Miracle-dz/UniFAR-FTUs huggingface dataset:
Emission of greenhouse gases from home aerobic composting, anaerobic digestion and vermicomposting of household wastes in Brisbane (Australia)

This study investigated greenhouse gas (GHG) emissions from three different home waste treatment methods in Brisbane, Australia. Gas samples were taken monthly from 34 backyard composting bins from January to April 2009. Averaged over the study period, the aerobic composting bins released lower amounts of CH4 (2.2 mg m- 2 h-1) than the anaerobic digestion bins (9.5 mg m-2 h-1) and the vermicomposting bins (4.8 mg m-2 h -1). The vermicomposting bins had lower N2O emission rates (1.2 mg m-2 h- 1) than the others (1.5—1.6 mg m-2 h -1). Total GHG emissions including both N2O and CH4 were 463, 504 and 694 mg CO2-e m- 2 h-1 for vermicomposting, aerobic composting and anaerobic digestion, respectively, with N2O contributing >80% in the total budget. The GHG emissions varied substantially with time and were regulated by temperature, moisture content and the waste properties, indicating the potential to mitigate GHG emission through proper management of the composting systems. In comparison with other mainstream municipal waste management options including centralized composting and anaerobic digestion facilities, landfilling and incineration, home composting has the potential to reduce GHG emissions through both lower on-site emissions and the minimal need for transportation and processing. On account of the lower cost, the present results suggest that home composting provides an effective and feasible supplementary waste management method to a centralized facility in particular for cities with lower population density such as the Australian cities.
Effect of Adding McKenzie Syndrome, Centralization, Directional Preference, and Psychosocial Classification Variables to a Risk-Adjusted Model Predicting Functional Status Outcomes for Patients With Lumbar Impairments.

Study Design Retrospective cohort. Background Patient-classification subgroupings may be important prognostic factors explaining outcomes. Objectives To determine effects of adding classification variables (McKenzie syndrome and pain patterns, including centralization and directional preference; Symptom Checklist Back Pain Prediction Model [SCL BPPM]; and the Fear-Avoidance Beliefs Questionnaire subscales of work and physical activity) to a baseline risk-adjusted model predicting functional status (FS) outcomes. Methods Consecutive patients completed a battery of questionnaires that gathered information on 11 risk-adjustment variables. Physical therapists trained in Mechanical Diagnosis and Therapy methods classified each patient by McKenzie syndromes and pain pattern. Functional status was assessed at discharge by patient-reported outcomes. Only patients with complete data were included. Risk of selection bias was assessed. Prediction of discharge FS was assessed using linear stepwise regression models, allowing 13 variables to enter the model. Significant variables were retained in subsequent models. Model power (R(2)) and beta coefficients for model variables were estimated. Results Two thousand sixty-six patients with lumbar impairments were evaluated. Of those, 994 (48%), 10 (<1%), and 601 (29%) were excluded due to incomplete psychosocial data, McKenzie classification data, and missing FS at discharge, respectively. The final sample for analyses was 723 (35%). Overall R(2) for the baseline prediction FS model was 0.40. Adding classification variables to the baseline model did not result in significant increases in R(2). McKenzie syndrome or pain pattern explained 2.8% and 3.0% of the variance, respectively. When pain pattern and SCL BPPM were added simultaneously, overall model R(2) increased to 0.44. Although none of these increases in R(2) were significant, some classification variables were stronger predictors compared with some other variables included in the baseline model. Conclusion The small added prognostic capabilities identified when combining McKenzie or pain-pattern classifications with the SCL BPPM classification did not significantly improve prediction of FS outcomes in this study. Additional research is warranted to investigate the importance of classification variables compared with those used in the baseline model to maximize predictive power. Level of Evidence Prognosis, level 4. J Orthop Sports Phys Ther 2016;46(9):726-741. Epub 31 Jul 2016. doi:10.2519/jospt.2016. 6266.
Economics of Education and Education Policymaking Processes in Pakistan: A critical Review

A number of critical economic issues are discussed linked to education; such as equity, productivity, public expenditure, regional and class divide, choice and competition, market failure, externalities. Different perspectives on impact of education and how education should be produced and financed are analyzed. Educational Policy making processes in Pakistan is critically assessed in its historical perspective. Recommendations derive out of analyzes that are immediate end to apartheid educational system, decrease inequality, increase public expenditure, more social justice, humanist inclined, less bureaucratic system should be devolved which can serve the society in best way.
Level-dependent coronal and axial moment-rotation corridors of degeneration-free cervical spines in lateral flexion.

BACKGROUND Aging, trauma, or degeneration can affect intervertebral kinematics. While in vivo studies can determine motions, moments are not easily quantified. Previous in vitro studies on the cervical spine have largely used specimens from older individuals with varying levels of degeneration and have shown that moment-rotation responses under lateral bending do not vary significantly by spinal level. The objective of the present in vitro biomechanical study was, therefore, to determine the coronal and axial moment-rotation responses of degeneration-free, normal, intact human cadaveric cervicothoracic spinal columns under the lateral bending mode. METHODS Nine human cadaveric cervical columns from C2 to T1 were fixed at both ends. The donors had ranged from twenty-three to forty-four years old (mean, thirty-four years) at the time of death. Retroreflective targets were inserted into each vertebra to obtain rotational kinematics in the coronal and axial planes. The specimens were subjected to pure lateral bending moment with use of established techniques. The range-of-motion and neutral zone metrics for the coronal and axial rotation components were determined at each level of the spinal column and were evaluated statistically. RESULTS Statistical analysis indicated that the two metrics were level-dependent (p < 0.05). Coronal motions were significantly greater (p < 0.05) than axial motions. Moment-rotation responses were nonlinear for both coronal and axial rotation components under lateral bending moments. Each segmental curve for both rotation components was well represented by a logarithmic function (R(2) > 0.95). CONCLUSIONS Range-of-motion metrics compared favorably with those of in vivo investigations. Coronal and axial motions of degeneration-free cervical spinal columns under lateral bending showed substantially different level-dependent responses. The presentation of moment-rotation corridors for both metrics forms a normative dataset for the degeneration-free cervical spines.
Relaxing Convergence Constraints in Local Priority Hysteresis Switching Logic

This paper addresses certain inherent limitations of local priority hysteresis switching logic. Our main result establishes that under persistent excitation assumption, it is possible to relax constraints requiring strict positivity of local priority and hysteresis switching constants. Relaxing these constraints allows the adaptive system to reach optimality which implies the performance improvement. The unconstrained local priority hysteresis switching logic is examined and conditions for global convergence are derived. Keywords—Adaptive control, convergence, hysteresis constant, hysteresis switching.
A semi-supervised clustering algorithm based on rough reduction

Clustering analysis is an important issue in data mining fields. Clustering in high dimensional space is especially difficult for a series of problems, such as the sparseness of spatial distribution of data, too much noise data points. Based on the analysis of current clustering algorithms can not get satisfying clustering results of high dimensional data. The theory of rough set and the idea of semi-supervised are introduced. And a semi-supervised grid clustering algorithm RSGrid based on the reduction of rough set theory is proposed. The theoretical analysis and experimental results indicate the algorithm can solve the problem of clustering in high dimensional space efficiently.
Exploratory Item Classification Via Spectral Graph Clustering

Large-scale assessments are supported by a large item pool. An important task in test development is to assign items into scales that measure different characteristics of individuals, and a popular approach is cluster analysis of items. Classical methods in cluster analysis, such as the hierarchical clustering, K-means method, and latent-class analysis, often induce a high computational overhead and have difficulty handling missing data, especially in the presence of high-dimensional responses. In this article, the authors propose a spectral clustering algorithm for exploratory item cluster analysis. The method is computationally efficient, effective for data with missing or incomplete responses, easy to implement, and often outperforms traditional clustering algorithms in the context of high dimensionality. The spectral clustering algorithm is based on graph theory, a branch of mathematics that studies the properties of graphs. The algorithm first constructs a graph of items, characterizing the similarity structure among items. It then extracts item clusters based on the graphical structure, grouping similar items together. The proposed method is evaluated through simulations and an application to the revised Eysenck Personality Questionnaire.
Combining task-dependent information with auditory attention cues for prominence detection in speech

Auditory attention is a highly complex mechanism that involves the process of low-level acoustic features of sound together with higher level cognitive rules. In this paper, a novel method that combines biologically inspired auditory attention cues with higher level lexical and syntactic information is proposed to model task-dependent inﬂuences on a given task. The feature maps are extracted from sound at multi-scales by mimicking the processing stages in the human auditory system, and converted to low-level auditory gist features. Then, the auditory attention model biases the gist features based on the task to maximize target detection. The top-down task-dependent inﬂuence of lexical and syntactic information is incorporated into the model using a probabilistic approach. The combined model is tested to detect prominent syllables in speech using the BU Radio News Corpus. The model achieves 88 % prominence detection accuracy at syllable level, which is comparable to reported human performance on this task.
Hypothyroidism and Depression

Background: A relationship between hypothyroidism and depression has been assumed for many years; however, the true nature of this association has been difficult to define with many conflicting studies. In recent years, our knowledge in this area has increased significantly with large cohort studies and genetically driven studies being published. Objectives: We reviewed the literature on thyroid function and depression to determine if this relationship has been clarified. Methods: We performed a search on the Pubmed database using the terms ‘thyroid' and ‘mental health', ‘depression' and ‘well-being'. Results: Large epidemiological studies generally suggest no association between thyroid function and depression in subjects without thyroid disease. Subjects on thyroxine have poorer psychological well-being than subjects with no thyroid disease even if biochemically euthyroid, they also show an association between thyroid function and well-being. Whilst there is some early evidence that genetic factors can influence well-being on thyroxine and response to combination therapy, there is also evidence to suggest that much morbidity on thyroxine may be due to initial misdiagnosis and mis-attribution of symptoms. Conclusion: Despite the large number of studies, the relationship between thyroid function and depression remains poorly defined. Clarification of the proportion of subjects on thyroxine incorrectly may assist the large (perhaps genetically driven) studies needed to move forward in this area, as it is expected that they cloud the results.
The dynamic adjustment of local government budgets: does Spain behave differently?

The aim of this article is to analyse whether Spanish municipalities adjust in response to budget shocks and (if so) which elements of the budget they are more likely to adjust. The methodology we use to answer these questions is a Vector Error Correction Model (VECM), estimated with data from a panel of Spanish municipalities during the period 1988 to 2006. Our results confirm that Spanish municipalities do indeed make adjustments in response to fiscal shocks (i.e. the deficit is stationary in the long run). We compare our results with those obtained for US and Germany to evaluate if the viability of local finance depends on the institutional arrangement and to analyse how it affects the adjustment patterns. We observe that grants have a more important role in the adjustment process in environments where either they have an equalization objective or where there is no clear rule that determines their distribution. This fact can generate a moral hazard problem: governments tend to spend more due to the expected intervention by the central government. Own revenues have a lower adjustment capacity in environments where subcentral governments have limited fiscal autonomy. These results, however, suggest that the viability of the local finance system is feasible with different institutional arrangements.
The Structural Basis of Functional Improvement in Response to Human Umbilical Cord Blood Stem Cell Transplantation in Hearts with Postinfarct LV Remodeling

Cellular therapy for myocardial repair has been one of the most intensely investigated interventional strategies for acute myocardial infarction. Although the therapeutic potential of stem cells has been demonstrated in various studies, the underlying mechanisms for such improvements are poorly understood. In the present study, we investigated the long-term effects of stem cell therapy on both myocardial fiber organization and regional contractile function using a rat model of postinfarct remodeling. Human nonhematopoietic umbilical cord blood stem cells (nh-UCBSCs) were administered via tail vein to rats 2 days after infarct surgery. Animals were maintained without immunosuppressive therapy. In vivo and ex vivo MR imaging was performed on infarct hearts 10 months after cell transplantation. Compared to the age-matched rats exposed to the identical surgery, both global and regional cardiac functions of the nh-UCBSC-treated hearts, such as ejection fraction, ventricular strain, and torsion, were significantly improved. More importantly, the treated hearts exhibited preserved fiber orientation and water diffusivities that were similar to those in sham-operated control hearts. These data provide the first evidence that nh-UCBSC treatment may prevent/delay untoward structural remodeling in postinfarct hearts, which supports the improved LV function observed in vivo in the absence of immunosuppression, suggesting a beneficial paracrine effect occurred with the cellular therapy.
Colloidal Particles at Liquid Interfaces: Contents

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Impact of Changing the Statistical Methodology on Hospital and Surgeon Ranking: The Case of the New York State Cardiac Surgery Report Card

Background:Risk adjustment is central to the generation of health outcome report cards. It is unclear, however, whether risk adjustment should be based on standard logistic regression, fixed-effects or random-effects modeling. Objective:The objective of this study was to determine how robust the New York State (NYS) Coronary Artery Bypass Graft (CABG) Surgery Report Card is to changes in the underlying statistical methodology. Methods:Retrospective cohort study based on data from the NYS Cardiac Surgery Reporting System on all patient undergoing isolated CABG surgery in NYS and who were discharged between 1997 and 1999 (51,750 patients). Using the same risk factors as in the NYS models, fixed-effects and random-effects models were fitted to the NYS data. Quality outliers were identified using 1) the ratio of observed-to-expected mortality rates (O/E ratio) and confidence intervals (CIs) calculated using both parametric (Poisson distribution) and nonparametric (bootstrapping) techniques; and 2) shrinkage estimators. Results:At the surgeon level, the standard logistic regression model, the fixed-effects model, and the fixed-effects component of the random-effects model demonstrated near-perfect agreement on the identity of quality outliers using a quality indicator based on the O/E ratio and the Poisson distribution. Shrinkage estimators identified the fewest outliers, whereas the O/E ratios with bootstrap CI identified the greatest number of outliers. The results were similar for hospitals, except that the fixed-effects model identified more outliers than either the NYS model or the fixed-effects component of the random-effects model. Conclusion:Shrinkage estimators based on random-effects models are slightly more conservative in identifying quality outliers compared with the traditional approach based on fixed-effects modeling and standard regression. Explicitly modeling surgeon provider effect (fixed-effects and random-effects models) did not significantly alter the distribution of quality outliers when compared with standard logistic regression (which does not model provider effect). Compared with the standard parametric approach, the use of a bootstrap approach to construct 95% confidence interval around the O/E ratio resulted in more providers being identified as quality outliers.
Expression of the alpha 1-proteinase inhibitor gene family during evolution of the genus Mus.

alpha 1-Proteinase inhibitors (alpha 1-PIs) are members of the serpin superfamily of proteinase inhibitors, and are important in the maintenance of homeostasis in a wide variety of animal taxa. Previous studies have shown that in mice (genus Mus), evolution of alpha 1-PIs is characterized by gene amplification, region-specific concerted evolution, and rapid accumulation of amino acid substitutions. The latter occurs primarily in the reactive center, which is the region of the alpha 1-PI molecule that determines the inhibitor's specificity for target proteinases. The P1 residue within the reactive center, which is methionine in so-called orthodox alpha 1-PIs and an amino acid other than methionine in unorthodox alpha 1-PIs, is a primary determinant of inhibitor specificity. In the present study, we find that the expression of mRNAs encoding unorthodox alpha 1-PIs is polymorphic within Mus species, i.e., among individuals or inbred strains. This is in striking contrast to mRNAs that encode orthodox alpha 1-PIs, whose concentrations are relatively invariant. The intraspecies variations in mRNA expression represent polymorphisms in the structure of the alpha 1-PI gene family. The results, taken together with previously described aspects of alpha 1-PI evolution, indicate that the dissimilar levels of polymorphism exhibited by orthodox and unorthodox alpha 1-PIs, which likely have distinct physiological functions, may reflect different levels of selective constraint. The significance of this finding to the evolution of gene families is discussed.
Robust and efficient voltage stability margin computation using synchrophasors

Results from two practical and fast methods to estimate systems' Maximum Loading Point (MLP) using Phasor Measurement Units (PMUs) are used in this paper as initial values for a robust and very efficient method that takes advantage of the geometric characteristics of the maximum loading hyperplane and uses the load flow with step size optimization (LFSSO) technique to estimate the system's proximity to the MLP. Both initializing methods are based on estimated Thévenin Equivalents (TEs) as seen from load buses using only local measurements. On the other hand, the latter method is based on successive load flow calculations of multiple operating points until the MLP is reached within a certain threshold defined by the user. The performance of the complete method (combination between the initializing methods and the LFSSO based method) was tested for some IEEE test systems and for a realistic Brazilian transmission system with more than 4,500 buses.
Developing Payout-Loyalty Matrix for Telecom Retailers – A Study on Murshidabad and Nadia Districts

Retailing is the route of selling consumer goods and/or services to the ultimate consumers for their personal or household consumption through multiple channels of distribution to make revenue. Retail marketing has undergone radical restructuring due to increase in GDP, per capita income, purchasing power of the people. Now-a-days retail industry has become dynamic industry in the world and this industry is contributing to the economic growth of many countries.Telecom retailers are earning substantial amount of commission from telecos owing to the huge monthly subscriber churn rate and the popularity of mobile numbers portability among users. The churn rate is calculated as the number of subscribers who get out of an operator’s network in a month as a percentage of its total subscriber base. Retail stores are the strategic touch points to tie with prospective customers. Indian customers mostly rely upon retailers and prefer personal interaction for advice and understanding offers. So telecom retailers play a pivotal role for the company to expand market share.The present paper is an endeavour to study the different types of telecom retailers considering two dimensions – loyalty and payout. This study will also help companies to formulate strategies for increasing sales revenue and market share. This study is qualitative in nature and the results are based on market survey of 425 telecom retailers selected from different parts of Murshidabad and Nadia districts by using convenience sampling technique. The study has yielded a number of valuable findings, which are of far-reaching.Consequences for policy formulation and decision making by the companies offering telecom services under study. The findings of Payout-Loyalty matrix indicate that there are six categories of telecom retailers in the market and these retailers are named as Inactive retailers, Bull, Gambler, Market maker, Loyal Screamer, Loyal but volatile & perfect profit maker, Brand & Business builders, Loyal Survivor & Savior and Mask Gambler. This Payout-Loyalty Matrix can help in balancing incentive structure so that retailers are not engaged in gambling company’s profitability.