Isothermal phase (vapour + liquid) equilibrium data for binary mixturesof propene (R1270) with either 1,1,2,3,3,3-hexafluoro-1-propene(R1216) or 2,2,3-trifluoro-3-(trifluoromethyl)oxirane in the temperature range of (279 to 318) K range.

International audienceIsothermal (vapour + liquid) equilibrium data (P–x–y) are presented for the 1-propene +1,1,2,3,3,3-hexafluoro-1-propene and the 1-propene + 2,2,3-trifluoro-3-(trifluoromethyl)oxirane binary systems. Both binary systems were studied at five temperatures, ranging from (279.36 to 318.09) K, atpressures up to 2 MPa. The experimental (vapour + liquid) equilibrium data were measured using an apparatus based on the ‘‘(static + analytic)’’ method incorporating a single movable Rapid On-Line Sampler-Injector to sample the liquid and vapour phases at equilibrium. The expanded uncertainties are approximated on average as = 0.07 K, 0.008 MPa, and 0.007 and 0.009 for the temperature, pressure, and the liquid and vapour mole fractions, respectively. A homogenous maximum-pressure azeotrope was observed for both binary systems at all temperatures studied. The experimental data were correlated with the Peng–Robinson equation of state using the Mathias–Copeman alpha function, paired with theWong–Sandler mixing rule and the Non-Random Two Liquid activity coefficient model. The model provided satisfactory representation of the phase equilibrium data measure

Efficient Real Time Recurrent Learning through combined activity and parameter sparsity

Backpropagation through time (BPTT) is the standard algorithm for training recurrent neural networks (RNNs), which requires separate simulation phases for the forward and backward passes for inference and learning, respectively. Moreover, BPTT requires storing the complete history of network states between phases, with memory consumption growing proportional to the input sequence length. This makes BPTT unsuited for online learning and presents a challenge for implementation on low-resource real-time systems. Real-Time Recurrent Learning (RTRL) allows online learning, and the growth of required memory is independent of sequence length. However, RTRL suffers from exceptionally high computational costs that grow proportional to the fourth power of the state size, making RTRL computationally intractable for all but the smallest of networks. In this work, we show that recurrent networks exhibiting high activity sparsity can reduce the computational cost of RTRL. Moreover, combining activity and parameter sparsity can lead to significant enough savings in computational and memory costs to make RTRL practical. Unlike previous work, this improvement in the efficiency of RTRL can be achieved without using any approximations for the learning process.Comment: Published as a workshop paper at ICLR 2023 Workshop on Sparsity in Neural Network

Structure, stability and stress properties of amorphous and nanostructured carbon films

Structural and mechanical properties of amorphous and nanocomposite carbon are investigated using tight-binding molecular dynamics and Monte Carlo simulations. In the case of amorphous carbon, we show that the variation of sp^3 fraction as a function of density is linear over the whole range of possible densities, and that the bulk moduli follow closely the power-law variation suggested by Thorpe. We also review earlier work pertained to the intrinsic stress state of tetrahedral amorphous carbon. In the case of nanocomposites, we show that the diamond inclusions are stable only in dense amorphous tetrahedral matrices. Their hardness is considerably higher than that of pure amorphous carbon films. Fully relaxed diamond nanocomposites possess zero average intrinsic stress.Comment: 10 pages, 6 figure

Assessment of support strategies in inclusive education in the Foundation Phase in the Umlazi District

A thesis submitted to the Faculty Of Education in fulfillment of the requirements for the Degree of Masters Of Education in the Department of Educational Psychology and Special Needs Education at the University Of Zululand, 2017It has been 16 years since the release of Education White Paper 6 however, South Africa continues to experience challenges in implementing Inclusive Education (IE) by providing support effective for learners who experience barriers to learning. Education in society is a fundamental part of our lives and IE provides the platform to achieve a unified society. The study focused on the Foundation Phase where barriers could be identified and early intervention could be provided. The aim of this study was to ascertain the nature of the support strategies employed by Foundation Phase teachers in two schools in the Umlazi District. It also aimed to establish if learners who experience barriers to learning as well as if the teachers and the school were adequately supported. It was apparent that although the department of education addressed some of the challenges by providing a policy and guidelines on the implementation of inclusive education (National Strategy on Screening, Identification, Assessment and Support (SIAS) and Guidelines for responding to learner diversity in the classroom) there was little evidence of stakeholders having knowledge of the documents or applying the recommended strategies. A mixed method design was used for this case study. The quantitative method comprised of a questionnaire constituted the initial phase of the data collection. It was then followed by the qualitative method which involved a focus group interview with selected participants. The questionnaire was completed by 21 teachers from the two schools and 5 teachers participated in the focus group interview from the first school and 8 from the second. This study established that although teachers attempted to provide support to learners that experience barriers to learning, they found these strategies to be ineffective. The pre-service in-service training that they received to address barriers to learning was ineffective and inadequate. Support networks at the schools were dysfunctional and there was confusion about the roles and responsibilities of the various support structures. Stakeholders and external support structures were ineffective and inaccessible. The lack of communication and collaboration amongst stakeholders was evident. These findings are These findings are common and consistent with discoveries from previous research. Contributions of the study are important for further research and implementation of the recommendations would assist in ensuring that learners receive quality education that can help them to be productive members of society

Energetics and stability of nanostructured amorphous carbon

Monte Carlo simulations, supplemented by ab initio calculations, shed light into the energetics and thermodynamic stability of nanostructured amorphous carbon. The interaction of the embedded nanocrystals with the host amorphous matrix is shown to determine in a large degree the stability and the relative energy differences among carbon phases. Diamonds are stable structures in matrices with sp^3 fraction over 60%. Schwarzites are stable in low-coordinated networks. Other sp^2-bonded structures are metastable.Comment: 11 pages, 7 figure

Pattern representation and recognition with accelerated analog neuromorphic systems

Despite being originally inspired by the central nervous system, artificial neural networks have diverged from their biological archetypes as they have been remodeled to fit particular tasks. In this paper, we review several possibilites to reverse map these architectures to biologically more realistic spiking networks with the aim of emulating them on fast, low-power neuromorphic hardware. Since many of these devices employ analog components, which cannot be perfectly controlled, finding ways to compensate for the resulting effects represents a key challenge. Here, we discuss three different strategies to address this problem: the addition of auxiliary network components for stabilizing activity, the utilization of inherently robust architectures and a training method for hardware-emulated networks that functions without perfect knowledge of the system's dynamics and parameters. For all three scenarios, we corroborate our theoretical considerations with experimental results on accelerated analog neuromorphic platforms.Comment: accepted at ISCAS 201

Balancing the interests of employer and employee in dismissal for misconduct

South Africa emerged from a history dogged by an oppressive system in which race was used as a medium of oppression. Workers and in particular African workers’ rights were severely curtailed. However, following the advent of the Constitution, several employees’ rights and freedoms are now entrenched key amongst them in the right to fair labour practices is enshrined in section 23 (1) of the Constitution. Post 1994, South Africa adopted various new forms of labour legislation, including the Labour Relations Act. This marked the watershed in changing the balance of power away from the employer. The LRA gives form and content to the rights enshrined in the Constitution by establishing substantive and procedural requirements prior to dismissal. Equally important is the guidelines contained in schedule 8 to the LRA which depict an attempt by the legislature to ensure that employees are protected against unfair dismissal. The historical background of the employment relationship stems from the Master and Servant Act. The common law evolved in South Africa from Roman-Dutch and English practices. The common law was shaped against the backdrop of Apartheid modified to some extent through the Wiehahn Commission4 and more recently politically through union and National Economic Development and Labour Council (NEDLAC) involvement regulating labour practices through legislation. In South Africa, the employment relationship is regulated by three main sources of law. These include the Constitution, labour legislation and the law of contract. Besides these sources, South Africa is a member state of the International Labour Organisation