The extensive use of petroleum-based synthetic and non-biodegradable materials for packaging applications has caused severe environmental damage. The rising demand for sustainable packaging materials has encouraged scientists to explore abundant unconventional materials. For instance, cellulose, extracted from lignocellulosic biomass, has gained attention owing to its ecological and biodegradable nature. This article reviews the extraction of cellulose nanoparticles from conventional and non-conventional lignocellulosic biomass, and the preparation of cellulosic nanocomposites for food packaging. Cellulosic nanocomposites exhibit exceptional mechanical, biodegradation, optical and barrier properties, which are attributed to the nanoscale structure and the high specific surface area, of 533 m² g⁻¹, of cellulose. The mechanical properties of composites improve with the content of cellulose nanoparticles, yet an excessive amount induces agglomeration and, in turn, poor mechanical properties. Addition of cellulose nanoparticles increases tensile properties by about 42%. Barrier properties of the composites are reinforced by cellulose nanoparticles; for instance, the water vapor permeability decreased by 28% in the presence of 5 wt% cellulose nanoparticles. Moreover, 1 wt% addition of filler decreased the oxygen transmission rate by 21%. We also discuss the eco-design process, designing principles and challenges.

The objectives of this study were to evaluate (1) the performance of an automated health-monitoring system (AHMS) to identify cows with metabolic and digestive disorders-including displaced abomasum, ketosis, and indigestion-based on an alert system (health index score, HIS) that combines rumination time and physical activity; (2) the number of days between the first HIS alert and clinical diagnosis (CD) of the disorders by farm personnel; and (3) the daily rumination time, physical activity, and HIS patterns around CD. Holstein cattle (n=1,121; 451 nulliparous and 670 multiparous) were fitted with a neck-mounted electronic rumination and activity monitoring tag (HR Tags, SCR Dairy, Netanya, Israel) from at least -21 to 80 d in milk (DIM). Raw data collected in 2-h periods were summarized per 24 h as daily rumination and activity. A HIS (0 to 100 arbitrary units) was calculated daily for individual cows with an algorithm that used rumination and activity. A positive HIS outcome was defined as a HIS of <86 during at least 1 d from -5 to 2 d after CD. Blood concentrations of nonesterified fatty acids, β-hydroxybutyrate, total calcium, and haptoglobin were determined in a subgroup of cows (n=459) at -11±3, -4±3, 0, 3±1, 7±1, 14±1, and 28±1 DIM. The sensitivity of the HIS was 98% [95% confidence interval (CI): 93, 100] for displaced abomasum (n=41); 91% (95% CI: 83, 99) for ketosis (n=54); 89% (95% CI: 68, 100) for indigestion (n=9); and 93% (95% CI: 89, 98) for all metabolic and digestive disorders combined (n=104). Days (mean and 95% CI) from the first positive HIS <86 and CD were -3 (-3.7, -2.3), -1.6 (-2.3, -1.0), -0.5 (-1.5, 0.5), and -2.1 (-2.5, -1.6) for displaced abomasum, ketosis, indigestion, and all metabolic and digestive disorders, respectively. The patterns of rumination, activity, and HIS for cows flagged by the AHMS were characterized by lower levels than for cows without a health disorder and cows not flagged by the AHMS from -5 to 5 d after CD, depending on the disorder and parameter. Differences between cows without health disorders and those flagged by the AHMS for blood markers of metabolic and health status confirmed the observations of the CD and AHMS alerts. The overall sensitivity and timing of the AHMS alerts for cows with metabolic and digestive disorders indicated that AHMS that combine rumination and activity could be a useful tool for identifying cows with metabolic and digestive disorders.

The objectives of this study were to evaluate (1) the performance of an automated health-monitoring system (AHMS) to identify cows with metritis based on an alert system (health index score, HIS) that combines rumination time and physical activity; (2) the number of days between the first HIS alert and clinical diagnosis (CD) of metritis by farm personnel; and (3) the daily rumination time, physical activity, and HIS patterns around CD. In this manuscript, the overall performance of HIS to detect cows with all disorders of interest in this study [ketosis, displaced abomasum, indigestion (companion paper, part I), mastitis (companion paper, part II), and metritis] is also reported. Holstein cattle (n=1,121; 451 nulliparous and 670 multiparous) were fitted with a neck-mounted electronic rumination and activity monitoring tag (HR Tags, SCR Dairy, Netanya, Israel) from at least -21 to 80 d in milk (DIM). Raw data collected in 2-h periods were summarized per 24 h as daily rumination and activity. An HIS (0 to 100 arbitrary units) was calculated daily for individual cows with an algorithm that used rumination and activity. A positive HIS outcome was defined as an HIS of <86 units during at least 1 d from -5 to 2 d after CD. Blood concentrations of nonesterified fatty acids, β-hydroxybutyrate, total calcium, and haptoglobin were determined in a subgroup of cows (n=459) at -11±3, -4±3, 0, 3±1, 7±1, 14±1, and 28±1 DIM. The overall sensitivity of HIS was 55% for all cases of metritis (n=349), but it was greater for cows with metritis and another disorder (78%) than for cows with metritis only (53%). Cows diagnosed with metritis and flagged based on HIS had substantial alterations in their rumination, activity, and HIS patterns around CD, alterations of blood markers of metabolic and health status around calving, reduced milk production, and were more likely to exit the herd than cows not flagged based on the HIS and cows without disease, suggesting that cows flagged based on the HIS had a more severe episode of metritis. Including all disorders of interest for this study, the overall sensitivity was 59%, specificity was 98%, positive predictive value was 58%, negative predictive value was 98%, and accuracy was 96%. The AHMS was effective for identifying cows with severe cases of metritis, but less effective for identifying cows with mild cases of metritis. Also, the overall accuracy and timing of the AHMS alerts for cows with health disorders indicated that AHMS that combine rumination and activity could be a useful tool for identifying cows with metabolic and digestive disorders, and more severe cases of mastitis and metritis.

With an ever-increasing human population, access to clean water for human use is a growing concern across the world. Seawater desalination to produce usable water is essential to meet future clean water demand. Desalination processes, such as reverse osmosis and multi-stage flash have been implemented worldwide. Reverse osmosis is the most effective technology, which uses a semipermeable membrane to produce clean water under an applied pressure. However, membrane biofouling is the main issue faced by such plants, which requires continuous cleaning or regular replacement of the membranes. Chlorination is the most commonly used disinfection process to pretreat the water to reduce biofouling. Although chlorination is widely used, it has several disadvantages, such as formation of disinfection by-products and being ineffective against some types of microbes. This review aims to discuss the adverse effect of chlorination on reverse osmosis membranes and to identify other possible alternatives of chlorination to reduce biofouling of the membranes. Reverse osmosis membrane degradation and mitigation of chlorines effects, along with newly emerging disinfection technologies, are discussed, providing insight to both academic institutions and industries for the design of improved reverse osmosis systems.

Green hydrogen is emerging as a pivotal energy carrier in the global transition toward decarbonization, offering a sustainable alternative to fossil fuels in sectors such as heavy industry, transportation, power generation, and long-duration energy storage. Despite its potential, large-scale deployment remains hindered by significant economic, technological, and infrastructure challenges. Current production costs for green hydrogen range from USD 3.8 to 11.9/kg H₂, significantly higher than gray hydrogen at USD 1.5–6.4/kg H₂, due to high electricity prices and electrolyzer capital costs exceeding USD 2000 per kW. This review critically examines the key bottlenecks in green hydrogen production, focusing on water electrolysis technologies, electrocatalyst limitations, and integration with renewable energy sources. The economic viability of green hydrogen is constrained by high electricity consumption, capital-intensive electrolyzer costs, and operational inefficiencies, making it uncompetitive with fossil fuel-based hydrogen. Infrastructure and supply chain challenges, including limited hydrogen storage, transport complexities, and critical material dependencies, further restrict market scalability. Additionally, policy and regulatory gaps, disparities in financial incentives, and the absence of a standardized certification framework hinder international trade and investment in green hydrogen projects. This review also highlights market trends and global initiatives, assessing the role of government incentives and cross-border collaborations in accelerating hydrogen adoption. While technological advancements and cost reductions are progressing, overcoming these challenges requires sustained innovation, stronger policy interventions, and coordinated efforts to develop a resilient, scalable, and cost-competitive green hydrogen sector.

The objectives of this study were to evaluate (1) the performance of an automated health-monitoring system (AHMS) to identify cows with mastitis based on an alert system (health index score, HIS) that combines rumination time and physical activity; (2) the number of days between the first HIS alert and clinical diagnosis (CD) of mastitis by farm personnel; and (3) the daily rumination time, physical activity, and HIS patterns around CD. Holstein cows (n=1,121; 451 nulliparous and 670 multiparous) were fitted with a neck-mounted electronic rumination and activity monitoring tag (HR Tags, SCR Dairy, Netanya, Israel.) from at least -21 to 80 d in milk (DIM). Raw data collected in 2-h periods were summarized per 24 h as daily rumination and activity. An HIS (0 to 100 arbitrary units) was calculated daily for individual cows with an algorithm that used rumination and activity. A positive HIS outcome was defined as an HIS of <86 units during at least 1 d from -5 to 2 d after CD. Blood concentrations of nonesterified fatty acids, β-hydroxybutyrate, total calcium, and haptoglobin were also determined in a subgroup of cows (n=459) at -11±3, -4±3, 0, 3±1, 7±1, 14±1, and 28±1 DIM. The sensitivity of the HIS was 58% [95% confidence interval (CI): 49, 67] for all cases of clinical mastitis (n=123), and 55% (95% CI: 46, 64; n=114) and 89% (95% CI: 68, 100; n=9) for cases of mastitis alone or concurrent with other health disorders, respectively. Among clinical cases, sensitivity was 80.7% (95% CI: 67, 97) for cases caused by Escherichia coli (n=31) and ranged from 45 to 48% for cases caused by gram-positive bacteria (n=39; Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus uberis, Streptococcus spp., Staphylococcus spp., and Trueperella pyogenes), Staphylococcus aureus (n=11), or cases with no bacterial growth (n=25). Days between the first HIS <86 and CD were -0.6 (95% CI: -1.1, -0.2) for all cases of mastitis. Cows diagnosed with mastitis had alterations of their rumination, activity, HIS patterns, and reduced milk production around CD depending on the type of mastitis case. Cows with mastitis also had some alterations of their calcium and haptoglobin concentrations around calving. The AHMS used in this study was effective for identifying cows with clinical cases of mastitis caused by E. coli and cows with another disease occurring during an event of mastitis, but it was less effective in identifying cows with mastitis not caused by E. coli.