25,186 research outputs found
Towards Advantages of Parameterized Quantum Pulses
The advantages of quantum pulses over quantum gates have attracted increasing
attention from researchers. Quantum pulses offer benefits such as flexibility,
high fidelity, scalability, and real-time tuning. However, while there are
established workflows and processes to evaluate the performance of quantum
gates, there has been limited research on profiling parameterized pulses and
providing guidance for pulse circuit design. To address this gap, our study
proposes a set of design spaces for parameterized pulses, evaluating these
pulses based on metrics such as expressivity, entanglement capability, and
effective parameter dimension. Using these design spaces, we demonstrate the
advantages of parameterized pulses over gate circuits in the aspect of duration
and performance at the same time thus enabling high-performance quantum
computing. Our proposed design space for parameterized pulse circuits has shown
promising results in quantum chemistry benchmarks.Comment: 11 Figures, 4 Table
The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions
The Metaverse offers a second world beyond reality, where boundaries are
non-existent, and possibilities are endless through engagement and immersive
experiences using the virtual reality (VR) technology. Many disciplines can
benefit from the advancement of the Metaverse when accurately developed,
including the fields of technology, gaming, education, art, and culture.
Nevertheless, developing the Metaverse environment to its full potential is an
ambiguous task that needs proper guidance and directions. Existing surveys on
the Metaverse focus only on a specific aspect and discipline of the Metaverse
and lack a holistic view of the entire process. To this end, a more holistic,
multi-disciplinary, in-depth, and academic and industry-oriented review is
required to provide a thorough study of the Metaverse development pipeline. To
address these issues, we present in this survey a novel multi-layered pipeline
ecosystem composed of (1) the Metaverse computing, networking, communications
and hardware infrastructure, (2) environment digitization, and (3) user
interactions. For every layer, we discuss the components that detail the steps
of its development. Also, for each of these components, we examine the impact
of a set of enabling technologies and empowering domains (e.g., Artificial
Intelligence, Security & Privacy, Blockchain, Business, Ethics, and Social) on
its advancement. In addition, we explain the importance of these technologies
to support decentralization, interoperability, user experiences, interactions,
and monetization. Our presented study highlights the existing challenges for
each component, followed by research directions and potential solutions. To the
best of our knowledge, this survey is the most comprehensive and allows users,
scholars, and entrepreneurs to get an in-depth understanding of the Metaverse
ecosystem to find their opportunities and potentials for contribution
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Food Security Under a Changing Climate: Exploring the Integration of Resilience in Research and Practice
Climate change poses significant risks to our food systems, thus jeopardising the food security of millions of people worldwide. The concept of resilience is increasingly being proposed as a framework to find solutions to these challenges. In this chapter, we assess how resilience has been integrated in discussions about climate change and food security by both academics and practitioners. We performed a targeted review of the academic literature on climate change, food security, and resilience and found that despite a growing body of literature on the subject, the pathways through which actions translate into resilience and then into food security remain unclear. An examination of a sample of projects implemented through the Adaptation Fund revealed that many good practices with potential for resilience-building are used but also that suitable indicators and methods to monitor and evaluate resilience and its outcomes are lacking. Based on our findings, we conclude that while the concept of resilience has accompanied and may have favoured a transition towards more integrated approaches and interventions in work related to climate change and food security, further efforts are needed to identify an efficient and rational sequence of interventions to improve food security in response to climate threats
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Ensuring Access to Safe and Nutritious Food for All Through the Transformation of Food Systems
Barren plateaus in quantum tensor network optimization
We analyze the barren plateau phenomenon in the variational optimization of quantum circuits inspired by matrix product states (qMPS), tree tensor networks (qTTN), and the multiscale entanglement renormalization ansatz (qMERA). We consider as the cost function the expectation value of a Hamiltonian that is a sum of local terms. For randomly chosen variational parameters we show that the variance of the cost function gradient decreases exponentially with the distance of a Hamiltonian term from the canonical centre in the quantum tensor network. Therefore, as a function of qubit count, for qMPS most gradient variances decrease exponentially and for qTTN as well as qMERA they decrease polynomially. We also show that the calculation of these gradients is exponentially more efficient on a classical computer than on a quantum computer
Application of Multichannel Active Vibration Control in a Multistage Gear Transmission System
Gears are the most important parts of rotating machinery and power transmission devices. When gears are engaged in meshing transmission, vibration will occur due to factors such as gear machining errors, meshing rigidity, and meshing impact. The traditional FxLMS algorithm, as a common active vibration algorithm, has been widely studied and applied in gear transmission system active vibration control in recent years. However, it is difficult to achieve good performance in convergence speed and convergence precision at the same time. This paper proposes a variable-step-size multichannel FxLMS algorithm based on the sampling function, which accelerates the convergence speed in the initial stage of iteration, improves the convergence accuracy in the steady-state adaptive stage, and makes the modified algorithm more robust. Simulations verify the effectiveness of the algorithm. An experimental platform for active vibration control of the secondary gear transmission system is built. A piezoelectric actuator is installed on an additional gear shaft to form an active structure and equipped with a signal acquisition system and a control system; the proposed variable-step-size multichannel FxLMS algorithm is experimentally verified. The experimental results show that the proposed multichannel variable-step-size FxLMS algorithm has more accurate convergence accuracy than the traditional FxLMS algorithm, and the convergence accuracy can be increased up to 123%
Consent and the Construction of the Volunteer: Institutional Settings of Experimental Research on Human Beings in Britain during the Cold War
This study challenges the primacy of consent in the history of human experimentation and argues that privileging the cultural frameworks adds nuance to our understanding of the construction of the volunteer in the period 1945 to 1970. Historians and bio-ethicists have argued that medical ethics codes have marked out the parameters of using people as subjects in medical scientific research and that the consent of the subjects was fundamental to their status as volunteers. However, the temporality of the creation of medical ethics codes means that they need to be understood within their historical context. That medical ethics codes arose from a specific historical context rather than a concerted and conscious determination to safeguard the well-being of subjects needs to be acknowledged. The British context of human experimentation is under-researched and there has been even less focus on the cultural frameworks within which experiments took place. This study demonstrates, through a close analysis of the Medical Research Council's Common Cold Research Unit (CCRU) and the government's military research facility, the Chemical Defence Experimental Establishment, Porton Down (Porton), that the `volunteer' in human experiments was a subjective entity whose identity was specific to the institution which recruited and made use of the subject. By examining representations of volunteers in the British press, the rhetoric of the government's collectivist agenda becomes evident and this fed into the institutional construction of the volunteer at the CCRU. In contrast, discussions between Porton scientists, staff members, and government officials demonstrate that the use of military personnel in secret chemical warfare experiments was far more complex. Conflicting interests of the military, the government and the scientific imperative affected how the military volunteer was perceived
Data-to-text generation with neural planning
In this thesis, we consider the task of data-to-text generation, which takes non-linguistic
structures as input and produces textual output. The inputs can take the form of
database tables, spreadsheets, charts, and so on. The main application of data-to-text
generation is to present information in a textual format which makes it accessible to
a layperson who may otherwise find it problematic to understand numerical figures.
The task can also automate routine document generation jobs, thus improving human
efficiency. We focus on generating long-form text, i.e., documents with multiple paragraphs. Recent approaches to data-to-text generation have adopted the very successful
encoder-decoder architecture or its variants. These models generate fluent (but often
imprecise) text and perform quite poorly at selecting appropriate content and ordering
it coherently. This thesis focuses on overcoming these issues by integrating content
planning with neural models. We hypothesize data-to-text generation will benefit from
explicit planning, which manifests itself in (a) micro planning, (b) latent entity planning, and (c) macro planning. Throughout this thesis, we assume the input to our
generator are tables (with records) in the sports domain. And the output are summaries
describing what happened in the game (e.g., who won/lost, ..., scored, etc.).
We first describe our work on integrating fine-grained or micro plans with data-to-text generation. As part of this, we generate a micro plan highlighting which records
should be mentioned and in which order, and then generate the document while taking
the micro plan into account.
We then show how data-to-text generation can benefit from higher level latent entity planning. Here, we make use of entity-specific representations which are dynam ically updated. The text is generated conditioned on entity representations and the
records corresponding to the entities by using hierarchical attention at each time step.
We then combine planning with the high level organization of entities, events, and
their interactions. Such coarse-grained macro plans are learnt from data and given
as input to the generator. Finally, we present work on making macro plans latent
while incrementally generating a document paragraph by paragraph. We infer latent
plans sequentially with a structured variational model while interleaving the steps of
planning and generation. Text is generated by conditioning on previous variational
decisions and previously generated text.
Overall our results show that planning makes data-to-text generation more interpretable, improves the factuality and coherence of the generated documents and re duces redundancy in the output document
Proof of Concept of Therapeutic Gene Modulation of MBNL1/2 in Myotonic Dystrophy
La distrofia miotónica tipo 1 es una enfermedad genética rara multisistémica que afecta a 1 de cada 3000-8000 personas. La causa molecular de la enfermedad proviene de repeticiones tóxicas “CTG” en el gen DMPK (DM Protein Kinase). Tras la transcripción, estas repeticiones forman una estructura de horquilla que se une con alta afinidad a la familia de proteínas MBNL (Muscleblind-like) que agota su función de regulación de la poliadenilación y el splicing alternativo postranscripcional en numerosos transcritos. La pérdida de función de MBNL provoca una cascada de efectos posteriores, que eventualmente conducen a síntomas clínicos que incluyen miotonía, debilidad y atrofia muscular, cataratas, disfunción cardíaca y trastorno cognitivo. La restauración de la función de la proteína MBNL es clave para aliviar los síntomas debilitantes de esta enfermedad. Se han utilizado oligonucleótidos antisentido (AON) para apuntar a las repeticiones de DMPK y liberar MBNL del secuestro, lo que da como resultado resultados terapéuticos prometedores en modelos celulares y animales de la enfermedad. Otro factor que interviene en la pérdida de función de las proteínas MBNL son los miRNAs que regulan su traducción. Aquí se muestra el uso de AON dirigidos a la actividad de miR-23b y miR-218, que se ha demostrado previamente que regulan directamente MBNL1 y MBNL2. Estos antimiRs recibieron modificaciones FANA para aumentar su entrega en las células y reducir la toxicidad. También se probaron los AON, denominados blockmiRs, que se unen de manera complementaria a los sitios de unión confirmados de miR-23b y miR-218 en los 3'-UTR de las transcripciones de MBNL1 y MBNL2. De esta manera, los miRNAs no pueden unirse y regular la traducción de MBNL, lo que aumenta la cantidad de proteína MBNL producida en una célula deficiente. Aquí se propone el uso de AON de nuevo diseño dirigidos a la actividad de miR-23b y miR-218 para regular MBNL1 y MBNL2 a través de (1) exploración del bloqueo de miRNA a través de FANA-antimiR AON in vitro, (2) exploración del bloqueo del sitio de unión de miRNA a través de la estrategia blockmiR in vitro e in vivo con el uso de modificaciones químicas de LNA, y (3) mejora de la química de la estrategia blockmiR mediante el uso de tecnología de péptidos de penetración celular in vitro e in vivo.Myotonic Dystrophy Type 1 is a multi-systemic rare genetic disease affecting 1 in 3000-8000 people. The molecular cause of the disease stems from toxic “CTG” repetitions in the DMPK (DM Protein Kinase) gene. Upon transcription, these repetitions form a hairpin structure that binds with high affinity to the MBNL (Muscleblind-like) family of proteins depleting their function of post-transcriptional alternative splicing and polyadenylation regulation on numerous transcripts. MBNL loss-of-function causes a cascade of downstream effects, which eventually lead to clinical symptoms including myotonia, muscle weakness and atrophy, cataracts, cardiac dysfunction, and cognitive disorder. The restoration of MBNL protein function is key to relieving the debilitating symptoms of this disease. Antisense oligonucleotides (AONs) have been used to target the DMPK repeats and release MBNL from sequestration resulting in promising therapeutic results in cellular and animal models of the disease. Another factor playing a role in the loss-of-function of MBNL proteins are the miRNAs that regulate their translation. Here is shown the use of AONs targeting miR-23b and miR-218 activity, which have been previously shown to directly regulate MBNL1 and MBNL2. These antimiRs were given FANA modifications to increase their delivery in cells and lower toxicity. Also tested are AONs, termed blockmiRs, that complementary bind to the confirmed binding sites of miR-23b and miR-218 in the 3’-UTRs of MBNL1 and MBNL2 transcripts. In this way, the miRNAs are unable to bind and regulate the translation of MBNL thereby augmenting the amount of MBNL protein made in an otherwise deficient cell. Proposed here is the use of newly designed AONs targeting miR-23b and miR-218 activity in order to regulate MBNL1 and MBNL2 through (1) exploration of miRNA blocking through FANA-antimiR AONs in vitro, (2) exploration of miRNA binding site blocking through blockmiR strategy in vitro and in vivo with the use of LNA chemical modifications, and (3) improvement of the chemistry of the blockmiR strategy through the use of cell penetrating peptide technology in vitro and in vivo
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