Miracle-dz/UniFAR-FTUs huggingface dataset:
Time to decision: the drivers of innovation adoption decisions

Organisations desire timeliness. Timeliness facilitates a better responsiveness to changes in an organisation's external environment to either attain or maintain competitiveness. Despite its importance, decision timeliness has not been explicitly examined. Decision timeliness is measured in this study as the time taken to commit to a decision. The research objective is to identify the drivers of decision timeliness in the context of adopting service-oriented architecture (SOA), an innovation for enterprise computing. A research model rooted in the technology–organisation–environment (TOE) framework is proposed and tested with data collected in a large-scale study. The research variables have been examined before in the context of adoption, but their applicability to the timeliness of innovation decision-making has not received much attention and their salience is unclear. The results support multiple hypothesised relationships, including the finding that a risk-oriented organisational culture as well as normative and coercive pressures accelerates decision timeliness. Top management support as well as the traditional innovation attributes (compatibility, relative advantage and complexity/ease-of-use) were not found to be significant when examining their influence on decision timeliness, which appears inconsistent with generally accepted knowledge and deserves further examination.
Orochi: Investigating Requirements and Expectations for Multipurpose Daily Used Supernumerary Robotic Limbs

Supernumerary robotic limbs (SRLs) present many opportunities for daily use. However, their obtrusiveness and limitations in interaction genericity hinder their daily use. To address challenges of daily use, we extracted three design considerations from previous literature and embodied them in a wearable we call Orochi. The considerations include the following: 1) multipurpose use, 2) wearability by context, and 3) unobtrusiveness in public. We implemented Orochi as a snake-shaped robot with 25 DoFs and two end effectors, and demonstrated several novel interactions enabled by its limber design. Using Orochi, we conducted hands-on focus groups to explore how multipurpose SRLs are used daily and we conducted a survey to explore how they are perceived when used in public. Participants approved Orochi's design and proposed different use cases and postures in which it could be worn. Orochi's unobtrusive design was generally well received, yet novel interactions raise several challenges for social acceptance. We discuss the significance of our results by highlighting future research opportunities based on the design, implementation, and evaluation of Orochi.
Automatic Smile and Frown Recognition with Kinetic Earables

In this paper, we introduce inertial signals obtained from an earable placed in the ear canal as a new compelling sensing modality for recognising two key facial expressions: smile and frown. Borrowing principles from Facial Action Coding Systems, we first demonstrate that an inertial measurement unit of an earable can capture facial muscle deformation activated by a set of temporal micro-expressions. Building on these observations, we then present three different learning schemes - shallow models with statistical features, hidden Markov model, and deep neural networks to automatically recognise smile and frown expressions from inertial signals. The experimental results show that in controlled non-conversational settings, we can identify smile and frown with high accuracy (F1 score: 0.85).
An example of population‐level risk assessments for small mammals using individual‐based population models

This article presents a case study demonstrating the application of 3 individual‐based, spatially explicit population models (IBMs, also known as agent‐based models) in ecological risk assessments to predict long‐term effects of a pesticide to populations of small mammals. The 3 IBMs each used a hypothetical fungicide (FungicideX) in different scenarios: spraying in cereals (common vole, Microtus arvalis), spraying in orchards (field vole, Microtus agrestis), and cereal seed treatment (wood mouse, Apodemus sylvaticus). Each scenario used existing model landscapes, which differed greatly in size and structural complexity. The toxicological profile of FungicideX was defined so that the deterministic long‐term first tier risk assessment would result in high risk to small mammals, thus providing the opportunity to use the IBMs for risk assessment refinement (i.e., higher tier risk assessment). Despite differing internal model design and scenarios, results indicated in all 3 cases low population sensitivity unless FungicideX was applied at very high (×10) rates. Recovery from local population impacts was generally fast. Only when patch extinctions occured in simulations of intentionally high acute toxic effects, recovery periods, then determined by recolonization, were of any concern. Conclusions include recommendations for the most important input considerations, including the selection of exposure levels, duration of simulations, statistically robust number of replicates, and endpoints to report. However, further investigation and agreement are needed to develop recommendations for landscape attributes such as size, structure, and crop rotation to define appropriate regulatory risk assessment scenarios. Overall, the application of IBMs provides multiple advantages to higher tier ecological risk assessments for small mammals, including consistent and transparent direct links to specific protection goals, and the consideration of more realistic scenarios. Integr Environ Assess Manag 2016;12:46–57. © 2015 SETAC
Facility ownership and mortality among older adults residing in care homes

Background and Objectives Nursing or care home characteristics may have a long-term impact on the residents’ mortality risks that has not been studied previously. The study’s main objective was to assess the association between facility ownership and long-term, all-cause mortality. Research Design and Methods. We conducted a mortality follow-up study on a cohort of 611 nursing-home residents in the city Madrid, Spain, from their 1998–1999 baseline interviews up to September 2013. Residents lived in three types of facilities: public, subsidized and private, which were also sub-classified according to size (number of beds). Residents’ information was collected by interviewing the residents themselves, their caregivers and facility physicians. We used time-to-event multivariable models and inverse probability weighting to estimate standardized mortality risk differences. Results After a 3728 person-year follow-up (median/maximum of 4.8/15.2 years), 519 participants had died. In fully-adjusted models, the standardized mortality risk difference at 5 years of follow-up between large-sized public facilities and medium-sized private facilities was 18.9% (95% confidence interval [CI]: −33.4 to −4.5%), with a median survival (95% CI) of 3.6 (0.5 to 6.8) additional years. The fully-standardized 5-year mortality difference (95% CIs) comparing for-profit private facilities with not-for-profit public institutions was −15.1% (−31.1% to 0.9%), and the fully-standardized median survival difference (95% CIs) was 3.0 (-1.7 to 7.7) years. Discussion and Implications These results are highly compatible with an effect on the long-term mortality risk for residents due to factors associated with the ownership of their facilities.
Situational Judgment Tests as a method for measuring personality: Development and validity evidence for a test of Dependability

Situational Judgment Tests (SJTs) are criterion valid low fidelity measures that have gained much popularity as predictors of job performance. A broad variety of SJTs have been studied, but SJTs measuring personality are still rare. Personality traits such as Conscientiousness are valid predictors of many educational, work and life-related outcomes and SJTs are less prone to faking than classical self-report measurements. We developed an SJT measure of Dependability, a core facet of Conscientiousness, by gathering critical incidents in semi-structured interviews using the construct definition of Dependability as a prompt. We examined the psychometric properties of the newly developed SJTs across two studies (N = 546 general population; N = 440 sales professionals). The internal validity of the SJTs was examined by correlating the SJT scores with related self-report measures of Dependability and Conscientiousness, as well as testing the unidimensionality of the measure with CFA. Additionally, we specified a bi-factor model of SJT, self-report and behavioral checklist measures of Dependability accounting for common and specific measurement variance. External validity was examined by correlating the SJT scale and specific factor with work-related outcomes. The results show that the Dependability SJTs with an expert based scoring procedure were psychometrically sound and correlated moderately to highly with traditional self-report measures of Dependability and Conscientiousness. However, a large proportion of SJT variance cannot be accounted for by personality alone. This supports the notion that SJTs measure general domain knowledge about the effectiveness of personality-related behaviors. We conclude that SJT measures of personality can be a promising addition to classical self-report assessments and can be used in a wide variety of applications beyond measurement and selection, for instance as formative assessments of personality.
Process and data fragmentation-oriented enterprise network integration with collaboration modelling and collaboration agents

With the process of globalisation and the development of management models and information technology, enterprise cooperation and collaboration has developed from intra-enterprise integration, outsourcing and inter-enterprise integration, and supply chain management, to virtual enterprises and enterprise networks. Some midfielder enterprises begin to serve for different supply chains. Therefore, they combine related supply chains into a complex enterprise network. The main challenges for enterprise network’s integration and collaboration are business process and data fragmentation beyond organisational boundaries. This paper reviews the requirements of enterprise network’s integration and collaboration, as well as the development of new information technologies. Based on service-oriented architecture (SOA), collaboration modelling and collaboration agents are introduced to solve problems of collaborative management for service convergence under the condition of process and data fragmentation. A model-driven methodology is developed to design and deploy the integrating framework. An industrial experiment is designed and implemented to illustrate the usage of developed technologies in this paper.
Substitution of Dietary Sulfur Amino Acids by DL-2-hydroxy-4-Methylthiobutyric Acid Increases Remethylation and Decreases Transsulfuration in Weaned Piglets

ABSTRACT Background DL-2-hydroxy-4-methylthiobutyric acid (DL-HMTBA), an L-methionine (L-Met) hydroxyl analogue, has been suggested to be a dietary L-Met source. How dietary DL-HMTBA compared with L-Met affects whole-body L-Met kinetics in growing individuals is unknown. Objectives We determined to what extent DL-HMTBA supplementation of an L-Met–deficient diet affects whole-body L-Met and L-cysteine (L-Cys) kinetics, protein synthesis (PS), and the L-Met incorporation rate in liver protein (L-MetInc) compared with L-Met and DL-Met supplementation in a piglet model. Methods Forty-five, 28-d-old weaned piglets (male, German Landrace) were allocated to 4 dietary groups: L-Met-deficient diet [Control: 69% of recommended L-Met plus L-Cys supply; 0.22% standardized ileal digestible (SID) L-Met; 0.27% SID L-Cys; n = 12] and Control diet supplemented equimolarly to 100% of recommended intake with either L-Met (n = 12; LMET), DL-Met (n = 11; DLMET), or DL-HMTBA (n = 10; DLHMTBA). At 47 d of age, the piglets were infused with L-[1-13C; methyl-2H3]-Met and [3,3-2H2]-Cys to determine the kinetics and PS rates. Plasma amino acid (AA) concentrations, hepatic mRNA abundances of L-Met cycle and transsulfuration (TS) enzymes, and L-MetInc were measured. Results During feed deprivation, L-Met kinetics did not differ between groups, and were ≤3 times higher in the fed state (P < 0.01). Remethylation (RM) was 31% and 45% higher in DLHMTBA than in DLMET and Control pigs, respectively, and the RM:transmethylation (TM) ratio was 50% higher in DLHMTBA than in LMET (P < 0.05). Furthermore, TS and the TS:TM ratio were 32% lower in DLHMTBA than in LMET (P < 0.05). L-MetInc was 42% lower in DLMET and DLHMTBA than in L-Met-deficient Control pigs, whereas plasma AA and hepatic mRNA abundances were similar among DL-HMTBA–, L-Met–, and DL-Met–supplemented pigs. Conclusions In piglets, DL-HMTBA compared with L-Met and DL-Met supplementation increases RM and reduces the TS rate to conserve L-Met, but all 3 Met isomers support growth at a comparable rate.
Developmental fluoxetine exposure in zebrafish reduces offspring basal cortisol concentration via life stage-dependent maternal transmission

Fluoxetine (FLX) is a pharmaceutical used to treat affective disorders in humans, but as environmental contaminant also affects inadvertently exposed fish in urban watersheds. In humans and fish, acute FLX treatment and exposure are linked to endocrine disruption, including effects on the reproductive and stress axes. Using the zebrafish model, we build on the recent finding that developmental FLX exposure reduced cortisol production across generations, to determine possible parental and/or life-stage-dependent (age and/or breeding experience) contributions to this phenotype. Specifically, we combined control and developmentally FLX-exposed animals of both sexes (F0) into four distinct breeding groups mated at 5 and 9 months, and measured offspring (F1) basal cortisol at 12 dpf. Basal cortisol was lower in F1 descended from developmentally FLX-exposed F0 females bred at 5, but not 9 months, revealing a maternal, life-stage dependent effect. To investigate potential molecular contributions to this phenotype, we profiled maternally deposited transcripts involved in endocrine stress axis development and regulation, epigenetic (de novo DNA methyltransferases) and post-transcriptional (miRNA pathway components and specific miRNAs) regulation of gene expression in unfertilized eggs. Maternal FLX exposure resulted in decreased transcript abundance of glucocorticoid receptor, dnmt3 paralogues and miRNA pathway components in eggs collected at 5 months, and increased transcript abundance of miRNA pathway components at 9 months. Specific miRNAs predicted to target stress axis transcripts decreased (miR-740) or increased (miR-26, miR-30d, miR-92a, miR-103) in eggs collected from FLX females at 5 months. Increased abundance of miRNA-30d and miRNA-92a persisted in eggs collected from FLX females at 9 months. Clustering and principal component analyses of egg transcript profiles separated eggs collected from FLX-females at 5 months from other groups, suggesting that oocyte molecular signatures, and miRNAs in particular, may serve as predictive tools for the offspring phenotype of reduced basal cortisol in response to maternal FLX exposure.
Augmenting Human With a Tail

Human-augmentation devices have been extensively proposed and developed recently and are useful in improving our work efficiency and our quality of life. Inspired by animal tails, this study aims to propose a wearable and functional tail device that combines physical and emotional-augmentation modes. In the physical-augmentation mode, the proposed device can be transformed into a consolidated state to support a user's weight, similar to a kangaroo's tail. In the emotional-augmentation mode, the proposed device can help users express their emotions, which are realized by different tail-motion patterns. For our initial prototype, we developed technical features that can support the weight of an adult, and we performed a perceptional investigation of the relations between the tail movements and the corresponding perceptual impressions. Using the animal-tail analog, the proposed device may be able to help the human user in both physical and emotional ways.
An improved adaptive online neural control for robot manipulator systems using integral Barrier Lyapunov functions

ABSTRACT Conventional Neural Network (NN) control for robots uses radial basis function (RBF) and for n-link robot with online control, the number of nodes and weighting matrix increases exponentially, which requires a number of calculations to be performed within a very short duration of time. This consumes a large amount of computational memory and may subsequently result in system failure. To avoid this problem, this paper proposes an innovative NN robot control using a dimension compressed RBF (DCRBF) for a class of n-degree of freedom (DOF) robot with full-state constraints. The proposed DCRBF NN control scheme can compress the nodes and weighting matrix greatly and provide an output that meets the prescribed tracking performance. Additionally, adaption laws are designed to compensate for the internal and external uncertainties. Finally, the effectiveness of the proposed method has been verified by simulations. The results indicate that the proposed method, integral Barrier Lyapunov Functions (iBLF), avoids the existing defects of Barrier Lyapunov Functions (BLF) and prevents the constraint violations.
Multiscale modeling of influenza A virus replication in cell cultures predicts infection dynamics for highly different infection conditions

Influenza A viruses (IAV) are commonly used to infect animal cell cultures for research purposes and vaccine production. Their replication is influenced strongly by the multiplicity of infection (MOI), which ranges over several orders of magnitude depending on the respective application. So far, mathematical models of IAV replication have paid little attention to the impact of the MOI on infection dynamics and virus yields. To address this issue, we extended an existing model of IAV replication in adherent MDCK cells with kinetics that explicitly consider the time point of cell infection. This modification does not only enable the fitting of high MOI measurements, but also the successful prediction of viral release dynamics of low MOI experiments using the same set of parameters. Furthermore, this model allows the investigation of defective interfering particle (DIP) propagation in different MOI regimes. The key difference between high and low MOI conditions is the percentage of infectious virions among the total virus particle release. Simulation studies show that DIP interference at a high MOI is determined exclusively by the DIP content of the seed virus while, in low MOI conditions, it is predominantly controlled by the de novo generation of DIPs. Overall, the extended model provides an ideal framework for the prediction and optimization of cell culture-derived IAV manufacturing and the production of DIPs for therapeutic use.
Hypergraph Game Theoretic Solutions for Load Aware Dynamic Access of Ultra-dense Small Cell Networks

A multi-channel access problem based on hypergraph model in ultra-dense small cell networks is studied in this paper. Due to the hyper-dense deployment of samll cells and the low-powered equipment, cumulative interference becomes an important problem besides the direct interference. The traditional binary interference model cannot capture the complicated interference relationship. In order to overcome this shortcoming, we use the hypergraph model to describe the cumulative interference relation among small cells. We formulate the multi-channel access problem based on hypergraph as two local altruistic games. The first game aims at minimizing the protocol MAC layer interference, which requires less information exchange and can converge faster. The second game aims at minimizing the physical layer interference. It needs more information interaction and converges slower, obtaining better performance. The
Face Spoofing Attack Detection Using Spatial Frequency and Gradient-Based Descriptor

Biometric recognition systems have been widely used for information security. Among the most popular biometric traits, there are fingerprint and face due to their high recognition accuracies. However, the security system that uses face recognition as the login method are vulnerable to face-spoofing attacks, from using printed photo or video of the valid user. In this study, we propose a fast and robust method to detect face-spoofing attacks based on the analysis of spatial frequency differences between the real and fake videos. We found that the effect of a spoofing attack stands out more prominently in certain regions of the 2D Fourier spectra and, therefore, it is adequate to use the information about those regions to classify the input video or image as real or fake. We adopt a divide-conquer-aggregate approach, where we first divide the frequency domain image into local blocks, classify each local block independently, and then aggregate all the classification results by the weighted-sum approach. The effectiveness of the methodology is demonstrated using two different publicly available databases, namely: 1) Replay Attack Database and 2) CASIA-Face Anti-Spoofing Database. Experimental results show that the proposed method provides state-of-the-art performance by processing fewer frames of each video.
Can a Convolutional Neural Network Support Auditing of NCI Thesaurus Neoplasm Concepts?

We present a Machine Learning methodology using a Convolutional Neural Network to perform a specific case of an ontology Quality Assurance, namely discovery of missing IS-A relationships for Neoplasm concepts in the National Cancer Institute Thesaurus (NCIt). The training step checking all “uncles” of a concept is computationally intensive. To shorten the time and to improve the accuracy, we define a restricted methodology to check only uncles that are similar to each current concept. The restricted technique yields higher classification recall (compared to the unrestricted one) when testing against known errors found by domain experts who manually reviewed Neoplasm concepts in a prior study. The results are encouraging and provide impetus for further improvements to our technique. Keywords—CNN; Deep Learning; Neoplasm Hierarchy; National Cancer Institute Thesaurus; Quality Assurance; Abstraction Network; Machine Learningion Network; Machine Learning
Virtual Super-Leaping: Immersive Extreme Jumping in VR

People sometimes imagine and yearn for a "Super Power," an ability they do not have naturally. In this paper, we propose Virtual Super-Leaping (VSL) as an immersive virtual experience that provides the feeling of extreme jumping in the sky. First, we define the necessary feedback elements and classify the action sequence of Super-Leaping, including the design of the multimodal feedback for each action state. Then, we describe the design of the VSL system, which has two components: (i) visual a head-mounted display-based feedback, and (ii) a VSL-enabling haptic device, which provides both kinesthesia and airflow using multiple synchronized propeller units. We end by reporting on our technical evaluation and public demonstrations. This work contributes to the enhancement of immersive virtual experiences and development of devices for human augmentation.