Miracle-dz/UniFAR-FTUs huggingface dataset:
Accelerated Researchers: Psychosocial Risks in Gendered Institutions in Academia

In recent decades, scientific institutions have undergone significant changes due to new managerialism and the application of excellence in research. This research model has given rise to tensions related to increasing pressures and working demands in a competitive international environment that accelerate the pace of academic life. In addition, precarious working conditions and job insecurity have affected academics’ lives and careers. Academic literature has already addressed these organizational changes and their impact on academics, however, few studies have focused on psychosocial risks related to time constraints, meritocratic pressures and career insecurity from a gender perspective. This analysis is relevant given the gendered distribution of responsibilities and the evidence of gender biases in academia that hinder the advancement of gender equality in scientific institutions, as the persistent lack of women at the top of research careers show. In this paper, we explore the psychosocial effects of the new organizational model of science characterized by accelerated time regimes and precarious working conditions from a gender perspective. We draw attention to gender-based discriminatory practices that may yield an accumulative effect on the well-being of women academics. We analyze 36 interviews from women and men researchers from five areas of knowledge in Spanish universities and research centers, following a ‘gendered institutions’ approach. The results highlight psychosocial risks for both men and women academics as a result of accelerated work organizations, intensified by uncertainty and hyper-competition due to lack of positions. The hegemonic male work model characterized by total availability confirms academia as a gendered institution, especially damaging women’s well-being and careers, as well as those of men committed to care responsibilities – challenging motherhood explanations – which may discourage them from the pursuit of gender equality. Our findings highlight discriminatory practices toward women academics which create psychological harm and feelings of being unwelcome, putting their career progression at risk. Lastly, we suggest a different model of work organization following the implementation of a culture based on an ‘ethics of care’ feminist approach.
Securing Minutia Cylinder Codes for Fingerprints through Physically Unclonable Functions: An Exploratory Study

A number of personal devices, such as smartphones, have incorporated fingerprint recognition solutions for user authentication purposes. This work proposes a dual-factor fingerprint matching scheme based on P-MCCs (Protected Minutia Cylinder-Codes) generated from fingerprint images and PUFs (Physically Unclonable Functions) generated from device SRAMs (Static Random Access Memories). Combining the fingerprint identifier with the device identifier results in a secure template satisfying the discriminability, irreversibility, revocability, and unlinkability properties, which are strongly desired for data privacy and security. Experiments convey the benefits of the proposed dual-factor authentication mechanism in enhancing the security of personal devices that utilize biometric authentication schemes.
Mode-Selective Transmission Line for Chip-to-Chip Terabit-per-Second Data Transmission

The recently developed mode-selective transmission line (MSTL) is proposed and exploited as an alternative approach to accommodate the growing and future ultrafast interconnects requirements of ultralarge-scale integration for high density, speed, performance, and bandwidth (BW). A parametric study is performed to optimize the MSTL structure for high-speed global interconnects and to provide high-performance signal integrity. Picosecond and rectangular pulse propagations on MSTL are examined, and pulse distortion, broadening, ringing, and reflection are characterized. An eye diagram is also shown to examine the jitter and noise. Due to our limited low-cost printed circuit board (PCB) fabrication accuracy, the frequency-domain measurement is carried out up to 110 GHz. Our optimal fabricated MSTL structures show an ultrawide absolute BW covering dc, maintain more than 200% relative BW while transmitting around 90° bends, and achieve a measured crosstalk of better than −45 dB over the entire band. Time-domain characterizations imply that the PCB-based MSTL accommodates data rates greater than 200 Gb/s. This technology allows, for the first time, the transmission of ultrahigh-speed electrical signal and picosecond pulse transmission through global interconnects with much lower dispersion and loss than today’s technologies.
Radiotherapy of Glioblastoma 15 Years after the Landmark Stupp’s Trial: More Controversies than Standards?

Abstract Background The current standard of care of glioblastoma, the most common primary brain tumor in adults, has remained unchanged for over a decade. Nevertheless, some improvements in patient outcomes have occurred as a consequence of modern surgery, improved radiotherapy and up-to-date management of toxicity. Patients from control arms (receiving standard concurrent chemoradiotherapy and adjuvant chemotherapy with temozolomide) of recent clinical trials achieve better outcomes compared to the median survival of 14.6 months reported in Stupp’s landmark clinical trial in 2005. The approach to radiotherapy that emerged from Stupp’s trial, which continues to be a basis for the current standard of care, is no longer applicable and there is a need to develop updated guidelines for radiotherapy within the daily clinical practice that address or at least acknowledge existing controversies in the planning of radiotherapy. The goal of this review is to provoke critical thinking about potentially controversial aspects in the radiotherapy of glioblastoma, including among others the issue of target definitions, simultaneously integrated boost technique, and hippocampal sparing. Conclusions In conjunction with new treatment approaches such as tumor-treating fields (TTF) and immunotherapy, the role of adjuvant radiotherapy will be further defined. The personalized approach in daily radiotherapy practice is enabled with modern radiotherapy systems.
Finance as Cognition

This paper proposes a theory of financial intermediation as a form of cognition. It shows that each of the important elements of financial intermediation performs a cognitive role. This includes foundational instruments such as money and institutions such as banks. By demonstrating the cognitive work it performs, this theory also offers a new explanation for emergent financial phenomena, such as asset price booms.
Extracellular Vesicles: A Novel Target for Exercise-Mediated Reductions in Type 2 Diabetes and Cardiovascular Disease Risk

Regular exercise is important for reducing type 2 diabetes (T2D) and/or cardiovascular disease (CVD) risk. However, only about 40–50% of this CVD risk reduction is accounted for by adiposity, hyperglycemia, hypertension, and dyslipidemia. Herein, we present the novel hypothesis that extracellular vesicles (EVs) are candidate biomarkers that may relate to impaired endothelial function and insulin resistance independent of obesity risk factors. EVs are small membrane-bound particles that are generated by cells following stimulation, stress, or activation. They carry markers of their parent cell and are thought to be potent bioactivators and communicators. We discuss the underlying physiology of specific cell type EVs, as well as examine how acute and chronic exercise interventions impact EV count and phenotype. We also propose that current gaps in the field are in part related to use of different detection techniques and the lack of standardized measurements of EV affecting the pre- and postanalytical phase. Ultimately, improving the understanding of how EVs impact cardiometabolic health and their function will lead to improved approaches for enhancing diagnostic options as well as designing exercise interventions that treat and/or prevent T2D and CVD.
Structure-Guided Redesign Improves NFL HIV Env Trimer Integrity and Identifies an Inter-Protomer Disulfide Permitting Post-Expression Cleavage

Soluble HIV-1 envelope glycoprotein (Env) trimers are under active investigation as vaccine candidates in relevant pre-clinical models. Like SOSIPs, the cleavage-independent native flexibly linked (NFL) trimers are faithful mimics of the Env spike. Here, we analyzed multiple new designs to explore alternative modifications, informing tertiary interactions, while maintaining NFL trimer homogeneity and integrity. Accordingly, we performed a proline (P) substitution screen in the gp41 heptad repeat 1 region, identifying other trimer-enhancing Ps, including L555P. This P improved trimer integrity compared to I559P in selected properties. Next, we screened 15 structure-guided potential cysteine pairs in gp140 and found that A501C-L663C (“CC2”) forms an inter-protomer disulfide bond that demonstrably increased NFL trimer thermostability. We combined these two approaches with trimer-derived substitutions, coupled with glycine substitutions at helix-to-coil transitions, developed by our group. To increase the exposure of the fusion peptide (FP) N-terminus, we engineered an enterokinase (EK) cleavage site upstream of the FP for controlled post-expression cleavage. In combination, the redesigns resulted in highly stable and homogeneous NFL mimics derived from different clades. Following recombinant EK cleavage, the NFL trimers retained covalent linkage, maintaining a native-like structure while displaying enhanced stability and favorable antigenic features. These trimers also displayed increased exposure of neutralizing epitopes in the FP and gp120/gp41 interface, while retaining other neutralizing epitopes and occluding non-neutralizing elements. This array of Env-structure-guided designs reveals additional interactive regions in the prefusion state of the HIV Env spike, affording the development of novel antigens and immunogens.
Differences of in-hospital outcomes within patients undergoing percutaneous coronary intervention at institutions with high versus low procedural volume: a report from the Japanese multicentre percutaneous coronary intervention registry

Objective We aimed to determine the relationship between the prevalence of in-hospital complications and annual institutional patient volume in a population of patients undergoing percutaneous coronary intervention (PCI). Methods Clinical data of patients receiving PCI between January 2010 and June 2015 were collected from 14 academic institutions in the Tokyo area and subsequently used for analysis. We employed multivariate hierarchical logistic regression models to determine the effect of institutional volume on several in-hospital outcomes, including in-hospital mortality and procedure-related complications. Results A total of 14 437 PCI cases were included and categorised as receiving intervention from either lower-volume (<200 procedures/year, n=6 hospitals) or higher-volume (≥200 procedures/year, n=8 hospitals) institutions. Clinical characteristics differed significantly between the two patient groups. Specifically, patients treated in higher-volume hospitals presented with increased comorbidities and complex coronary lesions. Unadjusted mortality and complication rate in lower-volume and higher-volume hospitals were 1.3% and 1.2% (p=0.0614) and 6.2% and 8.1% (p=0.001), respectively. However, multivariate hierarchical logistic regression models adjusting for differences in the patient characteristics demonstrated that institutional volume was not associated with adverse clinical outcomes. Conclusions In conclusion, we observed no significant association between annual institutional volume and in-hospital outcomes within the contemporary PCI multicentre registry. Trial registration number UMIN R000005598.
IoT-Enabled Adaptive Context-Aware and Playful Cyber-Physical System for Everyday Energy Savings

Home energy savings via eco-feedback is often considered a serious, tedious, or even distracting task due to the need for frequent human intervention. In addition, most existing eco-feedback systems focus on providing energy usage information and ignore the users’ contexts. This may render the systems incapable of capturing the users’ changes when proenvironmental behaviors have been encouraged. To address this, our study leverages Internet of Things (IoT) enabled technologies to realize an adaptive, context-aware, and playful cyber-physical system (CPS) for everyday energy savings with the hope of facilitating collaboration between a person and a smart energy-saving (ES) system to the greatest extent possible. To leverage the benefits inherent in a CPS, bidirectionally interactive information visualization integrated with pet-raising gamification was incorporated into the adaptive CPS. This synchronized the information from the user's physical environment with its counterpart in the pet's virtual environment. In order to provide flexible services, all IoT devices were agentized to form reconfigurable agents. In our experimental evaluation, this bidirectional mapping empowered users to flexibly control remote appliances anywhere and anytime in a more natural way, which enabled users to embed interactions with the ES CPS into their daily routine. Furthermore, improvements to system adaptability (33% in precision; 21% in recall) along with the reconfigurable ES services (additionally saving energy about 16.21%) show the potential of the CPS to enhance the users’ experience and prolong the users' engagement in everyday energy savings.
Critical Response of Nonlinear Base-Isolated Building Considering Soil-Structure Interaction Under Double Impulse as Substitute for Near-Fault Ground Motion

The critical nonlinear response considering soil-structure interaction is investigated for a base-isolated building under a double impulse as a substitute for near-fault earthquake ground motions. The complicated model of the nonlinear base-isolated building considering soil-structure interaction is first modeled as a two-degree-of-freedom (2DOF) system (SDOF superstructure and base-isolation story) on a swaying-rocking spring-dashpot system. Then the 2DOF system on a swaying-rocking spring-dashpot system is transformed into an SDOF system on a swaying-rocking spring-dashpot system by neglecting the mass on the base-isolation story. Finally the SDOF system on a swaying-rocking spring-dashpot system is further transformed into an SDOF system by neglecting the mass and moment of inertia of the base mat. Since an explicit expression had been derived in the previous paper on the maximum elastic-plastic response of an SDOF damped bilinear hysteretic structure subjected to the ‘critical double impulse input’ causing the maximum response for variable interval of impulses with the input level kept constant, this expression is applied to the finally transformed SDOF system. The transformation of structural viscous damping in different elements is another new aspect in this paper. The reliability and accuracy of the proposed simplification methodology are investigated by comparing with the results by the time-history response analysis under the critical double impulse and the one-cycle sine wave as a representative of the main part of the near-fault earthquake ground motion.
Utilization of a healthcare failure mode and effects analysis to identify error sources in the preanalytical phase in two tertiary hospital laboratories

Introduction The presence of errors in the preanalytical phase is a thoroughly studied problem. A strategy to increase their source detection might be the use of the Healthcare Failure Mode and Effects Analysis (HFMEA). The aim of this study is improving the capacity of identifying sources of error during the preanalytical period in samples provided by primary care clinics (PCC) with the use of the HFMEA as a tool in the laboratories of two tertiary hospitals. Materials and methods A HFMEA was carried out in each laboratory, by means of the creation of groups of experts with similar characteristics (doctors and nurses from PCC and laboratory, support staff, and laboratory technicians). The Risk Priority Number (RPN) was calculated. Results Items with elevated RPN were presented in both centers. The highest RPN were in LAB1: “two request notes for a patient” and “the segregation of oncology urgent samples” (both with 384), while in LAB2 was “the lack of information in patients with oral glucose overload test” (RPN 576). Considering the different steps in the preanalytical phase, LAB1 paid attention in sampling, samples reception and the programming in the Laboratory Information System, while LAB2 paid attention in the request form, the appointment system, sampling procedures, transport and reception. Conclusion The laboratories prioritized the problems differently. However, both centers offer solutions to these possible sources of error. We proposed improvement actions that can be resolved easily, with a low cost for the system, mainly to schedule a specific formative programme and a deep revision of the existing protocols.
Downregulation of PIK3CA via antibody-esiRNA-complexes suppresses human xenograft tumor growth

Precision cancer therapy requires on the one hand detailed knowledge about a tumor’s driver oncogenes and on the other hand an effective targeted therapy that specifically inhibits these oncogenes. While the determination of genomic landscape of a tumor has reached a very precise level, the respective therapy options are scarce. The application of small inhibitory (si) RNAs is a promising field of investigation. Here, we present the effective in vivo-treatment of colorectal cancer (CRC) xenograft tumors with antibody-complexed, endoribonuclease-prepared small inhibitory (esi)RNAs. We chose heterogeneous endoribonuclease-prepared siRNA pools (esiRNAs) against the frequently mutated genes PIK3CA and KRAS and coupled them to the anti-EGFR antibody cetuximab, which was internalized specifically into the tumor cells. esiRNA pools have been shown to exhibit superior specificity in target gene knockdown compared to classic siRNAs. We identified a significant decrease in tumor growth upon this treatment due to decreased tumor cell proliferation. The ex vivo-analysis of the xenograft CRC tumors revealed the expected downregulation of the intended direct targets PIK3CA and KRAS on protein level. Moreover, known downstream targets for EGFR signaling such as p-ERK, p-AKT, and c-MYC were decreased as well. We therefore propose the use of antibody-esiRNA complexes as a novel experimental treatment option against key components of the EGFR signaling cascade.
An empirical study on TensorFlow program bugs

Deep learning applications become increasingly popular in important domains such as self-driving systems and facial identity systems. Defective deep learning applications may lead to catastrophic consequences. Although recent research efforts were made on testing and debugging deep learning applications, the characteristics of deep learning defects have never been studied. To fill this gap, we studied deep learning applications built on top of TensorFlow and collected program bugs related to TensorFlow from StackOverflow QA pages and Github projects. We extracted information from QA pages, commit messages, pull request messages, and issue discussions to examine the root causes and symptoms of these bugs. We also studied the strategies deployed by TensorFlow users for bug detection and localization. These findings help researchers and TensorFlow users to gain a better understanding of coding defects in TensorFlow programs and point out a new direction for future research.
Davram: Distributed Virtual Memory in User Space

One of the most challenging problems in modern distributed big data systems lies in their memory management: these systems preallocate a fixed amount of memory before applications start. In the best case where more memory can be acquired, users have to reconfigure the deployment and re-compute many intermediate results. If no more memory is available, users are then forced to manually partition the job into smaller tasks, incurring both development and performance overhead. This paper presents a user-level utility for managing the memory in distributed systems—the Distributed and Autonomous Virtual RAM (Davram). Davram enables to efficiently swap data between memory and disk in a distributed system without users' intervention or applications' awareness.
Development of Graphene Oxide-/Galactitol Polyester-Based Biodegradable Composites for Biomedical Applications

We have developed nanocomposites based on galactitol/adipic acid in the molar ratio of 1:1 with different weight percentages of graphene oxide (GO). The objective of this study was to analyze the effect of enhanced physicochemical properties achieved due to the addition of GO to the polymers on cellular responses. The chemical structures of the polymer and composites were confirmed by Fourier transform infrared spectroscopy. Scanning electron microscopy revealed the uniform distribution of GO in the polymers. Differential scanning calorimetry showed no significant variation in the glass-transition temperature of the nanocomposites. Dynamic mechanical analysis demonstrated the increase of Young’s modulus with the increase in the addition of GO to the polymer from 0.5 to 1 wt % and a dramatic decrease in modulus with the addition of 2 wt % GO to the polyester. Contact angle analysis illustrated a slight increase in hydrophilicity with the addition of GO to the polyester. Investigations on the hydrolytic degradation and dye release were performed and revealed that the degradation and release decreased with the increase in the weight percentages of GO but increased for 2 wt % GO with the polymer. The rates of degradation and dye release followed first-order and Higuchi kinetics, respectively. The initial in vitro cytocompatibility studies exhibited minimal toxicity. Mineralization studies proved that these nanocomposites stimulated osteogenesis. This study has salient implications for designing biodegradable polymers for use as scaffolds with tailored release.
A Deep Learning Architecture to Detect Events in EEG Signals During Sleep

Electroencephalography (EEG) during sleep is used by clinicians to evaluate various neurological disorders. In sleep medicine, it is relevant to detect macro-events (≥ 10s) such as sleep stages, and micro-events (≤ 2s) such as spindles and K-complexes. Annotations of such events require a trained sleep expert, a time consuming and tedious process with a large inter-scorer variability. Automatic algorithms have been developed to detect various types of events but these are event-specific. We propose a deep learning method that jointly predicts locations, durations and types of events in EEG time series. It relies on a convolutional neural network that builds a feature representation from raw EEG signals. Numerical experiments demonstrate efficiency of this new approach on various event detection tasks compared to current state-of-the-art, event specific, algorithms.