The influence of local waste management culture on individual recycling behavior

The transition towards sustainable consumption and production requires public engagement and support. In this context, understanding the determinants of individual pro-environmental behavior can assist in sustainability policy design, and contribute to explaining cross-country and regional differences in its implementation and effectiveness. This paper examines the influence of local waste management culture on individual recycling behavior. To isolate the impact of location-specific norms, habits and traditions comprising waste management culture from the confounding effect of contemporaneous local economic and social conditions, we use data from over 40,000 domestic immigrants in Greece. Estimating models relating individual recycling activity in the region of current residence to recycling practices in the region of origin, we find robust evidence that region of origin waste management practices have quantitatively and statistically significant influence on individual recycling behavior: a 10 percentage point increase in the prevalence of recycling in the region of origin, increases the probability a subject recycles by 0.9 percentage points. The results suggest that locally prevailing waste management norms and practices influence individual recycling behavior independently of local economic, social and environmental circumstances. Designing effective sustainability policy may need to account for regional variation in norms and preferences, and encourage investment in the development of sustainable waste management culture

Assessing public preferences for a wildfire mitigation policy in Crete, Greece

The increased frequency and severity of wildfires in the Mediterranean region generates significant damages in ecosystems and landscapes while harming human populations. Institutional complexities, along with socioeconomic and demographic changes encouraging development into the wildland-urban interface, rural abandonment, and focus on fire suppression, are increasing the vulnerability and flammability of Mediterranean ecosystems. Developing effective strategies for managing wildfire incidence and its aftermath requires understanding of the public preferences for wildfire policy characteristics. Here we elicit public preferences for wildfire mitigation policies employing a stated choice experiment applied in Crete, Greece. A region with typical Mediterranean landscape experiencing significant development and rural-to-urban migration that disrupts existing fire regimes. We estimate conditional logit, mixed logit and latent class models to study the general public's preferences and willingness to pay for limiting wildfire frequency and agricultural land burnt, maintaining landscape features, and managing post-wildfire recovery. Results of our study show that measures to manage post-wildfire damage are consistently valued as the most positive amongst the sampled respondents, achieving values that range between €25.92 in conditional logit model to €46 in one of the latent classes identified. Improving the landscape quality follows in importance, although it shows more heterogeneity in the responses. The latent class approach allowed to identify that those associated with either the agricultural or the tourism sector of the sampled individuals, displayed significantly different preferences for the proposed attributes. Overall, our findings indicate that there is a strong preference amongst the general public to shift current policies based on suppression towards more integrated approaches dealing both with prevention and post-fire management. The outcomes of this study serve to guide decision makers on targeted management plans based on their audience

Global Globin Network and adopting genomic variant database requirements for thalassemia

\ua9 The Author(s) 2024. Published by Oxford University Press.Thalassemia is one of the most prevalent monogenic disorders in low- and middle-income countries (LMICs). There are an estimated 270 million carriers of hemoglobinopathies (abnormal hemoglobins and/or thalassemia) worldwide, necessitating global methods and solutions for effective and optimal therapy. LMICs are disproportionately impacted by thalassemia, and due to disparities in genomics awareness and diagnostic resources, certain LMICs lag behind high-income countries (HICs). This spurred the establishment of the Global Globin Network (GGN) in 2015 at UNESCO, Paris, as a project-wide endeavor within the Human Variome Project (HVP). Primarily aimed at enhancing thalassemia clinical services, research, and genomic diagnostic capabilities with a focus on LMIC needs, GGN aims to foster data collection in a shared database by all affected nations, thus improving data sharing and thalassemia management. In this paper, we propose a minimum requirement for establishing a genomic database in thalassemia based on the HVP database guidelines. We suggest using an existing platform recommended by HVP, the Leiden Open Variation Database (LOVD) (https://www.lovd.nl/). Adoption of our proposed criteria will assist in improving or supplementing the existing databases, allowing for better-quality services for individuals with thalassemia. Database URL: https://www.lovd.nl/

Ground reaction force, spinal kinematics and their relationship to lower back pain and injury in cricket fast bowling: A review

BACKGROUND: Fast bowlers display a high risk of lower back injury and pain. Studies report factors that may increase this risk, however exact mechanisms remain unclear. OBJECTIVE: To provide a contemporary analysis of literature, up to April 2016, regarding fast bowling, spinal kinematics, ground reaction force (GRF), lower back pain (LBP) and pathology. METHOD: Key terms including biomechanics, bowling, spine and injury were searched within MEDLINE, Google Scholar, SPORTDiscuss, Science Citation Index, OAIster, CINAHL, Academic Search Complete, Science Direct and Scopus. Following application of inclusion criteria, 56 studies (reduced from 140) were appraised for quality and pooled for further analysis. RESULTS: Twelve times greater risk of lumbar injury was reported in bowlers displaying excessive shoulder counter-rotation (SCR), however SCR is a surrogate measure which may not describe actual spinal movement. Little is known about LBP specifically. Weighted averages of 5.8 ± 1.3 times body weight (BW) vertically and 3.2 ± 1.1 BW horizontally were calculated for peak GRF during fast bowling. No quantitative synthesis of kinematic data was possible due to heterogeneity of reported results. CONCLUSIONS: Fast bowling is highly injurious especially with excessive SCR. Studies adopted similar methodologies, constrained to laboratory settings. Future studies should focus on methods to determine biomechanics during live play

TANGLE: Two-Level Support Vector Regression Approach for Protein Backbone Torsion Angle Prediction from Primary Sequences

Protein backbone torsion angles (Phi) and (Psi) involve two rotation angles rotating around the Cα-N bond (Phi) and the Cα-C bond (Psi). Due to the planarity of the linked rigid peptide bonds, these two angles can essentially determine the backbone geometry of proteins. Accordingly, the accurate prediction of protein backbone torsion angle from sequence information can assist the prediction of protein structures. In this study, we develop a new approach called TANGLE (Torsion ANGLE predictor) to predict the protein backbone torsion angles from amino acid sequences. TANGLE uses a two-level support vector regression approach to perform real-value torsion angle prediction using a variety of features derived from amino acid sequences, including the evolutionary profiles in the form of position-specific scoring matrices, predicted secondary structure, solvent accessibility and natively disordered region as well as other global sequence features. When evaluated based on a large benchmark dataset of 1,526 non-homologous proteins, the mean absolute errors (MAEs) of the Phi and Psi angle prediction are 27.8° and 44.6°, respectively, which are 1% and 3% respectively lower than that using one of the state-of-the-art prediction tools ANGLOR. Moreover, the prediction of TANGLE is significantly better than a random predictor that was built on the amino acid-specific basis, with the p-value<1.46e-147 and 7.97e-150, respectively by the Wilcoxon signed rank test. As a complementary approach to the current torsion angle prediction algorithms, TANGLE should prove useful in predicting protein structural properties and assisting protein fold recognition by applying the predicted torsion angles as useful restraints. TANGLE is freely accessible at http://sunflower.kuicr.kyoto-u.ac.jp/~sjn/TANGLE/

Prediction of backbone dihedral angles and protein secondary structure using support vector machines

<p>Abstract</p> <p>Background</p> <p>The prediction of the secondary structure of a protein is a critical step in the prediction of its tertiary structure and, potentially, its function. Moreover, the backbone dihedral angles, highly correlated with secondary structures, provide crucial information about the local three-dimensional structure.</p> <p>Results</p> <p>We predict independently both the secondary structure and the backbone dihedral angles and combine the results in a loop to enhance each prediction reciprocally. Support vector machines, a state-of-the-art supervised classification technique, achieve secondary structure predictive accuracy of 80% on a non-redundant set of 513 proteins, significantly higher than other methods on the same dataset. The dihedral angle space is divided into a number of regions using two unsupervised clustering techniques in order to predict the region in which a new residue belongs. The performance of our method is comparable to, and in some cases more accurate than, other multi-class dihedral prediction methods.</p> <p>Conclusions</p> <p>We have created an accurate predictor of backbone dihedral angles and secondary structure. Our method, called DISSPred, is available online at <url>http://comp.chem.nottingham.ac.uk/disspred/</url>.</p

Heterogeneous and opportunistic wireless networks

Recent years have witnessed the evolution of a large plethora of wireless technologies with different characteristics, as a response of the operators' and users' needs in terms of an efficient and ubiquitous delivery of advanced multimedia services. The wireless segment of network infrastructure has penetrated in our lives, and wireless connectivity has now reached a state where it is considered to be an indispensable service as electricity or water supply. Wireless data networks grow increasingly complex as a multiplicity of wireless information terminals with sophisticated capabilities get embedded in the infrastructure. © 2012 Springer Milan. All Right Reserved

Worthy to Lose Some Money for Better Air Quality: Applications of Bayesian Networks on the Causal Effect of Income and Air Pollution on Life Satisfaction in Switzerland

One important determinant of well-being is the environmental quality. Many countries apply environmental regulations, reforms and policies for its improvement. However, the question is how the people value the environment, including the air quality. This study examines the association between air pollution and life satisfaction using the Swiss Household Panel survey over the years 2000–2013. We follow a Bayesian network (BN) strategy to estimate the causal effect of the income and air pollution on life satisfaction. We look at five main air pollutants: the ground-level ozone (O3), sulphur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO) and particulate matter of 10 micrometres (PM10). Then, we calculate the individuals’ marginal willingness to pay (MWTP) of reducing air pollution that aims to improve their life satisfaction. Beside the BN model, we take advantage of the panel structure of our data and we follow two approaches as robustness check. This includes the adapted probit fixed effects and the generalised methods of moments system. Our findings show that O3 and PM10 present the highest MWTP values ranging between $8000 and$12,000, followed by the remained air pollutants with MWTP extending between $2000 and$6500. Applying the BNs, we find that the causal effect of income on life satisfaction is substantially increased. We also show the causal effects of air pollutants remain almost the same, leading to lower values of willingness to pay

Human activity, daylight saving time and wildfire occurrence

Wildfires shape landscapes and ecosystems, affecting health and infrastructure. Understanding the complex interactions between social organization, human activity and the natural environment that drive wildfire occurrence is becoming increasingly important as changing global environmental conditions combined with the expanding human-wildland interface, are expected to increase wildfire frequency and severity. This paper examines the anthropogenic drivers of wildfire, and the relationship between the organization of human activity in time and wildfire occurrence focusing on the effects of transitions into and out of Daylight Saving Time (DST). DST transitions shift activity in relation to natural wildfire risk within a solar day, induce changes in the time allocated to wildfire-causing activities and disrupt sleep patterns. The paper estimates short and medium run effects of DST-induced changes in the temporal organization of human activity through a Regression Discontinuity Design with time as the running variable and Fixed Effects models, using data from over 1.88 million non-prescribed ignitions recorded in the contiguous US over 23 years. Estimates suggest that DST has a quantitatively and statistically significant immediate and medium-run effect on wildfire occurrence. Wildfire occurrence jumps by around 30% in the immediate aftermath of transitions into DST, adding about 98 human-caused wildfires across the contiguous US per year, while the transition's effect is detectable for 3 weeks. Transitions induce within-day temporal displacement of wildfires in a pattern compatible with the shifting of human activity mechanism, while the result cannot be attributed exclusively on disruptions in sleep patterns. Naturally arising lightning-strike wildfires do not respond to changes in civil time, while the results are robust to changes in assumptions. Results suggest that wildfire policy should account for the temporal organization of human activity

An assessment of the relationship between daylight saving time, disruptions in sleep patterns and dwelling fires

Residential fires pose threats to living environments, generating costs to health and property. Understanding the roles of human behavior and social organization in determining fire occurrence is important for developing strategies to manage fire risk. This paper tests the impact of daylight saving time (DST) transitions on dwelling fire occurrence. DST transitions affect sleep patterns, impairing human cognitive and motor performance, potentially influencing the incidence of dwelling fires. Employing a regression discontinuity design with time as the running variable and using data from over 260,000 primary dwelling fires that took place in the U.K. over 8 years we do not find evidence suggesting that DST transitions impact on dwelling fire occurrence. For both the start of DST and end of DST transitions, estimated effects is quantitatively small and statistically insignificant. Results suggest that disruptions in sleep patterns induced by DST are not a driver of dwelling fires in the U.K