Miracle-dz/UniFAR-FTUs huggingface dataset:
Serious complications related to regional anaesthesia: Study of Greek Courts’ Decisions

Background Regional anaesthesia and analgesia present many advantages. Related complications are few and have been fully described. Information on regional anaesthesia malpractice is lacking in Greece. The objectives of the analysis were to highlight areas of high litigation risk and report the financial impact of claims. Methods Published judicial decisions of criminal, civil, administrative and disciplinary content, from 1995 to 2020, were searched in the legal information banks. The court decisions were analysed by an expert in collaboration with the lawyers of the investigation. Results A total of 26 court decisions related to complications from regional anaesthesia were found involving 10 cases, which comprised: 8 convictions, 1 referral of the case for a new expert opinion and 1 acquittal. In 6 cases the medical negligence involved complications after epidural anaesthesia and in 2 after subarachnoid anaesthesia. In 1 case there was collective liability of the anaesthesiologist and the obstetrician for negligent homicide and in 7 cases liability of the anaesthesiologist for bodily injuries. The duration of the litigation was 5–16 years. Conclusions Analysis of court cases made it possible to identify the causes that led to complications during regional anaesthesia. Informed consent, non-traumatic technique, careful patient selection, adherence to safety rules, and early diagnosis and treatment of complications are essential to avoid permanent injury.
Dynamic Output‐Feedback Control for T‐S Fuzzy Systems with Input Time‐Varying Delay

This paper considers the problem of the H∞ control for T‐S fuzzy systems with input time‐varying delay via dynamic output feedback. Firstly, by applying the reciprocally convex approach, new delay‐dependent sufficient condition for H∞ performance analysis is obtained. Then, a less conservative condition for the existence of the H∞ controllers is given in terms of linear matrix inequalities (LMIs). Moreover, in the considered system, the time‐delay term is included in the measured output. This results in the difficulty in designing the controllers being increased and the obtained results being applied to a wider class of fuzzy systems than the most existing ones. The main contribution of this work lies in the application of the reciprocally convex inequality and the time‐delay term included in the measured output. Finally, the advantages and effectiveness of the present results are shown by several numerical examples.
Analysis of Higher Dimensional Converter Using Graphical Approach

The main intention of this paper is to propose a methodology for deriving a reduced-order model from a complex n-dimensional system. The mathematical model for a voltage-lift-based quadratic high-gain dc-dc converter is proposed with a reduced-order model in continuous conduction mode (CCM). The chosen topology amalgamates voltage-lift cells with a quadratic boost topology to obtain improved voltage gain. The operating principle of the configuration with steady-state analysis is discussed in CCM. The state-space averaging procedure and switching flow graph (SFG) obtain the open-loop performance to design a suitable controller for the converter. To reduce the state variables and simplify the modelling, reduced-order modelling is carried out for the topology. Additionally, the pole clustering method minimizes the converter’s order. The impact of parameter variation with the pole-zero location is discussed elaborately. The Ziegler-Nicholas tuning technique attains the PI controller’s proportional and integral time constant. The closed-loop response presents better step response output than the open-loop response. Time-domain parameters are compared for open-loop and closed-loop to validate the controller. Lastly, a 50 W prototype is used for evaluating the converter’s ability at a steady state.
Assisted Reproductive Technology and Breech Delivery: A Nationwide Cohort Study in Singleton Pregnancies

Since essential factors have changed in recent years in assisted reproduction technologies (ARTs), this study reassessed the association between ART and breech presentation. We primarily aimed to estimate the correlation between ART and breech at delivery. Secondary purposes were to evaluate the correlation between other subfertility treatments (OSTs) and breech and to assess possible confounding factors and temporal trends. This study investigated the 31,692,729 live birth certificates from US states and territories in the 2009–2020 period. The inclusion criteria were singleton births reporting the method of conception and the presentation at delivery. The outcome was the breech presentation at delivery, while the primary exposure was ART, the secondary exposure was OST, and the potential confounding factors from the literature were considered. ART (OR 2.32 CI.95 2.23–2.41) and OST (OR 1.79 CI.95 1.71–1.87) were independent and significant risk factors for breech at delivery (p < 0.001). This study confirmed breech presentation risk factors maternal age, nulliparity, tobacco smoke, a previous cesarean delivery (CD), neonatal female sex, gestational age, and birth weight. Black race and Hispanic origin were verified to be protective factors. We found breech prevalence among ART and OST to be stable during the study period. Meanwhile, newborn birth weight was increased, and the gap between breech and other presentations in ART was reduced. Our results indicate that singleton pregnancies conceived by ART or OST were associated with a higher risk of breech at delivery. Well-known risk factors for the breech presentation were also confirmed. Some of these factors can be modified by implementing interventions to reduce their prevalence (e.g., tobacco smoke and previous CD).
The Influence of Non-Performing Loans on Profitability at Bank Rakyat Indonesia Persero Tbk

The purpose of this study is to obtain developments to what extent the influence of Non-Performing Loans (NPL) on Profitability (ROA). The method used in this research is descriptive and verification method by testing the hypothesis. From the research results, data analysis shows that the influence of variable X or non-performing loans on profitability is 70.4% and the remaining 29.6% is influenced by other variables not tested in this study. Besides that the t-table is still in the area of HO rejection, so HO is rejected and H1 is accepted, so it can be concluded that Non-Performing Loans have a significant effect on Profitability (ROA) at PT. Bank Rakyat Indonesia, Tbk. Therefore, through the research of PT. Bank Rakyat Indonesia, Tbk is expected to increase the profit value by taking into account the NPL value analysis. Keywords: Non-Performing Loans (NPL); Profitability (ROA); Bank; hypothesis; Profit Abstrak Tujuan penelitian ini adalah untuk memperoleh perkembangan sejauh mana pengaruh Non Performing Loan (NPL) terhadap Profitabilitas (ROA). Adapun metode yang digunakan pada penelitian ini adalah metode deskriptif dan verifikatif dengan melakukan uji hipotesis. Dari hasil penelitian analisis data menunjukkan bahwa Pengaruh variabel X atau non perfoming loan terhadap Profitabilitas sebesar 70,4% dan sisanya 29,6% dipengaruhi variabel lain yang tidak diuji dalam penelitian ini. Selain itu t-tabel masih berada didaerah penolakan HO maka HO ditolak dan H1 diterima, sehingga dapat disimpulkan Non Performing Loan berpengaruh signifikan terhadap Profitabilitas (ROA) pada PT. Bank Rakyat Indonesia, Tbk. Oleh sebab itu, melalui penelitian PT. Bank Rakyat Indonesia, Tbk ini diharapkan dapat meningkatkan nilai laba dengan memperhatikan analisis nilai NPL. Kata Kunci: Kredit bermasalah (NPL); Profitabilitas (ROA); Bank; Hipotesis; Laba
JRCC-Net: A Segmentation Network With Joint Representation and Contrast Clustering for Surface Anomaly Detection

The goal of unsupervised surface anomaly detection is to detect areas of the image that are different from the normal pattern, which can be considered as a semantic segmentation problem oriented to anomalous patterns. However, this problem is challenging due to the lack of actual available anomaly sam- ples. In this article, we transform unsupervised anomaly detection into a self-supervised problem by the proposed anomaly simulation strategy. Using only normal samples for training, real anomalies appearing in the inference phase can be detected. Thus, we propose a segmentation network with joint representation and contrast clustering (JRCC-Net). The proposed method learns a joint representation between simulated samples and the magnitude of the differences in distance from their nearest memory samples, as well as a decision boundary between normal and anomalous samples. Moreover, we propose a novel contrast clustering-based representation learning strategy, which allows the model to better learn general patterns from normal samples and mine the latent differences between simulated anomalous and normal samples. JRCC-Net is able to locate anomalies directly in an end-to-end manner and can be trained well with our elaborate anomaly simulation strategy. On the challenging MVTec AD dataset, JRCC-Net outperforms the state-of-the-art unsupervised methods, achieving 98.2% image-level area under the receiver operating characteristics (AUROC) and 97.7% pixel-level AUROC, respectively, and even on the extensively used DAGM dataset, its localization accuracy greatly exceeds that of fully supervised methods.
The Prevalence of Xerostomia in Older Thai Individuals with Type II Diabetes Mellitus and Its Association with Type of Toothpaste and Oral Functions: A Cross-Sectional Study Using Questionnaires

Aim: To investigate the prevalence of xerostomia in older people with diabetes mellitus and its impacts on oral functions, as well as to determine potential risk factors for xerostomia. Methods: An analytical cross-sectional study was conducted on 623 older type 2 diabetes mellitus (T2DM) Thai people using valid structural questionnaires. Patients were interviewed, and data were recorded. Xerostomia was assessed using subjective symptom questionnaires. Risk factors for xerostomia were analyzed using bivariate and multiple logistic regression analyses. Results: Among the study participants, 38.4% of the older T2DM people had xerostomia, which is associated with sex, age, type of toothpaste, years of diabetes, hemoglobin A1c level, other systemic diseases, medication, smoking, alcohol consumption, and denture wearing. It was significant that xerostomia was associated with toothpaste containing spicy herbal extracts (OR: 9.32 [3.46 to 15.25]), while toothpaste containing artificial sweeteners tended to lower the risk of xerostomia. In addition, older T2DM adults with xerostomia had greater impaired oral functions, which include difficulties in speaking (OR: 3.31 [1.11 to 9.80]), tasting (OR: 5.12 [3.26 to 8.06]), swallowing (OR: 3.59 [2.32 to 5.53]), and chewing (OR: 3.34 [1.15 to 5.82]). Conclusions: Xerostomia is prevalent in older Thai people with T2DM. The results suggest that toothpaste containing spicy herbal extracts might increase the risk of xerostomia, resulting in various oral function problems. Therefore, greater awareness of xerostomia in this group should be raised to monitor dental health, and professionals should work in parallel with other aspects of oral health promotion.
Pre-sowing treatments to improve seed germination and seedling growth of Commiphora swynnertonii (Burrt.) and Synadenium glaucescens (Pax.)

Medicinal and pesticidal plant propagation is hampered by poor seed germination due to seed dormancy. This study aimed to enhance seed germination and seedling growth using various pre-sowing treatments. A triplicated two-factor experiment in a Randomized Complete Block design was used. Soaking in water at 25°C for 24 h (T1), soaking in 60°C hot water for 10 min (T2), 10 ppm Potassium nitrate (KNO 3 ) treatment for 24 h (T3), 20 ppm Potassium nitrate (KNO 3 ) treatment for 24 h (T4), Treating seeds with Gibberellin (GA 3 ) solution at 250 ppm (T5), GA 3 Treating seeds with Gibberellin (GA 3 ) solution at 500 ppm for 72 (T6), Treating seeds with Gibberellin (GA 3 ) solution at 1000 ppm for 72 h (T7), and seeds without any pre-treatment were sown and used as control (T o ) on seed germination and seedling growth of two MPP species. The ability of a pre-sowing treatment to break seed dormancy was significantly dependent (p = 0.002) on the plant species. The effects due to interaction between pre-sowing seed treatment and plant species on seedling growth parameters (height, branches/shoot, leaves/shoot/, leaf area, fresh and dry weight) were significant (p < 0.05). These results provide the basis for the sustainable use of MPPs through propagation and conservation.
IKA-FLOW : A Flexible Body Overset Mesh Implementation for Fish Swimming

Simulation of inertial aquatic swimmers requires fluid structure interactions with temporal body geometry deformation. In practice, his results in a change of the computational domain boundaries that represent the ”swimmer. ” These simulations are traditionally done sing body-fitted mesh and mesh morphing methods, but have drawbacks of negative cell volumes and small time-steps to account for the complex swimming motion. In contrast, the overset mesh method, also provided by OpenFOAM®, overcomes most of the drawbacks of the mesh morphing method at the expense of interpolation error. The current OpenFOAM® overset motion library only supports rigid body motion and cannot be used to resolve a body undergoing undulation. A modified motion solver is presented that allows for the complex mesh motion of an overset mesh for four body-caudal fin (BCF) virtual swimmers. The results of this solver are compared with published data of body-fitted meshes. The effect of different simulation parameters (including number of solving iterations, time delay, and temporal resolution) is investigated. Additionally, a novel simulation and comparison of the Ostraciiform locomotion mode with Anguilliform, Carangiform, and Thunniform modes are made investigating the wake, drag and lift. It is concluded that fish undulation has a marked effect on reducing lift generation. Lastly, a comparison of turbulence models (Spalart-Allmaras, k − ω SST, and k − kL − ω) at multiple Reynolds numbers shows that all three models have similar performance at lower Reynolds numbers but diverge at higher numbers.
Characterization and Control of Root Rot and Wilt Fungi of Geranium (Pelargonium graveolens L.) with Special Reference to First Record for Fusarium proliferatum as Wilt Pathogen on Geranium in Egypt

Geranium root rot and wilt are the most destructive geranium diseases, limiting global production. During the present study, yielded fungal isolates belonging to four fungal species were recovered from diseased geranium ( Pelargonium graveolens L.) plants showing root rot and wilt symptoms collected from nurseries and fields in Qaliobia and Behera governorates during 2021. Four fungal species were identified as Fusarium proliferatum, Fusarium solani, Macrophomina phaseolina , and Rhizoctonia solani with frequencies of 40.78, 17.48, 22.33, and 19.42, respectively. Pathogenicity tests showed that all the tested fungi were pathogenic on geranium to different degrees. However, Fusarium proliferatum showed only wilt symptoms recognized with yellowing of leaves, discoloration of the internal vascular tissues, and no rot symptoms were developed on the plants. According to the available literature, the present study suggests that this is the first report of F. proliferatum as a wilt pathogen of geranium in Egypt. Moreover, control studies were performed in vitro and under greenhouse and field conditions to control root rot and wilt fungi of geranium. The in vitro studies showed that the three tested essential oils, i.e . , marjoram, peppermint, and thyme, completely (100%) inhibited the growth of the tested fungi in vitro at 4000, 5000, and 4000 ppm, respectively. Also, the greenhouse experiment showed that dipping healthy rooted cuttings in the tested essential oils at the above-mentioned concentrations before planting with another treatment as soil drench at 30 days after planting significantly decreased disease severity percentages (DS%) of root rot and wilt of geranium by 89.68, 71.07, and 92.20%, for the three tested essential oils, respectively. This is compared to 75.37, and 61.61, for the check treatments with Plant Guard (4 mL/l) biocide, Rhizo-N )3 g/l) biocide, and Occidor 50% SC (2g/l) fungicide, respectively, and compared to 89.42% for Occidor 50% SC (2g/l) fungicide. Meanwhile, a similar trend was obtained in fields naturally infested with the root rot and wilt fungi of geranium in Beheira and Qaliobia governorates during 2022/2023 season. Treatments by dipping the rooted cuttings before planting and then treatment at 30 days after planting as soil drench in marjoram, peppermint, and thyme essential oils, significantly, decreased DS% by 49.50, 34.55, and 55.87 %, significantly. This is compared to 43.49, 49.23, and 55.87% for Plant (4 mL/l), and Rhizo-N )3 g/l) and Occidor 50% SC (2g/l) fungicide, respectively. Furthermore, all these essential oils treatments under field conditions showed significant improvement effects in growth characteristics (plant height, number of branches, fresh weight) and the oil productivity of geranium grown in field naturally infested with root rot and wilt fungi.
Algebraic descriptions of weighted directed graphs and their applications

1: We show that an algebraic formulation of weighted directed graphs leads to introduce a k-vector space equipped with two coproducts ∆ and ∆ verifying the so-called coassociativity breaking equation (∆⊗id)∆ = (id⊗∆)∆. Such a space is called a L-coalgebra. Explicit examples of such spaces are constructed and links between graph theory and coassociative coalgebras are given.
LGMA-DRSN: a lightweight convex global multi-attention deep residual shrinkage network for fault diagnosis

Recently, the fault diagnosis domain has witnessed a surge in the popularity of the deep residual shrinkage network (DRSN) due to its robust denoising capabilities. In our previous research, an enhanced version of DRSN named global multi-attention DRSN (GMA-DRSN) is introduced to augment the feature extraction proficiency of DRSN specifically for noised vibration signals. However, the utilization of multiple attention structures in GMA-DRSN leads to an escalation in the computational complexity of the network, which may pose practical deployment challenges. To address this limitation, this paper proposes a lightweight variant of GMA-DRSN, referred to as lightweight convex global multi-attention deep residual shrinkage network (LGMA-DRSN), building upon our prior work. Firstly, the numerical variation regularity of the adaptive inferred slope parameters in the global parametric rectifier linear unit is analyzed, where we surprisingly find that a convex parameter combination always occurs in pairs. Based on this convex regularity, the sub-network structure of the adaptive inferred slope with attention mechanism is optimized, which greatly reduces the computational complexity compared to our previous work. Finally, the experimental outcomes demonstrate that LGMA-DRSN not only enhances diagnostic efficiency, but also ensures a high level of diagnostic accuracy in the presence of noise interference, when compared with our prior work.
YouTube Influencer: How Source Credibility and Information Quality Influence Destination Image and Visit Intention of Young Travelers?

This study aims to analyze the effects of YouTube influencers’ source credibility and the information quality of the platform on destination image and young travellers’ intention to visit a destination. Stimulus-organism-response (SOR) theory was adopted to develop the tested research model. This study applied a quantitative approach where primary data was collected through online surveys to 198 YouTube subscribers who had watched the examined YouTube channels’ content. The PLS-SEM technique was utilized to assess the structural model in the study. The results of this study show that source credibility had a significant positive effect on information quality, destination image, and visit intention. The information quality positively affected destination image but did not directly impact the visit intention. Furthermore, the destination image significantly mediates the effect of source credibility and information quality on visit intention. This study enriches the literature on the relationships among source credibility, information quality, and how these credibility and information quality could influence the destination image and young travellers’ intention to visit a destination in an emerging country like Indonesia. Keywords— Destination Image; Information Quality; Source Credibility; Visit Intention: YouTube Influencer; Young Travelers.
On stable region-of-interest reconstruction in tomography: examples of non-existence of bounded inverse

In applications of computerized tomography (CT) it is often of interest to reconstruct a function in a proper subset, the region of interest (ROI), of its support from a proper subset of a full CT-scan. In several recent works it has been shown that stable ROI reconstruction is possible in certain limited data situations. In this paper we investigate the limits of what is possible in that direction by proving that reconstruction in an interior ROI is severely unstable for a certain set of data that contains integrals over all lines that intersect the ROI and is large enough for the unknown function to be uniquely determined.
Impact of wind profiles on ground-generation airborne wind energy system performance

Abstract. This study investigates the performance of pumping-mode ground-generation airborne wind energy systems (AWESs) by determining cyclical, feasible, power-optimal flight trajectories based on realistic vertical wind velocity profiles. These 10 min profiles, derived from mesoscale weather simulations at an offshore and an onshore site in Europe, are incorporated into an optimal control model that maximizes average cycle power by optimizing the trajectory. To reduce the computational cost, representative wind conditions are determined based on k-means clustering. The results describe the influence of wind speed magnitude and profile shape on the power, tether tension, tether reeling speed, and kite trajectory during a pumping cycle. The effect of mesoscale-simulated wind profiles on power curves is illustrated by comparing them to logarithmic wind profiles. Offshore, the results are in good agreement, while onshore power curves differ due to more frequent non-monotonic wind conditions. Results are references against a simplified quasi-steady-state model and wind turbine model. This study investigates how power curves based on mesoscale-simulated wind profiles are affected by the choice of reference height. Our data show that optimal operating heights are generally below 400 m with most AWESs operating at around 200 m.