Advanced Formation Fluid Evaluation While Drilling with a New Heavy Gas Detector

In this paper, a chromatograph which exploits the benefits of FID technology optimized for the high resolution detection of heavier hydrocarbon gas components is described. The components analyzed span from n-hexane to toluene. Flame Ionization Detector (FID) technology is not new to gas detection on the field, however it had never been applied to the detection of gases heavier than n-pentane. The instrumentation has been installed and run on a number of wells in different fields and countries, and it has operated as a complement of an advanced surface logging system for a period of two years. Unlike other technologies presently utilized for this scope, this system reduces dedicated equipment and personnel to a minimum. The results presented show the clear identification of formation fluid contacts with higher accuracy than standard light gas detectors, the recognition of contaminants within the drilling fluid, and the practicality of operating an advanced gas detection system with minimal operational and logistic footprint. Some of the indications obtained challenge common beliefs about gas detection: consistent extraction of heavy hydrocarbon gases from the drilling fluid is possible at relatively low temperatures, provided that the entire gas extraction system is rigorously controlled in terms of gas sample pressure, flow, and temperature. Furthermore, gas data analysis can yield indications on the fluid composition even when the gases analyzed are in extremely low quantity. The system utilizes known technologies, developed and optimized to obtain new results. The system supports formation evaluation when LWD or wireline can be inconclusive, in the presence of a low porosity pay or fresh water. It can also guide and optimize the MDT testing program. Furthermore, the system takes into account the constraints of drilling operations, and strikes a balance between data accuracy and practicality of the application

Deep learning applied to EEG source-data reveals both ventral and dorsal visual stream involvement in holistic processing of social stimuli

Perception of social stimuli (faces and bodies) relies on “holistic” (i.e., global) mechanisms, as supported by picture-plane inversion: perceiving inverted faces/bodies is harder than perceiving their upright counterpart. Albeit neuroimaging evidence suggested involvement of face-specific brain areas in holistic processing, their spatiotemporal dynamics and selectivity for social stimuli is still debated. Here, we investigate the spatiotemporal dynamics of holistic processing for faces, bodies and houses (adopted as control non-social category), by applying deep learning to high-density electroencephalographic signals (EEG) at source-level. Convolutional neural networks were trained to classify cortical EEG responses to stimulus orientation (upright/inverted), separately for each stimulus type (faces, bodies, houses), resulting to perform well above chance for faces and bodies, and close to chance for houses. By explaining network decision, the 150–200 ms time interval and few visual ventral-stream regions were identified as mostly relevant for discriminating face and body orientation (lateral occipital cortex, and for face only, precuneus cortex, fusiform and lingual gyri), together with two additional dorsal-stream areas (superior and inferior parietal cortices). Overall, the proposed approach is sensitive in detecting cortical activity underlying perceptual phenomena, and by maximally exploiting discriminant information contained in data, may reveal spatiotemporal features previously undisclosed, stimulating novel investigations

Artificial neural-network technique for precipitation nowcasting from satellite imagery

The term nowcasting reflects the need of timely and accurate predictions of risky situations related to the development of severe meteorological events. In this work the objective is the very short term prediction of the rainfall field from geostationary satellite imagery entirely based on neural network approach. The very short-time prediction (or nowcasting) process consists of two steps: first, the infrared radiance field measured from geostationary satellite (Meteosat 7) is projected ahead in time (30 min or 1 h); secondly, the projected radiances are used to estimate the rainfall field by means of a calibrated microwave-based combined algorithm. The methodology is discussed and its accuracy is quantified by means of error indicators. An application to a satellite observation of a rainfall event over Central Italy is finally shown and evaluated

Fatigue behavior of foreign object damaged 7075 heat treated aluminum alloy coated with PVD WC/C

AbstractThe effect of a physically vapor deposited (PVD) WC/C coating on the fatigue behavior of as produced and foreign object damaged (FOD) solution heat treated and aged 7075 aluminum alloy was studied. Coated and uncoated samples were tested under rotating bending to determine the fatigue strengths between 104 and 106 cycles in both damaged and smooth condition. FOD was produced with single shots of small hard steel spheres impacting at 100 m/s in the minimum cross section. SEM was used to characterize the features of the fracture surfaces

The Modified Five-Point Test (MFPT): normative data for a sample of Italian elderly

INTRODUCTION: Non-verbal figural fluency is related to executive functions and specifically to the ability to create as many unique designs as possible, while minimizing their repetitions. An Italian version of figural fluency is the Modified Five-Point Test (MFPT), which is highly employed in the clinical practice of neuropsychologists. To date, reference data of Italian population are limited to a sample aged between 16 and 60 years old. Thus, the current study aims to provide normative data of the MFPT in the context of a population-based setting, conducted in Southern Italy. MATERIAL AND METHODS: We collected N = 340 Italian healthy subjects, aged over 65 years old (range: 65-91), pooled across subgroups for age, sex, and education. Multiple regression analyses were performed to estimate the effect of age, education, and sex on the participant's performance. Equivalent scores and cut-off scores were also defined for the number of unique designs (UDs) and the number of strategies (CSs). RESULTS: Multiple regression analyses revealed that UDs increase with decreasing age and increasing educational level. CSs are influenced by higher educational levels but neither by age nor sex. A significant inverse correlation between the UDs and percentage of errors occurred, suggesting that a higher number of UDs are associated with a fewer number of errors and higher CSs employed. CONCLUSION: The MFPT provides a measure of cognitive functioning in terms of the ability to initiate and realize designs, affording useful hints for clinical settings. The MFPT may represent a handy and useful tool with a specific focus in the differentiation of healthy versus pathological aging

Analysis of the genetic basis of periodic fever with aphthous stomatitis, pharyngitis, and cervical adenitis (PFAPA) syndrome.

PFAPA syndrome is the most common autoinflammatory syndrome in children from Western countries. In spite of its strong familial clustering, its genetic basis and inheritance pattern are still unknown. We performed a comprehensive genetic study on 68 individuals from 14 families. Linkage analysis suggested a susceptibility locus on chromosome 8, but direct molecular sequencing did not support this initial statistical finding. Exome sequencing revealed the absence of any gene that was mutated in all patients. Exhaustive screening of genes involved in other autoinflammatory syndromes or encoding components of the human inflammasome showed no DNA variants that could be linked to PFAPA molecular pathology. Among these, the previously-reported missense mutation V198M in the NLRP3 gene was clearly shown not to co-segregate with PFAPA. Our results on this relatively large cohort indicate that PFAPA syndrome is unlikely to be a monogenic condition. Moreover, none of the several genes known to be involved in inflammation or in autoinflammatory disorders seem to be relevant, alone, to its etiology, suggesting that PFAPA results from oligogenic or complex inheritance of variants in multiple disease genes and/or non-genetic factors

Anatomic feasibility of in-situ fenestration for isolate left subclavian artery preservation during thoracic endovascular aortic repair using an adjustable needle puncturing system

Objectives: To evaluate the feasibility of thoracic endovascular aortic repair (TEVAR) using the AnkuraTM device (Lifetech Scientific, Shenzhen, China) with left subclavian artery (LSA) in-situ fenestration (ISF) using an adjustable puncture device system. Methods: It is a single center, retrospective, financially unsupported cohort study of TEVAR performed from 16 February 2007 to 10 January 2023. Inclusion criteria were isolate LSA revascularization for elective or urgent/emergent “zone 2” TEVAR, and the availability of the preoperative computed tomography angiography. Results: Post-hoc analysis identified 52 TEVARs. There were 39 (75.0%) males, and 13 (25.0%) females: median age was 74.5 years (IQR, 65.5–78). Index TEVAR was performed for atherosclerotic aneurysm in 27 (51.9%) cases, dissection-related diseases in 18 (34.6%), penetrating aortic ulcer in 5 (9.6%), and blunt traumatic aortic injury in 2 (3.8%). Access-vessel feasibility rate of TEVAR using the AnkuraTM device would have been 98.1% (51/52). Considering the morphology of the aortic arch, ISF TEVAR feasibility would have been 61.5% (32/52). Binary logistic regression analysis identified LSA angulation (OR: 1.1, 95%CI: 1.03–1.14, p = 0.003) to be associated with ISF feasibility using this endograft and a self-centering adjustable needle-based puncture device. Conclusions: Potential feasibility of TEVAR using the AnkuraTM endograft with ISF using a self-centering adjustable needle system was 61.5%. Left subclavian artery angulation seems to be the most important and limiting anatomical constraint

Darts fast-learning reduces theta power but is not affected by Hf-tRNS: A behavioral and electrophysiological investigation

Sports trainers have recently shown increasing interest in innovative methods, including transcranial electric stimulation, to enhance motor performance and boost the acquisition of new skills during training. However, studies on the effectiveness of these tools on fast visuomotor learning and brain activity are still limited. In this randomized single-blind, sham-controlled, between-subjects study, we investigated whether a single training session, either coupled or not with 2 mA online high-frequency transcranial random noise stimulation (hf-tRNS) over the bilateral primary motor cortex (M1), would affect dart-throwing performance (i.e., radial error, arm range of motion, and movement variability) in 37 healthy volunteers. In addition, potential neurophysiological correlates were monitored before and after the training through a 32-electrode portable electroencephalogram (EEG). Results revealed that a single training session improved radial error and arm range of motion during the dart-throwing task, but not movement variability. Furthermore, after the training, resting state-EEG data showed a decrease in theta power. Radial error, arm movement, and EEG were not further modulated by hf-tRNS. This indicates that a single training session, regardless of hf-tRNS administration, improves dart-throwing precision and movement accuracy. However, it does not improve movement variability, which might require multiple training sessions (expertise resulting in slow learning). Theta power decrease could describe a more efficient use of cognitive resources (i.e., attention and visuomotor skills) due to the fast dart-throwing learning. Further research could explore different sports by applying longer stimulation protocols and evaluating other EEG variables to enhance our understanding of the lasting impacts of multi-session hf-tRNS on the sensorimotor cortex within the framework of slow learning and training assistance

Atrial Flutter Mechanism Detection Using Directed Network Mapping

Atrial flutter (AFL) is a common atrial arrhythmia typically characterized by electrical activity propagating around specific anatomical regions. It is usually treated with catheter ablation. However, the identification of rotational activities is not straightforward, and requires an intense effort during the first phase of the electrophysiological (EP) study, i.e., the mapping phase, in which an anatomical 3D model is built and electrograms (EGMs) are recorded. In this study, we modeled the electrical propagation pattern of AFL (measured during mapping) using network theory (NT), a well-known field of research from the computer science domain. The main advantage of NT is the large number of available algorithms that can efficiently analyze the network. Using directed network mapping, we employed a cycle-finding algorithm to detect all cycles in the network, resembling the main propagation pattern of AFL. The method was tested on two subjects in sinus rhythm, six in an experimental model of in-silico simulations, and 10 subjects diagnosed with AFL who underwent a catheter ablation. The algorithm correctly detected the electrical propagation of both sinus rhythm cases and in-silico simulations. Regarding the AFL cases, arrhythmia mechanisms were either totally or partially identified in most of the cases (8 out of 10), i.e., cycles around the mitral valve, tricuspid valve and figure-of-eight reentries. The other two cases presented a poor mapping quality or a major complexity related to previous ablations, large areas of fibrotic tissue, etc. Directed network mapping represents an innovative tool that showed promising results in identifying AFL mechanisms in an automatic fashion. Further investigations are needed to assess the reliability of the method in different clinical scenarios

Homozygosity mapping reveals novel and known mutations in Pakistani families with inherited retinal dystrophies.

Inherited retinal dystrophies are phenotypically and genetically heterogeneous. This extensive heterogeneity poses a challenge when performing molecular diagnosis of patients, especially in developing countries. In this study, we applied homozygosity mapping as a tool to reduce the complexity given by genetic heterogeneity and identify disease-causing variants in consanguineous Pakistani pedigrees. DNA samples from eight families with autosomal recessive retinal dystrophies were subjected to genome wide homozygosity mapping (seven by SNP arrays and one by STR markers) and genes comprised within the detected homozygous regions were analyzed by Sanger sequencing. All families displayed consistent autozygous genomic regions. Sequence analysis of candidate genes identified four previously-reported mutations in CNGB3, CNGA3, RHO, and PDE6A, as well as three novel mutations: c.2656C > T (p.L886F) in RPGRIP1, c.991G > C (p.G331R) in CNGA3, and c.413-1G > A (IVS6-1G > A) in CNGB1. This latter mutation impacted pre-mRNA splicing of CNGB1 by creating a -1 frameshift leading to a premature termination codon. In addition to better delineating the genetic landscape of inherited retinal dystrophies in Pakistan, our data confirm that combining homozygosity mapping and candidate gene sequencing is a powerful approach for mutation identification in populations where consanguineous unions are common