Miracle-dz/UniFAR-FTUs huggingface dataset:
University of Birmingham Making and unmaking cosmopolitans

Objective. In this article, we test whether emotions mediate the effect of international development appeals on cosmopolitanism and donation behavior. Methods. We design and conduct a lab experiment to test the impact of representations of global poverty on participants’ cosmopolitan sentiments and their likelihood to donate to development charities. We use multiple mediation analysis to test the intervening role of six emotional responses—anger, guilt, solidarity, hope, repulsion, and pity—as causal pathways to our two outcomes of interest: cosmopolitanism and donations. Results. Hope is the most consistent and powerful pathway through which appeals affect respondents’ sense of cosmopolitanism and willingness to donate. Negative imagery and text erode people’s sense of hope, but drive donations, particularly via guilt. Conclusions. Our ﬁndings suggest we should move away from a mono-causal view of emotional responses to disaster and development imagery, and provide a cautionary tale for practitioners: using negative imagery can undermine the public’s sense of hope and cosmopolitanism.
Information Technology Platforms: Conceptualisation and a Review of Emerging Research in the IS Discipline

The concept of an information technology (IT) related “platform” is broad and covers phenomena ranging from the operating system Linux to the Internet. Such platforms are of increasing importance to innovation and value creation across many facets of industry and daily life. There is, however, a lack of common understanding in both research and industry about what is mean by the term “platform” when related to IT. This lack of consensus is detrimental to research and knowledge development. Thus, the aims of this study are to: (i) conceptualise an IT-platform by identifying its distinguishing dimensions and show the concept’s extension to ecosystems; and (ii) identify important current research directions for the IT-platform concept. To achieve these aims a systematic literature review was undertaken with 132 relevant articles taken from major information systems journals, conferences, and business publications. The study contributes by providing a sound base for future research into IT-platforms.
Evaluating the Prevent Effect of Human Papillomavirus 16E7 Peptide-Based Therapeutic Vaccine Utilizing an Orthotopic TC-1 Cervical Tumour Model by 3.0T Magnetic Resonance Imaging in Mice

The goal of this paper is to investigate whether a 3.0T magnetic resonance scanner with a small animal coil can monitor the orthotopic TC-1 cell Cervical Tumour (CT) growth in mice, and to evaluate the tumour growth prevent effect of Human Papillomavirus (HPV)16E7 peptide-based therapeutic vaccine. The TC-1 cells were implanted into cervical cavity of 52 female C57BL/6J mice (6 experiments), and followed by subcutaneously immunization of HPV16E7 peptide-based with interleukin 10 receptor antibody in 18 mice (3 groups) to observe the efficacy of the therapeutic vaccine. The same Magnetic Resonance Imaging (MRI) equipment and protocols were performed through the entire experiments. Images of each tumour-bearing mice were compared with blank mice to determine when the CTs can be determined by MRI. The Tumour Volume (TV) of each mice was monitored including 3 contrast enhanced tumors. The TV changes were evaluated by comparing the size on the same coronal MR images, and Signal Intensity (SI) measurement was adopted on 6 mice to predict the tumour growth trend. This study showed that the average CTs success rate was 90.38% (47/52), the tumour could be clearly detected on average 10 days. The maximum average SI values of tumour-bearing mice on day 4 was 2447, which was significantly higher than that of the blank mice, and increasing from day4 to day12. This study concluded that clinical 3.0T MRI scanner with small animal coil can be used to monitor the CTs, and to evaluate the CTs growth inhibitory effect of HPV16E7 peptide-based therapeutic vaccine, SI values may be used to predict cervical tumour growth and reliable than visual observation of early tumour images.
Identification of a high affinity ligand that exhibits complete Ah receptor antagonism

The biological functions of the aryl hydrocarbon receptor (AHR) can be delineated into dioxin response element (DRE)-dependent or independent activities. Ligands exhibiting either full or partial agonist activity, e.g. TCDD and α -naphthoflavone, have been demonstrated to potentiate both DRE-dependent and independent AHR function. In contrast, the recently identified selective AHR modulators (SAhRMs), e.g. SGA360, bias AHR towards DRE-independent functionality while displaying antagonism with regard to ligand-induced DRE-dependent transcription. Recent studies have expanded the physiological role of AHR to include modulation of hematopoietic progenitor expansion and immunoregulation. It remains to be established whether such physiological roles are mediated through DRE-dependent or independent pathways. Here, we present evidence for a third class of AHR ligand, ‘pure’ or complete antagonists with the capacity to suppress both DRE-dependent and independent AHR functions, which may facilitate dissection of physiological AHR function with regard to DRE or non-DRE-mediated signaling. Competitive ligand binding assays together with in silico modeling identify GNF351 (N-[2-(3H-indol-3-yl)ethyl]-9-isopropyl-2-(5-methyl-3-pyridyl)purin-6-amine) as a high-affinity AHR ligand. DRE-dependent reporter assays, in conjunction with quantitative PCR analysis of AHR targets, reveal GNF351 as a potent AHR antagonist that demonstrates efficacy in the nM range. Furthermore, unlike many currently utilized AHR antagonists, e.g. α -naphthoflavone, GNF351 is devoid of partial agonist potential. Interestingly, in a model of AHR-mediated DRE-independent function, i.e. suppression of cytokine-induced acute phase gene expression, GNF351 has the capacity to antagonize agonist and SAhRM-mediated suppression of SAA1 . Such data indicate that GNF351 is a pure antagonist with the capacity to inhibit both DRE-dependent that is an AHR ligand that functions as a “pure antagonist” 2 . We have found that this compound displays antagonist activity at a lower concentration than most previously cited AHR antagonists, exhibits no AHR agonist activity, and antagonizes both the DRE-mediated and acute phase gene repression activities of the AHR. These findings will prove valuable towards further characterization of the AHR and its ability to be activated by various classes of ligands, as well as further insight into its role as a therapeutic agent. or increasing concentrations of GNF351 for 4 h (A). qRT-PCR was performed for RNA samples isolated from HepG2 40/6 cells treated with DMSO, TCDD (5 nM), or increasing concentrations of GNF351 for 4 h and examining the expression of CYP1A1 levels, normalized to L13a levels (B). Each treatment for parts (A) and (B) was conducted in triplicate wells. Data represent the mean ±SEM, with statistically significant results marked with an
Fully convolutional networks for the classiﬁcation of aerial VHR imagery

A BSTRACT . Remote sensing images provide the capability to obtain information of various land cover classes. This information is useful to the process of urban planning, socio-economic modelling and population studies. There is a need for accurate and efficient methods to obtain this information, particularly in regions where there is a scarcity of reference data. In this work, we develop a methodology based on fully convolutional networks (FCN) that is trained in an end-to-end fashion using aerial RGB images only as input. The experiments are conducted on the city of Goma in the Democratic Republic of Congo. We compare the results to a state-of-the art approach based on a semi-automatic Geographic object image-based analysis (GEOBIA) processing chain. State-of-the-art classification accuracies are obtained by both methods whereby FCN and the best baseline method have an overall accuracy of 91.24% and 89.34% respectively. The maps have good visual quality and the use of a FCN skip architecture minimizes the rounded edges that is characteristic of FCN maps. Finally, additional experiments are done to refine FCN classified maps using segments obtained from GEOBIA. This resulted in improved edge delineation in the FCN maps, and future work will involve explicitly incorporating boundary information from the GEOBIA segmentation into the FCN pipeline in an end-to-end fashion.
A Bibliometric Survey of Fashion Analysis using Artificial A Bibliometric Survey of Fashion Analysis using Artificial Intelligence Intelligence

In the 21 st century, clothing fashion has become an inevitable part of every individual human as it is considered a way to express their personality to the outside world. Currently the traditional fashion business models are experiencing a paradigm shift from being an experience-based business strategy implementation to a data driven intelligent business improvisation. Artificial Intelligence is acting as a catalyst to achieve the infusion of data intelligence into the fashion industry which aims at fostering all the business brackets such as supply chain management, trend analysis, fashion recommendation, sales forecasting, digitized shopping experience etc. The field of “Fashion AI'' is still under research progress because the fashion data is a multifaceted entity which is available in any of the forms like an image, video, text and numerical values. Therefore, it becomes a challenging research arena. There is a paucity of a common study which can provide a bird’s eye view about the research efforts and directions. In this paper, the authors represent a bibliometric survey of the AI based fashion analysis domain based on the Scopus database. The study was conducted by retrieving 581 Scopus research papers published from 1975-2020 and analysed to find out critical insights such as publication volume, co-authorship networks, citation analysis, and demographic research distribution. The study revealed that significant contribution is made via concept propositions in conferences and some papers published in the journal. However, there is a scope of lots of research work in the direction of improving fashion industry with AI techniques.
Aspects of tail muscle ultrastructure and its degeneration in Rana temporaria

1. Tail muscles of larval Rana temporaria and to a lesser extent Xenopus laevis, at prometamorphosis, were investigated by light and electron microscopy. In the case of Rana their degeneration is described at metamorphic climax. 2. The non-degenerate tail muscles of both genera are generally similar in their ultrastructure and likewise similar to those striated muscles of other adult vertebrates including amphibians.3. At climax tail muscles of Rana degenerate by autolysis. It seems likely that lysosomal enzymes are directly involved in sarcoplasmic degeneration. The relationship between lysosomes and myofibrillar degradation is difficult to establish. The subject is discussed in the light of relevant information (mainly mammalian) on muscle dystrophies. 4. Anuran tail muscle is highly degraded before its probable phagocytosis by mesenchymal macrophages.
Relationship virtual learning environment and student learning experience: What are the mediating variables?

Virtual Learning Environment (VLE) tools as a web based digital technology and software facilitate teaching activities and student learning experience. It is increasingly becoming an innovative way of learning and an essential part of courses in the Higher Education sector. Although the speedy explosion and increased recognition of virtual learning, little is known how VLE diffusion rate and innovative attributes affect module delivery and student learning experience through the mediating role of virtual collaboration. Using an usable response of 209 university students from the online self-administered survey, our results indicates that there are direct and indirect significant relationships between innovative attributes, module virtual collaboration and learning experience. As a result, lecturers should actively encourage and support students to virtually collaborate with each other around key issues related to VLE in order to enhance their learning experience. The senior management teams of the university should equip academic and support staff with VLE for being able to fully use VLE its full capacity.
ESTIMATION OF LOGISTIC SMOOTH TRANSITION AUTOREGRESSIVE MODEL USING GENETIC ALGORITHM

Time series data not only create linear model but also nonlinear model, especially in the economic. One of nonlinear model in time series is smooth transition autoregressive (STAR). STAR model is the development of Self-Exciting Autoregressive (SETAR) model with two regimes. STAR smoothen the SETAR two regimes with a transition function and one of that is logistic function which then form LSTAR models (logistic smooth transition autoregressive). After, determining order p and delay d, estimation of π1, π2, γ and c using genetic algotihm. By GA (genetic algorithm), that is a technique to search for solutions with various combinations of genes in a chromosome in order to obtain a global optimum solution, . Evaluation of chromosomes carried by the fitness function through procedures such as selection, crossover and mutation. Application of genetic algorithm (GA) will be conducted to identify the data model of LSTAR on stock return are included in the LQ 45 index that show LSTAR with GA better than AR model. Key words: genetic algorithm, nonlinear, stock return, LSTAR
Toponym Resolution on Historical Serial Sources

Various challenges are present in the resolution of toponyms from historical serial sources, where problems range from spelling errors to incorrect information. In this thesis, such problems are identified, design decisions for a resolution system are made, applicable heuristics from all over literature are gathered and complemented, the implementation of such a system is described, the implemented system’s result is evaluated towards actual problems for toponym resolution, and the system is compared to other available systems regarding employed heuristics. It is found that Data Matching heuristics, in combination with heuristics from various works towards toponym resolution, are capable of solving such problems; depending on the set of data, above 90% recall, precision, and accuracy can be reached when allowing an error tolerance of 20km. To evaluate the system, gold standard files were produced on lines of historical serial sources dated 1870 and 1914, spanning 800 cases. It is assumed by the author that the system result is, in many cases, actually of higher quality than this identification by hand.
Synchronous reference frame DQ current control for single phase grid connected cascaded H bridge multilevel inverter

The main focus on this paper deals with a current control technique for the inverter using a PV system for grid connected topology. The work of this paper is to evolve the PV model by tracking maximum power point using Incremental conductance algorithm by applying synchronous reference frame control method for single phase transformer less cascaded H Bridge Multilevel Inverter via boost converter system connected to 230V grid. A Phase shifted pulse width modulation technique is also projected in order to afford the pulse for voltage source inverter. The mathematical expressions for the control design for the single phase system is expressed in this paper. The analysis of the control is adopted using PI control method and is executed in synchronous rotating d-q reference frame in order to carry out the response of the best output voltage for the grid connected single phase PV system. The d-q technique is applicable only for the three phase system due to the minimum requirement of two independent phases. Hence one quadrature phase inverter is added additionally in the control method. The simulation is done using MATLAB/SIMULINK.
BIOACTIVITY OF GREEN SYNTHESIZED SILVER NANOPARTICLES FROM CALOTROPIS GIGANTEA (L.) R.BR LEAVES AND STEMS

: In this study, we have synthesised and analysed the potential efficiency of the green synthesized silver nanoparticles (AgNPs) using Calotropis gigantea (Linn) R. Br leaves and stems extract as a reducing and stabilizing agent under surfactant-free conditions. The formation of AgNPs is monitored by recording the UV – vis absorption spectra. The green synthesized AgNPs were characterized by UV – visible, FT-IR, XRD, EDAX, and SEM techniques. The green synthesized AgNPs of C. gigantea (Linn) R. Br leaves and stems were significantly showed more effective free radical scavenging activity. Synthesised silver nanoparticles shows potent antibacterial, antifungal, antibiofilm, antiangiogenic, mosquitocidal activity. Also the green synthesized silver nanoparticles exhibit cytotoxicity against Hep2 and AGS cell lines, further it may use effectively in treatment of carcinomas. The results observed in the present study showed the promising potential of C. gigantea (Linn.) R.Br- synthesised AgNPs for the development of novel antimicrobials, antibiofilm, and antiangiogenesis, mosquitocidal, anticancer and for various purposes.
Selenium in Critical Ill Patients, The Ongoing Discussion

Selenium (Se) is an essential trace element to human health. Its capacity to act, through selenoproteins, both as an antioxidant and antiinflammatory agent, provides it with a particular interest in clinical nutrition. In critical care patient, oxidative stress is a characteristic pathogenic event which usually is accompanied of Systemic Inflammatory Response Syndrome (SIRS). Because of this, pharmaconutrition with Se has been considered as a possible key point in the patient’s treatment and recovery. However, due to the narrow therapeutic window, there is no consensus on Se use. The aim of this review was to summarize the current opinion about Se and its supplementation in Intensive Care Units (ICUs) as pharmaconutrient, being a potential biomarker in clinical patient outcome.
The N -oxide metabolite of sorafenib inhibits hepatic CYP2C8

23 The multikinase inhibitor sorafenib (SOR) is a frontline agent in the treatment of 24 hepatocellular and renal cancers. In recent clinical studies SOR has been evaluated 25 increasingly in combination with other oncology agents, such as paclitaxel. However, the use 26 of such combinations could increase the likelihood of pharmacokinetic drug-drug interactions 27 (DDIs) and adverse events. It has been reported that SOR may inhibit a number of human 28 drug oxidation pathways mediated by multiple CYPs. Oxidative biotransformation of SOR 29 generates the pharmacologically active N -oxide metabolite (SNO) that has been shown to 30 accumulate in the serum of some individuals who have been treated with the drug. Recent 31 evidence has suggested that the metabolite SNO is more effective than the parent drug as an 32 inhibitor of some CYP-mediated drug oxidations. Molecular docking studies have shown that 33 SNO is associated with an increase in the binding interactions with active site amino acid 34 residues in these enzymes. SOR has been implicated as an inhibitor of CYP2C8, which is an 35 important catalyst in the oxidative elimination of oncology drugs such as paclitaxel and 36 imatinib; inhibition is potentiated by NADPH-dependent biotransformation of SOR. The 37 present study evaluated the potential contribution of SNO to the inhibition of CYP2C8 and 38 the closely related enzyme CYP2C9. The principal finding to emerge was that SNO was ~2- 39 fold more effective than SOR as an inhibitor of CYP2C8-mediated paclitaxel 6  - 40 hydroxylation in human liver. Both SOR and SNO interacted with active site residues in the 41 catalytic center of CYP2C8; there were four additional hydrogen and halogen bonding 42 interactions involving SNO. In contrast, the binding of SOR and SNO in the active site of 43 CYP2C9 and the capacity to inhibit microsomal losartan oxidation were similar. These 44 findings suggest that SNO has the potential to contribute to pharmacokinetic interactions 45 between SOR and drugs that are substrates for CYP2C8, perhaps in those individuals in 46 whom SNO accumulates.
Adaptive Scheduler in Apache Storm

:- Apache Storm is a distributed, error-tolerant, and highly scalable platform for streaming data. Storm supports a wide range of use cases, including real-time analysis, machine learning, continuous computation, and much more. This is extremely fast, with the ability to check one million records per second for a medium-sized cluster node. In the Storm framework, the Storm default scheduler distributes a topology workload equally into worker processes using a simple round-robin algorithm without considering any priority or criteria, leading to higher response time and less throughput. Two advanced general scheduling proposals provide better performance for the storm. The network connection works by analyzing the topology and traffic and load constraints between nodes RST scheduling works; the second scheduling enhancement is the former method by redistributing executors through available slots at runtime to improve overall performance.
Semantic change and knowledge transmission: Some case studies in the distribution of words in ECCO

This article attempts to make good on the affordances of lexical co-association to investigate semantic change in the British eighteenth-century corpus, mindful of the theories of knowledge that have been presented in an adumbrated state above. Pulling back to enquire into the whole of the eighteenth-century printed corpus, and designing tools ﬁt for apprehending and making sense of such a large, impersonal, non-individual view, will result in a complementary picture of how knowledge was structured and transmitted in the eighteenth century compared with individualistic or ‘great man’ narratives of the history of ideas. Taking the eighteenth-century corpus as a ﬁeld of
Japanese Candlestick Trading Strategies: A Review of Literature

The purpose of this study is to review the evidence on the performance of Japanese candlestick trading strategies. To achieve this, the study comprehensively reviews survey, theoretical and empirical studies on the subject of candlestick trading strategies and discusses the consistency and reliability of candlestick trading across markets and over time. The majority of the studies were collected from academic journals published from 1998 to the present and recent working papers, books and magazines. The reviews are arranged under two sections, first section contains review of studies that state candlestick trading rules are not profitable and second section contains review of studies that state candlestick trading rules are profitable.
Mapping the artificial sky brightness in Europe from DMSP satellite measurements: the situation of the night sky in Italy in the last quarter of century

We present a project to map the artificial sky brightness in Europe in the main astronomical photometrical bands with a resolution better than 3 km. The aim is to understand the state of night sky pollution in Europe, to quantify the present situation and to allow future monitoring of trends. The artificial sky brightness in each site at a given position on the sky is obtained by the integration of the contributions produced by every surface area in the surroundings of the site. Each contribution is computed taking in account the propagation in the atmosphere of the upward light flux emitted by the area and measured from DMSP satellites. The project is a long term study in which we plan to take in account successively of many different details in order to improve the maps. We present, as a preliminary result, a map of the V-band artificial sky brightness in Italy in 1998 and we compare it with the map obtained 27 years earlier by Bertiau, Treanor and De Graeve. Predictions for the artificial sky brightness within the next 27 years are also shown.