Aakash Deep^*, Sushil Kumar, Bhagwan Singh Chaudhary

Revue Internationale de Géomatique, Vol.35, pp. 79-100, 2026, DOI:10.32604/rig.2026.074969 - 05 February 2026

Abstract The assessment of groundwater quality is crucial for ensuring its safe and sustainable use for domestic and agricultural purposes. The Kurukshetra district in the Indian state of Haryana relies heavily on groundwater to meet household and agricultural needs. Sustainable groundwater management must be assessed in terms of suitability for domestic and agricultural needs in a region. The current study analyzed pre-monsoon geochemical data from groundwater samples in the study area for 1991, 2000, 2010, and 2020. A Geographic Information System (GIS) was used to create spatial distribution maps for hydrogen ion concentration, total hardness, total… More >

Zakia Akter¹, Sumona Akter Jannat², Sheikh Md. Shibly¹, Afroza Sultana¹, Amdadul Hoque Amran¹, Joairia Hossain Faria¹, Sabina Yeasmin¹, Md. Parvez Anwar^1,*

Phyton-International Journal of Experimental Botany, Vol.95, No.1, 2026, DOI:10.32604/phyton.2026.075524 - 30 January 2026

Abstract Seaweed extract contains plant growth regulators and bio-stimulants that enhance plant growth and development. In Bangladesh, winter rice (Boro rice) in the nursery bed often shows poor seed emergence and weak seedling growth due to low temperature. This problem can be addressed by using seaweed extract as a seed priming agent and bio-stimulant. The objective of this study was to evaluate the effectiveness of seaweed extract (Crop Plus) on seed emergence, seedling growth, and vigor of winter rice in the nursery. Two experiments were conducted at Bangladesh Agricultural University using BRRI dhan89. The laboratory experiment… More >

Aaron David Lugo-Palacios¹, Edgar Omar Rueda-Puente², César Omar Montoya-García², Ignacio Orona-Castillo³, Urbano Nava-Camberos³, José Luis García-Hernández^3,*

Phyton-International Journal of Experimental Botany, Vol.95, No.1, 2026, DOI:10.32604/phyton.2025.075449 - 30 January 2026

Abstract To ensure the efficient use of resources, particularly in water-scarce arid and semi-arid regions where abiotic stress threatens food security, assessing soil and climate suitability for specific crops is crucial. Simultaneously, food production must align with sustainable development goals by minimizing negative environmental impacts. Therefore, establishing agro-climatic suitability using a spatiotemporal approach is essential. This involves three key steps: first, determining the climatically appropriate months based on the species’ requirements (temporal suitability), and second, establishing the soil suitability of specific plots (spatial suitability). Following this, quantifying crop evapotranspiration allows for optimized water use. This study… More >

Kirti A. Yadav¹, Yachana Jha¹, Haiam O. Elkatry², Heba I. Mohamed^3,*, Ahmed Mahmoud Ismail⁴, Abdelrahman R. Ahmed^2,*

Phyton-International Journal of Experimental Botany, Vol.95, No.1, 2026, DOI:10.32604/phyton.2026.074570 - 30 January 2026

Abstract Phytophthora blight is a devastating disease of pigeon pea (Cajanus cajan) that severely impacts plant growth and productivity. This study investigates the morphological, anatomical, and biochemical responses of a susceptible variety (ICPL 11260) and a resistant variety (IPAC-02) following infection by Phytophthora. Morphological analyses showed that infection caused a drastic reduction in root length, shoot length, leaf number, fresh weight, and dry weight in the susceptible ICPL 11260 variety, with reductions ranging from 0.5- to 2-fold compared to non-infected controls. Anatomical observations revealed pronounced cellular damage and mycelial invasion in infected ICPL 11260 plants by 30… More >

Yuxin Guo^1,2, Xinqiao Liu^3,*

International Journal of Mental Health Promotion, Vol.28, No.1, 2026, DOI:10.32604/ijmhp.2025.074063 - 28 January 2026

Abstract Background: Mental health concerns among doctoral students have become increasingly prominent, with consistently low levels of well-being making this issue a critical focus in higher education research. This study aims to synthesize existing evidence on the mental health and well-being of doctoral students and to identify key factors and intervention strategies reported in the literature. Methods: A systematic review was conducted to examine the determinants and interventions related to doctoral students’ mental health and well-being. Relevant studies were comprehensively searched in Web of Science, PubMed, Scopus, and EBSCO, with the final search conducted on September 19,… More >

Guebin Choi^*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.073985 - 29 January 2026

Abstract This study proposes a novel forecasting framework that simultaneously captures the strong periodicity and irregular meteorological fluctuations inherent in solar radiation time series. Existing approaches typically define inter-regional correlations using either simple correlation coefficients or distance-based measures when applying spatio-temporal graph neural networks (STGNNs). However, such definitions are prone to generating spurious correlations due to the dominance of periodic structures. To address this limitation, we adopt the Elastic-Band Transform (EBT) to decompose solar radiation into periodic and amplitude-modulated components, which are then modeled independently with separate graph neural networks. The periodic component, characterized by strong More >

Amel Ksibi^*, Hatoon Albadah, Ghadah Aldehim, Manel Ayadi

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.073533 - 29 January 2026

Abstract Sustainable energy systems will entail a change in the carbon intensity projections, which should be carried out in a proper manner to facilitate the smooth running of the grid and reduce greenhouse emissions. The present article outlines the TransCarbonNet, a novel hybrid deep learning framework with self-attention characteristics added to the bidirectional Long Short-Term Memory (Bi-LSTM) network to forecast the carbon intensity of the grid several days. The proposed temporal fusion model not only learns the local temporal interactions but also the long-term patterns of the carbon emission data; hence, it is able to give… More >

Jihoon Moon^*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.071052 - 29 January 2026

Abstract Predicting the behavior of renewable energy systems requires models capable of generating accurate forecasts from limited historical data, a challenge that becomes especially pronounced when commissioning new facilities where operational records are scarce. This review aims to synthesize recent progress in data-efficient deep learning approaches for addressing such “cold-start” forecasting problems. It primarily covers three interrelated domains—solar photovoltaic (PV), wind power, and electrical load forecasting—where data scarcity and operational variability are most critical, while also including representative studies on hydropower and carbon emission prediction to provide a broader systems perspective. To this end, we examined… More >

Firas Mahmood Younis^1,*, Omar Mohammad Hamdoon², Ayad Younis Abdulla¹

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.073483 - 27 January 2026

Abstract This paper presents an experimental analysis of a solar-assisted powered underfloor heating system, designed primarily to boost energy efficiency and achieve reliable desired steady-state temperature in buildings. We thoroughly tested the system’s thermal and operational features by subjecting it to three distinct scenarios that mimicked diverse solar irradiance and environmental conditions. Our findings reveal a strong correlation between variations in solar input and overall system performance. The Solar Fraction (SF), our key energy efficiency metric, varied significantly across the cases, ranging from 63.1% up to 88.7%. This high reliance on renewables resulted in a substantial… More >

Cheng Yang^*, Hanjie Qi, Qing Yin

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.070957 - 27 January 2026

Abstract In order to enhance the off-peak performance of gas turbine combined cycle (GTCC) units, a novel collaborative power generation system (CPG) was proposed. During off-peak operation periods, the remaining power of the GTCC was used to drive the adiabatic compressed air energy storage (ACAES), while the intake air of the GTCC was heated by the compression heat of the ACAES. Based on a 67.3 MW GTCC, under specific demand load distribution, a CPG system and a benchmark system (BS) were designed, both of which used 9.388% of the GTCC output power to drive the ACAES.… More >