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According to the grasping requirements for fragile workpieces with cylindrical inner walls, a manipulator with internal bracing has been designed. The manipulator utilizes a constant-speed push cylinder to drive the linkage mechanism and accomplish the related works. Considering the fragile nature of the workpieces, reducing the impact velocity between the manipulator finger and the workpiece is a primary objective in the mechanism design. To achieve this, an optimization design is carried out, which maintains the overall average speed of the manipulator, while reducing the average speed only during the contact between the finger and the workpiece. The goal of optimization is to minimize the impact velocity at the contact point, using the linkage structure parameters as variables. The genetic algorithm (GA) is employed for the optimization process. The results show that optimization reduces the impact velocity at the contact point by 44.80%. To gain further insight into the influence of the process, a finite element model of a finger grasping a fragile object was created using joint modeling with the SolidWorks, Hyper Mesh, and LS-DYNA software. Simulations reveal that, after optimization, the maximum internal stress of three workpieces with thicknesses of 2.00 mm, 1.00 mm, and 0.50 mm was reduced by 47.42%, 41.53%, and 44.20%, respectively. To study the general law of the mechanical hand grasping fragile workpieces, the relationship between the cylinder driving speed and the impact speed is established. Based on the simulation results of maximum contact impact velocity, workpiece wall thickness, and maximum contact force, a prediction model of workpiece internal force is established using the Kriging prediction model theory. Additionally, the feasible range of grasping parameters under different wall thickness conditions is determined and discussed. The reliability of the designed structure is experimentally verified, providing valuable insights for ensuring the lifting work reliability of manipulators handling fragile workpieces.

Abstract High-temperature unconventional superconductivity quite generically emerges from doping a strongly correlated parent compound, often (close to) an antiferromagnetic insulator. The recently developed dynamical vertex approximation is a state-of-the-art technique that has quantitatively predicted the superconducting dome of nickelates. Here, we apply it to study the effect of pressure in the infinite-layer nickelate Sr x Pr1−x NiO2. We reproduce the increase of the critical temperature (T c ) under pressure found in experiment up to 12 GPa. According to our results, T c can be further increased with higher pressures. Even without Sr-doping the parent compound, PrNiO2, will become a high-temperature superconductor thanks to a strongly enhanced self-doping of the Ni $${d}_{{x}^{2}-{y}^{2}}$$ d x 2 − y 2 orbital under pressure. With a maximal T c of 100 K around 100 GPa, nickelate superconductors can reach that of the best cuprates.

Abstract Recent progress on the signatures of pressure-induced high-temperature superconductivity in Ruddlesden–Popper (RP) nickelates (La n+1Ni n O3n+1) has attracted growing interest in both theoretical calculations and experimental efforts. The fabrication of high-quality single-crystalline RP nickelate thin films is critical for possible reducing the superconducting transition pressure and advancing applications in microelectronics in the future. In this study, we report the observations of an active phase transition in RP nickelate films induced by misfit strain. We found that RP nickelate films favor the perovskite structure (n = ∞) under tensile strains, while compressive strains stabilize the La3Ni2O7 (n = 2) phase. The selection of distinct phases is governed by the strain dependent formation energy and electronic configuration. In compressively strained La3Ni2O7, we experimentally determined the e g splitting energy is ~0.2 eV and electrons prefer to occupy in-plane orbitals. First-principles calculations unveil a robust coupling between strain effects and the valence state of Ni ions in RP nickelates, suggesting a dual driving force for the inevitable phase co-existence transition in RP nickelates. Our work underscores the sensitivity of RP nickelate formation to epitaxial strain, presenting a significant challenge in fabricating pure-phase RP nickelate films. Therefore, special attention to stacking defects and grain boundaries between different RP phases is essential when discussing the pressure-induced superconductivity in RP nickelates.

Conflicting theoretical scenarios for infinite-layer nickelate superconductors have been hotly debated, particularly regarding whether only a single Ni-3d_{x^{2}−y^{2}} band is relevant at low energies besides electron pockets or whether multiorbital physics including Ni-3d_{z^{2}} is instead essential. The first scenario has emerged from density-functional theory plus dynamical mean-field theory (DFT + DMFT) calculations. Comparing the previous DFT + DMFT spectra to recent angular-resolved photoemission spectroscopy (ARPES) experiments, we find excellent agreement for both the Fermi surface and the strongly renormalized quasiparticle bands, supporting the first scenario. Our key findings further suggest that the “waterfalls” observed in ARPES might emerge from the quasiparticle-to-Hubbard-band crossover, and that additional spectral weight close to the A pocket likely originates from the Ni-3d_{xy} orbital.

This study aimed to explore the role and mechanism of felodipine in lung cancer therapy. Murine subcutaneous lung squamous cancer (LUSC) models constructed by KLN-205 cells were utilized to assess the effect of felodipine monotherapy and in combination with the programmed cell death protein 1 antibody (PD1ab) and cytotoxic T lymphocyte-associated antigen-4 (CTLA4ab). Immunohistochemistry analysis was subsequently applied to detect the number of CD8+ T cells and Ki67+ cells. Lastly, a series of in vitro and in vivo experiments were performed to evaluate the effects of felodipine on human LUSC cells and explore the preliminary mechanism underlying felodipine inhibition. The results revealed that felodipine monotherapy exerted a significant inhibitory effect on LUSC growth and synergistic antitumoral activity with PD1ab and CTLA4ab. Meanwhile, immunohistochemistry analysis displayed that felodipine promoted CD8+ T-cell infiltration and downregulated Ki67 expression in tumor cells. Moreover, in vitro and in vivo experiments utilizing human LUSC cells determined that felodipine impaired the proliferative and migratory abilities of cancer cells. In addition, TCGA data analysis uncovered that nuclear factor of activated T cell (NFAT1) expression was positively correlated with overall survival and disease-free survival. Finally, the cell counting kit-8 assay signaled that felodipine might suppress tumor growth by modulating NFAT1.

Neutrophils are more innate immune cells found in coronavirus disease in 2019(COVID-19). The accounting of neutrophils and the level of plasma neutrophil extracellular traps(NETs) were positively correlated with the severity of COVID-19. This article reviews the relevant studies of neutrophils, formation and degradation of NETs involved in the pathological process of COVID-19, providing the reference for further studies of pathogenesis and intervention.

Neurointervention surgery is an important method for diagnosis and treatment of neurological disorders and related brain scientific research. Robot⁃assisted neurointervention surgery can improve the minimally invasive and accurate interventional surgery, which is an important research direction. At present, the navigation technology of neurointervention surgery has gradually developed from the traditional optical navigation to MRI navigation, the interventional materials have developed from rigid puncture needle to active flexible puncture needle, and the surgical path planning and navigation technology and the surgical robot control technology have also been developing. This paper summarizes the four key technologies mentioned above and reviews the research progress of robot⁃assisted neurointervention surgery to promote its clinical application.

Depression, a mood disorder characterized by persistent feelings of sadness and aversion to activity that can interfere with daily life, is a condition of great concern. Prebiotics, which are non-digestible substances selectively utilized by host microorganisms for health benefits, have gained attention for their potential to improve overall wellness and alleviate various disorders including depression. This study aims to review clinical trials utilizing carbohydrate-type prebiotics such as inulin-type fructans, galactooligosaccharides (GOS), human milk oligosaccharides, resistant starch, prebiotic phytochemicals including epigallocatechin gallate (EGCG), chlorogenic acids, resveratrol, and prebiotic lipids (n-3 polysaturated fatty acids) to determine their effects on depression. Our findings suggest that GOS at a daily dosage of 5 g and eicosapentaenoic acid at or less than 1 g can effectively mitigate depressive symptoms. While EGCG exhibits potential antidepressant properties, a higher dosage of 3 g/d may be necessary to elicit significant effects. The plausible mechanisms underlying the impact of prebiotics on depression include the synthesis of neurotransmitters, production of short-chain fatty acids, and regulation of inflammation.

Objective Nursing intern students are important observers in the clinical environment. Comprehensive data about palliative care in medical environment can come from a survey that asked nursing intern students about the behaviors of faculty. Methods This survey included a total of 126 third-year nursing intern students from Peking Union Medical College. A self-designed questionnaire was used to investigate the extent to which the students were satisfied about faculty's behaviors related to palliative care, including communication, symptom control and difficult conversations. The students aged 20 to 21. Results There were 63.5%(80/126) students satisfied with the pain management, 34.1%(43/126) and 35.7%(45/126) students were satisfied with the daily communication and conversations to overcome barriers between faculty and patients. Only 33.3%(42/126) were satisfied with the care to the family members after patient'deaths. Nursing intern students who recently experienced the death of patients had significantly lower satisfaction with clinical environment dealing with decedent's family members than those without this experience(25.21 vs 28.41, P＜0.01). Students who received training of palliative care had shown significantly lower satisfaction with clinical environment than those without the training (26.18 vs 31.90, P＜0.001). Conclusions Nursing intern students are unsatisfied with the clinical environment for the training of palliative care indicating some weakness in the performance of palliative care in hospital and the need to improve clinical teaching of palliative care.

Objective To verify the accuracy and cost of the value of serum sodium fluctuation in predicting adverse clinical outcomes, and to propose a warning value of serum sodium fluctuations for early warning of in-hospital death and summarize the methodology for setting warning values. Methods This investigation covered all patients admitted to Peking Union Medical College Hospital from January 1, 2014 to December 31, 2014. Patients with normal serum sodium at the time of admission and older than 18 years old were included. Patients without serum sodium retested during the hospitalization were excluded. Clinical characteristics including gender, age, primary diagnosis, and causes of death were documented and laboratory examinations were collected including all serum sodium values during hospitalization. The highest and lowest values among all measurements of serum sodium during hospitalization were identified. The difference between the highest and lowest serum sodium value was defined as the fluctuation value of serum sodium level.The area under the curve (AUC) of sodium fluctuations predicting in-hospital death was calculated. The specificities and sensitivities were calculated with the cut-off points of 10, 12, 14, 16, 18, 20, 22, and 24 mmol/L. A warning related to death in the hospital was defined as a true warning, and a warning unrelated to death in the hospital was defined as a false warning. The number of false warnings was defined as the cost of warning.The ratio of the true warnings to the total warnings was defined as the efficiency of warning. An appropriate cut-off point was selected for combined accuracy, cost, and efficiency of warning. Results In total, 33 323 hospitalization records met the inclusion criteria, of which 191 patients (0.57%) died. 148 records of death were analyzed. Among these patients, 53 died from tumor (35.6%), 52 died from infection (34.9%), 46 died from respiratory failure (30.9%), and 26 died from heart failure (17.4%), 6 died from sudden death (4.0%), 5 died from cerebral hemorrhage (3.4%), 6 died from bleeding from other parts (4.0%), and 1 died from cerebral herniation (0.7%).There were 75 patients (50.7%) experienced serum sodium fluctuations within 10 days before death. The average serum sodium fluctuation was (13.36±8.62)mmol/L, and the highest was 35 mmol/L. Serum sodium fluctuation predicted in-hospital death with an AUC of 85.2% (95% CI:81.8%-88.5%). Predicting in-hospital death with a serum sodium fluctuation greater than 20 mmol/L had a specificity of 99.0% and a sensitivity of 28.8%. If serum sodium fluctuation greater than 20 mmol/L was set as a warning value, 28.8% of hospital deaths would be identified, the number of warnings would be 397, the number of true warnings would be 55, the cost of warning would be 342, and the efficiency of warning would be 13.9%. Conclusions Serum sodium fluctuation greater than 20 mmol/L could be used as a biomarker value for early warning of in-hospital death with high accuracy and low management cost. Serum sodium fluctuations greater than 20 mmol/L is a warning value point and can be potentially used as a predicting warning to suppot the identification of critically ill patients and thus to improve the management of inpatients at high risk of death.

Objective To explore the effect of early intervention for perioperative delirium in older (> 60 years) hip fracture patients. Methods This prospective study enrolled hip fracture patients aged ≥60 years who were admitted into our hospital between July 2011 and August 2019. Hip fractures were classified according to the Arbeitsgemeinschaft für Osteo‐synthesefragen (AO) classification. This study included patients with isolated hip fracture and excluded patients with pathological or peri prosthetic fracture or patients with multiple traumatic injuries and high‐energy trauma. They were randomized to receive conventional orthopedic care group (n = 65) or comprehensive orthopedic care group including preoperative psychological counseling and preventative risperidone (n = 63). Daily assessment was based on patient interview with the CAM‐CR, and delirium was diagnosed by the Delirium Rating Scale (DRS‐R‐98). The rate, severity and duration of perioperative delirium and the length of postoperative stay were analyzed. Results Totally 200 patients were screened for eligibility. Twenty patients were excluded due to alcohol abuse and 40 were excluded because of brain lesions on head CT. In addition, 12 patients were excluded because of impaired cognition. Finally 128 patients were enrolled. Their mean age was 75.3 ± 2.2 years for the comprehensive orthopedic care group and 73.5 ± 6.1 years for the conventional orthopedic care group, and 53.9% of the patients were female. Sixty‐eight (53.1%) patients had intertrochanteric fracture, 39.8% patients had femoral head fracture, and 7.0% patients had subtrochanteric fracture. In addition, 58.6% patients underwent internal fixation and 41.4% patients received arthroplasty. In this study, 63 patients were randomized to the comprehensive orthopedic care group and 65 patients to the conventional orthopedic care group. The two groups were comparable in demographic and baseline characteristics (P > 0.05). The rate of perioperative delirium was significantly lower in the comprehensive care group vs the conventional care group (15.9% vs. 30.8%; P 60 years).

Objective: To investigate the relationship between maternal blood pressure (BP) and neonatal cord blood telomere length (TL) during pregnancy, and to clarify the sensitive period. Methods: We conducted a prospective cohort study with 621 mother‐newborn pairs from the Guangxi Zhuang Birth Cohort (GZBC) in China. Multiple informant models, restricted cubic spline regression (RCS) models, and quantile regression models were conducted to analyze the correlation between maternal BP and neonatal TL. Results: Maternal diastolic blood pressure (DBP) was inversely related to neonatal cord blood TL in the second trimester (P = 0.015) and the third trimester (P = 0.011). There was a male‐specific relationship between maternal BP and neonatal TL. A 1 mmHg increment in maternal systolic blood pressure (SBP) and DBP during the second trimester was related with 0.42% (95% CI: −0.80%, −0.04%) and 0.61% (95% CI: −1.13%, −0.09%) shorter TL in male newborns, respectively. Per unit increase of maternal DBP during the third trimester was related with 0.54% (95% CI: −1.03%, −0.05%) shorter TL in male newborns. Pregnant women with hypertensive disease of pregnancy (HDP) had male offspring with shorter TL (P = 0.003). However, no significant relationships were found in female newborns (P = 0.570). Conclusion: Maternal BP during pregnancy is inversely correlated with male neonatal TL and the second and third trimesters are sensitive windows. Synopsis: Maternal blood pressure during pregnancy is inversely correlated with male neonatal telomere length and the second and third trimesters are sensitive windows. [ABSTRACT FROM AUTHOR]

Asplenium is one of the most species‐rich genera of ferns. While ubiquitous polyploidy and hybridization events, as well as vast distribution ranges, contribute to its remarkable diversity, these facts also lead to extreme classification difficulties. The A. exiguum complex is a natural morphological assemblage of taxa sharing part or all ancestral genomes due to polyploidy and hybridization. Consisting of 4 to 13 taxa mainly distributed in the Sino‐Himalayan region, taxonomic issues of this complex have been debatable for a long time. Here, we collected 49 samples representing the majority of the recognized taxa and reconstructed phylogenetic trees using two plastid loci (rbcL, rpl32‐trnP) and three nuclear loci (pgiC, SQD1, nrDNA). Evidence from ploidy, macro‐ and micromorphology, geographical pattern, and ecological niche was also integrated to illuminate the species boundaries and evolutionary history within the complex. According to our investigation, six taxa, including two diploid species (A. barkamense, A. lushanense), three tetraploid species (A. exiguum, A. glenniei, A. nesii), and one triploid nothospecies (A. ×mickelii), are accepted. Asplenium barkamense, which used to be treated as a synonym of A. nesii in Flora of China, is an independent species and the common diploid progenitor of autotetraploid A. nesii and allotetraploid A. glenniei. Moreover, A. glenniei (= A. yunnanense), widespread in the subtropical and temperate regions of East Asia and occasionally seen in the southwestern United States, Mexico, and northern Guatemala of North America, is an allotetraploid originated from A. barkamense and A. lushanense, whereas A. exiguum, known with a narrow distribution in tropical Asia, is a putative autotetraploid offspring of A. lushanense. Therefore, A. glenniei is restored as an independent species from A. exiguum. Asplenium ×mickelii is supported as a sterile hybrid of A. lushanense and A. glenniei. In addition, our study suggests that the majority of speciation events in the complex probably took place in the Hengduan Mountains, where complicated orogenic activities and climatic oscillations facilitate geographic isolation and polyploid establishment. The two tetraploids, A. nesii and A. glenniei, adapted to distinct climate conditions and colonized wider ranges compared to their parents. [ABSTRACT FROM AUTHOR]

Finding a material that turns superconducting under ambient conditions has been the goal of over a century of research, and recently Pb$_{10-x}$Cu$_x$(PO$_4$)$_6$O aka LK-99 has been put forward as a possible contestant. In this work, we study the possibility of electronically driven superconductivity in LK-99 also allowing for electron or hole doping. We use an ab initio derived two-band model of the Cu $e_g$ orbitals for which we determine interaction values from the constrained random phase approximation (cRPA). For this two-band model we perform calculations in the fluctuation exchange (FLEX) approach to assess the strength of orbital and spin fluctuations. We scan over a broad range of parameters and enforce no magnetic or orbital symmetry breaking. Even under optimized conditions for superconductivity, spin and orbital fluctuations turn out to be too weak for superconductivity anywhere near to room-temperature. We contrast this finding to non-self-consistent RPA, where it is possible to induce spin singlet d-wave superconductivity at $T_c$ ≥300K if the system is put close enough to a magnetic instability.

In real-time video streaming, data packets are transported over the network from a transmitter to a receiver. The quality of the received video fluctuates as the network conditions change, and it can degrade substantially when there is considerable packet loss. Forward error correction (FEC) techniques can be used to recover lost packets by incorporating redundant data. Conventional FEC schemes do not work well when scalable video coding (SVC) is adopted. In this paper, we propose a novel FEC scheme that overcomes the drawbacks of these schemes by considering the reference picture structure of SVC and weighting the reference pictures more when FEC redundancy is applied. The experimental results show that the proposed FEC scheme outperforms conventional FEC schemes.

The worldwide spread of coronavirus disease 2019 (COVID-19) has caused a heavy burden on the public health of all countries. As the specific antiviral treatment is not available, it is necessary to monitor various clinical indicators, and minimize the risk factors related to poor outcomes in the management of COVID-19. COVID-19 is often presented with hyponatremia which is frequently associated with prolonged hospitalization, increased rate of intensive care unit transfer, higher risk of severe pneumonia and mortality. Hyponatremia is an important index for early identification of patients with poor prognosis. COVID-19 related hyponatremia is mainly caused by inappropriate antidiuretic hormone secretion syndrome and hypovolemia. If hyponatremia can be diagnosed and corrected in time, the poor clinical outcomes related to hyponatremia can be prevented.

Perinatal depression is a mood disorder that is reported in women during pregnancy (prenatal) and after childbirth (postnatal). The onset of perinatal depression is associated with changes in reproductive hormones, stress hormones and neurosteroids. These chemical compounds can be modulated by the gut microbiota, which may affect maternal mental health during the perinatal period via the gut-brain-axis. Recent studies suggest that nutritional and dietary interventions (vitamin D, ω-3 fatty acids, iron, and fiber) effectively prevent or mitigate maternal depression and anxiety, but their efficacy is confounded by various factors, including the gut microbiota. Probiotics are efficacious in maintaining microbiota homeostasis, and thus, have the potential to modulate the development of perinatal mood disorders, despite no evidence in human. Therefore, clinical trials are warranted to investigate the role of probiotic supplementation in perinatal depression and behavioral changes. This article reviews the interplay between nutrition, gut microbiota and mood and cognition, and the evidence suggesting that probiotics affect the onset and development of perinatal depression.

With the popularity of mobile intelligent terminals such as mobile phones in the whole society,the production capacity of digital content has sunk to all levels of the society,forming a multi-source,independent and native Internet media content manufacturing pattern.With the vigorous development of various emerging media represented by social media and we media,the propagation ability of digital content has been greatly enhanced,especially in the reporting of sensitive,hot and important events in the process of propagation,which will produce a lot of derivative content.The improvement of the above two abilities causes the internet information to be characterized by mass,uneven content quality and multi-point of view.How to accurately recommend the news of correct value orientation and accurate information disclosure related to judicial work to maintain and promote social fairness and justice has become a new problem and challenge in the judicial field. 河北科技大学学报 2021年 第2期 王子岩，等:基于系统动力学的资讯个性化推荐研究 Recommender system effectively solved the problem that it was difficult for users to find the information they need efficiently in the mass of information.Content based recommendation technology analyzed the items that users are interested in before,got the similar items by calculation,and then pushed the items with the highest similarity to users.Collaborative filtering (CF) is the most widely used recommendation system,which was first proposed by Goldberg in 1992 when developing tapestry e-mail filtering system.Its core idea is to analyze the user′s historical behavior data through the algorithm,mine the user′s interest preferences,classify users according to different interest preferences,and recommend items with similar preferences.Collaborative filtering is the most widely used algorithm in recommendation system.It was first proposed by Goldberg in 1992 when developing tapestry e-mail filtering system.Its core idea was to analyze the user′s historical behavior data through the algorithm,mine the user′s interest preferences,classify users according to different interest preferences,and recommend items with similar preferences.At present,personalized recommendation has been widely used in e-commerce,film and television works,food and beverage,news and other fields.For example,the recommendation of Jingdong started in 2012,and the recommendation products were based on rule matching.The combination of the whole recommendation product lines was like a loose primitive tribe,and there was no intersection of engineering and algorithm between the tribes.Taobao launched the recommendation engine of "personalized recommendation",namely "thousands of people and thousands of faces" in 2013,which used some users′behaviors to speculate what users may like through algorithms.Meituan has built the world′s largest food knowledge base,created knowledge graphs for more than 2 million businesses and 300 million products,made user portraits for 250 million users,and built the world′s largest O2O intelligent recommendation platform for users. Douban used social behavior analysis to solve recommendation problems,such as collaborative filtering technology based on the sameusers′behavior ,and friends or neighbors recommendation,etc.,which is also a supplement of personalized recommendation.The introduction of social recommendation can solve the problem of narrow recommendation range caused by simple product content recommendation.The personalized recommendation algorithm of Toutiao was based on voting,and its core idea was to vote.Each user can cast his only vote to the article he likes.After statistics,the final result was likely to be the best article in this crowd,and the article would be recommended to the same group of users.This method seems to be very simple,but in fact,it needs massive user behavior data mining and analysis.System dynamics is an interdisciplinary subject based on system theory,cybernetics and information theory,and with the help of computer simulation technology.From the perspective of system,structured and dynamic analysis and model simulation are conducted,which is good at analyzing high-order,nonlinear and time-varying complex systems,and is suitable for analyzing the dynamic and complex process of personalized information recommendation by combining qualitative and quantitative analysis..Based on the theory of system dynamics,this paper modeled and simulated the important factors that affect the effect of information recommendation in Vensim software,and constructed the causal feedback model and stock flow model including the number of users,articles,tags and the influence among subsystems.The system dynamics equation model was established,and the sensitivity analysis of related factors was carried out.The results show that the number of articles,the characteristic tags and the interest factors of articles all have an important impact on the recommendation effect.They are the key factors to be considered in the design of the recommendation system,and are also the important ways to solve the key problems,such as the cold start,real-time and "information cocoon room" of the recommendation system.Research on information personalized recommendation based on system dynamics can actively and effectively meet the challenges of information disclosure in the judicial field and improve the accurate recommendation effect.