Miracle-dz/UniFAR-FTUs huggingface dataset:
Structure Based Refinement of a Humanized Monoclonal Antibody That Targets Tumor Antigen Disialoganglioside GD2

Disialoganglioside GD2 is an important target on several pediatric and adult cancer types including neuroblastoma, retinoblastoma, melanoma, small-cell lung cancer, brain tumors, sarcomas, and cancer stem cells. We have utilized structural and computational methods to refine the framework of humanized monoclonal antibody 3F8, the highest affinity anti-GD2 antibody in clinical development. Two constructs (V3 and V5) were designed to enhance stability and minimize potential immunogenicity. Construct V3 contained 12 point mutations and had higher thermal stability and comparable affinity and in vitro tumor cells killing as the parental hu3F8. Construct V5 had nine point mutations to minimize potential immunogenicity, but resulted in weaker thermal stability, weaker antigen binding, and reduced tumor killing potency. When construct V3 was combined with the single point mutation HC:G54I, the resulting V3-Ile construct had enhanced stability, antigen binding, and a nearly sixfold increase in tumor cell killing. The resulting product is a lead candidate for clinical development for the treatment of GD2-positive tumors.
Modelling Large Datasets Using Algebraic Datatypes: A Case Study of the CONFMAN Database

Being able to provide clear specifications of large datasets comprising hundreds of variables, each of which can take on many different values, while still being able to efficiently and accurately learn functional relations from such data would certainly make data mining techniques even more viable in the real world. In this report we describe a new modelling approach, which essentially generalizes discrete decision tree learning to induction of non-recursive functions over algebraic datatypes. Taking the CONFMAN mediation database as guiding example, we demonstrate how this approach allows us to give more natural data specifications that can take into account semantic aspects which are hard or even impossible to model in common attribute-value representations. We will also explain how this can have a positive impact on accuracy and efficiency.
Simulation and visualization tools for teaching parallel merge sort

This paper describes tools [4] which simulate and visualize the CREW PRAM optimal parallel merge sort algorithm by Cole [1]. These tools can be used to run simulations of the algorithm for diflerent data and sampling strategies, to gather statistics during the simulations, to animate the flow of data and the processor allocations during the execution of the algom“thm, and most importantly to aid in understanding the algorithm. These tools can be used in conjunction with a discussion of the algorithm in a course on algorithms or parallel algorithms at the senior undergraduate or graduate level.
The effect of aleks on students' mathematics achievement in an online learning environment and the cognitive complexity of the initial and final assessments

For many courses, mathematics included, there is an associated interactive e-learning system that provides assessment and tutoring. Some of these systems are classified as Intelligent Tutoring Systems. MyMathLab, Mathzone, and Assessment of LEarning in Knowledge Space (ALEKS) are just a few of the interactive e-learning systems in mathematics. In ALEKS, assessment and tutoring are based on the Knowledge Space Theory. Previous studies in a traditional learning environment have shown ALEKS users to perform equally or better in mathematics achievement than the group who did not use ALEKS. The purpose of this research was to investigate the effect of ALEKS on students' achievement in mathematics in an online learning environment and to determine the cognitive complexity of mathematical tasks enacted by ALEKS's initial (pretest) and final (posttest) assessments. The targeted population for this study was undergraduate students in College Mathematics I, in an online course at a private university in the southwestern United States. The study used a quasi-experimental One-Group nonrandomized pretest and posttest design. Five methods of analysis and one model were used in analyzing data: t-test, correlation analysis, simple and multiple regression analysis, Cronbach's Alpha reliability test and Webb's depth of knowledge model. A t-test showed a difference between the pretest and posttest reports, meaning ALEKS had a significant effect on students' mathematics achievement. The correlation analysis showed a significant positive linear relationship between the concept mastery reports and the formative and summative assessments reports meaning there is a direct relationship between the ALEKS concept mastery and the assessments. The regression equation showed a better model for predicting mathematics achievement with ALEKS when the time spent learning in ALEKS and the concept mastery scores are used as part of the model. According to Webb‘s depth of knowledge model, the cognitive complexity of the pretest and posttest question items used by ALEKS were as follows: 50.5% required application of skills and concepts, 37.1% required recall of information, and 12.4% required strategic thinking: None of the questions items required extended thinking or complex reasoning, implying ALEKS is appropriate for skills and concepts building at this level of mathematics.
BEYOND CONVERGENCE: SPACE, SCALE, AND REGIONAL INEQUALITY IN CHINA

Since the late 1980s there has been a renewed interest in regional inequality, fuelled by the concern over the effects of globalisation and liberalisation, and facilitated by theoretical and methodological developments in geography and economics. In essence, the new convergence theory, like the old convergence theory, is another theory devoid of space and time. Research on China has unfolded a complex landscape of regional development, the existence of distinct models of regional development, and the significant role of institutions. This paper examines regional inequality in China, especially Zhejiang Province, and attempts to uncover the trend and driving forces of regional inequality. It adopts a top-down and bottom-up strategy and employs recent developments in exploratory spatial data analysis (ESDA) and geographically weighted regression (GWR). We have found that regional inequality is sensitive to geographic scales and spatial organisation, and that conventional approaches mask spatial agglomeration and the significance of regions in shaping trends of regional inequality. Overall, regional inequality in Zhejiang rose during the reform period and a division between coastal and interior Zhejiang formed, additionally sustained by weak linkages between the two regions and the significance of location and nonstate enterprises in development. This paper further reveals the emergence of Wenzhou, and discusses its effect on regional inequality. Copyright (c) 2009 by the Royal Dutch Geographical Society KNAG.
SARNA-Predict-pk: Predicting RNA secondary structures including pseudoknots

Pseudoknots are RNA tertiary structures which perform essential biological functions. This paper presents SARNA-Predict-pk, an algorithm for pseudoknotted RNA secondary structure prediction based on Simulated Annealing (SA). The research presented here extends previous work of SARNA-Predict and incorporates a new thermodynamic model into the algorithm, effectively enabling it to predict pseudo-knotted RNA structures. An evaluation of the performance of SARNA-Predict-pk in terms of prediction accuracy is made via comparison with several state-of-the-art prediction algorithms. We measured the sensitivity and specificity using five prediction algorithms. Three of these are dynamic programming algorithms: Pseudoknot (pknotsRE), NUPACK, and pknotsRG-mfe. The other two are heuristic algorithms: SARNA-Predict-pk and HotKnots algorithms. An evaluation for the performance of SARNA-Predict-pk in terms of prediction accuracy was verified with native structures. Experiments on ten individual known structures from six RNA classes (tRNA, viral RNA, anti-genomic HDV, telomerase RNA, tmRNA, and RNaseP) were performed. The results presented in this paper demonstrate that SARNA-Predict-pk can out-perform other state-of-the-art algorithms in terms of prediction accuracy.
Assessment of Life Satisfaction in Apostolic Women Religious: The Development of a New Instrument

ASSESSMENT OF LIFE SATISFACTION IN APOSTOLIC WOMEN RELIGIOUS: THE DEVELOPMENT OF A NEW INSTRUMENT Maria Clara Kreis, M.A. Marquette University, 2010 The trend in today‘s U.S. society is one of decreased membership within traditional civic/faith organizations and in particular within women‘s religious organizations. Women religious are known particularly for their historic contribution to the U.S. social capital (Ebaugh et al., 1996; Nygren & Ukeritis, 1993; Weakland, 1994). Thus, there is a need to study the motivational factors and life satisfaction levels across different generations of apostolic women religious within the Roman Catholic Church. The purpose of the current study was to (a) develop an instrument specifically designed to assess the life satisfaction levels of the various generations of women religious, (b) establish preliminary psychometrics for this particular instrument, and (c) look for additional information related to motivations within and across generations of women religious that influence Sisters‘ satisfaction with religious life. This study describes the stages of item development and the field testing of the LSSAWR (50 items). The quantitative data from a representative nation-wide sample of apostolic women religious (N = 1116) were analyzed and psychometric properties revealed the elimination of four items and the loading of 46 items on one factor of the LSSAWR. Estimate of internal consistency was examined for the LSSAWR and its one factor and indicated the alpha coefficient at 0.95. The construct validity of the LSSAWR was established with two measures; one designed to assess levels of general life satisfaction, Satisfaction With Life Scale (0.47), and the other to assess levels of optimism, The Life Orientation Test (0.21). Applying the generation theory of Strauss and Howe (1991) to the current study revealed generational differences on the LSSAWR based on participants‘ responses. Finally, the findings of the qualitative research reasserted the content that originally emerged in the exploratory study. Overall, the results of this study suggest that the LSSAWR has the potential to be used as a screening tool useful to identify levels of satisfaction with religious life among apostolic women religious who have committed themselves to this way of life.
Brain structure visualization using spectral fiber clustering

The visualization of human brain structure is an important new challenge in the area of computer graphics. We present a novel algorithm that allows for visualizing white matter fiber tracts in realtime. Related structure is grouped by our spectral clustering method very efficiently and curvature and spatial depth of the fibers are accentuated by new GPU-based illustrative rendering techniques. Our fiber clustering results are much more accurate and comprehensible than that obtained by previous feature space methods.
An Artificial Landmark Design Based on Mobile Robot Localization and Navigation

Autonomous mobile robots are a very dynamic part of the robotics domain, this subject which based on artificial landmarks of mobile robot localization and navigation is one of the hot topics. How to identify signs fast and accurately is the key problem to the mobile robot localization and navigation in complex and unstructured environments for mobile robots. In this paper, a new artificial landmark design is proposed based on image segmentation technology and projective method with directional feature. Finally, lots experiments are carried out, the statistical theory and experiment results show that this new landmark is a good solution to the mobile robot's identification of signs, and with the characters is easy detection, a good real-time and ant interference ability.
ADAPTIVE DYNAMIC ROUTING IN MOBILE WIRELESS AD HOC NETWORKS UTILIZING ON-LINE LINK LIFE ESTIMATES

The current duration of a link in a mobile wireless ad hoc network (MANET) can be used for link stability assessment through on-line remaining link life estimation. These estimates implicitly include the effects of true propagation mechanisms, mobility space geometry, power control mechanisms and other phenomena that are ignored or simplistically modeled in other methods based on location or signal strength measures. In this paper we use such estimates for multipath/backup adaptive dynamic routing, and compare its performance with a corresponding multipath/backup version of DSR. ⋅
Measurement-Based Evaluation of TCP Throughput

SUMMARY Since the TCP is the transport protocol for most Internet applications, evaluation of TCP throughput is important. In this paper, we establish a framework of evaluating TCP throughput by simple measurement. TCP throughput is generally measured by sending TCP traffi ca nd monitoring its arrival or using data from captured packets, neither of which suits our proposal because of heavy loads and lack of scalability. While there has been much research into the analytical modeling of TCP behavior, this has not been concerned with the relationship between modeling and measurement. We thus propose a lightweight method for the evaluation of TCP throughput by associating measurement with TCP modeling. Our proposal is free from the defects of conventional methods, since measurement is performed to obtain the input parameters required to calculate TCP throughput. Numerical examples show the proposed framework’s effectiveness.
Skills , capabilities and change : are we keeping up with progress ?

Advances in technology are changing rapidly the discipline areas of information technology and eBusiness. Keeping the curriculum up-to-date and relevant has become a challenge. A prime educators’ task is the development of skills and capabilities meeting diverse employers’ needs. The paper presents the results of a survey to study the relevance of the professional academic content. Three research hypotheses related to the specific learning outcomes of two major business specialisations were formulated and validated. The research models used in the study are derived from a general framework which can be applied to other disciplines. The results show an increased emphasis on technical skills and their integration in the business process within the workplace.
A Model Driven Approach for Generating Code from Security Requirements

Nowadays, Information Systems are present in numerous areas and they usually contain data with special security requirements. However, these requirements do not often receive the attention that they deserve and, on many occasions, they are not considered or are only considered when the system development has nished. On the other hand, the use of model driven approaches has recently demonstrated to o er numerous bene ts. This paper tries to align the use of a model driven development paradigm with the consideration of security requirements from early stages of software development (such as requirements elicitation). With this aim, a security requirements metamodel that formalizes the de nition of this kind of requirements is proposed. Based on this metamodel, a Domain Speci c Language (DSL) has been built which allows both the construction of requirements models with security features and the automatic generation of other software artefacts from them. An application example that illustrates the approach is also shown.
Modeling and Analysis of Clandestine Networks

Abstract : Since Sept. 11, 2001, there has been great interest in the military and intelligence communities in using Social Network Analysis (SNA) to support the disruption and destruction of global terrorist networks. SNA results, however, tend to be descriptive and are limited due to the lack of advantageous properties of the relationship measures applied to the arcs in a social network. Further, SNA techniques generally focus on a single network context while real relationships are based in multiple contexts. This thesis develops a new proxy measure of pair-wise potential influence between members of a network, a Holistic Interpersonal Influence Measure (HIIM). The HIIM considers the topology of the multiple formal and informal networks to which group members belong as well as non-network characteristics such as age and education level that may indicate potential influence. The HIIM, once constructed results in a network of pair-wise potential influence between group members. Further, the numeric properties of the HIIM are appropriate for use in Operations Research Network Flow models, which will enable analysts to provide prescriptive analysis focused on specific actions and their outcomes. In addition to an overall measure of influence, the HIIM methodology provides important intermediate results such as the development of operational group profiles. The methodology is applied to open source data on both Al Qaeda and the Jemaah Islamiah (JI) terrorist networks. Key leaders are identified, and leadership profiles are developed. Further, a parametric analysis is performed to compare influence based on individual characteristics, network topology characteristics, and mixtures of network and non-network characteristics.
On the security of blind signature and partially blind signature

Blind signature allows a user to obtain a signature from an authority on any document, in such a way that the authority learns nothing about the message that is being signed. The blindness is an important property which distinguishes the blind signature from other signature schemes. Partially blind signature is an extension of blind signature that allows a signer to sign a partially blinded message that include pre-agreed information in the resulting signatures. Recently, Liao et al. proposed a pairing-based provable blind signature scheme without random oracles, and Hu et al. proposed an efficient ID-based partially blind signature scheme with security proof. But in this paper, we show that the two schemes do not satisfy the blindness and partially blindness, respectively. Liao et al.'s scheme is linkability and in Hu et al.'s scheme, a malicious user can replace pre-agreed common information with a special information
A model-based collaborative filtering method for bounded support data

Collaborative filtering (CF) is an important technique used in some recommendation systems. The task of CF is to estimate the persons' preferences (e.g., ratings) or to predict the preferences for the future, based on some already known persons' preferences. In general, the model-based CF performs better than the memory-based CF, especially for highly sparse data. In this paper, we present a new model-based CF method for bounded support data, which takes into account the facts that the ratings are usually in a limited interval. A nonnegative matrix factorization (NMF) model is applied to investigate and learn the patterns hidden in the observed data matrix. Each rating value is assumed to be beta distributed and we assign the gamma prior to the parameters in a beta distribution for the purpose of Bayesian estimation. With variation inference framework and some lower bound approximations, an analytically tractable solution can be obtained for the proposed NMF model. By comparing with several existing low-rank matrix approximation methods, the good performance of the proposed method is demonstrated.
Leadership style as a component of diversity management experience

The growing importance of managing workplace diversity necessitates investigating leadership style as a component of diversity management experience. This study aimed to determine the kind of leadership style required to establish a positive experience of diversity management in organisations. The proposition is that an engaging leadership style results in a more positive experience of diversity management. Four hundred and forty (440) leadership styles were measured in 11 selected workplaces. Their influence on diversity management experience along race, gender and generational lines among two thousand six hundred and sixty-nine (2 669) respondents in 11 workplaces were established. The symbolic interactionist study used the interrelated interactive leadership theories of Mintzberg (2004), McClelland (1975), McClelland and Burnham (1976), Burnham (2003) and the diversity and inclusion management indicators of Roberson (2004). This study used the Hall and Hawker (1988) inventory to determine leadership styles and a diversity questionnaire to measure diversity management experience. These were correlated using Spearman rank order correlations. Management styles in the 11 respondent workplaces were predominantly affiliative or tended towards heroic. The engaging leadership style of Mintzberg (2004) correlated positively with diversity management experience. Diversity management experience differed significantly between race and gender groups. No significant generational differences were established. Male respondents correlated positively with engaging leadership styles regardless of race, whereas female respondents correlated positively with heroic leadership styles. Younger generation respondents correlated negatively with fight/flight leadership styles. This study concluded with a symbolic interactive diversity competency model developed from Mintzberg (2004), with reference to Chang and Thorenou (2004) and Human (2005). Leadership style Diversity management experience V
Effects of Menthol Supplementation in Feedlot Cattle Diets on the Fecal Prevalence of Antimicrobial-Resistant Escherichia coli

The pool of antimicrobial resistance determinants in the environment and in the gut flora of cattle is a serious public health concern. In addition to being a source of human exposure, these bacteria can transfer antibiotic resistance determinants to pathogenic bacteria and endanger the future of antimicrobial therapy. The occurrence of antimicrobial resistance genes on mobile genetic elements, such as plasmids, facilitates spread of resistance. Recent work has shown in vitro anti-plasmid activity of menthol, a plant-based compound with the potential to be used as a feed additive to beneficially alter ruminal fermentation. The present study aimed to determine if menthol supplementation in diets of feedlot cattle decreases the prevalence of multidrug-resistant bacteria in feces. Menthol was included in diets of steers at 0.3% of diet dry matter. Fecal samples were collected weekly for 4 weeks and analyzed for total coliforms counts, antimicrobial susceptibilities, and the prevalence of tet genes in E. coli isolates. Results revealed no effect of menthol supplementation on total coliforms counts or prevalence of E. coli resistant to amoxicillin, ampicillin, azithromycin, cefoxitin, ceftiofur, ceftriaxone, chloramphenicol, ciprofloxacin, gentamicin, kanamycin, nalidixic acid, streptomycin, sulfisoxazole, and sulfamethoxazole; however, 30 days of menthol addition to steer diets increased the prevalence of tetracycline-resistant E. coli (P < 0.02). Although the mechanism by which menthol exerts its effects remains unclear, results of our study suggest that menthol may have an impact on antimicrobial resistance in gut bacteria.