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Abstract Eliminating poverty is a shared aspiration of people worldwide. This article analyzes 762 rural poverty-related texts promulgated and implemented by the Chinese Government since 1984 using content analysis based on a three-dimensional framework encompassing the time of policy issuance, policy goals, and types of policy instruments. The study outlines the overall landscape and evolutionary context of the policy system. The results show that, during absolute poverty governance, China’s rural poverty governance can be broadly divided into three stages: regional development-oriented poverty alleviation, comprehensive poverty alleviation, and targeted poverty alleviation. Based on the production-oriented welfare model, economic development became the primary goal of poverty alleviation policies, while insufficient attention was given to service support and capacity-building goals. The alleviation of poverty mainly relied on the propulsive force generated by supply-side policy instruments led by the Government and the external driving force generated by environmental policy instruments, with a significant deficiency in the propulsive force produced by demand-side policy instruments. Entering the phase of relative poverty governance, optimizing poverty governance policy instruments requires breaking free from path dependence, following the evolutionary pattern of poverty governance. It involves ensuring that policy instruments support economic development while emphasizing addressing service support and capacity-building goals. It is crucial to increase the frequency of using demand-side policy instruments, stimulate their pulling force on poverty alleviation, and achieve a trend of evolutionary innovation and the collaborative governance of policy instruments.

The optimal scheduling method of the power grid considering the node coupling degree and the duality of mutual inverse mapping is studied to effectively establish the random dynamic scene of the power grid and improve its optimal scheduling effect. Considering the duality of the mutual inverse mapping, a random dynamic scene of the power grid is generated. The optimization model of the grid random dynamic scene partition was established considering the coupling degree of the nodes in the region. The anti-prey particle swarm optimization algorithm was used to solve the optimization model, and the scene partition results were obtained. To construct an optimization scheduling model for the regional power grid with the objective functions of minimizing energy abandonment rate and grid loss and the constraints of power flow, output, and climbing power. A predator-prey particle swarm optimization algorithm is used to solve the optimization scheduling model, and the minimum energy abandonment rate, minimum grid loss, and corresponding optimal scheduling strategies are obtained. The experimental results show that this method can effectively generate random dynamic scenes of a power grid and has a better scene partitioning effect. Under different working conditions, this method can achieve optimal dispatching of the power grid and reduce the power grid energy abandonment rate and network loss.

Abstract Blue phosphorene (BlueP), a theoretically proposed phosphorous allotrope with buckled honeycomb lattice, has attracted considerable interest due to its intriguing properties. Introducing chirality into BlueP can further enrich its physical and chemical properties, expanding its potential for applications. However, the synthesis of chiral BlueP remains elusive. Here, we demonstrate the growth of large-area BlueP films on Cu(111), with lateral size limited by the wafer dimensions. Importantly, we discovered that the BlueP is characterized by an ultraflat honeycomb lattice, rather than the prevailing buckled structure, and develops highly ordered spatial chirality plausibly resulting from the rotational stacking with the substrate and interface strain release, as further confirmed by the geometric phase analysis. Moreover, spectroscopic measurements reveal its intrinsic metallic nature and different characteristic quantum oscillations in the image-potential states, which can be exploited for a range of potential applications including polarization optics, spintronics, and chiral catalysis.

Abstract Background The relationship of testosterone and estradiol concentrations with cognitive function among community-dwelling older men was inconclusive. To examine the association of serum testosterone and estradiol concentrations with cognitive function in older men with or without vascular risk factors (VRFs). Methods This cross-sectional study consisted of 224 community-dwelling men aged 65–90 years in the Songjiang District of Shanghai, China. Serum testosterone and estradiol were measured by electrochemiluminescence immunoassay. The following five factors were defined as VRFs in this study: obesity, history of hypertension, diabetes, stroke, and coronary heart disease. Multivariable linear regression was used to examine the association of testosterone and estradiol with the Mini-Mental State Examination (MMSE) in participants with or without VRF. Restricted cubic spline (RCS) regression was performed to account for the nonlinearity of these associations. Results An inverted “U” shaped non-linear relationship was found between testosterone concentration and MMSE score in men with one VRF (P overall =.003, non-linear P =.002). Estradiol showed an inverted “U” shaped non-linear relationship with MMSE score independent of VRFs (men without VRF, P overall =.049, non-linear P =.015; men with one VRF, overall P =.007, non-linear P =.003; men with two or more VRFs, overall P =.009, non-linear P =.005). Conclusion In older men, an optimal level of sex steroid concentration may be beneficial to cognitive function and the VRFs should be considered when interpreting the relationship between sex steroid and cognitive function.

Unilateral biportal endoscopic spinal surgery (UBE) is a rapidly growing surgical method and has attracted much interest recently. The most common complication of this technique is cerebrospinal fluid (CSF) leakage due to intraoperative dural tears. There have been no reports of bacterial meningitis due to dural tears in UBE surgery and its treatment and prevention. We reported a 47 year-old man with CSF due to an intraoperative dural tear. A drainage tube was routinely placed and removed on the fourth day after surgery, resulting in fever and headache on the fifith postoperative day. Blood and CSF cultures showed Klebsiella pneumoniae infection, and with lumbar drainage and appropriate antibiotics based on sensitivity tests, the patient's fever and headache were effectively relieved. This case report suggests the importance of prolonged drainage tube placement, adequate drainage, careful intraoperative separation to avoid dural tears, and effective sensitive antibiotic therapy.

The imbalance of the lateral shoulder is reflected by the clavicle angle (CA) in radiology. It remains unclear how to achieve postoperative lateral shoulder balance (LSB) after spinal deformity correction surgery. A retrospective analysis was conducted on AIS patients who underwent surgery by the same spine surgeon at our hospital from 2016 to 2020. A total of 110 patients with spinal deformity were included in the study to verify the correlation between the T1–T5 tilt angle and CA before and after surgery, as well as the relation-ship between the change in T1–T5 tilt angle before and after surgery and the change in CA before and after surgery. By comparing the correlation coefficients, it was found that there may not be a direct relationship between the pre- and postoperative tilt angles of T1–5 and CA, but their changes were closely related to the changes in CA. The change in T1 tilt angle after orthopaedic surgery was significantly correlated with the change in CA, with a correlation coefficient of 0.976, indicating a close relationship between T1 and the clavicle. As the vertebrae moved down, the correlation gradually decreased. In summary, this study suggests that there is a close relationship between T1–T5 and the clavicle and that the change in T1 tilt angle after spinal scoliosis correction surgery is significantly correlated with CA, which decreases as the vertebra moves down.

Conclusion: Our findings indicate that EIF2S1 appears to facilitate the progression of NB by protecting tumor cells from ferroptosis through modulating GPX4 and SLC7A11 expression. Consequently, EIF2S1 may serve as a potential therapeutic target for the management of NB.

Being one of the main elements of water resources, lakes perform an indispensable part in social production as well as in life. During recent decades, the area of the lake has significantly altered due to global climate variability and growing intensity of the anthropogenic activities. The shrinkage and expansion of lakes have seriously affected both its ecological function and the sustainable development of the regional economy. With this study, we obtain the areas of 38 lakes in China by using the Landsat serial of remote-sensing satellite images in the period 1989–2019 in combination with NDWI water body index and Otsu adaptive thresholding method according to Google Earth Engine (GEE) to explore the trends of lake area changes and related drivers. The outcomes revealed that (1) the overall lake area in the Yunnan-Guizhou Plateau Lake Region (YGP_LR) showed a decreasing trend during the period from 1989 to 2019; the total area of the two lakes(Selin Co and Yangzhuoyong Co) in the Qinghai-Tibet Plateau (QTP_LR) shows an expanding trend; the area of Wulungu Lake in the Mong-Xin Plateau Lake Region (MXP_LR) and Xingkai Lake in the Northeast Plain and Mountain Lake Region (NPM_LR) on a tendency to expand; the area of lakes in the Eastern Plain Lake Region (EP_LR) fluctuated greatly, and the overall area shows a decreasing trend. (2) The increase of temperature promoted the expansion of lake area fed by glacier melt. The increase of rainfall is conducive to the expansion of lake area. The lake area of YGP_LR and EP_LR is closely related to the conversion of other land use types. (3) The lake area of the QTP_LR (Selin Co, Yangzhuoyong Co) varies are mainly affected by climatic factors. Lake area changes in the YGP_LR, Northeast Plain and Mountainous Lake Region (Xingkai Lake), MXP_LR (Wulungu Lake), and EP_LR are influenced by a combination of both climatic changes and the activities of humans. Impact factors of area change in the NPM_LR (Xingkai Lake) need to be further explored.

Background: The ‘obesity paradox’ in elderly patients suffering from percutaneous coronary intervention (PCI) remains a source of controversy. The present meta-analysis focused on exploring the real existence of ‘obesity paradox’ in these patients. Methods: As of November 2022, PubMed, Cochrane and Embase databases were comprehensively searched to identify articles reporting all-cause mortality according to diverse body mass index (BMI) categories after PCI among the old cases developing coronary artery disease (CAD). Summary estimates of risk ratios (RRs) were assigned four BMI groups, including underweight, normal weight, overweight, and obesity groups. Results: There were altogether nine articles involving 25,798 cases selected for further analysis. Relative to normal weight group, overweight and obesity groups had decreased all-cause mortality (RR 0.86, 95%CI 0.77-0.95 for overweight group; RR 0.57,95%CI 0.40-0.80 for obesity group), while underweight group had elevated all-cause mortality (RR 1.52, 95%CI 1.01-2.29). Conclusions: Our study revealed an ‘obesity paradox’ relation of BMI with all-cause mortality in elderly cases receiving PCI. In comparison with normal weight group, overweight and obesity groups had decreased all-cause mortality, while underweight group had increased all-cause mortality.

Zinc (Zn) is considered a promising biodegradable metal for implant applications due to its appropriate degradability and favorable osteogenesis properties. In this work, laser powder bed fusion (LPBF) additive manufacturing was employed to fabricate pure Zn with a heterogeneous microstructure and exceptional strength-ductility synergy. An optimized processing window of LPBF was established for printing Zn samples with relative densities greater than 99% using a laser power range of 80 ∼ 90 W and a scanning speed of 900 mm s ^−1 . The Zn sample printed with a power of 80 W at a speed of 900 mm s ^−1 exhibited a hierarchical heterogeneous microstructure consisting of millimeter-scale molten pool boundaries, micrometer-scale bimodal grains, and nanometer-scale pre-existing dislocations, due to rapid cooling rates and significant thermal gradients formed in the molten pools. The printed sample exhibited the highest ductility of ∼12.1% among all reported LPBF-printed pure Zn to date with appreciable ultimate tensile strength (∼128.7 MPa). Such superior strength-ductility synergy can be attributed to the presence of multiple deformation mechanisms that are primarily governed by heterogeneous deformation-induced hardening resulting from the alternative arrangement of bimodal Zn grains with pre-existing dislocations. Additionally, continuous strain hardening was facilitated through the interactions between deformation twins, grains and dislocations as strain accumulated, further contributing to the superior strength-ductility synergy. These findings provide valuable insights into the deformation behavior and mechanisms underlying exceptional mechanical properties of LPBF-printed Zn and its alloys for implant applications.

Abstract Background Working memory deficits are one of the core and most characteristic clinical features of cognitive impairment in schizophrenia. Cognitive training can improve the cognitive function of patients with schizophrenia. However, the overall and transfer effects of working memory treatment (WMT) require improvement. Numerous studies have confirmed that transcranial direct current stimulation (tDCS) enhances neuroplasticity in the brain, providing a new treatment approach for cognitive impairment in patients with schizophrenia. We hypothesize that a training mode combining “preheating” (tDCS, which changes the neural activity of working memory-related brain regions) and “ironing” (WMT) affords greater cognitive improvements than WMT alone. In addition, this study aims to examine the mechanisms underlying the superiority of tDCS combined with WMT in improving cognitive function in patients with schizophrenia. Methods This study will include 120 patients with schizophrenia aged 18–60 years. The patients will be randomized into four groups: the study group (tDCS + WMT), tDCS group (tDCS + simple response training, SRT), WMT group (sham tDCS + WMT), and control group (sham tDCS + SRT). Patients will receive 20-min, 2 mA sessions of active or sham tDCS twice a day on weekdays for 2 weeks. Each stimulation will be immediately followed by a 1 − 2-min rest and 40 min of WMT or SRT. The primary outcome is cognitive function, measured using Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and some subscales of the MATRICS Consensus Cognitive Battery (MCCB). The secondary outcomes are other behavioral measures, variations in brain imaging, and serum levels of brain-derived neurotrophic factor (BDNF). All outcomes will be measured at baseline, post-treatment, and 3-month follow-up, except for brain imaging and BDNF levels, which will be measured at baseline and post-treatment only. Discussion If tDCS combined with WMT results in significant improvements and prolonged effects on working memory, this method could be considered as a first-line clinical treatment for schizophrenia. Moreover, these results could provide evidence-based support for the development of other approaches to improve cognitive function in patients with schizophrenia, especially by enhancing WMT effects. Trial registration Chictr.org.cn; ChiCTR2200063844. Registered on September 19, 2022.

INTRODUCTION: Artificial intelligence is a product of high-end technological development since the 21st century, which has subverted people's traditional cognition in many aspects and greatly enriched and improved people's lives. Artificial intelligence has covered every aspect of life, and the distribution network overhead line project is also one of them. The combination of the two symbolizes the combination of modern technology and infrastructure construction, which is of great significance for modern economic and social development and transformation and upgrading. OBJECTIVES: In order to solve the practical problems in the design of artificial intelligence and distribution network overhead line engineering, this paper focuses on the practical use of such artificial intelligence as robots in distribution network overhead line engineering. METHODS: The models of spatial perception, target recognition and automatic calculation are established, and some key technical problems of robots put into actual engineering are simulated and calculated. RESULTS: In the spatial perception model, the combination of robotic arm and laser device is utilized to solve the problem of direct sunlight, which affects the localization. In the target recognition model, combining the algorithms of minimum spanning tree and maximum critical path, the computational accuracy is improved to 1 mm. in the automatic computation model, the introduction of auxiliary lines and the secondary confirmation of manpower make the error of the work further reduced. CONCLUSION: This paper's simulation algorithm for the reality of the distribution network overhead line project provides a more detailed solution to improve the technical content of the distribution network overhead line project and the quality of construction management is not a simple task, the need for the relevant distribution network overhead line project enterprises as well as the corresponding distribution network overhead line project personnel to take targeted measures.

INTRODUCTION: The development of artificial intelligence technology in the context of the intelligent era shows vigorous vigor and vitality, and artificial intelligence fusion of robotic automation technology can assist manpower to complete all kinds of difficult operations, distribution network overhead line as the current power transmission lines equipped with the main way for domestic power transmission and regional power safety is of great significance. OBJECTIVES: In order to reduce the labor intensity of operators, reduce the occurrence of power outages, and ensure the reliability of power supply, we discuss the application of robotic automation technology of machine-assisted and artificial intelligence in the distribution network overhead line project. METHODS: Distribution network with power operation intelligent robot will grid lines in the wave speed information through the sensor transmission to the computer system, the computer system will grid lines in the wave speed converted to the wave speed of the overhead line, can be mixed lines in the wave speed inconsistent problem to provide a good solution. RESULTS: At the scene of the work, the artificial intelligence distribution network power-carrying operation robot integrating artificial intelligence technology has a good application effect for the wiring in the distribution network overhead line project. CONCLUSION: Robot automation technology incorporates the advantages of artificial intelligence, can rely on sensor systems and computer systems to perceive and identify things, and can autonomously control their own behavior, automated processing of complex actions, with a certain degree of perception, planning and collaborative ability, can be applied to the distribution network overhead line project.

This study focuses on the protocol-based control for single-area power systems subject to actuator failures and deception attacks. Specifically, actuator failures, network attacks, unreliability, and bandwidth restrictions that emerge in power systems are taken into consideration at the same time. To cut down on the number of broadcast packets, a novel memory-adaptive event-triggered protocol is developed, where the trigger threshold parameter is adaptively changed in accordance with numerous historical sampled signals. Then, in virtue of the proposed algorithm, sufficient stabilization conditions are acquired to ensure the asymptotically stable of power systems with H∞ performance. Finally, the efficiency of the proposed control strategy is demonstrated by using a simulation example.

Solid-state high-order harmonic generation (HHG) now is a strong tool for detecting target properties, like band structure, Berry curvature and transition dipole moments (TDMs). However, the physical mechanism of high-order harmonic generation (HHG) in solids has not been fully elucidated. According to previously published works, in addition to the inter-band polarization, intra-band currents, and anomalous currents due to Berry curvature, there is another term which will be called the mixture term (MT). Taking monolayer ZnO as a sample, it is found that the intensity of the mixture term, which has been ignored for a long time in previous works, actually is comparable with other terms. Additionally, we compare the orientation-dependent HHG spectra that originated from different mechanisms. It is found that the inter-band and mixture HHG show similar orientation features. Meanwhile, Berry curvature only produces perpendicularly polarized even harmonics, and intra-band perpendicularly polarized even harmonics show special orientation features which can be explained by the orientation-dependent group velocity. This work will help people understand the mechanisms of solid-HHG better.

Feature loss in IoT scenarios is a common problem. This situation poses a greater challenge in terms of real-time and accuracy for the security of intelligent edge computing systems, which also includes network security intrusion detection systems (NIDS). Losing some packet information can easily confuse NIDS and cause an oversight of security systems. We propose a novel network intrusion detection framework based on an improved neural network. The new framework uses 23 subframes and a mixer for multi-classification work, which improves the parallelism of NIDS and is more adaptable to edge networks. We also incorporate the K-Nearest Neighbors (KNN) algorithm and Genetic Algorithm (GA) for feature selection, reducing parameters, communication, and memory overhead. We named the above system as Combinatorial Multi-Classification-NIDS (CM-NIDS). Experiments demonstrate that our framework can be more flexible in terms of the parameters of binary classification, has a fairly high accuracy in multi-classification, and is less affected by feature loss.

Rapid industrialization and ambitious socio-economic targets have presented significant challenges to China’s carbon neutrality process. However, digital transformation offers new opportunities for sustainable development. This research examines the influence of digital governance (Digov) on carbon emission performance (Cep) and explores its underlying mechanisms. The study utilizes data from cities in China’s Yangtze River Delta from 2011 to 2019. The results show that digital governance has significantly improved carbon emission performance, a conclusion that remains robust even after conducting a series of rigorous tests and addressing endogeneity concerns. The main impact mechanisms of digital governance on carbon emission performance include energy intensity reduction, energy consumption scale reduction, industrial structure adjustment, and energy consumption structure optimization.Furthermore, the results indicate that the variation in carbon emission reduction due to digital governance can be attributed to differences in city administrative level, city size, and government capacity. In particular, digital governance plays a pivotal role in facilitating the sustainable transformation of resource-based cities.From the perspective of digital governance, this study provides effective recommendations and valuable insights for achieving low-carbon targets and promoting sustainable development of cities.

Five different chitosan samples (CHI-1 to CHI-5) from crustacean shells with high deacetylation degrees (>93%) have been deeply characterized from a chemical and physicochemical point of view in order to better understand the impact of some parameters on the bioactivity against two pathogens frequently encountered in vineyards, Plasmopara viticola and Botrytis cinerea. All the samples were analyzed by SEC-MALS, 1H-NMR, elemental analysis, XPS, FTIR, mass spectrometry, pyrolysis, and TGA and their antioxidant activities were measured (DPPH method). Molecular weights were in the order: CHI-4 and CHI-5 (MW >50 kDa) > CHI-3 > CHI-2 and CHI-1 (MW < 20 kDa). CHI-1, CHI-2 and CHI-3 are under their hydrochloride form, CHI-4 and CHI-5 are under their NH2 form, and CHI-3 contains a high amount of a chitosan calcium complex. CHI-2 and CHI-3 showed higher scavenging activity than others. The bioactivity against B. cinerea was molecular weight dependent with an IC50 for CHI-1 = CHI-2 (13 mg/L) ≤ CHI-3 (17 mg/L) < CHI-4 (75 mg/L) < CHI-5 (152 mg/L). The bioactivity on P. viticola zoospores was important, even at a very low concentration for all chitosans (no moving spores between 1 and 0.01 g/L). These results show that even at low concentrations and under hydrochloride form, chitosan could be a good alternative to pesticides.