bluuebunny/crossref_metadata_2025 huggingface dataset:
Constructing stable lithium metal anodes using a lithium adsorbent with a high Mn3+/Mn4+ ratio
Authors: Zhao Yue , Liu Ziqiang , Li Zhendong , Peng Zhe , Yao Xiayin
Published: September 2022

Lithium (Li) metal batteries (LMBs) have emerged as the most prospective candidates for post-Li-ion batteries. However, the practical deployment of LMBs is frustrated by the notorious Li dendrite growth on hostless Li metal anodes. Herein, a protonated Li manganese (Mn) oxide with a high Mn3+/Mn4+ ratio is used as a Li adsorbent for constructing highly stable Li metal anodes. In addition to the Mn3+ sites with high Li affinity that afford an ultralow Li nucleation overpotential, the decrease in the average Mnn+ oxidation state also induces a disordered adsorbent structure via the Jahn-Teller effect, resulting in improved Li transfer kinetics with a significantly reduced Li electroplating overpotential. Based on the mutually improved Li diffusion and adsorption kinetics, the Li adsorbent is used as a versatile host to enable dendrite-free and stable Li metal anodes in LMBs. Consequently, a modified Li||LiNi0.8Mn0.1Co0.1O2 (NMC811) coin cell with a high NMC811 loading of 4.3 mAh cm-2 delivers a high Coulombic efficiency of 99.85% over 200 cycles and the modified Li||NMC811 pouch cell also achieves a remarkable improvement in electrochemical performance. This work demonstrates a novel approach for the preparation of highly efficient Li protection structures for safe LMBs with long lifespans.
Pre-Treatment Hemoglobin Concentration and Absolute Monocyte Count as Independent Prognostic Factors for Survival in Localized or Locally Advanced Prostate Cancer Patients undergoing Radiotherapy
Authors: Magrowski Łukasz , Masri Oliwia , Ciepał Jakub , Depowska Gabriela , Nowicka Zuzanna , Stando Rafał , Chimiak Krystyna , Bylica Gabriela , Czapla Barbara , Masri Małgorzata , Cichur Franciszek , Jabłońska Iwona , Gmerek Marta , Wojcieszek Piotr , Krzysztofiak Tomasz , Sadowski Jacek , Suwiński Rafał , Rajwa Paweł , Moll Matthias , Goldner Gregor , Majewski Wojciech , Miszczyk Marcin
Published: September 2022

The prognostic value of inflammatory indices such as absolute monocyte count (AMC) has been a subject of interest in recent prostate cancer (PCa) literature, while hemoglobin concentration (HGB) has been recognized as a survival factor in castration-resistant metastatic prostate cancer, but its value remains unclear in localized disease. The aim of this study was to test the prognostic value of these two simple and inexpensive biomarkers for survival based on a cohort of 1016 patients treated with primary radiotherapy and androgen deprivation therapy for localized or locally advanced intermediate- or high-risk PCa. Complete survival data was available for all cases based on the National Cancer Registry with a median observation time of 120 months (IQR 80.9-144.7). Missing blood test data were supplemented using the Nearest Neighbor Imputation, and the Cox proportional hazards regression model was used for analysis. The median age was 68.8 years (IQR 63.3-73.5). The five-year overall survival was 82.8%, and 508 patients were alive at the time of analysis. The median time between blood tests and the first day of radiotherapy was 6 days (IQR 0-19). HGB (p = 0.009) and AMC (p = 0.003) were independent prognostic factors for survival, along with age, ISUP Grade Group, clinical T stage and maximum PSA concentration. The study demonstrated that HGB and AMC can be useful biomarkers for overall survival in patients treated with radiotherapy for localized intermediate- or high-risk PCa.
Modeling Green Energy Consumption and Natural Resources Rents Impacts on Economic Growth in Africa: An Analysis from the Dynamic Panel ARDL Models and the Feasible Generalized Least Squares Estimator
Authors: Mumuni Sulemana , Mwimba Thomas
Published: September 2022

The concept of green energy is now at the forefront of development discourse, with the United Nations Sustainable Development Goals (SDGs) 7, 11, and 12 all aimed at promoting green energy consumption to combat the three planetary crises: climate change, biodiversity loss, and pollution. Similarly, issues regarding Africa’s natural resource curse have caused a stir in the growth and development literature for some time now and there is no sign that it will die out. This study, the first of its kind, simultaneously assesses the impact of green energy consumption and Africa’s natural resources rents on economic growth by applying the Feasible Generalized Least Square (FGLS) estimator and the dynamic panel models of the Pooled Mean Group (PMG) and Mean Group (MG) estimators on data from 1990 to 2020 for 24 selected African countries. The results show that green energy consumption has a short-run growth-limiting effect and a long-run growth-enhancing effect in Africa. The study also found evidence of the natural resource curse phenomenon in Africa. The study, therefore, calls for the advancement and usage of green energy for both domestic and industrial production in Africa. The study further calls for a revamp in the global tax policy to curb illicit financial activities and strengthening institutional quality for transparency and accountability in the entire value chain of natural resource management in Africa.
Kinetic Theory and Memory Effects of Homogeneous Inelastic Granular Gases Under Nonlinear Drag
Authors: Santos Andrés , Megías Alberto
Published: September 2022

We study in this work a dilute granular gas immersed in a thermal bath made of smaller particles with nonnegligible masses as compared with the granular ones. The kinetic theory for this system is developed and described by an Enskog--Fokker--Planck equation for the one-particle velocity distribution function. Granular particles are assumed to have inelastic and hard interactions, losing energy in collisions as accounted by a constant coefficient of normal restitution. The interaction with the thermal bath is based on a nonlinear drag force plus a white-noise stochastic force. To get explicit results of the temperature aging and steady states, Maxwellian and first Sonine approximations are developed. The latter takes into account the coupling of the excess kurtosis with the temperature. Theoretical predictions are compared with direct simulation Monte Carlo and event-driven molecular dynamics simulations. While good results for the granular temperature are obtained from the Maxwellian approximation, a much better agreement, especially as inelasticity and drag nonlinearity increase, is found when using the first Sonine approximation. The latter approximation is, additionally, crucial to account for memory effects like Mpemba and Kovacs-like ones.
Applicability of Asymmetric Specimens for Residual Stress Evaluation in Fiber Metal Laminates
Authors: Wiedemann Johannes , Schmidt Jan-Uwe R. , Hühne Christian
Published: September 2022

Residual stresses in fiber metal laminates (FML) inevitably develop during the manufacturing process. The main contributor to these stresses is the difference in the coefficients of thermal expansion (CTE) between fibers and metal in combination with high process temperatures. To quantify these stresses, the use of specimens with an asymmetric layup is an easily adaptable method. The curvature that develops after the manufacturing of flat laminates with an asymmetrical layer stack is a measure of the level of residual stresses evolving during cure. However, the accuracy of the curvature evaluation is highly dependent on specimen design and other influencing parameters. In this work a large set of FML specimens is investigated to identify relevant influencing parameters and derive conclusions about specimen design and evaluation techniques. For certain layups and process parameters, there is a good correlation between the curvature and the stress-free temperature, which is further covered by analytical solutions for bimetals. This correlation is the basis to transfer curvature into a stress-free temperature that can consequently be used for the quantification of residual stress levels in more complex FMLs. The transfer is validated by in-situ strain measurements during cure using a strain gage technique. Based on the results, the application of asymmetric specimens for residual stress characterization in more complex laminates is presented in the form of a workflow.
Technical and Economic Viability of Distributed Recycling of Low-density Polyethylene Water Sachets into Waste Composite Pavement Blocks
Authors: Tsala-Mbala Celestin , Hayibo Koami Soulemane , Meyer Theresa K. , Couao-Zotti Nadine , Cairns Paul , Pearce Joshua M
Published: September 2022

In many developing countries, plastic waste management is left to citizens. This usually results in hazardous landfilling or open-air burning, leading to emissions that are harmful to human health and the environment. An easy, profitable, and clean method of processing and transforming the waste into value is required. In this context, this study provides an open-source methodology to transform low-density polyethylene drinking water sachets, into pavement blocks by using a streamlined do-it-yourself approach that requires only modest capital. Two different materials, sand, and ashes are evaluated as additives in plastic composites and the mechanical strength of the resulting blocks are tested for different proportion mix of plastic, sand, and ash. The best composite had an elastic modulus of 169MPa, a compressive strength of 29MPa, and a water absorptivity of 2.2%. The composite pavers can be sold at 100% profit while employing workers at 1.5X the minimum wage. In the West African region, this technology has the potential to produce 19 million pavement tiles from 28,000 tons of plastic water sachets annually in Ghana, Nigeria, and Liberia. This can contribute to waste management in the region while generating a gross revenue of 2.85 billion XOF (4.33 million USD).
ANN Controller Design and Comparison with Other Equivalent Controllers for Low Cost Sustainable and Precise IndoorLighting Design Using Simultaneous Dual Control to Adjust Artificial Lighting and Daylight Harvesting
Authors: M.A.S. Mahmoud Muhammad
Published: September 2022

This article is a continuity of prevouse two reserch in daylight harvastion control that were deigned using classical control apoproach and then fuzzy logic technique, In this article ANN controller is designed and its response is compared with the performance of the other two controllers. Detailed compression for the different error type is illustrated, however, the results show that the three controller operate with satisfactory accuracy.
Pemberdayaan Ibu-ibu PKK Di Kelurahan Tawang Rejo, Wonogiri dengan Pelatihan Pembuatan nugget dan sosis Tinggi Serat
Authors: Yanti Yuli , Riyanto Joko , Dewanti Ratih , Cahyadi Muhammad , Wati Ari Kusuma , Pawestri Wari
Published: September 2022

Empowerment of PKK Group Village in Tawangrejo Wonogiri by Training Making Nugget and Sausage Contains Fiber. This community service aimed to increase the knowledge of PKK mothers in Tawangrejo village about processing livestock products, especially nuggets and sausages rich in fiber which are healthy and potential to increase the financial income. The service has been carried out in two groups of PKK women, Tawang Rejo sub-district, Jatipurno District, Wonogiri Regency. The service has been held on June 19, 2021. The method used is training and direct practice. The first activity is to provide a questionnaire to measure the level of initial knowledge of respondents about livestock products and how to process them. Next is training on livestock product processing technology and the practice of making livestock products into healthy functional foods because they are rich in fiber and vitamins. The third activity is giving another questionnaire to measure whether the materials and practices presented have succeeded in increasing the knowledge of the respondents. The ingredients used are chicken, broccoli, moringa leaves, corn and peanuts. From this activity, it was found that prior to the activity, knowledge of processing livestock products was only limited to meatballs, partners had never made their own nuggets and sausages. This is because partners do not yet know how to make it. After the extension and practice activities, respondents' knowledge about livestock products and processing methods increased. As much as 79% knowledge of making nuggets increased, while sausage making increased by 100%. As many as 100% of respondents have plans to start a business from processing livestock products, but only 26.4% of respondents will start a business as soon as possible. Partners obtain equipment in the form of an electric meat grinder and a vacuum machine. This service activity is able to increase the knowledge of partners about processing livestock products and open up business opportunities for partners.
A High-Precision Power Line Recognition and Location Method Based on Structured-Light Binocular Vision
Authors: Jian Xu , Li Jinbin , Chen Xin , Wang Xing-Ao , Chen Jun , Wu Chuanqi ,   Electric Power Research Institute, State Grid Hubei Electric Power Co., Ltd. No.227 Xudong Street, Hongshan District, Wuhan 430077, China,   School of Automation, China University of Geosciences No.388 Lumo Road, Hongshan District, Wuhan 430074, China,   Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems No.388 Lumo Road, Hongshan District, Wuhan 430074, China
Published: September 2022

To complete the wiring operation of the main transmission line stripped of its insulating skin in a live power distribution system, a structured-light binocular vision method is utilized to identify and locate the line. First, aiming at the interference of the background information, a depth threshold segmentation method is used to filter the background area. Second, a mean filtering method is proposed to filter out the mismatch noise of a binocular vision camera in an outdoor environment. The Canny algorithm is then utilized to extract the contour, the central axis of the main transmission line is fitted, and the difference in the neighborhood pixel value is used to recognize the stripping area. Finally, the spatial equation and attitude of the central axis of the fitting transmission line are obtained along with the central coordinates of the stripping area, guiding the robot to carry out the wiring.
Extreme Gradient Boosting for Surface Electromyography Classification on Time-Domain Features
Authors: Zhao Juan , She Jinhua , Wang Dianhong , Wang Feng ,   School of Automation, China University of Geosciences No.388 Lumo Road, Hongshan, Wuhan 430074, China,   Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074, China,   Engineering Research Center of Intelligent Technology for Geo-Exploration, Ministry of Education Wuhan 430074, China,   School of Engineering, Tokyo University of Technology 1404-1 Katakura, Hachioji 192-0982, Japan
Published: September 2022

Surface electromyography (sEMG) signals play an essential role in disease diagnosis and rehabilitation. This study applied a powerful machine learning algorithm called extreme gradient boosting (XGBoost) to classify sEMG signals acquired from muscles around the knee for distinguishing patients with knee osteoarthritis (KOA) from healthy subjects. First, to improve data quality, we preprocessed the data via interpolation and normalization. Next, to ensure the description integrity of model input, we extracted nine time-domain features based on the statistical characteristics of sEMG signals over time. Finally, we classified the samples using XGBoost and cross-validation (CV) and compared the results to those produced by the support vector machine (SVM) and the deep neural network (DNN). Experimental results illustrate that the presented method effectively improves classification performance. Moreover, compared with the SVM and the DNN, XGBoost has higher accuracy and better classification performance, which indicates its advantages in the classification of patients with KOA based on sEMG signals.
Dissociation and Recombination Processes in Lactose Monohydrate Detected by THz Time-Domain Spectroscopy
Authors: Alvi Muhammad Adnan , Zhang Zhaohui , Zhao Xiaoyan , Yu Yang , Zhang Tianyao , Aslam Jawad ,   School of Automation and Electrical Engineering, University of Science and Technology Beijing 30 Xueyuan Road, Haidian District, Beijing 100083, China,   School of Mechanical and Manufacturing Engineering, National University of Science and Technology H-12, Islamabad 44000, Pakistan
Published: September 2022

The terahertz (THz) region has much appeal for differentiating between hydrate systems and for physically characterizing pharmaceutical drug materials. The present study employs THz absorption spectroscopy to investigate the effect of heating on dehydration and hydration in α-lactose monohydrate. Distinctive THz absorption spectra were observed following various heating durations. The THz absorption spectra for α-lactose monohydrate and anhydrous α-lactose exhibit clear differences. Pure α-lactose monohydrate displays clear absorption peaks at 0.53, 1.05, 1.11, 1.33, and 1.56 THz. The complete dehydration of α-lactose monohydrate takes only 15 mins at 145°C (418 K). Moreover, the THz refractive index of α-lactose monohydrate decreases during dehydration. The dehydration of α-lactose monohydrate was also studied using Beer–Lambert law to compare THz absorption spectra as functions of the heating time. The absorption coefficient spectra recorded at 0.53 and 1.35 THz for α-lactose monohydrate after different dehydration times vary linearly with the remaining water content.
Analysis of State Transition of COVID-19 Positive Cases in Tokyo, Japan and its Application to Agent Simulation
Authors: Takama Yasufumi ,   Tokyo Metropolitan University 6-6 Asahigaoka, Hino-shi, Tokyo 191-0065, Japan
Published: September 2022

This paper estimates the state transition of COVID-19 positive cases by analyzing the data about confirmed positive cases in Tokyo, Japan. The prediction of the number of newly infected persons is one of the active research topics for the COVID-19 pandemic. Although such a prediction is important for recognizing the future risk of spreading infectious diseases, understanding the state transition after they are confirmed to be positive is also important for estimating the number of required ICUs, hotel rooms for isolation, etc. This paper classifies the state after being positive into “in hotel/home for isolation,” “in hospital with a mild state,” “in hospital with a severe state,” “recovered,” and “dead” and estimates the transition probabilities among those states from the data about confirmed positive cases in Tokyo, Japan. This paper shows the parameters estimated from different periods and discusses the difference considering the pandemic situation. An agent simulation using the estimated transition probabilities as its parameters is also proposed. The result of the simulation from August to November 2020 shows the predicted number of agents is close to the actual data. As one of the possible applications to the proposed agent simulation, this paper shows the simulation result from December 2020 to January 2021 under a hypothetical situation.
Estimation and Dynamic Evolution of Provincial Factor-Output Elasticity in China
Authors: Xu Zhengzhi , Li Xiujie , Zhang Chaojie , Zhu Jiani , Zhang Shangfeng , Lu Ke ,   Modern Educational Technology Center, Zhejiang University of Water Resources and Electric Power 583 Xuelin Street, Xiasha Education Park, Hangzhou, Zhejiang 310018, China,   College of Statistics and Mathematics, Zhejiang Gongshang University 18 Xuezheng Street, Xiasha Education Park, Hangzhou, Zhejiang 310018, China,   College of Information Engineering, Zhejiang University of Water Resources and Electric Power 583 Xuelin Street, Xiasha Education Park, Hangzhou, Zhejiang 310018, China
Published: September 2022

China is currently in a new phase of transition from high-speed growth to high-quality growth, and accurate estimation of element outputs is essential for the smooth progress of the transition. Using the back-fitting method, this study constructed a model of a spatiotemporal-varying elasticity production function to estimate the factor-output elasticity from 1993 to 2017 in 31 Chinese provinces. Nonparametric kernel density method was applied to describe the spatiotemporal evolution characteristics of factor-output elasticity. The results show that the factor-output elasticity of different provinces shows a nonlinear change trend over time and between regions. Overall, the elasticity of labor output shows a decreasing trend, the elasticity of capital output shows an increasing tendency, the eastern region has the lowest level of labor-output elasticity, but the highest level of capital-output elasticity. The western region has the highest level of labor-output elasticity but the lowest level of capital-output elasticity. On the whole, regions with higher resilience in labor output gradually shift towards the West, while capital shifts towards the East.
Object Detection and Segmentation Using Deeplabv3 Deep Neural Network for a Portable X-Ray Source Model
Authors: Rogelio Jayson P. , Dadios Elmer P. , Vicerra Ryan Ray P. , Bandala Argel A. ,   Department of Science and Technology, Metals Industry Research and Development Center General Santos Ave., Bicutan, Taguig 1631, Philippines,   Department of Electronics and Computer Engineering, De La Salle University 2401 Taft Avenue, Malate, Manila 1004, Philippines,   Department of Manufacturing Engineering and Management, De La Salle University 2401 Taft Avenue, Malate, Manila 1004, Philippines
Published: September 2022

The primary purpose of this research is to implement Deeplabv3 architecture’s deep neural network in detecting and segmenting portable X-ray source model parts such as body, handle, and aperture in the same color scheme scenario. Similarly, the aperture is smaller with lower resolution making deep convolutional neural networks more difficult to segment. As the input feature map diminishes as the net progresses, information about the aperture or the object on a smaller scale may be lost. It recommends using Deeplabv3 architecture to overcome this issue, as it is successful for semantic segmentation. Based on the experiment conducted, the average precision of the body, handle, and aperture of the portable X-ray source model are 91.75%, 20.41%, and 6.25%, respectively. Moreover, it indicates that detecting the “body” part has the highest average precision. In contrast, the detection of the “aperture” part has the lowest average precision. Likewise, the study found that using Deeplabv3 deep neural network architecture, detection, and segmentation of the portable X-ray source model was successful but needed improvement to increase the overall mean AP of 39.47%.
Low-Cost Underwater Camera: Design and Development
Authors: Dadios Elmer P. , Almero Vincent Jan , II Ronnie S. Concepcion , Vicerra Ryan Rhay P. , Bandala Argel A. , Sybingco Edwin ,   Department of Manufacturing Engineering and Management, De La Salle University (DLSU) 2401 Taft Avenue, Malate, Manila 1004, Philippines,   Center for Engineering and Sustainability Development Research, De La Salle University (DLSU) 2401 Taft Avenue, Malate, Manila 1004, Philippines,   Department of Electronics and Computer Engineering, De La Salle University (DLSU) 2401 Taft Avenue, Malate, Manila 1004, Philippines
Published: September 2022

The understanding of vision-based data acquisition and processing aids in developing predictive frameworks and decision support systems for efficient aquaculture monitoring and management. However, this emerging field is confronted by a lack of high-quality underwater visual data, whether from public or local setups and high cost of development. In this regard, an underwater camera that captures underwater images from an inland freshwater aquaculture setup was proposed. The components of the underwater camera system are primarily based on Raspberry Pi, an open-source computing platform. The underwater camera continuously provides a real-time video streaming link of underwater scenes, and the local processor periodically acquires and stores data from this link in the form of images. These data are stored locally and remotely. Based on the results of the developed low-cost underwater camera, it captures and differentiate fish region to its background before and after flushing as influenced by turbidity. Hence, the developed camera can be used for both aquarium and inland aquaculture pond setup for fish monitoring.
Effect of Fluid Viscosity and Fiber Length on the Performance of Fibrous Fluid in Horizontal Well Cleanout
Authors: Mendez Michael , Garcia Sergio Prada , Ahmed Ramadan , Karami Hamidreza , Nasser Mustafa , Hussein Ibnelwaleed A.
Published: September 2022

During drilling, completion, and intervention operations, solids can deposit in the wellbore. Innovative cleanout fluids reduce the problems associated with inadequate hole cleaning. Various methods have been developed to improve hole cleaning, but their effectiveness decreases as the wellbore inclination increases. One way to solve this issue is to add fibers to the drilling fluid and reduce the settling velocity of the solids to improve the fluid’s lifting capacity.

The purpose of this study is to evaluate the cleanout performance of fibrous fluids in horizontal wells using a large-scale flow loop. Thus, flow loop experiments were conducted to assess the impact of fiber on equilibrium bed height. The experiment measures equilibrium bed height and pressure loss in an eccentric annular test section. During the investigation, the flow rate and apparent viscosity of the fluid and fiber length were varied.

The results demonstrate the effectiveness of long fiber (length = 0.5 in.) in improving hole cleanout in horizontal wellbores. When a small amount (0.04% wt.) of long fiber was added, the cleanout performance of the high-viscosity fluid did not show a noticeable change. In contrast, the performance of the low-viscosity fluid improved. Even though adding fiber has minimal impact on the apparent viscosity of the fluids, the long fiber improved the cleaning performance of the low-viscosity fluid.

Hole cleaning is challenging in operations such as coiled tubing (CT) in which rotating the drillstring is impossible. Hence, this study focuses on cleanout operations in horizontal wellbores without drillstring rotation. The novelty of this work lies in demonstrating how the adjustment of fluid viscosity can positively impact the hole cleaning performance of fibrous fluids in the absence of pipe rotation. The study also presents a new approach to modeling the effects of solids bed irregularity on wellbore pressure loss and equivalent circulating density (ECD).
Organisational approaches to the use of extracorporeal cardiopulmonary resuscitation
for refractory out of hospital cardiac arrest: a narrative review
Authors: Nikolov Kalina , Ahl Eric , Wagner Henrik , Härdig Bjarne Madsen
Published: September 2022

Background: The objective of this narrative review was to provide an overview of how programmes around the world are organised regarding the use of extracorporeal cardiopulmonary resuscitation for refractory out of hospital cardiac arrest.
Methods: A systematic literature search was performed in PubMed, EMBASE, ClinicalTrials.gov, the EU Clinical Trials Register, and Cochrane Library. The main parameters assessed were article type, region- population-size, cost–benefit analyses, inclusion and exclusion criteria, procedure location, team composition and outcome parameters reported.
Results: Sixty-three articles were eligible for inclusion. One randomised trial had been published and 4 were ongoing. Among the 58 articles that reported data on organisational topics, 47 transported the patient to the hospital for cannulation, 10 initiated extracorporeal cardiopulmonary resuscitation on-scene and one did both. The organisations cover different populations sizes that ranged between 30,788–19,303,000 inhabitants. The most common inclusion criterion was a lower age limit of 18 years (in 86% articles), followed by an upper age limit (in 83% articles), but this varied (50 and 80 years). Other criteria were witnessed collapse (67%) and initial shockable rhythm (43%), asystole (3%), pulseless electrical activity (5%), pulmonary embolism (2%), and signs of life during cardio- pulmonary resuscitation (5%). The most common exclusion criterion was a Do-Not-Resuscitate order (38%) followed by existence of major comorbidities (36%). The extracorporeal cardiopulmonary resuscitation teams varied between 2–8 members and had various professions involved. Of the 44 studies reporting outcomes, 77% reported survival to hospital discharge. Outcome as one- (in 14%), 3- (in 5%) and 6-month survival (in 7%), Cerebral-Performance-Category-score of 1–2 was reported by 50% of the studies.
Conclusion: There is variation in regional size, team composition, inclusion and exclusion criteria and reported outcomes. These discrepancies make it difficult to determine how to use extracorporeal cardiopulmonary resuscitation in the most effective manner from the current publications. Despite an increasing amount of research published in the last few years, there remains a need for better coherence to inclusion/exclusion criteria and outcome reporting, the optimal team composition and location for the procedure.
Impact of Drought on Forest Cover Change in Yabelo Forest in Semi-arid Region of Ethiopia
Authors: Wolteji Bayisa Negasa , Gizawu Fayera , Gemeda Dessalegn Obsi
Published: September 2022

Drought is a key challenge of third world countries whose economies are based on agriculture. Also, lack of rainfall plays a major role in exacerbating climate change. Drought is resulting in a decline in vegetation greenness and plant mortality specifically in semi-arid region. In this study, satellite-based drought assessment was used to characterize drought, and its impact on forest in semi-arid region of Ethiopia. Drought severity and forest cover change were detected over the period between 2014, and 2022 using geographic information system and remote sensing techniques. Vegetation condition index (VCI) and normalized difference vegetation index (NDVI) are used to detect drought severity over the past decades. Results show that 2015, 2017, 2019and 2022 were the most drought years. The spatial forest covers is significantly decreased during severe drought years. Minimum dense forest was observed in 2017and 2019 over spatial extend of 0.80 ha and 124.6 ha, respectively during drought years. To evaluate how precipitation deficit affect forest function, simple linear regression is performed. Result of (R2 = 0.49 and P = 0.05) indicate that, nearly 50% of forest greenness is influenced by precipitation deficit. This study suggested that remote sensing indices are very crucial to characterize drought pattern at small “scale” particularly in assessment of drought impact on forest resource.
Investigating Potential Vulnerability of Critical Infrastructure and way forward – recommendations to enhance security and resilience
Authors: Melaku Henock Mulugeta
Published: September 2022

In this research, firstly critical infrastructures (CIs) that are found in Ethiopia are identified. Then, potential security vulnerabilities of these CIs are identified by performing strategic and tactical level risk and vulnerability assessments. To perform the stated assessments, questionnaires were prepared using different standards. Moreover, on-site interviews, existing document and literature reviews were conducted. By performing the above research methodologies, the security vulnerabilities of selected CIs were thoroughly investigated. Finally, factors that contribute to the security vulnerabilities are critically identified and way forward recommendations are given to fill the identified security gaps and vulnerabilities.
Validation of the HLS-EU-Q6 and HLS-EU-Q16 questionnaire of Portuguese version - a methodological study
Authors: Pedro Ana Rita , Raposo Beatriz , Luís Luís , Amaral Odete , Escoval Ana , Dias Sara Simões
Published: September 2022

Background
Health Literacy (HL) refers to the empowerment and competencies of individuals and the general population to navigate in the various areas of health care, to make decisions regarding their health in everyday life in an individual, family, or social context. Due to the dynamic process of health literacy, health professionals need to have a set of skills and real information that allow them to adapt to the changing landscape of people's literacy in order to empower them in the areas they need. To succeed, it is crucial to have the means to determine the health literacy level of the general population, in this case in the Portuguese context. Therefore, this study aims to validate the Portuguese version of HLS-EU-Q16 (HLS-EU-PT-Q16) and HLS-EU-Q6 (HLS-EU-PT-Q6) from the long form of HLS-EU-Q47 already validated for Portugal (HLS-EU-PT).
Methods
In order to analyse the results already obtained, a comparison was made with HLS-EU-PT index. Spearman correlation analysis was performed between the single items and scale scores. Cronbach’s alphas for all the indexes were calculated as a measure of internal consistency. For comparison associations between all the HL indexes - non-parametric test were calculated. The software used for the statistical analysis was SPSS (version 28.0).
Results
Cronbach’s alpha coefficient for HLS-EU-PT-Q16 internal consistency was 0.89 overall, and regarding HLS-EU-PT-Q6 the Cronbach’s alpha coefficient obtained was 0.777 overall. Indexes were not normally distributed, and Spearman correlation was computed. The results obtained in the correlation between G HL47 and G HL16 indexes (ρ = 0.949, p < 0.001) and the correlation between G HL6 and HLS-EU-PT-Q6 have a perfect correlation.
Conclusions
The HLS-EU-PT-Q16 and HLS-EU-PT-Q6 are concise and valid instruments to determine the health literacy level of the Portuguese population. However, the forms that show the smallest differences between the percentages of the levels of health literacy are the 47-item and the 16-item forms.
Analysis of macro and micronutrient contents and spatial distribution for assessment at regional-scale: Case study Vushtrria region (Kosovo)
Authors: Shehu Ilir
Published: September 2022

Soil fertility determines crop growth productivity and consequently affects quality and sustainability. Thirty composite samples were taken, most in intensive cultivation and some in uncultivated soil. For soil analysis, classic and instrumental methods were used. Micronutrients in soil were measured by the ICP-OES method. Assessing contents, relationships between macro and micronutrients, and spatial distribution, were used methods descriptive statistics, Pearson correlation, Arcgis pro map, clusters, and PCA analyses. The physicochemical properties and potassium levels reflect the balanced distribution. Nitrogen (N) and Phosphorus (P) were at depleted levels. The kriging interpolation patterns showed uniform distribution of macronutrients, small changes were presented in uncultivated soil. Iron (Fe) and copper (Cu) showed acceptable balances, Nickel (Ni), Molybdenum (Mo), and Zinc (Zn) showed increased values compared to the New Dutch list and SEPA, while Boron (B) and selenium (Se) were at low content. PCA analysis and Dendrograms reflected the grouping of variables in one component resulting in the same source. Correlation analysis displays significant relationships between the parameters which were related to the inorganic component of the soil. Is recommended to add fertilizers, and micronutrients for balancing based on good practices and continuous monitoring.
An Alternative Parameter Free Algorithm to DBSCAN Method by Using Data Point Positioning Analysis (DBSCAN-DPPA)
Authors: Mustapha S.M.F.D Syed
Published: September 2022

Density-based spatial clustering of applications with noise (DBSCAN) is a powerful unsupervised clustering method for its ability to manage noises and arbitrary cluster shapes without the need to pre-determine the total clusters. However, the performance of DBSCAN is dependable to right choice of its two initial parameters – MinPts and Eps. Much research had been done to overcome the challenges by reducing the dependencies of these two parameters or automatically determine the values. This paper will review some of these various techniques related to reducing the dependencies of two DBSCAN initial parameters and subsequently proposes the new algorithm called DBSCAN-DPPA which do not require the initial setting of the two parameters by using Data Point Positioning Analysis. The algorithm is simple as it does not need any parameters to be initially assigned manually as it performs analysis on the positions of data points to determine the 1-NN and Max-NN. The algorithm is applied on 13 benchmark datasets that have been applied in many clustering algorithms. The performance of the algorithm is visually compared with the three-dimensional graph plotting at various angles to prove the number of clusters. The results show that the modified DBSCAN-DPPA algorithms are comparable to the performance of the traditional DBSCAN algorithm such that it manages to detect arbitrary cluster shapes, identify the number of clusters and manage the data sets with noises.
The Effects of Source Doping Concentration and Doping Gradient on the ON-State Current of Si Nanowire TFETs
Authors: Liu Keng-Ming , Hsieh Yu-En
Published: September 2022

Tunnel field-effect transistor (TFET) has been considered one of the promising next-generation transistors due to its potentially limit-breaking low subthreshold swing and better immunity against the short-channel effects. However, the low ON-state current (ION) of TFETs has been a critical problem to be dealt with. In this work, we investigated the effects of the source doping concentration and the source doping gradient (SDG) on the ION of the n-type Si gate-all-around (GAA) nanowire (NW) TFETs by the Atlas device simulator. Unexpectedly, we found that increasing the source doping concentration does not necessarily improve the ION especially for the TFETs with large SDG. Besides, reducing the SDG indeed increases the ION, however, for the TFETs with low source doping concentration such as 1×1019 cm-3, the ION improvement by lessening SDG becomes insignificant.
Densification behaviour of laser powder bed fusion processed Ti6Al4V: Effects of customized heat treatment (CHT) and build direction
Authors: Pathania Akshay , Subramaniyan Anand Kumar , Kenchappa Nagesha Bommanahalli
Published: September 2022

The present work exploits the customized heat treatment (CHT) to study the porosity levels of Optical microscopy evaluates the porosity level and microstructure in different conditions. Further, the porosities are classified as inter-micropores (size < 10 µm) and super-micropores (size > 10 µm). Moreover, the XRD technique was used to analyse the different phases that arose during laser powder bed fusion (LPBF) and CHT. The CHT at elevated temperature (1050ºC) helps to reduce the overall porosity level by two times that of as-printed samples due to the sintering self-healing phenomenon. Interestingly, the super-micropores observed in as-printed samples are reduced via CHT, which is favourable for enhancing mechanical properties. Moreover, the refinement of microstructures into different phases after CHT has improved the densification behaviour. (i). Classification and quantifications of the porosities level of LPBF processed Ti6Al4V alloy under both directions due to CHT. (ii). The effect of CHT and its pore self-healing mechanism and microstructure refinement on LPBF processed Ti6Al4V alloy. (iii) This study reveals that the CHT technique can be beneficial in introducing isotropic microstructure and densifying the distinctive LPBF components.
Growing uncertainty in projected spring onset variability in the Northern Hemisphere
Authors: Li Xiaolu , Ault Toby , Evans Colin , Lehner Flavio , Carrillo Carlos , Donnelly Alison , Crimmins Theresa , Gallinat Amanda , Schwartz Mark
Published: September 2022

Plant phenology regulates the carbon cycle and land-atmosphere coupling. Currently, climate models often disagree with observations on the seasonal cycle of vegetation growth, partially due to how spring onset is measured and simulated. Here we use both thermal and leaf area index (LAI) based indicators to characterize spring onset in CMIP6 models. Although the historical timing varies considerably across models, most agree that spring has advanced in recent decades and will continue to arrive earlier with future warming. Across the Northern Hemisphere for the periods 1950–2014, 1981–2014, and 2015–2099, thermal-based indicators estimate spring advances of -0.7 ± 0.2, -1.4 ± 0.4, and − 2.4 ± 0.7 days/decade, while LAI-based indicators estimate − 0.4 ± 0.3, -0.1 ± 0.3, and − 1 ± 1.1 days/decade. Thereby, LAI-based indicators exhibit later spring and weaker trends toward earlier onset, leading to index-related uncertainty being as large or larger than model uncertainty for a given index. Reconciling index-related discrepancies is therefore critical for understanding future changes in spring onset.
Surveillance Strategy after Curative Resection for Oesophageal Squamous Cell Cancer Using the Hazard Function
Authors: Kanematsu Kyohei , Kudose Yozo , Utsunomiya Daichi , Kubo Kentaro , Fujii Yusuke , Kurita Daisuke , Ishiyama Koshiro , Oguma Junya , Daiko Hiroyuki
Published: September 2022

Background The optimal surveillance period and frequency after curative resection for oesophageal squamous cell carcinoma (OSCC) remain unclear, and current guidelines are mainly based on traditional Kaplan–Meier analyses of cumulative incidence rather than risk analysis. The aim of this study was to determine a suitable follow-up surveillance program following oesophagectomy for OSCC using the hazard function. Methods A total of 1187 patients who underwent curative resection for OSCC between 2000 and 2014 were retrospectively analyzed. The changes in the estimated hazard rates (HRs) of recurrence over time were analyzed according to tumour-node-metastasis stage. Results Four hundred seventy-eight (40.2%) patients experienced recurrence during the follow-up period (median, 116.5 months). The risk of recurrence peaked at 9.2 months after treatment (HR = 0.0219) and then decreased to half the peak value at 24 months post-surgery. The HRs for Stage I and II patients were low (< 0.007) post-treatment. The HR for Stage III patients peaked at 9.9 months (HR = 0.031) and the hazard curve declined to a plateau at 30 months. Furthermore, the HR peaked at 10.8 months (HR = 0.052) in Stage IV patients and then gradually declined from 50 months. Conclusions According to tumour-node-metastasis stage, changes in the HRs of postoperative recurrence in OSCC varied significantly. Intensive surveillance should be undertaken for 3 years in Stage III patients and for 4 years in Stage IV patients, followed by annual screening. For Stage I OSCC patients, a reduction in the surveillance intensity could be taken into consideration.
Predictability of fossil fuel CO2 from air quality emissions
Authors: Miyazaki Kazuyuki , Bowman Kevin
Published: September 2022

Anthropogenic emissions of long-lived greenhouse gases and short-lived air quality (AQ) pollutants drive climate change and impact human health. Quantifying the coevolution of these pollutants can provide insight into underlying anthropogenic processes enabling predictions of their emission trajectories. To that end, we classify the dynamics of historic emissions in terms of a modified Environmental Kuznets Curve (MEKC), which postulates the coevolution of fossil fuel (FFCO2) and NOx emissions as a function of macroeconomic development, and assess the predictability of FFCO2 given AQ emissions based upon a novel Kalman filter. For about the last two decades the MEKC broadly captures the distinct FFCO2/AQ dynamical regimes for countries including the US, China, and India. While the US trajectory plateaued, some developing countries have transitioned rapidly between these regimes by leveraging technological advances. We also show that a number of IPCC scenarios are well-represented by MEKC but differ from historic estimates in their timing and magnitude. Given these dynamics, we find the predictive skill of FFCO2 given NOx emissions constrained by satellite data is less than 2% error at one-year lags for many countries and less than 10% for 4-year lags. The results point to the important interplay between AQ and GHG emission processes at time scales relevant to international assessments, e.g., Global Stocktake. The proposed framework in conjunction with an increasing AQ and carbon satellite constellation could provide valuable guidance to near-term emission scenario development and evaluation.
Design of peptide inhibitors targeting β-catenin using generative deep learning and molecular dynamics simulations
Authors: Chen Sijie , Lin Tong , Basu Ruchira , Wang Shen , Luo Yichuan , Kara Levent , Pei Dehua , Cheng Xiaolin
Published: September 2022

Computational design of therapeutic peptides that enables fast exploration of a combinatorial number of amino acid possibilities has emerged as a popular strategy in antibiotics discovery but identifying peptide inhibitors targeting specific protein-protein interactions (PPIs) still faces significant challenges. Here, we present a new approach for de novo design of target-specific peptides, which combines a Gated Recurrent Unit (GRU) based variational autoencoder (VAE) with Rosetta
FlexPepDock for peptide sequence generation and potency assessment, followed by the refinement with all-atom molecular dynamics (MD) simulations. We have utilized the computational protocol to design eight peptide inhibitors specifically disrupting the interaction of β-catenin with TCF/LEF family transcription factors. Four of these peptide inhibitor candidates were synthesized and experimentally tested, of which two displayed enhanced binding affinities for β-catenin compared to the best-known peptide made of all natural amino acids. We also constructed a random peptide library of 710,000 unique peptides, and none of these peptides showed a higher binding affinity than our computationally designed peptides. Our study exemplifies the success of combining deep learning and structure-based modeling and simulation for target-specific peptide design. Besides the development of therapeutic
peptides targeting β-catenin/TCF, our approach should be transferable to other PPIs, such as p53/MDM2, Bcl-2/Bax, and CD40/CD40L.