Disassortativity in Biological and Supply Chain Networks

Network science has allowed researchers to model complex real world systems as networks in order to identify non trivial topological patterns. Degree correlations (or assortativity) is one such non trivial topological property, which indicates the extent to which nodes with similar degrees tend to pair up with each other. Biological networks have long been known to display anti-degree correlations (disassortativity), where highly connected nodes tend to avoid linking with each other. However, the mechanism underlying this structural organisation remain not well understood. Recent work has suggested that in some instances, disassortativity can be observed merely as a model artefact due to simple network representations not allowing multiple link formations between the node pairs. This phenomena is known as structural disassortativity. In this paper, we analyse datasets from two distinct classes of networks, namely; man made supply chain networks and naturally occurring biological networks. We examine whether the observed disassortativity in these networks are structurally induced or owing to some external process. Degree preserving randomisation is used to generate an ensemble of null models for each network. Comparison of the degree correlation profiles of each network, against that of their degree preserving randomised counterparts reveal whether the observed disassortativity in each network is of structural nature or not. We find that in all biological networks, the observed disassortativity is of structural nature, meaning their disassortative nature can be fully explained by their respective degree distributions, without attribution to any underlying mechanism which drives the system towards disassortativity. However, in supply chain networks, we find one case where disassortativity is structurally induced and in other cases where it is mechanistically driven. We conclude by emphasizing on ruling out structural disassortativity in future research, prior to investigating mechanisms underlying disassortativity in networks

A network science approach to analysing manufacturing sector supply chain networks: Insights on topology

Due to the increasingly complex nature of the modern supply chain networks (SCNs), a recent research trend has focussed on modelling SCNs as complex adaptive systems. Despite the substantial number of studies devoted to such hypothetical modelling efforts, studies analysing the topological properties of real world SCNs have been relatively rare, mainly due to the scarcity of data. This paper aims to analyse the topological properties of twenty-six SCNs from the manufacturing sector. Moreover, this study aims to establish a general set of topological characteristics that can be observed in real world SCNs from the manufacturing sector, so that future theoretical work modelling the growth of SCNs in this sector can mimic these observations. It is found that the manufacturing sector SCNs tend to be scale free with degree exponents below two, tending towards hub and spoke configuration, as opposed to most other scale-free networks which have degree exponents above two. This observation becomes significant, since the importance of the degree exponent threshold of two in shaping the growth process of networks is well understood in network science. Other observed topological characteristics of the SCNs include disassortative mixing (in terms of node degree as well as node characteristics) and high modularity. In some networks, we find that node centrality is strongly correlated with the value added by each node to the supply chain. Since the growth mechanism that is most widely used to model the evolution of SCNs, the Barabasi - Albert model, does not generate scale-free topologies with degree exponent below two, it is concluded that a novel mechanism to model the growth of SCNs is required to be developed

Topological Structure of Manufacturing Industry Supply Chain Networks

Empirical analyses of supply chain networks (SCNs) in extant literature have been rare due to scarcity of data. As a result, theoretical research have relied on arbitrary growth models to generate network topologies supposedly representative of real-world SCNs. Our study is aimed at filling the above gap by systematically analysing a set of manufacturing sector SCNs to establish their topological characteristics. In particular, we compare the differences in topologies of undirected contractual relationships (UCR) and directed material flow (DMF) SCNs. The DMF SCNs are different from the typical UCR SCNs since they are characterised by a strictly tiered and an acyclic structure which does not permit clustering. Additionally, we investigate the SCNs for any self-organized topological features. We find that most SCNs indicate disassortative mixing and power law distribution in terms of interfirm connections. Furthermore, compared to randomised ensembles, self-organized topological features were evident in some SCNs in the form of either overrepresented regimes of moderate betweenness firms or underrepresented regimes of low betweenness firms. Finally, we introduce a simple and intuitive method for estimating the robustness of DMF SCNs, considering the loss of demand due to firm disruptions. Our work could be used as a benchmark for any future analyses of SCNs

Work-related complaints of arm, neck and shoulder among computer office workers in an Asian country: prevalence and validation of a risk-factor questionnaire

<p>Abstract</p> <p>Background</p> <p>Complaints of arm, neck and/or shoulders (CANS) affects millions of computer office workers. However its prevalence and associated risk factors in developing countries are yet to be investigated, due to non availability of validated assessment tools for these countries. We evaluated the 1-year prevalence of CANS among computer office workers in Sri Lanka and tested the psychometric properties of a translated risk factor questionnaire.</p> <p>Methods</p> <p>Computer office workers at a telecommunication company in Sri Lankan received the Sinhalese version of the validated Maastricht Upper Extremity Questionnaire (MUEQ). The 94 items in the questionnaire covers demographic characteristics, CANS and evaluates potential risk factors for CANS in six domains. Forward and backward translation of the MUEQ was done by two independent bi-lingual translators. One-year prevalence of CANS and psychometric properties of the Sinhalese questionnaire were investigated.</p> <p>Results</p> <p>Response rate was 97.7% (n = 440). Males were 42.7%. Mean age was 38.2 ± 9.5 years. One-year prevalence of CANS was 63.6% (mild-53.7% and severe-10%). The highest incidences were for neck (36.1%) and shoulder (34.3%) complaints. Two factors for each domain in the scale were identified by exploratory factor analysis (i.e. work-area, computer-position, incorrect body posture, bad-habits, skills and abilities, decision-making, time-management, work-overload, work-breaks, variation in work, work-environment and social-support). Calculation of internal consistency (Cronbach's alpha 0.43-0.82) and cross-validation provided evidence of reliability and lack of redundancy of items.</p> <p>Conclusion</p> <p>One year prevalence of CANS in the study population corresponds strongly with prevalence in developed countries. Translated version of the MUEQ has satisfactory psychometric properties for it to be used to assess work-related risk factors for development of CANS among Sri Lankan computer office workers.</p

Work related complaints of neck, shoulder and arm among computer office workers: a cross-sectional evaluation of prevalence and risk factors in a developing country

<p>Abstract</p> <p>Background</p> <p>Complaints of arms, neck and shoulders (CANS) is common among computer office workers. We evaluated an aetiological model with physical/psychosocial risk-factors.</p> <p>Methods</p> <p>We invited 2,500 computer office workers for the study. Data on prevalence and risk-factors of CANS were collected by validated Maastricht-Upper-extremity-Questionnaire. Workstations were evaluated by Occupational Safety and Health Administration (OSHA) Visual-Display-Terminal workstation-checklist. Participants' knowledge and awareness was evaluated by a set of expert-validated questions. A binary logistic regression analysis investigated relationships/correlations between risk-factors and symptoms.</p> <p>Results</p> <p>Sample size was 2,210. Mean age 30.8 ± 8.1 years, 50.8% were males. The 1-year prevalence of CANS was 56.9%, commonest region of complaint was forearm/hand (42.6%), followed by neck (36.7%) and shoulder/arm (32.0%). In those with CANS, 22.7% had taken treatment from a health care professional, only in 1.1% seeking medical advice an occupation-related injury had been suspected/diagnosed. In addition 9.3% reported CANS-related absenteeism from work, while 15.4% reported CANS causing disruption of normal activities. A majority of evaluated workstations in all participants (88.4%,) and in those with CANS (91.9%) had OSHA non-compliant workstations. In the binary logistic regression analyses female gender, daily computer usage, incorrect body posture, bad work-habits, work overload, poor social support and poor ergonomic knowledge were associated with CANS and its' severity In a multiple logistic regression analysis controlling for age, gender and duration of occupation, incorrect body posture, bad work-habits and daily computer usage were significant independent predictors of CANS</p> <p>Conclusions</p> <p>The prevalence of work-related CANS among computer office workers in Sri Lanka, a developing, South Asian country is high and comparable to prevalence in developed countries. Work-related physical factors, psychosocial factors and lack of awareness were all important associations of CANS and effective preventive strategies need to address all three areas.</p

Non-resolution of non-alcoholic fatty liver disease (NAFLD) among urban, adult Sri Lankans in the general population: A prospective, cohort follow-up study.

BACKGROUND:There are few studies investigating the natural course of non-alcoholic fatty liver disease (NAFLD) in the community. We assessed resolution of NAFLD in a general population cohort of urban Sri Lankans adults. METHODS:Participants were selected by age-stratified random sampling from electoral lists. They were initially screened in 2007 and re-evaluated in 2014. On both occasions structured interview, anthropometric-measurements, liver ultrasonography, and biochemical/serological tests were performed. NAFLD was diagnosed on ultrasound criteria for fatty liver, safe-alcohol consumption (<14-units/week for men, <7-units/week for women) and absence of hepatitis B/C markers. Non-NAFLD was diagnosed on absence of any ultrasound criteria for fatty liver and safe-alcohol consumption. Resolution of NAFLD was defined as absence of ultrasound criteria for fatty liver. Changes in anthropometric indices [Weight, Body-Mass-Index (BMI), waist-circumference (WC), waist-hip ratio (WHR)], clinical [systolic blood pressure (SBP), diastolic blood pressure (DBP)] and biochemical measurements [Triglycerides (TG), High Density Lipoprotein (HDL), Total Cholesterol (TC), HbA1c%] at baseline and follow-up were compared. RESULTS:Of the 2985 original study participants, 2148 (71.9%) attended follow-up after 7 years. This included 705 who had NAFLD in 2007 and 834 who did not have NAFLD in 2007. Out of 705 who had NAFLD in 2007, 11(1.6%) changed their NAFLD status due to excess alcohol consumption. After controlling for baseline values, NAFLD patients showed significant reduction in BMI, weight, WHR, HDL and TC levels and increase in HbA1c levels compared to non-NAFLD people. Despite this, none of them had complete resolution of NAFLD. CONCLUSION:We did not find resolution of NAFLD in this general population cohort. The observed improvements in anthropometric, clinical and biochemical measurements were inadequate for resolution of NAFLD