The purpose of the article is to present the current situation in the rail freight transport in Thailand and the direction of changes in this area. Firstly, Thailand statistics in volume of freight transport by rail and modal share of freight transport have been presented. Afterwards, problems and obstacles in railway operational practices and in using rail transport services have been identified to improve railway system in Thailand and the outcome was assessed in terms of railway capacity and utilization. The findings were used to outline the direction of changes in rail freight transport. The results show that the rail transport capacity in double-track would increase by 48% (at present by 15.5% and as plan by 30%) and the ratio by rail transport to total freight transport would increase from at present by 1.87% to 10% in 2037.

Information transparency is a basic principle of good governance that few studies in the literature have thoroughly examined. Riau Province in particular has a high record of land and forest conflicts that needs urgent response, yet environmental policies have mostly been scrutinized for its resource extraction and regulation aspects, not their aspect of information transparency. Low proactive disclosure of information from local governments is a recurring issue in Riau Province, so FITRA Riau initiated the Public Information Openness Index (IKIP) to cover the Riau Province and 12 regencies/cities. To address this research gap of governmental public bodies’ information transparency, this study conducted the novel substantive approach critical review to see the extent of local government’s transparency regarding their budgeting for one of Riau’s most prevalent issues, namely land and forest governance (TKHL). From March to September 2019, this study used a triangulation of data collected from information access tests, IKIP evaluation, and focus group discussion involving the Riau Information Commission, the Information Management and Documentation Officers (PPID) of the 12 regencies, and the Governor of Riau Province. After analyzing the four aspects of regulation, institution, budget, and TKHL information, results determined that the most open region in Riau Province is Indragiri Hulu, and the least open region is Kuantan Singingi. Information transparency is still limited in procedural terms, in which all regions have more or less fulfilled the administrative regulation demands but the substance of the public information across all aspects is too generic to truly inform the public of the regions’ TKHL.

Research on retailers’ behavioral intention and behavior of using the omnichannel ecommerce solution (OES) used the Unified Theory of Acceptance and Use of Technology (UTAUT2) model and supplemented the other factors such as seamless supply, omnichannel integration. Research concerns about behavioral intention and behavior of using OES as this is a global trend; OES has become one of the top priorities for businesses to thrive in the rapidly changing market and retain customers; increasingly high standards are being set for digital experiences. Therefore, retailers must quickly adapt to new trends for sustainable development to keep up with the transformation and increase the use of OES. The results show that effort expectation, social influence, hedonic motive, retailers’ capacity, seamlessly connecting have a positive impact on retailers’ behavioral intention and behavior of using OES. Behavioral intention and favorable conditions have a positive impact on behavior of using OES. Meantime, omnichannel integration have a negative impact on behavior of using OES in Vietnam. This research helps managers and OES providers to develop their skills and expertise, and the study results may prove diagnostically useful to the retailers’ behavioral intention and behavior of using OES.

This study analyses the dynamic development of soybean (Glycine max (L.) Merr.) breeding in Russia, particularly examining its historical development, status, and future predictions. With the global demand for vegetable protein rising, understanding Russia’s potential contribution becomes crucial. This research provides valuable insights, offering precise data that may be unfamiliar to international researchers and the private sector. The authors trace the history of soybean selection in Russia, emphasizing its expansion from the Far East to other regions in Russia. The expansion is primarily attributed to the pioneering work of Soviet breeder V. A. Zolotnitsky and the development of the soybean variety in the Amur region in the 1930s. The study highlights the main areas of soybean variety originators, with approximately 40% of foreign varieties registered. The Krasnodar and Amur regions emerge as critical areas for breeding soybean varieties. In Russia, the highest yield potential of soybeans is in the Central Federal District. At the same time, the varieties registered in the Volga Federal District have higher oil content, and the Far Eastern Federal District has high protein content in the registered soybean varieties. The research outlines the state’s pivotal role in supporting soybean breeding and fostering a competitive market with foreign breeders. The study forecasts future soybean breeding development and the main factors that can influence the industry.

Breast cancer was a prevalent form of cancer worldwide. Thermography, a method for diagnosing breast cancer, involves recording the thermal patterns of the breast. This article explores the use of a convolutional neural network (CNN) algorithm to extract features from a dataset of thermographic images. Initially, the CNN network was used to extract a feature vector from the images. Subsequently, machine learning techniques can be used for image classification. This study utilizes four classification methods, namely Fully connected neural network (FCnet), support vector machine (SVM), classification linear model (CLINEAR), and KNN, to classify breast cancer from thermographic images. The accuracy rates achieved by the FCnet, SVM, CLINEAR, and k-nearest neighbors (KNN) algorithms were 94.2%, 95.0%, 95.0%, and 94.1%, respectively. Furthermore, the reliability parameters for these classifiers were computed as 92.1%, 97.5%, 96.5%, and 91.2%, while their respective sensitivities were calculated as 95.5%, 94.1%, 90.4%, and 93.2%. These findings can assist experts in developing an expert system for breast cancer diagnosis.