bluuebunny/crossref_metadata_2025 huggingface dataset:
Scheduling mechanisms to control the spread of COVID-19
Authors: Augustine John , Hourani Khalid , Molla Anisur Rahaman , Pandurangan Gopal , Pasic Adi
Published: September 2022

We study scheduling mechanisms that explore the trade-off between containing the spread of COVID-19 and performing in-person activity in organizations. Our mechanisms, referred to asgroup scheduling, are based on partitioning the populationrandomlyinto groups and scheduling each group on appropriate days with possible gaps (when no one is working and all are quarantined). Each group interacts with no other group and, importantly, any person who is symptomatic in a group is quarantined. We show that our mechanisms effectively trade-off in-person activity for more effective control of the COVID-19 virus spread. In particular, we show that a mechanism which partitions the population into two groups that alternatively work in-person for five days each, flatlines the number of COVID-19 cases quite effectively, while still maintaining in-person activity at 70% of pre-COVID-19 level. Other mechanisms that partitions into two groups with less continuous work days or more spacing or three groups achieve even more aggressive control of the virus at the cost of a somewhat lower in-person activity (about 50%). We demonstrate the efficacy of our mechanisms by theoretical analysis and extensive experimental simulations on various epidemiological models based on real-world data.
Tolerance to soil acidity of soybean (Glycine max L.) genotypes under field conditions Southwestern Ethiopia
Authors: Bedassa Tolossa Ameyu , Abebe Abush Tesfaye , Tolessa Alemayehu Regassa
Published: September 2022

Soil acidity with associated low nutrient availability is one of the major constraints to soybean production in southwestern Ethiopia. Integrated use of lime and acid-tolerant crops is believed to reduce soil acidity and improve crop production. The experiment was conducted in the field condition of Mettu, southwestern Ethiopia during the 2017/18 main cropping season. The experiment comprised fifteen soybean genotypes and two soil amendment (lime and unlimed) treatments arranged in a split-plot design with three replications. For each treatment, four rows were planted per plot; data related to growth, root, nodule, and yield of the crop were collected at a necessary stage for each. Liming and genotype interaction had significantly (P = 0.01) affected all parameters considered except for hundred seed weight and root volume and were affected only by the main effects of genotypes and liming. A significant reduction for most parameters was found on lime-untreated soil than treated soil. Though some genotypes showed higher performance for root, growth parameters, and yield components under unlimed soils; however, gave higher yield and yield components, when grown on lime-untreated with an average yield reduction of 13.7%, due to soil acidity. The maximum grain yield of (1943.93 kg ha-1) was obtained under lime treated acid soil from PI567046A genotype; while the lowest (510.49 kg ha-1) were recorded from SCS-1genotype under the lime untreated acid soil. Genotype BRS268 showed higher yield (1319.83 kg ha-1) under lime untreated acid soil than lime treated acid soil (1143.47 kg ha-1) and showed less reduction percentage for a number of the nodules, root weight, and number of seeds per plant; while PI567046A showed high reduction percentage for yield, biomass, number of pod and seed per plant. A high difference was observed among the soybean genotypes for soil acidity tolerance, which might be further exploited by breeders for the genetic improvement of soybean. Genotype BRS268 had performed better than other tested genotypes under increased soil acidity. selection would be effective to improve soybean genotypes performance on acid soils and identify low Phosphorus tolerant genotype that helps smallholder farmers optimize soybean productivity on acid soils in the study area. HAWASSA-04 variety is the most tolerant among the tested materials. However, further study is required by considering additional genotypes to reach a conclusive recommendation
Proximal tubular renal dysfunction among HIV infected patients on Tenofovir versus Tenofovir sparing regimen in western Kenya
Authors: Karoney Mercy Jelagat , Koech Mathew Kirtptonui , Njiru Evangeline Wawira , Owino Ong’or Willis Dixon
Published: September 2022

Introduction

Tenofovir Disoproxil Fumarate (TDF) is the most widely used Anti-Retroviral Therapy (ART) drug due to its potency, safety profile and World Health Organization (WHO) recommendation. TDF causes proximal tubular renal dysfunction (PTRD) leading to Fanconi syndrome, acute kidney injury and chronic kidney disease. Modest rates (2–4%) of TDF related toxicity based on estimated Glomerular Filtration Rate (GFR) have been described, while TDF-induced PTRD has been reported to be 22%. TDF toxicity is more likely among African patients, it is reversible and TDF may be renal dosed in patients with dysfunction. The objective of this study was to assess proximal tubular renal dysfunction, global renal function, and their determinants among patients on TDF versus TDF-sparing regimen.

Methods

This was a cross-sectional study among people living with HIV/AIDS (PLWHA) attending the Academic Model Providing Access to Healthcare (AMPATH) program. The primary outcome of interest in this study was PTRD while the secondary outcome of interest was estimated GFR. PTRD was defined as any two of beta-2 microglobulin in urine, metabolic acidosis, normoglycemic glucosuria and fractional excretion of phosphate. Student’s t-test, chi-square and their non-parametric equivalents were used to test for statistical significance. Univariate and multivariate logistic regression analysis was carried out.

Results

A total of 516 participants were included in the final analysis, 261 on TDF while 255 were on TDF-sparing regimens. The mean (SD) age of all participants was 41.5 (12.6) years with majority being female (60.3%). The proportion of PTRD was 10.0% versus 3.1% in the TDF compared to TDF-sparing group (P<0.001). Mean estimated GFR was 112.8 (21.5) vs 109.7 (21.9) ml/min/1.73mm3 (P = 0.20) for the TDF compared to TDF-sparing group. TDF users were more likely to have PTRD compared to non-TDF users, adjusted Odds Ratio (AOR) 3.0, 95% CI 1.12 to 7.75.

Conclusion

There was significant PTRD in the TDF compared to TDF-sparing group without significant difference in estimated GFR. The clinical significance of these findings may not be clear in the short term.
Mentoring future mentors in undergraduate medical education
Authors: Ong Yun Ting , Quek Chrystie Wan Ning , Pisupati Anushka , Loh Eleanor Kei Ying , Venktaramana Vaishnavi , Chiam Min , Krishna Lalit Kumar Radha
Published: September 2022

Background

Efforts to support flagging mentoring programs facing shortages of experienced clinical mentors have had an unexpected and welcome effect. Supplementing traditional mentoring programs with peer-mentoring have not only addressed gaps in practice, structure, support and mentee oversight but have offered mentees charged with peer-mentoring duties the opportunity to take on mentoring roles under senior supervision. This study evaluates the experiences of peer-mentors within a local research mentoring program to better understand and advance this endeavor.

Methods

Semi-structured interviews and post-interview surveys based on recent reviews on mentoring were employed. Adapting the Systematic Evidence Based Approach, data was analysed using thematic and content analysis. Results were combined using the Jigsaw Perspective to ensure that key elements of the different mentoring stages were identified.

Results

The interviews and surveys revealed the following domains: Motivation, Initiation, Practicing, and Mentoring Environment.

Conclusion

These findings provide novel insight into a structured framework that may help guide the experiences, training, assessment, and oversight of peer-mentors beyond the auspices of our local program. These general observations will equip host organizations with the direction they need to take in designing and executing peer-mentoring training and assessment programs of their own. Whilst the stages of peer-mentoring need further evaluation and an effective means of assessment and support pivotal, we believe our findings suggest that peer-mentoring may not only help to address the shortfall in mentors but is an invaluable learning experience that prepares and instils key values, beliefs and principles in young would-be mentors.
Sri Lankan traditional parboiled rice: A panacea for hyperglycaemia?
Authors: Thennakoon T. P. A. U. , Ekanayake S.
Published: September 2022

The research aimed to scientifically prove that parboiled Sri Lankan traditional rice elicits lower glycaemic responses comparative to raw unpolished or polished rice. Thus the proximate composition and glycaemic indices (GI) of raw, raw polished, and parboiled traditional Sri Lankan rice (Oryza sativa L.) varieties Godaheenati, Batapola el, Dik wee, Dahanala, Unakola samba, and Hangimuththan were studied as comparative data are not available. Cooked parboiled rice contained significantly high moisture (P<0.05) than raw or raw polished. Mineral content was low (<1.5%) regardless of processing. Crude protein was comparatively high (5.8–11.0% DM) with 2.1–5% (DM) fat with raw unpolished and parboiled having higher contents. Digestible starch of raw polished was highest compared to parboiled or raw unpolished (68.8–90.5% DM). Resistant starch was significantly (P<0.05) high in parboiled rice (1.1–7.2%) with the least total dietary fibre in raw polished rice. All varieties of parboiled and raw polished were found to elicit low GI and high GI respectively. High moisture, high resistant starch, and low starch in cooked parboiled rice contributed to low GI compared to raw unpolished or raw polished rice.
Modeling spatial determinants of initiation of breastfeeding in Ethiopia: A geographically weighted regression analysis
Authors: Hailegebreal Samuel , Haile Yosef , Seboka Binyam Tariku , Enyew Ermias Bekele , Shibiru Tamiru , Mekonnen Zeleke Abebaw , Mengiste Shegaw Anagaw
Published: September 2022

Background

The World Health Organization (WHO) encourages breastfeeding to begin within the first hour after birth in order to save children’s lives. In Ethiopia, different studies are done on the prevalence and determinants of breastfeeding initiation, up to our knowledge, the spatial distribution and the spatial determinants of breast feeding initiation over time are not investigated. Therefore, the objectives of this study were to assess spatial variation and its spatial determinant of delayed initiation of breastfeeding in Ethiopia using Geographically Weighted Regression (GWR).

Methods

A cross-sectional study was undertaken using the nationally representative 2016 Ethiopian Demographic and Health Survey (EDHS) dataset. Global Moran’s I statistic was used to measure whether delayed breastfeeding initiation was dispersed, clustered, or randomly distributed in study area. Ordinary Least Squares (OLS) regression was used to identify factors explaining the geographic variation in delayed breastfeeding initiation. Besides, spatial variability of relationships between dependent and selected predictors was investigated using geographically weighted regression.

Result

A total weighted sample of 4169 children of aged 0 to 23 months was included in this study. Delayed initiation of breastfeeding was spatially varies across the country with a global Moran’s I value of 0.158 at (p-value<0.01). The hotspot (high risk) areas were identified in the Amhara, Afar, and Tigray regions. Orthodox religion, poor wealth index, caesarian section, baby postnatal checkup, and small size of a child at birth were spatially significant factors for delayed breastfeeding initiation in Ethiopia.

Conclusion

In Ethiopia initiation of breastfeeding varies geographically across region. A significant hotspot was identified in the Amhara, Afar, and Tigray regions. The GWR analysis revealed that orthodox religion, poor wealth index, caesarian section, baby postnatal checkup, and small birth weight were spatially significant factors.
MalFuzz: Coverage-guided fuzzing on deep learning-based malware classification model
Authors: Liu Yuying , Yang Pin , Jia Peng , He Ziheng , Luo Hairu
Published: September 2022

With the continuous development of deep learning, more and more domains use deep learning technique to solve key problems. The security issues of deep learning models have also received more and more attention. Nowadays, malware has become a huge security threat in cyberspace. Traditional signature-based malware detection methods are not adaptable to the current large-scale malware detection. Thus many deep learning-based malware detection models are widely used in real malware detection scenarios. Therefore, we need to secure the deep learning-based malware detection models. However, model testing currently focuses on image and natural language processing models. There is no related work to test deep learning-based malware detection models specifically. Therefore, to fill this gap, we propose MalFuzz. MalFuzz uses the idea of coverage-guided fuzzing to test deep learning-based malware detection models. To solve the model state representation problem, MalFuzz uses the first and last layer neuron values to approximately represent the model state. To solve the new coverage calculation problem, MalFuzz uses the fast approximate nearest neighbor algorithm to compute the new coverage. The mutation strategy and seed selection strategy in image model or natural language processing model testing is not appropriate in deep learning-based malware detection model testing. Hence MalFuzz designs the seed selection strategy and seed mutation strategy for malware detection model testing. We performed extensive experiments to demonstrate the effectiveness of MalFuzz. Based on MalConv, Convnet, and CNN 2-d, we compared the modified TensorFuzz and MAB-malware with MalFuzz. Experiment results show that MalFuzz can detect more model classification errors. Likewise, the mutation operation of MalFuzz can retain the original functionality of malware with high probability. Moreover, the seed selection strategy of MalFuzz can help us explore the model state space quickly.
Performance evaluation of the Roche Elecsys® Anti-SARS-CoV-2 immunoassays by comparison with neutralizing antibodies and clinical assessment
Authors: Takei Satomi , Ai Tomohiko , Yamamoto Takamasa , Igawa Gene , Kanno Takayuki , Tobiume Minoru , Hiki Makoto , Saito Kaori , Khasawneh Abdullah , Wakita Mitsuru , Misawa Shigeki , Miida Takashi , Okuzawa Atsushi , Suzuki Tadaki , Takahashi Kazuhisa , Naito Toshio , Tabe Yoko
Published: September 2022

Quantitative measurement of SARS-CoV-2 neutralizing antibodies is highly expected to evaluate immune status, vaccine response, and antiviral therapy. The Elecsys® Anti-SARS-CoV-2 S (Elecsys® anti-S) was developed to measure anti-SARS-CoV-2 S proteins. We sought to investigate whether Elecsys® anti-S can be used to predict neutralizing activities in patients’ serums using an authentic virus neutralization assay. One hundred forty-six serum samples were obtained from 59 patients with COVID-19 at multiple time points. Of the 59 patients, 44 cases were included in Group M (mild 23, moderate 21) and produced 84 samples (mild 35, moderate 49), while 15 cases were included in Group S (severe 11, critical 4) and produced 62 samples (severe 43, critical 19). The neutralization assay detected 73% positive cases, and Elecsys® anti-S and Elecsys® Anti-SARS-CoV-2 (Elecsys® anti-N) showed 72% and 66% positive cases, respectively. A linear correlation between the Elecsys® anti-S assay and the neutralization assay were highly correlated (r = 0.7253, r2 = 0.5261) than a linear correlation between the Elecsys® anti-N and neutralization assay (r = 0.5824, r2 = 0.3392). The levels of Elecsys® anti-S antibody and neutralizing activities were significantly higher in Group S than in Group M after 6 weeks from onset of symptoms (p < 0.05). Conversely, the levels of Elecsys® anti-N were comparable in both groups. Three immunosuppressed patients, including cancer patients, showed low levels of anti-S and anti-N antibodies and neutralizing activities throughout the measurement period, indicating the need for careful follow-up. Our data indicate that Elecsys® anti-S can predict the neutralization antibodies in COVID-19.
On network backbone extraction for modeling online collective behavior
Authors: Gomes Ferreira Carlos Henrique , Murai Fabricio , Silva Ana P. C. , Trevisan Martino , Vassio Luca , Drago Idilio , Mellia Marco , Almeida Jussara M.
Published: September 2022

Collective user behavior in social media applications often drives several important online and offline phenomena linked to the spread of opinions and information. Several studies have focused on the analysis of such phenomena using networks to model user interactions, represented by edges. However, only a fraction of edges contribute to the actual investigation. Even worse, the often large number of non-relevant edges may obfuscate the salient interactions, blurring the underlying structures and user communities that capture the collective behavior patterns driving the target phenomenon. To solve this issue, researchers have proposed several network backbone extraction techniques to obtain a reduced and representative version of the network that better explains the phenomenon of interest. Each technique has its specific assumptions and procedure to extract the backbone. However, the literature lacks a clear methodology to highlight such assumptions, discuss how they affect the choice of a method and offer validation strategies in scenarios where no ground truth exists. In this work, we fill this gap by proposing a principled methodology for comparing and selecting the most appropriate backbone extraction method given a phenomenon of interest. We characterize ten state-of-the-art techniques in terms of their assumptions, requirements, and other aspects that one must consider to apply them in practice. We present four steps to apply, evaluate and select the best method(s) to a given target phenomenon. We validate our approach using two case studies with different requirements: online discussions on Instagram and coordinated behavior in WhatsApp groups. We show that each method can produce very different backbones, underlying that the choice of an adequate method is of utmost importance to reveal valuable knowledge about the particular phenomenon under investigation.
Prevalence, etiology and antibiotic resistance patterns of community-acquired urinary tract infections in Dhaka, Bangladesh
Authors: Islam Mohammad Aminul , Islam Md Rayhanul , Khan Rizwana , Amin Mohammed Badrul , Rahman Mahdia , Hossain Muhammed Iqbal , Ahmed Dilruba , Asaduzzaman Muhammad , Riley Lee W.
Published: September 2022

Urinary tract infection (UTI) accounts for a significant morbidity and mortality across the world and is a leading cause for antibiotic prescriptions in the community especially in developing countries. Empirical choice of antibiotics for treatment of UTI is often discordant with the drug susceptibility of the etiologic agent. This study aimed to estimate the prevalence of community-acquired UTI caused by antibiotic resistant organisms. This was a cross-sectional study where urine samples were prospectively collected from 4,500 patients at the icddr,b diagnostic clinic in Dhaka, Bangladesh during 2016–2018. Urine samples were analyzed by standard culture method and the isolated bacteria were tested for antibiotic susceptibility by using disc diffusion method and VITEK-2. Descriptive statistics were used to estimate the prevalence of community acquired UTI (CA-UTI) by different age groups, sex, and etiology of infection. Relationship between the etiology of CA-UTI and age and sex of patients was analyzed using binary logistic regression analysis. Seasonal trends in the prevalence of CA-UTI, multi-drug resistant (MDR) pathogens and MDR Escherichia coli were also analyzed. Around 81% of patients were adults (≥18y). Of 3,200 (71%) urine samples with bacterial growth, 920 (29%) had a bacterial count of ≥1.0x105 CFU/ml indicating UTI. Women were more likely to have UTI compared to males (OR: 1.48, CI: 1.24–1.76). E. coli (51.6%) was the predominant causative pathogen followed by Streptococcus spp. (15.7%), Klebsiella spp. (12.1%), Enterococcus spp. (6.4%), Pseudomonas spp. (4.4%), coagulase-negative Staphylococcus spp. (2.0%), and other pathogens (7.8%). Both E. coli and Klebsiella spp. were predominantly resistant to penicillin (85%, 95%, respectively) followed by macrolide (70%, 76%), third-generation cephalosporins (69%, 58%), fluoroquinolones (69%, 53%) and carbapenem (5%, 9%). Around 65% of patients tested positive for multi-drug resistant (MDR) uropathogens. A higher number of male patients tested positive for MDR pathogens compared to the female patients (p = 0.015). Overall, 71% of Gram-negative and 46% of Gram-positive bacteria were MDR. The burden of community-acquired UTI caused by MDR organisms was high among the study population. The findings of the study will guide clinicians to be more selective about their antibiotic choice for empirical treatment of UTI and alleviate misuse/overuse of antibiotics in the community.
One-session treatment for specific phobias: Barriers, facilitators and acceptability as perceived by children & young people, parents, and clinicians
Authors: Hayward Emily , Solaiman Kiera , Bee Penny , Barr Amy , Edwards Hannah , Lomas Jennifer , Tindall Lucy , Scott Alexander J. , Biggs Katie , Wright Barry
Published: September 2022

Between 2015 and 2020 the Alleviating Specific Phobias Experienced by Children Trial (ASPECT) was conducted in the UK to examine the non-inferiority of One-Session Treatment in comparison to Cognitive Behavioural Therapy based interventions for children and young people with specific phobias. A nested qualitative evaluation was conducted as part of this trial to examine the acceptability of One-Session Treatment. Qualitative interviews were conducted with children and young people taking part in the trial, their parents/guardians, and clinicians delivering the intervention, about their experiences and the acceptability of One Session Treatment. Interviews were digitally recorded and transcribed verbatim. Analysis followed a qualitative framework approach, a widely used method of analysing primary qualitative data pertaining to healthcare practices with policy relevance. Stakeholder groups found One Session Treatment to be an acceptable intervention and barriers and facilitators for its implementation into services were also identified. Potential barriers included challenges to patient flow and treatment scepticism, whilst facilitators included adopting a child-centred approach, child readiness and suitability, opportunity for increased momentum, parental support and involvement, and proximal and distal gains. For One Session Treatment’s successful implementation into services, consideration of these barriers is needed and suitability guidance for its use in this population should be developed. Further research exploring children and young people’s experiences of receiving Cognitive Behavioural Therapy and its acceptability in comparison to One Session Treatment would be welcomed.
Emotion-focused coping mediates the relationship between COVID-related distress and compulsive buying
Authors: Kovács Lilla Nóra , Katzinger Eva , Yi Sunghwan , Demetrovics Zsolt , Maraz Aniko , Kökönyei Gyöngyi
Published: September 2022

Background and aims

COVID-19 posits psychological challenges worldwide and has given rise to nonadaptive behavior, especially in the presence of maladaptive coping. In the current study, we assessed whether the relationship between COVID-related distress and compulsive buying is mediated by task-focused and emotion-focused coping. We also examined whether these associations were invariant over time as the pandemic unfolded.

Methods

Self-report surveys were administered online in the United States in the first six months of the pandemic (March–October 2020) in sampling batches of 25 participants every three days, resulting in a total sample of N = 1,418 (40% female, mean age = 36.6). We carried out structural equation modeling to assess whether the relationship between distress related to COVID-19 and compulsive buying is mediated by task-focused and emotion-focused coping. Time was used as a grouping variable based on events related to the pandemic in the U.S. to calculate model invariance across three time periods.

Results

The results indicated significant mediation between distress, emotion-focused coping, and compulsive buying, but not between task-focused coping and compulsive buying. The mediation model showed excellent fit to the data (χ² = 1119.377, df = 420, RMSEA = 0.059 [0.055–0.064], SRMR = 0.049, CFI = 0.951, TLI = 0.947). Models were not invariant across the three examined time periods.

Conclusions

Our results indicate that compulsive buying is more likely to occur in relation to emotion-focused coping as a response to COVID-related distress than in relation to task-focused coping, especially during periods of increasing distress. However, model paths varied during the course of the pandemic.
Tactile Biography Questionnaire: A contribution to its validation in an Italian sample
Authors: Mariani Wigley Isabella Lucia Chiara , Pastore Massimiliano , Mascheroni Eleonora , Tremolada Marta , Bonichini Sabrina , Montirosso Rosario
Published: September 2022

As the interest in the beneficial effects of positive touch experiences is rapidly growing, having reliable and valid tools to its assessment is essential. The Tactile Biography Questionnaire (TBQ) allows to quantify individual differences in affective touch experiences throughout life. The aim of this article is to present a contribution to its validation in the Italian population. Data analysis were run on a sample of 2040 Italian individuals (Females = 1342, 64%) participating in an on-line survey. Confirmatory Factor Analysis and invariance analyses for gender were applied. Concurrent validity was checked using two specific subscales of the Touch Avoidance Questionnaire (TAQ—i.e., Family and Stranger). The four-dimensional structure of the TBQ was confirmed in the overall sample and by gender. Also, the TBQ showed an excellent internal consistency and a good concurrent validity with TAQ. The present study suggests that the TBQ can be used to support healthcare professionals and researchers to assess experiences of affective touch in different settings.
Progressive privacy-preserving batch retrieval of lung CT image sequences based on edge-cloud collaborative computation
Authors: Zhuang Yi , Jiang Nan
Published: September 2022

Background

A computer tomography image (CI) sequence can be regarded as a time-series data that is composed of a great deal of nearby and similarCIs. Since the computational and I/O costs of similarity measure, encryption, and decryption calculation during a similarity retrieval of the largeCIsequences (CIS) are extremely high, deploying all retrieval tasks in the cloud, however, will lead to excessive computing load on the cloud, which will greatly and negatively affect the retrieval performance.

Methodologies

To tackle the above challenges, the paper proposes a progressive privacy-preservingBatchRetrieval scheme for the lungCISs based on edge-cloud collaborative computation called theBRSmethod. There are four supporting techniques to enable theBRSmethod, such as: 1)batch similarity measure for CISs, 2)CIB-based privacy preserving scheme, 3)uniform edge-cloud index framework, and 4)edge buffering.

Results

The experimental results reveal that our method outperforms the state-of-the-art approaches in terms of efficiency and scalability, drastically reducing response time by lowering network communication costs while enhancing retrieval safety and accuracy.
Diagnostic performance of deep learning-based automatic white matter hyperintensity segmentation for classification of the Fazekas scale and differentiation of subcortical vascular dementia
Authors: Joo Leehi , Shim Woo Hyun , Suh Chong Hyun , Lim Su Jin , Heo Hwon , Kim Woo Seok , Hong Eunpyeong , Lee Dongsoo , Sung Jinkyeong , Lim Jae-Sung , Lee Jae-Hong , Kim Sang Joon
Published: September 2022

Purpose

To validate the diagnostic performance of commercially available, deep learning-based automatic white matter hyperintensity (WMH) segmentation algorithm for classifying the grades of the Fazekas scale and differentiating subcortical vascular dementia.

Methods

This retrospective, observational, single-institution study investigated the diagnostic performance of a deep learning-based automatic WMH volume segmentation to classify the grades of the Fazekas scale and differentiate subcortical vascular dementia. The VUNO Med-DeepBrain was used for the WMH segmentation system. The system for segmentation of WMH was designed with convolutional neural networks, in which the input image was comprised of a pre-processed axial FLAIR image, and the output was a segmented WMH mask and its volume. Patients presented with memory complaint between March 2017 and June 2018 were included and were split into training (March 2017–March 2018, n = 596) and internal validation test set (April 2018–June 2018, n = 204).

Results

Optimal cut-off values to categorize WMH volume as normal vs. mild/moderate/severe, normal/mild vs. moderate/severe, and normal/mild/moderate vs. severe were 3.4 mL, 9.6 mL, and 17.1 mL, respectively, and the AUC were 0.921, 0.956 and 0.960, respectively. When differentiating normal/mild vs. moderate/severe using WMH volume in the test set, sensitivity, specificity, and accuracy were 96.4%, 89.9%, and 91.7%, respectively. For distinguishing subcortical vascular dementia from others using WMH volume, sensitivity, specificity, and accuracy were 83.3%, 84.3%, and 84.3%, respectively.

Conclusion

Deep learning-based automatic WMH segmentation may be an accurate and promising method for classifying the grades of the Fazekas scale and differentiating subcortical vascular dementia.
Spatial and chromatic properties of numerosity estimation in isolation and context
Authors: Gheorghiu Elena , Goldschmitt Dirk
Published: September 2022

Numerosity estimation around the subitizing range is facilitated by a shape-template matching process and shape-coding mechanisms are selective to visual features such as colour and luminance contrast polarity. Objects in natural scenes are often embedded within other objects or textured surfaces. Numerosity estimation is improved when objects are grouped into small clusters of the same colour, a phenomenon termed groupitizing, which is thought to leverage on the subitizing system. Here we investigate whether numerosity mechanisms around the subitizing range are selective to colour, luminance contrast polarity and orientation, and how spatial organisation of context and target elements modulates target numerosity estimation. Stimuli consisted of a small number (3-to-6) of target elements presented either in isolation or embedded within context elements. To examine selectivity to colour, luminance polarity and orientation, we compared target-only conditions in which all elements were either the same or different along one of these feature dimensions. We found comparable performance in the same and different feature conditions, revealing that subitizing mechanism do not depend on ‘on-off’ luminance-polarity, colour or orientation channel interactions. We also measured the effect of varying spatial organisation of (i) context, by arranging the elements either in a grid, mirror-symmetric, translation-symmetric or random; (ii) target, by placing the elements either mirror-symmetric, on the vertices of simple shapes or random. Our results indicate higher accuracy and lower RTs in the grid compared to all other context types, with mirror symmetric, translation and random arrangements having comparable effects on target numerosity. We also found improved performance with shape-target followed by symmetric and random target arrangements in the absence and presence of context. These findings indicate that numerosity mechanisms around the subitizing range are not selective to colour, luminance polarity and orientation, and that symmetric, translation and random contexts organisations inhibit target-numerosity encoding stronger than regular/grid context.
A training strategy for hybrid models to break the curse of dimensionality
Authors: E. Samadi Moein , Kiefer Sandra , Fritsch Sebastian Johaness , Bickenbach Johannes , Schuppert Andreas
Published: September 2022

Mechanistic/data-driven hybrid modeling is a key approach when the mechanistic details of the processes at hand are not sufficiently well understood, but also inferring a model purely from data is too complex. By the integration of first principles into a data-driven approach, hybrid modeling promises a feasible data demand alongside extrapolation. In this work, we introduce a learning strategy for tree-structured hybrid models to perform a binary classification task. Given a set of binary labeled data, the challenge is to use them to develop a model that accurately assesses labels of new unlabeled data. Our strategy employs graph-theoretic methods to analyze the data and deduce a function that maps input features to output labels. Our focus here is on data sets represented by binary features in which the label assessment of unlabeled data points is always extrapolation. Our strategy shows the existence of small sets of data points within given binary data for which knowing the labels allows for extrapolation to the entire valid input space. An implementation of our strategy yields a notable reduction of training-data demand in a binary classification task compared with different supervised machine learning algorithms. As an application, we have fitted a tree-structured hybrid model to the vital status of a cohort of COVID-19 patients requiring intensive-care unit treatment and mechanical ventilation. Our learning strategy yields the existence of patient cohorts for whom knowing the vital status enables extrapolation to the entire valid input space of the developed hybrid model.
Sickness absence in relation to first childbirth in nulliparous women, employed in the education and care branches in the public or private sectors: A Swedish longitudinal cohort study
Authors: László Krisztina D. , Svedberg Pia , Lindfors Petra , Lidwall Ulrik , Alexanderson Kristina
Published: September 2022

Background

Pregnancy and childbirth entail increased risks of sickness absence (SA). Many women work in education and care, two branches characterised by high SA levels; it is not known if the link between childbirth and SA in these branches differs between private and public sectors. We examined SA and disability pension (DP) in relation to childbirth among women working in the education and care branches, and if these patterns differed between public and private sectors.

Methods

We performed a Swedish register-based cohort study. Study participants were nulliparous women living in Sweden in December 2004 and employed in education or care (n = 120,013). We compared SA/DP in the three years before and after 2005 among women who had no childbirth during follow-up (B0), had one childbirth in 2005 and no more (B1), and had one childbirth in 2005 and at least one more during follow-up (B1+). Analyses were performed for all and by public or private sector.

Results

Of all studied women, 70% worked in the public sector. Women in B1 and B1+ had, except for the year before childbirth, comparable or lower mean combined SA/DP days than women in the B0 group; women in the B1+ group had, except for the year before childbirth, the lowest mean level of SA/DP. We observed no substantial differences in these patterns between public and private sectors.

Conclusions

Patterns of SA/DP among nulliparous women who did or did not give birth did not differ substantially between public and private sectors among women in the educational and care branches.
An innovative strategy to identify new targets for delivering antibodies to the brain has led to the exploration of the integrin family
Authors: Cegarra Céline , Cameron Béatrice , Chaves Catarina , Dabdoubi Tarik , Do Tuan-Minh , Genêt Bruno , Roudières Valérie , Shi Yi , Tchepikoff Patricia , Lesuisse Dominique
Published: September 2022

Background

Increasing brain exposure of biotherapeutics is key to success in central nervous system disease drug discovery. Accessing the brain parenchyma is especially difficult for large polar molecules such as biotherapeutics and antibodies because of the blood-brain barrier. We investigated a new immunization strategy to identify novel receptors mediating transcytosis across the blood-brain barrier.

Method

We immunized mice with primary non-human primate brain microvascular endothelial cells to obtain antibodies. These antibodies were screened for their capacity to bind and to be internalized by primary non-human primate brain microvascular endothelial cells and Human Cerebral Microvascular Endothelial Cell clone D3. They were further evaluated for their transcytosis capabilities in three in vitro blood-brain barrier models. In parallel, their targets were identified by two different methods and their pattern of binding to human tissue was investigated using immunohistochemistry.

Results

12 antibodies with unique sequence and internalization capacities were selected amongst more than six hundred. Aside from one antibody targeting Activated Leukocyte Cell Adhesion Molecule and one targeting Striatin3, most of the other antibodies recognized β1 integrin and its heterodimers. The antibody with the best transcytosis capabilities in all blood-brain barrier in vitro models and with the best binding capacity was an anti-αnβ1 integrin. In comparison, commercial anti-integrin antibodies performed poorly in transcytosis assays, emphasizing the originality of the antibodies derived here. Immunohistochemistry studies showed specific vascular staining on human and non-human primate tissues.

Conclusions

This transcytotic behavior has not previously been reported for anti-integrin antibodies. Further studies should be undertaken to validate this new mechanism in vivo and to evaluate its potential in brain delivery.
Advances in understanding red blood cell modifications by Babesia
Authors: Hakimi Hassan , Yamagishi Junya , Kawazu Shin-ichiro , Asada Masahito
Published: September 2022

Babesia are tick-borne protozoan parasites that can infect livestock, pets, wildlife animals, and humans. In the mammalian host, they invade and multiply within red blood cells (RBCs). To support their development as obligate intracellular parasites, Babesia export numerous proteins to modify the RBC during invasion and development. Such exported proteins are likely important for parasite survival and pathogenicity and thus represent candidate drug or vaccine targets. The availability of complete genome sequences and the establishment of transfection systems for several Babesia species have aided the identification and functional characterization of exported proteins. Here, we review exported Babesia proteins; discuss their functions in the context of immune evasion, cytoadhesion, and nutrient uptake; and highlight possible future topics for research and application in this field.
Genotypic characterization of mecA gene and antibiogram profile of coagulase-negative staphylococci in subclinical mastitic cows
Authors: Ibrahim Eman S. , Dorgham Sohad M. , Mansour Asmaa S. , Abdalhamed Abeer M. , Khalaf Doaa D.
Published: September 2022

Background and Aim: Coagulase-negative staphylococci (CNS) are becoming the major cause of clinical and subclinical bovine mastitis around the world. This study aims to estimate the prevalence, antibiogram, and frequency of the methicillin-resistant (MR) (mecA) gene in CNS collected from cows with subclinical mastitis.

Materials and Methods: Thirty-four milk samples were collected from 20 cows. Fifteen subclinical mastitis samples (∼44.12%) were identified as CNS isolates. The Vitek2 compact system method was employed for the identification of the species. Furthermore, antibiotic sensitivity tests were performed against 10 different antibiotics for CNS strains. The mecA gene from isolated CNS was detected by conventional polymerase chain reaction (PCR).

Results: Staphylococcus haemolyticus was the most predominant isolated species with an incidence of 33.3% (5/15 isolates), followed by 26.7% for Staphylococcus sciuri and Staphylococcus vitamins (4/15 isolates), and 13.3% for Staphylococcus vitulinus (2/15 isolates), respectively. The highest resistance rates were determined to be 40% (6/15 isolates) against penicillin and oxacillin (OX), 33.3% (5/15 isolates) against clindamycin, 13% (2/15 isolates) against chloramphenicol, amoxicillin, and erythromycin, and 5% (1/15 isolates) against ciprofloxacin, respectively. The results revealed that the isolates were resistant to one or more antimicrobial agents, with five isolates displaying multiple antimicrobial resistance. Furthermore, the results exhibit that all CNS isolates had the mecA gene at 310 bp with a 100% frequency. Moreover, for detecting MR isolates, there are significant discrepancies between phenotypic and genotypic approaches, and only 6/15 CNS isolates phenotypically demonstrated OX resistance.

Conclusion: The results emphasize the necessity of frequent monitoring of phenotypic and genotypic profiles of CNS isolates to ensure effective control measures and the prevention of multidrug resistance strain evolution.
Mild and severe diabetic ketoacidosis in children: a report of two cases
Authors: Jamarin Vini , Marzuki Nanis Sacharina
Published: September 2022

Diabetic ketoacidosis (DKA) is a severe complication of diabetes mellitus (DM) in children caused by insulin deficiency. This condition is often unidentified or diagnosed late, and treated with inadequate therapy. Diabetic ketoacidosis can lead to several complications, the most fatal being cerebral edema. We present two cases of DKA with different clinical presentation and severity. Early identification and proper management of DKA can help improve outcomes and avoid complications.
On the effects of modified lane configuration due to construction works on bridge loading
Authors: Nowak Marcel , Fischer Oliver
Published: September 2022

Construction works are frequently recurring events within highway networks, temporarily altering the characteristics of the traffic flow and hence of the bridge loading process. Consequently, highway bridge superstructures usually carrying unidirectional traffic might have to face modified configurations, with possibly altered lane widths and transverse lane positions, or even an increased number of lanes and the occurrence of bidirectional traffic flow. While usually covering only short periods compared to the average service life of a bridge, such scenarios might represent extreme loading situations, potentially dominating the traffic loading process. Therefore, their consideration and accurate modeling in the course of traffic load assessment and development of object-specific traffic load models are of utmost importance. The presented study analyzes data from bridge monitoring along federal highway A92 in Southern Germany. The data covers standard and different modified lane configurations due to construction works. Besides analyzing the effects on traffic flow characteristics and resulting occurrence rates of multiple truck presence on the bridge, the consequences for load effects and their extreme value behavior are also evaluated. The findings support verification of related code background works and can serve as base and guidance for future research efforts on bridge load modeling in this context.
Climate Change Awareness and Risk Perceptions in the Coastal Marine Ecosystem of Palawan, Philippines
Authors: Alcantara Lutgardo , Creencia Lota , Madarcos Karen , Madarcos John Roderick , Jontila Jean Beth , Culhane Fiona
Published: September 2022

Understanding the coastal communities’ awareness and risk perceptions of climate change impact is essential in developing effective risk communication tools and in developing mitigation strategies to reduce the vulnerability of coastal communities. In this study, we examined the coastal community’s climate change awareness and risk perceptions of climate change impact on the coastal marine ecosystem, sea level rise impact on the mangrove ecosystem, and as a factor affecting coral reefs and seagrass beds. The data were gathered by conducting face-to-face surveys with 291 respondents from the coastal areas of Taytay, Aborlan, and Puerto Princesa in Palawan, Philippines. Results showed that most participants (82%) perceived that climate change is happening and a great majority (75%) perceived it as a risk to the coastal marine ecosystem. Sea level rise was perceived by most participants (60%) to cause coastal erosion and affect the mangrove ecosystem, but they also perceived that coastal erosion can be prevented by mangroves. On coral reefs and seagrass ecosystems, anthropogenic pressures and climate change were perceived to have a high impact, while marine livelihoods had a low impact. In addition, we found that climate change risk perceptions were influenced by direct experiences of extreme weather events (i.e., temperature rise and excessive rainfall), and climate-related livelihood damages (i.e., declining income). Climate change risk perceptions were also found to vary with household income, education, age group, and geographical location. The results suggest that addressing poverty, and effectively communicating climate change risks can improve climate change awareness and risk perceptions.
"Então" como nexo conclusivo nas diferentes sequências tipológicas
Authors: Arena Ana Beatriz
Published: September 2022

O presente trabalho tem como objetivo aprofundar a discussão sobre o então como nexo conclusivo, associando-o às sequências tipológicas. Verificar-se-á se, conforme o contexto linguístico, o juntor expressa uma consequência factual, em que representa linguisticamente eventos da realidade externa (dictum), ou uma conclusão do falante, assumindo valor textual argumentativo (modus). Para tal, lança-se mão dos estudos funcionalistas, segundo os quais itens lexicais passam por um processo de gramaticalização, isto é, em determinados contextos linguísticos, servem a funções gramaticais, e, uma vez gramaticalizados, continuam a desenvolver novas funções gramaticais.
Linguística de Corpus e as Novas Tecnologias de Informação e Comunicação (ICTs)
Authors: Kindermann Cristina Arcuri Eluf
Published: September 2022

Este artigo visa investigar a inserção da Linguística de Corpus (LC) dentro de práticas educacionais na formação de professores de Língua Inglesa em uma universidade particular de São Paulo. Objetivamos, por meio de reflexões críticas e socioculturais, estabelecer um design de interface entre a LC e as novas tecnologias de informação e comunicação (ICTs) na atualidade.
Corpora no Ensino de Línguas Estrangeiras
Authors: Fromm Guilherme
Published: September 2022

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