Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatio-temporal composition of discard associated with the deep water rose shrimp fisheries ( Parapenaeus longirostris , Lucas 1846) in the south-central Mediterranean Sea

Discarding in fisheries is the fraction of the total catch brought on board and returned to the sea dead or alive for legal or eco - nomic reasons. The reduction of discard is one of the main objectives of the European Common Fishery Policy. This study aimed to improve the current knowledge of the discard associated with the deep-water rose shrimp (DPS) fisheries in the south-central Mediterranean Sea. We analyzed data collected from January 2009 to December 2013. Multivariate data analysis and generalized additive models (GAMs) were used to assess the spatio-temporal composition of the discard (which represented 36% of the total catch) and factors influencing its distribution. Multiple analysis of variance highlighted the significant effect of depth factor on discard assemblage. Moreover, in general, bony fish were the most discarded organisms (23.5%), while cartilaginous fish, crusta - ceans and other invertebrates represented approximately 13% of the total catch. GAMs showed that the fraction of discard in the catch presented significant variation regarding the years, depth and fishing ground. Although the negative trend in discard sug - gested that the DPS fisheries are moving towards a more sustainable exploitation, the discard fraction in some areas/assemblages remains high. Our results showed that most of the discard was due to species that had a minimum legal size (Hake, DPS, Trachurus spp.), and consequently would be subjected to the European discard ban. In order to improve the fisheries management, specific measures aimed to minimize the unwanted catches of undersized species need to be implemented.
The combined effect of Metarhizium anisopliae and some natural oils against Ephestia kuehniella and Ephestia cutella ( Lepidoptera-Pyralidae ) under laboratory and store conditions

The potential activities of four essential oils (Anise; Eucalyptus; Garlic and Rosemary) and microbial agent Metarhizium anisopliae and their combinations against Ephestia cutella and E. kuehniella were evaluated. In choice test, Rosemary and Eucalyptus revealed highly percentage of repellency after 5 days the repellency % recorded (72% & 50% ) ,respectively in case of E. kuehniella and (71% & 54% ) ,respectively in case of E. cautella . The most effective oil in enhancing the potency of M. anisopliae was Rosemary against insect species and decreased the LC50 of E. cautella and E. kuehniella, respectively. The least effective combination was M.a. + Anise and M.a. + Garlic in case of E. cautella and E. kuehniella, respectively. Accumulative mortality of larvae of tested insect species increased gradually with the increase of exposure intervals. The highest %. Of adult malformation was recorded in case of Rosemary+ M. a and Eucalyptus + M.an against tested insects. Rosemary oil was the most efficient oil in increasing the strength of M. anisopliae. The oviposition was mostly inhibited when stored gunny bags were covered with spraying foam with Rosemary+ M. anisopliae in both tested insects.
STRUCTURAL SEGMENTATION OF POINT CLOUDS WITH VARYING DENSITY BASED ON MULTI-SIZE SUPERVOXELS

Ground objects can be regarded as a combination of structures of different geometries. Generally, the structural geometries can be grouped into linear, planar and scatter shapes. A good segmentation of objects into different structures can help to interpret the scanned scenes and provide essential clues for subsequent semantic interpretation. This is particularly true for the terrestrial static and mobile laser scanning data, where the geometric structures of objects are presented in detail due to the close scanning distances. In consideration of the large data volume and the large variation in point density of such point clouds, this paper presents a structural segmentation method of point clouds to efficiently decompose the ground objects into different structural components based on supervoxels of multiple sizes. First, supervoxels are generated with sizes adaptive to the point density with minimum occupied points and minimum size constraints. Then, the multi-size supervoxels are clustered into different components based on a structural labelling result obtained via Markov random field. Two datasets including terrestrial and mobile laser scanning point clouds were used to evaluate the performance of the proposed method. The results indicate that the proposed method can effectively and efficiently classify the point clouds into structurally meaningful segments with overall accuracies higher than 96%, even with largely varying point density. * Corresponding author
CENTRE FOR APPLIED MACRO – AND PETROLEUM ECONOMICS ( CAMP ) CAMP Working Paper Series No 5 / 2017 Asset returns , news topics , and media effects

We decompose the textual data in a daily Norwegian business newspaper into news topics and investigate their predictive and causal role for asset prices. Our three main findings are: (1) a one unit innovation in the news topics predict roughly a 1 percentage point increase in close-to-open returns and significant continuation patterns peaking at 4 percentage points after 15 business days, with little sign of reversal; (2) simple zero-cost news-based investment strategies yield significant annualized risk-adjusted returns of up to 20 percent; and (3) during a media shortage, due to an exogenous strike, returns for firms particularly exposed to our news measure experience a substantial fall. Our estimates suggest that between 20 to 40 percent of the news topics’ predictive power is due to the causal media effect. Together these findings lend strong support for a rational attention view where the media alleviate information frictions and disseminate fundamental information to a large population of investors. JEL-codes: C5, C8, G4, G12
Information Technology and Quantitative Management ( ITQM 2017 ) TIDM : Topic-Specific Information Detection Model

Nowadays information control and detection on the social network have become a problem that we should solve as soon as possible. Unfortunately, due to the informal expressions, detecting the massive data on the internet is a big challenge based on the traditional text mining methods such as Topic Model. In our paper, we propose a simple 4-Tuple Structure instead of the raw text event which usually contains many meaningless words. Using the word embedding technique, we propose the Topic-Specific Information Detection Model (TIDM) for detecting the specific information. For training the words and idiomatic phrases, we adopt the supervise learning technique: manually constructing a specific Semantic Dataset for training our model. Our experiments based on the Amazon Reviews demonstrate that the TIDM can effectively detect and recognize the information. © 2017 The Authors. Published by Elsevier B.V. Selection and/or peer-review under responsibility of the organizers of ITQM 2017
VILLE TYRVÄINEN INFLUENCE OF ESPORTS SPECTATING ON CUSTOMER RE- TENTION IN FREEMIUM VIDEO GAMES

VILLE TYRVÄINEN: Influence of esports spectating on customer retention in freemium video games. Tampere University of Technology Master of Science Thesis, 53 pages, 5 Appendix pages November 2018 Master’s Degree Programme in Information and Knowledge Management Major: Data management Examiner: Professor Juho Hamari, Assistant professor Henri Pirkkalainen
Title A Joint Specification Test for Response Probabilities inUnordered Multinomial Choice Models

Estimation results obtained by parametric models may be seriously misleading when the model is misspecified or poorly approximates the true model. This study proposes a test that jointly tests the specifications of multiple response probabilities in unordered multinomial choice models. The test statistic is asymptotically chi-square distributed, consistent against a fixed alternative and able to detect a local alternative approaching to the null at a rate slower than the parametric rate. We show that rejection regions can be calculated by a simple parametric bootstrap procedure, when the sample size is small. The size and power of the tests are investigated by Monte Carlo experiments.
SETDB 2 Links E 2 A-PBX 1 to Cell-Cycle Dysregulation in Acute Leukemia through CDKN 2 C Repression

Acute lymphoblastic leukemia (ALL) is associated with significant morbidity and mortality, necessitating further improvements in diagnosis and therapy. Targeted therapies directed against chromatin regulators are emerging as promising approaches in preclinical studies and early clinical trials. Here, we demonstrate an oncogenic role for the protein lysine methyltransferase SETDB2 in leukemia pathogenesis. It is overexpressed in pre-BCR+ ALL and required for their maintenance in vitro and in vivo. SETDB2 expression is maintained as a direct target gene of the chimeric transcription factor E2A-PBX1 in a subset of ALL and suppresses expression of the cell-cycle inhibitor CDKN2C through histone H3K9 tri-methylation, thus establishing an oncogenic pathway subordinate to E2A-PBX1 that silences a major tumor suppressor in ALL. In contrast, SETDB2 was relatively dispensable for normal hematopoietic stem and progenitor cell proliferation.
Automated and Data-driven Computational Design of Patient-Specific Biomechanical Interfaces

Biomechanical interfaces are mechanical structures that form the connection between a device and a tissue region, and, through appropriate load transfer, aim to minimize tissue discomfort and injury. A patient-specific and data-driven computational framework for the automated design of biomechanical interfaces is presented here. Optimization of the design of biomechanical interfaces is complex since it is affected by the interplay of the geometry and mechanical properties of both the tissue and the interface. The proposed framework is presented for the application of transtibial amputee prostheses where the interface is formed by a prosthetic liner and socket. Conventional socket design and manufacturing is largely artisanal, non-standard, and insufficiently data-driven, leading to discrepancies between the quality of sockets produced by different prosthetists. Furthermore, current prosthetic liners are often not patient-specific. The proposed framework involves: A) non-invasive imaging to record patient geometry, B) indentation to assess tissue mechanical properties, C) data-driven and automated creation of patientspecific designs, D) patient-specific finite element analysis (FEA) and design evaluation, and finally E) computer aided manufacturing. Uniquely, the FEA procedure controls both the design and mechanical properties of the devices, and simulates, not only the loading during use, but also the pre-load induced by the donning of both the liner and the socket independently. Through FEA evaluation, detailed information on internal and external tissue loading, which are directly responsible for discomfort and injury, are made available. Further, these provide quantitative evidence on the implications of design choices, e.g. : 1) alterations in the design can be used to locally enhance or reduce tissue loading, 2) compliant features can aid in relieving local surface pressure. The proposed methods form a patient-specific, data-driven and repeatable design framework for biomechanical interfaces, and by enabling FEA-based optimization reduces the requirement for repeated patient involvement in the currently manual and iterative design process.
Design of a Learning Dashboard in "Self-Regulator" to Support Planning for Distributed Online Learning

“Self-Regulator” is a system embedded in a learning management system (LMS) to support students’ regulation of online learning focusing on the forethought phase in the self-regulated learning (SRL) academic cycle. Previous research indicates that, through its careful instructional design, Self-Regulator is effective in assisting students’ planning before actual learning and in reducing procrastination behavior. The purpose of this research is to present a new function, a learning dashboard, in order to improve SelfRegulator and thus foster students’ effective planning for learning regulation based on the learning regulation theories of SRL and co-regulation of learning (CoRL).
LEDs : the new revolution in lighting / Les LED : la nouvelle révolution de l ’ éclairage Historical perspective on the physics of artificial lighting Perspective historique sur la physique de l ’ éclairage

Mots-clés : Éclairage Diodes électroluminescentes Manchon à gaz Lampes Sources lumineuses We describe the evolution of lighting technologies used throughout the ages, and how the need for improvements was such that any new technology giving better and cheaper lighting was immediately implemented. Thus, every revolution in energy sources – gas, petrol electricity – was first put to large-scale use in lighting. We describe in some detail several “ancient” techniques of scientific interest, along with their physical limitations. Electroluminescence – the phenomenon by which LEDs directly convert electricity into light – was long thought to only be of use for indicators or flat panel displays supposed to replace the bulky cathode-ray tubes. The more recent uses of LEDs were mainly for street traffic lights, car indicators, small phone displays, followed by backlighting of TV screens. LED lamps for general lighting only emerged recently as the dominant application of LEDs thanks to dramatic decrease in cost, and continuous improvements of color quality and energy conversion efficiency. © 2018 Published by Elsevier Masson SAS on behalf of Académie des sciences. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Titre : Title : Analytical technologies for influenza virus-like particle candidate vaccines : challenges and emerging approaches Auteurs :

Influenza virus-like particle vaccines are one of the most promising ways to respond to the threat of future influenza pandemics. VLPs are composed of viral antigens but lack nucleic acids making them non-infectious which limit the risk of recombination with wild-type strains. By taking advantage of the advancements in cell culture technologies, the process from strain identification to manufacturing has the potential to be completed rapidly and easily at large scales. After closely reviewing the current research done on influenza VLPs, it is evident that the development of quantification methods has been consistently overlooked. VLP quantification at all stages of the production process has been left to rely on current influenza quantification methods (i.e. Hemagglutination assay (HA), Single Radial Immunodiffusion assay (SRID), NA enzymatic activity assays, Western blot, Electron Microscopy). These are analytical methods developed decades ago for influenza virions and final bulk influenza vaccines. Although these methods are time-consuming and cumbersome they have been sufficient for the characterization of final purified material. Nevertheless, these analytical methods are impractical for in-line process monitoring because VLP concentration in crude samples generally falls out of the range of detection for these methods. This consequently impedes the development of robust influenza-VLP production and purification processes. Thus, development of functional process analytical techniques, applicable at every stage during production, that are compatible with different production platforms is in great need to assess, optimize and exploit the full potential of novel manufacturing platforms.
Management of submucosal posterior gastric GIST by endoscopic assisted laparoscopic wedge gastrectomy-A modification of classical laparoscopic and endoscopic cooperative surgery

Laparoscopy and endoscopy can be used in tandem for tumors in difficult locations like submucosal gastrointestinal stromal tumor (GIST) in the posterior wall of the stomach. This combined approach ensures accurate localization of the tumors resulting in negative margins which would be much difficult to obtain by conventional laparoscopic approach alone. Endoscopic localization of tumor helps not only in accurate localization but also in observing for staple line integrity. The aim of the article is to show the use of both techniques in the management of submucosal GIST in a difficult location like posterior gastric wall.
BIOACTIVITY OF LEAVES OF MACARANGA SPECIES

LIM TY, LIM YY & YULE CM. 2014. Bioactivity of leaves of Macaranga species in tropical peat swamp and non-peat swamp environments. Very few studies have been reported on the chemical properties of peat swamp plants compared with their non-peat swamp counterparts. In this study, the total phenolic content, antioxidant activity and antibacterial activity of fresh Macaranga gigantea, M. hosei, M. hypoleuca, M. kingii, M. pruinosa and M. triloba leaf extracts from four tropical peat swamp forests and three non-peat swamp forests were measured and compared. Total phenolic content was measured by the Folin–Ciocalteu assay. Antioxidant activity was determined using the 1,1-diphenyl-2-picrylhydrazyl free radical scavenging and ferric reducing power assays, while disc-diffusion technique was used to determine the antibacterial properties. Reversed-phasehigh-performance liquid chromatography methods were used to identify and quantify the concentrations of phenolics. Antioxidant properties of leaf extracts from peat swamp forest species were 42 to 60% higher than those of the same plant species from non-peat swamp forest. However, no significant differences were observed for samples collected from within the same environmental conditions. No significant differences were found in antibacterial activities between peat swamp and non-peat swamp samples. The results suggest that trees in peat swamp forests are producing higher levels of phenolic compounds in response to extreme conditions.
Heavy metals soil contamination detection using combined geochemistry and ASD Field Spectrometry over a highly contaminated floodplain site in the United Kingdom

: Technological advances in hyperspectral remote sensing have been widely applied in heavy metal soil contamination studies, as they are able to provide assessments in a rapid and cost-effective way. The present work investigates the potential role of combining ﬁeld and laboratory spectroradiometry with geochemical data of lead (Pb), zinc (Zn), copper (Cu) and cadmium (Cd) in quantifying and modelling heavy metal soil contamination (HMSC) for a ﬂoodplain site located in Wales, United Kingdom. The study objectives were to: (i) collect ﬁeld- and lab-based spectra from contaminated soils by using ASD FieldSpec ® 3, where the spectrum varies between 350 and 2500 nm; (ii) build ﬁeld- and lab-based spectral libraries; (iii) conduct geochemical analyses of Pb, Zn, Cu and Cd using atomic absorption spectrometer; (iv) identify the speciﬁc spectral regions associated to the modelling of HMSC; and (v) develop and validate heavy metal prediction models (HMPM) for the aforementioned contaminants, by considering their spectral features and concentrations in the soil. Herein, the ﬁeld- and lab-based spectral features derived from 85 soil samples were used successfully to develop two spectral libraries, which along with the concentrations of Pb, Zn, Cu and Cd were combined to build eight HMPMs using stepwise multiple linear regression. The results showed, for the ﬁrst time, the feasibility to predict HMSC in a highly contaminated ﬂoodplain site by combining soil geochemistry analyses and ﬁeld spectroradiometry. The generated models help for mapping heavy metal concentrations over a huge area by using space-borne hyperspectral sensors. The results further demonstrated the feasibility of combining geochemistry analyses with ﬁled spectroradiometric data to generate models that can predict heavy metal concentrations. N. -E. -I.B. , Writing-Review K.M. P.A. B. ; N. -E. -I.B. ;
Behavioural patterns of the soft-shell clam Mya arenaria: implications for benthic oxygen and nitrogen dynamics

It is well established that benthic infauna alter sediment biogeochemistry, but the importance of their behavioural patterns in biogeochemical processes has only recently been fully appreciated. Using arrays of O2 microoptodes, siphon imaging, accelerometer loggers and different incubation approaches, we investigated the importance of behavioural patterns of the soft-shell clam Mya arenaria for benthic O2 and nitrogen dynamics. The investigations resolved a new behavioural component of buried M. arenaria: pedal water ejection (PWE). During PWE, the clams contracted their valves while briefly closing the siphon to expel oxic water previously accumulated within the mantle cavity through the pedal gape. Consequently, an upward-moving oxic plume embedded most of the shell, and oxia at the shell−sediment interface was observed for 15% of the total time of investigation. The buried clams displayed 2 additional behavioural stages: resting (R) and ventilation (V) that occurred for 57 and 28% of the time, respectively. During the V and PWE stages, the siphon of the clam was elongated above the sediment surface and surrounded by a dynamic oxic halo; both behavioural stages thus markedly increase the sediment oxygenation. The resolved irrigation patterns enhanced the benthic exchange of O2 and NH4 as well as the benthic denitrification rate, presumably via increased benthic NO3 supply and production. Particularly, the extensive sediment irrigation induced by the PWE stage has important implications for benthic nutrient cycling as well as for sediment oxidation and biogeochemical function of coastal sediments.
Higher Order Thinking through Bloom’s Taxonomy

The development of higher order thinking skills is crucial to academic success. The use of content as the basis of a SLA classroom promotes the acquisition of these skills alongside language skills. The use of Bloom’s Taxonomy as a framework for teaching and assessment is an effective way to structure a lesson, unit, or curriculum. The taxonomy includes both ways to assess knowledge (factual, conceptual, procedural, and metacognitive) as well as develop cognitive skills (remembering, understanding, applying, analyzing, evaluating and creating). Bloom’s Taxonomy is the perfect addition to any teacher interested in content based instruction (CBI) or adding cognitive elements to a non CBI situation. Rethinking the Taxonomy The role of cognitive skills in a content-based classroom should be self evident. If we are going to focus on the content in a meaningful way, then it follows that we must develop the subsequent cognitive skills that will give our students a chance to create meaningful content. Bloom’s Taxonomy is a way in which we as teachers can create better assessments and allow students to explore a greater depth of learning. This paper will focus briefly on the two basic aspects of Bloom’s Taxonomy that are applicable to many different SLA contexts and content-based instruction specifically. These are teaching higher order cognitive skills and assessing higher order
Managerial Use of Mobile Business Intelligence : An Exploratory Study

As a new trend in business intelligence (BI), mobile BI has been gaining increasing adoption by managers. However, there is little academic research about the managerial use of mobile BI. Adopting the key constructs of Task-Technology Fit theory as the theoretical lens, this exploratory study aims to deliver a preliminary understanding on why and how managers use mobile BI, from both the managers’ and the vendor’s perspectives. A case study was conducted with a large government authority whose mobile BI vendor is an industry leader worldwide. Semi-structured interviews were carried out with seven senior managers from this organization and the vendor. Through discussing the reasons why managers use mobile BI and their use patterns, a series of emergent propositions are drawn. This study not only contributes to this currently underexplored area of mobile BI, but also help enable the industry to make mobile BI products that better suit managers’ needs.