Miracle-dz/UniFAR-FTUs huggingface dataset:
Anatomical Study of the Infrapatellar Branch of the Saphenous Nerve with Applications to Knee Surgery

The infrapatellar branch of the saphenous nerve is a cutaneous nerve that innervates the area surrounding the patella and contributes to the peripatellar plexus. This nerve is target to iatrogenic injuries during a great deal of knee pro cedur s, such as tendon harvesting, total knee arthroplasty and medial arthroscopic approaches to the knee. Lesion to this nerve can produce sen so ial loss at its innervation territory. The study conducted herein aims to observe the anatomical aspects of the infrapatellar branch in cad veric specimens. The infrapatellar branch of the saphenous nerve of 40 male cadavers was dissected with the purpose of identifying th e number of branches, its relation with the patella, tibial tuberosity and sartorius muscle. The nerve was dissected and several mea urements were performed with the aid of a digital caliper. Statistical analysis was performed with the MedCalc 16.1 software. The infrap atellar branch of the saphenous nerve was present in 100 % of the sample. Its mean distance from its origin to its branching point was 16.35±6.48 mm on the right and 21.94 ± . 31 mm on the left, with statistically significant differences (p < 0.05). A relatively safe zone for surgery was observed on the superior and medial aspect of the patella, which received less branches.
THE DETERMINANTS OF ENTREPRENEURSHIP IN DEVELOPING COUNTRIES – A CASE STUDY OF ASIA

The study is aimed to examine the influence of different determinants on entrepreneurship in some developing Asian countries. In this dissertation, entrepreneurship determinants are represented by a set of independent variables including Economic development, Population Growth Unemployment, Macroeconomic volatility, Education level, Financial development Technological development, Tax level, Corruption, Political stability and Cost of doing business. In addition, entrepreneurship, which is dependent variable of this research, is measured New Density entry firm. The sample of this research is collected from 9 Asian developing countries (Afghanistan, India, Indonesia, Kazakhstan, Malaysia, Nepal, Philippines, Tajikistan and Thailand). Collected data are analyzed by implementing OLS regression model. The research results show that the stage of economic development, population growth rate, unemployment rate, financial development, level of political stability are the most influent determinants of entrepreneurship. In the meanwhile, level of education, inflation rate and level of the tax system are found to have negative impact on the level of entrepreneurial activities.
THE EFFECTS OF LARGER FISH AND SIZE GRADING ON GROWTH PERFORMANCE OF WHITE SEA BREAM JUVENILES

This study was conducted to determine the effects of size grading on growth performance of white sea bream ( small (5.6 g) and large (7.5 g) and then four experimental groups were assigned as 100% small group (S100), 25% large + 75% small group (S75), 50% small + 50% large group (S50), and finally 75% small + 25% large group (S25). Twenty fish were stocked into flow through system in three replicates per treatment. commercial feed similar in all experimental groups (P>0.05) (P<0.05) (S25, S50 and S75) (P<0.05). The results have demonstrated that the larger individuals in the present study did not suppress growth of the smallest individuals. The fish in S by the absence of large fish and this was postulated to be due to poor competition for food acquisition in this group. For this reason size grading seems to be unnecessary to improve growth and survival of white sea bream of aro
Investigating the Metabolic and Pathophysiological Ramifications of Elevated Dietary Cholesterol and Macronutrient Manipulation in Guinea Pigs (Cavia porcellus) with Non-alcoholic Fatty Liver Disease (NAFLD)

Evidence from numerous animal and human studies have implicated dietary cholesterol as a lipotoxic mediator in the transition of hepatic steatosis to non-alcoholic steatohepatitis (NASH), a critical event in the progression of nonalcoholic fatty liver disease (NAFLD). Here, we sought to examine the impact of a dietary cholesterol challenge on NAFLD progression in phenotypically normal guinea pigs, an animal that more closely approximates humans in terms of hepatic cholesterol handling and metabolism than other commonly utilized animal models. Young (3-month) male Hartley guinea pigs (n =10/group) were subjected to either a high-cholesterol (H-Chol) diet containing 0.25% dietary cholesterol or a control, 0.04% low-cholesterol (L-Chol) diet for six weeks and evaluated by metabolic and histopathological parameters. Interestingly, H-Chol fed guinea pigs had lower final body weights (p = 0.002) and decreased daily food intake (p < 0.0001) compared to the L-Chol group. Compared to L-Chol controls, H-Chol guinea pigs developed marked hypercholesterolemia (284 vs 48 mg/dL; p = 0.0001) and elevated plasma activity of ALT and AST, which are biochemical indicators of hepatic injury (p < 0.05 for both) while displaying no differences in plasma glucose, non-esterified fatty acid, or triglyceride (TG). Plasma total cholesterol was shown to be correlated with plasma ALT activity (r = .78, p = 0.02) in the H-Chol group only. H-Chol feeding resulted in increased hepatic accumulation of TG (p = 0.002) along with total, free, and esterified cholesterol (p < 0.0001 for all), resulting in modest hepatic steatosis.
Investigating Linguistic and Semantic Features for Turn-Taking Prediction in Open-Domain Human-Computer Conversation

In this paper we address the problem of turn-taking prediction in open-ended communication between humans and dialogue agents. In a non-task-oriented interaction with dialogue agents, user inputs are apt to be grammatically and lexically diverse, and at times quite lengthy, with many pauses; all of this makes it harder for the system to decide when to jump in. As a result recent turn-taking predictors designed for specific tasks or for human-human interactions will scarcely be applicable. In this paper we focus primarily on the predictive potential of linguistic features, including lexical, syntactic and semantic features, as well as timing features, whereas past work has typically placed more emphasis on prosodic features, sometimes supplemented with non-verbal behaviors such as gaze and head movements. The basis for our study is a corpus of 15 “friendly” dialogues between humans and a (Wizard-of-Oz enabled) virtual dialogue agent, annotated for pause times and types. The model of turn-taking obtained by supervised learning predicts turn-taking points with increasing accuracy using only prosodic features, only timing and speech rate features, only lexical and syntactic features, and achieves state-of-the art performance with a mixture-of-experts model combining these features along with a semantic criterion.
Yeast antagonist and microwave treatment control blue mold rots of harvested jujube fruits

In this study, the functions of antagonistic yeast alone or in combination with microwave treatment in controlling blue mold rot of jujube fruit were investigated. Meanwhile, their effects on the quality of the harvested fruits were also detected. Therefore, in vitro and vivo experiments were both adopted for the study. For in vitro test, the growth of Penicillium citrinum was almost completely inhibited (98%) by 2 and 3 min 2450 MHz microwave treatments, respectively. In addition, the population density of the pathogenic bacteria in the surface wounds of fruit was also significantly lower than that of the control in vivo test. The results showed that the microwave treatment reduced disease incidence and lesion diameter of infected wounds from 100% to 36.0% and 1.92 cm to 1.38 cm, respectively. Similarly, the Metschnikowia pulcherrima were capable of reducing incidence from 100% to 45.0% and lesion diameter from 1.92 cm to 1.50 cm, respectively. The disease incidence and lesion diameter were only 21.0% and 1.00 cm, respectively, when treated with the combination of microwave and antagonist yeast. Meanwhile, the incidence of the natural decay on treated fruits was similar to that of the inoculated fruits. Therefore, the results also demonstrated that all the treatments did not influence the quality parameters of Jujube fruit. In short, our research suggested that yeast antagonist in combination with microwave treatment could be an alternative to synthetic fungicides for controlling the postharvest blue mold rot of jujube fruits.
Light intensity effects on some molecular and biochemical characteristics of Dunaliella salina

To gain a better understanding of molecular and biochemical events involved in light intensity adaptations of Dunaliella salina, we studied the expression of phytoen synthase (psy) gene; pigments, carbohydrates, proteins and lipids accumulation under two light intensities. The cells were pre-cultured under 50 μmol photon ms light intensity and then transferred to two different light intensities of 200 and 1000 μmol photon ms. The psy gene expression in high light (1000 μmol photon ms) decreased and remained fairly constant until 48 h however, a more decrease was appeared under the low light (200 μmol photon ms). After 2 weeks cultivation, the high light led to a considerable decrease of Chl a and Chl b contents, and an increase in carotenoids/total chlorophylls and Chl a/Chl b ratios. Total, soluble and non-soluble (starch) carbohydrates; proteins and lipids contents of cells were increased under the high light conditions. The results suggest that D. salina cells can have light intensity dependent adjustments in gene expressions, photosynthesis apparatus function, and structure as well as biochemical cell composition.
Basis Learning Autoencoders for Hybrid Collaborative Filtering in Cold Start Setting

In recent years, most recommender systems rely on collaborative filtering (CF) based on matrix factorization (MF) that can predict unknown ratings by completing a rating matrix. However, this approach cannot be used for the cold start where no rating information is available for a given user or item. To address this problem, we develop a new hybrid CF (HCF) technique incorporating CF with content information. The proposed HCF is based on an auto-encoder (AE) consisting of a nonlinear encoder and a linear decoder. This type of AE is called the basis learning AE (BAE), because it can learn the basis of the row space of a sparse input matrix by its encoder. In the proposed scheme, the input to the BAE is a content augmented rating matrix; the BAE learns the basis of the row space of a given rating matrix, which is a subset of the basis of the content augmented rating matrix, and recovers each row of the rating matrix by a linear combination of the learned basis. Unlike most existing HCF schemes, our model does not incorporate additional content-based objective terms; yet extensive experiments on real-world datasets show that the proposed HCF can significantly advance the state-of-the-art.
Binary Speech Features for Keyword Spotting Tasks

Keyword spotting is a classification task which aims to detect a specific set of spoken words. In general, this type of task runs on a power-constrained device such as a smartphone. One method to reduce the power consumption of a keyword spotting algorithm (typically a neural network) is to reduce the precision of the network weights and activations. In this paper, we propose a new representation of speech features which is more adapted to low-precision networks and compatible with binary/ternary neural networks. The new representation is based on the logMel spectrogram and models the variation of power over time. Tested on a ResNet, this representation produces results nearly as accurate as full-precision MFCCs, which are traditionally used in speech recognition applications.
Assessment of effect of different herbicides on morphological traits of Gladiolus grandiflorus

Floriculture is emerging as a profitable venture due to divergence of farmers towards high value floral crops and utilization of flowers in social and industrial level. Manual weeding is a very tedious and expensive labour practice of weed control that often damages the crop as well. Worldwide different weed control strategies are employed in the crops such as preventive, cultural, mechanical, biological and chemical. However, the chemical control using herbicides is one of the recent practice that is used in modern agriculture. The effectiveness of herbicide is decided by its specificity and mode of action under a soil conditions, its organic matter content, weather conditions and soil moisture prevailing at that particular area. Present study was conducted at Floriculture Research Area, Institute of Horticultural Sciences, University of Agriculture, Faisalabad, Pakistan, during 2011-12 to study the effect of different herbicides on growth and yield of gladiolus plants. Pre emergence and post emergence applications of herbicides improved the growth of Gladiolus plant. Pendimethalin applied at 12ml/litre as pre emergence herbicide significantly increased plant height of white prosperity (100.78cm). [Ali Z, Qadeer A, Ahmad HM, Aziz O, Qasam M, Ali Q. Assessment of effect of different herbicides on morphological traits of Gladiolus grandiflorus. Life Sci J 2015;12(4s):87-93]. (ISSN:1097-8135). http://www.lifesciencesite. com. 12
Early Sepsis Prediction Using Ensemble Learning with Features Extracted from LSTM Recurrent Neural Network

Early prediction of sepsis can help to identify potential risks in time and help take necessary measures to prevent more dangerous situations from occurring. In PhysioNet/Computing in Cardiology Challenge 2019, we integrate Long Short Term Memory (LSTM) recurrent neural network and ensemble learning to achieve early sepsis prediction. Specifically, we tackle the problem of class imbalance and data missing firstly, and then we manually extract features according to the prior knowledge from the medical field. In addition, we regard the prediction of sepsis as a time series prediction problem and pre-train LSTM-based models as feature extractors to obtain the "deep" features on time series that might be related to the onset of sepsis. Manual features and "deep" features are then used to train prediction models under the framework of ensemble learning, including Extreme Gradient Boosting (XGBoost) and Gradient Boosting Decision Tree (GBDT) regressor. The final normalized utility score our team (UCAS_DataMiner) have obtained was 0.313 on full hidden test set.
A STUDY ON THE EFFECT OF USING A KNOWLEDGE MANAGEMENT SYSTEM ON DESIGN EDUCATION

The importance of peer learning in design education has been recognized recently. To facilitate the peer learning among students, a Design Knowledge Management System (DKMS) was constructed. This system provided a web-based platform for students to share their knowledge and perform peer-to-peer recommendation among good works. In addition, an experiment was conducted in different courses within three universities. Students in these courses were asked to submit their homework through this system for the duration of experiments. Their performances of learning were then evaluated by the instructors. Furthermore, after the experiment, a questionnaire survey was conducted to study their
Correlation between miRNA-21 expression and diagnosis , metastasis and prognosis of prostate cancer

Objective: To find out the correlation between miRNA-21 expression and diagnosis, metastasis and prognosis of prostate cancer. Methods: Eighty-eight patients with prostate cancer (62 cases underwent radical prostatectomy), 84 patients with benign prostatic hyperplasia and 80 healthy subjects were enrolled in this study. The relative expression level of miRNA-21 in the blood and its predictive value in diagnosis, metastasis and prognosis of prostate cancer were observed. Results: The expression of miRNA was significantly higher in the prostate cancer group than in the prostatic hyperplasia group and the healthy group (both P < 0.001), but there was no significant difference between the prostatic hyperplasia group and the healthy group. Prostate cancer patients with Gleason score > 7 points had higher relative expression of miRNA than patients with Gleason score ≤ 7 points (P < 0.05). The relative expression of miRNA was the highest in T4 group than in other T staging groups (all P < 0.001), was higher in N1 group than in N0 group, and was higher in M1 group than in M0 group (both P < 0.05). In terms of the risk levels, the relative expression of miRNAs in the low risk group was significantly lower than that in the intermediate risk and high risk groups (both P < 0.001). Conclusion: The relative expression of miRNA-21 in the blood of patients with prostate cancer is increased, and related to the malignant degree and biochemical recurrence of tumors. So, it is a valuable indicator for the diagnosis and prediction of prostate cancer.
WITHIN-SPEAKER PERCEPTION AND PRODUCTION OF DIALECTAL /aɪ/-RAISING

In the Fort Wayne, Indiana area, speakers are beginning to raise /aɪ/ to /ʌɪ/ preceding voiceless consonants, similar to canonical Canadian raising. Under consideration in this work is the relationship between the perceptual salience of this progressing sound change and speakers’ production of the same novel sound. It has been posited that in sound change situations, perception precedes production of novel forms [1, 5]. For the speakers in the current study, however, those who do not yet raise /aɪ/ themselves also do not perceive words with distinctive raising in pre-flap context as consistently as the true raisers. These results indicate that in this situation, individuals in the speech community who are operating within the sound change but not participating in it themselves do not use the raised /aɪ/ at above-chance levels to distinguish otherwise identical words, whereas speakers who do raise use the raised /aɪ/ in perception.
Changing against tone merging trends in community? The case of C. Y. Leung

Compared to the voluminous literature of sound change and variation across speakers and generations, much less is understood about change and variation within individuals across the lifespan. In this paper, we present a study of the Cantonese speech of a public figure, Mr. Chun-ying Leung (1954-), recorded over a span of three decades (1984-2013), which coincides with a period when multiple sound changes were in progress in Hong Kong Cantonese, including the merging of tones. Assisted with automatic segmentation and annotation, 13,389 tokens representing 878 unique characters with unchecked tones were measured for F0. Our results show that instead of merging tones, Leung made increasingly greater distinction in the past three decades between potential tonemerging targets, exhibiting sound changes in the opposite directions of the ongoing changes
STABILITY OF ACOUSTIC CUES OF THE THREE-WAY VOICING CONTRAST IN THAI MOTHERS’ STOP PRODUCTION

Recent findings have shown age-related and possibly sex-related shift in stops’ VOT values in some Asian languages (e.g., Japanese and Korean). This study examines VOT modifications of Thai stop contrasts (/b/, /p/, and /ph/) in infant directed speech (IDS). Ten Thai mother-infant dyads were recruited; infants were from two age groups: 4–6 and 8–10 months. The mothers produced repetitions of target syllables in carrier sentence while interacting with their infant and later with experimenter (ADS). Durational measures were taken from the stops and the following vowel. Durational differences in IDS vs. ADS of same mothers within each group (younger vs. older infants) were compared. Vocalic differences (longer in IDS) were significant in all factors. Overall, VOT differences in IDS vs. ADS were non-significant, but slightly wider interquartile range and more instances of varied phonetic realizations were observed in IDS, such as “bleed” in [b] and fricated stop in [ph].
Short-Term Load Forecasting for a Single Household Based on Convolution Neural Networks Using Data Augmentation

Advanced metering infrastructure (AMI) is spreading to households in some countries, and could be a source for forecasting the residential electric demand. However, load forecasting of a single household is still a fairly challenging topic because of the high volatility and uncertainty of the electric demand of households. Moreover, there is a limitation in the use of historical load data because of a change in house ownership, change in lifestyle, integration of new electric devices, and so on. The paper proposes a novel method to forecast the electricity loads of single residential households. The proposed forecasting method is based on convolution neural networks (CNNs) combined with a data-augmentation technique, which can artificially enlarge the training data. This method can address issues caused by a lack of historical data and improve the accuracy of residential load forecasting. Simulation results illustrate the validation and efficacy of the proposed method.
Chromatin Evolution andMolecular Drive in Speciation

Are there biological generalities that underlie hybrid sterility or inviability? Recently, around a dozen “speciation genes” have been identified mainly in Drosophila, and the biological functions of these genes are revealing molecular generalities. Major cases of hybrid sterility and inviability seem to result from chromatin evolution and molecular drive in speciation. Repetitive satellite DNAs within heterochromatin, especially at centromeres, evolve rapidly through molecular drive mechanisms (both meiotic and centromeric). Chromatin-binding proteins, therefore, must also evolve rapidly to maintain binding capability. As a result, chromatin binding proteins may not be able to interact with chromosomes from another species in a hybrid, causing hybrid sterility and inviability.
Trait-based selection

Metal mining creates waste tailings that function as microdeserts which feature severe abiotic stresses imposed by high concentrations of trace elements, high conductivity, low pH, physical instability and scant soil and water resources (Conesa, Faz, & Arnaldos, 2006). Around 700 million tons of metalliferous wastes are laid down annually (Warhurst, 2000). These extreme environments, which hinder both the natural recolonization and humandriven restoration, yield very depleted ecosystem services that require innovative restoration strategies. Conventional minerehabilitation techniques (e.g. waste removal, dam building, onsite containment by sealing) have Received: 19 July 2017 | Accepted: 8 December 2017 DOI: 10.1111/1365-2664.13094
The Diachronic Coronal-Velar Nasal Relationship

This paper investigates the phonetic factors of diachronic nasal place change from the alveolar to the velar place of articulation. Evidence is given from Cuban Spanish, Hausa, Brazilian Portuguese, and Chinese. There appear to be two distinct pathways leading to change. The first is a pathway in which the word-final alveolar nasal becomes velar with no independent stage of phonemic word-final nasalized vowels (Cuban Spanish, Hausa, and certain dialectal groups of Chinese). In the second pathway (Brazilian Portuguese), there is a documented stage of phonemically nasalized vowels. It is concluded that the change from alveolar-to-velar nasal is one of phonetic changes, in no way explained by an abstract notion of markedness.