Miracle-dz/UniFAR-FTUs huggingface dataset:
Remote sensing of the environment with small unmanned aircraft systems ( UASs ) , part 1 : a review of progress and challenges 1

The recent development and proliferation of unmanned aircraft systems (UASs) has made it possible to examine environmental processes and changes occurring at spatial and temporal scales that would be difficult or impossible to detect using conventional remote sensing platforms. This review article highlights new developments in UAS-based remote sensing, focusing mainly on small UASs (<25 kg). Because this class is generally less expensive and more versatile than larger systems the use of small UASs for civil, commercial, and scientific applications is expected to expand considerably in the future. To highlight different environmental applications, we provide an overview of recent progress in remote sensing with small UASs, including photogrammetry, multispectral and hyperspectral imaging, thermal, and synthetic aperture radar and LiDAR. We also draw on the literature and our own research experience to identify some key research challenges, including limitations of the current generation of platforms and sensors, and the development of optimal methodologies for processing and analysis. While much of the potential of small UASs for remote sensing remains to be realised, it is likely that the next few years will see such systems being used to provide data for an ever-increasing range of environmental applications.
Incidental Diagnosis of a Gastrointestinal Stromal Tumor during Cesarean Section : A case Report and Review of the Literature

Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal tumors that develop from the interstitial Cajal cells of the gastrointestinal tract. Given the age distribution of ocurrence, a diagnosis of GISTs during pregnancy or puerperium is very uncommon. A 26-year-old primigravid woman was admitted to our emergency department with labor pain. During cesarean a 7 cm mass was found incidentally, which originated from the antimesenteric wall of the small intestine. The patient underwent a small bowel resection and partial omentectomy on the 38th day after cesarean section by the general surgical team. Pathology revealed a 9x6x6 cm infiltrative gastrointestinal stromal tumor. Imatinib therapy was started with medical oncology’s recommendation. The patient is still being followed by the medical oncology clinic. In conclusion, exploration of the abdomen during a cesarean section is important for the detection of asymptomatic masses.
Emerging E-Threats and Data Security Model for Organizations in Nepal

This research mainly focuses on identifying most emerging e-threats that have been evolved by the date and distinguishes the effects they produce within the infected organizations. The research is conducted to distinguish various factors that play roles in data security requirements and data security approaches. The research also focuses on the study of various security models adopted by various private commercial organizations and governmental organizations that operate on sensitive/critical information in Nepal. The study was conducted using survey questionnaire and direct interview as a method of data collection and mixed research method as a research paradigm. This analysis is based on defined conceptual framework and policies which describes and classifies the techniques and processes that has to undergo within an organization in order to secure data and application from threats in organizations. The study highlighted some of the areas which could be vulnerable to the organization’s operations such as not having a proper information technology policy. The data security model suggested in this report recommends different phases and tasks that need to be performed in order to get increase the performance of the data security model as well as optimize the data security cost.
Textural complexity-based rate control algorithm

This paper presents an efficient rate control algorithm based on our content-adaptive initial quantization parameter setting scheme for H.264/AVC. For versatile video scenes, our algorithm can adaptively set an appropriate initial QP based on the textural complexity estimated from the first picture. In addition, our bit-allocation strategy effectively distributes the bit-rate budget based on the monotonic property to enhance the coding efficiency. Our proposed algorithm surpasses JVT-H014 rate control algorithm and Cauchy-density-based bit-allocation scheme in terms of average PSNR for about 0.47 dB and 0.81 dB respectively. Besides, our algorithm provides more impressive visual quality and more robust buffer controllability.
Erlotinib Versus Gefitinib for Control of Leptomeningeal Carcinomatosis in Non–Small-Cell Lung Cancer

Introduction: Leptomeningeal carcinomatosis (LMC) from non–small-cell lung cancer (NSCLC) is a clinically important neurological complication in the era of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs). The purpose of this study was to compare the efficacy of gefitinib and erlotinib for control of LMC in NSCLC. Methods: We retrospectively reviewed medical records of 25 EGFR TKI–treated NSCLC patients with LMC between 2004 and 2012 at Seoul National University Hospital. Cytologic negative conversion was defined as absence of malignant cells in the cerebrospinal fluid three times in succession. Cytologic conversion rates were compared between the gefitinib arm and the erlotinib arm. Results: Nine patients had exon 21 point mutations and eight patients had exon 19 deletional mutations. Nine of 25 patients had already used EGFR TKIs and switched to another EGFR TKI after LMC occurrence. The other 16 patients received EGFR TKIs after LMC diagnoses. All the patients received intrathecal chemotherapy, including methotrexate, and six of them were treated with combined whole-brain radiotherapy. Gefitinib and erlotinib were administered to 11 and 14 patients, respectively. Ten patients had LMC controlled with cytologic negative conversion, whereas in 15 patients, cytological clearance of the cerebrospinal fluid could not be achieved. Patients treated with erlotinib showed better cytologic conversion rate of LMC than those with gefitinib (64.3% [9 of 14] in the erlotinib arm versus 9.1% [1 of 11] in the gefitinib arm; p = 0.012). Conclusion: This study suggested that erlotinib had better control rate for LMC in NSCLC than gefitinib. Further prospective study is warranted.
Quantitative interdependence of coeffectors, CcpA and cre in carbon catabolite regulation of Bacillus subtilis

The phosphoproteins HPrSerP and CrhP are the main effectors for CcpA‐mediated carbon catabolite regulation (CCR) in Bacillus subtilis. Complexes of CcpA with HPrSerP or CrhP regulate genes by binding to the catabolite responsive elements (cre). We present a quantitative analysis of HPrSerP and CrhP interaction with CcpA by surface plasmon resonance (SPR) revealing small and similar equilibrium constants of 4.8 ± 0.4 µm for HPrSerP–CcpA and 19.1 ± 2.5 µm for CrhP–CcpA complex dissociation. Forty millimolar fructose‐1,6‐bisphosphate (FBP) or glucose‐6‐phosphate (Glc6‐P) increases the affinity of HPrSerP to CcpA at least twofold, but have no effect on CrhP–CcpA binding. Saturation of binding of CcpA to cre as studied by fluorescence and SPR is dependent on 50 µm of HPrSerP or > 200 µm CrhP. The rate constants of HPrSerP–CcpA–cre complex formation are ka = 3 ± 1 × 106 m−1·s−1 and kd = 2.0 ± 0.4 × 10−3·s−1, resulting in a KD of 0.6 ± 0.3 nm. FBP and Glc6‐P stimulate CcpA–HPrSerP but not CcpA‐CrhP binding to cre. Maximal HPrSerP‐CcpA–cre complex formation in the presence of 10 mm FBP requires about 10‐fold less HPrSerP. These data suggest a specific role for FBP and Glc6‐P in enhancing only HPrSerP‐mediated CCR.
Effect of mixed organic-inorganic fertilizer on growth and phosphorus uptake of setaria grass ('Setaria splendida')

Increasing phosphorus (P) availability in tropical P deficient soils is a challenging task. Vermicomposting of organic wastes in the presence of phosphate rock facilitates the release of P and this has the potential to address crop P needs. A study was conducted to assess and compare the effects of application of gafsa phosphate rock (GPR) alone and GPR in combination with empty oil palm fruit bunches, earthworms (Pontoscolex corethrurus), arbuscular mycorrhiza fungi (Glomus mosseae), and P-enriched vermicompost, in fulfilling the P requirements of the setaria (Setaria splendida L.,) grass. Application of mixed organic fertilizer combined with GPR was effective in increasing dry matter yield of grass, with 19% higher dry matter production as compared to the use of GPR alone. Among the organic fertilizers, application of P-enriched vermicompost was the best to support the grass growth. Nitrogen, P, Ca, and Mg uptake of the grass treated with P-enriched vermicompost was higher. Nitrogen and P utilization efficiency of the setaria grass treated with P-enriched vermicompost was also high. Residual P in soil treated with GPR was higher as compared to that treated with P-enriched vermicompost. However, plant available P was higher than that for the other GPR application techniques. The different types of earthworms had no effect on the quantum of nutrient uptake and the dry matter yield of the setaria grass. Application of a mixture of GPR and empty oil palm fruit bunch to the soil increased the dry matter of setaria compared to the use of inorganic fertilizer alone. We conclude that soil treated with P-enriched vermicompost was an efficient treatment for increasing availability of P (24.28 mg kg-1), N, P, Ca and Mg uptake (53.76, 41.83, 13.58 and 15.16 mg pot-1, respectively); which ultimately enhanced root volume (163 cm3) and dry matter yield (5.75 to 6.46 g pot-1).
SYSTEMIC PLASMA LEVELS OF NITRITE/NITRATE (NOX) REFLECT BRACHIAL FLOW‐MEDIATED DILATION RESPONSES IN YOUNG MEN AND WOMEN

1 The aim of the present study was to determine the relationship between plasma levels of nitrite/nitrite (NOx) and brachial flow‐mediated dilation (FMD) in healthy young men and women. 2 Brachial artery FMD was assessed non‐invasively using high‐resolution ultrasound in 36 young men and women (21 ± 3 years; 18 men and 18 women). Blood samples for NOx assays were collected from an indwelling venous catheter in the forearm following an overnight fast and a 36 h low‐nitrate diet. 3 Plasma levels of NOx were related to peak brachial FMD% (r = 0.53; P = 0.001). The relationship was maintained when the brachial dilation was expressed as absolute diameter change (Δmm; r = 0.51; P = 0.002) and when it was normalized (/s) to the mean shear rate (r = 0.50; P = 0.002). 4 The present study demonstrates a relationship between peak FMD in the brachial artery and plasma levels of NOx in young men and women. This relationship suggests that brachial FMD and/or plasma NOx may be used as markers of peripheral endothelial function.
FaceSwapNet: Landmark Guided Many-to-Many Face Reenactment

Recent face reenactment studies have achieved remarkable success either between two identities or in the many-to-one task. However, existing methods have limited scalability when the target person is not a predefined specific identity. To address this limitation, we present a novel many-to-many face reenactment framework, named FaceSwapNet, which allows transferring facial expressions and movements from one source face to arbitrary targets. Our proposed approach is composed of two main modules: the landmark swapper and the landmark-guided generator. Instead of maintaining independent models for each pair of person, the former module uses two encoders and one decoder to adapt anyone's face landmark to target persons. Using the neutral expression of the target person as a reference image, the latter module leverages geometry information from the swapped landmark to generate photo-realistic and emotion-alike images. In addition, a novel triplet perceptual loss is proposed to force the generator to learn geometry and appearance information simultaneously. We evaluate our model on RaFD dataset and the results demonstrate the superior quality of reenacted images as well as the flexibility of transferring facial movements between identities.
Democratizing the Network Edge

The cloud and telecommunications industry is in the midst of a transition towards the edge. There is a tremendous opportunity for the research community to influence this transformation, but doing so requires understanding industry momentum, and making a concerted effort to align with that momentum. We believe there are three keys to doing this: (1) focus on the intersection of the cloud and access networks, (2) contribute to the relevant open source projects, and (3) address the challenge of operationalizing the results. The paper puts forward a concrete proposal for all three, and discusses the opportunity to influence how the Internet evolves at the edge and enable innovative edge applications.
On the Oosterhoff dichotomy in the Galactic bulge – II. Kinematical distribution

We present a study of the Oosterhoff (Oo) dichotomy in the Galactic bulge using 8 141 fundamental mode RR Lyrae stars. We used public photometric data from the Optical Gravitational Lensing Experiment (OGLE) and the Vista Variables in the VVV survey (VVV). We carefully selected fundamental mode stars without modulation and without association with any globular cluster located towards the Galactic bulge. Subsequently, we identified and separated the Oosterhoff groups I and II on the basis of their period-amplitude distribution and using a relation fitted to the Oosterhoff I locus. Both Oosterhoff groups were then compared to observations of two bulge globular clusters and with models of stellar pulsation and evolution. We found that some of the variables classified as Oo II belong to a third Oo group. The Oosterhoff II variables are more metal-poor on average, more massive, and cooler than their Oosterhoff I counterparts. The analysis of their spatial distribution shows a systematic difference between foreground, central and background regions in the occurrence of the Oosterhoff II group. The difference between the Oo I and II groups is also seen in their distance distributions with respect to the Galactic bar, but neither group is associated with the bar.
Video-based Person Re-identification with Two-stream Convolutional Network and Co-attentive Snippet Embedding

Recently, the applications of person re-identification in visual surveillance and human-computer interaction are sharply increasing, which signifies the critical role of such a problem. In this paper, we propose a two-stream convolutional network (ConvNet) based on the competitive similarity aggregation scheme and co-attentive embedding strategy for video-based person re-identification. By dividing the long video sequence into multiple short video snippets, we manage to utilize every snippet's RGB frames, optical flow maps and pose maps to facilitate residual networks, e.g., ResNet, for feature extraction in the two-stream ConvNet. The extracted features are embedded by the co-attentive embedding method, which allows for the reduction of the effects of noisy frames. Finally, we fuse the outputs of both streams as the embedding of a snippet, and apply competitive snippet-similarity aggregation to measure the similarity between two sequences. Our experiments show that the proposed method significantly outperforms current state-of-the-art approaches on multiple datasets.
Manipulating a Learning Defender and Ways to Counteract

In Stackelberg security games when information about the attacker's payoffs is uncertain, algorithms have been proposed to learn the optimal defender commitment by interacting with the attacker and observing their best responses. In this paper, we show that, however, these algorithms can be easily manipulated if the attacker responds untruthfully. As a key finding, attacker manipulation normally leads to the defender learning a maximin strategy, which effectively renders the learning attempt meaningless as to compute a maximin strategy requires no additional information about the other player at all. We then apply a game-theoretic framework at a higher level to counteract such manipulation, in which the defender commits to a policy that specifies her strategy commitment according to the learned information. We provide a polynomial-time algorithm to compute the optimal such policy, and in addition, a heuristic approach that applies even when the attacker's payoff space is infinite or completely unknown. Empirical evaluation shows that our approaches can improve the defender's utility significantly as compared to the situation when attacker manipulation is ignored.
The Mediating Roles of Psychological Autonomy, Competence and Relatedness on Work-Life Balance and Well-Being

The main objective of this current research is to investigate the impact of “work balance” on “psychological well-being” using employees within the hospitality industry in United Arab Emirates as statistical units. To meet the objective of this research, we developed a structural equation model to examine how psychological autonomy, psychological competence, and psychological relatedness affect psychological well-being and work-life balance, as well as the effect of work-life balance on psychological well-being. We also examine the mediating effect of work-life balance in these relationships. The results of this study show that psychological autonomy affect positively both psychological well-being and work-life balance, whereas psychological competence only affect psychological well-being positive. Moreover, psychological relatedness affects negatively both psychological well-being and work-life balance while work-life balance affects positively psychological well-being.
Union Visual Translation Embedding for Visual Relationship Detection and Scene Graph Generation

Relations amongst entities play a central role in image understanding. Due to the combinatorial complexity of modeling (subject, predicate, object) relation triplets, it is crucial to develop a method that can not only recognize seen relations, but also generalize well to unseen cases. Inspired by Visual Translation Embedding network (VTransE), we propose the Union Visual Translation Embedding network (UVTransE) to capture both common and rare relations with better accuracy. UVTransE maps the subject, the object, and the union (subject, object) image regions into a low-dimensional relation space where a predicate can be expressed as a vector subtraction, such that predicate $\approx$ union (subject, object) $-$ subject $-$ object. We present a comprehensive evaluation of our method on multiple challenging benchmarks: the Visual Relationship Detection dataset (VRD); UnRel dataset for rare and unusual relations; two subsets of Visual Genome; and the Open Images Challenge. Our approach decisively outperforms VTransE and comes close to or exceeds the state of the art across a range of settings, from small-scale to large-scale datasets, from common to previously unseen relations. On Visual Genome and Open Images, it also achieves promising results on the recently introduced task of scene graph generation.
Statistical bounds for entropic optimal transport: sample complexity and the central limit theorem

We prove several fundamental statistical bounds for entropic OT with the squared Euclidean cost between subgaussian probability measures in arbitrary dimension. First, through a new sample complexity result we establish the rate of convergence of entropic OT for empirical measures. Our analysis improves exponentially on the bound of Genevay et al. (2019) and extends their work to unbounded measures. Second, we establish a central limit theorem for entropic OT, based on techniques developed by Del Barrio and Loubes (2019). Previously, such a result was only known for finite metric spaces. As an application of our results, we develop and analyze a new technique for estimating the entropy of a random variable corrupted by gaussian noise.
Differentiable Algorithm Networks for Composable Robot Learning

This paper introduces the Differentiable Algorithm Network (DAN), a composable architecture for robot learning systems. A DAN is composed of neural network modules, each encoding a differentiable robot algorithm and an associated model; and it is trained end-to-end from data. DAN combines the strengths of model-driven modular system design and data-driven end-to-end learning. The algorithms and models act as structural assumptions to reduce the data requirements for learning; end-to-end learning allows the modules to adapt to one another and compensate for imperfect models and algorithms, in order to achieve the best overall system performance. We illustrate the DAN methodology through a case study on a simulated robot system, which learns to navigate in complex 3-D environments with only local visual observations and an image of a partially correct 2-D floor map.
Research on the Development Path of Blockchain in Shipping Industry

As a new decentralized infrastructure, blockchain has received attention and research in various fields. The decentralization, openness, autonomy and anonymity of the blockchain are of great significance to the development of the shipping industry. This paper outlines the characteristics and key technologies of the blockchain and introduces the infrastructure model of the blockchain. Combined with the characteristics of blockchain and shipping industry, this paper expounds the application status of blockchain in the shipping industry, analyzes the application prospects of the shipping industry to exploit the advantages of blockchain, and proposes the application barriers in the process of integration. This presents the development path of the blockchain in the shipping industry.
A Memorization Approach for Test Case Generation in Concurrent UML Activity Diagram

Test case generation is the most important part of software testing. Currently, researchers have used the UML activity diagram for test case generation. Testing concurrent system is difficult task due to the concurrent interaction among the threads and the system results in test case explosion. In this paper, we proposed a novel approach to generate test cases for concurrent systems using a dynamic programming technique with tester specification to avoid the path explosion. The tester can configure the concurrency specifications that follow the business flow constraints. In order to evaluate the quality of test cases, activity coverage and causal ordering coverage were measured. By experimental results, the proposed approach is superior as compared to DFS and BFS algorithms. Finally, the proposed approach helps to avoid generating all possible concurrent activity paths which are able to minimize test cases explosion.