Miracle-dz/UniFAR-FTUs huggingface dataset:
HIRO-NET: Heterogeneous Intelligent Robotic Network for Internet Sharing in Disaster Scenarios

This article describes HIRO-NET, an Heterogeneous Intelligent Robotic Network. HIRO-NET is an emergency infrastructure-less network that aims to address the problem of providing connectivity in the immediate aftermath of a natural disaster, where no cellular or wide area network is operational and no Internet access is available. HIRO-NET establishes a two-tier wireless mesh network where the Lower Tier connects nearby survivors in a self-organized mesh via Bluetooth Low Energy (BLE) and the Upper Tier creates long-range VHF links between autonomous robots exploring the disaster-stricken area. HIRO-NET's main goal is to enable users in the disaster area to exchange text messages to share critical information and request help from first responders. The mesh network discovery problem is analyzed and a network protocol specifically designed to facilitate the exploration process is presented. We show how HIRO-NET robots successfully discover, bridge and interconnect local mesh networks. Results show that the Lower Tier always reaches network convergence and the Upper Tier can virtually extend HIRO-NET functionalities to the range of a small metropolitan area. In the event of an Internet connection still being available to some user, HIRO-NET is able to opportunistically share and provide access to low data-rate services (e.g., Twitter, Gmail) to the whole network. Results suggest that a temporary emergency network to cover a metropolitan area can be created in tens of minutes.
The Reference Analysis as a Quality Characteristic of a Scientific Article

Nowadays the qualitative characteristics of a scientific document are becoming more and more relevant because a large number of conferences, sem-inars, and journals generate a huge amount of scientific papers. A scientific paper consists of such elements as title, information about the authors, abstract, keywords, body and a list of references. References are one of the important factors that affect paper quality. In this paper, the authors analyze the qualitative characteristics of the cited sources and highlight the formal features that characterize the quality of the references. Ukrainian scientific papers were used as data for the experiments. In this paper, the authors have developed an application that allows the reviewer to analyze the list of paper references and an approach to the analysis of the bibliography, which allows identifying those sources that may not be relevant to the research topic. This approach allows determining the artificial increase of irrelevant references.
Centripetal and centrifugal forces in technological activities: linking regional innovation performances to EU Science & Technology policies

In this paper we analyse the technological activities of EU regions to assess the degree of technological concentration and asymmetries in the EU area and the role of the EC Programme for research and innovation – Horizon 2020 – at reducing or amplifying regional asymmetries. Technological capabilities are very unevenly distributed in the EU, and spatial concentration is much higher than that of GDP. Over the period examined (2001-16) some technological convergence of the most peripheral and least innovative regions of Europe has occurred even if it has been slow, involving almost exclusively the Eastern EU regions. Horizon 2020 seems to favour the integration of regions from peripherical countries. However, the focus on scientific excellence, particularly of the European Research Council, may instead contribute to exacerbate the technological gaps across EU regions. Our results suggest there is a trade-off between inclusion and excellence when designing research and innovation policies. This finding will help to inform policy makers and policy analysists in implementing the Horizon Europe scheme (2021-2027).
“Designing Strategies for Sustainable Livelihood in Peri-Urban Settlement” – A Review

The present concern of urban planners is related to recovering the challenges posed by the accelerated growth of metropolitan cities. It is realized that there is a very thin line between urbanization and sustainability. Peri-urban settlements are characterized by various flows from the urban. These flows tend to have an impact on the social, economic and physical aspects in these settlements. Literature reading is carried out to understand the peri-urban areas and its challenges. The works of literature referred are based on the planning of land use, rural spatial planning, Sustainable Livelihood, Peri-Urban area. To achieve sustainable development, one shall apply integrated planning approach, micro level planning in rural land, zoning, village development plan and other such corrective planning theories. The current paper puts forth the impacts on the livelihood sustainability in the peri-urban due to the urban impacts.
Towards Continuous Estimation of Dissatisfaction in Spoken Dialog

We collected a corpus of human-human task-oriented dialogs rich in dissatisfaction and built a model that used prosodic features to predict when the user was likely dissatisfied. For utterances this attained a F.25 score of 0.62,against a baseline of 0.39. Based on qualitative observations and failure analysis, we discuss likely ways to improve this result to make it have practical utility.
A SUFFICIENT CONDITION FOR ACYCLIC 5-CHOOSABILITY OF PLANAR GRAPHS WITHOUT 5-CYCLES

A proper vertex coloring of a graph G is acyclic if G contains no bicolored cycle. A graph G is acyclically L-list colorable if for a given list assignment L = {L(v) : v ∈ V (G)}, there exists an acyclic coloring φ of G such that φ(v) ∈ L(v) for all v ∈ V (G). A graph G is acyclically k-choosable if G is acyclically L-list colorable for any list assignment with L(v) ≥ k for all v ∈ V (G). Let G be a planar graph without 5-cycles and adjacent 4-cycles. In this article, we prove that G is acyclically 5choosable if every vertex v in G is incident with at most one i-cycle, i ∈ {6, 7}.
Salmonella alters heparanase expression and reduces tumor metastasis

Salmonella causes salmonellosis, is a facultative anaerobe and is one of the common Gram-negative bacteria. Salmonella has anti-tumor potential and tumor-targeting activity. The heparin sulfate on cell surfaces can be cleaved by heparanase that is an endo-β-D-glucuronidase. Heparanase can destroy the extracellular matrix and is involved in tumor metastasis and angiogenic activity. Previously, Salmonella was demonstrated to inhibit tumor metastasis. It remains unclear whether Salmonella inhibits metastasis by regulating heparanase. The expression of heparanase in Salmonella-treated tumor cells was found to be decreased. Transwell and wound-healing assays demonstrated the inhibition of cell migration after Salmonella treatment. Salmonella was found to influence the levels of phosphate-protein kinase B (P-AKT) and phosphate-extracellular regulated protein kinases (P-ERK), which are involved in heparanase expression. Salmonella reduced the heparanase expression induced upregulating PERK and PAKT signaling pathways. The mice bearing an experimental metastasis tumor model was used to evaluate the anti-tumor metastatic effects of Salmonella. Compared with the control group, Salmonella significantly reduced the number of metastatic nodules and enhanced survival. The results of our study indicate that Salmonella plays a vital role in the inhibition of tumor metastasis through the downregulation of heparanase.
Robust Command Recognition for Lithuanian Air Traffic Control Tower Utterances

The maturity of automatic speech recognition (ASR) systems at controller working positions is currently a highly relevant technological topic in air traffic control (ATC). However, ATC service providers are less interested in pure word error rate (WER). They want to see benefits of ASR applications for ATC. Such applications transform recognized word sequences into semantic meanings, i.e., a number of related concepts such as callsign, type, value, unit, etc., which are combined to form commands. Digitized concepts or recognized commands can enter ATC systems based on an ontology for utterance annotation agreed between European ATC stakeholders. Command recognition (CR) has already been performed in approach control. However, spoken utterances of tower controllers are longer, include more free speech, and contain other command types than in approach. An automatic CR rate of 95.8% is achievable on perfect word recognition, i.e., manually transcribed audio recordings (gold transcriptions), taken from Lithuanian controllers in a multiple remote tower environment. This paper presents CR results for various speech-to-text models with different WERs on tower utterances. Although WERs were around 9%, we achieve CR rates of 85%. CR rates only slightly decrease with higher WERs, which enables to bring ASR applications closer to operational ATC environment.
A Focused Analysis of Twitter-based Disinformation from Foreign Influence Operations

Detection of foreign political influence operations is an important problem in the current era of high-information transaction. In this paper, we present a focused study on disinformation from a foreign influence campaign over twitter during the 2016 US presidential election. We introduce a new dataset of political disinformation related to a foreign influence operation on Twitter during the 2016 presidential campaign in the United States. We further analyze the differences between information pushed forward by foreign agents and legitimate information concerning word usage. We also investigate the utility of subword level information for classification. Contrary to popular belief we observe that considering only subword level information may lead to sub-optimal results.
Pioneering Chiplet Technology and Design for the AMD EPYC™ and Ryzen™ Processor Families : Industrial Product

For decades, Moore’s Law has delivered the ability to integrate an exponentially increasing number of devices in the same silicon area at a roughly constant cost. This has enabled tremendous levels of integration, where the capabilities of computer systems that previously occupied entire rooms can now fit on a single integrated circuit.In recent times, the steady drum beat of Moore’s Law has started to slow down. Whereas device density historically doubled every 18-24 months, the rate of recent silicon process advancements has declined. While improvements in device scaling continue, albeit at a reduced pace, the industry is simultaneously observing increases in manufacturing costs.In response, the industry is now seeing a trend toward reversing direction on the traditional march toward more integration. Instead, multiple industry and academic groups are advocating that systems on chips (SoCs) be "disintegrated" into multiple smaller "chiplets. " This paper details the technology challenges that motivated AMD to use chiplets, the technical solutions we developed for our products, and how we expanded the use of chiplets from individual processors to multiple product families.
Diagnosis of Schistosoma infection in non-human animal hosts: A systematic review and meta-analysis

Background Reliable and field-applicable diagnosis of schistosome infections in non-human animals is important for surveillance, control, and verification of interruption of human schistosomiasis transmission. This study aimed to summarize uses of available diagnostic techniques through a systematic review and meta-analysis. Methodology and principal findings We systematically searched the literature and reports comparing two or more diagnostic tests in non-human animals for schistosome infection. Out of 4,909 articles and reports screened, 19 met our inclusion criteria, four of which were considered in the meta-analysis. A total of 14 techniques (parasitologic, immunologic, and molecular) and nine types of non-human animals were involved in the studies. Notably, four studies compared parasitologic tests (miracidium hatching test (MHT), Kato-Katz (KK), the Danish Bilharziasis Laboratory technique (DBL), and formalin-ethyl acetate sedimentation-digestion (FEA-SD)) with quantitative polymerase chain reaction (qPCR), and sensitivity estimates (using qPCR as the reference) were extracted and included in the meta-analyses, showing significant heterogeneity across studies and animal hosts. The pooled estimate of sensitivity was 0.21 (95% confidence interval (CI): 0.03–0.48) with FEA-SD showing highest sensitivity (0.89, 95% CI: 0.65–1.00). Conclusions/significance Our findings suggest that the parasitologic technique FEA-SD and the molecular technique qPCR are the most promising techniques for schistosome diagnosis in non-human animal hosts. Future studies are needed for validation and standardization of the techniques for real-world field applications.
Image Caption Generator Based On Deep Neural Networks

In this project, we systematically analyze a deep neural networks based image caption generation method. With an image as the input, the method can output an English sentence describing the content in the image. We analyze three components of the method: convolutional neural network (CNN), recurrent neural network (RNN) and sentence generation. By replacing the CNN part with three state-of-the-art architectures, we ﬁnd the VG-GNet performs best according to the BLEU score. We also propose a simpliﬁed version the Gated Recurrent Units (GRU) as a new recurrent layer, implementing by both MATLAB and C++ in Caffe. The simpliﬁed GRU achieves comparable result when it is compared with the long short-term memory (LSTM) method. But it has few parameters which saves memory and is faster in training. Finally, we generate multiple sentences using Beam Search. The experiments show that the modiﬁed method can generate cap-tions comparable to the-state-of-the-art meth-ods with less training memory.
Uterine natural killer cells mediate dedifferentiation of spiral artery vascular smooth muscle cells in early human pregnancy

A. Robson1, G.E. Lash2, B.A. Innes, J.Y. Zhang2, S.C. Robson, J.N. Bulmer* 5 Reproductive and Vascular Biology Group, Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, UK; 1Current address; Sir William Dunn School of Pathology, University of Oxford, Oxford OX1 3RE, UK; 2Current address; Guangzhou Women and Children’s Medical Center, Guangzhou, China 10 Running title: Uterine spiral artery muscle dedifferentiation
Circular Economy in Cities requires a Systems Approach

”Rather than an economic model based on growth-consumption-obsolescence-disposal that continually exploits the planet’s resources, we need circular economies where waste is feedstock, recycling rates are close to 100 per cent, new materials and products are designed to be re-used and re-purposed, cultural norms encourage re-use, maintenance and repair, and fossil carbon stays underground. Rather than large, polluting energy systems for domestic use, industry and transport, we need to switch to clean and often localised energy production and consumption, and clean mobility-as-a-service that will require changes in the way we live and work. Food production must be transformed as well, by changing diets and by replacing intensive tilling with no-till practices to prevent the breakdown of soil structure and by promoting the sequestering of carbon, thereby slowing climate warming. Our obsession with short-term returns in financial markets must be replaced with patient capital designed to value fully the social and environmental benefits of investment, accompanied by a radical shift away from banking on the ‘stranded assets’ of an expiring fossil carbon economy. ”
An advanced Decentralized Conditional Anonymous Payment System for Cryptocurrency using Blockchain

— Blockchain, a circulated record innovation, can possibly be conveyed in a wide scope of utilizations. Among these applications, decentralized payment frameworks (for example Bitcoin) have been perhaps the most developed blockchain applications with inescapable appropriation. While the early plans (for example Bitcoin) are regularly the cash of decision by cybercriminals, they just give pseudo-secrecy, as in
Classifying Common Knee Rehabilitation Exercise Mistakes Using IMU Data

Physical therapy following major surgeries is a branch of medicine that has seen its fair share of technologically inspired advances. One important facet of physical therapy, the “athome exercises” patients are prescribed to do, is still somewhat of a “black box” to many physical therapists (PTs). PTs have no way of knowing (1) whether the patient is doing the home exercises, or (2) whether the patient is doing the exercises in the correct and healthy manner. This lack of awareness makes it difficult for the PT to guide the patient, which can often lead to prolonged rehabilitation periods or (sometimes) can create life-long health problems for patients. In this thesis, we provide a means for a PT to remotely monitor patient’s performance of at-home exercises. We combined the capabilities of wearable motion sensors with computational algorithms to provide patients feedback on the quality of their performed exercises. We evaluated this approach by asking 20 healthy volunteers to perform popular knee-rehabilitation exercises with various mistakes while wearing motion sensors. After preprocessing and extracting features from the sensor data, we trained machine-learning models on the extracted features. The models showed a high rate of accuracy during testing, which brings us a step closer to giving physical therapists and doctors a tool to automatically and objectively classify certain exercises and mistakes made during those exercises.
Andror2: A Dataset of Manually-Reproduced Bug Reports for Android apps

Software maintenance constitutes a large portion of the software development lifecycle. To carry out maintenance tasks, developers often need to understand and reproduce bug reports. As such, there has been increasing research activity coalescing around the notion of automating various activities related to bug reporting. A sizable portion of this research interest has focused on the domain of mobile apps. However, as research around mobile app bug reporting progresses, there is a clear need for a manually vetted and reproducible set of real-world bug reports that can serve as a benchmark for future work. This paper presents AndroR2: a dataset of 90 manually reproduced bug reports for Android apps listed on Google Play and hosted on GitHub, systematically collected via an in-depth analysis of 459 reports extracted from the GitHub issue tracker. For each reproduced report, AndroR2 includes the original bug report, an apk file for the buggy version of the app, an executable reproduction script, and metadata regarding the quality of the reproduction steps associated with the original report. We believe that the AndroR2 dataset can be used to facilitate research in automatically analyzing, understanding, reproducing, localizing, and fixing bugs for mobile applications as well as other software maintenance activities more broadly.
Application of biologics to feedstuff

The application of biologics additives from enzyme, prebiotics and probiotics to improve the feedstuff utilization and animal growth is an aim for safety and hygiene animal products. These additives are gradually replacing the antibiotics. As biotechnology develops to meet animal demand, high bioavailability and low production cost technological products will be novel feed additives, including high production efficiency transformed microorganism and probiotics of transformed enzyme gene or raw material of feedstuff using biotechnology (e.g. fermentation) to enhance nutritive value. However, the availability of these biotechnological products shall be proved by the animal feeding trial.
Collaborative Learning Intervention associated with Increases in Home-Based School Involvement for Families in Deprived Neighborhoods

The current study set out to investigate the impact of the Dutch low-SES family-oriented Collaborative Learning intervention, characterized by a partnership approach and provision of personalized support. We assessed effects on parents’ home-based school involvement, the quality of the relationship with their child’s teacher, and parents’ parenting skills. Fifty-six children in grades 1-4 and their families were randomly assigned to an intervention or waiting list condition. Results of two path models, using cluster-robust standard errors to adjust for nesting within our data, and controlling for baseline values of our outcome variables, indicated significant improvements in home-based school involvement among families in the intervention group, but no differences in the quality of the parent-teacher relationship nor in parenting skills. Our findings support the idea that a partnership approach and the provision of personalized support by means of home visits are an effective strategy to increase home-based school involvement amongst low-SES families.
An overview of H.26x series and its applications

The advent of compression standards has led to the proliferation of innovative techniques in the compressed domain has become an active research topic. This paper presents an overview of the latest video compression standards related to the H.26xSeries and this paper is specifically covered including its latest standard, H.265 otherwise known as AVC (Advanced Video Coding). It also provides an overview of compression rules of thumb for different standards and the corresponding performance requirements for real-time implementations.
Assessment on Air Quality Index in Kolkata and suburban area of West Bengal, India using cluster analysis and neural network Techniques

Air quality index (AQI) is the single value numerical expression to evaluate the quality of a given air at a particular location. The present study classifies the locations with different air pollution characteristics in respect of AQI and to evaluate the parameters of the locations of the monitoring program. A selected cluster analysis is applied to the pollution monitoring dataset which including SPM, RPM, SO 2 , NO 2 . A computer-simulated artificial neural network (ANN) model is developed using Matlab to get a good interaction between the different components of air of different location in Kolkata responsible for Air Quality measurement and their relationship with AQI.
Facilitating Online Distributed Critical Making: Lessons Learned

The global pandemic has brought numerous challenges for educators who take a maker-centered approach, whose instruction involves direct engagement with materials through collaborative and exploratory social interactions. Many educators have found creative ways to address the obstacles of being remote. However, inciting critical reflection through making, already difficult during in-person settings, has become an even greater challenge in remote settings. This paper reports on the lessons learned from a two-week online afterschool maker workshop where participants worked on a maker project being in remote locations, while engaged in critical reflections on ethical implications of biowearable devices. The results showed preliminary evidence that participants were able to produce a prototype and engaged in critical reflection on the ethical issues of biowearables. We also found that while online environments offer limited social cues and flexibility, access to multiple communication channels enabled just-in-time facilitation for critical reflection.