A total of 25 SSR primers were screened on 37 putative F₁s derived from the five different crosses. Identified cross specific highly informative SSRs primers, i.e., 14 for the first cross, 10 for the second, 12 for the third and 6 each for fourth and fifth crosses. For the first cross Bhagwa × Daru 17, four primers (HvSSRT_375, NRCP_SSR9, NRCP_SSR12 and NRCP_SSR92) were found to be highly informative with higher 100% hybrid purity index (HPI), PIC (~0.52), and observed heterozygosity (Ho, range 0.87–0.93) values, and two F₁s namely H₁ and H₂ were found to be highly heterotic with a heterozygosity index (HI) of 92.85%. Similarly, for Bhagwa × Nana, three primers (HvSSRT_375, HvSSRT_605 and NRCP_SSR19) had higher HPI (70%–100%), PIC (0.52–0.69), and Ho (0.75–0.33) values, and three F₁s H₁, H₂, and H₄ had 70% (HI). For Bhagwa × IC318712, four SSRs (HvSSRT_254, HvSSRT_348, HvSSRT_826 and NRCP_SSR95) had higher Ho (~0.83), HPI (100%) and PIC (~0.52) values, and four F₁s H₂, H₇, H₉, and H₁₀ showed 91.66% (HI). For Bhagwa × Nayana, HvSSRT_605, HvSSRT_826, and HvSSRT_432, and for Ganesh × Nayana, HVSSRT_375, HVSSRT_605, and HvSSRT_826 were found informative. These markers will be highly useful in developing maps of populations.

COVID-19 pandemic has caused many design bid build projects to suffer losses. Design bid build or DBB has the disadvantage of depth partnering. The research purpose is to reveal the depth of partnering of DBB, the characteristics of existing partnering in DBB through detection in each project life cycle in DBB, then efforts to increase DBB partnering to partnering in integrated project delivery (IPD). The methodology used is secondary data from three project DBB, then validation using focused group discussions (FGD) with expert judgment, then the Delphi method to analyse and propose recommendations. This project recommends that DBB project can improve the project performance so stakeholder can increase partnering toward integrated project delivery (IPD) partnering. This research can be used for increasing partnering in DBB projects towards partnering in IPD. This research will produce strategic recommendations that can be utilized by stakeholders (owner, contractor, designer) in improving project performance to generate great value for the project, will result in long-term project sustainability, improve relationships, and learn valuable lessons for future projects. DBB projects usually experience many problems due to the competitive nature of partnering for owners, contractors, and designers, so it is necessary to develop an overall strategy as an option to improve partnering in DBB project contracts. This research will help create a sustainable project by the owner, contractor, and designer.

The study examined the socio-demographic factors affecting access to and utilization of social welfare services in Yenagoa Local Government Area of Bayelsa State, Nigeria. Quantitative and qualitative approaches were adopted to select 570 respondents from the study area. Probability and non-probability sampling techniques were adopted in the selection of communities, and respondents. The quantitative data were analyzed using frequency distribution tables and percentages, while chi-square statistic was used to determine the relationship between socio-demographic variables and access to and utilization of social welfare services. The qualitative data were analyzed in themes as a complement to the quantitative data. This study reveals that although all the respondents reported knowing available social welfare services, 44.3% reported not having access to existing social services due to factors connected to serendipity variables, such as terrain condition, ethnicity and knowing someone in government. Therefore, the study recommends that the government and other stakeholders should push for the massive delivery of much-needed social welfare services to address the issue of welfare service deficit across the nation, irrespective of the ethnic group and whether the community is connected to the government of the day or not, primarily in rural areas.

This study aims to elucidate the digital transformation process in Tunisian companies, identify its driving factors, and explain its key success factors. We examine a sample of 70 companies across various economic sectors using a Multinomial Logistic regression to assess the impact of digital strategy, corporate culture, and leadership on digital transformation success. The dependent variable “digital maturity” is categorized into low, medium, and high, with medium serving as the reference category. The results indicate a significant and positive effect of digital strategy on digital transformation success. Leadership influences companies at a low level of digital maturity but does not significantly impact those at a high maturity level. Corporate culture does not significantly affect digital transformation. Digital strategy is crucial for the success of digital transformation in Tunisian companies, while leadership plays a role primarily at lower maturity levels. Corporate culture, however, does not significantly contribute to digital maturity. The study provides insights for Tunisian companies and policymakers to focus on developing robust digital strategies and leadership qualities to enhance digital transformation efforts. This research expands the theoretical base on digital transformation in the Tunisian context, identifying critical success factors and barriers, and confirming the significant role of digital strategy in successful digital transformations.

Water splitting, the process of converting water into hydrogen and oxygen gases, has garnered significant attention as a promising avenue for sustainable energy production. One area of focus has been the development of efficient and cost-effective catalysts for water splitting. Researchers have explored catalysts based on abundant and inexpensive materials such as nickel, iron, and cobalt, which have demonstrated improved performance and stability. These catalysts show promise for large-scale implementation and offer potential for reducing the reliance on expensive and scarce materials. Another avenue of research involves photoelectrochemical (PEC) cells, which utilize solar energy to drive the water-splitting reaction. Scientists have been working on designing novel materials, including metal oxides and semiconductors, to enhance light absorption and charge separation properties. These advancements in PEC technology aim to maximize the conversion of sunlight into chemical energy. Inspired by natural photosynthesis, artificial photosynthesis approaches have also gained traction. By integrating light-absorbing materials, catalysts, and membranes, these systems aim to mimic the complex processes of natural photosynthesis and produce hydrogen fuel from water. The development of efficient and stable artificial photosynthesis systems holds promise for sustainable and clean energy production. Tandem cells, which combine multiple light-absorbing materials with different bandgaps, have emerged as a strategy to enhance the efficiency of water-splitting systems. By capturing a broader range of the solar spectrum, tandem cells optimize light absorption and improve overall system performance. Lastly, advancements in electrocatalysis have played a critical role in water splitting. Researchers have focused on developing advanced electrocatalysts with high activity, selectivity, and stability for the oxygen evolution reaction (OER) and hydrogen evolution reaction (HER). These electrocatalysts contribute to overall water-splitting efficiency and pave the way for practical implementation.

One of the main concerns in computer science today is integrating the Internet of Things (IoT) into manufacturing processes. This trend could influence a country’s strategy and policy development regarding technological infrastructure. However, despite extensive research on the implementation of IoT in manufacturing, no study has yet focused on the growing research interest in this topic. Based on 2487 papers indexed in the Scopus database between 2013 and 2023, this bibliometric review examines current trends and patterns in IoT research in manufacturing. The literature was selected and screened using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. Data visualization was created using VOSviewer. The results show a notable increase in research papers centered around IoT in manufacturing. The findings reveal patterns and trends in IoT research publications in the manufacturing sector, author collaboration networks, country collaboration networks, and both established and newly trending topics surrounding IoT in the manufacturing industry.