Miracle-dz/UniFAR-FTUs huggingface dataset:
Simultaneous Determination of Inorganic Anions and Cations in Water and Biological Samples by Capillary Electrophoresis with a Capacitive Coupled Contactless Conductivity Detector Using Capillary Filling Method

An analytical method for concurrent analysis of inorganic anions and cations has been developed using a capillary electrophoresis (CE)-capacitively coupled contactless conductivity detector (C4D) system. Although hydrodynamic and electrokinetic injection techniques have been widely used in CE, we employed a capillary filling method (CFM) for the analysis of inorganic ions. The procedure is relatively simple and has the advantage that CMF does not require pressure control and vial exchange. Three anions (chloride, sulfate, nitrate) and five cations (ammonium, potassium, sodium, magnesium, calcium) were successfully separated and detected at ppm levels within 80 s using a 9 mM histidine/15 mM malic acid (pH 3.6) containing 50 mM N -dodecyl- N , N -dimethyl-3-ammonio-1-propanesulfonate as background electrolyte. Applying this analytical condition, the electroosmotic flow is negligible and anions and cations were migrated concurrently to different polarities according to their electrophoretic mobility. Obtained raw data showed stepwise increases in detected conductivity due to the migration of sample components, which expresses as peak profiles by differentiation of electropherograms. The RSD values of the peak area and migration times for the anions and cations were satisfactory and were less than 5.15 and 2.04%, respectively. The developed method was applied for the analysis of inorganic anions and cations in commercial mineral waters, tap water, urine, and exhaled breath condensate. These results indicate that the CE-C4D system with CFM is suitable for the rapid analysis of inorganic anions and cations in various samples.
3D volumetric MR arthrographic assessment of shoulder joint capacity in patients with primary adhesive capsulitis.

OBJECTIVE To evaluate the three-dimensional (3D) volumetric MR arthrographic findings of shoulder joint capacity in patients with primary adhesive capsulitis. METHODS Thin-section 3D volumetric MR arthrography sequences of the shoulder joint were obtained in 28 patients with clinically and radiologically proven primary adhesive capsulitis and in 25 controls. Volumetric measurements of the total glenohumeral joint capacity, extra-articular contrast material leakage, and the rotator interval, axillary recess, and biceps tendon sheath capacities were performed for the study and control groups. RESULTS Mean volume of the rotator interval was 7.67 ± 2.6 cm3 in the study group, which was significantly lower than in the control group (12.31 ± 2.5 cm3) (p < 0.0001). Mean volume of the bicipital groove was significantly decreased in the patient group compared to the control group (1.67 ± 0.9 cm3 vs 2.88 ± 0.9 cm3) (p ≤ 0.0001). Mean volume of extra articular contrast material extravasation was 9.93 ± 1.7 cm3 in the patient group, which was significantly higher than in the control group (5.1 ± 1.4 cm3) (p = 0.002). Mean total glenohumeral joint volume was 22.52 ± 1.1 cm3 in the patient group and 26.01 ± 1.2 cm3 in the control group (p = 0.003). CONCLUSION On 3D volumetric MR arthrographic examination, obliterations in the biceps tendon sheath and rotator interval as well as decreased joint capacity may be useful imaging criteria for diagnosing primary adhesive capsulitis. ADVANCES IN KNOWLEDGE In the present study, MR arthrography showed contrast material extravasation in 71% of the patients and showed extra articular contrast material extravasation in 48% of the control subjects. On 3D volumetric MR arthrographic examination, obliterations in the biceps tendon sheath and rotator interval as well as decreased joint capacity may be useful imaging criteria for diagnosing primary adhesive capsulitis.In patients with primary adhesive capsulitis, thin-section 3D volumetric MR arthrography is a useful imaging modality to evaluate both joint capacity and capsular structure.
Predicting group satisfaction in meeting discussions

We address the task of automatically predicting group satisfaction in meetings using acoustic, lexical, and turn-taking features. Participant satisfaction is measured using post-meeting ratings from the AMI corpus. We focus on predicting three aspects of satisfaction: overall satisfaction, participant attention satisfaction, and information overload. All predictions are made at the aggregated group level. In general, we find that combining features across modalities improves prediction performance. However, feature ablation significantly improves performance. Our experiments also show how data-driven methods can be used to explore how different facets of group satisfaction are expressed through different modalities. For example, inclusion of prosodic features improves prediction of attention satisfaction but hinders prediction of overall satisfaction, but the opposite for lexical features. Moreover, feelings of sufficient attention were better reflected by acoustic features than by speaking time, while information overload was better reflected by specific lexical cues and turn-taking patterns. Overall, this study indicates that group affect can be revealed as much by how participants speak, as by what they say.
Naturalistic Digital Task Modeling for Personal Information Assistance via Continuous Screen Monitoring

Despite the growth of personal digital information use, both in scale and application diversity, conventional user models are still reliant on limited user input data to improve a variety of services for specific applications and tasks. This trend toward increased application diversity renders it difficult for a system to generate inferences about a user's evolving interests and naturalistic tasks in real-life settings. This workshop paper introduces a novel approach, aimed at training a user model to recognize real-life tasks on the basis of naturalistic user behavioral data via continuous screen monitoring. The resulting task model could be used in real-life settings for personal information assistance, which proactively retrieves useful documents and resources for the user, on a personal computer, with respect to the task context and information demand.
Shopping intent recognition and location prediction from cyber-physical activities via wi-fi logs

This paper investigates the Cyber-Physical behavior of a user in a large indoor shopping center by leveraging anonymized (opt in) Wi-Fi association and browsing logs recorded by the center operators. Our analysis shows that many users exhibit high correlation between their cyber activities and physical context. To find this correlation, we propose a mechanism to semantically label a physical space with rich categorical information from Wikipedia concepts and compute a contextual similarity that represents a customer's activities with the mall context. We further show the use of cyber-physical contextual similarity in two different applications: user behavior classification and future location prediction. The experimental results demonstrate that the users' contextual similarity significantly improves the accuracy of such applications.
UbiTtention 2018: 3rd International Workshop on Smart & Ambient Notification and Attention Management

In the advancing ubiquitous computing, users are increasingly confronted with a tremendous amount of information proactively provided via notifications from versatile applications and services, through multiple devices and screens in their environment. The human's attention is becoming a new significant bottleneck. Further, the latest computing trends with emerging new devices including versatile IoT devices, and contexts, such as smart cities and vehicles, are even accelerating this situation. In such situations, "attention management", including attention representation, sensing, prediction, analysis, and adaptive behavior in the computer systems, are needed in our computing system. Following last years' successful UbiTtention 2016 and UbiTtention 2017 workshops with up to 50 participants, the UbiTtention 2018 workshop brings together researchers and practitioners from academy and industry to explore the management of human attention and notifications with versatile devices and smart situations to overcome information overload and overchoice.
Cross-Modal Approach for Conversational Well-being Monitoring with Multi-Sensory Earables

We propose a cross-modal approach for conversational well-being monitoring with a multi-sensory earable. It consists of motion, audio, and BLE models on earables. Using the IMU sensor, the microphone, and BLE scanning, the models detect speaking activities, stress and emotion, and participants in the conversation, respectively. We discuss the feasibility in qualifying conversations with our purpose-built cross-modal model in an energy-efficient and privacy-preserving way. With the cross-modal model, we develop a mobile application that qualifies on-going conversations and provides personalised feedback on social well-being.
Functional mechanism of tracheal relaxation, antiasthmatic, and toxicological studies of 6‐hydroxyflavone

Previously, we described tracheal rat rings relaxation by several flavonoids, being 6‐hydroxyflavone (6‐HOF) the most active derivative of the series. Thus, its mechanism of action was determined in an ex vivo tracheal rat ring bioassay. The anti‐asthmatic effect was assayed in in vivo OVAlbumin (OVA)‐sensitized guinea pigs. Finally, the toxicological profile of 6‐HOF was studied based on Organization of Economic Cooperation and Development guidelines with modifications. 6‐HOF–induced relaxation appears to be related with receptor‐operated calcium channel and voltage‐operated calcium channel blockade as the main mechanism of action, and also through the production of relaxant second messengers NO and cGMP. Molecular docking supports that 6‐HOF acts as calcium channel blocker and by activation of nitric oxide synthase. In addition, the in vivo anti‐asthmatic experiments demonstrate the dose‐dependent significant anti‐allergic effect of 6‐HOF induced by OVA, with best activity at 50 /kg. Finally, toxicological studies determined a LD50 > 2,000 mg/kg and, after 28 day of treatment with 6‐HOF (50 mg/kg) by intragastric route, mice did not exhibit evidence of any significant toxicity. In conclusion, experiments showed that 6‐HOF exerts significant relaxant activity through calcium channel blockade, and possibly, by NO/cGMP‐system stimulation on rat trachea, which interferes with the contraction mechanism of smooth muscle cells in the airways. In addition, the flavonoid shows potential anti‐asthmatic properties in an anti‐allergic pathway. Furthermore, because the pharmacological and safety evidence, we propose this flavonoid as lead for the development of a novel therapeutic agent for the treatment of asthma and related respiratory diseases.
QSPR modelling for prediction of glass transition temperature of diverse polymers

ABSTRACT The glass transition temperature is a vital property of polymers with a direct impact on their stability. In the present study, we built quantitative structure–property relationship models for the prediction of the glass transition temperatures of polymers using a data set of 206 diverse polymers. Various 2D molecular descriptors were computed from the single repeating units of polymers. We derived five models from different combinations of six descriptors in each case by employing the double cross-validation technique followed by partial least squares regression. The selected models were subsequently validated by methods such as cross-validation, external validation using test set compounds, the Y-randomization (Y-scrambling) test and an applicability domain study of the developed models. All of the models have statistically significant metric values such as r2 ranging from 0.713–0.759, Q2 ranging from 0.662-0.724 and ranging 0.702–0.805. Finally, a comparison was made with recently published models, though the previous models were based on a much smaller data set with limited diversity. We also used a true external set to demonstrate the performance of our developed models, which may be used for the prediction and design of novel polymers prior to their synthesis.
Measuring Study Activity across High School Students Using Commercial EOG Glasses

Health monitoring using a wearable device is gaining increasing research interest. Several longitudinal studies have been conducted across college students taking advantage of the robust data acquisition of wearable devices. In these studies, watch-type wearable device and mobile phone are often used to collect data. However, longitudinal activity tracking using an eyewear-type device is challenging because such devices often result in significant discomfort to the user due to their bulky hardware. This paper reports on a longitudinal study on high school students using commercial electrooculography glasses to track study activity. Initial result indicates that weekly feedback via text messages can contribute to longer use of the device.
Detecting Emotions using Smartphone Sensors: Technique to Raise Self-Awareness for Social Media Users

Emotions are the driving force for posting content on a social media platform. Although modeling and predicting in emotion with social media have been proposed, they often require post-investigation such as sentiment analysis. This often limits users to be aware of negative emotional states while publishing content on social media. In this project, we will propose an emotion detection technique by extracting the physiological responses of social media users from smartphone commodity sensors. We aim to provide design opportunities for social media platforms to raise emotional self-awareness of the users while using social media on the smartphone.
The effects of collection and storage conditions in the field on salivary testosterone, cortisol, and sIgA values

Abstract Aim: To determine if field-typical storage and collection conditions are related to salivary testosterone (T), cortisol (cort) and secretory immunoglobulin A (sIgA) as measured using commercially available kits. Subjects and methods: This study assessed whether storage time (∼6 months to 1.5 years) at −35 °C impacted levels of the measured biomarkers (n = 10,247 samples). For a sub-set of T samples (n = 2954), we also evaluated the impact of collection conditions, such as time spent at room temperature in participants’ homes (0–39 hours) and time spent in coolers (0.3–10 hours) in transit. Results: T was unrelated to storage and collection variables and there was no evidence of reduced sample fidelity at longer storage times. Cort samples stored at −35 °C for longer had significantly lower values, but the effect was small (β = −0.003 nmol/L/day, SE <0.001, p = 0.005). sIgA trended higher with longer storage at −35 °C (β = 0.84 µg/mL/day, SE = 0.45, p = 0.063). Collection and storage time variables did not improve the fit of any of the models except the one that evaluated cortisol. Conclusions: Salivary T was unaffected by extended storage at −35 °C and only a weak relationship was found between storage time and salivary cort or sIgA. Findings underscore the robustness of these biomarkers under field-typical freezer storage conditions.
Future Perspectives on GLP-1 Receptor Agonists and GLP-1/glucagon Receptor Co-agonists in the Treatment of NAFLD

Along the obesity pandemic, the prevalence of non-alcoholic fatty liver disease (NAFLD), often regarded as the hepatic manifestation of the metabolic syndrome, increases worldwide representing now the prevalent liver disease in western countries. No pharmacotherapy is approved for the treatment of NAFLD and, currently, the cornerstone treatment is lifestyle modifications focusing on bodyweight loss, notoriously difficult to obtain and even more difficult to maintain. Thus, novel therapeutic approaches are highly demanded. Glucagon-like peptide-1 (GLP-1) receptor agonists (GLP-1RAs) are approved for the treatment of type 2 diabetes and obesity. They exert their body weight-lowering effect by reducing satiety and food intake. GLP-1RAs have also been shown to reduce liver inflammation and fibrosis. Furthermore, glucagon receptor agonism is being investigated for the treatment of NAFLD due to its appetite and food intake-reducing effects, as well as its ability to increase lipid oxidation and thermogenesis. Recent studies suggest that glucagon receptor signaling is disrupted in NAFLD, indicating that supra-physiological glucagon receptor agonism might represent a new NAFLD treatment target. The present review provides (1) an overview in the pathophysiology of NAFLD, including the potential involvement of GLP-1 and glucagon, (2) an introduction to the currently available GLP-1RAs and (3) outlines the potential of emerging GLP-1RAs and GLP-1/glucagon receptor co-agonists in the treatment of NAFLD.
Venous thromboembolism prophylaxis after hip preservation surgery: a review and presentation of institutional experience

ABSTRACT Venous thromboembolism (VTE) is a serious complication after major orthopedic procedures. The best options for prevention of the VTE are still debated. The most popular evidence-based guidelines for prevention and treatment of VTE in orthopedic surgery addressed the total hip or knee arthroplasty and hip fractures as the major orthopedic surgeries. Majority of studies have evaluated the different modalities of the VTE prophylaxis in patients undergiong hip or knee arthroplasty. Hip preservation surgeries (HPS) including mini-open femoroacetabular osteoplasty, surgical dislocation of the hip, arthroscopic procedures, and periacetabular osteotomy (PAO) are gained popularity in recent two decades. The majority of these patients are young, healthy and active and may not be considered at high risk for VTE. The frequency of VTE in patients undergoing PAO seems to be low between 0 and 5%. There is a paucity of data regarding rates of VTE in young healthy patients undergoing HPS as well as the optimal prevention methods for VTE. Hence current VTE prevention guidelines do not cover HPS adequately. We aimed to review the available literature regarding VTE events and VTE prophylaxis options after HPS. We discussed the available and potential options for prophylaxis of VTE events in these procedures along with our experience in a large cohort of hip preservation surgery.
Are TADs supercoiled?

Abstract Topologically associating domains (TADs) are megabase-sized building blocks of interphase chromosomes in higher eukaryotes. TADs are chromosomal regions with increased frequency of internal interactions. On average a pair of loci separated by a given genomic distance contact each other 2–3 times more frequently when they are in the same TAD as compared to a pair of loci located in two neighbouring TADs. TADs are also functional blocks of chromosomes as enhancers and their cognate promoters are normally located in the same TAD, even if their genomic distance from each other can be as large as a megabase. The internal structure of TADs, causing their increased frequency of internal interactions, is not established yet. We survey here experimental studies investigating presence of supercoiling in interphase chromosomes. We also review numerical simulation studies testing whether transcription-induced supercoiling of chromatin fibres can explain how TADs are formed and how they can assure very efficient interactions between enhancers and their cognate promoters located in the same TAD.
Almost optimal distance oracles for planar graphs

We present new tradeoffs between space and query-time for exact distance oracles in directed weighted planar graphs. These tradeoffs are almost optimal in the sense that they are within polylogarithmic, subpolynomial or arbitrarily small polynomial factors from the naïve linear space, constant query-time lower bound. These tradeoffs include: (i) an oracle with space O(n1+є) and query-time Õ(1) for any constant є>0, (ii) an oracle with space Õ(n) and query-time O(nє) for any constant є>0, and (iii) an oracle with space n1+o(1) and query-time no(1).
A Framework for Group Identification using Smartphone and Wearables

Human beings are social by nature and like to form the group with the similar minded people. Therefore, for understanding the behaviour of an individual, besides the information of the individual, we need to look at the interaction of the individual in physical world groups. Likewise, the workers form various formal and informal groups in the organization for mutual interactions. For monitoring context as well as behaviours of the workers, identification of such groups and understanding their dynamics are essential. Moreover, this information is used for analysing the organizational efficiency. In an institutional environment, the knowledge of the student group formation helps the instructor to the analyse the performance of the students. On the other side, the proper selection of groups leads to the improvement of the students. Understanding the group dynamics in sports is also important. The proper interpretation of the group dynamics reveals the strategy of the team. Hence, for the future sports event, it is useful to the opponent team.
An early resource characterisation of wi-fi sensing on residential gateways

Recent research has successfully shown brand new models with Wi-Fi signals explaining space dynamics, assessing social environments, and even tracking people's posture, gesture and emotion. However, these models are seldom used in real execution and operating environments, i.e., on residential gateways with networking tasks. In this paper, we present the first, albeit preliminary, measurement study of common Wi-Fi sensing models on a residential gateway. This investigation aims to understand the performance characteristics, resource requirements, and execution bottlenecks for Wi-Fi sensing when being used in parallel with communication tasks. Based on our findings, we propose two optimisation techniques - i) dynamic sampling and ii) dynamic planning of inference execution - for optimum Wi-Fi sensing performance without compromising the quality of communication service. The results and insights lay an empirical foundation for the development of optimisation methods and execution environments that enable sensing models to be more readily integrated into next-generation residential gateways.
Textile Sensor-based Visualization to Enhance Skills to Understand the Body-Pressure Distribution for Pressure Ulcer Prevention

This study proposes a system to visualize the body-pressures applied to body parts in a bed, with textile pressure sensors to support caregivers to learn posture change skill for pressure ulcer prevention. As the result of an evaluation with 21 nursing students, the comparison group using our system for learning showed better scores than ones of the control group with skill to understand the body-pressure distribution of sub-body parts: head (6/6, 100%) and right leg (3/6, 50%).
The Burst Failure Influence on the H∞ Norm

In this work, we present an analysis of the Burst failure effect in the $H_\infty$ norm. We present a procedure to perform an analysis between different Markov Chain models and a numerical example. In the numerical example the results obtained pointed out that the burst failure effect in the performance does not exceed 6.3%. However, this work is an introduction for a wider and more extensive analysis in this subject.