bluuebunny/crossref_metadata_2025 huggingface dataset:
Enviados directo a Londres: objetos colombianos en la Colección de Botánica Económica del Real Jardín Botánico de Kew
Authors: Echeverri Sánchez Hernando Alberto , Sánchez-Garzón Natalí Ximena , Nesbitt Mark , Ávila Fabio , Diazgranados Mauricio
Published: March 2022

Este artículo es el resultado de una valoración de los objetos colombianos en la Colección de Botánica Económica del Real Jardín Botánico de Kew. Hace parte del proyecto ColPlantA, encargado de documentar la colección colombiana y de producir un portal de búsqueda sobre la flora colombiana. Para este artículo se hizo un análisis general de la colección colombiana, que resultó en una descripción de los géneros y especies representativas, los usos de la flora nativa colombiana y sus coleccionistas. Además, se describen algunos objetos que reflejan los intereses científicos y económicos de Gran Bretaña en Colombia. Esta colección es una ventana a las dinámicas entre una institución académica imperial como Kew con regiones como Colombia, de la periferia global de aquel entonces.
La restauración del exconvento de Tzintzuntzan. Un modelo de participación comunitaria
Authors: Martínez Aguilar José Manuel , Rodríguez C´ázarez Mirna
Published: March 2022

En enero de 2004 inició la primera etapa de la restauración del ex convento franciscano de Tzintzuntzan, México, con la participación directa de la comunidad local, a través de la Escuela Taller de Tzintzuntzan y el apoyo de instituciones de gobierno y privadas. Debido a la importancia histórica del edificio, las condiciones en que se encontraba, sus dimensiones, pero sobre todo la manera en cómo se involucró a la comunidad, la obra puede considerarse una de las más importantes que se hayan realizado en Michoacán y un modelo en lo que respecta a la intervención y cuidado del patrimonio edificado en México y América Latina. La restauración se desarrolló en varias etapas y duró casi ocho años, pero concluyó de manera exitosa, abriéndose el edificio al público en 2012 con el nombre de Centro Cultural Comunitario Tzintzuntzan.
Tensiones vecinales por el barrio patrimonial: la construcción de imaginarios sobre zonas típicas en Santiago de Chile. Un estudio de caso
Authors: Yáñez Garrido Vicente Ernesto
Published: March 2022

Durante las últimas décadas, se ha desarrollado la tendencia en la sociedad civil chilena de recurrir a la declaración patrimonial de barrios como forma de preservar sectores residenciales expuestos a procesos de renovación urbana, en el contexto de un urbanismo neoliberalizado. Bajo ese escenario, en el presente artículo expongo los resultados de una investigación etnográfica respecto al caso de un sector residencial de clase media alta donde se constituyeron dos organizaciones vecinales que disputaron durante 2017 y 2018 la patrimonialización de su vecindario, unos a favor y otros en contra. Sobre la base de dicha disputa, examino el modo en que se configuran imaginarios divergentes respecto de los barrios patrimoniales, los cuales invitan a reflexionar sobre las diversas formas en que la ciudadanía construye representaciones del patrimonio, particularmente cuando esta se cruza con la dimensión residencial
Effect of Different Solder Volumes on the Laser Soldering Process: Numerical and Experimental Investigation
Authors: Bachok Zuraihana , Abas Mohamad Aizat , Nazarudin Muhammad Zaim Hanif , Zahiri Saifulmajdy A. , Mohd Sharif Mohamad Fikri , Che Ani Fakhrozi
Published: March 2022

Laser soldering is becoming more popular for soldering pin through-hole (PTH) components onto printed circuit boards (PCBs). Solder volume influences soldering joint reliability. However, it is difficult to accurately measure the effect of solder volume during the laser soldering process. The finite volume method (FVM) is used to simulate the molten solder flow in laser soldering to connect the through-hole capacitor onto the PCB in ansysfluent software. The simulation results reveal the effects of different SAC305 solder volumes on joining quality in terms of fillet shape formation, pressure, and velocity. The preferred solder volume is 1.517 mm3 with a filling time of 1.7 s, a temperature of 642 K, a hole diameter of 1.0 mm, a lead diameter of 0.5 mm and a PCB thickness of 1.20 mm, produces a fillet shape similar to a real sample of PTH laser soldering joint from the industry. This ideal volume was chosen with a suitable pressure and velocity to create a nice concave fillet shape and minimize voids during soldering. The pressure and velocity increase when the solder volume increases causing solidified solder to melt. The discrepancy between numerical and experimental values of fillet height is comparable, which inferred that the numerical model was well-validated. The good consistency between both results proves that the finite volume model will effectively predict the optimum solder volume. This opens up new opportunities for the optimization of the laser soldering parameters in the application of electronic manufacturing.
Social–Ecological Considerations in Sustaining Comprehensive School Physical Activity Programs: A Follow-Up Study
Authors: Nam Kahyun , Kulinna Pamela H. , Mulhearn Shannon C. , Yu Hyeonho , Griffo Janelle M. , Mason Aaron J.
Published: March 2022

Purpose: The purpose of this study was to investigate the perspective of school personnel regarding the impact of social–ecological factors and to identify salient ways to support school personnel in sustaining Comprehensive School Physical Activity Programs. Methods: In this mixed-methods longitudinal study, stakeholders were surveyed at two points in time (n = 67) and interviewed in semistructured interviews (n = 41) using card sorting to understand the influence of social–ecological factors on Comprehensive School Physical Activity Programs sustainability. Results: Across time, the perceived influence of social–ecological levels varied considerably: individual, t(78.86) = −4.22, p < .001, d = 0.52, interpersonal, t(88.20) = −2.32, p = .023, d = 0.09, organizational, t(80.56) = −2.38, p = .02, d = 0.29, and the community factor, t(83.24) = −3.05, p = .003, d = 0.30. Stakeholders rated ecological levels from greatest to least influential as individual, organizational, interpersonal, community, and policy. Themes within levels provided a deeper understanding of these influences. Conclusion: To successfully sustain Comprehensive School Physical Activity Programs in schools, balanced support from all social–ecological levels may be needed.
Killing the golden goose for STEM
Authors: Meléndez-Ackerman Elvia , Colón Jorge L.
Published: March 2022

In 2016, the US Congress enacted the Puerto Rico Oversight, Management, and Economic Stability Act (PROMESA), which led to a federally appointed Financial Oversight and Management Board (FOMB) to oversee restructuring of the island’s $74 billion debt and achieve sustainable budgets. Many economists argue that even debt adjustment, which was approved in January, will not be enough to put Puerto Rico on a road to recovery. Unprecedented budget cuts by FOMB have already reduced funding from Puerto Rico’s state government for the University of Puerto Rico (UPR). UPR is the island’s premier institute of higher learning in science, technology, engineering, and mathematics (STEM). State funding for UPR must be restored if Puerto Rico is to stably recover from years of economic despair.
Environmental Potential for Microbial 1,4-Dioxane Degradation Is Sparse despite Mobile Elements Playing a Role in Trait Distribution
Authors: Goff Kira L. , Hug Laura A.
Published: March 2022

New regulatory limits for 1,4-dioxane in groundwater have been proposed or adopted in many countries, including the United States and Canada, generating a direct need for remediation options as well as better tools for assessing the fate of dioxane in an environment. A comprehensive suite of biomarkers associated with dioxane degradation was identified and then leveraged to examine the global potential for dioxane degradation in natural and engineered environments.
Identification of Novel 5′ and 3′ Translation Enhancers in Umbravirus-Like Coat Protein-Deficient RNA Replicons
Authors: Liu Jingyuan , Simon Anne E.
Published: March 2022

Umbra-like associated RNAs (ulaRNAs) are a recently discovered type of subviral RNA that use their encoded RNA-dependent RNA polymerase for replication but do not encode any coat proteins, movement proteins, or silencing suppressors yet can be found in plants in the absence of any discernible helper virus. We report the first analysis of their translation using class 2 ulaRNA citrus yellow vein-associated virus (CYVaV).
Bioinformatic Mining and Structure-Activity Profiling of Baeyer-Villiger Monooxygenases from Mycobacterium tuberculosis
Authors: Tomas Nicolas , Leonelli Dimitri , Campoy Martin , Marthey Sylvain , Le Nguyen-Hung , Rengel David , Martin Véronique , Pál Adrian , Korduláková Jana , Eynard Nathalie , Guillet Valérie , Mourey Lionel , Daffé Mamadou , Lemassu Anne , André Gwenaëlle , Marrakchi Hedia
Published: March 2022

Tuberculosis (TB), caused by
Mycobacterium tuberculosis
, is one of the leading causes of death worldwide. The rise in drug resistance highlights the urgent need for innovation in anti-TB drug development.
Pathogen Stimulation of Interleukin-8 from Human Vaginal Epithelial Cells through CD40
Authors: Schlievert Patrick M. , Kilgore Samuel H. , Benavides Andrea , Klingelhutz Aloysius J.
Published: March 2022

Most bacterial and fungal pathogens cause disease across mucosal, and to a lesser extent, skin barriers with the help of induced chemokines from epithelial cells. In this study, we showed that potential vaginal pathogens
Staphylococcus aureus
, group A and B streptococci, some
Enterococcus faecalis
strains,
Escherichia coli
, and
Candida albicans
use the immune costimulatory molecule CD40 to induce the chemokine interleukin-8 production.
The Performance of Nine Commercial Serological Screening Assays for the Diagnosis of Lyme Borreliosis: a Multicenter Modified Two-Gate Design Study
Authors: Hoeve-Bakker B. J. A. , Jonker Mark , Brandenburg Afke H. , den Reijer P. Martijn , Stelma Foekje F. , van Dam Alje P. , van Gorkom Tamara , Kerkhof Karen , Thijsen Steven F.T. , Kremer Kristin
Published: March 2022

Serology plays an important role in the diagnosis of Lyme borreliosis. Guidelines prescribe a two-tier testing algorithm in which a highly sensitive screening assay is used for screening and reactive sera are retested with an immunoblot to reduce false positivity rates.
Melt surges, flow differentiation, and remobilization of crystal-rich mushes in response to unloading: Observations from Kīlauea Iki lava lake, Hawaii
Authors: Helz Rosalind T.
Published: March 2022

Field and laboratory studies of the 1959 Kīlauea Iki lava lake have provided insight into differentiation processes in mafic magma chambers. This paper explores how partially molten basaltic mushes responded to unloading as a consequence of drilling. Most holes drilled from 1967 to 1979 terminated in a melt-rich internal differentiate with a sharp crust-melt interface. These interfaces were not stable, so the boreholes were backfilled by melt-rich (<5% crystal) ooze. This process, with melt ascent rates of 1.3–4.2 m/s, occurred within minutes of intersecting the bodies, mimicking volcanic eruptions, albeit on a small scale.

One borehole (KI79-1), which did not encounter such a discontinuity, was backfilled over a period of 16 days by upward flow of crystal-rich mushes rather than melt-rich ooze. The first interval of ooze recovered had undergone extensive internal differentiation. Its most conspicuous feature was production of melt-rich layers by lateral migration of interstitial melt from the wallrock into the rising crystal-rich mush. In addition, two smaller-scale processes occurred within the rising mush: segregation of melt into discrete blebs within the rising mush column and aggregation of groundmass crystals into crystal-rich clumps formed adjacent to coarser olivine crystals. The upper parts of the ooze are enriched in melt relative to deeper samples, which suggests that the melt blebs rose relative to their olivine-rich matrix. Similar melt blebs and crystal-rich clumps are observed in naturally occurring diapiric bodies within the lava lake. These processes appear to be intrinsic to the upwelling of narrow cylindrical mush bodies whether constrained within a borehole (like the oozes) or unconstrained (as were the diapirs in the lava lake).

The most striking behavior observed during repeated reentry of KI79-1 was a sharp change in rheology during the second and third re-entries of the borehole. The shift in behavior observed was that the oozes rose up the borehole, with ascent rates of 1.0–1.7 m/s, which are comparable to the rates of the crystal-poor oozes from melt-rich internal differentiates. These oozes contain more melt than the original core at equivalent depths, presumably because melt moved relative to crystals down the pressure gradient created by the open borehole. Groundmass textures in these inflated mushes show erosion of crystal outlines, especially of grain-to-grain contacts between different phases, so that the tenuous crystalline network observed in the original core samples was replaced by rounded crystals in continuous melt at crystallinities of 55–65 vol%. The transition from stable coherent mush to inflatable mush occurred at 25–28 vol% melt. This behavior appears similar to certain types of reactive transport observed in other studies.
Charge Transport in Nonstoichiometric SiOx Obtained by Treatment of Thermal SiO2 in Hydrogen Plasma of Electronic-Cyclotron Resonance
Authors: Iskhakzay R. M. Kh. , Kruchinin V. N. , Aliev V. Sh. , Gritsenko V. A. , Dementieva E. V. , Zamoryanskaya M. V.
Published: March 2022

Currently, a new generation of high-speed, information-intensive resistive memory based on nonstoichiometric dielectrics is being developed. The electron structure of nonstoichiometric silicon oxide SiOx is set by the value of parameter x. It is found that the treatment of thermal SiO2 in hydrogen plasma electron cyclotron resonance leads to the enrichment of silicon oxide with excess silicon, which in turn leads to the appearance of electron and hole traps in SiOx. SiOx conductivity is bipolar: electrons are injected from negatively biased silicon and holes are injected from positively biased silicon. Cathodoluminescence (CL) experiments confirm the assumption that the traps in SiOx are due to the excess silicon. p++-Si(100)/SiOx/Ni memristor metal-dielectric-semiconductor (MDS) structures are fabricated based on the developed procedure for the preparation of nonstoichiometric oxide in hydrogen plasma of electron cyclotron resonance. Such structures have the properties of resistive switching of SiOx that do not require a forming operation.
Cooled radiofrequency ablation for pain related to Perthes’ disease: a novel application
Authors: Tee Qiao Xin , Nambiar Mithun , Mahendru Gautam , Singh Parminder
Published: March 2022

Perthes’ disease is a rare paediatric condition involving idiopathic avascular necrosis of the femoral head, leading to degenerative hip joint disease. While joint replacement surgery is considered as the definitive surgical choice of managing degenerative hip disease, alternative methods of pain relief are available, especially for young patients, to defer joint replacement to a later date. One method of reducing pain for 18–24 months is cooled radiofrequency ablation (CRFA). CRFA has been gaining recognition as an effective treatment option for chronic musculoskeletal-related pain in multiple joints. This is the first case report describing the successful use of CRFA in the non-surgical management of Perthes’ disease-related osteoarthritic hip pain in a man in his 40s. CRFA treatment led to a reported subjective improvement in pain of 60%–70%, with a documented objective improvement in the Oxford Hip Score from 18 to 40 within 6 weeks of the CRFA procedure.
Vocal brain development in infants of mothers with serious mental illness (CAPRI-Voc): study protocol
Authors: Stibbs-Eaton Lucy , Hodgson Catherine , Kolade Adekeye , Crowell Jennifer , Gemignani Jessica , Hope Holly , Pierce Matthias , Elmadih Alya , Zhao Chen , Downey Darragh , Elliott Rebecca , Abel Kathryn M
Published: March 2022

Introduction

Improving the lives of children and adolescents with parental mental illness (CAPRI) remains an urgent political and public health concern for the UK and European Union. Recurrent parental mental illness is believed to lead to fractures in the family, academic and social lives of these children, yet interventions are poorly targeted and non-specific. Part of an interdisciplinary programme of work (the CAPRI Programme; grant number: 682741), CAPRI-Voc aims to achieve two goals: first, to test the feasibility of our longitudinal imaging paradigm in mother–infant pairs where the mother has a diagnosis of severe mental illness. Second, to compare development of vocal processing in these infants with infants in the general population.

Methods and analysis

Recruitment of 100 infants of mothers with mental illness, alongside 50 infants of healthy mothers. Both cohorts of infants will undergo functional near infrared spectroscopy (fNIRS) brain imaging at three time points: 9, 12 and 18 months to explore differences between cohorts in their neural responses to vocal stimuli in our language paradigm. Mothers will complete an interview and psychological questionnaires. We shall also complete an infant developmental battery and mother–child interaction play session. Data on recruitment, retention and dropout will be recorded.

Ethics and dissemination

It will be made clear that fNIRS is a safe, non-invasive technology widely used in infant clinical and psychological research. We shall reassure mothers that no definitive causal link exists between maternal mental illness and language development in infants, and that individual data will only exist as part of the wider dataset. As the study includes both children and vulnerable adults, all research staff will complete National Health Service (NHS) Safeguarding level 3 training. Dissemination will be via direct feedback to stakeholders, patient and advisory groups, and through presentations at conferences, journal publications and university/NHS trust communications. The study was approved through North West–Greater Manchester West Research Ethics Committee (17/NW/0074) and Health Research Authority (212715).
Dilation versus laser resection in subglottic stenosis: protocol for a prospective international multicentre randomised controlled trial (AERATE trial)
Authors: Soumagne Thibaud , Guibert Nicolas , Atallah Ihab , Lacasse Yves , Dutau Hervé , Fortin Marc
Published: March 2022

Introduction

Subglottic stenosis (SGS) is a rare condition that results from progressive narrowing of the upper airways. Outcomes and treatment options depend on the benign or complex nature of the stenosis. Treatment options for SGS include surgery and endoscopic techniques. The main endoscopic techniques used are dilation and laser resection. Observational and retrospective studies suggest that endoscopic laser resection may be more effective than dilation. We, therefore, aimed to compare the effectiveness of dilation and laser resection in preventing recurrence of SGS.

Methods and analysis

AERATE (dilAtion vs laser Endoscopic Resection in subglottic trAcheal sTEnosis) is a multicentre, investigator-initiated, randomised controlled trial, comparing endoscopic dilation to endoscopic laser resection for simple benign SGS (less than 1 cm long without underlying cartilaginous damage) referred for endoscopic treatment (first treatment or recurrence). The study will be conducted in three centres in France and one in Canada with other centres from France and Canada expected to join. The primary outcome is the recurrence rate of stenosis at 2 years. Recurrence is defined as having a new onset of symptoms along with a stenosis of more than 40% (confirmed by bronchoscopy) requiring a new procedure. A sample size of 100 patients is calculated for the primary endpoint assuming a 10% recurrence rate in the laser resection group and 33% in the dilation group with a statistical significance level of 5%, a power of 80%.

Ethics and dissemination

This study is approved by local and national ethics committees as required. Results will be published, and trial data will be made available.

Trial registration number

NCT04719845.
Decision regret regarding treatments among women with early-stage breast cancer: a systematic review protocol
Authors: Liu Jing , Hunter Sharyn , Zhu Jiemin , Lee Regina Lai-Tong , Chan Sally Wai-Chi
Published: March 2022

Introduction

Women with early-stage breast cancer (EBC) are commonly required to make treatment decisions. Decision regret regarding treatments is an adverse outcome that negatively affects women’s psychological well-being and quality of life. A systematic review will be conducted to synthesise evidence about decision regret among women regarding treatments for EBC. The study will focus on levels of decision regret, what is regretted, and the factors associated with decision regret.

Methods and analysis

A systematic review will be conducted following the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols 2015 checklist. Electronic databases, including CINAHL Complete, Embase, PubMed, Medline and Web of Science, will be searched for relevant articles published from 2000 to 2021. The reference lists of eligible studies will also be manually searched. All types of quantitative, qualitative and mixed-methods studies that report on decision regret regarding treatments among women with EBC will be included. The primary outcome of this review will be women’s levels of decision regret regarding breast cancer treatments. The secondary outcomes will include the content of their regrets, and the factors contributing to decision regret. The methodological quality of the studies will be assessed using the Joanna Briggs Institute appraisal tools. Meta-analysis and thematic synthesis approaches will be used to synthesise quantitative and qualitative data, respectively. A convergent parallel approach will be used to integrate quantitative and qualitative findings.

Ethics and dissemination

Ethical approval is not required for this systematic review. The findings of this work will be disseminated at international conferences and peer-reviewed journals. The findings of this systematic review will inform the development of decision interventions to improve the decision outcomes of breast cancer treatments.

PROSPERO registration number

CRD42021260041.
Association of ectatic non-infarct-related artery with 1-month stent thrombosis in patients with ST elevation myocardial infarction
Authors: Zeren Gönül , Avci İlhan İlker , Sungur Mustafa Azmi , Şimşek Barış , Sungur Aylin , Yılmaz Mehmet Fatih , Can Fatma , Gurkan Ufuk , Karabay Can Yücel
Published: March 2022

Background

Ectatic infarct-related artery (IRA) has been shown to be associated with higher thrombus burden, no-reflow, stent thrombosis (ST) and major adverse cardiovascular events in patients with ST-elevation myocardial infarction (STEMI). The effect of ectatic non-IRA on ST without ectatic IRA is not known. We aimed to assess the effect of ectatic non-IRA presence on ST within 1 month after primary percutaneous intervention (pPCI) in patients with STEMI.

Methods

A total of 1541 patients with a diagnosis of STEMI and underwent pPCI between 2015 and 2020 were retrospectively included in the study. Patients with and without 1 month ST were compared. Penalised logistic regression method was used to assess the association between ST and candidate predictors due to the risk of overfitting.

Results

Median age of the study group was 56.5 (48.7 to 67.2) years. The Synergy between PCI with Taxus and Cardiac Surgery (SYNTAX) score, ectatic non-IRA presence and use of tirofiban were significantly higher in the ST group (18.2±9.9 vs 15.1±9.9, p=0.03; 25% vs 7.2%, p<0.001; 54.2% vs 30.5%, p<0.001; respectively). Significantly higher thrombus aspiration (14.3% vs 6.7%, p=0.03) and lower stent implantation (67.7% vs 84%, p<0.001) rates were observed in ectatic IRA group compared with ectatic non-IRA group. In multivariable analysis, ectatic non-IRA presence was independently associated with 1-month ST (OR 4.01, 95% CI 1.86 to 8.63, p=0.01).

Conclusion

Ectatic non-IRA presence without ectatic IRA in patients with STEMI increases the risk of ST within the first month of pPCI.
Greedy and Local Search Heuristics to Build Area-Optimal Polygons
Authors: Crombez Loïc , da Fonseca Guilherme D. , Gerard Yan
Published: March 2022

In this article, we present our heuristic solutions to the problems of finding the maximum and minimum area polygons with a given set of vertices. Our solutions are based mostly on two simple algorithmic paradigms: greedy and local search. The greedy heuristic starts with a simple polygon and adds vertices one by one, according to a weight function. A crucial ingredient to obtain good solutions is the choice of an appropriate weight function that avoids long edges, since long edges impede the insertion of too many different edges later on. The local search part consists of moving consecutive vertices to another location in the polygonal chain. We also discuss the different implementation techniques that are necessary to reduce the running time.
Network Design for
s
-
t
Effective Resistance
Authors: Chan Pak Hay , Lau Lap Chi , Schild Aaron , Wong Sam Chiu-Wai , Zhou Hong
Published: March 2022

We consider a new problem of designing a network with small
s
-
t
effective resistance. In this problem, we are given an undirected graph
G
=
(V,E)
, two designated vertices
s,t ∈ V
, and a budget
k
. The goal is to choose a subgraph of
G
with at most
k
edges to minimize the
s
-
t
effective resistance. This problem is an interpolation between the shortest path problem and the minimum cost flow problem and has applications in electrical network design.

We present several algorithmic and hardness results for this problem and its variants. On the hardness side, we show that the problem is NP-hard, and the weighted version is hard to approximate within a factor smaller than two assuming the small-set expansion conjecture. On the algorithmic side, we analyze a convex programming relaxation of the problem and design a constant factor approximation algorithm. The key of the rounding algorithm is a randomized path-rounding procedure based on the optimality conditions and a flow decomposition of the fractional solution. We also use dynamic programming to obtain a fully polynomial time approximation scheme when the input graph is a series-parallel graph, with better approximation ratio than the integrality gap of the convex program for these graphs.
Socially Enhanced Situation Awareness from Microblogs Using Artificial Intelligence: A Survey
Authors: Lamsal Rabindra , Harwood Aaron , Read Maria Rodriguez
Published: March 2022

The rise of social media platforms provides an unbounded, infinitely rich source of aggregate knowledge of the world around us, both historic and real-time, from a human perspective. The greatest challenge we face is how to process and understand this raw and unstructured data, go beyond individual observations and see the “big picture”—the domain of Situation Awareness. We provide an extensive survey of Artificial Intelligence research, focusing on microblog social media data with applications to Situation Awareness, that gives the seminal work and state-of-the-art approaches across six thematic areas:
Crime
,
Disasters
,
Finance
,
Physical Environment
,
Politics
, and
Health and Population
. We provide a novel, unified methodological perspective, identify key results and challenges, and present ongoing research directions.
(Compress and Restore)
N
: A Robust Defense Against Adversarial Attacks on Image Classification
Authors: Ferrari Claudio , Becattini Federico , Galteri Leonardo , Bimbo Alberto Del
Published: March 2022

Modern image classification approaches often rely on deep neural networks, which have shown pronounced weakness to adversarial examples: images corrupted with specifically designed yet imperceptible noise that causes the network to misclassify. In this article, we propose a conceptually simple yet robust solution to tackle adversarial attacks on image classification. Our defense works by first applying a JPEG compression with a random quality factor; compression artifacts are subsequently removed by means of a generative model Artifact Restoration GAN. The process can be iterated ensuring the image is not degraded and hence the classification not compromised. We train different AR-GANs for different compression factors, so that we can change its parameters dynamically at each iteration depending on the current compression, making the gradient approximation difficult. We experiment with our defense against three white-box and two black-box attacks, with a particular focus on the state-of-the-art BPDA attack. Our method does not require any adversarial training, and is independent of both the classifier and the attack. Experiments demonstrate that dynamically changing the AR-GAN parameters is of fundamental importance to obtain significant robustness.
Report on the 1st simulation for information retrieval workshop (Sim4IR 2021) at SIGIR 2021
Authors: Balog Krisztian , Maxwell David , Thomas Paul , Zhang Shuo
Published: March 2022

Simulation is used as a low-cost and repeatable means of experimentation. As
Information Retrieval (IR)
researchers, we are no strangers to the idea of using simulation within our own field---such as the traditional means of IR system evaluation as manifested through the
Cranfield paradigm.
While simulation has been used in other areas of IR research (such as the study of user behaviours), we argue that the potential for using simulation has been recognised by relatively few IR researchers so far.

To this end, the
Sim4IR
workshop was held online on July 15
th
, 2021 in conjunction with ACM SIGIR 2021. Building on past efforts, the goal of the workshop was to create a forum for researchers and practitioners to promote methodology and development of more widespread use of simulation for IR evaluation. Around 80 participants took part over two sessions. A total of two keynotes, three original paper presentations, and eight
'encore talks'
were presented. The main conclusions from the resultant discussion were that simulation has the potential to offer solutions to the limitations of existing evaluation methodologies, but there is more research needed toward developing realistic user simulators; and the development and sharing of simulators, in the form of toolkits and online services, is critical for successful uptake.

Date
: 15 July, 2021.

Website
: https://sim4ir.org.
Improved Serotonin Measurement with Fast-Scan Cyclic Voltammetry: Mitigating Fouling by SSRIs
Authors: Stucky Chase , Johnson Michael A.
Published: March 2022

Selective serotonin reuptake inhibitors (SSRIs) have been used for decades to treat disorders linked to serotonin dysregulation in the brain. Moreover, SSRIs are often used in studies aimed at measuring serotonin with fast-scan cyclic voltammetry (FSCV) in living tissues. Here, we show that three different SSRIs—fluoxetine, escitalopram, and sertraline—significantly diminish the faradaic oxidation current of serotonin when employing the commonly used Jackson waveform. Coating carbon-fiber microelectrodes (CFMs) with Nafion resulted in further degradation of peak current, increased response times, and decreased background charging currents compared to bare CFMs. To decrease fouling, we employed a recently published extended serotonin waveform, which scans to a maximum positive potential of +1.3 V, rather than +1.0 V used in the Jackson waveform. Use of this waveform with bare CFMs alleviated the decrease in faradaic current, indicating decreased electrode fouling. Collectively, our results suggest that fouling considerations are important when designing FSCV experiments that employ SSRIs and that they can be overcome by using the appropriate waveform.
Analysis of Noise in Current Mirror Circuits Based on CNTFET and MOSFET
Authors: Marani R. , Perri A. G.
Published: March 2022

In this paper we present a comparative analysis of noise performance of Carbon Nanotube Field Effect Transistors (CNTFETs) and MOSFET, through the design of two circuits: a basic current mirror and self-bias current mirror, each time with different current values. For this aim we use a semi-empirical compact CNTFET model, already proposed by us, including noise source contributions, and the BSIM4 model for MOS device. Then we analyze and discuss the spectral density of output noise current, comparing the two considered technology. The software used is Advanced Design System (ADS), compatible with the Verilog A programming language.
Contact Effect On Twisted Graphene Based Schottky Transistor
Authors: Ahmadi Ramin , Ahmadi Mohammad Taghi
Published: March 2022

Owing to the exceptional electrical properties of different one dimensional (1D) classifications of graphene structure such as graphene nanoribbon (GNR) and twisted graphene (TWG) led to a revolution in nanoelectronic researche and applications. Thus, these materials have been extensively explored in nanoelectronics science and materials. This paper is focused on GNR and TWG junction as metal-semiconductor-metal (MSM) in the form of a transistor. The wave vectors of TWG and GNR based on the geometrical effects are discussed. By considering 1D potential barrier at the junction of TWG as a semiconducting region and GNR as a metallic region, the transmission probability is calculated. Then, the I–V characteristics of GNR-TWG Schottky transistor based on quantum tunneling effect arepresented and discussed, as well. The performance of GNR-TWG Schottky transistor under variation of gate-source voltage, channel length, number of twists, width of GNR, and temperature are investigated. It is concluded that increment in number of twists and width of GNR lead to increasing the drain current and threshold voltage. Finally, comparison study with graphene nanoscroll (GNS) Schottky transistor, trilayer graphene nanoribbon (TGNR) Schottky transistor, and reported experimental data are performed and results represent that GNR-TWG Schottky transistor has larger drain current than these works.
Real-Time Modulation of Physical Training Intensity Based on Wavelet Recursive Fuzzy Neural Networks
Authors: Fang Wenzhou , Wang Lili , Liao Xinxin , Tan Miao
Published: March 2022

In this study, a wavelet recurrent fuzzy neural network is used to conduct in-depth research and analysis on the real-time regulation of physical training intensity. Firstly, an inter-process control technique is proposed to solve the problem of incomplete control flow graph construction caused by the inability to effectively collect all program control flow information in the process of static analysis, in preparation for the research of fuzzy testing technique. Next, a wavelet recursive fuzzy neural network-guided fuzzy testing technique is proposed to solve the problem of fuzzy tests falling into invalid variation due to the lack of directionality in the fuzzy testing process. Each neuron in the feedforward network is divided into different groups according to the order of receiving information. Each group can be regarded as a neural layer. The neurons in each layer receive the output of the neurons in the previous layer and output to the neurons in the next layer. The empirical data show that injury-preventive fitness training can effectively improve all physical qualities in the first phase of preparation and can effectively maintain the physical state and effectively contribute to their abilities during the competition period, and its injury-preventive fitness training interventions were verified by statistical analysis to have a dangerous main effect on their pre and post-test performance. Therefore, it is still not possible to determine its correlation with the coordination and improvement of the athletes’ physical fitness, and the integration of the basic physical training and rehabilitation physical training systems, making this theory a new special training theory.
Magnetic Resonance Image in Monitor and Diagnosis of Patients with Neuromyelitis Optica
Authors: Lu Shujuan , Wang Dongming , Zhang Fengxian , Liu Meilan
Published: March 2022

This study was aimed to investigate the craniocerebral magnetic resonance imaging (MRI) measurement and clinical characteristics of patients with neuromyelitis optica (NMO) and multiple sclerosis (MS). 50 patients with NMO (NMO group) and 50 patients with MS (MS group) were studied. The clinical manifestations, brain injury morphology, MRI signal characteristics, brain distribution characteristics, and related laboratory tests (serum aquaporin 4 [AQP4] antibody) were statistically analyzed. The results showed that the analysis of clinical manifestations of patients revealed that optic neuritis (37 cases) was the most common disease in NMO patients, and myelitis (16 cases) was more common in MS patients than NMO patients. There were significant differences in gender ratio, abnormal expression of brain MR1, positive serum AQP4‐IgG, and other immune diseases and symptoms between the two groups (P < 0.05). When the lesions measured by MRI were located in the white matter area of the cerebral hemisphere, the image showed blurred edges and a relatively symmetrical distribution. When the lesions measured by MRI were located around the medulla oblongata, the lesions mainly involved the central gray matter and white matter of the spinal cord, with patchy and line‐like long T1 and long T2 signals. Moreover, in the late stage of recurrence of spinal cord disease, severe spinal cord atrophy may occur. In conclusion, craniocerebral MRI measurement in NMO patients can provide more basis for the diagnosis and differential diagnosis of the disease, so as to improve the diagnostic level of NMO.
A Coal Bump Risk Assessment and Prediction Model Based on Multiparameter Indices
Authors: Luo Tao , Fan Gangwei , Zhang Shizhong , Ren Shang , Fan Yibo , Shen Ruiliang
Published: March 2022

Coal bump, a common dynamic disaster in mining of deep coal resources, its assessing and predicting is an important component in safety management. This paper presents a model to assess and predict coal bump risk based on multiparameter indices. A new energy accumulation index

S

was proposed by considering acoustic emission and electromagnetic emission signal characteristics in mine shocks. Combined with indices

E

(energy of microseisms) and

N

(frequency of microseisms) of microseismic monitoring, a static and dynamic coal bump risk assessment and prediction model was established. We studied coal bump events that occurred during extraction in 311305 working face of Bayangale coal mine in Inner Mongolia, China. We obtained the acoustic emission and electromagnetic emission signal distribution and change law, using principal component analysis method and density ellipse to establish the index

S

. A typical precursory of coal bumps is that AE and EME strength has obvious fluctuation period of 3-4 days, index

S

showing an obvious decreasing trend, while the time-series curve of the microseismic energy is relatively stable, and the vibration frequency curve has a significant upward trend. After predict the potential coal bump risk and its area of occurrence, large diameter drilling (Φ150 mm) on-site was used to relief pressure concertation in coal seam and roof. The results demonstrate that this model based on multiparameter indices is capable of quantitatively prewarning rock burst risk.
Neuronal Apoptosis in Patients with Liver Cirrhosis and Neuronal Epileptiform Discharge Model Based upon Multi-Modal Fusion Deep Learning
Authors: Chi Nannan , Wang Xiuping , Yu Yun , Wu Manman , Yu Jianan
Published: March 2022

Neurons refer to nerve cells. Each neuron is connected with thousands of other neurons to form a corresponding functional area and carry out complex communication with other functional areas. Its importance to the human body is self-evident. There are also many scholars studying the mechanism of apoptosis. This paper proposes a study of neuronal apoptosis in patients with liver cirrhosis and neuronal epileptiform discharge models based on multi-modal fusion deep learning, aiming to study the influencing factors of abnormal neuronal discharge in the brain. The method in this paper is to study multi-modal information fusion methods, perform Bayesian inference, and analyze multi-modal medical data. The function of these research methods is to obtain the relationship between the independence of information and the intersection of information among modalities. In the neuronal epileptiform discharge model, the mRNA expression level of the necroptotic signaling pathway related protein was detected, and the mechanism of neuronal necrosis in patients with liver cirrhosis was explored. Experiments show that the neuron recognition rate has been increased from 67.2% to 84.5%, and the time has been reduced, proving the effectiveness of deep learning.
Thoracic Endometriosis: A Presentation of an Uncommon Disease in a Black African Woman
Authors: Ogunkoya John Omotola , Solaja Taiwo Olufemi , Ogunlade Akinwale Folarin , Ogunmola Marion Itohan
Published: March 2022

Introduction. Endometriosis is defined as a chronic gynecologic disease which is characterized by the presence of endometrial glands and stroma in anatomical sites and organs outside the uterine cavity. The exact prevalence of endometriosis is difficult to determine because many women remain asymptomatic. However, endometriosis affects about 10% to 15% of women. Thoracic endometriosis (TES) is the most common endometriosis outside the abdominopelvic cavity. It refers to endometriosis within the thoracic cavity including the lung parenchyma, diaphragm, and pleural surfaces. It can manifest as catamenial chest pain, pneumothorax, hemoptysis, hemothorax, catamenial haemoptysis, and pulmonary nodules. Case Summary. A 39-years-old married female presented with recurrent right-sided chest pain of 22 years duration, recurrent cough of more than 20 years and progressive breathlessness of a month duration. The chest pain is pleuritic, and it often starts few days to the onset of her menses and lasts throughout menstrual flow only to abate after the stoppage of menstrual bleeding. Cough was unproductive, paroxysmal often worse with worsening chest pain. It disappears after the end of menstrual bleed. Breathlessness was initially on mild to moderate exertion before progressing to occasional breathlessness at rest. No history of orthopnea, paroxysmal nocturnal dyspnea, and pedal swelling was found. Over the years, she had presented to several clinics where she was said to have menstrual pain referred to the chest. Conclusion. Diagnosis of extrapelvic endometriosis can be challenging and delayed because it presents in a myriad of ways and in some cases, it may be difficult to link symptoms and the menstrual cycle.
Sentiment Analysis Models with Bayesian Approach: A Bike Preference Application in Metropolitan Cities
Authors: Vitetta Antonino
Published: March 2022

Social media data is an important source of information that can also be used for the study of the passenger mobility sector. In transport systems, user choice is studied through demand models that define how user behavior is affected by the performance of the supply system. Demand models are typically calibrated through data observed in the transport system. The observed data includes the choices actually made by users. This paper investigates how sentiment analysis of data available in social media can be adopted to specify, calibrate, and validate demand models in certain choice levels. In this work a model based on the Bayesian approach is specified, calibrated, and validated in the case of bike preference in some Italian metropolitan cities. The model takes into account the discrete choice approach. Specification, calibration, and validation made it possible to identify the relevant variables that influence sentiments and obtain the posterior distribution probability of the parameters. The prior and the posterior conditional probabilities are compared, and some indications are obtained on the elasticity and weight of the sentiments that influence the choice.
Random Forest and LightGBM-Based Human Health Check for Medical Device Fault Detection
Authors: Wang Weiwei
Published: March 2022

Medical devices are items used directly or indirectly in the human body and are a prerequisite for hospital treatment of patients, and their quality can have a direct impact on the health of patients, so strengthening the quality control of medical device use is a hot spot of concern in the clinic. Current medical device testing can reduce the occurrence of adverse events, but it cannot be completely avoided, and its work still needs to be further strengthened. In this paper, we design a two-way feature selection algorithm based on PSO_RF. We use random forest to calculate the importance of the feature attributes of the sample data and sort the results in descending order, where a particle swarm algorithm is introduced to optimize the parameters of the random forest algorithm. The 245 medical device adverse event reports received by the testing center were selected, the occurrence and types of adverse events were analyzed retrospectively, and quality control countermeasures for medical device use were formulated.
Robust Data-Driven Fault Detection: An Application to Aircraft Air Data Sensors
Authors: Zhao Yunmei , Zhao Hang , Ai Jianliang , Dong Yiqun
Published: March 2022

Fault detection (FD) is important for health monitoring and safe operation of dynamical systems. Previous studies use model-based approaches which are sensitive to system specifics, attenuating the robustness. Data-driven methods have claimed accurate performances which scale well to different cases, but the algorithmic structures and enclosed operations are “black,” jeopardizing its robustness. To address these issues, exemplifying the FD problem of aircraft air data sensors, we explore to develop a robust (accurate, scalable, explainable, and interpretable) FD scheme using a typical data-driven method, i.e., deep neural networks (DNN). To guarantee the scalability, aircraft inertial reference unit measurements are adopted as equivalent inputs to the DNN, and a database associated with 6 different aircraft/flight conditions is constructed. Convolutional neural networks (CNN) and long-short time memory (LSTM) blocks are used in the DNN scheme for accurate FD performances. To enhance robustness of the DNN, we also develop two new concepts: “large structure” which corresponds to the parameters that can be objectively optimized (e.g., CNN kernel size) via certain metrics (e.g., accuracy) and “small structure” that conveys subjective understanding of humans (e.g., class activation mapping in CNN) within a certain context (e.g., object detection). We illustrate the optimization process we adopted in devising the DNN large structure, which yields accurate (90%) and scalable (24 diverse cases) performances. We also interpret the DNN small structure via class activation mapping, which yields promising results and solidifies the robustness of DNN. Lessons and experiences we learned are also summarized in the paper, which we believe is instructive for addressing the FD problems in other similar fields.