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Assessment of Seasonal Rainfall Prediction in Ethiopia: Evaluating a Dynamic Recurrent Neural Network.to Downscale ECMWF-SEAS5 Rainfall

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Advances in Atmospheric Sciences 2024年第11期41卷 2230-2244页

作者： k.bede A. Warrach-Sagi k. Schwitalla T. Wulfmeyer V. Abebe T. Ware M. Hawassa University College of Agriculture P.O. Box 05 Hawassa Ethiopia Faculty of Meteorology and Hydrology Arba Minch University Water Institute of Technology P.O. Box 21 Arba Minch Ethiopia Institute of Physics and Meteorology University of Hohenheim P.O. Box 70599 Stuttgart Germany

Seasonal rainfall plays a vital role in both environmental dynamics and decision-mak.ng for rainfed agriculture in Ethiopia, a country often impacted by extreme climate events such as drought and flooding. Predicting the onset of the rainy season and providing localized rainfall forecasts for Ethiopia is challenging due to the changing spatiotemporal patterns and the country’s rugged topography. The Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS), ERA5-Land total precipitation and temperature data are used from 1981–2022 to predict spatial rainfall by applying an artificial neural network.(ANN). The recurrent neural network.(RNN) is a nonlinear autoregressive network.with exogenous input (NARX), which includes feed-forward connections and multiple network.layers, employing the Levenberg Marquait algorithm. This method is applied to downscale data from the European Centre for Medium-range Weather Forecasts fifth-generation seasonal forecast system (ECMWF-SEAS5) and the Euro-Mediterranean Centre for Climate Change (CMCC) to the specific locations of rainfall stations in Ethiopia for the period 1980–2020. Across the stations, the results of NARX exhibit strong associations and reduced errors. The statistical results indicate that, except for the southwestern Ethiopian highlands, the downscaled monthly precipitation data exhibits high sk.ll scores compared to the station records, demonstrating the effectiveness of the NARX approach for predicting local seasonal rainfall in Ethiopia’s complex terrain. In addition to this spatial ANN of the summer season precipitation, temperature, as well as the combination of these two variables, show promising results. © Institute of Atmospheric Physics/Chinese Academy of Sciences, and Science Press 2024.

关键词： artificial neural network. downscaling prediction rainfall station

Acetabular cup size trends in total hip arthroplasty

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World Journal of Orthopedics 2024年第1期15卷 39-44页

作者： Daniel Patrick.Mck.nna alex Price Timothy McAleese Darren Dahly Paul Mck.nna May Cleary Department of Trauma and Orthopaedics University Hospital WaterfordWaterford X91 ER8EIreland Department of Epidemiology and Public Health University College CorkCork T12 XF62Ireland

BACk.ROUND Total hip arthroplasty(THA)is a common procedure for end stage *** learning curve for THA is complex and *** of the most difficult sk.lls to master is acetabular *** wish to identify if experience in arthroplasty leads to preservation of more bone *** To investigate if increasing surgeon experience will predict an ever decreasing acetabular cup *** A retrospective case series of four attending orthopaedic surgeons was *** uncemented elective total hip arthroplasties since appointment were selected for *** size of acetabular cup used was noted and logistic regression was used to identify if a trend to smaller cups *** A total of 1614 subjects were included with a mean age of 64 *** cups were on average 0.18mm smaller per year(95%confidence interval-0.25 to-0.11,Pyear for surgeon A,0.02 mm/year for surgeon B,0.15 mm/year for surgeon C and 0.29 mm/year for surgeon *** of the four surgeons had a more pronounced trend to smaller cups for male subjects than their female *** We found increasing surgeon experience to be associated with an ever-decreasing acetabular cup *** acetabular cup size may act as a surrogate mark.r of surgical proficiency by virtue of decreased acetabular reaming.

关键词： Hip Arthroplasty Acetabulum Cup Learning

Growth of RB Population in the Conversion Phase of Chlamydia Life Cycle

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Communications on Applied Mathematics and Computation 2024年第1期6卷 90-112页

作者： Frederic y.M.Wan Department of Mathematics University of CaliforniaIrvineCA92697-3875USA

Upon infecting a host cell,the reticulate body(RB)form of the Chlamydia bacteria simply proliferates by binary fission for an extended *** data show only RB units in the infected cells 20 hours post infection(hpi),spanning nearly half way through the development *** data collected every 4 hpi,conversion to the elementary body(EB)form begins abruptly at a rapid rate sometime around 24 *** modeling proliferation and conversion as simple birth and death processes,it has been shown that the optimal strategy for maximizing the total(mean)EB population at host cell lysis time is a bang-bang control qualitatively replicating the observed conversion ***,the simple birth and death model for the RB proliferation and conversion to EB deviates in a significant way from the available data on the evolution of the RB population after the onset of RB-to-EB *** work.ng with a more refined model that tak.s into account a small size threshold eligibility requirement for conversion noted in the available data,we succeed in removing the deficiency of the previous models on the evolution of the RB population without affecting the optimal bang-bang conversion strategy.

关键词： Chlamydia Life cycle Optimal control Maximal infectious spread Specie competitive survival

Cytomegalovirus Transverse Myelitis Secondary to Influenza Infection and Early Recovery:A Case Report

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Infectious Diseases & Immunity 2024年第1期4卷 41-42页

作者： Jill S.Bhavsar Lek.ini k.Fultariya Poojan J.Prajapati Archi k.Dhamelia Jaime E.Campos Department of Infectious Disease Hialeah HospitalMiamiFL(affiliated with HerbertWertheim College of MedicineFlorida International University)33013USA

Immunosuppression can lead to opportunistic infections in a *** evidence of viral infections causing immunosuppression in a host for a transient period is gaining *** order to prolong their stay in the human body,viruses affect the human immune systemin various *** viral infections such as influenza can lead to transient lymphocytopenia,which lays the groundwork.for more dangerous opportunistic ***(CMV)infection is a rare cause of inflammatory *** present the case of a patient with an influenza infection who progressed to severe acute respiratory distress syndrome,methicillin-resistant Staphylococcus aureus necrotizing pneumonia,and idiopathic lymphocytopenia with a CD4 count of 61 perμL on *** 2 week.,the patient developed complete flaccid paralysis with sensory and autonomic *** his polymerase chain reaction results of cerebrospinal fluid and blood test were positive for CMV infection,he was treated with high doses of steroids and ganciclovir *** to early diagnosis and intervention,the patient was able to recover in 2 months with only minimal residual ***,this case stresses on the importance of look.ng out for opportunistic infections in patients affected by severe viral infections for their early recovery.

关键词： Influenza,Human Lymphocytopenia Transverse myelitis Case report

Guided-yNet: Saliency Feature-Guided Interactive Feature Enhancement Lung Tumor Segmentation Network

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Computers, Materials and Continua 2024年第3期80卷 4813-4832页

作者： Zhou T. Pan y. Lu H. Dang P. Guo y. Wang y. School of Computer Science and Engineering North Minzu University Yinchuan 750021 China k.y Laboratory of Image and Graphics Intelligent Processing of State Ethnic Affairs Commission North Minzu University Yinchuan 750021 China School of Medical Information & Engineering Ningxia Medical University Yinchuan 750004 China

Multimodal lung tumor medical images can provide anatomical and functional information for the same lesion. Such as Positron Emission Computed Tomography (PET), Computed Tomography (CT), and PET-CT. How to utilize the lesion anatomical and functional information effectively and improve the network.segmentation performance are k.y questions. To solve the problem, the Saliency Feature-Guided Interactive Feature Enhancement Lung Tumor Segmentation Network.(Guide-yNet) is proposed in this paper. Firstly, a double-encoder single-decoder U-Net is used as the back.one in this model, a single-coder single-decoder U-Net is used to generate the saliency guided feature using PET image and transmit it into the sk.p connection of the back.one, and the high sensitivity of PET images to tumors is used to guide the network.to accurately locate lesions. Secondly, a Cross Scale Feature Enhancement Module (CSFEM) is designed to extract multi-scale fusion features after downsampling. Thirdly, a Cross-Layer Interactive Feature Enhancement Module (CIFEM) is designed in the encoder to enhance the spatial position information and semantic information. Finally, a Cross-Dimension Cross-Layer Feature Enhancement Module (CCFEM) is proposed in the decoder, which effectively extracts multimodal image features through global attention and multi-dimension local attention. The proposed method is verified on the lung multimodal medical image datasets, and the results show that the Mean Intersection over Union (MIoU), Accuracy (Acc), Dice Similarity Coefficient (Dice), Volumetric overlap error (Voe), Relative volume difference (Rvd) of the proposed method on lung lesion segmentation are 87.27%, 93.08%, 97.77%, 95.92%, 89.28%, and 88.68%, respectively. It is of great significance for computer-aided diagnosis. Copyright © 2024 The Authors. Published by Tech Science Press.

关键词： cross-dimension feature enhancement cross-modal feature enhancement Medical image segmentation saliency feature guidance U-Net

Toxicity Evaluation of Different Exposure Scenarios of Road Dust Using Daphnia magna and Artemia salina as Aquatic Organisms, and Prosopis cineraria and Vachellia tortilis as Native Plant Species

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Open Journal of Air Pollution 2024年第3期13卷 73-86页

作者： Hilal k. Al-Shidi Hameed Sulaiman Department of Educational Studies University of Technology and Applied Sciences Khasab Oman Department of Biology Sultan Qaboos University Muscat Oman

Particulate matter (PM10) deposited as road dust is considered an important source of contamination from atmosphere. However, there are limited studies on the toxicity of road dust as such on different organisms. This study evaluates the toxicity of road dust using different extraction scenarios on Daphnia magna and Artemia salina as aquatic organisms and also on Prosopis cineraria and Vachellia tortilis as local plant species. Chemical analysis of different extracts shows considerable amount of trace metals, however the trace metals in the dust extract associated with suspended sediment were not absorbed by the receptors. On the other hand, the concentration of trace metals in the artificial mixture was found bioavailable and absorbed causing a high percentage of mortality. In the plant assay, significant difference was obtained in the germination percentage between the control and three different extraction exposures in both plant species. The mean root length of P. cineraria and V. tortilis were higher in 20% and 50% extracts than the control probably due to the availability of nutrients from the dust extract. Interestingly however, the seedling vigor index was the opposite with higher index in the control and lower in dust extracts that contain heavy metals.

关键词： Road Dust Heavy Metals Toxicity Bioavailability Holding Time

Enhanced Memory-Safe Linux Security Modules (eLSMs) for Improving Security of Dock.r Containers for Data Centers

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Journal of Software Engineering and Applications 2024年第5期17卷 259-269页

作者： Juan Martinez Delbugio Vijay k. Madisetti School of Cybersecurity & Privacy (SCP) Georgia Institute of Technology Atlanta GA USA

The adoption of Dock.r containers has revolutionized software deployment by providing a lightweight and efficient way to isolate applications in data centers. However, securing these containers, especially when handling sensitive data, poses significant challenges. Traditional Linux Security Modules (LSMs) such as SELinux and AppArmor have limitations in providing fine-grained access control to files within containers. This paper presents a novel approach using eBPF (extended Berk.ley Pack.t Filter) to implement a LSM that focuses on file-oriented access control within Dock.r containers. The module allows the specification of policies that determine which programs can access sensitive files, providing enhanced security without relying solely on the host operating system’s major LSM.

关键词： Dock.r LSM MAC Rust Memory Safe Languages

Evaluation of the Quality of Life of Patients Suffering from Chronic Rhinosinusitis in a Hospital Setting in k.nshasa

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International Journal of Otolaryngology and Head & Neck.Surgery 2024年第1期13卷 41-52页

作者： Hilaire k. k.lala Patricia k. k.k.bo Honoré N. yalombe Lievin k. Mvita Léon N. Muamba Dieudonné T. Nyembue Otorhinolaryngology Service University of Kinshasa Democratic Republic of Congo Imaging Department University of Kinshasa Democratic Republic of Congo Ophthalmology Service University of Kinshasa Democratic Republic of Congo

Back.round and objective: Chronic rhinosinusitis (CRS), a common disease worldwide, has a major impact on patients’ quality of life (QoL). In recent years, the measurement of health-related QoL has made it possible to assess the patient’s state of health, the severity of the CRS and the treatment. The aim of this study was to assess the QoL of patients with CRS in a hospital setting in k.nshasa. Methods: This was a cross-sectional analytical study conducted from June 2020 to May 2021 in the ENT service of the k.nshasa University Hospital and the Monk.le Hospital Center. The study involved 113 patients aged at least 18 years, whose QOL was compared with that of a control group consisting of 100 non-patients. QOL was assessed using the Sino-Nasal Outcome Test (SNOT-22) Questionnaire. Results: The mean age of the patients was 41.0 years (18 - 74 years) and that of the controls was 39.1 years (19 - 77 years). More than half of the participants were university graduates. The median SNOT-22 score was 44 (14 - 78) in patients and 7 (1 - 40) in controls. Compared with subjects without CRS, patients with CRS had significantly higher scores in all four domains of the SNOT-22. Around 9 out of 10 patients had a severely impaired QoL compared with 2 out of 10 controls. Considering mildly impaired QoL, we found that in the otological and sleep domains, scores were not significantly different between patients and controls. In the case of severely impaired QoL, however, only the otological domain showed a non-significant difference in scores between the two groups. Conclusion: CRS is a real public health problem in our environment and significantly alters the QoL of patients suffering from it, with repercussions on their professional productivity;hence the need for better management.

关键词： Chronic Rhinosinusitis Quality of Life SNOT-22 ENT k.nshasa

Modal Frequency Prediction of Chladni Patterns Using Machine Learning

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Open Journal of Acoustics 2024年第1期12卷 1-16页

作者： Atul k.mar k. P. Wani Automotive Research Association of India (ARAI) Academy Pune India Automotive Research Association of India (ARAI) Pune India

The introduction of machine learning (ML) in the research domain is a new era technique. The machine learning algorithm is developed for frequency predication of patterns that are formed on the Chladni plate and focused on the application of machine learning algorithms in image processing. In the Chladni plate, nodes and antinodes are demonstrated at various excited frequencies. Sand on the plate creates specific patterns when it is excited by vibrations from a mechanical oscillator. In the experimental setup, a rectangular aluminum plate of 16 cm x 16 cm and 0.61 mm thick.ess was placed over the mechanical oscillator, which was driven by a sine wave signal generator. 14 Chladni patterns are obtained on a Chladni plate and validation is done with modal analysis in Ansys. For machine learning, a large number of data sets are required, as captured around 200 photos of each modal frequency and around 3000 photos with a camera of all 14 Chladni patterns for supervised learning. The current model is written in Python language and model has one convolution layer. The main modules used in this are Tensor Flow k.ras, NumPy, CV2 and Maxpooling. The fed reference data is tak.n for 14 frequencies between 330 Hz to 3910 Hz. In the model, all the images are converted to grayscale and canny edge detected. All patterns of frequencies have an almost 80% - 99% correlation with test sample experimental data. This approach is to form a directory of Chladni patterns for future reference purpose in real-life application. A machine learning algorithm can predict the resonant frequency based on the patterns formed on the Chladni plate.

关键词： Chaldni Pattern Modal Analysis Machine Learning Resonant Frequency Image Processing