Miracle-dz/UniFAR-FTUs huggingface dataset:
Automorphic symbols, p-adic L-functions and ordinary cohomology of Hilbert modular varieties

We introduce the notion of automorphic symbol generalizing the classical modular symbol and use it to attach very general $p$-adic $L$-functions to nearly ordinary Hilbert automorphic forms. Then we establish an exact control theorem for the $p$-adically completed cohomology of a Hilbert modular variety localized at a suitable nearly ordinary maximal ideal of the Hecke algebra. We also show its freeness over the corresponding Hecke algebra which turns out to be a universal deformation ring. In the last part of the paper we combine the above results to construct $p$-adic $L$-functions for Hida families of Hilbert automorphic forms in universal deformation rings of Galois representations.
A comparison of the pattern- and total deviation-based Glaucoma Change Probability programs.

PURPOSE To compare the rates of progression of visual field defects in glaucoma patients, by using the Glaucoma Change Probability program based on pattern deviation and total deviation probability maps. METHODS The incidence of progression of visual field loss among 67 eyes of 56 glaucoma patients with an average of 6 years of follow-up was estimated by applying the criteria set by the Early Manifest Glaucoma Treatment study, which uses the output from the Glaucoma Change Probability (GCP) program of the Humphrey Field Analyzer (San Leandro, CA) based on pattern deviation probability maps. This incidence estimate was compared with one obtained by applying the same criteria but using the GCP program based on total deviation probability maps. RESULTS The 6-year incidence of progression among patients with glaucoma was 23.2% and 35.7% using the GCP program based on pattern deviation and total deviation probability maps, respectively. Not all patients in whom visual field loss progressed according to pattern deviation also showed progression according to total deviation. CONCLUSIONS The GCP program based on pattern deviation probability maps appears to screen out patients in whom progression of visual field defects may be due to diffuse loss from cataract, but the pattern deviation maps may also be identifying other types of field loss not detected by the total deviation maps.
An adaptive AQM algorithm based on neuron reinforcement learning

In recent years, it has become an active research direction to develop adaptive and robust active queue management (AQM) scheme for congestion control of complex time-varying network. A novel adaptive AQM scheme based on Neuron Reinforcement Learning (NRL) is presented in this paper. This scheme uses queue length and link rate as congestion notification to determine an appropriate drop/mark probability, and the parameters of neuron can be adjusted online according to the time-varying network environment so that the stability of queue dynamics and robustness for fluctuation of TCP loads are guaranteed. This scheme is easy to implement with simple structure, and it is independent of the model of plant to be controlled. Simulation results show that this proposed algorithm is especially suitable for solving the complex network congestion control problem, and also has better stability and robustness.
School belonging among young adolescents with SEMH and MLD: the link with their social relations and school inclusivity

ABSTRACT Despite the considerable institutional changes schools have made to accommodate the individual needs of pupils with special educational needs and disabilities (SEND), as underpinned by key principles of inclusion, there is still international concern about the mainstream experiences pupils with SEND have in school settings. This study helps us understand the schooling experiences of pupils with behavioural difficulties and learning difficulties by investigating whether they have a sense of belonging and positive social relations and whether these vary according to the level of inclusiveness of the school ethos at the institution they attend. Perceived social relations and feelings of belonging of 1,440 (282 SEND) young adolescents from three secondary mainstream settings that differ in inclusivity, were analysed using a self-reporting questionnaire. Findings demonstrated that pupils with SEND are not a homogeneous group, as pupils with behavioural difficulties were found to have less of a sense of belonging, and social relations than those with learning difficulties. It was also found that the sense of belonging of both groups is associated with their positive perceived relations with teachers and their inclusiveness of school ethos. These findings contribute as they offer ways of enhancing the sense of belonging of pupils with behavioural and learning difficulties in schools.
Reverse Engineering Relational Schemas to Object-Orient ed Schemas

Due to the wide use of object-oriented technology in software development, reverse engineering of relational schemas to object-oriented schemas is gaining a lot of interest. One of the major problems with existing approaches for this schema mapping is the extensive amount of information that must be gathered either automatically or from the user. This paper presents an object-centered approach (as opposed to other relation-centered approaches) for doing the schema mapping. The procedure maps a 3NF relational schema into an object-oriented schema without the explicit use of inclusion dependencies and provides a greater scope for automation.
Ideal Strategy to Improve Datawarehouse Performance

—Data warehouse is set up for the benefits of business analysts and executives across all functional areas. The primary goal of data warehouse is to free the information locked up in the operational database so that decision makers and business analyst can make queries, analysis and planning regardless of the data changes in operational database. Data analysis in a large database requires some innovative techniques; there should be some new methods and procedures to look at the data with different angles. While executing adhoc queries over a large database degrade the query performance at considerable level because query will have to go through from large volume of data after making lot of joins. Moreover, as the number of queries is large, therefore, in certain cases there is reasonable probability that same query submitted by the one or multiple users at different times. Each time when query is executed, all the data of warehouse is analyzed to generate the result of that query. In this paper we purpose an ideal approach which definitely minimizes response time and improves the efficiency of data warehouse overall, particularly when data warehouse is updated at regular interval. This approach has been validated by Formal Method.
Induction of Intracellular Tau Aggregation Is Promoted by α-Synuclein Seeds and Provides Novel Insights into the Hyperphosphorylation of Tau

Intracytoplasmic proteinaceous inclusions, primarily composed of tau or α-synuclein (α-syn), are predominant pathological features of Alzheimer's disease (AD) and Parkinson's disease (PD), respectively. However, the coexistence of these pathological aggregates is identified in many neurodegenerative disorders, including spectrum disorders of AD and PD. Whereas α-syn can spontaneously polymerize into amyloidogenic fibrils, in vitro, tau polymerization requires an inducing agent. The current study presents a human-derived cellular model, in which recombinant, preformed α-syn fibrils cross-seed intracellular tau to promote the formation of neurofibrillary tangle-like aggregates. These aggregates were hyperphosphorylated, Triton insoluble, and thioflavin-S positive, either comingling with endogenously expressed α-syn aggregates or induced by only exogenously applied recombinant α-syn fibrils. Furthermore, filamentous, amyloidogenic tau took over the cellular soma, displacing the nucleus and isolating or displacing organelles, likely preventing cellular function. Although a significant proportion of wild-type tau formed these cellular inclusions, the P301L mutation in tau increased aggregation propensity resulting from α-syn seeds to over 50% of total tau protein. The role of phosphorylation on the development of these tau aggregates was investigated by coexpressing glycogen synthase kinase 3 β or microtubule-associated protein/microtubule affinity-regulating kinase 2. Expression of either kinase inhibited the formation of α-syn-induced tau aggregates. Analyses of phosphorylation sites suggest that multiple complex factors may be associated with this effect and that Triton-soluble versus Triton-insoluble tau may be independently targeted by kinases. The current work not only provides an exceptional cellular model of tau pathology, but also examines α-syn-induced tau inclusion formation and provides novel insights into hyperphosphorylation observed in disease.
Acculturation in context: The moderating effects of immigrant and native peer orientations on immigrants’ acculturation experiences

Immigrant adolescents have to navigate through a complex social environment consisting of, at least, both a native and a co-ethnic community. This study used a multi-level framework to consider two research questions involving this complexity. The individual-level associations of acculturation orientations and acculturative hassles (language and sociocultural adaptation) was assessed in immigrant youths, and whether this association differs depending on the school-level acculturation orientations held by co-ethnic peers, and the school-level orientations toward immigrants held by native German peers. We then investigated whether acculturative hassles are associated with the psychosocial functioning (self-efficacy, depressive symptoms) of immigrant adolescents. The sample comprised 650 ethnic German Diaspora migrant adolescents (mean age 15.6 years, 53.7 % female) and their 787 native German peers (mean age 15.05 years, 51 % female). The results showed that contextual factors (co-ethnic acculturation orientation, native friendship preferences) moderated the association between the acculturation orientations of adolescent immigrants and both types of acculturative hassles. Acculturative hassles, in turn, were associated with the psychosocial functioning of adolescents. This research demonstrates that a person-by-context perspective is needed to better understand the adaptation of adolescent immigrants. This perspective has to take into account both the native and the co-ethnic peer environment.
A Simplified Full-Duplex Wavelength Interleaved DWDM Hybrid Access Radio-Over-Fiber System

We demonstrate a simplified full-duplex wavelength interleaved (WI)-DWDM hybrid access radio-over-fiber (ROF) system for providing 2 GB/s wired and 1 GB/s wireless downlink and 1 GB/s uplink data data simultaneously. In this scheme, we use only one arrayed waveguide grating device to realize both the demultiplexing and multiplexing functions. Because of using only the subcarriers of the single channel to carry both the wired and wireless data, we do not need extra optical components such as interleaver to separate them at the base stations. The experimental results demonstrate that this scheme is feasible and has good transmission performance for the future WI-DWDM hybrid access ROF system.
Supervised Morphology Generation Using Parallel Corpus

Translating from English, a morphologically poor language, into morphologically rich languages such as Persian comes with many challenges. In this paper, we present an approach to rich morphology prediction using a parallel corpus. We focus on the verb conjugation as the most important and problematic phenomenon in the context of morphology in Persian. We define a set of linguistic features using both English and Persian linguistic information, and use an English-Persian parallel corpus to train our model. Then, we predict six morphological features of the verb and generate inflected verb form using its lemma. In our experiments, we generate verb form with the most common feature values as a baseline. The results of our experiments show an improvement of almost 2.1% absolute BLEU score on a test set containing 16K sentences.
Mechatronics Characterization of a Novel High-Performance Ergonomic Exoskeleton for Space Robotics Telepresence

This paper introduces the mechatronic design of the X-Arm-2 haptic exoskeleton. The X-Arm-2 is a new and fully actuated force-reflecting human arm exoskeleton, based on our previously proposed ergonomic kinematic exoskeleton structure [1]. The X-Arm-2 is the result of an overall research effort on ergonomic haptic wearable devices [2]. This effort has led to a power-dense haptic device design that is explicitly human-centered. The X-Arm-2 can a) interact with varying operator arm sizes without requiring adjustments (5 th – 95 th %-ile range for Astronaut crew), b) provide crisp force-feedback performance through a human-oriented scaling and implementation of actuators and torque sensors, c) interact with the full workspace of the human limb without limiting natural movement and without creating interface forces [3] and d) has a low overall mass (without motor drivers) of only 6.2 kg. The inertia of its movable structure was minimized by re-locating some of its most powerful drives via Bowden cable transmissions [4].
Coordination Assistance for Mixed Human and Computational Agent Systems

In many application areas (such as concurrent engineering, software development, hospital scheduling, manufacturing scheduling, and military planning), individuals are responsible for an agenda of tasks and face choices about the best way to locally handle each task, in what order to do tasks, and when to do them. Such decisions are often hard to make because of coordination problems: individual tasks are related to the tasks of others in complex ways, and there are many sources of uncertainty (no one has a complete view of the task structure at arbitrary levels of detail, the situation may be changing dynamically, and no one is entirely sure of the outcomes of all of their actions). The focus of this paper is the development of support tools for distributed, cooperative work by groups (collaborative teams) of human and computational agents. We will discuss the design of a set of distributed autonomous computer programs (“agents”) that assist people in coordinating their activities by helping them to manage their agendas. Our approach can also supply coordination and scheduling facilities to computational domain agents (such as autonomous design checkers or databases). We briefly describe an initial implementation of these ideas using only computational agents and abstract task environments. This work was supported by DARPA contract N00014-92-J-1698, Office of Naval Research contract N00014-92-J-1450, and NSF contract IRI-9321324. The content of the information does not necessarily reflect the position or the policy of the Government and no official endorsement should
Insight into 3D goal-directed movements through a division into meaningful movement phases

The measures that are currently used to evaluate users’ performances on interaction tasks in virtual environments often do not provide sufficient information for how to improve these interactions. The current paper proposes a new method for analyzing 3D goal-directed movements based on dividing them into meaningful phases. We apply the method to experimental data that we have collected earlier for a 3D task that resembles a standardized 2D multi-directional pointing task (ISO 9241-9). Our analysis demonstrates how a more detailed insight into 3D goal-directed movements can be gained. We claim that this analysis can help to better identify weak and strong points of input devices or interaction techniques.
A Sketch-based Clustering Algorithm for Uncertain Data Streams

Due to the inaccuracy and noisy, uncertainty is inherent in time series streams, and increases the complexity of streams clustering. For the continuous arriving and massive data size , efficient data storage is a crucial task for clustering uncertain data streams. With hash-compressed structure , an extended uncertain sketch and update strategy are proposed to store uncertain data streams . And based on divergence and sketch metric , a sketch based similarity is given to measure objects distances . Then with core-sets and the max-min cluster distance measure, an initial cluster centers selection algorithm is proposed to improve the quality of clustering uncertain time series streams. Finally, the effectiveness of the proposed clustering algorithm is illustrated through the experimental results.
Tissue biomarkers in cancer of the urinary bladder and kidney : High-throughput tissue microarrays in the study of urinary tract malignancies

9 REVIEW OF THE LITERATURE 11 High-throughput techniques in cancer research 11 Tissue microarrays 11 Construction of TMAs 13 Detection of targets on TMA slides 13 TMA technique in cancer research 15 Limitations 16 Tumor profiling 17 Biomarkers 18 Actin-associated proteins 18 Markers of proliferation 20 Tumor suppressor proteins 21 Urinary bladder cancer 23 Overview 23 Pathological classification 24 Pathophysiology 24 Markers associated with bladder malignancies 24 Renal cell carcinoma 27 Overview 27 Pathological classification 27 Pathophysiology 28 Markers associated with renal malignancies 30 Future prospects 30 AIMS OF THE STUDY 35 MATERIALS AND METHODS 36 Patient samples 36 Urothelial cancer 36 Renal cancer 36 Tissue microarrays 38
Special relative permeability functions with analytical solutions for transient flow into unsaturated rock matrix

This paper presents a class of analytical solutions for transient flow into unsaturated rock matrix. These analytical solutions are derived using specially correlated, physically meaningful relative permeability and capillary functions. The transient flow processes in unsaturated rock matrix blocks are generally described by the Richards' equation. The analytical solutions describe the full transient behavior of flow into unsaturated matrix blocks and have proven (through various examples) to be useful for verifying numerical model results.
Geographic Location-Based Service Reliability Prediction

How to design an effective and efficient reliability prediction method for services is one of the important topics in the research field of Services Computing. With the increasing complexity of network environments, the effect of network environments and other environments related properties on service reliability cannot be neglected any more. However, most of the existing reliability prediction methods focus on the service itself, and have not paid enough attention to the potential impact of external factors on service reliability, which leads to the result that accuracy of predicted reliability of services cannot be guaranteed. To address the problems above, a geographic location-based reliability prediction method (GLBRP) for services is proposed in this paper. Mapping techniques and Pearson Correlation Coefficient are used to classify users based on users' geographic location information. Deductive reasoning and ontology as well as the calculation of similarity are also employed to clarify services based on services' location information. Effective feedback can be extracted based on the grouping of users and services. Service reliability is predicted through the smoothing forecasting method of weighted moving series on effective feedback. Simulation results show that the proposed GLBRP method can significantly improve accuracy and efficiency of prediction results compared with other methods.
Improving reverberant VTS for hands-free robust speech recognition

Model-based approaches to handling additive background noise and channel distortion, such as Vector Taylor Series (VTS), have been intensively studied and extended in a number of ways. In previous work, VTS has been extended to handle both reverberant and background noise, yielding the Reverberant VTS (RVTS) scheme. In this work, rather than assuming the observation vector is generated by the reverberation of a sequence of background noise corrupted speech vectors, as in RVTS, the observation vector is modelled as a superposition of the background noise and the reverberation of clean speech. This yields a new compensation scheme RVTS Joint (RVTSJ), which allows an easy formulation for joint estimation of both additive and reverberation noise parameters. These two compensation schemes were evaluated and compared on a simulated reverberant noise corrupted AURORA4 task. Both yielded large gains over VTS baseline system, with RVTSJ outperforming the previous RVTS scheme.
Investigation of localized coupled-cavity modes in two-dimensional photonic bandgap structures

We present a detailed study of the localized coupled-cavity modes in 2-D dielectric photonic crystals. The transmission, phase, and delay time characteristics of the various coupled-cavity structures are measured and calculated. We observed the eigenmode splitting, waveguiding through the coupled cavities, splitting of electromagnetic waves in waveguide ports, and switching effect in such structures. The corresponding field patterns and the transmission spectra are obtained from the finite-difference-time-domain (FDTD) simulations. We also develop a theory based on the classical wave analog of the tight-binding (TB) approximation in solid state physics. Experimental results are in good agreement with the FDTD simulations and predictions of the TB approximation.
Computational Intelligence in Gait Research: A Perspective on Current Applications and Future Challenges

Our mobility is an important daily requirement so much so that any disruption to it severely degrades our perceived quality of life. Studies in gait and human movement sciences, therefore, play a significant role in maintaining the well-being of our mobility. Current gait analysis involves numerous interdependent gait parameters that are difficult to adequately interpret due to the large volume of recorded data and lengthy assessment times in gait laboratories. A proposed solution to these problems is computational intelligence (CI), which is an emerging paradigm in biomedical engineering most notably in pathology detection and prosthesis design. The integration of CI technology in gait systems facilitates studies in disorders caused by lower limb defects, cerebral disorders, and aging effects by learning data relationships through a combination of signal processing and machine learning techniques. Learning paradigms, such as supervised learning, unsupervised learning, and fuzzy and evolutionary algorithms, provide advanced modeling capabilities for biomechanical systems that in the past have relied heavily on statistical analysis. CI offers the ability to investigate nonlinear data relationships, enhance data interpretation, design more efficient diagnostic methods, and extrapolate model functionality. These are envisioned to result in more cost-effective, efficient, and easy-to-use systems, which would address global shortages in medical personnel and rising medical costs. This paper surveys current signal processing and CI methodologies followed by gait applications ranging from normal gait studies and disorder detection to artificial gait simulation. We review recent systems focusing on the existing challenges and issues involved in making them successful. We also examine new research in sensor technologies for gait that could be combined with these intelligent systems to develop more effective healthcare solutions.