Miracle-dz/UniFAR-FTUs huggingface dataset:
Lymphocyte proteins in Huntington's disease: quantitative analysis by use of two-dimensional electrophoresis and computerized densitometry.

We used quantitative two-dimensional electrophoresis to study lymphocyte proteins in Hungtington's disease. Three hundred and six polypeptides from 14C-labeled, phytohemagglutinin-stimulated lymphocytes were measured for variation in relative spot density and 186 for variation in spot position by use of a computer program requiring operator interaction. Each polypeptide was measured in a total of 30 electrophoretograms from 28 individuals, including 13 with Huntington's disease, 2 at risk for it, and 13 controls. The study included two sets of identical twins and, as neurological controls, individuals with neurofibromatosis, Alzheimer's disease, or Shy-Drager syndrome. Seven protein polymorphisms were identified among the 186 most dense polypeptides of each gel, corresponding to a minimum average heterozygosity of 1.4%. Stringent criteria were used to define polymorphic proteins, including observation of at least one individual with each of two homozygous phenotypes and one with the heterozygous phenotype, demonstration of the expected gene dosage relationship by quantitative densitometry, consistency with genetic relationships, and reproducibility. One polymorphic protein showed three electrophoretically variant alleles. Our identification of seven polymorphisms among the 186 proteins measured on a single electrophoretogram illustrates the potential of this technique for performing linkage analysis in diseases of genetic origin. However, we observed no quantitative or positional protein variations that were characteristic of (i.e. specific for) Huntington's disease.
The epidermal barrier function is dependent on the serine protease CAP1/Prss8

Serine proteases are proteolytic enzymes that are involved in the regulation of various physiological processes. We generated mice lacking the membrane-anchored channel-activating serine protease (CAP) 1 (also termed protease serine S1 family member 8 [Prss8] and prostasin) in skin, and these mice died within 60 h after birth. They presented a lower body weight and exhibited severe malformation of the stratum corneum (SC). This aberrant skin development was accompanied by an impaired skin barrier function, as evidenced by dehydration and skin permeability assay and transepidermal water loss measurements leading to rapid, fatal dehydration. Analysis of differentiation markers revealed no major alterations in CAP1/Prss8-deficient skin even though the epidermal deficiency of CAP1/Prss8 expression disturbs SC lipid composition, corneocyte morphogenesis, and the processing of profilaggrin. The examination of tight junction proteins revealed an absence of occludin, which did not prevent the diffusion of subcutaneously injected tracer (∼600 D) toward the skin surface. This study shows that CAP1/Prss8 expression in the epidermis is crucial for the epidermal permeability barrier and is, thereby, indispensable for postnatal survival.
Multi-element aperiodic array synthesis by Compressive Sensing

In recent years, Compressive Sensing has attracted considerable attention in various areas of antennas and electromagnetics, including the synthesis of sparse array antennas. The CS synthesis of arrays achieves higher accuracy than analytical methods and allows for the fast and deterministic design of large complex arrays, without resorting to computationally expensive Global Optimization methods. The CS approach presented here has been previously studied by the authors for the design of maximally sparse arrays in the presence of mutual coupling effects, beam scanning degradation, as well as the imposition of symmetries for design modularity. In this manuscript the authors demonstrate another (yet unexplored) capability of such an approach, i.e., to incorporate different element types and determine their optimum combination in the course of the array synthesis procedure. Numerical examples are illustrated for large arrays comprising uniform circular aperture elements and operating in a SATCOM multi-beam scenario. It is shown that by exploiting this capability it is possible to simultaneously reduce the number of elements and gain scan loss.
Micro-Doppler analysis and classification of UAVs at Ka band

Recent critical instances have demonstrated the demand for an effective way of detecting and classifying small Unmanned Aerial Vehicles (UAVs) as they pose a serious threat in civil security. We present results of radar measurements with a one channel continuous wave system at Ka band aiming at classifying UAVs through a detailed micro-Doppler analysis. High-sensitivity measurements of different UAVs (quadcopters of different size, octocopter, helicopter, fixed-wing plane) with a large number of different trajectories and flight parameters were obtained. Our analysis is based on different time-frequency transforms (Short-Time Fourier Transform, Cadence Velocity, Cepstrogram), followed by different feature extraction methods including a singular value decomposition. We present first classification results based on a Support Vector Machine algorithm for two different cases: (i) a global classification of the measured UAVs as man-made objects against a set of simulated flying bird data, and (ii) classification and characterization of different types of UAVs. In the latter case we also extract parameters such as number of rotors, rotation rate and rotor blade length. Our first results indicate very good classification accuracies ranging between 96% and 100 %.
Essential role for platelet‐activating factor‐induced NF‐κB activation in macrophage‐derived angiogenesis

Activated monocyte‐macrophages have been implicated in tumor angiogenesis via their capacity to produce many potent angiogenic factors. However, the mechanisms leading to production of these angiogenic factors in macrophages remain to be elucidated. In this study, we demonstrated by use of a mouse Matrigel implantation model that mouse peritoneal macrophages induce angiogenesis. mRNA expression and protein synthesis of macrophage‐derived crucial angiogenic factors such as IL‐1, TNF‐α, basic fibroblast growth factor, and vascular endothelial growth factor (VEGF) were blocked by platelet‐activating factor (PAF) receptor antagonists. It was also observed that inhibitors of NF‐κB blocked macrophage production of these angiogenic factors. Gene expression and protein synthesis of the angiogenic factors cited above were also inhibited in IκBα‐mutated macrophages. VEGF is the most potent angiogenic factor in macrophage‐induced angiogenesis. PAF antagonists or NF‐κB inhibitors also inhibit the capacity of conditioned medium from LPS‐stimulated human peripheral blood monocytes to induce sprouting of porcine pulmonary arterial endothelial cells. Thesedata indicate that PAF‐induced NF‐κB activation is a common upstream pathway leading to the production of crucial macrophage‐derived angiogenic factors. This will provide an important clue for a better understanding of mechanisms involved in tumor angiogenesis.
Individual Flexibility in the Workplace

During the past few decades, scholars have undertaken numerous studies to map various determinants of flexibility at various levels: organizational, group, and individual. However, limited attention has been paid to the role of context and spatiality in realizing individual flexibility. This article aims to fill this gap and seeks to inquire into links between flexibility and spatiality. More specifically, this article will explore how organizational spatial layouts affect individual flexibility as everyday work activities are undertaken in the production of services in two settings, namely, health care and financial services. The findings show that spatial layout is important to better understand and conceptualize individual and organizational flexibility. The findings also show how spatial layout affords various and unexpected outcomes and that layouts that unilaterally foster flexibility are difficult to achieve due to the polymorphous nature of flexibility.
Identifying 802.11 Traffic from Passive Measurements Using Iterative Bayesian Inference

In this paper, we propose a classification scheme that differentiates Ethernet and WLAN TCP flows based on measurements collected passively at the edge of a network. This scheme computes two quantities, the fraction of wireless TCP flows and the degree of belief that a TCP flow traverses a WLAN inside the network, using an iterative Bayesian inference algorithm that we developed. We prove that this iterative Bayesian inference algorithm converges to the unique maximum likelihood estimate (MLE) of these two quantities. Furthermore, it has the advantage that it can handle any general K-classification problem given the marginal distributions of these classes. Numerical and experimental evaluations demonstrate that our classification scheme obtains accurate results. We apply this scheme to two sets of traces collected from two campus networks: one set collected from UMass in mid 2005 and the other collected from UConn in late 2010. Our technique infers that 4%-7% and 52%-55% of incoming TCP flows traverse an IEEE 802.11 wireless link in these two networks, respectively.
An Iterated Conditional Modes / Medians Algorithm for Empirical Bayes Selection of Massive Variables

Empirical Bayes methods are privileged in data mining because they can absorb prior information on model parameters and are free of choosing tuning parameters. We proposed an iterated conditional modes/medians (ICM/M) algorithm to implement empirical Bayes selection of massive variables while incorporating sparsity or more complicated a priori information. The algorithm is constructed on the basis of iteratively minimizing a conditional loss function. The iterative conditional modes are employed to obtain data-driven estimates of hyperparameters, and the iterative conditional medians are used to estimate the model coefficients and therefore enable the selection of massive variables. The ICM/M algorithm is computationally fast, and can easily extend the empirical Bayes thresholding, which is adaptive to parameter sparsity, to complex data. Empirical studies suggest very competitive performance of the proposed method, even in the simple case of selecting massive regression predictors.
State self-esteem following stroke.

BACKGROUND AND PURPOSE Physical rehabilitation after stroke is often highlighted in the absence of consideration of psychosocial factors. This study sought to determine the relationship between state self-esteem and functional independence in patients recovering from stroke. METHODS In a longitudinal study, data were collected from 152 stroke patients within 48 hours of admission to a rehabilitation hospital and at 2 weeks and 3 months after admission. The Modified Barthel Index was used to assess functional ability. Patients' current feelings of self-worth were assessed with use of the State Self-Esteem Scale. Additional variables included perceived social support, trait self-esteem, age, previous stroke, side of stroke, comorbidity, marital status, and gender. RESULTS State self-esteem was significantly correlated to functional independence. The results of linear stepwise regression analysis indicated that functional ability and state self-esteem at 2 weeks, as well as the presence of heart disease, were significant predictors (55%) of functional ability at 3 months. For those with a functional ability score of >/=81 on admission to the rehabilitation unit, state self-esteem and functional ability at 2 weeks as well as previous stroke explained 53% of the variance in functional ability at 3 months. When functional ability was </=80, baseline and 2-week functional ability, state self-esteem at 2 weeks, and age predicted 53% of the variance in functional ability at 3 months. CONCLUSIONS Functional ability at 2 weeks was a stronger predictor than baseline functional ability in this study. The level of state self-esteem was also a consistent factor in the prediction of functional outcome of patients after stroke.
Social restricted Boltzmann Machine: Human behavior prediction in health social networks

Modeling and predicting human behaviors, such as the activity level and intensity, is the key to prevent the cascades of obesity, and help spread wellness and healthy behavior in a social network. The user diversity, dynamic behaviors, and hidden social influences make the problem more challenging. In this work, we propose a deep learning model named Social Restricted Boltzmann Machine (SRBM) for human behavior modeling and prediction in health social networks. In the proposed SRBM model, we naturally incorporate self-motivation, implicit and explicit social influences, and environmental events together into three layers which are historical, visible, and hidden layers. The interactions among these behavior determinants are naturally simulated through parameters connecting these layers together. The contrastive divergence and back-propagation algorithms are employed for training the model. A comprehensive experiment on real and synthetic data has shown the great effectiveness of our deep learning model compared with conventional methods.
Use of computational fluid dynamics as a tool for establishing process design space for mixing in a bioreactor

The concept of “design space” plays an integral part in implementation of quality by design for pharmaceutical products. ICH Q8 defines design space as “the multidimensional combination and interaction of input variables (e.g., material attributes) and process parameters that have been demonstrated to provide assurance of quality. Working within the design space is not considered as a change. Movement out of the design space is considered to be a change and would normally initiate a regulatory post‐approval change process. Design space is proposed by the applicant and is subject to regulatory assessment and approval. ” Computational fluid dynamics (CFD) is increasingly being used as a tool for modeling of hydrodynamics and mass transfer. In this study, a laboratory‐scale aerated bioreactor is modeled using CFD. Eulerian‐Eulerian multiphase model is used along with dispersed k–ε turbulent model. Population balance model is incorporated to account for bubble breakage and coalescence. Multiple reference frame model is used for the rotating region. We demonstrate the usefulness of CFD modeling for evaluating the effects of typical process parameters like impeller speed, gas flow rate, and liquid height on the mass transfer coefficient (kLa). Design of experiments is utilized to establish a design space for the above mentioned parameters for a given permissible range of kLa. © 2011 American Institute of Chemical Engineers Biotechnol. Prog. , 2012
Shared extensible learning spaces

This paper presents a rationale for including the construction of interactive simulations in an Information Technology (IT) curriculum, describes ongoing work in the Shared Extensible Learning Spaces (SHELS) project, and describes how we integrate that work into our curriculum. As computing technologies advance, the complexity of the data generated increases, as does the need for tools to help make sense of the data. There are many domains - science, education, and business, to name a few - that have the need for tools to visualize and analyze complex and dynamic information sets, with information presented in a manner that allows patterns and insight to emerge. We believe that the development of tools for interactive simulation and visualization is an appropriate area of focus in Information Technology, and are currently developing such tools in our Computer Mediated Experience (CME) curriculum. Shared Extensible Learning Spaces-the SHELS project-is an evolving set of strategies for the representation of complex concepts in interactive media spaces. In current projects, faculty and students are creating 3-D spaces populated by smart actors to explore emergent behavior in self-organizing systems, and to document the cognitive experience of users in virtual worlds. We are developing software tools at three levels. At the top level are complete products: interactive simulations for learners and researchers. The bottom level is an extensible set of modules and components for the programming environment in which our tools are built. Our middle level tools allow user/authors to participate in the SHELS project at the level most appropriate to their skills and objectives. These components scaffold the experience of simulation building for content experts and learners whose purposes are best served by working at a higher level. We design our environments to facilitate active learning and encourage inquiry and scholarship at every level.
Pre-Service Teachers' Perception of Quick Response (QR) Code Integration in Classroom Activities.

Quick Response (QR) codes have been discussed in the literature as adding value to teaching and learning. Despite their potential in education, more research is needed to inform practice and advance knowledge in this field. This paper investigated the integration of the QR code in classroom activities and the perceptions of the integration by pre-service teachers. Forty-four pre-service teachers enrolled on an undergraduate degree at a higher education institution in the United Arab Emirates took part in the study. Data were collected from a questionnaire, student journals and focus group interviews to enable triangulation. The main results suggested that the pre-service teachers perceived the use of QR codes to be easy and useful in learning activities. They also demonstrated positive attitudes towards the QR codes and stated the intention to use this application in their future career. The study provided practical examples of how QR codes can be integrated in teaching. It also revealed certain challenges that could hinder effective integration of QR code applications in the classroom. Recommendations for practice and future research are discussed.
THE EXPERIENCE OF EXPERIENTIAL EXERCISES IN MANAGEMENT CLASSES: A PROFESSOR'S VIEW

Research documents the benefits of experiential exercises in business courses. The experiential exercise is a teaching method that allows students to be engaged in the learning process. Experiential learning is widely recognized as an effective way for students to learn about essential business management topics. Just to name a few, experiential exercises are employed in understanding such topics as social responsibility and ethics, team effectiveness, decision making, organizational and international culture, emotional intelligence, and conflict management. The key to experiential exercises is that if provides an opportunity to understand management in a manner that shifts the student from a passive to an active participant in the learning process. However, the experiential exercise can be both fulfilling and terrifying for the professor. This paper offers practical guidelines to assist professors in the implementation of experiential exercises in management classes.
Everyday experiences of memory problems and control: the adaptive role of selective optimization with compensation in the context of memory decline

The present study examined the role of long-term working memory decline in the relationship between everyday experiences of memory problems and perceived control, and we also considered whether the use of accommodative strategies [selective optimization with compensation (SOC)] would be adaptive. The study included Boston-area participants (n = 103) from the Midlife in the United States study (MIDUS) who completed two working memory assessments over 10 years and weekly diaries following Time 2. In adjusted multi-level analyses, greater memory decline and lower general perceived control were associated with more everyday memory problems. Low perceived control reported in a weekly diary was associated with more everyday memory problems among those with greater memory decline and low SOC strategy use (Est. = −0.28, SE= 0.13, p = .036). These results suggest that the use of SOC strategies in the context of declining memory may help to buffer the negative effects of low perceived control on everyday memory.
Rational design of viscosity reducing mutants of a monoclonal antibody: Hydrophobic versus electrostatic inter-molecular interactions

High viscosity of monoclonal antibody formulations at concentrations ≥100 mg/mL can impede their development as products suitable for subcutaneous delivery. The effects of hydrophobic and electrostatic intermolecular interactions on the solution behavior of MAB 1, which becomes unacceptably viscous at high concentrations, was studied by testing 5 single point mutants. The mutations were designed to reduce viscosity by disrupting either an aggregation prone region (APR), which also participates in 2 hydrophobic surface patches, or a negatively charged surface patch in the variable region. The disruption of an APR that lies at the interface of light and heavy chain variable domains, VH and VL, via L45K mutation destabilized MAB 1 and abolished antigen binding. However, mutation at the preceding residue (V44K), which also lies in the same APR, increased apparent solubility and reduced viscosity of MAB 1 without sacrificing antigen binding or thermal stability. Neutralizing the negatively charged surface patch (E59Y) also increased apparent solubility and reduced viscosity of MAB 1, but charge reversal at the same position (E59K/R) caused destabilization, decreased solubility and led to difficulties in sample manipulation that precluded their viscosity measurements at high concentrations. Both V44K and E59Y mutations showed similar increase in apparent solubility. However, the viscosity profile of E59Y was considerably better than that of the V44K, providing evidence that inter-molecular interactions in MAB 1 are electrostatically driven. In conclusion, neutralizing negatively charged surface patches may be more beneficial toward reducing viscosity of highly concentrated antibody solutions than charge reversal or aggregation prone motif disruption.
Application of the Arming System for the Expression of the 380R Antigen from Red Sea Bream Iridovirus (RSIV) on the Surface of Yeast Cells: A First Step for the Development of an Oral Vaccine

The cell surface is a functional interface between the inside and the outside of the cell. Moreover, cells have systems for anchoring surface specific proteins and for confining surface proteins to particular domains on the cell surface. For use in bioindustrial processes applied to oral vaccination, we consider that cell‐surface display systems must be useful and that the yeast Saccharomyces cerevisiae, the most suitable microorganism for practical purposes, is available as a host for genetic engineering because it can be subjected to many genetic manipulations. In particular, the rigid structure of the cell makes the yeast suitable for several of the applications. In this study, we describe the expression of one of the target antigens, 380R, from the red sea bream iridovirus (RSIV), which is one of the most common viral diseases in the cultured marine fish Pagrus major in Japan, using the arming yeast system and aiming at its application for oral vaccination. We first performed the molecular cloning and expression of the 380R antigen from RSIV in Escherichia coli. The nucleotide sequence of the 380R antigen was composed of an open reading frame (ORF) of 1360 bp encoding a protein of 453 residues. To prepare a specific antibody against the 380R antigen, the recombinant protein was overexpressed and purified in E. coli. As a result of indirect immunofluorescence with the specific antibody, we could observe the expression of the 380R antigen on the surface of the yeast cells. Thus, we have successfully prepared the source of an oral vaccine using cell‐surface display technology in yeast.