Miracle-dz/UniFAR-FTUs huggingface dataset:
The Association of Astigmatism and Spherical Refractive Error in a High Myopia Cohort

Purpose. The purposes of this study were to determine whether the degree of myopia influences the presence and degree of total astigmatism, and to assess risk factors of astigmatism in patients with familial nonsyndromic severe myopia. Methods. We performed a retrospective study of 217 subjects from families with two or more subjects from successive generations with a myopic spherical refractive error of at least -5 D or greater in one eye. Mean myopic spherical equivalent was -10 D and the mean age of myopia onset was 7 years. Refractive error measurements were obtained and the association between the degree of myopia and cylinder power was examined by correlation analysis. Results. The prevalence of astigmatism (1.0 D of cylinder) was 36.1%. With-the-rule astigmatism was most common (55.8%), and the majority of astigmats had between 1.0 and 2.5 D of cylinder (77.6%). Statistically significant associations were found between the presence of astigmatism and risk factors of age and the age of myopia onset. In those patients with astigmatism, however, there was a moderate correlation between the degree of spherical equivalent and cylinder power (r = -0.34, p < 0.0001). Younger age (<16 years) (p = 0.03) was associated with higher cylinder power. Conclusions. In severely myopic patients, there is a high prevalence of astigmatism that is predominantly with-the-rule. The degree of myopic spherical refractive error is correlated with astigmatism severity but is not a risk factor for the presence of astigmatism.
Slope-Based Stochastic Resonance: How Noise Enables Phasic Neurons to Encode Slow Signals

Fundamental properties of phasic firing neurons are usually characterized in a noise-free condition. In the absence of noise, phasic neurons exhibit Class 3 excitability, which is a lack of repetitive firing to steady current injections. For time-varying inputs, phasic neurons are band-pass filters or slope detectors, because they do not respond to inputs containing exclusively low frequencies or shallow slopes. However, we show that in noisy conditions, response properties of phasic neuron models are distinctly altered. Noise enables a phasic model to encode low-frequency inputs that are outside of the response range of the associated deterministic model. Interestingly, this seemingly stochastic-resonance (SR) like effect differs significantly from the classical SR behavior of spiking systems in both the signal-to-noise ratio and the temporal response pattern. Instead of being most sensitive to the peak of a subthreshold signal, as is typical in a classical SR system, phasic models are most sensitive to the signal's rising and falling phases where the slopes are steep. This finding is consistent with the fact that there is not an absolute input threshold in terms of amplitude; rather, a response threshold is more properly defined as a stimulus slope/frequency. We call the encoding of low-frequency signals with noise by phasic models a slope-based SR, because noise can lower or diminish the slope threshold for ramp stimuli. We demonstrate here similar behaviors in three mechanistic models with Class 3 excitability in the presence of slow-varying noise and we suggest that the slope-based SR is a fundamental behavior associated with general phasic properties rather than with a particular biological mechanism.
LARGE-SCALE FOREST FIRES IN SIBERIA ANALYSED BY MODIS, MERIS AND ASTER MULTIRESOLUTION SATELLITE IMAGERY

Exceptionally large fires were observed in Southern Siberia in 2003. Persistent cloud cover and orbit parameters did not allow observation of large areas with high resolution imagery shortly after the fires. Therefore we used a combination of high, medium and low resolution satellite imagery in which Moderate Resolution Imaging Spectroradiometer (MODIS) was used to record fire occurrence each day over large areas, while multispectral MEdium Resolution Imaging Spectrometer (MERIS) and Advanced Spaceborne Thermal Emission and Reflection (ASTER) imagery were used to determine the burnt area in cloud-free subsets of our study site. A regression analysis showed that there were linear correlations between burnt areas derived from ASTER and MERIS imagery as well as between MERIS imagery and MODIS hotspot data. We then extrapolated the detailed results on burnt areas obtained from ASTER and MERIS to the full range covered by MODIS hotspots data. The analysis showed that the burnt area derived from MODIS hotspots resulted in an underestimate of approximately 40%. To determine the land cover types affected by fire we intersected the burnt area with the GLC2000 land cover map. 71.4% of the burnt area was forest, 10% was humid grasslands. Large scale wildfires like the one observed in 2003 amplified by climate extremes will diminish the carbon sequestration potential of this largest resource of boreal forest worldwide and thus to a net carbon release to the atmosphere.
Concurrent Band Selection and Traversability Estimation from Long-Wave Hyperspectral Imagery in Off-Road Settings

Autonomous navigation has become increasingly popular in recent years; However, most existing methods focus on on-road navigation and utilize active sensors, such as LiDAR. This paper instead focuses on autonomous off-road navigation using traversability estimation from passive sensors, specifically long-wave (LW) hyperspectral imagery (HSI). We present a method for selecting a subset of hyperspectral bands that are most useful for traversability estimation by designing a band selection module that designs a minimal sensor that measures sparsely-sampled spectral bands while jointly training a semantic segmentation network for traversability estimation. The effectiveness of our method is demonstrated using our dataset of LW HSI from diverse off-road scenes including forest, desert, snow, ponds, and open fields. Our dataset includes imagery collected both during the daytime and nighttime during various weather conditions, including challenging scenes with a wide range of obstacles. Using our method, we learn a small subset (2%) of all the HSI bands that can achieve competitive or better traversability estimation accuracy to that achieved when utilizing all hyperspectral bands. Using only 5 bands, our method is able to achieve a mean class accuracy that is only 1.3% less than that achieved using full 256-band HSI and only 0.1% less than that achieved using 250-band HSI, demonstrating the success of our method.
Energy efficient and distributed resource allocation for wireless powered OFDMA multi-cell networks

In this paper, we investigate the energy efficient resource allocation problem for the wireless powered OFDMA multi-cell networks. In the considered system, the users who have data to transmit in the uplink are empowered by the wireless power obtained from multiple base stations (BSs) with a large scale of multiple antennas in the downlink. A time division protocol is considered to divide the time of wireless power transfer (WPT) in the downlink and wireless information transfer (WIT) in the uplink into separate time slot. With the objective to improve the energy efficiency (EE) of the system, we propose the antenna selection, time allocation, subcarrier and power allocation schemes. Due to the non-convexity of the formulated optimization problem, we first apply the nonlinear programming scheme to convert it to a convex optimization problem and then address it through an efficient alternating direction method of multipliers based distributed resource allocation algorithm. Extensive simulations are conducted to show the effectiveness of proposed schemes.
Estimating Urban Heat Island Effect through Building Façade System and Form Detection on Street View and Aerial Images

Reducing urban energy consumption is critical to achieving the 2050 Net Zero Emission Goal. In the past fewer years, researchers and experts have focused on improving energy efficiency; however, not only does the building energy efficiency affect energy consumption, but the urban scale factors also play an essential role in it, like the urban heat island effect. To predict urban electricity consumption, many researchers use different urban planning parameters such as road width, green belt, building parameters such as building use type, and other public parameters for analysis, but the calculation and statistical steps require a lot of manpower, in addition, many researchers use some confidential parameters in the research such as single-user power data, which involve privacy issues and are difficult to obtain in different cities or countries, causing their results are limited in a specific area. Using computer vision and deep learning, this research can quickly and effectively identify and calculate 10 urban and building characteristic parameters such as urban green ratio, average road width, window ratio, and building height from aerial images. The above characteristic parameters are combined with the government's public information that can be obtained on the Internet. This research uses regression analysis to quickly predict urban power consumption, which can be used for analysis in different cities. In advance, it can provide an objective prediction result to government offices while making an urban (renewal) plan.
post-Incorporating a prediction of postgrazing herbage mass into a whole-farm model for pasture-based dairy systems

The DairyNZ whole-farm model (WFM; DairyNZ, Hamilton, New Zealand) consists of a framework that links component models for animal, pastures, crops, and soils. The model was developed to assist with analysis and design of pasture-based farm systems. New (this work) and revised (e.g., cow, pasture, crops) component models can be added to the WFM, keeping the model flexible and up to date. Nevertheless, the WFM does not account for plant-animal relationships determining herbage-depletion dynamics. The user has to preset the maximum allowable level of herbage depletion [i.e., postgrazing herbage mass (residuals)] throughout the year. Because residuals have a direct effect on herbage regrowth, the WFM in its current form does not dynamically simulate the effect of grazing pressure on herbage depletion and consequent effect on herbage regrowth. The management of grazing pressure is a key component of pasture-based dairy systems. Thus, the main objective of the present work was to develop a new version of the WFM able to predict residuals, and thereby simulate related effects of grazing pressure dynamically at the farm scale. This objective was accomplished by incorporating a new component model into the WFM. This model represents plant-animal relationships, for example sward structure and herbage intake rate, and resulting level of herbage
Deﬁnition of Estrogen Receptor Pathway Critical for Estrogen Positive Feedback to Gonadotropin-Releasing Hormone Neurons and Fertility

Summary The mechanisms through which estrogen regulates gonadotropin-releasing hormone (GnRH) neurons to control mammalian ovulation are unknown. We found that estrogen positive feedback to generate the pre-ovulatory gonadotropin surge was normal in estrogen receptor b knockout (ER b ) mutant mice, but absent in ER a mutant mice. An ER a -selective compound was sufﬁcient to generate positive feedback in wild-type mice. As GnRH neurons do not express ER a , estrogen positive feedback upon GnRH neurons must be indirect in nature. To establish the cell type responsible, we generated a neuron-speciﬁc ER a mutant mouse line. These mice failed to exhibit estrogen positive feed-back, demonstrating that neurons expressing ER a are critical. We then used a GnRH neuron-speciﬁc Pseu-dorabies virus (PRV) tracing approach to show that the ER a -expressing neurons innervating GnRH neurons are located within rostral periventricular regions of the hypothalamus. These studies demonstrate that ovulation is driven by estrogen actions upon ER a - expressing neuronal afferents to GnRH neurons
Voice Interfaces will never eclipse touch screens as means of accessing services.

With the voice recognition technologies on the rise, Voice User Interfaces (VUIs) are becoming ubiquitously available, being embedded into almost every type of personal devices. However, the challenge of interaction design still exists or even be ampli ﬁ ed due to the variety of user interfaces as well as complexity of the functionality provided by devices. Although the growing presence of voice on mobile devices, desktops, home assistants, and appliances represents an accelerating shift away from graphical user interfaces for many key functions, exactly how users of such devices practically thread that use into their everyday social interactions remains un-derexplored. We take the position that voice user interfaces will never eclipse touch screens as means of accessing services. As argument, we try to point out the limitations due to voice recognition technology itself as well as the ﬂ aw in human values and ethics. After giving evidence in our favor, we will illustrate some real interviews about the experience of using voice interfaces.
Hidden copy number variation in the HapMap population

Recently, the extent of copy number variation (CNV) throughout the genome has been shown to be far greater than previously thought. Further, it has been demonstrated that specific copy number variable regions (CNVRs) are associated with particular diseases, suggesting that these genetic variations may have an important biological role. Hence, calling CNVRs and subsequently classifying samples as “losses” or “gains” is of great interest. A number of papers have been published containing classifications of CNVs, and here we show how the presence of pedigree information can be used for assessing the performance of those classification methods. In this article, by examining CNV classifications made in the HapMap samples, we show that estimates of the number of false-positive classifications per individual made by current approaches can be determined. Moreover, commonplace technologies for determining the locations of CNVRs aggregate information across the maternal and paternal chromosomes at the locus of interest. Here, we show that copy number variation on each chromosome can be inferred and, in particular, we discuss the existence of a class of CNVs that are inevitably misclassified and give an estimate of their prevalence. Although our focus is not on the development of calling algorithms per se, we describe and provide an example of how our model might be incorporated into the initial classification procedure to produce more robust results. Finally, we discuss how this methodology might be applied to future studies to obtain better estimates of the extent of CNV across the genome.
Plaintext-Recovery Attacks Against Datagram TLS

The Datagram Transport Layer Security (DTLS) protocol provides confidentiality and integrity of data exchanged between a client and a server. We describe an efficient and full plaintext recovery attack against the OpenSSL implementation of DTLS, and a partial plaintext recovery attack against the GnuTLS implementation of DTLS. The attack against the OpenSSL implementation is a variant of Vaudenay’s padding oracle attack and exploits small timing differences arising during the cryptographic processing of DTLS packets. It would have been prevented if the OpenSSL implementation had been in accordance with the DTLS RFC. In contrast, the GnuTLS implementation does follow the DTLS RFC closely, but is still vulnerable to attack. The attacks require new insights to overcome the lack of error messages in DTLS and to amplify the timing differences. We discuss the reasons why these implementations are insecure, drawing lessons for secure protocol design and implemen-
UvA-DARE (Digital Academic Repository) Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification

Zero-shot learning strives to classify unseen categories for which no data is available during training. In the generalized variant, the test samples can further belong to seen or unseen categories. The state-of-the-art relies on Generative Adversarial Networks that synthesize unseen class features by leveraging class-speciﬁc semantic embeddings. During training, they generate semantically consistent features, but discard this constraint during feature synthesis and classiﬁcation. We propose to enforce semantic consistency at all stages of (generalized) zero-shot learning: training, feature synthesis and classiﬁcation. We ﬁrst introduce a feedback loop, from a semantic embedding decoder, that iteratively reﬁnes the generated features during both the training and feature synthesis stages. The synthesized features together with their corresponding latent embeddings from the decoder are then transformed into discriminative features and utilized during classiﬁcation to reduce ambiguities among categories. Experiments on (generalized) zero-shot object and action classiﬁcation reveal the beneﬁt of semantic consistency and itera-tive feedback, outperforming existing methods on six zero-shot learning benchmarks. Source code at https://github.com/akshitac8/tfvaegan .
Impact of Environmental Thermal Stimulation on Activation of Hypothalamic Neuronal Nitric Oxide Synthase during the Prenatal Ontogenesis in Muscovy Ducks

The aim of the study is to investigate the influence of prenatal temperature stimulation on neuronal NO synthase (nNOS) expression in the anterior hypothalamus of Muscovy duck embryos. Experiments were performed on embryonic day (E) E20, E23, E28, and E33 using histochemistry for identification of the nicotinamide adenine dinucleotide phosphate-diaphorase (NADPH-d) as marker of NOS-containing neurons. Until the experiments, all duck embryos were incubated under standard temperature conditions (37.5°C). During 3 hours before the start of the experiments, one group was incubated at 37.5°C (control group), the second was warm-experienced at 39°C, and the third was cold-experienced at 34°C. In normal and warm-incubated duck embryos, nNOS activity could be first detected on E23. Particularly, after cold stimulation, a significant increase in nNOS activity was found in all embryos investigated even on day 20. Warm stimulation obviously induces the opposite effect, but at later embryonic age (E33). It can be concluded that probably in late-term bird embryos NO acts as a mediator of the neuronal cold pathway in the anterior hypothalamus, which might be improved by prenatal cold stimulation.
QoS-directed error control of video multicast in wireless networks

In this paper we present a QoS-directed error control scheme (QDEC) for video multicast in wireless networks. In order to provide multimedia services to mobile users, it is necessary to have not only sufficient bandwidth, but also effective control over wireless channel errors, which are characterized as bursty and location-dependent. The QDEC scheme includes: (1) a video QoS differentiation specification to direct the error control; and (2) three error control algorithms with corresponding channel error conditions under which the algorithms should be chosen. Through analysis and simulation, we show that QDEC has the following key properties: (1) high error recovery rate for QoS-essential video frames, (2) excellent scalability, (3) high transmission efficiency, and (4) no QoS degradation for receivers who observe no channel errors.
International Conference on Sustainable Computing in Science, Technology & Management (SUSCOM-2019)

Biodiversity is a boon for reinforcement of sustainability and innovation for betterment of society via transformation of scientific temper. Nature has consciousness and invincible strength to bio diversified plants against protection from unforeseen turbulence is observed by researchers. Natural bamboo is a type of Bio composites found in tropical region has strength to weight ratio and aesthetics valuation more than alloy steels hence it is useful in ultra luxurious segment of society. The purpose of the paper is to elaborate mechanism and mechanics of natural bamboo materials explicitly for determination of micro/macro rupture of fibre matrix adhesion subjected to severe shearing as efficient natural strength of tensile strength and bending strength inbuilt with bamboo by nature and failure mode is conventional in plane twisting of composite culms. The paper is useful for researchers focussing on innovation and green technology for achievement of sustainable development goals.
Automatic replay generation for soccer video broadcasting

While most current approaches for sports video analysis are based on broadcast video, in this paper, we present a novel approach for highlight detection and automatic replay generation for soccer videos taken by the main camera. This research is important as current soccer highlight detection and replay generation from a live game is a labor-intensive process. A robust multi-level, multi-model event detection framework is proposed to detect the event and event boundaries from the video taken by the main camera. This framework explores the possible analysis cues, using a mid-level representation to bridge the gap between low-level features and high-level events. The event detection results and mid-level representation are used to generate replays which are automatically inserted into the video. Experimental results are promising and found to be comparable with those generated by broadcast professionals.
The role of ultrasound and magnetic resonance in local drug delivery

Local drug delivery has recently attracted much attention since it represents a strategy to increase the drug concentration at the target location and decrease systemic toxicity effects. Ultrasound can be used in different ways to trigger regional drug delivery. It can cause the local drug release from a carrier vehicle and the local increase of cell membrane permeability either by a mechanical action or by a temperature increase. Ultrasound contrast agents may enhance these effects by means of cavitation. Ultrasound can be focused deep inside the body into a small region with dimensions on the order of 1 mm. Several types of drug microcarriers have been proposed, from nano‐ to micrometer sized particles. The objective of real‐time imaging of local drug delivery is to assure that the delivery takes place in the target region, that the drug concentration and the resulting physiological reaction are sufficient, and to intervene if necessary. Ultrasound and nuclear imaging techniques play an important role. MRI is rather insensitive but allows precise targeting of (focused) ultrasound, can provide real‐time temperature maps, and gives access to a variety of imaging biomarkers that may be used to assess drug action. Examples from recent articles illustrate the potential of the principles of ultrasound‐triggered local drug delivery. J. Magn. Reson. Imaging 2008;27:400–409. © 2008 Wiley‐Liss, Inc.
A moment magnitude scale

The nearly coincident forms of the relations between seismic moment M_0 and the magnitudes M_L, M_S, and M_w imply a moment magnitude scale M = ⅔ log M_0 - 10.7 which is uniformly valid for 3 ≲ M_L ≲ 7, 5 ≲ M_s ≲ 7½, and M_w ≳ 7½.