Overt hyperthyroidism during pregnancy is associated with risk of maternal-fetal complications. The antithyroid drugs (ATD) have a potential risk for teratogenic effects and fetal–neonatal hy-pothyroidism. This study evaluated ATD treatment and thyroid function control during preg-nancy, and pregnancy outcome in women with hyperthyroidism. Patients and methods: retro-spective analysis of 36 single fetus pregnancies in 29 consecutive women (median age 30.3 ± 4.7 years) with hyperthyroidism diagnosed before or during pregnancy; a control group of 39 healthy euthyroid pregnant women was used. Results: 26 women had Graves’ disease (GD, 33 pregnan-cies), 1 had a hyperfunctioning autonomous nodule, 2 had gestational transient thyrotoxicosis (GTT). Methimazole (MMI) was administered in 22 pregnancies (78.5%), Propylthiouracil (PTU) in 2 (7.1%), switch from MMI to PTU in 4 (14.2%), no treatment in 8 pregnancies (3 with subclinical hyperthyroidism, 5 euthyroid with previous GD remission before conception). One spontaneous abortion at 5 weeks (3.4% of pregnancies) and 1 premature delivery at 32 weeks with perinatal death in 24h (3.4%) were recorded in 2 of the 8 pregnancies of GD patients diagnosed shortly before (< 6 weeks) or during gestation. In women treated more than 6 months until conception (20 pregnancies): a) median ATD doses were lower than those in women diagnosed shortly before or during pregnancy; b) ATD was withdrawn in 40% of pregnancies in trimester (T) I, all on MMI < 10 mg/day (relapse in 14.2%), and in up to 55% in TIII; c) TSH level was below normal in 37%, 35% and 22% of pregnancies in T I, II and III respectively; FT4 was increased in 5.8% (T I) and sub-normal in 11.75% in TII and III; d) one fetal death due to a true umbilical cord knot was recorded. Hyperthyroidism relapsed postpartum in 83% of GD patients (at median 3 ± 2.6 months). One child had neonatal hyperthyroidism (3.3% of live children in GD women) and a small atrial sept defect (4% of live children in ATD treated women). Mean birth weight did not differ from that of the control group. Conclusion. In hyperthyroid women with long-term ATD control before con-ception, drugs could be withdrawn in TI in a third of them, and fetal complications were rare. Frequent serum TSH and FT4 monitoring is needed in order to maintain optimal thyroid function during pregnancy.

Urban trees are often more sun- and wind-exposed than their forest-grown counterparts. These environmental differences can impact how many species grow – impacting trunk taper, crown spread, branch architecture, and other aspects of tree form. Given these differences, windthrow models derived from traditional forest production data sources may not be appropriate for urban forest management. Additionally, visual abnormalities historically labeled as “defects” in timber production may not have a significant impact on tree failure potential. In this study, we look at urban tree failures associated with Hurricane Irma in Tampa, Florida, USA. We used spatial analysis to determine if patterns of failure existed among our inventoried trees. We also looked at risk assessment data to determine which visual defects were the most common and the most likely to be associated with branch or whole-tree failure. Results indicate that there was no spatial pattern associated with the observed tree failures – trees failed or withstood the storm as individuals. While some defects like decay and dead wood were associated with increased tree failure, other defects like weak branch unions and poor branch architecture were less problematic.

Tissue engineering and regenerative medicine has gradually evolved as a promising therapeutic strategy to the modern healthcare of the aging and diseased population. In this study, we developed a novel nano-fibrous scaffold and verified its application in the critical bone defect regeneration. The metformin-incorporated nano-gelatin/hydroxyapatite fibers (NGF) was produced by electrospinning, cross-linked, and then characterized by XRD and FTIR. Cytotoxicity, cells adhesion, cell differentiation, and quantitative osteogenic gene and protein expression were analyzed by bone marrow stem cells from rat. Rat forearm critical bone defect model was performed for the in vivo study. The nano-gelatin/hydroxyapatite fibers (NGF) were characterized by their porous structures with proper interconnectivity without significant cytotoxic effects; the adhesion of bone marrow stem cells on the nano-gelatin/hydroxyapatite fibers (NGF) could be enhanced. The osteogenic gene and protein expression were upregulated. Post implantation, the new regenerated bone in bone defect was well demonstrated in the NGF samples. We demonstrated that the metformin-incorporated nano-gelatin-hydroxyapatite fibers greatly improved healing potential on the critical sized bone defect. Although metformin-incorporated nano-gelatin/hydroxyapatite fibers had advantageous effectiveness during bone regeneration, further validation is required before it can be applied to clinical applications.

Electromagnetic sensors have been used for inspecting small surface defects of metals. Based on the eddy-current thin-skin regime, a revised algorithm is proposed for a triple-coil drive-pickup eddy-current sensor scanning over long surface crack slots (10 mm) with different rotary angles. The method is validated by the voltage measurement of the designed EC sensor scanning over a benchmark (ferromagnetic) steel with surface defects of different depths and rotary angles. With an additional sensing coil for the designed EC sensor, the defect angle (or orientation) can be measured without spatially and coaxially rotating the excitation coil. By referring to the voltage change (due to the defect) diagram (voltage sum versus voltage different) of two sensing pairs, the rotary angle of the surface crack is retrieved with a maximum residual deviation of 3.5 %.

This is a single tertiary center in southwest Romania, population-based, study. We retrospectively compared data obtained in two periods: January 2008 - December 2013 and January 2018 - De-cember 2023, respectively. The global incidence of transposition of great arteries (TGA) - the ter-minated cases added to the ones resulting in live-born pregnancies, remained almost constant. The live-born incidence of TGA decreased (0.34% to 0.013%). The prenatal detection rate increased slightly (71.42% to 87.5%). The median gestational age at the diagnosis decreased, from 29.3 ges-tational weeks (mean 25.4) to 13.4 weeks (mean 17.2). The proportion of terminated pregnancies significantly increased (14.28% to 75%, p = 0.019).

Preterm infants have increased body adiposity at term equivalent age and risk for adverse metabolic outcomes. The aim of the study was to define how nutrient intake may impact body composition (BC) of very low birth weight infants fed with early progressive enteral feeding and standard fortification. Eighty-six infants with

This paper presents a groundbreaking approach to real-time image processing in electronic component assembly, enhancing quality control in manufacturing. By capturing images from pick and place machines between component pickup and mounting, defects are identified and addressed in-line, significantly reducing the likelihood of defective products. Leveraging fast network protocols like gRPC and orchestration with Kubernetes, along with C++ programming and TensorFlow, this method achieves an average turnaround time of less than 5 milliseconds. Tested on 20 live production machines, it ensures compliance with IPC-A-610, and IPC-STD-J-001 standards while optimizing production efficiency and reliability.

Single crystals of quaternary adamantine type Cu•GaGeS4 were grown by chemical vapor transport technique using iodine as transport agent. Dark red transparent crystals grew in a temperature gradient of dT = 900–750 °C. Chemical characterization by X-ray fluorescence showed an off-stoichiometric composition of the Cu•GaGeS4 crystals, in particular a slight Ge-deficit. By X-ray diffraction, Cu•GaGeS4 was found to adopt the chalcopyrite-type structure with the space group I-42d. The cation distribution in this structure was analyzed by multiple energy anomalous synchrotron X-ray diffraction and it was found that Cu and vacancies occupy the 4a site, whereas Ga and Ge occupy the 4b site. The band gap energies of several off-stoichiometric Cu•GaGeS4 crystals were determined by UV-Vis spectroscopy and are in the range of 2.1 to 2.4 eV. A non-linear correlation of the band gap energy with the Ge-content of the compound follows the usual bowing behaviour of semiconductor alloys with a bowing parameter of b = 1.45(0.08).

Large volume bone defect regeneration is complex and demands time to complete. Several regeneration phases with unique characteristics including immune responses follow, overlap, and interdepend on each other and, if successful, lead to the regeneration of the organ bone's form and function. However, during traumatic, infectious, or neoplastic clinical cases, the intrinsic bone regeneration capacity may exceed, and surgical intervention is indicated. Scaffold-guided bone regeneration (SGBR) has recently shown efficacy in preclinical and clinical studies. To investigate different SGBR strategies over periods of up to 3 years we have established a well characterized large segmental tibial bone defect ovine model, for which we have developed and optimized immunohistochemistry (IHC) protocols. We present an overview of the immunohistochemical characterization of different experimental groups in which all ovine segmental defects were treated with a bone grafting technique combined with a three-dimensionally printed medical-grade polycaprolactone-tricalcium phosphate (mPCL-TCP) scaffold. The qualitative data set is based on osteoimmunological findings gained from IHC analyses of over &gt;350 sheep surgeries over the past two decades. Our systematic and standardized IHC protocols enabled us to gain further insight into the complex and long-drawn-out bone regeneration processes, which ultimately proved to be a critical element for successful translational research.

Surface defect detection is one of the most widely used research areas in the field of image processing and machine vision. Detection of surface defects is used in visual inspection systems and medical image analysis. In this manuscript, an innovative method for detecting surface defects based on energy changes in co-occurrence matrices is presented in several directions. The method presented in this manuscript includes two stages of learning and testing. In the learning phase, to extract texture features, the gray level co-occurrence matrix operator is applied on the healthy image of the desired level. Then the energy value of the output matrix is ​​calculated. In the following, changes in the amount of energy are considered as statistical characteristics that are a good representative of the image of a healthy surface. Finally, with its help, a suitable threshold for the health of the images is obtained. Then, in the test phase, with the help of the calculated quorum, the defective windows that have suffered from non-normality are distinguished from the healthy surface sections. In the results section, the efficiency of the mentioned method has been measured on medical images and stone and ceramic images, and its detection accuracy has been compared with some previous effective methods. The advantages of the presented method include high accuracy, low calculations and compatibility with all types of levels due to the use of the learning stage. The proposed approach can be used in medical applications to diagnose abnormalities such as diseases. All extracted features are statistical, so its detection speed is higher than deep neural networks.

The effect of thermal radiation on the two – dimensional, steady-state, conjugate heat transfer from a circular cylinder with an internal heat source in steady laminar crossflow is investigated in this work. P₀ (Rosseland) and P₁ approximations were used to model the radiative transfer. The mathematical model equations were solved numerically. Qualitatively, P₀ and P₁ approximations show the same effect of thermal radiation on conjugate heat transfer; the increase in the radiation – conduction parameter decreases the cylinder surface temperature and increases the heat transfer rate. Quantitatively, there are significant differences between the results provided by the two approximations.

The main purpose of this research is to use “DMAIC” and “DMADV” framework of six sigma to reduce cost of projects, increase yields, improve performance and reduce defects. This study conclude that the sigma level of cement bag production in four production lines is “4.7 DPMO” values of 710 and the possibility of defects per unit of 11 possibilities this situation was handled by using six sigma. Any business or industry run only to satisfy customer and increase their profits, this can be attained as development of quality product..For the ranking of newly established universities the certification of those institutes is very important and also a critical process. For this process we used Lean six sigma approach that can identify the wastes that affect this process.Six sigma can be applied to any work field such as education, power optimization and other types of industries Six sigma “DMAIC” approach is also used for the testing of EDA tools that occurs due to the complex coding or configurations, flows and platforms they support. To improve the process quality of SDLC it’s necessary to remove the defects of system in advance along with thorough valuation of size and it also makes project accordant with real time environment

Software defect prediction is an important means to guarantee software quality. Because there are no sufficient historical data within a project to train the classifier, cross-project defect prediction (CPDP) has been recognized as a fundamental approach. However, traditional defect prediction methods using feature attributes to represent samples, which can not avoid negative transferring, may result in poor performance model in CPDP. This paper proposes a multi-source cross-project defect prediction method based on dissimilarity space ( DM-CPDP). This method first uses the density-based clustering method to construct the prototype set with the cluster center of samples in the target set. Then, the arc-cosine kernel is used to form the dissimilarity space, and in this space the training set is obtained with the earth mover’s distance (EMD) method. For the unlabeled samples converted from the target set, the KNN algorithm is used to label those samples. Finally, we use TrAdaBoost method to establish the prediction model. The experimental results show that our approach has better performance than other traditional CPDP methods.

An effective method to inspect inaccessible nuclear power facility by interface wave which propagate along the shrink fit boundary of reactor head is proposed in this study. Reactor head is relatively thick to inspect from the outside of reactor by conventional ultrasonic testing. The proposed interface wave can propagate a long distance from the fixed transducer position. The inside of nuclear reactor is limited to access due to the high radiation, so transducers are located at outside of nuclear facility and interface wave propagates into the nuclear reactor for defect detection. The numerical simulation and experiments were carried out to validate the effectiveness of the proposed interface wave inspection method. Various defect cases simulating field failures are also presented with satisfactory detectability by the proposed technique with the features for defect classification.

This study aimed to evaluate the early-childhood comorbidities of cerebral palsy (CP) in children with low birth weight (LBW) and assess the impact of maternal bio-psychosocial factors on the risk of CP in preterm infants across varying birth weights. Data for 15,181 prematurely born infants from 2009 to 2013 and 151,810 matched controls from Taiwan's National Health Insurance Research Database were analyzed. Period prevalence of CP, and comorbidities of LBW were verified, and odds ratios (ORs) were calculated. Results confirmed that increasing prematurity and low birth weight (LBW) rates in Taiwan. LBW was associated with higher CP prevalence. Maternal age extremes (&lt;20 and &gt;40 years) were significant risk factors of CP in LBW infants. LBW infants showed higher risks of respiratory, circulatory, and nervous system and psycho-developmental comorbidities compared to controls. Infants with the lowest birth weights had even higher ORs for these comorbidities. However, gastrointestinal and nutritional comorbidities were less prevalent in premature infants. Maternal factors such as family income, number of hospital admissions, and length of hospital stay were significantly correlated with birth weight and subsequent complications. Each additional gestational week significantly reduced the risk of complications in premature infants. Additionally, maternal bio-psychosocial factors were associated with birth weight and related outcomes in premature infants, emphasizing the importance of addressing these factors in prenatal care and interventions.

The increase in the rate and prevalence of diseases associated with the localized and general loss of bone mass calls for an investigation into therapeutic alternatives that largely involve the de-velopment of new biomaterials and cell therapy, converting tissue bioengineering into a prom-ising option. An experimental model of a critical mandibular lesion in rats has been used to study bone re-generation by treating the ostectomy with the biomaterials Evolution® and Gen-Os® (OsteoBiol®, Italy) combined, or not, with dental pulp stem cells (DP-MSC). The results obtained through the Micro-CT and histological study reveal the almost complete re-covery of the lesion in the group with DP-MSC. These results are supported by increases in endoglin, TGF-β, protocollagen I, parathormone, and calcitonin, generating an environment of bone generation and development when combining Evolution® and Gen-Os® (OsteoBiol®, Italy) with DP-MSC. These promising results confirm the transcendental role of DP-MSC in combina-tion with osteogenic biomaterials for bone regeneration, and warrant further studies, including its assessment in clinical trials.

Industrial radiography is a pivotal non-destructive testing (NDT) method that ensures quality and safety in a wide range of industrial sectors. Conventional human-based approaches, however, are prone to challenges in defect detection accuracy and efficiency, primarily due to the high inspection demand from manufacturing industries with high production throughput. To solve this challenge, numerous computer-based alternatives have been developed, including Auto-mated Defect Recognition (ADR) using deep learning algorithms. At the core of training, these algorithms demand large volumes of data that should be representative of real-world cases. However, the availability of digital X-ray radiography data for open research is limited by non-disclosure contractual terms in the industry. This study presents a pipeline that is capable of modeling synthetic images based on statistical information acquired from X-ray intensity distribution from real digital X-ray radiography images. Through meticulous analysis of the intensity distribution in digital X-ray images, the unique statistical patterns associated with the exposure conditions used during image acquisition, type of component, thickness variations, beam divergence, anode heel effect, etc., are extracted. The realized synthetic images were utilized to train deep learning models, yielding an impressive model performance with mean intersection over union (IoU) of 0.93, and mean dice coefficient of 0.96, on real unseen digital X-ray radiography images. This methodology is scalable and adaptable, making it suitable for diverse industrial applications.

Concrete-filled steel tube (CFST) members have been widely used in the field of civil engineering due to their advanced superior mechanical properties. However, internal defects such as concrete core voids and interface debonding are likely to weaken the load-carrying capacity and stiffness of these members, which affects safety and serviceability of CFST structures. Visualizing the inner defects of concrete core in CFST members have been a critical need in civil engineering construction, a travel time tomography (TTT) is introduced to quantitatively identify and visualize the sizes and positions of CFST members in this paper. Moreover, a parameter analysis is performed to investigate the relationship between TTT imaging qualities and influence factors, e.g. inversion parameters, defect sizes and positions. The effectiveness and accuracy of the TTT algorithm are verified by several numerical examples and the results demonstrate that TTT can identify the sizes and positions of concrete core void defects in CFST members efficiently and several inversion parameters including model weighting matrix and inversion grid size really pose a significant impact on the imaging results of CFST members. In addition, several optimum parameters are recommended to benefit the future study of the promising TTT approach for CFST members.

In response to the growing inspection demand exerted by process automation in component manufacturing, Non-destructive testing (NDT) continues to explore automated approaches that utilize deep learning algorithms for defect identification, including within digital X-ray radiography images. This necessitates a thorough understanding of the implication of image quality parameters on the performance of these deep learning models. This study investigates the influence of two image quality parameters, namely Signal-to-Noise Ratio (SNR) and Contrast-to-Noise Ratio (CNR), on the performance of U-net deep learning segmentation model. Input images were acquired with varying combinations of exposure factors such as kilovoltage, milli-ampere, and exposure time, which altered the resultant quality. The data was sorted into 5 different datasets according to their measured SNR and CNR values. The deep learning model was trained 5 distinct times, utilizing a unique dataset for each training session. Training the model with high CNR values yielded an intersection over Union (IoU) metric of 0.9594 on test data of the same category but drops to 0.5875 when tested on lower CNR test data. The result in this study emphasizes the importance of achieving a balance in training dataset according to the investigated quality parameters, to enhance the performance of deep learning segmentation models in NDT radiography applications.

In roll-to-roll (R2R) processing, uniformity of the web is a crucial factor that can guarantee high coating quality. To understand web defects due to thermal deformation, we analyzed the effects of web unevenness on the coating quality of an yttria-stabilized zirconia (YSZ) layer, a brittle electrolyte of solid oxide fuel cells (SOFCs). We used finite element analysis to analyze the thermal and mechanical deformations at different drying temperatures. A YSZ layer was also coated using R2R slot-die coating to observe effects of web unevenness on the coating quality. It was seen that web unevenness was generated by thermal deformation due the conduction and convection heat from the dryer. Owing to varying web unevenness with time, the YSZ layer developed cracks. At higher drying temperatures, more coating defects having larger widths were generated. Results indicated that web unevenness at the coating section led to coating defects, which could damage the SOFC and decrease its yield in the R2R process. From this study, we suggest that coating defects, generated by the web unevenness owing to the convection and conduction heat, should be considered for the high-volume production of brittle electrolytes using the R2R process.

Aluminum profile surface defects can greatly affect the performance, safety and reliability of products. Traditional human-based visual inspection is low accuracy and time consuming, and machine vision-based methods depend on hand-crafted features which need to be carefully designed and lack robustness. To recognize the multiple types of defects with various size on aluminum profiles, a multiscale defect detection network based on deep learning is proposed. Then, the network is trained and evaluated using aluminum profile surface defects images. Results show 84.6%, 48.5%, 96.9%, 97.9%, 96.9%, 42.5%, 47.2%, 100%, 100%, 43.3% average precision(AP) for the ten defect categories, respectively, with a mean AP of 75.8%, which illustrate the effectiveness of the network in aluminum profile surface defects detection. In addition, saliency maps also show the feasibility of the proposed network.

(1) Background: The aim of this work was to systematically review existing studies on whether hysteroscopy improves the reproductive outcomes of women with infertility even in the absence of intrauterine pathologies when compared to women who did not receive a hysteroscopy. (2) Methods: We established the Participant-Intervention-Comparison-Outcome strategy and used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement to conduct a systematic review of 11 studies which were retrieved from 3 electronic databases: Ovid-Medline, Ovid-Embase, and the Cochrane Library. Two independent investigators extracted the data from the included studies and used the Cochrane risk-of-bias tool to assess their quality. (3) Results: The primary outcome measures were the clinical pregnancy rates (CPRs) and live birth rates (LBRs) in the in vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) cycles. Hysteroscopy in infertile women without intrauterine pathologies showed higher CPRs and LBRs than those in the same population who did not receive hysteroscopy in cases of recurrent implantation failure and IVF (odds ratio: 1.79 and 1.46, 95% confidence interval: 1.46-2.30 and 1.08-1.97 for CPR and LBR, respectively); however, the degree of significance was not as high for LBR. (4) Conclusions: Hysteroscopy before IVF/ICSI in infertile women without intrauterine pathologies may potentially be effective in improving the CPRs and LBRs in patients with RIF. Robust and high-quality randomized trials are warranted to confirm this finding.

Software stands as one of the most rapidly evolving technologies in the present era, characterized by its swift expansion in both scale and complexity which leads to challenges in quality assurance. Software Defect Prediction (SDP) emerges as a methodology crafted to anticipate undiscovered defects, leveraging known defect data from existing codes. This methodology serves to facilitate software quality management, thereby ensuring overall product quality. Machine Learning (ML) and Deep Learning (DL) methodologies exhibit superior accuracy and adaptability compared to traditional statistical approaches catalyzing active researches in this domain. However, it makes us hard to generalize not only because of the disparity between open-source project and commercial project but also the difference on each industrial sectors. Consequently, further research utilizing datasets sourced from diverse real-world sectors becomes imperative to bolster the applicability of these findings. In this study, we utilized embedded software for telecommunication systems of SAMSUNG ELECTRONICS, supplemented by the introduction of nine novel features to train the model, and subsequent analysis of results ensued. Experimental outcomes revealed that the F-measurement metric has been enhanced from 0.58 to 0.63 upon integration of the new features, thereby signifying a performance augmentation of 8.62%. This case study is anticipated to contribute to bolster the application of SDP methodologies within analogous industrial sectors.

In this review, we focus on a small section of the extensive literature that deals with the materials containing pristine defective CNs and those incorporated in the hybrid materials. We will discuss only those topics that focus on structural defects related to the introduction of perturbation into the surface topology of a nanostructure. We focus mainly on the method using microwave (MW) irradiation, which is a powerful tool for synthesizing and modifying carbon-based solid materials. In addition, the simplicity of the technique, economy, and the possibility of conducting the reaction in solvents and solid phase, in the presence of components of different chemical nature, allows use in various combinations. In this review, we will emphasize the advantages of synthesis using MW-assisted heating and indicate the influence of the structure of the obtained materials on their physical and chemical properties. We will also highlight the role of the occurrence of defects in the carbon material and the implication in designing their properties and applications.

New experimental and clinical findings question the historic view of hydrocephalus and its 100-year-old classification. In particular, real-time MRI evaluation of CSF flow and detailed insights into brain water regulation on the molecular scale indicate the existence of at least three main mechanisms that determine the dynamics of neurofluids. (i) Inspiration is a major driving force (ii) Adequate filling of brain ventricles by balanced cerebrospinal fluid upsurge is sensed by cilia (iii) The perivascular glial network connects the ependymal surface to the pericapillary Virchow-Robin spaces. Hitherto, these aspects have not been considered a common physiologic framework improving knowledge and therapy for severe disorders of normal-pressure and post-haemorrhagic hydrocephalus, spontaneous intracranial hypotension and spaceflight disease.

Births occurring before thirty-seven weeks of gestation are referred to as preterm births (PTBs), which is the primary cause of neonatal mortality and long-term disabilities. The unknown mechanism behind PTB makes diagnosis difficult, yet early detection is necessary for controlling and averting related consequences. The primary focus of this work is to provide an overview of the known risk factors associated with preterm labor and the conventional and advanced procedures for early detection of PTB, including multi-omics and artificial intelligence (AI)/machine learning (ML)-based approaches. It also discusses the principles of detecting various proteomic biomarkers based on lateral flow immunoassay and microfluidic chips, along with the commercially available point-of-care testing (POCT) devices and associated challenges. After briefing the therapeutic and preventive measures of PTB, the review summarizes with an outlook.

(1) Birth asphyxia is the major cause for delivery room resuscitation. Subsequent organ failure and hypoxic-ischemic encephalopathy (HIE) account for 25% of all early postnatal deaths. The neonatal Sequential Organ Failure Assessment (nSOFA) considers platelet count, respiratory and cardiovascular dysfunction in neonates with sepsis. To evaluate whether nSOFA is also a useful predictor for in-hospital mortality in neonates (≥ 36+0 weeks of gestation (GA)) following asphyxia with HIE and therapeutic hypothermia (TH), (2) nSOFA was documented at ≤ 6 hours of life. (3) 65 infants fulfilled inclusion criteria for TH. All but one infant received cardiopulmonary resuscitation and/or respiratory support at birth. nSOFA was lower in survivors (median 0 [IQR 0-2]; n = 56, median GA 39+3, female n = 28 (50%)) than in non-survivors (median 10 [4-12], p < 0.001; n = 9, median GA 38+6, n = 4 (44.4%)). This was also observed for the respiratory (p < 0.001), cardiovascular (p < 0.001), and hematologic sub scores (p = 0.003). The odds ratio for mortality was 1.6 [95% CI = 1.2 – 2.1] per one-point increase in nSOFA. The optimal cut-off value of nSOFA to predict mortality was 3.5 (sensitivity 100.0%, specificity 83.9%). (4) Since early accurate prognosis following asphyxia with HIE and TH is essential to guide end-of-life decisions, nSOFA (≤ 6 hours of life) offers the potential to identify infants at risk of mortality.

In this paper, we investigate the structural, microstructural, dielectric, and energy storage properties of Nd and Mn co-doped Ba0.7Sr0.3TiO3 [(Ba0.7Sr0.3)1-xNdxTi1-yMnyO3 (BSNTM) ceramics (x = 0, 0.005, and y = 0, 0.0025, 0.005, and 0.01)] via a defect dipole engineering method. The complex defect dipoles (MnTi"-VO∙∙)∙ and (MnTi"-VO∙∙) between acceptor ions and oxygen vacancies capture electrons, enhancing the breakdown electric field and energy storage performances. XRD, Raman spectroscopy, and microscopic investigations of BSNTM ceramics revealed the formation of a tetragonal phase, increased oxygen vacancies, and reduced grain size with Mn dopant, respectively. The BSNTM ceramics with x=0.005 and y=0 exhibit a high dielectric constant of 2058 and a dielectric loss of 0.026 at 1 kHz. These values gradually decreased to 1876 and 0.019 for x=0.005 and y=0.01 due to the Mn2+ ions at Ti4+-site, which facilitates the formation of oxygen vacancies, and prevents the decrease of Ti4+. In addition, the defect dipoles act as a driving force for depolarization to tailor the domain formation energy and domain wall energy, which provides a high difference between the maximum polarization of Pmax and remnant polarization of Pr (ΔP=10.39 µC/cm2). Moreover, the complex defect dipoles with optimum oxygen vacancies in BSNTM ceramics can provide not only a high ΔP but also reduce grain size, which together improve the breakdown strength from 60.4 to 110.6 kV/cm, giving rise to a high energy storage density of 0.41 J/cm3 and high efficiency of 84.6% for x=0.005 and y=0.01. These findings demonstrate that defect dipoles engineering is an effective method to enhance the energy storage performance of dielectrics for capacitor applications.

Insulator defect detection is of great significance to compromise the stability of the power transmission line. The state-of-the-art network of object detection, YOLOv5, has been widely used on insulator and defect detection. However, YOLOv5 network has some limitations like poor detection rate and high computational loads in detecting small insulator defects. To solve these problems, we proposed a light-weight network for insulator and defect detection. In this network, we introduced Ghost module into YOLOv5 backbone and neck to reduce the parameters and model size to enhance the performance in unmanned aerial vehicles (UAVs). Besides, we added small object detection anchors and layers for small defect detection. In addition, we optimized the backbone of YOLOv5 by applying convolutional block attention module (CBAM) to focus on critical information for insulator and defect detection and suppress uncritical information. The experiment result shows the mean average precision (mAP) 0.5 and the mAP0.5:0.95 of our model can reach 99.4% and 91.7%, the parameters and model weight are reduced to 3807372 and 8.79M, which can easily deploy to embedded devices like UAVs. And the speed of detection can reach 10.9ms/image, which can meet the real-time detection requirement.

The 22q11.2 deletion syndrome is a multisystemic disorder characterized by a marked variability of phenotypic features making the diagnosis challenging for clinicians. The wide spectrum of clinical manifestations includes congenital heart defects, most frequently conotruncal cardiac anomalies, thymic hypoplasia and predominating cellular immune deficiency, laryngeal developmental defects, midline anomalies with cleft palate and velar insufficiency, structural airway defects, facial dysmorphism, parathyroid and thyroid gland hormonal dysfunctions, speech delay, developmental delay, neurocognitive and psychiatric disorders. Significant progress has been made in understanding the complex molecular genetic etiology of the 22q11.2 deletion syndrome underpinning the heterogeneity of clinical manifestations. The deletion is caused by chromosomal rearrangements in meiosis and is mediated by non-allelic homologous recombination events between low copy repeats or segmental duplications in the 22q11.2 region. A range of genetic modifiers, environmental factors as well as the impact of hemizygosity on the remaining allele contribute to the intricate genotype-phenotype relationships. This comprehensive review has been aimed at highlighting the molecular genetic background of 22q11.2 deletion syndrome in correlation with a clinical multidisciplinary approach.

miRNAs have recently attracted investigators' interest as regulators of valvular diseases pathogenesis, diagnostic biomarkers, and therapeutical targets. Evidence from in-vivo and in-vitro studies demonstrated stimulatory or inhibitory roles in mitral valve prolapse development, aortic leaflet fusion, and calcification pathways, specifically osteoblastic differentiation and transcription factors modulation. Tissue expression assessment and comparison between physiological and pathological phenotypes of different disease entities, including mitral valve prolapse and mitral chordae tendineae rupture, emerged as the best strategies to address miRNAs over or under-representation and thus, their impact on pathogeneses. In this review, we discuss the fundamental intra- and intercellular signals regulated by miRNAs leading to defects in mitral and aortic valves, congenital heart diseases, and the possible therapeutic strategies targeting them. These miRNAs inhibitors comprise of antisense oligonucleotides and sponge vectors. The miRNA mimics, miRNA expression vectors, and small molecules are instead possible practical strategies to increase specific miRNA activity. Advantages and technical limitations of these new drugs, including instability and complex pharmacokinetics, are also presented. Novel delivery strategies, such as nanoparticles and liposomes, are described to improve knowledge on future personalized treatment directions.

Cost-effective and functionalized scaffolds are in high demand for stem-cell-based regenerative medicine to treat refractory bone defects in craniofacial abnormalities and injuries. One potential strategy is to utilize pharmacological and cost-effective plant polyphenols and biocompatible proteins, such as gelatin. Nevertheless, the use of chemically modified proteins with plant polyphenols in this strategy has not been standardized. Here, we demonstrated that gelatin chemically modified with epigallocatechin gallate (EGCG), the major catechin isolated from green tea, can be a useful material for dedifferentiated fat cells and adipose-derived stem cells and can induce bone regeneration in a rat congenial cleft-jaw model in vivo. Vacuum-heated gelatin sponge modified with EGCG (vhEGCG-GS) induced superior osteogenesis from these two cell types compared with vacuum-heated gelatin sponge (vhGS). The EGCG-modification converted the water wettability of vhGS to a hydrophilic property (contact angle: 110° to 3.8°) and the zeta potential to a negative surface charge; the modification enhanced the cell adhesion property and promoted calcium phosphate precipitation. These results suggest that the EGCG-modification with chemical synthesis can be a useful platform to modify the physicochemical property of gelatin. This alteration is likely to provide a preferable microenvironment for multipotent progenitor cells, inducing superior bone formation in vivo.

Background: There is an exponential increase in caesarean sections with epidemic proportions worldwide, which is considered as a serious public health issue that influences negatively both maternal and childhood health. Aims: This study aimed to evaluate the associations between pre-dominant maternal risk factors and the prevalence of caesarean section in a representative sample of women from Greece. Methods: This is a cross-sectional study conducted on 5182 healthy, re-productive-aged women from 11 geographically diverse Greek areas after applying specific inclu-sion and exclusion criteria. Statistical analysis was applied to evaluate the impact of maternal so-ciodemographic, anthropometric, lifestyle and perinatal factors in the risk of caesarean section de-liveries. Results: A high prevalence of 56.4% of caesarean section deliveries was recorded in the study population. The incidence of caesarean sections reached to 51.5% in private hospitals in which an increasing rate of 47.5% for planned caesarean sections were noticed. Older maternal age, pre-pregnancy overweight and obesity, excess gestational weight gain, high rates of preterm birth, better economic status, smoking habits, and private type of birth hospital were significantly related with enhanced risk of caesarean section, independently of multiple confounding factors. Conclu-sions: Our study revealed that caesarean section rates are continuously increase, while several maternal risk factors, including especially pre-pregnancy overweight/obesity and excess gestational weight gain, cumulatively raise its prevalence which further increase the risk for postnatal adverse outcomes for both the mothers and their children. Emergent public health policies and strategies should be promoted to confront the predominant maternal risk factors-related with caesarean sec-tion and inform future mothers how to be prevented from them by applying healthier nutritional and lifestyle habits and to select caesarean section only due to emergency medical reasons. Alarmingly enough, targeted nutritional intervention strategies are strongly recommended to ef-fectively reduce the prevalence of maternal pre-pregnancy overweight/obesity and the excess gestational weight gain, which in turn may minimize the risk of childhood overweight/obesity.

Plant-parasitic nematodes cause expressive annual yield losses to worldwide agricultural production. Most cultivated plants have no known resistance against nematodes and the few bearing a resistance gene can be overcome by certain species. The chemical methods that have been deployed to control nematodes were largely banned from use due to their poor specificity and high toxicity. Hence, there is an urgent need for the development of cleaner and more specific control methods. Recent advances in nematode genomics, including in phytoparasitic species, provide an unprecedented opportunity to identify genes and functions specific to these pests. Using phylogenomics, we compared 61 nematode genomes, including 16 for plant-parasitic species and identified more than 24,000 protein families specific to these parasites. In the genome of Meloidogyne incognita, one of the most devastating plant parasites, we found ca. 10,000 proteins with orthologs restricted only to phytoparasitic species and no further homology in protein databases. Among these phytoparasites-specific proteins, ca. 1,000 shared the same properties as known secreted effectors involved in essential parasitic functions. Of those, 68 were novel and showed strong expression during the endophytic phase of the nematode life cycle, based on both RNA-seq and RT-qPCR analyses. Besides effector candidates, transcription-related and neuro-perception functions were enriched in phytoparasites-specific proteins, revealing interesting targets for nematode control methods. This phylogenomics analysis, constitutes an unprecedented resource for the further understanding of the genetic basis of nematode adaptation to phytoparasitism and for the development of more efficient control methods.

Convolutional Neural Networks combined with autonomous drones are increasingly seen as enablers of partially automating the aircraft maintenance visual inspection process. Such an innovative concept can have a significant impact on aircraft operations. Through supporting aircraft maintenance engineers detect and classify a wide range of defects, the time spent on inspection can significantly be reduced. Examples of defects that can be automatically detected include aircraft dents, paint defects, cracks and holes, and lightning strike damage. Additionally, this concept could also increase the accuracy of damage detection and reduce the number of aircraft inspection incidents related to human factors like fatigue and time pressure. In our previous work, we have applied a recent Convolutional Neural Network architecture known by MASK R-CNN to detect aircraft dents. MASK-RCNN was chosen because it enables the detection of multiple objects in an image while simultaneously generating a segmentation mask for each instance. The previously obtained F1 and F2 scores were 62.67% and 59.35% respectively. This paper extends the previous work by applying different techniques to improve and evaluate prediction performance experimentally. The approaches uses include (1) Balancing the original dataset by adding images without dents; (2) Increasing data homogeneity by focusing on wing images only; (3) Exploring the potential of three augmentation techniques in improving model performance namely flipping, rotating, and blurring; and (4) using a pre-classifier in combination with MASK R-CNN. The results show that a hybrid approache combining MASK R-CNN and augmentation techniques leads to an improved performance with an F1 score of (67.50%) and F2 score of (66.37%)

Statistical modeling lies at the heart of product design and development throughout numerous engineering disciplines, especially since processing large amounts of data has become increasingly ubiquitous. While mathematical statistics provide elegant guidance pertaining to the question of whether or not some particular underlying modeling assumptions are justified and appropriate, when pursuing a more comprehensive assessment of product design and development other considerations often increase in significance. Therefore, we will examine and analyze the tedious interactions and implications of statistical modeling choices and product liability exposure. To the best of our knowledge, this paper is the first to draw attention to and explore some often overlooked or oversimplified dangers and pitfalls that enter the equation when product design heavily relies on statistical modeling. In particular, through a diligent analysis of both statistical and legal aspects we will explore how statistically optimal procedures may yield far from optimal outcomes in terms of product liability when applied to actual real life problems and why suboptimal nonparametric or robust approaches may constitute better alternatives.

The epidemic transmission of Zika virus (ZIKV) in Brazil has been identified as a cause of microcephaly and other neurological malformations in babies of ZIKV-infected women. This study provides a descriptive analysis, since the onset of symptoms to the delivery, of a cohort who were registered as having ZIKV infection in pregnancy, from November 2015 to December 2016. Suspected cases were registered at a referral center for infectious and tropical diseases in Manaus, in the Brazilian Amazonian region. A total of 834 women with suspected ZIKV in pregnancy were included, of whom 91.4% had confirmed pregnancy. Reverse-transcriptase polymerase chain reaction (RT-PCR) confirmed ZIKV infection in 42.2% of the cohort. In 35.2% of the cohort, ZIKV was the sole infection identified. Severe adverse pregnancy outcomes (abortion, stillbirth, or microcephaly) were observed in both RT-PCR ZIKV-positive (4.96%) and ZIKV-negative (2.15%) cases. Women with suspected ZIKV infection were much more likely to have adverse pregnancy outcomes if they were symptomatic during the first trimester of pregnancy (odds ratio 10.5; 95% confidence interval 4.0–27.0; p<0.001). Among pregnant women with suspected ZIKV infection, the occurrence of symptoms in the first trimester is associated with an especially high risk of severe adverse pregnancy outcomes.

This study investigated defect formation and strain distribution in high Mg content Al-Mg alloys during normal rolling and cross-rolling processes. The finite element analysis (FEA) revealed the presence of wave defects and strain localization-induced zipper cracks in normal cold rolling, which were confirmed by experimental results. The concentration of shear strain played a significant role in crack formation and propagation. However, the influence of wave defects was minimal in the cross-rolling process, which exhibited a relatively uniform strain distribution. Nonetheless, strain concentration at the edge and center regions led to the formation of zipper cracks and edge cracks, with more pronounced propagation observed in the experiments compared to FEA predictions. Furthermore, texture evolution was found to be a crucial factor affecting crack propagation, particularly with the development of the Goss texture component which is observed by electron backscattered diffraction analysis at bending points. The Goss texture hindered crack propagation, while the Brass texture allowed cracks to pass through. This phenomenon was consistent with both FEA and experimental observations. To mitigate edge crack formation and propagation, potential strategies involve promoting the formation of the Goss texture at the edge through alloy and process conditions, as well as implementing intermediate annealing to alleviate stress accumulation. These measures can enhance the overall quality and reliability of Al-Mg alloys during cross-rolling processes. In summary, understanding the mechanisms of defect formation and strain distribution in Al-Mg alloys during rolling processes is crucial for optimizing their mechanical properties. The findings of this study provide insights into the challenges associated with wave defects, strain localization, and crack propagation. Future research and optimization efforts should focus on implementing strategies to minimize defects and improve the overall quality of Al-Mg alloys in industrial applications.

Software is playing the most important role in recent vehicle innovation, and consequently the amount of software has been rapidly growing last decades. Safety-critical nature of ships, one sort of vehicles, makes Software Quality Assurance (SQA) has gotten to be a fundamental prerequisite. Just-In-Time Software Defect Prediction (JIT-SDP) aims to conduct software defect prediction (SDP) on commit-level code changes to achieve effective SQA resource allocation. The first case study of SDP in maritime domain reported feasible prediction performance. However, we still consider that the prediction model has still rooms for improvement since the parameters of the model are not optimized yet. Harmony Search (HS) is a widely used music-inspired meta-heuristic optimization algorithm. In this article, we demonstrated that JIT-SDP can produce the better performance of prediction by applying HS-based parameter optimization with balanced fitness value. Using two real-world datasets from the maritime software project, we obtained an optimized model that meets the performance criterion beyond baseline of previous case study throughout various defect to non-defect class imbalance ratio of datasets. Experiments with open source software also showed better recall for all datasets despite we considered balance as performance index. HS-based parameter optimized JIT-SDP can be applied to the maritime domain software with high class imbalance ratio. Finally, we expect that our research can be extended to improve performance of JIT-SDP not only in maritime domain software but also in open source software.

Our objective was to evaluate whether pregnancy is prolonged by use of a proteomics-based maternal serum screening test followed by treatment interventions. This is a secondary analysis of the PREVENT-PTB randomized trial comparing screening with the PreTRM test versus no screening. The primary trial analysis found no significant between-group difference in preterm birth rate. Rather than considering a dichotomous outcome (preterm vs term), we treated gestational age at birth as a continuous variable using survival analysis. We also evaluated between-group difference in NICU length of stay and duration of respiratory support. Results indicated that pregnancy was significantly prolonged in subjects screened with PreTRM test compared to controls (adjusted hazard ratio 0.53, 95% confidence interval 0.36-0.78, P &lt;0.01). Newborns of screened subjects had significantly shorter NICU stay but no significant decrease in duration of respiratory support. In the PreTRM screen-positive group, interventions that were associated with pregnancy prolongation included care management and low-dose aspirin but not 17-hydroxyprogesterone caproate. We concluded that screening with the PreTRM test followed by interventions for screen-positive pregnancies can prolong pregnancy and reduce NICU-LOS.

The lung microbiota is a complex community of microorganisms that colonize the respiratory tract of individuals from or even before birth. Although the lungs were traditionally believed to be sterile, recent research has shown that there is a diversity of bacterial species in the respiratory system. Knowledge about the lung microbiota in the newborn and its relationship with bacterial infections is of vital importance to understand the pathogenesis of respiratory diseases in neona-tal patients undergoing mechanical ventilation. In this article, the current evidence on the compo-sition of the lung microbiota in the newborn will be reviewed, as well as its role in the develop-ment of bacterial infections in mechanically ventilated neonates. Although advances in many as-pects of the neonatal intensive care unit care have significantly improved the survival of preterm infants, the diagnosis and treatment of ventilator-associated pneumonia has not progressed in recent decades. Avoiding dysbiosis caused by inappropriate use of antibiotics around birth, as well as avoiding intubation of patients or promoting early removal of endotracheal tubes are among the most important preventive measures for ventilator-associated pneumonia. The use of probiotics and prebiotics to prevent infectious, allergic or metabolic complications in the short or long term constitutes a very important field of research in perinatal medicine.

Maternal and child nutrition has been a critical component of health, sustainable development, and progress in low- and middle-income countries (LMIC). While a decrement in maternal mortality is an important indicator, simply surviving pregnancy and childbirth does not imply better maternal health. One of the fundamental obligations of nations under international human rights law is to enable mothers and teenage girls to endure pregnancy and delivery as an aspect of their enjoyment of reproductive and sexual health and rights and live a dignified life. The aim of this study was to discover the correlation between the Maternal Observation and Motivation (MOM) program and m-Health support for maternal and newborn health. A Comparative study was done among 109 pregnant mothers (study group-94; control group-102 mothers) with not less than 20 weeks of gestation. Maternal outcomes such as Hb, weight gain and newborn results like birth weight and crown- heel length was obtained on the baseline, 28 and 36 weeks of gestation. Other secondary data collected were abortion, stillbirth, low birth weight, major congenital malformations, twin or triplet pregnancies, physical activity and maternal wellbeing. The MOM intervention included initial face to face education, three in-person visits and eight virtual health coaching by WhatsApp. The baseline data on Hb of the mothers show that 31(32.98%) vs 27(28.72%) of the study and control group had anaemia, which improved to 27.66% and 14.98% among study group mothers at 28 and 36 weeks of gestation (p<0.001). The weight gain (p< 0.001), level of physical activity (p< 0.001), and maternal wellbeing (p< 0.01) also had significant differences after the Intervention. Even after controlling for potentially confounding variables, the maternal food practices regression model revealed that birth weight was directly correlated with consumption of milk (p 0.001), fruits (p 0.01), and green vegetables (p 0.05).As per the physical activity and maternal wellbeing regression model, the birth weight and crown heel length were strongly related with the physical activity and maternal wellbeing of mothers at 36 weeks of gestation (p <0.05). Combining the MOM intervention with standard antenatal care is a safe and effective way to improve maternal welfare while upholding pregnant mothers' human rights.

Buckling defect will appear on the outer surface of the deformed ring during constrained ring rolling (CRR) of aluminum alloy thin wall conical ring with inner high ribs (AATWCRIHR), if the geometrical dimension of the ribs doesn't match the wall thickness. To avoid the buckling defect, a quantitative method for characterizing the degree of the buckling defect is proposed using the area of buckling profile. Then an orthogonal experimental scheme was designed taking the width of the middle rib, thickness of wall, and height of the middle rib as design variables and defining the area of buckling profile as optimization objective. Subsequently, a quadratic polynomial response surface model was established by combining the optimization algorithm with the finite element method (FEM), and the geometrical dimension of the middle ribs of the deformed AATWCRIHR is optimized. Also the optimal parameter combination to minimize the area of buckling profile is obtained and verified using FE simulation. Results show that the AATWCRIHR after optimization doesn’t generate the buckling defect during constrained ring rolling, and it is proved that the quantitative buckling defect representation method and the optimization design method based on the response surface model and the finite element simulation results are feasible for the constrained ring rolling process of the AATWCRIHR.

The 2022-2023 Mpox multi-country outbreak, identified in over 110 WHO Member States, revealed a predominant impact on cisgender men, particularly those engaging in sex with men, while less frequently affecting women. This disparity prompted a focused investigation into the gender-specific characteristics of Mpox infections, particularly among women, to address a notable knowledge gap. This review systematically gathers and analyzes scientific literature and case reports concerning Mpox infections in women, covering a broad geographical spectrum including regions such as Buenos Aires, Brazil, Northern California, Colombia, Nigeria, Europe, Vietnam, Spain, Switzerland, and the United States. The analysis delves into various aspects of Mpox in women, including clinical features, epidemiology, psychological impacts, preparedness strategies, and case studies, with particular attention to pregnant women and those with underlying health conditions. Empirical data from multiple studies underscore the unique epidemiological and clinical patterns of Mpox in women. In the United States, a small percentage of Mpox cases were reported among cisgender women, with a notable portion involving non-Hispanic Black or African American, non-Hispanic White, and Hispanic or Latino ethnicities. The primary transmission route was identified as sexual or close intimate contact, with the virus predominantly manifesting on the legs, arms, and genital areas. Further, a study in Spain highlighted significant disparities in diagnosis delays, transmission modes, and clinical manifestations between genders, indicating a different risk profile and disease progression in women. Additionally, a case from Vietnam linked to a new Mpox sublineage in women emphasizes the role of women in the transmission dynamics and the importance of genomic monitoring. This review emphasizes the necessity for inclusive surveillance and research to fully understand Mpox dynamics across diverse population groups, including women. Highlighting gender and sexual orientation in public health responses is crucial for an effective approach to managing the spread and impact of the disease. The findings advocate for a gender-diverse assessment in health services and further research to explore the nuances of Mpox transmission, behavior, and progression among different groups, thereby enhancing the global response to Mpox and similar public health challenges.

A widely accepted concept is that boys are more susceptible than girls to oxidative stress related complications of prematurity, including bronchopulmonary dysplasia (BPD), retinopathy of prematurity (ROP), necrotizing enterocolitis (NEC), intraventricular hemorrhage (IVH), and periventricular leukomalacia (PVL). We aimed to quantify the effect size of this male disadvantage by performing a systematic review and meta-analysis of cohort studies exploring the association between sex and complications of prematurity. Risk ratios (RRs) and 95% CIs were calculated by a random-effects model. Of 1365 potentially relevant studies, 41 met the inclusion criteria (625680 infants). Male sex was associated with decreased risk of hypertensive disorders of pregnancy, fetal distress, and C-section, but increased risk of low Apgar score, intubation at birth, respiratory distress, surfactant use, pneumothorax, postnatal steroids, late onset sepsis, any NEC, NEC&gt;stage 1 (RR 1.12, CI 1.06-1.18), any IVH, severe IVH (RR 1.28, CI 1.22-1.34), severe IVH or PVL, any BPD, moderate/severe BPD (RR 1.23, CI 1.18-1.27), severe ROP (RR 1.14, CI 1.07-1.22), and mortality (RR 1.23, CI 1.16-1.30). In conclusion, preterm boys have higher clinical instability and greater need for invasive interventions than preterm girls. This leads to a male disadvantage in mortality and short-term complications of prematurity.

AbstractIntroduction: Increasing knowledge of obstetric danger signs (ODS) and encouraging birth preparedness and complication readiness (BPCR) practices are strategies to increase skilled maternal health service utilization in low-income countries. One of the methods to increase mothers' knowledge about ODS and promote BPCR practice is through health education intervention (HEI). However, the effect of context-specific community-based health education led by women's groups on these outcomes has not been comprehensively studied, and the existing evidence is inconclusive. Thus, we aimed to evaluate the effect of a context-specific community-based HEI led by women's groups on mothers' knowledge regarding ODS and BPCR practices in southern Ethiopia.Methods: An open-label, two-arm parallel group cluster-randomized controlled trial was conducted from January to August 2023 on pregnant women from 24 clusters (kebeles) (12 interventions and 12 controls) in the northern zone of the Sidama region. The Open Data Kit smartphone application was utilized to collect data. The intention-to-treat analysis was used to compare outcomes between groups. We fitted multi-level mixed-effects modified Poisson regression with robust standard error to account for between and within cluster effects. Results: One thousand and seventy pregnant women (540 in the intervention and 530 in the control clusters) responded to this study, making the overall response rate 95.02%. Excessive vaginal bleeding (94.3% in the interventional group vs. 88.7% in the control group) was the commonest ODS mentioned during childbirth. Overall, 68.7% of women in the intervention group and 36.2% of mothers in the control group had good knowledge of ODS (P-value < 0.001). Saving money and materials (97.1% in the interventional group vs. 92.7% in the control group) was the most frequently practiced BPCR plan. Overall, 64.3% of women in the intervention group and 38.9% of mothers in the control group practiced BPCR (P-value < 0.001). HEI significantly increased overall knowledge of ODS (adjusted risk ratio [ARR]: 1.71; 99% CI: 1.14-2.57) and improved overall BPCR practice (ARR: 1.55; 99% CI: 1.02-2.39). Conclusions: A community-based HEI led by women's groups improved mothers' knowledge regarding ODS and BPCR practices in a rural setting in southern Ethiopia. Interventions designed to increase women's knowledge of ODS and improve BPCR practice must implement context-specific, community-based HEI that aligns with World Health Organization recommendations. Trial registration: NCT05865873

Background: Despite tremendous efforts to reduce neonatal mortality worldwide and in 24 Ethiopia, there is the country is one of the countries with highest neonatal morbidity and health 25 losses. Never the less, the past three decades’ national trend and subnational distribution of 26 neonatal morbidity and mortality and its health loss in Ethiopia, was not well documented. 27 Hence, this study had aimed to analyze the trend and distributions as well as health losses 28 resulting from neonatal morbidity in the past three decades in Ethiopia, 2019. 29 Objective: To assess the national trend and sub national distributions of neonatal morbidity and 30 neonatal mortality in the previous three decades by using Global Burden of Diseases, 2019 data. 31 Methods: The data sources were primary and secondary data related to risk factors, morbidity, 32 disability, deaths, Disability Adjusted Life Years, Years Lived with Disability and Years Life Lost 33 were collected form case studies and case series, household surveys, socio-demographic surveys 34 and surveillances, health facilities surveys, Health facility observations and interviews and 35 published and unpublished literatures. The prevalence, deaths and health losses were calculated 36 by using embedded model. The study period covered from 1990 to 2019. Results were presented 37 buy using texts, tables and graphs. 38 Results: Seventy percent of neonatal disorders had occurred among early neonates aged 0 to 6 39 days. Between 1990 and 2019, the national prevalence of neonatal disorders had increased by 40 47% in to 28,319 (95% UI, 25646-30,361). Bet Similarly, the highest number of neonatal deaths 41 caused by neonatal sepsis had shifted from Southern Nations Nationalities and Peoples region to 42 Oromia region while Harari remains to bear the lowest burden in the last three decades. The 43 highest and the lowest YLL as a result of neonatal disorders had occurred in Oromia 44 [(2,753,038,95% UI, 2,184,142-3,497-926) and Amhara 1,360,847 [(95% UI, 95% UI, 45 1,062,660-1,762,028)] regions respectively. Unlike other regions, Addis Ababa had the highest 46 (52%) prevalence of preterm birth in 2019 47 Conclusion and Recommendation: About seven in ten of neonatal death had occurred among 48 early neonates indicating narrowed occurrence of the event. The highest and the lowest number 49 of neonatal death and health loss had occurred in Oromia and Harari regions respectively. The 50 main causes of death were neonatal sepsis and other infections, neonatal preterm, hemolytic 51 disease and other jaundice and neonatal encephalopathy and trauma. Hence, Contextualized, 52 locally accepted innovative early neonatal care is crucial to avert the event.

This paper presents a study to accurately evaluate defects in reinforced concrete decks using ultrasonic pulse-echo signals. Two validation specimens were designed and tested where reinforced concrete deck slab specimens included planned voids and defects. A commercial Ultrasonic Pulse-Echo (UPE) device obtains 2-D images of the void/defect locations of the reinforced concrete deck. The UPE is based on the ultrasonic shear-wave test method using dry-point-contact transmitting and receiving transducers and employing a synthetic aperture focusing technique. The authors analyzed the recorded UPE A-scan data to enhance the accuracy of estimating the defects' locations using the synthetic aperture focusing technique imaging method. The analysis benefitted from an advanced denoising approach and defect echo peak extraction based on empirical modal decomposition, Hurst exponent characterization, and Hilbert envelope estimation. While output from conventional UPC devices can only provide qualitative results, the new method provides quantitative information on the anomalies inside the reinforced concrete deck. The developed approach accurately assists with assessing the location and depth of the voids/defects in the reinforced concrete deck slabs.

Abstract: The purpose of this study was to understand the role of infection in the origin of chromosomal anomalies linked to neurodevelopmental disorders. In patients with neurodevelopmental disorders, DNA’s from viruses and bacteria including known teratogens were tested against chromosome anomalies known to cause the disorders. Results support a theory that parental infections disrupt elaborate multi-system gene coordination needed for neurodevelopment. Genes essential for neurons, lymphatic drainage, immunity, circulation, angiogenesis, barriers, structure, and chromatin activity were all found close together in polyfunctional clusters that were deleted in neurodevelopmental disorders. These deletions account for immune, circulatory, and structural deficits that accompany neurologic deficits. In deleted clusters, specific and repetitive human DNA matched infections and passed rigorous artifact tests. In some patients, epigenetic driver mutations were found and may be functionally equivalent to deleting a cluster or changing topologic chromatin interactions because they change access to large chromosome segments. In three families, deleted DNA sequences were associated with intellectual deficits and were not included in any database of genomic variants. These sequences were thousands of bp and unequivocally matched foreign DNAs. Analogous homologies were also found in chromosome anomalies of a recurrent neurodevelopmental disorder. Viral and bacterial DNAs that match repetitive or specific human DNA segments are thus proposed to interfere with highly active break repair during meiosis, and sometimes delete polyfunctional clusters, and disable epigenetic drivers. Mis-repaired gametes produce zygotes containing rare chromosome anomalies which cause neurologic disorders and accompanying non-neurologic signs. Neurodevelopmental disorders may be examples of assault on the human genome by foreign DNA with some infections more likely tolerated because they resemble human DNA segments. Further tests of this model await new technology.

The main purpose of this study was to develop a model for predicting the quality of holes drilled in the root part of a spar of helicopter main rotor blades made of the Glass Fiber Reinforced Plastic (GFRP)-Ti multilayer polymer composite. As the main quality criterion, delaminations at the entry and exit of the drill from the hole were taken. In the experimental study a conventional drill and two modified geometry drills: a double-point angle drill and a dagger drill were used. Preliminary experiments showed the best hole quality when using modified drills, which allowed further detailed study only with both modified drills at different drilling speeds and feed rates. Its results in the form of training sets were used to build the Artificial Neural Networks (ANNs) to predict delamination at the entry and exit of drilled holes. The analysis of the fitted response functions, presented as 3D surfaces plots and superimposed contour plots, made it possible to choose the better tool - a double-point angle drill and determine the optimal area for drilling speed and feed rates, confirming that the prediction of the quality and productivity of machining composites based on ANN is an effective tool to search and quantify the quality criteria of such technologies.

Recombinant human collagen peptide (RCP) is a recombinantly created xeno-free biomaterial enriched in RGD (arginine-glycine-aspartic acid) sequences, with good processability that is being investigated for regenerative medicine applications. Recently, the biocompatibility and osteogenic ability of β-TCP/RCP (RCP granules combined with β-tricalcium phosphate (TCP) submicron particles) were demonstrated. In the present study, β-TCP/RCP was implanted into experimental periodontal tissue defects (three-walled bone defect) created in beagle dogs to investigate tissue responses and subsequent regenerative effects. Micro computed tomography image analysis at 8 weeks postoperatively showed that the amount of new bone after β-TCP/RCP graft was significantly greater (2.2 fold, P&lt;0.05) than that of the control (no graft) group. Histological findings showed that the transplanted β-TCP/RCP induced active bone-like tissue formation including TRAP-positive and OCN-positive cells as well as bioabsorbability. Ankylosis did not occur, and periostin-positive periodontal ligament-like tissue formation was observed. Histological measurements revealed that β-TCP/RCP implantation formed 1.7-fold more bone-like tissue and 2.1-fold more periodontal ligament-like tissue than the control, and significantly suppressed gingival recession and epithelial downgrowth (P&lt;0.05). These results suggest that β-TCP/RCP is effective as a periodontal tissue regenerative material.

To date, the patent foramen ovale (PFO) does not get the deserved medical attention. The PFO poses a serious threat to health and even life of mankind. The first respective case report in the medical literature dates back to the 19th century. It led to death. The fact that a PFO is present in roughly 25% of people underscores its overall potential to do harm. Yet at the same time by the sheer number, it discourages the medical community from screening for it and from treating it. About 5% of the population have particularly dangerous forms of PFOs. Such PFOs portray a high enough risk for clinical events, the likes of death, stroke, myocardial infarction, or ocular, visceral, and peripheral embolism, to justify screening for them. Highly significant health incidents being at stake, it appears obvious that PFO closure should be used for primary prevention. This is supported by the fact that closing a PFO is the simplest intervention in cardiology, with presumably the highest clinical yield. Being mainly a preventive measure, PFO closure represents a mechanical vaccination. When closing PFOs for one of the rarer therapeutic indications (migraine, platypnea orthodeoxia, etc.), patients automatically profit from the collateral benefit of getting at the same time mechanically vaccinated for life against paradoxical embolism. Vice versa, closing a PFO for prevention of paradoxical embolism not infrequently betters or cures migraine or exercise dyspnea, thereby improving quality of life as a collateral benefit.