Miracle-dz/UniFAR-FTUs huggingface dataset:
A comparative study between the correlation of the in silico and in vitro hydrolysis of whey proteins: Discovery of potential new antimicrobial peptides

Milk proteins are the principal source of bioactive peptides encrypted within primary amino acid sequence, which can be released by digestive enzymes (both in vivo, during gastrointestinal transit, or in vitro), fermentation or ripening during food processing to achieve their specific bioactive roles (Korhonen & Pihlanto 2006; Benkerroum 2010; Chakrabarti et al. 2014). Some of these peptides have been shown to possess antihypertensive, antibacterial, antioxidant, immunomodulatory and opioid-like properties (da Costa et al. 2007; López-Expósito et al. 2007; Pihlanto 2006; Gauthier et al. 2006; Mizuno et al. 2005). Despite the notable success of lactoferricin (LFcin) and kappacin, few studies have addressed the antimicrobial properties of peptides released from dairy proteins by enzymatic hydrolysis (Florisa et al. 2003; Clare et al. 2003; Kamau et al. 2010). In response to the changing mindset of consumers, who demand more products without chemical additives, the research for new antimicrobial peptides (AMPs) to be used as food-grade biopreservatives or as health-promoting food supplements is increasing (Théolier et al. 2014). A second driving force for research on AMPs is the increasing resistance to conventional antibiotics. In fact, the majority of AMPs present similar physicochemical properties with conventional antibiotics, including small molecular size and cationic and Abstract
SODA: A Generic Online Detection Framework for Smart Contracts

—Smart contracts have become lucrative and profitable targets for attackers because they can hold a great amount of money. Unfortunately, existing ofﬂine approaches for discovering the vulnerabilities in smart contracts or checking the correctness of smart contracts cannot conduct online detection of attacking transactions. Besides, existing online approaches only focus on speciﬁc attacks and cannot be easily extended to detect other attacks. Moreover, developing a new online detection system for smart contracts from scratch is time-consuming and requires deep understanding of blockchain internals, thus making it difﬁcult to quickly implement and deploy mechanisms to detect new attacks. In this paper, we propose a novel generic online detection framework named SODA for smart contracts on any blockchains that support Ethereum virtual machine (EVM). SODA distinguishes itself from existing online approaches through its capability, efﬁciency, and compatibility. First, SODA empowers users to easily develop apps for detecting various attacks online (i.e., when attacks happen) by separating information collection and attack detection with layered design. At the higher layer, SODA provides uniﬁed interfaces to develop detection apps against various attacks. At the lower layer, SODA instruments EVM to collect all primitive information necessary to detect various attacks and constructs 11 kinds of structural information for the ease of developing apps. Based on SODA , users can develop new apps in a few
The Happiness Gap: The Impact of Governance on Wellbeing

Can governance impact directly on well-being? In this paper we examine subjective well-being (SWB) as measured by both life satisfaction and happiness using the World Values data set. We then also analyse the differences between these two measures, what we term the happiness gap which is further linked to an „aspirations gap‟. Significant determinants of this include settlement size, marital status, income, unemployment and being part of a linguistic minority/majority grouping. Satisfaction with the state of democracy and the way the country is being run are also both significant. The use of the happiness gap as the dependent variable rather than happiness or satisfaction per se reduces potential problem of simultaneity. Finally, we disaggregate the functions looking at SWB for men and women separately, for the poor and rich and finally for poor and rich countries.
Overview of some Contribution for Business Intelligence research

Summary. In the last years Prof. Lenz has contributed a lot of work on Business Intelligence. This articles tries to give a short overview of selected papers. Since 1975 Hans-J. Lenz published more than 350 scientiﬁc books, papers and reports. A brief overview on the work on Business Intelligence is given in this article. Corresponding to the structure of this book the following articles are outlined.
A Computational Framework for Revealing Competitive Travel Times with Low-Carbon Modes Based on Smartphone Data Collection

Evaluating potential of shifting to low-carbon transport modes requires considering limited travel-time budget of travelers. Despite previous studies focusing on time-relevant modal shift, there is a lack of integrated and transferable computational frameworks, which would use emerging smartphone-based high-resolution longitudinal travel datasets. This research explains and illustrates a computational framework for this purpose. The proposed framework compares observed trips with computed alternative trips and estimates the extent to which alternatives could reduce carbon emission without a significant increase in travel time. The framework estimates potential of substituting observed car and public-transport trips with lower-carbon modes, evaluating parameters per individual traveler as well as for the whole city, from a set of temporal and spatial viewpoints. The illustrated parameters include the size and distribution of modal shifts, emission savings, and increased active-travel growth, as clustered by target mode, departure time, trip distance, and spatial coverage throughout the city. Parameters are also evaluated based on the frequently repeated trips. We evaluate usefulness of the method by analyzing door-to-door trips of a few hundred travelers, collected from smartphone traces in the Helsinki metropolitan area, Finland, during several months. The experiment’s preliminary results show that, for instance, on average, 20% of frequent car trips of each traveler have a low-carbon alternative, and if the preferred alternatives are chosen, about 8% of the carbon emissions could be saved. In addition, it is seen that the spatial potential of bike as an alternative is much more sporadic throughout the city compared to that of bus, which has relatively more trips from/to city center. With few changes, the method would be applicable to other cities, bringing possibly different quantitative results. In particular, having more thorough data from large number of participants could provide implications for transportation researchers and planners to identify groups or areas for promoting mode shift. Finally, we discuss the limitations and lessons learned, highlighting future research directions.
Nachzucht und Larvalentwicklung der Sulu-Seenadel Dunckerocampus pessuliferus, einschließlich eines Überblicks über die aktuelle Zoopopulation: Ein Ansatz in Richtung nachhaltige Bestände in Menschenhand

As guideline for increased Dunckerocampus breeding, based on D. pessuliferus as husbandry analogue, we oppose husbandry management, captive reproduction and larval development of the species in the State Museum of Natural History Karlsruhe, Germany, and in the Aquarium of the Cologne Zoo, Germany. We observed mating, during which eggs were attached to the male, lasting up to an hour. Juveniles hatched after eight days at sizes of 4-5 mm. Adult color pattern developed after three weeks and maturity was reached after six months, at total sizes of 10.5-11 cm. We present survival rates and provide recommendations for optimum feeding. We further performed a ZIMS (Zoological Information Management System) database analysis (in October 2016 and May 2018) and observed a recent increase in the keeping of D. pessuliferus *Corresp. Author: E-Mail: ziegler@koelnerzoo.de (Thomas Ziegler) 8 J. Kirchhauser et al. · Breeding and larval development of Dunckerocampus pessuliferus with currently nine institutions in a global scale (fi ve of them being in Europe) holding this species (with 43 individuals in total). As not all zoos enter their collection data into ZIMS, we also checked the website “Zootierliste” (http://www.zootierliste.de/) for locating additional species holdings in Germany and other countries in Europe, however, which also includes private zoos and animal rescue facilities. Entries on the website “Zootierliste” from May 2018 showed a total of 17 European institutions holding D. pessuliferus: In total ten institutions in Germany and seven institutions in different European countries. Six of the listed institutions from Germany and other European countries were not included in ZIMS. According to ZIMS, only two further species of the seven currently recognized Dunckerocampus species are held in zoos globally: D. dactyliophorus with 70 individuals distributed among 16 zoos in North America (10), Europe (5), and Africa (1), and D. multiannulatus with 4 individuals in only one institution in Europe. We emphasize the importance of breeding efforts of not yet or so far only rarely bred marine fi sh species as well as improved exchange of knowledge and available zoo stock between institutions including publication of husbandry management and breeding successes for more sustainable aquaristics.
Leptin concentrations in African Blacks with Metabolic Syndrome and Type 2 diabetes mellitus

Background: Mortality rate from metabolic/cardiometabolic syndromes (MS/CMS) and type 2 diabetes mellitus (DM2) are highly prevalent in African blacks known with higher mortality from cardiovascular diseases than caucasians. Leptin, a satiety-regulating hormone increases in obesity and is associated with cardiovascular risk and prediction of MS. This study is designed to evaluate leptin in Nigerians with MS and DM2 to assist in the early diagnosis and prevention of metabolic diseases. Methods: 136 participants (45 with MS, 47 with DM2 and 44 apparently healthy individuals (controls)) aged 18-80 years were included in a cohort study at the University College Hospital, Ibadan. Measures of adiposity-%body fat, body mass index (BMI), waist and hip circumferences (WC and HC respectively), waist to hip ratio (WHR), and blood pressure were obtained by standard methods. 10 ml of blood were obtained from each participant after an overnight fast (10-14 h) and analysed for leptin, total cholesterol (TC), triglycerides (TG), high density lipoprotein (HDL), and glucose by standard methods while low density lipoprotein (LDL) was calculated. Data obtained were analysed statistically with SPSS software version 16.0. Results: Weight, BMI, WC, HC, WHR, %body fat, blood pressure, TG, LDL-C, and glucose were significantly higher while HDL-C was significantly lower in individuals with MS and DM2 compared with controls (p<0.039). Leptin levels were significantly higher in MS group and not in DM2 group when compared with controls (p=0.000). Leptin did not correlate with any of the biochemical indices (p>0.05) tested but correlated significantly with different measures of adiposity in all groups. Leptin correlated negatively but significantly with blood pressure in MS group only. Conclusion: Increases in leptin levels in both MS and DM2 groups might reflect adiposity. Observed high leptin levels in MS group might be a compensatory mechanism for maintenance of weight/fat loss and blood pressure. Its routine analysis may assist in assessing adiposity associated with MS and DM2 for probable prevention of metabolic diseases.
Economic Perspectives on Utah Medicaid Reform under the ACA

Executive Summary . 2 Broadening the Scope of Inquiry . 3 The essentials of cost‐benefit analysis. 3 Uncertainties. 8 Unintended consequences . 9 Moral, legal, and political considerations. 10 Health Economics and the ACA . 11 Income and the demand for health insurance & medical care . 11 Incentives in health care and insurance markets . 15 Distributional Consequences of Medicaid Expansion . 23 External Effects of Medicaid Expansion. 25 Concluding Comments. 29 References . 31
7 Link-based Classification

Summary. A key challenge for machine learning is the problem of mining richly structured data sets, where the objects are linked in some way due to either an explicit or implicit relationship that exists between the objects. Links among the objects demonstrate certain patterns, which can be helpful for many machine learning tasks and are usually hard to capture with traditional statistical models. Recently there has been a surge of interest in this area, fuelled largely by interest in web and hypertext mining, but also by interest in mining social networks, bibliographic citation data, epidemiological data and other domains best described using a linked or graph structure. In this chapter we propose a framework for modeling link distributions, a link-based model that supports discriminative models describing both the link distributions and the attributes of linked objects. We use a structured logistic regression model, capturing both content and links. We systematically evaluate several variants of our link-based model on a range of data sets including both web and citation collections. In all cases, the use of the link distribution improves classiﬁcation performance.
Dialogue Model and Response Generation for Emotion Improvement Elicitation

As the technology develops, the potential of agents to improve the emotional-well being of users has been growing as well. Emotional support through human-computer interactions (HCI) has the potential advantage of being ubiquitous, round-the-clock, and accessible. However, existing works which address user emotion are still performed in a restrictive manner and bound to an oversimpliﬁed view of the emotional processes. In this paper, we build upon the existing works on positive emotion elicitation and extend them towards emotion processing through an entirety of a dialogue. The contribution of this paper is three-fold: 1) We construct a corpus of spontaneous human conversation carefully designed to highlight emotion improvement elicitation common in day-to-day situations. 2) We analyze the aforementioned corpus to ﬁnd a shared dialogue structure representing the cognitive process underlying emotional changes and how it takes place in dialogue. 3) We apply this model in a dialogue system framework using a hybrid n-gram and neural network approach.
When Participatory Design Becomes Policy: Technology Comprehension in Danish Education

While several studies have addressed the challenge of sustaining PD initiatives over time and supporting large-scale participatory processes, little is known about how PD and ideals fare on a national scale. We examine the process in which outcomes from a PD project were used and implemented as part of a mandatory course in Technology Comprehension in K9 education, commissioned by the Danish Ministry of Education. Our study is based on interviews with 12 people from the Danish educational sector, ranging from schoolteachers to the Minister of Education. Our findings demonstrate that while knowledge generated in a PD project can travel to the level of national policy, significant challenges emerge when outcomes from bottom-up PD is used in top-down policy. We conclude the paper by reflecting on how PD is equipped to create impact through policy.
Dynamically Evolving, Large-scale Information Systems

PageRank-style authority analyses of Web graphs are of great importance for Web mining. Such authority analyses also apply to hot “Web 2.0” applications that exhibit a nat-ural graph structure, such as social networks (e.g., MySpace, Facebook) or tagging communities (e.g., Flickr, Del.icio.us). Finding the most trustworthy or most important authorities in such a community is a pressing need, given the huge scale and also the anonymity of social networks. Computing global authority measures in a Peer-to-Peer (P2P) collaboration of autonomous peers is a hot research topic, in particular because of the incomplete local knowledge of the peers, which typically only know about (arbitrarily overlapping) sub-graphs of the complete graph. We demonstrate a self-organizing P2P collaboration that, based on the local sub-graphs, eﬃciently computes global authority scores. In hand with the loosely-coupled spirit of a P2P system, the computation is carried out in a completely asynchronous manner without any central knowledge or coordinating instance. We demonstrate the applicability of authority analyses to large-scale distributed systems.
Dynamically Evolving, Large-scale Information

We consider the well-known vertex coloring problem: given a graph G , (cid:2)nd a coloring of the vertices so that no two neighbors in G have the same color. It is trivial to see that every graph of maximum degree (cid:1) can be colored with (cid:1)+1 colors, and distributed algorithms that (cid:2)nd a ((cid:1)+1) - coloring in a logarithmic number of communication rounds, with high probability, are known since more than a decade. This is in general the best possible if only a constant number of bits can be sent along every edge in each round. In fact, we show that for the n -node cycle the bit complexity of the coloring problem is (cid:10)(log n ) . More precisely, if only one bit can be sent along each edge in a round, then every distributed coloring algorithm (i.e., algorithms in which every node has the same initial state and initially only knows its own edges) needs at least (cid:10)(log n ) rounds, with high probability, to color the cycle, for any (cid:2)nite number of colors. But what if the edges have orientations, i.e., the end-points of an edge agree on its orientation (while bits may still (cid:3)ow
Liquefaction analysis of undrained cyclic tests by calibration of constitutive models

liquefaction analysis poses constitutive and numerical challenges. This work presents a calibration of constitutive models capable of reproducing liquefaction: UBC3D, Hypoplastic for sand and PM4Sand. Simulation is done with the Soil Test tool, implemented in the finite element program Plaxis, based on cyclic direct simple shear tests on Fraser River Sand. Different vertical pressures and initial densities are studied. All three models show pore pressure build-up and reach liquefaction state. In this text, some parameters are modified to accurately reproduce the experimental response. However, a unique set of parameters should be used for different applied pressures and initial densities.
Caspar: Extracting and Synthesizing User Stories of Problems from App Reviews

A user's review of an app often describes the user's interactions with the app. These interactions, which we interpret as mini stories, are prominent in reviews with negative ratings. In general, a story in an app review would contain at least two types of events: user actions and associated app behaviors. Being able to identify such stories would enable an app's developer in better maintaining and improving the app's functionality and enhancing user experience. We present Caspar, a method for extracting and synthesizing user-reported mini stories regarding app problems from reviews. By extending and applying natural language processing techniques, Caspar extracts ordered events from app reviews, classifies them as user actions or app problems, and synthesizes action-problem pairs. Our evaluation shows that Caspar is effective in finding action-problem pairs from reviews. First, Caspar classifies the events with an accuracy of 82.0% on manually labeled data. Second, relative to human evaluators, Caspar extracts event pairs with 92.9% precision and 34.2% recall. In addition, we train an inference model on the extracted action-problem pairs that automatically predicts possible app problems for different use cases. Preliminary evaluation shows that our method yields promising results. Caspar illustrates the potential for a deeper understanding of app reviews and possibly other natural language artifacts arising in software engineering.
Differential Effectiveness of Three Therapeutic Packages in Fostering Adolescents’ Intrapersonal Relationship

This study investigated the effect of Enhanced Thinking Skills, Rational Emotive Behaviour Therapy and Social Skills programs in fostering intrapersonal relationship among Nigerian adolescents. A quasi experimental research design of 3x2x2 factorial matrix type was used for this study. The study participants were 216 Senior Secondary 1 and 2 students randomly selected from 3 coeducational secondary schools from three different Local Government Areas in Remo educational block of Ogun State, Nigeria. Two standardized instrument was used in collecting data while analysis of covariance was used to analyze the generated data. Results show that all the treatment packages (F (2,212) = 7.089; p = . 005) were effective in improving adolescents’ intrapersonal relationship while REBT was found to be most effective. Based on the findings; it was recommended that the treatment packages could be used as veritable tools in equipping adolescents with necessary skills to help the youths live a worthy life.
UCSD MOLECULE PAGES BARD1

BARD1 was originally identified as a protein interacting with BRCA1, the breast cancer predisposition gene product. BARD1, like BRCA1, has an amino-terminal RING-finger domain and carboxy-terminal BRCT domains. In addition, BARD1 has three ankyrin repeats adjacent to the BRCT domains. BARD1 and BRCA1 form a stable heterodimer via their RING-finger domains. BRCA1, like many RING-finger proteins, has E3 ubiquitin ligase activity, which is amplified when in association with BARD1. By contrast, BARD1 alone has no such activity. The binding of BARD1 to BRCA1 stabilizes BRCA1 and, to some extent, BARD1. BARD1 and BRCA1 are co-expressed in most proliferating tissues and are localized to the nucleus. Based mostly on its ubiquitin ligase activity, the BARD1/BRCA1 complex has functions in DNA repair, transcriptional regulation, chromatin condensation, cell-cycle regulation, mitotic spindle formation and cytokinesis. BARD1 is highly conserved, having orthologs in many species. In mice, BARD1 has essential functions during development, and Bard1-null mice, like Brca1-null mice, die between embryonic days 7 and 8, suggesting that the defect is caused by the lack of a functional BARD1/BRCA1 heterodimer. Whereas only a few somatic and germline mutations of BARD1 have been found associated with breast, ovarian and endometrial cancer, nine commonly found alleles of BARD1 that contain single nucleotide polymorphisms have been found to be significantly associated with childhood neuroblastoma. In breast and ovarian cancers, truncated forms of BARD1 derived by differential RNA splicing are highly upregulated and are localized to the cytoplasm. The expression of these BARD1 isoforms in breast and ovarian cancer is correlated with a poor prognosis.
A Survey on Students’ Preference in Knowledge Sharing Tools to Support Learning in Higher Education

—Knowledge sharing tools is among the technologies that play important role in institutions as it enables them to leverage knowledge management solutions. The aim of this study is to determine the preference of students in higher education toward Knowledge sharing tools to support their learning. A research questionnaire was used to collect data from the respondents whereby both online and offline were deployed. A total of 287 responses were analyzed using SPSS v20 in which descriptive statistic was used in data analysis. The outcome revealed majority of the students prefer features such as Search engine, Instant Messaging and e-mail, Online Group Discussion, Electronic Documents (e-books, journals, projects etc), Tutorials, and News and adverts of the Knowledge sharing tools higher than others. Similarly, Feedback, Video Conferencing, Blog, and Content/lesson creation have a significant role in sharing of knowledge. The least preferred features of Knowledge sharing tools are Help desk (care lines), Audio Conferencing, Web Conferencing, and Instructional games. 