Miracle-dz/UniFAR-FTUs huggingface dataset:
A naming convention for atmospheric organic aerosol

Abstract. While the field of atmospheric organic aerosol scientific research has experienced thorough and insightful progress over the last half century, this progress has been accompanied by the evolution of a communicative and detailed yet, at times, complex and inconsistent language. The menagerie of detailed classification that now exists to describe organic compounds in our atmosphere reflects the wealth of observational techniques now at our disposal as well as the rich information provided by state-of-the-science instrumentation. However, the nomenclature in place to communicate these scientific gains is growing disjointed to the point that effective communication within the scientific community and to the public may be sacrificed. We propose standardizing a naming convention for organic aerosol classification that is relevant to laboratory studies, ambient observations, atmospheric models, and various stakeholders for air-quality problems. Because a critical aspect of this effort is to directly translate the essence of complex physico-chemical phenomena to a much broader, policy-oriented audience, we recommend a framework that maximizes comprehension among scientists and non-scientists alike. For example, to classify volatility, it relies on straightforward alphabetic terms (e.g., semivolatile, SV; intermediate volatility, IV; etc.) rather than possibly ambiguous numeric indices. This framework classifies organic material as primary or secondary pollutants and distinguishes among fundamental features important for science and policy questions including emission source, chemical phase, and volatility. Also useful is the addition of an alphabetic suffix identifying the volatility of the organic material or its precursor for when emission occurred. With this framework, we hope to introduce into the community a consistent connection between common notation for the general public and detailed nomenclature for highly specialized discussion. In so doing, we try to maintain consistency with historical, familiar naming schemes, unify much of the scattered nomenclature presented in recent literature, reduce the barrier of comprehension to outside audiences, and construct a scaffold into which insights from future scientific discoveries can be incorporated.
Improved hydrophone calibration by combining acoustic holography with the radiation force balance measurements

Ultrasound sources are frequently characterized by the radiation force (RF) balance method that is based on the relation between the total acoustic power and RF on absorbing or reflecting targets. This relation is usually taken from the plane-wave approximation or with a geometrical correction for focused sources. However, real sources emit inhomogeneous acoustic beams. Acoustic holography is a method of recording the true field by measuring both pressure magnitude and phase over a 2D surface (a hologram). The hologram makes it possible to accurately calculate the radiation stress tensor on the surface of the absorbing target. Such measurements allow the relation of hydrophone sensitivity with measured RF based on the known exact expression for RF as a function of the 2D pattern of acoustic pressure and particle velocity. This suggests an improved approach for single-frequency hydrophone calibration that benefits from the inherent accuracy of mass balances as well as the fact that pressure approximately scales with one half of the accuracy of the RF measurement. In the current study this approach was used to calibrate a hydrophone by characterizing a 1-MHz flat piezoceramic source in water using acoustic holography and a RF balance. [Work supported by RFBR and NIH EB007643. ]
Localization of the inferior alveolar canal using ultralow dose CT with iterative reconstruction techniques

Objectives: To compare subjective and objective localization of the inferior alveolar canal (IAC) on multidetector CT (MDCT) images obtained by ultralow doses in combination with the reconstruction techniques of filtered backprojection (FBP), adaptive statistical iterative reconstruction (ASIR), or model-based iterative reconstruction (MBIR) as compared to standard dose MDCT and FBP. Methods: Three cadavers were imaged with a reference standard dose MDCT examination (volume CT dose index: 29.4 mGy) reconstructed with FBP and 5 low dose protocols (LD1-5) (volumeCT dose index: 4.19, 2.64, 0.99, 0.53, 0.29 mGy) reconstructed with FBP, ASIR 50, ASIR 100, and MBIR. Linear measurements from the crest of the ridge to the roof of the IAC were recorded. The results from the test protocols were compared with those from the reference using Bland–Altman plots. Results: Only three test protocols allowed the identification of the position of the IAC on all the sample sites: LD1/FBP and LD1/ASIR 100 and LD2/FBP. All three protocols allowed identification of the IAC with comparable results to the reference dose protocol; the 95% confidence interval limits for the measurement differences were ± 0.41 mm, but the differences were not statistically significant. The calculated effective dose for the LD2 protocol, for a scan length of 5 cm, was 27.7 µSv. Conclusions: Using FBP, comparable IAC measurements were achieved with 91% reduction in dose compared with a standard exposure protocol. The use of ASIR and MBIR did not improve identification of the IAC in MDCT low dose images.
Determinantes da estrutura de capital das empresas portuguesas cotadas

Este artigo relata os resultados empiricos de um inquerito sobre a estrutura de capital das empresas portuguesas, dirigido aos diretores financeiros de empresas portuguesas com titulos cotados em Bolsa. O inquerito foi enviado a 48 diretores financeiros de Portugal, no sentido de analisar os seus pontos de vista sobre as decisoes referentes a estrutura de capital das respectivas empresas, a fim de comparar os fatores praticos de influencia da estrutura de capital e as premissas teoricas sobre esta tematica. Os resultados obtidos indiciam que a natureza do negocio e o ciclo de vida das empresas sao fatores importantes aquando da consideracao da estrutura de capital das empresas. Os resultados apontam para a existencia de um racio objetivo de endividamento. De um modo geral, encontramos base para as hipoteses «trade-oft» e «pecking-order». Palavras-chave: Estrutura de Capital; Fatores Determinantes; Questionario.
EFFECT OF DIETARY PREBIOTICS , PROBIOTICS AND SYNBIOTICS AS FEED ADDITIVES ON BLOOD PROFILE AND BROILER PERFORMANCE

This study was undertaken to investigate the effect of incorporating prebiotics, probiotics and synbiotics as a growth promoter in broiler feed on growth performance and blood profile. 240 day-old commercial broiler chicks (Cobb-400) were divided equally into four groups of 60 birds each, and were assigned to four isocaloric isonutritive diets, viz., Diet-I basal control diet without additives, Diet-II prebiotics (500g/tonne), Diet-III probiotics (100g/tonne) and Diet-IV synbiotics (250g/tone prebiotics+ 50g/tone probiotics). The experiment was conducted in three replicates each of 20 birds. Feed and water were offered ad libitum till the termination of the trial at 42 days. The starter and finisher diets were given to birds from 1 to 28 and 29 to 42 days of age, respectively. Growth performance parameters and blood parameters were measured. Broilers fed Diet II had significantly (P<0.05) increased feed intake. Body weight, body weight gain and efficiency of feed utilization of birds were superior with Diet-IV. Values for different haemato-biochemical parameters like hemoglobin (Hb), packed cell volume (PCV), total erythrocyte count (TEC), total leucocyte count (TLC), alanine transaminase (ALT) and aspartate amino transferase (AST) were found non-significant among different experimental groups, but the values of all were within normal range. It was thus concluded that use of synbiotics (250g/tonne prebiotics + 50g/tonne probiotics) and prebiotics (500g/tonne), improves the overall performance without altering the normal blood values of broilers.
Spatially resolved investigation of competing nanocluster emission in quantum-disks-in-nanowires structure characterized by nanoscale cathodoluminescence

Abstract. We report on the study and characterization of nanoclusters-related recombination centers within quantum-disks-in-nanowires heterostructure by utilizing microphotoluminescence (μ-PL) and cathodoluminescence scanning transmission electron microscopy (CL-STEM). μ-PL measurement shows that the nanoclusters-related recombination center exhibits different temperature-dependent characteristics compared with the surrounding InGaN quantum-disks-related recombination center. CL-STEM measurements reveal that these recombination centers mainly arise from irregularities within the quantum disks, with a strong, spatially localized emission when measured at low temperature. The spectra obtained from both CL-STEM and μ-PL correlate well with each other. Our work sheds light on the optical and structural properties of simultaneously coexisting recombination centers within nanowires heterostructures.
Are Bullying Perpetration and Victimization Associated with Adolescent Deliberate Self-Harm? A Meta-Analysis

This study sought to appraise internationally published literature investigating bullying in its association with deliberate self-harm (DSH). A systematic review and series of meta-analyses using random effects models were conducted. A total of 68 effect sizes, analyzing data from 156,284 adolescents aged 11–19 years were examined. Results showed significant associations between both traditional bullying perpetration (OR 1.81, 95% CI [1.33, 2.47], p < .0001) and victimization (OR 2.34, 95% CI [1.89, 2.89], p < .0001) and DSH. Cyber-bullying victimization (OR 3.55, 95% CI [2.71, 4.65], p < .0001) and the co-occurrence of traditional and cyber-bullying victimization (OR 3.39, 95% CI [1.56, 7.37], p = .002) were also associated with DSH. Moderator analyses showed variation in results based on methodological- and sample-level variables. Findings suggested that exposure to bullying, either as perpetrators or victims, poses risks for DSH.
A Characterization of the Diffuse Galactic Emissions in the Anticenter of the Galaxy

Using the Archeops and WMAP data, we perform a study of the anticenter Galactic diffuse emissions—thermal dust, synchrotron, free-free, and anomalous emissions—at degree scales. The high-frequency data are used to infer the thermal dust electromagnetic spectrum and spatial distribution allowing us to precisely subtract this component at lower frequencies. After subtraction of the thermal dust component, a mixture of standard synchrotron and free-free emissions does not account for the residuals at these low frequencies. Including the all-sky 408 MHz Haslam data we find evidence for anomalous emission with a spectral index of −2.5 in units. However, we are not able to provide coclusion regarding the nature of this anomalous emission in this region. For this purpose, data between 408 MHz and 20 GHz covering the same sky region are needed.
Detecting Homoglyph Attacks with a Siamese Neural Network

A homoglyph (name spoofing) attack is a common technique used by adversaries to obfuscate file and domain names. This technique creates process or domain names that are visually similar to legitimate and recognized names. For instance, an attacker may create malware with the name svch0st.exe so that in a visual inspection of running processes or a directory listing, the process or file name might be mistaken as the Windows system process svchost.exe. There has been limited published research on detecting homoglyph attacks. Current approaches rely on string comparison algorithms (such as Levenshtein distance) that result in computationally heavy solutions with a high number of false positives. In addition, there is a deficiency in the number of publicly available datasets for reproducible research, with most datasets focused on phishing attacks, in which homoglyphs are not always used. This paper presents a fundamentally different solution to this problem using a Siamese convolutional neural network (CNN). Rather than leveraging similarity based on character swaps and deletions, this technique uses a learned metric on strings rendered as images: a CNN learns features that are optimized to detect visual similarity of the rendered strings. The trained model is used to convert thousands of potentially targeted process or domain names to feature vectors. These feature vectors are indexed using randomized KD-Trees to make similarity searches extremely fast with minimal computational processing. This technique shows a considerable 13% to 45% improvement over baseline techniques in terms of area under the receiver operating characteristic curve (ROC AUC). In addition, we provide both code and data to further future research.
WISE/NEOWISE OBSERVATIONS OF ACTIVE BODIES IN THE MAIN BELT

We report results based on mid-infrared photometry of five active main belt objects (AMBOs) detected by the Wide-field Infrared Survey Explorer (WISE) spacecraft. Four of these bodies, P/2010 R2 (La Sagra), 133P/Elst-Pizarro, (596) Scheila, and 176P/LINEAR, showed no signs of activity at the time of the observations, allowing the WISE detections to place firm constraints on their diameters and albedos. Geometric albedos were in the range of a few percent, and on the order of other measured comet nuclei. P/2010 A2 was observed on 2010 April 2–3, three months after its peak activity. Photometry of the coma at 12 and 22 μm combined with ground-based visible-wavelength measurements provides constraints on the dust particle mass distribution (PMD), dlog n/dlog m, yielding power-law slope values of α = −0.5 ± 0.1. This PMD is considerably more shallow than that found for other comets, in particular inbound particle fluence during the Stardust encounter of comet 81P/Wild 2. It is similar to the PMD seen for 9P/Tempel 1 in the immediate aftermath of the Deep Impact experiment. Upper limits for CO2 and CO production are also provided for each AMBO and compared with revised production numbers for WISE observations of 103P/Hartley 2.
Meta-Gradient Reinforcement Learning

The goal of reinforcement learning algorithms is to estimate and/or optimise the value function. However, unlike supervised learning, no teacher or oracle is available to provide the true value function. Instead, the majority of reinforcement learning algorithms estimate and/or optimise a proxy for the value function. This proxy is typically based on a sampled and bootstrapped approximation to the true value function, known as a return. The particular choice of return is one of the chief components determining the nature of the algorithm: the rate at which future rewards are discounted; when and how values should be bootstrapped; or even the nature of the rewards themselves. It is well-known that these decisions are crucial to the overall success of RL algorithms. We discuss a gradient-based meta-learning algorithm that is able to adapt the nature of the return, online, whilst interacting and learning from the environment. When applied to 57 games on the Atari 2600 environment over 200 million frames, our algorithm achieved a new state-of-the-art performance.
SOSELETO: A Unified Approach to Transfer Learning and Training with Noisy Labels

We present SOSELETO (SOurce SELEction for Target Optimization), a new method for exploiting a source dataset to solve a classification problem on a target dataset. SOSELETO is based on the following simple intuition: some source examples are more informative than others for the target problem. To capture this intuition, source samples are each given weights; these weights are solved for jointly with the source and target classification problems via a bilevel optimization scheme. The target therefore gets to choose the source samples which are most informative for its own classification task. Furthermore, the bilevel nature of the optimization acts as a kind of regularization on the target, mitigating overfitting. SOSELETO may be applied to both classic transfer learning, as well as the problem of training on datasets with noisy labels; we show state of the art results on both of these problems.
Balancing Translation Quality and Sentiment Preservation (Non-archival Extended Abstract)

Social media platforms such as Twitter and Facebook are hugely popular websites through which Internet users can communicate and spread information worldwide. On Twitter, messages (tweets) are generated by users from all over the world in many different languages. Tweets about different events almost always encode some degree of sentiment. As is often the case in the field of language processing, sentiment analysis tools exist primarily in English, so if we want to understand the sentiment of the original tweets, we are forced to translate them from the source language into English and pushing the English translations through a sentiment analysis tool. However, Lohar et al. (2017) demonstrated that using freely available translation tools often caused the sentiment encoded in the original tweet to be altered. As a consequence, they built a series of sentiment-specific translation engines and pushed tweets containing either positive, neutral or negative sentiment through the appropriate engine to improve sentiment preservation in the target language. For certain tasks, maintaining sentiment polarity in the target language during the translation process is arguably more important than the absolute translation quality obtained. In the work of Lohar et al. (2017), a small drop off in translation quality per se was deemed tolerable. In this work, we focus on maintaining the level of sentiment preservation while trying to improve translation quality still further. We propose a nearest sentiment classcombination method to extend the existing sentiment-specific translation systems by adding training data from the nearest-sentiment class. Our experimental results on German-to-English reveal that our approach is capable of achieving a proper balance between translation quality and sentiment preservation.
Double-observer evaluation of pronghorn aerial line-transect surveys

Abstract Context. Distance sampling is used to estimate abundance for several taxa, including pronghorn (Antilocapra americana). Comparisons between population estimates derived from quadrat sampling and distance sampling suggest that distance sampling underestimates pronghorn density, likely owing to violations of the critical assumption of distance sampling that all pronghorn within the innermost distance band (A band; nearest to the aircraft) are detected. Aims. We sought to rigorously test the assumption that all pronghorn clusters are detected within the innermost distance band by applying a double-observer approach to an established pronghorn aerial-survey protocol. Additionally, we evaluated potential effects of cluster size, landscape composition and seat position (front seat versus rear) on the probability of detection. Methods. We conducted aerial line-transect distance-sampling surveys using independent, paired observers and modelled the probability of detection with mark–recapture distance-sampling (MRDS) analysis techniques that explicitly estimate the probability of detection for pronghorn clusters in the innermost distance band. We compared density estimates produced by the MRDS analysis with those produced by multiple-covariate distance sampling (MCDS), a method that assumes complete detection for clusters on the transect line. Key results. We identified violations of the assumption that all clusters within the innermost distance band were detected, which would contribute to proportional biases in density estimates for analysis techniques that assume complete detection. The frequency of missed clusters was modest from the front-seat position, with 45 of the 47 (96%) clusters in the A band detected. In contrast, the frequency of missed clusters was more substantial for the rear position, from which 37 of 47 (79%) clusters in the A band were detected. Further, our analysis showed that cluster size and landscape composition were important factors for pronghorn sightability. Conclusions. When implementing standard survey methodologies, pronghorn aerial-line transect surveys underestimated population densities. A double-observer survey configuration allowed us to quantify and correct for the bias caused by the failure of observers to detect all pronghorn clusters within the innermost distance band. Implications. Population monitoring programs should incorporate double-observer validation trials to quantify the extent of bias owing to undetected clusters within the innermost distance band realised under typical survey conditions. Wildlife managers can improve the precision of pronghorn aerial line-transect surveys by incorporating cluster size and measures of landscape composition and complexity into detection models without incurring additional survey costs.
Knowledge of Risk Factors and Screening for Diabetes Mellitus Among Youths in Southwestern Nigeria

With the adoption of western lifestyle, youths are at risk of Diabetes mellitus (DM), a disease traditionally known to be common among older people. This study assessed prevalence and knowledge of risk factors for DM among youths in Southwestern Nigeria. Descriptive cross sectional study among 1610 students of tertiary institutions selected by serial recruitments. Research instrument consist of self-administered semi structured and pre-tested questionnaires. Data was analyzed using the SPSS software version 17.0. Mean age of respondents was 22.9 (+2.6) years. Four hundred and sixty (28.6%) were aware of DM. About 321 (19.9%) had good while 1289 (80.1%) had poor knowledge scores of risk factors for DM. The blood sugar level of > 6.1mmol/L (hyperglycemia) showed that 48 (3.0%) were diabetic out of which 32 (66.7%) were females. A total of 21 (1.3%) had transient hypoglycemia out of which 3 (61.9%) were females. Conclusively, DM was not uncommon among Nigerian youths. The poor knowledge scores of risk factors underscores the need for sustained health education targeted at risk reduction and prevention of Non-Communicable Diseases (NCD) most especially DM.
Modified IL-10-expressing dendritic cells ameliorate TNBS-induced Crohn's disease in mice

This article investigated the therapeutic effects of immature Dendritic Cells (imDC) expressing modified interleukin-10 (IL-10) in a mouse model of Crohn's disease and the possible underlying mechanisms. Forty mice were randomly divided into control group, imDC- treatment group (imDC group), LacZ gene-modified imDC treatment group (LacZ-imDC group) and IL-10 gene-modified imDC treatment group (IL-10-imDC group). The DAI scores of the imDC group, LacZ-imDC group, and IL-10-imDC group were significantly lower than that of the control group (P<0.05). Furthermore, the DAI score of the IL-10-imDC group was markedly reduced compared to those of the imDC and LacZ-imDC groups (P<0.05). Similarly, the TDI scores of the imDC group, LacZ-imDC group, and IL-10-imDC group were significantly lower than that of the control group (P<0.05). In particular, the TDI score of the IL-10- imDC group was significantly lower than those of the imDC and LacZ-imDC groups (P<0.05). The percentages of splenic Treg cells in the imDC, LacZ-imDC, and IL-10-imDC groups were significantly higher than that of the control group (P<0.05). The percentage of Treg cells in the IL-10-imDC group was also markedly higher than those in the imDC and LacZ-imDC groups (P<0.05). In conclusion, when successfully transfected into imDC, IL-10 can inhibits the process of DC maturation. Infusion of this IL-10-imDC can significantly alleviate the progress of Crohn's disease compared with imDC without IL-10 modification, and the mechanism of action may be associated with the upregulation of Treg cells.