Optimizing methanol synthesis from CO2 using graphene-based heterogeneous photocatalyst under RSM and ANN-driven parametric optimization for achieving better suitability.

Assessment of the performance of linear and nonlinear regression-based methods for estimating in situ catalytic CO2 transformations employing TiO2/Cu coupled with hydrogen exfoliation graphene (HEG) has been investigated. The yield of methanol was thoroughly optimized and predicted using response surface methodology (RSM) and artificial neural network (ANN) model after rigorous experimentation and comparison. Amongst the different types of HEG loading from 10 to 40 wt%, the 30 wt% in the HEG-TiO2/Cu assisted photosynthetic catalyst was found to be successful in providing the highest conversion efficiency of methanol from CO2. The most influencing parameters, HEG dosing and inflow rate of CO2, were found to affect the conversion rate in the acidic reaction regime (at pH of 3). According to RSM and ANN, the optimum methanol yields were 36.3 mg g-1 of catalyst and 37.3 mg g-1 of catalyst, respectively. Through the comparison of performances using the least squared error analysis, the nonlinear regression-based ANN showed a better determination coefficient (overall R2 > 0.985) than the linear regression-based RSM model (overall R2 ∼ 0.97). Even though both models performed well, ANN, consisting of 9 neurons in the input and 1 hidden layer, could predict optimum results closer to RSM in terms of agreement with the experimental outcome.

Optimization of gearbox housing shape for agricultural UTV using structural-acoustic coupled analysis.

In this study, gearbox radiated noise was successfully reduced through housing shape optimization. First, dynamic and structural-acoustic coupled analysis models of an agricultural UTV gearbox were developed. Then, the test equipment was configured to match that of the simulation model, and a test was conducted. The analysis and test results showed errors within 0.1 dB for vibration and 0.2 dB(A) for noise, indicating that the models were reliable. The housing design was then optimized using topology optimization based on the developed structural-acoustic coupling analysis model. The sound pressure level around the housing was used as an objective function for topology optimization. The optimal distribution of materials for the housing was also derived to reduce the radiated noise. Lastly, the housing rib was designed based on the optimization result, and an improvement in the radiated noise by approximately 2.43 dB(A) was confirmed in the operation area.

Rice Husk-Cellulose-Based Agricultural Waste Enhances the Degradation of Synthetic Dyes Using Multiple Enzyme-Producing Extremophiles.

The brightly colored synthetic dyes used in the textile industry are discharged at high concentrations-for example, various azo dyes including Methylene Blue (MB) and Methyl Orange (MO)-which is a matter of global concern, as such dyes are harmful to humans and the environment. Microbial degradation is considered an efficient alternative for overcoming the disadvantages of conventional physical and chemical dye removal methods. In this study, we investigated the potential of multiple types of the enzyme-producing extremophilic bacteria Bacillus FW2, isolated from food waste leachate, for the decolorization and bioremediation of artificial synthetic dyes. The screening of enzyme production and assaying of bacterial strain enzymes are essential for enhancing the breakdown of azo bonds in textile azo dyes. The degradation efficiencies of the water-soluble dyes MB and MO were determined at different concentrations using rice husk, which is an efficient substrate. Using the rice husks, the MO was removed completely within 20 h, and an estimated 99.8% of MB was degraded after 24 h by employing shaking at 120 rpm at 40 °C-whereas a removal efficiency of 98.9% was achieved for the combination of MB + MO. These results indicate the possibility of applying an extremophilic bacterial strain, Bacillus sp., for large-scale dye degradation in the future.

Dissemination of sulfonamide resistance genes in digester microbiome during anaerobic digestion of food waste leachate.

The preeminence of sulfonamide drug resistance genes in food waste (FW) and the increased utilization of high-strength organic FW in anaerobic digestion (AD) to enhance methane production have raised severe public health concerns in wastewater treatment plants worldwide. In this regard, the dissemination patterns of different sulfonamide resistance genes (sul1 and sul2) and their impact on the digester core microbiota during AD of FW leachate (FWL) were evaluated. The presence of various sulfonamide antibiotics (SAs) in FWL digesters improved the final methane yield by 37 % during AD compared with FWL digesters without SAs. Microbial population shifts towards hydrolytic, acidogenic, and acetogenic bacteria in the phyla Actinobacteriota, Bacteroidota, Chloroflexi, Firmicutes, Proteobacteria, and Synergistota occurred due to SA induced substrate digestion and absorption through active transport; butanoate, propanoate, and pyruvate metabolism; glycolysis; gluconeogenesis; the citrate cycle; and pentose phosphate pathway. The initial dominance of Methanosaeta (89-96 %) declined to 47-53 % as AD progressed and shifted towards Methanosarcina (40 %) in digesters with the highest SA concentrations at the end of AD. Dissemination of sul1 depended on class 1 integron gene (intl1)-based horizontal gene transfer to pathogenic members of Chloroflexi, Firmicutes, and Patescibacteria, whereas sul2 was transmitted to Synergistota independent of intl1. Low susceptibility and ability to utilize SAs during methanogenesis shielded methanogenic archaea against selection pressure, thus preventing them from interacting with sul or intl1 genes, thereby minimizing the risk of antibiotic resistance development. The observed emergence of cationic antimicrobial peptide, vancomycin, and ß-lactam resistance in the core microbiota during AD of FWL in the presence of SAs suggests that multidrug resistance caused by bacterial transformation could lead to an increase in the environmental resistome through wastewater sludge treatment.

Effects of manufacturing errors of gear macro-geometry on gear performance.

In gear design, gear performance metrics such as safety factors for tooth root stress and surface durability, peak-to-peak static transmission error (PPSTE), efficiency, mass, and volume are considered. They are calculated by the geometric parameters of gear macro- and micro-geometry, and manufacturing errors related to gear geometry significantly affect gear performance. However, previous studies have only focused on the micro-geometry errors. In this study, Monte Carlo-type robustness analysis was performed considering the manufacturing errors for tooth thickness, tip diameter, and center distance. Gear performance metrics except PPSTE were calculated based on the international standards and geometric characteristics. PPSTE was evaluated analytically due to lack of standards. When the errors were considered, two gear pairs with the safety factors satisfying the design requirements and similar performance for PPSTE, efficiency, mass, and volume showed different gear performances. There were many samples in gear pair 1 that could not satisfy the design requirements of safety factors, and gear pair 2 had the robustness of PPSTE not only at the specific torque but also with wide torque range when compared to gear pair 1. These results imply that considering the gear macro-geometry errors and robustness of PPSTE is significantly important when designing gears.

Changes in Barriers That Cause Unmet Healthcare Needs in the Life Cycle of Adulthood and Their Policy Implications: A Need-Selection Model Analysis of the Korea Health Panel Survey Data.

Using 68,930 observations selected from 16,535 adults in the Korea Health Panel Survey (2014-2018), this study explored healthcare barriers that prevent people from meeting their healthcare needs most severely during adulthood, and the characteristics that are highly associated with the barrier. This study derived two outcome variables: a dichotomous outcome variable on whether an individual has experienced healthcare needs, and a quadchotomous outcome variable on how an individual's healthcare needs ended. An analysis was conducted using a multivariable panel multinomial probit model with sample selection. The results showed that the main cause of unmet healthcare needs was not financial difficulties but non-financial barriers, which were time constraints up to a certain age and the lack of caring and support after that age. People with functional limitations were at a high risk of experiencing unmet healthcare needs due to a lack of caring and support. To reduce unmet healthcare needs in South Korea, the government should focus on lowering non-financial barriers to healthcare, including time constraints and lack of caring and support. It seems urgent to strengthen the foundation of "primary care", which is exceptionally scarce now, and to expand it to "community-based integrated care" and "people-centered care".

Extrinsic Calibration of Multiple 3D LiDAR Sensors by the Use of Planar Objects.

Three-dimensional light detection and ranging (LiDAR) sensors have received much attention in the field of autonomous navigation owing to their accurate, robust, and rich geometric information. Autonomous vehicles are typically equipped with multiple 3D LiDARs because there are many commercially available low-cost 3D LiDARs. Extrinsic calibration of multiple LiDAR sensors is essential in order to obtain consistent geometric information. This paper presents a systematic procedure for the extrinsic calibration of multiple 3D LiDAR sensors using plane objects. At least three independent planes are required within the common field of view of the LiDAR sensors. The planes satisfying the condition can easily be found on objects such as the ground, walls, or columns in indoor and outdoor environments. Therefore, the proposed method does not require environmental modifications such as using artificial calibration objects. Multiple LiDARs typically have different viewpoints to reduce blind spots. This situation increases the difficulty of the extrinsic calibration using conventional registration algorithms. We suggest a plane registration method for cases in which correspondences are not known. The entire calibration process can easily be automated using the proposed registration technique. The presented experimental results clearly show that the proposed method generates more accurate extrinsic parameters than conventional point cloud registration methods.

Sex-Specific Association between Underlying Diseases and the Severity and Mortality Due to COVID-19 Infection: A Retrospective Observational Cohort Analysis of Clinical Epidemiological Information Collected by the Korea Disease Control and Prevention Agency.

This study is a retrospective observational cohort analysis aiming to explore the relationship between underlying disease and the severity and mortality rate of coronavirus disease (COVID-19) by sex. As sample subjects, 5077 confirmed COVID-19 patients were selected. The dependent variable was each patient's clinical severity, dichotomized into two groups: clinical non-severity group and clinical severity group (including death group). Eleven underlying diseases were considered variables of interest, and each was dichotomized. Binary multivariate logistic regression model analyses were performed. Our results showed that the proportion of male patients (7.1%) in the clinical severity group was significantly higher than that of female patients (4.5%) and that the risk of being in the clinical severity group was higher in patients with specific underlying diseases. The underlying diseases varied: in males, rheumatism and autoimmune (adjusted odds ratio (aOR) = 6.69, 95% confidence interval (CI) = 1.60-27.98), dementia (aOR = 4.09, 95% CI = 2.14-7.82), cancer (aOR = 2.69, 95% CI = 1.27-5.69), and diabetes mellitus (aOR = 1.81, 95% CI = 1.18-2.77); in females, chronic kidney disease (aOR = 5.09, 95% CI = 1.87-13.86), dementia (aOR = 3.08, 95% CI = 1.18-5.23), diabetes mellitus (aOR = 1.87, 95% CI = 1.15-3.02), and hypertension (aOR = 1.73, 95% CI = 1.08-2.78). This study identified certain underlying diseases related to the high risk of being in clinically severe conditions and found that they differ between sexes. Prevention and treatment measure should be developed to reduce severity or mortality in confirmed COVID-19, based on underlying diseases and sex. However, further in-depth research is required to explore whether the findings and suggestions of this study can be generalized to other countries.

Genome-Scale Profiling and High-Throughput Analyses Unravel the Genetic Basis of Arsenic Content Variation in Rice.

Ionomics, the study of the composition of mineral nutrients and trace elements in organisms that represent the inorganic component of cells and tissues, has been widely studied to explore to unravel the molecular mechanism regulating the elemental composition of plants. However, the genetic factors of rice subspecies in the interaction between arsenic and functional ions have not yet been explained. Here, the correlation between As and eight essential ions in a rice core collection was analyzed, taking into account growing condition and genetic factors. The results demonstrated that the correlation between As and essential ions was affected by genetic factors and growing condition, but it was confirmed that the genetic factor was slightly larger with the heritability for arsenic content at 53%. In particular, the cluster coefficient of japonica (0.428) was larger than that of indica (0.414) in the co-expression network analysis for 23 arsenic genes, and it was confirmed that the distance between genes involved in As induction and detoxification of japonica was far than that of indica. These findings provide evidence that japonica populations could accumulate more As than indica populations. In addition, the cis-eQTLs of AIR2 (arsenic-induced RING finger protein) were isolated through transcriptome-wide association studies, and it was confirmed that AIR2 expression levels of indica were lower than those of japonica. This was consistent with the functional haplotype results for the genome sequence of AIR2, and finally, eight rice varieties with low AIR2 expression and arsenic content were selected. In addition, As-related QTLs were identified on chromosomes 5 and 6 under flooded and intermittently flooded conditions through genome-scale profiling. Taken together, these results might assist in developing markers and breeding plans to reduce toxic element content and breeding high-quality rice varieties in future.

Effect of Aging on Educational Differences in the Risk of Cognitive Impairment: A Gender-Specific Analysis Using Korean Longitudinal Study of Aging (2006-2016).

This study examined the effect of aging on gender-specific educational differences in the risk of cognitive impairment using a nationally representative sample of 4278 men and 5495 women aged 45 years and older from the dataset of the Korean Longitudinal Study of Aging. Sociodemographics, lifestyle, and medical conditions were included as covariates in the mixed logistic regression analysis models. The prevalence of cognitive impairment was higher in women than in men at baseline. The risk of cognitive impairment in each age group decreased with education in both men and women. The risk by educational rank was worse at lower levels and increased with age, more so for women than men. Aging appears to widen the impact of educational differences on the risk of cognitive impairment and is more unfavorable for women than for men. Public health policies regarding population aging need to consider this and identify the target population to reduce both the level of and the difference in the risk of cognitive impairment.

Feasibility assessment of bioethanol production from humic acid-assisted alkaline pretreated Kentucky bluegrass (Poa pratensis L.) followed by downstream enrichment using direct contact membrane distillation.

The effective fractionation of structural components of abundantly available lignocellulosic biomass is essential to unlock its full biorefinery potential. In this study, the feasibility of humic acid on the pretreatment of Kentucky bluegrass biomass in alkaline condition was assessed to separate 70.1% lignin and hydrolyzable biocomponents. The humic acid-assisted delignification followed by enzymatic saccharification yielded 0.55 g/g of reducing sugars from 7.5% (w/v) pretreated biomass loading and 16 FPU/g of cellulase. Yeast fermentation of the biomass hydrolysate produced 76.6% (w/w) ethanol, which was subsequently separated and concentrated using direct contact membrane distillation. The hydrophobic microporous flat-sheet membrane housed in a rectangular-shaped crossflow module and counter-current mode of flow of the feed (hot) and distillate (cold) streams yielded a flux of 11.6 kg EtOH/m2/24 h. A modular, compact, flexible, and eco-friendly membrane-integrated hybrid approach is used for the first time to effectively valorize Kentucky bluegrass biomass for sustainable production of biofuel.

Platelet-to-White Blood Cell Ratio Is Associated with Adverse Outcomes in Cirrhotic Patients with Acute Deterioration.

Background: The platelet-to-white blood cell ratio (PWR) is a hematologic marker of the systemic inflammatory response. Recently, the PWR was revealed to have a role as an independent prognostic factor for mortality in patients with hepatitis B virus (HBV)-related acute-on-chronic failure (ACLF) and HBV-related liver cirrhosis (LC) with acute decompensation (AD). However, the prognostic role of the PWR still needs to be investigated in LC patients with AD. In this study, we analyzed whether the PWR could stratify the risk of adverse outcomes (death or liver transplantation (LT)) in these patients. Methods: A prospective cohort of 1670 patients with AD of liver cirrhosis ((age: 55.2 ± 7.8, male = 1226 (73.4%)) was enrolled and evaluated for 28-day and overall adverse outcomes. Results: During a median follow-up of 8.0 months (range, 1.9−15.5 months), 424 (25.4%) patients had adverse outcomes (death = 377, LT = 47). The most common etiology of LC was alcohol use (69.7%). The adverse outcome rate was higher for patients with a PWR ≤ 12.1 than for those with a PWR > 12.1. A lower PWR level was a prognostic factor for 28-day adverse outcomes (PWR: hazard ratio 1.707, p = 0.034) when adjusted for the etiology of cirrhosis, infection, ACLF, and the MELD score. In the subgroup analysis, the PWR level stratified the risk of 28-day adverse outcomes regardless of the presence of ACLF or the main form of AD but not for those with bacterial infection. Conclusions: A lower PWR level was associated with 28-day adverse outcomes, indicating that the PWR level can be a useful and simple tool for stratifying the risk of 28-day adverse outcomes in LC patients with AD.

Characteristics Associated With Financial or Non-financial Barriers to Healthcare in a Universal Health Insurance System: A Longitudinal Analysis of Korea Health Panel Survey Data.

While many studies have explored the financial barriers to healthcare, there is little evidence regarding the non-financial barriers to healthcare. This study identified characteristics associated with financial and non-financial barriers to healthcare and quantified the effects of these characteristics in South Korea, using a nationally representative longitudinal survey dataset. Overall, 68,930 observations of 16,535 individuals aged 19 years and above were sampled from Korea Health Panel survey data (2014-2018). From self-reported information about respondents' experiences of unmet healthcare needs, a trichotomous dependent variable-no barrier, non-financial barrier, and financial barrier-was derived. Sociodemographics, physical and health conditions were included as explanatory variables. The average adjusted probability (AAP) of experiencing each barrier was predicted using multivariable and panel multinomial logistic regression analyses. According to the results, the percentage of people experiencing non-financial barriers was much higher than that of people experiencing financial barriers in 2018 (9.6 vs. 2.5%). Women showed higher AAPs of experiencing both non-financial (9.9 vs. 8.3%) and financial barriers (3.6 vs. 2.5%) than men. Men living in the Seoul metropolitan area showed higher AAPs of experiencing non-financial (8.7 vs. 8.0%) and financial barriers (3.4 vs. 2.1%) than those living outside it. Household income showed no significant associations in the AAP of experiencing a non-financial barrier. People with a functional limitation exhibited a higher AAP of experiencing a non-financial barrier, for both men (17.8 vs. 7.8%) and women (17.4 vs. 9.0%), than those without it. In conclusion, people in South Korea, like those in most European countries, fail to meet their healthcare needs more often due to non-financial barriers than financial barriers. In addition, the characteristics associated with non-financial barriers to healthcare differed from those associated with financial barriers. This finding suggests that although financial barriers may be minimised through various policies, a considerable degree of unmet healthcare needs and disparity among individuals is very likely to persist due to non-financial barriers. Therefore, current universal health insurance systems need targeted policy instruments to minimise non-financial barriers to healthcare to ensure effective universal health coverage.

Bacterial Biosorbents, an Efficient Heavy Metals Green Clean-Up Strategy: Prospects, Challenges, and Opportunities.

Rapid industrialization has led to the pollution of soil and water by various types of contaminants. Heavy metals (HMs) are considered the most reactive toxic contaminants, even at low concentrations, which cause health problems through accumulation in the food chain and water. Remediation using conventional methods, including physical and chemical techniques, is a costly treatment process and generates toxic by-products, which may negatively affect the surrounding environment. Therefore, biosorption has attracted significant research interest in the recent decades. In contrast to existing methods, bacterial biomass offers a potential alternative for recovering toxic/persistent HMs from the environment through different mechanisms for metal ion uptake. This review provides an outlook of the advantages and disadvantages of the current bioremediation technologies and describes bacterial groups, especially extremophiles with biosorbent potential for heavy metal removal with relevant examples and perspectives.

Coconut Mesocarp-Based Lignocellulosic Waste as a Substrate for Cellulase Production from High Promising Multienzyme-Producing Bacillus amyloliquefaciens FW2 without Pretreatments.

Facing the crucial issue of high cost in cellulase production from commercial celluloses, inexpensive lignocellulosic materials from agricultural wastes have been attractive. Therefore, several studies have focused on increasing the efficiency of cellulase production by potential microorganisms capable of secreting a high and diversified amount of enzymes using agricultural waste as valuable substrates. Especially, extremophilic bacteria play an important role in biorefinery due to their high value catalytic enzymes that are active even under harsh environmental conditions. Therefore, in this study, we aim to investigate the ability to produce cellulase from coconut-mesocarp of the potential bacterial strain FW2 that was isolated from kitchen food waste in South Korea. This strain was tolerant in a wide range of temperature (-6-75 °C, pH range (4.5-12)) and at high salt concentration up to 35% NaCl. The molecular weight of the purified cellulase produced from strain FW2 was estimated to be 55 kDa. Optimal conditions for the enzyme activity using commercial substrates were found to be 40-50 °C, pH 7.0-7.5, and 0-10% NaCl observed in 920 U/mL of CMCase, 1300 U/mL of Avicelase, and 150 U/mL of FPase. It was achieved in 650 U/mL, 720 U/mL, and 140 U/mL of CMCase, Avicelase, and FPase using coconut-mesocarp, respectively. The results revealed that enzyme production by strain FW2 may have significant commercial values for industry, argo-waste treatment, and other potential applications.

Application of flexible pin for planetary gear set of wind turbine gearbox.

Wind turbines are eco-friendly energy sources that generate electricity from wind power. Among their various components, gearboxes constitute the most critical loss owing to their longest downtime. To guarantee their durability, a flexible pin was designed based on the original straddle-mounted pin for enhanced tooth load sharing and distribution in the planetary gear set (PGS) of a wind turbine gearbox (WTGB). The improved durability was evaluated by calculating the mesh load factor and face load factor for contact stress and comparing these values with those of the original straddle-mounted pin. The mesh load factor decreased from 1.37 to 1.08, whereas the maximum face load factor decreased slightly, moderating the overall safety factor variation. Furthermore, the structure of the proposed flexible pin model was analyzed and verified that no static failure or interference occurred. Additionally, microgeometry optimization was applied to improve the load distribution. Therefore, it was verified that a flexible pin applied to a single helical-geared PGS, thus far considered impossible, enhances the durability of WTGBs by improving the load sharing and distribution of a PGS. Consequently, the possibility of designing single helical-geared planetary gearboxes with flexible pins to take advantages of both helical gears and flexible pins was shown analytically.

Association between Handgrip Strength and Cognitive Function in Older Adults: Korean Longitudinal Study of Aging (2006-2018).

Accumulating research indicates that handgrip strength is associated with cognitive function. Studies have also shown the difference in cognitive decline between males and females. We investigated the association between baseline handgrip strength and later cognitive function in older adults according to sex using the dataset from Korean Longitudinal Study of Aging (2006-2018). Overall, 9707 observations of 1750 participants (989 males and 761 females) over 65 years of age were sampled from the first wave, followed by six consecutive waves. The Korean version of the Mini-Mental State Examination and baseline handgrip strength scores were assessed. Sociodemographic and health-related variables were also included as covariates in the multivariable linear mixed models. Males in the lowest quartile of the baseline handgrip strength decreased in cognitive function (ß = -0.54, standard error (SE) = 0.16, p < 0.001), compared to males in the highest quartile. For females, those in the second lowest quartile (ß = -0.65, SE = 0.19, p < 0.001) and the lowest quartile (ß = -0.53, SE = 0.19, p< 0.01) decreased in cognitive function. Handgrip strength may be positively associated with later cognitive function, but the association may be non-linear and differ between sexes. Sex-specific preventive assessment of handgrip strength may help identify older adults at risk for cognitive impairment.

Frequent and Automatic Update of Lane-Level HD Maps with a Large Amount of Crowdsourced Data Acquired from Buses and Taxis in Seoul.

Recently, HD maps have become important parts of autonomous driving, from localization to perception and path planning. For the practical application of HD maps, it is significant to regularly update environmental changes in HD maps. Conventional approaches require expensive mobile mapping systems and considerable manual work by experts, making it difficult to achieve frequent map updates. In this paper, we show how frequent and automatic updates of lane marking in HD maps are made possible with enormous crowdsourced data. Crowdsourced data is acquired from onboard low-cost sensing devices installed on many city buses and taxis in Seoul, South Korea. A large amount of crowdsourced data is daily accumulated on the server. The quality of sensor measurement is not very high due to the limited performance of low-cost devices. Therefore, the technical challenge is to overcome the uncertainty of the crowdsourced data. Appropriately filtering out a large amount of low-quality data is a significant problem. The proposed HD map update strategy comprises several processing steps including pose correction, observation assignment, observation clustering, and landmark classification. The proposed HD map update strategy is experimentally verified using crowdsourced data. If the changed environments are successfully extracted, then precisely updated HD maps are generated.

Improvement of Hydrogen Production during Anaerobic Fermentation of Food Waste Leachate by Enriched Bacterial Culture Using Biochar as an Additive.

It has become urgent to develop cost-effective and clean technologies for the rapid and efficient treatment of food waste leachate, caused by the rapid accumulation of food waste volume. Moreover, to face the energy crisis, and to avoid dependence on non-renewable energy sources, the investigation of new sustainable and renewable energy sources from organic waste to energy conversion is an attractive option. Green energy biohydrogen production from food waste leachate, using a microbial pathway, is one of the most efficient technologies, due to its eco-friendly nature and high energy yield. Therefore, the present study aimed to evaluate the ability of an enriched bacterial mixture, isolated from forest soil, to enhance hydrogen production from food waste leachate using biochar. A lab-scale analysis was conducted at 35 °C and at different pH values (4, no adjustment, 6, 6.5, 7, and 7.5) over a period of 15 days. The sample with the enriched bacterial mixture supplemented with an optimum of 10 g/L of biochar showed the highest performance, with a maximum hydrogen yield of 1620 mL/day on day three. The total solid and volatile solid removal rates were 78.5% and 75% after 15 days, respectively. Acetic and butyrate acids were the dominant volatile fatty acids produced during the process, as favorable metabolic pathways for accelerating hydrogen production.

Investigation of Lipolytic-Secreting Bacteria from an Artificially Polluted Soil Using a Modified Culture Method and Optimization of Their Lipase Production.

Compared to lipases from plants or animals, microbial lipases play a vital role in different industrial applications and biotechnological perspectives due to their high stability and cost-effectiveness. Therefore, numerous lipase producers have been investigated in a variety of environments in the presence of lipidic carbon and organic nitrogen sources. As a step in the development of cultivating the unculturable functional bacteria in this study, the forest soil collected from the surrounding plant roots was used to create an artificially contaminated environment for lipase-producing bacterial isolation. The ten strongest active bacterial strains were tested in an enzyme assay supplemented with metal ions such as Ca2+, Zn2+, Cu2+, Fe2+, Mg2+, K+, Co2+, Mn2+, and Sn2+ to determine bacterial tolerance and the effect of these metal ions on enzyme activity. Lipolytic bacteria in this study tended to grow and achieved a high lipase activity at temperatures of 35-40 °C and at pH 6-7, reaching a peak of 480 U/mL and 420 U/mL produced by Lysinibacillus PL33 and Lysinibacillus PL35, respectively. These potential lipase-producing bacteria are excellent candidates for large-scale applications in the future.