Finite element analysis of artificial hip joint movement during human activities

The range of motion of artificial hip joint during human activities, measured from the postoperative total hip arthroplasty patients, has been reported previously. There were two human activities discussed, i.e. Western-style and Japanese-style. This paper analyzes the hip joint movement during human activities, based on the measured range of motion, using finite element simulation. The Western-style activities consist of picking up, getting up and sitting, while the Japanese-style activities consist of sitting on legs with fully flexed at the knee (seiza), squatting and sitting on legs with fully flexed at the knee (zarei). The aim of this study is to investigate the probability of prosthetic impingement to occur and to calculate the von Mises stress during the activities. A three-dimensional nonlinear finite element (FE) method was used in the simulation. The acetabular liner cup positions were varied. Results show that in the Western-style activities, the picking up activity induces prosthetic impingement in a certain acetabular liner cup position, whereas in the Japanese-style activities there is no prosthetic impingement observed. However, the Japanese's Zarei activity has a critical value in the range of motion. The von Mises stresses during the prosthetic impingement have been shown and the value is higher than the yield stress of the material

Super-Sentinel Chickens and Detection of Low-Pathogenicity Influenza Virus

Chicken interferon-α administered perorally in drinking water acts on the oropharyngeal mucosal system as an adjuvant that causes chickens to rapidly seroconvert after natural infection by low-pathogenicity Influenza virus. These chickens, termed super sentinels, can serve as sensitive early detectors of clinically inapparent infections

Dynamic shipments of inventories in shared warehouse and transportation networks

In shared warehouse and transportation networks, dynamic shipments of inventories are carried out based on up-to-date inventory information. This paper studies the effect of network structures on optimal decision-making. We propose a discrete time modeling framework with stochastic demand, capturing a wide variety of network structures. Using Markov decision processes, we obtain optimal order and dynamic shipment decisions for small networks. We compare optimal solutions of different four-node network structures. Results indicate product characteristics significantly influence the effectiveness of network structures. Surprisingly, two-echelon networks are occasionally costlier than any other network. Moreover, dynamic shipments yield considerable gains over static shipments

Are lower urinary tract symptoms in men associated with cardiovascular diseases in a primary care population:a registry study

BACKGROUND: Although lower urinary tract symptoms (LUTS) seem to be related to cardiovascular disease (CVD) in men, it is unclear whether this relationship is unbiased. In order to investigate this relationship, we used longitudinal data for establishing the possible predictive value of LUTS for the development of CVD in a primary care population. METHODS: We performed a registry study using data from the Registration Network Groningen (RNG). All data from men aged 50 years and older during the study period from 1 January 1998 up to 31 December 2008 were collected. Cox proportional hazard regression analysis was used to determine the association between the proportions of CVD (outcome) and LUTS in our population. RESULTS: Data from 6614 men were analysed. The prevalence of LUTS increased from 92/1000 personyears (py) in 1998 up to 183/1000 py in 2008. For cardiovascular diseases the prevalence increased from 176/1000 py in 1998 up to 340/1000 py in 2008. The incidence numbers were resp. 10.2/1000 py (1998) and 5.1/1000 py (2008) for LUTS, and 12.9/1000 py (1998) and 10.4/1000 py (2008) for CVD. Of all men, 23.2% reported CVD (41.1% in men with LUTS vs 19.5% in men without LUTS, p < 0.01). The hazard ratio of LUTS for cardiovascular events, compared to no LUTS, in the adjusted multivariate model, was 0.921(95% CI: 0.824 - 1.030; p = 0.150). CONCLUSION: Based on the results, LUTS is not a factor that must be taken into account for the early detection of CVD in primary care

Hepatitis E virus sequences in swine related to sequences in humans, The Netherlands.

Hepatitis E virus (HEV), a major cause of viral hepatitis in much of the developing world, has recently been detected in swine in North America and Asia, raising concern about potential for zoonotic transmission. To investigate if HEV is commonly present in swine in the Netherlands, pooled stool samples from 115 swine farms and nine individual pigs with diarrhea were assayed by reverse transcription-polymerase chain reaction (RT-PCR) amplification. HEV RNA was detected by RT-PCR and hybridization in 25 (22%) of the pooled specimens, but in none of the individual samples. RT-PCR amplification products of open reading frames 1 and 2 were sequenced, and the results were compared with published sequences of HEV genotypes from humans and swine. HEV strains from swine in the Netherlands were clustered in at least two groups, together with European and American isolates from swine and humans. Our data show that HEV in swine in the Netherlands are genetically closely related to HEV isolates from humans. Although zoonotic transmission has not been proven, these findings suggest that swine may be reservoir hosts of HEV

Improving predictive performance on survival in dairy cattle using an ensemble learning approach

Cow survival is a complex trait that combines traits like milk production, fertility, health and environmental factors such as farm management. This complexity makes survival difficult to predict accurately. This is probably the reason why few studies attempted to address this problem and no studies are published that use ensemble methods for this purpose. We explored if we could improve prediction of cow survival to second lactation, when predicted at five different moments in a cow's life, by combining the predictions of multiple (weak) methods in an ensemble method. We tested four ensemble methods: majority voting rule, multiple logistic regression, random forest and naive Bayes. Precision, recall, balanced accuracy, area under the curve (AUC) and gains in proportion of surviving cows in a scenario where the best 50% were selected were used to evaluate the ensemble model performance. We also calculated correlations between the ensemble models and obtained McNemar's test statistics. We compared the performance of the ensemble methods against those of the individual methods. We also tested if there was a difference in performance metrics when continuous (from 0 to 1) and binary (0 or 1) prediction outcomes were used. In general, using continuous prediction output resulted in higher performance metrics than binary ones. AUCs for models ranged from 0.561 to 0.731, with generally increasing performance at moments later in life. Precision, AUC and balanced accuracy values improved significantly for the naive Bayes and multiple logistic regression ensembles in at least one data set, although performance metrics did remain low overall. The multiple logistic regression ensemble method resulted in equal or better precision, AUC, balanced accuracy and proportion of animals surviving on all datasets and was significantly different from the other ensembles in three out of five moments. The random forest ensemble method resulted in the least significant improvement over the individual methods