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The two-dimensional quantum dots (2D-QDs) have been developed significantly in the past decades. The 2D-QDs could be used in bioimaging, biosensing, drug/gene delivery, and photodynamic/photothermal therapy. The potential applications in biology receive increasing attention, which makes them the novel and emerging candidates in biomaterial research fields. In this context, we discuss a variety of 2D-QDs with different physical and chemical properties. We focuse on the latest synthesis progress and recent applications in biotechnological, and biomedical applications of the 2D-QDs and we also evaluate the challenges and prospects in this field.

With the rapid advancement of artificial intelligence, machine learning and big data analytics have become essential tools for enhancing the cybersecurity of power monitoring systems. This study proposes a network traffic anomaly detection model based on Convolutional Long Short-Term Memory (C-LSTM) networks, which integrates convolutional layers to capture spatial features and LSTM layers to model long-term temporal dependencies in network traffic. Incorporated into a cybersecurity situation awareness platform, the model enables comprehensive data collection, intelligent analysis, and rapid response to cybersecurity incidents, significantly enhancing the system’s ability to detect, warn, and mitigate potential threats. Experimental evaluations on the CICIDS2017 dataset demonstrate that the proposed model achieves high accuracy (95.3%) and recall (94.7%), highlighting its effectiveness and potential for practical application in safeguarding critical infrastructure against evolving cybersecurity challenges.

Carbon and iron composites have drawn much attention for their unique electromagnetic properties. In addition, nitrogen doping of carbon can effectively modulate the dielectric properties of carbon. Therefore, synthesis of N-doped carbon and iron composites is an alternative method for obtaining high-efficiency microwave absorption materials. In previous studies, the synthesis process was very complicated including multistep routes. In this work, N-doped carbon with embedded Fe/Fe3C was synthesized in-situ via pyrolysis of amino phenol formaldehyde resin (APF) scattered with Fe2O3 nanoparticles (APF/Fe2O3), which was obtained through a simple hydrothermal process. During the heat-treatment process, the APF resin was converted into N-doped carbon, and simultaneously, the Fe2O3 was reduced to iron nanoparticles. Then, inevitably, the iron nanoparticles reacted with carbon to form Fe3C at the interface between the iron particles and carbon. Taking advantage of multiple heterogenous interface, the interfacial polarization relaxation could be enhanced. Therefore, the N-doped carbon with embedded Fe/Fe3C particles displays microwave absorption with a maximum reflection loss of − 70 dB. Moreover, the effective absorption bandwidth (reflection loss of less than − 10 dB) reaches 6.02 GHz at a thickness of 2.13 mm. This study not only provides composites of N-doped carbon with embedded Fe/Fe3C particles with excellent stable microwave absorption but also offers a simple method for synthesizing N-doped carbon with embedded Fe/Fe3C particles.

Windows are the least energy efficient part of the buildings, as building accounts for 40% of global energy consumption. Traditional smart windows can only regulate solar transmission, while all the solar energy on the window is wasted. Here, for the first time, the authors demonstrate an energy saving and energy generation integrated smart window (ESEG smart window) in a simple way by combining louver structure solar cell, thermotropic hydrogel, and indium tin oxides (ITO) glass. The ESEG smart window can achieve excellent optical properties with ≈90% luminous transmission and ≈54% solar modulation, which endows excellent energy saving performance. The outstanding photoelectric conversion efficiency (18.24%) of silicon solar cells with louver structure gives the smart window excellent energy generation ability, which is more than 100% higher than previously reported energy generation smart window. In addition, the solar cell can provide electricity to for ITO glass to turn the transmittance of hydrogel actively, as well as the effect of antifreezing. This work offers an insight into the design and preparation together with a disruptive strategy of easy fabrication, good uniformity, and scalability, which opens a new avenue to realize energy storage, energy saving, active control, and antifreezing integration in one device. The authors develop a revolutionary smart window with a multi‐layer louver structure, containing a silicon solar cell, thermotropic hydrogel, and ITO active layer, which combine both an energy saving and energy generation ability (ESEG smart window) with leverages high solar energy modulation together with high photoelectric conversion efficiency (PCE).

Background Osteoporosis is a very common bone disease in the elderly population and can lead to fractures and disability. Malnutrition can lead to osteoporosis. The geriatric nutritional risk index (GNRI) is a tool used to assess the risk of malnutrition and complications associated with nutritional status in older patients and is a crucial predictor of many diseases. Hence, this study investigated the association between the GNRI and the presence of osteoporosis and assessed the value of this index for predicting osteoporosis in patients with type 2 diabetes mellitus (T2DM). Methods This cross-sectional study enrolled 610 elderly patients with T2DM. General and laboratory data of the patients were collected, along with their measurements of bone mineral density (BMD). The GNRI was calculated based on ideal body weight and serum albumin (ABL) levels. Correlation analysis was performed to determine the relationship between the GNRI and BMD and bone metabolism indices. The GNRI predictive value for osteoporosis development was analyzed through logistic regression analysis and by creating a receiver operating characteristic curve (ROC), calculating the area under the curve (AUC). Results All patients were divided into the no-nutritional risk and nutritional risk groups. Compared with the no-nutritional risk group, the nutritional risk group had a longer diabetes course, older age, higher HbA1c levels, higher prevalence of osteoporosis; lower BMI, ABL,triglyceride (TG),Calcium (Ca),25-hydroxy-vitamin-D(25(OH)D),and parathyroid hormone(PTH) and lower femoral neck BMD,total hip BMD ( P  < 0.05). All patients were also assigned to the non-osteoporosis and osteoporosis groups. The non-osteoporosis group had higher GNRI values than the osteoporosis group ( P  < 0.05). Correlation analysis revealed a positive correlation between the GNRI and lumbar BMD, femoral neck BMD, and total hip BMD ( P  < 0.05). After the adjustment for confounding factors, Spearman’s correlation analysis revealed that the GNRI was positively correlated with Ca, 25(OH)D, and PTH and negatively correlated with alkaline phosphatase (ALP) and procollagen of type-1 N-propeptide (P1NP). Regression analysis exhibited that the GNRI was significantly associated with osteoporosis. The ROC curve analysis was performed using the GNRI as the test variable and the presence of osteoporosis as the status variable. This analysis yielded an AUC for the GNRI of 0.695 and was statistically significant ( P  < 0.05). Conclusions A lower GNRI among T2DM patients in northern China is associated with a higher prevalence of osteoporosis.

Iron-chromium flow batteries (ICRFBs) have emerged as an ideal large-scale energy storage device with broad application prospects in recent years. Enhancement of the Cr3+/Cr2+ redox reaction activity and inhibition of the hydrogen evolution side reaction (HER) are essential for the development of ICRFBs and require a novel catalyst design. However, elucidating the underlying mechanisms for modulating catalyst behaviors remains an unresolved challenge. Here, we show a novel precisely controlled preparation of a novel thermal-treated carbon cloth electrode with a uniform deposit of low-cost indium catalyst particles. The density functional theory analysis reveals the In catalyst has a significant adsorption effect on the reactants and improves the redox reaction activity of Cr3+/Cr2+. Moreover, H+ is more easily absorbed on the surface of the catalyst with a high migration energy barrier, thereby inhibiting the occurrence of HER. The assembled ICRFBs have an average energy efficiency of 83.91% at 140 mA cm−2, and this method minimizes the electrodeposition process and cleans the last obstacle for industry long cycle operation requirements. The ICRFBs exhibit exceptional long-term stability with an energy efficiency decay rate of 0.011% per cycle at 1000 cycles, the lowest ICRFBs reported so far. Therefore, this study provides a promising strategy for developing ICRFBs with low costs and long cycle life. Schematic diagram of the ICRFBs and the fabrication of the electrode. [Display omitted] •A novel thermal-treated carbon cloth electrode with a uniform deposit of low-cost indium catalyst particles.•DFT simulation explains the mechanism of In catalysts to enhance Cr3+/Cr2+ reaction activity and inhibit HER.•We successfully demonstrated the scale-up from laboratory-level experiments to a kW-scale stack.

Iron–chromium redox flow batteries (ICRFB) possess the advantage of low raw material cost, intrinsic safety, long charge–discharge cycle life, good life-cycle economy, and environmental friendliness, which has attracted attention from academia and industry over time. The proton exchange membrane (PEM) is an important part of the ICRFB system, impacting the efficiency and lifetime of the battery. Currently, the most widely used PEMs in the market are per-fluorinated sulfonic acid (PFSA) membranes, which possess high electrolyte stability and achieve the separation of positive and negative electrolytes. In addition, the complex preparation process and extremely high market price limited the usage of PEM in ICRFB. In this paper, we developed a remanufactured membrane (RM) strategy from waste PFSA resins. The RM has higher electrical conductivity and better proton transport ability than the commodity membrane N212. In the cell performance test, the RM exhibits similar coulombic efficiency (CE) as N212 at different current densities, which is stabilized at over 95%. Furthermore, the voltage efficiency (VE) and energy efficiency (EE) of the RM are improved compared to N212. At a current strength of 140 mA cm−2, the degree of energy loss is lower in the RM, and after 60 cycles, the capacity decay rate is lower by only 16.66%, leading to long-term battery life. It is a cost-effective method for membrane recovery and reformulation, which is suitable for large-scale application of ICRFB in the future.

Iron‐chromium redox flow batteries (ICRFBs) show promise for large‐scale energy storage, but their performance is hindered by the hydrogen evolution reaction (HER) and sluggish anode Cr3⁺/Cr2⁺ redox kinetics. Here, an octahedral In2O3 catalyst with exposed high‐activity (222) crystal planes is reported, synthesized via high‐temperature solution thermal decomposition and grown in situ on carbon cloth. The catalyst is grown in situ on carbon cloth to form a nanostructured indium‐based electrode (In2O3‐TCC). Grazing incidence wide‐angle X‐ray scattering confirms In2O3 phase formation, while XANES reveals abundant oxygen vacancies (Ov) serving as anode reaction active sites. In2O3‐TCC exhibits enhanced electrochemical properties, including a tripled double‐layer capacitance (8.92 mF cm−2), a reduced charge transfer resistance (1.042 Ω), and improved Cr3⁺/Cr2⁺ kinetics. Density functional theory (DFT) shows that anode HER suppression arises from favorable H⁺ adsorption energy and a high desorption barrier. Furthermore, an in situ differential electrochemical mass spectrometer (DEMS) confirms effective anode HER suppression. The electrode achieves an energy efficiency of 84.02% at 140 mA cm−2 and stable performance over 500 cycles. This work offers a new pathway for designing high‐efficiency, long‐lifetime ICRFB electrodes. The electrode modified with octahedral indium oxide catalyst with exposed high activity (222) crystal plane can suppress the hydrogen evolution side reaction and improve the reaction kinetics of chromium of iron‐chromium flow batteries. The battery exhibits extremely high energy efficiency of 84.02% at an ultra‐high current density of 140 mA·cm−2.

Carbon dots (CDs), a new zero-dimensional material, have ignited a revolution in the fields of sensing, bioimaging, and biomedicine. However, the difficulty of preparing CDs with Fenton-like catalytic properties has seriously hindered their application in the diagnosis of oxidation/reduction biomolecules or metal ions. Here, an innovative method was successfully established to synthesize Mn 3+ /Mn 4+ ion-doped blue-green fluorescent CDs with Fenton-like catalytic properties using manganese acetate as the manganese source. Specifically, the CDs prepared here were equipped with functional groups of -COOH, NH 2 , C=O, and Mn-O, offering the possibility to function as a fluorescence sensor. More importantly, the introduction of manganese acetate resulted in the preparation of CDs with Fenton-like catalytic properties, and the dual-signal fluorescence detection of dopamine (DA) was realized with linear ranges of 100–275 nM and 325–525 nM, and the detection limits were 3 and 12 nM, respectively. In addition, due to the Fenton-like catalytic activity of Mn 3+ /Mn 4+ ion-doped CDs, the material has broad application prospects in the detection of oxidation/reduction biomolecules or metal ions related to disease diagnosis and prevention.

3D visual grounding is crucial for understanding cross-modal scenes, linking visual objects to their corresponding language descriptions. Traditional methods often use fixed attention patterns in visual encoders, limiting the utility of language-guided attention mechanisms. To address this, we introduce a novel language-guided visual context modeling (LGVC) strategy. Our approach enriches the visual encoding at multiple levels through language knowledge: (1) A Language-Object Embedding (LOE) Module directs attention toward language-relevant proposals in 3D visual scenes, and (2) a Language-Relation Embedding (LRE) Module explores the relationships among objects in the context of accompanying text. Extensive experiments show that LGVC efficiently filters out language-irrelevant proposals and aligns multimodal entities, outperforming state-of-the-art methods.