Miracle-dz/UniFAR-FTUs huggingface dataset:
MASCARA: the multi-site all-sky CAameRA: concept and first results

MASCARA, the Multi-site All-Sky CAmeRA, will consist of several fully-automated stations distributed across the globe. Its goal is to find exoplanets transiting the brightest stars, in the mV = 4 to 8 magnitude range, currently probed neither by space- nor by ground-based surveys. The nearby transiting planet systems that MASCARA is expected to discover will be key targets for future detailed planet atmosphere observations. The target population for MASCARA consists mostly of hot Jupiters. The main requirement set on MASCARA to detect these planets around stars down to magnitude 8 is to reach a minimum Signal-to-Noise Ratio of 100 within one hour of observation. Each MASCARA station consists of five low-noise off-the-shelf full-frame CCD cameras, fitted with standard Canon 24 mm , f/1.4 lenses, monitoring the near-entire sky down to magnitude 8 at that location. Measurements have demonstrated that the required Signal-to-Noise Ratio of 100, can be achieved in less than thirty minutes. MASCARA aims at deploying several stations world-wide to provide a nearly continuous coverage of the dark sky, at sub-minute cadence. While at the faint end MASCARA is limited mainly by photon noise, at the bright end scintillation and red noise become the limiting factors. Instrumental noise sources are reduced by placing the cameras in a fixed orientation and in a temperature controlled environment. By defocusing and allowing stars to drift over the detector, the impact of pixel-to-pixel variations on the photometry are minimized, while taking exposures at fixed sidereal times allows accurate cross-calibration of consecutive nights. The exposure time of 6.4 seconds gives rise to a high data acquisition rate of a MASCARA station, around 500GB per night. In order to minimize data transport and data storage requirements, the raw images are reduced to produce accurate light curves in nearly real time. The first MASCARA station will be integrated on La Palma during the summer of 2014. MASCARA test data were taken in July 2013 with one camera targeting the transiting exoplanet HD 189733b. Its brightness of mV = 7:7 is close to the faint end of the MASCARA magnitude range. The 5 - σ detection of the 2.8% deep transit with a 5-minute binning of the data confirms that we will be able to detect 1% transit at the faint end within one hour.
Diffraction stress analysis of macroscopically elastically anisotropic specimens: On the concepts of diffraction elastic constants and stress factors

A unifying, rigorous treatment has been given for the diffraction stress analysis of both macroscopically elastically isotropic specimens and macroscopically elastically anisotropic specimens. The applicability ranges of so-called diffraction elastic constants and diffraction stress factors have been discussed. It has been shown that the diffraction stress factors, originally introduced for the diffraction stress analysis of textured specimens, can be generally used in the diffraction stress analysis of macroscopically elastically anisotropic specimens exhibiting direction-dependent grain interaction, independently of the presence of texture. The grain-interaction tensor has been introduced and investigated for various grain interaction models. The notion surface anisotropy of bulk specimens has been revisited as a special case of direction-dependent grain interaction.
CNN-BASED FEATURES FOR FILTERING OF CRISIS RELATED SOCIAL MEDIA MESSAGES

Từ các thông tin trên các trang mạng xã hội, bài toán phân tích xác định nội dung là thật hay giả là một vấn đề cần nghiên cứu trong xử lý ngôn ngữ tự nhiên (NLP). Bài báo trình bày một phương pháp để phân loại trường hợp cấp thiết trong các tin nhắn trên Tweeter. Nhóm nghiên cứu dựa vào biểu diễn các đặc trưng văn bản bằng các mẫu hình ảnh thay vì sử dụng các đặc trưng text được trích xuất trực tiếp từ tin nhắn văn bản. Trong các kỹ thuật xử lý ngôn ngữ tự nhiên, các đặc trưng text thường trích chọn dựa trên việc phân đoạn hoặc phân tích thống kê tần suất xuất hiện của các từ khóa trong các tin nhắn văn bản. Để làm tăng độ chính xác của việc phân lớp nhóm nghiên cứu đã cài đặt một phương pháp dựa trên nhận dạng các mẫu ảnh. Việc chuyển từ đặc trưng text thành ảnh cho phép áp dụng các phép toán tích chập để nhận dạng các mẫu. Điều này mở ra một sự kết hợp giữa NLP và phân tích hình ảnh. Bài báo sử dụng mạng nơ ron tích chập (CNN) thực hiện với các mẫu ảnh để phân lớp các câu. Nghiên cứu cũng được so sánh với các phương pháp khác để đánh giá trong phần mô phỏng so sánh của nghiên cứu đề xuất.
Community Psychology: Why this Gap in Britain?

Community psychology has developed in other parts of the world, but not in the UK. We contrast the development of psychology, in its wider social context, between 1960 and 1980 in the UK and the USA, in order to try to understand some of the reasons for the absence of community psychology in the UK A scheme of enquiry is proposed which includes exploration of the different social policy contexts; ways in which the ideological and theoretical character ofpsychology equipped psychologists to use opportunities arising in the broader social context; analysis of the availability of appropriately oriented psychology graduates; and the relative absence of other community orientated workers. It is argued that each of these factors illuminates key differences between the USA and the UK in terms of the development of community psychology. It is suggested that contemporary social conditions in the UK may facilitate moves towards a more community-focused psychology.
Evaluating the Quality and Readability of Online Resources for Labiaplasty

Objectives The aim of this study was to evaluate the quality, readability, and accuracy of Web-based information regarding labiaplasty and to characterize the types of Web sites providing this information. Methods Investigators used 3 major search engines to query the internet using the search terms labiaplasty, labia reduction, and vaginal rejuvenation. Two validated tools were used to evaluate Web sites: the JAMA benchmark tool and the DISCERN instrument. Three physicians independently reviewed each Web site. Interrater agreement was assessed, and reviewer scores were averaged. Flesch-Kincaid reading ease and Flesch-Kincaid grade level of each site were assessed. Data were analyzed using Stata 14.0 (College Station, TX). Results Of the 112 Web sites reviewed, 100 Web sites were from North America, 9 from Europe, 2 from Australia, and 1 from Asia. The median score using the JAMA tool was 1.0 (0.33–4.0), indicating low accountability, whereas the median score using the DISCERN tool was 28 (18.7–77) of 80 with higher scores indicating higher quality. Cohen’s weighted κ statistic (0.81) demonstrated near perfect agreement among reviewers for DISCERN scores. The median reading level was 11.9 (6.4–19.5). A majority of the Web sites (92) were for-profit businesses or blogs. Conclusions The internet enables patients to research sensitive topics and seek answers without worry of social stigma. Online health-related information is a widely used yet poorly studied source of medical information. The majority of Web sites reviewed lack balanced, evidence-based information. Given the wide variation in the quality of information, physicians should guide patients to reputable online resources.
Integral Equation for the Heat Transfer with the Moving Boundary

Although the heat conduction problem in cooling  ns is usually consideredto haveone steady-statesolutionfor givenboundaryconditions, two solutions may exist when nonstandard, yet physically admissible, boundary conditions are applied. In particular, the situation inwhich the cooling  n has  xed temperatureat both ends and speci ed heat  ux at the root is examined. The analysis shows that, depending on the value of the heat  ux at the  n root, the problem may have no solutions, one solution, or two solutions for the  n length. The results can  nd practical applications in the design of passive safety devices for chemical or nuclear plants.
Exploring the use of assessment for learning in the mathematics classroom

Assessment for Learning is useful in producing feedback that mathematics teachers may utilise to enhance classroom teaching. In this study, we look at how mathematics teachers in Alexandra Township, South Africa, utilise assessment for learning (AfL) to create a classroom culture that responds to learners' knowledge acquisition. This study used a qualitative technique within an interpretivist paradigm and a case study design. We purposively selected nine Grade 6 primary school mathematics teachers. Data, collected through face-to-face semi-structured interviews, non-participant classroom observation, and documents, was analysed using qualitative data analysis. Results revealed, first, that the participants understand AfL as those activities given in class at the end of the lesson to measure learner understanding. Second, data revealed that the participants depend on textbooks for AfL activities that do not always take learners' contexts into account. Finally, the study revealed AfL challenges because teachers teach mathematics in a language other than the learners' home language. We recommend that in-service teachers attend several assessment developmental workshops to help them focus on pedagogical practices that will improve AfL implementation.
Whisper Denoising in Joint Time-Frequency Domain Based on Real-Valued Discrete Gabor Transform

Whispered speech can be effectively used for quiet and private communications over mobile phones and is also the communication means for ENT patients under a regime of voice rest. However, little progress has been made on the denoising of whispered speech in noisy environment because of its special acoustic characteristics.In this paper, we propose a whisper denoising algorithm in joint time-frequency domain based on real-valued discrete Gabor transform(RDGT). Noisy whisper is first transformed into the joint time-frequency domain by fast real-valued discrete Gabor transform. The MMSE based log-amplitude estimator is derived under speech presence uncertainty hypothesis. Clean whisper spectral is then estimated by inverse transform of RDGT. Experimental results show that the proposed algorithm is very effective in avoiding the musical residual noise and retaining weak speech components.
A Comparative Investigation of Automatic Speech Recognition Platforms for Aphasia Assessment Batteries

The rehabilitation of aphasics is fundamentally based on the assessment of speech impairment. Developing methods for assessing speech impairment automatically is important due to the growing number of stroke cases each year. Traditionally, aphasia is assessed manually using one of the well-known assessment batteries, such as the Western Aphasia Battery (WAB), the Chinese Rehabilitation Research Center Aphasia Examination (CRRCAE), and the Boston Diagnostic Aphasia Examination (BDAE). In aphasia testing, a speech-language pathologist (SLP) administers multiple subtests to assess people with aphasia (PWA). The traditional assessment is a resource-intensive process that requires the presence of an SLP. Thus, automating the assessment of aphasia is essential. This paper evaluated and compared custom machine learning (ML) speech recognition algorithms against off-the-shelf platforms using healthy and aphasic speech datasets on the naming and repetition subtests of the aphasia battery. Convolutional neural networks (CNN) and linear discriminant analysis (LDA) are the customized ML algorithms, while Microsoft Azure and Google speech recognition are off-the-shelf platforms. The results of this study demonstrated that CNN-based speech recognition algorithms outperform LDA and off-the-shelf platforms. The ResNet-50 architecture of CNN yielded an accuracy of 99.64 ± 0.26% on the healthy dataset. Even though Microsoft Azure was not trained on the same healthy dataset, it still generated comparable results to the LDA and superior results to Google’s speech recognition platform.
Social capital: Is it a good idea?

Psychologists should be familiar with the now popular idea of social capital. Despite its critics, it promises to help us explain the influence on health of the communities in which people live. It challenges us to raise our sights from the individual and the family, to consider the ways in which people, places and organisations are interdependent, to consider new inter-disciplinary alliances, and to think of the community values that underpin our work.
Surface diagnosis of large reflector antennas using microwave holographic metrology: An iterative approach

Recent investigations have shown that it is quite possible to accurately characterize the surface profile of large reflectors using microwave holographic techniques. In these techniques the complex (amplitude and phase) far-field pattern of the antenna is measured first. The surface profile is then constructed using the Fourier transform relationship which exists between the far field and a function related to the induced surface current. In this paper the concept of the Fourier transform relationship is first investigated to demonstrate that it is, in general, a summation of many Fourier transforms. However, for large reflectors with small beam widths, only the first term of the series has the major contribution. Furthermore, an iterative scheme is described to analytically/numerically continue the far-field pattern outside the measurement window. This, then, results in an improved resolution of the surface map data and, in particular, reduces the amplitude artifacts outside the boundary of the reflector. A novel and efficient simulation model has been developed to properly evaluate the accuracy of the technique in recovering the simulated surface errors. Finally, results of a recent measurement are summarized.
Toward Interdisciplinary Synergies in Molecular Communications: Perspectives from Synthetic Biology, Nanotechnology, Communications Engineering and Philosophy of Science

Within many chemical and biological systems, both synthetic and natural, communication via chemical messengers is widely viewed as a key feature. Often known as molecular communication, such communication has been a concern in the fields of synthetic biologists, nanotechnologists, communications engineers, and philosophers of science. However, interactions between these fields are currently limited. Nevertheless, the fact that the same basic phenomenon is studied by all of these fields raises the question of whether there are unexploited interdisciplinary synergies. In this paper, we summarize the perspectives of each field on molecular communications, highlight potential synergies, discuss ongoing challenges to exploit these synergies, and present future perspectives for interdisciplinary efforts in this area.
Compact Microstrip Bandpass Filter with Multispurious Suppression

A compact microstrip bandpass fllter (BPF) with multispurious suppression is presented. The fllter consists of two coupled half-wavelength stepped impedance resonators (SIRs) and tapped input/output (I/O) lines. With tuning the impedance ratio (K) and length ratio (fi) of SIRs, a very wide stopband can be easily achieved. The fllter is designed at 2.4GHz (f0) with a wide stopband to 20GHz (8.16f0) and an average rejection level better than 25dB. This study provides a simple and efiective method to achieve a fllter with very wide stopband and compact circuit size simultaneously. Good agreement between the full-wave electromagnetic (EM) simulation and measurement is compared.
Virtual-Axis Injection Based Online Parameter Identification of PMSM Considering Cross Coupling and Saturation Effects

Existing online parameter identification methods of permanent magnet synchronous motors (PMSMs) are generally based on the voltage equations, the precision of which is affected by the cross coupling and magnetic saturation effects. In order to deal with this issue, a virtual-rotary-axis high-frequency signal injection based online parameter identification method is proposed in this article, where the cross coupling and magnetic saturation effects on the traditional dq-axis model are analyzed. On this basis, an optimized voltage model under the composite magnetic field rotary axis is introduced. In the proposed method, the cross-coupling angle and the dq-axis inductances can be identified by injecting the high-frequency signal into the constructed virtual rotary axis. In addition, the complex Simpson integral algorithm is adopted to obtain the information of the incremental and apparent inductances. Finally, the permanent magnet flux linkage can be estimated based on the composite magnetic field rotary axis voltage equations. The effectiveness and feasibility of the proposed method are verified by the experiments on a 2.2-kW PMSM drive.
Chronic Kidney Disease and Periodontitis Interplay—A Narrative Review

Periodontitis (PO), a chronic microbially-induced inflammation of the supporting tissues of the tooth, is linked to various systemic diseases. We analyze its bidirectional relationship to chronic kidney disease (CKD), a major health-care problem with impressive excess mortality. Overwhelming associative relationship between CKD and PO are analyzed. Major pathophysiologic mechanisms that link CKD to PO are then presented: systemic inflammation, endothelial dysfunction, and imbalance of oxidative stress characteristic of CKD have a role in PO development and might influence escape mechanisms of oral microbiota. Subclinical local and systemic inflammation induced by PO might influence in turn CKD outcomes. Homeostatic changes induced by CKD such as mineral bone disorders, acidosis, uremic milieu, or poor salivary flow are also relevant for the occurrence of PO. There is insufficient evidence to recommend a standardized diagnostic and therapeutic approach regarding association of PO to CKD.
Evolution of neocortical folding: A phylogenetic comparative analysis of MRI from 34 primate species

We present a comparative analysis of cerebral size and neocortical folding. Magnetic resonance imaging data was collected from 54 individuals belonging to 33 different primate species. We measured several neocortical folding parameters and studied their evolution using phylogenetic comparative methods. Our results suggest that the most likely model is one where phenotypical differences vary randomly through evolution (the Brownian Motion model). We present estimations of the ancestral primate phenotypes as well as estimations of the rates of phenotypic change.
Continuous Control With Swarm Intelligence Based Value Function Approximation

Value function approximation, such as Q-learning, is widely used in the discrete control rather than the continuous one because the optimal action in the discrete setting is more easily selected. Optimizing the action is a non-convex optimization problem with respect to the complex value function. Some notable studies simplify the non-convex optimization problem by assuming the value function as quadratic in the actions or by discretizing the action space. However, the performance of the output policy will decline if these studies’ premises do not hold. In order to address the problem, we propose a framework that combines swarm intelligence algorithms with value-based Reinforcement Learning, where the swarm intelligence algorithms are employed to search for the optimal action with respect to the state and the value function. To ensure the correctness of this framework, we conditionally claim the convergence rate of swarm intelligence algorithms with high probability. We then implement it by searching the batch optimal actions to various states on the GPU platform for the batch training. Furthermore, we employ the population-based atomic actions for the compatibility with the existing related work about solving discrete control problems. Four classical control models and four robot simulation environments are utilized in the comparisons. According to empirical results, our framework outputs a policy comparable with that of the policy-based algorithms by 10% timesteps in the continuous control. Note to Practitioners—This paper is motivated by the exploration-exploitation dilemma of Reinforcement Learning to solve continuous control tasks. To balance the exploration and exploitation, the stochastic exploration and the prioritized exploration are roughly two feasible ways, where the prioritized one is a better choice due to the higher data efficiency than the stochastic one, e.g. $\varepsilon $ -greedy. Normally, the prioritized exploration works well in the value-based Reinforcement Learning algorithms rather than the policy-based ones; meanwhile, the policy-based algorithms are more suitable to continuous control tasks than the value-based ones. To tackle this conflict, we especially design a particle swarm optimization to maximize the Q-value of action in Q-learning. Our design can be hybridized by various swarm intelligence and value-based Reinforcement Learning algorithms. Also, it can be embedded in most intelligent control systems easily. The aim of this study is to solve the continuous control tasks by value-based algorithms as the first step of applying the prioritized exploration. The simulative results verify the effectiveness and efficiency of our design.
Photonic force microscopy of local tension at cell surface focal adhesions

The ability of cells to sustain mechanical stress is essential. It is however not very well understood how tension is expressed from the inside of the cell to the exterior. Here we show that these forces can be measured by photonic force microscopy (PFM), which is able to apply a force to cells and to probe their response to the physical stress. Our setup consists of an inverted microscope coupled with an optical trap from a 5W ND:YVO4 fiber laser. Forces are applied to the cell by the trap through a 5μm polystyrene bead coated with fibronectin, pre-incubated with cells to allow bead attachment and creation of focal adhesions. The reaction of the cell is monitored by sensing the position of the bead relative to the trap center by a quadrant photodiode, when the bead is in an equilibrium state between the photonics forces and the membrane elasticity and cell stiffness. The detection system is calibrated using a piezo nano-positioner and thermal noise analysis. We observed increased deformation of H4 cells treated with cytocholasin D, which disrupts the actin microfilaments. This observation is correlated to an overall decrease in the force by the photonics force microscope. Our results suggest that cell stiffness can be assessed by the PFM, which allows quantification of a tension within cells with sufficient precision.
Impact of microstructure on the Mn valence of La2/3Ca1/3MnO3 thin films

The oxidation state of Mn in ${\mathrm{La}}_{2∕3}{\mathrm{Ca}}_{1∕3}\mathrm{Mn}{\mathrm{O}}_{3}$ thin films grown on single crystalline $\mathrm{Sr}\mathrm{Ti}{\mathrm{O}}_{3}$, $\mathrm{La}\mathrm{Al}{\mathrm{O}}_{3}$ and $\mathrm{Nd}\mathrm{Ga}{\mathrm{O}}_{3}$ substrates has been analyzed by soft x-ray absorption spectroscopy. The spectra at the $\mathrm{Mn}\text{\ensuremath{-}}{\mathrm{L}}_{2∕3}$ edges and at the O-K edge indicate the presence of a ${\mathrm{Mn}}^{2+}$ component, besides the expected ${\mathrm{Mn}}^{3+}∕{\mathrm{Mn}}^{4+}$ mixed valence state being characteristic for this material. It is observed that the appearance of the ${\mathrm{Mn}}^{2+}$ component is closely related to the exposure of samples to ambient atmosphere. The divalent Mn spectral contribution ${I}_{{\mathrm{Mn}}^{2+}}$ to the Mn ${\mathrm{L}}_{2∕3}$-edge spectra is almost thickness independent but exhibits a clear dependence on the substrate used. The origin of the Mn valence instability giving rise to the ${\mathrm{Mn}}^{2+}$ formation and the substrate dependent behavior is discussed in connection with the different microstructure of the samples.