Miracle-dz/UniFAR-FTUs huggingface dataset:
An Integrated Approach for Processor Allocation and Scheduling of Mixed-Parallel Applications

Computationally complex applications can often be viewed as a collection of coarse-grained data-parallel tasks with precedence constraints. Researchers have shown that combining task and data parallelism (mixed parallelism) can be an effective approach for executing these applications, as compared to pure task or data parallelism. In this paper, we present an approach to determine the appropriate mix of task and data parallelism, i.e., the set of tasks that should be run concurrently and the number of processors to be allocated to each task. An iterative algorithm is proposed that couples processor allocation and scheduling of mixed-parallel applications on compute clusters so as to minimize the parallel completion time (makespan). Our algorithm iteratively reduces the makespan by increasing the degree of data parallelism of tasks on the critical path that have good scalability and a low degree of potential task parallelism. The approach employs a look-ahead technique to escape local minima and uses priority based backfill scheduling to efficiently schedule the parallel tasks onto processors. Evaluation using benchmark task graphs derived from real applications as well as synthetic graphs shows that our algorithm consistently performs better than CPR and CPA, two previously proposed scheduling schemes, as well as pure task and data parallelism
A Murine Model in Which Protection Correlates with Pertussis Vaccine Efficacy in Children Reveals Complementary Roles for Humoral and Cell-Mediated Immunity in Protection againstBordetella pertussis

ABSTRACT The results of phase 3 efficacy trials have shown that acellular and whole-cell pertussis vaccines can confer protection against whooping cough. However, despite the advances in vaccine development, clinical trials have not provided significant new information on the mechanism of protective immunity against Bordetella pertussis. Classical approaches based on measurement of antibody responses to individual antigens failed to define an immunological correlate of protection. A reliable animal model, predictive of acellular and whole-cell pertussis vaccine potency in children, would facilitate an elucidation of the mechanism of immune protection againstB. pertussis and would assist in the regulatory control and future development of pertussis vaccines. In this study, we have shown that the rate of B. pertussis clearance following respiratory challenge of immunized mice correlated with vaccine efficacy in children. Using this model together with mice with targeted disruptions of the gamma interferon (IFN-γ) receptor, interleukin-4 or immunoglobulin heavy-chain genes, we have demonstrated an absolute requirement for B cells or their products in bacterial clearance and a role for IFN-γ in immunity generated by previous infection or immunization with the whole-cell pertussis vaccine. The results of passive immunization experiments suggested that protection early after immunization with acellular pertussis vaccines is mediated by antibody against multiple protective antigens. In contrast, more complete protection conferred by previous infection or immunization with whole-cell pertussis vaccines reflected the induction of Th1 cells. Our findings suggest that the mechanism of immunity againstB. pertussis involves humoral and cellular immune responses which are not directed against a single protective antigen and thus provide an explanation for previous failures to define an immunological correlate of protection.
Question Answering Biographic Information and Social Network Powered by the Semantic Web

After several years of development, the vision of the Semantic Web is gradually becoming reality. Large data repositories have been created and offer semantic information in a machine-processable form for various domains. Semantic Web data can be published on the Web, gathered automatically, and reasoned about. All these developments open interesting perspectives for building a new class of domain-specific, broad-coverage information systems that overcome a long-standing bottleneck of AI systems, the notoriously incomplete knowledge base. We present a system that shows how the wealth of information in the Semantic Web can be interfaced with humans once again, using natural language for querying and answering rather than technical formalisms. Whereas current Question Answering systems typically select snippets from Web documents retrieved by a search engine, we utilize Semantic Web data, which allows us to provide natural-language answers that are tailored to the current dialog context. Furthermore, we show how to use natural language processing technologies to acquire new data and enrich existing data in a Semantic Web framework. Our system has acquired a rich biographic data resource by combining existing Semantic Web resources, which are discovered from semi-structured textual data in Web pages, with information extracted from free natural language texts.
The shape of the human language-ready brain

Our core hypothesis is that the emergence of our species-specific language-ready brain ought to be understood in light of the developmental changes expressed at the levels of brain morphology and neural connectivity that occurred in our species after the split from Neanderthals–Denisovans and that gave us a more globular braincase configuration. In addition to changes at the cortical level, we hypothesize that the anatomical shift that led to globularity also entailed significant changes at the subcortical level. We claim that the functional consequences of such changes must also be taken into account to gain a fuller understanding of our linguistic capacity. Here we focus on the thalamus, which we argue is central to language and human cognition, as it modulates fronto-parietal activity. With this new neurobiological perspective in place, we examine its possible molecular basis. We construct a candidate gene set whose members are involved in the development and connectivity of the thalamus, in the evolution of the human head, and are known to give rise to language-associated cognitive disorders. We submit that the new gene candidate set opens up new windows into our understanding of the genetic basis of our linguistic capacity. Thus, our hypothesis aims at generating new testing grounds concerning core aspects of language ontogeny and phylogeny.
A plea for confidence intervals and consideration of generalizability in diagnostic studies

Sir, Many thanks for letting us respond to the interesting letter concerning our recent paper. We are grateful for the chance to clarify the points raised, which suggest our conclusions were too optimistic. In our paper (Kloppel et al. , 2008), we used MRI scans from pathologically proven cases of Alzheimer's disease and frontotemporal lobar degeneration (FTLD) to validate trained sets for a machine learning-based support vector machine (SVM) approach to the categorization of structural scans from normal and each other. This rigorous approach substantially limited the number of available subjects, which we made perfectly clear in our article, but which was unavoidable given our novel approach. Frost and colleagues are right to point out that such low numbers result in larger confidence intervals than if we were able to include more scans. This is an object of our further empirical studies—what is the improvement in classification gained using this technique with greater numbers of scans in the trained set? The graph below (Fig. 1 …
The Impact of Ethanol Production on U.S. and Regional Gasoline Prices and on the Profitability of the U.S. Oil Refinery Industry

Using pooled regional time-series data and panel data estimation, we quantify the impact of monthly ethanol production on monthly retail regular gasoline prices. This analysis suggests that the growth in ethanol production has caused retail gasoline prices to be $0.29 to $0.40 per gallon lower than would otherwise have been the case. The analysis shows that the negative impact of ethanol on gasoline prices varies considerably across regions. The Midwest region has the biggest impact, at $0.39/gallon, while the Rocky Mountain region had the smallest impact, at $0.17/gallon. The results also indicate that ethanol production has significantly reduced the profit margin of the oil refinery industry. The results are robust with respect to alternative model specifications.
Are interpretations of syntactic ambiguities under working memory load "good-enough"? : evidence from eye movements

Syntactically ambiguous sentences offer an insight into how sentences generally are processed, by examining how readers recognise and reanalyse the ambiguity. However, it is only more recently that the comprehension product of syntactic analysis has been adequately tested, demonstrating that ambiguities are not always fully processed. This work has led to the good-enough approach to language processing and comprehension (e.g., Ferreira & Patson, 2007), which argues that sentence processing is merely good enough for the current task, and that our comprehension may not exactly match the content of what has been read. The work presented in this thesis set out to examine what it means for syntactic ambiguity processing to be good enough, by monitoring patterns of eye movements as people read sentences containing a temporary syntactic ambiguity. Comprehension questions probed the extent to which the syntactic ambiguity had been resolved. Across six experiments, it was demonstrated that both online sentence processing and comprehension are influenced by the presence of an extrinsic memory load, the presence or absence of comprehension questions, the length of texts being read, and the age of participants. Eye movement patterns were more superficial if the task permitted it; similarly, syntactic ambiguities were misinterpreted more commonly as the task demands increased. The results support a good-enough, adaptive sentence processing system, where initial misinterpretations can linger in the product of syntactic analysis, and which is affected by task demands and individual differences.
Dynamic Modularity of Host Protein Interaction Networks in Salmonella Typhi Infection

Background Salmonella Typhi is a human-restricted pathogen, which causes typhoid fever and remains a global health problem in the developing countries. Although previously reported host expression datasets had identified putative biomarkers and therapeutic targets of typhoid fever, the underlying molecular mechanism of pathogenesis remains incompletely understood. Methods We used five gene expression datasets of human peripheral blood from patients suffering from S. Typhi or other bacteremic infections or non-infectious disease like leukemia. The expression datasets were merged into human protein interaction network (PIN) and the expression correlation between the hubs and their interacting proteins was measured by calculating Pearson Correlation Coefficient (PCC) values. The differences in the average PCC for each hub between the disease states and their respective controls were calculated for studied datasets. The individual hubs and their interactors with expression, PCC and average PCC values were treated as dynamic subnetworks. The hubs that showed unique trends of alterations specific to S. Typhi infection were identified. Results We identified S. Typhi infection-specific dynamic subnetworks of the host, which involve 81 hubs and 1343 interactions. The major enriched GO biological process terms in the identified subnetworks were regulation of apoptosis and biological adhesions, while the enriched pathways include cytokine signalling in the immune system and downstream TCR signalling. The dynamic nature of the hubs CCR1, IRS2 and PRKCA with their interactors was studied in detail. The difference in the dynamics of the subnetworks specific to S. Typhi infection suggests a potential molecular model of typhoid fever. Conclusions Hubs and their interactors of the S. Typhi infection-specific dynamic subnetworks carrying distinct PCC values compared with the non-typhoid and other disease conditions reveal new insight into the pathogenesis of S. Typhi.
Towards apriori and posteriori estimation models for renewable energy projects in software engineering

Currently, cost estimation for renewable energy projects is one of the important issues in software engineering projects. It has been observed in the industry that cost estimates of renewable energy projects often differ from the final costs by a factor of two or more; such large overestimates impact on process integrity and, ultimately, on final quality. RE development organizations are expected to deliver projects on time and on budget in a context of fixed-price contracts. To meet these market demands, managers must determine well in advance such estimates which called is the apriori cost estimation. These organizations typically use an estimation techniques based either on informal personal or organizational experience, or on aposteriori estimation models developed internally or developed by outside consultancy. This paper collects most of the common used models of the cost estimation models throughout the apriori and aposteriori contexts, and we highlights some of their mixed uses between these estimating models in software engineering development projects for RE and lists some of the estimating techniques used in A priori and A posteriori contexts.
Greedy Mechanism Design for Truthful Combinatorial Auctions

We study the combinatorial auction problem, in which a set of objects are to be distributed amongst selfish bidders with the goal of maximizing social we lfar . We consider mechanisms that apply greedy algorithms, and ask to what extent truthful greedy me chanisms can find approximate solutions to the combinatorial auction problem. We associate the noti o of greediness with a broad class of algorithms known as priority algorithms. We show that no truthfu l priority mechanism obtains a sub-linear approximation ratio. We also consider a particular type of p riority algorithm for use with submodular bidders, and show that no such algorithm can be made truthful .
Hand gesture based TV control system — Towards both user- & machine-friendly gesture applications

A man-machine interface plays an important role to convey an intention from a user to machine. Nowadays, vision-based solution has been attracting a lot of attention since it does not require any attachment sensors on the body. One of the most famous applications is to control TV operations by hand gestures. Instead of bothersome operations using a specific controller, a user can send a command to a system by intuitive hand gestures. Most of previous studies have been focused on a strategy to detect/recognize hand motions, and the design concept to realize high usability of the application got less attention. This paper discusses how to design a user-friendly and also machine-friendly hand gesture application. Our concept gives a user an opportunity to customize a TV control interface by selecting hand shapes and hand motions through interaction with a hand gesture selection system.
Delaying Variable Binding Commitments in Planning

One of the problems with many partial-order planners is their eager commitment to variable bindings. This is contrary to their control decision in delayed-commitment of operator orderings. In this paper we present an extension to the classical partial-order planners by associating every variable with a finite domain of values. The extended planner applies constraint satisfaction routines to check for the consistency of variable bindings. With the extended planner, we perform a set of experiments to show that it is able to reduce the amount of backtracking in domains where few variable instantiations can lead to final solutions. We also investigate the frequency of CSP application to determine how often should constraint checking be performed in order to yield the best performance.
Display models for visualization

Models for visualization are important, helping the developer and user to understand the visualization process; to follow the connections and the data paths through the system; and to reference and compare the functionality and the limitations of different systems or techniques. Display models specifically classify the data by what type of output can be created. Bertin, J. (1962) described a symbolic reference model that he used to describe images and displays. We review his and other 'display orientated models' describing important aspects of these methods and ideas. We then translate Bertin's scheme into an algebraic form as a method to describe visualizations.
Laser-induced mouse model of chronic ocular hypertension.

PURPOSE To develop an inducible mouse model of glaucoma. METHODS An obstruction of aqueous humor outflow in adult C57BL6/J mice was induced by combined injection of indocyanine green (ICG) dye into the anterior chamber and diode laser treatment. To evaluate intraocular pressure (IOP), tonometry was performed with a modified Goldmann tonometer. The function of the retina was evaluated with electroretinography (ERG). RESULTS IOP was significantly elevated in surgical eyes compared with control eyes: before surgery, 15.2 +/- 0.6 mm Hg; 10 days after surgery, 33.6 +/- 1.5 mm Hg (P < 0.001); and 30 days after surgery, 27.4 +/- 1.2 mm Hg (P < 0.001). However, 60 days after surgery, IOP in the surgical eyes decreased to 19.5 +/- 0.9 mm Hg and was not significantly different compared with control eyes (control, 17.3 +/- 0.7 mm Hg; P = 0.053). ERG amplitudes, expressed as a ratio (surgical/control), were decreased in surgical eyes. The amplitudes for b-wave were: before surgery, 107.6% +/- 4.6%; 28 days after surgery, 61% +/- 4% (P < 0.001); and 56 days after surgery, 62% +/- 5.6% (P < 0.001). Oscillatory potentials were the most dramatically affected: before surgery, 108.6% +/- 6.7%; 28 days after surgery, 57.5% +/- 5% (P < 0.01); and 56 days after surgery, 57% +/- 8.5% (P < 0.001). Amplitudes of the a-waves had relatively smaller but still significant deficits: before surgery, 105.8% +/- 6.9%; 28 days after surgery, 72.2% +/- 5.4% (P < 0.01); and 56 days after surgery, 79.8% +/- 11.0% (P < 0.01). Histologic analysis of the surgical eyes revealed development of anterior synechia, loss of retinal ganglion cells (RGCs), and thinning of all retinal layers. Electron microscopy of optic nerve cross sections revealed swelling and degeneration of the large diameter axons and gliosis. CONCLUSIONS Diode laser treatment of ICG saturated episcleral veins causes a chronic elevation of IOP and sustained ERG deficits.
Enhanced transmission of slit arrays in an extremely thin metallic film

Horizontal resonances of slit arrays are studied. They can lead to an enhanced transmission that cannot be explained using the single-mode approximation. A new type of cavity resonance is found when the slits are narrow for a wavelength very close to the period. It can be excited for very low thicknesses. Optimization shows these structures could constitute interesting monochromatic filters.
Explanation for Recommender Systems: Satisfaction vs. Promotion

There is much work done on Recommender Systems, systems that automate the recommendation process; however there is little work done on explaining recommendations. The only study we know did an experiment measuring which explanation system increased user’s acceptance of the item how much (promotion). We took a different approach and measured which explanation system estimated the true quality of the item the best so that the user can be satisfied with the selection in the end (satisfaction).
Influence of program inputs on the selection of garbage collectors

Many studies have shown that the best performer among a set of garbage collectors tends to be different for different applications. Researchers have proposed application-specific selection of garbage collectors. In this work, we concentrate on a second dimension of the problem: the influence of program inputs on the selection of garbage collectors. We collect tens to hundreds of inputs for a set of Java benchmarks, and measure their performance on Jikes RVM with different heap sizes and garbage collectors. A rigorous statistical analysis produces four-fold insights. First, inputs influence the relative performance of garbage collectors significantly, causing large variations to the top set of garbage collectors across inputs. Profiling one or few runs is thus inadequate for selecting the garbage collector that works well for most inputs. Second, when the heap size ratio is fixed, one or two types of garbage collectors are enough to stimulate the top performance of the program on all inputs. Third, for some programs, the heap size ratio significantly affects the relative performance of different types of garbage collectors. For the selection of garbage collectors on those programs, it is necessary to have a cross-input predictive model that predicts the minimum possible heap size of the execution on an arbitrary input. Finally, based on regression techniques, we demonstrate the predictability of the minimum possible heap size, indicating the potential feasibility of the input-specific selection of garbage collectors.
Explaining Language Universals in Connectionist Networks

Across languages there are certain characteristics which they share. Linguists, trying to explain language universals, have come up with different theories: They argue for (1) the innatedness of general linguistic principles, (2) the communicative functions reflected in linguisitic structure, (3) the psychological demands placed upon language users, or (4) grammar-internal explanations. This paper tries to explain some of the morphological universals in the framework of a connectionist network, supporting the third approach. Employing simple recurrent networks, a series of experiments were done on various types of morphological rules. The results show that the model's performance mirrors the extent to which the different types of rules occur in natural languages. The paper explains how the model has discovered these universals.
Multi frame guided local search for semiautomatic endocardial contour estimation in echocardiography sequences

We present a guided local search (GLS) algorithm in a multi-frame environment for the detection of endocardial contours in echo cardiographic image sequences. The proposed method requires minimal user intervention at the first frame of the image sequence for specifying the candidate points of the contour. The initial contour is approximated by fitting an ellipse in the region defined by the points specified. First level of regularization on the contour is made by radial gradient search incorporating both magnitude and direction. The second level of regularization makes use of the GLS algorithm. The GLS with features and constraints for solution space and penalty terms overcome the optimization being trapped in local minima. The proposed method also incorporates the temporal information from the adjacent frames during the regularization process. The subsequent frames in sequence are initialized by the final contour of the previous frame. The algorithm developed was applied to 20 data sets over a cardiac cycle and the results were validated by comparing computer generated boundaries to those manually outlined by one expert. The maximum error in the contours detected was plusmn3.1 mm. The application of guided local search algorithm proposed in this paper offers a fast and efficient method for semiautomatic segmentation of heart chambers in 2D echocardiography sequences.