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In this article, automatic machine learning (ML) technology and global optimization algorithms have been combined to achieve a fast and high-performance extended interaction oscillator (EIO) design. An EIO model is manually designed to give a comparison. The manually designed EIO model can predict an output power of 7.9 kW with an efficiency of 15.8%. The data to train ML models are generated with CST-MATLAB co-simulation. During dataset creation, some EIO models are derived from high-output-power models by changing voltage and current parameters. By adding these derived models into dataset, power gradients over current and voltage are decreased. This is the key to the success of the whole project. Particle swarm optimization (PSO) and genetic algorithm (GA) are tested and compared to achieve the EIO fast design. PSO algorithm performs better than GA for relatively fixed searching directions and less randomness. An EIO optimized by PSO can predict an output power of 11.9 kW. The EIO electronic efficiency is 19.3%, which is 3.5% higher than that of the manually designed oscillator.

This article investigates machine learning (ML) security, focusing on threats and attacks against ML. We have created a threat model for ML to illustrate the threat actors involved. We present a new approach to classify threats and attacks targeting ML.

The decoupled-type triple active bridge converter (DTAB) offers improved power density and power-decoupling features by removing an auxiliary inductance from one port. However, traditional phase-shift modulation schemes fail to extend the zero-voltage-switching (ZVS) range, limiting efficiency and practical application. To broaden the ZVS range of DTAB converters, in this paper, a streamlined quadruple phase-shift (QPS) modulation scheme, evolved form the volt–sec-balance principle in dual active bridge (DAB) converters, is proposed to achieve ZVS operation in the two ports maintained with the auxiliary inductance. To avoid increasing computational burden, the influence of magnetizing inductance is considered for the ZVS operation in the inductance-canceled port, whose optimal design is analyzed, particularly suitable for DTAB converters. Consequently, this software–hardware-integrated strategy offers computational efficiency, particularly advantageous for time-intensive scenarios such as electric vehicle (EV) charging system. Additionally, to simplify the ZVS analysis, a unified ZVS model of DTAB converters based on the complete circuit response equation is introduced, obviating the need for complex mode-dependent ZVS analysis and also applicable to TAB converters. Finally, the efficacy of the proposed strategy is validated in a 3.3 kW/100 kHz SiC-based DTAB prototype, tailored to the EV a plications, achieving peak efficiency of 95% at partial load conditions.

Zinc complexation forms hydrophobic protective layers inhibiting dendrite growth and hydrogen evolution, ensuring stable zinc metal anodes in aqueous batteries.

Aim: To systematically review the current status of strategies and barriers to implementing guidelines in China to promote the better application of guidelines in clinical practice. Methods: We searched CNKI, CBM, WanFang, PubMed, Embase, and WOS up to October 2022. Our reviewers performed literature screening, data extraction, and quality assessment in duplicate. Potential barriers and strategies were mapped based on evidence, target population, organizations, and resource and environment. Results: We included 16 surveys involving a total of 7147 health care providers. Two third of included surveys were moderate to high quality. Thirty-one barriers were grouped into four categories, including evidence, target population, organization, and resources and environment. Lack of applicability, ambiguous recommendations, and less convenient were the main evidence-related barrier factors. The top three barriers related to the target population included the lack of awareness, language barriers, and patients’ attitude toward healthcare workers. The most common organization-related barriers were insufficient publicity and insufficient training/education. Lack of resources and non-applicability to primary hospitals were factors hindering the implementation of guidelines at the level of resources and environment. Establishing a national guideline database and involving primary care physicians in the guideline development process were considered by many respondents to be effective strategies for promoting guideline implementation. Conclusions: In China, implementing guidelines is hindered mainly by lack of applicability, ambiguous recommendation, and lack of education. The solution might be establishing multidisciplinary collaborative teams, building a national guideline clearinghouse, and increasing education and training.

In order to address the limitation of fixed-ratio transmission (FRT), which compromises the attainment of both optimal main rotor speed and optimal power turbine speed, an optimal speed control method based on hybrid variable speed (HVS) is proposed. Firstly, based on the integrated performance calculation model of helicopter/turboshaft engine system, the distribution factors of variable speed are applied, and the integrated optimization method of optimal speed is proposed based on the minimum engine fuel flow. Subsequently, an online estimation technique employing a high-order filter is devised and engineered to achieve superior cascaded control of turboshaft engines. Finally, a novel real-time optimal speed control method based on hybrid variable speed is proposed. The simulation results under different operation conditions demonstrate that regardless of whether it is FRT or HVS, the optimal main rotor speed increases with forward velocity. In the case of HVS, turboshaft engine degradations have a significant impact on the optimal power turbine speed rather than optimal main rotor speed. Adopting an estimation method based on high-order filtering for gas turbine rotational acceleration proves more advantageous in mitigating high-frequency oscillation and continuous saltation of estimated values. Moreover, in comparison with the optimal speed control method of FRT, HVS-based approach enables simultaneous attainment of the optimal main rotor speed and power turbine speed, thereby enhancing the overall efficiency of the integrated helicopter/turboshaft engine system and significantly decreasing engine fuel consumption by over 2%. Consequently, there has been a remarkable enhancement in the overall performance of the integrated helicopter/turboshaft engine system.

A wet chemical method deposits an amorphous aluminum phosphate layer on P2-type Na0.55Ni0.1Co0.1Mn0.8O2, contributing to enhanced performance. This study reveals insights into phase stability and diffusion kinetics of coated electrode.

• A flexible multilayered piezoresistive sensor based on cMOF/LDH is fabricated. • The sensor has a dendritic nanostructure and a compressible internal structure. • The piezoresistive sensor exhibits high sensitivity and a broad detection range. • Wearable sensors can be used for human motion monitoring and sound detection. • The sensor is demonstrated to detect the concentration of NH 3 and sunlight intensity. Highly sensitive sensors with extensive applications are extremely desired in the next-generation wearable electronics for human motion monitoring, human-machine interface and intelligent robotics, while single-functional pressure sensors cannot fulfill the growing demands of modern technological advances. Herein, an all-fabric and multilayered piezoresistive sensor based on conductive metal-organic framework/layered double hydroxide (cMOF/LDH) hetero-nanoforest is demonstrated to achieve multiple applications including pulse detection, joint motion detection, sound detection and information transmission. Benefiting from the synergism of cMOF/LDH hetero-nanoforest and multilayered structure, the sensor exhibits a high sensitivity (1.61 × 109 kPa−1) over a broad pressure range (0–100 kPa), a fast response/recovery time (71 ms/71 ms) and a low detection limit (18 Pa), as well as reliable dynamic stability (8000 cycles). It is gratifying to note that the introduction of cMOFs endows the sensor with the potential to detect the concentration of NH 3 (1–100 ppm) and sunlight intensity (10–100 mW cm−2). This work shows great potential in multifunctional sensing, which enlightens a strategy for advancing the development process of highly sensitive intelligent wearable devices. [Display omitted] [ABSTRACT FROM AUTHOR]

Rational regulation of the electrochemical CO2reduction reaction (CO2RR) pathway to produce desired products is particularly interesting, yet designing economical and robust catalysts is crucial. Here, we report an antimony-modified copper (CuSb) catalyst capable of selectively producing both CO and multicarbon (C2+) products in the CO2RR. At a current density of 0.3 A/cm2, the faradaic efficiency (FE) of CO was as high as 98.2% with a potential of −0.6 V vs reversible hydrogen electrode (RHE). When the current density increased to 1.1 A/cm2at −1.1 V vs RHE, the primary products shifted to C2+compounds with a FE of 75.6%. Experimental and theoretical studies indicate that tuning the potential could manipulate the oxygen species on the CuSb surface, which determined the product selectivity in the CO2RR. At a more positive potential, the existence of oxygen species facilitates the potential-limiting step involving *COOH formation and reduces the adsorption of *CO intermediates, thereby promoting CO production. At a more negative potential, the localized high CO concentration coupled with the enhanced adsorption of *CO intermediates due to Sb incorporation facilitates C–C coupling and deep hydrogenation processes, resulting in an increased C2+selectivity.

Conductive hydrogels exhibit tremendous potential for wearable bioelectronics, biosensing, and health monitoring applications, yet concurrently enhancing their biocompatibility and antimicrobial properties remains a long-standing challenge. Herein, we report an all-natural conductive supramolecular hydrogel (GT5-DACD2-B) prepared via the Schiff base reaction between the biofriendly dialdehyde cyclodextrin and gelatin. The potent antibacterial agent fusidic acid (FA) is incorporated through host–guest inclusion, enabling 100% inhibition of Staphylococcus aureusproliferation. The biocompatibility of our hydrogel is bolstered with tannic acid (TA) facilitating antibacterial effects through interactions with gelatin, while borax augments conductivity. This supramolecular hydrogel not only exhibits stable conductivity and rapid response characteristics but also functions as a flexible sensor for monitoring human movement, facial expressions, and speech recognition. Innovatively integrating biocompatibility, antimicrobial activity, and conductivity into a single system, our work pioneers a paradigm for developing multifunctional biosensors with integrated antibacterial functionalities, paving the way for advanced wearable bioelectronics with enhanced safety and multifunctionality.

Metal-oxo clusters show great promise in lithium ion battery applications as anode materials by virtue of their native nature of well-defined nanostructures and multielectron redox activities. However, their intrinsic unsatisfactory electrical conductivity and tendency to aggregation make them difficult to fully utilize. Herein, a well-dispersed Mn12O12(CH3COO)16(H2O)4(denoted as Mn12) cluster is constructed by rationally adopting carbon dots (CDs) with nanosize and high conductivity as stabilizers. Thanks to the fully exposed redox sites of Mn12clusters and additional interfacial energy storage mechanism, the optimized Mn12/CDs-1:20 anode delivers a high specific capacity of 1643 mAh g–1at 0.2 A g–1(0.25 C) and exhibits outstanding rate and cycling capabilities. This paper provides a green and efficient paradigm to synthesize well-dispersed manganese-oxo clusters for the first time and builds a new platform for cluster-based energy storage.

Reperfusion injury represents a significant impediment to recovery after recanalization in an ischemic stroke and can be alleviated by neuroprotectants. However, inadequate drug delivery to ischemic lesions impairs the therapeutic effects of neuroprotectants. To address this issue, an ischemic microenvironment-targeted bioinspired lipoprotein system encapsulating lipoic acid (LA@PHDL) is herein designed to sequentially penetrate ischemic lesions and be readily taken up by neurons and microglia. In transient middle cerebral artery occlusion (tMCAO) mouse models, LA@PHDL accumulates rapidly and preferentially in the ischemic brain, with a 2.29-fold higher than the nontargeted nanoplatform in the early stage. Furthermore, LA@PHDL effectively restores neurological function, reduces infarct volume to 17.70%, prevents brain cell necrosis and apoptosis, and attenuates inflammation in tMCAO mouse models. This design presents new opportunities for delivering neuroprotectants to cerebral ischemic lesions to improve the outcome of an ischemic stroke.

(±)-Salvicatone A (1), a C27-meroterpenoid featuring a unique 6/6/6/6/6-pentacyclic carbon skeleton with a 7,8,8a,9,10,10a-hexahydropyren-1 (6H)-one motif, was isolated from the roots and rhizomes of Salvia castaneaDiels f. tomentosaStib. Its structure was characterized by comprehensive spectroscopic analyses along with computer-assisted structure elucidation, including ACD/structure elucidator and quantum chemical calculations with 1H/13C NMR and electronic circular dichroism. Biogenetically, compound 1was constructed from decarboxylation following [4 + 2] Diels–Alder cycloaddition reaction between caffeic acid and miltirone analogue. Bioassays showed that (−)-1and (+)-1inhibited nitric oxide production in lipopolysaccharide-induced RAW264.7 macrophage cells with an IC50value of 6.48 ± 1.25 and 15.76 ± 5.55 μM, respectively. The structure-based virtual screening based on the pharmacophores in ePharmaLib, as well as the molecular docking and molecular dynamics simulations study, implied that (−)-1and (+)-1may potentially bind to retinoic acid receptor-related orphan receptor C to exert anti-inflammatory activities.

Conductive nanofiltration (CNF) membranes hold great promise for removing small organic pollutants from water through enhanced Donnan exclusion and electrocatalytic degradation. However, current CNF membranes face limitations in conductivity, structural stability, and nanochannel control strategies. This work addresses these challenges by introducing aniline-functionalized carbon nanotubes (NH2-CNTs) as an interlayer. NH2-CNTs enhance the dispersibility and adhesion of pristine carbon nanotubes, leading to a more conductive and stable composite nanofiltration membrane. The redesigned NH2-CNTs interlayered conductive nanofiltration (NICNF) membrane exhibits a 10-fold increase in conductivity and a high response degree (80%) with excellent cyclic stability, surpassing existing CNF membranes. The synergistic effects of enhanced Donnan exclusion, voltage switching, and electrocatalysis enable the NICNF membrane to achieve selective recovery of mixed dyes, 98.97% removal of residual wastewater toxicity, and a 5.2-fold increase in permeance compared to the commercial NF270 membrane. This research paves the way for next-generation multifunctional membranes capable of the efficient recovery and degradation of toxic organic pollutants in wastewater.

Metabolic reprogramming and cellular senescence greatly contribute to cancer relapse and recurrence. In aging and treated prostate, persistent accumulating senescence-associated secretory phenotype (SASP) of cancer cells often limits the overall survival of patients. Novel strategic therapy with monoacylglycerol lipase (MGLL) upregulation that counters the cellular and docetaxel induced SASP might overcome this clinical challenge in prostate cancer (PCa). With primary comparative expression and survival analysis screening of fatty acid (FA) metabolism signature genes in the TCGA PCa dataset and our single center cohort, MGLL was detected to be downregulated in malignancy prostate tissues and its low expression predicted worse progression-free and overall survival. Functionally, overexpression of MGLL mainly suppresses NF-κB-driven SASP (N-SASP) which mostly restricts the cancer cell paracrine and autocrine tumorigenic manners and the corresponding cellular senescence. Further investigating metabolites, we determined that MGLL constitutive expression prevents lipid accumulation, decreases metabolites preferably, and consequently downregulates ATP levels. Overexpressed MGLL inhibited IκBα phosphorylation, NF-κB p65 phosphorylation, and NF-κB nuclear translocation to deactivate NF-κB transcriptional activities, and be responsible for the repressed N-SASP, partially through reducing ATP levels. Preclinically, combinational treatment with MGLL overexpression and docetaxel chemotherapy dramatically delays tumor progression in mouse models. Taken together, our findings identify MGLL as a switch for lipase-related N-SASP suppression and provide a potential drug candidate for promoting docetaxel efficacy in PCa.

Hybrid nanomaterials with controllable structures and diverting components have attracted significant interest in the functional materials field. Here, we develop a solvent evaporation-induced self-assembly (EISA) strategy to synthesize nanosheet-assembled phosphomolybdic acid (H3PMo)-alumina hybrid hollow spheres. The resulting nanoflowers display a high surface area (up to 697 m2g–1), adjustable diameter, high chemical/thermal stability, and especially molecularly dispersed H3PMo species. By employing various microscopic and spectroscopic techniques, the formation mechanism is elucidated, revealing the simultaneous control of the morphology by heteropoly acids and water through the water-induced Kirkendall effect. The versatility of the synthesis method is demonstrated by varying surfactants, heteropoly acids, and metal oxide precursors for the facile synthesis of hybrid metal oxides. Spherical hybrid alumina serves as an attractive support material for constructing metal–acid bifunctional catalysts owing to its advantageous surface area, acidity, and mesoporous microenvironment. Pt-loaded hollow flowers exhibit excellent catalytic performance and exceptional stability in the hydrodeoxygenation of vanillin with recyclability for up to 10 cycles. This research presents an innovative strategy for the controllable synthesis of hybrid metal oxide nanospheres and hollow nanoflowers, providing a multifunctional platform for diverse applications.

Ferroptosis is a unique type of cell death, characterized by its reliance on iron dependency and lipid peroxidation (LPO). Consequently, small-molecule ferroptosis modulators have garnered substantial interest as a promising avenue for cancer therapy. Herein, we explored the ferroptosis sensitivity of epigenetic modulators and found that the antiproliferative effects of class I histone deacetylase (HDAC) inhibitors are significantly reliant on ferroptosis. Subsequently, we developed a novel series of HDAC inhibitors, identifying HL-5swith robust inhibitory activity against class I HDACs, particularly HDAC1. Notably, HL-5sinduces ferroptosis by augmenting LPO production. Mechanistically, HL-5sincreased the YB-1 acetylation and inhibited the Nrf2/HO-1 signaling pathway. Furthermore, HL-5snot only significantly suppresses tumor growth in the PC-9 xenograft model but also remodels the tumor microenvironment in the LLC allograft model. Our study has unveiled that class I HDAC inhibitors can exert antitumor effects by triggering ferroptosis, and HL-5smay serve as a promising candidate for future cancer treatment.

The synthesis of fluorinated isoquinoline derivatives holds significant value in organic synthesis and medicine. Research into the reaction mechanisms and possible pathways for synthesizing these compounds plays a crucial role in advancing the development and applications of isoquinoline derivatives. Using density functional theory methods, we explored the reaction mechanism and potential pathways of the Rh(III)-catalyzed defluorinative annulation of N-sulfonylarylamides with ethyl 2-diazo-3,3,3-trifluoropropanoates. Theoretical calculations indicate that the reaction initiates with the formation of a metal carbene via C–H activation and denitrogenation, followed by migratory insertion. Subsequent steps involve metal-assisted β-fluoride elimination and anion exchange. Finally, intramolecular cyclization, defluorination, and sulfonyl migration yield isoquinoline products.

Plasmonic nanomaterials such as Au, Ag, and Cu are widely recognized for their strong light–matter interactions, making them promising photothermal materials for solar steam generation. However, their practical use in water evaporation is significantly limited by the trade-off between high costs and poor stability. In this regard, we introduce a novel, nonmetallic dual plasmonic TiN/MoO3–xcomposite. This composite features a three-dimensional, urchin-like biomimetic structure, with plasmonic TiN nanoparticles embedded within a network of plasmonic MoO3–xnanorods. As a solar absorber, the TiN/MoO3–xcomposite achieves a high evaporation rate of ∼2.05 kg m–2h–1with an energy efficiency up to 106.7% under 1 sun illumination, outperforming the state-of-the-art plasmonic systems. The high photothermal stability and unique dual plasmonic nanostructure of the TiN/MoO3–xcomposite are demonstrated by advanced in situlaser-heating transmission electron microscopy and photon-induced near-field electron microscopy/electron energy-loss spectroscopy, respectively. This work provides new inspiration for the design of plasmonic materials.

High-performance polymer foams from engineering plastics are highly desirable in the field of core materials for high-performance composites, especially under high temperature conditions. Here, semicrystalline poly(m-xylylene adipamide) (MXD6-PA) was used to prepare high-performance MXD6-PA/LiCl composite foams by a supercritical carbon dioxide (sc-CO2) foaming technique. LiCl was added to form cross-linking sites via the complexation between LiCl and amide groups of MXD6-PA, which could restrain the cold crystallization process of MXD6-PA melt and mediate the melt behavior of MXD6-PA during the foaming process. As a result, the change in the melt strength of MXD6-PA/LiCl composites remained small during the foaming process; thus, the foamability of the MXD6-PA/LiCl composite was dramatically improved, including a reduced foaming temperature and widened temperature window for the foaming process. The obtained MXD6-PA/LiCl composite foam showed an excellent compressive performance (1.92 MPa, density: ∼115 kg/m3) compared with other engineering plastic foams. Furthermore, the presence of cross-linking sites in the MXD6-PA/LiCl composite increases the glass transition temperature, so the heating resistance performance was dramatically improved. This novel fabrication method presents great potential in the preparation of high-performance foams for meeting the application requirements.

Cuproptosis is an emerging form of cell death that relies on the targeted delivery of copper ions to lipoylated tricarboxylic acid cycle proteins. However, a major challenge associated with cuproptosis is its potential to kill both normal and tumor cells without discrimination. Therefore, it is crucial to develop strategies for precise intracellular delivery and redox control of copper to create effective cuproptosis-based tumor therapies. We have introduced a class of nanoagents called metabolism aiming Cu2–xS (MACuS) through a glucose-mediated biomineralization approach. MACuS nanoagents can be specifically targeted to tumors via the glucose transport receptor 1, and we found that NIR-II irradiation can not only result in direct hyperthermia ablation of tumor cells but also facilitate efficient cuproptosis and enhance reactive oxygen species-induced cytotoxicity in tumor cells. As a result, the triple effect of MACuS treatment induced immunogenic cell death, which triggered systemic antitumor immune responses and demonstrated potent efficacy in inhibiting growth, metastasis, and recurrence in mouse and rabbit breast cancer models. The precise intracellular delivery and redox control of copper provided by MACuS hold great potential for the development of highly efficient cuproptosis-based tumor therapies with minimal off-target effects.

Pickering foams have great potential for applications in aerated foods, but their foaming ability and physical stability are still far from satisfactory. Herein, solid lipid particles (SLNs) were fabricated by using diacylglycerol of varying acyl chain lengths with modification by a protein. The SLNs showed different crystal polymorphisms and air–water interfacial activity. C14-DAG SLN with a contact angle ∼ 79° formed aqueous foam with supreme stability and high plasticity. Whey protein isolate and sodium caseinate (0.1 wt %) considerably enhanced the foamability and interfacial activity of SLNs and promoted the packing of particles at the bubble surface. However, high protein concentration caused foam destruction due to the competitive adsorption effect. β-sheet increased in protein after adsorption and changed the polymorphism and thermodynamic properties of SLN. The foam collapsing behaviors varied in the presence of protein. The results gave insights into fabricating ultrastable aqueous foams by using high-melting DAG particles. The obtained foams demonstrated good temperature sensitivity and plasticity, which showed promising application prospects in the food and cosmetic fields.

During software development, programmers often rely on a wide range of application programming interfaces (APIs) to facilitate their tasks. However, APIs have been growing rapidly in recent years, making it difficult for developers to choose among the many APIs that suit their programming needs. To facilitate the development process, automatic API recommendation is becoming increasingly important. Although there have been many effective research methods, these methods have a high dependence on the accuracy of the user's description of his own task, and there is a knowledge difference between the user's query and the user's actual task, increasing the difficulty of accurate API recommendation. In this article, we propose REAPI, a method to bridge the knowledge gap between the user's query and the user's actual task to improve the recommendation accuracy. The REAPI approach involves reconstructing query by tapping into Stack Overflow data to glean user intentions. Refactoring the user's query to display implicit information can better capture the user's true intentions. Specifically, we generate three candidate reconstruction statements based on natural language queries and Stack Overflow data and incorporate user feedback to refine and select the final statement. To evaluate the effectiveness of REAPI, we conducted experiments at both the class-level and method-level. Our results show that REAPI outperforms state-of-the-art baselines across key evaluation metrics such as S@1, S@3, S@10, MRR, and MAP.

Understanding the influence mechanism of microstructures and inclusions during heat treatment on the corrosion resistance of L-PBF 316L stainless steel (SS) is crucial for steel quality control and subsequent industrial application. In this study, the evolution of microstructure, inclusions and passive film in the L-PBF 316L SS during heat treatment at the temperature of 1000 °C and 1200 °C for 2 h, including crystal characteristics, dislocation density, passivation film composition and so on, were characterized by electron backscatter diffraction (EBSD), transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy (XPS). The corrosion resistance of L-PBF 316L SS samples was evaluated by Tafel test and electrochemical impedance spectroscopy test. The corrosion mechanisms of L-PBF 316L SS before and after heat treatment were clarified to elucidate the intrinsic effect of microstructure and inclusions on the corrosion resistance of the steel. Results showed that the heat treatment conducted at 1200 °C effectively reduced the number of grain boundaries and induced a substantial number of Σ3 twin grain boundaries in the L-PBF 316L SS, thereby efficiently impeding the precipitation of detrimental phases and reducing corrosion susceptibility at the grain boundaries. Meanwhile, the recrystallization-induced rearrangement of dislocations and the homogenization of grains effectively facilitated the growth of passivation film, thereby increasing the corrosion resistance of HT1200 sample. Additionally, the increase of MoO3content compensated for the detrimental impact on the stability of the passivation film resulting from the reduction in chromium oxide content. Transformation from the MnO–SiO2–Cr2O3inclusions in the as-built sample to the SiO2inclusions in the HT1200 sample would also retard the penetration of corrosive ions into the steel matrix.

AbstractCardiovascular disease (CVD) is a group of diseases, affecting the human heart and accounting for 30% of deaths worldwide. Major CVDs include heart failure, hypertension, stroke, etc. Various therapeutics are available against CVD, still there is a dire need to find out potential protein drug targets to reduce economic burden and mortality rate. Goal of the current study was to utilize sequential computational techniques to find the best cardiovascular drug targets and their inhibitors. Common human cardiovascular targets of both databases (GeneCards and Uniprot) were subjected to bioinformatics analyses. Purpose was to validate putative therapeutic targets employing the structure-based bioinformatics methods to determine their physiochemical properties and biological processes. Three stable proteins, that have 0 transmembrane helices, and possess biological processes were screened as potential protein-based therapeutic targets: Hemoglobin subunit beta (HBB), Gamma-enolase (ENO2), and Cholesteryl ester transfer protein (CETP). Tertiary structures of target proteins were retrieved from PDB, and molecular docking technique was utilized to evaluate a library of 5000 phytochemicals against the interacting residues of the target protein as well as their respective standard drugs through MOE and Pyrx software. Top five phytochemicals (d-Sesamin, 1,3-benzodioxole, Sativanone, Thiamine, and Cajanol) were identified based on their RMSD and docking scores as compared to their standard drugs. The docking studies were also validated by MM-GBSA binding free energy and molecular dynamics simulations. According to the study’s findings, these phytochemicals may eventually be used as drugs to treat CVD. Further in vitrotesting is required to confirm their efficacy and drug potency.Communicated by Ramaswamy H. Sarma

Automated visualization recommendation facilitates the rapid creation of effective visualizations, which is especially beneficial for users with limited time and limited knowledge of data visualization. There is an increasing trend in leveraging machine learning (ML) techniques to achieve an end-to-end visualization recommendation. However, existing ML-based approaches implicitly assume that there is only one appropriate visualization for a specific dataset, which is often not true for real applications. Also, they often work like a black box, and are difficult for users to understand the reasons for recommending specific visualizations. To fill the research gap, we propose AdaVis, an adaptive and explainable approach to recommend one or multiple appropriate visualizations for a tabular dataset. It leverages a box embedding-based knowledge graph to well model the possible one-to-many mapping relations among different entities (i.e., data features, dataset columns, datasets, and visualization choices). The embeddings of the entities and relations can be learned from dataset-visualization pairs. Also, AdaVis incorporates the attention mechanism into the inference framework. Attention can indicate the relative importance of data features for a dataset and provide fine-grained explainability. Our extensive evaluations through quantitative metric evaluations, case studies, and user interviews demonstrate the effectiveness of AdaVis.

Quantum computing offers significant speedup compared to classical computing, which has led to a growing interest among users in learning and applying quantum computing across various applications. However, quantum circuits, which are fundamental for implementing quantum algorithms, can be challenging for users to understand due to their underlying logic, such as the temporal evolution of quantum states and the effect of quantum amplitudes on the probability of basis quantum states. To fill this research gap, we propose QuantumEyes, an interactive visual analytics system to enhance the interpretability of quantum circuits through both global and local levels. For the global-level analysis, we present three coupled visualizations to delineate the changes of quantum states and the underlying reasons: a Probability Summary View to overview the probability evolution of quantum states; a State Evolution View to enable an in-depth analysis of the influence of quantum gates on the quantum states; a Gate Explanation View to show the individual qubit states and facilitate a better understanding of the effect of quantum gates. For the local-level analysis, we design a novel geometrical visualization dandelion chart to explicitly reveal how the quantum amplitudes affect the probability of the quantum state. We thoroughly evaluated QuantumEyes as well as the novel dandelion chart integrated into it through two case studies on different types of quantum algorithms and in-depth expert interviews with 12 domain experts. The results demonstrate the effectiveness and usability of our approach in enhancing the interpretability of quantum circuits.

Online job advertisements on various job portals or websites have become the most popular way for people to find potential career opportunities nowadays. However, the majority of these job sites are limited to offering fundamental filters such as job titles, keywords, and compensation ranges. This often poses a challenge for job seekers in efficiently identifying relevant job advertisements that align with their unique skill sets amidst a vast sea of listings. Thus, we propose well-coordinated visualizations to provide job seekers with three levels of details of job information: a skill-job overview visualizes skill sets, employment posts as well as relationships between them with a hierarchical visualization design; a post exploration view leverages an augmented radar-chart glyph to represent job posts and further facilitates users’ swift comprehension of the pertinent skills necessitated by respective positions; a post detail view lists the specifics of selected job posts for profound analysis and comparison. By using a real-world recruitment advertisement dataset collected from 51Job, one of the largest job websites in China, we conducted two case studies and user interviews to evaluate JobViz. The results demonstrated the usefulness and effectiveness of our approach.

Traditional centralized Proportional Integral (PI) controller design methods based on Equivalent Transfer Functions (ETFs) have poor decoupling effect in turboprop engines. In this paper, a centralized PI design method based on dynamic imaginary matrix and equivalent transfer function is proposed. Firstly, a method for solving equivalent transfer functions based on the dynamic imaginary matrix is proposed, which adopts dynamic imaginary matrix to describe the dynamic characteristics of the system, and obtains the equivalent transfer function based on the dynamic imaginary matrix characteristics. Secondly, for the equivalent transfer function, a centralized PI control gain is designed using the Taylor expansion method. Meanwhile, this paper further proves that the centralized PI design method proposed in this paper has integral stability. Considering the impact of altitude and Mach number on turboprop engines, a linear feedforward control method based on the transfer function matrix is further proposed based on the centralized PI controller, and the stability of the entire comprehensive control method is proved. Finally, to ensure the safe and effective operation of the turboprop engine, a temperature and torque limiting protection controller is designed for the turboprop engine. Simulation results show that the centralized PI controller design method and linear feedforward control method proposed can effectively improve the control quality of turboprop engine control systems.

Pores are among the primary defects in 316L stainless steel when fabricated through laser powder bed fusion (L-PBF). To better understand and precisely control the formation behavior of pores in the L-PBF-manufactured 316L stainless steel, effects of L-PBF process parameters on the melt pool and pore characteristics have been investigated. A method utilized for extreme values statistics analysis was also applied to investigate and predict the sizes of pores. Relationships among the count of measurements, the laser energy density, the reduced variate, and the maximum pore size were revealed. The findings showed an overall increase in melt pool depth as the laser energy densities was raised, yet the magnitude of this growth weakened as the laser energy density continued to increase. Conversely, it was discovered that the connection between the width of the melt pool and the density of laser energy exhibited a markedly less distinct correlation. As laser energy density escalated, there was a shift in the melt pool mode from conduction-based to a transitional phase, and upon further elevation of the laser energy density, it transitioned to keyhole mode. To obtain a reliable statistical analysis of pores, at least 40 measurements should be acquired for the estimation of the pore sizes by taking comprehensive consideration of time cost. Beside, in all three melt pool modes, at a fixed observation area, the maximum size of pores generally decreased with the escalation in laser energy densities.