Miracle-dz/UniFAR-FTUs huggingface dataset:
PFKFB4 promotes angiogenesis via IL-6/STAT5A/P-STAT5 signaling in breast cancer

Breast cancer has become the most newly-diagnosed cancer and the 5th leading cause of cancer death worldwide. The 5-year survival rate of breast cancer is about 90%. However, the 5-year survival rate drops to <30% when metastasis to distant sites occurs. The blood vessel formation (i.e., angiogenesis) plays a crucial role during the metastatic process. In this study, we investigated the role of PFKFB4 in angiogenesis of breast cancer. Employing in vitro HUVEC tube formation or in vivo orthotopic mouse model, and gene editing or specific small inhibitors strategy, and utilizing qPCR, western blot, ELISA, or immunofluorescent/immunohistochemistry staining methods, we found the following: 1) PFKFB4 upregulates IL-6 expression via NF-κB signaling in breast cancer cells; 2) PFKFB4-induced lactate secretion contributes to NF-κB activation in breast cancer cells; 3) IL-6 elicits angiogenesis via STAT5A/P-STAT5 in HUVEC; 4) 5-MPN (a specific PFKFB4 inhibitor) suppresses angiogenesis in vitro and in vivo. Our findings suggest a potential strategy whereby 5-MPN may lead to an improved therapeutic outcome for breast cancer patients.
Optimisation of a rapid and efficient transformation protocol for fungal blast-susceptible indica rice cultivars HR-12 and CO-39.

Rice is an important staple crop and fungal blast disease destroys about 10-30% of its global produce, annually. Although genetic manipulation has largely been employed in crop-improvement programmes and agricultural biotechnology, the ease of transformation of several recalcitrant indica cultivars continues to be a challenge. HR-12 and CO-39 are two indica cultivars that are commonly used in breeding programmes, but are susceptible to biotic threats like fungal blast and sheath blight disease. Here in this study, we have optimised a rapid and reproducible transformation protocol for the said cultivars, having compared both the tissue-culture and in-planta methods of transformation. Murashige & Skoog basal media supplemented with maltose and 2.5 mg l-1 2,4-D induced efficient callogenesis in HR-12, while maltose with 3 mg l-1 2,4-D gave optimum results in case of CO-39. The media containing 0.5 mg l-1 NAA, 3 mg l-1 BAP, and 1 mg l-1 kinetin yielded a maximum regeneration efficiency of 62% and 65% in HR-12 and CO-39, respectively. The studies with Agrobacterium tumefaciens, LBA4404 strain harbouring pCAMBIA1303 suggested that although these cultivars demonstrated successful gene-transfer, they failed to regenerate efficiently, post-transformation. Alternatively, our modified in-planta piercing and vacuum infiltration-based protocol resulted in 33-35% transformation efficiency in less than half the time required for tissue-culture based transformation method. As per our knowledge, it is among the highest obtained from existing piercing-based direct transformation protocols in rice, and can also be implemented in genetically manipulating other recalcitrant varieties of rice.
Textile Digital Printing Technologies

Abstract Textile digital printing emerged in the 1990s as a prototyping tool and a vehicle for printing small batches of fabric for niche market products. Developments over the past 5 years have been dramatic, with major practitioner conferences in the U.S. and in Europe, and a specialist trade press journal. We are now at the stage where all the ingredients are present for producing commercial print runs, but there are still many hurdles to jump for digital printing technologies to make an impact in world markets. This monograph reviews the technological issues and sets these in a wider commercial context. It explains how new markets are being successfully created and how digital printing technologies have provided a springboard for product innovation.
Biocompatibility and Osteogenic Potential of Calcium Silicate-Based Cement Combined with Enamel Matrix Derivative: Effects on Human Bone Marrow-Derived Stem Cells

The characteristics of retrograde filling material are important factors that can affect the long-term success of apical microsurgery. Various calcium silicate-based cements (CSC) were introduced to overcome drawbacks of mineral trioxide aggregate (MTA), while Emdogain is known to be effective in the regeneration of periodontal tissues. The aim of this study is to evaluate the biocompatibility and osteogenic potential of various CSCs combined with Emdogain on human bone marrow-derived mesenchymal stem cells. Experimental groups were classified into eight groups depending on the material and the presence of Emdogain. In the cell-counting kit test, all experimental groups combined with Emdogain showed higher cell viability compared with those without Emdogain at days 1 and 2. In the wound-healing assay, cell migration increased significantly over time, with or without Emdogain. In the alkaline phosphatase assay, all groups treated with Emdogain showed higher activity compared with those without Emdogain at day 3 (p < 0.05). Using alizarin red S staining, all groups treated with Emdogain showed greater calcium nodule formation compared with those without Emdogain at days 7 and 14 (p < 0.05). In conclusion, using CSCs as retrograde filling materials and the application of additional Emdogain will increase bone regeneration and improve the prognosis of apical microsurgery.
Characterizing Fatigue of Asphalt Binders with Viscoelastic Continuum Damage Mechanics

Fatigue cracking, either top-down or bottom-up, is one of the major distresses for asphalt pavements. As the binding agent, asphalt binder plays a critical role in the fatigue resistance of hot-mix asphalt (HMA). Accurate characterization and proper selection of fatigue-resistant asphalt binders could prolong the fatigue life of asphalt pavement. The fatigue indicator currently used in the Superpave® binder specification is based on the fatigue behaviors of asphalt binders within the undamaged, linear viscoelastic range. There have been some controversies on the validity of this parameter. In reality, HMA and asphalt binders develop cracks under repeated traffic loads. Therefore, a more fundamental approach is needed to characterize the fatigue behaviors at a stage of damage to understand the true fatigue mechanism of the asphalt binder. This paper presents the study of the application of viscoelastic continuum damage (VECD) mechanics, which has been successfully applied to HMA, to test results of asphalt binders in the shear mode under various loading conditions. The results indicated that VECD can be effectively applied to asphalt binders, present a good potential for characterizing asphalt binders and predict the contribution to fatigue resistance by means of a fundamental approach that parallels some of the advanced work regarding asphalt mixtures. This potential could allow for a unified model for fatigue of mixtures and binders.
Electromagnetic stirring for continuous casting - Part 2

The multiple versions of electromagnetic stirring in continuous casting are described. For long products, linear or rotational stirring appears confusing, but is clarified based on liquid steel flow pattern and metallurgical results. Rotational mould stirring is the predominant application. For slabs, butterfly type single and double strand stirring and rotational mould stirring coexist with different metallurgical purposes. Also, the evolution to higher casting speeds has required a new type of mould stirring that combines accelerating and braking functions. The trend goes to multi-mode systems.
The design of linear phase FIR filters using the IDFT

The paper presents a comprehensive set of equations for specifying the transfer function of linear phase finite-impulse response (LPFIR) filters. A procedure for designing the eight possible LPFIR filters (symmetric and anti-symmetric, even and odd length, type 1 and type 2 filters), using the inverse discrete Fourier transform (IDFT) is described. This technique can be equally applied to the window method and the frequency sampling method.
Semi-universal geo-crack detection by machine learning

Introduction: Cracks are a key feature that determines the structural integrity of rocks, and their angular distribution can be used to determine the local or regional stress patterns. The temporal growth of cracks can be monitored in order to predict impending failures of materials or structures such as a weakened dam. Thus, cracks and their spatial-temporal distributions should be automatically monitored for assessing their structural integrity, the associated stress patterns and their potential for failure. Method: We show that the U-Net convolutional neural network, semantic segmentation and transfer learning can be used to accurately detect cracks in drone photos of sedimentary massifs. In this case, the crack distributions are used to assess the safest areas for tunnel excavation. Compared to the coarse performance of ridge detection, the U-Net accuracy in identifying cracks in images can be as high as 98% when evaluated against human identification, which is sufficient for assessing the general crack properties of the rock faces for the engineering project. Result: Based on approximately 100 h of manual cracks labeling in 127 drone photos and 20 h of network training, the U-Net was able to successfully detect cracks in 23,845 high-resolution photographs in less than 22 h using two Nvidia V100 GPUs. Meanwhile, the network was able to detect more than 80% of the observable cracks of a volcanic outcrop in Idaho without additional training. With a modest amount of extra labeling on photos of the volcanic outcrop and transfer training, we found that the accuracy significantly improved. The surprising outcome of this research is that the U-Net crack detector laboriously trained on photos of sedimentary rocks can also be effectively applied to photos of volcanic rock faces. This can be important for real-time assessment of geological hazards and lithology information for dam inspection and planetary exploration by autonomous vehicles. For another application, we accurately detected fractures and faults with a scale of tens of kilometers from Martian photographs. Conclusions: In summary, our methodology of using CNN with transfer training suggests that it can be used as a semi-universal detector of cracks in across a range of diverse geological settings.
Multi-modal Data Fusion Method for Human Behavior Recognition Based on Two IA-Net and CHMM

The multi-modal data fusion method based on IA-net and CHMM technical proposed is designed to solve the problem that the incompleteness of target behavior information in complex family environment leads to the low accuracy of human behavior recognition.The two improved neural networks(STA-ResNet50、STA-GoogleNet)are combined with LSTM to form two IA-Nets respectively to extract RGB and skeleton modal behavior features in video. The two modal feature sequences are input CHMM to construct the probability fusion model of multi-modal behavior recognition.The experimental results show that the human behavior recognition model proposed in this paper has higher accuracy than the previous fusion methods on HMDB51 and UCF101 datasets. New contributions: attention mechanism is introduced to improve the efficiency of video target feature extraction and utilization. A skeleton based feature extraction framework is proposed, which can be used for human behavior recognition in complex environment. In the field of human behavior recognition, probability theory and neural network are cleverly combined and applied, which provides a new method for multi-modal information fusion.
Friend Overprotection in Emerging Adulthood: Associations with Autonomy Support and Psychosocial Adjustment

Abstract Overprotection is a known risk factor in parent-child relationships, but has received little attention in the context of friendships. No studies have examined overprotection in emerging-adult friendships. Yet, overprotection may be especially significant during this developmental period given the prevalence of autonomy-seeking and risk-taking behaviors. In this study, we thus investigated whether overprotection is a feature of emerging-adult friendships that is meaningfully associated with psychosocial adjustment. We also examined whether friend autonomy support is one mechanism by which friend overprotection impacts outcomes. University students (N = 363) completed a new self-report measure of friend overprotection developed for this study, and previously validated measures of relationship qualities (friendship quality, helicopter parenting) and internalizing symptoms (social anxiety, depression). We found initial support for the reliability and validity of the new friend overprotection measure. A path analysis revealed positive associations between friend overprotection and friendship quality and internalizing symptoms, with friend autonomy support as an explanatory mechanism of these associations. Findings are novel as they suggest that overprotection is a salient feature of many friendships during emerging adulthood that may impact psychosocial adjustment in both helpful and harmful ways.
Passive multi-source energy harvesting schemes

Mobile electronics have continually decreased in size; however, mobile power sources have not had comparable increases in energy density or specific energy. Researchers are considering energy harvesting technologies to reduce dependence on batteries, providing alternate sources of power. Combining multiple energy harvesters onto a single platform is a logical and practical method to increase energy output and system robustness. This study explored the dynamics of two passive, multi-source energy harvesting schemes: disparate sources of piezoelectric and photovoltaic, as well as an array of piezoelectrics. A series and a parallel topology were explored for each scheme. For both the schemes, the series topology lends itself to high-level, low-duty cycle load characteristics as it is able to achieve greater amounts of energy on a storage capacitor. The parallel topology lends itself to low-level, high-duty cycle load characteristics due to increased maximum power levels. Both the parallel and the series topologies of the array of piezoelectrics effectively combine the power from the two harvesters in the absence of differences between the two signals. The series topology is insensitive to amplitude differences, and the parallel topology is insensitive to a phase angle or a frequency difference.
Unsupervised extraction and quantification of the bronchial tree on ultra-low-dose vs. standard-dose CT

Automatic extraction of the tracheobronchial tree from high resolution CT data serves visual inspection by virtual endoscopy as well as computer aided measurement of clinical parameters along the airways. The purpose of this study is to show the feasibility of automatic extraction (segmentation) of the airway tree even in ultra-low-dose CT data (5-10 mAs), and to compare the performance of the airway extraction between ultra-low-dose and standard-dose (70-100 mAs) CT data. A direct performance comparison (instead of a mere simulation) was possible since for each patient both an ultra-low-dose and a standard-dose CT scan were acquired within the same examination session. The data sets were recorded with a multi-slice CT scanner at the Charite university hospital Berlin with 1 mm slice thickness. An automated tree extraction algorithm was applied to both the ultra-low-dose and the standard-dose CT data. No dose-specific parameter-tuning or image pre-processing was used. For performance comparison, the total length of all visually verified centerlines of each tree was accumulated for all airways beyond the tracheal carina. Correlation of the extracted total airway length for ultra-low-dose versus standard-dose for each patient showed that on average in the ultra-low-dose images 84% of the length of the standard-dose images was retrieved.
Long term stability of aerial optical cables with respect to gigabit/s data rates

For the extension of existing optical fiber links to higher data transfer rates in the multi-gigabit range and the expected higher power density due to DWDM one must consider possible limitations of the deployed cables. Many investigations have identified polarization mode dispersion PMD as a crucial parameter especially for cables exposed to environmental stresses. Three aerial optical fiber cable links were characterized by measuring PMD, optical time domain reflectometry OTDR, polarization-OTDR, and bit error rate BER. Measurement results over several days are correlated to temperature data from weather stations along the cable lines.
Analysing High Frequency Data Using ARCH and GARCH Methods

High frequency data is a recent entrant to the world of statistics as they relate to the markets. With tick by tick data we get to see the microstructure of the markets and often are better able to see how they vary from the traditional portrayal. Traditional tools used to look at daily and weekly volatilities are not often very useful in timescales of seconds and minutes. In this paper we try to look at two of the most highly traded stocks in the Indian stock market. The large and small errors tend to cluster together, and thus autoregressive conditional heteroscedasticity models are introduced. First we look at ARCH models on tick by tick data of SBI. Then we look at the GARCH models – with two stocks SBI and TATA – and its variants such as PGARCH and EGARCH to try to see if we can predict the conditional variance. We also glance at the DCC GARCH model to see if a bivariate view gives us any new insights. Finally we try to sum up the various techniques by evaluating them according to their utility in estimating high frequency data.
Impact of Nurse-Led Titration Versus Physician Prescription of Hypoglycaemic Agents on HbA1c Level in Type 2 Diabetes Patients: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

A nurse-led diabetic clinic to manage type 2 diabetes, which emphasizes medication adherence, titration of hypoglycemic agents, behavior modification, and motivation for lifestyle changes, is widely recommended and practiced in western countries. This review aims to examine the impact of a nurse-led diabetic clinic versus a standard physician-led diabetic clinic on glycaemic control of type 2 diabetes patients. Studies were obtained using a comprehensive search in the electronic databases of PubMed, Embase, SCOPUS, Cochrane Library, and gray literature through March 2021. We calculated the pooled effect estimate with 95% confidence intervals (CIs) comparing subjects with and without nurse-led titration of hypoglycemic agents using standardized mean difference (SMD) for continuous outcomes and risk ratio (RR) for dichotomous outcomes. Four trials comprising 470 participants (241 intervention group and 229 control group) met the inclusion criteria. Glycated hemoglobin (HbA1c levels and BMI were lower in participants with a nurse-led diabetic clinic (SMD = -0.54, 95% CI -0.89 to -0.20, I2 = 67%, p = 0.002) and (SMD = -0.26 (95% CI -0.45 to -0.07, I2 = 0%, p = .008), respectively, than in those attending a standard physician-led diabetic clinic. Similarly, the pooled result shown that patients attending the nurse-led diabetic clinic had a 31% higher satisfaction level (RR 0.69; 95% CI, 0.51 to 0.92, I2 = 0%, p= 0.01). On the other hand, there was no significant association of the nurse-led diabetic clinics on patients’ blood pressure and intensification of hypoglycemic agents. The certainty of the evidence assessed using Grading of Recommendations Assessment, Development, and Evaluation (GRADE) was moderate for outcomes like HbA1c level, intensification of hypoglycemic agents, and patients' satisfaction and low for other secondary outcomes. Our meta-analysis allows for the conclusion that nurse-led titration of hypoglycemic agents is associated with better glycemic control and enhances patients' satisfaction. Therefore, it is recommended to establish and strengthen nurses-led diabetic clinics for better HbA1c control where physician-led diabetic services are limited. Further research is needed to enhance the quality of the evidence.
Highly non‐linear and wide‐band mmWave active array OTA linearisation using neural network

This paper proposes a neural network (NN) ‐ based over ‐ the ‐ air (OTA) linearisation technique for a highly non ‐ linear and wide ‐ band mmWave active phased array (APA) transmitter and compares it with the conventional memory polynomial model (MPM) ‐ based technique. The proposed NN effectively learns the distinctive non ‐ linear distortions, which may not easily fit to existing MPM solutions, and can, therefore, successfully cope with the challenges introduced by the high non ‐ linearity and wide bandwidth. The proposed technique has been evaluated using a state ‐ of ‐ the ‐ art 4 � 4 APA operating in highly non ‐ linear regions at 28 GHz with a 100 ‐ MHz ‐ wide 3GPP base ‐ station signal as input. Experimental results show the pre ‐ distortion signal generated by the NN exhibits the peak ‐ to ‐ average power ratio (PAPR) much lower than the one generated by MPM and consequently superior linearisation performance in terms of adjacent channel leakage ratio (ACLR) and error vector magnitude (EVM) for high non ‐ linearity cases. Using the proposed NN ‐ based linearisation technique, an improvement of 5 ‐ dB ACLR and 7% points in EVM are achieved, which demonstrates the promising potential of this technique for emerging
Eco-friendly ultrasound-assisted extraction method for determination of metals in oily sludges using inductively coupled plasma-mass spectrometry

ABSTRACT Oily sludge is a potentially toxic waste produced in large quantities by the oil and gas industry and the determination of metal concentrations in complex oily samples still presents an analytical challenge. Consequently, the development of suitable sample preparation procedures is required to allow the monitoring of potentially toxic elements in this type of waste. This paper describes a method for the determination of Cd, Co, Cu, Ni, V and Zn in oily sludges by inductively coupled plasma-mass spectrometry (ICP-MS) using a simple and eco-friendly sample preparation procedure based on ultrasound-assisted extraction (UAE). The UAE was performed using 10.5 mol L−1 of nitric acid as the extraction solution, applying 45 min of extraction in an ultrasonic bath at a temperature of 60 ± 5℃. The limits of detection (LOD) and quantification (LOQ) ranged from 0.1 to 0.5 mg kg−1 and from 0.3 to 1.7 mg kg−1, respectively. The accuracy was evaluated through the comparison of results with acid digestion and the paired t-test indicated no difference between the results (n = 6,95% of confidence level). In addition, regression analysis indicated R > 0.999 and differences of < 14.1% from the optimal slope of 1.0, expressing a good correlation between the results obtained applying UAE and acid digestion. The method precision (RSD) was better than 21.0%, which can be considered adequate for the analysis of complex sample matrices. The method was applied to determine the analytes in seven oily sludges from different oil storage tanks and all results were in the mg kg−1 range. The proposed method was evaluated on the Eco-Scale and the score obtained was 84, indicating excellent greenness. Thus, the proposed method is simple, fast, eco-friendly and efficient, and offers good potential for the extraction and determination of potentially toxic metals in oily sludges.
NON-INVASIVE INVESTIGATION METHOD OF NATURAL FIBER SEEDS QUALITY

The paper tries to analyze the possibilities of classification of hemp fiber plant seeds in order to provide a sorting system to select the high quality seeds destined for human consumption. The existing automatic classification systems for seeds take in consideration the size, shape, color and texture in order to assess the quality of nutritional seeds. This work investigates the classification possibilities of image systems using photo images acquired by an RGB camera.