Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating the reliability of field identification and morphometric classifications for carnivore scats confirmed with genetic analysis

Scat surveys are commonly used to monitor carnivore populations. Scats of sympatric carnivores can be difficult to differentiate and field-based identification can be misleading. We evaluated the success of field-based species identification for scats of 2 sympatric carnivores—coyotes (Canis latrans) and kit foxes (Vulpes macrotis). We conducted scat surveys in the Great Basin desert of Utah, USA, during the winter and summer of 2013, and we detected 1,680 carnivore scats. We classified scats based on field identification, recorded morphometric measurements, and collected fecal DNA samples for molecular species identification. We subsequently evaluated the classification success of field identification and the predictive power of 2 nonparametric classification techniques—k-nearest neighbors and classification trees—based on scat measurements. Overall, 12.2% of scats were misclassified by field identification, but misclassifications were not equitable between species. Only 7.1% of the scats identified as coyote with field identification were misclassified, compared with 22.9% of scats identified as kit fox. Results from both k-nearest neighbor and classification-tree analyses suggest that morphometric measurements provided an objective alternative to field identification that improved classification of rarer species. Overall misclassification rates for k-nearest neighbor and classification-tree analyses were 11.7% and 7.5%, respectively. Using classification trees, misclassification was reduced for kit foxes (8.5%) and remained similar for coyotes (7.2%), relative to field identification. Although molecular techniques provide unambiguous species identification, classification approaches may offer a cost-effective alternative. We recommend that monitoring programs employing scat surveys utilize molecular species identification to develop training data sets and evaluate the accuracy of field-based and statistical classification approaches. © 2015 The Wildlife Society.
Kateryna Lytvyniuk Predicting Information Diffusion on Social Media

Social media has become a part of the everyday life of modern society. A lot of information is created and shared with the world continuously. Predicting information has been studied in the past by many researchers since it has its applications in various domains such as viral marketing, news propagation etc. Some information spreads faster compared to others depending on what interests people. In this thesis, by using supervised machine learning algorithms, we studied information diffusion in a social network and predicted content popularity. Three datasets from Twitter are collected and analysed for building and testing various models based on different machine learning algorithms. We defined tweet popularity as number of retweets any original message received and stated our research problems as binary and multiclass prediction tasks. We investigated how initial retweeting behaviour of a message affects the predictive power of a model. We also analysed if a recent one-hour retweeting behaviour can help to predict a tweet popularity of the following hour. Besides that, main focus is made on finding features important for the prediction. For binary prediction, the models showed performance of AUC up to 95% and F1 up to 87%. For multiclass prediction, the models were able to predict up to 60% of overall accuracy and 67% of F1, with more accurate performance of classes with messages with very low and high retweet counts comparing to others. We created our models using one dataset and tested our approach on the other two datasets, which showed that the models are robust enough to deal with multiple topics.
Identification of the Active Ingredients in Methanolic Leaf Extract of Aspilia africana (Pers.) C.D. Adams and their Effects on Ibuprofen Induced Ulcer Model in Wistar Rats

Peptic ulcer is one of the most dreadful diseases in the world today. However, the present study was investigated to identify the active ingredients in the methanolic leaf extract of Aspilia africana and their possible effects on Ibuprofen induced ulcer model in Wistar rats using standard analytical methods. The GC-MS spectral analysis revealed thirty three (33) active ingredients with 9,12,15Octadecatrienoic acid, methyl-ester(z,z,z)-, stigmasterol, hexadecanoic acid, methylester(z)-, Methyl linolelaidate, n-Hexadecanoic acid, squalene, phytol and vitamin E possessing important pharmacological and cytoprotective functions. The oral acute (LD50) toxicity study divulged that the extract did not cause mortality to any of the experimental animals even at the highest dose of 5000mg/kg. Other studies disclosed that the induction of ulcerogenesis by ibuprofen led to alterations in the mucosal membrane and this was evidenced by severe distortions in gastric contents, serum concentrations of blood glucose, antioxidant enzymes, lipid peroxidation marker, hepatocellular enzymes, renal function and haematological indexes. Pretreatment with the natural antidote (A. africana leaf extract) remediated this imbalance significantly more than a standard antiulcer drug (omeprazole). From these observations, we conclude that the methanolic leaf extract of A. africana offers more promising gastroprotection than omeprazole and due to low toxicity; it should be incorporated in traditional medicine for the management and treatment of peptic ulcer disease.
Systematic revision and reappraisal of the Kakaducarididae Bruce (Crustacea : Decapoda : Caridea) with the description of three new species of Leptopalaemon Bruce & Short

Abstract. The freshwater shrimp family Kakaducarididae Bruce, 1993 is revised and its familial status reappraised using morphological characters and the results of a complementary molecular study (Page et al. 2008). Based on combined morphological–molecular data, the Kakaducarididae is synonymised with the Palaemonidae Rafinesque, 1815 and the monotypic genus Kakaducaris Bruce, 1993 is synonymised with Leptopalaemon Bruce & Short, 1993. The Texan cave shrimp, Calathaemon holthuisi (Strenth, 1976), provisionally included in the Kakaducarididae by Bruce (1993), is re-assigned back to the Palaemonidae. Leptopalaemon is re-diagnosed and three new species, L. gibbosus, sp. nov., L. gudjangah, sp. nov. and L. magelensis, sp. nov., are described from the north-western edge of the Arnhem Land plateau/escarpment complex, Northern Territory, Australia. The two previously described species, L. gagadjui Bruce & Short, 1993 and L. glabrus (Bruce, 1993), comb. nov. are re-diagnosed. A key to the five presently recognised Leptopalaemon species is provided.
A Word-Complexity Lexicon and A Neural Readability Ranking Model for Lexical Simplification

Current lexical simplification approaches rely heavily on heuristics and corpus level features that do not always align with human judgment. We create a human-rated word-complexity lexicon of 15,000 English words and propose a novel neural readability ranking model with a Gaussian-based feature vectorization layer that utilizes these human ratings to measure the complexity of any given word or phrase. Our model performs better than the state-of-the-art systems for different lexical simplification tasks and evaluation datasets. Additionally, we also produce SimplePPDB++, a lexical resource of over 10 million simplifying paraphrase rules, by applying our model to the Paraphrase Database (PPDB).
Effects of Maternal Growth on Fecundity and Egg Quality of Wild and Captive Atka Mackerel

Abstract Trade-offs in energy allocation between growth and reproduction can result in variations in reproductive potential in fish with differing growth patterns. Spawning biomass is often used as a proxy for reproductive potential on the assumption that fecundity is directly proportional to body weight. We examined variations in the reproductive potential of Atka mackerel Pleurogrammus monopterygius by studying the effect of differential growth and condition patterns on fecundity, atresia, and egg energy. Fecundity and egg energy were determined for fish from two geographic areas, Seguam Pass and Amchitka Island, Alaska, and compared with those of fish held in captivity. These Atka mackerel showed distinct differences in growth and condition, with weight at length and length at age being the highest among captive fish, intermediate among fish from Seguam Pass, and lowest among fish from Amchitka Island. Realized fecundity showed that on average captive fish spawned seven batches, fish from Seguam Pass six batches, and fish from Amchitka Island five batches. For wild fish, potential and realized fecundity at length or age was significantly higher at Seguam Pass than at Amchitka Island, whereas the fecundity-at-weight relationship did not differ by area, suggesting that weight is a better predictor of fecundity than length or age. Atresia and batch fecundity by length or weight did not differ by area, suggesting that the variation in fecundity is better explained by the variation in batch number than by batch size. Oocyte dry weight was higher for captive fish than for wild fish, whereas batch order did not significantly affect oocyte dry weight. Increased potential fecundity, realized fecundity, and oocyte quality in Atka mackerel females were strongly related to body size, indicating that growth differences and maternal feeding success impact the fecundity and oocyte quality of Atka mackerel. Therefore, changes in growth and condition patterns need to be taken into account to accurately estimate the reproductive potential of this species.
Formulation and in vitro evaluation of mucoadhesive controlled release matrix tablets of flurbiprofen using response surface methodology

The objective of the current study was to formulate mucoadhesive controlled release matrix tablets of flurbiprofen and to optimize its drug release profile and bioadhesion using response surface methodology. Tablets were prepared via a direct compression technique and evaluated for in vitro dissolution parameters and bioadhesive strength. A central composite design for two factors at five levels each was employed for the study. Carbopol 934 and sodium carboxymethylcellulose were taken as independent variables. Fourier transform infrared (FTIR) spectroscopy studies were performed to observe the stability of the drug during direct compression and to check for a drug-polymer interaction. Various kinetic models were applied to evaluate drug release from the polymers. Contour and response surface plots were also drawn to portray the relationship between the independent and response variables. Mucoadhesive tablets of flurbiprofen exhibited non-Fickian drug release kinetics extending towards zero-order, with some formulations (F3, F8, and F9) reaching super case II transport, as the value of the release rate exponent (n) varied between 0.584 and 1.104. Polynomial mathematical models, generated for various response variables, were found to be statistically significant (P<0.05). The study also helped to find the drug's optimum formulation with excellent bioadhesive strength. Suitable combinations of two polymers provided adequate release profile, while carbopol 934 produced more bioadhesion.
Seeing Ourselves in Others: Reviewer Ambiguity, Egocentric Anchoring, and Persuasion

Consumers increasingly inform one another about marketplace offerings in online review forums. The authors demonstrate that when given no information about a reviewer (i.e., when the reviewer's identity is ambiguous), consumers use an accessibility-based egocentric anchor to infer that ambiguous reviewers have similar tastes to their own, leading consumers to be (1) similarly persuaded by reviews written by ambiguous and similar reviewers and (2) more persuaded by reviews written by ambiguous reviewers than by reviews written by dissimilar reviewers. The authors demonstrate that this effect holds in a single-offering, single-reviewer context. The authors also show that when consumers are exposed to multiple offerings with multiple reviewers, there may be a slight “cost” to ambiguity as opposed to similarity but that ambiguity remains much more persuasive than dissimilarity. Finally, the authors demonstrate that the effects of egocentric anchoring on persuasion can be moderated, first, by making other-related thoughts accessible and, second, by providing external cues about potential reviewer heterogeneity. These findings have important implications for both the management and monitoring of consumer-to-consumer online communication.
The in Silico Approach to Identify a Unique Plant-Derived Inhibitor Against E6 and E7 Oncogenic Proteins of High-Risk Human Papillomavirus 16 and 18

Background: Globally, the human papillomavirus (HPV) remains the foremost cause of cancer mortality among women. There is a need to identify natural anti-cancerous compounds that can fight against life-threatening infections by HPV. Various kinds of natural plant-originated compounds have been used in the traditional system of medicine for cancer therapy. Different studies have reported the effective inhibition of HPV infection enacted by certain natural compounds. Out of all the different HPV types, HPV-16 and 18 are the ones mainly associated with causing cervical cancer; furthermore, the E6 and E7 oncoproteins of these two high-risk HPV types typically interact with tumor protein 53 (p53) and retinoblastoma tumor suppressor proteins (pRb) of human host which consequent to cancer formation. Objectives: The goal of this study is to identify unique plant-originated compounds to utilize in order to combat the high-risk human papillomavirus oncoproteins using docking measures. Materials and Methods: Twelve natural compounds jaceosidin, withaferin A, curcumin, epigallocatechin-3-gallate (EGCG), artemisinin, gingerol, ursolic acid, ferulic acid, berberin, silymarin, resveratrol, and indol-3-carbinol were docked against E6 and E7 oncoproteins of high-risk HPV types 16 and 18 using a protein-ligand docking software called AutoDock4.2. Results: Out of these 12 natural compounds, withaferin A was found to inhibit all four oncoproteins withminimumbinding energy. Conclusions: These in silico findings indicate that withaferin A may be used as a common drug for cervical cancer caused by high risk HPV types, perhaps by restoring the normal functions of tumor suppressor proteins.
ReSyf: a French lexicon with ranked synonyms

In this article, we present ReSyf, a lexical resource of monolingual synonyms ranked according to their difficulty to be read and understood by native learners of French. The synonyms come from an existing lexical network and they have been semantically disambiguated and refined. A ranking algorithm, based on a wide range of linguistic features and validated through an evaluation campaign with human annotators, automatically sorts the synonyms corresponding to a given word sense by reading difficulty. ReSyf is freely available and will be integrated into a web platform for reading assistance. It can also be applied to perform lexical simplification of French texts.
CBIR-MSVM : Content-based Image Retrieval using Multi-Labelled Support Vector Machines

Content Based Image Retrieval (CBIR) technique is the emergent application to extract the appropriate query based images. But, the query based extraction is the one of complicated task for reducing the classification accuracy. To overcome these issue, proposed the CBIR based Multi-labelled Support Vector Machine classifier is used to enhance the classification outcomes. The preprocessing stage is processed into two main forms such as image resizing and the image filtering. In this framework, Gaussian Filtering technique is performed to remove the unwanted features and filter the relevant content based features. Then, three feature extraction process are as color, shape, and the texture feature are extracted based on the Color Histogram, REGIONPROPS, and the Grey Level Co-occurrence Matrix (GLCM). The Color Histogram technique is utilized to remove the unwanted RGB based structures from the results of preprocessed image and applying REGIONPROPS shape feature to extract the specific area and the perimeter based shapes. Then, performing GLCM texture based feature extraction to extract the statistical related features. Among the extracted features, the similarity computation process is accomplished to classify the content based images. Finally, MSVM classifier is processed to classify the content based pictures. The presentation result of the proposed framework is predicted with the help of parameters such as precision, specificity, recall, sensitivity, and the classification accuracy. Hence, the proposed research work is superior to the other existing techniques.
A Review on Elimination of Heavy Metals from Wastewater Using Agricultural Wastes as Adsorbents

In this article, the potential of various low-cost adsorbents for the removal of heavy metals from contaminated water has been reviewed. There are various conventional methods for heavy metal removal from wastewater such as precipitation, evaporation, electroplating and also ion-exchange have been applied since previous years. However, these methods have several disadvantages such as only limited to certain concentrations of metals ions, generation large amount of toxic sludge and the capital costs are much too high to be economical. Adsorption is the alternative process for heavy metal removal due to the wide number of natural materials or agricultural wastes gathering in abundance from our environment. In this review, a list of adsorbent has been compiled to provide available information on a wide range of low cost adsorbents for removing heavy metals from wastewater.
PLATINUM-IRIDIUM COATINGS FOR INCREASING SENSITIVITY OF IMPEDANCE-BASED POLYMER MICROFLUIDIC SENSORS

We present the first use of electrodeposited platinum-iridium (Pt-Ir) coatings for improving sensitivity and measurement range of impedance-based MEMS fluidic sensors. Pt-Ir deposited onto Pt microelectrodes increased electrochemical surface area (ESA) and decreased electrochemical impedance, enabling transduction at significantly lower frequencies (from 1 to 100 kHz) and increasing sensitivity. MEMS patency and flow sensors were characterized before and after Pt-Ir electrodeposition. Patency sensing utilizing larger electrodes exhibited moderate sensitivity gains (~3-11%), while flow sensing utilizing smaller electrodes improved significantly (61% sensitivity increase and 2x improvement in resolution (39 to 19 μm/s)). Pt-Ir coating reduced drift by an order of magnitude in flow sensors over a 12-hour period.
SEASONALLY ICE-COVERED WATERS

Seasonal ice cover is a major driver of seasonality in aquatic ecosystems in the Baltic Sea region. Ice cover influences the underwater light conditions directly by limiting the light transfer and indirectly by modifying the mixing and circulation under the ice. Light conditions and stratification are key factors controlling the onset of the phytoplankton spring bloom. Therefore, the seasonal ice cover has an important role in setting the time frames for the primary production and in influencing the seasonality of the ecological processes. This thesis investigates the optical properties of the ice cover and the bio-optical substances in the water column. Bio-optical substances, suspended particulate matter (SPM), Coloured dissolved organic matter (CDOM) and Chlorophyll-a (Chl-a), determine the availability and spectral distribution of light. Measuring turbidity is quick and easy compared to the gravimetrical determination of the SPM concentration. Paper I provides a new model to estimate the concentration of SPM from turbidity. The new SPM-turbidity model predicts SPM concentrations well, despite the high CDOM absorption and the optical differences in the coastal northwestern and southeastern Baltic proper. Therefore, the new SPM-turbidity model offers a cost-effective and reliable method to monitor SPM concentration. The light transfer through the snow and ice cover was studied both in freshwater lake ice and in brackish sea ice (Papers II and III). Additionally, the seasonal evolution of light transmission through lake ice was investigated during spring. The crystal structure of the ice cover was analysed both in the coastal fast ice zone and in drift ice in the open Baltic Sea. The snow and ice cover was found not only to reduce the amount of light, but also to change its spectral and directional distribution. The light field under ice depended strongly on the snow cover. In addition, the bio-optical substances were analysed within sea ice and in the underlying water, as well as their effect on the light conditions. The seasonal sea ice cover also limits the wind-driven mixing of the water column. The development of stratification was investigated in a coastal bay in the northwestern Baltic proper (Paper IV). The preconditions for an under-ice plume development were defined along with the spatial and temporal dimensions of the stratification pattern. Furthermore, an under-ice plume was found to cause a delay in the onset of the phytoplankton spring bloom, but the timing of the Chl-a maximum was not affected. The results also show that although diatoms dominate the phytoplankton community with and without under-ice plume, the dynamic conditions without under-ice plume seem to favour the motile photosynthetic ciliate Mesodinium rubrum. Overall, this thesis contributes to better understanding of the current role of seasonal ice cover on the light conditions and consequently on to the ecosystem.
The Broken Shield: Measuring Revocation Effectiveness in the Windows Code-Signing PKI

Recent measurement studies have highlighted security threats against the code-signing public key infrastructure (PKI), such as certificates that had been compromised or issued directly to the malware authors. The primary mechanism for mitigating these threats is to revoke the abusive certificates. However, the distributed yet closed nature of the code signing PKI makes it difficult to evaluate the effectiveness of revocations in this ecosystem. In consequence, the magnitude of signed malware threat is not fully understood. In this paper, we collect seven datasets, including the largest corpus of code-signing certificates, and we combine them to analyze the revocation process from end to end. Effective revocations rely on three roles: (1) discovering the abusive certificates, (2) revoking the certificates effectively, and (3) disseminating the revocation information for clients. We assess the challenge for discovering compromised certificates and the subsequent revocation delays. We show that erroneously setting revocation dates causes signed malware to remain valid even after the certificate has been revoked. We also report failures in disseminating the revocations, leading clients to continue trusting the revoked certificates.
Science and Innovation Dynamics and Policy in Scotland : The Perceived Impact of Increased Autonomy

The Scottish referendum of 2014 encouraged massive public debate, including on Scotland’s scientific performance and ability to harness innovation and increase global competitiveness. The science base in Scotland has traditionally been strong but has not translated well into innovation. This paper uses statistical data, over 30 interviews and two workshops with business and policy leaders, to analyse key scientific and industrial innovation dynamics, using a regional innovation systems approach. It investigates the perceived impact of increased autonomy on the dynamics of the Scottish innovation system. The paper shows the weak relationship between science and innovation and evidences the static nature of Scottish innovation policy geared to bridging a gap rather than improving the dynamics of the various elements in the innovation system. It suggests that an approach which aims to spur evolution in specific elements of the territorial governance system would strengthen Scottish innovation capabilities.