Miracle-dz/UniFAR-FTUs huggingface dataset:
CESA and VASA for the treatment of urge urinary incontinence

Hypothesis / aims of study According to the Integral Theory a dysfunction of the uterosacral ligament (USL) is responsible for urge urinary incontinence (UUI). We developed a standardized operation for the replacement of the USL by PVDF tapes (CESA and VASA). In previous studies we found that up to 40% of patients were curd, however, the remaining 60% of patients developed stress urinary incontinence thereafter (1). These patients received a standardized TOT 8/4 which we used since 2013. The outcome of the first 72 patients treated with both standardized modalities was evaluated.
DETECTION OF EATING DISORDERS RISKS AMONG 12TH GRADE STUDENTS

The attitude to the healthy eating and eating habits takes its roots in the family. When becoming a grown-up, a person prefers eating the favorite and habitual food. It depends only on a person’s own choice to observe the basic laws of the healthy eating and keeping to them and in this way to support own health. As opposed to healthy, balanced, diversified, regular and sufficient amount of food there are the strategies that can cause eating disorders if to follow them. Among such disorders might be neurotic anorexia, neurotic bulimia, compulsive overeating and other unspecified eating disorders. The prevalence of eating disorders nowadays is connected with the influence of increased stress, an enlarged information load, an awareness of modern beauty standards as a result, eating disorders risks are increasing. Prompt information and provision of knowledge for teachers, parents and students on eating disorders prevalence, manifestation and the importance of timely recognition for successful treatment is the most important element of preventive measures. The topicality of the research on eating disorders among students is justified by the fact that the early detection of students’ eating disorders can promote timely recognition of the problem and the beginning of treatment reducing serious physical and psychological complications and even fatal cases. The primary goal of this research was to find out eating disorders risks among the 12 th grade students. The second goal was to determine eating disorders risks among the 12 th grade students due to the gender differences of students. To gain the results of the research the quantitative research method with the research tool – EAT-26 test (Garner et al., 1982) was used. Two hundreds of the 12 th grade students were involved into the research as respondents. The results of the survey show that the 5 th part of the respondents have got eating disorders risks indicators. There are statistically significant differences between men and women (р<0.001).
Pharmacokinetics of Cefquinome in Layer Birds Following Intramuscular and Intravenous Administration

Received: Revised: Accepted: Published online: February 19, 2019 April 02, 2019 April 14, 2019 April 26, 2019 Cefquinome is approved for use against many bacterial infections in a number of animal species. This study was conducted to evaluate the pharmacokinetics of Cefquinome after intramuscular (IM) and intravenous (IV) administration in layer birds for its safety evaluation. Twelve healthy layer birds were randomly allocated in two equal groups. Each group was administered with 5mg/kg b.w. of Cefquinome by intramuscular and intravenous routes. Highly sensitive high performance liquid chromatography with ultraviolet detection (HPLC-UV) method was developed for quantification of Cefquinome in layer bird’s plasma with >80% recovery. The Limit of detection and quantification were 0.02 and 0. 05μg/ml, respectively. The pharmacokinetic data showed that mean Area under the curve (AUC) after IM and IV administration were 7.838±0.165 and 11.729±0.346h×μg/ml, respectively. The maximum concentration (Cmax) following IM administration (4.525±0.129 μg/ml) was almost same the mean Cmax after IV administration (4.635±0.270μg/ml). Time to reach maximum concentration (Tmax) after IV and IM administration were 0.1h and 0.5h, respectively. Cefquinome sulphate had a relatively shorter half-life (1.19±0.14h) after IV dose administration. The shorter half-life depicts a rapid elimination. Total recovery after each administration was greater than 75%. The mean resident time after IM and IV administration was found to be 1.528±0.09h and 1.988±0.0311h, respectively. The bioavailability after IM administration was 66.84±2.05%. This study indicated that Cefquinome sulphate has favorable pharmacokinetics following both administrations in healthy layer birds which can help to form optimum dosage regimes thus ultimately leading to its use for eradication of various systemic and local infections. ©2019 PVJ. All rights reserved
Complete chloroplast genome of Ulva pertusa, one of the causal species of green macroalgal blooms in the coastal waters of Qinhuangdao, China

Abstract Since 2015, macroalgae blooms have appeared along the Qinhuangdao coast of the Bohai Sea in China and they have recurred annually during the months of April to September. One of the causal species that results in the macroalgal blooms, Ulva pertusa, has been detrimental to the environment and ecosystem along the coast of the Qinhuangdao, China. In the present study, we sequenced the chloroplast genome of U. pertusa for the first time (GenBank accession number MN853875) and found that the annular genome comprised 104,380 base pairs, including 71 protein-coding genes, 26 tRNAs, and 2 rRNAs. We then constructed a phylogenetic tree of U. pertusa and 17 other species based on core genes, which showed that U. pertusa is the closest sister species of U. fasciata.
A machine learning approach to quantum spin chains

The aim of this work is to present a computational method to solve many-body quantum system problems. The proposed approach is a Machine Learning method to deal with images, where the input is the Hamiltonian of the desired system. We trained a VGG-16 Convolutional Neural Network to predict the ground state energy of the XXZ Hamiltonian, as well as the negativity of the pairwise entangled mixed states. The results predict with good precision the values of the energy and the pairwise entanglement. Particularly, we can reduce the dimension of the Hamiltonian before it passes through the network. The method can be generalized to arbitrary physical properties.
Estimating the Information Source under Decaying Diffusion Rates

Recently, as arising from online social network services such as Facebook and Twitter, people are more actively using social networks to exchange their new information. In this consideration, finding the information source becomes one of the indispensable and useful tasks in detecting a malicious agent and an influential person in the networks. A seminal work by Shah and Zaman in 2010 showed that the detection probability cannot be beyond 31% even for regular trees if time goes to infinity. From the study, extensive researches have been done for this problem, whose major interests lie in constructing an efficient estimator and providing theoretical analysis on its detection performance. However, most of the works assumed the homogeneous diffusion rate of the information, where the diffusion rate does not change at all times over the network. In practice, it is reported that information has a lifetime and it becomes less attractive over time. In this paper, we study the problem of detecting the information source when the diffusion rate decreases by the distance from the source in the network. As a result, we obtain analytical detection performance of Maximum Likelihood Estimator (MLE) and validate our theoretical findings over the regular tree, random and real-world networks.
Symmetry for Initial Boundary Value Problems of PDEs

Aldhlki T. Jassim Dep. of MathsCollege of Basic Education University of Mustansirya, Baghdad, Iraq talatjassim10@yahoo.com Abstract In this paper, we discuss the reduction of IBVP by using the definition of Bluman or Ibragimov. Moreover, some examples that explain this definition for linear and nonlinear heat equation, are given. Next, we will give some restrictions on the Lie symmetry, which make the initial-boundary conditions are invariant. Finally, we find an initial condition which need not to be left invariant by a Lie symmetry in order to find an invariant solution, which satisfies that initial condition.
A Tomato Quality Identification Method Based on Raman Spectroscopy and Convolutional Neural Network

in recent years, more and more technologies have been applied in monitoring growth and production efficiency of plants, i.e. agricultural Internet of Things (IOT) and new information-aware technologies. The architecture of the IOT is divided into four layers, i.e., the sensing layer, network layer, processing layer and application layer[1-4]. Among them, the perception layer is the facial features and the skin of the IOT, which is the basis of the IOT [5]. Raman spectroscopy technology has the advantages of fast, simplicity, accuracy, non-destructive and automatic identification, which has become a powerful analytical verifying method. The method of tomato quality identification that based on the Raman spectroscopy combined with convolutional neural network (CNN)[6]was explored. The Raman spectrum of tomato was collected by Raman sensor to construct a neural network with deep network structure. Through repeatedly learning and training in Raman map, we can determine the map recognition model of high quality tomatoes and use matplotlib to realize the identification simulation.
Analyzing the educational goals, problems and techniques used in educational big data research from 2010 to 2018

ABSTRACT The purpose of this study is to review journal papers on educational big data research published from 2010 to 2018. A total of 143 papers were selected. The papers were characterized based on three dimensions: (a) educational goals; (b) educational problems addressed; and (c) big data analytical techniques used. A qualitative content analysis approach was conducted to develop a coding scheme for analyzing the selected papers. The results identified four types of educational goals, with a clear predominance of quality assurance. The identification of the most mentioned educational problems resulted in four main concerns: the lack of detecting student behavior modeling and waste of resources; inappropriate curricula and teaching strategies; oversights of quality assurance; and privacy and ethical issues. Concerning the most mentioned big data analytical techniques, the coding scheme revealed that the majority of the papers focused on the educational data mining technique followed by the learning analytics technique. The visual analytics technique was mentioned in a few papers. The results also indicated that the educational data mining technique is the most suitable technique to use for quality assurance and to provide potential solutions for the lack of detecting student behavior modeling and the waste of resources in institutions.
Pull-Based Distributed Event-Triggered Circle Formation Control for Multi-Agent Systems with Directed Topologies

This paper investigates a circle formation control problem for multi-agent systems with directed topologies via pull-based distributed event-triggered control principles. Firstly, for scenarios of continuous communication, a pull-based distributed event-triggered principle is proposed. It is proved that if the communication topology is irreducible and has a directed spanning tree, the event-triggered coupling continuous communication can lead multiple agents to form a desired circle formation. Then, the results are extended to discontinuous communication scenarios, where all the agents use a model of their neighborhoods to generate self-triggered instants without monitoring continuously, update the local controller here, and if necessary, local broadcast information based on the adopted control inputs to neighboring agents. In addition, Zeno behavior can be excluded during the whole process. Finally, numerical simulation results are given to demonstrate the effectiveness of the proposed circle formation control methods.
Impact of Chinese Renminbi on Korean Exports: Does Quality Matter?

ABSTRACT This study examines the impact of changes in the Chinese exchange rate on Korean exports considering the characteristics of products exported. We use import data from OECD countries from 2002 to 2014 and find that Korea’s exports of products having a greater competition further decline as renminbi depreciates. On the other hand, Korean exports of products having a greater complementarity degree with Chinese are more likely to increase as renminbi depreciates. In addition, the degree of negative impacts become smaller once Korean export products have a relatively higher quality than those of China.
Improved SLAM closed-loop detection algorithm based on DBoW2

In order to solve the problems of dbow2-based closed-loop detection algorithm, it is necessary to determine the appropriate level of dictionary tree and K value of clustering algorithm according to experience in advance. First, the new algorithm obtains the initial image feature clustering of training set by k-means ++ algorithm within the search range of cluster number (H, L). Secondly, by merging the form of similar classes, the cluster number is gradually reduced until the CRI function converges. Finally, the clustering value at this point is the best clustering value adopted by the training set to train the dictionary tree, and the clustering is repeated until the complete dictionary tree is generated. The feasibility of this algorithm is verified through experimental analysis, and the new method proposed can solve the problem of dictionary tree generation of training sets under different backgrounds, which plays a very important role in closed-loop detection based on visual image similarity detection, and has certain theoretical and practical reference value.
Psoas major cross-sectional area: A potential marker of cardiorespiratory fitness

Background and Aim: Cardiorespiratory fitness is an important marker for overall health that significantly correlates with obesity-associated morbidities and mortality. Maximal oxygen uptake (VO2max) recorded during an incremental exercise test is the gold standard assessment for aerobic fitness. However, its cost, chronic illness, and frailty often preclude its application. The cross-sectional area (CSA) of the abdominal psoas major muscle is a predictor of sarcopenia and surgery outcomes and represents a promising biomarker for cardiorespiratory health. Therefore, in the present study, we have planned to assess the relationship between psoas major CSA, anthropometry, and body composition in a UK-based cohort of 210 men and women. Methods: Body mass (kg), height (cm), waist circumference (cm), VO2max, and blood pressure were measured in each participant. The CSA of psoas major, rectus abdominus, and another abdominal muscle of the core muscle group were assessed. Results: Following adjustment for height, psoas major CSA was found to be a significant predictor of percentage body fat (P = 0.02) in men, and body mass index (BMI) in both men (P = 0.015) and women (P = 0.004). We found psoas major CSA correlated more strongly with VO2max (r = 0.74, P < 0.01) than any other study outcome, including age and BMI. Conclusion: Psoas major muscle CSA represents an accurate, reproducible, and time-efficient surrogate for cardiorespiratory fitness and body composition.
A Nesterov-Like Gradient Tracking Algorithm for Distributed Optimization Over Directed Networks

In this article, we concentrate on dealing with the distributed optimization problem over a directed network, where each unit possesses its own convex cost function and the principal target is to minimize a global cost function (formulated by the average of all local cost functions) while obeying the network connectivity structure. Most of the existing methods, such as push-sum strategy, have eliminated the unbalancedness induced by the directed network via utilizing column-stochastic weights, which may be infeasible if the distributed implementation requires each unit to gain access to (at least) its out-degree information. In contrast, to be suitable for the directed networks with row-stochastic weights, we propose a new directed distributed Nesterov-like gradient tracking algorithm, named as D-DNGT, that incorporates the gradient tracking into the distributed Nesterov method with momentum terms and employs nonuniform step-sizes. D-DNGT extends a number of outstanding consensus algorithms over strongly connected directed networks. The implementation of D-DNGT is straightforward if each unit locally chooses a suitable step-size and privately regulates the weights on information that acquires from in-neighbors. If the largest step-size and the maximum momentum coefficient are positive and small sufficiently, we can prove that D-DNGT converges linearly to the optimal solution provided that the cost functions are smooth and strongly convex. We provide numerical experiments to confirm the findings in this article and contrast D-DNGT with recently proposed distributed optimization approaches.
The temporal dynamics of insight problem solving – restructuring might not always be sudden

Abstract Insight problems are likely to trigger an initial, inappropriate mental representation, which needs to be restructured in order to find the solution. Despite the widespread theoretical assumption that this restructuring process happens suddenly, which leads to the typical Aha! experience, the evidence is inconclusive. Among the reasons for this lack of clarity is a reluctance to measure solvers’ subjective experience of the solution process. Here, we overcome previous methodological problems by measuring the dynamics of the solution process using eye movements in combination with the subjective Aha! experience. Our results demonstrate that in a problem that requires restructuring of the initial mental representation, paying progressively more attention to the crucial elements of the problem often preceded the finding of the solution. Most importantly, the sooner solvers started paying attention to the crucial elements, the less sudden and surprising the solution felt to them. The close link between the eye movement patterns and self-reported Aha! experience in the present study underlines the necessity of measuring both the cognitive and the affective components of insight to capture the essence of this phenomenon.
Novel Treatment Strategies for Major Depressive Disorder: Investigating Ketamine’s Antidepressant Effects and the Role of the c-Jun N-Terminal Kinase Pathway

Current first-line treatments for depression, namely monoamine-based drugs such as SSRIs, take weeks to show any clinical effects, and they are only effective in 60-70% of patients. There is therefore an urgent need to develop more rapid and efficacious treatments. Ketamine, an N-methyl-D-aspartate (NMDA) receptor antagonist often used as a dissociative anesthetic, has been found to have rapid (within hours) antidepressant effects, even in historically treatment resistant patients. Nevertheless, ketamine has its own limitations, such as unwanted side effects and abuse potential. The overarching goal of this thesis was to gain a better understanding of the antidepressant mechanisms of ketamine. Interestingly, we found that ketamine did not impact the typical stress hormone, corticosterone, nor did it modulate brain-region specific monoamine changes that were induced by acute (restraint) or systemic (lipopolysaccharide; LPS) stressors. However, ketamine did have anti-inflammatory actions, reducing interleukin-1 beta (IL-1β) and tumor necrosis factor alpha (TNF-α), and further still, repeated ketamine treatment promoted adult neurogenesis within the hippocampus. Notably, repeated ketamine also had an antidepressant-like behavioral effect that was still detectable 8 days after the final ketamine injection. In terms of potential mechanistic factors, ketamine increased active levels of the signaling factor c-Jun N-terminal kinase (JNK) within the cortex, and inhibition of JNK itself increased corticosterone levels. Intriguingly, JNK inhibition also modulated some stress-induced behavioral and monoaminergic changes, implying a diverse role for the protein. Overall, the data support a role for ketamine in neuroplasticity and immune function, and set the stage for future investigations into the pathways (i.e. JNK) associated with its antidepressant effects.
Partial Purification and Characterization of Antifungal Peptides Produced by Bacillus amyloliquefaciens PEP3 Against Phytophthora capsici

The prevalence of antibiotic-resistant microorganisms has triggered the exploration for novel antimicrobial compounds. Peptides are biological molecules that are found in all living organisms. They play key roles in many biological processes including organism’s defense. We have previously isolated Bacillus species ( Bacillus amyloliquefaciens PEP3) that showed antagonistic properties against fungi. Metabolites precipitates obtained from B. amyloliquefaciens PEP3 showed antifungal activity against plant pathogenic fungus, Phytophthora capsici . Further analysis showed that these metabolites were stable in the pH range of 6 to 8 and temperatures of between 25°C to 85°C after which it began to lose its activity. Polyacrylamide gel analysis indicated that the molecular weight of the metabolites to be approximately 5 kDa. The presence of biosynthetic lipopeptides producing genes namely ituD , srfA , fenD and Ipa-14 genes were detected via the use of specific primers. The metabolites were then isolated via methanol extraction, however none of the major lipopetides family were detected using liquid chromatogrpahy-mass spectrometry (LC-MS). Nevertheless, the results derived from this work suggested that B. amyloliquefaciens PEP3 to have biocontrol research value and warrants further analysis.
Complete mitochondrial genome of the important bio-control fungus Purpureocillium lilacinum (Ophiocordycipitaceae, Hypocreales) and its phylogenetic analysis

Abstract Purpureocillium lilacinum is widely used as commercialized bio-control agents for controlling plant parasitic nematodes, as well as other insects and plant pathogens. In this study, the complete mitogenome of P. lilacinum was determined using the next-generation sequencing technology. The mitogenome is a circular molecule of 23,495 bp containing 15 protein-coding genes (PCGs), 2 rRNA (rnl and rns) genes and 22 tRNA genes. The overall base composition is 35.5% A, 36.0% T, 12.9% C and 15.6% G, with a CG content of 28.5%. Phylogenetic analysis inferred from 14 concatenated PCGs of 47 taxa shows that P. lilacinum is clustered with the genus Tolypocladium of Ophiocordycipitaceae and forms a separate clade with strong statistical support. This study contributes to our understanding about sytematics and evolutionary biology of cordycipitoid fungi.
Management of maxillary central incisor with an extracanal and periapical cyst using cone-beam computed tomography as a diagnostic aid

The success of endodontic treatment depends on the knowledge of internal and external anatomy of the tooth, the normal supporting tissues of the tooth and any pathology related to it. The a im of the present study is to present the management of maxillary incisor with two canals and periapical lesion. The presence of two canals in maxillary central incisor was confirmed with cone-beam computed tomography. The tooth was cleaned and shaped with hand filing and obturated with lateral condensation technique. Periapical lesion was treated with surgical approach. 1-, 3 and 9-month follow-ups showed good healing of periapical tissue and suffi cient bone formation. The patient remained asymptomatic. Sufficient knowledge of the normal root canal anatomy and its variations, and proper treatment planning aids in successful endodontic treatment.