Miracle-dz/UniFAR-FTUs huggingface dataset:
Measuring Emotions in Real Time

This study introduces a new approach for assessing traveler’s emotions in natural settings and discusses the implications of this approach within the context of designing tourism places; in particular, the electrodermal activity (EDA) of two travelers during a four-day visit to Philadelphia (USA) were used, where they were exposed to a range of experiences while collecting EDA data on a second-by-second basis. The data were then combined with post hoc interviews, including time, locations, activities, and perceptions to aid interpretation. The results indicate that the visitors exhibited substantial variation in emotions depending on the places visited, their activities, and the people they met. It is concluded that the ability to measure travelers’ emotions in real time and in natural settings leads to new knowledge about the relationship between travelers’ emotions and the physical and social environments, which, in turn, provides a useful foundation for designing and managing tourism experiences
Low-rank regularized collaborative filtering for image denoising

Effective noise removal from image signals strongly relies on good image prior, which that comes from the ill-posed nature of image denoising problem. Nonlocal self-similarity and sparsity are two popular and widely used image priors which have led to several state-of-the-art methods in natural image denoising. In recent years, much progress has been made on low-rank modeling and it has achieved great successes in various image analysis problems. In this paper, we propose a new denoising algorithm based on iterative low-rank regularized collaborative filtering of image patches under a nonlocal framework. This collaborative filtering is formulated as recovery of low rank matrices from noisy data. Based on recent results from random matrix theory, an optimal singular value shrinkage operator is applied to efficiently solve this problem. Our experimental results demonstrate the superior denoising performance of the proposed algorithm as compared with the state-of-the-art methods.
Santa Clara University&#8217;s Marine Education Program

Designing, developing and implementing a marine education program from scratch can be a formidable task. Despite being landlocked and facing competition from traditional Silicon Valley projects, Santa Clara University’s (SCU) Robotic Systems Laboratory (RSL) has successfully established a stable, ongoing, undergraduate marine education program in less than seven years. More than 100 students have participated in the program with approximately 50 focusing their capstone design project on a marine-themed problem. This project-based education program first engages students in a marine operations course and then draws the top students into working with the RSL on an underwater vehicle development project for their senior-year, capstone design thesis. The project requirements are derived from RSL and RSL science partner research objectives. This paper will describe the framework of the marine education program that the RSL has developed throughout the past seven years at Santa Clara University and how that framework produces undergraduate and graduate students who are able to not only design, build, and operate underwater vehicles but also perform research with them.
The Analysis of on Instrument for Screening Learning Disabilities

Most instruments used in screening for learning disabilities were not developed specifically for that purpose and therefore do not measure various factors of learning disabilities. The classroom screening instrument (CSI) was investigated for its usefulness as a screening measure. Data collected from 400 children on the CSI were thoroughly factor analyzed to locate the common factor space and to locate the number of original items contributing to the factor space. Of the original 80 items, 48 were found to be loading on 10 factors. Forty of those items were of complexity one, seven were of complexity two, and one item was of complexity three. The factor solution based upon 48 items was of different structure than the original instrument, revealing somewhat different dimensions. The CSI was found to consist of factors which would be very useful in screening for learning disabilities.
Hepatitis C Virus NS5A-Mediated Activation of Phosphoinositide 3-Kinase Results in Stabilization of Cellular β-Catenin and Stimulation of β-Catenin-Responsive Transcription

ABSTRACT The hepatitis C virus (HCV) nonstructural NS5A protein has been shown to bind to and activate phosphoinositide 3-kinase (PI3K), resulting in activation of the downstream effector serine/threonine kinase Akt/protein kinase B. Here we present data pertaining to the effects of NS5A-mediated Akt activation on its downstream targets. Using a recombinant baculovirus to deliver the complete HCV polyprotein to human hepatoma cells in a tetracycline-regulable fashion, we confirm that expression of the complete HCV polyprotein also activates PI3K and Akt. We further show that this results in the inhibition of the Akt substrate Forkhead transcription factor and the stimulation of phosphorylation of a second key Akt substrate, glycogen synthase kinase-3β (GSK-3β). Phosphorylation of GSK-3β results in its inactivation; consistent with this, we show that expression of the HCV polyprotein results in the accumulation of β-catenin. Finally, we show that levels of β-catenin-dependent transcription are also elevated in the presence of the HCV polyprotein. Given the prevalence of β-catenin mutations in many human tumors, especially colon and hepatocellular carcinomas, these data implicate NS5A-mediated PI3K activation as a contributory factor in the increasingly common association between HCV infection and the development of hepatocellular carcinoma.
The cost‐effectiveness implications of suboptimal treatment for different severities of Alzheimer's disease in the UK

This study aims to evaluate the impact of suboptimal treatment, defined in terms of lower population coverage (percentage of total patient population receiving optimal treatment) and delay to treatment on the cost‐effectiveness of pharmacological therapies approved for the treatment of different severities of Alzheimer's disease (AD) in the UK.
Detection of EML4-ALK Fusion Gene in Chinese Non–Small Cell Lung Cancer by Using a Sensitive Quantitative Real-Time Reverse Transcriptase PCR Technique

Anaplastic lymphoma kinase (ALK) rearrangement is present in approximately 5% of lung adenocarcinoma. Clinical trials on ALK inhibitor phase I to III have shown an interesting disease control rate and acceptable tolerability in ALK rearrangement patients. In clinical application, the precise diagnostic strategy for identifying ALK rearrangements remains to be determined. In this study, ALK rearrangement was screened by using quantitative real-time reverse transcriptase polymerase chain reaction (qRT-PCR), direct sequencing, 2 fluorescence in situ hybridization (FISH) assays, and immunohistochemistry in 173 lung adenocarcinomas. We identified 18 cases (10.4%) with EML4-ALK fusion-positive by qRT-PCR, and all were positive for EML4-ALK fusion gene validated by direct sequencing. The result was consistent with that of other methods. Furthermore, of the 18 EML4-ALK fusion-positive cases, 16 (9.2%) were positive by using EML4-ALK fusion probe FISH, and 15 (8.7%) were positive by using ALK break-apart probe FISH and immunohistochemistry staining. Of the 18 ALK fusion-positive lung adenocarcinomas, 8 cases (44.4%) were histologically diagnosed as subtypes of cribriform adenocarcinoma, 7 cases (38.9%) as cribriform adenocarcinoma mixed with papillary and/or mucinous pattern, 2 cases (11.1%) as papillary adenocarcinoma, and 1 case (5.6%) as mucinous adenocarcinoma. In the present study, the ALK rearrangement frequency detected by qRT-PCR in Chinese NSCLC patients was higher than that in the western populations. QRT-PCR is a rapid, sensitive technology that could be used as a screening tool for identifying EML4-ALK fusion-positive NSCLC patients who would be sensitive for receiving ALK inhibitor therapy.
TBX3 Regulates Splicing In Vivo: A Novel Molecular Mechanism for Ulnar-Mammary Syndrome

TBX3 is a member of the T-box family of transcription factors with critical roles in development, oncogenesis, cell fate, and tissue homeostasis. TBX3 mutations in humans cause complex congenital malformations and Ulnar-mammary syndrome. Previous investigations into TBX3 function focused on its activity as a transcriptional repressor. We used an unbiased proteomic approach to identify TBX3 interacting proteins in vivo and discovered that TBX3 interacts with multiple mRNA splicing factors and RNA metabolic proteins. We discovered that TBX3 regulates alternative splicing in vivo and can promote or inhibit splicing depending on context and transcript. TBX3 associates with alternatively spliced mRNAs and binds RNA directly. TBX3 binds RNAs containing TBX binding motifs, and these motifs are required for regulation of splicing. Our study reveals that TBX3 mutations seen in humans with UMS disrupt its splicing regulatory function. The pleiotropic effects of TBX3 mutations in humans and mice likely result from disrupting at least two molecular functions of this protein: transcriptional regulation and pre-mRNA splicing.
Resilience-Oriented Critical Load Restoration Using Microgrids in Distribution Systems

A resilience-oriented service restoration method using microgrids to restore critical load after natural disasters is proposed in this paper. Considering the scarcity of power generation resources, the concept of continuous operating time (COT) is introduced to determine the availability of microgrids for critical load restoration and to assess the service time. Uncertainties induced by intermittent energy sources and load are also taken into account. The critical load restoration problem is modeled as a chance-constrained stochastic program. A Markov chain-based operation model is designed to describe the stochastic energy variations within microgrids, based on which the COT is assessed. A two-stage heuristic is developed for the critical load restoration problem. First, a strategy table containing the information of all feasible restoration paths is established. Then the critical load restoration strategy is obtained by solving a linear integer program. Numerical simulations are performed on the IEEE 123-node feeder system under several scenarios to demonstrate the effectiveness of the proposed method. The impacts of fault locations, available generation resources, and load priority on the restoration strategy are discussed.
Discrete and Rhythmic Motor Primitives for the Control of Humanoid Robots

Controlling robots with multiple degrees of freedom (DOFs) is still an open and challenging issue, notably because planning complex, multidimensional trajectories in time-varying environments is a laborious and costly process. In this dissertation, we propose a control architecture where the planning consists in defining the key characteristics of the desired movement (e.g., the target for reaching), while the generation of the complete trajectory is based on predefined dynamics. More precisely, the generation of joint trajectories is decoupled from high-level planning (i.e., the definition of the task) through the use of a combination of discrete and rhythmic motor primitives, that is, movements with predefined dynamics. The concept of motor primitives is inspired by the study of the motor system of vertebrates: animals are capable not only of performing highly complex tasks in a robust way but also of rapidly adapting to changes or uncertainties in the environment. Interestingly, the planning of movements and the actual generation of trajectories are most likely decoupled in vertebrates: the actual spatio-temporal sequence of activation of the muscles is produced at the spinal level through neural networks called central pattern generators (CPGs). These networks are activated by simple, non-patterned control signals from the brain, that is, only the key parameters of the movement seems to be needed from the brain for a task to be completed. Here we develop a control architecture for the generation of both discrete and rhythmic movements based on motor primitives that has the following attributes (i) the planning phase is simplified thanks to the motor primitives, in the sense that the control commands that are required are reduced to the key characteristics of the movement, (ii) the implementation intrinsically ensures smooth transitions between different tasks (discrete and rhythmic) (iii) the dynamics of the motor primitives can be modulated by sensory feedback in order to have fast adaptive responses and (iv) several DOFs can be coupled together to ensure coordinated behaviors. In addition, this method has a low computational cost and is well-fitted for applications requiring fast control loops. We illustrate the efficiency of the architecture through two applications: (a) interactive drumming with the Hoap2 and the iCub and (b) infant-like crawling and reaching with the iCub.
Unraveling of a Neutralization Mechanism by Two Human Antibodies against Conserved Epitopes in the Globular Head of H5 Hemagglutinin

ABSTRACT The rapid spread of highly pathogenic avian influenza (HPAI) H5N1 virus underscores the importance of effective antiviral treatment. Previously, we developed human monoclonal antibodies 65C6 and 100F4 that neutralize almost all (sub)clades of HPAI H5N1. The conserved 65C6 epitope was mapped to the globular head of HA. However, neither the 100F4 epitope nor the neutralization mechanism by these antibodies was known. In this study, we determined the 100F4 epitope and unraveled a neutralization mechanism by antibodies 65C6 and 100F4.
Synthesis of H2 optimal static structured controllers: Primal and dual formulations

We consider the design of H2 optimal static structured feedback gains for large-scale interconnected systems. The design of distributed controllers with access to measurements of a small number of the subsystems imposes particular sparsity constraints on the feedback gains. For this nonconvex constrained optimal control problem, we study both the primal and dual formulations to obtain optimality bounds. We exploit the sparsity structure present in large-scale systems by implementing an efficient quasi-Newton algorithm to solve the primal problem. We employ the subgradient method to solve the dual problem and obtain a lower bound for the optimal value of the performance index. Surprisingly, in many problems of practical interest, the upper bounds from solving primal problems and the lower bounds from solving dual problems are almost identical, suggesting the lack of duality gap in these applications and that the globally optimal structured gains have in fact been attained.
Religious leaders' response to AIDS in Nigeria

Abstract Increasingly, faith-based organisations are being asked to participate in HIV prevention and care activities. This paper presents formative research on HIV/AIDS prevention messages, activities and policies within six religious institutions in Cross River State, Nigeria, at urban and rural sites. Data collection methods included a review of written HIV policies gathered from national church and mosque offices and 48 key informant interviews. The study highlights differences in messages between mainstream and Pentecostal Christians and Muslims. Although all groups stated a core message of abstinence outside marriage and faithfulness within marriage, Pentecostal churches tended to have more messages of punishment and condemnation for people infected with HIV. Urban churches/mosques tended to have more HIV resources and programmes. Attitudes towards condom use varied by denomination and individual; although few saw a role for religious institutions to promote condoms there were exceptions voiced. These findings indicate that religious organisations are already playing a role in HIV prevention but their responses are not uniform. Public health organisations and policy-makers should be aware of these denominational differences as they engage with religious institutions and leaders in HIV prevention and care.
The Relationship Between Diversity and the Multidimensional Measure of Leader-Member Exchange (LMX-MDM)

Drawing upon the existing literature, this study investigated the relationship between the Diversity dimensions of individualism, collectivism, and gender egalitarianism – and the four LMX dimensions of Contribution, Loyalty, Affect, and Professional Respect. In this study of 300 working adults, we found that there was a significant positive relationship between Diversity and the Multidimensional Measure of Leader-Member Exchange. Further regression analysis indicated that the Diversity dimension, Collectivism, was the driving factor of the relationship. This outcome indicated that Collectivism was a strong predictor of how positively participants rated their attitudes toward their immediate supervisor and perceptions of leadership. Furthermore, it strengthens the argument that organizations must be prepared evaluate their policies with regard to diversity in the organization, particularly with respect to Collectivism.
Pollen Organ Telangiopsis sp. of Late Devonian Seed Plant and Associated Vegetative Frond

Pollen organ Telangiopsis sp. , associated with but not attached to vegetative fronds, has been collected from the Upper Devonian (Famennian) Wutong Formation, Dongzhi County, Anhui Province, China. Fertile axes with terminal pollen organs are dichotomous for 2–4 times and may be proximally attached by fragmentary pinnules. Pollen organs are synangiate and borne on the top of a short stalk. Synangia are radial in symmetry and each consists of 4–8 elongate microsporangia fused at base. Microsporangia have a longitudinal dehiscence line and show a tapered apex. The associated stem is spiny and bears a vegetative frond which bifurcates once at the basalmost part. Frond rachises possess one order of pinna arranged alternately. Pinnules are borne alternately, planate, highly dissected, and equally dichotomous for 2–3 times. Comparisons among Late Devonian seed plants recognize several branching patterns in the fertile fronds/axes bearing terminal pollen organs. Telangiopsis sp. reinforces that the Late Devonian pollen organs are synangiate usually with basally fused microsporangia. It is suggested that the evolutionary divergence of radial and bilateral symmetries of pollen organs may have occurred in the Famennian, when the earliest seed plants evolved planate and sometimes laminate pinnules.
A Systematic Analysis and Design Approach to Develop Adaptable Services in Service Oriented Computing

Service-oriented architecture (SOA) provides a considerably new of invoking functionality. Service providers are to develop and deploy reusable services, and service consumers are to discover right services. A main difficulty in developing generic services is to design services generic enough so that the services can be effectively adapted to diverse service consumers. Moreover, this adaptation takes place at runtime, and hence dynamic adaptation and compositions are essential in service-oriented computing (SOC). For this, service variability among different consumers and contexts should be analyzed and designed into service components. In this dissertation, a service-oriented analysis and design (SOAD) process is presented, which focuses on modeling service variability and mismatch, engineering adaptability into service components and adapters, and enabling dynamic composition of services.
Identifying smart design attributes for Industry 4.0 customization using a clustering Genetic Algorithm

Industry 4.0 aims at achieving mass customization at a mass production cost. A key component to realizing this is accurate prediction of customer needs and wants, which is however a challenging issue due to the lack of smart analytics tools. This paper investigates this issue in depth and then develops a predictive analytic framework for integrating cloud computing, big data analysis, business informatics, communication technologies, and digital industrial production systems. Computational intelligence in the form of a cluster k-means approach is used to manage relevant big data for feeding potential customer needs and wants to smart designs for targeted productivity and customized mass production. The identification of patterns from big data is achieved with cluster k-means and with the selection of optimal attributes using genetic algorithms. A car customization case study shows how it may be applied and where to assign new clusters with growing knowledge of customer needs and wants. This approach offer a number of features suitable to smart design in realizing Industry 4.0.
‘This isn’t what I signed up for’

Although some insight into the sources and scope of occupational stress among rural police officers exists, historically, researchers have focused largely on their policing styles, rather than the relationship between what officers do and how they feel about their work as police in rural jurisdictions. To address this lacuna in knowledge and literature, we draw on data collected from semi-structured interviews conducted with 20 active police officers, each of whom is presently assigned to one of seven rural police detachments in a province in Eastern Canada and field observation of police working in a rural detachment in this same province. In adopting a role theory perspective, we first reveal how officers operationalize their roles as law enforcers, peacekeepers, social workers and/or knowledge workers. We then examine their experiences of role strain as a result of mismatches between their desired versus actual occupational role(s). The majority of officers aspired to hold either the law enforcement or social worker role, which they saw as being most closely associated with their perceptions of what it means to be a ‘police officer’. However, most felt they performed tasks related to less desirable roles, which was tied to role strain. Training recommendations are discussed for officers recruited for rural policing.
Construction of Latent Descriptor Space and Inference Model of Hand-Object Interactions

Appearance-based generic object recognition is a challenging problem because all possible appearances of objects cannot be registered, especially as new objects are produced every day. Function of objects, however, has a comparatively small number of prototypes. Therefore, function-based classification of new objects could be a valuable tool for generic object recognition. Object functions are closely related to hand-object interactions during handling of a functional object; i.e., how the hand approaches the object, which parts of the object and contact the hand, and the shape of the hand during interaction. Hand-object interactions are helpful for modeling object functions. However, it is difficult to assign discrete labels to interactions because an object shape and grasping hand-postures intrinsically have continuous variations. To describe these interactions, we propose the interaction descriptor space which is acquired from unlabeled appearances of human hand-object interactions. By using interaction descriptors, we can numerically describe the relation between an object's appearance and its possible interaction with the hand. The model infers the quantitative state of the interaction from the object image alone. It also identifies the parts of objects designed for hand interactions such as grips and handles. We demonstrate that the proposed method can unsupervisedly generate interaction descriptors that make clusters corresponding to interaction types. And also we demonstrate that the model can infer possible hand-object interactions.