Miracle-dz/UniFAR-FTUs huggingface dataset:
Oxygen environment and islet size are the primary limiting factors of isolated pancreatic islet survival

Background Type 1 diabetes is an autoimmune disease that destroys insulin-producing beta cells in the pancreas. Pancreatic islet transplantation could be an effective treatment option for type 1 diabetes once several issues are resolved, including donor shortage, prevention of islet necrosis and loss in pre- and post-transplantation, and optimization of immunosuppression. This study seeks to determine the cause of necrotic loss of isolated islets to improve transplant efficiency. Methodology The oxygen tension inside isolated human islets of different sizes was simulated under varying oxygen environments using a computational in silico model. In vitro human islet viability was also assessed after culturing in different oxygen conditions. Correlation between simulation data and experimentally measured islet viability was examined. Using these in vitro viability data of human islets, the effect of islet diameter and oxygen tension of the culture environment on islet viability was also analyzed using a logistic regression model. Principal findings Computational simulation clearly revealed the oxygen gradient inside the islet structure. We found that oxygen tension in the islet core was greatly lower (hypoxic) than that on the islet surface due to the oxygen consumption by the cells. The hypoxic core was expanded in the larger islets or in lower oxygen cultures. These findings were consistent with results from in vitro islet viability assays that measured central necrosis in the islet core, indicating that hypoxia is one of the major causes of central necrosis. The logistic regression analysis revealed a negative effect of large islet and low oxygen culture on islet survival. Conclusions/Significance Hypoxic core conditions, induced by the oxygen gradient inside islets, contribute to the development of central necrosis of human isolated islets. Supplying sufficient oxygen during culture could be an effective and reasonable method to maintain isolated islets viable.
Improved SOM based data mining of seasonal flu in mainland China

SOM (Self-Organizing Maps) is an efficient and unsupervised data mining method based on neural networks clustering algorithm. It has become a new hotspot in data mining and visualization. Data mining methods are often manipulated by epidemiologists to reveal the regulation of the diseases. As the temporal characteristics exist in the data of the infectious diseases, and the limitations of the original SOM method, this paper introduce an improved position adjustable SOM and then study seasonal flu in mainland China in 2006 with it. The result shows the improved SOM is an efficient method analyses spatiotemporal infectious disease data. Using this improved SOM method, some abnormal data in dataset has been easily found, such as data-entry error. Clustering result revealed several types of flu virus transmitted in different Chinese cities in 2006, which include: winter flu peaks in the Yangtze River delta areas, winter and summer flu peaks in Donggang, and the whole year high rate of flu in Tianjing, Honghe and Guilin.
Novel cloning vectors for Bacillus thuringiensis

Seven replication origins from resident plasmids of Bacillus thuringienis subsp. kurstaki HD263 and HD73 were cloned in Escherichia coli. Three of these replication origins, originating from plasmids of 43, 44, and 60 MDa, were used to construct a set of compatible shuttle vectors that exhibit structural and segregational stability in the Cry- strain B. thuringiensis HD73-26. These shuttle vectors, pEG597, pEG853, and pEG854, were designed with rare restriction sites that permit various adaptations, including the construction of small recombinant plasmids lacking antibiotic resistance genes. The cryIA(c) and cryIIA insecticidal crystal protein genes were inserted into these vectors to demonstrate crystal protein production in B. thuringiensis. Introduction of a cloned cryIA(c) gene from strain HD263 into a B. thuringiensis subsp. aizawai strain exhibiting good insecticidal activity against Spodoptera exigua resulted in a recombinant strain with an improved spectrum of insecticidal activity. Shuttle vectors of this sort should be valuable in future genetic studies of B. thuringiensis as well as in the development of B. thuringiensis strains for use as microbial pesticides.
Distributed (δ+1)-coloring in linear (in δ) time

The distributed (Δ + 1)-coloring problem is one of most fundamental and well-studied problems in Distributed Algorithms. Starting with the work of Cole and Vishkin in 86, there was a long line of gradually improving algorithms published. The current state-of-the-art running time is O(Δ log Δ + log* n), due to Kuhn and Wattenhofer, PODC'06. Linial (FOCS'87) has proved a lower bound of 1/2 log* n for the problem, and Szegedy and Vishwanathan (STOC'93) provided a heuristic argument that shows that algorithms from a wide family of locally iterative algorithms are unlikely to achieve running time smaller than Θ(Δ log Δ). We present a deterministic (Δ + 1)-coloring distributed algorithm with running time O(Δ) + 1/2 log* n. We also present a tradeoff between the running time and the number of colors, and devise an O(Δ • t)-coloring algorithm with running time O(Δ / t + log* n), for any parameter t, 1 < t ≤ Δ1-ε, for an arbitrarily small constant ε, 0 < ε < 1. Our algorithm breaks the heuristic barrier of Szegedy and Vishwanathan, and achieves running time which is linear in the maximum degree Δ. On the other hand, the conjecture of Szegedy and Vishwanathan may still be true, as our algorithm is not from the family of locally iterative algorithms. On the way to this result we study a generalization of the notion of graph coloring, which is called defective coloring. In an m-defective p-coloring the vertices are colored with p colors so that each vertex has up to m neighbors with the same color. We show that an m-defective p-coloring with reasonably small m and p can be computed very efficiently. We also develop a technique to employ multiple defective colorings of various subgraphs of the original graph G for computing a (Δ+1)-coloring of G. We believe that these techniques are of independent interest.
Workplace-Based Participatory Approach to Weight Loss for Correctional Employees

Objective: To evaluate the effectiveness of a participatory approach using an employee design team for a 12-week weight-loss program with an 8-week follow-up. Methods: Twenty-four employees with mean [standard error (SE)] for weight 233.24 lb [8.16], body mass index 33.29 kg/cm2 [0.82], and age 42.7 years [1.5] participated in the study, among whom 75% were men and 25% women. Results: Significant reductions in weight, body mass index, and waist circumference (among men) were observed before and after intervention (P < 0.05). About 73% and 68% of the variation in weight change (P < 0.01) and waist circumference (P < 0.01), respectively, were explained by Nutrition Knowledge and Exercise Confidence scores after controlling for gender and age. Conclusions: A participatory program with employee involvement resulted in positive outcomes. Increasing participants' knowledge and providing skills to manage their weight seem to change their attitudes, resulting in better outcomes.
Morphology of Clusters and Superclusters in N-Body Simulations of Cosmological Gravitational Clustering

We analyze shapes of overdense regions (clusters and superclusters) in controlled N-body simulations of gravitational clustering with power-law initial spectra P(k) ∝ kn, n = -3, -2, -1, 0. At values of the density just above the percolation transition, the number of distinct (isolated) clusters peaks, and we use this "natural threshold" to study the shapes and multiplicity function of clusters and superclusters. We find that the extent of both filamentarity and pancakeness increases as the simulation evolves, the former being appreciably larger than the latter at virtually all epochs and for all spectra considered by us. Our results also show that high-density regions within very massive clusters/superclusters are likely to be noticeably filamentary or pancake/ribbon-like when compared to the less dense regions within these objects. We make a detailed study of two moment-based "shape statistics" proposed, respectively, by Babul and Starkman (BS) and Luo and Vishniac (LV) and find that both LV and BS have certain built-in limitations: LV is biased toward oblate structures and tends to overemphasize this property, and neither BS nor LV correctly describe the shape of strongly curved or topologically nontrivial objects. For instance, a thin filamentary torus and a ribbon are both described by BS and LV as being pancakes! By contrast, "Shapefinders," a new shape diagnostic not constructed from density moments but from Minskowski functionals, does not suffer from these limitations and appears to faithfully reproduce the shapes of both simple and topologically complex objects.
Cross-Platform Access-Rights Analysis of Mobile Applications

We live in the era of mobile computing. Mobile devices havemore sensors and more capabilities than desktop computers. Forany computing device that contains sensitive information andaccesses the Internet, security is a major concern for bothenterprises and end-users. Of the mobile devices commonly inuse, iOS and Android are the prevalent platforms; each platformhas a unique architecture and security policy relating to howthey handle these sensitive permissions; due to these differencesone platform is likely more secure than the other. A deep staticand dynamic analysis of the applications available for eachplatform was conducted in order to determine on whichoverprivileged applications were more prevalent.
Cortical Modulations Increase in Early Sessions with Brain-Machine Interface

Background During planning and execution of reaching movements, the activity of cortical motor neurons is modulated by a diversity of motor, sensory, and cognitive signals. Brain-machine interfaces (BMIs) extract part of these modulations to directly control artificial actuators. However, cortical modulations that emerge in the novel context of operating the BMI are poorly understood. Methodology/Principal Findings Here we analyzed the changes in neuronal modulations that occurred in different cortical motor areas as monkeys learned to use a BMI to control reaching movements. Using spike-train analysis methods we demonstrate that the modulations of the firing-rates of cortical neurons increased abruptly after the monkeys started operating the BMI. Regression analysis revealed that these enhanced modulations were not correlated with the kinematics of the movement. The initial enhancement in firing rate modulations declined gradually with subsequent training in parallel with the improvement in behavioral performance. Conclusions/Significance We conclude that the enhanced modulations are related to computational tasks that are significant especially in novel motor contexts. Although the function and neuronal mechanism of the enhanced cortical modulations are open for further inquiries, we discuss their potential role in processing execution errors and representing corrective or explorative activity. These representations are expected to contribute to the formation of internal models of the external actuator and their decoding may facilitate BMI improvement.
Homonyms and synonyms in the n-objects naming game

We examine a naming game with two agents trying to establish a common vocabulary for n objects. Such efforts lead to the emergence of language that allows for an efficient communication and exhibits some degree of homonymy and synonymy. Although homonymy reduces the communication efficiency, it seems to be a dynamical trap that persists for a long, and perhaps indefinite, time. On the other hand, synonymy does not reduce the efficiency of communication, but appears to be only a transient feature of the language. Thus, in our model the role of synonymy decreases over time, and it might explain its apparent rareness in present natural languages. The role of noise, that distorts the communicated words, is also examined. Although, in general, the noise reduces the communication efficiency, it also regroups the words so that they are more evenly distributed within the available ”verbal” space.
Potentially lethal damage versus sublethal damage: independent repair processes in actively growing Chinese hamster cells.

Actively growing V79 Chinese hamster cells, treated with anisotonic phosphate-buffered saline (PBS) after x irradiation, are more sensitive than cells treated with isotonic PBS or cells promptly incubated with complete medium immediately after irradiation. The sensitization of irradiated cells results from hypotonic as well as hypertonic NaCl concentrations in PBS, is strongly dependent on both temperature and time, and is mainly due to an increase in the final slope of the single-dose survival curve. After two x-ray dose fractions, the net response of cells sensitized after each fraction by anisotonic post-treatment is similar to that obtained for isotonically treated cells and indicates that sublethal damage repair is not influenced by the enhanced expression of lethal damage. Independence of the repair of damage which is potentially lethal from the repair of damage which is sublethal is further suggested by the more rapid rate of the former compared to that of the latter. The proposal is advanced that the enhanced expression of damage which, after x irradiation, can be shown to be potentially lethal results from a destabilization of the structural relationship between DNA and the nuclear envelope, and/or DNA and the nuclear protein matrix, as a consequence of osmotic changes producedmore » by anisotonic treatment. « less
A robust algorithm for the simultaneous estimation of hierarchical logit models

Estimating simultaneous hierarchical logit models is conditional to the availability of suitable algorithms. Powerful mathematical programs are necessary to maximize the associated non-linear, non-convex, log-likelihood function. Even if classical methods (e.g. Newton-Raphson) can be adapted for relatively simple cases, the need of an e cient and robust algorithm is justi ed to enable practioners to consider a wider class of models. The purpose of this paper is to analyze and to adapt to this context methodologies available in the optimization literature. An algorithm is proposed based on two major concepts from non-linear programming : a trust region method, that ensures robustness and global convergence, and a conjugate gradients iteration, that can be used to solve the quadratic subproblems arising in the estimation process described in this paper. Numerical experiments are nally presented that indicate the power of the proposed algorithm and associate software. Transportation Research Group Department of Mathematics, Facult es Universitaires ND de la Paix, Namur, Belgium E-mail : mb@math.fundp. ac.be
Expected and Unexpected Outcomes of a Service-Learning Program Rooted in Social Justice and Pragmatic Constructivism

Marco, Sally, Juanita (3 of 3) Sarah, Yolanda, Richard, Linda (4 of 6) Esteban, Guillermo, Stevie, Kate (4 of 5) Note. The data was collected from three separate focus groups: Focus Group 1 (2 females, 1 male), Focus Group 2 (5 females, 1 male), and Focus Group 3 (3 females, 2 males). All focus group members identified themselves as Hispanic. Groups 1 and 2 consisted of student graduates and Group 3 consisted of current students.
H-Star: Hilbert-order Based Star Network Expansion Cloaking Algorithm in Road Networks

The proliferations of position identifying devices become increasing privacy threat in location-based services (LBSs). It is very difficult to avoid the privacy threat of a user in processing his/her request because the user has to submit his/her exact location with a query to the LBS. To protect privacy in road networks, the existing method employs a XStar framework to hide the query issuer and provide protection from attack resilience. However, it incurs low anonymization success rate and computation cost is quite high. To address these issues, we propose Hilbert-order based star network expansion cloaking algorithm (H-Star). Our H-Star guarantees K-anonymity under the strict reciprocity condition and increases anonymization success rate by reducing computation overhead. Through comprehensive experimental evaluations, we show the effectiveness of our algorithm in the field of spatial cloaking.
The Social Aspects of Hand Washing in American Restaurants: An Administrative Approach to Reducing Public and Private Health Care Costs

Proper hand sanitation prevents spreading of many types of illness and infection, thereby lowering the quantitative and qualitative costs of public and private health care. Research shows that thinking or knowing someone is watching you wash your hands in a public lavatory appreciably improves the odds of you doing so. Nevertheless, most restaurants place their hand washing facilities inside the bathroom, beyond public view. Reformers from the public and private sectors should work cooperatively to incentivize restaurant owners voluntarily to place their hand washing facilities in public spaces. If this uncompelled approach proves unsuccessful, reformers should seek to impose laws requiring that all public eateries place their bathroom washbasins in conspicuous locations. The discussion closes by suggesting ancillary improvements to test in pursuit of further improving hand washing rates and practices in public spaces.
Smart crawler for hidden web interfaces

Deep web is termed as data present on web but inaccessible to search engine. This data must be accessed through HTML forms filling manually and get access to the deep web i.e. forms. To access deep web data automatically we need to understand search interfaces. The deep web grows at very fast pace and it is always different to manage such data and to give it for deep web crawling. Smart crawler for hidden web interfaces consist of mainly two stages first is site locating another is insite exploring. Site locating starts from seed sites and obtains relevant websites through reverse searching and obtains relevant sites through feature space of URL, anchor and text around URL. Second stage takes input from site locating and goes to find relevant link from those sites. The adaptive link learner is used to find out relevant links with help of link priority and link rank. Proposed system is contributing the searching query as per-query and post-query to obtain wider coverage is obtained through DFS and SCFS classifier.
The Impact of Hydrochloride Heroin on Mental Flexibility, Abstract Reasoning, Impulsivity, and Attention

there is a paucity of research on hydrochloride heroin addiction and its effects on human executive functions. Executive system is a cognitive system that controls and manages cognitive processes. This system is named as the executive function, supervisory attentional system, or cognitive control. This system is also used to describe a defined collection of brain processes that are responsible for planning, abstract thinking, rule acquisitioning,
Predicting the Industry of Users on Social Media

Automatic profiling of social media users is an important task for supporting a multitude of downstream applications. While a number of studies have used social media content to extract and study collective social attributes, there is a lack of substantial research that addresses the detection of a user's industry. We frame this task as classification using both feature engineering and ensemble learning. Our industry-detection system uses both posted content and profile information to detect a user's industry with 64.3% accuracy, significantly outperforming the majority baseline in a taxonomy of fourteen industry classes. Our qualitative analysis suggests that a person's industry not only affects the words used and their perceived meanings, but also the number and type of emotions being expressed.
Improved actionSLAM for long-term indoor tracking with wearable motion sensors

We present an indoor tracking system based on two wearable inertial measurement units for tracking in home and workplace environments. It applies simultaneous localization and mapping with user actions as landmarks, themselves recognized by the wearable sensors. The approach is thus fully wearable and no pre-deployment effort is required. We identify weaknesses of past approaches and address them by introducing heading drift compensation, stance detection adaptation, and ellipse landmarks. Furthermore, we present an environment-independent parameter set that allows for robust tracking in daily-life scenarios. We assess the method on a dataset with five participants in different home and office environments, totaling 8.7h of daily routines and 2500m of travelled distance. This dataset is publicly released. The main outcome is that our algorithm converges 87% of the time to an accurate approximation of the ground truth map (0.52m mean landmark positioning error) in scenarios where previous approaches fail.
Field of Groves: An Energy-Efficient Random Forest

Machine Learning (ML) algorithms, like Convolutional Neural Networks (CNN), Support Vector Machines (SVM), etc. have become widespread and can achieve high statistical performance. However their accuracy decreases significantly in energy-constrained mobile and embedded systems space, where all computations need to be completed under a tight energy budget. In this work, we present a field of groves (FoG) implementation of random forests (RF) that achieves an accuracy comparable to CNNs and SVMs under tight energy budgets. Evaluation of the FoG shows that at comparable accuracy it consumes ~1.48x, ~24x, ~2.5x, and ~34.7x lower energy per classification compared to conventional RF, SVM_RBF , MLP, and CNN, respectively. FoG is ~6.5x less energy efficient than SVM_LR, but achieves 18% higher accuracy on average across all considered datasets.
A Latino Practical Theology: Mapping the Road Ahead

[The author uses the pastoral circle or “see-judge-act” practical theological method to review the status of Hispanic/Latino ministry. He takes note of new research findings, while stressing the importance of an integrating framework for shaping the Catholic Church's response to the multiple challenges presented by the Latino/a presence. Paul VI's Evangelii nuntiandi provides the needed framework with its stress on inculturation, liberation, and interreligious dialogue. Sections are then devoted to the challenges of popular religion, youth, the flight to other religions, multiculturalism, and pluralism. Finally, he names several practical implications and lays out a map suggesting where this may be heading. ]
STLAC: A spatial and temporal locality-aware cache and network-on-chip codesign for tiled many-core systems

The spatial and temporal locality of workloads are the root causes for cache designs to overcome the memory wall problem. However, few existing state-of-the-art designs exploit both the two locality features to optimize the memory hierarchies in the area of tiled many-core systems, which losses the opportunities to explore more performance improvement. To address this problem, an adaptive spatial and temporal locality-aware cache and network-on-chip (NoC) codesign (STLAC) is proposed, which dynamically partitions the last level cache (LLC) as data prefetch buffer or victim cache for locality prediction and exploits a hybrid burst-support NoC for fast data prefetch. The data prefetch buffer speculates the data blocks in subsequent addresses to exploit the spatial locality, while the victim cache collects the evicted data blocks from the upper memory hierarchy to exploit the temporal locality. By combining the proposed adaptive cache partition with the hybrid burst-support NoC, the off-chip misses and on-chip network usage are greatly reduced. Experimental results demonstrate that the proposed STLAC reduces up to 43% off-chip misses and improves 15% performance on average compared with the traditional shared LLC design.