nils-herrmann/clean_scirepeval huggingface dataset:
Life Cycle Assessment and Monetary Measurements for the Carbon Footprint Reduction of Public Buildings
Year: 2020

Energy consumption in public buildings increased drastically over the last decade. Significant policy actions towards the promotion of energy efficiency in the building sector have been developed involving sustainable low CO2 emission technologies. This paper presents the results of an economic environmental valuation of a standard energy retrofit project for a public building in a Mediterranean area, integrating a life cycle assessment (LCA) into the traditional economic financial evaluation pattern. The study results show that simple retrofit of sustainable low CO2 emission strategies such as wooden double glazed windows, organic external wall insulation systems, and green roofs can reduce energy needs for heating and cooling by 58.5% and 33.4% respectively. Furthermore, the implementation of an LCA highlights that the use of sustainable materials reduces the building's carbon footprint index by 54.1% after retrofit compared to standard materials, thus providing an additional increase in the socio environmental economic financial results of 18% Some proposals are made about the accounting of the replacement costs and the residual value as requested in the logic of life cycle cost (that is the economic extension of the LCA) namely concerning the method to take into account the replacement costs and the residual value. The economic calculation highlights the fundamental role played by tax benefits supporting the building energy retrofit, also in temperate climate zones, thus allowing the creation of environmental benefits in addition to remarkable cost savings.
Control and Mechanism Analysis of Serrated Chip Formation in High Speed Machining of Aluminum Alloy 7050 T7451
Year: 2020

Aluminum alloy 7050 T7451 is widely used in aeronautical large structural parts, and high speed cutting is often used in machining. The serrated chip is a critical state for chip formation in high speed cutting, and its formation and control mechanism are of great significance for actual machining. To study the chip formation of high speed cutting aluminum alloy 7050 T7451, the chips at different cutting speeds are obtained by high speed cutting experiments. Combined with microscopic observation, the chip shape evolution, chip localization fracture process and mechanism of different cutting speeds are analyzed. The morphological evolution of chips and the mechanism of chip breaking during high speed cutting of aluminum alloy are revealed. According to the machined surface of the chip root and the angle of the chip, the formation mechanism of the curl radius formed by the chip is analyzed. The critical cutting speed of plastic brittle transformation of aluminum alloy 7050 T7451 in high speed cutting is obtained by studying the critical condition for strip to serration transition of chip morphology.
Unbiased Identification of trans Regulators of ADAR and A to I RNA Editing.
Venue: Cell reports
Year: 2020

Adenosine to inosine RNA editing is catalyzed by adenosine deaminase acting on RNA (ADAR) enzymes that deaminate adenosine to inosine. Although many RNA editing sites are known, few trans regulators have been identified. We perform BioID followed by mass spectrometry to identify trans regulators of ADAR1 and ADAR2 in HeLa and M17 neuroblastoma cells. We identify known and novel ADAR interacting proteins. Using ENCODE data, we validate and characterize a subset of the novel interactors as global or site specific RNA editing regulators. Our set of novel trans regulators includes all four members of the DZF domain containing family of proteins: ILF3, ILF2, STRBP, and ZFR. We show that these proteins interact with each ADAR and modulate RNA editing levels. We find ILF3 is a broadly influential negative regulator of editing. This work demonstrates the broad roles that RNA binding proteins play in regulating editing levels, and establishes DZF domain containing proteins as a group of highly influential RNA editing regulators.
Recent developments in supercritical fluid extraction of bioactive compounds from microalgae: Role of key parameters, technological achievements and challenges
Year: 2020

Microalgae are a rich source of natural bioactive compounds, e.g. astaxanthin, b carotene, lutein, and fatty acids (FAs) that are currently in high demand in the market. Conventional extraction methods often produce adverse effects on some of these compounds. Replacing conventional extraction methods with more efficient advanced green technologies that offer greater extracts purity and low environmental impact is therefore a challenging and sought for target. This review is a comprehensive overview of supercritical fluid (SCF) extraction processes, including the latest research on the extraction of bioactive compounds from microalgae biomass and their benefits on human health. In addition, the role of key operating parameters on the selectivity of various compounds is discussed. This study provides useful knowledge that can productively contribute to the future development of SCF based extraction technologies on an industrial scale.
Spectrum aware cross layered routing protocol for cognitive radio ad hoc networks
Venue: Comput. Commun.
Year: 2020

Cognitive radio network has been proposed as a promising technology to satisfy the manifold requirements of future generation (5G) wireless system by intelligently accessing the underutilized channel of a primary user. However, due to the heterogeneity in channel propagation characteristics, intermittent availability of licensed channel, recurrent hand offs, and need of a protection to primary users, finding a successful route is more challenging. Also, incorporation of opportunistic spectrum access in cognitive radio network requires a potential spectrum management functions across the network layers. Hence, a cross layered channel assignment algorithm and routing algorithm is proposed for a cognitive radio ad hoc network which can overcome above mentioned challenges and provide a stable path for routing of data packets. A novel metric, for the probability of successful transmission of a channel is derived by considering channel statistics, sensing periodicity of the cognitive user, and time varying channel quality. Also, the number of available channels and their characteristics is considered for the selection of a next hop node with an aim to avoid the one hop neighbors located in the PU transmission range. The proposed routing protocol is simulated in ns 2 and compared with the existing similar protocols. The performance shows that the proposed algorithm performs better in terms of throughput, end to end delay, number of spectrum hand offs, and interference to the primary user in a significant manner.
Model based test case generation from UML sequence diagrams using extended finite state machines
Venue: Softw. Qual. J.
Year: 2021

The effectiveness of model based testing (MBT) is mainly due to its potential for automation. If the model is formal and machine readable, test cases can be derived automatically. One of the most used formal modeling techniques is the interpretation of a system as an extended finite state machine (EFSM) However, formal models are not a common practice in the industry. The Unified Modeling Language (UML) has become the de facto standard for software modeling. Nevertheless, due to the lack of formal semantics, its diagrams can be given ambiguous interpretations and are not suitable for testing automation. This article introduces a systematic procedure for the generation of tests from UML models that uses concepts of model driven engineering (MDE) for formalizing UML sequence diagrams into extended finite state machines and providing a precise semantics for them. It also applies ModelJUnit and JUnit libraries for an automatic generation of test cases. A case study was conducted in a real software towards the evaluation of its applicability.
Should All Cars Be Electric by 2025? The Electric Car Debate in Europe
Venue: Sustainability
Year: 2019

The car is still the most common mode of transport in Western countries, particularly so across the European Union, as it accounts for about two thirds of daily commuting. So far, measures aiming to reduce automobile traffic and incentives for the modal shift to public transport and non polluting methods of travel (walking, cycling, etc. have had little effect. Moreover, the car lies at the core of a very complex system that has proven to be difficult to unlock. In light of these challenges, using new types of engine power may appear to be a solution. Electric vehicles have the potential to improve the efficiency, affordability, and sustainability of the transport system. However, there remains much uncertainty as to how such a transition from one type of engine to another may unfold, and where it could take place within the European context. In June 2017, the H2020 project SHAPE ENERGY launched an online debate on the Debating Europe platform with the question: "Should all cars be electric by 2025?" The aim of the debate was to elicit citizens views on whether the goal could be reached, how and with which consequences. The diversity of the vantage points that have appeared in the subsequent discussion generated by the strands of debate allows us to bring into discussion the viewpoints and arguments that are not often addressed in the literature on the adoption of electric cars in a comprehensive way. The article sheds light on those debates across Europe, in order to bring new insights to European policymakers that are seeking to promote the market for electric vehicles. It also broadens the scope and offers important contributions to scholarly debates on the diffusion and adoption of such vehicles.
Regulatory T cell derived inhibitory cytokines and regulation of anti tumor immunity
Year: 2020

Regulatory T cells (Tregs) play a crucial role in the maintenance of self tolerance and prevent overt immune responses during infection. One of the primary mechanisms of immune regulation by Tregs is via secretion of inhibitory cytokines (IL 10, IL 35, and TGF b) and activated Tregs producing these inhibitory cytokines are highly enriched in the tumor microenvironment (TME) However, it is yet unclear whether intratumoral Tregs preferentially utilize one regulatory mechanism over others in the TME. We have previously demonstrated that Treg derived IL 35 regulate anti tumor immunity by promoting the inhibitory receptor expression in CD8+ TILs. As induction of a dysfunctional state known as T cell exhaustion in tumor infiltrating T cells presents a barrier to effective cancer immunotherapy, it is imperative to understand the mechanism of Treg derived inhibitory cytokine mediated induction of T cell exhaustion and the developmental relationship between subpopulations of effector Tregs in the TME. In Chapter 3, I demonstrate that IL 10+ and IL 35+ Tregs are not distinct, stable subsets of Tregs, and intratumoral Tregs exhibit the environmentally inducible adaptive plasticity of the IL 10 and IL 35 expression. In Chapter 4, I show that Treg derived IL 10 and IL 35, despite the difference in their receptors and the downstream signal transduction, commonly target the BLIMP1 IR axis in CD8+ T cells to directly promote a dysfunctional state of T cells. Furthermore, in Chapter 5, I present an alternative function of Treg derived Ebi3 that is independent of the IL 12 cytokine family and a novel cytokine complex composed of IL 10 and Ebi3 produced by activated Tregs. Treg derived Ebi3 may have a broader physiological role than previously appreciated, and a comprehensive understanding of such unconventional role of Ebi3 in modulating immune responses is crucial to develop a novel therapeutic approach to target Ebi3 rationally. In addition to my thesis study, Appendix A lists the publications that I have contributed, as well as additional academic achievements such as awards and honors received at external conferences.
Two dimensional semiconductors with possible high room temperature mobility
Venue: Nano Research
Year: 2014

We have calculated the longitudinal acoustic phonon limited electron mobility of 14 two dimensional semiconductors with composition of MX2, where M Mo, W, Sn, Hf, Zr and Pt) is the transition metal, and X is S, Se and Te. We treated the scattering matrix by the deformation potential approximation. We found that out of 14 compounds, MoTe2, HfSe2 and ZrSe2 are promising regarding to their possible high mobility and finite band gap. The phonon limited mobility can be above 2,500 cm2*V 1*s 1 at room temperature.
Real time Short Term Trajectory Prediction Based on GRU Neural Network
Venue: 2019 IEEE/AIAA 38th Digital Avionics Systems Conference (DASC)
Year: 2019

From the perspective of historical trajectory data and real time trajectory data, a short term real time trajectory coordinate point prediction method based on GRU (Gated Recurrent Unit) cyclic neural network is proposed. The main method of real time trajectory prediction algorithm, in the first stage, is neural network initialization training. The GRU neural network parameters are learned by batch processing, and the network parameters which have been trained are input to the second stage as the initial parameters of the next stage GRU neural network. The second stage is the real time prediction of the trajectory. The GRU neural network parameters trained in the first stage are used as the initial values of parameters of the online prediction network. The real time trajectory data is used to adaptively update the parameters of the GRU neural network online and real time predicted the flight points. Finally, compared with other typical time series prediction models based on real flight data simulation experiments, the method is verified that the proposed short term real time prediction model has obvious advantages in prediction accuracy and applicability.
Thermodynamic and kinetics studies on adsorption of Indigo Carmine from aqueous solution by activated carbon
Year: 2019

The kinetic and equilibrium parameters of the quantitative adsorption for Indigo Carmine (IC) removed by commercial activated carbon (AC) were studied by UV visible absorption spectroscopy. AC with a high specific surface area (1250.320 m2/g) was characterized by the Brunauer Emmett Teller (BET) method and point of zero charge (pzc) The effect of the initial dye concentration (10 60 mg/L) contact time (0 90 min) pH (1 12) agitation speed (0 600 rpm) adsorbent dose (1 10 g/L) and temperature (298 323 K) were determined to find the optimal conditions for a maximum adsorption. The adsorption mechanism of Indigo Carmine onto AC was studied using the first pseudo order, second pseudo order and Elovich kinetics models. The adsorptions kinetic were found to follow a pseudo second order kinetic model with a determination coefficient (R2) of 0.999. To get an idea on the adsorption mechanism, we applied the Webber Morris diffusion model. The equilibrium adsorption data for Indigo Carmine on AC were analyzed by the Langmuir, Freundlich, Elovich, Dubinin and Temkin models. The results indicate that the Langmuir model provides the best correlation at 25 degC (qmax 79.49 mg/g) and Dubinin at 40 degC (qmax 298.34 mg/g) The adsorption isotherms at different temperatures have been used for the determination of thermodynamic parameters such as free energy (DGdeg 0.071 to 1.050 kJ/mol) enthalpy (DHdeg 28.11 kJ/mol) entropy (DSdeg 0.093 kJ/mol*K) and activation energy (Ea) of 51.06 kJ/mol of adsorption. The negative DGdeg and positive DHdeg values indicate that the overall adsorption is spontaneous and endothermic.
Learning Speaker Representations with Mutual Information
Venue: INTERSPEECH
Year: 2019

Learning good representations is of crucial importance in deep learning. Mutual Information (MI) or similar measures of statistical dependence are promising tools for learning these representations in an unsupervised way. Even though the mutual information between two random variables is hard to measure directly in high dimensional spaces, some recent studies have shown that an implicit optimization of MI can be achieved with an encoder discriminator architecture similar to that of Generative Adversarial Networks (GANs) In this work, we learn representations that capture speaker identities by maximizing the mutual information between the encoded representations of chunks of speech randomly sampled from the same sentence. The proposed encoder relies on the SincNet architecture and transforms raw speech waveform into a compact feature vector. The discriminator is fed by either positive samples (of the joint distribution of encoded chunks) or negative samples (from the product of the marginals) and is trained to separate them. We report experiments showing that this approach effectively learns useful speaker representations, leading to promising results on speaker identification and verification tasks. Our experiments consider both unsupervised and semi supervised settings and compare the performance achieved with different objective functions.
Estimation of complexity by using an object oriented metrics approach and its proposed algorithm and models
Year: 2019

The high pace emergence of software applications and associated technologies have enabled us an efficient and luxurious. This research paper focus the procedure of investigating the different object oriented metrics by taking an example and finally evaluate complexities, statistical measurements. A proposed model, flowchart and algorithm are used for measuring the metrics in the software project. Comparison done between the programming languages like C+ and Python and conclude that Python is better than C+
MUL TI FERROIC MAGNETOELECTRICS
Year: 2017

Domain aspects of multi ferroics are reviewed, i.e. of materials in which two or all three of the properties ferroelectricity, ferromagnetism, and ferroelasticity occur simultaneously in the same phase, and in which the magnetic point group has been reliably established by magnetoelec. optical, dielec. magnetic and related studies on single crystals and single domains. Nearly only members of the boracite crystal family are concerned, whereas for the perovskite family and other classes of material there is great paucity of data on single crystals. Polarized light microscopy is shown to be an indispensable tool for the study of multi ferroics, in particular when ferroelasticity is involved. Potential multi ferroic magnetoelecs. so far only known in ceramic form, are excluded from the survey. 106 Refs. SCHMID, Hans. Multi ferroic magnetoelectrics. Ferroelectrics, 1994, vol. 162, no. 1 4, p.
Large scale video classification using both visual and audio features on YouTube 8 M dataset
Year: 2017

Convolutional Neural Networks (CNNs) have achieved state of art in image classification and have been progressing rapidly in the field of video classification and audio understanding in recent years. Encouraged by these results, we propose jointly using video and audio features in order to provide a promising classifier for the Youtube 8M Kaggle challenge a video classification task for a dataset of 7 million YouTube videos belonging to 4716 classes[2] In this paper, we explore several models of different combination of video level visual and audio features. Our best model uses the mixture of experts (MoE) to receive three inputs. They are video level visual feature only, audio feature only and a concatenation of visual and audio feature. Then we apply a dense layer followed by a ReLu activation layer. The gating network we applied in MoE uses softmax function. We train our model with Tensorflow using 1 GPU on Google Cloud Platform. The average training time is 1 hour 15 minutes. As a result, we achieve Avg Hit@1 of 0.84, Avg PERR (average precision at equal recall rate) of 0.709, and mAP (mean average precision) of 0.415 compared to the best performing baseline proposed in  with Avg Hit@1 0.645, Avg PERR of 0.573, mAP of 0.266.
Integrated management of Bayoud disease on date palm (Phoenix dactylifera L. caused by Fusarium oxysporum f. sp. albedinis in Algeria
Year: 2017

Date palm (Phoenix dactylifera L. is one of the most important fruit trees growing in Algeria, Arabian world and some neighboring countries represents a good crop economy sources for many farmers. Date palm diseases are among the major factors that affecting the products. The agent pathogen F.oxysporum f. sp. Albedinis (Foa) is a soil borne fungus that cause dangerous disease called Bayoud. To control this tracheomycosis by using chemical methods is uneconomic and inefficient. The practical way for controlling the disease by IPM (Integrated disease management) focused by cultural methods, biological control with antagonistic and mycoparasitic microorganisms, and genetical control by selecting of resistant high quality cultivars, it may will be the best solution against this disease.
Citation Analysis of Education Dissertations for Collection Development
Year: 2013

The reference lists of forty three education dissertations on curriculum and instruction completed at the University of Minnesota during the calendar years 2000 2002 were analyzed to inform collection development. As one measure of use of the academic library collection, the citation analysis yielded data to guide journal selection, retention, and cancellation decisions. The project aimed to ensure that the most frequently cited journals were retained on subscription. The serial monograph ratio for citation also was evaluated in comparison with other studies and explored in the context of funding ratios. Results of citation studies can provide a basis for liaison conversations with faculty in addition to guiding selection decisions. This research project can serve as a model for similar projects in other libraries that look at literature in education as well as other fields.
Potential Health Benefits of Deep Sea Water: A Review
Venue: Evidence based complementary and alternative medicine eCAM
Year: 2016

Deep sea water (DSW) commonly refers to a body of seawater that is pumped up from a depth of over 200 m. It is usually associated with the following characteristics: low temperature, high purity, and being rich with nutrients, namely, beneficial elements, which include magnesium, calcium, potassium, chromium, selenium, zinc, and vanadium. Less photosynthesis of plant planktons, consumption of nutrients, and organic decomposition have caused lots of nutrients to remain there. Due to this, DSW has potential to become a good source for health. Research has proven that DSW can help overcome health problems especially related to lifestyle associated diseases such as cardiovascular disease, diabetes, obesity, cancer, and skin problems. This paper reviews the potential health benefits of DSW by referring to the findings from previous researches.
Planning for Disaster Resilience in Japan: Integration of 'Build Back Better'
Venue: Indian Journal of Public Administration
Year: 2019

'Build back better' as a policy, is an integral part of planning for disaster resilience in Japan. This policy puts emphasis on addressing the underlying causes of disaster vulnerability during the recovery process so that people, infrastructures and assets can withstand the impacts of future disasters. Enforcing 'Build back better' policy offers a range of benefits: it prevents loss of life and property from future disasters; it stimulates economic activities; and it generates co benefits. However, as a policy, countries around world do not have a common understanding of what 'build back better' means, including how to achieve and sustain it. This article reviews the case of Japan and argues that enforcement of 'Build back better' policy demands regular drills and simulations, making it part of the 'culture of resilience'