澳洲坚果主导品种Own Choice的品种配置研究

为了明确澳洲坚果园主导品种Own Choice(O.C)的最适配置品种,选择HAES863、D、D4、HAES816、HAES906、HAES294、HAES900、A4等8个品种为O.C授粉,统计分析不同授粉处理的着果率、杂交不亲和性程度指数、着果花序率、每果序着果数、落果率、壳果横径等指标。结果表明,以着果率及着果花序率统计的杂交不亲和性程度指数发现,HAES863、D、D4、HAES816、HAES906与O.C的杂交亲和性高于A4、HAES294、HAES900。供试品种处理的着果率与着果花序率之间存在正相关关系,初步推断可使用着果花序率代替着果率评价O.C与不同品种的杂交不亲和性程度;8个授粉处理的平均着果花序率为40.60%,可以此推断O.C与不同授粉品种的田间杂交不亲和性程度。综合分析推断,澳洲坚果主导品种O.C的最适配置品种为HAES863和D4,根据小气候可选择性搭配种植D、HAES906、HAES816。

Discrete Choice Models and Artificial Intelligence Techniques for Predicting the Determinants of Transport Mode Choice--A Systematic Review

Forecasting travel demand requires a grasp of individual decision-making behavior.However,transport mode choice(TMC)is determined by personal and contextual factors that vary from person to person.Numerous characteristics have a substantial impact on travel behavior(TB),which makes it important to take into account while studying transport options.Traditional statistical techniques frequently presume linear correlations,but real-world data rarely follows these presumptions,which may make it harder to grasp the complex interactions.Thorough systematic review was conducted to examine how machine learning(ML)approaches might successfully capture nonlinear correlations that conventional methods may ignore to overcome such challenges.An in-depth analysis of discrete choice models(DCM)and several ML algorithms,datasets,model validation strategies,and tuning techniques employed in previous research is carried out in the present study.Besides,the current review also summarizes DCM and ML models to predict TMC and recognize the determinants of TB in an urban area for different transport modes.The two primary goals of our study are to establish the present conceptual frameworks for the factors influencing the TMC for daily activities and to pinpoint methodological issues and limitations in previous research.With a total of 39 studies,our findings shed important light on the significance of considering factors that influence the TMC.The adjusted kernel algorithms and hyperparameter-optimized ML algorithms outperform the typical ML algorithms.RF(random forest),SVM(support vector machine),ANN(artificial neural network),and interpretable ML algorithms are the most widely used ML algorithms for the prediction of TMC where RF achieved an R2 of 0.95 and SVM achieved an accuracy of 93.18%;however,the adjusted kernel enhanced the accuracy of SVM 99.81%which shows that the interpretable algorithms outperformed the typical algorithms.The sensitivity analysis indicates that the most significant parameters influencing TMC are the age,total trip time,and the number of drivers.

A comparison of model choice strategies for logistic regression

Purpose:The purpose of this study is to develop and compare model choice strategies in context of logistic regression.Model choice means the choice of the covariates to be included in the model.Design/methodology/approach:The study is based on Monte Carlo simulations.The methods are compared in terms of three measures of accuracy:specificity and two kinds of sensitivity.A loss function combining sensitivity and specificity is introduced and used for a final comparison.Findings:The choice of method depends on how much the users emphasize sensitivity against specificity.It also depends on the sample size.For a typical logistic regression setting with a moderate sample size and a small to moderate effect size,either BIC,BICc or Lasso seems to be optimal.Research limitations:Numerical simulations cannot cover the whole range of data-generating processes occurring with real-world data.Thus,more simulations are needed.Practical implications:Researchers can refer to these results if they believe that their data-generating process is somewhat similar to some of the scenarios presented in this paper.Alternatively,they could run their own simulations and calculate the loss function.Originality/value:This is a systematic comparison of model choice algorithms and heuristics in context of logistic regression.The distinction between two types of sensitivity and a comparison based on a loss function are methodological novelties.

Discrete Choice Analysis of Temporal Factors on Social Network Growth

Social networks like Facebook, X (Twitter), and LinkedIn provide an interaction and communication environment for users to generate and share content, allowing for the observation of social behaviours in the digital world. These networks can be viewed as a collection of nodes and edges, where users and their interactions are represented as nodes and the connections between them as edges. Understanding the factors that contribute to the formation of these edges is important for studying network structure and processes. This knowledge can be applied to various areas such as identifying communities, recommending friends, and targeting online advertisements. Several factors, including node popularity and friends-of-friends relationships, influence edge formation and network growth. This research focuses on the temporal activity of nodes and its impact on edge formation. Specifically, the study examines how the minimum age of friends-of-friends edges and the average age of all edges connected to potential target nodes influence the formation of network edges. Discrete choice analysis is used to analyse the combined effect of these temporal factors and other well-known attributes like node degree (i.e., the number of connections a node has) and network distance between nodes. The findings reveal that temporal properties have a similar impact as network proximity in predicting the creation of links. By incorporating temporal features into the models, the accuracy of link prediction can be further improved.

Type 2 Diabetes—Hard to Select a Healthy Choice

Introduction: The use of foods containing high levels of sugar is increasing all the time. This is a risk factor for increased incidence of type 2 diabetes. There are few studies that have investigated the availability of low-sugar müsli products in grocery stores. Purpose: The study aims to identify which types of müsli contain high respectively low levels of sugar, and which brands are involved. Methods: The material consists of both qualitative interviews and observations from five grocery stores: City Gross, Hemköp, Ica Maxi, Stora Coop and Willy’s in Helsingborg, Sweden. The qualitative interviews had a semi-structured character and were recorded. The interviews took approx. 20 minutes and a textual analysis was conducted of the results. Data from observation was analyzed based on brand, nutritional composition and flavors, and also, where low sugar products were placed on store shelves. Results: The grocery stores provided together brands from AXA, Coop, Finax, Frebaco, Garant, ICA, Risenta, Saltå Kvarn och Urtekram, in total 24 müsli products. Of these products, 19 were high in sugar. The observation reveals that müsli products with high sugar content (17 - 29 g per 100 g müsli) are more prominently displayed than those with low sugar content. From the interviews with the store managers, it became clear that it would be valuable to highlight healthy müsli products on the shelves. However, central bureaucracy puts obstacles to such measures. Discussion: The study emphasizes the need for increased visibility of low-sugar products and proposes solutions such as negotiating with responsible person at the head office in Stockholm. Several reviews have shown that if the grocery store raises the prices of unhealthy food, the consumer is willing to purchase healthier müsli and other products. Conclusion: This study shows the need for grocery stores to upgrade healthy müsli products along with advertising to be able to influence customer’s shopping habits. Also, further research is needed how type 2 diabetes is affected by high intakes of food products with high sugar content.

Factors Influence Hanoians’ Choice of Non-Motorized Transport Mode to Access Bus Stations

Hanoi’s rapid urbanization has led to a surge in private vehicle ownership, particularly motorcycles, amidst inadequate public transportation infrastructure. Despite government efforts, many still prefer motorized transport, citing mobility and safety concerns, exacerbated by insufficient pedestrian infrastructure. This study examines the motivations behind this reliance on motorized vehicles, particularly motorcycles, in Hanoi. Findings reveal safety and convenience as primary factors driving motorized transport use, especially for accessing bus stations. Economic incentives could promote non-motorized travel and public transport adoption. Policy implications highlight the importance of addressing economic factors and improving access infrastructure to manage motorized vehicle reliance and foster sustainable urban mobility in Hanoi.

The Ethical Choice of Business English Interpreters under Chesterman’s Model of Translation Ethics

This paper explores the ethical challenges encountered by business English interpreters using Chesterman’s Model of Translation Ethics,set against the context of economic globalization and the“Belt and Road”initiative.With the increasing demand for interpreters,the paper delves into the ongoing discussion about the role of AI in translation and its limitations,especially concerning cultural subtleties and ethical issues.It highlights the importance of human interpreters’cross-cultural understanding and the ethical principles that inform their work,such as the Ethics of Representation,Service,Communication,Norm-based Ethics,and Commitment.Moreover,the paper examines how these ethical models are applied in practical business situations,including business banquets,business negotiations,business talks and business visits,etc.,and investigates the cultural misunderstandings that may occur during these interactions.The study concludes that although AI provides efficiency and cost savings,human interpreters are essential for their capacity to handle the intricacies of cross-cultural communication with cultural awareness and ethical discernment.

Editor-in-Chief articles of choice and comments from January to June 2024

As the Editor-in-Chief of the World Journal of Gastroenterology,I carefully review all articles every week before a new issue’s online publication,including the title,clinical and research importance,originality,novelty,and ratings by the peer reviewers.Based on this review,I select the papers of choice and suggest pertinent changes(e.g.,in the title or text)to the company editors responsible for publication.This process,while time-consuming,is essential for assuring the quality of publications and highlighting important articles that readers may revisit.

Editor-in-Chief articles of choice and comments at the year-end of 2023

As the Editor-in-Chief of World Journal of Gastroenterology,every week prior to a new issue’s online publication,I perform a careful review of all encompassed articles,including the title,clinical and/or research importance,originality,novelty,and ratings by the peer reviewers.Based on this review,I select the papers of choice and suggest pertinent changes(e.g.,in the title)to the Company Editors responsible for publication.This process,while time-consuming,is very important for assuring the quality of publications and highlighting important articles that Readers may revisit.

The Influence of Social Media on College Choice among Undergraduates Majoring in Big Data Management and Application in China:Taking Guilin University of Electronic Technology as an Example

This study aims to investigate the influence of social media on college choice among undergraduates majoring in Big Data Management and Application in China.The study attempts to reveal how information on social media platforms such as Weibo,WeChat,and Zhihu influences the cognition and choice process of prospective students.By employing an online quantitative survey questionnaire,data were collected from the 2022 and 2023 classes of new students majoring in Big Data Management and Application at Guilin University of Electronic Technology.The aim was to evaluate the role of social media in their college choice process and understand the features and information that most attract prospective students.Social media has become a key factor influencing the college choice decision-making of undergraduates majoring in Big Data Management and Application in China.Students tend to obtain school information through social media platforms and use this information as an important reference in their decision-making process.Higher education institutions should strengthen their social media information dissemination,providing accurate,timely,and attractive information.It is also necessary to ensure effective management of social media platforms,maintain a positive reputation for the school on social media,and increase the interest and trust of prospective students.Simultaneously,educational decision-makers should consider incorporating social media analysis into their recruitment strategies to better attract new student enrollment.This study provides a new perspective for understanding higher education choice behavior in the digital age,particularly by revealing the importance of social media in the educational decision-making process.This has important practical and theoretical implications for higher education institutions,policymakers,and social media platform operators.

Choice between Ways of Talent Training in Marine Cultural Industry--Based on Collaborative Innovation of Governments, Enterprises, Colleges, Scientific Institutions and Users

Based on the present situation of talent training in marine cultural industry,the collaborative innovation mode of governments,enterprises,colleges,scientific institutions and users was used to study the ways of talent training in marine cultural industry.

瑞波西利联合内分泌治疗用于绝经前侵袭性HR+/HER2-晚期乳腺癌患者:随机Ⅱ期RIGHT Choice试验

1文献来源Lu Y-S, Mahidin EIBM, Azim H, et al.Abstract GS1-10:Primary results from the randomized phaseⅡRIGHT Choice trial of premenopausal patients with aggressive HR+/HER2-advanced breast cancer treated with ribociclib+endocrine therapy vs physician’s choice combination chemotherapy[J].Cancer Res,2023,83(5S):GS1-10.

Consumers’experiences and preferences for plant-based meat food:Evidence from a choice experiment in four cities of China

This paper examined consumers’experiences in and preferences for plant-based meat(PBM)food and their respective correlates,based on data from an online survey of 579 consumers in four major cities in China in early 2021.We first described consumers’experiences in consuming and purchasing PBM food and their correlates,and then analyzed consumer preferences using hypothetical choice experiment.The experiment offered consumers various options to purchase burgers made from PBM or animal-based meat(ABM),combined with different countries of origin(COO),taste labels,and prices.Our data showed that respondents hold overall positive attitudes toward PBM food;85 and 82%of respondents reported experience in eating and purchasing PBM food,respectively.More than half of them ate PBM food because they wanted to try new food(58%),or were interested in healthy food(56%).Income,religion,and dietary restrictions were significantly correlated with consumers’experiences in PBM food consumption.Results from the Random Parameter Logit Model based on the hypothetical choice experiment data showed that 79%of respondents chose PBM burgers and were willing to pay an average of 88 CNY for a PBM burger.We also found that 99.8 and 83%of respondents are willing to buy burgers made in China and those with a taste label,with a willingness to pay(WTP)of 208 and 120 CNY,respectively.The heterogeneity test revealed that females and those with at least a bachelor’s degree,higher income,religious beliefs,and dietary restrictions are more likely to buy PBM burgers than their counterparts.

Dynamic portfolio choice with uncertain rare‑events risk in stock and cryptocurrency markets

In response to the unprecedented uncertain rare events of the last decade,we derive an optimal portfolio choice problem in a semi-closed form by integrating price diffusion ambiguity,volatility diffusion ambiguity,and jump ambiguity occurring in the traditional stock market and the cryptocurrency market into a single framework.We reach the following conclusions in both markets:first,price diffusion and jump ambiguity mainly determine detection-error probability;second,optimal choice is more significantly affected by price diffusion ambiguity than by jump ambiguity,and trivially affected by volatility diffusion ambiguity.In addition,investors tend to be more aggressive in a stable market than in a volatile one.Next,given a larger volatility jump size,investors tend to increase their portfolio during downward price jumps and decrease it during upward price jumps.Finally,the welfare loss caused by price diffusion ambiguity is more pronounced than that caused by jump ambiguity in an incomplete market.These findings enrich the extant literature on effects of ambiguity on the traditional stock market and the evolving cryptocurrency market.The results have implications for both investors and regulators.

Poke And Delayed Drink Intertemporal Choice Task(POKE-ADDICT):An open-source behavioral apparatus for intertemporal choice testing in rodents

Advancements in neuroscience research present opportunities and challenges,requiring substantial resources and funding.To address this,we describe here“Poke And Delayed Drink Intertemporal Choice Task(POKE-ADDICT)”,an open-source,versatile,and cost-effective apparatus for intertemporal choice testing in rodents.This allows quantification of delay discounting(DD),a cross-species phenomenon observed in decision making which provides valuable insights into higher-order cognitive functioning.In DD,the subjective value of a delayed reward is reduced as a function of the delay for its receipt.Using our apparatus,we implemented an effective intertemporal choice paradigm for the quantification of DD based on an adjusting delayed amount(ADA)algorithm using mango juice as a reward.Our paradigm requires limited training,a few 3D-printed parts and inexpensive electrical components,including a Raspberry Pi control unit.Furthermore,it is compatible with several in vivo procedures and the use of nose pokes instead of levers allows for faster task learning.Besides the main application described here,the apparatus can be further extended to implement other behavioral tests and protocols,including standard operant conditioning.In conclusion,we describe a versatile and cost-effective design based on Raspberry Pi that can support research in animal behavior,decision making and,more specifically,delay discounting.

Accessibility Measures in Modal Choice Models: A Proof of Concept Applied to Freight Transport

Modal choice models applied to interregional or international freight transportation network models are often based on rather coarse origin-destination matrices, containing annual transported tonnages between (sub)regions, for instance. Generally, only basic (sometimes constructed) independent variables (transportation costs or transit times) are used because other variables such as shipment sizes, service frequencies, etc. are not available. Using origin-destination matrices and an assignment model, it is also possible to compute spatial accessibility measures that can further be used as additional explanatory variables. Indeed, several published studies have identified network accessibility as an important element in the mode-choice decision. This paper also shows that the inclusion of an accessibility measure in the utility functions of a logit model substantially improves the performance of a transportation network model, both in the modal choice and the assignment levels of the classical four-step model. Consequently, the assignment of the estimated modal demands results in more accurate estimated traffic on the networks. The model presented in this paper is to be considered as a proof of concept because its workflow should further be streamlined to make it easily useable by modelers.

How Users Perceive Infrastructure Development Affects Their Transport Mode Choice

Transport infrastructure development and perception vary across and within countries, influencing mode choice among road users. This study explores how road users perceive the development of infrastructure modes, service attributes, embedded safety levels, and commuting modes. Additionally, the research examines whether participants’ environmental backgrounds impact their mode choice patterns. The study gathered responses from 1169 participants residing in two regions of Amman, Jordan, each with distinct infrastructure development and population densities. Participants completed a standardized questionnaire, and several statistical techniques were employed for analysis. The findings revealed that facilities’ infrastructure attributes, development, and safety were assessed using three indices. Both participant groups perceived these indices differently on average. Residents of low population density areas with relatively developed infrastructure showed more consistent assessments, irrespective of their most frequently used mode of transportation, tending towards lower scores. Interestingly, subjective ratings of infrastructure development were higher (4.96) than attribute-based ratings (4.32). Despite their generally low-quality perception, public transportation services received the highest appraisal (4.9). Conversely, pedestrian infrastructure complementing public transport received the lowest assessment (4.57), only slightly higher than street environments (4.59). The study found weak associations between subjective service characteristics ratings. Traveler and trip characteristics influenced mode choice and trips more than infrastructure perception. In conclusion, the study suggests that policies should be developed to encourage green transportation, ensure social equality and safety. In addition, the study contributes to understanding perceptions about transport infrastructure, modes of transportation, and the factors that influence sustainable and equitable transportation systems.

A Study of the Self-efficacy of Viola Majors in Chinese Universities Regarding Career Choice

This study examined and analysed the impact of self-efficacy on the career decisions of 52 viola students enrolled in Chinese universities.According to the findings,the level of self-efficacy influences the learning and career decisions of students directly.Higher self-efficacy can positively affect how individuals perceive their past experiences and those of others.Therefore,a high degree of self-efficacy can be advantageous.Self-efficacy is primarily influenced by a person’s prior experiences,alternative experiences,verbal persuasion,and physical and emotional state during work-based learning.Schools may offer courses that foster and improve the development of self-efficacy in order to help viola majors in improving their self-efficacy effectively.

Traffic Speed Interface Development in Route Choice Decision

In this paper,a method has been developed based on historic traffic data(speed),which helps the commuters to choose routes by their intelligence knowing the traffic conditions in Google maps.Data has been collected on basis of video analysis from several segments between Tuker Bazar and Bandar Bazar route.For each of the video footage,a reference length has been recorded with measurement tape for use in video analysis.A software has been also developed based on Java language to get the traffic information from historic data,which shows the output as images consisting of traffic speed details on the available routes by giving day and time limit as inputs.The developed models provide useful insights and helpful for the policy makers that can lead to the reduction of traffic congestion and increase the scope of intelligence of the road users,at least for the underdeveloped or developing country where navigation is still unavailable.

Education Voucher Scheme in India: Would Lead to School Choice and Universal Education?

To remove obstacles in the path of‘Education for All’,the government of India launched several programs,Sarva Shiksha Abhiyan(SSA)being one of them.Despite several attempts,the government has failed to be successful in providing education to all students and the impact of such schemes has not been very good at the ground level.In India,children are not absent from school owing to a lack of demand;rather,low quality of government education delivery is a major cause for their absence.There is a need to redefine the Indian education system or policy to a new level as government schools are unable to fulfil the growing demand for high-quality education.Direct government funding to children or parents rather than schools can provide parents or children with the ability to select the school of their choice,whether it is a government or private school.This may be accomplished through the education voucher scheme.Governments do not need to spend any additional public funds on vouchers to implement this approach.The education voucher scheme deserves an effort among the several approaches that are being pursued to improve school education.