Miracle-dz/UniFAR-FTUs huggingface dataset:
Face recognition based on KPCA and SVM

KPCA algorithm can solve the problem of nonlinear characteristic that the PCA algorithm can't handle with and the traditional curvelet decomposition algorithm cannot take full advantage of the fine scale component information. So we put forward KPCA algorithm and data fusion algorithm. The KPCA algorithm has a good effect on extracting face contour and the curve detail information through internal nonlinear kernel function. Data fusion algorithm can make use of different scale of image which decomposed by curvelet according to certain proportion. Support Vector Machine (SVM) has the strong ability of classification of small samples and the advantage of dealing with nonlinear and high dimension. In this paper, the KPCA and SVM methods were combined with and used for face recognition. At first, the paper made use of the low-frequency of the face images decomposed by curvelet transform, then the feature vectors were extracted by KPCA, and the strategy of “one vs one” of SVM was chosen to perform recognition. The results based on the ORL and Yale shows the success of KPCA+SVM employed in face recognition. Then the curvelet faces were reduced dimension by PCA. The coarse information and the fine information were combined by data fusion. The results based on the ORL shows the success of data fusion employed in face recognition.
Fuzzy information and degree of resolution within the context of a control hierarchy

The authors discuss a hierarchical control structure from the viewpoints of the degree of information resolution and the fuzziness of the knowledge base at various levels of the hierarchy. In particular, the concept of fuzzy resolution is addressed. The specific control system considered is a workcell for automated mechanical processing of fish. Qualitatively, the required information resolution decreases and fuzziness of the knowledge base increases with the hierarchical level of the system. Correspondingly, the fuzzy resolution will decrease. Also, since the quantity of data increases with resolution, and, furthermore, the duration of event cycles is generally longer at high levels, the bandwidth of information and control will decrease with the hierarchical level. These considerations are equally applicable to control, sensing, and organizational functions within the hierarchical structure. >
Validation of compact models of microcantilever actuators for RF-MEMS application

Microcantilever specimens for in-plane and out-of-plane bending tests are here analyzed. Experimental validation of 2D and 3D numerical models is performed. Main features of in-plane and out-of-plane layouts are then discussed. Effectiveness of plane models to predict pull-in in presence of geometric nonlinearity due to a large tip displacement and initial curvature of microbeam is investigated. The paper is aimed to discuss the capability of 2D models to be used as compact tools to substitute some model order reduction techniques, which appear unsuitable in presence of both electromechanical and geometric nonlinearities.
Simulation-based study on the effect of inversion charge layer on triple material double gate Tunnel FET

The impact of inversion charge layer on triple material double gate (TMDG) Tunnel FET (TFET) has been inspected in this work by using 2D TCAD simulations. Simulation results show that band-to-band tunneling current saturates due to inversion layer formation. Inversion charges cause the pinning of surface potential and make drain current less responsive to gate voltage. The contribution of source and drain in forming the inversion layer is measured quantitatively. The influence of different device parameters on inversion layer formation has also been inspected.
Visual laser-SLAM in large-scale indoor environments

Loop closure is a well-known problem in the research of laser based simultaneous localization and mapping, especially for applications in large-scale environments. The cumulative errors in the estimated pose and map make the loop detection difficult, no matter using particle filter-based or graph-based SLAM methods. Camera has the advantage of rich information but suffers from short distance and relative high computation burden. In this paper, we proposed a novel approach to address the loop closure problem in large-scale laser-SLAMs, where both laser and camera sensors are integrated. ORB features and bags-of-word were applied to obtain fast and robust performance of loop detection. The well-recognized LRGC SLAM framework and SPA optimization algorithm were then used to achieve the SLAM. Finally, several experiments in different large-scale environments were performed to verify the effectiveness of the proposed approach.
Cystic fibrosis: a disease in electrolyte transport

Cystic fibrosis (CF) is a fatal genetic disease caused by abnormalities in fluid and electrolyte transport in exocrine epithelia. Both absorptive and secretory processes are affected by an underlying membrane defect in Cl− permeability. However, the impact of the defect on transport function is tissue specific. Net electrolyte absorption is decreased in the sweat duct, increased in airway epithelia, and not affected in intestine. The defect is expressed in secretion as a consistent failure in most, if not all, exocrine tissues, to β‐adrenergically stimulated and cAMP mediated secretory response. However, the secretory response to cholinergic and Ca2+‐mediated stimulation is normal in the sweat gland, apparently normal in the airway, but absent in the intestine. The basic defect is not fatal in and of itself, and the imbalance between absorption and secretory functions may be of some selective advantage to heterozygotes in surviving complications of intestinal infections. The inherent defect in transport is probably the primary physiological cause of the ultimately fatal secondary infections in the lungs of CF homozygotes. —Quinton, P. M. Cystic fibrosis: a disease in electrolyte transport. FASEB J. 4: 2709‐2717; 1990.
Event Handling for Distributed Real-Time Cyber-Physical Systems

Cyber-Physical Systems (CPS) provides a smart infrastructure connecting abstract computational artifacts with the physical world. This paper presents some challenges for developing distributed real-time Cyber-Physical Systems. The focus is on one particular challenge, namely event modelling in distributed real-time CPS. A Web-of-Things based CPS framework for event handling and processing is proposed. To illustrate the application of the proposed framework, a case study for achieving demand response in a smart home is provided.
Study on suppressing nonlinear chaos of electric submersible motor for identifying temperature

In order to decrease negative effect and increase identification the precision of DC Injection Method(DIM) for identifying temperature of Electric Submersible Motor (ESM), we focus on the need for suppressing nonlinear chaos of electromagnetic torque of ESM. Based on analyzing qualitative relationship of electromagnetic torque to the stator current of ESM, the oscillation of instant torque and surge current of the stator induced by DIM is studied. Based on dynamics analysis the Wishout-filter state feedback control method is used to suppress the chaotic oscillation of electromagnetic torque of ESM. The design rules of series impedance between power system and the stator of ESM which influence on surge current of the stator is given by proposed method. Experiment results of 12 kW ESM shows the relative error of identification temperature of the stator of ESM reaches to 4.0%. It denotes the proposed method can provides theoretical and engineering basis for identifying the temperature of higher power AC motor by employing a newly developed DIM to suppressing corresponding negative effect.
Children's expectations and memories of acute distress: short- and long-term efficacy of pain management interventions.

OBJECTIVE To examine the effect of psychologic and pharmacologic interventions on children's expectations and 6-month recollections of painful procedures. METHODS A repeated measures design allowed examination of 22 fourth graders' expectations, experiences, and memories of distress across three conditions (typical care, distraction, topical anesthetic) for a three-injection vaccination series. All participants were African American and from urban, low-income families. RESULTS Across conditions, children's expectations of distress were significantly higher than their experience of distress. Distress ratings did not differ among conditions prior to or immediately following the injections; however, children later recalled that the treatment conditions were superior to control for distress relief. Analyses of recall accuracy suggest that the interventions buffered the children from forming negative recollections that occurred with typical care. CONCLUSIONS Children have negative expectations prior to a procedure despite knowing that a distress management intervention will be employed. However, interventions may thwart the development of negative memories of distress.
Three ways to solve for bond prices in the Vasicek model

Three approaches in obtaining the closed-form solution of the Vasicek bond pricing problem are discussed in this exposition. A derivation based solely on the distri- bution of the short rate process is reviewed. Solving the bond price partial dierential equation (PDE) is another method. In this paper, this PDE is derived via a martingale approach and the bond price is determined by integrating ordinary dierential equations. The bond pricing problem is further considered within the Heath-Jarrow-Morton (HJM) framework in which the analytic solution follows directly from the short rate dynamics under the forward measure.
Analysis to detecting methods of analogue based on variable threshold value neuron

In this paper, piecewise linearization and piecewise variable slope are used to train the detecting methods of non-linear analogue based on variable threshold neuron. The relationship between two training methods is given. The training method of piecewise variable slope can calibrate the detecting curve from the training method of piecewise linearization at the sampled-data feature, which improves the detecting precision and detecting resolution. The simulation result above-mentioned are provided.
Model-Based Autonomic and Performance-Aware System Adaptation in Heterogeneous Resource Environments: A Case Study

Recent trends like cloud computing show that service providers increasingly adopt to modern self-adaptive system architectures promising higher resource efficiency and lower operating costs. In this paper, we apply a holistic model-based approach to engineering performance-aware system adaptation. More specifically, we employ the Descartes Modeling Language (DML), a domain-specific language for modeling the performance behavior and run-time adaptation processes of modern dynamic IT systems. The conducted case study evaluates the applicability and effectiveness of our approach and demonstrates that DML provides suitable modeling abstractions that can be used as a basis for self-adaptive performance and resource management in heterogeneous environments. We apply a holistic model-based approach to build a self-adaptive system that automatically maintains performance requirements and resource efficiency in the heterogeneous resource environment of Blue Yonder. The application of DML enables to automatically adapt service infrastructures to changing customer workloads and service-level agreements in heterogeneous environments.
Maximal Ratio Combining Diversity Technique for IDMA Systems

Fading problem is termed as severe problem in wireless communication which can be mitigated with help of diversity techniques. This paper is concentrating on Maximal Ratio Combining (MRC) diversity approach for mitigation of the fading problem in iterative interleave-division multiple-access (IDMA) receivers. The approach explains maximal ratio combining diversity technique on receiver side, with one transmit and two receive antennas and one transmit and four receive antennas in low rate coded environment. For the purpose of simulations, random interleaver as well tree based interleaver has been considered for study. The simulation results demonstrate that in both environments, tree based interleavers outperforms the random interleaver when considered with other parameters. Significant improvements in performance of IDMA scheme is observed with MRC diversity technique using both the configurations.
Single-Cell Gene Expression Analysis of Cholinergic Neurons in the Arcuate Nucleus of the Hypothalamus

The cholinoceptive system in the hypothalamus, in particular in the arcuate nucleus (ARC), plays a role in regulating food intake. Neurons in the ARC contain multiple neuropeptides, amines, and neurotransmitters. To study molecular and neurochemical heterogeneity of ARC neurons, we combine single-cell qRT-PCR and single-cell whole transcriptome amplification methods to analyze expression patterns of our hand-picked 60 genes in individual neurons in the ARC. Immunohistochemical and single-cell qRT-PCR analyses show choline acetyltransferase (ChAT)-expressing neurons in the ARC. Gene expression patterns are remarkably distinct in each individual cholinergic neuron. Two-thirds of cholinergic neurons express tyrosine hydroxylase (Th) mRNA. A large subset of these Th-positive cholinergic neurons is GABAergic as they express the GABA synthesizing enzyme glutamate decarboxylase and vesicular GABA transporter transcripts. Some cholinergic neurons also express the vesicular glutamate transporter transcript gene. POMC and POMC-processing enzyme transcripts are found in a subpopulation of cholinergic neurons. Despite this heterogeneity, gene expression patterns in individual cholinergic cells appear to be highly regulated in a cell-specific manner. In fact, membrane receptor transcripts are clustered with their respective intracellular signaling and downstream targets. This novel population of cholinergic neurons may be part of the neural circuitries that detect homeostatic need for food and control the drive to eat.
Genetic influences of the intercellular adhesion molecule 1 (ICAM-1) gene polymorphisms in development of Type 1 diabetes and diabetic nephropathy

Aim The intercellular adhesion molecule‐1 (ICAM‐1) gene is located on chromosome 19p13, which is linked to Type 1 diabetes (T1D). ICAM‐1 expression is related to development of T1D and diabetic nephropathy. The present study aims to evaluate the genetic influence of ICAM‐1 gene polymorphisms on the development of T1D and diabetic nephropathy.
Adaptive Content Sequencing without Domain Information

In this paper we show that a performance prediction method can be used to sequence contents ameliorating sequencing over common domain informed strategies. Our developed sequencer is able to sequence content without knowledge on the domain, i.e. without knowing the number of skills involved in a content and the relative difficulties. Moreover, we discuss if a synthetic learning process can be modeled in a plausible way in order to facilitate testing with sequencing, which is generally difficult to evaluate on real students. In conclusion we show that Matrix Factorization is able to deal with all the important actual problems of Intelligent Tutoring Systems: personalization, multiple skill content modeling, and difficulty.
Modified hierarchical privacy-aware role based access control model

Privacy-aware role based access control (PRBAC) model extends much appreciated RBAC model and it is one of the leading models to define privacy policies and their enforcement. PRBAC extension, to hierarchical PRBAC (H-PRBAC), can express most of the privacy policies. But the limitation in H-PRBAC's Purpose hierarchy can lead to the explosion of policy assignments. In this paper, we review and provide an enhancement needed in the H-PRBAC model to overcome these limitations. Another limitation of PRBAC model is the lack of condition redundancy checking required for the assignment of new policies. In this paper, we provide an algorithm that was much needed for this purpose and review its complexity.
Adapt for Seamless Messaging in Heterogeneous Communication Networks

This paper describes the difficult problem of seamless messaging in heterogeneous communication environments and the design of cooperative agents to address the problem. The seamless messaging agents include coarse-grained agents such as user agents, message transfer agents, server agents (for resources uch as speech recognition and generation), application agents (interfacing to mail applications such as Microsoft and Unix mail) and device agents (for wireless phones, laptops, etc.). It also includes fine-grained agents, namely, user surrogate agents. Seamless messaging requires real-time performance which necessitates a tradeoff between agent communication, adaptability and intelligence to achieve a variety of tasks. In addition, seamless messaging requires user interface mediation between users and device agents to allow, for example, messages sent by users from a powerful graphic workstation to be received transparently by a cellular phone.
Course Content Analysis: An Initiative Step toward Learning Object Recommendation Systems for MOOC Learners

With the accelerating development of open education, lowcost online learning resources, such as Massive Open Online Courses (MOOCs), are reaching a wide audience around the world. However, when faced with these appealing but overwhelming learning resources, learners are prone making rash learning decisions, which may be either excessive or insufficient to their learning capacities. To avoid the mismatch between learners and learning objects, we propose a supporting system that recommends a personalized path of learning objects for a given learner. In realizing this system, a domain knowledge structure is necessary to connect learners’ information and learning objects. As an initiative step, we employ the Labeled Latent Dirichlet Allocation method to predict how the content of a course is distributed over different categories in the domain. We conduct experiments by utilizing course syllabi as course content, and curriculum guidelines as domain knowledge. The predicting performance is improved when involving external texts related to the concerned domain knowledge unit.
Similarity Search of Flexible 3D Molecules Combining Local and Global Shape Descriptors

In this paper, a framework for shape-based similarity search of 3D molecular structures is presented. The proposed framework exploits simultaneously the discriminative capabilities of a global, a local, and a hybrid local-global shape feature to produce a geometric descriptor that achieves higher retrieval accuracy than each feature does separately. Global and hybrid features are extracted using pairwise computations of diffusion distances between the points of the molecular surface, while the local feature is based on accumulating pairwise relations among oriented surface points into local histograms. The local features are integrated into a global descriptor vector using the bag-of-features approach. Due to the intrinsic property of its constituting shape features to be invariant to articulations of the 3D objects, the framework is appropriate for similarity search of flexible 3D molecules, while at the same time it is also accurate in retrieving rigid 3D molecules. The proposed framework is evaluated in flexible and rigid shape matching of 3D protein structures as well as in shape-based virtual screening of large ligand databases with quite promising results.
Synthetic TDR Measurements for TEM and GTEM Cell Characterization

This paper describes the main features of the time-domain reflectometry (TDR) measurement technique and, in particular, the TDR analysis performed using a proper operating mode of the vector network analyzer (VNA), which is called synthetic TDR. Furthermore, some results of reflection measurement, which aim to characterize the impedance behavior of transverse electromagnetic (TEM) and gigahertz TEM cells by means of a commercial VNA in time-domain mode, are presented
Rho/Rho Kinase and Phosphoinositide 3-Kinase Are Parallel Pathways in the Development of Spontaneous Arterial Tone in Deoxycorticosterone Acetate-Salt Hypertension

Hypertension is characterized by abnormal vascular contractility and function. Arteries from deoxycorticosterone acetate (DOCA)-salt hypertensive rats develop spontaneous tone that is not observed in arteries from normotensive rats. Inhibition of phosphoinositide 3-kinase (PI3-kinase) by 2-(4-morpholinyl)-8-phenyl-4H-1-benzopyran-4-one (LY294002) reduces spontaneous tone development. The Rho/Rho-kinase pathway has been suggested to play a role in hypertension and may be dependent on PI3-kinase activity. We hypothesized that Rhokinase is involved in spontaneous tone development and that Rho/Rho-kinase is a downstream effector of PI3-kinase. Using endothelium-denuded aortic strips in isolated tissue bath, we demonstrated that (+)-(R)-trans-4-(1-aminoethyl)-N-(4-pyridyl) (Y27632) (1 μM), a Rho-kinase inhibitor, significantly reduced spontaneous tone in the DOCA aorta but that it did not affect sham aorta basal tone (DOCA 63.5 ± 15.9 versus sham 1.2 ± 0.4 total change in percentage of phenylephrine contraction). We examined the interaction between the PI3-kinase and Rho pathways by observing the effects of LY294002 on a Rhokinase effector, myosin phosphatase (MYPT), and Y27632 on a PI3-kinase effector, Akt, using Western blot analysis. Inhibition of PI3-kinase reduced spontaneous tone, but it had no effect on the phosphorylation status of MYPT, indicating that PI3-kinase is not a downstream effector of Rho/Rho-kinase. These data indicate that there is little interaction between the Rho/Rhokinase and PI3-kinase pathways in the DOCA-salt aorta, and the two pathways seem to operate in parallel in supporting spontaneous arterial tone. These data reflect spontaneous tone only and do not rule out the possibility of interaction between these pathways in agonist-stimulated tone.
Perceptions of risk and barriers to cervical cancer screening at Moi Teaching and Referral Hospital (MTRH), Eldoret, Kenya.

BACKGROUND Affordable screening cervical cancer methods using visual inspection with acetic acid (VIA) and with Lugol's iodine (VILI) are being developed. Scaling up of screening services requires an understanding of the user perceptions about screening. OBJECTIVES Determine the perceptions of risk and barriers to previous cervical cancer screening by women attending MCH-FP clinic of MTRH, Eldoret, Kenya. METHODS Cross-sectional questionnaire survey involving a consecutive sample of 219 consenting non-pregnant women about perceptions on cervical cancer risk, barriers to screening and previous screening. RESULTS Of 219 women interviewed, 12.3% of participants had screened before. Women of over 30 years were more likely to have screened before (p=0.012). While 22.8% felt that they were at risk of the cervical cancer, 65% of all participants, nevertheless, wished to be screened. Perception of being at risk was significantly associated with a felt need for screening (p=0.002), an association that persisted only for women reporting multiple lifetime sex partners (p=0.005). Fear of abnormal results and lack of finances were the commonest barriers to screening reported by 22.4% and 11.4% of respondents, respectively. CONCLUSIONS Previous screening was uncommon. Cheaper screening methods are needed. Messages about screening should clarify the meaning and consequences of possible results.