Miracle-dz/UniFAR-FTUs huggingface dataset:
Baruch

Despite being cited relatively rarely by ancient exegetes, the book of Baruch enjoyed authority and inclusion in most Bible manuscripts because of its association with the prophet Jeremiah. In modern scholarship, the book of Baruch can be read as an example of the creative reuse of scriptures by a Jewish author (or authors) of the Hellenistic or Roman period. Its message about alienation, sin, repentance, and restoration is presented from different angles through the genres of confessional prayer, wisdom poem, and prophetic poem of consolation. Its Deuteronomic theology, which unites the various parts of the book, is very typical of the literature of ancient Judaism. At the same time, it is a powerful reminder to take responsibility for one’s own part in perpetuating structures of social injustice, even when one feels oppressed by them.
Simple tunable dual-band microstrip patch antenna

A novel technique for designing a tunable dual-band microstrip patch antenna is proposed. Dual-band operation is easily achieved by loading a microstrip patch antenna with one varactor diode placed on a small gap between a square patch and a parasitic strip. It is observed from the measured result that the proposed antenna shows a wide tuning range at the two resonant frequencies.
Theory of multiple-stage interband photovoltaic devices and ultimate performance limit comparison of multiple-stage and single-stage interband infrared detectors

A theoretical framework for studying signal and noise in multiple-stage interband infrared photovoltaic devices is presented. The theory flows from a general picture of electrons transitioning between thermalized reservoirs. Making the assumption of bulk-like absorbers, we show how the standard semiconductor transport and recombination equations can be extended to the case of multiple-stage devices. The electronic noise arising from thermal fluctuations in the transition rates between reservoirs is derived using the Shockley-Ramo and Wiener-Khinchin theorems. This provides a unified noise treatment accounting for both the Johnson and shot noise. Using a Green's function formalism, we derive consistent analytic expressions for the quantum efficiency and thermal noise in terms of the design parameters and macroscopic material properties of the absorber. The theory is then used to quantify the potential performance improvement from the use of multiple stages. We show that multiple-stage detectors can achieve.
Benefit‐cost analysis of best management practices implemented to control nitrate contamination of groundwater

Implementing best management practices (BMPs) can reduce nitrate concentration in groundwater, but does it pay to invest in programs that reduce nitrate by encouraging increased adoption of BMPs? In this paper we evaluate water quality improvement by benefit‐cost analysis of adopting BMPs under such a program. The analysis shows that under current levels of contamination, costs of the program to foster BMP implementation will be equal to annually accrued benefits over a period of 6 years. However, under the worsening scenarios of increased nitrate‐N concentrations, the same costs will be equal to the benefits in a 4‐ to 5‐year period. If water quality improves to acceptable levels through adoption of BMPs, the results reveal that in the long run, investing in a BMP program will be more cost effective to reduce contamination than to seek alternative sources of safe drinking water supplies.
An investigation of instructional technology use in middle schools and student achievement on a statewide computer skills test

In today's society, technology is vital in preparing students for the global community to be able to apply, analyze, or evaluate information (Marzano, Pickering, & Pollock, 2001) to be successful in school and in the work world. The purpose of this study was to investigate seventh grade teachers' use of instructional technology in the classroom and the relationship between schools' models of technology instruction and student achievement on the North Carolina Online Test of Computer Skills (NCOTCS). Specifically this study was designed to determine the following: (a) How do seventh grade academic teachers use instructional technology in the classroom? and (b) Is there a relationship between schools' models of technology instruction and student achievement on the NCOTCS? Two data sources were used in this study: a researcher-developed survey and the eighth grade 2006-2007 NCOTCS scores. The researcher-developed survey included a combination of Likert-type items, selected response questions with preset responses, and closed-ended response items. The survey was mailed to 276 seventh grade academic teachers in 42 schools in western North Carolina. The sample consisted of 109 teachers in 34 schools with an overall response rate of 39.5%. The sample for the second research question consisted of 5,967 eighth grade students from the 34 schools whose teachers responded to the survey. Models of technology instruction were defined based on a combination of teacher survey responses and schools' career technical education course offerings. This study resulted in several interesting findings. Some of the North Carolina computer strands were covered by over two-thirds of teachers, but other strands, like database and keyboarding, were integrated less frequently. Over two-thirds of the teachers used a computer for the following activities with their students: word processing, internet skills, electronic reference tools, writing, solving problems, and performing research. There was no statistically significant relationship between schools' models of technology instruction and students' achievement on the NCOTCS. Recommendations were made for using technology to meet students' technological needs.
Extraction of Online Monitoring Signals by Lifting Wavelet in Digital Substation

On the requirement of fast signal processing and transmitting in time in digital substation, this paper presents an approach of lifting wavelet for extracting online monitoring signals of the electrical plants in digital substation. The lifting wavelet de-nosing algorithm is based on a threshold estimation formula based on Stain unbiased risk estimation (SURE). The de-noising experiments of stationary signals and non-stationary signal, i.e. simulative partial discharge (PD) signal are presented. The results show that the white noise can be removed effectively by the proposed lifting wavelet. Meanwhile, the lifting wavelet is a much less time-consuming scheme and exhibits a promising prospect in practical application.
Packaged bulk micromachined resonant force sensor for high-temperature applications

We present a packaged micro resonator for static load measurement under high temperature, performing with high precision and a resolution better than 100 ppm. There is an industrial need for such measurement tasks, however, such sensing cells are not available so far. To minimize temperatures stress we developed an all-in-silicon, in difference to micro machined resonant force sensors, which have been published. We propose a force sensor where load coupling, the excitation and detection of the vibration of the micro resonator are integrated in one and the same single crystal silicon package. The complete single crystal design together with a fiber-optical on-chip detection method will allow measurements at high temperatures. A considerable degree of freedom for the resonator's shape design, as needed for the investigation of filer mechanisms, is given by a DRIE fabrication method.
Harmonic Distortion in Switched Current Cells Due to Settling Error

An analysis of the harmonic distortion in switched-current cells produced by the non-linear settling error is presented. Two approaches for computing the harmonic components are addressed: discrete-time Fourier series and power series expansion. They are based on the large signal behavior of the SI cell. A compact and flexible expression is obtained with series expansion. An alternative expression is presented for cases where only the settling error magnitude is required. The effect of charge redistribution between the input and the sampling nodes is analyzed. It is shown that including that effect, the harmonic distortion is increased, and the DC gain of the SI integrator is reduced. An analysis of the total harmonic distortion when clock-feed-through and non-linear settling error are both taken into account is presented. It is demonstrated that minimum distortion is reached for a given capacitive value. For a SI cell designed with 0.8 μm standard CMOS technology working at a sampling frequency of 8 MHz, a minimum THD of −72 dB can be obtained with a Cgs ≈ 2.4 pF.
Systematic review of the effect of perch height on keel bone fractures, deformation and injuries, bone strength, foot lesions and perching behavior

This report provides a summary of four systematic reviews on the impact of perch height on laying hen keel bone fractures, deformation and injuries, bone strength, foot lesions and perching behavior. After conducting a scoping review and identifying outcomes of interest, the review protocols were developed. An extensive literature search was conducted in information sources such as CABI, PUBMED and relevant conference proceedings. 1518 abstracts were assessed for relevance and 9 studies reported perch use and 1 reported keel injuries. No studies reported summary effect sizes; therefore it was not possible to conduct a meta-analysis. In lieu of a formal meta-analysis, a descriptive analysis was conducted, which plotted reported perch height against metrics of perch use. This descriptive analysis was not able to account for lack of independence, differences in sample size and other importance sources of heterogeneity such as cage height. The descriptive analysis suggested a positive association with metrics that measured perch use and height, i.e., increased usage was associated with increased height. © European Food Safety Authority, 2015
A Predictive Model of Crude Oil Dispersion in Water: A Case Study of the Niger-Delta Area of Nigeria

Abstract The qualities of the environment are adversely affected by the massive activities of the petroleum industry, especially in Nigeria, with a particular reference to the Niger-Delta Area. The use of oil and other natural resources without losses is almost impossible; losses normally occur during exploration, drilling, transportation, processing, storage, and use. Discharging gases, liquids, and solid wastes into the environment threatens the health of the populace and damage the overall qualities of the environment by rendering the farm land and water bodies unusable. This work, therefore, focuses on the development of a predictive model for spreading rate, spreading coefficient, and flow dimensions of experimentally determined physical properties of spilled oil and stream medium. The developed model is simulated and the results obtained are compared with the experimental results. The statistical analyses of the experimental and simulated results show a little variation between them with a correlation coefficient in the range of 0.9938–0.9999 and standard error in the range of 0.25–29.94 depending on the type and volume of oil spilled. The simulated results also indicate that the extent of spread depends on the physical properties of the crude, aquatic environment dimension, exposure time, and quality of oil discharged.
DİKEY SIÇRAMA SIRASINDA KISA MESAFE KOŞUCULARI VE FUTBOLCULARIN DİZ EKSTENSÖR KASLARINA AİT EMG AKTİVETELERİNİN KARŞILAŞTIRILMASI

Amac: Bu calismanin amaci dikey sicrama sirasinda kisa mesafe kosuculari ve futbolcularin diz ekstensor kaslarina (vastus lateralis ve vastus medialis) ait EMG aktivitelerinin karsilastirilmasidir. Yontem: Bu calismaya 53 sporcu (32 kisa mesafe kosucusu, ( ) yas: 21,91 ± 1,55 yil; vucut agirligi: 67,29 ± 8,11kg; boy: 176,81 ± 5,87cm ve 21 futbolcu, ( ) yas: 23,33 ± 1,77 yil; vucut agirligi: 69,50 ± 7,06kg; boy: 174,33 ± 5,65cm) gonullu olarak katilmistir. Bes dakikalik standart bir isinmadan sonra deneklerin maksimal dikey sicramalari sirasinda vastus lateralis (VL) ve vastus medialis (VM) kaslarindan elde edilen EMG sinyalleri kaydedildi ve Root Mean Square (RMS) degerleri hesaplandi. Dikey sicrama test protokolu sicrama performansini (sicrama yuksekligi ve maksimum anaerobik guc) belirlemek icin kullanildi. Verilerin analizinde; sicrama yuksekligi, maksimum anaerobik guc (MAG), VL ve VM kaslarina ait RMS degerleri bakimindan kisa mesafe kosuculari ve futbolcularin karsilastirilmasi icin Bagimsiz Orneklemlerde t-testi kullanilmistir. Bulgular: Bu calismanin bulgularina gore kisa mesafe kosucularinin VL (t= 3,318; p 0,05) ve MAG (t= -1,868; p>0,05) degerleri acisindan iki grup arasinda istatistiksel olarak fark bulunmamistir. Sonuc: Bu calismada, spor dallarina bagli olarak EMG aktivitelerinin farklilasabilecegi sonucuna varilmistir. Anahtar Kelimeler: EMG, Root mean square, Dikey Sicrama.
Wavelet analysis of partial discharges acoustic waves obtained using an optical fibre interferometric sensor for transformer applications

The main problem in power transformers is the degradation of the isolation, and partial discharges are a major contribution to this shortcoming. Partial discharges inside medium and high power transformers generate ultrasonic pressure waves which are detected, in this work, with an optical fibre interferometric sensor. The Mach-Zehnder interferometric sensor implemented, for the detection of partial discharges inside power transformers, is described. This sensor allows a high level sensitivity to be achieved for the typical small pressure variations created by partial discharges. Wavelet analysis is used to identify the acoustic patterns instead of more commonly used Fourier analysis. Acoustic signals contain numerous non-stationary or transitory characteristics that Fourier analysis does not allow them to be obtained: when transforming to frequency domain, temporal information disappears. It is possible to state when a particular event took place. The wavelet analysis helps to solve this problem. Some of the results of which are presented here. These results are compared to those obtained with piezoelectric acoustic sensors, when looking for the best wavelet application, showing good agreement between both methods. We have obtained clear signal between 15-17 kHz and, for the first time, wavelet analysis has provided a tool to identify the shape of the acoustic waves associated to partial discharges.
Pulsed eddy current: Finding corrosion independently of transducer lift-off

The pulsed eddy current (PEC) technique holes the potential of becoming the primary means of detecting corrosion in multi-layer structures. However, it is still considered an experimental technique because there are stumbling blocks that must be overcome before it finds acceptance as a field application. In particular, it is necessary to be able to interpret the transient response and distinguish between transducer lift-off, defect locations, and defect size when these effects occur simultaneously. Thus far, most researchers in pulsed eddy currents have not considered lift-off variations in their studies. This parameter is kept constant as it complicates the analysis of pulsed eddy current transient responses. However, lift-off variations will be encountered during field inspections. This paper takes this issue into consideration. Specifically, the paper details an inspection technique which enables the positive identification of corrosion in a multi-layer structure. Moreover, the proposed technique provides a quantitative evaluation of material loss which is independent of lift-off variations.
What now for nuclear

The public perception of nuclear energy has taken a battering in the wake of the Fukushima nuclear accident. It had been a painfully sluggish process, but since the nightmare scenario of a complete meltdown of a nuclear plant 25 years ago at Chernobyl, the public had, inch by inch, been creeping towards a grudging acceptance of a nuclear future.
Spatial-Net: A Self-Adaptive and Model-Agnostic Deep Learning Framework for Spatially Heterogeneous Datasets

Knowledge discovery from spatial data is essential for many important societal applications including crop monitoring, solar energy estimation, traffic prediction and public health. This paper aims to tackle a key challenge posed by spatial data - the intrinsic spatial heterogeneity commonly embedded in their generation processes - in the context of deep learning. In related work, the early rise of convolutional neural networks showed the promising value of explicit spatial-awareness in deep architectures (i.e., preservation of spatial structure among input cells and the use of local connection). However, the issue of spatial heterogeneity has not been sufficiently explored. While recent developments have tried to incorporate awareness of spatial variability (e.g., SVANN), these methods either rely on manually-defined space partitioning or only support very limited partitions (e.g., two) due to reduction of training data. To address these limitations, we propose a Spatial-Net to simultaneously learn a space-partitioning scheme and a deep network architecture with a Significance-based Grow-and-Collapse (SIG-GAC) framework. SIG-GAC allows collaborative training between partitions and uses an exponential reduction tree to control the network size. Experiments using real-world datasets show that Spatial-Net can automatically learn the pattern underlying heterogeneous spatial process and greatly improve model performance.
IoT Powered Cancer Observation System.

Cancer is a global challenge and the second leading cause of death worldwide as reported by the World Health Organization. With the current global pandemic caused by the novel coronavirus, cancer patients are identified as having increased risk of mortality. With the growing number of cancer patients every year, the need for a continuous and round the clock observation system has become quite imperative. An Internet of Things (IoT) based system for monitoring cancer patients has the potential to timely detect cancer related symptoms in its early stages, to continuously monitor cancer diagnosed patients and to monitor those that got cured for post-treatment measures. This paper proposes a multi-layered architecture of an IoT-based cancer observation system that can be utilized as a platform to remotely diagnose and monitor cancer patients. An implementation framework of the proposed system is also presented is this work, along with a prototype design of a Patient Side Unit (PSU) represented by a wearable wrist band. The proposed system has the potential to be applied as a solution for reducing expensive and exhausting hospital visits, while gaining similar quality of medical services when residing at home.
MusicStand: Listening to Song Lyrics Using a Map Query Interface

Music is present in numerous forms in our daily lives and is deemed essential to it. Multiple applications have been proposed to let users check into a location and tag that check-in with the song to which they are listening. This is time-consuming and requires much work in voluntary manual tagging. One of our major goals is to automatically determine the spatial scope of a song. Our research challenge is how to identify locations in unstructured and badly-cased lyric texts (e.g., all caps, camel case, non-cased, studly caps, etc.) that are mostly submitted by volunteers from all over the world. Uncertain casing leads to a severe performance drop when using named entity recognition (NER) and geographical information is often lost due to a failure to correctly identify geographical entities. We overcome this failure by normalizing the lyrics in the sense that the information loss is minimized and propose the MusicStand(http://musicstand.umiacs.io/) framework to process/input lyric text that involves three steps: cleaning, truecasing, and geotagging. MusicStand enables users to explore or search a music collection where the goal is to find and play songs about particular geographic entities (i.e., toponyms) using a map query interface. Note that the collection may be static (e.g., a songbook) or dynamic (e.g., a radio playlist).
Feat-SKSJ: Fast and Exact Algorithm for Top-k Spatial-Keyword Similarity Join

Due to the proliferation of GPS-enabled mobile devices and IoT environments, location-based services are generating a large number of objects that contain both spatial and keyword information, and spatial-keyword databases are receiving much attention. This paper addresses the problem of top-k spatial-keyword similarity join, which outputs k object pairs with the highest similarity. This query is a primitive operator for important applications, including duplicate detection, recommendation, and clustering. The main bottleneck of the top-k spatial-keyword similarity join is to compute the similarity of a given object pair. To avoid this computation as much as possible, a state-of-the-art algorithm utilizes a filter that can skip the exact similarity computation of a given pair. However, this algorithm suffers from a loose threshold at the first stage, a high filtering cost, and the impossibility of filtering many pairs in a batch. We propose Feat-SKSJ, which removes these drawbacks and quickly outputs the exact result. Extensive experiments on real datasets show that Feat-SKSJ is significantly faster than the state-of-the-art algorithm.
A Constraint-based Formulation of Stable Neo-Hookean Materials

In computer graphics, soft body simulation is often used to animate soft tissue on characters or rubber like objects. Both are highly incompressible, however commonly used models such as co-rotational FEM, show significant volume loss, even under moderate strain. The Neo-Hookean model has recently become popular in graphics. It has superior volume conservation, recovers from inverted states, and does not require a polar decomposition. However, solvers for Neo-Hookean finite-element problems are typically based on Newton methods, which require energy Hessians, their Eigen-decomposition, and sophisticated linear solvers. In addition, minimizing the energy directly in this way does not accommodate modeling incompressible materials since it would require infinitely stiff forces. In this paper we present a constraint-based model of the Neo-Hookean energy. By decomposing the energy into deviatoric (distortional), and hydrostatic (volume preserving) constraints, we can apply iterative constrained-optimization methods that require only first-order gradients. We compare our constraint-based formulation to state-of-the-art force-based solvers and show that our method is often an order of magnitude more efficient for stiff volume preserving materials.
A simple carrier-based neutral point potential regulator for three-level diode clamped inverter

Three-level diode clamped inverter is a proven technology nowadays in medium and high power applications. Despite of its several advantages such as harmonic reduction and achieving high voltage and high power capabilities without series and parallel connections of switching devices, neutral point potential (NPP) variation is the inherent problem with this topology. This paper presents a simple NPP regulator based on addition of offset voltage to the reference sinusoidal voltages. This not only regulates the NPP, but also reduces the output voltage and current harmonics of the inverter. Simultaneously, second harmonic get reduced which may otherwise produce torque pulsations, harmonic currents and power losses. Simulation and experimental results have been presented to validate the concept.