Miracle-dz/UniFAR-FTUs huggingface dataset:
Recent advances in photo‐anode for dye‐sensitized solar cells: a review

Dye‐sensitized solar cell (DSSC) attracts immense interest in the last few decades due to its various attractive features such as low production cost, ease of fabrication and relatively high conversion efficiency, which make it a strong competitor to the conventional silicon‐based solar cell. In DSSC, photo‐anode performs two important functions, viz. governs the collection and transportation of photo‐excited electrons from dye to external circuit as well as acts as a scaffold layer for dye adsorption. The photo‐anode usually consists of wide band gap semiconducting metal oxides such as titanium dioxide (TiO2) and zinc oxide (ZnO) deposited on the transparent conducting oxide substrates. The morphology and composition of the semiconductor oxides have significant impact on the DSSC photovoltaic performance. Therefore, enormous research efforts have been undertaken to investigate the influences of photo‐anode modifications on DSSC performance. The modifications can be classified into three categories, namely interfacial modification through the introduction of blocking and scattering layer, doping with non‐metallic anions and metallic cations and replacing the conventional mesoporous semiconducting metal oxide films with one‐dimensional or two‐dimensional nanostructures. In the present review, the previously mentioned modifications on photo‐anode are summarized based on the recent findings, with particular emphasis given to published works for the past 5 years. Copyright © 2017 John Wiley & Sons, Ltd.
Comprehensive electro‐thermal battery‐model for Li‐ion batteries in microgrid applications

Battery energy storage systems (BESSs) are frequently used to buffer the difference between intermittent renewable generations and energy demand in microgrids. The operation of BESS is affected by dynamics of charging/discharging current, internal temperature build up, extreme reaches of state of charge level, and so forth. This article presents a comprehensive electro‐thermal model for Li‐ion batteries that can be used to investigate dynamic and static performances of a microgrid under real time operating conditions. The battery‐model has the ability to self‐update its parameters with the variation of core‐temperature, and also to accommodate inherent hysteresis present on parameters between charging and discharging events. The developed model is presented as a block in MATLAB/Simulink for easier use by others. In parallel with that, the details of the development of a complete simulation platform of a microgrid is also described, which includes battery charging and discharging converter systems, bidirectional grid‐end AC/DC converter system, wind energy input, solar PV energy input, load and closed loop control associated with converter systems. The battery model is simulated within the microgrid platform with a chosen energy management criteria. The results of the simulation are also presented and discussed.
Safety and efficacy of pyrazine derivatives including saturated ones belonging to chemical group 24 when used as flavourings for all animal species

Abstract Following a request from the European Commission, the EFSA Panel on Additives and Products or Substances used in Animal Feed (FEEDAP) was asked to deliver a scientific opinion on the safety and efficacy of 22 compounds belonging to chemical group 24 (pyrazine derivatives). They are currently authorised as flavours in food. The FEEDAP Panel concludes that: 2,3‐diethylpyrazine [14.005], 2‐ethyl‐3‐methylpyrazine [14.006], 5,6,7,8‐tetrahydroquinoxaline [14.015], 2,3,5,6‐tetramethylpyrazine [14.018], 2,3,5‐trimethylpyrazine [14.019], 2,5‐dimethylpyrazine [14.020], 2,6‐dimethylpyrazine [14.021], 2‐ethylpyrazine [14.022], 2‐ethyl‐3,5‐dimethylpyrazine [14.024], 2,5 or 6‐methoxy‐3‐methylpyrazine [14.025], 2‐methylpyrazine [14.027], acetylpyrazine [14.032], 6,7‐dihydro‐5‐methyl‐5H‐cyclopenta(b)pyrazine [14.037], 2‐isobutyl‐3‐methoxypyrazine [14.043], 2‐acetyl‐3‐ethylpyrazine [14.049], 2,3‐dimethylpyrazine [14.050], 2,3‐diethyl‐5‐methylpyrazine [14.056], 2‐(sec‐butyl)‐3‐methoxypyrazine [14.062], 3,(5‐ or 6‐)‐dimethyl‐2‐ethylpyrazine [14.100], 2‐ethyl‐3‐methoxypyrazine [14.112] and 2‐methoxy‐3‐methylpyrazine [14.126] are safe at the proposed maximum dose level (0.5 mg/kg complete feed) as feed for cattle, salmonids and non‐food‐producing animals, and at the proposed normal use level of 0.1 mg/kg complete feed for pigs and poultry; 5‐methylquinoxaline [14.028] are safe only at concentrations below the proposed use levels (0.08 mg/kg complete feed for cattle, salmonids and non‐food‐producing animals, and 0.05 mg/kg complete feed for pigs and poultry). No safety concern would arise for the consumer from the use of these compounds up to the highest proposed level in feeds. Hazards for skin and eye contact, and respiratory exposure are recognised for the majority of the compounds under application. Most are classified as irritating to the respiratory system. The proposed maximum use levels in feed are unlikely to have detrimental effects on the terrestrial and fresh water compartments. Because all the compounds under assessment are used in food as flavourings and their function in feed is essentially the same as that in food, no further demonstration of efficacy is necessary.
An Analysis of Multiclass Imbalanced Data Problem in Machine Learning for Network Attack Detections

In the current trend, machine learning has been used widely for network attack detection. The performance of a machine learning model depends on its training dataset and the dataset distribution. Network attack detection is one of the problems that usually suffer from the imbalanced data distribution. However, the effect of this imbalanced data is generally neglected by researchers. Therefore, in this research, we studied the impact of an imbalanced multiclass dataset to the machine learning performance. Five state-of-the-art machine learning algorithms were used in this study, and the classifiers that can classify the minority class or the majority class instances accurately were also identified. In this research, the performances of these classifiers were evaluated by using the performance metrics: true positive rate, false positive rate, precision, F-measure, ROC area, and classification accuracy. The results show that the J48 classifier outperforms the other four classifiers in every aspect. Besides, Naïve Bayes, J48, has also worked as the best classifier that able to classifies the instances of the minority class accurately.
Marriage to the Same Kind: Organizational Political Ideology and Mergers and Acquisitions

This study contributes to the growing literature on organizational political ideology by positing that acquiring firms choose targets with similar organizational political ideology in their effort to retain employees post-merger. Using a sample of M&A announcements in the United States from 1996 to 2014, we find a positive relationship between the similarity of political ideologies of the merging organizations and the likelihood of M&A announcement. In addition, we find that our main relationship is stronger the more homogeneous the organizational political ideology of the acquirer, and the more the human capital intensity of the merging firms. In addition, we find support for the proposed mechanism that drives the main relationship. We thus introduce the concept of organizational political ideology into the debate over the influence of organizational values in M&As, and we extend the theoretical application of political ideology to settings with inter-organizational partnerships.
An SDN empowered location aware routing for energy efficient next generation vehicular networks

With the ever expanding and all pervasive growth of information and communication technologies, vehicular ad-hoc networks (VANETs) have been found wanting for sophistication. The ﬁfth generation (5G) communication has brought about uncharted band-width capabilities SDN have enabled real time network control while cloud and fog computing have brought unprecedented computation and storage capabilities for leveraging analytics on massive data volumes and bringing down response times. These information and communication technologies can effectively handle the challenges of next generation autonomous vehicular networks including maintaining road disciplines and safety in VANETs. Moreover, energy efﬁcient operations is the key for any upcoming technology. To this end, this paper assumes the use of 5G and fog computing based vehicular network and using SDN controller’s cognizance of global vehicular topology, it proposes an SDN enabled location-aware routing that intelligently manages workload at fog nodes for reduced energy consumption while satisfying bandwidth and delay constraints. The VANET energy minimization has been formulated as an integer linear programming problem and simulations has been carried out to test the efﬁcacy of the proposed model and the results shows the efﬁcacy of the proposed model 15.74% of improvement of energy consumption as compared that of the optimal algorithm.
On-tree fruit monitoring system using IoT and image analysis

On-tree fruit monitoring is an important practice to provide the exact status of the fruits concerning its quality, quantity and degree of maturity in the farm. In large farm, it is difficult to look over the individual tree manually to acquire the knowledge about the fruits. Again, the manual inspection method is time-consuming, labor intensive and erroneous. The image processing and IoT are the advance techniques applied in diverse field individually. In agriculture sector, image processing is applied for diagnosis of crops. With help of sensors, the IoT based system able to monitor the condition of field remotely. This paper suggests a frame work, which is the combination of image processing and IoT for on-tree fruit monitoring. İn addition, the on-tree counting and size estimation in terms of coefficient of correlation (R2) are 0.994 and 0.997 respectively.
Multi stratagem analysis of sentiments on twitter data using partial phrase harmonizing

Sentiment analysis is constructive in the application environment for business intelligence and suggests systems because it is a very easy medium for the two ends of the availability to communicate. Numerous strategies and schemes have been worn inside the sentiment analysis, such as language processing, polarity lexicons, machine learning, and psychometric scales which establish diverse types of analyzing sentiments as assumptions ended, scheme reveals, and corroboration data set. Since the internet has to turn into a commanding resource of retrospect the sphere of sentiment is moreover referred to as Sentiment Analysis or Opinion Mining. It has seen an enormous boost in academia over the decades. Analyzing sentiment to extract sentiments in different levels like word, sentence, and document provides articles’ feeling polarities. While well identified consumers’ sentiments articulated in sentences by opinion. Customary machine learning schemes cannot virtuously mirror the views of writers. This paper proposes a scheme called multi-strategy sentiments with semantic resemblance to disentangle the topic with partial phrase matching. Additionally, the Naïve Bayes classification is applied to search for the probability of the distribution of knowledge in different categories of knowledge set.
Edge turbulence in ISTTOK: a multi-code fluid validation

Fluid models used to study the edge plasma region need to be benchmarked against similar conditions given that models can strongly differ in complexity and therefore the results they produce. Via this validation study undertaken through the framework of EUROfusion Enabling Research, four state-of-the art models—GBS, Hermes/BOUT++, hot-edge-sol-electrostatic and TOKAM3X—are compared to experimental plasma turbulence measurements on the ISTTOK tokamak. Statistical comparisons of simulation and experiment data show that fluid models used here can replicate most of the experiment in terms of Isat and Vfloat fluctuations despite their differences. Furthermore, it is shown that without including more complex information (like core turbulence information and domain geometry details and magnetic topological aspects) in fluid models, the results recovered vary from their experimental counterparts. Via the simulations using these codes, it is demonstrated that fluid models continue to be a good cost-effective tool in recovering many global aspects of edge plasma behaviour.
Second-order Markov chain models of rainfall in Ibadan, Southwest Nigeria

Understanding the dynamics of rainfall is important for maximizing the agricultural potential, environmental planning, as well as policy development. In this study, a two-state second-order Markov chain model was developed for the annual and daily occurrence of different rainfall sequences in Ibadan, southwestern Nigeria. The annual variation was adapted to a sine series model. The model was able to account for more than 30% of the observed variation. Markov chain approach to modelling rainfall in tropical region is unique because it considers the “memory” – previous rainfall events, which is lacking in other methods. The daily occurrences showed patterns consistent with tropical regions. Results from this study is significant for economic, health and environmental planning in the location.
Evaluations of Hemostatic Activity of Ethanol Extract of Euonymus fortunei Aerial Parts

Aim: To investigate the hemostatic effect of ethanol extracts of Euonymus fortunei and their different polar fractions, and to analyze the changes in intracellular calcium ion concentration in platelet cells. Methodology: Bleeding time and clotting time was assessed by the slide method and the tailbreaking method, respectively. Four coagulation indexes, including prothrombin time, activated partial thromboplastin time, thrombin time, and the content of fibrinogen, as well as platelet aggregation effect were also determined. The concentration of calcium ions in platelet cells treated by n-butanol fraction with good active hemostatic activity was also examined. Results: Compared with the control group, the n-butanol fraction of E. fortunei can not only significantly shorten the bleeding time and coagulation time, but also obviously shorten activated partial thromboplastin time. However, no significant difference was found on the content of fibrinogen. Platelet aggregation experiments show that the n-butanol fraction can increase the Original Research Article Ouyang et al.; JPRI, 32(46): 8-15, 2020; Article no.JPRI. 64437 9 intracellular Ca concentration of platelet cells, which may be related to the activation of downstream signals through the platelet membrane G protein-coupled receptor. Conclusion: Ethanol extract of E. fortunei has excellent hemostatic activity, which may be related to the increase of intracellular Ca 2+ concentration caused by G protein-coupled receptor on the platelet membrane surface. E. fortunei could be a potential medicinal plant used for hemostatic
A revision of bird skin preparation aimed at improving the scientific value of ornithological collections

The methods used to preserve bird skins in museums have a potentially crucial impact on the feasibility and use of these specimens as a source of biological knowledge, although this subject is rarely broached. Study skins of birds are usually prepared with folded wings and straight legs to facilitate storage in the collection; yet, this method can hamper the measurement and examination of certain important features such as wing-feather moult. To make consultation easier for ornithologists, alternative preparation methods such as the splitting of wings and tarsi from the rest of the animal have been proposed by curators. Our aim was to study whether or not preparing bird specimens with spread limbs makes consultation simpler. First, we used two different methods to prepare two specimens each of two common European passerine species: (1) ‘traditional’ (folded wings and straight tarsi) and (2) ‘spread’ (limbs spread on one side of the body). Then, we asked 22 experienced ornithologists to identify moult limits and take three biometric measurements (wing chord, length of the third primary feather and tarsus length) from all four specimens. Subsequently, we asked which preparation method they preferred for obtaining data. The ‘spread’ preparation was preferred for moult, third primary feather length and tarsus length, whilst the ‘traditional’ preparation was preferred for wing chord. Data obtained from the folded and spread preparations were very highly repeatable within each method but only moderately to highly repeatable between methods. One of the handicaps with the ‘spread’ preparation is the increase in storage space required, a factor that should be taken into account before it is employed. Nevertheless, this specimen preparation technique can greatly facilitate consultation and therefore improve the scientific value of ornithological collections.
EXPLORING POTENTIAL OF 4-THIAZOLIDINONE: A BRIEF REVIEW

ABSTRACT Thiazolidinone, a saturated form of thiazole with carbonyl group on fourth carbon, has been considered as a magic moiety (wonder nucleus) which posses almost all types of biological activities. This diversity in the biological response profile has attracted the attention of many researchers to explore this skeleton to its multiple potential against several activities. Present article is sincere attempt to review chemistry, synthesis, spectral studies and applications of 4-thiazolidinone. Key words: Thiazolidinone, Thiazole. INTRODUCTION Thiazolidinones are the derivatives of thiazolidine which belong to an important group of heterocyclic compounds containing sulfur and nitrogen in a five member ring. A lot of research work on thiazolidinones has been done in the past. The nucleus is also known as wonder nucleus because it gives out different derivatives with all different types of biological activities. Numbers of methods for synthesis by using various agents are available in the references.
A Cluster-based Approach for Finding Domain wise Experts in Community Question Answering System

Community Question Answering (CQA) systems is an emerging web-based information service. CQA enables web users to get precise answers to questions from experts of the specific domain.CQA is used in wide areas such as biomedicine, information technology, tourism, etc. This paper focused on finding experts in community question answering system using unsupervised machine learning technique. Our Proposed system consists of three phases namely i) Clustering tags ii) Determining Experts for the unanswered questions iii) Finding experts for the given Question. By doing the tag analysis process, identified similar tags in a particular domain, and formed a cluster. By doing question analysis, we found the unanswered questions in each domain and identified the experts. For the given question, suggest the expert by doing pattern matching technique. The results section proves that our system predicts the experts for the given question with good accuracy.
The patterns of elemental concentration (Ca, Na, Sr, Mg, Mn, Ba, Cu, Pb, V, Y, U and Cd) in shells of invertebrates representing different CaCO3 polymorphs: a case study from the brackish Gulf of Gdańsk (the Baltic Sea)

Abstract. The shells of calcitic arthropod Amphibalanus improvisus; aragonitic bivalves Cerastoderma glaucum, Limecola balthica, and Mya arenaria; and bimineralic bivalve Mytilus trossulus were collected in the brackish waters of the southern Baltic Sea in order to study patterns of bulk elemental concentration (Ca, Na, Sr, Mg, Ba, Mn, Cu, Pb, V, Y, U and Cd) in shells composed of different crystal lattices (calcite and aragonite). The factors controlling the elemental composition of shells are discussed in the context of crystal lattice properties, size classes of organisms and potential environmental differences between locations. Clams that precipitate fully aragonitic shells have a clear predominance of Sr over Mg in shells, contrary to predominant accumulation of Mg over Sr in calcitic shells of barnacles. However, the barnacle calcite shell contains higher Sr concentration than bivalve aragonite. The elemental variability between size-grouped shells is different for each studied species, and the elemental concentrations tend to be lower in the large size classes compared to the smaller size classes. Biological differences between and within species, such as growth rate, feeding strategy (including feeding rate and assimilation efficiency or composition) and contribution of organic material, seem to be important factors determining the elemental accumulation in shells. Because specimens used in this study were obtained from different sampling sites within the gulf, the impact of location-specific environmental factors, such as sediment type, cannot be excluded.
Effects of Pyrolysis Bio-Oils on Fuel Atomisation—A Review

Bio-oils produced by biomass pyrolysis are substantially different from those produced by petroleum-based fuels and biodiesel. However, they could serve as valuable alternatives to fossil fuels to achieve carbon neutral future. The literature review indicates that the current use of bio-oils in gas turbines and compression-ignition (diesel) engines is limited due to problems associated with atomisation and combustion. The review also identifies the progress made in pyrolysis bio-oil spray combustion via standardisation of fuel properties, optimising atomisation and combustion, and understanding long-term reliability of engines. The key strategies that need to be adapted to efficiently atomise and combust bio-oils include, efficient atomisation techniques such as twin fluid atomisation, pressure atomisation and more advanced and novel effervescent atomisation, fuel and air preheating, flame stabilization using swrilers, and filtering the solid content from the pyrolysis oils. Once these strategies are implemented, bio-oils can enhance combustion efficiency and reduce greenhouse gas (GHG) emission. Overall, this study clearly indicates that pyrolysis bio-oils have the ability to substitute fossil fuels, but fuel injection problems need to be tackled in order to insure proper atomisation and combustion of the fuel.