Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatial Division Multiplexing-Based Reflective Intensity-Modulated Fiber Optics Displacement Sensor

Due to the benefit of multiple parallel channels within single cladding and easy implementation of multi-input multioutput technique, we present the spatial division multiplexing (SDM)-based reflective intensity-modulated fiber optics displacement sensor (RIMFODS). Under the condition of single-input single-output, we experimentally compare the transfer function of RIMFODS by using a pair of standard single-mode fibers (SSMFs), single seven-core-single-mode fiber, and single seven-core-few-mode fiber. In comparison with the conventional SSMF-based RIMFODS, the use of seven-core-few-mode fiber can reduce the dead zone of measurement range from 200 to 100 μm. Meanwhile, the system sensitivity can be enhanced from 0.14 to 12.2 nW/μm. In particular, with the help of two-input-five-output technique, the dead zone can be further reduced to 70 μ m, with sensitivity reaching as high as 53.87 nW/μm. Finally, we theoretically investigate the effect of both the core size and the core spacing of multicore fiber on the transfer function of RIMFODS. Such an SDM-based RIMFODS with compact footprint has lots of potential to be exploited.
Artificial-Noise-Aided Precoding Design for Multi-User Visible Light Communication Channels

Secure transmission is becoming an essentially important aspect in visible light communication (VLC). In this paper, we investigate the designs of artificial noise (AN)-aided precoding to improve physical layer security in a multi-user single eavesdropper wiretap VLC channels. The AN-aided precoding is designed to solve the max-min fairness signal- to-interference-plus-noise ratio (SINR) problem among users in two different scenarios: unknown and known eavesdropper's channel state information (CSI) at the transmitter. In the former case, we adopt the traditional null- space AN scheme and then study the impact of the AN power on the fairness performance. In the case of known eavesdropper's CSI, the AN-aided precoding is designed in such a way that keeps the SINR of the eavesdropper below a predefined threshold. Numerical results show that in both cases, the design could significantly degrade the quality of the eavesdropper's channel, thus enhancing communication secrecy.
The effect of synchronised metronome training: A case study in a single leg, below knee Paralympic sprinter

Background To optimise sprint performance, one needs to understand how motor control affects motor performance. Researchers have proposed that the Dynamic Systems Theory be adopted for explaining motor performance, skill acquisition and the development of pedagogical methods. Within this theory, the individual is seen as a complex system that functions as the interaction of many sub-systems. Entrained movements would be characterised by optimal sequencing, timing and grading of muscle activation. One of the identified control parameters for running is the rhythm in the coordination pattern. Objectives The objectives of this study were twofold: firstly to investigate whether 6 weeks of timing and rhythmicity training using the computer-based Interactive Metronome™ (IM™) system improves motor timing and rhythmicity, and secondly to investigate whether such effects of IM™ influence the kinematic variables of a sprint. Methods This study followed a semi-quantitative analysis case study approach using a Paralympic sprinter with a single below knee amputation participated in this study. Data for acceleration and maximal running velocity phases were collected using video recorders. Results and conclusions As found by previous research, the IM™ programme improved the motor timing and rhythmicity of the athlete. However, in contrast to previous research, only minimal improvements, non-significant improvements, were seen in the actual motor performance. This athlete was an older more established athlete and it is therefore recommended that these types of programmes should be followed by young participants in the more fundamental phases of their movement development, to show best results.
Mesoscale Modeling of the Meteorological Impacts of Irrigation during the 2012 Central Plains Drought

AbstractIn the summer of 2012, the central plains of the United States experienced one of its most severe droughts on record. This study examines the meteorological impacts of irrigation during this drought through observations and model simulations using the Community Land Model coupled to the Weather Research and Forecasting (WRF) Model. A simple parameterization of irrigation processes is added into the WRF Model. In addition to keeping soil moisture in irrigated areas at a minimum of 50% of soil moisture hold capacity, this irrigation scheme has the following new features: 1) accurate representation of the spatial distribution of irrigation area in the study domain by using a MODIS-based land surface classification with 250-m pixel size and 2) improved representation of the time series of leaf area index (LAI) values derived from crop modeling and satellite observations in both irrigated and nonirrigated areas. Several numerical sensitivity experiments are conducted. The WRF-simulated temperature fiel.
Real-time detection of traffic behavior using traffic loops

Traffic accidents and stopped vehicles in tunnels can result in dangerous situations. Fast responses to these kinds of events are essential to limit the danger and to restore the traffic flow. In most tunnels, inductive traffic loops are used in combination with a rule-based system to alert the traffic controller. The rule-based system that is currently used gives many alerts to the traffic controller which do not require his or her attention. Because of these false alarms, traffic controllers stop relying on the existing system. Such false alarms occur mostly during rush hour traffic. The goal of this thesis is to better inform the traffic controllers by using machine learning to find different types of traffic behavior. By doing this the traffic controller can determine what to do based on the type of traffic. A Multilayer Perceptron was trained as a binary classifier to distinguish between normal and abnormal traffic. The existing rule-based system was used as a baseline for the binary classifier. In order for the MLP to outperform the rule-based system historical data was necessary during classification. Using only the current data of the traffic loops was not enough for the MLP to outperform the rule-based network. The rule-based network scores an F1score of 0.6601. While the MLP using only the current data scores an F1score of 0.5249. However, if historical timesteps are used it scores an F1score of 0.7872. The data generated by the traffic loops is a sequence of passing cars, so Recurrent Neural Networks and Hidden Markov Models were also used because they are designed for sequence data. The Recurrent Neural Networks were the best performing machine learning methods. Both a LSTM and a GRU were used and the GRU performed the best with an F1score of 0.8236. While the Hidden Markov Models were not able to outperform the rule-based system with an F1score of 0.0059.
Knowledge-based Development and Its Relation to Economic Prosperity in Developing Countries

This paper explains how integrative knowledge-based development can contribute to economic growth and social development as an important field of research. We show how it would be useful for country-specific demands and issues, and the significance of investment in knowledge-based research and the importance of universities in the practice and advancement of integrative approaches of knowledge-based development. Academic communities still prefer knowledge and research from applied sciences and physical sciences to contribute to government policies and initiatives in the context of development. But there is less attention paid to the contribution of the social sciences to economic and social development. Recently, research has been emphasized that incorporates multidisciplinary approaches in problem solving and best solutions for improving social, environmental, political, and economic crises. Though knowledge-based development is an international phenomenon, the concept of knowledge-based development as a form of capital and a well managed investment is still not realized in developing countries compared with developed countries. Universities are a platform to promote and advance knowledge-based development by cultivating multidisciplinary and integrative research beyond individual discipline boundaries.
A 0.2 V 32-Kb 10T SRAM With 41 nW Standby Power for IoT Applications

This paper proposes a new 10-transistor (10T) bitcell for robust operations at subthreshold voltages without any boost circuitry. Features of the proposed bitcell include: 1) differential pre-discharged bit-lines and a pair of decoupled access ports to resist disturbance; 2) footed latch for write assist; 3) spare latch-foot to fight against half-select disturbances; and 4) highly stacked pull-down structure to reduce both leakage and power. A bit-interleaved SRAM macro, constructed with the proposed 10T bitcell, is fabricated in 28 nm CMOS. The power consumption has been measured as 90 nW for 30 kHz access at 0.25 V, and 41 nW for retention at 0.20 V, of which the leakage is 31% better than the state-of-the-art design.
How companies communicate their brand identity online-A quantitative study on Swedish and French companies Degree project ( EXC 504 ) Spring term 2018

The purpose of this Bachelor’s Thesis Project in Business Administration is to investigate how companies communicate their company brand identity online. The writing of this paper has been motivated by a lack of researches regarding the companies’ dimension in term of identity communication and the brand identity promotion process online. This paper is based on a quantitative research on companies from French and Swedish. The research question is formulated as follows: How companies communicate their brand identity online through virtual media? In order to investigate the companies, a questionnaire was implemented and shared by an emailing process. This questionnaire, following a quantitative approach, has been constructed by combining several theories about the branding process, the brand identity concept, its keys concepts and also the online business landscape since the development of the Internet. According to our analysis, companies mainly share their brand identity online through two main vehicles, Website and Facebook. These media are the ones mainly used to share the three identity dimensions and to support the tools to communicate this company brand identity communication. By this analysis, deeper knowledge was created in order to provide useful data for future analysis.
COTA: Improving the Speed and Accuracy of Customer Support through Ranking and Deep Networks

For a company looking to provide delightful user experiences, it is of paramount importance to take care of any customer issues. This paper proposes COTA, a system to improve speed and reliability of customer support for end users through automated ticket classification and answers selection for support representatives. Two machine learning and natural language processing techniques are demonstrated: one relying on feature engineering (COTA v1) and the other exploiting raw signals through deep learning architectures (COTA v2). COTA v1 employs a new approach that converts the multi-classification task into a ranking problem, demonstrating significantly better performance in the case of thousands of classes. For COTA v2, we propose an Encoder-Combiner-Decoder, a novel deep learning architecture that allows for heterogeneous input and output feature types and injection of prior knowledge through network architecture choices. This paper compares these models and their variants on the task of ticket classification and answer selection, showing model COTA v2 outperforms COTA v1, and analyzes their inner workings and shortcomings. Finally, an A/B test is conducted in a production setting validating the real-world impact of COTA in reducing issue resolution time by 10 percent without reducing customer satisfaction.
MicroRNA-18b promotes cell proliferation and invasion in non-small cell lung cancer by directly targeting runt-related transcription factor 3

Lung cancer is the most common cancer and the leading cause of cancer-related deaths in men and women globally. Increasing evidence has demonstrated that microRNAs (miRNAs) may be critical regulators in cancer-related processes. Therefore, understanding the molecular mechanism between Non-Small Cell Lung Cancer (NSCLC) and abnormal miRNA expression levels may help identify novel diagnostic biomarkers and therapeutic targets for patients with NSCLC. MiRNA-18b (miR-18b) is abnormally expressed in multiple types of human cancers. However, the expression pattern, function and underlying mechanisms of miR-18b in NSCLC have yet to be elucidated. This study aimed to detect the expression levels of miR-18b, explore the regulatory roles of miR-18b in NSCLC and reveal the possible underlying mechanisms of miR-18b involved in this process. Experiments indicated that miR-18b was upregulated in NSCLC tissues and cell lines. MiR-18b downregulation suppressed the proliferation and invasion of NSCLC cells. Runt-related transcription factor 3 (RUNX3) was identified as a direct target of miR-18b in NSCLC by a series of experiments. Moreover, RUNX3 overexpression played the same role as miR-18b under expression in NSCLC cells, by a series of experiments. These findings suggested that miR-18b inhibition may provide a novel effective therapeutic method for patients with NSCLC.
Historical trends in precipitation and stream discharge at the Skjern River catchment, Denmark

A 133 yr data set from the 1055 km 2 Skjern River catchment in western Denmark has been analysed with respect to precipitation, temperature, evapotranspiration and discharge. The precipitation series have been tested and corrected using the standard normal homogeneity test and subsequently corrected for undercatch. The degree of change in the climatic variables is examined using the non-parametric Mann–Kendall test. During the last 133 yr the area has experienced a significant change in precipitation of 26% and a temperature change of 1.4°C, leading to increases in river discharge of 52% and groundwater recharge of 86%. A lumped conceptual hydrological model, NAM, was calibrated on the period 1951–1980 and showed generally an excellent match between simulated and observed discharge. The capability of the hydrological model to predict climate change impact was investigated by looking at performances outside the calibration period. The results showed a reduced model fit, especially for recent time periods (after the 1980s), and not all hydrological changes could be explained. This might indicate that hydrological models cannot be expected to predict climate change impacts on discharge as accurately in the future, compared to the performance under present conditions, where they can be calibrated. The (simulated) stream discharge was subsequently analysed using high flow and drought indices based on the threshold method. The extreme signal was found to depend highly on the period chosen as reference to normal. The analysis indicated that no significant amplitude increase of the hydrograph for both wet and dry extremes could be found superimposed on the overall discharge increase.
Effect of Callosobruchus Maculatus ( Coleoptera : Bruchidae ) and Acanthoscelides Obtectus Say Infestation on the Qualitative and Quantitative Phytochemicals of Vigna Unguiculata , Vigna Aconitifolia , Phaseolus Vulgaris , Phaseolus Lunatus and Phaseolus

Infestation of grains has been reported in many stored grains. This research was carried out to determine the effect of infestation on the qualitative and quantitative phytochemicals of five beans species. Results of qualitative analysis revealed the presence of seven and the absence of three phytochemicals in infested and uninfested samples T-test analysis of results revealed increase in alkaloids in infested V. unguiculata, V. aconitifolia and P. autifolius with decease in infested P. vulgaris and P. lunatus. Reductions in glycosides were significant (p<0.05) in infested V. unguiculata and P. lunatus, with increases in P. vulgaris, P. autifolius and V. aconitifolia. Saponins were reduced in P. lunatus, V. aconitifolia and P. vulgaris with significant increases in infested V. unguiculata and P. autifolius. Flavonoids and tannins showed reductions due to infestation. Effect of infestation resulted in polyphenols decreases of 30.1%, 25.9%, 14.5% in P. vulgaris, P. lunatus, P. autifolius respectively with associated increases of 69.4%, 58.0% for V. aconitifolia and V. unguiculata. Infestation caused increases in reducing compounds in all the beans species studied with the exception of P. vulgaris. This study concluded that infestation engendered significant reductions and increases in infested seeds of the beans species investigated.
Does Adding Silver Nanoparticles to Leukocyte- and Platelet-Rich Fibrin Improve Its Properties?

Objectives Leucocyte- and platelet-rich fibrin (L-PRF) membrane can be used in various regenerative treatments. In the case of classical heterologous membrane exposure, microorganisms can be colonized on it and jeopardize the success of treatment. The aim of this study was to compare the antibacterial, mechanical, and histologic characteristics of the L-PRF membrane before and after the addition of silver nanoparticles (SNP). Materials and Method This study was performed on 10 volunteer men aged 25-35 years. 20 ml whole bloods were collected from each person and L-PRFs were made by routine and SNP modified method. Mechanical, antibacterial, and histological properties were evaluated. Results The antibacterial efficacy of L-PRF and nanosilver-modified L-PRF was presented as Klebsiella pneumonia had growth on the L-PRF membrane after 12 hours. After 24 hours, Klebsiella pneumonia and Streptococcus viridans had growth on L-PRF and only Klebsiella pneumonia had growth on SNP-L-PRF. The tensile strength and stiffness were significantly higher in the SNP-L-PRF. Precipitation of the SNPs was patchy in the outer layers and quite homogeneous in the inner core. Conclusion Modification of L-PRF with SNP improves the mechanical properties and antibacterial activity of the L-PRF. It can play an important role in regenerative procedures.
Proximity to reef influences density of small predatory fishes, while type of seagrass influences intensity of their predation on crabs

The magnitude of the influence that predators exert on their prey is partly determined by factors that influence the density and behaviour of predators, and partly by factors that influence the survival of prey in the presence of predators. We tested whether the presence of reefs influences the density of small predatory fishes inhabiting seagrass meadows, and the intensity of predation by these fishes on tethered crabs, by taking measurements at increasing distances from 10 rocky reefs at 2 locations separated by several hundred km. We also tested whether these variables were influ- enced by type of seagrass by comparing patterns yielded in meadows dominated by Amphibolis spp. and Posidonia sinuosa, 2 seagrasses with different morphological and architectural characteristics. The densities of small predatory fishes declined rapidly with increasing distance from reefs, with sig- nificantly lower densities 30 m from reefs than immediately adjacent to reefs. Densities >300 m from reefs were generally not significantly different to densities 30 m from reefs. However, the survival of tethered crabs showed no consistent trend associated with distance from reefs. Type of seagrass was not a significant influence on the density of small predatory fishes, but did influence the survival of tethered crabs: those in Amphibolis spp. meadows were 3.1× more likely to be eaten than those in P. sinuosa meadows. These patterns were consistent between locations. Our results suggest that over landscape scales (hundreds of metres) reefs are an important influence on abundance of small preda- tory fishes, but not on the intensity of predation on crabs. Differences in the intensity of predation between the 2 seagrass species are likely due to their dissimilar morphological and architectural characteristics.
A new microscopy for imaging retinal cells

The evaluation and monitoring of cells health in the human retina is crucial and follow time course of retinal diseases, detect lesions before irreversible visual loss and to evaluate treatment effects. Towards this goal, a major challenge is to image and quantify retinal cells in human eyes in a non-invasive manner. Despite the phenomenal advances in Optical Coherence Tomography (OCT) and Adaptive Optics systems, in vivo imaging of many of these cells is limited by the fact that cell contrast in reflection is extremely low. Here, we report on a major advance by proposing and demonstrating a radically different method compared with OCT to visualize retinal cells with high contrast, resolution and an acquisition time suitable for clinical use. The method uses a transscleral illumination which provides a high numerical aperture in a dark field configuration. The light backscattered by the Retinal Pigment Epithelium (RPE) and the choroid provides a forward illumination for the upper layer of the retina, thus providing a transmission illumination condition. By collecting the scattered light through the pupil, the partially coherent illumination produces dark field images, which are combined to reconstruct a quasi-quantitative phase image with twice the numerical aperture given by the eye's pupil. The retrieved quasi-quantitative phase images (QPI) of cells in ex vivo human and pig's eyes are validated with those taken with a standard QPI system. We then apply the technique in vivo on human eye, without pupil dilation, we demonstrated the feasibility to image retinal cells up to the retinal pigment epithelium within a few seconds.
Symmetric-Key Generation Protocol (SGenP) for Body Sensor Network

Sensors of a Body Sensor Network (BSN) transmit messages over a non-secure wireless channel. Messages are encrypted using a secret key to attain privacy. In this paper, we propose Secret- key Generation Protocol (SGenP), assuming that all sensors are capable of capturing physiological signals. SGenP evades any pre-distribution of keying materials. SGenP consists of two sub- protocols: 1. Hash Message Authentication Code Feature Exchange (HMAC-FE) protocol and 2. Secret Key Construction (SKC) protocol. HMAC-FE facilitates a secret feature exchange using a HMAC function. The HMAC function works as a module, therefore with different HMAC functions, different levels of security (from Cryptographic to Information-theoretic) can be achieved. Once a set of common features between two sensors is decided, SKC protocol outputs a secret key. SGenP offers some essential properties like plug-n-play, replaceability, scalability, flexibility and easy refreshment of keys. SGenP is compared with OPFKA and found that energy consumption due to communications is reduced by 89.2%.