Drinking locations and alcohol-related harm: Cross-sectional and longitudinal associations in a sample of young Swiss men.

BACKGROUND: Alcohol consumption--in particular drinking volume (DV) and risky single occasion drinking (RSOD)--has been related to a wide range of negative consequences and health problems. Previous studies also suggested that drinking in certain locations may be more strongly associated with the occurrence of alcohol-related harm than drinking in others. However, they were conducted in countries culturally and legally different from European countries and were limited to cross-sectional designs. This study investigates the cross-sectional and longitudinal associations of alcohol-related harm with DVs in different locations in a sample of young Swiss men. METHODS: A representative sample of 4536 young Swiss male drinkers completed baseline and 15-month follow-up questionnaires. These assessed DVs in 11 locations, alcohol-related harm (i.e. number of alcohol-related consequences and alcohol use disorder criteria) and frequency of RSOD. Cross-sectional and longitudinal associations of alcohol-related harm with DVs in each location were tested using regression models, with and without adjustment for frequency of RSOD. RESULTS: Both cross-sectional and longitudinal analyses showed significant positive associations between alcohol-related harm and DVs at friends' homes, in discos/nightclubs and in outdoor public places, when controlling for frequency of RSOD. In contrast, the contribution of DVs at one's own home and in restaurants was consistently not significant when adjusted for frequency of RSOD. When controlling for RSOD, associations between alcohol-related harm and DVs in bars/pubs, when playing sports, during other leisure activities, at cinemas/theatres, during sporting events, and during special events were not consistent between cross-sectional and longitudinal analyses. CONCLUSION: Results suggest that prevention interventions should not only target reducing the overall volume of alcohol consumed and the frequency of RSOD in general, but they should additionally focus on limiting alcohol consumption in outdoor public places, discos/nightclubs, and in friends' homes in particular, or at least on preventing harm occurring in these occasions.

Antibody levels against GLURP R2, MSP1 block 2 hybrid and AS202.11 and the risk of malaria in children living in hyperendemic (Burkina Faso) and hypo-endemic (Ghana) areas.

Differences in parasite transmission intensity influence the process of acquisition of host immunity to Plasmodium falciparum malaria and ultimately, the rate of malaria related morbidity and mortality. Potential vaccines being designed to complement current intervention efforts therefore need to be evaluated against different malaria endemicity backgrounds. The associations between antibody responses to the chimeric merozoite surface protein 1 block 2 hybrid (MSP1 hybrid), glutamate-rich protein region 2 (GLURP R2) and the peptide AS202.11, and the risk of malaria were assessed in children living in malaria hyperendemic (Burkina Faso, n = 354) and hypo-endemic (Ghana, n = 209) areas. Using the same reagent lots and standardized protocols for both study sites, immunoglobulin (Ig) M, IgG and IgG sub-class levels to each antigen were measured by ELISA in plasma from the children (aged 6-72 months). Associations between antibody levels and risk of malaria were assessed using Cox regression models adjusting for covariates. There was a significant association between GLURP R2 IgG3 and reduced risk of malaria after adjusting age of children in both the Burkinabe (hazard ratio 0.82; 95 % CI 0.74-0.91, p < 0.0001) and the Ghanaian (HR 0.48; 95 % CI 0.25-0.91, p = 0.02) cohorts. MSP1 hybrid IgM was associated (HR 0.85; 95 % CI 0.73-0.98, p = 0.02) with reduced risk of malaria in Burkina Faso cohort while IgG against AS202.11 in the Ghanaian children was associated with increased risk of malaria (HR 1.29; 95 % CI 1.01-1.65, p = 0.04). These findings support further development of GLURP R2 and MSP1 block 2 hybrid, perhaps as a fusion vaccine antigen targeting malaria blood stage that can be deployed in areas of varying transmission intensity.

Trabecular bone score in kidney transplant recipients.

UNLABELLED: It is uncertain whether bone mineral density (BMD) can accurately predict fracture in kidney transplant recipients. Trabecular bone score (TBS) provides information independent of BMD. Kidney transplant recipients had abnormal bone texture as measured by lumbar spine TBS, and a lower TBS was associated with incident fractures in recipients. INTRODUCTION: Trabecular bone score (TBS) is a texture measure derived from dual energy X-ray absorptiometry (DXA) lumbar spine images, providing information independent of bone mineral density. We assessed characteristics associated with TBS and fracture outcomes in kidney transplant recipients. METHODS: We included 327 kidney transplant recipients from Manitoba, Canada, who received a post-transplant DXA (median 106 days post-transplant). We matched each kidney transplant recipient (mean age 45 years, 39 % men) to three controls from the general population (matched on age, sex, and DXA date). Lumbar spine (L1-L4) DXA images were used to derive TBS. Non-traumatic incident fracture (excluding hand, foot, and craniofacial) (n = 31) was assessed during a mean follow-up of 6.6 years. We used multivariable linear regression models to test predictors of TBS, and multivariable Cox proportional hazard regression was used to estimate hazard ratios (HRs) per standard deviation decrease in TBS to express the gradient of risk. RESULTS: Compared to the general population, kidney transplant recipients had a significantly lower lumbar spine TBS (1.365 ± 0.129 versus 1.406 ± 0.125, P < 0.001). Multivariable linear regression revealed that receipt of a kidney transplant was associated with a significantly lower mean TBS compared to controls (-0.0369, 95 % confidence interval [95 % CI] -0.0537 to -0.0202). TBS was associated with fractures independent of the Fracture Risk Assessment score including BMD (adjusted HR per standard deviation decrease in TBS 1.64, 95 % CI 1.15-2.36). CONCLUSION: Kidney transplant recipients had abnormal bone texture as assessed by TBS and a lower lumbar spine TBS was associated with fractures in recipients.

Contratación de la mano de obra y desempeño en los servicios intensivos en conocimiento: una visión del capital intelectual

Objeto: El desempeño de las actividades de servicios de alto valor añadido ofrecidospor las empresas manufactureras, de la misma forma que el de los servicios intensivosen conocimiento, puede verse afectado por las formas de contratación de la mano deobra utilizadas en ellas. Se estudia el impacto del uso de trabajo contingente (temporal y autónomo) sobre la productividad del trabajo en las empresas de servicios intensivos en conocimiento. Para desarrollar las hipótesis, se tiene en cuenta el impacto potencial del trabajo contingente sobre el capital intangible de la empresa, así como los resultados de la literatura empírica.Diseño/metodología: Se analizan los datos de una muestra de 279 empresas de servicios intensivos en conocimiento localizadas en Cataluña, mediante dos modelos de regresión lineal.Aportaciones y resultados: Los resultados muestran que el empleo de formas de trabajo contingentes, como el trabajo temporal y los trabajadores autónomos, tiene un impacto negativo en la productividad del trabajo. No existe, en cambio, una relación cuadrática entre estas variables. Limitaciones: La muestra utilizada procede exclusivamente de Cataluña (España), noes perfectamente extrapolable al conjunto de empresas de servicios intensivos enconocimiento y se obtuvo en la fase alcista del ciclo económico. El diseño del estudio estransversal. La clasificación de las empresas como intensivas en conocimiento esdicotómica, en función del sector al que pertenecen. Implicaciones prácticas:Las decisiones sobre la contratación de mano de obra en actividades de servicios de alto valor añadido deberían minimizar las formas de trabajocontingentes, si quieren mejorar su productividad.Implicaciones sociales: Un modelo productivo que pretenda potenciar los servicios de mayor valor añadido no puede descansar sobre la base de un mercado laboral en el que las empresas utilizan una elevada proporción de trabajo contingente en su mano de obra. Valor añadido: Este artículo ofrece nuevos datos para a la escasa literatura que relaciona el uso de trabajo contingente con la productividad en el sector de los servicios intensivos en conocimiento. La creciente importancia de los servicios de alto valor añadido, tanto en empresas de servicios como manufactureras, y el interés por conocer los determinantes de su productividad justifican la necesidad de realizar estudios como el que se presenta.

Combining Advanced Forecasting Methods with System Dynamics - the Case of Finnish Seaports

Seaports play an important part in the wellbeing of a nation. Many nations are highly dependent on foreign trade and most trade is done using sea vessels. This study is part of a larger research project, where a simulation model is required in order to create further analyses on Finnish macro logistical networks. The objective of this study is to create a system dynamic simulation model, which gives an accurate forecast for the development of demand of Finnish seaports up to 2030. The emphasis on this study is to show how it is possible to create a detailed harbor demand System Dynamic model with the help of statistical methods. The used forecasting methods were ARIMA (autoregressive integrated moving average) and regression models. The created simulation model gives a forecast with confidence intervals and allows studying different scenarios. The building process was found to be a useful one and the built model can be expanded to be more detailed. Required capacity for other parts of the Finnish logistical system could easily be included in the model.

Tilastollinen tutkimus ohjelmiston laatuun vaikuttavista tekijöistä

Tämä työ on tehty osana MASTO-tutkimushanketta, jonka tarkoituksena on kehittää ohjelmistotestauksen adaptiivinen referenssimalli. Työ toteutettiin tilastollisena tutkimuksena käyttäen survey-menetelmää. Tutkimuksessa haastateltiin 31 organisaatioyksikköä eri puolelta suomea, jotka tekevät keskikriittisiä sovelluksia. Tutkimuksen hypoteeseina oli laadun riippuvuus ohjelmistokehitysmenetelmästä, asiakkaan osallistumisesta, standardin toteutumisesta, asiakassuhteesta, liiketoimintasuuntautuneisuudesta, kriittisyydestä, luottamuksesta ja testauksen tasosta. Hypoteeseista etsittiin korrelaatiota laadun kanssa tekemällä korrelaatio ja regressioanalyysi. Lisäksi tutkimuksessa kartoitettiin minkälaisia ohjelmistokehitykseen liittyviä käytäntöjä, menetelmiä ja työkaluja organisaatioyksiköissä käytettiin, ongelmia ja parannusehdotuksia liittyen ohjelmistotestaukseen, merkittävimpiä tapoja asiakkaan vaikuttamiseksi ohjelmiston laatuun sekä suurimpia hyötyjä ja haittoja ohjelmistokehityksen tai testauksen ulkoistamisessa. Tutkimuksessa havaittiin, että laatu korreloi positiivisesti ja tilastollisesti merkitsevästi testauksen tason, standardin toteutumisen, asiakasosallistumisen suunnitteluvaiheessa sekä asiakasosallistumisen ohjaukseen kanssa, luottamuksen ja yhden asiakassuhteeseen liittyvän osakysymyksen kanssa. Regressioanalyysin perusteella muodostettiin regressioyhtälö, jossa laadun todettiin positiivisesti riippuvan standardin toteutumisesta, asiakasosallistumisesta suunnitteluvaiheessa sekä luottamuksesta.

The effect on prices of the attributes of holiday hotels: a hedonic prices approach

This article examines the effect on price of different characteristics of holiday hotels in the sun-and-beach segment. The effect on price is estimated under the hedonic function perspective by means of random effect models, known also as mixed or panel models. Some 82,000 prices were gathered between 1991 and 1998 from tour operator catalogues. The study reveals huge price differences between 4-star hotels and the rest, coupled with practically no difference between 1-star and 2-star hotels. Other attributes with a significant effect on price are town, hotel size, distance to the beach and availability of parking place. The results can assist hotel managers in shaping pricing and investment strategies

Swarm Intelligent Selection and Optimization of Machining System Parameters for Microchannel Fabrication in Medical Devices

Current technology trends in medical device industry calls for fabrication of massive arrays of microfeatures such as microchannels on to nonsilicon material substrates with high accuracy, superior precision, and high throughput. Microchannels are typical features used in medical devices for medication dosing into the human body, analyzing DNA arrays or cell cultures. In this study, the capabilities of machining systems for micro-end milling have been evaluated by conducting experiments, regression modeling, and response surface methodology. In machining experiments by using micromilling, arrays of microchannels are fabricated on aluminium and titanium plates, and the feature size and accuracy (width and depth) and surface roughness are measured. Multicriteria decision making for material and process parameters selection for desired accuracy is investigated by using particle swarm optimization (PSO) method, which is an evolutionary computation method inspired by genetic algorithms (GA). Appropriate regression models are utilized within the PSO and optimum selection of micromilling parameters; microchannel feature accuracy and surface roughness are performed. An analysis for optimal micromachining parameters in decision variable space is also conducted. This study demonstrates the advantages of evolutionary computing algorithms in micromilling decision making and process optimization investigations and can be expanded to other applications

Capital Structure of Finnish SMEs and Financial Constraints

This thesis studies capital structure of Finnish small and medium sized enterprises. The specific object of the study is to test whether financial constraints have an effect on capital structure. In addition influences of several other factors were studied. Capital structure determinants are formulated based on three capital structure theories. The tradeoff theory and the agency theory concentrate on the search of optimal capital structure. The pecking order theory concerns favouring on financing source over another. The data of this study consists of financial statement data and results of corporate questionnaire. Regression analysis was used to find out the effects of several determinants. Regression models were formed based on the presented theories. Short and long term debt ratios were considered separately. The metrics of financially constrained firms was included in all models. It was found that financial constrains have a negative and significant effect to short term debt ratios. The effect was negative also to long term debt ratio but not statistically significant. Other considerable factors that influenced debt ratios were fixed assets, age, profitability, single owner and sufficiency of internal financing.

Commodity Price Driven Risk Management from Viewpoint of High Grade Steel Alloys

The study of price risk management concerning high grade steel alloys and their components was conducted. This study was focused in metal commodities, of which nickel, chrome and molybdenum were in a central role. Also possible hedging instruments and strategies for referred metals were studied. In the literature part main themes are price formation of Ni, Cr and Mo, the functioning of metal exchanges and main hedging instruments for metal commodities. This section also covers how micro and macro variables may affect metal prices from the viewpoint of short as well as longer time period. The experimental part consists of three sections. In the first part, multiple regression model with seven explanatory variables was constructed to describe price behavior of nickel. Results were compared after this with information created with comparable simple regression model. Additionally, long time mean price reversion of nickel was studied. In the second part, theoretical price of CF8M alloy was studied by using nickel, ferro-chrome and ferro-molybdenum as explanatory variables. In the last section, cross hedging possibilities for illiquid FeCr -metal was studied with five LME futures. Also this section covers new information concerning possible forthcoming molybdenum future contracts as well. The results of this study confirm, that linear regression models which are based on the assumption of market rationality, are not able to reliably describe price development of metals at issue. Models fulfilling assumptions for linear regression may though include useful information of statistical significant variables which have effect on metal prices. According to the experimental part, short futures were found to incorporate the most accurate information concerning the price movements in the future. However, not even 3M futures were able to predict turning point in the market before the faced slump. Cross hedging seemed to be very doubtful risk management strategy for illiquid metals, because correlations coefficients were found to be very sensitive for the chosen time span.

Determinação de açúcar total em café cru por espectroscopia no infravermelho próximo e regressão por mínimos quadrados parciais

In this work a fast method for the determination of the total sugar levels in samples of raw coffee was developed using the near infrared spectroscopy technique and multivariate regression. The sugar levels were initially obtained using gravimety as the reference method. Later on, the regression models were built from the near infrared spectra of the coffee samples. The original spectra were pre-treated according to the Kubelka-Munk transformation and multiplicative signal correction. The proposed analytical method made possible the direct determination of the total sugar levels in the samples with an error lower by 8% with respect to the conventional methodology.

Clinical consequences of switching from olanzapine to risperidone and vice versa in outpatients with schizophrenia: 36-month results from the worldwide schizophrenia outpatients health outcomes (W-SOHO) study

BACKGROUND: With many atypical antipsychotics now available in the market, it has become a common clinical practice to switch between atypical agents as a means of achieving the best clinical outcomes. This study aimed to examine the impact of switching from olanzapine to risperidone and vice versa on clinical status and tolerability outcomes in outpatients with schizophrenia in a naturalistic setting. METHODS: W-SOHO was a 3-year observational study that involved over 17,000 outpatients with schizophrenia from 37 countries worldwide. The present post hoc study focused on the subgroup of patients who started taking olanzapine at baseline and subsequently made the first switch to risperidone (n=162) and vice versa (n=136). Clinical status was assessed at the visit when the first switch was made (i.e. before switching) and after switching. Logistic regression models examined the impact of medication switch on tolerability outcomes, and linear regression models assessed the association between medication switch and change in the Clinical Global Impression-Schizophrenia (CGI-SCH) overall score or change in weight. In addition, Kaplan-Meier survival curves and Cox-proportional hazards models were used to analyze the time to medication switch as well as time to relapse (symptom worsening as assessed by the CGI-SCH scale or hospitalization). RESULTS: 48% and 39% of patients switching to olanzapine and risperidone, respectively, remained on the medication without further switches (p=0.019). Patients switching to olanzapine were significantly less likely to experience relapse (hazard ratio: 3.43, 95% CI: 1.43, 8.26), extrapyramidal symptoms (odds ratio [OR]: 4.02, 95% CI: 1.49, 10.89) and amenorrhea/galactorrhea (OR: 8.99, 95% CI: 2.30, 35.13). No significant difference in weight change was, however, found between the two groups. While the CGI-SCH overall score improved in both groups after switching, there was a significantly greater change in those who switched to olanzapine (difference of 0.29 points, p=0.013). CONCLUSION: Our study showed that patients who switched from risperidone to olanzapine were likely to experience a more favorable treatment course than those who switched from olanzapine to risperidone. Given the nature of observational study design and small sample size, additional studies are warranted.

Predictors of remission in the treatment of major depressive disorder: real-world evidence from a 6-month prospective observational study

BACKGROUND: This study examined potential predictors of remission among patients treated for major depressive disorder (MDD) in a naturalistic clinical setting, mostly in the Middle East, East Asia, and Mexico. METHODS: Data for this post hoc analysis were taken from a 6-month prospective, noninterventional, observational study that involved 1,549 MDD patients without sexual dysfunction at baseline in 12 countries worldwide. Depression severity was measured using the Clinical Global Impression of Severity and the 16-item Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR16). Depression-related pain was measured using the pain-related items of the Somatic Symptom Inventory. Remission was defined as a QIDS-SR16 score ≤5. Generalized estimating equation regression models were used to examine baseline factors associated with remission during follow-up. RESULTS: Being from East Asia (odds ratio [OR] 0.48 versus Mexico; P<0.001), a higher level of depression severity at baseline (OR 0.77, P=0.003, for Clinical Global Impression of Severity; OR 0.92, P<0.001, for QIDS-SR16), more previous MDD episodes (OR 0.92, P=0.007), previous treatments/therapies for depression (OR 0.78, P=0.030), and having any significant psychiatric and medical comorbidity at baseline (OR 0.60, P<0.001) were negatively associated with remission, whereas being male (OR 1.29, P=0.026) and treatment with duloxetine (OR 2.38 versus selective serotonin reuptake inhibitors, P<0.001) were positively associated with remission. However, the association between Somatic Symptom Inventory pain scores and remission no longer appeared to be significant in this multiple regression (P=0.580), (P=0.008 in descriptive statistics), although it remained significant in a subgroup of patients treated with selective serotonin reuptake inhibitors (OR 0.97, P=0.023), but not in those treated with duloxetine (P=0.182). CONCLUSION: These findings are largely consistent with previous reports from the USA and Europe. They also highlight the potential mediating role of treatment with duloxetine on the negative relationship between depression-related pain and outcomes of depression.

Air pollution and emergency admissions for cardiorespiratory diseases in Lisbon (Portugal)

Daily records of hospital admissions due to cardiorespiratory diseases and levels of PM10, SO2, CO, NO, NO2, and O3 were collected from 1999-2004 to evaluate the relationship between air pollution and morbidity in Lisbon. Generalised additive Poisson regression models were adopted, controlling for temperature, humidity, and both short and long-term seasonality. Significant positive associations, lagged by 1 or 2 days, were found between markers of traffic-related pollution (CO and NO2) and cardiocirculatory diseases in all age groups. Increased childhood emergency admissions for respiratory illness were significantly correlated with the 1-day lagged SO2 levels coming from industrial activities.

Analysis of patterns in mining time series using Qlucore

Raw measurement data does not always immediately convey useful information, but applying mathematical statistical analysis tools into measurement data can improve the situation. Data analysis can offer benefits like acquiring meaningful insight from the dataset, basing critical decisions on the findings, and ruling out human bias through proper statistical treatment. In this thesis we analyze data from an industrial mineral processing plant with the aim of studying the possibility of forecasting the quality of the final product, given by one variable, with a model based on the other variables. For the study mathematical tools like Qlucore Omics Explorer (QOE) and Sparse Bayesian regression (SB) are used. Later on, linear regression is used to build a model based on a subset of variables that seem to have most significant weights in the SB model. The results obtained from QOE show that the variable representing the desired final product does not correlate with other variables. For SB and linear regression, the results show that both SB and linear regression models built on 1-day averaged data seriously underestimate the variance of true data, whereas the two models built on 1-month averaged data are reliable and able to explain a larger proportion of variability in the available data, making them suitable for prediction purposes. However, it is concluded that no single model can fit well the whole available dataset and therefore, it is proposed for future work to make piecewise non linear regression models if the same available dataset is used, or the plant to provide another dataset that should be collected in a more systematic fashion than the present data for further analysis.