Miracle-dz/UniFAR-FTUs huggingface dataset:
Hummingbird: energy efficient GPS receiver for small satellites

Global Positioning System is a widely adopted localization technique. With the increasing demand for small satellites, the need for a low-power GPS for satellites is also increasing. To enable many state-of-the-art applications, the exact position of the satellites is necessary. However, building low-power GPS receivers which operate in low earth orbit pose significant challenges. This is mainly due to the high speed (~7.8 km/s) of small satellites. While duty-cycling the receiver is a possible solution, the high relative Doppler shift between the GPS satellites and the small satellite contributes to the increase in Time To First Fix (TTFF), thus increasing the energy consumption. Further, if the GPS receiver is tumbling along with the small satellite on which it is mounted, longer TTFF may lead to no GPS fix due to disorientation of the receiver antenna. In this paper, we elucidate the design of a low-cost, low-power GPS receiver for small satellite applications. We also propose an energy optimization algorithm called F3to improve the TTFF which is the main contributor to the energy consumption during cold start. With simulations and in-orbit evaluation from a launched nanosatellite with our μGPS and high-end GPS simulators, we show that up to 96.16% of energy savings (consuming only ~ 1/25th energy compared to the state of the art) can be achieved using our algorithm without compromising much (~10 m) on the navigation accuracy. The TTFF achieved is at most 33 s.
Snug: architectural support for relaxed concurrent priority queueing in chip multiprocessors

Many parallel algorithms in domains such as graph analytics and simulations rely on priority-based task scheduling. In such environments, the data structure of choice is a concurrent priority queue (PQ). Unfortunately, PQ algorithms exhibit an undesirable tradeoff. On one hand, strict PQs always dequeue the highest-priority task, and thus fail to scale because of contention at the head of the queue. On the other hand, relaxed PQs avoid contention by dequeuing tasks that are sometimes so far from the head that the resulting schedule misses the benefit of priority-based scheduling. We propose a novel architecture for relaxing PQs without straying far from the priority-based schedule. Our chip-level architecture, called Snug, distributes the PQ into subqueues, and maintains a set of Work registers that point to the highest-priority task in each sub-queue. Snug provides an instruction that picks a high-quality task to execute. The instruction periodically switches between obtaining an accurate global snapshot, and visiting only local subqueues to reduce traffic. Overall, Snug dequeues high-quality tasks while avoiding both hotspots and excessive network traffic. We evaluate Snug on graph analytics and event simulation programs. On a simulated 64-core chip, Snug reduces the average execution time of the programs by 1.4X, 2.4X and 3.6X compared to state-of-the-art concurrent skip list, SprayList, and software-distributed PQs, respectively.
Enhancing UAV-SfM 3D Model Accuracy in High-Relief Landscapes by Incorporating Oblique Images

Complex landscapes with high topographic relief and intricate geometry present challenges for complete and accurate mapping of both lateral (x, y) and vertical (z) detail without deformation. Although small uninhabited/unmanned aerial vehicles (UAVs) paired with structure-from-motion (SfM) image processing has recently emerged as a popular solution for a range of mapping applications, common image acquisition and processing strategies can result in surface deformation along steep slopes within complex terrain. Incorporation of oblique (off-nadir) images into the UAV–SfM workflow has been shown to reduce systematic errors within resulting models, but there has been no consensus or documentation substantiating use of particular imaging angles. To address these limitations, we examined UAV–SfM models produced from image sets collected with various imaging angles (0–35°) within a high-relief ‘badland’ landscape and compared resulting surfaces with a reference dataset from a terrestrial laser scanner (TLS). More than 150 UAV–SfM scenarios were quantitatively evaluated to assess the effects of camera tilt angle, overlap, and imaging configuration on the precision and accuracy of the reconstructed terrain. Results indicate that imaging angle has a profound impact on accuracy and precision for data acquisition with a single camera angle in topographically complex scenes. Results also confirm previous findings that supplementing nadir image blocks with oblique images in the UAV–SfM workflow consistently improves spatial accuracy and precision and reduces data gaps and systematic errors in the final point cloud. Subtle differences among various oblique camera angles and imaging patterns suggest that higher overlap and higher oblique camera angles (20–35°) increased precision and accuracy by nearly 50% relative to nadir-only image blocks. We conclude by presenting four recommendations for incorporating oblique images and adapting flight parameters to enhance 3D mapping applications with UAV–SfM in high-relief terrain.
Seed science in the 21st century: its role in emerging economies

Abstract Emerging economies (Brazil, Russia, India, China and other countries) are expected to play a major role in the global economy during the 21st century. Some of these countries have exceptional soil and climate characteristics that determine evident advantages for food production. These features, combined with a rapid adoption of technologies generated by industrialized economies (i.e. transgenic crops and others), have been instrumental to fast expansion of agricultural production in recent years. For such reasons, some of these economies are strongly based on production of food commodities (agriculture represents 18.3, 12.6, 9.4 and 8.1% of the gross domestic product of India, China, Argentina and Brazil, respectively) and have a great share in global food production. Despite the mentioned characteristics that make agricultural activity so efficient in these countries, generation of new technologies in order to guarantee the systems' sustainability and add value to agricultural production (by means of, for example, royalties or technologies generated with local criteria) relies on research carried out in areas such as crop science, biotechnology, ecology, plant breeding and, of course, seed science. However, the amount of local research carried out in these countries appears not to be in agreement with the importance that agricultural production has in their economies. For example, Argentina produces 16.20% of the soybean produced in the world but only 2% of the scientific literature related to this crop in its many aspects. This imbalance between the weight that agricultural production has on these economies and generation of knowledge in the related disciplines, threatens the sustainability of these economic models and, therefore, of global food production. Seed science, then, is called on to play a major role in these emerging economies, through the different approaches (i.e. ecological, physiological, agronomical and molecular) that the discipline has to offer. Here we provide four examples in which seed science (through any of the four approaches mentioned above): (1) has identified subtle but crucial components of newly adopted production systems; (2) has proposed means for their adjustment in order to secure the sustainability of those systems; and (3) might help to add value to agricultural production through the development of new germplasm displaying specific features (e.g. timing of dormancy release adjusted to industrial necessities).
Nestling sex-ratio variation in Western Bluebirds

ABsTRAcr. -We tested five hypotheses for facultative manipulation of sex ratios in a population of Western Bluebirds (Sialia mexicana) studied for 13 years in California. Based on 2,187 nestlings from 549 broods, the overall mean (? SE) proportion of males was 51.9 + 1.1%, not significantly different from 50%. Sex ratios of nestlings were significantly biased in only 1 of 13 years, and we failed to detect any significant bias related to brood reduction, breeder female age, presence of helper males, first-egg date, condition of the breeder female, or annual differences in environmental conditions. These results allow us to reject all five hypotheses, including: (1) nestling size dimorphism and local resource competition, both of which predict a female-biased sex ratio; (2) local resource enhancement via the "repayment model" of Emlen et al. (1986), which predicts a more male-biased sex ratio than we observed; and (3) seasonal changes in either maternal condition or nestling condition, both of which predict shifts in sex ratios not observed in our data. These results prompt us to urge caution when reporting sex-ratio biases in natural populations and when interpreting published studies, many of which suffer from small sample sizes, post hoc analyses, and insufficiently conservative statistical tests. Sex-ratio biases in birds are uncommon, and considerable data will be necessary to determine which hypotheses (if any) are sufficiently robust to regularly select for avian sex ratios that deviate significantly from 50:50. Received 22 January 1996, accepted 20 June 1996.
STAN: Synthetic Network Traffic Generation using Autoregressive Neural Models

Deep learning models have achieved great success in recent years. However, large amounts of data are typically required to train such models. While some types of data, such as images, videos, and text, are easier to find, data in certain domains is difficult to obtain. For instance, cybersecurity applications routinely use network traffic data which organizations are reluctant to share, even internally, due to privacy reasons. An alternative is to use synthetically generated data; however, most existing data generating methods lack the ability to capture complex dependency structures that are usually prevalent in real data by assuming independence either temporally or between attributes. This paper presents our approach called STAN, Synthetic Network Traffic Generation using Autoregressive Neural models, to generate realistic synthetic network traffic data. Our novel autoregressive neural architecture captures both temporal dependence and dependence between attributes at any given time. It integrates convolutional neural layers (CNN) with mixture density layers (MDN) and softmax layers to model both continuous and discrete variables. We evaluate performance of STAN by training it on both a simulated dataset and a real network traffic data set. Multiple metrics are used to compare the generated data with real data and with data generated via several baseline methods. Finally, to answer the question -- can real network traffic data be substituted with synthetic data to train models of comparable accuracy -- we consider two commonly used models for anomaly detection in such data, and compare F1/MSE measures of models trained on real data and those on increasing proportions of generated data. The results show only a small decline in accuracy of models trained solely on synthetic data.
Phylogénies moléculaires et insertions-délétions de nucléotides

Molecular trees based on the analysis of sequence data can be obtained through parsimony procedures. Such approaches identify evolutionary events (homologies and homoplasies and their location in the tree). Nevertheless, it is not possible generally to analyze directly the information given by the aligned sequences. Noticeably, gaps ("indel") need special coding. Standard procedures for coding gaps offer alternatives which suffer of several weaknesses. In this article a new strategy of coding the sequences is defined in view to express the potential phylogenetic information contained in complex zones with internested insertion/deletion and substitutions, contrary to what is done up to the present. This strategy applies without loss or distortion of information to any case where gaps are present in aligned sequences. According to the hierarchy of internested states of characters (sites), this strategy introduces in the data matrix question marks, "? ", which are optimized in fine in the cladogram based on all data. These "? " are not missing data, they are methodological codes, neutral to a priori phylogenetic hypotheses.
Perfect Matching Index versus Circular Flow Number of a Cubic Graph

The perfect matching index of a cubic graph $G$, denoted by $\pi(G)$, is the smallest number of perfect matchings that cover all the edges of $G$. According to the Berge-Fulkerson conjecture, $\pi(G)\le5$ for every bridgeless cubic graph~$G$. The class of graphs with $\pi\ge 5$ is of particular interest as many conjectures and open problems, including the famous cycle double cover conjecture, can be reduced to it. Although nontrivial examples of such graphs are very difficult to find, a few infinite families are known, all with circular flow number $\Phi_c(G)=5$. It has been therefore suggested [Electron. J. Combin. 23 (2016), $\#$P3.54] that $\pi(G)\ge 5$ might imply $\Phi_c(G)\ge 5$. In this article we dispel these hopes and present a family of cyclically $4$-edge-connected cubic graphs of girth at least $5$ (snarks) with $\pi\ge 5$ and $\Phi_c\le 4+\frac23$.
Pulmonary Delivery of Biological Drugs

In the last decade, biological drugs have rapidly proliferated and have now become an important therapeutic modality. This is because of their high potency, high specificity and desirable safety profile. The majority of biological drugs are peptide- and protein-based therapeutics with poor oral bioavailability. They are normally administered by parenteral injection (with a very few exceptions). Pulmonary delivery is an attractive non-invasive alternative route of administration for local and systemic delivery of biologics with immense potential to treat various diseases, including diabetes, cystic fibrosis, respiratory viral infection and asthma, etc. The massive surface area and extensive vascularisation in the lungs enable rapid absorption and fast onset of action. Despite the benefits of pulmonary delivery, development of inhalable biological drug is a challenging task. There are various anatomical, physiological and immunological barriers that affect the therapeutic efficacy of inhaled formulations. This review assesses the characteristics of biological drugs and the barriers to pulmonary drug delivery. The main challenges in the formulation and inhalation devices are discussed, together with the possible strategies that can be applied to address these challenges. Current clinical developments in inhaled biological drugs for both local and systemic applications are also discussed to provide an insight for further research.
Handling the Hurdles on the Way to Anti-tuberculosis Drug Development

The global epidemic of tuberculosis (TB) imposes a sustained epidemiologic vigilance and investments in research by governments. Mycobacterium tuberculosis, the main causative agent of TB in human beings, is a very successful pathogen, being the main cause of death in the population among infectious agents. In 2018, ~10 million individuals were contaminated with this bacillus and became ill with TB, and about 1.2 million succumbed to the disease. Most of the success of the M. tuberculosis to linger in the population comes from its ability to persist in an asymptomatic latent state into the host and, in fact, the majority of the individuals are unaware of being contaminated. Even though TB is a treatable disease and is curable in most cases, the treatment is lengthy and laborious. In addition, the rise of resistance to first-line anti-TB drugs elicits a response from TB research groups to discover new chemical entities, preferably with novel mechanisms of action. The pathway to find a new TB drug, however, is arduous and has many barriers that are difficult to overcome. Fortunately, several approaches are available today to be pursued by scientists interested in anti-TB drug development, which goes from massively testing chemical compounds against mycobacteria, to discovering new molecular targets by genetic manipulation. This review presents some difficulties found along the TB drug development process and illustrates different approaches that might be used to try to identify new molecules or targets that are able to impair M. tuberculosis survival.
Validation Analysis of Scalable Vector Graphics (SVG) File Upload using Magic Number and Document Object Model (DOM)

The use of technology is increasing rapidly, such as applications or services connected to the Internet. Security is considered necessary because of the growing and increasing use of digital systems. With the number of threats to attacks on digital form or server systems is required to handle the risk of attacks on the server, the file upload feature. The system usually processes the file upload feature on a website or server with server-side (back-end) validation or filtering of digital object file types or a client-side (front-end) web browser in HTML or Javascript. Filtering techniques for Scalable Vector Graphics (SVG) usually files only see the file extension or Multipurpose Internet Mail Extension (MIME) type of an uploaded file. However, this filtering can still manipulate, for example, in ASCII prefix checking, which has two writes, namely "<? xml” and “<svg ”. SVG files do not contain metadata such as image encoded in JPEG or PNG files. This problem can overcome by adding filtering techniques to check the validation of a file with validation of eXtensible Markup Language (XML) using magic numbers and the Document Object Model (DOM). This research developed using the waterfall method and black-box security testing refers to a software security testing method in which security controls, defense, and application design are tested. Handling of security validation for uploading SVG files using file extensions and MIME types has a success rate of 75 percent from the eight tested scenarios while handling using file extensions, magic numbers, and Document Object Model (DOM) produces a success rate of 100 percent from 8 test scenarios. Testing uses a black-box so that handling using the file extension, magic number, and Document Object Model (DOM) is better than using only file extensions and mime types.
A Hybrid Impedance Controller for Series Elastic Actuators to Render a Wide Range of Stable Stiffness in Uncertain Environments

Accurate and wide-range stiffness control is important for safe human-robot interaction. Accurate stiffness control can be better achieved using series elastic actuators (SEAs) than conventional rigid actuators. However, the stable range of virtual stiffness rendered by SEAs is limited by the stiffness of the actual spring, which cannot be too high in order to ensure good force control accuracy. Adding a virtual damper or derivative gain can increase the stable range of virtual stiffness, but the stable range would highly depend on the environmental stiffness. To relax the stiffness limitation in uncertain environments and explore more merits of SEAs, this letter proposes a hybrid impedance controller. This new controller linearly combines the spring force feedback and inertia force feedback. The stable range of virtual stiffness can be easily increased to ten times the actual spring stiffness with minimum effect on the force control accuracy. Unlike typical impedance controllers, the environmental stiffness can be used to raise the stable range of stiffness and hence the robustness of the controller can be ensured. Experiments will be provided to verify the hybrid impedance controller. We expect that the hybrid impedance controller can be used for SEAs in unstructured environments to provide a wide range of virtual stiffness.
A MODEL INVESTIGATION OF AZORES IMPACTS OVER FRANCE

Saqib-Ur-Rehman 1 , Bilal Ahmed Usmani 2 , Mustafain Ali 2 , Syeda Sadia Zia 1 Atia Elahi 1 , Sara Ali 1 , Sarwat Zehra Zaidi 1 and Kamran Khan 3 . 1. Department of Mathematics, University of Karachi, Karachi, Pakistan. 2. Department of Bio Medial Engineering, NED University of Engineering and Technology, Karachi, Pakistan. 3. Mathematical Sciences Research Center, Federal Urdu University of Arts, Sciences and Technology, Karachi, Pakistan. Manuscript Info Abstract . Manuscript History Received: 02 January 2018 Final Accepted: 04 February 2019 Published: March 2019
Questionable Reliability of Malondialdehyde to Measure Oxidative Stress in Sjögren’s Syndrome: Preliminary Study

Purpose:Purpose: To investigate the expression of malondialdehyde (MDA), lipid peroxidation marker for oxidative stress (OS), in autoimmune Sjögren’s syndrome (SjS) by utilizing the SjS-prone C57BL/6.NOD-Aec1Aec2 (B6DC) mouse and the SjS patient plasma samples. Methods:Methods: The MDA concentrations in the lysates of the submandibular gland, liver, and serum samples from the SjS-prone B6DC mouse model were compared with those from the C57BL/6J as a control. A thiobarbituric acid reactive substance (TBARS) assay kit was used to measure MDA. Plasma samples from five SjS patients and five control subjects were also evaluated. Results:Results: The MDA concentrations in experimental animals and controls were not significantly different. There were no significant differences between the plasma of SjS patients and of controls. Conclusions:Conclusions: The expression of MDA was investigated in the organs from the SjS-prone B6DC mouse for the first time and in the plasma samples of SjS patients. No significant differences were observed between SjS and control samples when MDA was the target molecule with the TBARS assay. MDA may not be a reliable marker to measure OS contrary to the published studies involving OS of
(Epi)Genetic Mechanisms Underlying the Evolutionary Success of Eusocial Insects

Simple Summary Social insects, namely ants, bees, and termites, are among the most numerous and successful animals on Earth. This is due to a variety of features: highly cooperative behavior performed by colony members and their specialization on a variety of tasks. Diverse physiological and behavioral specializations are regulated not only by the genetic system, but also by the epigenetic system which alters gene expressions without modifying the genetic code. This review will summarize recent advancements in such studies in eusocial insects. Abstract Eusocial insects, such as bees, ants, and wasps of the Hymenoptera and termites of the Blattodea, are able to generate remarkable diversity in morphology and behavior despite being genetically uniform within a colony. Most eusocial insect species display caste structures in which reproductive ability is possessed by a single or a few queens while all other colony members act as workers. However, in some species, caste structure is somewhat plastic, and individuals may switch from one caste or behavioral phenotype to another in response to certain environmental cues. As different castes normally share a common genetic background, it is believed that much of this observed within-colony diversity results from transcriptional differences between individuals. This suggests that epigenetic mechanisms, featured by modified gene expression without changing genes themselves, may play an important role in eusocial insects. Indeed, epigenetic mechanisms such as DNA methylation, histone modifications and non-coding RNAs, have been shown to influence eusocial insects in multiple aspects, along with typical genetic regulation. This review summarizes the most recent findings regarding such mechanisms and their diverse roles in eusocial insects.