Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Robust Neuroadaptive HCI: Exploring Modern Machine Learning Methods to Estimate Mental Workload From EEG Signals

Estimating mental workload from brain signals such as Electroencephalography (EEG) has proven very promising in multiple Human-Computer Interaction (HCI) applications, e.g., to design games or educational applications with adaptive difficulty, or to assess how cognitively difficult to use an interface can be. However, current EEG-based workload estimation may not be robust enough for some practical applications. Indeed, the currently obtained workload classification accuracies are relatively low, making the resulting estimations not fully trustable. This paper thus studies promising modern machine learning algorithms, including Riemannian geometry-based methods and Deep Learning, to estimate workload from EEG signals. We study them with both user-specific and user-independent calibration, to go towards calibration-free systems. Our results suggested that a shallow Convolutional Neural Network obtained the best performance in both conditions, outperforming state-of-the-art methods on the used data sets. This suggests that Deep Learning can bring new possibilities in HCI.
CFar: A Tool to Increase Communication, Productivity, and Review Quality in Collaborative Code Reviews

Collaborative code review has become an integral part of the collaborative design process in the domain of software development. However, there are well-documented challenges and limitations to collaborative code review---for instance, high-quality code reviews may require significant time and effort for the programmers, whereas faster, lower-quality reviews may miss code defects. To address these challenges, we introduce CFar, a novel tool design for extending collaborative code review systems with an automated code reviewer whose feedback is based on program-analysis technologies. To validate this design, we implemented CFar as a production-quality tool and conducted a mixed-method empirical evaluation of the tool usage at Microsoft. Through the field deployment of our tool and a laboratory study of professional programmers using the tool, we produced several key findings showing that CFar enhances communication, productivity, and review quality in human--human collaborative code review.
Beyond the Libet Clock: Modality Variants for Agency Measurements

The Sense of Agency (SoA) refers to our capability to control our own actions and influence the world around us. Recent research in HCI has been investigating SoA to provide users an instinctive sense of "I did that" as opposed to "the system did that". However, current agency measurements are limited. The Intentional Binding (IB) paradigm provides an implicit measure of the SoA, however, it is constrained by requiring high visual attention to a "Libet clock" on-screen. In this paper, we extended the timing stimuli through auditory and tactile cues. Our results demonstrate that audio timing through voice commands and haptic timing through tactile cues on the hand, are an effective alternative measure of the SoA using the IB paradigm. They both address current limitations of the traditional method such as visual attention overload and lack of engagement. We discuss how our results can be applied to measure SoA in tasks involving different interactive scenarios such as in Mixed/Virtual Reality.
A Novel Feature Extraction Technique for Speaker Identification

paper presents a novel feature extraction approach for speaker identification when the speech is corrupted by additive noise. The environmental mismatch between training and testing data degrades the performance of speaker identification system. The performance degradation is primarily due to presence of background noise when try to match a given speaker to the set of known speakers in a database. Mel frequency cepstral coefficients (MFCCs) are perhaps the most widely used front ends in the state of the art speaker identification systems. One of the major issues with MFCCs is that they are very sensitive to additive noise. To overcome this bottleneck, a temporal filtering procedure on the autocorrelation sequence is proposed to minimize the effect of additive noise. The proposed feature is called Relative Autocorrelation Mel Frequency Cepstral Coefficients (A-MFCC) which is derived based on filtering the temporal trajectories of short time one sided autocorrelation sequence. This filtering process minimizes the effect of additive noise. No prior knowledge of noise characteristics is required. The additive noise can be a colored noise. For speaker identification, Hindi database was constructed from the speech samples of each known speaker. Feature vectors (MFCCs and A-MFCCs) were extracted from the samples by short-term spectral analysis, and processed further by vector quantization for locating the clusters in the feature space. Experimental results indicated that A-MFCCs significantly improved the performance of speaker identification system in noisy environment.
REDUCTION OF ORIENTATION EFFECTS IN THE QUANTITATIVE X-RAY DIFFRACTION ANALYSIS OF KAOLIN MINERALS

Two simple methods for reducing preferential orientation of kaolinite and dickite in porvder mounts for the r-ray diffractometer have been evaluated. Neither of these methods requires the use of diluents or any unusual amount of sample preparation. Grinding the porvder in a high-speed vibratory mill is shorvn to reduce the orientation index to a satisfactory level, but not without severely reducing the crystallinity of the clay mineral. Packing -325 mesh powder into an end-loading specimen holder efiectively reduces the orientation index to the predicted theoretical value. The latter method is recommended as a simple and effective method for controlling orientation effects during quantitative analysis of kaolin minerals when basal reflections must be used as analytical lines. However, it is sholvn that, provided no interfering lines are present, and line intensities are sufficiently high, the non-basal (060) reflection provides a more satisfactory analytical line.
Supervised Generative Reconstruction: An Efficient Way To Flexibly Store and Recognize Patterns

Matching animal-like flexibility in recognition and the ability to quickly incorporate new information remains difficult. Limits are yet to be adequately addressed in neural models and recognition algorithms. This work proposes a configuration for recognition that maintains the same function of conventional algorithms but avoids combinatorial problems. Feedforward recognition algorithms such as classical artificial neural networks and machine learning algorithms are known to be subject to catastrophic interference and forgetting. Modifying or learning new information (associations between patterns and labels) causes loss of previously learned information. I demonstrate using mathematical analysis how supervised generative models, with feedforward and feedback connections, can emulate feedforward algorithms yet avoid catastrophic interference and forgetting. Learned information in generative models is stored in a more intuitive form that represents the fixed points or solutions of the network and moreover displays similar difficulties as cognitive phenomena. Brain-like capabilities and limits associated with generative models suggest the brain may perform recognition and store information using a similar approach. Because of the central role of recognition, progress understanding the underlying principles may reveal significant insight on how to better study and integrate with the brain.
Mechanochemical conditioning tool

A tool (1) for mechanochemical treatment comprises a shaft (10), a number n of working ledges (20), n>= 1, and a force application arrangement (2). The force application arrangement (2) is configured for applying a working force (F) on the working ledges (20). The working ledges (20) comprise wear-resistant material with a Vickers number above 800HV and a Young modulus above 200GPa. Each working ledge (20) has a contact surface (22) facing away from a main axis (11) and having a surface roughness Ra below 1[mu]m. The contact surface (22) has a convex curvature which has a radius of curvature that is at most equal to a closest distance from that point to the main axis. A width of the contact surface (22) is less than r/2n. The working force applied on each working ledge (20) is at least P-L-r/2n, wherein P=107 Pa and L is the contact surface length.
Engineering of an alternative electron transfer path in photosystem II

The initial steps of oxygenic photosynthetic electron transfer occur within photosystem II, an intricate pigment/protein transmembrane complex. Light-driven electron transfer occurs within a multistep pathway that is efficiently insulated from competing electron transfer pathways. The heart of the electron transfer system, composed of six linearly coupled redox active cofactors that enable electron transfer from water to the secondary quinone acceptor QB, is mainly embedded within two proteins called D1 and D2. We have identified a site in silico, poised in the vicinity of the QA intermediate quinone acceptor, which could serve as a potential binding site for redox active proteins. Here we show that modification of Lysine 238 of the D1 protein to glutamic acid (Glu) in the cyanobacterium Synechocystis sp. PCC 6803, results in a strain that grows photautotrophically. The Glu thylakoid membranes are able to perform light-dependent reduction of exogenous cytochrome c with water as the electron donor. Cytochrome c photoreduction by the Glu mutant was also shown to significantly protect the D1 protein from photodamage when isolated thylakoid membranes were illuminated. We have therefore engineered a novel electron transfer pathway from water to a soluble protein electron carrier without harming the normal function of photosystem II.
Enhanced Frequency Droop Method for load sharing in LVDC power systems

The main objectives of a load sharing control in dc power systems are proper power sharing among dc sources with an acceptable voltage regulation through the grid. Virtual resistor based droop methods also called voltage droop methods have low performance and accuracy. Hence, supervisory controllers reinforced by a communication system are required to improve the effectiveness of the voltage droop methods. Furthermore, frequency droop approaches have been presented for accurate load sharing control in dc power systems without utilizing a communication system. However, the ripples are superimposed on voltage and current waveforms affecting overall system efficiency and power quality. This paper proposes an Enhanced Frequency Droop Method (EFDM) to overcome the main drawbacks of the frequency droop approaches by stopping voltage superimposing at steady state. Preliminary simulation results show the effectiveness of the proposed approach.
Diphenyl chlorothiophosphonate

The complete molecule of the title compound, C12H10ClO2PS, is generated by crystallographic mirror symmetry, with the P, S and Cl atoms lying on the mirror plane. The resulting PO2SCl tetrahedron is significantly distorted [O—P—O = 96.79 (9)°]. The crystal packing exhibits no directional interactions.
Nucleic Acids Research

Right-handed and left-handed hices of poly(dA-dC). (dG-dT) ABSTRACT The secondary structures of poly(dA-dC). (dG-dT) were studied using CD and IR spectroscopies. We give spectroscopic evidence of secondary structure transitions of poly(dA-dC). (dG-dT) frqm a B to a Z-like helix, induced by transition metal ions (Ni- ) in presence of high concentrations of Cs and Na In the pre- sence of Na , the B^'Z transition occurs at any temperature, whereas premelting conditions are required in presence of Cs . Fog these two alkali ions the Z-like form is only induced by Ni-ions through their specific interactions at N7 of purines. under conditions of low water activity due to the high alkali salt concentration. We also show that the CD spectrum obtained in presence of Cs ions and characterized by a negative band at 275 nm, cannot be interpreted in terms of Z-like left-handed helix but reflects a modified B right-handed helix.
Laughter and Humor Therapy in Dialysis

Laughter and humor therapy have been used in health care to achieve physiological and psychological health‐related benefits. The application of these therapies to the dialysis context remains unclear. This paper reviews the evidence related to laughter and humor therapy as a medical therapy relevant to the dialysis patient population. Studies from other groups such as children, the elderly, and persons with mental health, cancer, and other chronic conditions are included to inform potential applications of laughter therapy to the dialysis population. Therapeutic interventions could range from humorous videos, stories, laughter clowns through to raucous simulated laughter and Laughter Yoga. The effect of laughter and humor on depression, anxiety, pain, immunity, fatigue, sleep quality, respiratory function and blood glucose may have applications to the dialysis context and require further research.
THE ROLE OF INTERPRETATION AND RECONTEXTUALIZATION IN THE ADOPTION OF MARKETING MANAGEMENT CONCEPTS: THE CASES OF MARKET ORIENTATION AND CRM

This interpretive study aims to understand the adoption of marketing knowledge, market orientation (MO) and customer relationship management (CRM) particularly. By means of a series of interviews with managers and employees of third-party logistics (TPL) service providers in Turkey, it has been found that practitioners interpret, reconstruct and reconfigure management knowledge in their own contexts. The adoption process may not be as apparent and straightforward as usually thought. Operational quality and goal relevance moderated the rate of adoption. Despite the small sample size as a major limitation, this study may form the basis for an expanded research effort that is international.
Exploiting Partially Annotated Data in Temporal Relation Extraction

Annotating temporal relations (TempRel) between events described in natural language is known to be labor intensive, partly because the total number of TempRels is quadratic in the number of events. As a result, only a small number of documents are typically annotated, limiting the coverage of various lexical/semantic phenomena. In order to improve existing approaches, one possibility is to make use of the readily available, partially annotated data (P as in partial) that cover more documents. However, missing annotations in P are known to hurt, rather than help, existing systems. This work is a case study in exploring various usages of P for TempRel extraction. Results show that despite missing annotations, P is still a useful supervision signal for this task within a constrained bootstrapping learning framework. The system described in this system is publicly available.
Diagnostic Agents: Collaborative Interpretation for Cardiac Patients at Home

HCI research shows that cardiac patients dislike the passive role imposed by current home monitoring technology. In this paper, we explored how cardiac patients reacted to taking on a more active role of being a diagnostic agent. We developed and implemented a technology probe for these patients to report symptoms and other health metrics to health providers daily . and We studied their interaction with the probe forover eight weeks. Our preliminary findings unfold three themes namely; patient reflection or obsession, patient roles and responsibility towards healthcare staff, and opportunities for nurses to use reports at the hospital in the process of collaborative interpretation. We add to earlier studies, by focusing on the daily, patient-initiated reporting and present topics for further studies.
Detecting Negative Emotion for Mixed Initiative Visual Analytics

The paper describes an efficient model to detect negative mind states caused by visual analytics tasks. We have developed a method for collecting data from multiple sensors, including GSR and eye-tracking, and quickly generating labelled training data for the machine learning model. Using this method we have created a dataset from 28 participants carrying out intentionally difficult visualization tasks. We have concluded the paper by a discussing the best performing model, Random Forest, and its future applications for providing just-in-time assistance for visual analytics.
Asymptotic generators of fermionic charges and boundary conditions preserving supersymmetry

We use a covariant phase space formalism to give a general prescription for defining Hamiltonian generators of bosonic and fermionic symmetries in diffeomorphism invariant theories, such as supergravities. A simple and general criterion is derived for a choice of boundary condition to lead to conserved generators of the symmetries on the phase space. In particular, this provides a criterion for the preservation of supersymmetries. For bosonic symmetries corresponding to diffeomorphisms, our prescription coincides with the method of Wald et al. We then illustrate these methods in the case of certain supergravity theories in d = 4. In minimal AdS supergravity, boundary conditions such that the supercharges exist as Hamiltonian generators of supersymmetry transformations are unique within the usual framework in which the boundary metric is fixed. In extended AdS supergravity, or more generally in the presence of chiral matter superfields, we find that there exist many boundary conditions preserving supersymmetry for which corresponding generators exist. These choices are shown to correspond to a choice of certain arbitrary boundary ‘superpotentials’, for suitably defined ‘boundary superfields’. We also derive corresponding formulae for the conserved bosonic charges, such as energy, in those theories, and we argue that energy is always positive, for any supersymmetry-preserving boundary conditions. We finally comment on the relevance and interpretation of our results within the AdS/CFT correspondence.
Quality assessment and drift analysis of IoT enabled ammonia sensor

Use of sensing technique is now a synonym to industrial work environment and detecting presence of hazardous gases in various industrial processes is nowadays mandatory. This aforementioned fact is realized in this paper, wherein, an integrated IoT server is build using nodejs, utilizing MQTT for M2M communication. The framework is designed for auto connection of sensor nodes as soon as they are powered up and the central server is used for analyzing the incoming sensor data of (CEERIs) ammonia gas sensor. The data collection is made over a period of 4 months with identical gas exposure in two exposure cycle. Here, Raspberry pi3 board is used as a gateway that implements the IoT server and hotspot for device connectivity. Sensors study includes baseline and sensitivity drift, the relative change in response to gas exposure and hysteresis effect together. A correlation of above-mentioned sensor parameters depicts mutual relation and effect of sensor parameters on each other. The industrial safety is also guaranteed by routine sensor health monitoring and possible replacement of the field sensor. The degradation study presented in this paper suggests the possible lifetime of the sensor by utilizing AR and NLRAX prediction models and when it is viable to replace the field sensor.
3D characterization of porosity in an air plasma‐sprayed thermal barrier coating and its effect on thermal conductivity

Air plasma spray (APS) thermal barrier coatings (TBCs) contain pores, cracks and splat interfaces that are preferentially aligned normal to the heat flux direction. These significantly reduce (by as much as 50%) the thermal conductivity over a fully dense coating. Here the microstructures of APS thermal barrier coatings (TBCs) have been characterised in 3D using X-ray micro-computed tomography (μ-CT). Pores larger than 2.8 μm 3 are resolved and their contribution to thermal conductivity reduction is evaluated using image-based microstructurally realistic numerical models. However, the models overestimate (by nearly 50 %) the measured thermal conductivity of the as-deposited TBC sample. It is shown that A cc ep te d A rt ic le This article is protected by copyright. All rights reserved. this discrepancy is due to very fine (micron and sub-micron) cracks which readily sinter after short term exposure to temperatures representative of TBC operating conditions causing the measured thermal conductivity to rise to within 15% of that predicted. This suggests that under the realistic service conditions, the 3D image-based models based on CT images provide a good indicator of the likely long-term TBC performance. Virtual experiments showed that for the retained pores, the larger pores which are flatter and more oriented in the plane of the APS splats, contribute disproportionately to the beneficial reduction in thermal conductivity. Our results demonstrate that X-ray imaging is a useful tool in establishing APS process conditions that gives rise to a beneficial distribution of such pores.
Thermal Resistance and Performance Correlate with Climate in Populations of a Widespread Mosquito

The abundance and success of widely distributed species across variable environments make them suitable models for exploring which traits will be important for resilience to climate change. Using a widespread mosquito species, Culex tarsalis, we have investigated population-level variation in the critical thermal maximum (CTmax) and the metabolic response to temperature (MR-T). Adult female C. tarsalis were sampled from three sites representing thermally distinct habitats in California, and flow-through respirometry was used to determine CTmax and MR-T relationships. CTmax differed significantly among the three populations and correlated positively with maximum temperatures at each site but not with mean temperatures. Culex tarsalis from our cool-temperature, high-altitude site had significantly higher metabolic rates at each test temperature compared with the two populations from warmer sites, consistent with previous examples of thermal compensation in ectothermic animals inhabiting cold climates. The MR-T slope was steepest in mosquitoes inhabiting the site with the lowest temperature variability, while shallower slopes were exhibited by mosquitoes from the two sites with higher thermal variability. Our results show the extent to which local populations may differentiate within their respective environments and suggest that plasticity in thermal tolerance traits may play a role in mediating resilience to climate change. Furthermore, our study highlights the importance of thermal variability and extremes rather than average temperatures for the evolution of thermal traits.
Intelligent level control in horizontal cylindrical tank

The paper aims for modeling and advanced control strategies for liquid level control in a nonlinear, horizontal cylindrical tank system. First principle modeling of the horizontal tank is derived and it is compared with developed neural and fuzzy models of the tank. The best modeling structure is selected for designing a controller for the nonlinear cylindrical tank system. Control strategies like Fuzzy PID control and gain scheduled PID controller are designed; their performances are analyzed using Integral Absolute Error (IAE) and the best controller design is suggested to be implemented in process industries.