Miracle-dz/UniFAR-FTUs huggingface dataset:
Metabolite Profiling and Biological Activity Assessment of Casuarina equisetifolia Bark after Incorporating Gold Nanoparticles

Objective: Casuarina equisetifolia bark is rich in various active metabolites and selected to be studied due to limitation of the synthetic antioxidants that have adverse side effects. The present study aimed to enhance efficiency of the most effective extract by incorporating gold nanoparticles (Au-NPs). Methods: The phytochemical and biological measurements were carried out in total methanolic extract and its successive fractions. Moreover, these measurements were assayed in the most effective extract after incorporating Au-NPs. Results: The study revealed that total methanolic extract exhibited the highest biological and cytotoxic activities as compared to other fractions. Therefore, it is considered as good candidate for nano-extract preparation. The methanolic extract incorporated with Au-NPs showed higher antioxidant, scavenging and cytotoxic activities in addition to higher inhibitory effect against α-amylase activity as compared to native extract itself. To pinpoint active agents in total methanolic extract, the secondary metabolite profiling via HPLC-MS showed that 33 and 17 metabolites were annotated in the extract before and after incorporating Au-NPs, respectively. The median lethal dose (LD50) showed that gold total methanolic nano-extract is safer than total methanolic extract. Conclusion: This study concluded that total methanolic C. equisetifolia bark extract is a valuable bioresource to synthesize an eco-friendly Au-NPs with health-enhancing effect as antioxidant, antidiabetic and cytotoxic agents. The present study is considered as the first report on utilization of C. equisetifolia bark in synthesis of Au-NPs by mean of green nanotechnology and investigation of its biological activity in relation to its metabolite fingerprint.
The stringent starvation protein SspA modulates peptidoglycan synthesis by regulating the expression of peptidoglycan synthases

The peptidoglycan (PG) layer of bacterial cells is essential for maintaining the cell shape and survival of cells; therefore, the synthesis of PG needs to be spatiotemporally controlled. While it is well established that PG synthesis is mediated posttranslationally through interactions between PG synthases and their cognate partners, much less is known about the transcriptional regulation of genes encoding these synthases. Based on a previous finding that the Gram‐negative bacterium Shewanella oneidensis lacking the prominent PG synthase exhibits impaired cell wall integrity, we performed genetic selections to isolate the suppressors. We discovered that disrupting the sspA gene encoding stringent starvation protein A (SspA) is sufficient to suppress compromised PG. SspA serves as a transcriptional repressor that regulates the expression of the two types of PG synthases, class A penicillin‐binding proteins and SEDS/bPBP protein complexes. SspA is an RNA polymerase‐associated protein, and its regulation involves interactions with the σ70‐RNAP complex and an antagonistic effect of H‐NS, a global nucleoid‐associated protein. We also present evidence that the regulation of PG synthases by SspA is conserved in Escherichia coli, adding a new dimension to the current understanding of PG synthesis and its regulation.
Statistical physics of spin glasses and information processing : an introduction

1. Mean-field theory of phase transitions 2. Mean-field theory of spin glasses 3. Replica symmetry breaking 4. Gauge theory of spin glasses 5. Error-correcting codes 6. Image restoration 7. Associative memory 8. Learning in perceptron 9. Optimization problems A. Eigenvalues of the Hessian B. Parisi equation C. Channel coding theorem D. Distribution and free energy of K-Sat References Index
Perspectives on “Community” with Inuit Living in Southern Quebec

ABSTRACT What is a community? This seemingly simple question emerged at the outset of the Qanuikkat Siqinirmiut? (QS) research project on Inuit health in southern Quebec, led in partnership with the Southern Quebec Inuit Association. The question finds its salience in the rapid growth of a southern Inuit population in cities across Canada, a population that has distinct and significant health needs. After early qualitative research, we came to doubt whether the term community adequately characterizes the situation of the roughly 2,000 Inuit living in the South. Thus, this article examines the discourse of community. Specifically, we present an analysis of two schools of thought on the subject: first, the notion of community from classic academic work in urban geography by the Chicago School; and second, inuuqatigiitsiarniq (living well together), which comes from an Inuit system of values and model of health. We first describe the ethnographic data upon which our analysis is drawn and introduce key concepts. Then, we identify conceptual shortcomings in the Chicago School’s notion of community and describe how inuuqatigiitsiarniq expands and nuances the concept. Finally, we discuss the potential of using both concepts to foster a refined understanding of relational health for Inuit living in Montreal.
Perceived convenience, usefulness, effectiveness and user acceptance of information technology: evaluating students’ experiences of a Learning Management System

ABSTRACT This study extended the technology acceptance model developed by Davis to examine the relationship among the variables: perceived convenience (PC), perceived effectiveness (PE), perceived usefulness (PU) and the extent to which they impact on students’ user acceptance of a Learning Management System (LMS). A Questionnaire was used to collect data from 109 second- and third-year students who enrolled in a course via the LMS for the first time. Regression and correlation analyses were used to explore the variables of the study. The results revealed that PC, PU and PE were antecedent factors that affected user acceptance of the LMS, PC being the best predictor of user acceptance. Perceived convenience also correlated positively with both PU and PE, the relationship being more pronounced between PC and PU. Implications of the results for scaling up or replicating the LMS initiative in the study context or in institutions with similar contexts are discussed.
On the Origin of Sub-subgiant Stars. II. Binary Mass Transfer, Envelope Stripping, and Magnetic Activity

Sub-subgiant stars (SSGs) lie to the red of the main sequence and fainter than the red giant branch in cluster color–magnitude diagrams (CMDs), a region not easily populated by standard stellar evolution pathways. While there has been speculation on what mechanisms may create these unusual stars, no well-developed theory exists to explain their origins. Here we discuss three hypotheses of SSG formation: (1) mass transfer in a binary system, (2) stripping of a subgiant’s envelope, perhaps during a dynamical encounter, and (3) reduced luminosity due to magnetic fields that lower convective efficiency and produce large starspots. Using the stellar evolution code MESA, we develop evolutionary tracks for each of these hypotheses, and compare the expected stellar and orbital properties of these models with six known SSGs in the two open clusters M67 and NGC 6791. All three of these mechanisms can create stars or binary systems in the SSG CMD domain. We also calculate the frequency with which each of these mechanisms may create SSG systems, and find that the magnetic field hypothesis is expected to create SSGs with the highest frequency in open clusters. Mass transfer and envelope stripping have lower expected formation frequencies, but may nevertheless create occasional SSGs in open clusters. They may also be important mechanisms to create SSGs in higher mass globular clusters.
Fibre reinforced sands: from experiments to modelling and beyond

Based on hypotheses derived directly from experimental observations of the triaxial behaviour, a constitutive model for fibre reinforced sands is built in this paper. Both the sand matrix and the fibres obey their own constitutive law, whereas their contributions are superimposed using a volumetric homogenization procedure. The Severn‐Trent sand model, which combines well‐known concepts such as critical state theory, Mohr‐Coulomb like strength criterion, bounding surface plasticity and kinematic hardening, is adopted for the sand matrix. Although the fibres are treated as discrete forces with defined orientation, an equivalent continuum stress for the fibre phase is derived to allow the superposition of effects of sand and fibres. The fibres are considered as purely tensile elements following a linear elastic constitutive rule. The strain in the fibres is expressed as a fraction of the strain in the reinforced sample so that imperfect bonding is assumed at the sand‐fibre interface. Only those fibres oriented within the tensile strain domain of the sample can mobilize tensile stress—the orientation of fibres is one of the key ingredients to capture the anisotropic behaviour of fibre reinforced soil that is observed for triaxial compression and extension loading. A further mechanism of partition of the volume of voids between the fibres and the sand matrix is introduced and shown to be fundamental for the simulation of the volumetric behaviour of fibre‐reinforced soils. Copyright © 2012 John Wiley & Sons, Ltd.
Stacked Convolutional Autoencoder with Multi-label Extreme Learning Machine (SCAE-MLELM) for Bangla Regional Language Classification

Several studies emphasized the importance of detecting the dialect spoken by the user, to improve customer-agent relationships in call centers operated by telecomunication companies. and to create advanced speech recognizing Artificial Intelligence devices using machine learning (ML) techniques. However, the extensive Bangla speech recognition research performed in the past did not address this issue. Therefore, in this paper, we propose a model that uses deep learning (DL) techniques, as a subset of ML, to classify the regional language in the audio signal of the Bangla speech. We build a model based on Stacked Convolutional Autoencoders (SCAE) and Multi-label Extreme Learning Machines (MLELM). SCAE extracts the spatial and temporal features from the input data and produces a detailed feature vector. In order to provide a soft classification score and hard labels, the information is passed onto a series of MLELM networks. For Bangla speech dataset created during this research, the proposed method produced an accuracy score of 95%. Furthermore, the proposed system performs remarkably well in classifying the age and gender of the speaker in Bangla.
Using Annotations for Sensemaking About Code

Developers spend significant amounts of time finding, relating, navigating, and, more broadly, making sense of code. While sensemaking, developers must keep track of many pieces of information including the objectives of their task, the code locations of interest, their questions and hypotheses about the behavior of the code, and more. Despite this process being such an integral aspect of software development, there is little tooling support for externalizing and keeping track of developers’ information, which led us to develop Catseye – an annotation tool for lightweight notetaking about code. Catseye has advantages over traditional methods of externalizing code-related information, such as commenting, in that the annotations retain the original context of the code while not actually modifying the underlying source code, they can support richer interactions such as lightweight versioning, and they can be used as navigational aids. In our investigation of developers’ notetaking processes using Catseye, we found developers were able to successfully use annotations to support their code sensemaking when completing a debugging task.
SparseIMU: Computational Design of Sparse IMU Layouts for Sensing Fine-grained Finger Microgestures

Gestural interaction with freehands and while grasping an everyday object enables always-available input. To sense such gestures, minimal instrumentation of the user’s hand is desirable. However, the choice of an effective but minimal IMU layout remains challenging, due to the complexity of the multi-factorial space that comprises diverse finger gestures, objects, and grasps. We present SparseIMU, a rapid method for selecting minimal inertial sensor-based layouts for effective gesture recognition. Furthermore, we contribute a computational tool to guide designers with optimal sensor placement. Our approach builds on an extensive microgestures dataset that we collected with a dense network of 17 inertial measurement units (IMUs). We performed a series of analyses, including an evaluation of the entire combinatorial space for freehand and grasping microgestures (393 K layouts), and quantified the performance across different layout choices, revealing new gesture detection opportunities with IMUs. Finally, we demonstrate the versatility of our method with four scenarios.
InterWeave: Presenting Search Suggestions in Context Scaffolds Information Search and Synthesis

Web search is increasingly used to satisfy complex, exploratory information goals. Exploring and synthesizing information into knowledge can be slow and cognitively demanding due to a disconnect between search tools and sense-making workspaces. Our work explores how we might integrate contextual query suggestions within a person’s sensemaking environment. We developed InterWeave a prototype that leverages a human wizard to generate contextual search guidance and to place the suggestions within the emergent structure of a searchers’ notes. To investigate how weaving suggestions into the sensemaking workspace affects a user’s search and sensemaking behavior, we ran a between-subjects study (n=34) where we compare InterWeave’s in context placement with a conventional list of query suggestions. InterWeave’s approach not only promoted active searching, information gathering and knowledge discovery, but also helped participants keep track of new suggestions and connect newly discovered information to existing knowledge, in comparison to presenting suggestions as a separate list. These results point to directions for future work to interweave contextual and natural search guidance into everyday work.
Interactive Public Displays and Wheelchair Users: Between Direct, Personal and Indirect, Assisted Interaction

We examine accessible interactions for wheelchair users and public displays with three studies. In a first study, we conduct a Systematic Literature Review, from which we report very few scientific papers on this topic and a preponderant focus on touch input. In a second study, we conduct a Systematic Video Review using YouTube as a data source, and unveil accessibility challenges for public displays and several input modalities alternative to direct touch. In a third study, we conduct semi-structured interviews with eleven wheelchair users to understand their experience interacting with public displays and to collect their preferences for more accessible input modalities. Based on our findings, we propose the “assisted interaction” phase to extend Vogel and Balakrishnan’s four-phase interaction model with public displays, and the “ability” dimension for cross-device interaction design to support, via users’ personal mobile devices, independent use of interactive public displays.
Effect of Mental Fatigue on Trust and Workload with AI-enabled Infrastructure Visual Inspection Systems

The visual inspection domain has been impacted by recent technological advancements facilitating the pairing of Artificial Intelligence (AI) with automation, transforming this time-and personnel-intensive routine task into one able to be performed remotely using drones with the human in the role of co-collab-orator (Agnisarman et al., 2019). However, as previous research has found, human trust and task workload, two essential elements for successful human-automation interaction, are impacted by the reliability of the automation: a decrease in reliability reduces human trust (Lee & See, 2004; Muir & Moray, 1996) and increases task workload (Lee & See, 2004; Dixon & Wickens, 2004). Similarly, the fatigue of the human, one of the leading contributors to errors and accidents in the aviation (Isaac et al., 2002) and automotive (Fritzsche et al., 2014) domains, has also been found to affect trust in automation, with the meta-analysis conducted by Schaefer et al. (2016) resulting in its addition to the Human Mental States category of human-related factors. This study investigates changes in the perceived level of trust and workload demand in participants with and without mental fatigue while working with AI-enabled systems of varying reliability. This study used two simulations. The first, the Wizard of Oz simulation, simulated a drone with an AI-enabled system for the visual inspection of a building façade. This drone either correctly identified or failed to identify defects during the inspection at three levels of reliability (90%, 50%, and 10%), recording a Hit, Miss, Correct Rejection, or False Alarm based on signal detection theory for each evaluation. For each reliability level, the drone analyzed 30 independent façade sections simulated to have either no defect or one of the six following defects:
Does My Driver Share My Moral View? Effects of Humanlikeness and Morality in an Adapted Trolley Problem

As autonomous systems become responsible for more complex decisions, it is crucial to consider how these systems will respond in situations wherein they must make potentially controversial decisions without input from users. While previous literature has suggested that users prefer machinelike systems that act to promote the greater good, little research has focused on how the humanlikeness of an agent influences how moral decisions are perceived. We ran two online studies where participants and an automated agent made a decision in an adapted trolley problem. Our results conflicted with previous literature as they did not support the idea that humanlike agents are trusted in a manner analogous to humans in moral dilemmas. Conversely, our study did support the importance for trust of shared moral view between users and systems. Further investigation is necessary to clarify how humanlikeness and moral view interact to form impressions of trust in a system.
Fluctuating Nonlinear Oscillators: From Nanomechanics to Quantum Superconducting Circuits

1. Circuit quantum electrodynamics with a nonlinear resonator 2. Quantum-classical correspondence for a dc-biased cavity resonator-Cooper-pair transistor system 3. Activated switching in nonlinear micromechanical resonators 4. Measurement and control of quantum cavities with electronic atoms 5. Non-degenerate three wave mixing with Josephson junctions 6. Dynamics of nano-magnetic oscillators 7. Periodically modulated quantum nonlinear oscillators 8. Nonlinear oscillators and high fidelity qubit state measurement in circuit quantum electrodynamics 9. Spontaneous time-symmetry breaking in a vibrating cold atom system 10. Nonlinear nanoelectromechanical systems 11. Collective dynamics in arrays of coupled nonlinear resonators 12. Carbon nanotubes: Nonlinear high-Q resonators with strong coupling to single-electron tunneling 13. Dissipative and conservative nonlinearity in carbon nanotube and graphene mechanical resonators 14. Dynamical bifurcation and amplification in Josephson junction oscillators 15. Parametric oscillators based on superconducting circuits
Fatigue Leads to Dynamic Shift in Fronto-parietal Sustained Attention Network

Recently, the gamma band (γ; 70-100 Hz) has been implicated in sustained attention decay across a vigil consistent with computational models of fatigue. Frontal γ indexing centrally controlled sustained attention and parietal γ linked to gated sensory processes declined across a 10-minute vigilance task, a pattern observed for faster but not slower performers. The anatomical distribution of γ activity indicates neural communication, or connectivity, within the fronto-parietal network. We used Granger Prediction to evaluate fatigue effects on network γ connectivity. Results showed stronger directional connectivity for frontal→parietal versus parietal→frontal over time, indicating that top-down control of attention largely remained intact. However, parietal→frontal early γ connectivity increased with time, suggesting a network shift to enhanced sensory-directed processes after only 8 minutes. This pattern of connectivity was mirrored by fast but not slower performers. Our findings provide new directions for computational accounts of fatigue mechanisms and highlight the importance of individual differences.
Overcoming the Lumberjack Effect Through Adaptive Autonomy

Research shows that there are a variety of performance advantages to increasing the degrees of autonomy that human-supporting autonomous systems possess, including organizational productivity and the reduction of human workload. Yet, not all the consequences of increasing autonomy are positive. One such negative consequence is the risk of human operators becoming more incapable of responding to system failures as autonomy levels increase, a phenomenon known as the Lumberjack Effect. This paper proposes a conceptual model for using adaptive autonomy as a means to avoid the risks of this phenomenon while retaining the advantages of higher autonomy levels in earlier stages of an organization’s work cycle. We apply our model to two research-based scenarios and discuss future research necessary to validate the model. This model provides the Human Factors community with a possible solution to the debate over the risks of designing human-supporting autonomous systems with higher degrees of autonomy.
Maybe I Can Do Better Myself: The Impact of Automation Levels on HRI

Although previous studies have developed scales to measure levels of robot autonomy and ways to quantify trust in human-robot teams, there is still much interest in determining how trust, individual differences, and levels of autonomy impact these teams. The primary objective of this study is to identify how pre-existing attitudes about robots, individual differences in normal cognition, and levels of robot autonomy affect performance, communication, and trust with a robot teammate. This study pairs participants with a robot teammate to compete against two robotic opponents in a simulated game of capture the flag. Game performance and interactions with the robot teammate will be collected as outcome measures. Subjective measures will include pre-existing negative attitudes toward robots (Nomura et al., 2006a) and trust (Schaefer, 2016).
Effects of Payment Rate and Country’s Income Level on Attitude Toward aCrowdsourcing Task

Using online crowdsourcing platforms has become an option for researchers to rapidly recruit participants for completing tasks that require human ingenuity. However, a growing concern is that workers on online crowdsourcing platforms, such as Amazon Mechanical Turk (AMT), receive unfair compensation for tasks completed. In this article, we explored the eﬀects of the income level of participant’s country and the rate of payment on perceived payment fairness, task quality, and subjective experience. We tested our hypothesis using 3-way ANOVA and chi-square test of independence. The results showed that lower compensation increased the number of participants whose data might be unusable for research. Participants in the lower compensation rate group reported better perceived performance compared to those who received higher compensation. We found that high income country participants report less perceived eﬀort and frustration than lower-middle income country participants.