Miracle-dz/UniFAR-FTUs huggingface dataset:
A General Finite Element Approach to the form Finding of Tensile Structures by the Updated Reference Strategy

Starting from a rigorous mechanical formulation, a numerical procedure is developed for the form finding of minimal surfaces and pre-stressed membrane structures. The method is based on an iteratively adapted regularisation of the stiffness matrix which gives the method its name: the updated reference strategy. The method can be applied to any finite element discretization of cable and membrane structures subjected to pre-stress as well as lateral pressure or other external loading. It is very robust and reliable as is shown by many illustrative examples. Further analysis states that the well known force density method is the special case of applying the updated reference strategy to cable nets.
Effects of probiotic feed additives (biosol and Zemos) on growth and related genes in broiler chickens

Abstract The goal of this study was to look into the effect of two probiotics as feed additives: Biosol (lipotropic factor containing probiotics) and/or Zemos, and to determine the best regimen for using both probiotics to improve growth performance, carcass traits, blood parameters, and transcription of some growth and immunity-related genes in broiler chickens. A commercial hatchery provided 400 one-day-old Cobb broiler chicks. The chicks were divided into four equal groups at random, each with 100 birds. Group 1 served as a negative control. Group 2 was given Probiotic 1(Biosol) in drinking water at a dose of 120 g/10,000 chick each day. Group 3 received probiotic 2 (Zemos) at a dose of 0.25 mL/L of drinking water for 3 days/week. Group 4 was given combined probiotics (Biosol + Zemos), with the same weekly dose of each probiotic alternatively. During the experiment, all chickens were fed and hydrated ad libitum and exposed to 24 h of light. Our findings revealed that chicks fed on diets supplemented with Biosol and Biosol + Zemos showed an increase in body weight gain and lower feed conversion rates. Total protein levels were elevated while cholesterol and triglyceride levels dropped, whereas, no effect was detected in the uric acid levels among those groups. Furthermore, the carcass traits of Biosol and Biosol + Zemos increased as a result of the dietary supplementations, however, the weight of the drumstick showed no difference among the four groups. Both probiotics influenced the cecal count of lactobacilli, total aerobes, E. coli, and Enterococci in, as well as the transcript levels of the MTOR, SMYD, TLR-4, and NBN genes. It is possible to conclude that supplementing broilers with probiotics and Biosol, in particular, can increase their growth performance, and improve the biochemical characteristics of the blood and transcript levels of the genes under investigation. Highlights Supplementation of the broiler diet with probiotics is essential Biosol and Zemos increased the growth performance Both probiotics improved the biochemical blood parameters Biosol up-regulated growth and immunity related genes
Pulsatile tissue deformation dynamics of the murine retina and choroid mapped by 4D optical coherence tomography

Irregular ocular pulsatility and altered mechanical tissue properties are associated with some of the most sight-threatening eye diseases. Here we present 4D optical coherence tomography (OCT) for the quantitative assessment and depth-resolved mapping of pulsatile dynamics in the murine retina and choroid. Through a pixel-wise analysis of phase changes of the complex OCT signal, we reveal spatiotemporal displacement characteristics across repeated frame acquisitions. We demonstrate in vivo fundus elastography (FUEL) imaging in wildtype mouse retinas and in a mouse model of retinal neovascularization and uncover subtle structural deformations related to ocular pulsation. Our data in mouse eyes hold promise for a powerful retinal elastography technique that may enable a new paradigm of OCT-based measurements and image contrast.
Another Look at Obesity Paradox in Acute Ischemic Stroke: Association Rule Mining

Though obesity is generally associated with the development of cardiovascular disease (CVD) risk factors, previous reports have also reported that obesity has a beneficial effect on CVD outcomes. We aimed to verify the existing obesity paradox through binary logistic regression (BLR) and clarify the paradox via association rule mining (ARM). Patients with acute ischemic stroke (AIS) were assessed for their 3-month functional outcome using the modified Rankin Scale (mRS) score. Predictors for poor outcome (mRS 3–6) were analyzed through BLR, and ARM was performed to find out which combination of risk factors was concurrently associated with good outcomes using maximal support, confidence, and lift values. Among 2580 patients with AIS, being obese (OR [odds ratio], 0.78; 95% CI, 0.62–0.99) had beneficial effects on the outcome at 3 months in BLR analysis. In addition, the ARM algorithm showed obese patients with good outcomes were also associated with an age less than 55 years and mild stroke severity. While BLR analysis showed a beneficial effect of obesity on stroke outcome, in ARM analysis, obese patients had a relatively good combination of risk factor profiles compared to normal BMI patients. These results may partially explain the obesity paradox phenomenon in AIS patients.
A Novel Surface-Mountable Millimeter-Wave

A novel millimeter-wave waveguide bandpass filter structure suitable for surface mounting is introduced. The filter is constructed using a rectangular waveguide formed in MMIC substrate employing recently introduced microstrip-to-waveguide transducer. Input and output of the filter are implemented as microstrip lines. The transitions between the microstrip lines and the rectangular waveguide are implemented by using the microstrip-to-waveguide transition. The waveguide filter structure is surface-mountable as flip-chip and can be manufactured using a MMIC process that makes it extremely accurate. It has potential applications in millimeter-wave systems like local multipoint distribution system (LMDS) and autonomous cruise control (ACC) radar for automobiles.
Analgesic Effects of Different κ-Receptor Agonists Used in Daytime Laparoscopic Cholecystectomy

Background Comparing the effect of two different κ-receptor agonists, nalbuphine and oxycodone, and regular morphine in patients for prophylactic analgesia of acute pain after daytime laparoscopic cholecystectomy. Methods One hundred and twenty-four patients undergoing laparoscopic cholecystectomy were randomly allocated to receive nalbuphine (group N), oxycodone (group O), and morphine (group M). The three groups were all given intravenous injection (iv.) of 0.15 mg/kg injection before incision and 0.05 mg/kg injection at the end of pneumoperitoneum. The Visual Analogue Scale (VAS) scores (incision, visceral, and shoulder) and Ramsay sedation scores at 1, 2, 4, 8, 12, 16, 20, and 24 hours after surgery, the time of extubation, the incidence of postoperative adverse events, the satisfaction of pain treatment, and the duration of stay after surgery were all recorded. Results Compared with group M, the VAS scores of visceral pain at rest decreased in group N and group O at 1-8 h after surgery (P < 0.05). The VAS scores of visceral pain at movement in group N decreased longer than those in group O (P < 0.05). Compared with that of group M, the postoperative time in Ramsay sedation score of group O increased longer than that of group N (P < 0.05). Compared with group N, patients had worse sleep quality in group O, longer length of stay in group M, and lower satisfaction in both groups. Conclusion Compared with morphine, prophylactic use of the κ-receptor agonists, nalbuphine and oxycodone, during laparoscopic cholecystectomy can reduce postoperative visceral pain. Furthermore, the nalbuphine group had fewer adverse reactions, better analgesia, and better satisfaction.
PROFESSIONAL DEVELOPMENT: PARALLEL TEACHING AND COLLABORATIVE MENTORING

This paper aims to identify certain common issues in the field of professional development, namely, its’ main focus is on the issue of collaborative learning and teaching. The effects of parallel teaching and collaborative feedback are noticeably positive in the recent years of development. Reflective feedback, self-reflections and observations all serve as indicators of overall professional development and of course, provide teachers with insights regarding their teaching methodology. The term collaboration (which might also be found as cooperation), stands for equal treatment and understanding of the individuals in the classroom and implies “working together to achieve a certain, common goal. ” Participants in the case study are MA students of Faculty of Education, English Language Teaching at IBU, which were engaged in parallel teaching in one of my courses. The procedure was followed by observation, self-reflection and self-criticism. The first procedure was implemented in order for students to observe each other in their teaching styles, namely, to observe how two different students teach the same lecture. The second part of the procedure, namely the self-refection part was intended for students to make a comparison between themselves and their colleagues by noticing what was lacking in their teaching and the third procedure, self-criticism served as a starting point in admitting that criticism is regarded as positive feedback in teaching, rather than negative. The whole procedure of events was followed by a round-table discussion, in which, students accepted their colleagues’ remarks. Questions that students responded to were questions such as: “What could I improve? ” and “What was lacking in my lesson? ” “How did the experience help me improve my theory? ” “What did I enjoy in this experience? ” etc. Also, statements that followed the experience were such as “I advise you to…” and “I would differently apply the following (in my teaching)” etc. The experience with the obtained results, student remarks and future recommendations will be presented below.
Forecasting active and reactive power at substations' transformers

Quality prediction of load evolution at different levels of distribution network is a basic requirement for adequate operation planning of modern power systems. This paper describes the models, based on artificial neural networks, developed for active and reactive power forecasting at primary substations' transformers. The main goal consists on defining a regression process characterized by good quality estimates of those future values, based on historical data. Anticipation interval shall include from the next hour to one week in advance. The implemented forecasting tool is able to deal with noisy data, holidays and special occasions and adapts forecasts in case of power network reconfiguration whenever planned. Used techniques and implementation foundations of selected forecasting models are reported. Finally, the potential of the adopted approach is sustained by illustrative examples.
A 2.8kV, Forward Drop JBS Diode with Low Leakage

High voltage Schottky-, Junction Barrier Schottky (JBS)- and PiN-diodes with an implanted JTE termination have been fabricated on the same 4H-SiC wafer. Blocking voltages of 2.5-2.8 kV were reached for JBS and PiN diodes while the Schottky diodes reach about 2.0 kV. It is shown that the JBS design increases the blocking voltage effectively compared to the Schottky device with less than 10% increase in on-state static losses. Also, a comparison of static losses to a PiN diode gives a decrease of 40% for the JBS. The leakage current is also lowered by two decades compared to the Schottky device at its blocking voltage. Temperature measurements show that the low leakage current is maintained up to at least 225 Â°C.
X-33/RLV System Health Management/Vehicle Health Management

To reduce operations costs, Reusable Launch Vehicles (RLVS) must include highly reliable robust subsystems which are designed for simple repair access with a simplified servicing infrastructure, and which incorporate expedited decision-making about faults and anomalies. A key component for the Single Stage To Orbit (SSTO) RLV system used to meet these objectives is System Health Management (SHM). SHM incorporates Vehicle Health Management (VHM), ground processing associated with the vehicle fleet (GVHM), and Ground Infrastructure Health Management (GIHM). The primary objective of SHM is to provide an automated and paperless health decision, maintenance, and logistics system. Sanders, a Lockheed Martin Company, is leading the design, development, and integration of the SHM system for RLV and for X-33 (a sub-scale, sub-orbit Advanced Technology Demonstrator). Many critical technologies are necessary to make SHM (and more specifically VHM) practical, reliable, and cost effective. This paper will present the X-33 SHM design which forms the baseline for the RLV SHM, and it will discuss applications of advanced technologies to future RLVs. In addition, this paper will describe a Virtual Design Environment (VDE) which is being developed for RLV. This VDE will allow for system design engineering, as well as program management teams, to accurately and efficiently evaluate system designs, analyze the behavior of current systems, and predict the feasibility of making smooth and cost-efficient transitions from older technologies to newer ones. The RLV SHM design methodology will reduce program costs, decrease total program life-cycle time, and ultimately increase mission success.
Optimization of Culture Conditions for Total Carotenoid Amount Using Response Surface Methodology in Green Microalgae / Ankistrodesmus convolutus

Commercial carotenoids of green microalgae have become significant especially for their applications in the cosmetic, pharmaceutical, food and feed industries. Effects of physical and chemical parameters on carotenoid contents in isolated microalgal species have been investigated. The variables of shaking rate, nitrogen concentration and light intensity affect biomass production and the synthesis of carotenoids in the green microalgae were investigated using the statistical design by Box-Behnken (BBD) employing Response Surface Methodology (RSM). Furthermore, the optimized cultivation conditions using BBD for Chlorella vulgaris, Ankistrodesmus convolutus, Dunaliel-la salina, Tetraselmis striata were determined using the spectrophotometric method to enhance carotenoid concentration. A. convolutus within the green algae was detected with the highest carotenoid concentration. The optimum conditions results indicated that the growth of A. convolutus (0.55 mg/L) and production of total carotenoids (25.1138 mg/g biomass) were found at the stirrer rate of 100 rpm under the light intensity of 100 μE/m 2 s, and in the nutrient component of 8.82 mM NaNO 3 . These conditions were validated experimentally for total carotenoid yield (24.13 mg/g biomass). After that the production was performed in a flat-plate photobioreactor with a volume of 6L based on the optimized conditions and the carotenoid profile was defined by HPLC-DAD using standards such as violaxanthin, astaxanthin and β -carotene. This study proposes that the RSM approach can be used to define optimal conditions for large-scale production of carotenoids by A. convolutus .
A Novel Prognostic Signature Based on Cell-In-Cell-Related Genes for Predicting Survival and Tumor Microenvironment in Pancreatic Cancer

Background: Pancreatic cancer (PC) is a highly malignant tumor featured with high intra-tumoral heterogeneity and poor prognosis. Cell-in-cell (CIC) structures have been reported in multiple tumor types, and their presence is thought to promote clonal selection and tumor evolution. Here, we aimed to establish a CIC-related gene signature for predicting the prognosis and evaluating immune microenvironment in PC. Methods: In this study, the gene expression data, as well as corresponding clinicopathological data of PC and normal pancreatic tissues were collected from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO) databases. Differential gene expression analysis, random forest screening, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis were performed on 101 CIC-related genes to construct a prognostic gene signature. The effectiveness and robustness of the prognostic gene signature were evaluated by receiver operating characteristic (ROC) curves, Kaplan-Meier survival analysis and establishing the nomogram model. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to annotate the biological functions of the differentially expressed genes (DEGs). Quantitative real-time PCR (qRT-PCR), western blotting and immunohistochemistry (IHC) staining were validated the core gene expression in both mRNA and protein levels. Results: A 4-gene signature was constructed to stratify patients into the low-risk and high-risk groups with distinct survival outcomes, somatic mutation profiles and immune features. The high-risk group had poorer prognosis than did the low-risk group. This signature was found to be an independent prognostic factor for PC patients with favorable predictive efficiency. Functional enrichment analyses showed that numerous terms and pathways associated with invasion and metastasis were enriched in the high-risk group. Moreover, the high-risk group had a higher tumor mutation burdens and lower immune cell infiltrations. KRT7, as the most important risk gene, was significantly associated with the worse prognosis of PC. CIC formation assay performing in PC cell lines indicated that KRT7 expression was correlated with CIC frequency. Conclusions: The signature based on four CIC-related genes could be applicable for predicting the prognosis of PC, and targeting CIC processes may be a potential therapeutic option. Further studies are needed to reveal the underlying molecular mechanisms and biological implications of CIC in PC progression.
A note on semiparametric efficient generalization of causal effects from randomized trials to target populations

Abstract When effect modifiers influence the decision to participate in randomized trials, generalizing causal effect estimates to an external target population requires the knowledge of two scores – the propensity score for receiving treatment and the sampling score for trial participation. While the former score is known due to randomization, the latter score is usually unknown and estimated from data. Under unconfounded trial participation, we characterize the asymptotic efficiency bounds for estimating two causal estimands – the population average treatment effect and the average treatment effect among the non-participants – and examine the role of the scores. We also study semiparametric efficient estimators that directly balance the weighted trial sample toward the target population, and illustrate their operating characteristics via simulations.
PET Image Reconstruction With Kernel and Kernel Space Composite Regularizer

Led by the kernelized expectation maximization (KEM) method, the kernelized maximum-likelihood (ML) expectation maximization (EM) methods have recently gained prominence in PET image reconstruction, outperforming many previous state-of-the-art methods. But they are not immune to the problems of non-kernelized MLEM methods in potentially large reconstruction variance and high sensitivity to iteration numbers, and the difficulty in preserving image details and suppressing image variance simultaneously. To solve these problems, this paper derives, using the ideas of data manifold and graph regularization, a novel regularized KEM (RKEM) method with a kernel space composite regularizer for PET image reconstruction. The composite regularizer consists of a convex kernel space graph regularizer that smooths the kernel coefficients, a concave kernel space energy regularizer that enhances the coefficients’ energy, and a composition constant that is analytically set to guarantee the convexity of composite regularizer. The composite regularizer renders easy use of PET-only image priors to overcome KEM’s difficulty caused by the mismatch of MR prior and underlying PET images. Using this kernel space composite regularizer and the technique of optimization transfer, a globally convergent iterative algorithm is derived for RKEM reconstruction. Tests and comparisons on the simulated and in vivo data are presented to validate and evaluate the proposed algorithm, and demonstrate its better performance and advantages over KEM and other conventional methods.
Utilising Virtual Reality in Pain Management: A Systematic Review

Virtual reality (VR) offers patient with a drug free supplement, an alternative or complementary therapy to traditional pain management. VR technology allowing its use in a wide variety of settings in the medicine world. So, we would like to evaluate the current existing evidence supporting VR in pain management. We conducted a systematic review of interventional and observational studies that examined VR applications in pain management between 2010 and 2019. We used Scopus databases, PubMed, Web of Science, Ovid MEDLINE and EBSCOhost to identify the studies using keywords “patient”, “virtual reality”, “medicine” and “pain management”. Data was obtained by two investigators and agreement was reached with the involvement of a third and fourth investigator. Narrative synthesis for all research was done. A total of 451 citations were identified, among which 12 studies met the criteria for inclusion. Studies involve various countries with participant age ranging from 6 to 75 years old. Studies were small, employed different design, instrument and measure for outcome. Studies addressed experimental, acute and chronic pain with four categories of condition which are burn injury, orthopedic diseases and chronic headache. VR was effective during the procedure in experimental and acute pain management. Majority of studies involving VR in painful physical rehabilitation therapy found VR reduced chronic pain and some provide evidence of lasting analgesia effect of VR after therapy. The usage of VR in chronic pain in term of psychological and cognitive behavioral therapy (CBT) showed improvement of positive mood, emotional and motivation that could lead to improvement of quality of life. VR also useful to elicit findings during painful cervical kinematics assessment in chronic neck pain. VR is a promising technology to be applied in managing chronic and acute pain. Some research showed that VR usage is able to provide lasting effect of analgesia even after VR session. However, there is a need for long term, larger sample sizes and well controlled studies to show clinical and cost-effectiveness for this technology to be used in clinical settings.