Miracle-dz/UniFAR-FTUs huggingface dataset:
Occurrence and predictive factors of psychiatric comorbidity in individuals with alcohol use disorders

Alcoholism is a disorder caused by an excessive and maladaptive pattern of alcohol consumption. A series of impairments can arise from such consumption, including psychiatric comorbidities. The objective of this study was to evaluate the rate of occurrence of anxiety and depression comorbidities in alcoholics and to investigate the associations of such comorbidities with the dose of ingested alcohol, period of alcohol use, personality traits and the presence of early emotional trauma. The sample consisted of 110 alcoholics, evaluated by the Structured Clinical Interview for DSM-IV (SCID-IV – clinical version) and recruited at the Hepatopathy Outpatient Service of a University Hospital. Data collection was individual and took place through the application of self-evaluation instruments. Statistical analysis was performed using parametric statistics with a significance level of p≤0.05. The main results showed that 46.3% of alcoholics had psychiatric comorbidities with mood disorders and/or anxiety. In addition, according to the logistic regression model, the increase in the doses of alcohol ingested and the presence of early emotional traumas were risk factors for the development of such comorbidities in alcoholics: (ODDS=1.18; p=0.005) and (ODDS=1.17; p=0.001), respectively. These data indicate the need for early intervention with regard to the primary care of both alcoholics who suffered early trauma and alcoholics who ingest large amounts of alcohol daily to decrease the risk of psychiatric comorbidities in this high-risk group.
K-Means Clustering Guided Generative Adversarial Networks for SAR-Optical Image Matching

Synthetic Aperture Radar and optical (SAR-optical) image matching is a technique of finding correspondences between SAR and optical images. SAR-optical image matching can be simplified to single-mode image matching through image synthesis. However, the existing SAR-optical image synthesis methods are unable to provide qualified images for SAR-optical image matching. In this work, we present a K-means Clustering Guide Generative Adversarial Networks (KCG-GAN) to improve the image quality of synthesizing by constraining spatial information synthesis. KCG-GAN uses k-means segmentations as one of the image generator’s inputs and introduces feature matching loss, segmentation loss, and L1 loss to the objective function. Meanwhile, to provide repeatable k-means segmentations, we develop a straightforward 1D k-means algorithm. We compare KCG-GAN with a leading image synthesis method—pix2pixHD. Qualitative results illustrate that KCG-GAN preserves more spatial structures than pix2pixHD. Quantitative results show that, compared with pix2pixHD, images synthesized by KCG-GAN are more similar to original optical images, and SAR-optical image matching based on KCG-GAN obtains at most 3.15 times more qualified matchings. Robustness tests demonstrate that SAR-optical image matching based on KCG-GAN is robust to rotation and scale changing. We also test three SIFT-like algorithms on matching original SAR-optical image pairs and matching KCG-GAN synthesized optical-optical image pairs. Experimental results show that our KCG-GAN significantly improves the performances of the three algorithms on SAR-optical image matching.
Worldwide training needs on Electronic Governance

In a world where entrepreneurship, global businesses, fast technological development, and specialization are the norm, the existing education system did not properly integrate the results from education and training on innovation and other fields relevant for the exploitation of research and technology, particularly in the public sector. The need to leverage e-Governance education and training in Europe is pointed out by many recent reports and studies. The purpose of this deliverable is to pinpoint the gaps in current education and training programmes in relation to eGovernance, highlight opportunities for the future of training and education in Europe, and propose recommendations for improvement. The analysis scope of the e-GOV 3.0 project is the exploitation of research results in the field of e-Governance. To fulfil these objectives, the present work provides, on the one hand, an overview of the existing e-Governance situation in education and, on the other hand, identifies trends for pointing out training gaps that should be covered. Chapter 1 presents the purpose and structure of the deliverable, while chapter 2 describes the method applied and tools used to identify the e-Governance training needs. Chapter 3 illustrates the collected data. Lastly, chapter 4 presents the analysis of the results, identifying the e-Governance training needsthat should be covered in the next work packages. Work package 2 will set up how future research directions can cover the identified training gaps of existing curricula. Work package 3 will create state of the art course curricula and modules based on the results of work packages 1 and 2.
Pneumonia Detection on Chest X-Ray Images using Convolutional Neural Networks Designed for Resource Constrained Environments

The problem of detecting pneumonia from X-ray images is considered here in the context of artificial intelligence. Particularly, in this work the possibility to use light-weight convolutional deep learning models is investigated from the perspective of building efficient recognition tools operating on portable equipment (resource-constrained resources), handy available to the medical personnel. Several state of the art lightweight deep neural network architectures as well as more complex (for better performance) ones were compared not only from the point of view of recognition accuracy but also from the complexity perspective. MobileNetV3, ShuffleNetV2 and SlimNet models with Android implementations in TensorFlow Lite are proposed to give a good compromise between accuracy and portability in building intelligent medical instruments.
Identifying Expert Reviews in the Crowd: Linking Curated and Noisy Domains

Over the past decade, vast number of online consumer reviews have made a significant presence on the Internet. These reviews play a vital role in consumer awareness about the products and deeply impact the consumer’s decision-making process. On one hand, websites like Amazon, Yelp provide huge collections of crowdsourced reviews, which are written by consumers themselves having experience in using that product. Many researchers argue about the credibility and bias of these reviews. These factors, coupled with the sheer plethora of reviews for each product, it can become tiring to form a perspective about the product. On other hand, websites like Wirecutter, Thesweetsetup provide hand-made highly curated detailed guides on products across various categories. Although these reviews are unbiased expert opinions, they require vigorous reporting, interviewing, and testing by various journalists, scientists, and researchers. Thus making them hard to scale. Our aim is to study the possible correlations between the crowd-sourced noisy domain reviews and the curated reviews. We take into account meta-features of reviews, context-based textual features of reviews and word-embedding based features of words from reviews. In addition to this, we identify “good reviews”, defined as those noisy domain reviews that align with the curated ones, and use this to propose a general purpose, extremely streamlined recommender that can provide value to the general public without any personalized inputs. This research will contribute significantly towards identifying unbiased crowd-sourced reviews that align with curated reviews, across different categories of products, thereby linking the curated and noisy domains. Our research will also contribute significantly towards understanding the intricacies of good product reviews across different categories.
DNA-based client puzzle for WLAN association protocol against connection request flooding

In recent past, Wireless Local Area Network (WLAN) has become more popular because of its flexibility. However, WLANs are subjected to different types of vulnerabilities. To strengthen WLAN security, many high security protocols have been developed. But those solutions are found to be ineffective in preventing Denial of Service (DoS) attacks. A ‘Connection Request Flooding’ DoS (CRF-DoS) attack is launched when an access point (AP) encounters a sudden explosion of connection requests. Among other existing anti CRF-DoS methods, a client puzzle protocol has been noted as a promising and secure potential solution. Nonetheless, so far none of the proposed puzzles satisfy the security requirement of resource-limited and highly heterogeneous WLANs. The CPU disparity, imposing unbearable loads on legitimate users, inefficient puzzle generation and verification algorithms; the susceptibility of puzzle to secondary attacks on legitimate users by embedding fake puzzle parameters; and a notable delay in modifying the puzzle difficulty – these are some drawbacks of currently existing puzzles. To deal with such problems, a secure model of puzzle based on DNA and queuing theory is proposed, which eliminates the above defects while satisfying the Chen puzzle security model. The proposed puzzle (OROD puzzle) is a multifaceted technology that incorporates five main components include DoS detector, queue manager, puzzle generation, puzzle verification, and puzzle solver. To test and evaluate the security and performance, OROD puzzle is developed and implemented in real-world environment. The experimental results showed that the solution verification time of OROD puzzle is up to 289, 160, 9, 3.2, and 2.3 times faster than the Karame-Capkun puzzle, the Rivest time-lock puzzle, the Rangasamy puzzle, the Kuppusamy DLPuz puzzle, and Chen's efficient hash-based puzzle respectively. The results also showed a substantial reduction in puzzle generation time, making the OROD puzzle from 3.7 to 24 times faster than the above puzzles. Moreover, by asking to solve an easy and cost-effective puzzle in OROD puzzle, legitimate users do not suffer from resource exhaustion during puzzle solving, even when under severe DoS attack (high puzzle difficulty).
Guidelines for monitoring contaminants in biota and sediments

a. develop draft technical annexes on monitoring of polybrominated diphenyl ethers and hexabromocycladodecane in sediments and biota following the structure of the existing technical annexes. SIME 2007 will be invited to clarify the congeners and compartments that are relevant for the development of monitoring guidance for brominated flame retardants. b. review the existing technical annexes on PAHs to see whether they are adequate for monitoring of the alkylated PAHs and, as appropriate, prepare advice on any revisions that are necessary. c. to develop a draft technical annex on monitoring of TBT and its breakdown products in biota”
Evaluation of the Development of R&D into Parkinson's Disease through Technology Monitoring Using Patent Documents and Scientific Articles

Characterized as a progressive neurodegenerative disease caused by the loss of dopaminergic neurons in the substantia nigra, Parkinson’s disease is affecting an ever greater number of people around the world as global life expectancy rises. As the disease progresses, it has physical, mental, emotional, social, and economic impacts on the patient, eroding their quality of life. Many studies have been done to understand what leads to the onset of the disease and to develop treatments or even prevention. This study uses technology foresight by identifying patents and scientific articles related to drugs for the treatment of the disease with the purpose of assessing the progress of research over time and map out the countries and companies that control the related technologies.
EFECT OF HIP ON LOW CYCLE FATIGUE OF MAR-M247 AT 900°C

Polycrystalline nickel-base superalloy MAR-M247 is used for high temperature applications requiring excellent combination of fatigue properties, creep resistance and surface stability. These superior high temperature characteristics derive from the microstructure which habitually consists of face centred cubic matrix γ and precipitate γ ́ (L12 type ordered structure). In the present work, the high temperature low cycle fatigue behaviour of cast nickel-base superalloy MAR-M247 in as received condition and in hot isostatically pressed (HIP) condition was studied. The microstructure of the materials is characterized by dendritic grains, carbides and casting defects. Distribution and size of defects in both materials were studied. Isothermal low cycle fatigue (LCF) tests were performed on cylindrical specimens under total strain control at 900°C in air. Cyclic stress–strain response and fatigue life of both materials were assessed. Beneficial effects of HIP process on cyclic stress-strain and fatigue life curves are discussed.
Internet Banking Adoption in Sweden

The development of technology over the recent years has led to tremendous changes in the finance and banking industry. One of the self-service technologies (SSTs) that has triggered a revolutionary impact is Internet banking. The majority of Internet banking users are adults and youths, as these target groups have risen with the emergence of this service. Hence, many seniors have been excluded to adopt Internet banking services since they have not grown up with these new technologies. This is a problem since the senior population of Sweden is increasing and so are the technological improvements at an even greater speed. Most of the previous research on the subject of Internet banking adoption has been tested with models such as: Theory of Reasoned Action (TRA), Theory of Planned Behavior (TPB) and Technological Acceptance Model (TAM). However, Internet banking adoption of seniors has not been examined before in the context of Sweden, or in Umeå. The authors believed that there is a research gap in this area which can be further investigated. The purpose of this study is to develop an understanding of what factors influence the elders’ adoption of Internet banking. In order to do so, data will be collected through qualitative interviews to members of senior associations in Umeå. The determinants for Internet banking usage based on the TAM are perceived usefulness (PU) and perceived ease-of-use (PEOU) while the TPB is more related towards behavioral factors. These elements of theories will establish the groundwork for the empirical results, as this study will be accomplished with an inductive approach. Based from previous research, education and technological behavior proved to be significant factors on the adoption of the service and were added to model. The authors extended the TAM by developing the Internet Banking Acceptance Model (IBAM), which is more suitable to explain the seniors’ adoption of Internet banking. The findings of the research showed that most of the seniors’ lacked education in Internet banking and their technological behavior affected their willingness to adopt IT services. The seniors should also be more open to new technologies, in this case, Internet banking instead of relying on external assistance. With this research the authors have realized there is a gap in Internet banking adoption, and that is, the seniors. They have demonstrated an interest in the service if provided with proper education and training either by the banks or relatives. The banks should look into this aspect because it would make the bank errands more practical for the seniors and cut down costs for the banks.
Understanding task preparation and resumption behaviors in cross‐device search

It is now common for individuals to have multiple computing devices, such as laptops, smart phones, and tablets. This multidevice environment increases the popularity of cross‐device search activities. Cross‐device search can be seen as a special case of cross‐session search. Previous studies regarded re‐finding behaviors in cross‐session search as task resumption. Based on this, this article proposes considering 2 phases of cross‐device search: task preparation and task resumption and to explore their features by modeling. A within‐subject user experiment was designed to collect data. Four groups of features were captured from specific behaviors of querying, clicking, gazing, and cognition. This article tested 3 machine‐learning methods and found that the C5.0 decision tree performed best. Five features were included in the task preparation behavior model, and 3 in the task resumption behavior model. The difference and relationship between task preparation and task resumption were investigated by comparing their behavioral features. It is concluded that information need remains blurred in task preparation and becomes clear in task resumption. The changing states of information need suggest an exploratory process in cross‐device search. We also identify some implications for search engine designers.
SINTERING OF COPPER LAYERS WITH A CONTROLLED POROUS STRUCTURE Authors: Wojciech DEPCZYŃSKI

The aim of the experiment was to study the technique of production of porous metal foams by reduction of metal oxides during sintering. The foams were produced by powder metallurgy. This technique allows us to combine irregular cellular structures with open or closed pores. The porosity range is largely dependent on the component materials, i.e., the type and size of particles. The porosity is also affected by the ratio of metal oxide to matrix metal. To obtain a porous structure, it is necessary to apply a metal oxide that is easy to reduce by the protective atmosphere during the sintering process. The porous metal foam technology is suitable to produce components similar to those obtained by powder metallurgy. The process was slightly modified to produce porous layers on elements used in heat transfer exchangers. The study concerned layers with the pre-determined porosity, layer thickness and open pores on heat exchangers made of electrolytic copper which operate at boiling heat transfer. The porous layers were produced by sintering and reduction of a mixture of copper and copper oxide powders varying in grain size.
Dynamic generalized linear model via product partition model

Metodos Bayesianos aplicados a series temporais comecaram a se destacar quando a classe de modelos lineares dinâmicos (MLD's) foi definida. A necessidade de trabalhar com series temporais nao Gaussianas atraiu muito interesse ao longo dos anos. A classe de modelos lineares generalizados dinâmicos (MLGD's) e uma extensao atrativa do MLD para observacoes na familia exponencial e, ao mesmo tempo, corresponde a uma extensao do modelo linear generalizado, permitindo que os parâmetros variem no tempo. Recorrentemente, essas series temporais podem ser afetadas por eventos externos que mudam a estrutura da serie, resultando em problemas de ponto de mudanca. O modelo particao produto (MPP) aparece como uma alternativa atrativa para identificar multiplos pontos de mudanca. Neste trabalho, propusemos estender a classe de modelos lineares generalizados dinâmicos utilizando o modelo particao produto para acomodar series temporais na familia exponencial com problemas de ponto de mudanca. Nesse contexto, o MPP promove uma estrutura de agrupamento para os dados, e a inferencia tradicional do MLGD e feita, mas ao inves de ser feita para cada observacao, a inferencia e feita por blocos de observacoes, implicando que observacoes no mesmo bloco terao um parâmetro de estado comum. A nova classe proposta e uma classe ainda mais ampla, uma vez que garante a exibilidade do MLGD conjuntamente com a habilidade de detectar pontos de mudanca atraves da metodologia do MPP. Nesse trabalho, analisamos bancos de dados reais objetivando ilustrar a aplicabilidade do modelo proposto.
An analysis of whole-body vibration and hand-arm vibration exposure on the Danube ship crew

This paper studies the WBV and HAV exposure on the crew members of river ships. All parameters (acceleration, frequency, exposure duration, etc) negatively influence the performance of the sailing staff. In order to study how the sum of these physical parameters, affect people’s work, a full analysis was made on 11 subjects, on 2 river ships, navigating the Romanian Danube area in January 2019. The vibrations transmitted to the subjects were measured with Maestro 01dB. Also, the meteorological parameters were measured with the Kestrel 5000 Portable Weather Station. All parameters were measured on the main deck. Specific questionnaires were used to detect the negative influence of the transmitted vibrations. Subjects are aged between 42 and 61 years old, most of them are smokers and some of them have health problems. According to ISO 20283-5:2016, ISO 8041:2005, ISO 6954:2000, ISO 2631:2018 and Guide for crew habitability on ships: 2016, there are the following stipulated values for work spaces: maximum RMS level must be 0.214m/s2 (for habitability criteria HAB), 0.178m/s2 (for HAB +) and 0.143m/s2 (for HAB ++). Mean values measured for the whole body vibration were 1.2÷1.4m/s2. The average values of the weather parameters, during the entire route, were normal for this period: temperature - 11÷4°C, atmospheric pressure 970÷1015mbar, humidity 75÷80%, wind speed 10÷30km/h; visibility 1 km, but the extremely dense fog persisted 86.66% of the time. The questionnaire responses showed the presence of musculoskeletal problems in a vibratory environment. Working on a ship is extremely difficult, especially in unfavorable weather conditions. Low temperatures amplify the negative effects of vibrations. It has been found that the values provided by all ISO are far exceeded. Moreover, due to the fact that most ships are old, their operation generates vibrations harmful to physical health. For this reason, a renewal of the fleet is necessary.
Pressure pain threshold and visual analogue scale changes in the high and low energy extracorporeal shock wave

Objective: This study aims to investigate high energy and low energy extracorporeal shockwave therapy (ESWT) and which one is more effective for shoulder pain. Design: Single blind randomized controlled trial. Methods: Fifty two subjects with upper trapezius (UT) trigger point (TrP) participated in this study. They were allocated to high energy (n=26) and low energy group (n=26). This study applies ESWT and investigates the changes of pressure pain threshold (PPT) and visual analogue scale (VAS). The high and low energy groups received focused piezo electric type ESWT 4 Hz, 1,000 pulses and 0.351 and 0.092 mJ/mm 2 respectively. Outcome measures of PPT and pain was measured by algometer and pain VAS. These measurements were performed before and after treatment. Results: The PPT value was significantly increased in both groups after treatment ( p <0.05) and VAS scores were significantly decreased after treatment in both groups ( p <0.05). However, there were no significant differences between groups. Conclusions: ESWT is an effective treatment for the application of the UT TrP. Although there were significant effects of extracorporeal shock wave therapy on PPT and VAS scores, there were no signficant differences between high and low energy extracorporeal shock wave therapy.