nils-herrmann/clean_scirepeval huggingface dataset:
Composition, properties and challenges of algae biomass for biofuel application: An overview

Algae based fuels are considered to be the most sustainable, renewable, effective and environment friendly response to climate change and food feed security, as well as the only renewable energy resource that has the capacity to meet the global demand for fuels in the long term. Therefore, an extended overview of the composition, properties and challenges of algae biomass for biofuel application was conducted based on reference peer reviewed data plus own investigations. Initially, some general considerations such as current bioenergy situation and significance of biofuel generations, as well as different aspects related to biomass use as biofuels are discussed. Then, common issues concerning taxonomical classification, habitat environment, carbon reserve capacity, production, use, and main advantages and disadvantages of algae or algae biofuel are addressed. Further, more than 135 characteristics related to the chemical, phase and mineral composition and properties of algae and algae ash are evaluated and compared to those of terrestrial biomass, coal and their ashes. As a result specific benefits and obstacles connected with the composition and properties of algae and algae ash are discussed. The behaviour of organic and inorganic matter during algae combustion is also described. Finally, the major technological and environmental challenges related to algae based fuels are emphasized. The present data demonstrate that the high contents of inorganic matter with unfavourable modes of element occurrences (chlorides, sulphates, carbonates, oxalates, nitrates and some oxyhydroxides, phosphates and amorphous material) in algae and algae ash provoke the most critical technological and environmental challenges during algae processing for biofuel application and especially during algae thermochemical conversion. Another very important challenge addressed is the indefinite availability of sustainable algae resources for production of biofuels and biochemicals and certain recommendations are given. It was found that the disadvantages of algae biofuel application prevail significantly over the advantages; however, the major economic, environmental and social benefits appear to compensate the technological and other barriers caused by the unfavourable composition and properties of algae.
Algae bacteria interactions: Evolution, ecology and emerging applications.
Venue: Biotechnology advances

Algae and bacteria have coexisted ever since the early stages of evolution. This coevolution has revolutionized life on earth in many aspects. Algae and bacteria together influence ecosystems as varied as deep seas to lichens and represent all conceivable modes of interactions from mutualism to parasitism. Several studies have shown that algae and bacteria synergistically affect each other's physiology and metabolism, a classic case being algae roseobacter interaction. These interactions are ubiquitous and define the primary productivity in most ecosystems. In recent years, algae have received much attention for industrial exploitation but their interaction with bacteria is often considered a contamination during commercialization. A few recent studies have shown that bacteria not only enhance algal growth but also help in flocculation, both essential processes in algal biotechnology. Hence, there is a need to understand these interactions from an evolutionary and ecological standpoint, and integrate this understanding for industrial use. Here we reflect on the diversity of such relationships and their associated mechanisms, as well as the habitats that they mutually influence. This review also outlines the role of these interactions in key evolutionary events such as endosymbiosis, besides their ecological role in biogeochemical cycles. Finally, we focus on extending such studies on algal bacterial interactions to various environmental and bio technological applications.
Life cycle assessment of algae biodiesel and its co products

There is a need to explore alternative energy sources to meet the future energy demand in a sustainable way. Algae could be a potential feed stock for biodiesel and other co products such as animal feed and chemicals. Life cycle assessment (LCA) of such production system has to be assessed before any implementation at commercial scale. In this context, a prospective LCA of algae biorefinery considering selected multi products (biodiesel, protein and succinic acid) was carried out to estimate the environmental impact compared to a reference system. LCA results revealed less CO2 emissions and land use for biodiesel, protein and succinic acid production system compared to that of only biodiesel and protein production system from algae. The impact reduction was even more when compared with conventional diesel, soy protein and fossil based succinic acid system. A higher carbohydrate composition in algae favors less CO2 emissions and fossil fuel consumption in the algae system compared to that of the reference system.
Sustentabilidade quanto as embalagens de alimentos no Brasil Sustainability concerning food packaging in Brazil

Change of habits and increasing consumerism observed in the recent decades have widely influenced technological innovations, as well as the growth of consumer goods production, which has consequently required a crescent packaging production. Packages are used in diverse sectors, among them the food industry stand out, in which their main functions are to contribute to food conservation and selling the product. Different materials, such as plastics, metals, glass and paper, have been used in the food packaging production. Each material has different attributes that help to conserve the product: gas, aroma, light, water barrier, microorganisms and mechanical strength are the main ones. Despite the several advantages of its application, its uncontrolled use and disposal result in a large volume of solid residues and environmental impact. Concerning this situation, alternative practices, such as reuse and development of biodegradable and green polymers, have been considered in order to reduce the impacts.
Teaching And Researching Speaking

Thank you very much for downloading teaching and researching speaking. As you may know, people have look numerous times for their favorite readings like this teaching and researching speaking, but end up in harmful downloads. Rather than reading a good book with a cup of coffee in the afternoon, instead they juggled with some harmful virus inside their laptop. teaching and researching speaking is available in our digital library an online access to it is set as public so you can download it instantly. Our digital library spans in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the teaching and researching speaking is universally compatible with any devices to read.
A method to solve the permutation problem in blind source deconvolution for audio signals based on phase linearity estimation
Venue: 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)

One approach to solve the blind source deconvolution (BSD) is to transform the observations into the frequency domain and apply common blind source separation (BSS) in each frequency bin. This approach is called frequency domain blind source separation (FD BSS) Generally FD BSS has a problem with indeterminacy of the permutation of the separated signals in each frequency bin. Furthermore, even if the permutation problem is solved, we cannot avoid the degradation of quality of the estimated signals because of noise or statistical error. In this paper, we describe a new approach for BSS that utilizes the phase linearity not only to solve the permutation problem but also to tune each value of the elements of the separating matrices. To effectively detect multi and ambiguous linearity, we propose the use of the Hough transform. To improve the signal to noise ratio (SNR) we propose not to persist in the independence, but to adopt the constraints of phase linearity. Simulation results for audio sources show the improvement of SNR with the proposed method.
Quantum Information Theory: Mathematical Foundation

This graduate textbook provides a unified view of quantum information theory. Clearly explaining the necessary mathematical basis, it merges key topics from both information theoretic and quantum mechanical viewpoints and provides lucid explanations of the basic results. Thanks to this unified approach, it makes accessible such advanced topics in quantum communication as quantum teleportation, superdense coding, quantum state transmission (quantum error correction) and quantum encryption. Since the publication of the preceding book Quantum Information: An Introduction, there have been tremendous strides in the field of quantum information. In particular, the following topics all of which are addressed here made seen major advances: quantum state discrimination, quantum channel capacity, bipartite and multipartite entanglement, security analysis on quantum communication, reverse Shannon theorem and uncertainty relation. With regard to the analysis of quantum security, the present book employs an improved method for the evaluation of leaked information and identifies a remarkable relation between quantum security and quantum coherence. Taken together, these two improvements allow a better analysis of quantum state transmission. In addition, various types of the newlydiscovered uncertainty relation are explained. Presenting a wealth of new developments, the book introduces readers to the latest advances and challenges in quantum information. To aid in understanding, each chapter is accompanied by a set of exercises and solutions.
Examination of the Relation between Academic Procrastination and Time Management Skills of Undergraduate Students in Terms of Some Variables

Academic procrastination is seen to be quite common among undergraduates and time management is thought to be one of the possible reasons of it. Two surveys, academic procrastination and time management, were given to 332 undergraduate students in this correlational research. Students' academic procrastination is explained through frequencies and percentages and a correlation is questioned between academic procrastination and time management. Regression analysis is used to find out if time management predicts academic procrastination in a statistically significant way. Besides, students' level of time management (low, medium, high) is examined and covariance analysis has been carried out to see if time management level and gender, time management level and housing type (private or state dormitory or house) time management level and their major and time management level and where they live have a common effect on academic procrastination. Results indicate that students are generally indecisive about their behaviors of procrastination in academic tasks and are in middle level in terms of time management skills. There is a moderate level, negative sided and statistically significant correlation between academic procrastination and time management. Not a common effect of mentioned above variables is seen.
An analytical benchmark and a Mathematica program for MD codes: Testing LAMMPS on the 2nd generation Brenner potential
Venue: Comput. Phys. Commun.

An analytical benchmark and a simple consistent Mathematica program are proposed for graphene and carbon nanotubes, that may serve to test any molecular dynamics code implemented with REBO potentials. By exploiting the benchmark, we checked results produced by LAMMPS (Large scale Atomic/Molecular Massively Parallel Simulator) when adopting the second generation Brenner potential, we made evident that this code in its current implementation produces results which are offset from those of the benchmark by a significant amount, and provide evidence of the reason.  MDBenchmarks Catalogue identifier: AFAS_v1_0  http:/cpc.cs.qub.ac.uk/summaries/AFAS_v1_0.html  CPC Program Library, Queen's University, Belfast, N. Ireland  GNU GPL v3 No. of lines in distributed program, including test data, etc. 22854 No. of bytes in distributed program, including test data, etc. 369171  tar.gz  Mathematica 9.  Any PC.  Any which supports Mathematica; tested under OS Yosemite.  7.7, 16.1, 16.13.  Testing commercial or open source molecular dynamics codes implementing off the shelf REBO potentials on an analytical benchmark.  Analytical equilibrium conditions for achiral carbon nanotubes are implemented and solved, delivering benchmark values for the corresponding natural radius and cohesive energy; material properties (Young's modulus and Poisson coefficient) are also computed.  Instantaneous, or a few seconds, depending on computer hardware
Past and present of active school transportation: An explanation of the influence of the built environment in Toronto, Canada, from 1986 to 2006

The health benefits of walking and cycling to and from school, also called active school transportation (AST) are well docu mented. In the context of a declining trend in AST across the West ern world, this paper examines school travel behavior of 11 year old children in Toronto, using multiple cross sectional data from 1986, 1996, and 2006  Results from bi nomial logit models suggest that school travel distance and neighbor hood built environment indeed explain some variation in the odds of AST between 1986 and 2006, and that the correlates of AST may have changed over time. Higher neighborhood block density correlated with walking/cycling in 1986. In contrast, household automobile owner ship was negatively associated with AST in 2006; the effect of the built environment was relatively weak for that year. In addition, fewer chil dren walked/cycled in 2006 compared to 1986, even when distance to school was short <0.8 kilometers) Policy and programs should recog nize the potentially changing role of travel distance to school and au tomobile ownership on a child's school travel outcome. Interventions in neighborhoods with high automobile ownership should specifically focus on education and encouragement to increase AST rates.
Content based hyperspectral image retrieval using bag of endmembers image descriptors
Venue: 2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)

This paper proposes a novel system for fast and accurate content based retrieval of hyperspectral images. The proposed system aims at retrieving hyperspectral images that have both similar spectral characteristics associated with specific materials and fractional abundances to the query image. It consists of two modules. The first module characterizes the query and the target hyperspectral images in the archive by two descriptors: 1) a binary spectral descriptor representing spectral characteristics of distinct materials 2) an abundance descriptor that contains the normalized cumulative fractional abundance information of the corresponding materials. Both descriptors are obtained by a novel bag of endmembers based strategy. The second module aims at retrieving hyperspectral images from the archive that are most similar to query image based on a hierarchical strategy which evaluates the spectral and abundance descriptors similarity. Experiments carried out on a benchmark archive of hyperspectral images demonstrated the effectiveness of the proposed system in terms of retrieval accuracy and time.
A novel content based hyperspectral image retrieval system based on bag of end members
Venue: 2016 24th Signal Processing and Communication Application Conference (SIU)

This paper proposes a bag of end members based novel method for content based hyperspectral image retrieval. The proposed system exploits high resolution spectral signatures of the distinct materials in the hyperspectral images and consists of two steps. In the first step, query and archive hyperspectral images are represented with a feature vector computed by a novel bag of end members based feature extraction method. In the second step, the similarities between the feature vector of the query image and those of the archive images are initially computed by the use of histogram intersection kernel and then the most similar images are retrieved. The proposed system is tested on a hyperspectral image archive created from an EO 1 Hyperion hyperspectral sensor image. The experimental results show that the proposed system increases hyperspectral image retrieval performance.
The Face of Fairness: Self Awareness as a Means to Promote Fairness among Managers with Low Empathy

Although managing fairness is a critical concern for organizations, not all managers are predisposed to enact high levels of fairness. Emerging empirical evidence suggests that personality characteristics can be an important antecedent of managers' fair behavior. However, relatively little attention has been devoted to understand how to promote fairness among managers who are naturally predisposed to engage in lower levels of fairness. Building upon self awareness theory, we argue that increasing managers' self awareness can motivate managers with low trait empathy to engage in greater levels of justice. We test the interactive effects of trait empathy and state self awareness using an experimental study (N 76) in which individuals were asked to communicate negative news. In support of our hypothesis, our results indicate that increasing self awareness through self focusing situations can help promote interactional justice when communicating negative news for individuals with low trait empathy. The theoretical and practical implications of these findings are discussed.
ProtAnnot: an App for Integrated Genome Browser to display how alternative splicing and transcription affect proteins
Venue: Bioinform.

One gene can produce multiple transcript variants encoding proteins with different functions. To facilitate visual analysis of transcript variants, we developed ProtAnnot, which shows protein annotations in the context of genomic sequence. ProtAnnot searches InterPro and displays profile matches (protein annotations) alongside gene models, exposing how alternative promoters, splicing and 3' end processing add, remove, or remodel functional motifs. To draw attention to these effects, ProtAnnot color codes exons by frame and displays a cityscape graphic summarizing exonic sequence at each position. These techniques make visual analysis of alternative transcripts faster and more convenient for biologists. Availability and implementation: ProtAnnot is a plug in App for Integrated Genome Browser, an open source desktop genome browser available from http:/www.bioviz.org.
Method development and validation of telmisartan in bulk and pharmaceutical dosage forms by UV spectrophotometric method

This paper describes the analytical method suitable for validation of Telmisartan by UV Spectrophotometric method. The method utilized UV spectroscopy (Shimadzu, model 1700).The solvent system was consists of Methanol: water in the ratio of 90:10 at wave length (lmax) 298 nm. Validation experiments were performed to demonstrate System suitability, Specificity, Precision, Linearity, Accuracy Interday assay, intraday assay, robustness, ruggedness, LOD, &LOQ. The method was linear over the concentration range of 5 45 mg/ml. The method was showed good recoveries (98.04 101.04% and the recovery studies were carried out by adding different amounts (80% 100% 120% of bulk samples of Telmisartan. The Proposed method was simple, sensitive &reliable with good Precise, Accurate, and Reproducible and rapid for the determination of Telmisartan. While estimating the commercial formulation without interference of excipients other additives hence this method can be used for routine determination of Telmisartan in bulk and their pharmaceutical dosage forms.
Interactive tool for analysis of EEG signal
Venue: 2016 ELEKTRO

The EegStudio, the powerful tool for displaying, analyzing and processing of electroencephalogram (EEG) with user friendly graphical interface is described in this paper. The EegStudio provides highlight of specific frequency bands of brain, interactive signal filtration, analysis in time frequency domain and topographic mapping of the brain activity. The brain mapping is used for visualization of brain activity over the scalp. This application allows amplitude, frequency, interhemispheric coherence and time delay brain mapping. The mapping of time delay in records with epileptic seizure can be used for localization of the epileptic focus.
Validation of a Predictive Model to Identify Patients at High Risk for Hospital Readmission
Venue: Journal for healthcare quality official publication of the National Association for Healthcare Quality

Hospital readmission is an adverse patient outcome that is serious, common, and costly. For hospitals, identifying patients at risk for hospital readmission is a priority to reduce costs and improve care. The purposes were to validate a predictive algorithm to identify patients at a high risk for preventable hospital readmission within 30 days after discharge and determine if additional risk factors enhance readmission predictability. A retrospective study was conducted on a randomized sample of 598 patients discharged from a Southeast community hospital. Data were collected from the organization's database and manually abstracted from the electronic medical record using a structured tool. Two separate logistic regression models were fit for the probability of readmission within 30 days after discharge. The first model used the LACE index as the predictor variable, and the second model used the LACE index with additional risk factors. The two models were compared to determine if additional risk factors increased the model's predictive ability. The results indicate both models have reasonable prognostic capability. The LACE index with additional risk factors did little to improve prognostication, while adding to the model's complexity. Findings support the use of the LACE index as a practical tool to identify patients at risk for readmission.
Identifying Diabetic Patients with High Risk of Readmission
Venue: ArXiv

Hospital readmissions are expensive and reflect the inadequacies in healthcare system. In the United States alone, treatment of readmitted diabetic patients exceeds 250 million dollars per year. Early identification of patients facing a high risk of readmission can enable healthcare providers to to conduct additional investigations and possibly prevent future readmissions. This not only improves the quality of care but also reduces the medical expenses on readmission. Machine learning methods have been leveraged on public health data to build a system for identifying diabetic patients facing a high risk of future readmission. Number of inpatient visits, discharge disposition and admission type were identified as strong predictors of readmission. Further, it was found that the number of laboratory tests and discharge disposition together predict whether the patient will be readmitted shortly after being discharged from the hospital (i.e. 30 days) These insights can help healthcare providers to improve inpatient diabetic care. Finally, the cost analysis suggests that $252.76 million can be saved across 98,053 diabetic patient encounters by incorporating the proposed cost sensitive analysis model.