Miracle-dz/UniFAR-FTUs huggingface dataset:
ii Reconstruction of biological networks for integrative analysis Reconstruction and Analysis of the Metabolic , Protein Secretion and Regulatory Network in Yeast

Biological systems can be very complex and consist of several thousand components that interact with each other in the cell. One of the goals of systems biology is to study biological systems from a systemic viewpoint in order to get an increased understanding of the behavior of the cell. Biological network reconstructions are important tools in systems biology in order to model the behavior of different biological systems. The biological networks can also be used as a scaffold for integrative analysis where highthroughput data from different conditions or different strains are integrated into the biological network to reduce the dimension of the data and to group the response between conditions or strains into biological pathways or key metabolites etc. The biological interpretation and discovery using integrative analysis can be facilitated by constructing more comprehensive and diverse biological networks. In this thesis I expanded current biological network reconstructions for the yeast Saccharomyces cereveisae in three steps and used them as a scaffold for biological interpretation and discovery. First I constructed an up-to-date yeast genome-scale metabolic model. The model is a comprehensive description of yeast metabolism and contains more genes, reactions and metabolites than previous models. The model performs well in simulating the metabolism under different conditions. Second, I studied the transcriptional regulatory network of yeast in terms of topology and structure of the network and compared it to transcriptional regulation in E. coli, human and mouse. I also used high-throughput data from many different conditions to study the conditiondependent response of the yeast transcriptional regulatory network. Third, I was involved in reconstruction of models of the protein secretion machinery in S. cerevisiae and for the high protein producer Aspergillus oryzae, describing protein folding, post-translational modifications and protein transport etc. High-throughput data from several different strains producing α-amylase were integrated into the models in order to get an insight in the mechanisms and bottlenecks of protein secretion in these organisms. The biological networks presented here were also used for data integration and the results and interpretation of the cellular behavior under different conditions can give us a deeper understanding and insight in for example condition-specific transcriptional regulation and protein production.
Protein synthesis by rice coleoptiles during prolonged anoxia: implications for glycolysis, growth and energy utilization.

BACKGROUND AND AIMS Anoxia-tolerant plant tissues synthesize a number of proteins during anoxia, in addition to the 'classical anaerobic proteins' involved in glycolysis and fermentation. The present study used a model system of rice coleoptile tips to elucidate patterns of protein synthesis in this anoxia-tolerant plant tissue. METHODS Coleoptile tips 7-11 mm long were excised from intact seedlings exposed to anoxia, or excised from hypoxically pre-treated seedlings and then exposed to anoxia for 72 h. Total proteins or 35S-labelled proteins were extracted, separated using two-dimensional isoelectric focusing/SDS-polyacrylamide gel electrophoresis and analysed using mass spectrometry. KEY RESULTS The coleoptile tips excised after intact seedlings had been exposed to anoxia for 72 h had a similar proteome to tips that were first excised and then exposed to anoxia. After 72 h anoxia, Bowman-Birk trypsin inhibitors and a glycine-rich RNA-binding protein decreased in abundance, whereas a nucleoside diphosphate kinase and several proteins with unknown functions were strongly enhanced. Using [35S]methionine as label, proteins synthesized at high levels in anoxia, and also in aeration, included a nucleoside diphosphate kinase, a glycine-rich RNA-binding protein, a putative elicitor-inducible protein and a putative actin-depolymerizing factor. Proteins synthesized predominately in anoxia included a pyruvate orthophosphate dikinase (PPDK), alcohol dehydrogenase 1 and 2, fructose 1,6-bisphosphate aldolase and a protein of unknown function. CONCLUSION The induction of PPDK in anoxic rice coleoptiles might, in combination with pyruvate kinase (PK), enable operation of a 'substrate cycle' producing PPi from ATP. Production of PPi would (a) direct energy to crucial transport processes across the tonoplast (i.e. the H+-PPiase); (b) be required for sucrose hydrolysis via sucrose synthase; and (c) enable acceleration of glycolysis, via pyrophosphate:fructose 6-phosphate 1-phosphotransferase (PFP) acting in parallel with phosphofructokinase (PFK), thus enhancing ATP production in anoxic rice coleoptiles; ATP production would need to be increased if there was a substantial requirement for PPi.
Online Scheduling Sequential Objects with Periodicity for Dynamic Information Dissemination

The scalability of data broadcasting has been manifested by prior studies on the base of the traditional data management systems where data objects, mapped to a pair of state and value in the database, are independent, persistent, and static against simple queries. However, many modern information applications spread dynamic data objects and process complex queries for retrieving multiple data objects. Particularly, the information servers dynamically generate data objects that are dependent and can be associated into a complete response against complex queries. Accordingly, the study in this paper considers the problem of scheduling dynamic broadcast data objects in a clients-providers-servers system from the standpoint of data association, dependency, and dynamics. Since the data broadcast problem is NP-hard, we derive the lower and the upper bounds of the mean service access time. In light of the theoretical analyses, we further devise a deterministic algorithm with several gain measure functions for the approximation of schedule optimization. The experimental results show that the proposed algorithm is able to generate a dynamic broadcast schedule and also minimize the mean service access time to the extent of being very close to the theoretical optimum.
Fingerprint based license checking for auto-mobiles

Driving license system is a very difficult task for the government to monitor. In this project, all the citizens' images will scan and recorded. Whenever a citizen crosses the traffic rules, the police can scan his image and can collect penalty / fine from the defaulter. Using this method, the police can track the history of the driver. This biometric based driving license monitoring system is very easy and convenient to monitor. According ancient Greek scripts BIOMETRICS means study of life. Biometrics studies commonly include fingerprint, face, iris, voice, signature, and hand geometry recognition and verification. Many other modalities are in various stages of development and assessment. Among these available biometric traits Finger Print proves to be one of the best traits providing good mismatch ratio and also reliable. Registering the attendances of students has become a hectic work as sometimes their attendance may be registered or missed. To overcome this problem i.e. to get the attendances registered perfectly we are taking the help of two different technologies viz. EMBEDDED SYSTEMS and BIOMETRICS.
Obesity in Pediatric ALL Survivors: A Meta-Analysis

BACKGROUND AND OBJECTIVE: Previous studies of survivors of pediatric acute lymphoblastic leukemia (ALL) have drawn heterogeneous conclusions regarding the prevalence of obesity and risk factors for developing obesity in pediatric ALL survivors. We sought to determine the prevalence of obesity in pediatric ALL survivors and examine risk factors for obesity through a systematic review and meta-analysis. METHODS: A MEDLINE search was performed from its inception through 2013. Studies met the inclusion criteria if they (1) included at least 10 survivors of pediatric ALL; (2) assessed the prevalence or indicators of obesity; and (3) compared obesity among ALL survivors to a reference population or external control group. Extracted data included patient and treatment characteristics, study design, population used for comparison, and prevalence of obesity. RESULTS: Forty-seven studies met the inclusion criteria. Despite significant heterogeneity among the studies (I2 = 96%), the mean BMI z score in 1742 pediatric ALL survivors was 0.83 (95% confidence interval: 0.60–1.06), which corresponds to the 80th BMI percentile, indicating a significantly higher BMI in pediatric ALL survivors than the reference population. Subgroup analyses found a high prevalence of obesity in ALL survivors regardless of survivors’ receipt of cranial irradiation, gender, or age at diagnosis. CONCLUSIONS: Obesity is prevalent in pediatric ALL survivors and is independent of patient- and treatment-related characteristics. Clinicians need to screen for obesity and its associated health conditions early in survivorship.
Valuing Brand Collaboration: Evidence From a Natural Experiment

We study complementarities between brands in the context of collaborations across museums. Over the course of our sample, one major museum with a highly recognized brand closed temporarily and sequentially collaborated with two established local museums. With individual panel data on museum memberships around these events, we measure how collaborations affect demand using an empirical framework of complementarities that are newly applied to the branding context. We observe two counter-acting demand patterns. First, customers with no history of buying membership from either museum enter the market, suggesting brand complementarities. Second, a sub-group of customers who previously purchased from either or both of the museums display decreased demand, consistent with brand dilution. Any structural approach that models the demand for collaboration with existing preferences for separate brands fails to create accurate demand predictions. The magnitude of the offsetting forces varies between collaboration events, which makes demand prediction even more challenging. These results call for a theory of brand being beyond a fixed utility primitive and have implications for counterfactuals that involve combining or altering of brands.
Global localization from a single feature correspondence

This paper presents a new approach to global localization for mobile robots from a single feature correspondence only. The method is based on a piece-wise planar environment map and uses planar natural landmarks as commonly encountered in man made environments. The method is especially useful in case of large occlusions. The standard Lu and Hager pose estimation algorithm [6] is extended to improve accuracy and robustness. Localization experiments are performed in a room-size real world scenario.
Transparent Object Reconstruction via Coded Transport of Intensity

Capturing and understanding visual signals is one of the core interests of computer vision. Much progress has been made w.r. t. many aspects of imaging, but the reconstruction of refractive phenomena, such as turbulence, gas and heat flows, liquids, or transparent solids, has remained a challenging problem. In this paper, we derive an intuitive formulation of light transport in refractive media using light fields and the transport of intensity equation. We show how coded illumination in combination with pairs of recorded images allow for robust computational reconstruction of dynamic two and three-dimensional refractive phenomena.
A Computational Investigation of Cardiac Caveolae as a Source of Persistent Sodium Current

Recent studies of cholesterol-rich membrane microdomains, called caveolae, reveal that caveolae are reservoirs of “recruitable” sodium ion channels. Caveolar channels constitute a substantial and previously unrecognized source of sodium current in cardiac cells. In this paper we model for the first time caveolar sodium currents and their contributions to cardiac action potential morphology. We show that the β-agonist-induced opening of caveolae may have substantial impacts on peak overshoot, maximum upstroke velocity, and ultimately conduction velocity. Additionally, we show that prolonged action potentials and the formation of potentially arrhythmogenic afterdepolarizations, can arise if caveolae open intermittently throughout the action potential. Our simulations suggest that caveolar sodium current may constitute a route, which is independent of channelopathies, to delayed repolarization and the arrhythmias associated with such delays.
Towards Practical Privacy Policy Enforcement

Organizations that use private information typically must provide assurances to regulators that their practices ensure that regulations are met. However, to the extent that they rely on electronic information systems for the management of private information, they really have no basis for providing those assurances. This paper proposes a framework for the design and implementation of information systems that provably enforce privacy policies. The privacy policies we aim to enforce are expressed in first-order temporal logic (FOTL). They capture not only safety, but also liveness requirements, which are essential in privacy policy. For a variety of reasons, prior work in runtime monitoring is of limited use in privacy policy enforcement. Among these reasons are the need to support liveness requirements, a desire to ensure through static verification that runtime policy violations do not occur, and above all, a recognition that users of electronic information systems require meaningful explanations when actions they attempt to initiate are denied. The latter is particularly relevant in the context of privacy policy because the (human) subject of information often needs to consent to having their personal information shared. So when a denial occurs, it may be that the user needs to seek permission from the subject to share his/her information. For all these reasons, our approach requires us to draw on and solve problems in diverse areas of computer science. We inventory open problems that must be solved, several of which we solve here.
Type IX collagen gene mutations can result in multiple epiphyseal dysplasia that is associated with osteochondritis dissecans and a mild myopathy

Multiple epiphyseal dysplasia (MED) is a clinically variable and genetically heterogeneous disease that is characterized by mild short stature and early onset osteoarthritis. Autosomal dominant forms are caused by mutations in the genes that encode type IX collagen, cartilage oligomeric matrix protein, and matrilin‐3: COL9A1, COL9A2, COL9A3, COMP, and MATN3, respectively. Splicing mutations have been identified in all three genes encoding type IX collagen and are restricted to specific exons encoding an equivalent region of the COL3 domain in all three α(IX) chains. MED has been associated with mild myopathy in some families, in particular one family with a COL9A3 mutation and two families with C‐terminal COMP mutations. In this study we have identified COL9A2 mutations in two families with MED that also have osteochondritis dissecans and mild myopathy. This study therefore extends the range of gene‐mutations that can cause MED‐related myopathy. © 2010 Wiley‐Liss, Inc.
Automated detection and guessing without semantics of sender-receiver relations in computer-mediated discourses

Automated tools for discourse analysis process tremendous amounts of computer-mediated discourses in a fast way. Assigning receivers to each message is an important step to answer the question "Who is communicating with whom" at any time. Direct addressing helps but is not used in every message. The focus of this paper is mainly split into two parts. First, automated detection and mapping of written receivers (or parts of them) to logged-in users. Second, if no receiver is written, automated receiver guessing without semantics. The architecture of the automated software is described in detail. As an applied example, the well-known and text-based chat system Internet Relay Chat (IRC) is used. An IRC discourse with 5605 messages is manually and automatically analyzed for comparing both approaches. Both - detection and guessing - are similarly well done as by hand.
Toward extracting malware features for classification using static and dynamic analysis

Because of a great many malware, they must be classified into malware family before being analyzed manually. Otherwise, we cannot analyze and handle them in real time. By classifying them, we can analyze only some unknown malwares intensively. In this paper, we propose a framework for malware classification using static and dynamic analysis. We focus on techniques that extract malware features. We name the framework GATTACA(Genome-based ATTACk geneAlogy) from the movie that covers genome of human. We define features of Malware as Mal-DNA(Malware DNA). Mal-DNA includes static, hybrid and dynamic characteristics. In short, GATTACA is the framework for extracting Mal-DNA from malwares and classifying them. GATTACA consists of three components: (1) START(STatic Analyzer using vaRious Techniques) extracts static Mal-DNA of malware. (2) DeBON(Debugging-based Behavior mOnitor and aNalyzer) extracts hybrid and dynamic Mal-DNA of them. (3) CLAM(CLassifier using Mal-DNA) classifies malwares based on Mal-DNA using machine learning. START and DeBON extract Mal-DNA, and CLAM classifies malwares based on Mal-DNA. In this paper, we target on START and DeBON extracting Mal-DAN from malwares.
New Literacies at the Digital Divide: American Indian Community Computing.

This study is about a community computing lab established by a U.S. Department of Commerce grant to bridge the Digital Divide in a rural Arizona American Indian community, a project called Native Connection (a pseudonym). This paper describes the process of integrating new literacies associated with a high-tech computer lab into the life of a small traditional community. Cultural Historical Activity Theory frames the dynamic interconnected elements of the lab: the participants, their purposes, the tools, and the community. Data were collected via questionnaires, interviews, and participant observation over most of a year. Findings demonstrated a steady increase in attendance and acceptance of the lab as part of the neighborhood, growth in after school lab activities by youth, and the beginnings of new literacy learning by lab users.
New Web cache replacement approaches based on internal requests factor

The increasing demand for World Wide Web (WWW) services has led to a considerable increase in the amount of Internet traffic. As a result, the network becomes highly prone to congestion which increases the load on servers, resulting in increasing the access times of WWW documents. Thus, Web caching is crucial for reducing the load on network, shorten network latency and improve clients' waiting time. Many web cashing systems and policies have been proposed to determine which objects to evict from the cache memory to accommodate new ones. Most of these systems and policies are mainly based on the enhancement of a well-known scheme called the Least Frequently Used (LFU) scheme. Although most of the proposed schemes could overcome the disadvantages of the LFU, they still have lots of overhead and are difficult to implement. This work proposes replacement approaches with better characteristics as they are easier to be implemented than the previous approaches. The proposed approaches consider the internal requests generated in each Web site. We added this factors to two famous approaches; LFU and Weighting Replacement Policy (WRP) to strength their performance. The experimental results indicate the superiority of the proposed approaches compared to both LFU and WRP, in terms of improvement in cache performance.
Learning Mathematics with tools

This paper presents the most recent researches in Mathematics Education in Italy, dealing with the use of tools and technologies at school. Its origin is in the document of Unione Matematica Italiana (U.M.I., the association of school and university teachers of Mathematics), which has published a curricular project for school Mathematics from the 1 to the 12 grade. The paper is a part of the book that is presented at ICME as the collection of all the most recent Italian researches in Mathematics Education.
Improving the Anti-Toxin Abilities of the CMG2-Fc Fusion Protein with the Aid of Computational Design

CMG2-Fc is a fusion protein composed of the extracellular domain of capillary morphogenesis protein 2 (CMG2) and the Fc region of human immunoglobulin G; CMG2-Fc neutralizes anthrax toxin and offers protection against Bacillus anthracis challenge. To enhance the efficacy of CMG2-Fc against anthrax toxin, we attempted to engineer a CMG2-Fc with an improved affinity for PA. Using the automatic design algorithm FoldX and visual inspection, we devised two CMG2-Fc variants that introduce mutations in the CMG2 binding interface and improve the computationally assessed binding affinity for PA. An experimental affinity assay revealed that the two variants showed increased binding affinity, and in vitro and in vivo toxin neutralization testing indicated that one of these mutants (CMG2-Fc(E117Q)) has superior activity against anthrax toxin and was suitable for further development as a therapeutic agent for anthrax infections. This study shows that the computational design of the PA binding interface of CMG2 to obtain CMG2-Fc variants with improving anti-toxin abilities is viable. Our results demonstrate that computational design can be further applied to generate other CMG2-Fc mutants with greatly improved therapeutic efficacy.
A wireless power telemetry with self-calibrated resonant frequency

A wireless power telemetry with self-calibrated resonant frequency is presented. The proposed calibration scheme adjusts the resonant frequency of inductively secondary coil to match the incident frequency of inductively primary coil. To adjust the resonant frequency of the secondary coil, the received power efficiency is improved. By experimented results, the overall power efficiency with frequency calibration is improved by a factor of 33%, compared with that one without frequency calibration. This wireless power telemetry has been fabricated in a standard 0. 35µm CMOS process, and the chip area is 1.536mm2 including I/O pads.
Selection of Ordinally Scaled Independent Variables

Ordinal categorial variables are a common case in regression modeling. Although the case of ordinal response variables has been well investigated, less work has been done concerning ordinal predictors. This article deals with the selection of ordinally scaled independent variables in the classical linear model, where the ordinal structure is taken into account by use of a dierence penalty on adjacent dummy coecients. It is shown how the Group Lasso can be used for the selection of ordinal predictors, and an alternative blockwise Boosting procedure is proposed. Emphasis is placed on the application of the presented methods to the (Comprehensive) ICF Core Set for chronic widespread pain.