Video as a mediating artefact of science learning: Cogenerated views of what helps students learn from watching video

© The Author(s). 2018“Doing” science in the form of practical work is one pedagogical approach to learning science alongside others such as talking science, writing science, reading science and representing science. However, scientific ideas cannot always be illustrated through practical work or field trips, therefore, different kinds of activities are needed to represent these ideas. This study focused on the power of cogenerative dialogues for teachers to learn about their students and their video preferences for learning science in a secondary science classroom. The analysis of the use of video as a mediating artefact drew on an interpretive approach framed as authentic participant-centered inquiry and employed multiple theoretical frameworks to generate perspectives on the affordances and constraints of learning from video. Through a cogenerative dialogue intervention we found that video could afford the learning of scientific ideas, however, some videographic features were distracting to students and constrained their learning. We argue that video clips as cultural artefacts are inscribed with emotion that structures students’ opportunities to engage with scientific ideas. However, to accept the authoritative information presented in videos as facts uncritically was a missed opportunity to shape students’ epistemological understanding that scientific knowledge is evidence-based and subject to critique. The implications for designing pedagogical approaches that encourage a critical stance to explore the ongoing social construction and communication of scientific ideas are discussed

Effect of Job Design on Employee Satisfaction (A Study of Fertilizer Companies Listed in Lahore Stock Exchange)

Human is declared as “Better” in all living creation. That is the reason behind the importance of the Human Resource whether in Business Organizations or Non-Business Organization. It is the asset which can neither be copied nor be created. In the past two decades, the importance of Human Resource becomes shinier for the organizations especially for the business sectors. Human Resource Management, now a day, is the most important area for Business Organizations and Vital Topic for the Researchers as well. Achieving target and goals, capturing new markets and niches, acquiring and selling are one dimension of success for the organization, but now organizations are putting a valuable consideration to Human Resource Management and its issues. Job Design, Job Enrichment, Job Enlargement, Employee Satisfaction and Motivation, Brain Drain, Performance and Reward are some factors which captured the attention of the organizations. This Research exist in the orbit of the topic “Effect of job design on Employee Satisfaction” and declare 6 Variables of job design which is Independent Variable and find the relation of these variables with employee satisfaction through correlation and linear regression technique. Through Questionnaire, Primary data is collected and by the use of SPSS and Excel 2007, the results are concluded that there is a strong positive correlation between Job Design and Employee Satisfaction and both of these variables move in the same direction. Keyword: Job Design, Employee Satisfaction, Fertilizer Companies, Lahore Stock Exchang

Substrate-dependent Photoconductivity Dynamics in a High-efficiency Hybrid Perovskite Alloy

Films of (FA$_{0.79}$MA$_{0.16}$Cs$_{0.05}$)$_{0.97}$Pb(I$_{0.84}$Br$_{0.16}$)$_{2.97}$ were grown over TiO$_{2}$, SnO$_{2}$, ITO, and NiO. Film conductivity was interrogated by measuring the in-phase and out-of-phase forces acting between the film and a charged microcantilever. We followed the films' conductivity vs. time, frequency, light intensity, and temperature (233 to 312 K). Perovskite conductivity was high and light-independent over ITO and NiO. Over TiO$_{2}$ and SnO$_{2}$, the conductivity was low in the dark, increased with light intensity, and persisted for 10's of seconds after the light was removed. At elevated temperature over TiO$_{2}$, the rate of conductivity recovery in the dark showed an activated temperature dependence (E$_{a}$ = 0.58 eV). Surprisingly, the light-induced conductivity over TiO$_{2}$ and SnO$_{2}$ relaxed essentially instantaneously at low temperature. We use a transmission-line model for mixed ionic-electronic conductors to show that the measurements presented are sensitive to the sum of electronic and ionic conductivities. We rationalize the seemingly incongruous observations using the idea that holes, introduced either by equilibration with the substrate or via optical irradiation, create iodide vacancies

Substrate-Dependent Photoconductivity Dynamics in a High-Efficiency Hybrid Perovskite Alloy

Films of (FA0.79MA0.16Cs0.05)0.97Pb(I0.84Br0.16)2.97 were grown over TiO2, SnO2, indium tin oxide (ITO), and NiO. Film conductivity was interrogated by measuring the in-phase and out-of-phase forces acting between the film and a charged microcantilever. We followed the films’ conductivity versus time, frequency, light intensity, and temperature (233−312 K). Perovskite conductivity was high and light-independent over ITO and NiO. Over TiO2 and SnO2, the conductivity was low in the dark,increased with light intensity, and persisted for 10’s of seconds after the light was removed. At an elevated temperature over TiO2, the rate of conductivity recovery in the dark showed an activated temperature dependence (Ea= 0.58eV). Surprisingly, the light-induced conductivity over TiO2 and SnO2 relaxed essentially instantaneously at a low temperature. We use a transmission-line model for mixed ionic−electronic conductors to show that the measurements presented are sensitive to the sum of electronic and ionic conductivities. We rationalize the seemingly incongruous observations using the idea that holes, introduced either by equilibration with the substrate or via optical irradiation, create iodide vacancies

Characterization of Histone Modifications in Late-Stage Rotator Cuff Tendinopathy

The development and progression of rotator cuff tendinopathy (RCT) is multifactorial and likely to manifest through a combination of extrinsic, intrinsic, and environmental factors, including genetics and epigenetics. However, the role of epigenetics in RCT, including the role of histone modification, is not well established. Using chromatin immunoprecipitation sequencing, differences in the trimethylation status of H3K4 and H3K27 histones in late-stage RCT compared to control were investigated in this study. For H3K4, 24 genomic loci were found to be significantly more trimethylated in RCT compared to control (p < 0.05), implicating genes such as DKK2, JAG2, and SMOC2 in RCT. For H3K27, 31 loci were shown to be more trimethylated (p < 0.05) in RCT compared to control, inferring a role for EPHA3, ROCK1, and DEFβ115. Furthermore, 14 loci were significantly less trimethylated (p < 0.05) in control compared to RCT, implicating EFNA5, GDF6, and GDF7. Finally, the TGFβ signaling, axon guidance, and regulation of focal adhesion assembly pathways were found to be enriched in RCT. These findings suggest that the development and progression of RCT is, at least in part, under epigenetic control, highlighting the influence of histone modifications in this disorder and paving the way to further understand the role of epigenome in RCT

SPARK and SAD: Leading-edge deep learning frameworks for robust and effective intrusion detection in SCADA systems

Considering SCADA systems operate and manage critical infrastructure and industrial processes, the need for robust intrusion detection systems-IDSs cannot be overemphasized. The complexity of these systems, added to their increased exposure to more sophisticated cyber-attacks, creates significant challenges for continuous, secure operations. Traditional approaches to intrusion detection usually fail to cope, scale, or be as accurate as is necessary when dealing with the modern, multi-faceted problem of an attack vector against SCADA networks and IIoT environments. Past works have generally proposed the use of different machine learning and deep learning anomaly detection strategies to find possible intrusions. While these methods have, in fact, been promising, their effects are not without their own set of problems, including high false positives, poor generalization to new types of attacks, and performance inefficiencies in large-scale data environments. In this work, against this background, two novel IDS models are put forward: SPARK (Scalable Predictive Anomaly Response Kernel) and SAD (Scented Alpine Descent), to further improve the security landscape in SCADA systems. SPARK enables an ensemble-based deep learning framework combining strategic feature extraction with adaptive learning mechanisms for volume data processing at high accuracy and efficiency. This architecture has stringent anomaly detection through a multi-layered deep network adapting to ever-evolving contexts in operational environments, allowing for low latency and high precision in the detections. The SAD model works in concert with SPARK by adopting a synergistic approach that embeds deep learning into anomaly scoring algorithms, enabled to detect subtle attack patterns and further reduce false-positive rates