Terms Of Applications Research Articles

şçılık Meslek Yüksekokulu Eğitim Mutfağı Uygulamalarında Oluşan Atıkların Miktarı ve Çeşitlerinin Belirlenmesi ve Eğitimde Çevreci Öneriler, Ortaca Meslek Yüksekokulu Örneği

It is possible to find waste classification and waste management studies related to the food and beverage industry in the literature. Waste classifications and counts have been made in restaurants, hotel kitchens or production areas of mass nutrition systems. However, there is no waste management study related to educational kitchens in the literature. Educational kitchens differ from other kitchen applications interms of purpose and content. In educational kitchens, there is a variety of products, a variety ofproduction, and a small amount of production. Studies in these kitchens are carried out not for one type,but for the products of all different types of production. There are lessons in Ottoman cuisine, Turkish cuisine, regional cuisines, world cuisine, pastry, bread and many other fields. In addition, it is possible to increase the amount of waste due to mistakes and wrong applications during production. In educational kitchens, which are different for these and other reasons, information should be given not only on food production; but also on how to make production without waste andhow to reduce waste. Bringing this awareness to kitchen workers of the future at the beginning of their studies will be beneficial in the sectoral sense. For these purposes, the tools and equipment used in all applications and wastes produced in the application kitchen of Muğla Sıtkı Koçman University Ortaca Vocational School Cooking Program were counted, classified and recorded over a period of two weeks. According to the data obtained, it was concluded that the highest waste was production waste, while the second highest waste was food waste at the end of the day. Suggestions were made for the recycling of production and food waste; and for waste-free production practices training.

Efficient Water Segmentation with Transformer and Knowledge Distillation for USVs

Water segmentation is a critical task for ensuring the safety of unmanned surface vehicles (USVs). Most existing image-based water segmentation methods may be inaccurate due to light reflection on the water. The fusion-based method combines the paired 2D camera images and 3D LiDAR point clouds as inputs, resulting in a high computational load and considerable time consumption, with limits in terms of practical applications. Thus, in this study, we propose a multimodal fusion water segmentation method that uses a transformer and knowledge distillation to leverage 3D LiDAR point clouds in order to assist in the generation of 2D images. A local and non-local cross-modality fusion module based on a transformer is first used to fuse 2D images and 3D point cloud information during the training phase. A multi-to-single-modality knowledge distillation module is then applied to distill the fused information into a pure 2D network for water segmentation. Extensive experiments were conducted with a dataset containing various scenes collected by USVs in the water. The results demonstrate that the proposed method achieves approximately 1.5% improvement both in accuracy and MaxF over classical image-based methods, and it is much faster than the fusion-based method, achieving speeds ranging from 15 fps to 110 fps.

Extraction, purification and characterization of papain enzyme from papaya

Papain is one of the widely used enzymes in the industry. This study aimed to extract papain enzyme from various parts (i.e. latex, leaves, peels and seeds) of papaya using distilled water and citric phosphate buffer and subsequently purified with a two-step salt precipitation method. The optimum protein concentration of purified papain was obtained with citric phosphate buffer (0.159-0.319 mg/mL) and distilled water (0.119-0.347 mg/ mL). The protein concentration was almost similar for crude extracted with both the solvent. The purification procedure enhanced up to 1.56 fold when extracted with distilled water and 0.83 fold when extracted with citric phosphate buffer. Latex, leaves, peels and seeds showed maximum enzyme activity at 60oC and pH 8.0 as well as better thermal stability at 60oC for 30 mins. Findings highlighted that extracted papain enzyme from waste parts of papaya could be utilized as a potential source of industrial application in terms of waste to value-added products.

Evaluation and adoption of artificial intelligence in the retail industry

PurposeThe introduction of artificial intelligence (AI) technology has had a substantial influence on the retail industry. However, AI adoption entails considerable responsibilities and risks for senior managers. In this study, the authors developed an evaluation and selection mechanism for successful AI technology adoption in the retail industry. The multifaceted measurement and identification of critical factors (CFs) can enable retailers to adopt AI technology effectively and maintain a sustainable competitive advantage.Design/methodology/approachThe evaluation and adoption of organisational AI technology involve multifaceted decision-making for management. Therefore, the authors used the analytic network process to develop an AI evaluation framework for calculating the weight and importance of each consideration. An expert questionnaire survey was distributed to senior retail managers and 17 valid responses were obtained. Finally, the Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) method was used to identify CFs for AI adoption.FindingsThe results revealed five CFs for AI adoption in the retail industry. The findings indicated that after AI adoption, top retail management is most concerned with factors pertaining to business performance and minor concerned about the internal system's functional efficiency. Retailers pay more attention to technology and organisation context, which are matters under the retailers' control, than to external uncontrollable environmental factors.Originality/valueThe authors developed an evaluation framework and identified CFs for AI technology adoption in the retail industry. In terms of practical application, the results of this study can help AI service providers understand the CFs of retailers when adopting AI. Moreover, retailers can use the proposed multifaceted evaluation framework to guide their adoption of AI technology.

Computation of Wiener Descriptor for Melamine Cyanuric Acid Structure

This paper shows the technique for calculating the Wiener index of melamine cyanuric acid structure by dividing it into smaller vertex-weighted quotient graphs. Melamine cyanuric acid is a crystalline complex made up of a 1 : 1 combination of melamine and cyanuric acid. One of the topological indices that have been investigated the most, both theoretically and in terms of practical applications, is the Wiener index. It has a strong relationship with boiling points and other quantities of molecules. The computational techniques decrease the computational cost by selecting such as the range of values for the Wiener index, the variety and the size of atoms and bonds, and the number of cycles. In this work, we have computed the Wiener index for melamine cyanuric acid structures and also have done a correlation between numerical values and chemical quantities.

Hydromagnetic flow of magnetite–water nanofluid utilizing adapted Buongiorno model

The hydromagnetic flow of magnetite–water nanofluid due to a rotating stretchable disk has been numerically assessed. The nanofluid flow has been modeled utilizing the adapted Buongiorno model that considers the volume fraction-dependent effective nanofluid properties and the major slip mechanisms. In addition, experimentally gleaned functions of effective dynamic viscosity and effective thermal conductivity are deployed. The modeled equations are transformed into a first-order ODEs scheme employing Von Kármán’s similarity conversions and then resolved via the Runge–Kutta algorithm through the shooting technique. The impact of pertinent terms over the physical quantities, nanoliquid temperature and nanoliquid concentration is explained with the support of graphs. Results show that rising volume fraction of magnetite nanoparticles (NPs) and magnetic field term enhance the drag force. Mass transport rate is demoted with augmenting values of magnetic field parameter whereas is promoted with increase in Schmidt number. Further, it is detected that the changes in stretching strength parameter are directly proportional to Nusselt number and inversely proportional to the thermal field. The findings of this numerical analysis have applications in spin coating, rotating disk reactors, storage devices for computers, food processing, and rotating heat exchangers.

Arsenic Contamination in Groundwater: Geochemical Basis of Treatment Technologies.

Arsenic (As) is abundant in the environment and can be found in both organic (e.g., methylated) and inorganic (e.g., arsenate and arsenite) forms. The source of As in the environment is attributed to both natural reactions and anthropogenic activities. As can also be released naturally to groundwater through As-bearing minerals including arsenopyrites, realgar, and orpiment. Similarly, agricultural and industrial activities have elevated As levels in groundwater. High levels of As in groundwater pose serious health risks and have been regulated in many developed and developing countries. In particular, the presence of inorganic forms of As in drinking water sources gained widespread attention due to their cellular and enzyme disruption activities. The research community has primarily focused on reviewing the natural occurrence and mobilization of As. Yet, As originating from anthropogenic activities, its mobility, and potential treatment techniques have not been covered. This review summarizes the origin, geochemistry, occurrence, mobilization, microbial interaction of natural and anthropogenic-As, and common remediation technologies for As removal from groundwater. In addition, As remediation methods are critically evaluated in terms of practical applicability at drinking water treatment plants, knowledge gaps, and future research needs. Finally, perspectives on As removal technologies and associated implementation limitations in developing countries and small communities are discussed.

Toward resilient cloud warehousing via a blockchain-enabled auction approach

Cloud warehousing service (CWS) has emerged as a promising third-party logistics service paradigm driven by the widespread use of e-commerce. The current CWS billing method is typically based on a fixed rate in a coarse-grained manner. This method cannot reflect the true service value under the fluctuating e-commerce logistics demand and is not conducive to CWS resilience management. Accordingly, a floating mechanism can be considered to introduce more flexible billing. A CWS provider lacks sufficient credibility to implement floating mechanisms because it has vested interests in terms of fictitious demand. To address this concern, this report proposes a blockchain-enabled floating billing management system as an overall solution for CWS providers to enhance the security, credibility, and transparency of CWS. A one-sided Vickrey–Clarke–Groves (O-VCG) auction mechanism model is designed as the underlying floating billing mechanism to reflect the real-time market value of fine-grained CWS resources. A blockchain-based floating billing prototype system is built as an experimental environment. Our results show that the O-VCG mechanism can effectively reflect the real-time market value of CWSs and increase the revenue of CWS providers. When the supply of CWS providers remains unchanged, allocation efficiency increases when demand increases. By analyzing the performance of the O-VCG auction and comparing it with that of the fixed-rate billing model, the proposed mechanism has more advantages. Moreover, our work provides novel managerial insights for CWS market stakeholders in terms of practical applications.

Risk Management Framework Analysis

Risk management is widely regarded as one of the most effective methods for preventing the occurrence, avoiding, or limiting the impact of risks through a systematic, structured approach. Therefore, it helps organizations achieve their desired goals with the fewest losses. While technology advances on a daily basis, cyber threats grow at an exponential rate. As a result, cyber risk has become an important field to manage in order to assist organizations in achieving their goals in terms of cyber security. In this study, we present the most popular and common risk management frameworks: the International Standard Organization ISO (ISO 31000:2018), the National Institute of Standards and Technology (NIST), and the Committee of Sponsoring Organizations of the Treadway Commission (COSO), which will help the organizations handle the cyber risk. We review their structures, principles, and processes and how they are working to analyze, assess, and manage risk. Also, how to apply the risk management framework in the context of cybercrime. Finally, we discuss the features and limitations of each of them in terms of applicability, orientations, similarities, and contrasts.

Effect of closed and open system freeze–thaw cycles on GMB–GCL interface transmissivity

An experimental study of the effect of closed system and a limited study of open system freeze–thaw cycles on the interface transmissivity at applied stresses between 10 and 150 kPa is described. The effect of closed system freeze–thaw is most apparent after 100 freeze–thaw cycles and permeation at a stress ≤25 kPa. The effect of permeating fluid chemistry is also evident but decreased with increasing stress. One notable effect of permeant is the potential for internal erosion along weaknesses in the bentonite created by freeze–thaw cycles when permeated by distilled or reverse osmosis water. This is not observed when permeated with simulated pore water containing cations. In terms of practical application, closed system freeze–thaw cycles appear to have little effect on interface transmissivity, and to the extent that there is an effect, it is beneficial. In contrast, cryogenic suction arising with open system freeze–thaw cycles is shown to result in the formation of ice lenses both within the geosynthetic clay liner (GCL) and at the GCL geomembrane interface. Although limited, the data suggest that the effect of ice lens formation on interface transmissivity after open system freeze–thaw cycles is largely eliminated at applied stress above 20–25 kPa, although more research is warranted.

Enhancement of microbial fuel cell performance using pure magnesium anode

MFCs (Microbial Fuel Cell) are bio-electrochemical devices that use microorganisms as biocatalysts to transform the chemical energy found in organic or inorganic compounds into electric currents. However, one of the limitations of this technology in terms of practical application is its lower electric efficiency, which greatly depends on the selection of anode material and the types of waste water used. In this work, organically rich wastewater and pure magnesium anode materials were utilized. Also, to investigate the effect of electrode size on power generation, five different sizes of coin-shaped anodes were employed for the variation in anode size, whose diameter and thickness were (15 mm × 2 mm), (20 mm × 2 mm), (20 mm × 3 mm), (20 mm × 4 mm), and (25 mm × 2 mm) with corresponding surface areas [2πr(r+h)] are 448 mm 2, 754 mm 2, 817 mm 2, 880 mm 2 and 1139 mm 2, respectively. The maximum obtained current density, power density, and energy densities were 4734.26 mA/m2, 37400.625 mW/m2 and 81.59 kW-h/kg respectively, by the smallest anode of size (15 mm × 2 mm). This investigation showed that a reduction in the size of the anode decreases the loss in the activation zone. As a result, from the smallest anode, maximum power and energy output were obtained. Finally, this analysis outlines the process and approaches for MFC to produce more power at a potentially lower cost. It is noted that same waste water has been used throughout the study where surface area of the samples vary from lowest to highest level.

Discovery of Partial Differential Equations from Highly Noisy and Sparse Data with Physics-Informed Information Criterion.

Data-driven discovery of partial differential equations (PDEs) has recently made tremendous progress, and many canonical PDEs have been discovered successfully for proof of concept. However, determining the most proper PDE without prior references remains challenging in terms of practical applications. In this work, a physics-informed information criterion (PIC) is proposed to measure the parsimony and precision of the discovered PDE synthetically. The proposed PIC achieves satisfactory robustness to highly noisy and sparse data on 7 canonical PDEs from different physical scenes, which confirms its ability to handle difficult situations. The PIC is also employed to discover unrevealed macroscale governing equations from microscopic simulation data in an actual physical scene. The results show that the discovered macroscale PDE is precise and parsimonious and satisfies underlying symmetries, which facilitates understanding and simulation of the physical process. The proposition of the PIC enables practical applications of PDE discovery in discovering unrevealed governing equations in broader physical scenes.

A Comprehensive Review on Study Methods of Aerosol Optical Properties in Different Dimensions

A comprehensive understanding of the optical properties of atmospheric aerosol is essential for a variety of applications, such as optical imaging, optical communication, and remote sensing. In recent years, many theories and numerical simulation methods have been developed to connect aerosol physical-chemical properties to their intrinsic and integral optical properties. Usually, simulations and measurements are intertwined to synergistically attain the retrieval of aerosol optical properties and mitigate or even eliminate the adverse impacts of aerosol during imaging, sensing, or communication. This review covers the fundamental theories of aerosol optical properties, the development of numerical simulations, the instrument-based sampling measurements, and the cutting-edge techniques of remote sensing. Numerical simulations have been progressing from symmetric particles to asymmetric particles over the past two decades, although any simulation method is limited by specific shape and a restricted size parameter range. Thus, this review also examines the most typical advances in aerosol instrumentation that are frequently used to measure the intrinsic optical properties of unknown aerosols. Such obtained properties validate simulations and constitute the basis of integral optical properties. In terms of practical applications, integral optical properties are the most critical knowledge about atmospheric aerosol. Remote sensing measurements, be it ground-based, airborne, or satellite-based, all retrieve integral optical properties of atmospheric aerosol from various perspectives, which are elaborated upon in this review. In conclusion, this review provides an all-encompassing comprehension of aerosol optical properties.

Applying frontier approach to measure the financial efficiency of hospitals.

The growth in global healthcare capacity has led to increased healthcare costs and a deterioration in the finances of universal health insurance. Hospitals must consider how to improve financial efficiency and service quality in order to survive and operate sustainably. This study applies data envelopment analysis (DEA) and stochastic frontier analysis (SFA) to measure the financial efficiency of hospitals and to identify the factors and business strategies to improve profitability. The findings and recommendations show that (1) the DEA and SFA methods are similar and have reference values; (2) financial efficiency should be improved by reducing medical costs; (3) the quality of medical staff should be improved and manpower reduced; and (4) information, computerisation, and human intelligence in healthcare and management should be enhanced. In terms of practical applications, this study recommends the promotion of smart healthcare to improve the efficiency and quality of healthcare services, as well as the introduction of artificial intelligence and big data analysis to optimise the use of healthcare manpower. Electronic medical records can be used to reduce the wastage of resources and labour costs, a medication management system can be established, and changes to the procurement system can be made to reduce inventory and improve the efficiency of medical equipment use. It is hoped that this study will provide reference materials and applications for healthcare organisations to improve their operational efficiency and strategies.

Systematic Literature Review of Customs Fees Through Schools of Economic Thought and their Role in Supporting the State Treasury

The goal of this research is to look at a variety of pertinent publications in order to contrast custom duties with the function of the state treasury and develop future research issues. This article does a systematic review of the literature on custom duty research published during 1990 and 2023. The analysis takes use of Scopus data in addition to pertinent terms such as custom duties and the role of state treasury. This complete literature evaluation was selected from 537 articles. This research found that investing in customs duties is critical for assuring the prosperity of a nation. To enhance customs duties and the role of the state treasury, it is vital to concentrate on critical topics that will benefit the country's growth. Therefore, the role of the state treasury system and transparent customs duties are critical for the nation sustainable development. This work established seven research topics for future researchers following a review and analysis of the custom duty’s literature, enabling the research to be carried out.

Application of Traditional Chinese Medicine Residue and Its Derivatives in Sewage Treatment

As traditional Chinese medicine treatment has received extensive attention in the treatment of novel coronavirus in recent years, output of Chinese medicine residues (CMR) increases. The produced CMR may lead to secondary pollution and waste of resources improperly, but it also can bring huge benefits for environmental protection as a potential resource with high efficiency. This article analyzes the advantages and disadvantages of a variety of CMR treatment methods over these years, investigates and summarizes the previous literature from the aspect of wastewater treatment, then finds that CMR and their derived materials can efficiently and stably absorb some pollutants as new adsorbents after modified treatment. In this article, the pollutants were divided into two main categories: heavy metals and organic matter. Varieties of treatments were proposed and their feasibility of application to wastewater treatment. The mechanism for the pollutant removal is further analyzed, where the adsorption methods include physical and chemical types. Research on the application of the CMR in wastewater is still in its infancy in terms of practical applications, but this research has great potential for development. In the process of recycling and application of the CMR, economic benefits would be brought to society and treatment methods of wastewater would be improved. Future research should be orientated to the study of adsorption treatment of large flow rates and mixed wastewater with multiple pollutants.

Superiority of the Supramolecular Halogen Bond Receptor over Its H-Bond Analogue toward the Efficient Extraction of Perrhenate from Water.

A halogen bond-based water-soluble tetrapodal iodoimidazolium receptor, (L-I)(4Br), exhibited a high degree of efficiency (∼96%) in extracting ReO4- from 100% aqueous medium within a wide range of concentrations and of pH values along with excellent reusability. The solid-state X-ray diffraction study showed the trapping of ReO4- by (L-I)(4Br) via the Re-O····I halogen bonding interaction. XPS studies also suggested the interaction between I and ReO4- through polarization of the electron density of I atoms by ReO4-. (L-I)(4Br) is found to be capable of retaining its high extraction efficiency in the presence of competing anions such as F-, Cl-, I-, SO42-, H2PO4-, CO32-, NO3-, BF4-, ClO4-, Cr2O72-, and a mixture of these anions. Interestingly, (L-I)(4Br) was found to be superior in ReO4- extraction as compared to its hydrogen-bond donor analogue, (L-H)(4Br), as confirmed by a series of control experiments and theoretical calculations. Our synthesized dipodal and tripodal halogen bond donor receptors and their H-analogues validated the superiority of these classes of supramolecular halogen bond donor receptors over their hydrogen-bond analogues. (L-I)(4Br) also showed superior practical applicability in terms of the removal of ReO4- at anion concentrations as low as ∼100 ppm, which was a major shortcoming of (L-H)(4Br).

A systematic approach to the peat machines and equipment classification development

The «National Security Strategy of the Russian Federation until 2030» prioritises the use of resource-saving and waste-free technologies for natural resource extraction and processing, import substitution of mining equipment in the Russian mining sector, and the introduction of digital technologies at all stages of resource extraction and processing in the mining industry to improve their safety. The aim of the article is to study the gradual development of peat machinery classification and the relevance of its improvement through integrated mechanization devices to create waste-free extraction and processing of peat deposits using fullcycle mobile complexes with the development of environmentally friendly and resource-saving technologies for peat production. The methodological basis of the research includes post-event analysis, peat machine design theory, and systems analysis. As a research result, new system factors influencing the development of the classification of currently available machinery and equipment for peat production, as well as classification variants combining the processes of extraction and processing of peat deposit resources are provided, which allow modeling the structure of full-cycle mobile complexes for extraction and processing of peat deposit resources without waste. In terms of practical application, the classification of peat machinery enables the development of a rational decision-making data system for optimizing the structure of the technological machinery and equipment fleet of peat extraction enterprises, taking into account the deteriorating conditions of peat resources and development technologies, the economic conditions of the industry and the current trends of digitalization in the extractive industry.

Toward efficient waste electric vehicle battery recycling via auction-based market trading mechanisms

This paper proposes an auction-based market trade mechanism for the electric vehicle battery recycling (EVBR) problem, which aims to realise the optimal resource allocation and pricing of EVBR. The main motivation of this paper is to attempt to explore an approach to achieving efficient battery recycling. We first consider an EVBR market with m buyers and n sellers, and develop the multi-unit trade reduction (MTR) mechanism in the EVBR market. According to the supply and demand relationship in the EVBR market, we consider three market scenarios of supply and demand balance, oversupply, and overdemand, and formulated corresponding auction allocation rules. Numerical study results show that the proposed MTR mechanism can achieve efficient resource allocation. We also observed that not all results increased with the number of sellers/buyers. Second, considering the distance between sellers and buyers, we developed a stochastic multiple MTR (SM-MTR) mechanism to enable sellers and buyers within the region to conduct transactions. Finally, we propose an integrated MTR, SM-MTR and one-sided Vickrey–Clarke–Groves auction mechanism that is feasible in both one-sided and bilateral environments. Furthermore, our work can provide novel managerial implications for EVBR market stakeholders in terms of practical application.

Efficient Adsorption of a Sulfonamide Antibiotic in Aqueous Solutions with N-doped Magnetic Biochar: Performance, Mechanism, and Reusability.

Conventional biochar has limited effectiveness in the adsorption of sulfonamide antibiotics, while modified biochar exhibits greater adsorption potential. Residues of sulfamethoxazole (SMX) in the aquatic environment can threaten the safety of microbial populations as well as humans. In this study, iron-nitrogen co-doped modified biochar (Fe-N-BC) was prepared from palm fibers and doped with Fe and urea via synthesis at 500 °C. Fe-N-BC has a richer surface functional group based on elemental content, X-ray photoelectron spectroscopy, X-ray diffraction, and Fourier transform infrared spectroscopy. The Brunauer-Emmett-Teller (BET) specific surface area test exhibited Fe-N-BC, which possessed a greater surface area (318.203 m2/g) and a better developed pore structure (0.149 cm3/g). The results of the hysteresis loop and the Raman spectrum show that Fe-N-BC has a higher degree of magnetization and graphitization. Fe-N-BC showed a remarkable adsorption capacity for SMX (42.9 mg/g), which could maintain 93.4% adsorption effect after four cycles, and 82.8% adsorption capacity in simulated piggery wastewater. The adsorption mechanism involves pore filling, surface complexation, electrostatic interactions, hydrogen bonding, and π-π EDA interactions. The results of this study show that Fe-N-BC prepared from palm fibers can be a stable, excellent adsorbent for SMX removal from wastewater and has promise in terms of practical applications.