Miracle-dz/UniFAR-FTUs huggingface dataset:
Antibody engineering: the use of Escherichia coli as an expression host

The hypervariable loops of an antibody molecule are supported on the relatively conserved β‐sheeted frameworks of the heavy‐ and light‐chain variable domains (designated VH and VL domains, respectively). Residues within and flanking these loops interact with antigen and confer the specificity and affinity of antigen binding on the immunoglobulin molecule. Thus, the isolation and expression of VH and VL domain genes are of particular interest both for analysis of the determinants of antibody specificity and for generation of fragments with binding affinities for use in therapy and diagnosis. The PCR can now be used to isolate diverse repertoires of antibody VH and VL domain genes from antibody‐producing cells from different species, including humans and mice. The genes can be expressed as either secreted or surface‐bound Fv or Fab fragments, using Escherichia coli expression systems, and the desired antigen‐binding specificity screened for or, preferably, selected. The use of E. coli as an expression host allows the required antigen‐binding specificity to be isolated in clonal form in a matter of days. The VH and VL domain genes can also be hyper‐mutated and higher‐affinity variants isolated by screening or selection. Thus, the use of this technology should allow the isolation of novel binding specificities or specificities that are difficult to generate by hybridoma technology. It will also facilitate the isolation of human‐derived Fv/Fab fragments that may be less immunogenic in therapy. This approach therefore has almost unlimited potential in the generation of therapeutics with binding specificities to order. The fragments can be used either alone or linked to effector functions in the form of antibody‐constant domains or toxins. The new technology could prove to be a method of choice for the rapid and convenient production of designer antibodies. —Ward, E. S. Antibody engineering: the use of Escherichia coli as an expression host. FASEB J. 6: 2422‐2427; 1992.
Job profiling in high performance printing

Digital presses have consistently improved their speed in the past ten years. Meanwhile, the need for document personalization and customization has increased. As a consequence of these two facts, the traditional RIP (Raster Image Processing) process has became a highly demanding computational step in the print workflow. Print Service Providers (PSP) are now using multiple RIP engines and parallelization strategies to speed up the whole ripping process which is currently based on a per-page base. Nevertheless, these strategies are not optimized in terms of assuring the best Return On Investment (ROI) for the RIP engines. Depending on the input document jobs characteristics, the ripping step may not achieve the print-engine speed creating a unwanted bottleneck. The aim of this paper is to present a way to improve the ROI of PSPs proposing a profiling strategy which enables the optimal usage of RIPs for specific jobs features ensuring that jobs are always consumed at least at engine speed. The profiling strategy is based on a per-page analysis of input PDF jobs identifying their key components. This work introduces a profiler tool to extract information from jobs and some metrics to predict a job ripping cost based on its profile. This information is extremely useful during the job splitting step, since jobs can be split in a clever way. This improves the load balance of the allocated RIPs engines and makes the overall process faster. Finally, experimental results are presented in order to evaluate both, the profiler and the proposed metrics.
Software reuse metrics for object-oriented systems

The importance of software measurement is increasing leading to development of new measurement techniques. Reusing existing software components is a key feature in increasing software productivity. It is one of the key elements in object-oriented programming, which reduces the cost and increases the quality of the software. An important feature of C++ called templates support generic programming, which allows the programmer to develop reusable software modules such as functions, classes, etc. The need for software reusability metrics is particularly acute for an organization in order to measure the degree of generic programming included in the form of templates in code. This research addresses this need and introduces a new set of metrics for object-oriented software. Two metrics are proposed for measuring amount of genericty included in the code and then analytically evaluated against Weyuker's set of nine axioms. This set of metrics is then applied to standard projects and accordingly ways in which project managers can use these metrics are suggested.
Effect of ferromagnetic proximity on critical behavior

The continuous phase transition in thin magnetic films and superlattices has been studied using the magneto-optical Kerr effect (MOKE) and polarized neutron scattering (PNR). It has been shown that the critical behavior of amorphous thin films belonging to the 2D XY universality class can be described within the same theory as crystalline sample. This means that quenched disorder only serves as a marginal perturbation in systems with this symmetry. The connection between interlayer exchange coupling and the observed critical behavior in Fe/V superlattices was explored. The results prove that the origin of unusually high values of the exponent β can be traced to a position dependence of the magnetization at elevated temperatures. The magnetization of the outermost layers within the superlattice shows a more pronounced decrease at lower temperatures, compared to the inner layers, which in turn have a more abrupt decrease in the vicinity of the critical temperature. This translates to a high exponent, especially when the layers are probed by a technique where more weight is given to the layers close to the surface, e.g.MOKE. The interlayer exchange coupling as a function of spacer thickness and temperature was also studied in its own right. The data was compared to the literature, and a dependence on the thickness of the magnetic layers was concluded. The phase transition in amorphous FeZr/CoZr multilayers, where the magnetization emanates from ferromagnetic proximity effects, was investigated. Even though the determined exponents of the zero-field magnetization, the susceptibility and the critical isotherm did not correspond to any universality class, scaling plots displayed an excellent data collapse. Samples consisting of Fe δ-layers (0.3-1.4 monolayers) embedded in Pd were studied using element-specific resonant x-ray magnetic scattering. The magnetization of the two constituents showed distinctly different temperature dependences.
DELOS: An Automatically Tagged Economic Corpus for Modern Greek

Text corpora resources have become an essential tool for Natural Language Processing tasks over the past years. A wide range of applications like information retrieval, ontology and terminology extraction require a sufficiently large corpus but of restricted domain. Manual tagging of such a corpus is very costly, making automatic annotation by a set of linguistic tools a very challenging idea. DELOS, described in this paper, is a Modern Greek corpus of economic domain consisting of 5 million word tokens, which is automatically tagged for morphology and shallow syntactic relations. The annotating tools described are embodied in an integrated system and their application to the corpus is performed using the GATE text engineering platform. The system output is a textual database marked up with the annotation tagset in plain text as well as in XML format.
3D-model retrieval using bag-of-salient local spectrums (BOS)

The interest of this paper is to present a new efficient method for indexing and retrieval of three-dimensional objects in general databases. The proposed method is based on Bag of Features (BoF) paradigm, and salient characteristics of objects. We first extract the salient points of target object using a scalar function calculated on the surface. Then, each interest point is associated with local Fourier descriptor. This descriptor is computed in its neighborhood by projecting the geometry onto the first eigenvectors of Laplace-Beltrami operator. Additionally, in an offline learning stage, a visual dictionary is built by clustering a large set of feature descriptors. Then each 3D shape is described by a histogram of occurrences of these visual words weighted by his local descriptors number. The obtained results show the highly discriminative capability of the proposed approach against rigid and non-rigid transformations, noise and geometry changes. The performance of our approach is also demonstrated for global and partial shape retrieval.
An integrated speech processing method utilizing general Kalman filter

Speech processing has two major applications namely, Speech enhancement which deals with extracting of clean speech from a noisy one and Speaker identification, a process of providing authentication basing on human speech. Since, speech is a non-stationary signal there are many adaptive algorithms developed to deal with the above applications. One such highly popular algorithm having many forms is Kalman filter. The purpose of present work is to study the use of General Kalman Filter (GKF) a form derived from Kalman filter along with Estimate Maximization (EM) algorithm. The first step of process involves understanding GKF and EM algorithm, second is to use them for Speech enhancement and third step is to use them in pre-processing step of Speaker identification, which shows its significance. Simulation results show the combination of GKF and EM provides a better Speech enhancement and acts as an efficient pre-processing step of Speaker identification over conventional method.
Comparative Evaluation of an Error Checking Approach for MPSoC

This paper proposes a hardware error checking approach（CCRC）by using redundancy core for multiprocessor system-on-chip (MPSoC) and describes several main error detection methods based on Software-Implemented Hardware Fault Tolerance (SHIF) idea proposed in literatures. The CCRC approach insert some error detection code in high level code, detect the existing of redundancy core in MPSoC, then complete the calculation of detection code in redundancy core. The author compares the CCRC approach with several main error detection methods on error detection capabilities, area, memory and performance overheads in an experiment platform. The result of comparative evaluation shows that the CCRC approach is effective for MPSoC, taking some advantages in versatility and lower cost.
Personalization of word-phrase-entity language models

We continue our investigations of Word-Phrase-Entity (WPE) Language Models that unify words, phrases and classes, such as named entities, into a single probabilistic framework for the purpose of language modeling. In the present study we show how WPE LMs can be adapted to work in a personalized scenario where class definitions change from user to user or even from utterance to utterance. Compared to traditional classbased LMs in various conditions, WPE LMs exhibited comparable or better modeling potential without requiring pre-tagged training material. We also significantly scaled the experimental setup by widening the target domain, amplifying the amount of training material and increasing the number of classes.
Using alice in CS1: a quantitative experiment

We present the results of a 2-semester study of using the 3-D graphical programming environment Alice to introduce programming fundamentals during the first two weeks of CS1. One cohort of students was taught basic programming constructs via traditional pseudocode, while a second group used Alice. A student survey was collected, along with performance metrics on a common quiz and first exam. Students using Alice scored lower than those taught with pseudocode on common performance metrics and responded less-favorably to Alice in a survey. Anecdotal evidence of using Alice with younger students was more positive.
When TEDDY meets GrizzLY: temporal dependency discovery for triggering road deicing operations

Temporal dependencies between multiple sensor data sources link two types of events if the occurrence of one is repeatedly followed by the appearance of the other in a certain time interval. TEDDY algorithm aims at discovering such dependencies, identifying the statically significant time intervals with a chi2 test. We present how these dependencies can be used within the GrizzLY project to tackle an environmental and technical issue: the deicing of the roads. This project aims to wisely organize the deicing operations of an urban area, based on several sensor network measures of local atmospheric phenomena. A spatial and temporal dependency-based model is built from these data to predict freezing alerts.
Enhancing Cultural Humility Through Critical Service-Learning in Teacher Preparation

Abstract To provide opportunities for preservice teachers to move beyond the limitations of their life experiences, the teacher preparation program at the University of Vermont has worked to advance service-learning experiences that push preservice teachers to examine their own identities and biases by providing them with opportunities to interact with others whose life experiences are different than their own. The goal of these experiences is to assist the preservice teachers in recognizing how their emerging practice, which is entrenched within their own positionality, impacts individuals that they work with as well as the broader community. This interpretive study examined outcomes of the experience through the lens of cultural humility. This study affirms the need to be explicit about practice, particularly as it relates to critical pedagogy to advance social justice. It also offers a glimpse into how teacher preparation programs may construct learning experiences to support the development of cultural humility.
Affective Learning in Residential and Pervasive Computing Environments

This article examines how emerging pervasive computing and affective computing technologies might enhance the adoption of ICT in eLearning which takes place in the home and wider city environment. In support of this vision we describe two cutting edge ICT environments which we are using as part of this research. The first is iSpace, a specialized pervasive computing test-bed taking the form of a two bed-roomed residential apartment situated at the University of Essex, the second a sophisticated eLearning platform based in Shanghai Jiao Tong University that caters for 17,000 learners. After describing these environments we then present our research that explores how emotion evolves during the learning process and how to leverage emotion feedback to provide adaptive eLearning Published in Information Systems Frontiers, Volume 10, Issue 4, pp 461-472, ISSN:1387-3326, Kluwer Academic Publishers Hingham, MA, USA, September 2008, © Shanghai Jiao Tong and Essex University 2008 2 system. The motivation driving this work is our desire to improve the performance of the educational experience by mediating the delivery of interactive eLearning content to the learner based on the learner’s emotional state (e.g. confusion, frustration etc). Finally we report on the results about the emotion recognition from physiological signals which achieved a best-case accuracy rate of 86.5% for four types of learning emotion. As far as we know, this is the first report on emotion detection by data collected from close-to-real-world learning sessions. We also reported some finding about emotion evolution during learning, which were still not enough to validate Kort’s learning spiral model.
Both Self-Report and Interview-Based Measures of Psychopathy Predict Attention Abnormalities in Criminal Offenders

Historically, psychopathy has been viewed as a clinical syndrome with a unitary etiology, assessed via clinical interview. However, factor analytic studies suggest that psychopathy may also be understood as a combination of two subfactors consisting of (a) interpersonal-affective and (b) lifestyle-antisocial traits. Furthermore, evidence supports the use of self-report measures to assess psychopathy and these subfactors. This investigation employed a Stroop-like task to determine the relationship of the two psychopathy factors, as assessed by both interview-based and self-report measures, to attention-related abnormalities in psychopathy. For both instruments, the factors interacted to predict performance (i.e., interference), though the unique main effects were nonsignificant. The results suggest that the anomalous selective attention of psychopathic offenders is specific to individuals with high scores on both factors. Moreover, these results have important implications for the two-factor model of psychopathy and provide preliminary support for the functional similarity of self-report and interview-based measures of psychopathy.
Considerations on the benchmarking of media forensics

In media forensics, most of the approaches are still far away from being mature enough for admission in court - the ultimate benchmark for any forensic method. The intended contribution of this paper is to facilitate the understanding between the researchers active in this field and the society perspective on media forensics. The intended benefit of this is that it allows these two to better understand each other: On one hand, showing researchers working on the development of forensic methods a precise picture of the compliance requirements installed by the society (here, requirements for potential court admissibil-ity); on the other hand, intending to help non-technicians to understand the challenges that researchers face. To achieve this contribution, a selected prominent example (the photo response non-uniformity (PRNU) based digital camera forensics) is discussed here briefly in the context of the established Daubert criteria as reference imposed as admissibility threshold for legal proceedings.
The Effects of Students' Learning Anxiety and Motivation on the Learning Achievement in the Activity Theory Based Gamified Learning Environment

Background:The advancement of mobile game-based learning has encouraged many related studies, which, through the use of mobile 3-dimensional virtual reality, has enabled students to learn more and faster.To enhance the clinical path of cardiac catheterization learning, this paper has developed a mobile 3D Cardiac Catheterization Game-Based Learning System for cardiac catheterization.Material and methods:We designed an activity theory as a 3D mobile medical game-based learning system and evaluated the learning effectiveness, based on ARCS (Attention, Relevance, Confidence and Satisfaction) theory. Totally 102 students with the relevant medical background, divided into three groups (n = 34). This study implemented a quasi-experimental design at a medical college in south Taiwan, in the experimental stage, this study collects the questionnaire and test scores for learning achievement, learning motivation, medical anxiety and demographic variables in order to analyze group differences.Results:The learning achievements of this study show that the experimental group achieved higher scores than both control groups. The statistical analysis of the learning motivation and learning achievement shows ARCS-R (Relevance) as the most important factor, followed by of ARCS-C (Confidence). Conclusions:The results show that the learning content was relevant to the learner’s level, and that it brought more confidence and increased the effectiveness of learning.
Lead Screening for HIV of C-C Chemokine Receptor Type 5 Receptor Inhibited by Traditional Chinese Medicine

The acquired immunodeficiency syndrome (AIDS), caused by the human immunodeficiency virus (HIV), has become a serious world-wide problem because of this disease's rapid propagation and incurability. Recent research has pointed out that the C-C chemokine receptor type 5 (CCR5) is an important target for HIV infection. The traditional Chinese medicine (TCM) database (http://tcm.cmu.edu.tw/) has been screened for molecular compounds that, by simulating molecular docking and molecular dynamics, may protect CCR5 against HIV. Saussureamine C, 5-hydroxy-L-tryptophan, and abrine are selected based on the docking score being higher than Maraviroc and other TCM compounds. The molecular dynamics are helpful in the analysis and detection of protein-ligand interactions. According to the docking poses, hydrophobic interactions, and hydrogen bond variations, this research surmises TRP86, TYR108, GLN194, TYR251, and GLU283 are the main regions of important amino acids in CCR5. In addition to the detection of TCM compound efficacy, we suggest saussureamine C is better than the others for maintaining protein composition during protein-ligand interaction, based on the structural variation.
Evaluation of head-free eye tracking as an input device for air traffic control

The purpose of this study was to investigate the possibility to integrate a free head motion eye-tracking system as input device in air traffic control (ATC) activity. Sixteen participants used an eye tracker to select targets displayed on a screen as quickly and accurately as possible. We assessed the impact of the presence of visual feedback about gaze position and the method of target selection on selection performance under different difficulty levels induced by variations in target size and target-to-target separation. We tend to consider that the combined use of gaze dwell-time selection and continuous eye–gaze feedback was the best condition as it suits naturally with gaze displacement over the ATC display and free the hands of the controller, despite a small cost in terms of selection speed. In addition, target size had a greater impact on accuracy and selection time than target distance. These findings provide guidelines on possible further implementation of eye tracking in ATC everyday activity. Practitioner Summary: We investigated the possibility to integrate a free head motion eye-tracking system as input device in air traffic control (ATC). We found that the combined use of gaze dwell-time selection and continuous eye–gaze feedback allowed the best performance and that target size had a greater impact on performance than target distance.
Toward Extractive Summarization of Multimodal Documents

Summarization research has focused on text, and relatively little attention has been given to the summarization of multimodal documents. If extractive summarization techniques are to be used on multimodal documents containing information graphics (bar charts, line graphs, etc.), then a strategy must be devised both for extracting the high-level content of the information graphics and for identifying where that content is relevant in the article’s text. This paper gives an overview of our prior work on constructing a summary of an information graphic and presents our new research on methods for selecting paragraphs in a multimodal document that are most relevant to a constituent information graphic. The results demonstrate that our methods are far superior to possible baseline methods and that our work advances the use of extractive techniques for summarizing multimodal documents.