Miracle-dz/UniFAR-FTUs huggingface dataset:
Patients with chronic pain exhibit a complex relationship triad between pain, resilience, and within- and cross-network functional connectivity of the default mode network

Abstract Resilience is a psychological trait that strongly predicts chronic pain–related health outcomes. The neural correlates of both pain and trait resilience are critical to understand the brain–behaviour relationship in chronic pain; yet, neural correlates of resilience in chronic pain states are unknown. However, measures of pain perception and a wide range of psychological health measures have been linked to function of the default mode network (DMN). Thus, we aimed to determine the relationships between resilience, pain perception, and functional connectivity (FC) within the DMN and between the DMN and other brain networks. Resting-state functional magnetic resonance imaging data were acquired from 51 chronic pain patients with a form of spondylarthritis (ankylosing spondylitis) and 51 healthy control participants. Participants completed a questionnaire on their individual trait resilience (the Resilience Scale), and patients reported their clinical pain. In healthy controls, we found within-DMN FC to be stronger in less resilient individuals. In patients with chronic pain, individual resilience was negatively correlated with pain and disease activity. Cross-network FC between the DMN and the sensorimotor network was abnormally high in patients with high clinical pain scores on the day of the study. Finally, there was an interaction between within-DMN FC and clinical pain report in patients: In patients reporting greater pain, the relationship between within-DMN connectivity and resilience was atypical. Thus, our findings reveal different neural representations of resilience and pain. The way in which these behavioural measures interact provides insight into understanding the neural correlates of chronic pain.
Revenue Management Through Dynamic Cross Selling in E-Commerce Retailing

This disclosure relates to a metering dispensing closure in which a pair of chambers are selectively placed in fluid communication with each other by an axially movable gravity actuated valve housed in one of the chambers. The valve includes a pair of diametrically opposite ports which are alternately in and out of registration with ports formed in the chamber housing the valve. When the closure is inverted a first of the chambers receives a predetermined quantity of a packaged product and upon reversion and subsequent inversion the predetermined quantity is transferred to a second of the chambers and dispensed through a port thereof to atmosphere.
The guaranty-of-liabilities model for 'PFI' projects

The paper investigates the roles of public assistance for PFI (Private Finance Initiative) projects. In order to realize PFI projects, it is sometimes necessary for the public sectors to induce the private sectors to participate in the projects by giving financial assistance The guaranties-of-liabilities are the basic means for public sectors to share part of the financial risks with project companies. A guaranty-of-liabilities model is presented to investigate the efficient risk sharing schemes between the private and public sectors.
Detection of the oxygen minimal zone — OMZ using fishing vessels in the Peruvian sea during 2007–2016

Using TASA fishing vessels on the Peruvian coast during the period 2007 to 2016, the Oxygen Minimum Zone (OMZ) was determined through echograms obtained using a digital echo sounders ES60 and ES70 SIMRAD. The purse-seine fleet operates during two seasons per year for anchovy fishing as well as in fishing activities for human consumption in the central-north and south area. Using Echoview software algorithms it is possible to determine the OMZ and to export the data in organized spreadsheet format for each season of the year and to calculate the area occupied using Surfer 8.0 program. Interannual variation were analyzed using the statistical program R. The results show that the OMZ can be obtained using the fishing fleets, but these results are based on the area covered by the fishing fleet. Due to the wide coverage of the fleet during the year, we can have a daily, monthly and seasonal monitoring during the year. The results show an average depth of 50 meters of the OZM.
Concept of Computational Fluid Dynamics (CFD) and its Applications in Food Processing Equipment Design

CFD is a simulation tool used to model fluid flow simulations which involves the use of powerful computers and applied mathematics for predicting heat and mass transfer in various processes. In recent years it has been applied in food processing equipment design. This paper reviews the applications of CFD in food processing including cleaning of storage tanks, designs of dryers, sterilizers, freezers, mixers etc. The advantages and disadvantages of using CFD are discussed along with its future in food processing industry.
Breast cancer patients' search for meaning

ABSTRACT The aim of this study was to analyze the search for meaning in women with breast cancer and its relationship with the emotional well-being. One hundred thirty-one breast cancer survivors were assessed using a mixed method. Results showed that the meaning of suffering cancer can be explained by nine categories; and the utility of the suffering experienced was divided in seven categories. Moreover, the results showed a significant correlation between the meaning and the utility of suffering cancer, and the emotional well-being. The search for meaning in breast cancer women affects the emotional well-being, so it is necessary to attend it.
Experimental Identification of the Magnetic Model of Synchronous Machines

This paper proposes and formalizes a comprehensive experimental approach for the identification of the magnetic model of synchronous electrical machines of all kinds. The identification procedure is based on controlling the current of the machine under test while this is driven at constant speed by another regenerative electric drive. Compensation of stator resistance and inverter voltage drops, iron loss, and operating temperature issues are all taken into account. A road map for implementation is given, on different types of hardware setups. Experimental results are presented, referring to two test motors of small size, and references of larger motors identified with the same technique are given from the literature.
GRAIN SIZE IN EYEWITNESS IDENTIFICATION

When making a memorial judgment, respondents can regulate their accuracy by adjusting the precision, or grain size, of their responses. In many circumstances, coarse-grained responses are less informative, but more likely to be accurate, than fine-grained responses. This paper describes a novel eyewitness identification procedure, the grain size lineup, in which participants eliminated any number of individuals from the lineup, creating a choice set of variable size. A decision was considered to be fine-grained if no more than one individual was left in the choice set or coarse-grained if more than one individual was left in the choice set. Participants (N = 384) watched two high-quality or low-quality videotaped mock crimes and then completed four standard simultaneous lineups or four grain size lineups (two targetpresent and two target-absent). There was some evidence of strategic regulation of grain size, as the most difficult lineup was associated with a greater proportion of coarse-grained responses than the other lineups. However, the grain-size lineup did not outperform the standard simultaneous lineup. Fine-grained suspect identifications were no more diagnostic than suspect identifications from standard lineups, while coarse-grained suspect identifications carried little probative value. Participants were generally reluctant to provide coarse-grained responses, which may have hampered the utility of the procedure. For a grainsize approach to be useful, participants may need to be trained or instructed to use the coarsegrained option effectively.
Utility of a new procedure for diagnosing mental disorders in primary care. The PRIME-MD 1000 study.

OBJECTIVE To assess the validity and utility of PRIME-MD (Primary Care Evaluation of Mental Disorders), a new rapid procedure for diagnosing mental disorders by primary care physicians. DESIGN Survey; criterion standard. SETTING Four primary care clinics. SUBJECTS A total of 1000 adult patients (369 selected by convenience and 631 selected by site-specific methods to avoid sampling bias) assessed by 31 primary care physicians. MAIN OUTCOME MEASURES PRIME-MD diagnoses, independent diagnoses made by mental health professionals, functional status measures (Short-Form General Health Survey), disability days, health care utilization, and treatment/referral decisions. RESULTS Twenty-six percent of the patients had a PRIME-MD diagnosis that met full criteria for a specific disorder according to the Diagnostic and Statistical Manual of Mental Disorders, Revised Third Edition. The average time required of the primary care physician to complete the PRIME-MD evaluation was 8.4 minutes. There was good agreement between PRIME-MD diagnoses and those of independent mental health professionals (for the diagnosis of any PRIME-MD disorder, kappa = 0.71; overall accuracy rate = 88%). Patients with PRIME-MD diagnoses had lower functioning, more disability days, and higher rates of health care utilization than did patients without PRIME-MD diagnoses (for all measures, P < .005). Nearly half (48%) of 287 patients with a PRIME-MD diagnosis who were somewhat or fairly well-known to their physicians had not been recognized to have that diagnosis before the PRIME-MD evaluation. A new treatment or referral was initiated for 62% of the 125 patients with a PRIME-MD diagnosis who were not already being treated. CONCLUSION PRIME-MD appears to be a useful tool for identifying mental disorders in primary care practice and research.
Intratumor Heterogeneity Characterized by Textural Features on Baseline 18F-FDG PET Images Predicts Response to Concomitant Radiochemotherapy in Esophageal Cancer

18F-FDG PET is often used in clinical routine for diagnosis, staging, and response to therapy assessment or prediction. The standardized uptake value (SUV) in the primary or regional area is the most common quantitative measurement derived from PET images used for those purposes. The aim of this study was to propose and evaluate new parameters obtained by textural analysis of baseline PET scans for the prediction of therapy response in esophageal cancer. Methods: Forty-one patients with newly diagnosed esophageal cancer treated with combined radiochemotherapy were included in this study. All patients underwent pretreatment whole-body 18F-FDG PET. Patients were treated with radiotherapy and alkylatinlike agents (5-fluorouracil-cisplatin or 5-fluorouracil-carboplatin). Patients were classified as nonresponders (progressive or stable disease), partial responders, or complete responders according to the Response Evaluation Criteria in Solid Tumors. Different image-derived indices obtained from the pretreatment PET tumor images were considered. These included usual indices such as maximum SUV, peak SUV, and mean SUV and a total of 38 features (such as entropy, size, and magnitude of local and global heterogeneous and homogeneous tumor regions) extracted from the 5 different textures considered. The capacity of each parameter to classify patients with respect to response to therapy was assessed using the Kruskal–Wallis test (P < 0.05). Specificity and sensitivity (including 95% confidence intervals) for each of the studied parameters were derived using receiver-operating-characteristic curves. Results: Relationships between pairs of voxels, characterizing local tumor metabolic nonuniformities, were able to significantly differentiate all 3 patient groups (P < 0.0006). Regional measures of tumor characteristics, such as size of nonuniform metabolic regions and corresponding intensity nonuniformities within these regions, were also significant factors for prediction of response to therapy (P = 0.0002). Receiver-operating-characteristic curve analysis showed that tumor textural analysis can provide nonresponder, partial-responder, and complete-responder patient identification with higher sensitivity (76%–92%) than any SUV measurement. Conclusion: Textural features of tumor metabolic distribution extracted from baseline 18F-FDG PET images allow for the best stratification of esophageal carcinoma patients in the context of therapy-response prediction.
Resonant pressure sensing using a micromechanical cantilever actuated by fringing electrostatic fields

We demonstrate a pressure-sensing approach based on the resonant operation of a single-crystal Si cantilever positioned near a flexible, pressurized membrane. The membrane deflection perturbs the electrostatic force acting on the cantilever and consequently alters the beam's resonant frequency. Sensitivity was enhanced by tailoring the actuating force nonlinearities through fringing electrostatic fields. With our coupled micromechanical system, we achieved frequency sensitivity to pressure and displacement of ≈ 30 Hz/kPa and −4 Hz/nm, respectively. Our results indicate that the suggested approach may have applications not only for pressure measurements, but also in a broad range of microelectromechanical resonant inertial, force, mass and bio sensors.
Happiness is a Choice: Sentiment and Activity-Aware Location Recommendation

Studying large, widely spread Twitter data has laid the foundation for many novel applications from predicting natural disasters and epidemics to understanding urban dynamics. Recent studies have focused on exploring people's emotional response to their urban environment, e.g., green spaces versus built up areas, through analysing the sentiment of tweets within that area. Since green spaces have the capacity to improve citizen's well-being, we developed a system that is capable of recommending green spaces to users. Our system is unique in the sense that the recommendations are tailored with regard to users' preferred activity as well as the degree of positive sentiments in each green space. We show that the incoming flow of tweets can be used to refine the recommendations over time. Furthermore, We implemented a web-based, user-friendly interface to solicit user inputs and display recommendation results.
Trendspedia: An Internet observatory for analyzing and visualizing the evolving web

The popularity of social media services has been innovating the way of information acquisition in modern society. Meanwhile, mass information is generated in every single day. To extract useful knowledge, much effort has been invested in analyzing social media contents, e.g., (emerging) topic discovery. With these findings, however, users may still find it hard to obtain knowledge of great interest in conformity with their preference. In this paper, we present a novel system which brings proper context to continuously incoming social media contents, such that mass information can be indexed, organized and analyzed around Wikipedia entities. Four data analytics tools are employed in the system. Three of them aim to enrich each Wikipedia entity by analyzing the relevant contents while the other one builds an information network among the most relevant Wikipedia entities. With our system, users can easily pinpoint valuable information and knowledge they are interested in, as well as navigate to other closely related entities through the information network for further exploration.
Near-Infrared Laser Adjuvant for Influenza Vaccine

Safe and effective immunologic adjuvants are often essential for vaccines. However, the choice of adjuvant for licensed vaccines is limited, especially for those that are administered intradermally. We show that non-tissue damaging, near-infrared (NIR) laser light given in short exposures to small areas of skin, without the use of additional chemical or biological agents, significantly increases immune responses to intradermal influenza vaccination without augmenting IgE. The NIR laser-adjuvanted vaccine confers increased protection in a murine influenza lethal challenge model as compared to unadjuvanted vaccine. We show that NIR laser treatment induces the expression of specific chemokines in the skin resulting in recruitment and activation of dendritic cells and is safe to use in both mice and humans. The NIR laser adjuvant technology provides a novel, safe, low-cost, simple-to-use, potentially broadly applicable and clinically feasible approach to enhancing vaccine efficacy as an alternative to chemical and biological adjuvants.
Depression in newly-urbanized elderly Africans

Two recent South African prevalence studies of depressive symptoms have revealed a high occurence of such symptoms among the black elderly population, particularly in the case of women. In a study of depression conducted in the Cape Peninsula townships of Langa and Khayelitsha (N = 195 and 170, respectively), an alarming vulnerability to depressive symptoms was found among black elderly women. with 27% of the women sampled in Langa and 44% of those in Khayelitsha identifying with these symptoms. The Multidimensional Survey (N = 4 400) demonstrated a greater prevalence of depression among elderly blacks than among other elderly population groups. Possible reasons for these findings are discussed.
Yes, No, Maybe So: College Students’ Attitudes Regarding Debt

Abstract:We examined college student attitudes regarding debt. Based on focus group interviews with 31 students from 4 different institutions within a Midwestern university system, data analysis yielded a continuum that captures students’ debt approaches while enrolled in college. Findings indicate that students avoided debt completely, made intentional efforts to minimize debt, or fully accepted carrying multiple forms of debt as an integral part of the college-going experience. Implications for practice and future research are discussed.
Comparative analysis about the study of maximum power point tracking algorithms: A review

This paper provides a detailed review of the most widely used Maximum power point tracking (MPPT) algorithms. For the ease of comparison, the algorithms are classified into three major categories, a) Conventional Methods, b) AI-based methods, c) Hybrid methods. The factors such as efficiency, complexity, cost, the technology used, play a very significant role in designing and selecting an MPPT technique. Hence all such factors are discussed in this paper, and elaborate table entails the comparison report. This paper should serve as a reference for understating of the different MPPT techniques and their working principals.
QUALITATIVE METHODS IN STATISTICS EDUCATION RESEARCH: METHODOLOGICAL PROBLEMS AND POSSIBLE SOLUTIONS

Despite being relatively new in statistics education research, qualitative approaches need special attention as attempts are being made to enhance the credibility and trustworthiness of this approach. It is important that researchers are aware of the limitations associated with these methods so that measures are put in place to try and minimize the effects of these limitations Philosophical roots and features of this paradigm are outlined. Challenges faced by qualitative researchers in terms of reliability, validity and generability are considered. Uses of the interview approach in research literature as a data gathering tool are considered next. Advantages and disadvantages of the interview approach are outlined. An example of a research in statistics education is provided to illustrate methodological problems and solutions related to qualitative
Efficient Implementation of the Backpropagation Algorithm in FPGAs and Microcontrollers

The well-known backpropagation learning algorithm is implemented in a field-programmable gate array (FPGA) board and a microcontroller, focusing in obtaining efficient implementations in terms of a resource usage and computational speed. The algorithm was implemented in both cases using a training/validation/testing scheme in order to avoid overfitting problems. For the case of the FPGA implementation, a new neuron representation that reduces drastically the resource usage was introduced by combining the input and first hidden layer units in a single module. Further, a time-division multiplexing scheme was implemented for carrying out product computations taking advantage of the built-in digital signal processor cores. In both implementations, the floating-point data type representation normally used in a personal computer (PC) has been changed to a more efficient one based on a fixed-point scheme, reducing system memory variable usage and leading to an increase in computation speed. The results show that the modifications proposed produced a clear increase in computation speed in comparison with the standard PC-based implementation, demonstrating the usefulness of the intrinsic parallelism of FPGAs in neurocomputational tasks and the suitability of both implementations of the algorithm for its application to the real world problems.
BASS: Boundary-Aware Superpixel Segmentation

We propose a new superpixel algorithm based on exploiting the boundary information of an image, as objects in images can generally be described by their boundaries. Our proposed approach initially estimates the boundaries and uses them to place superpixel seeds in the areas in which they are more dense. Afterwards, we minimize an energy function in order to expand the seeds into full superpixels. In addition to standard terms such as color consistency and compactness, we propose using the geodesic distance which concentrates small superpixels in regions of the image with more information, while letting larger superpixels cover more homogeneous regions. By both improving the initialization using the boundaries and coherency of the superpixels with geodesic distances, we are able to maintain the coherency of the image structure with fewer superpixels than other approaches. We show the resulting algorithm to yield smaller Variation of Information metrics in seven different datasets while maintaining Undersegmentation Error values similar to the state-of-the-art methods.
Progress on the Use of Commercial Digital Optical Disc Units for Low-Power Laser Micromachining in Biomedical Applications

The development of organ-on-chip and biological scaffolds is currently requiring simpler methods for microstructure biocompatible materials in three dimensions, to fabricate structural and functional elements in biomaterials, or modify the physicochemical properties of desired substrates. Aiming at addressing this need, a low-power CD-DVD-Blu-ray laser pickup head was mounted on a programmable three-axis micro-displacement system in order to modify the surface of polymeric materials in a local fashion. Thanks to a specially-designed method using a strongly absorbing additive coating the materials of interest, it has been possible to establish and precisely control processes useful in microtechnology for biomedical applications. The system was upgraded with Blu-ray laser for additive manufacturing and ablation on a single platform. In this work, we present the application of these fabrication techniques to the development of biomimetic cellular culture platforms thanks to the simple integration of several features typically achieved with traditional, less cost-effective microtechnology methods in one step or through replica-molding. Our straightforward approach indeed enables great control of local laser microablation or polymerization for true on-demand biomimetic micropatterned designs in transparent polymers and hydrogels and is allowing integration of microfluidics, microelectronics, surface microstructuring, and transfer of superficial protein micropatterns on a variety of biocompatible materials.