Terms Of Loss Research Articles

Surgical management of neck of femur fractures in patients younger than sixty-five years: a comparative study of three fixation methods.

Several surgical implants have been used for the treatment of neck of femur fracture (NOF) in younger patients such as dynamic hip screw (DHS) and cannulated compression screw. However, the superiority of one or another osteosynthesis device remains a matter of debate. The aim of this work is to evaluate and compare three fixation modalities: Cannulated Hip Screws (CHS), DHS and DHS associated to anti-rotating screw for surgical treatment of femoral neck fracture in young adults. It is a retrospective comparative study of three series of NOF fractures treated surgically over a period of ten years; including young adult patients (age > 18 years and < 65 years) treated conservatively using closed or open reduction and internal fixation. All types of NOF fractures according to Garden classification were included. Pathological, basi-cervical fractures and fractures on previously operated hips were excluded. The minimum follow-up recommended was two years. Clinical evaluation was based on the Postel Merle d'Aubigné score (PMA), the visual analogue scale (VAS), the Parker score, and the Hip Disability and Osteoarthritis Outcome Score (HOOS score). Reduction quality was assessed on X-rays. Our series included 72 patients that were divided in three groups: Group A: Fixation using cannulated hip screws (33 patients). Group B: Fixation using DHS only (21 patients). Group C: Fixation using DHS associated to anti-rotation screw (18 patients). The patients of group A had better PMA and VAS scores, but there was no statistically significant difference. However, a significant difference (p=0.001) was found for the HOOS score. The fractures treated with DHS associated with anti-rotating screws, had the highest loss of reduction in the vertical axis (Yp) with the highest femoral head collapse (Zp) values. Group A had the lowest loss of reduction in the horizontal axis (Xp). There was no significant difference between the three methods of osteosynthesis in terms of loss of correction though. We found comparable results in terms of healing and complication rates and loss of reduction for the three groups with no significant difference. However, the HOOS score was significantly better in the cannulated hip screw group.

Reliability constrained dynamic generation expansion planning using honey badger algorithm

Generation expansion planning (GEP) is a complex, highly constrained, non-linear, discrete and dynamic optimization task aimed at determining the optimum generation technology mix of the best expansion alternative for long-term planning horizon. This paper presents a new framework to study the GEP in a multi-stage horizon with reliability constrained. GEP problem is presented to minimize the capital investment costs, salvage value cost, operation and maintenance, and outage cost under several constraints over planning horizon. Added to that, the spinning reserve, fuel mix ratio and reliability in terms of Loss of Load Probability are maintained. Moreover, to decrease the GEP problem search space and reduce the computational time, some modifications are proposed such as the Virtual mapping procedure, penalty factor approach, and the modified of intelligent initial population generation. For solving the proposed reliability constrained GEP problem, a novel honey badger algorithm (HBA) is developed. It is a meta-heuristic search algorithm inspired from the intelligent foraging behavior of honey badger to reach its prey. In HBA, the dynamic search behavior of honey badger with digging and honey finding approaches is formulated into exploration and exploitation phases. Added to that, several modern meta-heuristic optimization algorithms are employed which are crow search algorithm, aquila optimizer, bald eagle search and particle swarm optimization. These algorithms are applied, in a comparative manner, for three test case studies for 6-year, 12-year, and 24-year of short- and long-term planning horizon having five types of candidate units. The obtained results by all these proposed algorithms are compared and validated the effectiveness and superiority of the HBA over the other applied algorithms.

Lumbar fusion through the anterolateral mini-approach: comparison of anterior interbody (OLIF-AF) and percutaneous pedicle (OLIF-PF) fixations in the surgical treatment of single-level stenosis

Objective. To perform comparative analysis of the clinical efficacy and safety of indirect decompression of the spinal roots and interbody fusion through the lateral pre-psoas approach (OLIF) with anterolateral (OLIF-AF) and posterior percutaneous (OLIF-PF) screw fixations in the surgical treatment of single-segment lumbar stenosis.Material and Methods. A retrospective comparative analysis of treatment of 88 patients aged 29 to 72 years with single-level lumbar stenosis was carried out. Posterior instrumental fixation (OLIF-PF) was performed in 60 cases, and anterolateral (OLIF-AF) – in 28.Results. The compared groups did not statistically significantly differ from each other in terms of age, gender, body mass index, clinical picture and duration of symptoms before surgery, assessment of neurological status according to the Zurich Claudication Questionnaire (ZCQ), preoperative diagnosis, localization of stenosis, pain assessment in the back and leg before surgery according to a digital rating scale, physical status (ASA), health assessment (SF-12, ODI), follow-up period, as well as smoking and the presence of comorbidities (p &gt; 0.05). In the OLIF-AF group, compared to the OLIF-PF group, a statistically significant advantage was found in terms of blood loss, duration of surgery and anesthesia, the level of radiological exposure, duration of patient’s hospitalization and hospital stay in the postoperative period, as well as the duration of antibiotic prophylaxis and intraoperative volume of infusions (p &lt; 0.05). Despite earlier discharge and less use of local anesthesia (35.7 % vs 73.3 %; p = 0.001), patients in the OLIF-AF group had statistically significantly lower level of back pain on the day of discharge (3.0 vs 3.5; p = 0.034) and were less likely to need opioids (3.6 % vs 31.7 %; p = 0.003). With regard to complications and adverse events, there were no statistically significant differences during dynamic follow-up period from 3 to 50 months in both groups (17.9 % vs 28.3 %; p = 0.290), including depending on the timing of complications (early or late). In addition, no statistically significant differences were found for neurological, infectious, gastrointestinal, urological, or implant-related complications (p &gt; 0.05).Conclusions. Indirect decompression of the spinal roots and interbody fusion through the lateral pre-psoas approach in combination with OLIF-AF is an effective and safe technique for the surgical treatment of single-segment lumbar stenosis. This method allows to reduce the invasiveness of surgery and severity of the pain syndrome and to create conditions for enhanced recovery after surgery. Further multicenter randomized trials are needed to comprehensively evaluate long-term outcomes.

Guided endodontics versus conventional access cavity preparation: an ex vivo comparative study of substance loss

BackgroundTo compare the outcomes of conventional access cavity preparation (CONV) versus guided endodontics (GE) for access cavity preparation in anterior teeth with pulp canal calcification (PCC) regarding root canal detection, substance loss, procedural time, and need for additional radiographs.MethodsExtracted, sound human teeth with PCC (n = 108) were matched in pairs, divided into two groups and used to produce 18 models. An independent endodontist and a general dentist performed access cavity preparation under simulated clinical conditions on nine models each (54 teeth). The endodontist used the conventional technique and the general dentist GE. Time needed to access the root canals and the number of additional radiographs were recorded. Pre- and postoperative cone-beam computed tomography scans were obtained to measure substance loss. Statistical significance was tested by examining the overlap of 95% confidence intervals (CIs) between the groups.ResultsAll root canals were successfully accessed by both methods. There were no significant differences in substance loss (CI: CONV 15.9–29.6 mm3 vs. GE 17.6-27.5mm3) or procedural time (CI: CONV 163.3-248.5 s vs. GE 231.9-326.8 s). However, 31 additional radiographs were required for GE compared to none for CONV.ConclusionsFor access cavity preparation in teeth with PCC, both CONV by a specialist and GE by a general dentist produce good results in terms of substance loss and time requirements.

Channel-assisted cervical key hole technology combined with ultrasonic bone osteotome versus posterior percutaneous endoscopic cervical foraminotomy: a clinical retrospective study

PurposeThe search for more effective and safe treatment methods for cervical spondylotic radiculopathy (CSR) has led to the rapid development and increasing popularity of minimally invasive posterior cervical foraminotomy (MI-PCF). This study aims to compare two important approaches for MI-PCF surgery: the channel-assisted cervical key hole technology combined with ultrasonic bone osteotome (CKH-UBO) and posterior percutaneous endoscopic cervical foraminotomy (PPECF).MethodsData from patients treated with single-level CKH-UBO (n = 35) or PPECF (n = 40) were analyzed. Clinical outcomes, including visual analogue scale (VAS) scores for neck and arm pain, Neck Disability Index (NDI), and modified Macnab criteria, were assessed preoperatively, as well as at three days, three months, and one year postoperatively.ResultsThe percentages of patients with excellent and good outcomes were 97.14% and 92.5%, respectively. The average surgical time in the CKH-UBO group was significantly shorter than in the PPECF group (p < 0.001), while the average incision length in the PPECF group was significantly smaller than in the CKH-UBO group. There were no significant differences between the two groups in terms of blood loss, hospital stay, and clinical outcomes at three days, three months, and 12 months postoperatively.ConclusionCKH-UBO can achieve the same surgical outcomes as PPECF for the treatment of CSR. However, CKH-UBO saves more time but requires patients to undergo larger incisions.

Viscoacoustic reverse time migration with stable and effective two-way attenuation compensation

Intrinsic attenuation in seismic wave propagation leads to amplitude dissipation and phase dispersion in seismic data. The attenuation (∼1/ Q) effect is a common cause for inaccurate image locations and dimmed image energy in reverse time migration (RTM). Conventional viscoacoustic or viscoelastic RTM methods implement attenuation compensation by reversing the sign of the amplitude loss term and keeping the dispersion term unchanged for forward and backward wavefield extrapolation, which requires the decoupled viscoacoustic wave equation and gives rise to the numerical instability issue. To address these problems, we develop a stable and effective two-way attenuation-compensated viscoacoustic RTM method. Our method uses a new two-way normalized crosscorrelation imaging condition to compensate the attenuation effect. In the new imaging condition, only the attenuated forward wavefield of sources and the viscoacoustic Green’s functions of receivers are required, which eliminates the instability source arising from the operation of reversing the sign of the dissipation term in the viscoacoustic wave equation. Because no modifications are made to the viscoacoustic wave equation, the new imaging condition can be calculated without any additional computational cost and can be applied to decoupled and coupled viscoacoustic wave equation-based RTMs, which is more flexible than other attenuation compensation strategies. Two synthetic tests and one field data example are presented to demonstrate the stability and effectiveness of our method.

Self-supervised Semantic Segmentation: Consistency over Transformation.

Accurate medical image segmentation is of utmost importance for enabling automated clinical decision procedures. However, prevailing supervised deep learning approaches for medical image segmentation encounter significant challenges due to their heavy dependence on extensive labeled training data. To tackle this issue, we propose a novel self-supervised algorithm, , which integrates a robust framework based on the proposed Inception Large Kernel Attention (I-LKA) modules. This architectural enhancement makes it possible to comprehensively capture contextual information while preserving local intricacies, thereby enabling precise semantic segmentation. Furthermore, considering that lesions in medical images often exhibit deformations, we leverage deformable convolution as an integral component to effectively capture and delineate lesion deformations for superior object boundary definition. Additionally, our self-supervised strategy emphasizes the acquisition of invariance to affine transformations, which is commonly encountered in medical scenarios. This emphasis on robustness with respect to geometric distortions significantly enhances the model's ability to accurately model and handle such distortions. To enforce spatial consistency and promote the grouping of spatially connected image pixels with similar feature representations, we introduce a spatial consistency loss term. This aids the network in effectively capturing the relationships among neighboring pixels and enhancing the overall segmentation quality. The approach iteratively learns pixel-level feature representations for image content clustering in an end-to-end manner. Our experimental results on skin lesion and lung organ segmentation tasks show the superior performance of our method compared to the SOTA approaches.

ExpertNet: A Deep Learning Approach to Combined Risk Modeling and Subtyping in Intensive Care Units.

Risk models play a crucial role in disease prevention, particularly in intensive care units (ICUs). Diseases often have complex manifestations with heterogeneous subpopulations, or subtypes, that exhibit distinct clinical characteristics. Risk models that explicitly model subtypes have high predictive accuracy and facilitate subtype-specific personalization. Such models combine clustering and classification methods but do not effectively utilize the inferred subtypes in risk modeling. Their limitations include tendency to obtain degenerate clusters and cluster-specific data scarcity leading to insufficient training data for the corresponding classifier. In this article, we develop a new deep learning model for simultaneous clustering and classification, ExpertNet, with novel loss terms and network training strategies that address these limitations. The performance of ExpertNet is evaluated on the tasks of predicting risk of (i) sepsis and (ii) acute respiratory distress syndrome (ARDS), using two large electronic medical records datasets from ICUs. Our extensive experiments show that, in comparison to state-of-the-art baselines for combined clustering and classification, ExpertNet achieves superior accuracy in risk prediction for both ARDS and sepsis; and comparable clustering performance. Visual analysis of the clusters further demonstrates that the clusters obtained are clinically meaningful and a knowledge-distilled model shows significant differences in risk factors across the subtypes. By addressing technical challenges in training neural networks for simultaneous clustering and classification, ExpertNet lays the algorithmic foundation for the future development of subtype-aware risk models.

A physically informed deep-learning approach for locating sources in a waveguide.

Inverse source problems are central to many applications in acoustics, geophysics, non-destructive testing, and more. Traditional imaging methods suffer from the resolution limit, preventing distinction of sources separated by less than the emitted wavelength. In this work we propose a method based on physically informed neural-networks for solving the source refocusing problem, constructing a novel loss term which promotes super-resolving capabilities of the network and is based on the physics of wave propagation. We demonstrate the approach in the setup of imaging an a priori unknown number of point sources in a two-dimensional rectangular waveguide from measurements of wavefield recordings along a vertical cross section. The results show the ability of the method to approximate the locations of sources with high accuracy, even when placed close to each other.

YSA ve Bukalemun Optimizasyon Algoritmalarına Dayalı DER'lerde Tekno Ekonomik için Pratik Radyal Dağıtım Besleyicisi

Distributed energy resources (DERs) are a better choice to meet load demand close to load centers. Optimal DER placement and DER ratings lead to power loss reduction, voltage profile improvement, environmental friendliness, dependability, and postponement of system changes. This study uses artificial neural networks and the Chameleon Optimization Algorithm to analyze the best integration of renewable energy sources and electric vehicles in distribution feeders to reduce power loss, regulate voltage levels, and decrease the cost and emissions under unpredictable load demand. In this study, the generated output power of the models is compared to solar photovoltaic generation systems and wind turbine generation systems. As a result, a fitness function with several objectives has been developed to reduce total active power loss while also reducing total cost and emissions generation. The study took into account the influence of EV charging/discharging behavior on the distribution system. The 28-bus rural distribution network in feeders is used to test the suggested methodology. Final analysis of the numerical results showed that the Artificial Neural Network and Chameleon Optimization Algorithms outperformed in terms of power loss (440.94 kw) and average purchase of real power (2224 kw), but these parameters do not favor the other optimization algorithms. This showed that the proposed strategy is both viable and effective.

Reflujo gastroesofágico tras gastrectomía vertical: la dimensión del problema

Sleeve gastrectomy is a safe and effective bariatric surgery in terms of weight loss and long-term improvement or resolution of comorbidities. However, its achilles heel is the possible association with the development with the novo and/or worsening of pre-existing gastroesophageal reflux disease. The anatomical and mechanical changes that this technique induces in the esophagogastric junction, support or contradict this hypothesis. Questions such as «what is the natural history of gastroesophageal reflux in the patient undergoing gastric sleeve surgery?», «how many patients after vertical gastrectomy will develop gastroesophageal reflux?» and «how many patients will worsen their previous reflux after this technique?» are intended to be addressed in the present article.

Investigative study on the properties of magnetic materials for electrical machines

&lt;p&gt;&lt;span&gt;The paper attempts to investigate the properties of the magnetic materials used in the construction of rotating electric machines, with a view to arrive at the appropriate choice for the induction motors in particular. Measurement of magnetic properties for rotating electrical machines are more important to both machine designer and operator. This paper discusses the influence of magnetic properties of electrical steel on performance of electrical machine. Here properties like BH curve, core loss, permeability and other vital parameters are measured using 400×400 Epstein tester over wide range flux density and frequency up to 50 Hz and 400 Hz. The results measured in terms of the core loss, BH curve and permeability showcase the benefits to decide on the suitability of the material for use in practice.&lt;/span&gt;&lt;/p&gt;

Antithrombotic therapy and spinal surgery: a retrospective cohort study of 289 consecutive elderly patients with degenerative lumbar stenosis.

Lumbar spinal stenosis (LSS) is a disabling degenerative process of the spine, mainly affecting older patients. LSS manifests with low-back and leg pain and neurogenic claudication. Disability and impairment in activities of daily living are consequences of the progressive narrowing of the lumbar spinal canal. Surgical decompression has been shown to be superior to conservative management. Nonetheless, intraoperative and postoperative blood loss in elderly patients taking antiplatelet or anticoagulant drugs owing to cardiovascular comorbidities may be a special issue. This study describes and compares early outcomes after surgical procedures in different groups of patients receiving antithrombotic drugs. The authors' study retrospectively recruited 289 consecutive patients aged ≥ 65 years who received lumbar decompression for spinal stenosis between January 2021 and May 2022. First, 183 patients taking antiplatelet therapy were divided into two groups according to the rationale for use: primary versus secondary prophylaxis of cardiovascular events (group 1 vs group 2). Primary prevention was stopped preoperatively, or secondary prevention was not discontinued during the perioperative period. Secondly, 106 patients who were not taking antiplatelet mediation were divided into two groups, depending on whether preoperative low-molecular-weight heparin had not been administered or had been (group A vs group B). Intraoperative blood loss, surgical time, and postoperative hospitalization were analyzed. No significant statistical differences were observed between groups 1 and 2 in terms of intraoperative blood loss and time of surgery, or between groups A and B in terms of all analyzed variables. No early or delayed complications were observed, perioperatively or during the postoperative 3-month follow-up period. The results of this study suggest that the use of anticoagulant and antiplatelet therapies in elective decompressive surgery could be devoid of early complications and could be safely continued perioperatively.

Gastroesophageal reflux after sleeve gastrectomy: The dimension of the problem

Sleeve gastrectomy is a safe and effective bariatric surgery in terms of weight loss and longterm improvement or resolution of comorbidities. However, its achilles heel is the possible association with the development with the novo and/or worsening of pre-existing gastroesophageal reflux disease. The anatomical and mechanical changes that this technique induces in the esophagogastric junction, support or contradict this hypothesis. Questions such as «what is the natural history of gastroesophageal reflux in the patient undergoing gastric sleeve surgery?», «how many patients after vertical gastrectomy will develop gastroesophageal reflux?» and «how many patients will worsen their previous reflux after this technique?» are intended to be addressed in the present article.

Optimal Resource Management for Hierarchical Federated Learning Over HetNets With Wireless Energy Transfer

Remote monitoring systems analyze the environment dynamics in different smart industrial applications, such as occupational health and safety, and environmental monitoring. Specifically, in industrial Internet of Things (IoT) systems, the huge number of devices and the expected performance put pressure on resources, such as computational, network, and device energy. Distributed training of Machine and Deep Learning (ML/DL) models for intelligent industrial IoT applications is very challenging for resource limited devices over heterogeneous wireless networks (HetNets). Hierarchical Federated Learning (HFL) performs training at multiple layers offloading the tasks to nearby Multi-Access Edge Computing (MEC) units. In this paper, we propose a novel energy-efficient HFL framework enabled by Wireless Energy Transfer (WET) and designed for heterogeneous networks with massive Multiple-Input Multiple-Output (MIMO) wireless backhaul. Our energy-efficiency approach is formulated as a Mixed-Integer Non-Linear Programming (MINLP) problem, where we optimize the HFL device association and manage the wireless transmitted energy. However due to its high complexity, we design a Heuristic Resource Management Algorithm, namely H2RMA, that respects energy, channel quality, and accuracy constraints, while presenting a low computational complexity. We also improve the energy consumption of the network using an efficient device scheduling scheme. Finally, we investigate device mobility and its impact on the HFL performance. Our extensive experiments confirm the high performance of the proposed resource management approach in HFL over HetNets, in terms of training loss and grid energy costs.

Discriminative Geometric-Structure-Based Deep Hashing for Large-Scale Image Retrieval.

Deep hashing reaps the benefits of deep learning and hashing technology, and has become the mainstream of large-scale image retrieval. It generally encodes image into hash code with feature similarity preserving, that is, geometric-structure preservation, and achieves promising retrieval results. In this article, we find that existing geometric-structure preservation manner inadequately ensures feature discrimination, while improving feature discrimination of hash code essentially determines hash learning retrieval performance. This fact principally spurs us to propose a discriminative geometric-structure-based deep hashing method (DGDH), which investigates three novel loss terms based on class centers to induce the so-called discriminative geometrical structure. In detail, the margin-aware center loss assembles samples in the same class to the corresponding class centers for intraclass compactness, then a linear classifier based on class center serves to boost interclass separability, and the radius loss further puts different class centers on a hypersphere to tentatively reduce quantization errors. An efficient alternate optimization algorithm with guaranteed desirable convergence is proposed to optimize DGDH. We theoretically analyze the robustness and generalization of the proposed method. The experiments on five popular benchmark datasets demonstrate superior image retrieval performance of the proposed DGDH over several state of the arts.

A Perceptual Shape Loss for Monocular 3D Face Reconstruction

AbstractMonocular 3D face reconstruction is a wide‐spread topic, and existing approaches tackle the problem either through fast neural network inference or offline iterative reconstruction of face geometry. In either case carefully‐designed energy functions are minimized, commonly including loss terms like a photometric loss, a landmark reprojection loss, and others. In this work we propose a new loss function for monocular face capture, inspired by how humans would perceive the quality of a 3D face reconstruction given a particular image. It is widely known that shading provides a strong indicator for 3D shape in the human visual system. As such, our new ‘perceptual’ shape loss aims to judge the quality of a 3D face estimate using only shading cues. Our loss is implemented as a discriminator‐style neural network that takes an input face image and a shaded render of the geometry estimate, and then predicts a score that perceptually evaluates how well the shaded render matches the given image. This ‘critic’ network operates on the RGB image and geometry render alone, without requiring an estimate of the albedo or illumination in the scene. Furthermore, our loss operates entirely in image space and is thus agnostic to mesh topology. We show how our new perceptual shape loss can be combined with traditional energy terms for monocular 3D face optimization and deep neural network regression, improving upon current state‐of‐the‐art results.

Isolating Features of Object and Its State for Compositional Zero-Shot Learning

The purpose of Compositional Zero Shot Learning (CZSL) is to recognize previously unseen compositions of known objects (e.g. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">apple, banana</i> ) and their states (e.g. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ripe, unripe</i> ) as seen in an image. The CZSL is a challenging problem as it is difficult to isolate the visual features of object and its states from its compositions in images. The features of a state may have wide variation across different compositions. For example, the state <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">sliced</i> has different visual features in compositions <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">sliced apple</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">sliced tomato</i> . In this paper, we attempt to solve the problem of CZSL using a two-stage recognition approach. Each stage sequentially performs recognition task utilising two distinct modalities of compositions. The modalities are image features as well as textual features representing features of objects and states respectively. We propose a novel gradient regularized loss term for better disentanglement of object and state features from the visual features of the composition. An appropriate disentanglement of the features of visual primitives (states and objects) leads to correct identification of images of unseen state-object compositions. The proposed approach and the competing methods are evaluated on three benchmark datasets, MIT States, UT-Zappos50 k and CGQA. Our extensive experiments establish the efficacy of our proposed algorithm that outperforms other state-of-the-art approaches.

Carbetocin versus Oxytocin with or without Tranexamic Acid for Prophylactic Prevention of Postpartum Hemorrhage after a Vaginal Delivery: A Randomized Clinical Trial

Objective: Our study’s primary objective was to examine the effects of four different prophylactic protocols on the prevention of postpartum hemorrhage following vaginal birth, including carbetocin only, oxytocin only, and a combination of carbetocin or oxytocin with tranexamic acid. Design: A multicentric randomized controlled trial. Participants/Materials, Setting, and Methods: This multicentric center prospective randomized controlled trial was conducted at the Department of Obstetrics and Gynecology of Bezmialem University and Van Health Teaching and Research Hospital from August 2022 to January 2023. The collected data included age, gravidity, parity, gestational age at birth, duration of delivery stages, prepartum hemoglobin and hematocrit concentrations, changes in hemoglobin and hematocrit concentrations, intrapartum blood loss, estimated blood loss after 2 h of vaginal delivery, Apgar scores at 1 and 5 min, birth weight, and neonatal intensive care unit (NICU) admission. Intrapartum blood loss was objectively measured in milliliters using a postpartum drape with a calibrated bag. The amount of bleeding was measured by subtracting the empty weight of the pads placed under the patient in the patient’s bed within 2 h after delivery. Group I: carbetocin 100 μg/mL (n = 75), group II: oxytocin 5 IU/mL (n = 75), group III: carbetocin and tranexamic acid 50 mg/mL (n = 75), group IV: oxytocin and tranexamic acid (n = 75). Results: The hemoglobin concentration decrease significantly differed between groups (1.03 ± 1.04, 1.3 ± 0.85, 1.4 ± 0.85, 1.41 ± 0.87, respectively; p < 0.001). Group 4 has the highest decrease in hemoglobin and hematocrit concentrations. When we investigated the subgroup differences, the decrease in hemoglobin concentration was significantly higher in group 2 than group 1 (1.30 ± 0.85 vs. 1.03 ± 1.04; p = 0.023), in group 2 than group 3 (1.3 ± 0.85 vs. 1.04 ± 0.9; p = 0.013), and in group 4 than group 3 (1.41 ± 0.87 vs. 1.04 ± 0.9; p < 0.001). The decrease in hematocrit level was significantly different between groups (3.07 ± 3.23, 3.55 ± 2.44, 2.13 ± 3.09, 4.25 ± 2.52; p < 0.001, respectively). No significant differences were observed in terms of mean blood loss between the four groups (277.19 ± 208.10, 294.13 ± 198.64, 274.33 ± 199.57, and 283.97 ± 178.11; p = 0.445, respectively). Furthermore, there was no significant difference between the groups in the rate of need for blood transfusion (1.3%, 5.4%, 4%, and 4%, respectively; p = 0.6). Limitations: The most important limitation of the study is a relatively small number of participants. Conclusion: In conclusion, our findings suggest that carbetocin may be more successful than oxytocin and oxytocin plus tranexamic acid regimens in terms of postpartum hemoglobin reduction, and there is no difference in terms of the need for blood transfusion when it is used for postpartum hemorrhage prophylaxis after vaginal delivery.

Comparative Study on Analysis of Losses and Leakage Current for Transformer-less Inverters for PV Applications: A Review

Abstract: The reduction in the Common Mode Voltage (CMV) and thermal losses in semiconductors play a crucial role in designing of a new transformer-less inverter topologies for solar powered applications. The galvanic isolation and the leakage current problem due to non-availability of transformer can be addressed either by providing additional switches on the dc side or on the ac side, but this results in more number of semiconductor devices being added into the conduction paths which are switched according to the desired output requirements which further results in high conduction and switching losses indirectly effecting the efficiency of the transformer-less inverters. Hence it is important to study the existing topologies in view of the total losses, CMV and leakage current parameters together. In this review paper H5, H6 and HERIC transformer-less inverter configurations in terms of CMV, Leakage current, Conduction and Switching losses as total losses have been analyzed using PSIM2022.2 simulation software package with the availability of the thermal module. The study of total losses with CMV and leakage current will help in noting the drawbacks of the topologies discussed in this paper.