Miracle-dz/UniFAR-FTUs huggingface dataset:
Research proposal Better living through computing — efficient in silico simulations of biological phenomena

Since 2000, the CPH STL research team at the Performance Engineering Laboratory has been a nexus of program-library development in the C++ programming language as well as practical and theoretical algorithmics research, evident by the many published papers, reports and high-standard implementations available online at the CPH STL website. Key areas of research have been runtime optimization, genericity in data structures and algorithms, and achieving optimality in implementation as well as proving theoretical bounds on optimality. The CPH STL has, however, also made strides in automated benchmarking and documentation, and is now mature for application to industrial-scale problems. One specific target for application is the E-Cell system—a platform that seeks to achieve precise whole-cell simulation. The growth in life-science datasets and knowledge complexity, exemplified by the human genome and more recently the human metabolome, underscore the need for continuous performance improvement in biological simulation software, and the E-Cell system is no exception. We have two goals in this project: to ship the industry-grade version of the CPH STL, and to use it in the E-Cell system as a runtime performance booster. We thus hope to use our expertise to aid in progress in drug discovery, metabolic pathway identification and in silico simulation of human physiology.
Optimal Static Pricing of Reverse-Link DS-CDMA Multiclass Traffic

Nowadays, third generation (3G) wireless systems are becoming very popular. Direct-sequence code-division multiple-access (DS-CDMA) is implemented in these systems but, due to a limited radio spectrum and the growing number of demanding applications, it seems likely that congestion would still remain an issue. Pricing appears as a simple way to tackle this problem. This paper studies the impact of a per-packet static pricing scheme on the use of the reverse-link in a cell, where demand (defined through the so-called utility functions) decreases when prices increase or quality of service decreases. Since DS-CDMA supports integrated services, we also deal with pricing of multiple classes. In a first step, we determine as a Nash equilibrium the number of customers that actually apply for service, depending on demand. In a second step, assuming perfect power control, we find the prices and received powers optimizing the service provider's revenue. We find that in the case where potential demand always exceeds capacity, the base station's best interest is to favor only one class, but that is not the case in a realistic situation when considering potential demand as a random variable over time
The multilocus sequence typing network: mlst.net

The unambiguous characterization of strains of a pathogen is crucial for addressing questions relating to its epidemiology, population and evolutionary biology. Multilocus sequence typing (MLST), which defines strains from the sequences at seven house-keeping loci, has become the method of choice for molecular typing of many bacterial and fungal pathogens (and non-pathogens), and MLST schemes and strain databases are available for a growing number of prokaryotic and eukaryotic organisms. Sequence data are ideal for strain characterization as they are unambiguous, meaning strains can readily be compared between laboratories via the Internet. Laboratories undertaking MLST can quickly progress from sequencing the seven gene fragments to characterizing their strains and relating them to those submitted by others and to the population as a whole. We provide the gateway to a number of MLST schemes, each of which contain a set of tools for the initial characterization of strains, and methods for relating query strains to other strains of the species, including clustering based on differences in allelic profiles, phylogenetic trees based on concatenated sequences, and a recently developed method (eBURST) for identifying clonal complexes within a species and displaying the overall structure of the population. This network of MLST websites is available at
All subtypes of the Pmp adhesin family are implicated in chlamydial virulence and show species-specific function

The bacterial pathogens Chlamydia trachomatis and C. pneumoniae are obligate intracellular parasites, cause a number of serious diseases, and can infect various cell types in humans. Chlamydial infections are probably initiated by binding of the bacterial outer membrane protein OmcB to host cell glycosaminoglycans (GAGs). Here, we show that all nine members of the polymorphic membrane protein (Pmp) family of C. trachomatis mediate adhesion to human epithelial and endothelial cells. Importantly, exposure of infectious particles to soluble recombinant Pmps blocks subsequent infection, thus implicating an important function of the entire protein family in the infection process. Analogous experiments with pairs of recombinant Pmps or a combination of Pmp and OmcB revealed that all Pmps probably act in an adhesion pathway that is distinct from the OmcB‐GAG pathway. Finally, we provide evidence that the Pmps of C. trachomatis and C. pneumoniae exhibit species and tissue specificity. These findings argue for the involvement of C. trachomatis Pmps in the initial phase of infection and suggest that they may interact with a receptor other than the epidermal growth factor receptor recently identified for their counterparts in C. pneumoniae.
A novel MPEG-4 short film production system based on mobile context photo

The explosive growth of the Internet and the rising popularity of mobile devices have created a varying environment where lots of mobile multimedia applications and services are emerging everyday. This paper proposes a novel MPEG-4 short film production system based on mobile context photo. This system records context information surrounding mobile user when taking photos, and uses the mobile context photos to produce short film by the object-oriented MPEG-4 coding technology. The implementation of a demonstration system including the mobile context camera application and multimedia production server is presented in this paper.
A Network of Conserved Damage Survival Pathways Revealed by a Genomic RNAi Screen

Damage initiates a pleiotropic cellular response aimed at cellular survival when appropriate. To identify genes required for damage survival, we used a cell-based RNAi screen against the Drosophila genome and the alkylating agent methyl methanesulphonate (MMS). Similar studies performed in other model organisms report that damage response may involve pleiotropic cellular processes other than the central DNA repair components, yet an intuitive systems level view of the cellular components required for damage survival, their interrelationship, and contextual importance has been lacking. Further, by comparing data from different model organisms, identification of conserved and presumably core survival components should be forthcoming. We identified 307 genes, representing 13 signaling, metabolic, or enzymatic pathways, affecting cellular survival of MMS–induced damage. As expected, the majority of these pathways are involved in DNA repair; however, several pathways with more diverse biological functions were also identified, including the TOR pathway, transcription, translation, proteasome, glutathione synthesis, ATP synthesis, and Notch signaling, and these were equally important in damage survival. Comparison with genomic screen data from Saccharomyces cerevisiae revealed no overlap enrichment of individual genes between the species, but a conservation of the pathways. To demonstrate the functional conservation of pathways, five were tested in Drosophila and mouse cells, with each pathway responding to alkylation damage in both species. Using the protein interactome, a significant level of connectivity was observed between Drosophila MMS survival proteins, suggesting a higher order relationship. This connectivity was dramatically improved by incorporating the components of the 13 identified pathways within the network. Grouping proteins into “pathway nodes” qualitatively improved the interactome organization, revealing a highly organized “MMS survival network. ” We conclude that identification of pathways can facilitate comparative biology analysis when direct gene/orthologue comparisons fail. A biologically intuitive, highly interconnected MMS survival network was revealed after we incorporated pathway data in our interactome analysis.
The Need for a Public Health Competency-Based Education for Integrative Health Care

Integrative health care (IH) is an approach to health that utilizes biomedical and social determinants of health to promote health and prevent disease, focusing on primary, secondary, and tertiary prevention, and utilizing not only the clinician–patient relationship but also how the family and community contribute to health promotion and disease. IH is a nascent area of practice within public health training. However, many people with a graduate degree in public health have a clinical profession that contributes to integrative primary health. To support the development of a competency-based education for IH, the National Center for Integrative Primary Healthcare convened an interprofessional leadership team to develop 10 “meta-competencies” in integrative primary health care. Following the development of the meta-competencies, individual members of the leadership team worked with colleagues within their profession to develop subcompetencies for specific professions for each meta-competency, including public health. The meta-competencies and public health subcompetencies were used to develop an online 33-hour introductory IH course: “Foundations in Integrative Health. ” The public health subcompetencies were used to guide the development of a case study for a 6-hour unit, “Interprofessional Practice in Community Settings and Systems at Large,” on how to conduct and utilize a community health assessment that focused on health equity issues related to diabetes, which can also be taken as a stand-alone course.
Pathogenesis of myelodysplastic syndromes: an overview of molecular and non-molecular aspects of the disease

Myelodysplastic syndromes (MDS) are a group of clonal disorders arising from hematopoietic stem cells generally characterized by inefficient hematopoiesis, dysplasia in one or more myeloid cell lineages, and variable degrees of cytopenias. Most MDS patients are diagnosed in their late 60s to early 70s. The estimated incidence of MDS in the United States and in Europe are 4.3 and 1.8 per 100,000 individuals per year, respectively with lower rates reported in some Asian countries and less well estimated in other parts of the world. Evolution to acute myeloid leukemia can occur in 10-15% of MDS patients. Three drugs are currently approved for the treatment of patients with MDS: immunomodulatory agents (lenalidomide), and hypomethylating therapy [HMT (decitabine and 5-azacytidine)]. All patients will eventually lose their response to therapy, and the survival outcome of MDS patients is poor (median survival of 4.5 months) especially for patients who fail (refractory/relapsed) HMT. The only potential curative treatment for MDS is hematopoietic cell transplantation. Genomic/chromosomal instability and various mechanisms contribute to the pathogenesis and prognosis of the disease. High throughput genetic technologies like single nucleotide polymorphism array analysis and next generation sequencing technologies have uncovered novel genetic alterations and increased our knowledge of MDS pathogenesis. We will review various genetic and non-genetic causes that are involved in the pathogenesis of MDS.
Does Corruption Relieve Foreign Investors of the Burden of Taxes and Capital Controls?

In a sample of fourteen source countries making bilateral investments in forty five countries, the author finds that taxes, capital controls, and corruption, all have large, statistically significant negative effects on foreign investment. Moreover, there is no robust support in the data for the"efficient grease"hypothesis - that corruption helps attract foreign investment by reducing firms'tax burden and the irritant of capital controls.
Evaluation of the software maintenance tasks based on fuzzy screening

Evaluation of software maintenance tasks can significantly contribute to the efficiency of maintenance management, which is recognized as the most costly part of the software life cycle. This paper presents an approach to evaluation of software maintenance tasks based on fuzzy screening. The construction of data set for the case study is based on the real data extracted from the maintenance repository available in a local very small software company. In the construction of data set participated researchers and experienced software experts from the selected company. Results of the analysis provide evidence that fuzzy screening can be used for evaluation of maintenance tasks based on selected attributes. Further work directions are outlined in the conclusion section.
Poster paper: HunPos – an open source trigram tagger

In the world of non-proprietary NLP software the standard, and perhaps the best, HMM-based POS tagger is TnT (Brants, 2000). We argue here that some of the criticism aimed at HMM performance on languages with rich morphology should more properly be directed at TnT’s peculiar license, free but not open source, since it is those details of the implementation which are hidden from the user that hold the key for improved POS tagging across a wider variety of languages. We present HunPos 1 , a free and open source (LGPL-licensed) alternative, which can be tuned by the user to fully utilize the potential of HMM architectures, offering performance comparable to more complex models, but preserving the ease and speed of the training and tagging process.
Opportunities for re-convergence of engineering and cognitive science accounts of spoken word recognition

As users are only too aware, contemporary large vocabulary speech recognition systems do not respond to speech in the same way as humans. The dictation systems that are in use today are very sensitive to disfluencies, restarts, background noise and change of speaker or voice quality. Furthermore the recognition mistakes they make seem to be very different to the ones that humans make even when listening in poor environments. There is no doubt that recognition systems will only become more comfortable to use when they act more like a human listener. This should mean that scientific knowledge about how humans process speech is relevant and important in the design of these systems. Unlike the situation in the early days of the field, it is now the case that scientific research into the human processing of language has diverged from research into systems. We now have separate and independent fields of ‘psycholinguistics’ and ‘spoken language engineering’. This article explores the relationship between the engineering and cognitive science communities within the relatively well-defined sub-field of spoken word recognition. That is we shall be mainly concerned with the processes by which word sequences are recovered from acoustic input. The article is in three parts: the roots of the divergence between engineering and cognitive science accounts of word recognition are explored in the first part. Differences in motivation, methodology and culture are all seen to play a part and are explored in a historical context. The second part of the article discusses the potential benefits of a re-convergence of the two scientific fields and argues that the time is ripe for progress now. Engineering systems are stable and successful enough to be worth interpreting in cognitive terms, while they are sophisticated enough to allow useful comparisons with humans to be undertaken. The final part of the article proposes some elements of a joint research programme which could act as a stimulus for the two communities to work together. Highlighted are the cognitive accounts of priming phenomena which relate to recent engineering work in adaptation, and cognitive accounts of morphological processing which relate to engineering problems of vocabulary selection and use. Other possibilities relate to phonetic reduction phenomena at the low end, and semantic grouping or phrasing at the high end of both human and machine recognition.
Exploiting web 2.0 forallknowledge-based information retrieval

This paper describes ongoing research into obtaining and using knowledge bases to assist information retrieval. These structures are prohibitively expensive to obtain manually, yet automatic approaches have been researched for decades with limited success. This research investigates a potential shortcut: a way to provide knowledge bases automatically, without expecting computers to replace expert human indexers. Instead we aim to replace the professionals with thousands or even millions of amateurs: with the growing community of contributors who form the core of Web 2.0. Specifically we focus on Wikipedia, which represents a rich tapestry of topics and semantics and a huge investment of human effort and judgment. We show how this can be directly exploited to provide manually-defined yet inexpensive knowledge-bases that are specifically tailored to expose the topics, terminology and semantics of individual document collections. We are also concerned with how best to make these structures available to users, and aim to produce a complete knowledge-based retrieval system-both the knowledge base and the tools to apply it-that can be evaluated by how well it assists real users in performing realistic and practical information retrieval tasks. To this end we have developed Koru, a new search engine that offers concrete evidence of the effectiveness of our Web 2.0 based techniques for assisting information retrieval.
Threshold Signcryption Based on Elliptic Curve

The signcryption scheme presented by Zheng uses hash function and symmetrical cipher to encrypt message. The first protocol for threshold generation of Zheng’s signcryption scheme couldn’t support multiple public verifiers. In this paper, we proposed a new signcryption scheme based on EC-ELGamal type encryption. Message to be transmitted is embedded in Elliptic Curve as a point P(m) and encrypted by point addition which is efficient and secure as well as exiting schemes. By using verifiable secret sharing and secure multi-party computation, we propose a protocol for threshold generation of the signcryption. Because point addition couldn’t map coordinate addition directly, we introduce a linear sum of coordinates to reconstruct the private coordinate. The protocol supports k out of n senders and the public verifier. The specific receiver can verify the validity of the signature before decrypting the cipher. The proposed protocol is a perfect threshold scheme. Thus, it can defend the attack launched by k-1 players. Complexity of them is less than the same schemes based on DLP (Discrete Logarithm Problem).
Comparison of FcRγ-Deficient and CD57+ Natural Killer Cells Between Cord Blood and Adult Blood in the Cytomegalovirus-Endemic Korean Population

Background FcRγ-deficient natural killer (NK) cells (g-NK cells) have been associated with cytomegalovirus (CMV) infection. However, the frequency of g-NK cells in a CMV-endemic area (i.e., Korea) has not yet been studied. We examined the frequency of g-NK cells and expression of CD57 on NK cells in cord blood (CB) and adult blood (AB). Methods Of the 24 AB samples collected, 95.8% (23/24) were CMV IgG+/IgM-, while 100% of the 13 healthy CB samples were CMV IgG+/IgM-. We performed whole-blood flow cytometry assays to analyze intracellular FcRγ and CD3ζ expression of CD3-/CD56dim NK cells from 13 CB and 24 AB samples, and surface CD57 expression on CD3-/CD56dim/CD16+ NK cells from 13 CB and 19 AB samples. Results All CMV seropositive AB samples contained g-NK cells (23/23), and the median proportion of g-NK cells in the CD3-/CD56dim NK cell pool was 35.0% (range: 11-77%). CD57+ NK cells in the CD3-/CD56dim/CD16+ NK cell population were detected in all 19 AB samples tested, but not in any CB samples. Conclusions Our data suggest that g-NK cells and CD57+ NK cells are present at a very high frequency in CMV-seropositive AB, but rare in CMV-naïve CB.
Efficient Optimization of Common Base Domains for Cross Parameterization

Given a set of corresponding user-specified anchor points on a pair of models having similar features and topologies, the cross parameterization technique can establish a bijective mapping constrained by the anchor points. In this paper, we present an efficient algorithm to optimize the complexes and the shape of common base domains in cross parameterization for reducing the distortion of the bijective mapping. The optimization is also constrained by the anchor points. We investigate a new signature, Length-Preserved Base Domain (LPBD), for measuring the level of stretch between surface patches in cross parameterization. This new signature well balances the accuracy of measurement and the computational speed. Based on LPBD, a set of metrics are studied and compared. The best ones are employed in our domain optimization algorithm that consists of two major operators, boundary swapping and patch merging. Experimental results show that our optimization algorithm can reduce the distortion in cross parameterization efficiently.
Adaptable swarm intelligence framework

Modern software systems must be continuously adapted to current performance and usability requirements. Indicators like overhead, computational complexity, parameter tuning, or ease of design and implementation are getting increasingly harder to accomplish due to constant increase in system dimensions like code size, API (Application Programming Interface), deployment size, component communication, network lag etc. Furthermore, many entities rely on classic, highly deterministic algorithms that are little or not capable of changing strategies on the fly. Lately, bio-inspired algorithms have successfully tackled this problem with significant, positive results. We propose a framework that may prove useful in obtaining better performance by automatically selecting and combining the best swarm intelligence algorithms with the best parameter selection.
DECENTRALIZED ADAPTIVE ROBUST TRACKING AND MODEL FOLLOWING FOR UNCERTAIN LARGE SCALE SYSTEMS

Abstract The problem of decentralized robust tracking and model following is considered for a class of uncertain large scale systems. In this paper, it is assumed that the upper bounds of the uncertainties and external disturbances are unknown. A modified adaptation law with γ–modification is introduced to estimate such unknown bounds, and on the basis of the updated values of these unknown bounds, a class of decentralized local state feedback controllers is constructed for robust tracking of dynamical signals. It is shown that the proposed decentralized adaptive robust tracking controllers can guarantee that the tracking errors between each subsystem and the corresponding local reference model decrease uniformly asymptotically to zero.