Stainless steel tubes and pipes are vital in dairy processing but require frequent cleaning, leading to notable energy consumption and environmental impact. This study delves into the cleanability of wet milk deposits at temperatures of 40°C and 60°C on an exceptionally smooth internal surface achieved through magnetic abrasive finishing (MAF) with a surface roughness of 0.01 μm R_a. We compare this surface with non-MAF tubes having surface roughness values of 0.37 and 3.7 μm R_a. To assess cleaning effectiveness, the study measured milk and protein residue removal after deposition and cleaning processes, employing a cleaning solution flow pattern at Reynolds numbers (Re) of 659–1318. Results indicate that smoother surfaces, particularly those with roughness values of 0.01 and 0.37 μm R_a, significantly enhance cleanability at 40°C. This leads to reductions (p < 0.05) of 34.5% and 22.6% for milk deposits and 27.9% and 22.7% for protein deposits, respectively, compared to tube surfaces with a roughness level of 3.7 μm R_a. These findings underscore the potential of highly smooth surfaces to improve cleanability below protein denaturation temperatures. Furthermore, the MAF tube with a roughness of 0.01 μm R_a exhibited nonsignificant reductions of 15.4% and 6.7% compared to the 0.37 μm R_a surface. The smoothing effect on the cleanability of milk and protein deposits was enhanced compared with the higher temperature condition. By addressing the challenges of routine cleaning, the study highlights MAF as a technology that optimizes surface quality in dairy processing equipment, addressing environmental and energy-related concerns.

Anaerobic digestion (AD) is a promising technology for converting organic waste into renewable energy, but its industrial implementation is often constrained by ammonia inhibition in nitrogen-rich feedstocks, which undermines both process stability and economic viability. Addressing this challenge is crucial for ensuring sustainable, financially resilient waste-to-energy systems. We hypothesized that the strategic addition of bamboo biochar (BBC) could mitigate ammonia stress while promoting a more robust microbial community, thereby enhancing both environmental and economic performance. To test this, batch experiments were conducted to determine optimum BBC dosages, followed by semi-continuous trials using 6.25 g/L BBC over four operational phases (Runs1–4), during which NH₄⁺-N was gradually increased from 2000 to 5000 mg/L. The biochar-amended system maintained stable performance under conditions that caused control reactors to fail, with a maximum 1447 % increase in methane production observed during the 4000 mg/L NH₄⁺-N phase. Mechanistic analysis revealed that BBC acted primarily by enriching syntrophic bacteria and hydrogenotrophic methanogens, enabling a stable syntrophic acetate oxidation pathway. Enhancing microbial resilience through biochar addition directly improves financial stability, a critical factor for industrial adoption. The biochar-added system achieved consistent profits of USD 8.08–16.27/m³ reactor/month, underscoring strong business potential in scalable waste-to-energy systems. Optimizing biochar dosing and evaluating full-scale implementation could further advance globally relevant, economically viable circular bioeconomy solutions.

This study explores the interactions between microbial communities, antibiotic resistance, and biogas production in anaerobic digestion systems, focusing on the acidogenic (AP) and methanogenic (MP) phases under varying organic loads, cefazolin (CEZ) exposure, and biochar supplementation. High organic loading (10 g/L glucose) significantly suppressed CEZ-resistant bacteria (CEZ-r) during the AP phase. However, their abundance markedly rebounded in MP, rising from 0.30 % to 36.28 % in control, indicating phase-specific dynamics. CEZ residues increased CEZ-r by 2.49 % and 9.30 % at 0 and 5 g/L glucose during AP. Although AP suppressed CEZ-r to 0.23 % in the CEZ-added reactor at 10 g/L glucose, MP rebounded CEZ-r to 8.30 %. In addition, CEZ exposure reduced methane yields by up to 28.14 %, likely due to the suppression of Methanosaetaceae and impaired acetic acid conversion. In contrast, biochar addition effectively reduced CEZ-r abundance to below 1.00 % at moderate to high organic loads and alleviated CEZ-induced inhibition on methane production. Biochar also enhanced Methanosaetaceae abundance (up to +6.55 %) compared to the control and promoted more efficient substrate utilization, possibly by facilitating direct interspecies electron transfer. These findings emphasize the role of organic load and digestion phase in shaping antibiotic resistance and system performance. Furthermore, biochar addition effectively mitigates the negative impacts of antibiotic residues, stabilizes microbial communities, and enhances biogas production.

The construction industry, being responsible for a large share of global carbon emissions, needs to reduce its high carbon output to meet carbon reduction goals. Artificial intelligence can provide efficient support for carbon emission calculation and prediction. Here, we review the use of artificial intelligence techniques in forecasting, management and real-time monitoring of carbon emissions, focusing on how they are applied, their impacts, and challenges. Compared to traditional methods, the prediction accuracy of artificial intelligence models has increased by 20%. Artificial intelligence-driven systems could reduce carbon emissions by up to 15% through real-time monitoring and adaptive management strategies. Artificial intelligence applications improve energy efficiency in buildings by up to 25%, while reducing operational costs by up to 10%. Artificial intelligence supports the establishment of a digital carbon management system and contributes to the development of the carbon trading market.

BioH₂, a modern biofuel with clean energy attributes and effective waste management capabilities, emerges as a promising energy source. This study employs quantitative modelling to evaluate India's bioH₂ production potential from major crop residues. Among the seven selected crop residues, West Bengal, Uttar Pradesh, and Karnataka stand out as the top three states with surplus crop residues. The annual estimated bioH₂ generation potential, without pretreatment, reaches approximately 103 PJ, a figure that soars to around 300 PJ with pretreatment, representing a remarkable 191 % improvement. The study underscores the effectiveness of pretreatment methods involving acid, alkali, or heat in enhancing bioH₂ production. Despite these promising findings, efficiency-related challenges, including temperature, pH, and pretreatment factors, are recognised. The study proposes further research and decentralised production projects as potential strategies to address these challenges, enhancing India's energy security by reducing dependence on imported fossil fuels.

In the shift toward sustainable energy, biodiesel production has garnered significant attention for its potential as an environmentally friendly alternative to petroleum diesel. This study reviews advancements in biodiesel production technologies, including traditional and emerging techniques such as microwave and ultrasonic-assisted transesterification. Comprehensive cost analyses demonstrate potential operational expense reductions with microwave-assisted and ultrasound-assisted methods. The study identifies critical challenges in feedstock selection, catalyst reusability, and production scalability while proposing innovative solutions, such as integrating waste-derived feedstocks and advanced heterogeneous catalysts. These findings provide practical insights into enhancing biodiesel production's economic feasibility and environmental sustainability.

Background: Allovahlkampfia spelaea (A. spelaea) is a free-living amoeba that has recently been recognized to
cause Acanthamoeba-like keratitis, the treatment of which is complex. The pathogenic potential of Allovahlkampfia
spp. remains unexplored. This study characterized A. spelaea through ultrastructural morphological
analysis and investigated the pathogenic potential of the A. spelaea strain KS1, which was isolated from a patient
with keratitis, in a murine model, with a focus on neuro-pulmonary infections. Additionally, this study assessed
the therapeutic effectiveness of ellagic acid (EA) against tissue damage caused by amoebic infections.
Methods: Immunosuppressed male Wister rats were intranasally inoculated with A. spelaea trophozoites (1 × 106/
ml) and divided into control, infected untreated, and infected treated (50 mg/kg EA daily) groups. Histopathological
and ultrastructural analyses of brain and lung tissues were conducted by scanning and transmission
electron microscopy. Additionally, the therapeutic effects of EA were assessed via comparative tissue pathology.
Results: A. spelaea infection induced A. spelaea-induced neural lesions resembling granulomatous amoebic encephalitis
(GAE) in the brain, which was characterized by gliosis, vasculitis, and necrosis, in addition to severe
pulmonary damage, including suppurative bronchopneumonia and abscesses. Trophozoites presented with
pseudopodia, acanthopodia, and amoebostomes, whereas cysts presented with double-layered walls. EA-treated
rats presented nearly normal brain and lung histology, with reduced inflammation and gliosis, highlighting the
anti-inflammatory and antioxidant properties of EA.
Conclusion: This study highlights the neurotropic and pulmonary pathogenicity of A. spelaea, with ultrastructures
parallel to those of Vahlkampfia spp. and Acanthamoeba spp. Ellagic acid significantly reduces infection-induced
damage, underscoring its potential as a therapeutic agent for infections caused by free-living amoebae.