nils-herrmann/clean_scirepeval huggingface dataset:
A rose by any other name? Transdisciplinarity in the context of UK research policy
Year: 2015

This paper assesses developments in transdisciplinary research in the UK. While we support the thesis that transdisciplinarity is still not mainstream and is rarely supported per se by funders of research, this paper examines the extent to which UK research policy has embraced the concept of transdisciplinarity. Five empirical case studies provide data about the interrelationship between the interdisciplinary and impact or knowledge exchange aspirations of Research Council UK (RCUK) investments. We find evidence that, to an extent, UK research funding policy is achieving some elements of transdisciplinarity in practice, if not in name. Drawing on broader debates about the limitations of knowledge mobilisation and the challenges of conducting interdisciplinary research, we reflect on how the situation has changed since our original 2004 paper. The evidence suggests that the absence of the 'transdisciplinary' label is not necessarily impeding the framing of research funding schemes oriented towards societal issues. Nevertheless, several areas where capacity building is required, including training for early career interdisciplinary researchers; improved research leadership skills; and the capacity to evaluate the quality of transdisciplinary processes and to learn from such evaluations, are identified.
Recent advances in the histo molecular pathology of human prion disease
Venue: Brain pathology
Year: 2019

Prion diseases are progressive neurodegenerative disorders affecting humans and other mammalian species. The term prion, originally put forward to propose the concept that a protein could be infectious, refers to PrPSc, a misfolded isoform of the cellular prion protein (PrPC) that represents the pathogenetic hallmark of these disorders. The discovery that other proteins characterized by misfolding and seeded aggregation can spread from cell to cell, similarly to PrPSc, has increased interest in prion diseases. Among neurodegenerative disorders, however, prion diseases distinguish themselves for the broader phenotypic spectrum, the fastest disease progression and the existence of infectious forms that can be transmitted through the exposure to diseased tissues via ingestion, injection or transplantation. The main clinicopathological phenotypes of human prion disease include Creutzfeldt Jakob disease, by far the most common, fatal insomnia, variably protease sensitive prionopathy, and Gerstmann Straussler Scheinker disease. However, clinicopathological manifestations extend even beyond those predicted by this classification. Because of their transmissibility, the phenotypic diversity of prion diseases can also be propagated into syngenic hosts as prion strains with distinct characteristics, such as incubation period, pattern of PrPSc distribution and regional severity of histopathological changes in the brain. Increasing evidence indicates that different PrPSc conformers, forming distinct ordered aggregates, encipher the phenotypic variants related to prion strains. In this review, we summarize the most recent advances concerning the histo molecular pathology of human prion disease focusing on the phenotypic spectrum of the disease including co pathologies, the characterization of prion strains by experimental transmission and their correlation with the physicochemical properties of PrPSc aggregates.
DNA magnetic bead detection using disposable cards and the anisotropic magnetoresistive sensor
Year: 2016

A disposable card incorporating specific DNA probes targeting the 16 S rRNA gene of Streptococcus suis was developed for magnetically labeled target DNA detection. A single stranded target DNA was hybridized with the DNA probe on the SPA/APTES/PDMS/Si as prepared card, which was subsequently magnetically labeled with superparamagnetic beads for detection using an anisotropic magnetoresistive (AMR) sensor. An almost linear response between the output signal of the AMR sensor and amount of single stranded target DNA varied from 4.5 to 18 pmol was identified. From the sensor output signal response towards the mass of magnetic beads which were directly immobilized on the disposable card surface, the limit of detection was estimated about 312 ng ferrites, which corresponds to 3.8 memu. In comparison with DNA detection by conventional biosensor based on magnetic bead labeling, disposable cards are featured with higher efficiency and performances, ease of use and less running cost with respects to consumables for biosensor in biomedical analysis systems operating with immobilized bioreceptor.
Strains of Bacillus ssp. regulate wheat resistance to Septoria nodorum Berk.
Venue: Applied Biochemistry and Microbiology
Year: 2017

The ability of Bacillus subtilis Cohn and Bacillus thuringiensis Berliner to induce systemic resistance in wheat plants to the casual agent of Septoria nodorum Berk. blotch has been studied. It has been shown that strains of Bacillus ssp. that possess the capacity for endophytic survival have antagonistic activity against this pathogen in vitro. A reduction of the degree of Septoria nodorum blotch development on wheat leaves under the influence of Bacillus spp. was accompanied by the suppression of catalase activity, an increase in peroxidase activity and H2O2 content, and expression of defence related genes such us PR 1, PR 6, and PR 9. It has been shown that B. subtilis 26 D induces expression levels of wheat pathogenesis related (PR) genes which marks a SA dependent pathway of sustainable development and that B. thuringiensis V 5689 and V 6066 induces a JA/ET dependent pathway. These results suggest that these strain Bacillus spp. promotes the formation of wheat plant resistance to S. nodorum through systemic activation of the plant defense system. The designed bacterial consortium formed a complex biological response in wheat plants infected phytopathogen.
Existence and multiplicity of nontrivial solutions for nonlinear Schrodinger equations with unbounded potentials
Year: 2018

We investigate the existence of nontrivial solutions and multiple solutions for the following class of elliptic equations u V(x)u K(x) f (u) x RN, u D1,2(RN) where N 3, V(x) and K(x) are both unbounded potential functions and f is a function with a superquadratic growth. Firstly, we prove the existence of infinitely many solutions with compact embedding and by means of symmetric mountain pass theorem. Moreover, we prove the existence of nontrivial solutions without compact embedding in weighted Sobolev spaces and by means of mountain pass theorem. Our results extend and generalize some existing results.
Kritische Diskursanalyse kontemporarer lateinamerikanischer Musik
Year: 2018

Ziel der vorliegenden Diplomarbeit war es, die stereotypen Geschlechterrollen und Machtstrukturen zwischen Mannern und Frauen in den Liedertexten kontemporarer lateinamerikanischer Musik, genauer gesagt den Genres Reggaeton und Latin Pop, aufzudecken. Auserdem war eine der Grundideen zwei kontrastierende Genres im Laufe der Arbeit immer wieder gegenuberzustellen, um die Ergebnisse und deren Bedeutung klar abzugrenzen. Dazu wurde auf Basis einer umfangreichen Literaturrezension die Methode der Kritischen Diskursanalyse nach Jager (2015: 90 91) gewahlt. Die vorgenommene theoretische Analyse diente dazu, den potenziellen Einfluss des Mediums Musik und deren Texte auf die RezipientInnen einzuschatzen und die Problematik der Folgen eines solchen Einflusses abzuschatzen. Zudem flossen auch quantitative Werte mit in die Auswertung der Ergebnisse ein. Wahrend der Analyse hat sich herausgestellt, dass die Geschlechterrollen in den Genres zwar unterschiedlich sind, sich gewisse Stereotype aber dennoch in beiden Genres abzeichnen.
Implications of Information Load on Fiscal Decentralization Delivery in Government Aided Primary Schools in Uganda
Venue: Public Policy and Administration Research
Year: 2019

The study explores the importance of information load in enhancing Fiscal Decentralization delivery in Government Aided Primary Schools in Busoga sub region, Eastern Uganda. The study is occasioned by availability of not so many empirical studies in many developing countries such as Uganda. The major objectives of this study are to establish the relationship between information load and Fiscal Decentralization in Busoga Sub region Government Aided Primary Schools in eastern Uganda.  This study adopted a cross sectional design under a quantitative and qualitative methods. Data collection was done on a sample of 314, respondents. The data was analyzed using multiple regression and confirmatory factor analysis using Amos.  The findings of the study indicate that the association is positive and significant which means the information load improves Fiscal Decentralization delivery. Unique contribution to the theory, practice and policy: It is therefore noted that many public schools face significant challenges in the management of fiscal resources, as such it is recommended that the Central Government streamlines communication and availability of information to the lowest accounting officers (Headteachers) such that there is prompt information availability in form of circulars using traditional media, organize regional meetings/workshops to disseminate information every quarter on release of funds to government institutions.  Fiscal decentralization delivery, information load, lowest accounting officers, Government aided primary schools DOI 10.7176/PPAR/9 7 08 Publication date :July 31 st 2019
Fungal Population of Nutmeg (Myristica fragrans) Kernels Affected by Water Activity During Storage
Year: 2018

The aim of this investigation was to determine the effect of various water activities (a w on fungal population in nutmeg kernels during storage. The seed nutmegs were obtained from ripe fruits one week after they fell on the ground in North Minahasa Regency, North Sulawesi Province, Indonesia. The kernels (moisture content 10% were stored 0, 15, and 30 days in various a w (0.75, 0.80, 0.83, 0.90, 0.97) using saturated salt solutions at 29 degC in sorption containers. Serial dilution method followed by a pour plate method in Dichloran 18% Glycerol Agar (DG18) was used to isolate and quantify the fungal population. Results revealed that kernels stored at a w 0.75 was not significantly p 0.05) different from at a w 0.80 0.83. Fungal population of kernels determined a w and significantly p 0.05) influenced by duration of storage. Range of a w 0.80 0.83 has a smaller total fungal population than a w 0.90. Thirteen different genera/species were isolated and identified including Aspergillus and Eurotium (6 species) Penicillium (3 species) Fusarium (2 species) 1 species each of Cladosporium or Syncephalastrum, and isolate A. The largest total fungal population (5.0x10 5 CFU g 1 was present at the beginning of storage (a w 0.97) and it was dominated by Penicillium citrinum (2.6x10 5 CFU g 1 followed by Cladosporium cladosporioides (1.7x10 5 CFU g 1 After 30 days of storage (a w 0.97) the population of P. citrinum was still dominant with a population of 2.4x10 4 CFU g 1 Eurotium chevalieri followed with a population of 1.2x10 4 CFU g 1
Learning Based Acoustic Source Microphone Distance Estimation Using the Coherent to Diffuse Power Ratio
Venue: 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2018

We propose a method for estimating the distance between a sound source and a pair of recording microphones. The developed algorithm operates in the short time Fourier transform domain and is based on estimates of the coherent to diffuse power ratio, which provides a measure for the amount of reverberation in each time frequency bin. For a direct use of these estimates, precise knowledge on the room characteristics is necessary, which is in practice usually not available and hard to obtain. Therefore, we use a learning based method, which adapts to the characteristics of the room in a training phase and estimates the source microphone distance in a testing phase. The experiments comprise various setups with simulated and real data. It is shown that the proposed method generalizes well for different microphone positions and works robustly for different source signals, directions of arrival, reverberation times, and signal observation intervals. This leads to a high estimation accuracy at a low computational complexity with a small amount of training data.
Assessment of awareness about various dental waste management practices among dental students and practicing clinicians
Year: 2019

To evaluate the knowledge of students and dental practitioners about dental and biomedical waste disposal and to impart emphasis on important aspects such as eco friendly waste management.  This questionnaire based study involved 186 participants which comprised of 5 domains, namely laws regarding biomedical waste, steps of waste management, categories of dental waste, general hazards of improper waste disposal and certain material/process specific questions.  Assessment of the first domain showed that only 58.4% of participants were able to correctly identify the Pollution Control Board of India as the regulatory body for the transport of medical waste. The second domain assessment revealed that 55.9% of subjects were adequately aware of the knowledge handling hospital waste. Assessment of the third domain displayed that the majority of the respondents (91.9% knew categories of dental waste generated. Evaluation of fourth domain exhibited that 89.8% students agreed that biomedical waste management (BWM) must be made a practical exercise in dental schools to reduce "Know Do gap" between undergraduates and postgraduates and the last domain demonstrated that only 32.3% of the participants knew the environmentally friendly technique to convert organic waste into commercially useful byproducts.  It was found that postgraduates had a better awareness of the proper methods to dispose of healthcare waste when compared to students and interns. However, the overall level of awareness was less than adequate. The need for special training in BWM in the clinical set up was highlighted through this study.
The state of the art in expert recommendation systems
Venue: Eng. Appl. Artif. Intell.
Year: 2019

The recent rapid growth of the Internet content has led to building recommendation systems that guide users to their needs through an information retrieving process. An expert recommendation system is an emerging area that attempts to detect the most knowledgeable people in some specific topics. This detection is based on both the extracted information from peoples' activities and the content of the documents concerned with them. Moreover, an expert recommendation system takes a user topic or query and then provides a list of people sorted by the degree of their relevant expertise with the given topic or query. These systems can be modeled by information retrieval approaches, along with search engines or a combination of natural language processing systems. The following study provides a critical overview of existing expert recommendation systems and their advantages and disadvantages, considering as well different techniques employed by them.
The function of RUDENIM on immigration monitoring for refugee
Year: 2020

Indonesia's strategic geographic position as a link between the Central and Middle East Asia regions with Australia in the movement of migration flow has made Indonesia a transit area that many immigrants pass through. What needs to be watched out for are illegal entrances (mouse path) both sea routes and land routes, considering that Indonesia is a large archipelagic country and existing crossings have not been optimally guarded. Looking at these conditions, the existence of a world organization in Indonesia that deals with refugees, namely the United Nations High Commissioner for Refugees (UNHCR) can provide some temporary or permanent solutions, with short or long processes and mechanisms, which must be passed by refugees. The existence of refugees in Indonesia should be managed by the flow of the process in which refugees will be placed in third countries. In the waiting process when they will be dispatched to a third country, the refugees occupy a shelter which is then under the supervision of RUDENIM (Immigration Detention Center) From the description above, the problem in this research is studying RUDENIM's supervisory function on additional tasks in the context of immigration control of refugees in the aspect of state sovereignty. The research method used in answering problems is using normative juridical research methods, by analyzing secondary data and legal materials related to statutory regulations, books, and scientific journals. This research also uses several approaches, namely statutory approach, conceptual approach, and case approach.
The Public Blockchain Ecosystem: An Empirical Analysis
Year: 2020

This paper offers an organizing empirical framework to understand the largely unexplored public blockchain ecosystem. Our framework casts blockchains in terms of their key economic attributes rather than as a set of disparate objects. The framework takes inspiration from the blockchain trilemma, constructing empirical analogs for each of its three attributes: (i) scale, (ii) security, and (iii) decentralization. Our analysis uncovers an association between these attributes and blockchain consensus protocols. We establish that Proof of Work (PoW) blockchains dominate on decentralization; Delegated Proof of Stake (DPoS) blockchains dominate on scale, and blockchains using non standard protocols dominate on security. We find that a small group of blockchains form the ecosystem's frontier, but no particular blockchain, not even Bitcoin, leads on all three attributes.
Electro thermal Stress Comparison between Full Pressure and Silver Sintered Package Press Pack IGBT
Venue: 2019 IEEE 10th International Symposium on Power Electronics for Distributed Generation Systems (PEDG)
Year: 2019

In order to analyze the reliability difference of different package IGBT, the electro thermal stress of full pressure and silver sintered package Press Pack IGBT (PP IGBT) are compared by using Finite Element Method (FEM) in this paper. Based on the actual structure and material physical properties of a 3300V/50A Press pack IGBT, a machine thermal electrical multi coupling field finite element model is eatablished and verified by the power cycling test platform. The simulation results show that, the silver sintered package could improves the heat dissipation capability of IGBT, while reduces the junction temperature and the saturation voltage of the device. However, the silver sintered package increases the von mises stress of PP IGBT.
Maximizing Marginal Utility per Dollar for Economic Recommendation
Venue: WWW
Year: 2019

Understanding the economic nature of consumer decisions in e Commerce is important to personalized recommendation systems. Established economic theories claim that informed consumers always attempt to maximize their utility by choosing the items of the largest marginal utility per dollar (MUD) within their budgets. For example, gaining 5 dollars of extra benefit by spending 10 dollars makes a consumer much more satisfied than having the same amount of extra benefit by spending 20 dollars, although the second product may have higher absolute utility value. Meanwhile, making purchases online may be risky decisions that could cause dissatisfaction. For example, people may give low ratings towards purchased items that they thought they would like when placing the order. Therefore, the design of recommender systems should also take users' risk attitudes into consideration to better learn consumer behaviors. Motivated by the first consideration, in this paper, we propose a learning algorithm to maximize marginal utility per dollar for recommendations. With the second, economic theory shows that rational people can be arbitrarily close to risk neutral when stakes are arbitrarily small, and this is generally applicable to consumer online purchase behaviors because most people spend a small portion of their total wealth for a single purchase. To integrate this theory with machine learning, we propose to augment MUD optimization with approximate risk neural constraint to generate personalized recommendations. Experiments on real world e Commerce datasets show that our approach is able to achieve better performance than many classical recommendation methods, in terms of both traditional recommendation measures such as precision and recall, as well as economic measures such as MUD.
Trapezoidal Pythagorean fuzzy linguistic entropic combined ordered weighted Minkowski distance operator based on preference relations
Venue: Int. J. Intell. Syst.
Year: 2019

Preference relations (PRs) as useful and efficient information description tools have been widely applied in practical multiple attribute group decision making (MAGDM) problems. Due to fuzziness and complexity of problems, the limitations of the experts' professional knowledge and experience, the provided PRs are usually inconsistent, will lead to unreasonable conclusion. Consequently, we define the concept of trapezoidal Pythagorean fuzzy linguistic PRs (TrPFLPRs) a method for confirm the consistent of PRs and repair inconsistent PFs in this paper. Meanwhile, we propose trapezoidal Pythagorean fuzzy linguistic entropic combined ordered weighted Minkowski distance operator to aggregate the TrPFLPRs information. Finally, a numerical example is given to illustrate the practicality and effectiveness of the proposed operator.
Reinforcement Evolutionary Learning Method for self learning
Venue: ArXiv
Year: 2018

In statistical modelling the biggest threat is concept drift which makes the model gradually showing deteriorating performance over time. There are state of the art methodologies to detect the impact of concept drift, however general strategy considered to overcome the issue in performance is to rebuild or re calibrate the model periodically as the variable patterns for the model changes significantly due to market change or consumer behavior change etc. Quantitative research is the most widely spread application of data science in Marketing or financial domain where applicability of state of the art reinforcement learning for auto learning is less explored paradigm. Reinforcement learning is heavily dependent on having a simulated environment which is majorly available for gaming or online systems, to learn from the live feedback. However, there are some research happened on the area of online advertisement, pricing etc where due to the nature of the online learning environment scope of reinforcement learning is explored. Our proposed solution is a reinforcement learning based, true self learning algorithm which can adapt to the data change or concept drift and auto learn and self calibrate for the new patterns of the data solving the problem of concept drift.  Reinforcement learning, Genetic Algorithm, Q learning, Classification modelling, CMA ES, NES, Multi objective optimization, Concept drift, Population stability index, Incremental learning, F1 measure, Predictive Modelling, Self learning, MCTS, AlphaGo, AlphaZero