Using Artificial Intelligence for COVID-19 Detection in Blood Exams: A Comparative Analysis

COVID-19 is an infectious disease that was declared a pandemic by the World Health Organization (WHO) in early March 2020. Since its early development, it has challenged health systems around the world. Although more than 12 billion vaccines have been administered, at the time of writing, it has more than 623 million confirmed cases and more than 6 million deaths reported to the WHO. These numbers continue to grow, soliciting further research efforts to reduce the impacts of such a pandemic. In particular, artificial intelligence techniques have shown great potential in supporting the early diagnosis, detection, and monitoring of COVID-19 infections from disparate data sources. In this work, we aim to make a contribution to this field by analyzing a high-dimensional dataset containing blood sample data from over forty thousand individuals recognized as infected or not with COVID-19. Encompassing a wide range of methods, including traditional machine learning algorithms, dimensionality reduction techniques, and deep learning strategies, our analysis investigates the performance of different classification models, showing that accurate detection of blood infections can be obtained. In particular, an F-score of 84% was achieved by the artificial neural network model we designed for this task, with a rate of 87% correct predictions on the positive class. Furthermore, our study shows that the dimensionality of the original data, i.e. the number of features involved, can be significantly reduced to gain efficiency without compromising the final prediction performance. These results pave the way for further research in this field, confirming that artificial intelligence techniques may play an important role in supporting medical decision-making

Hysteroscopic Myomectomy: the Guidelines of the International Society for Gynecologic Endoscopy (ISGE)

Objective: With this publication, the International Society for Gynecologic Endoscopy (ISGE) aims to provide the clinicians with the recommendations arising from the best evidence currently available on hysteroscopic myomectomy (HM). Study design: The ISGE Task Force for HM defined key clinical questions, which led the search of Medline/PubMed and the Cochrane Database. We selected and analyzed relevant English-language articles, published from January 2005 to June 2021, including original works, reviews and the guidelines previously published by the European Society for Gynecological Endoscopy (ESGE) and the American Association of Gynecologic Laparoscopists (AAGL), in which bibliographies were also checked in order to identify additional references, using the medical subject heading (MeSH) term "Uterine Myomectomy" (MeSH Unique ID: D063186) in combination with ''Myoma" (MeSH Unique ID: D009214) and ''Hysteroscopy" (MeSH Unique ID: D015907). We developed the recommendations through multiple cycles of literature analysis and expert discussion. Results: The ISGE Task Force did develop 10 grade 1A-C and 4 grade 2A-C recommendations. For planning HM, evaluation of the uterus with saline infusion sonohysterography (SIS) or combined assessment by transvaginal ultrasound (TVUS) and diagnostic hysteroscopy is recommended (Grade 1A). The use of STEPW (Size, Topography, Extension of the base, Penetration and lateral Wall position) classification system of submucosal leiomyoma (LM) is recommended to predict the complex surgeries, incomplete removal of the LM, long operative time, fluid overload and other major complications (grade 1B). For type 0 LMs, in addition to resectoscopy (slicing technique), morcellation is recommended, being faster and having a shorter learning curve with respect to resectoscopy (grade 1C). For type 1-2 LMs, slicing technique is currently recommended (grade 1C). A fluid deficit of 1000 mL also in case of bipolar myomectomy with saline solution, in healthy women of reproductive age, contains low risk for major complications. Lower thresholds (750 mL) for fluid deficit should be considered in the elderly and in women with cardiovascular, renal or other co-morbidities (Grade 1B). Conclusion: HM is the most effective conservative minimally invasive gynecologic intervention for submucous LM. The set of 14 ISGE recommendations can significantly contribute to the success of HM and the safety of patients for whom the choice of appropriate surgical technique, as well as the surgeon's awareness and measures to prevent complications are of the utmost importance.info:eu-repo/semantics/publishedVersio

An Anomaly Detection Approach to Determine Optimal Cutting Time in Cheese Formation

The production of cheese, a beloved culinary delight worldwide, faces challenges in maintaining consistent product quality and operational efficiency. One crucial stage in this process is determining the precise cutting time during curd formation, which significantly impacts the quality of the cheese. Misjudging this timing can lead to the production of inferior products, harming a company’s reputation and revenue. Conventional methods often fall short of accurately assessing variations in coagulation conditions due to the inherent potential for human error. To address this issue, we propose an anomaly-detection-based approach. In this approach, we treat the class representing curd formation as the anomaly to be identified. Our proposed solution involves utilizing a one-class, fully convolutional data description network, which we compared against several stateof-the-art methods to detect deviations from the standard coagulation patterns. Encouragingly, our results show F1 scores of up to 0.92, indicating the effectiveness of our approach

Selective photooxidation of ortho-substituted benzyl alcohols and the catalytic role of ortho-methoxybenzaldehyde

It has been recently reported by Palmisano et al. (2015) [1] that the oxidation of 2-methoxybenzyl alcohol (2-MBA) to 2-methoxybenzaldehyde (2-MBAD) proceeds in water under near-UV light with an unexpected catalytic effect of 2-MBAD. In order to investigate the catalytic role of aldehyde in photolytic oxidation of ortho-substituted benzyl alcohols (OSBAs), reactivity runs were carried out with 2-methylbenzyl alcohol (2-MeBA), 2-nitrobenzyl alcohol (2-NBA), 2-hydroxybenzyl alcohol (2-HBA) and 2-chlorobenzyl alcohol (2-ClBA) in the absence and in the presence of their corresponding aldehyde. None of those alcohols showed a measurable oxidation rate even in the presence of their aldehydes but 2-NBA was oxidised very fast, although no corresponding carbonyl product was obtained. The possible catalytic role of 2-MBAD was investigated for the photolytic oxidation of 4-methoxybenzyl alcohol (4-MBA), 4-nitrobenzyl alcohol (4-NBA), 2-ClBA, 2-HBA, 2-MeBA and ferulic acid (FA). The results showed that 2-MBAD acts as a catalyst only for 4-MBA, 2-HBA and FA. The photocatalytic oxidation of OSBAs in the presence of powdered TiO2 has been also carried out in order to investigate the mutual influences, if any, between homogeneous and heterogeneous processes. The reactivity runs were carried out with TiO2 photocatalyst in water and under near-UV irradiation; a home-prepared (HP) TiO2 sample was used along with Degussa P25. HP catalyst showed the best performance: the 2-MBA half-life time was 5 times smaller and the selectivity to aldehyde 13 times higher than in the presence of Degussa P25

CMS endcap RPC gas gap production for upgrade

The CMS experiment will install a RE4 layer of 144 new Resistive Plate Chambers (RPCs) on the existing york YE3 at both endcap regions to trigger high momentum muons from the proton-proton interaction. In this paper, we present the detailed procedures used in the production of new RPC gas gaps adopted in the CMS upgrade. Quality assurance is enforced as ways to maintain the same quality of RPC gas gaps as the existing 432 endcap RPC chambers that have been operational since the beginning of the LHC operation

Microwave Spectroscopy Investigation of Carasau Bread Doughs: Effects of Composition up to 8.5 GHz

Carasau bread is a flat bread, typical of Sardinia (Italy). The market of this food product has a large growth potential, and its industry is experiencing a revolution, characterized by digitalization and automation. To monitor the quality of this food product at different manufacturing stages, microwave sensors and devices could be a cost-effective solution. In this framework, knowledge of the microwave response of Carasau dough is required. Thus far, the analysis of the microwave response of Carasau doughs through dielectric spectroscopy has been limited to the dynamics of fermentation. In this work, we aim to perform complex dielectric permittivity measurements up to 8.5 GHz, investigating and modeling the role of water amount, salt and yeast concentrations on the spectra of this food product. A third-order Cole–Cole model was used to interpret the microwave response of the different samples, resulting in a maximum error of 1.58% and 1.60% for the real and imaginary parts of permittivity, respectively. Thermogravimetric analysis was also performed to support the microwave spectroscopy investigation. We found that dielectric properties of Carasau bread doughs strongly depend on the water content. The analysis highlighted that an increase in water quantity tends to increase the bounded water fraction at the expense of the free water fraction. In particular, the free water amount in the dough is not related to the broadening parameter (Formula presented.) of the second pole, whereas the bound water weight fraction is more evident in the (Formula presented.) and (Formula presented.) parameters. An increase in electrical conductivity was observed for increasing water content. The microwave spectrum of the real part of the complex permittivity is slightly affected by composition, while large variation in the imaginary part of the complex dielectric permittivity can be identified, especially for frequencies below 4 GHz. The methodology and data proposed and reported in this work can be used to design a microwave sensor for retrieving the composition of Carasau bread doughs through their dielectric signature

Gas Analysis and Monitoring Systems for the RPC Detector of CMS at LHC

The Resistive Plate Chambers (RPC) detector of the CMS experiment at the LHC proton collider (CERN, Switzerland) will employ an online gas analysis and monitoring system of the freon-based gas mixture used. We give an overview of the CMS RPC gas system, describe the project parameters and first results on gas-chromatograph analysis. Finally, we report on preliminary results for a set of monitor RPC.Comment: 9 pages, 8 figures. Presented by Stefano Bianco (Laboratori Nazionali di Frascati dell'INFN) at the IEEE NSS, San Diego (USA), October 200

The CMS RPC gas gain monitoring system: an overview and preliminary results

The status of the CMS RPC Gas Gain Monitoring (GGM) system developed at the Frascati Laboratory of INFN (Istituto Nazionale di Fisica Nucleare) is reported on. The GGM system is a cosmic ray telescope based on small RPC detectors operated with the same gas mixture used by the CMS RPC system. The GGM gain and efficiency are continuously monitored on-line, thus providing a fast and accurate determination of any shift in working point conditions. The construction details and the first result of GGM commissioning are described.Comment: 8 pages, 9 figures, uses lnfprepCMS.sty, presented by L. Benussi at RPC07, Mumbai, INDIA 200

Recent results and developments on double-gap RPCs for CMS

Abstract A 3 mm wide-gap Resistive Plate Chamber, as proposed for CMS, has been tested in the H2 Cern beam line. Results on efficiency, rate capability, time resolution and cluster size are reported

Resistive Plate Chambers in avalanche mode: a comparison between model predictions and experimental results

Abstract In this paper a model simulating the main aspects of avalanche growth and signal development in Resistive Plate Chambers (RPCs) is presented. The model has been used to compute the performances, in particular, charge distribution and efficiency of single- double- and multi-gap RPCs, and to compare them with the available experimental results. This model could be used to optimize the characteristics of this type of detector with a view to its use in the future large experiments at LHC: ATLAS and CMS