^(1)H and ^(13)C NMR spectral assignments for low-concentration bile acids in biological samples

Bile acids are the main body of enterohepatic circulation in vivo.They have essential functions such as emulsifying fat,bacteriostasis and regulating multiple metabolic pathways as signal molecules.However,the assignments of NMR signals for some lowconcentration bile acids are still needed.This study combined 1D nuclear magnetic resonance(NMR)and 2D NMR techniques including 1He1H correlation spectroscopy(COSY),1He1H total correlation spectroscopy(TOCSY),1H J-resolved spectroscopy(J-Res),1He13C heteronuclear single quantum coherence spectroscopy(HSQC),and 1He13C heteronuclear multiple bond correlation spectroscopy(HMBC)to assign the 1H and 13C signals of six bile acids in aqueous solution at physiological pH(~7.4)and nine bile acids in methanol.These data are of importance to the NMR-based studies on lipid digestion,absorption,and metabolism.

~1H and ^(13)C NMR Assignments for Amlodipine and Risperidone

Aim To investigate the NMR spectroscopy of amlodipine and risperidone.Methods 1D NMR and 2D NMR experimental techniques of gCOSY, gHSQC and gHMBC were wsed. Results Theassignments of the ~1H and ^(13) C NMR data for the two drugs were performed and confirmed by theevidence of J_(HF) and J_(CF). Conclusion The structures of amlodipine and risperidone wereconfirmed by careful analysis of regular 1D and 2D NMR spectroscopy.

Design of Cellular Manufacturing Systems Considering Dynamic Production Planning and Worker Assignments

This article presents a comprehensive mathematical model for the design and analysis of Dynamic Cellular Manufacturing Systems （DCMS）. The proposed DCMS model considers several manufacturing attributes such as multi period production planning, dynamic system reconfiguration, duplicate machines, machine capacity, the available time for workers, worker assignments, and machine procurement. The objective is to minimize total costs; consisting of holding cost, outsourcing cost, inter-cell material handling cost, maintenance and overhead cost, machine relocation cost. While a study of published articles in the area of Cellular Manufacturing Systems （CMS） shows that workforce management issues have not sufficiently been addressed in the literature, the model presented also incorporates CMS workforce management issues such as salaries, hiring and firing costs of workers in addition to the manufacturing attributes. In-depth discussions on the results for two numerical examples are presented to illustrate applications of the proposed model. The model developed aims to raise the envelope by expanding and improving several CMS models previously presented in the literature.

Assignments of ~1H and ^(13)C NMR Signals of Mogroside Ⅳa

Aim To investigate the structure of mogroside Ⅳa isolated from traditionalChinese medicine fructus mo-mordicae [fruits of Siraitia grosvenori (Swingle) C. Jeffery] andsummarize the NMR characteristics of the structure. Methods Common extraction, separation andpurification methods were used. Various NMR techniques including ~1H NMR, ^(13)C NMR, DEPT, ~1H-~1HCOSY, HSQC, HMBC, NOESY and molecular model simulated by computer were used to elucidate thestructure. Results ~1H and ^(13)C NMR signals of mogroside Ⅳa were assigned, and spectroscopicbasis was obtained for identification of such type of compounds. Conclusion 1D and 2D NMR techniquesincluding ~1H-~1H COSY, HSQC, HMBC, NOESY spectra are powerful tools for structure analysis. Thestructure determined by NMR methods is identical with energy minimized conformation simulated bycomputer.

Computer Assisted Assignments of Rotationally Resolved Molecular Spectra

A graphically oriented interactive program for assignments of rotationally resolved molecular spectra has been devised. The program functions by grouping spectral lines in term of the second difference principle. and graphing spectral intensity versus frequency in a bar graph of the selected groups, distinguished by color and/or line-type. This allows for easy detection of regular patterns buried in the observed spectrum. Furthermore, it includes a Loomis-Wood view for assisting in spectral assignments. As an example, the program was applied in assigning the molecular spectrum of the production in the discharge of PCl3 buffered by helium gas, which may belong to several species. The results suggest that the program is highly efficient and quite useful in the assignment and the analysis of molecular spectra, especially those of symmetric top, slightly asymmetric top and linear molecules. The accuracy and efficiency of this program will likely ensure its wide application in the processing of molecular spectra.

Chemical shift assignments of two oleanane triterpenes from Euonymus hederaceus

1H-NMR and 13C-NMR assignments of 12-oleanene-3,11-dione (compound 1) were completely described for the first time through conventional 1D NMR and 2D shift-correlated NMR experiments using 1H-1HCOSY, HMQC, HMBC techniques. Based on its NMR data, the assignments of 28-hydroxyolean-12-ene-3,11-dione (compound 2) were partially revised.

Configuration and Spin Assignments of Yrast Band for Doubly Odd Nucleus ^(122)Cs

Energy spectrum of yrast band for ^(122)Cs is studied by using particle-rotor model(PRM)of odd-odd nuclei,in which special attention is paid to the model basis accounting for the effect of the instabilityγvibration perturbation around axial symmetry.In order to check the assignments of this band,two calculation schemes are put into practice.The first one is for previousπh11/2 vg7/2 configuration with bandhead spin I_(0)=(6^(-))which was obtained from cranked shell model(CSM)calculation,and the other one is forπh_(11/2) vh_(11/2) configuration with I_(0)=(9^(+))supported by the systematic analyses of experimental data.A qualitative comparison between the present PRM calculation and that of CSM has also been made.The results indicate that,rather thanπh_(11/2) vg_(7/2) I_(0)=(6^(-)),πh_(11/2) vh_(11/2) with I_(0)=(9^(+))is a more reasonable assignment to the yrast band in ^(122)Cs.

Graphs with <i>k</i>-Role Assignments

For a given graph G, a k-role assignment of G is a surjective function ?such that , where N(x) and N(y) are the neighborhoods of x and y, respectively. Furthermore, as we limit the number of different roles in the neighborhood of an individual, we call r a restricted size k-role assignment. When the hausdorff distance between the sets of roles assigned to their neighbors is at most 1, we call r a k-threshold close role assignment. In this paper we study the graphs that have k-role assignments, restricted size k-role assignments and k-threshold close role assignments, respectively. By the end we discuss the maximal and minimal graphs which have k-role assignments.

Automatic bug assignments without texts: a study

1 Introduction Automatic bug assignment has been well-studied in the past decade.As textual bug reports usually describe the buggy phenomena and potential causes,engineers highly depend on these reports to fix bugs.Therefore,researchers spend much effort on processing bug reports,aiming for obtaining key information and/or clues for reproducing bugs,analyzing their root causes,assigning them to developers/maintainers,and fixing these bugs.However,our previous research[1]reveals that noises in texts bring adverse impacts to automatic bug assignments unexpectedly,mainly due to insufficiency of classical Natural Language Processing(NLP)techniques.

Strategies for Designing Online Course Assignments: Based on “XuetangX” Course Samples

Assignments are an important tool to evaluate learners’learning effectiveness in online courses.Clarifying assignment design strategies is of great significance for promoting the quality construction of online education courses.This paper uses Bloom’s taxonomy framework revised by Anderson and Krathwohl(2001)as a reference to label the knowledge types and cognitive dimensions in the assignment context of eight courses.Combined with a literature review,a discipline–objective–schedule(DOS)three-dimensional analysis framework based on the achievement of curriculum objectives,the design of chapter schedule,and the heterogeneity of disciplines is constructed to conduct an in-depth analysis of online course assignment design strategies.The research findings show that the online course assignment design strategy has an obvious curriculum objective orientation,follows the gradual learning rule,and presents typical disciplinary differences.The study finds that the current assignment design of online courses has three issues:first,a mismatch between assignment design and curriculum objectives;second,a lack of diversity in assignment formats;and third,insufficient comprehensiveness of some subject assignments.Based on the above discussions,corresponding suggestions are provided.

Channel assignment and power allocation for throughput improvement with PPO in B5G heterogeneous edge networks

In Beyond the Fifth Generation(B5G)heterogeneous edge networks,numerous users are multiplexed on a channel or served on the same frequency resource block,in which case the transmitter applies coding and the receiver uses interference cancellation.Unfortunately,uncoordinated radio resource allocation can reduce system throughput and lead to user inequity,for this reason,in this paper,channel allocation and power allocation problems are formulated to maximize the system sum rate and minimum user achievable rate.Since the construction model is non-convex and the response variables are high-dimensional,a distributed Deep Reinforcement Learning(DRL)framework called distributed Proximal Policy Optimization(PPO)is proposed to allocate or assign resources.Specifically,several simulated agents are trained in a heterogeneous environment to find robust behaviors that perform well in channel assignment and power allocation.Moreover,agents in the collection stage slow down,which hinders the learning of other agents.Therefore,a preemption strategy is further proposed in this paper to optimize the distributed PPO,form DP-PPO and successfully mitigate the straggler problem.The experimental results show that our mechanism named DP-PPO improves the performance over other DRL methods.

Development of SNP parentage assignment techniques in the yellowfin seabream Acanthopagrus latus

Acanthopagrus latus is an essential aquaculture species on the south coast of China.However,there is a lack of systematic breeding of A.latus,which considerably limits the sustainable development of A.latus.As a result,genetic improvements are urgently needed to breed new strains of A.latus with rapid growth and strong resistance to disease.During selective breeding,it is necessary to estimate the genetic parameters of the target trait,which in turn depends on an accurate disentangled pedigree for the selective population.Therefore,it is necessary to establish the parentage assignment technique for A.latus.In this study,95 individuals selected from their parents and their 14 families were used as experimental material.SNPs were developed by genome resequencing,and highly polymorphic SNPs were screened on the basis of optimized filtering parameters.A total of 14392738 SNPs were discovered and 205 SNPs were selected for parentage assignment using the CERVUS software.In the model where the gender of the parents is known,the assignment success rate is 98.61%for the male parent,97.22%for the female parent,and 95.83%for the parent pair.In the model where the gender of the parents is unknown,the assignment success rate is 100%for a single parent and 90.28%for the parent pair.The results of this study were expected to serve as a reference for the breeding of new varieties of A.latus.

A self-organization formation configuration based assignment probability and collision detection

The formation control of multiple unmanned aerial vehicles(multi-UAVs)has always been a research hotspot.Based on the straight line trajectory,a multi-UAVs target point assignment algorithm based on the assignment probability is proposed to achieve the shortest overall formation path of multi-UAVs with low complexity and reduce the energy consumption.In order to avoid the collision between UAVs in the formation process,the concept of safety ball is introduced,and the collision detection based on continuous motion of two time slots and the lane occupation detection after motion is proposed to avoid collision between UAVs.Based on the idea of game theory,a method of UAV motion form setting based on the maximization of interests is proposed,including the maximization of self-interest and the maximization of formation interest is proposed,so that multi-UAVs can complete the formation task quickly and reasonably with the linear trajectory assigned in advance.Finally,through simulation verification,the multi-UAVs target assignment algorithm based on the assignment probability proposed in this paper can effectively reduce the total path length,and the UAV motion selection method based on the maximization interests can effectively complete the task formation.

Multi-UAV Collaborative Mission Planning Method for Self-Organized Sensor Data Acquisition

In recent years,sensor technology has been widely used in the defense and control of sensitive areas in cities,or in various scenarios such as early warning of forest fires,monitoring of forest pests and diseases,and protection of endangered animals.Deploying sensors to collect data and then utilizing unmanned aerial vehicle(UAV)to collect the data stored in the sensors has replaced traditional manual data collection as the dominant method.The current strategies for efficient data collection in above scenarios are still imperfect,and the low quality of the collected data and the excessive energy consumed by UAV flights are still the main problems faced in data collection.With regards this,this paper proposes a multi-UAV mission planning method for self-organized sensor data acquisition by comprehensively utilizing the techniques of self-organized sensor clustering,multi-UAV mission area allocation,and sub-area data acquisition scheme optimization.The improvedα-hop clustering method utilizes the average transmission distance to reduce the size of the collection sensors,and the K-Dimensional method is used to form a multi-UAV cooperative workspace,and then,the genetic algorithm is used to trade-off the speed with the age of information(AoI)of the collected information and the energy consumption to form the multi-UAV data collection operation scheme.The combined optimization scheme in paper improves the performance by 95.56%and 58.21%,respectively,compared to the traditional baseline model.In order to verify the excellent generalization and applicability of the proposed method in real scenarios,the simulation test is conducted by introducing the digital elevation model data of the real terrain,and the results show that the relative error values of the proposed method and the performance test of the actual flight of the UAV are within the error interval of±10%.Then,the advantages and disadvantages of the present method with the existing mainstream schemes are tested,and the results show that the present method has a huge advantage in terms of space and time complexity,and at the same time,the accuracy for data extraction is relatively improved by 10.46%and 12.71%.Finally,by eliminating the clustering process and the subtask assignment process,the AoI performance decreases by 3.46×and 4.45×,and the energy performance decreases by 3.52×and 4.47×.This paper presents a comprehensive and detailed proactive optimization of the existing challenges faced in the field of data acquisition by means of a series of combinatorial optimizations.

Reinforcement Learning Based Quantization Strategy Optimal Assignment Algorithm for Mixed Precision

The quantization algorithm compresses the original network by reducing the numerical bit width of the model,which improves the computation speed. Because different layers have different redundancy and sensitivity to databit width. Reducing the data bit width will result in a loss of accuracy. Therefore, it is difficult to determinethe optimal bit width for different parts of the network with guaranteed accuracy. Mixed precision quantizationcan effectively reduce the amount of computation while keeping the model accuracy basically unchanged. In thispaper, a hardware-aware mixed precision quantization strategy optimal assignment algorithm adapted to low bitwidth is proposed, and reinforcement learning is used to automatically predict the mixed precision that meets theconstraints of hardware resources. In the state-space design, the standard deviation of weights is used to measurethe distribution difference of data, the execution speed feedback of simulated neural network accelerator inferenceis used as the environment to limit the action space of the agent, and the accuracy of the quantization model afterretraining is used as the reward function to guide the agent to carry out deep reinforcement learning training. Theexperimental results show that the proposed method obtains a suitable model layer-by-layer quantization strategyunder the condition that the computational resources are satisfied, and themodel accuracy is effectively improved.The proposed method has strong intelligence and certain universality and has strong application potential in thefield of mixed precision quantization and embedded neural network model deployment.

Structural Characteristics and Influencing Factors of Carbon Emission Spatial Association Network:A Case Study of Yangtze River Delta City Cluster,China

City cluster is an effective platform for encouraging regionally coordinated development.Coordinated reduction of carbon emissions within city cluster via the spatial association network between cities can help coordinate the regional carbon emission management,realize sustainable development,and assist China in achieving the carbon peaking and carbon neutrality goals.This paper applies the improved gravity model and social network analysis(SNA)to the study of spatial correlation of carbon emissions in city clusters and analyzes the structural characteristics of the spatial correlation network of carbon emissions in the Yangtze River Delta(YRD)city cluster in China and its influencing factors.The results demonstrate that:1)the spatial association of carbon emissions in the YRD city cluster exhibits a typical and complex multi-threaded network structure.The network association number and density show an upward trend,indicating closer spatial association between cities,but their values remain generally low.Meanwhile,the network hierarchy and network efficiency show a downward trend but remain high.2)The spatial association network of carbon emissions in the YRD city cluster shows an obvious‘core-edge’distribution pattern.The network is centered around Shanghai,Suzhou and Wuxi,all of which play the role of‘bridges’,while cities such as Zhoushan,Ma'anshan,Tongling and other cities characterized by the remote location,single transportation mode or lower economic level are positioned at the edge of the network.3)Geographic proximity,varying levels of economic development,different industrial structures,degrees of urbanization,levels of technological innovation,energy intensities and environmental regulation are important influencing factors on the spatial association of within the YRD city cluster.Finally,policy implications are provided from four aspects:government macro-control and market mechanism guidance,structural characteristics of the‘core-edge’network,reconfiguration and optimization of the spatial layout of the YRD city cluster,and the application of advanced technologies.

不变性原则与Python亮点

针对目前Python教学中“以C语言知识解释Python语法”的倾向及其所导致的一些基本概念错误,回顾“软件危机”发生以来人们在“去变量赋值”副作用和函数式编程两个方面的努力,从不变性原则的高度阐述这些举措对于提高程序质量的意义,在此基础上提出Python程序设计语言的亮点并强调对于回归Python本质的重要性,目的是为进一步学习和应用打下坚实基础。

Test Generation with Unspecified Variable Assignments

ATPG for very large scale integrated circuit designs is an important problem in industry. With the advent of SOC designs, testing and verification of the core-based designs become a challenging problem. This paper presents an algebraic test generation algorithm with unspecified variable assignments. Given a stuck at fault of the circuit with unspecified signals, the proposed algorithm uses a new encoding scheme for unspecified variable assignments, and solves the Boolean satisfiability formula representing the Boolean difference to obtain a test pattern. Experimental results demonstrate the efficiency and feasibility of the proposed algorithm.

A New Approach to Pointer Analysis for Assignments

Pointer analysis is a technique to identify at compile-time the potential values of the pointer expressions in a program, which promises significant benefits for optimizing and parallelizing compilers. In this paper, a new approach to pointer analysis for assignments is presented. In this approach, assignments are classified into three categories: pointer assignments, structure (union) assignments and normal assignments which don't affect the point-to information. Pointer analyses for these three kinds of assignments respectively make up the integrated algorithm. When analyzing a pointer assignment, a new method called expression expansion is used to calculate both the left targets and the right targets. The integration of recursive data structure analysis into pointer analysis is a significant originality of this paper, which uniforms the pointer analysis for heap variables and the pointer analysis for stack variables. This algorithm is implemented in Agassiz, an analyzing tool for C programs developed by institute of Parallel Processing, Fudan University. Its accuracy and effectiveness are illustrated by experimental data.

Absolute Configurational Assignments of Amino Acid Esters by a CD-Sensitive Malonamide-Linked Zinc Bisporphyrinate Host

A novel malonamide-linked zinc bisporphyrinate[Zn_(2)-1]has been designed and synthesized.UV-vis and NMR spectroscopic studies suggest the molecule aggregates in solution.Such zinc bisporphyrinate is very CD-sensitive when it is mixed with amino acid ethyl esters.The amplitude value of the induced circular dichroism(ICD)is up to ca.1500 L•mol^(−1)•cm^(−1).Further studies by ^(1)H NMR and UV-vis spectroscopies reveal amino acid esters function as monodentate ligands,and[Zn_(2)-1]interacts with amino acid ethyl esters through coordination and hydrogen bonding interactions.