Miracle-dz/UniFAR-FTUs huggingface dataset:
A Simple Chromosome Doubling Technique Is Effective for Three Species of Cupressaceae

Platycladus orientalis (L.) Franco (syn. Thuja orientalis L.), Thuja occidentalis L. , and T. plicata D. Don. are conifers often used in the landscape. Most of the available cultivars of these species share the character of having foliage that turns an off-color during winter as a result of photoinhibition. Tetraploids of the related japanese-cedar (Cryptomeria japonica (L. f.) D. Don. ) have exhibited greener color retention than diploids during winter and a recent report described a simple technique to double its chromosomes. The technique used to double the chromosome number of C. japonica was applied to the three species mentioned to determine if it would be effective for inducing polyploidy and, if so, optimal duration of treatment. Seedlings were treated at the cotyledon stage for 0 (control), 10, 20, or 30 days with an aqueous solution containing 150 mM oryzalin + 0.1% Tween20 using a standard household spray bottle that created a fine mist. No tetraploids were observed for any species in control treatments, indicating all recovered tetraploids resulted from applying oryzalin. Tetraploids were observed for all other treatments except T. plicata at 30 days. Efficacy ranged from 0% to 27.1% of transplanted seedlings being tetraploid. There was a quadratic relationship between duration oftreatment andpercenttetraploids inT. occidentalisandT.plicataand alinear relationship for P. orientalis. Based on regression analysis, the optimal duration of treatment was 20.5 days for T. occidentalis and 13.9 days for T. plicata. The highest percenttetraploidsrecoveredforP.orientaliswasat30daysanditisunclearifincreasing
Control and Cybernetics Robust Goal Programming

In the paper a new approach to goal programming is presented: the robust approach, applied so far to a single-objective linear programming. It is a ”pessimistic” approach, meant to find a solution which will be reasonably good even in a bad case, but it is based on the assumption that almost never everything goes bad the decision maker can control and simulate the pessimistic aspect of the decision situation. The pessimism refers here to uncertain coefficients in the goal functions. It is assumed that in each case only a certain number of them can take on unfavourable values but we do not know which ones. A robust solution, i.e. the one which will be good even in the most pessimistic case among those considered to be possible is determined, using only the linear programming methods.
Myoelectric activity of antagonist ankle-muscles in 6-to-8-year-old children during walking

Great co-contraction, i.e. simultaneous contraction of agonist and antagonist muscles crossing a joint, of ankle muscles during the stance phase has been identified as one of the typical features of the immature gait. The goal of the present study was the assessment of the co-contractions of tibialis anterior (TA) and gastrocnemius lateralis (GL) during walking in 20 healthy 6-to-8-year-old children, critical age for the maturation of gait. To this aim, Statistical gait analysis, a recent methodology performing a statistical characterization of gait by averaging spatial-temporal and surface-EMG-based parameters over numerous strides, was performed in each subject. Co-contractions were assessed as the period of overlap between activation intervals of TA and GL. Results showed that GL and TA act as pure antagonists for ankle plantar/dorsiflexion (no co-contractions) in only 18.7% of strides. In the remaining strides, statistically significant (p<;0.05) co-contractions were detected in early stance (45.0% of the strides), mid-stance (27.7%), pre-swing (14.6%), and swing (74.1%). The presence of all these different kinds of ankle-muscle co-contractions seems to suggest the need of a stabilizing control in children, supporting the hypothesis that a young neurocontrol system can operate on more degrees of freedom. In conclusion, the present analysis represents the first attempt for providing a quantitative assessment for ankle-muscle co-contraction in healthy 6-to-8-year-old children, in order to give further information on the maturation of gait in children.
The path so far: introducing moral education in Botswana senior secondary schools

This study investigated the classroom practices of moral education (ME) teachers in three (3) of the ten (10) Botswana senior secondary schools that are piloting the curriculum. The aim of the study was to gain insight into classroom practices and the challenges that moral education teachers face when implementing a new curriculum. Interviews and classroom observations were used to collect data from five (5) participants who were purposively sampled. The results suggest that teachers have a positive attitude towards the subject despite the challenges faced in implementing the new curriculum. This study finds that it is not always easy for moral education teachers to methodically follow a particular approach or approaches in teaching moral education, as per the expectations of the curriculum, since they are generally not sure which ones are the most appropriate. The findings of this study may be of use to curriculum planners, policy makers, teachers and researchers in education in their efforts to better understand the thinking and practices of teachers in classrooms.
Underwater Laser-based Structured Light System for one-shot 3D reconstruction

A Laser-based Structured Light System (LbSLS) has been designed to perform underwater close-range 3D reconstructions even with high turbidity conditions and outperform conventional systems. The system uses a camera and a 532 nm green laser projector. The optical technique used is based on the projection of a pattern obtained placing a Diffractive Optical Element (DOE) in front of the laser beam. In the experiments described in this manuscript, the DOE used diffracts the laser beam in 25 parallel lines providing enough information in a single camera frame to perform a 3D reconstruction.
Robotic agriculture - the future of agricultural mechanisation?

Developed agriculture needs to find new ways to improve efficiency. One approach is to utilise available information technologies in the form of more intelligent machines to reduce and target energy inputs in more effective ways than in the past. Precision Farming has shown benefits of this approach but we can now move towards a new generation of equipment. The advent of autonomous system architectures gives us the opportunity to develop a complete new range of agricultural equipment based on small smart machines that can do the right thing, in the right place, at the right time in the right way.
Facial action unit prediction under partial occlusion based on Error Weighted Cross-Correlation Model

Occlusive effect is a crucial issue that may dramatically degrade performance on facial expression recognition. As emotion recognition from facial expression is based on the entire facial feature, occlusive effect remains a challenging problem to be solved. To manage this problem, an Error Weighted Cross-Correlation Model (EWCCM) is proposed to effectively predict the facial Action Unit (AU) under partial facial occlusion from non-occluded facial regions for providing the correct AU information for emotion recognition. The Gaussian Mixture Model (GMM)-based Cross-Correlation Model (CCM) in EWCCM is first proposed not only modeling the extracted facial features but also constructing the statistical dependency among features from paired facial regions for AU prediction. The Bayesian classifier weighting scheme is then adopted to explore the contributions of the GMM-based CCMs to enhance the prediction accuracy. Experiments show that a promising result of the proposed approach can be obtained.
Bad data injection in smart grid: attack and defense mechanisms

In modern smart grid networks, the traditional power grid is empowered by technological advances in sensing, measurement, and control devices with two-way communications between the suppliers and consumers. The smart grid integration helps the power grid networks to be smarter, but it also increases the risk of attacks because of the existing obsolete cyber-infrastructure. In this article, we focus on bad data injection attacks for smart grid. The basic problem formulation is presented, and the special type of stealth attack is discussed. Then we investigate the strategies of defenders and attackers, respectively. Specifically, from the defender's perspective, an adaptive cumulative sum test is able to determine the possible existence of adversaries at the control center as quickly as possible. From the attacker's point of view, independent component analysis is employed for the attackers to make inferences through phasor observations without prior knowledge of the power grid topology. The inferred structural information can then be used to launch stealth attacks.
An utility-based job scheduling algorithm for current computing Cloud considering reliability factor

The analysis and research of power system necessitates the current computing. However, the bottleneck of current computing lies in the limited computing capacity in power system. Cloud computing's service-oriented characteristics advance a new way of service provisioning called utility based computing, which could provide powerful computing capability for current computing. However, toward the deployment of practical current computing Cloud, we encounter one challenge that the existing job scheduling algorithms under utility based computing do not take hardware/software failure and recovery in the Cloud into account. In an attempt to address this challenge, we introduce the failure and recovery scenario in the current Cloud computing entities and propose a Reinforcement Learning (RL) based algorithm to make job scheduling in the current computing Cloud fault tolerant. We carry out experimental comparison with Resource-constrained Utility Accrual algorithm (RUA), Utility Accrual Packet scheduling algorithm (UPA) and LBESA to demonstrate the feasibility of our proposed approach.
A Load-Balanced Parallel and Distributed Sorting Algorithm Implemented with PGX.D

Sorting has been one of the most challenging studied problems in different scientific researches. Although many techniques and algorithms have been proposed on the theory of having efficient parallel sorting implementation, however achieving desired performance on different types of the architectures with large number of processors is still a challenging issue. Maximizing parallelism level in applications can be achieved by minimizing overheads due to load imbalance and waiting time due to memory latencies. In this paper, we present a distributed sorting algorithm implemented in PGX. D, a fast distributed graph processing system, which outperforms the Spark's distributed sorting implementation by around 2x-3x by hiding communication latencies and minimizing unnecessary overheads. Furthermore, it shows that the proposed PGX. D sorting method handles dataset containing many duplicated data entries efficiently and always results in keeping balanced workloads for different input data distribution types.
Effect of the Supplier Heterogeneity on Knowledge Transfer between the Upstream and the Downstream Partners in the Auto Manufacturing Industry

In the auto manufacturing industry, there is high level of differences among suppliers. The principal purpose of this paper is discussing the situations of knowledge transfer between different supplier and auto makers based on the analysis of supplier heterogeneity, which can offer theoretical instruction to suppliers for their knowledge acquisition strategy in the supply chain. We construct a systemic framework, in which the importance of the component supplied by a supplier and the role of him are integrated to express the characteristic of the supplier. Further, we analyze the nature and harvest of different suppliers’ knowledge transfer with auto makers, among which we emphasize the interaction effect between importance of supplier’s components and supplier role on its knowledge transfer with auto makers.
Design of energy-efficient discrete cosine transform using pruned arithmetic circuits

Inexact circuits and approximate computing have been gaining a lot of interest in order to improve performances and energy efficiency beyond the boundaries of conventional digital circuits. Image and video processing is one of the best candidate for applying such techniques. As one of the key building blocks, Discrete Cosine Transform (DCT) accelerators are investigated using pruned arithmetic circuits. A design methodology is presented in order to optimize both image quality and circuit performances. This work demonstrates that with such technique, savings are possible not only on arithmetic units, but in the entire accelerator hardware. Simulations show up to 12 % area and 10 % power savings with less than 20 dB PSNR degradation compared to the conventional DCT design.
Turnout in the European Union: how perception of democracy in the European Union influences electoral participation

This Bachelor-Thesis, being part of a project dealing with the European elections 2009, deals with the topic of perception of democracy and electoral participation. Turnout rates show differences between national and European elections, with an average of 22,6% higher turnout for national elections in the EU member states. Why is this the case? This paper seeks to explain how the perception of a certain government (in this case the EU) might influence the decision whether to vote or not. The research question is: “What is the perception of European citizens towards the degree of democracy (democratic elements) in the European Union, and in how far does this affect the decision whether or not to vote in European Parliament elections? ” Data was collected by a survey in the Netherlands and Germany around the European elections, in total n = 727 answered questionnaires could be used. Analyzing the data shows that there in fact is a relationship between the perception of democracy and electoral participation. The more democratic the people think the EU works, the more likely they are to vote in European elections. This relationship is also tested against two different third factors, age and education, which are both being regarded as influencing the decision whether to vote or not. Although the initial relation between perception of democracy and electoral participation could not be shown for each of the categories of age and education, clear general tendencies were found. It seems likely that there actually is a relationship between what people think of the EU in democratic terms and whether they will vote or not. Nevertheless further research has to deepen and broaden the knowledge about this topic, and has to investigate further. For example similar studies could be extended to more European countries (EU members), or include more third variables to test the initial relationship.
To Add or Not to Add: Privacy and Social Honeypots

Online Social Networks (OSNs) have become a mainstream cultural phenomenon in the past years, where million of people connect to each other and share memories, digital media and business relations. Many users also publish personal information about their activities, relationships, locations and interests on these sites, seemingly unaware of how these data can be used by other parties. Sites typically attempt to restrict data-sharing to members of a user''s social network, but this is only effective if these social networks cannot be exploited by malicious users. In this paper we perform an experiment in order to assess the vulnerability and privacy awareness of users when engaging in online relations with random unknown users, or those pretending to be a famous character. We find that usually users do not accept random friendship requests, but some aggressively search for celebrities, making a perfect case for spammers to form honeypots using such fake profiles. We present a set of suggestions for enhancing privacy on social networks which could reduce the threats of identity theft in such environments.
OSR-Lite: Fast and deadlock-free NoC reconfiguration framework

Current and future on-chip networks will feature an enhanced degree of reconfigurability. Power management and virtualization strategies as well as the need to survive to the progressive onset of wear-out faults are root causes for that. In all these cases, a non-intrusive and efficient reconfiguration method is needed to allow the network to function uninterruptedly over the course of the reconfiguration process while remaining deadlock-free. This paper is inspired by the overlapped static reconfiguration (OSR) protocol developed for off-chip networks. However, in its native form its implementation in NoCs is out-of-reach. Therefore, we provide a careful engineering of the NoC switch architecture and of the system-level infrastructure to support a cost-effective, complete and transparent reconfiguration process. Performance during the reconfiguration process is not affected and implementation costs (critical path and area overhead) are proved to be fully affordable for a constrained system. Less than 250 cycles are needed for the reconfiguration process of an 8×8 2D mesh with marginal impact on system performance.
Beyond Instructional Leadership: The Lived Experiences of Principals in Successful Urban Schools

Despite national statistics that suggest declining African American and Latino student achievement, few schools accept the challenge of educating the neediest students, and even fewer succeed. This phenomenological study examined the experiences of and strategies employed by three principals of urban schools that effectively educate traditionally underserved students. Contrary to instructional leadership practices, these principals limited opportunities for teachers to share in the decision-making process regarding school operation and leadership, instead expecting teachers to concentrate on classroom instruction as the priority. Additionally, these principals focused and nurtured teachers’ personal and professional characteristics to enhance the quality of instruction at their particular schools.
A fast matrix iterative algorithm for WLS design of 2-D linear-phase FIR filters

The weighted least square (WLS) design of two-dimensional (2-D) linear-phase finite impulse response (FIR) filters with quadrantally symmetric or anti-symmetric magnitude responses is studied in this paper. Firstly, the necessary and sufficient condition for minimizing the WLS error is obtained in the form of matrix equation. Based on the matrix equation, a novel algorithm is derived for the WLS design of 2-D filters with two-valued weighting functions. Further, convergence of the algorithm is established and the computational complexity is analyzed. Because the new algorithm deals with the filter parameters in their natural 2-D form and the transition band is not sampled, the amount of computation required is reduced significantly, especially for high order cases. Finally, examples are presented to illustrate the performance of the proposed algorithm.
Generalized Alon--Boppana Theorems and Error-Correcting Codes

In this paper we describe several theorems that give lower bounds on the second eigenvalue of any quotient of a given size of a fixed graph, $G$. These theorems generalize Alon--Boppana-type theorems, where $G$ is a regular (infinite) tree. When $G$ is a hypercube, our theorems give minimum distance upper bounds on linear binary codes of a given size and information rate. Our bounds at best equal the current best bounds for codes and apply only to linear codes. However, it is of interest to note that (1) one very simple Alon--Boppana argument yields nontrivial code bound, and (2) our Alon--Boppana argument that equals a current best bound for codes has some hope of improvement. We also improve the bound in sharpest known Alon--Boppana theorem (i.e., when $G$ is a regular tree).
The must preorder revisited: an algebraic theory for web services contracts

We define a language for Web services contracts as a parallelfree fragment of ccs and we study a natural notion of compliance between clients and services in terms of their corresponding contracts. The induced contract preorder turns out to be valuable in searching and querying registries of Web services, it shows interesting connections with the must preorder, and it exhibits good precongruence properties when choreographies of Web services are considered. Our contract language may be used as a foundation of Web services technologies, such as wsdl and wscl.
Optimized JPEG image decompression with super-resolution interpolation using multi-order total variation

We propose a novel framework to obtain an artifact-free enlarged image from a given JPEG image. The proposed formulation based on a newly introduced JPEG image acquisition model realizes decompression and super-resolution interpolation simultaneously using multi-order total variation, so that we can drastically reduce artifacts appearing in JPEG images such as block noise and mosquito noise, without generating staircasing effect, which is typical in existing total variation-based JPEG decompression methods. We also present a computationally-efficient optimization scheme, derived as a special case of a primal-dual splitting type algorithm, for solving the convex optimization problem associated with the proposed formulation. Numerical examples show that the proposed method works effectively compared with existing methods.
Automatic segmentation, learning and retrieval of melodies using a self-organizing neural network

We introduce a neural network, known as SONNETMAP, capable of automatic segmentation, learning and retrieval of melodies. SONNET-MAP is a synthesis of the SONNET (Self-Organizing Neural NETwork) architecture (Nigrin, 1993) and an associative map derived from ARTMAP (Carpenter, Grossberg, and Reynolds, 1991). SONNET-MAP automatically segments a melody based on pitch and rhythmic grouping cues. Separate SONNET modules represent the pitch and rhythm dimensions of each segmented phrase independently, with two associative maps fusing these representations at the phrase level. Further SONNET modules aggregate these phrases forming a hierarchical memory structure that encompasses the entire melody. In addition, melodic queries may be used to retrieve any encoded melody. As far as we are aware, SONNET-MAP is the first self-organizing neural network architecture capable of automatically segmenting and retrieving melodies based on both pitch and rhythm.
ASAP: a transistor sizing tool for speed, area, and power optimization of static CMOS circuits

This paper introduces an automated transistor sizing tool (ASAP) that incorporates accurate gate-level functional models and can be used for delay, area, and power optimization of CMOS combinational logic circuits in a VLSI design environment. The optimization technique is based on simulated annealing and considers the performance improvement of VLSI circuits by optimally sizing the transistors on the N most critical paths. <<ETX>>
Inductive learning spatial attention

This paper investigates the automatic induction of spatial attention from the visual observation of objects manipulated on a table top. In this work, space is represented in terms of a novel observer-object relative reference system, named Local Cardinal System, defined upon the local neighbourhood of objects on the table. We present results of applying the proposed methodology on five distinct scenarios involving the construction of spatial patterns of coloured blocks.