Miracle-dz/UniFAR-FTUs huggingface dataset:
ECOS: An SOCP solver for embedded systems

In this paper, we describe the embedded conic solver (ECOS), an interior-point solver for second-order cone programming (SOCP) designed specifically for embedded applications. ECOS is written in low footprint, single-threaded, library-free ANSI-C and so runs on most embedded platforms. The main interior-point algorithm is a standard primal-dual Mehrotra predictor-corrector method with Nesterov-Todd scaling and self-dual embedding, with search directions found via a symmetric indefinite KKT system, chosen to allow stable factorization with a fixed pivoting order. The indefinite system is solved using Davis' SparseLDL package, which we modify by adding dynamic regularization and iterative refinement for stability and reliability, as is done in the CVXGEN code generation system, allowing us to avoid all numerical pivoting; the elimination ordering is found entirely symbolically. This keeps the solver simple, only 750 lines of code, with virtually no variation in run time. For small problems, ECOS is faster than most existing SOCP solvers; it is still competitive for medium-sized problems up to tens of thousands of variables.
Building and Exploring Dynamic Topic Models on the Web

Topic modeling is a machine learning technique that identifies latent topics in a text corpus. There are several existing tools that allow end-users to create and explore topic models using graphical user interfaces. In this paper, we present a visual analytics system for dynamic topic models that goes beyond the existing breed of tools. First, it decouples the Web-based user interface from the underlying data sets, enabling exploration of arbitrary text data sets in the Web browser. Second, it allows users to explore dynamic topic models, while existing tools are often limited to static topic models. Finally, it comes with a tool server in the backend that allows the design and execution of scientific workflows to build topic models from any data source. The system is demonstrated by building and exploring a dynamic topic model of CIKM proceedings published since 2001.
Brief Report: Child Sexual Abuse Inquiries in Hong Kong, 2000–2017

Abstract Community advocates in Hong Kong found no formal curriculum on child sexual abuse (CSA) prevention and started a newspaper column in 1999 to disseminate public education. This study analyzed the inquiries sent to this prevention column from 2000 to 2017. Content analysis found that, in 515 inquiries, 170 (33%) reported CSA incidents. Based on age information in 147 incidents, female abusers (n = 28) targeted victims averaging 6.48 years of age, which is 3.08 years significantly younger than those abused by male abusers (n = 119). In 82 inquiries with abusers’ age information, 42 minor “abusers” were reported. Early sex education is highly recommended.
TRAINED FUZZY NEURAL NETWORK WEIGHTS BACKTRACKING ALGORITHM FUZZIFIED DATA SET FAM BANK REDUNDANT AND CONFLICTING FUZZY

Fuzzy neural networks (FNNs) provide a new approach for classification of multispectral data and to extract and optimize classification rules. Neural networks deal with issues on a numeric level, whereas fuzzy logic deals with them on a semantic or linguistic level. FNNs synthesize fuzzy logic and neural networks. Recently, there has been growing interest in the research community not only to understand how FNNs arrive at particular decisions but how to decode information stored in the form of connection strengths in the network. In this paper, we propose fuzzy neural network models for classification of pixels in multispectral images and to extract fuzzy classification rules. During the training phase, the connection strengths are updated. After training, classification rules are extracted by backtracking along the weighted paths through the FNN. The extracted rules are then optimized using a fuzzy associative memory (FAM) bank. The data mining system described above is useful in many practical applications such as mapping, monitoring and managing our planet’s resources and health, climate change impacts and assessments, environmental change detection and military reconnaissance.
ECM Inspired Coating of Embroidered 3D Scaffolds Enhances Calvaria Bone Regeneration

Resorbable polymeric implants and surface coatings are an emerging technology to treat bone defects and increase bone formation. This approach is of special interest in anatomical regions like the calvaria since adults lose the capacity to heal large calvarial defects. The present study assesses the potential of extracellular matrix inspired, embroidered polycaprolactone-co-lactide (PCL) scaffolds for the treatment of 13 mm full thickness calvarial bone defects in rabbits. Moreover the influence of a collagen/chondroitin sulfate (coll I/cs) coating of PCL scaffolds was evaluated. Defect areas filled with autologous bone and empty defects served as reference. The healing process was monitored over 6 months by combining a novel ultrasonographic method, radiographic imaging, biomechanical testing, and histology. The PCL coll I/cs treated group reached 68% new bone volume compared to the autologous group (100%) and the biomechanical stability of the defect area was similar to that of the gold standard. Histological investigations revealed a significantly more homogenous bone distribution over the whole defect area in the PCL coll I/cs group compared to the noncoated group. The bioactive, coll I/cs coated, highly porous, 3-dimensional PCL scaffold acted as a guide rail for new skull bone formation along and into the implant.
Frequency of Alleles Conferring Resistance to Bt Cotton in North Zone Populations of the Spotted Bollworm, Earias insulana (Boisduval)

Transgenic Bt cotton with insect resistance was introduced for commercial cultivation in India in 2002 (Barwale et al. 2004). Bt cotton expressing Cry1Ac is mainly toxic to the bollworm complex (Helicoverpa armigera, Pectinophora gossypiella, Earias insulana and E. vittella). The rapid adoption of Bt cotton technology in India imposes a strong selection pressure on the target pest with a risk of resistance development to Cry toxins including Cry2Ab following the introduction of dual gene BG-II cotton in 2006. Spotted bollworm, Earias insulana infests the cotton crop during the early season as a shoot borer and damages fruiting bodies during mid-season crop growth. Efficacy of Bt cotton hybrids BG-II (Cry1Ac + Cry2Ab) and Bt (Cry1Ac) through leaf (90–95-day-old crop) and square (80–85-day-old crop) bioassay under laboratory conditions, recorded 97–100 % mortality on leaves of BG-II, 93 % on Bt and 1.3–5.4 % on non Bt against 1-day-old larvae of Earias insulana. Observed mortalities on plant squares were 94–100 % in BG-II, 91 % in Bt and 1.3–5.6 % in non-Bt genotypes. Frequency of resistance alleles in field populations of Earias insulana to Cry1Ac protein by using F2 screening procedure was also undertaken. In the present study on F2 screening on 266 isofemale lines of Earias insulana collected from Sirsa (Haryana), Sriganganagar (Rajasthan) and Mansa (Punjab) during 2013–14, 2014–15 and 2015–16, no alleles could be detected conferring major resistance to Cry1Ac in the population of Earias insulana from all three locations. However, evidence for partial resistance alleles in F2 generation of two isofemale lines from Sirsa (Haryana) population was recorded during 2013 but could not be reconfirmed.
Breast Cancer Cells through Induction of Bax Conformational Change in Human Epothilone B Analogue ( BMS-247550 )-mediated Cytotoxicity

Epothilone B is a novel nontaxane antimicrotubule agent that is active even against paclitaxel (Taxol)-resistant cancer cells. The present study further explores the mechanisms underlying epothilone B-mediated cytotoxicity in human breast cancer cells. We show that BMS-247550 (EpoB), a novel epothilone B analogue, induces cell cycle arrest at the G2-M phase transition and subsequent apoptotic cell death of MDA-MB-468 (468) cells. Treating cells with EpoB triggers a conformational change in the Bax protein and its translocation from the cytosol to the mitochondria, which is accompanied by cytochrome c release from the inter-membrane space of mitochondria into the cytosol. Overexpression of Bcl-2 delays Bax conformational change, cytochrome c release, and apoptosis induced by EpoB. Conversely, the Bcl-2 antagonist Bak-BH3 peptide or HA14-1 compound abrogates the antiapoptotic effects of Bcl-2 and enhances apoptosis of 468 cells pretreated with EpoB (to induce mitotic arrest). In synchronized 468 cells, EpoB is more potent in inducing Bax conformational change and apoptosis at G2-M phase compared with G1-S phase of the cell cycle. Taken together, these findings demonstrate that EpoB induces apoptosis through a Bcl-2-suppressible pathway that controls a conformational change of the proapoptotic Bax protein. The enhanced cytotoxicity of EpoB by blocking Bcl-2 at mitochondria implies a potential application of the combination of EpoB and Bcl-2 antagonists in the treatment of human breast cancer.
Towards Tangible Work Modelling

Digital Montessori-inspired Manipulatives (MiMs), so far have been used effectively for knowledge transfer in elementary educational settings. For work modelling and task-based interactive systems design we propose a modelling concept and usage scenario that should help to increase effectiveness in organization and technology development. The Tangible Task Modelling Demonstrator (TTMD) facilitates the representation and development of work and task models by means of MiMs. Using the TTMD users can directly grasp and manipulate work tasks. As a result, the cognitive load for modelling and (re-)arranging elements of work spaces can be reduced.
Multi-objective Differential Evolution Based Optimization of Risk Budgeted Global Asset Allocation Portfolios

The Risk Budgeted Global Asset Allocation Portfolio problem strives to obtain an optimal portfolio of assets across global markets, with the objective of maximizing its Sharpe Ratio, subject to the constraints of risk budgets and other specific conditions imposed by the investors on the various asset classes comprising the portfolio. The mathematical formulation of the optimization problem turns out to be a Single objective Non linear Constrained Fractional Programming model, with the risk budgets contributing to the non linearity of the problem and Sharpe Ratio objective, to the Fractional Programming aspect of the problem. In the absence of analytical methods to solve an unexplored problem of such a nature, an attempt was made earlier to solve the problem using conventional Differential Evolution by employing Joines and Houcke's Dynamic Penalty Function Strategy. However, with the increasing popularity of employing multi-objective optimization concepts to tackle non linear constraints in single objective optimization problems, this work attempts to solve the problem concerned using a Multi-objective Differential Evolution algorithm and compare the same with its predecessor. The performance analysis of the two competing methods over the characteristics of consistency of performance and convergence, have been experimented over a realistic global asset allocation portfolio.
Face Recognition Based on Projection Map and Fourier Transform for One Training Image Per Person

—At present there are many methods that could deal well with frontal view face recognition when there is sufficient number of representative training samples. However, few of them can work well when only one training sample per person is available. In this paper, we present a method of face recognition based on projection map and Fourier Transform to solve the one training sample problem. To acquire more information from the single training sample, each original training image is linearly combined with its projection map into a new training image. By using Fourier transform, the Fourier spectrum of face image is obtained that is invariant against spatial translation. The L1 distance classifier is adopted in recognition. The proposed algorithm obtains acceptable experimental results on the ORL face database.
MACHIAVELLIANISM AND PERSONAL TRAITS IN YOUNG AGE

The article is devoted to one of the vital problems of modern society, the problem of Machiavellianism. It is noted that manipulative forms of interaction between people become common, and it can lead to a tendency to use the manipulation by an increasing number of people and, in its turn, to the loss of openness, sincerity, and congruence of communication. The results of an empirical study of Machiavellianism and its interrelationship with personality traits in young age are discussed. The study is based on a dispositional approach to the person, suggesting that it consists of reliable, stable, interrelated elements (properties, traits) that determine its internal essence and behavior. Differences in the behavior of people are explained by the differences in the intensity of personality traits. The article shows that adolescence is one of the most sensitive ways to consolidate manipulative strategies in the behavior of a person. The obtained results prove the existence of a interrelationship between Machiavellianism and a number of personality traits, according to the theory of R. B. Cattell. Among such personality traits are communicative (closed), regulative (low normative, low self-control behavior), emotional (rigidity) and intellectual (radicalism). Knowledge of the personal profile of a personality prone to Machiavellianism in adolescence will allow continuing the study within the framework of studying ways of preventing extreme manifestations of manipulative behavior and widening the range of constructive patterns of youth behavior.
A Small Universal Petri Net

A universal deterministic inhibitor Petri net with 14 places, 29 transitions and 138 arcs was constructed via simulation of Neary and Woods' weakly universal Turing machine with 2 states and 4 symbols; the total time complexity is exponential in the running time of their weak machine. To simulate the blank words of the weakly universal Turing machine, a couple of dedicated transitions insert their codes when reaching edges of the working zone. To complete a chain of a given Petri net encoding to be executed by the universal Petri net, a translation of a bi-tag system into a Turing machine was constructed. The constructed Petri net is universal in the standard sense; a weaker form of universality for Petri nets was not introduced in this work.
Advanced Thermal-Moisture Analogy Scheme for Anisothermal Moisture Diffusion Problem

We propose an advanced thermal-moisture analogy scheme to cope with the inherent limitations of the existing analogy schemes. The new scheme is based on the experimentally observed unique hygroscopic behavior of polymeric materials used in microelectronics; i.e., the saturated concentration is only a function of relative humidity regardless of temperature. A new analogy formulation based on the modified solubility is presented and the scheme is implemented to investigate its accuracy and applicability. The results from a simple case study corroborate that the advanced scheme can be used effectively for package assemblies subjected to general anisothermal loading conditions.
A Monoclonal Antibody against a Human B Lymphoblastoid Cell Line Induces Tumor Regression in Mice 1

We have developed a monoclonal antibody (BAT) to Daudi B lympho blastold cell line membranes. The antibody was selected for Its abifity to stimulate lymphocyte proliferation. Splenocytes of BALBIC or C57BL mice given LV. Injections of 10 pg/mouse of BAT exhibited increased proliferation and cytotoxic activity. A single @v. administration of BAT monodonal antibody 2 weeks after B16 melanoma cell inoculation re suited in a strlldng antitumor effect as manifested by the elimination of lung metastases and prolonged survival of the treated mice BAT mono clonal antibody was also effective in the regression of tumors in mice bearing 3LL (Lewis lung carcinoma) and MCA-lO5 (flbrosarcoma). Transfer of 1O@â€”1O@ splenocytes from mice that had been given injections of BAT to B16or 3LL-inoculated recipients led to a reduction of lung metastases. Splenocytes from B16-inoculated mice that were cured by BAT were more effective than those from mice treated with BAT alone against red@ts bearing either B16 or 3LL tumors. The antitumor activity of BAT Is related to its immunostimulatory properties.
Path Planner for Objects, Robots and Mannequins by Multi-Agents Systems or Motion Captures

In order to optimise the costs and time of design of the new products while improving their quality, concurrent engineering is based on the digital model of these products. However, in order to be able to avoid definitively physical model without loss of information, new tools must be available. Especially, a tool making it possible to check simply and quickly the maintainability of complex mechanical sets using the numerical model is necessary. Since one decade, the MCM team of IRCCyN works on the creation of tools for the generation and the analysis of trajectories of virtual mannequins. The simulation of human tasks can be carried out either by robot-like simulation or by simulation by motion capture. This paper presents some results on the both two methods. The first method is based on a multi-agent system and on a digital mock-up technology, to assess an efficient path planner for a manikin or a robot for access and visibility task taking into account ergonomic constraints or joint limits. The human operator is integrated in the process optimisation to contribute to a global perception of the environment. This operator cooperates, in real-time, with several automatic local elementary agents. In the second method, we worked with the CEA and EADS/CCR to solve the constraints related to the evolution of human virtual in its environment on the basis of data resulting from motion capture system. An approach using of the virtual guides was developed to allow to the user the realization of precise trajectory in absence of force feedback.
Fuzzy assessment model for operative groups in virtual educational forums

This research consisted in applying the Fuzzy COPPE-Cosenza Hierarchy Model to assess student's and group's performance, using virtual discussion forum to achieve an educational task. The work brings up concepts from Pichon-Rivière's Operative Groups technique. It uses the software CQMsg - Messages Classifier and Qualifier for messages assessment and it applies, for the first time in education, COPPE-Cosenza Fuzzy Hierarchy Model, which has been successful in other areas. After analysis, results suggest that COPPE-Cosenza Fuzzy Hierarchy Model may support formative assessment for educational operative groups using a virtual discussion forum.
A Massively Parallel Algorithm for Polyline Simplification Using an Associative Computing Model

- Line simplification is a process of reducing the number of line segments to represent a polyline. This reduction in the number of line segments and vertices can improve the performance of spatial analysis applications. The classic Douglas-Peucker algorithm developed in 1973 has a complexity of O(mn), where n denotes the number of vertices and m the number of line segments. Its enhanced version proposed in 1992 has a complexity of O(nlogn). In this paper, we present a parallel line simplification algorithm using a parallel Multiple-instruction-stream Associative Computing model (MASC). Using one instruction stream of the MASC model, our algorithm has a parallel complexity of O(n) in the worst case using n processing elements.
Social Network based community Users' Viscosity enhanced model

Users' Viscosity is the key to the success of community application, how to improve the Users' Viscosity as much as possible is the challenge that researchers have to face. In the paper, we propose a Social Network based community Users' Viscosity enhanced model. In the model we divide the big social network into small social networks and introduce the competition mechanism among them, the number of members, the degree of Activity and Contribution of them is used to compute the live value of the small social network. Simulating experiments prove that the model can make the small social networks become more prosperous, thus it can improve the viscosity of community users.
A computational study of the aerodynamic forces and power requirements of dragonfly (Aeschna juncea) hovering

SUMMARY Aerodynamic force generation and mechanical power requirements of a dragonfly (Aeschna juncea) in hovering flight are studied. The method of numerically solving the Navier–Stokes equations in moving overset grids is used. When the midstroke angles of attack in the downstroke and the upstroke are set to 52° and 8°, respectively (these values are close to those observed), the mean vertical force equals the insect weight, and the mean thrust is approximately zero. There are two large vertical force peaks in one flapping cycle. One is in the first half of the cycle, which is mainly due to the hindwings in their downstroke; the other is in the second half of the cycle, which is mainly due to the forewings in their downstroke. Hovering with a large stroke plane angle (52°), the dragonfly uses drag as a major source for its weight-supporting force (approximately 65% of the total vertical force is contributed by the drag and 35% by the lift of the wings). The vertical force coefficient of a wing is twice as large as the quasi-steady value. The interaction between the fore- and hindwings is not very strong and is detrimental to the vertical force generation. Compared with the case of a single wing in the same motion, the interaction effect reduces the vertical forces on the fore- and hindwings by 14% and 16%, respectively, of that of the corresponding single wing. The large vertical force is due to the unsteady flow effects. The mechanism of the unsteady force is that in each downstroke of the hindwing or the forewing, a new vortex ring containing downward momentum is generated, giving an upward force. The body-mass-specific power is 37 W kg-1, which is mainly contributed by the aerodynamic power.
Book Review: Feminist Judgments of Aotearoa New Zealand Te Rino: A Two-Stranded Rope

funding, time limits and counselling; and on the other, there is diversion through promotion of sex education and contraception. This, Miller argues, obfuscates the fact that individual women choose to have abortions and it will always be required regardless of restrictions or diversions. In the conclusion, Miller advocates for a rethink of pro-choice politics and scholarship. She argues that there are multiple pregnancy subjectivities. By disrupting the rhetoric behind choice and motherhood as a placeholder, of the foetus as an autonomous subject with varying value based on race and class, abortion can be depoliticized and emotional scripts can be disposed of. When there is no fixed norm, shame and guilt could disappear from the affective landscape of abortion. Miller highlights various unapologetic narratives, such as #shoutyourabortion, which began to challenge these normative assumptions and emotional inevitabilities. With pregnancy viewed as a subjective condition, women can have the freedom to respond to it as they need. Abortion can be an ‘occasion for happiness or hope just as easily and legitimately as grief or sadness’ (p. 280). This book encourages its readers to interrogate assumptions that are made when arguing for abortion access. Miller reveals the various ways that arguments used pragmatically to bridge the gap between ideologies, or in a common-sense way, may lead to a reification of normative femininity and motherhood. Her arguments about the perpetuation of shame and guilt through arguments for interventions, such as sex education and contraception, was an important demonstration of this. Australia was a great case study as the book had plenty of real-world examples and debates. This book did focus on the Anglosphere, so it would be interesting to see whether these dynamics were reflected in the Global South, or places where abortion access continues to be restricted.