Miracle-dz/UniFAR-FTUs huggingface dataset:
The UV-brightest Lyman continuum emitting star-forming galaxy

We report the discovery of J0121+0025, an extremely luminous and young star-forming galaxy (MUV = −24.11, log[LLyα/erg s−1] = 43.8) at z = 3.244 showing copious Lyman continuum (LyC) leakage ( fesc,abs ≈ 40%). High SNR rest-frame UV spectroscopy with the Gran Telescopio Canarias reveals a high significance (7.9σ) emission below the Lyman limit (< 912Å), with a flux density level f900 = 0.78 ± 0.10μJy, and strong P-Cygni in wind lines of O vi 1033Å, N v 1240Å and C iv 1550Å that are indicative of a young age of the starburst (< 10 Myr). The spectrum is rich in stellar photospheric features, for which a significant contribution of an AGN at these wavelengths is ruled out. Low-ionization ISM absorption lines are also detected, but are weak (EW0 ' 1Å) and show large residual intensities, suggesting a clumpy geometry of the gas with a non-unity covering fraction or a highly ionized ISM. The contribution of a foreground andAGNcontamination to the LyC signal is unlikely. Deep optical to Spitzer/IRAC 4. 5μm imaging show that the spectral energy distribution of J0121+0025 is dominated by the emission of the young starburst, with log(Mburst ★ /M ) = 9.9 ± 0.1 and SFR = 981 ± 232 M yr−1. J0121+0025 is the most powerful LyC emitter known among the star-forming galaxy population. The discovery of such luminous and young starburst leaking LyC radiation suggests that a significant fraction of LyC photons can escape in sources with a wide range of UV luminosities and are not restricted to the faintest ones as previously thought. These findings might shed further light on the role of luminous starbursts to the cosmic reionization.
Combining Online Learning and Offline Learning for Contextual Bandits with Deficient Support

We address policy learning with logged data in contextual bandits. Current offline-policy learning algorithms are mostly based on inverse propensity score (IPS) weighting requiring the logging policy to have \emph{full support} i.e. a non-zero probability for any context/action of the evaluation policy. However, many real-world systems do not guarantee such logging policies, especially when the action space is large and many actions have poor or missing rewards. With such \emph{support deficiency}, the offline learning fails to find optimal policies. We propose a novel approach that uses a hybrid of offline learning with online exploration. The online exploration is used to explore unsupported actions in the logged data whilst offline learning is used to exploit supported actions from the logged data avoiding unnecessary explorations. Our approach determines an optimal policy with theoretical guarantees using the minimal number of online explorations. We demonstrate our algorithms' effectiveness empirically on a diverse collection of datasets.
Multi-Perspective Content Delivery Networks Security Framework Using Optimized Unsupervised Anomaly Detection

Content delivery networks (CDNs) provide efficient content distribution over the Internet. CDNs improve the connectivity and efficiency of global communications, but their caching mechanisms may be breached by cyber-attackers. Among the security mechanisms, effective anomaly detection forms an important part of CDN security enhancement. In this work, we propose a multi-perspective unsupervised learning framework for anomaly detection in CDNs. In the proposed framework, a multi-perspective feature engineering approach, an optimized unsupervised anomaly detection model that utilizes an isolation forest and a Gaussian mixture model, and a multi-perspective validation method, are developed to detect abnormal behaviors in CDNs mainly from the client Internet Protocol (IP) and node perspectives, therefore to identify the denial of service (DoS) and cache pollution attack (CPA) patterns. Experimental results are presented based on the analytics of eight days of real-world CDN log data provided by a major CDN operator. Through experiments, the abnormal contents, compromised nodes, malicious IPs, as well as their corresponding attack types, are identified effectively by the proposed framework and validated by multiple cybersecurity experts. This shows the effectiveness of the proposed method when applied to real-world CDN data.
Learning and Generalizing Variable Impedance Manipulation Skills from Human Demonstrations

By learning a variable impedance control policy, robot assistants can intelligently adapt their manipulation compliance to ensure both safe interaction and proper task completion when operating in human-robot coexisting environments. In this paper, we propose a DMP-based framework that learns and generalizes variable impedance manipulation skills from human demonstrations. This framework improves robots′ adaptability to environment changes(i.e. the weight and shape changes of grasping object at the robot end-effector) and inherits the efficiency of demonstration-variance-based stiffness estimation methods. Besides, with our stiffness estimation method, we generate not only translational stiffness profiles but also rotational stiffness profiles that are ignored or incomplete in most learning variable impedance control papers. Real-world experiments on a 7 DoF redundant robot manipulator have been conducted to validate the effectiveness of our framework.
Optical Properties and Surface Enhanced Raman Scattering of L-Shaped Silver Nanorod Arrays

Optical reflection, transmission, and surface-enhanced Raman scattering (SERS) of L-shaped silver nanorod arrays with different lengths prepared by oblique angle deposition are studied and compared in detail to those properties of straight silver nanorod arrays. With the increase of the arm length of both the L-shaped and straight nanorods, the optical reflectance increases, but the transmittance decreases. The reflectance of L-shaped Ag nanorods is similar to that of straight nanorods with the same total length, but the transmittance is lower for the former than for the latter. Transfer matrix method for multilayer thin films based on anisotropic effective medium theory has been used to calculate the optical properties of both the L-shaped and straight Ag nanorod arrays, and the calculated results are qualitatively consistent with the experimental results. The SERS enhancement of the L-shaped and straight Ag nanorod arrays increases when the total arm length increases from 350 to 650 nm. The SERS behavio.
FOREIGN LANGUAGE ANXIETY EXPERIENCES OF FILIPINO STUDENTS ACROSS THE FOUR MACRO SKILLS

Throughout the years, scholars have determined that foreign language learning is associated with negative emotional reactions rooted from communication apprehension, test anxiety, and fear of negative evaluation; a phenomenon more widely known as Foreign Language Anxiety (FLA), which has effectively hindered language learning for many students. Moreover, it does not help that the abrupt and drastic pedagogical transformations brought about by the COVID-19 pandemic in itself has proven to be stressful and anxiety-provoking for the learners. In this context, the aim of this study was to determine the foreign language anxiety experienced by Filipino learners in the remote learning setup. This mixed method study gathered data from 83 Filipino college students about their FLA experience across the four macro skills: reading, writing, listening and speaking amidst remote learning. Results revealed the participants experienced the highest level of anxiety with speaking. However, it must be noted that the fear of making mistakes and fear of negative evaluation can be observed across all the four macro-skills. Participants also struggle with opportunities to improve across the four macro skills due to the intermittent internet connection, inadequate resources, and limited interaction with their teachers and peers.
Proﬁling the Gender Identity of Non-binary Authors Bachelor’s Thesis

Gender is one of the social traits most frequently predicted from texts in author proﬁling. All research in author proﬁling treated gender as a binary trait, only distinguishing male and female. Therefore, these studies measure sex rather than gender. But texts as source of data reﬂect an authors gender identity. And gender identities are not exclusively male and female. We rethink these approaches by adding transgender and non-binary authors to classical author proﬁling tasks. Therefore, we access data from Reddit and show how to label authors of Reddit with gender. We present a dataset of Reddit comments from which we removed a topic bias. By applying features that previously performed well on binary gender prediction to non-binary gender prediction as a multiclass-classiﬁcation task, we ﬁnd a common classiﬁcation model to achieve solid performance. We conclude with incentives to reﬁne dataset development and prediction setups for better performance in future works.
Title : Pedestrians Detection in Images for Autonomous Vehicles Supervisor :

With the rapid development of the world’s economy, the number of vehicles is constantly increasing. Due to the driver's subjective error, traffic accidents occur frequently, which seriously threatens the life and safety of pedestrians on the road. The emergence of autonomous vehicles will reduce traffic accidents caused by human factors. Pedestrian detection is the most important technology in the automatic driving systems because man's life is more precious than anything. Pedestrian detection method is a valuable and challenging topic in the field of computer vision because pedestrian with both rigid property and flexible property, whose appearance is easily affected by such factors as clothes, occlusion, scale, posture, and viewed angle. This master thesis processes a pedestrian detection method based on traditional method (HOG+SVM) and neural network method (faster-rcnn). After comparing the detection precision of these two methods, it is obviously to find the second one is better. This thesis mainly carries out the following research: 1.Introduce the theory of traditional objective detection method (HOG+SVM) and deep learning method (rcnn, fast-rcnn, faster-rcnn). 2.Due to the limitation of space, the fasterRCNN is selected as the detector algorithm. 3.Training these two detection models and comparing their precious. Verifying the superiority of neural network detector.
RASGRF2 gene fusions identified in a variety of melanocytic lesions with distinct morphological features

The WHO classification identifies nine classes of melanocytic proliferations according to location, UV exposure, histological, and genetic features. Only a minority of lesions remain unclassified. We describe five cases that harbored either an ERBIN‐RASGRF2 or an ATP2B4‐RASGRF2 in‐frame fusion transcript. These lesions were collected from different studies, unified only by the lack of identifiable known mutations, with a highly variable phenotype. One case was a large abdominal congenital nevus, three were slowly growing pigmented nodules, and the last was an ulcerated nodule arising on the site of a preexisting small nevus, known since childhood. The latter was diagnosed as a 4 mm thick melanoma with loss of BAP1 expression. The four other cases were compound, melanocytic proliferations with an unusual deep pattern of small dense nests of bland melanocytes encased in a fibrous background. The RASGRF2 fusion was confirmed by a break‐apart FISH technique. Array CGH performed in three cases found non‐recurrent secondary copy number alterations. Follow‐up was uneventful. In silico analysis identified a single RASGRF2 fusion in the TCGA pan‐cancer database, whereas RASGRF2 variants were stochastically distributed in all cancer subtypes.
Depressive symptoms and perception of risk during the first wave of the COVID‐19 pandemic: A web‐based cross‐country comparative survey

Abstract Evidence is accumulating of the negative impact of the COVID‐19 pandemic and related public health measures on mental health. In this emergent field, there has been little research into the role of risk perception on depressive symptoms and the contribution of health‐care resources to model risk perception and mental health. The aim of this paper is to describe the relationship between individual‐level perception of risk and depression, controlling for a set of confounders and for country‐level heterogeneity. A cross‐sectional and observational online survey was conducted using a non‐probability snowball sampling technique. We use data on 11,340 respondents, living in six European countries (Italy, Sweden, United Kingdom, France, Poland, Czech Republic) who completed survey questionnaires during the first months of the pandemic. We used a fixed‐effect approach, which included individual and macro‐level variables. The findings suggest that a high proportion of people suffering from depression and heightened risk perception is positively associated with reporting depressive symptoms, even if this relationship varies significantly between countries. Moreover, the association is moderated by contextual factors including health‐care expenditure as a percentage of Gross Domestic Product, hospital beds for acute care, and number of medical specialists per head of population. Investment in health care offers a concrete means of protecting the mental health of a population living under pandemic restrictions.
Synthesis and Characterisation of In 2 O 3 Na-noparticles from Astragalus gummifer

Exploitation of green chemistry approach for the synthesis of Indium Oxide nanoparticles using green synthesis has received a great attention in the field of nanotechnology. To demonstrate a biogenic method that involves the Katira gum (Astragalus gummifer) leading to the formation of different morphological In2O3 using the precursor Indium (III) Acetylacetonate and TG-DTA is characterised for calcination temperature and it is found to be above 500℃. Different techniques such as XRD, UV-VIS, SEM and EDAX have been used for the characterisation of In2O3 nanoparticles. The average crystallite size of Indiumoxide nanoparticles is determined as 19 nm by using Scherrer’s Equation and PSA and studying optical properties.
Synthesis and Exchange for Li+ of Spinel Type Material LiMn0.75Ti0.5O3

LiMn0.75Ti0. 5O3 was prepared by a solid state reaction crystallization method. The acid treatments of LiMn0.75Ti0. 5O3 caused Li2+ extractions of more than 75%, while the dissolutions of Mn4+ and Ti4+ were less than 13%. The experimental results have proved that the acid-treated sample has a capacity of exchange 4.1mmol·g-1 for Li+ in the solution.
Seroprevalence estimate and risk factors for Coxiella burnetii infections among humans in a highly urbanised Brazilian state.

BACKGROUND Q fever is among the top 13 global priority zoonoses, however, it is still neglected and under-reported in most of the world, including Brazil. Thus, we evaluated the seroprevalence of and the risk factors for Coxiella burnetii infections in humans from Minas Gerais, a highly urbanised Brazilian state. METHODS Coxiella burnetii was searched for patient samples (n=437), which were suspected of then later confirmed as negative for dengue fever, by the indirect immunofluorescence technique and real-time PCR. Risk factors for infections and spatial clusters for both C. burnetii-seropositive individuals and livestock concentration were evaluated. RESULTS We found that 21 samples (4.8%; 95% CI 3.0 to 7.2%) were reactive for at least one class of anti-C. burnetii antibodies (titer of ≥64), with rural residence (p=0.036) being a risk factor. Also, two spatial clusters of seropositivity were found within a significant area by Scan, and a probable relationship between the Scan result and the livestock concentration by area was found. CONCLUSIONS Seropositive individuals were associated with rural residence, with a likely relationship with the livestock concentration. Thus, this study establishes baseline figures for C. burnetii seroprevalence in humans in a state of Brazil, allowing the monitoring of trends and setting of control targets, as well as more representative longitudinal and risk analysis studies.
Establishing an invertebrate Galleria mellonella greater wax moth larval model of Neisseria gonorrhoeae infection

ABSTRACT Neisseria gonorrhoeae (gonococcus) causes the human sexually transmitted disease gonorrhea. Studying gonococcal pathogenesis and developing new vaccines and therapies to combat the increasing prevalence of multi-antibiotic resistant bacteria has made use of many ex vivo models based on human cells and tissues, and in vivo vertebrate models, for example, rodent, pig and human. The focus of the current study was to examine the utility of the invertebrate greater wax moth Galleria mellonella as an in vivo model of gonococcal infection. We observed that a threshold of ~106 – 107 gonococci/larva was required to kill >50% of larvae (P < 0.05), and increased toxicity correlated with reduced health index scores and pronounced histopathological changes such as increases in the total lesion grade, melanized nodules, hemocyte reaction, and multifocal adipose body degeneration. Larval death was independent of the expression of pilus or Opa protein or LOS sialylation within a single gonococcal species studied, but the model could demonstrate relative toxicity of different isolates. N. meningitidis, N. lacatamica and gonococci all killed larvae equally, but were significantly less toxic (P > 0.05) than Pseudomonas aeruginosa. Larvae primed with nontoxic doses of gonococci were more susceptible to subsequent challenge with homologous and heterologous bacteria, and larval survival was significantly reduced (P < 0.05) in infected larvae after depletion of their hemocytes with clodronate-liposomes. The model was used to test the anti-gonococcal properties of antibiotics and novel antimicrobials. Ceftriaxone (P < 0.05) protected larvae from infection with different gonococcal isolates, but not azithromycin or monocaprin or ligand-coated silver nanoclusters (P > 0.05).
pH-sensitive polymer-based carriers as a useful approach for oral delivery of therapeutic protein: A review.

There are many proteins and enzymes in the human body, and their dysfunction can lead to disease. The use of proteins as a drug is common in various diseases such as diabetes. Proteins are hydrophilic molecules whose spatial structure is critical to their correct function. There are different ways to the administration of proteins. Protein structures are degraded by gastric acid and enzymes in the gastrointestinal tract and have a slight ability to permeation from the gastrointestinal epithelium due to their large hydrophilic nature. Therefore, their oral use has limitations. Since the oral use of drugs is one of the best and easiest routes for patients, many studies have been done to increase the stability, penetration and ultimately increase the bioavailability of proteins through oral administration. One of the studied strategies for oral delivery of protein is the use of pH-sensitive polymer-based carriers. These carriers use different pH-sensitive polymers such as eudragit®, chitosan, dextran, and alginate. The use of pH-sensitive polymer-based carriers by protecting the protein from stomach acid (low pH) and degrading enzymes, increasing permeability, and maintaining the spatial structure of the protein leads to increased bioavailability. In this review, we focus on the various polymers used to prepare pH-sensitive polymer-based carriers for the oral delivery of proteins.
How direct and indirect non-native interactions can promote plant invasions, lead to invasional meltdown and inform management decisions.

In 1999, Daniel Simberloff and Betsy Von Holle introduced the term ‘invasional meltdown’. The term and the concept have been embraced and critiqued but have taken a firm hold within the invasion biology cannon. The original formulation of the concept argued two key points: first, biologists rarely study how nonnatives interact with one another. Second, nearly all the conceptual models about the success and impact of invasive species are predicated on the importance of competitive interactions and an implicit assumption that nonnatives should interfere with establishment, spread and impact of other nonnatives. In response, Simberloff and Von Holle called for more research on invader interactions and proposed an alternative consequence of nonnative species interactions – invasional meltdown – where facilitative interactions among nonnatives could increase the invasion rate or ecological impacts in invaded systems. This chapter outlines the primary pathways in which direct and indirect interactions among nonnatives could lead to invasional meltdown. It provides examples of how different types of interactions among nonnatives could lead to net positive effects on the invasion success of nonnative plants or the impact of nonnative plants on invaded ecosystems. Direct effects are by far the most commonly explored form of nonnativenonnative interaction, primarily focusing on plant mutualisms with pollinators, seed dispersers or soil microbial mutualists. There are, however, also examples of nonnative plants that benefit from commensal and even herbivorous interactions with other nonnatives. Indirect interactions among nonnatives are very infrequently studied. Although examples are scarce, nonnatives may indirectly benefit other nonnative plants through trophic cascades, apparent competition and indirect mutualisms. It remains unclear whether indirect effects are important pathways to invasional meltdown. More work is needed on studying ecosystems that are invaded by multiple nonnative species and we need to consider the full range of interactions among nonnatives that could either stymie or promote their spread, population growth and impact. Only then can we address how common facilitative interactions are relative to competitive interactions among nonnatives or provide robust suggestions on how to manage
Conserved cholesterol-related activities of Dispatched 1 drive Sonic hedgehog shedding from the cell membrane

ABSTRACT The Sonic hedgehog (Shh) pathway controls embryonic development and tissue homeostasis after birth. Long-standing questions about this pathway include how the dual-lipidated, firmly plasma membrane-associated Shh ligand is released from producing cells to signal to distant target cells and how the resistance–nodulation–division transporter Dispatched 1 (Disp, also known as Disp1) regulates this process. Here, we show that inactivation of Disp in Shh-expressing human cells impairs proteolytic Shh release from its lipidated terminal peptides, a process called ectodomain shedding. We also show that cholesterol export from Disp-deficient cells is reduced, that these cells contain increased cholesterol amounts in the plasma membrane, and that Shh shedding from Disp-deficient cells is restored by pharmacological membrane cholesterol extraction and by overexpression of transgenic Disp or the structurally related protein Patched 1 (Ptc, also known as Ptch1; a putative cholesterol transporter). These data suggest that Disp can regulate Shh function via controlled cell surface shedding and that membrane cholesterol-related molecular mechanisms shared by Disp and Ptc exercise such sheddase control.