Miracle-dz/UniFAR-FTUs huggingface dataset:
DeepRemote: A smart remote controller for intuitive control through home appliances recognition by deep learning

In ordinary households, as the number of home appliances increases, the number of remote controllers also increases. This makes it difficult to manage remote controllers and find an appropriate one for the target appliance. Recently, systems that can control multiple home appliances through one interface have been proposed. However, such systems have the following problems: interface gets complicated as the number of target appliances increases, a special device needs to be attached to each home appliance or a controller. In this paper, we propose DeepRemote, a smart remote controller that can recognize various home appliances and operate them through IR or network. DeepRemote mounts a camera, an infrared (IR) transceiver, Wi-Fi module, four buttons, an inertial measurement unit (IMU) and a speaker. To recognize a target home appliance, the user just points DeepRemote to the appliance intuitively. After recognition, it automatically enters a particular mode to operate the known home appliance. Then the user can control it through a simple interface using buttons and gestures. Through experiments, we confirmed that DeepRemote achieved 81.07% recognition accuracy for five types of home appliances from different user positions, with about 5 seconds for operating a home appliance when the recognition is accurate.
Trio Clinical Exome Sequencing in a Patient With Multicentric Carpotarsal Osteolysis Syndrome: First Case Report in the Balkans

Exome sequencing can interrogate thousands of genes simultaneously and it is becoming a first line diagnostic tool in genomic medicine. Herein, we applied trio clinical exome sequencing (CES) in a patient presenting with undiagnosed skeletal disorder, minor facial abnormalities, and kidney hypoplasia; her parents were asymptomatic. Testing the proband and her parents led to the identification of a de novo mutation c.188C>T (p.Pro63Leu) in the MAFB gene, which is known to cause multicentric carpotarsal osteolysis syndrome (MCTO). The c.188C>T mutation lies in a hotspot amino acid stretch within the transactivation domain of MAFB, which is a negative regulator of RANKL-induced osteoclastogenesis. MCTO is an extremely rare autosomal dominant (AD) disorder that typically arises spontaneously and causes carpotarsal osteolysis, often followed by nephropathy. To the best of our knowledge, this is the first study reporting genetically diagnosed MCTO in the Balkans.
DeepJ: Style-Specific Music Generation

Recent advances in deep neural networks have enabled algorithms to compose music that is comparable to music composed by humans. However, few algorithms allow the user to generate music with tunable parameters. The ability to tune properties of generated music will yield more practical benefits for aiding artists, filmmakers, and composers in their creative tasks. In this paper, we introduce DeepJ - an end-to-end generative model that is capable of composing music conditioned on a specific mixture of composer styles. Our innovations include methods to learn musical style and music dynamics. We use our model to demonstrate a simple technique for controlling the style of generated music as a proof of concept. Evaluation of our model using human raters shows that we have improved over the Biaxial LSTM approach.
Power Peak Shaving With Data Transmission Delays for Thermal Management in Smart Buildings

This paper presents a scheme aimed at mitigating the influence of random data transmission delays in networked thermal appliance control systems in smart buildings. The impact of this type of delays is first analyzed, and it is proposed to utilize loose timing synchronization and add blank gaps between the consecutive appliance operations to avoid the possible violation of the given power budget. A cooperative control of thermal appliance operation is developed using a networked model predictive control-based controller to deal with delays. It is also shown that the schedulability of such a control scheme can be assessed online. The performance of the proposed control scheme is assessed by a simulation study based on the thermal dynamics of an eight-room office building. The obtained results show that the proposed solution can achieve an efficient power peaks shaving in the presence of random network delays.
Valve morphogenesis in Diploneis smithii (Bacillariophyta)

Diploneis species have perhaps the most complex valve structure among pennate diatoms. The development of this structure was studied in Diploneis smithii and begins with the formation of a primary band, which then develops secondary arms at both poles and the center, as in the classic Chiappino–Volcani model of raphid diatom ontogeny. Spine‐like projections grow out from the primary band and secondary arms to establish the transapical ribs (virgae) of the mature valve and themselves develop spines, which are spaced first oppositely and then alternately and fuse with each other to delimit the stria pores. Subsequently, new pattern and structures develop both externally (formation of bifurcating projections that fuse to delimit the outer, sieve‐like layer of the valve) and internally (growth and fusion of flanges from the first‐formed ribs to create the longitudinal canals and deposition of a hymenate strip over the internal face of each stria). Comparisons are made with morphogenesis in other diatoms. Diploneis smithii ontogeny suggests how very slight developmental changes might have created the very variable external morphology of Diploneis species. It also indicates that the longitudinal canals of Diploneis and Fallacia have different origins, since the porous external wall is not formed as a unilaterally attached flap in Diploneis and the canal is internal to the first‐formed rib–stria system in Diploneis, but external to it in Fallacia.
A Comparison of Traditional and Novel Definitions (RIFLE, AKIN, and KDIGO) of Acute Kidney Injury for the Prediction of Outcomes in Acute Decompensated Heart Failure

Aims: To determine if newer criteria for diagnosing and staging acute kidney injury (AKI) during heart failure (HF) admission are more predictive of clinical outcomes at 30 days and 1 year than the traditional worsening renal function (WRF) definition. Methods: We analyzed prospectively collected clinical data on 637 HF admissions with 30-day and 1-year follow-up. The incidence, stages, and outcomes of AKI were determined using the following four definitions: KDIGO, RIFLE, AKIN, and WRF (serum creatinine rise ≥0.3 mg/dl). Receiver operating curves were used to compare the predictive ability of each AKI definition for the occurrence of adverse outcomes (death, rehospitalization, dialysis). Results: AKI by any definition occurred in 38.3% (244/637) of cases and was associated with an increased incidence of 30-day (32.3 vs. 6.9%, χ2 = 70.1; p < 0.001) and 1-year adverse outcomes (67.5 vs. 31.0%, χ2 = 81.4; p < 0.001). Most importantly, there was a stepwise increase in primary outcome with increasing stages of AKI severity using RIFLE, KDIGO, or AKIN (p < 0.001). In direct comparison, there were only small differences in predictive abilities between RIFLE and KDIGO and WRF concerning clinical outcomes at 30 days (AUC 0.76 and 0.74 vs. 0.72, χ2 = 5.6; p = 0.02) as well as for KDIGO and WRF at 1 year (AUC 0.67 vs. 0.65, χ2 = 4.8; p = 0.03). Conclusion: During admission for HF, the benefits of using newer AKI classification systems (RIFLE, AKIN, KDIGO) lie with the ability to identify those patients with more severe degrees of AKI who will go on to experience adverse events at 30 days and 1 year. The differences in terms of predictive abilities were only marginal.
Mereotopological Correction of Segmentation Errors in Histological Imaging

In this paper we describe mereotopological methods to programmatically correct image segmentation errors, in particular those that fail to fulfil expected spatial relations in digitised histological scenes. The proposed approach exploits a spatial logic called discrete mereotopology to integrate a number of qualitative spatial reasoning and constraint satisfaction methods into imaging procedures. Eight mereotopological relations defined on binary region pairs are represented as nodes in a set of 20 directed graphs, where the node-to-node graph edges encode the possible transitions between the spatial relations after set-theoretic and discrete topological operations on the regions are applied. The graphs allow one to identify sequences of operations that applied to regions of a given relation, and enables one to resegment an image that fails to conform to a valid histological model into one that does. Examples of the methods are presented using images of H&E-stained human carcinoma cell line cultures.
Perceived and geographic food access and food security status among households with children

Abstract Objective To examine the association of both perceived and geographic neighbourhood food access with food security status among households with children. Design This was a cross-sectional study in which participants’ perceptions of neighbourhood food access were assessed by a standard survey instrument, and geographic food access was evaluated by distance to the nearest supermarket. Multinomial logistic regression models were used to examine the associations. Subjects The Midlands Family Study included 544 households with children in eight counties in South Carolina, USA. Food security status among participants was classified into three categories: food secure (FS), food insecure (FI) and very low food security among children (VLFS-C). Results Compared with FS households, VLFS-C households had lower odds of reporting easy access to adequate food shopping. VLFS-C households also had lower odds of reporting neighbourhood access to affordable fruits and vegetables compared with FS households and reported worse selection of fruits and vegetables, quality of fruits and vegetables, and selection of low-fat products. FI households had lower odds of reporting fewer opportunities to purchase fast food. None of the geographic access measures was significantly associated with food security status. Conclusions Caregivers with children who experienced hunger perceived that they had less access to healthy affordable food in their community, even though grocery stores were present. Approaches to improve perceived access to healthy affordable food should be considered as part of the overall approach to improving food security and eliminating child hunger.
Gett ing Ready: Promoting School Readiness through a Relationship-Based Partnership Model

School readines! l is determined by the Ilk aperiences of young children between birth and en.roUment in lonnal eduation Pl:I)8I'Wns. Early Inter- , vention and education programs deSigned to promotc rK:hool 'readiness oftcn focus on skills a child fails to demonstrate that are believed to be of itnponancc to soc:lal and acildemlc sw:. :ceSS. The Gettins Ready mod<:I of early childhood intervention ",cognizes the trans.::tional natur<: of yoWll! children's development and the Imponant role parentll play in preschool readiness and rK:hool.age sU<:CC:f,s. In the G,tNng Ready model, collabora tive pattncnhips betwUn parentI and professionals ate encouraged to promote parent's competence and confidence In maximizing children's natural lcamlpg opportunities, and pr<:paring both parentll and ch.\. Id.n:n for long-tenn school success. Parent.clllld Interactions in everyday experi ences, mutual obsel. 'V3t1ons, and goaI-direded problellMlQlving, and yoWll!
Understanding Linux Malware

For the past two decades, the security community has been fighting malicious programs for Windows-based operating systems. However, the recent surge in adoption of embedded devices and the IoT revolution are rapidly changing the malware landscape. Embedded devices are profoundly different than traditional personal computers. In fact, while personal computers run predominantly on x86-flavored architectures, embedded systems rely on a variety of different architectures. In turn, this aspect causes a large number of these systems to run some variants of the Linux operating system, pushing malicious actors to give birth to “Linux malware. ” To the best of our knowledge, there is currently no comprehensive study attempting to characterize, analyze, and understand Linux malware. The majority of resources on the topic are available as sparse reports often published as blog posts, while the few systematic studies focused on the analysis of specific families of malware (e.g., the Mirai botnet) mainly by looking at their network-level behavior, thus leaving the main challenges of analyzing Linux malware unaddressed. This work constitutes the first step towards filling this gap. After a systematic exploration of the challenges involved in the process, we present the design and implementation details of the first malware analysis pipeline specifically tailored for Linux malware. We then present the results of the first largescale measurement study conducted on 10,548 malware samples (collected over a time frame of one year) documenting detailed statistics and insights that can help directing future work in the area.
Influence of Social and Health Indicators on Pain Interference With Everyday Activities Among Older Black and White Cancer Patients

Objective: This prospective study aimed to determine the influence social and health factors have on pain interference with everyday activities among older patients receiving outpatient treatment services from a comprehensive cancer center. Method: Participants were surveyed on questions assessing pain interference, and social (communication), health (pain severity, comorbidities), behavioral (self-efficacy, affect), and demographic characteristics. Multivariate analyses were specified to examine determinants of pain interference, with items loading on separate cluster composites: physical interference and psychosocial interference. Results: Pain severity was a significant indicator for physical interference. Similarly, pain severity, education, self-efficacy, negative affect, and communication were predictors of psychosocial interference. Discussion: Factors defining the daily lived experiences of older adults are important in providing baseline information on functional status. This emphasizes the need to rigorously examine the association between pain, and clinical and psychosocial indicators, but more importantly indicators that contribute to the patient’s ability to perform normal everyday activities.
A Longitudinal Approach to Changes in the Motivation of Dutch Pharmacists in the Current Continuing Education System

Objective. To explore the changes in motivation of Dutch pharmacists for Continuing Education (CE) in the Dutch CE system. Methods. Pharmacists’ motivation was measured across three time points with the Academic Motivation Scale, based on the Self-Determination Theory of motivation. The Latent Growth Modelling technique was used to analyze these data. Results. Over a period of 21 months, Controlled Motivation had increased and Relative Autonomous Motivation of Dutch pharmacists had decreased. Traineeship was the only demographic factor with a significant influence on the change in motivation. No subgroups with different trajectories could be identified. Conclusion. Relative Autonomous Motivation of Dutch pharmacists for CE decreases over time. This indicates a loss of Autonomous Motivation (“good” motivation) in favor of Controlled Motivation (“bad” motivation). Further research needs to be conducted to gain a better understanding of the association between pharmacist motivation and the features of the current CE system.
Patients’ preferences for attributes related to health care services at hospitals in Amhara Region, northern Ethiopia: a discrete choice experiment

Background Information from the patient’s point of view is essential in policy and clinical decisions. Prioritizing what patients value, need, and prefer in various aspects of a health program can be helpful in evaluating and designing hospital health care services. Objective To examine patients’ preference for attributes related to health care services and to ascertain the relative impact of attributes at hospitals in Amhara Region, northern Ethiopia. Methods A stated-preference discrete choice experiment survey was performed in multistage, stratified, and systematic sampling of patients who visited the hospitals. Attributes were selected based on a literature review of the most important characteristics of hospital health care service and reviewed and validated with inputs from patients and researchers in the field. Attributes included in the study were waiting time, physician communication, nursing communication, drug availability, continuity of care, and diagnostic facilities. A random-effects probit model was used to perform the analysis. Results One thousand and five respondents who received care in the outpatient and inpatient departments participated in the study. All attributes included in the study affected the choice of hospital. Patients were willing to wait up to 3.3 hours and 2.7 hours to get full drugs in the hospital and good nursing communication, respectively. The interaction terms indicate that preferences differ with the variables sex, occupation, and type of hospital. Patients expressed clear preferences in a decreasing order of all the significant attribute levels: a lot of diagnostic facilities, full drug availability, continuity of care, good nursing communication, partial drug availability, good physician communication, and shorter waiting time for the consultation. Conclusion Different hospital care attributes had a significant and different influence on patients’ choice of hospital. The study informs about patients’ preferences and the trade-offs among different possible process-related attributes. Decision makers should focus on patient preferences and consider selected attributes when designating hospital services, and hence to maximize patient satisfaction.
Decomposition of terminology graphs for domain knowledge acquisition

We propose a graph decomposition algorithm for analyzing the structure of complex graph networks. After multi-word term extraction, we apply techniques from text mining and visual analytics in a novel way by integrating symbolic and numeric information to build clusters of domain topics. Terms are clustered based on surface linguistic variations and clusters are inserted in an association network based on their intersection with documents. The graph is then decomposed based on atom graph structure into central (non-decomposable) atom and peripheral atoms. The whole process is applied to publications from the Sloan Digital Sky Survey (SDSS) project in the Astronomy field. The mapping obtained was evaluated by a domain expert and appeared to have captured interesting conceptual relations between different domain topics.
Sensors Based on Bio and Biomimetic Receptors in Medical Diagnostic, Environment, and Food Analysis

Analytical chemistry is now developing mainly in two areas: automation and the creation of complexes that allow, on the one hand, for simultaneously analyzing a large number of samples without the participation of an operator, and on the other, the development of portable miniature devices for personalized medicine and the monitoring of a human habitat. The sensor devices, the great majority of which are biosensors and chemical sensors, perform the role of the latter. That last line is considered in the proposed review. Attention is paid to transducers, receptors, techniques of immobilization of the receptor layer on the transducer surface, processes of signal generation and detection, and methods for increasing sensitivity and accuracy. The features of sensors based on synthetic receptors and additional components (aptamers, molecular imprinted polymers, biomimetics) are discussed. Examples of bio- and chemical sensors’ application are given. Miniaturization paths, new power supply means, and wearable and printed sensors are described. Progress in this area opens a revolutionary era in the development of methods of on-site and in-situ monitoring, that is, paving the way from the “test-tube to the smartphone”.
A growing multi-expert structure for open-ended unsupervised learning of sensory state spaces

We propose a new algorithm, called Growing Multi-Expert Structure (GMES) for unsupervised learning of discrete state spaces in open-ended reinforcement learning tasks. The proposed incremental algorithm is suitable for on-line state space learning on small-scale adaptive systems due to its low computational requirements. It directly processes sequential, raw sensory data, can follow its non-stationarity, and needs only a few parameters to be tuned. The development of the state space is demonstrated in a set of RL experiments using a physically simulated pendulum with varying learning goals started from a tabula-rasa-situation. Furthermore, we show that the system benefits from intrinsic motivation by feeding back the measured learning progress as a separate source of reward to improve the system's capabilities of self-exploration.
An experimental study on relationship between foveal range and FoV of a human eye using eye tracking devices

Various methodologies have been scrutinized to model a human eye. Most of them have failed to consider aspects pertaining to free movement of the head and mainly focus on the gaze of a Human Eye. Today's eye trackers offer gaze data with respect to the normalized coordinate system. In this paper, experimental results are presented that infer that the point of gaze of a human eye, highly lies within the foveal view and drifts along the foveal view as the user traces the gaze points on the 2D plane.
Association between carotid intima-media thickness and adiponectin in participants without diabetes or cardiovascular disease of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil)

Objective The study assessed the association of adiponectin concentration with carotid intima-media thickness (CIMT) in middle-aged participants of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) without diabetes or cardiovascular disease. Design Cross-sectional analyses. Methods A sample of 687 individuals (35–54 years old) without diabetes or cardiovascular disease was stratified into two categories according to CIMT (< or ≥ 75th percentile). Traditional risk factors, C-reactive protein and adiponectin values were compared between categories by Student’s t-test and frequencies by chi-square test. In linear regression models, associations of CIMT with adiponectin, adjusted for adiposity, blood pressure, C-reactive protein and homeostasis model assessment–insulin resistance were tested. Mean CIMT values were compared across quartiles of adiponectin concentrations using analysis of variance. Results Three hundred and forty-one individuals (49.6%) were women and 130 (19.0%) had three traditional cardiovascular risk factors. Those with elevated CIMT (21.8%) had greater mean values of body mass index (26.2(3.8) vs. 27.7(4.0)kg/m2, p < 0.001), waist circumference (86.9(10.1) vs. 90.1(10.8) cm, p = 0.001), systolic blood pressure (116.2(13.6) vs.121.2(16.1) mmHg, p < 0.001), homeostasis model assessment index (1.4(0.9–2.4) vs. 1.8(1.1–2.9), p = 0.011), C-reactive protein (1.2 (0.6–2.6) vs. 1.4(0.8–3.2) mg/l, p = 0.054) and adiponectin (9.9 (6.0–14.7) vs. 8.9 (5.3–13.8) µg/ml, p = 0.002) levels than the counterpart, while plasma glucose and lipids were not different between groups. In the adjusted model, blood pressure (directly) and adiponectin (inversely) persisted associated with high CIMT. Mean CIMT was greater in the first quartile of adiponectin when compared with the other three quartiles (p = 0.019). Conclusions Lower adiponectin levels together with higher blood pressure were independently associated with elevated CIMT. Adiponectin concentration may be an independent marker of early structural damage in individuals at low-to-moderate cardiovascular risk.