Miracle-dz/UniFAR-FTUs huggingface dataset:
Neuropilin-1 as a Potential Biomarker of Prognosis and Invasive-Related Parameters in Liver and Colorectal Cancer: A Systematic Review and Meta-Analysis of Human Studies

Simple Summary Neuropilin-1 (NRP1) is a transmembrane protein which has had recently increased interest from cancer researchers. Liver cancer and colorectal cancer (CRC) are two of the most frequent and deadly tumors worldwide. Here, we assessed the prognostic, diagnostic and clinicopathological value of NRP1 in liver cancer and CRC patients by systematic searches in PubMed, Scopus, Web of Science, Embase and Cochrane Library and a meta-analysis. Results obtained showed that NRP1 overexpression was significantly correlated with lower survival in liver cancer patients and with tumor development in hepatocarcinoma patients, and high levels of NRP1 were strongly correlated with an increased risk of vascular invasion in liver cancer and metastasis in CRC and liver tumors. Therefore, these findings could establish novel interest of NRP1 as a useful biomarker for patient prognosis as well as for invasive-related characteristics in patients with liver cancer or CRC. Abstract Neuropilin-1 (NRP1) is a transmembrane protein involved in numerous cellular functions which has had increasing interest from cancer researchers. Liver cancer and colorectal cancer (CRC) are two of the most frequent and deadly tumors with a complex pharmacological framework. Here, we assessed the prognostic, diagnostic and clinicopathological value of NRP1 in liver cancer and CRC patients. We searched PubMed, Scopus, Web of Science, Embase and Cochrane Library databases for articles evaluating the NRP1 correlation with survival parameters, tumor development or clinicopathological features. Hazard ratios and odds ratios with 95% confidence intervals were extracted or estimated by Parmar method and pooled to evaluate the overall effect size with STATA 16 software. Heterogeneity was analyzed by chi-square-based Q test and I2 statistic, along with meta-regression and subgroup analysis, and publication bias was assessed by funnel plot asymmetry and Egger’s test. The study protocol was registered in PROSPERO (CRD42022307062). NRP1 overexpression was significantly correlated with lower survival in liver cancer patients and with tumor development in hepatocarcinoma patients, and was strongly correlated with an increased risk of vascular invasion in liver cancer and metastasis in CRC and liver tumors. These results support the role of NRP1 as a potential and useful biomarker in both types of cancer.
Morphometric, meristic and genetic characteristics of Atlantic bonito (Sarda sarda) in the Black Sea

The Atlantic bonito (Sarda sarda) is a commercially important and popular species in the world as well as in Turkish fisheries sector. In this study, the morphologic and meristic features and genetic characteristics of Atlantic bonito in the Black Sea were examined. We found that most of the morphometric measurements in females were greater than males. Besides, 10 haplotypes were found for COI gene region, 3 haplotypes for 16s gene region and 4 haplotypes for the rhodopsin gene region. Genetic closure was determined in Tirebolu population for the first time.
Transition metal complexes produced from dipicolinic acid: synthesis, structural characterization, and anti-microbial investigations

ABSTRACT. A novel series of mononuclear complexes of the type, [M(L)(H2O)2] [M = Co(II) (1), Ni(II) (2), Zn(II) (3), Cd(II) (4), L = dipicolinate), has been investigated using various techniques, including elemental analyses, FT-IR, 1H- and 13C NMR spectroscopy, powder XRD and thermogravimetric analysis. The results indicate that the coordination of the dipicolinic acid to the metal ions involves two carboxylate O atoms, the pyridine N atom, and two water molecules. The pyridine-2,6-dicarboxylic acid and its studied compounds have been screened against microbial species. The findings show that the complexes have higher activity in comparison to the free pyridine-dicarboxylic acid. KEY WORDS: Dipicolinic acid, Metal complexes, Antimicrobial activity Bull. Chem. Soc. Ethiop. 2022, 36(3), 607-615. DOI: https://dx.doi. org/10.4314/bcse.v36i3. 10
Air Pollution and Workplace Choice: Evidence from China

Understanding the impacts of air pollution on public health and individual behavior is crucial for optimal environmental policy design. Using 2015 census microdata in China, this paper examined the causal effect of air pollution on working place choice. The research design relies on a regression discontinuity design based on China’s Huai River Policy. The discontinuity in air pollution caused by the Huai River Policy provides a natural experiment to estimate the impact of air pollution. The results show that air pollution significantly increases the possibility of individuals working near home. The positive effect of air pollution on working near home is more significant for women, the elderly, urban individuals and those individuals working in secondary and tertiary industries. This study improves our understanding of the health effects and avoidance behavior associated with environmental hazards, discusses the negative impact of air pollution on labor mobility and mismatch by making individuals work nearby, and emphasizes that strengthening air pollution control should be a long-term policy.
Achromobacter Species: An Emerging Cause of Community-Onset Bloodstream Infections

Background: Case reports and small series indicate that Achromobacter species bloodstream infection (BSI) is most commonly a complication of hospitalization among patients with chronic lung disease. The aim of the present study was to determine the incidence, risk factors, and outcomes of Achromobacter sp. BSI in an Australian population. Methods: Retrospective, laboratory-based surveillance was conducted in Queensland, Australia (population ≈ 5 million) during 2000–2019. Clinical and outcome data were obtained by linkage to state hospital admissions and vital statistics databases. BSI diagnosed within the community or within the first two calendar days of stay in hospital were classified as community-onset. Community-onset BSIs were grouped into community-associated and healthcare-associated. Results: During more than 86 million person-years of surveillance, 210 incidents of Achromobacter sp. BSI occurred among 195 individuals for an overall age-and sex-standardized annual incidence of 2.6 per million residents. Older individuals and males were at highest risk (2.9 vs. 2.0 per million, IRR for males 1.5; 95% CI, 1.1–1.9; p = 0.008). Most (153; 73%) cases were of community-onset of which 100 (48%) and 53 (25%) were healthcare- and community-associated, respectively. An increasing proportion of community-onset cases were observed during twenty years of surveillance. Underlying medical illnesses were common with median (interquartile range) Charlson Comorbidity Index (CCI) scores of 3 (1–5). CCI scores of 0, 1, 2, and 3+ were observed in 37 (18%), 27 (13%), 40 (19%), and 105 (50%) of cases, respectively. All but one of the cases were admitted to hospital for a median (interquartile range) length of stay of 12 (5–34) days. All-cause case–fatality rates in hospital by day 30 and by day 90 were 30 (14%), 28 (13%), and 42 (20%), respectively. The 90-day case–fatality rate increased with increasing comorbidity and was 3% (1/37), 11% (3/27), 25% (10/40), and 27% (28/105) among those with Charlson Comorbidity Indices of 0, 1, 2, and 3+, respectively (p = 0.004). Conclusions: Although comorbidity is an important determinant of risk, most Achromobacter sp. BSI are of community-onset and one-fifth of cases occur in patients without significant underlying chronic co-morbidities. This study highlights the value of population-based methodologies to define the epidemiology of an infectious disease.
The Potential Role of Renal Denervation in the Management of Heart Failure

Sympathetic nervous system activation in patients with heart failure is one of the main pathophysiologic mechanisms associated with the worse outcomes. Pharmacotherapies targeting neurohormonal activation have been at the center of heart failure management. Despite the advancement of therapies and the available treatments, heart failure continues to have an overall poor prognosis. Renal denervation was originally developed to lower systemic blood pressure in patients with poorly controlled hypertension, by modulating sympathetic outflow. However, more recently, multiple studies have investigated the effect of renal denervation in heart failure patients with both preserved (HFpEF) and reduced ejection fractions (HFrEF). This paper provides an overview of the potential effect of renal denervation in altering the various pathophysiologic, sympathetically mediated pathways that contribute to heart failure, and reviews the literature that supports its future use in those patients.
The potential of gene therapies for spinal cord injury repair: a systematic review and meta-analysis of pre-clinical studies

Currently, there is no cure for traumatic spinal cord injury but one therapeutic approach showing promise is gene therapy. In this systematic review and meta-analysis, we aim to assess the efficacy of gene therapies in pre-clinical models of spinal cord injury and the risk of bias. In this meta-analysis, registered at PROSPERO (Registration ID: CRD42020185008), we identified relevant controlled in vivo studies published in English by searching the PubMed, Web of Science, and Embase databases. No restrictions of the year of publication were applied and the last literature search was conducted on August 3, 2020. We then conducted a random-effects meta-analysis using the restricted maximum likelihood estimator. A total of 71 studies met our inclusion criteria and were included in the systematic review. Our results showed that overall, gene therapies were associated with improvements in locomotor score (standardized mean difference [SMD]: 2.07, 95% confidence interval [CI]: 1.68–2.47, Tau2 = 2.13, I2 = 83.6%) and axonal regrowth (SMD: 2.78, 95% CI: 1.92–3.65, Tau2 = 4.13, I2 = 85.5%). There was significant asymmetry in the funnel plots of both outcome measures indicating the presence of publication bias. We used a modified CAMARADES (Collaborative Approach to Meta-Analysis and Review of Animal Data in Experimental Studies) checklist to assess the risk of bias, finding that the median score was 4 (IQR: 3–5). In particular, reports of allocation concealment and sample size calculations were lacking. In conclusion, gene therapies are showing promise as therapies for spinal cord injury repair, but there is no consensus on which gene or genes should be targeted.
Design, Characterization, and Liftoff of an Insect-Scale Soft Robotic Dragonfly Powered by Dielectric Elastomer Actuators

Dragonflies are agile and efficient flyers that use two pairs of wings for demonstrating exquisite aerial maneuvers. Compared to two-winged insects such as bees or flies, dragonflies leverage forewing and hindwing interactions for achieving higher efficiency and net lift. Here we develop the first at-scale dragonfly-like robot and investigate the influence of flapping-wing kinematics on net lift force production. Our 317 mg robot is driven by two independent dielectric elastomer actuators that flap four wings at 350 Hz. We extract the robot flapping-wing kinematics using a high-speed camera, and further measure the robot lift forces at different operating frequencies, voltage amplitudes, and phases between the forewings and hindwings. Our robot achieves a maximum lift-to-weight ratio of 1.49, and its net lift force increases by 19% when the forewings and hindwings flap in-phase compared to out-of-phase flapping. These at-scale experiments demonstrate that forewing–hindwing interaction can significantly influence lift force production and aerodynamic efficiency of flapping-wing robots with passive wing pitch designs. Our results could further enable future experiments to achieve feedback-controlled flights.
E-commerce packaging as an embedded resource in three network settings

ABSTRACT Packaging in e-commerce distribution receives attention from many perspectives, often in relation to sustainability and efficiency. This attention may concern the use of packaging material or the mismatch between parcel size and the products to be shipped. From a retailer’s or third-party logistics provider’s perspective, the attention includes costs related to packaging material and packing. Distribution has evolved over time and well-established settings of interconnected and embedded resources provide complexity in terms of opportunities for change. This paper investigates this embeddedness in terms of analysing e-commerce packaging as a resource interfacing with other resources such as products (including product packaging) in three network settings; the product development setting, the packing setting, and the sorting setting. The paper shows how the embeddedness of e-commerce packaging makes efforts to change a complicated matter due to the complex set of resource interdependencies. The study highlights why some network settings may be given more attention by firms involved in retail distribution, and others less. Furthermore, the study shows that although much attention is given to adjust the packing setting, it is important to understand the history of this setting and how adaptations of other settings, such as the product development and sorting setting, entail opportunities for change.
A Method for Broadband Polyimide Permittivity Measurement of Silicon Interposer Applied for High Speed Digital Microsystem

High-speed digital microsystems has emerged as one of the most important solutions for improving system performance, bandwidth, and power consumption. Based on mature micro-system processing technology, a material extraction approach for silicon interposer applied for high-speed digital microsystems was presented in order to obtain frequency-dependent precise material parameters. By combining microwave theory and mathematical model of iterative algorithm, the dielectric constant (Dk) and the dissipation factor (Df) of polyimide dielectric layer is acquired, which minimizes testing costs and streamlines testing process. The method is based on two-port transmission/reflection measurements. Vector Network Analyzer (VNA) is used to extract the scattering parameters with an extraction range of 1 MHz to 10 GHz. The algorithm is programmed using MATLAB. The observed Dk values at 2 GHz, 6 GHz, 8 GHz, and 10 GHz are, respectively, 3.22, 3.04, 2.96, 3.03, and 2.91, while the corresponding Df values are 0.021, 0.025, 0.026, 0.026, and 0.024. Finally, the complex permittivity derived is simulated and analyzed using Ansys HFSS. The results verify the validity of the theoretical method and proves that the values of the complex permittivity obtained by the method in this paper are reliable.
Editorial: Controlling psychometric measures for method effects by means of factor analysis

COPYRIGHT © 2022 DiStefano, Schweizer and Troche. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Editorial: Controlling psychometric measures for method e ects by means of factor analysis
Advanced Feature-Selection-Based Hybrid Ensemble Learning Algorithms for Network Intrusion Detection Systems

As cyber-attacks become remarkably sophisticated, effective Intrusion Detection Systems (IDSs) are needed to monitor computer resources and to provide alerts regarding unusual or suspicious behavior. Despite using several machine learning (ML) and data mining methods to achieve high effectiveness, these systems have not proven ideal. Current intrusion detection algorithms suffer from high dimensionality, redundancy, meaningless data, high error rate, false alarm rate, and false-negative rate. This paper proposes a novel Ensemble Learning (EL) algorithm-based network IDS model. The efficient feature selection is attained via a hybrid of Correlation Feature Selection coupled with Forest Panelized Attributes (CFS–FPA). The improved intrusion detection involves exploiting AdaBoosting and bagging ensemble learning algorithms to modify four classifiers: Support Vector Machine, Random Forest, Naïve Bayes, and K-Nearest Neighbor. These four enhanced classifiers have been applied first as AdaBoosting and then as bagging, using the aggregation technique through the voting average technique. To provide better benchmarking, both binary and multi-class classification forms are used to evaluate the model. The experimental results of applying the model to CICIDS2017 dataset achieved promising results of 99.7%accuracy, a 0.053 false-negative rate, and a 0.004 false alarm rate. This system will be effective for information technology-based organizations, as it is expected to provide a high level of symmetry between information security and detection of attacks and malicious intrusion.
Spatial and Source Multiplication Effects on the Area Ratio Reactivity Determination Method in a Strongly Heterogeneous Subcritical System

Abstract The area ratio method of Sjöstrand is generally considered one of the most reliable reactivity determination methods and thus is a major candidate for off-line calibration purposes in future accelerator-driven systems for high-level waste incineration. In this work, the Sjöstrand area ratio method has been evaluated experimentally under thorough conditions in the strongly heterogeneous subcritical facility YALINA-Booster. Both strengths and weaknesses of the method have been identified. Most surprisingly, it has been found that the area ratio reactivity estimates may differ a factor of 2 depending on detector position. It is also shown that this strong spatial dependence can be explained based on a simple two-region point-kinetics model and corrected by means of correction factors obtained through Monte Carlo simulations. A new Monte Carlo correction method is proposed that includes, at the same time, the spatial disturbance and the effective delayed neutron fraction. In that way, the value of the effective multiplication factor is obtained from the measured dollar reactivity without the need of calculating the effective delayed neutron fraction explicitly, and thereby, the delayed neutron transport is performed only once. Further, it has been found that the Sjöstrand area ratio method is not sensitive to perturbations of the source multiplication factor.
Shape optimizations for body-assisted light-matter interactions

We implement a shape optimization algorithm for body-assisted light–matter interactions described by the formalism of macroscopic quantum electrodynamics. The approach uses the level-set method to represent and incrementally evolve dielectric environments. Utilizing ﬁnite-diﬀerence time-domain techniques we demonstrate the ability of the algorithm by optimizing the rate of resonance energy transfer in two dimensions. The resulting geometries enhance the transfer rate by several orders of magnitude.
Impact of Background Traffic on the BBR and CUBIC Variants of the TCP Protocol

This letter analyzes the performance of the TCP CUBIC and TCP BBR protocols in the presence of background traffic. The analysis is performed via emulation using actual TCP implementations and considering high capacity end-to-end data connections and different connection durations (e.g., mouse and elephant flows). The results indicate that the BBR protocol produces higher throughput and fairness than the CUBIC protocol.
A multiple dominance analysis of sharing coordination constructions using tree adjoining grammar

This thesis examines the syntax of sharing coordination constructions, in which a single phonologically overt element at the periphery of one conjunct is interpreted to belong syntactically and semantically to both conjuncts. I argue for a multiple dominance analysis of these constructions, against ellipsis and literal movement approaches, which I formalize in a lexicalized tree adjoining grammar (LTAG) framework. This analysis extends the empirical domain of previous TAG research beyond shared arguments to provide an account of shared modifiers, lexical items and derivationally non-local sharing. Finally, I define a linearization algorithm that linearizes the terminals of multiple dominance structures and produces the novel result of deriving the peripherality conditions on both left and right sharing constructions.
Rheological Controls on Magma Reservoir Failure in a Thermo‐Viscoelastic Crust

As volcanoes undergo unrest, understanding the conditions and timescales required for magma reservoir failure, and the links to geodetic observations, are critical when evaluating the potential for magma migration to the surface and eruption. Inferring the dynamics of a pressurized magmatic system from episodes of surface deformation is heavily reliant on the assumed crustal rheology, typically represented by an elastic medium. Here, we use Finite Element models to identify the rheological response to reservoir pressurization within a temperature‐dependent Standard Linear Solid viscoelastic (“thermo‐viscoelastic”) domain. We assess the mechanical stability of a deforming reservoir by evaluating the overpressures required to initiate brittle failure along the reservoir wall, and the sensitivity to key parameters. Reservoir inflation facilitates compression of the ductile wall rock, due to the non‐uniform crustal viscosity, impacting the temporal evolution of the induced tensile stress. Thermo‐viscoelasticity enables a deforming reservoir to sustain greater overpressures prior to failure, compared to elastic analyses. High‐temperature (e.g., mafic) reservoirs fail at lower overpressures compared to low‐temperature (e.g., felsic) reservoirs, producing smaller coincident displacements at the ground surface. The impact of thermo‐viscoelasticity on reservoir failure is significant across a wide range of overpressure loading rates. By resisting mechanical failure on the reservoir wall, thermo‐viscoelasticity impacts dyke nucleation and formation of shear fractures. Numerical models may need to incorporate additional processes that act to promote failure, such as regional stresses (e.g., topographic and tectonic), external triggers (e.g., earthquake stress drops), or pre‐existing weaknesses along the reservoir wall.
Precise Deposition of Carbon Nanotube Bundles by Inkjet-Printing on a CMOS-Compatible Platform

Carbon nanotubes (CNTs) are ultimately small structures, attractive for future nanoelectronics. CNT-bundles on Si nanostructures can offer an alternative pathway to build hybrid CMOS-compatible devices. To develop a simple method of using such CNT-bundles as transistor channels, we fabricated semiconductor single-walled CNT field-effect transistors using inkjet printing on a CMOS-compatible platform. We investigated a method of producing stable CNT solutions without surfactants, allowing for CNT debundling and dispersion. An inkjet-printing system disperses CNT-networks with ultimately low density (down to discrete CNT-bundles) in Al source-drain gaps of transistors. Despite the small number of networks and random positions, such CNT-bundles provide paths to the flow current. For enhanced controllability, we also demonstrate the manipulation of CNT-networks using an AFM technique.