cluster membership
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2022 ◽  
Vol 34 (4) ◽  
Author(s):  
NGUYEN THI KIM QUYEN ◽  
◽  
TRAN THI BACH YEN ◽  
ANNA KARIA LERØY RIPLE

The increasing demand by international customers for high-quality shrimp products has led to the introduction of various certificates of traceability intended to validate quality products in Vietnam. The Vietnamese good agricultural practices (VietGAP), better known in aquaculture as the Vietnamese good aquaculture practices, has emerged as a reliable certificate for small-scale farmers and a prerequisite for international certification. This study investigates factors affecting applications for VietGAP by small-scale shrimp farmers in Vietnam. Cost-benefit analysis and binary logistic regression approaches were used to categorise shrimp farms with and without VietGAP certification. Findings indicated that while the adoption of VietGAP raised production costs by 14.5 %, it could increase net profit by up to 22 %. The increase in net profit is from increased productivity and antibiotics and chemical-free products in shrimp farming, helped fetch better prices. The results also revealed three factors that positively influenced the farmers’ decision to acquire VietGAP; education, farm size, and production system. Shrimp farmers with longer schooling years, larger farms, and those who possess cooperative/farming cluster membership are more likely to acquire VietGAP certification. The results imply that the VietGAP certification should be better promoted to cooperative production forms of farming, by strengthening the schooling year of farmers and increasing awareness of VietGAP certification to farmers who operate shrimp farms of 5,000–9,000 m2.


2021 ◽  
Vol 12 (1) ◽  
pp. 54
Author(s):  
Lauren E. Kenney ◽  
Adrianna M. Ratajska ◽  
Francesca V. Lopez ◽  
Catherine C. Price ◽  
Melissa J. Armstrong ◽  
...  

Prevalence rates for mild cognitive impairment in Parkinson’s disease (PD-MCI) remain variable, obscuring the diagnosis’ predictive utility of greater dementia risk. A primary factor of this variability is inconsistent operationalization of normative cutoffs for cognitive impairment. We aimed to determine which cutoff was optimal for classifying individuals as PD-MCI by comparing classifications against data-driven PD cognitive phenotypes. Participants with idiopathic PD (n = 494; mean age 64.7 ± 9) completed comprehensive neuropsychological testing. Cluster analyses (K-means, Hierarchical) identified cognitive phenotypes using domain-specific composites. PD-MCI criteria were assessed using separate cutoffs (−1, −1.5, −2 SD) on ≥2 tests in a domain. Cutoffs were compared using PD-MCI prevalence rates, MCI subtype frequencies (single/multi-domain, executive function (EF)/non-EF impairment), and validity against the cluster-derived cognitive phenotypes (using chi-square tests/binary logistic regressions). Cluster analyses resulted in similar three-cluster solutions: Cognitively Average (n = 154), Low EF (n = 227), and Prominent EF/Memory Impairment (n = 113). The −1.5 SD cutoff produced the best model of cluster membership (PD-MCI classification accuracy = 87.9%) and resulted in the best alignment between PD-MCI classification and the empirical cognitive profile containing impairments associated with greater dementia risk. Similar to previous Alzheimer’s work, these findings highlight the utility of comparing empirical and actuarial approaches to establish concurrent validity of cognitive impairment in PD.


Author(s):  
Feifei Han

This study investigates to what extent there is an association between students’ self-reported perceptions of online learning and observed online learning behaviors recorded by the learning analytic data. The participants were 319 undergraduates studying an engineering course in an Australian university. Data analyses were conducted using cluster analyses, Hidden Markov Model, one-way ANOVAs, and a cross-tabulation. The relations between students’ self-reported perceptions and their academic learning outcome show that those with positive perceptions tended to have higher scores. The relations between observational online learning behaviors and their academic learning outcome demonstrate that students with most learning sessions achieved more highly. The cross-tabulation finds a significant association between the cluster membership generated by by the self-reported perceptions and observational online learning behaviors. Amongst students who had most study sessions characterized by high percentages of reading and formative states and low percentage of summative states, the proportion of those with positive perceptions (40.2%) was significantly higher than those with negative perceptions (20.0%). Of students who had the least study sessions represented by moderate reading and summative states, and low formative states, the proportion of students with positive perceptions (3.0%) was significantly lower than the proportion of students having negative perceptions (8.7%).


2021 ◽  
Author(s):  
Rodrigo A. Olarte ◽  
Rebecca Hall ◽  
Javier Tabima ◽  
Dean Malvick ◽  
Kathryn Bushley

Sudden death syndrome (SDS) of soybean is a damaging disease caused by the fungus Fusarium virguliforme. Since this pathogen was first reported in the southern US state of Arkansas in 1971, it has spread throughout the Midwestern U.S. The SDS pathogen primarily colonizes roots but also produces toxins that translocate to and damage leaves. Previous studies detected little to no genetic differentiation among isolates, suggesting F. virguliforme in North America has limited genetic diversity and a clonal population structure. Yet, isolates vary in virulence to roots and leaves. We characterized a set of F. virguliforme isolates from the Midwestern U.S. representing a south to north latitudinal gradient from Arkansas to Minnesota. Ten previously tested microsatellite loci were used to genotype isolates and plant assays were conducted to assess virulence. Three distinct population clusters were differentiated across isolates. Although isolates ranged in virulence classes from low to very high, little correlation was found between virulence phenotype and cluster membership. Similarly, population structure and geographic location were not highly correlated. However, the earliest diverging cluster had the lowest genetic diversity and was detected only in southern states, while the other two clusters were distributed across the Midwest and were predominant in Minnesota. One of the Midwestern clusters had the greatest genetic diversity and was found along the northern edge of the known distribution. The results support three genetically distinct population clusters of F. virguliforme in the U.S., with two clusters contributing most to spread of this fungus across the Midwest.


2021 ◽  
Author(s):  
◽  
Sara Yaghoubi

<p>Ambidexterity, defined as the ability to simultaneously explore new knowledge and exploit existing knowledge, allows firms to adapt over time, build a sustainable competitive advantage and achieve growth in the long run. However, due to the tensions and trade-offs between exploration and exploitation, pursuing ambidexterity or developing a more balanced strategy can be challenging. Previous research on ambidexterity has focused primarily on large and well-established organizations and the outcomes of ambidexterity such as performance, whereas little is known about how ambidexterity of small- and medium-sized family businesses in an international business context is managed, especially with regard to exporting, which is the most common form of internationalisation for those firms.  Therefore, the purpose of this qualitative case study is to understand how small- and medium-sized family firms manage ambidexterity in exporting. Specifically, I shed light on both market and product domains in exporting and further the impact of industrial cluster on firms’ approach to becoming ambidextrous. Using data from semi-structured interviews with six family-owned wineries located in the Marlborough wine region, New Zealand, the research provides evidence that family firms’ unique characteristics, that is, the socioemotional wealth, guide them to particular types of export exploration and exploitation activities in both market and product domains. These are not only aligned with their non-economic goals but also create synergies among seemingly contradictory ambidextrous activities. These findings suggest a behaviour logic and path to explain how ambidexterity in exporting is achieved, through combining and integrating exploration and exploitation in a balanced way. The findings also show that cluster membership improves family firms’ ability to achieve export ambidexterity by providing access to critical resources.  Overall, the study adds to the growing body of literature on family business internationalisation and organizational ambidexterity by focusing on the export context. It further links ambidexterity research to industrial cluster literature.</p>


2021 ◽  
Author(s):  
◽  
Sara Yaghoubi

<p>Ambidexterity, defined as the ability to simultaneously explore new knowledge and exploit existing knowledge, allows firms to adapt over time, build a sustainable competitive advantage and achieve growth in the long run. However, due to the tensions and trade-offs between exploration and exploitation, pursuing ambidexterity or developing a more balanced strategy can be challenging. Previous research on ambidexterity has focused primarily on large and well-established organizations and the outcomes of ambidexterity such as performance, whereas little is known about how ambidexterity of small- and medium-sized family businesses in an international business context is managed, especially with regard to exporting, which is the most common form of internationalisation for those firms.  Therefore, the purpose of this qualitative case study is to understand how small- and medium-sized family firms manage ambidexterity in exporting. Specifically, I shed light on both market and product domains in exporting and further the impact of industrial cluster on firms’ approach to becoming ambidextrous. Using data from semi-structured interviews with six family-owned wineries located in the Marlborough wine region, New Zealand, the research provides evidence that family firms’ unique characteristics, that is, the socioemotional wealth, guide them to particular types of export exploration and exploitation activities in both market and product domains. These are not only aligned with their non-economic goals but also create synergies among seemingly contradictory ambidextrous activities. These findings suggest a behaviour logic and path to explain how ambidexterity in exporting is achieved, through combining and integrating exploration and exploitation in a balanced way. The findings also show that cluster membership improves family firms’ ability to achieve export ambidexterity by providing access to critical resources.  Overall, the study adds to the growing body of literature on family business internationalisation and organizational ambidexterity by focusing on the export context. It further links ambidexterity research to industrial cluster literature.</p>


2021 ◽  
Vol 13 (2) ◽  
pp. 113
Author(s):  
Jajang Jajang ◽  
Nunung Nurhayati ◽  
Yhenis Apriliana

Clustering N objects into c clusters can be used to get information about data observation. Among the clustering methods are K-Means (KMC) and Fuzzy C-means (FCM) methods. In the K-means method, objects are members or not members of the cluster, while in the FCM method, objects are included in the cluster based on the degree of membership. This study discusses the implementation of KMC and FCM in the custering of sub-districts in Banyumas Regency based on total of population, the number of health workers and the number of health facilities and infrastructure. The results showed that the KMC and FCM methods produced the same cluster membership. Furthermore, the analysis of clustering based on the number of population, the number of health workers and the number of health facilities and infrastructure (scenario 1) and based on the number of health workers and the number of health facilities and infrastructure which have been corrected by population (scenario 2). The percentage of the variance ratio between clusters to the total variance in scenario 1 is 69% while in scenario 2 it is 85%. Clustering based on scenario 2 is better than scenario 1.


2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 775-776
Author(s):  
Kristin Litzelman ◽  
Irene Kizza ◽  
Ashley Berghoff

Abstract Caregivers engage in myriad tasks from household help to complex medical care. However, little information is available on how caregivers experience individual tasks – particularly key end-of-life tasks such as managing breathing problems or patients' sadness and anxiety. The purpose of this study was therefore to assess task difficulty. Using data from the National Health and Aging Trends Survey and the National Survey on Caregivers (2015-2017), we assessed eleven caregiving tasks in 241 primary caregivers of care recipients in their last month of life. A latent cluster analysis revealed three key clusters: 1) pervasive difficulties, in which caregivers reported difficulty across most or all of the tasks; 2) minimal difficulties; and 3) emotional management difficulties, in which caregivers reported difficulty with managing sadness and anxiety and lower levels of difficulty on the other tasks. Weighted frequency analyses revealed that caregivers in the pervasive difficulties cluster were most likely to be filial caregivers (85% versus 63% of the full sample, p&lt;0.05) or co-residing with the care recipient (49% versus 37% of the full sample, p&lt;0.05). Caregivers identified as having pervasive difficulties were also more likely to report providing intensive care, more than 100 hours per week (54% versus 36% of the full sample, p&lt;0.05). Care recipient condition was not associated with cluster membership. The findings highlight the need to consider caregiver coping at the task-level and have implications for understanding unmet needs. Future research will assess predictors of cluster membership and how task difficulties are associated with symptoms and well-being outcomes.


2021 ◽  
Vol 922 (2) ◽  
pp. 268
Author(s):  
Yolanda Jiménez-Teja ◽  
Jose M. Vílchez ◽  
Renato A. Dupke ◽  
Paulo A. A. Lopes ◽  
Nícolas O. L. de Oliveira ◽  
...  

Abstract We present a pilot study of the intracluster light (ICL) in massive clusters using imaging of the z = 0.566 cluster of galaxies WHL J013719.8–08284 observed by the RELICS project with the Hubble Space Telescope. We measure the ICL fraction in four optical ACS/WFC filters (F435W, F475W, F606W, and F814W) and five infrared WFC3/IR bands (F105W, F110W, F125W, F140W, and F160W). The ICL maps are calculated using the free-of-a-priori-assumptions algorithm CICLE, and the cluster membership is estimated from photometric properties. We find optical ICL fractions that range between ∼6% and 19%, in nice agreement with the values found in previous works for merging clusters. We also observe an ICL fraction excess between 3800 Å and 4800 Å, previously identified as a signature of merging clusters at 0.18 < z < 0.55. This excess suggests the presence of an enhanced population of young/low-metallicity stars in the ICL. All indicators thus point to WHL J013719.8–08284 as a disturbed cluster with a significant amount of recently injected stars, bluer than the average stars hosted by the cluster members and likely stripped out from infalling galaxies during the current merging event. Infrared ICL fractions are ∼50% higher than optical ones, which could be signatures of an older and/or higher-metallicity ICL population that can be associated with the buildup of the brightest cluster galaxy, passive evolution of previously injected young stars, or preprocessing in infalling groups. Finally, investigating the photometry of the cluster members, we tentatively conclude that WHL J013719.8–08284 fulfills the expected conditions for a fossil system progenitor.


2021 ◽  
Vol 162 (6) ◽  
pp. 285
Author(s):  
Isabel Lipartito ◽  
John I. Bailey III ◽  
Timothy D. Brandt ◽  
Benjamin A. Mazin ◽  
Mario Mateo ◽  
...  

Abstract We present orbits for 24 binaries in the field of open cluster NGC 2516 (∼150 Myr) and 13 binaries in the field of open cluster NGC 2422 (∼130 Myr) using results from a multiyear radial-velocity (RV) survey of the cluster cores. Six of these systems are double-lined spectroscopic binaries. We fit these RV variable systems with orvara, a MCMC-based fitting program that models Keplerian orbits. We use precise stellar parallaxes and proper motions from Gaia EDR3 to determine cluster membership. We impose a barycentric RV prior on all cluster members; this significantly improves our orbital constraints. Two of our systems have periods between five and 15 days, the critical window in which tides efficiently damp orbital eccentricity. These binaries should be included in future analyses of circularization across similarly-aged clusters. We also find a relatively flat distribution of binary mass ratios, consistent with previous work. With the inclusion of TESS light curves for all available targets, we identity target 378–036252 as a new eclipsing binary. We also identify a field star whose secondary has a mass in the brown dwarf range, as well as two cluster members whose RVs suggest the presence of an additional companion. Our orbital fits will help constrain the binary fraction and binary properties across stellar age and across stellar environment.


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