Integrated strategies for chemotherapy cycles in nasopharyngeal carcinoma patients: Real-world data from two epidemic centers guiding decision-making

objective:Two cycles of induction chemotherapy(IC)followed by 2 cycles of platinum-based concurrent chemoradiotherapy(CCRT)(2IC+2CCRT)for locoregionally advanced nasopharyngeal carcinoma(LA-NPC)is widely adopted but not evidence-confirmed.This study aimed to determine the clinical value of 2IC+2CCRT regarding efficacy,toxicity and cost-effectiveness.Methods:This real-world study from two epidemic centers used propensity score matching(PSM)and inverse probability of treatment weighting(IPTW)analyses.The enrolled patients were divided into three groups based on treatment modality:Group A(2IC+2CCRT),Group B(3IC+2CCRT or 2IC+3CCRT)and Group C(3IC+3CCRT).Long-term survival,acute toxicities and cost-effectiveness were compared among the groups.We developed a prognostic model dividing the population into high-and low-risk cohorts,and survivals including overall survival(OS),progression-free survival(PFS),distant metastasis-free survival(DMFS)and locoregional relapse-free survival(LRRFS)were compared among the three groups according to certain risk stratifications.Results:Of 4,042 patients,1,175 were enrolled,with 660,419,and 96 included in Groups A,B and C,respectively.Five-year survivals were similar among the three groups after PSM and confirmed by IPTW.Grade 3-4 neutropenia and leukocytopenia were significantly higher in Groups C and B than in Group A(52.1%vs.41.5%vs.25.2%;41.7%vs.32.7%vs.25.0%)as were grade 3-4 nausea/vomiting and oral mucositis(29.2%vs.15.0%vs.6.1%;32.3%vs.25.3%vs.18.0%).Cost-effective analysis suggested that 2IC+2CCRT was the least expensive,while the health benefits were similar to those of the other groups.Further exploration showed that 2IC+2CCRT tended to be associated with a shorter PFS in high-risk patients,while 3IC+3CCRT potentially contributed to poor PFS in low-risk individuals,mainly reflected by LRRFS.Conclusions:In LA-NPC patients,2IC+2CCRT was the optimal choice regarding efficacy,toxicity and costeffectiveness;however,2IC+2CCRT and 3IC+3CCRT probably shortened LRRFS in high-and low-risk populations,respectively.

Decision-making of biomass ethanol fuel policy based on life cycle 3E assessment

To evaluate the environmental, economic, energy performance of biomass ethanol fuel in China and to support the decision-making of biomass ethanol energy policy, an assessment method of life cycle 3E (economy, environment, energy) was applied to the three biomass ethanol fuel cycle alternatives, which includes cassava-based, corn-based and wheat-based ethanol fuel. The assessments provide a comparison of the economical performance, energy efficiency and environmental impacts of the three alternatives. And the development potential of the three alternatives in China was examined. The results are very useful for the Chinese government to make decisions on the biomass ethanol energy policy, and some advises for the decision-making of Chinese government were given.

USING LIFE CYCLE ASSESSMENT METHODS TO GUIDE ARCHITECTURAL DECISION-MAKING FOR SUSTAINABLE PREFABRICATED MODULAR BUILDINGS

Within this work,life cycle assessment modeling is used to determine top design priorities and quantitatively inform sustainable design decision-making for a prefabricated modular building.A case-study life-cycle assessment was performed for a 5,000 ft2 prefabricated commercial building constructed in San Francisco,California,and scenario analysis was run examining the life cycle environmental impacts of various energy and material design substitutions,and a structural design change.Results show that even for a highly energy-efficient modular building,the top design priority is still minimizing operational energy impacts,since this strongly dominates the building life cycle’s environmental impacts.However,as an energy-efficient building approaches net zero energy,manufacturing-phase impacts are dominant,and a new set of design priorities emerges.Transportation and end-of-life disposal impacts were of low to negligible importance in both cases.

Multi-objective optimization and evaluation of supercritical CO_(2) Brayton cycle for nuclear power generation

The supercritical CO_(2) Brayton cycle is considered a promising energy conversion system for Generation IV reactors for its simple layout,compact structure,and high cycle efficiency.Mathematical models of four Brayton cycle layouts are developed in this study for different reactors to reduce the cost and increase the thermohydraulic performance of nuclear power generation to promote the commercialization of nuclear energy.Parametric analysis,multi-objective optimizations,and four decision-making methods are applied to obtain each Brayton scheme’s optimal thermohydraulic and economic indexes.Results show that for the same design thermal power scale of reactors,the higher the core’s exit temperature,the better the Brayton cycle’s thermo-economic performance.Among the four-cycle layouts,the recompression cycle(RC)has the best overall performance,followed by the simple recuperation cycle(SR)and the intercooling cycle(IC),and the worst is the reheating cycle(RH).However,RH has the lowest total cost of investment(C_(tot))of$1619.85 million,and IC has the lowest levelized cost of energy(LCOE)of 0.012$/(kWh).The nuclear Brayton cycle system’s overall performance has been improved due to optimization.The performance of the molten salt reactor combined with the intercooling cycle(MSR-IC)scheme has the greatest improvement,with the net output power(W_(net)),thermal efficiencyη_(t),and exergy efficiency(η_(e))improved by 8.58%,8.58%,and 11.21%,respectively.The performance of the lead-cooled fast reactor combined with the simple recuperation cycle scheme was optimized to increase C_(tot) by 27.78%.In comparison,the internal rate of return(IRR)increased by only 7.8%,which is not friendly to investors with limited funds.For the nuclear Brayton cycle,the molten salt reactor combined with the recompression cycle scheme should receive priority,and the gas-cooled fast reactor combined with the reheating cycle scheme should be considered carefully.

Evolutionary Decision-Making and Planning for Autonomous Driving Based on Safe and Rational Exploration and Exploitation

Decision-making and motion planning are extremely important in autonomous driving to ensure safe driving in a real-world environment.This study proposes an online evolutionary decision-making and motion planning framework for autonomous driving based on a hybrid data-and model-driven method.First,a data-driven decision-making module based on deep reinforcement learning(DRL)is developed to pursue a rational driving performance as much as possible.Then,model predictive control(MPC)is employed to execute both longitudinal and lateral motion planning tasks.Multiple constraints are defined according to the vehicle’s physical limit to meet the driving task requirements.Finally,two principles of safety and rationality for the self-evolution of autonomous driving are proposed.A motion envelope is established and embedded into a rational exploration and exploitation scheme,which filters out unreasonable experiences by masking unsafe actions so as to collect high-quality training data for the DRL agent.Experiments with a high-fidelity vehicle model and MATLAB/Simulink co-simulation environment are conducted,and the results show that the proposed online-evolution framework is able to generate safer,more rational,and more efficient driving action in a real-world environment.

Dynamic simulation analysis of molten salt reactor-coupled air-steam combined cycle power generation system

A nonlinear dynamic simulation model based on coordinated control of speed and flow rate for the molten salt reactor and combined cycle systems is proposed here to ensure the coordination and stability between the molten salt reactor and power system.This model considers the impact of thermal properties of fluid variation on accuracy and has been validated with Simulink.This study reveals the capability of the control system to compensate for anomalous situations and maintain shaft stability in the event of perturbations occurring in high-temperature molten salt tank outlet parameters.Meanwhile,the control system’s impact on the system’s dynamic characteristics under molten salt disturbance is also analyzed.The results reveal that after the disturbance occurs,the controlled system benefits from the action of the control,and the overshoot and disturbance amplitude are positively correlated,while the system power and frequency eventually return to the initial values.This simulation model provides a basis for utilizing molten salt reactors for power generation and maintaining grid stability.

Bicycle-related traumatic injuries: a retrospective study during COVID-19 pandemic

BACKGROUND:This study aimed to review bicycle-related injuries during the COVID-19 pandemic to assist with reinforcement or implementation of new policies for injury prevention.METHODS:This is a retrospective descriptive analysis of injuries sustained during cycling for patients 18 years old and above who presented to Singapore General Hospital from January to June 2021.Medical records were reviewed and consolidated.Descriptive analyses were used to summarize patient characteristics,and differences in characteristics subgrouped by triage acuity and discharge status were analyzed.RESULTS:The study included 272 patients with a mean age of 43 years and a male predominance(71.7%).Most presented without referrals(88.2%)and were not conveyed by ambulances(70.6%).Based on acuity category,there were 24(8.8%)Priority 1(P1)patients with 7 trauma activations,174(64.0%)and 74(27.2%)P2 and P3 patients respectively.The most common injuries were fractures(34.2%),followed by superficial abrasion/contusion(29.4%)and laceration/wound(19.1%).Thirteen(4.8%)patients experienced head injury and 85 patients(31.3%)were documented to be wearing a helmet.The majority occurred on the roads as traffic accidents(32.7%).Forty-two patients(15.4%)were admitted with a mean length of stay of 4.1 d and 17(6.3%)undergone surgical procedures.Out of 214(78.7%)discharged patients,no re-attendances or mortality were observed.In the subgroup analysis,higher acuity patients were generally older,with higher proportions of head injuries leading to admission.CONCLUSION:Our study highlights significant morbidities in bicycle-related injuries.There is also a high proportion of fractures in the young healthy male population.Injury prevention is paramount and we propose emphasizing helmet use and road user safety.

Effect of drying-wetting cycles on pore characteristics and mechanical properties of enzyme-induced carbonate precipitation-reinforced sea sand

Enzyme-induced carbonate precipitation(EICP)is an emanating,eco-friendly and potentially sound technique that has presented promise in various geotechnical applications.However,the durability and microscopic characteristics of EICP-treated specimens against the impact of drying-wetting(D-W)cycles is under-explored yet.This study investigates the evolution of mechanical behavior and pore charac-teristics of EICP-treated sea sand subjected to D-W cycles.The uniaxial compressive strength(UCS)tests,synchrotron radiation micro-computed tomography(micro-CT),and three-dimensional(3D)recon-struction of CT images were performed to study the multiscale evolution characteristics of EICP-reinforced sea sand under the effect of D-W cycles.The potential correlations between microstructure characteristics and macro-mechanical property deterioration were investigated using gray relational analysis(GRA).Results showed that the UCS of EICP-treated specimens decreases by 63.7% after 15 D-W cycles.The proportion of mesopores gradually decreases whereas the proportion of macropores in-creases due to the exfoliated calcium carbonate with increasing number of D-W cycles.The micro-structure in EICP-reinforced sea sand was gradually disintegrated,resulting in increasing pore size and development of pore shape from ellipsoidal to columnar and branched.The gray relational degree suggested that the weight loss rate and UCS deterioration were attributed to the development of branched pores with a size of 100-1000 m m under the action of D-W cycles.Overall,the results in this study provide a useful guidancee for the long-term stability and evolution characteristics of EICP-reinforced sea sand under D-W weathering conditions.

Durable K-ion batteries with 100% capacity retention up to 40,000 cycles

Currently,the major challenge in terms of research on K-ion batteries is to ensure that they possess satisfactory cycle stability and specific capacity,especially in terms of the intrinsically sluggish kinetics induced by the large radius of K+ions.Here,we explore high-performance K-ion half/full batteries with high rate capability,high specific capacity,and extremely durable cycle stability based on carbon nanosheets with tailored N dopants,which can alleviate the change of volume,increase electronic conductivity,and enhance the K+ion adsorption.The as-assembled K-ion half-batteries show an excellent rate capability of 468 mA h g^(−1) at 100 mA g^(−1),which is superior to those of most carbon materials reported to date.Moreover,the as-assembled half-cells have an outstanding life span,running 40,000 cycles over 8 months with a specific capacity retention of 100%at a high current density of 2000 mA g^(−1),and the target full cells deliver a high reversible specific capacity of 146 mA h g^(−1) after 2000 cycles over 2 months,with a specific capacity retention of 113%at a high current density of 500 mA g^(−1),both of which are state of the art in the field of K-ion batteries.This study might provide some insights into and potential avenues for exploration of advanced K-ion batteries with durable stability for practical applications.

Involvement of the ABA-and H_(2)O_(2)-Mediated Ascorbate-Glutathione Cycle in the Drought Stress Responses of Wheat Roots

Abscisic acid(ABA),hydrogen peroxide(H_(2)O_(2)) and ascorbate(AsA)–glutathione(GSH)cycle are widely known for their participation in various stresses.However,the relationship between ABA and H_(2)O_(2) levels and the AsA–GSH cycle under drought stress in wheat has not been studied.In this study,a hydroponic experiment was conducted in wheat seedlings subjected to 15%polyethylene glycol(PEG)6000–induced dehydration.Drought stress caused the rapid accumulation of endogenous ABA and H_(2)O_(2) and significantly decreased the number of root tips compared with the control.The application of ABA significantly increased the number of root tips,whereas the application of H_(2)O_(2) markedly reduced the number of root tips,compared with that under 15%PEG-6000.In addition,drought stress markedly increased the DHA,GSH and GSSG levels,but decreased the AsA levels,AsA/DHA and GSH/GSSG ratios compared with those in the control.The activities of the four enzymes in the AsA–GSH cycle were also markedly increased under drought stress,including glutathione reductase(GR),ascorbate peroxidase(APX),monodehydroascorbate reductase(MDHAR)and dehydroascorbate reductase(DHAR),compared with those in the control.However,the application of an ABA inhibitor significantly inhibited GR,DHAR and APX activities,whereas the application of an H_(2)O_(2) inhibitor significantly inhibited DHAR and MDHAR activities.Furthermore,the application of ABA inhibitor significantly promoted the increases of H_(2)O_(2) and the application of H_(2)O_(2) inhibitor significantly blocked the increases of ABA,compared with those under 15% PEG-6000.Taken together,the results indicated that ABA and H_(2)O_(2) probably interact under drought stress in wheat;and both of them can mediate drought stress by modulating the enzymes in AsA–GSH cycle,where ABA acts as the main regulator of GR,DHAR,and APX activities,and H_(2)O_(2) acts as the main regulator of DHAR and MDHAR activities.

有向图上基于层次树索引的最大cycle truss社区搜索

社区搜索旨在从信息网络中找出包含用户查询顶点的高内聚连通子图,cycle truss是一种基于cycle三角形的社区搜索模型,而现有的基于索引的cycle truss社区搜索方法存在索引空间大、搜索效率低、社区内聚性低的缺点。为了解决这一问题,提出一种基于层次树索引的最大cycle truss社区搜索方法。首先,提出了k-cycle truss分解算法,并引入了两个重要的概念:cycle三角连通与k-层次等价。基于k-层次等价设计了层次树索引TreeCIndex与表结构索引SuperTable,在此基础上,并基于这两个新的索引,提出了两个高效的cycle truss社区搜索算法。在4个真实数据集上与已有的基于TrussIndex与EquiTruss的社区搜索算法进行了比较,实验结果表明,TreeCIndex与SuperTable比TrussIndex与EquiTruss节省至少41.5%的空间,索引构建的时间节省8.2%至98.3%,且搜索最大cycle truss社区的效率分别高出了一个和两个数量级。

Toward Trustworthy Decision-Making for Autonomous Vehicles:A Robust Reinforcement Learning Approach with Safety Guarantees

While autonomous vehicles are vital components of intelligent transportation systems,ensuring the trustworthiness of decision-making remains a substantial challenge in realizing autonomous driving.Therefore,we present a novel robust reinforcement learning approach with safety guarantees to attain trustworthy decision-making for autonomous vehicles.The proposed technique ensures decision trustworthiness in terms of policy robustness and collision safety.Specifically,an adversary model is learned online to simulate the worst-case uncertainty by approximating the optimal adversarial perturbations on the observed states and environmental dynamics.In addition,an adversarial robust actor-critic algorithm is developed to enable the agent to learn robust policies against perturbations in observations and dynamics.Moreover,we devise a safety mask to guarantee the collision safety of the autonomous driving agent during both the training and testing processes using an interpretable knowledge model known as the Responsibility-Sensitive Safety Model.Finally,the proposed approach is evaluated through both simulations and experiments.These results indicate that the autonomous driving agent can make trustworthy decisions and drastically reduce the number of collisions through robust safety policies.

Orientation and Decision-Making for Soccer Based on Sports Analytics and AI:A Systematic Review

Due to ever-growing soccer data collection approaches and progressing artificial intelligence(AI) methods, soccer analysis, evaluation, and decision-making have received increasing interest from not only the professional sports analytics realm but also the academic AI research community. AI brings gamechanging approaches for soccer analytics where soccer has been a typical benchmark for AI research. The combination has been an emerging topic. In this paper, soccer match analytics are taken as a complete observation-orientation-decision-action(OODA) loop.In addition, as in AI frameworks such as that for reinforcement learning, interacting with a virtual environment enables an evolving model. Therefore, both soccer analytics in the real world and virtual domains are discussed. With the intersection of the OODA loop and the real-virtual domains, available soccer data, including event and tracking data, and diverse orientation and decisionmaking models for both real-world and virtual soccer matches are comprehensively reviewed. Finally, some promising directions in this interdisciplinary area are pointed out. It is claimed that paradigms for both professional sports analytics and AI research could be combined. Moreover, it is quite promising to bridge the gap between the real and virtual domains for soccer match analysis and decision-making.

A Review on Technologies for the Use of CO2 as a Working Fluid in Refrigeration and Power Cycles

The use of carbon dioxide as a working fluid has been the subject of extensive studies in recent years, particularly in the field of refrigeration where it is at the heart of research to replace CFC and HCFC. Its thermodynamic properties make it a fluid of choice in the efficient use of energy at low and medium temperatures in engine cycles. However, the performance of transcritical CO2 cycles weakens under high temperature and pressure conditions, especially in refrigeration systems;On the other hand, this disadvantage becomes rather interesting in engine cycles where CO2 can be used as an alternative to the organic working fluid in small and medium-sized electrical systems for low quality or waste heat sources. In order to improve the performance of systems operating with CO2 in the field of refrigeration and electricity production, research has made it possible to develop several concepts, of which this article deals with a review of the state of the art, followed by analyzes in-depth and critical of the various developments to the most recent modifications in these fields. Detailed discussions on the performance and technical characteristics of the different evolutions are also highlighted as well as the factors affecting the overall performance of the systems studied. Finally, perspectives on the future development of the use of CO2 in these different cycles are presented.

Ethical Decision-Making Framework Based on Incremental ILP Considering Conflicts

Humans are experiencing the inclusion of artificial agents in their lives,such as unmanned vehicles,service robots,voice assistants,and intelligent medical care.If the artificial agents cannot align with social values or make ethical decisions,they may not meet the expectations of humans.Traditionally,an ethical decision-making framework is constructed by rule-based or statistical approaches.In this paper,we propose an ethical decision-making framework based on incremental ILP(Inductive Logic Programming),which can overcome the brittleness of rule-based approaches and little interpretability of statistical approaches.As the current incremental ILP makes it difficult to solve conflicts,we propose a novel ethical decision-making framework considering conflicts in this paper,which adopts our proposed incremental ILP system.The framework consists of two processes:the learning process and the deduction process.The first process records bottom clauses with their score functions and learns rules guided by the entailment and the score function.The second process obtains an ethical decision based on the rules.In an ethical scenario about chatbots for teenagers’mental health,we verify that our framework can learn ethical rules and make ethical decisions.Besides,we extract incremental ILP from the framework and compare it with the state-of-the-art ILP systems based on ASP(Answer Set Programming)focusing on conflict resolution.The results of comparisons show that our proposed system can generate better-quality rules than most other systems.

Long-Cycle Lithium Batteries with LiNi_(0.8)Co_(0.1)Mn_(0.1)O_(2) Cathodes above 4.5 V Enabled by Uniform Coating of Nanosized Garnet Electrolytes

The pursuit of high-energy cathode materials has been focused on raising the charging cutoff voltage of nickel (Ni)-rich layered oxide cathode such as LiNi_(0.8)Co_(0.1)Mn_(0.1)O2 (NCM811). However, the NCM811 suffers from rapid capacity fading upon cycling at cutoff voltage higher than 4.5 V, owing to their structural degradation and labile surface reactivity. Surface-coating with solid electrolytes has been recognized as an effective method to mitigate the performance failure of NCM811 at high voltage. Herein, the nano-sized Li_(6.4)La_(3)Ta_(0.6)Zr_(1.4)O_(12) (LLZTO) is uniformly coated on the surface of single-crystal NCM811 particles, accompanied with the long-range Ta^(5+) diffusion into the transition metal layer of NCM811 lattice. It is revealed that the LLZTO coating can not only inhibit the surface reactions of NCM811 with liquid electrolytes but also play an important role in suppressing the bulk microcracking within the NCM811 particles. The incorporation of Ta^(5+) ion expands the lattice spacing and thereby improves the homogeneity of the Li^(+) diffusion in the single-crystal NCM811, which alleviates the mechanical strain and intragranular cracks caused by nonuniform phases-transformation at high charging voltage. The synergy of surface protection and structural stabilization realized by LLZTO coating enables the NCM811-based lithium batteries to achieve a remarkable electrochemical performance. Typically, LLZTO coated NCM811 delivers a high reversible specific capacity of 202.1 mAh⋅g^(−1) with an excellent capacity retention as high as 70% over 1000 cycles upon charging to 4.5 V at 1 C.

Stroke Risk Assessment Decision-Making Using a Machine Learning Model:Logistic-AdaBoost

Stroke is a chronic cerebrovascular disease that carries a high risk.Stroke risk assessment is of great significance in preventing,reversing and reducing the spread and the health hazards caused by stroke.Aiming to objectively predict and identify strokes,this paper proposes a new stroke risk assessment decision-making model named Logistic-AdaBoost(Logistic-AB)based on machine learning.First,the categorical boosting(CatBoost)method is used to perform feature selection for all features of stroke,and 8 main features are selected to form a new index evaluation system to predict the risk of stroke.Second,the borderline synthetic minority oversampling technique(SMOTE)algorithm is applied to transform the unbalanced stroke dataset into a balanced dataset.Finally,the stroke risk assessment decision-makingmodel Logistic-AB is constructed,and the overall prediction performance of this new model is evaluated by comparing it with ten other similar models.The comparison results show that the new model proposed in this paper performs better than the two single algorithms(logistic regression and AdaBoost)on the four indicators of recall,precision,F1 score,and accuracy,and the overall performance of the proposed model is better than that of common machine learning algorithms.The Logistic-AB model presented in this paper can more accurately predict patients’stroke risk.

Determination of the best materials for development and designing product using a multi-criteria decision-making

Purpose–Material selection,driven by wide and often conflicting objectives,is an important,sometimes difficult problem in material engineering.In this context,multi-criteria decision-making(MCDM)methodologies are effective.An approach of MCDM is needed to cater to criteria of material assortment simultaneously.More firms are now concerned about increasing their productivity using mathematical tools.To occupy a gap in the previous literature this research recommends an integrated MCDM and mathematical Bi-objective model for the selection of material.In addition,by using the Technique for Order Preference by Similarity to Ideal Solution(TOPSIS),the inherent ambiguities of decision-makers in paired evaluations are considered in this research.It goes on to construct a mathematical bi-objective model for determining the best item to purchase.Design/methodology/approach–The entropy perspective is implemented in this paper to evaluate the weight parameters,while the TOPSIS technique is used to determine the best and worst intermediate pipe materials for automotive exhaust system.The intermediate pipes are used to join the components of the exhaust systems.The materials usually used to manufacture intermediate pipe are SUS 436LM,SUS 430,SUS 304,SUS 436L,SUH 409 L,SUS 441 L and SUS 439L.These seven materials are evaluated based on tensile strength(TS),hardness(H),elongation(E),yield strength(YS)and cost(C).A hybrid methodology combining entropy-based criteria weighting,with the TOPSIS for alternative ranking,is pursued to identify the optimal design material for an engineered application in this paper.This study aims to help while filling the information gap in selecting the most suitable material for use in the exhaust intermediate pipes.After that,the authors searched for and considered eight materials and evaluated them on the following five criteria:(1)TS,(2)YS,(3)H,(4)E and(5)C.The first two criteria have been chosen because they can have a lot of influence on the behavior of the exhaust intermediate pipes,on their performance and on the cost.In this structure,the weights of the criteria are calculated objectively through the entropy method in order to have an unbiased assessment.This essentially measures the quantity of information each criterion contribution,indicating the relative importance of these criteria better.Subsequently,the materials were ranked using the TOPSIS method in terms of their relative performance by measuring each material from an ideal solution to determine the best alternative.The results show that SUS 309,SUS 432L and SUS 436 LM are the first three materials that the exhaust intermediate pipe optimal design should consider.Findings–The material matrix of the decision presented in Table 3 was normalized through Equation 5,as shown in Table 5,and the matrix was multiplied with weighting criteriaß_j.The obtained weighted normalized matrix V_ij is presented in Table 6.However,the ideal,worst and best value was ascertained by employing Equation 7.This study is based on the selection of material for the development of intermediate pipe using MCDM,and it involves four basic stages,i.e.method of translation criteria,screening process,method of ranking and search for methods.The selection was done through the TOPSIS method,and the criteria weight was obtained by the entropy method.The result showed that the top three materials are SUS 309,SUS 432L and SUS 436 LM,respectively.For the future work,it is suggested to select more alternatives and criteria.The comparison can also be done by using different MCDM techniques like and Choice Expressing Reality(ELECTRE),Decision-Making Trial and Evaluation Laboratory(DEMATEL)and Preference Ranking Organization Method for Enrichment Evaluation(PROMETHEE).Originality/value–The results provide important conclusions for material selection in this targeted application,verifying the employment of mutual entropy-TOPSIS methodology for a series of difficult engineering decisions in material engineering concepts that combine superior capacity with better performance as well as cost-efficiency in various engineering design.

The Impact of Network Topologies and Radio Duty Cycle Mechanisms on the RPL Routing Protocol Power Consumption

The Internet of Things(IoT)has witnessed a significant surge in adoption,particularly through the utilization of Wireless Sensor Networks(WSNs),which comprise small internet-connected devices.These deployments span various environments and offer a multitude of benefits.However,the widespread use of battery-powered devices introduces challenges due to their limited hardware resources and communication capabilities.In response to this,the Internet Engineering Task Force(IETF)has developed the IPv6 Routing Protocol for Low-power and Lossy Networks(RPL)to address the unique requirements of such networks.Recognizing the critical role of RPL in maintaining high performance,this paper proposes a novel approach to optimizing power consumption.Specifically,it introduces a developed sensor motes topology integrated with a Radio Duty Cycling(RDC)mechanism aimed at minimizing power usage.Through rigorous analysis,the paper evaluates the power efficiency of this approach through several simulations conducted across different network topologies,including random,linear,tree,and elliptical topologies.Additionally,three distinct RDC mechanisms—CXMAC,ContikiMAC,and NullRDC—are investigated to assess their impact on power consumption.The findings of the study,based on a comprehensive and deep analysis of the simulated results,highlight the efficiency of ContikiMAC in power conservation.This research contributes valuable insights into enhancing the energy efficiency of RPL-based IoT networks,ultimately facilitating their widespread deployment and usability in diverse environments.

Parametric Energy and Economic Analysis ofModified Combined Cycle Power Plant with Vapor Absorption and Organic Rankine Cycle

To meet the escalating electricity demand and rising fuel costs,along with notable losses in power transmission,exploring alternative solutions is imperative.Gas turbines demonstrate high efficiency under ideal International Organization for Standardization(ISO)conditions but face challenges during summer when ambient temperatures reach 40℃.To enhance performance,the proposal suggests cooling inlet air by 15℃using a vapor absorption chiller(VAC),utilizing residual exhaust gases from a combined cycle power plant(CCPP)to maximize power output.Additionally,diverting a portion of exhaust gases to drive an organic Rankine cycle(ORC)for supplementary power generation offers added efficiency.This integrated approach not only boosts power output but alsominimizes environmental impact by repurposing exhaust gases for additional operations.This study presents a detailed energy and economic analysis of a modified combine cycle power plant,in Kotri,Pakistan.R600A is used as organic fuel for the ORC while LiBr-H2O solution is used for the VAC.Two performance parameters,efficiency and energy utilization factor,Four energetic parameters,Work output of ORC,modified CCPP,original CCPP and cooling rate,and one economics parameter,payback period were examined under varying ambient conditions and mass fraction of exhaust gases from outlet of a gas turbine(ψ).A parametric investigation was conducted within the temperature range of 18℃to 50℃,relative humidity between 70%and 90%,and theψranging from 0 to 0.3.The findings reveal that under elevated ambient conditions(40℃,90%humidity)withψat 0,the Energy Utilization Factor(EUF)exceeds 60%.However,the ORC exhibits a low work output of 100KWalongside a high cooling load of 29,000 kW.Conversely,the modified system demonstrates an augmented work output of approximately 81,850 KWcompared to the original system’s 78,500KW.Furthermore,the integration of this systemproves advantageous across all metrics.Additionally,the payback period of the system is contingent on ambient conditions,with lower conditions correlating to shorter payback periods and vice versa.