Functional Failure Research Articles

Retrospective cohort study of self-reported outcomes after unilateral dacryocystorhinostomy in patients with bilateral epiphora and suspected nasolacrimal obstruction

ABSTRACT Purpose This study aimed to quantify the proportion of patients with bilateral epiphora and suspected nasolacrimal obstruction who self-reported improved epiphora bilaterally following unilateral dacryocystorhinostomy and investigate predictive factors. Methods A retrospective cohort study of patients from an Australian lacrimal clinic was performed. Eligible patients were at least 18 years of age, complained of bilateral epiphora, underwent unilateral dacryocystorhinostomy between 2012 and 2022 and followed-up. Outcome groups were created by grouping self-reported epiphora improvement levels for each eye. Two-sided confidence intervals were calculated for the proportion of participants in each outcome group. Ordinal elastic net regression identified clinical features associated with outcome groups and estimated their effect sizes. Results Of 243 patients, the median post-operative follow-up duration was 3 months. Fifty-eight percent (95% CI 52–64%, n = 141) reported significant improvement (≥50% ipsilateral and any contralateral improvement), 5% (95% CI 3–9%, n = 13) reported small improvement (<50% ipsilateral and any contralateral improvement) and 26% (95% CI 20–31%, n = 62) reported ipsilateral improvement only. Eleven percent had functional or anatomical failure. Older age (OR 1.01), contralateral nasolacrimal duct narrowing (OR 1.37), contralateral nasolacrimal duct obstruction (OR 0.93) and longer follow-up time (OR 0.85) predicted outcome groups. Conclusions After unilateral DCR, many patients with bilateral epiphora and suspected nasolacrimal obstruction report an improvement of their symptoms bilaterally in the early postoperative period. Contralateral nasolacrimal system diagnosis, patient age and follow-up duration were associated with outcomes. Further study using validated epiphora assessment tools may quantify this observation, and we suggest a potential underlying mechanism of contralateral effects after unilateral treatment.

Intelligent Ureteral Stent Placeable via Standard Procedure for Kidney Pressure Telemetry: An Ex-Vivo Study.

This paper reports the first telemetric ureteral stent compatible with common placement procedure, enabling wireless sensing and detection of ureteral obstruction and resultant kidney swelling known as hydronephrosis at an early stage. This sensor-integrated "intelligent" ureteral stent is prototyped via the design and fabrication approaches that raise the practicality of the device and tested in a harvested swine kidney-ureter model ex vivo. Leveraging a polymeric double-J stent and micro-electro-mechanical systems technology, the intelligent stent is built by embedding micro pressure sensors and a radiofrequency antenna, forming a resonant circuit that enables wireless kidney pressure monitoring in an operating frequency of 40-50MHz. The stent device is entirely packaged with Parylene-C for both biocompatibility and electrical insulation of the device in order to function in the real environment including urine, an electrically conductive liquid. A comparison between the results measured in in-vitro and ex-vivo settings show a good match in the sensitivity to applied pressure. In particular, the ex-vivo test in the kidney-ureter model pressurized with artificial urine in a cycled manner demonstrates wireless pressure tracking with a response of 1.3kHz/mmHg, over pressures up to 37mmHg that well covers a range of pressure increase known for chronic obstruction. This testing is enabled by the prototype placement into the ex-vivo model using the standard stenting technique and tools without noticeable functional degradation or failures, showing potential compatibility of the device with today's clinical need as a ureteral stent.

Matters of assuring functional dependability compliance of digital manufacturing

Aim. To propose a methodological approach to ensuring the functional dependability of industrial facilities using SMART documents in the context of import-independent digital processes. Methods. The evolving applicability of the dependability theory and information systems design has defined the methodological provisions for algorithmising the application of SMART standards for minimising functional faults and failures of industrial processes. Digital models of production lines were examined as tools for machine-recognisable representation of standards. The proposed form of regulatory documents is intended to enable the transition from machine-readable data to machine-understandable content. Findings. The application of the proposed methods of content systematisation in the context of manufacturing process standardisation shows that the classification of process data based on standardised characteristics of digital information exchange processes is one of the key methodological provisions ensuring unambiguous interpretation of regulatory requirements. Specialised projects often use individual provisions rather than complete regulatory documents. In this case, in order to ensure machine-understandability of the developed content, it is proposed using special identifiers, e.g., «paragraph», «graphic object», «table cell». The deployment of such identification tools will allow creating a class of SMART standards that collect into a single document the provisions regarding the delivery of intended results in situations when the operating equipment is diverse. Publications created using intelligent processing of SMART documents are considered as containers of structured and unstructured data that take into account the conditions of particular projects. The existing dynamics of the demand for advanced industrial products often determines the admissibility of its industrial production by various companies with the parallel use of unique technologies. The conditions of such an organisation impose their limitations on the comparability of various process requirements, therefore, it is proposed to harmonise the presentation of the results of managerial, design, and process engineering solutions using the term «manufacturing system asset». The introduction of relative result estimates as part of the digital format is an efficient mechanism for ensuring management consistency. In this context, the importance of a uniform regulatory framework as the foundation for such assessments is growing. As one of the ways of minimising faults and failures of industrial equipment, it is proposed to create a situation centre with a decision support system based on the regulatory data with harmonised manufacturing system asset requirements. An experience of Industry 4.0 regulation is described in the review of the ISA digital manufacturing series of standards. It was shown that the deployment of SMART standards improves the stability of interaction between information management systems and the functional dependability of production lines. The introduction of provisions regulating the use of algorithms for the development, editing, and examination of draft regulatory documents into the content machine-understandability facilities is an important factor in ensuring the functional dependability of products. Conclusions. The presented approach is focused on the methodology for developing standards that take into account requirements from various subject areas. In the context of ongoing import substitution in manufacturing, the paper examines the feasibility of minimizing digital process faults and failures caused by the use of regulatory frameworks that are not equivalent to the provisions of international documents and take into account the specificity of Russian industrial systems.

PSIII-2 Exploring differential gene expression and pathways associated with pregnancy outcomes in beef heifers

Abstract Heifer fertility is a key factor in the success of beef production systems, as the reproductive performance of a heifer correlates with her stayability in the breeding herd. However, despite being reproductively mature and physically healthy, 5 to 15% of these heifers fail to conceive within a designated breeding season. The underlying physiological mechanisms preventing these heifers from achieving pregnancy remain elusive. Therefore, this study aimed to determine differentially expressed genes (DEGs) and biological pathways associated with pregnancy outcomes in beef heifers. Angus-Simmental crossbred heifers were subjected to an estrus synchronization and fixed-time artificial insemination (AI) program (7-d CO-Synch + CIDR) and blood samples were collected at the time of AI for isolation of peripheral white blood cells (PWBC). After pregnancy check, heifers were classified as pregnant (P) and non-pregnant (NP). Based on that, 6 animals per group were randomly selected for total RNA isolation from the PWBC samples, and genome-wide expression was measured through RNA sequencing. The RNA-Seq data were analyzed using an in-house bioinformatics pipeline, with filtered reads aligned to the Bos taurus reference genome using STAR. DEGs were identified using DESeq2, followed by functional analysis using ShinyGO. Our approach unveiled 230 DEGs, comprising 102 up and 128 downregulated genes in the NP group (P-value ≤ 0.05 and |log2FC| &amp;gt; 0.5). Upregulated genes included those from the cytochrome P450 superfamily (CYP27B1 and CYP2U1). The genes SCML2, USIG2, and FBP1 were upregulated and have been associated with immune response and increased PWBC counts. This may be related to the over-representation of biological processes involved in cell division based on the upregulated genes. KEGG pathway over-representation analysis of DEGs retrieved allograft rejection, graft-versus-host disease, type I Diabetes Mellitus, insulin signaling pathway, and transcriptional misregulation of cancer. These pathways included genes such as BOLA-DQB, PRKAR1B, CALML4 and JUP, which were reported as downregulated during times of inflammatory response. Another downregulated gene was GZMB, which is needed for proper cell targeting during immune response. This finding may provide a link between immune function and early pregnancy failure. However, the relationship between the immune system and pregnancy warrants further investigation. Our results shed light on the molecular mechanisms underlying reproductive performance in beef heifers and support previous studies associating immune function with pregnancy outcomes. These differentially expressed genes may be further explored as potential avenues for enhancing fertility in beef production systems.

Supramolecular Association of a Block Copolymer via Strong Hydrogen Bonding to Form Self-Healable Ionogels.

The drive to enhance the operational durability and reliability of stretchable and wearable electronic and electrochemical devices has led to the exploration of self-healing materials that can recover from both physical and functional failures. In the present study, we fabricated a self-healable solid polymer electrolyte, referred to as an ionogel, using reversible hydrogen bonding between the ureidopyrimidone units of a block copolymer (BCP) network swollen in an ionic liquid (IL). The BCP consisted of poly(styrene-b-(methyl acrylate-r-ureidopyrimidone methacrylate)) [poly(S-b-(MA-r-UPyMA)], with the IL-phobic polystyrene forming micellar cores that were interconnected via intercorona hydrogen bonding between the ureidopyrimidone units. By precisely regulating the molecular weight and the composition of the hydrogen-bondable motifs, the mechanical, electrical, and self-healing characteristics of the ionogel were systematically evaluated. The resulting ionogel samples exhibited suitable stretchability, ionic conductivity, and room-temperature self-healability due to reversible hydrogen bonding. To highlight the applicability of the self-healing ionogel as a high-capacitance gate insulator, an electrolyte-gated transistor (EGT) was fabricated using a poly(3-hexylthiophene-2,5-diyl) semiconductor, and the performance of the EGT was fully recovered from a complete cut without any external stimuli.

An Investigation into Building Functional Failures in Akure South Local Government, Ondo State, Nigeria

Functional failures and faults are regular occurrences in buildings and construction industries. The rate of building collapse in Nigeria has increased dramatically over the last decade and shows no signs of abating which has led to massive losses causing loss of physical properties, destruction of movable properties, injury, and loss of life. Beyond this, building collapse always has far-reaching economic, financial, psychological, and sociological implications. This study reported the causes of functional failures of buildings in Akure South Local Government Area, Nigeria. As a result, this study aimed to investigate the causes of functional failures in buildings and their impact on the quality and functionality of a building to build a theoretical framework that can help address the functional failures in buildings. The study utilized a questionnaire-based survey in the Akure South Local Government area. Data was collected from residents occupying the buildings. Information obtained includes the type of building and the current physical condition of the houses they live in, and 90 responses were collected and analyzed. The analysis identified six factors of functional failures in buildings investigated; damp 30%, cracks 50%, poor plumbing 45%, poor electrical wiring 35%, roofing defects 25% and Inadequate maintenance 70% and four causes of building failures; poor construction materials 32.7%, human errors 20.7%, natural disasters 12.4%, and a combination of the three factors 34.2%. Based on the findings, the results showed that the combination of the three factors was the most significant cause of building functional failures in the Akure South LGA, while natural disasters were the least significant cause. To mitigate the functional failures in buildings, it is important to enforce stringent regulations and standards by involving Governmental bodies (architectural Engineers and structural Engineers) to check building drawings and structural analysis report properly and correctly before design approvals, conduct regular inspections and internal audits, to help detect and rectify errors and maintaining standards throughout the construction process in order to enhance the quality, safety, and resilience of buildings, ensuring their functionality and longevity.

Results of Lucia Keratoprosthesis Implantation in Severe Corneal Disease

Describe complications, functional success, and retention of the Lucia Keratoprosthesis (KPro). Retrospective interventional case series METHODS: The demographic data, baseline characteristics, complications, functional success, and retention were analyzed for Lucia KPro at the Instituto de Oftalmologia Conde de Valenciana in Mexico City from 2021 to 2023. Multivariate regression analysis and Kaplan-Meier plots were performed to identify associations with functional failure. The main outcome measures were postoperative complications, functional success defined as best-corrected visual acuity (BCVA) ≥20/200 (logMAR 1.0), and device retention rate. Forty-eight eyes of 48 patients (56.88% male) were studied. The mean age at implantation was 57.29 ± 15.63 years (range 27-91), with a mean follow-up of 20.5 ± 8.83 months (range 3-40). Diagnostic indications for implantation included recurrent graft rejection (54.17%), autoimmune disease (20.83%), chemical injury (12.5%), and other (12.5%). At least 1 postoperative complication occurred in 75% of patients, leading to 65 additional interventions (mean number of subsequent procedures: 1.35 ± 1.3, range 0-5). The preoperative BCVA was 2.40 ± 0.36 logMAR. At the final follow-up, 62.5% had achieved functional success and 22.92% had a BCVA of 20/40 (logMAR 0.3) or better. Glaucoma (adjusted OR 469.74, 95% CI 5.02-43939.14, P = .007) and retinal pathology before KPro (adjusted OR 372.38, 95% CI 4.18-33162.11, P = .009) were associated with functional failure. The device remained in place in 95.83% of recipients over the follow-up period. The Lucia KPro offers functional success in severe corneal diseases and excellent retention in the short to intermediate term.

Comparing the prognostic impact of 131I and/or artificial liver support system on liver function failure combined with hyperthyroidism.

Hyperthyroidism, a prevalent endocrine disorder, can lead to complications such as liver failure due to the liver's essential role in thyroid hormone metabolism. The study aimed to elucidate the respective contributions of 131I and/or ALSS in managing hyperthyroidism alongside liver failure. A retrospective analysis was carried out on 74 patients diagnosed with severe liver failure in the context of Graves' disease. Patients were categorized into three groups: group A (n = 34) received 131I treatment, group B (n = 17) underwent 131I and ALSS treatment, and group C (n = 24) received artificial liver support system (ALSS) treatment alone. Throughout the treatment period, the liver function indexes in all groups exhibited a declining trend. The thyroid function of group A and group B treated with 131I was significantly improved compared to that before treatment. There was no significant change in thyroid function in group C. After the correction of hyperthyroidism, significant improvements were observed in the liver function of individuals in groups A and B, particularly with more noticeable amelioration compared to group C. After two months of treatment, the efficacy rates for the three groups were 79.41%, 82.35%, and 60.87% respectively. Mortality rates of the three groups were 5.88%, 17.65%, and 36% (P < 0.01). Group B, receiving both 131I and ALSS treatments, exhibited a lower mortality rate than group C. In cases of severe liver failure accompanied by hyperthyroidism, prompt administration of 131I is recommended to alleviate the adverse effects of hyperthyroidism on liver function and facilitate a conducive environment for the recovery of liver functionality.

Targeting AnxA2-EGFR signaling: hydroxychloroquine as a therapeutic strategy for bleomycin-induced pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a disease that causes progressive failure of lung function, and its molecular mechanism remains poorly understood. However, the AnnexinA2-epidermal growth factor receptor (EGFR) signaling pathway has been identified as playing a significant role in its development. Hydroxychloroquine, a common anti-malarial drug, has been found to inhibit this pathway and slow down the progression of IPF. To better understand the role of the AnxA2-EGFR signaling pathway in pulmonary fibrosis, an in vivo study was conducted. In this study, mice were induced with pulmonary fibrosis using bleomycin, and HCQ was administered intraperitoneally the next day of bleomycin induction. The study also employed nintedanib as a positive control. After the induction, the lungs showed increased levels of fibronectin and vimentin, along with enhanced expression of AnxA2, EGFR, and Gal-3, indicating pulmonary fibrosis. Additionally, the study also found that HCQ significantly inhibited these effects and showed antifibrotic properties similar to nintedanib. Overall, these findings suggest that HCQ can attenuate bleomycin-induced pulmonary fibrosis by inhibiting the AnxA2-EGFR signaling pathway. These results are promising for developing new treatments for IPF.

Lab-on-a-chip models of cardiac inflammation.

Cardiovascular diseases are the leading cause of morbidity and mortality worldwide with numerous inflammatory cell etiologies associated with impaired cardiac function and heart failure. Inflammatory cardiomyopathy, also known as myocarditis, is an acquired cardiomyopathy characterized by inflammatory cell infiltration into the myocardium with a high risk of progression to deteriorated cardiac function. Recently, amidst the ongoing COVID-19 pandemic, the emergence of acute myocarditis as a complication of SARS-CoV-2 has garnered significant concern. Given its mechanisms remain elusive in conjunction with the recent withdrawal of previously FDA-approved antiviral therapeutics and prophylactics due to unexpected cardiotoxicity, there is a pressing need for human-mimetic platforms to investigate disease pathogenesis, model dysfunctional features, and support pre-clinical drug screening. Traditional in vitro models for studying cardiovascular diseases have inherent limitations in recapitulating the complexity of the in vivo microenvironment. Heart-on-a-chip technologies, combining microfabrication, microfluidics, and tissue engineering techniques, have emerged as a promising approach for modeling inflammatory cardiac diseases like myocarditis. This review outlines the established and emerging conditions of inflamed myocardium, identifying key features essential for recapitulating inflamed myocardial structure and functions in heart-on-a-chip models, highlighting recent advancements, including the integration of anisotropic contractile geometry, cardiomyocyte maturity, electromechanical functions, vascularization, circulating immunity, and patient/sex specificity. Finally, we discuss the limitations and future perspectives necessary for the clinical translation of these advanced technologies.

Post-earthquake functional state assessment of communication base station using Bayesian network

The reliability and resilience of communication base stations are critical to the post-earthquake performance of the communication system, and consequently influence the communication, rescue, and emergence management after an earthquake. There is a lack of models that can fully evaluate the post-earthquake functional states of base stations with the consideration of the dependencies between different components. This paper proposes a Bayesian network method to evaluate the post-earthquake functionality of communication base stations. The method considers the dependence between the equipment and its hosting building structure, and the impact of power outages. This model produces seismic functional fragility curves for typical base stations that enable both qualitative and quantitative evaluations of base station functionality. The model is validated using seismic damage data from the Ludian Earthquake. It was found that the proposed model can reasonably predict the post-earthquake functional failure of base stations, in good agreement with the observed seismic damage data. The application of this model provides support for the operation and maintenance of communication base stations, and insights for managing seismic risk and resilience of the communication system.

Failure behavior and probabilistic safety assessment of containment structure under internal pressure considering time-varying prestress loss

This paper adopts a refined method to calculate the prestress loss of containment and evaluates the impact of time-varying effects on the mechanical properties and safety of containment under accident pressure. Firstly, a new method for converting the commonly used creep model into the Kelvin chain creep model is proposed, and rate-type constitutive relationships considering time-varying factors are established. Utilizing the developed subroutine scripts, these constitutive relationships are incorporated into the ABAQUS platform. Subsequently, the prestress losses of containment at different service times are calculated. Finally, the failure behavior and the probabilistic performance of containment under prestress loss and internal pressure conditions are systematically discussed. Results show that the proposed method exhibits high applicability, and the fitted creep compliance function based on the Kelvin chain model agrees well with the original creep compliance function. For the investigated containment, the time-varying prestress loss is most pronounced in the horizontal tendons near penetrations. Under design pressure, the containment remains elastic for all investigated prestress loss conditions, but the structural deformation, steel liner strains, and principal tensile stresses in concrete increase with the increase in time-varying prestress losses. At the limit state, greater time-varying prestress loss makes the containment more prone to functional failure at lower internal pressures. The time-varying prestress loss has a significant impact on the fragility and reliability of the penetrations in containment, while its impact on regular segments is relatively small.

Failure probability of F-100 Pratt &amp; Whitney-220E turbofan engine on F-16 fighting falcon aircraft

Engine failure is a condition where the engine operates outside normal conditions. One of the abnormal conditions that occurs can be caused by a fault that occurs in each engine module. Engine module is one of the components on an aircraft that functions for supports the aircraft to fly and controls all engine operations, wether on the ground and during flight. The problem can occur in each engine module at any time causing engine failure. Therefore, it is necessary to carry out further analysis to determine the cause of the failure that occurred, as well as to implement appropriate mitigation measures. The method used is the Fault Tree Analysis (FTA) method, which is a method for identifying risks that contribute to failure and determining failure probability. From the analysis using the qualitative fault tree analysis method 71 events were obtained with 35 basic events. Meanwhile, the quantitative analysis produces a cumulative probability failure of 0.747. The probability value has almost reached 1, therefore preventive maintenance has to be carried out to prevent functional failure.

Pothole detection and International Roughness Index (IRI) calculation using ATVs for road monitoring

The accelerated deterioration of roads is conditioned by parameters such as climate change, poor construction, and heavy vehicle traffic. Two relevant measures to monitor the condition of a road are the International Roughness Index (IRI) and the number of functional failures in a segment, mainly potholes, since they are associated with higher risks such as accidents or damage to vehicle mechanics. In the state of the art, pothole detection or International Roughness Index (IRI) calculation algorithms are proposed, but they use vehicles designed to produce less vibration and use phones that decrease the performance of the embedded sensors. In addition, some works propose complex algorithms of higher computational load that leads to use more hardware and power consumption. In this context, the present work aims to monitor the condition of a road through low-cost dedicated sensors implemented in an urban patrolling all-terrain vehicles (ATVs), where energy consumption is optimized using low-complexity signal processing techniques for noise reduction and detection algorithms. The results show an average accuracy of 90.5% in the detection of potholes, a relative error of 8.41% in the calculation of the International Roughness Index (IRI) and an average reduction of 65.4% in the monitoring time.

The beginning of iron corrosion - high-resolution visualization with 3D electron tomography

Understanding the genesis and early-phase reactions of iron corrosion is essential for the early detection, mitigation and prevention of metal degradation. In this work, high-resolution 3D tomography of metallic iron oxidation was acquired using high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM). In particular, dendritic capillaries (<0.5 nm) were observed during the initial oxidation of fresh nanoscale zero-valent iron due to the differential oxygen diffusion and iron atoms migration. This observation led to the proposal of a nanoscale “pothole” model for early-phase corrosion, wherein hollowing out of the metal nanoparticle and formation of nanovoids beneath the iron/oxide interface through Kirkendall effect. Coalescence of the nanocapillaries results in the ultimate collapse of metal structure and/or functional failure. Using nanoscale zero-valent iron as a research model, this work provides unprecedented insights into the nano- and atomic-scale mechanisms of iron oxidation, paving the way for advanced detection and prevention strategies for iron corrosion.

Features of the course of menopause in women under chronic stress: An observational cohort study

Background. Functional processes in the female organism at the stage of reproductive function failure in menopause attract considerable interest of researchers. The paper presents a study of great medical, biological and social importance into reproductive function failure in women living in the territories with permanent military operations for a long time and, thus, suffering from post-traumatic syndrome, which significantly affects the character of menopause. Objectives. To identify the features of menopausal syndrome in women who have been living under chronic stress (6–8 years) in the zone of ongoing military operations, namely in the Donetsk and Luhansk People’s Republics, and in women from Rostov Oblast — the region free from active military operations.Methods. An observational cohort study involved 60 women (refugees), long-term residents of the territories with ongoing military operations and 60 long-term residents of the territories without military operations, aged 50–65 years, with clinical manifestations of menopausal syndrome; all women were patients of the Research Institute of Obstetrics and Pediatrics, Rostov State Medical University. In accordance with the Stages of Reproductive Aging Workshop (STRAW+10) classification and clinical manifestations of menopause, two clinical groups (n = 30) were formed from the representatives of each region of residence. Group I included 30 women, aged 50–55, from the Donetsk and Luhansk People’s Republics, who had late menopausal transition (stage -1 of STRAW+10) and menopausal syndrome. Group II involved 30 postmenopausal patients (stages +1 and +2 of STRAW+10), aged 60–65, with menopausal syndrome. Group 1 enrolled 30 residents of Rostov Oblast, aged 50–55, who had late menopausal transition (stage -1 of STRAW+10) and menopausal syndrome, group 2 included 30 postmenopausal patients (stages +1 and +2 of STRAW+10), aged 60–65, with menopausal syndrome. Modified menopausal index was considered as the main indicator of the study. Statistical data processing was carried out by means of Statistica 10.01 (StatSoft, USA), Microsoft Excel 2010 (Microsoft, USA), IBM SPSS 24.0 (IBM, USA), and MedCalc (MedCalc Software, Belgium).Results. Long-term female residents of the territories with ongoing military operations were reported to develop menopausal syndrome more often. Rostov Oblast female residents in the late menopausal transition revealed a statistically significant prevalence of a mild degree of menopausal syndrome in 63.3 % of cases compared to 36.7 % of a similar severity of menopausal syndrome in residents of the Donetsk and Luhansk People’s Republics. Meanwhile, women from the Donetsk and Luhansk People’s Republics were indicated with moderate menopausal syndrome in 50.0 % of cases in late menopausal transition and severe syndrome in 33.3 % in postmenopause versus 23.4 % and 10 % of women from Rostov Oblast, respectively. The intensity of neurovegetative and psycho-emotional disorders in women of both regions increases with the aging process of the reproductive system and appears most pronounced in the postmenopausal period.Conclusion. Residents of the Donetsk and Luhansk People’s Republics, who live in the war zone and are exposed to constant threat to life, develop post-traumatic syndrome which significantly intensifies and modulates the already existing functional and hormonal restructuring in the brain subsystems during perimenopause. Non-uniform functional shifts at different levels of the central nervous system under conditions of chronic stress lead to a significant change in intracerebral processes and to an increase in the occurrence and severity of various dysfunctional deviations.

Micro/Nano Hierarchical Crater-Like Structure Surface With Mechanical Durability and Low-Adhesion for Anti-Icing/Deicing.

Superhydrophobic surfaces have attracted significant attention for their ability to prevent ice formation and facilitate deicing without requiring external energy. However, these surfaces are often vulnerable to damage from external forces, leading to functional failure due to poor mechanical stability, which limits their widespread use. Drawing inspiration from the hierarchical groove of rose petals and the micropapillae of lotus leaves, a simple laser-based method is proposed to create a superhydrophobic surface with a micro/nano hierarchical crater-like structure (HCLS). To enhance the surface, boiling water treatment is applied to induce dense nanostructures, resulting in an optimal contact angle (CA) of 162° and a desirable sliding angle (SA) of 2.0°. The initial ice adhesion strength of HCLS is as low as 1.4kPa and remains below 10kPa even after 300cm sandpaper abrasion. Furthermore, the HCLS demonstrates excellent mechanical durability, maintaining its performance under conditions that simulate the continuous impact of water and sand in extreme weather. This approach offers an innovative design concept that has the potential to advance the development of anti-icing and deicing surfaces for future aircraft.

COPDVD: Automated classification of chronic obstructive pulmonary disease on a new collected and evaluated voice dataset

BackgroundChronic obstructive pulmonary disease (COPD) is a severe condition affecting millions worldwide, leading to numerous annual deaths. The absence of significant symptoms in its early stages promotes high underdiagnosis rates for the affected people. Besides pulmonary function failure, another harmful problem of COPD is the systemic effects, e.g., heart failure or voice distortion. However, the systemic effects of COPD might provide valuable information for early detection. In other words, symptoms caused by systemic effects could be helpful to detect the condition in its early stages. ObjectiveThe proposed study aims to explore whether the voice features extracted from the vowel “a” utterance carry any information that can be predictive of COPD by employing Machine Learning (ML) on a newly collected voice dataset. MethodsForty-eight participants were recruited from the pool of research clinic visitors at Blekinge Institute of Technology (BTH) in Sweden between January 2022 and May 2023. A dataset consisting of 1246 recordings from 48 participants was gathered. The collection of voice recordings containing the vowel “a” utterance commenced following an information and consent meeting with each participant using the VoiceDiagnostic application. The collected voice data was subjected to silence segment removal, feature extraction of baseline acoustic features, and Mel Frequency Cepstrum Coefficients (MFCC). Sociodemographic data was also collected from the participants. Three ML models were investigated for the binary classification of COPD and healthy controls: Random Forest (RF), Support Vector Machine (SVM), and CatBoost (CB). A nested k-fold cross-validation approach was employed. Additionally, the hyperparameters were optimized using grid-search on each ML model. For best performance assessment, accuracy, F1-score, precision, and recall metrics were computed. Afterward, we further examined the best classifier by utilizing the Area Under the Curve (AUC), Average Precision (AP), and SHapley Additive exPlanations (SHAP) feature-importance measures. ResultsThe classifiers RF, SVM, and CB achieved a maximum accuracy of 77 %, 69 %, and 78 % on the test set and 93 %, 78 % and 97 % on the validation set, respectively. The CB classifier outperformed RF and SVM. After further investigation of the best-performing classifier, CB demonstrated the highest performance, producing an AUC of 82 % and AP of 76 %. In addition to age and gender, the mean values of baseline acoustic and MFCC features demonstrate high importance and deterministic characteristics for classification performance in both test and validation sets, though in varied order. ConclusionThis study concludes that the utterance of vowel “a” recordings contain information that can be captured by the CatBoost classifier with high accuracy for the classification of COPD. Additionally, baseline acoustic and MFCC features, in conjunction with age and gender information, can be employed for classification purposes and benefit healthcare for decision support in COPD diagnosis. Clinical trial registration numberNCT05897944.

Redundant series cell voltage measurement circuit design of battery management system for functional safety

In most battery management system (BMS) circuit designs, the analog front end (AFE) chip is used to get the series cell voltage of the battery pack. However, it can lead to incorrect calculations by the BMS, causing errors in battery information, failures in protection control, and triggering a battery system fire accident if the AFE chip is abnormal. Unfortunately, the BMS will never know the correct of measured results if it is measured by a single AFE chip. This paper proposes a redundant series voltage measurement system (RSVMS) for the series cell voltage of the battery pack. The original AFE is referred to as the main AFE (m-AFE). The RSVMS can be regarded as redundant AFE (r-AFE). In this paper, the r-AFE consists of a series cell selector and an analog-to-digital (ADC) converter with an isolated communication function to transmit measurement results to the microcontroller unit (MCU) of the BMS. Due to the hardware requirements of functional safety, it does not allow using two identically designed hardware as redundant systems. To satisfy the hardware level of functional safety and to minimize the hardware cost and size, the series cell selector of r-AFE shares the same hardware circuit as the Active Hybrid Equalizer Circuit (A-HEC). The cell selector of A-HEC is composed of the back-to-back MOSFET switch array with a simple ON/OFF function. The MCU of BMS will identify the abnormal of voltage measurement results when the difference of m-AFE and r-AFE is over the threshold. In summary, r-AFE can ensure the accuracy of cell voltage measurement for m-AFE to avoid significant errors when estimating battery information and avoid disaster caused by failure or malfunction of protection functions. In addition, the m-AFE and r-AFE are two independent designs to avoid similar errors caused by identical circuit configurations.

AFFECT: an R package for accelerated functional failure time model with error-contaminated survival times and applications to gene expression data

BackgroundSurvival analysis has been used to characterize the time-to-event data. In medical studies, a typical application is to analyze the survival time of specific cancers by using high-dimensional gene expressions. The main challenges include the involvement of non-informaive gene expressions and possibly nonlinear relationship between survival time and gene expressions. Moreover, due to possibly imprecise data collection or wrong record, measurement error might be ubiquitous in the survival time and its censoring status. Ignoring measurement error effects may incur biased estimator and wrong conclusion.ResultsTo tackle those challenges and derive a reliable estimation with efficiently computational implementation, we develop the R package AFFECT, which is referred to Accelerated Functional Failure time model with Error-Contaminated survival Times.ConclusionsThis package aims to correct for measurement error effects in survival times and implements a boosting algorithm under corrected data to determine informative gene expressions as well as derive the corresponding nonlinear functions.