Miracle-dz/UniFAR-FTUs huggingface dataset:
Control Strategy for Underactuated Multi-Fingered Robot Hand Movement Using Electromyography Signal with Wearable Myo Armband

The main goal of this research is to develop a control strategy for an underactuated robotic hand, based on surface electromyography (sEMG) signal obtained from a wireless Myo gesture armband, to distinguish six, several hand movements. The pattern recognition system is employed to analyze these gestures and consists of three main parts: segmentation, feature extraction, and classification. A series of 150 trials is carried out for each movement and it is established which was most suitable for electromyography signals that can be later used in recognition systems. A backpropagation neural network was used as a classifier. The architecture has a hidden network and six output layers. The number of neurons of the hidden network (20) was determined based on the performance in training progress. The proposed system is tested on datasets extracted from five healthy subjects. A great accuracy (94.94% correct assessment). between the experimentally values and those predicted by the artificial neural network (ANN) was achieved. In addition, kinematic analysis of the proposed underactuated hand has been carried out to verify the motion range of the joints. Simulations and experiments are carried out to verify the effectiveness of the proposed fingers mechanism and the hand prosthesis to generate grasp or postures.
Compact quintuple notched-band UWB BPF with high selectivity and wide bandwidth

Abstract In this paper, a compact quintuple notched-band ultra-wideband bandpass filter with high selectivity and wide bandwidth is proposed. The filter adopts an approximate closed-loop C-shaped stepped impedance resonator to generate triple notched bands, and uses Hilbert fractal curve slit and L-shaped resonator to create single notched band, respectively. Multiple notched-band are centered at 5.29, 6.61, 7.92, 8.95, and 9.93 GHz to eliminate undesired interference from coexisting wireless services of WLAN, C-band, and X-band. Additionally, two transmission zeros are introduced to enhance the sharp skirt selectivity up to 0.944. This filter could exhibit high sharp selectivity and wider bandwidth simultaneously. The filter is fabricated on a RT/Duroid 5880 substrate (ɛr = 2.2 and thickness = 0.787 mm) and measured to verify the simulation results. Both simulation and measurement are in well agreement, showing the good performance of the filter.
Exendin-based targeting of beta cells for in vivo monitoring of transplanted islets

Islet transplantation is a novel promising strategy to cure type 1 diabetes. However, the long-term outcome is still poor, because both function and survival of the transplant decline over-time. Non-invasive imaging methods have the potential to enable monitoring of islet survival after transplantation and the effects of immunosuppressive drugs on transplantation outcome. 111In-labeled exendin-3 is a promising tracer to visualize native and transplanted islets by SPECT (Single Photon Emission Computed Tomography). In the present study, we hypothesized that islet microvasculature plays an important role determining the uptake of exendin-3 in islets when monitoring transplant survival. We observed 111In-exendin-3 accumulation in the transplant as early as three days after transplantation and an increase in the uptake up to three weeks post-transplantation. Islet-revascularization correlated with the increase of uptake of 111In-exendin-3, whereas fully re-established islet vasculature coincided with a stabilized uptake of the radiotracer in the transplant. Here, we demonstrate the importance of islet vasculature for in vivo delivery of radiotracers to transplanted islets and we demonstrate that optimal and stable uptake of exendin four weeks after transplantation opens the possibility for long-term monitoring of islet survival by SPECT imaging.
Microstructure Evolution and Mechanical Behavior of Mo–Si–N Films

The molybdenum silicon nitride (Mo–Si–N) films were deposited by a radio frequency (RF) magnetron reactive dual-gun co-sputtering technique with process control on input power and gas ratio. Composition variation, microstructure evolution, and related mechanical and tribological behavior of the Mo–Si–N coatings were investigated. The N2/(Ar + N2) flow ratios were controlled at 10/20 and 5/20 levels with the tuning of input power on the Si target at 0, 100, and 150 W. As the silicon contents increased from 0 to 33.7 at. %, the film microstructure evolved from a crystalline structure with Mo2N and MoN phases to an amorphous feature with the Si3N4 phase. The analysis of selected area electron diffraction patterns in TEM also indicated an amorphous feature of the Mo–Si–N films when Si content reached 20 at. % and beyond. The hardness and Young’s modulus changed from 16.5 to 26.9 and 208 to 273 GPa according to their microstructure features. The highest hardness and modulus were attributed to nanocrystalline Mo2N and MoN with Si solid-solution. The crystalline Mo–Si–N films showed a smooth tribological track and less wear failure was found. In contrast, the wear track with severe failures were observed for Mo–N and amorphous Mo–Si–N coatings due to their lower hardness. The ratios of H/E and H3/E2 were intensively discussed and correlated to the wear behavior of the Mo–Si–N coatings.
Linguistic recycling in language acquisition

Abstract The paper examines how children quote their parents’ utterances. In other words, it investigates linguistic recycling as an aspect of language learning and how the child-directed speech (CDS) of adults influences child speech (CS). This topic is examined especially in the light of research made in the crosslinguistic project on pre- and protomorphology in language acquisition. Premorphology is characterized by rote-learned forms, which the child has memorized and stored as chunks from CDS (e.g., Finn vetta, Est vett ‘water,’ partitive form). During protomorphology, the child imitates CDS and produces analogical forms (e.g. Finn CDS: soi vs. CS: syoi ‘ate’, Est CDS: utles vs. CS: ukki ‘said’), which then gradually evolve into adult-like grammar. Usage-based approaches to language acquisition rely on the assumption that language structures are learned from language use. Typical material in present-day child language research is based on tape recordings and transcripts made from these recordings. This kind of data makes it possible to take into account the influence of CDS to CS in a more accurate way than the earlier data collecting methods, such as diary material, which usually contains mostly utterances produced by the child do. The article examines how CDS gives models to CS and how the acquisition proceeds from early rote-learned forms to adult-like grammar from the perspective of frequency distributions of inflectional patterns and elaboration on linguistic forms in CDS – CS interaction. On the basis of analyzed speech samples and previous results, it is obvious that the quoting in children’s and adults’ speech is present on different levels of language and is often bidirectional in nature.
Systematic Review and Quantitative Comparison of Cyberattack Scenario Detection and Projection

Intrusion Detection Systems (IDSs) automatically analyze event logs and network traffic in order to detect malicious activity and policy violations. Because IDSs have a large number of false positives and false negatives and the technical nature of their alerts requires a lot of manual analysis, the researchers proposed approaches that automate the analysis of alerts to detect large-scale attacks and predict the attacker’s next steps. Unfortunately, many such approaches use unique datasets and success metrics, making comparison difficult. This survey provides an overview of the state of the art in detecting and projecting cyberattack scenarios, with a focus on evaluation and the corresponding metrics. Representative papers are collected while using Google Scholar and Scopus searches. Mutually comparable success metrics are calculated and several comparison tables are provided. Our results show that commonly used metrics are saturated on popular datasets and cannot assess the practical usability of the approaches. In addition, approaches with knowledge bases require constant maintenance, while data mining and ML approaches depend on the quality of available datasets, which, at the time of writing, are not representative enough to provide general knowledge regarding attack scenarios, so more emphasis needs to be placed on researching the behavior of attackers.
A Robust Double Active Control System Design for Disturbance Suppression of a Two-Axis Gimbal System

This paper presents a robust controller design with disturbance decoupling and rejection of a two-degree-of-freedom (2-DOF) Inertially Stabilized Platform (ISP). The objective of these mechanisms is to stabilize the line of sight (LOS) of imaging sensors pointing towards a specific target. There is currently tremendous interest in ISP applications in marine systems. Such a harsh environment subjects the imaging sensors to multiple disturbances, which requires the design of robust control strategies to enhance the performances of ISP systems. The controller designed in this study is a double active controller composed of an inner compensator, and a feedback controller designed based on the H∞ framework. The main advantage of the proposed controller is that it can be implemented in real time, with lower computational complexity and good performance. In this paper, a comparative experimental study was conducted between the designed controller and an integral sliding-mode controller (ISMC). The comparison was achieved through two major tasks of ISP systems: motion tracking and target tracking.
An open-source research tool to study triaxial inertial sensors for monitoring selected behaviors in sheep

Abstract The use of automated systems for monitoring animal behavior provides information on individual animal behavior and can be used to enhance animal productivity. However, the advancement of this industry is hampered by technology costs, challenges with power supplies, limited data accessibility, and inconsistent testing approaches for confirming the detection of livestock behaviors. Development of open-source research tools similar to commercially available wearable technologies may contribute to the development of more-efficient and affordable technologies. The objective of this study was to demonstrate an open-source, microprocessor-based sensor designed to monitor and enable differentiation among selected behaviors of adult wethers. The sensor was comprised of an inexpensive espressif ESP-32-WROOM-32 microprocessor with Bluetooth communication, a generic MPU92/50 motion sensor that contains a three-axis accelerometer, three-axis magnetometer, a three-axis gyroscope, and a 5-V rechargeable lithium-ion battery. The open-source Arduino IDE software was used to program the microprocessor and to adjust the frequency of sampling, the data packet to send, and the operating conditions. For demonstration purposes, sensors were placed on six housed sheep for three 1-h increments with concurrent visual behavioral observation. Sensor readings (x-, y-, and z-axis) were summarized (mean and SD) within a minute and compared to animal behavior observations (also on a by-minute basis) using a linear mixed-effect model with animal as a random effect and behavioral classifier as a fixed effect. This analysis demonstrated the basic utility of the sensor to differentiate among animal behaviors based on sensed data (P < 0.001). Although substantial additional work is needed for algorithm development, power source testing, and network optimization, this open-source platform appears to be a promising strategy to research wearable sensors in a generalizable manner.
A Quantitative Model‐Based Assessment of Stony Desert Landscape Evolution in the Hami Basin, China: Implications for Plio‐Pleistocene Dust Production in Eastern Asia

Dust plays an important role in climate, and while our current representation of dust production includes shifts in vegetation, soil moisture, and ice cover, it does not account for the role of landscape evolution. Here, we use the Weather Research and Forecasting model coupled to an aerosol chemistry model to quantify the effects of arid landscape evolution on boundary layer conditions, dust production, and radiative properties in the Hami Basin, China, a dynamic stony desert in eastern Asia. Relative to today, altered surface roughness, sediment erodibility, and albedo combine to produce up to a ~44% increase in wind speeds (mean ≈ 15%), up to a ~59% increase in dust loading (mean ≈ 30%), and up to a ~4.4 W m−2 increase in downwelling radiation (mean ≈ 2.4 W m−2) over the Hami Basin. Our modeling results, along with geomorphological data for the western Gobi Desert, provide evidence that stony deserts acted as important Plio‐Pleistocene dust sources.
Discovering Transcriptional Regulatory Rules from Gene Expression and TF-DNA Binding Data by Decision Tree Learning

Background: One of the most promising but challenging task in the post-genomic era is to reconstruct the transcriptional regulatory networks. The goal is to reveal, for each gene that responds to a certain biological event, which transcription factors affect its transcription, and how several transcription factors coordinate to accomplish specific regulations. Results: Here we propose a supervised machine learning approach to address these questions. We build decision trees to associate the expression level of a gene with the transcription factor binding data of its promoter. From the decision trees, we extract regulatory rules that specify how the binding of a combination of several transcription factors affects the expression of a gene. Such rules are easy to interpret, and represent experimentally testable hypotheses. We use a decision tree ensemble approach to increase modeling accuracy and robustness. We also propose a novel method to integrate rules learned from several time series that measure the same biological processes. We apply our method to publicly available cell cycle expression data and transcription factor binding data for the budding yeast. Cross-validation experiments show that our method is highly accurate and reliable. The method correctly identifies all major known yeast cell cycle transcription factors, and assigns them into appropriate cell
Screening bacterial symbionts of marine invertebrates for ribosomally synthesized natural products

ii Declaration. iii Acknowledgements . iv Abbreviations . v List of Tables and Figures . viii Chapter 1 . 18 1. The need for natural product discovery and drug development . 19 2. Classification of natural products . 20 3. The marine environment as a source for natural products . 34 4. Methods for the biodiscovery of natural products . 39 5. Aims and objectives . 53 Chapter 2 . 55
Drivers of ‘inclusive secondary schools’ selection: lessons from Lebanon

ABSTRACT Despite growing interest in educating students with disabilities in mainstream environments over the last two decades in Lebanon, how students with disabilities and their parents identify suitable schools remains ambiguous. This research explores factors that influence students with vision impairments and their parents when selecting a school. It adopts Bronfenbrenner’s [1979. The Ecology of Human Development: Experiments by Design and Nature. Harvard University Press] ecological model. Qualitative data was gathered from 29 pre-secondary and secondary students with vision impairments, 10 parents, 14 headteachers and 9 leaders of governmental and non-governmental organisations. Findings reveal that for those requiring support provision, the school’s willingness to accept them and available support drive school selection. However, when children do not require support provision, academic attainment, convenience and school reputation drive selection. Furthermore, findings showed that autonomous decisions were connected to ‘normalisations’ whereby students with vision impairments acted in a way considered ‘acceptable’ by society. It can be argued that whilst some schools offer access to education for some students with disabilities, those offers, and subsequently student retention, are often dictated by school and supporting authorities and made in an exclusionary rather than inclusionary manner, demanding adaptation from students rather than the educational environment.
Power transformer demand forecast with Box Jenkins ARIMA model

Demand forecasting is based on the principle of trying to forecast the demand for the outputs of enterprises in the field of manufacturing or service for the next periods. It requires the estimation of various future scenarios, if necessary, taking measures and taking steps, and during the application phase, the technique that is most suitable for the characteristics of the examined data set is selected and used. As a result of a healthy analysis carried out in this way, detailed plans and strict measures can be taken for the unknown, negative scenarios of the future. This study analyzes the characteristics of a series of power transformers of a company operating in the electromechanical industry in the past years, and as a result of this analysis, the Box Jenkins Autoregressive Integrated Moving Average method (ARIMA), which best fits the results, is expected to occur for power transformers in the future. It was made to estimate the amount of demand. Within the scope of this study, firstly, the most suitable model was tried to be determined by taking into consideration the past 132 months data of PTS. It was decided that the best choice among the alternative models was the ARMA (4,4) x (0,1) 12 model. The model was found to be stable and it was decided that the root mean square error (RMSE), mean absolute percentage error (MAPE) and Theil inequality coefficient values determined in the performance measurements were appropriate.
Acute kidney injury pathology and pathophysiology: a retrospective review

Abstract Acute kidney injury (AKI) is the clinical term used for decline or loss of renal function. It is associated with chronic kidney disease (CKD) and high morbidity and mortality. However, not all causes of AKI lead to severe consequences and some are reversible. The underlying pathology can be a guide for treatment and assessment of prognosis. The Kidney Disease: Improving Global Outcomes guidelines recommend that the cause of AKI should be identified if possible. Renal biopsy can distinguish specific AKI entities and assist in patient management. This review aims to show the pathology of AKI, including glomerular and tubular diseases.
Seeds of Giant Dodder (Cuscuta reflexa) as a Function of Extract Procedure and Solvent Nature

Seeds of a renowned medicinal plant, giant dodder (Cuscuta reflexa), were assessed to appraise the effect of solvent and extraction technique variation on antioxidants potential. Dodder seed, also called cuscuta seed, has been considered superb tonic in traditional herbal medication for eyes, liver, spleen and kidney. Results show that selected solvent and procedure plays a key role in the composition and activity of extractable material. Three extraction procedures Orbital shaker, Decoction and Ultrasonic assisted extraction and five different solvents n-hexane, ethyl acetate, 100% methanol, 80% methanol and 60% methanol were used to get optimized conditions. Total phenolic and flavonoids content were found maximum in the extracts of aqueous organic system containing 80% methanol in Ultrasonic assisted extraction method but in case of tannins ethyl acetate and Orbital shaker extraction was found more suitable partner. Antioxidant estimation assays showed a little bit variation as DPPH and ABTS exhibited maximum inhibition in 80% methanol and Ultrasonic assisted extraction but 100% methanol was found better for FRAP assay. Decoction results were mostly in between the both Orbital shaker and Ultrasonic assisted extraction. Overall results indicate that coexistence of polar solvents and Ultrasonic assisted extraction gives a better choice for extractability of potent antioxidants from seeds. HPLC analysis confirmed presence of valuable phenolic acids. Pearson’s correlation coefficient reveals a significant relationship between extracted components and antioxidant capacity P< 0.05 or 0.01.
California's Historic Legacy For Landscape Change, the Wieslander Vegetation Type Maps

Abstract This paper presents the digitized edition of the Wieslander Vegetation Type Maps (VTMs). The VTMs were part of the first statewide systematic survey of California's vegetation, conducted 1928–1939. Under the direction of Albert Wieslander, crews recorded the patterns of vegetation that they observed from vantage points across the state. The survey covers 176,901 km2 including border and lake polygons and 165,652 km2 of landscapes that we describe in more detail. There are 251,541 polygons in the full extent of the maps, with 249,630 in the analysis extent. These polygons are annotated with codes indicating the dominant plant species, for which voucher specimens were collected. The maps contain 655 species codes, representing 535 species or sub-species in 229 genera, including 34 Arctostaphylos Adans. and 16 Quercus L. species. The 249,630 polygons contain 26,013 unique combinations of species and levels of disturbance. These can be classified into 525 vegetation alliances or provisional alliances using the 2009 edition of the Manual of California Vegetation, or into 53 of the simpler California Wildlife Habitat Relationships (WHR) classes. The most extensive WHR types in the VTMs are Annual grasslands (25,733 km2) Chamise-redshank chaparral (14,771 km2), Mixed chaparral (9314 km2), and Coastal Scrub (7088 km2). California's Southwestern ecoregion is the most completely surveyed, with 93% of the area mapped, followed by the Central Western ecoregion (88.2%, including the Bay Area), the Sierra Nevada (71.6%), and the Great Valley (39.7%). The VTMs in these ecoregions provide a baseline for assessment of landcover change across large areas, and are an important legacy of the biogeographic patterns of plants and vegetation in California. This paper provides the methods used to digitize the collection and suggestions about how the data may be properly used in future studies.
Breeding Ecology of the Masked Laughingthrush Garrulax perspicillatus, a Cooperative Breeder in Central China

In this paper, we provide for the first time a detailed description of the breeding ecology of the Masked Laughingthrush Garrulax perspicillatus. Our findings indicate that this species is a cooperative breeder with retained offspring. Flocks of Masked Laughingthrushes occurred in winter; these split into smaller breeding groups during the spring. The size of breeding groups varied from three to six individuals (mean = 3.8 individuals, n = 26). Clutches were initiated between early March and early August. Clutch size averaged 3.3 eggs and ranged from two to five (n = 18). The incubation period lasted on average 13.2 days (n = 9) and chicks left the nest after 12 days (n = 23). Breeding groups produce 2–3 broods per year (n = 2). 82.8% of 58 breeding attempts resulted in fledged offspring. Helpers were observed participating in nest-building, incubation and provisioning. The size of breeding groups was significantly related to both the overall frequency of feeding trips to the nest and brood size at fledging, with a higher frequency of feeding trips and more fledglings for larger groups. Hence, both breeders and helpers may potentially derive fitness benefits from helping at the nest.