Miracle-dz/UniFAR-FTUs huggingface dataset:
An evaluation of two grassland-based systems of mid-season prime lamb production using prolific ewes of two genotypes

A 4-year study was undertaken to evaluate the effects of two contrasting management systems [year-round grazing (YRG) and normal seasonal grazing followed by indoor feeding during winter (GWF)] on performance of mid-season lambing ewes. On the GWF system, the annual stocking rate was 14.4 ewes/ha, grass silage was conserved for winter feeding indoors, and the ewes were lambed indoors and were then turned out to pasture. The YRG system was stocked at 10.5 ewes/ha, was grazed during the winter, had outdoor lambing and the animals had access to all the farmlet for summer grazing. The ewes were Belclare and Cheviot × Belclare which were balanced across systems. Mean lambing dates and fertiliser N application rates were 20 and 30 March, and 85 and 92 kg/ha, for the GWF and YRG systems, respectively. Concentrate supplementation during late pregnancy was similar on both systems. For the GWF and YRG systems, litter size, lamb mortality, number of lambs reared, birth weight (kg), weaning weight (kg) and lamb carcass output (kg/ha) were 2.17 and 2.24 (s.e. 0.038), 10.1 and 13.8% (P = 0.05), 1.77 and 1.78 (s.e. 0.042), 4.0 and 4.7 (s.e. 0.05, P < 0.001), 27.9 and 30.8 (s.e. 0.25, P < 0.001) and 469 and 348, respectively. Belclare ewes had a higher litter size (2.34 v 2.07; s.e. 0.038, P < 0.001) and number of lambs reared per ewe joined (1.86 v 1.69; s.e. 0.048, P < 0.01) than the Cheviot × Belclare ewes. There were no significant interactions between system and ewe breed type. It is concluded that the YRG system of prime lamb production was sustainable using prolific ewes but at a reduced stocking rate (�26%) and with greater lamb mortality relative to the GWF system. Ewe genotypes with a mean litter size of up to 2.34 lambs are suitable for both systems. Lamb carcass output of 501 kg/ha was achieved from a primarily grass-based system of mid-season prime lamb production using prolific ewes (Belclare).
Fire in the boreal forest: Proximate effects on reproduction and long-term consequences for territory occupancy of American kestrels

Abstract There is currently a great deal of interest in documenting habitat use of birds in the boreal forest, especially in response to disturbances such as harvesting and forest fires. Studies have shown that some avian species are much more common in recently burned areas, whereas others are absent. Despite this, we know little about the immediate effect of a large forest fire, and its considerable alteration of habitat, on birds during a single breeding season. In 1995, a 72,000-ha forest fire in our study area gave us the opportunity to assess the effects of fire on reproduction of American kestrels (Falco sparverius) in comparison to an adjacent control area. In addition, we also examined territory occupancy by kestrels in the burned and control areas 8 y following the fire. We found no immediate effect of the fire on body condition of adult kestrels, their ability to hatch eggs, or to fledge at least one young. Birds breeding in the area that burned, however, did fledge fewer offspring per nest, and these nestlings had reduced body mass compared to control nests, possibly because of an immediate reduction in available prey following the fire. Nonetheless, given the profound alteration of habitat following the fire, the fact than any birds remained to continue breeding is remarkable. Territory occupancy of the burned area in 2003 was similar to 1995, the year of the fire, but occupancy in the adjacent control area declined during this period. It therefore appears that the control area is becoming a less suitable habitat for kestrels as the forest continues to mature, whereas the burned area is still providing viable habitat for kestrels. We present evidence suggesting that some of the differences in occupancy between the control and burned area may be due to fewer nest predators in the burned area in 2003.
Design of Robust Gradient Method for Convex Optimization Problem using Biased Integral Quadratic Constraints

Gradient based methods are the most widely used algorithms for convex optimization problems due to their simplicity and reliability. Applications based on gradient methods works well in absence of any external factors (noise, precision error etc.) with appropriate step size. In presence of uncertainty though, the shortcomings of the gradient methods become obvious from increased convergence time or in severe cases even the failure of convergence depending upon the noise level and the step size. This paper tries to address the issue of achieving the optimal performance from the gradient methods in presence of uncertainty. A case study of gradient descent algorithm has been conducted in this paper. The robust convergence of gradient based convex optimization methods is transformed into an equivalent stabilization problem in a dynamical system framework. The paper proposes a novel characterization of optimization algorithms by adopting the biased integral quadratic constraint (BIQC) framework which is generally used for robust analysis of dynamical systems. Using this approach an algorithmic procedure is devised to perform dynamics computation of upper bound of the step size which guarantees robust convergence towards an equilibrium point even in presence of uncertainty.
Refractory Vasospastic Angina: When Typical Medications Don't Work

Vasospastic angina (VSA) is defined as spasm of the coronaries leading to transient constriction and eventual myocardial ischemia. VSA is treated typically with calcium-channel blockers (CCBs) and nitrates. However, there are times when the vasospasm is refractory to typical medications. When this occurs, unconventional treatment modalities may be employed for symptomatic relief. We present a case of a 48-year-old-male with a history of inferior ST-elevation myocardial infarction (STEMI) status post percutaneous coronary intervention (PCI) with drug-eluting stent (DES) to the distal right coronary artery (RCA), who presented with recurrent angina. The pain was described as pressure-like, substernal, radiating to both arms, and similar to his previous STEMI presentation. On presentation to the emergency room, he had an elevated serum troponin with no electrocardiogram (EKG) changes. He was taken to the cath lab where it was found that he revealed severe focal stenosis just proximal to the previously placed stent. Immediately after guidewire passage into the RCA, acute vasospasm developed, resulting in diffuse, severe stenosis, extending over previously normal segments to the proximal RCA, resolving with intracoronary nicardipine and nitroglycerin, including the initial focal stenosis. The patient was diagnosed with VSA. Unfortunately, despite optimal medical therapy, he developed refractory VSA, requiring the use of unconventional treatment methods. Our patient presented with a lesser-known phenomenon called refractory VSA, where intermittent vasospasm continues despite being on a combination of two medications. Treatment for VSA is well-documented, however, little data is available for refractory VSA.
Prevalence of Argulus foliaceus and fungal infections in some ornamental fishes [discus (Symphysodon discus), dwarf gourami (Trichogaster lalius) and guppy (Poecilia reticulata)] in Isfahan city of Iran.

Summary This study was aimed to determine the prevalence Argulus foliaceus and some fungal diseases of ornamental fishes (discus, dwarf gourami and guppy) in Isfahan, Iran. The 90 ornamental fish from 2 pet fish supply store in Isfahan city of Iran were randomly selected. The study demonstrated that only 2 out of those 90 samples were infested with A. foliaceus. The highest infestation rate was in Dwarf gourami (Trichogaster lalius) (23.31%), and the lowest infestation rate was in Guppy (Poecilia reticulata) (6.66%). A total of 90 fishes of 3 species were examined. The contaminant fungal species were identified as Acremonium sp. , Aspergillus sp. , Alternaria sp. , Penicillium sp. , and Saprolegnia sp. Fungal infection was observed in discus, dwarf gourami and guppy. According to the presented study, it is clear that A. foliaceus can act as a potential risk factor for natural ecosystems and native fish population of Iran and other countries.
Gastroesophageal fat pad has no clinical significance in patients with GERD, giant hiatus hernia and in repeat surgery

BACKGROUND: The objective of the study was to assess the clinical significance of evident gastroesophageal fat pad (EGFP) in patients operated on for gastroesophageal reflux disease (GERD), giant hiatal hernia (HH) types III and IV and repeat surgery for recurrent hernia. METHODS: Data about EGFP were prospectively evidenced at operation. An EGFP was defined as a well encapsulated lipoma-like lipidic tissue more than 2 cm in its small diameter, not covered with peritoneum. A group of 119 patients receiving surgery for either GERD and HH. Patients with repeat operations were also included in the study. The preferred operations were laparoscopic Toupet and Nissen fundoplication. RESULTS: In total 49% of patients presented with an EGFP, 46% from the GERD group and 53% from the HH group. The presence of EGFP did not affect the symptoms of GERD. Number of stiches as indirect evaluation of hernia size was practically equal in patients with and without EGFP. A positive correlation was observed between EGFP and BMI of the patients. Of 119 patients, 12 patients received repeat surgery. In this group an EGFP was found in six cases (50%). CONCLUSION: An EGFP was present in 49% of all studied patients and in 50% of the patients receiving reoperation. Patients with higher BMI had significantly more EGFP (p=0.001). An EGFP were not associated with the clinical manifestation of GERD and the size of HH. An EGFP resected from mediastinum and left intraabdominally is not associated with incidence of hernia recurrence.
Diverse Region-Based CNN for Tongue Squamous Cell Carcinoma Classification With Raman Spectroscopy

Border discrimination is very important in the treatment of tongue squamous cell carcinoma (TSCC). This study proposes an ensemble convolutional neural network (CNN) framework based on fiber optic Raman spectroscopy and deep learning techniques to distinguish between TSCC and non-tumor tissue frameworks. First, the data used in the experiments was collected by a fiber optic Raman system. A total of 44 tissues of 22 patients were collected for Raman spectroscopy, with TSCC and adjacent normal tissues each accounting for half. The spectral data range used in the model from a full spectrum of 600-4000 cm−1. Then, the ensemble CNN model was used in the experiment. By using two convolution kernels, the model is able to extract nonlinear feature representations from different spectral regions. It has two advantages, on the one hand, it reduces the generation of noise, on the other hand, it obtains a stronger distinguishing ability. Finally, a feature vector is formed by the fusion layer, and is sent to the fully connected layer for the TSCC classification task. The results showed that the sensitivity and specificity of the model were 99.2% and 99.2%, respectively. In addition, comparison with existing methods shows that our method achieves the highest accuracy of TSCC classification. By comparing the different channels, the results show that the spectral range of 1380-2250cm−1 data has the greatest impact on the results. Therefore, Raman spectroscopy combined with the ensemble CNN model has great potential and can provide a useful technique for intraoperative evaluation of the margins of oral tongue squamous cell carcinoma.
Early Experience in Forecasting Blood Glucose Levels Using a Delayed and Auto-Regressive Jump Neural Network

Type 1 diabetes mellitus is a widespread chronic disease that, if not properly treated, can lead to short- and longterm complications. In recent years, continuous glucose monitoring has become very popular among patients since it allows to keep track of glucose levels for 24 hours. Nevertheless, hypo- and hyper-glycemic events are still widely reported, motivating the development of methods that forecast blood glucose levels at given prediction horizons, which usually range from 15 to 30 minutes. However their application, regardless of the approaches adopted, is limited in practice by the fact that they usually need a long training time and other information gathered from the patients. To overcome these issues in this work we present a new neural network that extends the jump network model by introducing time delays from the input to the hidden layer and auto-regressive feedback from the output to the hidden layer. The proposed neural network shows promising results at 15, 20 and 30-minute prediction horizons, which are comparable to or slightly better than the results reported in the literature, although the training period used in this work is considerably shorter.
Compact, Portable, High-Density Functional Near-Infrared Spectroscopy System for Brain Imaging

Advancements in functional near-infrared spectroscopy (fNIRS) neuroimaging have extended its usage from clinical settings to real-life applications. We developed a wearable and wireless fNIRS-based neuroimaging system that can be applied for brain disease diagnostics and during daily life activities. We utilized 128 compact dual-wavelength LEDs of 735 nm and 850 nm and a silicon photodiode (SiPD). The LEDs and SiPD were closely assembled in a 3D-printed flexible configuration holder fitted in a soft neoprene cap. The developed configuration has 128 channels in a $7\times 7$ cm area with source-detector separations ranging from 5 mm to 38 mm, which intends to provide a high-density device. The system acquires data from multiple brain depths to generate a 3D activation image. Short-separation channels provide the physiological noise in the superficial layer, which can be used to enhance fNIRS signals. The experimental data are stored in a USB flash disk attached to the device. We developed software that is connected to the device using Wi-Fi to display the oxyhemoglobin (HbO) and deoxyhemoglobin (HbR) levels in real-time. The system architecture allows the selection of channels and the use of multiple devices simultaneously. The system was tested using a silicone phantom as well as human subjects. The LED intensity is dynamically calibrated within the safety range once the device is set up, so that every channel can acquire stable data. The system provided high-quality signals with a signal-to-noise ratio of more than 64 dB, high optical sensitivity, and dynamic optical range of 140 dB in the phantom test. A sampling rate of 30 Hz was achieved with all the channels used. The system exhibited valid HbO and HbR responses during the arterial occlusion test and a motor task. These results show that the developed system can provide precise, robust, and multi-depth measurements resulting in high-density images. With these novel characteristics, the system favors clinical usage and outdoor activities as well as brain-computer interface applications.
Improved Transmission Line Parameter Calculation Through TCAD Process Modeling for Superconductor Integrated Circuit Interconnects

The Florida Object-Oriented Device, Process and Reliability Simulator (FLOOXS) technology computer-aided design process modeling tools developed at the University of Florida have been adapted under the Intelligence Advanced Research Projects Activity SuperTools program to support the MIT Lincoln Laboratory SFQ5ee fabrication process. We use FLOOXS to build meshed models of passive transmission lines from superconductor integrated circuit layouts. We have previously developed a numerical solver that extracts transmission line parameters from the meshed model. In this work, we convert a layout slice to FLOOXS inputs, generate two-dimensional meshes of cross-sectional geometries from simulated process steps, and then extract the transmission line parameters from the meshes. Results are shown compared against the results for simplified transmission lines that do not utilize process modeling. The results confirm that process modeling alters the extracted parameter values and suggest that process modeling will become more important as cell density of superconducting electronics increases. We conclude with a discussion on the necessity of process modeling for high-quality parameter extraction.
Mass Selection by Seed Size and Specific Gravity in Soybean Populations 1

Three cycles of mass selection for seed size and specific gravity were evaluated for their effect on the protein and oil composition of F₆-F₈ heterogeneous soybean populations from two crosses. An approximately linear change in seed size was observed with each selection cycle. Effective progress was obtained for protein content in cycle 1 of both crosses, but the effectiveness of subsequent cycles differed between crosses. Selection was effective for oil content in cycle 1, but progress in subsequent cycles differed between large and small seed populations of both crosses. Maximum progress for high protein and low oil was obtained by selecting for large seed and high specific gravity. Selection for small seed and low specific gravity resulted in maximum progress for high oil and low protein. Heritability was . 93, . 87, . 77, and . 73 for seed size, specific gravity, protein, and oil, respectively.
Optimization of Multiple Access Channel Cooperation between Non-Ideal Full-Duplex Sources

This paper considers a problem of cooperative multiple access channels (CMAC), where two full-duplex sources simultaneously send their own messages to a common destination and also relay part of each other's message using a decode-forward protocol. Due to non-ideal self-interference cancellation at the sources, the cooperation is hindered by residual self-interference (RSI). To characterize the achievable rate region of CMAC with RSI, a non-convex power allocation problem is formulated. By analyzing the properties of the optimal solution, the original optimization problem is recast into a problem to find the optimal solutions of two quasi-convex subproblems and two convex subproblems. The optimal power allocation in a semi-closed form is derived, which determines the points on the boundary of the achievable rate region. Numerical results show that the proposed scheme can almost double the signal-to-noise ratio at the destination of the conventional MAC in certain channel conditions.
Time Dispersion Parameters of Outdoor Cross-Polar Self-Interference Radio Channels in sub-8-GHz Bands

Indeed, self-interference cancellation has been proven to be the key-enabling technique for realizing a full-duplex duplexing scheme. However, a self-interference canceller must possess an up-to-date knowledge about its sensed self-interference wireless channel. In wireless communication systems, these channels usually possess multi-path and time-invariant properties. Moreover, they are very environment dependant. Therefore, in this paper we chose to investigate outdoors experienced channels, more specifically, ones are encountered in a street-level deployment scenario. Furthermore, we narrowed down the focus to concentrate on cross-polar self-interference channels. These channels are observed in dually polarized antenna's configurations among transmitter and receiver ones. In nutshell, we have dedicated this paper to study the multi-path propagation characteristics of outdoor cross-polar self-interference radio channels. By means of an empirical method, time dispersion behavior of our measured self-interference channel was analzyed. To measure a cross-polar self-interference channel, a channel sounding experiment equipped with a dually-polarized ridged horn antenna was performed. For that purpose, we assembled a channel sounding setup, which is composed of a vector network analyzer connected to the dually polarized antenna. The measurement antenna was placed at 3.5 m height, where measurement data were captured at 26 different locations - on a route parallel to the street. Additionally, for the sake of investigating the frequency dependancy on a cross-polar self-interference channel, two broad frequency bands were measured: A band between 2.9 GHz and 4.1 GHz, and a band between 5.9 GHz and 7.1 GHz. Finally, we derive - from measurement data - empirical probability distributions of channels' time dispersion parameters, such as the maximum peak of the self-interference backscatter (SIBS) channel gain, channel delay spread, and maximum excess delay. These statistical analysis results are presented for both measured frequency bands.
Fusion-Based Approach for Respiratory Rate Recognition From Facial Video Images

The respiratory rate is an important vital parameter that provides information about persons’ physical condition. In clinical practice it is currently only monitored using contact-based techniques, which can have negative effects on patients. In this study, a new algorithm for remote respiratory rate recognition is presented using photoplethysmographic signals derived from facial video images in the visible light spectrum. The effects of different implementation steps in the presented algorithm are investigated in order to optimize the approach and gain new findings in this research field. In addition, a detailed examination of already implemented procedures is performed and the results are compared on two different databases. We show that by fusing the results of seven different respiratory-induced modulations in combination with other processing steps, very good estimates for the respiratory rate on both moving and non-moving data are achieved. The obtained detection rates of 72.16 % and 87.68 % are significantly higher than those of the best comparison algorithm with 37.37 % and 59.13 %. The comparison algorithms developed so far are not competitive with the newly designed method, especially for video recordings involving persons in motion. This paper provides important new findings in the field of facial video-based respiratory rate recognition for the research community. A new method has been created that delivers significantly better estimates of the respiratory rate than previously developed techniques.
Information processing in unregulated and autoregulated gene expression

How living cells can reliably process biochemical cues in the presence of molecular noise is not fully understood. Here we investigate the fidelity of information transfer in the expression of a single gene. We use the established model of gene expression to examine how precisely the protein levels can be controlled by two distinct mechanisms: (i) the transcription rate of the gene, or (ii) the translation rate for the corresponding mRNA. The fidelity of gene expression is quantified with the information-theoretic notion of information capacity. Derived information capacity formulae reveal that transcriptional control generally provides a tangibly higher capacity as compared to the translational control. We next introduce negative feedback regulation in gene expression, where the protein directly inhibits its own transcription. While negative feedback reduces noise in the level of the protein for a given input signal, it also decreases the input-to-output sensitivity. Our results show that the combined effect of these two opposing forces is a reduced capacity in the presence of feedback. In summary, our analysis presents analytical quantification of information transfer in simple gene expression models, which provides insight into the fidelity of basic gene expression control mechanisms.