Characteristics of Infertile Clientele Attending a Public in Vitro Fertilization Clinic: Appraising Priorities in a Low-Income Country

Introduction: Infertilityaffects one in six couples, and it is an important public health issue largely due to thepervasive effects on the emotional and psychological wellbeing of affected couples. In many developing nations emphasis is placed on childbirth and inability to fulfill this role can be very distressing. There is an unmet need for assisted reproductive technology (ART) in many developing countries and where facilities exist, they are mostly privately owned, expensive and concentrated in urban areas. To bridge this gap, public fertility clinics have been established to provide subsidized care. Evaluating the characteristics and peculiarities of clientele presenting at these public facilities will aid planning and prioritization of care. Methodology: A descriptive retrospective study of 116 infertile patients presenting to the fertility clinic of the University College Hospital, Ibadan, Nigeria from inception on the 14th of February 2019 and 31st of December 2022.Data was analyzed using the Statical Package for Social Sciences (IBM, SPSS, New York) version 23. Descriptive statistics were used to summarize the results which were presented with the aid of bar charts and frequency tables. Result: The mean age of the patients was 40.70 ± 6.62 years. Post-menopausal patients accounted for about one-fifth of the study population while 80.2% (93 women) were older than 35 years. The mean duration of infertility was 9.39 ± 6.11years and nine patients (7.8%) had a duration greater than 2 decades. Secondary infertility occurred in 67.2% of the women. Twenty-nine women (25%) had undergone myomectomy prior to presentation. Hypertension (11.2%) was the most prevalent comorbidity. Nineteen patients (16.4%) had used contraceptives in the past with the male condom (36.8%)being the most preponderant. Sixty-seven patients had experienced pregnancy losses before 28 weeks of gestation while just 16 patients (13.8%) had undergone ART, and none was successful. Conclusion: Secondary infertility was the prevalent type of infertility and may not be unconnected with the low contraceptive usage and high risk of sexually transmitted infection. Late presentation coupled with a large proportion of post-menopausal clientele suggests delayed health-seeking behavior most probably due to the prohibitive cost of ART. The need to streamline services offered in public fertility clinics is paramount in low-income countries grappling with scarce resources. A pragmatic approach will involve the provision of low-cost ART, while enhancing gamete donation programs through the implementation of gamete sharing policies. This will invariably bridge the unmet need and skewed access to ART in developing countries.

Shape Analysis of Agricultural Parcels for Land Consolidation Priorities in Tekirdag Province,Turkey

Shape irregularity,a sub-factor of parcel fragmentation is a problem that hinders sustainable agriculture and is solved using land consolidation projects.Determination of the parcel shape degree contributes significantly to spatial prioritization where there is also a high probability of achieving positive effects of consolidation projects.This study aims to determine the shape degree of the agricultural parcels both at singular and rural county scales in Tekirdag Province,Turkey in 2020 by combining the parcel shape index(PSI) with the minimum bounding geometry index(MBG) to improve parcel scores.Hot-spot zones of the highly irregular and near optimum parcels were also determined using Getis-Ord G_(i)^(*) statistic.The parcel degrees were classified into four categories,namely highly irregular,irregular,regular and near optimum.The obtained unweighted scores of the parameters exhibit deviations from the expected values.After weighting by pairwise comparison,the values approached ideal scores.Among 346 740 parcels,53% were highly irregular and irregular and 47% were regular and near optimum shapes after weighting whereas these were 70% and 30%,respectively before weighting.The average parcel degree of 63 rural counties was regular while the average parcel degree of the remaining 264 rural counties was irregular.The combined use of PSI and MBG index improved the correctness of the parcel shape score.It could be suggested to use as a tool in land consolidation prioritization.

Effect of ZrC Modified Graphite on Structure and Properties of Low-carbon Al_(2)O_(3)-C Refractories

To address the issues of reduced performance and shortened lifespan during the low-carbonizating process of Al_(2)O_(3)-C refractories,nano-crystalline ZrC modified graphite was prepared using Zr powder and flake graphite as raw materials,with NaCl and NaF mixed salt serving as the medium.The flake graphite was gradually replaced by ZrC modified graphite in the preparation of Al_(2)O_(3)-C refractories,and its impact on the material’s structure and properties was investigated.The results indicate that,compared to samples with only flake graphite,the introduction of 1 mass%to 5 mass%nano-crystalline ZrC modified graphite can significantly enhance the mechanical performance of low-carbon Al_(2)O_(3)-C refractories.When 5 mass%ZrC modified graphite is added,the mechanical properties of the samples are optimal,with the cold modulus of rupture and elastic modulus reaching 22.5 MPa and 65.0 GPa,respectively.

Performance Evaluation of Low-Carbon and Clean Transformation of China’s Coal Economy

In China,the oversupply of coal occurred in 2009,and from that year onwards,China’s coal economy began a low-carbon and clean transformation.Evaluating transformation performance is the research goal of this paper.The data collection for this paper includes data on deep processing of Chinese coal products from 2009 to 2020,as well as data on asset structure evolution and financial performance of 34 listed companies in the Chinese coal mining.Entropy value method is used to calculate the entropy value of low-carbon transformation,and the regression analysis is used to study the performance of cleaner transformation,the conclusion is as follows:(1)From 2009 to 2020,in China’s total energy consumption,coal consumption accounted for 71.6%in 2009 and 56.8%in 2020,the goals set by the state have been achieved.(2)The national goal of reducing the proportion of coal consumption and reducing carbon emissions has forced the transformation of deep processing of coal products.The transformation of coal enterprises towards low-carbon and clean production has achieved remarkable results.(3)From 2009 to 2020,the non coal industry income of 34 listed companies in China’s coal mining industry increased by 8.21%annually.At the same time,the asset structure was adjusted,and nearly 80%of the asset structure evolution showed an orderly development trend.(4)The regression analysis results show that the entropy value of coal deep processing products and the entropy value of asset structure adjustment are significantly related to transformation performance.The paper proposes to summarize the successful experience of China’s coal energy economic transformation,lay a foundation for achieving the carbon peak and carbon neutral goals in the future,further increase the intensity of coal deep processing,increase the proportion of clean energy in total energy consumption,and strive to control asset operation towards the goal of increasing the proportion of non coal industry income.

Plasma-electrified up-carbonization for low-carbon clean energy

Low-value,renewable,carbon-rich resources,with different biomass feedstocks and their derivatives as typical examples,represent virtually inexhaustive carbon sources and carbon-related energy on Earth.Upon conversion to higher-value forms(referred to as“up-carbonization”here),these abundant feedstocks provide viable opportunities for energy-rich fuels and sustainable platform chemicals production.However,many of the current methods for such up-carbonization still lack sufficient energy,cost,and material efficiency,which affect their economics and carbon-emissions footprint.With external electricity precisely delivered,discharge plasmas enable many stubborn reactions to occur under mild conditions,by creating locally intensified and highly reactive environments.This technology emerges as a novel,versatile technology platform for integrated or stand-alone conversion of carbon-rich resources.The plasma-based processes are compatible for integration with increasingly abundant and cost-effective renewable electricity,making the whole conversion carbon-neutral and further paving the plasma-electrified upcarbonization to be performance-,environment-,and economics-viable.Despite the chief interest in this emerging area,no review article brings together the state-of-the-art results from diverse disciplines and underlies basic mechanisms and chemistry underpinned.As such,this review aims to fill this gap and provide basic guidelines for future research and transformation,by providing an overview of the application of plasma techniques for carbon-rich resource conversion,with particular focus on the perspective of discharge plasmas,the fundamentals of why plasmas are particularly suited for upcarbonization,and featured examples of plasma-enabled resource valorization.With parallels drawn and specificity highlighted,we also discuss the technique shortcomings,current challenges,and research needs for future work.

The Low-Carbon Transition of Energy Systems:A Bibliometric Review from an Engineering Management Perspective

As a major solution to climate change,the low-carbon transition of energy systems has received growing attention in the past decade.This paper presents a bibliometric review of the literature on the low-carbon transition of energy systems from an engineering management perspective.First,the definition and boundaries of the energy system transition are clarified,covering transformation of the energy structure,decarbonization of fossil fuel utilization,and improvement in energy efficiency.Second,a systematic search of the related literature and a bibliometric analysis are conducted to reveal the research trends.It is found that the number of related publications has been growing exponentially during the past decade,with researchers from China,the United Kingdom,the United States,Germany,and the Netherlands comprising the majority of authors.Related studies with interdisciplinary characteristics appear in journals focusing on energy engineering,environmental science,and social science related to energy issues.Four major research themes are identified by clustering the existing literature:(1)low-carbon transition pathways with different spatiotemporal scales and transition constraints;(2)low-carbon technology diffusion with a focus on renewable energy technologies,pollution control technologies,and other technologies facilitating the energy transition;(3)infrastructure network planning for energy systems covering various sectors and regions;and(4)transition-driving mechanisms from the political,economic,social,and natural perspectives.These four topics play distinct but mutually supportive roles in facilitating the low-carbon transition of energy systems,and require more in-depth research on designing resilient low-carbon transition pathways with coordinated goals,promoting low-carbon technologies with cost-effective and reliable infrastructure network deployment,and balancing multi-level risks in various systems.Finally,business models,nongovernment actors,energy justice,deep decarbonization,and zero-energy buildings are recognized as emerging hot topics.

An Intelligent Control Method for the Low-Carbon Operation of Energy-Intensive Equipment

Based on an analysis of the operational control behavior of operation experts on energy-intensive equipment,this paper proposes an intelligent control method for low-carbon operation by combining mechanism analysis with deep learning,linking control and optimization with prediction,and integrating decision-making with control.This method,which consists of setpoint control,self-optimized tuning,and tracking control,ensures that the energy consumption per tonne is as low as possible,while remaining within the target range.An intelligent control system for low-carbon operation is developed by adopting the end-edge-cloud collaboration technology of the Industrial Internet.The system is successfully applied to a fused magnesium furnace and achieves remarkable results in reducing carbon emissions.

Dynamic decision and its complex dynamics analysis of low-carbon supply chain considering risk-aversion under carbon tax policy

This study establishes a low-carbon supply chain game model under the centralized decision situation and the decentralized decision situation considering the manufacturer risk-aversion behavior, and discusses the influence of the manufacturer risk-aversion behavior on the optimal decision, profit, coordination, and complex dynamics of the supply chain. We find that comparing with the risk-neutral decentralized decision, the increase of manufacturer's risk tolerance attitude can narrow the gap between the supply chain profit and the centralized decision, but it will further reduce the carbon emission reduction level. The increase of risk tolerance of the manufacturer and carbon tax will narrow the stable region of the system. Under this situation, the manufacturer should carefully adjust parameters to prevent the system from losing stability,especially the adjustment parameters for carbon emission reduction level. When the system is in a chaotic state, the increase of carbon tax rate makes the system show more complex dynamic characteristics. Under the chaotic state, it is difficult for the manufacturer to make correct price decision and carbon emission reduction strategy for the next period, which damages its profit, but increases the profit of the retailer and the supply chain. Finally, the carbon emission reduction cost-sharing contract is proposed to improve the carbon emission reduction level and the supply chain efficiency, achieving Pareto improvement. The stability region of the system is larger than that in the centralized decision situation, but the increase of the cost sharing coefficient will reduce the stability of the system in the decentralized decision-making situation.

Core Competitiveness Construction of Clothing Brands in Low-Carbon Economy

The climate issue has become an environmental concern for all sectors of the world and the low-carbon economy has thus become a new economic development model to combat climate change.With the development of low-carbon economy era,the textile and clothing industry plays an important role in stabilizing the development of low-carbon economy and society,and China has put forward the development requirements of low-carbon transformation for the textile and clothing industry,and also it has an important strategic value to promote the high-quality development of low-carbon economy and society,and the construction of brands’ core competitiveness is an inevitable choice for clothing brands in the face of the new form of international competition.As a result,the evaluation indicator of clothing brands’ core competitiveness in the low-carbon economy is used to measure the core competitiveness of clothing brands.Based on the corresponding verification results obtained by analytic hierarchy process(AHP) analysis,it can guide the low-carbon development of the clothing industry,thus proposing a more reasonable way to build the core competitiveness of clothing brands.It can promote the low-carbon transformation and upgrading of the clothing industry,effectively increase the market share of clothing brands,and promote the high-quality development of clothing brands.

Risk preferences and the low-carbon agricultural technology adoption:Evidence from rice production in China

Climate change which is mainly caused by carbon emissions is a global problem affecting the economic development and well-being of human society.Low-carbon agriculture is of particular significance in slowing down global warming and reaching the goal of“carbon peak and carbon neutrality”.Therefore,taking straw incorporation as an example,this paper aims to investigate the impact of risk preferences on farmers’low-carbon agricultural technology(LCAT)adoption.Based on a two-phase micro-survey data of 1038 rice farmers in Jiangsu,Jiangxi,and Hunan provinces,this paper uses experimental economics methods to measure farmers’risk aversion and loss aversion to obtain the real risk preferences information of the farmers.We also explore the data to examine the actual LCAT adoption behavior of farmers.The results revealed that both risk aversion and loss aversion significantly inhibit farmers’LCAT adoption:more risk-averse or more loss-averse farmers are less likely to adopt LCAT.It is further found that crop insurance,farm scale and governmental regulations can alleviate the negative impact of risk aversion and loss aversion on farmers’LCAT adoption.Therefore,we propose that local governments need to promote low-carbon agricultural development by propagating the benefits of LCAT,extending crop insurance,promoting appropriate scale operations,and strengthening governmental regulations to promote farmers’LCAT adoption.

Cold plasma-activated Cu-Co catalysts with CN vacancies for enhancing CO_(2)electroreduction to low-carbon alcohol

Electrocatalytic CO_(2)reduction reaction to low-carbon alcohol is a challenging task,especially high selectivity for ethanol,which is mainly limited by the regulation of reaction intermediates and subsequent C–C coupling.A Cu-Co bimetallic catalyst with CN vacancies is successfully developed by H_(2)cold plasma toward a high-efficiency CO_(2)RR into low-carbon alcohol.The Cu-Co PBA-V_(CN)(Prussian blue analogues with CN vacancies)electrocatalyst yields methanol and ethanol as major products with a total low-carbon alcohol FE of 83.8%(methanol:39.2%,ethanol:44.6%)at-0.9 V vs.RHE,excellent durability(100 h)and a small onset potential of-0.21 V.ATR-SEIRAS(attenuated total internal reflection surface enhanced infrared absorption spectroscopy)and DFT(density functional theory)reveal that the steric hindrance of V_(CN)can enhance the CO generation from*COOH,and the C–C coupling can also be increased by CO spillover on uniformly dispersed Cu atoms.This work provides a strategy for the design and preparation of electrocatalysts for CO_(2)RR into low-carbon alcohol products and highlights the impact of catalyst steric hindrance to catalytic performance.

Prioritizing the efforts:lived experiences of family when taking care of people with cancer

Objective:Cancer has one of the highest disease mortality rates.Families are very important in the treatment of people with cancer.By using a phenomenological design,this study aimed to explore the experience of families in caring for a person with cancer and to identify the needs of these families.Methods:First,eight interviews were under taken with family members selected through a purposive sampling method.Then,another three interviews were conducted for data validation.The collected data were analyzed using the framework method of analysis.Results:The core theme,“Prioritizing the efforts:Being aware of the best we could do for our family,”reflected family’s experiences of caring for a person with cancer and was underpinned by five themes:“Decisions to make,”“Keeping up the good support,”“Acknowledging the others’contributions,”“Assisting my family to alleviate the disease,”and“Adapting to the current situation.”Conclusions:The results suggest that building mutual trust and communication between family and healthcare professionals is vital in decision-making for people with cancer.Family may also work with the person in fulfilling their needs,without disregarding the needs of the family.When suppor ting the needs of people with diabetes,the family requires appropriate information,and thus,healthcare professionals wisely select which information can help the family make a decision regarding the treatment.After administering the treatment and providing information for people with cancer and their family,asking for feedback is required for evaluation.

Boundedness and liveness enforcement for labeled Petri nets using transition priority

This paper deals with the supervisory control problem of discrete event systems modeled by labeled Petri nets. The system is originally unbounded. First, the solvability of the problem is confirmed. A necessary condition is given and proven for the existence of a feasible priority-based controller based on the notions of liveness and transition invariants. Next, a cyclic behavior graph is constructed, which shows the reachable markings that guarantee the maximum liveness of the system within a given bound vector. Finally, an on-line control strategy is proposed to enforce boundedness and liveness to the given system by appending priority relations to transitions. The dynamic priority relation changes flexibly according to the current state of the system and enforces the system evolving in a bounded and live manner. In addition, numerical examples are studied to verify the validity of the proposed approach that remains the structure of the plant net and is efficient for on-line control.

Prevalence of Some World Health Organization Priority Organisms from an Abattoir at Kwata, Anambra State, Nigeria

The abattoir is one of the important sectors in the food industry, therefore the need for close monitoring of everything concerning it to minimize microbial contamination. The aim of the study is to identify bacteria listed as WHO priority organisms associated with meat from Kwata abattoir in Awka, Anambra state. The study was carried out over a three (3) months period from September to December 2022. Thirteen samples were collected from the floor, table, water, meat, knife and soil in the abattoir. The samples were cultured using streak and spread plate methods on MacConkey and Cetrimide agar. The isolates were identified with the following biochemical tests: catalase, oxidase, citrate and indole tests. Ampiclox levofloxacin, gentamicin, ofloxacin impenem ceftraixone, cefixime, cefuroxime and nitrofurantoin were used for sensitivity test following Kirby Bauer disc diffusion method and biofilm formation was determined using the tube method. The 75 isolates obtained were identified as follows;29.3% E. coli, 26.7% Klebsiella spp., 16% Proteus spp., and 28% Pseudomonas spp. The result of antibiotics sensitivity test interpreted using the European Committee on Antimicrobial Susceptibility Testing (EUCAST) breakpoints showed that (98%) of the isolates were resistant to the antibiotics used. Test for biofilm formation with 52 isolates showed 31 strong, 12 moderate and 9 weak biofilm formers. The result of this study confirms the presence of bacteria contaminants within the WHO priority list in the abattoir, as such there is need for improved handling of animals. Slaughtering, cleaning and distribution of meat should be done using aseptic procedures. .

Impact of minimalism on consumers’ low-carbon innovation behavior: Interactive role of quantitative behavior

Minimalism has become a new consumer trend that can guide low-carbon innovation behaviors.This study uses two experiments and one survey to explore the mechanisms underlying the relationships among minimalism,quantitative behavior,and low-carbon innovation behavior.The results show that(1)minimalism can positively influence consumers’low-carbon innovation behavior;(2)the interactive effect of minimalist and quantitative behavior on low-carbon innovation behavior is significant;and(3)meaning in life can play a significant mediating role in the relationship between minimalism and low-carbon innovation behavior.Finally,corresponding strategies for theory and management practices are proposed.

Priority Detector and Classifier Techniques Based on ML for the IoMT

Emerging telemedicine trends,such as the Internet of Medical Things(IoMT),facilitate regular and efficient interactions between medical devices and computing devices.The importance of IoMT comes from the need to continuously monitor patients’health conditions in real-time during normal daily activities,which is realized with the help of various wearable devices and sensors.One major health problem is workplace stress,which can lead to cardiovascular disease or psychiatric disorders.Therefore,real-time monitoring of employees’stress in the workplace is essential.Stress levels and the source of stress could be detected early in the fog layer so that the negative consequences can be mitigated sooner.However,overwhelming the fog layer with extensive data will increase the load on fog nodes,leading to computational challenges.This study aims to reduce fog computation by proposing machine learning(ML)models with two phases.The first phase of theMLmodel assesses the priority of the situation based on the stress level.In the second phase,a classifier determines the cause of stress,which was either interruptions or time pressure while completing a task.This approach reduced the computation cost for the fog node,as only high-priority records were transferred to the fog.Low-priority records were forwarded to the cloud.Four MLapproaches were compared in terms of accuracy and prediction speed:Knearest neighbors(KNN),a support vector machine(SVM),a bagged tree(BT),and an artificial neural network(ANN).In our experiments,ANN performed best in both phases because it scored an F1 score of 99.97% and had the highest prediction speed compared with KNN,SVM,and BT.

A low-carbon economic dispatch model for electricity market with wind power based on improved ant-lion optimisation algorithm

Introducing carbon trading into electricity market can convert carbon dioxide into schedulable resources with economic value.However,the randomness of wind power generation puts forward higher requirements for electricity market transactions.Therefore,the carbon trading market is introduced into the wind power market,and a new form of low-carbon economic dispatch model is developed.First,the economic dispatch goal of wind power is be considered.It is projected to save money and reduce the cost of power generation for the system.The model includes risk operating costs to account for the impact of wind power output variability on the system,as well as wind farm negative efficiency operating costs to account for the loss caused by wind abandonment.The model also employs carbon trading market metrics to achieve the goal of lowering system carbon emissions,and analyze the impact of different carbon trading prices on the system.A low-carbon economic dispatch model for the wind power market is implemented based on the following two goals.Finally,the solution is optimised using the Ant-lion optimisation method,which combines Levi's flight mechanism and golden sine.The proposed model and algorithm's rationality is proven through the use of cases.

Two-Stage Low-Carbon Economic Dispatch of Integrated Demand Response-Enabled Integrated Energy System with Ladder-Type Carbon Trading

Driven by the goal of“carbon neutrality”and“emission peak”,effectively controlling system carbon emissions has become significantly important to governments around the world.To this end,a novel two-stage low-carbon economic scheduling framework that considers the coordinated optimization of ladder-type carbon trading and integrated demand response(IDR)is proposed in this paper for the integrated energy system(IES),where the first stage determines the energy consumption plan of users by leveraging the price-based electrical-heat IDR.In contrast,the second stage minimizes the system total cost to optimize the outputs of generations with consideration of the uncertainty of renewables.In addition,to fully exploit the system’s emission reduction potential,a carbon trading cost model with segmented CO_(2) emission intervals is built by introducing a reward-penalty ladder-type carbon trading mechanism,and the flexible thermal comfort elasticity of customers is taken into account by putting forward a predicted mean vote index on the load side.The CPLEX optimizer resolves the two-stage model,and the study results on a modified IES situated in North China show the proposed model can effectively reduce carbon emissions and guarantee economical efficiency operation of the system.

China's low-carbon competitiveness and its effect decomposition from the perspective of wellbeing performance of ecological input

From the perspective of wellbeing performance of ecological input,this paper constructs a low-carbon competitiveness evaluation model with wellbeing performance of carbon emissions as the measurement standard,and uses the LMDI factor decomposition method to decompose the total effect of low-carbon competitiveness changes into technology effect and service effect.And then it conducts positive analysis and comparison of the low-carbon competitiveness and its effect contribution of G20 countries from1990 to 2018.The results are as follows:Firstly,in 2018,the UK,France,Argentina,Brazil,and Germany had higher low-carbon competitiveness.From 1990 to 2018,the low-carbon competitiveness of the UK,Turkey,Germany,Italy,and Brazil increase rapidly.Secondly,from 1990 to 2018,the total effect of low-carbon competitiveness of G20 member states was all positive,that is to say,the overall wellbeing performance of carbon emissions increased,technology effect and service effect are positive in 17 countries and negative in 2 countries respectively.Thirdly,China's low-carbon competitiveness is low,lacking static and dynamic advantages,although the technology effect is the highest,but the service effect is the lowest,resulting in a low total effect,which indicates that the wellbeing performance of economic growth is the main bottleneck of China's low-carbon development.Finally,the policy recommendations for China's future low-carbon transition and sustainable development are put forward.

The value rationality and tool rationality of Health Priority

Health Priority is increasingly becoming a human need and an international consensus.In addition to the basic value judgment and direction-leading function,Health Priority also has a clear,practical meaning and distinct tool attributes.The text adheres to the organic unity of regularity and purpose,follows the modern medical model and the philosophy of system theory,combines the characteristic facts,and discusses the value rationality and tool rationality of Health Priority based on the whole process management,and tries to refine the Health Priority governance model with Chinese characteristics,so as to provide a reference for global health governance.