Search Results (7)

Asynclitism, a misalignment of the fetal head with respect to the plane of passage through the birth canal, represents a significant obstetric challenge. High degrees of asynclitism are associated with labor dystocia, difficult operative delivery, and cesarean delivery. Despite its clinical relevance, the diagnosis of asynclitism and its influence on the outcome of labor remain matters of debate. This study analyzes the role of the degree of asynclitism (AD) in assessing labor progress and predicting labor outcome, focusing on its ability to predict intrapartum cesarean delivery (ICD) versus non-cesarean delivery. The study also aims to assess the performance of the AIDA (Artificial Intelligence Dystocia Algorithm) algorithm in integrating AD with other ultrasound parameters for predicting labor outcome. This retrospective study involved 135 full-term nulliparous patients with singleton fetuses in cephalic presentation undergoing neuraxial analgesia. Data were collected at three Italian hospitals between January 2014 and December 2020. In addition to routine digital vaginal examination, all patients underwent intrapartum ultrasound (IU) during protracted second stage of labor (greater than three hours). Four geometric parameters were measured using standard 3.5 MHz transabdominal ultrasound probes: head-to-symphysis distance (HSD), degree of asynclitism (AD), angle of progression (AoP), and midline angle (MLA). The AIDA algorithm, a machine learning-based decision support system, was used to classify patients into five classes (from 0 to 4) based on the values of the four geometric parameters and to predict labor outcome (ICD or non-ICD). Six machine learning algorithms were used: MLP (multi-layer perceptron), RF (random forest), SVM (support vector machine), XGBoost, LR (logistic regression), and DT (decision tree). Pearson’s correlation was used to investigate the relationship between AD and the other parameters. A degree of asynclitism greater than 70 mm was found to be significantly associated with an increased rate of cesarean deliveries. Pearson’s correlation analysis showed a weak to very weak correlation between AD and AoP (PC = 0.36, p < 0.001), AD and HSD (PC = 0.18, p < 0.05), and AD and MLA (PC = 0.14). The AIDA algorithm demonstrated high accuracy in predicting labor outcome, particularly for AIDA classes 0 and 4, with 100% agreement with physician-practiced labor outcome in two cases (RF and SVM algorithms) and slightly lower agreement with MLP. For AIDA class 3, the RF algorithm performed best, with an accuracy of 92%. AD, in combination with HSD, MLA, and AoP, plays a significant role in predicting labor dystocia and labor outcome. The AIDA algorithm, based on these four geometric parameters, has proven to be a promising decision support tool for predicting labor outcome and may help reduce the need for unnecessary cesarean deliveries, while improving maternal-fetal outcomes. Future studies with larger cohorts are needed to further validate these findings and refine the cut-off thresholds for AD and other parameters in the AIDA algorithm. Full article

Preservation of foods, along with health and safety issues, is a growing concern in the current generation. Essential oils have emerged as a natural means for the long-term protection of foods along with the maintenance of their qualities. Direct applications of essential oils have posed various constraints to the food system and also have limitations in application; hence, encapsulation of essential oils into biopolymers has been recognized as a cutting-edge technology to overcome these challenges. This article presents and evaluates the strategies for the development of encapsulated essential oils on the basis of fascination with the modeling and shuffling of various biopolymers, surfactants, and co-surfactants, along with the utilization of different fabrication processes. Artificial intelligence and machine learning have enabled the preparation of different nanoemulsion formulations, synthesis strategies, stability, and release kinetics of essential oils or their bioactive components from nanoemulsions with improved efficacy in food systems. Different mathematical models for the stability and delivery kinetics of essential oils in food systems have also been discussed. The article also explains the advanced application of modeling-based encapsulation strategies on the preservation of a variety of food commodities with their intended implication in food and agricultural industries. Full article

With the gradual operation of large-capacity HVDC transmission, HVDC), the characteristics of the “strong and weak communication” of the power grid are increasingly obvious. The power impact of the DC line after locking has a great impact on the power angle stability of the system and seriously threatens the transient stability of the delivery end system. By establishing the equivalent model of the AC/DC system with the energy storage power station and analyzing the transient process after DC locking, we propose a control strategy for the transient stability of the energy storage system and the delivery system after DC locking. This strategy controls the charge and discharge of the energy storage system by collecting real-time power angle and voltage data of the grid, uses the equal area rule, and initiates the cutting machine after the energy storage system is withdrawn. To verify the validity and correctness of the proposed method, a simulation analysis was performed in a modified cross-flow CEPRI-36 node AC–DC system. Full article

Research on stimuli-responsive host–guest systems is at the cutting edge of supramolecular chemistry, owing to their numerous potential applications such as catalysis, molecular machines, and drug delivery. Herein, we present a multi-responsive host–guest system comprising azo-macrocycle 1 and 4,4′-bipyridinium salt G1 for pH-, photo-, and cation- responsiveness. Previously, we reported a novel hydrogen-bonded azo-macrocycle 1. The size of this host can be controlled through light-induced E↔Z photo-isomerization of the constituent azo-benzenes. The host is found in this work to be capable of forming stable complexes with bipyridinium/pyridinium salts, and implementing guest capture and release with G1 under light in a controlled manner. The binding and release of the guest in the complexes can also be easily controlled reversibly by using acid and base. Moreover, the cation competition-induced dissociation of the complex 1a₂⊃G1 is achieved. These findings are expected to be useful in regulating encapsulation for sophisticated supramolecular systems. Full article

A conduction transformation-based coordination method for product structure optimization design was proposed for the conflict between satisfying product functional requirements and realizing adaptive modification. Customer functional requirements were analyzed hierarchically, the extension domains that indicated the matching degree between customer requirement and product function were delimited; and then a multi-layer function-behavior-structure (FBS) mapping model was established. Product function-structure correlation analysis was carried out in two dimensions, i.e., “structure-structure”, and “structure-function”; a product structure behavior function (SBF) reverse conduction model was constructed based on FBS decomposition model; thus, to realize reverse conduction from structure layer to function layer. For conflict coordination in structure modification, extension transformation operations were created, the conduction transformation trigger unit was extracted, and the trigger condition was also clarified; thus, the coordination strategy for the contradiction in adaptive design could be generated by conducting active and conduction transformations. Finally, the effectiveness and feasibility of this method were verified with the structure optimization design of a delivery system of cutting machine as an example; and the discussion section emphasized that this proposed method used conduction transformation to address design conflict, instead of generating the optimal change propagation path, and how to obtain innovation inspiration. Full article

We describe the manufacture of low-cost microfluidic systems to produce nanoscale liposomes with highly uniform size distributions (i.e., low polydispersity indexes (PDI)) and acceptable colloidal stability. This was achieved by exploiting a Y-junction device followed by a serpentine micromixer geometry to facilitate the diffusion between the mixing phases (i.e., continuous and dispersed) via advective processes. Two different geometries were studied. In the first one, the microchannels were engraved with a laser cutting machine on a polymethyl methacrylate (PMMA) sheet and covered with another PMMA sheet to form a two-layer device. In the second one, microchannels were not engraved but through-hole cut on a PMMA sheet and encased by a top and a bottom PMMA sheet to form a three-layer device. The devices were tested out by putting in contact lipids dissolved in alcohol as the dispersed phase and water as the continuous phase to self-assemble the liposomes. By fixing the total flow rate (TFR) and varying the flow rate ratio (FRR), we obtained most liposomes with average hydrodynamic diameters ranging from 188 ± 61 to 1312 ± 373 nm and 0.30 ± 0.09 PDI values. Such liposomes were obtained by changing the FRR from 5:1 to 2:1. Our results approached those obtained by conventional bulk synthesis methods such as a thin hydration bilayer and freeze-thaw, which produced liposomes with diameters ranging from 200 ± 38 to 250 ± 38 nm and 0.30 ± 0.05 PDI values. The produced liposomes might find several potential applications in the biomedical field, particularly in encapsulation and drug delivery. Full article

The need for machining advanced materials has increased exponentially in recent years. Ni-based alloys, Ti-based alloys or some steel grades are commonly used in transport, energy generation or biomedicine industries due to their excellent properties that combine hardness, high temperature strength and corrosion resistance. These desirable properties make such alloys extremely difficult to machine, inducing a quick cutting tool wear that must be overcome. In the last decade, cryogenic machining has emerged in order to improve the machining of these materials. By means of cryogenic fluids such as cutting coolants, significant improvements in the life of cutting tools are obtained. However, most studies on this new technology are focused on turning processes, because of the difficulty of introducing cryogenic fluids through a rotary tool in processes such as drilling and milling. In this study, a cryogenic milling system integrated within the tool holder is used for milling Gamma TiAl, Inconel 718 and grade EA1N steel using carbon dioxide as a coolant. This system has been compared with the traditional cooling method (emulsion) in terms of tool life to check if it is possible to improve the machining operation in terms of efficiency by supplying the cryogenic coolant directly to the cutting zone. The results show that by replacing traditional pollutant cooling fluids with other more ecologically-friendly alternatives, it is possible to improve tool life by 100% and 175% in the cases of Gamma TiAl and grade EA1N steel, respectively, when using the new delivery system for the coolant. Full article