Miracle-dz/UniFAR-FTUs huggingface dataset:
Can mental health problems predict dispositional self-determination? Needs satisfaction as mediator

Motivational self-determination and its role in relation to various health-related variables in Western countries have been the focus of many researchers. However, little is known about dispositional self-determination and the influence of mental health problems among the Chinese. We examined dispositional self-determination among Chinese first-year college students and tested whether or not mental health problems could predict self-determination through needs satisfaction. Data were collected from 496 students at 2 time periods. Results showed that there was no difference in dispositional self-determination among the various demographic groups. However, participants whose university experience met their expectations reported a higher degree of self-determination than did those who had found it did not meet their expectations. Structural equation modeling results revealed that mental health problems at Time 1 could negatively predict self-determination at Time 2. This relationship was partially mediated by needs satisfaction measured at Time 2. Practical implications and limitations are discussed.
Bacterial Cinnamoyl Esterase Activity Screening for the Production of a Novel Functional Food Product

ABSTRACT Lactobacillus helveticus MIMLh5 was selected for its strong cinnamoyl esterase activity on chlorogenic acid and employed for the preparation of a food product containing a high concentration of free caffeic acid. The novel food product was demonstrated to display high total antioxidant power and potential probiotic properties.
Evaluation of a Decentralized Architecture for Large Scale Collaborative Intrusion Detection

An important problem in network intrusion detection is how to detect large scale coordinated attacks such as scans, worms and denial-of-service attacks. These coordinated attacks can be difficult to detect at an early stage, since the evidence of the attack may be widely distributed across different subnetworks in the Internet. A critical issue for research is how to detect these large scale attacks by correlating information from multiple intrusion detection systems in an efficient manner. Several collaborative detection systems have been proposed in the literature. However, these proposals have lacked large scale testing in real networks, and the practicalities of how to optimize the trade-off between detection accuracy and reaction time of these systems has not been demonstrated. To address these challenges, we propose LarSID, a scalable decentralized large scale intrusion detection framework. LarSID provides a service for defending against attacks by sharing potential evidence of intrusions between participant intrusion detection systems via a distributed hash table (DHT) architecture. In particular, we investigate how to optimize the trade-off between detection accuracy and reaction time of LarSID based on an analysis of a large, real-world intrusion detection dataset (DShield Dataset), which has been collected from over 1600 firewall administrators across the world. LarSID has been deployed and tested on the PlanetLab testbed, and is built on top of OpenDHT - a public DHT service. Our experimental results show significant reductions in detection latency compared to a centralized detection architecture. Currently, LarSID has been deployed on 128 PlanetLab nodes as a large scale intrusion detection service.
The impact of improved irrigation systems on water scarcity and sustainable development

The completion of this thesis would not have been possible if it wasn’t for my caring supervisor Professor Adel Beshai. It has been an honor to be his student and I have benefited greatly from his knowledge and support. I also want to thank my readers Professors Samir Makary and Mohamed Bouaddi. Thank you for making it possible for me to master my topic, for teaching me and for your time and effort. It is truly an honor to have such great professors taking part of this research. I owe great gratitude to Professor Ahmed Kamaly for helping me take the right path and cross over from writing a course paper to starting a thesis topic. Thank you for your guidance, patience and support. I am in debited to thank every great professor I had the chance to be their student. Thank you for enlightening me. I want to thank Mrs. Amira Bishara, Mrs. Nancy and Mrs. Heba Halim for all the help, assistance and advising they granted. I have found my passion in economics thanks to my first undergraduate economics professor, Professor Hala El Hadidy. Thanks to my family, friends and work colleagues and superiors for giving me the strength to get where I am and motivating me to follow my dreams.
Creating Advantages with Franchising in Healthcare: An Explorative Mixed Methods Study on the Role of the Relationship between the Franchisor and Units

Background Franchising is a promising and increasingly used organizational form to improve strategic, organizational, professional and client-related results in healthcare. However, evidence is scarce regarding how franchises should be operated to actualize such results. This paper aimed to explore the association between the results achieved by healthcare franchises and the working relationships among actors in these franchises. Methods A sequential mixed methods approach was used to obtain both in-depth and broader quantifiable insights into a little-investigated phenomenon. We first employed a qualitative multiple embedded case study. Data were collected through observations, document analyses, and 96 in-depth semi-structured interviews in three Dutch healthcare franchises. Within-case and cross-case comparative analyses were conducted. Subsequently, a cross-sectional survey was developed based on the qualitative study and disseminated among 19 healthcare franchises. 40 franchisors and 346 unit actors filled in the questionnaire. Findings It seems important to have open, committed, cooperative franchise relationships in which professional franchisees and unit managers feel and trust that they have the opportunity to introduce ideas and articulate their needs to the franchisor. Such relationships help ensure satisfaction, survival, and quality of care, because they serve to foster synergy realization and local fit and prevent reinventing the wheel and professional resistance.
Simultaneous X-Ray and Gamma-Ray Observations of TeV Blazars: Testing Synchro-Compton Emission Models and Probing the Infrared Extragalactic Background

The last years have seen a revolution in ground-based γ-ray detectors. We can now detect the spectra of nearby TeV blazars like Mrk 421 and Mrk 501 out to ~20 TeV, and during the strongest flares, we can now follow fluctuations in these spectra on timescales close to the shortest ones likely in these objects. We point out that this represents a unique opportunity. Using these and future detectors in combination with broadband X-ray satellites like BeppoSAX and Rossi X-Ray Timing Explorer, we will be able to simultaneously follow all significant X-ray/γ-ray variations in a blazar's emission. This will provide the most stringent test yet of the synchrotron-Compton emission model for these objects. In preparation for the data to come, we present sample synchrotron self-Compton model calculations using a fully self-consistent, accurate code to illustrate the variability behavior one might see and to show how good timing information can probe physical conditions in the source. If the model works, i.e., if X-ray/TeV variations are consistent with being produced by a common electron distribution, then we show it is possible to robustly estimate the blazar's intrinsic TeV spectrum from its X-ray spectrum. Knowing this spectrum, we can then determine the level of absorption in the observed spectrum. Constraining this absorption, which is due to γ-ray pair production on diffuse radiation, provides an important constraint on the infrared extragalactic background intensity. Without the intrinsic spectrum, we show that detecting absorption is very difficult and argue that Mrk 421 and Mrk 501, as close as they are, may already be absorbed by a factor 2 at ~3 TeV. This should not be ignored when fitting emission models to the spectra of these objects.
Decitabine reactivated pathways in platinum resistant ovarian cancer

Combination therapy with decitabine, a DNMTi and carboplatin resensitized chemoresistant ovarian cancer (OC) to platinum inducing promising clinical activity. We investigated gene-expression profiles in tumor biopsies to identify decitabine-reactivated pathways associated with clinical response. Gene-expression profiling was performed using RNA from paired tumor biopsies before and 8 days after decitabine from 17 patients with platinum resistant OC. Bioinformatic analysis included unsupervised hierarchical-clustering, pathway and GSEA distinguishing profiles of “responders” (progression-free survival, PFS>6months) and “non-responders” (PFS<6months). Functional validation of selected results was performed in OC cells/tumors. Pre-treatment tumors from responders expressed genes associated with enhanced glycosphingolipid biosynthesis, translational misregulation, decreased ABC transporter expression, TGF-β signaling, and numerous metabolic pathways. Analysis of post-treatment biopsies from responders revealed overexpression of genes associated with reduced Hedgehog pathway signaling, reduced DNA repair/replication, and cancer-associated metabolism. GO and GSEA analyses revealed upregulation of genes associated with glycosaminoglycan binding, cell-matrix adhesion, and cell-substrate adhesion. Computational findings were substantiated by experimental validation of expression of key genes involved in two critical pathways affected by decitabine (TGF-β and Hh). Gene-expression profiling identified specific pathways altered by decitabine and associated with platinum-resensitization and clinical benefit in OC. Our data could influence patient stratification for future studies using epigenetic therapies.
Aging Algorithm for Anthropometric Digital Humans: Quantitative Estimation for Ergonomic Applications

This paper introduces an approach to estimate the effect of aging on surface anthropometry, articulation limits and physical strength for digital humans at joint level. By making use of an anthropometric database, physical characteristic database and prioritized Inverse Kinematics architecture, the developed simulation system could be a core engine for ergonomic analysis at the conceptual design stage of a product development cycle. The proposed system could be an efficient tool for helping designers more quickly and easily identify ergonomic flaws. The results have been validated with real human subjects indicating the practical implication of the total system as an ergonomic design tool.
Putative Role of Prostaglandin Receptor in Intracerebral Hemorrhage

Each year, approximately 795,000 people experience a new or recurrent stroke. Of all strokes, 84% are ischemic, 13% are intracerebral hemorrhage (ICH) strokes, and 3% are subarachnoid hemorrhage strokes. Despite the decreased incidence of ischemic stroke, there has been no change in the incidence of hemorrhagic stroke in the last decade. ICH is a devastating disease 37–38% of patients between the ages of 45 and 64 die within 30 days. In an effort to prevent ischemic and hemorrhagic strokes we and others have been studying the role of prostaglandins and their receptors. Prostaglandins are bioactive lipids derived from the metabolism of arachidonic acid. They sustain homeostatic functions and mediate pathogenic mechanisms, including the inflammatory response. Most prostaglandins are produced from specific enzymes and act upon cells via distinct G-protein coupled receptors. The presence of multiple prostaglandin receptors cross-reactivity and coupling to different signal transduction pathways allow differentiated cells to respond to prostaglandins in a unique manner. Due to the number of prostaglandin receptors, prostaglandin-dependent signaling can function either to promote neuronal survival or injury following acute excitotoxicity, hypoxia, and stress induced by ICH. To better understand the mechanisms of neuronal survival and neurotoxicity mediated by prostaglandin receptors, it is essential to understand downstream signaling. Several groups including ours have discovered unique roles for prostaglandin receptors in rodent models of ischemic stroke, excitotoxicity, and Alzheimer disease, highlighting the emerging role of prostaglandin receptor signaling in hemorrhagic stroke with a focus on cyclic-adenosine monophosphate and calcium (Ca2+) signaling. We review current ICH data and discuss future directions notably on prostaglandin receptors, which may lead to the development of unique therapeutic targets against hemorrhagic stroke and brain injuries alike.
A Three-Layer Approach to Semistructured DataAndr

The eld of semistructured data arises from the fact that the amount of data available and the variety of representations has grown tremendously over the past couple of years. We propose a graph-based three-layer model for querying semistructured data. The bottom layer consists of syntactically well-formed objects, the middle layer of diierent sorts of schemata and the top layer of the database-related constructs such as queries. For the middle layer we suggest predicate and path schemata. These schema sorts serve as the basis for the queries. The modularity of the approach and the more direct relationship between schema and query lead to more exibility and interactivity when moving from content-based to structure-based data handling, which is to us the core issue of semistructured data.
A kind of universal constructor method for buffer operator

In this paper, according to the data sequence of system behavior {x(k)}<inf>k=1</inf><sup>n</sup> and a set of data {y(k)}<inf>k=1</inf><sup>n</sup> satisfying y(n) = x(n), the authors prove that there always exists a buffer operator D satisfying XD={x(k)d}<inf>k=1</inf><sup>n</sup>, which can provide a specific constructor method of buffer operator. Finally, the axiom of invariable trend is proposed to add in the axiom systems of buffer operator.
Tree-Based Partitioning Approach for Network-on-Chip Synthesis

Since most System-on-Chips (SoCs) consist of heterogeneous IP core(s), application-specific Network on Chip (NoC) architectures are appropriate to meet the design requirements. The energy and performance optimization in the NoC design will continue to be the main design goal in nanoscale technologies. In this paper, we present a new hierarchal partitioning approach considering not only the reduction of wire length among cores, but also the optimization of switching power consumption subject to performance constraints. The experimental results on different benchmarks showed that our NoC topology synthesis algorithm can effectively save power and improve performance.
Dissolution of Platinum in the Operational Range of Fuel Cells

Abstract One of the most important practical issues in low‐temperature fuel‐cell catalyst degradation is platinum dissolution. According to the literature, it initiates at 0.6–0.9 VRHE, whereas previous time‐ and potential‐resolved inductively coupled plasma mass spectrometry (ICP–MS) experiments, however, revealed dissolution onset at only 1.05 VRHE. In this manuscript, the apparent discrepancy is addressed by investigating bulk and nanoparticulated catalysts. It is shown that, given enough time for accumulation, traces of platinum can be detected at potentials as low as 0.85 VRHE. At these low potentials, anodic dissolution is the dominant process, whereas, at more positive potentials, more platinum dissolves during the oxide reduction after accumulation. Interestingly, the potential and time dissolution dependence is similar for both types of electrode. Dissolution processes are discussed with relevance to fuel‐cell operation and plausible dissolution mechanisms are considered.
The Rodney L. White Center for Financial Research Variable Selection for Portfolio Choice

We study asset allocation when the conditional moments of returns are partly predictable. Rather than rst model the return distribution and subsequently characterize the portfolio choice, we determine directly the dependence of the optimal portfolio weights on the predictive variables. We combine the predictors into a single index that best captures time-variations in investment opportunities. This index helps investors determine which economic variables they should track and, more importantly, in what combination. We consider investors with both expected utility (mean-variance and CRRA) and non-expected utility (ambiguity aversion and prospect theory) objectives and characterize their market-timing, horizon e ects, and hedging demands. We thank John Campbell, George Constantinides, David Chapman, Frank Diebold, Han Hong, Paul P eiderer, Jessica Wachter, and especially Anthony Lynch for their comments and suggestions. We also thank seminar participants at the 2001 Annual Meeting of the American Finance Association, Columbia University, Harvard University, MIT, NYU, Princeton University, Stanford University, and the University of Chicago. This research was conducted during the rst author's tenure as an Alfred P. Sloan Research Fellow. Financial support from the NSF under grant SBR-9996023, the Bendheim Center for Finance at Princeton University, and the Rodney White Center at the Wharton School is gratefully acknowledged. Princeton, NJ 08544-1021. Phone: (609) 258-4015. E-mail: yacine@princeton.edu. Philadelphia, PA 19104-6367. Phone: (215) 898-3609. E-mail: brandtm@wharton.upenn.edu. The latest revision of this paper is available at: http://brandt.wharton.upenn.edu
The self regulating star formation of gas rich dwarf galaxies in quiescent phase

The expected episodic or intermittent star formation histories (SFHs) of gas rich dwarf irregular galaxies (dIrrs) are the longstanding puzzles to understand their whole evolutional history. Solving this puzzle, we should grasp what physical mechanism causes the quiescent phase of star formation under the very gas rich condition after the first starburst phase. We consider that this quiescent phase is kept by lack of ${\rm H_2}$, which can be important coolant to generate the next generation of stars in the low-metal environment like dIrrs. Furthermore, in dIrrs, ${\rm H_2}$ formation through gas-phase reactions may dominate the one on dust-grain surfaces because their interstellar medium (ISM) are very plentiful and the typical dust-to-gas ratio of dIrrs ($D_{{\rm dIrrs}} = 1.31$ $\times$ $10^{-2}\,D_{{\rm MW}}$, where $D_{{\rm MW}}$ is its value for the local ISM) is on the same order with a critical value $D_{{\rm cr}} \sim 10^{-2}\,D_{{\rm MW}}$. We show that the lack of ${\rm H_2}$ is mainly led by ${\rm H^-}$ destruction when gas-phase ${\rm H_2}$ formation dominates since ${\rm H^-}$ is important intermediary of gas-phase ${\rm H_2}$ formation. ${\rm H^-}$ is destroyed by the radiation from all stars born in the previous starburst phase because ${\rm H^-}$ destroying infrared photon can penetrate the whole ISM of dIrrs. Considering the physical process which timescale is the longest as main process in regulating global star formation, we can show this lack of ${\rm H_2}$ leads the quiescent phase of star formation. Hence, we can say that the stellar radiation which destroys ${\rm H^-}$ and leads low ${\rm H_2}$ abundance should be properly treated in studying SFHs of dIrrs.
Changes in Expression of Genes Regulating Airway Inflammation Following a High-Fat Mixed Meal in Asthmatics

Consumption of a high fat meal can increase neutrophilic airway inflammation in asthma subjects. This study investigates the molecular mechanisms driving airway neutrophilia following a high fat meal in asthmatics. Subjects with asthma (n = 11) and healthy controls (n = 8) consumed a high-fat/energy meal, containing total energy (TE) of 3846 kJ and 48 g of total fat (20.5 g saturated). Sputum was induced at 0 and 4 h, and gene expression was examined by microarray and quantitative real-time PCR (qPCR). Following the high fat dietary challenge, 168 entities were significantly differentially expressed greater than >1.5 fold in subjects with asthma, whereas, in healthy controls, only 14 entities were differentially expressed. Of the 168 genes that were changed in asthma, several biological processes were overrepresented, with 25 genes involved in “immune system processes”. qPCR confirmed that S100P, S100A16, MAL and MUC1 were significantly increased in the asthma group post-meal. We also observed a strong correlation and a moderate correlation between the change in NLRP12 and S100A16 gene expression at 4 h compared to baseline, and the change in total and saturated non-esterified plasma fatty acid levels at 2 h compared to baseline. In summary, our data identifies differences in inflammatory gene expression that may contribute to increased airway neutrophilia following a high fat meal in subjects with asthma and may provide useful therapeutic targets for immunomodulation. This may be particularly relevant to obese asthmatics, who are habitually consuming diets with a high fat content.
Compressive sensing of digital sparse signals

This paper discusses compressive sensing with digital sparse signals. The motivation is that most existing sparse signal recovery algorithms, like matching pursuit, convex relaxation and Bayesian framework, do not fully exploit the digital nature of signals when dealing with digital sparse signals, which result in certain performance losses. In this paper, we solve this problem via a permutation-based multi-dimensional sensing matrix and an iterative recovery algorithm with maximum likelihood (ML) local detectors. The sensing matrix considered consists of several sub-matrices, each composed of a random permutation matrix and a block-diagonal matrix. The measurements generated from the same permutation matrix are referred to as a dimension. The block-diagonal matrices allow the use of the low-complexity ML detector in each dimension, which best utilizes the digital nature of signals. The multi-dimensional structure of the sensing matrix enables information exchange between dimensions through an iterative process to achieve a near global-optimal estimation. Numerical results are used to show the rate-distortion performance of the proposed technique. It is shown that it can achieve much better rate-distortion than the existing approaches based on convex relaxation and Bayesian framework with digital source signals.
Secure time synchronization protocols for wireless sensor networks

Time synchronization is essential in wireless sensor networks as it is needed by many applications for basic communication. The inherent characteristics of sensor networks do not permit simply applying traditional time synchronization algorithms. Therefore, many new time synchronization algorithms have been proposed, and a few of them provide security measures against various degrees of attacks. In this article we review the most commonly used time synchronization algorithms and evaluate these algorithms based on factors such as their countermeasures against various attacks and the types of techniques used.
Testing Stationarity With Surrogates: A Time-Frequency Approach

An operational framework is developed for testing stationarity relatively to an observation scale, in both stochastic and deterministic contexts. The proposed method is based on a comparison between global and local time-frequency features. The originality is to make use of a family of stationary surrogates for defining the null hypothesis of stationarity and to base on them two different statistical tests. The first one makes use of suitably chosen distances between local and global spectra, whereas the second one is implemented as a one-class classifier, the time- frequency features extracted from the surrogates being interpreted as a learning set for stationarity. The principle of the method and of its two variations is presented, and some results are shown on typical models of signals that can be thought of as stationary or nonstationary, depending on the observation scale used.