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Prevalence of visual impairment and estimation of refractive errors among school children in Kakamega,Kenya

International Journal of Ophthalmology(English edition) 2024年第5期17卷 932-939页

作者： Isabel Signes-Soler Alfred Ragot Sheilah Nangena andrew Wekesa Raúl Montalbán Llamusí Department of Optics and Optometry and Vision Sciences Universidat de ValènciaBurjassotValencia 46010Spain NGO Vision Without Borders(Visio Sense Fronteres VSF)Calpe 03710AlicanteSpain Masinde Muliro University of Science and Technology P.O Box 190-50100KakamegaKenya clinica Baviera Alicante c/Ausóy Monzó 16Alicante 03006Spain

AIM:To investigate the prevalence of visual impairment(VI)and provide an estimation of uncorrected refractive errors in school-aged children,conducted by optometry students as a community ***:The study was *** 3343 participants were included in the *** initial examination involved assessing the uncorrected distance visual acuity(UDVA)and visual acuity(VA)while using a+2.00 D *** inclusion criteria for a subsequent comprehensive cycloplegic eye examination,performed by an optometrist,were as follows:a UDVAcimal(0.20 logMAR)and/or a VA with+2.00 D≥0.8 decimal(0.96 logMAR).RESULTS:The sample had a mean age of 10.92±2.13y(range 4 to 17y),and 51.3%of the children were female(n=1715).The majority of the children(89.7%)fell within the age range of 8 to *** the ethnic groups,the highest representation was from the Luhya group(60.6%)followed by Luo(20.4%).Mean logMAR UDVA choosing the best eye for each student was 0.29±0.17(range 1.70 to 0.22).Out of the total,246 participants(7.4%)had a full eye *** estimated prevalence of myopia(defined as spherical equivalent≤-0.5 D)was found to be 1.45%of the total *** around 0.18%of the total sample had hyperopia value exceeding+1.75 *** astigmatism(cilce was 1.26%of the total *** our cases of VI,76.2%could be attributed to uncorrected refractive *** was detected in 0.66%(22/3343)of the screened *** was no statistically significant correlation observed between age or gender and refractive ***:The primary cause of VI is determined to be uncorrected refractive errors,with myopia being the most prevalent refractive error *** findings underscore the significance of early identification and correction of refractive errors in school-aged children as a means to alleviate the impact of VI.

关键词： visual impairment refractive errors myopia amblyopia sustainable development goals

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Spreadability of powders for additive manufacturing: A critical review of metrics and characterisation methods

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PARTIcUOLOGY 2024年第10期93卷 211-234页

作者： Talebi, Fatemeh A. Haydari, Zobaideh Salehi, Hamid Mehrabi, Mozhdeh Gardy, Jabbar Bradley, Mike Bayly, andrew E. Hassanpour, Ali Univ Leeds Sch Chem & Proc Engn Leeds LS2 9JT England Univ Greenwich Sch Engn Greenwich ME4 4TB England cormica Ltd Listerhills Sci PkCampus Rd Bradford BD7 1HR England

Powder bed fusion methods of additive manufacturing (AM) require consistent, reproducible, and uniform layers of powder for the reliable production of high-quality parts, where properties of powder are central to achieving this. Among these properties, powder flowability and spreadability play critical roles in determining the quality of these powder layers. While extensive research has been conducted on powder flow and spreading behaviour, and on their characterisation, there is little critical comparison and review of these terms in the context of AM. Such a review is necessary to further develop and enhance our comprehension of spreading dynamics and its relation to powder properties in AM systems. This review paper aims to build a coherent understanding of the correlation between powder characteristics and spreading in powder based additive manufacturing and its impact on manufactured parts. It highlights the current progress in comprehending spreading dynamics, the influence of powder characteristics, environmental conditions, spreading system, and the development of testing tools to assess powder spreadability. Furthermore, the paper critically discusses the challenge of finding appropriate quantitative metrics and recent advances in the use of standardised methods for evaluating powder spreadability. (c) 2024 chinese Society of Particuology and Institute of Process Engineering, chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the cc BY license (http:// ***/licenses/by/4.0/).

关键词： Powder spreading Powder flowability Powder properties Quality of layer and final products DIScRETE ELEMENT SIMULATION PARTIcLE-SIZE DISTRIBUTION SPREADING PROcESS FLOW PROPERTIES NUMERIcAL-SIMULATION DENSITY BULK FLOWABILITY SEGREGATION BEHAVIOR

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Implementation of Fuzzy Logic control into an Equivalent Minimization Strategy for Adaptive Energy Management of A Parallel Hybrid Electric Vehicle

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Journal of Transportation Technologies 2024年第1期14卷 88-118页

作者： Jared A. Diethorn andrew c. Nix Mario G. Perhinschi W. Scott Wayne Department of Mechanical and Aerospace Engineering West Virginia University Morgantown WV USA

As government agencies continue to tighten emissions regulations due to the continued increase in greenhouse gas production, automotive industries are seeking to produce increasingly efficient vehicle technology. Hybrid electric vehicles (HEVs) have been introduced to mitigate problems while improving fuel economy. HEVs have led to the demand of creating more advanced controls software to consider multiple components for propulsive power in a vehicle. A large section in the software development process is the implementation of an optimal energy management strategy meant to improve the overall fuel efficiency of the vehicle. Optimal strategies can be implemented when driving conditions are known a prior. The Equivalent consumption Minimization Strategy (EcMS) is an optimal control strategy that uses an equivalence factor to equate electrical to mechanical power when performing torque split determination between the internal combustion engine and electric motor for propulsive and regenerative torque. This equivalence factor is determined from offline vehicle simulations using a sensitivity analysis to provide optimal fuel economy results while maintaining predetermined high voltage battery state of charge (SOc) constraints. When the control hierarchy is modified or different driving styles are applied, the analysis must be redone to update the equivalence factor. The goal of this work is to implement a fuzzy logic controller that dynamically updates the equivalence factor to improve fuel economy, maintain a strict charge sustaining window of operation for the high voltage battery, and reduce computational time required during algorithm development. The adaptive algorithm is validated against global optimum fuel economy and charge sustaining results from a sensitivity analysis performed for multiple drive cycles. Results show a maximum fuel economy improvement of 9.82% when using a mild driving style and a 95% success rate when maintaining an ending SOc within 5% of th

关键词： Hybrid Electric Vehicle Fuzzy Logic Adaptive control charge Sustainability

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Estimation of Peanut Maturity Using color Image Analysis

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American Journal of Plant Sciences 2024年第8期15卷 617-635页

作者： Wei-Zhen Liang Kendall R. Kirk James S. Thomas andrew c. Warner Department of Biological Systems Engineering University of Nebraska-Lincoln Lincoln NE USA Panhandle Research and Extension center University of Nebraska-Lincoln Scottsbluff NE USA Department of Plant Environmental Science Clemson University Clemson SC USA Edisto Research and Education center Clemson University Blackville SC USA University of Georgia-Athens cooperative Extension Athens GA USA

Peanuts pods grow underground and mature unevenly, resulting that choosing the correct time to harvest is more complicated than other crops. Pod maturity can be determined by blasting with a pressure washer to remove outer skin of the pod (exocarp) to expose the color of the middle layer (mesocarp). The mesocarp color changes with maturity from white to yellow, orange, brown and finally black. The sum of percentage from orange, brown, and black mesocarp (OBB) color and black color (BL) represents the kernels that are mature enough to harvest. The goal of this research is to identify methodologies to estimate OBB and BL of the pods using RGB images taken in the field and validate the proposed model using other pod images. The Mahalanobis distance classification method was used to process sets of images and calculate pod area (number of pixels) corresponding to two classes (mesocarp and background) with nine different color groups. The results showed a performance of 94% effectiveness for mesocarp using Mahalanobis distance classification. Statistical regression for OBB and BL was developed based on 315 images of peanut pods taken from the field. The R2 and root mean square error of predicted and actual OBB were 0.93 and 4.1%, respectively. The R2 and root mean square error of predicted and actual BL were 0.88 and 1.8%, respectively. The validation of OBB using other images provided reasonable estimation (R2 = 0.98 and RMSE = 2.73%). This study introduces a novel, cost-effective, and non-destructive method for estimating peanut maturity using RGB imagery and Mahalanobis distance classification in the field. This innovative approach addresses the limitations of traditional methods and offers a robust alternative for real-time maturity assessment.

关键词： Peanut Maturity Mesocarp Exocarp Mahalanobis Distance Statistical Regression

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DeepRice: A deep learning and deep feature based classification of Rice leaf disease subtypes

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ARTIFIcIAL INTELLIGENcE IN AGRIcULTURE 2024年第1期11卷 34-49页

作者： Ritharson, P. Isaac Raimond, Kumudha Mary, X. Anitha Robert, Jennifer Eunice andrew, J. Karunya Inst Technol & Sci Dept CSE Coimbatore Tamilnadu India Karunya Inst Technol & Sci Dept Robot Engn Coimbatore India Manipal Acad Higher Educ Manipal Inst Technol Dept Mechatron Engn Manipal 576104 Karnataka India Manipal Acad Higher Educ Manipal Inst Technol Dept Comp Sci & Engn Manipal 576104 Karnataka India

Rice stands as a crucial staple food globally, with its enduring sustainability hinging on the prompt detection of rice leaf diseases. Hence, efficiently detecting diseases when they have already occurred holds paramount importance for solving the cost of manual visual identification and chemical testing. In the recent past, the identification of leaf pathologies in crops predominantly relies on manual methods using specialized equipment, which proves to be time-consuming and inefficient. This study offers a remedy by harnessing Deep Learning (DL) and transfer learning techniques to accurately identify and classify rice leaf diseases. A comprehensive dataset comprising 5932 self-generated images of rice leaves was assembled along with the benchmark datasets, categorized into 9 classes irrespective of the extent of disease spread across the leaves. These classes encompass diverse states including healthy leaves, mild and severe blight, mild and severe tungro, mild and severe blast, as well as mild and severe brown spot. Following meticulous manual labelling and dataset segmentation, which was validated by horticulture experts, data augmentation strategies were implemented to amplify the number of images. The datasets were subjected to evaluation using the proposed tailored convolutional Neural Networks models. Their performance are scrutinized in conjunction with alternative transfer learning approaches like VGG16, Xception, ResNet50, DenseNet121, Inception ResnetV2, and Inception V3. The effectiveness of the proposed custom VGG16 model was gauged by its capacity to generalize to unseen images, yielding an exceptional accuracy of 99.94%, surpassing the benchmarks set by existing state-of-the-art models. Further, the layer wise feature extraction is also visualized as the interpretable AI. (c) 2023 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi communications co., Ltd. This is an open access article under the cc BY-Nc-ND license (http://creativeco

关键词： Rice leaf disease Deep learning cNN crop yield Agriculture Food security IDENTIFIcATION

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Light sheet microscope scanning of biointegrated microlasers for localized refractive index sensing

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Photonics Research 2024年第8期12卷 1673-1680页

作者： ROSS c.cOWIE MARcEL ScHUBERT SUPA School of Physics and AstronomyUniversity of St AndrewsSt AndrewsUK Humboldt centre for Nano and Biophotonics Department of ChemistryUniversity of CologneCologneGermany

Whispering gallery mode(WGM)microlasers are highly sensitive to localized refractive index changes allowing to link their emission spectrum to various chemical,mechanical,or physical *** recently found applications in biological studies within single cells,in three-dimensional samples such as multicellular spheroids,or in ***,detailed studies of biological samples also need to account for the structural heterogeneity of tissues and live animals,therefore requiring a combination of high-resolution microscopy and laser ***,we design and construct a light sheet fluorescence microscope with a coupled spectrometer for use in microlaser studies for combined high-resolution,high-speed imaging and WGM spectral *** light sheet illumination profile and the decoupled geometry of excitation and emission hereby directly affect the lasing and sensing properties,mainly through geometric constraints and by light coupling *** demonstrate the basic working principle of microlaser spectroscopy under light sheet excitation and measure the absolute refractive index within agarose and in zebrafish tail muscle *** further analyze the light coupling conditions that lead to the occurrence of two separate oscillation *** so-called cross modes can be scanned around the entire microlaser surface,which allows to estimate a surface-averaged refractive index profile of the microlaser environment.

关键词： refractive index excitation

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A toast to a zebrafish germ cell induction cocktail

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Science china(Life Sciences) 2024年第6期67卷 1314-1315页

作者： Mary c.Mullins Department of cell and Developmental Biology University of Pennsylvania Perelman School of MedicinePhiladelphia 19104USA

The zebrafish field is ringing in the new year with a publication from Yonghua Sun's laboratory(Wang et al.,2023)of a cocktail of germline factors that can induce all cells of the zebrafish embryo into primordial germ cells(PGcs)at phenomenal *** major advance is not only of great interest to germ cell biologists,but it has important applications to the entire zebrafish field,as shown in Wang et al.(2023).

关键词： fish zebra field

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chronic effects of stretching on range of motion with consideration of potential moderating variables:A systematic review with meta-analysis

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Journal of Sport and Health Science 2024年第2期13卷 186-194页

作者： Andreas Konrad Shahab Alizadeh Abdolhamid Daneshjoo Saman Hadjizadeh Anvar andrew Graham Ali Zahiri Reza Goudini chris Edwards carina Scharf David George Behm Institute of Human Movement Science Sport and HealthGraz UniversityGraz A-8010Austria School of Human Kinetics and Recreation Memorial University of NewfoundlandSt.John’sNL A1C 5S7Canada Department of Sport Injuries and corrective Exercises Faculty of Sport SciencesShahid Bahonar University of KermanKerman 76169-13439Iran

Background:It is well known that stretch training can induce prolonged increases in joint range of motion(ROM).However,to date more information is needed regarding which training variables might have greater influence on improvements in ***,the purpose of this metaanalysis was to investigate the effects of stretch training on ROM in healthy participants by considering potential moderating variables,such as stretching technique,intensity,duration,frequency,and muscles stretched,as well as sex-specific,age-specific,and/or trained state-specific adaptations to stretch ***:We searched through PubMed,Scopus,Web of Science,and SportDiscus to find eligible studies and,finally,assessed the results from 77 studies and 186 effect sizes by applying a random-effect ***,by applying a mixed-effect model,we performed the respective subgroup *** find potential relationships between stretch duration or age and effect sizes,we performed a ***:We found a significant overall effect,indicating that stretch training can increase ROM with a moderate effect compared to the controls(effect size=-1.002;Z=-12.074;95%confidence interval:-1.165 to-0.840;pcant difference between the stretching techniques(p=0.01)indicating that proprioceptive neuromuscular facilitation and static stretching produced greater ROM than did ballistic/dynamic ***,there was a significant effect between the sexes(p=0.04),indicating that females showed higher gains in ROM compared to ***,further moderating analysis showed no significant relation or ***:When the goal is to maximize ROM in the long term,proprioceptive neuromuscular facilitation or static stretching,rather than ballistic/dynamic stretching,should be *** to consider in future research as well as sports practice is that neither volume,intensity,nor frequency of stretching were

关键词： Flexibility Long-term stretching Stretch training

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Performance of evolutionary optimized machine learning for modeling total organic carbon in core samples of shale gas fields

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Petroleum 2024年第1期10卷 150-164页

作者： Leonardo Goliatt c.M.Saporetti L.c.Oliveira E.Pereira Department of computational and Applied Mechanics Federal University of Juiz de Fora Department of computational Modeling Polytechnic Institute Rio de Janeiro State University Petrobras Department of Stratigraphy and Paleontology Rio de Janeiro State University

Rock samples' TOc content is the best indicator of the organic matter in source rocks. The origin rock samples' analysis is used to calculate it manually by specialists. This method requires time and resources because it relies on samples from many well intervals in source rocks. Therefore, research has been done to aid this effort. Machine learning algorithms can estimate total organic carbon instead of well logs and stratigraphic studies. In light of these efforts, the current work present a study on automating the total organic carbon estimation using machine learning approaches improved by an evolutionary methodology to give the model flexibility and precision. Genetic algorithms, differential evolution, particle swarm optimization, grey wolf optimization, artificial bee colony, and evolution strategies were used to improve machine learning models to predict TOc. The six metaheuristics were integrated into four machine learning methods: extreme learning machine, elastic net linear model, linear support vector regression, and multivariate adaptive regression splines. core samples from the YuDong-Nan shale gas field, located in the Sichuan basin, were used to evaluate the hybrid strategy. The findings show that combining machine learning models with an evolutionary algorithms in a hybrid fashion produce flexible models that accurately predict TOc. The results show that, independent of the metaheuristic used to guide the model selection, optimized extreme learning machines attained the best performance scores according to six metrics. Such hybrid models can be used in exploratory geological research,particularly for unconventional oil and gas resources.

关键词： Total organic carbon Hybrid models Automated machine learning Evolutionary algorithms Geology

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Remodeling Tumor Immune Microenvironment by Using Polymer-Lipid-Manganese Dioxide Nanoparticles with Radiation Therapy to Boost Immune Response of castration-Resistant Prostate cancer

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Research 2024年第3期2023卷 83-96页

作者： Abdulmottaleb E.Zetrini HoYin Lip Azhar Z.Abbasi Ibrahim Alradwan Taksim Ahmed chunsheng He Jeffrey T.Henderson andrew M.Rauth Xiao Yu Wu Advanced Pharmaceutics and Drug Delivery Laboratory Leslie Dan Faculty of PharmacyUniversity of TorontoM5S 3M2TorontoONCanada. Departments of Medical Biophysics and Radiation Oncology University of TorontoM5G 1L7TorontoONCanada.

Despite substantial progress in the treatment of castration-resistant prostate cancer (cRPc), including radiation therapy and immunotherapy alone or in combination, the response to treatment remains poor due to the hypoxic and immunosuppressive nature of the tumor microenvironment. Herein, we exploited the bioreactivity of novel polymer–lipid manganese dioxide nanoparticles (PLMDs) to remodel the tumor immune microenvironment (TIME) by increasing the local oxygen levels and extracellular pH and enhancing radiation-induced immunogenic cell death. This study demonstrated that PLMD treatment sensitized hypoxic human and murine cRPc cells to radiation, significantly increasing radiation-induced DNA double-strand breaks and ultimately cell death, which enhanced the secretion of damage-associated molecular patterns, attributable to the induction of autophagy and endoplasmic reticulum stress. Reoxygenation via PLMDs also polarized hypoxic murine RAW264.7 macrophages toward the M1 phenotype, enhancing tumor necrosis factor alpha release, and thus reducing the viability of murine cRPc TRAMP-c2 cells. In a syngeneic TRAMP-c2 tumor model, intravenous injection of PLMDs suppressed, while radiation alone enhanced recruitment of regulatory T cells and myeloid-derived suppressor cells. Pretreatment with PLMDs followed by radiation down-regulated programmed death-ligand 1 and promoted the infiltration of antitumor cD8+ T cells and M1 macrophages to tumor sites. Taken together, TIME modulation by PLMDs plus radiation profoundly delayed tumor growth and prolonged median survival compared with radiation alone. These results suggest that PLMDs plus radiation is a promising treatment modality for improving therapeutic efficacy in radioresistant and immunosuppressive solid tumors.

关键词： RAW264.7 alone treatment

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