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ABSTRACTSpeeding has been acknowledged as a critical determinant in increasing the risk of crashes and their resulting injury severities. This paper employs Global Moran’s I coefficient and local Getis – Ord G* indexes to systematically account for the spatial distribution feature of speeding-related crashes, study the global spatial pattern of speeding-related crashes, and identify severe crash cluster districts. The findings demonstrate that severe speeding-related crashes within the state of Pennsylvania have a spatial clustering trend, where four crash datasets are extracted from four hotspot districts. Two log-likelihood ratio (LR) tests were conducted to determine whether speeding-related crashes classified by hotspot districts should be modeled separately. The results suggest that separate modeling is necessary. To capture the unobserved heterogeneity, four correlated random parameter order models with heterogeneity in means are employed to explore the factors contributing to crash severity involving at least one vehicle speeding.

Amino acids are essential building blocks in biology and chemistry. Whereas nature relies on a small number of amino acid structures, chemists desire access to a vast range of structurally diverse analogues1–3. The selective modification of amino acid side-chain residues represents an efficient strategy to access non-canonical derivatives of value in chemistry and biology. While semisynthetic methods leveraging the functional groups found in polar and aromatic amino acids have been extensively explored, highly selective and general approaches to transform unactivated C–H bonds in aliphatic amino acids remain less developed4,5. Here we disclose a stepwise dehydrogenative method to convert aliphatic amino acids into structurally diverse analogues. The key to the success of this approach lies in the development of a selective catalytic acceptorless dehydrogenation method driven by photochemical irradiation, which provides access to terminal alkene intermediates for downstream functionalization. Overall, this strategy enables the rapid synthesis of new amino acid building blocks and suggests possibilities for the late-stage modification of more complex oligopeptides.

This article presents a novel approach for computing substructure characteristic modes. This method leverages electromagnetic (EM) scattering matrices and spherical wave expansion to directly decompose EM fields. Unlike conventional methods that rely on the impedance matrix generated by the method of moments (MoMs), our technique simplifies the problem into a small-scale ordinary eigenvalue problem, improving numerical dynamics and computational efficiency. We have developed analytical substructure characteristic mode solutions for a scenario involving two spheres, which can serve as benchmarks for evaluating other numerical solvers. A key advantage of our method is its independence from specific MoM frameworks, allowing for the use of various numerical methods. This flexibility paves the way for substructure characteristic mode decomposition to become a universal frequency-domain technique.

Early detection of faults in power batteries is essential for the safety of electric vehicles (EVs). However, the character of early faults is similar to that of noise, which makes it challenging to accurately diagnose early faults without misdiagnosis. To address this problem, a method based on the cumulation of anomalies is proposed in this article, which can quantify the anomalies of the battery and accumulate them through biased integration. Consequently, the anomalies induced by faults are progressively amplified during the fault duration, whereas the noise-induced anomalies diminish once the noise ceases. The method consists of three steps: prediagnosis, fusion, and cumulation. The quantitative battery anomaly degree can be obtained through steps 1 and 2, which are then further processed and accumulated in step 3 to differentiate between faults and noise. Experimental results reveal that the presented approach simultaneously guarantees a high fault detection rate of 95% and a low misdiagnosis rate of 20%, significantly surpassing traditional methods by approximately 35% and 30%, respectively. Thus, the proposed method proves effective for the detection of early faults in EV power batteries.

This manuscript provides insights into the characteristics of shock wave propagation and flame development mechanisms in bifurcated tubes due to accidental leakage from a high-pressure hydrogen storage unit in the energy and chemical industries. Incorporating the non-stop working process of tube plugging in gas transportation in industrial production, two types of bifurcated tubes with axial and normal blocking are designed. The experimental results indicate that, compared to straight tube, both types of blocking tube structures can effectively reduce shock wave pressure intensity at the nozzle. Under the initial burst pressure of 8 MPa, the lowest shock wave pressure at the nozzle of the axially blocking tube is just 0.47 MPa. However, the peak shock wave pressure inside the blocking tubes is higher, and the ignition critical pressure is lower. Within the axially sealed blocking tube, flame quenching is observed, offering experimental support for mitigating the development of continuous jet fires outside of high-pressure hydrogen tubes.

Fault diagnosis technology can detect the minor anomalies of batteries, which is of crucial significance to ensuring the safe operation of electric vehicles (EVs). However, the voltages of early minor faults do not exceed the safety threshold, which is difficult to detect using the conventional fault diagnosis methods. Herein, a minor fault diagnosis approach for lithium-ion batteries based on phase plane sample entropy is presented. Specifically, the battery phase plane is defined for the first time, taking the voltages as abscissa and the first-order difference of voltages as ordinate. In addition, the two-dimensional sample entropy of each cell phase plane is calculated through a sliding window, which allows minor faults to be accurately detected and the time of occurrence of the fault to be predicted. The experimental results demonstrate the effectiveness, robustness, and generalizability of the proposed approach. More importantly, the presented technique achieves a 92.50% fault detection rate and an 82.33% detection accuracy rate with a minor fault amplitude of 50 mV, which are approximately 14% and 16% higher than that of the conventional sample entropy methods, respectively. In summary, the proposed method highlights the broad application of phase planes for battery fault diagnosis.

In this paper, an innovative decoder‐type gate driver on array (GOA) model employing IGZO TFTs is proposed, which is suitable for intelligent split‐screen (ISS) and external compensation technology. At the same time, we explored a new multi‐frequency driving method through this model, and through the verification of panel actual measurement, this new multi‐frequency driving almost eliminates the Mura caused by different frequencies in split‐screen. Finally, we successfully used this model to light up a 5‐inch AMOLED display with 170PPI bottom emission, and achieved a border of only 5mm.

AR display has been the most promising new technology in the current display market. Among which surface relief grating waveguide has the advantages of large field of view, small volume and light weight. This article adopts the large‐area (370 mm * 470 mm) waveguide prepraration route as a solution to the low‐cost and high‐efficiency waveguide route, showing excellent structural uniformity of more than 95%. The waveguide numbers is 5 to 10 times that of the conventional wafer‐level route, which can further promote the practical application of AR waveguides.

The use of β-lactam (BL) and β-lactamase inhibitor combination to overcome BL antibiotic resistance has been validated through clinically approved drug products. However, unmet medical needs still exist for the treatment of infections caused by Gram-negative (GN) bacteria expressing metallo-β-lactamases. Previously, we reported our effort to discover pan inhibitors of three main families in this class: IMP, VIM, and NDM. Herein, we describe our work to improve the GN coverage spectrum in combination with imipenem and relebactam. This was achieved through structure- and property-based optimization to tackle the GN cell penetration and efflux challenges. A significant discovery was made that inhibition of both VIM alleles, VIM-1 and VIM-2, is essential for broad GN coverage, especially against VIM-producing P. aeruginosa. In addition, pharmacokinetics and nonclinical safety profiles were investigated for select compounds. Key findings from this drug discovery campaign laid the foundation for further lead optimization toward identification of preclinical candidates.

ABSTRACT Three crumb rubbers (CRs) from typical waste tires were used to modify two base bitumens. The chemical compositions and the morphologies of CRs were characterized by the thermogravimetry-mass spectrometer [...]

The widespread use of home consumer electronics (CEs) provides residents facility, assistance and comfort. Meanwhile, smart meters are deployed at households to optimize electricity supply and demand and improve electricity efficiency. These meters monitor, collect and aggregate the electricity consumption of the home CEs in a near-real-time way. However, such processes seriously invade consumer privacy, e.g., household occupancy and economic status. Many existing privacy-preserving schemes rely on the assumption that certain components can be trusted, which is hard to be ensured, and cannot resist against collusion attacks. In this study, we leverage differential privacy and a re-encryption model to produce a privacy-preserving aggregation mechanism, called PREEN, for smart-metering communications. PREEN simultaneously facilitates data aggregation, differential privacy, and protection against various attacks. Specifically, we adopt ElGamal algorithm to construct the re-encryption scheme and differential privacy to aggregate the consumption measurements of residential users at the gateways and control center, thereby enabling resistance against slashing privacy attacks. Strict and detailed security proofs as well as extensive performance evaluations are adopted to demonstrate that the proposed PREEN provides rigorous privacy preservation and confidentiality against diverse external and internal attacks, while remaining a comparable or even lower computational overhead and a negligible communication overhead and a reasonable accuracy in terms of the utility of differential privacy, compared to the state-of-the-art mechanisms.

Accurate vehicle trajectory prediction is critical for autonomous vehicles and advanced driver assistance systems to make driving decisions and improve traffic safety. This paper proposes a novel Temporal Multi-task Mixture Of Experts (TMMOE) model for simultaneously predicting the vehicle trajectory and driving intention, considering interconnections among tasks. As for the methodology, the proposed model consists of three layers: a shared layer, an expert layer, and a fully connected layer. In more detail, the first layer utilizes Temporal Convolutional Network (TCN) to extract temporal features whereas the expert layer incorporates the gating mechanism to memorize and filter the temporal dependence of sequences and, finally, the fully connected layer is applied to integrate and export prediction results. Furthermore, the homoscedastic uncertainty algorithm is used to construct the multi-task loss function. The open data source CitySim dataset is chosen to validate the performance of the proposed TMMOE model; moreover, a novel lane line reconstruction method is introduced to mitigate measurement errors of the dataset. Two-part information, including the history of the vehicle's trajectory and the interaction indicators, are employed as the input variables. The result indicates that the TMMOE algorithm exhibits superior performance when compared to the other five models, including Long Short-Term Memory (LSTM) Network, Convolutional Neural Network (CNN), CNN-LSTM, TCN, and Gate Recurrent Unit (GRU), while considering varying input sequence lengths are 3 s, 6 s, and 9 s respectively. Finally, the sensitivity analysis demonstrates that considering driving intentions in vehicle trajectory prediction can significantly enhance the prediction accuracy of vehicle trajectories.

High-reliability and low-latency communication is essential for timely information exchange in vehicle platooning. As a key enabler of this, the cellular vehicular-to-everything (C-V2X) network uses a sensing-based semi-persistent scheduling (SPS) protocol, where radio resources are reserved for a number of transmissions with reduced resource re-allocation and control overhead. However, consecutive access collisions may be caused by reservation conflict, which leads to long delay and threatens platoon’s stability and safety. In this paper, a coordinating resource reservation (CRR) protocol is proposed for vehicle platooning. By implementing error detection with coordination among platoon vehicles, the resource reservation is improved for reduced collisions and delay. Specifically, packet reception/loss information is sent out by platoon vehicles through their own packets. Such information is shared with transmitters and guides them to reserve new resources when access collision occurs. As a result, long delay is avoided while no extra feedback packet is introduced. Furthermore, Markov analysis is presented to evaluate the performance of SPS and the proposed CRR for vehicle platooning, providing the quantified performance gains. Finally, simulation results demonstrate the superiority of the proposed CRR in reducing packet loss and latency, compared with the legacy SPS and other state-of-the-art solutions.

Maintaining the safety of lithium-ion battery modules is the priority in promoting the application of electric vehicles (EVs). In practical EV applications, only the total voltage of the battery module and the maximum/minimum cell voltages are available. Under this circumstance, most existing methods are unable to diagnose the faults of EV battery modules. Therefore, an applicable minor short-circuit fault diagnosis method for automotive lithium-ion batteries based on extremum sample entropy (ESE) is proposed to solve the above issues. Specifically, the extremum sequences are first extracted from the original voltage data. Then, the sample entropy of the sum/difference sequence is applied to diagnose minor cell internal short-circuit (C-ISC) faults and module external short-circuit (M-ESC) faults. Eventually, the mean extreme difference model is established to quantitatively evaluate the internal short-circuit (ISC) resistances. The experimental results reveal that the proposed ESE algorithm can successfully diagnose the different degrees of minor C-ISC and M-ESC faults. Moreover, the average value of the estimated ISC resistance is 71 mΩ, whose estimated error is 5.6%. More importantly, the proposed ESE approach requires only 1 s to detect 100 battery cells, which increases the calculation speed by 30 times compared with the traditional method.

In the future 6G intelligent transportation system, the edge server will bring great convenience to the timely computing service for connected vehicles. To guarantee the quality of service, the time-critical services need to be migrated according to the future location of the vehicle. However, predicting vehicle mobility is challenging due to the time-varying of road traffic and the complex mobility patterns of vehicles. To address this issue, a spatial-temporal awareness proactive service migration strategy is proposed in this paper. First, a spatial-temporal neural network is designed to obtain accurate mobility by using gated recurrent units and graph convolutional layers extracting features from spatial road traffic and multi-time scales driving data. Then a proactive migration method is proposed to guarantee the reliability of services and reduce energy consumption. Considering the reliability of services and the real-time workload of servers, the migration problem is modeled as a multi-objective optimization problem, and the Lyapunov optimization method is utilized to obtain utility-optimal migration decisions. Extensive simulations based on real-world datasets are performed to validate the performance of the proposed method. The results show that the proposed method achieved 6% higher prediction accuracy, 10% lower dropping rate, and 10% lower energy consumption compared to state-of-the-art methods.

Innovation in decarbonizing wastewater treatment is urgent in response to global climate change. The practical implementation of anaerobic ammonium oxidation (anammox) treating domestic wastewater is the key to reconciling carbon-neutral management of wastewater treatment with sustainable development. Nitrite availability is the prerequisite of the anammox reaction, but how to achieve robust nitrite supply and accumulation for mainstream systems remains elusive. This work presents a state-of-the-art review on the recent advances in nitrite supply for mainstream anammox, paying special attention to available pathways (forward-going (from ammonium to nitrite) and backward-going (from nitrate to nitrite)), key controlling strategies, and physiological and ecological characteristics of functional microorganisms involved in nitrite supply. First, we comprehensively assessed the mainstream nitrite-oxidizing bacteria control methods, outlining that these technologies are transitioning to technologies possessing multiple selective pressures (such as intermittent aeration and membrane-aerated biological reactor), integrating side stream treatment (such as free ammonia/free nitrous acid suppression in recirculated sludge treatment), and maintaining high activity of ammonia-oxidizing bacteria and anammox bacteria for competing oxygen and nitrite with nitrite-oxidizing bacteria. We then highlight emerging strategies of nitrite supply, including the nitrite production driven by novel ammonia-oxidizing microbes (ammonia-oxidizing archaea and complete ammonia oxidation bacteria) and nitrate reduction pathways (partial denitrification and nitrate-dependent anaerobic methane oxidation). The resources requirement of different mainstream nitrite supply pathways is analyzed, and a hybrid nitrite supply pathway by combining partial nitrification and nitrate reduction is encouraged. Moreover, data-driven modeling of a mainstream nitrite supply process as well as proactive microbiome management is proposed in the hope of achieving mainstream nitrite supply in practical application. Finally, the existing challenges and further perspectives are highlighted, i.e., investigation of nitrite-supplying bacteria, the scaling-up of hybrid nitrite supply technologies from laboratory to practical implementation under real conditions, and the data-driven management for the stable performance of mainstream nitrite supply. The fundamental insights in this review aim to inspire and advance our understanding about how to provide nitrite robustly for mainstream anammox and shed light on important obstacles warranting further settlement.

Cysteine (Cys) plays key roles in various pathological and physiological processes. Thus, the specific detection of Cys is a great necessity for the related disease diagnosis. Herein, we present a novel fluorescent probe based on a 2-benzothiazolyl-6-quinazolinyl-4-methylphenol moiety as fluorophore and a 2,4-dinitrobenzenesulfonyl moiety as detection functioned group. The probe presented a rapid and specific turn on response to Cys under physiological conditions, which could be convenient observed by the naked eyes. The detection mechanism was elucidated by HRMS, UV/vis absorption, fluorescence and DFT calculation. Furthermore, the probe was applied to monitor the endogenous Cys in living cells and mice.

Metal-organic frameworks (MOFs) with exposed boron sites are potentially promising materials to catalyze oxidative dehydrogenation of propane (ODHP). The reticular chemistry enables a detailed investigation of the role of boron sites with different chemical environments in catalyzing the ODHP reaction and further designing MOFs with high efficiency. However, the poor oxidation resistance of MOFs limits their use in ODHP applications. In this study, we develop a metal-borate-organic network (denoted as MBON-2) with a pillared layered structure. MBON-2 features a nanosheet-assembled 3D flower-like hierarchical structure and remarkable thermal stability. By taking advantage of the structural featural of graphene-like ZnBO layers, the edges of the MBON-2 nanosheet expose numerous boron sites that exhibit excellent catalytic performance in ODHP. The characterization and density functional theory results suggest that neighboring boron sites, when at an optimal distance, offer a potential reaction pathway that synergistically abstracts H atoms of propane sequentially.

A radical sulfonation–ipso-cyclization cascade promoted by Mn(OAc)3·2H2O using functionalized alkynes or alkenes and potassium metabisulfite (K2S2O5) is reported. A total of 30 spirocyclic sulfonates were synthesized under mild conditions. We also demonstrate a modular synthesis approach in multiple steps for the preparation of various azaspiro[4,5]-trienone-based sulfonamides and sulfonate esters.

A compact double periodic leaky-wave antenna is designed in this letter, which has been developed to suppress the open-stopband (OSB). This antenna is loaded with shorting vias and folded slots on a substrate-integrated waveguide (SIW) periodically. The proposed antenna can scan from backward to forward continuously with a high radiation gain at broadside. The double periodic cell made the overall size only 2.6 wavelengths. Compared with traditional SIW leaky-wave antennas (LWAs), the size is conspicuously reduced. The equivalent circuits of several different types of cell are analyzed to understand the mechanism of OSB suppression. This antenna realized the steering range from −20° to 30°. Results showed that radiation gain of the antenna varies from 8.6 to 10.8 dBi in the frequency range from 13.5 to 17 GHz while 9 dBi gain achieved at broadside. The simulation results agree well with the measured results. The compact LWA operates in a large scanning range with the high directivity of continuous beam scanning.

The rising global uncertainty has been proved to have great impact on labor market. Compared to the adults defined as those aged 25 years and above, the youth aged between 15 and 24 years has experienced sharper employment losses. In this study, we examine the effect of economic policy uncertainty (EPU) on the choice of employment city by youth labor using the employment data of 46,804 graduates in China from 2014 to 2019. We find that: (1) EPU can significantly reduce the likelihood of youth leaving their hometown for employment. In other words, uncertainty makes graduates more “conservative” in their choice of cities; (2) City characteristics are important factors influencing graduates’ choice of city, with economic factors being among the most important ones; (3) The probability of male and graduates with doctoral degree leaving their hometown for employment is relatively less affected by the negative effect of uncertainty, while female and graduates with master degree are more affected. Our findings can generate important implication for youth-oriented labor market policies.

Peridynamics has unique advantages in solving discontinuity problems such as explosive damage of structures. To further promote the peridynamic models, numerical algorithms and applications, a bond-associated non-ordinary state-based peridynamics (BA-NOSB PD) approach embedded with the Johnson–Holmquist II (JH-2) constitutive is established to analyze the explosive damage and failure of concrete structures. The BA-NOSB PD with the JH-2 constitutive not only can avoid the numerical instability problem, but also can accurately describe the complex mechanical behaviors of quasi-brittle materials such as large strain, high strain rate, and high pressure. The wave propagation and superposition in a concrete bar and the dynamic branch of a rectangular concrete slab are first modeled to display the reliability of the proposed method. Besides, an empirical formula of explosion overpressure is provided to exert the near-field air explosion load. The PD simulation of a reinforced concrete slab under explosion impact captures the typical damage mode well, globally consistent with the actual experiment test. Then, the significance of the influence function on the simulation results is discussed. Finally, the damage process of a concrete gravity dam under explosive loading conditions and the influencing factors such as detonation distance and TNT mass on the damage degree are studied. The simulation results illustrate that the proposed peridynamic approach can accurately and efficiently reproduce the damage and failure process of concrete structures under explosion impact.

The thermal performance of the heat exchanger is strongly influenced by the supporting structure. Corrugated baffle enhances flow field disturbance and heat transfer through its complex and changeable flow channel. In order to enhance the thermal performance of the torsional flow heat exchanger (TFHX), the sinusoidal corrugated baffle (SCB) is used to replace the flat baffle (FB) and the full-section cycle model of the torsional flow heat exchanger with sinusoidal corrugated baffle (TFHX-SCB) is established. Computational fluid dynamics (CFD) method was used to discuss the flow resistance characteristics of the shell-side of heat exchangers. The results show that the SCB can improve the turbulence intensity and the uniformity of the flow field between the adjacent baffles. The combination of structural configurations on the shell-side of TFHX-SCB is analyzed by the central composite design (CCD)-response surface method (RSM). When the amplitude of the SCB is 1.37 mm, the cycles of the SCB are 4.42; the initial phase of the SCB is 112.73°, and the combination of heat transfer coefficient and comprehensive performance is optimal. Compared with the original structure, the heat transfer coefficient is increased by 11.58%, and the comprehensive performance is increased by 5.48%. The laser doppler velocimetry (LDV) experimental device irradiated the specified measurement point, and the dependability and accuracy of numerical simulation methods were verified. The research conclusion provides a basic theory for the structural development of the TFHX.

For periodical beacon broadcasting in cellular vehicle-to-everything (C-V2X) networks, a distributed reservation media access control (MAC) protocol, the sensing-based semi-persistent scheduling (SPS), is adopted. However, how to quantify the communication reliability and latency is an open issue, which is critical for low-latency and high-reliability services. In this paper, an analytical model for SPS is presented, based on which the impacts of beacon rate, range settings and system configuration on access collision probability and delay outage probability are quantified. The analytical model provides important insights and guideline to adapt and optimize protocol parameters including the sensing range, transmit power and resource reservation. The enhanced MAC protocol can maintain high-reliability and low-latency services with a wide range of vehicle density. Simulations are conducted to validate the analysis and the results demonstrate that the proposed MAC enhancement solution can reduce collision probability while ensuring the delay outage probability based on service requirements.

Selenium (Se), one of the indispensable nutrients for both human health and animal growth, participates in various physiological functions, such as antioxidant and immune responses and metabolism. The role of dietary Se, in its organic and inorganic forms, has been well documented in domestic animals. Furthermore, many feeding strategies for different animals have been developed to increase the Se concentration in animal products to address Se deficiency and even as a potential nutritional strategy to treat free radical-associated diseases. Nevertheless, studies on investigating the optimum addition of Se in feed, the long-term consequences of Se usage in food for animal nutrition, the mechanism of metallic Se nanoparticle (SeNP) transformation in vivo, and the nutritional effects of SeNPs on feed workers and the environment are urgently needed. Starting from the absorption and metabolism mechanism of Se, this review discusses the antioxidant role of Se in detail. Based on this characteristic, we further investigated the application of Se in animal health and described some unresolved issues and unanswered questions warranting further investigation. This review is expected to provide a theoretical reference for improving the quality of food animal meat as well as for the development of Se-based biological nutrition enhancement technology.

The safety concerns triggered by thermal runaway (TR) are the major obstacle to the large-scale commercialization of lithium-ion batteries (LIBs). In essence, TR is an electrical-thermal coupling process involving the interaction between internal short circuits (ISC) and exothermic reactions. Nevertheless, most existing models primarily focus on exothermic decomposition reactions and temperature prediction during TR, while overlooking the modeling of ISC behavior from a mechanistic perspective. This paper proposes a novel modeling approach that defines the ISC state of the battery through the degree of separator shrinkage. Firstly, differential scanning calorimeter (DSC) experiments are performed on the separator to ascertain its thermal shrinkage characteristics. Following this, a shrinkage function is constructed to quantitatively describe the thermal shrinkage of the separator. Subsequently, the ISC conductivity as a function of separator shrinkage degree is integrated into the electrical-thermal coupling model. Consequently, the model can quantitatively assess ISC behavior resulting from separator shrinkage or melting. The average relative error of the model for voltage and temperature prediction is 0.57 % and 1.8 %, respectively. This indicates that the model can accurately capture the electrical-thermal coupling characteristics and ISC state of LIBs. This work presents a novel perspective on the mechanism research of TR and model-based TR warning.

High concentration refractory organic matters, particular humic substances, often account for the majority of organic pollutants in mature landfill leachate, which cannot be effectively decomposed by biological processes. The iron-carbon micro-electrolysis combined with persulfate activated (ICME-PS) process was developed for the advanced treatment of biologically treated mature landfill leachate in this study. By employing the single factor experiment and Response Surface Methodology, the maximum COD removal rate reached 83.45% under the optimal conditions: persulfate dosage of 35.60 g/L, Fe-C dosage of 210.69 g/L, aeration rate of 0.44 L/min and initial pH of 6.70. Among them, persulfate dosage and initial pH had more significant effects on the COD removal of the ICME-PS process. Furthermore, the application of ICME-PS process in continuous flow mode indicated that the COD removal rate could reach 79.97 %, which demonstrated the feasibility of ICME-PS process in practical application. Through the ICME-PS process, conjugated polymers, aromatic compounds and polycyclic aromatic hydrocarbons in mature landfill leachate were broken down into various small molecular organic matters. The humic acid-like substances were destroyed and the humification degree was reduced. Taken together, the ICME-PS process provides an effective method for landfill leachate advanced treatment.

Background: Azithromycin has been used to treat primary and secondary syphilis and as prophylaxis for sexual partners. We evaluated syphilis treatment failure in patients who received azithromycin therapy. Methods: Patients who did not respond to azithromycin therapy were referred to Shanghai Skin Disease and sexually transmitted disease hospital. Treatment failure was defined as follows: (1) persistent ulcers or cutaneous or mucosal lesions 1 month after therapy; or (2) detection of spirochetes in dark-field microscopy examination of a lesion at least 1 week after treatment; or (3) failure of rapid plasma reagin titers to decrease 4-fold at 3 months after treatment. Results: A total of 132 patients with primary and secondary syphilis who failed azithromycin therapy were referred to our hospital between January 2001 and October 2008. Of 132 patients, 42 (31.8%) had primary syphilis and 90 (68.2%) had secondary syphilis. Twenty-six patients with primary syphilis developed multiple lesions or secondary syphilis, or persistent ulcers despite using azithromycin. The skin or mucosal lesions did not resolve in 37 patients with secondary syphilis after azithromycin treatment. Ten patients had a positive dark-field examination for Treponema pallidum (T. pallidum) after treatment. The serum rapid plasma reagin titers studied in all cases had failed to decrease 4-fold at 3 months after therapy. The doses of azithromycin used for treatment ranged from 4 to 30 g. Conclusions: The failure of azithromycin to cure a substantial number of patients with primary and secondary syphilis in Shanghai suggests that azithromycin has limited therapeutic value in this setting.

Mechanistic target of rapamycin complex 1 (mTORC1) regulates cell growth and metabolism in response to multiple nutrients, including the essential amino acid leucine1. Recent work in cultured mammalian cells established the Sestrins as leucine-binding proteins that inhibit mTORC1 signalling during leucine deprivation2,3, but their role in the organismal response to dietary leucine remains elusive. Here we find that Sestrin-null flies (Sesn−/−) fail to inhibit mTORC1 or activate autophagy after acute leucine starvation and have impaired development and a shortened lifespan on a low-leucine diet. Knock-in flies expressing a leucine-binding-deficient Sestrin mutant (SesnL431E) have reduced, leucine-insensitive mTORC1 activity. Notably, we find that flies can discriminate between food with or without leucine, and preferentially feed and lay progeny on leucine-containing food. This preference depends on Sestrin and its capacity to bind leucine. Leucine regulates mTORC1 activity in glial cells, and knockdown of Sesnin these cells reduces the ability of flies to detect leucine-free food. Thus, nutrient sensing by mTORC1 is necessary for flies not only to adapt to, but also to detect, a diet deficient in an essential nutrient.

In geotechnical engineering, the transparent soil (also called transparent media) technique is an effective tool for conducting experimental tests and investigating the displacement characteristics and stress distribution of soils. It plays a vital role in the observation of internal soil deformations. This study aims to briefly review the current state of some of the common materials used to formulate transparent soil models and the application of the transparent soil technique to underground construction over the last 20 years. To this end, the basic concepts of transparent soils are introduced. Then, several representative applications of transparent soil in underground construction (i.e., soil deformations induced by the penetration of pile foundations, tunnel excavation-induced movements, and structural responses caused by braced excavations) are presented. Because some research gaps may exist, certain potential research topics are proposed. This review can serve as a guideline for researchers performing experiments using transparent soils.

Mechanistic target of rapamycin complex 1 (mTORC1) controls growth by regulating anabolic and catabolic processes in response to environmental cues, including nutrients1,2. Amino acids signal to mTORC1 through the Rag GTPases, which are regulated by several protein complexes, including GATOR1 and GATOR2. GATOR2, which has five components (WDR24, MIOS, WDR59, SEH1L and SEC13), is required for amino acids to activate mTORC1 and interacts with the leucine and arginine sensors SESN2 and CASTOR1, respectively3–5. Despite this central role in nutrient sensing, GATOR2 remains mysterious as its subunit stoichiometry, biochemical function and structure are unknown. Here we used cryo-electron microscopy to determine the three-dimensional structure of the human GATOR2 complex. We found that GATOR2 adopts a large (1.1 MDa), two-fold symmetric, cage-like architecture, supported by an octagonal scaffold and decorated with eight pairs of WD40 β-propellers. The scaffold contains two WDR24, four MIOS and two WDR59 subunits circularized via two distinct types of junction involving non-catalytic RING domains and α-solenoids. Integration of SEH1L and SEC13 into the scaffold through β-propeller blade donation stabilizes the GATOR2 complex and reveals an evolutionary relationship to the nuclear pore and membrane-coating complexes6. The scaffold orients the WD40 β-propeller dimers, which mediate interactions with SESN2, CASTOR1 and GATOR1. Our work reveals the structure of an essential component of the nutrient-sensing machinery and provides a foundation for understanding the function of GATOR2 within the mTORC1 pathway.

Herein, we reported a so far unprecedented Mn(OAc)3·2H2O-promoted homolytic aromatic sulfonation. The reaction was performed under mild conditions with K2S2O5employed as a green sulfonating reagent. Various arenes were successfully converted into desired sulfonic acids or sulfonates in high efficiency. Preliminary mechanistic studies demonstrated that the present reaction proceeds via a homolytic aromatic substitution-type mechanism involving an SO3–radical. The combination of Mn(OAc)3·2H2O and HFIP plays a crucial role.

In an urbanization process, infrastructure elements such as tunnels and deep excavations are widely used to service the development of cities. Owing to the lengthy geological processes of geomaterials and the limited availability of site-specific test data, soil and rock properties exhibiting spatial variability are frequently encountered in geological and geotechnical engineering. This paper presents a comprehensive review of the application of spatial variability in tunneling and deep excavation over the past 20 years. It is found that the spatial variability is generally modeled as a random field (RF) in finite element software, based on random field theory (RFT). This model has been widely used in the design, stability evaluation, and probabilistic analysis of tunnels and excavations. Previous works have proven that the performance of tunnels and deep excavations can be better captured by considering the spatial variability, as compared with conventional deterministic analysis methods. Nonetheless, current research still faces many factual scientific problems. Therefore, this paper also identifies some research gaps, as well as recommendations for further investigations.

Shell and tube heat exchanger is an important part of industrial heating and cooling system. Because of the harsh operating conditions, and its complex fin and baffle structure with numerous holes, it is a great challenge for engineers to design and evaluate the baffle structure on the premise of ensuring the comprehensive performance. This paper aims to provide a method to optimize the baffle structure of torsional flow heat exchanger by comprehensively considering thermal, hydraulic, and mechanical properties. Based on fluid-structure interaction method, response surface methodology was applied to improve the structure configurations of torsional flow heat exchanger. The results show that the effects of various input parameters on objectives are related to each other, and the baffle width and inclination angle have a more obvious impact on heat exchanger. The tradeoff analysis is carried out for the optimization objectives, the candidate points obtained by optimization reveal that the fluid comprehensive performance of the optimal structure is increased by 10.99%, and the maximum equivalent stress is reduced by 8.74%. The research results offer theoretical guidance for the equipment maintenance and structural design of torsional flow heat exchanger.

Reservoir slope stability during water level drawdown has drawn increasing concern in geotechnical engineering in recent years. In this study, an efficient reliability analysis framework based on the extreme gradient boosting (XGBoost) surrogate model is employed to evaluate the failure probability of unsaturated slopes subjected to the rapid drawdown considering the depth-dependent properties of spatially varying soils. A c-φslope is selected as an illustrative example to investigate the coupled influence of the non-stationary characteristic of shear strength parameters and saturated hydraulic conductivity, as well as water level drawdown velocity, maximum drop height and scale of fluctuation on the slope failure probability. Results show that the adopted framework can estimate the low-level probability of slope failure with high accuracy and efficiency. It is found that the velocity and maximum height of water level drawdown have a significant effect on the unsaturated slope stability. Furthermore, it is recommended that the depth-dependent non-stationary soil properties be considered in most cases to ensure a more accurate result.

A strategy based on metal-organic decomposition is proposed to enhance the tube-tube interactions of carbon nanotubes (CNTs).The robust tube-tube interactions of CNTs enhance both EMI shielding performance and mechanical properties of CNT film.This innovative approach provides an effective way to obtain high-performance CNT film.

Timely and accurate diagnosis of lithium-ion battery faults is crucial for ensuring the safety of electric vehicles. While incremental capacity (IC)-based diagnostic methods are effective, they can only be employed under charging conditions. To address this issue, a fault diagnostic method based on phase plane analysis is proposed to extend the application to various operating conditions. In a phase plane, the battery voltage is plotted on the x-axis, while the differential in voltage is plotted on the y-axis. During charging, diagnostic vectors indicating the occurrence and type of faults are extracted from the trajectories in the phase plane. Under complex operating conditions, early faults can be detected based on the morphological and scale deviation of the trajectories. Experimental results have shown that the proposed method can effectively detect minor faults. The fault detection rate and detection accuracy rate under charging conditions are 96.25 % and 97.73 %, respectively, which are 17.5 % and 8.54 % higher than those of the IC-based diagnostic method. Furthermore, the fault detection rate and accuracy rate under UDDS (Urban Dynamometer Driving Schedule) are 91.76 % and 97.23 %, respectively. Additionally, the diagnostic speed of the proposed method is twice as fast as that of the IC-based method.

The use of neutron methods in environmental and biological sciences is rapidly emerging and accelerating with the development of new instruments at neutron user facilities. This article, based on a workshop held at Oak Ridge National Laboratory (ORNL), offers insights into the application of neutron techniques in environmental and biological sciences. We highlight recent advances and identify key challenges and potential future research areas. These include soil and rhizosphere processes, root water dynamics, plant-microbe interactions, structure and dynamics of biological systems, applications in synthetic biology and enzyme engineering, next-generation bioproducts, biomaterials and bioenergy, nanoscale structure, and fluid dynamics of porous materials in geochemistry. We provide an outlook on emerging opportunities with an emphasis on new capabilities that will be enabled at the Spallation Neutron Source Second Target Station currently under design at ORNL. The mission of scientific neutron user facilities worldwide is to enable science using state-of-the-art neutron capabilities. We aim to encourage researchers in the environmental and biological research community to explore the unique capability afforded by neutrons at these facilities.

With the rapid proliferation of electric vehicles, the safety concerns related to lithium-ion batteries are gaining more and more attention. Fault diagnosis is a key approach to reducing the risk of battery failure. However, existing battery management systems (BMS) apply under-sampled voltage signal acquisition, which leads to misdiagnosis and omission of faults. To address this issue, a minor fault early diagnosis method based on static-dynamic compensation voltage data is proposed. First, the voltages of the series-connected cells are asynchronously collected. Then, the collected voltage sequences from various modules are mapped to the voltage sequence of the target battery using the static-dynamic compensating method, which can obtain a new sequence with a significantly higher equivalent sampling frequency. Finally, the sample entropy method is employed to detect minor faults based on the new sequence after compensation. Experimental results reveal that the presented method can increase the sampling frequency by about 8 times. The proposed method can successfully detect minor short circuits and poor connection faults in the battery under different ambient temperatures.

This research aimed at ascertaining the effects of prebiotic exopolysaccharide on inflammatory bowel disease (IBD).

ABSTRACTIt has been proved that lighting has nonvisual effects on the human body, including changes in heart rate and blood pressure. Heart rate and blood pressure are associated with the autonomic nervous system and can indicate stress level. The present study investigates whether heart rate and blood pressure are influenced by the frequency or duty cycle of pulsed light, together with the duration of lighting. Twelve healthy young subjects were recruited for the investigation. Subjects were exposed to pulsed light of varying frequencies (40 Hz, 100 Hz, 300 Hz) and duty cycles (10%, 50%, 90%). Exposure time was divided into two groups: short-time (20 min) and long-time (3 hours). Heart rate and blood pressure were measured during the experiments. Results showed that after a short lighting period (20 min), heart rate and blood pressure were significantly higher under 40 Hz pulsed than that under stable light, while 100 Hz and 300 Hz had no significant difference. After 3 hours of exposure time, the two indices became higher under 100 Hz (no flicker perceived with eyes) with 10% duty cycle, while 50% and 90% duty cycle showed no significant difference. These findings indicate that pulsed light will cause a deviation of heart rate and blood pressure from that under stable light.

To overcome the defect of the significant increase in pressure drop when the heat transfer performance of helical baffle heat exchanger is improved, a novel helical baffle heat exchanger with twisted oval tube is proposed. Numerical simulation was done to exhibit the shell side heat transfer and flow characteristics with CFD software Fluent. The field synergy principle was used to evaluate the shell side performance. The results show that the flow velocity distribution on the shell side of the spiral baffle heat exchanger is more uniform and the velocity near the tube wall increases in the range of research parameters, as the circular tube is replaced by a twisted elliptical tube with the same perimeter length. Moreover, the helical baffle heat exchanger with twisted oval tube has better field synergy of velocity and temperature gradient, velocity and pressure gradient. The helical baffle heat exchanger with helix angle of 15° has better performance than that of circular tube, and its heat transfer coefficient is improved about 3.3% and pressure drop is reduced by 17.1%–19.1%. Hence, the comprehensive heat transfer performance is improved by 21.5%–22.5%. When the helix angle is 20°, the comprehensive heat transfer performance is increased by 16.1%–18.0% with heat transfer coefficient improvement of 3.6% and pressure drop reduction of 13.9%–16.5%.

The surface effect induced transformation texture during vacuum annealing of cold-rolled high manganese transformation-induced plasticity (TRIP) steels was studied. Due to Mn removal occurring at the surface layer, γ → δ diffusional phase transformation leads to the formation of hard pancake-shaped ferrite grains due to solution strengthening at the surface and the centre layer remains as austenite + martensite after annealing. In the case of slow heating, {112}/{111}<110> textures for the surface ferrite were strengthened with the increase in temperature and holding time, indicating an inheritance of rolling textures. By increasing the heating rate of annealing, the rotated cube texture was developed in surface ferrite. This kind of multiphase sandwich structure with hard ferrite surface layer and tough austenite dominant centre can increase tensile strength and should also improve deep drawing properties, therefore providing new possibility of controlling properties for the application of high manganese TRIP steel.

Dear Editor, Any fault of a battery system that is not handled timely can cause catastrophic consequences. Therefore, it is significant to diagnose battery faults early and accurately. Due to the complex nonlinear features and inconsistency of lithium batteries, traditional fault diagnosis methods usually fail to detect battery minor faults in the early stages. Therefore, this letter proposes a real-time unsupervised learning diagnosis approach for early battery faults based on improved principal component analysis. The technique rotates the battery pack voltage sequence into a new coordinate space through linear combination, while the detection metrics of square prediction errors and modified contribution plots are employed to achieve minor fault traceability. In addition, the training sample relies on the voltage sequence of the battery health state instead of the fault data, which is difficult to collect. Moreover, this approach can not only locate the battery cell where the fault occurs but also diagnose battery open-circuit and short-circuit faults as well as the occurrence and duration of the fault in real-time. Furthermore, the feasibility and stability of the proposed method are verified by applying different experimental data. In summary, the presented approach provides an easy-to-implement option that does not require accurate mathematical modeling, expert understanding, and complex computational processes.

A new Brønsted acid-catalyzed oxo-cyclization of propargyl alcohols with azlactones to synthesize C2-azlactonized 2H-chromenes has been established that uses 1,1′-binaphthyl-2,2′-diyl hydrogen phosphate (BiNPO4H) as the catalyst and gives excellent diastereoselectivities (≥19:1 dr) in most cases. This protocol has a high compatibility with various substituents of substrates, offering a catalytic and useful entry to the fabrication of the synthetically important C2-functionalized 2H-chromene scaffold.