Miracle-dz/UniFAR-FTUs huggingface dataset:
A Tuning Range Extension Technique for Waveform-Shaping Single-Core CMOS Oscillators With No Dedicated Harmonic Tuning

This brief presents a tuning range extension technique for output voltage waveform-shaping single-core CMOS oscillators. First, the parasitic capacitors in previous waveform-shaping oscillators that limit the tuning range are analyzed. Next, a triple coupled LC resonator (TCLCR) is proposed to separate the differential-mode and common-mode (CM) resonance path which improves the tuning range significantly. The TCLCR is also able to establish the harmonically tuned impedance without using dedicated harmonic tuning both at CM 2rd harmonic and 3rd harmonic for oscillator’s implicit CM resonance or class-F23 operation to suppress the white noise and flicker noise conversion to phase noise. Finally, as a proof of concept, a 2.79-to-4.9 GHz class-F23 oscillator prototype covering a wide tuning range of 54.9% is designed and fabricated in a 130-nm CMOS technology. The oscillator achieves figure-of-merit with tuning range (FOMT) of 199.4/202.2 dBc/Hz, 196.3/200.9 dBc/Hz and 195/199.7 dBc/Hz at 100-kHz/1-MHz offset from 2.79, 3.83 and 4.9 GHz.
Oscillators Based on Step-Impedance and Slow Wave Transmission Lines for Sensing Applications

This work investigates the capabilities of oscillators based on step-impedance and slow wave structures to sense dielectric constants. The material under test (MUT) is placed over the structure and the objective is to achieve a high sensitivity of the oscillation frequency with the advantage of low phase noise, enabled by the high quality factor of the structure. With the aid of simplified analytical models, we will initially study the variation of the resonance frequency of a istep-impedance transmission line with the dielectric constant of the MUT, paying attention to the influence of the number of line sections. The study includes the derivation of analytical expressions for the sensitivity of the resonance frequency. Next, the structure will be connected to the oscillator active core, which will be modeled with a numerical nonlinear admittance function extracted from harmonic-balance (HB) simulations. The resulting semianalytical formulation will provide insight into the variation of the oscillation frequency and amplitude with the dielectric constant of the MUT, as well as the variation of the phase-noise spectral density. It will also enable a versatile test and optimization of the various structures to achieve high sensitivity with low phase noise. The methods have been successfully applied to an field-effect transistor (FET)-based oscillator at about 2 GHz.
Algebraic Principles of Quantum Field Theory I: Foundation and an exact solution of BV QFT

This is the first in a series of papers on an attempt to understand quantum field theory mathematically. In this paper we shall introduce and study BV QFT algebra and BV QFT as the proto-algebraic model of quantum field theory by exploiting Batalin-Vilkovisky quantization scheme. We shall develop a complete theory of obstruction (anomaly) to quantization of classical observables and propose that expectation value of quantized observable is certain quantum homotopy invariant. We shall, then, suggest a new method, bypassing Feynman's path integrals, of computing quantum correlation functions when there is no anomaly. An exact solution for all quantum correlation functions shall be presented provided that the number of equivalence classes of observables is finite for each ghost numbers. Such a theory shall have its natural family parametrized by a smooth-formal moduli space in quantum coordinates, which notion generalize that of flat or special coordinates in topological string theories and shall be interpreted as an example of quasi-isomorphism of general QFT algebra.
The Role of Oral Fusobacterium nucleatum in Female Breast Cancer: A Systematic Review and Meta-Analysis

Introduction Breast cancer is the world's most prevalent malignancy, with an increasing incidence and a predisposition for postpubertal females from all cultural and ethnic backgrounds. More recently, oral Fusobacterium nucleatum species have been observed in cancerous human breast tissue, drawing attention to the role of microbes in cancer pathogenesis. Objectives Investigating oral Fusobacterium nucleatum species as potential biomarkers for female-specific breast cancer. Methods A systematic search in The Central Register of Controlled Trials, EMBASE, EBSCO, NCBI, and MEDLINE databases was undertaken from the 1st January, 1983–31st March, 2022. Articles included were in English and based on women between the ages of 18–96 years with confirmed gingivitis/periodontal disease and breast cancer diagnoses from registered specialists. Authors extracted data independently, and a meta-analysis of risk estimations measuring associations between oral Fusobacterium nucleatum species and female-specific breast cancer was elucidated via calculated relative risks and 95% confidence intervals. Results AXIS tool analysis revealed 78.70% of articles with a positive correlation between oral Fusobacterium nucleatum and female-specific breast cancer. The risk of breast cancer development increased with significant levels of oral Fusobacterium nucleatum due to gingivitis/periodontitis (relative risk = 1.78, 95% confidence interval = 1.63–1.91). Low-moderate statistical heterogeneity was found (I2 = 41.39%; P = 0.02), and the importance of periodontal status on breast cancer pathogenesis was determined (relative risk = 1.24, 95% confidence interval = 1.01–1.30). Conclusions Oral Fusobacterium nucleatum species are a risk factor for breast cancer development, thus elevating their biomarker potentiality.
Large Raman gain and nonlinear phase shifts in high-purity As 2 Se 3 chalcogenide fibers

Third-order Kerr nonlinearities and Raman gain are studied experimentally in high-purity As2Se3 optical fibers for wavelengths near 1.55 μm. Kerr nonlinear coefficients are measured to be nearly 1000 times higher than those for silica fibers. In pulsed mode, nonlinear phase shifts near 1.2-π rad are measured in fibers only 85 cm long with peak pulse powers near 3 W. However, there are nonlinear losses near 20% for nonlinear phase shifts near π. By use of a cw optical pump, large Raman gains nearly 800 times that of silica were measured. In the cw case there were losses in the form of index gratings formed from standing waves at the exit face of the fiber. Discrete Raman amplifiers and optical regenerators are discussed as possible applications.
Comparison of the efficacy of mud-pack and hot-pack treatments in chronic non-specific neck pain: A single-blind, randomized-controlled study

Objectives This study aims to compare the short-term efficacy of mud-pack (MP) and hot-pack (HP) treatments with the same temperature and duration on sleep, function, depression, and quality of life for chronic non-specific neck pain (CNNP) patients. Patients and methods Between December 2018 and September 2019, a total of 70 patients with CNNP diagnosis (12 males, 58 females; mean age: 50.2±9.4 years; range, 24 to 65 years) were included. The patients were divided into two groups. The MP group (n=35) had a total of 15 sessions of MP for 20 min + transcutaneous electrical nerve stimulation (TENS) for 20 min + home exercise (HE) on five days per week for three weeks. The HP group (n=35) had 15 similar sessions of HP for 20 min + TENS for 20 min + HE. The patients were assessed with the Visual Analog Scale (VAS-pain), VAS physician’s and patient’s global assessments, modified Neck Disability Index (mNDI), Beck Depression Inventory (BDI), Pittsburgh Sleep Quality Index (PSQI), and Short Form-36 (SF-36) measures before treatment, at the end of post-treatment third week and one month later. Results In the MP group, there were statistically significant improvements in all parameters at the end of treatment three-week and one-month follow-up (p<0.05), apart from SF-36 Vitality/Energy (SF-36V/E) at the end of treatment and SF-36 General Health (SF-36GH) at one month. In the HP group, there were statistically significant improvements observed for all parameters (p<0.05), apart from the SF-36 Physical Role and SF-36GH at the end of treatment third week and SF-36V/E at the first-month assessment. The VAS-pain(p<0.001), mNDI (p=0.019), BDI (p=0.002), SF-36GH (p<0.001), SF-36V/E (p<0.001) and SF-36 mental health (p<0.001) showed statistically significantly superior improvements in the MP group (p<0.05). Conclusion In CNNP patients, both MP and HP treatments are effective. However, MP therapy has more positive effects on pain, function, depression, and quality of life parameters. The MP treatment may be used in addition to TENS treatment for CNNP patients.
The Effect of Food Vouchers and an Educational Intervention on Promoting Healthy Eating in Vulnerable Families: A Pilot Study

Cost has been reported as the main barrier to healthy eating in vulnerable groups. We aimed to evaluate the effect of a nutrition education intervention on adherence to Mediterranean Diet and health when providing food vouchers. This pilot study has a randomized control trial design. We included 66 vulnerable users from the Red Cross of Zaragoza (Spain). Intervention and control group individuals received 120 euros/month of food vouchers over 3 months to be spent in supermarkets (60 euros/month if under 12 y) plus a 10-week nutrition education program for the intervention group. Family food purchases were assessed using electronically recorded supermarket-obtained transactions. During and at the end of the intervention the percentage of healthy food was higher in the intervention than in the control group. Once the nutrition education was over, differences between groups dissipated. In the intervention group, health parameters improved, particularly weight-status, lipids, and liver enzymes. Control participants gained weight, although lipid and liver enzymes improved. Blood pressure and HbA1c did not improve in either the intervention or the control group. In conclusion, providing unrestricted food vouchers to vulnerable groups to increase healthy food consumption appears to be insufficient and should be accompanied by medium-long term nutrition education.
A High frequency stock price prediction model based on Boosting and information entropy weighted LSTM neural network

With the continuous development of data acquisition technology, high-frequency time series forecasting, such as stock prices, has become a hot issue. This paper proposes a LSTM neural network based on Boosting and information entropy weighting. The proposed method extracts the functional features of high-frequency time series by using orthogonal polynomial expansion, and uses the Boosting frame to recursively fit the residual predicted by LSTM neural network. Considering that the dimension of the prediction variable of LSTM neural network is a super parameter, we propose a model average method based on information entropy weighting, which theoretically balances the variance and bias of the prediction model. In addition, the basic model in the Boosting framework can be arbitrary, which greatly expands the applicability of the proposed method. The results of real data analyses show that the proposed method can effectively improve the prediction accuracy of the original LSTM neural network and has robustness. Finally, the proposed method can be further applied to the real-time monitoring of trace elements, the monitoring of road traffic flow and the prediction of daily average temperature curve in environmental science.
Deep Learning Models to Predict Fatal Pneumonia Using Chest X-Ray Images

Background and Aims Chest X-ray (CXR) is indispensable to the assessment of severity, diagnosis, and management of pneumonia. Deep learning is an artificial intelligence (AI) technology that has been applied to the interpretation of medical images. This study investigated the feasibility of classifying fatal pneumonia based on CXR images using deep learning models on publicly available platforms. Methods CXR images of patients with pneumonia at diagnosis were labeled as fatal or nonfatal based on medical records. We applied CXR images from 1031 patients with nonfatal pneumonia and 243 patients with fatal pneumonia for training and self-evaluation of the deep learning models. All labeled CXR images were randomly allocated to the training, validation, and test datasets of deep learning models. Data augmentation techniques were not used in this study. We created two deep learning models using two publicly available platforms. Results The first model showed an area under the precision-recall curve of 0.929 with a sensitivity of 50.0% and a specificity of 92.4% for classifying fatal pneumonia. We evaluated the performance of our deep learning models using sensitivity, specificity, PPV, negative predictive value (NPV), accuracy, and F1 score. Using the external validation test dataset of 100 CXR images, the sensitivity, specificity, accuracy, and F1 score were 68.0%, 86.0%, 77.0%, and 74.7%, respectively. In the original dataset, the performance of the second model showed a sensitivity, specificity, and accuracy of 39.6%, 92.8%, and 82.7%, respectively, while external validation showed values of 38.0%, 92.0%, and 65.0%, respectively. The F1 score was 52.1%. These results were comparable to those obtained by respiratory physicians and residents. Conclusions The deep learning models yielded good accuracy in classifying fatal pneumonia. By further improving the performance, AI could assist physicians in the severity assessment of patients with pneumonia.
Hom-prealternative superalgebras

The purpose of this paper is to introduce Hom-prealternative superalgebras and their bimodules. Some constructions of Hom-prealternative superalgebras and Hom-alternative superal- gebras are given, and their connection with Hom-alternative superalgebras are studied. The corre- sponding bimodules and their relationships are dicussed.
Exploring the Effective Components and Mechanism of Action of Japanese Ardisia in the Treatment of Autoimmune Hepatitis Based on Network Pharmacology and Experimental Verification

Japanese Ardisia is widely used as a hepatoprotective and anti-inflammatory agent in China. However, the active ingredients in Japanese Ardisia and their potential mechanisms of action in the treatment of autoimmune hepatitis (AIH) are unknown. The pharmacodynamic substance and mechanism of action of Japanese Ardisia in the treatment of AIH were investigated using network pharmacology and molecular docking technology in this study. Following that, the effects of Japanese Ardisia were evaluated using the concanavalin A (Con A)-induced acute liver injury rat model. The active ingredients and targets of Japanese Ardisia were searched using the Traditional Chinese Medicine Systems Pharmacology database, and hepatitis-related therapeutic targets were identified through GeneCards and Online Mendelian Inheritance in Man databases. A compound–target network was then constructed using Cytoscape software, and enrichment analysis was performed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Molecular docking technology was used to simulate the docking of key targets, and the AIH rat model was used to validate the expression of key targets. Nineteen active chemical components and 143 key target genes were identified. GO enrichment analysis revealed that the treatment of AIH with Japanese Ardisia mainly involved DNA–binding transcription factor binding, RNA polymerase II-specific DNA transcription factor binding, cytokine receptor binding, receptor-ligand activity, ubiquitin-like protein ligase binding, and cytokine activity. In the KEGG enrichment analysis, 165 pathways were identified, including the lipid and atherosclerotic pathway, IL-17 signaling pathway, TNF signaling pathway, hepatitis B pathway, and the AGE–RAGE signaling pathway in diabetic complications. These pathways may be the key to effective AIH treatment with Japanese Ardisia. Molecular docking showed that quercetin and kaempferol have good binding to AKT1, IL6, VEGFA, and CASP3. Animal experiments demonstrated that Japanese Ardisia could increase the expression of AKT1 and decrease the expression of CASP3 protein, as well as IL-6, in rat liver tissues. This study identified multiple molecular targets and pathways for Japanese Ardisia in the treatment of AIH. At the same time, the effectiveness of Japanese Ardisia in treating AIH was verified by animal experiments.
Canonical representation of quasi-cyclic codes

A linear block code C of length n is called quasi-cyclic (QC) if it is invariant under a cyclic shift of L positions, T/sup L/, where L<n. Any cyclic code can be represented by a unique generator polynomial. In this paper we associate with QC-codes a polynomial generator set which is a natural generalization of the generator polynomial of a cyclic code. A canonical generator matrix of a QC-code which is invariant under T/sup L/ is introduced which shows the symmetric structure of the n/L-section minimal trellis diagram (MTD). The state space dimension is nondecreasing on the left half of this trellis. The canonical generator matrix is important because it provides considerable information about the trellis complexity of QC codes as well as the relation between these codes and convolutional codes.
Extremely thin and defect‐free Si‐on‐insulator fabrication by tunnel epitaxy

A novel technique for extremely thin and defect‐free Si‐on‐insulator (SOI) fabrication, called tunnel epitaxy, is demonstrated. A lateral/vertical growth ratio of 20 is achieved with precisely controlled SOI film thickness, where the minimum thickness for the fabricated SOI is 0.05 μm. No defect was observed in the fabricated SOI with 〈001〉 lateral growth direction. The growth front is a flat (001) plane. The lateral growth length is limited to 1–2 μm by tunnel clogging, due to poly‐Si grain growth. The tunnel epitaxy, however, has a potential for larger area SOI fabrication, because the fabricated tunnel length is 10 μm.
Variation of Extremal Length Functions on Teichmüller Space

Extremal length is an important conformal invariant on Riemann surface. It is closely related to the geometry of Teichmuller metric on Teichmuller space. By identifying extremal length functions with energy of harmonic maps from Riemann surfaces to $\mathbb{R}$-trees, we study the second variation of extremal length functions along Weil-Petersson geodesics. We show that the extremal length of any measured foliation is a pluri-subharmonic function on Teichmuller space.
Crowdfunding Platform Recommendation Algorithm Based on Collaborative Filtering

Crowdfunding platforms are a novel method of internet fundraising. The production of data from the crowdfunding platform has increased, but the benefits of this data have not. This has led to a state of "information overload. " User-specific recommendation systems driven by data mining can play an effective role in solving this problem. This study introduces a collaborative filtering system that is driven by its end-users by fusing user input with the closest neighbor technique from machine learning. The results of this test demonstrate that the algorithm can provide useful project suggestions to those who utilize the crowdfunding site.
Wild-Type Isocitrate Dehydrogenase-Dependent Oxidative Decarboxylation and Reductive Carboxylation in Cancer and Their Clinical Significance

Simple Summary While isocitrate dehydrogenases have been known for decades, their mechanisms in tumors are gradually becoming clearer. The three isocitrate dehydrogenase isoforms in human cells differ in their subcellular localization, molecular structure, cofactor requirement, and catalytic mechanism. Here, we review the role of isocitrate dehydrogenases in metabolism, provide a current overview of cancer-linked isocitrate dehydrogenases and point to future lines of research to better understand the complex biology in health and disease. Abstract The human isocitrate dehydrogenase (IDH) gene encodes for the isoenzymes IDH1, 2, and 3, which catalyze the conversion of isocitrate and α-ketoglutarate (α-KG) and are required for normal mammalian metabolism. Isocitrate dehydrogenase 1 and 2 catalyze the reversible conversion of isocitrate to α-KG. Isocitrate dehydrogenase 3 is the key enzyme that mediates the production of α-KG from isocitrate in the tricarboxylic acid (TCA) cycle. In the TCA cycle, the decarboxylation reaction catalyzed by isocitrate dehydrogenase mediates the conversion of isocitrate to α-KG accompanied by dehydrogenation, a process commonly known as oxidative decarboxylation. The formation of 6-C isocitrate from α-KG and CO2 catalyzed by IDH is termed reductive carboxylation. This IDH-mediated reversible reaction is of great importance in tumor cells. We outline the role of the various isocitrate dehydrogenase isoforms in cancer, discuss the metabolic implications of interference with IDH, summarize therapeutic interventions targeting changes in IDH expression, and highlight areas for future research.
Thickness Uniformity of Spin Coated Film Influenced by Nonuniform Temperature of Substrates

The film thinning process in the spin coating has been analyzed by finite difference computational simulations. The coating liquid was assumed to be a solution of polymer solute and volatile organic solvent, for which Newtonian viscosity was given as a function of solute concentration. The flow of the coating liquid film that covers the entire substrate surface was analyzed where heat and mass transfer due to evaporation of solvent and heating/cooling by the substrate surface were taken into consideration. The whole process until all the solvent evaporates off the coating liquid and a dry coating film of the solute is left on the substrate was solved, and then the final film thickness was determined. Especially, influences of nonuniform substrate temperature on the profile of the final film thickness have been focused, for which three dimensional computational simulations have been performed. The case where the substrate is at rest and coating is processed only by drying the liquid film after a certain am.
Exploration of high and negative Poisson's ratio elastomer‐matrix laminates

Elastomer‐matrix composites show promise for high Poisson's ratio and negative Poisson's ratio (auxetic) applications due to high orthotropy. There are approximately five orders of magnitude between the axial stiffness of high modulus graphite fibres and the stiffness of low durometer elastomers. Although the maximum Poisson's ratio for isotropic elastomers is 0.5, it is easily shown that inplane Poisson's ratios twice unity can be obtained with a graphite/epoxy angle‐ply laminate at 25°. Chou and others have predicted inplane Poisson's ratios greater than 7 for certain cord‐rubber combinations. Peel previously predicted inplane Poisson's ratios higher than 32 and less than –60. Preliminary experimental results have produced inplane Poisson's ratios as high as 14. Certain combinations of un‐balanced highly orthotropic laminates may also produce inplane negative Poisson's ratios. Inplane Poisson's ratios, experimentally obtained from two laminate configurations with approximately the same axial stiffness are compared. A symmetric, balanced laminate produced an inplane Poisson's ratio of 3.7; while an unbalanced laminate with an equivalent axial stiffness produced an average inplane Poisson's ratio of –1.5. Certain high and negative Poisson's ratio elastomer‐matrix laminates appear to have quasi anti‐symmetric relationships about 0°, although laminate designers may consider dual angle‐ply laminates to be the more likely counterpart to the unbalanced dual angle auxetic laminates. Unbalanced symmetric laminates experience significantly more inplane shear deformation when axially loaded than their balanced counterparts. The high shear may be desirable for damping applications, but less desirable otherwise. (© 2007 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)