

Rationale: in medical education, the traditionally employed methodology in Human Anatomy classes is the dissection of cadavers, a method fraught with logistical, ethical, and financial limitations. In this context, the use of imaging exams not only contributes to the teaching of human anatomy, which is fundamental knowledge for professionals, but also facilitates an understanding of radiology, which is subsequently addressed in medical school. Furthermore, imaging exams represent one of the primary applications of anatomy in medical practice. Objectives: The present study aims to develop a proposal for an Essential Curriculum in Radiological Anatomy of the chest, outlining the fundamental structures to be identified in imaging exams by general practitioner and supporting the teaching of anatomy in medical education. Methods: A questionnaire was sent to medical professors and/or preceptors at the PUCPR medical school, where they were asked to assess the relevance of thoracic anatomical structures in the context of radiology on a 4-point Likert scale. The questionnaire was structured into four sections based on the most used imaging exams. The responses were entered into an Excel® spreadsheet and statistically analyzed for consensus using the Loe Index. Structures with high and moderate consensus among experts were included in the Core Curriculum. Results: The study included 26 medical professors and preceptors from PUCPR's medical school, representing 15 different medical specialties. The proposed Core Curriculum comprises 43 out of the initially listed 94 structures. Conclusion: In line with the stated objective, the result of this study is the development of a Core Curriculum in Radiological Anatomy of the Chest, consisting of 43 relevant structures to assist professionals in the evaluation of X-ray and computed tomography exams.

Investing of Chatbots to Enhance the Library Services

Artificial Intelligence (AI) has become an indispensable tool in our daily lives and is a concept that refers to complex tasks that usually require significant human effort. Chatbots stand out as one of the primary applications of artificial intelligence, aiming to foster an interactive dialogue environment between humans and machines to address inquiries through textual or voice interfaces that simulate human cognition. Libraries can serve as an ideal environment for implementing this technology, where it can deliver advanced information services and streamline repetitive routine tasks typically performed by library staff. The paper discusses the applications of chatbots in automating library services, including reference services, user recommendations, information retrieval, data analysis, and other related processes, and their mechanism of action in processing natural language queries and responding to them accurately. Through a web survey, the study identified eighteen chatbot models that could be implemented in libraries. This survey provided details about these bots, including their type (free or commercial), ownership, release date, operating platforms, and key features. This allows libraries to choose from them. Integrating chatbots into libraries will open new horizons for enhancing their services and improving the user experience. Despite the benefits offered by these chatbots, they face several challenges and concerns regarding their usage, notably data privacy and security, and bias in retrieval. It is expected that in the future, these chatbots will become a fundamental component of providing library services.

Role of Medicinal Plants in the Treatment of COVID-19: A Review

As of right now, there is no evidence to support the idea that COVID-19 specific treatments exist; what is known is that the immune system is a major factor in the development and course of the illness. Chemicals of high efficacy and low toxicity have been found in plants and some of these chemicals are used as building blocks to create highly potent synthetic drugs. While the primary application of herbal treatments is in prevention, certain nations have published guidelines recommending the use of traditional remedies for varying stages of COVID-19 infection. Although Europe has a long and rich history of employing medicinal plants for therapeutic purposes, there aren't as many scientific trials for this kind of approach as there are in Asia. The ability to prevent and treat COVID-19 would be significantly impacted in this way by a bridge connecting tradition and science.