Search Results (26)

Objectives: To describe the perinatal outcomes of a series of monochorionic diamniotic (MCDA) twin pregnancies complicated by selective fetal growth restriction (sFGR), classified according to the umbilical artery (UA) Doppler flow pattern of the smaller twin, and managed in a single centre over a 12-year period. Methods: Retrospective cohort study involving MCDA twin pregnancies followed up at the Twin Pregnancy Care Unit of Sant’Anna Hospital, Turin, Italy, between January 2010 and May 2023. We compared perinatal outcomes of MCDA pregnancies classified based on the UA Doppler flow pattern of the smaller twin. Results: The percentage of sFGR in our sample was 14.8%. A total of 103 MCDA pregnancies with sFGR were included. In 34.9% cases, the UA flow pattern changed throughout pregnancy. At last examination, 58.3% cases were classified as type I, 25.2% as type II and 16.5% as type III. The perinatal survival rate of both twins in type I and III was 100%, in type II 88.5%. Type II sFGR had the highest perinatal mortality rate (7.7%). Type III twins were more likely to have malformations compared to type II and type I; compared to type I sFGR babies, they were more likely to develop RDS and to be admitted to NICU, where the length of stay was longer. Conclusions: Although the UA flow pattern correlates with perinatal outcome, it can change throughout pregnancy. Type III sFGR may have lower risk of fetal demise than traditionally thought. The main challenge remains finding the optimal balance between adverse outcomes and premature birth. Full article

It is increasingly recognized that the twin transitions of digitalization and green transformation are pivotal to achieving sustainable development. This study examines how digital trade affects corporate green total factor productivity (GTFP), using panel data from Chinese A-share listed firms and 287 prefecture-level cities in Mainland China from 2012 to 2022. The results demonstrate that digital trade exerts a significant positive impact on GTFP, primarily through improvements in technical efficiency, with heterogeneous effects across different stages of the corporate life cycle. Endogeneity concerns are carefully addressed through instrumental variable estimation and quasi-experimental designs, and robustness checks confirm the reliability of the findings. Mechanism analyses further reveal that digital trade enhances GTFP by stimulating green technological innovation and optimizing supply chain management. Importantly, threshold regression reveals non-linear effects. Both the level of digital trade and institutional factors, such as environmental regulation, intellectual property protection, and market integration, moderate the relationship between digital trade and GTFP in U-shaped, N-shaped, and other positive non-linear patterns. These insights enhance the understanding of how digitalization interacts with institutional contexts to drive sustainable productivity growth, providing practical implications for policymakers seeking to optimize digital trade strategies and complementary regulatory frameworks. Full article

Artificial Intelligence has recently expanded across various applications. Machine Learning, a subset of Artificial Intelligence, is a powerful technique for identifying patterns in data to support decision making and managing the increasing volume of information. Simultaneously, Digital Twins have been applied in several fields. In this context, combining Digital Twins, Machine Learning, and Smart Buildings offers significant potential to improve energy efficiency and operational effectiveness in building management. This review aims to identify and analyze studies that explore the application of Machine Learning and Digital Twins for operation and energy management in Smart Buildings, providing an updated perspective on these rapidly evolving topics. The methodology follows the PRISMA guidelines for systematic reviews, using Scopus and Web of Science databases. This review identifies the main concepts, objectives, and trends emerging from the literature. Furthermore, the findings confirm the recent growth in research combining Machine Learning and Digital Twins for building management, revealing diverse approaches, tools, methods, and challenges. Finally, this paper highlights existing research gaps and outlines opportunities for future investigation. Full article

Digital Twins (DTs) of buildings can generate large volumes of dynamic data from various sources (e.g., sensors and IoT devices), enabling real-time representation of physical building states in a digital environment. Although machine learning (ML) techniques are increasingly used to predict building energy consumption from this DT data, existing approaches often lack scalability in handling data growth (data scalability) and/or adapting to evolving data patterns (model scalability). This study aims to address both drawbacks by developing a scalable cloud-based framework for the prediction of the building energy consumption. A key contribution to the field is the inclusion of a “monitoring and maintenance” module, which continuously evaluates model performance and triggers retraining only when needed. This enables timely adaptation of the ML model while avoiding unnecessary retraining and the associated computational costs. The framework was implemented and tested in a case study of a commercial building for 90 days, demonstrating its applicability. In a practical setting, the developed model could detect anomalies in time when the accuracy declined below the set threshold (70%) for five days and prevented unnecessary retraining of ML models. The findings support the feasibility of using cloud-based approaches to implement scalable ML models for energy prediction in buildings. Full article

This study assesses the wind resistance and vortex-induced vibration (VIV) risks of the Dongzhou River Bridge in China reconstruction during critical construction stages. Computational Fluid Dynamics (CFD) simulations analyzed wind effects when the twin main girders were maximally separated, revealing asymmetric vortex shedding patterns influenced by upstream–downstream aerodynamic interactions. The upstream girder’s wake generated complex flow fields, increasing turbulence on the downstream girder and indicating elevated VIV susceptibility. A 1:50 scale aeroelastic model validated these findings through wind tunnel tests, confirming that CFD-predicted critical VIV wind speeds aligned with experimental observations. Tests identified a distinct “jump-like” vibration mode at specific wind speeds (35–40 m/s full-scale equivalent), characterized by abrupt amplitude escalation rather than gradual growth—a signature of unstable VIV resonance. However, measured amplitudes remained below the 61.5 mm full-scale equivalent safety threshold, confirming that vibrations posed no critical risk. While aerodynamic coupling between girders requires monitoring during cantilever construction, the study concludes that existing control measures ensure safe construction and operation without structural modifications. These results provide actionable guidelines for wind risk mitigation through construction sequencing and real-time wind speed restrictions. Full article

Agrivoltaics is defined as “the dual use of land for solar energy production and agriculture”. On this topic, a number of issues are still to be properly addressed, e.g., how the shading effect of the solar panels affects crop growth. In this work, the development of a large-scale digital twin model to predict crop yield under varying solar panel coverage is discussed. A framework is proposed to exploit Internet of Things (IoT) concepts, with a sensor network to collect data on the field merged with sensor fusion to possibly handle information gathered by satellite images. The aim of the entire work is related to the synergic optimization of energy production and crop yield, and data analytics based on artificial intelligence tools are to be extensively developed. Herein, the results are reported of an experimental activity, currently under way at the Fantoli laboratory of Politecnico di Milano. Wooden panels, placed above the crops with a varying pattern, are used to study the shading effect with a specific target on the conditions typical of Northern Italy. The laboratory facility is equipped with a comprehensive sensor network to acquire the data necessary to build the targeted large-scale digital twin of the agrivoltaic system. Full article

The widespread adoption of arc additive manufacturing techniques across various industries has advanced the field of SS316L stainless steel manufacturing. It is crucial to acknowledge that different welding modes exert distinct influences on the forming and mechanical performance. This study analyzed the thermal input associated with four specific welding modes in LORCH MIG welding, clarifying the transition dynamics of molten droplets through waveform analysis and examining the resultant effects on microstructure and performance characteristics. The Pulse, Speed-Pulse-XT, and Twin-Pulse modes were found to induce spatter during the manufacturing process, consequently reducing molding efficiency in comparison to the SA-XT mode. Notably, the Twin-Pulse mode, characterized by double-pulse agitation, generated fish scale patterns along the lateral surfaces of the fabricated parts, promoting anisotropic grain growth. This microstructural refinement, compared to single-pulse samples with equivalent thermal input, resulted in enhanced mechanical properties. Nevertheless, the horizontal tensile strength of the three pulse modes was lower than the industrial standard for SA-XT mode and forging. In contrast, the SA-XT mode with an average hardness of 168.1 ± 6.9 HV and a tensile strength of 443.58 ± 5.7 MPa. Therefore, while three pulse modes offer certain microstructural advantages, the SA-XT mode demonstrates superior overall performance. Full article

Monitoring weight development is essential for decision-making and assessing the effectiveness of management strategies. However, this practice is often hindered by the lack of scales on farms. This study aimed to characterize the weight development and growth curves of male and female Santa Inês lambs from birth to weaning, managed on pasture with creep-fed concentrate supplementation. Data from 212 lambs during the pre-weaning phase were analyzed. The animals were weighed every seven days to evaluate total weight gain and average daily gain. Biometric measurements were taken every 28 days. Mixed models were used to assess the effects of sex and birth type on birth and weaning weights. Simple and multiple linear regression models were employed to estimate live weight using biometric measurements. The non-linear Gompertz model was utilized to describe weight development and formulate growth curves. Results were considered significant at p < 0.05. An interaction effect between birth type and sex (p < 0.05) was noted for birth weight, with the lowest weight observed in twin-birth females (2.96 kg) and the highest in single-birth males (3.73 kg) and females (3.65 kg) (p > 0.05). Birth type significantly influenced average daily gain, total weight gain, and weaning weight (p < 0.05). The Gompertz model accurately depicted the growth curves, effectively describing the weight development. Pearson’s correlation coefficients between biometric measurements and weight were positive and significant (p < 0.05), ranging from 0.599 for hip height to 0.847 for heart girth. Consequently, the simple and multiple regression equations demonstrated high precision in predicting weaning weight. In conclusion, twin-birth lambs receiving concentrate supplementation via creep-feeding and managed on pasture showed different developmental patterns compared to single-birth lambs under the same conditions. The Gompertz model proved effective for monitoring development during the pre-weaning phase. All simple and multiple linear regression models were effective in predicting weaning weight through biometric measurements. However, for practical application, the model incorporating two measurements—body length and abdominal circumference—is recommended. Full article

The construction sector of Pakistan is on a cross-growth trajectory, developing under the twin pressures of emerging infrastructure-based demands and sustainable practices that need to be inculcated urgently. This article focuses on the critical evaluation of sustainable waste management practices within the fast-developing construction industry of Pakistan, and clearly delineates a research gap in the current methodologies and use of data combined with the absence of a strategy for effective management of concrete waste. This research aims to utilize an algorithm based on machine learning that will provide accurate prediction in the generation of construction waste by harnessing the potential of real-time data for improved sustainability in the construction process. This research has identified fundamental factors leading systematically to the generation of concrete waste by creating an extensive dataset from construction firms all over Pakistan. This research study also identifies the potential concrete causes and proposed strategies towards the minimization of waste with a strong focus on the reuse and recycling of the same concrete material to enhance the adoption of sustainable practices. The prediction of the model indicates that the volumes of construction are to increase to 158 cubic meters by 2030 and 192 cubic meters by 2040. Further, it projects the increase in concrete construction waste volumes to 223 cubic meters by the year 2050 through historical wastage patterns. Full article

Background and Objectives: Neonates born from thawed embryo transfers tend to have a significantly higher birthweight compared to those from fresh embryo transfers. The aim of this study was to compare the crown-rump length (CRL) between thawed and fresh embryos to investigate the potential causes of different growth patterns between them. Materials and Methods: This was a retrospective study (July 2010–December 2023) conducted at the Third Department of Obstetrics and Gynecology, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Greece. In total, 3082 assisted reproductive technology (ART) pregnancies (4044 embryos) underwent a routine scan at 11⁺⁰–13⁺⁶ gestational weeks and were included in the study. Maternal age, the type of embryo transfer (thawed vs. fresh, donor vs. their own oocytes), CRL, twin and singleton gestations were analyzed. Results: The mean maternal age in thawed was significantly higher than in fresh embryos (39.8 vs. 35.8 years, p-value < 0.001). The mean CRL z-score was significantly higher in thawed compared to fresh embryo transfers (0.309 vs. 0.199, p-value < 0.001). A subgroup analysis on singleton gestations showed that the mean CRL z-score was higher in thawed blastocysts compared to fresh (0.327 vs. 0.215, p-value < 0.001). Accordingly, an analysis on twins revealed that the mean CRL z-score was higher in thawed blastocysts (0.285 vs. 0.184, p-value: 0.015) and in oocytes’ recipients compared to own oocytes’ cases (0.431 vs. 0.191, p-value: 0.002). Conclusions: The difference in CRL measurements between thawed and fresh embryos may be a first indication of the subsequent difference in sonographically estimated fetal weight and birthweight. This finding highlights the need for additional research into the underlying causes, including maternal factors and the culture media used. Full article

Transition delaying is of great importance for the drag and heat flux reduction of hypersonic flight vehicles. The first mode, with low frequency, and the second mode, with high frequency, exist simultaneously during the transition through the hypersonic boundary layer. This paper proposes a novel bi-frequency synthetic jet to suppress low- and high-frequency disturbances at the same time. Orthogonal table and variance analyses were used to compare the control effects of jets with different positions (USJ or DSJ), low frequencies (f₁), high frequencies (f₂), and amplitudes (a). Linear stability analysis results show that, in terms of the growth rate varying with the frequency of disturbance, an upstream synthetic jet (USJ) with a specific frequency and amplitude can hinder the growth of both the first and second modes, thereby delaying the transition. On the other hand, a downstream synthetic jet (DSJ), regardless of other parameters, increases flow instability and accelerates the transition, with higher frequencies and amplitudes resulting in greater growth rates for both modes. Low frequencies had a significant effect on the first mode, but a weak effect on the second mode, whereas high frequencies demonstrated a favorable impact on both the first and second modes. In terms of the growth rate varying with the spanwise wave number, the control rule of the same parameter under different spanwise wave numbers was different, resulting in a complex pattern. In order to obtain the optimal delay effect upon transition and improve the stability of the flow, the parameters of the bi-synthetic jet should be selected as follows: position it upstream, with f₁ = 3.56 kHz, f₂ = 89.9 kHz, a = 0.009, so that the maximum growth rate of the first mode is reduced by 9.06% and that of the second mode is reduced by 1.28% compared with the uncontrolled state, where flow field analysis revealed a weakening of the twin lattice structure of pressure pulsation. Full article

The enzootic abortion of ewes, caused by the bacterium Chlamydia abortus (C. abortus), is one of the main causes of abortion in sheep. There are multiple contributory factors, including chlamydial growth, host immune response, and hormonal balance, that result in different pregnancy outcomes, such as abortion, the birth of weak lambs that may die, or healthy lambs. This study aimed to determine the relationship between phenotypical patterns of immune cell infiltration and different pregnancy outcomes in twin-bearing sheep (both lambs born dead; one alive and one dead; both alive) when experimentally infected with C. abortus. Both the sheep uteri and placentae were collected after parturition. All samples were analysed for specific immune cell features, including cell surface antigens and the T-regulatory (Treg) cell-associated transcription factor and cytokines, by immunohistochemistry and in situ hybridisation. Some of these immunological antigens were evaluated in ovine reproductive tissues for the first time. Differential patterns of T helper/Treg cells revealed significant group effects in the placentae. It suggests the potential role that the balance of lymphocyte subsets may play in affecting different pregnancy outcomes in C. abortus-infected sheep. The present study provides novel detailed information about the immune responses observed at the maternofoetal interface in sheep at the time of pre-term abortion or lambing. Full article

Caudofoveates are benthic organisms that reside in the deep waters of continental slopes in the world. They are considered to be a group that is of phylogenetic and ecological importance for the phylum Mollusca. However, they remain poorly studied. In this work, we revealed the structure of the spicules of Caudofoveatan mollusks Falcidens sp. The spicules presented a hierarchical organization pattern across different length scales. Various imaging and analytical methods related to light and electron microscopy were employed to characterize the samples. The primary imaging methods utilized included: low voltage field emission scanning electron microscopy (FEG-SEM), focused ion beam-scanning electron microscopy (FIB-SEM), high-resolution transmission electron microscopy (HRTEM), atomic force microscopy (AFM), and electron diffraction. In addition, we performed a physicochemical analysis by electron energy loss spectroscopy (EELS) and energy dispersive X-ray spectroscopy (EDS). A crucial factor for successfully obtaining the results was the preparation of lamellae from the spicules without damaging the original structures, achieved using FIB-SEM. This allowed us to obtain diffraction patterns of significant areas of well-preserved sections (lamellae) of the spicules in specific directions and demonstrate for the first time that the bulk of these structures is organized as a single crystal of calcium carbonate aragonite. On the other hand, AFM imaging of the spicules’ dorsal surface revealed a wavy appearance, composed of myriads of small, pointed crystallites oriented along the spicules’ longer axis (i.e., the c-axis of the aragonite). The organization pattern of these small crystallites, the possible presence of twins, the relationship between confinement conditions and accessory ions in the preference for mineral polymorphs, and the single crystalline appearance of the entire spicule, along with the observation of growth lines, provide support for further studies employing Caudofoveata spicules as a model for biomineralization studies. Full article

This study provides new unique information on bovine twin pairs during the late embryonic period (28–34 days of pregnancy) in relation to (1) a predictive ultrasound measurement that was differential for sexing heterosexual twins; (2) intrauterine embryonic growth patterns in twin pairs; and (3) a higher vulnerability of female embryos compared to males following an induced embryo reduction in heterosexual twins. The study population comprised 92 dairy cows carrying bilateral twins. A length difference between co-twins equal to or greater than 25% in around 50% of pregnancies served to determine the sex of embryos with 100% accuracy in heterosexual twins, which was assessed four weeks later on the remaining fetus after twin reduction. The apparent rates of growth of twin pairs and of individual male and female embryos from day 28 to 34 of gestation were similar to established growth pattern standards for singletons. Mean embryo sizes in relation to gestational age were smaller by some 5 days’ growth equivalent in twins compared to singletons. After the reduction in the female embryo in heterosexual twins, the risk of male embryo loss was null. This new information allowed for sex selection at the time of twin reduction. Full article

As the lightest engineering materials, magnesium alloys have been widely used. Because of the specific chemical and physical characteristics, the weldability of magnesium alloy is poor. Adopting suitable welding technology and improving the quality of magnesium alloy welded joints is key to their successful application. According to previous research data, it was found that the combined action of magnetic field and activated flux has a positive effect on improving-welding efficiency and improving the properties of a welded joint, butanalysis of microstructure evolution is insufficient. In this paper, AZ91 magnesium alloy was welded by TIG welding with activated flux and external longitudinal AC magnetic field. The phase composition and microstructure evolution were investigated. The experimental results revealed that the phase composition of welded joint was not changed due to the introduction of the magnetic field and activated flux, the growth patterns of grain in the weld seam and heat-affected zone were different. When the activated flux amount was 3 mg/cm² with the effect of the magnetic field, the grain size of the weld seam was the finest, which was 18.96 μm. However, the grain size of the weld seam was larger than that of base metal. The crystallographic characteristics of grain boundaries in the weld seam and base metal were both LAGBs. The microstructure of the weld seam was messier than the base metal due to the larger misorientation angle. Under the combined action of the magnetic field and activated flux, the crystallization nucleation condition of the molten pool was changed, the formation of twins was promoted, and the crystal could selectively grow parallel with the (0001) basal plane. Full article