The Cisadane Watershed is in a critical state, which has expanded residential areas upstream of Cisadane. Changes in land use and cover can impact a region's hydrological characteristics. The Soil and Water Assessment Tool (SWAT) is a hydrological model that can simulate the hydrological characteristics of the watershed affected by land use. This study aims to evaluate the impact of land use change on the hydrological characteristics of the Cisadane watershed using SWAT under different land use scenarios. The models were calibrated and validated, and the results showed satisfactory agreement between observed and simulated streamflow. The main river channel is based on the results of the watershed delineation process, with the watershed boundary consisting of 85 sub-watersheds. The hydrological characteristics showed that the maximum flow rate (Q max) was 12.30 m³/s, and the minimum flow rate (Q min) was 5.50 m³/s. The study area's distribution of future land use scenarios includes business as usual (BAU), protecting paddy fields (PPF), and protecting forest areas (PFA). The BAU scenario had the worst effect on hydrological responses due to the decreasing forests and paddy fields. The PFA scenario yielded the most favourable hydrological response, achieving a notable reduction from the baseline BAU in surface flow, lateral flow, and groundwater by 2%, 7%, and 2%, respectively. This was attributed to enhanced water infiltration, alongside increases in water yield and evapotranspiration of 3% and 15%, respectively. l Therefore, it is vital to maintain green vegetation and conserve land to support sustainable water availability.

This study examines how the framing of organizational gender-equity policies shapes support among Generation Z employees. Drawing on performativity (Butler, 1990) and intersectionality (Crenshaw, 1991), we conceptualize framing as mediating how Gen Z employees perceive equity initiatives. Using a mixed-methods design, we combine survey data from 4,861 Gen Z respondents in 30 countries with directed content analysis of four HR policy documents (coded for equity vs enforcement, identity recognition, and youth engagement). Results reveal a gender gap: Gen Z women strongly endorse inclusive equity measures, consistent with evidence that women show stronger support for equality policies, whereas Gen Z men are more skeptical of policies framed as exclusive or punitive – mirroring polls finding many Gen Z men say equality efforts have gone too far. These findings suggest that performative policy framing activates social identities differently by gender and that intersectional policy language affects reception. Practically, we recommend framing equity initiatives in terms of shared fairness and collective benefit, using transparent rationale and inclusive identity language. Gen Zers expect fair pay, inclusive policies, and transparency, so HR communications should emphasize fairness and allyship to enhance legitimacy and support among this cohort.

Under the concept of independent maintenance proposed by the Meteorology, Climatology, and Geophysics Agency (BMKG) for operational equipment, a thorough analysis of its management processes is necessary. Leadership involvement at various levels can affect maintenance outcomes, impacting sustainability. This research creates a thinking model that connects responsible leadership (RL) with sustainable performance (SP) through agile organization (AO) mediation and maintenance management implementation (MMI) in the management of leading operations equipment. The method used was a survey of 366 respondents who were BMKG employees, and explanatory analysis was analyzed based on descriptive statistical analysis using SmartPLS. The research results show that the third hypothesis proposed is acceptable, and the two mediator variables are partial mediation. The discussion of the study results shows some theoretical and practical implications for achieving the goals of SP, where organizations should encourage RL behavior that can implement current practices regarding AO and MMI. The test results show that AO and MMI have a significant role as mediators in encouraging the influence of RL on SP. This study is the first step in examining the relationship of RL to SP using AO and MMI mediation. Furthermore, this model can be developed and analyzed in other sectors or fields to increase knowledge.

Four alloys based on niobium and containing about 33wt.%Cr, 0.4wt.C and, in atomic content equivalent to the carbon one, Ta, Ti, Hf or Zr, were elaborated by classical foundry under inert atmosphere. Their as-cast microstructures were characterized by X-ray diffraction, electron microscopy, energy dispersion spectrometry and while their room temperature hardness was specified by Vickers indentation. The microstructures are in the four cases composed of a dendritic Nb-based solid solution and of an interdendritic NbCr₂ Laves phase. Despite the MC-former behavior of Ta, Ti, Hf and Zr usually observed in nickel or cobalt-based alloys, none of the four alloys contain MC carbides. Carbon is essentially visible as graphite flakes. These alloys are brittle at room temperature and hard to machine. Indentation shows that the Vickers hardness is very high, close to 1000HV_10kg. Indentation lead to crack propagation through the niobium phase and the Laves areas. Obviously no niobium-based alloys microstructurally similar to high performance MC-strengthened nickel-based and cobalt-based can be expected. However the high temperature mechanical and chemical properties of these alloys remain to be investigated.

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.

Purpose: This article explores the adoption of Artificial Intelligence (AI) in Human Resource Management (HRM) in the UAE, focusing on the critical challenges of fairness, bias, and privacy in recruitment processes. The study aims to understand how AI is transforming HR practices in the UAE, highlighting the issues of bias and privacy while examining real-world applications of AI in recruitment, employee engagement, talent management, and learning and development. Methodology: Through case study methodology, detailed insights are gathered from these companies to understand real-world applications of AI in HRM. A comparative analysis is conducted, comparing AI-driven HRM practices in UAE-based organizations with international examples to highlight global trends and best practices. Findings: The research reveals that while AI holds significant potential to streamline HR functions such as recruitment, onboarding, performance monitoring, and talent management, it also discusses challenges and strategies companies face and develop in integrating AI into their HRM processes, reflecting the broader context of AI adoption in the UAE’s HR landscape. Originality: This paper contributes to the growing body of literature on AI in HRM by focusing on the unique context of the UAE, a rapidly developing market with a highly diverse workforce. It highlights the specific challenges and opportunities faced by organizations in the UAE when implementing AI in HRM, particularly regarding fairness, bias, and data privacy.