Miracle-dz/UniFAR-FTUs huggingface dataset:
Hypoxia Tumor Microenvironment Activates GLI2 through HIF-1α and TGF-β2 to Promote Chemotherapy Resistance of Colorectal Cancer

Background A majority of relapse cases have been reported in colorectal cancer patients due to cancer stem cell progenitors. The factors responsible for chemoresistance have yet to be discovered and investigated as CSCs have reported escaping from chemotherapy's killing action. Objective In this study, we have investigated the effects of HIF-1α and TGF-β2 in hypoxia conditions on the expression of GLI2, which is a potential factor for causing chemoresistance. Material and Methods. Colorectal samples of treated patients were collected from the Hospital Biological Sample Library. Culture of patient-derived TSs and fibroblasts was performed. The collected patient samples and cells were used for immunohistochemistry, quantitative PCR, and western blotting studies which were performed. Results It was reported that HIF-1α (hypoxia-inducible factor) and TGF-β2 secreted from cancer-associated fibroblasts (CAFs) synergistically work to express GLI2 in cancer stem cells. Hence, it increased the stemness as well as resistance to chemotherapy. Conclusion The HIF-1α/TGF-β2-mediated GLI2 signaling was responsible for causing chemoresistance in the hypoxia environment. High expressions of HIF1α/TGF-β2/GLI2 cause the relapsing of colorectal cancer, thus making this a potential biomarker for identifying the relapse and resistance in patients. The study uncovers the mechanism involved in sternness and chemotherapy resistance which will help in targeted treatment.
Reduced n-3 and n-6 PUFA (DHA and AA) Concentrations in Breast Milk and Erythrocytes Phospholipids during Pregnancy and Lactation in Women with Obesity

Obesity during pregnancy is a worrying public health problem worldwide. Maternal diet is critical for fatty acid (FA) placental transport and FA content in breast milk (BM). We evaluated FA composition in erythrocytes phospholipids (EP) and BM in pregnant women with (OBE, n = 30) and without (non-OBE, n = 31) obesity. Sixty-one healthy women were evaluated at their 20–24th gestational week and followed until 6th month of lactation. Diet was evaluated through a food frequency questionnaire. FA composition of EP and BM was assessed by gas-liquid chromatography. The OBE group showed lower diet quality, but total n-6 and n-3 polyunsaturated FA (PUFA), ALA, EPA, and DHA dietary intake was similar between groups. N-3 PUFA, ALA, DHA, and the n-6/n-3 PUFA ratio in EP were lower at the 6th lactation month in the OBE group. In BM, the arachidonic acid (AA) concentration was lower at the end of the lactation, and DHA content showed an earlier and constant decline in the OBE group compared to the non-OBE group. In conclusion, n-3 PUFA and AA and DHA levels were reduced in EP and BM in pregnant women with obesity. Strategies to increase n-3 PUFA are urgently needed during pregnancy and lactation, particularly in women with obesity.
An Infrared Thermo Image Processing Framework Based on MRF Model to Detect Surface Defect on a Metal Element

An infrared thermo image processing framework was proposed to complete the detection task using the MRF model-based image segmentation method.Firstly,the preprocessing including a few steps is implemented on the infrared thermo image to get the enhancement image.Secondly,MRF model-based image segmentation method is used to cluster the defect pixels.Lastly,the mean gray level in the original gray level image of clustered pixels is taken as a feature to find the defect cluster and the morphological area opening operator is lastly used get the accurate information of defect.Experimental result shows that the proposed framework has very promising performance and can obtain precise information of defects on a metal element even the element has some rough surface.
A comparative evaluation of microleakage and dentin shear bond strength of three restorative materials

Abstract Aim To evaluate the microleakage and dentin shear bond strength of two glass containing restorative materials, Zirconomer and Cention N, and to compare them with a conventional glass ionomer cement (GIC) (GC Fuji II). Materials and methods Zirconomer (Shofu) and GC Fuji II (GC Corp.) are self-curing GICs whereas Cention N (IvoclarVivadent) also offers a self-curing option as well as the option of light-curing using an adhesive. For evaluating microleakage, standardized class V cavities were prepared on the buccal surface of 30 premolars. The cavities were restored with one of the three restorative materials (n = 10) according to manufacturers’ instructions, Cention N being used with an adhesive (Te-EconomBond, IvoclarVivadent) and in the light-curing mode. After restoration and thermocycling, the microleakage assessment was made under a stereomicroscope at 40x magnification following immersing of the teeth in 0.5% methylene blue dye and buccolingual sectioning. For evaluating dentin shear bond strength, the occlusal surface of the 30 premolars was ground flat, and cylinders of the three restorative materials (n = 10) were bonded to the occlusal surface according to manufacturers’ instructions, Cention N being used with an adhesive (Te-EconomBond, IvoclarVivadent) and in the light-curing mode. Following 24-h storage at 100% humidity, the dentin shear bond strength was measured and the fracture mode was determined under a stereomicroscope at 10× magnification. Data were statistically analyzed using Mann–Whitney and Scheffé tests (p = .05). Results Cention N displayed significantly less microleakage than did Zirconomer and GC Fuji II at occlusal as well as the gingival margins. Dentin shear bond strength varied significantly between 5.15 and 9.89 MPa with Cention N showing the highest bond strength and GC Fuji II the lowest. Conclusion In this in vitro evaluation, Cention N consistently performed better than the conventional GIC (GC Fuji II) as well as Zirconomer.
Comparative Approach of Unmanned Aerial Vehicle Restrictions in Controlled Airspaces

Recent public discourse regarding unmanned aerial vehicle (UAV) usage and regulation is focused around public privacy and safety. Most authorities have employed key guidelines and licensing procedures for piloting UAVs, however there is marginal consensus amongst regulators and a limited view towards unified procedures. This paper aims to analyze the key challenges that affect the use of UAVs and to determine if the current rules address those challenges. For this purpose: privacy, safety, security, public nuisance and trespass are tested. A set of criteria are developed to perform a comparative analysis against the existing UAV regulations to determine how they are meeting the specified criteria. Within this framework, five countries are selected: Australia, Canada, European Union (EU), United Kingdom (UK) and the United States of America (USA), with usage data and length of time between regulatory reviews ensuring any analysis is realized on updated protocols. The regulations of each country are then compared against the developed criteria. The findings show there are shortfalls with the majority of regulations failing to meet some criteria and the results confirm that key issues fail to be addressed. Finally, recommendations are suggested for filling the gaps in the regulations.
Biological Principles of Orthodontic Tooth Movement: A Review Article

Orthodontic tooth mobility is discussed in this article, and the numerous concepts or theories of movement of tooth and the phases through which a tooth undergoes after application of forces. The effect of orthodontic pressure exerted on the dental architecture promotes movement of tooth through remodeling, which is the growth and resorption of alveolar bone. These forces can either be light forces or heavy forces depending upon their magnitudes. Biological aspects of tooth movement changes in accordance with the magnitude, force, time span and direction of force exerted. Variations in force application can be decided based on the kind of movement of tooth desired. These forces result in complex physiological events, cellular events in the surrounding tissues and, release of various chemical mediators to re-establish the equilibrium which gets interrupted by applying forces. Recently, many researches are going on how to enhance the speed of movement of the tooth with light forces so as to reduce the damage caused by the heavy forces, reduce the treatment time overall and treatment planning which results in minimal adverse effects.
Kinetic Analysis of Human Gait using different types of footwear as Design Input for Activity based prosthetic foot

Recent trends emphasize the use of kinetic analysis (GRF, COP) of human gait for prosthetic development. These analysis help in designing and performance quantification of device specifically lower limb prosthetics. Footwear used plays an important role in normal gait. The effect of footwear was a topic of biomechanics research. The paper evaluates the effect of footwear (heeled and cushioned) in normal walking of individuals. The findings are used as a design input parameters for a development of new prosthetic foot and quantification of indigenously developed electronic knee.
Mutation in the CX3C Motif of G Protein Disrupts Its Interaction with Heparan Sulfate: A Calorimetric, Spectroscopic, and Molecular Docking Study

Respiratory syncytial virus (RSV) is the leading cause of lower respiratory tract infection in children and infants. To date, there is no effective vaccine available against RSV. Heparan sulfate is a type of glycosaminoglycan that aids in the attachment of the RSV to the host cell membrane via the G protein. In the present study, the effect of amino acid substitution on the structure and stability of the ectodomain G protein was studied. Further, it was investigated whether mutation (K117A) in the CX3C motif of G protein alters the binding with heparan sulfate. The point mutation significantly affects the conformational stability of the G protein. The mutant protein showed a low binding affinity with heparan sulfate as compared to the wild-type G protein, as determined by fluorescence quenching, isothermal titration calorimetry (ITC), and molecular docking studies. The low binding affinity and decreased stability suggested that this mutation may play an important role in prevention of attachment of virion to the host cell receptors. Collectively, this investigation suggests that mutation in the CX3C motif of G protein may likely improve the efficacy and safety of the RSV vaccine.
Challenges of Applying Permanent Magnet (PM) Technology in Wind Power Generators

More than half of the world's top 10 turbine manufacturers are either investigating PM generator technology or have already been offering PMGs to the market.Often,the easiest way to convert traditional DFIGs to PMGs is to replace the existing DFIG behind the high-speed gear with the same speed PMG and full-power converter.The technique requires only minimal design changes of the turbine and nacelle layout. PM technology offers a large variety of different concepts, starting from 10～20 r/min,large torque and direct-driven generators.It also offers various constructional options,like outer rotor and axial-flux generators.PM excitation gives the machines both high efficiency and high torque,because the excitation does not require a continuous energy flow to the system.It also produces low synchronous inductance,which causes the large torque capacity of the machine.
Financing the low-carbon transition: The impact of financial frictions on clean investment

Carbon pricing aims to shift the risk-adjusted returns on investment in favor of green technologies vis-‘a-vis fossil investment, relying on efficient capital markets to redirect investment accordingly. Capital markets with financial frictions can distort this transmission of climate policy. This study analyses the impact of emission taxes on mitigation and low-carbon investment in the presence of financial frictions. We develop a two-sector environmental dynamic stochastic general equilibrium model calibrated to the Euro Area, to simulate an economic transition in line with the EU climate targets. Financial frictions dampen the response of the economy to the carbon tax such that the emissions target will be missed by 11 percentage points. Moreover, the adverse effects of financial frictions increase when climate policy is delayed. We further identify a volume and a risk effect that drive the impact of a financial wealth shock and an uncertainty shock on emission intensity.
BCUN: Bayesian Fully Convolutional Neural Network for Hyperspectral Spectral Unmixing

Spectral unmixing (SU) plays a fundamental role in hyperspectral image (HSI) processing. Effective SU relies on the accurate and efficient characterization of the noise effect, the endmembers, and the spatial correlation effect in abundances, as well as efficient optimization techniques to estimate these effects. To address these issues, this article presents a Bayesian fully convolutional hyperspectral unmixing network (BCUN) with the following key characteristics. First, a fully convolutional neural network (FCNN)-based deep image prior (DIP) is designed for enhanced characterization and estimation of the spatial context information in abundance maps, leading to more efficient and accurate abundance modeling than the traditional nonnegative least squares (NNLS) approaches. Second, a multivariate Gaussian distribution with an anisotropic covariance matrix is designed to characterize the conditional distribution of the spectral observations, leading to a novel Mahalanobis distance-based loss for FCNN training that is better capable of addressing the noise heterogeneous effect in HSI than the Euclidean distance-based mean squared error (MSE) loss in traditional deep neural networks. Third, the designed conditional distribution of spectral observations also enables the incorporation of the spectral mixture model (SMM) into the FCNN training process for effectively leveraging the knowledge in the forward spectral model. Fourth, the endmembers are modeled and estimated by a “purified means” approach that is capable of better characterizing endmembers. Finally, the above key components are coherently integrated into a Bayesian framework, and the resulting maximum a posteriori (MAP) problem is solved by a designed expectation–maximization (EM) algorithm. Experimental results on both simulated and real HSIs demonstrate that the proposed BCUN approach outperforms the other classical and state-of-the-art methods on both endmember estimation and abundance estimation.
Fast inference for robust nonlinear mixed-effects models

The interest for nonlinear mixed-effects models comes from application areas as pharmacokinetics, growth curves and HIV viral dynamics. However, the modeling procedure usually leads to many difficulties, as the inclusion of random effects, the estimation process and the model sensitivity to atypical or nonnormal data. The scale mixture of normal distributions include heavy-tailed models, as the Student-t, slash and contaminated normal distributions, and provide competitive alternatives to the usual models, enabling the obtention of robust estimates against outlying observations. Our proposal is to compare two estimation methods in nonlinear mixed-effects models where the random components follow a multivariate scale mixture of normal distributions. For this purpose, a Monte Carlo expectation-maximization algorithm (MCEM) and an efficient likelihood-based approximate method are developed. Results show that the approximate method is much faster and enables a fairly efficient likelihood maximization, although a slightly larger bias may be produced, especially for the fixed-effects parameters. A discussion on the robustness aspects of the proposed models are also provided. Two real nonlinear applications are discussed and a brief simulation study is presented.
Robust Multi-Beam Multiplexing Design Based on a Hybrid Beamforming Structure With Nearly Equal Magnitude Analogue Coefficients

One novel design considering two practical application constraints based on the interleaved subarray architecture is proposed to achieve multi-beam multiplexing for arbitrary directions to serve corresponding users. One is an equal magnitude constraint imposed on the analogue coefficients so that beamforming can be achieved by pure phase shifters after the normalisation of magnitudes; the other one is a robust constraint against steering vector errors. Designed examples are provided to verify the effectiveness of the proposed method.
Predictive Optimization Based Energy Cost Minimization and Energy Sharing Mechanism for Peer-to-Peer Nanogrid Network

The scientific community believes that peer-to-peer energy trading will dominate a significant portion of forthcoming power generation systems research. Despite a plethora of optimal energy trading solutions, optimizing the trading cost and intelligent formation of energy sharing strategies are deemed exigent problems. Contemplating the excessive rise of energy demands across the globe, this study introduces a predictive optimization-based nanogrid energy trading model that minimizes energy trading cost and provides an optimal energy sharing plan between peers connected within a nanogrid network/cluster. The proposed study comprises two folds: (1) PSO-enabled objective function incorporating actual and predicted values of essential energy attributes, is implemented to reduce the trading cost, (2) an intelligent time-aware energy sharing strategy to determine the role of peers, and foster the harness of renewable energy to meet the energy requirements. The study also comprehensively analyzes essential nano-grid energy parameters and predicts energy load, consumption, and cost to grasp the time-interval-based energy trends. In addition, an optimal ESS charging and discharging operation is devised to manage excess power efficiently. The proposed model is validated on the case study containing data of 12 nanogrid houses. The outcomes yield that the proposed study holds significant potential in reducing the trading cost and optimally sharing the energy within the P2P network.
M-PolKA: Multipath Polynomial Key-Based Source Routing for Reliable Communications

Innovative traffic engineering functions and services require disrupting routing and forwarding mechanisms to be performed with low overhead over complex network topologies. Source routing (SR) is a prominent alternative to table-based routing for providing the needed expressiveness and agility by reducing the number of network states. This work proposes the M-PolKA, a topology-agnostic multipath source routing scheme and orchestration architecture for reliable communications, which explores special properties from the Residue Number System (RNS) polynomial arithmetic. A P4-based proof-of-concept is experimentally demonstrated using emulated and hardware prototypes. Also, use cases for revealing M-PolKA’s functionalities are tested in different scenarios in order to address problems, such as communication reliability improvement, agile path migration and fast failure reaction. Finally, low overhead for extra functionalities is observed when RNS-based SR is compared to traditional routing approaches.
A Resource Allocation Scheme for Real-Time Energy-Aware Offloading in Vehicular Networks with MEC

With the emergence of new vehicular applications, computation offloading based on mobile edge computing (MEC) has become a promising paradigm in resource-constrained vehicular networks. However, an unreasonable offloading strategy in offloading can cause serious energy consumption and latency. A real-time energy-aware offloading scheme for vehicle networks, based on MEC, is proposed to optimize communication and computation resource to decrease energy consumption and latency. Because the problem of computation offloading and resource allocation is the mixed-integer nonlinear problem (MINLP), this article uses a bi-level optimization method to transform the original MINLP into two subproblems. Furthermore, considering the mobility of vehicle users (V-UEs) and the availability of cloud resources, an offloading scheme based on deep reinforcement learning (DRL) is adopted to help users make the optimal offloading decisions. The simulation results show that the proposed bi-level optimization algorithm reduces the total overhead by nearly 40% to the compared algorithm.
Jackfruit Byproducts: Functional Properties and Scope of Utilization as Unleavened Flat Bread

ABSTRACT Byproducts generated during jackfruit processing that mainly consists of rind, strand, core, and seeds were analyzed for their composition. It was found that jackfruit is rich in fiber content (highest in core part, 32%) and a good source of protein (highest in seed part, 15%). Different parts possess appreciable functional properties, which give an advantage of being used in bakery products. For a desirable flatbread, the jackfruit and wheat flour formulations were made using D-optimal mixture design. It demonstrated that the dough springiness, flatbread color, flatbread overall acceptability, and shear force varied significantly with respect to the incorporation of flour of different parts of jackfruit in wheat for the formulation of flatbread. The results indicate that the replacement of the jackfruit flour in flatbread is highly nutritious at the same time stays acceptable.
Method of Evaluating Dielectric Interruption Capability of High-Voltage Circuit Breaker

Two performance indices using the local dielectric strength are proposed to measure interruption capabilities for breaker terminal fault duties in high-voltage circuit breakers. The dielectric strength at a part in the insulating gas volume between arcing contacts surrounded by an insulating nozzle was evaluated by comparing the applied electric field strength with the critical electric field strength calculated from the gas flow properties. The first index quantifies the effect of suppressing the discharge evolution, which is calculated by integrating the ratio of the critical electric field to the applied electric field in the space between the arcing contacts. The second index expresses the ease of initiating dielectric breakdown, which is calculated by integrating the inverse of the first index in the range of space including the surface of the insulating nozzle. To determine the criteria for the performance indices, gas flow simulations were conducted under experimental conditions with 10–100% of the rated interrupting current. The region excluding failure cases was considered to be the high-performance area.