Miracle-dz/UniFAR-FTUs huggingface dataset:
A meta-analysis

Purpose:Amplified in breast cancer 1 (AIB1) expression is known to be involved in the initiation and progression of malignant breast cancer (BC), but its prognostic role remains uncertain. This meta-analysis assessed reported studies to evaluate this relationship. Methods:Electronic databases were systematically reviewed to collect eligible studies using pre-established criteria. Hazard ratios (HRs) or odds ratios (ORs) and 95% confidence intervals (CIs) were pooled to estimate the impact of AIB1 protein expression on overall survival (OS) and clinicopathologic properties of BC cases. Results: Nine eligible studies, including 6774 patients, were finally assessed by the current clinical meta-analysis. AIB1 positivity correlated with reduced OS (pooled HR=1.409, 95% CI 1.159–1.714, P= .001). AIB1 overexpression also impacted prognosis as shown by univariate (pooled HR=1.420, 95% CI 1.154–1.747, P= .001) and multivariate (pooled HR=1.446, 95% CI 1.099–1.956; P= .009) analyses. Notably, subgroup analyses also revealed that AIB1 overexpression was associated with poor OS in some subgroups, such as ER-positive group (pooled HR=1.511, 95% CI 1.138–2.006, P= .004), ER-positive without tamoxifen administration group (pooled HR=2.338, 95% CI 1.489–3.627, P< .001), and premenopausal women group (pooled HR=1.715, 95%CI 1.231–2.390, P= .001). Additionally, high AIB1 protein levels were associated with HER2 positivity (pooled OR=0.331, 95% CI 0.245–0.448; P< .001), poorly differentiated histological grade (pooled OR=0.377, 95% CI 0.317–0.448; P< .001), high Ki67 (pooled OR=0.501, 95% CI 0.410–0.612; P< .001), presence of lymph node metastases (pooled OR=0.866, 95% CI 0.752– 0.997; P= .045), and absence of progesterone receptor (pooled OR=1.447, 95% CI 1.190–1.759; P< .001). Conclusions: This analysis demonstrated that AIB1 overexpression is related to aggressive phenotypes and unfavorable clinical outcomes in BC, and might involve in tamoxifen resistance. AIB1 may be a new prognostic biomarker and therapeutic target in BC. Abbreviations: AIB1= amplified in breast cancer 1, AR= androgen receptor, BC = breast cancer, CI = confidence interval, ER = estrogen receptor, HR = hazard ratio, OR = odds ratio, OS = overall survival, PR = progesterone receptor.
Transfer Learning with Convolutional Neural Network for Gastrointestinal Diseases Detection using Endoscopic Images

Automated and accurate classification of pathologies on endoscopic images is a current challenge for Gastroenterology. This paper presents an approach to assist medical diagnosis processes of diseases and anomalies in the gastrointestinal tract based on the classification of features extracted from endoscopic images with a convolutional neural network and transfer learning type fine-tuning. The proposed strategy was evaluated on real endoscopic images from the Kvasir dataset. Specifically, we used 8000 images from 8 classes showing anatomical landmarks, pathological findings, and endoscopic procedures in the gastrointestinal tract. The proposed method allows obtaining an accuracy classification of 94.6%, which is 2.1% more accurate than the best result in the literature under very similar conditions, and up to 13.6% more precise.
Modulated Model Predictive Torque and Power Control of Gearless PMSG Wind Turbines

In this paper, novel modulated model predictive toque and power control schemes are proposed for machine- and grid-side converters, respectively in the gearless permanent magnet synchronous generator-based wind turbines. The state variables such as generator torque and flux, and grid active and reactive powers are predicted and evaluated by two independent duty-cycle optimized cost functions. The stationary voltage vectors corresponding to the optimal duty cycles are then synthesized by the space vector modulation to achieve fixed switching frequency operation for the back-to-back connected voltage source converter. With the proposed control schemes, the state variables are controlled precisely with fast transient response and low steady-state errors to accomplish the control goals of wind turbines during a wide-dynamic range operation. The feasibility of the proposed schemes is verified through simulation results using a 750-kW wind turbine system.
Photochemotherapy Induces Interferon Type III Expression via STING Pathway

DNA-damaging cancer therapies induce interferon expression and stimulate the immune system, promoting therapy responses. The immune-activating STING (Stimulator of Interferon Genes) pathway is induced when DNA or double-stranded RNA (dsRNA) is detected in the cell cytoplasm, which can be caused by viral infection or by DNA damage following chemo- or radiotherapy. Here, we investigated the responses of cutaneous T-cell lymphoma (CTCL) cells to the clinically applied DNA crosslinking photochemotherapy (combination of 8–methoxypsoralen and UVA light; 8–MOP + UVA). We showed that this treatment evokes interferon expression and that the type III interferon IFNL1 is the major cytokine induced. IFNL1 upregulation is dependent on STING and on the cytoplasmic DNA sensor cyclic GMP-AMP synthase (cGAS). Furthermore, 8–MOP + UVA treatment induced the expression of genes in pathways involved in response to the tumor necrosis factor, innate immune system and acute inflammatory response. Notably, a subset of these genes was under control of the STING–IFNL1 pathway. In conclusion, our data connected DNA damage with immune system activation via the STING pathway and contributed to a better understanding of the effectiveness of photochemotherapy.
Sample strategies for quantification of hepatic fat fraction mean MRI in healthy cats during body weight gain

Hepatic fat fraction (HFF) can be non-invasively estimated with magnetic resonance imaging (MRI) multiple echo gradient recalled echo (GRE) sequence. The aim of this study was to test different methods of sampling strategies to quantify the HFF in healthy cats during body weight gain. Twelve healthy adult male cats were examined in a 3 Tesla MRI unit. Sequences included morphological images, and multiple echo GRE sequence. Cats were scanned at the beginning of the study and twice, each 20 weeks apart during body weight gain. HFF was calculated with 5 different methods of sampling on the multiple echo GRE sequence with different number, size and position of regions of interest (ROIs) and by 2 operators. Results indicated that HFF increased with increasing body weight, and the increase was appreciated with all the 5 methods. There was overall excellent agreement (interclass correlation coefficient = 0.820 (95% confidence interval:0.775–0.856)) between the 2 operators. HFF in the left lateral hepatic lobe was lower than in the other analyzed lobes. HFF measured on large free-hand drawn ROIs was higher than HFF measured with smaller ROIs size. This study proves that different sampling methods for quantification of HFF on multiple echo GRE sequence have overall excellent repeatability and ability to appreciate increased HFF.
A phantom study to evaluate three different registration platform of 3D/3D, 2D/3D, and 3D surface match with 6D alignment for precise image‐guided radiotherapy

Abstract Purpose To evaluate two three‐dimensional (3D)/3D registration platforms, one two‐dimensional (2D)/3D registration method, and one 3D surface registration method (3DS). These three technologies are available to perform six‐dimensional (6D) registrations for image‐guided radiotherapy treatment. Methods Fiducial markers were asymmetrically placed on the surfaces of an anthropomorphic head phantom (n = 13) and a body phantom (n = 8), respectively. The point match (PM) solution to the six‐dimensional (6D) transformation between the two image sets [planning computed tomography (CT) and cone beam CT (CBCT)] was determined through least‐square fitting of the fiducial positions using singular value decomposition (SVD). The transformation result from SVD was verified and was used as the gold standard to evaluate the 6D accuracy of 3D/3D registration in Varian’s platform (3D3DV), 3D/3D and 2D/3D registration in the BrainLab ExacTrac system (3D3DE and 2D3D), as well as 3DS in the AlignRT system. Image registration accuracy from each method was quantitatively evaluated by root mean square of target registration error (rmsTRE) on fiducial markers and by isocenter registration error (IRE). The Wilcoxon signed‐rank test was utilized to compare the difference of each registration method with PM. A P < 0.05 was considered significant. Results rmsTRE was in the range of 0.4 mm/0.7 mm (cranial/body), 0.5 mm/1 mm, 1.0 mm/1.5 mm, and 1.0 mm/1.2 mm for PM, 3D3D, 2D3D, and 3DS, respectively. Comparing to PM, the mean errors of IRE were 0.3 mm/1 mm for 3D3D, 0.5 mm/1.4 mm for 2D3D, and 1.6 mm/1.35 mm for 3DS for the cranial and body phantoms respectively. Both of 3D3D and 2D3D methods differed significantly in the roll direction as compared to the PM method for the cranial phantom. The 3DS method was significantly different from the PM method in all three translation dimensions for both the cranial (P = 0.003–P = 0.03) and body (P < 0.001–P = 0.008) phantoms. Conclusion 3D3D using CBCT had the best image registration accuracy among all the tested methods. 2D3D method was slightly inferior to the 3D3D method but was still acceptable as a treatment position verification device. 3DS is comparable to 2D3D technique and could be a substitute for X‐ray or CBCT for pretreatment verification for treatment of anatomical sites that are rigid.
Aux/IAA14 Regulates microRNA-Mediated Cold Stress Response in Arabidopsis Roots

The phytohormone auxin and microRNA-mediated regulation of gene expressions are key regulators of plant growth and development at both optimal and under low-temperature stress conditions. However, the mechanistic link between microRNA and auxin in regulating plant cold stress response remains elusive. To better understand the role of microRNA (miR) in the crosstalk between auxin and cold stress responses, we took advantage of the mutants of Arabidopsis thaliana with altered response to auxin transport and signal. Screening of the mutants for root growth recovery after cold stress at 4 °C revealed that the auxin signaling mutant, solitary root 1 (slr1; mutation in Aux/IAA14), shows a hypersensitive response to cold stress. Genome-wide expression analysis of miRs in the wild-type and slr1 mutant roots using next-generation sequencing revealed 180 known and 71 novel cold-responsive microRNAs. Cold stress also increased the abundance of 26–31 nt small RNA population in slr1 compared with wild type. Comparative analysis of microRNA expression shows significant differential expression of 13 known and 7 novel miRs in slr1 at 4 °C compared with wild type. Target gene expression analysis of the members from one potential candidate miR, miR169, revealed the possible involvement of miR169/NF-YA module in the Aux/IAA14-mediated cold stress response. Taken together, these results indicate that SLR/IAA14, a transcriptional repressor of auxin signaling, plays a crucial role in integrating miRs in auxin and cold responses.
Investigating the Benefit of Combined Androgen Modulation and Hypofractionation in Prostate Cancer

Hypofractionation is currently considered a valid alternative to conventional radiotherapy for the treatment of patients with organ-confined prostate cancer. Recent data have demonstrated that extreme hypofractionation, which involves the use of a high radiation dose per delivered fraction and concomitant reduction of sessions, is a safe and effective treatment, even though its radiobiological rationale is still lacking. The present work aims to investigate the biological basis sustaining this approach and to evaluate the potential of a hypofractionated regimen in combination with androgen deprivation therapy, one of the major standards of care for prostate cancer. Findings show that androgen receptor (AR) modulation, by use of androgens and antiandrogens, has a significant impact on cell survival, especially in hypoxic conditions (4% O2). Subsequent experiments have revealed that AR activity as a transcription factor is involved in the onset of malignant senescence-associated secretory phenotype (SASP) and activation of DNA repair cascade. In particular, we found that AR stimulation in hypoxic conditions promotes the enhanced transcription of ATM gene, the cornerstone kinase of the DNA damage repair genes. Together, these data provide new potential insights to justify the use of androgen deprivation therapy, in particular with second-generation anti-androgens such as enzalutamide, in combination with radiotherapy.
Text recycling in STEM: A text-analytic study of recently published research articles

ABSTRACT Text recycling, sometimes called “self-plagiarism,” is the reuse of material from one’s own existing documents in a newly created work. Over the past decade, text recycling has become an increasingly debated practice in research ethics, especially in science and technology fields. Little is known, however, about researchers’ actual text recycling practices. We report here on a computational analysis of text recycling in published research articles in STEM disciplines. Using a tool we created in R, we analyze a corpus of 400 published articles from 80 federally funded research projects across eight disciplinary clusters. According to our analysis, STEM research groups frequently recycle some material from their previously published articles. On average, papers in our corpus contained about three recycled sentences per article, though a minority of research teams (around 15%) recycled substantially more content. These findings were generally consistent across STEM disciplines. We also find evidence that researchers superficially alter recycled prose much more often than recycling it verbatim. Based on our findings, which suggest that recycling some amount of material is normative in STEM research writing, researchers and editors would benefit from more appropriate and explicit guidance about what constitutes legitimate practice and how authors should report the presence of recycled material.
APLCNet: Automatic Pixel-Level Crack Detection Network Based on Instance Segmentation

The accurate and automatic detection of pavement cracks is essential for pavement maintenance. However, automatic crack detection remains a challenging problem due to the inconspicuous visual features of cracks in complex pavement backgrounds, the complicated shapes and structures of cracks, and the influences of weather changes and noise. In recent years, with the development of artificial intelligence technology, crack detection methods based on classification and semantic segmentation have laid a good foundation for the automation of pavement crack detection. However, there remain shortcomings in the comprehensive acquisition of pavement crack attribute information and detection accuracy. To solve these problems, this paper proposes an instance segmentation network for pavement crack detection. The network can simultaneously obtain the crack category, position, and mask, and can realize end-to-end pixel-level crack detection. A semantic segmentation branch is first added to Mask R-CNN. This branch can extract the bottom-level detail information of the cracks and ultimately improves the accuracy of crack mask prediction. An adaptive feature fusion module is then designed. During feature fusion, this module highlights the attribute information and location information of cracks according to the channel attention mechanism and the spatial attention mechanism. Finally, these two modules are integrated to form an automatic pixel-level crack detection network, namely APLCNet. Without any embellishment, APLCNet achieves a precision of 92.21%, a recall of 94.89%, and an F1-score of 93.53% on the challenging public CFD dataset, thereby outperforming CrackForest and MFCD for pixel-wise crack detection. Moreover, APLCNet achieves a 16.5% mask AP on the self-captured GDPH dataset, thereby surpassing Mask R-CNN and PANet.
Empirical Model With Inclusion of System Inductance for Electrically Exploded Conductor-Based Opening Switch in Inductive Energy Storage Systems

Empirical models have been reported earlier to estimate the resistivity of electrically exploded conductors (EECs) as a function of geometrical parameters only, such as cross-sectional area and length. Since inductance of inductive energy storage system (IESS) also affects the resistivity of EEC, similar models but with modified empirical coefficients are reported here by including inductance of IESS which makes them applicable for the prediction of resistivity of EEC at different time-scales/systems. Using curve fitting on experimental data reported earlier, methods to evaluate modified empirical coefficients are presented. Circuit simulations carried out using these models are able to predict the current as well as voltage profile in EEC and load for different inductances of IESS. Experiments have been carried out to validate the results predicted by simulation and are found to be in close agreement.
Detection of impulsive sounds in stream of audio signals

Video analysis has become a standard feature of many security cameras. However, built-in audio analytics continues to be quite rare despite the presence of both the audio channel itself in the devices and the available computing power for processing audio data. Audio analytics has some advantages over video analytics such as cheaper devices and maintenance costs. Furthermore, when the system is running in real-time, the audio data stream is significantly smaller in volume than the data stream from video cameras and makes it more loyal requirements for the bandwidth of the data channel. Audio analytics systems can be particularly useful for urban surveillance with the start of automated broadcasting live video to the police console from the scene of an explosion and shooting. Audio analytics technologies can also be used to study video recordings and determine events. This article proposes a method for automatic detection of pulse sounds that signifies critical situation in audio signals based on Support Vector Machine learning models. The models were able to classify sounds from events such as gunshot, broken glass, explosion, siren, cry and dog barking with accuracy ranges from 95% to 81 %.
Cascaded H-Bridge Multilevel Converter for Large-Scale Solar PV-BES System

In this paper, a fundamental switched modulated MW size eleven-level cascaded H-bridge (11L-CHB) VSC (Voltage Source Converter) is utilized in a 48MW/336MWh BES (Battery Energy Storage) for a 80 MW solar PV plant for energy timeshifting application. The CHB-VSC and NAS-battery both complement each other, as CHB allows a direct connection of a NAS battery container with its H-bridges for independent control of the battery state of charge (SOC). On the other hand, the NAS-battery offers an isolated voltage source for a CHB VSC for generation of staircase voltage waveform and allows a high voltage integration of NAS-BES to the grid. Moreover, with the utilization of soft-switching technique in CHB, enables high conversion efficiency and lower device switching losses as compared with high-frequency PWM switching. An 11L-CHB VSC with NAS-BES is developed in Matlab/Simulink environment to validate the design and control. Harmonics, steady state and dynamic performances of it, are demonstrated in detail to justify its utility.
Analysis of the catalytic growth of carbon nanotubes

This thesis covers the analysis of the catalytic growth of carbon nanotubes under well de fined conditions, the optimization of the field emission properties of those structures and introduces a model for the growth mechanism based on the experimental results. Experimental investigations are presented which allow to get a comprehensive picture of the catalytic growth of carbon nanotube films. These films were generated by patterning silicon surfaces with transition metal catalysts usingmicro contact printingand subsequent generation of nanotubes by means of chemical vapor deposition (CVD). The development of the used catalyst was characterized as function of growth time and applied temperature. The subsequent studies of the morphology of the carbon structures grown by CVD revealed a significant influence of the deposition temperature and the catalyst material on the quality of the carbon structures. Electron microscopy and Raman spectroscopy were used to investigate the character of these structures in more detail. It was found that the increase in temperature above 800°C resulted in the formation of a polycrystalline outer shell over a nanotube core. Based on those experimental results a mechanism for the growth of carbon nanotubes is suggested. Acetylene is dissociated catalytically on the catalyst nanoparticles spread on the substrate surface. In a first stage the acetylene reduces the metal oxide grains to pure metal. The further catalytic dissociation of acetylene takes presumably place at facets of well-defined crystallographic orientation and the carbon diffuses into the particle. The resultingdensit y gradient of carbon dissolved in the particle drives the diffusion of carbon through the particle. In order to avoid dangling bonds, the carbon atoms assemble at a less reactive facet of the particle, which leads to the formation of a nanotube. Thicker nanotubes at higher temperatures are generated due to the dissociation of acetylene in the gas phase, which leads to the formation of carbon flakes that condense on the catalytically grown structures. In order to support the growth model, simple classic calculations and simulations were performed, which yielded formulas that allow to estimate nanotube growth properties, like the growth velocity. The theoretical results correspond well with the experimental. Furthermore a mechanism for the cessation of the nanotube growth was proposed. Complementary, the field emission properties of different carbon structures were determined. It turned out that the thinnest nanotubes emit at lowest fields. Furthermore, in regard to applications nanotubes have been grown on glass substrates and the field emission properties of such samples have been characterized. Finally, a scanningprob e microscope is presented which exploits the field emission of carbon nanotubes. It would offer new possibilities to characterize samples on a nanometer scale.
Discrimination of noise channels on the basis of quantum memory

From the point of view of communication theory, a quantum channel can be defined as a physical process mapping from initial to final state in the form of CPTP (Completely positive trace preserving) map. Quantum information theory provide a theoretical framework and some mathematical methods to accomplish this. In order to preserve information, we proposed a scheme for the protection of two-qubit state through various noise channel, where successive uses of noise channels are correlated. These successive uses of channels are called memory. Different types of noise channels with memory have been dicsussed in details. We compare the dynamics of entanglement of two-qubit state under different noise channel and it has been seen that one can preserve two-qubit steady state quantum correlation under noise channels with memory. The study of memory effect in quantum channel will emerge as an interesting phenomena to trace back information from the surrounding which is considered as a resource in quantum information task. However, we also define some mores measures of entanglement and their preservation. We hope that our new findings may help to study the two-qubit entanglement structure.