Miracle-dz/UniFAR-FTUs huggingface dataset:
lodination of Surface Components of the Spheroidal and Ameboid Spermatozoa of Ascaris suum (NematodaP

The protein constituents and iodinatable components of the spheroidal and ameboid forms of Ascaris spermatozoa were characterized by SDS-gel electrophoresis, lactoperoxidase iodination and 112511 -diazodiiodosulfanilic acid (DD ‘25ISA) labeling. Electrophoresis of spermatozoan total proteins on SDS-gels revealed 16 bands, two of which represent one major polypeptide (18,400 MW) and one major periodic acid-Schiff staining glycoprotein (12,000 MW). The spheroidal and ameboid spermatozoa shared four major components iodinatable by lactoperoxidase and DD125ISA methods. Three of these components have approximate molecular weights of 51,000, 55,000 and 62,000, respectively. The molecular weight of the fourth component was extremely large as suggested by its position near the top of SDS-gel. In both forms three small molecular weight components (10,000, 12,000 and 18,400 MW), minimally iodinated by lactoperoxidase, were more extensively labeled with DD’25lSA. The ameboid spermatozoa differed from the spheroidal form in showing a decrease in iodination of the slowest electrophoretic band and in the presence of two iodinatable components (greater than 66,000 MW) not detectable in the spheroidal form. These differences were evident in the iodination profiles of both lactoperoxidase and DD’25 ISA methods. Both spheroidal and ameboid spermatozoa contain two molecular species of Conconavalin A (Con A) receptors identified by histochemical staining after electrophoresis on SDS-gels. The electrophoretic mobilities of these two Con A receptors are similar in the two forms of spermatozoa and are characterized by having large molecular weights; one receptor has a molecular weight of 62,000, and the second has a molecular weight much greater than 66,000.
APPLICATION OF FACTORIAL DESIGN TO FORMULATE AND OPTIMIZE LOSARTAN POTASSIUM- LOADED SOLID LIPID NANOPARTICLES

Losartan Potassium (LP) belongs to class III in biopharmaceutics classification system with antihypertensive activity. The aim of this study is to design Losartan Potassium loaded Solid lipid nanoparticles (LP-SLNs) and to optimize on their physio-chemical properties including particle size (PS), entrapment efficiency (%EE), zeta potential (ZP) and in-vitro release of drug. Losartan Potassium loaded solid lipid nanoparticles (LP-SLNs) were prepared by means of a w/o/w double emulsion solvent evaporation technique employing stearic acid alone or mixture of stearic acid and GeleolTM as a lipid matrix. A (2 3 ) non-randomized full factorial design was adopted to optimize LP-SLNs physicochemical properties. Three independent parameters were selected in this design including the lipid type, the concentration of polyvinyl alcohol (%w/v) and the amount of lipid (mg). The impacts of these parameters on particle size (PS), entrapment efficiency (%EE), zeta potential (ZP) and in-vitro release of drug were inspected. The designed preparations of LP-SLNs possessed a spherical shape with a particle size in the range of 294 nm to 671 nm and a negative zeta potential range from -18.04 to -8.02 mV. The % entrapment efficiency of LP-SLNs formulations were found to be in the range of 20.18 to 32.19. Fourier Transformation Infrared Spectroscopy (FTIR) revealed no possible interactions between LP and other additives while differential scanning calorimetric (DSC) manifested transformation of LP from crystalline to amorphous state in SLNs formulation. Stability studies of the chosen freeze dried LP-SLNs formulations showed a high stability during a period of three months.
Running head: YOUTH ANTISOCIAL BEHAVIOR IN SOUTH AFRICA What are the risk factors for antisocial behavior among low-income youth in Cape Town?

What are the risk factors for antisocial behavior among low-income youth in Cape Town? Frances Gardner and Rebecca Waller Centre for Evidence-Based Intervention, Department of Social Policy and Intervention, University of Oxford Barbara Maughan MRC Social Genetic & Developmental Psychiatry Centre, King’s, London Lucie Cluver Centre for Evidence-Based Intervention, Department of Social Policy and Intervention, University of Oxford & Department of Psychiatry & Mental Health, University of Cape Town.
C Consiglio Nazionale delle Ricerche The critical transmitting range for Connectivity in Mobile Packet Radio Networks

It is known that the critical transmitting range for connectivity in stationary packet radio networks is r=c q log n n , for some constant c>0, under the assumption that n nodes are uniformly distributed in R = [0;1] 2 . In this note, we investigate how mobility a(cid:11)ects this asymptotic result. We consider the well known random waypoint mobility model, whose asymptotic node spatial distribution has been recently derived. We prove that as long as the spatial distribution has a uniform component, the mobile critical transmitting range di(cid:11)ers from the stationary one at most by a constant factor. On the contrary, when the uniform component is null there is an asymptotic gap between the mobile and stationary case, i.e. r (cid:29) c q logn n for any constant c>0. Hence, the asymptotic behavior of the mobile critical transmitting range depends on the choice of the mobility parameters.
Degradation Markers in Nutritional Products. A Review

The main objective of the present review is to develop a brief overview of the current state of the knowledge on the analytical determination of oxidation and/or degradation parameters in nutritional products. Basically, since it is one of the major causes of food quality deterioration, and it has been a challenge for manufacturers and food scientists alike, lipid oxidation has traditionally been the most studied process throughout the history. There are many analytical methods to perform the detection of changes in food quality, focusing on the determination of the formation of oxidation products or on the changes in the standard profile of specific compounds. In addition, sensory analyses to identify oxidative changes in foods are also common. However, it is not the only parameters to measure the oxidation of food. Proteins and carbohydrates are also susceptible to oxidation; and therefore, many undesirable and/or harmful metabolites can also be found in food after this type of degradation that food industry must necessary control. The proposed summarized review will focus on both oxidation processes in order to better understand the evolution throughout the history of food control. technology available. Throughout the history, several analytical methods have been proposed to keep under control the oxidation of nutritional products. There are very different techniques that can be applied depending on the final objective and the product under study. The oxidation parameters to measure can be classified in three important groups depending of the sample: lipids, proteins or carbohydrates. Another classification could be done taking into account the technique used to control the oxidation: chemical or sensory methods. Finally, a third classification could be showed comparing two modes: general oxidation or determination of target compounds.
Analysesof bindingsequencesofthePhaR protein ofRhodobacter sphaeroides FJ1

The phaC, phaP, phaR, and phaZ genes are involved in the synthesis, accumulation, and degradation of poly-b-hydroxybutyrate (PHB). These genes encode the PHB synthase, phasin, regulatory protein, and PHB depolymerase, respectively, and are located in the same locus in the genome of Rhodobacter sphaeroides FJ1, a purple nonsulfur bacterium capable of producing PHB. We have previously found that the PhaR protein binds to the promoter regions of phaP, phaR, and phaZ and represses their expression. In this study, we determined that PhaR binds to an 11bp palindromic sequence, 5-CTGCN3GCAG-3 0, located at nucleotides 69 to 59 and 97 to 87 relative to the translation start site of phaP. Substitution of the three spacer nucleotides with any three or four nucleotides in this sequence had no effect on PhaR binding, but all other base deletions or substitutions in this sequence abolished its ability to bind PhaR both in vitro and in vivo. These results suggest that PhaR regulates the expression of phaP in R. sphaeroides FJ1.
The role of online attention in the supply of disinformation in Wikipedia

Wikipedia and many User-Generated Content (UGC) communities are known for producing reliable, quality content, but also for being vulnerable to false or misleading information. Previous work has shown that many hoaxes on Wikipedia go undetected for extended periods of time. But little is known about the creation of intentionally false or misleading information online. Does collective attention toward a topic increase the likelihood it will spawn disinformation? Here, we measure the relationship between allocation of attention and the production of hoax articles on the English Wikipedia. Analysis of traffic logs reveals that, compared to legitimate articles created on the same day, hoaxes tend to be more associated with traffic spikes preceding their creation. This is consistent with the idea that the supply of false or misleading information on a topic is driven by the attention it receives. These findings improve our comprehension of the determinants of disinformation in UGC communities and could help promote the integrity of knowledge on Wikipedia.
Application and Optimization of Wing Structure Design of DF-2 Light Sports Aircraft Based on Composite Material Characteristics

Compared with ordinary metal structures, advanced composite materials have the characteristics of high strength, high rigidity, and light weight. The use of composite materials in aircraft structures is currently a hot research topic. This research mainly discusses the optimization design of the composite wing structure of the DF-2 light sports aircraft. This article takes the DF-2 light sports aircraft planned to be produced by the company as the source. Based on its overall design basis, aerodynamic requirements, and the original wing structure design, according to the composite material aircraft structure design theory and method, the aircraft wing structure is carried out. Composite materials are materials with new properties that are composed of two or more materials with different properties at the macroscale by physical and chemical methods. Composite materials can be divided into functional composite materials and structural composite materials according to the nature of the application. Functional composites are materials with special functions, such as conductive composites, ablative materials, and frictional composites. At present, the main research is on structural composite materials, which are composed of two components: matrix material and reinforcing material. The new structural scheme design and structural strength analysis are designed to meet the structural strength requirements of the wing and the lightest weight. In this paper, according to the force transmission characteristics of different structural types of the wing, the characteristics of the load transmission are analyzed, and the shape parameters and load parameters of the wing structure design are used as initial conditions, and the quantitative analysis model of the wing structure is constructed according to the requirements of strength, stiffness, and stability. Through rapid mathematical modeling and analysis of the wing structure, the weight and efficiency of different configurations can be evaluated. Through the quantitative analysis model of the wing, the wing structure type can be quickly determined according to the wing parameters in the preliminary design, which makes the basis for the selection of the wing structure type. After optimization, the weight of the wing structure decreased from 0.966 kg to 0.803 kg, a decrease of 16.87%. The designability of composite materials is one of its major characteristics. By optimizing the layup angle, layup sequence, and dropout area, the performance indicators of the structure are finally improved. This research will promote the further development of the aerospace field.
Upright-Net: Learning Upright Orientation for 3D Point Cloud

A mass of experiments shows that the pose of the input 3D models exerts a tremendous influence on automatic 3D shape analysis. In this paper, we propose Upright-Net, a deep-learning-based approach for estimating the upright orientation of 3D point clouds. Based on a well-known postulate of design states that “form ever follows function”, we treat the natural base of an object as a common functional structure, which supports the object in a most commonly seen pose following a set of specific rules, e.g. physical laws, functionality-related geometric properties, semantic cues, and so on. Thus we apply a data-driven deep learning method to automatically encode those rules and formulate the upright orientation estimation problem as a classification model, i.e. extract the points on a 3D model that forms the natural base. And then the upright orientation is computed as the normal of the natural base. Our proposed new approach has three advantages. First, it formulates the continuous orientation estimation task as a discrete classification task while preserving the continuity of the solution space. Second, it automatically learns the comprehensive criteria defining a natural base of general 3D models even with asymmetric geometry. Third, the learned orientation-aware features can serve well in downstream tasks. Results show that our network outperforms previous approaches on orientation estimation and also achieves remarkable generalization capability and transfer capability.
Subset Selection in Machine Learning: Theory, Applications, and Hands On

Tutorial Outline Machine learning, and specifically deep learning has transformed numerous application domains like computer vision and video analytics, speech recognition, natural language processing, and so on. As a result, significant focus of researchers in the last decade has been on obtaining the most accurate models, often matching and sometimes surpassing human level performance in these areas. However, deep learning is also unlike human learning in many ways. To achieve the human level performance, deep models require large amounts of labeled training data, several GPU instances to train, and massive size models (ranging from hundreds of millions to billions of parameters). In addition, they are often not robust to noise, imbalance, and out of distribution data, and can also easily inherit the biases in the training data. Motivated by these desiderata and many more, we will present a rich framework of subset selection and coreset based approaches. We will begin by studying the theoretical aspects of subset selection, such as the modeling paradigms of coresets and submodularity, and the resulting optimization algorithms and theoretical properties. We will then study the application of subset selection to a number of areas like: a) compute-efficient training of deep models, b) label efficient methods like active learning, c) feature selection and model compression, d) targeted subset selection for robust, fair, and personalized learning, and e) human assisted learning. An important component of this tutorial will be a hands-on session where we will present a number of toolkits developed as a part of DECILE (www.decile.org), which include SUBMODLIB (submodular optimization), CORDS (coresets and subset selection for compute efficient training),
Why are open ascending auctions popular? The role of information aggregation and behavioral biases

The popularity of open ascending auctions is often attributed to the fact that openly observable bidding allows to aggregate dispersed information. Another reason behind the frequent utilization of open auction formats may be that they activate revenue enhancing biases. In an experiment, we compare three auctions that differ in how much information is revealed and in the potential activation of behavioral biases: (i) the ascending Vickrey auction, a closed format; and two open formats, (ii) the Japanese–English auction, and (iii) the Oral Outcry auction. Even though bidders react to information conveyed in others’ bids, information aggregation fails in both open formats. In contrast, the Oral Outcry raises higher revenue than the other two formats by stimulating bidders to submit unprofitable jump bids and triggering a quasi-endowment effect.
Relationships between corruption, electoral polarization, economic growth and inequality in the Peruvian case

This study analyzes the relationships between the variables of corruption, political polarization, economic growth, and income inequality for the Peruvian economy over the period 1998-2020. The methodology used to verify the degree of association and/or causality of the study variables were Pearson's correlation, linear, and quadratic regressions. The results point to a significant negative correlation between corruption and economic growth, and between electoral polarization and GDP, but that political polarization is positively associated with economic inequality measured by the Gini index (alpha = 1%). It was also found that economic growth decreases inequality. Therefore, it is concluded that corruption decreases economic growth, but that there is a "U"-shaped relationship between corruption and the Gini index. Consequently, at lower levels of corruption, an increase in the corruption perceptions index (CPI) decreases the Gini coefficient, but at higher levels of corruption, a rise in the CPI increases income inequality. Finally, the global coronavirus crisis has aggravated inequality in developed and developing countries, so it is recommended that policymakers implement political measures to reduce economic inequality and, at the same time, mitigate political polarization.
PyCantonese: Cantonese Linguistics and NLP in Python

This paper introduces PyCantonese, an open-source Python library for Cantonese linguistics and natural language processing. After the library design, implementation, corpus data format, and key datasets included are introduced, the paper provides an overview of the currently implemented functionality: stop words, handling Jyutping romanization, word segmentation, part-of-speech tagging, and parsing Cantonese text.
Do Bubbles exist in Chinese Share Markets ?

In this paper, we apply a recursive unit root test to investigate whether there are multiple bubbles in two Chinese share markets – Shanghai and Shenzhen. The method is best suited for a practical implementation with a time series and delivers a consistent date-stamping strategy for the origination and termination of multiple bubbles. Empirical results indicate that there existed six bubbles during 1990s – 2016s, when the stock price deviated from its intrinsic value based on market fundamentals. Specifically, the stock price contains the fundamentals and bubble components. The dates of the bubbles corresponded to specific events in the politics and financial markets. These findings have important economic and policy implications to recognize the cause of bubbles and take corresponding measures to reduce the impact on the real economy cause of the fluctuation of stock price. ○C 2016 IRABF All rights reserved.
Some results on η-Yamabe solitons in 3-dimensional trans-Sasakian manifold

where r is the scalar curvature of the manifold M. In 2-dimension case, the Yamabe flow is equivalent to the Ricci flow, which is defined by ∂ ∂t g(t) = −2S(g(t)), where S denotes the Ricci tensor. But in dimension > 2 the Yamabe and Ricci flows do not agree, since the Yamabe flow preserves the conformal class of the metric but the Ricci flow does not in general. A Yamabe soliton [1, 13] corresponds to self-similar solution of the Yamabe flow, is defined on a Riemannian or pseudo-Riemannian manifold (M, g) by a vector field ξ satisfying the equation 1 2 £V g = (r − λ)g, (1)
Assessment of Factors Affecting Employees' Adaptions When Using E-Office in Public Sector by AHP Method: An Empirical Study in Vietnam

The aim of the study is to identify the most prominent factors affecting the adaptation of employees when using electronic offices in state agencies, and public administration. The paper first identifies the various factors that influence employees in using the e-office by prioritizing them using the analytical hierarchical process method (AHP). AHP is a multi-criteria decision-making tool (MCDM), which combines all factors into a hierarchical model and quantitatively measures the importance of factors through pairwise comparisons. In this study, there are eleven factors that influence employees when using an e-office were identified, which are classified according to four main factors, namely employee personal characteristics, technical factor, organizational factor, and organizational factor. The findings show that organizational factors and technical factors are the two most important factors affecting employees in using electronic office systems. Furthermore, the sub-factors such as training, technical infrastructure, technical support, access speed, and computer and internet skills are the top factors that are considered important for employees in getting the job done. using electronic offices in state agencies and public administration. The research results can help organizations and state agencies to evaluate important factors in the use of electronic offices by employees more effectively.
Bias Amplification

• BA. We use nouns, verbs, adjectives, and adverbs of the top 1, 000 common words in the captions as L and calculate the co-occurrence of the gender words and the common words in the captions. As [18], we filter the words that are not strongly associated with humans by removing words that do not occur with each gender at least 100 times in the ground-truth captions, leaving a total of 290 words. • DBAG and DBAO. Let p denote the probability calculated by the (co-)occurrence. The definition of DBAG and DBAO [15] is:
A. Details on Pretrained Tokenizers

In this paper, we use the visual tokenizer of a pretrained image VQ-VAE from [2, 6], which is also called discrete VAE [6]. For DALL-E [6], the tokenizer of the VQ-VAE is trained to transform each 256 × 256 image into a 32 × 32 image token map according to a visual codebook, while the decoder of the VQ-VAE is trained to reconstruct each input image from its tokens. The vocabulary size of the visual tokens is 8192.
Supplementary Material: Physical Simulation Layer for Accurate 3D Modeling

In this work, we develop an approach to produce a physically realistic 3D content. We hope our work (or the principles behind it) will contribute in lowering the barrier to bringing the research efforts in 3D modeling to real-world fabrication. We also hope that our work will inspire more adjacent research fields, such as 3D object and scene understanding, to benefit from online physics as a rich and universal cue. However, at the same time, we note that working on generative models always bears the risk of creating false and manipulating content. Besides, like all deep neural network models, our approach requires a relatively large amount of compute and hence may have a noticeable carbon footprint.
Studies on Histones

Histones from a number of animal tissues have been shown to be divisible into three main types, which are roughly characterized according to the predominant basic residues: f 1, lysine-rich; f 2, moderately lysine-rich; f3, arginine-rich (Johns, Phillips, Simson & Butler, 1960). Preparations of these fractions from several tissues of the calf and rat showed no marked differences between similar fractions from different tissues, either in their compositions or in their starch-gel-electrophoresis patterns (Hnilica, Johns & Butler, 1962). To see if this similarity also holds with widely different species, we have examined preparations of the histones from wheat germ. A previous preparation from this source was described by Cruft, Mauritzen & Stedman (1957 b), who examined it by electrophoresis at pH 6-15 and found that, although it was heterogeneous, the principal fraction was unlike the ,B-fractions from animal tissues. However, no complete analyses were given.