Scanning Electron Microscopy Studies of Extended Defects in Semiconductors

Extended defects, such as dislocations and grain boundaries, play an important role in determining the performance of various semiconductor devices. This paper reviews applications of electron-beam-induced-current and cathodoluminescence scanning electron microscopy for the investigation of dislocations and grain boundaries in semiconductors. We developed a simple analytical method for the determination of the grain boundary recombination velocity and the minority carrier diffusion length, in contrast to a previous method which requires the use of a computer for the numerical calculation of an integral expression. We, also, studied theoretically the influence of an individual dislocation on the minority carrier lifetime. Investigation of dislocations in GaP indicated that the carrier recombination takes place at a Cottrell atmosphere of the S-donor/Cu complexes surrounding the dislocations

Synergistic Gravity and the Role of Resonances in GRS-Inspired Braneworlds

We consider 5D braneworld models of quasi-localized gravity in which 4D gravity is reproduced at intermediate scales while the extra dimension opens up at both the very short and the very long distances, where the geometry is flat. Our main interest is the interplay between the zero mode of these models, whenever a normalizable zero mode exists, and the effects of zero energy graviton resonant modes coming from the contributions of massive KK modes. We first consider a compactified version of the GRS model and find that quasi-localized gravity is characterized by a scale for which both the resonance and the zero mode have significant contribution to 4D gravity. Above this scale, gravity is primarily mediated by the zero mode, while the resonance gives only minor corrections. Next, we consider an asymmetric version of the standard non-compact GRS model, characterized by different cosmological constants on each AdS side. We show that a resonance is present but the asymmetry, through the form of the localizing potential, can weaken it, resulting in a shorter lifetime and, thus, in a shorter distance scale for 4D gravity. As a third model exhibiting quasi-localization, we consider a version of the GRS model in which the central positive tension brane has been replaced by a configuration of a scalar field propagating in the bulk.Comment: 18 pages, 3 figures, added 1 figure, revised version as published in Class. Quant. Gra

Twice-Exceptional Students of Mathematics in England: What Do the Teachers Know?

Although they have the potential to excel, twice-exceptional (2e) students of mathematics do not usually have this opportunity as their special educational abilities, and special needs, are often misdiagnosed or “missed” diagnosed in schools due to the teachers’ lack of knowledge. The study explored this issue using an electronic survey for primary school teachers in four local authorities in England. It was planned as a pilot study to gather insights from a small number of schools aiming to identify areas for further study and larger-scale research. When comparing responses from teachers with gifted-related training and those without, the study found some knowledge of specific types of 2e students among both groups of teachers, but no significant difference between them. This raised concerns about the effectiveness of the training, as well as identifying areas that need further and more systematic research

Altered cross-frequency coupling in resting-state MEG after mild traumatic brain injury

Cross-frequency coupling (CFC) is thought to represent a basic mechanism of functional integration of neural networks across distant brain regions. In this study, we analyzed CFC profiles from resting state Magnetoencephalographic (MEG) recordings obtained from 30 mild traumatic brain injury (mTBI) patients and 50 controls. We used mutual information (MI) to quantify the phase-to-amplitude coupling (PAC) of activity among the recording sensors in six nonoverlapping frequency bands. After forming the CFC-based functional connectivity graphs, we employed a tensor representation and tensor subspace analysis to identify the optimal set of features for subject classification as mTBI or control. Our results showed that controls formed a dense network of stronger local and global connections indicating higher functional integration compared to mTBI patients. Furthermore, mTBI patients could be separated from controls with more than 90% classification accuracy. These findings indicate that analysis of brain networks computed from resting-state MEG with PAC and tensorial representation of connectivity profiles may provide a valuable biomarker for the diagnosis of mTBI

From Theory to Action: Developing and Evaluating Learning Analyticsfor Learning Design

Producción CientíficaThe effectiveness of using learning analytics for learning design primarily depends upon two concepts: grounding and alignment. This is the primary conjecture for the study described in this paper. In our design-based research study, we design, test, and evaluate teacher-facing learning analytics for an online inquiry science unit on global climate change. We design our learning analytics in accordance with a socioconstructivism-based pedagogical framework, called Knowledge Integration, and the principles of learning analytics Implementation Design. Our methodology for the design process draws upon the principle of the Orchestrating for Learning Analytics framework to engage stakeholders (i.e. teachers, researchers, and developers). The resulting learning analytics were aligned to unit activities that engaged students in key aspects of the knowledge integration process. They provided teachers with actionable insight into their students' understanding at critical junctures in the learning process. We demonstrate the efficacy of the learning analytics in supporting the optimization of the unit's learning design. We conclude by synthesizing the principles that guided our design process into a framework for developing and evaluating learning analytics for learning design.Ministerio de Ciencia, Innovación y Universidades (Project TIN2017-85179-C3-2-R)Junta de Castilla y León (project VA257P18) by the European Commission under project grant 588438-EPP-1-2017-1-EL-EPPKA2-KA

Reconfiguration of dominant coupling modes in mild traumatic brain injury mediated by δ-band activity: a resting state MEG study

During the last few years, rich-club (RC) organization has been studied as a possible brain-connectivity organization model for large-scale brain networks. At the same time, empirical and simulated data of neurophysiological models have demonstrated the significant role of intra-frequency and inter-frequency coupling among distinct brain areas. The current study investigates further the importance of these couplings using recordings of resting-state magnetoencephalographic activity obtained from 30 mild traumatic brain injury (mTBI) subjects and 50 healthy controls. Intra-frequency and inter-frequency coupling modes are incorporated in a single graph to detect group differences within individual rich-club subnetworks (type I networks) and networks connecting RC nodes with the rest of the nodes (type II networks). Our results show a higher probability of inter-frequency coupling for (δ–γ1), (δ–γ2), (θ–β), (θ–γ2), (α–γ2), (γ1–γ2) and intra-frequency coupling for (γ1–γ1) and (δ–δ) for both type I and type II networks in the mTBI group. Additionally, mTBI and control subjects can be correctly classified with high accuracy (98.6%), whereas a general linear regression model can effectively predict the subject group using the ratio of type I and type II coupling in the (δ, θ), (δ, β), (δ, γ1), and (δ, γ2) frequency pairs. These findings support the presence of an RC organization simultaneously with dominant frequency interactions within a single functional graph. Our results demonstrate a hyperactivation of intrinsic RC networks in mTBI subjects compared to controls, which can be seen as a plausible compensatory mechanism for alternative frequency-dependent routes of information flow in mTBI subjects

Paraneoplastic hypoglycaemia secondary to IGF-2 secretion from a metastatic gastrointestinal stromal tumour

We report the case of a 79-year-old male with previous history of non-Hodgkin's lymphoma in remission, who presented acutely to the Accident and Emergency department with recurrent episodes of hypoglycaemia. At the time of presentation, a random glucose was low at 1.4 mmol/l, which upon correction resolved his symptoms. In hindsight, the patient recalled having had similar episodes periodically over the past 2 months to which he did not give much notice. While hospitalized, he continued having episodes of symptomatic hypoglycaemia, requiring treatment with intravenous dextrose and per os steroids. Once stable, he was discharged on oral prednisolone and dietary advice. A computed tomography scan performed during inpatient stay showed multiple deposits in the abdomen. An ultrasound guided biopsy of one of the liver deposits was performed. Immunohistochemistry supported the diagnosis of a gastrointestinal stromal tumour (GIST) positive for CD34 and CD117. The diagnosis of non-islet cell tumour hypoglycaemia (NICTH) secondary to an IGF2 secreting GIST was confirmed with further biochemical investigations (IGF2=105.9 nmol/l; IGF2:IGF1 ratio 23, Upper Level of Normal (ULN) <10). Targeted cytoreductive treatment with Imatinib mesylate following assessment of the tumour's mutational status was successful in preventing hypoglycaemia over a 21-month follow-up observation period

Improving the detection of mtbi via complexity analysis in resting - state magnetoencephalography

Diagnosis of mild Traumatic Brain Injury (mTBI) is difficult due to the variability of obvious brain lesions using imaging scans. A promising tool for exploring potential biomarkers for mTBI is magnetoencephalography which has the advantage of high spatial and temporal resolution. By adopting proper analytic tools from the field of symbolic dynamics like Lempel-Ziv complexity, we can objectively characterize neural network alterations compared to healthy control by enumerating the different patterns of a symbolic sequence. This procedure oversimplifies the rich information of brain activity captured via MEG. For that reason, we adopted neural-gas algorithm which can transform a time series into more than two symbols by learning brain dynamics with a small reconstructed error. The proposed analysis was applied to recordings of 30 mTBI patients and 50 normal controls in δ frequency band. Our results demonstrated that mTBI patients could be separated from normal controls with more than 97% classification accuracy based on high complexity regions corresponding to right frontal areas. In addition, a reverse relation between complexity and transition rate was demonstrated for both groups. These findings indicate that symbolic complexity could have a significant predictive value in the development of reliable biomarkers to help with the early detection of mTBI