Miracle-dz/UniFAR-FTUs huggingface dataset:
Matrix-Based Margin-Maximization Band Selection With Data-Driven Diversity for Hyperspectral Image Classification

For hyperspectral image classification, high-dimensional spectral features not only increase the computational and storage burden but also degrade the classification accuracy due to the Hughes phenomenon. Band selection is an important technique to solve these issues without destroying the interpretation of data. This paper presents a matrix-based margin-maximization method of band selection with data-driven diversity. In particular, the matrices composed of adjacent pixels in space are fed to the hinge loss function with a row-sparse constraint. This constraint is used to select the expected bands and preserve the spatial structure information simultaneously while maximizing the margin between the classes. In consideration of the continuity of bands in the spectral dimension, a novel regularization term that is continually updated according to the current context is added to promote the differential expression of dissimilar bands. Finally, the one-against-all parallel mechanism is used to learn a coefficient matrix for each class, and class-related bands are then carefully selected by a partitioning strategy (e.g., k-means clustering) based on the learned coefficient matrix. Experiments are conducted on three hyperspectral data sets and four widely used classifiers. The experimental results have shown that our proposed method is superior to several state-of-the-art methods, especially when the number of selected bands is relatively small.
Exploration of Sarcoptes scabiei Antigenic Protein Which Play Roles in Scabies Pathogenesis in Goats and Rabbits

Background: Scabies or mange is an infectious skin disease caused by the mite Sarcoptes scabiei. This skin disease affects various livestock such as goats, sheep, swine, cattle, other animals like dogs, cats, wild animals and also affect human. This research aimed to explore the protein in mites S. scabiei which has antigenic character and play roles in scabies pathogenesis in goats and rabbits. Methods: S.scabiei mites were isolated from goats and rabbits, and characterized using SDS-PAGE. In addition the protein was also analysed using Western Blot assay. The isolation and identification were carried out in 2015 at the Parasitology Laboratory of Veterinary Medicine Faculty, Universitas Airlangga, Surabaya, Indonesia. Results: The identification results using SDS-PAGE of mites S. scabiei var. caprae expressed 12 protein bands between 26,7 kDa and 205,8 kDa, continued by Western Blot showed 3 protein bands, after being reacted with blood serum from scabies infected goat, it could be identified antigenic protein with molecule weight 205.8 kDa, 57.3 kDa, and 43 kDa. While protein in mites S. scabiei var. cuniculi identified 9 protein bands between 24 kDa and 75 kDa by SDS-PAGE, and the Western Blot assay identified antigenic protein with molecule weight 62 kDa and 51 kDa. Conclusion: The antigenic protein of S. scabiei var. caprae and S. scabiei var. cuniculi showed that they are probably involved in the scabies pathogenesis in goats and rabbits.
Enhancement of support for mandibular complete denture prosthesis: a preprosthetic ridge augmentation procedure by distraction osteogenesis.

Poor and resorbed mandibular residual alveolar ridge result from periodontal disease, trauma or disuse atrophy, which complicate the clinical procedures of fabrication and limit the support for the complete denture prosthesis. Reconstruction of the residual alveolar ridge is challenging because the deformity involves deficiency in both the bone and the mucosa. Alveolar distraction osteogenesis is a relatively recent method that, compared with onlay grafts or guided bone regeneration, has less morbidity, better previsibility, and less bone resorption. Compared with other techniques of regeneration, alveolar distraction osteogenesis permits less treatment time because the distraction segments are well formed in 12 weeks. This article presents a case report of a successful alternative approach prior to prosthodontic rehabilitation of a patient with poor and resorbed mandibular ridges, using alveolar distraction osteogenesis as a preprosthetic procedure and further discusses the merits and demerits of this novel procedure when considering implant placement.
On Modeling Shortest Path Length Distribution in Scale-Free Network Topologies

Complex and interconnected systems belonging to biological, social, economic, and technology application fields are generally described through scale-free topology models. In this context, it is essential to characterize the distribution of shortest paths in order to obtain precious insights on the network behavior. Unfortunately, the few contributions available in the current scientific literature require a case-by-case tuning of model parameters. To bridge this gap, novel Gaussian-based models are proposed hereby, whose parameters can be immediately tuned based on the number of nodes (<inline-formula><tex-math notation="LaTeX">$N$</tex-math></inline-formula>) composing the network, only. In this way, given <inline-formula><tex-math notation="LaTeX">$N$</tex-math></inline-formula>, it becomes possible to predict the distribution of shortest paths without retuning the model for each scenario of interest. The outcomes of the proposed models have been successfully validated and compared with respect to state-of-the-art approaches in a wide set of network topologies. To provide a further insight, the conceived Gaussian-based models have been also evaluated for real Internet topologies, learned from reference data sets. Obtained results highlight that the proposed models are able to reach a good tradeoff between the level of accuracy and complexity, even for real network configurations.
Predicting diabetes-related hospitalizations based on electronic health records

Objective: To derive a predictive model to identify patients likely to be hospitalized during the following year due to complications attributed to Type II diabetes. Methods: A variety of supervised machine learning classification methods were tested and a new method that discovers hidden patient clusters in the positive class (hospitalized) was developed while, at the same time, sparse linear support vector machine classifiers were derived to separate positive samples from the negative ones (non-hospitalized). The convergence of the new method was established and theoretical guarantees were proved on how the classifiers it produces generalize to a test set not seen during training. Results: The methods were tested on a large set of patients from the Boston Medical Center – the largest safety net hospital in New England. It is found that our new joint clustering/classification method achieves an accuracy of 89% (measured in terms of area under the ROC Curve) and yields informative clusters which can help interpret the classification results, thus increasing the trust of physicians to the algorithmic output and providing some guidance towards preventive measures. While it is possible to increase accuracy to 92% with other methods, this comes with increased computational cost and lack of interpretability. The analysis shows that even a modest probability of preventive actions being effective (more than 19%) suffices to generate significant hospital care savings. Conclusions: Predictive models are proposed that can help avert hospitalizations, improve health outcomes and drastically reduce hospital expenditures. The scope for savings is significant as it has been estimated that in the USA alone, about $5.8 billion are spent each year on diabetes-related hospitalizations that could be prevented.
Variance adaptation in navigational decision making

Sensory systems relay information about the world to the brain, which enacts behaviors through motor outputs. To maximize information transmission, sensory systems discard redundant information through adaptation to the mean and variance of the environment. The behavioral consequences of sensory adaptation to environmental variance have been largely unexplored. Here, we study how larval fruit flies adapt sensory-motor computations underlying navigation to changes in the variance of visual and olfactory inputs. We show that variance adaptation can be characterized by rescaling of the sensory input and that for both visual and olfactory inputs, the temporal dynamics of adaptation are consistent with optimal variance estimation. In multisensory contexts, larvae adapt independently to variance in each sense, and portions of the navigational pathway encoding mixed odor and light signals are also capable of variance adaptation. Our results suggest multiplication as a mechanism for odor-light integration.
Information Power Efficiency Tradeoffs in Mixed Signal CMOS Circuits

Title of dissertation: INFORMATION POWER EFFICIENCY TRADEOFFS IN MIXED SIGNAL CMOS CIRCUITS Nicole McFarlane, Doctor of Philosophy, 2010 Dissertation directed by: Professor Pamela Abshire Department of Electrical and Computer Engineering Increasingly sensors for biological applications are implemented using mixed signal CMOS technologies. As feature sizes in modern technologies decrease with each generation, the power supply voltage also decreases, but the intrinsic noise level increases or remains the same. The performance of any sensor is quantified by the weakest detectable signal, and noise limits the ability of a sensor to detect the signal. In order to explore the trade-offs among incoming signal, the intrinsic physical noise of the circuit, and the available power resources, we apply basic concepts from information theory to CMOS circuits. In this work the circuits are modeled as communication channels with additive colored Gaussian noise and the signal transfer characteristics and noise properties are used to determine the classical Shannon capacity of the system. The waterfilling algorithm is applied to these circuits to obtain the information rate and the bit energy is subsequently calculated. In this dissertation we restricted our attention to operational transconductance amplifiers, a basic building block for many circuits and sensors and oftentimes a major source of noise in a sensor system. It is shown that for typical amplifiers the maximum information rate occurs at bandwidths above the dominant pole of the amplifier where the intrinsic physical circuit noise is diminished, but at the same time the output signal is attenuated. Thus these techniques suggest a methodology for the optimal use of the amplifier, but in many cases it is not practical to use an amplifier in this manner, that is at frequencies above its 3dB cutoff. Further, a direct consequence of applying the classic waterfilling algorithm leads to the idea of using modulation techniques to optimize system performance by shifting signals internally to higher frequencies, providing a practical means to achieve the information rates predicted by waterfilling and at the same time maintaining the real world application of these amplifiers. In addition, the information rates and bit energy for basic CMOS amplifier configurations are studied and compared across configurations and processes. Further the additional design constraints formed by adding the information rate and the bit energy to traditional design characteristics is explored. INFORMATION POWER EFFICIENCY TRADEOFFS IN MIXED SIGNAL CMOS CIRCUITS
Altered testosterone levels associated with venlafaxine use: a case report -

Sexual dysfunction is a frequent side effect of selective serotonin reuptake inhibitors and serotonin–norepinephrine reuptake inhibitors. However, accompanying the alteration in testosterone levels is uncommon. We present the case of a patient with major depressive disorder, posttraumatic stress disorder, and panic disorder, whose symptoms were well-controlled with venlafaxine-extended release (150 mg/d). Because of low testosterone levels, the venlafaxine treatment was tapered off.
High-Speed Silicon Photonics Modulators

The realization of gigahertz bandwidth modulators out of silicon-based technology in the early 2000s marked a cornerstone of silicon photonics development. While modulation speeds have since progressed well above 50 GHz and satisfy the bandwidth requirements of current and emerging modulation formats, concurrently obtaining low drive voltages and low insertion losses remains a very active area of research. While modulators generally come in two categories, direct absorption and those relying on embedded phase shifters, the focus of this paper lies on the latter capable of supporting both complex-valued modulation and optically broadband operation. The paper provides an overview of the current state of the art, as well as of currently explored improvement paths. First, common phase shifter configurations, aspects related to electrical driving, and associated power consumption are reviewed. Slow-wave, resonant, and plasmonic enhancements are further discussed. The reader is familiarized with the optimization of these devices and provided with a sense of the limitations of current technology and the potential of novel hybrid material integration.
A Non-Rigid Image Registration Algorithm Based on NURBS

Non-rigid image registration is an interesting and challenging research work in medical image processing, computer vision and remote sensing fields. In this paper we present a free form deformable algorithm based on NURBS because NURBS (Non-uniform Rational B Spline ) with a non-uniform grid has a higher registration precision and a higher registration speed in comparison with B spline. In our experiment we compare the NURBS based FFD method with the B spline based FFD method quantitatively. The experiment result shows that the algorithm can improve highly the registration precision.
A control-configured flexible arm: integrated structure control design

The integrated structure/control design of flexible robot arms is presented. The open loop, poles, and zeros are relocated by modifying the geometry and the structure of the arm. To determine the geometry and structure in a systematic manner, an inverse mapping method based on finite-element modeling and sensitivity analysis is applied to the flexible arm design. Using this method, a beam geometry that allows for a significantly high natural frequency is obtained. In order to relocate zeros, the torque transmission technique is applied. It makes it possible to remove nonminimum-phase zeros and make the endpoint control robustly stable. Based on the theoretical analysis and computation, a prototype arm was designed and built, and its performance was evaluated. <<ETX>>
Nonpharmacological Management of Behavioral and Psychological Symptoms of Dementia: What Works, in What Circumstances, and Why?

Abstract Objective Behavioral and psychological symptoms of dementia (BPSD) refer to the often distressing, noncognitive symptoms of dementia. BPSD appear in up to 90% of persons with dementia and can cause serious complications. Reducing the use of antipsychotic medications to treat BPSD is an international priority. This review addresses the following questions: What nonpharmacological interventions work to manage BPSD? And, in what circumstances do they work and why? Method A realist review was conducted to identify and explain the interactions among context, mechanism, and outcome. We searched electronic databases for empirical studies that reported a formal evaluation of nonpharmacological interventions to decrease BPSD. Results Seventy-four articles met the inclusion criteria. Three mechanisms emerged as necessary for sustained effective outcomes: the caring environment, care skill development and maintenance, and individualization of care. We offer hypotheses about how different contexts account for the success, failure, or partial success of these mechanisms within the interventions. Discussion Nonpharmacological interventions for BPSD should include consideration of both the physical and the social environment, ongoing education/training and support for care providers, and individualized approaches that promote self-determination and continued opportunities for meaning and purpose for persons with dementia.
Your Wish is My Command: Programming By Example

Foreword Ben Shneiderman Introduction Henry Lieberman 1) Novice Programming Comes of Age David Canfield Smith, Allen Cypher, Larry Tesler 2) Generalizing by Removing Detail: How Any Program Can Be Created by Working with Examples Ken Kahn 3) Demonstrational Interfaces: Sometimes You Need a Little Intelligence Sometimes You Need a Lot Brad A. Myers, Richard McDaniel 4) Web Browsing by Demonstration Atsushi Sugiura 5) Programming by Demonstration for Information Agents Mathias Bauer, Dietmar Dengler, Gabriele Paul 6) End Users and GIS: A Demonstration is Worth a Thousand Words Carol Traynor and Marian Williams 7) Bring Programming by Demonstration to CAD Users Patrick Girard 8) Demonstrating the Hidden Features That Make an Application Work Richard McDaniel 9) A reporting tool using programming by example for format designation Tetsuya Masuishi and Nobuo Takahashi 10) Composition by Example Toshiyuki Masui 11) Learning Repetitive Text-editing Procedures with SMARTedit Tessa Lau, Steve Wolfman, Pedro Domingos and Daniel S. Weld 12) Training Agents to Recognize Text by Example Henry Lieberman, Bonnie A. Nardi and David J. Wright 13) SWYN: A Visual Representation for Regular Expressions Alan Blackwell 14) Learning Users' Habits to Automate Repetitive Tasks Jean-David Ruvini and Christophe Dony 15) Domain-independent programming by demonstration in existing applications Gordon W. Paynter and Ian H. Witten 16) Stimulus-Response PBD: Demonstrating When as Well as What David Wolber and Brad A. Myers 17) Pavlov: Where PBD Meets Macromedia's Director David Wolber 18) Programming by Analogous Examples Alexander Repenning and Corrina Perrone-Smith 19) Visual Generalization in Programming by Example Robert St. Amant, Henry Lieberman, Richard Potter, and Luke Zettlemoyer
Phytochemical analysis and anti-inflammatory potential of Fenugreek.

A large number of medicinal plants are being used today to bring about traditional cure of inflammatory conditions, yet many of them need to be properly investigated and scientifically validated for the same. Potential active constituents from Trigonella foenum-graecum (Fenugreek) have been isolated and purified. A comprehensive overview of the phytochemical analysis of the seed extract and the literature survey carried out for the antiinflammatory potential and the other medicinal properties of fenugreek seeds.
Quantitative assessment of interferometric SAR images registration accuracy

Accurate registration of images is very important for interferometric SAR topography mapping. The interferogram (phase pattern) extracted from the conjugate product of two complex images registered with different registration algorithms will be slightly different too. In this paper, we investigate the theoretical relationship between registration accuracy and probability of residue. Based on the derived model, we present that the number of residues can be used as a criterion to judge the registration accuracy and select the optimal interferogram. A pair of ERS1/2 SAR images has been used to illustrate the effectiveness of this means.
Effects of Parental Obesity on Fat Metabolism During Submaximal Exercise in Children

The aim of the present study was to compare fat metabolism during submaximal exercise in children with a morbidly obese parent - (COP) (BMI [greater than or equal to] 40 kg/m²) to children with relatively lean parents - (CLP) (BMI [less than or equal to] 28 kg/m²). All participants in the COP and CLP groups (n = 10 per group) completed two, ten minute submaximal exercise sessions at an absolute workload of 15 W and a relative workload of 65% VO2 peak as expired gases were measured. Actigraph GT1M accelerometers were also worn by the participants to determine physical activity patterns during periods of normal living. Despite the participants being matched for age, maturity, body composition, cardiovascular fitness, and physical activity levels, the COP group had a significantly higher RER and lower percentage of energy from fat than the CLP group at an absolute workload of 15 W (P[less than or equal to] 0.05). The difference in RER and percentage of energy from fat at the relative workload of 65% VO2 peak was not significantly different. From our results there appears to be a decreased reliance on fat for energy at lower intensity exercise in children with at least one morbidly obese parent compared to children with lean parents. This decrease in fat metabolism may be genetically predetermined and increase the risk of being obese.
Formal verification approaches in the web service composition: A comprehensive analysis of the current challenges for future research

Today, service composition is emerging paradigm on the communication networks such as cloud environments, internet of things, wireless sensor network, and software‐defined network. The goal of service composition method is to provide the interactions between user requirements and smart objects of intelligent communication systems. There have been many efforts to use formal verification and behavioral modeling methods to evaluate the service composition mechanisms. Up to now, there is not a comprehensive analysis research on this topic. Therefore, this paper focuses on several formal verification approaches that are performed to confirm the service composition correctness in communication networks. The objective of this paper is to comprehensively categorize and examine current research techniques on formal verification of the service composition. This research analysis provides an overview of recent service composition approaches according to structural and functional properties. Comparison results show that most of the verification approaches in explanation of the service composition correctness are semantic‐aware approach with 43%. The most used verification method for the service composition is model checking with 69%. The process algebra is used 29%, and some theorem proving methods are applied in 9% of the investigated mechanism. Moreover, most widely used modeling tools are NuSMV (22%), SPIN (17%), CPN (12%), UPPAAL (12%), Event‐B (10%), and PAT (5%).
A Characteristic-Mode-Based Polarization-Reconfigurable Antenna and its Array

This paper reports a novel polarization-reconfigurable antenna based on the theory of characteristic mode (CM), which can electronically alter its polarization states between linear polarization (LP), left-hand circular polarization (LHCP), and right-hand circular polarization (RHCP). A square patch with an I-shaped slot is used as a main radiator, which has two LP orthogonal CMs with the same modal significance and 90° characteristic angle difference at 2.4 GHz. A simple feeding network is designed to excite the different combinations of the two modes. By properly choosing the state of the excitation, the LP, LHCP, and RHCP waves can be generated. A <inline-formula> <tex-math notation="LaTeX">$1 \times 4$ </tex-math></inline-formula> antenna array is designed for the demonstration of array application, and experiments are carried out to validate the proposed design. The measured overlapping impedance bandwidth (BW) (<inline-formula> <tex-math notation="LaTeX">$\vert \text{S}_{11}\vert \le -10$ </tex-math></inline-formula> dB) and 3-dB gain BW is 2.25–2.7 GHz in the LP state. The overlapping BWs in conjunction with the 3-dB axial ratio BW are 2.16–2.65 and 2.1–2.55 GHz in the LHCP and RHCP states, respectively. The measured maximum gains are 7.2 dBi, 9.78 dBic, and 9.8 dBic for the LP, LHCP, and RHCP states, respectively. The common BW for all three polarization states is 2.25–2.55 GHz or 12.5%. Experimental results show a good performance of the proposed antenna array.