Miracle-dz/UniFAR-FTUs huggingface dataset:
Lightweight hardware monitoring of IoT devices

IoT devices are systematically vulnerable to vendor introduced bugs, network as well as supply chain attacks. Further, unprotected and unmonitored physical access is common while single board computer based IoT devices have limited or no ability to detect and mitigate most types of attacks. Various methods have been described that use software based analysis, execution monitoring, and other cryptographic functions but these methods are not practical for small devices and often require modifications or additions to a simple sensor board that uses more power and is itself vulnerable to software bugs. Also, additional software space for non-mission code is difficult or not possible to add. This paper describes a novel light weight method to detect a compromise or abnormal behavior through the monitoring of readable and writable hardware elements on the device. An example prototype is described using an Arduino class device, common for many commercial sensing applications.
Advancing research on emergency care systems in low-income and middle-income countries: ensuring high-quality care delivery systems

Emergency care systems (ECS) address a wide range of acute conditions, including emergent conditions from communicable diseases, non-communicable diseases, pregnancy and injury. Together, ECS represent an area of great potential for reducing morbidity and mortality in low-income and middle-income countries (LMICs). It is estimated that up to 54% of annual deaths in LMICs could be addressed by improved prehospital and facility-based emergency care. Research is needed to identify strategies for enhancing ECS to optimise prevention and treatment of conditions presenting in this context, yet significant gaps persist in defining critical research questions for ECS studies in LMICs. The Collaborative on Enhancing Emergency Care Research in LMICs seeks to promote research that improves immediate and long-term outcomes for clients and populations with emergent conditions. The objective of this paper is to describe systems approaches and research strategies for ECS in LMICs, elucidate priority research questions and methodology, and present a selection of studies addressing the operational, implementation, policy and health systems domains of health systems research as an approach to studying ECS. Finally, we briefly discuss limitations and the next steps in developing ECS-oriented interventions and research.
Are community health workers effective in retaining women in the maternity care continuum? Evidence from India

Objectives Despite the recognised importance of adopting a continuum of care perspective in addressing the care of mothers and newborns, evidence on specific interventions to enhance engagement of women along the maternity care continuum has been limited. We use the example of the Accredited Social Health Activist (ASHA) programme in India, to understand the role of community health workers in retaining women in the maternity care continuum. Methods Using the Indian Human Development Survey data from 2011 to 2012, we assess the association between individual and cluster-level exposure to ASHA and four key components along the continuum of care—at least one antenatal care (ANC) visit, four or more ANC visits, presence of a skilled birth attendance (SBA) at the time of birth and postnatal care for the mother or child within 48 hours of birth, for 13 705 women with a live birth since 2005. To understand which of these services experience maximum dropout along the continuum, we use a linear probability model to calculate the weighted percentages of using each service. We assess the association between exposure to ASHA and number of services utilised using a multinomial logistic regression model adjusted for a range of confounding variables and survey weights. Results Our study indicates that exposure to the ASHA is associated with an increased probability of women receiving at least one ANC and SBA. In terms of numbers of services, exposure to ASHA accounts for a 12% (95% CI: 9.1 to 15.1) increase in women receiving at least some of the services, and an 8.8% (95% CI: −10.2 to −7.4) decrease in women receiving no services. However, exposure to ASHA does not increase the likelihood of women utilising all the services along the continuum. Conclusions While ASHA is effective in supporting women to initiate and continue care along the continuum, it does not significantly affect the completion of all services along the continuum.
Metabolic Adaptation in Methicillin-Resistant Staphylococcus aureus Pneumonia

Methicillin-resistant Staphylococcus aureus (MRSA) is a versatile human pathogen that is associated with diverse types of infections ranging from benign colonization to sepsis. We postulated that MRSA must undergo specific genotypic and phenotypic changes to cause chronic pulmonary disease. We investigated how MRSA adapts to the human airway to establish chronic infection, as occurs during cystic fibrosis (CF). MRSA isolates from patients with CF that were collected over a 4-year period were analyzed by whole-genome sequencing, transcriptional analysis, and metabolic studies. Persistent MRSA infection was associated with staphylococcal metabolic adaptation, but not changes in immunogenicity. Adaptation was characterized by selective use of the tricarboxylic acid cycle cycle and generation of biofilm, a means of limiting oxidant stress. Increased transcription of specific metabolic genes was conserved in all host-adapted strains, most notably a 10,000-fold increase in fumC, which catalyzes the interconversion of fumarate and malate. Elevated fumarate levels promoted in vitro biofilm production in clinical isolates. Host-adapted strains preferred to assimilate glucose polymers and pyruvate, which can be metabolized to generate N-acetylglucosamine polymers that comprise biofilm. MRSA undergoes substantial metabolic adaptation to the human airway to cause chronic pulmonary infection, and selected metabolites may be useful therapeutically to inhibit infection.
Nature of Complex Network of Dengue Epidemic as a Scale-Free Network

Objectives Dengue epidemic is a dynamic and complex phenomenon that has gained considerable attention due to its injurious effects. The focus of this study is to statically analyze the nature of the dengue epidemic network in terms of whether it follows the features of a scale-free network or a random network. Methods A multifarious network of Aedes aegypti is addressed keeping the viewpoint of a complex system and modelled as a network. The dengue network has been transformed into a one-mode network from a two-mode network by utilizing projection methods. Furthermore, three network features have been analyzed, the power-law, clustering coefficient, and network visualization. In addition, five methods have been applied to calculate the global clustering coefficient. Results It has been observed that dengue epidemic follows a power-law, with the value of its exponent γ = −2.1. The value of the clustering coefficient is high for dengue cases, as weight of links. The minimum method showed the highest value among the methods used to calculate the coefficient. Network visualization showed the main areas. Moreover, the dengue situation did not remain the same throughout the observed period. Conclusions The results showed that the network topology exhibits the features of a scale-free network instead of a random network. Focal hubs are highlighted and the critical period is found. Outcomes are important for the researchers, health officials, and policy makers who deal with arbovirus epidemic diseases. Zika virus and Chikungunya virus can also be modelled and analyzed in this manner.
An Application of Natural Language Processing for Triangulation of Cognitive Load Assessments in Third Level Education

Work has been done to measure Mental Workload based on applications mainly related to ergonomics, human factors, and Machine Learning. The influence of Machine Learning is a reflection of an increased use of new technologies applied to areas conventionally dominated by theoretical approaches. However, collaboration between MWL and Natural Language Processing techniques seems to happen rarely. In this sense, the objective of this research is to make use of Natural Languages Processing techniques to contribute to the analysis of the relationship between Mental Workload subjective measures and Relative Frequency Ratios of keywords gathered during pre-tasks and post-tasks of MWL activities in third-level sessions under different topics and instructional designs. This research employs secondary, empirical and inductive methods to investigate Cognitive Load theory, instructional designs, Mental Workload foundations and measures and Natural Language Process Techniques. Then, NASA-TLX, Workload Profile and Relative Frequency Ratios are calculated. Finally, the relationship between NASA-TLX and Workload Profile and Relative Frequency Ratios is analysed using parametric and non-parametric statistical techniques. Results show that the relationship between Mental Workload and Relative Frequency Ratios of keywords, is only medium correlated, or not correlated at all. Furthermore, it has been found out that instructional designs based on the process of hearing and seeing, and the interaction between participants, can overcome other approaches such as those that make use of videos supported with images and text, or of a lecturer’s speech supported with slides.
Patterns of gaze in speech agent interaction

While gaze is an important part of human to human interaction, it has been neglected in the design of conversational agents. In this paper, we report on our experiments with adding gaze to a conventional speech agent system. Tama is a speech agent that makes use of users' gaze to initiate a query, rather than a wake word or phrase. In this paper, we analyse the patterns of detected gaze when interacting with the device. We use k-means clustering of the log data from ten users tested in a dual-participant discussion tasks. These patterns are verified and explained through close analysis of the video data of the trials. We present similarities of patterns between conditions both when querying the agent and listening to the answers. We also present the analysis of patterns detected when only in the gaze condition. Users can take advantage of their understanding of gaze in conversation to interact with a gaze-enabled agent but are also able to fluently adjust their use of gaze to interact with the technology successfully. Our results point to some patterns of interaction which can be used as a starting point to build gaze-awareness into voice-user interfaces.
Design of a 12-bit SAR ADC with digital self-calibration for radiation detectors front-ends

The paper describes the design of a 12-bit SAR ADC with digital self-calibration to be used in multi-channel ASICs for radiation detectors employed in nuclear and particle physics. In these systems, a highly segmented sensor is coupled to a front-end chip with many channels operating in parallel. The details of the signal processing to be performed depend on the particular applications, but in several cases it is necessary to embed on the front-end chip a large number of analog-to-digital converters (32 or more) that have to operate simultaneously. Typical requirements for the converter are a resolution in the 10–12 bits range, a sampling frequency above 20 Msamples/sec, very low power consumption and good radiation hardness. The ADC discussed in this paper is based on a fully differential SAR architecture assisted by a digital background calibration that relies on the Offset Double Conversion (ODC) method. The algorithm uses an analog offset injection to compute the intrinsic error of the ADC conversion due to mismatch among the DAC capacitors. The approach allows to find a set of weights, which are then applied at each conversion to achieve a real-time correction. The ADC was preliminary modelled with a high level C++ code. Physical implemented in both in 110 nm and 65 nm CMOS technologies is underway. The paper focuses on the design and hardware implementation of the calibration algorithm. The average ENOB after correction is incremented by 4 bits by using a 15% random capacitor mismatch. The SFDR is hold below −90 dB. The power consumption of the calibration circuit is 5.6 mW and 3 mW respectevely for 110 nm and 65 nm node. A further study investigated how many bit have to be calibrated to hold a reasonable ENOB.
Towards an Equational Theory of Rhythm Notation

Trees are classical representations of hierarchical structures in symbolic music, in particular for rhythm notations, where the durations are defined by a hierarchy of subdivisions. Structures called rhythm trees have been integrated since a long time into Computer Aided Composition environments such as Patchwork and OpenMusic , for programming rhythmic objects. Term rewriting and tree automata and transducers are well established formalisms for transforming and reasoning on trees. With solid theoretical foundations, they are used in a wide range of applications including automatic reasoning, natural language processing, and foundations of web data processing. In this work, we consider a tree structured representation of rhythm suitable for defining a set of rewrite rules (i.e. oriented equations) preserving rhythms, while enabling the simplification of notations. This set can be seen as an axiomatization of rhythm notation which can be applied to reasoning on equivalent notations in assisted composition.
Effect of simultaneous administration of foot-and-mouth disease (FMD) and anthrax vaccines on antibody response to FMD in sheep

Purpose Foot-and-mouth disease (FMD) and anthrax are important diseases in sheep. Vaccination is a favorable strategy against both infections. Simultaneous administration of vaccines does generally not impede the immune responses of each other, although there are some exceptions, and it may help reduce the labor and costs of vaccination as well as distress on animals. Although oil adjuvant FMD vaccine has been tried with live anthrax vaccine in cattle, there are no reports on the simultaneous use of both vaccines in sheep. Materials and Methods In this study, FMD seronegative sheep were used to investigate the impact of the simultaneous vaccination of FMD and anthrax on FMD antibody titers of sheep. Virus neutralization test and liquid phase blocking enzyme-linked immunosorbent assay were used to determine the antibody response to the FMD vaccine. Results The results demonstrated that both vaccines can be used simultaneously without any interference with the FMD response. Moreover, the simultaneous administration with anthrax vaccine had a stimulating effect on the early (day 7 post-vaccination) virus neutralization antibody response to the FMD vaccine. Conclusion The simultaneous use of the FMD and anthrax vaccines did not hinder the response to the FMD vaccine in sheep.
Towards optimal path computation in a simplicial complex

Computing optimal path in a configuration space is fundamental to solving motion planning problems in robotics and autonomy. Graph-based search algorithms have been widely used to that end, but they suffer from drawbacks. We present an algorithm for computing the shortest path through a metric simplicial complex that can be used to construct a piece-wise linear discrete model of the configuration manifold. In particular, given an undirected metric graph, G, which is constructed as a discrete representation of an underlying configuration manifold (a larger “continuous” space typically of dimension greater than one), we consider the Rips complex, R ( G ) , associated with it. Such a complex, and hence shortest paths in it, represent the underlying metric space more closely than what the graph does. Our algorithm requires only a local connectivity-based description of an abstract graph, G = ( V , E ) , and a cost/length function, d : E → ℝ + , as inputs. No global information such as an embedding or a global coordinate chart is required. The local nature of the proposed algorithm makes it suitable for configuration spaces of arbitrary topology, geometry, and dimension. We not only develop the search algorithm for computing shortest distances, but we also present a path reconstruction algorithm for explicitly computing the shortest paths through the simplicial complex. The complexity of the presented algorithm is comparable with that of Dijkstra’s search, but, as the results presented in this paper demonstrate, the shortest paths obtained using the proposed algorithm represent the geodesic paths in the original metric space significantly more closely.
Conversation is multimodal: thus conversational user interfaces should be as well

In this paper we try to provoke by teasing the question "if conversational user interfaces should be multimodal? ". Of course they should! In decades of research in multimodal HCI excellent arguments can be found. We substantiate our perspective with an example showing how conversational interaction becomes more robust and efficient through the use of multimodality.
Speech emotion recognition methods: A literature review

Recently, attention of the emotional speech signals research has been boosted in human machine interfaces due to availability of high computation capability. There are many systems proposed in the literature to identify the emotional state through speech. Selection of suitable feature sets, design of a proper classifications methods and prepare an appropriate dataset are the main key issues of speech emotion recognition systems. This paper critically analyzed the current available approaches of speech emotion recognition methods based on the three evaluating parameters (feature set, classification of features, accurately usage). In addition, this paper also evaluates the performance and limitations of available methods. Furthermore, it highlights the current promising direction for improvement of speech emotion recognition systems.
A Study of Hormone Receptor Status in Breast Carcinoma and use of HER2-Targeted Therapy in a Tertiary Care Center of India

Abstract Aims: The aim is to study the hormone receptor status, association of HER2 expression with prognostic factors and use of HER2-targeted therapy in North Indian breast cancer patients. Subjects and Methods: Immunohistochemistry reports of 288 breast cancer patients registered in the department of Radiotherapy, SMS Medical College, Jaipur in 2015–2016 were analyzed for estrogen receptor (ER), progesterone receptor (PR), and c-erb B-2 protein (HER2/neu) expression. Equivocal HER2 (2+) was further confirmed by fluorescent in situ hybridization (FISH). Number of patients receiving HER2/neu-targeted therapy was also studied. Results: For ER, positive status was more common (56%), whereas for PR and HER2/neu, negative status was more common (59% and 60% resp.). HER2 status was unknown for 25% patients. The percentage of equivocal HER2 (immunohistochemistry 2+) cases showing amplification on FISH was also high (56.7%). The percentage of eligible cases for targeted therapy actually receiving it was low (28%). The percentage of triple negative phenotype (ER-/PR-/HER2-) was high (29.8%). Triple-negative breast cancer phenotype was more common in young-aged premenopausal women but was not statistically significant. All HER2/neu + cases were infiltrating ductal carcinoma. HER2/neu expression was significantly higher with large tumor size (P = 0.001), high tumor grade (P < 0.001), advanced stage (P = 0.001), greater number of positive lymph nodes (P = 0.02), and ER/PR negativity (P < 0.001). Conclusions: Most of the breast cancer patients are ER and/or PR positive and HER2/neu negative. The percentage of triple-negative phenotype is higher. More than half of HER2/neu 2+ cases show amplification on FISH assay. The percentage of eligible patients actually receiving targeted therapy is low. HER2/neu protein expression is significantly higher with adverse features such as large tumor size, high grade, advanced stage, greater number of positive lymph nodes, and ER/PR negativity.
Vixen: a games user research tool for collection and interactive visualization of usertesting data

Visualization techniques can facilitate the understanding and exploration of relationships in usertesting data. For example, data from players' in-game movement can be combined with interview data or questionnaire results. However, the process of amalgamation is not straightforward, because the underlying data often exists in different formats. Another challenge is making these visualizations simple enough to provide a quick overview for producers, but also detailed enough to be usable and practical for gameplay programmers. Hence, there is a need for an interactive visualization tool that can adjust data representation based on the nature and detail level of data required from di erent members of a development team. This thesis reports development e orts on a tool that assists data collection and provides a dynamic and interactive representation of usertesting data. The thesis reports two studies to evaluate the e ectiveness of the tool with game developers.
Thermo Mammogram as a Tool to Assess Response to Neoadjuvant Chemotherapy in Breast Carcinoma

Abstract Introduction: Response to neoadjuvant chemotherapy (NACT) is predicted by clinical examination alone in locally advanced breast carcinoma. This study uses thermo mammogram (TMG) to assess the response. Aim and Objectives: The aim is to study TMG changes during NACT in breast cancer and predict response to NACT in locally advanced carcinoma and to compare clinical response with TMG response/changes in any form. Patients and Methods: All patients with locally advanced breast cancer who had treated with NACT were included in this study. Baseline TMG picture was taken using illumina360° (digital robotic rotational thermography device for 360 degree view of each breast) system before chemotherapy. TMG was repeated before next cycle. All patients were also assessed clinically during and after each cycle of chemotherapy. To assess the potential of TMG in predicting tissue response to chemotherapy, the precool, postcool, and the temperature difference between precool and postcool before every cycle were analyzed. Results: A total of 19 patients were analyzed. Eight patients had complete clinical response, six patients had partial response, and five patients had static disease. Median of precool, temperature difference between precool and postcool for patients between no response and complete response did not show statistically significant difference. However, the median of postcool spot temperature showed statistically significant difference. Median of postcool temperature difference for patients between partial response and complete response showed statistically significant difference. The median of postcool spot temperature for patients with no response and partial response did not show statistically significant difference. Precool temperature difference for all the visits showed no statistically significant difference. Conclusion: This preliminary study suggests that the TMG has potential for monitoring NACT response in breast cancer patients. Postcool temperature measurement is an early indicator of response to NACT.