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This thesis investigates models of stochastic volatility which are able to accommodate the clustering of jumps typical of many high-frequency financial time series, both in terms of describing significant features of the data, and forecasting. Chapter 1 gives an overview on the jump-diffusion stochastic volatility models, clustering behaviours of jumps and contributions of this thesis to current literature. Chapter 2 examines the clustering behaviour of price and variance jumps using high-frequency data, modelled as a marked Hawkes process embedded in a bivariate jump-diffusion model with intraday seasonal effects. We find that the jumps of both individual stocks and a broad index exhibit self-exciting behaviour. The three dimensions of the model, namely positive price jumps, negative price jumps and variance jumps, impact one another in an asymmetric manner, that is positively and significantly correlated with jump size. We estimate model parameters using Bayesian inference by Markov Chain Monte Carlo, and find that the inclusion of the jump parameters improves model fitness. We quantify the jump intensity and study characteristics of jump clusters, we find under high-frequency settings, jump clustering activities can last 2.5 to 6 hours in average, we also find that the model with marked Hawkes process models mostly outperform others in terms of reproducing two cluster-related characteristics. Chapter 3 uses a bivariate jump-diffusion model incorporating jump clustering features by embedding a multivariate marked Hawkes process for high-frequency forecasting. In the out-of-sample period, we use a particle filter to estimate variance at each state and forward simulating return and variance distributions. We apply i a Kalman filter to correct errors that arise with microstructure noises in the highfrequency data. The simulation studies show the effectiveness of the Kalman filter. We show that the inclusion of jump clustering significantly improves the performance of high-frequency volatility forecasting and daily realised volatility forecasting. In high-frequency volatility forecasting, we find that forecasting performance is especially better with forecasting horizons of less than two hours. We also show that expected losses of two risk measures, value-at-risk and expected shortfall, can be reduced by up to 15% using models with jump clustering features. Chapter 4 forecasts Bitcoin’s returns and return jumps using a self-exciting process embedded in a stochastic volatility model. We show the existence of the jump clustering feature, which varies depending on the frequency of the data. In an out-of-sample setting, we use a particle filter to sample latent states and conduct one-step-ahead probabilistic forecasting on future jumps (underlying intensities). We assess the forecasts by a continuous ranked probability score. We further develop a statistic that takes the discrepancies between the predicted probabilities of positive and negative jumps. We find that high and low values of the difference in predicted probabilities of positive and negative jumps is able to predict returns, and that a trading strategy based on this has a Sharpe ratio of 4.36. Lastly, Chapter 5 concludes the thesis and discusses future research.

Filchnerella huiningensis sp. nov. (Figs. a–h) Type material: Holotype: J, Taohuashan, Huining County, Gansu Province, China. 35°68 ‘N, 105°08 ‘E, 1944 m, 2006–VII–23, collected by Dao-Chuan Zhang and Yong-Chao Zhi. Paratypes: 6 J and 7 ♀, same as the holotype. Male (Figs. a–e) Body medium-sized (fig a), with hairs, especially on legs. Vertex short and wide, width between two eyes is about 3.9 times as wide as frontal ridge between bases of antennae, fastigial furrow present, dorsal side of head depressed, with granular and club-like projection, preocellar foveolae irregular. Frontal ridge distinct, with a groove along its whole length, between the bases of antennae slightly projecting forward, constructed slightly under ocellus, widened gently downwards, widen distinctly on base of labrum. Lateral facial carinae distinct, but invisible in dorsal view. Eyes small, near circle, subocular furrow 1.25 times vertical diameter in length. Antennae filiform, 18–19 segments, length nearly equal to the total length of head and pronotum, the length of a segment 2.3 times its width in the middle part. Pronotum rough, with short subuliform projection, anterior and posterior margin angled protruding, two very high projection in front part on lateral lobes (fig c), median carina elevated into lamellate, strongly incised on the posterior transverse groove, metazona 1.2 times prozona in length, median carina incised by the 2 transverse grooves in prozona, median carina of metazona arc-ike raised. Prosternum with a strong lamellate process on anterior margin, having obvious and shallow emarginate in the middle. Interspace of mesosternum lateral lobes trapezoid, the narrowest part wider 1.3 times than the broadest part of lateral lobes. Tegmina reaching the posterior margin of fifth abdominal tergite or middle of hind femur, length 2.5 times maximum width. Hind femur wide and compressed, length is 2.9 times the width of broadest part, upper median carina of hind femur serrated, with arc-like concave near apex of knee (fig d). Hind tibia with apical spine on inner and outer side, with 10 spines on external side and 8–9 spines on internal side (including apical spine). Arolium between claws of tarsus large, its apex reaching to the middle of claws. Tympanum organ developed, tympanal aperture expanded, tympanic flap small. Krause’s organ near triangle, with thinly rugose on surface. Abdomen with a row of tubercles in the middle. Epiproct near tongue-like, with longitudinal groove in the middle. Cercus long conical, curved inward. Subgenital plate short conical, apex acute (fig e). Epiphallus shield like, with 8–10 denticle on lateral plates, ancorae smaller (fig b). Female (figs. f–h) Body thick and larger than male. Vertex extremely wider, the width between two eyes is about 4.5 times as wide as frontal ridge between bases of antennae (fig g). Length of antennae shorter than the length of head and pronotum together. Tegmina lobi-form, dorsally widely separated, apex reaching or not the posterior margin of first abdominal tergite (fig h), not cover the Tympanum organ completely, slightly shorter than metazona of pronotum. Cercus short conical. Subgenital plate project at an angle in the middle of posterior margin. Ovipositor valves short, hooked, apex acute, outer margin of lower valve with concave near the apex (fig f). Coloration. Body filemot. Inner side of hind femur dark blue, lower margin red with slightly dark blue, upper margin black, red in pergendicular, inner knee lobe red. Inner side of hind tibia red on the base and end, dark blue on the middle. Measurements (in mm): Length of body: J18.7–21.6, ♀ 30.6–24.7. Length of pronotum: J5.4–7.7, ♀ 8.8–10.4. Length of tegmina: J6.3–8.3, ♀ 3.3–5.3. Length of hind femur: J10.1–11.8, ♀ 12.6–14.1. Diagnosis. The new species is allied to Filchnerella rubimargina Zheng, 1992. The major differences are in Table 1. Etymology. The specific epithet is named after Huining, the type locality.

Wang, Li, Chen, Jian-Yu, Li, Xin-Jiang (2023): A new species of the genus Filchnerella Karny, 1908 (Orthoptera: Acridoidea: Pamphagidae) from China. Zootaxa 5319 (1): 141-144, DOI: 10.11646/zootaxa.5319.1.11, URL: http://dx.doi.org/10.11646/zootaxa.5319.1.11

Echinacoside (ECH) is the main compound of Cistanche deserticola, which possesses antioxidant, antitumor, antifatigue, and anti-inflammatory properties. The present study investigated the protective effects of echinacoside on type 2 diabetes mellitus (T2DM)-induced injury in T2DM injury db/db mice model and insulin-resistant LO2 cell model. The results demonstrated that ECH probably alleviated T2DM-induced injury by mediating the AKT pathway, which provided a new direction for the treatment of T2DM-induced injury.

Colletotrin A (1), a new 1,4-benzoxazine derivative, and eight known compounds, including two alkaloids (2-3), one acylamide (4), one benzaldehyde (5), and four sterols (6-9) were obtained from endophytic fungus Colletotrichum gloeosporioides B-142, which was isolated from Dracaena cochinchinensis. Among them, 1,2,3,4-tetrahydroquinoline-4,8-diol (2) was reported for the first time as natural product. The structure of compound 1 was elucidated with help of spectroscopic data including IR, UV, electronic circular dichroism (ECD) calculation, HRESIMS, 1D and 2D NMR (COSY, HSQC and HMBC). The antimicrobial activities were evaluated by disc diffusion method.

For the past decades, scientists have endeavored to develop efficient and suitable approaches to monitor heavy-metal pollution through technological development. Conventional monitoring methods for heavy metals are still complicated, relatively expensive, and time-consuming. This research aims to develop an innovative heavy-metal monitor, the novel approach of ion-exchange resin sachets combined with X-ray fluorescence core scanner (XRF-CS), to achieve an efficient way to effectively monitor vast areas for contamination. The resin sachets, which have a large capacity to quickly take up heavy metals, were deployed in the river weekly to capture heavy metals and then analyzed using the non-destructive, fast, and cost-efficient Itrax XRF core scanner. Two four-week sampling sessions, performed during the dry and wet periods, respectively, were conducted in northeastern Taiwan, where the environment was contaminated by a copper smelter and coal mine activities in the late twentieth century. The results suggest that ion-exchange resins are useful as long-term monitors of heavy metals in a low pollution-level settings (metal concentration

Diabetes mellitus during pregnancy, which can be classified into pregestational diabetes and gestational diabetes, has become much more prevalent worldwide. Maternal diabetes fosters an intrauterine abnormal environment for fetus, which not only influences pregnancy outcomes, but also leads to fetal anomaly and development of diseases in later life, such as metabolic and cardiovascular diseases, neuropsychiatric outcomes, reproduction malformation, and immune dysfunction. The underlying mechanisms are comprehensive and ambiguous, which mainly focus on microbiota, inflammation, reactive oxygen species, cell viability, and epigenetics. This review concluded with the influence of intrauterine hyperglycemia on fetal structure development and organ function on later life and outlined potential mechanisms that underpin the development of diseases in adulthood. Maternal diabetes leaves an effect that continues generations after generations through gametes, thus more attention should be paid to the prevention and treatment of diabetes to rescue the pathological attacks of maternal diabetes from the offspring.

During the past decades, rheumatoid arthritis had become a serious problem, torturing millions of patients because of unclear pathogenesis and no ideal therapies. Natural products remain an important source of medicines to treat various major diseases such as rheumatoid arthritis (RA) given their excellent biocompatibility and structural diversity. Herein, we have developed a versatile synthetic method for constructing various skeletons of akuammiline alkaloid analogs based on our previous research on the total synthesis of the related indole alkaloids. We have also evaluated the effect of these analogs on the proliferation of RA fibroblast-like synoviocytes (FLSs) in vitro and analyzed the corresponding structure-activity relationship (SAR). Among these analogs, compounds 9 and 17c have demonstrated a promising inhibitory effect on the proliferation of RA-FLSs, with IC50 values of 3.22 ± 0.29 μM and 3.21 ± 0.31 μM, respectively. Our findings provide a solid foundation for future pharmacological studies on akuammiline alkaloid derivatives and inspiration for the development of anti-RA small molecule drugs derived from natural products.

Leaf traits are important indicators of plant life history and may vary according to plant functional type (PFT) and environmental conditions. In this study, we sampled woody plants from three PFTs (e.g., needle-leaved evergreens, NE; broad-leaved evergreens, BE; broad-leaved deciduous, BD) on the eastern Qinghai-Tibetan Plateau, and 110 species were collected across 50 sites. Here, the divergence and correlations of leaf traits in three PFTs and relationships between leaf traits and environment were studied. The results showed significant differences in leaf traits among three PFTs, with NE plants showed higher values than BE plants and BD plants for leaf thickness (LT), leaf dry matter content (LDMC), leaf dry mass per area (LMA), carbon: nitrogen ratio (C/N), and nitrogen content per unit area (Narea), except for nitrogen content per unit mass (Nmass). Although the correlations between leaf traits were similar across three PFTs, NE plants differed from BE plants and BD plants in the relationship between C/N and Narea. Compared with the mean annual precipitation (MAP), the mean annual temperature (MAT) was the main environmental factor that caused the difference in leaf traits among three PFTs. NE plants had a more conservative approach to survival compared to BE plants and BD plants. This study shed light on the regional-scale variation in leaf traits and the relationships among leaf traits, PFT, and environment. These findings have important implications for the development of regional-scale dynamic vegetation models and for understanding how plants respond and adapt to environmental change.

As a common geological material, soil is a key aspect of construction engineering. Soil has typical multi-scale characteristics, but current multi-scale methods analyze these characteristics only in regard to geometric space. More exploration of the coupling influence mechanism of the basic properties of particles on the microstructure and macroscopic properties of soil is needed. This study analyzed the influence of geometric scale and mineral composition on the surface energy of particles at the microscopic level for development of the energy multi-scale method. Experiments were performed to determine the influence of mineral composition and particle size on the plasticity index (Ip) of the soil, and experimental results are discussed and interpreted quantitatively using the energy multi-scale method. The conclusions derived from this work are as follows: 1) the mineral composition and particle size of the soil can cause interface and surface effects; 2) the comprehensive ratio of micro-force to weight (CRFW) of the particles can be determined using the energy multi-scale method and quantitatively reflects the influence of particle size and mineral composition on the microscopic properties of the soil; and 3) the energy multi-scale method explains the mechanism of the plasticity index of soil and has allowed identification of a new division of soil plasticity. When the CRFW was used as the control index, the plasticity index of the three materials was practically the same, even if the mineral composition and particle sizes of the three materials were different.

The study of the creep properties of soils is of great importance for the management of future settlements and the safe use of buildings. However, starting from the micro level is an effective way to explore the creep mechanism of soft soil. In this paper, the influence of the mineral composition and the mineral content on the structure and creep properties of soft soil was analyzed at the microscopic level and the energy scale method was proposed. Then, the energy scale method was used to analyze and discuss the results of the direct shear creep test. The discussion showed that 1) the average viscosity coefficient of kaolin was greater than that of bentonite, which decreased with an increase of kaolin and bentonite; 2) the thickness of adsorbed water or the double electric layer (DEL) on the particle surface was positively correlated with the soft soil creep; and 3) λ was positively correlated with the adsorbed water content and negatively correlated with the average viscosity coefficient of the soft soil. λ characterized the adsorption capacity of the particles at the micro level; hence, the energy scale method can explain the mechanism of the soft soil creep at the microscopic level and also quantitatively describe the influencing law of the basic characteristics of the particles on the properties of the soft soil creep.

Real-time systems require the formal guarantee of timing constraints, not only for the individual tasks but also for the end-to-end latency of data flows. The data flow among multiple tasks, e.g., from sensors to actuators, is described by a cause-effect chain, independent from the priority order of the tasks. In this paper, we provide an end-to-end timing-analysis for cause-effect chains on asynchronized distributed systems with periodic task activations, considering the maximum reaction time (i.e., the duration of data processing) and the maximum data age (i.e., the worst-case data freshness). We first provide an analysis of the end-to-end latency on one local electronic control unit (ECU) that has to consider only the jobs in a bounded time interval. We extend our analysis to globally asynchronized systems by exploiting a compositional property to combine the local results. Throughout synthesized data based on an automotive benchmark as well as on randomized parameters, we show that our analytical results improve the state-of-the-art.

IL-12α plays an important role in modulating inflammatory response, fibroblast proliferation and angiogenesis through modulating macrophage polarization or T cell function, but its effect on cardiorespiratory fitness is not clear. Here, we studied the effect of IL-12α on cardiac inflammation, hypertrophy, dysfunction, and lung remodeling in IL-12α gene knockout (KO) mice in response to chronic systolic pressure overload produced by transverse aortic constriction (TAC). Our results showed that IL-12α KO significantly ameliorated TAC-induced left ventricular (LV) failure, as evidenced by a smaller decrease of LV ejection fraction. IL-12α KO also exhibited significantly attenuated TAC-induced increase of LV weight, left atrial weight, lung weight, right ventricular weight, and the ratios of them in comparison to body weight or tibial length. In addition, IL-12α KO showed significantly attenuated TAC-induced LV leukocyte infiltration, fibrosis, cardiomyocyte hypertrophy, and lung inflammation and remodeling (such as lung fibrosis and vessel muscularization). Moreover, IL-12α KO displayed significantly attenuated TAC-induced activation of CD4+ T cells and CD8+ T cells in the lung. Furthermore, IL-12α KO showed significantly suppressed accumulation and activation of pulmonary macrophages and dendritic cells. Taken together, these findings indicate that inhibition of IL-12α is effective in attenuating systolic overload-induced cardiac inflammation, heart failure development, promoting transition from LV failure to lung remodeling and right ventricular hypertrophy.

IntroductionMicrobiota in the human body are closely related to human diseases. Female urogenital tract and rectal microbes have been considered as important factors affecting female pregnancy, but the mechanism is unknown.MethodsCervical, vaginal, urethral, and rectal swabs were collected from 22 infertile patients and 10 controls, and follicular fluid was extracted from 22 infertile patients. The microbial composition of different sampling sites of infertile patients was examined. By comparing the microbial composition difference between infertile patients and controls and combining bioinformatics methods to analyze the potential impact of the female urogenital tract (cervical, vaginal and urethral) and rectal microbial diversity on female infertility and pregnancy outcomes.ResultsLactobacillus predominated in the female urogenital tract, but its abundance decreased in infertile patients, whereas the abundance of Gardnerella and Atopobium increased. The microbial changes in the urethra had the same trend as that in the vagina. Compared with healthy controls, the cervical and rectal microbial diversity of infertile patients were significantly increased and decreased, respectively. There might be interactions between microbes in different parts of female. Geobacillus thermogeniticans was enriched in the urogenital tract and rectum of infertile patients, and has a good predictive effect on infertility. Compared with infertile patients, L. johnsonii was enriched in the vagina, urethra, and intestine of the control group. L. acidophilus in follicular fluid might be associated with Non-pregnancy.ConclusionThis study found that the microbial composition of infertile patients was changed compared with that of healthy people. The translocation of Lactobacillus between the rectum and urogenital tract might play a protective barrier role. The changes of Lactobacillus and Geobacillus might be related to female infertility or pregnancy outcome. The study provided a theoretical basis for the future treatment of female infertility from the perspective of microorganisms by detecting the microbial changes associated with female infertility.

IntroductionTea is the main raw material for preparing tea wine.MethodsIn this research, four types of tea wine were prepared using different categories of tea leaves, including green tea, oolong tea, black tea, and dark tea, and the comparative study looking their physicochemical, sensorial, and antioxidant profiles were carried out.ResultsThe dynamic changes of total soluble solids, amino acids and ethanol concentrations, and pH were similar in four tea wines. The green tea wine (GTW) showed the highest consumption of total soluble solids and amino acids, and produced the highest concentrations of alcohol, malic, succinic, and lactic acid among all tea wines. The analysis of volatile components indicated the number and concentration of esters and alcohols increased significantly after fermentation of tea wines. GTW presented the highest volatile concentration, while oolong tea wine (OTW) showed the highest number of volatile compounds. GTW had the highest total catechins concentration of 404 mg/L and the highest ABTS value (1.63 mmol TEAC/mL), while OTW showed the highest DPPH value (1.00 mmol TEAC/mL). Moreover, OTW showed the highest score of sensory properties.DiscussionTherefore, the types of tea leaves used in the tea wine production interfere in its bioactive composition, sensorial, and antioxidant properties.

Objective To investigate the effect of LH level changes on the outcomes of controlled ovarian hyperstimulation (COH) and embryo transfer (ET) in gonadotropin-releasing hormone antagonist (GnRH-ant) protocol. Methods: A total of 721 patients undergoing GnRH-ant protocol COH for the first IVF/ICSI cycles were retrospectively analyzed. COH process were divided into 2 stages, before (stage 1) and after (stage 2) the GnRH-ant initiation, and each with 5 groups basing on LH levels: LH decreased more than 50% (A1, A2), decreased 25%-50% (B1, B2), change less than 25% (C1, C2), increased 25%-50% (D1, D2), and increased more than 50% (E1, E2). Results: There were no significant differences among groups of stage1 regarding COH and ET outcomes. For stage 2, the more obvious the decrease of LH level, the more the number of oocytes retrieved, mature oocytes, fertilized oocytes, embryos cleavaged and the numbers of embryo available (P

Over the past two decades, multiobejective gradient descent methods have received increasing attention due to the seminal work of Fliege and Svaiter. Recently, Chen et al. pointed out that imbalances among objective functions can lead to a small stepsize in Fliege and Svaiter's method, which significantly decelerates the convergence. To address the issue, Chen et al. propose the Barzilai-Borwein descent method for multiobjective optimization (BBDMO). Their work demonstrated that BBDMO achieves better stepsize and performance compared to Fliege and Svaiter's method. However, a theoretical explanation for the superiority of BBDMO over the previous method has been open. In this paper, we extend Chen et al.'s method to composite cases and propose two types of Barzilai-Borwein proximal gradient methods (BBPGMO). Moreover, we prove that the convergence rates of BBPGMO are $O(\frac{1}{\sqrt{k}})$, $O(\frac{1}{k})$, and $O(r^{k})(0

With the end of Moore's Law, there is a growing demand for rapid architectural innovations in modern processors, such as RISC-V custom extensions, to continue performance scaling. Program sampling is a crucial step in microprocessor design, as it selects representative simulation points for workload simulation. While SimPoint has been the de-facto approach for decades, its limited expressiveness with Basic Block Vector (BBV) requires time-consuming human tuning, often taking months, which impedes fast innovation and agile hardware development. This paper introduces Neural Program Sampling (NPS), a novel framework that learns execution embeddings using dynamic snapshots of a Graph Neural Network. NPS deploys AssemblyNet for embedding generation, leveraging an application's code structures and runtime states. AssemblyNet serves as NPS's graph model and neural architecture, capturing a program's behavior in aspects such as data computation, code path, and data flow. AssemblyNet is trained with a data prefetch task that predicts consecutive memory addresses. In the experiments, NPS outperforms SimPoint by up to 63%, reducing the average error by 38%. Additionally, NPS demonstrates strong robustness with increased accuracy, reducing the expensive accuracy tuning overhead. Furthermore, NPS shows higher accuracy and generality than the state-of-the-art GNN approach in code behavior learning, enabling the generation of high-quality execution embeddings.

Semi-supervised learning (SSL) has achieved great success in leveraging a large amount of unlabeled data to learn a promising classifier. A popular approach is pseudo-labeling that generates pseudo labels only for those unlabeled data with high-confidence predictions. As for the low-confidence ones, existing methods often simply discard them because these unreliable pseudo labels may mislead the model. Nevertheless, we highlight that these data with low-confidence pseudo labels can be still beneficial to the training process. Specifically, although the class with the highest probability in the prediction is unreliable, we can assume that this sample is very unlikely to belong to the classes with the lowest probabilities. In this way, these data can be also very informative if we can effectively exploit these complementary labels, i.e., the classes that a sample does not belong to. Inspired by this, we propose a novel Contrastive Complementary Labeling (CCL) method that constructs a large number of reliable negative pairs based on the complementary labels and adopts contrastive learning to make use of all the unlabeled data. Extensive experiments demonstrate that CCL significantly improves the performance on top of existing methods. More critically, our CCL is particularly effective under the label-scarce settings. For example, we yield an improvement of 2.43% over FixMatch on CIFAR-10 only with 40 labeled data., typos corrected, 5 figures, 3 tables

Additional file 1. Supplementary Material.

Learning from noisy labels is an important and long-standing problem in machine learning for real applications. One of the main research lines focuses on learning a label corrector to purify potential noisy labels. However, these methods typically rely on strict assumptions and are limited to certain types of label noise. In this paper, we reformulate the label-noise problem from a generative-model perspective, $\textit{i.e.}$, labels are generated by gradually refining an initial random guess. This new perspective immediately enables existing powerful diffusion models to seamlessly learn the stochastic generative process. Once the generative uncertainty is modeled, we can perform classification inference using maximum likelihood estimation of labels. To mitigate the impact of noisy labels, we propose the $\textbf{L}$abel-$\textbf{R}$etrieval-$\textbf{A}$ugmented (LRA) diffusion model, which leverages neighbor consistency to effectively construct pseudo-clean labels for diffusion training. Our model is flexible and general, allowing easy incorporation of different types of conditional information, $\textit{e.g.}$, use of pre-trained models, to further boost model performance. Extensive experiments are conducted for evaluation. Our model achieves new state-of-the-art (SOTA) results on all the standard real-world benchmark datasets. Remarkably, by incorporating conditional information from the powerful CLIP model, our method can boost the current SOTA accuracy by 10-20 absolute points in many cases.

Additional file 1: Supplementary Table 1. Table of 3-Minute Step Test index values and cardiopulmonary function.

In statistics, samples are drawn from a population in a data- generating process (DGP). Standard errors measure the uncer- tainty in sample estimates of population parameters. In sci- ence, evidence is generated to test hypotheses in an evidence- generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sam- ple. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.

Supplementary Material 1

Model-based mutation analysis is a recent research area, and real-time system testing can benefit from using model mutants. Model-based mutation testing (MBMT) is a particular branch of model-based testing. It generates faulty versions of a model using mutation operators to evaluate and improve test cases. Mutation testing is an effective way to ensure software correctness and has been applied to various application areas. Simulink is a vital modeling language for real-time systems. This paper introduces Simulink model mutation analysis to improve Model-in-the-loop (MIL) testing. We propose a set of Simulink mutation operators based on AUTOSAR, which reflects the temporal correctness when a Simulink model is mapped to Operating System tasks. We implement a mutation framework that generates mutants for implicit clock Simulink models. Finally, we demonstrate how this framework generates mutants to reveal task interference issues in the simulation. Our work integrates the Simulink model with the timed systems to better support mutation testing automation.

Supplementary Material 3

Binarized Neural Networks (BNNs) significantly reduce the computation and memory demands with binarized weights and activations compared to full-precision NNs. Executing a layer in a BNN on different devices of a heterogeneous multiprocessor platform consisting of CPU and GPU can affect the inference performance, i.e., accuracy and latency. Usually, a heterogeneous HW platform consisting of a CPU and a GPU is available to execute the BNN workloads. However, to use the heterogeneous HW effectively, it is necessary to find an efficient strategy for BNN workload mapping. In this work, we propose a framework that generates efficient BNN layer-to-device mappings (i.e. suitable parallel configuration for each layer of the model) for execution platforms comprised of CPU and CUDA-capable GPU. We evaluate our proposed framework with two BNN architectures using two well-known datasets, Fashion-MNIST and CIFAR-10, on three hardware platforms with different characteristics. The results show that compared to running a fully-parallelized GPU implementation, our framework generates an efficient configuration up to 2x, 2.6x and 11.8x faster on our tested hardware respectively., Comment: This paper has been accepted for presentation in the 5th Workshop on Accelerated Machine Learning (AccML), co-located with HiPEAC23. 8 Pages, 5 figures

A near-field secure transmission framework is proposed. Employing the hybrid beamforming architecture, a multi-antenna base station (BS) transmits confidential information to a multi-antenna legitimate user (U) against a multi-antenna eavesdropper (E) in the near field. A two-stage algorithm is proposed to maximize the near-field secrecy capacity. Based on the fully-digital beamformers obtained in the first stage, the optimal analog beamformers and baseband digital beamformers can be alternatingly derived in the closed-form expressions in the second stage. Numerical results demonstrate that in contrast to the far-field secure communication relying on the angular disparity, the near-field secure communication mainly relies on the distance disparity between U and E., Comment: 5 pages

The presence of a large number of bots in Online Social Networks (OSN) leads to undesirable social effects. Graph neural networks (GNNs) have achieved state-of-the-art performance in bot detection since they can effectively utilize user interaction. In most scenarios, the distribution of bots and humans is imbalanced, resulting in under-represent minority class samples and sub-optimal performance. However, previous GNN-based methods for bot detection seldom consider the impact of class-imbalanced issues. In this paper, we propose an over-sampling strategy for GNN (OS-GNN) that can mitigate the effect of class imbalance in bot detection. Compared with previous over-sampling methods for GNNs, OS-GNN does not call for edge synthesis, eliminating the noise inevitably introduced during the edge construction. Specifically, node features are first mapped to a feature space through neighborhood aggregation and then generated samples for the minority class in the feature space. Finally, the augmented features are fed into GNNs to train the classifiers. This framework is general and can be easily extended into different GNN architectures. The proposed framework is evaluated using three real-world bot detection benchmark datasets, and it consistently exhibits superiority over the baselines.

Three 12, 8-guaianolide sesquiterpene lactones, including a new compound intybusin F (1), and a new natural product cichoriolide I (2), along with six known 12, 6-guaianolide compounds (4–9) were isolated from the roots of Cichorium intybus L. Their structures were determined by extensive spectroscopic analysis. The absolute configurations of new compounds were elucidated based on analysis of the experimental and calculated electronic circular dichroism spectra. Compounds 1, 2, 4, 7, 8 showed significant effects on facilitating the glucose uptake in oleic acid plus high glucose-stimulated HepG2 cells at 50 μM. In addition, compounds 1, 2, 3, 6, 7 exhibited obvious inhibitory effects against NO production, of them, compounds 1, 2, 7 can significantly decrease the secretion of inflammatory cytokines (TNF-α, IL-6 and COX-2) levels in this hyperglycemic HepG2 cell model.

Additional file 1: Table S1. CUMS stressors in every week of CUMS procedure. Table S2. Results of behavioral tests in the two groups. Table S3. Differential OTUs between the two groups. Table S4. Differential fecal metabolites between the two groups. Table S5. Differential liver metabolites between the two groups. Table S6. Differential neurotransmitters between the two groups.

Proton tunneling is believed to be non-local in ice but has never been shown experimentally. Here we measured thermal conductivity of ice under pressure up to 50 GPa and found it to increase with pressure until 20 GPa but decrease at higher pressures. We attribute this anomalous drop of thermal conductivity to the collective tunneling of protons at high pressures, supported by large-scale quantum molecular dynamics simulations. The collective tunneling loops span several picoseconds in time and are as large as nanometers in space, which match the phonon periods and wavelengths, leading to strong phonon scattering at high pressures. Our results show direct evidence of collective quantum motion existing in high-pressure ice and provide a new perspective to understanding the coupling between phonon propagation and atomic tunneling.

Supplementary Material 1

Supplemental material, sj-pdf-1-jcb-10.1177_0271678X231167924 for Preceding transient ischemic attack was associated with functional outcome after stroke thrombectomy: A propensity score matching study by Jiali Xu, Wenting Guo, Jin Ma, Qingfeng Ma, Jian Chen, Haiqing Song, Changhong Ren, Sijie Li, Yuchuan Ding, Wenbo Zhao and Xunming Ji in Journal of Cerebral Blood Flow & Metabolism

This paper designs a helper-assisted resource allocation strategy in non-orthogonal multiple access (NOMA)-enabled mobile edge computing (MEC) systems, in order to guarantee the quality of service (QoS) of the energy/delay-sensitive user equipments (UEs). To achieve a tradeoff between the energy consumption and the delay, we introduce a novel performance metric, called \emph{energy-delay tradeoff}, which is defined as the weighted sum of energy consumption and delay. The joint optimization of user association, resource block (RB) assignment, power allocation, task assignment, and computation resource allocation is formulated as a mixed-integer nonlinear programming problem with the aim of minimizing the maximal energy-delay tradeoff. Due to the non-convexity of the formulated problem with coupled and 0-1 variables, this problem cannot be directly solved with polynomial complexity. To tackle this challenge, we first decouple the formulated problem into a power allocation, task assignment and computation resource allocation (PATACRA) subproblem. Then, with the solution obtained from the PATACRA subproblem, we equivalently reformulate the original problem as a discrete user association and RB assignment (DUARA) problem. For the PATACRA subproblem, an iterative parametric convex approximation (IPCA) algorithm is proposed. Then, based on the solution obtained from the PATACRA subproblem, we first model the DUARA problem as a four-sided matching problem, and then propose a low-complexity four-sided UE-RB-helper-server matching (FS-URHSM) algorithm. Theoretical analysis demonstrates that the proposed algorithms are guaranteed to converge to stable solutions with polynomial complexity. Finally, simulation results are provided to show the superior performance of our proposed algorithm in terms of the energy consumption and the delay.

Additional file 1: Figure S1. Flowchart for the collection of marine prokaryotic genomes. Figure S2. (A) BGC counts, (B) ratio of BGCs on edge, and (C) number of genomes in genomes with varying degrees of completeness. Figure S3. Bar chart depicting the composition of GCFs within genomes of different categories, (A) all taxa, (B) bacteria, (C) archaea, (D) cultured genome, (E) MAG, and (F) SAG. Figure S4. A selected (A) RiPPs and (B) NRPS gene cluster family (GCF) and the comparison of the BGCs in the corresponding GCF. Figure S5. The predicted core peptides of BGCs in selected RiPPs GCFs. The peptide sequences from each GCF were aligned using Muscle [2] and then visualized in TBtools [3]. Figure S6. Gene cluster family network of the 25 predicted BGCs from Aquimarina muelleri DSM 19832 T. A. muelleri DSM 19832 T possesses 20 orphan BGCs and five genus-specific BGCs (only showing a high similarity to BGCs from Aquimarina strains). Figure S7. Comparison of the experimental mass spectrum of N-acetyltryptamine with its spectrum from the GNPS database. Figure S8. Genomic distribution of secondary metabolite biosynthetic genes clusters in A. muelleri DSM 19832 T. The biosynthetic gene clusters are shown in the outer layer. Table S1. Genomic features and the anti-SMASH results of the 33,904 marine prokaryotes-derived genomes. Table S2. Information about the 70,011 BGCs. Table S3. Information about the reported microbial natural products. Table S4. Information about the 24,536 GCFs. Table S5. Information about the RiPPs BGCs. Table S6. Information about the core peptides encoded by RiPPs BGCs. Table S7. Metabolite annotation in metabolomic data of A. muelleri DSM 19832 T.

A simultaneously transmitting and reflecting surface (STARS) enabled integrated sensing and communications (ISAC) framework is proposed, where a novel bi-directional sensing-STARS architecture is devised to facilitate the full-space communication and sensing. Based on the proposed framework, a joint optimization problem is formulated, where the Cramer-Rao bound (CRB) for estimating the 2-dimension direction-of-arrival of the sensing target is minimized. Two cases are considered for sensing performance enhancement. 1) For the two-user case, an alternating optimization algorithm is proposed. In particular, the maximum number of deployable sensors is obtained in the closed-form expressions. 2) For the multi-user case, an extended CRB (ECRB) metric is proposed to characterize the impact of the number of sensors on the sensing performance. Based on the proposed metric, a novel penalty-based double-loop (PDL) algorithm is proposed to solve the ECRB minimization problem. To tackle the coupling of the ECRB, a general decoupling approach is proposed to convert it to a tractable weighted linear summation form. Simulation results reveal that 1) the proposed PDL algorithm can achieve a near-optimal performance with consideration of sensor deployment; 2) without violating the communication under the quality of service requirements, reducing the receive antennas at the BS does not deteriorate the sensing performance; and 3) it is preferable to deploy more passive elements than sensors in terms of achieving optimal sensing performance, Comment: journal paper

Supplemental material, sj-pdf-1-jcb-10.1177_0271678X231167924 for Preceding transient ischemic attack was associated with functional outcome after stroke thrombectomy: A propensity score matching study by Jiali Xu, Wenting Guo, Jin Ma, Qingfeng Ma, Jian Chen, Haiqing Song, Changhong Ren, Sijie Li, Yuchuan Ding, Wenbo Zhao and Xunming Ji in Journal of Cerebral Blood Flow & Metabolism

Additional file 1: Figure S1. mRNA expression of CD200 in different brain regions after exposure to CSDS. A Analysis of CD200 mRNA expression in the mPFC region of mice after CSDS. B Analysis of CD200 mRNA expression in the Hip region of mice after CSDS. C Analysis of CD200 mRNA expression in the DG region of mice after CSDS. D Analysis of CD200 mRNA expression in the CA1 region of mice after CSDS. E Analysis of CD200 mRNA expression in the CA3 region of mice after CSDS. Data are expressed as mean ± SEM. *P < 0.05; ***P < 0.001. Figure S2. Injection of CD200Fc into the lateral ventricle alleviates CSDS-induced depressive-like behavior. A Experimental timelines for CSDS procedure, CD200Fc administration and behavioral testing. B The social interaction ratio in the SIT of control and CSDS mice with exogenous CD200Fc injection. C, D The immobility time in the TSTand FSTof control and CSDS mice with exogenous CD200Fc injection. E The total distance in the OFT of control and CSDS mice with exogenous CD200Fc injection. Data are expressed as mean ± SEM. *P < 0.05; **P < 0.01; ***P < 0.001. Figure S3. Overexpression of CD200 in DG facilitates the expression of anti-inflammatory factors after CSDS. A Experimental timelines for CSDS procedure, AAV–CD200 stereotaxical injection and behavioral testing. B Analysis of mRNA levels of Arg-1, YM-1, IL-4, TNF-α, IL-6, and IL-1β after injection of AAV–CD200 virus to the DG region in susceptible mice. Data are expressed as mean ± SEM. *P < 0.05; **P < 0.01. Figure S4. CD200 increases the expression of BDNF in the DG brain region of susceptible mice. A Experimental timelines for CSDS procedure, CD200Fc administration and behavioral testing. B Representative immunostaining for BDNFin the DG of control and CSDS group after CD200Fc administration. Scale bars: 80 μm. C The fluorescence intensity of BDNF in the DG of control and CSDS group after CD200Fc administration. Data are expressed as mean ± SEM. *P < 0.05; ***P < 0.001. Figure S5. CD200Fc ameliorates adult hippocampal neurogenesis impairment in susceptible mice. A Experimental timelines for CSDS procedure, CD200Fc administration and behavioral testing. B Representative immunostaining for BrdU/DCX in the DG of control and CSDS group after CD200Fc administration. Scale bars: 40 μm. C, D Statistical graph for the number of BrdU+ and BrdU+ DCX+ cells in the DG of control and CSDS group after CD200Fc administration. Data are expressed as mean ± SEM. *P < 0.05; **P < 0.01; ***P < 0.001. Figure S6. Raw blot data for Fig. 1G, 3C and 4D. Table S1. Sequences of primers for qPCR. Table S2. Statistical analysis for each figure.

Supplementary Material 2

Jian Chen,1 Xiaoyun Liu,1 Jian Lan,1 Tingchao Li,2 Chaokun She,1 Qingyun Zhang,1 Wei Yang3 1Department of Gynecology and Obstetrics, The Third Affiliated Hospital of Zunyi Medical University (The First People’s Hospital of Zunyi), Zunyi City, Guizhou Province, People’s Republic of China; 2Pathology Department, The Third Affiliated Hospital of Zunyi Medical University (The First People’s Hospital of Zunyi), Zunyi City, Guizhou Province, People’s Republic of China; 3Imaging Department, The Third Affiliated Hospital of Zunyi Medical University (The First People’s Hospital of Zunyi), Zunyi City, Guizhou Province, People’s Republic of ChinaCorrespondence: Xiaoyun Liu; Jian Lan, Department of Gynecology and Obstetrics, The Third Affiliated Hospital of Zunyi Medical University (The First People’s Hospital of Zunyi), No. 98, Fenghuang Road, Zunyi, Guizhou, 563000, People’s Republic of China, Email 656479556@qq.com; 1981551873@qq.comAbstract: Rhabdomyosarcoma, a common soft tissue malignant tumor in children and adolescents, is exceedingly rare in adults. Nevertheless, The outcome in adults is very poor, especially when compared to outcomes in children in whom significant improvements in treatment has been achieved. The first case was of a 24-year-old pregnant Chinese woman with a rare primary site of rhabdomyosarcoma in the perineal body. She presented with a perineal mass and was diagnosed during the second trimester of pregnancy, which is a very rare occurrence. The second case was a 70-year-old Chinese woman who suffered from right lower abdominal pain for 1 month and was misdiagnosed with an epithelial ovarian carcinoma. Mesenteric pleomorphic rhabdomyosarcoma was later confirmed by postoperative pathology. Both cases had undergone preoperative examination with chest and abdominal computed tomography (CT) and pelvic magnetic resonance imaging (MRI) examinations, as well as examination of complete blood count, liver panel, renal panel, and serum tumor markers. Diagnosis was based on histopathology and immunohistochemistry. The patient in the first case received chemotherapy after which the mass decreased in size; however, the patient was lost to follow-up. The second case underwent tumor resection and received chemotherapy and radiotherapy.Keywords: rhabdomyosarcoma, adult, pregnancy, diagnosis, heterogeneity, prognosis

Small-loop transient electromagnetic (TEM) method can be used for urban underground space detection. Given the mutual inductance between transmitting and receiving coils, the early secondary field signals are contaminated by primary field signals. To compensate for the primary field, bucking coil technology has been utilized in the airborne TEM system due to attractive features of the technology which include a compensation effect and a strong coupling strength between the receiving coil and the underground body. However, many problems arise when the bucking coil technology is used directly in a ground small-loop TEM system. One is that the size of the receiving coil is limited, resulting in insufficient bandwidth; the other is that the bucking coil brings the near-field effect which causes the loss of shallow information. To solve these problems, we proposed a new TEM structure with non-coplanar bucking compensation. Compared with the traditional design, the new structure overcomes not only the near-field effect, but also reduces the constraint of the receiving coil size. Furthermore, the approach can suppress the primary field coupling more effectively, and has a better fault tolerance for the installation accuracy. The simulation and field experiment results verify the effectiveness and practicability of the new structure.

(Ce,Gd):YAG-Al2O3 composite ceramics were prepared for high-brightness yellow LED (565−590 nm) applications. Phase fraction, microstructure, thermal quenching effect, and luminescent properties of composite ceramics with varying compositions were studied in detail. Collaborating composite ceramics with InGaN blue chips, the relationship between thermal conductivity, temperature rise during LED-driven phosphor conversion, and steady-state luminous efficiency were elucidated. As the proportion of Al2O3 increases from 0 to 40 wt%, the steady-state luminous efficiency of yellow LED is enhanced from 100.88–109.49 lm W−1, benefiting from the increased thermal stability and reduced operating temperature of ceramics (from 141.1–132.2 °C). Additionally, scattering behavior and extraction efficiency of composite ceramics with different thicknesses were investigated.