Miracle-dz/UniFAR-FTUs huggingface dataset:
A Motivation-Aware Approach for Point of Interest Recommendations

Most existing context aware recommender systems primarily use a combination of ratings data, content data like features or attributes of the product or service, context data like location or time and social network data. In this paper, we propose a novel approach for refining the recommendations made by locationaware recommender systems based on user motivations for checking in at locations in location based social networks. Based on a classification that classifies user’s motivation for checking in at a Point Of Interest into seven categories we propose an approach that will help refine recommendations in a way that can be better explained to the user. We also show the applicability of our approach by analyzing a dataset extracted from Foursquare.
Kernel principal component analysis from a data modelling point of view

I show an example of how the principal component analysis met hod can be used for solving a specific computer vision problem—the one of fitting an ellipse to a set of points . In the example, the feature map is given(postulated) as part of the problem specification. More generally, the fea tur map in the kernel principal component analysis has the interpretation of the model class in data modelling p roblems. This interpretation relates the kernel selection problem in machine learning to the model selection problem i n system identification. Data fitting by a second order model Consider the second order model B(A,b,c) := {d ∈ R | dAd+bd+c= 0} ⊂ R, with A = A (1) and define a parameter vector θ := col(a11,a12,a22,b1,b2,c) ∈ R. Any θ ∈ R6 corresponds to a second order model in R2, defined by (1), and vice verse, to any second order model in R2 there is a nonunique parameter vector θ ∈ R6, such that the model is (1). It can be verified that B(A,b,c) = {d ∈ R | θΦ(d) = 0} =: B(θ), where Φ(d) := col(d1d1,2d1d2,d2d2,d1,d2,1). (2) Note thatB(θ) = B(αθ) for anyα 6= 0, so that the parameter θ is unique only up to a multiplication by a nonzero constant. The considered data fitting problem is to find a second order mo del that best matches a set of given points D = {d, . ,d} ⊂ R in the sense of minimization of the fitting criterion
Architecture for a Next-Generation GCC

This paper presents a design and implementation of a whole-program interprocedural optimizer built in the GCC framework. Through the introduction of a new languageindependent intermediate representation, we extend the current GCC architecture to include a powerful mid-level optimizer and add linktime interprocedural analysis and optimization capabilities. This intermediate representation is an SSA-based, low-level, strongly-typed, representation which is designed to support both efficient global optimizations and highlevel analyses. Because most of the program is available at link-time, aggressive “wholeprogram” optimizations and analyses are possible, improving the time and space requirements of compiled programs. The final proposed organization of GCC retains the important features which make it successful today, requires almost no modification to either the frontor back-ends of GCC, and is completely compatible with user makefiles.
Interactive modelling from sketches using spherical implicit functions

We present an interactive modelling technique, which reconstructs three-dimensional objects from user-drawn two-dimensional strokes. We first extract a skeleton from the 2D contour, and the skeleton is used to define an implicit surface that fits the 2D contour. The reconstructed 3D shape has a natural aspect, it is very smooth and can easily be edited and modified using strokes or performing operations on the skeleton. This method is very accessible for non-specialist users and it allows fast and easy shape prototyping.
Direct Heuristic Algorithms of Possibilistic Clustering Based on Transitive Approximation of Fuzzy Tolerance

This paper deals with the problem of a heuristic approach to possibilistic clustering. The approach is based on the concept of allotment among fuzzy clusters. The paper provides the description of basic concepts of the heuristic approach to possibilistic clustering. Plans of direct prototype-based heuristic algorithms of possibilistic clustering based on a transitive approximation of a fuzzy tolerance are described in detail. An illustrative example of application of the basic version of the proposed algorithms to Sneath and Sokal's two- dimensional data set is considered. Preliminary conclusions are formulated.
A user-mode port of the Linux kernel

The Linux kernel has been ported so that it runs on itself, in a set of Linux processes. The result is a user space virtual machine using simulated hardware constructed from services provided by the host kernel. A Linux virtual machine is capable of running nearly all of the applications and services available on the host architecture. This paper describes the capabilities of a user-mode virtual machine, the design and implementation of the port, some of the applications that it lends itself to, and some of the work that remains to be done.
Current path in light emitting diodes based on nanowire ensembles

Light emitting diodes (LEDs) have been fabricated using ensembles of free-standing (In, Ga)N/GaN nanowires (NWs) grown on Si substrates in the self-induced growth mode by molecular beam epitaxy. Electron-beam-induced current analysis, cathodoluminescence as well as biased μ-photoluminescence spectroscopy, transmission electron microscopy, and electrical measurements indicate that the electroluminescence of such LEDs is governed by the differences in the individual current densities of the single-NW LEDs operated in parallel, i.e. by the inhomogeneity of the current path in the ensemble LED. In addition, the optoelectronic characterization leads to the conclusion that these NWs exhibit N-polarity and that the (In, Ga)N quantum well states in the NWs are subject to a non-vanishing quantum confined Stark effect.
A Comprehensive Study on Willingness Maximization for Social Activity Planning with Quality Guarantee

Studies show that a person is willing to join a social group activity if the activity is interesting, and if some close friends also join the activity as companions. The literature has demonstrated that the interests of a person and the social tightness among friends can be effectively derived and mined from social networking websites. However, even with the above two kinds of information widely available, social group activities still need to be coordinated manually, and the process is tedious and time-consuming for users, especially for a large social group activity, due to complications of social connectivity and the diversity of possible interests among friends. To address the above important need, this paper proposes to automatically select and recommend potential attendees of a social group activity, which could be very useful for social networking websites as a value-added service. We first formulate a new problem, named Willingness mAximization for Social grOup (WASO). This paper points out that the solution obtained by a greedy algorithm is likely to be trapped in a local optimal solution. Thus, we design a new randomized algorithm to effectively and efficiently solve the problem. Given the available computational budgets, the proposed algorithm is able to optimally allocate the resources and find a solution with an approximation ratio. We implement the proposed algorithm in Facebook, and the user study demonstrates that social groups obtained by the proposed algorithm significantly outperform the solutions manually configured by users.
Symptom Burden, Medication Detriment, and Support for the Use of the 15D Health-Related Quality of Life Instrument in a Chronic Pain Clinic Population

Chronic noncancer pain is a prevalent problem associated with poor quality of life. While symptom burden is frequently mentioned in the literature and clinical settings, this research highlights the considerable negative impact of chronic pain on the individual. The 15D, a measure of health-related quality of life (HRQOL), is a user-friendly tool with good psychometric properties. Using a modified edmonton symptom assessment scale (ESAS), we examined whether demographics, medical history, and symptom burden reports from the ESAS would be related statistically to HRQOL measured with the 15D. Symptom burden, medication detriment scores, and number of medical comorbidities were significant negative predictors of 15D scores with ESAS symptom burden being the strongest predictor. Our findings highlight the tremendous symptom burden experienced in our sample. Our data suggest that heavier prescription medication treatment for chronic pain has the potential to negatively impact HRQOL. Much remains unknown regarding how to assess and improve HRQOL in this relatively heterogeneous clinical population.
A Computational Framework for Boundary-Value Problem Based Simulations

A framework is presented for step-by-step imple mentation of weighted-residual methods (MWR) for simulations that require the solution of boundary-value problems. A set of MATLAB-based functions of the computationally common MWR solution steps has been developed and is used in the application of eigenfunction expansion, collo cation, and Galerkin-projection discretizations of time-dependent, distributed-parameter system models. Four industrially relevant examples taken from electronic materials and chemical processing applications are used to demonstrate the simula tion approach developed. This library of functions and several demonstration scripts can be obtained from the MWRtools project Website located at http://www.ench. umd.edu/software/MWRtools.
Empathy as a foot in the inter-ethnic door: Facilitation of positive bilateral perception among Jewish and Arab students in Israel

A heavy load of blame, hostility, and violence typifies the relationships between Jews and Arabs in Israel for nearly two centuries in a row. The present study is an exploratory experimental attempt, within the framework of Functional Measurement, to examine the viability of empathy as a means to facilitate a positive shift in functional cognitive schemata of helping. The participants, 143 Jewish and Arab (57 and 86, respectively) female students, were sampled from an Israeli academic college, where the Jews-Arabs ratio is nearly 50-50. Each Participant met individually 4-8 times, once a week, with a same sex and same age experimenter (another student). Each experimental session included a conversation where the experimenter approached the participant empathetically for approximately 15-20 minutes and asked her repeatedly to imagine a series of meetings between two female students (Jews and Arabs in all combinations) where one such protagonist attempts to receive form the other (Jew or Arab) lesson notes. This manipulation was arranged within the framework of a bi-factorial model, that isi.e. , the level of needs of both protagonists (3 x 3). In each such encounter the participant was asked to estimate the likelihood that the imagined request will be fulfilled. The results show that serial exposure to empathy affected positively mainly Jewish students. The relevance of the findings to the notion of 'functional social cognition' and to the body of knowledge which deals with majority-minority relations is pointed at.
Exponential Synchronization of Linearly Coupled Neural Networks With Impulsive Disturbances

This brief investigates globally exponential synchronization for linearly coupled neural networks (NNs) with time-varying delay and impulsive disturbances. Since the impulsive effects discussed in this brief are regarded as disturbances, the impulses should not happen too frequently. The concept of average impulsive interval is used to formalize this phenomenon. By referring to an impulsive delay differential inequality, we investigate the globally exponential synchronization of linearly coupled NNs with impulsive disturbances. The derived sufficient condition is closely related with the time delay, impulse strengths, average impulsive interval, and coupling structure of the systems. The obtained criterion is given in terms of an algebraic inequality which is easy to be verified, and hence our result is valid for large-scale systems. The results extend and improve upon earlier work. As a numerical example, a small-world network composing of impulsive coupled chaotic delayed NN nodes is given to illustrate our theoretical result.
New graph-based text summarization method

The exponential growth of text data on the World Wide Web as well as on databases off line created a critical need for efficient text summarizers that significantly reduce its size while maintaining its integrity. In this paper, we present a new multigraph-based text summarizer method. This method is unique in that it produces a multi-edge-irregular-graph that represents words occurrence in the sentences of the target text. This graph is then converted into a symmetric matrix from which we can produce the ranking of sentences and hence obtain the summarized text using a threshold. To test our method performance, we compared our results with those from the most popular publicly available text summarization software using a corpus of 1000 samples from 6 different applications: health, literature, politics, religion, science and sports. The simulation results show that the proposed method produced better or comparable summaries in all cases. The proposed method is fast and can be implement for real time summarization.
Priority-Based Inter-Vehicle Communication for Highway Safety Messaging Using IEEE 802.11e

We propose to use IEEE 802.11e in conjunction with retransmission mechanisms for priority-based Intervehicle Communication (IVC) for highway safety messaging in both vehicular infrastructure and ad hoc networks. Each IVC message, which is assigned a priority based on the safety event urgency, requires different quality of service in terms of communication reliability and average delay. To increase the communication reliability in a broadcast-based IVC, we apply retransmission mechanisms that can provide proportional reliability differentiation for each prioritized message. We evaluate the performance of our proposed protocol using OPNET Modeler, in terms of percentage of successful transmissions and average delay. The protocol performance is evaluated for (1) different system parameters such as the packet size, number of vehicles, and percentage of priority 1 vehicles, and (2) priority-based protocol parameters, such as contention window, interframe spacing and retransmission parameters. The results show that proper protocol parameter settings per priority message result in an efficient solution for priority based broadcast IVC. Moreover, the proposed protocol is fully compatible with both IEEE 802.11 and IEEE 802.11e standards.
Semantic Integration of Heterogeneous Information Sources Using a Knowledge-Based System

A growing number of decision support applications require the ability to formulate ad hoc queries that access information from heterogeneous information sources. The Boeing Company recently conducted a study to investigate the feasibility of applying a highperformance knowledge base to interface the information sources to the decision support system. A commercially available knowledge-based development environment provided a number of useful features for this problem including an expressive knowledge representation language, an efficient inference engine, and a large repository of common-sense knowledge. Our objectives were to determine if the pre-stored knowledge would significantly reduce the time required for knowledge engineering in large scale applications, to determine if the domain model was expressive enough to support the wide range of ad-hoc queries typical of our applications, and to determine if the common-sense knowledge would extend the inference power beyond simply combining information from the available data sources. Our preliminary results indicate that the upper and middle ontologies do in fact provide a significant knowledge infrastructure that facilitates creation of the domain model. We were able to express a large fraction of the domain in terms of existing concepts with simple extensions. The existing knowledge about human activities, spatial and temporal concepts, and physical and functional decomposition both simplified the generation of the domain model and supported a wide range of ad hoc queries. The knowledge representation language was relatively easy to acquire and the domain models we created are readily extensible.
Crosstalk between Akt/GSK3β signaling and dynamin‐1 regulates clathrin‐mediated endocytosis

Clathrin‐mediated endocytosis (CME) regulates signaling from the plasma membrane. Analysis of clathrin‐coated pit (CCP) dynamics led us to propose the existence of a rate‐limiting, regulatory step(s) that monitor the fidelity of early stages in CCP maturation. Here we show that nascent endocytic vesicles formed in mutant cells displaying rapid, dysregulated CME are defective in early endosomal trafficking, maturation and acidification, confirming the importance of this “checkpoint. ” Dysregulated CME also alters EGF receptor signaling and leads to constitutive activation of the protein kinase Akt. Dynamin‐1, which was thought to be neuron specific, is activated by the Akt/GSK3β signaling cascade in non‐neuronal cells to trigger rapid, dysregulated CME. Acute activation of dynamin‐1 in RPE cells by inhibition of GSK3β accelerates CME, alters CCP dynamics and, unexpectedly, increases the rate of CCP initiation. CRISPR‐Cas9n‐mediated knockout and reconstitution studies establish that dynamin‐1 is activated by Akt/GSK3β signaling in H1299 non‐small lung cancer cells. These findings provide direct evidence for an isoform‐specific role for dynamin in regulating CME and reveal a feed‐forward pathway that could link signaling from cell surface receptors to the regulation of CME.
Stimulatory and inhibitory effects of genistein on human uterine leiomyoma cell proliferation are influenced by the concentration.

BACKGROUND Due to dietary exposure of women to genistein, a soy-derived phytoestrogen, and the estrogen responsiveness of uterine leiomyomas 'fibroids', we evaluated the effects of genistein (0.001-50 microg/ml) on human uterine leiomyoma (UtLM) cells versus uterine smooth muscle cells (UtSMCs) in vitro. METHODS Light microscopy was used to determine the effects of genistein on cell morphology. Proliferation was assessed using a colorimetric assay and proliferating cell nuclear antigen (PCNA) immunocytochemistry. Flow cytometry was used to quantitate cells in the S-phase and those undergoing apoptosis. A fluorometric assay and confocal microscopy were used to detect caspase-3 activity and apoptotic bodies, respectively. RESULTS In UtLM cells, low concentrations (< or = 1 microg/ml) of genistein stimulated proliferation, increased PCNA labeling and the percentage of cells in the S-phase, but this did not occur in UtSMCs. Higher concentrations (> or = 10 microg/ml) of genistein adversely affected the morphology, significantly inhibited proliferation, decreased PCNA labeling, increased caspase-3 activity and induced apoptosis in both cell types. CONCLUSIONS Genistein's effects are concentration-dependent in both cell lines. Lower concentrations elicit proliferative effects on UtLM cells only; whereas, higher concentrations alter morphology, inhibit proliferation, and increase caspase activity and apoptosis in both cell types, with the latter two effects being more extensive in UtSMCs.
Effective Capacity Modulation as an Explicit Control Knob for Public Cloud Profitability

We explore the efficacy of dynamic effective capacity modulation (i.e., using virtualization techniques to offer lower resource capacity than that advertised by the cloud provider) as an explicit control knob for a cloud provider's profit maximization complementing the more well-studied approach of dynamic pricing. Our focus is on emerging cloud ecosystems wherein we expect tenants to modify their demands strategically in response to such modulation in effective capacity and prices. We consider a simple model of a cloud provider that offers a single type of virtual machine to its tenants and devise a leader/follower game-based control framework to capture the interactions between the provider and its tenants. We assume both parties employ myopic control and short-term predictions to reflect their operation under the high dynamism and poor predictability in such environments. Our evaluation using a combination of real-world data center traces and benchmarks hosted on a prototype OpenStack-based cloud shows 10-30% profit improvement for a cloud provider compared with baselines that use static pricing and/or static effective capacity.
“I Know I’m an Adult When…I Can Care for Myself and Others”

Growing populations of emerging adults are demographically diverse in terms of race/ethnicity, socioeconomic status, and immigration history in the United States and many attend community colleges. Yet, we still do not fully understand the developmental experiences of emerging adults in community colleges which mostly serve low-income, ethnically diverse immigrant-origin commuter populations. This descriptive mixed-method study examined the ways in which (N = 645) 18- to 25-year-old students at three community college campuses in the Northeast United States perceive adulthood and identify criteria for adulthood. Participants responded to measures of subjective sense of adulthood and responsibilities for family, community, and work, as well as provided an open-ended response to criteria for adulthood. Subjective sense of adulthood significantly increased with age. Participants listed responsibilities for themselves and others, independence, and role transitions as the three most important criteria characteristic of adulthood. Findings revealed that as community college students emerge into adulthood, they engage in multiple social responsibilities as they navigate community college. Furthermore, engaging with community responsibilities was associated with higher levels of subjective sense of adulthood. These data point to the possible existence of a sixth pillar of emerging adulthood, caring for others. Community colleges need to take into account the various social responsibilities present in students’ lives, not only as a competing responsibility on the road to degree attainment but as a resource to be drawn upon. We must find ways for these youth to contribute to both the institutional and economic structures that they find themselves embedded within.