Miracle-dz/UniFAR-FTUs huggingface dataset:
Cytochrome P450 Expression of Cultured Rat Small Hepatocytes after Long-Term Cryopreservation

Small hepatocytes (SHs) are hepatic progenitor cells that can be cryopreserved for a long time. After thawing, the cells can proliferate and, when treated with Matrigel, they can differentiate into mature hepatocytes (MHs). In this study, we investigated whether cryopreserved SHs could express cytochromes P450 (P450s), whether P450 expression was induced by appropriate inducers, and whether P450 activities were measurable. 3-Methylcholanthrene (3-MC), phenobarbital (PB), pregnenolone-16α-carbonitrile (PCN), and ethanol were used as inducers for CYP1A, 2B, 3A, and 2E, respectively. Immunoblot analysis indicated that cryopreserved SHs constitutively expressed CYP1A1/2, CYP2E1, and CYP3A2 as much as 26 days after plating. Significant expression of CYP1A1/2 and 3A2 in the cells treated with Matrigel was induced by 3-MC and PCN, respectively. Although Matrigel did not up-regulate the enzymatic activity of CYP1A, CYP3A and CYP2E activities increased. Induction of CYP1A and CYP3A activities by each inducer was observed in cryopreserved cells treated with Matrigel. Although the expression of CYP2B1 could be detected in subcultured SHs treated with PB, it was not detected in cryopreserved SHs. The activity of NADPH-cytochrome P450 reductase was measured in both subcultured and cryopreserved SHs, although the activities in both were approximately 30% of that of MHs. Profiles of 14C-testosterone metabolites were examined in cultured MHs and in cryopreserved SHs by high-performance liquid chromatography. Similar peaks for testosterone metabolites in MHs and SHs were observed in the same elution time. These results indicate that, although induction of CYP3A and 2B in cryopreserved SHs is inferior to that in subcultured ones, SHs can maintain the expression and activities of P450s after long-term cryopreservation.
Addressing the Same but different - different but similar problem in automatic music classification

We present a hybrid method in which we classify music from a raw audio signal according to their spectral features, while maintaining the ability to assess similarities between any two pieces in the set of analyzed works. First we segment the audio file into discrete windows and create a vector of triplets respectively describing the spectral centroid, the short-time energy function, and the short-time average zero-crossing rates of each window. In the training phase these vectors are averaged and charted in three-dimensional space using k-means clustering. In the test phase each vector of the analyzed piece is considered in terms of its proximity to the graphed vectors in the training set using k-Nearest Neighbor method. For the second phase we apply Foote's (1999) similarity matrix to retrieve the similar content of the music structures between two members in the database.
Parents’ Choices and Rationales for Alternative Vaccination Schedules

Background. A growing number of parents adopt alternative vaccination schedules for their children. A better understanding of parents’ rationales for these choices is needed to guide vaccine decision making. Methods. We conducted 24 semistructured telephone interviews with parents of 12- to 36-month-olds and analyzed data using an inductive approach. Results. We identified 5 alternative vaccination approaches: “Dr Sears” schedule, shot-limiting approach, selective delay or decline, visit-by-visit decisions, and refusal of all vaccines. Parents who adopted alternative approaches expressed a desire for more control of exposure to vaccine ingredients; vaccine safety, immune system burden, and perceived disease risk were articulated as concerns. Conclusions. Parents who adopt alternative vaccination schedules can be classified in defined subgroups based on their decision-making approaches, and many describe considered reasons to support their actions. Communications that acknowledge and address those reasons may be better able to engage parents and ultimately enhance the process of decision making about vaccines.
Evaluating a Simple Method for Estimating Black-White Gaps in Median Wages

Racial differences in wage rates are important measures of economic inequality among races because, for almost all individuals, labor income constitutes the most important component of lifetime income. As a consequence, the prices at which individuals may sell their time provide vital infornation about the distribution of welfare and economic success. However, we only observe prices when market transactions occur, and thus we only observe wage rates for individuals who are employed. Since the wages of employed workers are not randomly sampled from the distribution of potential wages, it is difficult to draw inferences concerning racial gaps in potential wages from data on observed wage rates. Richard Butler and James Heckman (1977) raised this issue in the context of assessing the impact of government policies on racial income inequality. Charles Brown (1984), James Smith and Finis Welch (1989), and Amitabh Chandra (2000) also examine the extent of racial differences in participation rates and the impact of these differences on measures of racial wage and income gaps. This topic remains salient, in part, because employment rates among working-age black males remain significantly below corresponding rates for whites. Neal and Johnson (1996) estimated racial gaps in median wages among men by imputing wages of zero for all men in a particular crosssection who report that they have not worked at all during the survey period. Under a specific assumption concerning the distribution of missing wages, this procedure yields consistent estimates of the black-white gap in median wages conditional on observed characteristics. Below, we spell out this assumption and use panel data to investigate the extent to which it may be violated in cross-section wage analyses. Our results suggest that imputing wages of zero for unemployed individuals may provide a reasonable way to estimate median wage regressions among men.
Employee Proactivity in Organizations: A Comparative Meta-Analysis of Emergent Proactive Constructs

This meta-analysis of 103 independent samples provides a comparative evaluation of the relationships associated with four emergent proactive constructs including proactive personality, personal initiative, voice, and taking charge. This study investigates comparative relationships among these focal proactive constructs and key organizational variables (i.e., job performance), personality traits (i.e., the Big Five), and individual variables (i.e., work experience). Results reveal significant correlations between proactivity and performance, satisfaction, affective organizational commitment, and social networking. Results also provide evidence that differentiates focal proactive constructs from the Big Five as well as individual differences in work experience, age, and general mental ability. Current progress towards a more integrative understanding of proactivity research is discussed.
Discussion Paper Series Quantile regression with clustered data

We show that the quantile regression estimator is consistent and asymptotically normal when the error terms are correlated within clusters but independent across clusters. A consistent estimator of the covariance matrix of the asymptotic distribution is provided and we propose a specification test capable of detecting the presence of intra-cluster correlation. A small simulation study illustrates the finite sample performance of the test and of the covariance matrix estimator. JEL classification code: C12, C21, C23.
Comparing static and dynamic measurements and models of the Internet's AS topology

Capturing a precise snapshot of the Internet's topology is nearly impossible. Recent efforts have produced autonomous-system (AS) level topologies with noticeably divergent characteristics, even calling into question the widespread belief that the Internet's degree distribution follows a power law. In turn, this casts doubt on Internet modeling efforts, since validating a model on one data set does little to ensure validity on another data set, or on the (unknown) actual Internet topology. We examine six metrics-three existing metrics and three of our own-applied to two large publicly-available topology data sets. Certain metrics highlight differences between the two topologies, while one of our static metrics and several dynamic metrics display an invariance between the data sets. Invariant metrics may capture properties inherent to the Internet and independent of measurement methodology, and so may serve as better gauges for validating models. We continue by testing nine models-seven existing models and two of our own-according to these metrics applied to the two data sets. We distinguish between growth models that explicitly add nodes and links over time in a dynamic process, and static models that add all nodes and links in a batch process. All existing growth models show poor performance according to at least one metric, and only one existing static model, called Inet, matches all metrics well. Our two new models-growth models that are modest extensions of one of the simplest existing growth models-perform better than any other growth model across all metrics. Compared with Inet, our models are very simple. As growth models, they provide a possible explanation for the processes underlying the Internet's growth, explaining, for example, why the Internet's degree distribution is more skewed than baseline models would predict
Grafting of discontinuous sites: a protein modeling strategy.

A strategy for modeling continuous as well as discontinuous sites in protein structures has been developed. Central to this modeling strategy is the search algorithm of FITSITE, a program to search a given target structure for suitable combinations of backbone positions mirroring as closely as possible the geometric relationships of a source structural motif of interest. All target sites detected by FITSITE are further refined to mimic the source geometry. The sidechain rotamer library concept fails to precisely describe side chains involved in coordinative bonding (e.g, metal binding sites). Therefore an algorithm using detailed data-base bonding parameter information was applied for the side-chain construction. The FITSITE program and the subsequent processing of the program output are presented in a test case. The Rop protein, a four-helix bundle structure, served as the target protein. It was searched for candidate sites to model a variety of metal binding sites, with structures extracted from Brookhaven Protein Database entries. The preliminary protein models were investigated for structural overlaps with neighboring residues by interactive computer graphics; if required, additional changes were performed. A set of parameters for energy minimization with AMBER (including metal ions) was developed, and the completed Rop variants were energy minimized. Finally, 12 potentially metal binding Rop variants were selected for production via genetic engineering.
Post-Golgi anterograde transport requires GARP-dependent endosome-to-TGN retrograde transport

GARP (tethering factor)- and VAMP4 (v-SNARE)-dependent endosome-to-TGN retrograde transport is required for the efficient post-Golgi anterograde transport of cell-surface integral membrane proteins. Golgi-resident membrane proteins TMEM87A and TMEM87B are involved in endosome-to-TGN retrograde transport.
Zigzag persistent homology in matrix multiplication time

We present a new algorithm for computing zigzag persistent homology, an algebraic structure which encodes changes to homology groups of a simplicial complex over a sequence of simplex additions and deletions. Provided that there is an algorithm that multiplies two n×n matrices in M(n) time, our algorithm runs in O(M(n) + n2 log2 n) time for a sequence of n additions and deletions. In particular, the running time is O(n2.376), by result of Coppersmith and Winograd. The fastest previously known algorithm for this problem takes O(n3) time in the worst case.
Mimicking human strategies in fighting games using a Data Driven Finite State Machine

Multiplayer fighting videogames have become an increasingly popular over the last few years, especially with the introduction of online play, making for a more competitive experience. Multiplayer fighting games give players the opportunity to utilize particular strategies and tactics to win, allowing them to use their own signature style. As a player can only play against a particular opponent who is actively participating in the game themselves, they cannot practice combating the opponent's style if the opponent is not participating in the game. This paper presents a novel approach for an avatar to learn and mimic the style of a player. It does this by recording and analyzing the data before splitting it up into two tiers; tactical data and strategic data. The approach uses a Naïve Bayes classifier to classify the tactics to particular states, and a Data Driven Finite State Machine to dictate when certain tactics are used. Statistics recorded during an experiment involving the approach are discussed, which indicate that the architecture of the Artificial Intelligence is fit for purpose, but does require refinement. Limitations of the architecture are discussed, including that such an approach may not provide accurate results when more parameters are considered.
The influence of the number of presented symptoms in product-claim direct-to-consumer advertising on behavioral intentions

Purpose – In order to improve the effectiveness of product‐claim direct‐to‐consumer advertising (DTCA), the current research examines the effect of a presentational element – the number of treatable symptoms for the advertised medical condition featured in the ad – on consumers' intentions to seek treatment.Design/methodology/approach – Ninety‐five participants recruited at a mall in the northeastern US provided data on behavioral and attitudinal intentions regarding a product‐claim print DTCA for an antidepressant.Findings – Featuring a high (vs low) number of symptoms improved the effectiveness of the product‐claim DTCA. Seeing more symptoms led to heightened perceptions of informativeness, lower persuasive intent, and higher intentions to discuss the advertised ailment and the advertised drug with the doctor. Perceptions of disease prevalence mediated this influence. The perceived impact of each symptom featured in the DTCA was controlled across experimental conditions.Research limitations/implications.
Coping strategies and collective efficacy as mediators between stress appraisal and quality of life among rescue workers.

Fire-fighters, paramedics, and emergency medical technicians routinely confront potentially traumatic events in the course of their jobs. The mediation role of coping strategies and collective efficacy in the relationship between stress appraisal and quality of life was examined (compassion satisfaction, compassion fatigue, and burnout) in a correlational study. Participants were 463 Italian rescue workers (fire fighters and different categories of emergency health care professionals). Participants filled out measures of stress appraisal, collective efficacy, coping strategies, and quality of life. The results showed that emotion and support coping, self-blame coping, and self-distraction mediated the relationship between stress appraisal and compassion fatigue. Moreover, collective efficacy, self-blame coping, and religious coping mediated the relationship between stress appraisal and burnout. Finally, collective efficacy, self-blame coping, and problem-focused coping mediated the relationship between stress appraisal and compassion satisfaction. Cognitive restructuring and denial did not mediate the relation between stress appraisal and any of the quality of life dimensions.
Predicting source code changes by mining revision history

Software developers are often faced with modification tasks that involve source which is spread across a code base. Some dependencies between source, such as the dependencies between platform dependent fragments, cannot be determined by existing static and dynamic analyses. To help developers identify relevant source code during a modification task, we have developed an approach that applies data mining techniques to determine change patterns—files that were changed together frequently in the past—from the revision history of the code base. Our hypothesis is that the change patterns can be used to recommend potentially relevant source code to a developer performing a modification task. We show that this approach can reveal valuable dependencies by applying the approach to the Eclipse and Mozilla open source projects, and by evaluating the predictability and interestingness of the recommendations produced.
A Functional Framework to Evade Network IDS

Signature based Network Intrusion Detection Systems (NIDS) apply a set of rules to identify hostile traffic in network segments. Currently they are so effective detecting known attacks that hackers seek new techniques to go unnoticed. Some of these techniques consist of exploiting network protocols ambiguities. Nowadays NIDS are prepared against most of these evasive techniques, as they are recognized and sorted out. The emergence of new evasive forms may cause NIDS to fail. In this paper we present an innovative functional framework to evade NIDS. Primary, NIDS are modeled accurately by means of Genetic Programming (GP). Then, we show that looking for evasions on models is simpler than directly trying to understand the behavior of NIDS. We present a proof of concept showing how to evade a self-built NIDS regarding two publicly available datasets. Our framework can be used to audit NIDS.
The impact of binge watching on memory and perceived comprehension

Binge watching via video-on-demand services is now considered the new ‘normal’ way to consume television programs. In fact, recent surveys suggest upwards of 80 percent of consumers prefer and indulge in binge watching behavior. Despite this, there is no evidence regarding the impact of binge watching on the enjoyment of and memory for viewed content. In this, the first empirical and controlled study of its kind, we determined that, although binge watching leads to strong memory formation immediately following program viewing, these memories decay more rapidly than memories formed after daily- or weekly-episode viewing schedules. In addition, participants in the binge watching condition reported significantly less show enjoyment than participants in the daily- or weekly-viewing conditions — though, important considerations with regards to this finding are discussed. Although it is a preferred viewing style catered to by many internet-based on-demand distribution companies, binge watching does not appear to benefit sustained memory of viewed content and may affect show enjoyment.
A 60-GHz Phase-Locked Loop with Inductor-Less Wide Operation Range Prescaler in 90-nm CMOS

A 60-GHz phase-locked loop (PLL) with an inductor-less prescaler is fabricated in a 90-nm CMOS process. The inductor-less prescaler has a smaller chip area than previously reported ones. The PLL operates from 61 to 63GHz and consumes 78mW from a 1.2V supply. The phase noise at 100kHz and 1MHz offset from carrier are -72 and -80dBc/Hz, respectively. The prescaler occupies 80 × 40µm2. The active area of the PLL is 0.31mm2.
Measuring Outcomes of Living-Learning Programs: Examining College Environments and Student Learning and Development

The National Study of Living-Learning Programs (NSLLP) survey instrument was designed to assess college environments and student learning and development outcomes associated with participation in living-learning programs. Data from the NSLLP show that students in living-learning programs demonstrate higher self-reported engagement and outcomes than students in traditional residence hall environments.
Disability and employment policy in the Israeli welfare state: between exclusion and inclusion

Based on the social model(s) of disability, this article seeks to analyse the historical development of Israeli employment policy toward disabled people during the first decade and a half of its existence (1948–1965). Findings from primary and secondary sources suggest that throughout this period disabled people, mainly immigrants, found themselves at the lowest echelons of Israeli society and the labour market. Furthermore, the Israeli welfare state offers an interesting case study of the gap between a welfare state’s stated adherence to social justice and the more limited, and even contradictory, outcomes of its policies. Our discussion suggests that a valuable way of reframing our findings can be found in the critique of de-commodification as an inadequate concept and in the use of related concepts such as re-commodification and quasi-commodification.
Strategies for using podcasting to support student learning.

The growth of podcasting since its incarnation in 2004 has been phenomenal. Within popular culture, podcasting has become an innovative way of broadcasting information on a range of subjects, from news-based items to comedy sketches. However, within an educational context, podcasting offers innovative and creative opportunities for academics to further support learning. The study reports upon the practice-based work that has been done on a level one undergraduate module “The Tourism Society”, where podcasting has been embedded within the weekly sessions. Enhanced podcasts, which in addition to audio recordings also incorporate images and reference material, have been developed to further engage students with the subject material. The study analyses the use of podcasting within education and proposes strategies for developing podcasts to support student learning.
Timing error handling on CGRAs

Error-detection sequential (EDS) circuits are used to detect timing errors in electronic systems. This paper presents an EDS circuit that avoids the generation of false error signals on a coarse grained reconfigurable architecture (CGRA). In a first step we analyzed the timing error handling mechanism of EDS circuits and formulated - based on that analysis - the conditions that must be satisfied for EDS circuits to accomplish the avoidance of false error signals. In a second step we constructed an EDS circuit by means of these theoretical results and integrated this EDS circuit in a CGRA. Finally, we tested the CGRA by SPICE simulations. These simulations confirm that our EDS circuit implementation avoids false error signal generation on a CGRA.
Telecommunication systems enabling real time navigation

Traffic is one of the most important problems in industrialized countries: roads are getting more and more crowded, especially during rush hours, with heavy consequences on people's quality of life, accidents, pollution, and fuel consumption. The transmission of up-to-date traffic information to on-board navigators would allow the redistribution of traffic flows over alternative routes, thus reducing road congestions and slowdowns. In this paper we investigate the possibility to send the information on the average-speed in any road of interest to on-board navigators by means of current broadcast and unicast communication technologies. A discussion on the most convenient transmission strategy will also be given with reference to real scenarios.