Miracle-dz/UniFAR-FTUs huggingface dataset:
Cloning of Distinct Subtypes From the Internal Thoracic Artery

Vascular smooth muscle cells (SMCs) perform diverse functions and this functional heterogeneity could be based on differential recruitment of distinct SMC subsets. In humans, however, there is little support for such a paradigm, partly because isolation of pure human SMC subsets has proven difficult. We report the cloning of 12 SMC lines from a single fragment of human internal thoracic artery and the elucidation of 2 distinct cellular profiles. Epithelioid clones (n59) were polygonal at confluence, 105 69 mm in length, and had a doubling time of 39 62 hours. Spindle-shaped clones (n53) were larger (267618 mm long, P,0.01) and grew slower (doubling time 654 hours, P,0.01). Both types of clones expressed smooth muscle (SM) a-actin, SM-myosin heavy chains, h-caldesmon, and calponin, but only spindle-shaped clones expressed metavinculin. Epithelioid clones displayed greater proliferation in response to platelet-derived growth factor-BB and fibroblast growth factor-2 and were more responsive to the migratory effect of platelet-derived growth factor-BB. Spindle-shaped clones showed more robust Ca 21 transients in response to angiotensin II, histamine, and norepinephrine, crawled more quickly, and expressed more type I collagen. On serum withdrawal, spindle-shaped clones differentiated into a contraction-competent cell. A regional basis for diversity among SMCs was suggested by stepwise arterial digestion, which liberated small, SM a-actin–positive cells from the abluminal medial layers and larger SMCs from all layers. These results identify inherent SMC diversity in the media of the adult internal thoracic artery and suggest differential participation of SMC subsets in the regulation of human arterial behavior. (Circ Res. 2001;89:517-525.)
Auctions vs. Negotiations in Vertically Related Markets

In a two-tier industry with bottleneck upstream and two downstream firms producing vertically differentiated goods, we identify conditions under which the upstream supplier chooses exclusive or non-exclusive negotiations, or an English auction to sell its essential input. Auctioning off a two-part tariff contract is optimal for the supplier when its bar- gaining power is low and the final goods are not too differentiated. Otherwise, the supplier enters into exclusive or non-exclusive negotiations with the downstream firm(s). Finally, in contrast to previous findings, an auction is never welfare superior to negotiations.
Effects of coat color pattern and sex on physiological traits and heat tolerance of indigenous goats exposed to solar radiation

In this century, climate change is one of the major problems affecting livestock productivity. This study aimed at evaluating the effect of body coat color pattern and sex on heat regulation and heat stress tolerance in indigenous goat breeds exposed to solar radiation. In the experiment, 4 bucks and 4 does (8 to 9 months age) with black, white, grey and brown coat color were selected and exposed to solar radiation during 12 days during the summer period. Water and feed were served add libitum . The consumption were measured daily at 17:00 for each animal. Rectal temperature (RT) and rate pulse (PR) were measured three-time (7:00, 12:00, and 17:00) every day on each animal during the experimental period. At the end of the experiment, blood samples were collected from the jugular vein and immediately delivered to the lab to determine biochemical (serum protein: albumin and globulin), and hematological parameters. Exposing goats to temperature variation affected the physiological, hematological as well as biochemical parameters in all subjects. The female with a black body coat color was mostly affected. The heat stress induced an increase of RT and PR, an increase in water consumption while depression in food intake was observed. Blood platelets, hematocrits, red cell distribution, white blood cell and albumin were damaged in goats with black coat color compared to goats with white coat color. These variations in physiological, hematological and biochemical parameters in female black goat could affect its productive and reproductive performances in high-temperature environments.
Safety and activity of hydroxychloroquine and aldesleukin in metastatic renal cell carcinoma: A cytokine working group phase II study.

4573Background: Aldesleukin (recombinant human interleukin-2, IL-2) has been an FDA-approved treatment for mRCC since 1992 with a 5-10% rate of durable complete response. Hydroxychloroquine (HCQ) i.
Preferences in Learning Styles among Undergraduate Students of Various Disciplines of Education from Selected Indian Universities

Students have different learning styles which can affect the way they learn. In the present scenario, it is vital even for the students to know their own learning style so that they can cope up easily with the learning processes in a comfort zone. Educators have a greater encumbrance to understand the heterogeneity of their students and potentially improve in a variety of ways to accommodate all learners' preferences. The aim of our study was to analyze preferred learning styles among undergraduate students of various disciplines of education. This cross sectional study was conducted in selected Indian universities. Final year students of various disciplines of education who were willing to participate in the study were selected. The demographic details were collected after obtaining their consent for participation. VARK questionnaire was administered to the students in the form of hard copies to analyze their preferred learning styles. Overall, the results revealed that students showed highest preference in kinesthetic learning. Engineering student’s least preferred visual learning in comparison to students of other disciplines. Medical students were less interested in aural and read/write learning than others. Kinesthetic learning is preferred more by medical and dental students than engineering students. All findings were statistically significant at p-value<0.05. Therefore, this study will help in revamping the teaching approaches to suit the students’ preferences so that they feel comfortable in enhancing their learning performance. Key-words: Learning Styles, VARK questionnaire ------------------------------------------------------------------------------------------------------------------------------------Date of Submission: 01-10-2018 Date of acceptance: 16-10-2018 -------------------------------------------------------------------------------------------------------------------------------------
To Mock or Not to Mock? An Empirical Study on Mocking Practices

When writing automated unit tests, developers often deal with software artifacts that have several dependencies. In these cases, one has the possibility of either instantiating the dependencies or using mock objects to simulate the dependencies' expected behavior. Even though recent quantitative studies showed that mock objects are widely used in OSS projects, scientific knowledge is still lacking on how and why practitioners use mocks. Such a knowledge is fundamental to guide further research on this widespread practice and inform the design of tools and processes to improve it. The objective of this paper is to increase our understanding of which test dependencies developers (do not) mock and why, as well as what challenges developers face with this practice. To this aim, we create MockExtractor, a tool to mine the usage of mock objects in testing code and employ it to collect data from three OSS projects and one industrial system. Sampling from this data, we manually analyze how more than 2,000 test dependencies are treated. Subsequently, we discuss our findings with developers from these systems, identifying practices, rationales, and challenges. These results are supported by a structured survey with more than 100 professionals. The study reveals that the usage of mocks is highly dependent on the responsibility and the architectural concern of the class. Developers report to frequently mock dependencies that make testing difficult and prefer to not mock classes that encapsulate domain concepts/rules of the system. Among the key challenges, developers report that maintaining the behavior of the mock compatible with the behavior of original class is hard and that mocking increases the coupling between the test and the production code.
Oxygen Uptake, Carbon Dioxide Production, Minute Ventilation and Heart Rate during Post Exercise Recovery in Healthy and Unmedicated Elderly and Young Men

This study investigated the influence of aging and effort intensity upon oxygen uptake ( 2 VO  ), carbon-dioxide production ( 2 VCO  ), minute ventilation ( E V ) and Heart Rate (HR) during postexercise recovery. Young (YG: n = 16; 24 ± 2 yr) and older (OG: n = 18; 63 ± 1 yr) groups performed cycle ergometer exercise bouts at 100%, 75%, and 40% of maximal work rate, preceded by 30-min resting assessment. Postexercise data were acquired during 15-min passive recovery. In all cases, postexercise recovery was best described by two vs. single exponential equation (0∫ ∞x(t)dt = A/α+ B/β), A/α and B/β constants designating fast and slow components, respectively. On average, the relative contribution of A/α was similar (P > 0.05) across age groups and work rates (YG vs. OG: 2 VO  42% vs. 45%; 2 VCO  38% vs. 39%; E V 26% vs. 27%; HR 15% vs. 16%). The relative contribution of B/β was also similar between age groups (P > 0.05) and increased with exercise intensity (P < 0.05) for 2 VO  (YG vs. OG: Ex100% 69% vs. 69%; Ex75% 56% vs. 50%; Ex40% 48% vs. 47%) and HR (YG vs. OG: Ex100% 93% vs. 92%; Ex40% 69% vs. 63%), but not 2 VCO  and E V . Total recovery was similar in OG and YG for all variables (P > 0.05). However, recovery curves of 2 VCO  , E V and HR lasted longer in OG than YG (P < 0.05). In conclusion, aging did not affect total postexercise recovery or relative contribution of fast or slow components. Exercise intensity but not age prolonged 2 VO  recovery, while slow components of 2 VCO  and E V were longer in OG. HR recovery increased with age and was markedly longer than respiratory variables, particularly among older individuals.
K-Anonymity Enhancement For Privacy Preservation With Hybridization Of Artificial Bee Colony And Neural Network

: The rising popularity of social networks has also raised the risk adjoining the dissemination of the user’s personal information over the network. This has raised the demand of privacy protection. Privacy preservation is the rising issue in the social networks that are the hot spots where information theft instances are very common. The present approach focuses the protection of sensitive information based on k-anonymity. K-anonymity is one of the most popular approaches privileged by graphs and nodes functionality. The proposed study is based on the enhancement of k-anonymity by focusing at node level to address the privacy protection issue. The process involves first identification of sensitive nodes and then applying optimization techniques. At this step, authors have introduced Neural Network (NN) and Artificial Bee Colony (ABC) in order to reduce the node miss placement in the groups. The study is evaluated against k-anonymity on small and larger datasets in terms of average path length and information loss. Comparative analyses have shown APL reduction of 1.636 and 1.371 is achieved using ARNET and SDFB datasets over 900 nodes. Additionally, optimization also resulted in average information loss reduction of 0.57% and 8.95% was observed for small and larger datasets.
Blending Human and Artificial Intelligence to Support Autistic Children’s Social Communication Skills

This article examines the educational efficacy of a learning environment in which children diagnosed with Autism Spectrum Conditions (ASC) engage in social interactions with an artificially intelligent (AI) virtual agent and where a human practitioner acts in support of the interactions. A multi-site intervention study in schools across the UK was conducted with 29 children with ASC and learning difficulties, aged 4–14 years old. For reasons related to data completeness and amount of exposure to the AI environment, data for 15 children was included in the analysis. The analysis revealed a significant increase in the proportion of social responses made by ASC children to human practitioners. The number of initiations made to human practitioners and to the virtual agent by the ASC children also increased numerically over the course of the sessions. However, due to large individual differences within the ASC group, this did not reach significance. Although no evidence of transfer to the real-world post-test was shown, anecdotal evidence of classroom transfer was reported. The work presented in this article offers an important contribution to the growing body of research in the context of AI technology design and use for autism intervention in real school contexts. Specifically, the work highlights key methodological challenges and opportunities in this area by leveraging interdisciplinary insights in a way that (i) bridges between educational interventions and intelligent technology design practices, (ii) considers the design of technology as well as the design of its use (context and procedures) on par with one another, and (iii) includes design contributions from different stakeholders, including children with and without ASC diagnosis, educational practitioners, and researchers.
Remote Sensing Techniques in Archaeology. From Space to Ground Investigation through the Microwave Spectrum: SAR and GPR Detection

The present research deals with the possibility to detect surface and subsurface archaeological structures by means of satellite SAR (Synthetic Aperture Radar) full-polarimetric data of ALOS PALSAR sensor and GPR (Ground Penetrating Radar) prospection of the soil. The archaeological sites of Veio (an Etruscan-Roman site 10 km North of Rome, Italy) and Aquino (an ancient Roman city in the Southern Lazio, Italy) have been selected for the study. The main goal of the research is to find a complementary non – invasive technique for archaeological investigation to be considered as a preliminary step for the detection of ancient structures, possibly to be used before any dig campaign start. The analysis of ALOS PALSAR products has been compared to optical images and to cartographic data as well, and then validated with the GPR prospection, in order to confirm what observed from satellite, both for well known archaeological marks and for assumed underground structures. Ancillary information (meteorological conditions, geologic maps, archaeological maps) and surveys in situ constitute a comprehensive critical and scientific approach for data interpretation. The work, still in progress, aims to define and propose a methodology based on the integration of information extracted from both SAR satellite and ground radar signals over different archaeological landscapes, providing a complete overview of the microwave portion of the spectrum.
A Crisis of Confidence: Adjusting P-Values for Multiple Hypothesis Testing

This paper addresses, perhaps, the most important issue in empirical science today: the ‘replicability crisis’ that arises when using a p value <0.05 in multiple hypothesis testing. To define a ‘crisis’, a benchmark of expected non replication is required and the p value is flawed in this regard. The Non Replication Rate (α*) is the ratio of false positives to all positives rather than false positives to the total number of tests (α). Using Bayes Theorem it is demonstrated that α*=P(H0|D) rather than α = P(D|H0) . The former unlike the latter is actually a test of the null hypothesis. As illustrated through an example in the field of asset pricing, the conventional p value associated with a pre-specified Non Replication Rate (α*) is calculated and used as an adjusted ‘hurdle of significance’ for multiple hypothesis testing.
Diversification in Simulated Food Webs: The Role of Closed Motifs

We allow a simulated food web to self-construct by repeated introduction of predators. Networks start with a source of biomass, and predators choose their prey according to a niche model. Species thrive or go extinct according to a standard predator-prey biomass model. We examine the correlation between structural motifs and the evolution of network architecture. We find two motifs that correlate strongly with network expansion, and we speculate casually but optimistically on implications and further research possibilities.
Expression of Paxillin in Benign and Malignant Salivary Gland Tumors

Statement of the Problem: Paxillin is a major cytoskeletal protein aberrantly deregulated in various human cancers and involved in tumor growth and invasion. However, the clinicopathological and prognostic significance of paxillin in salivary gland tumors (SGTs) is still unclear. Purpose: This study was conducted to evaluate the relationship between paxillin expression and clinicopathological features of patients with SGTs. Materials and Method: In this retrospective study, 50 paraffin-embedded tissue samples which were histologically confirmed as benign (pleomorphic adenoma, PA) or malignant (mucoepidermoid carcinoma (MEC), adenoid cystic carcinoma, ACC) SGTs, and 19 specimens from those with normal salivary gland (NSG) as a control group were assessed for paxillin expression using the immunohistochemistry. The paxillin expression in our samples was scored based on the extent and intensity of immunoreactivity and compared with histological type, clinical stage, and distant metastasis. Results: High paxillin expression was identified in 66% of SGTs whereas all patients with NSG showed low expression (p< 0.0001). Although the expression of paxillin in patients with benign and malignant tumors is similar, there is a significant difference between patients with PA, MEC, and ACC with that of the NSG (p< 0.0001). Paxillin expression was not correlated with clinicopathological features of patients. Conclusion: High expression of paxillin was observed in tumoral tissues compared with the controls that establish an important role of paxillin in SGTs but its prognostic role was unclear and need further evaluation.
SCION’s Hidden Paths Design Formal Security Analysis

When designing complex software architectures, shortcomings concerning its intended security properties are simply to be expected. Fortunately, nowadays we can rely on sophisticated tools to support the formal modeling and analysis of security protocols, which can help to drastically reduce the possibility of real-world attacks on the resulting infrastructure. More precisely, with the use of automated provers, we can obtain formal proofs for all the specific security properties that we are interested in verifying for the message exchanges under analysis. In this thesis, we focus on SCION, a security-first Future Internet architecture developed at ETH Zurich. In particular, we start from an intuition on how to address a lack of server authentication in SCION’s Hidden Paths Design and, from there, we propose a sensible solution to this problem that maximizes the reuse of well established protocols and minimizes the deployment efforts, all while making sure that we are not violating SCION’s architectural principles. Finally, we perform a formal security analysis of our solution by leveraging Tamarin, a state-of-the-art security protocol verification tool that comes with a sound and complete proof search algorithm. In this context, we also explain how our analysis successfully yielded all the results we were hoping for, thus confirming the correctness of our proposed solution and justifying its suitability to be adopted as part of SCION’s specification.
ATMoS: Autonomous Threat Mitigation in SDN using Reinforcement Learning

Machine Learning has revolutionized many fields of computer science. Reinforcement Learning (RL), in particular, stands out as a solution to sequential decision making problems. With the growing complexity of computer networks in the face of new emerging technologies, such as the Internet of Things and the growing complexity of threat vectors, there is a dire need for autonomous network systems. RL is a viable solution for achieving this autonomy. Software-defined Networking (SDN) provides a global network view and programmability of network behaviour, which can be employed for security management. Previous works in RL-based threat mitigation have mostly focused on very specific problems, mostly non-sequential, with ad-hoc solutions. In this paper, we propose ATMoS, a general framework designed to facilitate the rapid design of RL applications for network security management using SDN. We evaluate our framework for implementing RL applications for threat mitigation, by showcasing the use of ATMoS with a Neural Fitted Q-learning agent to mitigate an Advanced Persistent Threat. We present the RL model’s convergence results showing the feasibility of our solution for active threat mitigation.
Pupil Size as a Window on Neural Substrates of Cognition

Cognitively driven pupil modulations reflect certain underlying brain functions. What do these reflections tell us? Here, we review findings that have identified key roles for three neural systems: cortical modulation of the pretectal olivary nucleus (PON), which controls the pupillary light reflex; the superior colliculus (SC), which mediates orienting responses, including pupil changes to salient stimuli; and the locus coeruleus (LC)-norepinephrine (NE) neuromodulatory system, which mediates relationships between pupil-linked arousal and cognition. We discuss how these findings can inform the interpretation of pupil measurements in terms of activation of these neural systems. We also highlight caveats, open questions, and key directions for future experiments for improving these interpretations in terms of the underlying neural dynamics throughout the brain.
Securing Multi-User Broadcast Wiretap Channels With Finite CSI Feedback

In this work, we investigate the problem of secure broadcasting over block-fading wiretap channels with limited channel knowledge at the transmitter. More particularly, we analyze the effect of having a finite rate feedback on the throughput of multi-user broadcast wiretap channels. We consider that the transmitter is only provided by a $b$ -bits feedback of the main channel state information (CSI) sent by each legitimate receiver, at the beginning of each fading block, over error-free public links with limited capacity. Also, we assume that the transmitter is aware of the statistics of the eavesdropper’s CSI but not of its channel’s realizations. Under these assumptions of CSI uncertainty, we characterize the ergodic secrecy capacity of the system when a common message is broadcasted to all legitimate receivers, the ergodic secrecy sum-capacity when multiple independent messages are transmitted, and the ergodic secrecy capacity region for the broadcast channel with confidential messages (BCCM). In all three scenarios, we show that as long as the transmitter has some knowledge of the main CSI, obtained even through a 1-bit CSI feedback, a non-zero secrecy rate can still be achieved. The impact of having the feedback sent over a binary erasure channel (BEC) is also investigated for the BCCM case. Here again, and even with the possibility of having the feedback bits erased, a positive secrecy rate can still be achieved as long as the erasure event is not a probability-one event. An asymptotic analysis of the obtained results is provided for the high SNR regime, and the scaling law of the system, when the number of legitimate receivers is large, is also presented.