Miracle-dz/UniFAR-FTUs huggingface dataset:
Ovariectomized rat model of osteoporosis: a practical guide

Osteoporosis affects about 200 million people worldwide and is a silent disease until a fracture occurs. Management of osteoporosis is still a challenge that warrants further studies for establishing new prevention strategies and more effective treatment modalities. For this purpose, animal models of osteoporosis are appropriate tools, of which the ovariectomized rat model is the most commonly used. The aim of this study is to provide a 4-step guideline for inducing a rat model of osteoporosis by ovariectomy (OVX): (1) selection of the rat strain, (2) choosing the appropriate age of rats at the time of OVX, (3) selection of an appropriate surgical method and verification of OVX, and (4) evaluation of OVX-induced osteoporosis. This review of literature shows that (i) Sprague-Dawley and Wistar rats are the most common strains used, both responding similarly to OVX; (ii) six months of age appears to be the best time for inducing OVX; (iii) dorsolateral skin incision is an appropriate choice for initiating OVX; and (iv) the success of OVX can be verified 1-3 weeks after surgery, following cessation of the regular estrus cycles, decreased estradiol, progesterone, and uterine weight as well as increased LH and FSH levels. Current data shows that the responses of trabecular bones of proximal tibia, lumbar vertebrae and femur to OVX are similar to those in humans; however, for short-term studies, proximal tibia is recommended. Osteoporosis in rats is verified by lower bone mineral density and lower trabecular number and thickness as well as higher trabecular separation, changes that are observed at 14, 30, and 60 days post-OVX in proximal tibia, lumbar vertebrae and femur, respectively.
' ' Title N-acetylglucosaminyltransferase I Activity of Bovine Oviduct Epithelial Cells : Stimulation by Luteinizing Hormone , Vascular Endothelial Growth Factor and Tumor Necrosis Factor α

N-acetylglucosaminyltransferase ! (GnT! ; EC 2.4.1.101), which catalyzes出efirst step加 出e conversion of oligomannose to cornplex or hybrid N-glycans of glycoproteins, was found in media cultured with bovine oviduct epi也elialcells (BOEC) obtained仕omnon-pregnant cows during the follicular phase. Combined treatment with specific hormones increased GnT 1 release仕omBOEC Luteinizing hormone (LH; 10 ng/ml) alone slightly, but together with 17 jhs甘adiol(E2; 1 ng/ml), synergistica11y increased GnT ! activity. Vascular endothelial growth factor (VEGF) and tumor necrosis factor行NF)α"which have been shown to have their highest activities出 thebovine oviduct during the periovulatory period, a150 increased in GnT 1 activity. This study provides the first evidence of an increase of GnT 1 release from BOEC in凹 trorand shows that endocrine as well as local factors such as LH, VEGF andτNFαincrease this activity. The results suggest that GnT 1 activity in the bovine oviduct may contribute to the induction of glycosylation and thereby contributing to the provision of the op出nalmicroenvirorunent for fertilization and early development of the embryos
PLink: Efﬁcient Cloud-based Training with Topology-aware Dynamic Hierarchical Aggregation

Training deep learning ( DL ) models has become an important workload on the commercial cloud. Scaling cloud-based distributed training faces unique challenges from the hierarchical network topology of the datacenter and the dynamic nature of the multi-tenant environment. Timely training of deep learning models requires effective use of topology-induced locality in the datacenter network. This work proposes PLink, an optimized communication library that probes the physical network and then generates and executes a ﬁtted hierarchical aggregation plan to take advantage of locality in the datacenter network. Further, it adapts to changing network conditions by dynamically selecting aggregation routes. PLink needs no support from cloud providers and operates out-of-the-box on unmodiﬁed commercial clouds. PLink techniques deliver up to 95% accuracy inferring VM physical afﬁnity. Crucially, PLink serves as a direct plug-in to many training frameworks, delivering up to 3x faster end-to-end training performance for popular DL models on Azure and EC2 compared to the state of the art.
Impact of atmospheric Coastal Jet off Central Chile on SST from satellite observations

1 Laboratoire d'Etudes en Géophysique et Océanographie Spatiale (LEGOS); 18, Avenue Edouard Belin 31401 Toulouse Cedex 9, France 2 IMARPE, Callao, Peru 3 Department of Geophysics, Universidad de Chile Blanco Encalada 2002. Santiago – Chile 4 LOCEAN, Université Pierre et Marie Curie, B 101 T. 45, Etages 3-4-5 , 4, place Jussieu F-75252 PARIS CEDEX 05, France 5 Earth & Space Research, 2101 Fourth Avenue, Suite 1310, Seattle, WA 98121, USA
SYNTHESIS AND SPECTROSCOPIC CHARACTERIZATION OF ANATASE TIO2 NANOPARTICLES

Titanium dioxide nanoparticles are used in various applications including environmental photocatalysis and solar cells. In this work we present the synthesis of TiO2 nanoparticles employing sol-gel methodology. The morphology, composition, particle size, surface area and band gap of these nanoparticles have been characterized and compared with a standard anatase TiO2 reference specimen exploiting several instrumental techniques namely, Scanning Electron Microscopy (SEM), Energy Dispersive X-Ray Spectroscopy (EDXS), X-Ray Diffraction (XRD), Diffused Reflectance UV-VIS spectrometry (DUR-UV-VIS), Transmission Electron Microscopy (TEM), Brunauer–Emmett–Teller (BET) theory and Raman Spectrometry.
Is it possible to produce meatballs made with lamb from animals fed on whole cottonseed without altering the sensory characteristics?

The aim of this study was to evaluate the chemical composition and the technological and sensory properties of lamb meatballs made with meat from animals fed with different levels of whole cottonseed (0, 10, 20, 30 and 40%). The meatballs prepared with lamb from animals fed on whole cottonseed presented higher (P<0.05) ash content. All the meatball formulations presented low levels of lipids (2.90%) and cholesterol (74.15 mg/100g), as well as high protein content (18.92%). The difference (P<0.05) observed in the variables of cooking characteristics did not have an effect on the texture profile, which was related to the microscopic observations of the product. In the triangle test for difference, the testers did not perceive difference between the control meatballs (0%) and those with up to 30% of whole cottonseed. However, in the acceptance test, the testers detected sensory alteration starting at a level of 12.5% of whole cottonseed. Thus, it is possible to produce meatballs with meat from lambs fed on up to 12.5% of whole cottonseed in the dry matter of their diet without altering the sensory characteristics of the product.
Khovanov homology , slice invariants , and exotic R 4

In [6] Khovanov defines an invariant of oriented knots and links called the Khovanov homology which takes on the form of a graded homology theory. Khovanov homology is constructed by categorifying the Jones polynomial; this relationship between Khovanov homology and the Jones polynomial is captured by the fact that the graded Euler characteristic of the Khovanov homology of an oriented link L is equal to the unnormalized Jones polynomial of L. To define the Khovanov homology, we first construct a bigraded chain complex associated to an oriented link diagram D, which we call the Khovanov complex. We then take the homology of this complex to get Khovanov’s invariant.
The Roles of Organizational and Ethical Climate on Individual Performance of Employees

Performance evaluation is a process in which the productivity of employees or institutions is measured according to certain pre-determined standards. Being competitive in national and international markets and increasing productivity have gained importance under the current market conditions and in the process of globalization. The most significant source for organizations to provide a sustainable competitive advantage is human resources. Therefore, providing a positive workplace atmosphere to employees in the organizations is of great importance. This study tests the roles of organizational climate and ethical climate, which gradually gain significance in new organizational structures that emerge with social, economic and technological changes under the market conditions of the 21st century, on the individual performance of employees. For this purpose, data were obtained by using the survey method on the white-collar employees of organizations functioning in three diverse areas of the private sector in Istanbul. It was determined that while organizational climate has a low influence on the individual performance of employees, the ethical climate has an important role on the individual performance of employees.
The Black-Scholes Equation with Variable Volatility Through the Adomian Decomposition Method

The Black-Scholes equation is a partial differential equation characterizing the price evolution of a European call option and put option on a stock. In this work, we use the Adomian Decomposition Method (ADM) for the approximation of the solution of the Black-Scholes equation and show how it can be applied to a case in which the volatility is not constant but is dependent on the price of the underlying asset. Finally, we expose a numerical example to validate the developed method. Mathematics Subject Classification: 91G80; 91B25; 91G60
The Un-Common Leopard: presence, distribution and abundance in Gallies and Murree Forest Division, Northern Pakistan

The leopard Panthera pardus is thought to be sparsely distributed across Pakistan and there is limited understanding of the demographic structure and distribution of the species in this country. We conducted a study, from April to July 2017, and, from March to June 2018, in the northern Pakistan region to establish the presence and distribution of leopards, mindful at the outset of their abundance in that region. The presence of leopards was confirmed in the Swat, Dir and Margalla Hills region. The leopard population in Gallies and Murree Forest Division was preliminarily assessed via camera-trapping. As a result, a total of 63 potential areas of leopard population were identified initially. The leopard was photo captured at 27 locations (hotspots) with 34 capture events yielding 195 images over the course of 3,022 active trap-nights. Camera trap images were examined to identify leopard individuals using their rosette patterns on both the left and right flanks and the dorsal side of the tail. Ultimately, 15 leopard individuals were identified during the first survey period of the study and four individuals were recaptured in the second survey period, together with three new individuals. The detection probability of individual leopards from MARK varied from 0.10 and 0.20 with a population size (preliminarily estimated to be 16–25 (SE = 3.18) in 2107 and 7–13 (SE = 1.87) in 2018. This gave a density of 4.5 to 9.5 leopards/100 km2, respectively. A home range of various individual leopards was found to extend from the Gallies Reserved Forest to the extended corridors of Guzara Forest. In general, this study suggests that the Guzara Forest is crucially important for the conservation of leopards in the region as this area allows them extended movement while searching for food and mates. Nature Conservation 37: 53–80 (2019) doi: 10.3897/natureconservation.37. 32748 http://natureconservation.pensoft. net Copyright Muhammad Asad et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. RESEARCH ARTICLE Launched to accelerate biodiversity conservation A peer-reviewed open-access journal
Genetic Node-Mapping Methods for Rapid Collective Communications

Inter-node communication is essential in parallel computation. The performance of parallel processing depends on the efficiencies in both computation and communication, thus, the communication cost is not negligible. A parallel application program involves a logical communication structure that is determined by the interchange of data between computation nodes. Sometimes the logical communication structure mismatches to that in a real parallel machine. This mismatch results in large communication costs. This paper addresses the node-mapping problem that rearranges logical position of node so that the degree of mismatch is decreased. This paper assumes that parallel programs execute one or more collective communications that follow specific traffic patterns. An appropriate node-mapping achieves high communication performance. This paper proposes a strong heuristic method for solving the node-mapping problem and adapts the method to a genetic algorithm. Evaluation results reveal that the proposed method achieves considerably high performance; it achieves 8.9 (4.9) times speed-up on average in single-(two-)traffic-pattern cases in 32 × 32 torus networks. Specifically, for some traffic patterns in small-scale networks, the proposed method finds theoretically optimized solutions. Furthermore, this paper discusses in deep about various issues in the proposed method that employs genetic algorithm, such as population of genes, number of generations, and traffic patterns. This paper also discusses applicability to large-scale systems for future practical use. key words: interconnection networks, node mapping, genetic algorithms
Integration of Vessel Traffic Control Systems and Geographical Information Systems

(Prof. Vasily Popovich, SPIIRAS, 14 Liniya, 39, St. Petersburg, Russia, popovich@mail.iias.spb.su) (Prof. Christophe Claramunt, Naval Academy Research I nstitute, France, christophe.claramunt@ecole-navale .fr) (Prof. Vasily Osipov, SPIIRAS, 14 Liniya, 39, St. Pe tersburg, Russia, osipov_vasiliy@mail.ru) (Dr. Cyril Ray, Naval Academy Research Institute, Fran ce, cyril.ray@ecole-navale.fr) (Dr. Tianzhen Wang, Shanghai Maritime University, Ch ina, tzwang@cle.shmtu.edu.cn) (Dmitry Berbenev, SPIIRAS, 14 Liniya, 39, St. Peters burg, Russia, berbenev@oogis.ru)
Towards a framework of knowledge for equitable mathematics teacher education

Attention to issues of social justice is becoming increasingly prominent in teacher education programs and in the field of mathematics education (e.g., White, Crespo, & Civil, 2016). Moreover, scholars have argued that instead of remaining isolated in a single course (typically the “multicultural” course), a focus on social justice must be integrated throughout teacher education programs (McDonald & Zeichner, 2009). This requires that mathematics teacher educators be prepared to address social justice in their mathematics content and methods courses. There are a variety of perspectives in the literature on social justice mathematics education (Wager & Stinson, 2012). In my work I focus on preparing teachers who can connect mathematics to real-world contexts that involve exploring, analyzing, and proposing solutions for current social and political issues (e.g., Gutstein, 2006)—which I refer to as sociopolitical mathematics teaching. By drawing on existing literature and my own experiences, I identify the knowledge bases that teachers and mathematics teacher educators must draw on in order to enact sociopolitical mathematics. I provide tools for engaging in sociopolitical mathematics teaching, discuss a concrete example from my own practice, and propose a framework for thinking about the knowledge needed for sociopolitical mathematics teaching.
The Spectrum of Microbial Keratitis: An Updated Review

In microbial keratitis, infection of the cornea can threaten vision through permanent corneal scarring and even perforation resulting in the loss of the eye. A literature review was conducted by Karsten, Watson and Foster (2012) to determine the spectrum of microbial keratitis. Since this publication, there have been over 2600 articles published investigating the causative pathogens of microbial keratitis.
Hybrid Model of Seasonal ARIMA-ANN to Forecast Tourist Arrivals through Minangkabau International Airport

The number of tourist arrivals forecasting is required for the future development of tourism industry to improve the economic growth. The number tourist arrivals data can be analyzed by building a model so that it will help to find out the number of tourist arrivals in the next period which is through Minangkabau International Airport. The linear model that is used is Seasonal Autoregressive Integrated Moving Average (SARIMA) used and continued to build a nonlinear model of the residual SARIMA model using Artificial Neural Network (ANN). In this research, SARIMA model which obtained is SARIMA (1, 0, 1) (1, 1, 0) 12 . But, residual of SARIMA model has not been fulfilled an autocorrelation assumption so that it isproposed a new model of SARIMA-ANN. The residual model of SARIMA is built using the ANN model architecture with 2–2–2–1 network topology. The performance rate of time series model of tourist arrivals which is the data started on January 2012 until March 2019 is measured using Mean Absolute Percentage Error (MAPE). Based on the MAPE value of 17.1770% indicates that the model obtained having good performance to forecast the number of tourist arrivals through Minangkabau International Airport in the future.
Forming Opportunities through Design Thinking

An interesting development in the entrepreneurial economy is the rise in both number and diversity of roles played by designers. Be it as consultants, contractors, educators, founders or funding decision-makers, design skills seem to be increasingly attractive to entrepreneurial teams, accelerator programs and venture capital. This exploratory study asks whether the practices, cognitive processes and mindsets prevalent in a formal design education help in the formation of entrepreneurial opportunities. Using a visual narrative approach, it compares the processes through which entrepreneurial opportunities were formed by 14 Chilean founders from design and non-design backgrounds, with the purpose of identifying how design thinking contributes to, hinders, or fails to support those processes. Findings suggest that collaborative work styles, thinking by doing and reflective reframing have the greatest positive impacts on opportunity formation, regardless of the disciplinary background of founders. Design thinking does not seem to provide a clear understanding of value creation and resource leveraging. The study finds parallels between design thinking and opportunity formation that can be drawn upon to improve development of entrepreneurial competencies among designers.
Absolute continuity of the spectrum in a twisted Dirichlet-Neumann waveguide

Quantum waveguides with the shape of a planar infinite straight strip and combined Dirichlet and Neumann boundary conditions on the opposite half-lines of the boundary are considered. The absence of the point as well as of the singular continuous spectrum is proved.Quantum waveguides with the shape of a planar infinite straight strip and combined Dirichlet and Neumann boundary conditions on the opposite half-lines of the boundary are considered. The absence of the point as well as of the singular continuous spectrum is proved.
Model Reuse With Reduced Kernel Mean Embedding Specification

Given a publicly available pool of machine learning models constructed for various tasks, when a user plans to build a model for her own machine learning application, is it possible to build upon models in the pool such that the previous efforts on these existing models can be reused rather than starting from scratch? Here, a grand challenge is how to find models that are helpful for the current application, without accessing the raw training data for the models in the pool. In this paper, we present a two-phase framework. In the upload phase, when a model is uploading into the pool, we construct a reduced kernel mean embedding (RKME) as a specification for the model. Then in the deployment phase, the relatedness of the current task and pre-trained models will be measured based on the value of the RKME specification. Theoretical results and extensive experiments validate the effectiveness of our approach.
Magic Cayley-Sudoku Tables.

A Cayley-sudoku table of a finite group G is a Cayley table for G, the body of which is partitioned into uniformly sized rectangular blocks in such a way that each group element appears exactly once in each block. A Cayley-sudoku table is pandiagonal magic provided the blocks are square and the "sum" (using the group operation) of elements in every row, column, broken diagonal, and broken antidiagonal in each block gives the group identity. We provide sufficient conditions for a group to have a pandiagonal magic Cayley-sudoku table and give some examples.
On the evolution of the velocity gradient tensor in transitional boundary layers

We study the transition to turbulence from the perspective of the velocity gradient tensor dynamics. Our work is motivated by the observation of nonlinear structures emerging during transition, as revealed by vortex identifiers such as the Q-criterion. To that end, we have derived transport equations based on several invariants of the velocity gradient tensor to obtain integral budgets spanning the different stages of transition from laminar to turbulent flow. We have also discussed which quantity would be the most appropriate in our study, while keeping in mind the potential for future modeling applications.
Classifying Wikipedia in a fine-grained hierarchy: what graphs can contribute

Wikipedia is a huge opportunity for machine learning, being the largest semi-structured base of knowledge available. Because of this, many works examine its contents, and focus on structuring it in order to make it usable in learning tasks, for example by classifying it into an ontology. Beyond its textual contents, Wikipedia also displays a typical graph structure, where pages are linked together through citations. In this paper, we address the task of integrating graph (i.e. structure) information to classify Wikipedia into a fine-grained named entity ontology (NE), the Extended Named Entity hierarchy. To address this task, we first start by assessing the relevance of the graph structure for NE classification. We then explore two directions, one related to feature vectors using graph descriptors commonly used in large-scale network analysis, and one extending flat classification to a weighted model taking into account semantic similarity. We conduct at-scale practical experiments, on a manually labeled subset of 22,000 pages extracted from the Japanese Wikipedia. Our results show that integrating graph information succeeds at reducing sparsity of the input feature space, and yields classification results that are comparable or better than previous works.
Dual Stochastic Natural Gradient Descent

Although theoretically appealing, Stochastic Natural Gradient Descent (SNGD) is computationally expensive, it has been shown to be highly sensitive to the learning rate, and it is not guaranteed to be convergent. Convergent Stochastic Natural Gradient Descent (CSNGD) aims at solving the last two problems. However, the computational expense of CSNGD is still unacceptable when the number of parameters is large. In this paper we introduce the Dual Stochastic Natural Gradient Descent (DSNGD) where we take benefit of dually flat manifolds to obtain a robust alternative to SNGD which is also computationally feasible.