Primary investigation of dose-effect relationship of ^(153)Sm-EDTMP in treating multiple bone metastases

Objective:To calculate the focus absorption dose of 153Sm-EDTMP with the Monte Carlo(MC)EGS4 method for treatment of bone metastases from nasopharyngeal carcinoma or breast cancer,and investigate the relationship between the focus absorption dose and painkilling effect of 153Sm-EDTMP.Methods:Four patients with multiple bone metastases from nasopharyngeal or breast carcinoma and suffered from grade IV bone pain were treated with radionuclide internal irradiation of 153Sm-EDTMP.The absorption dose and dose distribution of bone metastases and other targeted organs were calculated with MC EGS4 program based on the time-order SPECT/CT scanning and the measurement of the radioactivity in the urine accumulation.The release of bone pain and the improvement of life quality were observed.Results:Bone pain of the patients was significantly alleviated to grade II for 3–4 weeks after internal 153Sm-EDTMP irradiation.The 3-dimensional absorption dose distribution image of bone metastases and targeted organs showed that the dose distribution in bone metastases was not asymmetrical.After injection of 0.65×37 MBq/kg 153Sm-EDTMP,the highest absorption dose in bone lesions was about 4.9–5.9 Gy,and the dose in the lesion margin was about 2.0 Gy.Using the highest dose as reference dose point,the relative absorption dose values of bone marrow,vertebra and sex organ near lesions were 0.48–1.1 Gy,0.51–0.85 Gy,and 0.01–0.14 Gy,respectively.Conclusion:The absorption dose of bone metastases is significantly lower than treatment dose of 30 Gy after single irradiation of 153Sm-EDTMP.The painkilling effect is limited and in accordance with clinical observation.

Survey of dose-effect relationship in Chinese materia medica

The research on the dose-effect relationship in Chinese materia medica is delayed due to the complexity of its composition, multi-efficacy, multi-targeting and other factors. Many experts put forward relevant research ideas and methods and worked out more and more research results in literature, experimental and clinical categories because of the progress of statistical methods and scientific and technological means in recent years. In this paper, these results were preliminarily combed to show the basic situation of dose-effect relationship research in Chinese materia medica.

Progress in the Research of Radix Astragali in Treating Chronic Heart Failure:Effective Ingredients,Dose-Effect Relationship and Adverse Reaction

Radix Astragali,a Chinese herbal medicine possessing important cardiovascular pharmacologic effects,is widely applied for the treatment of chronic heart failure（CHF） in clinical practice.This paper summarizes briefly the researches in the last 10 years on its chemical compositions,effective ingredients for improving cardiac function,dose-effect relationship in treating CHF,and adverse reactions that occurred in clinical practice.

Clinical Observations on the Dose-effect Relationship of Gegen Qin Lian Decoction (葛根芩连汤) on 54 Out-patients with Type 2 Diabetes

Objective: To observe the therapeutic effect of different dosages of Gegen Qin Lian Decoction (葛根芩连汤) on type 2 diabetic patients. Methods: Fifty-four type 2 diabetic patients from low dosage group (20 cases), medium dosage group (19 cases) and high dosage group (15 cases) were treated with different dosage of Gegen Qin Lian Decoction for 12 weeks. Fasting blood-glucose (FBG), postprandial blood sugar (PBG) and Hemoglobin A1c (HbAlc) were determined before and after treatment. Results: With the increase of dosage, the overall effective rate of glycaemic control increased, and FBG, PBG, HbAlc decreased. The overall effective rate of blood glucose control of high dosage, medium dosage and low dosage group were 80%, 47%, 30% respectively, and there were significant differences between high dosage group and low dosage group. The decrease of FBG, PBG and HbAlc of high dosage showed significant differences from low dosage too. These data was analyzed by trend χ2 test and covariance analysis. Conclusion: The result indicated that different dosage of Gegen Qin Lian Decoction has dose-effect relationship in reducing HbAlc and FBG.

Research ideas and strategies on the dose-effect relationship of traditional Chinese medicine prescriptions and herbs

We discuss here the complexity of the doses of traditional Chinese medicine(TCM) prescriptions and herbs from different viewpoints,including the heterogeneity of drug quality,the flexibility of prescriptions,and the diversity of drug effects.Then,the corresponding research ideas and strategies are proposed.We can reveal the actual situation of clinical doses based on in-depth "real-world study" of the safety and effectiveness of TCM prescriptions,create an analytical method for dose-effect relationships in accordance with the features of TCM,and reveal the correlated regular nature of the effectiveness and dosage of TCM prescriptions and herbs.

Tunable dispersion relations manipulated by strain in skyrmion-based magnonic crystals

We theoretically investigate the propagation characteristics of spin waves in skyrmion-based magnonic crystals. It is found that the dispersion relation can be manipulated by strains through magneto-elastic coupling. Especially, the allowed bands and forbidden bands in dispersion relations shift to higher frequency with strain changing from compressive to tensile,while shifting to lower frequency with strain changing from tensile to compressive. We also confirm that the spin wave with specific frequency can pass the magnonic crystal or be blocked by tuning the strains. The result provides an advanced platform for studying the tunable skyrmion-based spin wave devices.

Understanding the Relationship Between Shrinking Cities and Land Prices:Spatial Pattern,Effectiveness,and Policy Implications

Urban shrinkage has emerged as a widespread phenomenon globally and has a significant impact on land,particularly in terms of land use and price.This study focuses on 2851 county-level cities in China in 2005–2018(excluding Hong Kong,Macao,Taiwan,and‘no data’areas in Qinhai-Tibet Plateau)as the fundamental units of analysis.By employing nighttime light(NTL)data to identify shrinking cities,the propensity score matching(PSM)model was used to quantitatively examine the impact of shrinking cities on land prices,and evaluate the magnitude of this influence.The findings demonstrate the following:1)there were 613 shrinking cities in China,with moderate shrinkage being the most prevalent and severe shrinkage being the least.2)Regional disparities are evident in the spatial distribution of shrinking cities,especially in areas with diverse terrain.3)The spatial pattern of land price exhibits a significant correlated to the economic and administrative levels.4)Shrinking cities significantly negatively impact on the overall land price(ATT=–0.1241,P<0.05).However,the extent of the effect varies significantly among different spatial regions.This study contributes novel insights into the investigation of land prices and shrinking cities,ultimately serving as a foundation for government efforts to promote the sustainable development of urban areas.

Attention-relation network for mobile phone screen defect classification via a few samples

How to use a few defect samples to complete the defect classification is a key challenge in the production of mobile phone screens.An attention-relation network for the mobile phone screen defect classification is proposed in this paper.The architecture of the attention-relation network contains two modules:a feature extract module and a feature metric module.Different from other few-shot models,an attention mechanism is applied to metric learning in our model to measure the distance between features,so as to pay attention to the correlation between features and suppress unwanted information.Besides,we combine dilated convolution and skip connection to extract more feature information for follow-up processing.We validate attention-relation network on the mobile phone screen defect dataset.The experimental results show that the classification accuracy of the attentionrelation network is 0.9486 under the 5-way 1-shot training strategy and 0.9039 under the 5-way 5-shot setting.It achieves the excellent effect of classification for mobile phone screen defects and outperforms with dominant advantages.

A Joint Entity Relation Extraction Model Based on Relation Semantic Template Automatically Constructed

The joint entity relation extraction model which integrates the semantic information of relation is favored by relevant researchers because of its effectiveness in solving the overlapping of entities,and the method of defining the semantic template of relation manually is particularly prominent in the extraction effect because it can obtain the deep semantic information of relation.However,this method has some problems,such as relying on expert experience and poor portability.Inspired by the rule-based entity relation extraction method,this paper proposes a joint entity relation extraction model based on a relation semantic template automatically constructed,which is abbreviated as RSTAC.This model refines the extraction rules of relation semantic templates from relation corpus through dependency parsing and realizes the automatic construction of relation semantic templates.Based on the relation semantic template,the process of relation classification and triplet extraction is constrained,and finally,the entity relation triplet is obtained.The experimental results on the three major Chinese datasets of DuIE,SanWen,and FinRE showthat the RSTAC model successfully obtains rich deep semantics of relation,improves the extraction effect of entity relation triples,and the F1 scores are increased by an average of 0.96% compared with classical joint extraction models such as CasRel,TPLinker,and RFBFN.

Generating Sets of the Complete Semigroup of Binary Relations Defined by Semilattices of the Class Σ8(X, 5)

In this article, we study generating sets of the complete semigroups of binary relations defined by X-semilattices of unions of the class Σ8(X, 5). Found uniquely irreducible generating set for the given semigroups and when X is finite set formulas for calculating the number of elements in generating sets are derived.

Precise Determination of the Bottom-Quark On-Shell Mass Using Its Four-Loop Relation to the MS-Scheme Running Mass

We explore the properties of the bottom-quark on-shell mass(M_(b))by using its relation to the MS mass(m_(b)).At present,this MS-on-shell relation has been known up to four-loop QCD corrections,which however still has a~2%scale uncertainty by taking the renormalization scale as m_(b)(m_(b))and varying it within the usual range of [m_(b)(m_(b))/2,2m_(b)(m_(b))].

Dispersion Relations in Diffraction in Time

In agreement with Titchmarsh’s theorem, we prove that dispersion relations are just the Fourier-transform of the identity, g(x′)=±Sgn(x′)g(x′), which defines the property of being a truncated functions at the origin. On the other hand, we prove that the wave-function of a generalized diffraction in time problem is just the Fourier-transform of a truncated function. Consequently, the existence of dispersion relations for the diffraction in time wave-function follows. We derive these explicit dispersion relations.

The Impact of Adolescent and Young Adult Cancer-AJA-on Family Functioning.Study of Family Relationships in Terms of Adaptability and Cohesion

Objectives:The arrival of cancer in adolescents and young adults(aged 15 to 24 years)-Adolescents and young adults(AJA)-corresponds to a fragile period during which the adulthood of the young person and the evolution of family ties mobilize the family as a whole.Therefore,cancer,beyond its individual traumatic dimension,affects the whole family,which can modify family ties and family functioning.Our objective is to evaluate family functioning from the complex model evaluating cohesion and adaptability when an adolescent or young adult has cancer.Methods:Adolescents and young adults with cancer(n=41),mothers(n=41),and fathers(n=13)participated in this study.They completed the Family Adaptation and Cohesion Scales(FACES Ⅲ)questionnaire.Family functioning when an aya is ill has been compared to that of families without any disease.Results:a comparison of the mean scores of perceived cohesion and adaptability of face Ⅲ indicates no significant difference for cohesion.In contrast,the averages of the adaptability scores of our sample with those of the general population indicate that families with cancer hais generally feel more“adaptable”than the non-clinical population.These results are statistically significant for AJA,but also for mothers and fathers.Regarding the mean scores of ideal cohesion and ideal adaptability,there are no significant differences between fathers in our sample and fathers in the general population.In contrast,mothers in our sample had less ideal adaptability than those in the general population.In aya patients with cancer,the scores of both adaptability and cohesion were significantly different from those of non-diseased adolescents.Conclusion:Cancer leads to many changes in family relationships,making it difficult to empower the young patient and latent the evolution of the relationship.

Case Retrieval Strategy of Turning Process Based on Grey Relational Analysis

To solve the problem of long response time when users obtain suitable cutting parameters through the Internet based platform,a case-based reasoning framework is proposed.Specifically,a Hamming distance and Euclidean distance combined method is designed to measure the similarity of case features which have both numeric and category properties.In addition,AHP(Analytic Hierarchy Process)and entropy weight method are integrated to provide features weight,where both user preferences and comprehensive impact of the index have been concerned.Grey relation analysis is used to obtain the similarity of a new problem and alternative cases.Finally,a platform is also developed on Visual Studio 2015,and a case study is demonstrated to verify the practicality and efficiency of the proposed method.This method can obtain cutting parameters which is suitable without iterative calculation.Compared with the traditional PSO(Particle swarm optimization algorithm)and GA(Genetic algorithm),it can obtain faster response speed.This method can provide ideas for selecting processing parameters in industrial production.While guaranteeing the characteristic information is similar,this approach can select processing parameters which is the most appropriate for the production process and a lot of time can be saved.

Enhancing Data Forwarding Efficiency in SIoT with Multidimensional Social Relations

Effective data communication is a crucial aspect of the Social Internet of Things(SIoT)and continues to be a significant research focus.This paper proposes a data forwarding algorithm based on Multidimensional Social Relations(MSRR)in SIoT to solve this problem.The proposed algorithm separates message forwarding into intra-and cross-community forwarding by analyzing interest traits and social connections among nodes.Three new metrics are defined:the intensity of node social relationships,node activity,and community connectivity.Within the community,messages are sent by determining which node is most similar to the sender by weighing the strength of social connections and node activity.When a node performs cross-community forwarding,the message is forwarded to the most reasonable relay community by measuring the node activity and the connection between communities.The proposed algorithm was compared to three existing routing algorithms in simulation experiments.Results indicate that the proposed algorithmsubstantially improves message delivery efficiency while lessening network overhead and enhancing connectivity and coordination in the SIoT context.

Defining the We-map Reference Frames and Providing Mathematical Expressions for Transformation Relations

We-map is an interactive mobile map that can be easily communicated and applied on personal electronic devices,such as personal computers and mobile phones.Therefore,the study of direction systems and coordinate systems is critical,and exploring reference frames is essential in direction and coordinate systems.Despite its significance,existing research on We-map lacks specific solutions for the exploration of reference frames is indispensable for the establishment of accurate direction and coordinate systems.In this paper,we endeavor to address this gap by elucidating the significance of We-map reference frames,defining them with mathematical constraints,summarizing their nature and characteristics,deriving their transformation relationships and representing them through mathematical formulars and equations.Our work contributes to the fundamental theory of We-map and provides valuable systems and support for the mathematical foundation of We-map,map production,and platform development.Ultimately,this research serves to advance the development of We-map.

Multi-party semi-quantum private comparison protocol of size relation based on two-dimensional Bell states

Currently,all quantum private comparison protocols based on two-dimensional quantum states can only compare equality,via using high-dimensional quantum states that it is possible to compare the size relation in existing work.In addition,it is difficult to manipulate high-dimensional quantum states under the existing conditions of quantum information processing,leading to low practicality and engineering feasibility of protocols for comparing size relation.Considering this situation,we propose an innovative protocol.The proposed protocol can make size comparison by exploiting more manageable two-dimensional Bell states,which significantly enhances its feasibility with current quantum technologies.Simultaneously,the proposed protocol enables multiple participants to compare their privacies with the semi-quantum model.The communication process of the protocol is simulated on the IBM Quantum Experience platform to verify its effectiveness.Security analysis shows that the proposed protocol can withstand common attacks while preserving the privacies of all participants.Thus,the devised protocol may provide an important reference for implementation of quantum private size comparison protocols.

Dose-effect correlation of chloride de-icing salt on Euonymus japonicus

In order to prevent severe pollution by de-icing salt on greenery along urban roads, a half lethal dose （LD_50）for a plant population was confirmed through stress simulation of chloride de-icing salt on Euonymus japonicus, with an ianalysis of physiological changes, statistics on mortality rate on plant populations and mathematic modeling during a 30- day subacute toxicity test. The results indicate that a significant positive correlation in the early stages and a significant negative correlation in the later stages were observed between the amount of chlorophyll a and b in plants and a cumulative dose of de-icing salt. The amounts of free proline in plants and the dose of de-icing salt were positively correlated Over the entire period. No significant correlation in the initial stage, but a significant negative correlation in later stages was observed between the soluble protein and the dose of de-icing salt. LDs0 of this chloride agent on E. japonicus is 5 kg.（L·m2）-1 over 30 days.

Relational Turkish Text Classification Using Distant Supervised Entities and Relations

Text classification,by automatically categorizing texts,is one of the foundational elements of natural language processing applications.This study investigates how text classification performance can be improved through the integration of entity-relation information obtained from the Wikidata(Wikipedia database)database and BERTbased pre-trained Named Entity Recognition(NER)models.Focusing on a significant challenge in the field of natural language processing(NLP),the research evaluates the potential of using entity and relational information to extract deeper meaning from texts.The adopted methodology encompasses a comprehensive approach that includes text preprocessing,entity detection,and the integration of relational information.Experiments conducted on text datasets in both Turkish and English assess the performance of various classification algorithms,such as Support Vector Machine,Logistic Regression,Deep Neural Network,and Convolutional Neural Network.The results indicate that the integration of entity-relation information can significantly enhance algorithmperformance in text classification tasks and offer new perspectives for information extraction and semantic analysis in NLP applications.Contributions of this work include the utilization of distant supervised entity-relation information in Turkish text classification,the development of a Turkish relational text classification approach,and the creation of a relational database.By demonstrating potential performance improvements through the integration of distant supervised entity-relation information into Turkish text classification,this research aims to support the effectiveness of text-based artificial intelligence(AI)tools.Additionally,it makes significant contributions to the development ofmultilingual text classification systems by adding deeper meaning to text content,thereby providing a valuable addition to current NLP studies and setting an important reference point for future research.

A Graph with Adaptive AdjacencyMatrix for Relation Extraction

The relation is a semantic expression relevant to two named entities in a sentence.Since a sentence usually contains several named entities,it is essential to learn a structured sentence representation that encodes dependency information specific to the two named entities.In related work,graph convolutional neural networks are widely adopted to learn semantic dependencies,where a dependency tree initializes the adjacency matrix.However,this approach has two main issues.First,parsing a sentence heavily relies on external toolkits,which can be errorprone.Second,the dependency tree only encodes the syntactical structure of a sentence,which may not align with the relational semantic expression.In this paper,we propose an automatic graph learningmethod to autonomously learn a sentence’s structural information.Instead of using a fixed adjacency matrix initialized by a dependency tree,we introduce an Adaptive Adjacency Matrix to encode the semantic dependency between tokens.The elements of thismatrix are dynamically learned during the training process and optimized by task-relevant learning objectives,enabling the construction of task-relevant semantic dependencies within a sentence.Our model demonstrates superior performance on the TACRED and SemEval 2010 datasets,surpassing previous works by 1.3%and 0.8%,respectively.These experimental results show that our model excels in the relation extraction task,outperforming prior models.