Effect of PCBN cutting tools wear on surface integrality in high-speed hard turning

In this paper, the effect of of flank wear polycrystalline cubic boron nitride （PCBN） tools on residual stresses, white layer and roughness of machined workpiece surfaces is studied. Experimental results indicate that with the increase of the tool wear, the surface of the machined workpiece tends to generate tensile residual stresses, and white layer becomes clearly thicker and uneven on the workpiece surface. The effect of the flank wear on the surface roughness is less within some range of flank wear value. The results show that it is possible to produce ideal surface integrality levels by controlling the tool flank wear.

Astrocytes integrate time and space

Astrocytes read and react to synaptic transmission through tripartite synapses,where the binding of neurotransmitters onto astrocytic receptors triggers an increase in intracellular calcium.Recent investigations have revealed that astrocytes exhibit two distinct states of intracellular calcium activity:(1)graded subcellular localized clusters with independently active microdomains,likely influenced by nearby synaptic events,and(2)whole-cell astrocyte calcium surges,believed to result from the coordinated activation of multiple synapses.Notably,astrocyte calcium responses are not solely graded;instead,a spatial threshold of intracellular calcium activity can be overcome to elicit an astrocyte calcium surge.Together these calcium responses,in turn,initiate downstream signaling pathways capable of modifying synaptic communication and overall network activity.In summary,astrocytes can function as integrators of local synaptic events,actively contributing to information processing within the brain.

Multisensory mechanisms of gait and balance in Parkinson’s disease:an integrative review

Understanding the neural underpinning of human gait and balance is one of the most pertinent challenges for 21st-century translational neuroscience due to the profound impact that falls and mobility disturbances have on our aging population.Posture and gait control does not happen automatically,as previously believed,but rather requires continuous involvement of central nervous mechanisms.To effectively exert control over the body,the brain must integrate multiple streams of sensory information,including visual,vestibular,and somatosensory signals.The mechanisms which underpin the integration of these multisensory signals are the principal topic of the present work.Existing multisensory integration theories focus on how failure of cognitive processes thought to be involved in multisensory integration leads to falls in older adults.Insufficient emphasis,however,has been placed on specific contributions of individual sensory modalities to multisensory integration processes and cross-modal interactions that occur between the sensory modalities in relation to gait and balance.In the present work,we review the contributions of somatosensory,visual,and vestibular modalities,along with their multisensory intersections to gait and balance in older adults and patients with Parkinson’s disease.We also review evidence of vestibular contributions to multisensory temporal binding windows,previously shown to be highly pertinent to fall risk in older adults.Lastly,we relate multisensory vestibular mechanisms to potential neural substrates,both at the level of neurobiology(concerning positron emission tomography imaging)and at the level of electrophysiology(concerning electroencephalography).We hope that this integrative review,drawing influence across multiple subdisciplines of neuroscience,paves the way for novel research directions and therapeutic neuromodulatory approaches,to improve the lives of older adults and patients with neurodegenerative diseases.

Challenges and improvement strategies in the hospitalization of chronic multimorbid patients

BACKGROUND Addressing the growing challenge of hospitalizing chronic multimorbid patients,this study examines the strain these conditions impose on healthcare systems at a local level,focusing on a pilot program.Chronic diseases and complex patients require comprehensive management strategies to reduce healthcare burdens and improve patient outcomes.If proven effective,this pilot model has the potential to be replicated in other healthcare settings to enhance the management of chronic multimorbid patients.AIM To evaluate the effectiveness of the high complexity unit(HCU)in managing chronic multimorbid patients through a multidisciplinary care model and to compare it with standard hospital care.METHODS The study employed a descriptive longitudinal approach,analyzing data from the Basic Minimum Data Set(BMDS)to compare hospitalization variables among the HCU,the Internal Medicine Service,and other services at Antequera Hospital throughout 2022.The HCU,designed for patients with complex chronic conditions,integrates a patient-centered model emphasizing multidisciplinary care and continuity post-discharge.RESULTS The study employed a descriptive longitudinal approach,analyzing data from the BMDS to compare hospitalization variables among the HCU,the Internal Medicine Service,and other services at Antequera Hospital throughout 2022.The HCU,designed for patients with complex chronic conditions,integrates a patient-centered model emphasizing multidisciplinary care and continuity post-discharge.CONCLUSION This study demonstrates the effectiveness of the HCU in managing patients with complex chronic diseases through a multidisciplinary approach.The coordinated care provided by the HCU results in improved patient outcomes,reduced unnecessary hospitalizations,and better management of patient complexity.The superiority of the HCU compared to standard care is evident in key outcomes such as fewer readmissions and higher patient satisfaction,reinforcing its value as a model of care to be replicated.

Cohort study on the treatment of BRAF V600E mutant metastatic colorectal cancer with integrated Chinese and western medicine

BACKGROUND Patients with BRAF V600E mutant metastatic colorectal cancer(mCRC)have a low incidence rate,poor biological activity,suboptimal response to conventional treatments,and a poor prognosis.In the previous cohort study on mCRC conducted by our team,it was observed that integrated Chinese and Western medicine treatment could significantly prolong the overall survival(OS)of patients with colorectal cancer.Therefore,we further explored the survival benefits in the population with BRAF V600E mutant mCRC.AIM To evaluate the efficacy of integrated Chinese and Western medicine in the treatment of BRAF V600E mutant metastatic colorectal cancer.METHODS A cohort study was conducted on patients with BRAF V600E mutant metastatic colorectal cancer admitted to Xiyuan Hospital of China Academy of Chinese Medical Sciences and Traditional Chinese Medicine Hospital of Xinjiang Uygur Autonomous Region from January 2016 to December 2022.The patients were divided into two cohorts.RESULTS A total of 34 cases were included,with 23 in Chinese-Western medicine cohort(cohort A)and 11 in Western medicine cohort(cohort B).The median overall survival was 19.9 months in cohort A and 14.2 months in cohort B,with a statistically significant difference(P=0.038,hazard ratio=0.46).The 1-3-year survival rates were 95.65%(22/23),39.13%(9/23),and 26.09%(6/23)in cohort A,and 63.64%(7/11),18.18%(2/11),and 9.09%(1/11)in cohort B,respectively.Subgroup analysis showed statistically significant differences in median OS between the two cohorts in the right colon,liver metastasis,chemotherapy,and first-line treatment subgroups(P<0.05).CONCLUSION Integrated Chinese and Western medicine can prolong the survival and reduce the risk of death in patients with BRAF V600E mutant metastatic colorectal cancer,with more pronounced benefits observed in patients with right colon involvement,liver metastasis,combined chemotherapy,and first-line treatment.

Harnessing artificial intelligence for identifying conflicts of interest in research

This editorial explores the transformative potential of artificial intelligence(AI)in identifying conflicts of interest(COIs)within academic and scientific research.By harnessing advanced data analysis,pattern recognition,and natural language processing techniques,AI offers innovative solutions for enhancing transparency and integrity in research.This editorial discusses how AI can automatically detect COIs,integrate data from various sources,and streamline reporting processes,thereby maintaining the credibility of scientific findings.

THE SPACE-TIME INTEGRALITY FOR SOLUTIONS OF SOME HIGHER EVOLUTION

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Crosstalk among canonical Wnt and Hippo pathway members in skeletal muscle and at the neuromuscular junction

Skeletal muscles are essential for locomotion,posture,and metabolic regulation.To understand physiological processes,exercise adaptation,and muscle-related disorders,it is critical to understand the molecular pathways that underlie skeletal muscle function.The process of muscle contra ction,orchestrated by a complex interplay of molecular events,is at the core of skeletal muscle function.Muscle contraction is initiated by an action potential and neuromuscular transmission requiring a neuromuscular junction.Within muscle fibers,calcium ions play a critical role in mediating the interaction between actin and myosin filaments that generate force.Regulation of calcium release from the sarcoplasmic reticulum plays a key role in excitation-contraction coupling.The development and growth of skeletal muscle are regulated by a network of molecular pathways collectively known as myogenesis.Myogenic regulators coordinate the diffe rentiation of myoblasts into mature muscle fibers.Signaling pathways regulate muscle protein synthesis and hypertrophy in response to mechanical stimuli and nutrient availability.Seve ral muscle-related diseases,including congenital myasthenic disorders,sarcopenia,muscular dystrophies,and metabolic myopathies,are underpinned by dys regulated molecular pathways in skeletal muscle.Therapeutic interventions aimed at preserving muscle mass and function,enhancing regeneration,and improving metabolic health hold promise by targeting specific molecular pathways.Other molecular signaling pathways in skeletal muscle include the canonical Wnt signaling pathway,a critical regulator of myogenesis,muscle regeneration,and metabolic function,and the Hippo signaling pathway.In recent years,more details have been uncovered about the role of these two pathways during myogenesis and in developing and adult skeletal muscle fibers,and at the neuromuscular junction.In fact,research in the last few years now suggests that these two signaling pathways are interconnected and that they jointly control physiological and pathophysiological processes in muscle fibers.In this review,we will summarize and discuss the data on these two pathways,focusing on their concerted action next to their contribution to skeletal muscle biology.However,an in-depth discussion of the noncanonical Wnt pathway,the fibro/a dipogenic precursors,or the mechanosensory aspects of these pathways is not the focus of this review.

The Roadmap of 2D Materials and Devices Toward Chips

Due to the constraints imposed by physical effects and performance degra certain limitations in sustaining the advancement of Moore’s law.Two-dimensional(2D)materials have emerged as highly promising candidates for the post-Moore era,offering significant potential in domains such as integrated circuits and next-generation computing.Here,in this review,the progress of 2D semiconductors in process engineering and various electronic applications are summarized.A careful introduction of material synthesis,transistor engineering focused on device configuration,dielectric engineering,contact engineering,and material integration are given first.Then 2D transistors for certain electronic applications including digital and analog circuits,heterogeneous integration chips,and sensing circuits are discussed.Moreover,several promising applications(artificial intelligence chips and quantum chips)based on specific mechanism devices are introduced.Finally,the challenges for 2D materials encountered in achieving circuit-level or system-level applications are analyzed,and potential development pathways or roadmaps are further speculated and outlooked.

3D‑Printed Carbon‑Based Conformal Electromagnetic Interference Shielding Module for Integrated Electronics

Electromagnetic interference shielding(EMI SE)modules are the core com-ponent of modern electronics.However,the tra-ditional metal-based SE modules always take up indispensable three-dimensional space inside electronics,posing a major obstacle to the integra-tion of electronics.The innovation of integrating 3D-printed conformal shielding(c-SE)modules with packaging materials onto core electronics offers infinite possibilities to satisfy ideal SE func-tion without occupying additional space.Herein,the 3D printable carbon-based inks with various proportions of graphene and carbon nanotube nanoparticles are well-formulated by manipulating their rheological peculiarity.Accordingly,the free-constructed architectures with arbitrarily-customized structure and multifunctionality are created via 3D printing.In particular,the SE performance of 3D-printed frame is up to 61.4 dB,simultaneously accompanied with an ultralight architecture of 0.076 g cm^(-3) and a superhigh specific shielding of 802.4 dB cm3 g^(-1).Moreover,as a proof-of-concept,the 3D-printed c-SE module is in situ integrated into core electronics,successfully replacing the traditional metal-based module to afford multiple functions for electromagnetic compatibility and thermal dissipa-tion.Thus,this scientific innovation completely makes up the blank for assembling carbon-based c-SE modules and sheds a brilliant light on developing the next generation of high-performance shielding materials with arbitrarily-customized structure for integrated electronics.

Prediction models of burst strength degradation for casing with considerations of both wear and corrosion

Casing wear and casing corrosion are serious problems affecting casing integrity failure in deep and ultra-deep wells.This paper aims to predict the casing burst strength with considerations of both wear and corrosion.Firstly,the crescent wear shape is simplified into three categories according to common mathematical models.Then,based on the mechano-electrochemical(M-E)interaction,the prediction model of corrosion depth is built with worn depth as the initial condition,and the prediction models of burst strength of the worn casing and corroded casing are obtained.Secondly,the accuracy of different prediction models is validated by numerical simulation,and the main influence factors on casing strength are obtained.At last,the theoretical models are applied to an ultra-deep well in Northwest China,and the dangerous well sections caused by wear and corrosion are predicted,and the corrosion rate threshold to ensure the safety of casing is obtained.The results show that the existence of wear defects results in a stress concentration and enhanced M-E interaction on corrosion depth growth.The accuracy of different mathematical models is different:the slot ring model is most accurate for predicting corrosion depth,and the eccentric model is most accurate for predicting the burst strength of corroded casing.The burst strength of the casing will be overestimated by more than one-third if the M-E interaction is neglected,so the coupling effect of wear and corrosion should be sufficiently considered in casing integrity evaluation.

Electro-spraying/spinning: A novel battery manufacturing technology

Lithium-ion battery(LIB) industry seems to have met its bottle neck in cutting down producing costs even though much efforts have been put into building a complete industrial chain. Actually, manufacturing methods can greatly affect the cost of battery production. Up to now, lithium ion battery producers still adopt manufacturing methods with cumbersome sub-components preparing processes and costly assembling procedures, which will undoubtedly elevate the producing cost. Herein, we propose a novel approach to directly assemble battery components(cathode, anode and separator) in an integrated way using electro-spraying and electro-spinning technologies. More importantly, this novel battery manufacturing method can produce LIBs in large scale, and the products show excellent mechanical strength, flexibility, thermal stability and electrolyte wettability. Additionally, the performance of the as-prepaed Li Fe PO_(4)||graphite full cell produced by this new method is comparable or even better than that produced by conventional manufacturing approach. In brief, this work provides a new promising technology to prepare LIBs with low cost and better performance.

Intelligent Small Sample Defect Detection of Concrete Surface Using Novel Deep Learning Integrating Improved YOLOv5

Dear Editor,This letter presents an intelligent small sample defect detection of concrete surface using novel deep learning integrating the improved YOLOv5 based on the Wasserstein GAN(WGAN)enhancement algorithm.The proposed method is capable of producing top-notch data sets to address the issues of insufficient samples and substandard quality.

基于SOA的光子脉冲LIF神经元研究

脉冲神经网络与传统人工神经网络相比,具有硬件友好性和低能耗的优点。而光子脉冲神经网络与电脉冲神经网络相比具有速度快、能耗低、传输容量大和抗电磁干扰能力强等优点。基于半导体光放大器(SOA)设计了一种新的光子脉冲神经元模型—LIF(泄漏积分与发射)模型,实现了信号的加权、延迟、积分和阈值判决等功能,并在此基础上探索了该LIF模型在数字逻辑中的应用。实现了基于该模型的“异或”逻辑功能,并改进了一种具有兴奋性和抑制性神经元,通过光通信仿真软件得到LIF模型、“异或”逻辑和具有兴奋性和抑制性神经元良好的输出。

Innovation leading development:a glimpse into three-dimensional bioprinting in Israel

Three-dimensional(3D)printing has attracted increasing research interest as an emerging manufacturing technology for devel-oping sophisticated and exquisite architecture through hierarchical printing.It has also been employed in various advanced industrial areas.The development of intelligent biomedical engineering has raised the requirements for 3D printing,such as flexible manufacturing processes and technologies,biocompatible constituents,and alternative bioproducts.However,state-of-the-art 3D printing mainly involves inorganics or polymers and generally focuses on traditional industrial fields,thus severely limiting applications demanding biocompatibility and biodegradability.In this regard,peptide architectonics,which are self-assembled by programmed amino acid sequences that can be flexibly functionalized,have shown promising potential as bioinspired inks for 3D printing.Therefore,the combination of 3D printing and peptide self-assembly poten-tially opens up an alternative avenue of 3D bioprinting for diverse advanced applications.Israel,a small but innovative nation,has significantly contributed to 3D bioprinting in terms of scientific studies,marketization,and peptide architectonics,including modulations and applications,and ranks as a leading area in the 3D bioprinting field.This review summarizes the recent progress in 3D bioprinting in Israel,focusing on scientific studies on printable components,soft devices,and tissue engineering.This paper further delves into the manufacture of industrial products,such as artificial meats and bioinspired supramolecular architectures,and the mechanisms,physicochemical properties,and applications of peptide self-assembly.Undoubtedly,Israel contributes significantly to the field of 3D bioprinting and should thus be appropriately recognized.

Silicon-based optoelectronic heterogeneous integration for optical interconnection

The performance of optical interconnection has improved dramatically in recent years.Silicon-based optoelectronic heterogeneous integration is the key enabler to achieve high performance optical interconnection,which not only provides the optical gain which is absent from native Si substrates and enables complete photonic functionalities on chip,but also improves the system performance through advanced heterogeneous integrated packaging.This paper reviews recent progress of silicon-based optoelectronic heterogeneous integration in high performance optical interconnection.The research status,development trend and application of ultra-low loss optical waveguides,high-speed detectors,high-speed modulators,lasers and 2D,2.5D,3D and monolithic integration are focused on.

Artificial intelligence-assisted repair of peripheral nerve injury: a new research hotspot and associated challenges

Artificial intelligence can be indirectly applied to the repair of peripheral nerve injury.Specifically,it can be used to analyze and process data regarding peripheral nerve injury and repair,while study findings on peripheral nerve injury and repair can provide valuable data to enrich artificial intelligence algorithms.To investigate advances in the use of artificial intelligence in the diagnosis,rehabilitation,and scientific examination of peripheral nerve injury,we used CiteSpace and VOSviewer software to analyze the relevant literature included in the Web of Science from 1994–2023.We identified the following research hotspots in peripheral nerve injury and repair:(1)diagnosis,classification,and prognostic assessment of peripheral nerve injury using neuroimaging and artificial intelligence techniques,such as corneal confocal microscopy and coherent anti-Stokes Raman spectroscopy;(2)motion control and rehabilitation following peripheral nerve injury using artificial neural networks and machine learning algorithms,such as wearable devices and assisted wheelchair systems;(3)improving the accuracy and effectiveness of peripheral nerve electrical stimulation therapy using artificial intelligence techniques combined with deep learning,such as implantable peripheral nerve interfaces;(4)the application of artificial intelligence technology to brain-machine interfaces for disabled patients and those with reduced mobility,enabling them to control devices such as networked hand prostheses;(5)artificial intelligence robots that can replace doctors in certain procedures during surgery or rehabilitation,thereby reducing surgical risk and complications,and facilitating postoperative recovery.Although artificial intelligence has shown many benefits and potential applications in peripheral nerve injury and repair,there are some limitations to this technology,such as the consequences of missing or imbalanced data,low data accuracy and reproducibility,and ethical issues(e.g.,privacy,data security,research transparency).Future research should address the issue of data collection,as large-scale,high-quality clinical datasets are required to establish effective artificial intelligence models.Multimodal data processing is also necessary,along with interdisciplinary collaboration,medical-industrial integration,and multicenter,large-sample clinical studies.

Microglial autophagy in neurogenesis:a new player in Alzheimer's disease

While extensive studies have illuminated the impact of Alzheimer's disease(AD) on neuronal survival,there is growing evidence that abnormal postnatal neurogenesis in early AD brains contributes to disease progression.Postnatal neurogenesis serves as a mechanism to replace dead or damaged neurons.New neurons generated from neural stem cells(NSCs) in the subgranular zone(SGZ) of the dentate gyrus integrate into the existing hippocampal circuit.

Carbon nanotube integrated circuit technology:purification,assembly and integration

As the manufacturing process of silicon-based integrated circuits(ICs)approaches its physical limit,the quantum effect of silicon-based field-effect transistors(FETs)has become increasingly evident.And the burgeoning carbon-based semiconductor technology has become one of the most disruptive technologies in the post-Moore era.As one-dimensional nanomaterials,carbon nanotubes(CNTs)are far superior to silicon at the same technology nodes of FETs because of their excellent electrical transport and scaling properties,rendering them the most competitive material in the next-generation ICs technology.However,certain challenges impede the industrialization of CNTs,particularly in terms of material preparation,which significantly hinders the development of CNT-based ICs.Focusing on CNT-based ICs technology,this review summarizes its main technical status,development trends,existing challenges,and future development directions.

Optimal synthesis of heat-integrated distillation configurations using the two-column superstructure

In the realm of the synthesis of heat-integrated distillation configurations,the conventional approach for exploring more heat integration possibilities typically entails the splitting of a single column into a twocolumn configuration.However,this approach frequently necessitates tedious enumeration procedures,resulting in a considerable computational burden.To surmount this formidable challenge,the present study introduces an innovative remedy:The proposition of a superstructure that encompasses both single-column and multiple two-column configurations.Additionally,a simultaneous optimization algorithm is applied to optimize both the process parameters and heat integration structures of the twocolumn configurations.The effectiveness of this approach is demonstrated through a case study focusing on industrial organosilicon separation.The results underscore that the superstructure methodology not only substantially mitigates computational time compared to exhaustive enumeration but also furnishes solutions that exhibit comparable performance.