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Abstract Purpose The purpose of this study was to propose a surgical technique for arthroscopic medial patellofemoral ligament (MPFL) reconstruction with polyethylene suture combined with medial retinaculum plication and to evaluate the efficacy of this surgical technique in the treatment of acute patellar dislocation. Methods Clinical data of patients with acute patellar dislocations treated with arthroscopic MPFL reconstruction with polyethylene tape (FiberTape) combined with medial support band compression were analyzed retrospectively from January 2018 to January 2021. The mean age of the patients was 25.15 ± 4.66 years; the mean follow-up time was 27.5 (24–36) months. Clinical evaluation consisted of apprehension test results, patellar extrapolation test results, Lysholm score, Kujala score, and IKDC score, the Patellar lateral shift distance and patellar tilt angle (PTA) measured by CT scan. Results All patients had no recurrent patellar dislocation or subluxation after surgery, and the apprehension test was negative. In all patients, the Kujala score (36.0 ± 9.9 vs. 98.2 ± 3.1), the IKDC score (48.6 ± 7.0 vs. 90.6 ± 4.4) and the Lysholm score (32.8 ± 10.4 vs. 96.7 ± 3.1) had improved at the 24-month follow up (P

Scanning radar angular super-resolution technology is based on the relationship between the target and antenna pattern, and a deconvolution method is used to obtain angular resolution capabilities beyond the real beam. Most current angular super-resolution methods are based on ideal distortion-free antenna patterns and do not consider pattern changes in the actual process due to the influence of factors such as radar radome, antenna measurement errors, and non-ideal platform motion. In practice, an antenna pattern often has unknown errors, which can result in reduced target resolution and even false target generation. To address this problem, this paper proposes an angular super-resolution imaging method for airborne radar with unknown antenna errors. First, based on the Total Least Square (TLS) criterion, this paper considers the effect of the pattern error matrix and derive the corresponding objective function. Second, this paper employs the iterative reweighted optimization method to solve the objective function by adopting an alternative iteration solution idea. Finally, an adaptive parameter update method is introduced for algorithm hyperparameter selection. The simulation and experimental results demonstrate that the proposed method can achieve super-resolution reconstruction even in the presence of unknown antenna errors, promoting the robustness of the super-resolution algorithm.

Abstract The manipulation of cell identity by reprograming holds immense potential in regenerative medicine, but is often limited by the inefficient acquisition of fully functional cells. This problem can potentially be resolved by better understanding the reprogramming process using in vivo genetic models, which are currently scarce. Here we report that both enterocytes (ECs) and enteroendocrine cells (EEs) in adult Drosophila midgut show a surprising degree of cell plasticity. Depleting the transcription factor Tramtrack in the differentiated ECs can initiate Prospero-mediated cell transdifferentiation, leading to EE-like cells. On the other hand, depletion of Prospero in the differentiated EEs can lead to the loss of EE-specific transcription programs and the gain of intestinal progenitor cell identity, allowing cell cycle re-entry or differentiation into ECs. We find that intestinal progenitor cells, ECs, and EEs have a similar chromatin accessibility profile, supporting the concept that cell plasticity is enabled by pre-existing chromatin accessibility with switchable transcription programs. Further genetic analysis with this system reveals that the NuRD chromatin remodeling complex, cell lineage confliction, and age act as barriers to EC-to-EE transdifferentiation. The establishment of this genetically tractable in vivo model should facilitate mechanistic investigation of cell plasticity at the molecular and genetic level.

The compound AgBiS2, a ternary sulfide, has gained significant attention in the field of photovoltaics due to its characteristic properties of being non-toxic, low-cost, and highly efficient. However, due to the instability of its grain boundaries, the structure of the AgBiS2 may be transformed at high temperatures, consequently influencing the lifetime of devices utilizing this material. In this study, the mechanism of interfacial structural transition and the factors affecting the stability of AgBiS2 were investigated by in-situ transmission electron microscopy. Our observations revealed that, under high-temperature conditions, the structure of the material changes with the formation of triangular hole-like defects at the AgBiS2 interface, which is directly related to the movement of defects. Furthermore, the surface energy of the AgBiS2 crystal planes is different due to different atomic arrangements. Combining the experiments with theoretical calculations, we found that the defects such as dislocations tend to cluster on the high-energy plane (111), thereby leading to localized stress and strain concentration. Then, the structure transforms by reconstructing its interfacial atoms to reduce the local stress. Of note, this reconstruction leads to the formation of triangular hole-like defects, consequently reducing the overall energy of the system.

The adhesive layer is an important factor affecting the mechanical properties of FRP- bamboo scrimber composite beams (FBSCB). However, studies on the interfacial shear stresses in the adhesive layers with both ends of FRP and bamboo scrimber beam aligned have been rarely reported. To this end, a two-parameter theoretical calculation model and a finite element model (FEM) based on cohesive zone model were hereby established to solve for the adhesive layer interface shear stresses, which was verified by four-point bending experiments. The results show that both the two-parameter theoretical model and the FEM can effectively compute the shear stress of the adhesive layer. Meanwhile, the FEM simulation results not only reflect the detailed changes of the shear stress, but also provide a better analysis of the shear stress at the adhesive layer with a small fluctuation range. There are three zones of shear stress at the adhesive layer of FBSCB under four-point bending load, i.e., the bending and shearing zone, the transition zone and the pure bending zone. In the bending and shearing zone, the shear stress of the adhesive layer interface increases 2.61 times and 2.5 times, respectively when the thickness and elastic modulus of FRP increase three times. However, the stress remains constant at zero in the pure bending zone.

Establishing cultivated grassland in the Qinghai-Tibet Plateau region is an effective method to address the conflict between vegetation and livestock. However, the high altitude, low temperature, and arid climate in the region result in slow regeneration and susceptibility to degradation of mixed cultivation grassland containing perennial legumes and gramineous plants. Therefore, we aim to through field experiments, explore the feasibility of establishing mixed cultivation grassland of Poaceae species in the region by utilizing two grass species, Poa pratensis L. and Puccinellia tenuiflora. By employing a mixture of P. pratensis and P. tenuiflora to establish cultivated grassland, we observed significant changes in forage yield over time. Specifically, during the 3rd to 6th years of cultivation, the yield in the mixed grassland was higher than in monocultures. It exceeded the yield of monoculture P. tenuiflora by 19.38% to 29.14% and surpassed the monoculture of P. pratensis by 17.18% to 62.98%. Through the analysis of soil physicochemical properties and soil microbial communities in the cultivated grassland, the study suggests that the mixed grassland with Poaceae species can enhance soil enzyme activity and improve soil microbial communities. Consequently, this leads to increased soil nutrient levels, enhanced nitrogen fixation efficiency, and improved organic phosphorus conversion efficiency. Therefore, establishing mixed grasslands with Poaceae species in the Qinghai-Tibet Plateau region is deemed feasible.

The output voltage of inverters is influenced by nonlinear factors such as dead time and voltage drops, injecting low-order harmonics. This results in fifth and seventh harmonic distortions in the stator current, causing periodic torque ripples and significantly affecting the control precision of Permanent Magnet Synchronous Motors (PMSMs). To address this issue, this paper proposes a control strategy named quasi-proportional-resonant sliding mode control (QPR-SMC). Initially, sliding mode control is employed as the current controller to enhance disturbance rejection capability and provide a rapid dynamic response. Subsequently, a quasi-proportional-resonant controller is introduced to extract the sixth harmonic component from the current, which is then used as a compensation term for the sliding mode control surface. Finally, the current tracking error and the compensation term are combined as inputs to the sliding mode control law, forming a current error-proportional resonant-sliding mode control surface. This approach enhances the harmonic suppression capability of the system. The results demonstrate that the proposed method effectively reduces the fifth and seventh harmonic components in the three-phase current and mitigates motor jitter by suppressing the sixth harmonic in the d–q coordinate system.

Intelligent scheduling of knitting workshops is the key to realizing knitting intelligent manufacturing. In view of the uncertainty of the workshop environment, it is difficult for existing scheduling algorithms to flexibly adjust scheduling strategies. This paper proposes a scheduling algorithm architecture based on deep reinforcement learning (DRL). First, the scheduling problem of knitting intelligent workshops is represented by a disjunctive graph, and a mathematical model is established. Then, a multi-proximal strategy (multi-PPO) optimization training algorithm is designed to obtain the optimal strategy, and the job selection strategy and machine selection strategy are trained at the same time. Finally, a knitting intelligent workshop scheduling experimental platform is built, and the algorithm proposed in this paper is compared with common heuristic rules and metaheuristic algorithms for experimental testing. The results show that the algorithm proposed in this paper is superior to heuristic rules in solving the knitting workshop scheduling problem, and can achieve the accuracy of the metaheuristic algorithm. In addition, the response speed of the algorithm in this paper is excellent, which meets the production scheduling needs of knitting intelligent workshops and has a good guiding significance for promoting knitting intelligent manufacturing.

Elymus sibiricus plays a crucial role in ecological protection and animal husbandry. However, after many years of growth, the biomass of E. sibiricus decreases, and the plants degrade. Moreover, there is no good solution to the problem of degradation of Elymus sibiricus; the addition of nitrogen (N) and phosphorus (P) fertilizers is the primary measure of cultivation management to improve yield, so it is crucial to find the appropriate level of fertilization. This study performed a two-factor split-plot experiment, including four levels of N (0, 45, 60, and 75 kg·hm−2) and four levels of P (0, 60, 75, and 90 kg·hm−2), to investigate the effect of N and P fertilizers on yield, yield components, and photosynthesis characteristics of E. sibiricus. The results showed that the forage yield in 2017 was higher than in 2018. The forage yield in 2017 was highest at N75P0 with a value of 29,926 kg·hm−2, and in 2018 it was highest at N45P0 and N75P0 with a value of 12,266 kg·hm−2 and 12,233 kg·hm−2, respectively, which demonstrates the large impact of year effects on the forage yield. All traits increased with the increase in N and P fertilizer application, but with excess fertilizer application, the photosynthesis was limited, leading to a slowdown in growth and a decrease in yield. In addition, under adequate N fertilization, the role of P fertilization was not significant (p > 0.05). N, P, and N × P can significantly (p < 0.05) affect the yield traits and forage yield of E. sibiricus. According to the PCA, it is clear that N fertilizer has the largest effect, and the growth capacity of degraded E. sibiricus grassland can be restored by adding 75 kg·hm−2 of nitrogen fertilizer.

We propose a simple interpretation of the γγ excesses reported by both CMS and ATLAS groups at 95 GeV together with the LEP excess in the Zbb¯ channel around the same mass in terms of a neutral scalar field in the minimal left-right symmetric model (LRSM). We point out that the scalar field which implements the seesaw mechanism for neutrino masses has all the right properties to explain these observations, without introducing any extra fields. The key point is that this scalar particle is hardly constrained because it couples only to heavy right-handed particles. As a result, the diphoton decay mode receives contributions from both mixing with the Standard Model (SM) Higgs and the heavy charged bosons in the LRSM. The latter depends on the SU(2)R×U(1)B−L symmetry breaking scale vR. The complete allowed parameter space for explaining the 95 GeV excesses in this model can be probed with the high-precision measurements of the SM Higgs mixing with other scalars at the high-luminosity LHC and future Higgs factories.

Nitrogen (N) addition is a simple and effective field management approach to enhancing plant productivity. Nonetheless, the regulatory mechanisms governing nitrogen concentrations and their effect on soil enzyme activity, nutrient levels, and seed yield in the Festuca kirilowii seed field have yet to be elucidated. Therefore, this study sought to investigate the effect of N fertilizer application on soil enzyme activities, soil nutrients, and seed yield of F. kirilowii Steud cv. Huanhu, the only domesticated variety in the Festuca genus of the Poaceae family, was investigated based on two-year field experiments in the Qinghai–Tibet Plateau (QTP). Results showed that N input significantly affected soil nutrients (potential of hydrogen, total nitrogen, organic matter, and total phosphorus). In addition, soil enzyme activities (urease, catalase, sucrase, and nitrate reductase) significantly increased in response to varying N concentrations, inducing changes in soil nutrient contents. Introducing N improved both seed yield and yield components (number of tillers and number of fertile tillers). These findings suggest that the introduction of different concentrations of N fertilizers can stimulate soil enzyme activity, thus hastening nutrient conversion and increasing seed yield. The exhaustive evaluation of the membership function showed that the optimal N fertilizer treatment was N4 (75 kg·hm−2) for both 2022 and 2023. This finding provides a practical recommendation for improving the seed production of F. kirilowii in QTP.

Due to the large terrain fluctuation and drop in Qianshuta well field, the layout of the ground large loop transient electromagnetic method detection device is limited. In order to find out the distribution range of goaf under the second Shanjing line of oil and gas pipeline in this area, numerical simulation and field test of small loop transient electromagnetic method were carried out to analyze the feasibility of ground detection, and optimized parameters were applied to the field. The results show that the numerical simulation confirms that the 3 m×3 m small loop transient electromagnetic method can effectively detect the goaf with a depth of more than 200 m and a mining height of more than 1 m, and has a more obvious effect on the water-filled goaf with low resistance; the field test adopts the small loop transient electromagnetic method with optimized parameters such as the length of the transmitting wire frame 3 m×3 m, the number of stacking times of 15, the transmitting frequency of 16 Hz, and more than 8 A transmitting current, which can achieve the purpose of effective detection and verify the correctness of the numerical simulation; a total of 5 abnormal areas were delineated and explained in the No.3 coal seam, which were inferred to be gobs or burned rock voids. The reliability of the small loop transient electromagnetic detection method is fully verified.

Due to natural and anthropogenic disturbances, natural gas hydrates with morphologies of nodules and chunks dissociate and release massive free gas, creating large cavities within fine-grained marine sediments. However, it is still a challenge to quantify the impact of gas cavities on mechanical properties of cavitied fine-grained marine sediments as there is a lack of efforts focusing on the inner structure visualization. In this study, an oedometer test and X-ray computed tomography scans are jointly conducted on marine clayey silt with gas cavities, and the confined compressibility as well as the inner structure change under an undrained condition are explored, followed by development of a theoretical model depicting the void ratio change. The results show that vertical loading induces a void ratio reduction, and the reduced void ratio can fully recover after being unloaded. Although being fully recovered, unrecovered changes of the inner structure still remain after being unloaded. Examples include closed cracks in the lower matrix, new occurring cracks in the upper matrix, and the fragmented gas cavity. In addition, the void ratio linearly increases with the increasing inverse of normalized pore gas pressure, while the coefficient of the effective stress linearly decreases with the increasing inverse of normalized vertical loading stress. The proposed theoretical model captures the essential physics behind undrained confined deformation of fine-grained marine sediments with gas cavities when subjected to loading and unloading.

Regularization methods, including single constraint regularization and joint constraints regularization, have been applied to radar forward-looking super-resolution imaging. However, the ill-posedness of the antenna measurement matrix is serious, which degrades the imaging performance in low signal-to-noise ratio (SNR) conditions. In our work, the following two-step regularization strategy is proposed to achieve super-resolution imaging in low SNR conditions: 1) in the first step, a projection regularization method is designed to repair the ill-posed antenna measurement matrix by truncating and modifying singular values, which mitigates the ill-posedness of the deconvolution process and suppresses noise amplification and 2) in the second step, based on the repaired convolution model, the $L_{1}$ norm is introduced for sparse targets to improve the radar azimuth resolution. The iteratively reweighted norm solver is employed to solve the optimization problem. The superiority of the proposed two-step strategy is analyzed from the perspectives of singular value decomposition. The effectiveness of the proposed strategy is verified by simulated and experimental data.

Abstract Background The association between Glasgow Prognostic Score (GPS) and the modified Glasgow Prognostic Score (mGPS) and clinical outcomes in patients receiving immune checkpoint inhibitors (ICIs) remains controversial. Thus, this meta‐analysis aimed to examine the prognostic performance of GPS and mGPS in patients treated with ICIs. Methods Eligible studies were retrieved from searches of EMBASE, PubMed, Web of Science, and Cochrane Library until July 2021. The hazard ratio (HR) and 95% confidence intervals (CIs) were pooled by using fixed‐effect or random‐effects model to evaluate the influence of GPS/mGPS on overall survival (OS) and progression‐free survival (PFS). Results A total of 1164 patients were included. Overall, mGPS score of 2 and 1 were related to inferior OS (p

Here the authors elucidate a simple transcription factor code that underlies the complex genetic specification of enteroendocrine cell (EE) subtypes, and reveal significant cellular plasticity amongst EE subtypes.

Abstract We address a method of limiting neutron–mirror neutron mixing ( $$\epsilon _{nn'}$$ ϵ n n ′ ) by analyzing its effect on neutron star (NS) heating. This method employs observational bounds on the surface temperature of NSs to constrain $$\epsilon _{nn'}$$ ϵ n n ′ . It has been suggested that the bound obtained this way is so stringent that it would exclude any discovery of $$n-n'$$ n - n ′ oscillation in the currently planned terrestrial experiments at various laboratories. This conclusion motivated us to critically analyze this suggestion in more detail. In this note, we point out a very interesting new effect present in nearly exact mirror models, which can significantly affect this bound. The new element is that in nearly exact mirror models there is the mirror analog of $$\beta $$ β decay, i.e. $$n' \rightarrow p' + e' + {\bar{\nu }}'_e$$ n ′ → p ′ + e ′ + ν ¯ e ′ , which creates a cloud of mirror particles $$n'$$ n ′ , $$p'$$ p ′ , $$e'$$ e ′ , $$D'$$ D ′ and He $$'$$ ′ inside the NS. The resulting $$e'$$ e ′ can “rob” the energy generated by the $$n \rightarrow n'$$ n → n ′ transition from the NS, via $$e-e'$$ e - e ′ scattering enabled by the presence of a (minute) millicharge in mirror particles. Such a tiny millicharge on mirror particles is highly likely in these models. This results in energy being emitted as unobserved mirror photons via fast mirror bremsstrahlung. whose effect is to relax the stringent bounds on $$\epsilon _{nn'}$$ ϵ n n ′ .

Abstract In this work, by using the machine learning methods, we study the sensitivities of heavy pseudo-Dirac neutrino N in the inverse seesaw at the high-energy hadron colliders. The production process for the signal is pp → ℓ → 3ℓ + E T miss $$ {E}_T^{\mathrm{miss}} $$ , while the dominant background is pp → WZ → 3ℓ + E T miss $$ {E}_T^{\mathrm{miss}} $$ . We use either the Multi-Layer Perceptron or the Boosted Decision Tree with Gradient Boosting to analyse the kinematic observables and optimize the discrimination of background and signal events. It is found that the reconstructed Z boson mass and heavy neutrino mass from the charged leptons and missing transverse energy play crucial roles in separating the signal from backgrounds. The prospects of heavy-light neutrino mixing |V ℓN | 2 (with ℓ = e, μ) are estimated by using machine learning at the hadron colliders with s $$ \sqrt{s} $$ = 14 TeV, 27 TeV, and 100 TeV, and it is found that |V ℓN | 2 can be improved up to O $$ \mathcal{O} $$ (10 −6) for heavy neutrino mass m N = 100 GeV and O $$ \mathcal{O} $$ (10 −4) for m N = 1 TeV.

Abstract Objective To describe and analyze the predictive models of the prognosis of patients with hepatocellular carcinoma (HCC) undergoing systemic treatment. Design Systematic review. Data sources PubMed and Embase until December 2020 and manually searched references from eligible articles. Eligibility criteria for study selection The development, validation, or updating of prognostic models of patients with HCC after systemic treatment. Results The systematic search yielded 42 eligible articles: 28 articles described the development of 28 prognostic models of patients with HCC treated with systemic therapy, and 14 articles described the external validation of 32 existing prognostic models of patients with HCC undergoing systemic treatment. Among the 28 prognostic models, six were developed based on genes, of which five were expressed in full equations; the other 22 prognostic models were developed based on common clinical factors. Of the 28 prognostic models, 11 were validated both internally and externally, nine were validated only internally, two were validated only externally, and the remaining six models did not undergo any type of validation. Among the 28 prognostic models, the most common systemic treatment was sorafenib (n = 19); the most prevalent endpoint was overall survival (n = 28); and the most commonly used predictors were alpha-fetoprotein (n = 15), bilirubin (n = 8), albumin (n = 8), Child–Pugh score (n = 8), extrahepatic metastasis (n = 7), and tumor size (n = 7). Further, among 32 externally validated prognostic models, 12 were externally validated > 3 times. Conclusions This study describes and analyzes the prognostic models developed and validated for patients with HCC who have undergone systemic treatment. The results show that there are some methodological flaws in the model development process, and that external validation is rarely performed. Future research should focus on validating and updating existing models, and evaluating the effects of these models in clinical practice. Systematic review registration PROSPERO CRD42020200187 .

BackgroundAdvanced hepatocellular carcinoma (HCC) is characterized as symptomatic tumors [performance status (PS) score of 1-2], vascular invasion and extrahepatic spread, but patients with PS1 alone may be eliminated from this stage. Although liver resection is used for liver-confined HCC, its role in patients with PS1 alone remains controversial. Therefore, we aimed to explore its application in such patients and identify potential candidates.MethodsEligible liver-confined HCC patients undergoing liver resection were retrospectively screened in 15 Chinese tertiary hospitals, with limited tumor burden, liver function and PS scores. Cox-regression survival analysis was used to investigate the prognostic factors and develop a risk-scoring system, according to which patients were substratified using fitting curves and the predictive values of PS were explored in each stratification.ResultsFrom January 2010 to October 2021, 1535 consecutive patients were selected. In the whole cohort, PS, AFP, tumor size and albumin were correlated with survival (adjusted P

This paper proposes an improved Soft Actor–Critic Long Short-Term Memory (SAC-LSTM) algorithm for fast path planning of mobile robots in dynamic environments. To achieve continuous motion and better decision making by incorporating historical and current states, a long short-term memory network (LSTM) with memory was integrated into the SAC algorithm. To mitigate the memory depreciation issue caused by resetting the LSTM’s hidden states to zero during training, a burn-in training method was adopted to boost the performance. Moreover, a prioritized experience replay mechanism was implemented to enhance sampling efficiency and speed up convergence. Based on the SAC-LSTM framework, a motion model for the Turtlebot3 mobile robot was established by designing the state space, action space, reward function, and overall planning process. Three simulation experiments were conducted in obstacle-free, static obstacle, and dynamic obstacle environments using the ROS platform and Gazebo9 software. The results were compared with the SAC algorithm. In all scenarios, the SAC-LSTM algorithm demonstrated a faster convergence rate and a higher path planning success rate, registering a significant 10.5 percentage point improvement in the success rate of reaching the target point in the dynamic obstacle environment. Additionally, the time taken for path planning was shorter, and the planned paths were more concise.

Although numerous effective Simultaneous Localization and Mapping (SLAM) systems have been developed, complex dynamic environments continue to present challenges, such as managing moving objects and enabling robots to comprehend environments. This paper focuses on a visual SLAM method specifically designed for complex dynamic environments. Our approach proposes a dynamic feature removal module based on the tight coupling of instance segmentation and multi-view geometric constraints (TSG). This method seamlessly integrates semantic information with geometric constraint data, using the fundamental matrix as a connecting element. In particular, instance segmentation is performed on frames to eliminate all dynamic and potentially dynamic features, retaining only reliable static features for sequential feature matching and acquiring a dependable fundamental matrix. Subsequently, based on this matrix, true dynamic features are identified and removed by capitalizing on multi-view geometry constraints while preserving reliable static features for further tracking and mapping. An instance-level semantic map of the global scenario is constructed to enhance the perception and understanding of complex dynamic environments. The proposed method is assessed on TUM datasets and in real-world scenarios, demonstrating that TSG-SLAM exhibits superior performance in detecting and eliminating dynamic feature points and obtains good localization accuracy in dynamic environments.

Multistatic airborne SAR (MuA-SAR) benefits from the ability to flexibly adjust the positions of multiple transmitters and receivers in space, which can shorten the synthetic aperture time to achieve the required resolution. To ensure both imaging efficiency and quality of different system spatial configurations and trajectories, the fast factorized back projection (FFBP) algorithm is proposed. However, if the FFBP algorithm based on polar coordinates is directly applied to the MuA-SAR system, the interpolation in the recursive fusion process will bring the problem of redundant calculations and error accumulation, leading to a sharp decrease in imaging efficiency and quality. In this paper, a unified Cartesian fast factorized back projection (UCFFBP) algorithm with a multi-level regional attention strategy is proposed for MuA-SAR fast imaging. First, a global Cartesian coordinate system (GCCS) is established. Through designing the rotation mapping matrix and phase compensation factor, data from different bistatic radar pairs can be processed coherently and efficiently. In addition, a multi-level regional attention strategy based on maximally stable extremal regions (MSER) is proposed. In the recursive fusion process, only the suspected target regions are paid more attention and segmented for coherent fusion at each fusion level, which further improves efficiency. The proposed UCFFBP algorithm ensures both the quality and efficiency of MuA-SAR imaging. Simulation experiments verified the effectiveness of the proposed algorithm.

Abstract This meta‐analysis was performed to assess the relationship between Lenvatinib use for malignancy and hypertension (HTN). A total of 2483 patients met inclusion criteria. The relative risk (RR) for all‐grade and high‐grade (≧3) HTN were 2.61 (p ≦ .001) and 3.35 (p≦ .001), respectively, for Lenvatinib compared with other multitarget tyrosine kinase inhibitors or placebo. The cumulative incidence of all‐grade and high‐grade HTN was 70% and 34%, respectively. The studies with median treatment duration (TD) longer than 7.4 months demonstrated a higher incidence of high‐grade HTN than studies with shorter TD (34% vs 28%). The incidence of all levels of HTN increased with TD (68% vs 49%). Trials with median progression‐free survival (PFS) longer than nine months had a higher incidence of both all‐grade (37% vs 28%) and high‐grade (71% vs 48%) HTN. Lenvatinib, a drug commonly used in cancer treatment, is a risk factor for the development of HTN. A longer duration of Lenvatinib treatment was associated with higher frequency of HTN. Further investigation for Lenvatinib of the association between the occurrence of HTN and prognosis will be warranted.

This study aims to reveal the effect of the blade chord length on the startup performance of the lift rotor that converts the kinetic energy of tidal currents. The computational fluid dynamics technique was used to simulate unsteady flows around the rotor. The six degrees of freedom method was adopted to model the correlation between the rotational speed of the rotor and influential torques acting on the rotor. A comparative analysis of transient flows, rotational speed, and output torque was implemented at different initial azimuthal angles. The results show that as the rotor starts up at the minimum torque, the time required to attain the maximum rotational speed is longer than that associated with the maximum torque. As the maximum rotational speed is reached, low-pressure elements are produced in the area enclosed by the rotor blades, which is insensitive to the initial setting angle. A large area of low pressure is responsible for low output torque. During the startup process, the rotational speed experiences stages of sharp increase, fluctuating decrease, and moderate fluctuation, as is common at different blade chord lengths. As the chord length increases from 0.16 to 0.24 m, the startup process is extended by 0.63 s, and the average rotational speed in the stabilization stage decreases.

BackgroundHepatoma arterial-embolization prognostic (HAP) series scores have been proposed for prognostic prediction in patients with unresectable hepatocellular carcinoma (uHCC) undergoing transarterial chemoembolization (TACE). However, their prognostic value in TACE plus sorafenib (TACE-S) remains unknown. Here, we aim to evaluate their prognostic performance in such conditions and identify the best model for this combination therapy.MethodsBetween January 2012 and December 2018, consecutive patients with uHCC receiving TACE-S were recruited from 15 tertiary hospitals in China. Cox regression analyses were used to investigate the prognostic values of baseline factors and every scoring system. Their prognostic performance and discriminatory performance were evaluated and confirmed in subgroup analyses.ResultsA total of 404 patients were enrolled. In the whole cohort, the median follow-up period was 44.2 (interquartile range (IQR), 33.2–60.7) months, the median overall survival (OS) time was 13.2 months, and 336 (83.2%) patients died at the end of the follow-up period. According to multivariate analyses, HAP series scores were independent prognostic indicators of OS. In addition, the C-index, Akaike information criterion (AIC) values, and time-dependent area under the receiver operating characteristic (ROC) curve (AUC) indicated that modified HAP (mHAP)-III had the best predictive performance. Furthermore, the results remained consistent in most subsets of patients.ConclusionHAP series scores exhibited good predictive ability in uHCC patients accepting TACE-S, and the mHAP-III score was found to be superior to the other HAP series scores in predicting OS. Future prospective high-quality studies should be conducted to confirm our results and help with treatment decision-making.

Abstract We study the non-standard interactions of neutrinos with light leptonic scalars (ϕ) in a global (B − L)-conserved ultraviolet (UV)-complete model. The model utilizes Type-II seesaw motivated neutrino interactions with an SU(2) L -triplet scalar, along with an additional singlet in the scalar sector. This UV-completion leads to an enriched spectrum and consequently new observable signatures. We examine the low-energy lepton flavor violation constraints, as well as the perturbativity and unitarity constraints on the model parameters. Then we lay out a search strategy for the unique signature of the model resulting from the leptonic scalars at the hadron colliders via the processes H ±± → W ± W ± ϕ and H ± → W ± ϕ for both small and large leptonic Yukawa coupling cases. We find that via these associated production processes at the HL-LHC, the prospects of doubly-charged scalar H ±± can reach up to 800 (500) GeV and 1.1 (0.8) TeV at the 2σ (5σ) significance for small and large Yukawa couplings, respectively. A future 100 TeV hadron collider will further increase the mass reaches up to 3.8 (2.6) TeV and 4 (2.7) TeV, at the 2σ (5σ) significance, respectively. We also demonstrate that the mass of ϕ can be determined at about 10% accuracy at the LHC for the large Yukawa coupling case even though it escapes as missing energy from the detectors.

The search for low-altitude targets becomes a more challenging task for airborne phased array radar, due to the limited system resources and serious ground clutter. In this article, an optimal search strategy using the digital elevation model (DEM) is proposed to allow for a fast and high-probability searches for low-altitude targets. First, a clutter-free detection region is formed by introducing the DEM. Compared with the traditional methods, the detection probability of the low-altitude targets can be improved. Second, the search problem is transformed into a constrained multiobjective optimization problem. The proposed strategy can simultaneously minimize the search time and maximize the target detection probability. Finally, two intelligent evolutionary algorithms are compared to verify the proposed strategy, and the proposed strategy is also testified by utilizing real DEM data of Dujiangyan, Sichuan, China. Simulated results indicate that the proposed optimal search framework improves the detection probability and reduces time cost for low-altitude targets.

Changes in undrained shear strength are important to the stability analysis of hydrate reservoirs during natural gas hydrate production. This study proposes a prediction model of undrained shear strength of hydrate-bearing fine-grained sediments based on the critical state theory. Several consolidated undrained triaxial shear tests are conducted on hydrate-bearing fine-grained samples from the Shenhu area of the South China Sea. The effects of effective consolidation stresses and hydrate saturations on the undrained shear strength are investigated. The results show that the undrained shear strength increases linearly with increasing effective consolidation stress. When the hydrate saturation is greater than the effective hydrate saturation, the undrained shear strength significantly increases with increasing hydrate saturation. The undrained shear strength of hydrate-bearing fine-grained sediments is a two-parameter function of effective hydrate saturation and a void ratio. The instability risk of the hydrate reservoir under undrained conditions is greater than that of under-drained or partially drained conditions. Furthermore, low-porosity reservoirs face more shear strength loss from hydrate decomposition yet lower risk than high-porosity ones. These results can improve the understanding of mechanical properties of hydrate-bearing fine-grained sediments under undrained conditions. This study also has implications for the design of marine structures in areas with hydrate-bearing sediment.

Siberian wildrye (Elymus sibiricus L.) is a perennial and self-fertilizing forage grass that support animal husbandry and environmental sustenance in the world. In order to explore influence of nitrogen(N) application in Siberian wildrye seed production, the field experiments were conducted to evaluated the effect of different N treatments (of 0, 30, 60, 90 and 120 kg/hm2) on dry matter, N accumulation, transport and utilization, yield components and seed yield of Siberian wildrye DJ-01, which was generated and stored in our lab. The results showed that the 90 kg/hm2 group significantly improved Fertile tillers m−2, spikelets per fertile tiller, 1000-grain weight and seed yield. Furthermore, the seed yield of 90 kg/hm2 group reached 899.3 kg/hm2 and elevated 45.6% compared with 0(CK) group. Moreover, we found that Siberian wildrye exhibited more advantages in dry matter and N translocation. The increment of grain N depended on pre-anthesis dry matter translocation (Pre-DMT) and pre-anthesis N translocation (Pre-NT), but not post-anthesis dry matter accumulation (Post-DMA) and post-anthesis N uptake (Post-NU) to seed yield. With the increase of N, N partial productivity and N absorption efficiency gradually decreased. All data showed the 90 kg/hm2 had the best effects on seed yield components, seed yield, dry matter accumulation (DMA), N accumulation and N efficiency. These results provide an ideal strategy to expand the plant area of Siberian wildrye.

Temperature and water potentials are considered the most critical environmental factors in seed germinability and subsequent seedling establishment. The thermal and water requirements for germination are species-specific and vary with the environment in which seeds mature from the maternal plants. Pedicularis kansuensis is a root hemiparasitic weed that grows extensively in the Qinghai–Tibet Plateau’s degraded grasslands and has seriously harmed the grasslands ecosystem and its utilization. Information about temperatures and water thresholds in P. kansuensis seed germination among different populations is useful to predicting and managing the weed’s distribution in degraded grasslands. The present study evaluated the effects of temperature and water potentials on P. kansuensis seed germination in cool and warm habitats, based on thermal time and hydrotime models. The results indicate that seeds from cool habitats have a higher base temperature than those from warm habitats, while there is no detectable difference in optimum and ceiling temperatures between habitats. Seed germination in response to water potential differed among the five studied populations. There was a negative correlation between the seed populations’ base water potential for 50% (Ψb(50)) germination and their hydrotime constant (θH). The thermal time and hydrotime models were good predictors of five populations’ germination time in response to temperature and water potentials. Consequently, future studies should consider the effects of maternal environmental conditions on seed germination when seeking effective strategies for controlling hemiparasitic weeds in alpine regions.

Abstract The low-energy U(1) B−L gauge symmetry is well-motivated as part of beyond Standard Model physics related to neutrino mass generation. We show that a light B − L gauge boson Z′ and the associated U(1) B−L -breaking scalar φ can both be effectively searched for at high-intensity facilities such as the near detector complex of the Deep Underground Neutrino Experiment (DUNE). Without the scalar φ, the Z′ can be probed at DUNE up to mass of 1 GeV, with the corresponding gauge coupling g BL as low as 10 −9. In the presence of the scalar φ with gauge coupling to Z′, the DUNE capability of discovering the gauge boson Z′ can be significantly improved, even by one order of magnitude in g BL , due to additional production from the decay φ → Z′Z′. The DUNE sensitivity is largely complementary to other long-lived Z′ searches at beam-dump facilities such as FASER and SHiP, as well as astrophysical and cosmological probes. On the other hand, the prospects of detecting φ itself at DUNE are to some extent weakened in presence of Z′, compared to the case without the gauge interaction.

Abstract The P2 experiment aims at high-precision measurements of the parity-violating asymmetry in elastic electron-proton and electron-12C scatterings with longitudinally polarized electrons. We discuss here the sensitivity of P2 to new physics mediated by an additional neutral gauge boson Z′ of a new U(1)′ gauge symmetry. If the charge assignment of the U(1)′ is chiral, i.e., left- and right-handed fermions have different charges under U(1)′, additional parity-violation is induced directly. On the other hand, if the U(1)′ has a non-chiral charge assignment, additional parity-violation can be induced via mass or kinetic Z-Z′ mixing. By comparing the P2 sensitivity to existing constraints, we show that in both cases P2 has discovery potential over a wide range of Z′ mass. In particular, for chiral models, the P2 experiment can probe gauge couplings at the order of 10 −5 when the Z′ boson is light, and heavy Z′ bosons up to 79 (90) TeV in the proton (12C) mode. For non-chiral models with mass mixing, the P2 experiment is sensitive to mass mixing angles smaller than roughly 10 −4, depending on model details and gauge coupling magnitude.

Abstract As a starting point in equipment manufacturing, sawing plays an important role in industrial production. Intelligent manufacturing equipment is an important carrier of intelligent manufacturing technologies. Due to the backwardness of intelligent technology, the comprehensive performance of sawing equipments in China is obviously different from that in foreign countries. State of the art of advanced sawing equipments is investigated along with the technical bottleneck of sawing machine tool manufacturing, and a new industrial scheme of replacing turning-milling by sawing is described. The key technologies of processing-measuring integrated control, multi-body dynamic optimization, the collaborative sawing network framework, the distributed cloud sawing platform, and the self-adapting service method are analyzed; with consideration of the problems of poor processing control stableness, low single machine intelligence level, no on-line processing data service and active flutter suppression of sawing with wide-width and heavy-load working conditions. Suggested directions for further research, industry implementation, and industry-research collaboration are provided.

Abstract The left-right symmetric model (LRSM) is a well-motivated framework to restore parity and implement seesaw mechanisms for the tiny neutrino masses at or above the TeV-scale, and has a very rich phenomenology at both the high-energy and high-precision frontiers. In this paper we examine the phase transition and resultant gravitational waves (GWs) in the minimal version of LRSM. Taking into account all the theoretical and experimental constraints on LRSM, we identify the parameter regions with strong first-order phase transition and detectable GWs in the future experiments. It turns out in a sizeable region of the parameter space, GWs can be generated in the phase transition with the strength of 10 −17 to 10 −12 at the frequency of 0.1 to 10 Hz, which can be detected by BBO and DECIGO. Furthermore, GWs in the LRSM favor a relatively light SU(2) R -breaking scalar H 3 0 $$ {H}_3^0 $$ , which is largely complementary to the direct searches of a long-lived neutral scalar at the high-energy colliders. It is found that the other heavy scalars and the right-handed neutrinos in the LRSM also play an important part for GW signal production in the phase transition.

Real aperture radar (RAR) usually sweeps a wide sector to continuously observe the scenario of interest. Because its angular resolution is limited by the size of the antenna aperture, target reconstruction methods are widely applied to obtain super-resolution radar images. However, the wide-sector processing mode suffers from high operational complexity because of the high-dimensional matrix inversion. Even worse, for the targets located at the scene edge, its echo data are received less than half beamwidth. The incomplete echo data will lead to the deformation of the reconstructed targets by existing reconstruction methods. To overcome the two problems, a data extrapolation-based parallel iterative adaptive approach is proposed to fast reconstruct the targets in the whole sector without the distortion at the scene edge. First, the echo model of RAR is repaired to remedy the model error. Then, based on the correlation of the echo data within one beamwidth, an autoregressive model is adopted to extrapolate the data of the missing half beamwidth. Finally, a parallel iterative adaptive approach method is proposed to efficiently recover the targets by exploiting the regular characteristics of the repaired steering matrix. Simulations and experimental data are applied to verify the proposed method.

Total variation-sparse (TV-sparse)-based multiconstraint devonvolution method has been used to realize superresolution imaging and preserve target contour information simultaneously of radar forward-looking imaging. However, due to the existence of matrix inversion, it suffers from high computational complexity, which restricts the ability of radar real-time imaging. In this article, an Gohberg-Semencul (GS) decomposition-based fast TV-sparse (FTV-sparse) method is proposed to reduce the computational complexity of TV-sparse method. The acceleration strategy utilizes the low displacement rank features of Toeplitz matrix, realizing fast matrix inversion by using a GS representation. It reduces the computational complexity of traditional TV-sparse method from O(N3) to O(N2), benefiting for improvement of the computing efficiency. The simulation and experimental data processing results show that the proposed FTV-sparse method has almost no resolution loss compared with the traditional TV sparse method. Hardware test results show that the proposed FTV-sparse method significantly improves the computational efficiency of TVsparse method.

Spaceborne-airborne multistatic synthetic aperture radar (SA-MuSAR) has the ability to provide high-resolution forward-looking imagery for receivers, but it relies on careful design of the geometric configuration (GC). In this article, a forward-looking GC optimization design method is proposed to obtain a high-quality fused image with limited observation time. First, the relationship between the spatial resolution and GC is illustrated by the wavenumber spectrum distribution of SA-MuSAR. Second, GC evaluators depending on the distribution of multiple wavenumber spectrum data are proposed. The GC design problem of coherent SA-MuSAR is transformed into a constrained multiobjective optimization problem. An intelligent evolutionary algorithm is adopted to optimize the wavenumber spectrum distribution. With the proposed method, high-quality forward-looking imagery can be obtained with a short observation time. Numerical simulations are carried out to verify the effectiveness of the proposed method.

A multistatic unmanned aerial vehicle-borne synthetic aperture radar (MuUAV-SAR) plays an important role in the applications of environmental monitoring and disaster warning because its distributed platforms can provide high-resolution imagery by fusing the multiple measurements. However, the flight paths of the multiple platforms are limited for such an unmanned system since the flight safety and the path length are basic conditions for guaranteeing the effective observation. This article first studies the observation signal model of the MuUAV-SAR imaging system and then analyzes the factors that determine the imaging resolution, while these factors are all determined by the flight path of unmanned aerial vehicles (UAVs). Second, an MuUAV-SAR imaging path planning problem is established as a constrained multiobjective optimization problem (CMOP), which considers the navigation and imaging performance of the UAV in the process of completing the path planning task in detail. For this CMOP, a heuristic search method is proposed to solve it, which can ensure that each step achieves local optimum, and it can also list all feasible solutions to meet the application requirements for selection. Finally, experimental results verify the effectiveness and practicability of the proposed heuristic path planning method.

Background In patients with stage 0–A (as per Milan criteria) hepatocellular carcinoma (HCC) image-guided ablation is less invasive and requires shorter hospitalization than resection, but long-term prognosis is poorer. This meta-analysis was conducted to investigate whether liver stiffness measurement (LSM) could be used to predict prognosis in HCC patients after tumor ablation. Methods A literature search was conducted for all studies published till July 2020 in PubMed, Web of Science, Cochrane Library and EMBASE. Studies were included if they investigated the association between pretreatment LSM and prognosis in HCC patients treated with ablation. Subgroup analysis, meta-regression, publication bias assessment and sensitivity were conducted. Results Eight studies (with a total of 1276 HCC patients) were included in this meta-analysis. All patients were treated with radiofrequency ablation. Pooled results showed that high pretreatment LSM were associated with poor overall survival (OS) (hazard ratio [HR] = 4.31, 95% confidence interval [CI]: 2.27–8.20, p

Super-resolution methods for real beam mapping (RBM) imagery play a significant role in many microwave remote sensing applications. However, the existing super-resolution methods require high-dimensional matrix operations in the case of wide-field imaging, which makes it difficult to satisfy the requirements of real-time signal processing. To solve this problem, this paper introduces an improved Poisson distribution-based maximum likelihood (IPML) method by adding an adaptive iterative acceleration factor to effectively improve the algorithm convergence speed without introducing high-dimensional matrix operations. Furthermore, a GPU-based parallel processing architecture is proposed through the multithreading characteristics of the computing platform, and a cooperative CPU–GPU working model is constructed. This can realize the parallel optimization of the echo reception, preprocessing, and super-resolution processing. We verify that the proposed parallel super-resolution method can significantly improve the computational efficiency without sacrificing performance, using a real dataset.

In recent years, sparse direction-of-arrival (DOA) estimation for multiple-input multiple-output (MIMO) radar has attracted extensive attention and been extensively studied, especially the method based on the classic least absolute shrinkage and selection operator (LASSO) estimator. The alternating-direction method of multipliers (ADMM) is an effective method for solving this problem at the cost of introducing an additional user parameter. To avoid introducing an additional user parameter, this paper adopts an equivalent transformation in the form of the generalized SParse Iterative Covariance-based Estimation (qSPICE) cost function to obtain a mean squared minimized form of the cost function. Then, the problem is transformed into a sparse optimization problem in the form of a weighted LASSO. Next, this unconstrained optimization problem is decomposed into three subproblems, which are solved separately to reduce the dimension of each problem and thus reduce the overall computational complexity based on ADMM. Simulation results and measured data indicate that the proposed method significantly outperforms the traditional super-resolution DOA estimation method and ADMM-LASSO method and slightly outperforms qSPICE in terms of resolution and sidelobe suppression capability. In addition, the proposed method has a much lower computational complexity and substantially fewer iterations than qSPICE.

Background: Hepatocellular carcinoma (HCC) accounts for the majority of liver cancer, with the incidence and mortality rates increasing every year. Despite the improvement of clinical management, substantial challenges remain due to its high recurrence rates and short survival period. This study aimed to identify potential diagnostic and prognostic biomarkers in HCC through bioinformatic analysis.Methods: Datasets from GEO and TCGA databases were used for the bioinformatic analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were carried out by WebGestalt website and clusterProfiler package of R. The STRING database and Cytoscape software were used to establish the protein-protein interaction (PPI) network. The GEPIA website was used to perform expression analyses of the genes. The miRDB, miRWalk, and TargetScan were employed to predict miRNAs and the expression levels of the predicted miRNAs were explored via OncomiR database. LncRNAs were predicted in the StarBase and LncBase while circRNA prediction was performed by the circBank. ROC curve analysis and Kaplan-Meier (KM) survival analysis were performed to evaluate the diagnostic and prognostic value of the gene expression, respectively.Results: A total of 327 upregulated and 422 downregulated overlapping DEGs were identified between HCC tissues and noncancerous liver tissues. The PPI network was constructed with 89 nodes and 178 edges and eight hub genes were selected to predict upstream miRNAs and ceRNAs. A lncRNA/circRNA-miRNA-mRNA network was successfully constructed based on the ceRNA hypothesis, including five lncRNAs (DLGAP1-AS1, GAS5, LINC00665, TYMSOS, and ZFAS1), six circRNAs (hsa_circ_0003209, hsa_circ_0008128, hsa_circ_0020396, hsa_circ_0030051, hsa_circ_0034049, and hsa_circ_0082333), eight miRNAs (hsa-miR-150-5p, hsa-miR-19b-3p, hsa-miR-23b-3p, hsa-miR-26a-5p, hsa-miR-651-5p, hsa-miR-10a-5p, hsa-miR-214-5p and hsa-miR-486-5p), and five mRNAs (CDC6, GINS1, MCM4, MCM6, and MCM7). The ceRNA network can promote HCC progression via cell cycle, DNA replication, and other pathways. Clinical diagnostic and survival analyses demonstrated that the ZFAS1/hsa-miR-150-5p/GINS1 ceRNA regulatory axis had a high diagnostic and prognostic value.Conclusion: These results revealed that cell cycle and DNA replication pathway could be potential pathways to participate in HCC development. The ceRNA network is expected to provide potential biomarkers and therapeutic targets for HCC management, especially the ZFAS1/hsa-miR-150-5p/GINS1 regulatory axis.

BackgroundCellular immunotherapy has become a new and promising treatment for patients with liver tumor. However, as most immune cells are delivered by intravenous injection, the effect is limited and is likely to produce systemic toxicity. Here, the objective was to investigate the efficacy and safety of cellular immunotherapy by local infusion, which seems to be a promising approach and has not been well-studied.MethodsThe PubMed, Web of Science, Embase, and Cochrane Library databases were searched to obtain literature. The overall response rate (ORR), overall survival (OS) rates, and adverse events were investigated to evaluate the effectiveness and safety of locoregional therapy. The methodological quality of the articles was assessed using the methodological index for non-randomized studies (MINORS) score. The meta-analysis was performed using Stata 15.0.ResultsThe eligible 17 studies involved a total of 318 patients. The random-effects model demonstrated that the ORR of local cell infusion therapy was 48% (95% confidence interval [CI]: 26%–70%). The pooled OS rate was 94% (95% CI: 83%–100%) at 6 months, 87% (95% CI: 74%–96%) at 12 months, and 42% (95% CI: 16%–70%) at 24 months. Subgroup analyses suggested that minimally invasive treatment and absence of metastasis were significantly associated with better ORR. Fourteen studies reported a variety of adverse events related to cell therapy by local perfusion. The most common complications after regional infusion of immune cells were myelosuppression (66%), fever (50%), gastrointestinal toxicity (22%), hepatic dysfunction (15%), and pleural effusion and/or ascites (14%).ConclusionsImmune cell therapy through local perfusion is effective for patients with liver cancer, with manageable toxicity. It demonstrates better prognosis when combined with minimally invasive therapy. Considering the potential limitations, more randomized controlled trials are needed to provide solid evidence for our findings.

Background: Immunotherapy has shown promising therapeutic efficacy in various cancers but not gliomas. Circulating lymphocytes play critical roles in cancer control and responses to immune checkpoint inhibitors. Treatment-related lymphopenia has been associated with poor survival in patients with various tumors. This meta-analysis evaluated the risk and impact of lymphopenia in patients with glioma.Methods: The PubMed, Embase, Web of Science, and Cochrane Library databases were comprehensively searched. Eligible studies were included if they reported the incidence and risk factors of lymphopenia and the impact of lymphopenia on survival. Stata 16.0 was used for this meta-analysis.Results: A total of 21 studies were included in the final systematic review and 20 were included in the quantitative analysis. The overall incidence of grade III/IV lymphopenia was 31.6% [95% confidence interval (CI), 22.3–40.8%]. Pooled results based on pathology of glioma revealed that the incidence in astrocytoma and astrocytoma oligodendroglioma patients was 20.2% (95% CI:5.9–34.4%), and the incidence in glioblastoma patients was 27.6% (95% CI:16.2–38.9%). Lymphopenia was associated with poor overall survival (hazard ratio, 1.99; 95% CI, 1.74–2.27; P< 0.001) compared to no lymphopenia. Brain receiving radiation dose of 20 or 25 Gy, female sex, older age, lower baseline lymphocyte count, and dexamethasone dose > 2 mg instead of baseline use were risk factors for lymphopenia.Conclusions: Treatment-related lymphopenia was associated with decreased survival in patients with glioma. Optimization of chemoradiation regimens, particularly in patients with concurrent risk factors, can reduce lymphopenia and potentially improve survival in the era of immunotherapy.

SQUAMOSA Promoter-binding protein-Like (SPL) genes affect a broad range of plant biological processes and show potential application in crop improvement by genetic modification. As the most widely planted forage crop in the world, biomass and abiotic stresses tolerance are important breeding targets for alfalfa (Medicago sativa L.). Nevertheless, the systematic analysis of SPL genes in alfalfa genome remains lacking. In the present study, we characterized 22 putative non-redundant SPL genes in alfalfa genome and uncovered the abundant structural variation among MsSPL genes. The phylogenetic analysis of plant SPL proteins separated them into 10 clades and clade J was an alfalfa-specific clade, suggesting SPL genes in alfalfa might have experienced gene duplication and functional differentiation within the genome. Meanwhile, 11 MsSPL genes with perfect matches to miRNA response elements (MREs) could be degraded by miR156, and the cleavage sites were gene specific. In addition, we investigated the temporal and spatial expression patterns of MsSPL genes and their expression patterns in response to multiple treatments, characterizing candidate SPL genes in alfalfa development and abiotic stress tolerant regulation. More importantly, overexpression of the alfalfa-specific SPL gene (MsSPL20) showed stable delayed flowering time, as well as increased biomass. Further studies indicated that MsSPL20 delayed flowering time by regulating the expression of genes involved in floret development, including HD3A, FTIP1, TEM1, and HST1. Together, our findings provide valuable information for future research and utilization of SPL genes in alfalfa and elucidate a possibly alfalfa-specific flowering time regulation, thereby supplying candidate genes for alfalfa molecular-assisted breeding.

Abstract The water cutting rate is recorded dynamically during the production process of a well. If the remaining oil saturation of the reservoir can be deduced based on the water cutting rate, it will give guidance to improve the reservoir recovery and can save expensive drilling costs. In the oil–water two-phase seepage experiment on core samples, the oil and water relative permeability reflects the relationship between the water cutting rate and water saturation, that is, percolating saturation formula. The relative permeability test data of 17 rock samples from six seal coring wells in Daqing Changyuan were used to optimize and construct the coefficients of the index percolating saturation formula that vary with the pore structure parameters of reservoirs, to form an index percolating saturation formula with variable coefficients that is more consistent with the regional geological characteristics of the reservoir. Based on this, the formula of water saturation calculated by the water cutting rate is deduced. And the high-precision formula for calculating the irreducible water saturation and residual oil saturation by effective porosity, absolute permeability, and shale content is given. The derivative formula of water saturation on the water cutting rate was established, and the parameters of 17 rock samples were calculated. It was found that the variation velocity of water saturation of each sample with the water cutting rate presented a “U” shape, which was consistent with the actual characteristics that the variation velocity of the water saturation in the early, middle, and late stages of oilfield development first decreased, then stabilized, and finally increased rapidly. The research results were applied to the prediction of remaining oil saturation in the research area, and the water saturation about six producing wells was calculated by using their present water cutting rates, and the remaining oil distribution profile was predicted effectively. The analysis of four layers of two newly drilled infill wells and reasonable oil recovery suggestions were given to achieve good results.

Abstract We explore the collider prospects of neutrino non-standard interaction with a Standard Model (SM) gauge-singlet leptonic scalar ϕ carrying two units of lepton-number-charge. These leptonic scalars are forbidden from interacting with the SM fermions at the renormalizable level and, if one allows for higher-dimensional operators, couple predominantly to SM neutrinos. For masses at or below the electroweak scale, ϕ decays exclusively into neutrinos. Its characteristic production signature at hadron collider experiments like the LHC would be via the vector boson fusion process and leads to same-sign dileptons, two forward jets in opposite hemispheres, and missing transverse energy, i.e., pp → ℓ α ± ℓ β ± jj + E T miss α β = e μ τ $$ pp\to {\mathrm{\ell}}_{\alpha}^{\pm }{\mathrm{\ell}}_{\beta}^{\pm } jj+{E}_T^{\mathrm{miss}}\left(\alpha, \beta =e,\mu, \tau \right) $$ . Exploiting the final states of electrons and muons, we estimate, for the first time, the sensitivity of the LHC to these lepton-number-charged scalars. We show that the LHC sensitivity is largely complementary to that of low-energy precision measurements of the decays of charged leptons, charged mesons, W, Z and the SM Higgs boson, as well as the neutrino beam experiments like MINOS, and searches for neutrino self-interactions at IceCube and in cosmological observations. For ϕ mass larger than roughly 10 GeV, our projected LHC sensitivity would surpass all existing bounds.