Miracle-dz/UniFAR-FTUs huggingface dataset:
GREEN-T (Green Terminals for Next Generation Wireless Systems): Survey and Progress

One of the biggest impediments of the future wireless communication systems is the need to reduce the energy consumption of mobile devices, which depend on batteries for their operations. GREEN-T will be the vehicle for tackling the problem of high energy requirement of beyond 3G mobile terminals, by dedicating its efforts towards saving energy on the mobile side, and especially addressing the energy dissipation for communication-related functions. This paper presents the initial progress of the GREEN-T project.
Spatio-temporal Access Methods

Spatiotemporal Database Management Systems (STDBMSs) manage data whose geometry changes over time. There are many applications that create such data, including global change (as in climate or land cover changes), transportation (traffic surveillance data, intelligent transportation systems), social (demographic, health, etc.), and multimedia (animated movies) applications. For simplicity we consider two spatial attributes, the object position and extent, either (or both) of which can change with time. Based on the rate that spatial attributes change, we identify two cases: the discrete and the continuous spatiotemporal environments. We first introduce the basic characteristics and interesting queries for each environment and then present efficient spatiotemporal indexing techniques.
Mobility performance of low‐vision adults using an electronic mobility aid

Visually impaired people rank obstacle location and identification as two of the most important mobility problems faced. Traditional mobility aids (the long cane) provide information about where an object is located but only within their limited (one metre) range. Although objects are located when traditional aids are used, it is unlikely that they are identified. The Bristol Mobility Aid (BMA) is an electronic travel aid that presents scene images to remaining residual vision in a number of view formats. Previous work has suggested visually impaired observers have better static object recognition using this aid. We investigated the mobility performance of subjects with retinitis pigmentosa using the BMA by determining the percentage preferred walking speed (PPWS), and the number of errors made with three different BMA headset views on an indoor mobility course. We found low‐vision subjects had significantly reduced PPWS in two of the three headset views and interestingly, sighted subjects had significantly reduced PPWS when using the BMA in all three views. The numbers of errors made were significantly higher across all vision groups when the BMA was worn. We found that the BMA does not currently increase mobility in the visually impaired. Results are discussed in terms of modifications that could be made to the aid and methodological limitations.
A Dark Laboratory: Exploring Soil Health Perceptions and Assessments in the Maritimes

X LIST OF ABBREVIATIONS USED . XI ACKNOWLEDGEMENTS . XIII CHAPTER 1: INTRODUCTION . 1 1. DEFINING SOIL HEALTH . 4 1.1. The Academic Perspective . 5 1.2. The Farmer Perspective . 7 2. MEASURING SOIL HEALTH . 9 3. RESEARCH OBJECTIVES AND HYPOTHESES . 13 CHAPTER 2: COMPARISON OF THREE SOIL HEALTH ASSESSMENTS AND THEIR RESPONSES TO MANAGEMENT HISTORY AND ENVIRONMENTAL FACTORS . 16
Ingress Pipeline Queues Packet Buffer DMA PipelineDMA Egress Pipeline

The recent surge of network I/O performance has put enormous pressure on memory and software I/O processing subsystems. We argue that the primary reason for high memory and processing overheads is the inefficient use of these resources by current commodity network interface cards (NICs). We propose FlexNIC, a flexible network DMA interface that can be used by operating systems and applications alike to reduce packet processing overheads. FlexNIC allows services to install packet processing rules into the NIC, which then executes simple operations on packets while exchanging them with host memory. Thus, our proposal moves some of the packet processing traditionally done in software to the NIC, where it can be done flexibly and at high speed. We quantify the potential benefits of FlexNIC by emulating the proposed FlexNIC functionality with existing hardware or in software. We show that significant gains in application performance are possible, in terms of both latency and throughput, for several widely used applications, including a key-value store, a stream processing system, and an intrusion detection
MuseMorphose: Full-Song and Fine-Grained Music Style Transfer with Just One Transformer VAE

Transformers and variational autoencoders (VAE) have been extensively employed for symbolic (e.g., MIDI) domain music generation. While the former boast an impressive capability in modeling long sequences, the latter allow users to willingly exert control over different parts (e.g., bars) of the music to be generated. In this paper, we are interested in bringing the two together to construct a single model that exhibits both strengths. The task is split into two steps. First, we equip Transformer decoders with the ability to accept segment-level, time-varying conditions during sequence generation. Subsequently, we combine the developed and tested in-attention decoder with a Transformer encoder, and train the resulting MuseMorphose model with the VAE objective to achieve style transfer of long musical pieces, in which users can specify musical attributes including rhythmic intensity and polyphony (i.e., harmonic fullness) they desire, down to the bar level. Experiments show that MuseMorphose outperforms recurrent neural network (RNN) based prior art on numerous widely-used metrics for style transfer tasks.
Variation of cloudiness in the mountain region on the example of the Sudetes

The purpose of the study is to present a comparison of cloudiness at different levels of a mountain region and to emphasize the specific characteristics of cloud cover observed in valleys and on mountain summits, based on the example of the Sudetes. The analysis is based on cloudiness observations made in Jelenia Góra and on Mt Śnieżka in the years 1971–2015. The results obtained in the study demonstrate that the average cloudiness generally increases with altitude in the Sudetes. However, in the colder half of the year, in anticyclonic weather and thermal inversion conditions, this system may be inverted. There are more cloudless and clear days on average in the valleys and more overcast and cloudy days recorded at the tops of the Sudetes. The annual cloud cover amount is similar, due to atmospheric circulation. The diurnal pattern varies as an effect of the influence of local conditions. The increase in cloudiness during the period from 1971–2015 is more significant in Jelenia Góra than on Śnieżka.
Identification and Avoidance of DDoS Attack for Secured Data Communication in Cloud

Distributed Denial of Service (DDoS) attack in a client server environment would collapse the entire system, but as far as cloud is concern it is not that effective but still it will try to disturb the regular activity of the system. We deploy multiple Intrusion Prevention System (IPS) to monitor the activity of the users and filter the request based on the behaviour and forwards to the corresponding servers through cloud server. Every server would have allocated certain space in cloud server. IPS monitors the activity of the users to avoid DDoS attacks. This system ensures the detection and avoidance of DDoS attack in the cloud server. Few DDoS attacks are listed and monitored. The behaviour patterns are 1.Continuous and same request from single user in a point of time,2.Different query from the same user within a period of time,3.Different queries from different users but from same IP, 4. Request of huge sized file beyond the permitted. Based on these patterns user behaviour is monitored therefore DDoS attack is avoided in cloud.
Increasing rates of screening and treatment of iron deficiency in ambulatory patients with heart failure with reduced ejection fraction: a quality improvement cohort study

Introduction Iron deficiency anaemia (IDA) is common in patients with heart failure (HF) and is associated with advanced HF and increased mortality. Intravenous iron supplementation increases exercise tolerance, improves quality of life, and decreases symptoms among patients with HF with reduced ejection fraction (HFrEF) and iron deficiency. Despite this, many patients are not screened or treated for IDA. We aimed to increase rates of screening and treatment of IDA among HF patients through the introduction of curated materials to aid HF clinicians with appropriate screening and treatment. Methods We conducted a retrospective chart review to identify the baseline number of HFrEF patients screened and treated for IDA at two ambulatory cardiology clinics in Toronto, Ontario. A quality improvement initiative was then introduced, which consisted of education and curated materials to aid clinicians in the screening and treatment of IDA among HFrEF patients. The proportion of patients screened and treated for IDA preintervention and postintervention were compared using χ2 tests of Independence. Results In the preintervention cohort, 36.3% (n=45) of patients with anaemia were screened for IDA. Among those screened, 64.4% (n=29) had IDA. Only 17.2% (n=5) of these were treated with IV iron. After implementation of the quality improvement initiative, 90.9% (n=60) of patients with anaemia were screened for IDA (p<0.001) and 90.3% (n=28) of those with IDA were treated with IV iron (p<0.001). Conclusion The introduction of curated materials to aid clinicians was associated with increased rates of screening and treatment of IDA among ambulatory HFrEF patients. Further work is required to identify barriers and implement strategies to increase screening and treatment rates of IDA among HFrEF patients.
Semantic Segmentation of Remote Sensing Data Based on Channel Attention and Feature Information Entropy

The common channel attention mechanism maps feature statistics to feature weights. However, the effectiveness of this mechanism may not be assured in remotely sensing images due to statistical differences across multiple bands. This paper proposes a novel channel attention mechanism based on feature information called the feature information entropy attention mechanism (FEM). The FEM constructs a relationship between features based on feature information entropy and then maps this relationship to their importance. The Vaihingen dataset and OpenEarthMap dataset are selected for experiments. The proposed method was compared with the squeeze-and-excitation mechanism (SEM), the convolutional block attention mechanism (CBAM), and the frequency channel attention mechanism (FCA). Compared with these three channel attention mechanisms, the mIoU of the FEM in the Vaihingen dataset is improved by 0.90%, 1.10%, and 0.40%, and in the OpenEarthMap dataset, it is improved by 2.30%, 2.20%, and 2.10%, respectively. The proposed channel attention mechanism in this paper shows better performance in remote sensing land use classification.
Contributions to cooperative localization techniques within mobile wireless bady area networks

The PhD investigations aim at exploring new WBAN cooperative localization mechanisms, which could benefit jointly from on-body links, body-to-body links between distinct mobile users or off-body links with respect to the infrastructure. Following a multidisciplinary approach, we have thus addressed theoretical questions related to physical modeling or to algorithmic and cross-layer design. A few more practical aspects have also been dealt with. More specifically, based on WBAN channel measurements, single-link ranging error models are first discussed for more realistic performance assessment. Then a Constrained Distributed Weighted Multi-Dimensional Scaling (CDWMDS) positioning algorithm is put forward for relative MoCap purposes, coping with on-body nodes' asynchronism to reduce system latency and exploiting the presence of constant-length radio links for better accuracy. Subsequently we consider extending this algorithm for larger-scale asbolute MoCap applications within a 2-step localization approach that incorporates additional off-body links in a heterogeneous WBAN framework. Then, both individual and collective kinds of navigation are addressed. In both MoCap and navigation scenarios, low-complexity solutions exploiting on-body deployment diversity enable to combat error propagation and strong range biases due to body shadowing, relying on on-body nodes' dispersion or graph neighborhood to approximate the corrupted distances. Finally, experiments based on real IR-UWB radio platforms validate in part the previous proposals, while showing their practical limitations.
Confined Space Nanoarchitectonics for Dynamic Functions and Molecular Machines

Nanotechnology has advanced the techniques for elucidating phenomena at the atomic, molecular, and nano-level. As a post nanotechnology concept, nanoarchitectonics has emerged to create functional materials from unit structures. Consider the material function when nanoarchitectonics enables the design of materials whose internal structure is controlled at the nanometer level. Material function is determined by two elements. These are the functional unit that forms the core of the function and the environment (matrix) that surrounds it. This review paper discusses the nanoarchitectonics of confined space, which is a field for controlling functional materials and molecular machines. The first few sections introduce some of the various dynamic functions in confined spaces, considering molecular space, materials space, and biospace. In the latter two sections, examples of research on the behavior of molecular machines, such as molecular motors, in confined spaces are discussed. In particular, surface space and internal nanospace are taken up as typical examples of confined space. What these examples show is that not only the central functional unit, but also the surrounding spatial configuration is necessary for higher functional expression. Nanoarchitectonics will play important roles in the architecture of such a total system.
A High-Resolution Imaging Method for Multiple-Input Multiple-Output Sonar Based on Deterministic Compressed Sensing

Differences between conventional sonar and Multiple-Input Multiple-Output (MIMO) sonar systems arise in achieving high angular and range resolution. MIMO sonar uses Matched Filtering (MF) with well-correlated transmitted signals to enhance spatial resolution by obtaining virtual arrays. However, imperfect correlation characteristics yield high sidelobe values, which hinder accurate target localization in underwater imagery. To address this, a Compressed Sensing (CS) method is proposed by reconstructing echo signals to suppress correlation noise between orthogonal waveforms. A shifted dictionary matrix and a deterministic Discrete Fourier Transform (DFT) measurement matrix are used to multiply received echo signals to yield compressed measurements. A sparse recovery algorithm is applied to optimize signal reconstruction before joint transmit–receive beamforming forms a 2D sonar image in the angle-range domain. Numerical simulations and lake experimental results confirm the effectiveness of the proposed method, by obtaining a lower sidelobe sonar image under sub-Nyquist sampling rates as compared with other approaches.
The Centennial Variation of El Niño Impact on Atlantic Tropical Cyclones

AbstractPredicting tropical cyclone (TC) activity becomes more important every year while the understanding of what factors impact them continues to be complicated. El Nino–Southern Oscillation (ENSO) is one of the primary factors impacting the activities in both the Pacific and the Atlantic, but an extensive examination of the fluctuation in this system has yet to be studied in its entirety. This article analyzes the ENSO impacts on the Atlantic tropical cyclone activity during the assessed warm and cold years to show the dominant centennial-scale variation impact. This study looks to plausibly link this variation to the Southern Ocean centennial variability, which is rarely mentioned in any factors affecting the Atlantic tropical cyclone activity. This centennial variability could be used to enhance future work related to predicting tropical cyclones.
Effect of Silica Fume Utilization on Structural Build-Up, Mechanical and Dimensional Stability Performance of Fiber-Reinforced 3D Printable Concrete

It is known that 3D printable concrete mixtures can be costly because they contain high dosages of binder and that the drying-shrinkage performance may be adversely affected. Mineral additives and fibers are generally used to control these negative aspects. In this study, the use of silica fume, a natural viscosity modifying admixture, was investigated to improve the rheological and thixotropic behavior of 3D printable concrete mixtures reinforced with polypropylene fiber (FR-3DPC). The effect of increasing the silica fume utilization ratio in FR-3DPC on the compressive strength (CS), flexural strength (FS), and drying-shrinkage (DS) performance of the mixtures was also examined. A total of five FR-3DPC mixtures were produced using silica fume at the rate of 3, 6, 9, and 12% of the cement weight, in addition to the control mixture without silica fume. As a result of the tests, the dynamic yield stress value decreased with the addition of 3% silica fume to the control mixture. However, it was found that the dynamic yield stress and apparent viscosity values of the mixtures increased with the addition of 6, 9, and 12% silica fume. With the increase in the use of silica fume, the CS values of the mixtures were generally affected positively, while the FS and DS behavior were affected negatively.
Does the goral (Naemorhedus) inhabit Laos or Vietnam

The goral (Naemorhedus) is sometimes taken as part of the fauna of Laos or Vietnam. We review relevant opinions and evidence, past and present, and conclude that the goral has not been biologically documented in either country. We encourage conservation personnel to be attentive to potential specimens, camera-trap records, or direct sightings.
A Light Multi-View Stereo Method with Patch-Uncertainty Awareness

Multi-view stereo methods utilize image sequences from different views to generate a 3D point cloud model of the scene. However, existing approaches often overlook coarse-stage features, impacting the final reconstruction accuracy. Moreover, using a fixed range for all the pixels during inverse depth sampling can adversely affect depth estimation. To address these challenges, we present a novel learning-based multi-view stereo method incorporating attention mechanisms and an adaptive depth sampling strategy. Firstly, we propose a lightweight, coarse-feature-enhanced feature pyramid network in the feature extraction stage, augmented by a coarse-feature-enhanced module. This module integrates features with channel and spatial attention, enriching the contextual features that are crucial for the initial depth estimation. Secondly, we introduce a novel patch-uncertainty-based depth sampling strategy for depth refinement, dynamically configuring depth sampling ranges within the GRU-based optimization process. Furthermore, we incorporate an edge detection operator to extract edge features from the reference image’s feature map. These edge features are additionally integrated into the iterative cost volume construction, enhancing the reconstruction accuracy. Lastly, our method is rigorously evaluated on the DTU and Tanks and Temples benchmark datasets, revealing its low GPU memory consumption and competitive reconstruction quality compared to other learning-based MVS methods.
Necessary and sufficient condition for M2-convergence to a Lévy process for billiards with cusps at flat points

We consider a class of planar dispersing billiards with a cusp at a point of vanishing curvature. Convergence to a stable law and to the corresponding Lévy process in theM1 andM2 Skorohod topologies has been studied in recent work. Here we show that certain sufficient conditions for M2-convergence are also necessary.
Fungal-Bacterial Combinations in Plant Health under Stress: Physiological and Biochemical Characteristics of the Filamentous Fungus Serendipita indica and the Actinobacterium Zhihengliuella sp. ISTPL4 under In Vitro Arsenic Stress

Fungal-bacterial combinations have a significant role in increasing and improving plant health under various stress conditions. Metabolites secreted by fungi and bacteria play an important role in this process. Our study emphasizes the significance of secondary metabolites secreted by the fungus Serendipita indica alone and by an actinobacterium Zhihengliuella sp. ISTPL4 under normal growth conditions and arsenic (As) stress condition. Here, we evaluated the arsenic tolerance ability of S. indica alone and in combination with Z. sp. ISTPL4 under in vitro conditions. The growth of S. indica and Z. sp. ISTPL4 was measured in varying concentrations of arsenic and the effect of arsenic on spore size and morphology of S. indica was determined using confocal microscopy and scanning electron microscopy. The metabolomics study indicated that S. indica alone in normal growth conditions and under As stress released pentadecanoic acid, glycerol tricaprylate, L-proline and cyclo(L-prolyl-L-valine). Similarly, d-Ribose, 2-deoxy-bis(thioheptyl)-dithioacetal were secreted by a combination of S. indica and Z. sp. ISTPL4. Confocal studies revealed that spore size of S. indica decreased by 18% at 1.9 mM and by 15% when in combination with Z. sp. ISTPL4 at a 2.4 mM concentration of As. Arsenic above this concentration resulted in spore degeneration and hyphae fragmentation. Scanning electron microscopy (SEM) results indicated an increased spore size of S. indica in the presence of Z. sp. ISTPL4 (18 ± 0.75 µm) compared to S. indica alone (14 ± 0.24 µm) under normal growth conditions. Our study concluded that the suggested combination of microbial consortium can be used to increase sustainable agriculture by combating biotic as well as abiotic stress. This is because the metabolites released by the microbial combination display antifungal and antibacterial properties. The metabolites, besides evading stress, also confer other survival strategies. Therefore, the choice of consortia and combination partners is important and can help in developing strategies for coping with As stress.
Multi-Object Trajectory Prediction Based on Lane Information and Generative Adversarial Network

Nowadays, most trajectory prediction algorithms have difficulty simulating actual traffic behavior, and there is still a problem of large prediction errors. Therefore, this paper proposes a multi-object trajectory prediction algorithm based on lane information and foresight information. A Hybrid Dilated Convolution module based on the Channel Attention mechanism (CA-HDC) is developed to extract features, which improves the lane feature extraction in complicated environments and solves the problem of poor robustness of the traditional PINet. A lane information fusion module and a trajectory adjustment module based on the foresight information are developed. A socially acceptable trajectory with Generative Adversarial Networks (S-GAN) is developed to reduce the error of the trajectory prediction algorithm. The lane detection accuracy in special scenarios such as crowded, shadow, arrow, crossroad, and night are improved on the CULane dataset. The average F1-measure of the proposed lane detection has been increased by 4.1% compared to the original PINet. The trajectory prediction test based on D2-City indicates that the average displacement error of the proposed trajectory prediction algorithm is reduced by 4.27%, and the final displacement error is reduced by 7.53%. The proposed algorithm can achieve good results in lane detection and multi-object trajectory prediction tasks.