Miracle-dz/UniFAR-FTUs huggingface dataset:
The Variational Kernel-Based 1-D Convolutional Neural Network for Machinery Fault Diagnosis

One-dimensional convolutional neural network (1-D CNN) can be directly applied to process temporal signals in the machinery fault diagnosis. However, it requires a large amount of data to train high-quality kernels and extract meaningful features. This article develops a novel method integrating learnable variational kernels into a 1-D CNN to pay more attention to extracting important fault-related data features and offer decent performance with even limited data. In the proposed method, the variational kernel is first derived by adapting constraints and formulations of the successive variational mode decomposition (SVMD). Next, a gradient descent process based on a fault classification loss is developed to estimate the parameter of the variational kernel. Lastly, a CNN-based diagnosis model is constructed to perform machinery fault diagnoses. The proposed model is benchmarked with two standard 1-D CNNs and four wavelet kernel-based 1-D CNNs. Datasets collected from train bearing and gearbox test rigs are used for validations. Results show that the proposed model identifies important fault-related features and performs better in machinery fault diagnoses with limited training data.
Neural Networks as a Side-Channel Countermeasure: Challenges and Opportunities

Specialized acceleration hardware for artificial deep neural network inference is available from the cloud to the edge. FPGAs in particular are heavily advertised for the acceleration of neural network-based applications. Traditionally, those applications are classification or nonlinear regression tasks with the goal to approximate an unknown function. However, they can be trained to replicate a fully known deterministic function - a classical example being the boolean XOR - as well. On the other hand, side-channel attacks remain a concern from the cloud to the edge, where attackers are often able to extract secret information through direct or indirect measurements of observables like power, voltage, electromagnetic emanation or timing. In this work, we show how an FPGA-mapped neural network implementation of the AES S-Box can improve side-channel resistance against Correlation Power Analysis (CPA) attacks. Although the implementation of a hardware-optimized algorithm such as the AES as a neural network introduces significant overhead, the generality of the representation allows to mitigate leakage in a manner agnostic to the overlying cryptographic primitive. We demonstrate the benefits of a generic representation, by optimizing an initially vulnerable neural network implementation towards side-channel resilience, through careful choice of activation function and input representation. The implementation is evaluated both against an external attacker measuring power with an oscilloscope, as well as a remote, internal adversary, who is able to capture voltage traces through FPGA-internal sensors in multi-tenant FPGAs. Our results show, how external attacks on the optimized neural network are no longer possible with up to one million traces, whereas an internal attacker is still able to recover the secret key. The latter result also exposes that in some cases measurement through internal sensors can be even more beneficial for an attacker than physical access with measurement equipment.
Capacity and Congestion Aware Flow Control Mechanism for Efficient Traffic Aggregation in Multi-Radio Dual Connectivity

Multi-Radio Dual Connectivity (MR-DC) is a crucial 3GPP technology that enables traffic aggregation to leverage the radio resources of two base stations (BSs), thereby increasing the per-user data rate. However, the traffic aggregation management in MR-DC is left up to vendor implementation. In this paper, we show that enabling an efficient traffic aggregation method is crucial to increase the throughput performance of both TCP- and UDP-based applications in MR-DC operation. Targeting the state-of-the-art gap on this topic, we propose a flow control mechanism, which efficiently aggregates traffic based on the assigned radio resources and buffering delay statistics of both BSs. The proposed traffic aggregation mechanism is applicable irrespective of the employed MR-DC architecture option, MAC packet scheduler design, and transport layer protocol in use. By means of exhaustive testbed experiments, we show that the proposed method achieves at least 85% and 95% of the theoretical aggregate throughput when employing MR-DC for TCP and UDP traffic, respectively.
"The robot may not notice my discomfort" – Examining the Experience of Vulnerability for Trust in Human-Robot Interaction

Ensuring trust in human-robot interaction (HRI) is considered essential for widespread use of robots in society and everyday life. While the majority of studies use game-based and high-risk scenarios with low familiarity to gain a deeper understanding of human trust in robots, scenarios with more subtle trust violations that could happen in everyday life situations are less often considered. In this paper, we present a theory-driven approach to studying the situated trust in HRI by focusing on the experience of vulnerability. Focusing on vulnerability not only challenges previous work on trust in HRI from a theoretical perspective, but is also useful for guiding empirical investigations. As a first proof-of-concept study, we conducted an interactive online survey that demonstrates that it is possible to measure human experience of vulnerability in the ordinary, mundane, and familiar situation of clothes shopping. We conclude that the inclusion of subtle trust violation scenarios occurring in the everyday life situation of clothes shopping enables a better understanding of situated trust in HRI, which is of special importance when considering more near-future applications of robots.
Switching of OAS1 splicing isoforms mitigates SARS-CoV-2 infection

Background The rapidly accumulating disease susceptibility information collected from coronavirus disease (COVID-19) patient genomes must be urgently utilized to develop therapeutic interventions for SARS-CoV-2 infection. Chromosome 12q24.13, which encodes the 2’-5’-oligoadenylate synthetase (OAS) family of proteins that sense viral genomic RNAs and trigger an antiviral response, is identified as one of the genomic regions that contains SNPs associated with COVID-19 severity. A high-risk SNP identified at the splice acceptor site of OAS1 exon 6 is known to change the proportions of the various splicing isoforms and the activity of the enzyme. Methods We employed in-silico motif search and RNA pull-down assay to define a factor responsible for the OAS1 splicing. Next, we rationally selected a candidate for slicing modulator to modulate this splicing. Results We found that inhibition of CDC-like kinase with a small chemical compound induces switching of OAS1 splice isoforms in human lung cells. In this condition, increased resistance to SARS-CoV-2 infection, enhanced RNA degradation, and transcriptional activation of interferon β1, were also observed. Conclusions The results indicate the possibility of using chemical splicing modifiers aided by genome-based precision medicine to boost the innate immune response against SARS-CoV-2 infection.
Using historical museum samples to examine divergent and parallel evolution in the invasive starling

During the Anthropocene, Earth has experienced unprecedented habitat loss, native species decline, and global climate change. Concurrently, greater globalisation is facilitating species movement, increasing the likelihood of alien species establishment and propagation. There is a great need to understand what influences a species’ ability to persist or perish within a new or changing environment. Examining genes that may be associated with a species’ invasion success or persistence informs invasive species management, assists with native species preservation, and sheds light on important evolutionary mechanisms that occur in novel environments. This approach can be aided by coupling spatial and temporal investigations of evolutionary processes. Here we use the common starling, Sturnus vulgaris, to identify parallel and divergent evolutionary change between contemporary native and invasive range samples and their common ancestral population. To do this, we use reduced-representation sequencing of native samples collected recently in north-western Europe and invasive samples from Australia, together with museum specimens sampled in the UK during the mid-19th Century. We found evidence of parallel selection on both continents, possibly resulting from common global selective forces such as exposure to pollutants (e.g. TCDD) and food carbohydrate content. We also identified divergent selection in these populations, which might be related to adaptive changes in response to the novel environment encountered in the introduced Australian range. Interestingly, signatures of selection are equally as common within both invasive and native range contemporary samples. Our results demonstrate the value of including historical samples in genetic studies of invasion and highlight the ongoing and occasionally parallel role of adaptation in both native and invasive ranges.
SmcHD1 underlies the formation of H3K9me3 blocks on the inactive X chromosome in mice

Stable silencing of the inactive X chromosome (Xi) in female mammals is critical for the development of embryos and their postnatal health. SmcHD1 is essential for stable silencing of the Xi, and its functional deficiency results in derepression of many X-inactivated genes. Although SmcHD1 has been suggested to play an important role in the formation of higher order chromatin structure of the Xi, the underlying mechanism is largely obscure. Here we explore the epigenetic state of the Xi in SmcHD1-deficient epiblast stem cells (EpiSCs) and mouse embryonic fibroblasts (MEFs) in comparison with their wild-type counterparts. The results suggest that SmcHD1 underlies the formation of H3K9me3-enriched blocks on the Xi, which, although the importance of H3K9me3 has been largely overlooked in mice, play a critical role in the establishment of the stably silenced state. We propose that the H3K9me3 blocks formed on the Xi facilitate robust heterochromatin formation in combination with H3K27me3, and the substantial loss of H3K9me3 caused by SmcHD1 deficiency leads to aberrant distribution of H3K27me3 on the Xi and derepression of X-inactivated genes.
Probing the orientation specificity of excitatory and inhibitory circuitries in the primary motor cortex with multi-channel TMS

Background The electric field orientation is a crucial parameter for optimizing the excitation of neuronal tissue in transcranial magnetic stimulation (TMS). Yet, the effects of stimulus orientation on the short-interval intracortical inhibition (SICI) and intracortical facilitation (ICF) paradigms are poorly known, mainly due to significant technical challenges in manipulating the TMS-induced stimulus orientation within milliseconds. Objective Our aim is to assess the effect of the TMS-induced stimulus orientation on the SICI and ICF paradigms and search for the optimal orientations to maximize the facilitation and suppression of the motor evoked potentials (MEP). Methods We applied paired-pulse multi-channel TMS in healthy subjects to generate SICI and ICF with conditioning and test pulses in the same, opposite, and perpendicular orientations to each other. The conditioning- and test-stimulus intensities were 80% and 110% of the resting motor threshold, respectively. Results Both SICI and ICF were significantly affected by the conditioning- and test-stimulus orientation. MEP suppression and facilitation were strongest with both pulses delivered in the same direction. SICI with a 2.5-ms and ICF with a 6.0-ms interstimulus interval (ISI) were more sensitive to changes in stimulus orientation compared with SICI at 0.5- and ICF at 8.0-ms ISIs, respectively. Conclusion Our findings provide evidence that SICI and ICF at specific ISIs are mediated by distinct mechanisms. Such mechanisms exhibit a preferential orientation depending on the anatomical and morphological arrangement of inhibitory and excitatory neuronal populations. We also demonstrate that the SICI and ICF can be maximized by adjusting the TMS-induced electric field orientation.
Monodopsis and Vischeria genomes elucidate the biology of eustigmatophyte algae

Members of eustigmatophyte algae, especially Nannochloropsis, have been tapped for biofuel production owing to their exceptionally high lipid content. While extensive genomic, transcriptomic, and synthetic biology toolkits have been made available for Nannochloropsis, very little is known about other eustigmatophytes. Here we present three near-chromosomal and gapless genome assemblies of Monodopsis (60 Mb) and Vischeria (106 Mb), which are the sister groups to Nannochloropsis. These genomes contain unusually high percentages of simple repeats, ranging from 12% to 21% of the total assembly size. Unlike Nannochloropsis, LINE repeats are abundant in Monodopsis and Vischeria and might constitute the centromeric regions. We found that both mevalonate and non-mevalonate pathways for terpenoid biosynthesis are present in Monodopsis and Vischeria, which is different from Nannochloropsis that has only the latter. Our analysis further revealed extensive spliced leader trans-splicing in Monodopsis and Vischeria at 36-61% of genes. Altogether, the high-quality genomes of Monodopsis and Vischeria not only serve as the much-needed outgroups to advance Nannochloropsis research, but also shed new light on the biology and evolution of eustigmatophyte algae.
Electrical activity recorded from the spinal cord in freely moving rats using a subdural bioelectronic implant

Bioelectronic devices have found use at the interface with neural tissue to investigate and treat nervous system disorders. Here, we present the development and characterization of a thin flexible bioelectronic implant inserted over the thoracic spinal cord in rats directly in contact with the spinal cord. There was no negative impact on hind-limb functionality nor any change in the volume or shape of the spinal cord. The bioelectronic implant was maintained in rats for a period of 3 months. We present the first subdural recordings of spinal cord activity in freely moving animals. Recordings contained multiple distinct voltage waveform shapes that were typically between 1 – 6 mV and lasted between 0.1 and 1 seconds. In the future, this implant will facilitate the identification of biomarkers in spinal cord injury and recovery, while enabling the delivery of localized treatments.
REPLY:

We appreciate the commentary on our study (HEP-20-0294.R1). We do not contest the Sperber hypothesis of osmotically driven water influx in bile formation per se. Rather, our data contests the belief that this water influx occurs in canaliculi to cause a 'canalicular flow'. We refine the Sperber hypothesis by showing that - (i) the anatomical site (Sperber's 'bile capillaries') where basal, secretin-induced as well as bile acid (BA)-stimulated water influx occurs is the intralobular bile duct. (ii) Canalicular bile flux is dominated by diffusion through the network, and not by fluid flow.
Spontaneously Resolving Joint Inflammation Is Characterised by Metabolic Agility of Fibroblast-Like Synoviocytes

Fibroblast-like synoviocytes (FLS) play an important role in maintaining joint homeostasis and orchestrating local inflammatory processes. When activated during injury or inflammation, FLS undergo transiently increased bioenergetic and biosynthetic demand. We aimed to identify metabolic changes which occur early in inflammatory disease pathogenesis which might support sustained cellular activation in persistent inflammation. We took primary human FLS from synovial biopsies of patients with very early rheumatoid arthritis (veRA) or resolving synovitis, and compared them with uninflamed control samples from the synovium of people without arthritis. Metabotypes were compared using NMR spectroscopy-based metabolomics and correlated with serum C-reactive protein levels. We measured glycolysis and oxidative phosphorylation by Seahorse analysis and assessed mitochondrial morphology by immunofluorescence. We demonstrate differences in FLS metabolism measurable after ex vivo culture, suggesting that disease-associated metabolic changes are long-lasting. We term this phenomenon ‘metabolic memory’. We identify changes in cell metabolism after acute TNFα stimulation across disease groups. When compared to FLS from patients with early rheumatoid arthritis, FLS from patients with resolving synovitis have significantly elevated mitochondrial respiratory capacity in the resting state, and less fragmented mitochondrial morphology after TNFα treatment. Our findings indicate the potential to restore cell metabotypes by modulating mitochondrial function at sites of inflammation, with implications for treatment of RA and related inflammatory conditions in which fibroblasts play a role.
Altered Cerebellar Resting-State Functional Connectivity in Early-Stage Parkinson's Disease Patients With Cognitive Impairment

Background: Cognitive impairment is one of the most prominent non-motor symptoms in Parkinson's disease (PD), due in part to known cerebellar dysfunctions. Furthermore, previous studies have reported altered cerebellar functional connectivity (FC) in PD patients. Yet whether these changes are also due to the cognitive deficits in PD remain unclear. Methods: A total of 122 non-dementia participants, including 64 patients with early PD and 58 age- and gender-matched elderly controls were stratified into four groups based on their cognitive status (normal cognition vs. cognitive impairment). Cerebellar volumetry and FC were investigated by analyzing, respectively, structural and resting-state functional MRI data among groups using quality control and quantitative measures. Correlation analysis between MRI metrics and clinical features (motor and cognitive scores) were performed. Results: Compared to healthy control subjects with no cognitive deficits, altered cerebellar FC were observed in early PD participants with both motor and cognitive deficits, but not in PD patients with normal cognition, nor elderly subjects showing signs of a cognitive impairment. Moreover, connectivity between the “motor” cerebellum and SMA was positively correlated with motor scores, while intracerebellar connectivity was positively correlated with cognitive scores in PD patients with cognitive impairment. No cerebellar volumetric difference was observed between groups. Conclusions: These findings show that altered cerebellar FC during resting state in early PD patients may be driven not solely by the motor deficits, but by cognitive deficits as well, hence highlighting the interplay between motor and cognitive functioning, and possibly reflecting compensatory mechanisms, in the early PD.
Evaluation of Histone Deacetylase Inhibitors as Radiosensitizers for Proton and Light Ion Radiotherapy

Significant opportunities remain for pharmacologically enhancing the clinical effectiveness of proton and carbon ion-based radiotherapies to achieve both tumor cell radiosensitization and normal tissue radioprotection. We investigated whether pretreatment with the hydroxamate-based histone deacetylase inhibitors (HDACi) SAHA (vorinostat), M344, and PTACH impacts radiation-induced DNA double-strand break (DSB) induction and repair, cell killing, and transformation (acquisition of anchorage-independent growth in soft agar) in human normal and tumor cell lines following gamma ray and light ion irradiation. Treatment of normal NFF28 primary fibroblasts and U2OS osteosarcoma, A549 lung carcinoma, and U87MG glioma cells with 5–10 µM HDACi concentrations 18 h prior to cesium-137 gamma irradiation resulted in radiosensitization measured by clonogenic survival assays and increased levels of colocalized gamma-H2AX/53BP1 foci induction. We similarly tested these HDACi following irradiation with 200 MeV protons, 290 MeV/n carbon ions, and 350 MeV/n oxygen ions delivered in the Bragg plateau region. Unlike uniform gamma ray radiosensitization, effects of HDACi pretreatment were unexpectedly cell type and ion species-dependent with C-12 and O-16 ion irradiations showing enhanced G0/G1-phase fibroblast survival (radioprotection) and in some cases reduced or absent tumor cell radiosensitization. DSB-associated foci levels were similar for proton-irradiated DMSO control and SAHA-treated fibroblast cultures, while lower levels of induced foci were observed in SAHA-pretreated C-12 ion-irradiated fibroblasts. Fibroblast transformation frequencies measured for all radiation types were generally LET-dependent and lowest following proton irradiation; however, both gamma and proton exposures showed hyperlinear transformation induction at low doses (≤25 cGy). HDACi pretreatments led to overall lower transformation frequencies at low doses for all radiation types except O-16 ions but generally led to higher transformation frequencies at higher doses (>50 cGy). The results of these in vitro studies cast doubt on the clinical efficacy of using HDACi as radiosensitizers for light ion-based hadron radiotherapy given the mixed results on their radiosensitization effectiveness and related possibility of increased second cancer induction.
The Effect of Individual Musculoskeletal Conditions on Depression: Updated Insights From an Irish Longitudinal Study on Aging

Few longitudinal studies have systematically investigated whether or how individual musculoskeletal conditions (IMCs) convey risks for negative psychological health outcomes, and approaches to assess such risk in the older population are lacking. In this Irish nationally representative longitudinal prospective study of 6,715 individuals aged 50 and above, machine learning algorithms and various models, including mediation models, were employed to elaborate the underlying mechanisms of IMCs leading to depression and to develop an IMC-induced negative psychological risk (IMCPR) classification approach. Resultantly, arthritis [odds ratio (95% confidence interval): 2.233 (1.700–2.927)], osteoporosis [1.681 (1.133–2.421)], and musculoskeletal chronic pain [MCP, 2.404 (1.838–3.151)] were found to increase the risk of depression after 2 years, while fracture and joint replacement did not. Interestingly, mediation models further demonstrated that arthritis per se did not increase the risk of depression; such risk was augmented only when arthritis-induced restrictions of activities (ARA) existed [proportion of mediation: 316.3% (ARA of usual), 213.3% (ARA of social and leisure), and 251.3% (ARA of sleep)]. The random forest algorithm attested that osteoarthritis, not rheumatoid arthritis, contributed the most to depressive symptoms. Moreover, bone mineral density was negatively associated with depressive symptoms. Systemic pain contributed the most to the increased risk of depression, followed by back, knee, hip, and foot pain (mean Gini-Index: 3.778, 2.442, 1.980, 1.438, and 0.879, respectively). Based on the aforementioned findings, the IMCPR classification approach was developed using an interpretable machine learning model, which stratifies participants into three grades. Among the IMCPR grades, patients with a grade of “severe” had higher odds of depression than those with a “mild” [odds ratio (95% confidence interval): 4.055 (2.907–5.498)] or “moderate” [3.584 (2.101–5.883)] grade. Females with a “severe” grade had higher odds of depression by 334.0% relative to those with a “mild” grade, while males had a relative risk of 258.4%. In conclusion, the present data provide systematic insights into the IMC-induced depression risk and updated the related clinical knowledge. Furthermore, the IMCPR classification approach could be used as an effective tool to evaluate this risk.