Miracle-dz/UniFAR-FTUs huggingface dataset:
Early metallurgy in the Near East

This is an account of an international reconnaisance expedition made in 1968, by a team of 10 persons under the leadership of T.A. Wertime, which traveled from Kabul in Afghanistan across Iran to Ankara, Turkey, over a distance of 12,000 km. and examined more than 40 sites of early metal working. Most sites belong to the Islamic period or later, but many could have been worked much earlier, especially those containing native copper. In many apparently a mixed metallurgy was practiced producing mainly copper, lead, zinc and iron. The existence of tin deposits was not confirmed. The production of zinc in early Islamic times is surprising but it does bear out descriptions of travelers like Hamd-Allah, Marco Polo and others. Very little evidence was found for the cupellation of land areas to produce silver. Furnace slag was found at many sites. The specimens of slag were examined by normal metallographic means, sometimes supplemented by x-ray fluorescence analysis. See reports of previous expeditions with the same aim made in 1962 and 1968 and described by T. A. Wertime in Science 146 (1964), pp. 1257-1267, (AATA (6)-H4-29) and 159 (1968), pp. 927-935, (AATA 8-1067). 24 refs. (an expansion of AATA 8-1573).
Undescribed species have higher extinction risk than known species

Newly discovered species are often threatened with extinction but in many cases have received limited conservation effort. To guide future conservation, it is important to determine the extinction risk of newly described species. Here, we test how time since formal description of a species is linked to its threat status to obtain a better insight into the possible threat status of newly described species and as yet undescribed species. We compiled IUCN Red List data for 53,808 species from five vertebrate groups described since 1758. Extinction risk for more recently described species has increased significantly over time; the proportion of threatened species among newly described species has increased from 11.9% for species described between 1758 and 1767 to 30.0% for those described between 2011 and 2020. Based on projections from our analysis, this could further increase to 47.1% by 2050. The pattern is consistent across vertebrate taxonomic groups and biomes. Current species extinction rates estimated from data of all known species are therefore highly likely to be underestimated. Intensive fieldwork to boost discovery of new species and immediate conservation action for newly described species, especially in tropical areas, is urgently required.
Intraoperative Load Sensing in Total Knee Arthroplasty Leads to a Functional but Not Clinical Difference: A Comparative, Gait Analysis Evaluation

Introduction: Although Total Knee Arthroplasty (TKA) is a successful procedure, a significant number of patients are still unsatisfied, reporting instability at the mid-flexion range (Mid-Flexion Instability-MFI). To avoid this complication, many innovations, including load sensors (LS), have been introduced. The intraoperative use of LS may facilitate the balance of the knee during the entire range of motion to avoid MFI postoperatively. The objective of this study was to perform a Gait Analysis (GA) evaluation of a series of patients who underwent primary TKA using a single LS technology. Methods: The authors matched and compared two groups of patients treated with the same posterior stabilized TKA design. In Group A, 10 knees were intraoperatively balanced with LS technology, while 10 knees (Group B) underwent standard TKA. The correct TKA alignment was preoperatively determined aiming for a mechanical alignment. Clinical evaluation was performed according to the WOMAC, Knee Society Score (KSS) and Forgotten Joint Score, while functional evaluation was performed using a state-of-the-art GA platform. Results: We reported excellent clinical results in both groups without any statistical difference in patient reported outcome measurements (PROMs); from a functional standpoint, several GA space–time parameters were closer to normal in the sensor group when compared to the standard group, but a statistically significant difference was not reached. Conclusions: Gait Analysis represents a valid method to evaluate TKA kinematics. This study, with its limitations, showed that pressure sensitive technology represents a valid aid for surgeons aiming to improve the postoperative stability of TKA; however, other factors (i.e., level of intra-articular constraint and alignment) may play a major role in reproducing the normal knee biomechanics.
ON-DEMAND FREQUENCY SWITCHABLE ANTENNA ARRAY OPERATING AT 24.8 AND 28 GHZ FOR 5G HIGH-GAIN SENSORS APPLICATIONS

A miniaturized in size linear multiple-input multiple-output (MIMO) antenna array operating on demand at 28GHz and 24.8GHz for 5G applications is presented and investigated in this research work. The antenna array has the capability to switch and operate efficiently from 28GHz to 24.8GHz with more than 15 dB gain at each frequency, having 2.1GHz and 1.9GHz bandwidth, respectively. The unit cell of the proposed antenna array consists of a transmission line (TL) fed circular patch connected with horizontal and vertical stubs. The vertical stubs are used to switch the operating frequency and mitigate the unwanted interaction between the adjacent elements of the antenna array to miniaturize the overall dimension of the array. The proposed antenna array is compared with the recent works published in the literature for 5G applications to demonstrate the features of miniaturization and high gain. The proposed array is a potential candidate for 5G sensors applications like cellular devices, drones, biotelemetry sensors, etc.
Study on the Incorporation of Oat and Yeast β-Glucan into Shortbread Biscuits as a Basis for Designing Healthier and High Quality Food Products

According to international health and food organizations and authorities, people should limit fat intake since fat is the most caloric component of food and it is often a source of unsafe saturated fatty acids (FA) and trans isomers. The greatest health benefits come from replacing shorts with dietary fiber molecules. The aim of the study was to determine the possibility of reducing shortening content, which has an undesirable profile of FA, by addition of β-glucan molecules in shortbread biscuits. The effect of oat and yeast β-glucan supplementation on physical and sensory quality of products with reduced fat content (max 15%) were studied. It was shown that the substitution of shortening by β-glucan in shortbread biscuits is possible to a limited extent. Reduction in product energy value (up to 36 kcal/100 g) and content of undesirable FA (maximum 2.1 g/100 g) and increased of β-glucan content, regardless of the type, caused deterioration of biscuits quality and affected changes during storage. The substitution of shortening by β-glucan in food is a good way to improve nutritional value by increasing the amount of dietary fiber molecules, reducing calories, and amount of SFA in diets.
Distribution and diversity of benthic macroinvertebrates in the Mohlapitsi River, South Africa

Abstract Freshwater ecosystems are facing degradation from human activities in the form of alterations of flow regimes, changes in land-use, and intensive water abstraction, in turn generating adverse effects on biodiversity and ecological functionality. Efficient assessment of river/stream ecosystem response to such anthropogenic changes is urgently needed. Many human activities that have an effect on water quality and river health are increasing along the Mohlapitsi River, which used to be one of the rivers with good water quality in South Africa. The aim of the study was to assess spatial variation in macroinvertebrate assemblages in relation to water quality of the Mohlapitsi River. A combination of canonical correspondence analysis and univariate analyses were used to examine the macroinvertebrate assemblages at six different sites of the Mohlapitsi River. The spatial difference in macroinvertebrate abundance was mostly related to changes in water quality. The number of taxa and the diversity of macroinvertebrates remained relatively high across the river as compared to other rivers in the Olifants River System. The midstream and downstream sites were mostly dominated by macroinvertebrates tolerant to disturbance/pollution. The most abundant family was the Thiaridae (about 60%) and mainly occurred in the midstream and downstream sites of the river (more disturbed sites). The study showed a higher evenness index in the upstream than the midstream and downstream sites which is an indication of good water quality at the upstream sites of the river. The results suggest that the river is being subjected to a moderate environmental pollution, which requires continuous assessment and monitoring to determine causes and initiate remedial measures.
Three-dimensional Magnetic Field Analysis and Optimum Design of Electromagnetic System for Micro-electro-mechanical Relay

With the advantage of small volume, low power consumption, quickly switch, and high stability, the micro-electro-mechanical relay may bridge the performance and economic gaps between conventional electromagnetic relay and solid state relay. Analysis of three-dimensional magnetic field is the foundation work for optimum design of electromagnetic system. In this paper the magnetic distribution character of micro-electro-mechanical relay was analyzed by applying Biot-Savart law and integral equation method(IEM). The results of IEM and FEM show the method which used in analyzing three-dimensional stationary magnetic field for Micro-electro-mechanical relay is feasible. The revised schemes were designed basing on the original model features, and central planer coil structure was preferable by analyzing electromagnetic attraction force of movable contact. The optimum design was realized associated with the relationship among coil turns, exciting current and electromagnetic attraction force. The conclusions are valuable in theory and practice to design Micro-electro-mechanical relay.
SnSe-Coated Microfiber Resonator for All-Optical Modulation

In this study, a tin monoselenide (SnSe)-based all-optical modulator is firstly demonstrated with high tuning efficiency, broad bandwidth, and fast response time. The SnSe nanoplates are deposited in the microfiber knot resonator (MKR) on MgF2 substrate and change its transmission spectra by the external laser irradiation. The SnSe nanoplates and the microfiber are fabricated using the liquid-phase exfoliation method and the heat-flame taper-drawing method, respectively. Due to the strong absorption and enhanced light–matter interaction of the SnSe nanoplates, the largest transmitted power tunability is approximately 0.29 dB/mW with the response time of less than 2 ms. The broad tuning bandwidth is confirmed by four external pump lights ranging from ultraviolet to near-infrared. The proposed SnSe-coated microfiber resonator holds promising potential for wide application in the fields of all-optical tuning and fiber sensors.
Time Petri-Net based Stuck-at Fault Model for Asynchronous Circuits Testing

On one hand, the major advantage of asynchronous circuits over synchronous ones is that their speed is not limited by the slowest part. On the other hand, the design and testing of asynchronous circuits is more complicate. By inserting some redundant part in order to guarantee that circuits operated correctly, there is the state exploration problem. Moreover, the absence of clock in asynchronous circuits makes it difficult to determine the exact state. As the result, asynchronous circuits need an appropriate method for testing. This paper proposes an algorithm for Time Petri Net (TPN) based stuck-at fault model, which has a hierarchical property in order to investigate the behavior of the faulty asynchronous circuits.
The DC Transformer Power Electronic Building Block: Powering Next-Generation Converter Design

Power electronics has evolved from being only present in a few applications such as variable speed drives in the 1970s to becoming ubiquitous, present in almost every industrial application, and powering our daily life. In this ever-expanding market, power converters have become a mature technology covering a wide range of applications, providing solutions from a few watts (e.g., LED drivers) to gigawatts (e.g., high-voltage direct current systems). Competition has driven technology development in pursuit of cost reduction, increased efficiency, performance improvements, high power quality, higher power density, reliability, and an accelerated time to market. To meet these requirements, power converter design has been driven toward a more modular approach based on embedded systems, intelligent power modules, and power electronics building blocks (PEBBs) [1].
Gaining insights in datasets in the shade of “garbage in, garbage out” rationale: Feature space distribution fitting

This article emphasizes comprehending the “Garbage In, Garbage Out” (GIGO) rationale and ensuring the dataset quality in Machine Learning (ML) applications to achieve high and generalizable performance. An initial step should be added in an ML workflow where researchers evaluate the insights gained by quantitative analysis of the datasets sample and feature spaces. This study contributes towards achieving such a goal by suggesting a technique to quantify datasets in terms of feature frequency distribution characteristics. Hence a unique insight is provided into how the features in the available dataset samples are frequent. The technique was demonstrated in 11 benign and malign (malware) Android application datasets belonging to six academic Android mobile malware classification studies. The permissions requested by applications such as CALL_PHONE compose a relatively high‐dimensional binary feature space. The results showed that the distributions fit well into two of the four long right‐tail statistical distributions: log‐normal, exponential, power law, and Poisson. Precisely, log‐normal was the most exhibited statistical distribution except the two malign datasets that were in exponential. This study also explores statistical distribution fit/unfit feature analysis that enhances the insights in feature space. Finally, the study compiles phenomena examples in the literature exhibiting these statistical distributions that should be considered for interpreting the fitted distributions. In conclusion, conducting well‐formed statistical methods provides a clear understanding of the datasets and intra‐class and inter‐class differences before proceeding with selecting features and building a classifier model. Feature distribution characteristics should be one to analyze beforehand.
Informational masking and attention focussing on environmental sound

It has been established that the appreciation of a soundscape depends on the cognitive and emotional evaluation of the sonic environment, with particular emphasis on the meaning associated with the perceived sound [1]. Before meaning can be attributed to a sound, it nevertheless has to be detected and recognised. Energetic masking due to the working of the inner ear has been mentioned as a reason for not hearing an environmental sound and thus proposed as a potential solution for improving negative soundscapes [2][3][4]. The central nervous system however also plays a crucial role. Informational masking may prohibit recognising or understanding the sound. In this context attention focussing is always around the corner. As attention gets focussed on an auditory stream, informational masking could be reduced even if the signal to noise ratio drops considerably after initial detection. Making practical use of this knowledge in the acoustic design of (urban) outdoor spaces is one of the long-term goals of soundscape research.
Geospatial Analysis of Geo-Ecotourism Site Suitability Using AHP and GIS for Sustainable and Resilient Tourism Planning in West Bengal, India

The current study intended to geospatially analyze the potentiality and site suitability of geo-ecotourism in West Bengal, India. The state of West Bengal is a great platform for diverse tourism and has enormous potential to cultivate geo-ecotourism, as has come up in recent years. The current effort throws some valuable light on the possibility of turning the many geologically, geomorphologically and ecologically significant tourist spots of West Bengal into geo-ecotourism sites, aided with geospatial techniques. The study deals with the qualitative and quantitative investigation of the potentiality of the whole state by dividing it into several geo-ecotourism zones, based on its physiographic setting and Land Use Land Cover (LULC) features, using satellite image data. The application of geospatial technology combined with Remote Sensing (RS) and Geographic Information System (GIS) was employed for this geospatial analysis to portray the potential zones using cartographic and statistical techniques. Furthermore, nine criteria were selected to run the Analytic Hierarchy Process (AHP) method to determine the site suitability for geo-ecotourism. The present submission attempts to record the mapping and analysis of geo-ecotourism of West Bengal employing a secondary database, an expert's opinions and primary observations, with the application of the AHP method and GIS. The outcomes of the study were found to be very significant, as they indicate a proviso for geo-ecotourism development in the state and will contribute to the formation of location-specific planning and the sustainable management of geo-ecotourism.
Exploring Language Markers of Mental Health in Psychiatric Stories

Diagnosing mental disorders is complex due to the genetic, environmental and psychological contributors and the individual risk factors. Language markers for mental disorders can help to diagnose a person. Research thus far on language markers and the associated mental disorders has been done mainly with the Linguistic Inquiry and Word Count (LIWC) program. In order to improve on this research, we employed a range of Natural Language Processing (NLP) techniques using LIWC, spaCy, fastText and RobBERT to analyse Dutch psychiatric interview transcriptions with both rule-based and vector-based approaches. Our primary objective was to predict whether a patient had been diagnosed with a mental disorder, and if so, the specific mental disorder type. Furthermore, the second goal of this research was to find out which words are language markers for which mental disorder. LIWC in combination with the random forest classification algorithm performed best in predicting whether a person had a mental disorder or not (accuracy: 0.952; Cohen’s kappa: 0.889). SpaCy in combination with random forest predicted best which particular mental disorder a patient had been diagnosed with (accuracy: 0.429; Cohen’s kappa: 0.304).
XCelHD: An Efficient GPU-Powered Hyperdimensional Computing with Parallelized Training

Hyperdimensional Computing (HDC) is an emerging lightweight machine learning method alternative to deep learning. One of its key strengths is the ability to accelerate it in hardware, as it offers massive parallelisms. Prior work primarily focused on FPGA and ASIC, which do not provide the seamless flexibility required for HDC applications. Few studies that attempted GPU designs are inefficient, partly due to the complexity of accelerating HDC on GPUs because of the bit-level operations of HDC. Besides, HDC training exhibited low hardware utilization due to sequential operations. In this paper, we present XCelHD, a high-performance GPU-powered framework for HDC. XCelHD uses a novel training method to maximize the training speed of the HDC model while fully utilizing hardware. We propose memory optimization strategies specialized for GPU-based HDC, minimizing the access time to different memory subsystems and redundant operations. We show that the proposed training method reduces the required number of training epochs by four-fold to achieve comparable accuracy. Our evaluation results on NVIDIA Jetson TX2 show that XCelHD is up to $35\times$ faster than the state-of-the-art TensorFlow-based HDC implementation.
Modified Economic Manufacturing Quantity Model for Product with Quality Loss under the Serial Production System and Rectifying Inspection Plan

The optimum process mean setting is an important method of modern statistical process control for determining the quality level. In 1994, Al-Sultan presented a single sampling plan applied in determining the optimum process mean for two machines in a serial production system. However, he didn’t consider the quality cost for the product within the specification limits, pointed out that the non-conforming items in the sample of accepted lot is replaced or eliminated from the lot, and proposed an integrated model with production and quality. In this paper, the author proposes a modified economic manufacturing quantity (EMQ) model based on a modified Al-Sultan’s model with k machines in a serial production system and asymmetric quadratic quality loss function for obtaining the maximum expected total profit per unit of time.
Minimal decrease in triathlon running performance compared to isolated running performance is important for sprint triathlon success

A strategy to improve running performance at the end of a triathlon (TR) is minimizing fatigue from the preceding exercise. However, little is known about decrease in TR compared to isolated running (IR) performance and the degree at which it changes. This study examined the decrease in TR performance compared with IR performance and the degree of change in the sprint triathlon competition results. We searched the web (http://www.jtu.or.jp/) for the official result times of certification competitive events from 2013 to 2016 of the Japan Triathlon Union and elite categories participating in the Asia Cup Osaka sprint triathlon from 2013 to 2016 of the International Triathlon Union. Data of 236 athletes who finished IR and TR in the same year were analyzed. The average time was significantly longer in TR than in IR and the effect size was large, regardless of competition years and sex (p < 0.01). The IR time variation (coefficient of variation) was 3.7? 8.2%, while the rate of change in performance variation was 35.6? 95.0%. The overall triathlon time and the rate of change in performance were significantly correlated (Speaman? rs = 0.47? 0.76, p < 0.05). TR performance was lower than the IR performance and the degree varied widely among individuals. For elite triathletes who have homogeneous IR performance, a minimal decrease in TR compared to IR performance effectively increases sprint triathlon success.
Advances in the Synthesis and Applications of Mussel-Inspired Polymers

Abstract Learning from nature and promoting original design concept is a significant way to develop functional materials with outstanding performance. Even since the discovery of the role of DOPA residues in the strong adhesion ability of mussel foot-byssus proteins (Mfps), numerous efforts have been devoted into the design of mussel-inspired polymers and many outstanding results have been achieved. Herein, this review is aimed to summarize the recent progress in mussel-inspired polymers in the last decade, including further explorations in the structure and functionality of Mfps, the design trend and driving forces for mussel-inspired polymers, and the applications and prospects for functional mussel-inspired polymers. We anticipate that this review can provide some guidance for researchers to explore novel biomimetic materials.