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Real-time bidding has become a major means for online advertisement exchange. The goal of a real-time bidding strategy is to maximize the benefits for stakeholders, e.g., click-through rates or conversion rates. However, in practise, the optimal bidding strategy for real-time bidding is constrained by at least three aspects: cost-effectiveness, the dynamic nature of market prices, and the issue of missing bidding values. To address these challenges, we propose Imagine and Imitate Bidding (IIBidder), which includes Strategy Imitation and Imagination modules, to generate cost-effective bidding strategies under partially observable price landscapes. Experimental results on the iPinYou and YOYI datasets demonstrate that IIBidder reduces investment costs, optimizes bidding strategies, and improves future market price predictions.

In view of the current problems of complex models and insufficient data processing in ultra-short-term prediction of photovoltaic power generation, this paper proposes a photovoltaic power ultra-short-term prediction model named HPO-KNN-SRU, based on a Simple Recurrent Unit (SRU), K-Nearest Neighbors (KNN), and Hunter–Prey Optimization (HPO). Firstly, the sliding time window is determined by using the autocorrelation function (ACF), partial correlation function (PACF), and model training. The Pearson correlation coefficient method is used to filter the principal meteorological factors that affect photovoltaic power. Then, the K-Nearest Neighbors (KNN) algorithm is utilized for effective outlier detection and processing to ensure the quality of input data for the prediction model, and the Hunter–Prey Optimization (HPO) algorithm is applied to optimize the parameters of the KNN algorithm. Finally, the efficient Simple Recurrent Unit (SRU) model is used for training and prediction, with the Hunter–Prey Optimization (HPO) algorithm applied to optimize the parameters of the SRU model. Simulation experiments and extensive ablation studies using photovoltaic data from the Desert Knowledge Australia Solar Centre (DKASC) in Alice Springs, Australia, validate the effectiveness of the integrated model, the KNN outlier handling, and the HPO algorithm. Compared to the Support Vector Regression (SVR), Long Short-Term Memory (LSTM), Temporal Convolutional Network (TCN), and Simple Recurrent Unit (SRU) models, this model exhibits an average reduction of 19.63% in Mean Square Error (RMSE), 27.54% in Mean Absolute Error (MAE), and an average increase of 1.96% in coefficient of determination (R2) values.

The thermal perception of different body parts can vary greatly throughout the human body and have different influences on overall thermal sensation and comfort. Various personal comfort systems (PCS) have been developed to stimulate local body parts for the purpose of enhancing human thermal comfort, yet the most effective body parts for intervention remain undetermined. Therefore, a series of climate chamber experiments under five uniform environments with three sets of suits were conducted in this study. The results showed that the head, chest, belly, and hands tended to feel no cooler than overall in cooler environments, but arms and legs felt generally no warmer than overall in warmer environments. The head, trunk and upper arms were more likely to be the comfort-dominant body parts. Additionally, the upper arms and upper back expected temperature regulation measures the most under non-neutral environments, thus they seem to be the two most needed and effective targeted body parts that a PCS could be applied to. The skin temperature and thermal sensation of limbs were more sensitive to indoor air temperatures than those of the torso. However, variations in the skin temperature of the head, chest, upper back, and calves had the strongest correlation with overall sensation vote changes. The above results and conclusions can not only serve as the basis for the future studies of local thermal comfort, but also provide theoretical guidance for the design of future PCS products.

Quarantine is one of the effective approaches to control the spread of COVID-19. However, prolonged isolation may harm the health of residents, especially students, who are quarantined in dormitories. This study surveyed students’ behaviors, living environment, and psychological state through an online questionnaire. The results showed that during the isolation period, the participants’ discomfort mainly came from high temperatures, high humidity, loud sounds, and dark lighting. Moreover, about half of the students experienced severe anxiety or depression, with poor sleep and an unclear mind being the most common problems. Additionally, this study focused on exploring the correlations between environmental perceptions and the psychological state of isolated students, that were identified to be significant. Furthermore, as isolation time was prolonged, the psychological state of isolated students worsened, and the most significant factor changed from thermal sensations to acoustic sensations. Interestingly, the psychological state of males was worse than females, and they were more easily affected by their thermal and acoustic environments. Therefore, keeping the environment comfortable has a positive influence on maintaining the good psychological condition of people in isolation. This study can provide suggestions for the improvement of indoor environments and for the mental health of people in isolation and in other similar situations.

Hydrogel coatings that can endow various substrates with superior properties (e.g., biocompatibility, hydrophilicity, and lubricity) have wide applications in the fields of oil/water separation, antifouling, anti-bioadhesion, etc. Currently, the engineering of multifunctional hydrogel-coated materials with superwettability and water purification property using a simple and sustainable strategy is still largely uninvestigated but has a beneficial effect on the world. Herein, we successfully prepared poly(2-acrylamido-2-methyl-1-propanesulfonic acid) hydrogel/β-FeOOH-coated poly(vinylidene fluoride) (PVDF/PAMPS/β-FeOOH) membrane through free-radical polymerization and the in situ mineralization process. In this work, owing to the combination of hydrophilic PAMPS hydrogel coating and β-FeOOH nanorods anchored onto PVDF membrane, the resultant PVDF/PAMPS/β-FeOOH membrane achieved outstanding superhydrophilicity/underwater superoleophobicity. Moreover, the membrane not only effectively separated surfactant-stabilized oil/water emulsions, but also possessed a long-term use capacity. In addition, excellent photocatalytic activity against organic pollutants was demonstrated so that the PVDF/PAMPS/β-FeOOH membrane could be utilized to deal with wastewater. It is envisioned that these hydrogel/β-FeOOH-coated PVDF membranes have versatile applications in the fields of oil/water separation and wastewater purification.

Tassieri et al. have introduced a novel rheological tool called “i-Rheo GT” that allows the evaluation of the frequency-dependent materials’ linear viscoelastic properties from a direct Fourier transform of the time-dependent relaxation modulus G(t), without artifacts. They adopted i-Rheo GT to exploit the information embedded in G(t) derived from molecular dynamics simulations of atomistic and quasi-atomistic models, and they estimated the polymers’ entanglement characteristic time (τe) from the crossover point of the moduli at intermediate times, which had never been possible before because of the poor fitting performance, at short time scales, of the commonly used generalized Maxwell models. Here, we highlight that the values of τe reported by Tassieri et al. are significantly different (i.e., an order of magnitude smaller) from those reported in the literature, obtained from either experiments or molecular dynamics simulations of different observables. In this work, we demonstrate that consistent values of τe can be achieved if the initial values of G(t), i.e., those governed by the bond-oscillation dynamics, are discarded. These findings have been corroborated by adopting i-Rheo GT to Fourier transform the outcomes of three different molecular dynamics simulations based on the following three models: a dissipative particle dynamics model, a Kremer–Grest model, and an atomistic polyethylene model. Moreover, we have investigated the variations of τe as function of (i) the ‘cadence’ at which G(t) is evaluated, (ii) the spring constant of the atomic bone, and (iii) the initial value of the shear relaxation modulus G(O). The ensemble of these results confirms the effectiveness of i-Rheo GT and provide new insights into the interpretation of molecular dynamics simulations for a better understanding of polymer dynamics.

Nanofiber bundles with specific areas bring a new opportunity for selective adsorption and oil/water or air separation. In this work, nanofiber bundles were prepared by the electrospinning of immiscible polystyrene (PS)/N-trifluoroacetylated polyamide 6 (PA6-TFAA) blends via the introduction of carbon nanotubes (CNTs) or a copolymer of styrene and 3-isopropenyl-α, α’-dimethylbenzene isocyanate (TMI), which was denoted as PS-co-TMI. Herein, CNT was used to increase the conductivity of the precursor for enhancing the stretch of PS droplets under the same electric field, and PS-co-TMI was used as a reactive compatibilizer to improve the compatibility of a PS/PA6-TFAA blend system for promoting the deformation. Those obtained nanofiber bundle membranes showed an increase in tensile strength and high hydrophobicity with a water contact angle of about 145.0 ± 0.5°. Owing to the special structure, the membranes also possessed a high oil adsorption capacity of 31.0 to 61.3 g/g for different oils. Moreover, it exhibits a high potential for gravity-driven oil/water separation. For example, those membranes had above 99% separation efficiency for silicon oil/water and paraffin wax/water. Furthermore, the air filtration efficiency of nanofiber bundle membranes could reach above 96%, which might be two to six times higher than the filtration efficiency of neat PS membranes.

Objective: To explore the effect and mechanism of peppermint essential oil on learning and memory ability of APP/PS1 transgenic mice. Methods: Morris water maze test and shuttle box test were used to explore the changes in learning and memory ability of APP/PS1 transgenic mice after sniffing essential oil. The cellular status of neurons in the hippocampal CA1 region of the right hemisphere, Aβ deposition, oxidative stress level, and serum metabonomics were detected to explore its mechanism. Results: Sniffing peppermint essential oil can improve the learning and memory ability of APP/PS1 transgenic mice. Compared with the model group, the state of neurons in the hippocampal CA1 region of the peppermint essential oil group returned to normal, and the deposition of Aβ decreased. The MDA of brain tissue decreased significantly, and the activity of SOD and GSH-PX increased significantly to the normal level. According to the results of metabonomics, it is speculated that peppermint essential oil may improve cognitive function in AD by regulating arginine and proline metabolism, inositol phosphate metabolism, and cysteine and methionine metabolism.

Personal thermal preference information can help to create a building environment that satisfies all staff, instead of an environment that only satisfies most people, to enhance personal thermal comfort. Research has shown that thermal preference can be predicted using parameters that are based on various local body parts, but the selected body parts are often different. Using too many body parts for the measurements leads to high costs, while using too few body parts results in large errors. In this study, 19 adult subjects (8 females and 11 males) were recruited, their overall and local thermal preferences were surveyed, and the skin temperature of seven body parts were measured. A machine learning algorithm, random forest, was employed to analyse the contributions of different body parts. Three criteria (the best combination, fewest combination, and common combinations) were employed to select body parts to use to establish thermal preference models for individuals and groups. The results show that the prediction power of these combinations reached 0.91 ± 0.07 (accuracy), 0.75 ± 0.16 (Cohen’s kappa), and 0.87 ± 0.09 (AUC) when using 2–8 body parts. The common combinations are recommended for their balance of their prediction power and the number of local body parts involved. This study offers a reference for efficient and economic measurements for thermal comfort research in building environments.

Keratin is a tough fibrous structural protein that is difficult to digest with pepsin and trypsin because of the presence of a large number of disulfide bonds. Keratin is widely found in agricultural waste. In recent years, especially, the development of the poultry industry has resulted in a large accumulation of feather keratin resources, which seriously pollute the environment. Keratinase can specifically attack disulfide bridges in keratin, converting them from complex to simplified forms. The keratinase thermal stability has drawn attention to various biotechnological industries. It is significant to identify keratinases and improve their thermostability from microorganism in extreme environments. In this study, the keratinases DgoKerA was identified in Deinococcus gobiensis I-0 from the Gobi desert. The amino acid sequence analysis revealed that DgoKerA was 58.68% identical to the keratinase MtaKerA from M. thermophila WR-220 and 40.94% identical to the classical BliKerA sequence from B. licheniformis PWD-1. In vitro enzyme activity analysis showed that DgoKerA exhibited an optimum temperature of 60 °C, an optimum pH of 7 and a specific enzyme activity of 51147 U/mg. DgoKerA can degrade intact feathers at 60 °C and has good potential for industrial applications. The molecular modification of DgoKerA was also carried out using site-directed mutagenesis, in which the mutant A350S enzyme activity was increased by nearly 30%, and the results provide a theoretical basis for the development and optimization of keratinase applications.

WRKY transcription factors comprise one of the largest gene families and serve as key regulators of plant defenses against herbivore attack. However, studies related to the roles of WRKY genes in response to herbivory are limited in maize. In this study, a total of 128 putative maize WRKY genes (ZmWRKYs) were identified from the new maize genome (v4). These genes were divided into seven subgroups (groups I, IIa–e, and III) based on phylogenomic analysis, with distinct motif compositions in each subgroup. Syntenic analysis revealed that 72 (56.3%) of the genes were derived from either segmental or tandem duplication events (69 and 3, respectively), suggesting a pivotal role of segmental duplication in the expansion of the ZmWRKY family. Importantly, transcriptional regulation prediction showed that six key WRKY genes contribute to four major defense-related pathways: L-phenylalanine biosynthesis II and flavonoid, benzoxazinoid, and jasmonic acid (JA) biosynthesis. These key WRKY genes were strongly induced in commercial maize (Jingke968) infested with the Asian corn borer, Ostrinia furnacalis, for 0, 2, 4, 12 and 24 h in the field, and their expression levels were highly correlated with predicted target genes, suggesting that these genes have important functions in the response to O. furnacalis. Our results provide a comprehensive understanding of the WRKY gene family based on the new assembly of the maize genome and lay the foundation for further studies into functional characteristics of ZmWRKY genes in commercial maize defenses against O. furnacalis in the field.

A micro-channel distillation device was used for the process intensification method to separate boron isotopes, 10B and 11B. Three-dimensional (3D) printing technology was introduced to manufacture the micro-channel device, which used the chemical exchange method with anisole as the donor to separate the boron isotopes. This device was tested in total reflux mode, and the height of an equivalent theoretical plate of the micro-channel distillation equipment was reduced to 1.56 cm. The accurate control of pressure and temperature, as well as the flow rate of the complex, were factors that affected separation ability. Thus, for process intensification, this micro-channel distillation device can be operated horizontally and connected in series into similar modules to effectively improve separation efficiency and reduce the size of the equipment.

Various algorithms predominantly use data-driven methods for forecasting building electricity consumption. Among them, algorithms that use deep learning methods and, long and short-term memory (LSTM) have shown strong prediction accuracy in numerous fields. However, the LSTM algorithm still has certain limitations, e.g., the accuracy of forecasting the building air conditioning power consumption was not very high. To explore ways of improving the prediction accuracy, this study selects a high-rise office building in Shanghai to predict the air conditioning power consumption and lighting power consumption, respectively and discusses the influence of weather parameters and schedule parameters on the prediction accuracy. The results demonstrate that using the LSTM algorithm to accurately predict the electricity consumption of air conditioners is more challenging than predicting lighting electricity consumption. To improve the prediction accuracy of air conditioning power consumption, two parameters, relative humidity, and scheduling, must be added to the prediction model.

Keratinase can specifically attack disulfide bridges in keratin to convert them from complex to simplified forms. Keratinase thermal stability has drawn attention to various biotechnological industries. In this study, a keratinase DgeKer was identified from a slightly thermophilic species, D. geothermalis. The in silico analysis showed that DgeKer is composed of signal peptide, N-terminal propeptide, mature domain, and C-terminal extension. DgeKer and its C-terminal extension-truncated enzyme (DgeKer-C) were cloned and expressed in E. coli. The purified DgeKer and DgeKer-C showed maximum activity at 70 °C and pH 9–The thermal stability assay (60 °C) showed that the half-life value of DgeKer and DgeKer-C were 103.45 min and 169.10 min, respectively. DgeKer and DgeKer-C were stable at the range of pH from 9 to 11 and showed good tolerance to some metal ions, surfactants and organic solvent. Furthermore, DgeKer could degrade feathers at 70 °C for 60 min. However, the medium became turbid with obvious softening of barbules after being treated with DgeKer-C, which might be due to C-terminal extension. In summary, a thermostable keratinase DgeKer with high efficiency degradation of feathers may have great potential in industry.

Most late embryogenesis abundant group 3 (G3LEA) proteins are highly hydrophilic and disordered, which can be transformed into ordered α-helices to play an important role in responding to diverse stresses in numerous organisms. Unlike most G3LEA proteins, DosH derived from Dinococcus radiodurans is a naturally ordered G3LEA protein, and previous studies have found that the N-terminal domain (position 1–103) of DosH protein is the key region for its folding into an ordered secondary structure. Synthetic biology provides the possibility for artificial assembling ordered G3LEA proteins or their analogues. In this report, we used the N-terminal domain of DosH protein as module A (named DS) and the hydrophilic domains (DrHD, BnHD, CeHD, and YlHD) of G3LEA protein from different sources as module B, and artificially assembled four non-natural hydrophilic proteins, named DS + DrHD, DS + BnHD, DS + CeHD, and DS + YlHD, respectively. Circular dichroism showed that the four hydrophile proteins were highly ordered proteins, in which the α-helix contents were DS + DrHD (56.1%), DS + BnHD (53.7%), DS + CeHD (49.1%), and DS + YLHD (64.6%), respectively. Phenotypic analysis showed that the survival rate of recombinant Escherichia coli containing ordered hydrophilic protein was more than 10% after 4 h treatment with 1.5 M NaCl, which was much higher than that of the control group. Meanwhile, in vivo enzyme activity results showed that they had higher activities of superoxide dismutase, catalase, lactate dehydrogenase and less malondialdehyde production. Based on these results, the N-terminal domain of DosH protein can be applied in synthetic biology due to the fact that it can change the order of hydrophilic domains, thus increasing stress resistance.

Human thermoregulation models can predict human thermal responses to evaluate thermal comfort and help create a healthy environment, while their applicability to older people has not been sufficiently validated. This study aimed to evaluate the performance of the Stolwijk model and the Tanabe model for predicting older people’s mean and local skin temperatures under thermal transient conditions. Eighteen healthy older people were recruited and exposed to transient environments including neutral (26 °C), low-temperature (23 and 21 °C), and high-temperature (29 and 32 °C) conditions. The local skin temperatures of the subjects were measured and compared to predictions of the Stolwijk model and the Tanabe model. The results revealed that the Stolwijk model and the Tanabe model could accurately predict the mean skin temperature of older people under neutral and high-temperature conditions, while their predictive accuracy declined under low-temperature conditions. Increased deviations were observed in the predictions of local skin temperatures for all conditions. This work attempted to provide an understanding of older people’s thermal response characteristics under transient conditions and to inspire the improvement of thermoregulation models for older people.

Enriched boron-10 and its related compounds have great application prospects, especially in the nuclear industry. The chemical exchange rectification method is one of the most important ways to separate the 10B and 11B isotope. However, a real-time monitoring method is needed because this separation process is difficult to characterize. Infrared spectroscopy was applied in the separation device to realize the online determination of the boron isotope ratio in boron trifluoride (BF3). The possibility of determining the isotope ratio via the 2ν3 band was explored. A correction factor was introduced to eliminate the difference between the ratio of peak areas and the true value of the boron isotope ratio. It was experimentally found that the influences of pressure and temperature could be ignored. The results showed that the infrared method has enough precision and stability for real-time, in situ determination of the boron isotope ratio. The instability point of the isotope ratio can be detected with the assistance of the online determination method and provides a reference for the production of boron isotope.

Predictions in ungauged basins (PUB) has been always a focus of hydrological research. The problem presented by ungauged basins is how to reasonably estimate water resource availability. To solve the issues of data scale, this study combines field experiments and hydrological models to estimate freshwater availability in a typical ungauged sea island located in southeastern China. The free parameters in the hydrological model were derived from the point-scale rainfall-runoff experiments rather than calibration using river discharge observations. The rainfall-runoff experiments were performed on six sites covering 11 land cover types. Model validation at a sub-catchment showed that the combined method could successfully reproduce monthly streamflow, with a Nash–Sutcliffe Efficiency of 0.82, correlation coefficient of 0.85, and flow volume error of 6.5%. The simulation results indicate high heterogeneity and distinct seasonal dynamics in freshwater availability across the entire island. This pioneering PUB study for Chinese islands could provide reference for planning and management of freshwater in a water shortage area.

Background: Neoadjuvant chemoradiation therapy (NCRT) followed by surgery is the standard treatment for locally advanced rectal cancer (LARC); approximately 80% of patients do not achieve complete response. Identifying prognostic factors predictive of survival in these patients to guide further management is needed. The intratumoural lymphocytic response (ILR), peritumoural lymphocytic reaction (PLR), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PtLR) are correlated with the tumour microenvironment and cancer-related systemic inflammation. This study aimed to explore the ability of the ILR, PLR, NLR, and PtLR to predict survival in LARC patients without a complete response to NCRT. Methods: Sixty-nine patients who underwent NCRT and surgery were retrospectively reviewed. The ILR and PLR were assessed in surgical specimens, and the NLR and PtLR were calculated using pre- and post-NCRT blood count data. The Kaplan–Meier method and Cox regression analyses were performed for survival analysis. Results: A high PLR and high post-NCRT NLR and PtLR were significantly associated with better prognosis. Lymphovascular invasion (LVI), post-NCRT neutrophil count, and lymphocyte count were significant predictors of overall survival. LVI and the PLR were independent predictors of disease-free survival. Conclusions: NCRT-induced local and systemic immune responses are favourable prognostic predictors in LARC patients without complete response to NCRT.

Fetal hyperthyroidism can occur secondary to maternal autoimmune hyperthyroidism. The thyroid-stimulating hormone receptor antibody (TRAb) transferred from the mother to the fetus stimulates the fetal thyroid and causes fetal thyrotoxicosis. Fetuses with this condition are difficult to detect, especially after maternal Graves disease therapy. Here, we present two cases of fetal hyperthyroidism with maternal hypothyroidism and review the assessment and intrauterine therapy for fetal hyperthyroidism. Both women were referred at 22+ and 23+ weeks of gestation with abnormal ultrasound findings, including fetal heart enlargement, pericardial effusion, and fetal tachycardia. Both women had a history of Graves disease while in a state of hypothyroidism with a high titer of TRAb. A sonographic examination showed a diffusely enlarged fetal thyroid with abundant blood flow. Invasive prenatal testing revealed no significant chromosomal aberration. Low fetal serum TSH and high TRAb levels were detected in the cord blood. Fetal hyperthyroidism was considered, and maternal oral methimazole (MMI) was administered as intrauterine therapy, with the slowing of fetal tachycardia, a reduction in fetal heart enlargement, and thyroid hyperemia. During therapy, maternal thyroid function was monitored, and the dosage of maternal levothyroxine was adjusted accordingly. Both women delivered spontaneously at 36+ weeks of gestation, and neonatal hyperthyroidism was confirmed in both newborns. After methimazole and propranolol drug treatment with levothyroxine for 8 and 12 months, both babies became euthyroid with normal growth and development.

Transistors made up of carbon nanotube CNT have demonstrated excellent current–voltage characteristics which outperform some high-grade silicon-based transistors. A continuously tunable energy barrier across semiconductor interfaces is desired to make the CNT-based transistors more robust. Despite that the direct band gap of the carbyne inside a CNT can be widely tuned by strain, the size of the carbyne cannot be controlled easily. The production of a monoatomic chain with more than 6000 carbon atoms is an enormous technological challenge. To predict the optimal chain length of a carbyne in different molecular environments, we have developed a Monte Carlo model in which a finite-length carbyne with a size of 4000–15,000 atoms is encapsulated by a CNT at finite temperatures. Our simulation shows that the stability of the carbyne@nanotube is strongly influenced by the nature and porosity of the CNT, the external pressure, the temperature, and the chain length. We have observed an initiation of the chain-breaking process in a compressed carbyne@nanotube. Our work provides much-needed input for optimizing the carbyne length to produce carbon chains much longer than 6000 atoms at ~300 K. Design rules are proposed for synthesizing ~1% strained carbyne@(6,5)CNT as a component in CNT-based transistors to tune the energy barriers continuously.

This paper presents a comprehensive study of the energy structure, optical characteristics, and spectral-kinetic parameters of elementary excitations in a high-purity nanocrystalline cubic Y2O3 film synthesized by reactive magnetron sputtering. The optical transparency gaps for direct and indirect interband transitions were determined and discussed. The dispersion of the refractive index was established based on the analysis of interference effects. It was found that the refractive index of the Y2O3 film synthesized in this study is higher in order of magnitude than that of the films obtained with the help of other technologies. The intrinsic emission of Y2O3 film has been discussed and associated with the triplet–singlet radiative relaxation of self-trapped and bound excitons. We also studied the temperature behavior of the exciton luminescence of Y2O3 for the first time and determined thermal activation barriers. The optical energy and kinetic parameters of cubic Y2O3 films were analyzed in comparison with those of the monoclinic films of yttrium oxide. The main difference between the optical properties of cubic and monoclinic Y2O3 films was established, which allowed for a supposition of their application prospects.

With the ever-growing demand in fresh water supply, great efforts have been devoted to developing sustainable systems which could generate fresh water continuously. Solar vapor generation is one of the promising strategies which comprise an unlimited energy source and efficient solar-to-heat generators for overcoming fresh water scarcity. However, current solar vapor generation systems suffer either from inefficient utilization of solar energy or an expensive fabrication process. In this paper, we introduced a nano-plasmonic approach, i.e., a floatable nanocompoiste where copper sulfide nanorods (Cu2-xS NRs) are embedded in a polyvinyl alcohol (PVA) matrix, for solar-to-vapor generation. A high solar vapor generation efficiency of ~87% and water evaporation rate of 1.270 kg m−2 h−1 were achieved under simulated solar irradiation of 1 sun. With the illumination of natural daylight, seawater was purified using Cu2-xS NRs-PVA gel, with high purity, as distilled drinking water. The plasmonic nanocomposites demonstrated here are easy to fabricate and highly efficient for solar vapor generation, illustrating a potential solution for future seawater desalination.

A promising protein target for computational drug development, the human cluster of differentiation 38 (CD38), plays a crucial role in many physiological and pathological processes, primarily through the upstream regulation of factors that control cytoplasmic Ca2+ concentrations. Recently, a small-molecule inhibitor of CD38 was shown to slow down pathways relating to aging and DNA damage. We examined the performance of seven docking programs for their ability to model protein-ligand interactions with CD38. A test set of twelve CD38 crystal structures, containing crystallized biologically relevant substrates, were used to assess pose prediction. The rankings for each program based on the median RMSD between the native and predicted were Vina, AD4 > PLANTS, Gold, Glide, Molegro > rDock. Forty-two compounds with known affinities were docked to assess the accuracy of the programs at affinity/ranking predictions. The rankings based on scoring power were: Vina, PLANTS > Glide, Gold > Molegro >> AutoDock 4 >> rDock. Out of the top four performing programs, Glide had the only scoring function that did not appear to show bias towards overpredicting the affinity of the ligand-based on its size. Factors that affect the reliability of pose prediction and scoring are discussed. General limitations and known biases of scoring functions are examined, aided in part by using molecular fingerprints and Random Forest classifiers. This machine learning approach may be used to systematically diagnose molecular features that are correlated with poor scoring accuracy.

Hydroxyapatite (HAP) is the most suitable biocompatible material for bone implant coatings; its brittleness, however, is a major obstacle, and the reason why research focuses on creating composites with biopolymers. Organosolv lignin (Lig) is used for the production of composite coatings, and these composites were examined in this study. Titanium substrate is a key biomedical material due to its well-known properties, but infections of the implantation site still impose a serious threat. One approach to prevent infection is to improve antimicrobial properties of the coating material. Silver doped hydroxyapatite (Ag/HAP) and HAP coatings on titanium were obtained by an electrophoretic deposition method in order to control deposited coating mass and morphology by varying applied voltage and deposition time. The effect of lignin on microstructure, morphology and thermal behavior of biocomposite coatings was investigated. The results showed that higher lignin concentrations protect the HAP lattice during sintering, improving coating stability. The corrosion stability was evaluated in simulated body fluid (SBF) at 37 °C. Newly formed plate-shaped carbonate-HAP was detected, indicating enhanced bioactive performance. The antimicrobial efficiency of Ag/HAP/Lig was confirmed by its higher reduction of bacteria Staphylococcus aureus TL (S. aureus TL) than of HAP/Lig coating. Cytotoxicity assay revealed that both coatings can be classified as non-toxic against healthy immunocompetent peripheral blood mononuclear cells (PBMC).

A novel bio-adsorbent was fabricated via grafting an amino-terminated hyperbranched polymer (HBP-NH2) onto bagasse cellulose. The morphology and microstructure of the HBP-NH2-grafted bagasse cellulose (HBP-g-BC) were characterized and its adsorption capacity for Cr(VI) ions in aqueous solutions was investigated. The rough surface structure of HBP-g-BC that is beneficial for improving the adsorption capacity was observed by scanning electron microscopy (SEM). The grafting reaction was confirmed by Fourier-transform infrared (FT-IR) spectroscopy. The adsorbent performance was shown to be better with a lower pH value, a higher adsorbent dosage, or a higher initial Cr(VI) concentration. Moreover, the kinetics study revealed that the adsorption behavior followed a pseudo-second-order model. The isotherm results showed that the adsorption data could be well-fitted by the Langmuir, Freundlich, or Temkin models. Moreover, HBP-g-BC could maintain 74.4% of the initial removal rate even after five cycles of regeneration. Thus, the high potential of HBP-g-BC as a bio-adsorbent for heavy metal removal has been demonstrated.