Clinical value of precise rehabilitation nursing in management of cerebral infarction

BACKGROUND Cerebral infarction,previously referred to as cerebral infarction or ischemic stroke,refers to the localized brain tissue experiencing ischemic necrosis or softening due to disorders in brain blood supply,ischemia,and hypoxia.The precision rehabilitation nursing model for chronic disease management is a continuous,fixed,orderly,and efficient nursing model aimed at standardizing the clinical nursing process,reducing the wastage of medical resources,and improving the quality of medical services.AIM To analyze the value of a precise rehabilitation nursing model for chronic disease management in patients with cerebral infarction.METHODS Patients(n=124)admitted to our hospital with cerebral infarction between November 2019 and November 2021 were enrolled as the study subjects.The random number table method was used to divide them into a conventional nursing intervention group(n=61)and a model nursing intervention group(n=63).Changes in the nursing index for the two groups were compared after conventional nursing intervention and precise rehabilitation intervention nursing for chronic disease management.RESULTS Compared with the conventional intervention group,the model intervention group had a shorter time to clinical symptom relief(P<0.05),lower Hamilton Anxiety Scale and Hamilton Depression Scale scores,a lower incidence of total complications(P<0.05),a higher disease knowledge mastery rate,higher safety and quality,and a higher overall nursing satisfaction rate(P<0.05).CONCLUSION The precision rehabilitation nursing model for chronic disease management improves the clinical symptoms of patients with cerebral infarction,reducing the incidence of total complications and improving the clinical outcome of patients,and is worthy of application in clinical practice.

Fish-on-Chips:unveiling neural processing of chemicals in small animals through precise fluidic control

Precise chemical cue presentation alongside advanced brainwide imaging techniques is important to the study of chemosensory processing in animals.Nevertheless,the dynamic nature of chemical-carrying media,such as water or air,poses a significant challenge for delivering highly-controlled chemical flow to an animal subject.Moreover,contact-based cue manipulation and delivery easily shift the position of the animal subject,which is often undesirable for high-quality brain imaging.Additionally,more advanced interfacing tools that align with the diverse range of body part sizes of an animal,ranging from micrometer-scale neurons to meter-long limbs,are much needed.This is particularly crucial when dealing with dimensions that are beyond the reach of conventional experimental tools.

Self-consistent and precise measurement of time-dependent radiative albedo of gold based on specially symmetrical triple-cavity Hohlraum

A self-consistent and precise method to determine the time-dependent radiative albedo,i.e.,the ratio of the reemission flux to the incident flux,for an indirect-drive inertial confinement fusion Hohlraum wall material is proposed.A specially designed symmetrical triple-cavity gold Hohlraum is used to create approximately constant and near-equilibrium uniform radiation with a peak temperature of 160 eV.The incident flux at the secondary cavity waist is obtained from flux balance analysis and from the shock velocity of a standard sample.The results agree well owing to the symmetrical radiation in the secondary cavity.A self-consistent and precise time-dependent radiative albedo is deduced from the reliable reemission flux and the incident flux,and the result from the shock velocity is found to have a smaller uncertainty than that from the multi-angle flux balance analysis,and also to agree well with the result of a simulation using the HYADES opacity.

Caliper-based precise positioning of the target(CALIPPOT)for transcranial magnetic stimulation without neuronavigation system

To the editor:Transcranial magnetic stimulation(TMS)is a non-invasive brain modulation technique.One important usage of TMS is the transient interruption of cognitive brain function(also named virtual lesion)for investigating precisely where and when a specific cortical region contributes to a specific cognitive function.1 A more important usage of TMS is the treatment of brain disorders by repetitive TMS(rTMS).

Methanol steam reforming for hydrogen production driven by an atomically precise Cu catalyst

Plasmon-induced hot-electron transfer from metal nanostructures is being intensely pursed in current photocatalytic research,however it remains elusive whether molecular-like metal clusters with excitonic behavior can be used as light-harvesting materials in solar energy utilization such as photocatalytic methanol steam reforming.In this work,we report an atomically precise Cu_(13)cluster protected by dual ligands of thiolate and phosphine that can be viewed as the assembly of one top Cu atom and three Cu_(4)tetrahedra.The Cu_(13)H_(10)(SR)_(3)(PR’_(3))_(7)(SR=2,4-dichlorobenzenethiol,PR’_(3)=P(4-FC_(6)H_(4))_(3))cluster can give rise to highly efficient light-driven activity for methanol steam reforming toward H_(2)production.

Beidou receiver based on anti-jamming antenna arrays with self-calibration for precise relative positioning

Unmanned aerial vehicles(UAVs)may be subjected to unintentional radio frequency interference(RFI)or hostile jamming attack which will lead to fail to track global navigation satellite system(GNSS)signals.Therefore,the simultaneous realization of anti-jamming and high-precision carrier phase difference positioning becomes a dilemmatic problem.In this paper,a distortionless phase digital beamforming(DBF)algorithm with self-calibration antenna arrays is proposed,which enables to obtain distortionless carrier phase while suppressing jamming.Additionally,architecture of high precision Beidou receiver based on anti-jamming antenna arrays is proposed.Finally,the performance of the algorithm is evaluated,including antenna calibration accuracy,carrier phase distortionless accuracy,and carrier phase measurement accuracy without jamming.Meanwhile,the maximal jamming to signal ratio(JSR)and real time kinematic(RTK)positioning accuracy under wideband jamming are also investigated.The experimental results based on the real-life Beidou signals show that the proposed method has an excellent performance for precise relative positioning under jamming when compared with other anti-jamming methods.

Development and Therapeutic Applications of Precise Gene Editing Technology

The advent of gene editing represents one of the most transformative breakthroughs in life science,making genome manipulation more accessible than ever before.While traditional CRISPR/Cas-based gene editing,which involves double-strand DNA breaks(DSBs),excels at gene disruption,it is less effective for accurate gene modification.The limitation arises because DSBs are primarily repaired via non-homologous end joining(NHEJ),which tends to introduce indels at the break site.While homology directed repair(HDR)can achieve precise editing when a donor DNA template is provided,the reliance on DSBs often results in unintended genome damage.HDR is restricted to specific cell cycle phases,limiting its application.Currently,gene editing has evolved to unprecedented levels of precision without relying on DSB and HDR.The development of innovative systems,such as base editing,prime editing,and CRISPR-associated transposases(CASTs),now allow for precise editing ranging from single nucleotides to large DNA fragments.Base editors(BEs)enable the direct conversion of one nucleotide to another,and prime editors(PEs)further expand gene editing capabilities by allowing for the insertion,deletion,or alteration of small DNA fragments.The CAST system,a recent innovation,allows for the precise insertion of large DNA fragments at specific genomic locations.In recent years,the optimization of these precise gene editing tools has led to significant improvements in editing efficiency,specificity,and versatility,with advancements such as the creation of base editors for nucleotide transversions,enhanced prime editing systems for more efficient and precise modifications,and refined CAST systems for targeted large DNA insertions,expanding the range of applications for these tools.Concurrently,these advances are complemented by significant improvements in in vivo delivery methods,which have paved the way for therapeutic application of precise gene editing tools.Effective delivery systems are critical for the success of gene therapies,and recent developments in both viral and non-viral vectors have improved the efficiency and safety of gene editing.For instance,adeno-associated viruses(AAVs)are widely used due to their high transfection efficiency and low immunogenicity,though challenges such as limited cargo capacity and potential for immune responses remain.Non-viral delivery systems,including lipid nanoparticles(LNPs),offer an alternative with lower immunogenicity and higher payload capacity,although their transfection efficiency can be lower.The therapeutic potential of these precise gene editing technologies is vast,particularly in treating genetic disorders.Preclinical studies have demonstrated the effectiveness of base editing in correcting genetic mutations responsible for diseases such as cardiomyopathy,liver disease,and hereditary hearing loss.These technologies promise to treat symptoms and potentially cure the underlying genetic causes of these conditions.Meanwhile,challenges remain,such as optimizing the safety and specificity of gene editing tools,improving delivery systems,and overcoming off-target effects,all of which are critical for their successful application in clinical settings.In summary,the continuous evolution of precise gene editing technologies,combined with advancements in delivery systems,is driving the field toward new therapeutic applications that can potentially transform the treatment of genetic disorders by targeting their root causes.

Performance Evaluation of Low-Cost Dual-Frequency GNSS Receivers for Precise Positioning in Senegal: Issues and Challenges

The development of this technology has favored the advances noted in recent years in the field of precise positioning. It has also paved the way for a wide range of research into the evaluation of their performance and reliability, their potential use in different fields, the improvement of performance and combined systems, etc. Single-frequency GNSS receivers, which for a long time remained the only category of low-cost GNSS receivers, often limited by their level of accuracy (metric) mainly due to their single-frequency nature, have been joined in the last decade by dual-frequency GNSS receivers developed by certain manufacturers of positioning equipment. These receivers now offer possible alternatives to the relatively expensive conventional (topographic quality) or geodetic receivers and. In this study, the performance of these low-cost dual-frequency receivers was evaluated in static and real-time kinematic GNSS positioning modes. Static positioning was carried out on three points with sessions of 2 h and 4 h over three days with antenna swapping (CHC i50, Leica GS14 and Emlid Reach RS2+). Real-time observations were carried out on eleven (11) points in open, poorly open and not at all open environments, in order to assess not only performance but also receiver sensitivity in environments with a high risk of multipath. The results obtained showed an average agreement of 2 cm in planimetry between the low-cost Emlid RS2+ receiver and the Leica GS14 and CHC i50 receivers. The differences in altimetry are nevertheless greater (sometimes up to decimetres for certain points). Real-time positioning results provided an average convergence of around 1 cm on the E, N and H components with the results from the low-cost Emlid Reach RS2+ and Ublox ZED-F9P receivers and the CHC i50 receiver. Analysis of the results obtained has enabled us to highlight the various issues and challenges associated with this new generation of GNSS receivers, with a view to enhancing their appropriation and optimal integration in the professional and research worlds.

From Control to Empowerment:A Paradigm Shift in the Discourse of Educational Supervision

As educational reforms intensify and societal emphasis shifts towards empowerment,the traditional discourse paradigm of management and control in educational supervision faces growing challenges.This paper explores the transformation of this discourse paradigm through the lens of empowerment,analyzing its distinct characteristics,potential pathways,and effective strategies.This paper begins by reviewing the concept of empowerment and examining the current research landscape surrounding the discourse paradigm in educational supervision.Subsequently,we conduct a comparative analysis of the“control”and“empowerment”paradigms,highlighting their essential differences.This analysis illuminates the key characteristics of an empowerment-oriented approach to educational supervision,particularly its emphasis on dialogue,collaboration,participation,and,crucially,empowerment itself.Ultimately,this research advocates for a shift in educational supervision towards an empowerment-oriented discourse system.This entails a multi-pronged approach:transforming ingrained beliefs,embracing renewed pedagogical concepts,fostering methodological innovation,and optimizing existing mechanisms and strategies within educational supervision.These changes are proposed to facilitate the more effective alignment of educational supervision with the pursuit of high-quality education.

Study on Independent Supervision Function of Design Assurance System

The effective operation of a design assurance system cannot be achieved without the effective performance of the independent supervision function.As one of the core functions of the design assurance system,the purpose of the independent supervision function is to ensure that the system operates within the scope of procedures and manuals.At present,the function of independent supervision is a difficult and confusing issue for various original equipment manufacturers as well as suppliers,and there is an urgent requirement to put forward relevant requirements and form relevant methods.Based on the above mentioned objective,the basic requirements of the independent supervision function of design assurance system were studied,the problems and deficiencies in the organization,staffing,and methods existing in the current independent supervision function were analyzed,the improvement suggestions and measures for the performance of the independent supervision function from the aspects of the organization,staffing,procedures,and suppliers were put forward.The present work and conclusions provide guidance and direction for the effective operation of the design assurance system.

Empowerment of Precise Ideological and Political Education in Higher Education with Educational Digitalization

The study explores how educational digitalization enables the precise development of ideological and political education in colleges and universities.Digital transformation enables colleges and universities to accurately define educational objectives,content strategies,effect evaluation,and process management,and realize the precision and intelligence of ideological and political education.The application of big data technology enhances the data-oriented thinking of teachers and students,promotes the accurate application of data,and improves the efficiency of ideological and political education.The research also prospected a new vision of the digital construction of ideological and political courses and clarified the theoretical and practical path of the implementation and evaluation mode of ideological and political courses under digital empowerment.Education digitalization enables precise ideological and political education,which is a key way to promote the innovative development of ideological and political education in colleges and universities and will strongly support the improvement of the overall quality of higher education and the training of excellent talents.

医科达Precise直线加速器常见故障及维修三例

医科达Precise医用直线加速器为精准治疗设备,为保证放射治疗工作,快速解决故障问题,本研究主要以Precise直线加速器的常见故障类型为对象,运用科学方法结合实际工作经验,分析总结其维修步骤方法,为相关维修工作者提供参考。在分析医用直线加速器的结构和工作原理的基础上,总结我科加速器频繁出现的“Dose Rate Mon”连锁、“Touch Guard”连锁和“Finepot offset Y2”连锁的故障原因,通过科学的方法逐一排查,最终有效地顺利解决故障问题。在充分掌握加速器结构和原理的基础上,通过故障原因分析与故障维修,有效排除故障问题并总结分析,确保机器的正常运转和临床治疗的工作正常开展,为治疗实施的稳定提供有力保障。

Foodborne doping and supervision in sports

Cases of foodborne doping are frequently reported in sports events and can cause severe consequences for athletes.The foodborne doping can be divided into natural endogenous and artifi cially added foods according to the sources,including anabolic agents,stimulants,diuretics,β-blockers,β2 agonists and others.In order to control foodborne doping,chromatographic technique,immunoassay,nuclear magnetic resonance,biosensor technology,pyrolytic spectroscopy,comprehensive analysis and electrochemical analysis have usually used as analytical and inspection strategies.Meanwhile,the legislation of anti-doping,the improvement of testing standard and technology,and the prevention and control of food safety,as well as the improvement of risk perception of athletes are highly necessary for achieving the effective risk control and supervision of foodborne doping,which will be benefi cial for athletes,doctors and administrators to avoid the risks of foodborne doping test and reduce foodborne doping risks for the health of athletes.

Research on the intelligent supervision and operation platform of railway real estate

Railway real estate is the fundamental element of railway transportation production and operation.Effective management and rational utilization of railway real estate is essential for railway asset operation.Based on the investigation of the requirements of railway real estate management and operation,combined with Beidou positioning,GIS(Geographic Information System),multi-source data fusion and other cutting-edge technologies,this paper puts forward the multi-dimensional dynamic statistical method of real estate information,the identification method of railway land occupation and the comprehensive evaluation method of real estate development and utilization potential,and build the railway real estate supervision and operation platform,design the function of the platform,so as to provide intelligent solutions for the railway real estate operation.

医科达Precise直线加速器常见故障及维修分析

医科达Precise直线加速器广泛应用于肿瘤疾病的放射治疗,对肿瘤患者疾病的治疗与后续身体恢复具有重要意义。应注重并对医科大Precise直线加速器的管理,及时发现该设备出现的故障,并采取科学、合理的方式进行维修,保证该设备可以安全、稳定的运行。结合4例常见故障,分析医科达Precise直线加速器的维修方法,为设备维修提供参考。

Routine Supportive Supervision and Management of Medicines and Other Health Products and Technologies in Vihiga County, Kenya

Health Products and Technologies (HPTs) are pivotal for an efficient health system. Availability and accessibility to affordable health products are critical indicators towards achieving universal health coverage. Routine supportive supervision, performance monitoring, recognition of efforts and client feedback are vital activities toward health supply chain system strengthening. This is a descriptive paper that describes a model of integrated commodity supportive supervision, and mentorship and its impact on various outcomes of health commodity management. Data were abstracted from the standardized scored checklists used during integrated commodity supportive supervision and supply chain audit in public health facilities in Vihiga County. Scores for the period 2020 to 2022 were analyzed on the eight key areas of interest. The analysis was done using Statistical Package for Social Sciences (SPSS version 26). Results are interpreted at 95% Confidence interval. This paper also shares findings from both quantitative and qualitative data from client exit and facility managers’ interviews. Six complete rounds of supervisions, three clients and service providers’ interviews, and three annual award events have been conducted. We observed trends across six data collections points and compared the results at first point or baseline (January-June 2020) to the results at the last point or end line (April-June 2022). Findings show significant improvements on the eight parameters in terms of mean scores as follows: resolution of issues from previous visits by 35.06% (46.75% - 81.81%);storage of HPTs by 17.41% (68.72% - 86.13%);inventory management by 28.16% (42.67% - 70.83%);availability and use of commodity data management information systems (MIS) tools by 22.39% (74.40% - 96.79%);verification of commodity data by 25.61% (65.56% - 91.17%);availability of guidelines and job aids for commodity management by 46.28% (36.65% - 82.93%). There was an improvement on the mean score on accountability by 20.22% (58.58% - 83.51%). The composite (final) score improved by 28.33% (56.19% - 84.52%). There was progressive narrowing of the standard deviations on all the indicators across the study period. This demonstrates that there is standardization of practices and positive competition among all the public health facilities. There were significant improvements on all the eight indicators. Routine integrated commodity supportive supervision has proven to be an effective high impact intervention in improving management of health products and technologies in Vihiga County, Kenya.

Efficient Improvement of Nutritional Content in Rice Grains by Precise Base Editing of OsROS1

Aleurone forms the outermost layer of the rice endosperm and plays a critical role in apoplastic nutrient uptake during endosperm development.Thickening the aleurone layer has been proposed to significantly increase the nutrient content of rice grains.In this study,we used a CRISPR/Cas9-mediated precise base editing method to target OsROS1,a gene associated with aleurone thickness,in the background of the japonica glutinous rice cultivar Zhennuo 19。

Model-constrained and data-driven double-supervision acoustic impedance inversion

Seismic impedance inversion is an important technique for structure identification and reservoir prediction.Model-based and data-driven impedance inversion are the commonly used inversion methods.In practice,the geophysical inversion problem is essentially an ill-posedness problem,which means that there are many solutions corresponding to the same seismic data.Therefore,regularization schemes,which can provide stable and unique inversion results to some extent,have been introduced into the objective function as constrain terms.Among them,given a low-frequency initial impedance model is the most commonly used regularization method,which can provide a smooth and stable solution.However,this model-based inversion method relies heavily on the initial model and the inversion result is band limited to the effective frequency bandwidth of seismic data,which cannot effectively improve the seismic vertical resolution and is difficult to be applied to complex structural regions.Therefore,we propose a data-driven approach for high-resolution impedance inversion based on the bidirectional long short-term memory recurrent neural network,which regards seismic data as time-series rather than image-like patches.Compared with the model-based inversion method,the data-driven approach provides higher resolution inversion results,which demonstrates the effectiveness of the data-driven method for recovering the high-frequency components.However,judging from the inversion results for characterization the spatial distribution of thin-layer sands,the accuracy of high-frequency components is difficult to guarantee.Therefore,we add the model constraint to the objective function to overcome the shortages of relying only on the data-driven schemes.First,constructing the supervisor1 based on the bidirectional long short-term memory recurrent neural network,which provides the predicted impedance with higher resolution.Then,convolution constraint as supervisor2 is introduced into the objective function to guarantee the reliability and accuracy of the inversion results,which makes the synthetic seismic data obtained from the inversion result consistent with the input data.Finally,we test the proposed scheme based on the synthetic and field seismic data.Compared to model-based and purely data-driven impedance inversion methods,the proposed approach provides more accurate and reliable inversion results while with higher vertical resolution and better spatial continuity.The inversion results accurately characterize the spatial distribution relationship of thin sands.The model tests demonstrate that the model-constrained and data-driven impedance inversion scheme can effectively improve the thin-layer structure characterization based on the seismic data.Moreover,tests on the oil field data indicate the practicality and adaptability of the proposed method.

Human-pose estimation based on weak supervision

Background In computer vision,simultaneously estimating human pose,shape,and clothing is a practical issue in real life,but remains a challenging task owing to the variety of clothing,complexity of de-formation,shortage of large-scale datasets,and difficulty in estimating clothing style.Methods We propose a multistage weakly supervised method that makes full use of data with less labeled information for learning to estimate human body shape,pose,and clothing deformation.In the first stage,the SMPL human-body model parameters were regressed using the multi-view 2D key points of the human body.Using multi-view information as weakly supervised information can avoid the deep ambiguity problem of a single view,obtain a more accurate human posture,and access supervisory information easily.In the second stage,clothing is represented by a PCA-based model that uses two-dimensional key points of clothing as supervised information to regress the parameters.In the third stage,we predefine an embedding graph for each type of clothing to describe the deformation.Then,the mask information of the clothing is used to further adjust the deformation of the clothing.To facilitate training,we constructed a multi-view synthetic dataset that included BCNet and SURREAL.Results The Experiments show that the accuracy of our method reaches the same level as that of SOTA methods using strong supervision information while only using weakly supervised information.Because this study uses only weakly supervised information,which is much easier to obtain,it has the advantage of utilizing existing data as training data.Experiments on the DeepFashion2 dataset show that our method can make full use of the existing weak supervision information for fine-tuning on a dataset with little supervision information,compared with the strong supervision information that cannot be trained or adjusted owing to the lack of exact annotation information.Conclusions Our weak supervision method can accurately estimate human body size,pose,and several common types of clothing and overcome the issues of the current shortage of clothing data.

RPNet: Rice plant counting after tillering stage based on plant attention and multiple supervision network

Rice is a major food crop and is planted worldwide. Climatic deterioration, population growth, farmland shrinkage, and other factors have necessitated the application of cutting-edge technology to achieve accurate and efficient rice production. In this study, we mainly focus on the precise counting of rice plants in paddy field and design a novel deep learning network, RPNet, consisting of four modules: feature encoder, attention block, initial density map generator, and attention map generator. Additionally, we propose a novel loss function called RPloss. This loss function considers the magnitude relationship between different sub-loss functions and ensures the validity of the designed network. To verify the proposed method, we conducted experiments on our recently presented URC dataset, which is an unmanned aerial vehicle dataset that is quite challenged at counting rice plants. For experimental comparison, we chose some popular or recently proposed counting methods, namely MCNN, CSRNet, SANet, TasselNetV2, and FIDTM. In the experiment, the mean absolute error(MAE), root mean squared error(RMSE), relative MAE(rMAE) and relative RMSE(rRMSE) of the proposed RPNet were 8.3, 11.2, 1.2% and 1.6%, respectively,for the URC dataset. RPNet surpasses state-of-the-art methods in plant counting. To verify the universality of the proposed method, we conducted experiments on the well-know MTC and WED datasets. The final results on these datasets showed that our network achieved the best results compared with excellent previous approaches. The experiments showed that the proposed RPNet can be utilized to count rice plants in paddy fields and replace traditional methods.