Miracle-dz/UniFAR-FTUs huggingface dataset:
Inline SAXS-coupled chromatography under extreme hydrostatic pressure

As continuing discoveries highlight the surprising abundance and resilience of deep ocean and subsurface microbial life, the effects of extreme hydrostatic pressure on biological structure and function have attracted renewed interest. Biological small angle X-ray scattering (BioSAXS) is a widely used method of obtaining structural information from biomolecules in solution under a wide range of solution conditions. Due to its ability to reduce radiation damage, remove aggregates, and separate monodisperse components from complex mixtures, size-exclusion chromatography coupled SAXS (SEC-SAXS) is now the dominant form of BioSAXS at many synchrotron beamlines. While BioSAXS can currently be performed with some difficulty under pressure with non-flowing samples, it has not been clear how, or even if, continuously flowing SEC-SAXS, with its fragile media-packed columns, might work in an extreme high-pressure environment. Here we show, for the first time, that reproducible chromatographic separations coupled directly to high-pressure BioSAXS can be achieved at pressures up to at least 100 MPa and that pressure-induced changes in folding and oligomeric state and other properties can be observed. The apparatus described here functions at a range of temperatures (0° C - 50° C), expanding opportunities for understanding biomolecular rules of life in deep ocean and subsurface environments.
Mineral Soils Are an Important Intermediate Storage Pool of Black Carbon in Fennoscandian Boreal Forests

Approximately 40% of earth's carbon (C) stored in land vegetation and soil is within the boreal region. This large C pool is subjected to substantial removals and transformations during periodic wildfire. Fire‐altered C, commonly known as pyrogenic carbon (PyC), plays a significant role in forest ecosystem functioning and composes a considerable fraction of C transport to limnic and oceanic sediments. While PyC stores are beginning to be quantified globally, knowledge is lacking regarding the drivers of their production and transport across ecosystems. This study used the chemo‐thermal oxidation at 375°C (CTO‐375) method to isolate a particularly refractory subset of PyC compounds, here called black carbon (BC), finding an average increase of 11.6 g BC m−2 at 1 year postfire in 50 separate wildfires occurring in Sweden during 2018. These increases could not be linked to proposed drivers, however BC storage in 50 additional nearby unburnt soils related strongly to soil mass while its proportion of the larger C pool related negatively to soil C:N. Fire approximately doubled BC stocks in the mineral layer but had no significant effect on BC in the organic layer where it was likely produced. Suppressed decomposition rates and low heating during fire in mineral subsoil relative to upper layers suggests potential removals of the doubled mineral layer BC are more likely transported out of the soil system than degraded in situ. Therefore, mineral soils are suggested to be an important storage pool for BC that can buffer short‐term (production in fire) and long‐term (cross‐ecosystem transport) BC cycling.
SlideCNA: Spatial copy number alteration detection from Slide-seq-like spatial transcriptomics data

Solid tumors are spatially heterogeneous in their genetic, molecular and cellular composition, and this variation can be meaningful for diagnosis, prognosis and therapy. Recent spatial profiling studies have mostly charted genetic and RNA variation in tumors separately. To leverage the potential of RNA to identify copy number alterations (CNAs), we developed SlideCNA, a computational tool to extract sparse spatial CNA signals from spatial transcriptomics data, using expression-aware spatial binning. We test SlideCNA on simulated and real Slide-seq data of metastatic breast cancer (MBC) and demonstrate its potential for spatial sub-clone detection.
Arabidopsis transcriptome responses to low water potential using high throughput plate assays

Soil-free assays that induce water stress are routinely used to investigate drought responses in the plant Arabidopsis thaliana. Due to their ease of use, the research community often relies on polyethylene glycol (PEG), mannitol and salt (NaCl) treatments to reduce the water potential of agar media, and thus induce drought conditions in the laboratory. However, while these types of stress can create phenotypes that resemble those of water deficit experienced by soil-grown plants, it remains unclear how these treatments compare at the transcriptional level. Here, we demonstrate that these different methods of lowering water potential elicit both shared and distinct transcriptional responses in Arabidopsis shoot and root tissue. When we compared these transcriptional responses to those found in Arabidopsis roots subject to vermiculite drying, we discovered many genes induced by vermiculite drying were repressed by low water potential treatments on agar plates (and vice versa). Additionally, we also tested another method for lowering water potential of agar media. By increasing the nutrient content and tensile strength of agar, we show the ‘hard agar’ (HA) treatment can be leveraged as a high-throughput assay to investigate natural variation in Arabidopsis growth responses to low water potential.
Equality of Corecursive Streams Defined by Finitary Equational Systems

In recent work, non-regular streams have been defined corecursively, by representing them with finitary equational systems built on top of various operators, besides the standard constructor. With finitary equational systems based only on the stream constructor, one can use the free theory of regular (a.k.a. rational) trees to get a sound and complete procedure to decide whether two streams are equal. However, this is not the case if one allows other operators in equations, since the underlying equational theory becomes non-trivial, hence equality of regular trees is too strong to guarantee termination of corecursive functions defined even only with the constructor and tail operators. To overcome this problem, we provide a weaker definition of equality between streams denoted by finitary equational systems built on different stream operators, including tail operator and constructor, and prove its soundness.
Reactivating Positive Personality Traits During Sleep Impacts Self-Evaluative Memories

28 People tend to view themselves through rose-tinted glasses, as evidenced by preferential recall of 29 positive personality traits. We asked whether reactivating positive personality traits during sleep 30 could enhance peoples’ positive self-evaluative memories. After a baseline self-referential 31 encoding task in which participants endorsed positive and negative traits as self-descriptive, 32 participants were trained to give timely responses to positive traits in a cue-approach training 33 (CAT) task. Once participants had entered slow-wave sleep during a subsequent nap, half of the 34 trained positive traits were unobtrusively re-played to them to promote consolidation (targeted 35 memory reactivation, TMR). Participants completed free-recall tasks about self-descriptive traits 36 to measure their self-evaluative memories. Our findings revealed that TMR prioritized the recall 37 of positive traits that were strongly memorized before sleep, while impairing the recall of 38 intermediate traits. The results suggest pre-TMR self-evaluative memory strength modulated the 39 TMR benefits. Sleep EEG analyses revealed that compared with weak/intermediate/control traits, 40 re-playing strongly memorized traits during sleep elicited greater sigma power changes, which 41 likely reflect preferential memory reactivation. Our results demonstrate the potential implication 42 of wakeful cue-approach training and sleep-based memory reactivation in strengthening positive 43 self-evaluative memories.
Inferring delays in partially observed gene regulatory networks

Motivation Cell function is regulated by gene regulatory networks (GRNs) defined by protein-mediated interaction between constituent genes. Despite advances in experimental techniques, we can still measure only a fraction of the processes that govern GRN dynamics. To infer the properties of GRNs using partial observation, unobserved sequential processes can be replaced with distributed time delays, yielding non-Markovian models. Inference methods based on the resulting model suffer from the curse of dimensionality. Results We develop a simulation-based Bayesian MCMC method for the efficient and accurate inference of GRN parameters when only some of their products are observed. We illustrate our approach using a two-step activation model: An activation signal leads to the accumulation of an unobserved regulatory protein, which triggers the expression of observed fluorescent proteins. With prior information about observed fluorescent protein synthesis, our method successfully infers the dynamics of the unobserved regulatory protein. We can estimate the delay and kinetic parameters characterizing target regulation including transcription, translation, and target searching of an unobserved protein from experimental measurements of the products of its target gene. Our method is scalable and can be used to analyze non-Markovian models with hidden components. Availability Accompanying code in R is available at https://github.com/Mathbiomed/SimMCMC. Contact jaekkim@kaist.ac. kr or kresimir.josic@gmail.com or cbskust@korea.ac. kr Supplementary information Supplementary data are available at Bioinformatics online.
A conditional histone H3.3 mutation in mice orthologous to a driver of paediatric diffuse instrinsic pontine glioma

Most paediatric diffuse intrinsic pontine gliomas carry a lysine- to methionine-27 (K27M) mutation in the histone variant H3.3 encoded by the ‘H3.3 histone A’ (H3F3A) gene. To establish a pre-clinical model of the disease we made a Cre/loxP conditional H3.3K27M mutation at the orthologous H3f3a locus in mice. Importantly, expression of the mutant transcript is under endogenous H3f3a regulatory control. This system is distinct from others in which H3.3M27 is ectopically expressed, thereby providing a resource for the development of pDIPG models with orthologous regulation of mutant H3.3. Mice in which expression of the mutant transcript was induced with a nestin-cre transgene developed as dwarfs in the presence of intact growth hormone signaling.
Isolation and characterization of a novel phage of Vibrio parahaemolyticus with biocontrol potential

Vibrio parahaemolyticus is a major foodborne pathogen that contaminates aquatic products and causes great economic losses to aquaculture. Because of the emergence of multidrug-resistant V. parahaemolyticus strains, bacteriophages are considered promising agents for their biocontrol as an alternative or supplement to antibiotics. Here, a lytic vibriophage, vB_VpaM_R16F (R16F), was isolated from sewage from a seafood market by infecting V. parahaemolyticus 1.1997T. R16F was found to infect V. parahaemolyticus, but not nine other Vibrio spp. The phage belongs to the myovirus morphotype and lysed host cells with a short latent period (<10 min) and a small burst size (13 plaque-forming units). R16F has a linear double-stranded DNA with genome size 139,011 bp and a G+C content of 35.21%. Phylogenetic and intergenomic nucleotide sequence similarity analysis revealed that R16F is distinct from currently known vibriophages and belongs to a novel genus. Several genes (e.g., encoding ultraviolet damage endonuclease and endolysin) that may enhance environmental competitiveness were found in the genome of R16F, while no antibiotic resistance- or virulence factor-related gene was detected. In consideration of its biological and genetic properties, R16F is suggested to be a candidate biocontrol agent for use against V. parahaemolyticus.
Comparison and Combination of Leaky ReLU and ReLU Activation Function and Three Optimizers on Deep CNN for COVID-19 Detection

COVID-19 detection is an interesting field of study in the medical world and the commonly used method is classification. In determining the best detection model, several classification architectures, such as SVM, KNN, and CNN were utilized. The CNN is a changeable architecture due to having combinations of varying numbers of hidden layers or different activation and optimizer functions. Therefore, this study uses a deep CNN architecture with a combination of Leaky ReLU activation functions and 3 different optimizers, which include Adagrad, Adadelta, and Adamax. The results showed that the combination of the Leaky ReLU activation function and the Adamax optimizer produced good and stable accuracy in the CRX and CT datasets. © 2022 The authors and IOS Press.
Distributed Programming of Smart Systems with Event-Condition-Action Rules

In recent years, event-driven programming languages, e.g. those based on Event Condition Action (ECA) rules, have emerged as a promising paradigm for implementing smart systems, such as IoT devices. Still, actual implementations are bound to a centralized infrastructure, limiting scalability and security. In this work, we present attribute-based memory updates (AbU), a new interaction mechanism aiming to extend the ECA programming paradigm to distributed systems. It relies on attribute-based communication , that is similar to broadcast, but receivers are selected “on the fly” by means of predicates over their attributes. With AbU, smart devices can be easily programmed via ECA rules and, at the same time, they can be deployed to a distributed network. Hence, a centralized infrastructure is not needed anymore: the computation is moved on the edge , improving reliability, scalability, privacy and security.
Computing Eternal Vertex Cover Number on Maximal Outerplanar Graphs in Linear Time

Eternal vertex cover problem is a variant of the classical vertex cover problem modeled as a two player attacker-defender game. Computing eternal vertex cover number of graphs is known to be NP-hard in general and even for bipartite graphs. There is a quadratic complexity algorithm known for this problem for chordal graphs. Maximal outerplanar graphs forms a subclass of chordal graphs, for which no algorithm of sub-quadratic time complexity is known. In this paper, we obtain a linear time recursive algorithm for computing eternal vertex cover number of maximal outerplanar graphs.
Zero Relaxation Limit to Centered Rarefaction Waves for a Rate-Type Viscoelastic System

Abstract We study a rate-type viscoelastic system proposed by I. Suliciu (1990, Internat. J. Engrg. Sci. 28 , 827–841), which is a 3×3 hyperbolic system with relaxation. As the relaxation time tends to zero, this system convergences to the well-known p -system formally. In the case where the initial data are the Riemann data such that the corresponding solutions of the p -system are centered rarefaction waves, we show that if the wave strength is suitably small, then the solution for the relaxation system exists globally in time and converges to the solution of the corresponding rarefaction waves uniformly as the relaxation time goes to zero, except for an initial layer. The jump discontinuities in the solutions are decaying exponentially fast as time tends to infinity.
Analyzing and designing of reliable multicast based on FEC in distributed switch

AS businesses become more dependent on IP networks, lots of real-time services are adopted and high availability in networks has become increasingly critical. With the development of carrier grade ethernet, the requirements of high speed metro ethernet device are more urgently. In order to reach the capacity of hundreds of Gbps or Tbps, most of core ethernet switches almost adopted distributed control architecture and large capacity forwarding fabric. When distributed switch works, they always have one CE and many FE. There for, it shows the feature of multicast with one sender and many receivers. It is deserved research for us how to apply reliable multicast to distributed switch inner communication system. In this paper, we present the general architecture of a distributed ethernet switch, focusing on analysis the model of internal communication subsystem. According to its character, a novel reliable multicast communication mechanism based on FEC recovery algorithm has been applied and evaluated in experiment.
Geometric Programming: Methods, Computations and Applications

In this paper, we give an applications-oriented survey of geometric programming. This important class of nonlinear programming problems has been intensively studied over the past decade and has played a crucial role in an extremely broad range of applications. The focus of the paper will be on posynomial programs and the slightly more general class of signomial programs. The approach used in studying posynomial programs has been generalized to a much broader class of optimization problems, and an excellent survey of that generalized theory recently appeared in a paper by E. L. Peterson [SIAM Rev., 18 (1976), pp. 1–51]. We do not consider that generalized theory here. It is our intent to provide the reader with an understanding of the basic results in posynomial and signomial programming that have played a crucial role in applications. After reviewing these basic results, we consider computational methods and applications. Three specific applications are considered in detail, and a bibliography indicating .
Developing an immersed boundary method for compressible flow

Development of a 3D sharp interface ghost node immersed boundary method (IBM) within a fluid solver based on the compressible Navier–Stokes equations is underway. The objective of the IBM is to accurately apply boundary conditions at fluid–solid interfaces. The Navier–Stokes solver is currently being verified using various test cases, including the classic cylinder in cross flow. As part of this verification process, particular attention was given to investigating the effects of different lateral boundary conditions. The results demonstrate that extrapolation boundary conditions exhibit better agreement with the literature compared to symmetry conditions, in cases with relatively narrow domains. These findings highlight the potential benefits of extrapolation boundary conditions in reducing confinement effects and removing nonphysical waves in external flow problems.
A Pedagogy of Mentoring

Sizable numbers of secondary school students require sustained one to one guidance to overcome gaps between their level of acquired skills and the academic outcomes they are expected to master. This article articulates a pedagogy of academic mentoring for educators to support underachieving students with one to one intervention. Academic mentors go beyond traditional tutors, using modeling and metacognitive techniques that allow students to consciously manipulate the internal cognitive strategies necessary for mastery, particularly of textual interpretation. The mentor makes the construction of meaning explicit by expressing thinking strategies out loud, thereby making them transmissible. By adopting the role of partner in shared academic exploration, the mentor incubates a student’s underlying potential through the medium of caring relationship.
The Role of Verbal Representation in Assessment of Category Judgments

The study examines the role of inner speech measured by verbal representation scale in assessment of category judgments and in transfer from the category example to the whole category. We used the conventionality effect of the category label, meaning that people perceive judgments containing commonly used category labels as more convincing even when the category itself is new, and its label is artificial [11]. We proposed that this effect can be enhanced if to use a metaphorical label for the category that emphasizes its feature. We also tested whether the metaphorical label could enhance the transfer of the feature from the category example to the whole category. We hypothesized that the conventionality effect and transfer of the trait will be different in participants depending on their level of verbal representation. In the first part of the study, we adapted the Internal Representation Questionnaire [16] and used verbal representation scale from it to divide participants into groups by their level of inner speech. The results show that participants with higher level of verbal representation were less influenced by the conventionality effect of the label. We also found that participants with lower level of verbal representation were more prone to transfer information of the metaphorical labels. Otherwise, participants with higher level of verbal representation were more inclined to transfer category information of non-metaphorical labels. The findings indicate the relationship between individual differences in verbal representation level and evaluation of category judgments.
A study on morphological, anatomical and phytochemical tests of Aesculus assamica Griffith. leaves and its antioxidant activity

Aesculus assamica Griffith. is locally known as Ye-myaw in Myanmar and this plant belongs to the family Hippocastanaceae had been studied. It was collected from Lo Kha Lo village, Pha Saung Township, Kayah State. The morphological characters of this plant were studied for classification and identification. Aesculus assamica Griffith. is tree with thyrus cylindric inflorescence and pale yellow flower. Fruits are capsule, depressed globose and hilum dark brown. In the anatomical study,the leaves of Aesculus assamica Griffith. were investigated. The anticlinal walls of upper surface of lamina are wavier than the lower one. Anomocytic type of stomata is present on both surfaces but more abundant stomata on lower surface. Circular-shaped of vascular bundle, closed collateral types are present in midrib and petiole. In the diagonostic characters, the odour of leaves is pungent. In the preliminary phytochemical tests, Aesculus assamica Griffith. leaves were found to be abundant alkaloid and saponin. Antioxidant activity , total phenolic contents and total flavonoid contents of investigations on the leaves of Aesculus assamica Griffith . were tested. All of these extracts of Aesculus assamica Griffith. leaves have the antioxidant activity.
CONTRIBUTIONS OF GRAIN SORGHUM TO NATURAL ENEMY POPULATIONS IN COTTON

Grain sorghum and cotton are grown in close association in most regions of Texas, and share a number of predators which can provide natural control of cotton bollworm and tobacco budworm in mid-late season cotton. The focus of this study was to determine the role of grain sorghum as a source of predators in cotton in the Southern Rolling Plains of Texas by identifying and quantifying important predators in grain sorghum and cotton through direct counts and collection, and quantifying the movement of predators from grain sorghum to cotton by self-marking of predators with fluorescent dust in sorghum and recovery of marked predators in adjacent cotton. Results show many of the common predators increase in both grain sorghum and cotton from early bloom of sorghum to hard dough stage, and continue to increase in cotton after sorghum harvest. Recovery of marked predators in cotton provide further evidence that grain sorghum is an important source of predators in cotton at a time when cotton is at risk from bollworm and budworm infestations.