Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Dynamic Characteristic Parameter of Air Spring

Based on the theories of thermodynamics and hydrodynamics, a physical model for air springs is established, its uniform mathematical expression is deduced, and the method of determining air spring parameters is put forward. And the factors affecting the dynamics of air springs are analyzed. The results show that shape of the air cell, properties of the material, volume of the appended gas chamber and diameter of the throttle hole are main factors affecting the dynamics of air springs.
Pattern synthesis of linear antenna array based on improved quantum particle swarm optimization

An improved quantum particle swarm optimization(QPSO) based on reverse learning is presented in this paper,which adopts reverse learning to increase the diversity of the population so as to enhance searching efficiency greatly and to avoid premature convergence of the algorithm effectively.Pattern synthesis of linear antennas array is actualized successfully using this improved algorithm,and the simulation results of three examples show that the improved QPSO is an effective method in solving such problems.
UvA-DARE ( Digital Academic Repository ) To employability and beyond Sustainable careers within contextual boundaries

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The Effect of Language Recognition in Music on Short-Term Memory Recall and Physiological Stress Response

Adolescent and young adult students frequently listen to music while studying. While there is extensive research on the effects of musi​c on memory, there is little evidence regarding whether style of music or language recognition is associated with the physiological mechanisms driving memory recall tasks. The objective of this study was to investigate the effects of language recognition in music on short-term memory performance and physiological variables. Participants in the study completed a word search while listening to a song in English, a song performed in native South African dialects, or no music at​ all. During the word search, heart rate, respiration rate, and skin conductance were recorded in order to assess the physiological response of the participant and their stress response. Immediately after, the participants was asked to recall as many words as they could from the word search as a way to measure short-term memory​. Results showed that listening to music in a non-native language has no effect on short-term memory performance or the physiological stress response of the participants when compared to the other two conditions. This suggests that foreign music may not act as a physiological stressor and distraction during a cognitive task. Instead, foreign music may function more as white noise. Introduction In preparation for exams, students typically engage with material while listening to music for a variety of reasons, such as aiding in focus, blocking out distractions, or for enjoyment, while building the information into their short-term memory (STM). However, it is likely that they have never considered whether listening to music, as well as the type of music they listen to, benefits or hinders their recall ability. The efficacy of listening to music on memory recall has long been debated in the literature. While some studies found no considerable effect of background music on STM (Jan​cke and Sandmann, 2010, Sandberg and Harmon, 2003), others reported negative impacts on performance when upbeat music with lyrics, such as rap, was played (Bugter and Carden, 2012, Salame and Baddeley, 1989). In addition, a study that used classical or instrumental music found that the Mozart Effect may occur due to more passive background music, which describes the improvement of STM while performing a mental task (Lehmann, 2017). While several aspects of music, such as tempo, genre, and the presence of lyrics have been repeatedly investigated, few studies have investigated the effects of music in an person’s non-native language on STM or physiological response. Listening to music in a person’s non-native language is more relevant now than it was in the past as iconic songs in non-English languages, such as Despacito by Luis Fonsi and Daddy Yankee, find their way onto many students’ study playlists before exams.
In-Vitro Evaluation of Some Traditional Medicinal Plants on Calcium Oxalate Urolithiasis

The prevalence of urolithiasis in Middle East countries is predominantly high. Traditional medicinal plants play a role in the prevention and management of urolithiasis. The effect of Petroselinum crispum, rind of Citrus sinensis L. , rind of Citrus limon L. , Ammi visnaga (L.) LAM. , Tamarindus indica L. , Nigella sativa L. , Cymbopogon proximus Hochst. ex A. Rich. , Hibiscus sabdariffa L. , Hordeum vulgare L. , and Cymbopogon schoenanthus (L.) Spreng. on calcium oxalate crystallization was investigated in-vitro. The antispasmodic activity on acetylcholine-induced contraction in rat ileum was also screened ex-vivo. A significant reduction in the mean diagonal of calcium oxalate crystals was observed for P. crispum, C. proximus, N. sativa, and C. limon (4.41 mm, 4.71, 5.44, and 5.67 mm, respectively) compared to the negative control (12.19 mm). H. sabdariffa exhibited antinucleation effect however, P. crispum showed a marked inhibition of calcium oxalate aggregation at 10 mg/mL after 60 min compared to the negative control. A remarkable ex-vivo antispasmodic activity was observed for C. proximus, C. schoenanthus, and A. visnaga extracts. Our results provide scientific evidence for the traditional use of the studied plant-derived products as potential therapies for calcium oxalate urolithiasis.
Information Transmission among Multiple Investors: A Micro Perspective Revealed by Motifs

We build the shareholder co-holding network (SCN) based on common shareholding data from 2007 to 2017. Considering the node attributes and the link weights, we reveal the basic structure and dynamic evolution of the SCN from two aspects: motif identification and motif evolution. Research on motif identification shows that although closed motifs have a low proportion, they are statistically significant. Further, research on the motif evolution shows that all motif structures have a higher tendency to disappear. The motifs containing financial investment company shareholders tend to disappear, while the motifs containing general corporate shareholders tend to remain unchanged during the evolution process. In short, we have developed the local motif structure of the SCN, which helps understand how information is transmitted among multiple investors.
Neural Precomputed Radiance Transfer

Recent advances in neural rendering indicate immense promise for architectures that learn light transport, allowing efficient rendering of global illumination effects once such methods are trained. The training phase of these methods can be seen as a form of pre‐computation, which has a long standing history in Computer Graphics. In particular, Pre‐computed Radiance Transfer (PRT) achieves real‐time rendering by freezing some variables of the scene (geometry, materials) and encoding the distribution of others, allowing interactive rendering at runtime. We adopt the same configuration as PRT – global illumination of static scenes under dynamic environment lighting – and investigate different neural network architectures, inspired by the design principles and theoretical analysis of PRT. We introduce four different architectures, and show that those based on knowledge of light transport models and PRT‐inspired principles improve the quality of global illumination predictions at equal training time and network size, without the need for high‐end ray‐tracing hardware.
An Exploration of Agricultural Lands Devoted to Corn-Based Ethanol Production

ABSTRACT Debate has surrounded corn-based ethanol since its introduction as a biofuel. This debate centers on whether corn-based ethanol plays a positive or negative role with regard to energy consumption, hunger and malnutrition, environmental degradation, and economic impacts. This study aims to improve the understanding of the changes in the amount of land in the United States devoted to corn production for corn-based ethanol. Through geographical analysis using data from the U.S. Department of Agriculture National Agricultural Statistics Service, this research explores (1) the change, from 2007 to 2012, in total number of acres harvested in each county of the United States; (2) the change, from 2007 to 2012, in total number of corn acres harvested in each county of the United States; and (3) significant relationships among total acres harvested and total corn acres harvested (2007–2012) by states in the United States. This analysis of corn production can aid in a further understanding of the land allocation increases in U.S. counties and states due to rising corn-based ethanol, livestock, and human population demands. The analysis provides potential awareness to the stressors corn production has on U.S. lands and the cultivation of other crops within county and state-level regions.
Solitary Gastric Metastasis of Breast İnvasive Lobular Carcinoma

A 52-year-old female patient with solitary gastric metastasis from breast invasive lobular cancer without any other organ involvement is presented in this study. Solitary gastric metastasis of breast cancers is very rare. It can be diagnosed incidentally by endoscopic biopsy and immuno-histo-chemical analysis. Symptoms and clinical findings are not different from primary gastric cancers. Prognosis of solitary gastric metastasis is good after surgical treatment according to patients with systemic metastasis .
The Study of Variation of Metabolites by Sleep Deficiency, and Intervention Possibility of Aerobic Exercise

The purpose of this study is to determine the difference in sleep-related factors and metabolites between normal sleep (NS) and sleep deficiency (SD) and to analyze the variations in metabolites according to the intensity of aerobic exercise under SD conditions. This study was conducted on 32 healthy male university students. Participants experienced both NS (8 h of sleep per night for 3 consecutive days) and SD (4 h of sleep per night for 3 consecutive days). After the SD period, the participants underwent treatment for 30 min by the assigned group [sleep supplement after SD (SSD), low-intensity aerobic exercise after SD (LES), moderate-intensity aerobic exercise after SD (MES), high-intensity aerobic exercise after SD (HES)]. For analysis, sleep-related factors were measured, and metabolites were analyzed by untargeted metabolite analysis using gas chromatography-time-of-flight mass spectrometry. As a result, SD showed that total sleep time (TST), duration of rapid eye movement (REM), duration of light sleep, and duration of deep sleep were significantly decreased compared to NS, whereas the Pittsburgh sleep quality index (PSQI), Epworth sleepiness scale (ESS), and visual analogue scale (VAS) were significantly increased compared to NS. The difference in metabolites between NS and SD showed that there were significant changes in the seven metabolites. There were 18 metabolites that changed according to the treatment groups in SD conditions. In summary, SD can exacerbate sleep quality, induce daytime sleepiness, increase fatigue, and increase metabolites that cause insulin resistance. Aerobic exercise under SD conditions can reduce metabolites that induce insulin resistance and increase the metabolites that help relieve depression caused by SD. However, HES has a negative effect, which increases fatigue, whereas LES has no negative effect. Thus, this study suggests that LES is the most appropriate exercise method under SD conditions.
Implementation of Wireless Sensor Network Node with Self Localization

Introduced a wireless sensor network node with self localization.It includes a dsPIC6014A microcontroller from Micro Chip Inc.,512 KB SRAM,a 2.4 GHz RF transceiver,a buzzer,a microphone and a power manager unit.The nodes' distances can be measured by TDOA(time difference of arrival) between RF(radio frequency) and acoustic signals.The nodes' location can be obtained from multi-nodes' distances.The power manager unit and the node's sleep period are controlled by an RTC(real time clock) chip.Test results show that the node can measure the distance longer than 25 meters with error 3%,the power supply in the sleep mode is less than 12 μW.
Land-Cover Change Detection for SAR Images Based on Biobjective Fuzzy Local Information Clustering Method With Decomposition

The existence of a speckle noise significantly affects the accuracy of land-cover change detection results for synthetic aperture radar (SAR) images. This letter proposes a biobjective fuzzy local information clustering method with decomposition (BIFLICM/D) to address this problem. SAR images change detection is described as a biobjective fuzzy local information clustering problem from the aspects of preserving image details and removing noise. To improve the ability to extract the original information detail, the log-mean ratio method is used to generate a first difference image in BIFLICM/D. The second difference image is achieved by combining the homomorphic filtering and saliency detection, which effectively removes the speckle noise. Fuzzy clustering objective functions are then constructed for the two difference images to recognize the changed and unchanged pixels under different requirements. A new fuzzy membership degree-updating method is adopted to optimize the two objective functions, which can balance the influences of the two objectives and improve the robustness of the proposed method. The experimental result demonstrates that the proposed method is more effective and superior to the comparison algorithms.
Knowledge and Practices of Bush Meat Consumption among Indigenous People in Belum Forest, Malaysia: An Analytical Cross-Sectional Study

Introduction Orang Asli are the indigenous people of Peninsular Malaysia, and theyconsume bush meat as a primary source of protein. Frequent contact with wildlife throughbush meat hunting for consumption and trade leaves people at risk of zoonotic infection. Thisstudy aims to assess the knowledge and practices of the Jahai tribe on the consumption andhandling of bush meat. Methods An analytical cross-sectional study was conducted amongJahai adults aged 18 years and above residing in Belum Forest. Due to their semi-nomadicnature of living, convenience sampling was used to select the participants, who wereapproached at their homes. A questionnaire was used to assess the knowledge and practicesrelating to bush meat and hygiene. Results The majority of the participants ate bush meatregularly but had poor knowledge about disease transmission. There was a significantassociation between sex and occupation with knowledge. A significant association was foundbetween knowledge on disease transmission with the consumption of bush meat. There wasno association between practice on cooking, hunting activities and handling carcasses andhand hygiene practice with the consumption of bush meat. Conclusion Most Jahai lackedsufficient knowledge on disease transmission and have poor practices regarding the handlingof bush meat and its carcasses, which might put them at a risk of infection. The findings canbe used as baseline data to develop effective strategies such as cultural-sensitive educationalprograms, to deepen the understanding of the community on the risk and prevention ofdeveloping diseases.
Probiotics-Containing Mucoadhesive Gel for Targeting the Dysbiosis Associated with Periodontal Diseases

Objective Periodontitis is a common disorder that leads to the loss of both tooth and personal well-being, contributing to worsen the risk for metabolic and cardiovascular diseases. Recently, probiotics, characterized by rapid oral dispersion, have been topically used. Here, we present data of a mucoadhesive gel containing probiotics, capable of ensuring a slow release of bacteria to prevent and treat periodontitis. Methods An original mucoadhesive gel (AL0005) that is anhydrous and of food grade, loaded with the blend of lactobacilli and plants' dry extracts, has been assayed. Results The release kinetics of the bacterial mixture in different experimental models in vitro, including simulated saliva or physiological solutions, showed a significant and stable release for 5–8 hours. In one in vivo study of a mouse model of periodontitis, a locally applied mucoadhesive gel enriched with probiotic strains improved significantly the tissue pathology when compared with vehicle-exposed mice. Conclusions Together, the results suggest that this mucoadhesive gel can be useful in the normalization of the gum bacterial flora and improvement of the tissue pathology of gum disorders.
Recognition of ATT Triplex and DNA:RNA Hybrid Structures by Benzothiazole Ligands

Interactions of an array of nucleic acid structures with a small series of benzothiazole ligands (bis-benzothiazolyl-pyridines—group 1, 2-thienyl/2-benzothienyl-substituted 6-(2-imidazolinyl)benzothiazoles—group 2, and three 2-aryl/heteroaryl-substituted 6-(2-imidazolinyl)benzothiazoles—group 3) were screened by competition dialysis. Due to the involvement of DNA:RNA hybrids and triplex helices in many essential functions in cells, this study’s main aim is to detect benzothiazole-based moieties with selective binding or spectroscopic response to these nucleic structures compared to regular (non-hybrid) DNA and RNA duplexes and single-stranded forms. Complexes of nucleic acids and benzothiazoles, selected by this method, were characterized by UV/Vis, fluorescence and circular dichroism (CD) spectroscopy, isothermal titration calorimetry, and molecular modeling. Two compounds (1 and 6) from groups 1 and 2 demonstrated the highest affinities against 13 nucleic acid structures, while another compound (5) from group 2, despite lower affinities, yielded higher selectivity among studied compounds. Compound 1 significantly inhibited RNase H. Compound 6 could differentiate between B- (binding of 6 dimers inside minor groove) and A-type (intercalation) helices by an induced CD signal, while both 5 and 6 selectively stabilized ATT triplex in regard to AT duplex. Compound 3 induced strong condensation-like changes in CD spectra of AT-rich DNA sequences.
Genetic landscape of pancreatic cancer: a narrative review.

BACKGROUND AND OBJECTIVE Pancreatic cancer is an aggressive disease with an impaired survival despite improvements in clinical management. Thus, understanding disease biology is of vital importance in order to overcome therapeutic challenges and achieve better prognosis. The purpose of this review is to outline the genetic landscape of pancreatic cancer along with its clinical implications. METHODS We reviewed existing literature using electronic databases to outline the genetic landscape in pancreatic cancer. KEY CONTENT AND FINDINGS This review mainly contains information on the genetic background of pancreatic cancer, mainly KRAS, CDKN2A, TP53 and SMAD4, with emphasis on the importance of understanding disease biology. CONCLUSIONS The genetic aspects of pancreatic cancer have been well described especially with the introduction of next generation sequencing techniques. Future studies focusing on translation of these alterations in clinical application might pave the way for personalized surveillance and therapy.
Does Intellectual Capital Affect Financial Leverage of Chinese Agricultural Companies? Exploring the Role of Firm Profitability

The objective of this paper is to examine the relationship between intellectual capital (IC) and firms’ financial leverage by exploring whether firm profitability mediates this relationship, using a dataset of Chinese agricultural listed companies during the period of 2014–2020. Financial leverage is measured by the debt-to-asset ratio, and IC is measured via the modified value-added intellectual coefficient (MVAIC) model. The results reveal that financial leverage is lower in firms with higher levels of IC, and IC positively affects firm profitability. In addition, firm profitability partially mediates the relationship between IC and financial leverage. When MVAIC is disaggregated into its four components, firm profitability has a partially mediating effect on the relationship between physical and human capitals and financial leverage. This paper might provide corporate managers with a clear understanding of IC’s impact on firm indebtedness.
Modeling dynamic land use changes in the eastern portion of the hexi corridor, China by cnn-gru hybrid model

ABSTRACT Deep learning models have been extensively employed to simulate dynamic Land Use Changes (LUC) at the regional level. However, existing studies were found to be limited by the inadequate extraction of Spatiotemporal Neighborhood Features (SNF) and ignored obvious Long-Term Dependence (LTD) in time series data, which low simulation accuracies. Consequently, it remains to be explored whether deep learning should be employed to initially extract spatial or temporal features in LUC simulations to achieve better results. We propose here a deep learning model of a Convolutional Neural Network – Gated Recurrent Unit (CNN-GRU), coupled with SNF learning to simulate LUC. Land use data for the Eastern Portion of the Hexi Corridor (EPHC) (2000–2020) were utilized to verify the effectiveness of our model, which was compared with four other models (GRU, CNN, CNN-LSTM, and GRU-CNN). We found that CNN-GRU the highest simulation accuracy (OA = 0.9346), whereas the kappa coefficient increased by 1.22%-4.57%. These results indicated that: (1) EPHC urbanization showed a trend of contraction, rapid expansion, and slow growth. (2) The CNN-GRU model effectively extracted SNF and LTD, which improved the accuracy of the simulation. (3) An enhanced effect could be achieved when spatial features were initially extracted during the SNF deep learning extraction process. (4) Variable neighborhood unit sizes influenced the simulation results, where a 3 × 3 window was most suitable for the study area.