Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of the Compression Behavior of Warp Knit Spacer Fabrics for Evaluating Suitability in Cushioning Applications

The article reviews the compression behavior of warp knit spacer fabrics intended for cushioning applications. An experimental study has been conducted on the compression behavior of a series of warp-knitted fabrics made for cushioning applications. The compression behavior of these fabrics and the effect of each structural parameter have been evaluated by the use of both the compression stress-strain curves and energy efficiency diagrams and the influence of each structural parameter analyzed. The findings show that warp knitted spacer fabrics are an ideal class of energy absorbers for cushioning applications, and their energy-absorption capacity can easily be tailored to meet specific end-use requirements by simply varying their structural parameters with the help of efficiency diagrams. The spherical compression behavior of warp knitted spacer fabrics has been studied by development of a theoretical model to predict the spherical ball compression properties of the spacer fabric. The analysis results reveal that the spherical compression effects decrease with increasing ball radius, and increase with increasing the fabric thickness. It is expected that this study could help us better understand the behavior of knitted spacer fabrics under spherical compression. The calculated values from the theoretical model have been compared with experimental measurements, and good agreements found between both. Based on the plane compression testing results, the validated model can be used to predict the spherical compression behaviors of knitted spacer fabrics compressed with different radii of the spherical balls.
Is spatial mobility on the rise or in decline? An order-specific analysis of the migration of young adults in Sweden

The aim of this study is to investigate spatial mobility over time. Research on ‘new mobilities’ suggests increasing movement of individuals, technology, and information. By contrast, studies of internal migration report declining spatial mobility in recent decades. Using longitudinal register data from Sweden, we calculate annual order-specific migration rates to investigate the spatial mobility of young adults over the last three decades. We standardize mobility rates for educational enrolment, educational level, family status, and place of residence to determine how much changes in individuals’ life domains explain changes in mobility. Young adults’ migration rates increased significantly in the 1990s; although all order-specific migration rates increased, first migration rates increased the most. Changes in population composition, particularly increased enrolment in higher education, accounted for much of the elevated spatial mobility in the 1990s. The analysis supports neither ever increasing mobility nor a long-term rise in rootedness among young adults in Sweden.
Extreme Toughening of Soft Materials with Liquid Metal

Soft and tough materials are critical for engineering applications in medical devices, stretchable and wearable electronics, and soft robotics. Toughness in synthetic materials is mostly accomplished by increasing energy dissipation near the crack tip with various energy dissipation techniques. However, bio‐materials exhibit extreme toughness by combining multi‐scale energy dissipation with the ability to deflect and blunt an advancing crack tip. Here, we demonstrate a synthetic materials architecture that also exhibits multi‐modal toughening, whereby embedding a suspension of micron sized and highly deformable liquid metal (LM) droplets inside a soft elastomer, the fracture energy dramatically increases by up to 50x (from 250 ± 50 J m‐2 to 11,900 ± 2600 J m‐2) over an unfilled polymer. For some LM‐embedded elastomer (LMEE) compositions, the toughness is measured to be 33,500 ± 4300 J m‐2, which far exceeds the highest value previously reported for a soft elastic material. This extreme toughening is achieved by (i) increasing energy dissipation, (ii) adaptive crack movement, and (iii) effective elimination of the crack tip. Such properties arise from the deformability of the LM inclusions during loading, providing a new mechanism to not only prevent crack initiation, but also resist the propagation of existing tears for ultra tough, soft materials.
Phase-based measures of cross-frequency coupling in brain electrical dynamics under general anesthesia

The state of general anesthesia (GA) is associated with an increase in spectral power in scalp electroencephalogram (EEG) at frequencies below 40 Hz, including spectral peaks in the slow oscillation (SO, 0.1–1 Hz) and α (8–14 Hz) bands. Because conventional power spectral analyses are insensitive to possible cross-frequency coupling, the relationships among the oscillations at different frequencies remain largely unexplored. Quantifying such coupling is essential for improving clinical monitoring of anesthesia and understanding the neuroscience of this brain state. We tested the usefulness of two measures of cross-frequency coupling: the bispectrum-derived SynchFastSlow, which is sensitive to phase-phase coupling in different frequency bands, and modulogram analysis of coupling between SO phase and α rhythm amplitude. SynchFastSlow, a metric that is used in clinical depth-of-anesthesia monitors, showed a robust correlation with the loss of consciousness at the induction of propofol GA, but this could be largely explained by power spectral changes without considering cross-frequency coupling. Modulogram analysis revealed two distinct modes of cross-frequency coupling under GA. The waking and two distinct states under GA could be discriminated by projecting in a two-dimensional phase space defined by the SynchFastSlow and the preferred SO phase of α activity. Our results show that a stereotyped pattern of phase-amplitude coupling accompanies multiple stages of anesthetic-induced unconsciousness. These findings suggest that modulogram analysis can improve EEG based monitoring of brain state under GA.
Performance Evaluation of Pipeline-Based Processing for the Caffe Deep Learning Framework

SUMMARY Many life-log analysis applications, which transfer data from cameras and sensors to a Cloud and analyze them in the Cloud, have been developed as the use of various sensors and Cloud computing technologies has spread. However, di ﬃ culties arise because of the limited network bandwidth between such sensors and the Cloud. In addition, sending raw sensor data to a Cloud may introduce privacy issues. Therefore, we propose a pipelined method for distributed deep learning processing be-tween sensors and the Cloud to reduce the amount of data sent to the Cloud and protect the privacy of users. In this study, we measured the processing times and evaluated the performance of our method using two di ﬀ erent datasets. In addition, we performed experiments using three types of machines with di ﬀ erent performance characteristics on the client side and compared the processing times. The experimental results show that the accuracy of deep learning with coarse-grained data is comparable to that achieved with the default parameter settings, and the proposed distributed processing method has performance advantages in cases of insu ﬃ cient network bandwidth between realistic sensors and a Cloud environment. In addition, it is conﬁrmed that the process that most a ﬀ ects the overall processing time varies depending on the machine performance on the client side, and the most e ﬃ cient distribution method similarly di ﬀ ers.
Intestinal microbiota and metabolites—Implications for broiler chicken health and performance1

SUMMARY Microbiota in the intestine of an animal species has evolved together with the host. This coevolution has produced specific host-microbe combinations, called superorganisms, with the best possible fitness in a given environment. Intestinal microbiota has an enormous metabolic potential and it affects both the nutrition and health of the host. The importance of intestinal microbiota for the performance of broiler chickens has been studied for decades. The microbial community structure of the cecum is significantly more complex and less well characterized than that of the crop and small intestine. Culture-independent molecular techniques have recently been introduced to bring fresh insights into the intestinal system of the broiler chicken. As a consequence, there is growing evidence of connection between the apparent metabolizable energy of the diet and microbiota composition in the hindgut of the host. This connection can be due to direct conversion of some dietary components into high-energy metabolites by specialized bacteria. The utilization of such fermentation end products would provide more energy for the host, which could be measured as improved feed conversion efficiency. However, it is also possible that cecal microbial profile is a reflection of feed digestion and nutrient absorption efficiency in the proximal intestine. Disorders in these functions cause excess nutrient bypass to the lower intestine, providing new, easily available substrates for bacteria that could otherwise not compete in that habitat. The 2 causal links described are likely to coexist in real life situations, but their relative dominance warrants further well-designed studies.
Development of Dengue Virus Serotype–Specific NS1 Capture Assays for the Rapid and Highly Sensitive Identification of the Infecting Serotype in Human Sera

Dengue fever can be caused by one of four distinct dengue virus (DENV) serotypes that cocirculate in many parts of the world. Point of care serotype-specific nonstructural protein-1 (NS1) capture assays for the rapid serotyping of DENV in human sera would greatly support epidemiological surveillance and potentially also prognosis in individual patients. To ensure both serotype specificity and broad coverage of variants within serotypes, we have applied an innovative approach for the generation and selection of serotype-specific anti-NS1 mAbs. To elicit mAbs against conformational epitopes, NMRI mice were immunized with living HEK 293 transfectants expressing the native target Ags in multiple display on the cell surface. For each serotype, three different NS1 sequence variants were sequentially used for immunization of mice, hybridoma selection, and capture assay development, respectively. Selection of optimal combinations of capturing and detecting mAbs yielded highly sensitive and specific NS1 serotyping ELISAs (st-ELISAs) for the four serotypes. st-ELISA testing of 41 dengue patient sera showed a 100% concordance with the serotype determined by serotype-specific reverse transcriptase real-time quantitative PCR. The respective NS1 variants could be detected for ∼10 d after the onset of illness. Ab-dependent enhancement of DENV infections may be associated with a specific range of pre-existing anti-DENV serological Ab titers. Testing of patient sera with the developed st-ELISAs will not only be useful for epidemiological studies and surveillance, but it may also help to develop and validate assays that can distinguish protective versus enhancing Ab responses for risk assessment for the development of severe dengue disease in individual patients.
Simultaneous search and monitoring by unmanned aerial vehicles

Simultaneous Search and Monitoring (SSM) is studied in this paper for a single Unmanned Aerial Vehicle (UAV) searcher and multiple moving ground targets. Searching for unknown targets and monitoring known targets are two intrinsically related problems, but have mostly been addressed in isolation. We combine the two problems with a joint objective function in a Partially Observable Markov Decision Process (POMDP). An online policy planning approach is proposed to plan a reactive policy to solve the POMDP, using both MonteCarlo sampling and Simulated Annealing. The simulation result shows that the searcher will successfully find unknown targets without losing known ones. We demonstrate, with a theoretical proof and comparative simulations, that the proposed approach can deliver a better performance than conventional foresight optimization methods.
Adaptive Estimation of Personalized Maximum Tolerated Dose in Cancer Phase I Clinical Trials Based on All Toxicities and Individual Genomic Profile

Background Many biomarkers have been shown to be associated with the efficacy of cancer therapy. Estimation of personalized maximum tolerated doses (pMTDs) is a critical step toward personalized medicine, which aims to maximize the therapeutic effect of a treatment for individual patients. In this study, we have established a Bayesian adaptive Phase I design which can estimate pMTDs by utilizing patient biomarkers that can predict susceptibility to specific adverse events and response as covariates. Methods Based on a cutting-edge cancer Phase I clinical trial design called escalation with overdose control using normalized equivalent toxicity score (EWOC-NETS), which fully utilizes all toxicities, we propose new models to incorporate patient biomarker information in the estimation of pMTDs for novel cancer therapeutic agents. The methodology is fully elaborated and the design operating characteristics are evaluated with extensive simulations. Results Simulation studies demonstrate that the utilization of biomarkers in EWOC-NETS can estimate pMTDs while maintaining the original merits of this Phase I trial design, such as ethical constraint of overdose control and full utilization of all toxicity information, to improve the accuracy and efficiency of the pMTD estimation. Conclusions Our novel cancer Phase I designs with inclusion of covariate(s) in the EWOC-NETS model are useful to estimate a personalized MTD and have substantial potential to improve the therapeutic effect of drug treatment.
Social Support, Parenting Competence, and Parenting Satisfaction Among Adolescent, African American, Mothers

This secondary analysis explored how social support changed during the first 6 months postpartum and examined the relationships among social support, parenting competence, and parenting role satisfaction. Single, low-income, adolescent, new mothers (N = 34) completed measures of perceived parenting competence, parenting role satisfaction, and four types of received social support (emotional, informational, tangible, problematic) from the entire social network at 1 week, 6 weeks, 3 months, and 6 months postpartum. Results indicated that social support did not change over time. Emotional, informational, and tangible social support were significantly correlated, concurrently and predictively, with perceived competence and satisfaction at most data collection points. Future social support intervention studies using social support as a modifiable variable with this high-risk group of African American adolescent new mothers are advocated. Health care professionals are encouraged to examine existing social support within these mothers’ identified family units.
Analisis Sifat Fisik dan Kompresibilitas Nanopowder Zinc Oxide (ZnO) sebagai Alternatif Material Amalgam

Severe effects of the mercury use on health as an amalgam material have required an alternative material in order to eliminate it from amalgam composition. This research was conducted to analyze the physical properties and compressibility of ZnO nanopowder as an alternative amalgam material. The physical properties including morphology, dimensions, and the atomic ratio were analyzed by SEM, XRD-XRF and EDX. Further, the compressibility was conducted by using hydraulic press machine. The results showed that ZnO has particle size of 14.34 nm with morphology classified as nanorods. In the compressibility test, both the variation of compression loadings and holding time have brought an effect on the significant increase of ZnO nanopowder density.
[Efficacy of cefotiam hexetil in acute maxillary sinusitis, with a short five day vs ten day treatment].

OBJECTIVE The aim of this multicentric, randomized, double blind study with direct individual benefit, was to compare two therapeutic regimens of cefotiam hexetil administration, 5 days vs 10 days, in acute maxillary sinusitis. METHOD The study was conducted in ambulatory patients treated by general practitioners according to AFSAPS (French agency for sanitary safety) guidelines for treatment of acute maxillary sinusitis. Five hundred and fifty three GPs included 1042 patients presenting with acute maxillary sinusitis in the study from December 2000 to July 2001. Patients were randomly treated with cefotiam hexetil 200 mg bid over a 5 day period followed by 5 days of placebo, or with cefotiam hexetil 200 mg bid over a 10 day period. RESULTS No significant difference was noted in each treatment group. Radiography performed in 72.2% of included patients confirmed the diagnosis in 78.8% of the cases. No significant difference occurred in the number and percentage of cured patients. In the ITT analysis (1018 patients) the clinical cure rates were respectively 85.5% and 85.3% in the 5 day and in the 10 day treatment groups, In the PP analysis (800 patients) the clinical cure rates were respectively 88.6% in each group. The low incidence of adverse effects (3.36%) was confirmed in both groups. CONCLUSION A 5 day course of cefotiam hexetil 200 mg bid is as effective as a 10 day course in the treatment of acute maxillary sinusitis in adults.
Coding for Positive Rate in the Source Model Key Agreement Problem

A two-party key agreement problem with public discussion, known as the source model problem, is considered. By relating key agreement to hypothesis testing, a new coding scheme is developed that yields a sufficient condition to achieve a positive secret-key (SK) rate in terms of Rényi divergence. The merits of this coding scheme are illustrated by applying it to an erasure model for Eve’s side information and by deriving an upper bound on Eve’s erasure probabilities for which the SK capacity is zero. This bound strictly improves on the best known single-letter lower bound on the SK capacity. Moreover, the bound is tight when Alice’s or Bob’s source is binary, which extends a previous result for a doubly symmetric binary source. The results motivate a new measure for the correlation between two random variables which is of independent interest.
TB-Places: A Data Set for Visual Place Recognition in Garden Environments

Place recognition can be achieved by identifying whether a pair of images (a labeled reference image and a query image) depict the same place, regardless of appearance changes due to different viewpoints or lighting conditions. It is an important component of systems for camera localization and for loop closure detection and a widely studied problem for indoor or urban environments. Recently, the use of robots in agriculture and automatic gardening has created new challenges due to the highly repetitive appearance with prevalent green color and repetitive texture of garden-like scenes. The lack of available data recorded in gardens or plant fields makes difficult to improve localization algorithms for such environments. In this paper, we propose a new data set of garden images for testing algorithms for visual place recognition. It contains images with ground truth camera pose recorded in real gardens at different times, with varying light conditions. We also provide ground truth for all possible pairs of images, indicating whether they depict the same place or not. We also performed a thorough benchmark of several holistic (whole-image) descriptors, and provide the results on the proposed data set. We observed that existing descriptors have difficulties with scenes with repetitive textures and large changes of camera viewpoint.
A Smartphone Application for Customized Frequency Table Selection in Cochlear Implants.

HYPOTHESIS A novel smartphone-based software application can facilitate self-selection of frequency allocation tables (FAT) in postlingually deaf cochlear implant (CI) users. BACKGROUND CIs use FATs to represent the tonotopic organization of a normal cochlea. Current CI fitting methods typically use a standard FAT for all patients regardless of individual differences in cochlear size and electrode location. In postlingually deaf patients, different amounts of mismatch can result between the frequency-place function they experienced when they had normal hearing and the frequency-place function that results from the standard FAT. For some CI users, an alternative FAT may enhance sound quality or speech perception. Currently, no widely available tools exist to aid real-time selection of different FATs. This study aims to develop a new smartphone tool for this purpose and to evaluate speech perception and sound quality measures in a pilot study of CI subjects using this application. METHODS A smartphone application for a widely available mobile platform (iOS) was developed to serve as a preprocessor of auditory input to a clinical CI speech processor and enable interactive real-time selection of FATs. The application's output was validated by measuring electrodograms for various inputs. A pilot study was conducted in six CI subjects. Speech perception was evaluated using word recognition tests. RESULTS All subjects successfully used the portable application with their clinical speech processors to experience different FATs while listening to running speech. The users were all able to select one table that they judged provided the best sound quality. All subjects chose a FAT different from the standard FAT in their everyday clinical processor. Using the smartphone application, the mean consonant-nucleus-consonant score with the default FAT selection was 28.5% (SD 16.8) and 29.5% (SD 16.4) when using a self-selected FAT. CONCLUSION A portable smartphone application enables CI users to self-select frequency allocation tables in real time. Even though the self-selected FATs that were deemed to have better sound quality were only tested acutely (i.e., without long-term experience with them), speech perception scores were not inferior to those obtained with the clinical FATs. This software application may be a valuable tool for improving future methods of CI fitting.
Combined AURKA and H3K9 Methyltransferase Targeting Inhibits Cell Growth By Inducing Mitotic Catastrophe

The current integrative pathobiologic hypothesis states that pancreatic cancer (PDAC) develops and progresses in response to an interaction between known oncogenes and downstream epigenomic regulators. Congruently, this study tests a new combinatorial therapy based on the inhibition of the Aurora kinase A (AURKA) oncogene and one of its targets, the H3K9 methylation–based epigenetic pathway. This therapeutic combination is effective at inhibiting the in vitro growth of PDAC cells both, in monolayer culture systems, and in three-dimensional spheroids and organoids. The combination also reduces the growth of PDAC xenografts in vivo. Mechanistically, it was found that inhibiting methyltransferases of the H3K9 pathway in cells, which are arrested in G2–M after targeting AURKA, decreases H3K9 methylation at centromeres, induces mitotic aberrations, triggers an aberrant mitotic check point response, and ultimately leads to mitotic catastrophe. Combined, these data describe for the first time a hypothesis-driven design of an efficient combinatorial treatment that targets a dual oncogenic–epigenomic pathway to inhibit PDAC cell growth via a cytotoxic mechanism that involves perturbation of normal mitotic progression to end in mitotic catastrophe. Therefore, this new knowledge has significant mechanistic value as it relates to the development of new therapies as well as biomedical relevance. Implications: These results outline a model for the combined inhibition of a genetic-to-epigenetic pathway to inhibit cell growth and suggest an important and provocative consideration for harnessing the capacity of cell-cycle inhibitors to enhance the future use of epigenetic inhibitors. Mol Cancer Res; 15(8); 984–97. ©2017 AACR.