scholarly journals Improvement and Application of Key Pasture Theory for the Evaluation of Forage–Livestock Balance in the Seasonal Grazing Regions of China’s Alpine Desert Grasslands

2020 ◽  
Vol 12 (17) ◽  
pp. 6794
Author(s):  
Hui Liu ◽  
Xiaoyu Song ◽  
Lin Qin ◽  
Wang Wen ◽  
Xiaodi Liu ◽  
...  
Keyword(s):  
Research Area ◽  
Traditional Theory ◽  
Cool Season ◽  
Practical Applications ◽  
Natural Processes ◽  
Dynamic Factors ◽  
Grassland Productivity ◽  
Dynamic Key ◽  
Seasonal Grazing ◽  
Dynamic Cycle

The calculation of theoretical carrying capacity (TCC) is one of the most fundamental tasks for the evaluation of the forage–livestock balance on grassland pastures. At present, the main methods for calculating TCC are the traditional theory (TT) and key pasture theory (KPT), but they both have obvious limitations in practical applications for the seasonal grazing regions in the alpine desert grasslands of China. In this study, the pastures in Wulan County (PWC) were selected as the research area. The unique features of the research area as well as the faulty applications of TT and KPT were fully analyzed, and then a new method named dynamic key pasture theory (DKPT) was established for calculating TCC by improving KPT with the introduction of the two dynamic factors of the livestock slaughter rate (α) and coefficient of grassland productivity (β). TT, KPT and DKPT were respectively used to calculate the TCC of the PWC under different precipitation scenarios. The forage–livestock balance in the PWC determined using DKPT was assessed by the forage–livestock balance index (FLBI). The results showed that the natural processes of grassland supply and livestock demand were significantly imbalanced in time and space and formed a dynamic cycle with four subprocesses, which was the supporting basis of DKPT; DKPT effectively improved the rationality of TCC and offered greater guidance for the evaluation of the forage–livestock balance in the seasonal grazing regions of China’s alpine desert grasslands. In the PWC, the TCCs of different pastures calculated by DKPT were clearly different from those calculated by TT and KPT; the areas of the pastures divided were extremely imbalanced, with a huge surplus of more than 50% in cool-season pastures; in the representative year of 2016, the pastures in the Xisai Basin were underloaded (FLBI = −35.19%) on the whole, while the pastures in the Chaka Basin were overloaded (FLBI = 24.34%).

scholarly journals Manufacturing and Characterization of Hybrid Bulk Voxelated Biomaterials Printed by Digital Anatomy 3D Printing

Polymers ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 123
Author(s):  
Hyeonu Heo ◽  
Yuqi Jin ◽  
David Yang ◽  
Christopher Wier ◽  
Aaron Minard ◽  
...  
Keyword(s):  
High Precision ◽  
Soft Matter ◽  
Research Area ◽  
Experimental Models ◽  
Effective Density ◽  
Practical Applications ◽  
3D Printers ◽  
Processing Techniques ◽  
Complex Surgical Procedures ◽  
Digital Anatomy

The advent of 3D digital printers has led to the evolution of realistic anatomical organ shaped structures that are being currently used as experimental models for rehearsing and preparing complex surgical procedures by clinicians. However, the actual material properties are still far from being ideal, which necessitates the need to develop new materials and processing techniques for the next generation of 3D printers optimized for clinical applications. Recently, the voxelated soft matter technique has been introduced to provide a much broader range of materials and a profile much more like the actual organ that can be designed and fabricated voxel by voxel with high precision. For the practical applications of 3D voxelated materials, it is crucial to develop the novel high precision material manufacturing and characterization technique to control the mechanical properties that can be difficult using the conventional methods due to the complexity and the size of the combination of materials. Here we propose the non-destructive ultrasound effective density and bulk modulus imaging to evaluate 3D voxelated materials printed by J750 Digital Anatomy 3D Printer of Stratasys. Our method provides the design map of voxelated materials and substantially broadens the applications of 3D digital printing in the clinical research area.

scholarly journals Recent Advances in the Development of Exogenous dsRNA for the Induction of RNA Interference in Cancer Therapy

Molecules ◽  
2021 ◽  
Vol 26 (3) ◽  
pp. 701
Author(s):  
Tatiana S. Golubeva ◽  
Viktoria A. Cherenko ◽  
Konstantin E. Orishchenko
Keyword(s):  
Gene Expression ◽  
Rna Interference ◽  
Molecular Biology ◽  
Gene Silencing ◽  
Regulation Of Gene Expression ◽  
Research Area ◽  
Disease Treatment ◽  
Practical Applications ◽  
Agricultural Plants ◽  
Insect Reproduction

Selective regulation of gene expression by means of RNA interference has revolutionized molecular biology. This approach is not only used in fundamental studies on the roles of particular genes in the functioning of various organisms, but also possesses practical applications. A variety of methods are being developed based on gene silencing using dsRNA—for protecting agricultural plants from various pathogens, controlling insect reproduction, and therapeutic techniques related to the oncological disease treatment. One of the main problems in this research area is the successful delivery of exogenous dsRNA into cells, as this can be greatly affected by the localization or origin of tumor. This overview is dedicated to describing the latest advances in the development of various transport agents for the delivery of dsRNA fragments for gene silencing, with an emphasis on cancer treatment.

scholarly journals Representation and Reasoning about Strategic Abilities with ω-Regular Properties

Mathematics ◽  
2021 ◽  
Vol 9 (23) ◽  
pp. 3052
Author(s):  
Liping Xiong ◽  
Sumei Guo
Keyword(s):  
Temporal Logic ◽  
Linear Time ◽  
Dynamic Logic ◽  
Research Area ◽  
Regular Expressions ◽  
Multi Agent Systems ◽  
Practical Applications ◽  
Multi Agent ◽  
Strategy Logic ◽  
Active Research

Specification and verification of coalitional strategic abilities have been an active research area in multi-agent systems, artificial intelligence, and game theory. Recently, many strategic logics, e.g., Strategy Logic (SL) and alternating-time temporal logic (ATL*), have been proposed based on classical temporal logics, e.g., linear-time temporal logic (LTL) and computational tree logic (CTL*), respectively. However, these logics cannot express general ω-regular properties, the need for which are considered compelling from practical applications, especially in industry. To remedy this problem, in this paper, based on linear dynamic logic (LDL), proposed by Moshe Y. Vardi, we propose LDL-based Strategy Logic (LDL-SL). Interpreted on concurrent game structures, LDL-SL extends SL, which contains existential/universal quantification operators about regular expressions. Here we adopt a branching-time version. This logic can express general ω-regular properties and describe more programmed constraints about individual/group strategies. Then we study three types of fragments (i.e., one-goal, ATL-like, star-free) of LDL-SL. Furthermore, we show that prevalent strategic logics based on LTL/CTL*, such as SL/ATL*, are exactly equivalent with those corresponding star-free strategic logics, where only star-free regular expressions are considered. Moreover, results show that reasoning complexity about the model-checking problems for these new logics, including one-goal and ATL-like fragments, is not harder than those of corresponding SL or ATL*.

scholarly journals Flexible 6-in-1 Microsensor for Real-Time Microscopic Monitoring of Proton Battery

Membranes ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 615
Author(s):  
Chi-Yuan Lee ◽  
Chia-Hung Chen ◽  
Chin-Yuan Yang ◽  
John-Shong Cheong ◽  
Yun-Hsiu Chien ◽  
...  
Keyword(s):  
Proton Exchange Membrane ◽  
Water Electrolysis ◽  
Research Area ◽  
Carbon Layer ◽  
Proton Exchange ◽  
Physical Parameters ◽  
Proton Battery ◽  
Practical Applications ◽  
Mems Technology ◽  
Physical Quantities

According to the comparison between a proton battery and a proton exchange membrane fuel cell (PEMFC), the PEMFC requires oxygen and hydrogen for generating electricity, so a hydrogen tank is required, leading to larger volume of PEMFC. The proton battery can store hydrogen in the carbon layer, combined with the oxygen in the air to form water to generate electricity; thus, the battery cost and the space for a hydrogen tank can be reduced a lot, and it is used more extensively. As the proton battery is a new research area, multiple important physical quantities inside the proton battery should be further understood and monitored so as to enhance the performance of battery. The proton battery has the potential for practical applications, as well as water electrolysis, proton storage and discharge functions, and it can be produced without expensive metals. Therefore, in this study, we use micro-electro-mechanical systems (MEMS) technology to develop a diagnostic tool for the proton battery based on the developed microhydrogen sensor, integrated with the voltage, current, temperature, humidity and flow microsensors developed by this laboratory to complete a flexible integrated 6-in-1 microsensor, which is embedded in the proton battery to measure internal important physical parameters simultaneously so that the reaction condition in the proton battery can be mastered more accurately. In addition, the interaction of physical quantities of the proton battery are discussed so as to enhance the proton battery’s performance.

scholarly journals eNetXplorer: an R package for the quantitative exploration of elastic net families for generalized linear models

2018 ◽  
Author(s):  
Julián Candia ◽  
John S. Tsang
Keyword(s):  
Generalized Linear Models ◽  
Linear Models ◽  
Statistical Significance ◽  
Model Fitting ◽  
Predictive Performance ◽  
R Package ◽  
Research Area ◽  
Elastic Net ◽  
Feature Identification ◽  
Practical Applications

AbstractBackgroundRegularized generalized linear models (GLMs) are popular regression methods in bioinformatics, particularly useful in scenarios with fewer observations than parameters/features or when many of the features are correlated. In both ridge and lasso regularization, feature shrinkage is controlled by a penalty parameter λ. The elastic net introduces a mixing parameter α to tune the shrinkage continuously from ridge to lasso. Selecting α objectively and determining which features contributed significantly to prediction after model fitting remain a practical challenge given the paucity of available software to evaluate performance and statistical significance.ResultseNetXplorer builds on top of glmnet to address the above issues for linear (Gaussian), binomial (logistic), and multinomial GLMs. It provides new functionalities to empower practical applications by using a cross validation framework that assesses the predictive performance and statistical significance of a family of elastic net models (as α is varied) and of the corresponding features that contribute to prediction. The user can select which quality metrics to use to quantify the concordance between predicted and observed values, with defaults provided for each GLM. Statistical significance for each model (as defined by α) is determined based on comparison to a set of null models generated by random permutations of the response; the same permutation-based approach is used to evaluate the significance of individual features. In the analysis of large and complex biological datasets, such as transcriptomic and proteomic data, eNetXplorer provides summary statistics, output tables, and visualizations to help assess which subset(s) of features have predictive value for a set of response measurements, and to what extent those subset(s) of features can be expanded or reduced via regularization.ConclusionsThis package presents a framework and software for exploratory data analysis and visualization. By making regularized GLMs more accessible and interpretable, eNetXplorer guides the process to generate hypotheses based on features significantly associated with biological phenotypes of interest, e.g. to identify biomarkers for therapeutic responsiveness. eNetXplorer is also generally applicable to any research area that may benefit from predictive modeling and feature identification using regularized GLMs.Availability and implementationThe package is available under GPL-3 license at the CRAN repository, https://CRAN.R-project.org/package=eNetXplorer

scholarly journals Natural and anthropogenic impacts reflected by paleoclimate proxy parameters in a lake-forest system in Bukovina, Romania

2021 ◽  
Vol 70 (4) ◽  
pp. 339-351
Author(s):  
Máté Karlik ◽  
◽  
Anna Vancsik ◽  
Zoltán Szalai ◽  
Marcel Mîndrescu ◽  
...  
Keyword(s):  
Organic Geochemistry ◽  
Anthropogenic Impacts ◽  
Sediment Cores ◽  
Research Area ◽  
High Temporal Resolution ◽  
Natural Processes ◽  
Weathering Indices ◽  
Eastern Carpathians ◽  
Wide Range ◽  
Paleoclimate Proxy

The research area is located in the Eastern Carpathians, Romania. This region is rich in various formations and indicates significant potential for paleo-environmental reconstruction. The present research was carried out on sediment cores collected at lake Bolătău-Feredeu, Feredeului Mountains (Eastern Carpathians, Romania). Preliminary examination of the sediment confirmed the possibility for data analysis with high temporal resolution. The aim of the research was to clarify and supplement the findings of previous research at this site, to explore the relationships between proxy parameters and to elucidate the cause for the changes. Core dating was carried out using 210Pb and radiocarbon isotopes and indicated that sediment cores span the past 500 years. The research uses a wide range of methodologies, including organic geochemistry with calculated n alkane indices (Phw and Pwax). Based on these proxies, the changes of woody and herbaceous coverage in the catchment can be estimated. Moreover, element concentration, weathering indices and particle size distribution assist to detect climate changes in the catchment area. The data and conclusions yielded by the analysis were compared with the regional modelled temperature profile, based on which five periods were separated. In addition to natural and anthropogenic events, the main factor among the natural processes is the change in annual temperature. Based on the obtained data, several parameters were found to be suitable for monitoring past temperature changes.

System dynamics applications in performance measurement research: progress and challenges

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Olufunke Oladimeji ◽  
Jennifer Cross ◽  
Heather Keathley-Herring
Keyword(s):  
System Dynamics ◽  
Performance Measurement ◽  
Organizational Performance ◽  
Relevant Literature ◽  
Research Area ◽  
Strategic Decision ◽  
Research Progress ◽  
Future Research ◽  
Content Type ◽  
Practical Applications

PurposeA systematic literature review (SLR) was used to identify and analyze literature related to use of system dynamics (SD) applications in organizational performance measurement (PM) research. The purpose of this article is to present the results of a thematic analysis (TA) conducted to synthesize existing empirical evidence, investigate trends and evaluate developments in the research area.Design/methodology/approachA SLR was conducted resulting in a dataset of 97 articles in this research area. Using TA, major themes/subthemes were inductively synthesized to explore the current development and emerging trends and provide guidance for future research.FindingsThe TA resulted in seven themes in the research area – Enhancing knowledge, Approaches to operationalizing PM systems, Utilizing simulation models, Improving organizational outcomes, Achieving strategic alignment, Applying systems thinking and Identifying critical variables. The analysis suggests that although SD has the potential to improve PM systems, there are many limitations and challenges that must be addressed to improve implementation and practical applications. In addition, the results showed that much of the work is exploratory and many fail to fully validate their models suggesting that this research is still in an relatively early phase of development.Research limitations/implicationsThe results of this study are limited to the 97 articles identified using the SLR protocol. Although the search was designed to be comprehensive, there may be other relevant literature that was excluded. Further, the TA was limited to addressing the research questions.Practical implicationsA key insight for managers is that these tools would support decision-makers in understanding performance behaviors and identifying performance drivers for improvement. This suggests that stakeholders can adopt the approach to improve understanding and effectiveness of PM, and to enhance strategic decision-making.Originality/valueThis study provides a distinct and thorough analysis of this research area by conducting an inductive synthesis of developments and challenges and guidance for future research and practice. The resulting thematic model, identified code definitions and proposed framework of strategies to overcome challenges, provide a general overview and resource to support future studies in the research area and facilitate practical use of SD capabilities to support PM.

scholarly journals Context Impacts in Accelerometer-Based Walk Detection and Step Counting

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3604 ◽  
Author(s):  
Buke Ao ◽  
Yongcai Wang ◽  
Hongnan Liu ◽  
Deying Li ◽  
Lei Song ◽  
...  
Keyword(s):  
Wearable Devices ◽  
Performance Comparison ◽  
Process Data ◽  
Algorithm Selection ◽  
Practical Applications ◽  
Dynamic Factors ◽  
Recent Emergence ◽  
Step Counting ◽  
Quantitative Performance ◽  
Series Of Experiments

Walk detection (WD) and step counting (SC) have become popular applications in the recent emergence of wearable devices. These devices monitor user states and process data from MEMS-based accelerometers and optional gyroscope sensors. Various algorithms have been proposed for WD and SC, which are generally sensitive to the contexts of applications, i.e., (1) the locations of sensor placement; (2) the sensor orientations; (3) the user’s walking patterns; (4) the preprocessing window sizes; and (5) the sensor sampling rates. A thorough understanding of how these dynamic factors affect the algorithms’ performances is investigated and compared in this paper. In particular, representative WD and SC algorithms are introduced according to their design methodologies. A series of experiments is designed in consideration of different application contexts to form an experimental dataset. Different algorithms are then implemented and evaluated on the dataset. The evaluation results provide a quantitative performance comparison indicating the advantages and weaknesses of different algorithms under different application scenarios, giving valuable guidance for algorithm selection in practical applications.

ON COMPUTING THE FUZZIFIER IN ↓FLVQ: A DATA DRIVEN APPROACH

2002 ◽  
Vol 12 (02) ◽  
pp. 149-157 ◽  
Author(s):  
L. B. ROMDHANE ◽  
B. AYEB ◽  
S. WANG
Keyword(s):  
Fuzzy Clustering ◽  
Research Area ◽  
Book Design ◽  
Data Set ◽  
Practical Applications ◽  
Probabilistic Clustering ◽  
Data Driven Approach ◽  
Optimal Setting ◽  
Important Research Area

Clustering is an important research area that has practical applications in many fields. Fuzzy clustering has shown advantages over crisp and probabilistic clustering, especially when there are significant overlaps between clusters. Most analytic fuzzy clustering approaches are derived from Bezdek's fuzzy c-means algorithm. One major factor that influences the determination of appropriate clusters in these approaches is an exponent parameter, called the fuzzifier. To our knowledge, no theoretical reason leading to an optimal setting of this parameter is available. This paper presents the development of an heuristic scheme for determining the fuzzifier. This scheme creates close interactions between the fuzzifier and the data set to be clustered. Experimental results in clustering IRIS data and in code book design required for image compression reveal a good performance of our proposal.

Improved Calculation of Eigenvector Sensitivities Using Matrix Perturbation Analysis

1997 ◽  
Vol 119 (1) ◽  
pp. 137-141 ◽  
Author(s):  
R. M. Lin ◽  
M. K. Lim ◽  
Z. Wang
Keyword(s):  
Finite Element ◽  
Dynamic Control ◽  
Element Model ◽  
Research Area ◽  
Computational Effort ◽  
Matrix Perturbation ◽  
Practical Applications ◽  
Structural Design Optimization ◽  
Matrix Perturbation Analysis ◽  
Eigenvector Derivatives

Derivatives of eigenvalues and eigenvectors have become increasingly important in the development of modern numerical methods for areas such as structural design optimization, dynamic system identification and dynamic control, and the development of effective and efficient methods for the calculation of such derivatives has remained to be an active research area for several decades. Based on the concept of matrix perturbation, this paper presents a new method for the improved calculation of eigenvector derivatives in the case where only few of the lower modes of a system under study have been computed. By using this new proposed method, considerable improvement on the accuracy of the estimation of eigenvector derivatives can be achieved at the expense of very tiny extra computational effort since only few matrix vector operations are required. Convergency criterion of the method has been established and the required accuracy can be controlled by including more higher order terms. Numerical results from practical finite element model have demonstrated the practicality of the proposed method. Further, the proposed method can be easily incorporated into commercial finite element packages to improve the accuracy of eigenderivatives needed for practical applications.

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