Miracle-dz/UniFAR-FTUs huggingface dataset:
Translational read-through inducing drugs for the treatment of inherited 1 retinal dystrophies

4 Introduction: 5 Inherited retinal disorders (IRDs) are the most common cause of certifiable blindness in 6 working age adults in the UK. There are currently no treatments for the majority of patients, 7 resulting in considerable morbidity with lifelong socioeconomic implications. 12% of all 8 genetic disease variants are nonsense mutations, which encode a premature termination 9 codon (PTC). The resultant transcript is either degraded through nonsense mediated decay 10 (NMD) or translated to produce a truncated protein. Nonsense suppression therapy aims to 11 bypass and allow peptide synthesis beyond the PTC, creating a full-length protein and 12 possible phenotypic rescue. The responsible agents, known as translational readthrough 13 inducing drugs (TRIDs), have been in continuous development to maximise readthrough 14 efficiency and minimise toxicity. These include aminoglycosides, aminoglycoside derivatives 15 and non-aminoglycoside small molecule drugs and have been successfully applied to a 16 number of disease models in recent preclinical studies. 17 18 Areas Covered: 19 This review provides an update in the advancements of nonsense suppression therapy in the 20 treatment of IRDs, including an overview of this process and NMD, advancements in the 21 development of TRIDs and barriers to clinical trials including drug developments, disease 22 modelling and patient selection. 23 24 Expert Opinion: 25 Clinical trials are forthcoming for patients with IRDs to determine TRID suitability as a 26 viable therapy option. 27 28 29
C Consiglio Nazionale delle Ricerche Link analysis of the Web

Inlinks to a page of the web are often used as indicators of the authority of the page, because it is commonly felt that if a page is linked from many other pages it is worth looking at. According to a widely accepted model, the inlinks follow a power law. Outlinking analysis, on the contrary, has received less attention. Nevertheless, the outlink structure should be included in the description of the web graph and used for designing and testing the algorithms for the real web. The power law has been proposed also for the outlinks, but the experimental observation has shown that the distribution of the pages with a low number of outlinks is not well modeled by the power law. In this paper we propose a linking model based on a preferential attachment strategy and a uniform attachment strategy. Similar models have already been considered in the literature. The substantial novelty of our approach on the previous ones concerns the approximation technique applied to the steady state so-lution. With this technique the model appears to be well suited for describing both inlink and outlink distributions. The experimentation on two subsets of the real web shows that the two attachment strategies play a diﬀerent role in the inlink and the outlink case.
Family Impact of Children with Autism and Asperger Syndrome: A Case for Attention and Intervention

This paper examined the impact of families living with young children (n = 15) with High Functioning Autism (HFA) and Asperger Syndrome (AS). A mixed-methodology design investigated parent perspectives and emerging themes encompassing the diagnostic process, the impact of child characteristics, accessing services, and parental concerns for the future. Results indicated that families experienced both positive and negative impact of having a child with HFA/AS; externalizing behaviours correlated negatively with positive family impact, r (13) = . 69, p < . 01. Findings have implications for medical professionals, families, and community partners in reference to providing effective resources for families experiencing HFA/AS.
Magnetometer Aided Navigation Filters for Improved Observability and Estimation on Ground Vehicles

Two modified extended Kalman filters, called the MGVA and MVVA filters, have been developed which combine the attitude determination capabilities of magnetometers with the standard extended Kalman filter. The standard extended Kalman filter is known to experience observability problems during driving which does not provide enough excitation to its sensors. The MGVA and MVVA filters attempt to remedy these problems by providing an attitude solution to the filter, via a process that utilizes magnetometer measurements. In order to show the e↵ectiveness of the MGVA and MVVA filters, the filters were tested both in simulation, and experimentally for low excitation trajectories. It is shown in simulation that the two filters are able to improve attitude and accelerometer bias estimation in situations where the standard filter experiences estimation error. In addition to this, it is shown that both modified filters increase the observability rank of the system such that it is full rank. Experimental testing of the two modified filters reveals that both the MGVA and MVVA filters provide improved attitude and accelerometer bias estimation during low-excitation trajectories. The MGVA and MVVA filters are also compared to a heading constrained filter that has been studied in the past. It is shown that the heading constrained filter produces more accurate estimates of heading than both of the modified filters. As a result, a further modification is implemented on both the MGVA and MVVA filters, and improved performance is shown for the MGVA filter. Finally, the MGVA and MVVA filters were tested on both simulated and experimental dynamic trajectories. This was done in order to test whether or not the filters are useful under typical trajectories that a ground vehicle might drive, not just low excitation trajectories. It is shown that under these circumstances the MGVA filter is su↵ers from the increased vehicle dynamics. In contrast, it is also shown that the MVVA
Evolutionary decision forests – decision making with multiple evolutionary constructed decision trees

Decision support systems that help experts are becoming very important part in virtually any field of expertise. They are based on different models and the best of them are providing an explanation together with an accurate and reliable response. One of the most viable among models are decision trees. Although effective and reliable, the traditional decision tree construction approach contains several deficiencies, one of the most important is their somewhat lower classification accuracy. Therefore, we decided to develop new approach to decision making using decision trees – decision forests. In the paper we present a self-adapting evolutionary algorithm for the induction of decision trees and describe the principle of decision making based on multiple evolutionary induced decision trees. The developed model is used as a fault predictive approach to foresee dangerous software modules, which identification can largely enhance the reliability of software. Key-Words: decision making, decision trees, decision forests, evolutionary algorithms
How Digitalised Innovation Environments Impact Companies' How Digitalised Innovation Environments Impact Companies' Innovation Capability - a Review and research Agenda Innovation Capability - a Review and research Agenda

The aim of this paper is to structure the diverse investigations into various Digitalized Innovation Environments (DIE) such as FabLabs, Makerspaces, and Innovation Laboratories and to identify the resulting potential for companies. In private and academic contexts, DIEs are already established as environments for fostering innovation and knowledge transfer. Taking into account a wide range of disciplines and perspectives, a total of four functions were identified that DIEs can potentially assume in companies. Based on this, both direct and indirect impacts could be derived and resulting research gaps were identified. These blind spots are supplemented by research questions on the structural integration of DIEs in companies. Thus, the paper provides an overview of the current state of research and reveals relevant research gaps, which contribute to a future structured investigation of the research subject DIE.
Wnet: Audio-Guided Video Object Segmentation via Wavelet-Based Cross- Modal Denoising Networks

Audio-Guided video object segmentation is a challenging problem in visual analysis and editing, which automatically separates foreground objects from the background in a video sequence according to the referring audio expressions. However, existing referring video object segmentation works mainly focus on the guidance of text-based referring expressions, due to the lack of modeling the semantic representations of audio-video interaction contents. In this paper, we consider the problem of audio-guided video semantic segmentation from the viewpoint of end-to-end denoising encoder-decoder network learning. We propose the wavelet-based encoder network to learn the cross-modal representations of the video contents with audio-form queries. Specifically, we adopt the multi-head cross-modal attention layers to explore the potential relations of video and query contents. A 2-dimension discrete wavelet trans-form is merged into the transformer encoder to decompose the audio-video features. Next, we maximize mutual information between the encoded features and multi-modal features after cross-modal attention layers to enhance the au-dio guidance. Then, a self attention-free decoder network is developed to generate the target masks with frequency-domain transforms. In addition, we construct the first large-scale audio-guided video semantic segmentation dataset. The extensive experiments show the effectiveness of our method11Code is available at: https://github.com/asudahkzj/Wnet.git.
Poor household participation in payments for environmental services in Nicaragua and Colombia

We evaluate the extent to which poor households are able to participate in Payments for Environmental Services (PES) scheme using data from a PES scheme implemented at two sites in Latin America. This allows us to compare environmental and livelihood impacts of PES across regions with different agronomic and socio-economic characteristics. In particular, one of our sites is composed almost entirely of poor or extremely poor households, while the other has households ranging from extremely poor to very well off. The results show that poorer households are in fact able to participate—indeed, by some measures they participated to a greater extent than better-off households. Moreover, their participation was not limited to the simpler, least expensive options. Extremely poor households had a somewhat greater difficulty in participating, but even in their case the difference is solely a relative one. Transaction costs may be greater obstacles to the participation of poorer households than household-specific constraints.
Accounting for variety Winkler, Julian

I introduce a general method to account for the distribution of underlying components (variety) of an aggregate quantity, using the notion of entropy. This accounting decomposition enables a number of insightful applications for index numbers in economics. The cross-entropy of GDP with respect to a benchmark captures the change in its distribution, and thus how well this benchmark matches data for price and volume indices across time. This ‘error’ changes demonstrably over time. Accounting of variety also lends itself to an decomposition of labour productivity growth by a technology component (how many more ‘average’ goods are produced per unit of labor? ), an allocation component (does the distribution of labor inputs converge to the distribution of outputs? ), and cost disease (does the distribution of expenditures diverge from the distribution of outputs? ).
LTP: Lane-based Trajectory Prediction for Autonomous Driving

The reasonable trajectory prediction of surrounding traf-fic participants is crucial for autonomous driving. Espe-cially, how to predict multiple plausible trajectories is still a challenging problem because of the multiple possibilities of the future. Proposal-based prediction methods address the multi-modality issues with a two-stage approach, com-monly using intention classification followed by motion re-gression. This paper proposes a two-stage proposal-based motion forecasting method that exploits the sliced lane seg-ments as fine-grained, shareable, and interpretable propos-als. We use Graph neural network and Transformer to en-code the shape and interaction information among the map sub-graphs and the agents sub-graphs. In addition, we propose a variance-based non-maximum suppression strategy to select representative trajectories that ensure the diversity of the final output. Experiments on the Argoverse dataset show that the proposed method outperforms state-of-the-art methods, and the lane segments-based proposals as well as the variance-based non-maximum suppression strategy both contribute to the performance improvement. More-over, we demonstrate that the proposed method can achieve reliable performance with a lower collision rate and fewer off-road scenarios in the closed-loop simulation.
Local Transformer Linear Linear Linear ��� Scaled dot-product attention

Figure 8. We propose a strong sequential module, i.e., Local Transformer (LT), which is used in the VLT backbone. It is built based on QANet [14], which validates the effectiveness of combining TCNs with self-attention, and the difference is that we further leverage Gaussian bias [5, 13] to introduce local contexts to the self-attention module, i.e., Local Self-attention (LSA). (L: the number of LT layers, we set it to 2 as default; RPE: relative positional encoding [10]; D: the window size of the Gaussian bias.)
Towards a feminist logic: Val Plumwood’s legacy and beyond

Val Plumwood’s 1993 paper, “The politics of reason: towards a feminist logic” (henceforth POR) attempted to set the stage for what she hoped would begin serious feminist exploration into formal logic – not merely its historical abuses, but, more importantly, its potential uses. This work offers us: (1) a case for there being feminist logic; and (2) a sketch of what it should resemble. The former goal of Plumwood’s paper encourages feminist theorists to reject anti-logic feminist views. The paper’s latter aim is even more challenging. Plumwood’s critique of classical negation (and classical logic) as a logic of domination asks us to recognize that particular logical systems are weapons of oppression. Against anti-logic feminist theorists, Plumwood argues that there are other logics besides classical logic, such as relevant logics, which are suited for feminist theorizing. Some logics may oppress while others may liberate. We provide details about the sources and context for her rejection of classical logic and motivation for promoting relevant logics as feminist.
A Performance and Reliability Analysis of Cross-Layer Optimizations of NAND Flash Controllers

NAND ﬂash memories are becoming the predominant technology in the implementation of mass storage systems for both embedded and high-performance applications. However, when considering data and code storage in non-volatile memories (NVMs), such as NAND ﬂash memories, reliability and performance become a serious concern for systems’ designer. Designing NAND ﬂash based systems based on worst-case scenarios leads to waste of resources in terms of performance, power consumption, and storage capacity. This is clearly in contrast with the request for run-time reconﬁgurability, adaptivity, and resource optimization in nowadays computing systems. There is a clear trend toward supporting differentiated access modes in ﬂash memory controllers, each one setting a differentiated trade-off point in the performance-reliability optimization space. This is supported by the possibility of tuning the NAND ﬂash memory performance, reliability and power consumption acting on several tuning knobs such as the ﬂash programming algorithm and the ﬂash error correcting code. However, to successfully exploit these degrees of freedom, it is mandatory to clearly understand the effect the combined tuning of these parameters have on the full NVM sub-system. This paper performs a comprehensive quantitative analysis of the beneﬁts provided by the run-time reconﬁgurability of an MLC NAND ﬂash controller through the combined effect of an adaptable memory programming circuitry coupled with run-time adaptation of the ECC correction capability. The full non-volatile memory (NVM) sub-system is taken into account, starting from the characterization of the low level circuitry to the effect of the adaptation on a wide set of realistic benchmarks in order to provide the readers a clear ﬁgure of the beneﬁt this combined adaptation would provide at the system level.
A Survey of Precision Formation Relative State Measurement Technology for Distributed Spacecraft

: High-precision relative-state measurement technology is one of the key technologies for achieving the precision formation ﬂying of distributed spacecraft. This paper conducts a comprehensive analysis of the precision formation-ﬂying projects of distributed spacecraft in various countries. In the context of practical application, the speciﬁc mission conﬁguration, orbit distribution, measurement technology, and payload of the project are summarized. On this basis, the relative state measurement techniques are outlined for the ﬁrst time, using non-autonomous measurement techniques, autonomous measurement techniques, and new composite relative measurement techniques. A detailed analysis of GNSS (Global Navigation Satellite System)—relative measurement, laser measurement, infrared measurement, RF measurement, visible light visual measurement, and multiple composite measurement methods is conducted. The applicable scenarios of each measurement method are thoroughly discussed from several aspects, such as the technical scheme, system design, accuracy requirements, advantages, and shortcomings. In addition, this paper proposes the concept of adopting a multidisciplinary optimization architecture from the perspective of the overall design of the precision formation of the distributed spacecraft. It enables relative-state measurement payload selection and property indicator optimization, on the premise of optimizing the overall formation performance. Finally, the optimization direction and future development trend of the spacecraft precision formation ﬂight project and relative state measurement technology are established.
A Modal Logic for Gödelian Intuition

This essay aims to provide a modal logic for rational intuition. Similarly to treatments of the property of knowledge in epistemic logic, I argue that rational intuition can be codiﬁed by a modal operator governed by the axioms of a dynamic provability logic, which embeds GL within the modal µ -calculus. Via correspondence results between modal logic and the bisimulation-invariant fragment of second-order logic, a precise translation can then be provided between the notion of ’intuition-of’, i.e., the cognitive phenomenal properties of thoughts, and the modal operators regimenting the notion of ’intuition-that’. I argue that intuition-that can further be shown to entrain conceptual elucidation, by way of ﬁguring as a dynamic-interpretational modality which induces the reinterpretation of both domains of quantiﬁcation and the intensions and hyperintensions of mathematical concepts that are formalizable in monadic ﬁrst-and second-order formal languages. Hyperintensionality is countenanced via four models, without a decision as to which model is to be preferred. The ﬁrst model makes intuition sensitive to hyperintensional topics, i.e. subject matters. The second model is a hyperintensional truthmaker semantics, in particular a novel epistemic two-dimensional truthmaker semantics. The third model is a topic-sensitive non-truthmaker epistemic two-dimensional semantics. The fourth model is a topic-sensitive epistemic two-dimensional truthmaker semantics.
Finding a Needle in a Haystack: A Novel Log Analysis Method with Test Clustering in Distributed Systems

- As the diversity and the complexity in digital design increases, the cost of design verification also increases. In such a trend, verification engineers are struggling with repetitive and tedious process, such as debugging common errors from different test cases. To solve this problem, verification engineers can use their own domain knowledge to prioritize test cases to find different errors, however, it takes time and efforts to do it manually. It is also not so easy tasks to understand different designs and test benches with limited time and resources. In this paper, we propose a novel approach of a test case prioritization algorithm based on clustering. Components from terabytes of simulation logs are considered as features in clustering algorithms. After clustering, the proposed algorithm reorders test cases with priority and recommends test cases that allow verification engineers to achieve a specific rate of error detection as early as possible. We also propose robust and scalable system architecture that can handle terabytes of data for practical use in design verification industry.
This paper is included in the Proceedings of the 2022 USENIX Annual Technical Conference.

Over the past two decades, the number of RFCs related to email and its security has exploded from below 100 to nearly 500. This embedded the Simple Mail Transfer Protocol (SMTP) into a tree of interdependent and delivery-relevant standards. In this paper, we investigate how far real-world deployments keep up with this increasing complexity of delivery-and security options. To gain an in-depth picture of email delivery apart from the giants in the ecosystem (Gmail, Outlook, etc.), we engage people to send emails to eleven differently configured target domains. Our measurements allow us to evaluate core aspects of email delivery, including security features, DNS configuration, and IP version support on the sending side across different types of providers. We find that novel technologies are often insufficiently supported, even by large providers. For example, while 65.4% of email providers can resolve hosts via IPv6, only 44.3% can also deliver emails via IPv6. Concerning security features, we observe that less than half (41.5%) of all providers rely on DNSSEC validating resolvers, and encryption is mostly opportunistic, with 89.7% of providers accepting invalid certificates. TLSA, as a DNS-based certificate verification method, is only used by 31.7% of the providers in our study. Finally, we turned our eye to the impact modern standards have on unsolicited bulk email (SPAM). We found that greylisting is effective, reducing the SPAM volume by roughly half while not impacting regular delivery. However, and interestingly, SPAM delivery currently seems to focus on plaintext IPv4 connections, making IPv6-only, TLS-enforcing inbound email servers a more effective anti-SPAM measure—even though it also means rejecting a major portion of legitimate emails.