Miracle-dz/UniFAR-FTUs huggingface dataset:
A METHOD FOR DISPERSING PARTICLE FILLERS IN THERMOPLASTIC COMPOSITES USING COMMINGLED YARNS

The incorporation of particles in a polymer material has the potential to increase the toughness of the polymer, and thereby potentially also the toughness of a fibre-reinforced composite material in which the polymer is used as a matrix. Particle-toughening of thermoset polymers is an established state-of-the art technique; the toughness of thermoplastic polymers – already higher than that of thermosets – may be further enhanced by using the same particle-toughening principle, leading to materials with even better performance. We present a simple and effective method for dispersing alumina nanoparticles inside a non-consolidated woven textile of continuous glass fibre-polyamide 6 commingled yarns that, when consolidated, produce thermoplastic composites with particle-filled matrices. The wet pick up of the particle suspension by the textile and the dispersion quality of the particles inside the fibrous architecture is reported. The effect of the hard Al2O3 particles on the fracture properties of the PA6 polymer is studied using single-edge cracked plate tests, indicating increased JIc values due to the particles in the PA6 matrix system. However, double cantilever beam tests investigating the effect of the particles on the interlaminar fracture toughness of the fibrereinforced thermoplastic composite material were inconclusive due to the failure of the material by transverse yarn debonding rather than by interlaminar failure.
Changes in Industry Leadership and Catch-up by the Latecomers : Toward a theory of catch-up cycles

This paper proposes an explanation of successive changes in industry leadership (which we call catch-up cycles) in which new firms and countries emerge in international leadership of a sector and others decline, and in which also the new leaders are then dethroned by other newcomers. This paper proposes to take a sectoral system view and, within that framework, to identify windows of opportunity that may emerge during the long run evolution of a sectoral system. Three windows related to the specific dimensions of a sectoral system are proposed: one related to changes in knowledge and technology, the second to changes in demand and the third to changes in institutions and public policy. The paper claims that it is the combination of the opening of a window (technological, demand or institutional/policy), the presence of capabilities and the appropriateness of responses/strategies by the actors that determines the changes in industrial leadership and catch up by latecomer firms. Sectors differ according to the type of windows that may open up most frequently may open up and to the patterns of change in the market shares among the key players. The paper discusses the cases of nine sectors, ranging from high technology (camera, semiconductors, mobile phones and aircraft), to scale intensive sectors (steel and shipbuilding), to service sectors (IT services and games) and to traditional ones (wine).
Metadata of the chapter that will be visualized in SpringerLink

The International Data Spaces Association (IDSA) has promoted the idea of International Data Spaces as a place for companies to share data with trust and security enforced by software and organizational competence. There has been considerable progress in delivering corporate guidelines, technical specifications, and software components available for testing and deploying applications to support IDS-based ecosystems, such as the IDS data connectors classified by the Fraunhofer Institute. However, full implementation of IDS applications seems still complex and expensive for small and medium enterprises (SMEs). A possible strategy to deal with such an issue is to break the IDSA specification’s complexity into smaller pieces and build small IDS ecosystems formed by its core business roles (e.g., data owners, users, and broker service providers). In this context, this paper addresses the problem of designing an application to support the broker service provider’s role in operating in an IDS-based ecosystem. This research, therefore, follows a Design Science approach in a three-step process. First, it investigates problems of practical relevance elicited from the IDSA guidelines in combination with requirements provided by representatives of the Dutch Logistics sector. Second, it gives design to tackle the problem by combining Semantic Web, Linked Data, and Enterprise Architecture modeling artifacts. Last, it validates the architecture of the broker service provider’s application by demonstrating its technical feasibility, innovation, and software integration.
PE-TU Participation at TAC 2018 Drug-Drug Interaction Extraction from Drug Labels

The Drug-Drug Reaction Extraction at NIST TAC 2018 conference aims to extract information on drug reactions from drug labels. In this paper, we describe the PE-TU’ model participated in mention extraction task. We provided a hybrid method that combines a dictionary-based, rule-based and machine learning techniques to extract mention from mention label text. The pipeline process of our method contains data graph creating, feature designing and model training, which are built on the machine learning platform, Saul. The experimental results prove the efficiency of our methods.
THE USE OF PAIR COMPOSITION METHOD ON STUDENTS’ DESCRIPTIVE WRITING SKILL

Abstract: This research was aimed to find out roles of pair composition method on students’ behaviour in learning processes and their writing assessment, and also to find out students’ attitude toward learning process of pair composition method in writing descriptive text in the classroom. Descriptive qualitative method was used in this research. The participants were 33 students of X grade of Senior High School. The data were collected from observation, the result of analysis showed that 66% of the seriousness of students during learning process was high, 78% of enthusiasm of students in doing task was high, and 58% of students’ participation was high. The increasing of students’ assessment was 18,7 from the average score before. The data collected from interview and questionnaire indicated that pair composition method provided the opportunities for sharing ideas, developing text, corresting writing errors, motivating students being active, and 50% students strongly agreed that pair composition method on writing descriptive text was lively and enjoyable. Keywords: Active learning strategy, cooperative learning, pair composition method, descriptive writing, descriptive text.
AREA EFFICIENT CORDIC FFT USING ERROR CORRECTION CODES AND PARSEVAL CHECKS FOR OFDM SYSTEMS

In the present Digital Communication systems, it is highly possible that the data or message get corrupted during transmission and reception through a noisy channel medium which leads to the injection of random bits into the original message and corrupt the original message. For some applications, an option is to use Algorithmic-Based Fault Tolerance (ABFT) techniques that try to exploit the algorithmic properties to detect and correct errors. One example is Fast Fourier transforms (FFTs) that is used in spectral analysis in the communication for Time to Frequency transform in the receiver side. There are several protection schemes to detect and correct errors in FFTs. The Parseval or sum of square check is the most widely known. It is most common to find several blocks operating in parallel in the modern communication systems. Recently, a new technique called Fault tolerant parallel filters has been proposed. In this work same technique is first applied to protect Cordic based FFT and then the protection schemes that combine the use of Error Correction Codes and Parseval checks are proposed and the area reduction of 12% was observed. The Power, area and delay is analyzed in Cadence using 180 nm Technology for 8-pointprotected FFT with input 32 bit length. Simulation and Compilation report for FFT using ECC, SOS and ECC-SOS are obtained in Modelsim-Altera 6.4a and Quartus II 9.0.
Study of pollution tolerance index for plant species exposed to vehicular traffic on urban streets

The problem of air pollution has become complex than any other environmental challenges as one cannot produce fresh ambient air to respire. Plant species reduce pollution through their leaf and other aerial surfaces from air by sedimentation and impaction process. In the present work, distinctive changes in plant towards air pollution were assessed by studying their biochemical contents to determine the value of air pollution tolerance index. The plant species chosen were Azadirachta indica, Dalbergia sisso, Ficus religiosa and Delonix regia grown-up as roadside plantation. The site was exposed to constant vehicular traffic plying on Najafgarh road network in Delhi. The tolerance index value was found to be maximum for Dalbergia sisso (16.59) followed by Azadirachta indica (14.66), Ficus religiosa (12.41) and last for Delonix regia (8.78). The values indicated a range for sensitive to tolerant kind of plant species growing under air pollution affected areas. The anticipated performance value for individual species was also evaluated to determine the benefits from physical features to other socio-economic uses in society. The study of pollution resistance feature in favor of urban vegetation represented an alternative way against air pollution through green spaces developed around emissions from vehicular pollution.
Human-efficient Discovery of Training Data for Visual Machine Learning

Deep learning has enabled valuable computer vision applications in many domains. It can be used to assist domain experts, such as scientists, military, and medical doctors, to detect phenomena of interest quickly. Unfortunately, the manual effort to collect large training sets of domain-specific targets remains a deterrent to deep learning in these domains. Crowd-sourcing is not a viable solution, because the crowds do not have the professional knowledge to accurately label examples. Interesting objects are usually scarce. As a result, a single expert may need to go through millions of unlabeled examples to find a few positive instances of a target.
TopHat: A formal foundation for task-oriented programming

Software that models how people work is omnipresent in today's society. Current languages and frameworks often focus on usability by non-programmers, sacrificing flexibility and high level abstraction. Task-oriented programming (TOP) is a programming paradigm that aims to provide the desired level of abstraction while still being expressive enough to describe real world collaboration. It prescribes a declarative programming style to specify multi-user workflows. Workflows can be higher-order. They communicate through typed values on a local and global level. Such specifications can be turned into interactive applications for different platforms, supporting collaboration during execution. TOP has been around for more than a decade, in the forms of iTasks and mTasks, which are tailored for real-world usability. So far, it has not been given a formalisation which is suitable for formal reasoning. In this paper we give a description of the TOP paradigm and then decompose its rich features into elementary language elements, which makes them suitable for formal treatment. We use the simply typed lambda-calculus, extended with pairs and references, as a base language. On top of this language, we develop TopHat, a language for modular interactive workflows. We describe TopHat by means of a layered semantics. These layers consist of multiple big-step evaluations on expressions, and two labelled transition systems, handling user inputs. With TopHat we prepare a way to formally reason about TOP languages and programs. This approach allows for comparison with other work in the field. We have implemented the semantic rules of TopHat in Haskell, and the task layer on top of the iTasks framework. This shows that our approach is feasible, and lets us demonstrate the concepts by means of illustrative case studies. TOP has been applied in projects with the Dutch coast guard, tax office, and navy. Our work matters because formal program verification is important for mission-critical software, especially for systems with concurrency.
Boresight Alignment with the DArk Matter ParticleExplorer

The DArk Matter Particle Explorer (DAMPE) can measure $\gamma$-rays in the energy range from a few GeV to about 10 TeV. The direction of each $\gamma$-ray is reconstructed with respect to the reference system of the DAMPE payload. In this proceeding, we adopt a maximum likelihood method and use the $\gamma$-ray data centered around several bright point sources to measure and correct the angular deviation from the real celestial coordinate system, the so called "boresight alignment" of the DAMPE payload. As a check, we also estimate the boresight alignment for some sets of simulation data with artificial orientation and obtain consistent results. The time-dependent boresight alignment analysis does not show evidence for significant variation of the parameters.
What all the noise is about : the physical basis of cellular individuality

Noise has been traditionally viewed as undesirable in biology, resulting in disorder, distortion, and disruption, and ultimately as something that needs to be filtered and removed. More recently, it has been shown that noise can also be beneficial. We briefly review historical developments pertaining to noise in biological physics, and some of the current research in the field of molecular and cellular biophysics. PACS Nos: 87.18. Tt, 05.40. Jc, 87.10. Mn, 87.10. Rt, 87.16. Yc, 87.23. Kg Résumé : Traditionnellement, le bruit a été vu comme étant indésirable en biologie, résultant en désordre, distorsion et perturbation, et ultimement comme quelque chose qui doit être filtré et éliminé. Dernièrement, la recherche a démontré que le bruit peut être utile. Dans ce travail nous passons brièvement en revue les développements historiques touchant le bruit dans le domaine de la physique biologique et la recherche actuelle en biophysique moléculaire et cellulaire. A historical perspective In 1827 a botanist named Robert Brown observed pollen particles moving about randomly in a fluid [1, 2]. He observed this with all sorts of nonliving materials including minerals, woods, and century-old dried out plants, and concluded that the erratic movements were not a property of living organisms. Many years later, physicist Georges Gouy [3] conceived that the motion observed by Brown was a result of the irregular thermal fluctuations of the molecules in the liquid. This phenomenon is now called Brownian motion (BM). It was a young Albert Einstein who worked out the now famous result describing the mean-square displacement (in one dimension) of a particle undergoing BM
CHARACTERIZATION OF A BYZANTINE MANUSCRIPT BY INFRARED SPECTROSCOPY AND THERMAL ANALYSIS

a National Museum of Romanian History/ Centre of Research and Scientific Investigation (MNIR/CCIS), 12 Calea Victoriei, 030026 Bucharest, Roumania b Department of Physical Chemistry, Faculty of Chemistry, University of Bucharest, 4-12 Bd. Regina Elisabeta, 030018 Bucharest, Roumania c National Institute for Research and Development in Electrical Engineering INCDIE ICPE-CA, 313 Splaiul Unirii, 030138 Bucharest, Roumania d “Prof. Ivan Dujčev” Centre for Slavo-Byzantine Studies, 18 Prof. Ivan Dujčev Str. , 1618 Sofia, Bulgaria e National Research and Development Institute for Textiles and Leather, Division Leather and Footwear Research Institute (INCDTP-ICPI), 93 Ion Minulescu Street, 031215 Bucharest, Roumania f Department of Chemistry, Faculty of Sciences, University of Craiova, 13 A.I. Cuza Street, 200585 Craiova, Roumania
Knowledge Markets : Cooperation Among Distributed Technical Specialists

Knowledge management issues are highlighted when organizational functions are decentralized. For example, distributed computing environments place more computer power in the hands of the end-user, and often demand increased technical support. In response, organizations may choose to move technical support personnel close to endusers. This can isolate them from each other, and may limit their ability to share knowledge. Thus, the growth of distributed computing calls for an increased ability to share knowledge across organizational boundaries. In that context, this paper presents the results of a case study investigating the roles of knowledge markets among distributed technologists. Our perspective is that knowledge markets are cultural entities shaped by the underlying work culture of their participants, and that the cultural forces that define knowledge markets are powerful, deeply held and difficult to change. Thus, improving the effectiveness of any given knowledge market will have less to do with the installation of information technology than with the ability to create a facilitating work culture. This study’s identification of clique knowledge markets, operating efficiently in parallel to the public knowledge market, may provide a hint of the type of work culture that will foster knowledge trading.
Time Encoded Imaging of Neutrons and Photons Using CLYC Detector Equipped with a Dual Mode Collimator

Information about a radiation source’s position is essential for methods of simultaneous detection of neutrons and photons. The detection system that is capable of spatial mapping of radiation in two dimensions was developed. A single Cs2LiYCl6:Ce detector enriched in 7Li isotope (C7LYC) was equipped with a hybrid dualmode rotational collimator. The collimator was designed as a coded aperture (a modified uniformly redundant array) using lead and plastic components. C7LYC scintillator enables segregation of neutron signals from photon signals, and neutron and photon energy measurements. Radiation measurements were performed at different angular positions of the collimator using a single detector. Maximum likelihood expectation technique was utilized to generate the image of an assayed radiation source. Time encoded imaging of neutron and photon sources was demonstrated using this detection system.
SMART PARTS FABRICATION USING POWDER BED FUSION ADDITIVE MANUFACTURING TECHNOLOGIES

Metallic components with embedded sensors or smart parts can be a beneficial tool for monitoring harsh environments in the energy, biomedical, automotive, and aerospace industries. Smart parts maintain structural integrity with added functionality of sensing temperature, pressure, and structural health. A non-intrusive placement of a sensor in metallic components was developed using powder bed fusion additive manufacturing (AM). A paused build procedure was used to fabricate a proof of concept, a cylindrical shaped smart part using both electron beam melting (EBM) and selective laser melting (SLM) technologies. This paper focuses on the fabrication process and characterization of the smart part. A functional complex shaped energy system component, a smart injector was fabricated to demonstrate the applicability in harsh environments. The pressure and temperature sensing capabilities were tested using compressive cyclic loading and hot fire testing in a combustion chamber testing. A maximum sensing response of 3V was obtained for EBM fabricated smart part while applying compressive load. An image analysis based part positioning method was demonstrated for EBM technology that can be employed in other AM technologies to alleviate or completely remove misalignment in a paused build fabrication process.
TRANSPORT CHARACTERISTICS AND SUBTHRESHOLD BEHAVIOR OF HIGH-K DIELECTRIC DOUBLE GATE MOSFETS WITH PARALLEL CONNECTED GATES

Transport characteristics and subthreshold behavior of a structurally modified high-κ dielectric Double Gate MOSFET in which each gate was a parallel combination of three gates with different work functions were analyzed. Various scattering mechanisms were modeled through simple Bϋttiker probe method. The subthreshold leakage and the drain induced barrier lowering decreased and the threshold voltage increased when the screen gate workfunction was greater than the middle gate (control gate) workfunction. The improvement in the subthreshold parameters was further enhanced when high- κ materials were used as insulator layers. High workfunction parallel connected metal gates exhibited better ballisticity as energy relaxing scattering mechanisms in those devices were less because of the decrease in the critical scattering length. It was concluded that to enhance further the comparatively better subthreshold behavior exhibited by double gate MOSFETs with high- κ insulator materials, screen gates with large work function could be used.
Interactive comment on “ Are EARLINET and AERONET climatologies consistent ? The case of Thessaloniki , Greece ” by Nikolaos Siomos et al

In this study we investigate the climatological behavior of the aerosol optical properties over Thessaloniki during the years 2003-2017. For this purpose, measurements of two independent instruments, a lidar and a sunphotomer : , :::: were :::: used. These two instruments represent two individual networks, the European Lidar Aerosol Network (EARLINET) and the Aerosol Robotic Network (AERONET). They include different measurement schedules. Fourteen years of lidar and sunphotometer measurements were analyzed : , :::::::::::: independendly :: of ::::: each ::::: other, in order to obtain the annual cycles and trends of multiple :::::: various 5 optical and geometrical aerosol properties in the boundary layer, in the free troposphere and for the whole atmospheric column. The analysis resulted in consistent statistically significant and decreasing AOD 355nm trends of -21.0% and -16.6 :::::: -23.2% ::: and ::::: -22.3% per decade in the study period over Thessaloniki for the EARLINET and the AERONET datasets respectively. Therefore, the analysis implies ::::::: indicates : that the EARLINET sampling schedule can be quite effective in producing data that can be applied to :::::::: long-term climatological studies. It has also been confirmed :: is ::: also :::::: shown that the observed decreasing trend 10 is mainly attributed to changes in the aerosol properties ::: load : inside the boundary layer. Seasonal profiles of the most dominant aerosol mixture types ::::::: observed :::: over ::::::::::: Thessaloniki have been generated from the lidar data. The higher values of the extinction ::::::::::::: vertical-resolved ::::::::: extinction ::::::::: coefficient at 355nm appear in summer, while the lower ones appear in winter. The dust component is much more dominant in the free troposphere than in the boundary layer during summerwhile the opposite is observed in winter. The strongest biomass burning episodes tend to occur during summer . :::: The ::::::: biomass ::::::: burning ::::: layers :::: tend :: to ::::: arrive in the 15 free troposphere and are probably attributed to wildfires rather than agricultural fires that are predominant during spring and autumn :::::: summer. This kind of information can be quite useful for applications that require a priori aerosol profiles. For instance, they can be utilized in models that require aerosol climatological data as input, in the development of algorithms for satellite products, and also in passive remote sensing techniques that require knowledge of the aerosol vertical distribution.