Miracle-dz/UniFAR-FTUs huggingface dataset:
How Artificial Intelligence Is Shaping Medical Imaging Technology: A Survey of Innovations and Applications

The integration of artificial intelligence (AI) into medical imaging has guided in an era of transformation in healthcare. This literature review explores the latest innovations and applications of AI in the field, highlighting its profound impact on medical diagnosis and patient care. The innovation segment explores cutting-edge developments in AI, such as deep learning algorithms, convolutional neural networks, and generative adversarial networks, which have significantly improved the accuracy and efficiency of medical image analysis. These innovations have enabled rapid and accurate detection of abnormalities, from identifying tumors during radiological examinations to detecting early signs of eye disease in retinal images. The article also highlights various applications of AI in medical imaging, including radiology, pathology, cardiology, and more. AI-based diagnostic tools not only speed up the interpretation of complex images but also improve early detection of disease, ultimately delivering better outcomes for patients. Additionally, AI-based image processing facilitates personalized treatment plans, thereby optimizing healthcare delivery. This literature review highlights the paradigm shift that AI has brought to medical imaging, highlighting its role in revolutionizing diagnosis and patient care. By combining cutting-edge AI techniques and their practical applications, it is clear that AI will continue shaping the future of healthcare in profound and positive ways.
Farmer’s management practices to maintain the genetic diversity of sorghum (Sorghum bicolor L. moench) in south of Chad

The objective of this study was to understand the farmer management practices in order to conserve the genetic diversity of sorghum and to determine the level of genetic diversity and local taxonomy in two regions (Logone Oriental and Moyen Chari) of the South of Chad. Total eight villages were visited and from these 53 accessions were collected from 116 inventoried accessions. The number of collected accessions varies from 3 to 9 per village and a loss of diversity was reported between 47 to 71% (average rate of 54.31%) in all villages and this rate varies from village to village. Results of study revealed that the farmer nomenclature is based on the criteria of accession using, origin, color of seeds, type of panicle, crop cycle and the size of plants. This study suggested significant losses in the sorghum diversity of Chad. Therefore, there is a strong need to run a national program to collect, validate and protect the genetic resources of sorghum. This will be helpful in the reducing genetic erosion and to improve the varieties of sorghum cultivated in Chad. GAPILI Naoura * and DJINODJI Reoungal
Extreme Gradient Boosting Combined with Conformal Predictors for Informative Solubility Estimation

We used the extreme gradient boosting (XGB) algorithm to predict the experimental solubility of chemical compounds in water and organic solvents and to select significant molecular descriptors. The accuracy of prediction of our forward stepwise top-importance XGB (FSTI-XGB) on curated solubility data sets in terms of RMSE was found to be 0.59–0.76 Log(S) for two water data sets, while for organic solvent data sets it was 0.69–0.79 Log(S) for the Methanol data set, 0.65–0.79 for the Ethanol data set, and 0.62–0.70 Log(S) for the Acetone data set. That was the first step. In the second step, we used uncurated and curated AquaSolDB data sets for applicability domain (AD) tests of Drugbank, PubChem, and COCONUT databases and determined that more than 95% of studied ca. 500,000 compounds were within the AD. In the third step, we applied conformal prediction to obtain narrow prediction intervals and we successfully validated them using test sets’ true solubility values. With prediction intervals obtained in the last fourth step, we were able to estimate individual error margins and the accuracy class of the solubility prediction for molecules within the AD of three public databases. All that was possible without the knowledge of experimental database solubilities. We find these four steps novel because usually, solubility-related works only study the first step or the first two steps.
Enforcement methods and influential factors of competitive intelligence ethics adoption: a case of South African ICT industry

The defining characteristic of CI practice is the implementation and strict adherence to ethical principles. While there is evidence of ongoing CI practices by corporations, critics argue that there is a dearth of scientific research on the implementation and enforcement of CI ethics. Critics contend that the absence of ethical adoption and enforcement of competitive intelligence (CI) principles has created a nebulous zone that blurs the distinction between CI and industrial espionage. The adoption and implementation of competitive intelligence (CI) ethics guarantees that companies engage in ethical and legal CI practices. It improves the standing of companies and reduces the cost of having to restore a damaged reputation. The aim of this study was to determine the level of acceptance of corporate integrity ethics in the ICT industry in South Africa. Furthermore, the objective is to evaluate the strategies employed for enforcing ethical practices and the various elements that impact the adoption of corporate integrity ethics in the ICT industry in South Africa. The research employed a quantitative approach, utilizing a web-based questionnaire to gather data from professionals working in the South African ICT business. The study discovered that South African ICT companies fully embraced CI ethics. Furthermore, the study identified seven elements that have an impact on the adoption of CI ethics, as well as multiple approaches for enforcing ethical practices. As a result, South African ICT enterprises are able to save money that would otherwise be spent on repairing their reputation after being accused of industrial espionage. Furthermore, companies should enhance and diminish aspects that have a positive and negative impact on the adoption of CI ethics, respectively.
The Correlation of Serum Uric Acid Levels With the Severity of Coronary Artery Disease in Diabetic Patients: A Cross-Sectional Study

Background and aim Coronary artery disease (CAD) is a severe and life-threatening complication in patients with diabetes, resulting in significant morbidity and death burden globally. Although serum uric acid levels have been linked to the aetiology of both CAD and diabetes, the association between uric acid and CAD severity in diabetic patients remains unknown. This study aimed to investigate the relationship between serum uric acid levels and the severity of CAD in patients with diabetes undergoing coronary angiography. This study also compared patient parameters and comorbidities linked with high uric acid levels. Material and methods This cross-sectional study was conducted at the Lady Reading Hospital in Peshawar, Pakistan, from October 20, 2022, to September 20, 2023. A total of 290 patients with diabetes were enrolled. These participants were divided into groups depending on their serum uric acid levels: Group A (n = 145) and Group B (n = 145). On average, patients in Group A had high serum uric acid levels, whereas those in Group B had normal serum uric acid levels. Coronary angiograms were analysed using well-established assessment methods to determine the severity of CAD using the Syntax score as the mean score was greater for Group A with higher serum uric acid levels than Group B. Results The mean age of patients in Group A was 59.2±7.1 years, whereas in Group B, it was 60.5±6.8 years. The percentage of male patients in Group A was 62% and 58.6% in Group B. The mean BMI for group A was 28.4±2.3 kg/m2, while the mean BMI for group B was 27.9±2.1 kg/m2. In both groups, the prevalence of hypertension, dyslipidemia and family history of CAD did not differ significantly. Group A's mean serum uric acid levels were 8.17 ± 1.64, while in Group B, 5.03 ± 1.09. Similarly, the mean Syntax score, which is a visual estimate of CAD burden and complexity, was higher in Group A (37.59 ± 3.41) compared to Group B (26.44 ± 2.97), and the difference was statistically significant (p = 0.001). The severity of CAD based on syntax score was found to be significantly different in both groups (p=0.04). Conclusion This study illustrates that patients with high uric acid levels are more likely to have CAD as indicated by a higher mean Syntax score in Group A compared to Group B. However, serum uric acid levels alone cannot accurately predict the severity of CAD on coronary angiography in diabetic patients. These findings add to the evidence already available, emphasizing the significance of serum uric acid as a potential biomarker for risk stratification in this vulnerable population.
Appropriation and usage of management control tools: An imperious reconsideration of the behavioral representations of actors in a public organization

Nowadays, public organizations are in a state of perpetual change. They are part of the need to improve performance supported by the New Public Management (NPM) trend (El Oussa & Fasly, 2023). In this sense, adherence to this movement is materialized by the insertion of management control tools, which are straddled between the instrumental aspect based on a technicality in relation to specific ends (Martineau, 2014) and the behavioral aspect is the real responsible for the fate of these tools. This paper aims to understand how users use appropriate management control tools, by determining the factors behind their usage behaviors. For this purpose, we have applied an interpretivist epistemology by conducting an exploratory qualitative study in a Moroccan public institution, we carried out semi-structured interviews with 10 members of the audit and management control department. Our results show that there are several modes of usage (solid, fragile, rejection) differing from one actor to another. This divergence in behavior is due to institutional factors, factors linked to the tool’s attributes and socio-psychological factors linked to the user. Our results contribute to enriching the literature by deducing the different usages and modes of appropriation supported by the factors that promote or hinder the implementation of management control tools.
Technology Innovation and Evolution in Circuit Protection

Significant improvement in performance has been made over the past decades for circuit breakers due to advancement of arcing contact science, material science, and electronic technology. Two key R&D areas are interruption capability and digitization. Physical phenomena and design parameters that affect arc interruption includes arc chamber material outgassing, contact materials and post-arc current phenomena. If not properly designed, they often lead to re-ignition after current zero, resulting in failed short circuit interruption. Understanding of these phenomena and their impact on arc interruption is critical for circuit breaker development and design.More recently, driven by energy transition and future power grid needs, significant investigation and study has been made in solid state and hybrid circuit breaker technology for DC applications. This type of circuit breakers can interrupt a short circuit event within tens or hundreds of microseconds instead of milliseconds or tens of milliseconds by electromechanical circuit breakers. They enable circuit protection with bi-directional current flow, remote controllability, and software-defined functionality.This paper will highlight some of the technology development work on circuit breaker by the author and his colleagues over three decades. Meanwhile it will provide an overview of needs and emerging technologies for future circuit protection.
The Correlation of Pain, Psychological Aspects, and Sleep in Fibromyalgia: A Cross-Sectional Analysis

Background This pilot study measures pain perception, somatosensory amplification and its relationship to health anxiety in patients with fibromyalgia (FM) and patients with FM and obstructive sleep apnea (OSA); this study also examines the effects of OSA on pain perception in patients with FM. Methods In this pilot study, patients diagnosed with FM or FM and OSA, completed three self-reported questionnaires: Short-Form McGill Pain Questionnaire (SF-MPQ), Somatosensory Amplification Scale (SSAS), and Illness Behavior Questionnaire (IBQ). Sleep study results were analyzed. Scores were summarized using medians and interquartile ranges and are compared using Wilcoxon rank sum tests. Results Overall FM (n = 25), female n=23 male n=3 mean age, 57.48 years. OSA n=17 (68%) and 8 (32%) were not. The SF-MPQ Sensory sub-scale scores and the SF-MPQ overall scores differed significantly between patients with and without OSA. The SF-MPQ Sensory sub-scale scores were significantly lower for patients with OSA (p=0.03), as were SF-MPQ overall scores (p=0.04). SSAS overall scores and IBQ overall scores did not differ significantly by OSA diagnosis. Correlations of the different dimensions of IBQ with SSAS and mean number of diagnoses in FM and FM+OSA, mean number of diagnoses in problem list of SSAS ≤30 was 29.5, mean number of diagnoses in SSAS ≥30 was 34.9. Discussion Developing a better understanding of the effects of OSA on pain perception in patients with FM is needed for improved health status. More research is needed to see if higher pain perception and SSAS score lead to increased health care utilization and to evaluate the relationship between untreated disordered sleeping and pain perception in patients with FM. Conclusion Our findings highlight the need for more research to evaluate the relationship between treated and untreated disordered sleeping, pain perception, somatization and illness behavior in the health status of individuals with FM.
A Real Time Physics-Based Industrial Control System Honeynet Architecture for the Smart Grid

Many details of cyber attacks occurred to Industrial Control Systems (ICS) such as power grids remain as a secret. To reveal those secrets and benefit a broad research community, we propose an original cyber-physical honeypot architecture that can seamlessly couple IT and OT components in an power grid. Specifically, we will provide high interaction with adversaries as physical processes of an ICS move forward, revealing attack strategies according to adversaries’ knowledge on physical trajectories of the target system. Our preliminary evaluations demonstrate that the proposed CPS honeypot can present realistic device fingerprints and application-layer payload that piggybacks meaningful measurements conforming to the physical model of a power grid. In addition, by leveraging runtime high-fidelity OPAL-RT simulator, our CPS honeypot causes small latency, at least one order of magnitude smaller compared to the existing work.
Sialic Acid Mimetic Microglial Sialic Acid-Binding Immunoglobulin-like Lectin Agonism: Potential to Restore Retinal Homeostasis and Regain Visual Function in Age-Related Macular Degeneration

Age-related macular degeneration (AMD), a leading cause of visual loss and dysfunction worldwide, is a disease initiated by genetic polymorphisms that impair the negative regulation of complement. Proteomic investigation points to altered glycosylation and loss of Siglec-mediated glyco-immune checkpoint parainflammatory and inflammatory homeostasis as the main determinant for the vision impairing complications of macular degeneration. The effect of altered glycosylation on microglial maintained retinal para-inflammatory homeostasis and eventual recruitment and polarization of peripheral blood monocyte-derived macrophages (PBMDMs) into the retina can explain the phenotypic variability seen in this clinically heterogenous disease. Restoring glyco-immune checkpoint control with a sialic acid mimetic agonist targeting microglial/macrophage Siglecs to regain retinal para-inflammatory and inflammatory homeostasis is a promising therapeutic that could halt the progression of and improve visual function in all stages of macular degeneration.
The export and fate of organic matter in the ocean: New constraints from combining satellite and oceanographic tracer observations

The ocean's biological pump transfers carbon from the surface euphotic zone into the deep ocean, reducing the atmospheric CO2 concentration. Despite its climatic importance, there are large uncertainties in basic metrics of the biological pump. Previous estimates of the strength of the biological pump, as measured by the amount of organic carbon exported from the euphotic zone, range from about 4 to 12 Pg C yr−1. The fate of exported carbon, in terms of how efficiently it is transferred into the deep ocean, is even more uncertain. Here we present a new model of the biological pump that assimilates satellite and oceanographic tracer observations to constrain rates and patterns of organic matter production, export, and remineralization in the ocean. The data‐assimilated model predicts a global particulate organic carbon (POC) flux out of the euphotic zone of ∼9 Pg C yr−1. The particle export ratio (the ratio of POC export to net primary production) is highest at high latitudes and lowest at low latitudes, but low‐latitude export is greater than predicted by previous models, in better agreement with observed patterns of long‐term carbon export. Particle transfer efficiency (Teff) through the mesopelagic zone is controlled by temperature and oxygen, with highest Teff for high‐latitude regions and oxygen minimum zones. In contrast, Teff in the deep ocean (below 1000 m) is controlled by particle sinking speed, with highest deep ocean Teff below the subtropical gyres. These results emphasize the utility of both remote sensing and oceanographic tracer observations for constraining the operation of the biological pump.
In Situ Synthesis of Highly Fluorescent, Phosphorus-Doping Carbon-Dot-Functionalized, Dendritic Silica Nanoparticles Applied for Multi-Component Lateral Flow Immunoassay

The sensitivity of fluorescent lateral flow immunoassay (LFIA) test strips is compromised by the low fluorescence intensity of the signaling molecules. In this study, we synthesized novel phosphorus-doped carbon-dot-based dendritic mesoporous silica nanoparticles (DMSNs-BCDs) with a quantum yield as high as 93.7% to break this bottleneck. Meanwhile, the in situ growth method increased the loading capacity of carbon dots on dendritic mesoporous silica, effectively enhancing the fluorescence intensity of the composite nanospheres. Applied DMSNs-BCDs in LFIA can not only semi-quantitatively detect a single component in a short time frame (procalcitonin (PCT), within 15 min) but also detect the dual components with a low limit of detection (LOD) (carbohydrate antigen 199 (CA199) LOD: 1 U/mL; alpha-fetoprotein (AFP) LOD: 0.01 ng/mL). And the LOD of PCT detection (0.01 ng/mL) is lower by 1.7 orders of magnitude compared to conventional colloidal gold strips. For CA199, the LOD is reduced by a factor of four compared to LFIA using gold nanoparticles as substrates, and for AFP, the LOD is lowered by two orders of magnitude compared to colloidal gold LFIA. Furthermore, the coefficients of variation (CV) for intra-assay and inter-assay measurements are both less than 11%.
Analysis of Bundles and Drivers of Change of Multiple Ecosystem Services in an Alpine Region

Approaches based on the concept of ecosystem services need analyses of the sets of spatially correlated services (i.e. bundles) and of the external factors that modify the ecosystem service supply (i.e. drivers of change). At present, appropriate methods to analyse bundles and drivers of change are still under development. This study proposes a method based on a combination of spatial and statistical analyses to define bundles and to explain the drivers of change of 24 ecosystem services in Trentino, an Alpine region of Italy. Results show that multiple services can be grouped in a few number of bundles with a complex shape. When mapping multiple services across the territory, the spatial units of representation are a combination of the intrinsic units of representation of single ecosystem services and land use classes. Land use management was found as the external factor that causes the greatest variability of the ecosystem services distribution across the region.
A Topological Data Analysis of the Protein Structure

Persistent homology is a tool from a set of methods called Topological data analysis, showing until nowadays a lot of success when it comes to application in biology since this latest uses metrics only for measuring similarities, Embedding the geometric details and focusing on the global shape is the key point making the success of persistent homology, this will be investigated in the paper since enormous work already done in the field and results seems to be endless, as an efficient topological data analysis tool. In this work we will be confirming the latest assumption (topology embeds geometry) by displaying the structure of COILED SERINE which is a protein estimated to constitute 3-5 percent of the encoded residues in most genomes, and giving a substitute of the optimal characteristic distance that can be used in the flexibility-rigidity index, a classic method used to simulate molecule movements and flexible behavior, when it comes to atomic rigidity functions. We will also analyze interesting patterns in the binding site of the beta sheet generated from the pdb file 2JOX. We will be detecting and giving a simple description of different patterns generated by using javaplex generating barcodes and linear statistical results as a summary statistics.
Validity and Reliability of the Malay Questionnaire for Olfactory Disorders

Background Olfactory disorders (OD) are an umbrella term for a diverse group of smell problems. Numerous tests and questionnaires have been formulated to identify and test the severity of smell impairment, which is not readily available or translated for the Malaysian population. This study aimed to translate the Questionnaire for Olfactory Disorders (QOD) and validate and test the reliability of the Malay Questionnaire for Olfactory Disorders (mQOD). Methods This cross-sectional study was conducted in two tertiary centres. A forward and backward translation was conducted for the QOD. The translated questionnaire was distributed to subjects with self-reported smell disorders on days 1 and 7. Internal consistency was analysed using Cronbach’s alpha and test-retest reliability was tested with an intraclass correlation coefficient. Confirmatory factor analysis was performed to test construct validity. Results A total of 375 participants were recruited, 52 dropped out and 323 completed the questionnaire a second time. The Cronbach’s alpha coefficient was 0.537 for parosmia (P), 0.892 for life quality (LQ), 0.637 for sincerity (S) and 0.865 for visual analogue score (VAS). The intraclass correlation coefficient (ICC) for domain scores was > 0.9, while the ICC for all items was good to excellent. A three-factor model for mQOD showed an acceptable fit with indices chi-square value (CMIN)/degree of freedom (DF) = 3.332, Tucker-Lewis fit index (TLI) = 0.923, comparative fit index (CFI) = 0.939, root mean square error of approximation (RMSEA) = 0.079 and standardised root mean square residual (SRMR) = 0.0574. Conclusion The mQOD is a valid and reliable tool for assessing OD in patients.