Miracle-dz/UniFAR-FTUs huggingface dataset:
Hollow‐Structured Mesoporous Materials: Chemical Synthesis, Functionalization and Applications

Hollow‐structured mesoporous materials (HMMs), as a kind of mesoporous material with unique morphology, have been of great interest in the past decade because of the subtle combination of the hollow architecture with the mesoporous nanostructure. Benefitting from the merits of low density, large void space, large specific surface area, and, especially, the good biocompatibility, HMMs present promising application prospects in various fields, such as adsorption and storage, confined catalysis when catalytically active species are incorporated in the core and/or shell, controlled drug release, targeted drug delivery, and simultaneous diagnosis and therapy of cancers when the surface and/or core of the HMMs are functionalized with functional ligands and/or nanoparticles, and so on. In this review, recent progress in the design, synthesis, functionalization, and applications of hollow mesoporous materials are discussed. Two main synthetic strategies, soft‐templating and hard‐templating routes, are broadly sorted and described in detail. Progress in the main application aspects of HMMs, such as adsorption and storage, catalysis, and biomedicine, are also discussed in detail in this article, in terms of the unique features of the combined large void space in the core and the mesoporous network in the shell. Functionalization of the core and pore/outer surfaces with functional organic groups and/or nanoparticles, and their performance, are summarized in this article. Finally, an outlook of their prospects and challenges in terms of their controlled synthesis and scaled application is presented.
Leveraging Data About Users in General in the Learning of Individual User Models

Models of computer users that are learned on the basis of data can make use of two types of information: data about users in general and data about the current individual user. Focusing on user models that take the form of Bayesian networks, we compare four types of model that represent different ways of combining these two types of data. Models of the four types are applied to the data of an experiment, and they are evaluated according to theoretical, empirical, and practical criteria. One of the model types is a new variant of the AHUGIN method for adapting the probabilities of a Bayesian network while it is being used: Differential adaptation is a principled way of determining the speed with which each aspect of a network is adapted to an individual user.
Proceedings of the Eighth Workshop on Foundations of Aspect-oriented Languages Held at the Eighth International Conference on Aspect-oriented Software Development Message from the Program Committee Chair a Type System for Functional Traversal-based Aspects

We present a programming language model of the ideas behind Functional Adaptive Programming (AP-F) and our Java implementation, DemeterF. Computation in AP-F is encapsulated in sets of functions that implement a fold over a data structure with the help of a generic traversal. In this paper we define the syntax, semantics, and typing rules of a simple AP-F model, together with a proof of soundness that guarantees that traversal expressions result in a value of the expected type. Applying a function set to a different structure can then be statically checked to eliminate some runtime tests and sources of program errors.
Towards an Adaptable and Generalizable Optimization Engine in Decision and Control: A Meta Reinforcement Learning Approach

Sampling-based model predictive control (MPC) has found significant success in optimal control problems with non-smooth system dynamics and cost function. Many machine learning-based works proposed to improve MPC by a) learning or fine-tuning the dynamics/ cost function, or b) learning to optimize for the update of the MPC controllers. For the latter, imitation learning-based optimizers are trained to update the MPC controller by mimicking the expert demonstrations, which, however, are expensive or even unavailable. More significantly, many sequential decision-making problems are in non-stationary environments, requiring that an optimizer should be adaptable and generalizable to update the MPC controller for solving different tasks. To address those issues, we propose to learn an optimizer based on meta-reinforcement learning (RL) to update the controllers. This optimizer does not need expert demonstration and can enable fast adaptation (e.g., few-shots) when it is deployed in unseen control tasks. Experimental results validate the effectiveness of the learned optimizer regarding fast adaptation.
Uncertainties associated with digital elevation models for hydrologic applications : a review

Digital elevation models (DEMs) represent the topography that drives surface flow and are arguably one of the more important data sources for deriving variables used by numerous hydrologic models. A considerable amount of research has been conducted to address uncertainty associated with error in digital elevation models (DEMs) and the propagation of error to derived terrain parameters. This review brings together a discussion of research in fundamental topical areas related to DEM uncertainty that affect the use of DEMs for hydrologic applications. These areas include: (a) DEM error; (b) topographic parameters frequently derived from DEMs and the associated algorithms used to derive these parameters; (c) the influence of DEM scale as imposed by grid cell resolution; (d) DEM interpolation; and (e) terrain surface modification used to generate hydrologicallyviable DEM surfaces. Each of these topical areas contributes to DEM uncertainty and may potentially influence results of distributed parameter hydrologic models that rely on DEMs for the derivation of input parameters. The current state of research on methods developed to quantify DEM uncertainty is reviewed. Based on this review, implications of DEM uncertainty and suggestions for the GIS research and user communities are offered.
Significance of spatial variability in precipitation for process-oriented modelling : results from two nested catchments using radar and ground station data

The importance of considering the spatial distribution of rainfall for process-oriented hydrological modelling is well-known. However, the application of rainfall radar data to provide such detailed spatial resolution is still under debate. In this study the process-oriented TAC D (Tracer Aided Catchment model, Distributed) model had been used to investigate the effects of different spatially distributed rainfall input on simulated discharge and runoff components on an event base. TAC is fully distributed (50×50 m2 raster cells) and was applied on an hourly base. As model input rainfall data from up to 7 ground stations and high resolution rainfall radar data from operational C-band radar were used. For seven rainfall events the discharge simulations were investigated in further detail for the mountainous Brugga catchment (40 km2) and the St. Wilhelmer Talbach (15.2 km 2) sub-basin, which are located in the Southern Black Forest Mountains, south-west Germany. The significance of spatial variable precipitation data was clearly demonstrated. Dependent on event characteristics, localized rain cells were occasionally poorly captured even by a dense ground station network, and this resulted in inadequate model results. For such events, radar data can provide better input data. However, an extensive data adjustment using ground station data is required. For this purpose a method was developed that considers the temporal variability in rainfall intensity in high temporal resolution in combination with the total rainfall amount of both data sets. The use of the distributed catchment model allowed further insights into spatially variable impacts of different rainfall estimates. Impacts for discharge predictions are the largest in areas that are dominated by the production of fast runoff components. The improvements for distributed Correspondence to: D. Tetzlaff (d.tetzlaff@abdn.ac.uk) runoff simulation using high resolution rainfall radar input data are strongly dependent on the investigated scale, the event characteristics and the existing monitoring network.
Differential principal component analysis of ChIP-seq

We propose differential principal component analysis (dPCA) for analyzing multiple ChIP- sequencing datasets to identify differential protein–DNA interactions between two biological conditions. dPCA integrates unsupervised pattern discovery, dimension reduction, and statistical inference into a single framework. It uses a small number of principal components to summarize concisely the major multiprotein synergistic differential patterns between the two conditions. For each pattern, it detects and prioritizes differential genomic loci by comparing the between-condition differences with the within-condition variation among replicate samples. dPCA provides a unique tool for efficiently analyzing large amounts of ChIP-sequencing data to study dynamic changes of gene regulation across different biological conditions. We demonstrate this approach through analyses of differential chromatin patterns at transcription factor binding sites and promoters as well as allele-specific protein–DNA interactions.
Population structure and genetic diversity analysis in faba bean (Vicia faba L.) germplasm using SSR markers

In the present study, population structure and genetic diversity were studied among 100 faba bean germplasm lines along with three checks using 29 SSR (microsatellite) markers and morphological traits. ET218734, ET226572, and ET218734 genotypes exhibited maximum seed yield and high mean performance for various yield-attributing traits. The D2 statistics analysis grouped genotypes into five clusters. SSR marker analysis revealed, on average, 2 alleles per locus ranging from 2 to 3 among the studied genotypes. Polymorphic information content (PIC) for these markers ranged from 0.063 to 0.492 with an average of 0.37. Population structure analysis classified the studied genotypes into three major clusters. The Molecular Diversity Distance was found to be greatest among Cluster III and Cluster I (0.289), while the lowest was among Cluster II and Cluster I (0.148). The allele frequency divergence (expected heterozygosity) was found highest on Cluster II (0.164), and the lowest was on Cluster III (0.096).
Baby-Friendly Hospital Accreditation, In-Hospital Care Practices, and Breastfeeding

OBJECTIVES: To investigate the effect of Baby-Friendly Hospital Initiative (BFHI) accreditation and hospital care practices on breastfeeding rates at 1 and 4 months. METHODS: All women who birthed in Queensland, Australia, from February 1 to May 31, 2010, received a survey 4 months postpartum. Maternal, infant, and hospital characteristics; pregnancy and birth complications; and infant feeding outcomes were measured. RESULTS: Sample size was 6752 women. Breastfeeding initiation rates were high (96%) and similar in BFHI-accredited and nonaccredited hospitals. After adjustment for significant maternal, infant, clinical, and hospital variables, women who birthed in BFHI-accredited hospitals had significantly lower odds of breastfeeding at 1 month (adjusted odds ratio 0.72, 95% confidence interval 0.58–0.90) than those who birthed in non–BFHI-accredited hospitals. BFHI accreditation did not affect the odds of breastfeeding at 4 months or exclusive breastfeeding at 1 or 4 months. Four in-hospital practices (early skin-to-skin contact, attempted breastfeeding within the first hour, rooming-in, and no in-hospital supplementation) were experienced by 70% to 80% of mothers, with 50.3% experiencing all 4. Women who experienced all 4 hospital practices had higher odds of breastfeeding at 1 month (adjusted odds ratio 2.20, 95% confidence interval 1.78–2.71) and 4 months (adjusted odds ratio 2.93, 95% confidence interval 2.40–3.60) than women who experienced fewer than 4. CONCLUSIONS: When breastfeeding-initiation rates are high and evidence-based practices that support breastfeeding are common within the hospital environment, BFHI accreditation per se has little effect on both exclusive or any breastfeeding rates.
Hyperspectral satellite imagery detection of ancient raw material sources: Soft‐stone vessel production at Aqir al‐Shamoos (Oman)

Soft‐stone vessels (made of the rock chloritite, which is comprised of the mineral chlorite) are an important component of the material culture record of ancient southeast Arabia. Given the prevalence of soft‐stone vessels in domestic and funerary contexts, and the natural geological occurrence of chloritite in the region, archaeologists have long suspected that soft‐stone vessels could have been produced in United Arab Emirates (UAE) or Oman. However, over many decades of research very few pieces of worked raw material or unfinished vessel fragments have been recovered in Arabia. This changed dramatically in 2015 with the discovery of the Iron Age village of Aqir al‐Shamoos where thousands of raw, worked, and unfinished pieces attest to soft‐stone vessel manufacture. Aqir al‐Shamoos continues to yield new insights regarding soft‐stone vessel production, but the source of raw material used to craft these objects initially remained unknown as no natural chloritite deposits had been found in the immediate vicinity of the site. We present results of hyperspectral satellite imagery target detection used to search for natural surface occurrences of chloritite near Aqir al‐Shamoos. Despite limitations in carbonate and phyllosilicate mineral discrimination, field survey of the satellite detection results revealed chloritite outcrops in the ophiolite formation mountains 1.4 km northwest of Aqir al‐Shamoos near the newly discovered archaeological site of ‘Waby al‐Zady. Reflectance spectroscopy (0.35–2.5 μm) of material from multiple chloritite sources indicates that chloritite from ‘Waby al‐Zady is spectrally very similar to material at Aqir al‐Shamoos but quite different in comparison with material from other locations. These findings indicate that: (1) hyperspectral satellite imagery target detection can be useful for chloritite prospection, (2) ‘Waby al‐Zady (or somewhere very nearby) was probably the source of chloritite used at Aqir al‐Shamoos, and (3) chloritite reflection spectra may be useful for distinguishing chloritite from different sources.
Pattern Discovery Techniques for Music Audio

Human listeners are able to recognize structure in music through the perception of repetition and other relationships within a piece of music. This work aims to automate the task of music analysis. Music is “explained” in terms of embedded relationships, especially repetition of segments or phrases. The steps in this process are the transcription of audio into a representation with a similarity or distance metric, the search for similar segments, forming clusters of similar segments, and explaining music in terms of these clusters. Several pre-existing signal analysis methods have been used: monophonic pitch estimation, chroma (spectral) representation, and polyphonic transcription followed by harmonic analysis. Also, several algorithms that search for similar segments are described. Experience with these various approaches suggests that there are many ways to recover structure from music audio. Examples are offered using classical, jazz, and rock music.
A mechanism for simultaneous sensing of aspartate and maltose by the Tar chemoreceptor of Escherichia coli

The Tar chemoreceptor of Escherichia coli exhibits partial sensory additivity. Tar can mediate simultaneous responses to two disparate ligands, aspartate and substrate‐loaded maltose‐binding protein (MBP). To investigate how one receptor generates concurrent signals to two stimuli, ligand‐binding asymmetry was imposed on the rotationally symmetric Tar homodimer. Mutations causing specific defects in aspartate or maltose chemotaxis were introduced pairwise into plasmid‐borne tar genes. The doubly mutated tar genes did not restore aspartate or maltose chemotaxis in a strain containing a chromosomal deletion of tar (Δtar ). However, when Tar proteins with complementing sets of mutations were co‐expressed from compatible plasmids, the resulting heterodimeric receptors enabled Δtar cells to respond to aspartate or maltose. The effect of one attractant on the response to the other depended on the relative orientations of the functional binding sites for aspartate and MBP. When the sites were in the ‘same’ orientation, saturating levels of one attractant strongly inhibited chemotaxis to the other. In the ‘opposite’ orientation, such inhibitory effects were negligible. These data demonstrate that opposing subunits of Tar can transmit signals to aspartate and maltose independently if the ligands are restricted to the ‘opposite’ binding orientation. When aspartate and MBP bind in the ‘same’ orientation, they compete for signalling through one subunit. In the wild‐type Tar dimer, aspartate and MBP can bind in either the ‘same’ or the ‘opposite’ orientation, a freedom that can explain the partial additivity of the aspartate and maltose responses that is seen with tar+ cells.
Active 2D materials for on-chip nanophotonics and quantum optics

Abstract Two-dimensional materials have emerged as promising candidates to augment existing optical networks for metrology, sensing, and telecommunication, both in the classical and quantum mechanical regimes. Here, we review the development of several on-chip photonic components ranging from electro-optic modulators, photodetectors, bolometers, and light sources that are essential building blocks for a fully integrated nanophotonic and quantum photonic circuit.
Long-Term Trajectories of Posttraumatic Stress Disorder Symptoms: A 20-Year Longitudinal Study of World Trade Center Responders

Objective. The present study examined the 20-year course of posttraumatic stress disorder (PTSD) in World Trade Center (WTC) responders to address four questions: (1) How stable are symptoms of PTSD? (2) What is the average symptom trajectory? (3) How much do responders differ from the average trend? (4) How quickly do PTSD symptoms improve or worsen? Methods. Data include 81,298 observations from n = 12,822 responders, spanning from July 2002 to December 2022. Fourteen percent meet PTSD criteria. PTSD symptoms were measured using the PCL-17. Retest correlations were calculated to estimate stability, growth curve models to estimate individual trajectories, and Kaplan-Meier curves to estimate the rate of clinically significant change. Results. Retest correlations were high overall (range =.49, .84), lower in PTSD cases (range =.21, .78), and decreased as a function of time between assessments. The best-fitting growth model represented trajectories continuously rather than multiple classes. Symptom burden peaked in 2011 and declined modestly by 2022 (Cohen d = -0.28 and -0.59 in all responders and PTSD cases, respectively). Median time before clinically significant improvement in responders with PTSD was 8.88 years (95% CI = 8.01, 9.79). Conclusions. In the longest and largest study of PTSD symptoms tracked continuously since exposure, illness course was characterized to find that, while symptoms were highly stable in the short term, symptoms changed significantly over two decades. Most responders experienced clinical improvement after nine years, but 10% had poor course and should be the focus of public health efforts.
Gestural motion editing using mobile devices

We present novel techniques for interactive editing the motion of an animated character by gesturing with a mobile device. Our approach is based on the notion that humans are generally able to convey motion using simple and abstract mappings from their own movement to that of an animated character. We first explore the feasibility of extracting robust sensor data with sufficiently rich features and low noise, such that the signal is predictably representative of a user's illustrative manipulation of the mobile device. In particular, we find that the linear velocity and device orientation computed from the motion sensor data are well-suited to the task of interactive character control. We show that these signals can be used for two different methods of interactively editing the locomotion of an animated human figure: discrete gestures for editing single motions, and continuous gestures for editing ongoing motions. We illustrate these techniques using various types of motion edits which affect jumps, strides and turning.
Proton Free Induction Decay MRSI at 7T in the Human Brain Using an Egg-Shaped Modified Rosette K-Space Trajectory

1.1 Purpose Proton (1H)-MRSI via spatial-spectral encoding poses high demands on gradient hardware at ultra-high fields and high-resolutions. Rosette trajectories help alleviate these problems, but at reduced SNR-efficiency due to their k-space densities not matching any desired k-space filter. We propose modified rosette trajectories, which more closely match a Hamming filter, and thereby improve SNR performance while still staying within gradient hardware limitations and without prolonging scan time. 1.2 Methods Analytical and synthetic simulations were validated with phantom and in vivo measurements at 7 T. The rosette and modified rosette trajectories were measured in five healthy volunteers in six minutes in a 2D slice in the brain. A 3D sequence was measured in one volunteer within 19 minutes. The SNR, linewidth, CRLBs, lipid contamination and data quality of the proposed modified rosette trajectory were compared to the rosette trajectory. 1.3 Results Using the modified rosette trajectories, an improved k-space weighting function was achieved resulting in an increase of up to 12% in SNR compared to rosette's dependent on the two additional trajectory parameters. Similar results were achieved for the theoretical SNR calculation based on k-space densities, as well as when using the pseudo-replica method for simulated, in-vivo and phantom data. The CRLBs improved slightly, but non-significantly for the modified rosette trajectories, while the linewidths and lipid contamination remained similar. 1.4 Conclusion By improving the rosette trajectory's shape, modified rosette trajectories achieved higher SNR at the same scan time and data quality. Key words: magnetic resonance spectroscopic imaging, SNR efficiency, gradient hardware restrictions, 7 T, non-Cartesian trajectory, modified rosette trajectory