Miracle-dz/UniFAR-FTUs huggingface dataset:
Network inference from AP-MS data: computational challenges and solutions

Protein-protein interaction is of primary importance to understand protein functions. In recent years, the high-throughput AP-MS experiments have generated a large amount of bait-prey data, posing great challenges on the computational analysis of such data for inferring true interactions and protein complexes. To date, many research efforts have been devoted to developing novel computational methods to analyze these AP-MS data sets. In this article, we review and classify the key computational methods developed for the inference of protein-protein interactions and the detection of protein complexes from the AP-MS experiments. We hope that our review as well as the challenges highlighted in the article will provide valuable insights into driving future research for further advancing the state-of-the-art technologies in computational prediction, characterization and analysis of protein-protein interactions and protein complexes from the AP-MS data.
VISAR: a system for inference and navigation of hypertext

Hypertext systems have traditionally been constructed by hand. This process can stand improvement in several aspects: it is laborious; requires a human to understand the text and infer all the relationships between the concepts/topics; and while the resulting hypertext may be traversed by a reader in an arbitrary fashion, s/he may still find it difficult to understand the concepts as expressed by the builder of the hypertext. We present a knowledge-intensive assistant for building hypertext fragments from a knowledge base customised both explicitly and implicitly by a user. Such a presentation may clarify relationships between concepts that were present implicitly in multiple sources of information. In the domain of an intelligent information retrieval system, we show how such an assistant may render customised views of knowledge extracted in a manageable form. While the presentation medium of the original system is graphic, we also speculate that presentation of the information in alternative hypermedia appears to be straightforward.
Generative pattern-based design of user interfaces

This paper suggests a method for developing graphical user interfaces based on generative patterns. A generative pattern contains portions of previously designed user interfaces are expressed through models that are either partially or totally instantiated. These portions could be identified and re-applied to a new design case study by generating code by instantiating the specifications contained in the models. The method involves typical models found in user interface development life cycle such as task, domain, abstract user interface, concrete user interface, final user interface, context model, and mappings between them. Any model could virtually be the source of a pattern and could be described, searched, matched, retrieved, and assembled together so as to create a new graphical user interface. For this purpose, a software has been developed that manages generative patterns by combining an existing user interface description language (UsiXML -- user interface extensible markup language) with concepts addressing problems raised by pattern description and matching in a pattern-based language (PLML -- Pattern Language Markup Language, a language was introduced to uniformly represent user interface patterns). Once instantiated from the generative patterns, the models give rise to a model-driven engineering based on model-to-model transformation and model-to-code compilation.
Models and implementations of hardware interface modules in a multi-processor system-on-chip simulator

This paper investigates the modeling of hardware interface modules in cycle accurate simulators. The implemented modules are integrated into a C++ multi-processor system-on-chip (MPSoC) simulator. The implementation of hardware interface models is driven by the following desired features: easy integration into the simulation model of the MPSoC and easy configuration. Regarding the first feature, it is achieved by employing a standardized interface for all modules and by using generic bus models and bus interfaces in order to perform data transfers to and from the modules. The configuration of the modules is achieved by employing a standardized XML configuration file. Four hardware interfaces are presented: DMA controller, LCD interface module, camera interface module, H264 decoder module and the bus traffic generator.
Job characteristics affect shared leadership

Purpose Shared leadership is characterized by exercising lateral leadership influence depending upon the task and the adroitness required for the task. The purpose of this paper is to examine the effects of job characteristics on shared leadership and explore the moderating effects of perceived self-efficacy, and psychological safety on the relationship between job characteristics and shared leadership. Design/methodology/approach The authors applied hierarchical regression and social network analysis using a sample of 23 teams consisting 219 employees from an Indian-based multinational BPO. Findings Results indicate that skill variety, task significance, autonomy and feedback are significant precursors for shared leadership, and psychological safety and perceived self-efficacy act as moderators. Research limitations/implications The study extends the literature associated with job characteristics in relation to shared leadership. Managers can encourage shared leadership using job design and by creating a psychologically safe environment to enhance performance of the team. The cross-sectional nature of the study and data from a single organization question the generalizability of the results. Originality/value The authors provide an initial understanding of the impact of job characteristics in a team for the development of shared leadership, which has not been studied so far. Also, psychological safety and self-efficacy of individuals in teams have not been explored in the past, moderating the job characteristics and shared leadership relationship.
Molecular characterization of human retinal progenitor cells.

PURPOSE To examine the molecular profile of fetal human retinal progenitor cells (hRPCs) expanded in vitro and those grown in a co-culture system with mouse retina through the analysis of protein and gene expression and neurotransmitter-stimulated calcium dynamics. METHODS hRPCS were isolated from human retina of 14 to 18 weeks gestational age (GA) and expanded in vitro. Immunoblot, microarray, and immunocytochemistry (ICC) assays were performed on undifferentiated hRPCs and those co-cultured with mouse retinas for 2 weeks. Cell function was assessed by using calcium imaging. RESULTS The ICC results showed a gradual decrease in the percentages of KI67-, SOX2-, and vimentin-positive cells from passages (P) 1 to P6, whereas a sustained expression of nestin and PAX6 was observed through P6. Microarray analysis of P1 hRPCs showed the expression of early retinal developmental genes: VIM (vimentin), KI67, NES (nestin), PAX6, SOX2, HES5, GNL3, OTX2, DACH1, SIX6, and CHX10 (VSX2). At P6, hRPCs continued to express VIM, KI67, NES, PAX6, SOX2, GNL3, and SIX6. On co-culture, there was a significant increase in the expression of MKI67, PAX6, SOX2, GNL3, SIX3, and RHO (rhodopsin). Calcium imaging showed a functional response to excitatory neurotransmitters. CONCLUSIONS Fetal-derived hRPCs show molecular characteristics indicative of a retinal progenitor state up to P6 (latest passage studied). They show a progressive decrease in the expression of immature markers as they reach P6. These cells are functional, respond to excitatory neurotransmitters, and exhibit changes in expression patterns in response to co-culture with mouse retina.
Joint Transmitter Power Control and Mobile Cache Management in Wireless Computing

We investigate efficient schemes for data communication from a server (base station and access point) to a mobile terminal over a wireless channel of randomly fluctuating quality. The terminal user generates requests for data items. If the buffer (cache) of the terminal contains the requested data, no access delay/latency is incurred. If not, the data is downloaded from the server, and until becoming available locally at the terminal, the user incurs a delay cost. Moreover, a transmission/power cost is incurred to transmit the data over the wireless link at a dynamically selected power level. To lower both the access delay and transmission costs, the system may prefetch data predictively and cache them on the terminal (especially during high-link-quality periods), anticipating future user requests. The goal is to jointly minimize the overall latency and power costs by dynamically choosing what data to (pre)fetch, what power level to use, and when to use it. We develop a modeling framework (based on dynamic programming and controlled Markov chains) that captures essential performance trade-offs. It allows for the computation of optimal decisions regarding what data to (pre)fetch and what power levels to use. To cope with emerging complexities, we then design efficient online heuristics whose simulation analysis demonstrates substantial performance gains over standard approaches.
COMPUTATIONAL APPROACHES TO NEUROLOGICAL DISEASE

Computational models have contributed to current understanding of normal brain function, and can offer new insights into the pathophysiology of neurological disease. We define some of the outstanding clinical questions in stroke, CNS injury, Alzheimer's disease, Parkinson's disease, and epilepsy from a neurologist's perspective, and discuss the potential impact of computational neurology on computational neuroscience. We consider representative examples of models constructed at several different levels of biological detail--from detailed membrane-level simulations to connectionist networks. We focus on what has been learned from several generations of models concerned with the after-effects of neural injury. In particular, we discuss how model assumptions, sometimes of ancillary importance, have constrained the ability to predict subsequent experimental results.
Efficient Hybrid-Game Strategies Coupled to Evolutionary Algorithms for Robust Multidisciplinary Design Optimization in Aerospace Engineering

A number of game strategies have been developed in past decades and used in the fields of economics, engineering, computer science, and biology due to their efficiency in solving design optimization problems. In addition, research in multiobjective and multidisciplinary design optimization has focused on developing a robust and efficient optimization method so it can produce a set of high quality solutions with less computational time. In this paper, two optimization techniques are considered; the first optimization method uses multifidelity hierarchical Pareto-optimality. The second optimization method uses the combination of game strategies Nash-equilibrium and Pareto-optimality. This paper shows how game strategies can be coupled to multiobjective evolutionary algorithms and robust design techniques to produce a set of high quality solutions. Numerical results obtained from both optimization methods are compared in terms of computational expense and model quality. The benefits of using Hybrid and non-Hybrid-Game strategies are demonstrated.
Dominating Circuits in Regular

In 1971, Nash-Williams proved that if G is a simple 2-connected graph on n vertices having minimum degree at least 3(n+2), then any longest cycle C in G is also edge-domininating; that is, each edge of G has at least one end-vertex incident with a vertex of C. We say that a circuit C in a matroidM is dominating if each component of M/C has rank at most one. In this paper, we show that an analogous theorem holds for regular matroids. More s pecifically, supposeM is a simple, connected, regular matroid and let C be a circuit inM. We show that if|C∗| > r(M) 3 + 1, for all cocircuitsC∗ in M which are disjoint fromC, then eitherC is a dominating circuit, or there is a circuit D such that the symmetric difference of C with D is a circuit which is strictly larger than C.
Automated Diagnosis Non-proliferative Diabetic Retinopathy in Fundus Images using Support Vector Machine

Diabetic retinopathy (DR) is caused by damage the retina because fluid leaks from blood vessels into the retina. Damage the posterior part of the eye of the diabetic patient. This disease that occurs when does not secrete enough insulin or the body is unable to process it properly. The main two types of diabetic retinopathy the first are non-proliferate diabetes retinopathy (NPDR) and second are proliferate diabetes retinopathy (PDR). The increasing number of DR cases world-wide demands to the development of an automated detection system. We have proposed a computer based method for the detection of diabetic retinopathy using the fundus images. Using Image pre-processing, morphological processing techniques involves processing of fundus images for detect features, such as blood vessel area, exudates, microaneurysms, hemorrhages, and texture. Proposed techniques used for the extraction of these features from digital fundus images. The proposed techniques have been tested on the images of DIARETDB0 database. In which have total 130 images they all images are tested and it’s classified into microaneurysms, hemorrhages, and texture using Support Vector Machine (SVM) for an automatic classification. The detection results obtained by comparing it with expert ophthalmologists. We demonstrated a classification sensitivity of 96.43%, specificity of 95.9 % and accuracy of 99.27 %.
Characterizing Servers Workload in Cloud Datacenters

Mastering the characteristics of the server workload is a key prerequisite in planning and good management of resources within a datacenter. However, for the purpose of research, it is very difficult to find reliable data that can be used to define models adapted to operations in data centers and tests. Google unwounded a portion of this problem by recently publishing a collection of traces from one of its biggest data centers. We conducted a series of analyzes on those data and it basically shows that a large part of the server load relates to non-priority applications and the amount of resources (mainly processors) consumed by servers is much higher than those required for the processing of the received requests. It also highlights the huge amount of wasted energy during processing in those types of data centers.
Connectivity and Stability at Failures in ISP Backbone Networks

When a link or node failure occurs, flows are detoured around the failed portion, so the hop count of flows could change dramatically as a result of a failure. It is therefore important to evaluate the reliability of backbone networks from the viewpoint of flow hop length stability as well as network connectivity. In this paper, we analyze the possible primary causes of the degradation of reliability of the backbone networks of 36 commercial ISPs and present guidelines for making effective investments in link addition.
SMG1 Identified as a Regulator of Parkinson’s Disease-Associated alpha-Synuclein through siRNA Screening

Synucleinopathies are a broad class of neurodegenerative disorders characterized by the presence of intracellular protein aggregates containing α-synuclein protein. The aggregated α-synuclein protein is hyperphosphorylated on serine 129 (S129) compared to the unaggregated form of the protein. While the precise functional consequences of S129 hyperphosphorylation are still being clarified, numerous in vitro and in vivo studies suggest that S129 phosphorylation is an early event in α-synuclein dysfunction and aggregation. Identifying the kinases and phosphatases that regulate this critical phosphorylation event may ultimately prove beneficial by allowing pharmacological mitigation of synuclein dysfunction and toxicity in Parkinson’s disease and other synucleinopathies. We report here the development of a high-content, fluorescence-based assay to quantitate levels of total and S129 phosphorylated α-synuclein protein. We have applied this assay to conduct high-throughput loss-of-function screens with siRNA libraries targeting 711 known and predicted human kinases and 206 phosphatases. Specifically, knockdown of the phosphatidylinositol 3-kinase related kinase SMG1 resulted in significant increases in the expression of pS129 phosphorylated α-synuclein (p-syn). Moreover, SMG1 protein levels were significantly reduced in brain regions with high p-syn levels in both dementia with Lewy bodies (DLB) and Parkinson’s disease with dementia (PDD). These findings suggest that SMG1 may play an important role in increased α-synuclein pathology during the course of PDD, DLB, and possibly other synucleinopathies.
The public safety broadband network: A novel architecture with mobile base stations

A nationwide interoperable public safety broadband network is being planned by the United States government. The network will be based on long term evolution (LTE) standards and use recently designated spectrum in the 700 MHz band. The public safety network has different objectives and traffic patterns than commercial wireless networks. In particular, the public safety network puts more emphasis on coverage, reliability and latency in the worst case scenario. Moreover, the routine public safety traffic is relatively light, whereas when a major incident occurs, the traffic demand at the incident scene can be significantly heavier than that in a commercial network. Hence it is prohibitively costly to build the public safety network using conventional cellular network architecture consisting of an infrastructure of stationary base transceiver stations. A novel architecture is proposed in this paper for the public safety broadband network. The architecture deploys stationary base stations sparsely to serve light routine traffic and dispatches mobile base stations to incident scenes along with public safety personnel to support heavy traffic. The analysis shows that the proposed architecture can potentially offer more than 75% reduction in terms of the total number of base stations needed.
RETRIEVAL OF RICE PHENOLOGY BY MEANS OF COPOLAR DUAL-POL IMAGES PROVIDED BY TERRASAR-X

The polarimetric behaviour of rice fields at different phenological stages has been analysed by using time series of TerraSAR-X images. These are X-band copolar dual-pol images available for the whole growth cycle. As plants grow, changes in their morphology produce clear signatures in various polarimetric observables. Based on this sensitivity to phenology, a physically based retrieval approach is designed to estimate the phenological stage of rice fields from a single acquisition. Despite the simplicity of the algorithm, our tests have demonstrated its usefulness for identifying some specific phenological phases of interest for planning and triggering practices by the rice farmers.
Websrcmed: a Mediator for Scaling up to Multiple Web Accessible Sources (websources) Universidad Simm on Bol Var Caracas Venezuela

The rapid growth of the Internet and Intranets has dramatically increased the number of WebSources. These sources are typically characterized by a limited query capability compared to a relational data source. They may also be incomplete, and there may be redundancy among them. These features increase the challenge of scaling to answer queries in a mediator-wrapper architecture with a large number of WebSources, and they impact the mediator tasks of capability based rewriting (CBR) and query optimization. We propose a mediator-wrapper based architecture for WebSources, WebSrcMed. Using query capability, content and coverage (completeness) descriptions of WebSources, we develop techniques for CBR that maintain the following properties: rst, we ensure that WebSrcMed only accepts queries for which it can guarantee that there is at least one WebSource that can evaluate this query { this is a safe query, for which there is a safe plan. For each safe query, we identify when the largest possible subquery can be submitted to a WebSource, depending on its capabilities, and this feature results in a maximal plan. Finally, if there is redundancy of complete descriptions of WebSources, we identify this redundancy in computing the answer and produce non-redundant plans. To maintain these properties, WebSrcMed exports a single interface which reeects the descriptions (capability, content and coverage) of multiple WebSources, for some domain. This interface is deened so that WebSrcMed can use it to accept only those queries for which there is a safe plan. To provide possibly maximal and non-redundant plans, WebSources and their descriptions are partitioned into equivalence classes. These equivalence classes are partially ordered within a lattice of complete WebSources that are redundant, and a lattice of possibly incomplete WebSources. WebSrcMed uses these lattices to identify relevant WebSources and to identify a set of alternate WebSources. The lattices also provide a description for each relevant WebSource, so that the WebSrcMed can produce a possibly maximal plan.
Introduction of a Novel Molecular Mechanism of Epilepsy Progression: Roles of Growth Hormone Signaling in a Mouse Model of Temporal Lobe Epilepsy

Epilepsy is a chronic neurological disease involving recurring behavioral seizures, and affects approximately 1% of the worldwide population of humans and cats, and 2-3% of dogs. Epilepsy causes recurring behavioral seizures, which are transient behavioral changes caused by disordered, synchronized, and rhythmic firings of populations of neurons in the brain that propagate to regions connected with the first insult on the neural circuits, induced by abnormal neural plasticity (Browne and Holmes 2000). The seizure expression is induced by idiopathic/cryptogenic and remote symptomatic causes, as concrete examples, febrile illness in children younger than 16 years (Besli et al., 2010) and cerebrovascular and ethanol/drug-related accidents in adults. When the seizures are prolonged, or occur in a series, there is an increased risk of status epilepticus. About 15 % of persons with epilepsy experience status epilepticus, which induces more brain damage. It is known that large populations of epilepsy patients express status epilepticus due to medication changes in both children and adults. Hence, improving the compliance of patients to take medicine appropriately is very helpful to prevent the expression of status epilepticus. Despite the importance of medication, more than one third of patients with epilepsy are estimated to have pharmacoresistant epilepsy (Browne and Holmes 2000). Half of patients with refractory epilepsy are characterized as having mesial temporal lobe epilepsy (TLE) with foci in the amygdaloid complex, hippocampus, and surrounding cortex. To solve the problem of pharmacoresistance, it is important to clarify the molecular mechanisms involved in the development of pharmacoresistant seizures. Additionally, patients with epilepsy are at high risk of developing anxiety, depression, learning disorders, and sudden death (Dodrill, 1986; Franks, 2003; Motamedi and Meador, 2003; Sillanpaa and Shinnar, 2010). To improve the quality of life of patients, it is useful to clarify the comorbidity between seizures and other neuropsychiatry disorders. Depression and anxiety have the highest incidence in patients with TLE (Perini, et al., 1996). Hence, it should be clarified how the molecular signaling system regulates the development of pharmacoresistant abnormal neural plasticity and, as a result, recurring prolonged seizures that are induced by symptomatic causes. New drugs that can respond to seizures that known drugs fail to cure