A Multidisciplinary Full Mouth Rehabilitation Of Non - Syndromic Oligodontia Using Twin Stage Hobo’s Technique – A Case Report.

Aims & Objectives Oligodontia is designated as the congenital agenesis of six or more permanent teeth, excluding third molars. Thus the comprehensive management of such a condition is always challenging and requires a multi-disciplinary approach involving orthodontic, oral surgical, periodontic and prosthodontic specialties. The purpose of this article is to throw light on the fact that early diagnosis and comprehensive treatment phases are essential for a successful treatment outcome. Case  description This case report presents a multidisciplinary management of a 20- year old female patient of familial non-syndromic oligodontia with congenitally missing eight permanent teeth. The first phase of therapy aimed at a pre-prosthetic orthodontic space gain, alignment, canine uprighting and corrections of intermaxillary relations as a pre-requisite for better treatment outcome. Phase two therapy was the full mouth rehabilitation of the entire dentition using ‘Twin stage Hobo technique’ at an increased vertical dimension of 3mm. Conclusion The prosthodontic rehabilitation was completed using tooth supported fixed metal ceramic restorations. These full mouth fixed restorations successfully restored function and esthetics

Microwave Detection Optimization of Disbond in Layered Dielectrics with Varying Thickness

The detection sensitivity optimization of air disbond in layered dielectric composites, using an open-ended rectangular waveguide, is studied both theoretically and experimentally. The sensitivity of the disbond detection is strongly influenced by the proper choice of parameters such as the operating frequency and the layered composite geometry (conductor backed or terminated by an infinite half-space of air). The capability of optimizing the measurement system parameters to detect and estimate the thickness of a disbonded layer independent of some changes in the thickness of the dielectric coating is also demonstrated. The impact of the parameters influencing detection optimization is theoretically investigated and then experimentally verified

A prospective study of clinical and diagnostic methods of ovarian tumors admitted in a tertiary care hospital and its correlation with histopathology

Background: Aim of the study was to study demographic profile and diagnostic modalities of ovarian tumors and their correlation with histopathological report (HPR).Methods: Prospective observational study conducted in NSCB medical college, Jabalpur from February 2019 to July 2020 on subjects with ultrasonographically diagnosed ovarian tumors. Relevant history obtained, gynecologic examination, investigations recorded. Subjects followed up to collection of HPR and correlation with histopathology done.Results: Out of 120 cases of ovarian tumors, 39.16% were malignant and 60.83% were benign ovarian tumors. Out of 80 premenopausal females, majority (78.75%) had benign ovarian masses. Amongst 40 postmenopausal females, 75% of ovarian masses were malignant. CA125 had sensitivity 76.59%, specificity 76.71% and accuracy 76.66% in diagnosing ovarian malignancy. Amongst 4 RMI scores, RMI 1 has the highest sensitivity and specificity 85.10%, 86.30% respectively. Sensitivity, specificity, and accuracy of ultrasound score was 65.21%, 86.30% and 77.5% respectively. Sensitivity and specificity of clinical diagnosis was 83% and 95.89% respectively and ROC analysis showed clinical diagnosis can accurately predict benign and malignant ovarian tumors in 89% cases.Conclusions: RMI 1 score has the highest sensitivity and specificity in our study. When all 4 methods of diagnosis i.e., RMI Score, ultrasound score, CA125 and clinical diagnosis were compared, clinical diagnosis has highest prediction of malignancy

Discovering Symbolic Laws Directly from Trajectories with Hamiltonian Graph Neural Networks

The time evolution of physical systems is described by differential equations, which depend on abstract quantities like energy and force. Traditionally, these quantities are derived as functionals based on observables such as positions and velocities. Discovering these governing symbolic laws is the key to comprehending the interactions in nature. Here, we present a Hamiltonian graph neural network (HGNN), a physics-enforced GNN that learns the dynamics of systems directly from their trajectory. We demonstrate the performance of HGNN on n-springs, n-pendulums, gravitational systems, and binary Lennard Jones systems; HGNN learns the dynamics in excellent agreement with the ground truth from small amounts of data. We also evaluate the ability of HGNN to generalize to larger system sizes, and to hybrid spring-pendulum system that is a combination of two original systems (spring and pendulum) on which the models are trained independently. Finally, employing symbolic regression on the learned HGNN, we infer the underlying equations relating the energy functionals, even for complex systems such as the binary Lennard-Jones liquid. Our framework facilitates the interpretable discovery of interaction laws directly from physical system trajectories. Furthermore, this approach can be extended to other systems with topology-dependent dynamics, such as cells, polydisperse gels, or deformable bodies

StriderNET: A Graph Reinforcement Learning Approach to Optimize Atomic Structures on Rough Energy Landscapes

Optimization of atomic structures presents a challenging problem, due to their highly rough and non-convex energy landscape, with wide applications in the fields of drug design, materials discovery, and mechanics. Here, we present a graph reinforcement learning approach, StriderNET, that learns a policy to displace the atoms towards low energy configurations. We evaluate the performance of StriderNET on three complex atomic systems, namely, binary Lennard-Jones particles, calcium silicate hydrates gel, and disordered silicon. We show that StriderNET outperforms all classical optimization algorithms and enables the discovery of a lower energy minimum. In addition, StriderNET exhibits a higher rate of reaching minima with energies, as confirmed by the average over multiple realizations. Finally, we show that StriderNET exhibits inductivity to unseen system sizes that are an order of magnitude different from the training system

Impact of morphine use in acute cardiogenic pulmonary oedema on mortality outcomes:a systematic review and meta-analysis

Background: Morphine is commonly used in the management of acute cardiogenic pulmonary oedema. The European Society of Cardiology (ESC) and National Institute for Health and Care Excellence (NICE) do not recommend the routine use of opioids in acute heart failure (AHF) due to dose-dependent side effects. However, the effect of morphine remains unclear. Our study aims to investigate the link between morphine use in acute cardiogenic pulmonary oedema and mortality. Methods: PubMed and Embase databases were searched from inception to October 2021. All studies were included (randomized, non-randomized, observational, prospective and retrospective). The references for all the articles were reviewed for potential articles of interest with no language restrictions. Studies looking at in-hospital mortality along with other outcomes were chosen. The Newcastle–Ottawa scale was used to appraise the studies. Heterogeneity was assessed using I 2. Meta-analysis was conducted using the Review Manager Software version 5.3 (The Nordic Cochrane Centre, The Cochrane Collaboration, 2014), by computing odds ratios (ORs) for pooled in-hospital mortality and clinical outcomes. Results: Six observational studies out of the 73 publications identified were eligible for the meta-analysis giving a total sample size of 152,859 (mean age 75, males 48%). Of these, four were retrospective analyses. The use of morphine in acute cardiogenic pulmonary oedema was associated with an increased rate of in-hospital mortality [OR = 2.39, confidence interval (CI) = 1.13 to 5.08, p = 0.02], increased need for invasive ventilation (OR = 6.14, CI = 5.84 to 6.46, p < 0.00001), increased need for non-invasive ventilation (OR = 1.85, CI = 1.45 to 2.36, p < 0.00001) and increased need for vasopressors/inotropes (OR = 2.93, CI = 2.20 to 3.89, p < 0.00001). Conclusion: Based on the observational studies, morphine use in acute cardiogenic pulmonary oedema is associated with worse outcomes. Further randomized controlled trials are needed to confirm any causative effect of morphine on mortality rates in acute cardiogenic pulmonary oedema

Sistem Otomatisasi Pengkondisian Suhu, pH, dan Kejernihan Air Kolam Pada Pembudidayaan Ikan Patin

Sistem Otomatisasi Pengkondisian Suhu, pH,dan Kejernihan Air Kolam Pada Pembudidayaan IkanPatin merupakan rancang bangun suatu sistem yangdapat memantau suhu, pH, dan kejernihan air kolam,serta dapat mengkondisikannya kedalam parameterparameteryang ditentukan. Dalam hal ini ikan patindipilih sebagai subjek perancangan untuk menentukanparameter suhu, pH, dan kejernihan agar mudahmelakukan analisa. Pada dasarnya alat ini dapat dipakaiuntuk semua kolam ikan, hanya parameter-parameternyayang berbeda sesuai kebutuhan. Pada pembudidayaan,dalam usia enam bulan ikan patin bisa mencapai panjang35-40 cm. Ikan patin merupakan salah satu ikan air tawaryang memiliki peluang ekonomi untuk dibudidayakan.Ikan patin dikenal sebagai komoditi yang berprospekcerah, karena memiliki harga jual yang tinggi. Hal inilahyang menyebabkan ikan patin mendapat perhatian dandiminati oleh para pengusaha untukmembudidayakannya. Pada tulisan ini telah didesainsuatu instrument yang dapat membantu para pengusahaikan patin untuk mendapatkan hasil panen yangmemuaskan.Kata Kunci—Sistem otomatisasi, Sensor Suhu, SensorpH, Sensor Kejernihan Air, Ikan Patin

Real-Time and On-Line Near-Field Microwave Inspection of Surface Defects in Rolled Steel

The potential and limitations of near-field microwave inspection techniques for detecting various surface defects in rolled steel have been investigated. The focus of this study has been to investigate this potential for tin mill products containing gross and subtle defects including steel induced defects, roll marks, holes, scratches and gouges

Neuronal Glud1 (Glutamate Dehydrogenase 1) Over-Expressing Mice: Increased Glutamate Formation and Synaptic Release, Loss of Synaptic Activity, and Adaptive Changes in Genomic Expression

Glutamate dehydrogenase 1 (GLUD1) is a mitochondrial enzyme expressed in all tissues, including brain. Although this enzyme is expressed in glutamatergic pathways, its function as a regulator of glutamate neurotransmitter levels is still not well defined. In order to gain an understanding of the role of GLUD1 in the control of glutamate levels and synaptic release in mammalian brain, we generated transgenic (Tg) mice that over-express this enzyme in neurons of the central nervous system. The Tg mice have increased activity of GLUD, as well as elevated levels and increased synaptic and depolarization-induced release of glutamate. These mice suffer age-associated losses of dendritic spines, nerve terminals, and neurons. The neuronal losses and dendrite structural changes occur in select regions of the brain. At the transcriptional level in the hippocampus, cells respond by increasing the expression of genes related to neurite growth and synapse formation, indications of adaptive or compensatory responses to the effects of increases in the release and action of glutamate at synapses. Because these Tg mice live to a relatively old age they are a good model of the effects of a “hyperglutamatergic” state on the aging process in the nervous system. The mice are also useful in defining the molecular pathways affected by the over-activation of GLUD in glutamatergic neurons of the brain and spinal cord