Comprehensive Objective Research Articles

Does Profit Maximization Assumption in Economics Comply with Shariah? Evidence from Theoretical and Empirical Findings

The objective of this paper is to discuss the issue of profit maximization from a shariah point of view. The study is very relevant, especially in the current development of Islamic economics. Profit maximization is the central issue in conventional economics and the implication is that all firm decisions must be intended to realize a profit. This paper uses a qualitative approach to answer the main research question. Using a comprehensive study on the Al-Quran and previous empirical findings, the study reveals that profit maximization is still accepted, but not as a single objective. Islamic economics must use comprehensive objectives that not only profit but also maqasid shariah maximization, including environmental, and social aspects.

Dynamic and Static Multiobjective Topology Optimization for Gears of Directional Drill Transmission System

Aiming at the multiobjective topology optimization design of the structure, this paper proposes a method to establish the comprehensive objective function based on the normalized subobjective of the compromise programming method and to determine the weight coefficient of the subobjective of the comprehensive objective function by the analytic hierarchy process (AHP). By using statistical analysis and modal analysis, the static and dynamic characteristics of the gear can be obtained. The single objective topology optimization is used to reduce the compliance of the gear and elevate the low-order natural frequency, and the frequency weighting method is used to suppress the oscillation phenomenon in the frequency-single-objective optimization. AHP was used to determine the weight coefficient of each subtarget. The compromise programming method is used for multiobjective topology optimization, and the gear design is improved according to the optimization results. By analyzing the improved gear structure, the weight of the optimized gear is reduced by 25.3%. The overall stiffness performance and strength performance are enhanced, and the natural frequencies of each order are improved to different degrees.

Developer obligations and negotiation-based benefit distribution in urban redevelopment: Evidence from Shenzhen, China

The distribution of potential benefits between local governments and developers in urban redevelopment shows a global popularity of negotiating developer obligations for more value capture in exchange for the adjustments to land-use regulations. Existing literature has focused on the institutional factors at national or city level that determine the effectiveness of developer obligations for public value capturing, neglecting the potential gains obtained by developers and overlooking the influencing factors at project level. This study examines the impact of project-based factors on distributional outcomes by applying a quantitative analysis of citywide urban renewal projects in Shenzhen, China. In the Chinese context, benefit distribution is affected by the involvement of state-owned enterprise (SOE) developers, which have established special relationships with local governments and such relationships vary between local and central SOEs. The results indicate that compared with non-SOEs, local SOEs contribute more negotiable developer obligations, while central SOEs are more likely to receive administrative support for project promotion. Though, neither of them is granted extra development density compared with non-SOEs. This study sheds light on the strategies adopted by Chinese local governments to achieve comprehensive objectives via differentiated treatment to SOEs and non-SOEs in the negotiation-based benefit distribution of marketized urban redevelopment.

Psychomotor slowing alters gait velocity, cadence, and stride length and indicates negative symptom severity in psychosis

Schizophrenia is a severe mental disorder, in which 50% of the patients present with motor abnormalities such as psychomotor slowing. Slow spontaneous gait has been reported in schizophrenia. However, comprehensive objective instrumental assessments of multiple gait conditions are missing. Finally, the specific gait patterns of subjects with psychomotor slowing are still unknown. Therefore, this study aimed to objectively assess multiple gait parameters at different walking conditions in patients with schizophrenia with and without psychomotor slowing. Also, we hypothesised gait impairments to correlate with expert ratings of hypokinetic movement disorders and negative symptoms. We collected gait data (GAITRite®) in 70 patients with psychomotor slowing (SRRS (Salpetriere retardation rating scale) ≥15), 22 non-psychomotor slowed patients (SRRS < 15), and 42 healthy controls. Participants performed four walking conditions (self-selected speed, maximum speed, head reclined, and eyes closed) and six gait parameters were extracted (velocity, cadence, stride length, functional ambulation profile (FAP), and variance of stride length and time). Patients with psychomotor slowing presented slower velocity, lower cadence, and shorter stride length in all walking conditions compared to healthy controls, with the non-slowed patients in an intermediate position (all F > 16.18, all p < 0.001). Secondly, slower velocity was associated with more severe hypokinetic movement disorders and negative symptoms. In conclusion, gait impairments exist in a spectrum with healthy controls on one end and patients with psychomotor slowing on the other end. Patients with psychomotor slowing are specifically impaired when an adaptation of gait patterns is required, contributing to the deleterious effects of sedentary behaviours.

Data-Driven Operation Modeling and Optimal Design for Batch Cooling Crystallization with a Case Study on β-LGA

In this paper, a data-driven modeling and optimization method is proposed for batch operation of the cooling crystallization process based on the design of experiments (DoE) in the operation ranges of cooling rate and initial solution supersaturation. The proposed model reflecting a mapping relationship between the manipulated variables of operating conditions and the product crystal size distribution (CSD) is established by two classes of basis functions, one is the wavelet basis function for reshaping the CSD and the other is the polynomial basis function for weighting the chosen wavelet basis functions to reflect the nonlinear relationship between the manipulated variables and the size distribution of product crystals. Meanwhile, a fractional factorial design of DoE is presented to reduce the number of experiments for the above modeling, in comparison with the classical full factorial design. The optimal operating conditions are designed by introducing a comprehensive objective function that combines the information entropy of the product CSD and the ratio of desired product yield with respect to the target crystal size. A particle swarm optimization algorithm with guaranteed convergence is given to solve the nonconvex optimization problem based on the established CSD prediction model. Simulation studies and experiments on the batch seeded β-form L-glutamic acid (LGA) crystallization process are conducted to demonstrate the effectiveness and advantage of the proposed method.

Optimization of a novel vacuum sublimation-rehydration thawing process.

To better guarantee the quality of the thawed meat, maximize the thawing rate, and minimize the system energy consumption, the multiparameter and multi-objective coupling optimizations for the newly proposed vacuum sublimation-rehydration thawing (VSRT) process was conducted. The polynomial nonlinear regression equations of single and comprehensive objectives were established by the central composite rotatable design, and the corresponding test of fitting degree and the analysis of influencing factors order were carried out. Furthermore, the interaction effects of influencing factors were investigated through the response surface methodology and were experimentally validated to obtain the optimal process parameters. The results showed that the established regression equations were in good agreement with the experimental values. For the different objectives, there were great differences in the influence order and interaction of factors. In the sublimation and rehydration stages, there existed an optimal region in the response surface to achieve a better value for the single and comprehensive objectives. When the sublimation time was 19min, the heating plate temperature was 26°C, the rehydration water volume was 1634ml, the rehydration water temperature was 29°C, the thawing time was relatively short (1.00h), and the thawing loss (1.19%), the total color difference (1.02), and the system-specific energy consumption (0.026kWh/kg) were relatively low. The comprehensive performance of the VSRT system reached the best state. PRACTICAL APPLICATION: The purpose of this work is to make the novel vacuum sublimation-rehydration thawing method not only better guarantee the quality of thawed meat but also maximize the thawing rate and minimize the energy consumption of the system, which can provide a new idea and reference for the development of new high-efficiency thawing equipment.

Dynamic Economic Environmental Dispatch of Power System Using An Improved Whale Algorithm

With the global energy crisis and environmental problems becoming increasingly serious, the construction of a new power system containing multiple renewable energy sources for power generation has become a current research direction. In this study, a dynamic economic environmental dispatch model for power systems containing wind and thermal power generation is proposed to promote renewable energy consumption while ensuring system power balance. Firstly, a comprehensive objective function that integrates system operating costs and pollutant emission targets is established, and system active balance constraints and unit output constraints are considered. Secondly, an improved whale optimization algorithm is proposed to deal with the solution problem of the dynamic economic environmental dispatch model by introducing circle chaos mapping, dynamic sine cosine factor, and polynomial variation strategy. Finally, the optimization capability of the proposed model is verified by running a unit test system. The proposed model promotes the consumption and utilization of wind and photovoltaic resources and positively impacts achieving carbon peaking and carbon neutrality.

An Energy Efficiency Optimization Strategy of Hybrid Electric Ship Based on Working Condition Prediction

Optimizing the operational performance of green ships can further improve the energy saving and emission reduction effect of ships, and speed optimization is one of the more widely used and effective measures. It is a new challenge for the shipping industry to achieve speed optimization that simultaneously saves energy, reduces emissions and meets transportation requirements, while considering changes in the navigation environment. In this paper, a hybrid electric ship energy efficiency optimization strategy based on working condition prediction is proposed to solve the problem of navigation condition at a future moment, by making a time series prediction of energy efficiency influencing factors, such as wind speed and current speed. Further, on the basis of establishing the sailing speed prediction model and the real-time energy efficiency operation index (EEOI) model, the real-time EEOI deviation and the sailing speed deviation are adopted as the comprehensive objective function to establish a dynamic optimization model of hybrid electric ship energy efficiency, considering the time-varying environmental factors. Then, the fast Non-Dominated Sorting Genetic Algorithm II (NSGA-II) is applied to solve the bi-objective optimization problem and obtain the optimal ship engine speed in real time. Finally, experimental studies show that the proposed optimization model can improve the energy-saving and emission-reduction effect of the ship under the given speed limit requirements and working environment conditions, which can provide theoretical support for the optimal navigation of hybrid electric ships.

Multi-objective optimum design of five-phase squirrel cage induction motor by differential evolution algorithm

Compared with the traditional induction motors, five-phase squirrel cage induction motor (FSCIM) have the advantages of lower torque ripple and single-phase power, flexible control strategy, higher power density and fault-tolerant operation, which has been widely applied on electrical vehicles, rail transit, underwater vehicles and so on. This paper presents an analytical design optimization method based on the coupling of electromagnetic equivalent circuit (EEC) and differential evolution algorithm (DEA). Furthermore, the difference between three and five-phase winding on harmonic specific leakage permeance is investigated in detail. The nonlinear and oeolotropic influences of design geometrical parameters (slots openings, main dimension ratio, yoke height, airgap length, etc.) on the performances of the basic FSCIM model are evaluated with analytical model. For more accurate results, the harmonic characteristics of five-phase winding structure, iron core saturation, rotor slot skew width, stator end winding, slot leakage inductance and stator and rotor slot structure are considered. Meanwhile, the efficiency, power factor, maximum torque, slot fill factor and material consumption of FSCIM are calculated as the comprehensive objective function. The transient finite element analysis (TFEA) and experimental test verify the accuracy of the proposed optimum model. In addition, the feasibility of the multi objective optimization design scheme provided by the analytical model is verified by TFEA.

The Role and Place of Thanatoradiological Studies in the Pathological Examination of Fetuses and Newborns.

Analysis of published data on the possibilities of using postmortem radiation studies in perinatology is carried out and the results of own thanatoradiological studies of the bodies of dead fetuses and newborns are presented. The possibilities of postmortem radiation studies for differential diagnosis of stillborn and deceased newborns, evaluation of the severity of maceration and the time of intrauterine fetal death, detection of pathological changes in the brain and spinal cord, respiratory and digestive organs, in the cardiovascular and urinary systems were demonstrated. It is concluded that postmortem CT has a high diagnostic efficiency in the study of the bone skeleton, free fluid accumulations in serous cavities and gas in the vessels and tissues of dead fetuses and deceased newborns. The advantage of postmortem MRI is more effective visualization of internal organs and soft tissues, which allows assessing their topography and size, as well as identifying a wide range of pathological changes. For a comprehensive objective analysis of the bodies of stillborn and deceased newborns, combined use of both imaging methods (CT and MRI) is required. At the same time, thanatoradiology should be used as a part of a comprehensive pathological study, but not as a substitute for traditional autopsy.

От «тайны» к «религии» прогресса (В.С. Соловьев и М.О. Гершензон)

The article discusses V.S. Solovyov’s influence on the reflections of M.O. Gershenzon in 1910–1920s about progress, personality, crisis of culture and war. The article affirms the thematic continuity of the views of the two thinkers and the conviction of M.O. Gershenzon in the key position of personality in the development of historical processes. It is emphasized that personality is a reference point in the coordinate system that builds the idea of progress in M.O. Gershenzon’s works. It is noted that the crisis of culture and the war are stages on the path of progress that neglects the personal, namely: the progress of abstract, highly specialized scientific knowledge in which the individual is alienated. The cultural heritage, which is not claimed by the individual as a single consciousness and therefore not assimilated by modern man, has become just a value that does not meet an individual request, turns ‘mystery’ into ‘religion’, an object of personal spiritual comprehension into obligatory ritual that alienates a person from action, the meaning of which is lost. Between Solovyov’s “mystery of progress” and Gershenzon’s “religion of progress” an entire epoch passes away, in which, as it seemed, war is no longer possible, but finally the war sweeps away the achievements of civilization with a fiery whirlwind. All the consequences M.O. Gershenzon’s statement that the main reason for this process is the loss of the individual (including personal search for truth), its transformation into a value in culture, are analyzed in the article. It is concluded that the World War I undermined faith in progress as a multiplication of values in culture; it was comprehended as a consequence of the violation of the organic “complexity of a whole life”, the alienation of a value that was personal in origin.

SCOTT: Scheduling of Comprehensive Objectives for Tasks with Multitargets in Computing Networks

Local and customized services are realized with new type computing architecture by utilizing the spare resources distributed on the helper nodes (HNs) throughout the network. The heterogeneity of mobile edge and fog computing networks makes them natural to support multitarget tasks, and efficient task scheduling is always a fundamental and hot issue in multitask multihelper (MTMH) computing networks. Unlike most of the researches concentrating on the optimization of a single or limited service metrics, this article proposes a service framework for multitarget tasks, which is more universal for future 6G networks supporting customized services. The comprehensive quality of service (CQoS) is constructed to indicate the comprehensive objectives of the task nodes (TNs) with multiple targets. By formulating and transforming the CQoS maximal problem into two one-variable form subproblems, an algorithm named scheduling of comprehensive objectives for tasks with multitargets (SCOTT) is proposed. The SCOTT algorithm achieves the optimal offloading service solutions considering service metrics including delay, energy consumption, and economic cost. Extensive numerical simulations are carried out, which indicate that the proposed SCOTT algorithm can effectively achieve the optimal offloading solutions including node selection, task division, and transmission power for TNs with various service targets. Moreover, the universal applicability of the SCOTT algorithm is verified with case studies and numerical results.

Multi-criteria decision making for adaptive façade optimal design in varied climates: Energy, daylight, occupants’ comfort, and outdoor view analysis

Adaptive façades can enhance interior environmental quality and reduce building energy expenditure. To this end, counterbalancing numerous objectives must be considered during the early stage. However, there remain challenges in this high-performance access, leading to difficulties in obtaining the final design solution. Therefore, this study aims to establish a robust design decision-making process for adaptive façade systems in actual commercial building scales. Firstly, the parametric simulation was implemented in varied climates, simultaneously integrating daylight, energy, and occupants' view analysis. Five comprehensive objectives of maximising daylighting and view quality whilst minimising energy use, thermal discomfort, and visual discomfort were assessed, in which the most challenging criterion, outdoor view, was built precisely upon three all-inclusive facets: view context, view access, and view clarity. Then, the robust multi-criteria decision-making framework was applied to determine the unique optimal design for each selected region with preferences sensitivity analysis. Simulation results revealed that climatic conditions, materials, and configurations significantly impact adaptive façade performance. Meanwhile, optimal design results showed that building energy can save as much as 17% compared to the average design values. Although daylighting and outdoor view criteria meet current building standards, it suggested proper architectural layouts to accomplish the most occupants’ comfort. • The parametric simulation was integrated for adaptive façades in varied climates. • Maximising daylight and view whilst minimising energy use and occupants' discomfort. • The proposed outdoor view factor comprised view context, access, and clarity. • Multi-criteria decision making was investigated by preferences sensitivity analysis. • The optimal designs found complied with current building performance standards.

Heuristic DRP‐DG optimization strategy adopted for maximizing total social welfare in the real time Indian utility network

The energy sector is subjected to an increase in power demand year after year. This increase in energy demand will continue due to the need for energy for modern societies. The service providers should face this situation smartly using renewable energy sources to avoid the intermittent nature of these sources and the fluctuations in the demand. Demand response programs (DRP) can play a vital role in increasing the correlation between the loads and the available generation from renewable energy sources (RES). Modern power systems recommend the use of distributed generation (DG) sources to reduce the transmission losses, contingency, and cost of energy and to increase the system reliability, efficiency, and power system loadability. Optimal DR use in the DG can further improve its performance which is the main focus of this paper. Here, a novel DRP-DG strategy is introduced to size and allocate the DG units for minimum congestion in IEEE 33-bus benchmark power system and real Indian power system having 17 buses. The active involvement of the consumers in the DRP facilitates the ultimate objective of maximized total social welfare (TSW) with minimized generation costs. To justify the above multi-objective optimization, two stages of heuristic optimization are introduced in which the rules are fired in the primary stage for determining the optimal size of DG. Implementation of DRP for achieving comprehensive objective function is vindicated in the secondary stage. A real-time Indian utility network is considered and a trade-off output is realized using heuristic fuzzy logic (FL) and genetic algorithm (GA). The results obtained from using the proposed strategy proved its superiority in achieving substantial cost reduction and maximum TSW compared to other soft computing techniques.

Society and consumption

This article discusses themes identified as aims and objectives of Consumption and Society, reflecting on connections between the journal’s two titular concepts. It contrasts two distinct definitions and understandings of consumption, as purchase via market exchange and as the use of goods and services. It argues that the latter provides a more suitable and comprehensive object for social scientific study. Briefly reviewing the legacy of the cultural turn, the article outlines socio-cultural approaches emphasising symbolic, material and practical culture, and identifies some common failings. It considers the role of consumption in domination and social hierarchy in the context of escalating material inequality. Revisiting the relation between consumption and economic production, it commends some recent advances in the analysis of commodification while proposing a more encompassing ‘modes of provision’ framework. In association with an extended concept of social embeddedness, this offers an avenue for understanding macro-social change and the effects of current and historic inequalities. The concept of ‘controversy’ is introduced to understand normative and institutional contexts of mobilisation for change arising from contestation over consumption. The article concludes with remarks about theory and the difference that definitions make, the value of the concept of social embeddedness, and the analytic space beyond culture and markets.

PrepOSCE: A Virtual, Scalable Solution to Prepare Residents for Their OSCE Examination.

The Royal College Comprehensive Objective Examination in Neurology provides certification for Canadian neurologists and consists of a written examination and the Observed Structured Clinical Encounter (OSCE). The OSCE portion of the certification involves residents visiting several patient stations where they address case scenarios with an examiner. Unfortunately, residents lack exam preparation time due to demanding work hours. In response to resident needs, we created a novel, virtual preparation OSCE program - "prepOSCE" - and evaluated its efficacy. The prepOSCE program employed a proprietary virtual solution from CTC Communications Corp. Ten virtual sessions accommodated 70 residents totally. Seven Canadian physicians and two co-chairs created case scenarios for the stations. On session day, seven residents arrived in a virtual plenary room for briefing followed by assignment to a station by CTC. Residents then moved virtually through prepOSCE stations a different examiner and case scenario in each. Following their session, residents and evaluators were surveyed to capture experiences. The average program rating was 4.22 out of 5 (n = 36 residents of 70 residents who participated in the program) and 4.35 (n = 17 evaluators). Ninety-two percent of residents agreed or strongly agreed that they would recommend this program to their peers; they would like prepOSCE to continue next year; and the program was relevant and added value to their studies. The positive feedback received from prepOSCE participants indicates there is a need for a program like prepOSCE. This model has potential for expansion and it is hoped that specialties outside of neurology could benefit from a similar program.

Reactive Power and Voltage Optimization of New-Energy Grid Based on the Improved Flower Pollination Algorithm

In order to solve the reactive power and voltage control problem caused by the high proportion of new energy connected to the power grid, this paper takes the minimum voltage deviation, minimum network loss and maximum dynamic reactive power margin of the whole system as the comprehensive optimization objectives and establishes a reactive power and voltage optimization model by considering the reactive power regulation ability of SVC (Static Var Compensator) and new energy units. In view of the continuous and discrete variables in the model, the traditional continuous FPA (Flower Pollination Algorithm) is discretized to form an improved continuous-discrete hybrid FPA, and the tournament selection mechanism is adopted to speed up the convergence. Through the example analysis of the IEEE-39 bus system, the feasibility of the proposed reactive power and voltage optimal control method in the new energy grid is verified. Compared with GA (Genetic Algorithm), the results show that the improved FPA has high optimization accuracy, which is suitable for solving the reactive power and voltage optimization problem of the new energy grid.

A Heterogeneously Integrated Spiking Neuron Array for Multimode-Fused Perception and Object Classification.

Multimode-fused sensing in the somatosensory system helps people obtain comprehensive object properties and make accurate judgments. However, building such multisensory systems with conventional metal-oxide-semiconductor technology presents serious device integration and circuit complexity challenges. Here, a multimode-fused spiking neuron (MFSN) with a compact structure to achieve human-like multisensory perception is reported. The MFSN heterogeneously integrates a pressure sensor to process pressure and a NbOx -based memristor to sense temperature. Using this MFSN, multisensory analog information can be fused into one spike train, showing excellent data compression and conversion capabilities. Moreover, both pressure and temperature information are distinguished from fused spikes by decoupling the output frequencies and amplitudes, supporting multimodal tactile perception. Then, a 3 × 3 MFSN array is fabricated, and the fused frequency patterns are fed into a spiking neural network for enhanced tactile pattern recognition. Finally, a larger MFSN array is simulated for classifying objects with different shapes, temperatures, and weights, validating the feasibility of the MFSNs for practical applications. The proof-of-concept MFSNs enable the building of multimodal sensory systems and contribute to the development of highly intelligent robotics.

Inventory routing model for perishable products toward circular economy

This paper introduces integrated Returnable Transport Items (RTIs) and perishable products closed loop green inventory routing problem with uncertain demand and pickup. The simultaneously delivery of perishable products and pick of empty RTIs and perished products is considered. A chance constrained programming model for vendor managed inventory system in closed loop supply is modeled. A set of valid inequalities is proposed and their effect on solution time is analyzed. The proposed comprehensive objective function minimizes the sum of inventory, wastage, routing, and emission costs. We have used exact solution approach (CPLEX) and meta-heuristic approach (Differential Evolutionary algorithm) to solve the proposed model. The numerical results are performed to analyze the benefits of heterogeneous fleet and comprehensive objective functions. Further sensitivity analysis is performed to study the effect of unit carbon emission cost, shelf life, demand variability and service level.

Building a multi-objective optimization model for Sponge City projects

The design of Sponge City projects is a typical multi-objective optimization problem. Existing models are limited in the inclusion and clarification of the goals, constraints, and decision variables, and also in implementability terms. In this paper, we present a new model to accommodate real-world practices of the Sponge City. The model involves three dimensions of objectives, namely project cost, facility efficacy, and landscape quality, of which the last one is first to be included to constitute a comprehensive objective system of Sponge City projects; it uses three representative sponge facilities as decision variables and includes a comprehensive set of constraints that reflects hydrological, engineering, economical, and planning concerns. The model demands much less data input than rival models and can be solved efficiently by NSGA-II. An exemplary implementation of the model in a project in Beijing yields a variety of sub-optimums which would help Sponge City designers with different prioritizations of the objectives to conveniently choose the most suitable solution. The model constitutes a timely remedy to the lack of practical tools for Sponge City project designs, so as to accommodate the further and broader development of the Sponge City in China and the Third World in general.