Specific Defects Research Articles

Trajectory-User Linking via Multi-Scale Graph Attention Network

Trajectory-User Linking (TUL) aims to link anonymous trajectories to their owners, which is considered an essential task in discovering human mobility patterns. Although existing TUL studies have shown promising results, they still have specific defects in the perception of spatio-temporal properties of trajectories, which manifested in the following three problems: missing context of the original trajectory, ignorance of spatial information, and high computational complexity. To address those issues, we revisit the characteristics of the trajectory and propose a novel model called TULMGAT (TUL via Multi-Scale Graph Attention Network) based on masked self-attention graph neural networks. Specifically, TULMGAT consists of four components: construction of check-in oriented graphs, node embedding, trajectory embedding, and trajectory user linking. Sufficient experiments on two publicly available datasets have shown that TULMGAT is the state-of-the-art model in task TUL compared to the baselines with an improvement of about 8% in accuracy and only a quarter of the fastest baseline in runtime. Furthermore, model validity experiments have verified the role of each module.

Poly-ADP-ribosylation dynamics, signaling, and analysis.

ADP-ribosylation is a reversible post-translational modification that plays a role as a signaling mechanism in various cellular processes. This modification is characterized by its structural diversity, highly dynamic nature, and short half-life. Hence, it is tightly regulated at many levels by cellular factors that fine-tune its formation, downstream signaling, and degradation that together impacts cellular outcomes. Poly-ADP-ribosylation is an essential signaling mechanism in the DNA damage response that mediates the recruitment of DNA repair factors to sites of DNA damage via their poly-ADP-ribose (PAR)-binding domains (PBDs). PAR readers, encoding PBDs, convey the PAR signal to mediate cellular outcomes that in some cases can be dictated by PAR structural diversity. Several PBD families have been identified, each with variable PAR-binding affinity and specificity, that also recognize and bind to distinct parts of the PAR chain. PARylation signaling has emerged as an attractive target for the treatment of specific cancer types, as the inhibition of PAR formation or degradation can selectively eliminate cancer cells with specific DNA repair defects and can enhance radiation or chemotherapy response. In this review, we summarize the key players of poly-ADP-ribosylation and its regulation and highlight PBDs as tools for studying PARylation dynamics and the expanding potential to target PARylation signaling in cancer treatment.

Optimized Gabor Filter Banks and Autoencoder Models for Enhanced Knitted Fabric Defect Detection

There is a high need for an automated system to detect fabric defects, as the current manual methods used in the garment industries in Nepal are unreliable and costly. Previous research has focused on specific fabric defects rather than overall fabric defects efficiently. This research employs two autoencoder models to identify different defects across different types of knitted fabrics, utilizing two datasets: the SFDG dataset and a custom dataset prepared from Butwal’s garment industries. The models benefit from a carefully designed Gabor filter bank to examine fabric compositions. This filter bank is fine-tuned by modifying parameters, wavelength, and orientation to detect varieties of defects in knitted fabrics. These models get feature representations from the Gabor filter bank’s outputs and help the system adapt to different types of defect patterns, making defect detection more reliable and accurate. The nearest neighbor density estimator finds possible defects and marks on the fabric images. The model's effectiveness and strength are shown by validating it on different types of knitted fabrics, including plain and patterned fabrics, using evaluation metrices like cTPR and ROC AUC. The first model achieves a cTPR of 0.879 and an AUC score of 0.947, while the second model achieves a cTPR of 0.899 and an AUC score of 0.958.

Facial Artery Perforator Flap for Perioral and Perinasal Oncologic Defect Reconstruction: Surgical Technique and Postoperative Outcomes.

Facial artery perforator (FAP) flap is a versatile and reliable one-step facial reconstruction technique. However, its full potential remains underutilized due to a lack of clear guidelines and rigorous technique requirements. This study report the use of FAP flaps in our centre for the management of perioral and nasal oncologic defects, focusing on surgical technique performed and post-operative management. We conducted a retrospective review of all patients who underwent reconstruction with a perioral or perinasal FAP flap only following tumor resection over a 4-year period (n = 29). Parameters measured included flap survival, complication rates, surgical technique performed, and the need for touch-up procedures. Patients were grouped based on age, defect size, and location and outcomes were compared across these groups. The mean histological tumor defect area was 331 mm2. During at least 6 months of follow-up, no local recurrence was observed. Twenty-seven (93.1%) flaps survived completely. Major postsurgical complications occurred in seven (23.8%) patients, including complete flap necrosis (1), partial flap necrosis (1), flap collapse (1), venous congestion (1), wound dehiscence (1), and local infection (2). A higher complication rate was associated with nose tip defects (80.0% vs. 12.5%, p = 0.007). Touch-up procedures were more frequently required for reconstructions involving the nasal sidewall and dorsum (53.8% vs. 13.3%, p = 0.04). Based on our experience, the FAP flap is highly effective for the reconstruction of the upper lip, nasolabial fold, and certain oncologic nasal defects. However, specific defect locations, such as the nose tip, may be associated with higher complication rates, necessitating careful patient selection and surgical planning.

Transformer-based models application for bug detection in source code

This paper explores the use of transformer-based models for bug detection in source code, aiming to better understand the capacity of these models to learn complex patterns and relationships within the code. Traditional static analysis tools are highly limited in their ability to detect semantic errors, resulting in numerous defects passing through to the code execution stage. This research represents a step towards enhancing static code analysis using neural networks. The experiments were designed as binary classification tasks to detect buggy code snippets, each targeting a specific defect type such as NameError, TypeError, IndexError, AttributeError, ValueError, EOFError, SyntaxError, and ModuleNotFoundError. Utilizing the «RunBugRun» dataset, which relies on code execution results, the models – BERT, CodeBERT, GPT-2, and CodeT5 – were fine-tuned and compared under identical conditions and hyperparameters. Performance was evaluated using F1-Score, Precision, and Recall. The results indicated that transformer-based models, especially CodeT5 and CodeBERT, were effective in identifying various defects, demonstrating their ability to learn complex code patterns. However, performance varied by defect type, with some defects like IndexError and TypeError being more challenging to detect. The outcomes underscore the importance of high-quality, diverse training data and highlight the potential of transformer-based models to achieve more accurate early defect detection. Future research should further explore advanced transformer architectures for detecting complicated defects, and investigate the integration of additional contextual information to the detection process. This study highlights the potential of modern machine learning architectures to advance software engineering practices, leading to more efficient and reliable software development.

Highly active nitrogen-doped biochar for catalytic reduction of 4-nitrophenol: Kinetic, thermodynamic and mechanism investigation

Biomass derived metal-free carbon catalysts are urgently needed in wastewater remediation and organic transformation, due to their environmental friendliness, low cost. In this respect, a series of nitrogen-doped hierarchically porous carbons (NHPCs) derived from cheap and abundant eggplant were fabricated via a one-pot strategy under different temperatures from 600 to 900°C, and employed as metal-free catalysts for the reduction of aromatic nitrophenols. Benefiting from the synergistic effects of the hierarchically porous structure, large specific surface area and abundant structural defects, NHPCs obtained from 800 °C has the highest reduction rate of 2.072 min−1 and maximal turnover frequency (TOF) for 4-nitrophenol of 1.23 × 10−2 mM·mg−1·min−1, which is superior to most of the reported metal-free catalysts. In addition, the NHPC-800 also exhibits satisfactory practicality and universality. The kinetic and thermodynamic studies were also conducted, finding that the obtained kinetics data over NHPC-800 fit well to L-H model with a low apparent activation energy (Ea = 18.96 kJ·mol−1). Furthermore, the mechanism was also elucidated by experimental investigation and theoretical calculations, which revealed that the pore creation and doping nitrogen can promote the adsorption of 4-NP and NaBH4 onto NHPC. This study make a significant contribution to the advancement of catalytic reduction of 4-NP by N-doped biochar catalysts.

Neuregulin1 Nuclear Signaling Influences Adult Neurogenesis and Regulates a Schizophrenia Susceptibility Gene Network within the Mouse Dentate Gyrus.

Neuregulin1 (Nrg1) signaling is critical for neuronal development and function from fate specification to synaptic plasticity. Type III Nrg1 is a synaptic protein which engages in bidirectional signaling with its receptor ErbB4. Forward signaling engages ErbB4 phosphorylation, whereas back signaling engages two known mechanisms: (1) local axonal PI3K-AKT signaling and (2) cleavage by γ-secretase resulting in cytosolic release of the intracellular domain (ICD), which can traffic to the nucleus (Bao et al., 2003; Hancock et al., 2008). To dissect the contribution of these alternate signaling strategies to neuronal development, we generated a transgenic mouse with a missense mutation (V321L) in the Nrg1 transmembrane domain that disrupts nuclear back signaling with minimal effects on forward signaling or local back signaling and was previously found to be associated with psychosis (Walss-Bass et al., 2006). We combined RNA sequencing, retroviral fate mapping of neural stem cells, behavioral analyses, and various network analyses of transcriptomic data to investigate the effect of disrupting Nrg1 nuclear back signaling in the dentate gyrus (DG) of male and female mice. The V321L mutation impairs nuclear translocation of the Nrg1 ICD and alters gene expression in the DG. V321L mice show reduced stem cell proliferation, altered cell cycle dynamics, fate specification defects, and dendritic dysmorphogenesis. Orthologs of known schizophrenia (SCZ)-susceptibility genes were dysregulated in the V321L DG. These genes coordinated a larger network with other dysregulated genes. Weighted gene correlation network analysis and protein interaction network analyses revealed striking similarity between DG transcriptomes of V321L mouse and humans with SCZ.

Algorithm for the Treatment ofTip Malformation Combining a Clinical Qualitative Assessment and Specific Closed-Rhinoplasty Techniques Based on Retrospective Analysis of Pellegrini's Fellows 40 Years' Experience.

The aesthetic importance of nasal tip and the complexity of its surgical correction make the surgery of this area one of the most fascinating facial surgical procedures. Despite description of different sculpturing techniques to correct nasal tip defects, this surgery remains one of the most discussed and challenging aesthetic procedures. The objective of this study was to define an algorithm of treatment for nasal tip surgery based on 40-year experience on Caucasian patients evaluated by our proposed clinical qualitative assessment, who were treated by closed rhinoplasty. We retrospectively reviewed 19,643 Caucasian patients (15,266 females and 4,377 males) who underwent primary closed rhinoplasty from 1979 to 2019 due to different tip defects. The patients were evaluated by volume projection rotation (VPR) assessment. The surgical indications options, long-term aesthetic results and complications were analysed. 22% patients with minimal nasal defects were treated by non-delivery approach and 78% patients with important tip malformation by delivery approach. In all cases, the surgery was performed to reduce tip volume and modify tip projection and rotation based on the specific nasal defects. 67% patients, who needed important reduction of tip projection, were treated by tip-interrupting techniques. 88.7% patientsdeclared full satisfaction after surgery,and only 12.3% needed a requiring minor revision surgery during the 20 years follow-up. The proposed algorithm may be a useful tool to plan surgery. The use of an adequate technique depending on the evaluation of volume, projection and rotation may guarantee higher patients satisfaction and a stable long-term aesthetic result. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Fracture mechanics of bi-material lattice metamaterials

The advent of additive manufacturing technology empowers precise control of multi-material components or specific defects in lightweight lattice metamaterials, however, fracture mechanics and toughening design strategies in such metamaterials remain enigmatic. By incorporating theoretical analysis, numerical simulation, and experimental investigation, our study reveals that stretch-bend synergistic strut deformations caused by bi-material components or topology defects contribute notably tougher lattice structures surpassing its ideal single-material lattices. A peak fracture energy at a critical modulus ratio was found in a designed bi-material lattice composed of triangular soft struts and hexagonal stiff struts, which originates from the shift of fracture modes at crack tip from strut bending to stretching dominated failure modes as the modulus of soft struts increases, where the compromise in competition between bending-enhanced and stretching-weakened energy dissipations of struts deformations results in the maximized fracture energy. A parametric design protocol was proposed to optimize fracture energy of bi-material lattices through tuning the modulus ratio and relative density. Furthermore, the concept of stretch-bend synergistic toughening can also be applied to make tougher single-material lattices with specific topological defects. Our findings not only provide physical insights into directing crack propagation but also provide quantitative guidance to optimize fracture resistance within low-density tough lattice metamaterials.

AUTS2 disruption causes neuronal differentiation defects in human cerebral organoids through hyperactivation of the WNT/β-catenin pathway

Individuals with the Autism Susceptibility Candidate 2 (AUTS2) gene disruptions exhibit symptoms such as intellectual disability, microcephaly, growth retardation, and distinct skeletal and facial differences. The role of AUTS2 in neurodevelopment has been investigated using animal and embryonic stem cell models. However, the precise molecular mechanisms of how AUTS2 influences neurodevelopment, particularly in humans, are not thoroughly understood. Our study employed a 3D human cerebral organoid culture system, in combination with genetic, genomic, cellular, and molecular approaches, to investigate how AUTS2 impacts neurodevelopment through cellular signaling pathways. We used CRISPR/Cas9 technology to create AUTS2-deficient human embryonic stem cells and then generated cerebral organoids with these cells. Our transcriptomic analyses revealed that the absence of AUTS2 in cerebral organoids reduces the populations of cells committed to the neuronal lineage, resulting in an overabundance of cells with a transcription profile resembling that of choroid plexus (ChP) cells. Intriguingly, we found that AUTS2 negatively regulates the WNT/β-catenin signaling pathway, evidenced by its overactivation in AUTS2-deficient cerebral organoids and in luciferase reporter cells lacking AUTS2. Importantly, treating the AUTS2-deficient cerebral organoids with a WNT inhibitor reversed the overexpression of ChP genes and increased the downregulated neuronal gene expression. This study offers new insights into the role of AUTS2 in neurodevelopment and suggests potential targeted therapies for neurodevelopmental disorders.

Atomic and Electronic Structure of Defects in hBN: Enhancing Single-Defect Functionalities.

Defect centers in insulators play a critical role in creating important functionalities in materials: prototype qubits, single-photon sources, magnetic field probes, and pressure sensors. These functionalities are highly dependent on their midgap electronic structure and orbital/spin wave function contributions. However, in most cases, these fundamental properties remain unknown or speculative due to the defects being deeply embedded beneath the surface of highly resistive host crystals, thus impeding access through surface probes. Here, we directly inspected the atomic and electronic structures of defects in thin carbon-doped hexagonal boron nitride (hBN:C) by using scanning tunneling microscopy (STM) and scanning tunneling spectroscopy (STS). Such investigation adds direct information about the electronic midgap states to the well-established photoluminescence response (including single-photon emission) of intentionally created carbon defects in the most commonly investigated van der Waals insulator. Our joint atomic-scale experimental and theoretical investigations reveal two main categories of defects: (1) single-site defects manifesting as donor-like states with atomically resolved structures observable via STM and (2) multisite defect complexes exhibiting a ladder of empty and occupied midgap states characterized by distinct spatial geometries. Combining direct probing of midgap states through tunneling spectroscopy with the inspection of the optical response of insulators hosting specific defect structures holds promise for creating and enhancing functionalities realized with individual defects in the quantum limit. These findings underscore not only the versatility of hBN:C as a platform for quantum defect engineering but also its potential to drive advancements in atomic-scale optoelectronics.

Mechanoresponsive regulation of myogenesis by the force-sensing transcriptional regulator Tono

Muscle morphogenesis is a multi-step program, starting with myoblast fusion, followed by myotube-tendon attachment and sarcomere assembly, with subsequent sarcomere maturation, mitochondrial amplification, and specialization. The correct chronological order of these steps requires precise control of the transcriptional regulators and their effectors. How this regulation is achieved during muscle development is not well understood. In a genome-wide RNAi screen in Drosophila, we identified the BTB-zinc-finger protein Tono (CG32121) as a muscle-specific transcriptional regulator. tono mutant flight muscles display severe deficits in mitochondria and sarcomere maturation, resulting in uncontrolled contractile forces causing muscle rupture and degeneration during development. Tono protein is expressed during sarcomere maturation and localizes in distinct condensates in flight muscle nuclei. Interestingly, internal pressure exerted by the maturing sarcomeres deforms the muscle nuclei into elongated shapes and changes the Tono condensates, suggesting that Tono senses the mechanical status of the muscle cells. Indeed, external mechanical pressure on the muscles triggers rapid liquid-liquid phase separation of Tono utilizing its BTB domain. Thus, we propose that Tono senses high mechanical pressure to adapt muscle transcription, specifically at the sarcomere maturation stages. Consistently, tono mutant muscles display specific defects in a transcriptional switch that represses early muscle differentiation genes and boosts late ones. We hypothesize that a similar mechano-responsive regulation mechanism may control the activity of related BTB-zinc-finger proteins that, if mutated, can result in uncontrolled force production in human muscle.

Identification of biomarkers for COVID-19 associated secondary hemophagocytic lymphohistiocytosis.

We aimed to define and validate novel biomarkers that could identify individuals with COVID-19 associated secondary hemophagocytic lymphohistiocytosis (sHLH) and to test whether fatalities due to COVID-19 in the presence of sHLH were associated with specific defects in the immune system. In two cohorts of adult patients presenting with COVID-19 in 2020 and 2021, clinical lab values and serum proteomics were assessed. Subjects identified as having sHLH were compared to those with COVID-19 without sHLH. Eight deceased patients defined as COVID-sHLH underwent genomic sequencing in order to identify variants in immune-related genes. Two tertiary care hospitals in Seattle, Washington (Virginia Mason Medical Center and Harborview Medical Center). 186 patients with COVID-19. None. Nine percent of enrolled COVID-19 subjects met our defined criteria for sHLH. Using broad serum proteomic approaches (O-link and SomaScan), we identified three biomarkers for COVID-19 associated sHLH (soluble PD-L1, TNF-R1, and IL-18BP), supporting a role for proteins previously associated with other forms of sHLH (IL-18BP and sTNF-R1). We also identified novel biomarkers and pathways of COVID-sHLH, including sPD-L1 and the syntaxin pathway. We detected variants in several genes involved in immune responses in individuals with COVID-sHLH, including in DOCK8 and in TMPRSS15, suggesting that genetic alterations in immune-related genes may contribute to hyperinflammation and fatal outcomes in COVID-19. Biomarkers of COVID-19 associated sHLH, such as soluble PD-L1, and pathways, such as the syntaxin pathway, and variants in immune genes in these individuals, suggest critical roles for the immune response in driving sHLH in the context of COVID-19.

Copper overload exacerbates testicular aging mediated by lncRNA:CR43306 deficiency through ferroptosis in Drosophila

Testicular aging manifests as impaired spermatogenesis and morphological alterations in Drosophila. Nonetheless, the comprehensive molecular regulatory framework remains largely undisclosed. This investigation illustrates the impact of copper overload on testicular aging and underscores the interplay between copper overload and lncRNA. Copper overload triggers Cuproptosis through the mitochondrial TCA cycle, facilitating intracellular interactions with Ferroptosis, thereby governing testicular aging. Dysfunction of lncRNA:CR43306 also contributes to testicular aging in Drosophila, emphasizing the significance of lncRNA:CR43306 as a novel aging-associated lncRNA. Moreover, copper overload exacerbates spermatid differentiation defects mediated by lncRNA:CR43306 deficiency through oxidative stress, copper, and iron transport. Therapeutically, Ferrostatin-1 and Resveratrol emerge as potential remedies for addressing testicular aging. This study offers perspectives on the regulatory mechanisms involving copper overload and lncRNA:CR43306 deficiency in the context of testicular aging.

Similarity searching for wafer bin maps by measuring shape, location, and size similarities of defect patterns

A wafer bin map (WBM) is a visual representation of the spatial distribution of defective chips on a wafer. WBMs showing specific defect patterns are usually a result of process-assignable causes; thus, it is important to identify them to eliminate assignable causes. With advances in semiconductor manufacturing technology, identifying new defect patterns, and diagnosing their causes have become critical. However, most existing methods for WBM analysis use a supervised learning approach, which only detects previously known defect patterns. The similarity-search approach is a suitable alternative for defining new defect patterns. The proposed method uses an unsupervised approach to search for similar WBMs by measuring the similarities of three spatial features of defect patterns–shape, location, and size–which are useful for defining new defect patterns and diagnosing their causes. These three similarities are achieved using tensor voting and the mountain function for shape similarity, Euclidean distance for location similarity, and a combination of defect count and average radius for size similarity. The overall similarity was assessed using the weighted average of the three similarities. The weights are determined by quantifying the uncertainty of each similarity based on information entropy theory to better distinguish between similar patterns. The experimental results demonstrate the effectiveness of the proposed method compared to existing methods and highlight its capability to identify and describe the spatial features of defect patterns.

Gata6 functions in zebrafish endoderm to regulate late differentiating arterial pole cardiogenesis.

Mutations in GATA6 are associated with congenital heart disease, most notably conotruncal structural defects. However, how GATA6 regulates cardiac morphology during embryogenesis is undefined. We used knockout and conditional mutant zebrafish alleles to investigate the spatiotemporal role of gata6 during cardiogenesis. Loss of gata6 specifically impacts atrioventricular valve formation and recruitment of epicardium, with a prominent loss of arterial pole cardiac cells, including those of the ventricle and outflow tract. However, there are no obvious defects in cardiac progenitor cell specification, proliferation or death. Conditional loss of gata6 starting at 24 h is sufficient to disrupt the addition of late differentiating cardiomyocytes at the arterial pole, with decreased expression levels of anterior secondary heart field (SHF) markers spry4 and mef2cb. Conditional loss of gata6 in the endoderm is sufficient to phenocopy the straight knockout, resulting in a significant loss of ventricular and outflow tract tissue. Exposure to a Dusp6 inhibitor largely rescues the loss of ventricular cells in gata6-/- larvae. Thus, gata6 functions in endoderm are mediated by FGF signaling to regulate the addition of anterior SHF progenitor derivatives during heart formation.

Study on the Impact of Pole Spacing on Magnetic Flux Leakage Detection under Oversaturated Magnetization.

Magnetic flux leakage (MFL) inspection employs leakage magnetic fields to effectively detect and locate pipeline defects. The spacing between magnetic poles significantly affects the leakage magnetic field strength. While most detectors typically opt for moderate pole spacing for routine detection, this study investigates the propagation characteristics of MFL signals at small pole spacings (under specimen oversaturated magnetization) and their impact on MFL detection. Through finite element simulation and experiments, it reveals a new signal phenomenon in the radial MFL signal By at small pole spacings, the double peak-valley (DPV) phenomenon, characterized by outer and inner peaks and valleys. Theoretical analysis based on the simulation results elucidates the mechanisms for this DPV phenomenon. Based on this, the impact of defect size, pipe wall thickness, and magnetic pole and rigid brush height on MFL signals under small magnetic pole spacings is examined. It is demonstrated that, under a smaller magnetic pole spacing, a potent background magnetic field manifests in the air above the defect. This DPV phenomenon is generated by the magnetic diffusion and compression interactions between the background and defect leakage magnetic fields. Notably, the intensity of the background magnetic field can be mitigated by reducing the height of the rigid brush. In contrast, the pipe wall thickness and magnetic pole height exhibit a negligible influence on the DPV phenomenon. The emergence of the DPV precipitates a reduction in the peak-to-valley difference within the MFL signal, constricting the depth range of detectable defects. However, the presence of DPV increases the identification of defects with smaller opening sizes. These findings reveal the characterization of the MFL signal under small pole spacing, offering a preliminary study on identifying specific defects using unconventional signals. This study provides valuable guidance for MFL detection.

Dominant-negative chaperonin mutation ptCPN60α1S57F uncovers redundancy in chloroplast rRNA processing.

The biogenesis of functional forms of chloroplast ribosomal RNAs (rRNAs) is crucial for the translation of chloroplast mRNAs into polypeptides. However, the molecular mechanisms underlying the proper processing and maturation of chloroplast rRNA species are poorly understood. Through a genetic approach, we isolated and characterized an Arabidopsis mutant, α1-4, harboring a missense mutation in the plastid chaperonin-60α1 gene. Using allelism tests and transgenic manipulation, we determined functional redundancy among ptCPN60 subunits. The ptCPN60α1S57F mutation caused specific defects in the formation of chloroplast rRNA species, including 23S, 5S, and 4.5S rRNAs, but not 16S rRNAs. Allelism tests suggested that the dysfunctional ptCPN60α1S57F competes with other members of the ptCPN60 family. Indeed, overexpression of the ptCPN60α1S57F protein in wild-type plants mimicked the phenotypes observed in the α1-4 mutant, while increasing the endogenous transcriptional levels of ptCPN60α2, β1, β2, and β3 in the α1-4 mutant partially mitigated the abnormal fragmentation processing of chloroplast 23S, 5S, and 4.5S rRNAs. Furthermore, we demonstrated functional redundancy between ptCPN60β1 and ptCPN60β2 in chloroplast rRNA processing through double-mutant analysis. Collectively, our data reveal a novel physiological role of ptCPN60 subunits in generating the functional rRNA species of the large 50S ribosomal subunit in Arabidopsis chloroplasts.

Maternal exposure to ambient temperature and birth defects in Brazil: a nationwide case-control study of over 11 million newborns.

Maternal exposure to extreme ambient temperature during pregnancy has been proposed as a potential risk factor for birth defects. Comprehensive investigations on this association remain limited, particularly in low- and middle-income countries. This study aims to examine the association between ambient temperature exposure during pregnancy and the risk of birth defects in Brazil, contributing to the broader understanding of environmental influences on birth outcomes. Using a large dataset of over 11 million live birth records, we analyzed 12 categories of birth defects, encompassing a time frame from 2001 to 2018. Ambient temperature data were assigned at the municipality level. For the exposure assessment, we considered two biologically driven pregnancy stages by dividing the gestational period into two specific windows: the first trimester (from week 1 to week 12) and the second trimester (from week 13 to week 28). We employed a two-stage case-control design. In the first stage, we applied a conditional logistic regression model to estimate the odds ratio (OR) for specific birth defects and each of the five Brazilian regions (North, Northeast, Midwest, Southeast, and South). The model was adjusted for potential confounding variables, including PM2.5, relative humidity, and socioeconomic status. Temporal trends were addressed using time-stratified sampling. In the second stage, we used mixed-effects meta-analysis to pool region-specific estimates. Our analysis revealed a significant association between maternal exposure to higher ambient temperatures during the first trimester and an increased risk of specific birth defect categories, including those affecting the genital organs (OR = 1.08, 95% CI: 1.02; 1.14), digestive system (OR = 1.12, 95% CI: 1.06; 1.19); circulatory system (OR = 1.08, 95% CI: 1.01; 1.17); eyes, ears, face, and neck (OR = 1.08, 95% CI: 1.02; 1.15); benign neoplasms tumors (OR = 1.17, 95% CI: 1.03; 1.32), musculoskeletal system (OR = 1.03, 95% CI: 1.01; 1.05); and other congenital anomalies (OR = 1.22, 95% CI: 1.15; 1.29). The associations with respiratory system, nervous system, and chromosomal anomalies were null. These findings have significant implications for public health policies aimed at mitigating the impact of environmental factors on birth outcomes, both in Brazil and globally.

Model for the Failure Prediction Mechanism of In-Service Pipelines Based on IoT Technology

With the rapid increase in pipeline mileage in China, the accurate prediction of corrosion issues in in-service pipelines has become crucial for ensuring safe pipeline operation. Traditional pipeline leakage monitoring methods are significantly limited by human factors and equipment precision, making it challenging to predict and identify leakage points accurately. Therefore, aligned with the trend of intelligent pipeline development, this study aims to construct a failure pressure prediction mechanism model for corroded pipelines based on IoT technology. This model leverages intelligent sensing and prediction to assess the safety status of corroded pipeline sections. Ultrasonic phased array technology detects specific corrosion points and detailed defect parameters within pipeline sections. The parameters are then utilized in the Simdroid domestic finite element analysis model to simulate the ultimate burst pressure of the pipeline. A single-variable approach is employed to analyze the sensitivity of different parameters to the pipeline’s ultimate burst pressure, with the minimum burst pressure point of multi-point corroded sections selected as the overall segment failure pressure. Finite element simulation data are integrated into a neural network database to predict the pipeline failure pressure. The real-time operational data of the pipeline are monitored using negative-pressure wave sensing. The operational pressure of the corroded points is compared with the algorithm-predicted failure pressure; if the values approach a critical threshold, an alarm is triggered. Moreover, the remote control terminals evaluate the pipeline’s self-rescue time, providing a buffer for pipeline leakage self-rescue. The failure prediction mechanism model for in-service pipelines was applied to the Fujian–Guangdong branch of the West–East Gas Pipeline III to verify its accuracy and feasibility. The research results offer technical support for the maintenance and emergency repair of pipeline leakage scenarios, leveraging intelligent pipeline technology to reduce costs and increase the efficiency of pipeline operations, thereby supporting the sustainable development of China’s oil and gas pipelines with theoretical and technical backing.