Miracle-dz/UniFAR-FTUs huggingface dataset:
Intra-abdominal fat volume estimation by multi-detector rows computed tomography: relevance in surgical fellowship training program in Shanghai: a retrospective study

Background Intra-abdominal fat volume (IFV) has been shown to have a negative impact on surgical outcomes in gastric cancer (GC) and other gastrointestinal surgeries. The purpose of this study is to look into the relationship between IFV and perioperative outcomes in GC patients using multi-detector rows computed tomography (MDCT) and assess the importance of implementing this observation in current surgical fellowship training programs. Methods Patients with GC who underwent open D2 gastrectomy between May 2015 and September 2017 were included in the study. Based on MDCT estimation, patients were divided into high IFV (IFV ≥ 3,000 ml) and low IFV (IFV < 3,000 ml) groups. Perioperative outcomes for cancer staging, type of gastrectomy, intraoperative blood loss (IBL), anastomotic leakage, and hospital stay were compared between the two groups. This study was registered as CTR2200059886. Results Out of 226 patients, 54 had early gastric carcinoma (EGC), while 172 had advanced gastric carcinoma (AGC). There were 64 patients in the high IFV group and 162 in the low IFV group. The high IFV group had significantly higher IBL mean values (p = 0.008). Therefore, having a high IFV was a risk factor for the occurrence of perioperative complications (p = 0.008). Conclusions High IFV estimated by MDCT prior to GC surgery was associated with increased IBL and postoperative complications. Incorporating this CT-IFV estimation into surgical fellowship programs may aid aspiring surgeons in selecting patients during independent practice in their learning curve and surgical practice for the most appropriate approach for treating GC patients.
Non rigid geometric distortions correction - Application to atmospheric turbulence stabilization

A novel approach is presented to recover an image degraded by atmospheric turbulence. Given a sequence of frames affected by turbulence, we construct a variational model to characterize the static image. The optimization problem is solved by Bregman Iteration and the operator splitting method. Our algorithm is simple, efficient, and can be easily generalized for different scenarios.
LED Illumination Modules Enable Automated Photoautotrophic Cultivation of Microalgae in Parallel Milliliter-Scale Stirred-Tank Bioreactors

Scalable lab-scale photobioreactors are needed for the exploration of new and improved photoautotrophic bioprocesses. Microbioreactor systems in which parallel bioreactors operate automatically are frequently employed to increase the speed of strain selection as well as the bioprocess-based exploration of heterotrophic fermentation processes. To enable the photoautotrophic operation of a commercially available parallel microbioreactor system with 48 stirred-tank bioreactors, LED illumination modules were designed to allow for individual light supply (400–700 nm) for each of the parallel bioreactors automated by a liquid handling station that performs both individual pH control and OD750 detection. The illumination modules enable dynamic variation of the incident light intensities of up to 1800 µmol m−2 s−1. Automated liquid level detection and volume control of each individual mL-scale gassed photobioreactor has to be established to compensate for evaporation because of the long process times of several days up to weeks. Photoautotrophic batch processes with Microchloropsis salina that employ either varying constant incident light intensities or day and night dynamics resulted in a standard deviation of OD750 of up to a maximum of 10%, with the exception of high-photoinhibiting incident light intensities. The established photoautotrophic microbioreactor system enables the automated investigation of microalgae processes in up to 48 parallel stirred photobioreactors and is thus a new tool that enables efficient characterization and development of photoautotrophic processes with microalgae.
Position Control of a Planar Three-link Underactuated Mechanical System Based on Model Reduction

This paper presents a position control method based on model reduction for a planar three-link passive-activeactive(PAA) under-actuated mechanical system with a passive first joint.Firstly,a mathematical model of the system is built,and its integral characteristic is analyzed.Next,the partially integrable three-link system is reduced to two completely integrable two-link systems by the method of piecewise degree reduction,and the state constraint relationships of the system between the active fink and the passive link can be obtained based on the two subsystems.Then,the target angles of the active links are calculated by particle swarm optimization(PSO) algorithm according to the target position of the end of the system.Finally,the controllers of the two link subsystems are designed respectively to achieve the system control objective from any initial position to any target position.Simulation results demonstrate the vafidity of the proposed control method.
Ocular partial-coherence interferometry

In the past interferometry has been applied in three main fields. Fringe interferometry has been used for the topographic measurement of surfaces. Interferometric length measurement techniques have been used for the measurement of distances, refractive indices, and wavelengths. In addition interferometric techniques have also been used in synthetic aperture imaging. Here we discuss various interferometric techniques which can be used in ophthalmology, describe the problems involved and present the results obtained so far.
In vitro and in silico investigation of garlic’s (Allium sativum) bioactivity against 15-lipoxygenase mediated inflammopathies

Introduction: Garlic (Allium sativum) is widely used as a flavor-enhancing dietary ingredient and exhibits a wide spectrum of pharmacological effects. This study aimed to investigate the therapeutic effects of aqueous garlic extract to explore the bioactivity against 15-lipoxygenase (15-LOX) mediated inflammopathies. Methods: In this study, the antioxidant (DPPH free radical scavenging assay and reducing power assay), anti-inflammatory (hypotonicity-induced hemolysis assay and 15-LOX inhibition assay) and anticoagulation (serine protease inhibition assay and prothrombin time assay) effects of the aqueous garlic extract were investigated. Furthermore, in silico molecular docking and dynamic simulation analysis of reported small compounds of garlic against 15-LOX1 and 15-LOX2 were performed to figure out the most efficient phytochemical ligands and validate the anti-inflammatory potential. Results: The DPPH scavenging effect and the reducing power of the extract were found with the IC50 of 213.87 ± 1.49 μgmL-1 and EC50 of 124.78 ± 3.39 μgmL-1, respectively. In the hypotonicity-induced hemolysis and 15-LOX inhibition assay, the IC50 values were observed as 147.59 ± 2.98 μgmL-1 and 250.05 ± 8.48 μgmL-1, respectively. The extract inhibited serine protease activity with an IC50 of 301.33 ± 1.31 μgmL-1 and prevented blood coagulation for 10.05 ± 0.35 minutes in prothrombin time assay. The in silico study identified Rhamnetin as a potential 15-LOX1 and 15-LOX2 inhibitor, and it exhibited a stable interaction with the targets throughout the 100 ns dynamic simulation. Conclusion: The findings of this study provide molecular insights into garlic’s medicinal properties as well as its bioactive compounds, which can be potential therapeutic interventions for 15-LOX mediated inflammations.
Cefepime-Induced Neutropenia: A Case Report and Literature Review

Abstract Cefepime is a fourth-generation cephalosporin utilized in treatment of multiple Gram-negative and -positive infections. The current report presents a case of 50-year-old man admitted with epidural abscess who developed neutropenia after prolonged use of cefepime. The neutropenia developed after 24 days of cefepime treatment and resolved 4 days after cessation of cefepime. Assessment of the patient’s profile indicated no other possible cause for neutropenia. A literature review was done, and is presented herein to compare and identify the pattern of cefepime-induced neutropenia in 15 patients. The data presented in this article highlight that despite its rarity, cefepime-induced neutropenia should be considered by clinicians when planning a prolonged course of cefepime.
A Highly Linear Temperature Sensor Operating up to 600°C in a 4H-SiC CMOS Technology

In this work, a highly linear temperature sensor based on a silicon carbide (SiC) p-n diode is presented. Under a constant current biasing, the diode has an excellent linear response to the temperature (from room temperature to 600°C). The best linearity (coefficient of determination ${R}^{{2}}$ = 99.98%) is achieved when the current density is 0.53 mA/cm2. The maximum sensitivity of the p-n diode is 3.04 mV/°C. The temperature sensor is fully compatible with Fraunhofer Institute (FHG) IISB’s open SiC CMOS (complementary metal-oxide-semiconductor) technology, thus enabling the monolithic integration with SiC readout circuits for high-temperature applications. The sensor also features a simple fabrication process. To our knowledge, the presented device is the first SiC diode temperature sensor that does not require a mesa etch or backside contacts.
Global Comparison of CFD and Wind-Tunnel-Derived Force and Moment Databases for the Space Launch System

Recently a very large (739 runs) collection of high-fidelity RANS CFD solutions was obtained for Space Launch System ascent aerodynamics for the vehicle to be used for the first exploratory (unmanned) mission (EM-1). The extensive computations, at full-scale conditions, were originally developed to obtain detailed line and protuberance loads and surface pressures for venting analyses. The line loads were eventually integrated for comparison of the resulting forces and moments to the database that was derived from wind tunnel tests conducted at sub-scale conditions. The comparisons presented herein cover the ranges 0.5 < or = M(infinity) < or = 5, 6deg < or = alpha < or = 6deg, and 6deg < or = beta < or = 6deg. For detailed comparisons, slender-body-theory-based component build-up aero models from missile aerodynamics are used. The differences in the model fit coefficients are shown to be relatively small except for the low supersonic Mach number range, 1.1 < or = M(infinity) < or = 2.0. The analysis is intended to support process improvement and development of uncertainty models.
Blind Quality Evaluator of Light Field Images by Group-Based Representations and Multiple Plane-Oriented Perceptual Characteristics

Due to the emergency of multi-view cameras and commercial Light Field (LF) cameras, the demand of high-performance LF quality evaluator is of great significance for guiding LF acquisition, processing and application and further promoting the visual perceived quality of LF visualizations. However, LF Images (LFIs), as high-dimensional data, suffer from various quality degradations not only in the spatial domain but also in the angular domain. Therefore, it is of great challenge to predict LF quality accurately. An effective LF evaluator should be able to represent these heterogeneous artifacts. In this paper, we provide a novel No-Reference LF Quality Assessment Evaluator (NR LF-QAE) to tackle this problem. Firstly, to measure angular consistency among viewports, we utilize group-based representations to character information similarity of aligned view stacks. Secondly, to better describe the texture information of LFIs, unifying spatial-angular texture statistic measurement is performed via Local Binary Patterns from Three Orthogonal Planes (LBP-TOP). Thirdly, we design 3D Log-Gabor filters to extract LF global structure information in Sub-Aperture Images (SAIs) as spatial feature characterizations and 2D Log-Gabor filters are adopted to characterize ray direction/depth information in Epipolar Plane Images (EPIs) as angular feature characterizations. By comprehensive LF information analyses in angular consistency and spatial-angular feature extraction with texture and structure descriptors, experimental results demonstrate the superiority of the proposed NR LF-QAE over the state-of-the-art comparative models in predicting the quality of LFIs on three available benchmark databases.
Evaluation of an Augmented Reality for Historical Context Experiences of 3D Restored Court Paintings

Court painting is a traditional Korean type of painting that depicts royal events. It should be understood in the context of royal rituals and historical writing. Therefore, it is only possible for visitors of a museum with historical knowledge to interpret the content accurately. This problem is often identified in traditional paintings in other countries, and existing methods have attempted to deal with it using digital media technologies. Most methods aim to reconstruct paintings as 3D virtual objects for visitors to view them. However, these methods prevent visitors from interacting with the historical events depicted in the paintings and do not explain the essential historical facts and stories that the paintings leave out. In this study, we propose an augmented reality system that provides 3D virtual restorations of information necessary for understanding court paintings and supports historical context experiences of royal events. Specifically, we restore the information required for the interpretation of the painting to a virtual 3D object so that visitors can intuitively understand the historical stories missing from the painting. In addition, the system allows visitors to experience royal events through various interactions. The structural design combines experiential learning theory and digital storytelling so that visitors can be exposed to historical knowledge in a stepwise manner. According to the user study results, our system provides visitors with a more immersive experience and gives more accurate information about royal events compared to the existing method. This result suggests that the proposed system effectively communicates historical information and stories of court paintings to visitors who view paintings that require prior historical knowledge.
Effects of Diabetes and Voluntary Exercise on IgA Concentration and Polymeric Immunoglobulin Receptor Expression in the Submandibular Gland of Rats

Background and Objectives: Patients with diabetes are more susceptible to upper respiratory tract infections (URTIs) because they are easily infected. Salivary IgA (sali-IgA) levels play a major role in transmitting URTIs. Sali-IgA levels are determined by salivary gland IgA production and polymeric immunoglobulin receptor (poly-IgR) expression. However, it is unknown whether salivary gland IgA production and poly-IgR expression are decreased in patients with diabetes. While exercise is reported to increase or decrease the sali-IgA levels, it is unclear how exercise affects the salivary glands of patients with diabetes. This study aimed to determine the effects of diabetes and voluntary exercise on IgA production and poly-IgR expression in the salivary glands of diabetic rats. Materials and Methods: Ten spontaneously diabetic Otsuka Long–Evans Tokushima Fatty (OLETF) rats (eight-week-old) were divided into two groups of five rats each: a non-exercise group (OLETF-C) and a voluntary wheel-running group (OLETF-E). Five Long–Evans Tokushima Otsuka (LETO) rats without diabetes were bred under the same conditions as the OLETF-C. Sixteen weeks after the study began, the submandibular glands (SGs) were collected and analyzed for IgA and poly-IgR expression levels. Results: IgA concentrations and poly-IgR expression levels in SGs were lower in OLETF-C and OLETF-E than in LETO (p < 0.05). These values did not differ between the OLETF-C and OLETF-E. Conclusions: Diabetes decreases IgA production and poly-IgR expression in the salivary glands of rats. Moreover, voluntary exercise increases sali-IgA levels but does not increase IgA production and poly-IgR expression in the salivary glands of diabetic rats. Increasing IgA production and poly-IgR expression in the salivary glands, which is reduced in diabetes, might require slightly higher-intensity exercise than voluntary exercise under the supervision of a doctor.
Distributed LSTM-GCN-Based Spatial–Temporal Indoor Temperature Prediction in Multizone Buildings

Indoor temperature prediction of multiple zones in near future horizons is vital in developing an optimal regulation strategy of heating, ventilation, and air conditioning systems in large-scale complex buildings. This is, however, challenging due to the spatial–temporal correlation and multivariable coupling characteristics. This article proposes a novel deep learning framework incorporating the distributed long short-term memory and graph convolution network namely DL-GCN for indoor temperature prediction in large public buildings, aiming to learn the spatial–temporal correlation and multivariable coupling features. First, the indoor temperature and humidity data from different zones are handled by GCN networks to extract the temperature spatial features. Then, in the distributed LSTM module, other data, such as light and ac power consumption, are fused with the outputs of the GCN module, respectively, in a distributed way to learn the coupling interactions and temporal characteristics between these variables. Comparison study and ablation experiments are conducted using real datasets from a large-scale building to verify its effectiveness and superior performance in multizone indoor temperature prediction.
A response-adaptive design targeting the best treatment for clinical trials with continuous responses

A response-adaptive design is used in a comparison study between treatment effects in order to skew the allocation probability of a patient to a treatment based on the data accrued during the study. We focus on two goals: (a) to collect evidence for determining the superior treatment and (b) to bias, along the experiment, the allocation probability toward the better treatment. In this study we consider a scheme implemented by a generalized urn model introduced in Muliere et al. (2006a). This design is optimal in the sense that the proportion of patients assigned to the better treatment converges to one as the number of patients involved in the experiment increases to infinity. This property is very desirable from an ethical point of view and it differentiates this design from most of the procedures proposed in literature, which have an asymptotic target allocation in $(0,1)$. Moreover, the design can also be used for experiments with responses with continuous distributions. We consider the following inferential problem: the experimenter wants to test the null hypothesis that the two treatments, say B and W, are equivalent, in the sense that the response means $\mu_B$ and $\mu_W$ are equal, against the alternative hypothesis that $\mu_B > \mu_W. $ In May and Flournoy (2006) and in May (2007), the usual test statistic $\zeta_0$ for comparing the difference of means is studied, and asymptotic normality of $\zeta_0$ is proved when the null hypothesis is true. Under the alternative hypothesis, the asymptotic distribution of $\zeta_0$ is a mixture of normals. Through numerical simulations we study the mixing distribution in order to evaluate the power function of the test. We investigate the performances of this adaptive design, following the guideline for the evaluation of a response-adaptive design proposed in Paganoni and Secchi (2007). \begin{thebibliography}{9} \bibitem{May.07} May, C. (2007). Asymptotics in a randomly reinforced P\'{o}lya urn model for sequential, response-adaptive designs. {\em Ph.D. Thesis}. \bibitem{May.et. Flournoy.06} May, C. Flournoy, N. (2006). Asymptotics in response-adaptive designs generated by a two-color, randomly reinforced urn. {\em Preprint}. \bibitem{Muliere.et. al.06} Muliere, P., Paganoni, A.M. and Secchi, P. (2006a). A randomly reinforced urn, {\em Journal of Statistical Planning and Inference}, 136, 1853-1874. \bibitem{Muliere.et. al.06b} Muliere, P., Paganoni, A.M. and Secchi, P. (2006b). Randomly reinforced urns for clinical trials with continuous responses, {\em SIS - Proceedings of the XLIII Scientific Meeting, Invited Session 9}, CLEUP Padova, 403-414. \bibitem{Paganoni.et. Secchi.07} Paganoni, A.M., Secchi, P. (2007). A numerical study for comparing two response-adaptive designs for continuous treatment effects, {\em Statistical Methods and Applications}. {\em In press}. \end{thebibliography}
Si–Sn codoped n-GaN film sputtering grown on an amorphous glass substrate

DC-pulse magnetron sputtering was utilized to deposit a 300 nm-thick n-type GaN thin film that was co-doped with Si–Sn onto an amorphous glass substrate with a ZnO buffer layer. The deposited thin films were then subjected to post-growth thermal annealing at temperatures of 300 °C, 400 °C, or 500 °C to enhance their crystal quality. Hall measurements revealed that the film annealed at 500 °C had the lowest thin-film resistance of 0.82 Ω cm and the highest carrier concentration of 3.84 × 1019 cm−3. The thin film surface was studied using atomic force microscopy; the film annealed at 500 °C had an average grain size and surface roughness of 25.3 and 2.37 nm, respectively. Furthermore, the x-ray diffraction measurements revealed a preferential (002) crystal orientation and hexagonal wurtzite crystal structure at 2θ ≈ 34.5°. The thin film had a full width at half maximum value of 0.387°, it was also found to be very narrow. Compositional analysis of the films was conducted with x-ray photoelectron spectroscopy and verified that both Si and Sn were doped into the GaN film utilizing covalent bonding with N atoms. Finally, the film annealed at 500 °C had a high optical transmittance of 82.9% at 400–800 nm, a high figure of merit factor of 490.3 × 10−3 Ω−1, and low contact resistance of 567 Ω; these excellent optoelectronic properties were attributed to the film’s high electron concentration and indicate that the material is feasible for application in transparent optoelectronic devices.
A system dynamics approach to unlock the complexity of the S&OP in virtual enterprises

ABSTRACT Virtual Enterprise (VE) enables organisations to compete by strengthening their core competencies and sharing risks through collaboration. However, for manufacturing-based VE, the literature fails to provide adequate simulation-based methods for understanding the complex behaviour of the production planning step at the tactical level, known as Aggregate Production Planning or Sales & Operations Planning (S&OP). In this context, this paper proposes a novel System Dynamics-based model to help to understand the dynamic behaviour of S&OP in VE. Results suggest the efficiency of the proposed model, including its ability to straightforwardly make simulation-based S&OP scenarios comparisons, thus expanding the analytic decision-making capacity of managers desiring to push the limits of traditional S&OP in VE.