Linkage Model Research Articles

Functional landscape connectivity for a select few: Linkages do not consistently predict wildlife movement or occupancy

Landscape-level connectivity models developed in geographic information systems (GIS) produce hypothetical objects proposed to connect areas of habitat in fragmented landscapes, hereafter called “linkages”. Assuming they are used by organisms in nature, linkages could be an important tool for the maintenance of viable wildlife populations and biodiversity conservation. We evaluated five California linkage models (four statewide and one desert specific) for use by common California mammal, reptile and amphibian species in two ways using >180,000 wildlife detections over 20 years. If species are using linkages more often than surrounding areas, we expect to find evidence of their occurrence within linkages significantly more than outside linkages. First, we focused on wildlife-vehicle collision (WVC) data as a proxy for wildlife movement across landscapes and tested whether linkages were an important predictor for the presence of WVCs. Second, we used occupancy modeling with inferred non-detections to assess whether linkages were important predictors of species presence on the landscape. We found that the linkage areas were not consistent predictors of WVCs, with the exception of certain large-bodied mammals by individual models. Linkage areas were also not important predictors for the probability of landscape occupancy for most species. These results show that, lacking validation, hypothetical landscape linkages alone will not support functional connectivity for general biodiversity conservation. Therefore, caution should be exercised when using linkages in land and transportation-based conservation planning. In urban environments, modeled linkages may reflect the critical last places for wildlife to move and should be reserved. However, in mixed-use landscapes where wildlife may move more easily, connectivity as a gradient across the landscape should be the target of conservation, including in land-use and transportation planning.

Evaluation of future flood probability in agricultural reservoir watersheds using an integrated flood simulation system

In agricultural reservoir watersheds, the presence of various agricultural hydraulic structures combined with the influence of climate change necessitates effective flood risk analysis. This study aims to develop a flood risk evaluation technique for agricultural basins by incorporating the low temporal resolution of climate change scenarios. The approach utilizes flood probability as a key component and incorporates the Multiplicative Random Cascade model as a probability-based rainfall time decomposition model to capture the inherent uncertainty in climate change data. Reliability analysis with the limit state equation is employed for probability-based risk evaluation. Given that agricultural watersheds typically consist of agricultural reservoirs and farmland, the study develops a hydraulic and hydrological linkage model to comprehensively calculate flood probability, simulating from the agricultural reservoir in the upper side to the farmland located at the bottom edge of the watershed. The flood risk assessment is applied to the Yedang Reservoir watershed in Korea, using the Shared Socio-economic Pathways climate change scenario. Results indicate that flood probability is the highest in river levees during future precipitation events, converging to nearly 100% under 24-hour duration rainfall, irrespective of the rain frequency. Despite the hydraulic structures at the farmland being designed for a lower frequency of rain events, the average probability of flooding in the farmland have reached 50%. The agricultural reservoir exhibits a low risk of flooding even under climate change conditions. The proposed method not only enables the establishment of flood countermeasures but also facilitates the evaluation and prediction of future flood risk for each hydraulic structure located in rural areas affected by climate change.

The economic hierarchy, linkage, and directions between the three northeastern provinces of China and Russian Far East

AbstractThe economic hierarchy index, economic linkage model, and economic membership model are used to study the economic hierarchy, linkage, and direction of Northeast China and Russian Far East from 2005 to 2020, using the three northeastern provinces of China and 11 Far East federal subjects of Russia as the research objects. The findings are as follows: (1) There is a major polarization effect between developed affluent economic regions and stagnant isolated backward regions in the economic rankings in the 11 Russian Far East federal subjects from 2005 to 2020. (2) The three northeastern provinces of China have more economic linkages with their near Russian neighbors— the east‐oriented Primorsky Territory, the north‐oriented Amur Region, and the north‐oriented Khabarovsk Territory, than with their farther neighbors— the Chukotka Autonomous Area, Magadan Region, and Kamchatka Territory. (3) From 2005 to 2020, the Primorsky Territory has been serving as the focal point of economic linkages between Russian Far East and Northeast China, showing the expanding outward pattern resembling the concentric circles.

Effectiveness of community-based oral antiviral treatments against severe COVID-19 outcomes in people 70 years and over in Victoria, Australia, 2022: an observational study

Oral Antiviral (OAV) COVID-19 treatments are widely used, but evidence for their effectiveness against the Omicron variant in higher risk, vaccinated individuals is limited. Retrospective study of two vaccinated cohorts of COVID-19 cases aged ≥70 years diagnosed during a BA.4/5 Omicron wave in Victoria, Australia. Cases received either nirmatrelvir-ritonavir or molnupiravir as their only treatment. Data linkage and logistic regression modelling was used to evaluate the association between treatment and death and hospitalisation and compared with no treatment. Of 38,933 individuals in the mortality study population, 13.5% (n=5250) received nirmatrelvir-ritonavir, 51.3% (n=19,962) received molnupiravir and 35.2% (n=13,721) were untreated. Treatment was associated with a 57% (OR=0.43, 95% CI 0.36-0.51) reduction in the odds of death, 73% (OR=0.27, 95% CI 0.17-0.40) for nirmatrelvir-ritonavir and 55% (OR=0.45, 95% CI 0.38-0.54) for molnupiravir. Treatment was associated with a 31% (OR=0.69, 95% CI 0.55-0.86) reduction in the odds of hospitalisation, 40% (OR=0.60, 95% CI 0.43-0.83) for nirmatrelvir-ritonavir and 29% (OR=0.71, 95% CI 0.58-0.87) for molnupiravir. Cases treated within 1 day of diagnosis had a 61% reduction in the odds of death (OR=0.39, 95% CI 0.33-0.46) compared with 33% reduction for a delay of 4 or more days (OR=0.67, 95% CI 0.44-0.97). Treatment with both nirmatrelvir-ritonavir or molnupiravir was associated with a reduction in death and hospitalisation in vaccinated ≥70 years individuals during the Omicron era. Timely, equitable treatment with OAVs is an important tool in the fight against COVID-19. There was no funding for this study.

Interest linkage models between new farmers and small farmers: Entrepreneurial organization form perspective.

Improving the interest linkage models between new farmers and small farmers is an important measure to realize the organic connection between small farmers and modern agricultural development. Based on the survey data of 572 new farmers in 16 provinces in China, this study uses the ordered probit model to empirically analyze the impact of entrepreneurial organization form on the interest linkage models between new farmers and small farmers. The results show that: (1) The choice of different entrepreneurial organization forms such as individual operation, cooperative operation, partner operation and company operation by new farmers will significantly affect the degree of interest linkage and then the linkage models. Partner operation and company operation have significantly improved the tightness of interest linkage between new farmers and small farmers. (2) The form of entrepreneurial organization significantly impacts the interest linkage between new farmers and small farmers. The higher the stability of entrepreneurial organization form, the closer the interest linkage and the more significant the impact on the interest linkage models. This effect remains significant after considering potential endogeneity issues and robustness tests. (3) In addition, further research also found significant regional differences and group differences in the impact of entrepreneurial organization form on the new farmers and small farmers' interest linkage models. The impact of the western region is more significant than that of the eastern and central regions, and government entrepreneurship support policies can significantly strengthen the interest linkage models. The research results of this paper have vital reference significance for exploring the path of agricultural modernization under the "big country with small farmers".

Magnetically threaded accretion disks in resistive magnetohydrodynamic simulations and asymptotic expansion

Aims. A realistic model of magnetic linkage between a central object and its accretion disk is a prerequisite for understanding the spin history of stars and stellar remnants. To this end, we aim to provide an analytic model in agreement with magnetohydrodynamic (MHD) simulations. Methods. For the first time, we wrote a full set of stationary asymptotic expansion equations of a thin magnetic accretion disk, including the induction and energy equations. We also performed a resistive MHD simulation of an accretion disk around a star endowed with a magnetic dipole, using the publicly available code PLUTO. We compared the analytical results with the numerical solutions, and discussed the results in the context of previous solutions of the induction equation describing the star-disk magnetospheric interaction. Results. We found that the magnetic field threading the disk is suppressed by orders of magnitude inside thin disks, so the presence of the stellar magnetic field does not strongly affect the velocity field, nor the density profile inside the disk. Density and velocity fields found in the MHD simulations match the radial and vertical profiles of the analytic solution. Qualitatively, the MHD simulations result in an internal magnetic field similar to the solutions previously obtained by solving the induction equation in the disk alone. However, the magnetic field configuration is quantitatively affected by magnetic field inflation outside the disk; this is reflected in the net torque. The torque on the star is an order of magnitude larger in the magnetic than in the non-magnetic case. Spin-up of the star occurs on a timescale comparable to the accretion timescale in the MHD case, and is an order of magnitude slower in the absence of a stellar magnetic field.

Semi-Supervised Variational User Identity Linkage via Noise-Aware Self-Learning

User identity linkage, which aims to link identities of a natural person across different social platforms, has attracted increasing research interest recently. Existing approaches usually first embed the identities as deterministic vectors in a shared latent space, and then learn a classifier based on the available annotations. However, the formation and characteristics of real-world social platforms are full of uncertainties, which makes these deterministic embedding based methods sub-optimal. Besides, semi-supervised models utilize the unlabeled data to help capture the intrinsic data distribution. However, the existing semi-supervised linkage methods heavily rely on the heuristically defined similarity measurements to incorporate the innate closeness between labeled and unlabeled samples. Such manually designed assumptions may not be consistent with the actual linkage signals and further introduce the noises. To address the mentioned limitations, in this paper we propose a novel Noise-aware Semi-supervised Variational User Identity Linkage (NSVUIL) model. Specifically, we first propose a novel supervised linkage module to incorporate the available annotations. Each social identity is represented by a Gaussian distribution in the Wasserstein space to simultaneously preserve the fine-grained social profiles and model the uncertainty of identities. Then, a noise-aware self-learning module is designed to faithfully augment the few available annotations, which is capable of filtering noises from the pseudo-labels generated by the supervised module. The filtered reliable candidates are added into the labeled set to provide enhanced training guidance for the next training iteration. Empirically, we evaluate the NSVUIL model over multiple real-world datasets, and the experimental results demonstrate its superiority.

A New Kinematic Synthesis Model of Spatial Linkages for Designing Motion and Identifying the Actual Dimensions of a Double Ball Bar Test Based on the Data Measured

This paper presents the new synthesis models of spatial linkages for designing measurement motion functions and ranges and identifying the actual dimension parameters. The spatial five-bar linkage is first introduced for the kinematic model of a double ball bar test of a two-axis rotary table. To design the ideal measurement motion and motion range of the double ball bar test, a novel saddle synthesis model of a spatial four-bar linkage RRSS is readily presented. Based on the output data measured from the double ball bar test, a new saddle synthesis model of a spatial five-bar linkage RRSPS is logically proposed for identifying their actual dimensions. Finally, three test cases and their results indicate that the new synthesis models presented in the paper can conveniently and efficiently calculate the measurement motion function and range and accurately identify the actual dimensions of the double ball bar test, which provides a suitable mathematical model for improving the accuracy of the double ball bar tests of a two-axis rotary table of machine tools.

Analogue model of rift linkage and inversion with application to the Western Alps

Analogue model of rift linkage and inversion with application to the Western Alps

Using probabilistic linkage to improve estimates of access to services among the migrant population: The case of access to immunisation programs in Chile

ObjectivesGovernments often struggle to accurately estimate the number of migrants using public services due to the lack of a unique national ID. We aim to study this in the context of migrant access to immunization programs in Chile and estimate vaccine coverage in school-age children.
 MethodsTo estimate vaccine coverage for migrant school-age children, we combined data from two databases: the Chilean National Immunization Register (which contained 77.9 million records) and the School Enrollment database (which contained around 68 million records, representing about 3.6 pupils per year). Using Splink, a Python package developed by the UK Ministry of Justice, we created a probability linkage model to link and deduplicate records of migrants who lack a unique national ID. The following linkage keys were considered in the model: first and second name, first and last name and date of birth. Linkage quality was evaluated using ‘gold standard data.
 ResultsIn 2022, we find that out of 3,644,467 students enrolled in school, 140,317 of them were migrants who didn't have a Chilean national ID. Additionally, in the NIR database, 5.2 out of 77.9 million records belonged to migrants without a national ID. After removing duplicates from both databases, our linkage model determined that 52,524 of the 140,317 students without a national ID in SE were linked to NIR (37.4%). We find that excluding migrants without national IDs when estimating national vaccine coverage for school-aged children leads to an underestimation of 2%, from 86% to 88%.
 ConclusionOur findings emphasize the significance of utilizing linkage techniques in order to accurately estimate access to public services for migrant populations who typically lack a national ID. By linking their records across public institutions, more reliable data can be obtained.

Splink: Latest developments and applications

Funded by ADR UK, a new data linking team at the Ministry of Justice set out to link administrative datasets across the justice space, for internal use and sharing with external researchers. To achieve this aim we sought a linkage implementation that was probabilistic, flexible, scalable and ideally open source.
 Taking into account the tools available at the MoJ, existing open-source software (and paid alternatives) failed to meet our desired criteria. It was decided to develop a software package that builds on FastLink’s implementation in R of an Expectation-Maximisation algorithm to estimate a Fellegi-Sunter linkage model, adding a range of technical improvements, increased functionality and customisation options. Distributed computing offered by Spark could facilitate comparable linkage jobs that run on much larger datasets and much faster. Working with government data, accountability and transparency are vital, so the data and models are made accessible by a range of intuitive visualizations.
 The Splink python package has been downloaded over 6 million times. This initially used Spark to deliver its superior performance, but Splink v3 caters for various SQL backends and more potential users. As we have made Splink more intuitive, more accessible, and more extensively documented we continue to receive feedback and contributions from around the world, driving further continuous development.
 Through technical innovation and user-focused development, Splink has improved access to cutting-edge data linkage, and created groundbreaking research opportunities at MoJ and beyond. The team is grateful to ONS and other collaborators for testing and adopting these tools, and we will present some of the latest developments as well as examples of how Splink has been used worldwide.

Characteristics of programmes designed to link community-dwelling older adults in high-income countries from community to clinical sectors: a scoping review protocol

IntroductionResearch on effectively navigating older adults into primary care is urgently needed. Community–clinic linkage models (CCLMs) aim to improve population health by linking the health and community sectors in order...

Cutting Force Fluctuation Suppression and Error Homogenization of Noncircular Gear Hobbing Based on the Tool Shifting Method

The current research on noncircular hobbing mainly focuses on the linkage model and motion realization. However, the intermittent cutting characteristics of hobbing would increase uncertainties in the manufacturing process. In this paper, a hobbing machining model with tool-shifting characteristics was proposed to solve the problems of cutting force fluctuation and inconsistency of tooth profile envelope accuracy at different positions of the pitch curve in noncircular gear hobbing. Based on the unit cutting force coefficient method, the undeformed chip volume generated by interrupted cutting was used to characterize the fluctuation trend of the hobbing force. The fluctuation characteristics of the cutting force generated by different hobbing models were compared and analyzed. Using the equivalent gear tooth and hob slotting numbers, an analysis model of the tooth profile envelope error of the noncircular gear was constructed. Subsequently, the tooth profile envelope errors at different positions of the pitch curve were compared and analyzed based on the constructed model. The transmission structure of the electronic gearbox was constructed based on the proposed hobbing model, and the hobbing experiment was conducted based on the self-developed noncircular gear CNC hobbing system. This paper proposes a hobbing method that can effectively suppress the fluctuation of the peak and whole circumference cutting force and reduce the maximum envelope error of the whole circumference gear teeth.

Creating a safer workplace: A linkage model for labour‒management partnership, psychological safety, collaborative industrial relations climate and organisational occupational and health safety performance

This study takes a mutual gains perspective to investigate how a labour‒management partnership (LMP) impacts organisational occupational and health safety (OHS) performance and creates a safe workplace. It develops a model linking employee psychological safety with a collaborative industrial relations (IR) climate and ultimately organisational OHS performance. The research context is China ‒ where LMP is driven by the Party-state in managing labour relations. To test the proposed linkage model, multi-level structural equation modelling is conducted, using matched employer‒employee data from 205 companies and 7229 employees in an industrial park in the Yangtze River Delta. The results support the use of the linkage model, demonstrating that partnership decision-making increases psychological safety, in turn developing a collaborative IR climate, ultimately reducing the number of accidents. This study contributes to partnership research by exploring the underlying mechanisms of how a partnership arising from the logic of neo-pluralism successfully delivers mutual gains for employees and employers in a non-pluralist context. It has wider implications for collaborative management and OHS management in a developing country.

A Study on Smallholder Farmers’ Willingness to Sustain Cooperation with New Farmers—Analysis Based on the Perspective of Smallholder Farmers’ Satisfaction

In the context of rural revitalization, it is important to promote the establishment of lasting cooperation between small farmers and new farmers to drive farmers to increase their income and achieve common prosperity. Based on the research data of 342 small farmers in six provinces, the article empirically analyzes the willingness of small farmers to continue cooperation with new farmers in the future from the perspective of satisfaction using an ordered logistic model. The research results show that small farmers’ satisfaction with the benefit linkage model, with the benefit distribution, and with benefit dispute handling positively and significantly influence small farmers’ willingness to continue cooperation with new farmers in the future. For every 1% increase in satisfaction with the benefit linkage model, the probability of continuing to cooperate with new farmers in the future increases by 9.40%, and for every 1% increase in satisfaction with the benefit distribution and satisfaction with benefit dispute handling, the probability of continuing to cooperate with new farmers increases by 7.30% and 9.40%, respectively. Accordingly, this paper puts forward policy suggestions such as respecting the choice of interest linkage model of small farmers, improving the benefit distribution mechanism, and handling cooperation disputes reasonably, in order to improve the satisfaction of small farmers’ cooperation, promote the construction of lasting cooperation between small farmers and new farmers, and build a rural community of interest.

A Fixed-Point Position Observation Algorithm and System-on-Chip Design Suitable for Sensorless Control of High-Speed Permanent Magnet Synchronous Motor

In the sensorless control algorithm of permanent magnet synchronous motors (PMSMs), there is a significant research focus on developing a high-performance position observer and a cost-effective, high-performance processor specifically designed for PMSMs. In this paper, we first reviewed the current mainstream position observation algorithms. Subsequently, we proposed a position observation algorithm based on a fixed-point nonlinear flux linkage model that introduces a variable gain model and an observer compensation model. Furthermore, we implemented the improved position observation algorithm in the circuit and designed a System-on-Chip (SOC) suitable for the sensorless control of high-speed permanent magnet synchronous motors using the ARM Cortex-M0 core. The functionality of the proposed SOC was verified on the Field Programmable Gate Array (FPGA) platform. The results demonstrate that the improved algorithm offers an excellent angle observation accuracy and fast convergence speed. The error between the observed angle and the actual angle is less than 0.2 rad. Additionally, the designed SOC balances the high efficiency of hardware implementation with the flexibility of software implementation. When running a sensorless control algorithm for PMSM, it achieves a 30.3% increase in execution efficiency, enabling support for higher frequency output PWM switching and making it suitable for the high-precision control of high-speed PMSM.

Documentary analysis on linkage models for higher education institutions

Las instituciones de educación superior requieren afrontar los retos y desafíos provocados por el cambio organizacional, la tecnología y la globalización. Por lo anterior, la vinculación permite conocer la necesidad del contexto del campo laboral y la sociedad; para atender estas necesidades por medio de la investigación en las academias, asesorías y consultorías, capacitación, servicios de educación continua y estancias cortas de los estudiantes y docentes. La presente investigación es de tipo documental - cualitativa, tiene como objetivo dar a conocer los resultados de un estudio documental sobre los modelos de vinculación a través de la identificación, análisis y síntesis de los modelos en comento. Se definieron las categorías de evolución, conceptualización, modelos de vinculación y estudios documentales sobre la vinculación en las instituciones de educación superior. Con el análisis de esta investigación se tuvo como resultado que no se tienen documentados los procedimientos del modelo de vinculación de las instituciones de educación superior; por lo tanto, se podrán derivar futuras investigaciones que beneficien a la universidad-empresa-gobierno con actividades de investigación y participación de estudiantes y docentes en la comunidad y la aplicación de la teoría con la práctica hacia la solución de problemas de la región, del estado y del país.

A multi-sensor cooperative detection target tracking method based on radar-optical linkage control

Radar is a common means of tracking a target, and with active enemy interference, it often causes the target to lose its track, thus causing the radar to lose continuous tracking of the target. To improve the tracking effect, a multi-sensor cooperative detection target tracking method based on radar photoelectric linkage control was established. The study is based on radar photoelectric linkage, constant velocity (CV), constant acceleration (CA) and current statistical model (CSM) as the mathematical model of moving targets for this study. Improved interactive multi-model (IMM) and standard IMM were compared for targets in different motion states, as well as single sensor electronic support measures (ESM) and multi-sensor electronic support measures (ESM), infrared search and track (IRST). The research results show that in variable speed motion, the improved IMM algorithm and multiple sensors are used for target tracking. The azimuth and elevation tracking errors of the target are low, which can effectively solve the problem of model mismatch during the conversion of motion modes such as CV and CA. The azimuth and elevation image curves fluctuate smoothly, and have high stability. This method can achieve better tracking results.

A Bayesian record linkage model incorporating relational data

AbstractIn this article, we introduce a novel Bayesian approach for linking multiple social networks in order to discover the same real world person having different accounts across networks. In particular, we develop a latent model that allows us to jointly characterize the network and linkage structures relying on both relational and profile data. In contrast to other existing approaches in the machine learning literature, our Bayesian implementation naturally provides uncertainty quantification via posterior probabilities for the linkage structure itself or any function of it. Our findings clearly suggest that our methodology can produce accurate point estimates of the linkage structure even in the absence of profile information, and also, in an identity resolution setting, our results confirm that including relational data into the matching process improves the linkage accuracy. We illustrate our methodology using real data from popular social networks such as Twitter, Facebook, and YouTube.

Analysis of Kinematic Constraints in the Linkage Model of a Mecanum-Wheeled Robot and a Trailer with Conventional Wheels

Mechanical systems that consist of a four-wheeled or two-wheeled robot with Mecanum wheels and a two-wheeled trailer with conventional wheels are considered. The kinematic characteristics of the mechanical systems under consideration of holonomic and non-holonomic constraints are presented and compared. From this, it is shown that the structure of the kinematic constraint equations for mobile systems with a trailer does not apply to Chaplygin’s dynamic equations. If the mechanical system is not Chaplygin’s system, then the dynamic equations cannot be integrated separately from the equations of kinematic constraints. This is the difference between the kinematic constraint equations for the robot-trailer system and the constraint equations for a single robot with Mecanum wheels. Examples of numerical calculations using the equations of kinematic constraints are given.