Miracle-dz/UniFAR-FTUs huggingface dataset:
OPTIMISING CROP REFUGE AREAS IN TRANSGENIC SUGARCANE FIELDS

Crops expressing genes from the bacterium Bacillus thuringiensis (Bt) produce a protein toxic to members of the order Lepidoptera and are a popular alternative to sprayed insecticides. Although these Bt crops are considered to be an effective pest control method, reckless usage adds environmental pressure on the pest population to develop resistance to the toxin over time. One method of limiting the rate of resistance development is to keep small portions of the cultivated land planted with the non-GMO crop which then acts as a refuge area for the pest, limiting its exposure to the toxin and removing the pressure to develop resistance. Strains of Bt sugarcane for the South African market that should limit the damage caused by the stalk borer moth, Eldana Saccharina Walker, are being developed, and a prerequisite to releasing such a product is a recommendation on the size and layout of the refuge areas to be planted, as too small an area may not curb the rate of resistance development enough, but too large an area may not be economically viable for the grower. A simulation-based model is presented where individual moths are modelled as agents on an underlying sugarcane field. To reduce the complexity of the model, the field is divided into a series of smaller cells that can interact with each other, which allows us to model the impact of a severe infestation on an area the size of an average sugarcane farm.
Integrated GANs: Semi-Supervised SAR Target Recognition

With the advantage of working in all weathers and all days, synthetic aperture radar (SAR) imaging systems have a great application value. As an efficient image generation and recognition model, generative adversarial networks (GANs) have been applied to SAR image analysis and achieved promising performance. However, the cost of labeling a large number of SAR images limits the performance of the developed approaches and aggravates the mode collapsing problem. This paper presents a novel approach namely Integrated GANs (I-GAN), which consists of a conditional GANs, an unconditional GANs and a classifier, to achieve semi-supervised generation and recognition simultaneously. The unconditional GANs assist the conditional GANs to increase the diversity of the generated images. A co-training method for the conditional GANs and the classifier is proposed to enrich the training samples. Since our model is capable of representing training images with rich characteristics, the classifier can achieve better recognition accuracy. Experiments on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset proves that our method achieves better results in accuracy when labeled samples are insufficient, compared against other state-of-the-art techniques.
Reconstruction of the CAD Model using TPS Surface

For several years, the reconstruction of Computer Aided Design (CAD) models from a deformed mesh get more and more attention. This CAD model is used in order to visualize 3D objects that were scanned and approximate their shapes by mathematical formulations. It represents the geometric support used in many other activities (analysis, manufacturing, assembly, etc.). Surface reconstruction is the most difficult problem of CAD model reconstruction. There are two types of surfaces: primitive surfaces and complex surfaces. In this paper, we propose a method to reconstruct complex surfaces. Our algorithm is based on Thin Plate Spline (TPS) method to optimize locations of control points of a B-Spline surface. Once surfaces are approximated, the geometric model can be reconstructed. We evaluate every step of our approach using mechanical models and show that we can achieve good results and meaningful approximated control points comparing with other methods.
Personalized Social Search Using Social Network

あらまし 近年増加の傾向を見せているソーシャルメディアの検索では,人の繋がりのような検索者個人に関わる指 標を的確に組み合わせることで,検索者に即した検索精度の向上が実現できると考えられる. その中でソーシャルネッ トワーク上のユーザ関係をドキュメントの検索対象のスコアリングに取り入れる提案やその有効性を示す研究もなさ れている. 本論文では,ソーシャルネットワーク上のユーザー関係をドキュメントのスコアリングに取り入れる事を 前提とした上で実際の検索処理を行う際の性能問題を明らかにし,その問題に対する高速化手法を提案する. 具体 的には,1)人間関係に基づくスコアの事前計算,2)ドキュメントの作成者情報を保持するよう転置ファイルを拡張, 3)Threshold Algorithmに基づく Top-k検索,の 3つの手法を提案し性能評価を行ない提案手法の有用性を示した. キーワード 情報検索,ソーシャルネットワーク,ソーシャルサーチ
Design Semantics : Even hybrid Motorcycles need to make noise

This paper explores the need for artificial sound in high tech products. Changing one of the four sides of the semantic frame changes the meaning and emotional impact of that product. There is a relationship between the four sides of the semantic frame (aesthetic, physiologic, technical, economic) and the five senses (sight, hearing, smell, taste, touch). Replacing sound with sight, smell, taste or touch does compensate for the absence of sound. When high tech products, such as motorcycles, omit sound it confuses the consumer. This research was conducted in two stages: In the first stage the sample consisted of 490 people. In the second stage, 69 people participated. We based our study on questions, interviews and practical tests to determine how artificial sound or the lack of it in high tech products affects the emotional state of the consumer.
V1082-Sgr: A magnetic cataclysmic variable with a lobe-filling companion star

V1082 Sgr is a cataclysmic variable with accretion luminosity above 1034 erg s−1, indicating a mass-transfer rate above $10^{-9}\, \mathrm{M}_{\odot }$ yr−1. However, its K-type companion was suggested to be underfilling its Roche lobe (RL), making the high mass-transfer rate a mystery. In this work we propose a possible model to explain this discrepancy. The system is proposed to be an intermediate polar, with its K-type companion filling its RL. The mass of the white dwarf star is evaluated to be $0.77\pm 0.11\, \mathrm{M}_{\odot }$ from both X-ray continuum fitting and Fe line flux ratio measurements. We make numerical simulations to search for the possible progenitors of the system. The results show that a binary with an initial 1.5–2.5$\, \mathrm{M}_{\odot }$ companion in a one to two day orbit (or an initial 1.0–1.4$\, \mathrm{M}_{\odot }$ companion in a 3.2–4.1 d orbit) may naturally evolve to a cataclysmic variable with a $\sim 0.55 \pm 0.11\, \mathrm{M}_{\odot }$, Roche-lobe-filling companion in a 0.86 d orbit. The effective temperature of the donor star, the mass-transfer rate, and the derived V-band magnitude are all consistent with previous observations.
Protective Effect of Total Phenolic Compounds from Inula helenium on Hydrogen Peroxide ‐ induced Oxidative Stress in SH ‐ SY 5 Y Cells

Inula helenium has been reported to contain a large amount of phenolic compounds, which have shown promise in scavenging free radicals and prevention of neurodegenerative diseases. This study is to investigate the neuroprotective effects of total phenolic compounds from I. helenium on hydrogen peroxide‐induced oxidative damage in human SH‐SY5Y cells. Antioxidant capacity of total phenolic compounds was determined by radical scavenging activity, the level of intracellular reactive oxygen species and superoxide dismutase activity. The cytotoxicity of total phenolic compounds was determined using a cell counting kit‐8 assay. The effect of total phenolic compounds on cell apoptosis due to hydrogen peroxide‐induced oxidative damage was detected by Hoechst 33258 and Annexin‐V/ PI staining using fluorescence microscope and flow cytometry, respectively. Mitochondrial function was evaluated using the mitochondrial membrane potential and mitochondrial ATP synthesis by JC‐1 dye and high performance liquid chromatography, respectively. It was shown that hydrogen peroxide significantly induced the loss of cell viability, increment of apoptosis, formation of reactive oxygen species, reduction of superoxide dismutase activity, decrease in mitochondrial membrane potential and a decrease in adenosine triphosphate production. On the other hand, total phenolic compounds dose‐dependently reversed these effects. This study suggests that total phenolic compounds exert neuroprotective effects against hydrogen peroxide‐induced oxidative damage via blocking reactive oxygen species production and improving mitochondrial function. The potential of total phenolic compounds and its neuroprotective mechanisms in attenuating hydrogen peroxide‐induced oxidative stress‐related cytotoxicity is worth further exploration.
MEMS based tunable circuits for millimetre wave systems

In this paper we describe millimetre wave impedance matching circuits based on Microelectro Mechanical Systems (MEMS) technology enabling easily more than one octave operation. The designs are based on the use of capacitive switches in a triple, double, and singe stub configurations as well as in a distributed transmission line design. The use of capacitive switches will enable 2^n number of impedance points (n is number of the switches), which cover practically fully the smith chart. Furthermore, very wide band and low loss operation of the tuner has been demonstrated. Measured results are shown over 20-110 GHz.
Choosing A Cloud DBMS: Architectures and Tradeoffs

As analytic (OLAP) applications move to the cloud, DBMSs have shifted from employing a pure shared-nothing design with locally attached storage to a hybrid design that combines the use of shared-storage (e.g., AWS S3) with the use of shared-nothing query execution mechanisms. This paper sheds light on the resulting tradeoffs, which have not been properly identified in previous work. To this end, it evaluates the TPC-H benchmark across a variety of DBMS offerings running in a cloud environment (AWS) on fast 10Gb+ networks, specifically database-as-a-service offerings (Redshift, Athena), query engines (Presto, Hive), and a traditional cloud agnostic OLAP database (Vertica). While these comparisons cannot be apples-to-apples in all cases due to cloud configuration restrictions, we nonetheless identify patterns and design choices that are advantageous. These include prioritizing low-cost object stores like S3 for data storage, using system agnostic yet still performant columnar formats like ORC that allow easy switching to other systems for different workloads, and making features that benefit subsequent runs like query precompilation and caching remote data to faster storage optional rather than required because they disadvantage ad hoc queries.
Underwater image enhancement through depth estimation based on random forest

Abstract. Light absorption and scattering in underwater environments can result in low-contrast images with a distinct color cast. This paper proposes a systematic framework for the enhancement of underwater images. Light transmission is estimated using the random forest algorithm. RGB values, luminance, color difference, blurriness, and the dark channel are treated as features in training and estimation. Transmission is calculated using an ensemble machine learning algorithm to deal with a variety of conditions encountered in underwater environments. A color compensation and contrast enhancement algorithm based on depth information was also developed with the aim of improving the visual quality of underwater images. Experimental results demonstrate that the proposed scheme outperforms existing methods with regard to subjective visual quality as well as objective measurements.
Deep Covariance Estimation Hashing

Deep hashing, the combination of advanced convolutional neural networks and efficient hashing, has recently achieved impressive performance for image retrieval. However, state-of-the-art deep hashing methods mainly focus on constructing hash function, loss function and training strategies to preserve semantic similarity. For the fundamental image characteristics, they depend heavily on the first-order convolutional feature statistics, failing to take their global structure into consideration. To address this problem, we present a deep covariance estimation hashing (DCEH) method with robust covariance form to improve hash code quality. The core of DCEH involves covariance pooling as deep hashing representation, performing global pairwise feature interactions. The covariance pooling can capture richer statistic information of deep convolutional features and produce more informative global representations.Due to convolutional features are usually high dimension and small sample size, we estimate robust covariance by shrinking its eigenvalues using power normalization, forming an independent structural layer. Then the structural layer is embedded into deep hashing paradigm in an end-to-end learning manner. Extensive experiments on three benchmarks show that the proposed DCEH outperforms its counterparts and achieves superior performance.
Frequency Magnitude and Images of Texture Studies on Relationships to Human Preference

A relationship between spatial frequency magnitude and aesthetic preference for texture is established in this work. This paper examines the mean output of three frequency settings in terms of preference ratings for a bank of Gabor filters. Three studies were conducted and the correlations between aesthetic ratings and the mean output for the filter set to extract frequency content at the scale of 0.35 cycles/ pixel were robust. The correlations for the mean frequency magnitude of this filter remained significant when image identifiability was incorporated; suggesting that memory and association are not exclusively driving (aesthetic) preference. These results are consistent with findings reported by Albrecht and Geisler (1997), demonstrating that human beings are tuned to specific frequencies and orientations. Overall, the results reported in this paper begin to substantiate a claim that specific frequencies contained in images do play a significant role in human preference. 1. Goodness of Form Prägnanz Early in the last century the quality of a visual experience was approached by Gestalt psychologists through the analysis of ‘goodness’ of form, or prägnanz, whichin their opinion was an important factor in perceptual experience (Beardslee et al., 1923; Kofka, 1922; Mowatt, 1940; Kohler, 1947). Perceptual “experience” was said to correspond to global properties of subjective simplicity, complexity and bilateral symmetry. Researchers did not believe whole figures could be understood by means of examining the local properties of those figures. Some images were thought to produce experiences of greater simplicity, order and regularity than others. Stimuli that are simple (contain adequate redundancy), symmetric (rotationally invariant) and familiar were considered “good”. However, a reliable description for judged simplicity was not determined and the relationship between symmetry and figural “goodness” (prägnanz) was not demonstrated. Symmetry proved only to be a tenable explanation and local asymmetry was not addressed (Garner 1962, 1970).
A Low Cost Indoor Aerial Robot with Passive Stabilization and Structured Light Navigation

The Pima Community College UAV Club has designed an air vehicle system to compete in the International Aerial Robotics Competition (IARC). The rules require an autonomous air vehicle to fly through an open portal into a cluttered indoor environment, search for a small flash drive and exchange the drive with a decoy while evading or deactivating various security systems. The mission deadline is between 5 and 10 minutes, depending on whether security alarms are triggered. The team designed a low cost air vehicle with a jellyfish configuration, on which a balloon stabilizer provides passive stability. The balloon also doubles as a radome and encloses a large directional antenna. Twin propellers suspended beneath the balloon provide lift, and a separate modular 2D thrust vector control system provides precise horizontal positioning, allowing the vehicle to respond rapidly to changes in HVAC air movement.
A Lightweight and Eﬃcient Data Sharing Scheme for Cloud Computing

Cloud storage is a useful service of cloud computing which allows users to upload their data in the cloud and share it with others. Although, this new service is aﬀordable and practical, but it is associated with several privacy and security challenges. Nowadays, Attribute Based Encryption (ABE) is widely used to provide secure data sharing in the distributed environment such as cloud computing. Unfortunately, most of the existing ABE schemes are not suitable for resource-constraint cloud systems, because they use expensive bilinear pairing operation and thus they cause a very high encryption and decryption computation overhead. In this paper, we propose an eﬃcient no-pairing and revocable ABE data sharing scheme based on Elliptic Curve Cryptography (ECC) for cloud storage systems. Moreover, a comprehensive security and performance analysis shows that our scheme is both secure and eﬃcient
Novel Insight Into the Epigenetic and Post-transcriptional Control of Cardiac Gene Expression by Thyroid Hormone

Thyroid hormone (TH) signaling is critically involved in the regulation of cardiovascular physiology. Even mild reductions of myocardial TH levels, as occur in hypothyroidism or low T3 state conditions, are thought to play a role in the progression of cardiac disorders. Due to recent advances in molecular mechanisms underlying TH action, it is now accepted that TH-dependent modulation of gene expression is achieved at multiple transcriptional and post-transcriptional levels and involves the cooperation of many processes. Among them, the epigenetic remodeling of chromatin structure and the interplay with non-coding RNA have emerged as novel TH-dependent pathways that add further degrees of complexity and broaden the network of genes controlled by TH signaling. Increasing experimental and clinical findings indicate that aberrant function of these regulatory mechanisms promotes the evolution of cardiac disorders such as post-ischemic injury, pathological hypertrophy, and heart failure, which may be reversed by the correction of the underlying TH dyshomeostasis. To encourage the clinical implementation of a TH replacement strategy in cardiac disease, here we discuss the crucial effect of epigenetic modifications and control of non-coding RNA in TH-dependent regulation of biological processes relevant for cardiac disease evolution.
Genetic Background Modifies the Topography of a Fitness Landscape, Influencing the Dynamics of Adaptive Evolution

Understanding the forces that drive the dynamics of adaptive evolution is a goal of many sub-fields and applications of evolutionary biology, including in evolutionary computation. The fitness landscape analogy has served as a useful abstraction for addressing these topics across many systems, and recent treatments have revealed how different environments can frame the particulars of adaptive evolution by changing the topography of fitness landscapes. In this study, we examine how the larger, ambient genetic context in which a protein is embedded affects fitness landscape topography and subsequent evolution. Using simulations on empirical fitness landscapes, we discover that the genetic background – genetic variability in regions outside of the locus under study (in this case, an essential bacterial enzyme target of antibiotics) – influences the speed and direction of evolution in several surprising ways. These findings have implications for how we study the evolution of drug resistance in nature, and for presumptions about how biological evolution might be expected to occur in genetically-modified organisms. More generally, the findings speak to theory surrounding how “difference can beget difference” in adaptive evolution (whether biological, computational, or technological): that small differences in environmental or genetic background can greatly alter the specifics of how evolution occurs, which can rapidly drive even slightly diverged populations further apart.
Head Anticipation During Locomotion With Auditory Instruction in the Presence and Absence of Visual Input

Head direction has been identified to anticipate trajectory direction during human locomotion. Head anticipation has also been shown to persist in darkness. Arguably, the purpose for this anticipatory behavior is related to motor control and trajectory planning, independently of the visual condition. This implies that anticipation remains in the absence of visual input. However, experiments so far have only explored this phenomenon with visual instructions which intrinsically primes a visual representation to follow. The primary objective of this study is to describe head anticipation in auditory instructed locomotion, in the presence and absence of visual input. Auditory instructed locomotion trajectories were performed in two visual conditions: eyes open and eyes closed. First, 10 sighted participants localized static sound sources to ensure they could understand the sound cues provided. Afterwards, they listened to a moving sound source while actively following it. Later, participants were asked to reproduce the trajectory of the moving sound source without sound. Anticipatory head behavior was observed during trajectory reproduction in both eyes open and closed conditions. The results suggest that head anticipation is related to motor anticipation rather than mental simulation of the trajectory.
$VJA\dot{G}\dot{G}$ -- A Thick-Client Smart-Phone Journey Detection Algorithm

In this paper we describe $Vja\dot{g}\dot{g}$, a battery-aware journey detection algorithm that executes on the mobile device. The algorithm can be embedded in the client app of the transport service provider or in a general purpose mobility data collector. The thick client setup allows the customer/participant to select which journeys are transferred to the server, keeping customers in control of their personal data and encouraging user uptake. The algorithm is tested in the field and optimised for both accuracy in registering complete journeys and battery power consumption. Typically the algorithm can run for a full day without the need of recharging and more than 88% of journeys are correctly detected from origin to destination, whilst 12% would be missing part of the journey.
Design and FPGA Implementation of a Novel Efficient FRM-Based Channelized Receiver Structure

The main application of the filter bank in radar signal processing is the wideband digital channelized receiver. In order to save hardware resources of the field programmable gate array (FPGA), the efficient channelized receiver structure using polyphase filter has been designed. However, when the number of channels is greatly increased or the transition bandwidth of the filter bank (FB) becomes very narrow, it still consumes large amounts of hardware resources. Therefore, a novel efficient channelized receiver structure based on frequency response masking (FRM) and modulation filter bank is proposed in this paper. The proposed novel structure has less computational complexity in implementing FB with narrow transition bandwidth (NTB). Compared with other efficient FRM-based structures, the proposed novel structure is more suitable for wideband digital channelization receiver. The proposed novel structure is verified correctly by Matlab simulation. The FPGA implementation of the polyphase channelized receiver structure and the proposed novel efficient FRM-based channelized receiver structure are completed by Xilinx System Generator. The result shows that the proposed novel efficient FRM-based channelized receiver structure can save 48.09% of the DSP48E1 hardware resources compared with the polyphase channelized receiver structure and has low group delay characteristic.