115 research outputs found
Understanding Quantum Technologies 2022
Understanding Quantum Technologies 2022 is a creative-commons ebook that
provides a unique 360 degrees overview of quantum technologies from science and
technology to geopolitical and societal issues. It covers quantum physics
history, quantum physics 101, gate-based quantum computing, quantum computing
engineering (including quantum error corrections and quantum computing
energetics), quantum computing hardware (all qubit types, including quantum
annealing and quantum simulation paradigms, history, science, research,
implementation and vendors), quantum enabling technologies (cryogenics, control
electronics, photonics, components fabs, raw materials), quantum computing
algorithms, software development tools and use cases, unconventional computing
(potential alternatives to quantum and classical computing), quantum
telecommunications and cryptography, quantum sensing, quantum technologies
around the world, quantum technologies societal impact and even quantum fake
sciences. The main audience are computer science engineers, developers and IT
specialists as well as quantum scientists and students who want to acquire a
global view of how quantum technologies work, and particularly quantum
computing. This version is an extensive update to the 2021 edition published in
October 2021.Comment: 1132 pages, 920 figures, Letter forma
Principles of Massively Parallel Sequencing for Engineering and Characterizing Gene Delivery
The advent of massively parallel sequencing and synthesis technologies have ushered in a new paradigm of biology, where high throughput screening of billions of nucleid acid molecules and production of libraries of millions of genetic mutants are now routine in labs and clinics. During my Ph.D., I worked to develop data analysis and experimental methods that take advantage of the scale of this data, while making the minimal assumptions necessary for deriving value from their application. My Ph.D. work began with the development of software and principles for analyzing deep mutational scanning data of libraries of engineered AAV capsids. By looking at not only the top variant in a round of directed evolution, but instead a broad distribution of the variants and their phenotypes, we were able to identify AAV variants with enhanced ability to transduce specific cells in the brain after intravenous injection. I then shifted to better understand the phenotypic profile of these engineered variants. To that end, I turned to single-cell RNA sequencing to seek to identify, with high resolution, the delivery profile of these variants in all cell types present in the cortex of a mouse brain. I began by developing infrastructure and tools for dealing with the data analysis demands of these experiments. Then, by delivering an engineered variant to the animal, I was able to use the single-cell RNA sequencing profile, coupled with a sequencing readout of the delivered genetic cargo present in each cell type, to define the variant’s tropism across the full spectrum of cell types in a single step. To increase the throughput of this experimental paradigm, I then worked to develop a multiplexing strategy for delivering up to 7 engineered variants in a single animal, and obtain the same high resolution readout for each variant in a single experiment. Finally, to take a step towards translation to human diagnostics, I leveraged the tools I built for scaling single-cell RNA sequencing studies and worked to develop a protocol for obtaining single-cell immune profiles of low volumes of self-collected blood. This study enabled repeat sampling in a short period of time, and revealed an incredible richness in individual variability and time-of-day dependence of human immune gene expression. Together, my Ph.D. work provides strategies for employing massively parallel sequencing and synthesis for new biological applications, and builds towards a future paradigm where personalized, high-resolution sequencing might be coupled with modular, customized gene therapy delivery.</p
Villages et quartiers à risque d’abandon
The issue of villages and neighborhoods at risk of abandonment is a common topic in many Mediterranean regions and is considered as a strategic point of the new European policies. The progressive abandonment of inland areas, with phenomena of emigration and fragmentation of cultural heritage, is a common trend in countries characterized by economic underdevelopment. This leads to the decay of architectural artifacts and buildings and problems with land management. Some aspects of this issue are also found in several urban areas. The goal of this research work is collecting international debates, discussions, opinions and comparisons concerning the analysis, study, surveys, diagnoses and graphical rendering of architectural heritage and landscape as well as demo-ethno-anthropological witnesses, typological-constructive stratifications, materials and technologies of traditional and vernacular constructions of historic buildings
Advances in Parvovirus Research 2020
Viruses of the Parvoviridae family constitute a most diverse and intriguing field of research. Parvoviruses can differ widely in their structure, genome organization and expression, virus–cell interactions, and impact on hosts. The translational implication of research on parvoviruses is relevant, since many viruses are important human and veterinary pathogens, while other viruses can be engineered as tools for oncolytic therapy or as sophisticated gene delivery vectors. Exploring the diversity and inherent complexity in the biology of these apparently simple viruses is a still challenging topic for the scientific community. The Special Issue of Viruses is a collection of recent contributions in the field of parvovirus research, encompassing many aspects of basic and translational research on viruses of the family Parvoviridae, including on their structure, replication, and gene expression in addition to virus–host interactions and the development of vaccines and viral vectors
Assuming Data Integrity and Empirical Evidence to The Contrary
Background: Not all respondents to surveys apply their minds or understand
the posed questions, and as such provide answers which lack coherence, and
this threatens the integrity of the research. Casual inspection and limited
research of the 10-item Big Five Inventory (BFI-10), included in the dataset of
the World Values Survey (WVS), suggested that random responses may be
common.
Objective: To specify the percentage of cases in the BRI-10 which include
incoherent or contradictory responses and to test the extent to which the
removal of these cases will improve the quality of the dataset.
Method: The WVS data on the BFI-10, measuring the Big Five Personality (B5P), in South Africa (N=3 531), was used. Incoherent or contradictory responses were removed. Then the cases from the cleaned-up dataset were analysed for their theoretical validity.
Results: Only 1 612 (45.7%) cases were identified as not including incoherent
or contradictory responses. The cleaned-up data did not mirror the B5P- structure, as was envisaged. The test for common method bias was negative. Conclusion: In most cases the responses were incoherent. Cleaning up the data did not improve the psychometric properties of the BFI-10. This raises concerns about the quality of the WVS data, the BFI-10, and the universality of B5P-theory. Given these results, it would be unwise to use the BFI-10 in South Africa. Researchers are alerted to do a proper assessment of the
psychometric properties of instruments before they use it, particularly in a
cross-cultural setting
Texture and Colour in Image Analysis
Research in colour and texture has experienced major changes in the last few years. This book presents some recent advances in the field, specifically in the theory and applications of colour texture analysis. This volume also features benchmarks, comparative evaluations and reviews
Bacillus thuringiensis Toxins: Functional Characterization and Mechanism of Action
Bacillus thuringiensis (Bt)-based products are the most successful microbial insecticides to date. This entomopathogenic bacterium produces different kinds of proteins whose specific toxicity has been shown against a wide range of insect orders, nematodes, mites, protozoa, and human cancer cells. Some of these proteins are accumulated in parasporal crystals during the sporulation phase (Cry and Cyt proteins), whereas other proteins are secreted in the vegetative phase of growth (Vip and Sip toxins). Currently, insecticidal proteins belonging to different groups (Cry and Vip3 proteins) are widely used to control insect pests and vectors both in formulated sprays and in transgenic crops (the so-called Bt crops). Despite the extensive use of these proteins in insect pest control, especially Cry and Vip3, their mode of action is not completely understood. The aim of this Special Issue was to gather information that could summarize (in the form of review papers) or expand (research papers) the knowledge of the structure and function of Bt proteins, as well as shed light on their mode of action, especially regarding the insect receptors. This subject has generated great interest, and this interest has been materialized into the 18 papers of important scientific value in the field (5 reviews and 13 research papers) that have been compiled in this issue
Drug development progress in duchenne muscular dystrophy
Duchenne muscular dystrophy (DMD) is a severe, progressive, and incurable X-linked disorder caused by mutations in the dystrophin gene. Patients with DMD have an absence of functional dystrophin protein, which results in chronic damage of muscle fibers during contraction, thus leading to deterioration of muscle quality and loss of muscle mass over time. Although there is currently no cure for DMD, improvements in treatment care and management could delay disease progression and improve quality of life, thereby prolonging life expectancy for these patients. Furthermore, active research efforts are ongoing to develop therapeutic strategies that target dystrophin deficiency, such as gene replacement therapies, exon skipping, and readthrough therapy, as well as strategies that target secondary pathology of DMD, such as novel anti-inflammatory compounds, myostatin inhibitors, and cardioprotective compounds. Furthermore, longitudinal modeling approaches have been used to characterize the progression of MRI and functional endpoints for predictive purposes to inform Go/No Go decisions in drug development. This review showcases approved drugs or drug candidates along their development paths and also provides information on primary endpoints and enrollment size of Ph2/3 and Ph3 trials in the DMD space
Automated recommendation, reuse, and generation of unit tests for software systems
This thesis presents a body of work relating to the automated discovery, reuse, and generation of unit tests for software systems with the goal of improving the efficiency of the software engineering process and the quality of the produced software.
We start with a novel approach to test-to-code traceability link establishment, called TCTracer, which utilises multilevel information and an ensemble of static and dynamic techniques to achieve state-of-the-art accuracy when establishing links between tests and tested functions and test classes and tested classes. This approach is utilised to provide test-to-code traceability links which facilitate multiple other parts of the work.
We then move on to test reuse where we first define an abstract framework, called Rashid, for using connections between artefacts to identify new artefacts for reuse and utilise this framework in Relatest, an approach for producing test recommendations for new functions. Relatest instantiates Rashid by using TCTracer to establish connections between tests and functions and code similarity measures to establish connections between similar functions. This information is used to create lists of recommendations for new functions.
We then present an investigation into the automated transplantation of tests which attempts to remove the manual effort required to transform Relatest recommendations and insert them into another project.
Finally, we move on to test generation where we utilise neural networks to generate unit test code by learning from existing function-to-test pairs. The first approach, TestNMT, investigates using recurrent neural networks to generate whole JUnit tests and the second approach, ReAssert, utilises a transformer-based architecture to generate JUnit asserts.
In total, this thesis addresses the problem by developing approaches for the discovery, reuse, and utilisation of existing functions and tests, including the establishment of relationships between these artefacts, developing mechanisms to aid automated test reuse and learning from existing tests to generate new tests
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