Set Of Preferences Research Articles

Optimizing Weekend Schedules in Home Health Care: The Essential Care on Weekends for Personal Support Quality Improvement Project

The availability of personal support workers (PSWs) is a limiting factor for home care system capacity, as this workforce provides 70% to 80% paid care in this sector. Without sufficient support to live at home, many seniors and people with disabilities experience poorer outcomes and require care in more expensive and less preferred institutional long-term care or hospital settings. Insufficient PSW availability is limiting access to necessary care in the community. Capacity challenges are particularly pronounced on weekends. The Essential Care on Weekends (ECoW) program was co-developed as one solution to adapt current PSW scheduling practices to increase the number of clients with high-intensity care needs who can be served within the constraints of PSW availability. ECoW focused on increasing weekend capacity and care consistency, particularly for clients with the highest care needs, through prioritizing essential care and moving less time sensitive tasks to weekdays. ECoW was operationalized through 4 activities: communication and engagement, clinical care plan review, geographic review of PSW schedules and the creation of the ECoW schedule. Implementation of ECoW demonstrated success in increasing access to and consistency of care for clients with the highest care needs: weekend capacity increased, access to care improved for clients requiring daily or near-daily care and missed care rates decreased both on weekends and weekdays. This strategy represents a change in scheduling practices that organizations can use to provide consistent service to a growing number of clients with high-intensity care needs in the context of increasingly limited health human resource capacity.

Deciphering Pediatric Root Canal Practices in Turkey: A Comparative Study Bridging the Gap between Practice and Literature.

BACKGROUND Pediatric endodontics is a critical area of dental practice, involving the treatment of root canals in primary teeth. Treatment approaches can significantly vary due to a range of factors, potentially impacting the success of the procedure and patient comfort. This variability, often influenced by regional practices, individual dentist preferences, and the pace of dental technology advancements, warrants detailed examination to improve standardization and care outcomes. Accordingly, our study aims to scrutinize the endodontic practices of pedodontists in Turkey and compare them with contemporary literature. MATERIAL AND METHODS We conducted an online survey with 15 questions that 217 Turkish pedodontists answered. The questionnaire sought information about their preferences in canal length measurement, canal sealer, irrigation solution, and other procedural decisions. Chi-square test was used to analyze the responses, with a significance level of p<0.05. RESULTS The majority of respondents were associated with universities (123 out of 217). 103 preferred rotary file sets, and 114 used apex locators for canal length measurement. Iodoform pastes (160) and sodium hypochlorite (180) were the most popular choices for canal sealers and irrigation solution, respectively. 152 participants did not prefer using rubber dam, and 186 did not favor sonic-ultrasonic activators. Many reported using hand files as students (184), with 39 continuing this practice. Post-graduation, 64 participants took root canal treatment courses, while 72 were reluctant to perform the procedure under general anesthesia. CONCLUSIONS No single method stood out as superior for primary root canal treatments in deciduous teeth. Incorporating advanced technology into dental practice may potentially improve treatment success and patient comfort.

Preference For Cervical Cancer Education: A Multisite Cross-Sectional Survey of Female Senior High School Students in Ghana.

Cervical cancer incidence continues to rise in Ghana. To enhance knowledge and prevention of cervical cancer among young people in Ghana, there is a need to better understand their education preferences. The study aimed to describe female senior school students' preferences for receiving cervical cancer education. A cross-sectional survey of students from 17 schools in the Ashanti Region of Ghana assessed the strength of preference for receiving cervical cancer education from a range of sources, settings and delivery mediums. Of the 2400 participants (aged 16-24years), the majority endorsed doctors (87%, 95%CI: 85-88%), nurses (80%, 95%CI: 78-82%) and credible health organisations (78%, 95%CI%: 76-79%) as their preferred source of education, and hospitals 83% (95%CI: 81-84%) as the preferred setting. Nearly all students (92%) endorsed at least three cervical cancer education delivery mediums, with at least three quarters endorsing television (78%, 95%CI: 77-80%), one-on-one health consultation in-person or online (77%, 95%CI: 75-79%; 75%, 95%CI: 73-77%), and health information websites (75%, 95%CI: 73-77%). Findings suggest that cervical cancer education efforts among female senior school students in Ghana should consider the use of a range of more resource-intensive individualised approaches to low-cost anonymous, generic approaches from credible sources and institutions.

Rapid population synthesis of black hole high-mass X-ray binaries: implications for binary stellar evolution

ABSTRACT We conduct binary population synthesis to investigate the formation of wind-fed high-mass X-ray binaries containing black holes (BH-HMXBs). We evolve multiple populations of high-mass binary stars and consider BH-HMXB formation rates, masses, spins, and separations. We find that systems similar to Cygnus X-1 likely form after stable Case A mass transfer (MT) from the main-sequence progenitors of BHs, provided such MT is characterized by low accretion efficiency, β ≲ 0.1, with modest orbital angular momentum losses from the non-accreted material. Additionally, efficient BH-HMXB formation relies on a new simple treatment for Case A MT that allows donors to retain larger core masses compared to traditional rapid population-synthesis assumptions. At solar metallicity, our Preferred model yields $\mathcal {O}(1)$ observable BH-HMXBs in the Galaxy today, consistent with observations. In this simulation, 8 per cent of BH-HMXBs go on to merge as binary black holes or neutron star-black hole binaries within a Hubble time; however, none of the merging binaries have BH-HMXB progenitors with properties similar to Cygnus X-1. With our preferred settings for core mass growth, mass transfer efficiency, and angular momentum loss, accounting for an evolving metallicity, and integrating over the metallicity-specific star formation history of the Universe, we find that BH-HMXBs may have contributed ≈2–5 BBH merger signals to detections reported in the third gravitational-wave transient catalogue of the LIGO–Virgo–KAGRA Collaboration. We also suggest MT efficiency should be higher during stable Case B MT than during Case A MT.

Patients' preference regarding inpatient versus outpatient setting - A systematic review.

Continuously rising healthcare costs have led to financial pressure on the healthcare systems. One of the trends for the reduction of costs is the shift towards outpatient treatment. However, research has not focused on the patients' preferences regarding inpatient versus outpatient treatment settings. The purpose of this review is to examine existing studies surveying patients' preferences related to inpatient and outpatient treatment methods. The aim is to find out whether patients' wishes were queried and considered in the decision-making process. Therefore, the reviewers performed a systematic approach utilizing the PRISMA standards and screened 1'646 articles out of 5'606 articles from the systematic search. The screening resulted in 4 studies that analyzed exclusively the patient's choice of treatment setting. The search showed an apparent paucity of current literature and highlights the need for further research. The authors' recommendation includes a better involvement of patients in the decision-making process as well as adding preferred treatment settings to advanced treatment directives and patient satisfaction questionnaires.

Disparities in employment outcomes among critical care graduates with different training backgrounds

Abstract Background We sought to characterize the impact of critical care training pathways on subsequent employment opportunities. Methods A survey assessing the postfellowship work environment and barriers to employment in a preferred setting was electronically distributed on September 16, 2019, to program directors and coordinators at all US adult critical care fellowships with instructions to forward it to the prior year’s graduates. Results Data collection was interrupted by the coronavirus disease 2019 pandemic. Fifty-nine participants were included, reflecting a low rate of return. Most worked in urban areas (76.6%) at academic hospitals (81.7%). Graduates of internal medicine critical care (IMCC) were more likely than pulmonary critical care (PCC) to report their fellowship as a barrier to employment (50% vs 0%; P &lt; 0.05). Emergency medicine graduates were more likely than internal medicine to report their residency as a barrier to employment (83.3% vs 4.6%; P &lt; 0.05). Inability to find a desired position at an academic center (50% vs 5.9%; P &lt; 0.05) and in the preferred metropolitan setting (37.5% vs 0%; P &lt; 0.05) were more common among IMCC than PCC. Conclusion In this survey of critical care graduates, residency in emergency medicine and fellowship in IMCC were associated with increased barriers to finding desired employment.

Identifying preferences when households are financially constrained

This paper shows that utilizing information on the extensive margin of financially constrained households can narrow down the set of admissible preferences in a large class of macroeconomic models. Estimates based on Spanish aggregate data provide further empirical support for this result and suggest that accounting for this margin can bring estimates closer to microeconometric evidence. Accounting for financial constraints and the extensive margin is shown to matter for empirical asset pricing and quantifying distortions in financial markets.

Business students’ experiences, perceptions, and motivations toward business research and information literacy: Ideas for better library practices

Based on a business student survey, this article explores students’ experiences, perceptions, attitudes, and motivation toward learning business information literacy (IL) skills. The survey received 413 responses and investigated topics including most encountered research tasks, use of research tools, most experienced feelings, self-rated research competencies, perceived research importance, interest to learn more, research scenarios, challenges, preferred learning settings and learning modes, motivational factors, the time commitment for learning, and preferred quality of a learning module. Incorporating students’ suggestions on improving their IL skills, the article proposes to create six dynamic learning opportunities for students and shares ideas for realizing these opportunities through collaboration, integration, and experimentation.

Living comfortably with heat in Australia – preferred indoor temperatures and climate zones

While the optimal mean annual temperature for people and nations is said to be between 13 °C and 18 °C, many people live productive lives in regions or countries that commonly exceed this temperature range. One such country is Australia. We carried out an Australia-wide online survey using a structured questionnaire to investigate what temperature people in Australia prefer, both in terms of the local climate and within their homes. More than half of the 1665 respondents (58%) lived in their preferred climatic zone with 60% of respondents preferring a warm climate. Those living in Australia's cool climate zones least preferred that climate. A large majority (83%) were able to reach a comfortable temperature at home with 85% using air-conditioning for cooling. The preferred temperature setting for the air-conditioning devices was 21.7 °C (SD: 2.6 °C). Higher temperature set-points were associated with age, heat tolerance and location. The frequency of air-conditioning use did not depend on the location but rather on a range of other socio-economic factors including having children in the household, the building type, heat stress and heat tolerance. We discuss the role of heat acclimatisation and impacts of increasing air-conditioning use on energy consumption.

Aero-Engine Blade Cryogenic Cooling Milling Deformation Simulation and Process Parameter Optimization.

For the machining of aero-engine blades, factors such as machining residual stress, milling force, and heat deformation can result in poor blade profile accuracy. To address this issue, simulations of blade milling were completed using DEFORM11.0 and ABAQUS2020 software to analyze blade deformation under heat-force fields. Process parameters such as spindle speed, feed per tooth, depth of cut, and jet temperature are used to design both a single-factor control and BBD test scheme to study the influence of jet temperature and multiple changes in process parameters on blade deformation. The multiple quadratic regression method was applied to establish a mathematical model correlating blade deformation with process parameters, and a preferred set of process parameters was obtained through the particle swarm algorithm. Results from the single-factor test indicated that blade deformation rates were reduced by more than 31.36% in low-temperature milling (-190 °C to -10 °C) compared with dry milling (10 °C to 20 °C). However, the margin of the blade profile exceeded the permissible range (±50 µm); therefore, the particle swarm optimization algorithm was used to optimize machining process parameters, resulting in a maximum deformation of 0.0396 mm when the blade temperature was -160 °C~-180 °C, meeting the allowable blade profile deformation error.

Analysis and validation of overall N-glycan conformation in Privateer.

The oligosaccharides in N-glycosylation provide key structural and functional contributions to a glycoprotein. These contributions are dependent on the composition and overall conformation of the glycans. The Privateer software allows structural biologists to evaluate and improve the atomic structures of carbohydrates, including N-glycans; this software has recently been extended to check glycan composition through the use of glycomics data. Here, a broadening of the scope of the software to analyse and validate the overall conformation of N-glycans is presented, focusing on a newly compiled set of glycosidic linkage torsional preferences harvested from a curated set of glycoprotein models.

Reduction Theorems in the Social Choice Theory

In the paper, combinatorial theorems related to the theory of social choice are obtained. These theorems describe general conditions under which the problem on the preserving the preference set 𝒟 by an arbitrary aggregation rule f and the problem on the compatibility of the preference set 𝒟 with a pair (f, 𝒞) can be reduced to similar problems for two specific aggregation rules: the majority rule maj and the “counting rhyme” rule cog. Results are obtained within the framework of clone approach in the theory of social choice proposed by S. Shelah and developed by the authors.

Identification of RAC1 in promoting brain metastasis of lung adenocarcinoma using single-cell transcriptome sequencing

This study aims to give a new perspective to the biomarkers in the lung adenocarcinoma (LUAD) brain metastasis, pathways involved and potential therapeutics. We performed a comprehensive single-cell level transcriptomic analysis on one LUAD patient with circulating tumor cells (CTCs), primary tumor tissue and metastatic tumor tissue using scRNA-seq approach to identify metastasis related biomarkers. Further scRNA-seq were performed on 7 patients to validate the cancer metastatic hallmark. with single cells collected from either metastatic or primary LUAD tissues. Pathological and functional studies were also performed to evidence the critical role of RAC1 in the LUAD metastasis. Hallmark gene was verified based on immunohistochemistry staining, cytological experiment, survival information from The Cancer Genome Atlas (TCGA), and staining results from Human Protein Atlas (HPA) databases. PCA analysis revealed that CTCs were in the intermediate place between the metastatic group and primary group. In the unsupervised clustering analysis CTCs were closer to one of the metastatic tumor cells, implying heterogeneity of the metastatic tumor and origin of the CTCs were from metastatic site. Transitional phase related gene analysis identified RAC1 was enriched in metastatic tumor tissue (MTT) preferred gene set functioning as regulated cell death and apoptosis as well as promoted macromolecule organization. Compared with normal tissue, expression levels of RAC1 increased significantly in LUAD tissue based on HPA database. High expression of RAC1 predicts worse prognosis and higher-risk. EMT analysis identified the propensity of mesenchymal state in primary cells while epithelial signals were higher in the metastatic site. Functional clustering and pathway analyses suggested genes in RAC1 highly expressed cells played critical roles in adhesion, ECM and VEGF signaling pathways. Inhibition of RAC1 attenuates the proliferation, invasiveness and migration ability of lung cancer cells. Besides, through MRI T2WI results, we proved that RAC1 can promote brain metastasis in the RAC1-overexpressed H1975 cell burden nude mouse model. RAC1 and its mechanisms might promote drug design against LUAD brain metastasis.

VACCELERATE Site Network: Real-time definition of clinical study capacity in Europe

BackgroundThe inconsistent European vaccine trial landscape rendered the continent of limited interest for vaccine developers. The VACCELERATE consortium created a network of capable clinical trial sites throughout Europe. VACCELERATE identifies and provides access to state-of-the-art vaccine trial sites to accelerate clinical development of vaccines. MethodsLogin details for the VACCELERATE Site Network (vaccelerate.eu/site-network/) questionnaire can be obtained after sending an email to. Interested sites provide basic information, such as contact details, affiliation with infectious disease networks, main area of expertise, previous vaccine trial experience, site infrastructure and preferred vaccine trial settings. In addition, sites can recommend other clinical researchers for registration in the network. If directly requested by a sponsor or sponsor representative, the VACCELERATE Site Network pre-selects vaccine trial sites and shares basic study characteristics provided by the sponsor. Interested sites provide feedback with short surveys and feasibility questionnaires developed by VACCELERATE and are connected with the sponsor to initiate the site selection process. ResultsAs of April 2023, 481 sites from 39 European countries have registered in the VACCELERATE Site Network. Of these, 137 (28.5 %) sites have previous experience conducting phase I trials, 259 (53.8 %) with phase II, 340 (70.7 %) with phase III, and 205 (42.6 %) with phase IV trials, respectively. Infectious diseases were reported as main area of expertise by 274 sites (57.0 %), followed by any kind of immunosuppression by 141 (29.3 %) sites. Numbers are super additive as sites may report clinical trial experience in several indications. Two hundred and thirty-one (47.0 %) sites have the expertise and capacity to enrol paediatric populations and 391 (79.6 %) adult populations. Since its launch in October 2020, the VACCELERATE Site Network has been used 21 times for academic and industry trials, mostly interventional studies, focusing on different pathogens such as fungi, monkeypox virus, Orthomyxoviridae/influenza viruses, SARS-CoV-2, or Streptococcus pneumoniae/pneumococcus. ConclusionsThe VACCELERATE Site Network enables a constantly updated Europe-wide mapping of experienced clinical sites interested in executing vaccine trials. The network is already in use as a rapid-turnaround single contact point for the identification of vaccine trials sites in Europe.

Weighted OWA (Ordered Weighted Averaging Operator) Preference Aggregation for Group Multicriteria Decisions

Group decision making is an integral part of operations and management functions in almost every business domain with substantial applications in finance and economics. In parallel to human decision makers, software agents operate in business systems and environments, collaborate, compete and perform algorithmic decision-making tasks as well. In both settings, information aggregation of decision problem parameters and agent preferences is a necessary step to generate group decision outcome. Although plenty aggregation information approaches exist, overcomplexity of the underlying aggregating operation, in most of them, is a drawback, especially for human based group decisions in practice. In this work we introduce an aggregation method for group decision setting, based on the Weighted Ordered Averaging Operator (WOWA). The aggregation is applied on decision maker preferences, following the majority concept to generate a unique set of preferences as input for the decision algorithm. We present the theoretical construction of the model and an application at a group multicriteria assignment decision problem, along with detailed numerical results. The proposed method contributes in the field, as it offers a novel approach that is simple and intuitive, and avoids overcomplexity during group decision process. The method can be also easily deployed into artificial environments and algorithmic decision-making mechanisms.

Indoor temperature preference setting control method for thermal comfort and energy saving based on reinforcement learning

The optimal control of heating, ventilation, and air-conditioning (HVAC) systems affects people's living and building energy consumption. Many studies have introduced personal thermal sensation into the air-conditioning system to reduce energy consumption while improving the indoor thermal environment. However, there are limitations that require multiple adjusted temperature settings to create a room thermal environment that meets personal thermal comfort needs, and the impact of room temperature set values on air-conditioning energy consumption is often ignored. This study proposes an indoor temperature preference setting control method (ITPSCM) for thermal comfort and energy saving based on reinforcement learning (RL), which uses personal thermal comfort and the energy-saving effect of the system as the reward function. Q-learning is employed to obtain optimized room temperature settings to meet users' temperature preferences. Several comparative experiments are carried out in an indoor environment control testbed, and the experimental data is used to train the RL algorithm. As the results show, compared with the temperature set value-based control method, the ITPSCM can realize an indoor thermal environment that meets personal thermal comfort preferences in the early stages of air-conditioning system operation. With just the thermal comfort as a reward, 22.34% of daily energy consumption can be saved; with both the thermal comfort reward and energy-saving effect reward are considered, 26.48% of daily energy consumption can be saved.

Formation of an Adaptive Decision-Making Support Means Components in Engineering Infrastructure Reconstruction Programs Management

The article is devoted to a decision-making support tool aimed at improving the efficiency of engineering infrastructure reconstruction program management in the context of developing the architecture and hierarchical structure of program work and program architecture management. As part of the study, the main components of the model are defined, which include a set of decision-maker preferences, decision-making tasks, sets of input data, and applied software components of the model. To support decision-making, the adaptive model applies the method of system modeling and forecasting the value of the objective function at a given system configuration. Forecasting is done using machine learning methods based on a dataset consisting of historical data related to existing engineering systems. The work describes the components of the redistribution of varied model parameters, which modify the model dataset based on the selected object type, which allows adapting the decision-making process to the existing program implementation goals. A description of the data post-processing process is provided, which allows the decision-maker to obtain information about the influence of the main parameters of the system on the target indicator. The main differences between the described adaptive decision support model and the currently existing tools have been determined. The application of the developed adaptive model is possible in the management of programs for the reconstruction of such engineering systems as systems of heat, gas, electricity supply, water supply and drainage, etc.

REFLECTION IN PHRASES OF THE UKRAINIAN AND ENGLISH MENTALITY

The article is devoted to the study of Ukrainian and English phrases that reflect the mentality of the peoples of Ukraine and Great Britain. The relevance of the study is due to the anthropocentrism of phraseology, i.e. the focus of stable units on the human world. The purpose of the article is to study the semantic features of phrases that reflect the Ukrainian and English mentalities. The article interprets mentality as a stable set of preferences and a formed system of values of a people, which is closely related to the national character, reflecting the spiritual face of a certain ethnic group. According to this definition of the term “phraseology”, its main types include phraseological splices, phraseological unities, phraseological combinations, and phraseological expressions (idioms, proverbs, sayings, aphorisms). According to the results of the analysis, phrases reflect such features of the Ukrainian mentality as religiosity, love of freedom, and hard work. In turn, the English mentality is the result of traditions and behavioral habits of the people of Great Britain; it reflects its climate, nature and geography. The English mentality is characterized by stability, hard work; tolerance and non-interference in the affairs of others; conservatism; restraint and individualism. The authors note that some components in the phraseological units of the analyzed languages give the phraseological units opposite connotations, although sometimes there are coincidences. This mostly concerns phraseological units containing components denoting weather phenomena, such as wind, rain, hurricane. According to the authors, this is due to the different climatic conditions in the UK and Ukraine. The difference between the phraseological units referring to labor is also established: while Ukrainian phraseological units verbalize hard or useless work, English ones mostly condemn laziness.

Heel riser height and slope gradient influence the physiology of ski mountaineering-A laboratory study.

In ski mountaineering it is the goal to reach the top of a mountain by sheer muscle force. The specific equipment (flexible boot, only toe fixated binding, and a skin on the ski to prevent from slipping backwards) enables the skier to move up the hill ergonomically, where the heel part of the binding offers a special adaptation possibility. The so-called riser height supports the heel standing height and can be adjusted to individually preferred settings. General recommendations suggest using lower heel support in flat ascents and higher heel support in steep ascents to maintain upright posture and lower the strain. Still, it remains unclear whether the application of riser height affects the physiological response during ski mountaineering. This study was designed to investigate the effects of riser height on physiological response during indoor ski mountaineering. Nineteen participants took part in the study and walked on a treadmill with ski mountaineering equipment. The three available riser heights (low, medium, and high) were applied randomized at 8%, 16%, and 24% gradient. Results show that global physiological measurements like heart rate (p = 0.34), oxygen uptake (p = 0.26) or blood lactate (p = 0.38) values were not affected by changes in riser height. But local measurements of muscle oxygen saturation were affected by the riser height. Additionally comfort and rating of perceived exertion were also prone to changes in riser height. These results suggest differences on local measurements and perceived parameters, while global physiological measurements did not change. The results are in line with the existing recommendations but need to be confirmed in an outdoor setting as well.

FORECASTING OF AIRLINE PASSENGERS BASED ON MACHINE LEARNING

The management of airlines depends on the forecasting of air passenger flow, but standard forecasting techniques cannot guarantee the accuracy of the forecast. When they encounter large-scale, multidimensional, nonlinear, and non-normal distributing time series data, they have the ability to generalize. In this paper the SVM regression is implemented to help with forecasting air passenger flow. We discover that the SVM regression algorithm's outcome exhibits the least inaccuracy when compared to the other two forecasting techniques by carefully choosing the parameters and kernel function. Concerns about demand splits among service providers have been given to every sector by the nearperfect competition scenario. This is especially important in the airline business, where high service standards are the norm. Demand is driven by the player who achieves the greatest mappings between every one of his the airline's offerings and the set of consumer preferences. The airline business has grown exponentially as a result of the economic reforms of 1991, which were promptly followed by the privatization of Indian skies, creating nearly ideal competition. More specifically, cross-border activities have started in the international sectors, where previously only domestic carriers operated. Keywords – Airline Passengers, Support Vector Machine, Forecasting, Machine Learning