Miracle-dz/UniFAR-FTUs huggingface dataset:
Reclaiming human space at IoT: contributions of the socially aware design

Computing has been incorporated into "things" (objects, clothes, etc.) which, using Internet protocols, are able to send and receive information, realizing ideas of ubiquity that were launched in the 1990s. Transforming a "thing" into a network node of a system that makes sense in people's environment has been a challenge for the Human-Computer Interaction (IHC) discipline. In this paper we investigate and propose a Socially Aware Design (SAwD) based process for building scenarios of ubiquitous and pervasive interaction with contemporary technology, including Internet of Things (IoT) scenarios. The starting point for SAwD is understanding the problem from stakeholders' engagement to evolve a design solution together. As part of the process, a solution proposal was created, implemented and iteratively tested with some of the stakeholders under the eyes of researchers. Three iterative cycles were held in workshops with children in a hospital setting that included the observation of researchers, discussions and proposals for the evolution of the solution. At each iteration in the process the importance of people in the technological environment was highlighted, emphasized by the intertwining of technology in the activities developed in each scenario built. The evolution of the system shows that the application of SAwD from its basic premise, which is to understand the problem with the stakeholders that act as the solution's co-designers, was fundamental in the process. Study results show the effectiveness of the proposed process and suggest recommendations for the design of Internet of Human Things (IoHT).
RTL bug localization through LTL specification mining (WIP)

As the complexity of contemporary hardware designs continues to grow, functional verification demands more effort and resources in the design cycle than ever. As a result, manually debugging RTL designs is extremely challenging even with full signal traces after detecting errors in chip-level software simulation or FPGA emulation. Therefore, it is necessary to reduce the burden of verification by automating RTL debugging processes. In this paper, we propose a novel approach for debugging with the use of LTL specification mining. In this approach, we extract fine-grained assertions that are implicitly encoded in the RTL design, representing the designer's assumptions, to localize bugs that are only detected when high-level properties are violated from long-running full-system simulations. We employ template-based RTL spec mining to infer both safety and bounded liveness properties. We propose strategies to convert multi-bit signals to atomic propositions based on common RTL design idioms such as ready-valid handshakes and specific state transitions using automatic static analysis. Our initial results with a tiny RISC-V core design show that this methodology is promising for localizing bugs in time and space by demonstrating that the mined fine-grained LTL properties are violated before a high-level test failure condition occurs, such as a timeout or hanging, and can point to specific lines of suspect RTL.
Towards An Active Learning Approach To Tool Condition Monitoring With Bayesian Deep Learning

With the current advances in the Internet of Things (IoT), smart sensors and Artificial Intelligence (AI), a new generation of condition monitoring solutions for smart manufacturing is starting to emerge. Computer Numerical Control (CNC) machines can now be sensorised and the vast amount of data generated can be processed using Machine Learning (ML) techniques. These can provide insights about the condition of the machine or tool in real-time, which can then be used by decision makers. This is fundamental in order to reach a new level of manufacturing capabilities in the context of Industry 4.0 (Lasi et al, 2014). Most current monitoring solutions rely on the off-line generation of models before they can be used online. This is not ideal when the data holds complex evolving features. There is a lack of approaches that are capable of determining what to learn and when to learn. This paper presents preliminary results on a new deep learning approach based on Bayesian Convolutional Neural Networks (BCNN) for online tool condition classification. Based on the uncertainty of the model, the proposed approach can determine using an entropy acquisition function if the incoming data cannot be classified, and therefore needs to be labelled and used for re-training. This constitutes the first step towards an online active learning tool condition monitoring approach. We demonstrate using a machine tool data set that the active learning approach can achieve similar accuracy of a deterministic Convolutional Neutral Network (CNN) with a smaller training data set.
Contributions of single-cell genomics to our understanding of planktonic marine archaea

Single-cell genomics has transformed many fields of biology, marine microbiology included. Here, we consider the impact of single-cell genomics on a specific group of marine microbes—the planktonic marine archaea. Despite single-cell enabled discoveries of novel metabolic function in the marine thaumarchaea, population-level investigations are hindered by an overall lower than expected recovery of thaumarchaea in single-cell studies. Metagenome-assembled genomes have so far been a more useful method for accessing genome-resolved insights into the Marine Group II euryarchaea. Future progress in the application of single-cell genomics to archaeal biology in the ocean would benefit from more targeted sorting approaches, and a more systematic investigation of potential biases against archaea in single-cell workflows including cell lysis, genome amplification and genome screening. This article is part of a discussion meeting issue ‘Single cell ecology’.
Dynamic changes and the relationship between cardiac function damage and glycogen synthase kinase-3 β expression induced by coronary microembolization in rats

Background: Coronary microembolization (CME) is a severe complication in the treatment of acute coronary syndrome (ACS) and percutaneous coronary intervention (PCI). It is a distal microvascular embolism caused by the shedding of atherosclerotic plaque debris, which can directly lead to “no blood flow” or “slow blood flow”. Aims: This study investigates the dynamic changes and the relationship between cardiac function damage and GSK-3β expression induced by coronary microembolization (CME) in rats. Materials and Methods: Specific Sprague Dawley rats (SD rats) were evenly divided into a microembolization group (CME group) and a sham operation group (Sham group). Each group of rats was randomly subdivided into 0h, 3h, 9h, and 24h groups. Results: Echocardiographic parameters showed that the left ventricular ejection fraction (LVEF) of the CME group was significantly lower than that of the sham group with the exception of the 0h time point (P < 0.05). The results of ELISA showed that the levels of TNF-α and IL-1β in myocardial tissue of the CME group began to increase at 3h, reached a peak at 9h, and decreased at 24h (P < 0.05). Western blot analysis showed that the protein expression of NF-κB p65 in the CME group began to increase at 3 h, peaked at 9h, and decreased at 24h. The protein expression of phospho-GSK-3β(Ser 9) began to decrease at 3 h, reached a low peak at 9 h, and increased at 24 h (P < 0.05). Conclusion: GSK-3βis involved in the damage of cardiac function induced by CME and shows obvious time-variation, which may be achieved by regulating the expression of TNF-α in myocardium.
Improvement implementation a software to analysis polysomnography signal

August 27 th , 2015) ABSTRACT: Sleep disorders have become nowadays one of the most important health issues in the community; they will affect many functions of the body and regular physical activities. The goal of our research is implementation improvement of the software for polysomnography signal analysis based on AASM standards published in 2014 to create a comprehensive assessment method for different abnormalities or pathologic symptoms. By using a combination of different learning machine algorithms, program can flexibly update threshold and characteristics of polysomnography signal for each people and reduce errors in calculated results. The program is designed with friendly user interface without support of other special software. The results checked by comparative measurements with other facilities showed high reliability, which give the similarity over 83% for all data. The most advantage of the software is the ability to synchronize data and analysis results with other systems. Program can be decomposed in block modules, which can be easily integrated with other equipment to make
Oral Health Knowledge, Perceptions, and Habits of Adolescents from Portugal, Romania, and Sweden: A Comparative Study

Aims: The study aimed to assess and compare the self-reported oral health knowledge, habits, and perceptions of adolescents in Portugal, Romania, and Sweden and the factors that may affect them. Materials and Methods: An oral health questionnaire with 25 questions was put together in English language and translated into Portuguese, Romanian, and Swedish language to investigate and compare oral health-related knowledge, habits, and perceptions of adolescents from the different countries. A voluntary sample of 879 teenagers completed it, mean aged 14.9 (±1.83) years, from Romania (n = 455), Portugal (n = 200), and Sweden (n = 224) as part of the EuHyDens project. The survey took place between November 2015 and June 2016. Results: It showed some differences between the countries studied but more similarities between Portuguese and Romanian adolescents as related to perceptions of oral health and the use of oral services. Sweden and Portugal are more similar regarding oral health habits (toothbrushing and diet) as compared to Romanian adolescents. Portuguese adolescents have a higher oral health-related knowledge. Conclusion: Assessment of knowledge, perceptions, and habits of a population is essential for the adequate understanding of the oral health-care needs of the society. From the data collected, several differences were found. These differences can be used for tailor interventions to minimize inequalities between countries.
CargoAffect: usage of affective computing to assess stress from truck drivers' verbal communication

Truck drivers, in their professional activity, often face stress conditions. Studies show that monitoring drivers' physiological signals can indicate undesirable situations such as fatigue, somnolence and stress, however, academic studies and commercial systems are still intrusive and prohibitively expensive. Prosody can be related to emotion; thus, audio communication between truck drivers and transportation operators can be monitored to detect stress conditions. This study aimed to identify stress applying Affective Computing and Machine Learning techniques in a audio corpus in Brazilian Portuguese, collected from truck drivers in their real work communication.
Usability assessment of the instagram application on smartphones with emphasis on elderly users

Information technologies have changed the way humans relate and communicate. In this scenario, smartphones have made use of the Internet and social networks much faster, easier and more accessible. Based on this communication need and on this facilitated channel, it is necessary for these technologies to be available and to be usable by users of all ages. This research aims to evaluate the usability of the Instagram social network app, through the use of smartphones, focusing on people aged over 60. The main results observed were that the elderly took, on average, five times longer than young adults, which did not imply a negative evaluation of the application. In addition, this group of participants stated that they would use Instagram again after their first contact with the application.
Assessment of correlation between serum cotinine levels and bone mineral density among male tobacco users

Osteoporosis is a progressive systemic skeletal disease causing reduced bone density. It is characterized by low density of bone tissue. Consequently, a bone becomes fragile with increased susceptibility to fracture. Tobacco exposure has been implicated as a risk factor for decreased bone density, which might result in osteoporosis. The early identification of individuals with low bone mineral density (BMD) and clinical risk factors, accurate diagnosis of osteoporosis and osteopenia, and initiation of appropriate treatment are crucial to reducing the incidence of fractures. Cotinine, a metabolite of nicotine, is commonly used as a marker for tobacco exposure. Objectives: The objective of the present study was to measure the serum cotinine levels and correlate these findings with BMD among male tobacco users either in smoke or smokeless form. Materials and Methods: A total of 120 subjects were included in the study and divided into 4 groups. Group I comprised 30 subjects with a history of tobacco chewing at least for a period of 1 year. Group II comprised 30 subjects with a history of tobacco smoking at least for a period of 1 year.Group III comprised 30 subjects with a history of both tobacco chewing and smoking at least for a period of 1 year. Group IV comprised 30 subjects with no habits of tobacco consumption either in smoke or smokeless form. Serum cotinine levels were assessed among all the four groups (Group I, Group II, Group III, and Group IV) using commercially available cotinine ELISA kit. The BMD was measured among all four groups by bone densitometry using ultrasound. Statistical analysis was done by one-way ANOVA test for comparison of BMD among study groups.Correlation was assessed between bone density, that is, t-score, and serum cotinine levels (in ng/ml) by Karl Pearson's correlation coefficient in four study groups. Chi-square test was done to know the association of BMD among the four groups. Results: The study result revealed that BMD was less among all the three groups when compared to control group (P = 0.2011), with indication of osteopenia. The mean density of bone was less among chewers (Group II) when compared to smokers (Group I) and subjects who used tobacco in both the form (Group III); also, the osteopenic subjects were more in the group who used tobacco in both form. The serum cotinine levels were significantly high among all the three groups when compared to control group (P = 0.00001). Conclusion: Thus, the present study affirms that use of tobacco affects the bone density among male tobacco users. This effect is more among those who use tobacco in smokeless form.
An Efficient Opportunistic Routing Protocol for ICN

Opportunistic routing protocols, such as delay tolerant networks (DTN), can be used to enable information centric networking (ICN) in disaster environments. Existing approaches using DTN for ICN suffers from message overhead due to the mobility of sparsely populated mobile nodes and overall performance degradation. We therefore propose an efficient opportunistic routing protocol for ICN to reduce message overhead and improve delivery probability, too. Performance evaluation results thorough simulation show that the proposed protocol has better delivery probability and overhead ratio than conventional protocol.
Inhibitory effects of methanolic Olea europaea and acetonic Acacia laeta on growth of Babesia and Theileria

Objective: To evaluate the antipiroplasmic activities of methanolic extract of Olea europaea (MOE) and acetonic extract of Acacia laeta (AAL) against Babesia and Theileria parasites in vitro and evaluate the chemotherapeutic effects of these extracts against Babesia (B.) microti in vivo. Methods: Fluorescence assay using SYBR Green 1 nucleic acid stain was used to detect inhibitory effects of the two extracts as well as the combination effects of the two extracts with diminazene aceturate and atovaquone on four Babesia species and Theileria equi in vitro while for in vivo experiments, 8-weekold female BALB/c mice were injected intraperitoneally with 1 × 107B. microti-iRBCs and treated orally at a dose of 150 mg/kg of both extracts. Results: The half maximal inhibitory concentration (IC50) values of AAL against B. bovis, B. bigemina, B. divergens, B. caballi, and Theileria equi were lower than those of MOE extracts. Toxicity assay on Madin–Darby bovine kidney, mouse embryonic fibroblast (MH/3T3), and human foreskin fibroblast cell lines showed that MOE and AAL affected only the viability of Madin–Darby bovine kidney cell line with half maximal effective concentrations (EC50) of (794.7±41.9) and (873.9±17.5) μg/mL, respectively. The oral treatments of MOE and AAL at 150 mg/kg inhibited the growth of B. microti in mice by 80.4% and 64.4%, respectively. The MOE and diminazene aceturate combination showed a higher chemotherapeutic effect than that of monotherapy. Conclusions: MOE and AAL have the potential to be an alternative remedy for treating piroplasmosis. Furthermore, the combination therapy of MOE + DA was more potent against B. microti infection in mice than their monotherapies.
A scientific update on myocardial infarction: A life-threatening issue

Cardiovascular diseases (CVDs) are the principal cause of mortality in India, 52% of population suffer CVDs before 70 years of age. Myocardial infarction (MI) makes up the largest proportion of CVDs. Coronary heart disease, namely stable angina pectoris, unstable angina pectoris, heart failure, and sudden death, is the main results of MI. The aim of this review is to summarize and present the scientific data regarding the physiology of the cardiac system, herbal research, risk factors, precautions, and pharmacological/nonpharmacological treatment of MI. Data were collected with the help of PubMed, Google Scholar, Medknow, and other online resources. The published scientific data revealed that MI is the result of obesity, smoking, family history, age, male gender, etc., and that the herbal resources are better than the synthetic or chemical treatment of MI. Because the synthetic molecules were not found to be safe, they can generate other health issues. Given problems with the pharmacological treatment of MI, precaution, and a good lifestyle is the better solution.
Redescription and Molecular Characterization of Placobdella pediculata Hemingway, 1908 (Hirudinida: Glossiphoniidae)

Abstract Placobdella pediculata Hemingway, 1908 was originally described from individuals that were attached to Aplodinotus grunniens (freshwater drum) in Lake Pepin, Minnesota, USA. Apparently, no type material was deposited. The acquisition of contemporary specimens from its type host in the type locality facilitated redescription of P. pediculata. Placobdella pediculata is different from its congeners in that its caudal sucker is extended from the body by a pedicel (peduncle), bears digitate processes near the rim of the caudal sucker, a smooth body surface, and its anal placement (few annuli anteriad of the caudal sucker). Molecular comparison of cytochrome c oxidase subunit I sequence data from P. pediculata revealed differences of 13.8% to 17.4% among congeners. Placobdella pediculata is a distinct species.
Creating chatbots to talk with humans: HCI evaluations and perspectives

More softwares are with the power of Artificial Intelligence (AI) making their functions, simultaneously more dynamic and capable of attending each users' personal needs. Chatfuel an application that allows users to create chatbots, an AI that can answer messages autonomously. However we question it: How easy chatbot creation is, especially when dealing the complex AI operating in them? In this sense, this exploratory research seeks to understand, through our volunteers' perspectives, with different levels of computational expertise, if this creation process is really as simple as divulged. To conduct the experiments, usability methods were used such as Cognitive Walkthrough, Communicability Evaluation and Attrakdiff. With the study results, among many others, users's noticed certain difficulty while using. the tool and we problematize certain aspects connected to AI, in the context of a human-computer interaction evaluation.
COMSenso: a framework to support emergency team communication and sensemaking

One of the key challenges for emergency teams is to deal efficiently with the scarcity and overload of information during complex situations. Rapid and precise communication can help improve the situational awareness of teams and contribute to the process of building a common operational image. This article analyzed records of an emergency response simulation for young captains, held at the School of Fire Brigade of Rio de Janeiro and proposes a Sensemaking oriented approach as a solution to problems related to communication in emergency environments. It is proposed a framework to guide the construction of systems whose function is to support communication and Sensemaking among team members during large-scale emergencies.
Identity and volition in Facebook digital memorials and the challenges of anticipating interaction

In the social network context, it is worth highlighting the changes in the way people in the digital milieu react to users' physical death. Facebook, for instance, is replete with interactions affected by death. From preliminary studies about digital memorials on Facebook, it has been observed that, although this social network models death issues and anticipated volition of the user, the currently existing solution does not fully meet the requirements suggested by the Social Web. By means of participatory design sessions with active Facebook users, solutions were proposed for design that would emphasize two elements of the social web: Identity and Volition. The resulting prototypes of participatory design were analyzed in the perspective of the challenges of the settings of Interaction Anticipation. The resulting proposals indicate that new solutions introduce more support to anticipating and revealing the deceased user's identity and the memorial's identity.
Approximate computing for multithreaded programs in shared memory architectures

In multicore and multicached architectures, cache coherence is ensured with a coherence protocol. However, the performance benefits of caching diminishes due to the cost associated with the protocol implementation. In this paper, we propose a novel technique to improve the performance of multithreaded programs running on shared-memory multicore processors by embracing approximate computing. Our idea is to relax the coherence requirement selectively in order to reduce the cost associated with a cache-coherence protocol, and at the same time, ensure a bounded QoS degradation with probabilistic reliability. In particular, we detect instructions in a multithreaded program that write to shared data, we call them Shared-Write-Access-Points (SWAPs), and propose an automated statistical analysis to identify those which can tolerate coherence faults. We call such SWAPs approximable. Our experiments on 9 applications from the SPLASH 3.0 benchmarks suite reveal that an average of 57% of the tested SWAPs are approximable. To leverage this observation, we propose an adapted cache-coherence protocol that relaxes the coherence requirement on stores from approximable SWAPs. Additionally, our protocol uses stale values for load misses due to coherence, the stale value being the version at the time of invalidation. We observe an average of 15% reduction in CPU cycles and 11% reduction in energy footprint from architectural simulation of the 9 applications using our approximate execution scheme.