Miracle-dz/UniFAR-FTUs huggingface dataset:
Serum retinyl esters are positively correlated with analyzed total liver vitamin A reserves collected from US adults at time of death.

Background Minimal human data exist on liver vitamin A (VA) compared with serum biomarkers. Cutoffs of 5% and 10% total serum VA as retinyl esters (REs) suggest a VA intoxication diagnosis. Objectives We compared total liver VA reserves (TLRs) with the percentage of total serum VA as REs to evaluate hypervitaminosis with the use of US adult autopsy samples. Secondary objectives evaluated serum retinol sensitivity, TLRs among lobes, and hepatic α-retinol concentrations, an α-carotene cleavage product. Design Matched serum and liver samples were procured from cadavers (n = 27; mean ± SD age: 70.7 ± 14.9 y; range: 49-101 y). TLRs and α-REs were quantified by ultra-performance liquid chromatography. Pearson correlations showed liver and serum associations. Sensitivity and specificity were calculated for >5%, 7.5%, and 10% total serum VA as REs to predict TLRs and for serum retinol <0.7 and 1 μmol/L to predict deficiency. Results Serum RE concentrations were correlated with TLRs (r = 0.497, P < 0.001). Nine subjects (33%) had hypervitaminosis A (≥1.0 μmol VA/g liver), 2 of whom had >7.5% total serum VA as REs; histologic indicators corroborated toxicity at 3 μmol/g liver. No subject had >10% total serum VA as REs. Serum retinol sensitivity to determine deficiency (TLRs <0.1 μmol VA/g) was 83% at 0.7 and 1 μmol/L. Hepatic α-retinol was positively correlated with age (P = 0.047), but removing an outlier nullified significance. Conclusions This study evaluated serum REs as a biomarker of VA status against TLRs (gold standard), and abnormal histology suggested that 7.5% total serum VA as REs is diagnostic for toxicity at the individual level in adults. The long-term impact of VA supplements and fortificants on VA status is currently unknown. Considering the high prevalence of hypervitaminotic TLRs in this cohort, and given that many countries are adding preformed VA to processed products, population biomarkers diagnosing hypervitaminosis before toxicity are urgently needed. This trial was registered at clinicaltrials.govas NCT03305042.
The anti‐inflammatory and antioxidant effects of leonurine hydrochloride after lipopolysaccharide challenge in broiler chicks

ABSTRACT This study was carried out to investigate the protective effects of leonurine hydrochloride (LH, from Leonurus sibiricus) on lipopolysaccharide (LPS)‐stimulated broiler chicks. A total of 120 one‐day‐old male Ross broilers were randomly divided into 4 treatment groups with 6 replicates of 5 birds per cage. The experiment was designed as a 2 × 2 factorial arrangement with LH (0 or 120 mg/kg) and LPS (injection of saline or 1.5 mg/kg body weight) levels as treatments. On days 14, 16, 18, and 20 of the trial, broilers were intraperitoneally injected with LPS or saline. Blood, spleen, and liver samples were collected on days 21 and 28 for analysis. The results showed that dietary LH had no effect on growth performance or immunoglobulin concentrations in the serum. However, dietary LH prevented LPS‐induced reductions in average daily gain and average daily feed intake in the broilers on days 15‐21 of the trial (P > 0.05). Dietary LH supplementation dramatically attenuated the LPS‐induced increases in the spleen index, reduced glutathione (GSH) activity (serum and liver) and total superoxide dismutase (T‐SOD) activity (serum and spleen), and significantly reduced malondialdehyde (MDA) levels (serum, spleen, and liver) on days 21 and 28 (P < 0.05). Additionally, LH supplementation significantly mitigated the LPS‐induced increases in the tumor necrosis factor (TNF)‐&agr; (serum and spleen), interleukin (IL)‐1&bgr; (serum, spleen and liver), IL‐2 (liver), IL‐6 (serum, spleen and liver), toll‐like receptor 4 (TLR4) (spleen and liver), and nuclear factor (NF)‐&kgr;B (spleen and liver) levels on days 21 and 28 (P < 0.05). Therefore, this study revealed that LH could downregulate the expression of proinflammatory factors, mainly by inhibiting the expression of TLR4 and the activation of NF‐&kgr;B. LH may be a potential feed additive with dual efficacy as an anti‐inflammatory and antioxidant agent.
DksA Controls the Response of the Lyme Disease Spirochete Borrelia burgdorferi to Starvation

The Lyme disease bacterium Borrelia burgdorferi survives diverse environmental challenges as it cycles between its tick vectors and various vertebrate hosts. B. burgdorferi must withstand prolonged periods of starvation while it resides in unfed Ixodes ticks. In this study, the regulatory protein DksA is shown to play a pivotal role controlling the transcriptional responses of B. burgdorferi to starvation. The results suggest that DksA gene regulatory activity impacts B. burgdorferi metabolism, virulence gene expression, and the ability of this bacterium to complete its natural life cycle. ABSTRACT The pathogenic spirochete Borrelia burgdorferi senses and responds to changes in the environment, including changes in nutrient availability, throughout its enzootic cycle in Ixodes ticks and vertebrate hosts. This study examined the role of DnaK suppressor protein (DksA) in the transcriptional response of B. burgdorferi to starvation. Wild-type and dksA mutant B. burgdorferi strains were subjected to starvation by shifting cultures grown in rich complete medium, Barbour-Stoenner-Kelly II (BSK II) medium, to a defined mammalian tissue culture medium, RPMI 1640, for 6 h under microaerobic conditions (5% CO2, 3% O2). Microarray analyses of wild-type B. burgdorferi revealed that genes encoding flagellar components, ribosomal proteins, and DNA replication machinery were downregulated in response to starvation. DksA mediated transcriptomic responses to starvation in B. burgdorferi, as the dksA-deficient strain differentially expressed only 47 genes in response to starvation compared to the 500 genes differentially expressed in wild-type strains. Consistent with a role for DksA in the starvation response of B. burgdorferi, fewer CFU of dksA mutants were observed after prolonged starvation in RPMI 1640 medium than CFU of wild-type B. burgdorferi spirochetes. Transcriptomic analyses revealed a partial overlap between the DksA regulon and the regulon of RelBbu, the guanosine tetraphosphate and guanosine pentaphosphate [(p)ppGpp] synthetase that controls the stringent response; the DksA regulon also included many plasmid-borne genes. Additionally, the dksA mutant exhibited constitutively elevated (p)ppGpp levels compared to those of the wild-type strain, implying a regulatory relationship between DksA and (p)ppGpp. Together, these data indicate that DksA, along with (p)ppGpp, directs the stringent response to effect B. burgdorferi adaptation to its environment. IMPORTANCE The Lyme disease bacterium Borrelia burgdorferi survives diverse environmental challenges as it cycles between its tick vectors and various vertebrate hosts. B. burgdorferi must withstand prolonged periods of starvation while it resides in unfed Ixodes ticks. In this study, the regulatory protein DksA is shown to play a pivotal role controlling the transcriptional responses of B. burgdorferi to starvation. The results suggest that DksA gene regulatory activity impacts B. burgdorferi metabolism, virulence gene expression, and the ability of this bacterium to complete its natural life cycle.
Numerical analysis of the flows in the pebble bed geometries

Many industrial processes in engineering occur in complex fluid-solid regions. In this thesis, we discuss Finite Element algorithms for modelling the fluid flow and heat transfer in such domains. Often times, for these types of problems, the meshing (and remeshing for time-dependant problems) process is the most computationally demanding portion of the solution process. We develop and analyze various algorithms that can be applied on a uniform mesh, by incorporating information about the geometry of the flow domain into the model.
The monitoring of land-cover change in western China from remote sensing data

There are serious environmental problems, such as deforestation, soil erosion, salinization, and desert encroachment in the western China, its natural conditions is very delicate. But little is known about change in this region. The remote sensing data and digital image processing techniques provide consistent, reliable and quantifiable regional scale land-cover for environmental change research. The objective of this study is analyzing the environment change in a year in western China by using remote sensing data. In this paper, three typical experiment sites, which are a desert and oasis area, a loess plateau area and the source area of the Yellow River, are selected for detail change analyses. The change of NDVI, land-cover classifications between 1980s and present are detected from the satellite data. The datasets of remote sensing include Landsat-TM, ETM, SPOT and ASTER, all of these image are normalized to 30 m resolution and same coordination system for change analyses. The results show that industry development, cultivated land increment, soil erosion, forest and grassland decrement are the main reason of environmental deterioration.
Stability of core language skill from infancy to adolescence in typical and atypical development

From infancy to adolescence, children show strong stability of individual differences in core language skill. Command of language is a fundamental life skill, a cornerstone of cognitive and socioemotional development, and a necessary ingredient for successful functioning in society. We used 15-year prospective longitudinal data from the Avon Longitudinal Study of Parents and Children to evaluate two types of stability of core language skill in 5036 typically developing and 1056 atypically developing (preterm, dyslexic, autistic, and hearing impaired) children in a multiage, multidomain, multimeasure, multireporter framework. A single core language skill was extracted from multiple measures at multiple ages, and this skill proved stable from infancy to adolescence in all groups, even accounting for child nonverbal intelligence and sociability and maternal age and education. Language skill is a highly conserved and robust individual-differences characteristic. Lagging language skills, a risk factor in child development, would profitably be addressed early in life.
How pump–probe differential reflectivity at negative delay yields the perturbed-free-induction-decay: theory of the experiment and its verification

We present a simple but mathematically complete first-principles theory for the pump–probe differential reflectivity experiment at negative delay (probe preceding the pump) to show how it gives information about the perturbed-free-induction-decay of coherent polarization. The calculation, involving the optical Bloch equations to describe the induced polarization and the Ewald–Oseen idea to calculate the reflected signal as a consequence of the free oscillations of perturbed dipoles, also explicitly includes the process of lock-in detection of a double-chopped signal after it has passed through a monochromator. The theory giving a closed form expression for the measured signal in both time and spectal domains is compared with experiments on high quality GaAs quantum well sample. The dephasing time inferred experimentally at 4 K compares remarkably well with the inverse of the absorption linewidth of the continuous-wave photoluminescence excitation spectrum. Spectrally-resolved signal at negative delay calculated from our theoretical expression nicely reproduces the coherent spectral oscillations observed in our experiments, although exact fitting of the experimental spectra with the theoretical expression is difficult on account of multiple resonances.
A variational approach to optimal nonholonomic motion planning

Nonholonomic motion planning (NMP) problems arise not only from the classical nonholonomic constraints, but also from symmetries and conservation laws of holonomic systems. In NMP problems an admissible configuration space path is constrained to a given nonholonomic distribution. Thus, NMP deals with the problem of (optimal) path finding subject to a nonholonomic distribution and possibly to additional holonomic constraints. The authors first study several representative NM systems and formulate the NMP problem. Variational principles are used to characterize optimal solutions to these problems. A simple algorithm solving an NMP problem is proposed, and simulation results are presented. <<ETX>>
Parallel Schedule of Live Migrations for Virtual Machine Placements

Cloud based services play a major role in collaborative computing on the Internet across the globe. Managing the computing and network resources to serve dynamic demands of the tenants of an infrastructure-as-a-service (IaaS) cloud is a major challenge for the cloud service provider (CSP). Accommodating the custom resource requirements often result in the migration of virtual machines (VMs) already executing on a server. Live VM migrations, which relocates a VM without halting, helps the CSP to achieve this objective. Identifying the best set of parallelized migrations which discovers the resources to meet tenants' demands would be highly beneficial to the CSP. This paper proposes a simulated annealing algorithm to find a set of migrations which can be scheduled in parallel so as to complete all the live migrations in minimal time. Completion of the migrations as per the schedule can aid in timely deployment of new VMs. Experimental evaluation shows that the proposed optimal scheduling can significantly speed up the process of resource provisioning compared to the existing techniques and a serial migration schedule.
A dynamic adaptive deviation registration algorithm for heterogeneous sensors

Deviation registration algorithm of homogeneous sensors has grown mature, but heterogeneous sensors deviation registration algorithm still faces the problems like strong nonlinearity and low precision, which needs urgent solutions. To eliminate the difficulties in deviation registration of heterogeneous sensors, especially the different dimensional sensors, the heterogeneous sensors deviation registration model and dynamic adaptive particle swarm optimized particle filter are proposed. In this paper, dynamic adaptive particle swarm optimized particle filter and Kalman filter is federated to carry out the real‐time calibration for the system deviation of radar and infrared sensor. With particle neighborhood information taken into account, this algorithm conducts a self‐adaptive adjustment over the number of particle's neighborhood particles by means of diversity factor, neighborhood extension factor, and neighborhood restriction factor. The adjustment is intended to control the influence of particle on neighborhood and reduce its local optimum so as to attain the optimal balance between convergence rate and optimization ability. The experimental result shows that the improved heterogeneous sensors deviation registration algorithm has upgraded the accuracy and speed of deviation registration; therefore, this algorithm is of high application value in the deviation registration of three‐dimensional radar and two‐dimensional infrared sensor.
APLIKASI ASESMEN DALAM PEMBELAJARAN IPA DI KELAS IV SEKOLAH DASAR NEGERI GELOGOR

Penelitian kualitatif ini menggunakan rancangan penelitian tindakan kelas. Subjek penelitiannya kelas IV SD Negeri Gelogor. Penelitian ini bertujuan untuk mengetahui bagaimana guru mengaplikasikan asesmen dalam pembelajaran IPA di kelas IV SD Negeri Gelogor sebagai suatu upaya meningkatkan efektivitas pelaksanaan evaluasi di sekolah dasar. Untuk mencapai tujuan ini diperlukan data empirik yang diperoleh dari kelas yang diberi tindakan dengan menggunakan teknik observasi, wawancara, dan evaluasi. Analisis data dilakukan selama dan sesudah pengumpulan data di lapangan. Pengamatan dilakukan secara ongoing proses, saat guru melakukan tindakan pembelajaran IPA. Hasil yang diperoleh adalah sebelum guru melaksanakan asesmen terlebih dahulu membuat rancangan alat evaluasi bersamaan dengan rancangan pembelajaran yang akan dilaksanakan. Kemudian saat pembelajaran berlangsung guru melaksanakan rancangan alat evaluasinya. Dalam pelaksanaan pembelajaran IPA tersebut guru berhasil melaksanakan asesmen dalam bentuk a) penilaian proses, b) portofolio, c) wawancara dan diskusi, dan d) tes formatif.
A Pharmacist-Initiated Method to Improve Venous Thromboembolic Prophylaxis Rates in Medically Ill Patients

Venous thromboembolism (VTE) is among the most preventable causes of hospital death; however, there is a significant underuse of VTE prophylaxis. The purpose of this study was to determine the impact of a pharmacist-initiated screening method on VTE prophylaxis rates. Clinical pharmacists practicing in an internal medicine teaching service at an academic medical center conducted a 6-month pilot project. Consecutive patients admitted to the service were screened for VTE and bleeding risk factors. Pharmacists made recommendations to the physicians in person, provided monthly educational presentations, and monitored patients daily until discharge to confirm continued appropriateness of recommendations. Of the 444 patients who were screened, 107 were identified to be candidates for VTE prophylaxis, and 21 of these patients also had bleeding risk factors. Appropriate use was significantly better after the screening intervention (37% before vs 85% after; P < .05). Moreover, inappropriate use in patients with bleeding risk factors was avoided by the screening intervention (29% before vs 0% after; P < .05). Clear improvements in VTE prophylaxis rates were observed. This pharmacist-initiated screening method presents unique opportunities for pharmacists.
Robust Recurrent CNV Detection in the Presence of Inter-Subject Variability

The study of recurrent copy number variations (CNVs) plays an important role in understanding the onset and evolution of complex diseases such as cancer. Array-based comparative genomic hybridization (aCGH) is a widely used microarray based technology for identifying CNVs. However, due to high noise levels and inter-sample variability, detecting recurrent CNVs from aCGH data remains a challenging topic. This paper proposes a novel method for identification of the recurrent CNVs. In the proposed method, the noisy aCGH data is modeled as the superposition of three matrices: a full-rank matrix of weighted piece-wise generating signals accounting for the clean aCGH data, a Gaussian noise matrix to model the inherent experimentation errors and other sources of error, and a sparse matrix to capture the sparse inter-sample (sample-specific) variations. We demonstrated the ability of our method to separate accurately recurrent CNVs from sample-specific variations and noise in both simulated (artificial) data and real data. The proposed method produced more accurate results than current state-of-the-art methods used in recurrent CNV detection and exhibited robustness to noise and sample-specific variations.
QuickCount®: a novel automated software for rapid cell detection and quantification.

We describe a novel automated cell detection and counting software, QuickCount® (QC), designed for rapid quantification of cells. The Bland-Altman plot and intraclass correlation coefficient (ICC) analyses demonstrated strong agreement between cell counts from QC to manual counts (mean and SD: -3.3 ± 4.5; ICC = 0.95). QC has higher recall in comparison to ImageJauto, CellProfiler and CellC and the precision of QC, ImageJauto, CellProfiler and CellC are high and comparable. QC can precisely delineate and count single cells from images of different cell densities with precision and recall above 0.9. QC is unique as it is equipped with real-time preview while optimizing the parameters for accurate cell count and needs minimum hands-on time where hundreds of images can be analyzed automatically in a matter of milliseconds. In conclusion, QC offers a rapid, accurate and versatile solution for large-scale cell quantification and addresses the challenges often faced in cell biology research.
OCMA: Fast, Memory-Efficient Factorization of Prohibitively Large Relationship Matrices

Matrices representing genetic relatedness among individuals (i.e., Genomic Relationship Matrices, GRMs) play a central role in genetic analysis. The eigen-decomposition of GRMs (or its alternative that generates fewer top singular values using genotype matrices) is a necessary step for many analyses including estimation of SNP-heritability, Principal Component Analysis (PCA), and genomic prediction. However, the GRMs and genotype matrices provided by modern biobanks are too large to be stored in active memory. To accommodate the current and future “bigger-data”, we develop a disk-based tool, Out-of-Core Matrices Analyzer (OCMA), using state-of-the-art computational techniques that can nimbly perform eigen and Singular Value Decomposition (SVD) analyses. By integrating memory mapping (mmap) and the latest matrix factorization libraries, our tool is fast and memory-efficient. To demonstrate the impressive performance of OCMA, we test it on a personal computer. For full eigen-decomposition, it solves an ordinary GRM (N = 10,000) in 55 sec. For SVD, a commonly used faster alternative of full eigen-decomposition in genomic analyses, OCMA solves the top 200 singular values (SVs) in half an hour, top 2,000 SVs in 0.95 hr, and all 5,000 SVs in 1.77 hr based on a very large genotype matrix (N = 1,000,000, M = 5,000) on the same personal computer. OCMA also supports multi-threading when running in a desktop or HPC cluster. Our OCMA tool can thus alleviate the computing bottleneck of classical analyses on large genomic matrices, and make it possible to scale up current and emerging analytical methods to big genomics data using lightweight computing resources.
Keep Drawing It: Iterative language-based image generation and editing

Conditional text-to-image generation approaches commonly focus on generating a single image in a single step. One practical extension beyond one-step generation is an interactive system that generates an image iteratively, conditioned on ongoing linguistic input / feedback. This is significantly more challenging as such a system must understand and keep track of the ongoing context and history. In this work, we present a recurrent image generation model which takes into account both the generated output up to the current step as well as all past instructions for generation. We show that our model is able to generate the background, add new objects, apply simple transformations to existing objects, and correct previous mistakes. We believe our approach is an important step toward interactive generation.