Academic literature on the topic 'TSpred'

The metalloprotease ADAM10/Kuzbanian catalyzes the ligand-dependent ectodomain shedding of Notch receptors and activates Notch. Here, we show that the human tetraspanins of the evolutionary conserved TspanC8 subfamily (Tspan5, Tspan10, Tspan14, Tspan15, Tspan17, and Tspan33) directly interact with ADAM10, regulate its exit from the endoplasmic reticulum, and that four of them regulate ADAM10 surface expression levels. In an independent RNAi screen in Drosophila, two TspanC8 genes were identified as Notch regulators. Functional analysis of the three Drosophila TspanC8 genes (Tsp3A, Tsp86D, and Tsp26D) indicated that these genes act redundantly to promote Notch signaling. During oogenesis, TspanC8 genes were up-regulated in border cells and regulated Kuzbanian distribution, Notch activity, and cell migration. Furthermore, the human TspanC8 tetraspanins Tspan5 and Tspan14 positively regulated ligand-induced ADAM10-dependent Notch1 signaling. We conclude that TspanC8 tetraspanins have a conserved function in the regulation of ADAM10 trafficking and activity, thereby positively regulating Notch receptor activation.

Side-channel attack (SCA) reveals confidential information by statistically analyzing physical manifestations, which is the serious threat to cryptographic circuits. Various SCA circuit-level countermeasures have been proposed as fundamental solutions to reduce the side-channel vulnerabilities of cryptographic implementations; however, such approaches introduce non-negligible power and area overheads. Among all of the circuit components, flip-flops are the main source of information leakage. This article proposes a three-phase single-rail pulse register (TSPR) based on the three-independent-gate field effect transistor (TIGFET) to achieve all desired properties with improved metrics of area and security. TIGFET-based TSPR consumes a constant power (MCV is 0.25%), has a low delay (12 ps), and employs only 10 TIGFET devices, which is applicable for the low-overhead and high-security cryptographic circuit design compared to the existing flip-flops. In addition, a set of TIGFET-based combinational basic gates are designed to reduce the area occupation and power consumption as much as possible. As a proof of concept, a simplified advanced encryption algorithm (AES), SM4 block cipher algorithm (SM4), and light-weight cryptographic algorithm (PRESENT) are built with the TIGFET-based library. SCA is implemented on the cryptographic implementations to prove its SCA resilience, and the SCA results show that the correct key of cryptographic circuits with TIGFET-based TSPRs is not guessed within 2,000 power traces.

The feasible solutions of the traveling salesman problem with pickup and delivery (TSPPD) are represented by vertex lists in existing literature. However, when the TSPPD requires that the loading and unloading operations must be performed in a last-in-first-out (LIFO) manner, we show that its feasible solutions can be represented by trees. Consequently, we develop a variable neighbourhood search (VNS) heuristic for the TSPPD with last-in-first-out loading (TSPPDL) involving several search operators based on the tree data structure. Experiments show that our VNS heuristic is superior to the current best heuristics for TSPPDL in terms of both solution quality and computing time.

To fully use high-pressure air, the two-stage piston expander (TSPE) has been widely studied. The following factors obstruct the use of the TSPE: A high expansion ratio will inevitably result in a lower air temperature in the cylinder, causing adverse effects such as ice blockage and lubricating oil freezing; the residual air from the I-stage cylinder will all flow into the II-stage cylinder, causing a large reverse force to the I-stage piston during the working process. To address the above problems, a modified two-stage piston expander (M-TSPE) based on spray heat transfer is proposed. Firstly, the working principle of the M-TSPE is introduced, followed by the construction of a mathematical model of the M-TSPE. Secondly, the valve-timing of the M-TSPE is determined and compared with the output power and efficiency of the TSPE. The output power and efficiency of the M-TSPE are increased by 57.58% and 13.28%, respectively. Then, the performance parameters of the M-TSPE with and without spray are compared and analyzed. Finally, parameter analysis is carried out on the air/water mass ratio and water mist particle size. Results show that when the intake pressure and load torque are set to 3 MPa and 150 N·m, respectively, the output power of the M-TSPE without spray is 14.22 kW and the output power of the M-TSPE with spray is 16.08 kW, which is a 13.08% increase in output power. The average air temperatures in the I-stage cylinder of the M-TSPE with and without spray are 321 K and 263 K, respectively, and the average air temperature in the I-stage cylinder is enhanced by 58 K. The output performance of the M-TSPE can be improved by increasing the mass ratio of the water mist in the cylinder and decreasing the particle size of the water mist.

Sixteen isolates of thermophilic bacteria from the genus Thermus, isolated from neutral and alkaline hot water springs in the southwest region of Iceland, were tested for the presence of restriction endonucleases. Extracts from five of the isolates showed evidence of the presence of restriction endonuclease activity by producing discrete nucleotide fragments when incubated at 65 degrees C with lambda phage DNA. Two of the isolates (Tsp4C and Tsp8E) were found to have particularly high levels of restriction endonuclease activity, and the respective enzymes from these two Thermus isolates were partially purified and characterized and their recognition and cleavage sites were determined. Enzyme Tsp4C I is a novel Type II restriction endonuclease recognizing the interrupted palindromic tetranucleotide sequence ACNGT, where N can be any one of the four bases in DNA. Tsp4C I, which retains full enzyme activity when incubated for 10 min at temperatures up to 76 degrees C, hydrolyses the phosphodiester bond in both strands of a double-stranded DNA substrate between the third and fourth bases of the recognition sequence (ACN/GT), generating fragments with a single base 3′-OH overhang. Enzyme Tsp8E I is a thermostable isoschizomer of the mesophilic Type II restriction endonuclease Bgl I (GCCNNNN/NGGC) [Lee, Clanton and Chirikjiam (1979) Fed. Proc. 28, 294], generating fragments with a three base 3′-OH overhang. However, unlike Bgl I, Tsp8E I exhibits considerable thermal stability, retaining full enzyme activity when incubated for 10 min at temperatures up to 78 degrees C. Both Tsp4C I and Tsp8E I represent significant additions to the small but expanding list of the extremely thermostable restriction endonucleases.

Turbocharged solid propellant ramjet (TSPR) is the combination of solid propellant gas generator air turbo ramjet (ATR)with solid ramjet, is cycle of augmented ATR, the parametric performance calculation were carried out for TSPR, The effects of independent design parameters including parameters of compressor and turbine and propellants were studied and the preferred compressor, turbine and propellants were obtained for TSPR; The operation envelop of TSPR and ATR were obtain under the preferred component limitation, the results shows that TSPR offers wide speed-altitude operation envelope, high specific thrust, high specific impulse, it is combining the advantages of the ATR and solid ramjet, and suitable for tactical missiles application meets potential requirements for boosting and cruising.

Internet ha supuesto el despegue de las redes de conmutación de paquetes, las ha convertido en un medio al que todo el mundo quiere acceder, y ha obligado a replantear todas las previsiones que manejaban los operadores sobre el tráfico que iban a soportar sus redes en cada una de sus partes: el acceso, la agregación y la dorsal. Precisamente, la evaluación de estas y otras situaciones deben estar incluidas en el proceso de diseño y planificación de cualquier red, en lo que se ha denominado planificación estratégica. La estimación de la demanda de tráfico resulta especialmente importante porque permite al operador anticiparse a situaciones de congestión y bloqueo de la red. Utiliza herramientas de modelado del tráfico, bien para su cálculo analítico o para su estudio mediante simulación, y al ser una herramienta fundamental, existe un extenso catálogo de modelos de tráfico: genéricos y particularizados, de fuentes individuales y de redes completas, de elementos de interconexión y de enlaces. En esta Tesis, se han analizado los diferentes modelos existentes y se ha desarrollado un nuevo modelo que tiene en cuenta el comportamiento del tráfico desde su preparación por parte de la capa de aplicación, hasta su inserción en la capa física. El modelo propuesto parte de la solución ON-OFF tradicional, aunque aplicado a tres niveles diferentes (conexión, sesión y ráfaga), de forma que cada estado ON se encuentra modulado por el modelo correspondiente a la capa inferior. Como alternativa más simple, surgen los modelos multifuente, que intentan introducir el efecto de la interacción entre las diferentes fuentes, también conocido como agregación. Para considerar este caso, se ha realizado un estudio de modelos específicos para su aplicación a puntos de agregación, especialmente los situados en la red de acceso, al ser ésta la parte de la red que más alto coste presenta en su implementación. Partiendo del modelo ON-OFF para una sola fuente, se ha propuesto una variante multifuente, que aprovecha las propiedades de la función de distribución binomial para realizar el cálculo del tráfico agregado por un número determinado de fuentes. El resultado ha sido comparado mediante la observación de flujos reales, tal como propone la teoría del Network Calculus, y que ha sido evaluada y aplicada en este trabajo con ejemplos prácticos que se han incluido en el documento. El estudio realizado en esta Tesis concluye que el tráfico de fuente está condicionado a tres premisas fundamentales: el usuario, el servicio y la tecnología de acceso, de donde surge un nuevo concepto que especifica de forma sistemática y ordenada todas las variaciones, denominada CASUAL (Cubo de Acceso/Servicios/Usuarios de Asignación Libre) y ha sido aplicada en una herramienta realizada a su efecto, junto con los modelos de tráfico de fuente propuestos.
Internet has been the catalyst of the development of packet switched networks, which have become the resource which everyone wants to access. As a consequence, the operators need to recalculate all their forecasts about the traffic to be transported by their networks. In fact, the evaluation of these and other situations should be included within the design and planning phases of any network, in the so called strategic planning overall process.Traffic demand estimation is particularly interesting, since it allows the operator to anticipate bottlenecks and blocking situations of the network. It uses traffic modelling tools, either for their analytical or simulation-based study. Since they have become an essential tool, there is a wide range of traffic models: generic and particularized, for individual sources and complete networks, for interconnection elements and links.In this thesis, we have analyzed the different models and have developed a new model that takes into account traffic patterns from preparation by the application layer to its insertion into the physical layer. The proposed model is based on the traditional on-off solution, but applied to three different levels (connection, session and burst), so that each ON state is modulated by the model corresponding to the bottom layer. As a simpler alternative, multisource models emerge, seeking to introduce the effect of the interaction between different sources, also known as aggregation. To consider this case, it has made a study of specific models for application to aggregation points, especially those located in the access network, as this is the part of the network that has higher cost in implementation. Based on the ON-OFF model for a single source, is a proposed multi-source variant, which exploits the properties of the binomial distribution function for the calculation of the aggregate traffic for a specified number of sources. The result has been compared by observation of actual flows, as proposed by the theory of Network Calculus, and has been evaluated and implemented in this work with practical examples that are included in the document.The study in this thesis concludes that the traffic source is conditioned on three fundamental premises: the user, service and technology access, where there was a new concept that specifies a systematic and orderly all the variations, called CASUAL (Cube of Access / Services / Users with Free Allocation) and has been implemented in a tool made of its effect, along with the traffic source models proposed.

This qualitative action research explores integration of Strategic Sustainable Development (SSD) at Inova business incubator (Karlstad, Sweden). Researchers and incubator agreed that planning with sustainability in mind at a very early stage of company development may have important impacts on future business success and societal welfare. The objective was to answer how SSD could be integrated into the processes at Inova and how Inova staff’s and entrepreneurs’ understanding of sustainability demonstrably evolve after exposure to SSD. Apart from general research methods, SSD methods and tools were used with three entrepreneurs and business incubator staff. The Five Level Framework for Planning and Decision-making in complex systems and the Templates for Sustainable Product Development approach were central to the study. Inova staff and entrepreneurs began to develop; an understanding of business’ dependence on and relationship to broader societal and ecological systems; and an ability to use backcasting from the basic socio-ecological principles of sustainability in business planning. In turn they experienced an increased capacity to identify sustainability related business risks and opportunities. A new incubation process integrating SSD was created. Although the outcome is specific to Inova, it is general enough for other assistance organizations to gain insight from. In conclusion, SSD should be integrated as early as possible in the business planning of start up companies. Organizations with a mission of assisting entrepreneurs have an important role to play In further research it is recommended that visionary sustainability leaders are identified and tracked from start up.

The Templates for Sustainable Product Development (TSPD) is a tool for sustainability practitioners to assist product development teams with bringing sustainability considerations to the early phases of product development in a strategic, quick and resource-efficient way. This thesis project builds on the earlier TSPD work by investigating the ways in which sustainability practitioners could apply the TSPD in order to improve the outcomes. The factors influencing the quality of the outcomes of a TSPD application were investigated. Then, support was developed for use by sustainability practitioners to address these factors. This support was field tested and refined in four iterations. It was discovered that achieving high quality outcomes from a TSPD application is dependent on having both high quality strategic sustainable product development content and high quality facilitation of the people considering this content. The quality of both content and facilitation influences the participants’ level of engagement, which influences the quality of the outcomes of the TSPD application. The support was developed such that it assists sustainability practitioners in addressing both content and facilitation through a participatory approach. There is some evidence that use of the developed support contributed to both high level of participants’ engagement and high quality outcomes of the TSPD applications.

Blog at http://sustainableproductdevelopment.blogspot.se/

International Telemetering Conference Proceedings / October 25-28, 1999 / Riviera Hotel and Convention Center, Las Vegas, Nevada
The Air Force SEEK EAGLE Office (AFSEO) was chartered by the Secretary of the Air Force in December 1987. The mission of the AFSEO is to provide the United States Air Force increased combat capability through central management of the aircraft-stores certification process and provide in-house engineering and operations research capabilities. Additionally, the AFSEO is required to ensure the future viability of the aircraft-stores organic in-house capability with the insertion of evolving technologies. To accomplish this mission, the AFSEO employs all phases of the test process; from Digital Model and Simulation (DMS) to Open Air Range (OAR) flight tests. The AFSEO desires to prepare for the future DoD environment, and minimize the cost of developing its products that require advanced sensors and telemetry capability. For a number of years, a mainstay in the process has been instrumented aircraft. These aircraft were specially instrumented to support the mission of AFSEO. Similarly, stores were instrumented to obtain environmental data such as loads and vibration. With the rising cost of instrumentation and the national DoD trend to reduce the cost of development and maintenance of instrumentation, a new method will need to be found. Several advanced concepts in ground and airborne instrumentation at Eglin AFB are needed to support the mission of the AFSEO. These include a new generation of telemetry devices, sensors, and data acquisition components to provide rapid and cost effective instrumentation of test aircraft, stores, and suspension equipment. The new generation telemetry will provide integrated circuitry with “peel and stick” subminiature telemetry sensors. These telemetry sensors will provide flutter and structural loads data for aircraft-stores combinations. In conjunction with the telemetry sensors, advanced aircraft platform instrumentation will be needed to match precision flight mechanics to the spatial telemetry measurements for stress, strain, and dynamic activity of stores.

This research aims to shed insights and produce supportive tools to help stimulate the design of education programs. First a characterization of opportunities and challenges for education programs is given from a global sustainability standpoint. Second a characterization of what education programs may contain and take into account from a full sustainability standpoint, as an outline of education programs in a desired future at a principle level, is provided to help inspire purpose-led education services organizations. Third an outline of possible tools and strategies to help strategically close the gap between the current unsustainable state and the desired sustainable future is provided. A special focus is put on the Template for Sustainable Product Development (TSPD) process tool, originally used to help industries in their production chain, but here adapted as the “Sustainability Potential” Express Strategic Assessment for Education Programs to benefit education programs stakeholders. The authors also propose a set of three abilities acting in synergy: Creativity, “Knowledge Making” & “Open Values” (CKMOV) that are at the heart of Strategic Sustainable Development and thus may help form three equally vital pillars, which education programs may strategically take support from while helping society transition to a sustainable equilibrium.

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Proteins play a central role in all the biological processes. The immense diversity in protein structures and functions despite similar underlying composition is intriguing. The work presented in this thesis aims to provide a deeper understanding of protein structure-function relationships. It describes some techniques that were developed in order to probe these relationships. Chapter 1 provides a general introduction to the topics discussed in the thesis. Chapter 2 focuses on an important aspect of protein structures, the cavities. Although proteins are composed of regular arrangements of secondary structures, namely, α helices and β sheets, there are some irregularities. The packing density is not uniform throughout the protein resulting into formation of cavities. The role of cavities has been previously probed using mutagenesis studies. The mutations designed to fill the cavities were observed to improve stability and cavity creating mutations adversely affected the stability. Cavities are thus reported to be important contributors to stability. In chapter 2, we refine and benchmark a method for prediction of protein cavities based on molecular dynamics simulations. The insights derived from the mutagenesis studies provide some basic understanding of substitution preferences in proteins. The exposed non-active site positions are more tolerant to mutations whereas, the buried positions are not. Introducing cavity filling and disulfide mutations in proteins have been demonstrated to improve stability. Engineering protein variants with improved stability has immense applications in biology. In chapter 3, we discuss an important application, i.e., immunogen designing. Surface glycoproteins of several viruses exhibit two conformations, namely the metastable prefusion conformation and the highly stable postfusion conformation adopted during the fusion of the virus with the host cell membrane. Stable immunogens exhibiting the prefusion conformation are promising candidates for subunit vaccines. In chapter 3, we discuss immunogen designing for the respiratory syncytial virus (RSV). In addition to stabilized mutants, temperature sensitive (Ts) mutants are another class of engineered proteins. The Ts mutants exhibit reduced activity levels above the permissive temperature. They have been extensively used in developmental biology. Ts mutants are excellent tools to modulate protein expression levels in cells. A model for prediction of Ts positions was developed previously. This model exploits residue hydrophobicity to infer residue burial in the structure solely based on the protein sequence. In the current work, we improved the accuracy of the model by incorporating structural information in the model. Chapter 4 describes the development and benchmarking of a server for the prediction of Ts mutants (TSpred). The TSpred server suggests a stereochemically diverse set of mutations at the putative buried positions which are would produce destabilization to different extents and at least one of them is likely to be Ts. The TSpred predictions were employed for designing live attenuated vaccine candidates for RSV. The work thus far elaborates on factors contributing to protein stability and application of that information for rationally designing mutants to modulate protein structure and function. In order to gain a deeper understanding of the role of each protein residue in its function, simultaneous analysis of multiple mutants is essential. Site saturation mutagenesis techniques generate all nineteen mutations at each residue position of the protein and the mutant function is linked to a phenotypic readout like cell viability or binding to a ligand. The mutant libraries are deep sequenced using one of the available platforms like Illumina, SOLiD, 454 and Ion torrent, and analysed to estimate the relative proportions of each of the mutants in the library. Automated programs are necessary to analyse the large amount of data generated after deep sequencing. A pipeline for analysis of data generated from the Illumina sequencing platform is discussed in chapter 5. A mutational sensitivity measure denoted as MSseq was previously derived for the Controller of Cell division or Death B protein (CcdB). The values of the MSseq parameter reflect mutant activity. The active or inactive phenotypes of various mutants were analysed as a function of residue burial. Additional insights about substitution preferences at buried positions were gained from this analysis. In addition to residue burial, the substitution preferences varied with the physico-chemical nature and the size of the wild type (WT) and the mutant side chains. The active site of the CcdB protein could be inferred based on the trends in the mutational sensitivity values. We quantitated these effects and developed a model, detailed in chapter 6, for prediction of the mutant phenotypes using a fraction of the CcdB mutational data. The model was observed to perform better than two other machine learning based predictors, SNAP2 and SuSPect. Chapter 7 describes an additional application of the mutational sensitivity data. By analysing the population distribution of the MSseq values, an empirical parameter, RankScore, was previously derived for each residue in CcdB. RankScore can be interpreted as a weighted average of the MSseq values. RankScore was found to correlate well with residue depth which measures the extent of burial of a residue. As the residue depths in the native structure correlated well (r = 0.6) with the RankScores, the residue depths in native-like models would also correlate well with RankScores. Based on this principle, native-like models could be distinguished from low quality decoys. In the analysis reported in chapter 7, we examine this methodology using decoy datasets for ~200 proteins. We also consider additional information like predicted secondary structure and model quality score to achieve better model discrimination. Studies thus far describe analyses performed using single protein mutants. Furthermore, information about residue interactions is also important. During the course of evolution, as the maintenance of specific interactions is essential for protein function, residues participating in such interactions are either conserved or varied in a correlated manner. Several computational models analysing such correlations among mutations are available. Experimental techniques are also available for identification of the spatially proximal residues. In chapter 8, we analyse various computational programs using CcdB and Diacylglycerol kinase A (DgkA) proteins and the results are then compared with the available experimental data. Overall little overlap was observed between the predictions based on the natural sequence co-variation and the experimental data. Both the computational and experimental approaches can be applied in conjugation as they provide complementary information. The analyses described in the current work would provide useful guidelines for rational design of mutations to modulate protein stability. This has important implications in immunogen designing. The tools developed as part of the current work can be applied for (i) rational designing of Ts mutants, (ii) the analysis of site saturation libraries, (iii) calculation or prediction of substitution preferences, (iv) structure prediction using correlated mutations as constraints, or (v) protein model discrimination. A small appendix section is also included in the thesis. Synonymous mutations with differential phenotypes were observed in our deep sequenced library. In order to analyse them further, we performed a multiple sequence alignment and analysed codon frequencies at different positions. However, only preliminary results are available and those are included in Appendix I section of this thesis.

The prediction of time series has gained increasingly more attention among researchers since it is a crucial aspect of decision-making activities. Unfortunately, most time series prediction methods assume the property of stationarity, i.e., statistical properties do not change over time. In practice, it is the exception and not the rule in most real datasets. Several transformation methods were designed to treat nonstationarity in time series. In this context, nonstationary time series prediction is challenging since it demands knowledge of both data transformation and prediction methods. Since there are no silver bullets, it leads to exploring a large number of data transformation and prediction method combinations for building prediction setups. However, selecting a prediction setup that is appropriate to a particular time series and application is not a simple task. Benchmarking of different candidate combinations helps this selection. This work contributes by providing a review and experimental analysis of transformation methods and a systematic framework (TSPred) for benchmarking and selecting prediction setups for nonstationary time series. Suitable nonstationary time series transformation methods provided improvements of more than 30% in prediction accuracy for half of the evaluated time series. They improved the prediction by more than 95% for 10% of the time series. The features provided by TSPred are also shown to be competitive regarding prediction accuracy. Furthermore, the adoption of a validation phase during model training enables the selection of suitable transformation methods.