Miracle-dz/UniFAR-FTUs huggingface dataset:
Feasibility of Using Shear Wave Ultrasonic Probes as Pump-Wave Sources in Concrete Microcrack Detection and Monitoring by Nonlinear Ultrasonic Coda Wave Interferometry

This paper represents a first attempt to study the feasibility of using shear wave (SW) ultrasonic probes as pump-wave sources in concrete microcrack detection and monitoring by Nonlinear Ultrasonic Coda Wave Interferometry (NCWI). The premise behind our study is that the nonlinear elastic hysteretic behavior at microcracks may depend on their orientation with respect to the stationary wave-field induced by the pump-wave source. In this context, the use of a SW probe as a pump-wave source may induce the nonlinear elastic behavior of microcracks oriented in directions not typically detected by a conventional longitudinal pump-wave source. To date, this premise is hard to address by current experimental and numerical methods, however, the feasibility of using SW probes as a pump-wave source can be experimentally tested. This idea is the main focus of the present work. Under laboratory conditions, we exploit the high sensitivity of the CWI technique to capture the transient weakening behaviour induced by the SW pump-wave source in concrete samples subjected to loading and unloading cycles. Our results show that after reaching a load level of 40% of the ultimate stress, the material weakening increases as a consequence of microcrack proliferation, which is consistent with previous studies. Despite the lack of exhaustive experimental studies, we believe that our work is the first step in the formulation of strategies that involve an appropriate selection and placement of pump-wave sources to improve the NCWI technique. These improvements may be relevant to convert the NCWI technique into a more suitable non-destructive testing technique for the inspection of microcracking evolution in concrete structures and the assessment of their structural integrity.
The Impact of Mindfulness Meditation on the Psychosomatic Spectrum of Oral Diseases: Mapping the Evidence

The psychological aspect of dis-ease, which is indeed a lack of ‘ease’ is generally overlooked in the management of myriad maladies that affect the human body. The concept of mindfulness meditation, which is an interesting hybrid born from the meditative discipline of the east and the intellectual discipline of the west is gaining attention in the past two decades for its benefits in the holistic development of individuals. When individuals with ailments are trained under therapists supervised by the clinicians, significant results can be seen in alleviating symptoms like pain, stress, anxiety and an improvement in the quality of life is observed. This review article focuses on the structure and basics of mindful meditation and the mechanisms of mindfulness and its positive effects on various diseases like lichen planus, urticaria, psoriasis, eczema, myofacial pain dysfunction syndrome, to name a few. There are various arenas within the discipline of oral and maxillofacial medicine where mindfulness-based techniques can be explored for its effectiveness in combating psychosomatic conditions. The article highlights the importance of holistic approach in treating diseases in which mindfulness meditation techniques play an important role.
Polish Court Ruling Classification Using Deep Neural Networks

In this work, the problem of classifying Polish court rulings based on their text is presented. We use natural language processing methods and classifiers based on convolutional and recurrent neural networks. We prepared a dataset of 144,784 authentic, anonymized Polish court rulings. We analyze various general language embedding matrices and multiple neural network architectures with different parameters. Results show that such models can classify documents with very high accuracy (>99%). We also include an analysis of wrongly predicted examples. Performance analysis shows that our method is fast and could be used in practice on typical server hardware with 2 Processors (Central Processing Units, CPUs) or with a CPU and a Graphics processing unit (GPU).
A Joint-Parameter Modeling Based Radar Emitter Identification Method

To deal with the problem of emitter identification caused by using complex operations used by hostile radars,a new identification algorithm based on joint-parameter modeling(JPM) is proposed in this paper.This algorithm can model the emitters in both pulse-level and statistical parameter level,then the model of joint-parameters is used for identification by constructing different identification methods for different models of the emitters.The kernel of this algorithm is the idea of JPM.A number of simulations are presented to demonstrate the modeling capability and identification capability of the JPM algorithm.Simulation results show that the proposed algorithm can model and identify the complex radar emitters correctly.
Association Between Type 2 Diabetes Mellitus and TCF7L2 And FTO Gene Variants Among Upper Egyptian Population

Background: Type 2 diabetes mellitus (T2DM) is a metabolic disorder caused by a complex interaction of genetic and environmental variables. T2DM is associated with transcription factor 7-like 2 (TCF7L2) and fat mass and obesityassociated (FTO) genetic polymorphism. Objectives: The goal of this study was to examine the common genetic risk factors of T2DM and related metabolic traits in Upper Egyptian population, in attempt to understand the genetic structure of T2DM in the Egyptian community. Methods and Materials: This case control study included 250 participants, 124 T2DM patients and 126 non-diabetics. Using mutagenically separated polymerase chain reaction (MS-PCR), genotyping of single nucleotide polymorphisms (SNP) rs7903146 of TCF7L2 and rs17817449 of FTO genes was carried out. Results: T allele of TCF7L2 variant rs7903146 confers a risk for T2DM (allelic OR=1.97, 95% CI: (1.34 to 2.88) p =<0.001). The minor G allele of FTO rs17817449 polymorphism was significantly higher in diabetics than controls (allelic OR=1.87, 95% CI=1.30 to 2.68, p<0.001). Genotype risk was evident under both recessive and dominant modes of inheritance (OR=3.18, CI (1.35-7.45), P =0.008, OR= 2.04, CI (1.23-3.38), p=0.006) for TCF7L2 and (OR= 2.55, CI (1.28 -5.09), p=0.008 and OR= 2.14, CI (1.25-3.63), p= 0.005) for FTO respectively Conclusion: TCF7L2 rs7903146 and FTO rs17817449 variant conferred risk for T2DM in Upper Egyptian population. The study noted the interaction between certain biological and environmental risk factors including BMI, age, and sex and the conferred genetic risk.
Oral Hypoglycemic Drugs Versus Insulin for the Management of Gestational Diabetes

Introduction: Gestational diabetes mellitus (GDM) is defined as any degree of glucose intolerance with onset or first recognition during pregnancy. Aim of the work: The aim of this study is to compare the efficacy of metformin with that of insulin in treatment of gestational diabetes mellitus. Patients and Methods: This two armed clinical trial was conducted prospectively on 100 pregnant women on regular antenatal care in the Diabetic Clinic of Minia Maternity Hospital during the period from January 2016 to September 2017. Results: This study included 95 pregnant women having GDM, 47 of them were treated with metformin, and the remaining number (48) were treated with insulin. Conclusion: Approximately 80% of women with GDM could be successfully and safely treated with metformin when diet therapy and exercise fail to reduce blood glucose values sufficiently.
Effectiveness of Silver Nanoparticles Botanically and Chemically Synthesized as well as Chitosan against Root-Knot Nematode Meloidogyne javanica in Vitro

The bioassay of some Silver nanoparticles AgNP synthesized botanically against Meloidogyne javanica J2. was conducted. All materials were prepared and evaluated at the concentrations of 100, 50, 25 and 12. 5μl/50 ml of nematode suspension. Mortalities% of M. javanica J2 were recorded after 96 hrs. The obtained data explained the increasing of Meloidogyne javanica J2 with the increasing of the material concentrations. AgNP prepared by oleander extract gave mortality of M. javanica J2 ranged between 37.1and 93.25% with the low and high concentrations. The LC50 was 15. 31μl/50 ml. Nanoparticles of silver by chamomile cause 34.30 and 91.33% mortality of 2 nematode juvenile with the low and high concentrations. The LC50 was 18. 72μl/50 ml. The Ag NP synthesized by thyme cause 14.3 and 91.0% mortality of M. javanica J2 with the low and high concentrations, respectively. LC50 was 37. 71μl/50 ml. The formulation of AgNP by ginger gave mortality of 52.0 and 92.0%. LC50 was 11.11. Silver nanoparticles formulated by jojoba surpassed other botanical formulation causing 59.55 and 95.84% mortality with the low and high concentrations, respectively and the LC50 was 10. 24μl/50ml. Chemical preparation of AgNP cause mortality of 40.8 and 82.0% at low and high concentrations. The LC50 was 18.88. The effectiveness of chitosan at the low molecular weight at the concentrations of 100, 50, 25 and 12. 5μl/50ml was tested revealing that at low and high concentrations the mortality ranged between 72.34 and 96.8 %, respectively. The estimated LC50 was 5. 16μl/50 ml. These results explain the superiority of chitosan over other materials.
A hybrid deep learning approach by integrating extreme gradient boosting‐long short‐term memory with generalized autoregressive conditional heteroscedasticity family models for natural gas load volatility prediction

Natural gas load forecasting provides decision‐making support for natural gas dispatch and management, pipeline network construction, pricing, and sustainable energy development. To explain the uncertainty and volatility in natural gas load forecasting, this study predicts the natural gas load volatility. As the natural gas load volatility has the time‐series features, along with long‐term memory, volatility aggregation, asymmetry, and nonnormality, this study proposes a natural gas load volatility prediction model by combining generalized autoregressive conditional heteroscedasticity (GARCH) family models, XGBoost algorithm, and long short‐term memory (LSTM) network. The model first takes the GARCH family models parameters of sliding estimation and meteorological factors as the influencing factors of volatility, and then it screens these influencing factors through the extreme gradient boosting (XGBoost) algorithm. Finally, the selected important features are input into the LSTM network to predict the volatility, and the 90% confidence interval of the volatility is calculated. Compared with a variety of single and combined models, the model proposed in this study has an average reduction of 45.404% in the evaluation index of mean squared error. The experimental results show that the model proposed in this study has a good performance and accuracy in predicting the volatility of natural gas load.
Insight into what they cite: a citation analysis of publications at the School of Business, Economics and Law at the University of Gothenburg

Abstract The purpose of this citation analysis is to understand what kind of publications are cited by scholars at the School of Business, Economics and Law at the University of Gothenburg. The study uses publication data from 2015 to 2018, and analyses the school’s four departments and their research sections. Four questions are examined: type of documents cited, most-cited journals, age of cited materials, and to what extent the library provides access to these materials. The analysis seeks to provide a better understanding of the similarities and differences across citation cultures, to respond to faculty research needs and to facilitate collection management decisions.
Proactively Invalidating Dead Blocks to Enable Fast Writes in STT-MRAM Caches

Spin-Transfer Torque Magnetic Random Access Memory (STT-MRAM) is a promising emerging memory technology for on-chip caches. It has a low read access time and low leakage power. Unfortunately, however, STT-MRAM suffers from its long write latency and high write energy consumption. This paper proposes a cache management technique called Proactive Invalidation (PROI) that proactively invalidates dead blocks in advance to enable fast writes in the STT-MRAM caches. Experimental evaluation shows that the proposed technique improves performance by 14% on average compared to the baseline STT-MRAM cache. This paper also proposes two optimization techniques called Proactive Invalidation-aware Data Encoding (PIDE) and Narrowness-aware Partial Write (NPW) to minimize the energy overheads of Proactive Invalidation. Experimental results demonstrate that the total energy consumption of the STT-MRAM cache with PROI is only 1.8% higher than the baseline when PROI is applied with PIDE and NPW.
Impact of Fault Ride-through Methods on Wind Power Generators in a VSC-HVDC System

Voltage source converter based high voltage direct current(VSC-HVDC)system is a relatively good choice for the grid integration of large-scale wind farms.When faults occur in the AC grid,the fault ride-through(FRT)controller of wind power generators can maintain the stability of the system.However,the controller will have impact on the wind power generators performance.To study on the FRT problem for wind power generators in a VSC-HVDC system,this paper develops a simulation model of the two-terminal VSC-HVDC system including detailed models of wind farms with conventional asynchronous generators and doubly-fed induction generators(DFIGs)using PSCAD/EMTDC.Two typical FRT methods,i.e.,frequency increase method and voltage reduction method are verified.Furthermore,the characteristics of different wind power generators with different FRT methods are studied.The typical impact of FRT methods on the wind power generators in a VSC-HVDC system is obtained.The conclusions can provide a reliable reference for choosing appropriate FRT methods for different wind power generators integrated into a VSC-HVDC system.
Combined Effect of Moringa (Moringa oleifera) Water Extracts and Vacuum Packaging on the Quality and Lipid Oxidation of the Sun-Dried Punti (Puntius sophore) During Storage

1 Department of Fisheries Technology, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur 1706, Bangladesh 2 Department of Food Production and Environmental Management, Faculty of Agriculture, Iwate University, 3-18-8 Ueda, Morioka, Japan 3 Sanriku Fisheries Research Center, Iwate University, Heta 3-75-1, Kamaishi 026-0001, Japan 4 Faculty of Science and Engineering, Iwate University, Ueda 4-3-5, Morioka 020-8551, Japan
EFFECT OF LATE-SEASON TREATMENTS ON THE POPULATION OF DIAPAUSING PINK BOLLWORM LARVAE .

The effect of late-season spraying by the conventional insecticide (chlorpyrifos) and the mineral oil (KZ oil), before and after harvest of seed cotton, on the population of pink bollworm larvae entering diapause was studied during 2004 and 2005 cotton seasons at the farm of Sakha Agricultural Research Station, Kafr El-Sheikh Governorate. The data revealed that the highest average reduction percentage in pink bollworm diapausing larvae during the two experimental seasons was 64.09% for the treatment of one insecticidal spray one week before harvest followed by another spray one week after harvest. The rest treatments could be arranged descendingly as follows: one spray of the insecticide before harvest followed by one spray of the oil after harvest (57.53%), one spray of the insecticide after harvest (47.32%). One spray of the insecticide before harvest (43.72%), and one spray of the oil after harvest (28.7%) average reduction on diapausing pink bollworm larval population.
Fragments of rDNA Genes Scattered over the Human Genome Are Targets of Small RNAs

Small noncoding RNAs of different origins and classes play several roles in the regulation of gene expression. Here, we show that diverged and rearranged fragments of rDNA units are scattered throughout the human genome and that endogenous small noncoding RNAs are processed by the Microprocessor complex from specific regions of ribosomal RNAs shaping hairpins. These small RNAs correspond to particular sites inside the fragments of rDNA that mostly reside in intergenic regions or the introns of about 1500 genes. The targets of these small ribosomal RNAs (srRNAs) are characterized by a set of epigenetic marks, binding sites of Pol II, RAD21, CBP, and P300, DNase I hypersensitive sites, and by enrichment or depletion of active histone marks. In HEK293T cells, genes that are targeted by srRNAs (srRNA target genes) are involved in differentiation and development. srRNA target genes are enriched with more actively transcribed genes. Our data suggest that remnants of rDNA sequences and srRNAs may be involved in the upregulation or downregulation of a specific set of genes in human cells. These results have implications for diverse fields, including epigenetics and gene therapy.
Infrared broadband nonlinear optical limiting technology based on stimulated Brillouin scattering in As2Se3 fiber

Jian Huang (黄 剑), Yuangang Lu (路元刚), Zhengnan Wu (吴政南), Youwen Xie (谢有文), Chongjun He (赫崇君), and Junfeng Wu (武俊峰) 1 Key Laboratory of Space Photoelectric Detection and Perception of Ministry of Industry and Information Technology, College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China 2 College of Science, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Impact of Rearing Strategies on the Metabolizable Energy and SID Lysine Partitioning in Pigs Growing from 90 to 200 kg in Body Weight

Simple Summary The nutritional recommendations for pigs largely focus on pigs with lean genotypes fed ad libitum until reaching up to 140 kg in body weight (BW). Under different rearing conditions, it is still unclear whether existing recommendations apply to pigs that weigh more than 140 kg in BW, especially in heavy pig production systems. In the current study, pigs growing from 90 to 200 kg in BW were raised with different feeding strategies. We observed that energy restriction had a negligible effect on pigs’ estimated metabolizable energy requirements at heavier BW under different feeding conditions. Under energy and protein restrictions, a value of 0.73 could be assumed as the maximum marginal efficiency of standardized ileal digestible lysine (SID lysine) utilization for protein deposition irrespective of BW, which corresponds to 9.8 g of SID lysine per 100 g of protein deposition as a minimum requirement. Abstract The current nutrient recommendations focus on pigs fed ad libitum up to 140 kg in body weight (BW). It remains unclear whether this applies to pigs weighing above 140 kg in BW under different rearing conditions. This study aimed to estimate protein (Pd) and lipid (Ld) depositions and the metabolizable energy (ME), standardized ileal digestible lysine (SID lysine) requirement and partitioning in 224 C21 Goland pigs (90–200 kg in BW). The control pigs (C) received diets limiting ME up to 170 kg in slaughter weight (SW) at 9 months of age (SA); older (OA) pigs had restricted diets limiting ME and SID lysine up to 170 kg in SW at >9 months SA; younger (YA) pigs were fed nonlimited amounts of ME and SID lysine up to 170 kg in SW at <9 months SA; and greater weight (GW) pigs were fed as the YA group, with 9 months SA at >170 kg in SW. The estimated MEm averaged 1.03 MJ/kg0.60. An 11% increase in MEm was observed in OA pigs compared to the controls. Energy restriction had negligible effects on the estimated MEm. The marginal efficiency of SID lysine utilization for Pd averaged 0.725, corresponding to a SID lysine requirement of 9.8 g/100 g Pd.
A Dynamic Task Allocation Algorithm for Heterogeneous UUV Swarms

Aiming at the task allocation problem of heterogeneous unmanned underwater vehicle (UUV) swarms, this paper proposes a dynamic extended consensus-based bundle algorithm (DECBBA) based on consistency algorithm. Our algorithm considers the multi-UUV task allocation problem that each UUV can individually complete multiple tasks, constructs a “UUV-task” matching matrix and designs new marginal utility, reward and cost functions for the influence of time, path and UUV voyage. Furthermore, in view of the unfavorable factors that restrict the underwater acoustic communication range between UUVs in the real environment, our algorithm complete dynamic task allocation of UUV swarms with optimization in load balance indicator by the update of the UUV individual and the task completion status in the discrete time stage. The performance indicators (including global utility and task completion rate) of the dynamic task allocation algorithm in the scenario with communication constraints can be well close to the static algorithm in the ideal scenario without communication constraints. The simulation experiment results show that the algorithm proposed in this paper can quickly and efficiently obtain the dynamic and conflict-free task allocation assignment of UUV swarms with great performance.
Histopathology of Nitrate Toxicity on Hepatopancreas of the Terrestrial Isopod, Porcellio laevis

The intensive addition of nitrogenous fertilizers to soil leads to the accumulation of soil nitrate that in turn affects soil fauna. The hepatopancreas is the major metabolic organ in crustaceans. It has an important function in the assimilation of nutrients and structurally includes two types of cells (B and S). This study was designed to investigate the negative effects of nitrate on the hepatopancreas of the terrestrial isopod Porcellio laevis. The isopod was subjected to different concentrations; 30, 60 and 90 ppm of NaNO3 in food diet to study the histopathological changes on the hepatopancreas. The study revealed that the hepatopancreatic epithelium of the exposed isopod displayed numerous pathological changes varied from destruction of the apical cell membrane with the appearance of deeply stained cytoplasm to complete disintegration of B cells especially in 90 ppm treated group. A trend toward histochemical changes of protein, neutral mucopolysaccharides, acidic and sulphated mucopolysaccharides in hepatopancreatic epithelium were observed. Quantifying these changes in the hepatopancreas were assessed, using image analysis, it indicated the presence of doserelated changes in the area of hepatopancreatic cells, nuclei and lumen. It could be concluded that the recovery process in P. laevis from nitrate toxicity is a slow one.
Conceptual Framework for Future WSN-MAC Protocol to Achieve Energy Consumption Enhancement

Nowadays, the rapid deployment of Wireless Sensor Networks (WSNs) and the integration of Internet of Things (IoT) technology has enabled their application to grow in various industrial fields in our country. Various factors influence the success of WSN development, particularly improvements in Medium Access Control (MAC) protocols, for which WSNs-IoT are deemed vital. Several aspects should be considered, such as energy consumption reduction, performance, scalability for a large deployment of nodes, and clustering intelligence. However, many protocols address this aspect in a constrained view of handling the medium access. This work presents a state-of-the-art review of recently proposed WSN MAC protocols. Different methods and approaches are proposed to enhance the main performance factors. Various performance issue factors are considered to be the main attribute that the MAC protocol should support. A comparison table is given to provide further details about using these approaches and algorithms to improve performance issues, such as network throughput, end-to-end delay, and packet drop, translated into energy consumption.