Ideal Scenario Research Articles

On the role of chance in fencing tournaments: An agent-based approach.

It is a widespread belief that success is mainly due to innate qualities rather than external forces. This is particularly true in sports competitions, where individual talent is usually considered the main, if not the only, ingredient to reach success. In this study, we explore the limits of this belief by quantifying the relative weight of talent and chance in fencing, a combat sport involving a weapon, with the help of both real data and agent-based simulations. Fencing competitions are structured as direct elimination tournaments, where randomness is explicitly present in some rules. We focused on épée, which is one of three disciplines. We collected data on international competition results and annual rankings, in the range 2008–2020, for male and female fencers under 20 years old (Junior category). Then, we built the model calibrated on our dataset and parametrized by just one free variable a, describing the importance of talent—and, consequently, of chance—in competitions (a = 1 indicates the ideal scenario where only talent matters, a = 0 the complete random one). Our agent-based approach can reproduce the main stylized facts observed in data, at the level of both single tournaments and the entire careers of a given community of épée fencers. We find that simulations approximate very well the data for both Junior Men and Women when talent weights slightly less than chance, i.e. when a is around 0.45. We conclude that the role of chance in fencing is unusually high and it probably represents an extreme case for individual sports. Our findings shed light on the importance of external factors in both athletes’ results in tournaments and throughout their career, making even more unfair the “winner-takes-all” disparities that often occur between the winner and the other classified competitors.

Outcome of liver transplantation with grafts from brain-dead donors treated with dual hypothermic oxygenated machine perfusion, with particular reference to elderly donors

Prompted by the utilization of extended criteria donors, dual hypothermic oxygenated machine perfusion (D‐HOPE) was introduced in liver transplantation to improve preservation. When donors after neurological determination of death (DBD) are used, D‐HOPE effect on graft outcomes is unclear. To assess D‐HOPE value in this setting and to identify ideal scenarios for its use, data on primary adult liver transplant recipients from January 2014 to April 2021 were analyzed using inverse probability of treatment weighting, comparing outcomes of D‐HOPE‐treated grafts (n = 121) with those preserved by static cold storage (n = 723). End‐ischemic D‐HOPE was systematically applied since November 2017 based on donor and recipient characteristics and transplant logistics. D‐HOPE use was associated with a significant reduction of early allograft failure (OR: 0.24; 0.83; p = .024), grade ≥3 complications (OR: 0.57; p = .046), comprehensive complication index (−7.20 points; p = .003), and improved patient and graft survival. These results were confirmed in the subset of elderly donors (>75‐year‐old). Although D‐HOPE did not reduce the incidence of biliary complications, its use was associated with a reduced severity of ischemic cholangiopathy. In conclusion, D‐HOPE improves postoperative outcomes and reduces early allograft loss in extended criteria DBD grafts.

Large-scale survey for canine vector-borne parasites in free-ranging dogs and foxes from six diverse bioclimatic regions of Chile.

Chile is a large country with a marked range of climate conditions that make it an ideal scenario for the study of vector-borne parasites (VBPs); however, knowledge about their distribution is limited to a few confined areas of this country. The presence of Hepatozoon spp., piroplasmids, Leishmania spp. and filarioids was investigated through molecular and serological methods in blood and serum samples of 764 free-ranging rural dogs, 154 Andean foxes (Lycalopex culpaeus), and 91 South American grey foxes (Lycalopex griseus) from six bioclimatic regions across Chile. Hepatozoon spp. DNA was exclusively detected in foxes (43% prevalence), including sequences closely related to Hepatozoon felis (24.1%; only Andean foxes), Hepatozoon americanum (16.2%; only grey foxes), and Hepatozoon canis (1.25%; in one grey fox). Risk factor assessment identified a higher probability of Hepatozoon infection in juvenile foxes. DNA of piroplasmids was detected in 0.7% of dogs (Babesia vogeli) but in no fox, whilst antibodies against Babesia sp. were detected in 24% of the dogs and 25% of the foxes, suggesting a wider circulation of canine piroplasmids than previously believed. A positive association between the presence of antibodies against Babesia and high Rhipicephalus sanguineus sensu lato burden was observed in dogs. Leishmania spp. DNA and antibodies were detected in 0.8% and 4.4% of the dogs, respectively. Acanthocheilonema reconditum was the only blood nematode detected (1.5% of the dogs and no fox). Differences in prevalence among bioregions were observed for some of the VBPs. These results expand our knowledge about the occurrence of vector-borne parasites in Chile, some of which are firstly reported herein. This information will facilitate the diagnosis of vector-borne diseases in domestic dogs and improve the control measures for both domestic and wild canids.

The Public's Preferences for Psychological Interventions During the COVID-19 Pandemic: A Discrete Choice Experiment.

AimsTo explore the public's preference for psychological interventions through a discrete choice experiment and to provide references for formulating psychological intervention policies and establishing psychological intervention procedures in response to public health emergencies.MethodsThis study is a discrete choice experiment. Attributes and levels were identified through literature reviews, in-depth interviews, focus group discussions, and expert consultations. Experimental design principles were applied to generate choice sets containing different attribute levels and develop a survey instrument. Convenience sampling was conducted nationwide, and 1,045 participants were investigated. A mixed logit model was used to evaluate the public's preferences.ResultsAll attributes in our study were found to have a significant influence on the public's preferences for psychological interventions during the COVID-19 pandemic. The public's preferences for providers and duration were influenced by the public's levels of education and classifications. Furthermore, the most ideal scenario was found to be a one-on-one psychological intervention provided by family and friends through social network platforms, for which the frequency is twice per week, and the duration of each intervention is 0.5–1 h.ConclusionsThe public's preferences for psychological interventions during the COVID-19 pandemic are affected by the method, form, frequency, provider, and duration of interventions. Our findings provide references for the formulation of psychological intervention policies and the establishment of psychological intervention procedures in response to public health emergencies.

Quantifying Compressed Air Leakage through Non-Intrusive Load Monitoring Techniques in the Context of Energy Audits

Following the recent European directives highlighting the need to increase energy efficiency in the European Union, this work aims to show the possibility of using Non-Intrusive Load Monitoring (NILM) techniques to improve energy audits by estimating the compressed air leakage from a dataset of a tertiary building. The first step towards the reduction of energy consumption is performing an energy audit, in which a detailed analysis of the energy performance is executed. This analysis usually uses on-site measured data by the auditors. However, the time available for these measurements is limited and may not include some modes of operation. One example of that is the quantification of compressed air leaks. This task can be performed by estimating the flow rate during a no compressed air consumption period. However, these periods may not coincide with the auditors’ original schedule. This problem could be addressed by using historical data. Nevertheless, historical data from energy management systems usually are only available for global consumption, and rarely for individual appliances. In this context, a NILM approach would be helpful to enhance energy audits carrying analysis of modes of operation not included in the on-site measurements. In this paper, the leaks are firstly quantified using measurements mostly for benchmarking purposes. The results suggested 62% of leaks in the study case. In a second step, the Factorial Hidden Markov Model (FHMM) was applied to the data. Five typical working days, simulating the context of an energy audit, were used as training data, while one week during vacation time, with no compressed air consumption, was used to quantify the leaks. The results show that it was possible, in the context of an energy audit, to estimate the compressed air leakage using NILM techniques in this dataset with less than a 1% difference when compared to the estimation made with actual measurement. Finally, savings estimations considering the elimination of the leaks were performed, varying between 10% and 100% of the leakage repair. Considering the ideal scenario of complete leaks elimination, the savings would represent around 44% in the compressed air system and 4.75% of the current annual global consumption.

Scenario Analysis of Water-Saving Potential in Yeast Manufacturing Industry under the Guidance of Water Intake Quota

While yeast manufacturing consumes a large amount of water per unit of product, water use efficiency varies widely within the industry due to disparity in water-saving technologies. By stipulating water intake per unit of product, the Norm of Water Intake––Part 41: Yeast Production (GB/T 18916.41-2019) will standardize production water use and improve the water-saving level of the yeast manufacturing industry. This paper estimates the industry’s production capacity from 2020 to 2024 through regression analysis. It examines the distribution of water use efficiency under different policy scenarios based on the standard for water intake, including the business-as-usual scenario, the bottom-line scenario, the ideal scenario, and the expected scenario. Then, the water use of the yeast manufacturing industry under different scenarios is calculated, and the water-saving potential is analyzed by comparing it with the business-as-usual scenario. The results indicate that depending on the intensity of policy implementation, the average annual water savings will range from 2.5 × 106 m 3 to 14 × 106 m 3 . The cumulative water savings will add up to 16 × 106 m 3 to 51 × 106 m 3 in the next five years, which is very large.

Building diversity in the speech-language pathology workforce through a blended online Master of Speech Pathology

Purpose: A lack of diversity in the speech-language pathology profession is widely recognised internationally. The role of speech-language pathology education in reproduction of this homogeneity and as a barrier to diversification is little understood. The potential of blended online education to increase access to education and diversify the speech-language pathology profession is yet to be explored. The purpose of the study was to investigate the profile of students engaging in the first blended online speech-language pathology course in Australia, including motivations for studying, experiences of studying via a blended online mode, and intentions for future practice. Method: Data were collected from 44 students in the first Australian blended online Master of Speech Pathology via an online survey. Quantitative data were analysed using descriptive statistics in SPSS and a content analysis of the qualitative data was conducted using NVivo. Result: With over 92% of participants choosing the course because it was offered online, flexible blended online study provided opportunity for those who would not have otherwise accessed speech-language pathology education, including rural students and those balancing work and home commitments. Participants found face to face elements of the course essential to their learning, but also the most challenging to manage and to fit around other commitments. Participants’ ideal work scenarios revealed that 82.9% wished to practice within 50kms of their current location, indicating that provision of tertiary education to people in rural areas is contributing to establishing and retaining a rurally focussed speech-language pathology workforce. Conclusion: Blended online study provides an opportunity to diversify the speech-language profession by providing access to students such as rural students and those balancing work and home commitments with tertiary education. By reducing barriers to studying speech-language pathology, flexible learning is helping address issues of access and equity in service delivery across Australia.

The ideal scenario in deep inferior epigastric perforator (DIEP) flap dissection: a complete muscle and nerve-sparing approach

The deep inferior epigastric perforator flap (DIEP) has become the gold standard method of autologous breast reconstruction by simultaneously maximising aesthetics of the breasts and abdomen, and maximising the function of the abdominal wall. While the anatomical variability of the DIEP flap perforators have been well characterised, there has been less attention paid to the hierarchy of DIEP perforators in terms of limiting abdominal dysfunction post-operatively. In this paper, we seek to draw attention to what is, in our opinion, the ideal scenario in DIEP flap harvest. Where present, a medial paramuscular cutaneous vessel (MPCV) may be harvested using the pyramidalis separation technique enabling a complete rectus abdominis muscle-sparing and abdominal motor nerve-sparing approach. Herein, we describe the pyramidalis separation technique and the results in representative cases. In our experience, this technique enables an expeditious surgical procedure, and dramatically reduces damage to both muscles and nerves.Level of evidence: Level V, therapeutic study

Pendugaan Erosi Tanah dan Perencanaan Tutupan Lahan Hulu DAS Jeneberang, Sulawesi Selatan

Soil erosion is the main cause of land degradation. Jeneberang watershed is one of the priority watersheds in Indonesia. It has a big problem related to erosion in the upstream area. Jeneberang watershed is important area, its function is as water catchment for Bili-bili reservoir. It is served for flood control, irrigation water sources, water and hydroelectric energy supply. The aims of this study were to analyze the soil erosion prediction based on existing condition; develop an ideal land cover scenario to decrease soil erosion; and suggest land cover planning recommendations based on tolerable soil loss indicators in the upstream of Jeneberang watershed. This study was conducted using map overlay method to determine the value of the erosion factor. Erosion was predicted based on Universal Soil Loss Equation (USLE). Land scenarios and simulations was calculated by estimating the erosion in forest area and spatial planning land cover. The result showed that soil erosion of existing condition was approximately 813.1 tons/ha/year. The tolerable soil loss was only 22.9 tons/ha/year. The landuse scenario that chooses the lowest presumed erosion result is the implementation of spatial planning of Gowa district 2012-2032 with soil conservation technique applied. It can reduce erosion and sediment as 96.6% in upstream Jeneberang watershed.
 
 Keywords: erosion, Jeneberang watershed, scenario, landuse

Integrating IPAT and CLUMondo Models to Assess the Impact of Carbon Peak on Land Use

China’s growth plans include a carbon emission peak policy, which is a restriction that indirectly impacts land use structure. In this study, we simulate different paths for achieving policy objectives, and explore the linkages between those paths and land use change. The IPAT model was used to simulate the carbon emissions generated from a natural development scenario, an ideal policy scenario, and a retributive carbon emission scenario in China from 2020 to 2030. The simulation results were incorporated into the CLUMondo model as a demand driver to simulate the land use change in 2030. The results show that carbon emission peak policy can somewhat reduce carbon emissions and increase building land in a regulated way. However, the policy may also lead to a short-term surge in carbon emissions, a reactive expansion of arable land and building land. This may reduce losses in economic development when carbon emissions are limited, but does not achieve the integration of social, economic, and ecological goals. This study links the carbon emission peak policy with land use change and provides a fresh perspective on the Chinese government’s carbon reduction policy.

State-of-the-art retinal vessel segmentation with minimalistic models

The segmentation of retinal vasculature from eye fundus images is a fundamental task in retinal image analysis. Over recent years, increasingly complex approaches based on sophisticated Convolutional Neural Network architectures have been pushing performance on well-established benchmark datasets. In this paper, we take a step back and analyze the real need of such complexity. We first compile and review the performance of 20 different techniques on some popular databases, and we demonstrate that a minimalistic version of a standard U-Net with several orders of magnitude less parameters, carefully trained and rigorously evaluated, closely approximates the performance of current best techniques. We then show that a cascaded extension (W-Net) reaches outstanding performance on several popular datasets, still using orders of magnitude less learnable weights than any previously published work. Furthermore, we provide the most comprehensive cross-dataset performance analysis to date, involving up to 10 different databases. Our analysis demonstrates that the retinal vessel segmentation is far from solved when considering test images that differ substantially from the training data, and that this task represents an ideal scenario for the exploration of domain adaptation techniques. In this context, we experiment with a simple self-labeling strategy that enables moderate enhancement of cross-dataset performance, indicating that there is still much room for improvement in this area. Finally, we test our approach on Artery/Vein and vessel segmentation from OCTA imaging problems, where we again achieve results well-aligned with the state-of-the-art, at a fraction of the model complexity available in recent literature. Code to reproduce the results in this paper is released.

A Unified Two-Dimensional Direction Finding Approach for Sensor Arrays Based on Deep Neural Networks With Inhomogeneous Angle and Frequency Partition

This paper develops a deep neural networks (DNNs) based direction finding approach for 2-D direction finding in multiple frequencies. The approach is frequency-unified and is capable of direction-of-arrival (DoA) prediction for multiple frequencies. A model output is proposed and proved for 2-D direction finding. In addition, different from the common mean squared error (MSE) loss, a label-dependent loss is proposed motivated by the different Cramer-Rao Lower Bound (CRLB) of direction finding accuracy for different DoAs, and an inhomogeneous angle and frequency partition strategy is suggested for efficient implementation. Following the model output and the partition strategy, the general DNN architecture consists of a series of classification networks for angle zoom partition and regression networks for DoA prediction. Several useful tips for model inputs and zoom partition are also suggested. Numerical investigations are included to evaluate the performance of the proposed approach and show desirable performance for both ideal and nonideal scenarios. The added value of treating samples of different frequencies in a unified manner is also shown.

The Change Matters! Measuring the Effect of Changing the Leader in Joint Music Performances

In a joint action, a group of individuals coordinate their movements to reach a shared goal. When a change–i.e., an event that affects group functioning–occurs, the group adopts strategies to face it. This article investigates how a change involving a strategic core role in a group affects interpersonal coordination, and ultimately group effectiveness in performing a joint action. Following the entrainment theory, interpersonal coordination is addressed in terms of the rhythmic cycles of the individuals and of the group and their adjustment. Music is used as an ideal ecological scenario for investigation. More specifically, this article focuses on orchestra playing. By adopting a computational approach, research is devoted to measure how a change of conductor (i.e., the leader) influences entrainment between players and its variation over time as well as the relationship between entrainment and external ratings of the orchestra performance. Results show that, whereas the change of conductor had a limited significant effect on entrainment, a significant effect was found when entrainment is used as a predictor of the external ratings. Both the obtained results and the techniques developed for measuring entrainment may open novel research directions in the area of automated analysis of group behavior, and particularly of emotion in groups.

COMPARATIVE STUDY OF CASE BASED LEARNING WITH TRADITIONAL TEACHING METHODS IN BIOCHEMISTRY FOR FIRST YEAR MEDICAL STUDENTS

Background: Case based learning (CBL), is a learning method aids learner to reorganize, elaborate their information and provide connection between current and new information. Moreover CBL is student centered, taken in small groups where teacher acts as facilitator or guide. This study was planned to perceive the need for initiating CBL, this study aimed to compare the biochemistry teaching among rst year medical students with that of traditional teaching. Methods This is an observational study conducted from August 2021 to December 2021. This research study was conducted on 99 students of First year MBBS students. Ten ideal case scenarios on the topic of protein energy malnutrition(PEM) in children and acid base balance were prepared, and pre validated by the faculty of Biochemistry, Paediatrics and Surgery medical education department in our institution. CBL was introduced and total three sessions were conducted and compared with traditional teaching. Results The mean (±SD) value of the score of gain in knowledge was 3.90±1.86 (n=99) for the batch of students who attended case based learning while the mean (±SD) gain in knowledge for the batch who underwent, traditional learning ( TL) was 2.60±2.29 (n=99). A paired t-test comparing didactic lectures with self-directed learning showed that the scores following didactic lectures were more compared to SDL and the results were statistically signicant. An unpaired t-test comparing case based learning to SDL also showed statistically signicant gain in knowledge following didactic lectures. Conclusion This study clearly showed that CBL is more effective over traditional teaching for our rst year MBBS students and for covering a wider area.

Operational speed strategy opportunities for autonomous trucking on highways

This study examines the potential for cost and carbon emission reduction for autonomous trucks to adopt lower peak speeds than today's human driven trucks, where the hourly cost of the driver remains a significant trade-off. Adopting lower speeds presents an indirect savings opportunity in addition to savings associated with the removal of the driver. Benefits and trade-offs for varying target speed of autonomous trucks on highways were investigated with a parameterised analysis of transport and cargo cost components. A validated fuel consumption model was used to compare fuel consumption for different speed strategies across idealised highway drive-cycles and vehicle scenarios. A volume-limited tractor-trailer (50% cargo mass capacity) could reduce fuel consumption and carbon emissions by 26% when reducing target speed from 90 km/h to 70 km/h. When the trade-offs of driver, vehicle and cargo time are considered for the same 20 km/h target speed reduction, combined costs increase by 3% for the human driver scenario, but decrease by 4% for an autonomous truck (assuming medium cargo time value). Sensitivity to vehicle type, loading, drive-cycle and cargo value was examined. A UK supermarket chain case study was investigated and key differences between a UK and US context were compared. Mandatory rest breaks and Hours-of-Service restrictions were identified as additional barriers for human driven vehicles to adopt slower speed strategies.

An updated approach for deriving PTV margins using image guidance and deformable dose accumulation

Objective. To demonstrate an updated approach for deriving planning target volume (PTV) margins for a patient population treated with volumetric image-guided radiotherapy. Approach. The approach uses a semi-automated workflow within commercial radiotherapy applications that combines dose accumulation with the bidirectional local distance (BLD) metric. The patient cohort is divided into derivation and validation datasets. For each patient in the derivation dataset, a treatment plan is generated with a 0 mm PTV margin (the idealized treatment scenario without the influence of the standard margin). Deformable image registration enabled dose accumulation of these zero-margin plans. PTV margins are derived by using the BLD to calculate the geometric extent of underdosed regions of the clinical target volume (CTV). The PTV margin is validated by ensuring the specified CTV coverage criterion is met when the margin is applied to the validation dataset. Main results. The methodology was applied to two cohorts: 40 oropharyngeal cancer patients and 50 early-stage breast cancer patients. Ten patients from each cohort were used for validation. PTV margins derived for the oropharyngeal and early-stage breast cancer patient cohorts were 3 and 5 mm, respectively, and ensure that 95% of the prescription dose is delivered to 98% of the CTV for 90% of patients. Dose accumulation showed that the CTV coverage criterion was achieved for at least 90% of patients when the margins were applied. Significance. This methodology can be used to derive appropriate PTV margins for realistic treatment scenarios and any disease site, which will improve our understanding of patient outcomes.

Thermopower in a boundary-driven bosonic ladder in the presence of a gauge field

We consider a bosonic two-legged ladder whose two-band energy spectrum can be tuned in the presence of a uniform gauge field, to four distinct scenarios: degenerate or non-degenerate ground states with gapped or gapless energy bands. We couple the ladder to two baths at different temperatures and chemical potentials and analyze the efficiency and power generated in the linear as well as nonlinear response regime. Our results, obtained with the Green's function method, show that the maximum performance efficiency and generated power are strongly dependent on the type of the underlying energy spectrum. We also show that the ideal scenario for efficient energy conversion, as well as power generation, corresponds to the case in which the spectrum has a gap between the bands, and the ground state is degenerate.

A Game-Theoretic Framework for Analyzing the Impact of Social Responsibility and Supply Chain Profitability

Supply chain collaboration plays an important role in profit maximization. Contract coordination is a successful strategy for collaboration and profit-sharing in supply chains. The study of contract coordination in supply chains under uncertainty and stochastic environmental conditions has attracted the attention of many researchers. We propose a single-period newsvendor model with one manufacturer and one retailer in the supply chains. The proposed model considers two variables, including order quantity and investment in corporate social responsibility, where the demand is stochastic and follows a normal standard distribution. The model considers quantity flexibility, advanced purchasing discounts (APDs), and buyback contracts under cooperative conditions. Numerical examples are used to exhibit the applicability of the model under various conditions, including the two-demand distribution and three coordination contracts. We demonstrate an ideal scenario where the APD contracting results in the most overall supply chain profit and increases for each supply chain partner.

Electrochemical reforming of ethanol with acetate Co-Production on nickel cobalt selenide nanoparticles

The energy efficiency of water electrolysis is limited by the sluggish reaction kinetics of the anodic oxygen evolution reaction (OER). To overcome this limitation, OER can be replaced by a less demanding oxidation reaction, which in the ideal scenario could be even used to generate additional valuable chemicals. Herein, we focus on the electrochemical reforming of ethanol in alkaline media to generate hydrogen at a Pt cathode and acetate as a co-product at a Ni1-xCoxSe2 anode. We first detail the solution synthesis of a series of Ni1-xCoxSe2 electrocatalysts. By adjusting the Ni/Co ratio, the electrocatalytic activity and selectivity for the production of acetate from ethanol are optimized. Best performances are obtained at low substitutions of Ni by Co in the cubic NiSe2 phase. Density function theory reveals that the Co substitution can effectively enhance the ethanol adsorption and decrease the energy barrier for its first step dehydrogenation during its conversion to acetate. However, we experimentally observe that too large amounts of Co decrease the ethanol-to-acetate Faradaic efficiency from values above 90% to just 50 %. At the optimized composition, the Ni0.75Co0.25Se2 electrode delivers a stable chronoamperometry current density of up to 45 mA cm−2, corresponding to 1.2 Ag−1, in a 1 M KOH + 1 M ethanol solution, with a high ethanol-to-acetate Faradaic efficiency of 82.2% at a relatively low potential, 1.50 V vs. RHE, and with an acetate production rate of 0.34 mmol cm−2h−1.

A Dynamic Task Allocation Algorithm for Heterogeneous UUV Swarms.

Aiming at the task allocation problem of heterogeneous unmanned underwater vehicle (UUV) swarms, this paper proposes a dynamic extended consensus-based bundle algorithm (DECBBA) based on consistency algorithm. Our algorithm considers the multi-UUV task allocation problem that each UUV can individually complete multiple tasks, constructs a “UUV-task” matching matrix and designs new marginal utility, reward and cost functions for the influence of time, path and UUV voyage. Furthermore, in view of the unfavorable factors that restrict the underwater acoustic communication range between UUVs in the real environment, our algorithm complete dynamic task allocation of UUV swarms with optimization in load balance indicator by the update of the UUV individual and the task completion status in the discrete time stage. The performance indicators (including global utility and task completion rate) of the dynamic task allocation algorithm in the scenario with communication constraints can be well close to the static algorithm in the ideal scenario without communication constraints. The simulation experiment results show that the algorithm proposed in this paper can quickly and efficiently obtain the dynamic and conflict-free task allocation assignment of UUV swarms with great performance.