The impact of the international construction standard application capability on contractors’ competitiveness: Chinese contractors’ experience

The application capability of international construction standards (ICS) has become a necessary element for the success of contractors in the international market. However, there is a lack of quantitative analysis of the impact of ICS application capability on contractors’ competitiveness. This paper aims to explore the driving paths between them. The authors divided the competitiveness indicators into market performance indicators and image performance indicators and developed a standard application capability measurement scale based on five dimensions (knowledge learning, talent guarantee, technical support, relationship management and organization guarantee). Then, a structural equation model (SEM), in which project performance was regarded as a mediator variable, was established to investigate the path and intensity of ICS application capability on contractors’ competitiveness. A questionnaire was distributed to the project personnel of Chinese contractors engaged in international projects, and 174 valid questionnaires were collected. The results show that 1) relationship management and technical support have a direct driving effect on the competitiveness of contractors; 2) talent guarantees and organization guarantees affect contractors’ competitiveness through project performance. This study can remind contractors of the importance of the ICS application capability and the weakness of ICS application. Additionally, it will ultimately help contractors adjust their competitiveness strategies

Integrative analysis of bioinformatics and machine learning to identify cuprotosis-related biomarkers and immunological characteristics in heart failure

BackgroundsCuprotosis is a newly discovered programmed cell death by modulating tricarboxylic acid cycle. Emerging evidence showed that cuprotosis-related genes (CRGs) are implicated in the occurrence and progression of multiple diseases. However, the mechanism of cuprotosis in heart failure (HF) has not been investigated yet.MethodsThe HF microarray datasets GSE16499, GSE26887, GSE42955, GSE57338, GSE76701, and GSE79962 were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed CRGs between HF patients and nonfailing donors (NFDs). Four machine learning models were used to identify key CRGs features for HF diagnosis. The expression profiles of key CRGs were further validated in a merged GEO external validation dataset and human samples through quantitative reverse-transcription polymerase chain reaction (qRT-PCR). In addition, Gene Ontology (GO) function enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and immune infiltration analysis were used to investigate potential biological functions of key CRGs.ResultsWe discovered nine differentially expressed CRGs in heart tissues from HF patients and NFDs. With the aid of four machine learning algorithms, we identified three indicators of cuprotosis (DLAT, SLC31A1, and DLST) in HF, which showed good diagnostic properties. In addition, their differential expression between HF patients and NFDs was confirmed through qRT-PCR. Moreover, the results of enrichment analyses and immune infiltration exhibited that these diagnostic markers of CRGs were strongly correlated to energy metabolism and immune activity.ConclusionsOur study discovered that cuprotosis was strongly related to the pathogenesis of HF, probably by regulating energy metabolism-associated and immune-associated signaling pathways

Noninvasive prenatal diagnosis of 21-Hydroxylase deficiency using target capture sequencing of maternal plasma DNA.

Here, we aimed to validate a noninvasive method using capture sequencing for prenatal diagnosis of congenital adrenal hyperplasia due to 21-Hydroxylase deficiency (21-OHD). Noninvasive prenatal diagnosis (NIPD) of 21-OHD was based on 14 plasma samples collected from 12 families, including four plasma sample collected during the first trimester. Targeted capture sequencing was performed using genomic DNA from the parents and child trios to determine the pathogenic and wild-type alleles associated with the haplotypes. Maternal plasma DNA was also sequenced to determine the fetal inheritance of the allele using hidden Markov model-based haplotype linkage analysis. The effect of fetal DNA fraction and sequencing depth on the accuracy of NIPD was investigated. The lower limit of fetal DNA fraction was 2% and the threshold mean sequence depth was 38, suggesting potential advantage if used in early gestation. The CYP21A2 genotype of the fetus was accurately determined in all the 14 plasma samples as early as day 1 and 8 weeks of gestation. Results suggest the accuracy and feasibility of NIPD of 21-OHD using a small target capture region with a low threshold for fetal DNA fraction and sequence depth. Our method is cost-effective and suggests diagnostic applications in clinical practice

Identifying Novel Copy Number Variants in Azoospermia Factor Regions and Evaluating Their Effects on Spermatogenic Impairment

Microdeletions in Y-chromosomal azoospermia factor (AZF) regions have been regarded as the risk factor of spermatogenic failure (SF). However, AZF-linked duplications or complex copy number variants (CNVs) (deletion + duplication) were rarely studied. In this study, we performed multiplex ligation-dependent probe amplification (MLPA) analysis on 402 fertile healthy male controls and 423 idiopathic infertile SF patients (197 azoospermia and 226 oligozoospermia) in Han Chinese population. In total, twenty-four types of AZF-linked CNVs were identified in our study, including eleven novel CNVs (one deletion, seven duplications, and three complex CNVs). Our study revealed that AZFc-linked duplications and the instability of Y chromosome might be associated with spermatogenesis. Besides, the complex CNVs (b2/b3 deletion + DAZ1/2 duplication) were confirmed to increase genetic risks for SF in Han Chinese population. This study illustrated a spectrum of AZF-linked CNVs and presented valuable information for understanding the clinical significance of AZF-linked CNVs in male infertility

Prenatal Diagnosis of Recurrent Distal 1q21.1 Duplication in Three Fetuses With Ultrasound Anomalies

Background: The phenotype of duplication of 1q21.1 region is variable, ranging from macrocephaly, autism spectrum disorder, congenital anomalies, to a normal phenotype. Few cases have been reported in the literature regarding prenatal diagnosis of 1q21.1 duplication syndrome. The current study presents prenatal diagnosis of 1q21.1 duplication syndrome in three fetuses with ultrasound anomalies.Case presentation: Three fetuses from three unrelated families were included in the study. The prenatal routine ultrasound examination showed nasal bone loss in Fetus 1 and Fetus 3, as well as duodenal atresia in Fetus 2. Chromosomal microarray analysis was performed to provide genetic analysis of amniotic fluid and parental blood samples. The CMA results revealed two de novo duplications of 1.34 and 2.69 Mb at distal 1q21.1 region in two fetuses with absent nasal bone, as well as a maternal inherited 1.35-Mb duplication at distal 1q21.1 in one fetus with duodenal atresia.Conclusions: The phenotype of 1q21.1 duplication syndrome in prenatal diagnosis is variable. The fetuses with nasal bone loss or duodenal atresia may be related to 1q21.1 duplication and chromosomal microarray analysis should be performed

SESAM mode-locked Tm:Y2O3 ceramic laser

We demonstrate a widely tunable and passively mode-locked Tm:Y2O3 ceramic laser in-band pumped by a 1627-nm Raman fiber laser. A tuning range of 318 nm, from 1833 to 2151 nm, is obtained in the continuous-wave regime. The SESAM mode-locked laser produces Fourier-transform-limited pulses as short as 75 fs at ∼ 2.06 µm with an average output power of 0.26 W at 86.3 MHz. For longer pulse durations of 178 fs, an average power of 0.59 W is achieved with a laser efficiency of 29%. This is, to the best of our knowledge, the first mode-locked Tm:Y2O3 laser in the femtosecond regime. The spectroscopic properties and laser performance confirm that Tm:Y2O3 transparent ceramics are a promising gain material for ultrafast lasers at 2 µm

Semi-supervised knowledge distillation framework for global-scale urban man-made object remote sensing mapping

Accurate mapping of global urban man-made objects such as buildings and roads is critical for monitoring urbanization. Remote sensing imagery provides a cost-effective way of mapping these objects, but the challenge of “knowledge forgetting” arises due to urban diversity and the continuous growth of global samples. Although the existing knowledge distillation approaches can transfer knowledge from a larger teacher model to a smaller student model by distilling the knowledge learned from reliable labels, they fail to work for global-scale mapping, which lies in two aspects: low-quality labeling and fixed-size models. In this paper, we propose GUMONet, which is a semi-supervised knowledge distillation framework for global-scale urban man-made object mapping. For the first phase, a label diversity progressive learning module is introduced for generating high-quality labels in a semi-supervised manner. Label diversity is used to measure the diverse urban patterns based on spatial-semantic uncertainty, where the diversified labels clustered in object boundaries and heterogeneous areas are attributed to high spatial uncertainty and semantic uncertainty, respectively. Based on the label diversity, the model decision boundary is progressively determined from coarse to fine. Specifically, at the early stage, instances away from the decision boundary are selected to ensure the stability of the model training. As the iteration progresses, instances close to the decision boundary are associated with a higher probability of further enhancing the quality of the uncertain labels by hard sample mining. For the second phase, a size-variable knowledge distillation module is adopted to optimize the data-model matching process. This module consists of a noise teacher model that prevents overfitting by injecting noise perturbations to increase the data distribution complexity and a size-variable student model that avoids underfitting by dynamically adjusting its size with the growth of global samples. We applied GUMONet to six study areas across four continents, with data from different sensors, achieving an 18.97% improvement in intersection over union, compared with the previous methods. Our results also demonstrate a positive correlation between urban development and urban diversity, with a correlation coefficient of 0.749. As urban development progresses, urban diversity stabilizes and building transformation becomes the primary means of promoting further development