Miracle-dz/UniFAR-FTUs huggingface dataset:
Adjusted Edit Distance Algorithm for Alias Detection

Muniba Shaikh, Humaira Dar, Asadullah Shaikh and Asadullah Shah 1, 3, 4 Department of Computer Science, Kulliyyah of Information and Communication Technology (KICT), International Islamic University Malaysia (IIUM) 1, 3 {muniba.shaikh,asadullah.shaikh}@live.iium. edu.my, asadullah@kict.iium. edu.my, Department of computer &information engineering Kulliyyah of electrical & electronic engineering, International Islamic University Malaysia (IIUM) {engg87.iium@gmail.com} Abstract. Alias detection (AD) as the name suggests, a process undertaken in order to quantify and identify different variants of single name showing up in multiple domains. This process is mainly performed by the inversion of one-to-many and many-to-one mapping. Aliases mainly occur when entities try to hide their actual names or real identities from other entities i.e.; when an object has multiple names and more than one name is used to address a single object. Edit distance algorithm (EDA) have find wide applicability in the process of AD when the same is based upon orthographic and typographic variations. Levenshtein approach, a popular EDA works well and fulfill the cause, but at the same time we uncover that Levenshtein EDA (LEDA) suffers from serious inabilities when applied to detect aliases occurring due to the transliteration of Arabic name into English. This is the area were we have tried to hammer in this paper. Effort in the paper has been streamlined in extending the edit distance metric measure of LSM algorithm to make the same evolve in order to detect aliases which have their basing on typographic error. Data for our research is of the string form (names & activities from open source web pages). A comparison has been made to show the effectiveness of our adjustment to LEDA by applying both forms of LEDA on the above data set. As expected we come across that adjusted LEDA works well in terms of both performance & functional efficiency when it comes to matching names based on transliteration of Arabic into English language from one domain to another.
RIPL peptide-conjugated nanostructured lipid carriers for enhanced intracellular drug delivery to hepsin-expressing cancer cells

Background To facilitate selective and enhanced drug delivery to hepsin (Hpn)-expressing cancer cells, RIPL peptide (IPLVVPLRRRRRRRRC, 16-mer)-conjugated nanostructured lipid carriers (RIPL-NLCs) were developed. Methods NLCs were prepared using a solvent emulsification-evaporation method and the RIPL peptide was conjugated to the maleimide-derivatized NLCs via the thiol-maleimide reaction. Employing a fluorescent probe (DiI), in vitro target-selective intracellular uptake behaviors were observed using fluorescence microscopy and flow cytometry. Separately, docetaxel (DTX) was encapsulated by pre-loading technique, then cytotoxicity and drug release were evaluated. In vivo antitumor efficacy was investigated in BALB/c nude mice with SKOV3 cell tumors after intratumoral injections of different DTX formulations at a dose equivalent to 10 mg/kg DTX. Results RIPL-NLCs showed positively charged nanodispersion, whereas NLCs were negatively charged. DTX was successfully encapsulated with an encapsulation efficiency and drug loading capacity of 95–98% and 44-46 µg/mg, respectively. DTX release was diffusion-controlled, revealing the best fit to the Higuchi equation. Cellular uptake of DiI-loaded RIPL-NLCs was 8.3- and 6.2-fold higher than that of DiI-loaded NLCs, in Hpn(+) SKOV3 and LNCaP cells, respectively. The translocation of RIPL-NLCs into SKOV3 cells was time-dependent with internalization within 1 h and distribution throughout the cytoplasm after 2 h. DTX-loaded RIPL-NLCs (DTX-RIPL-NLCs) revealed dose-dependent in vitro cytotoxicity, while drug-free formulations were non-cytotoxic. In SKOV3-bearing xenograft mouse model, DTX-RIPL-NLCs significantly inhibited tumor growth: the inhibition ratios of the DTX solution-treated and DTX-RIPL-NLC-treated groups were 61.4% and 91.2%, respectively, compared to those of the saline-treated group (control). Conclusion RIPL-NLCs are good candidates for Hpn-selective drug targeting with a high loading capacity of hydrophobic drug molecules.
An Online Motion Planning and Control Strategy for UAVs in Wind using Reduced Order Forward Models

This paper presents an online motion planning strategy for Unmanned Aerial Vehicles (UAVs) in an obstacle-strewn environment that is complicated by uncertainties stemming from unmodeled effects and environmental disturbances, particularly cross-winds. During execution underlying wind currents are estimated and applied to the forward model used in online trajectory planning. To facilitate on-board computations, a reduced order forward model is used. We consider a 2D slice of the operating environment and assume that the UAV has independent bounded control over airspeed and altitude. Results are demonstrated from simulation using a medium fidelity non-linear model of a small UAV (Sig Rascal) under wind disturbances of varying magnitude and direction. The approach is tested in base winds in excess of 22 knots (50% forward speed). Results suggest that the method provides an efficient strategy for navigating to the desired destination by re-routing the trajectory as opposed to pure-pursuit methods under significant disturbance.
How to increase technology transfers to developing countries: a synthesis of the evidence

The existing United Nations Framework Convention on Climate Change (UNFCCC) has failed to deliver the rate of low-carbon technology transfer (TT) required to curb GHG emissions in developing countries. This failure has exposed the limitations of universalism and renewed interest in bilateral approaches to TT. Gaps are identified in the UNFCCC approach to climate change TT: missing links between international institutions and the national enabling environments that encourage private investment; a non-differentiated approach for (developing) country and technology characteristics; and a lack of clear measurements of the volume and effectiveness of TTs. Evidence from econometric literature and business experience on climate change TT is reviewed, so as to address the identified pitfalls of the UNFCCC process. Strengths and weaknesses of different methodological approaches are highlighted. International policy recommendations are offered aimed at improving the level of emission reductions achieved through TT.
Understanding the Dynamics of Young People's Self-Presentation on Social Media

Social media provides a flexible platform for self-presentation, which is one of the prominent functions used by young people. Young people post profile pictures, status updates, images and videos about their lives. However, the truthfulness of self-presentation may range from selected presentation, ideal self, self-promotion, to twisted, false self. Research has reported that the selective self-presentation on social media may have negative impact on the well being of young people. Using the theory of users and gratifications, this research attempts to investigate the interdependence between self-presentation, peer feed backs and peer comparison, and how the interdependence shapes young people's self-presentation on social media.
Do Effective Micro-Organisms Affect Greenhouse Gas Emissions from Slurry Crusts?

Slurry crusts form on the slurry surface and act as a primary barrier to gaseous emissions and could also be a zone where CH4 is consumed by methane-oxidising bacteria present. However, slurry crusts have also been reported as sources of nitrous oxide emissions. This study evaluated methane oxidation rate and nitrous oxide emissions from a 8 months developed slurry crust followed by 8 weeks application of a mixed microbial consortia (effective microorganism; EM). There was no clear evidence of CH4 oxidation following EM ® application. Whilst there was no significant reduction of N2O fluxes from EM-treated crusts, there was a tendency for lower N2O emissions from EM-sprayed crusts. N2O emissions were greater than CH4 consumption, resulting in net greenhouse gas (GHG) emissions of between 13.8-46.7 mg CO2 eq. g -1 DM hr. We conclude that it is important to consider net GHG emissions (CO2 eq.) when reporting CH4 oxidation from slurry crusts.  Index Term—slurry crust, methane oxidation, nitrous oxide, effective microorganisms, GHG mitigation
Syddansk Universitet Nuclear localization of the CK 2-subunit correlates with poor prognosis in Clear Cell Renal Cell Carcinoma

Protein kinase CK2α, one of the two catalytic isoforms of the protein kinase CK2 has been shown to contribute to tumor development, tumor proliferation and suppression of apoptosis in various malignancies. We conducted this study to investigate CK2 expression in different subtypes of Renal Cell Carcinoma (RCC) and in the benign oncocytoma. qRT-PCR, immunohistochemistry and Western blot analyses revealed that CK2α expression was significantly increased at the mRNA and protein levels in clear cell RCC (ccRCC). Also the kinase activity of CK2 was significantly increased in ccRCC compared to normal renal cortex. Nuclear protein expression of CK2α correlated in univariate analysis with poor Progression Free Survival (HR = 8.11, p = 0.016). Functional analyses (cell proliferation assay) revealed an inhibitory effect of Caki-2 cell growth following CK2 inhibition with CX-4945. Our results suggest that CK2α promotes migration and invasion of ccRCC and therefore could serve as a novel prognostic biomarker and molecular therapeutic target in this type of cancer.
Using MATLAB to Create IP for System Generator for DSP

www.xilinx. com 1 © 2006 Xilinx, Inc. All rights reserved. All Xilinx trademarks, registered trademarks, patents, and further disclaimers are as listed at http://www.xilinx. com/legal.htm. All other trademarks and registered trademarks are the property of their respective owners. All specifications are subject to change without notice. NOTICE OF DISCLAIMER: Xilinx is providing this design, code, or information "as is. " By providing the design, code, or information as one possible implementation of this feature, application, or standard, Xilinx makes no representation that this implementation is free from any claims of infringement. You are responsible for obtaining any rights you may require for your implementation. Xilinx expressly disclaims any warranty whatsoever with respect to the adequacy of the implementation, including but not limited to any warranties or representations that this implementation is free from claims of infringement and any implied warranties of merchantability or fitness for a particular purpose. Custom DSP algorithms are best modeled mathematically using MATLAB®, while complete systems are best modeled cycle-accurately using Simulink. The marriage of these two modeling domains provides an efficient means to design DSP systems into FPGAs. DSP systems are often best described using a combination of graphical and language-based methods. The MathWorks, the industry leader in DSP modeling software, caters to this dichotomy by providing a cycle-accurate graphical design environment called Simulink® and a mathematical modeling language called MATLAB. White Paper: Xilinx FPGAs
Back-dropout transfer learning for action recognition

Transfer learning aims at adapting a model learned from source dataset to target dataset. It is a beneficial approach especially when annotating on the target dataset is expensive or infeasible. Transfer learning has demonstrated its powerful learning capabilities in various vision tasks. Despite transfer learning being a promising approach, it is still an open question how to adapt the model learned from the source dataset to the target dataset. One big challenge is to prevent the impact of category bias on classification performance. Dataset bias exists when two images from the same category, but from different datasets, are not classified as the same. To address this problem, a transfer learning algorithm has been proposed, called negative back-dropout transfer learning (NB-TL), which utilizes images that have been misclassified and further performs back-dropout strategy on them to penalize errors. Experimental results demonstrate the effectiveness of the proposed algorithm. In particular, the authors evaluate the performance of the proposed NB-TL algorithm on UCF 101 action recognition dataset, achieving 88.9% recognition rate.
IMPACT OF AMMONIUM NITRATE ON WOOD FROG ( RANA SYLVATICA ) TADPOLES : EFFECTS ON SURVIVORSHIP AND BEHAVIOR

—Nitrogenous based fertilizers, such as ammonium nitrate, are commonly used in agriculture, entering aquatic ecosystems through runoff. Ammonium nitrate has been shown to affect the survivorship and behavior of anurans. We conducted an experiment to examine the potential toxic effects of ammonium nitrate on Wood Frog (Rana sylvatica) tadpoles. We also examined whether ammonium nitrate might interact with predator cues to affect tadpole behavior. Ammonium nitrate decreased survivorship of Wood Frog tadpoles (> 50 mg L NH4NO3). Activity level of Wood Frog tadpoles decreased when exposed to ammonium nitrate, as well as in the presence of predator (Mosquitofish, Gambusia affinis) chemical cues. Our results suggest that ammonium nitrate can have significant effects on anuran larvae, both through direct toxicological effects on survivorship, but also through behavioral effects.
Assessing Numerical Resolution Methods Performance for Kinetic Models of Receptors and Channels

In systems biology, systems of kinetic reactions are generally used to model and simulate various biochemical pathways. These reactions are translated into ordinary differential equations, which are computationally resolved by numerical algorithms. Computation performance, defined by how fast the algorithm converges to a numerical solution of the system of ordinary differential equations, critically depends on the choice of the appropriate algorithm. In this paper, we compared several algorithms used to solve ordinary differential equations applied to several kinetic models that describe the dynamic behavior of receptors and ion channels found in chemical synapses of the Central Nervous System; we provide a simplified method to determine the performances of these ordinary differential equation solvers, in order to provide a benchmark for algorithm selection. This method will facilitate the choice of the most efficient algorithm for a given kinetic model with a minimum number of tests. Our results provide a tool for identifying optimal solvers for any biological bilinear kinetic models under various experimental conditions. This comparison also underscored the complexity of biological kinetic models and illustrates how their input dependency could interfere with performance. Despite these challenges, our simplified method helps to select the best solvers for any synaptic receptors kinetic models described, with a bilinear system with minimal a priori information on the solver structure and the model.
Optimal Water Pipe Replacement Policy

Water scarcity is the major problem confronting both urban and rural dwellers in Enugu State. This scarcity emanated from indiscriminate pipe failure, lack of adequate maintenance, uncertainty on the time of repair or replacement of pipes etc. There is no systematic approach to determining replacement or repair time of the pipes. Hence, the rule of thumb is used in making such a vital decision. The population is increasing, houses are built but the network is not expanded and the existing ones that were installed for no less than two to three decades ago are not maintained. These compounded the problem of scarcity of water in the state. Replacement or repair of water pipes when they are seen spilling water cannot solve this lingering problem. The solution can be achieved by developing an adequate predictive model for water pipe replacement. Hence, this research is aimed at providing a solution to this problem of water scarcity by suggesting a policy that will be used for better planning. The interests in this paper were to obtain a water pipe failure model, the intensity function λ(t) [failure rate], the reliability R(t) and the optimal time of replacement and they were achieved. It was observed that the failure rate of the pipes increases with time while their reliability deteriorates with time. Hence, the Optimal replacement policy is that each pipe should be replaced after 4th break when the reliability = 0.0011.
Joint Spatio-Temporal Action Localization in Untrimmed Videos with Per-Frame Segmentation

Inspired by the recent spatio-temporal action localization efforts with tubelets (sequences of bounding boxes), we present a new spatio-temporal action detector Segment-tube, which consists of sequences of per-frame segmentation masks. The proposed Segment-tube detector can temporally pinpoint the starting/ending frame of each action class in the presence of preceding/subsequent interference actions in untrimmed videos. Simultaneously, the Segment-tube detector produces per-frame segmentation masks instead of bounding boxes, offering superior spatial accuracy to tubelets. This is achieved by alternating iterative optimization between temporal action localization and spatial action segmentation. Experimental results on multiple datasets validate the efficacy of the proposed detector.
Large Scale Geographical Mapping of Essential Oil Volatiles in Heracleum (Apiaceae): Identification of Novel Compounds and Unraveling Cryptic Variation

Conspecific populations of plants in their native range are expected to show considerable variation due to long‐term ecological and evolutionary factors. We investigated the levels of secondary metabolites in Heracleum including H. persicum a valuable medicinal plant to depict the magnitude of cryptic variation and the potential significance of novel chemical traits. The essential oil volatiles from fruits of 34 populations from different species of Heracleum in Iranian distribution range and a native of H. sphondylium and an invasive population of H. persicum from Norway were analyzed with GC/MS. Out of 48 compounds identified, a contrasting pattern in the level of two major compounds, octyl acetate and hexyl butyrate was found among all studied species. Interestingly, a significant geographic pattern was observed; the hexyl butyrate/octyl acetate ratio was high (range 1.8 – 3.2) in the northwestern Iranian populations of H. persicum compared to that in northern and central populations (range 0.3 – 0.9). Four populations from Zagros mountains also exhibited a unique composition. Anethole was found in two populations of H. persicum from central Zagros, which has not been previously reported for essential oil of fruits of Heracleum so far. The results suggest high efficiency of large scale sampling from distribution range of species in identifying novel compounds. The unique pattern of geographic structuring also provides novel information to unravel cryptic variation in Heracleum.
Effect of Pleurotus florida on paddy straw digestibility and biogas production

Biogas production from paddy straw offers a great potential as an alternative to fossilfuels. But, lignin and silica adversely affect the efficient utilization of paddy straw. Henceforth, the potential of biological pretreatment of paddy straw by a lignocellulolytic fungus, Pleurotus florida was investigated whereby the straw was inoculated with different spore concentrations of Pleurotus florida for different durations . Biodegradability of paddy straw was determined at different incubation periods and the selected pretreatment was further used for biogas production studies. An incubation period of 30 days was found to be the optimum pretreatment period in enhancing paddy straw digestibility with 19.3% increase in cellulose and 55.1% decrease in lignin. The biologically degraded paddy straw resulted in 15.4% increase in biogas production than that of the untreated paddy straw. DOI: http://dx.doi. org/10.3126/ijls.v6i1. 5550
Disclosures About Disclosures: Can Conflict of Interest Warnings Be Made More Effective?

People regularly rely on advisors who have conflicts of interest. The law often requires advisors to disclose these conflicts. Despite these disclosures, people generally insufficiently discount conflicted advice. This might be partly due to people interpreting the very fact that the advisor is disclosing a conflict of interest as a sign that the advisor is trustworthy, undermining the purpose and effectiveness of the disclosure. This article presents the results of an experiment indicating that requiring advisors to also disclose that they are legally required to disclose their conflict of interest makes people discount their advice more. This occurs, at least in part, because such advisors are viewed as less trustworthy than advisors who merely disclose their conflict of interest without also stating that the disclosure is legally required.
Proteomic Approach Analysis of Mammary Membrane Proteins Expression Profiles in Holstein Cows

To investigate host defense mechanisms for protecting the mammary gland from mastitis infection, the membrane fraction of mammary tissues from Holstein cows was purified by differential velocity centrifugation, and then the sodium dodecyl sulfate-polyacrylamid gel electrophoresis (SDS-PAGE) separated proteins were identified by ion trap mass spectrometer equipped with a Surveyor high performance liquid chromatography (HPLC) system. A total of 183 proteins were identified. Bioinformatics software was applied to analyse physicochemical characteristics of the identified proteins and to predict biochemical function. These data may provide valuable information to investigate the mechanisms of mammary gland milk secretion and infectious disease, and enable a clear identification of proteins and potential protein targets for therapies.
Constructing Click Models for Mobile Search

Users' click-through behavior is considered as a valuable yet noisy source of implicit relevance feedback for web search engines. A series of click models have therefore been proposed to extract accurate and unbiased relevance feedback from click logs. Previous works have shown that users' search behaviors in mobile and desktop scenarios are rather different in many aspects, therefore, the click models that were designed for desktop search may not be as effective in mobile context. To address this problem, we propose a novel Mobile Click Model (MCM) that models how users examine and click search results on mobile SERPs. Specifically, we incorporate two biases that are prevalent in mobile search into existing click models: 1) the click necessity bias that some results can bring utility and usefulness to users without being clicked; 2) the examination satisfaction bias that a user may feel satisfied and stop searching after examining a result with low click necessity. Extensive experiments on large-scale real mobile search logs show that: 1) MCM outperforms existing models in predicting users' click behavior in mobile search; 2) MCM can extract richer information, such as the click necessity of search results and the probability of user satisfaction, from mobile click logs. With this information, we can estimate the quality of different vertical results and improve the ranking of heterogeneous results in mobile search.