Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Impedance-Conditioned Phase-Locked Loop for the VSC Converter Connected to Weak Grid

In this paper, an adaptive version of the impedance-conditioned phase-locked loop (IC-PLL), namely the adaptive IC-PLL (AIC-PLL), is proposed. The IC-PLL has recently been proposed to address the issue of synchronisation with a weak AC grid by supplementing the conventional synchronous reference frame phase-locked loop (SRF-PLL) with an additional virtual impedance term. The resulting IC-PLL aims to synchronise the converter to a remote and stronger point in the grid, hence increasing the upper bound on the achievable power transfer achieved by the VSC converter connected to the weak grid. However, the issue of the variable grid strength imposes another challenge in the operation of the IC-PLL. This is because the IC-PLL requires impedance estimation methods to estimate the value of the virtual impedance part. In AIC-PLL, the virtual impedance part is estimated by appending another dynamic loop in the exciting IC-PLL. In this method, an additional closed loop is involved so that the values of the virtual inductance and resistance are internally estimated and adapted. Hence, the VSC converter becomes effectively viable for the case of the grid strength variable, where the estimation of the grid impedance becomes unnecessary. The results show that the converter that relies on AIC-PLL has the ability to transfer power that is approximately equal to the theoretical maximum power while maintaining satisfactory dynamic performance.
Operational optimisation of a tailings storage facility based on statistical analysis of historical monitoring records

Operational control and trigger action response plans for tailings storage facilities (TSFs) routinely measure a number of operational aspects to assess risk and ensure the TSF does not exceed certain design considerations. Measurements that are routinely used for this purpose include topographical surveys and beacon settlements, density and moisture measurements, and discharge characteristics, among others. A statistical analysis of the cumulative historical operational datasets from a TSF allows improved knowledge of the level of variability of the considered parameters, and potentially enhances risk-based decision-making by increasing the understanding of uncertainties and the potential for expected deviations during operations (ICMM 2021). The inclusion of a probabilistic dataset in the design inputs allows a performance-based approach to managing a TSF, considering a series of scenarios defined by performance objectives, determining key factors to identify them in a timely manner, and incorporating effective corrective or ‘failure’ control measurements, that can be improved with sequential forecasts of the TSF behaviour. This approach was undertaken to optimise the deposition strategy of the Cerro Vanguardia TSF and expand its life-of-mine (LOM), allowing for tighter construction planning and deferral of construction by several years. This had considerable benefits during the current COVID-19 contingency. Statistical analysis of ongoing operational monitoring data was adequately incorporated into operational design optimisation and to select an adequate level of risk tolerance based on an ‘as low as reasonably practical’ (ALARP) perspective. Performance-based scenarios were identified and plans for timely decision-making were established to forecast reasonable economical/financial planning, and a probability-based events selection to trigger timely operational adjustments.
Accuracy of human papillomavirus tests on self-collected urine versus clinician-collected samples for the detection of cervical precancer: a systematic review and meta-analysis

Objective The human papillomavirus (HPV) test is an effective screening tool to prevent cervical cancer. Urinary sampling for HPV detection improves the accessibility and participation of screening services and reduces the cost and burden on physicians. The clinical accuracy of urinary HPV test has yet to be determined via meta-analysis. This study assessed the clinical accuracy of these tests to detect cervical intraepithelial neoplasia (CIN) 2 or worse. Methods Relevant studies were identified using the PubMed, Embase, and Cochrane databases. Research eligibility was based on the clinical accuracy of HPV test on clinician-collected samples as a comparator test, and urine as an index test. The reference standard was the presence of CIN2 or worse. The pooled absolute, relative sensitivity, and specificity of the urinary HPV test versus clinician-collected samples were assessed using a bivariate model. Results The pooled sensitivity of urinary HPV test was significantly lower than that of clinician-collected samples (ratio=0.84, 95% confidence interval [CI]=0.78–0.91). However, some polymerase chain reaction (PCR)-based HPV test such as GP5+/6+ (relative sensitivity=0.98, 95% CI=0.91–1.05), SPF10 (relative sensitivity=0.98, 85% CI=0.88–1.08) and non GP5+/6+ PCR (relative sensitivity=1.00, 95% CI=0.88–1.14) showed similar sensitivity in both the urine and clinician-collected samples. Conclusion Our findings indicate that HPV test with some PCR-based assay on urine versus clinician-collected samples demonstrate similar clinical accuracy to detect CIN2 or worse. It suggests that urinary HPV test may present itself as a decent alternative screening tool for the detection of cervical pre-cancer. Trial Registration PROSPERO identifier: CRD42021227901
Bioinformatic analyses determine the importance of CXCL2 and CXCL8 in atypical meningioma development and reoccurrence.

AIM Meningiomas are the second most common type of brain neoplasms. Atypical meningiomas are a class of malignant meningiomas with a higher rate of recurrence. The molecular mechanisms underlying meningioma reoccurrence are still not clear, and the treatment options are limited to surgery and radiotherapy. MATERIAL AND METHODS The microarray datasets GSE43290 and GSE16581 were downloaded from Gene Expression Omnibus (GEO) database to explore the key genes involved in meningioma formation and reocurrence. Additionally, the relationship between the key genes identified and clinical factors, including age, survival, and recurrence, was assessed. To investigate the the biological functions of the key genes, the gene ontology (GO) and Kyoto Encyclopedia of Gene and Genomes (KEGG) pathways enrichment analyses were performed. Finally, the differences in immune infiltration between atypical meningiomas and healthy tissues were assessed. RESULTS A total of 286 hub genes were identified, which were enriched in leukocyte migration, collagen-containing extracellular matrix, signaling receptor activator activity, and receptor-ligand activity. The differentially expressed genes(DEGs) were mainly enriched in the IL-17 signaling pathway and focal adhesion. Among these hub genes, two overlapping genes, including CXCL8 and CXCL2, were selected as key genes which were correlated with tumor survival and recurrence. These two genes were enriched in mediating chemokine and cytokine responses, especially neutrophil and granulocyte responses, and influenced the immune cells infiltrated in the tumor tissue, thereby, influencing prognosis. CONCLUSION The implications of this study excavated the key genes in atypical meningiomas which could help us understand the molecular mechanisms and provide the candidate therapeutic targets.
Repair of Geological Models Based on Multiple Material Marching Cubes

In this paper, we present a multi-domain implicit surface reconstruction algorithm for geological modeling based on the labeling of voxel points. The improved algorithm sets a label for each voxel point to represent the type of its geological domain and then obtains all the voxel points in the void areas. After that, the improved algorithm modifies the labels of the voxel points in the void areas and finally reconstructs the geological models through the Multiple Material Marching Cubes (M3C) algorithm. The improved algorithm solves the problems of some unexpected overlaps and voids in geological modeling by setting and modifying the labels of the voxel points. Our key contribution is proposing a labeling processing method to repair the overlap and void defects generated in the geological modeling and realizing the improved M3C algorithm. The experimental results of some geological models show the performance of the improved method. Compared with the original method, the improved method can repair the overlap and void defects in geological modeling to ensure the raw structural adjacency relationships of the geological bodies.
Feminist/queer/diasporic temporality in Bernardine Evaristo's Girl, Woman, Other (2019)

Claiming that individuals and communities get their choices, rhythms and practices biopolitically choreographed by temporal mechanisms that dictate which human experiences are included or excluded, Elizabeth Freeman states that those ‘whose activities do not show up on the official time line, whose own time lines do not synchronize with it, are variously and often simultaneously black, female, queer’ (2005). The narrative subject of Bernardine Evaristo's Girl, Woman, Other ( 2019) is black, female and (mostly) queer in her design of a polyphonic text featuring twelve black women moving through the world in different decades and occupying a temporal dimension that deviates from the linear and teleological modes. I draw on Edelman (2004); Freeman (2010) and Ahmed (2010, 2017) to analyse Evaristo's novel as a text informed by feminist queer temporality and thus explore these characters’ resistance to chrononormative assumptions like ‘the straight time of domesticated gender, capital accumulation, and national coherence’ ( Ramberg, 2016). In this light, I address her cast of ‘time abjects’ –lesbians, transgender women, feminist killjoys and menopausal females—as characterized ‘chronotopically’ as their racialized and gendered subjectivities coalesce temporally and spatially seeing their pasts and futures interact in a typically transpositional, queer and diasporic continuum. By invoking Freeman's notion of ‘erotohistoriography’ ( 2010) as a distinctive mode of queer time that not only recognizes non-linear chronopolitics, but decidedly prioritizes bodies and pleasures in self-representation, I contend that Evaristo depicts bodies as likewise performing this encounter between past and present in hybrid, carnal and trans-temporal terms. I conclude that in her joining temporality and corporeality, memory and desire, she suggests alternative ways of representing contemporary black British womanhood
Correlation between Decreased Nuclear Factor Kappa Beta (NFKβ), Kras, and Braf Genes’ Expression and Enhanced Chemosensitivity of Human Squamous Cell Carcinoma Cells to 5-fluorouracil and/or Mesenchymal Stem Cells-derived Microvesicles

OBJECTIVE Oral squamous cell carcinoma (OSCC) comprises about 10% of head and neck cancer. 5-fluorouracil (5-FU) is commonly used for the treatment of OSCC. However, it has many limitations due to its identified side effects. Therefore, this work compared squamous cell carcinoma (SCC) cells’ chemosensitivity to 5-FU, mesenchymal stem cells-derived microvesicles (MVs), and their combination. METHODS Human SCC cell line (SCC152) was subjected to 5-FU or MVs or their combination for 24 h and 48 h. Inverted microscopic evaluation of apoptosis, MTT cell proliferation assay, DNA comet assay, and detection of NFKβ, Kras, and Braf genes’ expression were performed. RESULTS The combination group, compared to 5-FU or MVs treated groups, showed the most apparent apoptotic features. Cell proliferation was significantly decreased, while the tailed DNA% was significantly increased in the combination group versus either the 5-FU or MVs groups. The combination group showed a significant decrease in NFKβ, Kras, and Braf genes’ expression than the 5-FU or MVs treated groups. The correlation between cell proliferation and the studied genes showed a very strong positive linear relationship, while a strong negative linear relationship existed between cell proliferation and tailed DNA%.
Customer Prioritization for Medical Supply Chain During COVID-19 Pandemic

During COVID-19, the escalated demand for various pharmaceutical products with the existing production capacity of pharmaceutical companies has stirred the need to prioritize its customers in order to fulfill their demand. This study considers a two-echelon pharmaceutical supply chain considering various pharma-distributors as its suppliers and hospitals, pharmacies, and retail stores as its customers. Previous studies have generally considered a balanced situation in terms of supply and demand whereas this study considers a special situation of COVID-19 pandemic where demand exceeds supply Various criteria have been identified from the literature that influences the selection of customers. A questionnaire has been developed to collect primary data from pharmaceutical suppliers pertaining to customer-selection criteria. These criteria have been prioritized with respect to eigenvalues obtained from Principal Component Analysis and also validated with the experts' domain-related knowledge using Analytical Hierarchy Process. Profit potential appeared to be the most important criteria of customer selection followed by trust and service convenience brand loyalty, commitment, brand awareness, brand image, sustainable behavior, and risk. Subsequently, Multi Criteria Decision Analysis has been performed to prioritize the customer-selection criteria and customers with respect to selection criteria. Three experts with seven and three and ten years of experience have participated in the study. Findings of the study suggest large hospitals, large pharmacies, and small retail stores are the highly preferred customers. Moreover, findings of prioritization of customer-selection criteria from both Principal Component Analysis and Analytical Hierarchy Process are consistent. Furthermore, this study considers the experience of three experts to calculate an aggregate score of priorities to reach an effective decision. Unlike traditional supply chain problems of supplier selection, this study considers a selection of customers and is useful for procurement and supply chain managers to prioritize customers while considering multiple selection criteria. © 2021 Tech Science Press. All rights reserved.
A Google Earth Engine-enabled Python approach for the identification of anthropogenic palaeo-landscape features

The necessity of sustainable development for landscapes has emerged as an important theme in recent decades. Current methods take a holistic approach to landscape heritage and promote an interdisciplinary dialogue to facilitate complementary landscape management strategies. With the socio-economic values of the “natural” and “cultural” landscape heritage increasingly recognised worldwide, remote sensing tools are being used more and more to facilitate the recording and management of landscape heritage. The advent of freeware cloud computing services has enabled significant improvements in landscape research allowing the rapid exploration and processing of satellite imagery such as the Landsat and Copernicus Sentinel datasets. This research represents one of the first applications of the Google Earth Engine (GEE) Python application programming interface (API) in studies of historic landscapes. The complete free and open-source software (FOSS) cloud protocol proposed here consists of a Python code script developed in Google Colab, which could be adapted and replicated in different areas of the world. A multi-temporal approach has been adopted to investigate the potential of Sentinel-2 satellite imagery to detect buried hydrological and anthropogenic features along with spectral index and spectral decomposition analysis. The protocol's effectiveness in identifying palaeo-riverscape features has been tested in the Po Plain (N Italy).
Impedance Learning-Based Adaptive Control for Human–Robot Interaction

In this article, a new learning-based time-varying impedance controller is proposed and tested to facilitate an autonomous physical human–robot interaction (pHRI). Novel adaptation laws are formulated for online adjustment of robot impedance based on human behavior. Two other sets of update rules are defined for intelligent coping with the robot’s structured and unstructured uncertainties. These rules ensure stability via Lyapunov’s theorem and provide uniform ultimate boundedness (UUB) of the closed-loop system’s response, without a need for HRI force/torque measurement. Accordingly, the convergence of response signals, including errors in tracking, online impedance learning, robot parameter adaptation, and controller gain variation, is proven to operate in a bounded region (compact set) in the presence of robot and human uncertainties and bounded disturbances. The performance of the developed intelligent impedance-varying control strategy is investigated through comprehensive experimental studies in a repetitive following task with a moving target.
Automated segmentation of osteoblastic vertebral metastasis: a radiomics approach

ABSTRACT Skeletal metastasis can be visualised as changes in bone texture. This investigation aimed to develop an automated method to segment spinal osteoblastic metastases in μCT images using radiomic-based feature extraction. Ex vivo μCT images were acquired of rat lumbar vertebrae with osteoblastic metastases. Pyradiomics was used to calculate 3D features for voxels of trabecular bone isolated using an atlas and level-set based approach. A Random Forest Classifier was used to combine features to develop automated predictions for segmenting the osteoblastic lesions. The automated Pyradiomics approach (77 ± 10%) yielded a dice similarity coefficients comparable to the manual intra and inter-user variability (82 15% and 76 15%, respectively).
Differences in allelopathic effect of tree of heaven root extracts and isolated ailanthone on test-species

The objective of this paper was to analyse allelopathic effect of 3 different aqueous solutions from tree of heaven’s ( Ailanthus altissima (Mill.) Swingle) root extract and their dilutions on common wheat ( Triticum aestivum L.), pigweed ( Amaranthus retroflexus L.) and red bristlegrass ( Setaria pumila L.). Investigated aqueous solutions obtained from tree of heaven’s root extract were root aqueous solution, aqueous solution with isolated ailanthone and root aqueous solution without ailanthone. Each of these solutions was diluted with water in ratio 1:4 and 1:16 before application on seeds of 3 test-plant species. Concentrated root and ailanthone aqueous solution and dilutions were equivalent to concentration of 0.48 mg/mL ailanthone. High allelopathic effect on radicle and shoot length of all test-species was proven for all investigated aqueous solution and their dilutions. Inhibitory effect on initial growth of all test-species was proportional to the increase in concentration in all treatments. The effect on initial growth was stronger in relation to the effect on germination of test-species. Lower concentrations caused stimulation of red bristlegrass germination. Pigweed was the most sensitive and common wheat the least sensitive test-species. The least significant effect was measured in the aqueous solution of isolated ailanthone.
Investigation of Sentinel-1 Derived Land Subsidence Using Wavelet Tools And Triple Exponential Smoothing Algorithm In Lagos, Nigeria

Lagos has a history of long-term groundwater abstraction that is often compounded by the rising indiscriminate private borehole and water well proliferation. This has resulted in various forms of environmental degradation, including land subsidence. Prediction of the temporal evolution of land subsidence is central to successful land subsidence management. In this study, a triple exponential smoothing algorithm was applied to predict the future trend of land subsidence in Lagos. Land subsidence time series is computed with SBAS-InSAR technique with Sentinel-1 acquisitions from 2015 to 2019. Besides, Matlab wavelet tool was implemented to investigate the periodicity within land displacement signal components and to understand the relationship between the observed land subsidence, and groundwater level change and that of soil moisture. Results show that land subsidence in the LOS direction varied approximately between –94 and 15 mm/year. According to the wavelet-based analysis result, land subsidence in Lagos is partly influenced by both groundwater level fluctuations and soil moisture variability. Evaluation of the proposed model indicates good accuracy, with the highest residual of approximately 8%. We then used the model to predict land subsidence between the years 2020 and 2023. The result showed that by the end of 2023 the maximum subsidence would reach 958 mm which is approximately 23% increase.
Evaluating the Intertwined Relationships of the Drivers for University Technology Transfer

Universities are the best places to gather knowledge and innovation, but the basis of technological development lies in talented R&D personnel who provide services to enterprise R&D activities, research institutions, and universities. Universities also gather many elites who cultivate talent for the country. However, universities do not have adequate technology transfer experience and do not network in industrial circles, which results in a huge gap between the concept and the practical result. This research determined the critical success factors and explored the causal relationships influencing the technology transfer from universities. We found that the main impact of the key factors was the technology market dimension. University technology transfer activities had to be classified as top priority. Technology industrial applicability was the main key evaluation factor, along with inventor attitude. In the organizational culture dimension, the attitude and ability of top management were the main evaluation factors. We attempted to draw upon our analysis results to make recommendations related to technology transfer to assist universities in successfully transferring their research results.
Parenting Styles, Food Parenting Practices and Dietary Intakes of Preschoolers

Previous evidence suggests that children’s eating behaviors were largely influenced by the parent and home eating structure. This study examined the relationship between parenting styles (including authoritative, authoritarian, indulgent, and uninvolved), food parenting practices (within Structure, Coercive Control, and Autonomy Support constructs) and dietary intakes of preschoolers. Children aged 3–5 years and their parents were recruited from preschools/daycare centers and parents completed the surveys (n = 166). Dietary intakes were collected using the Harvard Service Food Frequency Questionnaire (HSFFQ), parenting style was assessed using the Parenting Dimensions Inventory-Short Version (PDI-S), and food parenting practices were measured using Comprehensive Home Environment Survey (CHES). The results showed that food parenting practices had a higher number of specific significant findings on children’s nutrient and food group intakes than parenting styles. Correlation analyses showed positive parenting practices within Structure were significantly related to healthier children’s intakes (e.g., vegetables, iron, and folate) and less unhealthy dietary intakes (e.g., sweets and total fats). Regression models show that children with authoritative parents consumed more fruits compared to children with authoritarian parents and indulgent parents. The results addressed the importance of parental influences for preschoolers’ healthy dietary intakes, which suggested that future interventions and educational programs could enhance parenting practices to impact child diet.