Miracle-dz/UniFAR-FTUs huggingface dataset:
Graph Connectivity Measures for Unsupervised Word Sense Disambiguation

Word sense disambiguation (WSD) has been a long-standing research objective for natural language processing. In this paper we are concerned with developing graph-based unsupervised algorithms for alleviating the data requirements for large scale WSD. Under this framework, finding the right sense for a given word amounts to identifying the most "important" node among the set of graph nodes representing its senses. We propose a variety of measures that analyze the connectivity of graph structures, thereby identifying the most relevant word senses. We assess their performance on standard datasets, and show that the best measures perform comparably to state-of-the-art.
Efficient Forward Regression with Marginal Likelihood

We propose an efficient forward regression algorithm based on greedy optimization of marginal likelihood. It can be understood as a forward selection procedure which adds a new basis vector at each step with the largest increment to the marginal likelihood. The computational cost of our algorithm is linear in the number n of training examples and quadratic in the number k of selected basis vectors, i.e. O(nk 2 ). Moreover, our approach is only required to store a small fraction of all columns of the full design matrix. We compare our algorithm with the well-known Rel- evance Vector Machines (RVM) which also optimizes marginal likelihood iteratively. The results show that our algorithm can achieve comparable prediction accuracy but with significantly better scaling performance in terms of both computational cost and memory requirements.
Statistical Arbitrage and Optimal Trading with Transaction Costs in Futures Markets

We consider the Brownian market model and the problem of expected utility maximization of terminal wealth. We, specifically, examine the problem of maximizing the utility of terminal wealth under the presence of transaction costs of a fund/agent investing in futures markets. We offer some preliminary remarks about statistical arbitrage strategies and we set the framework for futures markets, and introduce concepts such as margin, gearing and slippage. The setting is of discrete time, and the price evolution of the futures prices is modelled as discrete random sequence involving Ito's sums. We assume the drift and the Brownian motion driving the return process are non-observable and the transaction costs are represented by the bid-ask spread. We provide explicit solution to the optimal portfolio process, and we offer an example using logarithmic utility.
Modeling the impact of interventions along the HIV continuum of care in Newark, New Jersey.

BACKGROUND The human immunodeficiency virus (HIV) epidemic in Newark, New Jersey, is among the most severe in the United States. Prevalence ranges up to 3.3% in some groups. The aim of this study is to use a mathematical model of the epidemic in Newark to assess the impact of interventions along the continuum of care, leading to virologic suppression. METHODS A model was constructed of HIV infection including specific care-continuum steps. The model was calibrated to HIV/AIDS cases in Newark among different populations over a 10-year period. Interventions applied to model fits were increasing proportions tested, linked and retained in care, linked and adherent to treatment, and increasing testing frequency, high-risk-group testing, and adherence. Impacts were assessed by measuring incidence and death reductions 10 years postintervention. RESULTS The most effective interventions for reducing incidence were improving treatment adherence and increasing testing frequency and coverage. No single intervention reduced incidence in 2023 by >5%, and the most effective combination of interventions reduced incidence by approximately 16% (2%-24%). The most efficacious interventions for reducing deaths were increasing retention, linkage to care, testing coverage, and adherence. Increasing retention reduced deaths by approximately 27% (24%-29%); the most efficacious combination of interventions reduced deaths in 2023 by approximately 52% (46%-57%). CONCLUSIONS Reducing HIV deaths in Newark over a 10-year period may be a realizable goal, but reducing incidence is less likely. Our results highlight the importance of addressing leaks across the entire continuum of care and reinforcing efforts to prevention new HIV infections with additional interventions.
Psychology Research and Behavior Management Prototype for Internet Support of Pregnant Women and Mothers with Type 1 Diabetes: Focus Group Testing

Background: The aim of this study was to pilot test a prototype website called MODIAB-web designed to support pregnant women and mothers with type 1 diabetes. Method: A focus group was undertaken and the results were analyzed using qualitative content analysis. Results: Eight subthemes were identified, comprising " blood glucose versus insulin, " " application for smart phones, " " the time aspect, " " interface and technology, " " forum, " " direct link to the diabetes midwife, " " ask the expert, " and " lack of contact information. " These subthemes were condensed into two main themes. The first theme was " easily understood interface, but in need of a more blood-glucose focused orientation " and the second theme was " forum for interaction with both equals and experts. " Conclusion: The women in this study had positive impressions of several of the MODIAB-web functions, including a forum for pregnant mothers with type 1 diabetes and the possibility of being able to put their blood glucose levels into a diagram which could be sent directly to the diabetes midwife. Access to articles and information via the " fact " tab and the ability to ask questions of experts were also significantly helpful to women in the focus group. Pregnant women and mothers with type 1 diabetes can gain support from such a Web-based self-help system.
Colon cancer diagnosis on digital tissue images

The purpose of this project is to develop a software which can be an aid for difficult colon cancer diagnosis and using this system the patients can be helped with an early diagnosis. The aim can be achieved with processing and analysing microscopic tissue images. This paper contains the basic knowledges related to the project and the description of the developed system. The implemented algorithms determines the locations and features of glands and save these information for the subsequent diagnosis. One of the most important algorithm in this project is the Color Structure Code, which performs a color based segmentation and the output is the starting point of the further process.
Performance Analysis of a General Tree Structure for Target Detection in Wireless Sensor Networks

One of the basic tasks of a wireless sensor network is target detection, and one of the main issues must be addressed in a detection sensor network is its active topology. Here, we assume a simple hierarchical topology, where sensors that are close to each other will form a cluster and each cluster has its own cluster head, which serves as the local fusion center. Based on decisions received from sensors located within a specific cluster, the corresponding cluster head will make a decision about target presence/absence within that sub-region. The decisions from cluster heads will be further transmitted to the central fusion node to inform it if there is a target or event in specific sub-regions. In this paper, we propose a general tree structure to fuse decisions within a cluster. The aim is to investigate the effects of using different tree topologies in a cluster on the detection performance and energy consumption in a detection sensor network. We will find a tradeoff between high performance and low energy consumption. For this purpose, a function named energy-error has been defined. By finding the minimum value of this function, it is possible to achieve a tradeoff between performance and energy consumption
Revitalising Old Thoughts: Class diagrams in Light of the Early Wittgenstein

The early work of Ludwig Wittgenstein aimed at outlining a set of postulates about the use of language to describe the world. This work bears a remarkable resemblance to the methodologies developed for data modelling. This paper discusses the features and constraints of object-oriented data modelling with UML class diagrams in light of the early theories developed by Wittgenstein and first published in 1921. The later criticism towards this theory illustrates some of the limitations of class diagrams as a language for describing the world.
Understanding the virtualization "Tax" of scale-out pass-through GPUs in GaaS clouds: An empirical study

Pass-through techniques enable virtual machines to directly access hardware GPU resources in an exclusive mode, delivering extraordinary graphics performance for client users in GaaS clouds. However, the virtualization overheads of pass-through GPUs may decrease the frame rate of graphics workloads by reducing the occupancy rate of the GPU working queue. In this work, we make the first attempt to characterize pass-through GPUs running in different consolidation scenarios and uncover the root causes of these overheads. Towards this end, we set up state-of-the-art empirical platforms equipped with NVIDIA GRID GPUs and execute graphics intensive workloads running in GaaS clouds. We first demonstrate the existence of virtualization overheads, which can slow down the GPU command generation rate. Compared with a bare-metal system, the performance of pass-through GPUs degrades 9.0% and 21.5% under a single VM and 8-VMs respectively. We analyze the workflow of Windows display driver model and VMEXIT events distribution and identify four factors (i.e. HLT instruction and idle domain, external interrupt delivery, IOMMU, and memory subsystem) that contribute to the performance degradation. Our evaluation results show that: (1) the VM-VMM context switch caused by a HLT instruction and wake-up interrupt injection of an idle domain result in 66. 7% idle time for a single pass-through GPU; (2) the external interrupt delivery and tasklet processing cause additional overheads. When 8 VMs are consolidated, the interrupt delivery processing time and interrupt frequency rise 30.7% and 127.3%, respectively; (3) the existing IOMMU design scales well with pass-through GPUs; and (4) interactions of domain guest's software stacks impact the hardware prefetching mechanism so that it fails to compensate the rapidly growing LLC miss rate when more pass-through GPU VMs are added. To the best of our knowledge, this is the first work that characterizes pass-through GPU virtualization overheads and underlying reasons. This study highlights valuable insights for improving the performance of future virtualized GPU systems.
PS-FPG: Pattern selection based co-design of floorplan and Power/Ground network with wiring resource optimization

As technology advances, the voltage (IR) drop in the Power/Ground (P/G) network becomes a serious problem in modern IC design. The P/G network co-design with floorplan can improve the power design quality. Different with traditional approaches which analyze P/G network during the floorplanning iterations, in this paper, an efficient pattern selection method is used to provide gradient information for fast signal-integrity estimation. We also propose a novel P/G aware incremental algorithm which can intelligently fix the violations during the floorplanning process. The P/G pin assignment and wire sizing method are adopted during the floorplanning process so that the power routing resource can be minimized with the constraints of IR drop and electron migration (EM) considered. Experimental results based on the MCNC benchmarks show that our design not only significantly speeds up the optimization process, but also optimizes the power routing resource while the quality of the floorplanning is maintained.
Collisions of cosmic F- and D-strings

Recent work suggests that fundamental and Dirichlet strings, and their (p,q) bound states, may be observed as cosmic strings. The evolution of cosmic string networks, and therefore their observational signals, depends on what happens when two strings collide. We study this in string perturbation theory for collisions between all possible pairs of strings; different cases involve sphere, disk, and annulus amplitudes. The result also depends on the details of compactification; the dependence on ratios of scales is only logarithmic, but this is still numerically important. We study a range of models and parameters, and find that in most cases these strings can be distinguished from cosmic strings that arise as gauge theory solitons.
Root resource foraging: does it matter?

Root traits have recently come out of the dark to take center stage in efforts to increase food production and transition toward sustainability, with calls for a “Second Green Revolution” focused on roots (Lynch, 2007; Den Herder et al., 2010). We will highlight some of the challenges en route to developing fruitful strategies for enhanced resource acquisition in crops. The article will focus on resource foraging, the process by which root system architecture (RSA, the ensemble of the root system in space) changes over time to acquire resources. Most studies on foraging in plants have focused on resource competition between wild species, using plants subjected to natural selection, not to agricultural selection (Cahill and McNickle, 2011). These studies have been extremely useful to begin to identify the mechanisms and selective forces that shape adaptation and survival in natural environments (Kembel et al., 2008; McNickle et al., 2009; de Kroon et al., 2012; Craine and Dybzinski, 2013; Padilla et al., 2013). A striking, albeit not surprising, conclusion from these studies is the diversity of root behavior, including foraging, observed in different species, even in different accessions of the same species, revealing its adaptive nature.
Transcription Factors and Plants Response to Drought Stress: Current Understanding and Future Directions

Increasing vulnerability of plants to a variety of stresses such as drought, salt and extreme temperatures poses a global threat to sustained growth and productivity of major crops. Of these stresses, drought represents a considerable threat to plant growth and development. In view of this, developing staple food cultivars with improved drought tolerance emerges as the most sustainable solution toward improving crop productivity in a scenario of climate change. In parallel, unraveling the genetic architecture and the targeted identification of molecular networks using modern “OMICS” analyses, that can underpin drought tolerance mechanisms, is urgently required. Importantly, integrated studies intending to elucidate complex mechanisms can bridge the gap existing in our current knowledge about drought stress tolerance in plants. It is now well established that drought tolerance is regulated by several genes, including transcription factors (TFs) that enable plants to withstand unfavorable conditions, and these remain potential genomic candidates for their wide application in crop breeding. These TFs represent the key molecular switches orchestrating the regulation of plant developmental processes in response to a variety of stresses. The current review aims to offer a deeper understanding of TFs engaged in regulating plant’s response under drought stress and to devise potential strategies to improve plant tolerance against drought.
Calcium Channels and Short-term Synaptic Plasticity*

Voltage-gated Ca2+ channels in presynaptic nerve terminals initiate neurotransmitter release in response to depolarization by action potentials from the nerve axon. The strength of synaptic transmission is dependent on the third to fourth power of Ca2+ entry, placing the Ca2+ channels in a unique position for regulation of synaptic strength. Short-term synaptic plasticity regulates the strength of neurotransmission through facilitation and depression on the millisecond time scale and plays a key role in encoding information in the nervous system. CaV2.1 channels are the major source of Ca2+ entry for neurotransmission in the central nervous system. They are tightly regulated by Ca2+, calmodulin, and related Ca2+ sensor proteins, which cause facilitation and inactivation of channel activity. Emerging evidence reviewed here points to this mode of regulation of CaV2.1 channels as a major contributor to short-term synaptic plasticity of neurotransmission and its diversity among synapses.
Retrieving answers from multiple documents using semantic skolem indexing

The representation of document content is very important factors in retrieval process. The failure to create a good knowledge representation will definitely lead to failure in terms of its retrieval no matter how good the retrieval engine is. Therefore, this research focused on creating a reliable knowledge representation for our retrieval engine. We are using skolem to capture the information conveyed by multiple text documents and used skolem as an index language. This research also focuses on utilizing the skolem index as its knowledge representation in its question answering system. The system is capable of retrieving the answer as well as states the exact document in which the answer is derived from.
Influence of coronary collateral blood flow on the development of exertional ischemia and Q wave infarction in patients with severe single-vessel disease.

The functional significance of coronary collateral flow from a nonobstructed supply artery was studied in 121 patients with severe (greater than or equal to 80%) single-vessel disease, 64 with and 57 without Q wave infarction. All patients underwent exercise thallium imaging and coronary angiography. On angiography, collateral flow was present in 85% of 74 occluded arteries compared with only 17% of 47 arteries with subtotal obstruction (p less than .001). Collateral flow was not seen in arteries with lesions of less than 90% obstruction. Collateral flow was present in 100% of 29 occluded arteries in patients without Q wave infarction compared with only 76% of 45 occluded arteries with Q wave infarction (p less than .005). Clinical variables did not correlate with collateral flow. Collateral flow did not prevent ischemia on exercise thallium imaging in patients without Q wave infarction: 30 of 33 (91%) with collateral flow had reversible thallium defects compared with 24 of 24 (100%) without collateral flow (p = NS). In patients with Q wave infarction, partially reversible exercise thallium defects (peri-infarctional ischemia) were more common with flow to the area from either subtotal obstruction (73%) or collateral flow (45%) than with no flow from total occlusion (27%; p = .05). In patients with severe single-vessel disease the presence of collateral flow is principally determined by coronary occlusion. Collateral flow may protect from Q wave infarction but does not prevent exercise ischemia on thallium imaging.
Architecture Design for the Environmental Monitoring System over the Winter Season

One of the applications as a source of big data, there is a sensor network for--the environmental monitoring that is designed to detect the deterioration of the infrastructure, erosion control and so on. The specific targets are bridges, buildings, slopes and embankments due to the natural disasters or aging. Basic requirement of this monitoring system is to collect data over a long period of time from a large number of nodes that installed in a wide area. However, in order to apply a wireless sensor network (WSN), using wireless communication and energy harvesting, there are not many cases in the actual monitoring system design. Because of the system must satisfy various conditions; measurement location and time specified by the civil engineering; communication quality and topology obtained from the network technology; the electrical engineering to solve the balance of weather environment and power consumption that depends on the above-mentioned conditions. We propose the whole WSN design methodology especially for the electrical architecture that is affected by the network behavior and the environmental disturbance. It is characterized by determining recursively mutual trade-off of a wireless simulation and a power architecture simulation of the node devices. Furthermore, the system allows the redundancy of the design. In addition, we deployed the actual slope monitoring WSN that is designed by the proposed method to the snow-covered area. A conventional similar monitoring WSN, with 7 Ah Li-battery, it worked only 129 days in a mild climate area. On the other hand, our proposed system, deployed in the heavy snow area has been working more than 6 months (still working) with 3.2 Ah batteries. Finally, it made a contribution to the civil engineering succeeded in the real time observation of the groundwater level displacement at the time of melting snow in the spring season.
The Role of Task Specification in Optimal Cue Integration

A full Bayesian approach to vision requires consideration of potential interactions between all the variables in both the scene and image.A complete model of the interactions, however, seems computationally intractable because of the high dimensionality of image measurements and scene properties.As a consequence, both artificial visual systems and models of human vision have relied on a premature commitment to computationally simple modular architectures in which a particular scene property (e.g. object depth) is estimated from a restricted set of image measurements (e.g. image size), without reference to other scene properties.Such “Depth-from-X” approaches create problems for inference that include invalid and contradictory assumptions and difficulties in fusing the potentially inconsistent estimates.The computational problem posed by optimal inference is not hopeless, however, and can be surmounted by restricting inference to particular tasks and taking advantage of the statistical structure of the problem.In a Bayesian context, modularity falls out of the conditional independencies in the joint distribution of scenes and images p(S, I). However, restricting optimal inference to particular tasks has the effect of making the choice of representation for the scene variables non-trivial.In particular, some representations lead to simpler inference algorithms than others.We illustrate the problem of modularity and cue combination for the perception of depth from two highly disparate cues, cast shadow position and image size.While strong modularity would suggest ad hoc or no cue combination, we find that the performance of human subjects is better predicted by near-optimal cue combination.