How to Develop a Realist Evaluation to Evaluate the Effectiveness of Integrated Management of Childhood Illness Strategy in Community Care Sites in the Democratic Republic of Congo

Background: In sub-Saharan Africa, the DRC ranks among countries with high infant mortality. To solve this problem, the Health Ministry has set up a programme: the use of integrated management childhood illness (IMCI) in community care sites (CCSs) managed by non-health professional persons known as community health workers (CHW). This approach has not yet been integrated into the health pyramid. This is why we chose the Realist Evaluation Approach to evaluate the effectiveness of this programme on Universal Access to care for children under 5 years of age in the DRC. Methods/design: To conduct this exploratory study which is essentially a descriptive case study, we applied the principles of a realist evaluation by context—mechanisms—effects explained in the conceptual framework. The preliminary theory of the programme was elaborated by data collection through a literature review coupled with semi-structured interviews with key informants who were managers of the government programme and technical and financial partners of the programme. Results: IMCI has been evaluated and shown its positive contribution in the reduction of global children mortality. In the DRC, summaries of data collection through a literature review coupled with semi-structured interviews showed the same result. However, under criticism, based on the data collected during this exploratory study, it is promisingly apparent that this programme will achieve the objectives assigned to it through the preliminary theory of the programme. Conclusion: The literature review corroborated the effectiveness of the IMCI programme. The application of this programme in CCS with non-health professionals who are Community Health Workers has been shown to be effective in the DRC. Based on this reality, it was possible to define the basis for a realist evaluation of the effectiveness of the programme in CCS.

Constructing a data platform for surface defect management using a multidimensional database

Surface quality has been one of the key factors influencing the ongoing improvement of the quality of steel. Therefore,it is urgent to provide methods for efficient supervision of surface defects. This paper first expressed the main problems existing in defect management and then focused on constructing a data platform of surface defect management using a multidimensional database. Finally, some onqine applications of the platform at Baosteel were demonstrated. Results show that the constructed multidimensional database provides more structured defect data, and thus it is suitable for swift and multi-angle analysis of the defect data.

Concept of Integrated Waste Management as Recoverable Resources in Product Cycle

This paper presents a conceptual framework of integrated waste management which focuses on all stages of product life cycle. A mechanism of resource recovery motivating from waste in economic system （designers, producers, consumers, stakeholders in the field of disposal of the product） is suggested. The classification of institutional and economic instruments in the field of waste management as recoverable resources is developed. The author has proposed a scientific and methodical approach to the formation of an integrated waste management as recoverable resources, which is based on a set of methods of economic incentives at all stages of product life cycle and ensures the maximum possible and the environmentally safe management of wastes containing valuable resource components.

Design and Implementation of Agricultural Products Logistics Management System based on WebGIS

The system will be to build a complete logistics monitoring system based on WebGIS, using the development technology of the third party map which is popular at present, the client technology Ajax is introduced into the two map development platform based on WebGIS, draw lessons from the mature MapABC map service interface for API programming, establish the optimization model of distribution route with hard time windows, and studies the application of tabu search algorithm to solve the distribution path optimization model. At the same time, t;he system can realize vehicle abnormal alarm, shortest path planning and analysis of statistical query functions, can display the corresponding curves on the map that query be some statistical analysis results or a heat map by the user, get a more intuitive feel and better user experience.

Development Status and Reform Pattern of Ecotourism Management

Eco-tourism is the emerging form of tourism rapidly developing, but also a hot topic in the current tourism industry. 1999 is the Year of Ecotourism which China National Tourism Administration regulates. Global experts predict that eco-tourism heat will rise in the world of moving towards protected areas, close to nature as the theme. It is ecstatic that China＇ s tourism industry is facing a rare opportunity, but we must attach great importance to the problem of the recent and long-term harm caused by tourism to the environment. Especially now under the banner of eco-tourism, some people actually did do damage to the environment. Therefore, we must study on the true meaning of eco-tourism, with China＇ s reality, to formulate laws and regulations and management measures for eco-tourism. With these to protect our natural landscape and cultural heritage, we can make tourism a sustainable green industry.

Research on Management Innovation and Development for Railway Passenger Station Construction

Based on the general high-quality development requirements for railway construction in the new era,combined with the new concept of railway passenger stations of China State Railway Group Co.Ltd,namely"being well-connected,fully-integrated,environmeni-friendlypassenger-oriented,economically-efficient,culturally-rich,intelligent and convenient"and aiming at the construction of exemplary passenger station projects,this paper summarizes the construction experience in construction,decoration furnishing culture and art expression of railway passenger stations,proposes the working patterns of formulating the implementation plans of exemplary railway passenger station projects and the expert reviews in innovative way studies and forms 6 special-subject designs such as for colorshape,space,environment,art and culture,as wellas the specific design requirements for 13 key areas including waiting hall entrance and exit corridor;VIP room,etc.,and summarizes and puts forward the construction management system of railway passenger stations in the new era,so as to ensure the expected exemplary project quality of railway passenger stations.

Overall-effective Measures for Sustainable Water Resources Management in the Coastal Areas of Shandong Province, China——Case Study: the Huangshuihe River Catchment of Longkou City

In the coastal catchments of Shandong Province the water scarcity is aggravated due to saltwater intrusion, reducing the usability of water resources available. Such a situation calls for sustainable integrated water resources management (IWRM). The idea for the objectives and implementation of the IWRM are explained in this paper. The general objective of the planned project disscussed in the present study is to bring together German traditional expertise in water resources management and newer developments in the context of the European Water Framework Directive; the research efforts aim to relieve the desperate water scarcity situation in the costal area of Shandong Province.

A multi-scale modelling framework to guide management of plant invasions in a transboundary context

Background：Attention has recently been drawn to the issue of transboundary invasions,where species introduced and naturalized in one country cross international borders and become problematic in neighbouring countries.Robust modelling frameworks,able to identify the environmental drivers of invasion and forecast the current and future potential distribution of invasive species,are needed to study and manage invasions.Limitations due to the lack of species distribution and environmental data,or assumptions of modelling tools,often constrain the reliability of model predictions.Methods：We present a multiscale spatial modelling framework for transboundary invasions,incorporating robust modelling frameworks（Multimodel Inference and Ensemble Modelling） to overcome some of the limitations.The framework is illustrated using Hakea sericea Schrad.（Proteaceae）,a shrub or small tree native to Australia and invasive in several regions of the world,including the Iberian Peninsula.Two study scales were considered：regional scale（western Iberia,including mainland Portugal and Galicia） and local scale（northwest Portugal）.At the regional scale,the relative importance of environmental predictors sets was evaluated and ranked to determine the main general drivers for the species distribution,while the importance of each environmental predictor was assessed at the local scale.The potential distribution of H.sericea was spatially projected for both scale areas.Results：Model projections for western Iberia suggest that a large area is environmentally suitable in both Portugal and Spain.Climate and landscape composition sets were the most important determinants of this regional distribution of the species.Conversely,a geological predictor（schist lithology） was more important in explaining its local-scale distribution.Conclusions：After being introduced to Portugal,H.sericea has become a transboundary invader by expanding in parts of Galicia（Spain）.The fact that a larger area is predicted as environmentally suitable in Spain raises concerns regarding its potential continued expansion.This highlights the importance of transboundary cooperation in the early management of invasions.By reliably identifying drivers and providing spatial projections of invasion at multiple scales,this framework provides insights for the study and management of biological invasions,including the assessment of transboundary invasion risk.

The Impact of Internet of Things in Manufacturing Management

The study investigated the impact of the Internet of Things in manufacturing management. Specifically, the study examined how IoT implementation and management affect organizational efficiency in Camanov Ltd.;and to what extent IoT implementation contributes to the saving of cost and time of the organization. The research design is a survey. The population of this study consisted of all 141 staff of Camanov Ltd. Port Harcourt. Since the population is not large, the researcher conducted a census of all, and 126 staff completed a structured questionnaire. The two research questions were analyzed using simple percentages and all two hypotheses were tested using sample proportion statistics (Z test) at a 0.05 level of significance. The result showed that the Internet of Things has a significant impact on organizational efficiency in Camanov Ltd. (Z = 4.73);and that the Internet of Things significantly contributes toward saving cost and time of the organization Camanov Ltd (Z = 4.95). It was recommended that organizations should encourage training of personnel in the improved limitless possibility of information gathered from the Internet of Things framework which supports planning, budgeting and monitoring approaches, providing more reliable information to support actions, in particular in the decision-making process, to enhance productivity.

Full-Service Operation and IMS Network Management

IP Multimedia Subsystems （IMS） is considered as a comprehensive approach for full-service operation. However, traditional network management concepts are not applicable to IMS network management. This is because IMS is characterized by a flat, all-IP architecture, simplified functionality of Network Elements （NE）, and a variety of NEs, This paper introduces an IMS network management system design that covers full-service operation. It then discusses the significant role IMS network management plays in the unification of NE management layers, the increasing importance of end-to-end applications, and the convergence of Enhanced Telecom Operation Map （eTOM） and IT Infrastructure Library （ITIL）.

Integrated Network Management System for CSL

CSL is a subsidiary of Australia＇ s Telstra Corporation and is the biggest mobile operator in Hong Kong. In March 2008, CSL contracted ZTE to evolve its existing mobile network into a new all-IP mobile network. To reduce the high Operating Expense （OPEX） of network operation and maintenance, CSL sought an Integrated Network Management System （INMS） to consolidate alarms from various network segments, and to improve network operation and maintenance efficiency. ZTE provided CSL with an integrated network solution based on Software Defined Radio （SDR） soft base stations. The SDR solution supports upgrade to High Speed Downlink Packet Access （HSDPA＋） and enables a smooth transition to a Long Term Evolution （LTE） network.

2024 Adult Compendium of Physical Activities:A third update of the energy costs of human activities

Background:The Compendium of Physical Activities was published in 1993 to improve the comparability of energy expenditure values assigned to self-reported physical activity(PA)across studies.The original version was updated in 2000,and again in 2011,and has been widely used to support PA research,practice,and public health guidelines.Methods:This 2024 update was tailored for adults 19-59 years of age by removing data from those≥60 years.Using a systematic review and supplementary searches,we identified new activities and their associated measured metabolic equivalent(MET)values(using indirect calorimetry)published since 2011.We replaced estimated METs with measured values when possible.Results:We screened 32,173 abstracts and 1507 full-text papers and extracted 2356 PA energy expenditure values from 701 papers.We added303 new PAs and adjusted 176 existing MET values and descriptions to reflect the addition of new data and removal of METs for older adults.We added a Major Heading(Video Games).The 2024 Adult Compendium includes 1114 PAs(912 with measured and 202 with estimated values)across 22 Major Headings.Conclusion:This comprehensive update and refinement led to the creation of The 2024 Adult Compendium,which has utility across research,public health,education,and healthcare domains,as well as in the development of consumer health technologies.The new website with the complete lists of PAs and supporting resources is available at https://pacompendium.com.

Older Adult Compendium of Physical Activities:Energy costs of human activities in adults aged 60 and older

Purpose:To describe the development of a Compendium for estimating the energy costs of activities in adults>60 years(OA Compendium).Methods:Physical activities(PAs)and their metabolic equivalent of task(MET)values were obtained from a systematic search of studies published in 4 sport and exercise databases(PubMed,Embase,SPORTDiscus(EBSCOhost),and Scopus)and a review of articles included in the 2011 Adult Compendium that measured PA in older adults.MET values were computed as the oxygen cost(VO_(2),mL/kg/min)during PA divided by 2.7 m L/kg/min(MET_(60+))to account for the lower resting metabolic rate in older adults.Results:We identified 68 articles and extracted energy expenditure data on 427 PAs.From these,we derived 99 unique Specific Activity codes with corresponding MET_(60+)values for older adults.We developed a website to present the OA Compendium MET_(60+)values:https://pacompendium.com.Conclusion:The OA Compendium uses data collected from adults>60 years for more accurate estimation of the energy cost of PAs in older adults.It is an accessible resource that will allow researchers,educators,and practitioners to find MET_(60+)values for older adults for use in PA research and practice.

Single nucleotide polymorphism within chromosome 8q24 is associated with prostate cancer development in Saudi Arabia

Objective: Genome-wide association studies have demonstrated that single nucleotide polymorphisms (SNPs) are important risk factors for the development of prostate cancer (PCa). Preliminary studies have suggested that the incidence of PCa in Saudi males is low but is probably familial or genetically related.Methods: To identify any possible association of SNP with PCa development in Saudi patients, we investigated a group of SNPs in Saudi PCa patients (n=85) and compared the outcomes to healthy normal controls (n=115) and nodular hyperplasia patients (n=120). DNA was extracted from paraffin-embedded formalin fixed tissue or whole blood from both patients’ groups and healthy control group. A total of thirteen SNPs were genotyped using TaqMan® minor groove binder polymerase chain reaction assay.Results: The rs16901979A, s629242T and rs1447295A alleles were found at significantly higher frequency in PCa patients than controls (p< 0.05). The rs16901979 CA genotype was found at significantly greater frequency in PCa patients than in healthy controls (43% vs. 14%, odds ratio=4.6, p=0.0001) and benign hyperplasia group (43% vs. 25%, odds ratio=2.2, p=0.009).Conclusion: Our study has highlighted the association of rs16901979 SNP with PCa in Saudi males. Such findings have important implications in the PCa diagnosis and in screening unaffected family members of Saudi patients.

Nonlinear Study on the Mechanical Performance of Built-Up Cold-Formed Steel Concrete-Filled Columns under Compression

Given their numerous functional and architectural benefits,such as improved bearing capacity and increased resistance to elastic instability modes,cold-formed steel(CFS)built-up sections have become increasingly developed and used in recent years,particularly in the construction industry.This paper presents an analytical and numerical study of assembled CFS two single channel-shaped columns with different slenderness and configurations(backto-back,face-to-face,and box).These columns were joined by double-row rivets for the back-to-back and box configurations,whereas they were welded together for the face-to-face design.The built-up columns were filled with ordinary concrete of good strength.Finite element models were applied,using ABAQUS software,to assess mechanical performance and study the influence of assembly techniques on the behavior of cold-formed columns under axial compression.Analytical approaches based on Eurocode 3 and Eurocode 4 recommendations for un-filled and concrete-filled columns respectively were followed for the numerical analysis,and concrete confinement effects were also considered per American Concrete Institute(ACI)standards for face-to-face and box configurations.The obtained results indicated a good correlation between the numerical results and the proposed analytical methodology which did not exceed 8%.The failure modes showed that the columns failed due to instabilities such as local and global buckling.

Improving mechanical properties and high-temperature oxidation of press hardened steel by adding Cr and Si

This work investigated the effect of Cr and Si on the mechanical properties and oxidation resistance of press hardened steel.Results indicated that the microstructure of the Cr-Si micro-alloyed press hardened steel consisted of lath martensite,M_(23)C_(6)carbides,and retained austenite.The retained austenite and carbides are responsible for the increase in elongation of the micro-alloyed steel.In addition,after oxidation at 930℃for 5 min,the thickness of the oxide scales on the Cr-Si micro-alloyed press hardened steel is less than 5μm,much thinner than 45.50μm-thick oxide scales on 22MnB5.The oxide scales of the Cr-Si micro-alloyed steel are composed of Fe_(2)O_(3),Fe_(3)O_(4),mixed spinel oxide(FeCr_(2)O_(4)and Fe_(2)SiO_(4)),and amorphous SiO_(2).Adding Cr and Si significantly reduces the thickness of the oxide scales and prevents the generation of the FeO phase.Due to the increase of spinel FeCr_(2)O_(4)and Fe_(2)SiO_(4)phase in the inner oxide scale and the amorphous SiO_(2)close to the substrate,the oxidation resistance of the Cr-Si micro-alloyed press hardened steel is improved.

Instance Segmentation of Characters Recognized in Palmyrene Aramaic Inscriptions

This study presents a single-class and multi-class instance segmentation approach applied to ancient Palmyrene inscriptions,employing two state-of-the-art deep learning algorithms,namely YOLOv8 and Roboflow 3.0.The goal is to contribute to the preservation and understanding of historical texts,showcasing the potential of modern deep learning methods in archaeological research.Our research culminates in several key findings and scientific contributions.We comprehensively compare the performance of YOLOv8 and Roboflow 3.0 in the context of Palmyrene character segmentation—this comparative analysis mainly focuses on the strengths and weaknesses of each algorithm in this context.We also created and annotated an extensive dataset of Palmyrene inscriptions,a crucial resource for further research in the field.The dataset serves for training and evaluating the segmentation models.We employ comparative evaluation metrics to quantitatively assess the segmentation results,ensuring the reliability and reproducibility of our findings and we present custom visualization tools for predicted segmentation masks.Our study advances the state of the art in semi-automatic reading of Palmyrene inscriptions and establishes a benchmark for future research.The availability of the Palmyrene dataset and the insights into algorithm performance contribute to the broader understanding of historical text analysis.

Integrated Energy-Efficient Distributed Link Stability Algorithm for UAV Networks

Ad hoc networks offer promising applications due to their ease of use,installation,and deployment,as they do not require a centralized control entity.In these networks,nodes function as senders,receivers,and routers.One such network is the Flying Ad hoc Network(FANET),where nodes operate in three dimensions(3D)using Unmanned Aerial Vehicles(UAVs)that are remotely controlled.With the integration of the Internet of Things(IoT),these nodes form an IoT-enabled network called the Internet of UAVs(IoU).However,the airborne nodes in FANET consume high energy due to their payloads and low-power batteries.An optimal routing approach for communication is essential to address the problem of energy consumption and ensure energy-efficient data transmission in FANET.This paper proposes a novel energy-efficient routing protocol named the Integrated Energy-Efficient Distributed Link Stability Algorithm(IEE-DLSA),featuring a relay mechanism to provide optimal routing with energy efficiency in FANET.The energy efficiency of IEE-DLSA is enhanced using the Red-Black(R-B)tree to ensure the fairness of advanced energy-efficient nodes.Maintaining link stability,transmission loss avoidance,delay awareness with defined threshold metrics,and improving the overall performance of the proposed protocol are the core functionalities of IEE-DLSA.The simulations demonstrate that the proposed protocol performs well compared to traditional FANET routing protocols.The evaluation metrics considered in this study include network delay,packet delivery ratio,network throughput,transmission loss,network stability,and energy consumption.

Intelligent Diagnosis Method for Typical Co-frequency Vibration Faults of Rotating Machinery Based on SAE and Ensembled ResNet-SVM

Intelligent fault diagnosis is an important method in rotating machinery fault diagnosis and equipment health management.To deal with co-frequency vibration faults,a type of typical fault in rotating machinery,this paper proposes a fault diagnosis method based on the stacked autoencoder(SAE)and ensembled ResNet-SVM.Furthermore,the time-and frequency-domain features of several co-frequency vibration faults are summarized based on the mechanism analysis and calculated using actual vibration data.To realize and validate the high-precision diagnosis method of rotating equipment with co-frequency faults proposed in this study,the following three criteria are required:First,to improve the effectiveness and robustness of the ensembled model and the sliding window using data augmentation,adding noise,autoencoder(AE)and SAE methods are analyzed in terms of principle and practical effects.Second,ResNet is used as the feature extractor for the ensembled ResNet-SVM model.Feature extraction is carried out twice,and the extracted co-frequency fault features are more comprehensive.Finally,the data augmentation method and ensemble ResNet-SVM are combined for fault diagnosis and compared with other methods.The experimental results show that the accuracy of the proposed method can exceed 99.9%.

Beyond p-y method:A review of artificial intelligence approaches for predicting lateral capacity of drilled shafts in clayey soils

In 2023,pivotal advancements in artificial intelligence(AI)have significantly experienced.With that in mind,traditional methodologies,notably the p-y approach,have struggled to accurately model the complex,nonlinear soil-structure interactions of laterally loaded large-diameter drilled shafts.This study undertakes a rigorous evaluation of machine learning(ML)and deep learning(DL)techniques,offering a comprehensive review of their application in addressing this geotechnical challenge.A thorough review and comparative analysis have been carried out to investigate various AI models such as artificial neural networks(ANNs),relevance vector machines(RVMs),and least squares support vector machines(LSSVMs).It was found that despite ML approaches outperforming classic methods in predicting the lateral behavior of piles,their‘black box'nature and reliance only on a data-driven approach made their results showcase statistical robustness rather than clear geotechnical insights,a fact underscored by the mathematical equations derived from these studies.Furthermore,the research identified a gap in the availability of drilled shaft datasets,limiting the extendibility of current findings to large-diameter piles.An extensive dataset,compiled from a series of lateral loading tests on free-head drilled shaft with varying properties and geometries,was introduced to bridge this gap.The paper concluded with a direction for future research,proposes the integration of physics-informed neural networks(PINNs),combining data-driven models with fundamental geotechnical principles to improve both the interpretability and predictive accuracy of AI applications in geotechnical engineering,marking a novel contribution to the field.