Miracle-dz/UniFAR-FTUs huggingface dataset:
NEUTRON MEASUREMENTS AT HANFORD’S PLUTONIUM FINISHING PLANT

The Pacific Northwest National Laboratory (PNNL) conducted neutron measurements at Hanford’s Plutonium Finishing Plant (PFP). The measurements were performed to evaluate the performance of the Hanford Standard Dosimeter (HSD) and the 8816 TLD component of the Hanford Combination Neutron Dosimeter (HCND) in the neutron fields responsible for worker neutron exposures. For this study, TEPC detectors and multisphere spectrometers were used to measure neutron dose equivalent rate, and multispheres were used to measure average neutron energy. Water-filled phantoms holding Hanford dosimeters were positioned at each measurement location. The phantoms were positioned in the same location where a multisphere measurement was taken and TEPCs were also positioned there. Plant survey meters were also used to measure neutron dose rates at all locations. Three measurement locations were chose near the HC-9B glovebox in room 228A of Building 234-5. The multisphere spectrometers measured average neutron energies in the range of 337 to 555 keV at these locations. Personal dose equivalent, Hp(10)n, as measured by the multisphere and TEPC, ranged from 2.7 to 9.7 mrem/h in the three locations. Effective dose assuming a rotational geometry (EROT) was substantially lower than Hp(10), ranging from 1.3 to 3.6 mrem/h. These values were lower than the reported values more » from dosimeters exposed on a rotating phantom. Effective dose assuming an AP geometry (EAP) was also substantially lower than Hp(10), ranging from 2.3 to 6.5 mrem/h. These values were lower than the reported values from the dosimeters on slab phantoms. Since the effective dose values were lower than reported values from dosimeters, the dosimeters were shown to be conservative estimates of the protection quantities. « less
Unifying Liquid and Granular Flow

Adding suspended particles to a fluid increases its viscosity. When the particles are widely separated, this increased viscosity reflects their hydrodynamic interactions. At higher volume fractions, however, contacts between particles become important, and eventually jamming occurs and the viscosity diverges. While this phenomenology is known, there is no general theory that predicts how the viscosity depends on volume fraction, particularly when both hydrodynamics and collisions are significant [1]. In a paper in Physical Review Letters[2], Francois Boyer and colleagues from Aix-Marseille University in France study suspensions using a framework previously used to describe the flow of dry granular materials, in which particles interact solely through contacts. In addition to unifying our understanding of the flow behavior (rheology) of two quite different systems, the work of Boyer et al. provides important new perspectives on both the jamming transition [3] and the rheology of suspensions such as mud, paints, and medicines.
Fibonacci Spiral Search for Block Matching in Video Coding

In video coding schemes, block matching algorithm is the key element for motion estimation. Motion estimation can significantly improve video coding efficiency by reducing temporal redundancy existing in a video sequence. In this paper, we propose a new algorithm using Fibonacci Spiral Search (FSS) for fast block motion estimation. The proposed FSS algorithm finds small motion vectors with fewer search points. The experimental results are compared with the various fast motion estimation algorithms that have been employed in H.264 video standard. The reduction in the number of search points significantly reduces the computational complexity and paved the way for speedy compression.
An Efficient Approach to a Class of Non-smooth Optimization Problems

This paper presents an entropy-based smoothing technique for solving a class of non-smooth optimization problems that are in some way related to the maximum function.Basic ideas concerning this approach are that we replace the non-smooth maximum function by a smooth one,called aggregate function,which is derived by employing the maximum entropy principle and its useful properties are proved.Wilh this smoothing technique,both unconstrained and constrained mimma.x problems are transformed into unconstrained optimization problems of smooth functions such that this class of non-smooth optimization problems can be solved by some existing unconstrained optimization softwares for smooth functions The present approach can be very easily implemented on computers with very fast and -. Inhie convergence.
Resilience Mediates the Relationship Between Parental Attachment and Posttraumatic Growth in Adolescents: A Longitudinal Study

Abstract Objective: Previous studies have shown that parental attachment was associated with higher levels of posttraumatic growth (PTG) in individuals who have experienced traumatic events. The aim of the current longitudinal study is to investigate resilience as one pathway through which parental attachment is related to PTG among Chinese adolescents following the Yancheng tornado. Methods: A total of 351 adolescent survivors participated in this longitudinal study. Participants completed the revised version of Inventory of Parent and Peer Attachment (IPPA-R) at 12 months (T1), and the revised Chinese version of the Post-Traumatic Growth Inventory (PTGI-R) and the Connor and Davidson’s Resilience Scale (CD-RISC) at 18 months (T2) after the tornado, respectively. Results: It indicated that parental attachment at T1 has direct and positive effect on PTG at T2, and resilience at T2 fully mediated the relationship between parental attachment at T1 and PTG at T2. Conclusion: The findings revealed that parental attachment and resilience are two key resources that promote adolescent’s PTG, and parental attachment acts through resilience to promote PTG in adolescents.
A twisted rudder for reduced cavitation

A rudder operating behind a propeller can experience large onset flow angles along the rudder span. At a given speed, the maximum rudder angle before cavitation is substantially higher in turning to one direction than to the opposite side. At high speeds, rudders can experience severe surface cavitation, even at zero degree rudder deflection angle. Observation from full-scale trials and dry dock inspection of a surface ship combatant show that rudder cavitation is a real problem in terms of ship operation and maintenance. It is shown in this paper that cavitation inception and erosion problems associated with the existing fleet rudders can be avoided or reduced by using the concept of a twisted rudder. A fleet rudder can be twisted along its span to align the incoming flow. The twisted rudder model has been designed, fabricated, and tested in the Navy's Large Cavitation Channel (LCC). Two-component Laser Doppler Velocimetry (LDV) was used to measure the field velocity and inflow angles in the propeller slipstream. A dynamometer and a series of pressure taps were used to measure rudder lift, drag and pressure distributions on the rudder surface. To evaluate the effect of twist angles on rudder performances, a full-scale rudder, designated the non-twisted rudder, has also been fabricated and tested back-to-back in the LCC with the twisted rudder for direct comparison. The advantages of using a twisted rudder to improve cavitation performance are presented in this paper.
High-power semiconductor laser chips for fiber-laser-based Lidar pump applications

Fiber lasers are becoming an increasingly important option for LIDAR light sources in autonomous driving technology due to their operation in the eye safe 1550 nm spectral region and their intrinsic high beam quality, power and pulse characteristics. As an essential component for the pumping of fiber lasers, semiconductor laser diodes with high temperature stability, power and reliability are necessary. In this report we present the results of a continuous-wave (CW) single edge emitting laser diode designed to operate at 94x nm at 25 °C heat sink temperature and 97x nm at 100 °C. Various epitaxial and laser geometry designs have been implemented to optimize the laser performance over this wide environmental temperature range. The laser epitaxy is based on the AlGaAs/GaAs material system, with an InGaAs strained quantum well (QW). With various designs of laser geometry including emitting area and cavity length, devices are designed, grown, fabricated, and tested with the optimized design improving the temperature stability, power, and efficiency of the laser chip. A peak efficiency of over 54% at heat sink temperature of 105 °C and over 12 W before thermal roll-over occurs has been achieved. In addition to the thermal performance we also report the slow axis beam parameter product of the chip of <5 mm.mrad with polarization purity >98% at operating current and show the preliminary reliability data at the high temperature operation.
Online political communication about the Tokyo Olympics

ABSTRACT This article investigates how Japanese politicians and their followers tweeted about the Tokyo Olympics between 1 January 2020 and 24 September 2021. Using a comprehensive dataset of Japanese politicians’ tweets and followers, plus text (sentiment) and network analysis, it finds that politicians from the ruling Liberal Democratic Party (LDP) stayed relatively quiet about the Games but did tweet positively about the Games after they started. In contrast, the Japanese Communist Party (JCP) politicians tweeted energetically in their attempt to have the Games cancelled. Politicians from other parties were more muted, in line with the levels of interest expressed by their followers. Followers of Kōmeitō politicians, junior coalition partners of the LDP, tweeted much less about the Games than users following LDP politicians. These findings were repeated when politically interested users were grouped into clusters of mutual followers. Overall, this suggests that the Olympics were a polarizing issue in Japan, with users following opposition figures strongly opposed to the Games while those following the largest governing party were more supportive.
Dual Graph Convolution Architecture Search for Travel Time Estimation

Travel time estimation (TTE) is a crucial task in intelligent transportation systems, which has been widely used in navigation and route planning. In recent years, several deep learning frameworks have been proposed to capture the dynamic features of road segments or intersections for travel time estimation. However, most existing works do not consider the joint features of the intersections and road segments. Moreover, most deep neural networks for TTE are designed based on empirical knowledge. Since the independent and joint features of intersections and road segments commonly vary with different datasets, the empirical deterministic neural architectures have limited adaptability to different scenarios. To tackle the above problems, we propose a novel automated deep learning framework, namely Automated Spatio-Temporal Dual Graph Convolutional Networks (Auto-STDGCN), for travel time estimation. Specifically, we propose to construct the node-wise graph and edge-wise graph to characterize the spatio-temporal features of intersections and road segments, respectively. In order to capture the joint spatio-temporal correlations of the dual graphs, a hierarchical neural architecture search approach is introduced, whose search space is composed of internal and external search space. In the internal search space, spatial graph convolution and temporal convolution operations are adopted to capture the respective spatio-temporal correlations of the dual graphs. Further, we design the external search space including the node-wise and edge-wise graph convolution operations from the internal architecture search to capture the interaction patterns between the intersections and road segments. We evaluate our proposed model Auto-STDGCN on three real-world datasets, which demonstrates that our model is significantly superior to the state-of-the-art methods. In addition, we also conduct case studies to visualize and explain the neural architectures learned by our model.
Hierarchical Resource Orchestration Framework for Real-Time Containers

Container-based virtualization is a promising deployment model in fog and edge computing applications because it allows a seamless co-existence of virtualized applications in a heterogeneous environment without introducing significant overhead. Certain application domains (e.g., industrial automation, automotive, or aerospace) mandate that applications exhibit a certain degree of temporal predictability. Container-based virtualization cannot be easily used for such applications since the technology is not designed to support real-time properties and handle temporal disturbances. This paper proposes a framework consisting of a static offline and a dynamic online phase for resource allocation and adaptive re-dimensioning of real-time containers. In the offline phase, the optimal initial deployment and dimensioning of containers are decided based on ideal system models. Additionally, in order to adapt to dynamic variations caused by changing workloads or interferences, the online phase adapts the CPU usage and limits of real-time containers at runtime in order to improve the real-time behavior of the real-time containerized applications while optimizing resource usage. We implement the framework in a real Linux-based system and show through a series of experiments that the proposed framework is able to adjust and re-distribute computing resources between containers in order to improve the real-time behavior of containerized applications in the presence of temporal disturbances while optimizing resource usage.
Upstream Stimulatory Factors Regulate HIV-1 Latency and Are Required for Robust T Cell Activation

RBF-2, composed minimally of the factors USF1, USF2, and TFII-I, is the cognate binding complex of stringently conserved cis-elements on the HIV-1 LTR, designated RBE3 and RBE1. Mutations of these elements prevent induction of provirus in response to T cell signaling. However, the function of USF1 and USF2 for this effect are relatively uncharacterized. Here, we find that deletion of the USF2 but not USF1 gene in T cells abrogates HIV-1 expression. Loss of USF2 caused a reduction in expression of USF1 protein, an effect that was not associated with decreased USF1 mRNA abundance. USF1 and USF2 were previously shown to exist predominately as heterodimers on DNA in vivo and cooperatively regulate target genes. To examine this, we performed RNA-seq analysis of T cell lines bearing knockouts of genes encoding these factors. In untreated cells we found limited evidence of coordinated global gene regulation between USF1 and USF2. In contrast we observed a high degree of genome-wide cooperative regulation of RNA expression between these factors in cells stimulated with the combination of PMA and ionomycin. In particular, we found that USF1 deletion resulted in a restricted T cell activation response, and this phenotype was exaggerated in USF2 knockout cells. These observations indicate that USF2, but not USF1, is crucial for HIV-1 expression, but the combined function of these factors is required for full T cell response.
A FLOWERING LOCUS T ortholog is associated with photoperiod-insensitive flowering in hemp (Cannabis sativa L.)

Hemp (Cannabis sativa L.) is an extraordinarily versatile crop, with applications ranging from medicinal compounds to seed oil and fibre products. Cannabis sativa is a short-day plant, and its flowering is tightly controlled by photoperiod. However, substantial genetic variation exists for photoperiod sensitivity in C. sativa, and photoperiod-insensitive (“autoflower”) cultivars are available. Using a bi-parental mapping population and bulked segregant analysis, we identified Autoflower2, a 0.5 Mbp locus significantly associated with photoperiod-insensitive flowering in hemp. Autoflower2 contains an ortholog of the central flowering time regulator FLOWERING LOCUS T (FT) from Arabidopsis thaliana which we termed CsFT1. Extensive sequence divergence between alleles of CsFT1 was identified between photoperiod-sensitive and insensitive cultivars of C. sativa, including a duplication of CsFT1 and sequence differences especially in introns. Genotyping of several mapping populations and a diversity panel confirmed a strong correlation between CsFT1 alleles and photoperiod response as well as affirming that at least two independent loci for this agriculturally important trait, Autoflower1 and Autoflower2, exist in the C. sativa gene pool. This study reveals the multiple independent origins of photoperiod insensitivity in C. sativa, supporting the likelihood of a complex domestication history in this species. By integrating the genetic relaxation of photoperiod sensitivity into novel C. sativa cultivars, expansion to higher latitudes will be permitted, thus allowing the full potential of this versatile crop to be reached.
Neuroticism and emotion regulation: An effective connectivity analysis of large-scale resting-state brain networks

The neurotic personality has an impact on the regulation of basic negative emotions such as anger, fear, and sadness. There has been extensive research in search of functional connectivity biomarkers of neuroticism and basic negative emotions but there is a lack of research based on effective connectivity. In the current research, we intended to determine the significance of causal interaction of three large-scale resting-state networks – default mode, salience, and executive networks – to predict neuroticism and basic negative emotions. In this study, a large-scale human connectome project dataset comprising functional MRI scans and self-reported scores of neuroticism and negative emotions of 1079 subjects, was utilized. Spectral dynamic causal modelling and parametric empirical Bayes was used to estimate the subject-level effective connectivity parameters and their group-level associations with the neuroticism and emotional scores. Leave-one-out cross-validation using parametric empirical Bayes was employed for prediction analysis. Our results for heightened emotions showed that the self-connection of right hippocampus can predict individuals with high fear, self-connections of dorsal anterior cingulate cortex, posterior cingulate cortex and left dorsolateral prefrontal cortex can predict individuals with high sadness. High anger, low sadness, and neuroticism scores of any emotion category except low fear, could not be predicted using triple network effective connectivity. Our findings revealed that the causal (directed) connections of the resting-state triple network can potentially serve as a connectomic signature for people with high and low fear, high sadness, low anger, and neuroticism with low fear.
GSR-DB: a manually curated and optimised taxonomical database for 16S rRNA amplicon analysis

Amplicon-based 16S ribosomal RNA sequencing remains the most widely used method to profile microbial communities, as a low-cost and low-complexity approach. Reference databases are a mainstay for taxonomic assignments, which typically rely on popular databases such as SILVA, Greengenes, GTDB, or RDP. However, the inconsistency of the nomenclature across databases, and the presence of shortcomings in the annotation of these databases are limiting the resolution of the analysis. To overcome these limitations, we created the GSR database (Greengenes, SILVA, and RDP database), an integrated and manually curated database for bacterial and archaeal 16S amplicon taxonomy analysis. Unlike previous integration approaches, this database creation pipeline includes a taxonomy unification step to ensure consistency in taxonomical annotations. The database was validated with three mock communities and two real datasets and compared with existing 16S databases such as Greengenes, GTDB, ITGDB, SILVA, RDP, and MetaSquare. Results showed that the GSR database enhances taxonomical annotations of 16S sequences, outperforming current 16S databases at the species level. The GSR database is available for full-length 16S sequences and the most commonly used hypervariable regions: V4, V1-V3, V3-V4, and V3-V5. IMPORTANCE Taxonomic assignments of microorganisms have long been hindered by inconsistent nomenclature and annotation issues in existing databases like SILVA, Greengenes, GTDB, or RDP. To overcome these issues, we created GSR-DB, accurate and comprehensive taxonomic annotations of 16S amplicon data. Unlike previous approaches, our innovative pipeline includes a unique taxonomy unification step, ensuring consistent and reliable annotations. Validated with mock communities and real datasets, GSR-DB outperforms existing databases in providing species-level resolution, making it a game-changer for microbiome studies. Moreover, GSR-DB is designed to be accessible to researchers with limited computational resources, making it a powerful tool for scientists across the board. Available for full-length 16S sequences and commonly used hypervariable regions, including V4, V1-V3, V3-V4, and V3-V5, GSR-DB is a go-to database for robust and accurate microbial taxonomy analysis.
OpenABC enables flexible, simplified, and efficient GPU accelerated simulations of biomolecular condensates

Biomolecular condensates are important structures in various cellular processes but are challenging to study using traditional experimental techniques. In silico simulations with residue-level coarse-grained models strike a balance between computational efficiency and chemical accuracy. They could offer valuable insights by connecting the emergent properties of these complex systems with molecular sequences. However, existing coarse-grained models often lack easy-to-follow tutorials and are implemented in software that is not optimal for condensate simulations. To address these issues, we introduce OpenABC, a software package that greatly simplifies the setup and execution of coarse-grained condensate simulations with multiple force fields using Python scripting. OpenABC seamlessly integrates with the OpenMM molecular dynamics engine, enabling efficient simulations with performances on a single GPU that rival the speed achieved by hundreds of CPUs. We also provide tools that convert coarse-grained configurations to all-atom structures for atomistic simulations. We anticipate that Open-ABC will significantly facilitate the adoption of in silico simulations by a broader community to investigate the structural and dynamical properties of condensates. Open-ABC is available at https://github.com/ZhangGroup-MITChemistry/OpenABC