Miracle-dz/UniFAR-FTUs huggingface dataset:
Approximate Gomory–Hu tree is faster than n – 1 max-flows

The Gomory-Hu tree or cut tree (Gomory and Hu, 1961) is a classic data structure for reporting s−t mincuts (and by duality, the values of s−t maxflows) for all pairs of vertices s and t in an undirected graph. Gomory and Hu showed that it can be computed using n−1 exact maxflow computations. Surprisingly, this remains the best algorithm for Gomory-Hu trees more than 50 years later, even for approximate mincuts. In this paper, we break this longstanding barrier and give an algorithm for computing a (1+є)-approximate Gomory-Hu tree using log(n) maxflow computations. Specifically, we obtain the runtime bounds we describe below. We obtain a randomized (Monte Carlo) algorithm for undirected, weighted graphs that runs in Õ(m + n3/2) time and returns a (1+є)-approximate Gomory-Hu tree algorithm whp. Previously, the best running time known was Õ(n5/2), which is obtained by running Gomory and Hu’s original algorithm on a cut sparsifier of the graph. Next, we obtain a randomized (Monte Carlo) algorithm for undirected, unweighted graphs that runs in m4/3+o(1) time and returns a (1+є)-approximate Gomory-Hu tree algorithm whp. This improves on our first result for sparse graphs, namely m = o(n9/8). Previously, the best running time known for unweighted graphs was Õ(mn) for an exact Gomory-Hu tree (Bhalgat et al., STOC 2007); no better result was known if approximations are allowed. As a consequence of our Gomory-Hu tree algorithms, we also solve the (1+є)-approximate all pairs mincut and single source mincut problems in the same time bounds. (These problems are simpler in that the goal is to only return the s−t mincut values, and not the mincuts.) This improves on the recent algorithm for these problems in Õ(n2) time due to Abboud et al. (FOCS 2020).
Harnessing Technologies in Focus Group Research

Abstract Focus group research is a useful methodology within and beyond the field of political science, as a source of core or supplementary data. The focus group literature is rich and full of guidance, but advice on using digital tools in certain stages of focus group research is relatively scarce. Aiming to fill those gaps, this article draws on experience with two projects in order to outline how researchers can harness technologies for focus group recruitment and data analysis. While traditional recruitment and data analysis techniques are useful, we identify advantages of technology-assisted approaches, particularly for focus group research with marginalized communities. Geared to both new and existing focus group users, the article identifies fruitful ways to harness a wider range of technologies for conducting focus group research while maintaining consistency with established principles and practices.
Flame edge structures and dynamics in planar turbulent non-premixed inclined slot-jet flames impinging at a wall

Abstract The present paper focuses on the structures and dynamics of flame edges in planar turbulent non-premixed flames bounded with a wall using direct numerical simulation (DNS). The global quenching behaviour was first examined and the flame edges were identified based on the intersections of mixture fraction and OH mass fraction iso-surfaces. For the upper branch of the planar jet flame, it is observed that the structures of flame edges change from tribrachial to monobrachial with increasing scalar dissipation rate. The flame edge speed is negatively correlated with the scalar dissipation rate in regions away from the wall, highlighting the role of turbulent mixing on the flame edge dynamics. During flame–wall interactions, the propagation speed of flame edges is mainly affected by the projection of edge flame normal in the wall-normal direction, i.e. $\boldsymbol {N}_{Z}\boldsymbol {\cdot }\boldsymbol {N}_{wall}$. In particular, the propagation speed increases with increasing $\boldsymbol {N}_{Z}\boldsymbol {\cdot }\boldsymbol {N}_{wall}$ in the near-wall region. The interactions of flame edges and turbulence bounded with a wall are characterized by the alignment between edge flame normal and principal strain rates. The normal of quenching edges has a tendency to align with the most extensive strain rate $\boldsymbol {e}_{1}$ in regions where the heat-release-induced dilatation is dominant over turbulent strain. In contrast, when the heat loss by cold wall effect is large enough to counteract the heat release induced by chemical reactions, turbulent strain is prevalent and the edge flame normal of the quenching edges preferentially aligns with the most compressive strain rate $\boldsymbol {e}_{3}$.
Genetic structure in patchy populations of a candidate foundation plant: a case study of Leymus chinensis (Poaceae) using genetic and clonal diversity

PREMISE The distribution of genetic diversity on the landscape has critical ecological and evolutionary implications. This may be especially the case on a local scale for foundation plant species since they create and define ecological communities, contributing disproportionately to ecosystem function. METHODS We examined the distribution of genetic diversity and clones, which we defined first as unique multi-locus genotypes (MLG), and then by grouping similar MLGs into multi-locus lineages (MLL). We used 186 markers from inter-simple sequence repeats (ISSR) across 358 ramets from 13 patches of the foundation grass Leymus chinensis. We examined the relationship between genetic and clonal diversities, their variation with patch-size, and the effect of the number of markers used to evaluate genetic diversity and structure in this species. RESULTS Every ramet had a unique MLG. Almost all patches consisted of individuals belonging to a single MLL. We confirmed this with a clustering algorithm to group related genotypes. The predominance of a single lineage within each patch could be the result of the accumulation of somatic mutations, limited dispersal, some sexual reproduction with partners mainly restricted to the same patch, or a combination of all three. CONCLUSIONS We found strong genetic structure among patches of L. chinensis. Consistent with previous work on the species, the clustering of similar genotypes within patches suggests that clonal reproduction combined with somatic mutation, limited dispersal, and some degree of sexual reproduction among neighbors causes individuals within a patch to be more closely related than among patches.
OFF-periods reduce the complexity of neocortical activity during sleep

Complexity of electroencephalographic signals decreases during slow-wave sleep (SWS), however, the neural mechanism for this decrease remains elusive. Here, we show that this complexity reduction is caused by synchronous neuronal OFF-periods. We analyse in-vivo recordings from neocortical neuronal populations, finding that OFF-periods in SWS trap cortical dynamics, making the population activity more recurrent, deterministic, and less chaotic than during REM sleep or Wakefulness. Importantly, when we exclude OFF-periods, SWS becomes indistinguishable from Wakefulness or REM sleep. In fact, we show that spiking activity for all states has a universal scaling compatible with critical phenomena. We complement these results by a critical branching model that replicates our experimental findings, where we show that forcing OFF-periods to a percentage of neurons suffices to generate a decrease in complexity that replicates SWS.
An automated method for precise axon reconstruction from recordings of high-density micro-electrode arrays

Objective: Neurons communicate with each other by sending action potentials (APs) through their axons. The velocity of axonal signal propagation describes how fast electrical APs can travel. This velocity can be affected in a human brain by several pathologies, including multiple sclerosis, traumatic brain injury and channelopathies. High-density microelectrode arrays (HD-MEAs) provide unprecedented spatio-temporal resolution to extracellularly record neural electrical activity. The high density of the recording electrodes enables to image the activity of individual neurons down to subcellular resolution, which includes the propagation of axonal signals. However, axon reconstruction, to date, mainly relies on manual approaches to select the electrodes and channels that seemingly record the signals along a specific axon, while an automated approach to track multiple axonal branches in extracellular action-potential recordings is still missing. Approach: In this article, we propose a fully automated approach to reconstruct axons from extracellular electrical-potential landscapes, so-called ‘electrical footprints’ of neurons. After an initial electrode and channel selection, the proposed method first constructs a graph based on the voltage signal amplitudes and latencies. Then, the graph is interrogated to extract possible axonal branches. Finally, the axonal branches are pruned, and axonal action-potential propagation velocities are computed. Main results: We first validate our method using simulated data from detailed reconstructions of neurons, showing that our approach is capable of accurately reconstructing axonal branches. We then apply the reconstruction algorithm to experimental recordings of HD-MEAs and show that it can be used to determine axonal morphologies and signal-propagation velocities at high throughput. Significance: We introduce a fully automated method to reconstruct axonal branches and estimate axonal action-potential propagation velocities using HD-MEA recordings. Our method yields highly reliable and reproducible velocity estimations, which constitute an important electrophysiological feature of neuronal preparations.
Feedback alignment with weight normalization can provide a biologically plausible mechanism for learning

The mechanism by which plasticity in millions of synapses in the brain is orchestrated to achieve behavioral and cognitive goals is a fundamental question in neuroscience. In this regard, insights from learning methods in artiﬁcial neural networks (ANNs) and in particular the idea of backpropagation (BP) seem inspiring. However, the implementation of BP requires exact matching of forward and backward weights, which is unrealistic given the known connectivity pattern in the brain (known as ”weight transport problem”). Notably, it is recently shown that under certain conditions, error BackPropagation Through Random backward Weights (BP-TRW), can lead to partial alignment of forward and backward weights overtime (feedback alignment or FA) and result in surprisingly good accuracies in simple classiﬁcation tasks using shallow ANNs. In this work, we took a closer look at FA to ﬁnd out why it occurs when using BP-TRW and explored ways to boost it for deep ANNs. We ﬁrst show that the gradual alignment of forward and backward weights arises from the successive application of BP-TRW update rule on forward weights regardless of learning or loss function if error signals and outputs of neurons satisfy certain conditions such as when they are autocorrelated. Moreover, we show that FA in deeper networks can be improved signiﬁcantly by applying a biologically-inspired weight normalization (WN) to the input weights of each neuron. In addition, WN can improve the performance of both BP and BP-TRW when class labels are changed across time, an under-explored phenomenon in ANNs which is crucial for ﬂexible learning in the brain in everyday life. With WN, BP-TRW test accuracy can almost match that of BP following class label changes. Altogether, our results portray a clearer picture of the FA mechanism and provide evidence for how learning can occur using BP-like mechanisms while abiding by biological limits on synaptic weights.
Nanopore sequencing of RNA and cDNA molecules expands the transcriptomic toolbox in prokaryotes

High-throughput sequencing dramatically changed our view of transcriptome architectures and allowed for ground-breaking discoveries in RNA biology. Recently, sequencing of full-length transcripts based on the single-molecule sequencing platform from Oxford Nanopore Technologies (ONT) was introduced and is widely employed to sequence eukaryotic and viral RNAs. However, experimental approaches implementing this technique for prokaryotic transcriptomes remain scarce. Here, we present an experimental and bioinformatic workflow for ONT RNA-seq in the bacterial model organism Escherichia coli, which can be applied to any microorganism. Our study highlights critical steps of library preparation and computational analysis and compares the results to gold standards in the field. Furthermore, we comprehensively evaluate the applicability and advantages of different ONT-based RNA sequencing protocols, including direct RNA, direct cDNA, and PCR-cDNA. We find that cDNA-seq offers improved yield and accuracy without bias in quantification compared to direct RNA sequencing. Notably, cDNA-seq can be readily used for simultaneous transcript quantification, accurate detection of transcript 5′ and 3′ boundaries, analysis of transcriptional units and transcriptional heterogeneity. In summary, we establish Nanopore RNA-seq to be a ready-to-use tool allowing rapid, cost-effective, and accurate annotation of multiple transcriptomic features thereby advancing it to become a standard method for RNA analysis in prokaryotes.
Personalized Antiplatelet Therapy Based on CYP2C19 Genotypes in Chinese ACS Patients Undergoing PCI: A Randomized Controlled Trial

Background: The clinical benefits of cytochrome P450 (CYP) 2C19 genotype-guided antiplatelet therapy in Asians remain unclear. In this study, we aimed to investigate the clinical outcomes of pharmacogenomic antiplatelet therapy in Chinese patients. Methods: Patients with acute coronary syndrome planning to undergo percutaneous coronary intervention were eligible for this study and were randomly divided into a genotype-guided treatment (GT) group and routine treatment (RT) group, with a ratio of 2:1. Patients in the GT group underwent CYP2C19 genotyping (*2 and *3 alleles), and the results were considered in selecting P2Y12 receptor inhibitors. Patients in the RT group were treated with P2Y12 receptor inhibitors according to their clinical characteristics. The primary endpoint was a composite of major adverse cardiovascular or cerebrovascular events (MACCE). The secondary endpoint was significant bleeding events. Results: Finally, 301 patients were enrolled; 75.1% were men and the mean age was 59.7 ± 9.8 years. In total, 281 patients completed the follow-up procedure. The primary endpoint occurred in 16 patients, 6 patients in the GT group and 10 in the RT group. The GT group showed lower MACCE rates than the RT group (6/189 vs. 10/92, 3.2 vs. 10.9%, hazard ratio: 0.281, 95% confidence interval: 0.102–0.773, P = 0.009). There was no statistically difference in significant bleeding events between the GT and RT groups (4.2 vs. 3.3%, hazard ratio: 1.315, 95% confidence interval: 0.349–4.956, P = 0.685). Conclusion: Personalized antiplatelet therapy that is based on CYP2C19 genotypes could decrease MACCE within a 12-month period in Chinese patients with acute coronary syndrome undergoing percutaneous coronary intervention. Clinical Trial Registration: http://www.chictr. org.cn, identifier: ChiCTR2000034352.
An in silico hiPSC-Derived Cardiomyocyte Model Built With Genetic Algorithm

The formulation of in silico biophysical models generally requires optimization strategies for reproducing experimentally observed phenomena. In electrophysiological modeling, robust nonlinear regressive methods are often crucial for guaranteeing high fidelity models. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), though nascent, have proven to be useful in cardiac safety pharmacology, regenerative medicine, and in the implementation of patient-specific test benches for investigating inherited cardiac disorders. This study demonstrates the potency of heuristic techniques at formulating biophysical models, with emphasis on a hiPSC-CM model using a novel genetic algorithm (GA) recipe we proposed. The proposed GA protocol was used to develop a hiPSC-CM biophysical computer model by fitting mathematical formulations to experimental data for five ionic currents recorded in hiPSC-CMs. The maximum conductances of the remaining ionic channels were scaled based on recommendations from literature to accurately reproduce the experimentally observed hiPSC-CM action potential (AP) metrics. Near-optimal parameter fitting was achieved for the GA-fitted ionic currents. The resulting model recapitulated experimental AP parameters such as AP durations (APD50, APD75, and APD90), maximum diastolic potential, and frequency of automaticity. The outcome of this work has implications for validating the biophysics of hiPSC-CMs in their use as viable substitutes for human cardiomyocytes, particularly in cardiac safety pharmacology and in the study of inherited cardiac disorders. This study presents a novel GA protocol useful for formulating robust numerical biophysical models. The proposed protocol is used to develop a hiPSC-CM model with implications for cardiac safety pharmacology.
Aggressive Cushing’s Disease: Molecular Pathology and Its Therapeutic Approach

Cushing’s disease is a syndromic pathological condition caused by adrenocorticotropic hormone (ACTH)-secreting pituitary adenomas (ACTHomas) mediated by hypercortisolemia. It may have a severe clinical course, including infection, psychiatric disorders, hypercoagulability, and metabolic abnormalities, despite the generally small, nonaggressive nature of the tumors. Up to 20% of ACTHomas show aggressive behavior, which is related to poor surgical outcomes, postsurgical recurrence, serious clinical course, and high mortality. Although several gene variants have been identified in both germline and somatic changes in Cushing’s disease, the pathophysiology of aggressive ACTHomas is poorly understood. In this review, we focused on the aggressiveness of ACTHomas, its pathology, the current status of medical therapy, and future prospects. Crooke’s cell adenoma (CCA), Nelson syndrome, and corticotroph pituitary carcinoma are representative refractory pituitary tumors that secrete superphysiological ACTH. Although clinically asymptomatic, silent corticotroph adenoma is an aggressive ACTH-producing pituitary adenoma. In this review, we summarize the current understanding of the pathophysiology of aggressive ACTHomas, including these tumors, from a molecular point of view based on genetic, pathological, and experimental evidence. The treatment of aggressive ACTHomas is clinically challenging and usually resistant to standard treatment, including surgery, radiotherapy, and established medical therapy (e.g., pasireotide and cabergoline). Temozolomide is the most prescribed pharmaceutical treatment for these tumors. Reports have shown that several treatments for patients with refractory ACTHomas include chemotherapy, such as cyclohexyl-chloroethyl-nitrosourea combined with 5-fluorouracil, or targeted therapies against several molecules including vascular endothelial growth factor receptor, cytotoxic T lymphocyte antigen 4, programmed cell death protein 1 (PD-1), and ligand for PD-1. Genetic and experimental evidence indicates that some possible therapeutic candidates are expected, such as epidermal growth factor receptor tyrosine kinase inhibitor, cyclin-dependent kinase inhibitor, and BRAF inhibitor. The development of novel treatment options for aggressive ACTHomas is an emerging task.
Letrozole for Female Infertility

Letrozole, an aromatase inhibitor that blocks estrogen synthesis by inhibiting the final step of the estrogen biosynthetic pathway, has been used in the applications of a wide range of infertility settings. It has been more than 20 years since the initial clinical trial of letrozole for ovulation induction. In light of the accumulating clinical and basic evidence, the efficacy and safety of letrozole have been identified. This mini review focuses on our current knowledge of the applications and mechanisms of letrozole for female infertility and various questions are put forward about how letrozole could be more effectively used.
Enhanced Mechanical Properties of Fe-Mn-Al-C Low Density Steel via Aging Treatment

This study investigated the tensile properties and deformation behavior of an aged Fe-26Mn-6Al-1C (mass%) alloy with a stacking fault energy of approximately 60 mJ·m−2. The results show that an ordered phase with a “short-range ordering” (SRO) structure formed after aging at 550°C for 10 h, further increasing the aging time to 48 h. Lamellar second-phase precipitates appeared at the austenitic grain boundaries. The aged sample at 550°C for 10 h exhibited an enhanced tensile strength (∼898 MPa) without notably sacrificing uniform elongation (∼46.3%), which was mainly attributed to the relatively high strain hardening in the entire plastic deformation due to the synergistic effects of planar slip, twinning-induced plasticity (TWIP), microband-induced plasticity (MBIP), and especially the formation of short-range ordering.
Dietary Supplementation With Xylo-oligosaccharides Modifies the Intestinal Epithelial Morphology, Barrier Function and the Fecal Microbiota Composition and Activity in Weaned Piglets

The present study determined the effects of dietary xylo-oligosaccharides (XOS) supplementation on the morphology of jejunum and ileum epithelium, fecal microbiota composition, metabolic activity, and expression of genes related to colon barrier function. A total of 150 piglets were randomly assigned to one of five groups: a blank control group (receiving a basal diet), three XOS groups (receiving the basal diet supplemented with 100, 250, and 500 g/t XOS, respectively), as well as a positive control group, used as a matter of comparison, that received the basal diet supplemented with 0.04 kg/t virginiamycin, 0.2 kg/t colistin, and 3,000 mg/kg ZnO. The trial was carried out for 56 days. The results showed that the lowest dose tested (100 g/t XOS) increased (P < 0.05) the ileal villus height, the relative amount of Lactobacillus and Bifidobacterium spp. , and the concentration of acetic acid and short-chain fatty acid in feces when compared with the blank control group. In conclusion, dietary 100 g/t XOS supplementation modifies the intestinal ecosystem in weaned piglets in an apparently overall beneficial way.
A Study on the Hysteresis Effect and Spectral Evolution in the Mini-Outbursts of Black Hole X-Ray Binary XTE J1550-564

One normal outburst and three mini-outbursts have been detected by Rossi X-ray Timing Explorer satellite after 2000 in the well-known black hole X-ray binary XTE J1550-564. In this work, we explore the hysteresis effect of the four outbursts, which is a phenomenon that a similar spectral state transition occurs at different luminosity in an outburst of black hole X-ray binary. A q-like track was found in the hardness-intensity diagram of the normal outburst in 2000 but not in the three mini-outbursts that only occur in the Low/Hard state. The results demonstrate that the hysteresis effect is not apparent in the three mini-outbursts and the X-ray spectra are harder than that of the normal outburst at the same photon count rate. Furthermore, the results of the correlation analysis show that the Γ − F2−10keV correlation of mini-outburst maintain negative in the Low/Hard state with the harder spectra than that of the normal outburst at the same X-ray flux. The X-ray spectral evolution can be well-explained by the state-transition model from the Shakura–Sunyaev disk to the advection-dominated accretion flow, which implies that the three mini-outbursts of XTE J1550-564 might originate from a smaller discrete accretion event.