Miracle-dz/UniFAR-FTUs huggingface dataset:
Episodic Gaussian Process-Based Learning Control with Vanishing Tracking Errors

Due to the increasing complexity of technical systems, accurate first principle models can often not be obtained. Supervised machine learning can mitigate this issue by inferring models from measurement data. Gaussian process regression is particularly well suited for this purpose due to its high data-efficiency and its explicit uncertainty representation, which allows the derivation of prediction error bounds. These error bounds have been exploited to show tracking accuracy guarantees for a variety of control approaches, but their direct dependency on the training data is generally unclear. We address this issue by deriving a Bayesian prediction error bound for GP regression, which we show to decay with the growth of a novel, kernel-based measure of data density. Based on the prediction error bound, we prove time-varying tracking accuracy guarantees for learned GP models used as feedback compensation of unknown nonlinearities, and show to achieve vanishing tracking error with increasing data density. This enables us to develop an episodic approach for learning Gaussian process models, such that an arbitrary tracking accuracy can be guaranteed. The effectiveness of the derived theory is demonstrated in several simulations.
Study on thermal insulation performance of EVA foaming materials

ABSTRACT Foaming EVA was prepared with molding method in this paper, the effect of the cell size, cell wall thickness and filling gas type on thermal insulation performance of foaming EVA were analysed by the mechanism of insulation. The results show that the cell size, cell wall thickness and filling gas type have a significant influences on the insulation performance. When the cell size is 71.3 μm, the thermal conductivity is the smallest at low frequency 1000 Hz, which is 0.042 W/ (m.k). When the cell wall thickness is 8.2 μm, thermal conductivity of foaming EVA is minimal, which is 0.045 W / (m.K), the insulation effect is ideal. When the filling gas is hydrogen, the thermal insulation performance of foaming EVA is poor, but when the filling gas is nitrogen, the result is opposite.
Exploring Environmental Drivers of Growth for Tree Species Associated with a Rare Limestone Bluff Cedar–Pine Forest in Vermont

Abstract - The limestone bluff cedar–pine forest is a rare upland natural community that is threatened by development and invasion by exotic species. Furthermore, the sensitivity of this forest-type to changes in climate and pollution exposure is unknown. We collected xylem increment cores from 4 conifer species (Thuja occidentalis [Northern White Cedar], Juniperus virginiana [Eastern Red Cedar], Pinus strobus [Eastern White Pine], and Tsuga canadensis [Eastern Hemlock]) and 4 hardwood species (Quercus rubrum [Northern Red Oak], Quercus alba [White Oak], Fagus grandifolia [American Beech], and Fraxinus americana [White Ash]) within and close to a cedar–pine forest along the eastern shore of Lake Champlain in Vermont and correlated radial tree growth to precipitation, snow, temperature, and pollution data to assess which factors influenced growth during the time period 1937–2016. We examined growth and possible environmental drivers of it for a variety of species to evaluate how unique these may be for the cedar and pine trees emblematic of the limestone-bluff community. For both conifers and hardwoods, precipitation exhibited the strongest positive correlations with growth and occurred with greater frequency compared to other climate and pollution parameters. Snow was positively associated and temperature was negatively associated with growth for all species. Despite growing over calcium-rich bedrock, and especially for the conifers, pollution seemed to limit growth in years prior to pollution reductions enacted following the 1990 Amendments to the Clean Air Act.
Green turtle (Chelonia mydas) hatching success at Raine and Heron Islands

ABSTRACT Raine Island, the world’s largest green turtle nesting location, has low nest hatching success. The main causes of this low hatching success are thought to be nest destruction by subsequent nesting females, and inundation of nests during high tides and storm surges. But even nests that are protected from nest destruction and inundation appear to have relatively low hatching success, with most of the embryo mortality occurring early in incubation. Here, I compare hatching success and developmental phase of embryo death of protected ‘dry’ nests from Raine Island (RI) with similar nests from Heron Island (HI), a nesting location previously reported as having high hatching success. Nests at both sites were sampled close to the peak time of nesting (December). Twenty-eight nests were sampled at RI and 14 nests at HI. Nest temperatures were cooler during the first week of incubation at HI (median 26.9°C) than at RI (median 30.1°C), but three-days-in-a-row maximum nest temperatures were higher at HI (median 36.0°C) than at RI (median 33.5°C). I found the hatching success of sampled nests at both locations was similar, ~70%, but most embryo death occurred early in incubation at RI (median 16.5%) compared to HI (median 3.8%), but late in incubation at HI (median 4.9%) compared to RI (median 0.2%).
Energy Implications of IO Interface Design Choices

With the availability of high performance storage technology, there is extra pressure on the efficiency of IO interfaces. In addition to the popular POSIX synchronous, POSIX asynchronous, and Linux asynchronous (libaio) IO interfaces, there are two recent interfaces, spdk and io_uring, that are increasingly attracting attention with their high performance asynchronous designs. While providing high performance IO is crucial, it is also essential to do so in an energy-aware manner. In this paper, we study the energy implications of IO interface design choices and how these choices impact a system's energy consumption. Our empirical evaluation using a power meter, an ultra-low latency storage device, and various workload behaviors including single and multiple thread scenarios allow us to lay out the most energy efficient design choices, with the goal of yielding energy-aware high-performance storage stack designs.
An Efficient Order-Preserving Recovery for F2FS with ZNS SSD

Storage devices use write buffers to improve performance, where multiple write requests are processed in parallel and completed in a random order. This may result in data loss in the event of a sudden failure. Therefore, Linux filesystems provide the fsync() system call to prevent data loss and ensure write order. However, the fsync() system call in F2FS, one of the most popular filesystems, is inefficient and insufficient for guaranteeing data consistency. We propose a new technique called Order-Preserving Recovery with Write pointer (OPRW) to ensure data consistency during the filesystem recovery. OPRW utilizes the write pointer in Zoned NameSpace (ZNS) SSDs to efficiently determine the persistence of data without the need for I/O operations. This approach allows OPRW to provide a higher level of consistency and performance improvement for fsync(), while minimizing the impact on recovery time. As a result, our solution improves performance by up to 1.2x on realistic workloads.
Fast, Fine-grained, and Robust Grouping of RFIDs

This paper presents the design, implementation, and evaluation of TaGroup, a fast, fine-grained, and robust grouping technique for RFIDs. It can achieve a nearly 100% accuracy in distinguishing multiple groups of closely located RFIDs, within only a few seconds. It would benefit many inventory tracking applications, such as self-checkout in retails and packaging quality control in logistics. We make two technical innovations. First, we propose a novel method which can measure the channels between multiple pairs of commercial RFID tags simultaneously, and then estimate the proximity relations between them based on the channel information. Second, we introduce a spatio-temporal graph model which captures a full picture of proximity relations among all the tags, based on which TaGroup can perform a robust grouping of the tags. These two designs together boost the grouping speed and accuracy of TaGroup. Our experiments show that in grouping 120 tags into 4 closely located groups, TaGroup can achieve a nearly 100% accuracy, at the cost of only 3 seconds.
Diapycnal Mixing Induced by Rough Small‐Scale Bathymetry

Diapycnal mixing impacts vertical transport rates of salt, heat, and other dissolved substances, essential for the overturning circulation and ecosystem functioning in marine systems. While most studies have focused on mixing induced by individual obstacles in tidal flows, we investigate the net effect of non‐tidal flow over multiple small‐scale (<1 km) bathymetric features penetrating a strongly‐stratified density interface in a coastal region. We combine high‐resolution broadband acoustic observations of turbulence microstructure with traditional shear microstructure profiling, to resolve the variability and intermittency of stratified turbulence related to the rough bathymetry. Scale analysis and acoustic imaging suggest that underlying mixing mechanisms are related to topographic wake eddies and breaking internal waves. Depth averaged dissipation rates (1.1 × 10−7 Wkg−1) and turbulent vertical diffusivities (7 × 10−4 m2s−1) in the halocline exceed reference values by two orders of magnitude. Our study emphasizes the importance of rough small‐scale bathymetric features for the vertical transport of salt in coastal areas.
Influence of a Cold Plastic Deformation on the Electrical Resistivity of CrMnFeCoNi High-Entropy Alloy

The influence of a cold rolling deformation on the electrical transport properties of CrMnFeCoNi high-entropy alloy (HEA) has been studied. It is shown that the growth of the strain ε at rolling gives rise to a decrease of the alloy electrical resistivity ρ and an increase of the temperature coefficient of resistance α. The X-ray diffraction study did not reveal any phase changes at that. Such dependences of ρ and α on ε differ from the behavior of those parameters in the majority of ordinary metal alloys. The temperature dependence of the electrical resistance of deformed samples at their heating is found to have an abnormal S-like shape. Using the positions of such S-anomalies obtained at different heating rates, the activation energy Ea of the process responsible for the appearance of this anomaly is determined with the help of the Kissinger method. The form of the dependence ρ(T ) and the value of Ea give us ground to connect the specific features in the behavior of ρ in deformed specimens with the existence of a “K-state” in the examined HEA, which emerges in some deformed alloys based on transition metals. Possible thermodynamic reasons for the appearance of this state have been discussed.
The Influence of Targeted Facebook Advertising Through Mobile Devices on South African Consumers’ Advertisement Perceptions

Abstract The study investigated the role of Facebook advertising via mobile devices on South African consumers’ advertising perceptions by combining multiple perception models. The study was executed through exploratory research and content analysis of in-depth interviews. The findings suggest both negative and positive responses by South African consumers toward interruptive advertising on social media with evidence of emotional and social influence. The emotional and active responses to the communication, and the perspectives toward the social media platform, the sender of the communication, and the message itself are provided. The findings offer managers further understanding of consumer perceptions of advertising delivered via social media with suggestions to consider during strategy formations. Future researchers can use the framework to further analyse the effectiveness of the model and expand on the influential variables to increase understanding of the advertising outcomes. Organisations can use the findings to assist in their knowledge of this market and in their marketing strategies.
Indigenizing environmental sustainability curriculum and pedagogy: confronting our global ecological crisis via Indigenous sustainabilities

ABSTRACT This Point for Departure highlights why higher education institutions (HEIs) should integrate Indigenous perspectives in their course offerings, campus management, and scholarly production. Much of HEI's sustainability focus today disproportionately focuses on climate change, which we argue is because its purported solutions actually serve to reinforce, business-as-usual industrial growth. The alternative paradigm to long-term sustainability we propose that HEIs should work to implement is to restructure their curriculum and pedagogy to incorporate what we refer to as Indigenous sustainabilities. In short, we call for academics to integrate Indigenous perspectives and place-based knowledges into their courses, research agenda, and service work in lieu of, or at least in addition to, the current Education for Sustainable Development (ESD) paradigms that often narrowly focus on how HEI are reducing their carbon emissions via so-called ‘clean’ energy, at the expense of addressing other equally, if not more, concerning threats to a healthy biosphere.
Uncharacterized yeast gene YBR238C, an effector of TORC1 signaling in a mitochondrial feedback loop, accelerates cellular aging via HAP4- and RMD9-dependent mechanisms

Uncovering the regulators of cellular aging will unravel the complexity of aging biology and identify potential therapeutic interventions to delay the onset and progress of chronic, aging-related diseases. In this work, we systematically compared gene sets involved in regulating the lifespan of Saccharomyces cerevisiae (a powerful model organism to study the cellular aging of humans) and those with expression changes under rapamycin treatment. Among the functionally uncharacterized genes in the overlap set, YBR238C stood out as the only one downregulated by rapamycin and with an increased chronological and replicative lifespan upon deletion. We show that YBR238C and its paralogue RMD9 oppositely affect mitochondria and aging. YBR238C deletion increases the cellular lifespan by enhancing mitochondrial function. Its overexpression accelerates cellular aging via mitochondrial dysfunction. We find that the phenotypic effect of YBR238C is largely explained by HAP4- and RMD9-dependent mechanisms. Further, we find that genetic or chemical-based induction of mitochondrial dysfunction increases TORC1 (Target of Rapamycin Complex 1) activity that, subsequently, accelerates cellular aging. Notably, TORC1 inhibition by rapamycin (or deletion of YBR238C) improves the shortened lifespan under these mitochondrial dysfunction conditions in yeast and human cells. The growth of mutant cells (a proxy of TORC1 activity) with enhanced mitochondrial function is sensitive to rapamycin whereas the growth of defective mitochondrial mutants is largely resistant to rapamycin compared to wild type. Our findings demonstrate a feedback loop between TORC1 and mitochondria (the TORC1-MItochondria-TORC1 (TOMITO) signaling process) that regulates cellular aging processes. Hereby, YBR238C is an effector of TORC1 modulating mitochondrial function.
Inhibition of excitatory synaptic transmission alters functional organization and efficiency in cortical neural networks

Fundamental neural mechanisms such as activity dependent Hebbian and homeostatic neuroplasticity are driven by balanced excitatory – inhibitory synaptic transmission, and work in tandem to coordinate and regulate complex neural network dynamics in both healthy and perturbed conditions. These neuroplasticity processes shape neural network activity, as well as structural and functional aspects of network organization, information transmission and processing. While crucial for all aspects of network function, understanding how the brain utilizes plasticity mechanisms to retain or regain function during and after perturbation is often challenging. This is because these processes occur at varying spatiotemporal scales simultaneously across diverse circuits and brain regions and are thus highly complicated to distinguish from other underlying mechanisms. However, neuroplasticity and self-organizing properties of the brain are largely conserved in in vitro biological neural networks, and as such, these networks enable us to investigate both structural and functional plasticity responses to perturbation networks at the micro and mesoscale level. In this study, we selectively silenced excitatory synaptic transmission in in vitro neural networks to investigate the impact of the perturbation on structural and functional network organization and resilience. Our results demonstrate that selective inhibition of excitatory transmission leads to transient de-clustering of modular structure, increased path length and degree in perturbed networks. These changes indicate a transient loss of network efficiency; with the network subsequently reorganizing to a state of increased clustering and short path lengths following recovery. These findings highlight the remarkable capacity of neural networks to reconfigure their functional organization following perturbation. The ability to detect and decode such processes as they evolve highlights the robustness of our models to investigate certain dynamic network properties that are often not accessible by in vivo methods.
Intracellular signaling in proto-eukaryotes evolves to alleviate regulatory conflicts of endosymbiosis

The complex eukaryotic cell resulted from a merger between simpler prokaryotic cells, yet the relative timing and the role of the mitochondrial endosymbiosis with respect to other eukaryotic innovations has remained under dispute. Although expansion of the regulatory repertoire has been inferred from phylogenetic studies, gene regulation has not been taken into account in current scenarios of the mitochondrial endosymbiosis which mostly focus on the complementary energetic and ecological perspectives. The endosymbiotic state introduced several unique challenges to cells such as coordination of host and symbiont cell cycles and its disruption by leaking gene products and DNA fragments between host and symbionts. To investigate how these unique challenges impacted genome and network evolution during eukaryogenesis, we study a constructive computational model where two simple cells are forced into an obligate endosymbiosis. Across multiple in silico evolutionary replicates, we observe the emergence of different mechanisms for the coordination of host and symbiont cell cycles, stabilizing the endosymbiotic relationship. The most commonly evolved mechanism, implicit control, works without signaling between host and symbiont. Signaling only evolves under the influence of leaking gene products, while such regulatory interference is inherently harmful. In the fittest evolutionary replicate, the host controls the symbiont cell cycle entirely through signaling, mimicking the regulatory dominance of the nucleus over the mitochondrion that evolved during eukaryogenesis.
ESGq: Alternative Splicing events quantification across conditions based on Event Splicing Graphs

Alternative Splicing (AS) is a regulation mechanism that contributes to protein diversity and is also associated to many diseases and tumors. Alternative splicing events quantification from RNA-Seq reads is a crucial step in understanding this complex biological mechanism. However, tools for AS events detection and quantification show inconsistent results. This reduces their reliability in fully capturing and explaining alternative splicing. We introduce ESGq, a novel approach for the quantification of AS events across conditions based on read alignment against Event Splicing Graphs. By comparing ESGq to two state-of-the-art tools on real RNA-Seq data, we validate its performance and evaluate the statistical correlation of the results. ESGq is freely available at https://github.com/AlgoLab/ESGq.
DeepCristae, a CNN for the restoration of mitochondria cristae in live microscopy images

Mitochondria play an essential role in the life cycle of eukaryotic cells. However, we still don’t know how their ultrastructure, like the cristae of the inner membrane, dynamically evolves to regulate these fundamental functions, in response to external conditions or during interaction with other cell components. Although high-resolution fluorescent microscopy coupled with recently developed innovative probes can reveal this structural organization, their long-term, fast and live 3D imaging remains challenging. To address this problem, we have developed a convolutional neural network (CNN), called DeepCristae, to restore mitochondrial cristae in low spatial resolution microscopy images. Our CNN is trained from 2D STED images using a novel loss specifically designed for cristae restoration. Random sampling centered on mitochondrial areas was also developed to improve training efficiency. Quantitative assessments were carried out using metrics we derived to give a meaningful measure of cristae restoration. Depending on the conditions of use indicated, DeepCristae works well on broad microscopy modalities (STED, Live-SR, AiryScan and LLSM). It is ultimately applied in the context of mitochondrial network dynamics during interaction with endo/lysosomes membranes.
Cross-species analysis of ARPP19 phosphorylation during oocyte meiotic maturation charts the emergence of a new cAMP-dependent role in vertebrates

In many animal species, elevated cAMP-PKA signaling initiates oocyte meiotic maturation upon hormonal stimulation, whereas in vertebrates, it acts as a negative regulator of this process. To address this “cAMP paradox”, we have focused on ARPP19 proteins. Dephosphorylation of Xenopus ARPP19 on a specific PKA site has been identified as a key step in initiating oocyte maturation. We first tracked evolution of the ARPP19 PKA phosphorylation site, revealing that it appeared early during the emergence of metazoans. This contrasts with strong conservation across eukaryotes of a phosphorylation site for the kinase Gwl in ARPP19 proteins, able to transform them into potent PP2A-B55 inhibitors and thus promote M-phase entry. We then compared the phosphorylation and function of Xenopus ARPP19 with its orthologue from the jellyfish Clytia, a model species showing cAMP-induced oocyte maturation. We confirmed that Clytia ARPP19 is phosphorylated on the conserved Gwl site in vitro as well as in maturing Xenopus and Clytia oocytes, behaving as a PP2A inhibitor and contributing to Cdk1 activation. However, Gwl-phosphorylated ARPP19 was unable to initiate oocyte maturation in Clytia, suggesting the presence of additional locks released by hormonal stimulation. Clytia ARPP19 was in vitro phosphorylated by PKA uniquely on the predicted site, but it was a much poorer substrate of PKA and of its antagonizing phosphatase, PP2A-B55δ, than the Xenopus protein. Correspondingly, PKA-phosphomimetic Clytia ARPP19 had a much weaker inhibitory activity on meiosis resumption in Xenopus oocytes than its Xenopus counterpart. Hence, poor recognition of Clytia ARPP19 by PKA and the absence of its targets in Clytia oocytes account for the cAMP paradox. This cross-species study of ARPP19 illustrates how initiation of oocyte maturation has complexified during animal evolution, and provides further insight into its biochemical regulation.