Search Results (6)

The diagnosis of overflow risk has always been an important area of research in drilling operations in the field of oil and gas engineering. In the face of the limitations and lag of traditional overflow diagnosis methods, the practical application effect of existing models and methods is not obvious, and there is no integration of the physical model and the intelligent algorithm model for overflow diagnosis, this paper proposes a method of adaptive weight fusion of physical model and intelligent algorithm model diagnosis results. Based on the fusion of the physical model and the intelligent algorithm model, an overflow diagnosis model of managed pressure drilling is established. The research results show that the fusion model in this paper can combine the accuracy weight of the physical model and the intelligent algorithm model for the intelligent diagnosis of overflow risk, which improves the mechanization and interpretability of the model and diagnosis results while ensuring accuracy and efficiency. And the intelligent algorithm model used in the fusion model is superior to other algorithm models. The overflow diagnosis accuracy of the fusion model on the test set samples reaches more than 98%, and the accuracy of the validation set is 94.25%. The content of this study provides guidance for drilling overflow diagnosis and model fusion methods. Full article

In offshore drilling, accidents such as gas invasion, overflow, and kicks are unavoidable, and they can escalate into blowouts and other catastrophic events, resulting in casualties and significant economic losses. Therefore, ensuring drilling safety requires precise monitoring of gas invasion and overflow. Currently, most overflow monitoring methods used at drilling sites are based on threshold criteria. However, the monitoring parameters obtained during actual drilling operations often contain noise signals, which makes it challenging for threshold-based methods to achieve a balance between improving accuracy and minimizing false positives. This paper proposes a novel method called Pattern-Recognition-based Kick Detection (PRKD) for diagnosing overflow in offshore drilling. The PRKD method utilizes the overflow evolution process by integrating multiphase flow calculations, data filtering theory, pattern recognition theory, the Bayesian framework, and other theoretical models. By analyzing the shape and wave characteristics of the curves, PRKD effectively detects and monitors gas intrusion and overflow based on single parameters. Through case analysis, it is demonstrated that the proposed method achieves high precision in monitoring drilling overflow while maintaining a low false positive rate. By combining advanced computational techniques with pattern recognition algorithms, PRKD improves the accuracy and reliability of kick detection, enabling proactive responses to potential risks, protecting the environment and human lives, and optimizing drilling operations. The case analysis shows that by integrating the probabilistic information of pre-drilling kicks and various characteristic parameters, when the noise amplitude is less than 8 L/s, the PRKD model exhibits superior detection performance. Moreover, when the noise amplitude is 16 L/s, the PRKD model detects the continuous overflow approximately 200 s after the actual overflow occurs and predicts a 95.8% probability of overflow occurrence at the specified location, meeting the on-site requirements. The gas invasion monitoring method proposed in this paper provides accurate diagnostic results and a low false positive rate, offering valuable guidance for gas invasion monitoring in drilling operations. Full article

During the waves of the coronavirus disease (COVID-19) pandemic, emergency departments were overflowing with patients suffering with suspected medical or surgical issues. In these settings, healthcare staff should be able to deal with different medical and surgical scenarios while protecting themselves against the risk of contamination. Various strategies were used to overcome the most critical issues and guarantee quick and efficient diagnostic and therapeutic charts. The use of saliva and nasopharyngeal swab Nucleic Acid Amplification Tests (NAAT) in the diagnosis of COVID-19 was one of the most adopted worldwide. However, NAAT results were slow to report and could sometimes create significant delays in patient management, especially during pandemic peaks. On these bases, radiology has played and continues to play an essential role in detecting COVID-19 patients and solving differential diagnosis between different medical conditions. This systematic review aims to summarize the role of radiology in the management of COVID-19 patients admitted to emergency departments by using chest X-rays (CXR), computed tomography (CT), lung ultrasounds (LUS), and artificial intelligence (AI). Full article

Background. Chromosome 22q11.2 Deletion Syndrome (22q11.2DS) is the most frequent microdeletion syndrome and is mainly characterized by congenital cardiac defects, dysmorphic features, hypocalcemia, palatal dysfunction, developmental delay, and impaired immune function due to thymic hypoplasia or aplasia. Thyroid anomalies are frequently reported in patients with 22q11.2DS, although only a few well-structured longitudinal studies about autoimmune thyroid disease (ATD) have been reported. Aim. To longitudinally evaluate the frequency of thyroid anomalies and ATD in patients with 22q11.2DS. Patients and Methods. Pediatric patients with a confirmed genetic diagnosis of 22q11.2DS were recruited and followed up on longitudinally. Clinical, biochemical, and immunological data were collected, as well as thyroid function, autoimmunity, and thyroid sonographic data. Results. The study included 73 children with 22q11.2DS, with a mean follow-up duration of 9.51 ± 5.72 years. In all, 16 of the 73 enrolled patients (21.9%) developed ATD before 18 years of age (mean age 12.92 ± 3.66 years). A total of 20.5% developed Hashimoto’s Thyroiditis (HT), of whom 50% required L-thyroxine treatment; 1.4% developed Graves Disease. Thyroid hypoplasia was found in 6/16 patients with ATD and left lobe hypoplasia in 9/16 patients. These features were also found in patients affected by 22q11.2DS without ATD. Among patients who developed ATD, at the first altered ultrasound scan, the most frequent anomalies suggestive of thyroiditis were inhomogeneous echotexture, diffuse or irregular hypo-echogenicity, and vascular overflow. Conclusion. We strongly recommend periodic screening of thyroid function and for autoimmunity in patients affected by 22q11.2DS. Along with blood tests, ultrasound scans of the thyroid gland should be performed periodically since some patients who go on to develop an ATD could have specific anomalies on ultrasound prior to any other anomaly. Full article

Dystonia diagnosis is based on clinical examination performed by a neurologist with expertise in movement disorders. Clues that indicate the diagnosis of a movement disorder such as dystonia are dystonic movements, dystonic postures, and three additional physical signs (mirror dystonia, overflow dystonia, and geste antagonists/sensory tricks). Despite advances in research, there is no diagnostic test with a high level of accuracy for the dystonia diagnosis. Clinical neurophysiology and genetics might support the clinician in the diagnostic process. Neurophysiology played a role in untangling dystonia pathophysiology, demonstrating characteristic reduction in inhibition of central motor circuits and alterations in the somatosensory system. The neurophysiologic measure with the greatest evidence in identifying patients affected by dystonia is the somatosensory temporal discrimination threshold (STDT). Other parameters need further confirmations and more solid evidence to be considered as support for the dystonia diagnosis. Genetic testing should be guided by characteristics such as age at onset, body distribution, associated features, and coexistence of other movement disorders (parkinsonism, myoclonus, and other hyperkinesia). The aim of the present review is to summarize the state of the art regarding dystonia diagnosis focusing on the role of neurophysiology and genetic testing. Full article

The wide variety of epigenetic controls available is rapidly expanding the knowledge of molecular biology even overflowing it. At the same time, it can illuminate unsuspected ways of understanding the etiology of cancer. New emerging therapeutic horizons, then, promise to overcome the current antitumor strategies need. The translational utility of this complexity is particularly welcome in oral cancer (OC), in which natural history is alarmingly disappointing due to the invasive and mutilating surgery, the high relapsing rate, the poor quality of life and the reduced survival after diagnosis. Melatonin activates protective receptor-dependent and receptor-independent processes that prevent tissue cancerisation and inhibit progressive tumor malignancy and metastasis. Related evidence has shown that melatonin pleiotropy encompasses gene expression regulation through all the three best-characterized epigenetic mechanisms: DNA methylation, chromatin modification, and non-coding RNA. OC has received less attention than other cancers despite prognosis is usually negative and there are no significant therapy improvements recorded in the past decade. However, a large research effort is being carried out to elucidate how melatonin´s machinery can prevent epigenetic insults that lead to cancer. In the light of recent findings, a comprehensive examination of biochemistry through which melatonin may reverse epigenetic aberrations in OC is an extraordinary opportunity to take a step forward in the clinical management of patients. Full article