Search

Diabetic foot ulcers (DFUs), a serious and increasingly common chronic issue among diabetics, often do not respond well to generalized treatment strategies. Hypoxia and the overexpression of reactive oxygen species (ROS), resulting in inflammatory dysregulation and subsequent imbalance in macrophage phenotypes, are critical factors contributing to the prolonged non‐healing of DFU wounds. These two issues often interact in a continuous, problematic cycle. Presently, there is a lack of comprehensive strategies aimed at addressing both of these factors simultaneously to interrupt this detrimental cycle. Herein, an immunomodulatory hydrogel (PHG2) is developed for reshaping the hostile DFU microenvironment. The engineered PHG2 not only removes excess internally‐produced ROS but also generates O2, with its efficiency further boosted by local hyperthermia (42.5 °C) activated by near‐infrared light. Through both in vitro and in vivo studies, along with transcriptomic assessment, it is confirmed that PHG2 disrupts the detrimental feedback loop between ROS and inflammation while also lowering the M1/M2 macrophage ratio. Such discoveries contribute to a significant enhancement in the healing process of injuries that undergo a gradual increase in movement, covering wounds from the back, mouth, to the foot. Ultimately, this method provides an easy, safe, and highly effective solution for treating DFUs. [ABSTRACT FROM AUTHOR]

Demand response capacity is a key reference for demand-side participation in peak regulation and earning profit in the electricity market, and it is influenced by not only external public factors but demand-side internal individual factors. Demand change caused by internal individual reasons cannot be recognized by public features. Single participating in response industrial and commercial consumers cannot balance this change through large numbers of participants, unlike aggregators. The prediction model only considering the external public factors will cause significant errors. However, the actual industrial and commercial data is difficult to obtain because of the cost and privacy, and the simulation platform cannot accurately describe this situation, resulting in the problem being ignored. Therefore, this paper aims to prove the importance of internal factors and proposes an improved method considering the problem. First, based on an actual dataset, the optimal responsive behavior of consumers is modeled to quantify response capacity. Second, a support vector machine (SVM) method is applied to predict response capacity. Finally, combined with raw data, this paper proves that significant errors are caused by internal factors and provides different improvement methods for internal and external operators. The case study indicates that the improved model can provide better performance. • The impact of internal factors on response capacity prediction is proven, and prediction accuracy has been improved. • A method is proposed to improve the prediction accuracy for operators who cannot directly obtain internal information. • Based on the actual dataset, optimization and simulation of user behavior can better reflect the real response situation. • This study is developed under the price-based and incentive-based composite demand response program. • This study improves the modeling method of HVAC. [ABSTRACT FROM AUTHOR]

Customer baseline load (CBL) estimation plays a crucial role in financial settlement for incentive-based demand response (DR). Most current CBL estimation methods utilize temporal auto-correlation or spatial cross-correlation to estimate the CBL, which would produce large errors when the load pattern suddenly changes on the DR event day or the number of CONTROL customers is insufficient. To this end, a spatio-temporal CBL estimation approach is proposed to improve the estimation accuracy in this article. First, all CONTROL customers are grouped into several nonoverlapping clusters by the K-means algorithm. Each DR customer is then matched to the most similar cluster according to the similarity between the typical load pattern and the cluster center. Second, spatio-temporal features are extracted from the historical load data of the DR customer itself and the load data of the matched CONTROL customers on the DR event day. Third, the least absolute shrinkage and selection operator regression model is constructed to estimate the CBL of each DR customer. The effectiveness and superiority of the proposed approach have been verified on a real-world load dataset. [ABSTRACT FROM AUTHOR]

An increasing number of residential customers have installed hybrid rooftop solar battery systems (HRSBSs). Currently, most HRSBSs are installed behind-the-meter (BTM), where only customers’ net load is measured by smart meters. This invisibility poses significant challenges to the system operation. Disaggregating BTM PV generation and battery charging/discharging profile of customers can enhance the grid-edge observability. This article proposes an energy disaggregation method to jointly separate the PV generation and battery charging/discharging power from the net load. First, a Home Smart Battery Management model is built to simulate the battery charging/discharging profile. Second, an optimal disaggregation model is established based on a contextually supervised source separation method. Furthermore, the feature vectors of PV, load, and battery are extracted as the input of the disaggregation model. Case studies on two datasets from Australia and China show that the proposed method has a promising disaggregation performance. [ABSTRACT FROM AUTHOR]

Residential customers account for an indispensable part in the demand response (DR) program for their capability to provide flexibility when the system required. However, their available DR capacity has not been fully comprehended by the aggregator, who needs the information to bid accurately on behalf of the residential customers in the market transaction. To this end, this article devised an optimal bidding strategy for the aggregator considering the bottom-up responsiveness of residential customers. First, we attempt to establish the customers’ responsiveness function in relation to different incentives, during which a home energy management system is introduced to implement load adjustment for electrical appliances. Second, the functional relation is applied to the aggregator's decision-making process to formulate the optimal bidding strategy in the day-ahead market and the optimal scheduling scheme for the energy storage system with the aim to maximize its own revenue. Finally, the validity of the proposed method is verified using the dataset from the Pecan Street experiment in Austin. The obtained outcome demonstrates the practical rationality of the proposed method. [ABSTRACT FROM AUTHOR]

This paper, for the first time ever, proposes a Laplace-like integral transform, which is called as He-Laplace transform, its basic properties are elucidated. The homotopy perturbation method coupled with this new transform becomes much effective in solving fractal differential equations. Phi-four equation with He's derivative is used as an example to reveal the main merits of the present technology. [ABSTRACT FROM AUTHOR]

In a typical electricity market, the load aggregator (LA) bids in the wholesale market to purchase electricity and meet the expected demand of its customers in the retail market. However, considering the uncertainty of the wholesale market prices, the LA has to undertake all the risks arising from the price volatility in the wholesale market, which may make the LA suffer from financial loss under some scenarios such as price spikes. To this end, first, this article proposes an optimal bidding strategy model for the LA that implements the demand response program (DRP), which enables the LA to reduce the risk of financial loss caused by price volatility. The bidding model is a mixed integer linear programming problem, which can be solved efficiently via a commercial solver. Second, making a rational and quantitative compensation mechanism is significant for the LA to induce its customers to participate in the DRP while there are few studies investigating it, hence, this article designs a quantitative compensation mechanism for the LA. Case studies using a dataset from the Thames valley vision verify the effectiveness of the proposed bidding model. The results confirm that the implementation of DRP not only brings great profits to LA but also benefits the other entities in the electricity market. [ABSTRACT FROM AUTHOR]

Atractylodes japonica is a perennial herb in Compositae family, which is used for stomach disorders as a traditional Chinese medicine (Guo et al. ). In 2013, a leaf spot disease was first observed on plants of A. japonica in a production field of Fushun County, Liaoning Province, China. The disease had a speckled appearance initially. Lesions with grey-white centre and brown margin gradually developed and enlarged. Eventually, infections usually caused yellowing of the leaves and premature defoliation. The causal agent of infection on plants was identified as Paraphoma chrysanthemicola based on morphological and cultural characteristics, pathogenicity tests and phylogenetic analysis. To our knowledge, this is the first report of a leaf spot disease on A. japonica caused by P. chrysanthemicola in China. [ABSTRACT FROM AUTHOR]

Summary Unit recordings in behaving animals have revealed the transformation of sensory to motor representations in cortical neurons. However, we still lack basic insights into the mechanisms by which neurons interact to generate such transformations. Here, we study cortical circuits related to behavioral control in mice engaged in a sensory detection task. We recorded neural activity using extracellular and intracellular techniques and analyzed the task-related neural dynamics to reveal underlying circuit processes. Within motor cortex, we find two populations of neurons that have opposing spiking patterns in anticipation of movement. From correlation analyses and circuit modeling, we suggest that these dynamics reflect neural ensembles engaged in a competition. Furthermore, we demonstrate how this competitive circuit may convert a transient, sensory stimulus into a motor command. Together, these data reveal cellular and circuit processes underlying behavioral control and establish an essential framework for future studies linking cellular activity to behavior. [ABSTRACT FROM AUTHOR]

This paper represents experimental and numerical investigations into the dynamic response of woven carbon fiber reinforced thick composite laminates under low-velocity impact. Experiments with nine impact energies are carried out by the drop weight testing machine. The force-displacement curves are extracted from experimental data, and the influence of impact energy on impact response is discussed. The relationships between impact energy and impact performance such as peak force, maximum displacement, and absorbed energy are analyzed. The damage morphology obtained by digital microscope and ultrasonic C-scan is used to analyze the damage mechanisms. Experimental results show that woven composite laminates considered here exhibited several failure modes, including indentation, delamination, matrix cracks and fiber breakage. The finite element model is established to study the complex damage and failure mechanisms by employing ABAQUS/Explicit. Good consistency is achieved between the experimental and numerical results by comparing the force-time curves, impact resistance and damage status. Finally, the impact damage behavior of woven composite laminates with helicoidal layups is explored. [ABSTRACT FROM AUTHOR]

This paper addresses the optimal decision problem of a distributed energy resources (DER) aggregator who manages wind turbines, solar PV systems and battery energy storage (BES) units while implementing real-time pricing (RTP) demand response program. The DER aggregator can procure electricity by bidding in the electricity market and scheduling its DER to meet the load demand of its customers. In the bidding and scheduling processes, the intrinsic uncertainties of distributed renewable generations and customer's responsiveness to RTP program have brought economical risks to the DER aggregator, which will lower the DER aggregator's profit. However, most of the current researches only consider the uncertainty of renewable generations while neglecting the uncertainty of customer's responsiveness. To this end, a robust optimization-based day-ahead optimal bidding and scheduling model is proposed for DER aggregator by jointly considering these two uncertainties. The objective of the proposed model is to maximize the aggregator's profit via optimally determining the hourly bidding quantities in the day-ahead market and the scheduled output power of distributed renewable generations and BES units. Case studies demonstrate that the proposed robust optimization model can help DER aggregator reduce the bidding and scheduling costs to obtain a higher expected profit. • The impact mechanism of price responsive load uncertainty is revealed. • Optimal bidding and scheduling strategies of a DER aggregator are proposed. • The necessity of considering price responsive load uncertainty is verified. • The proposed method is more effective for more price-sensitive customers. [ABSTRACT FROM AUTHOR]

• Goal state moderated the correlation between goal-directed unethical behavior and meaning in life. • Meaning in life was significantly correlated with unethical behavior only after, but not prior to, goal completion. • Negative affect was correlated with unethical behavior both when a goal was actively pursued and when it was completed. The process of goal pursuit provides a unique opportunity to investigate real-life psychological implications of unethical behaviors. In two studies, we had participants recall the frequency of engaging in unethical behaviors during goal pursuit and report current experience of negative affect and meaning in life, during different goal states (i.e., ongoing vs. completed). Both studies revealed that meaning in life was negatively associated with unethical behaviors implemented in the process of pursuing a goal only after but not prior to goal completion. Negative affect, however, was positively associated with unethical behavior frequencies in both goal states. The current research helps integrate studies on personal goals and unethical behaviors, and sheds light on the dynamic consequences of engaging in unethical behaviors. [ABSTRACT FROM AUTHOR]

Visual spatial perception in the mammalian brain occurs through two parallel pathways: one reaches the primary visual cortex (V1) through the thalamus and another the superior colliculus (SC) via direct projections from the retina. The origin, development, and relative function of these two evolutionarily distinct pathways remain obscure. We examined the early functional development of both pathways by simultaneously imaging pre- and post-synaptic spontaneous neuronal activity. We observed that the quality of retinal activity transfer to the thalamus and superior colliculus does not change across the first two postnatal weeks. However, beginning in the second postnatal week, retinal activity does not drive V1 as strongly as earlier wave activity, suggesting that intrinsic cortical activity competes with signals from the sensory periphery as the cortex matures. Together, these findings bring new insight into the function of the SC and V1 and the role of peripheral activity in driving both circuits across development. • Second week ("stage 3") retinal waves are very distinct from first week ("stage 2") • Stage 3 waves are especially sensitive to inhibitory blockade • Retinal influence on the colliculus and thalamus does not change over development • However, the cortex becomes relatively insensitive to retinal drive before eye opening By simultaneously measuring input activity and output activity, Gribizis et al. show that peripheral spontaneous retinal activity consistently and strongly drives response in the midbrain superior colliculus during development, while the cortex becomes progressively less sensitive to peripheral drive. [ABSTRACT FROM AUTHOR]

• A mild one-step fabrication method of cross-linked GO membrane was proposed. • DA/PEI modification improved the structures and performances of GO membranes. • Flux and rejection simultaneously enhanced for removing heavy metal ions. • GO@DA/PEI 40 membrane exhibited superior anti-fouling performance and stability. Heavy metal ion contamination poses a significant threat to both our environment and human health. Consequently, there is a need for proficient and environmentally friendly remediation techniques to tackle this issue. Among various strategies, membrane-based separation using graphene oxide (GO) laminate membranes has emerged as a promising solution. However, traditional GO membranes have low water permeance, poor selectivity, structural instability, and inconsistent layer spacing. In this study, we cross-linked GO with polydopamine/polyethyleneimine (DA/PEI) using a mild one-step strategy to prepare a GO@DA/PEI membrane for heavy metal ion removal and evaluated the effect of cross-linking duration on the interlayer structure, membrane properties, and heavy metal ion removal performance. The successful formation of a cross-linked network between DA/PEI and GO was proven by various characterization methods. Compared with previously reported GO-based membranes, the prepared GO@DA/PEI 40 membrane exhibited excellent performance, including a peak pure water flux of 326.7 L/m2h and ion rejection of 99.6 % for Cu2+, 93.5 % for Pb2+, and 96.6 % for Zn2+, thereby overcoming the conventional trade-off" effect. The mechanism for the high flux was discussed. The cross-linking reaction between the oxygen-containing functional groups at the edges and basal planes of the GO flakes and DA/PEI were crucial to the high flux. In addition, the GO@DA/PEI 40 membrane had excellent anti-fouling performance in the presence of humic acid and long-term stability under different conditions. Overall, the GO@DA/PEI membrane has good potential for heavy metal ion removal. [ABSTRACT FROM AUTHOR]

This article proposes a meta-heuristic optimization-based two-stage residential load pattern clustering (LPC) approach to address two main issues that exist in the most current LPC methods: 1) unreasonable typical load pattern (TLP) extraction; 2) a good clustering should achieve a good balance between the compactness and separation of the formed clusters. However, few clustering algorithms integrate both of these two aspects into the objective function of clustering for consideration. In the first stage, an adaptive density-based spatial clustering of applications with noise (DBSCAN) is proposed to automatically detect the uncommon load curves and obtain the TLP of each individual customer. In the second stage, LPC is formulated as an optimization problem in which clustering validity index (CVI) considering both compactness and separation is used as the objective function. Gravitational search algorithm (GSA) is adopted to solve this optimization problem. Four different CVIs are investigated to find the most appropriate one for LPC. A comparative case study using the real load data from 208 households from the U.K. verified the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Thermodynamics and fluid mechanics are used to study the mechanical properties of a class of thermoelastic fluid materials. Using the law of thermodynamics and the law of conservation of energy, thermal science analysis of dissipative thermoelastic fluid materials is performed in a planar 2-D flow field, and a corresponding mathematical model is established. Fractal theory, operator semigroup theory and fractional calculus are used to study the overall well-posedness of a dissipative thermoelastic flow. [ABSTRACT FROM AUTHOR]

• A novel sandwich panel is designed by filling foam material into corrugated core. • The synergetic damage of the panels under combined blast loading is analyzed. • Special focus is placed on revealing the effects of stand-off distance, foam density and core configuration. • Performance difference for panels under bare and combined blast loading is discussed. Foam filling strategy has been demonstrated to owing the ability to improve the blast resistance of sandwich panels under bare blast loading. But it is unclear that the effect of foam filling for performance improvement of sandwich panels in response to combined blast and fragments loading. In this paper, the corrugated core sandwich panels with and without aluminum foam fillers were designed, fabricated and finally tested under combined blast loading. Main attention focused on the influence of stand-off distance, foam filler density and core configuration on the dynamic responses in terms of deformation modes and failure mechanisms. The perforation failure of target panels could be alleviated with the increase of stand-off distance. The increase of foam filler density hardly affected the deformation/failure modes of panels, but it could reduce the permanent deformation of core webs and front face sheet. Relative to unfilled sandwich panels, foam filling behavior is an effective way to relieve the debonding failure between face sheet and core webs. Overall, the performance of foam-filled sandwich panels under combined blast loading is mediocre. The failure mode of foam-filled sandwich panels would transform from localized plastic deformation mode under bare blast loading to catastrophic failure under combined blast loading. [ABSTRACT FROM AUTHOR]

Individuals may engage in immoral behavior to achieve the ends they desire. Two studies (total N = 1257) investigated whether the impact of such goal-directed immoral behavior on self-perceived authenticity would vary according to different goal states. Study 1 employed an experimental task whereas Study 2 surveyed participants on their personal goal pursuit. In both studies, we found that the association between immoral behavior and self-perceived authenticity was stronger after than prior to goal completion. Our findings corroborate the goal competition perspective on authenticity, and suggest avenues for future research on state authenticity and the dynamic consequences of immoral behavior. [ABSTRACT FROM AUTHOR]

Management of diabetic wounds becomes increasingly challenging as bacterial infections intensify the inflammation. Employing polysaccharide hydrogels with inherent antibacterial qualities can significantly reduce the need for antibiotics to manage infections in diabetic wounds. The typical approach to achieving antibacterial outcomes with hydrogels relies on the penetration of bacteria into their porous architecture. Such penetration not only takes time but can also prolong inflammation, thus impeding the healing of wounds. Hence, the quick capture and eradication of bacteria are essential for optimizing the hydrogel's antibacterial performance. Herein, we introduce a multifunctional polysaccharide hydrogel dressing—designated as HAQ—created for managing bacterial infections in diabetic wounds. This dressing is based on hyaluronic acid, which is modified with methacrylic anhydride, and special functional groups are added to the modified hyaluronic acid matrix: phenylboronic acid for capturing bacteria and quaternary ammonium chitosan for bacterial destruction. As expected, the HAQ system exhibits robust antibacterial effectiveness against both methicillin-resistant Staphylococcus aureus and multidrug-resistant Pseudomonas aeruginosa in vitro and in vivo. Consequently, HAQ stands as a promising hydrogel dressing with intrinsic antibacterial capabilities and offers significant potential for managing diabetic wounds infected by drug-resistant bacteria. • A polysaccharide hydrogel (HAQ) had been formulated to address bacterial infections in diabetic wounds. • HAQ was composed of quaternized chitosan, 3-(acrylamido)phenylboronic acid, and methacrylated hyaluronic acid. • HAQ demonstrated strong capabilities in capturing and eliminating bacteria. • HAQ significantly accelerated the healing of bacteria-infected diabetic wounds. [ABSTRACT FROM AUTHOR]

• A hydrogel patch (MPG3) with immunomodulatory properties was designed for treating oral ulcers. • MPG3 was synthesized by incorporating platinum-decorated melanin nanoparticles into a modified gelatin matrix. • MPG3 demonstrated robust adhesive capabilities and excelled in anti-inflammatory performance. • MPG3 facilitated oral ulcer healing by reshaping the wound immune microenvironment. Oral ulcers may be addressed with various biomaterials infused with medications or cytokines. However, many patients derive little advantage from these substances due to inadequate adhesion, brief retention in the mouth, and diminished drug effectiveness. Here, we introduce a hydrogel patch (MPG3) consisting of a biopolymer matrix with light-activated adhesion features infused with platinum-decorated melanin nanoparticles that possess healing-promoting abilities. Initially, through straightforward local application, an adhesive hydrogel barrier forms over mucosal imperfections upon exposure to ultraviolet light. Following this, MPG3 exhibits outstanding oxygen production and reactive oxygen species elimination properties. These capabilities contribute to regulating the wound microenvironment, thereby expediting the wound's transition from the inflammatory to the proliferative stage. In rat models of oral ulcers, the MPG3 patch hastens recovery by modulating the inflammatory milieu of the damaged tissue and fostering expedited re-epithelialization and blood vessel formation. Conclusively, this light-activated adhesive hydrogel shows promise for swift wound healing and could revolutionize therapeutic approaches for treating clinical oral ulcers, especially in diabetic patients. [ABSTRACT FROM AUTHOR]

• An immunomodulatory hydrogel (Ga/GA) was developed for treating bacteria-infected pressure ulcers; • Ga/GA consisted of glycyrrhizic acid (GA) that self-assembled under the influence of gallium (Ga) ions; • Ga/GA successfully reduced the M1/M2 macrophage balance under inflamed scenarios; • Ga/GA notably hastened the recovery of pressure ulcer wounds with bacterial infections. Current approaches to treating infected pressure ulcers (IPUs) tend to lack specificity. Such injuries frequently exhibit extended inflammation and slow tissue regeneration, largely due to a surplus of M1 macrophages in the impacted regions. While immunomodulatory hydrogels offer potential for targeted IPU care, facilitating a safe and efficient shift from M1 to M2 macrophages continues to be a considerable challenge. The wound's harsh microenvironment—marked by unchecked infections and reactive oxygen species—often undermines the effectiveness of these hydrogels. We unveil a custom-engineered hydrogel dressing specifically designed to have immunomodulatory properties for expediting the healing of IPUs. Consisting of intertwined polymer networks, this hydrogel incorporates gallium (Ga) ions-triggered self-assembled glycyrrhizic acid (GA). Crucially, both in vitro and in vivo examinations, along with RNA sequencing assessments, demonstrate that the Ga/GA combination successfully reduces the M1/M2 macrophage ratio under inflamed circumstances, thereby contributing to improved IPU wound recovery. In summary, our proposed immunomodulatory strategy provides a simple, secure, and highly efficacious method for managing IPUs. [ABSTRACT FROM AUTHOR]

Customer baseline load (CBL) estimation is very important in demand response (DR) program. Due to the increasing installation of distributed photovoltaic system (DPVS), the load patterns of residential customers become more complex and random. The actual load power of the customer is coupled with the DPVS output power, which makes it more difficult to estimate CBL. Since the electricity meter can only measure the net load data, this article proposes a PV-load decoupling approach to improve the CBL estimation accuracy in the presence of DPVS. CBL is the difference between actual load power and DPVS output power, so the CBL estimate is converted into two sub-problems: the estimation of actual load power and the estimation of DPVS output power. First, the actual load power of DR customers is estimated based on the load power of the control group customers. Then, the DPVS output during DR period is obtained based on the DPVS output estimation model. Finally, CBL is estimated based on the actual load power and DPVS output power. In order to verify the effectiveness and feasibility of the approach, two real datasets from Sydney and Austin are used to simulate the CBL estimation. Compared with the net load directly estimating the CBL, the comparison results indicate that the proposed method shows better accuracy performance. [ABSTRACT FROM AUTHOR]

Household characteristics play an important role in helping utilities carry out efficient and personalized services. Current methods to obtain such information, e.g., surveys, are usually costly and time-consuming. The widespread installation of smart meters enables the collection of fine-grained residential electricity consumption data and thus, making the identification of household characteristics from smart meter data possible. This article proposes a time–frequency feature combination based household characteristic identification approach using smart meter data. First, in addition to conventional time-domain statistical features, several frequency-domain features are extracted using discrete wavelet transform. Second, the random forest algorithm is used to select a subset of important features and remove redundant information contained in the original feature set. Third, a support vector machine is used as a classifier with the input of the selected features to infer the household characteristics. Finally, case study using the realistic data from Ireland indicates that the proposed approach shows better performance after incorporating the frequency-domain features. [ABSTRACT FROM AUTHOR]

The technological advancement in the communication and control infrastructure helps those smart households (SHs) that more actively participate in the incentive-based demand response (IBDR) programs. As the agent facilitating the SHs’ participation in the IBDR program, load aggregators (LAs) need to comprehend the available SHs’ demand response (DR) capacity before trading in the day-ahead market. However, there are few studies that forecast the available aggregated DR capacity from LAs’ perspective. Therefore, this article proposes a forecasting model aiming to aid LAs forecast the available aggregated SHs’ DR capacity in the day-ahead market. First, a home energy management system is implemented to perform optimal scheduling for SHs and to model the customers’ responsive behavior in the IBDR program; second, a customer baseline load estimation method is applied to quantify the SHs’ aggregated DR capacity during DR days; third, several features which may have significant impacts on the aggregated DR capacity are extracted and they are processed by principal component analysis; and finally, a support vector machine based forecasting model is proposed to forecast the aggregated SHs’ DR capacity in the day-ahead market. The case study indicates that the proposed forecasting framework could provide good performance in terms of stability and accuracy. [ABSTRACT FROM AUTHOR]

• A Summary of inorganic–organic nanomaterials for photothermal antibacterial therapy. • Common strategies for the construction of inorganic–organic nanomaterials. • Properties of inorganic–organic nanomaterials and photothermal antibacterial mechanisms. • Improvements in photothermal antibacterial therapy. The clinical management of bacterial infections has become a growing global public health challenge. Such therapy is presently limited to antibiotics, but the misuse of antibiotics has led to multi-drug resistance and high mortality rates in anti-infective treatment. Therefore, it is critical to develop alternative biocides to open up new avenues of disinfection. Photothermal therapy (PTT), which usually kills bacteria by hyperthermia produced by photothermal agents (PTAs) under laser irradiation, has sparked increasing concern due to its low invasiveness, deep penetration, high selectivity, and avoidance of drug-resistant bacteria. Inorganic–organic hybrid nanomaterials that merge inorganic and organic elements can integrate the distinctive advantages of both while mitigating their innate shortcomings, displaying tremendous potential in the field of PTT antibacterial. In this review, we first briefly describe various strategies for fabricating functional inorganic–organic nanohybrid PTAs. Subsequently, the properties of the nanohybrid PTAs are discussed, covering characteristics from inorganic and organic parts, synergistic features, morphology dependence, and self-assembly of the nanohybrids. After that, the current status of nanohybrids for PTT antibacterial is demonstrated. Finally, we summarize and discuss some key issues, current challenges, and future developments in the rational synthesis of inorganic–organic nanohybrid PTAs for photothermal antibacterial therapy. [ABSTRACT FROM AUTHOR]

This paper presents an experimental investigation into the dynamic response and microstructure evolution of titanium alloy plates subjected to low-velocity impact load. The impact experiments with different impact energies were designed and conducted. The effects of impact energy on the impact response curves and the interested impact resistance were analyzed. The macro deformation/failure mechanisms were examined by using digital microscope. The microstructure evolution induced by the variation of impact energy was further elaborated via scanning electron microscope (SEM) and electron backscatter diffraction (EBSD) technique. On the basis of same impact condition, the impact behaviors of titanium alloy specimens were compared with the ones of woven carbon fiber reinforced composite laminates (CFRP) with the same areal density. The results show that the impact response of titanium alloy specimens is mainly characterized with linear loading stage, nonlinear loading stage and unloading stage. Linear relationships of peak impact force, maximum impactor displacement and absorbed energy with impact energy are found. The increase of impact energy will increase the content of α phase due to the difference in plastic deformation resistance of microstructures. Different impact behaviors appeared for titanium alloy specimens and CFRP specimens. CFRP specimens exhibited superior impact resistance with lower peak impact force and higher energy absorption relative to titanium alloy specimens. • Dynamic response of titanium alloy plates under different impact energies is studied. • Microstructure morphology and fractography of post-test specimens are examined. • Deformation/failure mechanisms underling the microstructure evolution are revealed. • Sufficient comparison between titanium alloy plates and CFRP laminates is performed. [ABSTRACT FROM AUTHOR]

• Materialism is positively associated with self-interest-triggered moral flexibility. • Materialists judged immoral acts done by the self and others more differentially. • Materialists' preference for moral rules is more contingent on their self-interest. This research examined the association between materialism and self-interest-triggered moral flexibility, the tendency to change moral judgments based on self-interest. Individuals high on materialism reported a greater discrepancy in the moral judgments of their own and others' behavior (Study 1), and showed a relatively more negative attitude towards fairness when being fair hindered rather than served their self-interests (Study 2). Studies 3 and 4 (both pre-registered) showed that when faced with moral conflict (equity vs equality in Study 3, and ingroup favoritism vs fairness in Study 4), materialism amplified the tendency to judge the moral values that served (vs interfered with) one's self-interest as more moral. Implications of these findings for the understanding of how materialists approach morality were discussed. [ABSTRACT FROM AUTHOR]

Summary The elaboration of nascent synaptic connections into highly ordered neural circuits is an integral feature of the developing vertebrate nervous system. In sensory systems, patterned spontaneous activity before the onset of sensation is thought to influence this process, but this conclusion remains controversial, largely due to the inherent difficulty recording neural activity in early development. Here, we describe genetic and pharmacological manipulations of spontaneous retinal activity, assayed in vivo, that demonstrate a causal link between retinal waves and visual circuit refinement. We also report a decoupling of downstream activity in retinorecipient regions of the developing brain after retinal wave disruption. Significantly, we show that the spatiotemporal characteristics of retinal waves affect the development of specific visual circuits. These results conclusively establish retinal waves as necessary and instructive for circuit refinement in the developing nervous system and reveal how neural circuits adjust to altered patterns of activity prior to experience. [ABSTRACT FROM AUTHOR]