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With advancements in science and technology, collaborative and industrial robotic arms are increasingly gaining popularity. Enhancing the intelligence and autonomy of robot arms, particularly in autonomous grasping, has become one of the research hotspots in robotics research. To improve the efficiency and success rate of industrial robot arms in grasping target objects and avoiding obstacles, a three-finger pneumatic flexible clamp was selected, and a flexible grasping module was designed. Communication between the upper computer and the single-chip computer via a serial port enables clamping and loosening actions, constructing an autonomous grasping system based on the traditional Informed -RRT* algorithm. An improved info-RRT * algorithm (Grasping informed-RRT *, GI-RRT*) for the GR-ConvNet model is proposed. First, the maximum number of iterations and the adaptive function are pre-set to shorten the generation time of the manipulator’s motion trajectory and enhance sampling guidance and quality. Second, direct sampling of elliptical subsets constrains the position of sampling points, improving sampling efficiency. Finally, a greedy algorithm deletes redundant path points, and a cubic B-spline curve smoothly constrains the trajectory of the robot arm, shortening its length and improving flexibility. The generated residual convolutional neural network (GR-ConvNet) model predicts inputs from color and depth images captured by a depth camera, outputting the appropriate mapping grab pose of the object in the field of view. To verify the grasping effect of the robot arm, simulation and grasping experiments were conducted on the cooperative robot arm FR3. Simulation results show that, compared with the traditional Informed-RRT* algorithm, the improved algorithm shortens trajectory length by 10.11% and reduces trajectory generation time by 62.68%. The robot arm independently avoids obstacles and grasps target objects, meeting the requirements for autonomous grasping. Experiments with the cooperative robot arm demonstrate its ability to independently grasp objects independently and successfully avoid obstacles. This further validates the algorithm’s effectiveness on a real robot arm, bringing hope for its further development and use. It reduces the difficulty for operators to use the robot arm and accelerates the wide application of domestic robot arms in factories. This paper aims to promote the practical application of robot arms.

Abstract Advanced pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis. Immunotherapy alone offers limited efficacy, but it is still unknown whether its combination with chemotherapy could offer synergistic anti-tumor effects. This phase Ib/II study evaluated the safety and efficacy of combining toripalimab with the gemcitabine plus nab-paclitaxel (GnP) regimen as first-line treatment for locally advanced or metastatic PDAC and explored predictive biomarkers (ChiCTR2000032293). The primary endpoints were safety and overall survival (OS). The secondary outcomes were objective response rate (ORR), disease control rate (DCR), and progression-free survival (PFS). Immune-related biomarkers including programmed death-ligand 1 (PD-L1) expression, genetic status, cytokine levels, and spatial features of the tumor immune microenviroment (TIME) were investigated. Neither serious treatment-related adverse events nor grade 4 immune-related adverse events were reported. Among the 72 patients, the median OS was 8.9 months, 12-month OS rate was 31.9%, with median PFS of 5.6 months, ORR of 33.3%, and DCR of 90.3%. Higher PD-L1 expression, without liver metastases were associated with higher ORR, however these factors could not effectively distinguish responders and non-responders. Importantly, dendritic cells - T helper cells - cytotoxic T lymphocytes (DC-Th-CTL) enriched immune niche and their spatial interactions were dominant predictors of response based on TIME analysis using a cyclic multiplex tissue staining assay, with an area under the curve value of 0.8. Overall, GnP plus toripalimab exhibited good safety and differentiated efficacy in selected population, and the spatial interactions of DC-Th-CTL represent promising predictors to efficacy of immunochemotherapy in locally advanced or metastatic PDAC.

Abstract With the increase of mining scope, rockburst occurs frequently, but its generation mechanism has not been understood comprehensively. Based on a rockburst in the coal pillar area of high tectonic stress zones (HTSZs), this study analyzed the distribution characteristics of large-energy microseismic (MS) events by using data statistics. The mechanical cause of the MS event that induced the rockburst was revealed by means of seismic moment tensor inversion. On this basis, by using numerical simulation, this study explored the distribution characteristics of static load in rockburst area and the effect of dynamic load in the floor, and then proposed the rockburst mechanism. The results show that under the squeezing action, the floor strata in HTSZs implode and transmit energy outward in the form of stress waves. This causes the cumulative damage and stress of the coal body in the fast track of coal pillar area increase in a short time. Since the coal in this area has already been in the critical stress state, small stress changes may lead to coal failure and rockburst. In this case of rockburst, the high static load of coal is the main force source, and the dynamic load plays a role in increasing coal body damage and inducing rockburst. Combined with seismic moment tensor inversion and numerical simulation, this paper proposes a rockburst research scheme, which makes the simulation of dynamic load more reasonable. The results provide the theoretical basis for rockburst control under similar conditions.

Prednisone, a synthetic glucocorticoid, possesses a moderate duration of action in the human body. To investigate the effect of prednisone on osteosarcoma cells in vitro, CCK8, wound healing, Transwell assays, flow-cytometry, western blot, and ELISA were used to measure cell proliferation, cell migration, cell invasion, cell cycle, cell apoptosis, and the key proteins in Wnt/β-catenin pathway. The results showed prednisone could inhibit the proliferation in osteosarcoma cells and exhibit lower proliferation toxicity towards normal bone cells compared to cisplatin by 17.5% (p

Abstract Background Bronchopulmonary dysplasia-associated pulmonary hypertension (BPD-PH) remains a devastating clinical complication seriously affecting the therapeutic outcome of preterm infants. Hence, early prevention and timely diagnosis prior to pathological change is the key to reducing morbidity and improving prognosis. Our primary objective is to utilize machine learning techniques to build predictive models that could accurately identify BPD infants at risk of developing PH. Methods The data utilized in this study were collected from neonatology departments of four tertiary-level hospitals in China. To address the issue of imbalanced data, oversampling algorithms synthetic minority over-sampling technique (SMOTE) was applied to improve the model. Results Seven hundred sixty one clinical records were collected in our study. Following data pre-processing and feature selection, 5 of the 46 features were used to build models, including duration of invasive respiratory support (day), the severity of BPD, ventilator-associated pneumonia, pulmonary hemorrhage, and early-onset PH. Four machine learning models were applied to predictive learning, and after comprehensive selection a model was ultimately selected. The model achieved 93.8% sensitivity, 85.0% accuracy, and 0.933 AUC. A score of the logistic regression formula greater than 0 was identified as a warning sign of BPD-PH. Conclusions We comprehensively compared different machine learning models and ultimately obtained a good prognosis model which was sufficient to support pediatric clinicians to make early diagnosis and formulate a better treatment plan for pediatric patients with BPD-PH.

Abstract In response to the suboptimal efficiency observed in the network configuration and administration of 5G photovoltaic base stations (PVBSs), as well as the inherent limitations in accurately forecasting photovoltaic power during inclement weather conditions, this research article introduces a concise and effective method for short‐term power prediction of PVBSs when subjected to non‐sunny weather conditions, leveraging the paradigm of software defined networking. This method ingeniously amalgamates the improved Northern Goshawk optimized back propagation neural network (INGO‐BP) and recurrent generative adversarial networks (RGAN). The investigation commences by delineating a comprehensive PVBS system framework underpinned by SDN principles. Subsequently, it employs the Pearson correlation coefficient technique and principal component analysis for the judicious selection of pertinent features from the PVBS photovoltaic dataset, thereby ameliorating the issue of multicollinearity within the predictive model. To culminate the research endeavour, the INGO algorithm is enlisted to optimize the weightings and bias parameters of the BP neural network, while RGAN is harnessed for the acquisition of distinctive distribution patterns in photovoltaic data across diverse meteorological conditions. This augmentation enhances the model's capacity to discern the intricate long‐term mappings between photovoltaic power and meteorological data. The empirical findings substantiate the elevated accuracy of the INGO‐BP prediction model across sunny, cloudy, and rainy weather conditions, with a discernible enhancement in predictive accuracy for PVBS performance under non‐sunny weather conditions facilitated by data augmentation via RGAN.

The rock burst frequently occurs in the roadways with top coal, and the roof disasters are particularly severe under dynamic stress in China. In order to explore the classification and instability mechanisms of anchoring structures in the roadways with top-coal, analog simulation experiments, theoretical analysis, and data statistics were used under the engineering background of the large-area rock burst roof failure in the Working Face 301 of a mine in Shaanxi Province, China. The dynamic load response characteristics of the stress, displacement, and surface acceleration of the surrounding rock in the roadways with top coal were analyzed. The classification characteristics of the roof anchoring structure under the influence of top coal thickness and cables were studied. The stress response mechanism of the roadways with top coal under elastic waves was explored, and the instability mechanism of the anchoring “beam arch” structure was proposed. The rock burst resistance of the air-return roadway in the Working Face 301 was evaluated, and the corresponding optimization schemes for the “beam-arch” composite structure were proposed. The results show that ① the monitoring data of stress and displacement of the surrounding rock in the roadways with top coal under dynamic stress verify the existence of internal and external beam or arch anchoring structures in the roof. Due to the increase in the thickness of top coal, there is a transition from “beam” to “arch” in the anchoring structure of the inner layer of the roof; ② based on the relative relationship between the thickness of the top coal and the cables, the roof anchoring structure is divided into “superimposed-beam and arch” for thin top coal, “composite-beam and arch” for thick top coal, and “combined arch” for extra thick top coal. A critical thickness index for the transformation of thick coal beams from “beam” to “arch” is established; ③ the instability mechanism of the beam structure and the arch structure is that they fail after reaching their tensile and shear strength limits under dynamic and static stress, respectively. The amplification effect of the “beam-arch” composite structure on the load stress is significantly affected by its size; ④ the bearing strength of the inner arch in the "combined arch" structure is relatively low. Increasing the length of cables can increase the thickness of the inner arch, and the corresponding “combined arch” structure’s bearing strength increases significantly, which is consistent with the evaluation results of the rock burst resistance.

Abstract With more and more interconnected smart devices (ISDs) accessing the Internet of Things (IoT), massive and diverse tasks need to be transformed and computed. Mobile edge computing enables the offloading of tasks to nearby servers to enhance processing efficiency, which makes ISDs idle, causing resource waste and failing to satisfy the high real‐time requirements of tasks. Besides, when tasks with different priorities are processed in the order they are generated, it will be difficult for IoT to guarantee a timely response to high‐priority tasks. To address the aforementioned issues, we establish an edge‐terminal‐local architecture by software‐defined networking to centrally manage idle ISD resource (2ISDR). Then the proposed two‐step scheduling mechanism with preemptive priority queue ensures the real‐time responses to high‐priority tasks, and the minimum resource allocation coefficients make offloading effective. Finally, we also propose a modified NSGA‐III algorithm named MNSGA‐III, which is designed to make decisions about offloading and solve resource allocation for tasks, and we correct infeasible solutions by a two‐step correction function to ensure the feasibility of MNSGA‐III. Experimental results show that the method can ensure a timely response to high‐priority tasks and optimize processing time, energy consumption, and economic cost through the utilization of 2ISDR.

The differential distribution of original rock stress and stress concentration caused by the variation in coal seam depth in karst topography are critical factors influencing the selection of roof-cutting parameters. Based on this, this study explores a method to determine reasonable roof-cutting parameters by incorporating the characteristics of coal seam depth variation in karst mountainous areas. A mechanical model of the cantilever beam structure for roof cutting in gob-side entry retention (GSER) is constructed, and the critical values and reasonable ranges of roof-cutting height and angle under different burial depths are derived. Furthermore, the displacement and stress evolution characteristics of surrounding rocks in gob-side entry retention under different coal seam burial depths, roof-cutting heights, and roof-cutting angles within the reasonable range of roof-cutting parameters are analyzed. The results show that there is a positive correlation between roof-cutting height and tensile stress in the uncut portion of the main roof, while roof-cutting angle and coal seam depth are negatively correlated with tensile stress. From the perspective of impact, roof-cutting height has a greater impact than roof-cutting angle, followed by coal seam depth. As for the distribution characteristics of the reasonable roof-cutting parameter range, the fan-shaped area of reasonable roof-cutting parameters gradually decreases with increasing coal seam depth. Taking the geological conditions of Anshun Coal Mine as an example, when the burial depth increases from 350 m to 550 m, adjusting the roof-cutting height to 6 m, 7 m, and 8 m, respectively, and setting the roof-cutting angle at 10° can effectively achieve the stability of the surrounding rock in the GSER. The research findings can provide a scientific basis and engineering references for selecting roof-cutting parameters in mines with similar geological conditions.

The occurrence of rock bursts due to penetrating faults are frequent in China, thereby limiting the safe production of coal mines. Based on the engineering background of a 501 working face in a TB coal mine, this paper investigates stress and energy evolution during the excavation of this working face due to multiple penetrating faults. Utilizing both theoretical analysis and numerical simulations, this study reveals the rock burst mechanism within the triangular coal pillar influenced by the penetrating faults. Based on the evolution of stress within the triangular coal pillar, a stress index has been devised to categorize both the rock burst danger regions and the levels of rock burst risks associated with the triangular coal pillar. Furthermore, targeted stress relief measures are proposed for various energy accumulation areas within the triangular coal pillar. The results demonstrate that: (1) the superimposed tectonic stress resulting from the T6 and T5 penetrating faults exhibits asymmetric distribution and has an influence range of about 90 m in the triangular coal pillar, reaching a peak value of 11.21 MPa at a distance of 13 m from the fault plane; (2) affected by the barrier effect of penetrating faults, the abutment stress of the working face is concentrated in the triangular coal pillar, and the magnitude of the abutment stress is positively and negatively correlated with the fault plane barrier effect and the width of the triangular coal pillar, respectively; (3) the exponential increase in abutment stress and tectonic stress as the width of the triangular coal pillar decreases leads to a high concentration of static stress, which induces pillar burst under the disturbance of dynamic stress from fault activation; (4) the numerical simulation shows that when the working face is 150 m away from the fault, the static stress and accumulated energy in the triangle coal pillar begins to rise, reaching the peak at 50 m away from the fault, which is consistent with the theoretical analysis; (5) the constructed stress index indicates that the triangular coal pillar exhibits moderate rock burst risks when its width is between 73 to 200 m, and exhibits high rock burst risks when the width is within 0 to 73 m. The energy accumulation pattern of the triangular coal pillar reveals that separate stress relief measures should be implemented within the ranges of 50 to 150 m and 0 to 50 m, respectively, in order to enhance the effectiveness of stress relief. Blasting stress relief measures for the roof and coal are proposed, and the effectiveness of these measures is subsequently verified.

Pavement cracks are crucial indicators for assessing the structural health of asphalt roads. Existing automated crack detection models depend on large quantities of precisely annotated crack sample data. The irregular morphology of cracks makes manual annotation time-consuming and costly, thereby posing challenges to the practical application of these models. This study proposes a pavement crack image detection method integrating fractal dimension analysis and semi-supervised learning. It identifies the self-similarity characteristics within the crack regions by analyzing pavement crack images and using fractal dimensions to preliminarily determine the candidate crack regions. The Crack Similarity Learning Network (CrackSL-Net) is then employed to learn the semantic similarity of crack image regions. Semi-supervised learning facilitates automatic crack detection by combining a small amount of labeled data with a large volume of unlabeled image data. Comparative experiments are conducted on two public pavement crack datasets against the HED, U-Net, and RCF models to comprehensively evaluate the performance of the proposed method. The results indicate that, with a 50% annotation ratio, the proposed method achieves high-precision crack detection, with an intersection over union (IoU) exceeding 0.84, which is close to that of U-Net. Visual analysis of the detection results confirms the method’s effectiveness in identifying cracks in complex environments.

With its technical advantages of high speed, low latency, and broad connectivity, fifth-generation mobile communication technology has brought about unprecedented development in numerous vertical application scenarios. However, the high energy consumption and expansion difficulties of 5G infrastructure have become the main obstacles restricting its widespread application. Therefore, aiming to optimize the energy utilization efficiency of 5G base stations, a novel distributed photovoltaic 5G base station DC microgrid structure and an energy management strategy based on the Curve Fitting–Perturb and Observe–Incremental Conductance (CF-P&O-INC) Maximum Power Point Tracking (MPPT) algorithm from the perspectives of energy and information flows are proposed. Simulation results show that the proposed MPPT algorithm can increase the efficiency to 99.95% and 99.82% under uniform irradiation and partial shading, respectively. Under the proposed strategy, when the base station load changes drastically, the voltage fluctuation of the DC bus is less than 1.875%, and returns to a steady state within 0.07s, alleviating the high energy consumption of 5G base stations effectively and achieving coordinated optimization management of various types of energy in multi-source power supply systems.

AbstractWith the increase of mining depth and mining intensity of the large inclined extra-thick coal seam (LIETCS), the number of rock bursts increases significantly. In this paper, based on a rock burst during upper roadway driving of the LIETCS, the distribution characteristics and fracture mechanism of microseismic (MS) events are analyzed using data statistics and seismic moment tensor inversion. By means of mechanical analysis and numerical simulation, this paper studies the static load distribution characteristics and dynamic load action effect of the LIETCS under upper slice mining condition. Based on the theory of dynamic and static combined load, the mechanism of rock bursts is proposed. The results show that the coal and rock mass of the LIETCS are mainly destroyed by shearing. The “shear-clamping” stress produced by the joint action of the roof and floor is the static load source. In upper slice mining, the shear stress and energy of the coal pillar behind the slice and the coal body below the coal pillar always remain high. Under the superposition of floor dynamic load, the regional stress environment changes, which induces rock bursts. This study provides a theoretical basis for rock burst prevention under similar conditions.

Abstract Background The anti-osteosarcoma effects of hydrocortisone and thiram, an inhibitor of type 2 11ß-hydroxysteroid dehydrogenase (11HSD2), have not been reported. The purpose of this study was to investigate the effects of hydrocortisone alone or the combination of hydrocortisone with thiram on osteosarcoma and the molecular mechanism, and determine whether they can be as new therapeutic agents for osteosarcoma. Methods Normal bone cells and osteosarcoma cells were treated with hydrocortisone or thiram alone or in combination. The cell proliferation, migration, cell cycle and apoptosis were detected by using CCK8 assay, wound healing assay, and flow cytometry, respectively. An osteosarcoma mouse model was established. The effect of drugs on osteosarcoma in vivo was assessed by measuring tumor volume. Transcriptome sequencing, bioinformatics analysis, RT–qPCR, Western blotting (WB), enzymelinked immunosorbent assay (ELISA) and siRNA transfection were performed to determine the molecular mechanisms. Results Hydrocortisone inhibited the proliferation and migration, and induced apoptosis and cell cycle arrest of osteosarcoma cells in vitro. Hydrocortisone also reduced the volume of osteosarcoma in mice in vivo. Mechanistically, hydrocortisone decreased the levels of Wnt/β-catenin pathway-associated proteins, and induced the expression of glucocorticoid receptor α (GCR), CCAAT enhancer-binding protein β (C/EBP-beta) and 11HSD2, resulting in a hydrocortisone resistance loop. Thiram inhibited the activity of the 11HSD2 enzyme, the combination of thiram and hydrocortisone further enhanced the inhibition of osteosarcoma through Wnt/β-catenin pathway. Conclusions Hydrocortisone inhibits osteosarcoma through the Wnt/β-catenin pathway. Thiram inhibits 11HSD2 enzyme activity, reducing hydrocortisone inactivation and promoting the effect of hydrocortisone through the same pathway.

Abstract Given the advancements in solar power generation and fifth‐generation (5G) technologies, it is crucial to reduce energy consumption based on accurate predictions of the photovoltaic power requirements of 5G base stations (BSs) connected to renewable energy sources. To ensure sufficient prediction performance even under complex weather conditions and promote two‐way flow of energy and information in the power supply system of the 5G BS, this work first proposes a reference scenario for a 5G BS with an energy router. Then, the comprehensive grey relational analysis is used to determine the optimal photovoltaic input variables. Finally, the improved logistic distribution, Laplacian distribution with inverse incomplete gamma‐function weight factor, and nonlinear mutation perturbation strategy are introduced to improve the ability of the sparrow search algorithm to avoid locally optimal solutions for an extreme learning machine of the short‐term photovoltaic power prediction model. The proposed model is applied to actual measured data for validation, and the results show that this model has the lowest mean percentage error as well as highest prediction accuracy under different weather conditions. The coefficient of determination for the proposed prediction model is greater than 99%; therefore, it is expected to improve the photovoltaic prediction performances of 5G energy‐routing BSs as well as promote sustainable development and sharing of energy and information.

Dynamic disasters such as rockbursts have different characteristics with different geological structures. The rockburst mechanism and the influencing factors of a typical composite fault-fold structure were explored by theoretical analysis and numerical simulation. The results showed that: (1) the influence of the composite fault-fold structure on the roadway group rockburst was mainly caused by tectonic stress disturbance; (2) the stress peak value and the influence range of the hanging wall of the fault were larger than those in the footwall, and the stress of the syncline axis was larger than that of the anticline axis; (3) the tectonic stress of the composite fault-fold structure was the highest, the stress value reached to the peak when the fault dip angle was 65°, and the tectonic stress was directly proportional to the elastic modulus of coal and first increased and then decreased with the increase in coal seam thickness; and (4) before rockburst, seismic activities concentrated within 200 m from the footwall and 0–250 m in the hanging wall of the fault, mainly concentrated in 0–20 and 0–40 m, respectively. The spatial distribution coincided with the high static stress area. HighlightsThe asymmetry of stress and microseismic events of composite fault-fold structure reveals the asymmetry of rockburst potential. The rockburst potential of the hanging wall of the fault is greater than that of the footwall, and the rockburst potential of the syncline is greater than that of the anticlineBased on the analysis of stress characteristics and fault activation, it is revealed that the rockburst of roadway group is mainly affected by the static tectonic stress of composite fault-fold structure.Four influencing factors: structure type, fault dip angle, coal seam thickness, and coal elastic modulus are analysed, and the causes of stress concentration of composite fault-fold structure are revealed.

# Background A large number of patient reported outcome measures (PROMs) have been developed for specific lower extremity orthopaedic pathologies. However, a consensus as to which PROMs are recommended for use in evaluating treatment outcomes for patients with hip, knee, ankle and/or foot pathology based on the strength of their psychometric properties is lacking. # Objective To identify PROMs that are recommended in systematic reviews (SRs) for those with orthopaedic hip, knee, foot, and ankle pathologies or surgeries and identify if these PROMs are used in the literature. # Study design Umbrella Review # Methods PubMed, Embase, Medline, Cochrane, CINAHL, SPORTDisucs and Scopus were searched for SRs through May 2022. A second search was done to count the use of PROMs in seven representative journals from January 2011 through May 2022. SRs that recommended the use of PROMs based on their psychometric properties were included in the first search. SRs or PROMs not available in the English were excluded. The second search included clinical research articles that utilized a PROM. Case reports, reviews, and basic science articles were excluded. # Results Nineteen SRs recommended 20 PROMs for 15 lower extremity orthopaedic pathologies or surgeries. These results identified consistency between recommended PROMs and utilization in clinical research for only two of the 15 lower extremity pathologies or surgeries. This included the use of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and the Copenhagen Hip and Groin Outcome Score to assess outcomes (HAGOS) for those with knee osteoarthritis and groin pain, respectively. # Conclusion A discrepancy was found between the PROMs that were recommended by SRs and those used to assess clinical outcomes in published research. The results of this study will help to produce more uniformity with the use of PROMs that have the most appropriate psychometric properties when the reporting treatment outcomes for those with extremity pathologies. # Level of evidence 3a

# Background A large number of patient reported outcome measures (PROMs) have been developed in the English language for various lower extremity orthopaedic pathologies. Twenty different PROMs were recommended for 15 specific musculoskeletal lower extremity pathologies or surgeries. However, the availability of cross-culturally adapted versions of these recommended PROMs is unknown. # Purpose The purpose of this study was to identify the cross-culturally adapted versions of recommended PROMs for individuals experiencing orthopedic lower extremity pathologies or undergoing surgeries, and to identify the psychometric evidence that supports their utilization. # Study design Literature Review # Methods PubMed, Embase, Medline, Cochrane, CINAHL, SPORTDisucs and Scopus were searched for cross-culturally adapted translated studies through May 2022. The search strategy included the names of the 20 recommended PROMs from previous umbrella review along with the following terms: reliability, validity, responsiveness, psychometric properties and cross-cultural adaptation. Studies that presented a non-English language version of the PROM with evidence in at least one psychometric property to support its use were included. Two authors independently evaluated the studies for inclusion and independently extracted data. # Results Nineteen PROMS had cross-culturally adapted and translated language versions. The KOOS, WOMAC, ACL-RSL, FAAM, ATRS, HOOS, OHS, MOXFQ and OKS were available in over 10 different language versions. Turkish, Dutch, German, Chinese and French were the most common languages, with each language having more than 10 PROMs with psychometric properties supporting their use. The WOMAC and KOOS were both available in 10 languages and had all three psychometric properties of reliability, validity, and responsiveness supporting their use. # Conclusion Nineteen of the 20 recommended instruments were available in multiple languages. The PROM most frequently cross-culturally adapted and translated were the KOOS and WOMAC. PROMs were most frequently cross-culturally adapted and translated into Turkish. International researchers and clinicians may use this information to more consistently implement PROMs with the most appropriate psychometric evidence available to support their use. # Level of evidence 3a

Acute T-lymphoblastic leukemia (T-ALL) is a type of leukemia that can occur in both pediatric and adult populations. Compared to acute B-cell lymphoblastic leukemia (B-ALL), patients with T-cell T-ALL have a poorer therapeutic efficacy. In this study, a novel anti-CD7 antibody–drug conjugate (ADC, J87-Dxd) was successfully generated and used for T-ALL treatment. Firstly, to obtain anti-CD7 mAbs, we expressed and purified the CD7 protein extracellular domain. Utilizing hybridoma technology, we obtained three anti-CD7 mAbs (J87, G73 and A15) with a high affinity for CD7. Both the results of immunofluorescence and Biacore assay indicated that J87 (KD = 1.54 × 10−10 M) had the highest affinity among the three anti-CD7 mAbs. In addition, an internalization assay showed the internalization level of J87 to be higher than that of the other two mAbs. Next, we successfully generated the anti-CD7 ADC (J87-Dxd) by conjugating DXd to J87 via a cleavable maleimide-GGFG peptide linker. J87-Dxd also possessed the ability to recognize and bind CD7. Using J87-Dxd to treat T-ALL cells (Jurkat and CCRF-CEM), we observed that J87-Dxd bound to CD7 was internalized into T-ALL cells. Moreover, J87-Dxd treatment significantly induced the apoptosis of Jurkat and CCRF-CEM cells. The IC50 (half-maximal inhibitory concentration) value of J87-Dxd against CCRF-CEM obtained by CCK-8 assay was 6.3 nM. Finally, to assess the antitumor efficacy of a J87-Dxd in vivo, we established T-ALL mouse models and treated mice with J87-Dxd or J87. The results showed that on day 24 after tumor inoculation, all mice treated with J87 or PBS died, whereas the survival rate of mice treated with J87-Dxd was 80%. H&E staining showed no significant organic changes in the heart, liver, spleen, lungs and kidneys of all mice. In summary, we demonstrated that the novel anti-CD7 ADC (J87-Dxd) had a potent and selective effect against CD7-expressing T-All cells both in vitro and in vivo, and could thus be expected to be further developed as a new drug for the treatment of T-ALL or other CD7-expression tumors.

Seismic energy analysis is the basis of coal burst risk assessment. The prerequisite for utilizing seismic energy to quantify coal burst hazards is the accurate understanding of seismic energy attenuation. Thereby the characteristics of seismic energy attenuation were first systematically investigated in this paper. Based on the seismic data and 24 coal burst records during the period of sixteen months, a risk assessment method including three indexes (Static Intensity Index (SII), Dynamic Intensity Index (DII), and Risk Assessment Index (RAI)) was derived from seismic energy attenuation. In consideration of the static and dynamic response, the superposition effects of seismic energy were proposed to improve the performance of risk assessment. Results show that residual seismic energy (RSE) is relatively correlated with seismic energy, source radius, and energy attenuation coefficient; the higher seismic energy, source radius, and lower energy attenuation coefficient would result in higher coal burst risk. The case study demonstrated that SII could effectively predict the damaged area, but its prediction efficiency of high-magnitude events (HMEs) is relatively low; DII could predict damaged areas and HMEs, but may lead to risk overestimation; and RAI could efficiently predict the damaged area and HMEs. The sensitivity of the monitoring system and seismicity activeness could be the two main restrictions of the proposed method, leading to low efficiency or even false risk assessment. This paper sheds light on seismic energy utilization to risk prediction in underground coal mines. HighlightsThe attenuation response characteristics of seismic energy to different factors including seismic energy, source radius, and attenuation coefficient were investigated.A new assessment method based on seismic energy attenuation calculation was proposed to assess coal burst risks. Three seismic-based indexes considering static and dynamic response and their superposition effects were proposed to assess coal burst risk.Sensitivity of monitoring system and seismicity activeness could be the two main restrictions leading to low accuracy or even false in risk assessing, which implies that the proposed method could also have false judgements in the place where rare seismicity is monitored.

Promoting the sustainable development of cities and unifying ecological, economic, and social benefits are of great significance to the long-term development of the country. Taking the macro level as the starting point, this paper constructs a hierarchical identification model of urban personality advantage characteristics from the perspective of sustainable development. To identify, classify and compare the sustainable urban development models, SPSS was used to analyze the weights of the dominant characteristics of various cities in China. First, according to the identification model, the individual advantages of each city are identified hierarchically; Secondly, all feature weights are clustered, and finally, the sustainable development patterns of different cities are discussed according to the clustering results, and relevant countermeasures are proposed. The comparison shows that each city has its advantages and disadvantages in sustainable development, and these cities have not been able to implement the concept and policies of sustainable development well. Given these problems, this paper recommends grasping the main force, gradually solving and improving the weaker links in sustainable development, and reducing the imbalance in development. In the context of sustainable development strategies, the development of Chinese cities in a virtuous circle is of great significance.

Due to cost-push inflation, the trade-off between safety costs and risk prevention (safety) has become difficult worldwide. Most companies experience the difficulty of safety cost overruns and allocate safety resource inefficiently. In this paper, a forward model maximizing safety input is formulated. Because there is a wide range of variation of safety resource cost coefficient parameters, it is hard to determine safety resource cost coefficients in the forward model, to make the decisions on which types of safety resources are allocated to which potentially risky locations with what prices, and to ensure total input is as close to the benchmark as possible. Taking allocation, themes, resources, and cost coefficient parameters as new decision variables, the inverse optimization model is formulated based on a bi-level model. With consideration of quaternion decision, bi-level programming, and NP-hard problem, based on the comparison of exact penalty algorithm and an improved PSO algorithm, in which the inertia weight is adaptively changing with the number of iterations, the PSO is suitable for solving the specific inverse model. Numerical experiments demonstrated the effectiveness of the PSO algorithm, proving that it can allocate the right amount and types of safety resources with the right prices at the right places.

AbstractWith the increase of mining depth, rock burst disasters frequently occur in steeply inclined coal seams. Firstly, this paper analyzes the rock burst of 5521-20 working face in Yaojie No. 3 coal mine and summarizes the characteristics of rock burst in horizontal section mining of steeply inclined extra-thick coal seam (SIETCS). Then, the static load distribution characteristics and the influence of dynamic load in the horizontal section mining of SIETCS are systematically studied by combining theoretical analysis with numerical simulation. On this basis, the mechanism of rock burst in horizontal section mining of SIETCS is put forward, verified by actual measurement. The results show that the SIETCS is “clamped” under the combined action of the same change trend of roof and floor. The maximum principal stress peak values on the roof and floor sides reach 22.0 MPa and 20.5 MPa. The maximum shear stress earned 8.7 MPa and 8.4 MPa, which makes the shear stress concentration in the coal body high and tends to “shear dislocation.” Under this “shear-clamping” action, an approximate “trapezoidal” plastic zone and a “rectangular” stress concentration zone are formed under the section. With the increase of mining depth, the “shear-clamping” action of SIETCS becomes more and more intense. When the roof cantilever reaches the ultimate span and breaks, the intense dynamic load increases the shear stress and failure of coal, which is easy to induce rock burst. The superimposed load greatly affects the area from the roof side to the middle of the working face, and the rock burst is intense. The rock burst is weak on the floor side due to the pressure relief of the surrounding plastic zone. The monitoring results show that the supports pressure and MS events activity on the roof side and near the middle part of the working face is considerable, while the floor side is opposite, which verifies the research results.

Solutions for the maintenance of safety in an isolated working face has not been well achieved; this is attributed to its unique overburden structure and the strong mining-induced stress during the advancement. This paper is devoted to filling this research gap and is based on the case study of LW 10304 in the Xinglongzhuang Coal Mine, in China. The overburden structure and stress distribution characteristics of this isolated working face were theoretically investigated, followed by the development of a comprehensive identification method. The research results showed the following: (1) The overburden strata of LW 10304 is in the form of a short “T” shape and the stress increment is featured with the overall “saddle” shape before the extraction of the isolated working face. During this period, the lower key strata and main key strata affect the stress level at the two ends and the central part of the working face, respectively; (2) Both the frequency and energy of micro-earthquakes in the working face account for more than 95%, which is positively correlated with roof damage and rib spalling, associated with some overlaps between the damaged zones; (3) The fracture movement of inferior key strata near the coal seam plays a dominant role in affecting microseism activity and mining-induced stress. The microseism energy attributed to roof breakage accounts for 43.34% of the overall energy; (4) A comprehensive indexing system, covering microseism frequency, microseism energy, and support resistance, was established to identify the mining-induced stress intensity of the isolated working face. The early warning efficiency of the “strong” degree of mining-induced stress is 0.94, which is believed to provide an option for other isolated working faces with similar geological and mining conditions.

Doublecortin-like kinase 1 (DCLK1) is upregulated in many tumors and is a marker for tumor stem cells. Accumulating evidence suggests DCLK1 constitutes a promising drug target for cancer therapy. However, the regulation of DCLK1 kinase activity is poorly understood, particularly the function of its autoinhibitory domain (AID), and, moreover, no physiological activators of DCLK1 have presently been reported. Here we determined the first DCLK1 kinase structure in the autoinhibited state and identified the neuronal calcium sensor HPCAL1 as an activator of DCLK1. The C-terminal AID functions to block the ATP-binding site and is competitive with ATP. HPCAL1 binds directly to the AID in a Ca2+-dependent manner, which releases the autoinhibition. We also analyzed cancer-associated mutations occurring in the AID and elucidate how these mutations disrupt DCLK1 autoinhibition to elicit kinase activity upregulation. Our results present a molecular mechanism for autoinhibition and activation of DCLK1 kinase activity and provide insights into DCLK1-associated tumorigenesis.

Coal burst is a severe and dynamic hazard, and understanding its mechanism is crucial in preventing such incidents. Strong tremors during the working face mining in the stress anomaly zone of the pinch-out coal seam are frequent. Theoretical analysis, numerical simulation, and field measurement methods are used to analyze the energy evolution law for mining at the working face and mechanism of coal burst. Mechanical models of the inclined and strike overhang structures are established, and the theoretical analysis of the strike and inclined energy distribution characteristics of the working face roof is carried out. The two key areas with a high overhang bending deformation energy accumulation are identified at the lower end and middle-upper part of the working face. The simulation results show that the energy accumulation area of the roof in the inclined coal seam has prominent asymmetric distribution characteristics. The roof energy accumulates in the lower end and middle-upper area of the working face. The floor energy accumulates in the lower end area of the working face, and the peak position of the overhead energy of the working face in the direction shifts toward the coal-wall side. Influenced by the local absence of the No. 8 coal seam, the vertical stress of the surrounding rock at the working face of the massive, inclined coal seam increased by 12.7%; the peak of roof energy at the working face inclination and strike increased by 46.2% and 32.2%; and the range of roof energy accumulation expanded. A deep directional hole blasting plan to prevent the phenomenon at the working face roof is developed, which effectively reduces the stress and energy level of the inclined hanging roof and avoids the occurrence of coal bursts in the abnormal stress area of the working face.

This study proposes a method for vehicle logo detection and recognition to detect missing and inaccurate vehicle marks under complex lighting conditions. For images acquired in complex light conditions, adaptive image enhancement is used to improve the accuracy of car sign detection by more than 2%; for the problems of multi-scale and detection speed of vehicle logo recognition in different images, the paper improves the target detection algorithm to improve the detection accuracy by more than 3%. The adaptive image enhancement algorithm and improved You Only Look One-level Feature (YOLOF) detection algorithm proposed in this study can effectively improve the correct identification rate under complex lighting conditions.

Efficient electrocatalytic oxidation of furfural to maleic acid (MA) is highly attractive, but challenging. Designing robust and cost-effective catalysts is the key for application. Herein, a bimetallic oxide catalyst (MnCeOx) was constructed by pyrolyzing the corresponding metal--organic framework (MOF) precursor. It was found that the obtained MnCeOx exhibited superior catalytic performance for electro-oxidation of furfural to produce MA, and the MA yield could reach 67.4% at an applied potential of 1.7 V vs. Ag/AgCl. Systematic investigations revealed that the excellent performance of MnCeOx originated from its suitable ability of forming surface oxygen vacancies, which could enhance the furfural adsorption on the active interfacial region of MnCeOx, thereby leading to the high catalytic activity of MnCeOx. [ABSTRACT FROM AUTHOR]