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Background Ovarian pregnancy is a rare type of ectopic pregnancy, accounting for 0.5% to 1% of all ectopic pregnancies, with an incidence ranging from 1 in 2,100 to 1 in 60,000 pregnancies. Due to its rarity and the lack of common risk factors, diagnosing ovarian pregnancy is often challenging and typically occurs during surgical exploration. Case Presentation We present the case of a 40-year-old woman who experienced severe pelvic pain, light vaginal bleeding, and 8 weeks of amenorrhea. Upon arrival at the hospital, she was hemodynamically unstable, with low blood pressure and a rapid heart rate. An ultrasound revealed an empty uterus, an irregular mass on her right ovary, and free fluid in the pelvis. Her beta-hCG level was elevated, and her hemoglobin level was low. Given the suspicion of an ectopic pregnancy, she underwent emergency surgery. During the operation, the surgical team discovered a large amount of clotted blood and a ruptured mass on her left ovary measuring 10 x 9.5 cm. Due to heavy bleeding, they performed a left oophorectomy and salpingectomy. Histopathological analysis later confirmed the diagnosis of ovarian pregnancy. Conclusion This case underscores the challenges in diagnosing ovarian pregnancy and highlights the necessity for prompt surgical intervention, particularly in unstable patients. Early detection and appropriate management are critical to prevent life-threatening complications.

Abstract Immunocompromised patients who develop invasive filamentous mycotic infections can be efficiently treated if rapid identification of the causative fungus is obtained. We report a case of fatal necrotic pneumonia caused by combined pulmonary invasive mucormycosis and aspergillosis in a 66 year-old renal transplant recipient. Aspergillus was first identified during the course of the disease by cytological examination and culture (A. fumigatus) of bronchoalveolar fluid. Hyphae of Mucorales (Rhizopus microsporus) were subsequently identified by culture of a tissue specimen taken from the left inferior pulmonary lobe, which was surgically resected two days before the patient died. Histological analysis of the lung parenchyma showed the association of two different filamentous mycoses for which the morphological features were evocative of aspergillosis and mucormycosis. However, the definitive identification of the associative infection was made by polymerase chain reaction (PCR) performed on deparaffinized tissue sections using specific primers for aspergillosis and mucormycosis. This case demonstrates that discrepancies between histological, cytological and mycological analyses can occur in cases of combined mycotic infection. In this regard, it shows that PCR on selected paraffin blocks is a very powerful method for making or confirming the association of different filamentous mycoses and that this method should be made available to pathology laboratories.

The dielectric properties of skin tissues in relation to different degrees of burn are a necessary prerequisite for designing non-invasive microwave sensing modalities. Due to the difficulties in obtaining human tissue samples, such databases are largely unavailable. To bridge the knowledge gap in this field, we attempt to create a dielectric database of various burn-degree skin samples and their statistical analysis in this work. This research is part of the European “Senseburn” project, which aims to create a non-invasive diagnostic tool that can measure the severity and depth of burns on humans in a clinical setting. In this work, several ex-vivo burnt samples were collected from the Uppsala University Hospital (Akademiska sjukhuset, Sweden). Out of that, eight samples with different degrees of burns in various human body locations were selected for the analysis. The dielectric characterization of the categorized samples was done using an Keysight N1501A dielectric open-end co-axial probe Kit. The dielectric characterization was made from 500 MHz to 10 GHz with 1001 points. The measurement was made systematically, and the clinician feedback forms were gathered and analyzed throughout the process. The measurement data followed the FASTCLUS procedure, which was initially analyzed using density plot, convergence, and cubic clustering criteria. For the statistical analysis, 11 frequency points were considered for eight samples. The results of the fundamental statistical analysis using the FASTCLUS procedure resulted in 88 data sets. Later, data sets were analyzed in sample-wise clusters. Every sample was made with two clusters, i.e., cluster 1, which consisted of healthy sectors, and cluster 2, which consisted of burnt sectors. We made the linear approximations for the sample-wise clusters and found the constant real permittivity difference. Furthermore, we found a pattern in the constant real permittivity differences of every sample that is proportional to the burn degrees. This information is needed in order to identify optimization parameters, i.e., the sensitivity with respect to dielectric difference for various burn degrees. For this purpose, extensive measurement campaigns across the microwave frequency band from 500 MHz – 10 GHz were conducted. Based on the analysis of dielectric data, each skin region of interest (ROI) has its own dielectric properties. Additionally, we developed a proof of concept non-invasive flexible microwave sensor based on the dielectric database collected from burnt ex-vivo human tissue samples. In this way, we could distinguish between phantoms with different dielectric properties in the burned human tissue sample range.

Large quantities of plant waste are rejected daily in our universe. Consequently, several researchers have proposed various ways to enhance them. One of these possible routes is recovery as a natural dye for textile use. This study aims to explore the possibility of recovering the Juglans Regia. L barks residues in natural dyeing. Hence, the extraction of a bio-dye was carried out by microwave, several parameters were studied, namely: the microwave power, the pH, and the duration. The total phenolic compounds, flavonoids, condensed and hydrolyzable tannins contents were estimated each time. Then, the colored extracts were used for dyeing wool fabrics. The Dyeing quality resulted was estimated by calculating the colorimetric coordinates (L*, a*, b*) and the color strength (K/S). Good results were obtained, with brown shades and a color strength (K/S) close to 15 was reached. The dyeing fastnesses were also checked, acceptable fastnesses to washing, rubbing and to light were obtained. Finally, the dyed and undyed wool samples were characterized by spectral Infrared analysis and a proposal of possible dyeing mechanisms was suggested.

The need for an environmentally friendly tool in textile production is the major concern of consumers and traders. The current study is aimed to use supercritical CO2 technology to improve dyeing of minor elastin containing cotton using CI. Reactive Blue 222 and CI. Direct Black 112 dyes. For this purpose, several minor elastin containing cotton were pretreated with both conventional water and supercritical CO2 methods. Physical properties such as mass per unit area, tensile strength, tear strength, and elasticity of these fabrics are studied. Obtained results show that the supercritical CO2 pre-treatment affects some of the physical parameters. Furthermore, the obtained results are very promising as they prove that it is possible to dye various base-cotton fabrics in supercritical CO2 medium with a very satisfying quality in terms of uniformity and conformity.

The paper focuses on the importance of prompt and efficient process fault detection in contemporary manufacturing industries, where product quality and safety protocols are critical. The study compares the efficiencies of two techniques for process fault detection: Kernel Principal Component Analysis (KPCA) and the observer method. Both techniques are applied to observe water volume variation within a hydraulic system comprising three tanks. PCA is an unsupervised learning technique used for dimensionality reduction and pattern recognition. It is an extension of Principal Component Analysis (PCA) that utilizes kernel functions to transform data into higher-dimensional spaces, where it becomes easier to separate classes or identify patterns. In this paper, KPCA is applied to detect faults in the hydraulic system by analyzing the variation in water volume. The observer method originates from control theory and is utilized to estimate the internal states of a system based on its output measurements. It is commonly used in control systems to estimate the unmeasurable or hidden states of a system, which is crucial for ensuring proper control and fault detection. In this study, the observer method is applied to the hydraulic system to estimate the water volume variations within the three tanks. The paper presents a comparative study of these two techniques applied to the hydraulic system. The results show that both KPCA and the observer method perform similarly in detecting faults within the system. This similarity in performance highlights the efficacy of these techniques and their potential adaptability in various fault diagnosis scenarios within modern manufacturing processes.

Fault diagnosis plays a crucial role in enhancing system dependability and minimizing potential catastrophic consequences for both equipment and human safety. This article presents a research study focused on developing a diagnosis and control approach for discrete event systems using the Petri net Fuzzy Interval (IFPN). The Petri net is utilized as a modeling tool for the target system. The paper describes a case study conducted on an ingredient mixing system, where the objective is to maintain the concentration of ingredients within a valid range. A diagnostic framework is constructed and successfully applied to identify faults in the system. The proposed approach is further validated through simulation tests conducted on a mixing system.

Abstract Recently, Deep Learning (DL) applications are getting more and more involved in different fields. Deploying such Deep Neural Networks (DNN) on embedded devices is still a challenging task considering the massive requirement of computation and storage. Given that the number of operations and parameters increases with the complexity of the model architecture, the performance will strongly depend on the hardware target resources and basically the memory footprint of the accelerator. Recent research studies have discussed the benefit of implementing some complex DL applications based on different models and platforms. However, it is necessary to guarantee the best performance when designing hardware accelerators for DL applications to run at full speed, despite the constraints of low power, high accuracy and throughput. Field Programmable Gate Arrays (FPGAs) are promising platforms for the deployment of large‐scale DNN which seek to reach a balance between the above objectives. Besides, the growing complexity of DL models has made researches think about applying optimization techniques to make them more hardware‐friendly. Herein, DL concept is presented. Then, a detailed description of different optimization techniques used in recent research works is explored. Finally, a survey of research works aiming to accelerate the implementation of DNN models on FPGAs is provided.

Rosmarinus officinalis L. is a dietary source that produces polyphenols as secondary metabolites. These natural compounds with potent antioxidant abilities are increasingly recommended as a supplement to inhibit oxidative stress. In the current work, we evaluated the impact of the extraction method on the chemical composition of R. officinalis extract, especially on the content of carnosic (CA) and rosmarinic (RA) acids using UPLC-MS-DAD as well as on their antioxidant potency. Four extracts of Tunisian rosemary were obtained from non-conventional extraction techniques:ultrasound-assisted extraction (UAE),supercritical extraction (SFE) and UAE and SFE combined ((UAE-SFE(I), UAE-SFE(II)). The UAE exhibited the best total phenolic compounds (i.e., 85.27 mg GAEg−1), the highest content of CAand RA and the strongest antioxidant abilities (i.e., IC50 = 0.13 mg/mL and EC50 = 0.93 mg/mL for DPPH scavenging test and iron reducing power ability assay). The evaluation of antioxidant activity of UAE inhuman skin fibroblast (HS-68) cell line was carried out after the induction of oxidative stress. The results determined by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay showed a strong protective effect against H2O2oxidative stress induction in cells pretreated with UAE. The obtained results allow us to give new insight about the effect of the extraction method on the chemical composition and biological activities of the extract and the importance of the choice of the most appropriate processing technique to prepare rosemary extract with a high antioxidant potency and protective effect against oxidative stress.

Phototherapy is the standard treatment for neonatal jaundice. We aimed to review the efficacy and safety of fenofibrate as an adjunct therapy. Twelve databases were searched and a systematic review and meta-analysis were conducted. Mean change (MC), mean difference (MD), and risk ratios (RR) with a 95% confidence interval (CI) were calculated using a random effects model. The GRADE approach was used to evaluate the evidence's certainty. Nine randomized trials were included. The MC of total serum bilirubin (mg/dL) was significant at 12, 24, 36, 48, and 72 h with respective MC (95% CI) values of −0.46 (−0.61, −0.310), −1.10 (−1.68, −0.52), −2.06 (−2.20, −1.91), −2.15 (−2.74, −1.56), and −1.13 (−1.71, −0.55). The FEN + PT group had a shorter duration of phototherapy (MD: −14.36 h; 95% CI: −23.67, −5.06) and a shorter hospital stay (MD: −1.40 days; 95% CI: −2.14, −0.66). There was no significant difference in the risk of complications (RR: 0.89; 95% CI: 0.54, 1.46) or the need for exchange transfusion (RR: 0.58; 95% CI: 0.12, 2.81). The certainty of the evidence was very low for all outcomes. In conclusion, fenofibrate might be a safe adjunct to neonatal phototherapy. Larger randomized controlled trials are needed for the confirmation of these results. [ABSTRACT FROM AUTHOR]

The objective of this research work is the study of the essential oils (EOs) of myrtle (MEO) and rosemary (REO) as novel and eco-friendly corrosion inhibitors. These EOs were extracted by the Clevenger technique and analyzed using the Gas Chromatography/Mass Spectrometry (GC/MS) and Fourier-transform infrared spectroscopy (FTIR). These techniques show that MEO and REO were rich in various volatile compounds.The investigation of copper corrosion behavior in 3 wt% NaCl solution, in the presence of EOs, via open circuit potential (OCP), potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) was carried out. The results of the electrochemical tests presented the same trends: EOs acting as cathodic type inhibitor for copper in 3 wt% NaCl solutions, the inhibition efficiency increasing upon the addition of EOs and the further increase with the increase of the EOs concentration and REO having moderately superior performance compared to MEO. The EOs molecules adsorption on the copper surface followed a Langmuir isotherm, and physical adsorption (vs. chemical adsorption) is dominant.