Process In Order Research Articles

Examining the student and teacher feedback on concept mapping as a teaching and learning method

Background: Nursing students struggle to link theory to practice; therefore, nurse educators are requested to use innovative methods to help them in this regard such as the concept mapping. Purpose: to examine the effectiveness of concept mapping as a teaching learning method in clinical setting. Method: A mixed method approach was used to student nurse and educators. A Likert scale of 15 items with 4 open ended questions was used to assess the effectiveness of the method in improving the students’ care plan. For qualitative, teacher’ reflection was used to assess the teacher perception about the effectiveness of concept map as a teaching learning method. Results: This study indicated concept mapping is an effective method in teaching in clinical setting, developing appropriate care plan and promoting critical thinking. The result showed that there is significant difference between the mean scores of participants in relation to critical thinking and usage of concept map in clinical setting, however there was no difference in regards of usage of concept map in developing care plan. Conclusion: Nurse Educators should consider the use of concept mapping as a way of teaching and learning process in order to improve critical thinking and quality of care.

Uncovering soil compaction: performance of electrical and electromagnetic geophysical methods

Abstract. Monitoring soil structure is of paramount importance due to its key role in the critical zone as the foundation of terrestrial life. Variations in the arrangement of soil components significantly influence its hydro-mechanical properties and therefore its impact on the surrounding ecosystem. In this context, soil compaction resulting from inappropriate agricultural practices not only affects soil ecological functions, but also decreases the water-use efficiency of plants by reducing porosity and increasing water loss through superficial runoff and enhanced evaporation. In this study, we compared the ability of electric and electromagnetic geophysical methods, i.e., electrical resistivity tomography (ERT) and frequency-domain electromagnetic (FDEM) method, to assess the effects caused by both heavy plastic soil deformations generated by a super-heavy vehicle and the more common tractor tramlines on silty-loam soils. We then tested correlations between geophysical response and soil variables (i.e., penetration resistance, bulk density, and volumetric water content on collected samples) at different homogeneous areas defined by k-means clustering. This work is intended to be a contribution to clarify expectations about the use of geophysical techniques to rapidly investigate soil compaction at various spatial scales, dissecting their suitability and limitations. It also aims to contribute to the methodological optimization of agrogeophysical acquisitions and data processing in order to obtain accurate soil models through a non-invasive approach. Electrical prospecting has finer spatial resolution and allows a tomographic approach, requiring higher logistic demands and the need for ground galvanic contact. On the other hand, contactless electromagnetic induction methods can be quickly used to define the distribution of electrical conductivity in the shallow subsoil in an easier way. In general, compacted soil portions are imaged as high-electrical-conductivity anomalies relative to the context. Results, validated with traditional soil characterization, show the pros and cons of both techniques and how differences in their spatial resolution heavily influence the ability to characterize compacted areas with good confidence.

An Analytical Desk Review of the Implementation of Fiscal Decentralisation in Zambia: Challenges and Opportunities

Fiscal decentralization, coupled with effective intergovernmental fiscal relations, stands as a cornerstone in the evolution of modern governance structures. This paper analyzes the implementation of fiscal decentralisation in Zambia as part of its initiatives across diverse socio-economic and political contexts for accelerated national development. The review was guided by three objectives which were: to review the existing legislation that supports implementation of fiscal decentralisation in Zambia; to assess the revenue and expenditure autonomy assignments of fiscal decentralisation in Zambia; and to recommend a fiscal transfer system to be used to enhance the implementation of fiscal decentralisation in Zambia. The study is based on secondary data on fiscal decentralization collected in official sources of Zambia’s Ministry of Finance and National Planning, Ministry of Local Government and Rural Development, and Cabinet Office – Decentralization Secretariat. All the data was processed by and used in the right format for the analysis of implementation of fiscal decentralization in Zambia. Through a combination of qualitative and quantitative methodologies, this study analysed the real level of fiscal decentralization made in Zambia. Key findings of the study was that Zambia does not have an institution to supervise fiscal decentralization except a desk at Cabinet Office – Decentralization Secretariat. Besides, Local authorities have little autonomy in administering revenues and expenses as such, one of them requires approval by the Minister of Local Government and Rural Development. This hampers innovation around revenue generation as there is no known parameter used to grant or deny approval. Additionally, some of the aspects of the Zambia Intergovernmental Fiscal Architecture have not been implemented thereby depriving local authorities of revenue. These include Matching grants, revenue sharing of tolls and Road Transport and Safety Agency (RATSA) fees which are supposed to be shared between Central Government and local authorities as road maintenance is a concurrent mandate and revenue sharing for national income collected by Central Government from local authority jurisdictions. Finally, the connection between the level of fiscal decentralization and the scheme of intergovernmental fiscal relations is very important, to ensure maximum effectiveness of local government financing. The quality of the distribution of funds provided by the scheme of intergovernmental fiscal relations and the level of fiscal decentralization has a direct relationship. Balancing these two mechanisms is the most important way to increase the quality of public services at the local level as a way of enhancing the implementation of the fiscal decentralization. Arising from the study’s finding, there is need for amendment and harmonization of legislation governing the devolution process and procedures in order to empower the designate entities to carry out their mandate without unnecessary cob-webs. The local authorities also need autonomy on revenue mobilization and expenditure which are devoid of central government interference and/or rent-seeking pursuits. Furthermore, there is need to balance the level of fiscal decentralization and the scheme of intergovernmental fiscal relations in order to improve the quality of funds distributed and the effectiveness and efficiency in local government financing.

Managing the University’s Educational Process Based on Predicting Students’ Academic Performance

The authors of the article present a comprehensive analysis of the accounting of students’ academic performance in the management of the educational process of the university. The information about students that affects their academic performance and satisfaction with the educational organization is analyzed and classified. The focus of the study is on the application of predictive models in the management of the educational process in order to adapt the content of disciplines to the current contingent of students. The study used data only on first-year students (2023/24 academic year) of bachelor’s and specialist’s degree levels (n=1549). The information is depersonalized and contains the following data: demographic (age, gender, citizenship), social (socio-cultural environment, place of residence, place of residence during study), academic (previous education, results of entrance tests, current academic performance, faculty, qualification level), economic (scholarship, type of competition – budget/contract). Methods of mathematical statistics were used to analyze the data: determining the type of data distribution using the Shapiro-Wilk test, establishing the presence of multicollinearity in the construction of multiple regression by the Pearson criterion, establishing correlation dependencies by Spearman’s rank correlation method. Machine learning methods are implemented in the Python programming language (v. 3.8) using the freely distributed Keras library. The main results. The classification of factors affecting the academic performance and satisfaction of students is presented. Using the methods of mathematical statistics, the importance of each factor for predicting academic performance has been established. An educational process management model based on Agile Learning Design has been developed and presented, which allows adapting a specific discipline to the current contingent of students.

Adaptation of an additively manufactured reactor concept for catalytic methanation with in-situ tar co-reforming of biogenic syngas

The methanation of biogenic syngas for GreenLNG production is a promising alternative for fossil gas. The market price of renewable methane is currently still too high to compete with fossil LNG. One of the reasons for that is the extensive gas cleaning that is necessary for the methanation of syngas from the thermochemical gasification of biomass. A main cost factor is the removal of tar components. As part of the Horizon Europe project CarbonNeutralLNG, we propose a 3D-printed methanation reactor, which makes use of the freedom in design gained by the additive manufacturing process in order to adapt the reactor design for the in-situ co-reforming of tars. The reactor uses heat pipes and a conically widened reaction channel to effectively control local temperatures, suiting the needs of the methanation reaction. A temperature hot spot near the inlet provides the necessary conditions (high temperature, a suitable catalyst and sufficient residence time) for the reforming of tar species, that are present in the syngas. Two reactor concepts are proposed. ADDmeth3.1 uses a dedicated internal channel structure that serves as a counter-current heat exchanger for the feed gas, whereas ADDmeth3.2 is optimized to fill the triangular footprint of a scalable reactor module as best as possible. Both designs were subject to a preliminary feasibility study, to ensure sufficient heat removal and a finite element analysis regarding structural stability was performed. Minimum safety factors against yielding of 3.53 and higher were achieved even without the internal diamond lattice support structure. The triangular modular reactor cell can easily be scaled up by connecting multiple cells in parallel, since the triangular shape can be extended efficiently into a honeycomb pattern.

LOGISTICS MANAGEMENT OF LAND PACKAGE COMPANIES IN CIUDAD DEL ESTE

The main purpose of this study was to analyze the current situation and logistics management of parcel distribution companies in Ciudad del Este during the 2022 school year. The methodology used qualitative descriptive research has been used, which has served to develop the most important aspects of this work, from the approach to the contracting of the results obtained in the interview conducted. The interview technique was applied in a population of 10 companies located in Ciudad del Este, of which 3 companies were taken for the application of the research, the surveys were directed to the managers and officials in charge of logistics management. The research work consists of four units. Unit 1: Logistics planning system. Unit 2: Distribution logistics. Unit 3: Distribution planning. Unit 4: Quality control. The findings indicated that the different units of the logistics process such as: inventory management, load distribution and transport managers, information flow and order processing, storage and distribution have a favorable influence on the logistics management of the companies studied. Based on the results in all companies, in order to achieve competitive advantages, a comprehensive logistics system is necessary that allows all processes to be carried out in an orderly and efficient manner, thus reducing costs, organizing processes, exercising control and improving each of the company's areas. With the constant improvement of transport, and the correct distribution of materials in the construction process, it will be more efficient and this will lead to a reduction in direct and indirect costs.

Assessment of Human Resource Management Functions at RSUD Datu Sanggul

The public sector, particularly hospitals, plays a crucial role in the provision of quality health services. However, many hospitals, including RSUD Datu Sanggul, face challenges in human resource management (HRM) that result in service performance. This study aims to analyze the functions of human resource management (HRM) in the Regional General Hospital (RSUD) Datu Sanggul and its impact on service performance, especially in the Surgical Poly. The method used is a qualitative approach with an exploratory design. Data were collected through observation, questionnaires, and documentation studies, involving 14 hospital leaders as respondents. The results showed that the recruitment and selection process of medical personnel at RSUD Datu Sanggul was still less than optimal, with several inequities and competency mismatches. The implementation of training and development programs for medical personnel recorded activities, but the evaluation of the results was minimal, indicating a lack of impact on performance improvement. In addition, performance appraisal systems and compensation policies also need to be improved to attract and retain medical personnel. This study provides recommendations to improve transparency and standards in the recruitment process, training evaluation, and compensation policy adjustments in order to improve the quality of health services at RSUD Datu Sanggul

Approaches to developing hybrid fulfillment models for e-commerce: The synergy of delivery and storage

Purpose: This study explores innovative approaches to hybrid fulfillment models in e-commerce, focusing on integrating multiple strategies to meet evolving market demands and enhance operational efficiency. Methodology: The research employs observational and analytical methods, drawing on both primary and secondary data from companies operating in the e-commerce fulfillment sector. Results: The study identifies key methods for hybrid fulfillment, including cross-docking, micro-fulfillment networks, and intelligent distribution. These approaches enable businesses to optimize order processing, reduce costs, and improve service quality. A case study of Gymshark demonstrates the successful implementation of a hybrid model, combining centralized warehousing with localized fulfillment centers. Theoretical contribution: This research contributes to the ongoing development of supply chain management strategies by providing a comprehensive analysis of hybrid fulfillment models and their potential to address challenges in traditional fulfillment approaches. Practical implications: The findings offer practical insights for e-commerce businesses seeking to enhance operational efficiency, customer satisfaction, and market competitiveness through the adoption of hybrid fulfillment models. Sustainable Development Goals (SDGs): SDG 9: Industry, Innovation and Infrastructure; SDG 12: Responsible Consumption and Production; SDG 13: Climate Action; SDG 8: Decent Work and Economic Growth; SDG 17: Partnerships for the Goals

THE GENETIC VARIABILITY IN TOMATO GENOTYPES L-11/53 AND V 5 GROWN IN PROTECTED SPACES

The tomato genotypes (L-11/53 and V 5) were subjected to an analysis regarding the variability of the main quantitative fruit characters (fruit weight, fruit height, pericarp thickness). The registered biometric data were statistically processed, calculating for each analyzed character the mean (x̄), the standard deviation (s), the coefficient of variability (s%) and the range of variability (k = x̄ ± s).The calculation and analysis of the variability of the characters studied in the tomato genotypes L-11/53 and V 5, revealed on average in the two years of the study a small variability for the height of the fruit (s% = 9.37% for L-11/53 and 7.52% for V 5) and medium for pericarp thickness (s% =16.59% for L-11/53 and 15.47% for V 5).The values of the calculated statistical indices, of the characters taken in the study, require the continuation of the selection process in order to maintain them within the specific limits of variability.

Supply Chain Analytics, Definitions, Characteristics and Applications: A Systematic Literature Review

While there is a high uptake of BDA in the realm of supply chain management, in the view of automation supply chains and improving their value proposition by providing more accurate data for demand forecasting. There are material knowledge gaps on the SC-specific analytics applied to match demand, albeit the existing knowledge could be more amorphous. From this backdrop, the study endeavored to analyze extant literature within the ambit of BDA to unpack the current trends and possible future research directions to foster the application of BDA in SC contexts. The study adopted a systematic literature review of the extant literature published between 2014-2023. The study adopted the five-stage iterative procedure used in the systematic review methodology. The review's findings depict extensive use of big data analytics in matching demand and supply and supply chain optimization. The findings of this study adduce almost non-rebuttable evidence that big data analytics can be applied in procurement, inventory control, logistics, and order processing. Under the auspices of BDA is the SCA. Arguably, extant research has demonstrated the capability of SCA in mitigating contemporary SC risks such as mismatches between demand and supply, sub-optimal SCs, and underutilization of the supply chain infrastructures at the cusps of various echelons.

Developing Scalable Microservices for High-Volume Order Processing Systems

Developing Scalable Microservices for High-Volume Order Processing Systems

Desorption of Antibiotics from Granular Activated Carbon during Water Treatment by Adsorption

Although desorption of adsorbed pharmaceuticals from granular activated carbon (GAC) may inadvertently lead to their partial discharge with adverse effects on aquatic environments, there have only been a few reports of this phenomenon. This study has investigated desorption of antibiotics vancomycin and rifampicin from activated carbon in aqueous media regarding contact time and pH regime. Various characterizations of the three types of GAC were investigated. Then, antibiotics were loaded on them via adsorption. Subsequently desorption and re-adsorption of antibiotics were quantified for a range of contact times and ambient pH values. Within the first hour of a reversed concentration gradient at neutral pH, desorption released 2% to 54% of previously adsorbed antibiotics to water, which were subsequently re-adsorbed within 24 hours to four weeks with less than 1% antibiotics remaining in the liquid phase. Lower desorption was positively associated with higher GAC mesopore content and larger specific surface area. Effects of the ambient pH regime varied between studied adsorbents. The results are evidence that mesopore content and pore size in relation to the kinetic diameter of adsorbate molecules are important determinants of the extent of antibiotic desorption from GAC and the rates of subsequent re-adsorption. Physisorption was the dominant mechanism involved in both processes. Observed proportions and rates of antibiotic desorption suggest that selection of GAC properties should also consider their effects on unintended desorption and the re-adsorption during treatment processes in order to minimize potential pollution discharge or promotion of antibiotic resistance during treatment processes.

Slow oscillation-spindle coupling predicts sequence-based language learning.

Sentence comprehension involves the rapid decoding of both semantic and grammatical information, a process fundamental to communication. As with other complex cognitive processes, language comprehension relies, in part, on long-term memory. However, the electrophysiological mechanisms underpinning the initial encoding and generalisation of higher-order linguistic knowledge remain elusive, particularly from a sleep-based consolidation perspective. One candidate mechanism that may support the consolidation of higher-order language is the temporal coordination of slow oscillations (SO) and sleep spindles during non-rapid eye movement sleep (NREM). To examine this hypothesis, we analysed electroencephalographic (EEG) data recorded from 35 participants (Mage = 25.4, SD = 7.10; 16 males) during an artificial language learning task, contrasting performance between individuals who were given an 8hr nocturnal sleep period or an equivalent period of wake. We found that sleep relative to wake was associated with superior performance for rules that followed a sequence-based word order. Post-sleep sequence-based word order processing was further associated with less task-related theta desynchronisation, an electrophysiological signature of successful memory consolidation, as well as cognitive control and working memory. Frontal NREM SO-spindle coupling was also positively associated with behavioural sensitivity to sequence-based word order rules, as well as with task-related theta power. As such, theta activity during retrieval of previously learned information correlates with SO-spindle coupling, thus linking neural activity in the sleeping and waking brain. Taken together, this study presents converging behavioral and neurophysiological evidence for a role of NREM SO-spindle coupling and task-related theta activity as signatures of successful memory consolidation and retrieval in the context of higher-order language learning.Significance statement The endogenous temporal coordination of neural oscillations supports information processing during both wake and sleep states. Here we demonstrate that slow oscillation-spindle coupling during non-rapid eye movement sleep predicts the consolidation of complex grammatical rules and modulates task-related oscillatory dynamics previously implicated in sentence processing. We show that increases in theta power predict enhanced sensitivity to grammatical violations after a period of sleep and strong slow oscillation-spindle coupling modulates subsequent task-related theta activity to influence behaviour. Our findings reveal a complex interaction between both wake- and sleep-related oscillatory dynamics during the early stages of language learning beyond the single word level.

Study of temperature dynamics and influencing factors during composting process

Abstract This study investigated the most influential composting parameters (temperature, pH, humidity, C/N ratio, and CO2 emissions) on final compost quality. Composting bags (turned daily) containing prunings, lignocellulose material, cattle manure, and household organic waste were monitored for eight weeks across three batches. All the temperature data registered daily were statistically analyzed with one-way ANOVA to verify the consistency between batches. This study employs a first-order kinetic model to quantify the decomposition of organic matter in composting, revealing the influence of temperature on the decomposition rate. Principal component analysis was conducted for these factors and their interactions with respect to the final compost quality. Finished compost showed a significantly high nitrogen, phosphorus, and potassium content compared with that in the feedstock of the initial compost mixture, while there was constant organic carbon content. In addition to the control of key parameters, a linear regression analysis allowed us to identify the factors that most influenced temperature. We identified two key models: one including pH, humidity, C/N ratio, and CO2 emissions, and another focusing only on CO2. This study emphasized the importance of monitoring and controlling the crucial parameters of the composting process in order to obtain quality compost suitable for application in soil use. Moreover, high temperatures possibly attained in the process of aerobic decomposition destroy the pathogens, making the end products safer for uses in agriculture.

Development of a Conceptual Scheme for Controlling Tool Wear During Cutting, Based on the Interaction of Virtual Models of a Digital Twin and a Vibration Monitoring System.

This article discusses the issue of the joint use of neural network algorithms for data processing and deterministic mathematical models. The use of a new approach is proposed, to determine the discrepancy between data from a vibration monitoring system of the cutting process and the calculated data obtained by modeling mathematical models of the digital twin system of the cutting process. This approach is justified by the fact that some coordinates for the state of the cutting process cannot be measured, and the vibration signals measured by the vibration monitoring system (the vibration acceleration of the tip of the cutting tool) are subject to external disturbing influences. Both the experimental method and the Matlab 2022b simulation method were used as research methods. The experimental research method is based on the widespread use of modern analog vibration transducers, the signals from which undergo the process of digitalization and further processing in order to identify arrays of additional information required for virtual digital twin models. The results obtained allow us to formulate a new conceptual approach to the construction of systems for determining the degree of cutting tool wear, based on the joint use of computational virtual models of the digital twin system and data obtained from the vibration monitoring system of the cutting process.

Development of a Process for Polyphenol Extraction and the Production of a Functional Powder for Food Fortification

The valorisation of co-products from food supply chains is consistent with the objectives of the national recovery and resilience plan (NRRP), which favours issues relating to the “green revolution and ecological transition”. The nutraceutical characteristics (antimicrobial, antiviral, anti-cancer, etc.) of grape pomace extracts are due to the presence of polyphenols. The objective of the following research was to develop an innovative extraction process in order to produce a special powder with high technological and nutraceutical value (polyphenols). For the experimentation, red grape pomace from Cabernet Sauvignon grapes was used. The first phase of the experimentation allowed the development of the extraction methods; the second involved the use of a pilot system for the extraction, filtration, and distillation phases. The result obtained is a powder with compositional characteristics suitable for the fortification of alcoholic and non-alcoholic food matrices, due to its colouring and antioxidant and nutraceutical properties.

تأثير استخدام الذكاء الاصطناعي في المتاجر الإلكترونية على المستهلكين

The study examines the impact of using artificial intelligence in e-stores on consumer behavior. The study highlights the importance of artificial intelligence in improving the online shopping experience, by providing personalized recommendations and analyzing purchasing patterns to better meet consumer needs. Artificial intelligence techniques such as natural language processing, deep learning, and augmented reality are used to provide a distinctive experience that contributes to increasing customer loyalty and raising conversion rates. The study indicates that artificial intelligence can automate many tasks, such as inventory management and order processing, which contributes to reducing costs and improving operational efficiency. Artificial intelligence also plays an important role in enhancing e-commerce security, as it can detect fraud and protect personal data. The study included the impact of AI-supported shopping practices on customers’ functional, financial, social, and emotional values. The results of previous studies reviewed indicate the positive impact of artificial intelligence on the efficiency of marketing methods, and raising the competitive advantage of e-stores by improving the mental image and increasing profitability.

An irregularly spaced ARMA(1,1) model and an application to contamination data

Missing observations and unevenly spaced data are problems common to different disciplines in the context of time series analysis. This paper introduces a new approach to deal with both issues, by considering an irregularly spaced autoregressive moving average process of order (1,1) that is stationary (and therefore homoscedastic) and invertible allowing temporal variations in its coefficients. We test our model in the analysis of greenhouse time series by comparing it with a standard benchmark in the literature. As a result, our methodology leads to a huge advantage in the computational time with respect to the competitor.

SCOPE ON BIM AS A TOOL FOR DESIGNING ARCHITECTURAL PROJECTS FOR ARCHITECTS AND ENGINEERS. CASE OF ALGERIA

Building Information Modeling, often known as BIM, is considered an indispensable component of the design and construction process in many nations throughout the world. In order to analyze the practitioners' perceptions of BIM's influence on construction in connection to the many tools and software, surveys were carried out and analyzed with the sphinx tool. The surveys were also carried out to determine the architects' and engineers' capacities to integrate BIM into their design processes. Despite having limited understanding about BIM as a new method of work, the results indicated that both architects and engineers are concerned about improving design processes in order to provide a higher level of quality to the projects they are working on in Algerian context.

Constructing Dual Schottky Junctions for High‐Performance Zinc Anode

AbstractAqueous zinc ion batteries provide new solutions for achieving environmentally friendly and safe energy storage devices. Unfortunately, the further application is hampered by the growth of zinc dendrites caused by uneven zinc deposition, hydrogen evolution and other side interfacial reactions at the zinc anode. Herein, a multifunctional Bi‐Bi2O3 hybrid artificial interface layer is constructed on the surface of the zinc anode using an in situ conversion reaction. Among them, the Bi‐Bi2O3 Schottky structure not only significantly accelerates the migration of Zn2+ through its built‐in electric field, but also effectively improves the hydrogen evolution barrier (ΔGH*), thereby suppressing side reactions. Moreover, the Schottky contact formed between the interface layer and the metal zinc interface also regulates the electronic distribution state on the zinc surface and optimizes the deposition process of Zn2+, ensuring a more uniform and orderly zinc deposition process. Based on the synergistic effect of dual Schottky junctions, symmetric batteries achieve stable cycling for 2000 h under the conditions of 1.0 mA cm−2 and 1.0 mAh cm−2. The full cell assembled with α‐MnO2 as the cathode maintains capacity of 112.7 mAh g−1 after 1000 cycles at 1 A g−1 with a capacity retention rate of 84%.