Miracle-dz/UniFAR-FTUs huggingface dataset:
Integral Equation Methods for Ocean Acoustics with Depth-Dependent Background Sound Speed

Integral Equation Methods for Ocean Acoustics with Depth-Dependent Background Sound Speed. Time-harmonic acoustic wave propagation in an ocean with depth-dependent background sound speed can be described by the Helmholtz equation in an infinite, twoor three-dimensional waveguide of finite height. A crucial subproblem for the anayltic and numeric treatment of associated wave propagation problems is a Liouville eigenvalue problem that involves the depthdependent contrast. For different types of background sound speed profiles, we discuss discretization schemes for the Liouville eigenvalue problem arising in the vertical variable. Due to variational theory in Sobolev spaces, we then show well-posedness of weak solutions to the corresponding scattering problem from a bounded inhomogeneity inside such an ocean: We introduce an exterior Dirichlet-to-Neumann operator for depth-dependent sound speed and prove boundedness, coercivity, and holomorphic dependence of this operator in suitable function spaces adapted to our weak solution theory. Analytic Fredholm theory then implies existence and uniqueness of solution for the scattering problem for all but a countable sequence of frequencies. Introducing the Green’s function of the waveguide, we prove equivalence of the source problem for the Helmholtz equation with depth-dependent sound speed profile, Neumann boundary condition on the bottom and Dirichlet boundary condition on the top surface, to the Lippmann-Schwinger integral equation in dimensions two and three. Next, we periodize the Lippmann-Schwinger integral equation in dimensions two and three. The periodized version of the Lippmann-Schwinger integral equation and an interpolation projection onto a space spanned by finitely many eigenfunctions in the vertical variable and trigonometric polynomials in the horizontal variables, two different collocation schemes are derived. A result of Sloan [J.Approx Theory, 39:97-117,1983] on non-polynomial interpolation yields both converge and algebraic convergence rates depending on the smoothness of the inhomogeneity and the source of both schemes. Using one collocation scheme we present numerical results in dimension two. We further present an optimization technique of the vertical transform process, when the height of the obstacle is small compared to the finite height of the ocean, which makes computation in dimension three possible. If several scatters are present in the waveguide, this discretization technique leads to one computational domain containing all scatterers. For a three dimensional waveguide, we reformulate the Lippmann-Schwinger integral equation as a coupled system in an union of several boxes, each containing one part of the scatter.
Serum uric acid lowering and effects of sodium‐glucose cotransporter‐2 inhibitors on gout: A meta‐analysis and meta‐regression of randomized controlled trials

To pool the effects of sodium‐glucose cotransporter‐2 (SGLT2) inhibitors on gout and to investigate the association of these effects with baseline serum uric acid (SUA), SUA lowering, and underlying conditions, such as type 2 diabetes mellitus (T2DM)/heart failure (HF).
Cultural adaptations and tailoring of public health nutrition interventions in Indigenous peoples and ethnic minority groups: opportunities for personalised and precision nutrition

Indigenous peoples and ethnic minority groups often experience poor diet quality and poor health outcomes. Such inequities may be partially due to nutrition interventions not meeting the unique cultural and linguistic needs of these population groups, which could be achieved using co-creation and/or personalised approaches. Cultural adaptation or tailoring of nutrition interventions has shown promise in improving some aspects of dietary intake, but this requires careful consideration to ensure it does not inadvertently exacerbate dietary inequities. The aim of this narrative review was to examine examples of cultural adaptations and/or tailoring of public health nutrition interventions that improved the dietary intake and to consider implications for the optimal design and implementation of personalised and precision nutrition interventions. This review identified six examples of cultural adaptation and/or tailoring of public health nutrition intervention in Indigenous peoples and ethnic minority groups across Australia, Canada and the US. All studies used deep socio-cultural adaptations, such as the use of Indigenous storytelling, and many included surface-level adaptations, such as the use of culturally appropriate imagery in intervention materials. However, it was not possible to attribute any improvements in dietary intake to cultural adaptation and/or tailoring per se, and the minimal reporting on the nature of adaptations limited our ability to determine whether the interventions used true co-creation to design content or were adapted from existing interventions. Findings from this review outline opportunities for personalised nutrition interventions to use co-creation practices to design, deliver and implement interventions in collaboration with Indigenous and ethnic minority groups.
Automated treatment planning for proton pencil beam scanning using deep learning dose prediction and dose‐mimicking optimization

Abstract Purpose The purpose of this study is to investigate the use of a deep learning architecture for automated treatment planning for proton pencil beam scanning (PBS). Methods A 3‐dimensional (3D) U‐Net model has been implemented in a commercial treatment planning system (TPS) that uses contoured regions of interest (ROI) binary masks as model inputs with a predicted dose distribution as the model output. Predicted dose distributions were converted to deliverable PBS treatment plans using a voxel‐wise robust dose mimicking optimization algorithm. This model was leveraged to generate machine learning (ML) optimized plans for patients receiving proton PBS irradiation of the chest wall. Model training was carried out on a retrospective set of 48 previously‐treated chest wall patient treatment plans. Model evaluation was carried out by generating ML‐optimized plans on a hold‐out set of 12 contoured chest wall patient CT datasets from previously treated patients. Clinical goal criteria and gamma analysis were used to compare dose distributions of the ML‐optimized plans against the clinically approved plans across the test patients. Results Statistical analysis of mean clinical goal criteria indicates that compared to the clinical plans, the ML optimization workflow generated robust plans with similar dose to the heart, lungs, and esophagus while achieving superior dosimetric coverage to the PTV chest wall (clinical mean V95 = 97.6% vs. ML mean V95 = 99.1%, p < 0.001) across the 12 test patients. Conclusions ML‐based automated treatment plan optimization using the 3D U‐Net model can generate treatment plans of similar clinical quality compared to human‐driven optimization.
P-ring: The conserved nature of phosphorus enriched cells in seedling roots of distantly related species

ABSTRACT Plants require sunlight, carbon dioxide, water and mineral ions for their growth and development. Roots in vascular plants sequester water and ions from soil and transport them to the aboveground parts of the plant. Due to heterogeneous nature of soil, roots have evolved several regulatory barriers from molecular to organismic level that selectively allows certain ions to enter the vascular tissues for transport according to the physiological and metabolic demands of plant cell. Current literature profusely elaborates about apoplastic barriers, but the possibility of the existence of a symplastic regulation through phosphorous-enriched cells has not been mentioned. Recent investigations on native ion distribution in seedling roots of several species (Pinus pinea, Zea mays and Arachis hypogaea) identified an ionomic structure termed as “P-ring”. The P-ring is composed of a group of phosphorous-rich cells arranged in radial symmetry encircling the vascular tissues. Physiological investigations indicate that the structure is relatively inert to external temperature and ion fluctuations while anatomical studies indicates that they are less likely to be apoplastic in nature. Furthermore, their localization surrounding vascular tissues and in evolutionarily distinct plant lineages might indicate their conserved nature and involvement in ion regulation. Undoubtedly, this is an interesting and important observation that has significant merit for further investigations by the plant science community.
Reducing the anxiety of patients undergoing an oral biopsy by means of graphic novels: an open-label randomized clinical trial

Background The use of graphic novels is a trending topic in health communication as a new form of visual storytelling which explores narratives of health care, cancer, healing, and disability. The objective of the present study was to evaluate - for the first time in the literature - the effect of graphic novels in reducing the anxiety of patients waiting for an incisional biopsy in an oral oncology setting. Material and Methods This open-label randomized clinical trial comprised 50 patients with a clinical suspicion of oral potentially malignant disorders. Twenty-five patients were randomly allocated to the test group, and a colourful graphic novel was provided. Subsequently, the Beck Depression Inventory and the Depression Anxiety Stress Scales-21 were administered to all 50 recruited patients, after which a biopsy was performed on each patient. Results No statistically significant difference was observed between the test and control groups for the variables regarding the demographic data (p>0.2). There was a significant difference after the introduction of the graphic novel, regardless of which questionnaire was used. The graphic novel demonstrated an improvement in the ability of the test group to tolerate anxiety while waiting for an oral biopsy in both psychological tests (p<0.05). Conclusions In light of these initial positive results, the authors of this study would like to suggest the use of graphic novels in oral oncology, dentistry, and medicine with the aim of reducing patient anxiety. Key words:Graphic novels, oral medicine, oral biopsy, potentially malignant disorders, oral cancer, anxiety, phobia.
A protocol for tactile function assessment using JVP domes: Feasibility study and preliminary results

Touch is a crucial sense for perceiving the spatial characteristics of objects. The JVP dome was developed to evaluate tactile spatial acuity using a grating orientation task. There were few studies depicting sequences and details for the entire task, including practice, training, and testing sessions. Therefore, we proposed and elaborated a protocol for the grating orientation task using the staircase method, which required fewer testing trials compared with the method of constant stimuli.
Direct Numerical Simulation of Multiple Particles Sedimentation at an Intermediate Reynolds Number

In this work the previously developed Lattice Boltzmann-Direct Forcing/ Fictitious Domain (LB-DF/FD) method is adopted to simulate the sedimentation of eight circular particles under gravity at an intermediate Reynolds number of about 248. The particle clustering and the resulting Drafting-Kissing-Tumbling (DKT) motion which takes place for the first time are explored. The effects of initial particle-particle gap on the DKT motion are found significant. In addition, the trajectories of particles are presented under different initial particle-particle gaps, which display totally three kinds of falling patterns provided that no DKT motion takes place, i.e. the concave-down shape, the shape of letter “M” and “in-line” shape. Furthermore, the lateral and vertical hydrodynamic forces on the particles are investigated. It has been found that the value of Strouhal number for all particles is the same which is about 0.157 when initial particle-particle gap is relatively large. The wall effects on falling patterns and particle expansions are examined in the final.
Mitochondria-Related Candidate Genes and Diagnostic Model to Predict Late-Onset Alzheimer's Disease and Mild Cognitive Impairment.

BACKGROUND Late-onset Alzheimer's disease (LOAD) is the most common type of dementia, but its pathogenesis remains unclear, and there is a lack of simple and convenient early diagnostic markers to predict the occurrence. OBJECTIVE Our study aimed to identify diagnostic candidate genes to predict LOAD by machine learning methods. METHODS Three publicly available datasets from the Gene Expression Omnibus (GEO) database containing peripheral blood gene expression data for LOAD, mild cognitive impairment (MCI), and controls (CN) were downloaded. Differential expression analysis, the least absolute shrinkage and selection operator (LASSO), and support vector machine recursive feature elimination (SVM-RFE) were used to identify LOAD diagnostic candidate genes. These candidate genes were then validated in the dataset validation group and clinical samples, and a LOAD prediction model was established. RESULTS LASSO and SVM-RFE analyses identified 3 mitochondria-related genes (MRGs) as candidate genes, including NDUFA1, NDUFS5, and NDUFB3. In the verification of 3 MRGs, the AUC values showed that NDUFA1, NDUFS5 had better predictability. We also verified the candidate MRGs in MCI groups, the AUC values showed a good performance. We then used NDUFA1, NDUFS5 and age to build a LOAD diagnostic model and AUC was 0.723. Results of qRT-PCR experiments showed that the three candidate genes were expressed significantly lower in the LOAD and MCI groups when compared to CN. CONCLUSION Two mitochondrial-related candidate genes, NDUFA1 and NDUFS5, were identified as diagnostic markers for LOAD and MCI. Combining these two candidate genes with age, a LOAD diagnostic prediction model was successfully constructed.
Convergent behavior of extended stalk regions from staphylococcal surface proteins with widely divergent sequence patterns

Staphylococcus epidermidis and Staphylococcus aureus are highly problematic bacteria in hospital settings. A major challenge is their ability to form biofilms on abiotic or biotic surfaces. Biofilms are well‐organized, multicellular bacterial aggregates that resist antibiotic treatment and often lead to recurrent infections. Bacterial cell wall‐anchored (CWA) proteins are important players in biofilm formation and infection. Many have putative stalk‐like regions or regions of low complexity near the cell wall‐anchoring motif. Recent work demonstrated the strong propensity of the stalk region of S. epidermidis accumulation‐associated protein (Aap) to remain highly extended under solution conditions that typically induce compaction. This behavior is consistent with the expected function of a stalk‐like region that is covalently attached to the cell wall peptidoglycan and projects the adhesive domains of Aap away from the cell surface. In this study, we evaluate whether the ability to resist compaction is a common theme among stalk regions from various staphylococcal CWA proteins. Circular dichroism spectroscopy was used to examine secondary structure changes as a function of temperature and cosolvents along with sedimentation velocity analytical ultracentrifugation, size‐exclusion chromatography, and SAXS to characterize structural characteristics in solution. All stalk regions tested are intrinsically disordered, lacking secondary structure beyond random coil and polyproline type II helix, and they all sample highly extended conformations. Remarkably, the Ser‐Asp dipeptide repeat region of SdrC exhibited nearly identical behavior in solution when compared to the Aap Pro/Gly‐rich region, despite highly divergent sequence patterns, indicating conservation of function by various distinct staphylococcal CWA protein stalk regions.
Multi-threshold Selection Using Maximum Reciprocal Entropy/Reciprocal Gray Entropy

The existing threshold selection methods based on Shannon entropy have the defects of undefined value and zero value,and they do not consider the uniformity of the gray scale within the object cluster and background cluster.In view of the above problems,the methods of multi-threshold selection based on maximum reciprocal entropy /reciprocal gray entropy and adaptive chaotic variation particle swarm optimization(ACPSO) are proposed for images including multiple objects or backgrounds in this paper.Firstly,the method of single threshold selection based on maximum reciprocal entropy is extended to multi-threshold selection.Then,reciprocal gray entropy is defined.The formulae of single threshold selection and multi-threshold selection based on maximum reciprocal gray entropy are derived.Finally,to find the optimal multiple thresholds quickly and accurately,the algorithm steps of multi-threshold selection based on reciprocal entropy / reciprocal gray entropy and ACPSO are given.The experimental results show that,compared with the existing related method,which is the method of multi-threshold selection based on maximum Shannon entropy and particle swarms optimization(PSO),the methods proposed in this paper have obvious advantages.Moreover,the methods have been used for image segmentation in infrared small target detection and satellite cloud image recognition,and they have excellent segmentation effect.
Landscape of Double-Stranded DNA Breaks in Postmortem Brains from Alzheimer’s Disease and Non-Demented Individuals

Background: Alzheimer’s disease (AD) brains accumulate DNA double-strand breaks (DSBs), which could contribute to neurodegeneration and dysfunction. The genomic distribution of AD brain DSBs is unclear. Objective: To map genome-wide DSB distributions in AD and age-matched control brains. Methods: We obtained autopsy brain tissue from 3 AD and 3 age-matched control individuals. The donors were men between the ages of 78 to 91. Nuclei extracted from frontal cortex tissue were subjected to Cleavage Under Targets & Release Using Nuclease (CUT&RUN) assay with an antibody against γH2AX, a marker of DSB formation. γH2AX-enriched chromatins were purified and analyzed via high-throughput genomic sequencing. Results: The AD brains contained 18 times more DSBs than the control brains and the pattern of AD DSBs differed from the control brain pattern. In conjunction with published genome, epigenome, and transcriptome analyses, our data revealed aberrant DSB formation correlates with AD-associated single-nucleotide polymorphisms, increased chromatin accessibility, and upregulated gene expression. Conclusion: Our data suggest in AD, an accumulation of DSBs at ectopic genomic loci could contribute to an aberrant upregulation of gene expression.
Permafrost thaw induces short‐term increase in vegetation productivity in northwestern Canada

Over the past several decades, various trends in vegetation productivity, from increases to decreases, have been observed throughout Arctic–Boreal ecosystems. While some of this variation can be explained by recent climate warming and increased disturbance, very little is known about the impacts of permafrost thaw on productivity across diverse vegetation communities. Active layer thickness data from 135 permafrost monitoring sites along a 10° latitudinal transect of the Northwest Territories, Canada, paired with a Landsat time series of normalized difference vegetation index from 1984 to 2019, were used to quantify the impacts of changing permafrost conditions on vegetation productivity. We found that active layer thickness contributed to the observed variation in vegetation productivity in recent decades in the northwestern Arctic–Boreal, with the highest rates of greening occurring at sites where the near‐surface permafrost recently had thawed. However, the greening associated with permafrost thaw was not sustained after prolonged periods of thaw and appeared to diminish after the thaw front extended outside the plants' rooting zone. Highest rates of greening were found at the mid‐transect sites, between 62.4° N and 65.2° N, suggesting that more southernly sites may have already surpassed the period of beneficial permafrost thaw, while more northern sites may have yet to reach a level of thaw that supports enhanced vegetation productivity. These results indicate that the response of vegetation productivity to permafrost thaw is highly dependent on the extent of active layer thickening and that increases in productivity may not continue in the coming decades.
Detection of biochemical variations among normal equine carpal and tarsocrural joint fluids based on infrared spectral characteristics and a modified approach to partial least squares discriminant analysis

In recent years the focus of osteoarthritis (OA) research has shifted from microscopic changes in cell number and total protein parameters, to the search for biomarkers (direct or indirect molecular indicators of abnormal skeletal turnover) for joint disease in horses. Infrared (IR) spectroscopy has been established as a useful tool for the assessment of biological molecules and the biochemical response to disease. Synovial fluid was collected from 105 normal clinically normal antebrachiocarpal (AC), midcarpal (MC) and tarsocrural (TC) joints. Thin films were prepared and infrared absorbance spectra in the mi-infrared (MIR) region of 400-4000 cm recorded using a FTIR spectrometer equipped with a deuterium tryglycine sulphate detector. For each acquisition, 512 interferograms were signal averaged and Fourier transformed to generate a spectrum with nominal resolution of 4 cm-1. Spectra were preprocessed and left and right spectra compared by ANOVA. Between joint comparisons were made using a novel modified method stemming from of partial least squares discriminant analysis and projection pursuit methods that maximized the difference of between-group variance minus within-group variance. Differences within animal between left and right joints were minimal. Differences among AC, MC and TC synovial fluid spectra were significant. The finding of a broad range biomolecular differences among these joints supports indicates that interarticular variation within the horse needs to be considered. Keywords-infrared spectroscopy, osteoarthritis, synovial fluid, discriminant analysis
Deep Learning in Mechanical Metamaterials: From Prediction and Generation to Inverse Design

Mechanical metamaterials are meticulously designed structures with exceptional mechanical properties determined by their microstructures and constituent materials. Tailoring their material and geometric distribution unlocks the potential to achieve unprecedented bulk properties and functions. However, current mechanical metamaterial design considerably relies on experienced designers' inspiration through trial and error, while investigating their mechanical properties and responses entails time‐consuming mechanical testing or computationally expensive simulations. Nevertheless, recent advancements in deep learning have revolutionized the design process of mechanical metamaterials, enabling property prediction and geometry generation without prior knowledge. Furthermore, deep generative models can transform conventional forward design into inverse design. Many recent studies on the implementation of deep learning in mechanical metamaterials are highly specialized, and their pros and cons may not be immediately evident. This critical review provides a comprehensive overview of the capabilities of deep learning in property prediction, geometry generation, and inverse design of mechanical metamaterials. Additionally, this review highlights the potential of leveraging deep learning to create universally applicable datasets, intelligently designed metamaterials, and material intelligence. This article is expected to be valuable not only to researchers working on mechanical metamaterials but also those in the field of materials informatics.