This study aims to analyze the Penta helix collaboration model for involving reserve component personnel in disaster resilience in Malang Regency. A qualitative approach was used with an in-depth interview method involving nine informants from various Penta helix actors, namely academia, business, the community, government, and the Media. The main findings indicate that the Penta helix collaboration model has the potential to enhance disaster resilience in Malang Regency. Its strengths lie in inclusive participation, transparency, clear leadership, and the commitment of stakeholders. However, there are still weaknesses, such as a lack of coordination, limited resources, and suboptimal role understanding that hinder the involvement of reserve component personnel. Each actor makes significant contributions: academics provide knowledge, businesses aid in logistics, communities engage in mitigation and emergency response, the government formulates policies, and the media disseminates information. Major challenges include a lack of coordination, limited resources, miscoordination, bureaucracy, insufficient training, and unclear legal frameworks. Improvement efforts include strengthening coordination, increasing resource capacity, clarifying roles, developing guidelines, and enhancing training. In conclusion, the Penta helix collaboration model in Malang Regency has great potential but requires improvements to enhance its effectiveness, providing insights for stakeholders to strengthen disaster resilience in the region.

Heavy metal contamination in soil poses a significant environmental challenge globally, affecting agricultural productivity and human health. Phytoremediation, using plants to extract and detoxify heavy metals, presents a promising solution. This study investigates the novel potential of Echium plantagineum, a metal-tolerant species, in phytostabilization and phytoremediation and explores the role of metallothioneins in heavy metal reduction. A comprehensive literature review identified known metallothioneins involved in heavy metal reduction across various plant species. Moreover, genome annotation and gene prediction of Echium plantagineum were performed, predicting a total of 39,520 proteins. This comprehensive protein list facilitates the identification of metallothioneins or other metal-related proteins with potential functional roles in heavy metal tolerance, suggesting new targets to improve the effectiveness of phytoremediation. The sequences of these proteins were utilized to construct a protein BLAST database, against which known metallothioneins protein sequences from other plant species were subjected to BLAST searches, resulting in 41 top hits. Subsequent 3D modeling, structural analysis, protein-metal virtual screening, and functional annotation of the proteins revealed novel high affinities of Ctr copper transporter, zinc/iron permease, and nicotianamine synthase proteins with nickel, zinc, and zinc ion, suggesting their unexplored roles in the uptake of aforementioned ligands. Notably, this study identifies novel metallothioneins proteins in Echium plantagineum, highlighting their role in metal tolerance and phytoremediation.

Natural disasters are natural activities that can disrupt various aspects. Natural disasters cannot be avoided, but the impact of natural disasters can be minimized through mitigation. This can be known through event history to determine an area’s vulnerability to natural disasters. This research aims to determine regional natural disaster vulnerability by calculating the natural disaster index. The data used in this research refers to data from the 2021 PODES data collection, which contains the intensity of natural disasters and casualties according to the type of natural disaster in Indonesia in 2020. The method used for the calculation is the weighted index method. The results of this research produced 5 clusters based on the level of natural disaster vulnerability according to sub-district/village. The top five provinces in Indonesia that have the highest natural disaster-prone areas are Aceh, North Sumatra, West Java, East Java, and Central Sulawesi. Research shows that sub-districts/villages in Indonesia are known according to their level of vulnerability to natural disasters. These results can be used as a reference for the government to carry out mitigation so that accelerated development in the local area can continue.

Soil erosion in the agricultural landscape of Assam has been impacting the livelihoods of millions. In administrative regions like districts, which are vulnerable to natural disasters like floods and bank erosion, GIS-based soil erosion estimating studies can help planners and policymakers identify areas of soil erosion to implement scientific conservation measures. The main purpose of this study is to estimate soil loss and to determine soil loss zones in the Morigaon district of Assam. The Revised Universal Soil Loss Equation (RUSLE) combined with GIS has been incorporated into the present study. The five parameters of RUSLE, namely, rainfall-runoff erosivity, soil erodibility, topographic factor, cover management, and conservation practices, are individually estimated from relevant and authentic data sources, and all these parameters are quantified in GIS. The research findings show that 46.89% of areas in the district are in moderate soil loss zone, eroding 0.78 ton/ha/year, 34.27% of areas are in low soil loss zone, 15.36% of areas are in high soil loss zone, eroding about 12.22 ton/ha/year and 3.47% of areas are in a very high soil loss zone, eroding 192.8 ton/ha/year. The high soil loss zones mainly cover the riverine areas and bare lands in the district. As per our estimation, there is an average of 205.85 tonnes of soil loss in the district per hectare per year.

Silver nanoparticles (AgNPs) were synthesized utilizing various methods, including bioreducing agents. The synthesis involved the use of silver nitrate (AgNO3) as the precursor and banana frond extract as the bioreducing agent, with different volume ratios being tested. Subsequently, the most optimal variant of AgNPs was immobilized onto activated carbon (AC) derived from soybean seeds. The AgNPs/SAC composite was subjected to thorough characterization using UV-Vis diffuse reflectance spectroscopy and X-ray diffraction (XRD). A series of degradation experiments were then conducted using methylene blue, with the reaction duration following a specific protocol. A comparison of methylene blue concentrations before and after the photodegradation process was made to assess the reaction’s efficacy. The findings revealed that the ideal ratio between the bioreducing agent and precursor was 9:30 (v/v). The AgNPs/SAC composite exhibited a peak absorption at a wavelength of 420-440 nm. The UV-DRS characterization of AgNPs/SAC unveiled a band gap energy of 1.52 eV. The AgNPs supported on AC displayed a peak absorption wavelength of 5,438.5 nm, showcasing a face-centered cubic (FCC) structure. The AgNPs/SAC effectively decreased the concentration of methylene blue through a combination of adsorption and photodegradation mechanisms, achieving efficiencies of 35.3813% and 81.1636%, respectively. The AgNPs/SAC composite demonstrates significant potential for efficient and sustainable water treatment.

The residual dye within the soil from the synthetic dye manufacturing and fabric industries is a global state of affairs. The discharge consists of an excessive content of pigments and other components, creating complicated structures. It leads to damage to the soil structure and its fertility. Amid existing amputation methods, microbial remediation takes significant consideration owing to its subordinate charge, sophisticated proficiency, and fewer influences on the milieu. The current study was premeditated for the seclusion and portrayal of azo dye- dye-decolorizing bacteria, which is a criterion for emerging a microorganism-facilitated treatment of adulterating dyes. In this present investigation, twenty sorts of bacteria that were talented to decolorize seven kinds of azo dyes (Crystal Violet, Methylene Blue, Safranine, Congo Red, Methyl Orange, Malachite Green, and Carbol Fuchsin) were isolated from dye-polluted soil from the dying industry near the railway station; in Calicut. Based on 16S rDNA scrutiny, the most resourceful decolourizing bacteria for these azo dyes was identified as Priestia megaterium strain NRBC 15308. After characterization, Priestia megaterium was found to be optimally nurtured at 35°C, on a pH of 7, with a 1.5% glucose concentration in a minimal salt medium. 100% decolorization of a 6% dye solution was found at optimal conditions by Priestia megaterium. Priestia megaterium can decolorize cotton and gauze suspended in the dye solution in 24 hours. Bioremediation studies with the isolate proved that the inhibition effect of the dye solution on seed germination could be removed by the application of Prestia megaterium. The isolation of Priestia megaterium strain NRBC 15308 as a dye-degrading bacterium holds immense promise for remediating dye-contaminated soil.

Microbially contaminated objects used in everyday life have been shown to impact human health by harboring infections through direct or indirect contact. For this reason, the development of alternative methods for bacterial elimination that do not lead to resistant microorganisms, large quantities of residues, or human cytotoxicity is warranted. Due to their proven bactericidal power, the use of electromagnetic waves lower than ultraviolet-C radiation would constitute a possible alternative. The main aim of this research was to determine the effect of 462 nm radiation emitted by light-emitting diodes (LEDs) on the most frequent bacteria contaminating everyday objects and surfaces in residential and hospital environments. The rationale behind the selection of this specific frequency within the blue light spectrum, in contrast to previous research exploring the application of higher frequencies, was its safety for individuals’ eyes and skin. The findings suggest that the use of low-frequency blue light can be effective in destroying environmental microorganisms stemming from the skin microbiome and mucous membranes, and even fecal bacteria, present in the surfaces of everyday objects such as inter alia, mobile phones, remote controls, credit cards, and of which some present high antibiotic resistance.

This study aims to develop a comprehensive flood hazard map for effective hazard management in the Noa river basin, located in Assam, India, through the integration of Geographic Information System (GIS) tools and a Maximum Entropy (MaxEnt) model. The MaxEnt machine learning algorithm was employed, utilizing eight selected geographic and environmental parameters as predictors to generate the flood hazard map. The accuracy of the generated map was evaluated using the Area Under the Curve (AUC) metric. Key findings of the study identified elevation and slope as critical parameters in the assessment of flood risk. Results revealed that the flood hazard map produced by the MaxEnt model achieved an AUC value of 0.85, indicating high predictive accuracy. The research underscores the significance of flood hazard maps as essential tools for policymakers, enabling the identification of areas vulnerable to severe environmental and economic damage. By providing a reliable and precise assessment of flood-prone zones, this study contributes valuable insights for the formulation of effective flood management strategies and mitigation measures. The implementation of such hazard maps is crucial in enhancing preparedness and resilience against flooding events, ultimately safeguarding lives, property, and infrastructure in the Noa River basin.

The port is a place for ships as sea transportation to dock. The port, as a place of entry and exit for goods or passengers from various regions, places, and environments, encourages the potential for disease transmission to a new environment. Pathogens present in the environment can directly contact the human body through air, touch, and transmission through food around areas with high mobilization. Therefore, this study aims to look at the results of hygiene observations and laboratory testing related to food, drinking water, and air samples at Galala Port, Ambon City. This study used descriptive research with a cross-sectional research design. From all parameter examination results, several examination results do not meet the standards such as food microbiology examination results (E. coli bacteria > 3.6MPN/gr), sanitation (walls and floors are not watertight), the presence of mosquito larvae (seven Aedes albopictus mosquito larvae), drinking water microbiology (total Coliforms 64 CFU.100 mL-1), and clean water microbiology (E. coli > 250 CFU. 100 mL-1 and total Coliforms 8 CFU.100 mL-1). Therefore, it can be concluded that the inspection of restaurants carried out at Galala port, Ambon City, is not appropriate and does not meet the standards according to the Minister of Health Decree number 942 of 2003.

Water plays a crucial role in the environment and in the process of liquefaction, which can occur during moderate to major earthquakes and cause significant structural damage. Liquefaction is defined as the transformation of granular material from a solid state to a liquid state, a process driven by increased pore water pressure and reduced effective stress within the soil. When an earthquake strikes, the shaking causes the pore water pressure between the sand grains to rise, which in turn reduces the contact forces between the grains. As a result, the sand loses its effective shear strength and starts to behave more like a fluid, leading to instability and potential collapse of structures built on such ground. Liquefaction can occur in moderate to major earthquakes, resulting in severe damage to structures. The transformation of granular material from a solid state to a liquid state due to increased pore pressure and reduced effective stress is defined as liquefaction. When this happens, the sand grains lose their effective shear strength and will behave more like a fluid. This phenomenon of dissolution of soil damages trees’ stability and disturbs the formation of the earth’s surface. Liquefaction resistance of soil depends on the initial state of soil to the state corresponding to failure. The liquefaction resistance can be evaluated based on tests on laboratory and in situ tests. For this research, liquefaction resistance using in-field tests based on SPT N values is attempted. Cyclic resistance ratio (CRR) is found based on the corrected N value. About 16 bore logs have been selected for the factor of safety calculation. The factor of safety for soil was arrived at by taking into account of corresponding corrected SPT N values. The liquefaction hazard map is prepared for the moment magnitude of 7.5-7.6 M w. It is also found that the areas close to water bodies and streams have the factor of safety less than unity. The bore log of locations having a factor of safety less than one indicates that up to a depth of about 6 m, very loose silty sand with clay and sand is present, which are defined as medium to fine sand having low field N values.