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Background: Mycoplasma genitalium is a gram negative, parasitic pathogenic bacterium, usually transmitted sexually into human and frequently causing urethritis in men and women as well as cervicitis and pelvic inflammation in women. This is an extremely small selfreplicating entity whose genome has been sequenced. This genome sequencing is advantageous in understanding pathogenesis and identifying therapeutic targets. In this study different bioinformatics tools and databases were adopted to analyze the functions of different hypothetical proteins from M. genitalium G37. Methodology: A total of 75 hypothetical proteins (HPs) were retrieved from KEGG database, while CDD-BLAST, Pfam, and InterProScan servers were used for conserved domains analysis. After that, those HPs were broadly analyzed for physicochemical properties, subcellular localization, GO annotation, and virulence factors. Results: Based on best score, hypothetical protein MG_476 was selected for homology modelling which produced a fairly good quality 3D model. The active site within MG_476 was predicted using CASTp server that helps to explore the surface features of the protein. Other approaches include the use of NetCTL, IEDB, Bcepred, and ABCpred servers to predict the location of B and T cell epitopes. Among the CD8+ T cell epitopes tested, ILQIIMFIL scored highest (0.23718) in terms of immunogenicity. Conclusion: Moreover, this analysis recommended MG_476 as a non-homologous protein and the data generated in this study may facilitate the experimental designing of novel drug and vaccines against M. genitalium. [ABSTRACT FROM AUTHOR]

• Exposure of GAC-BAF to GO showed no toxicity on viable cells within the biofilm. • Presence of GO increased biomass growth, demonstrating biocompatibility. • Specific growth rate increased by 20 %–46 % when exposed to GO concentrations. • GO sheets acted as a scaffold for bacterial growth and biofilm formation. • GAC-BAF with GO showed a more diverse bacterial community. With widespread occurrence and increasing concern of emerging contaminants (CECs) in source water, biologically active filters (BAF) have been gaining acceptance in water treatment. Both BAFs and graphene oxide (GO) have been shown to be effective in treating CECs. However, studies to date have not addressed interactions between GO and microbial communities in water treatment processes such as BAFs. Therefore, in the present study, we investigated the effect of GO on the properties and microbial growth rate in a BAF system. Synthesized GO was characterized with a number of tools, including scanning electron microscopy (SEM), energy dispersive x-ray spectroscopy (EDX), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and Raman spectrometry. GO exhibited the characteristic surface functional groups (i.e., C-OH, C=O, C-O-C, and COOH), crystalline structure, and sheet-like morphology. To address the potential toxicity of GO on the microbial community, reactive oxygen species (ROS) generation was measured using nitro blue tetrazolium (NBT) assay. Results revealed that during the exponential growth phase, ROS generation was not observed in the presence of GO compared to the control batch. In fact, the adenosine triphosphate (ATP) concentrations increased in the presence of GO (25 μg/L - 1000 μg/L) compared to the control without GO. The growth rate in systems with GO exceeded the control by 20 % to 46 %. SEM images showed that GO sheets can form an effective scaffold to promote bacterial adhesion, proliferation, and biofilm formation, demonstrating its biocompatibility. Next-generation sequencing (Illumina MiSeq) was used to characterize the BAF microbial community, and high-throughput sequencing analysis confirmed the greater richness and more diverse microbial communities compared to systems without GO. This study is the first to report the effect of GO on the microbial community of BAF from a water treatment plant, which provides new insights into the potential of utilizing a bio-optimized BAF for advanced and sustainable water treatment or reuse strategies. [Display omitted] [ABSTRACT FROM AUTHOR]

The unsteady magneto-convective heat-mass transport passing in a vertical porous sheet with the thermal radiation and the chemical reaction effects has been examined numerically. The governing PDEs have been transferred into ODEs by applying the local similarity transformation. The nondimensional governing equations including the boundary conditions are solved by applying the superposition method with the help of the "MATLAB ODE45" software numerically. The influence of emerging nondimensional numbers/parameters, for example, the Prandtl number (Pr), thermal radiation parameter (R), Schmidt number (Sc), and chemical reaction parameter K r , on fluid velocity, concentration, and thermal radiation within the boundary layer has been examined. The outcomes indicate that enhancing values of the Soret and Dufour numbers reduce the thermal boundary layer thickness. Uplifting values of the thermal radiation (0.5-3.5) enhance the local skin friction coefficient and mass transfer rate by approximately 15% and 78% but decrease the heat transfer rate by 47%. The local skin friction coefficient enhances about 21%, and the mass transfer rate reduces about 64% due to an increase in the chemical reaction parameter (0.5-2.0). Finally, we compared our numerical results with previously published literature and observed them to have a good agreement. [ABSTRACT FROM AUTHOR]

• Investigate assigning shipping requests to crowdsourcees with time and capacity constraints • Propose a centralized, deep reinforcement learning-based approach • Present new state space representation encompassing spatial-temporal and capacity information • Embed heuristics-guided action choice in DRL to preserve tractability and enhance efficiency • Integrate rule-interposing into DRL to further enhance training and implementation efficiency This paper investigates the problem of assigning shipping requests to ad hoc couriers in the context of crowdsourced urban delivery. The shipping requests are spatially distributed each with a limited time window between the earliest time for pickup and latest time for delivery. The ad hoc couriers, termed crowdsourcees, also have limited time availability and carrying capacity. We propose a new deep reinforcement learning (DRL)-based approach to tackling this assignment problem. A deep Q network (DQN) algorithm is trained which entails two salient features of experience replay and target network that enhance the efficiency, convergence, and stability of DRL training. More importantly, this paper makes three methodological contributions: 1) presenting a comprehensive and novel characterization of crowdshipping system states that encompasses spatial-temporal and capacity information of crowdsourcees and requests; 2) embedding heuristics that leverage information offered by the state representation and are based on intuitive reasonings to guide specific actions to take, to preserve tractability and enhance efficiency of training; and 3) integrating rule-interposing to prevent repeated visiting of the same routes and node sequences during routing improvement, thereby further enhancing the training efficiency by accelerating learning. The computational complexities of the heuristics and the overall DQN training are investigated. The effectiveness of the proposed approach is demonstrated through extensive numerical analysis. The results show the benefits brought by the heuristics-guided action choice, rule-interposing, and having time-related information in the state space in DRL training, the near-optimality of the solutions obtained, and the superiority of the proposed approach over existing methods in terms of solution quality, computation time, and scalability. [ABSTRACT FROM AUTHOR]

Nanoparticles offer unique physiochemical properties and diverse applications, providing significant advantages for fish culture. Their antimicrobial properties effectively combat bacterial, viral, and fungal infections, addressing crucial challenges in aquaculture. Moreover, nanoparticles are efficient carriers for delivering therapeutic agents, vaccines, and immune stimulants directly to fish, optimizing treatment and minimizing environmental impacts. Therefore, researchers are focusing more on developing optimal dosage and delivery mechanisms and their interaction between nanoparticles and the fish immune system. In this paper, we will discuss the recent applications of nanotechnology in aquaculture, including feed ingredients, fish medicine, wastewater treatment, and fish packaging fisheries accessories. It will also emphasize nanoparticle utilization's potential benefits and challenges in fish culture. Nanoparticles could be applied through fish feed to enhance growth, reproduction, and other aspects, added to water for treatment, or administered via injection. By incorporating nanomaterials into feed, fish improve their appearance and become stronger and healthier, effectively preventing diseases. This paper explores various applications of nanotechnology in fish culture, including enhancing fish medicine, facilitating sex reversal, achieving optimal nutrition, and improving water treatment practices. [ABSTRACT FROM AUTHOR]

• Biofilm presence on LDPE surface significantly increased the Pb uptake. • Presence of chlorine residuals significantly reduced Pb adsorption onto LDPE surface. • Pseudo 2nd order kinetic model best described Pb adsorption to LDPE with biofilm. • Greater quantity of Pb is released from LDPE at lower pH and dynamic conditions. • Lower pH and greater mass transfer at dynamic condition accelerated the Pb release. In this study, the influence of biofilm presence and water chemistry conditions on lead (Pb) deposition onto low density polyethylene (LDPE) surface was examined. The results demonstrated that biofilm presence on LDPE surfaces strongly and significantly enhanced Pb uptake, with the 13-fold greater equilibrium Pb surface loading when biofilm was present (1602 μg/m2) compared to the condition when it was absent (124 μg/m2). The kinetics of Pb adsorption onto LDPE surface when biofilm was present is best described by Pseudo 2nd order kinetic model. Pb adsorption onto new LDPE surfaces was significantly reduced from 1101 μg/m2 to 134 μg/m2 with increased aqueous solution's ionic strength from 3 × 10−6 M to 0.0072 M. The presence of chlorine residual (2 mg/L) significantly reduced Pb adsorption onto LDPE surfaces by possible oxidation of Pb2+ to Pb4+ species. The kinetics of Pb release from LDPE surfaces was investigated under static and dynamic conditions through immediate exposure of Pb accumulated LDPE pellets to the synthetic water at pH 5.0 and 7.8. The results demonstrated a greater Pb release (86 %) at pH 5.0 compared to the pH 7.8 (58 %). An enhanced Pb release into the contact water was found under dynamic conditions compared to static conditions. [ABSTRACT FROM AUTHOR]