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The neutron-induced total cross sections of natural lead have been measured in a wide energy range (0.3 eV–20 MeV) on the back-streaming white neutron beamline (Back-n) at the China Spallation Neutron Source. Neutron energy was determined by the neutron total cross-section spectrometer using the time-of-flight technique. A fast multi-cell fission chamber was used as the neutron detector, and a 10-mm-thick high-purity natural lead sample was employed for the neutron transmission measurements. The on-beam background was determined using Co, In, Ag, and Cd filters. The excitation function of natPb(n, tot) reaction below 20 MeV was calculated using the TALYS-1.96 nuclear-reaction modeling program. The present results were compared with previous results, the evaluated data available in the five major evaluated nuclear data libraries (i.e., ENDF/B-VIII.0, JEFF-3.3, JENDL-5, CENDL-3.2, and BROND-3.1), and the theoretical calculation curve. Good agreement was found between the new results and those of previous experiments and with the theoretical curves in the corresponding region. This measurement obtained the neutron total cross section of natural lead with good accuracy over a wide energy range and added experimental data in the resonance energy range. This provides more reliable experimental data for nuclear engineering design and nuclear data evaluation of lead.

The neutron total cross-section of Cr plays a crucial role in new nuclear engineering design and fundamental science. A new measurement of the neutron-induced total cross-sections of Cr was performed using the transmission method on the back-streaming white neutron beamline (Back-n) at the China Spallation Neutron Source (CSNS). The neutron energy was determined using the time-of-flight technique. The neutron total cross-sections of Cr were obtained across a broad energy range (0.3 eV−20 MeV) in one experiment for the first time. The resulting effective total cross-sections were compared with the existing experimental data in different energy ranges, which revealed good agreement with the evaluated libraries. Theoretical calculation of the total cross-section in the energy range of 1.5 to 20 MeV was then conducted using TALYS-1.96 and compared with the present results. The measurement provides a high-quality total cross-section of Cr, including detailed uncertainty data across a wide energy range, offering a valuable reference for nuclear data re-evaluation and nuclear engineering design.

We have performed a test run for laser cooling experiments with ¹²C³⁺ ion beams at an energy of 122 MeV/u at the CSRe with a pulsed laser. During this beamtime a lot of progress have been made. This was the first time we could successfully separate the ¹²C³⁺ ions and ¹⁶O⁴⁺ ions in the Schottky spectrum with the help of electron cooling. And our newly installed CPM detector worked well during the experiment. We tried to see effects from the interaction of the pulsed laser light with the stored ¹²C³⁺ ion beams, but no cooling effects could yet be observed.

Given that it was a once-in-a-century emergency event, the confinement measures related to the coronavirus disease 2019 (COVID-19) pandemic caused diverse disruptions and changes in life and work patterns. These changes significantly affected water consumption both during and after the pandemic, with direct and indirect consequences on biodiversity. However, there has been a lack of holistic evaluation of these responses. Here, we propose a novel framework to study the impacts of this unique global emergency event by embedding an environmentally extended supply-constrained global multi-regional input-output model (MRIO) into the drivers-pressure-state-impact-response (DPSIR) framework. This framework allowed us to develop scenarios related to COVID-19 confinement measures to quantify country-sector-specific changes in freshwater consumption and the associated changes in biodiversity for the period of 2020-2025. The results suggest progressively diminishing impacts due to the implementation of COVID-19 vaccines and the socio-economic system's self-adjustment to the new normal. In 2020, the confinement measures were estimated to decrease global water consumption by about 5.7% on average across all scenarios when compared with the baseline level with no confinement measures. Further, such a decrease is estimated to lead to a reduction of around 5% in the related pressure on biodiversity. Given the interdependencies and interactions across global supply chains, even those countries and sectors that were not directly affected by the COVID-19 shocks experienced significant impacts: Our results indicate that the supply chain propagations contributed to 79% of the total estimated decrease in water consumption and 84% of the reduction in biodiversity loss on average. Our study demonstrates that the MRIO-enhanced DSPIR framework can help quantify resource pressures and the resultant environmental impacts across supply chains when facing a global emergency event. Further, we r

Evaluating disruptions in public transport (PT) utilisation is challenging due to often stochastic traveller behaviour and missing data information on affected services. This paper proposes a new approach for modelling PT patronage and disruption impact using integrated data-driven modelling and the Fourier transform technique. Firstly, using tap-on and off information of smart-card data, we estimate in-vehicle passenger numbers to integrate as well as trips passing through the incident area. Secondly, considering the PT patronage pattern as a periodic function, we employ the Fourier transform to convert it into a sum of simpler trigonometric functions to filter out the one representing common data noise successfully and generate an accurate profile for a typical day. Thirdly, we introduce an enhanced sensitivity test to improve the model's ability to identify the impact of the disruption. Finally, multiple impact measurement methods are compared to capture the disruption impact. The findings demonstrate the effectiveness of leveraging in-vehicle count to maximise data volume and enhance impact identification. The PT patronage pattern can be effectively modelled using the Fourier transform. The utilisation of the enhanced sensitivity test can effectively filter out unnecessary trigonometric components, resulting in a refined model capable of accurately identifying the impact of disruption.

Converter blown limestone powder steelmaking process has the advantages of energy saving and high efficiency to meet the needs of low carbon metallurgy. Based on a thermogravimetric-differential thermal analyzer, the effect of high CO2 partial pressure on the pyrolysis behavior of limestone at steelmaking temperatures was investigated at 20 °C/min, 30 °C/min, and 40 °C/min, the kinetic parameters of limestone pyrolysis were calculated by the improved double extrapolation method.

Epidemic outbreaks can cause critical health concerns and severe global economic crises. For countries or regions with new infectious disease outbreaks, it is essential to generate preventive strategies by learning lessons from others with similar risk profiles. A Strategy Transfer and Decision Support Approach (STDSA) is proposed based on the profile similarity evaluation. There are four steps in this method: (1) The similarity evaluation indicators are determined from three dimensions, i.e., the Basis of National Epidemic Prevention & Control, Social Resilience, and Infection Situation. (2) The data related to the indicators are collected and preprocessed. (3) The first round of screening on the preprocessed dataset is conducted through an improved collaborative filtering algorithm to calculate the preliminary similarity result from the perspective of the infection situation. (4) Finally, the K-Means model is used for the second round of screening to obtain the final similarity values. The approach will be applied to decision-making support in the context of COVID-19. Our results demonstrate that the recommendations generated by the STDSA model are more accurate and aligned better with the actual situation than those produced by pure K-means models. This study will provide new insights into preventing and controlling epidemics in regions that lack experience., Comment: 20 pages, 9 figures

The neutron-induced total cross-section of 209Bi is crucial for the physical design and safety assessment of lead-based fast reactors, and the quality of experimental data should be improved for evaluation and application. A recent experiment was conducted on the back-streaming white neutron beamline (Back-n) at the China Spallation Neutron Source (CSNS) using the neutron total cross-section spectrometer (NTOX). The neutron energy was determined using a fast multi-cell fission chamber and the time-of-flight technique. Two high-purity bismuth samples, 6 mm and 20 mm in thickness, were chosen for neutron transmission measurements and comparisons. The neutron total cross-sections of 209Bi, ranging from 0.3 eV to 20 MeV, were derived considering neutron flight time determination, flight path calibration, and background subtraction. A comparison of the experimental results with the data in the ENDF/B-VIII.0 library showed fair agreement, and the point-wise cross-sections were found to be consistent with existing experimental data. Special attention was given to the determination of resonance parameters, which were analyzed using the R -matrix code SAMMY and Bayesian method in the 0.5 keV to 20 keV energy range. The extracted resonance parameters were compared to previously reported results and evaluated data. This study is recognized as the first one where the neutron total cross-section of bismuth across such a broad energy spectrum is measured in a single measurement or experiment, and it provides valuable data for the assessment of related reaction information for evaluated libraries and the advancement of lead-bismuth-based nuclear systems.

Benzene and its aromatic derivatives are typical volatile organic compounds for indoor and outdoor air pollution, harmful to human health and the environment. It has been considered extremely difficult to break down benzene rings at ambient conditions without external energy input, due to the extraordinary stability of the aromatic structure. Here, we show one such solution that can thoroughly degrade benzene to basically water and carbon dioxide at 25 °C in air using atomically dispersed Fe in N-doped porous carbon, with almost 100% benzene conversion. Further experimental studies combined with molecular simulations reveal the mechanism of this catalytic reaction. Hydroxyl radicals (·OH) evolved on the atomically dispersed FeN4O2 catalytic centers were found responsible for initiating and completing the oxidation of benzene. This work provides a new chemistry to degrade aromatics at ambient conditions and also a pathway to generate active ·OH oxidant for generic remediation of organic pollutants.

This study quantified age-related changes to retinal autophagy using the CAG-RFP-EGFP-LC3 autophagy reporter mice and considered how aging impacts autophagic responses to acute intraocular pressure (IOP) stress. IOP was elevated to 50 mm Hg for 30 minutes in 3-month-old and 12-month-old CAG-RFP-EGFP-LC3 (n = 7 per age group) and Thy1-YFPh transgenic mice (n = 3 per age group). Compared with younger eyes, older eyes showed diminished basal autophagy in the outer retina, while the inner retina was unaffected. Autophagic flux (red:yellow puncta ratio) was elevated in the inner plexiform layer. Three days following IOP elevation, older eyes showed poorer functional recovery, most notably in ganglion cell responses compared to younger eyes (12 months old: -33.4 ± 5.3% vs. 3 months mice: -13.4 ± 4.5%). This paralleled a reduced capacity to upregulate autophagic puncta volume in the inner retina in older eyes, a response that was seen in younger eyes. Age-related decline in basal and stress-induced autophagy in the retina is associated with greater retinal ganglion cells' susceptibility to IOP elevation.

Estimation of the large-scale demand estimation for public transport in different cities can vary depending on the public transport network, public transport modes, and traffic data. To overcome the issue of traffic data shortage and effectively estimate the Origin-Destination (OD) matrix, we use the most accessible data: total boarding and alighting and public transport timetable, to capture the public transport dynamic patronage, and from this perspective, we establish a dynamic and microscopic OD matrix for public transport. In this paper, we propose a new method to model the dynamic large-scale stop-by-stop OD demand for public transport by developing a boosting of the gravity model via graph theory and Shannon's entropy. First, we propose a novel cost matrix estimation method that considers various sources of travel cost features extracted from both the traffic flow information in the traffic network and topological information in the graph network. Secondly, we proposed an ``Ensemble Cost Matrix Weighted by Entropy'' method to estimate the best weights of importance for each feature using Shannon's Entropy to maximise the performance of the cost matrix in OD matrix estimation. Third, we validate the proposed approach using real smart-card data. Last, by comparing the effectiveness of our proposed method with the traditional deterrence function-oriented methods, we prove that our proposed cost matrix estimation method cooperated OD matrix modelling method is superior in accurately OD matrix estimation to traditional methods by almost 54.46\% according to RMSE, 84.44\% according to MAPE, and 85.09\% according to MAE.

CLINICAL RELEVANCE: The use of chloroquine or hydroxychloroquine can lead to both acute and chronic changes to both retinal structure and function. BACKGROUND: Chloroquine (CQ) and hydroxychloroquine (HCQ) have the potential for retina toxicity. The acute impact of short-term drug exposure (2-4 weeks) on in vivo retinal structure and function and assess whether short wavelength light exposure further exacerbates any structural and functional changes was assessed in a murine model. METHODS: Adult C57BL/6 J mice received intraperitoneal injection of vehicle or hydroxychloroquine (10 mg/kg) 3 times per week for 2 or 4 weeks, or chloroquine for 4 weeks (10 mg/kg). Over this period, animals were exposed to room light (8 hours) or short-wavelength light 4 hours per day (4 hours of normal room light) for 5 days each week. Retinal changes were assessed using electroretinography (ERG), in vivo optical coherence tomography (OCT) imaging. RESULTS: Short-term low-dose HCQ and CQ treatment led to RPE thickening and elongation of photoreceptors. These structural changes were associated with a no dysfunction in the case of HCQ treatments and widespread functional changes (photoreceptor sensitivity, bipolar cell amplitude and oscillatory potential amplitude) in the case of CQ treatment. Exposure to low intensity short-wavelength light does not appear to alter the effect of HCQ or CQ. CONCLUSIONS: HCQ and CQ treatment has acute effects on both retinal structure and function, effects that were not exacerbated by short wavelength light exposure. Whether chronic short wavelength light exposure exacerbates these changes require further study.

Bismuth(III) sulfide (Bi2S3) is a promising cathode material for aqueous zinc ion batteries (ZIBs), yet suffers from serious capacity issues due to its poor electrical conductivity and microstructural degradations. In this work, Bi2S3 anchored on reduced graphene oxide (rGO) is prepared through hydrothermal reaction and is used as cathode material for aqueous ZIBs. Raman and XPS characterizations confirmed that the oxygen bridge in Bi–O–C heterostructures is successfully created during the hydrothermal synthesis. These oxygen bridges are energy favourable in the Bi2S3/rGO composite materials and serve as the electron transfer channels for rapid charge compensation during Zn2+ incorporation/extraction. Rotating ring–disc electrode (RRDE) measurements demonstrate improved electrochemical stability of the Bi2S3/rGO composite material compared to pristine Bi2S3. As a result of these improved characteristics, Bi2S3/rGO composite shows notably better rate performance and cycling stability than unsupported Bi2S3. Ex-situ X-ray diffraction and XPS characterizations indicate that Zn2+ undergoes a reversible conversion reaction with Bi2S3 to form ZnS/Bi0, rather than being intercalated into Bi2S3 crystal interlayers. The rGO substrate forms chemical bonds with bismuth in the composite material, and the strongly anchored bismuth on the rGO through a Bi–O–C bridge enables a highly reversible conversion reaction. As a result, the Bi2S3/rGO composite with 8 wt% rGO can deliver a reversible capacity of ∼186 mAh g−1 at the current density of 500 mA g−1 after 150 cycles, showing high promise as Zn-ion battery material.

Pathogenic variants in HCN1 are associated with a range of epilepsy syndromes including a developmental and epileptic encephalopathy. The recurrent de novo HCN1 pathogenic variant (M305L) results in a cation leak, allowing the flux of excitatory ions at potentials where the wild-type channels are closed. The Hcn1M294L mouse recapitulates patient seizure and behavioral phenotypes. As HCN1 channels are highly expressed in rod and cone photoreceptor inner segments, where they shape the light response, mutated channels are likely to impact visual function. Electroretinogram (ERG) recordings from male and female mice Hcn1M294L mice revealed a significant decrease in the photoreceptor sensitivity to light, as well as attenuated bipolar cell (P2) and retinal ganglion cell responses. Hcn1M294L mice also showed attenuated ERG responses to flickering lights. ERG abnormalities are consistent with the response recorded from a single female human subject. There was no impact of the variant on the structure or expression of the Hcn1 protein in the retina. In silico modeling of photoreceptors revealed that the mutated HCN1 channel dramatically reduced light-induced hyperpolarization, resulting in more Ca2+ flux during the response when compared with the wild-type situation. We propose that the light-induced change in glutamate release from photoreceptors during a stimulus will be diminished, significantly blunting the dynamic range of this response. Our data highlight the importance of HCN1 channels to retinal function and suggest that patients with HCN1 pathogenic variants are likely to have a dramatically reduced sensitivity to light and a limited ability to process temporal information.SIGNIFICANCE STATEMENT Pathogenic variants in HCN1 are emerging as an important cause of catastrophic epilepsy. HCN1 channels are ubiquitously expressed throughout the body, including the retina. Electroretinogram recordings from a mouse model of HCN1 genetic epilepsy showed a marked decrease in

The central engine that powers gamma-ray bursts (GRBs), the most powerful explosions in the universe, is still not identified. Besides hyper-accreting black holes, rapidly spinning and highly magnetized neutron stars, known as millisecond magnetars, have been suggested to power both long and short GRBs. The presence of a magnetar engine following compact star mergers is of particular interest as it would provide essential constraints on the poorly understood equation of state for neutron stars. Indirect indications of a magnetar engine in these merger sources have been observed in the form of plateau features present in the X-ray afterglow light curves of some short GRBs. Additionally, some X-ray transients lacking gamma-ray bursts (GRB-less) have been identified as potential magnetar candidates originating from compact star mergers. Nevertheless, smoking gun evidence is still lacking for a magnetar engine in short GRBs, and the associated theoretical challenges have been addressed. Here we present a comprehensive analysis of the broad-band prompt emission data of a peculiar, very bright GRB 230307A. Despite its apparently long duration, the prompt emission and host galaxy properties point toward a compact star merger origin, being consistent with its association with a kilonova. More intriguingly, an extended X-ray emission component emerges as the $\gamma$-ray emission dies out, signifying the emergence of a magnetar central engine. We also identify an achromatic temporal break in the high-energy band during the prompt emission phase, which was never observed in previous bursts and reveals a narrow jet with half opening angle of approximately $3.4^\circ$., Comment: 44 pages, 10 figures, 5 tables

The Lobster Eye Imager for Astronomy (LEIA), a pathfinder of the Wide-field X-ray Telescope of the Einstein Probe (EP) mission, was successfully launched onboard the SATech-01 satellite of the Chinese Academy of Sciences on 27 July 2022. In this paper, we introduce the design and on-ground test results of the LEIA instrument. Using state-of-the-art Micro-Pore Optics (MPO), a wide field-of-view (FoV) of 346 square degrees (18.6 degrees * 18.6 degrees) of the X-ray imager is realized. An optical assembly composed of 36 MPO chips is used to focus incident X-ray photons, and four large-format complementary metal-oxide semiconductor (CMOS) sensors, each of 6 cm * 6 cm, are used as the focal plane detectors. The instrument has an angular resolution of 4 - 8 arcmin (in FWHM) for the central focal spot of the point spread function, and an effective area of 2 - 3 cm2 at 1 keV in essentially all the directions within the field of view. The detection passband is 0.5 - 4 keV in the soft X-rays and the sensitivity is 2 - 3 * 10-11 erg s-1 cm-2 (about 1 mini-Crab) at 1,000 second observation. The total weight of LEIA is 56 kg and the power is 85 W. The satellite, with a design lifetime of 2 years, operates in a Sun-synchronous orbit of 500 km with an orbital period of 95 minutes. LEIA is paving the way for future missions by verifying in flight the technologies of both novel focusing imaging optics and CMOS sensors for X-ray observation, and by optimizing the working setups of the instrumental parameters. In addition, LEIA is able to carry out scientific observations to find new transients and to monitor known sources in the soft X-ray band, albeit limited useful observing time available., Comment: Accepted by RAA

Neural knowledge models emerged and advanced common-sense-centric knowledge grounding. They parameterize a small seed curated commonsense knowledge graph (CS-KG) in a language model to generalize more. A current trend is to scale the seed up by directly mixing multiple sources of CS-KG (e.g., ATOMIC, ConceptNet) into one model. But, such brute-force mixing inevitably hinders effective knowledge consolidation due to i) ambiguous, polysemic, and/or inconsistent relations across sources and ii) knowledge learned in an entangled manner despite distinct types (e.g., causal, temporal). To mitigate this, we adopt a concept of commonsense knowledge dimension and propose a brand-new dimension-disentangled knowledge model ((DKM)-K-2) learning paradigm with multiple sources. That is, a generative language model with dimension-specific soft prompts is trained to disentangle knowledge acquisitions along with different dimensions and facilitate potential intra-dimension consolidation across CS-KG sources. Experiments show our knowledge model outperforms its baselines in both standard and zero-shot scenarios.

To address the problem of insufficient ductility of traditional Carbon Fibre-reinforced polymer (CFRP) strengthened marine structures and to enhance the application of CFRP in marine engineering, the present study develops novel prestressed CFRP-strengthened RC beams using H-type end anchors with ductility controllable devices. In this device, part of the reinforcement bars are replaced by CFRP, which is prestressed as the structural enhancement material. The CFRP sheet is connected with a tensioned screw, which is used to realize the function of early warning based on a large plastic deformation when the structure is overloaded. Thus, the ductility of the composite structure could be improved based on yielding of the screw rod rather than the fracture failure of the CFRP sheet compared to that with CFRP bonded. This study investigates the flexural static and impact performance of the representative large-scale RC beams strengthened by prestressed CFRP through four-point bending and drop-weight impact. The results show that the H-typed end anchor and raising the prestress level of CFRP not only improve the ultimate resistance and ductility, but also realize the overload warning function under static load. Accordingly, the design still shows advantages in energy consumption and impact resistance through drop-weight impact. An advanced 3D nonlinear finite element model is built to simulate well the multiple impact performance in terms of the failure modes, impact force and displacement history. This study provides a new approach to address design deficiencies with insufficient ductility behaviour while using CFRP as a strengthening material. This prestressing technology is able to utilize the material efficiency of high-strength CFRP and open a new path for CFRP applications in marine civil engineering.

Aging and elevated intraocular pressure (IOP) are two major risk factors for glaucomatous optic neuropathy; a condition characterized by the selective, progressive injury, and subsequent loss of retinal ganglion cells (RGCs). We examined how age modified the capacity for RGCs to functionally recover following a reproducible IOP elevation (50 mmHg for 30 min). We found that RGC functional recovery (measured using electroretinography) was complete by 7 days in 3-month-old mice but was delayed in 12-month-old mice until 14 days. At the 7-day recovery endpoint when RGC function had recovered in young but not older eyes, we examined RGC structural responses to IOP-related stress by analyzing RGC dendritic morphology. ON-RGC cell volume was attenuated following IOP elevation in both young and older mice. We also found that following IOP elevation OFF-RGC dendritic morphology became less complex per cell volume in young mice, an effect that was not observed in older eyes. Our data suggest that adaptations in OFF-RGCs in young eyes were associated with better functional recovery 7 days after IOP elevation. Loss of RGC cellular adaptations may account for delayed functional recovery in older eyes.

Shortening inter-vehicle distance can increase traffic throughput on roads for increasing volume of vehicles. In the process, traffic accidents occur more frequently, especially for multi-car accidents. Furthermore, it is difficult for drivers to drive safely under such complex driving conditions. This article investigates multi-vehicle longitudinal collision avoidance issue under such traffic conditions based on the Advanced Emergency Braking System (AEBS). AEBS is used to avoid collisions or mitigate the impact during critical situations by applying brake automatically. Hierarchical multi-vehicle longitudinal collision avoidance controller is proposed to guarantee safety of multi-cars using Vehicle-to-Infrastructure (V2I) communication capability in addition to radar for longitudinal vehicle control. High-level controller is designed to ensure safety of multi-cars and optimize total energy by calculating the target braking force. Vehicle network is used to get the key vehicle-road interaction data and constrained hybrid genetic algorithm (CHGA) is adopted to decouple the vehicle-road interactive system,which can obtain the maximum ground friction through vehicle-road data, and provide key predictive parameters for multi-vehicle safety controller. Lower level non-singular Fractional Terminal Sliding Mode(NFTSM) Controller is built to achieve control goals of high-level controller. Simulations are carried out under typical driving conditions. Results verify that the proposed system in this article can avoid or mitigate the collision risk compared to the vehicle without this system. © 1967-2012 IEEE.

The scientific outcomes of the 2022 Landslide4Sense (L4S) competition organized by the Institute of Advanced Research in Artificial Intelligence are presented here. The objective of the competition is to automatically detect landslides based on large-scale multiple sources of satellite imagery collected globally. The 2022 L4S aims to foster interdisciplinary research on recent developments in deep learning (DL) models for the semantic segmentation task using satellite imagery. Over the past few years, DL-based models have achieved performance that meets expectations on image interpretation due to the development of convolutional neural networks. The main objective of this article is to present the details and the best-performing algorithms featured in this competition. The winning solutions are elaborated with state-of-the-art models, such as the Swin Transformer, SegFormer, and U-Net. Advanced machine learning techniques and strategies, such as hard example mining, self-training, and mix-up data augmentation, are also considered. Moreover, we describe the L4S benchmark dataset in order to facilitate further comparisons and report the results of the accuracy assessment online. The data are accessible on Future Development Leaderboard for future evaluation at https://www.iarai.ac.at/landslide4sense/challenge/ , and researchers are invited to submit more prediction results, evaluate the accuracy of their methods, compare them with those of other users, and, ideally, improve the landslide detection results reported in this article.

Medical data mainly includes various types of biomedical signals and medical images, which can be used by professional doctors to make judgments on patients' health conditions. However, the interpretation of medical data requires a lot of human cost and there may be misjudgments, so many scholars use neural networks and deep learning to classify and study medical data, which can improve the efficiency and accuracy of doctors and detect diseases early for early diagnosis, etc. Therefore, it has a wide range of application prospects. However, traditional neural networks have disadvantages such as high energy consumption and high latency (slow computation speed). This paper presents recent research on signal classification and disease diagnosis based on a third-generation neural network, the spiking neuron network, using medical data including EEG signals, ECG signals, EMG signals and MRI images. The advantages and disadvantages of pulsed neural networks compared with traditional networks are summarized and its development orientation in the future is prospected.

Nanoplastics (NPs) pollution of aquatic systems is becoming an emerging environmental issue due to their stable structure, high mobility, and easy interactions with ambient contaminants. Effective removal technologies are urgently needed to mitigate their toxic effects. In this study, we systematically investigated the removal effectiveness and mechanisms of a commonly detected nanoplastics, carboxyl-modified polystyrene (PS-COOH) via coagulation and sedimentation processes using aluminum chloride (AlCl3) as a coagulant. PS-COOH appeared as clearly defined and discrete spherical nanoparticles in water with a hydrodynamic diameter of 50 nm. The addition of 10 mg/L AlCl3 compressed and even destroyed the negatively charged PS-COOH surface layer, decreased the energy barrier, and efficiently removed 96.6% of 50 mg/L PS-COOH. The dominant removal mechanisms included electrostatic adsorption and intermolecular interactions. Increasing the pH from 3.5 to 8.5 sharply enhanced the PS-COOH removal, whereas significant loss was observed at pH 10.0. High temperature (23 °C) favored the removal of PS-COOH compared to lower temperature (4 °C). High PS-COOH removal efficiency was observed over the salinity range of 0 - 35‰. The presence of positively charged Al2O3 did not affect the PS-COOH removal, while negatively charged SiO2 reduced the PS-COOH removal from 96.6% to 93.2%. Moreover, the coagulation and sedimentation process efficiently removed 90.2% of 50 mg/L PS-COOH in real surface water even though it was rich in inorganic ions and total organic carbon. The fast and efficient capture of PS-COOH by AlCl3 via a simple coagulation and sedimentation process provides a new insight for the treatment of NPs from aqueous environment.

To achieve sustainable development, local governments are under enormous pressure to simultaneously achieve the three assessment tasks (TATs) of energy saving, CO₂ reduction, and pollution reduction. However, the TATs are often managed by different authorities and have three types of measures (TTMs) that correspond to them. The lack of adequate cooperation between these authorities has led to the inefficient investment of policy resources and even to policy conflicts, and the interactions among the TTMs are not yet known. To this end, this paper uses the MCEE model to assess the interactions among the TTMs quantitatively using Guangzhou, China, as a case study. The results showed the following. (1) According to the current development trend, if the authorities managing the TATs continue to work alone, they will not be able to fulfill the corresponding assessment tasks in the future. (2) The TTMs have interactions with each other, and their synergies are far greater than their trade-offs. From 2015 to 2035, it is expected that energy-saving measures can accomplish 54.39% of the CO₂ reduction tasks and 32.74% of the pollution reduction tasks indirectly, and low-carbon measures can accomplish 55.53% of the energy saving tasks and 27.20% of the pollution reduction tasks indirectly, However, environmental-protection measures will cause fewer trade-offs (energy demand and CO2 emissions increase by 3.76% and 2.88%, respectively). (3) In some years, the contribution of interactions among the TTMs are even higher than their direct contribution to the TATs. Our findings suggest that intensive cooperation between authorities is necessary, and that the benefits of such cooperation will outweigh the disadvantages.

Most computational hemodynamic studies of aortic dissections rely on idealized or general boundary conditions. However, numerical simulations that ignore the characteristics of the abdominal branch arteries may not be conducive to accurately observing the hemodynamic changes below the branch arteries. In the present study, two men (M-I and M-II) with type B aortic dissection (TBAD) underwent arterial-phase computed tomography angiography and four-dimensional flow magnetic resonance imaging (MRI) before and after thoracic endovascular aortic repair (TEVAR). The finite element method was used to simulate the computational fluid dynamic parameters of TBAD [false lumen (FL) with or without visceral artery involvement] under MRI-specific and three idealized boundary conditions in one cardiac cycle. Compared to the results of zero pressure and outflow boundary conditions, the simulations with MRI boundary conditions were closer to the initial MRI data. The pressure difference between TL and FL after TEVAR under the other three boundary conditions was lower than that of the MRI-specific results. The results of the outflow boundary conditions could not characterize the effect of the increased wall pressure near the left renal artery caused by the impact of Tear-1, which raised concerns about the distal organ and limb perfused by FL. After TEVAR, the flow velocity and wall pressure in the FL and the distribution areas of high time average wall shear stress and oscillating shear index were reduced. The difference between the calculation results for different boundary conditions was lower in M-II, wherein FL did not involve the abdominal aorta branches than in M-I. The boundary conditions of the abdominal branch arteries from MRI data might be valuable in elucidating the hemodynamic changes of the descending aorta in TBAD patients before and after treatment, especially those with FL involving the branch arteries.

As a novel X-ray focusing technology, lobster eye micro-pore optics (MPO) feature both a wide observing field of view and true imaging capability, promising sky monitoring with significantly improved sensitivity and spatial resolution in soft X-rays. Since first proposed by Angel (1979), the optics have been extensively studied, developed and trialed over the past decades. In this Letter, we report on the first-light results from a flight experiment of the Lobster Eye Imager for Astronomy ($LEIA$), a pathfinder of the wide-field X-ray telescope of the Einstein Probe mission. The piggyback imager, launched in July 2022, has a mostly un-vignetted field of view of $18.6^\circ \times 18.6^\circ $. Its spatial resolution is in the range of 4$-$7 arcmin in FWHM and the focal spot effective area is 2$-$3 cm$^2$, both showing only mild fluctuations across the field of view. We present images of the Galactic center region, Sco X-1 and the diffuse Cygnus Loop nebular taken in snapshot observations over 0.5$-$4 keV. These are truly wide-field X-ray images of celestial bodies observed, for the first time, by a focusing imaging telescope. Initial analyses of the in-flight data show excellent agreement between the observed images and the on-ground calibration and simulations. The instrument and its characterization are briefly described, as well as the flight experiment. The results provide a solid basis for the development of the present and proposed wide-field X-ray missions using lobster eye MPO., Comment: 11 pages, 4 figures. Accepted for publication in Astrophysical Journal Letter

We report the phase-connected timing ephemeris, polarization pulse profiles, Faraday rotation measurements, and Rotating-Vector-Model (RVM) fitting results of twelve millisecond pulsars (MSPs) discovered with the Five-hundred-meter Aperture Spherical radio Telescope (FAST) in the Commensal radio Astronomy FAST survey (CRAFTS). The timing campaigns were carried out with FAST and Arecibo over three years. Eleven of the twelve pulsars are in neutron star - white dwarf binary systems, with orbital periods between 2.4 and 100 d. Ten of them have spin periods, companion masses, and orbital eccentricities that are consistent with the theoretical expectations for MSP - Helium white dwarf (He WD) systems. The last binary pulsar (PSR J1912$-$0952) has a significantly smaller spin frequency and a smaller companion mass, the latter could be caused by a low orbital inclination for the system. Its orbital period of 29 days is well within the range of orbital periods where some MSP - He WD systems have shown anomalous eccentricities, however, the eccentricity of PSR J1912$-$0952 is typical of what one finds for the remaining MSP - He WD systems., Comment: 11 pages, 5 figures, MNRAS accepted

This paper reviews the first NTIRE challenge on perceptual image enhancement with the focus on proposed solutions and results. The participating teams were solving a real-world photo enhancement problem, where the goal was to map low-quality photos from the iPhone 3GS device to the same photos captured with Canon 70D DSLR camera. The considered problem embraced a number of computer vision subtasks, such as image denoising, image resolution and sharpness enhancement, image color/contrast/exposure adjustment, etc. The target metric used in this challenge combined PSNR and SSIM scores with solutions' perceptual results measured in the user study. The proposed solutions significantly improved baseline results, defining the state-of-the-art for practical image enhancement.

Knowledge about topsoil (0–0.3 m) clay is required to maintain sugarcane profitability in Queensland, Australia. However, laboratory analysis to get this knowledge is tedious and time consuming. To add value to limited clay data, a digital soil map (DSM) can be created by using digital data and mathematical models. At the field level, site-specific linear regression (LR) models are often used along with gamma-ray (γ-ray) spectrometry and electromagnetic induction data (i.e. soil apparent electrical conductivity – ECa). But these LR might not perform well in site-independent calibrations across multiple sites. In this regard, support vector machine (SVM) might be useful. In this research, we first aimed to determine, using a stepwise SVM and calibration dataset, the optimal digital data (i.e. individual or combined) to develop local (for each individual site) and universal (for combined sites) SVM models. Using optimal digital data, our second aim was to predict clay for validation datasets by using local SVM in site-specific approach and universal SVM in site-independent, holdout and spiking approaches. Using these approaches, DSM of predicted clay and associated uncertainty were generated for a representative study site (i.e., Mossman). The third aim was to determine the suitable number of spiking samples and by varying the size of both spiking set and calibration model. Approaches were compared using prediction agreement (Lin's concordance) and accuracy (ratio of performance to deviation – RPD). We concluded from stepwise SVM that combining digital data resulted in better accuracy (RPD = 2.17) than individual γ-ray (1.79) or ECa (1.49) data. In terms of independent validation, the results of Mossman reflected the general rank order of different approaches with site-specific (3.03) excellent, spiking (1.89) very good, site-independent (1.84) good and holdout (1.18) poor predictions. In case of DSM and uncertainty maps, under-predictions were problematic at field ed

Важность исследования принципов, методов и стратегий перевода названий блюд китайской кухни на русский язык в последние годы привлекает внимание всё большего числа учёных и специализированных академических учреждений в связи с глобализацией мировой экономики. Этот вид культурной коммуникативной деятельности предполагает не только преобразование языковых символов, но и интеграцию культур. В то время как язык является частью культуры, зарубежное развитие и рост индустрии общественного питания в Китае является важной частью мировой экономической деятельности. Русский перевод названий китайских блюд больше не является чисто литературным переводом текста. В известном смысле это должна быть некоторая внешняя коммуникационная деятельность или даже полноценная внешнеэкономическая деятельность. Качество русского перевода названий китайских блюд во многом напрямую влияет на масштабы и эффективность развития китайской индустрии общественного питания в России. Однако в силу культурных различий и других причин существует множество трудностей с переводом названий китайских блюд на русский язык. Это требует использования необходимых приёмов перевода названий китайских блюд на русский язык, чтобы переведённые названия полностью отражали региональные и национальные особенности китайской кухни. На основе исследования китайского переводчика Бао Хуэйнаня и британского переводчика Taylor по переводу названий блюд в данной статье обобщаются проблемы перевода названий китайских блюд на русский язык. Автор статьи пытается теоретически решить проблемы, возникающие при переводе китайских названий блюд на русский язык. По словам переводчиков Carl и Taylor, поиск подходящего метода перевода для различных ситуаций перевода – лучшая стратегия. Что касается культурных различий, встречающихся при переводе названий китайских блюд на русский язык, рекомендуется, чтобы переводчики рассмотрели и изучили эти две стратегии диалектически, исторически, а не статически и абсолютно. Согласно изложенным выше, The relevance of the work. The importance of researching the principles, methods, and strategies for translating the names of Chinese dishes into Russian in recent years has attracted the attention of an increasing number of scientists and specialized academic institutions in connection with the globalization of the world economy. This type of cultural communication activity involves not only the transformation of linguistic symbols but also the integration of cultures. While language is part of the culture, the overseas development, and growth of China's foodservice industry is an important part of global economic activity. The Russian translation of the names of Chinese dishes is no longer a purely literary translation of the text. In a sense, this should be external communication activity or even a full-fledged foreign economic activity. The quality of the Russian translation of the names of Chinese dishes in many ways directly affects the scale and effectiveness of the development of the Chinese catering industry in Russia. However, due to cultural differences and other reasons, there are many difficulties in translating the names of Chinese dishes into Russian. This requires the use of the necessary techniques for translating the names of Chinese dishes into Russian so that the translated names fully reflect the regional and national characteristics of Chinese cuisine. Based on the research of Chinese translator Bao Huinan and British translator Taylor on the translation of dish names, this article summarizes the problems of the translation of Chinese dish names into Russian. The author of this article attempts to find a solution to the problems encountered in translating Chinese dish names into Russian on a theoretical basis. According to translators Carl and Taylor, finding a suitable translation method according to different translation situations is the best strategy. Regarding the cultural differences encountered in translating Chinese dish names into Russ

Management of Vertosols in southeast Australia, requires information about soil physical (e.g. particle size fractions) and chemical (e.g. cation exchange capacity [CEC – cmol(+) kg−1], exchangeable sodium percentage [ESP - %] and pH) properties. While visible and near-infrared (vis-NIR) spectroscopy calibration models have been developed, little has been done in Vertosols. The performance of multi-depth or depth-specific (i.e. topsoil [0–0.3 m], subsurface [0.3–0.6 m] and subsoil [0.9–1.2 m]) calibration models has also seldom been discussed. In this paper, using a spiking approach across seven cotton growing areas, our first aim was to determine which model (e.g. machine learning algorithm (Cubist) or partial least square regression with bootstrap aggregation [bagging-PLSR]) produced better calibrations using multi-depth data. The second aim was to see how these calibrations predict depth-specific soil properties using independent validation. Our third aim was to investigate whether depth-specific calibrations could produce better predictions. In terms of multi-depth calibration, exemplified by CEC, Cubist (R2 = 0.86) was stronger than bagging-PLSR (0.72). However, in terms of prediction agreement for independent validation, bagging-PLSR was superior to Cubist in the topsoil (LCCC = 0.84) and subsoil (0.83) and equivalent in the subsurface (0.74). Moreover, the depth-specific bagging-PLSR achieved equivelent prediction agreement for the independent validation of CEC to the multi-depth bagging-PLSR in the topsoil (LCCC = 0.85), subsoil (0.85) and subsurface (0.76). In terms of the other soil properties (i.e. clay, silt and sand), multi-depth bagging-PLSR was superior and overall a multi-depth spectral library is recommended for Vertosols. This has implications for acquiring a vis-NIR library more quickly and prediction efficiency with multi-depth calibrations.

Charge exchange between highly charged ions and neutral atoms and molecules has been considered as one of the important mechanisms controlling soft X ray emissions in many astrophysical objects and environments. However, for modeling charge exchange soft X ray emission, the data of n and l resolved state selective capture cross sections are often obtained by empirical and semiclassical theory calculations. With a newly built cold target recoil ion momentum spectroscopy (COLTRIMS) apparatus, we perform a series of measurements of the charge exchange of Ne(8,9)+ ions with He and H2 for collision energy ranging from 1 to 24.75 keV/u. n resolved state selective capture cross-sections are reported. By comparing the measured state selective capture cross sections to those calculated by the multichannel Landau Zener method (MCLZ), it is found that MCLZ calculations are in good agreement with the measurement for the dominant n capture for He target. Furthermore, by using nl resolved cross sections calculated by MCLZ and applying l distributions commonly used in the astrophysical literature to experimentally derived n resolved cross sections, we calculate the soft X ray emissions in the charge exchange between 4 keV/u Ne8+ and He by considering the radiative cascade from the excited Ne7+ ions. Reasonable agreement is found in comparison to the measurement for even and separable models, and MCLZ calculations give results in a better agreement.

The ionosphere plays an important role in satellite navigation, radio communication, and space weather prediction. However, it is still a challenging mission to develop a model with high predictability that captures the horizontal-vertical features of ionospheric electrodynamics. In this study, multiple observations during 2005–2019 from space-borne global navigation satellite system (GNSS) radio occultation (RO) systems (COSMIC and FY-3C) and the Digisonde Global Ionosphere Radio Observatory are utilized to develop a completely global ionospheric three-dimensional electron density model based on an artificial neural network, namely ANN-TDD. The correlation coefficients of the predicted profiles all exceed 0.96 for the training, validation and test datasets, and the minimum root-mean-square error of the predicted residuals is 7.8 × 104 el/cm3. Under quiet space weather, the predicted accuracy of the ANN-TDD is 30%–60% higher than the IRI-2016 at the Millstone Hill and Jicamarca incoherent scatter radars. However, the ANN-TDD is less capable of predicting ionospheric dynamic evolution under severe geomagnetic storms compared to the IRI-2016 with the STORM option activated. Additionally, the ANN-TDD successfully reproduces the large-scale horizontal-vertical ionospheric electrodynamic features, including seasonal variation and hemispheric asymmetries. These features agree well with the structure revealed by the RO profiles derived from the FORMOSAT/COSMIC-2 mission. Furthermore, the ANN-TDD successfully captures the prominent regional ionospheric patterns, including the equatorial ionization anomaly, Weddell Sea anomaly and mid-latitude summer nighttime anomaly. The new model is expected to play an important role in the application of GNSS navigation and in the explanation of the physical mechanisms involved.

Non-invasive intracranial pressure (ICP) monitoring is possible using venous ophthalmodynamometry to observe a pulsation in retinal blood vessels when intraocular pressure (IOP) exceeds ICP. Here, we identify features in the eye - optic disc and retinal blood vessel locations - and identify pulsation in large retinal blood vessels. The relationship between force and the magnitude of pulsation is used to estimate ICP when force is applied to the eye to gradually increase IOP over time. This approach yields 77% accuracy in automatically observing vessel pulsation.Clinical Relevance - Non-invasive ICP monitoring is desirable to improve patient outcome by reducing potential trauma and complications associated with invasive assessment with intracranial sensors or lumbar puncture.

PURPOSE: To investigate changes in aqueous humor dynamics during intraocular pressure (IOP) elevation induced by circumlimbal suture in mice. METHODS: Ocular hypertension (OHT) was induced by applying a circumlimbal suture behind the limbus in male adult C57BL6/J mice. In the OHT group, the suture was left in place for an average of 8 weeks (n = 10, OHT group). In the sham control group the suture was cut at 2 days (n = 9, sham group) and in the naïve control group (n = 5) no suture was implanted. IOP was measured at baseline across 3 days, 1 h post-suture implantation, and at the chronic endpoint. Anterior segments were assessed using optical coherence tomography (OCT). Episcleral venous pressure (EVP), total outflow facility (C), uveoscleral outflow (Fu) and aqueous humor flow rate (Fin) were determined using a constant-flow infusion model. RESULTS: All aqueous dynamic and chronic IOP outcome measures showed no difference between sham and naïve controls (p > 0.05) and thus these groups were combined into a single control group. IOP was elevated in OHT group compared with controls (p < 0.01). Chronic suture implantation did not change pupil size, anterior chamber depth or iridocorneal angles (p > 0.05). EVP was significantly higher in OHT eyes compared to control eyes (p < 0.01). There was no statistical difference in C, Fu and Fin between groups (p > 0.05). A significant linear correlation was found between IOP and EVP (R2 = 0.35, p = 0.001). CONCLUSIONS: Circumlimbal suture implantation in mouse eyes results in chronic IOP elevation without angle closure. Chronic IOP elevation is likely to reflect higher EVP.

Glaucoma, a major cause of irreversible blindness worldwide, is associated with elevated intraocular pressure (IOP) and progressive loss of retinal ganglion cells (RGCs) that undergo apoptosis. A mechanism for RGCs injury involves impairment of neurotrophic support and exogenous supply of neurotrophic factors has been shown to be beneficial. However, neurotrophic factors can have widespread effects on neuronal tissues, thus targeting neurotrophic support to injured neurons may be a better neuroprotective strategy. In this study, we have encapsulated LM22A-4, a small neurotrophic factor mimetic, into Annexin V-conjugated cubosomes (L4-ACs) for targeted delivery to injured RGCs in a model of glaucoma, which is induced by acute IOP elevation. We have tested cubosomes formulations that encapsulate from 9% to 33% LM22A-4. Our data indicated that cubosomes encapsulating 9% and 17% LM22A-4 exhibited a mixture of Pn3m/Im3m cubic phase, whereas 23% and 33% showed a pure Im3m cubic phase. We found that 17% L4-ACs with Pn3m/Im3m symmetries showed better in-situ and in-vitro lipid membrane interactions than the 23% and 33% L4-ACs with Im3m symmetry. In vivo experiments showed that 17% L4-ACs targeted the posterior retina and the optic nerve head, which prevented RGCs loss in a mouse model of acute IOP elevation. These results provide evidence that cubosomesbased LM22A-4 delivery may be a useful targeted approached to prevent the progression of RGCs loss in glaucoma.

The photocatalytic properties of TiO2 have aroused a broad range of research interest since 1972 due to its abundance, chemical stability, and easily available nature. To increase its overall activity, in the past few decades, much effort has been devoted to the fabrication of advanced TiO2‐based photocatalysts with visible‐light response and these photocatalysts have shown great potential in the field of solar energy utilization. Here, recent progress in the investigation of visible‐light responsive TiO2‐based materials are reviewed. Notably, the fabrication strategies and corresponding chemical/physical properties of visible‐light responsive TiO2‐based materials are described in detail, with a focus on bandgap engineering and junction engineering from the perspective of light absorption, charge transfer and separation, and surface reactions. Their applications in solar‐fuel production, organic synthesis, bacterial disinfection, pollutant degradation and nitrogen fixation are also discussed. Moreover, the new trends and ongoing challenges in this field are proposed and highlighted.

Inherited paediatric cataract is a rare Mendelian disease that results in visual impairment or blindness due to a clouding of the eye's crystalline lens. Here we report an Australian family with isolated paediatric cataract, which we had previously mapped to Xq24. Linkage at Xq24-25 (LOD = 2.53) was confirmed, and the region refined with a denser marker map. In addition, two autosomal regions with suggestive evidence of linkage were observed. A segregating 127 kb deletion (chrX:g.118373226_118500408del) in the Xq24-25 linkage region was identified from whole-genome sequencing data. This deletion completely removed a commonly deleted long non-coding RNA gene LOC101928336 and truncated the protein coding progesterone receptor membrane component 1 (PGRMC1) gene following exon 1. A literature search revealed a report of two unrelated males with non-syndromic intellectual disability, as well as congenital cataract, who had contiguous gene deletions that accounted for their intellectual disability but also disrupted the PGRMC1 gene. A morpholino-induced pgrmc1 knockdown in a zebrafish model produced significant cataract formation, supporting a role for PGRMC1 in lens development and cataract formation. We hypothesise that the loss of PGRMC1 causes cataract through disrupted PGRMC1-CYP51A1 protein-protein interactions and altered cholesterol biosynthesis. The cause of paediatric cataract in this family is the truncating deletion of PGRMC1, which we report as a novel cataract gene.

Marine shipping emissions exert important air quality and climate impacts. This study characterized the ambient pollutants predominant by emissions from a variety of marine vessel types near the mid-latitude East China Sea. Two discernible primary shipping emissions were identified by factorization analysis on detailed mass spectra of organic aerosol (OA), as emissions in maneuvering and cruise, highly linked with NOx (and less oxidized OA, black carbon, BC) or CO (and more oxidized OA), respectively. Using radio-recorded quantities and activities of 3566 vessels mixed with slow and high-speed diesel engines, we found emission of NOx or BC per vessel was positively correlated with vessel speed, while CO emission peaked at moderate speed. The approach here based on vessel operation mode directly linked the vessel activities to ambient concentrations of pollutants from marine shipping emission, and may synthesize the complex vessel types in shipping emission inventory.

Current understanding on the interactions between micro/nano-structured Ti surfaces and macrophages is still limited. In this work, TiO2 nano-structures were introduced onto acid-etched Ti surfaces by alkali-heat treatment, ion exchange and subsequent heat treatment. By adjusting the concentration of NaOH during alkali-heat treatment, nano-flakes, nano-flakes mixed with nano-wires or nano-wires could formed on acid-etched Ti surfaces. The micro- and micro/nano-structured Ti surfaces possessed similar surface chemical and phase compositions. In vitro results indicate that the morphology of macrophages was highly dependent on the morphological features of nano-structures. Nano-flakes and nano-wires were favorable to induce the formation of lamellipodia and filopodia, respectively. Compared to micro-structured Ti surface, micro/nano-structured Ti surfaces polarized macrophages to their M2 phenotype and enhanced the gene expressions of osteogenic growth factors in macrophages. The M2 polarized macrophages promoted the maturation of osteoblasts. Compared to that with nano-flakes or nano-wires, the surface with mixed features of nano-flakes and nano-wires exhibited stronger anti-inflammatory and osteo-immunomodulatory effects. The findings presented in the current work suggest that introducing micro/nano-topographies onto Ti-based implant surfaces is a promising strategy to modulate the inflammatory response and mediate osteogenesis.

Real-time intelligent video processing on embedded devices with low power consumption can be useful for applications like drone surveillance, smart cars, and more. However, the limited resources of embedded devices is a challenging issue for effective embedded computing. Most of the existing work on this topic focuses on single device based solutions, without the use of cloud computing mechanisms for parallel processing to boost performance. In this paper, we propose a cloud platform for real-time video processing based on embedded devices. Eight NVIDIA Jetson TX1 and three Jetson TX2 GPUs are used to construct a streaming embedded cloud platform (SECP), on which Apache Storm is deployed as the cloud computing environment for deep learning algorithms (Convolutional Neural Networks — CNNs) to process video streams. Additionally, self-managing services are designed to ensure that this platform can run smoothly and stably, in the form of a metric sensor, a bottleneck detector and a scheduler. This platform is evaluated in terms of processing speed, power consumption, and network throughput by running various deep learning algorithms for object detection. The results show the proposed platform can run deep learning algorithms on embedded devices while meeting the high scalability and fault tolerance required for real-time video processing.

We propose a simple realization of a 2-dimensonal (2D) PT-symmetric photonic structure: a honeycomb arrangement of alternating cylinders with gain or loss in a dielectric background. The structure provides a periodic modulation of the refractive index on the wavelength scale, which combined with an anti-symmetric gain/loss distribution on the same scale, leads to non-reciprocal light coupling at resonance frequencies. Numerical simulations show asymmetric right-left transmission of light beams., We acknowledge financial support by Spanish Ministerio de Ciencia e Innovacion, and European Union FEDER through project FIS2011-29731-0O2-01 and -02 and and Generalitat de Catalunya (2009 SGR 1168)., IEEE, IEEE Photon Soc, Light Tec, Agilent Technologies, Cerebra InformationsSysteme GmbH, IEEE Austria Sect, Inst Engn ; Technol, Natl Inst Telecommunicat, IIIE Media Event, ML11, GRAZ, Osterreichischer Verband Elektrotechnik, IEEE Photon Soc, Raiffeisen Meine Bank, GRAZ Stadt, Graz Univ Technology, TEST, Spanish Ministerio de Ciencia e InnovacionInstituto de Salud Carlos IIISpanish Government; European Union FEDEREuropean Commission [FIS2011-29731-0O2-01, FIS2011-29731-0O2-02]; Generalitat de CatalunyaGeneralitat de Catalunya [2009 SGR 1168]

We propose a simple realization of a 2-dimensonal (2D) PT-symmetric photonic structure: a honeycomb arrangement of alternating cylinders with gain or loss in a dielectric background. The structure provides a periodic modulation of the refractive index on the wavelength scale, which combined with an anti-symmetric gain/loss distribution on the same scale, leads to non-reciprocal light coupling at resonance frequencies. Numerical simulations show asymmetric right-left transmission of light beams., We acknowledge financial support by Spanish Ministerio de Ciencia e Innovacion, and European Union FEDER through project FIS2011-29731-0O2-01 and -02 and and Generalitat de Catalunya (2009 SGR 1168)., IEEE, IEEE Photon Soc, Light Tec, Agilent Technologies, Cerebra InformationsSysteme GmbH, IEEE Austria Sect, Inst Engn ; Technol, Natl Inst Telecommunicat, IIIE Media Event, ML11, GRAZ, Osterreichischer Verband Elektrotechnik, IEEE Photon Soc, Raiffeisen Meine Bank, GRAZ Stadt, Graz Univ Technology, TEST, Spanish Ministerio de Ciencia e InnovacionInstituto de Salud Carlos IIISpanish Government; European Union FEDEREuropean Commission [FIS2011-29731-0O2-01, FIS2011-29731-0O2-02]; Generalitat de CatalunyaGeneralitat de Catalunya [2009 SGR 1168]

The wide applications of high-capacity lithium metal anodes for lithium metal batteries are restricted by the uncontrollable lithium dendrite growth caused by the uneven lithium deposition and the infinite volume change of lithium anodes during the plating/stripping process. Herein, the composite ionic/electronic interlayer of Li2S/Mo is deposited on the surface of stainless steel mesh (SSM) by in situ electrochemical conversion reaction from MoS2 nanosheet arrays. The Li2S/Mo interlayer with high ionic conductivity can regulate uniform lithium-ion flux and promote homogeneous lithium deposition without dendrite growth. The half cells with Li2S/Mo-modified SSM current collector show stable cycling performance of more than 400 cycles at 1 and 1 mAh cm−2, with the average Coulombic efficiency higher than 96%. By coupling with LiFePO4 cathodes, the assembled full cells demonstrate improved cycling performance. This work provides a new idea for using metal sulfides as a lithiophilic interlayer to facilitate dendrite-free lithium deposition.

Object detection in autonomous driving applications implies that the detection and tracking of semantic objects are commonly native to urban driving environments, as pedestrians and vehicles. One of the major challenges in state-of-the-art deep-learning based object detection are false positives which occur with overconfident scores. This is highly undesirable in autonomous driving and other critical robotic-perception domains because of safety concerns. This paper proposes an approach to alleviate the problem of overconfident predictions by introducing a novel probabilistic layer to deep object detection networks in testing. The suggested approach avoids the traditional Sigmoid or Softmax prediction layer which often produces overconfident predictions. It is demonstrated that the proposed technique reduces overconfidence in the false positives without degrading the performance on the true positives. The approach is validated on the 2D-KITTI objection detection through the YOLOV4 and SECOND (Lidar-based detector). The proposed approach enables interpretable probabilistic predictions without the requirement of re-training the network and therefore is very practical., Comment: This work has been accepted for publication as a REGULAR PAPER in the Transactions on Intelligent Transportation Systems-ITS