Miracle-dz/UniFAR-FTUs huggingface dataset:
Feedback particle filter: Application and evaluation

Recent research has provided several new methods for avoiding degeneracy in particle filters. These methods implement Bayes' rule using a continuous transition between prior and posterior. The feedback particle filter (FPF) is one of them. The FPF uses feedback gains to adjust each particle according to the measurement, which is in contrast to conventional particle filters based on importance sampling. The gains are found as solutions to partial differential equations. This paper contains an evaluation of the FPF on two highly nonlinear estimation problems. The FPF is compared with conventional particle filters and the unscented Kalman filter. Sensitivity to the choice of gains is discussed and illustrated. We demonstrate that with a sensible approximation of the exact gain function, the FPF can decrease tracking errors with more than one magnitude while significantly improving the quality of the particle distribution.
Model-based image analysis of human motion using constraint propagation

A system capable of analyzing image sequences of human motion is described. The system is structured as a feedback loop between high and low levels: predictions are made at the semantic level and verifications are sought at the image level. The domain of human motion lends itself to a model-driven analysis, and the system includes a detailed model of the human body. All information extracted from the image is interpreted through a constraint network based on the structure of the human model. A constraint propagation operator is defined and its theoretical properties outlined. An implementation of this operator is described, and results of the analysis system for short image sequences are presented.
The Vasopressin System: Physiology and Clinical Strategies

Vasopressin, synthesized in the hypothalamus, is released by increased plasma osmolality, decreased arterial pressure, and reductions in cardiac volume. Three subtypes of vasopressin receptors, V1, V2, and V3, have been identified, mediating vasoconstriction, water reabsorption, and central nervous system effects, respectively. Vasopressin and its analogs have been studied intensively for the treatment of states of “relative vasopressin deficiency,” such as sepsis, vasodilatory shock, intraoperative hypotension, and cardiopulmonary resuscitation. Infusion of vasopressin (0.01–0.04 U/min) decreases catecholamine requirements in patients with sepsis and other types of vasodilatory shock. Bolus application of 1 mg terlipressin, the V1 agonist, reverses refractory hypotension in anesthetized patients and has been studied in patients with septic shock and chronic liver failure. During cardiopulmonary resuscitation, a 40-U bolus dose of vasopressin may be considered to replace the first or second bolus of epinephrine regardless of the initial rhythm. The side effects of vasopressin and its analogs must be further characterized.
Extrinsic Evaluation of Dialog State Tracking and Predictive Metrics for Dialog Policy Optimization

During the recent Dialog State Tracking Challenge (DSTC), a fundamental question was raised: “Would better performance in dialog state tracking translate to better performance of the optimized policy by reinforcement learning? ” Also, during the challenge system evaluation, another nontrivial question arose: “Which evaluation metric and schedule would best predict improvement in overall dialog performance? ” This paper aims to answer these questions by applying an off-policy reinforcement learning method to the output of each challenge system. The results give a positive answer to the first question. Thus the effort to separately improve the performance of dialog state tracking as carried out in the DSTC may be justified. The answer to the second question also draws several insightful conclusions on the characteristics of different evaluation metrics and schedules.
Gate Current Reduction and Improved DC/RF Characteristics in GaN-Based MOS-HEMTs Using Thermally Grown TiO2 as a Dielectric

This paper demonstrates a reduction in the gate leakage current and improvement in transistor characteristics in thermally grown TiO2/AlGaN/GaN heterostructure-based metal–oxide–semiconductor high-electron-mobility transistors (MOS-HEMTs). In contrast to the conventional AlGaN/GaN HEMTs, thermionic field emission through gate is not the dominant current transport mechanism for the thermally grown TiO2/AlGaN interface. The gate current is greatly affected by the properties of the oxide material and oxide–semiconductor interface in addition to the property of the barrier layer. The MOS-HEMTs with a 3.4-nm-thick TiO2 gate insulator exhibits a low gate leakage current of 10−8 Acm−2, which leads to superior device performances in terms of saturation drain current, peak transconductance, subthreshold swing, and unity gain frequency of 620 mA/mm, 158 mS/mm, 75 mV/decade, and 7 GHz, respectively, for a 400-nm gate length device. This is further augmented by an increase in ON/OFF ratio to ${5}\times {10}^{{8}}$ and a large reduction in the subthreshold leakage current by at least two orders of magnitude in comparison to that of a control HEMT. Trap-assisted tunneling (TAT) and Poole–Frenkel (PF) emission are found to be the dominant current mechanisms for gate leakage at high temperatures and moderate electric field. The activation energy of traps in PF emission is found to be 0.49 eV, and the extracted trap energy levels for the TAT are found to be in the range of 1.7–2.2 eV. The reverse bias current is found to saturate at high voltages when the field across the diode also saturates. The transistor characteristics improvement is largely ascribed to an increase in 2-D electron gas (2DEG) density.
The Coactivator PGC-1 Cooperates with Peroxisome Proliferator-Activated Receptor α in Transcriptional Control of Nuclear Genes Encoding Mitochondrial Fatty Acid Oxidation Enzymes

ABSTRACT Peroxisome proliferator-activated receptor α (PPARα) plays a key role in the transcriptional control of genes encoding mitochondrial fatty acid β-oxidation (FAO) enzymes. In this study we sought to determine whether the recently identified PPAR gamma coactivator 1 (PGC-1) is capable of coactivating PPARα in the transcriptional control of genes encoding FAO enzymes. Mammalian cell cotransfection experiments demonstrated that PGC-1 enhanced PPARα-mediated transcriptional activation of reporter plasmids containing PPARα target elements. PGC-1 also enhanced the transactivation activity of a PPARα-Gal4 DNA binding domain fusion protein. Retroviral vector-mediated expression studies performed in 3T3-L1 cells demonstrated that PPARα and PGC-1 cooperatively induced the expression of PPARα target genes and increased cellular palmitate oxidation rates. Glutathione S-transferase “pulldown” studies revealed that in contrast to the previously reported ligand-independent interaction with PPARγ, PGC-1 binds PPARα in a ligand-influenced manner. Protein-protein interaction studies and mammalian cell hybrid experiments demonstrated that the PGC-1–PPARα interaction involves an LXXLL domain in PGC-1 and the PPARα AF2 region, consistent with the observed ligand influence. Last, the PGC-1 transactivation domain was mapped to within the NH2-terminal 120 amino acids of the PGC-1 molecule, a region distinct from the PPARα interacting domains. These results identify PGC-1 as a coactivator of PPARα in the transcriptional control of mitochondrial FAO capacity, define separable PPARα interaction and transactivation domains within the PGC-1 molecule, and demonstrate that certain features of the PPARα–PGC-1 interaction are distinct from that of PPARγ–PGC-1.
A high precision visual localization sensor and its working methodology for an indoor mobile robot

To overcome the shortcomings of existing robot localization sensors, such as low accuracy and poor robustness, a high precision visual localization system based on infrared-reflective artificial markers is designed and illustrated in detail in this paper. First, the hardware system of the localization sensor is developed. Secondly, we design a novel kind of infrared-reflective artificial marker whose characteristics can be extracted by the acquisition and processing of the infrared image. In addition, a confidence calculation method for marker identification is proposed to obtain the probabilistic localization results. Finally, the autonomous localization of the robot is achieved by calculating the relative pose relation between the robot and the artificial marker based on the perspective-3-point (P3P) visual localization algorithm. Numerous experiments and practical applications show that the designed localization sensor system is immune to the interferences of the illumination and observation angle changes. The precision of the sensor is ±1.94 cm for position localization and ±1.64◦ for angle localization. Therefore, it satisfies perfectly the requirements of localization precision for an indoor mobile robot.
Multiple object identification with passive RFID tags

We investigate the applicability of passive RFID systems to the task of identifying multiple tagged objects simultaneously, assuming that the number of tags is not known in advance. We present a combinatorial model of the communication mechanism between the reader device and the tags, and use this model to derive the optimal parameter setting for the reading process, based on estimates for the number of tags. Some results on the performance of an implementation are presented.
Real-Time Solution of the Inverse Kinematic-Rate Problem

Solving the inverse kinematic-rate problem is an old and ever-present problem in robotics. Many methods of solution for this problem have been discussed over the past 30 years and, as computational speeds have improved, there has been greater expectation that this calculation will be performed online. This paper compares the merits of many of the methods already presented and describes a new approach that leads to a fast and numerically well-conditioned algorithm. This method is most advantageous for robots with a spherical wrist, which is a common feature among industrial robots. More important, we uncover some interesting properties of efficient solutions that can be applied to a variety of robot architectures. We apply this and other methods to an industrial robot with near to PUMA geometry and report calculation speeds indicative of the real-time cost of each of the several procedures.
A prototype for unsupervised analysis of tissue microarrays for cancer research and diagnostics

The tissue microarray (TMA) technique enables researchers to extract small cylinders of tissue from histological sections and arrange them in a matrix configuration on a recipient paraffin block such that hundreds can be analyzed simultaneously. TMA offers several advantages over traditional specimen preparation by maximizing limited tissue resources and providing a highly efficient means for visualizing molecular targets. By enabling researchers to reliably determine the protein expression profile for specific types of cancer, it may be possible to elucidate the mechanism by which healthy tissues are transformed into malignancies. Currently, the primary methods used to evaluate arrays involve the interactive review of TMA samples while they are viewed under a microscope, subjectively evaluated, and scored by a technician. This process is extremely slow, tedious, and prone to error. In order to facilitate large-scale, multi-institutional studies, a more automated and reliable means for analyzing TMAs is needed. We report here a web-based prototype which features automated imaging, registration, and distributed archiving of TMAs in multiuser network environments. The system utilizes a principal color decomposition approach to identify and characterize the predominant staining signatures of specimens in color space. This strategy was shown to be reliable for detecting and quantifying the immunohistochemical expression levels for TMAs.
Novel GDAP1 Mutation in a Vietnamese Family with Charcot-Marie-Tooth Disease

Background Mutations of GDAP1 gene cause autosomal dominant and autosomal recessive Charcot-Marie-Tooth (CMT) disease and over 80 different mutations have been identified so far. This study analyzed the clinical and genetic characteristics of a Vietnamese CMT family that was affected by a novel GDAP1 mutation. Methods We present three children of a family with progressive weakness, mild sensory loss, and absent tendon reflexes. Electrodiagnostic analyses displayed an axonal type of neuropathy in affected patients. Sequencing of GDAP1 gene was requested for all members of the family. Results All affected individuals manifested identical clinical symptoms of motor and sensory impairments within the first three years of life, and nerve conduction study indicated the axonal degeneration. A homozygous GDAP1 variant (c.667_671dup) was found in the three affected children as recessive inheritance pattern. The mutation leads to a premature termination codon that shortens GDAP1 protein (p.Gln224Hisfs∗37). Further testing showed heterozygous c. 667_671dup variant in the parents. Discussion Our study expands the mutational spectrum of GDAP1-related CMT disease with the new and unreported GDAP1 variant. Alterations in GDAP1 gene should be evaluated as CMT causing variants in the Vietnamese population, predominantly axonal form of neuropathy in CMT disease.
An Attempt to Design a Better Algorithm for the Uncapacitated Facility Location Problem

The uncapacitated facility location has always been an important problem due to its connection to operational research and infrastructure planning. Byrka obtained an algorithm that is parametrized by $\gamma$ and proved that it is optimal when $\gamma>1.6774$. He also proved that the algorithm achieved an approximation ratio of 1.50. A later work by Shi Li achieved an approximation factor of 1.488. In this research, we studied these algorithms and several related works. Although we didn't improve upon the algorithm of Shi Li, our work did provide some insight into the problem. We also reframed the problem as a vector game, which provided a framework to design balanced algorithms for this problem.
A Multiagent Platform for Educational Resources Retrieval driven by Cultural Aspects

In this work we propose a multiagent architecture for web educational resources retrieval that helps users to find courses according to their personal and cultural aspects. Cultural aspects are preferences and ways of behavior determined by the person’s culture. In this work, the cultural aspects are just the features that distinguish between the preferences of users from different regions. This multiagent platform includes several kinds of agents with different functionalities. We particularly model the Educational Resources Finder Agent as a Graded BDI Agent, which is in charge of a flexible retrieval of the best courses according to the student profile. We outline the overall multiagent system and present an example illustrating the searching process.
An intelligent semi-automatic application porting system for application accelerators

Work involving the use of application acceleration devices is showing great promise, however, there are still major obstacles preventing their widespread adoption. Currently the process of porting applications to an accelerator requires expertise in both the computer science and application domains, due to the lack of abstraction available. We present our work associated with the development of a novel solution to this abstraction problem; an intelligent semi-automatic application porting system, that will allow a higher level of abstraction, to be presented to the end user, while maintaining reasonable performance levels. A prototype system has been constructed that can successfully port applications to Graphics Processing Units (GPUs) and shows promising results in terms of performance comparisons between CPU and GPU. We are presently extending our prototype to other application acceleration devices and to allow the automatic selection of the most appropriate device for an application using Machine Learning techniques. We expect our work and results will be of widespread interest to the increasing community involved in porting code to application accelerators.
Structure of the Photon

The photon is of course the gauge boson of QED, and is as far as we know elementary. When we measure photon “structure”, what we are in fact doing is probing the quantum fluctuations of the field theory. The photon couples - via a splitting into virtual, charged fermion-antifermion pairs - into the electroweak and strong interactions. Such behaviour is an important aspect of quantum field theories, and similar phenomena arise in many different situations. For example, the gluon splitting to quarks drives the scaling violations in hadronic structure. Studies of photon structure test our understanding of this behaviour. In this talk I give an overview of the current data and phenomenology, and outline some opportunities available in the medium term future.
Under the Radar: The Effects of Monitoring Firms on Tax Compliance

This paper analyzes the effects of size-dependent tax enforcement on firms' tax compliance. We exploit quasi-experimental variation generated by a Large Taxpayers Unit (LTU) in Spain, which monitors firms with more than €6 million in reported revenue. Firms strategically bunch below the eligibility threshold in order to avoid stricter tax enforcement. The response is stronger in sectors where transactions leave more paper trail, suggesting that monitoring effort and the traceability of information reported by firms are complements. We estimate that there would be substantial welfare gains from extending stricter tax monitoring to smaller businesses.
Triterpenoid Biosynthesis and Engineering in Plants

Triterpenoid saponins are a diverse group of natural products in plants and are considered defensive compounds against pathogenic microbes and herbivores. Because of their various beneficial properties for humans, saponins are used in wide-ranging applications in addition to medicinally. Saponin biosynthesis involves three key enzymes: oxidosqualene cyclases, which construct the basic triterpenoid skeletons; cytochrome P450 monooxygenases, which mediate oxidations; and uridine diphosphate-dependent glycosyltransferases, which catalyze glycosylations. The discovery of genes committed to saponin biosynthesis is important for the stable supply and biotechnological application of these compounds. Here, we review the identified genes involved in triterpenoid biosynthesis, summarize the recent advances in the biotechnological production of useful plant terpenoids, and discuss the bioengineering of plant triterpenoids.
A new approach in single Image Super Resolution

Super Resolution image reconstruction tries to obtain a high resolution image from one or more observed low resolution images of the same scene, using signal processing techniques. Variety of super resolution methods have been proposed in last decades. In this paper, we propose a new super resolution algorithm based on single low resolution image. As the super resolution reconstruction is an inverse problem, our method consists of three phases up-sampling, deblurring and denoising. Experimental results show the effectiveness of the proposed method.
Roll Clouds Associated with an East Asian Cold Front

Abstract On 11 January 1998, a cold front formed in southeast China as a result of a cold-air outbreak in northeast Asia. During this synoptic development, a series of roll clouds (along the SW–NE direction) was observed in East Asia; some of the clouds stretched for over a thousand kilometers. This roll cloud formation moved southeastward across Taiwan, the Ryukyu Islands, and Japan, and eventually into the open ocean. In order to explore the possible cause of these roll clouds the following preliminary analyses were made in this study: the location of roll clouds relative to the cold front was determined in terms of the contrast between the infrared images of the Geostationary Meteorological Satellite of Japan and surface charts issued by the JapanMeteorological Agency, the intrusion of the density current was identified using upper-air soundings at Taipei, and the migrations of roll clouds and the cold front were judged by comparing the arrival time of the first roll cloud and the front with time serie.
Joint relevance and answer quality learning for question routing in community QA

Community question answering (cQA) has become a popular service for users to ask and answer questions. In recent years, the efficiency of cQA service is hindered by a sharp increase of questions in the community. This paper is concerned with the problem of question routing. Question routing in cQA aims to route new questions to the eligible answerers who can give high quality answers. However, the traditional methods suffer from the following two problems: (1) word mismatch between the new questions and the users' answering history; (2) high variance in perceived answer quality. To solve the above two problems, this paper proposes a novel joint learning method by taking both word mismatch and answer quality into a unified framework for question routing. We conduct experiments on large-scale real world data set from Yahoo! Answers. Experimental results show that our proposed method significantly outperforms the traditional query likelihood language model (QLLM) as well as state-of-the-art cluster-based language model (CBLM) and category-sensitive query likelihood language model (TCSLM).
Theory Of Planned Behavior Implementation (Planned Behavior) In Mother Behavior In Postpartum Care In The House Of Mother's Children Fauziah Tulungagung

Postpartum or puerperium begins 1 hour after birth of the placenta up to 6 weeks (42 days) afterwards. Parents, especially mothers, need to have the knowledge and readiness to conceive, give birth and breastfeed children. One of the factors that can cause maternal death is complications that occur during the puerperium. Postpartum complications of the highest incidence rate in Indonesia are bleeding and infection. This research is an observational analytic research with cross sectional approach. In the cross-sectional study, the researchers conducted observations or measurements of variables at one particular moment. Measurement of variables in one moment does not mean that all objects are observed exactly at the same time, but it means that each subject is observed only once and the measurement of the subject variable is performed during the examination. The results of research based on chi square test showed a significant influence that is attitude ρ = 0,18 where ρ > α (0,05) so that H0 accepted mean no attitude influence. The subjective norm ρ = 0.35> ρ > α (0,05) so that H0 is accepted which means there is no influence between subjective norms. Ability to control ρ = 0.12 > ρ > α (0,05) so that H0 is accepted which means there is no influence between the perception of control ability. Interest ρ = 0.96 > ρ > α (0.05) so that H0 is accepted which means there is no influence of interest. The most dominant fator is the education level, p = 0.03 > p < α (0.05) so that H0 is rejected which means there is an influence between the level of education in behavior on postpartum care at Rumah Sakit Ibu Anak Fauziah Tulungagung. The Health Service of Tulungagung through mother's hospital Fauziah is expected to socialize the community about postpartum care so that the public can express the problems especially the mothers without burdened by the existence of panisment such as influence in value and others.