Miracle-dz/UniFAR-FTUs huggingface dataset:
An Integrated Model of U.S. State Attorney General Behavior in Multi-State Litigation

Multi-state lawsuits, filed by U.S. state attorneys general (AGs), have become an important method by which state consumer protection laws are enforced. Patterns of participation in these lawsuits vary tremendously across the states, yet little is known about the factors driving this variation. I argue that state AGs are primarily concerned with achieving electoral and policymaking goals. Consequently, I expect AGs to be responsive to strong consumer interests and to participate in cases with severe infractions. Additionally, whether it is for public interest or electoral goals, AGs should be attracted to cases that promise bigger settlements. My analysis of each state's decision to join each of 172 multi-state lawsuits filed and settled between 1989 and 2002 provides support for each of these hypotheses.
Combinatorial Optimization of Pulverizers for Blended-Coal-Fired Power Plant

Coal blending has become an important way to ease the tension of coal purchase for many Chinese power plants. Mixed by pulverizers which has been widely used, is considered the most reasonable and convenient approach of coal blending. The implementation of this approach meet three main problems, that is to determine the optimum coal blending formula, to select the pulverizer combination for single coals and to allocate the outputs of pulverizers. Previous scholars have done a lot research on the model and algorithm of the first problem, but the latter two which were lack of theoretical guidance, rely mainly on experience in the application. To remedy this situation, a novel model of pulverizer optimization based on new indicators characterizing the burnout ands lagging characteristics, the property of stable combustion at low load and pollutant emissions characteristics among different pulverizer combinations, was proposed in this paper. The model contains the pulverizer-coal combination optimization and optimum output of each pulverizer, which are solved by exhaustive algorithm and non-dominated sorting genetic algorithm II(NSGA-II) respectively. It has now been successfully applied in the Dynamic Coal Blending Optimization System of Guangdong Red Bay Power Plant.
Discriminatively trained Probabilistic Linear Discriminant Analysis for speaker verification

Recently, i-vector extraction and Probabilistic Linear Discriminant Analysis (PLDA) have proven to provide state-of-the-art speaker verification performance. In this paper, the speaker verification score for a pair of i-vectors representing a trial is computed with a functional form derived from the successful PLDA generative model. In our case, however, parameters of this function are estimated based on a discriminative training criterion. We propose to use the objective function to directly address the task in speaker verification: discrimination between same-speaker and different-speaker trials. Compared with a baseline which uses a generatively trained PLDA model, discriminative training provides up to 40% relative improvement on the NIST SRE 2010 evaluation task.
The CB1 Neutral Antagonist Tetrahydrocannabivarin Reduces Default Mode Network and Increases Executive Control Network Resting State Functional Connectivity in Healthy Volunteers

Background: The cannabinoid cannabinoid type 1 (CB1) neutral antagonist tetrahydrocannabivarin (THCv) has been suggested as a possible treatment for obesity, but without the depressogenic side-effects of inverse antagonists such as Rimonabant. However, how THCv might affect the resting state functional connectivity of the human brain is as yet unknown. Method: We examined the effects of a single 10mg oral dose of THCv and placebo in 20 healthy volunteers in a randomized, within-subject, double-blind design. Using resting state functional magnetic resonance imaging and seed-based connectivity analyses, we selected the amygdala, insula, orbitofrontal cortex, and dorsal medial prefrontal cortex (dmPFC) as regions of interest. Mood and subjective experience were also measured before and after drug administration using self-report scales. Results: Our results revealed, as expected, no significant differences in the subjective experience with a single dose of THCv. However, we found reduced resting state functional connectivity between the amygdala seed region and the default mode network and increased resting state functional connectivity between the amygdala seed region and the dorsal anterior cingulate cortex and between the dmPFC seed region and the inferior frontal gyrus/medial frontal gyrus. We also found a positive correlation under placebo for the amygdala-precuneus connectivity with the body mass index, although this correlation was not apparent under THCv. Conclusion: Our findings are the first to show that treatment with the CB1 neutral antagonist THCv decreases resting state functional connectivity in the default mode network and increases connectivity in the cognitive control network and dorsal visual stream network. This effect profile suggests possible therapeutic activity of THCv for obesity, where functional connectivity has been found to be altered in these regions.
Morton Effect Cyclic Vibration Amplitude Determination for Tilt Pad Bearing Supported Machinery

This paper presents theoretical models and simulation results for the synchronous, thermal transient, instability phenomenon known as the Morton effect. A transient analysis of the rotor supported by tilting pad journal bearing is performed to obtain the transient asymmetric temperature distribution of the journal by solving the variable viscosity Reynolds equation, a 2D energy equation, the heat conduction equation, and the equations of motion for the rotor. The asymmetric temperature causes the rotor to bow at the journal, inducing a mass imbalance of overhung components such as impellers, which changes the synchronous vibrations and the journal’s asymmetric temperature. Modeling and simulation of the cyclic amplitude, synchronous vibration due to the Morton effect for tilting pad bearing supported machinery is the subject of this paper. The tilting pad bearing model is general and nonlinear, and thermal modes and staggered integration approaches are utilized in order to reduce computation time. The simulation results indicate that the temperature of the journal varies sinusoidally along the circumferential direction and linearly across the diameter. The vibration amplitude is demonstrated to vary slowly with time due to the transient asymmetric heating of the shaft. The approach’s novelty is the determination of the large motion, cyclic synchronous amplitude behavior shown by experimental results in the literature, unlike other approaches that treat the phenomenon as a linear instability. The approach is benchmarked against the experiment of de Jongh. [DOI: 10.1115/1.4007884]
How do we Measure the Environment? Linking Intertidal Thermal Physiology and Ecology Through Biophysics1

Abstract Recent advances in quantifying biochemical and cellular-level responses to thermal stress have facilitated a new exploration of the role of climate and climate change in driving intertidal community and population ecology. To fruitfully connect these disciplines, we first need to understand what the body temperatures of intertidal organisms are under field conditions, and how they change in space and time. Newly available data logger technology makes such an exploration possible, but several potential pitfalls must be avoided. Body temperature during aerial exposure is driven by multiple, interacting climatic factors, and extremes during low tide far exceed those during submersion. Moreover, because of effects of body size and morphology, two organisms exposed to identical climatic conditions can display very different body temperatures, which can also be substantially different from the temperature of the surrounding air. These same factors drive the temperature recorded by data loggers, and one logger type is unlikely to serve as an effective proxy for all organisms at a site. Here I describe the difficulties involved in quantifying patterns of body temperature in intertidal organisms, and explore the implications of this complexity for intertidal physiological ecology. I do so using data from temperature loggers designed to mimic the thermal characteristics of the mussel Mytilus californianus, and deployed at multiple sites along the West Coast of the United States. Results indicate a highly intricate pattern of thermal stress, where the interaction of climate with the dynamics of the tidal cycle determines the timing and magnitude of temperature extremes, creating a unique “thermal signal” at each site.
A packet-in message filtering mechanism for protection of control plane in openflow networks

Protecting control planes in networking hardware from high rate packets is a critical issue for networks under operation. One common approach for conventional networking hardware is to offload expensive functions onto hard-wired offload engines as ASICs. OpenFlow networks are expected to provide greater network control flexibility by an open interface to the packet-forwarding plane and by centralized controllers. In OpenFlow networks, the approach for conventional networking hardware alone is inadequate because it restricts a certain amount of flexibility that OpenFlow is expected to provide. Therefore, we need a generic control plane protection mechanism in OpenFlow switches as a last resort. In this paper, we propose a mechanism to filter out Packet-In messages without dropping important ones for network control. Our proposed mechanism works simply. Switches record the values of packet header fields before sending Packet-In messages, which are specified by the controllers in advance, and filter out packets that have the same values as the recorded ones. We implemented and evaluated the proposed mechanism on a prototype software switch, concluding that it dramatically reduces CPU loads in the switches and passes important Packet-In messages for network control.
EECS: an energy efficient clustering scheme in wireless sensor networks

Data gathering is a common but critical operation in many applications of wireless sensor networks. Innovative techniques that improve energy efficiency to prolong the network lifetime are highly required. Clustering is an effective topology control approach in wireless sensor networks, which can increase network scalability and lifetime. In this paper, we propose a novel clustering schema EECS for wireless sensor networks, which better suits the periodical data gathering applications. Our approach elects cluster heads with more residual energy through local radio communication while achieving well cluster head distribution; further more it introduces a novel method to balance the load among the cluster heads. Simulation results show that EECS outperforms LEACH significantly with prolonging the network lifetime over 35%.
Improving Legal Document Summarization Using Graphical Models

In this paper, we propose a novel idea for applying probabilistic graphical models for automatic text summarization task related to a legal domain. Identification of rhetorical roles present in the sentences of a legal document is the important text mining process involved in this task. A Conditional Random Field (CRF) is applied to segment a given legal document into seven labeled components and each label represents the appropriate rhetorical roles. Feature sets with varying characteristics are employed in order to provide significant improvements in CRFs performance. Our system is then enriched by the application of a term distribution model with structured domain knowledge to extract key sentences related to rhetorical categories. The final structured summary has been observed to be closest to 80% accuracy level to the ideal summary generated by experts in the area.
A Study of the Characteristics of Developers' Activities in GitHub

What types of developers do active software projects have? This paper presents a study of the characteristics of developers' activities in open source software development. GitHub, a widely-used hosting service for software development projects, provides APIs for collecting various kinds of GitHub data. To clarify the characteristics of developers' activities, we used these APIs to investigate GitHub events generated by each developer. Using this information, we categorized developers based on measures such as whether they prefer communication by coding or comments, or whether they are specialists or generalists. Our study indicates that active software projects have various kinds of developers characterized by different types of development activities.
An Alternative Canonical Approach to the Ghost Problem in a Complexified Extension of the Pais-Uhlenbeck Oscillator

Our purpose in this paper is to analyze the Pais-Uhlenbeck (PU) oscillator using complex canonical transformations. We show that starting from a Lagrangian approach we obtain a transformation that makes the extended PU oscillator, with unequal frequencies, to be equivalent to two standard second order oscillators which have the original number of degrees of freedom. Such extension is provided by adding a total time derivative to the PU Lagrangian together with a complexification of the original variables further subjected to reality conditions in order to maintain the required number of degrees of freedom. The analysis is accomplished at both the classical and quantum levels. Remarkably, at the quantum level the negative norm states are eliminated, as well as the problems of unbounded below energy and non-unitary time evolution. We illustrate the idea of our approach by eliminating the negative norm states in a complex oscillator. Next, we extend the procedure to the Pais-Uhlenbeck oscillator. The corresponding quantum propagators are calculated using Schwinger's quantum action principle. We also discuss the equal frequency case at the classical level.
Cooperative satellite to land mobile gap-filler-less interactive system architecture

Considerable efforts are being made in the area of interactive satellite broadcast services to mobiles, which range from the development of specific communication standards to the realization of practical proof-of-concept prototypes. The main reasons for such a big interest lie in the fact that interactive satellite services are a large potential market with many possible applications. Frequent and long-lasting shadowing caused by surrounding buildings in urban and suburban scenarios greatly limits system availability. The common approach to solve the problem consists in deploying fixed gap fillers, which imply a great consumption of economic and bandwidth resources. In the present paper we propose a novel hybrid satellite-terrestrial system architecture in which cooperative communication techniques are extensively adopted in order to reduce the number of gap-fillers needed to get a target system availability. Nodes are meant to have both networking and satellite communication capabilities so that each of them can possibly act as a Mobile Gap-Filler (MGF).
Novel GLP-1 Fusion Chimera as Potent Long Acting GLP-1 Receptor Agonist

GLP-1 has a variety of anti-diabetic effects. However, native GLP-1 is not suitable for therapy of diabetes due to its short half-life (t1/2<2 min). To circumvent this, we developed a long-lasting GLP-1 receptor agonist by the fusion of GLP-1 with human IgG2 Fc (GLP-1/hIgG2). ELISA-based receptor binding assay demonstrated that GLP-1/hIgG2 had high binding affinity to the GLP-1R in INS-1 cells (Kd = 13.90±1.52 nM). Upon binding, GLP-1/hIgG2 was rapidly internalized by INS-1 cells in a dynamin-dependent manner. Insulin RIA showed that GLP-1/IgG2 dose-dependently stimulated insulin secretion from INS-1 cells. Pharmacokinetic studies in CD1 mice showed that with intraperitoneal injection (i.p.), the GLP-1/hIgG2 peaked at 30 minutes in circulation and maintained a plateau for >168 h. Intraperitoneal glucose tolerance test (IPGTT) in mice showed that GLP-1/hIgG2 significantly decreased glucose excursion. Furthermore, IPGTT performed on mice one week after a single drug-injection also displayed significantly reduced glucose excursion, indicating that GLP-1/hIgG2 fusion protein has long-lasting effects on the modulation of glucose homeostasis. GLP-1/hIgG2 was found to be effective in reducing the incidence of diabetes in multiple-low-dose streptozotocin-induced type 1 diabetes in mice. Together, the long-lasting bioactive GLP-1/hIgG2 retains native GLP-1 activities and thus may serve as a potent GLP-1 receptor agonist.
Variants Affecting Exon Skipping Contribute to Complex Traits

DNA variants that affect alternative splicing and the relative quantities of different gene transcripts have been shown to be risk alleles for some Mendelian diseases. However, for complex traits characterized by a low odds ratio for any single contributing variant, very few studies have investigated the contribution of splicing variants. The overarching goal of this study is to discover and characterize the role that variants affecting alternative splicing may play in the genetic etiology of complex traits, which include a significant number of the common human diseases. Specifically, we hypothesize that single nucleotide polymorphisms (SNPs) in splicing regulatory elements can be characterized in silico to identify variants affecting splicing, and that these variants may contribute to the etiology of complex diseases as well as the inter-individual variability in the ratios of alternative transcripts. We leverage high-throughput expression profiling to 1) experimentally validate our in silico predictions of skipped exons and 2) characterize the molecular role of intronic genetic variations in alternative splicing events in the context of complex human traits and diseases. We propose that intronic SNPs play a role as genetic regulators within splicing regulatory elements and show that their associated exon skipping events can affect protein domains and structure. We find that SNPs we would predict to affect exon skipping are enriched among the set of SNPs reported to be associated with complex human traits.
A context ontology for pervasive service provision

Pervasive computing systems that strive to be minimally intrusive and exhibit inherent proactiveness and dynamic adaptability to the user preferences and environment need to be context-aware. Context-awareness provides computing environments with the ability to adapt the services or content they provide, by implicitly sensing and automatically deriving the users' needs from the context that surrounds them, making services more attentive, responsive and predictive. This paper is concerned with the development of an ambient context management system that aims to maximize the automation of the complete context knowledge lifecycle via the establishment of flexible prototype context ontology.
Fast filter-and-refine algorithms for subsequence selection

Large sequence databases, such as protein, DNA and gene sequences in biology, are becoming increasingly common. An important operation on a sequence database is approximate subsequence matching, where all subsequences that are within some distance from a given query string are retrieved. This paper proposes a filter-and-refine algorithm that enables efficient approximate subsequence matching in large DNA sequence databases. It employs a bitmap indexing structure to condense and encode each data sequence into a shorter index sequence. During query processing, the bitmap index is used to filter out most of the irrelevant subsequences, and false positives are removed in the final refinement step. Analytical and experimental studies show that the proposed strategy is capable of reducing response time substantially while incurring only a small space overhead.
MIP V 6 P ROTOCOLS : A SURVEY AND C OMPARATIVE A NALYSIS

As the future generation networks are envisioned to be heterogeneous in nature, seamless mobility in such networks is an important issue. While IETF work groups have standardized various mobility management protocols, such as Mobile IPv6 (MIPv6), Fast Handovers for Mobile IPv6 (Predictive FMIPv6, and Reactive FMIPv6), Hierarchical Mobile IPv6 (HMIPv6), Proxy Mobile IPv6 (PMIPv6) and Fast Handovers for PMIPv6 (Predictive FPMIPv6, and Reactive FPMIPv6), out of which some are host based and some are network based, the decision regarding which protocol suits the future networks is still a research issue. The study of various mobility management protocols in terms handover latency and the number of hops is needed to evaluate these protocols. Even though much study has been done in literature in terms of handover latency, study still needs performance evaluation in terms of average hop delay. In this paper we study various mobility management protocols by applying simple numerical analysis. The study is carried out for performance evaluation of various mobility management protocols in terms of average hop delay, wireless link delay, wired part delay, and binding update and registration delay. In this work, the average hop delay is estimated in terms of total handover latency and total number of hops contributing to each protocol. The study enables us to make a few important observations regarding the performance of these mobility management protocols.
Evaluating synchronization techniques for light-weight multithreaded/multicore architectures

This paper deals with architectures that expose novel concurrency models by using light-weight multithreading and support high computation to memory ratio by leveraging technologies such as Processing-In-Memory (PIM), Embedded DRAM, or Stacked Memory [1, 2]. In this paper we explore the idea of implementing key parallel processing functions such as synchronization locks and barriers for one such architecture, namely the Light-Weight Processing (LWP) architecture (Figure 1). Each LWP core is highly multithreaded, allowing a large number of hardware threads (order of 16-32 threads per core) to be concurrently in execution within both the LWP and the larger Light-Weight Processing Chip (LPC). The minimal state of these Light-Weight Threads (LWTs) make it possible to efficiently manage them in hardware. Support for large number of hardware threads needs to be backed by low overhead synchronization capability. The LWP architecture uses Full/Empty Bits (FEB) [1, 2] in memory to support fast producer-consumer communication. FEB append an extra bit to each word in memory and can exist in either Full or Empty state. This bit can be (re-)set atomically when performing a load/store instruction hence providing conditional access to the memory work depending on the state of the bit. This allows threads to block on memory words when the FEB status is not the same as expected. Unlike atomic memory operations, FEBs do not lock the entire memory bank but instead only lock the memory location under consideration. Multiple producer-consumer synchro-
A novel LTM-based method for multi-partition clustering

Early research work on clustering usually assumed that there was one true clustering of data. However, complex data are typically multifaceted and can be meaningfully clustered in many different ways. There is a growing interest in methods that produce multiple partitions of data. One such method is based on latent tree models (LTM). But previous methods for learning general LTM are computationally inefficient. In this paper, we propose a fast algorithm for learning LTM. Empirical results on two real world datasets are given to show that our method can produce rich and meaningful partitions.