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A collection of all-original stories set in the Black Tide Rising series of novels created by multiple New York Times best-selling author John Ringo Stories by John Ringo, Eric Flint, John Scalzi & Dave Klecha, Sarah A. Hoyt, Jody Lynn Nye, Michael Z. Williamson and more. The news that humanity had been dreading for ages had come true. Zombies are real. Worst of all, we created them. The apocalypse was upon us, and every man, woman and child had to answer a simple question of themselves: \"What do we do now?\" For a group of neighbors in the Chicago suburbs of Northern Indiana, it was \"work together or die\"...and figure out how to live on top of oil storage tanks to keep the zombies at bay. For the Biological Emergency Response Teams in New York City, it was \"how long can we fight off the infected before it's too late\".as well as having to fight other groups all out to claim a dwindling stock of supplies and safety. And for a group of cheerleaders, it was about the end of their world. And about what happens when you get a group of physically fit young women really, really angry. Featuring original stories from some of the brightest stars in the science fiction universe: John Ringo; Eric Flint, John Scalzi & Dave Klecha, Sarah A. Hoyt, Jody Lynn Nye, Michael Z. Williamson, Kacey Ezella--cheerleading coach, veteran, and helicopter pilot--and more\"-- Provided by publisher.

Surface water quality parameters are important means for determination of water’s suitability for irrigation. In this research, data from 32 irrigation stations were used to calculate the sodium adsorption rate (SAR), sodium percentage (Na%), Kelly index (KI), permeability index (PI) and irrigation water quality index (IWQI) for evaluation of surface water quality. The obtained SAR, KI and Na% values, respectively, varied between 0.10 and 9.43, 0.03–1.37 meq/l and 3.16–57.82%. The calculated PI values indicate that, 93.75% of the water samples is in “suitable” category, and 6.25% is in “non-suitable” category. The IWQI values obtained from the research area varied between 30.59 and 81.09. In terms of irrigation water quality, 12.5% of the samples is of “good” quality, 15.62% is of “poor” quality, 68.75% is of “very poor” quality, and 3.12% is of “non-suitable” quality. Accordingly, IWQI value was estimated on the basis of SAR, Na%, KI and PI values using multiple regression and artificial neural network (ANN) model. The regression coefficient (R2) was determined as 0.6 in multiple regression analysis, and a moderately significant relationship (p < 0.05) was detected. As the calculated F value was higher than the tabulated F value, a real relationship between the dependent and independent variables is inferred. Four different models were built with ANN, and the statistical performance of the models was determined using statistical parameters such as average value (µ), standard error (SE), standard deviation (σ), R2, root mean square error (RMSE) and mean absolute percentage error (MAPE). The training R2 value belonging to the best model was found to be significantly high (0.99). The relation between the estimation results of ANN model and the experimental data (R2 = 0.92) verifies the model’s success. As a result, ANN proved to be a successful means for IWQI estimation using different water quality parameters.

Individual personality traits are powerful determinants of behavior, and they can profoundly influence consumer decisions as a comprehensive understanding of consumer personality traits. Their role in decision-making can improve the predictability of consumer-related behavior. In this study, data on consumers’ preferences and personality traits were collected through questionnaires using the Wood Furniture Product Characteristics Consumer Preference Scale and the Big Five Personality Inventory Simplified. Bivariate correlation analysis and stepwise multiple regression analysis were used to investigate the relationship between the Big Five personality traits (neuroticism, extraversion, openness, agreeableness, and conscientiousness) and wood furniture product characteristics consumer preferences. Correlation analysis indicated that neuroticism was correlated negatively with wood furniture product characteristic consumer preference scores. Extraversion, agreeableness, and conscientiousness were correlated positively with wood furniture product characteristic consumer preference scores. There was no correlation between openness and consumer preference. Regression analysis indicated that neuroticism, extraversion, agreeableness, and conscientiousness predicted wood furniture product trait consumer preferences. Overall, assessing personality traits can help provide insight into the psychological and behavioral characteristics of consumers when purchasing wood furniture products, allowing for a more comprehensive understanding of market demand and more effective marketing and product positioning strategies.

To identify sociodemographic and illness-related factors associated with quality of life among people with Schizophrenia. A hospital-based cross-sectional study design was employed among 351 people with schizophrenia and attending the followup service at Jimma University Medical Center, psychiatric clinic during the study period. Participants were recruited using a systematic random sampling method and a sample fraction of two was used after the first person was identified by a lottery method. Data entry was done using EpiData version 3.1 and then exported to Statistical Package for Social Sciences version 25 for analysis. Multiple regression analysis was used to determine the statistically significant association between quality of life and independent variables. Among the four domains of quality of life, respondents scored the lowest mean in the social relationships domain (10.14 ± 3.12). Final adjusted multiple regression model revealed, being divorced was negatively associated with the physical domain (β = -0.72, p = 0.02), having no formal education was negatively associated with physical health domain (β = -0.69, p = 0.001) and age was positively associated with the psychological domain (β = 0.371, p = 0.071). Being rural resident was negatively associated with physical domain (β = -0.48, p = 0.01), with environmental domain (β = -0.64, p = 0.03), with social relationships domain (β = -0.45, p = 0.04), and with overall quality of life (β = -1.93, p = 0.006). Positive symptoms (β = -0.22, p = 0.001), negative symptoms (β = -0.36, p = 0.001), and general psychopathology (β = -0.098, p = 0.006) were inversely associated with overall quality of life. In this study, the social relationship domain of quality of life among people with schizophrenia has the lowest mean score. Some socio-demographic variables and psychiatric symptoms were found to be key significant associated factors of quality of life. Priority interventions to improve the social deficits and addressing psychiatric symptoms of people with schizophrenia is essential to improve their quality of life.

The water-conducting fractured zone induced by mining under aquifers is channels for water and sand inrushes. A method based on multiple regression analysis and a geographic information system (GIS) is proposed to predict the height of the water-conducting fractured zone in this paper. Five main indicators are found to control the height of the water-conducting fractured zone during fully mechanized caving mining under aquifers in which the thickness of the coal seam is more than 3 m: thickness of the coal seam, proportion of hard rock, length of the panel, mined depth and dip angle. The height of water-conducting fractured zone and the predictive variables from eighteen coal mines in China are investigated. Based on information entropy theory, a nonlinear multiple regression model and the weight of the indicators are considered, and the nonlinear multiple regression model is used in the GIS. Then, the approach is validated with a case study of the Xiegou Coalmine in the Shanxi province of China, in which the thickness of the coal seam which is under aquifers is more than 3 m. Error analysis of the approach is calculated with different hydrogeology classification. The results indicate that this model is a useful tool for predicting and analyzing the height of the water-conducting fractured zone, since the height of the water-conducting fractured zone can be quantitatively calculated and visualized.

International business researchers commonly estimate proportions, percentages, rates, or fractions – so-called “proportional dependent variables”. In this paper, we posit that two regression strategies are particularly pertinent to the international business field: Tobit and fractional regression. Reviewing recent international business research, we find that, while fractional regression is rarely used, analyses from Tobit regression are often incomplete or erroneously interpreted with consequences for the validity of the reported results. Accordingly, we clarify how researchers should choose between Tobit and fractional regression and interpret their results. We present insights based on simple simulations and data examples with associated Stata code and a decision tree for choosing between types of models for use with proportional dependent variables.

More and better collaboration between farmers and other stakeholders has repeatedly been identified as a key strategy for sustainable agriculture. However, for collaboration to actually benefit sustainable agriculture certain conditions have to be met. In this paper, we scrutinize the conditions that support or hamper the success of collaborative efforts in the context of sustainable agriculture. For this purpose, we conducted an exploratory case study meta-analysis to consolidate insights from 30 case studies on local and regional collaborative groups for a more sustainable agriculture in the EU. Through multiple regression analysis, we evaluated which factors influence the 'success' of such collaboratives. Thereby, we measured success through five explicit and comprehensive success criteria. We found two external, five actor-related, and five organization and management-related factors to decisively influence the different success criteria. Overall, our results highlight that collaboration success requires defining priorities as for each of the success criteria a different set of factors is decisive. Although our results showed trade-offs between the achievement of social and economic goals, it is possible to pursue some success criteria simultaneously. Furthermore, our results give reason to be optimistic about the performance of collaboratives: internal factors, which are in the hand of the collaboratives, are likely to be of greater importance than uncontrollable external conditions. Additionally, conditions encountered at the outset of a collaborative matter less than the way these conditions develop toward later stages. Thus, rather than depending on external and predefined conditions, success largely depends on the agency within the collaboratives.

Great uncertainty exists in the global exchange of carbon between the atmosphere and the terrestrial biosphere. An important source of this uncertainty lies in the dependency of photosynthesis on the maximum rate of carboxylation (Vcmax) and the maximum rate of electron transport (Jmax). Understanding and making accurate prediction of C fluxes thus requires accurate characterization of these rates and their relationship with plant nutrient status over large geographic scales. Plant nutrient status is indicated by the traits: leaf nitrogen (N), leaf phosphorus (P), and specific leaf area (SLA). Correlations between Vcmax and Jmax and leaf nitrogen (N) are typically derived from local to global scales, while correlations with leaf phosphorus (P) and specific leaf area (SLA) have typically been derived at a local scale. Thus, there is no global‐scale relationship between Vcmax and Jmax and P or SLA limiting the ability of global‐scale carbon flux models do not account for P or SLA. We gathered published data from 24 studies to reveal global relationships of Vcmax and Jmax with leaf N, P, and SLA. Vcmax was strongly related to leaf N, and increasing leaf P substantially increased the sensitivity of Vcmax to leaf N. Jmax was strongly related to Vcmax, and neither leaf N, P, or SLA had a substantial impact on the relationship. Although more data are needed to expand the applicability of the relationship, we show leaf P is a globally important determinant of photosynthetic rates. In a model of photosynthesis, we showed that at high leaf N (3 gm−2), increasing leaf P from 0.05 to 0.22 gm−2 nearly doubled assimilation rates. Finally, we show that plants may employ a conservative strategy of Jmax to Vcmax coordination that restricts photoinhibition when carboxylation is limiting at the expense of maximizing photosynthetic rates when light is limiting. Great uncertainty exists in the global exchange of carbon between the atmosphere and the terrestrial biosphere. To reduce this uncertainty we analysed data collected in the literature from across the globe on the maximum rate of carboxylation (Vcmax) and the maximum rate of electron transport (Jmax) in relation to plant nutrient status indicated by the traits: leaf nitrogen (N), leaf phosphorus (P), and specific leaf area (SLA). Vcmax was strongly related to leaf N and increasing leaf P substantially increased the sensitivity of Vcmax to leaf N and in a model of photosynthesis we showed that at high leaf N (3 gm−2) increasing leaf P from 0.05 to 0.22 gm−2 nearly doubled assimilation rates. Finally we show that plants may employ a conservative strategy of Jmax to Vcmax co‐ordination that restricts photoinhibition when carboxylation is limiting at the expense of maximising photosynthetic rates when light is limiting.

Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to construct standardized logistic regression coefficients, there is now sufficient evidence to suggest a single best approach to the construction of a standardized logistic regression coefficient 1 that can be used in the same way across a broad range of problems as the standardized linear regression coefficient and also to suggest the adequacy of other approaches for limited purposes. This article reviews the state of knowledge regarding the use of standardized coefficients in general and standardized logistic regression coefficients in particular, and makes specific recommendations on how to best use (and avoid abusing) standardized logistic regression coefficients.

Allostatic load (AL) is a surrogate of the physiological response to stress and reflects the 'wear and tear' on the body. Previous studies indicated that socioeconomic and behavioral determinants influence AL, which in turn is associated with health outcomes. Therefore, AL is increasingly used to operationalize the relationship between social inequality, stress, and health outcomes. This study aimed to investigate associated factors and patterns of AL in the population over a 20-year period using data from the CARLA cohort. The analysis included 473 participants from the CARLA study (Cardiovascular Disease, Living and Ageing in Halle), aged 45-80 years at baseline. From recruitment in 2002 in Halle (Saale), three follow-up examinations took place until 2022. We calculated AL scores as the sum of standardized z-scores for metabolic, immune, cardiovascular, and anthropometric components. Descriptive statistics of AL scores were stratified by sex and age categories. Multiple regression analyses were conducted for the first and third follow-up to assess if there were changes in associations between sociodemographic factors and AL. Average AL scores of men decreased, while women's AL scores returned to baseline levels after an initial decrease observed at the first follow-up. Stratified analyses of AL scores revealed that women in the younger age cohorts had lower mean AL scores at baseline than men (women: -3.47, 95% CI [-4.24; -2.71] vs. men: -1.13, 95% CI [-1.84; -0.42] at age <55). At the same time, women showed higher mean AL scores than men in older age cohorts (women: -0.32, 95% CI [-1.58; 0.95] vs. men: -0.93, 95% CI [-1.99; 0.14] at age 65-<70). Results of multiple regression models indicated lower AL scores for women (β: -1.21, 95% CI [-1.93, -0.49]). Professional status was associated with lower AL scores for men but not for women (β: -1.06, 95% CI [-2.02, -0.11] for men). Further, physical activity was negatively associated with AL scores for the total study sample and for women (β: -0.54, 95% CI [-0.82, -0.26]) for total sample and β: -0.74, 95% CI [-1.17, -0.32] for women). Our results highlight the importance of health awareness and physical activity for overall health, assessed by AL. Distinct AL score changes and sex-specific socioeconomic influences offer insights into sex-related patterns of aging. Further research is needed to understand the underlying mechanisms of socioeconomic influences on stress-related aging processes between sexes.