Miracle-dz/UniFAR-FTUs huggingface dataset:
Using support vector machines on photoplethysmographic signals to discriminate between hypovolemia and euvolemia

Identifying trauma patients at risk of imminent hemorrhagic shock is a challenging task in intraoperative and battlefield settings given the variability of traditional vital signs, such as heart rate and blood pressure, and their inability to detect blood loss at an early stage. To this end, we acquired N = 58 photoplethysmographic (PPG) recordings from both trauma patients with suspected hemorrhage admitted to the hospital, and healthy volunteers subjected to blood withdrawal of 0.9 L. We propose four features to characterize each recording: goodness of fit (r2), the slope of the trend line, percentage change, and the absolute change between amplitude estimates in the heart rate frequency range at the first and last time points. Also, we propose a machine learning algorithm to distinguish between blood loss and no blood loss. The optimal overall accuracy of discriminating between hypovolemia and euvolemia was 88.38%, while sensitivity and specificity were 88.86% and 87.90%, respectively. In addition, the proposed features and algorithm performed well even when moderate blood volume was withdrawn. The results suggest that the proposed features and algorithm are suitable for the automatic discrimination between hypovolemia and euvolemia, and can be beneficial and applicable in both intraoperative/emergency and combat casualty care.
Replication-incompetent gammaretroviral and lentiviral vector-based insertional mutagenesis screens identify prostate cancer progression genes

Replication-incompetent gammaretroviral (γRV) and lentiviral (LV) vectors have both been used in insertional mutagenesis screens to identify cancer drivers. In this approach the vectors stably integrate in the host cell genome and induce cancers by dysregulating nearby genes. The cells that contain a retroviral vector provirus in or near a proto-oncogene or tumor suppressor are preferentially enriched in a tumor. γRV and LV vectors have different integration profiles and genotoxic potential, making them potentially complementary tools for insertional mutagenesis screens. We performed screens using both γRV and LV vectors to identify driver genes that mediate progression of androgen-independent prostate cancer (AIPC) using a xenotransplant mouse model. Vector transduced LNCaP cells were injected orthotopically into the prostate gland of immunodeficient mice. Mice that developed tumors were castrated to create an androgen-deficient environment and metastatic tumors that developed were analyzed. A high-throughput modified genomic sequencing PCR (MGS-PCR) approach identified the positions of vector integrations in these metastatic tumors. OR2A14, FER1L6, TAOK3, MAN1A2, MBNL2, SERBP1, PLEKHA2, SPTAN1, ADAMTS1, SLC30A5, ABCC1, SLC7A1 and SLC25A24 were identified as candidate prostate cancer (PC) progression genes. TAOK3 and ABCC1 expression in PC patients predicted the risk of recurrence after androgen deprivation therapy. Our data shows that γRV and LV vectors are complementary approaches to identify cancer driver genes which may be promising potential biomarkers and therapeutic targets.
The Transfer of Improved Cavity Processing Protocols to Industry for LCLS-II: N-Doping and Electropolishing

Based on the R&D efforts of colleagues at FNAL, Cornell, and JLab, the LCLS-II project adopted a modification to the rather standard niobium SRF cavity surface processing protocol that incorporates a high temperature diffusion doping with nitrogen gas. This change was motivated by the resulting higher Q0 and the prospect of significantly lower cryogenic heat load for LCLS-II. JLab is responsible for managing the cavity procurement for the LCLS-II project. The first phase of the procurement action is to transfer the nitrogen-doping protocol to the industrial vendors. We also seek to exploit improvements in understanding of the niobium electropolishing process as part of the production processing of the TESLA-style LCLS-II cavities. We report on the technology transfer activities and progress toward the envisaged performance demonstration of vendor-processed cavities. N-DOPING REQUIREMENTS Based on the multi-lab R&D effort that validated the discovery from FNAL of the beneficial effects of nitrogen doping of niobium cavities and explored its sensitivity to process variations, the LCLS-II project selected a particular protocol for cavity preparation that has consistently yielded higher Q0, and thus lower cryogenic losses, than has previously been accessible. This R&D effort has been documented [1-5], and the subsequent preparation of cavities for the two LCLS-II prototype cryomodules are reported at this conference. [6-11] By conference time the cavity vendors for the LCLS-II project have been selected. Both vendors visited JLab and FNAL to consult regarding modifications to the cavity treatment protocols compared with prior experience. Furnace gas flow control requirements were discussed. Procedures for controlled cavity electropolishing were discussed. Vendors observed application of both processes to cavities at JLab. Vendors are now in the process of adapting their own facilities to accomplish the modified processes. First commissioning runs are anticipated soon after the conference. Per the terms of the contract, JLab staff will advise and assist. Vendors are required to pass a qualification test by successfully processing two cavities supplied by the project, success being demonstrated by documented process control and acceptable high-Q performance of cavities delivered to JLab under vacuum for cryogenic test. The cavity preparation protocol is a relatively minor, but controlled variation on the now rather standard niobium cavity surface preparation methods developed by the community over the past decades. It involves lowpressure nitrogen gas exposure at the end of a 800 °C vacuum bake, followed by a light electropolish (EP) removing a few microns from the cavity surface. The control parameters associated with the heat treat cycle issued to the vendors are listed in Tables 1 and 2. Table 1: Vacuum Heat Treatment and Nitrogen Doping
Interfacial effects in polypropylene–silica nanocomposites

Grafted inorganic nanoparticles can greatly improve the mechanical performance of polymers. To examine the effects of the interfacial characteristics generated by the grafting polymer bonded to nanoparticle surfaces, we chemically grafted nano-silica with different polymers and then melt-mixed it with polypropylene (PP). We extracted the homopolymers produced during the graft polymerization from the grafted products before the composites were manufactured to get rid of the side effects of the nongrafting polymers. We tailored the interfacial interaction between the grafted nano-SiO2 and PP matrix by changing the amount of the grafting polymers on the nanoparticles, that is, the grafting percentage. Mechanical tests indicated that all the composites incorporated with grafted nano-SiO2 particles possessed much higher impact strength than untreated SiO2/PP composites and neat PP. The greatest contribution of the particles was made at a low grafting percentage. Tensile measurements showed that the treated nanoparticles could provide PP with stiffening, strengthening, and toughening effects at a rather low filler content (typically 0.8 vol %) because of the enhanced interfacial adhesion resulting from molecular entanglement and interdiffusion between the grating polymers on the nanoparticles and matrix macromolecules. The presence of grafting polymers on the nanoparticles provided the composites with a tailorable interphase. The tensile performance of the composites was sensitive to the nature of the grafting polymers. Basically, a hard interface was beneficial to stress transfer, whereas a soft one hindered the development of cavities in the matrix. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 92: 1771–1781, 2004
Pinpoint: fast and precise sparse value flow analysis for million lines of code

When dealing with millions of lines of code, we still cannot have the cake and eat it: sparse value-flow analysis is powerful in checking source-sink problems, but existing work cannot escape from the “pointer trap” – a precise points-to analysis limits its scalability and an imprecise one seriously undermines its precision. We present Pinpoint, a holistic approach that decomposes the cost of high-precision points-to analysis by precisely discovering local data dependence and delaying the expensive inter-procedural analysis through memorization. Such memorization enables the on-demand slicing of only the necessary inter-procedural data dependence and path feasibility queries, which are then solved by a costly SMT solver. Experiments show that Pinpoint can check programs such as MySQL (around 2 million lines of code) within 1.5 hours. The overall false positive rate is also very low (14.3% - 23.6%). Pinpoint has discovered over forty real bugs in mature and extensively checked open source systems. And the implementation of Pinpoint and all experimental results are freely available.
A clustering approach to infer Wikipedia contributors' profile

Recent studies have improved our knowledge about the different types or profiles of online contributors, from casual to very involved ones, through focused people. But they use very complex methodologies, making their replication by the practitioners limited. We show on both Romanian and Danish wikis that using only the edit and their distribution over time to feed clustering techniques, allows to build these profiles with good accuracy and stability. This suggests that light monitoring of newcomers may be sufficient to adapt the interaction with them and to increase the retention rate.
On Capacity of Network Error Correction Coding With Random Errors

In this letter, we consider the capacity results of network error correction coding over a general multicast network, where a malicious error occurs on each edge with a fixed probability <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula> at each transmission. A pair of upper and lower bounds on the capacity are given, which are proved to coincide for a unicast network with <inline-formula> <tex-math notation="LaTeX">$|\mathcal {E}|$ </tex-math></inline-formula> parallel channels connected directly from source to sink node, where <inline-formula> <tex-math notation="LaTeX">$\mathcal {E}$ </tex-math></inline-formula> is the edge set of the network. A scheme with non-linear coding at the source and linear coding at the intermediate nodes is proposed, which achieves a strictly higher transmission rate than linear network coding.
A Novel Sidelobe Reduction Algorithm Based on Two-Dimensional Sidelobe Correction Using D-SVA for Squint SAR Images

Sidelobe reduction is a very primary task for synthetic aperture radar (SAR) images. Various methods have been proposed for broadside SAR, which can suppress the sidelobes effectively while maintaining high image resolution at the same time. Alternatively, squint SAR, especially highly squint SAR, has emerged as an important tool that provides more mobility and flexibility and has become a focus of recent research studies. One of the research challenges for squint SAR is how to resolve the severe range-azimuth coupling of echo signals. Unlike broadside SAR images, the range and azimuth sidelobes of the squint SAR images no longer locate on the principal axes with high probability. Thus the spatially variant apodization (SVA) filters could hardly get all the sidelobe information, and hence the sidelobe reduction process is not optimal. In this paper, we present an improved algorithm called double spatially variant apodization (D-SVA) for better sidelobe suppression. Satisfactory sidelobe reduction results are achieved with the proposed algorithm by comparing the squint SAR images to the broadside SAR images. Simulation results also demonstrate the reliability and efficiency of the proposed method.
Transplantation in highly HLA-sensitized patients: challenges and solutions

Despite better understanding of the impact of development of the human leukocyte antigen (HLA) antibody and numerous advancements in immunosuppressive therapy, the abil- ity to successfully transplant highly sensitized patients remains a significant challenge. As the percentage of the waiting list becomes increasingly populated with highly sensitized patients, there is a growing demand for effective strategies to manage these patients. Over the past 20 years, desensitization therapies have been modified and developed, and are mainly utilized at transplant centers that have developed expertise. In addition, recognition that the highly sensitized patient population is disadvantaged on the transplant waiting list has led to recent changes in national kidney allocation policy. Furthermore, creative strategies, such as enroll- ment of sensitized patients into paired kidney exchange programs, have been developed to find compatible matches for these patients. The goal of this article is to address some of the specific challenges related to transplanting the highly sensitized patient at a high-volume transplant center with experience in desensitization and to review established and emerging solutions to help this patient population.
Anti-cancer effect of toosendanin and its underlying mechanisms

Abstract Toosendanin (TSN) is a triterpenoid purified from the medicinal herb Melia toosendan Sieb. et Zucc and has been used as an insecticide for decades. Recent studies have attracted increasing interest of TSN due to its novel anti-cancer effect in diverse cancer models. The broad spectrum anti-cancer activity suggests that TSN inhibits multiple pathways/targets that are critical for cancer cell survival and proliferation. Our recent study indicated that TSN has anti-cancer effect in glioblastoma through induction of estrogen receptor β (ERβ) and p53. This review highlights the anti-cancer efficacy of TSN and provides proof-of-principle insight into the underlying mechanisms. Graphical Abstract
Associations of Number Line Estimation With Mathematical Competence: A Meta-analysis.

The number line estimation task is widely used to investigate mathematical learning and development. The present meta-analysis statistically synthesized the extensive evidence on the correlation between number line estimation and broader mathematical competence. Averaged over 263 effect sizes with 10,576 participants with sample mean ages from 4 to 14 years, this correlation was r = . 443. The correlation increased with age, mainly because it was higher for fractions than for whole numbers. The correlation remained stable across a wide range of task variants and mathematical competence measures (i.e., counting, arithmetic, school achievement). These findings demonstrate that the task is a robust tool for diagnosing and predicting broader mathematical competence and should be further investigated in developmental and experimental training studies.
On the dynamical thermoelasticity problem for a hollow funtionally graded cylinder

ABSTRACT A thermoelasticity problem of a pressurized infinite cylinder made of functionally graded material is solved analytically where material properties vary with radial position. Time dependent thermal and mechanical boundary conditions are assumed to act on the inner and outer surfaces of the cylinder. For thermal boundary conditions, temperature is prescribed on both surfaces, whereas for mechanical boundary conditions, tractions are prescribed on the boundaries. Obtaining distribution of temperature throughout the cylinder, the dynamical structural problem is solved and closed form relations are extracted for distributions of stress components.
Language Modeling with Generative AdversarialNetworks

Generative Adversarial Networks (GANs) have been promising in the field of image generation, however, they have been hard to train for language generation. GANs were originally designed to output differentiable values, so discrete language generation is challenging for them which causes high levels of instability in training GANs. Consequently, past work has resorted to pre-training with maximum-likelihood or training GANs without pre-training with a WGAN objective with a gradient penalty. In this study, we present a comparison of those approaches. Furthermore, we present the results of some experiments that indicate better training and convergence of Wasserstein GANs (WGANs) when a weaker regularization term is enforcing the Lipschitz constraint.
Generating global political priority for urban health: the role of the urban health epistemic community

&NA; Over the past decade there has been much discussion of the challenges posed by rapid urbanization in the developing world; yet the health of the urban poor, and especially those residing in low‐ and middle‐income countries, continues to receive little political priority in most developing countries and at the global level. This research applies social science scholarship and a public policy analytical framework to assess the factors that have challenged efforts to make health in urban poor settings a priority. We conducted 19 semi‐structured phone interviews with key urban health proponents and experts representing agencies that shape opinions and manage resources in global health. We also conducted a literature review, which included published scholarly literature and reports from organizations involved in urban health provision and advocacy. Utilizing a process‐tracing method, we triangulated among these sources of data to create a historical narrative and analyse the factors that shape the global level of attention to and resources for urban health. The urban health agenda continues to be challenged by six factors, three of which concern the political context or characteristics of the issue: long‐standing competition with the dominant development agenda that is rural health oriented; limited data and measurement tools that can effectively gauge the extent of the problem; and lack of evidence on how to best to address the issue. The other three factors are directly under the control of the urban health community: the community's ineffective governance; little common understanding among its members of the problem and how to address it; and an unconvincing framing of the issue to the public. The study offers suggestions as to what advocates can do to secure greater attention and resources in order to help address the health needs of the urban poor.
Simulation of the Effect of Different Presbyopia-Correcting Intraocular Lenses With Eyes With Previous Laser Refractive Surgery.

PURPOSE To simulate the optical performance of three presbyopia-correcting intraocular lenses (IOLs) implanted in eyes with previous laser refractive surgery. METHODS A simulation of the through-focus modulation transfer function (MTF) was performed for three presbyopia-correcting IOLs (Mplus, Oculentis GmbH, Berlin, Germany; Symfony, Johnson & Johnson Vision, Santa Ana, CA; and Mini Well, SIFI S.p.A., Lavinaio, Italy) in one eye with previous myopic LASIK and another with hyperopic LASIK. Real topographic data and the wavefront aberration profile of each IOL obtained with a Hartmann-Shack sensor were used. RESULTS In the eye with myopic LASIK, all IOLs lost optical quality at near and intermediate distances for 4- and 4.7-mm pupil size. For 3-mm pupil size, the Mini Well IOL showed the best intermediate and near MTF and maintained the far focus independently of the pupil. In the eye with hyperopic LASIK, the Mini Well IOL showed an intermediate, distance, and -4.00-diopter (D) foci for all pupils. The Symfony IOL showed a depth of focus at far and intermediate distance for 3-mm and a focus at -2.50 D in the rest. The Mplus showed a focus of -4.50 and -3.00 D for the 3- and 4-mm pupil, respectively. CONCLUSIONS The Mini Well and Symfony IOLs seem to work better than the Mplus IOL in eyes with previous myopic LASIK. With previous hyperopic LASIK, the Mini Well IOL seems to be able to provide acceptable near, intermediate, and far foci for all pupil sizes. These findings should be confirmed in future clinical studies. [J Refract Surg. 2018;34(4):222-227. ].
A C++ Implementation of UML Subsets and Unions for MDE

This paper shows and discusses the realization of advanced data structures used in the UML specification (namely subsets, unions, and subset-unions) for a C++ execution engine. Those data structures have been realized thanks to the use of variadic templates, which were first introduced in C++11. Thanks to those templates which allow to take as parameters a non-fixed number of elements in an elegant manner, it has been possible to automatically generate from the Ecore and UML ecore models type-safe data structures which avoid elements being duplicated or the generation of additional lists during run-time. A performance analysis is presented to show how our implementation behaves compared to the other possible approaches.
Self-Alignment and Bonding of Microparts Using Adhesive Droplets

This paper describes the self-alignment and bonding of microparts using adhesive surface tension to assemble microsystems in air. The alignment and bonding were tested experimentally using adhesive droplets, and the resulting performance was evaluated. The adhesive, which was inorganic and water-soluble before hardening, was diluted with water to a ratio of 10:1 so that its surface tension generated a sufficient restoring force for self-alignment. The experimental results showed that the average of the alignment errors obtained using the adhesive on 1.0 × 1.0 × 0.15-㎜ micro parts was less than 2 ㎛ in the X and Y directions and 0.2 degrees in the θ direction. These alignment errors were almost the same as those obtained using water. The use of a suitable adhesive had no negative effects on the alignment accuracy. The average tensile strength of the adhesive bond after self-alignment was 0.61 N/㎟.
Flexural performance of extruded ECC panel

This paper presents the materials, production process, and mix proportion applied to an ex- truded ECC panel and the effect of the fiber distribution characteristics, which are uniquely obtained with ap- plication of the extrusion process, on the flexural behavior of the panel. In order to demonstrate the fiber dis- tribution effect, a series of experiments and analyses, including a sectional image analysis and micro- mechanical analysis, was performed. From test results, it was found that the flexural behavior of the panel was highly affected by slight variation in the mix composition. This is mainly attributable to the difference in mix composition resulting in change of the micro-mechanical properties as well as fiber distribution characte- ristics. In terms of the average fiber orientation, the fiber distribution was found to be similar to that derived under the assumption of a two-dimensional random distribution, irrespective of the mix composition. In con- trast, the probability density function for the fiber orientation was measured to vary extensively depending on the mix composition.