nils-herrmann/clean_scirepeval huggingface dataset:
Virtualization of 5G Cellular Networks as a Hierarchical Combinatorial Auction
Venue: IEEE Transactions on Mobile Computing

Virtualization has been seen as one of the main evolution trends in the forthcoming fifth generation (5G) cellular networks which enables the decoupling of infrastructure from the services it provides. In this case, the roles of infrastructure providers (InPs) and mobile virtual network operators (MVNOs) can be logically separated and the resources (e.g. subchannels, power, and antennas) of a base station owned by an InP can be transparently shared by multiple MVNOs, while each MVNO virtually owns the entire BS. Naturally, the issue of resource allocation arises. In particular, the InP is required to abstract the physical resources into isolated slices for each MVNO who then allocates the resources within the slice to its subscribed users. In this paper, we aim to address this two level hierarchical resource allocation problem while satisfying the requirements of efficient resource allocation, strict inter slice isolation, and the ability of intra slice customization. To this end, we design a hierarchical combinatorial auction mechanism, based on which a truthful and sub efficient resource allocation framework is provided. Specifically, winner determination problems (WDPs) are formulated for the InP and MVNOs, and computationally tractable algorithms are proposed to solve these WDPs. Also, pricing schemes are designed to ensure incentive compatibility. The designed mechanism can achieve social efficiency in each level even if each party involved acts selfishly. Numerical results show the effectiveness of the proposed scheme.
Energy Storage Sharing in Smart Grid: A Modified Auction Based Approach
Venue: IEEE Transactions on Smart Grid

This paper studies the solution of joint energy storage (ES) ownership sharing between multiple shared facility controllers (SFCs) and those dwelling in a residential community. The main objective is to enable the residential units (RUs) to decide on the fraction of their ES capacity that they want to share with the SFCs of the community in order to assist them in storing electricity, e.g. for fulfilling the demand of various shared facilities. To this end, a modified auction based mechanism is designed that captures the interaction between the SFCs and the RUs so as to determine the auction price and the allocation of ES shared by the RUs that governs the proposed joint ES ownership. The fraction of the capacity of the storage that each RU decides to put into the market to share with the SFCs and the auction price are determined by a noncooperative Stackelberg game formulated between the RUs and the auctioneer. It is shown that the proposed auction possesses the incentive compatibility and the individual rationality properties, which are leveraged via the unique Stackelberg equilibrium solution of the game. Numerical experiments are provided to confirm the effectiveness of the proposed scheme.
US preschoolers' trust of and learning from media characters

The current study examined the relations between children's perceptions of character social realism, identification with characters, trust of characters as knowledgeable informants, and learning from media characters. Thirty six 3 1/2 to 6 year old children watched a short clip of an animated educational television program about a preschool aged boy who enjoys learning about science. Participants provided ratings of the character's social realism, their identification with the character, and their trust in the character as a knowledgeable informant. Participants were asked to solve problems based on information in the video clip. Findings revealed character trust was the strongest indicator of learning from the character. Results are discussed in the context of the different factors that influence learning from curriculum based media for young children.
Optimization of ultrasound assisted extraction of bioactive compounds from wild garlic (Allium ursinum L.
Venue: Ultrasonics sonochemistry

Ultrasound assisted extraction was used for extraction of bioactive compounds and for production of Allium ursinum liquid extract. The experiments were carried out according to tree level, four variables, face centered cubic experimental design (FDC) combined with response surface methodology (RSM) Temperature (from 40 to 80 degC) ethanol concentration (from 30% to 70% extraction time (from 40 to 80 min) and ultrasonic power (from 19.2 to 38.4 W/L) were investigated as independent variables in order to obtain the optimal conditions for extraction and to maximize the yield of total phenols (TP) flavonoids (TF) and antioxidant activity of obtained extracts. Experimental results were fitted to the second order polynomial model where multiple regression and analysis of variance were used to determine the fitness of the model and optimal condition for investigated responses. The predicted values of the TP (1.60 g GAE/100 g DW) TF (0.35 g CE/100 g DW) antioxidant activity, IC50 (0.71 mg/ml) and EY (38.1% were determined at the optimal conditions for ultrasound assisted extraction: 80 degC temperature, 70% ethanol, 79.8 min and 20.06 W/L ultrasonic power. The predicted results matched well with the experimental results obtained using optimal extraction conditions which validated the RSM model with a good correlation.
Protein pathways working in human follicular fluid: the future for tailored IVF?
Venue: Expert Reviews in Molecular Medicine

The human follicular fluid (HFF) contains molecules and proteins that may affect follicle growth, oocyte maturation and competence acquiring. Despite the numerous studies, an integrated broad overview on biomolecular and patho/physiological processes that are proved or supposed to take place in HFF during folliculogenesis and oocyte development is still missing. In this review we report, for the first time, all the proteins unambiguously detected in HFF and, applying DAVID (Database for Annotation, Visualization and Integrated Discovery) and MetaCore bioinformatic resources, we shed new lights on their functional correlation, delineating protein patterns and pathways with reasonable potentialities for oocyte quality estimation in in vitro fertilisation (IVF) programs. Performing a rigorous PubMed search, we redacted a list of 617 unique proteins unambiguously annotated as HFF components. Their functional processing suggested the occurrence in HFF of a tight and highly dynamic functional network, which is balanced by specific effectors, primarily involved in extracellular matrix degradation and remodelling, inflammation and coagulation. Metalloproteinases, thrombin and vitamin D receptor/retinoid X receptor alpha resulted as the main key factors in the nets and their differential activity may be indicative of ovarian health and oocyte quality. Despite future accurate clinical investigations are absolutely needed, the present analysis may provide a starting point for more accurate oocyte quality estimation and for defining personalised therapies in reproductive medicine.
Human follicular fluid and effects on reproduction.
Venue: JBRA assisted reproduction

Fertility the ability to produce offspring is considered a prerequisite for the development and perpetuation of species. Several factors may positively or negatively affect one's reproductive capabilities, such as regular exercises and maintaining a healthy bodyweight, versus aging, obesity, and stress. Follicular fluid (FF) is a liquid composed primarily of hormones, enzymes, anticoagulants, electrolytes, reactive oxygen species and antioxidants, which fills the follicular antrum and acts as an important mediator in the communication between cells in the antral follicle while bathing and carrying nutrients to the oocyte. Thus, human FF is a key element to the success of natural fertilization present in every stage of the conception process, from the communication between gametes to the development of fully viable embryos, and a vital component in the occurrence of spontaneous pregnancies. This literature review aimed to describe the possible effects of human follicular fluid on the natural fertilization process and to assess its role in follicular growth, oocyte quality, sperm capacitation, fertilization, and early embryonic development.
Most Cleaved Anti Mullerian Hormone Binds Its Receptor in Human Follicular Fluid but Little Is Competent in Serum.
Venue: The Journal of clinical endocrinology and metabolism

Anti Mullerian hormone (AMH) is an important clinical marker for diagnosing and assessing the reproductive status and/or disorders in men and women. Most studies have not distinguished between levels of inactive AMH precursor and the cleaved noncovalent complex that binds the AMH type II receptor (AMHRII) and initiates signaling.  The objective of the study was to measure the levels of AMH cleavage and bioactivity in human body fluids.  AMH cleavage levels and bioactivity were measured in the serum of six boys and in the follicular fluid and serum of nine control women and 13 women with the polycystic ovary syndrome (PCOS) MAIN OUTCOME MEASURES AMH cleavage levels were measured by capturing AMH with an anti AMH antibody, followed by Western blotting. The bioactivity of cleaved AMH was assessed with an ELISA that measures the levels of AMH capable of binding AMHRII.  PCOS women have an elevated level of AMH cleavage in their follicular fluid (24% vs 8% in control women) and most of the cleaved AMH can bind AMHRII. Higher levels of cleavage are observed in female (60% and male (79% serum, but very little of the cleaved AMH can bind AMHRII.  These results support an autocrine role for AMH in the pathophysiology of PCOS in the follicle. In addition, they indicate that AMH undergoes interactions or structural changes after cleavage that prevent receptor binding, meaning, unexpectedly, that the level of cleaved AMH in biological fluids does not always reflect the level of bioactive AMH.
A Study of Impact of Ownership Structure and Disclosure Quality on Information Asymmetry in Iran

Executive Summary Capital market uses financial information with high disclosure quality, and this information can influence capital market decision making. Corporate governance research shows that ownership structure can influence financial reporting quality, and thus play an effective role in capital market decision making. The main purpose of the current study is to examine the impact of ownership structure and disclosure quality on the information asymmetry phenomenon among the listed companies on the Tehran Stock Exchange (TSE) Ownership structure (including ownership concentration and institutional ownership) and disclosure quality (including reliability and timeliness) are considered as independent variables, and their impact is examined on the dependent variable (information asymmetry) Consistent with extant literature, bid ask spread is used as a proxy variable for information asymmetry. The statistical results, based on data collected from 102 listed companies on the TSE during 2007 2014, revealed positive impact of ownership structure and negative impact of disclosure quality on information asymmetry. These results show that information asymmetry is less in firms that published more reliable and timely information, and is more in firms with more concentrated ownership structure, higher institutional ownership, and lower disclosure quality. In other words, reliability and timeliness of information have a positive role in stock price identification and close up views of the buyer and seller in TSE. Findings of this article can assist accounting researchers and theoreticians in comparing real world facts with hypotheses developed with respect to ownership structure, disclosure quality, and information asymmetry. By increasing transparency in the capital markets, market participants, decision makers, financial analysts, and potential investors are aided in their analysis of plans for investments in financial assets.
Mammographic Mass Detection Based on Saliency with Deep Features
Venue: ICIMCS

Breast cancer continues to be an attentional public health problem all over the world. Because of being indistinguishable from the surrounding normal tissues, automated mass detection is challenging in computer aided detection (CAD) system. This paper presents a novel mass detection system for digital mammograms which integrates visual saliency model with deep learning techniques. After a visual saliency model applied to the pre processed mammogram, a sliding window strategy is adopted to scan the breast area segmented from the whole mammogram. For each subimage produced by sliding window strategy, convolutional neural networks (CNN) features are extracted and propagated to a classifier to predict the class label. Large scale experiments on Digital Database for Screening Mammography (DDSM) demonstrate the effectiveness of the proposed mass detection method.
Singular Gelfand Tsetlin modules of gl(n)

The classical Gelfand Tsetlin formulas provide a basis in terms of tableaux and an explicit action of the generators of gl n for every irreducible finite dimensional gl n module. These formulas can be used to define a gl n module structure on some infinite dimensional modules the so called generic Gelfand Tsetlin modules. The generic Gelfand Tsetlin modules are convenient to work with since for every generic tableau there exists a unique irreducible generic Gelfand Tsetlin module containing this tableau as a basis element. In this paper we initiate the systematic study of a large class of non generic Gelfand Tsetlin modules the class of 1 singular Gelfand Tsetlin modules. An explicit tableaux realization and the action of gl n on these modules is provided using a new construction which we call derivative tableaux. Our construction of 1 singular modules provides a large family of new irreducible Gelfand Tsetlin modules of gl n and is a part of the classification of all such irreducible modules for n 3
Learning Representations from EEG with Deep Recurrent Convolutional Neural Networks
Venue: ICLR

One of the challenges in modeling cognitive events from electroencephalogram (EEG) data is finding representations that are invariant to inter and intra subject differences, as well as to inherent noise associated with such data. Herein, we propose a novel approach for learning such representations from multi channel EEG time series, and demonstrate its advantages in the context of mental load classification task. First, we transform EEG activities into a sequence of topology preserving multi spectral images, as opposed to standard EEG analysis techniques that ignore such spatial information. Next, we train a deep recurrent convolutional network inspired by state of the art video classification to learn robust representations from the sequence of images. The proposed approach is designed to preserve the spatial, spectral, and temporal structure of EEG which leads to finding features that are less sensitive to variations and distortions within each dimension. Empirical evaluation on the cognitive load classification task demonstrated significant improvements in classification accuracy over current state of the art approaches in this field.
Structured Low Rank Matrix Factorization for Haplotype Assembly
Venue: IEEE Journal of Selected Topics in Signal Processing

In matrix factorization problems, one seeks to decompose a data matrix into a product of two matrices frequently, one captures meaningful information contained in the data, and the other specifies how this information is combined to generate the data matrix. In this paper, matrix factorization that arises in haplotype assembly, an important NP hard problem in genomics, is studied. Haplotypes are sequences of chromosomal variations in an individual's genome, which are of critical importance for understudying the individual's susceptibility to various diseases. A novel formulation of haplotype assembly as the partially observed low rank matrix factorization problem is proposed and efficiently solved via a modified gradient descent method that exploits salient structural properties of sequencing data. In particular, the observed matrix in the problem at hand contains noisy samples of the product of an informative matrix with rows having entries from a finite alphabet and a matrix with rows that are standard unit basis. Convergence of the proposed algorithm is analyzed and its performance tested on both synthetic and experimental data. The results demonstrate superior accuracy and speed of the proposed method as compared to state of the art haplotype assembly techniques.
The Effect of Adoption of International Public Sector Accounting Standards on Quality of Financial Reports in Public Sector in Kenya

Quality financial reports plays significant role in accountability of government to their citizens and how it meets its financial management responsibilities. The introduction of IPSAS formed an important part of public sector reforms and followed a global trend in government accounting in response to calls for greater government financial accountability and transparency which is a fundamental principles of democracy. This study focused on effect of adoption of IPSAS on quality of financial reports in meeting the criteria for decision usefulness. The design of this study was the descriptive survey design while the target population was the 19 ministries of the national government in Kenya. Data was collected using secondary means and was analysed using descriptive statistics and t test for differences. The study indicated enhancement in the quality of characteristics of comparability, relevance, timeliness and faithful representation by adoption of IPSAS while the quality of characteristics of understandability declined. The study also showed no significant difference in items pertaining to transparency and accountability indicating that the goal for government reforms in achieving greater transparency and accountability may not be fully achieved. The study also revealed that adoption of IPSAS is adjudged to have moderate effect on quality of financial reports in public sector in Kenya using a 5 point likert scale. The study concluded that there exist statistically significant difference between old accounting standard based financial reports and IPSAS based financial reports in meeting the criteria for decision usefulness as revealed by paired sample t test.
An EFL Flipped Classroom Teaching Model: Effects on English Language Higher order Thinking Skills, Student Engagement and Satisfaction

This study aimed at investigating the effect of a suggested EFL Flipped Classroom Teaching Model (EFL FCTM) on graduate students' English higher order thinking skills (HOTS) engagement and satisfaction. Also, it investigated the relationship between higher order thinking skills, engagement and satisfaction. The sample comprised (67) graduate female students; an experimental group (N=33) and a control group (N=34) studying an English course at Taif University, KSA. The study used mixed method design; a pre post HOTS test was carried out and two 5 Likert scale questionnaires had been designed and distributed; an engagement scale and a satisfaction scale. The findings of the study revealed statistically significant differences between the two group in HOTS in favor of the experimental group. Also, there was significant difference between the pre and post administration of the engagement scale in favor of the post administration. Moreover, students satisfaction on the (EFL FCTM) was high. Finally, there were high significant relationships between HOTS and student engagement, HOTS and satisfaction and between student engagement and satisfaction.  flipped Classroom; English Language; HOTS; Engagement; Satisfaction.
Factors Underlying Low Achievement of Saudi EFL Learners

This paper is devoted to examining the factors responsible for the low achievement in English as a foreign language (EFL) among Saudi students. While some of these factors are demographic variables that pertain specifically to the learners themselves, such as gender, age, motivation, attitudes, aptitude, anxiety, autonomy, learning strategies, and learning style, most are external and outside the learners' control. These external factors are particularly represented by sociocultural factors, such as the influence of Arabic as the first language (L1) religion, culture, and society; instructional variables, such as teacher behavior and teaching styles, the curriculum, and the teaching methods; and finally, problems with the educational system in Saudi Arabia, such as overcrowded classes, lack of teacher training, and a lack of technology. This paper begins by emphasizing the importance of English language learning for Saudis, followed by an analysis and a discussion of the factors that might explain their lack of achievement. The paper concludes by presenting some implications and offering recommendations for EFL practitioners and policymakers in the Kingdom of Saudi Arabia (KSA) to address the factors contributing to low EFL achievement among Saudi learners.
aenwkhidaelathRsdiiphuuenthaankaarepnphuunamkh`ngphuubrihaarsthaansueksaaainstwrrsthii 21 Fundamental Concepts and Theories for being Leaders of School Administrators in the 21st century

phbrhaarsthaansksaaykhaihmainstwrrsth 21 ainthaanaepnphnamthm`ththphlt`bkhlaakrphaayainmbthbaatht`kaarkamhndthsthaang noybaay aelanamphaasthaansksaaaipskhwaamsamerccht`ngmkhwaamphr`maindaankhnlksnathoddedn klaawkh`mthksathaangpyyaasng epnnkbrhaarm``aachph mcchtechngsraangsrrkh mecchtkhtthd aelaepnbkhkhlthmwsythsn mkhwaamkhaadhwngsngthmngsraangkhwaamsaaercchkh`ngngaan tl`dcchnphthnaasthaansksaaaihepn`ngkhkraehngkaarerynr aelasraangsthaansksaaaihepn`ngkhkrnwtkrrmykhaihm n`kcchaakn phbrhaarsthaansksaaykhaihmt`ngmbthbaaththsamkhykh` t`ngprbeplynbthbaathcchaakkaarepnphkhwbkhmmaaepnphnamthwaangaenwthaangkaarptbtngaankh`ngbkhlaakr mkhwaamekhaaaicchainkhwaamhlaakhlaaythaangwthnthrrmaelakaarbrhaarcchdkaarechngrk ydhlkkaarmswnrwmprb`ngkhkraihepn`ngkhkaarkhnaadelkaelamokhrngsraangaenwraab aelaesrmsraangkaarmhnswnthaangkaarsksaadngnnphnam`ngkhkrykhaihmainstwrrsth 21 cchngt`ngmkaaraeswnghaakhwaamrthng echngthRst kaarptbtaelaprasbkaarn School administrators of new age in the 21 st century as leaders influencing internal personnel, playing a critical role in determining directions and policy, and taking the institution to achievement must get ready to have the outstanding characteristics, including advanced cognitive skills, professional principalship, creative mind, and good attitudes. They must also possess visions and high expectations seeking for the success, developing the institution as a learning organization, and building the institution as a modern innovative organization. In addition, the administrators of new age must play a significant role in changing from being a controller to being a leader who plans the ways of practice for personnel. They must understand cultural diversity and proactive management, holding the principle of participation. The administrators must adjust the organization to make it small with a flat structure and they must promote the educational partnership. Therefore, the organization leaders of new age in the 21 st century must seek for theoretical, practical, and experiential knowledge.
Business Intelligence and Big Data Analytics for Higher Education: Cases from UK Higher Education Institutions

With the rise of big data, its impact has becoming apparent even in the Higher Education sector. The strategic use and applications of big data in higher education would lead to higher educational quality and better student and staff experience. Using the output from UK JISC's Business Intelligence projects, this paper reviews and outlines eleven cases of big data analytics in the UK Higher Education institutions, followed by presenting one of the projects to demonstrate the application of big data analytics on student engagement. This leads to further research implications for future big data research in Higher Education.