Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Approach to Identify the Brain Tumour Using Convolutional Neural Network

INTRODUCTION: Determining the possibility that an individual is affected by a tumour is an intricate process in today's modern technological and biological age, when feats are reaching unprecedented levels with every passing second. Machine learning modalities could dramatically enhance the accuracy of diagnosis. OBJECTIVES: Our research makes it feasible to detect tumours early, aiding in early diagnosis, and is a necessity for the curative efforts of cancer patients. METHODS: In our research model Convolutional Neural Network (CNN) was implemented using Jupiter to give an accurate result. RESULTS: In our proposed model we got 99% accuracy that is higher than the other results. CONCLUSION: Our research demonstrates the potential of using machine learning techniques to improve the accuracy and efficiency of medical diagnosis.
A method for esophageal cancer classification using mutual information feature selection and adversarial samples

Early detection and treatment of esophageal cancer may improve the survival rate of patients, despite its high incidence and mortality. The use of computer technology can assist in the diagnosis of esophageal cancer. RNA-Seq gene expression data can be used for the diagnosis of esophageal cancer, but it is difficult to analyze directly because of its high dimension and small sample size. Applying computer technology to this data can solve these problems. In our work, we used the RNA-Seq gene expression dataset and considered the specificity of the sample, proposed an artificial intelligence approach for esophageal cancer classification through selecting the comprehensive features of RNA-Seq gene expression data using mutual information feature selection and obtaining a set of sample specific features by generating adversarial examples using one-pixel attack method to reduce the dimensionality of the dataset. Finally, the deep learning method is used to construct a deep neural network as the classifier. The experimental results reveal that this method outperforms other state-of-the-art algorithms in terms of accuracy and other metrics.
Place de la thermodiffusion dans l'évaluation de l'état initial des gisements pétroliers

After their migration into the trap, the fluids are shaped by various forces, among them, gravity has the most striking effect and was widely studied. Yet, in the case of diphasic reservoirs, the observed variations of composition are significantly stronger than those calculated with this approach. The contribution of other forces like the thermal gradient is more difficult to assess because of the lack of reliable data on thermodiffusion coefficients. At a first look, the effect of geothermal gradient does not account for the gap between data and gravitational profile. In the case of a complex diphasic fluid column in a reservoir from Guinea Gulf, we concluded to the presence of a dynamic transition zone between the oil and the gas zone due to thermo-convection in the gas phase. As a consequence, an increase of the compositionnal gradients in the oil zone close to the interface is likely. The on-going studies on thermodiffusion phenomena should soon provide a reliable modelling of such phenomena.
Design of Dual-Band Doherty Power Amplifier Using a New Phase Compensation Technique

In this brief, a novel methodology for designing a dual-band Doherty power amplifier (DPA) is proposed by using different current combining phases between the carrier and peaking power amplifiers (PAs) at different operating frequencies. It is illustrated that, by configuring appropriate dual-band current combining phases, an equivalent quarter-wavelength network can be used to replace the dual-band impedance inverter network (IIN) for dual-band Doherty operation. The required high-efficiency impedance conditions of carrier PA at output back-off (OBO) level are analyzed in detail based on the proposed architecture. To validate the proposed method, a dual-band DPA employing commercial GaN devices is designed and implemented. The fabricated DPA achieves 67%/70% efficiencies for saturated power level at 1.8/2.6 GHz. At 6-dB OBO level, the measured efficiencies are 56%/59% at 1.8/2.6 GHz, respectively.
Real-Time Event Detection Using Self-Evolving Contextual Analysis (SECA) Approach

Dynamically monitoring and analyzing evolving real-world events (riots, earthquakes, and football matches) using publicly available short texts (social media posts) is becoming increasingly important. This content can hold critical information about various events, which can help decision-makers to make better decisions. Significant research efforts have been made in this regard. However, most of these provide solutions based on black-box engines, in which technical capabilities are required to understand their internal mechanics. Also, they offer very little information about the detected events and generally tend to answer very high-level questions, such as: “what are the main topic clusters? ” “what are the main words (e.g. top ten words) of these topics? ”. These challenges can limit their usage in some critical domains, where the need for transparency, and more information, to analyze a particular situation is crucial. Thus, to complement and fill the gap in the direction of existing studies, in which the effectiveness and success of the proposed approaches are insufficiently determined by their performance scores, this paper presents datasets that can be used for dynamic topic detection of different frequencies over time based on real Tweets and a new transparent method for the dynamic event detection problem called Self-Evolving Contextual Analysis (SECA). It helps to answer, for any given time frame, other fundamental questions, such as: “what are the sub-topics of, and their relationship to, a topic (or a sub-topic? )”, “what are the changing topics and sub-topics? ”, “what are the new trends? ”, “what are the topics no longer being discussed? ” and most importantly, “why and how have these topics and changes been identified and generated? ”. Moreover, Performance and Carbon Footprint assessments reveal the comparative effectiveness of the proposed approach. In addition, this paper presents a practical implementation of SECA to dynamically analyze tweets collected during the FIFA World Cup 2022 Final Match.
Analysis of Ocean Acidification in the Pacific Ocean Based on the Data-driven Evaluation of the Air-sea Carbon Dioxide Flux

The ocean absorbs about 1/3 of the anthropogenic CO2 released to the atmosphere. As more CO2 accumulates in the ocean, the oceanic pH decreases, leading to ocean acidification. In order to better understand the carbon cycle in the ocean and associated long-term pH variation, we estimate CO2 exchange flux at the sea surface in the Pacific Ocean with the empirical method proposed by Sugimoto et al. (2012) exploiting the publically available oceanic dataset. The oceanic CO2, the air-sea CO2 flux, and pH are successfully evaluated for the Pacific Ocean from 1985 through 2008. The pH and CO2 absorption relation is then argued along with climatological influences during the ENSO events.
Optimal Promotional Effort and Pricing Policies for a Multiple Item Innovation Diffusion Model involving Fuzzy Parameters

With immense competition, coupled with short and unpredictable shelf life of products in some cases, companies rely upon diversifying their product range to disperse risk associated with failure of one product. Since pricing is also dynamic, varying with time, there is also a need for the companies to formulate appropriate pricing policies to maximize profits as against expenses incurred in promotion of multiple products. In this paper we device and analyze policies for promoting sales of multiple products in the market through optimal control theory problems. The main aim is to maximize profits while considering multiple product range, demand requirements and optimum pricing policy for an available budget for promotion. To be as near as possible to a real-life situation, the total available budget is taken to be imprecise. Further, optimal control model with fuzzy parameter is converted into crisp form by using both necessity and possibility constraints. The solution is derived using Pontryagin Maximum principle and the entire technique is illustrated by giving a numerical example.
Cooperatively inhibition effect of miR-143-5p and miR-145-5p in tumorigenesis of glioblastoma cells through modulating AKT signaling pathway

Introduction: As the most common aggressive primary brain tumor, glioblastoma is inevitably a recurrent malignancy whose patients’ prognosis is poor. miR-143 and miR-145, as tumor suppressor miRNAs, are downregulated through tumorigenesis of multiple human cancers, including glioblastoma. These two miRNAs regulate numerous cellular processes, such as proliferation and migration. This research was intended to explore the simultaneous replacement effect of miR-143, and miR-145 on in vitro tumorgenicity of U87 glioblastoma cells. Methods: U87 cells were cultured, and transfected with miR-143-5p and miR-145-5p. Afterward, the changes in cell viability, and apoptosis induction were determined by MTT assay and Annexin V/PI staining. The accumulation of cells at the cell cycle phases was assessed using the flow cytometry. Wound healing and colony formation assays were performed to study cell migration. qRT-PCR and western blot techniques were utilized to quantify gene expression levels. Results: Our results showed that miR-143-5p and 145-5p exogenous upregulation cooperatively diminished cell viability, and enhanced U-87 cell apoptosis by modulating Caspase-3/8/9, Bax, and Bcl-2 protein expression. The combination therapy increased accumulation of cells at the sub-G1 phase by modulating CDK1, Cyclin D1, and P53 protein expression. miR-143/145-5p significantly decreased cell migration, and reduced colony formation ability by the downregulation of c-Myc and CD44 gene expression. Furthermore, the results showed the combination therapy of these miRNAs could remarkably downregulate phosphorylated-AKT expression levels. Conclusion: In conclusion, miR-143 and miR-145 were indicated to show cooperative anti- cancer effects on glioblastoma cells via modulating AKT signaling as a new therapeutic approach.
ASSESSMENT OF THE EFFECT OF AEROSOL DISINFECTION OF NANOSILVER AND HYDROPEROXIDE AG+ AT CAN THO UNIVERSITY OF MEDICINE AND PHARMACY

Background: One of the crucial methods for lowering hospital infections is air disinfection. Because the airborne contagion environment is difficult to control, the development of effective air disinfectants is critical to maintaining a safe air environment and preventing respiratory infections. At the Hospital of Can Tho University of Medicine and Pharmacy, nanosilver and hydroperoxide Ag+ are two different kinds of airborne infection control, so an analytical cross-sectional study was conducted with objectives: to compare the disinfection efficacy of two solutions, nanosilver and 5% Hydroperoxide - 0.005% Ag+, and to assess the efficacy of the silver nano solution and 5% Hydroperoxide - 0.005% Ag+ solution in disinfecting hospital air. Materials and methods: This study was conducted on 156 air microbiological samples in 13 wards at the Can Tho University of Medicine and Pharmacy Hospital using Koch's dust deposition method based on the principle of allowing dust to settle on the surface of nutrient agar boxes for a certain period. Data analysis using SPSS 26.0 software. Results: After disinfecting the rooms with nanosilver, the air quality was good in 69.23% of cases and pretty in 30.07%. With 5% Hydroperoxide - 0.005% Ag+, the number of rooms with good air quality was 15.39%, with pretty air was 69.23, and with poor air was 15.39%. Nanosilver can eradicate the fungus from Sabouraud Agar medium, and the density after disinfection was lower than before; the difference was not statistically significant (p>0.05). Moreover, on Macconkey Agar and Blood Agar medium, bacterial density after disinfecting by nanosilver was decreased; the difference was statistically significant (p < 0.05). Nanosilver reduced the bacterial density in 4 types of rooms better than 5% Hydroperoxide - 0.005% Ag+ solution. However, the difference was not statistically significant (p > 0.05). Conclusions: Nanosilver can be used to disinfect the hospital air as an alternative to 5% Hydroperoxide - 0.005% Ag+. Nanosilver disinfects well on gram-negative and gram-positive bacteria. Additional methods for improving the antifungal impact of nanosilver are required.
Mediators of psychosocial well-being for immigrant women living with breast cancer in Canada: a critical ethnography

Abstract Background: Immigrant women living with breast cancer experience a lack of psychosocial and emotional support, which adds to the complexity of navigating and using health care services in Canada. Aim: To explore the mediators of psychosocial well-being for immigrant women living with breast cancer in Canada. Methods: A critical ethnography was used. The study identified 27 immigrants living with breast cancer, who had been born in a foreign country, migrated to Canada within the past 10 years, and lived in rural communities of British Columbia between August 2021 and March 2022. Institutional research ethics board approval and informed consent were obtained. Results: The findings indicated two significant themes: The immigrant women had limited knowledge, information, and communication and experienced physical, psychological, and emotional distress. Conclusion: There is a significant need for culturally responsive care services for immigrant women living with breast cancer in rural communities. Recommendations include the development of psychosocial oncology, such as integrated counseling and therapies, to reduce cancer-related post-traumatic stress and improve their psychosocial and emotional well-being. Interdisciplinary approaches to psychosocial oncology are particularly crucial for immigrants and rural communities, where women need access to cancer navigation and ongoing support for a better health-related quality of life.
Lava dome growth and evolution with an independently deformable talus

Subduction zone volcanism occurs due to partial melting from subducting slabs, which generally results in high-viscosity magma containing a large amount of volatiles. Such volcanic eruptions can form a lava dome, from which collapse events are a common and important part of their evolution. Collapse events can have devastating consequences; in the form of block and ash avalanche deposits, pyroclastic ﬂows, surges and the generation of tsunamis if they enter the sea. In addition to this, once a mass of lava dome has been removed during a collapse event, this results in a drop in pressure in the remaining volatile-rich magma, which may then erupt explosively. The internal structure of a lava dome and the extent of the surrounding carapace/talus is unknown, but likely to be critical for hazard assessment, and is the motivation for this research. Presented is a computational model for the growth and evolution of an endogenous lava dome, including an independently deformable talus, using the Finite Element Method. Dome growth is modelled to occur under two time-scales: continuous dome expansion via the addition of new magma into the molten core interior, and relatively instantaneous talus readjustments due to rockfalls and the disintegration of the solid surface. The continuous deformation of the dome is modelled as a ﬂuid with a yield strength in the talus region. While talus deformation is modelled as a granular material that rests at angles below its angle of repose. Both surfaces, dome and core/talus interface, are displaced using the level-set method. The model is axi-symmetric and assumes that solidiﬁcation, and therefore talus growth, occurs due to gas exsolution which promotes crystallisation, rather than from surface cooling, appropriate for intermediate composition lava ﬂows. For the purpose of this paper we consider and apply the model to the Soufriere Hills Volcano, Montserrat, but the techniques used are generic, allowing the model to be applied to other dome forming eruptions. The model provides information on the shape of the dome, with the growth and extent of the talus and core found to be predominantly governed by the lava extrusion rate, degree of solidiﬁcation (i.e. a solidus pressure), the friction angle associated with the talus, and lava dome viscosity.
Global health reciprocal innovation to address mental health and well-being: strategies used and lessons learnt

Over the past two decades there have been major advances in the development of interventions promoting mental health and well-being in low- and middle-income countries (LMIC), including delivery of care by non-specialist providers, incorporation of mobile technologies and development of multilevel community-based interventions. Growing inequities in mental health have led to calls to adopt similar strategies in high-income countries (HIC), learning from LMIC. To overcome shared challenges, it is crucial for projects implementing these strategies in different global settings to learn from one another. Our objective was to examine cases in which mental health and well-being interventions originating in or conceived for LMIC were implemented in the USA. The cases included delivery of psychological interventions by non-specialists, HIV-related stigma reduction programmes, substance use mitigation strategies and interventions to promote parenting skills and family functioning. We summarise commonly used strategies, barriers, benefits and lessons learnt for the transfer of these innovative practices among LMIC and HIC. Common strategies included intervention delivery by non-specialists and use of digital modalities to facilitate training and increase reach. Common barriers included lack of reimbursement mechanisms for care delivered by non-specialists and resistance from professional societies. Despite US investigators’ involvement in most of the original research in LMIC, only a few cases directly involved LMIC researchers in US implementation. In order to achieve greater equity in global mental health and well-being, more efforts and targeted funding are needed to develop best practices for global health reciprocal innovation and iterative learning in HIC and LMIC.
Obstructive Sleep Apnea Screening by Joint Saturation Signal Analysis and PPG-Derived Pulse Rate Oscillations

Obstructive sleep apnea (OSA) is a high-prevalence disease in the general population, often underdiagnosed. The gold standard in clinical practice for its diagnosis and severity assessment is the polysomnography, although in-home approaches have been proposed in recent years to overcome its limitations. Today's ubiquitously presence of wearables may become a powerful screening tool in the general population and pulse-oximetry-based techniques could be used for early OSA diagnosis. In this work, the peripheral oxygen saturation together with the pulse-to-pulse interval (PPI) series derived from photoplethysmography (PPG) are used as inputs for OSA diagnosis. Different models are trained to classify between normal and abnormal breathing segments (binary decision), and between normal, apneic and hypopneic segments (multiclass decision). The models obtained 86.27% and 73.07% accuracy for the binary and multiclass segment classification, respectively. A novel index, the cyclic variation of the heart rate index (CVHRI), derived from PPI's spectrum, is computed on the segments containing disturbed breathing, representing the frequency of the events. CVHRI showed strong Pearson's correlation (r) with the apnea-hypopnea index (AHI) both after binary (r = 0.94, p $< $ 0.001) and multiclass (r = 0.91, p$< $0.001) segment classification. In addition, CVHRI has been used to stratify subjects with AHI higher/lower than a threshold of 5 and 15, resulting in 77.27% and 79.55% accuracy, respectively. In conclusion, patient stratification based on the combination of oxygen saturation and PPI analysis, with the addition of CVHRI, is a suitable, wearable friendly and low-cost tool for OSA screening at home.
Physical activity and sedentary behaviour in a school sample of Kuwaiti adolescents : sociodemographic correlates and associations with adiposity and blood pressure : the Study of Health and Activity among Adolescents in Kuwait (SHAAK)

Background. Epidemiological studies of both physical activity and sedentary behaviour in Kuwait and Middle East are scarce and rely almost entirely on self-reported measures. Levels of physical activity and sedentary behaviour patterns have not been described using objective measures. Research on sociodemographic correlates of physical activity and sedentary behaviour are limited and the links between physical activity, sedentary behaviour with adiposity and blood pressure are unclear and inconsistent. Aims. The main aim of this PhD was to describe the levels of physical activity, sedentary behaviour and their socio-demographic correlates among adolescents in Kuwait using self-reported and accelerometer based measures and to examine the associations of physical activity and sedentary behaviour with two sets of key cardiometabolic outcomes (adiposity and blood pressure). Methods. Participants (279 male and 310 female) in school grades 6-12 were recruited. Physical activity and sedentary behaviour were assessed using a self-administered questionnaire and a GT1M Actigraph accelerometer worn for 7 consecutive days. Results. Very few adolescents met the physical activity recommendations, 14% using self-report and 2% using objective physical activity measure. Results revealed that 93% of the adolescents in this study did not limit screen time to less than two hours per day. Accelerometer based physical activity was lower among girls and declined with age, while sedentary behaviour was higher among girls and increased with age. The study revealed that accelerometer based physical activity and sedentary behaviour was not ass ociated with adiposity or blood pressure. Conclusion. These data will provide baseline information to enable overnmental authorities to steer physical activity promotion programmes to key target populations. The low physical activity levels documented in this study call for action to promote physical activity and reduce sedentary behaviour among Kuwaiti adolescents.
Analysis of PIT tag recoveries through 2009

This was the fi nal year of scanning for PIT tag recoveries. Patterns of recoveries were consistent with recent years. This year we fi tted some new models to the data, and the best fi tting model allowed emigration probability to be a linear function of halibut length on the logistic scale. Under this model, quite different relationships were estimated for each regulatory area, with smaller fi sh being more likely to migrate from Areas 4A and 3B, and larger fi sh having greater, albeit imprecisely estimated, migration rates from eastern areas. Estimates of net migration in terms of exploitable biomass are also presented in this report. These show that relative to their area’s biomasses, Area 2B is the greatest net recipient and Area 4A the greatest net exporter.