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Armed forces the world over have three primary functions – force development, force deployment and force employment. Defence policy plays a guiding role in all of these, but it is especially important in establishing the rationale for the creation of credible military deterrence. Usually, a defence policy presupposes the development of armed forces that are effective at executing their mandate, a condition that is measurablein terms of the discipline, skill and quality of the organisation. The study on which this article reports, used this concept to describe how change management – especially by focusing on incorporating effective prioritisation – could enhance the current defence policy. A general analysis of South African defence policy publications indicates that, indeed, the policymakers had thoroughly considered the effectiveness of the armed forces when they wrote the White Paper on Defence of 1996 and the Defence Review of 1998. By 2006, the South African Army had interpreted national defence policy and formulated a future strategy of its own very much in alignment with the ‘modern system’ approach of the original policy publications. The present study suggests that the principal reason for the large variance between defence policy, military capabilities, and real operational demands stems from the lack of effective prioritisation of defence. This article, therefore, concludes that the South African National Defence Force (SANDF) has been largely unsuccessful in complying with the demands of defence policy, irrespective of the fact that the policy by itselfmay be obsolete and/or inappropriate for the South African context. Furthermore, it is concluded that military effectiveness in meeting current operational demands is also doubtful. Finally, the schizophrenic organisational culture of the defence force may be the primary cause of its moving ever closer to reneging on its constitutional mandate.

Voltage notches are steady-state sub-cycle waveform distortions caused by the normal operation of line-commutated power converters, significantly impacting power quality in industrial low-voltage (LV) networks. Despite their common occurrence, research on this phenomenon is still incipient, and realistic simulation platforms are lacking. This paper introduces a detailed MATLAB (R2024a)/Simulink-based simulation platform that models a benchmark low-voltage industrial installation, including a six-pulse controlled rectifier, linear loads, and a capacitor bank for power factor correction. Systematic simulations are performed with the platform to examine the sensitivity of notch characteristics to key parameters within plausible ranges, such as short-circuit power at the point of common coupling, commutation reactance, firing angle, snubber circuits, and rated power of the rectifier. In addition, parameters such as the rated power of linear loads and the compensation power of the capacitor bank are examined. Other influencing parameters including background voltage unbalance and distortion are also modeled and considered. A comparative analysis with field measurements from German industrial LV networks validates the plausibility and suitability of the simulations. Building upon this platform, a Monte Carlo simulation approach is adopted to generate extensive datasets of realistic voltage notch waveforms by randomly varying these key parameters. A case study conducted under conditions typical of German LV networks demonstrates the applicability of the simulations. To support further research, the simulation platform and exemplary synthetic waveforms are provided alongside the paper, serving as a valuable tool for testing and designing strategies for analysis, detection, and monitoring of voltage notches. [ABSTRACT FROM AUTHOR]

Highlights: A python-based tool called DL-SCAN for automated cell segmentation and thorough analysis of fluorescence microscopy image data. A user-friendly interface with several pre- and post-processing options to streamline the analysis workflow. Single- and multi-cell analysis options. DL-SCAN provides valid segmentation results on both synthetic and real biological data. DL-SCAN tracks changes in cells' morphology over time in response to pathological events such as ischemia. DL-SCAN generates a range of statistics, such as rise time, rise rate, decay time, decay rate, duration, and amplitude of time traces with a few clicks. With the recent surge in the development of highly selective probes, fluorescence microscopy has become one of the most widely used approaches to studying cellular properties and signaling in living cells and tissues. Traditionally, microscopy image analysis heavily relies on manufacturer-supplied software, which often demands extensive training and lacks automation capabilities for handling diverse datasets. A critical challenge arises if the fluorophores employed exhibit low brightness and a low signal-to-noise ratio (SNR). Consequently, manual intervention may become a necessity, introducing variability in the analysis outcomes even for identical samples when analyzed by different users. This leads to the incorporation of blinded analysis, which ensures that the outcome is free from user bias to a certain extent but is extremely time-consuming. To overcome these issues, we developed a tool called DL-SCAN that automatically segments and analyzes fluorophore-stained regions of interest such as cell bodies in fluorescence microscopy images using deep learning. We demonstrate the program's ability to automate cell identification and study cellular ion dynamics using synthetic image stacks with varying SNR. This is followed by its application to experimental Na+ and Ca2+ imaging data from neurons and astrocytes in mouse brain tissue slices exposed to transient chemical ischemia. The results from DL-SCAN are consistent, reproducible, and free from user bias, allowing efficient and rapid analysis of experimental data in an objective manner. The open-source nature of the tool also provides room for modification and extension to analyze other forms of microscopy images specific to the dynamics of different ions in other cell types. [ABSTRACT FROM AUTHOR]

We report a method for serial X-ray crystallography at X-ray free-electron lasers (XFELs), which allows for full use of the current 120-Hz repetition rate of the Linear Coherent Light Source (LCLS). Using a micropatterned silicon chip in combination with the high-speed Roadrunner goniometer for sample delivery, we were able to determine the crystal structures of the picornavirus bovine enterovirus 2 (BEV2) and the cytoplasmic polyhedrosis virus type 18 polyhedrin, with total data collection times of less than 14 and 10 min, respectively. Our method requires only micrograms of sample and should therefore broaden the applicability of serial femtosecond crystallography to challenging projects for which only limited sample amounts are available. By synchronizing the sample exchange to the XFEL repetition rate, our method allows for most efficient use of the limited beam time available at XFELs and should enable a substantial increase in sample throughput at these facilities.

An accurate self-assessment of student work can enhance student learning and subsequently improve academic performance. Instructors can facilitate this process by providing "standards" that students can utilize as feedback when self-evaluating their understanding. Traditional forms of feedback, such as marked assessment tasks, are limited in their ability to serve as standards, as they do not adequately capture variations corresponding to different levels of understanding. To develop a complex understanding in physiology, students have to integrate concepts pertaining to different subcomponents of body systems. The present study attempted to ascertain if exposing students to variations in complexity would refine their ability to self-evaluate their understanding and capacity to integrate concepts. Students were tasked to answer an essay-length, open-ended physiology question to expose their current understanding of the topic. The change in students' self-marking of their answer before and after being exposed to the variations in conceptual understanding of the topic were used to determine whether improvements in self-evaluation accuracy occurred. These variations were presented as instructor-generated answers to the open-ended question, framed using the structure of the observed learning outcome (SOLO) taxonomy. Student scores in the integrative questions of the end-of-semester exam were used as a measure of student ability to integrate concepts. Findings indicated that this intervention led to improvements in student self-evaluation and exam performance, and the positive outcomes were replicated across multiple iterations of the activity.

The growth of renewables in public energy networks requires suitable strategies to assess the stable operation of the respective power electronic devices, e.g., inverters. Different assessment methods can be performed with regard to the available knowledge and the assessment objective, e.g., a specific frequency range or the input signal characteristics that are typically classified into small-signal and large-signal disturbances. This paper addresses the limits of the measurement-based small-signal stability analysis in the harmonic frequency range of commercially available single-phase inverters for photovoltaic applications. The harmonic stability is analyzed, and the results for a sinusoidal background voltage and distorted background voltages are assessed based on measurements. The measurements prove that even in the harmonic frequency range, the harmonic stability analysis can only provide a sufficient but not a necessary condition in terms of the statement towards an instable operation. [ABSTRACT FROM AUTHOR]

Despite growing applications of social and healthcare marketing to enhance public well-being through anti-stigma campaigns, little research investigates how public stigma surrounding health conditions might limit the outcomes of these campaigns. By drawing on the theory of implicit worldviews, this study identifies reasons for public stigma as well as associated message frames to address these reasons. Study 1a provides evidence that implicit worldviews are relevant to campaign results. Study 1b and Study 2 demonstrate that fitting consumers' implicit worldview with suitable (i.e., biomedical or biopsychosocial) health frames reduces stigma endorsement. Study 3 identifies the perceived severity of a mental illness as a boundary condition; marketing communications have the greatest impact when they refer to an illness with lower perceived severity. Finally, Study 4 expands understanding of the phenomenon by extending the findings to physical health conditions (i.e., obesity). The article concludes by discussing the implications of these findings for policy and future applications., Author(s): Jan-Hinrich Meyer [sup.1] , Ko De Ruyter [sup.2] [sup.3] , Dhruv Grewal [sup.4] , Kathleen Cleeren [sup.5] , Debbie Isobel Keeling [sup.6] , Scott Motyka [sup.7] Author Affiliations: (1) [...]

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The Threshold Capability Integrated Theoretical Framework (TCITF) is presented as a framework for the design of university curricula, aimed at developing graduates' capability to deal with previously unseen situations in their professional, social, and personal lives. The TCITF is a new theoretical framework derived from, and heavily dependent upon, the ideas of the Threshold Concepts Framework (Meyer and Land 2003a; Land et al. 2006) and Capability Theory (Bowden and Marton 1998; Bowden et al. 2000; Bowden 2004). Capability theory is firmly based in phenomenography and variation theory, is concerned with the development of knowledge capability, but has had limited application in practice. The threshold concepts framework has enjoyed greater acceptance by a large range of academics in many fields. This acceptance has initially focussed on analytic studies of what constitutes a threshold concept--and the location and distribution of such concepts--in a given domain. In many instances subsequent attention has focussed on issues of pedagogy and assessment, including the design of curricula. We propose a merging of capability theory and the threshold concepts framework and argue that capability and variation theories provide the ideal mechanism for developing a strong pedagogical approach based on newly emerging knowledge of the critical features of threshold concepts within different domains.

The present study aims to analyse the complex relationships between the relevant constructs of students' demographic background, perceptions, learning patterns and (proxy measures of) learning outcomes in order to delineate the possible direct, indirect, or spurious effects among them. The analytical methodology is substantively framed against the studies of Richardson (British Journal of Educational Psychology 76:867-893, "2006", Higher Education 54:385-416, "2007") that utilised a regression-based methodology to infer the possible causal relationships among the relevant learning constructs. A composite research instrument, written in Chinese and derived from the Inventory of Learning Styles (ILS) and the Course Experience Questionnaire (CEQ), was used to collect students' feedback on their perceptions of the learning environment and their learning patterns. Valid responses were obtained from 1,572 students studying at six institutions in the post-secondary education sector in Hong Kong, a new response-context for both the CEQ and the ILS. In adapting the research instruments to a new Chinese response-context, the findings are generally consistent with those reported in other published works (e.g. no relationship between students' demographic background and their satisfaction with the programme, and a significant relationship between students' exhibition of undirected learning patterns and low expected performance), but there are also some noteworthy discrepancies. The findings therefore buttress the confidence with which an ILS-based General Theoretical Model of student learning, adapted from Richardson (British Journal of Educational Psychology 76:867-893, "2006", Higher Education 54:385-416, "2007"), may be used to conceptualise and interpret the dynamics of variation across different cultural response-contexts. While the CEQ provides some valuable complementary insights, it is an instrument that requires further development in the response-context of the present study.