bluuebunny/crossref_metadata_2025 huggingface dataset:
Weather patterns in Southeast Asia: Relationship with tropical variability and heavy precipitation
Authors: Howard Emma , Thomas Simon , Frame Thomas H.A. , Gonzalez Paula L.M. , Methven John , Martínez‐Alvarado Oscar , Woolnough Steven J.
Published: December 2021

Two sets of weather patterns describing variability in 850 hPa winds in Southeast Asia are presented and compared. Patterns are calculated using EOF/k‐means clustering with and without imposing a separation between planetary‐scale and regional‐scale circulation features. The former are labelled as tiered patterns while the latter are referred to as flat. The ability of the patterns to distinguish between known modes of tropical circulation variability is examined. This includes climate modes such as the seasonal monsoons, the El Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) as well as sub‐seasonal modes including cold surges, phases of the MJO and Boreal summer intraseasonal oscillation (BSISO), tropical cyclones, Borneo vortices and equatorial waves. All these modes are well captured by the weather patterns except for the equatorial waves and the IOD. The tiered patterns are shown to better describe large‐scale modes of variability, while the flat patterns better describe the synoptic variability. Both sets of weather patterns are then used to study the likelihood of heavy precipitation depending on synoptic circulation by considering the regime‐conditioned probability of high‐percentile precipitation using the satellite‐derived Global Precipitation Measurement (GPM) dataset. It is shown that the pattern centroids explain up to 10% of the seasonally anomalous precipitation over land, and that a perfect weather pattern forecast would outperform a perfect MJO forecast. These weather patterns show promising potential in extending the useful forecast range for the risk of heavy precipitation, dependent on their forecastability.
Bayesian regularization for a nonstationary Gaussian linear mixed effects model
Authors: Gecili Emrah , Sivaganesan Siva , Asar Ozgur , Clancy John P. , Ziady Assem , Szczesniak Rhonda D.
Published: December 2021

In omics experiments, estimation and variable selection can involve thousands of proteins/genes observed from a relatively small number of subjects. Many regression regularization procedures have been developed for estimation and variable selection in such high‐dimensional problems. However, approaches have predominantly focused on linear regression models that ignore correlation arising from long sequences of repeated measurements on the outcome. Our work is motivated by the need to identify proteomic biomarkers that improve the prediction of rapid lung‐function decline for individuals with cystic fibrosis (CF) lung disease. We extend four Bayesian penalized regression approaches for a Gaussian linear mixed effects model with nonstationary covariance structure to account for the complicated structure of longitudinal lung function data while simultaneously estimating unknown parameters and selecting important protein isoforms to improve predictive performance. Different types of shrinkage priors are evaluated to induce variable selection in a fully Bayesian framework. The approaches are studied with simulations. We apply the proposed method to real proteomics and lung‐function outcome data from our motivating CF study, identifying a set of relevant clinical/demographic predictors and a proteomic biomarker for rapid decline of lung function. We also illustrate the methods on CD4 yeast cell‐cycle genomic data, confirming that the proposed method identifies transcription factors that have been highlighted in the literature for their importance as cell cycle transcription factors.
Diversity of Coordination Architecture of Zinc Complexes with Diphenylarsinate
Authors: Chen Xiao , Hu Huijuan , Wang Shan , Li Biao , Wang Hongmei
Published: December 2021

The zinc complexes of diphenylarsinate [(Ph2AsO2)ZnCl] (1), [(Ph2AsO2)Zn(Ph2As(O)OH)Cl] (2) and [(Ph2AsO2)2Zn] (3) were prepared through the reaction of ZnCl2 with dihydroxodiphenylarsonium chloride [Ph2As(OH)2]Cl. Single‐crystal X‐ray diffraction analyses indicate that all three compounds form 1D polymer chain arrangements. Specifically, the [Ph2AsO2]− ligand coordinates with three Zn centres giving a syn,syn,anti μ3‐η1 : η2 mode in compound 1. A more diverse binding mode arised in compound 2: [Ph2AsO2]− shows a syn,anti μ2‐η1 : η1 bridging mode; while free ligand Ph2As(O)OH is bound to Zn through the oxygen atom of the As=O unit (monodentate). In addition, the hydrogen atom of Ph2As(O)OH forms a moderate hydrogen bond with the oxygen atom of [Ph2AsO2]−. Even though all [Ph2AsO2]− ligands also coordinate in a bridging mode in compound 3, a chain‐like arrangement with alternate single (anti,anti μ2‐η1 : η1) and triple (syn,syn μ2‐η1 : η1) bridging diphenylarsinate groups between tetrahedrally coordinated Zn atoms was identified.
miR‐141‐3p regulates saturated fatty acid‐induced cardiomyocyte apoptosis through Notch1/PTEN/AKT pathway via targeting PSEN1
Authors: Xin Xin , Duan Lian , Yang Huimin , Yu Hang , Bao Yandong , Jia Dalin , Wu Nan , Qiao Ying
Published: December 2021

It has been reported that miR‐141‐3p levels are markedly upregulated in the cardiomyocytes of obese rats induced by a high‐fat diet. However, the role of miR‐141‐3p in myocardial lipotoxicity remains elusive. In the present study, the role of miR‐141‐3p in lipotoxic injury of H9c2 cells induced by palmitic acid (PA) and its possible mechanisms were assessed. The results indicated that miR‐141‐3p was significantly upregulated in PA‐induced cardiomyocytes. miR‐141‐3p inhibitor enhanced the cell viability, reduced the release of lactate dehydrogenase (LDH), creatine kinase‐MB (CK‐MB), and troponin I (CTN‐I), decreased cell apoptosis rate, and repressed the activation of mitochondrial apoptosis pathway in PA‐treated H9c2, whereas treatment with miR‐141‐3p mimics resulted in the opposite effects. Mechanistically, it was further revealed that miR‐141‐3p could specifically bind to presenilin 1 (PSEN1) 3′UTR, and upregulating miR‐141‐3p levels reduced the expression of PSEN1, thereby inhibiting the activation of the Notch1/PTEN/AKT pathway. Additionally, inhibition of Notch1/AKT signaling pathway by its inhibitor could abrogate the effect of miR‐141‐3p on mitochondrial‐mediated apoptosis induced by PA. In conclusion, the present study demonstrates that miR‐141‐3p regulates saturated fatty acid‐induced cardiomyocyte apoptosis through Notch1/PTEN/AKT pathway via targeting PSEN1, which gains a new insight into the mechanisms of myocardial lipotoxic injury.
Nasolacrimal duct disease secondary to an unerupted tooth in a dog
Authors: Bach Ana , Parry Andrew , de Lacerda Rodrigo Pinheiro , Gomez Alberto Palella
Published: December 2021

A 5‐year‐old male neutered Lurcher was evaluated for left‐sided epiphora of 4 months’ duration and persistence following topical treatment and nasolacrimal duct irrigation. Physical examination revealed a missing left maxillary canine tooth, and CT dacryocystorhinography showed extrinsic compression of the left lacrimal duct and adjacent nasal turbinates caused by an impacted maxillary canine tooth. Further irrigation was successful in clearing debris from the nasolacrimal duct and temporarily relieving the patient of epiphora; however, surgical extraction of the tooth and radiographic monitoring was declined by the owner. Ophthalmic disorders may be secondary to overlooked dental conditions. This case describes the importance of inspecting the oral cavity as part of a general physical examination when presented with ocular signs, as well as assessing impacted teeth for evidence of pathology, and being aware of sequelae to dental impaction when advising clients on case management.
Acoustic Exposure to Turbine Operation Quantifies Risk to Bats at Commercial Wind Energy Facilities
Authors: Peterson Trevor S. , Mcgill Brian , Hein Cris D. , Rusk Adam
Published: December 2021

Turbine‐related bat mortality at commercial wind energy facilities may threaten populations of migratory tree‐roosting bat species in North America. Industry stakeholders and regulatory agencies alike are investigating strategies to reduce risk of population‐level consequences as the wind energy industry grows. Bats collide with turbines only when turbine rotors are spinning and curtailing turbine operation at low wind speeds can effectively reduce bat fatality rates. Nonetheless, few quantitative data exist to determine appropriate threshold wind speeds below which turbine operations should be curtailed. Carcass monitoring is labor‐intensive and does not provide information on factors linked to bat fatality rates on any scale finer than nightly. We tested whether acoustic bat data recorded at turbine nacelles could provide a more precise and sensitive measure of fatality risk to bats by analyzing acoustics, weather, turbine operation, and carcass data collected at 2 commercial wind energy facilities in West Virginia over 7 years. Each wind facility implemented several distinct curtailment treatments during our study, allowing us to compare fatality rates and acoustic bat activity across multiple operational strategies. We found that bat passes exposed to turbine operation explained close to 80% of the variation in carcass‐based estimates of bat fatality rates and accounted for significant variation in raw carcass counts per turbine and probability of finding bat carcasses during individual turbine searches. Conversely, bat activity occurring when turbines were not operating had little or no relationship to fatality rates. We also found that patterns in bat activity exposure could be predicted accurately among turbines and years. Our results demonstrate that measuring exposure of acoustic bat activity provides a quantitative basis for designing, evaluating, and adaptively managing curtailment strategies. This is an important advance towards using curtailment to reduce bat fatality rates strategically while allowing for increased generation of renewable energy. © 2021 The Authors. Wildlife Society Bulletin published by Wiley Periodicals LLC on behalf of The Wildlife Society.
Drivers of the Formalization of Banking Supervision
Authors: Hotori Eiji , Wendschlag Mikael , Giddey Thibaud
Published: December 2021

In this chapter, the drivers of the formalization of banking supervision are examined from seven perspectives: (a) charter requirements, (b) banknote issuance, (c) liability rules, (d) ensuring the public’s trust, (e) financial crises, (f) economic control, and (g) financial globalization. Our analysis shows that formalization occurred in response to the shifting needs of the time/era and that the formalization process was basically incremental. Notably, financial crises, which are generally considered to be the primary drivers of major regulatory and supervisory reforms, did not always play a leading role in the formalization of banking supervision. It should also be noted that from a historical perspective, regulation and supervision were not “natural” responses to a dysfunctional banking system. Rather, the formalization of banking supervision was the product of complex political actions negotiated by relevant stakeholders with divergent interests in a specific social, political, and economic environment.
Ethical problems in the use of algorithms in data management and in a free market economy
Authors: Szopa Rafał
Published: December 2021

The problem that I present in this paper concerns the issue of ethical evaluation of algorithms, especially those used in social media and which create profiles of users of these media and new technologies that have recently emerged and are intended to change the functioning of technologies used in data management. Systems such as Overton, SambaNova or Snorkel were created to help engineers create data management models, but they are based on different assumptions than the previous approach in machine learning and deep learning. There is a need to analyze both deep learning algorithms and new technologies in database management in terms of their actions towards a person who leaves their digital footprints, on which these technologies work. Then, the possibilities of applying the existing deep learning technology and new Big Data systems in the economy will be shown. The opportunities offered by the systems mentioned above seem to be promising for many companies and—if implemented on a larger scale—they will affect the functioning of the free market.
Extent, pattern, and prognostic value of MGMT promotor methylation: does it differ between glioblastoma and IDH-wildtype/TERT-mutated astrocytoma?
Authors: Teske Nico , Karschnia Philipp , Weller Jonathan , Siller Sebastian , Dorostkar Mario M. , Herms Jochen , von Baumgarten Louisa , Tonn Joerg Christian , Thon Niklas
Published: December 2021

Introduction

The cIMPACT-NOW update 6 first introduced glioblastoma diagnosis based on the combination of IDH-wildtype (IDHwt) status and TERT promotor mutation (pTERTmut). In glioblastoma as defined by histopathology according to the WHO 2016 classification, MGMT promotor status is associated with outcome. Whether this is also true in glioblastoma defined by molecular markers is yet unclear.

Methods

We searched the institutional database for patients with: (1) glioblastoma defined by histopathology; and (2) IDHwt astrocytoma with pTERTmut. MGMT promotor methylation was analysed using methylation-specific PCR and Sanger sequencing of CpG sites within the MGMT promotor region.

Results

We identified 224 patients with glioblastoma diagnosed based on histopathology, and 54 patients with IDHwt astrocytoma with pTERTmut (19 astrocytomas WHO grade II and 38 astrocytomas WHO grade III). There was no difference in the number of MGMT methylated tumors between the two cohorts as determined per PCR, and also neither the number nor the pattern of methylated CpG sites differed as determined per Sanger sequencing. Progression-free (PFS) and overall survival (OS) was similar between the two cohorts when treated with radio- or chemotherapy. In both cohorts, higher numbers of methylated CpG sites were associated with favourable outcome.

Conclusions

Extent and pattern of methylated CpG sites are similar in glioblastoma and IDHwt astrocytoma with pTERTmut. In both tumor entities, higher numbers of methylated CpG sites appear associated with more favourable outcome. Evaluation in larger prospective cohorts is warranted.
Prediction of critical liquid loading time for water-producing gas wells: Effect of liquid drop rotation
Authors: Chongyang Xiao , Heng Fu , Leli Cheng , Wenyu Pei
Published: December 2021

After more than 20 years of continuous development, part of the wells in the Moxilei-1 gas reservoir located at the Sichuan Basin have entered the middle–later production stage. With the continuous decline in formation pressure and production rates, some of the gas wells have entered the potential period of liquid loading, while some have already suffered water plugging. Currently, the field engineers usually carry out some corresponding drainage measures after the occurrence of liquid loading in the gas well, which will first affect the production progress of the gas field, then increase the difficulty in drainage and reduce the drainage effect afterward. On the basis of Pan’s model for evaluating critical liquid-carrying flow rate, the influence of liquid drop rotation was considered in the new model. Further, combined with the Arps production decline equation, a prediction model of liquid loading timing was deduced. Taking a typical well in the Moxilei-1 gas reservoir as an example, based on the early-stage production data of the gas well, the model was used to predict the liquid loading timing accurately. The model can predict the possibility and timing of liquid loading in gas wells at different production stages. It can check the gas wells with potential liquid loading, so as to reduce the workload for field workers. Furthermore, it can predict the potential liquid accumulation and its timing in advance, so as to guide the field workers to prepare for drainage in advance.
Decomposition approaches for parallel machine scheduling of step-deteriorating jobs to minimize total tardiness and energy consumption
Authors: Wu Xiao , Guo Peng , Wang Yi , Wang Yakun
Published: December 2021

In this paper, an identical parallel machine scheduling problem with step-deteriorating jobs is considered to minimize the weighted sum of tardiness cost and extra energy consumption cost. In particular, the actual processing time of a job is assumed to be a step function of its starting time and its deteriorating threshold. When the starting time of a job is later than its deteriorating threshold, the job faces two choices: (1) maintaining its status in holding equipment and being processed with a base processing time and (2) consuming an extra penalty time to finish its processing. The two work patterns need different amounts of energy consumption. To implement energy-efficient scheduling, the selection of the pre-processing patterns must be carefully considered. In this paper, a mixed integer linear programming (MILP) model is proposed to minimize the total tardiness cost and the extra energy cost. Decomposition approaches based on logic-based Benders decomposition (LBBD) are developed by reformulating the studied problem into a master problem and some independent sub-problems. The master problem is relaxed by only making assignment decisions. The sub-problems are to find optimal schedules in the job-to-machine assignments given by the master problem. Moreover, MILP and heuristic based on Tabu search are used to solve the sub-problems. To evaluate the performance of our methods, three groups of test instances were generated inspired by both real-world applications and benchmarks from the literature. The computational results demonstrate that the proposed decomposition approaches can compute competitive schedules for medium- and large-size problems in terms of solution quality. In particular, the LBBD with Tabu search performs the best among the suggested four methods.
A Novel Binary Slime Mould Algorithm with AU Strategy for Cognitive Radio Spectrum Allocation
Authors: Li Ling , Pan Tien-Szu , Sun Xiao-Xue , Chu Shu-Chuan , Pan Jeng-Shyang
Published: December 2021

Spectrum has now become a scarce resource due to the continuous development of wireless communication technology. Cognitive radio technology is considered to be a new method to solve the shortage of spectrum resources. The spectrum allocation model of cognitive radio can effectively avoid the waste of spectrum resources. A novel binary version of slime mould algorithm is proposed for the spectrum allocation model to solve the spectrum allocation scheme. In addition, adding unselected factors strategy can make the approach find a better solution. Compared with other algorithms, the novel binary slime mould algorithm and the strategy of adding unselected factors proposed in this paper have a good performance in spectrum allocation. The resulting spectrum allocation scheme can achieve efficient use of network resources.
Research on the Minimum Size of Received Signal Strength Difference Localization Network
Authors: Ma Fangli , Xu Yang , Xu Peng
Published: December 2021

The received signal strength difference (RSSD) localization is a kind of method to locate emission sources by measuring the differences of received signal strength level between the monitoring stations and is essentially the truth value ratios of measured signal strength. In the existing literatures, only the rule of RSSD localization circle of two monitoring stations and the geometric relation of RSSD localization circle of five monitoring stations were analyzed, but the number and the station layout of the minimum RSSD localization network have not been investigated. In the present work, first, based on the existing RSSD localization equation, the constants of the commonly used wave propagation models are provided. Then, the minimum RSSD localization network is proved through algebraic analysis, which is that four monitoring stations not distributed on a straight line can locate the signal source at one point. The relationship between the localization accuracy and the signal strength error of the RSSD location network with different scales is studied further and formulated as a nonlinear programming optimization problem. It is found that the localization stability of the network with four stations is poor, and there is a serious localization deviation outlier phenomenon. Therefore, the network with four stations is not available for radio monitoring networks with a signal strength error of ± 5 to  ± 10 dB. The RSSD network with five stations is basically the minimum available size, and the RSSD network with nine stations can approach the localization accuracy of the angle of arrival (AOA) network with three stations.
Evolutionary Social Poisson Factorizationfor Temporal Recommendation
Authors: Yin ChunYan , Chen YongHeng , Zuo Wanli
Published: December 2021

Preference-based recommendation systems analyze user-item interactions to reveal latent factors that explain our latent preferences for items and form personalized recommendations based on the behavior of others with similar tastes. Most of the works in the recommendation systems literature have been developed under the assumption that user preference is a static pattern, although user preferences and item attributes may be changed through time. To achieve this goal, we develop an Evolutionary Social Poisson Factorization (EPF$$\_$$
_
Social) model, a new Bayesian factorization model that can effectively model the smoothly drifting latent factors using Conjugate Gamma–Markov chains. Otherwise, EPF$$\_$$
_
Social can obtain the impact of friends on social network for user’ latent preferences. We studied our models with two large real-world datasets, and demonstrated that our model gives better predictive performance than state-of-the-art static factorization models.
A New X-bar Control Chart for Multiple Dependent State Sampling Using Neutrosophic Exponentially Weighted Moving Average Statistics with Application to Monitoring Road Accidents and Road Injuries
Authors: Khan Nasrullah , Ahmad Liaquat , Rao G. Srinivasa , Aslam Muhammad , AL-Marshadi Ali Hussein
Published: December 2021

In this article, an efficient mean chart for symmetric data have been presented for multiple dependent state (MDS) sampling using neutrosophic exponentially weighted moving average (NEWMA) statistics. The existing neutrosophic exponentially weighted moving average charts are not capable of seizure the unusual changes threatened to the manufacturing processes. The control chart coefficients have been estimated using the symmetry property of the Gaussian distribution for the uncertain environment. The neutrosophic Monte Carlo simulation methodology has been developed to check the efficiency and performance of the proposed chart by calculating the neutrosophic average run lengths and neutrosophic standard deviations. The proposed chart has been compared with the counterpart charts for confirmation of the proposed technique and found to be a robust chart.
SCMFTS: Scalable and Distributed Complexity Measures and Features for Univariate and Multivariate Time Series in Big Data Environments
Authors: Baldán Francisco J. , Peralta Daniel , Saeys Yvan , Benítez José M.
Published: December 2021

Time series data are becoming increasingly important due to the interconnectedness of the world. Classical problems, which are getting bigger and bigger, require more and more resources for their processing, and Big Data technologies offer many solutions. Although the principal algorithms for traditional vector-based problems are available in Big Data environments, the lack of tools for time series processing in these environments needs to be addressed. In this work, we propose a scalable and distributed time series transformation for Big Data environments based on well-known time series features (SCMFTS), which allows practitioners to apply traditional vector-based algorithms to time series problems. The proposed transformation, along with the algorithms available in Spark, improved the best results in the state-of-the-art on the Wearable Stress and Affect Detection dataset, which is the biggest publicly available multivariate time series dataset in the University of California Irvine (UCI) Machine Learning Repository. In addition, SCMFTS showed a linear relationship between its runtime and the number of processed time series, demonstrating a linear scalable behavior, which is mandatory in Big Data environments. SCMFTS has been implemented in the Scala programming language for the Apache Spark framework, and the code is publicly available.
Enhanced Tunicate Swarm Algorithm for Solving Large-Scale Nonlinear Optimization Problems
Authors: Rizk-Allah Rizk M. , Saleh O. , Hagag Enas A. , Mousa Abd Allah A.
Published: December 2021

Nowadays optimization problems become difficult and complex, traditional methods become inefficient to reach global optimal solutions. Meanwhile, a huge number of meta-heuristic algorithms have been suggested to overcome the shortcomings of traditional methods. Tunicate Swarm Algorithm (TSA) is a new biologically inspired meta-heuristic optimization algorithm which mimics jet propulsion and swarm intelligence during the searching for a food source. In this paper, we suggested an enhancement to TSA, named Enhanced Tunicate Swarm Algorithm (ETSA), based on a novel searching strategy to improve the exploration and exploitation abilities. The proposed ETSA is applied to 20 unimodal, multimodal and fixed dimensional benchmark test functions and compared with other algorithms. The statistical measures, error analysis and the Wilcoxon test have affirmed the robustness and effectiveness of the ETSA. Furthermore, the scalability of the ETSA is confirmed using high dimensions and results exhibited that the ETSA is least affected by increasing the dimensions. Additionally, the CPU time of the proposed algorithms are obtained, the ETSA provides less CPU time than the others for most functions. Finally, the proposed algorithm is applied at one of the important electrical applications, Economic Dispatch Problem, and the results affirmed its applicability to deal with practical optimization tasks.
Edge Computing Using Embedded Webserver with Mobile Device for Diagnosis and Prediction of Metastasis in Histopathological Images
Authors: Johny Anil , Madhusoodanan K. N.
Published: December 2021

Diagnosis of different breast cancer stages using histopathology whole slide images is the gold standard in grading the tissue metastasis. Traditional diagnosis involves labor intensive procedures and is prone to human errors. Computer aided diagnosis assists medical experts as a second opinion tool in early detection which prevents further proliferation. Computing facilities have emerged to an extent where algorithms can attain near human accuracy in prediction of diseases, offering better treatment to curb further proliferation. The work introduced in the paper provides an interface in mobile platform, which enables the user to input histopathology image and obtain the prediction results with its class probability through embedded web-server. The trained deep convolutional neural networks model is deployed into a microcomputer-based embedded system after hyper-parameter tuning, offering congruent performance. The implementation results show that the embedded platform with custom-trained CNN model is suitable for medical image classification, as it takes less execution time and mean prediction time. It is also noticed that customized CNN classifier model outperforms pre-trained models when used in embedded platforms for prediction and classification of histopathology images. This work also emphasizes the relevance of portable and flexible embedded device in real time clinical applications.
Easy Access to Antibiotics; Spread of Antimicrobial Resistance and Implementation of One Health Approach in India
Authors: Jani Kunal , Srivastava Vibhaw , Sharma Preeti , Vir Aruna , Sharma Avinash
Published: December 2021

Antimicrobial resistance (AMR) is a global public health concern because of its fast spread. India, one of the world’s top consumer of antibiotics and second most populated country has its unique constraints of social, cultural and economic strata. The continual self-medication, use of antibiotics for the growth promotion in animals, and accumulation of residual antibiotics in the environment challenge the implementation of AMR containment policy. Hence, the present review attempts to delineate the influence of antibiotics abuse on the human, animal and environmental health under the realm of one health. It was based on the literature search using public databases to highlight the rapid surge in the burden of AMR in India affecting various sectors and/or ecosystems in India. It was found that the irrational and overuse of antibiotics in different sectors have led to the emergence of extended antimicrobial resistance wherein the environment acts as a reservoir of antibiotic resistance genes (ARGs); completing the cycle of contamination and recontamination. There are efforts by government policy makers to reduce the burden of AMR in the country to reduce the health risks, through the One Health approach. Parallel efforts in educating healthcare professionals, strict legislation for pharmacies and pharmaceutical companies should be prioritize. At the same time surveillance of newly emerged AMR pathogens, prioritising research focusing on AMR, and awareness camps or programs among the local population is critical while addressing the consequences of spared of AMR in India.
Using Model Selection Criteria to Choose the Number of Principal Components
Authors: Sclove Stanley L.
Published: December 2021

The use of information criteria, especially AIC (Akaike’s information criterion) and BIC (Bayesian information criterion), for choosing an adequate number of principal components is illustrated.
A Test for Multiple Binary Endpoints with Continuous Latent Distribution in Clinical Trials
Authors: Ishihara Takuma , Yamamoto Kouji
Published: December 2021

In clinical trials, two or more binary responses obtained by dichotomizing continuous responses are often employed as multiple primary endpoints. Testing procedures for multiple binary variables with latent distribution have not yet been adequately discussed. Based on the association measure among latent variables, we provide a statistic for testing the superiority of at least one binary endpoint. In addition, we propose a testing procedure with a framework in which the trial efficacy is confirmed only when there is superiority of at least one endpoint and non-inferiority of the remaining endpoints. The performance of the proposed procedure is evaluated through simulations.
Current antimicrobial prescription at outpatient dentistry centers and clinics in tertiary-care hospitals in Tokyo, Japan: A multicenter cross-sectional study
Authors: Tagashira Yasuaki , Horiuchi Masao , Kosaka Atsushi , Washino Takuya , Horiuchi Mikihiro , Murakami Shutaro , Tagashira Itoe , Honda Hitoshi
Published: December 2021

Background:

Antimicrobial administration is necessary before specific dental procedures to prevent postprocedural infections and complications and antimicrobials are sometimes indicated for the treatment of odontogenic infections. However, antimicrobials are commonly misused by dentists.

Methods:

This cross-sectional study was conducted at 4 public, tertiary-care hospitals in Tokyo, Japan, from June to July 2019. We included patients who received an antimicrobial prescription at the outpatient dentistry center or clinic at each participating hospital. The indications for antimicrobial prescription were (1) antimicrobial prescriptions for prophylaxis (APPs) or (2) antimicrobial prescriptions for treatment (APTs). Prescribing patterns were described in terms of antimicrobial choice, timing, and dosages for APPs and APTs.

Results:

During the study period, 1,772 patients received an antimicrobial prescription. Among them 1,439 (81.2%) were APPs and 333 (18.8%) were APTs. The most common aim of APP was to prevent local infections and complications following tooth extraction (n = 1,244, 86.4%). The proportion of appropriate APPs was only 0.8% (12 of 1,439). Among 1,439 total APPs, 171 (11.9%) were unnecessary, 32 (2.2%) were inappropriate, and 1,224 (85.1%) were suboptimal. Whereas 101 (30.3%) of 333 APTs were appropriate, the remaining 97 instances (29.1%) were unnecessary, 86 (26.7%) were inappropriate, and 46 (13.8%) were suboptimal.

Conclusion:

Inappropriate antimicrobial prescriptions were common among dentists in Japan. Understanding the differences in the current antimicrobial prescribing patterns for prophylaxis and treatment is critically important for implementing an effective antimicrobial stewardship program in dentistry.
Atypical symptom reporting after mild traumatic brain injury
Authors: Sullivan Karen , Keyter Anna , Jones Kelly , Ameratunga Shanthi , Starkey Nicola , Barker-Collo Suzanne , Webb James , Theadom Alice
Published: December 2021

Objective:

Early reporting of atypical symptoms following a mild traumatic brain injury (mTBI) may be an early indicator of poor prognosis. This study aimed to determine the percentage of people reporting atypical symptoms 1-month post-mTBI and explore links to recovery 12 months later in a community-dwelling mTBI sample.

Methods:

Adult participants (>16 years) who had experienced a mTBI were identified from a longitudinal incidence study (BIONIC). At 1-month post-injury, 260 participants completed the Rivermead Post-Concussion Symptoms Questionnaire (typical symptoms) plus four atypical symptom items (hemiplegia, difficulty swallowing, digestion problems and difficulties with fine motor tasks). At 12 months post-injury, 73.9% (n = 193) rated their overall recovery on a 100-point scale. An ordinal regression explored the association between atypical symptoms at 1 month and recovery at 12 months post-injury (low = 0–80, moderate = 81–99 and complete recovery = 100), whilst controlling for age, sex, rehabilitation received, ethnicity, mental and physical comorbidities and additional injuries sustained at the time of injury.

Results:

At 1-month post-injury <1% of participants reported hemiplegia, 5.4% difficulty swallowing, 10% digestion problems and 15.4% difficulties with fine motor tasks. The ordinal regression model revealed atypical symptoms were not significant predictors of self-rated recovery at 12 months. Older age at injury and higher typical symptoms at 1 month were independently associated with poorer recovery at 12 months, p < 0.01.

Conclusion:

Atypical symptoms on initial presentation were not linked to global self-reported recovery at 12 months. Age at injury and typical symptoms are stronger early indicators of longer-term prognosis. Further research is needed to determine if atypical symptoms predict other outcomes following mTBI.
Anthelmintic activity ofStevia multiaristataextract againstEchinococcus granulosus sensu stricto
Authors: Albani C. M. , Borgo J. , Fabbri J. , Pensel P. , Fasciani L. , Elso O. , Papademetrio D. , Grasso D. , Paladini A. , Beer M. F. , Farias N. E. , Elissondo N. , Gambino G. , Zoppi J. , Sülsen V. , Elissondo M. C.
Published: December 2021

Cystic echinococcosis is a zoonotic disease caused by the larval stage of the parasiteEchinococcus granulosus sensu lato. The available anti-parasitic treatment is mostly limited to a continuous administration of albendazole. However, due to its numerous side-effects and efficacy of around 50%, there is a need to find new drugs to improve the treatment for this disease. In the current study, thein vitroandin vivoefficacy of aStevia multiaristataextract againstE. granulosus sensu stricto(s.s.) was demonstrated.Stevia multiaristataextract (100 and 50μg mL−1) caused a quick viability decrease on protoscoleces which was consistent with the observed tegumental alterations. Loss of turgidity was detected in 95 ± 3.4% of cysts incubated withS. multiaristataextract during 2 days (100μg mL−1) and the collapse of the germinal layer was observed in 60 ± 9.3% of cysts treated with 100μg mL−1of theS. multiaristataextract during 4 days. The half maximal effective concentration value was 69.6μg mL−1and the selectivity index forE. granulosus s.s.cysts was 1.9. In this clinical efficacy study, the treatment of infected mice with theS. multiaristataextract (50 mg kg−1) caused a significant decrease in the weight of the cysts compared with the control group. These results coincided with the tissue damage observed in the cysts at the ultrastructural level. In conclusion, we observed high protoscolicidal and cysticidal effects, and significant reduction in the weight of the cysts in experimentally infected mice following treatment with theS. multiaristataextract.
At-Home Humbugs: Freaks and Fakes in the Nineteenth-Century Parlor Museum
Authors: D'Alessandro Michael
Published: December 2021

In April 1885, aNew York Heraldjournalist rushed to Madison Square Garden for a special reception highlighting Jo-Jo, the Dog-Faced Boy. A feature of P. T. Barnum's traveling show, Jo-Jo was confounding scientists who had requested a stand-alone inspection of the mysterious attraction. Accordingly, the reporter provided an anthropological description of the boy: “He stands about five feet high. . . . His whole body is covered by a very thick growth of long, tow colored hair . . . and the peculiar formation of his head [is] very suggestive of the Russian dachshund.” At first, Jo-Jo appeared docile, but as the scientists prodded him more and more, he started “snarling, showing his three canine teeth” and asked his guardian if he could bite the inspectors. Jo-Jo was decidedly not a dog-boy, or not exactly. He was, in fact, a Russian teenager suffering from hypertrichosis, a condition causing excessive hair growth all over the body, including nearly every surface area of the face. Barnum had signed him to perform a year earlier, and the boy made quite an auspicious debut. However, Jo-Jo was simply the latest in a long line of supposed hybrid species and exotic curiosities that Barnum had been displaying since midcentury. The famed showman built his name in part by presenting human creation itself as a continual spectrum. Barnum's attractions ranged from live tigers and giraffes to enigmatic simian performers to wax statues of America's degraded lower classes. As much of a draw as he became, even Jo-Jo had to share a bill with Tattooed Hindoo Dwarfs, Hungarian Gypsies, Buddhist Priests, as well as a menagerie of animals including baby elephants, kangaroos, lions, and twenty-foot-long “great sinewy serpents.” But Jo-Jo's specific appeal was tied to his inexplicability. Even given the closer inspection of the dog-faced boy, “none of the physicians present would hazard an opinion as to his ancestry.”
Two multistate outbreaks of a reoccurring Shiga toxin-producing Escherichia coli strain associated with romaine lettuce: USA, 2018–2019
Authors: Waltenburg Michelle A. , Schwensohn Colin , Madad Asma , Seelman Sharon L. , Peralta Vi , Koske Sarah E. , Boyle Michelle M. , Arends Katherine , Patel Kane , Mattioli Mia , Gieraltowski Laura , Neil Karen P. ,   Outbreak Investigation Team
Published: December 2021

Leafy green vegetables are a common source of Shiga toxin-producing Escherichia coli O157:H7 (STEC O157) foodborne illness outbreaks. Ruminant animals, primarily cattle, are the major reservoir of STEC O157. Epidemiological, traceback and field investigations were conducted to identify potential outbreak sources. Product and environmental samples were tested for STEC. A reoccurring strain of STEC O157 caused two multistate outbreaks linked to romaine lettuce in 2018 and 2019, resulting in 234 illnesses in 33 states. Over 80% of patients interviewed consumed romaine lettuce before illness. The romaine lettuce was sourced from two California growing regions: Santa Maria and Salinas Valley in 2018 and Salinas Valley in 2019. The outbreak strain was isolated from environmental samples collected at sites >90 miles apart across growing regions, as well as from romaine-containing products in 2019. Although the definitive route of romaine contamination was undetermined, use of a contaminated agricultural water reservoir in 2018 and contamination from cattle grazing on adjacent land in 2019 were suspected as possible factors. Preventing lettuce contamination from growth to consumption is imperative to preventing illness. These outbreaks highlight the need to further understand mechanisms of romaine contamination, including the role of environmental or animal reservoirs for STEC O157.
Contextual risks, child problem-solving profiles, and socioemotional functioning: Testing the specialization hypothesis
Authors: Li Zhi , Sturge-Apple Melissa L. , Davies Patrick T.
Published: December 2021

Guided by the evolutionary perspective and specialization hypothesis, this multi-method (behavioral observation, questionnaire) longitudinal study adopted a person-centered approach to explore children’s problem-solving skills within different contexts. Participants were 235 young children (M age = 2.97 years at the first measurement occasion) and their parents assessed in two measurement occasions spaced one year apart. Latent profile analyses revealed four unique problem-solving profiles, capturing variability in children’s performance, and observed engagement in abstract vs. reward-oriented (RO) problem-solving tasks at wave one. The four profiles included: (a) a high-abstract-high-RO, (b) a high-abstract-low-RO, (c) a low-abstract-high-RO, and (d) a low-abstract-low-RO classes. Contextual risks within and outside families during wave one, including greater neighborhood crime, impoverishment, and observed lower maternal sensitivity were linked to the elevated likelihood for children from the two profiles with low-abstract problem-solving, particularly those from the low-abstract-high-RO problem-solving profile. Furthermore, child problem-solving profiles were linked to meaningful differences in their socioemotional functioning one year later. The present finding has important implications in revealing the heterogeneity in child problem-solving within different contexts that responded differently to contextual risks. In addition, this study advanced the understanding of the developmental implications of child problem-solving capacity.
Status and habitat description of the globally threatened Udzungwa Forest PartridgeXenoperdix udzungwensisthirty years after discovery
Authors: DINESEN LARS , JENSEN FLEMMING PAGH , SONNE JESPER , LEVINSKY IRINA , MULUNGU ELIA
Published: December 2021

The Udzungwa Forest PartridgeXenoperdix udzungwensiswas discovered in 1991 in the geologically old and eco-climatically stable Udzungwa Mountains (hereafter the Udzungwas) in Tanzania - a global biodiversity hotspot in the Eastern Arc Mountains of East Africa. The partridge is categorised as globally ‘Endangered’ and this study aims at assessing its population status and habitat requirements in the two separate montane forests where it was discovered c.30 years ago and for the first time using systematic playback technique. We estimate the partridge population at c.2,800 individuals (1,680–3,860) confined to less than 150 km2and now confined to a single forest and with a clearly declining distribution within the last few decades since its discovery. The species is confined to evergreen closed (semi-closed) canopy forest habitat with leaf litter and sedges on the forest floor for feeding and cover. The partridge has become an emblem for the high concentration of endemic species of the Udzungwa Mountains National Park. At the same time there is a risk that this species could go extinct without notice if the Tanzanian authorities do not tackle two envisaged main drivers, namely fragmentation of the evergreen forest area over the last few centuries and current illegal hunting. Hence it seems crucial to allow natural expansion of its forest habitat in the Udzungwas and to eliminate hunting in the other forest within its recently known distribution where the population has presumably been extirpated. The partridge is remarkable as its closest relatives are in South-east Asia and it is used as a flagship species for the Udzungwas, which has one of the highest concentrations of endemic species on earth.
Importation of plastic fragments into a seabird colony: accident or design, threat or benign?
Authors: VAN DE CROMMENACKER JANSKE , SOARES JOANNA H. , LAROSE CHRISTINE S. , FEARE CHRIS J.
Published: December 2021

Plastic pollution affects marine ecosystems worldwide and poses risks for seabirds. Most recorded impacts on organisms are negative but, in some cases, the constructive use of plastic fragments or objects by birds has also been recorded. Small blue and green plastic fragments are found scattered among nests in a large (c.500,000 pairs) Sooty Tern Onychoprion fuscatus nesting colony on Bird Island, Seychelles. We investigated whether the fragments were being imported by the birds, and if so whether import was accidental or intentional. We found that Sooty Terns were the only seabird species to have plastic fragments in their nesting area and import of fragments varied seasonally and spatially. Throughout the colony, plastic fragments were imported during egg-laying, incubation, and chick-rearing, but import declined as chicks began to fledge. A part of the colony where all eggs were harvested for human consumption received more fragments than among undisturbed nests. We failed to find evidence of ingestion and excretion of fragments and suggest other avenues for investigation.
The Portuguese Hub of Companies in 1973 – Discussing the Corporate Concentration in the Portuguese Economy on the Eve of the April Revolution
Authors: Reis Mourao Paulo
Published: December 2021

The network of Portuguese companies in 1973 has been identified as a relevant element for understanding the economic structure of the country in the decade of 1970–1980. This network had been formed before 1974, during the dictatorship, but it remained after the Carnation Revolution. In spite of such research, this network has not yet been properly analysed, especially through adequate tools from network analysis. This work will detail this network, the different scores of centrality of each company, and their modular structures; it will also discuss estimates from exponential random graph models to identify significant attributes that explain the discovered flows of investment. This work will also detail the processes of vertical integration as well as the specificities of the identified oligopolies.