Explore the vast range of titles available.

This study examines the effects of state ownership and its interaction with corporate governance mechanisms-specifically, the number of non-executive directors, board size and foreign ownership-on agency costs in Vietnamese-listed construction and real estate firms. Data were collected from 122 companies listed on the Vietnam Stock Exchange from 2011 to 2022. The results from the SGMM regression technique indicate that higher state ownership is associated with lower agency costs, as measured by residual losses. Furthermore, State Ownership intensifies the negative impact of foreign ownership on agency costs while weakening the reducing effects of both the size of the board of directors and the number of non-executive directors on agency costs. This highlights the need for improved oversight of the state's role within these firms.

North Atlantic midlatitude cyclones are among the most severe weather systems, causing enormous economic damages and threatening human lives. The cyclone is typically characterized by cyclonic convergent surface winds, strong updrafts, and precipitation. However, extreme surface winds are often observed within the cyclone where downdrafts develop. The present study investigates the dynamical and thermodynamical characteristics of the horizontal winds impinging on the cold frontal surface and the associated downdrafts. It is shown that the cyclonic winds into the cold frontal surface are mainly responsible for the downdrafts that transport the high‐altitude horizontal momentum to the surface and cause intense surface winds. About half of the North Atlantic midlatitude cyclones are accompanied by the downdrafts especially in the southern and western parts of the cyclone center. Plain Language Summary In the midlatitudes, air temperature decreases toward the poles, and cyclone systems typically travel eastward along regions characterized by strong meridional temperature gradients. Over the cyclone‐influencing area, the cyclonic, counterclockwise rotating, wind induces southward cold advection on the western side of the cyclone center. Therefore, during the early phase of the North Atlantic midlatitude cyclone, the generation of the cold front, which has a steep gradient of temperature to the west of the cyclone center, and that is a common feature. Even after the formation of the cold front, the horizontal winds keep impinging on the frontal surface. Then the horizontal winds blocked by the frontal surface and downdrafts are induced. The downdrafts transport the upper‐level intense wind speed to the lower level strengthening the surface winds. Key Points Surface winds within North Atlantic midlatitude cyclones are strengthened by strong downdrafts and downward momentum transports Downdrafts can be generated by the horizontal winds impinging on the cold frontal surface Cyclones tend to accompany the downdrafts more to the south and west of the cyclone center

The building sector is the largest energy consumer accounting for 40% of global energy usage. An energy forecast model supports decision-makers to manage electric utility management. Identifying optimal values of hyperparameters of prediction models is challenging. Therefore, this study develops a novel time-series Wolf-Inspired Optimized Support Vector Regression (WIO-SVR) model to predict 48-step-ahead energy consumption in buildings. The proposed model integrates the support vector regression (SVR) and the grey wolf optimizer (GWO) in which the SVR model serves as a prediction engine while the GWO is used to optimize the hyperparameters of the SVR model. The 30-min energy data from various buildings in Vietnam were adopted to validate model performance. Buildings include one commercial building, one hospital building, three authority buildings, three university buildings, and four office buildings. The dataset is divided into the learning data and the test data. The performance of the WIO-SVR was superior to baseline models including the SVR, random forests (RF), M5P, and decision tree learner (REPTree). The WIO-SVR model obtained the highest value of correlation coefficient (R) with 0.90. The average root-mean-square error (RMSE) of the WIO-SVR was 2.02 kWh which was more accurate than those of the SVR model with 10.95 kWh, the RF model with 16.27 kWh, the M5P model with 17.73 kWh, and the REPTree model with 26.44 kWh. The proposed model improved 442.0–1207.9% of the predictive accuracy in RMSE. The reliable WIO-SVR model provides building managers with useful references in efficient energy management.

This study investigates the impact of arc length, current intensity, travel speed, and gas flow rate on surface hardness and line width during arc quenching process of S45C steel. The current intensity has the greatest influence on the surface hardness of S45C steel, followed by the travel speed, gas flow rate, and arc length. Using the Taguchi method, the optimal values of the parameters such as the arc length of 1.5 mm, the current intensity of 125 A, the travel speed of 250 mm/min and the gas flow rate of 12.5 l/min were calculated. The optimal surface hardness would be 379 HV, with a standard deviation of 46.4 HV. The current intensity is the most critical component in determining line width among these parameters. The arc length ranks second, followed by the TIG gun’s travel speed. The gas flow rate is the least significant factor. A longer arc length may result in a broader heat zone, which leads to a better line width. Increasing the arc length, current intensity, travel speed, and gas flow rate results in a similar pattern of surface hardness change caused by the low-heated and over-heated phenomena. The microhardness distribution showed a hardening zone of up to 2500 μm and a maximum hardness of 453 HV. The microstructure of arc quenching samples has three zones: hardening, heat-affected, and base metal. The hardening zone exhibits a martensite microstructure with a tiny needle shape and a residual austenite matrix.

In this study, we present a novel approach to injection molding, focusing on the strength of weld lines in polyamide 6 (PA6) composite samples. By implementing a mold temperature significantly higher than the typical molding practice, which rarely exceeds 100°C, we assess the effects of advanced mold temperature management. The research introduces a newly engineered mold structure specifically designed for localized mold heating, distinguishing it as the ’novel cavity.’ This innovative design is compared against traditional molding methods to highlight the improvements in weld line strength at elevated mold temperatures. To optimize the molding parameters, we apply an Artificial Neural Network (ANN) in conjunction with a Genetic Algorithm (GA). Our findings reveal that the optimal ultimate tensile strength (UTS) and elongation values are achieved with a filling time of 3.4 seconds, packing time of 0.8 seconds, melt temperature of 246°C, and a novel high mold temperature of 173°C. A specific sample demonstrated the best molding parameters at a filling time of 3.4 seconds, packing time of 0.4 seconds, melt temperature of 244°C, and mold temperature of 173°C, resulting in an elongation value of 582.6% and a UTS of 62.3 MPa. The most influential factor on the PA6 sample’s UTS and elongation at the weld line was found to be the melt temperature, while the filling time had the least impact. SEM analysis of the fracture surfaces revealed ductile fractures with rough surfaces and grooves, indicative of the weld line areas’ bonding quality. These insights pave the way for significant improvements in injection molding conditions, potentially revolutionizing the manufacturing process by enhancing the structural integrity of the weld lines in molded PA6 samples.

In vitro maturation (IVM) of human immature oocytes has been shown to be a viable option for patients at risk of ovarian hyperstimulation syndrome (OHSS), those seeking urgent fertility preservation and in circumstances where controlled ovarian stimulation is not feasible. Moreover, IVM techniques can be combined with ovarian tissue cryobanking to increase the chances of conception in cancer survivors. The clinical applications of IVM in the field of reproductive medicine are rapidly expanding and the technique is now classified as non-experimental. In contrast to conventional IVF (in vitro fertilization), IVM offers several advantages, such as reduced gonadotropin stimulation, minimal risk of ovarian hyperstimulation syndrome (OHSS), reduced treatment times and lower costs. However, the technical expertise involved in performing IVM and its lower success rates compared to traditional IVF cycles, still pose significant challenges. Despite recent advances, such as innovative biphasic IVM systems, IVM is still an evolving technique and research is ongoing to refine protocols and identify techniques to improve its efficiency and effectiveness. A comprehensive understanding of the distinct mechanisms of oocyte maturation is crucial for obtaining more viable oocytes through in vitro methods, which will in turn lead to significantly improved success rates. In this review, the present state of human IVM programs and future research directions will be discussed, aiming to promote a better understanding of IVM and identify potential strategies to improve the overall efficiency and success rates of IVM programs, which will in turn lead to better clinical outcomes.

We describe a method for generating a video of a talking face. The method takes still images of the target face and an audio speech segment as inputs, and generates a video of the target face lip synched with the audio. The method runs in real time and is applicable to faces and audio not seen at training time. To achieve this we develop an encoder–decoder convolutional neural network (CNN) model that uses a joint embedding of the face and audio to generate synthesised talking face video frames. The model is trained on unlabelled videos using cross-modal self-supervision. We also propose methods to re-dub videos by visually blending the generated face into the source video frame using a multi-stream CNN model.

Increasing attention to the research on activity monitoring in smart homes has motivated the employment of ambient intelligence to reduce the deployment cost and solve the privacy issue. Several approaches have been proposed for multi-resident activity recognition, however, there still lacks a comprehensive benchmark for future research and practical selection of models. In this paper, we study different methods for multi-resident activity recognition and evaluate them on the same sets of data. In particular, we explore the effectiveness and efficiency of temporal learning algorithms using sequential data and non-temporal learning algorithms using temporally-manipulated features. In the experiments we compare and analyse the results of the studied methods using datasets from three smart homes.

This study aimed to compare the trueness of intraoral scanners (IOSs) according to the subgingival finish line depth of tooth preparation for fixed prostheses. The prepared maxillary right first molar was fabricated by using ceramic material. A computer-aided design (CAD) reference model (CRM) of the abutment was obtained by using a contact scanner. The subgingival finish line was located according to the depth at 0-mm, 0.25-mm, 0.5-mm, 0.75-mm, and 1-mm. CAD test models (CTMs) were obtained by using 2 IOSs (i500 and CS3600). CRM and CTM were superimposed and analyzed (Geomagic control X). The one-way analysis of variance (ANOVA) was used to compare the trueness according to the subgingival finish line depth. The paired t test was used to compare the trueness of IOSs with and without gingival retraction (α = .05). When the gingival displacement code was not used, it was observed that the trueness of both IOSs decreased significantly as the depth of the subgingival finish line increased ( P  < 0.001). When the subgingival finish line was positioned deeper than 0.5-mm, the trueness of both IOSs exceeded 100 µm in the marginal region. When the gingival displacement cord was used, the trueness of both IOSs did not exceed 100 µm regardless of the subgingival finish line depth. When gingival cord was used, it showed significantly higher trueness than when not used ( P  < 0.001). When the gingival displacement cord was not used, the trueness of IOSs decreased as the subgingival finish line depth increased. But the use of the gingival displacement cord improved the scanning trueness by 90%. Thus, it is necessary to use the gingival displacement cord according to the clinical situation to improve scan trueness at the subgingival finish line.