165 research outputs found
Value-added Evaluation System for Vocational School Students Construction and Practice Research
Student evaluation in the new era should be rooted in the educational macro background of "cultivating people by virtue" and comply with the overall policy orientation of educational evaluation reform. This research focuses on the construction and implementation of value-added evaluation system. Combined with the characteristics of vocational school students, this paper constructs a four-level index system and refines the student evaluation standards. The evaluation subjects are students, head teachers, teachers, parents and enterprise managers. Through the development of the related APP, it is convenient for each evaluation subject to input information, and finally use K-line chart to visually present the change process of the appreciation in students' literacy. A value-added evaluation system with strong timeliness, objectivity, motivation and operability is constructed
Mining Frequent Itemsets over Uncertain Databases
In recent years, due to the wide applications of uncertain data, mining
frequent itemsets over uncertain databases has attracted much attention. In
uncertain databases, the support of an itemset is a random variable instead of
a fixed occurrence counting of this itemset. Thus, unlike the corresponding
problem in deterministic databases where the frequent itemset has a unique
definition, the frequent itemset under uncertain environments has two different
definitions so far. The first definition, referred as the expected
support-based frequent itemset, employs the expectation of the support of an
itemset to measure whether this itemset is frequent. The second definition,
referred as the probabilistic frequent itemset, uses the probability of the
support of an itemset to measure its frequency. Thus, existing work on mining
frequent itemsets over uncertain databases is divided into two different groups
and no study is conducted to comprehensively compare the two different
definitions. In addition, since no uniform experimental platform exists,
current solutions for the same definition even generate inconsistent results.
In this paper, we firstly aim to clarify the relationship between the two
different definitions. Through extensive experiments, we verify that the two
definitions have a tight connection and can be unified together when the size
of data is large enough. Secondly, we provide baseline implementations of eight
existing representative algorithms and test their performances with uniform
measures fairly. Finally, according to the fair tests over many different
benchmark data sets, we clarify several existing inconsistent conclusions and
discuss some new findings.Comment: VLDB201
New insights into the hypothalamic–pituitary–thyroid axis:a transcriptome- and proteome-wide association study
Introduction: Thyroid hormones have systemic effects on the human body and play a key role in the development and function of virtually all tissues. They are regulated via the hypothalamic–pituitary–thyroid (HPT) axis and have a heritable component. Using genetic information, we applied tissue-specific transcriptome-wide association studies (TWAS) and plasma proteome-wide association studies (PWAS) to elucidate gene products related to thyrotropin (TSH) and free thyroxine (FT4) levels. Results: TWAS identified 297 and 113 transcripts associated with TSH and FT4 levels, respectively (25 shared), including transcripts not identified by genome-wide association studies (GWAS) of these traits, demonstrating the increased power of this approach. Testing for genetic colocalization revealed a shared genetic basis of 158 transcripts with TSH and 45 transcripts with FT4, including independent, FT4-associated genetic signals within the CAPZB locus that were differentially associated with CAPZB expression in different tissues. PWAS identified 18 and ten proteins associated with TSH and FT4, respectively (HEXIM1 and QSOX2 with both). Among these, the cognate genes of five TSH- and 7 FT4-associated proteins mapped outside significant GWAS loci. Colocalization was observed for five plasma proteins each with TSH and FT4. There were ten TSH and one FT4-related gene(s) significant in both TWAS and PWAS. Of these, ANXA5 expression and plasma annexin A5 levels were inversely associated with TSH (PWAS: P = 1.18 × 10−13, TWAS: P = 7.61 × 10−12 (whole blood), P = 6.40 × 10−13 (hypothalamus), P = 1.57 × 10−15 (pituitary), P = 4.27 × 10−15 (thyroid)), supported by colocalizations. Conclusion: Our analyses revealed new thyroid function-associated genes and prioritized candidates in known GWAS loci, contributing to a better understanding of transcriptional regulation and protein levels relevant to thyroid function.</p
De novo assembly and Characterisation of the Transcriptome during seed development, and generation of genic-SSR markers in Peanut (Arachis hypogaea L.)
<p>Abstract</p> <p>Background</p> <p>The peanut (<it>Arachis hypogaea </it>L.) is an important oilseed crop in tropical and subtropical regions of the world. However, little about the molecular biology of the peanut is currently known. Recently, next-generation sequencing technology, termed RNA-seq, has provided a powerful approach for analysing the transcriptome, and for shedding light on the molecular biology of peanut.</p> <p>Results</p> <p>In this study, we employed RNA-seq to analyse the transcriptomes of the immature seeds of three different peanut varieties with different oil contents. A total of 26.1-27.2 million paired-end reads with lengths of 100 bp were generated from the three varieties and 59,077 unigenes were assembled with N50 of 823 bp. Based on sequence similarity search with known proteins, a total of 40,100 genes were identified. Among these unigenes, only 8,252 unigenes were annotated with 42 gene ontology (GO) functional categories. And 18,028 unigenes mapped to 125 pathways by searching against the Kyoto Encyclopedia of Genes and Genomes pathway database (KEGG). In addition, 3,919 microsatellite markers were developed in the unigene library, and 160 PCR primers of SSR loci were used for validation of the amplification and the polymorphism.</p> <p>Conclusion</p> <p>We completed a successful global analysis of the peanut transcriptome using RNA-seq, a large number of unigenes were assembled, and almost four thousand SSR primers were developed. These data will facilitate gene discovery and functional genomic studies of the peanut plant. In addition, this study provides insight into the complex transcriptome of the peanut and established a biotechnological platform for future research.</p
Unsupervised Adaptation from Repeated Traversals for Autonomous Driving
For a self-driving car to operate reliably, its perceptual system must
generalize to the end-user's environment -- ideally without additional
annotation efforts. One potential solution is to leverage unlabeled data (e.g.,
unlabeled LiDAR point clouds) collected from the end-users' environments (i.e.
target domain) to adapt the system to the difference between training and
testing environments. While extensive research has been done on such an
unsupervised domain adaptation problem, one fundamental problem lingers: there
is no reliable signal in the target domain to supervise the adaptation process.
To overcome this issue we observe that it is easy to collect unsupervised data
from multiple traversals of repeated routes. While different from conventional
unsupervised domain adaptation, this assumption is extremely realistic since
many drivers share the same roads. We show that this simple additional
assumption is sufficient to obtain a potent signal that allows us to perform
iterative self-training of 3D object detectors on the target domain.
Concretely, we generate pseudo-labels with the out-of-domain detector but
reduce false positives by removing detections of supposedly mobile objects that
are persistent across traversals. Further, we reduce false negatives by
encouraging predictions in regions that are not persistent. We experiment with
our approach on two large-scale driving datasets and show remarkable
improvement in 3D object detection of cars, pedestrians, and cyclists, bringing
us a step closer to generalizable autonomous driving.Comment: Accepted by NeurIPS 2022. Code is available at
https://github.com/YurongYou/Rote-D
Pre-Training LiDAR-Based 3D Object Detectors Through Colorization
Accurate 3D object detection and understanding for self-driving cars heavily
relies on LiDAR point clouds, necessitating large amounts of labeled data to
train. In this work, we introduce an innovative pre-training approach, Grounded
Point Colorization (GPC), to bridge the gap between data and labels by teaching
the model to colorize LiDAR point clouds, equipping it with valuable semantic
cues. To tackle challenges arising from color variations and selection bias, we
incorporate color as "context" by providing ground-truth colors as hints during
colorization. Experimental results on the KITTI and Waymo datasets demonstrate
GPC's remarkable effectiveness. Even with limited labeled data, GPC
significantly improves fine-tuning performance; notably, on just 20% of the
KITTI dataset, GPC outperforms training from scratch with the entire dataset.
In sum, we introduce a fresh perspective on pre-training for 3D object
detection, aligning the objective with the model's intended role and ultimately
advancing the accuracy and efficiency of 3D object detection for autonomous
vehicles
Flexoelectricity-stabilized ferroelectric phase with enhanced reliability in ultrathin La:HfO2 films
Doped HfO2 thin films exhibit robust ferroelectric properties even for
nanometric thicknesses, are compatible with current Si technology and thus have
great potential for the revival of integrated ferroelectrics. Phase control and
reliability are core issues for their applications. Here we show that, in
(111)-oriented 5%La:HfO2 (HLO) epitaxial thin films deposited on
(La0.3Sr0.7)(Al0.65Ta0.35)O3 substrates, the flexoelectric effect, arising from
the strain gradient along the films normal, induces a rhombohedral distortion
in the otherwise Pca21 orthorhombic structure. Density functional calculations
reveal that the distorted structure is indeed more stable than the pure Pca21
structure, when applying an electric field mimicking the flexoelectric field.
This rhombohedral distortion greatly improves the fatigue endurance of HLO thin
films by further stabilizing the metastable ferroelectric phase against the
transition to the thermodynamically stable non-polar monoclinic phase during
repetitive cycling. Our results demonstrate that the flexoelectric effect,
though negligibly weak in bulk, is crucial to optimize the structure and
properties of doped HfO2 thin films with nanometric thicknesses for integrated
ferroelectric applications
DeepBouton: Automated Identification of Single-Neuron Axonal Boutons at the Brain-Wide Scale
Fine morphological reconstruction of individual neurons across the entire brain is essential for mapping brain circuits. Inference of presynaptic axonal boutons, as a key part of single-neuron fine reconstruction, is critical for interpreting the patterns of neural circuit wiring schemes. However, automated bouton identification remains challenging for current neuron reconstruction tools, as they focus mainly on neurite skeleton drawing and have difficulties accurately quantifying bouton morphology. Here, we developed an automated method for recognizing single-neuron axonal boutons in whole-brain fluorescence microscopy datasets. The method is based on deep convolutional neural networks and density-peak clustering. High-dimensional feature representations of bouton morphology can be learned adaptively through convolutional networks and used for bouton recognition and subtype classification. We demonstrate that the approach is effective for detecting single-neuron boutons at the brain-wide scale for both long-range pyramidal projection neurons and local interneurons
Genetics of osteopontin in patients with chronic kidney disease: The German chronic kidney disease study
Osteopontin (OPN), encoded by SPP1, is a phosphorylated glycoprotein predominantly synthesized in kidney tissue. Increased OPN mRNA and protein expression correlates with proteinuria, reduced creatinine clearance, and kidney fibrosis in animal models of kidney disease. But its genetic underpinnings are incompletely understood. We therefore conducted a genome-wide association study (GWAS) of OPN in a European chronic kidney disease (CKD) population. Using data from participants of the German Chronic Kidney Disease (GCKD) study (N = 4,897), a GWAS (minor allele frequency [MAF]>= 1%) and aggregated variant testing (AVT, MAFAuthor summaryOsteopontin (OPN) is involved in many (patho)physiological processes of the human body. Among others, it is known to be associated with adverse kidney outcomes. Since its genetic underpinnings are incompletely understood, we conducted a genome-wide association study of OPN in a European chronic kidney disease (CKD) population (N = 4,897). Of the three detected signals, two could be replicated within a population-based study of Finns. One locus is located upstream of SPP1 which encodes the OPN protein and is related to OPN production. This gene was also disclosed by an analysis of rare variants, all presumably effecting the gene product. Another locus maps into KLKB1 encoding prekallikrein (PK) that after processing to kallikrein (KAL) is implicated in blood pressure control and inflammation among others. Overall, our results highlight the multi-functional role of OPN and its possible pathological role in CKD. Further studies are needed to elucidate the complex role of OPN in humans.</p
An intermediate-effect size variant in UMOD confers risk for chronic kidney disease
The kidney-specific gene UMOD encodes for uromodulin, the most abundant protein excreted in normal urine. Rare large-effect variants in UMOD cause autosomal dominant tubulointerstitial kidney disease (ADTKD), while common low-impact variants strongly associate with kidney function and the risk of chronic kidney disease (CKD) in the general population. It is unknown whether intermediate-effect variants in UMOD contribute to CKD. Here, candidate intermediate-effect UMOD variants were identified using large-population and ADTKD cohorts. Biological and phenotypical effects were investigated using cell models, in silico simulations, patient samples, and international databases and biobanks. Eight UMOD missense variants reported in ADTKD are present in the Genome Aggregation Database (gnomAD), with minor allele frequency (MAF) ranging from 10(−5) to 10(−3). Among them, the missense variant p.Thr62Pro is detected in ∼1/1,000 individuals of European ancestry, shows incomplete penetrance but a high genetic load in familial clusters of CKD, and is associated with kidney failure in the 100,000 Genomes Project (odds ratio [OR] = 3.99 [1.84 to 8.98]) and the UK Biobank (OR = 4.12 [1.32 to 12.85). Compared with canonical ADTKD mutations, the p.Thr62Pro carriers displayed reduced disease severity, with slower progression of CKD and an intermediate reduction of urinary uromodulin levels, in line with an intermediate trafficking defect in vitro and modest induction of endoplasmic reticulum (ER) stress. Identification of an intermediate-effect UMOD variant completes the spectrum of UMOD-associated kidney diseases and provides insights into the mechanisms of ADTKD and the genetic architecture of CKD
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