bluuebunny/crossref_metadata_2025 huggingface dataset:
BERE: Ensuring Immutability and Transparency with Blockchain in Real Estate Appraisal Industry
Authors: Kalkan Muruvvet , Karakus Murat
Published: June 2024

Real estate appraisal plays a pivotal role in various financial transactions and regulatory processes, necessitating the assurance of unalterable and transparent Real Estate Appraisal rePorts (REA_Ps). Authorized appraisal experts employ diverse methodologies to ascertain the market value of real estate properties, contributing to critical decisions in property transactions, loans, taxation, insurance, financial reporting, and lease calculations. The standardized format and jurisdiction-compliant methodologies used in official REA_Ps emphasize the need for their preservation in an unaltered state. Despite the importance of official REA_Ps, the potential for unauthorized alterations poses a significant challenge when stored in centralized databases. With its inherent tamper-proof nature, Blockchain (BC) technology emerges as an ideal solution to safeguard the integrity of the REA_Ps. This study proposes a Blockchain-Enhanced Real Estate appraisal management framework, BERE, to the immutability of ensure REA_Ps and enhance appraisal process transparency. The proposed BERE framework fosters trust among stakeholders in the real estate appraisal sector. By securely storing REA_Ps authored by on-field appraisal experts on the BC, the method prevents unauthorized modifications and ensures the confidentiality of private data. Simulations employ a variety of measures, such as BC size, transaction verification time, CPU usage, and message overhead on transaction generation, to assess system performance. The results indicate that the BERE framework successfully maintains the accuracy and reliability of REA_Ps.
To the best of our knowledge, this is the first comprehensive study showcasing a practical application of BC technology to demonstrate its ability to transform the appraisal process and inspire trust in the accuracy of REA_Ps.
Defining a Super App and Analyzing It from an Ecosystemic Perspective
Authors: Lucas Durval , Lopes Evandro Luiz
Published: June 2024

The creation of super apps is a recent development, establishing itself as the new pinnacle of increased technology and digital market participation in retail operations. It is primarily inspired by Chinese apps, open platforms where partners can create mini-applications and make them available to users. Although the rise of super apps is a widely disseminated phenomenon, there has been a lack of harmonization regarding the concept. Therefore, this paper aims to present a definition of the super app concept, analyzing how it consolidates the perspective oriented towards digital ecosystems. To this end, a systematic literature review was conducted, which included, at the end of the screening process, 26 scientific articles published in journals from the years 2018 to 2023. Following the analysis, a harmonized concept of super apps was achieved. Furthermore, it was observed that the concept is divided into two specific viewpoints, characterized by their geographical origin and the way these apps materialize digital ecosystems. These viewpoints support the perspective of DeSanctis and Poole (1994) and Schmitz et al. (2016) regarding the variability in technology appropriation processes, disciplined by the social context in which these artifacts are embedded.
Energy Equipartition a Tool to Study Tsunami/Bathymetry Interaction
Authors: Brazhnikov Dmitry , Kowalik Zygmunt
Published: June 2024

We propose a new approach to investigate tsunami propagation and interaction with bathymetry by considering the partitioning of the kinetic and potential energy in the total energy. Investigations of the total energy in time show that the equipartition of potential and kinetic energies is frequently disrupted due to wave interactions with varying bathymetry. First, the approach is tested in the channel with abrupt changes in the bathymetry. Along with usual, incident, reflected, and transmitted waves at the depth jump, the lack of equipartition of energy has been observed. The strength of differences between energies depends on the depth difference between the shallow and deep parts of the channel. Therefore, the differences between energies are correlated with reflection and transmission coefficients. Application to the ocean tsunami is made for the Japan/Tohoku tsunami of 2011. The observed kinetic and potential energies show equipartition along the considerable propagation distance until the wave impinges on prominent bathymetric features like Koko Guyot Seamount and Hess Rise. The energy difference again strongly depends on the relative depth between the ocean bottom plain and the seamount top. This research applied to Koko Guyot uncovered somewhat unusual signal amplification over the seamount. The modification of tsunami amplification and the wavefronts radiating energy to Hess Rise were related to the amplification of the negative sea level. This strong negative level is directed towards Crescent City as a secondary wave.
Evaluation of Henle's Fiber Layer with directional OCT in mild to moderate glaucoma patients
Authors: İlgüy Serdar
Published: June 2024

Purpose: To investigate the Henles’s fiber layer (HFL) to detect the damage that may develop in photoreceptors and axons in patients with mild to moderate glaucoma.
Study Design: Single center retrospective study
Methods: For this study, 25 eyes of 25 subjects diagnosed with glaucoma and 50 eyes of 50 age and sex matched healthy people were enrolled. Macular retinal thickness, peripapillary retinal nerve fiber layer (RNFL) thickness and macular ganglion cell-inner plexiform layer (GC-IPL) thickness measured on OCT. The OCT images with nasal, central and temporal tilt were processed with ImageJ software and HFL area was measured. Measurements were compared between the two groups.
Results: The two groups were similar in age and gender. When the two groups were compared, HFL measurements were thinner in glaucoma patients (p<0.001). The inner inferior, outer temporal and outer superior quadrants of the retinal thickness were significantly thinner in the glaucoma group (p=0.012, p=0.010, p=0.004, respectively). All quadrants of GC-IPL thicknesses were significantly thinner in the glaucoma group. Additionally, statistically significant changes were detected differences in the thickness of the superior, inferior quadrants and average RNFL (p=0.029, p<0.001, p=0.001, respectively).
Conclusion: From the early stages of glaucoma, automated HFL measurements can be used to monitor progression.
Anisotropy parameters from two-body dissociations
Authors: Olsson Emelie , Wallner Måns , Squibb Richard J. , Ideböhn Veronica , Parriani Marco , Parkes Michael A. , Price Stephen D. , Eland John H.D. , Feifel Raimund
Published: June 2024

When a molecule loses two electrons, Coulomb repulsion makes the resulting doubly charged system likely to fragment into two singly charged ions. These monocations can be detected in a correlated fashion using multiplex time-of-flight spectroscopy. The island shapes in the ion-ion coincidence maps derived from such two-body dissociations contain detailed information on the physical processes underlying the fragmentation. Here, a simple method is presented where a fit function is used to determine the anisotropy parameter β of the molecular distribution from the peak shape of the time-of-flight difference of the two ions. The validity of the method is demonstrated by performing fits to simulated peak shapes, recovering the β value of the input angular distribution, and by comparison of experimental peak shapes to β values known from the literature.
A Genomic Study to Explore the Coping Mechanisms of Bacteria to Hydrocarbon Stress
Authors: Dasgupta Abhisek
Published: June 2024

This study investigated the survival mechanisms of bacteria in a hydrocarbon-enriched environment, focusing on factors such as osmotic stress, biofilm formation, and complex carbohydrate utilization. The whole genome of a bacterial isolate (AR19) capable of degrading benzo[a]pyrene (B[a]P) was sequenced and analyzed. The draft genome size was 3.63 Mb, and the closest reference genome was identified as Bacillus altitudinis. The genome contained 3,777 coding genes. Noteworthy findings from the genome analysis included: (i) the involvement of biofilm and biosurfactant in B[a]P adsorption by AR19, (ii) the utilization of extradiol ring cleavage for B[a]P degradation, and (iii) the importance of osmotic stress protection in maintaining cell structure under hydrocarbon stress. The results of this study have potential implications for the development of bioremediation strategies using ex-situ and in-situ techniques.
Identification of BIRC5 and HMMR as Prognostic Biomarkers for Immune Infiltration in Prostate Cancer
Authors: Tang Huarui , Zhou Fanyang , Hu Wentao , Zhang Chen , Tao Jianping , Xing Fawang , Zhang Zhenxing , Gao Yukui
Published: June 2024

Background The delineation of molecular mechanisms and identification of prognostic markers between different subtypes and stages of prostate cancer is vital for the enhancement of therapeutic approaches against this disease. We aimed to identify novel immune-related biomarkers that could be instrumental in assessing and prognosticating prostate cancer across its different stages.Methods Transcriptomic and clinical data were obtained from the TCGA and GEO databases to identify differentially expressed genes (DEGs) associated with the progression of prostate cancer. The correlation between immune cell infiltration in the tumor microenvironment and the expression levels of BIRC5 and HMMR was investigated using xCELL and quanTISeq algorithms.Results Through our analysis, we identified ten key hub genes, and survival analysis revealed that elevated expressions of BIRC5 and HMMR are correlated with adverse outcomes and may be associated with tumor progression. Importantly, the expressions of BIRC5 and HMMR were significantly associated with the tumor-infiltrating lymphocytes (TILs) across different subgroups of prostate cancer. The results from immunohistochemistry (IHC) evaluations were consistent with our bioinformatics findings.Conclusion Our study identifies BIRC5 and HMMR as potential biomarkers for predicting the prognosis of prostate cancer.
Mechanically Enabled Formal Reductive Cross-Coupling Reaction of Two Inert Bonds
Authors: Lian Zhong , Liu Tianfen , Zhang Xuemei
Published: June 2024

Reductive cross-coupling reactions involving two electrophilic reagents have become increasingly important in modern synthetic chemistry. Previous studies have investigated electrophilic reagents featuring zero or one inert bond; however, reactions involving electrophilic reagents with two inert bonds remain unexplored. This study presents the inaugural nickel-catalyzed reductive cross-coupling reaction induced by mechanical force, involving aryl ethers and aryl fluorides, both of which contain inert bonds. This reaction results in the successful assembly of a series of versatile biaryl compounds and demonstrates excellent tolerance for various functional groups. This novel coupling reaction offers innovative approaches for polymer degradation and the development of luminescent materials.
Depression and Suicidal Ideation Among College Students with and without Learning Disabilities in Tamil Nadu Regions: Chennai and Coimbatore
Authors: R Anjit Raja , Nagarajan B.
Published: June 2024

This research investigates depression and suicidal ideation among college students with and without learning difficulties in Chennai and Coimbatore, two cities in Tamil Nadu, India. A total of 28,745 students aged 17 to 23 participated, comprising 11,203 male and 17,542 female students. Utilizing three validated instruments, the study employed a descriptive research approach with a purposive sample technique. Data analysis involved calculating mean, standard deviation, and Pearson product-moment correlation. Results indicated that students with learning disabilities were more prone to experiencing depression and suicidal thoughts compared to their peers without cognitive difficulties. Recommendations include the need for mental health professionals to address these issues among tertiary education students. The study also highlights the alarming rate of student suicides in India, particularly in Tamil Nadu, underscoring the inadequacy of support systems and mental health services. As such, this research aims to examine suicide behaviors and influencing variables among teenagers in Chennai and Coimbatore, employing web mining techniques and statistical analysis to identify key factors and develop machine learning strategies for the protection of India's younger generations.
Great Investment Returns in the COVID-19 Pandemic or Just Another Bubble?
Authors: Simpson Shawn
Published: June 2024

This study examines the impact of the COVID-19 pandemic on the S&P 500 Index through accounting return on equity. Previous literature examines the impact of the pandemic on the United States economy, government restrictions, and global market reaction. Accounting return on equity is employed due to the unmediated impact it has on shareholder wealth. The data obtained from Compustat comprise all available companies listed in the S&P 500 Index. This analysis stems from the first reported case of COVID-19 in the United States, January 21, 2020 and concludes on December 31, 2021. Significant (p-value < 0.0001) evidence conveys that the index had a strong negative initial response. However, the index recovered expeditiously. A multivariable regression model is employed to determine if the recovery led to inflated stock prices. For the purpose of this study, inflated stock prices are interpreted as return on equity is more pronounced than the intrinsic value of the companies that they represent. The results provide significant (p-value < 0.0001) evidence that return on equity is inflated on December 31, 2021. Controlled variables in this analysis include book to market, enterprise value multiple, price to operating earnings, price to earnings, price to sales, price to cash flow, total debt to total assets, total debt to equity, asset turnover, and price to book.
Bayesian adaptive designs in a breast cancer trial with a delayed binary outcome
Authors: Hong Wei , McLachlan Sue-Anne , Moore Melissa , Mahar Robert K
Published: June 2024

Background
Clinical trials using Bayesian adaptive designs can be more efficient than those using traditional fixed designs, but there is a vast range of possible design approaches described in literature. We performed virtual re-executions of a breast cancer clinical trial with a delayed binary outcome to demonstrate what would have happened if the trial had used various Bayesian adaptive designs instead, and to explore which specific designs yielded the most benefits.
Methods
We retrospectively “re-executed” a randomised controlled trial that compared two chemotherapy regimens for women with metastatic breast cancer (ANZ 8614) using Bayesian adaptive designs. We used computer simulations to estimate the power and sample sizes of a large number of different candidate designs and shortlisted designs with the either highest power or the lowest average sample size. Using the real-world data, we explored what would have happened had ANZ 8614 been conducted using these shortlisted designs.
Results
Adaptive designs that prioritised small sample size reduced the average sample size by up to 50% when there was no clinical effect and by up to 21% at the target clinical effect. Adaptive designs that prioritised high power yielded up to an absolute increase of 6.5% in power without a corresponding increase in type I error. The performance of the adaptive designs when applied to the real-world ANZ 8614 data was consistent with the simulations.
Conclusion
Bayesian adaptive designs improved power or lowered the average sample size substantially when applied to this data set. When designing new oncology trials, researchers should consider whether a Bayesian adaptive design may be beneficial.
Explainable Artificial Intelligence Methods for Analysis of Factors Influencing Covid-19 Cases in Türki̇ye
Authors: İçöz Cenk
Published: June 2024

COVID-19 disease emerged in Wuhan, China, in 2019 and evolved into a pandemic that negatively affected all countries worldwide. Researchers have employed methods such as machine learning and spatial machine learning methods, including spatial and multiple linear regression, geographically weighted regression and geographical random forests, to determine the importance of factors such as sociocultural, demographic, environmental, racial, and economic development related to COVID-19 cases or deaths caused by COVID-19. In this study, the explainability of the general factors analyzed by the random forest model of COVID-19 cases based on provinces in Türkiye was examined. In addition, traditional machine learning methods, compared with spatial machine learning models, as the Explainable Artificial Intelligence (XAI) methods directed toward employing spatial associations. The most important factors in the model might differ locally among provinces according to cluster. The spatial machine learning models performed better than the random forest model.
Impact of Direct İncorporation of Organic Waste on Soil Properties and Strawberry (Fragaria X Ananassa Duch.) Growth
Authors: GAMAL Mohammed , ElFEEL Rania A , CHEN Ri-zhao , KIZILKAYA Rıdvan , HUSSEN Adel
Published: June 2024

Aims This study delves into the impact of incorporating diverse organic waste materials on soil biological and chemical attributes within the rhizosphere of Albion strawberry plants (Fragaria x ananassa Duch.).Methods Eight organic waste types, including Cow Manure (CM), Poultry Manure (PM), Sheep Manure (SM), Vermicompost (VC), Rice Husk (RH), Wheat Straw (WS), Tea Waste (TW), and Hazelnut Husk (HH), were directly applied before strawberry transplantation. Effects on plant growth, soil chemical, and biological characteristics were assessed. In a controlled greenhouse, animal and plant waste impacts on rhizosphere and strawberry growth were examined. After applying organic waste (5% of pot weight), strawberries were transplanted. Soil moisture was monitored and maintained near field capacity. Employing a 61-day completely randomized design, soil samples were collected, analyzing microbial biomass C, basal soil respiration, dehydrogenase, and catalase.Results Findings revealed TW pronounced influence on basal soil respiration compared to controls, while WS significantly impacted microbial biomass carbon (MBC). SM notably affected DHA, while PM most influenced CA. All treatments augmented OM. SM, CM, and VC increased total N; conversely, TW, RH, WS, HH, and PM decreased it.Conclusions These findings highlight the ability of diverse organic waste to improve soil health and plant development within the rhizosphere of Albion strawberry plants. In addition to adds to our understanding of sustainable farming practices and provides useful information for farmers and policymakers who want to maximize organic waste usage in agricultural systems. More research and field experiments are needed to investigate the long-term impacts of these organic waste additions in real-world agricultural contexts.
Effect of Hexane and Methanol Extracts of Piper guineense (Schum and Thonn) Seeds against the Maize Weevil (Sitophilus zeamais) in Stored Maize Grains
Authors: Odii Emmanuel , Okonkwo Nnaemeka Joe , Uko Ibeabuchi
Published: June 2024

Methanolic and hexane extract of black pepper Piper guineense Schum & Thonn was evaluated for its insecticidal properties against the maize weevil Sitophilus zeamais Motschulsky in stored maize grains. The extracts were applied at various concentrations (4000, 2000, 1000, 500, 250 µl/ml) with ordinary acetone as control. The experimental setup involved placing ten unsexed adults of each insect species into petri dishes treated with each of the extracts as applicable for the residual treatment application. Also, maize grains weighing twenty grams were treated with the different concentrations of the extracts and the control before being artificially infested with Sitophilus zeamais and left for a period of thirty-three days. All of the treatments significantly reduced emergence holes and grain damage compared with the control.
Masked by Sustainability Metrics: Exposing the Sustainable Development Target Indicator 11.3.1’s Blindness to Urban Disparities in Ulaanbaatar City’s Expansion
Authors: Guanyu YAN , Wataru TAKEUCHI
Published: June 2024

Urban expansion in developing countries is a complex phenomenon, often accompanied by disparities of informal settlements. The United Nations’ Sustainable Development Goal (SDG) 11.3.1 index, which measures the ratio of land consumption rate to population growth rate, has been widely adopted for monitoring urban growth. This study posits that the index may fail to adequately capture the internal dynamics of rapidly urbanizing cities in the developing world. Using Ulaanbaatar, Mongolia as a case study, we critically analyze the SDG 11.3.1 indicator and propose a comprehensive approach that incorporates both city-wide and district-level analyses, with a focus on informal settlement. We find the indicator of the city total is in reverse trend to that of informal settlement area, the "Ger District." Our findings highlight the limitations of the existing indicator design and underscore the need for a more nuanced understanding of urban expansion in developing countries, informing sustainable urban policy-making.
Personalized Food Elimination Diet: A Clinical Trial based on Food sensitivity assessment
Authors: Krishnamurthy Hari Krishnan , Pereira Michelle , Jayaraman Vasanth , Krishna Karthik , Wang Tianhao , Bei Kang , Barker Suzanne , Turnpaugh Chris , West Cynthia , Murray Rebecca , Lee Edwin , Mazaheri Terri , Rustad Janis , Ellis Erin , Levinson Andrew Marc , Kirschling Meaghan , Rajasekaran John J.
Published: June 2024

Food sensitivity, a common but overlooked condition, has been associated with a variety of gastrointestinal symptoms. Typically, patients suffering from food sensitivity are placed on elimination diets, although the success of this approach has not been sufficiently validated. We aimed to assess whether effective serological assessment for food sensitivity and the implementation of a subsequent elimination diet improved patients’ symptoms and overall well-being. In this study, 52 participants were tested for serum IgG and IgA levels against 262 food antigens. Based on the results, participants followed personalized elimination diets excluding foods they were reactive to, for a period of 4 weeks. Symptoms were assessed weekly using the ‘Food Sensitivity-Symptom Severity Scale’ (FS-SSS), which was seen to decrease in 88.46% of participants from baseline to week 4 (p < 0.05). The physician’s evaluation of participants' responses was analyzed using the ‘Food Sensitivity-Global Improvement Scale’ (FS-GIS), where 84.61% of participants saw notable improvements. Antibody titers post-intervention showed improved IgG levels in 96.15% of the participants while IgA levels showed improvement in 84.61% of the participants. Serological assessment followed by a personalized elimination diet effectively addressed food sensitivity, evidenced by reduced symptoms, improved antibody titers, and favorable physician assessments of patient response.
Enhancing Sustainable Urban Planning Through Sleuth Modeling: a Case Study of Urban Growth in the Asan Watershed, Uttarakhand, India
Authors: Sharma Ankita , Krishan Radha , Nikam Bhaskar , Bagri Dhirendra Singh
Published: June 2024

Urban growth monitoring and assessment are crucial for sustainable long-term planning and the efficient utilization of natural resources. Unplanned urbanization poses risks such as pollution and environmental disruption, emphasizing the need for proactive management. Changes in Land Use and Land Cover (LULC) with time indicate ongoing urbanization trends. This study focuses on predicting and simulating urban growth in the Asan watershed, Uttarakhand, India until 2040 using the SLEUTH model and assessing the impact on the surrounding areas. The research utilizes primary datasets from 1980 to 2016, including the Digital Elevation Model (DEM) and LULC, to forecast future urban expansion. The SLEUTH (Slope, Land use, Exclusion, Urban, Transportation, and Hill-shade) model, based on Cellular Automata (CA) principles, is employed to simulate urban growth by analysing and projecting LULC changes from 2016 to 2040. Recent methodologies prioritize the detection of LULC changes through multispectral satellite images, emphasizing factors like radiometric efficiency, spatial uniformity, and climatic conditions. The predicted urban growth output revealed that the projected increase of urban area by 2040 will be 67.73 km² from 36.5 km² in 2016 with an increment of 31.23 km². Additionally, by 2040, urban settlement is expected to occupy around 9.5% of the total watershed area, an increase of 4.3% from the urban area observed in 2016. The study aims to guide infrastructure planning and promote sustainable development practices by comprehending urban dynamics, growth patterns, and resource management.
Investigating the effect of salinity and UV stress on the biochemical properties of Scenedesmus obliquus algae
Authors: Fatemeh
Published: June 2024

Scenedesmus obliquus is a unique eukaryotic microorganism that has a high range of tolerance against environmental fluctuations including salinity and UV radiation. The purpose of this study was to investigate the coping method of Scenedesmus obliquus algae cells against salinity stress and ultraviolet rays. The experiments were performed under different salinity treatments of 0 mM, 150 mM , 250 mM , 350 mM NaCl, 450 mM NaCl, 150mM NaCl+UV, 250mM NaCl+UV, 350mM NaCl+UV, 450mM NaCl+UV and UV. The effect of salinity and ultraviolet radiation on survival ability, growth rate, total protein content, photosynthetic pigment content, total sugar content, soluble sugars, insoluble sugars, hydrogen peroxide content, malondialdehyde content, activity of antioxidant enzymes including catalase, peroxidase, ascorbate peroxidase and polyphenol oxidase were investigated. In high concentrations of sodium chloride along with UV stress, cell growth rate, total protein content, photosynthetic pigments, content of insoluble sugar, peroxidase enzyme activity and polyphenol oxidase enzyme activity decreased. The content of soluble sugars, catalase enzyme activity and ascorbate peroxidase enzyme activity increased along with the content of hydrogen peroxide and malondialdehyde. According to the findings of this research, it can be said that ultraviolet rays combined with high salinity reduce the growth of Scenedesmus obliquus algae. The increase in soluble sugar content is caused by the activity of catalase and ascorbate peroxidase enzymes to deal with oxidative damage to cells. Also, the reduction of photosynthetic pigmentand and other indicators show the low resistance and lack of adaptation of this type of algae to the intensity of ultraviolet rays and high salinity.
Right heart strain on CT pulmonary Angiography in Pulmonary Embolism patients and its prognosis
Authors: kanwal shadab
Published: June 2024

Objective :
The purpose of this study was to identify the different factors on CTPA that determine right heart strain and the prognostic significance of right heart strain in pulmonary embolism patients.
Method:
In this prospective cohort study, we selected 100 patients of pulmonary embolism. Factors determining the presence of right heart strain were looked for on CT, patients were followed for 30 days and their record was reviewed for mortality. Univariable logistic regression was employed to compare this result in patients with right heart strain versus those without right heart strain.
Results:
Out of 100 patients, 31% showed right heart strain on CT pulmonary angiogram. Patients with right heart strain had higher 30-day death rates(13%) compared to those without right heart strain(4%)
Conclusion :
Our study concludes that Right heart strain is a significant predictor of 30 day mortality in acute pulmonary embolism highlighting the importance of early detection and aggressive management in right heart strain patients.
Stakeholders’ Perceptions of the Implementation of the Door-to-Door Vaccination Campaign for the Novel Oral Polio Vaccine (nOPV2) in Uganda, 2022 – 2023: A Qualitative Study
Authors: Katana Elizabeth B. , Simbwa Brenda N. , Odongpiny Eva Agnes Laker , Nsubuga Edirisa J. , Namayanja Josephine , Amodan Bob O. , Ampeire Immaculate , Kisakye Annette , Ario Alex R.
Published: June 2024

Background
Mass vaccination campaigns are crucial for public health interventions, especially in the eradication of diseases such as polio. Understanding stakeholders' perceptions and experiences during the implementation of these campaigns is essential for improving strategies and addressing challenges. This study aimed to document experiences, identify challenges, and explore stakeholders' perceptions of the implementation of a door-to-door mass vaccination campaign for the novel oral polio vaccine (nOPV2) in Uganda.
Methods
A qualitative research design was employed using face-to-face in-depth interviews with 46 randomly selected implementers from eight randomly selected districts in Uganda. The stakeholders included national/central supervisors, district, subcounty, and parish-level supervisors directly involved in the campaign implementation. Thematic analysis was employed to analyze the collected data, aligning with the major campaign activities.
Findings
Stakeholders expressed good views with some of the campaign aspects, including effective communication, advocacy and social mobilization, successful vaccine delivery and distribution, efficient district readiness assessments, appropriate cold chain management, coordination, and partner/intersectoral collaborations.
However, they highlighted challenges that included poor planning, inadequate training of vaccination teams, community resistance, difficulties in recruitment and teaming of vaccinators, payment delays, and logistical issues. They perceived that the first round of the campaign was poorly planned and implemented, while the second round showed improvement based on lessons learned.
Conclusion
The study highlights successes in implementation from the perspectives of the campaign supervisors that can be a benchmark for the implementation of the door-to-door mass campaigns for nOPV2 in Uganda.
It also highlights the need for improvements in future campaigns, focusing on motivating implementers and addressing logistical issues. Recommendations include performance reviews, enhanced planning, routine updates, verification of target populations, microplanning training, and mapping of community resistance. We also recommend that campaign planning and implementation should take the bottom-up approach as opposed to the current top-down approach that begins at the national level of the health system and regular simulations of mass vaccination response plans. These findings provide valuable insights for the implementation of future mass campaigns and contribute to the ongoing efforts to eradicate polio.
Evaluating the Quality of Large Language Model-Generated Cybersecurity Advice in GRC Settings
Authors: Li Zhiyuan , Wang Xiaoxi , Zhang Qingxiang
Published: June 2024

The growing complexity and frequency of cybersecurity threats require innovative approaches to enhance Governance, Risk, and Compliance (GRC) frameworks. Evaluating the quality of cybersecurity advice generated by ChatGPT and Google Gemini introduces a novel method to harness artificial intelligence for more effective threat mitigation and regulatory compliance. The study reveals that ChatGPT generally outperforms Google Gemini across metrics such as relevance, accuracy, completeness, and contextual appropriateness. Detailed comparative analysis, statistical evaluation, and case studies demonstrate the superior performance of ChatGPT, while also highlighting areas for improvement in both models. The findings emphasize the potential benefits of integrating LLMs into GRC frameworks, provided that their use is complemented with human expertise to address nuanced challenges. This research offers valuable insights into the practical application of AI in cybersecurity, suggesting strategic directions for future advancements.
Distributive Convolution for Faster Feature Mapping of Two-Dimensional and Volumetric Images
Authors: Xu Qinwu , Jiang Yifan
Published: June 2024

This study introduces a distributive convolution framework for feature mapping based on the distributive property of matrix multiplication, aiming to improve computing speed of convolutions for the two-dimensional (2D) plane and three-dimensional (3D) volumetric images. This method distributes the 2D and 3D kernels (filters) to the 1D (one-dimensional) and 2D ones, and apply convolutions concurrently at each spatial direction, and then fuses (adds) results together. It is different than the spatially separable convolution based on the associative property which applies convolution with separated filters in sequence. The Gaussian and Laplacian filters using the distributive convolution are evaluated on some public images for de-noise and edge detection. Results show that this method achieves similar effects as compared to the traditional convolution, and even improves the edge detection performance for some cases. The fusion of direct linear addition achieves similar performance as that of root mean square. In comparison, the spatially separable convolution obtains similar effect for the Gaussian blur but inferior performance for edge detection.
A variable template matching algorithm for anomaly detection versus kernel density and gradient convolution algorithms and ResNet-50
Authors: Xu Qinwu
Published: June 2024

This study first proposes a variable template matching algorithm for anomaly detection of images. Variational forms of template for defect with multiple scales, rotations and perspective transformations are included to improve its variational robustness. The normalized cross correlation between the template and the sliding window on the image is computed as the matching result. Secondly, it proposes a kernel density algorithm, in which a lower kernel density index (intensity percentile/range) of the sliding window indicates a potential anomaly. Lastly, it proposes a gradient convolution algorithm. These three traditional computer vision algorithms are implemented for anomaly detection of a group of biological images, and results are compared with that of the convolutional neural network ResNet-50. Results show that the variable template matching algorithm achieves superior performance (true positive 82% and false positive 4.9%) than both the kernel density and gradient convolution algorithms. Its detection rate is lower than the prediction of ResNet-50 (true positive 86%), but it is much faster and does not need any train images as an unsupervised learning. Therefore, it can be a potential candidate for object detection of small dataset or for a quick solution.
A Study of the Impact of Feature Selection on the Accuracy of
Short-term Crude Oil Price Prediction
Authors: Abu-Ajamieh Fayez
Published: June 2024

In this study, we analyze the impact of input feature selection on the accuracy of short-term 1 price predictions of crude oil futures. We analyze the impact of using 39 different features compared 2 to using the Close price alone. The features we consider are the High, the Low, the Open and the 3 Close (OHLC) prices and the Volume, in addition to a list of technical indicators derived from them. 4 We use a model built from Bi-directional Gated Recurrent Units (BGRUs) for the analysis. In addition, 5 we quantitatively analyze the impact of varying the prediction window on the accuracy of prediction. 6 We find that adding more input features does not improve the accuracy of prediction compared 7 to using the Close price alone. On the contrary, we find evidence that using more input features 8 beyond the close price actually deteriorates the accuracy of prediction. We also find that the accuracy 9 of prediction is quickly lost once the prediction window exceeds about an hour into the future. 10 Therefore, it is recommended to confine the input features to the Close price alone, and limit the 11 prediction window to less than an hour for the purposes of day trade.
Paulišite, Ca2Zn(CO3)3·2H2O, a new mineral with a novel crystal structure
Authors: Sejkora Jiří , Biagioni Cristian , Dolníček Zdeněk , Škoda Radek , Ederova Jana
Published: June 2024

Paulišite, Ca2Zn(CO3)3·2H2O, is a new mineral species discovered in the underground workings at the abandoned mine adit of the 1st level of the Staročeské Lode, near the historical shaft Šafary, Kaňk near Kutná Hora, central Bohemia, Czech Republic. Paulišite is associated with hydrozincite and aragonite (holotype sample) or with calcite, aragonite, hydrozincite and monohydrocalcite (other samples). The new mineral occurs as crusts, up to 1 cm thick, formed by parallel or radial aggregates of acicular crystals, elongated on [100], up to 5 mm in length. Paulišite is colorless to white, with a white streak. It is transparent and has a vitreous luster. Mohs hardness is ca. 4; the calculated density is 2.756 g/cm3. Paulišite is optically biaxial positive, with α = 1.554(1), β = 1.569(2), and γ = 1.605(1) (589 nm), and 2V(meas.) = 68(2)°. The empirical formula, based on electron-microprobe analyses (n = 11), is Ca2.00(Zn0.97Mg0.02Cu0.01Al0.01)Σ1.01(CO3)3·2H2O on the basis of three cations (excluding C) per formula unit. The ideal formula is Ca2Zn(CO3)3·2H2O, which requires (in wt%) CaO 31.02, ZnO 22.50, CO2 36.51, H2O 9.97, total 100.00. The strongest reflections of the powder X-ray diffraction pattern [d(Å)/(Irel)/hkl] are: 8.226/(100)/011, 6.492/(100)/002, 4.112/(18)/022, 3.246/(35)/004, 3.085/(19)/130, and 2.458/(21)/042. According to single-crystal X-ray diffraction data, paulišite is monoclinic, space group Ia, Z = 4 with a = 6.3007(6), b = 10.6236(11), c = 12.9837(12) Å, β = 90.840(5)°, V = 868.99(15) Å3. The crystal structure was refined to R1 = 0.0229 for 2330 unique reflections with Fo > 4σ(Fo) and 164 refined parameters. It is characterized by Zn(1)-centered tetrahedra, two independent Ca(1)- and Ca(2)-centered polyhedra, and CO3 groups. Heteropolyhedral Ca-Zn-CO3 {001} layers occur in paulišite and are connected along c through CO3 groups and Ca(2)-centered polyhedra, as well as H-bonds. Along with minrecordite, skorpionite, and znucalite, paulišite is the fourth mineral containing Ca, Zn, and (CO3) groups as species-defining elements. Its origin is related to the supergene alteration of ore deposits following the mining activity, probably at low T and basic pH conditions. The mineral and its name, honouring the Czech mineralogist and geologist Petr Pauliš (b. 1956), have been approved by the Commission on New Minerals, Nomenclature and Classification of the International Mineralogical Association (number 2023-031).
Next-Generation Sequencing in the Development of Climate-Resilient and Stress-Responsive Crops – A Review
Authors: Roy Amitava , Dutta Suman , Das Sumanta , Choudhury Malini Roy
Published: June 2024

Current agricultural production is seriously threatened by climate change and global warming, which also bring new difficulties including the spread of pests and diseases and changes in the environment that can have a big influence on crop yields. Innovative strategies are required to guarantee food security and agricultural sustainability in light of these changing circumstances. To overcome these obstacles, molecular breeding techniques have become essential, particularly with the introduction of next-generation sequencing technology. Chain termination and enzymatic techniques, which were known for their low throughput and efficiency, were the methods used for DNA sequencing in the past. A paradigm change was brought about by the advent of the polymerase chain reaction (PCR) and PCR-based sequencing, which allowed for higher throughput and more effective sequencing procedures. On the other hand, next-generation sequencing, with its unmatched capabilities, represents the latest breakthrough. With the use of this technology, characteristics that govern how the body and metabolism react to different stresses in a changing environment may be examined in greater detail. These developments in molecular breeding technologies not only improve our knowledge of plant responses to global challenges to food production, but they also offer useful tools for creating crops that are climate resilient. Scientists and farmers alike may work towards developing crops that survive the effects of global warming and contribute to a more sustainable and secure food supply by decoding the genetic composition with unprecedented accuracy. In this review, we discuss the opportunities, mechanisms, and implications of next-generation sequencing in the development of climate-resilient crops.
Discovery and Development of Antimalarial Drug Resistance Reversal Agents
Authors: Moyo Phanankosi , Maharaj Vinesh , Mutombo Sephora M. , Andayi Warren Andrew , Amoah Linda , Kalili Kathithileni M. , Asare Kwame Kumi , Danquah Cynthia Amaning
Published: June 2024

Despite the meritorious measures taken to curb the malaria scourge in the last two decades, the drug-resistance phenomenon threatens to reverse the gains made. Evidence of partial resistance against the first-line antimalarial drugs, the artemisininbased combination therapies, in Africa, a region that accounts for 95% of global malaria cases, has aroused fears that it could spread fast and significantly jeopardise malaria control and eradication efforts. While the antimalarial drug discovery pipeline has several, encouraging candidates emerging through it, unfortunately, the attrition rate is high, with some candidates failing either in preclinical studies or clinical trials. Moreover, the rate of emergence of drug-resistant Plasmodium parasite strains far exceeds that of the drug discovery and development process. These challenges demand novel strategies to complement the discovery and development of new therapeutics. One such strategy is the reversal of Plasmodium falciparum resistance to old antimalarials by combining these drugs with agents that specifically target drugresistance mechanisms. This strategy has been successfully used in the antibiotics field, with a classical successful example being the amoxicillin and clavulanic acid combination. In this chapter, we present a case for the need to discover and develop antimalarial drug-resistance reversal agents to prolong the efficacy and use of currently available antimalarial quinoline drugs as well as the re-use of old antimalarial quinoline drugs that have been rendered ineffective by drug-resistance. Furthermore, we provide an overview of noteworthy significant innovations that have been made in the field in search for antimalaria drug-resistance reversal agents. We conclude by providing perspectives on how these efforts can be expedited.
Coffee Agro-industry Conceptual Model Using System Dynamics in Lampung Province, Indonesia
Authors:   IPB University, Rosiana Nia , Feryanto Feryanto ,   IPB University, Simorangkir Nadya Carolina ,   Telkom Indonesia Witel Banten
Published: June 2024

Abstract The consumption trend of coffee downstream products is increasing every year. However, the high variation in the quality of raw materials on the upstream side impacts agroindustrial activities. The limited capacity of processed coffee production indicates that coffee processing activities are not optimal. High competition and individual business activities cause the upstream and downstream linkage of the coffee industry to be limited. The research objective is to analyze the conceptual model of coffee agro-industry development based on the complexity of problems faced by the actors. Primary and secondary data are used as the basis for compiling the conceptual model of the coffee agro-industry using Vensim Software PLE 9.3.5x64. The conceptual sub-models built are farmers, intermediary traders, and processors. Coffee agro-industry is developed by improving the quality and continuity of raw materials, processing capacity, and the actors' skills. Quality and production are connecting variables of the three submodels built. The quality of raw materials produced by farmers will improve the quality of processed coffee. Improving the quality of raw materials is not only from using superior seeds but also from the technical skills of the actors involved. Increased processing capacity can increase the absorption capacity of the coffee agro-industry. Keywords: coffee, dynamic model, intermediary traders, processors, farmers Abstrak Tren konsumsi produk hilir kopi meningkat setiap tahun, tetapi variasi yang tinggi pada kualitas bahan baku di sisi hulu berdampak pada kegiatan agroindustri. Kapasitas produksi olahan kopi yang terbatas mengindikasikan bahwa kegiatan pengolahan kopi belum optimal. Persaingan yang tinggi dan kegiatan usaha yang individual menyebabkan linkage hulu dan hilir industri kopi terbatas. Tujuan penelitian ini adalah menganalisis model konseptual pengembangan agroindustri kopi berdasarkan kompleksitas permasalahan yang dihadapi para pelaku agroindustri kopi. Penelitian dilakukan di Kabupaten Lampung Barat, Provinsi Lampung, Indonesia. Data primer dan sekunder digunakan sebagai dasar penyusunan model konseptual agroindustri kopi dengan menggunakan Software Vensim PLE 9.3.5x64. Submodel konseptual yang dibangun adalah petani, pedagang perantara, dan pengolah. Pengembangan agroindustri kopi dilakukan melalui peningkatan kualitas dan kontinyuitas bahan baku, kapasitas pengolahan, dan skill para pelaku yang terlibat. Kualitas dan produksi menjadi variabel penghubung dari ketiga submodel yang dibangun. Kualitas bahan baku yang dihasilkan petani akan meningkatkan kualitas mutu kopi olahan. Peningkatan kualitas bahan baku dipengaruhi oleh penggunaan bibit unggul dan peningkatan skill teknis dari para pelaku yang terlibat. Peningkatan kapasitas pengolahan dapat meningkatkan daya serap agroindustri kopi. Kata kunci: kopi, model dinamis, pedagang perantara, pengolah, petani