System In Order Research Articles

Plate Food Waste in Food Services: A Systematic Review and Meta-Analysis.

Food waste is considered to be a social, environmental, administrative, and economic problem. Given the large-scale production and distribution of food, food waste in food services has been widely discussed by experts, professors, and scientists in the field. This systematic review aimed to understand which food service has the highest percentage of plate food waste. A systematic review and meta-analysis were conducted until January 2024 in ten electronic databases: MEDLINE, Embase, IBECS, BINACIS, BDENF, CUMED, BDNPAR, ARGMSAL, Cochrane Library, Sustainable Development Goals, and the gray literature. The protocol was previously registered with PROSPERO under the code CRD42024501971. Studies that have assessed plate food waste in food services were included. There were no restrictions on language, publication location, or date. The risk of bias analysis was carried out using the JBI instrument. A proportion meta-analysis was carried out using R software (version 4.2.1). This systematic review with meta-analysis showed that the type of distribution and the food service are the factors that have the greatest impact on the percentage and per capita of plate food waste. In the face of increased waste, interventions should be targeted by type and distribution system, diners, and meals in order to lessen the impact of these factors.

Using Affine Arithmetic to Design a Controller for Large Uncertain System

This study presents a approach for creating the supervisor of expansive uncertain systems. The Controller for a particular high order system is designed using a reduced order model. The numerator and denominator polynomial in the suggested reduction approach is derived using modified polynomial differential method. A lower order model with least ISE optimization is obtained. Assuming that the initial high-order system is stable, the proposed approach guarantees the stability of the streamlined model. Through With reference to the original high-order systems, a PID controller is created for the suggested low-order model. In order to explain the method's efficiency, a few numerical examples were taken into consideration. It has been demonstrated that applying Control from the lower order model to the higher order system is improved and the controlled system's performance. Common numerical illustrations seen in the literature have been used to test the method, and the results show that it works satisfactorily.

Understanding provider use of a new clinical decision support tool aimed at reducing excess telemetry in an academic health system: A retrospective study.

Cardiac monitoring has often been identified as an area of overutilization and remains a limited resource in many hospitals. With the aim of reducing telemetry overuse, we added clinical decision support to our health system's telemetry order with guidance on appropriate indications for monitoring. The new order requires selection of an appropriate clinical indication. In this study, we aimed to understand provider engagement with this tool by assessing concordance between selected indications within the order and the clinical presence of those conditions as documented within the patient chart. We randomly selected 100 telemetry orders from July to October 2022 across four different hospitals at NYU Langone Health. Two independent, blinded reviewers used a structured protocol to identify documentation of actual indications for telemetry in each selected chart. We calculated the rate of concordance between indications selected in the order and indications that were determined to be clinically present on chart review. There were 30,839 telemetry orders placed during the study timeframe. Overall concordance between the selection within the order and the actual indication was 48% (95% confidence interval [CI], 38.21%-57.79%). We observed especially low concordance rates for vague indications, such as 'Other', and for 'Confirmed Stroke', which was the only indication allowing for indefinite telemetry. The overall low concordance suggests a disconnect between the support tool and clinical practice. Providers are more likely to select an indication that reduces downstream work regardless of a patient's true clinical indication.

Colour gamut analysis of low‐cost dye‐sensitised solar cells using natural dyes

AbstractDue to the increasing effects of greenhouse gases and environmental pollution, the need for new clean energies like solar energy attracts much attention. Although the characteristics and the efficiency of green photovoltaic devices have been researched, the colour gamut achievable from those devices has not been studied. This study investigates the colour gamut of low‐cost dye‐sensitised solar cells (DSSCs). To do this, 14 natural dye extracts were obtained from herbal resources including dragon fruit, blueberry, mango, radish, yellow rose, red cabbage, sour pomegranate, beetroot, olive, green cabbage pepper, eggplant, parsley, bramble and cherry, and employed as photosensitiser in solar cells. Then, the colorimetric attributes of the photosensitisers were studied in three‐dimensional (3D)‐colour space, that is, CIELab, CIELCH and CIE1931 chromaticity diagram. Additionally, the convex hull method was employed to determine the colour gamut boundary and the corresponding colour gamut volume. Results showed that the majority of samples benefited from approximately 3°–82° of hue angle in a*b* diagram of CIELab colour space and showed the yellowish to reddish tint effects. In CIELCH colour order system, cherry and parsley showed the lowest and highest lightness attributes while the chroma property of samples varied from minimum 1.2 for eggplant to maximum 60.2 for the dragon fruit. Moreover, the results of using the convex hull method showed the volume of 7.73 × 104 that is bounded by the colour gamut of 3D colour points over the CIELab colour space.

Numerical Investigation of PV/T System by Using Graphene Based Nanofluids

The effective use of solar radiation can be maximized by the implementation of a novel hybrid device referred to as a photovoltaic thermal collector (PV/T), which has the capability to simultaneously generate both electrical and thermal energy. As temperature increases, the efficiency of the photovoltaic (PV) cell drops. The present work employs graphene nanofluids as a means to decrease the temperature of the system in order to evaluate the photovoltaic thermal (PV/T) performance. The PV/T system is subjected to Computational Fluid Dynamics (CFD) simulation, wherein graphene nanofluids of different volume concentrations (0%, 0.1%, 0.2%, and 0.3%) and mass flow rates (0.065, 0.075, and 0.085 kg/s) are employed. The PV/T system demonstrated enhanced performance as a result of the implementation of the proposed approach, which effectively reduced the temperature of the solar cell during the period of maximum solar radiation, spanning from 9 AM to 4 PM. The utilization of the system was employed for the generation of thermal and electrical energy due to its respective thermal and electrical efficiency of 67% and 11.5%. The completed research has demonstrated that the integration of graphene nanofluids has the potential to enhance the efficiency of PV/T systems.

The role of telehealth in the delivery of oral and maxillofacial surgery services at a level 6 hospital in New South Wales Australia during COVID-19 - the John Hunter Hospital experience: a commentary, review and cautionary tale for the future.

The objective of this article is to understand the uptake in use of Telehealth services during the COVID-19 pandemic as a way to provide compelling impetus for further research and promotion of Telehealth in general. A data review of Outpatient Department data from 2020 to 2023, as compiled by the Surgical Outcomes improvement Unit. Telehealth was widely adopted during the COVID-19 pandemic for clinicians to provide healthcare to patients whilst adhering to strict lockdown guidelines aimed at limiting exposure and spread of the respiratory virus. There has been minimal analysis, however, of the ethical and legal implications of telemedicine. Whilst it seems that access to care is improved via telehealth, there are subtle, inherent barriers intrinsic to it. There was a significant increase in the use of audio and audiovisual aids in the delivery of Oral and Maxillofacial Outpatient care during the COVID-19 period. Further analysis and improvements need to be made to the system before it can be considered as sufficient and adequate. Where there is rapid adoption of Telehealth in the delivery of Oral and Maxillofacial Surgery Services, there must be concurrent rigorous review and update of systems in order to address the key areas of patient safety and accuracy of treatment.

Determining the potato samples processed manner with an electronic nose system supported by a machine-learning approach

Through several studies, electronic nose (E-nose) devices have been demonstrated to serve as useful measurement equipment for the fast and reliable analysis of complex odour profiles in a wide range of fields, including the area of ensuring food safety. In the same perspective, i.e. checking food safety comes this work, where potatoes are assessed using an E-nose principally made of five metal oxide gas sensors supported with a machine learning algorithm, said evaluation is based on their origin fields: naturally treated, treated with chemical NPK fertilizers, or treated with chicken manure. The technique of support vector machines has been exploited for the data obtained from the multi-sensor system in order to distinguish the potato types mentioned by following two methods: a direct method where all the data have been exploited with a rate of success of 91.7%, and a composed method where the classification was first between naturally treated samples and those treated differently with a success rate of 96.7%, then a classification between those treated differently had a 92.5% success rate. A microbiological analysis was also carried out and its results were compared with those obtained by the E-nose. As per the two methods’ results, the distinction of the potato types by the nature of the cultivated fields is possible with the recording of the multisensory system superiority due to response time, low cost, simplicity, and portability.

Risk Categorization in On-Farm Welfare in Different-Sized Dairy Sheep Flocks.

The objective of the present work was to categorize the risks in the on-farm welfare of dairy sheep in semi-extensive systems in order to highlight if risks in welfare vary according to the farm size. To the best of our knowledge, this study constitutes one of the few categorizations of the risks in the welfare of dairy sheep reared semi-extensively. The survey was conducted on 12 semi-extensive dairy sheep farms in Tuscany (Central Italy), which were classified according to flock size: <500, from 500 to 1000, and >1000. The results showed an adequate rating for all the farms included in the study. The most critical issues concerned the ratio between the number of stockpersons and the number of animals within the farms, the small decubitus areas, the lack of udder cleaning procedures during milking operations, and, in terms of biosecurity, the lack of prevention, control, and eradication plans for the most important infectious ovine diseases. The results show that different items in the five areas evaluated, including the assessments of management of the flock, the number of daily inspections, and the hygiene of the water supplies are associated with the farm size. In large farms, the assessment of management of the flock was better, but the number of daily inspections and the hygiene of the water supplies were worse.

Cooperative Adaptive Fuzzy Control for the Synchronization of Nonlinear Multi-Agent Systems under Input Saturation

This research explores the synchronization issue of leader–follower systems with multiple nonlinear agents, which operate under input saturation constraints. Each follower operates under a spectrum of unknown dynamic nonlinear systems with non-strict feedback. Additionally, due to the fact that the agents may be geographically dispersed or have different communication capabilities, only a subset of followers has direct communication with the leader. Compared to linear systems, nonlinear systems can provide a more detailed description of real-world physical models. However, input saturation is present in most real systems, due to various factors such as limited system energy and the physical constraints of the actuators. An auxiliary system of Nth order is introduced to counteract the impact of input saturation, which is then employed to create a collaborative controller. Due to the powerful capability of fuzzy logic systems in simulating complex nonlinear relationships, they are deployed to approximate the enigmatic nonlinear functions intrinsic to the systems. A distributed adaptive fuzzy state feedback controller is designed by approximating the derivative of the virtual controller by filters. The proposed controller ensures the synchronization of all follower outputs with the leader output in the communication graph. It is shown that all signals in the closed-loop system are semi-globally uniformly ultimately bounded, and the tracking errors converge to a small neighborhood around the origin. Finally, a numerical example is given to demonstrate the effectiveness of the proposed approach.

Quaternary blended eco high performance concrete utilizing high volumes of siliceous additives

This research examines the optimal feasibility of incorporating siliceous additives as an adjunct material for cement in the formulation of environmentally sustainable high-performance concrete (Eco-HPC). Siliceous materials, including Nano silica (NS), Rice Husk Ash (RHA), and Fly Ash (FA), were fine-tuned within the cementitious system in order to achieve the amplified performance of Eco-HPC by reducing the required cement content from 370 kg/m3 to 273 kg/m3. This is achieved by employing the Modified Andreasen and Andreasen (MA&A) particle packing model, with ‘q’ (distribution factor) as ‘0.3’. The Levenberg Marquardt algorithm (curve fitting) was utilized to validate the packing density of each concrete blends. Initially, the dry NS agglomerates are synthesized into stabilized aqueous dispersion through High shear mixing (10 min/1750 rpm) followed by probe sonication (15 min/(1/3) s/s) with anionic surfactant dosage of 0.1 g/10 g. Incorporating secondary siliceous binders into the cement matrix led to an enhancement in the packing density, increasing from 0.94 (nullary) to 0.96 (quaternary) which in turn alters the reactivity and cohesiveness of the matrix. Compressive strength values for Binary (NS2), Ternary (RN15, FN20), and quaternary mix (FRN25) were observed as 57.42 MPa, 56.83 MPa, 55.34 MPa, and 52.58 MPa, respectively, for primary binder contents of 362 kg/m3, 314 kg/m3, 296 kg/m3, and 273 kg/m3 without compromising durability parameters. An assessment on reduced carbon dioxide emissions indicated that increasing the cement replacement percentages in Eco-HPC by up to 30% for binder contents of 358 kg/m3, 296 kg/m3, 259 kg/m3, and 273 kg/m3 resulted in a reduction of CO2 emissions by 2.98%, 18%, 27%, and 23.33%, respectively. Among the twelve formulated mixes, FRN25, FRN20, FRN15 and FN30 are identified as Eco-HPC mix through a computational framework which integrates the packing density, carbon emission, strength and diffusion coefficient.

Periodic solutions in reversible symmetric second order systems with multiple distributed delays

In this paper, we study a class of nonlinear differential equations with multiple distributed delays. We reduced the problem of search for periodic solutions of the distributed delay differential equations to that of finding zeros of an operator on some Banach space. Utilizing the equivariant degree theory, we obtain some sufficient conditions to guarantee the existence of multiplicity of periodic solutions. Also, we give some information about the symmetry of the periodic solutions. At last, we give an example to illustrate our result.

Optimization of White Box Testing by Utilizing Branching and Repeating Structures in Java Programs Using Base Path

Software testing is a process created to detect anomalies in the operation of a program or system in order to achieve the expected results. White box testing is a software testing method that tests the internal structure, design and program code. This research aims to produce an optimization method for white box testing in Java programs by utilizing branching and repetition structures using the basis path method, as well as analyzing the effectiveness of the proposed method in generating test cases. The Java program tested in this research includes input function calls, loops, branching, and exception handling. Test case design is carried out by applying the basis path method to achieve comprehensive coverage. The test results show that the base path method is able to produce effective test cases for testing control structures without redundancy. Test case design is assisted by flowgraph and matrix graph modeling. It is hoped that this research can contribute to the optimization of white box testing techniques.

APPLICATION OF HYDROGELS FOR WATER SHUTOFF TREATMENTS. Message No. 2

The article analyzes the use of hydrogels with nanoparticle additives for well water shutoff, as well as the development of a mathematical apparatus for hydrodynamic modeling of water shutoff operations. One of the most significant trends in the development of gel forming compounds for well water shutoff in the last 10 years has been the use of nanocomposites. The base polymers for nanocomposites used for water shutoff operations are either synthetic or biopolymer origin. The article highlights the novelty and prospects of using nanoparticles in sealing compositions. Various nanocomponent additives are used to increase the success of the use of hydrogel polymer systems in order to limit water inflow and expand the scope of their application in complicated reservoir conditions. These include carbon and mineral nanoparticles, which increase the stability and strength of crosslinked gels in formation conditions.In this paper, we consider the optimization of the repair and insulation operations design using gels for well water shutoff using mathematical modeling, which helps to justify the volume of hydrogel injection and calculate the necessary pressure gradients at which the sealing screen remains stable. The paramount importance of determining the source of well flooding is emphasized, depending on which the processing design is already being built, and appropriate materials are selected; trends in the development of repair and insulation operations at the present stage are traced. Based on the results of the implementation of the proposed model by numerical methods, the authors constructed diagrams of the stability of the waterproofing screen depending on the fracture width, screen size, gel injection rate and reservoir permeability. The technique proposed in the work allows to correctly select and optimize the technological parameters of the operation to maintain the stability of the screen in specific geological conditions.Mathematical modeling allows us to strictly justify the volume of injection of the gel screen, increase the technological and economic efficiency of the process, and in large fields — to rank wells according to the priority of processing. Oilfield practice in various regions of the country fully confirms the main conclusions made in this review article. Preliminary mathematical modeling and the introduction of microdispersions into gel formulations can significantly increase the efficiency of water shutoff operations. The next step in the development of water insulation technologies is the use of nanodispersions, which look very promising in laboratory modeling and are no longer exotic materials with unrealistic cost.

Irrigation Schedule Optimization for Wheat and Sunflower Intercropping under Water Supply Restrictions in Inner Mongolia, China

Precise water management is essential for the efficient development of irrigated agricultural crops in the Hetao Irrigation Area of Inner Mongolia. Given the severe water scarcity in the region and the significant use of intercropping as a cropping method, the development of rational irrigation scheduling is crucial. The objective of this work was to combine the ISAREG model with wheat–sunflower intercropping crops in order to enhance the effectiveness of irrigation scheduling in intercropping systems. This was achieved by changing and verifying crucial parameters for simulating irrigation patterns in intercropping. We conducted an assessment of nine irrigation schedules for a wheat–sunflower intercropping system in order to provide a range of irrigation scenarios that effectively fulfill the water requirements of the system. In light of this, we suggested implementing restrictions on the dates and volumes of irrigation based on the demand for agricultural irrigation. This approach aimed to establish irrigation schedules that are highly efficient and tailored to the specific crops in the area. As a result, we achieved a water use efficiency rate of 100%, saved 28.78% of water resources, optimized crop irrigation schedules, and enhanced crop economics by 6.7%. This study presents a novel and efficient method to optimize agricultural irrigation schedules, boost agricultural water use efficiency, and maximize crop yields in order to promote sustainable agricultural development.

An innovative Vieta–Fibonacci wavelet collocation method for the numerical solution of three-component Brusselator reaction diffusion system of fractional order

An innovative Vieta–Fibonacci wavelet collocation method for the numerical solution of three-component Brusselator reaction diffusion system of fractional order

Solving the global STEM educational crisis using Cognitive Load Optimization and Artificial Intelligence–A preliminary comparative analysis

There is a persistent STEM educational crisis exemplified by low student enrolments, and both high failure and attrition rates. ChatGPT is easy to use, however pedagogical quality is not necessarily assured. In one experiment the output had a high cognitive load exacerbated by cognitive gaps making the material hard to teach and learn. ChatGPT is a useful pedagogical technology but not a learning theory. Science, technology and engineering all start by quantitatively modelling systems in order to make accurate and quantitative predictions prior to construction or system modification. By contrast, the current learning theories in use today are based on qualitative soft-science principles, with subjective guidelines that are open to interpretation, which can lead to wide variations in the quality of instructional materials and learning outcomes. Cognitive Load Optimization (CLO) is a new Science of Learning (SoL) theory that quantitatively models relational knowledge as coherent, contiguous, pedagogically scalable schemas optimized for the lowest cognitive load. CLO schemas represent the easiest, fastest and most efficient learning paths and are the fundamental basis of instructional design and teaching. Because CLO schemas are pedagogically scalable it is possible to create CLO schemas that are contiguous across different educational levels (school, college and university) thereby uniquely meeting the goals of the American National Science Foundation SoL (‘optimized learning for all’) and the Australian Grattan Institute (‘optimized learning from pre-school to university’). Using CLO results in significant improvements in STEM learning outcomes but is a detailed methodology that can be time consuming to use. The relative advantages and disadvantages of ChatGPT and CLO are highlighted.

Hybrid Approach for Detection and Diagnosis of Short-Circuit Faults in Power Transmission Lines

In this article, the main problem under investigation is the detection and diagnosis of short-circuit faults in power transmission lines. The proposed fault detection (FDD) approach is mainly based on principal component analysis (PCA). The proposed fault diagnosis/identification (FAI) approach is mainly based on sliding-window versions of the discrete Fourier transform (DFT) and discrete Hilbert transform (DHT). The main contributions of this article are (a) a fault detection approach based on principal component analysis in the two-dimensional scores space; and (b) a rule-based fault identification approach based on human expert knowledge, combined with a probabilistic decision system, which detects variations in the amplitudes and frequencies of current and voltage signals, using DFT and DHT, respectively. Simulation results of power transmission lines in Portugal are presented in order to show the robust and high performance of the proposed FDD approach for different signal-to-noise ratios. The proposed FDD approach, implemented in Python, that can be executed online or offline, can be used to evaluate the stress to which circuit breakers (CBs) are subjected, providing information to supervision- and condition-based monitoring systems in order to improve predictive and preventive maintenance strategies, and it can be applied to high-/medium-voltage power transmission lines as well as to low-voltage electronic transmission systems.

Analytical modelling and design of linear controlled dynamic systems

A generalized canonical mathematical model of multidimensional controlled mining transportation complexes and other technical systems in form by A.M. Letov is considered. A principle of symmetry and an algebraic concept are in the basis of the developed analytical methods of design. A principle of symmetry is realized on a set of indexes of roots of a characteristic equation of the system and on a set of indexes of phase coordinates of the mathematical model. The problem of quality of dynamic processes in time is reduced to an algebraic problem of distribution of roots of a corresponding characteristic equation in a complex plane. An analogy in a procedure of transformation of a characteristic determinant into a polynomial and a structure of elementary symmetrical polynomials of roots is established. A new formulation of an analytical representation of change of phase coordinates in time in a form of ordered determinants with respect to indexes of roots and indexes of phase coordinates is obtained based on residue theorem. An illustration of the developed analytical method of design is performed on a special case of a well-known controlled technical system of the fourth order.

Stability analysis of fractional difference equations with delay.

Long-term memory is a feature observed in systems ranging from neural networks to epidemiological models. The memory in such systems is usually modeled by the time delay. Furthermore, the nonlocal operators, such as the "fractional order difference," can also have a long-time memory. Therefore, the fractional difference equations with delay are an appropriate model in a range of systems. Even so, there are not many detailed studies available related to the stability analysis of fractional order systems with delay. In this work, we derive the stability conditions for linear fractional difference equations with an arbitrary delay τ and even for systems with distributed delay. We carry out a detailed stability analysis for the cases of single delay with τ=1 and τ=2. The results are extended to nonlinear maps. The formalism can be easily extended to multiple time delays.

Improving of test utilization through modification of the electronic ordering system for blood zinc level

Improving of test utilization through modification of the electronic ordering system for blood zinc level