Miracle-dz/UniFAR-FTUs huggingface dataset:
AutoCRAFT: Layout Automation for Custom Circuits in Advanced FinFET Technologies

Despite continuous efforts in layout automation for full-custom circuits, including analog/mixed-signal (AMS) designs, automated layout tools have not yet been widely adopted in current industrial full-custom design flows due to the high circuit complexity and sensitivity to layout parasitics. Nevertheless, the strict design rules and grid-based restrictions in nanometer-scale FinFET nodes limit the degree of freedom in full-custom layout design and thus reduce the gap between automation tools and human experts. This paper presents AutoCRAFT, an automatic layout generator targeting region-based layouts for advanced FinFET-based full-custom circuits. AutoCRAFT uses specialized place-and-route (P&R) algorithms to handle various design constraints while adhering to typical FinFET layout styles. Verified by comprehensive post-layout analyses, AutoCRAFT has achieved promising preliminary results in generating sign-off quality layouts for industrial benchmarks.
Pain Level Modeling of Intensive Care Unit patients with Machine Learning Methods: An Effective Congeneric Clustering-based Approach

Recent studies showed that machine learning can assist to better evaluate the induced pain level(s) on healthy individuals in a controlled environment. However, the role of these methods in clinical settings remained unclear and there is an unmet need to develop machine learning assisted tools in pain. The aim of this paper is to develop an automatic pain level assessment model based on patients' physiologic measures from the Medical Information Mart for Intensive Care (MIMIC III). There were two study phases; 1) pilot study, tested three existing machine learning methods proposed recently for healthy individuals. However, these yield poor performances in MIMIC III patients. 2) group study, a novel congeneric clustering method which divided patients into eleven categories and trained a dedicated model for each one. The clustering effectiveness of the proposed congeneric clustering method by showing the highest classification accuracy of 82.86%.
Flexible Operation of Electric Power Transmission Grids

In order to reduce carbon emissions and increase sustainability many countries in the world are switching to renewable sources of energy for electricity production. European Commission has set targets for its Member States to reduce such emissions and proposed share of renewables of around 30% in gross final energy consumption by 2030. Moreover, the electricity market is decentralized in Europe. As a result of decentralization and increased renewable penetration into the system, Transmission System Operators (TSOs) are faced with new challenges to operate their system securely. Some of the means of congestion management by the TSOs have become costly after decentralization. Moreover, variability associated with renewables can create congestion in a distant grid location which belongs to another TSO. Hence, TSOs are forced to find alternatives to operate their systems securely and in a cost effective manner. Inter-TSO coordination is one such non-costly alternative which requires increasing attention when more renewables are integrated into the system. The coordination (preventively and/or curatively) will help to operate the existing transmission grids more flexibly when more renewables integration demands transmission expansion, which is severely limited in Europe.
Peptide-RNA Coacervates as a Cradle for the Evolution of Folded Domains

Peptide-RNA coacervates can result in the concentration and compartmentalization of simple biopolymers. Given their primordial relevance, peptide-RNA coacervates may have also been a key site of early protein evolution. However, the extent to which such coacervates might promote or suppress the exploration of novel peptide conformations is fundamentally unknown. To this end, we used electron paramagnetic resonance (EPR) spectroscopy to characterize the structure and dynamics of an ancient and ubiquitous nucleic acid binding element, the helix-hairpin-helix (HhH) motif, alone and in the presence of RNA, with which it forms coacervates. Double electron-electron resonance (DEER) spectroscopy applied to singly labeled peptides containing one HhH motif reveals the presence of dimers, even in the absence of RNA, and transient α-helical character. Moreover, dimer formation is promoted upon RNA binding and was detectable within peptide-RNA coacervates. The distance distributions between spin labels are consistent with the symmetric (HhH)2-Fold, which is generated upon duplication and fusion of a single HhH motif and traditionally associated with dsDNA binding. These results support the hypothesis that coacervates are a unique testing ground for peptide oligomerization and that phase-separating peptides could have been a resource for the construction of complex protein structures via common evolutionary processes, such as duplication and fusion.
Heterogeneity in the size of the apical surface of cortical progenitors

The apical surface of epithelial cells is highly specialized, it is important for morphogenetic processes that are essential to shape organs and tissues and it plays a role in morphogen and growth factor signaling. Apical progenitors in the mammalian neocortex are pseudoepithelial cells whose apical surface lines the ventricle. Whether changes in their apical surface sizes are important for cortical morphogenesis and/or other aspects of neocortex development after neurulation has not been thoroughly addressed. Here we show that apical progenitors are heterogeneous with respect to their apical surface area. In Efnb1 mutants, the size of the apical surface is modified and this correlates with discrete alterations of tissue organization without impacting proliferation or differentiation. Altogether, our data reveal heterogeneity in apical progenitors AS area in the developing neocortex and shows a role for Ephrin B1 in controlling AS size. Our study also indicates that changes in AS size does not have strong repercussion on apical progenitor behavior.
Growth limitation via chemically complex carbohydrates reduces sensitivity of synthetic human gut communities to perturbations

Dietary fiber affects the composition and functions of microbial communities that reside in the human gut. However, we lack a detailed and quantitative understanding of how these nutrients shape microbial community dynamics, interaction networks and systems-level properties. Using synthetic human gut communities coupled to computational modeling, we dissect the effects of varied fiber types or their constituent sugars on community assembly and sensitivity to perturbations. By quantifying carbohydrate chemical complexity, we demonstrate that microbial growth decreases as a function of complexity. We further demonstrate that the balance of species occupying distinct metabolic niches is altered by the presence of chemically complex carbohydrates. The frequency of negative inter-species interactions is reduced in the presence of complex carbohydrates. Communities grown in complex carbohydrates reproducibly assemble from a wide range of initial species abundances and display reduced sensitivity to invasion. Resource competition is identified as a key mechanism influencing the response of communities to perturbations. The strength of resource competition can promote sensitivity of community assembly to variations in initial species proportions and impact community resistance to invasion. By limiting microbial growth, complex carbohydrates promote the expansion of species occupying niches beyond carbohydrate utilization, shape the distribution of inter-species interactions, which in turn determines the community’s response to perturbations.
Recalibrating vision-for-action requires years after sight restoration from congenital blindness

Being able to perform goal-directed actions requires predictive, feed-forward control, including a mapping between the visually estimated target locations and the motor commands reaching for them. When the mapping is perturbed, e.g., due to muscle fatigue or optical distortions, we are quickly able to recalibrate the sensorimotor system to update this mapping. Here we investigated whether early visual and visuomotor experience is essential for developing the ability to recalibrate. To this end, we assessed young individuals deprived from vision due to dense congenital bilateral cataracts, who were surgically treated for sight restoration only years after birth. We compared their recalibration performance to such distortion to that of age-matched sighted controls. Their recalibration performance was impaired right after surgery. This finding cannot be explained by their still lower visual acuity, since blurring vision in controls to a matching degree did not lead to comparable behavior. Nevertheless, the recalibration ability of cataract-treated participants improved with experience, matching controls’ performance after around 2 years from surgery. Thus, the lack of early visual experience affects visuomotor recalibration. However, this ability is not lost but slowly develops after sight restoration, highlighting the importance of sensorimotor experience for brain plasticity late in life.
Extending Direct Strength Design to Cold-Formed Steel Beams with Holes

Abstract The extension of the American Iron and Steel Institute’s Direct Strength Method (DSM) to cold-formed steel beams with holes is nearly in place. DSM was first introduced to the AISI specification in 2004 as an alternative to the effective width method, and is widely considered a major advancement in cold-formed steel component design. In DSM, the beam elastic buckling properties for a general cross-section are obtained with a computer analysis utilizing the finite strip method. A disadvantage of the finite strip method and DSM has been that discrete holes along the member length could not be easily accounted for, although the recent development of simplified elastic buckling approximations including holes has now alleviated the inherent shortcoming. This paper provides an introduction to the DSM approach for cold-formed steel beams with holes, where the critical elastic buckling moments for local, distortional, and global buckling are calculated including the presence of holes, and then input into strength prediction expressions modified to capture the strength reduction from yielding at the net section. A DSM design example of a joist with evenly spaced web holes is provided.
Diversity and evolution of telomere and subtelomere DNA sequences in insects

In insects, two types of telomere length maintenance are known: telomerase-dependent, resulting in chromosome ends consisting of short nucleotide repeats (typically TTAGG), and telomerase-independent, resulting in chromosome ends consisting of long nucleotide repeats or transposon-like elements. However, only a few species have been previously studied with regard to their telomere DNA sequences. Here, based on analysis of chromosome-level genome assemblies, I present the data on telomere and subtelomere organization for 180 species from 148 genera, 53 families and 8 orders of insects. Analysis of these taxa reveals that in fact chromosome ends of most insect species have an intermediate structure and consist of numerous arrays of short telomeric repeats interspersed with telomere-specific non-LTR retrotransposons. An unexpectedly high level of diversity of short telomeric motifs (22 variants ranging in length from 1 to 17 nucleotides) is documented. Telomeres consisting of long repeats (from 173 to 374 bp) are confirmed for flies (the order Diptera) and also found in the orders Odonata and Hymenoptera. The most unusual telomere structure is found in the bee Lasioglossum lativentre, in which the chromosomes possess the short telomeric repeat TTAGGTCTGGG at only one end, whereas opposing ends terminate with medium and long repeats. I conclude that different types of telomere organization and numerous variants of long and short T-containing motifs, including the (T)n mononucleotide sequence, are compatible with the performance of telomere functions. I argue that both telomerase-dependent and telomerase-independent mechanisms for maintaining telomere length operate simultaneously in many insects. The balance between them and the exchange of sequences between telomeres and subtelomeres are most likely the key factors that determine the structure and evolution of telomeres. Significance Multilayer telomeres, resulted from numerous, site-specific insertions of retrotransposons into the region of short telomeric repeats, are not an aberrant type of organization, as previously thought. They are widely distributed among insects and can represent up to 30-40 % of eukaryotic species diversity. Accordingly, the telomere maintenance mechanism based on the joint work of telomerase-dependent and telomerase-independent mechanisms can also be extremely widespread in nature.
Neural mass modelling for the masses: Democratising access to whole-brain biophysical modelling with FastDMF

Different whole-brain models constrained by neuroimaging data have been developed during the last years to investigate causal hypotheses related to brain mechanisms. Among these, the Dynamic Mean Field (DMF) model is a particularly attractive model, combining a biophysically realistic single-neuron model that is scaled up via a mean-field approach and multimodal imaging data. Despite these favourable features, an important barrier for a widespread usage of the DMF model is that current implementations are computationally expensive – to the extent that the model often becomes unfeasible when no high-performance computing infrastructure is available. Furthermore, even when such computing structure is available, current implementations can only support simulations on brain parcellations that consider less than 100 brain regions. To remove these barriers, here we introduce a user-friendly and computationally-efficient implementation of the DMF model, which we call FastDMF, with the goal of making biophysical whole-brain modelling accessible to neuroscientists worldwide. By leveraging a suit of analytical and numerical advances – including a novel estimation of the feedback inhibition control parameter, and a Bayesian optimisation algorithm – the FastDMF circumvents various computational bottlenecks of previous implementations. An evaluation of the performance of the FastDMF showed that it can attain a significantly faster performance than previous implementations while reducing the memory consumption by several orders of magnitude. Thanks to these computational advances, FastDMF makes it possible to increase the number of simulated regions by one order of magnitude: we found good agreement between empirical and simulated functional MRI data parcellated at two different spatial scales (N=90 and N=1000 brain regions). These advances open the way to the widespread use of biophysically grounded whole-brain models for understanding the interplay among anatomy, function and brain dynamics in health and disease, and to provide mechanistic explanations of recent results obtained from empirical fine-grained neuroimaging data sets, such as turbulence or connectome harmonics. Highlights We present the FastDMF, a user-friendly and computationally efficient implementation of the Dynamic Mean Field model for simulations of whole-brain dynamics. Using analytical and numerical tools, we develop a novel estimation of the feedback inhibition control based on the structural connectivity, bypassing an important computational bottleneck. The FastDMF is coupled with a Bayesian Optimization algorithm significantly reducing the number of simulations required to fit the FastDMF to empirical neuroimaging data. Our advances open the possibility of simulating thousands of brain regions in a biophysically grounded whole-brain model.
A chemomechanical model of sperm locomotion reveals two modes of swimming

The propulsion of mammalian spermatozoa during reproduction relies on the spontaneous periodic oscillation of their flagella. These oscillations are driven internally by the coordinated action of ATP-powered dynein motors that exert active sliding forces between microtubule doublets, resulting in bending waves that propagate along the flagellum and enable locomotion of the cell through the viscous medium. In this work, we present a chemomechanical model of a freely swimming spermatozoon that uses a sliding-control model of the flagellar axoneme capturing the coupling of motor kinetics with elastic deformations and accounts for the effect of non-local hydrodynamic interactions between the sperm head and flagellum. Nonlinear simulations of the model equations are shown to produce realistic beating patterns and swimming trajectories, which we analyze as a function of sperm number and motor activity. Our results demonstrate that the swimming velocity does not vary monotonically with dynein activity, but instead displays two local maxima corresponding to distinct modes of swimming, each characterized by qualitatively different waveforms and trajectories.
Genotypic and phenotypic diversity of the multidrug-resistant Mycobacterium tuberculosis strains from eastern India

Mycobacterium tuberculosis (Mtb) poses a great challenge to human health and wellbeing and hinders economic growth of a region. India along with other south east Asian countries are known as high Tuberculosis burden countries. Adoption of whole genome sequencing in studying genetic diversity, evolution, transmission pattern and drug resistance development provided a great opportunity for developing and improving diagnostic and therapeutic approaches. In our study we have sequenced 118 Mtb whole genome from North East(NE) and Odisha as a representative of the diversity in eastern region of India for the first time. We observed high prevalence of multi-drug resistant(MDR) lineage-2(n=52) strains in NE whereas presence of mostly lineage-1(n=30) & 3 (n=11) strains in Odisha. The MDR strains from Sikkim demonstrated similar resistance profile of fluroquinolones and pair-wise SNP distances showed presence of local transmission clusters. We also detected significant enrichment of short INDELs in MDR samples in contrast to drug susceptible samples. This study provides molecular level insight into Mtb strains of eastern region in comparison with Indian and global perspective.
Phylogenetic-informed graph deep learning to classify dynamic transmission clusters in infectious disease epidemics

In the midst of an outbreak, identification of groups of individuals that represent risk for transmission of the pathogen under investigation is critical to public health efforts. Several approaches exist that utilize the evolutionary information from pathogen genomic data derived from infected individuals to distinguish these groups from the background population, comprised of primarily randomly sampled individuals with undetermined epidemiological linkage. These methods are, however, limited in their ability to characterize the dynamics of these groups, or clusters of transmission. Dynamic transmission patterns within these clusters, whether it be the result of changes at the level of the virus (e.g., infectivity) or host (e.g., vaccination implementation), are critical in strategizing public health interventions, particularly when resources are limited. Phylogenetic trees are widely used not only in the detection of transmission clusters, but the topological shape of the branches within can be useful sources of information regarding the dynamics of the represented population. We evaluate the limitation of existing tree shape statistics when dealing with smaller sub-trees containing transmission clusters and offer instead a phylogeny-based deep learning system –DeepDynaTree– for classification of transmission cluster. Comprehensive experiments carried out on a variety of simulated epidemic growth models indicate that this graph deep learning approach is effective in predicting cluster dynamics (balanced accuracy of 0.826 vs. 0.533 and Brier score of 0.234 vs. 0.466 in independent test set). Our deployment model in DeepDynaTree incorporates a primal-dual graph neural network principle using output from phylogenetic-based cluster identification tools (available from https://github.com/salemilab/DeepDynaTree).
Trascriptome meta-analysis of microalga Dunaliella tertiolecta under stress condition

Microalgae are photosynthetic organisms, which are considered as a potential source for sustainable metabolite production. Furthermore, stress conditions can affect metabolite production. In this study, a meta-analysis of RNA-seq experiments was performed to evaluate the response of metabolite biosynthesis pathways in Dunaliella tertiolecta to abiotic stress conditions, including high light, nitrogen deficiency, and high salinity. The results indicated down-regulation of light reaction, photorespiration, tetrapyrrole, and lipid-related pathways in salt stress. In comparison to salt stress, nitrogen deficiency mostly induced light reaction and photorespiration metabolisms. The up-regulation of phosphoenolpyruvate carboxylase, phosphoglucose isomerase, bisphosphoglycerate mutase, and glucose-6-phosphate-1-dehydrogenase (involved in central carbon metabolism) was observed under salt, high light, and nitrogen stress conditions. Interestingly, the results indicated that the meta-genes (i.e., modules of genes strongly correlated) tended to be located in a hub of stress-specific PPI (Protein-Protein Interaction) networks. Module enrichment of meta-genes PPI networks highlighted the cross talk between photosynthesis, fatty acids, starch, and sucrose metabolism under multiple stress conditions. Moreover, it was observed that the coordinated expression of the tetrapyrrole intermediated with meta-genes involved in starch biosynthesis. The results of the present study also showed that some pathways such as vitamin B6 metabolism, methane metabolism, ribosome biogenesis, and folate biosynthesis responded to different stress factors specifically. In conclusion, the results of this study revealed the main pathways underlying the abiotic stress responses for optimized metabolite production by the microalga Dunaliella in future studies. PRISMA check list was also included in the study.
High-throughput Oligopaint screen identifies druggable regulators of genome folding

Although the molecular rules governing genome organization are being quickly elucidated, relatively few proteins regulating this process have been identified. To address this gap, we developed a fully automated imaging pipeline, called HiDRO (high-throughput DNA or RNA labeling with optimized Oligopaints), that permits quantitative measurement of chromatin interactions across a large number of samples. Using HiDRO, we screened the human druggable genome and identified >300 factors that regulate chromatin folding during interphase, including 43 validated hits that either increase or decrease interactions between topological associating domains (TADs). We discovered that genetic or chemical inhibition of the ubiquitous kinase GSK3A enhances long-range interactions by dysregulating cohesin-mediated chromatin looping. Collectively, these results highlight a noncanonical role for GSK3A signaling in nuclear architecture and underscore the broader utility of HiDRO-based screening to identify novel mechanisms that drive the spatial organization of the genome.