Miracle-dz/UniFAR-FTUs huggingface dataset:
TO FOLLOW OR TO UNFOLLOW: MOTIVES FOR THE ACADEMIC USE OF TWITTER

Twitter appears to be a popular social media service for academics, especially computer scientists. While some studies have begun to examine motives for academic Twitter use, little is known about academics’ considerations for following and unfollowing other users. Based on the uses and gratifications theory and prior research, we conducted an online survey among 54 computer scientists. Results show that academic Twitter use is generally characterized by information motives as well as by various social considerations. As the main reasons for using Twitter, we identify dissemination and, to a lesser degree, collection of information. However, users are also motivated by community development considerations. Accordingly, when following an account, users do not only look for content that is informative, interesting, of high quality, and current. They also tend to follow an account whose owner shares similar research interests, is an important researcher in the field, and that is personally known and liked. Unfollowing, while rather ubiquitous, is largely driven by considerations of content. To summarize, we find that academics’ subjective considerations oscillates between content and personal aspects, with content aspects driving usage, but personal aspects also shaping following decisions. These insights contribute to the current state of research on motives of academic Twitter usage finding that information and community development motives play central roles in the ensuing communication behavior and structures.
A Development Framework for Normalized Systems (Extended abstract)

—The theory of Normalized Systems addresses the problem of developing information systems that can evolve over time, by guaranteeing that each new feature can be implemented with a limited number of changes that does not depend on the actual size of the system. The theory is supported by a software architecture that includes a set of ﬁve distinct elements to implement the application logic. One of those elements is the workﬂow element, which represents a sequence of actions and can be used to implement process behavior based on state machines. In this work, we propose a different approach to the implementation of process behavior in Normalized Systems. Speciﬁcally, the approach is based on the use of rules and events as ﬁne-grained elements to build complex behavior. Our previous experience in the retail industry suggests that such approach is capable of dealing with the increasing complexity of business processes in that sector. We also discuss some details regarding the implementation of this new architecture on top of a popular technological platform and its supporting tools.
Contextual Food Recommendation Through Factorization Machines

This paper aims at bringing recent advances in the area of contextual recommendation systems into the food domain, namely by experimenting with models based on factorization machines for recommending food items. This problem domain has several unique characteristics that motivate the usage of modern approaches that can deal well with a large number of contextual features, given that the consumption of food items is associated to heterogeneous information about ingredients, their chemical composition, nutritional aspects, cooking methods, ingredient combination effects, as well as monetary costs, availability, cultural, social and even environmental factors. We propose to model user preferences of food items as an aggregation of extracted features, latter leveraging factorization machines to capture latent low-rank interactions between the features. Experiments with three datasets related to user ratings for recipes attest for the effectiveness of this approach, showing that considering contextual attributes leads to gains in terms of recommendation performance.
Photoperiod effects on carcass traits, meat quality, and stress response in heart and lung of broilers

This study evaluated effects of photoperiod treatments on slaughter and carcass traits, meat quality, indicators of oxidative stress, and heat shock protein 70 (Hsp70) levels of lung and heart tissues in broilers. Five hundred Ross 308 broiler chicks were used. The treatments consisted of 23 hours of continuous light and one hour of darkness (23L1D), four hours of light followed by two hours of darkness (4L2D), eight hours of light and four hours of darkness (8L4D), and 16 hours of light and eight hours of darkness (16L8D). After 42 days, two birds from each replicate were slaughtered. Birds that had been subjected to 16L8D had lower slaughter, carcass, and breast weights than the other treatments. Significant correlations were observed for slaughter, carcass and breast weights and white stripe. At 10 min post mortem, the pH of the breast was the highest in 23L1D. Breasts from birds subjected to 23L1D and 16L8D had most fat and least protein, while white striping was not different among treatments. The 4L2D treatment resulted in the highest lung glutathione (GSH) concentration. Malondialdehyde (MDA) and GSH concentrations in the heart tissues of broilers from 8L4D and 4L2D were greater than those from 23L1D and 16:8. Glutathione peroxidase (GSH-Px) and superoxide dismutase concentrations were greatest for birds subjected to 16L8D. Heat shock protein 70 was lowest in lung and heart from birds subjected to 8L4D. Thus, shorter and more frequent periods of darkness can be recommended for welfare with little compromise in performance. Keywords: carcass quality, heat shock protein 70, oxidative stress, white stripe
BankOnBox Fraud Detector

Link Consulting is a portuguese company that owns an internet banking application that allows users to remotely access their bank accounts via internet and do the same operations they would on ATM. But as many other applications this one can also be a victim of malicious users, therefore needing security mechanisms to prevent fraud attacks. The system BankOnBox Fraud Detector allows the detection of fraud in historical data or in a real time transaction. An interface was also designed to allow the Back Office users to keep track of possible malicious users or to performance maintenance of the BankOnBox Fraud Detector System. The evaluation of the system showed that all the planned functionalities were completed and also showed the potential of this system in a real internet banking application.
Learning Boundary Edges for 3D‐Mesh Segmentation

This paper presents a 3D‐mesh segmentation algorithm based on a learning approach. A large database of manually segmented 3D‐meshes is used to learn a boundary edge function. The function is learned using a classifier which automatically selects from a pool of geometric features the most relevant ones to detect candidate boundary edges. We propose a processing pipeline that produces smooth closed boundaries using this edge function. This pipeline successively selects a set of candidate boundary contours, closes them and optimizes them using a snake movement. Our algorithm was evaluated quantitatively using two different segmentation benchmarks and was shown to outperform most recent algorithms from the state‐of‐the‐art.
From a monolithic to a microservices architecture Hierarchical clustering modularity re-engineering through transactional contexts

Microservices are considered a hot trend, with every company that implements it having an exclusive blog detailing every change in its codebase. Its functional decomposition and scaling capabilities coupled with autonomous development makes it highly valuable in business comparing to a traditional monolithic approach. This thesis researches the scope regarding the incremental migration from a monolithic to a microservices architecture, merging all background and principles necessary for the development of tools that assist developers on this process while addressing software re-engineering concepts, such as domain-driven design, code analysis and graph clustering. The proposed method starts with the retrieval of information regarding the relationship between the classes and controllers of an application, subsequently applying hierarchical clustering with a similarity measure based on controller access. This allows us to explore transactional contexts while addressing the migration issue of context separation. The results of this approach, paired with an user interface with visualization capabilities, allows the ﬁlling of a gap in terms of support tools that exist for software architecture migrations. The comparison of our approach with software architecture formal tools and expert decompositions resulted in high precision values, that reﬂect that accurate service candidates are produced. The approach proposed in this thesis asserts that from the transactional contexts of an application, modular conclusions can be drawn, while also showing that it can better inform developers in the process of an architecture migration to microservices.
SEQUENCE IDENTIFICATION AND GENETIC PROFILE OF FMDV IN A 2007 DISEASE OUTBREAK IN ISRAEL USING FULL LENGTH GENOMIC ANALYSIS

FMD is endemic and widely spread among various animal species in the Middle East. Periodically devastating epidemics occur that spread rapidly across national borders. In 2007, Israel was severely affected by serotype O epidemics despite the presence of a national compulsory vaccination program using a trivalent vaccine in cattle (containing types O, A22 and Asia1) and a monovalent vaccine in small ruminants (containing type O). Three strains of serotype O are included in the vaccine: O1 Manisa, Geshure Isr/2/85 and 3039. In addition to the unexpected nature of the outbreak, instances of mortality in affected goats were reported. To understand the genetic characteristics of the virus causing this outbreak, and analyze the possible source for these antigenic variants, a complete genome analysis of isolates obtained from geographically distinct regions affected by the outbreak was conducted. Six specimens from FMDV infected animals were selected for analysis including one probang and four tongue epithelium samples from affected cattle and one cardiac tissue sample from an affected goat. Viral genomic sequences were amplified using RT-PCR with primers that produced overlapping fragments which were subjected to automated dideoxy sequencing methods. Similarities between the nucleotide and amino acid sequences of the complete ORF among the six virus isolates demonstrated greater than 98.9% and 99.2%, respectively. Phylogenetic analysis of the P1 region of all six viruses revealed that they belong to a unique sub-lineage of the O serotype. They were also distinct from two vaccine strains (O1 Manisa and Geshur Isr2/85) used in the vaccination program, and were also distinct from other known type O FMDV isolates from Turkey between 1989 and 2000. Further analysis of the VP1 region on 446 type O viruses from GenBank revealed that the cluster of Israel isolates was more related to strains isolated from South-Asia in Bhutan, Nepal and Malaysia than those from the Middle East during 2003 and 2004, although this result may have been biased by incomplete representation of samples from the region in GenBank. Full length viral genome sequence analysis applied to FMDV outbreaks is of importance in the characterization of outbreak isolates and may facilitate identification of viral genetic attributes linked to the pathogenesis of emerging FMDV isolates.
ARENA: Asserting the Quality of Modeling Languages

Nowadays, we assist at a growing number of mobile and desktop applications. Some of them are developed using programming languages, the traditional way, while some have been developed using other approaches, such as Model-Driven (Software) Development ― MD(S)D. It considers models as first class elements in the context of software development. Since there are so many modeling languages, there is a need to compare them and choose the best for each concrete situation. The selection of the most appropriate modeling language may influence the output's quality, whether it is only a set of models or software. This Thesis has the main purpose of creating and debating a framework to evaluate the quality and effectiveness of developed Domain-Specific Modeling Languages, taking into account their domains and the influence they have when models are created. It should also be useful for General-Purpose Modeling Languages.
Optimizing Service Protection with Model Driven Security@run.time

Enterprises are more and more involved in collaborative business. This leads to open and outsourcing all or part of their information system (IS) to create collaborative processes by composing business services picked in each partner IS and to take advantage of Cloud computing. Business services outsourcing and their dynamic collaboration context can bring lost of control on IS and new security risks can occur. This leads to inconsistent protection allowing competitors to access to unauthorized information. To address this issue, systematic security service invocations may be added, without paying attention to the business context leading to costly over protection. To address this issue, an adaptive security service model deployment is required to provide a business service consistent protection by taking into account the collaboration context (business service data criticity, partners involved in the collaboration, etc.), and the cloud deployment and execution environment. In this paper, we propose an adaptive security model based on MDS@run.time, the marriage of Model Driven Security (MDS) and Models@run.time approaches, allowing to select at runtime the appropriate security components to apply. The MDS approach is used to generate security policies, which are interpreted at runtime and load appropriate security mechanisms depending on the context (which takes advantage of the Models@run.time approach) ensuring business process end to end protection. A proof of concept prototype is built on top of the OW2 FraSCAti middleware, validating our proposition efficiency. Our experiments and simulations show that MDS@run.time improves the system efficiency when the over-protection risk rate increases.
Medium chain fatty acid feed supplementation reduces the probability of colonization in broilers

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Medium chain fatty acid feed supplementation reduces the probability of colonization in broilers Twan van Gerwe, Annemarie Bouma, Don Klinkenberg, Jaap A. Wagenaar, Wilma F. Jacobs-Reitsma, Arjan Stegeman
Matching Census Data Records

Record Linkage is the task of matching two records that refer to the same entity. In Portugal, Statistics Portugal started a study to use administrative data in the Census. However, due to inconsistent and anonymised data, Statistics Portugal was unable to pair all the records. In this context, this work aims to match records of administrative databases for improving the process of the Portuguese data Census. This dissertation presents methods for record linkage taking into account effectiveness, efficiency and related Census works. Moreover, presents a record linkage system based on Supervised Learning as well as methods to evaluate the results. Our methodology led to an increase of the records matched where the best result was between BDIC (Civil Population Register) and AT (Tax Authority) by pairing 244 903 records which represent a 60.95% increase.
Skill-based Progression Model for Smash Time

Nowadays an increasing number of games use procedurally generated content to provide immersive and engaging gaming experiences. Most of the endless single player games generate content just based on the difficulty of the challenges combined with the duration of the current game session. In this dissertation, we address the problem of keeping the players engaged in a game for longer periods of time generating game content that is modeled according to the player’s performance, to improve the gameplay experience. In order to increase the overall gameplay experience of a game, we should increase the feeling of progression. To solve this problem, we propose a progression model that creates content based on the player skill and performance to overcome those challenges. We also propose to control the variety of the challenges to create a better gameplay experience. We theorize that, by providing a progression that is adapted to the player based on the player skill, keeping the variety of the challenges will lead to more engaging and fun gameplay experiences, increasing the replayability in single player games. We propose a progression model that uses player skill and challenges’ variety, in the endless level of the mobile game Smash Time. With this work, we believe to have created a skill-based progression model that is robust and dynamic enough to be used in different types of games and that excludes the need of using preset difficulty settings and/or adaptation rules. The results from playtests with users suggest that the developed skill-based progression model is able to increase the number and duration of the game sessions. The results also suggest that the progression model has the potential to increase player immersion, and consequently to create more engaging gameplay experiences. With the potential to create longer and more engaging gameplay experiences as well as to increase their frequency, comes the possibility to, ultimately, increase the overall lifetime of the game itself.
Radiation Damage in Structured Silicon Semiconductor Detectors

The basic mechanisms of radiation damage in silicon detectors and their consequences on detector performance are described. This is done for two very different applications: spectroscopic imaging detectors as used in X-ray astronomy and position measuring tracking detectors which have to work in the extreme radiation environment of presently constructed particle colliders. The areas most prone to damage are identified and suggestions are given for improving the design or altering the concept. 80805 München – Föhringer Ring 6
The influence of dietary protein intake on the responsiveness of skeletal muscle to resistance exercise training in older adults

Sarcopenia can have serious consequences for health and quality of life. As the main drivers of anabolism, resistance exercise and protein ingestion may potentially be targets for interventions to alleviate these effects. Hence, two systematic reviews were conducted. Results of Chapter 2 indicated no augmentation of the effects of RET when older adults were supplemented with protein. Chapter 3 aimed to assess the effects of protein timing and distribution, but identified only six studies indicating a lack of research in the area. In Chapter 4, habitual protein intake in older adults was assessed to identify potential areas for improvement. While total intake was sufficient, distribution across meals was highly skewed, which is suboptimal according to current thinking. Chapter 5 compared effects of even and uneven protein distributions, alongside two weeks of resistance exercise, in women ≥65 years. A stable isotope protocol (deuterated water) was used to measure muscle protein synthesis. There was no significant difference in MPS between even (trained leg 1.02%.day-1) and uneven (1.16%.day-) diets, or in muscle strength change. These results do not support the theory of an optimal protein distribution based on the maximal MPS threshold dose, although there is potential for future research.
LPS-Induced Inflammation Alters Cytokines in Amniotic Fluid andSerum of Pregnant Wistar Rats and their Offspring

Intrauterine inflammation is a major cause of early pregnancy loss and impaired fetal growth, besides associated with the biogenesis of neuropsychiatric disorders such as autism spectrum and schizophrenia. Animal models of maternal immunity activation aim to elucidate the inflammatory mechanisms and their relationship with neurodevelopmental disorders. Thus, we investigated the effects of LPS-induced inflammation at different doses in female rats and their relation with the duration of the inflammatory event and maternal changes. Pregnant Wistar rats were grouped and treated once (on E17) or 3 times (on E15-E17) with LPS (15 or 150 μg/kg, IP). LPS at a concentration of 150 μg/kg, both in single and repeated doses, impaired gestational weight gain, in addition to cause death in 23.07% of the rats and significantly decreasing the number of live-born pups. LPS injection increased the level of TNF-α in the amniotic fluid which decreased 72 hours after injection, with no changes in these cytokines in the maternal serum. IL1-β was increased in amniotic fluid after a single dose of LPS (150 μg/kg) but decreased after the application of 3 doses, with a difference between the duration of treatments at this dose. Also, was increased in the offspring serum following 3 repeated doses of LPS 150 μg/kg. IL-6 was increased in amniotic fluid at a single dose of 150 μg/kg and decreased after three days of daily LPS injections. There was an increase in maternal serum IL-6 levels at doses of 15 μg/kg applied once and 150 μg/kg after 3 consecutive injections. IL-10 was increased in amniotic fluid after both doses of LPS applied once but decreased 72 h after application of the highest dose. In the maternal serum, only the highest dose increased IL-10 after 72 hours of LPS. These findings demonstrate that even a single dose of low LPS concentration is sufficient to activate the maternal immune system and may have a direct implication on gestational progress that could affect fetal development.
3-D Sound Enhanced Presence in Virtual Environments

Virtual Environments (VEs) are being widely used to improve communications between collocated users. A development of a VE is mostly concerned in oﬀering a high quality graphics visualization system to enhance presence. It is known that sound can reduce visual workload and improve awareness of information outside users’ ﬁeld of view. Im-pressively, these values are usually forgotten, and the sound system is just used to reproduce some 2-D sound eﬀects. To encourage the use of a 3-D sound system when developing an Immersive Virtual Environment (IVE), we performed three diﬀerent experiments. Our focus was the beneﬁts of us-ing 3-D sound to improve navigation and enhance presence. We also measured the subjective perception of sound when the loudspeakers were hidden or visible. 3-D sound proved to be essential not only to enhance presence (experiment 1) but also to improve navigation, orientation and way-ﬁnding (experiment 2). Experiment 3 proved that a simple, cheap and eﬀortless technique enables greatest positioning errors between the image and the sound and improves users’ con-ﬁdence and correctness.