Miracle-dz/UniFAR-FTUs huggingface dataset:
Non-purposive perceptual region grouping

Non-purposive or general-purpose region grouping (NPG) plays a significant role in bridging image segmentation and high-level image understanding. We propose a probabilistic model for the NPG problem by defining the regions as a Markov random field (MRF). A collection of energy functions is used to characterize single-region properties and pair-wise region properties. The single-region properties include region area, region convexity, region compactness, and color variances in one region. The pair-wise properties include color mean differences between two regions; edge strength along the shared boundary; color variance of the cross-boundary area; and contour continuity between two regions. Experiments have been performed on hundreds of images to show the effectiveness of the grouping algorithm.
Phylogeographic Analysis of Blastomyces dermatitidis and Blastomyces gilchristii Reveals an Association with North American Freshwater Drainage Basins

Blastomyces dermatitidis and Blastomyces gilchristii are dimorphic fungal pathogens that cause serious pulmonary and systemic infections in humans. Although their natural habitat is in the environment, little is known about their specific ecologic niche(s). Here, we analyzed 25 microsatellite loci from 169 strains collected from various regions throughout their known endemic range in North America, representing the largest and most geographically diverse collection of isolates studied to date. Genetic analysis of multilocus microsatellite data divided the strains into four populations of B. dermatitidis and four populations of B. gilchristii. B. dermatitidis isolates were recovered from areas throughout North America, while the B. gilchristii strains were restricted to Canada and some northern US states. Furthermore, the populations of both species were associated with major freshwater drainage basins. The four B. dermatitidis populations were partitioned among (1) the Nelson River drainage basin, (2) the St. Lawrence River and northeast Atlantic Ocean Seaboard drainage basins, (3) the Mississippi River System drainage basin, and (4) the Gulf of Mexico Seaboard and southeast Atlantic Ocean Seaboard drainage basins. A similar partitioning of the B. gilchristii populations was observed among the more northerly drainage basins only. These associations suggest that the ecologic niche where the sexual reproduction, growth, and dispersal of B. dermatitidis and B. gilchristii occur is intimately linked to freshwater systems. For most populations, sexual reproduction was rare enough to produce significant linkage disequilibrium among loci but frequent enough that mating-type idiomorphic ratios were not skewed from 1:1. Furthermore, the evolutionary divergence of B. dermatitidis and B. gilchristii was estimated at 1.9 MYA during the Pleistocene epoch. We suggest that repeated glaciations during the Pleistocene period and resulting biotic refugia may have provided the impetus for speciation as theorized for other species associated with temperate freshwater systems.
Initiation of EDC-37 measured with embedded electromagnetic particle velocity gauges

Planar shock wave initiation of the explosive EDC-37 was studied using multiple embedded magnetic particle velocity gauges. EDC-37 consists of (by weight) 91% HMX, 1% nitrocellulose, and 8% K10, a liquid eutectic mixture of di-nitro-ethyl-benzene and tri-nitro-ethyl-benzene. Its nominal density is 1.841±0.002 g/cm3. The Hugoniot for EDC-37 was measured as US=2.4+2.4uP, similar to other explosives of this density containing at least 90% HMX. The run distance to detonation, X*, vs. shock pressure P, was measured as log(X*)=2.0−1.5 log(P). This curve is shifted to a few GPa higher pressure compared to that of other plastic bonded explosives containing 90–95% HMX. This shift is most likely due to the low void content of EDC-37. Like other high density HMX based explosives, EDC-37 initiates with wave profiles having a little increase in particle velocity at the shock front (heterogeneous initiation), and also a second wave which starts small at the impact surface, grows as it travels, and reaches a large ampli.
The size effect in foams and its theoretical and numerical investigation

Experimental data for foams lead to different values of the elastic moduli depending on the performed test, i.e. compression and tension tests give a different set of parameters than shear and bending tests. This may be explained by the size effect, which depends on the microstructure of the foams. Thus, in this paper, the behaviour of foams is investigated on the basis of both microscopic and macroscopic mechanical models. The microscopic approach is based on a lattice beam model. The solution of this model shows that the boundary–layer effect is strongly local but allows for the explanation of the size effect. Furthermore, the size effect can be included in the macroscopic continuum model by application of a Cosserat formulation. The extended continuum model allows for the independent fit of material parameters to different load cases, i.e. to compression and shear. The solution of the macroscopic Cosserat model permits a relation of the internal length–scale to the average cell size of the microstructure.
Graph theory reveals dysconnected hubs in 22q11DS and altered nodal efficiency in patients with hallucinations

Schizophrenia is postulated to be the prototypical dysconnection disorder, in which hallucinations are the core symptom. Due to high heterogeneity in methodology across studies and the clinical phenotype, it remains unclear whether the structural brain dysconnection is global or focal and if clinical symptoms result from this dysconnection. In the present work, we attempt to clarify this issue by studying a population considered as a homogeneous genetic sub-type of schizophrenia, namely the 22q11.2 deletion syndrome (22q11.2DS). Cerebral MRIs were acquired for 46 patients and 48 age and gender matched controls (aged 6–26, respectively mean age = 15.20 ± 4.53 and 15.28 ± 4.35 years old). Using the Connectome mapper pipeline (connectomics.org) that combines structural and diffusion MRI, we created a whole brain network for each individual. Graph theory was used to quantify the global and local properties of the brain network organization for each participant. A global degree loss of 6% was found in patients' networks along with an increased Characteristic Path Length. After identifying and comparing hubs, a significant loss of degree in patients' hubs was found in 58% of the hubs. Based on Allen's brain network model for hallucinations, we explored the association between local efficiency and symptom severity. Negative correlations were found in the Broca's area (p < 0.004), the Wernicke area (p < 0.023) and a positive correlation was found in the dorsolateral prefrontal cortex (DLPFC) (p < 0.014). In line with the dysconnection findings in schizophrenia, our results provide preliminary evidence for a targeted alteration in the brain network hubs' organization in individuals with a genetic risk for schizophrenia. The study of specific disorganization in language, speech and thought regulation networks sharing similar network properties may help to understand their role in the hallucination mechanism.
Glycation of Fetal Hemoglobin Reflects Hyperglycemia Exposure In Utero

OBJECTIVE The lifetime risk of metabolic diseases in offspring of women with gestational diabetes mellitus (GDM) depends, at least in part, on the impact of glycemic fetal programming. To quantify this impact, we have developed and validated a unique mass spectrometry method to measure the percentage of glycated hemoglobin in cord blood. RESEARCH DESIGN AND METHODS This case-control study includes 37 GDM women and 30 pregnant women with normal glucose tolerance (NGT). RESULTS Glycation of the α-chain (Glα) was higher in neonates from GDM (2.32 vs. 2.20%, P < 0.01). Glα strongly correlated with maternal A1C measured at delivery in the overall cohort (r = 0.67, P < 0.0001) as well as in each group (GDM: r = 0.66, P < 0.0001; NGT: r = 0.50, P = 0.01). CONCLUSIONS Thus, Glα may reflect hyperglycemic exposure during the last weeks of fetal development. Future studies will confirm Glα is a predictive biomarker of prenatally programmed lifetime metabolic health and disease.
1-CMDb: A Curated Database of Genomic Variations of the One-Carbon Metabolism Pathway

Background: The one-carbon metabolism pathway is vital in maintaining tissue homeostasis by driving the critical reactions of folate and methionine cycles. A myriad of genetic and epigenetic events mark the rate of reactions in a tissue-specific manner. Integration of these to predict and provide personalized health management requires robust computational tools that can process multiomics data. The DNA sequences that may determine the chain of biological events and the endpoint reactions within one-carbon metabolism genes remain to be comprehensively recorded. Hence, we designed the one-carbon metabolism database (1-CMDb) as a platform to interrogate its association with a host of human disorders. Methods: DNA sequence and network information of a total of 48 genes were extracted from a literature survey and KEGG pathway that are involved in the one-carbon folate-mediated pathway. The information generated, collected, and compiled for all these genes from the UCSC genome browser included the single nucleotide polymorphisms (SNPs), CpGs, copy number variations (CNVs), and miRNAs, and a comprehensive database was created. Furthermore, a significant correlation analysis was performed for SNPs in the pathway genes. Results: Detailed data of SNPs, CNVs, CpG islands, and miRNAs for 48 folate pathway genes were compiled. The SNPs in CNVs (9670), CpGs (984), and miRNAs (14) were also compiled for all pathway genes. The SIFT score, the prediction and PolyPhen score, as well as the prediction for each of the SNPs were tabulated and represented for folate pathway genes. Also included in the database for folate pathway genes were the links to 124 various phenotypes and disease associations as reported in the literature and from publicly available information. Conclusion: A comprehensive database was generated consisting of genomic elements within and among SNPs, CNVs, CpGs, and miRNAs of one-carbon metabolism pathways to facilitate (a) single source of information and (b) integration into large-genome scale network analysis to be developed in the future by the scientific community. The database can be accessed at http://slsdb.manipal. edu/ocm/.
Standardization of 68Ge/68Ga Using Three Liquid Scintillation Counting Based Methods

A solution containing 68Ge in equilibrium with its daughter, 68Ga, has been standardized for the first time at the National Institute of Standards and Technology (NIST) using 3 liquid scintillation-based techniques: live-timed 4πβ -γ anticoincidence (LTAC) counting, the Triple-to-Double Coincidence Ratio (TDCR) method, and 3H-standard efficiency tracing with the CIEMAT1/NIST (CNET) method. The LTAC technique is much less dependent on level scheme data and model-dependent parameters and was thus able to provide a reference activity concentration value for the master solution with a combined standard uncertainty of about 0.3 %. The other two methods gave activity concentration values with respective differences from the reference value of +1.2 % and −1.5 %, which were still within the experimental uncertainties. Measurements made on the NIST “4π”γ secondary standard ionization chamber allowed for the determination of calibration factors for that instrument, allowing future calibrations to be made for 68Ge/68Ga without the need for a primary measurement. The ability to produce standardized solutions of 68Ge presents opportunities for the development of a number of NIST-traceable calibration sources with very low (<1 %) relative standard uncertainties that can be used in diagnostic medical imaging.
pH‐Dependent Anticancer Drug Release from Silk Nanoparticles

Silk has traditionally been used as a suture material because of its excellent mechanical properties and biocompatibility. These properties have led to the development of different silk‐based material formats for tissue engineering and regenerative medicine. Although there have been a small number of studies about the use of silk particles for drug delivery, none of these studies have assessed the potential of silk to act as a stimulus‐responsive anticancer nanomedicine. This report demonstrates that an acetone precipitation of silk allows the formation of uniform silk nanoparticles (98 nm diameter, polydispersity index 0.109), with an overall negative surface charge (–33.6 ± 5.8 mV), in a single step. Silk nanoparticles are readily loaded with doxorubicin (40 ng doxorubicin/μg silk) and show pH‐dependent release (pH 4.5≫ 6.0 > 7.4). In vitro studies with human breast cancer cell lines demonstrates that the silk nanoparticles are not cytotoxic (IC50 > 120 μg mL−1) and that doxorubicin‐loaded silk nanoparticles are able to overcome drug resistance mechanisms. Live cell fluorescence microscopy studies show endocytic uptake and lysosomal accumulation of silk nanoparticles. In summary, the pH‐dependent drug release and lysosomal accumulation of silk nanoparticles demonstrate the ability of drug‐loaded silk nanoparticles to serve as a lysosomotropic anticancer nanomedicine.
How Sound Symbolism Is Processed in the Brain: A Study on Japanese Mimetic Words

Sound symbolism is the systematic and non-arbitrary link between word and meaning. Although a number of behavioral studies demonstrate that both children and adults are universally sensitive to sound symbolism in mimetic words, the neural mechanisms underlying this phenomenon have not yet been extensively investigated. The present study used functional magnetic resonance imaging to investigate how Japanese mimetic words are processed in the brain. In Experiment 1, we compared processing for motion mimetic words with that for non-sound symbolic motion verbs and adverbs. Mimetic words uniquely activated the right posterior superior temporal sulcus (STS). In Experiment 2, we further examined the generalizability of the findings from Experiment 1 by testing another domain: shape mimetics. Our results show that the right posterior STS was active when subjects processed both motion and shape mimetic words, thus suggesting that this area may be the primary structure for processing sound symbolism. Increased activity in the right posterior STS may also reflect how sound symbolic words function as both linguistic and non-linguistic iconic symbols.
Fracture mechanics analysis of delamination failures in IC packages

This paper describes the application of fracture mechanics to the analysis of delamination in IC packages. An introduction to the fundamentals of interfacial fracture mechanics will first be given together with a description of some numerical methods for calculating fracture mechanics parameters such as strain energy release rate and mode mixity. Fracture mechanics methodology will then be applied to analyze the popcorn cracking failure of moisture-preconditioned plastic-encapsulated IC packages undergoing solder reflow. The effect of moisture in engendering hygrostress and degrading interfacial fracture toughness will be discussed. Simulation of heat transfer and moisture diffusion processes occurring during package qualification will be described. Experiments which verify the methodology for predicting delamination in packages using the fracture mechanics approach will then be presented, followed by some interesting case studies.
Approximate Query Answering by Model Averaging

In earlier work we have introduced and explored a variety of different probabilistic models for the problem of answering selectivity queries posed to large sparse binary data sets. These models can be directly scaled to hundreds or thousands of dimensions, in contrast to other approximate querying techniques (such as histograms or wavelets) that are inherently limited to relatively small numbers of dimensions. In this paper, we extend this work by applying probabilistic model-averaging to the problem of query answering, a scheme that allows the query-answering algorithm to automatically and optimally adapt to both the specific nature of the data and the distribution of queries being issued any specific user. We demonstrate that on realworld and simulated data sets that model-averaging can reduce the prediction error of any single model by factors of up to 50%. Learning the combining weights is a straightforward and scalable optimization problem that can be easily automated, providing a practical framework for approximate query answering with massive data sets.
Visual Response Properties of V1 Neurons Projecting to V2 in Macaque

Visual area V2 of the primate cortex receives the largest projection from area V1. V2 is thought to use its striate inputs as the basis for computations that are important for visual form processing, such as signaling angles, object borders, illusory contours, and relative binocular disparity. However, it remains unclear how selectivity for these stimulus properties emerges in V2, in part because the functional properties of the inputs are unknown. We used antidromic electrical stimulation to identify V1 neurons that project directly to V2 (10% of all V1 neurons recorded) and characterized their electrical and visual responses. V2-projecting neurons were concentrated in the superficial and middle layers of striate cortex, consistent with the known anatomy of this cortico-cortical circuit. Most were fast conducting and temporally precise in their electrical responses, and had broad spike waveforms consistent with pyramidal regular-spiking excitatory neurons. Overall, projection neurons were functionally diverse. Most, however, were tuned for orientation and binocular disparity and were strongly suppressed by large stimuli. Projection neurons included those selective and invariant to spatial phase, with roughly equal proportions. Projection neurons found in superficial layers had longer conduction times, broader spike waveforms, and were more responsive to chromatic stimuli; those found in middle layers were more strongly selective for motion direction and binocular disparity. Collectively, these response properties may be well suited for generating complex feature selectivity in and beyond V2.
A dynamic RWA algorithm in a wavelength-routed all-optical network with wavelength converters

Existing research demonstrated that an effective routing and wavelength assignment (RWA) scheme and a wavelength converter placement algorithm are the two primary vehicles for improving the blocking performance in a wavelength-routed all-optical network. However, these issues have largely been investigated separately, in particular, the RWA has seldom considered the existence of wavelength converters. In this paper, we argue perhaps for the first time, that an effective RWA algorithm needs to take into account the presence of wavelength conversion as the latter is usually done at much earlier stage during the capacity planning. We proceed to show that existing dynamic RWA algorithms largely fail in the presence of wavelength conversion. We then propose a weighted least-congestion routing and first-fit wavelength assignment (WLCR-FF) RWA algorithm in conjunction with a simple heuristic wavelength converter placement algorithm called minimum blocking probability first (MBPF) that considers both the distribution of free wavelengths and the lengths of each route jointly. We further introduce an analytical model that can obtain the blocking performance of the proposed WLCR routing algorithm. Using both analysis and simulation, we carry out extensive numerical studies over the typical topologies including the ring, mesh-torus, and two mesh topologies, the 14-node NSFNET and the 19-node European Optical Network (EON); we compare the performance of proposed algorithm with a wide variety of existing routing algorithms including static routing, fixed-alternate routing and least-loaded routing algorithms. The results conclusively demonstrate that the proposed WLCR-FF algorithm can achieve much better blocking performance in the environment of sparse or/and full wavelength conversion.
Clinical Overview of MDM2/X-Targeted Therapies

MDM2 and MDMX are the primary negative regulators of p53, which under normal conditions maintain low intracellular levels of p53 by targeting it to the proteasome for rapid degradation and inhibiting its transcriptional activity. Both MDM2 and MDMX function as powerful oncogenes and are commonly over-expressed in some cancers, including sarcoma (~20%) and breast cancer (~15%). In contrast to tumors that are p53 mutant, whereby the current therapeutic strategy restores the normal active conformation of p53, MDM2 and MDMX represent logical therapeutic targets in cancer for increasing wild-type (WT) p53 expression and activities. Recent preclinical studies suggest that there may also be situations that MDM2/X inhibitors could be used in p53 mutant tumors. Since the discovery of nutlin-3a, the first in a class of small molecule MDM2 inhibitors that binds to the hydrophobic cleft in the N-terminus of MDM2, preventing its association with p53, there is now an extensive list of related compounds. In addition, a new class of stapled peptides that can target both MDM2 and MDMX have also been developed. Importantly, preclinical modeling, which has demonstrated effective in vitro and in vivo killing of WT p53 cancer cells, has now been translated into early clinical trials allowing better assessment of their biological effects and toxicities in patients. In this overview, we will review the current MDM2- and MDMX-targeted therapies in development, focusing particularly on compounds that have entered into early phase clinical trials. We will highlight the challenges pertaining to predictive biomarkers for and toxicities associated with these compounds, as well as identify potential combinatorial strategies to enhance its anti-cancer efficacy.
Short loop length and high thermal stability determine genomic instability induced by G‐quadruplex‐forming minisatellites

G‐quadruplexes (G4) are polymorphic four‐stranded structures formed by certain G‐rich nucleic acids, with various biological roles. However, structural features dictating their formation and/or function in vivo are unknown. In S. cerevisiae, the pathological persistency of G4 within the CEB1 minisatellite induces its rearrangement during leading‐strand replication. We now show that several other G4‐forming sequences remain stable. Extensive mutagenesis of the CEB25 minisatellite motif reveals that only variants with very short (≤ 4 nt) G4 loops preferentially containing pyrimidine bases trigger genomic instability. Parallel biophysical analyses demonstrate that shortening loop length does not change the monomorphic G4 structure of CEB25 variants but drastically increases its thermal stability, in correlation with the in vivo instability. Finally, bioinformatics analyses reveal that the threat for genomic stability posed by G4 bearing short pyrimidine loops is conserved in C. elegans and humans. This work provides a framework explanation for the heterogeneous instability behavior of G4‐forming sequences in vivo, highlights the importance of structure thermal stability, and questions the prevailing assumption that G4 structures with short or longer loops are as likely to form in vivo.