bluuebunny/crossref_metadata_2025 huggingface dataset:
Elle
Authors: Kingsbury Kyle , Alvaro Peter
Published: December 2021

Users who care about their data store it in databases, which (at least in principle) guarantee some form of transactional isolation. However, experience shows that many databases do not provide the isolation guarantees they claim. With the recent proliferation of new distributed databases, demand has grown for checkers that can, by generating client workloads and injecting faults, produce anomalies that witness a violation of a stated guarantee. An ideal checker would be sound (no false positives), efficient (polynomial in history length and concurrency), effective (finding violations in real databases), general (analyzing many patterns of transactions), and informative (justifying the presence of an anomaly with understandable counterexamples). Sadly, we are aware of no checkers that satisfy these goals.

We present Elle: a novel checker which infers an Adya-style dependency graph between client-observed transactions. It does so by carefully selecting database objects and operations when generating histories, so as to ensure that the results of database reads reveal information about their version history. Elle can detect every anomaly in Adya et al's formalism (except for predicates), discriminate between them, and provide concise explanations of each. This paper makes the following contributions: we present Elle, demonstrate its soundness over specific datatypes, measure its efficiency against the current state of the art, and give evidence of its effectiveness via a case study of four real databases.
Scotch
Authors: Kiefer Martin , Poulakis Ilias , Breß Sebastian , Markl Volker
Published: December 2021

Sketching algorithms are a powerful tool for single-pass data summarization. Their numerous applications include approximate query processing, machine learning, and large-scale network monitoring. In the presence of high-bandwidth interconnects or in-memory data, the throughput of summary maintenance over input data becomes the bottleneck. While FPGAs have shown admirable throughput and energy-efficiency for data processing tasks, developing FPGA accelerators requires a sophisticated hardware design and expensive manual tuning by an expert.

We propose Scotch, a novel system for accelerating sketch maintenance using FPGAs. Scotch provides a domain-specific language for the user-friendly, high-level definition of a broad class of sketching algorithms. A code generator performs the heavy-lifting of hardware description, while an auto-tuning algorithm optimizes the summary size. Our evaluation shows that FPGA accelerators generated by Scotch outperform CPU- and GPU-based sketching by up to two orders of magnitude in terms of throughput and up to a factor of five in terms of energy efficiency.
EdgeDIPN
Authors: Guo Long , Hua Lifeng , Jia Rongfei , Fang Fei , Zhao Binqiang , Cui Bin
Published: December 2021

With the rapid growth of e-commerce in recent years, e-commerce platforms are becoming a primary place for people to find, compare and ultimately purchase products. To improve online shopping experience for consumers and increase sales for sellers, it is important to understand user intent accurately and be notified of its change timely. In this way, the right information could be offered to the right person at the right time. To achieve this goal, we propose a unified deep intent prediction network, named EdgeDIPN, which is deployed at the edge, i.e., mobile device, and able to monitor multiple user intent with different granularity simultaneously in real-time. We propose to train EdgeDIPN with multi-task learning, by which EdgeDIPN can share representations between different tasks for better performance and saving edge resources in the meantime. In particular, we propose a novel task-specific attention mechanism which enables different tasks to pick out the most relevant features from different data sources. To extract the shared representations more effectively, we utilize two kinds of attention mechanisms, where the multi-level attention mechanism tries to identify the important actions within each data source and the inter-view attention mechanism learns the interactions between different data sources. In the experiments conducted on a large-scale industrial dataset, EdgeDIPN significantly outperforms the baseline solutions. Moreover, EdgeDIPN has been deployed in the operational system of Alibaba. Online A/B testing results in several business scenarios reveal the potential of monitoring user intent in real-time. To the best of our knowledge, EdgeDIPN is the first full-fledged real-time user intent understanding center deployed at the edge and serving hundreds of millions of users in a large-scale e-commerce platform.
Multi-modal transportation recommendation with unified route representation learning
Authors: Liu Hao , Han Jindong , Fu Yanjie , Zhou Jingbo , Lu Xinjiang , Xiong Hui
Published: December 2021

Multi-modal transportation recommendation aims to provide the most appropriate travel route with various transportation modes according to certain criteria. After analyzing large-scale navigation data, we find that route representations exhibit two patterns: spatio-temporal autocorrelations within transportation networks and the semantic coherence of route sequences. However, there are few studies that consider both patterns when developing multi-modal transportation systems. To this end, in this paper, we study multi-modal transportation recommendation with unified route representation learning by exploiting both spatio-temporal dependencies in transportation networks and the semantic coherence of historical routes. Specifically, we propose to unify both dynamic graph representation learning and hierarchical multi-task learning for multi-modal transportation recommendations. Along this line, we first transform the multi-modal transportation network into time-dependent multi-view transportation graphs and propose a
spatiotemporal graph neural network
module to capture the spatial and temporal autocorrelation. Then, we introduce a
coherent-aware attentive route representation learning
module to project arbitrary-length routes into fixed-length representation vectors, with explicit modeling of route coherence from historical routes. Moreover, we develop a
hierarchical multi-task learning
module to differentiate route representations for different transport modes, and this is guided by the final recommendation feedback as well as multiple auxiliary tasks equipped in different network layers. Extensive experimental results on two large-scale real-world datasets demonstrate the performance of the proposed system outperforms eight baselines.
Toward a better understanding and evaluation of tree structures on flash SSDs
Authors: Didona Diego , Ioannou Nikolas , Stoica Radu , Kourtis Kornilios
Published: December 2021

Solid-state drives (SSDs) are extensively used to deploy persistent data stores, as they provide low latency random access, high write throughput, high data density, and low cost. Tree-based data structures are widely used to build persistent data stores, and indeed they lie at the backbone of many of the data management systems used in production and research today.

We show that benchmarking a persistent tree-based data structure on an SSD is a complex process, which may easily incur subtle pitfalls that can lead to an inaccurate performance assessment. At a high-level, these pitfalls stem from the interaction of complex software running on complex hardware. On the one hand, tree structures implement internal operations that have non-trivial effects on performance. On the other hand, SSDs employ firmware logic to deal with the idiosyncrasies of the underlying flash memory, which are well known to also lead to complex performance dynamics.

We identify seven benchmarking pitfalls using RocksDB and WiredTiger, two widespread implementations of an LSM-Tree and a B+Tree, respectively. We show that such pitfalls can lead to incorrect measurements of key performance indicators, hinder the reproducibility and the representativeness of the results, and lead to suboptimal deployments in production environments. We also provide guidelines on how to avoid these pitfalls to obtain more reliable performance measurements, and to perform more thorough and fair comparisons among different design points.
Receipt
Authors: Lakhotia Kartik , Kannan Rajgopal , Prasanna Viktor , De Rose Cesar A. F.
Published: December 2021

Tip decomposition is a crucial kernel for mining dense subgraphs in bipartite networks, with applications in spam detection, analysis of affiliation networks etc. It creates a hierarchy of vertex-induced subgraphs with varying densities determined by the participation of vertices in butterflies (2, 2-bicliques). To build the hierarchy, existing algorithms iteratively follow a
delete-update
(peeling) process: deleting vertices with the minimum number of butterflies and correspondingly updating the butterfly count of their 2-hop neighbors. The need to explore 2-hop neighborhood renders tip-decomposition computationally very expensive. Furthermore, the inherent sequentiality in peeling only minimum butterfly vertices makes derived parallel algorithms prone to heavy synchronization.

In this paper, we propose a novel parallel tip-decomposition algorithm - REfine CoarsE-grained Independent Tasks (RECEIPT) that relaxes the peeling order restrictions by partitioning the vertices into multiple independent subsets that can be concurrently peeled. This enables RECEIPT to simultaneously achieve a high degree of parallelism and dramatic reduction in synchronizations. Further, RECEIPT employs a hybrid peeling strategy along with other optimizations that drastically reduce the amount of wedge exploration and execution time.

We perform detailed experimental evaluation of RECEIPT on a shared-memory multicore server. It can process some of the largest publicly available bipartite datasets
orders of magnitude faster
than the state-of-the-art algorithms - achieving up to 1100× and 64× reduction in the number of thread synchronizations and traversed wedges, respectively. Using 36 threads, RECEIPT can provide up to 17.1× self-relative speedup.
Comprehensive and efficient workload compression
Authors: Deep Shaleen , Gruenheid Anja , Koutris Paraschos , Naughton Jeffrey , Viglas Stratis
Published: December 2021

This work studies the problem of constructing a representative workload from a given input analytical query workload where the former serves as an approximation with guarantees of the latter. We discuss our work in the context of workload analysis and monitoring. As an example, evolving system usage patterns in a database system can cause load imbalance and performance regressions which can be controlled by monitoring system usage patterns, i.e., a representative workload, over time. To construct such a workload in a principled manner, we formalize the notions of workload
representativity
and
coverage.
These metrics capture the intuition that the distribution of features in a compressed workload should match a target distribution, increasing representativity, and include common queries as well as outliers, increasing coverage. We show that solving this problem optimally is computationally hard and present a novel greedy algorithm that provides approximation guarantees. We compare our techniques to established algorithms in this problem space such as sampling and clustering, and demonstrate advantages and key trade-offs.
Investigating the relationship between linguistic changes in L2 writers’ paraphrasing, paraphrasing performance and L2 proficiency
Authors: Di Zhang Emily , Yu Shulin
Published: December 2021

While the typology of paraphrasing revolves around linguistic changes of paraphrasing, little is known about the importance of different types of linguistic changes and their relationship between paraphrasing performance and L2 proficiency. Empirical enquiry has focused on L2 writers’ inappropriate paraphrasing performance against the norm of L1 writer, which is problematic in that L2 and L1 writers displayed considerable variation in paraphrasing. The present study drew upon 202 Chinese EFL writers’ written responses in a paraphrasing test to look into the discrete linguistic transformations in paraphrasing and examine how the frequency of different linguistic changes in paraphrasing relates to their paraphrasing performance and L2 proficiency. Correlation analysis was run to analyze the relationship between the frequency of linguistic changes and paraphrasing performance. Multivariate analysis of variance analysis was conducted to examine how the frequency of linguistic changes relates to L2 proficiency. The findings revealed that Conceptual Transformation had the highest significant correlation with paraphrasing scores, followed by Lexical Transformation and then Syntactic Transformation. The frequency of Synonym Substitution, Morphology, Multiple Word Units, Phrase/Clause Shift, Active/Passive Shift and Conceptual Transformation increased as L2 writers’ proficiency levels increased. Implications are drawn from the findings for paraphrasing instruction and assessment, research in paraphrasing and L2 writers’ academic writing practice.
Classification of plant diseases using machine and deep learning
Authors: Lamba Monika , Gigras Yogita , Dhull Anuradha
Published: December 2021

Detection of plant disease has a crucial role in better understanding the economy of India in terms of agricultural productivity. Early recognition and categorization of diseases in plants are very crucial as it can adversely affect the growth and development of species. Numerous machine learning methods like SVM (support vector machine), random forest, KNN (k-nearest neighbor), Naïve Bayes, decision tree, etc., have been exploited for recognition, discovery, and categorization of plant diseases; however, the advancement of machine learning by DL (deep learning) is supposed to possess tremendous potential in enhancing the accuracy. This paper proposed a model comprising of Auto-Color Correlogram as image filter and DL as classifiers with different activation functions for plant disease. This proposed model is implemented on four different datasets to solve binary and multiclass subcategories of plant diseases. Using the proposed model, results achieved are better, obtaining 99.4% accuracy and 99.9% sensitivity for binary class and 99.2% accuracy for multiclass. It is proven that the proposed model outperforms other approaches, namely LibSVM, SMO (sequential minimal optimization), and DL with activation function softmax and softsign in terms of F-measure, recall, MCC (Matthews correlation coefficient), specificity and sensitivity.
A review on the corrosion resistance of electroless Ni-P based composite coatings and electrochemical corrosion testing methods
Authors: Shozib Imtiaz Ahmed , Ahmad Azlan , Abdul-Rani Ahmad Majdi , Beheshti Mohammadali , Aliyu Abdul’Azeez Abdu
Published: December 2021

This paper aims to review the impact of different factors influencing the corrosion resistance of electroless Ni-P based coatings. Emphasis has been given onto the impact of phosphorus content, incorporation of alloying elements, addition of particles and heat treatment which have been discussed in detail and critically reviewed. The effect of corrosive media and coating process parameters on corrosion resistance are studied concisely. Furthermore, the role of the incorporation of various elements and particles’ contents on the corrosion resistance of electroless Ni-P coating are studied systematically. This paper also presents an overview of the latest electrochemical corrosion measuring techniques. The following approaches deserve special attention in the analysis: localized electrochemical impedance spectroscopy (LEIS), scanning vibrating electrode technique (SVET), scanning ion-selective electrode technique (SIET), scanning droplet cell (SDC), scanning electrochemical microscopy (SECM), scanning Kelvin probe (SKP) and novel contactless technique (NCT).
Corrosion characteristics of plasma spray, arc spray, high velocity oxygen fuel, and diamond jet coated 30MnB5 boron alloyed steel in 3.5 wt.% NaCl solution
Authors: Güney Bekir , Dilay Yusuf , Solomon Moses M. , Gerengi Hüsnü , Özkan Adem , Yıldız Mesut
Published: December 2021

30MnB5 boron alloyed steel surface is coated using different coating techniques, namely 60(Ni-15Cr-4.4Si-3.5Fe-3.2B 0.7C)-40(WC 12Co) metallic powder plasma spray, Fe-28Cr-5C-1Mn alloy wire arc spray, WC-10Co-4Cr (thick) powder high velocity oxy-fuel (HVOF), and WC-10Co-4Cr (fine) diamond jet HVOF. The microstructure of the crude steel sample consists of ferrite and pearlite matrices and iron carbide structures. The intermediate binders are well bonded to the substrate for all coated surfaces. The arc spray coated surface shows the formation of lamellae. The cross-section of HVOF and diamond jet HVOF coated surfaces indicates the formation of WC, W2C Cr, and W parent matrix carbide structures. The corrosion characteristic of the coated steel has been investigated in 3.5 wt.% NaCl solution using electrochemical impedance spectroscopy (EIS), scanning electron microscope (SEM), and energy dispersive X-ray spectroscopy (EDAX) techniques. The results reveal that the steel corroded in the medium despite the coatings. However, the extent of corrosion varies. HVOF coated sample demonstrated the highest corrosion resistance while arc spray coated sample exhibited the least. EDAX mapping reveals that the elements in the coatings corroded in the order of their standard electrode potential (SEP). Higher corrosion resistance of HVOF coated sample is linked to the low SEP of tungsten.
Virgin coconut oil abrogates depression-associated cognitive deficits by modulating hippocampal antioxidant balance, GABAergic and glutamatergic receptors in mice
Authors: Edem Edem Ekpenyong , Ihaza Blessing Eghosa , Fafure Adedamola Adediran , Ishola Azeez Olakunle , Nebo Kate Eberechukwu , Enye Linus Anderson , Akinluyi Elizabeth Toyin
Published: December 2021

Objectives

GABA and glutamate neurotransmission play critical roles in both the neurobiology of depression and cognition; and Virgin coconut oil (VCO) is reported to support brain health. The present study investigated the effect of VCO on depression-associated cognitive deficits in mice.

Methods

Thirty male mice divided into five groups were either exposed to chronic unpredicted mild stress (CUMS) protocol for 28 days or pre-treated with 3 mL/kg b. wt. of VCO for 21 days or post-treated with 3 mL/kg b. wt. of VCO for 21 days following 28 days of CUMS exposure. Mice were subjected to behavioural assessments for depressive-like behaviours and short-term memory, and thereafter euthanised. Hippocampal tissue was dissected from the harvested whole brain for biochemical and immunohistochemical evaluations.

Results

Our results showed that CUMS exposure produced depressive-like behaviours, cognitive deficits and altered hippocampal redox balance. However, treatment with VCO abrogated depression-associated cognitive impairment, and enhanced hippocampal antioxidant concentration. Furthermore, immunohistochemical evaluation revealed significant improvement in GABAA and mGluR1a immunoreactivity following treatment with VCO in the depressed mice.

Conclusions

Therefore, findings from this study support the dietary application of VCO to enhance neural resilience in patients with depression and related disorders.
A call to action: next steps to advance diagnosis education in the health professions
Authors: Graber Mark L. , Holmboe Eric , Stanley Joan , Danielson Jennifer , Schoenbaum Stephen , Olson Andrew P.J.
Published: December 2021

Objectives

Improving diagnosis-related education in the health professions has great potential to improve the quality and safety of diagnosis in practice. Twelve key diagnostic competencies have been delineated through a previous initiative. The objective of this project was to identify the next steps necessary for these to be incorporated broadly in education and training across the health professions.

Methods

We focused on medicine, nursing, and pharmacy as examples. A literature review was conducted to survey the state of diagnosis education in these fields, and a consensus group was convened to specify next steps, using formal approaches to rank suggestions.

Results

The literature review confirmed initial but insufficient progress towards addressing diagnosis-related education. By consensus, we identified the next steps necessary to advance diagnosis education, and five required elements relevant to every profession: 1) Developing a shared, common language for diagnosis, 2) developing the necessary content, 3) developing assessment tools, 4) promoting faculty development, and 5) spreading awareness of the need to improve education in regard to diagnosis.

Conclusions

The primary stakeholders, representing education, certification, accreditation, and licensure, in each profession must now take action in their own areas to encourage, promote, and enable improved diagnosis, and move these recommendations forward.
Synthesis of NPK fertilizer from low-grade phosphate raw material
Authors: Kareeva Anar , Besterekov Uilesbek , Abdurazova Perizat , Nazarbek Ulzhalgas , Pochitalkina Irina , Raiymbekov Yerkebulan
Published: December 2021

The article presents the results of studies of the process of obtaining NPK fertilizer from low-grade phosphate raw materials with P2O5 of about 18%. Phosphate raw materials were leached with a mixture of nitric-phosphoric acids with the addition of potassium carbonate, which serves as a source of potassium in the final product. The main parameters determined were the content of the main nutrients P2O5:N:K2O, temperature and time of the leaching process. According to the graphical method, the “apparent” activation energy of the heterogeneous process is found, which is equal to 3.8 kJ/mol indicates the intradiffusion nature of the process. Methods of chemical analysis, scanning electron microscopy and XRD analysis were used for a comprehensive study of raw materials and final products.
Numerical scheme and analytical solutions to the stochastic nonlinear advection diffusion dynamical model
Authors: Yasin Muhammad W. , Iqbal Muhammad S. , Seadawy Aly R. , Baber Muhammad Z. , Younis Muhammad , Rizvi Syed T. R.
Published: December 2021

In this study, we give the numerical scheme to the stochastic nonlinear advection diffusion equation. This models is considered with white noise (or random process) having same intensity by changing frequencies. Furthermore, the stability and consistency of proposed scheme are also discussed. Moreover, it is concerned about the analytical solutions, the Riccati equation mapping method is adopted. The different families of single (shock and singular) and mixed (complex solitary-shock, shock-singular, and double-singular) form solutions are obtained with the different choices of free parameters. The graphical behavior of solutions is also depicted in 3D and corresponding contours.
Israel Kirzner’s Presence in the History of Economic Thought: A Review of His Professional Engagement in Honor of His 91 Years
Authors: Casonato Lucas
Published: December 2021

This paper analyzes the presence of Israel Kirzner in the History of Economic Thought and focusing on his professional engagement with other economists. His academic trajectory is contextualized on three milestones of the recent history of the Austrian School. The first one is the ending of the socialist economic calculation debate, when the Austrian was considered unconvincing due to the economics’ shift to a general equilibrium model of the economy; in the aftermath of the debate, Kirzner entered at the New York University’s PhD program and was mentored by Ludwig von Mises. At this point, Kirzner started to develop his ideas on entrepreneurship and to aim an audience wider than his Austrian peers. The second is the Austrian Revival in the 1970s, in which the prestigious recovery stage of the Austrian School, thanks to Kirzner assuming a leadership role in the process. The third is in the 1980s, when a more consolidated Austrian School attempts to define itself, as Kirzner retains an Austrian vision founded on the synthesis between Mises and Hayek. It is concluded that Kirzner’s professional engagement was fundamental in the recovery of Austrian theory. He communicated Austrian ideas to a wider audience and synthetized Misesian and Hayekian proposals on the market process. These efforts allow us to recognize a Kirznerian view of the Austrian School, established with the traditional microeconomic theory, but including greater subjectivity on the interpretation of economic phenomena, becoming a more general, more realistic theory.
Unique continuation property of solutions to general second order elliptic systems
Authors: Honda Naofumi , Lin Ching-Lung , Nakamura Gen , Sasayama Satoshi
Published: December 2021

This paper concerns the weak unique continuation property of solutions of a general system of differential equation/inequality with a second order strongly elliptic system as its leading part.
We put not only some natural assumptions which we call basic assumptions, but also some technical assumptions which we call further assumptions.
It is shown as usual by first applying the Holmgren transform to this equation/inequality and then establishing a Carleman estimate for the leading part of the transformed inequality.
The Carleman estimate is given via a partition of unity and the Carleman estimate for the operator with constant coefficients obtained by freezing the coefficients of the transformed leading part at a point.
A little more details about this are as follows.
Factorize this operator with constant coefficients into two first order differential operators.
Conjugate each factor by a Carleman weight, and derive an estimate which is uniform with respect to the point at which we froze the coefficients for each conjugated factor by constructing a parametrix for its adjoint operator.
FSO performance analysis of a metro city in different atmospheric conditions
Authors: Giri Rajat Kumar
Published: December 2021

In this article, a free-space-optics (FSO) model for a metro city based on real-time visibility data under different weather conditions is presented. Here, the relation between atmospheric attenuation and visibility value and its impact on the FSO performance is carried out. Also, the hybrid-SIM modulation technique is applied for the bit error rate (BER) improvement of the system. Here, Bhubaneswar (the capital of Odisha, India) is considered for the above analysis. The total attenuation, BER, and link margin are calculated for the FSO performance evaluation of Bhubaneswar city and these are simulated using Matlab. The simulation results show that the proposed hybrid-SIM modulation technique achieves about 2.9 dB of SNR improvement than the existing BPSK-SIM technique. Also, from the link margin analysis, it is observed that the sunny day is the most suitable for FSO link transmission. These results can be helpful to decide the FSO parameters and the FSO setup can be designed for any city.
Outcomes from birth to 6 months of publicly insured infants born to mothers with severe acute respiratory syndrome coronavirus 2 infection in the United States
Authors: Schuh Tina L. , Mithal Leena B. , Naureckas Sara , Miller Emily S. , Garfield Craig F. , Shah Malika D.
Published: December 2021

Objectives

We evaluated inpatient management, transition to home, breastfeeding, growth, and clinical outcomes of infants born to mothers diagnosed with SARS-CoV-2 infection in pregnancy and followed in a Federally Qualified Health Center (FQHC), that serves a diverse and low-income patient population, from birth through 6 months of life.

Methods

Infants born between 4/3/20 and 7/26/20 at Prentice Women’s Hospital with mothers who received prenatal care at Erie Family Health Center (Erie), the second largest FQHC in Illinois, and had confirmed SARS-CoV-2 during pregnancy were included. Data were abstracted from delivery hospital admission and outpatient follow-up appointments between 4/8/20 and 2/4/21.

Results

Thirty-three infants met inclusion criteria. Average gestational age was 38.9 weeks (IQR 37.6–40.4), 3 (10%) were premature and 5 (15%) required NICU admission. Nearly all (97%) mothers expressed intent to breastfeed. Outpatient follow-up rates were similar to historical cohorts and 82% (23/28) of infants were vaccination compliant. Growth parameters showed normal distributions at all time points. At 6 months, any and exclusive breast milk feeding rates were lower compared to historic cohorts (18 vs. 36%, p<0.05, 0 vs. 21%, p<0.01). Three infants (10%) received development-related referrals, one carried an underlying genetic diagnosis. Outpatient visits were predominantly face-to-face with telemedicine use comprising only 6% of visits (11/182).

Conclusions

Longitudinal follow-up of 33 publicly insured infants born to mothers with SARS-CoV-2 infection in pregnancy followed in an FQHC showed high rates of follow-up and vaccination compliance, normal growth patterns and reassuring clinical status, and lower than expected rates of breastfeeding.
Adverse perinatal outcomes following the prenatal diagnosis of isolated single umbilical artery in singleton pregnancies: a systematic review and meta-analysis
Authors: Dagklis Themistoklis , Siargkas Antonios , Apostolopoulou Aikaterini , Tsakiridis Ioannis , Mamopoulos Apostolos , Athanasiadis Apostolos , Sotiriadis Alexandros
Published: December 2021

Objectives

A systematic review and meta-analysis was conducted to quantitatively synthesize the current evidence on the association of prenatally diagnosed isolated single umbilical artery (iSUA) in singleton pregnancies with small for gestational age (SGA) neonates and other perinatal outcomes.

Methods

A search of PubMed/Medline, Scopus and The Cochrane Library was conducted, from inception to February 2021, in order to identify studies comparing the risk of SGA and other perinatal adverse outcomes in prenatally diagnosed iSUA singleton pregnancies vs. those with a 3-vessel cord (3VC). The quality of eligible studies was assessed according to the improved Newcastle–Ottawa Scale (NOS). The heterogeneity of results across the studies was tested using the I2 test. Funnel plots and Egger’s test were used to assess the possibility of publication bias. Prospero RN: CRD42020182586.

Results

The electronic search identified 7,605 studies, of which 11 were selected, including three retrospective cohort and eight retrospective case control studies, overall reporting on 1,533 iSUA cases. The risk of delivering SGA neonates was increased in cases with iSUA (OR: 2.90; 95% CI: 2.02–4.18; p<0.00001; I2=71%). Similarly, iSUA was associated with an increased risk of pregnancy-induced hypertension (PIH) (OR: 2.23; 95% CI: 1.41–3.54; p<0.000; I2=1%), intrauterine death (IUD) (OR: 2.62; 95% CI: 1.43–4.79; p=0.002; I2=0%), preterm birth (PTB) (OR: 2.48; 95% CI: 1.73–3.56; p<0.00001; I2=56%), cesarean section (CS) (OR: 1.64; 95% CI: 1.11–2.41; p=0.01; I2=78%) and admission to neonatal intensive care unit (NICU) (OR: 2.28; 95% CI: 1.52–3.44; p<0.000001; I2=73%).

Conclusions

In prenatally diagnosed iSUA there is a higher risk of SGA, PIH, IUD, PTB, CS and NICU admission. These findings support the value of prenatal diagnosis of iSUA, which may subsequently intensify surveillance for the detection of specific pregnancy complications.
Analysis of prevalence and sociodemographic conditions among women in labor with and without COVID-19 in public hospitals in Chile
Authors: Vera von Bargen Helga , Espinosa Serrano María , Martin Navarrete Daniel , Ahumada Droguett Paz , Méndez Benavente Carolina , Flores Castillo Mónica , Ramírez González Natalia , Ulloa Contador Gabriela , López Aceiton Marcia
Published: December 2021

Objectives

The SARS-CoV-2 virus continues wreaking worldwide havoc on health and between March and August 2020, the first outbreak of COVID-19 hit Chile. The pregnant population is especially vulnerable to infection. Studies have been published that associate socioeconomic status, overcrowding, and poverty with a higher prevalence of SARS-CoV-2 infection. There are few studies about the development of this pandemic in Latin American countries so far. This study seeks to show the prevalence and sociodemographic and perinatal characteristics in pregnant women at the time of delivery, comparing both groups with positive and negative COVID-19 PCR results.

Methods

A prospective, cross-sectional study of pregnant women who delivered at the San Juan de Dios Hospital in Santiago between April 15, 2020 and June 15, 2020. Analysis of epidemiological, sociodemographic, obstetric, perinatal and sociodemographic data of patients with positive and negative COVID-19 PCR results.

Results

There were 701 patients included in the study. The prevalence of those with a positive COVID-19 PCR was 9.7% and 67.7% being asymptomatic. Pre-term delivery was significantly higher in the group of positive patients (23.5%) vs. negative patients (8.7%), which was not the same rate as with cesarean sections (C-sections). A 13.2% of patients required management of the pathology in the Critical Care Unit (CCU) and there were no cases of maternal or fetal deaths. We found no significant difference between both groups when analyzing socioeconomic variables, though we noted a trend of greater overcrowding among the group of patients with infection.

Conclusions

The majority of pregnant patients with SARS-CoV-2 infection are asymptomatic. COVID-19 increases the rate of premature births, but this rate is not same with C-sections. Sociodemographic conditions and overcrowding do not show a higher infection rate in a homogeneous population in relation to the economic, social and demographic level.
High frequency band limits in spectral analysis of heart rate variability in preterm infants
Authors: Israeli-Mendlovic Hadas , Mendlovic Joseph , Zuk Luba , Katz-Leurer Michal
Published: December 2021

Objectives

The current study aims to assess different high-frequency (HF) band power calculations based on different frequency bandwidth values, and compare them with the time domain the root mean square of successive RR differences (RMSSD) value in preterm infants.

Methods

At week 32, electrocardiogram (ECG) and breathing rate (BR) were recorded for 24 h on 30 preterm infants born between 28 and 32 weeks. The recording held in the neonatal intensive care unit without any interruption of routine.

Results

The median 24 h BR was 40–78 breaths per minute. The RMSSD was highly and positively correlated with frequency bands that were based on each preterms BR range, or on a constant frequency with band limits of 0.4–2 Hz.

Conclusions

At week 32, HF band Hz limits should be calculated based on each child’s breathing rate, generally between 0.4 and 2 Hz.
Healthcare workers’ attitudes about vaccination of pregnant women and those wishing to become pregnant
Authors: Daskalakis George , Pergialiotis Vasilios , Antsaklis Panagiotis , Theodora Marianna , Papageorgiou Dimitrios , Rodolakis Alexandros
Published: December 2021

Objectives

We designed an electronic query that was distributed to healthcare workers in order to evaluate their attitudes towards COVID-19 vaccination of women that wish to conceive and those that are pregnant.

Methods

An electronic survey was designed and distributed through a network of 5.654 e-mails. The query was uploaded in Google Forms.

Results

Overall, 1,226 answers were retrieved. Ninety percent of respondents replied that they prescribe COVID-19 vaccination in women that wish to conceive, however, the rate falls to 80% for those that have schedules for imminent artificial reproductive techniques. Approximately 1 in 2 physicians (obstetricians and pediatricians) suggests that a delay in assisted reproduction following immunization is not recommended. At least 13% of women of reproductive age and 30% of women wishing to conceive with ART declined to do so according to respondents, report. Only 75% of respondents favored immunization during pregnancy and of those 48% responded that vaccination could be done in all trimesters of pregnancy. Approximately 40% of women decline; however, to receive vaccination.

Conclusions

Despite the directions provided by international organizations; physician and patient hesitancy towards vaccination during pregnancy (and particularly the first trimester) remains an issue that deserves further attention.
Digital toolbox for vector field characterization
Authors: Singh Keshaan , Dudley Angela
Published: December 2021

Vectorial structured light fields have displayed properties advantageous in many disciplines ranging from communications, microscopy and metrology to laser cutting and characterizing quantum channels. The generation of these fields has been made convenient through the implementation of nanophotonic metasurfaces amongst other static and digital techniques. Consequently, the detection and characterisation of these fields is of equal importance. Most existing techniques involve using separate polarization optics and correlation filters to perform the projective measurements – or are only able to perform such measurements on a subset of possible vector states. We present a compact, fully automated measurement technique based on a digital micro-mirror device (DMD), which facilitates the complete, local and global, characterisation of the spatial mode and polarization degrees-of-freedom (DOFs) for arbitrary vectorial fields. We demonstrate our approach through the identification of relevant hybrid-order Poincaré spheres, the reconstruction of state vectors on these spheres, as well as the recovery of the non-separability and states-of-polarization for a variety of vector beams.
Cones with a three-fold symmetry constructed from three hydrogen bonded theophyllinium cations that coat [FeCl4]− anions in the crystal structure of tris(theophyllinium) bis(tetrachloridoferrate(III)) chloride trihydrate, C21H33Cl9Fe2N12O9
Authors: Reiss Guido J. , Wyshusek Maik
Published: December 2021

C21H33Cl9Fe2N12O9, trigonal,

R

3
‾

$R\overline{3}$

(no. 148), a = 13.1897(3) Å, c = 39.5222(9) Å, Z = 6, V = 5954.4(3) Å3, R

gt
(F) = 0.0255, wR

ref
(F
2) = 0.0743, T = 120 K.
Flammability and physical stability of sugar palm crystalline nanocellulose reinforced thermoplastic sugar palm starch/poly(lactic acid) blend bionanocomposites
Authors: Nazrin Asmawi , Sapuan Salit Mohd , Zuhri Mohamed Yusoff Mohd , Tawakkal Intan Syafinaz Mohamed Amin , Ilyas Rushdan Ahmad
Published: December 2021

In this study, sugar palm crystalline nanocellulose (SPCNC)-reinforced thermoplastic sugar palm starch (TPS) was blended with poly(lactic acid) (PLA) in order to prioritize the biodegradation feature while offsetting individual polymer limitation. Prior to melt blending process, SPCNC was dispersed through sonication in advance of starch gelatinization which was later casted into petri dishes. PLA and TPS were melt blended into five different ratios using Brabender mixer followed by compression molding. Soil degradation (4 months) and water uptake (4 weeks) tests were conducted to evaluate the physical stability of PLA/TPS blend bionanocomposites. Based on Fickian law, the diffusion curve and coefficient of diffusion for seawater, river water, and sewer water were calculated. The flammability and limiting oxygen index (LOI) tests were conducted in accordance with ASTM D635 and ASTM D2863, respectively. For PLA60TPS40 (40% TPS), significant reduction (46–69%) was recorded in maximum water uptake in all mediums, while soil degradation rate experienced insignificant increment (7.92%) for PLA70TPS30 (30% TPS) owing to the reinforcement of SPCNC through the well-dispersed TPS within PLA. Meanwhile, the flammability rates and LOI values for PLA40TPS60 and PLA60TPS40 indicated flammable material properties.
The chemistry of melting oxynitride phosphate glasses
Authors: Muñoz Francisco
Published: December 2021

Oxide glasses are the most commonly studied non-crystalline materials in Science and Technology, though compositions where part of the oxygen is replaced by other anions, e.g. fluoride, sulfide or nitride, have given rise to a good number of works and several key applications, from optics to ionic conductors. Oxynitride silicate or phosphate glasses stand out among all others because of their higher chemical and mechanical stability and their research continues particularly focused onto the development of solid electrolytes. In phosphate glasses, the easiest way of introducing nitrogen is by the remelting of the parent glass under a flow of ammonia, a method that allows the homogeneous nitridation of the bulk glass and which is governed by diffusion through the liquid-gas reaction between NH3 and the PO4 chemical groupings. After nitridation, two new structural units appear, the PO3N and PO2N2 ones, where nitrogen atoms can be bonded to either two or three neighboring phosphorus, thus increasing the bonding density of the glass network and resulting in a quantitative improvement of their properties. This short review will gather all important aspects of the synthesis of oxynitride phosphate glasses with emphasis on the influence of chemical composition and structure.
The Effect of the Spanish Civil War on City Shares
Authors: González-Val Rafael , Silvestre Javier
Published: December 2021

This paper examines the effect of the Spanish Civil War (1936–1939) shock on city shares of population applying the methodology proposed by Davis, D. R., and D. E. Weinstein. 2002. “Bones, Bombs, and Break Points: The Geography of Economic Activity.” The American Economic Review 92 (5): 1269–89. We make use of an unexploited long-term, historical dataset of populations disaggregated at the city level. Our instruments, a key methodological issue, are based on dead and wounded data collected by historians. We show that the effect of the Spanish Civil War on capital cities was temporary, and argue that the locational fundamentals theory is the principal explanation.
A local green composite study: the effect of edible oil on the morphological and mechanical properties of PBS/bentonite composite
Authors: Phattarateera Supanut , Ausab Rudeerat , Jemkuntod Neungruthai , Wiriya-amornchai Atiwat
Published: December 2021

Composites of a biodegradable thermoplastic aliphatic polyester, polybutylene succinate (PBS), with bentonite were investigated for morphological and mechanical properties. The bentonite was modified with soybean oil (SBO) and lard oil (LO) (2:98 clay:oil % by weight) by mechanical stirring and ultrasonication. The PBS/modified bentonite composite was prepared by using an internal mixer and processed by compression molding. Under bentonite modification conditions, XRD and SEM showed that the bentonite layers were broken into small layers, and the d-spacing between the layers was increased by edible oil molecules. A small plate like structure of modified bentonite composite was observed by SEM micrograph, which revealed short and long layer silicate structure non-directionally throughout the matrix phase. The mechanical properties of PBS were reinforced by this structure. The tensile modulus and elongation at break seem to depend on its directional bentonite. Interestingly, considerable improvement in impact strength was observed at over 2 wt% of clay. The impact strengths of PBS, PBS/modified BTN with SBO composite, and PBS/modified BTN with LO composite were increased from 1 to 1.5 and 2 kJ/m2, respectively. Comparatively, using LO modified bentonite had a better performance for increased interlayer and resulted in higher impact strength of the composite than that of SBO composite. The results demonstrated that PBS/modified bentonite using edible oil could be a potential alternative low cost, eco-friendly material with superior impact properties useful for further applications.
Status and progress of ion-implanted βNMR at TRIUMF
Authors: MacFarlane W. Andrew
Published: December 2021

Beta-detected NMR is a type of nuclear magnetic resonance that uses the asymmetric property of radioactive beta decay to provide a “nuclear” detection scheme. It is vastly more sensitive than conventional NMR on a per nuclear spin basis but requires a suitable radioisotope. I briefly present the general aspects of the method and its implementation at TRIUMF, where ion implantation of the NMR radioisotope is used to study a variety of samples including crystalline solids and thin films, and more recently, soft matter and even room temperature ionic liquids. Finally, I review the progress of the TRIUMF βNMR program in the period 2015–2021.
THE IMPACT OF INTRADAY MOMENTUM ON STOCK RETURNS: EVIDENCE FROM S&P500 AND CSI300
Authors: Hossain Saddam , Gavurová Beáta , Yuan Xianghui , Hasan Morshadul , Oláh Judit
Published: December 2021

This paper analyzes the statistical impact of COVID-19 on the S&P500 and the CSI300 intraday momentum. This study employs an empirical method, that is, the intraday momentum method used in this research. Also, the predictability of timing conditional strategies is also used here to predict the intraday momentum of stock returns. In addition, this study aims to estimate and forecast the coefficients in the stock market pandemic crisis through a robust standard error approach. The empirical findings indicate that the intraday market behavior an unusual balanced; the volatility and trading volume imbalance and the return trends are losing overwhelmingly. The consequence is that the first half-hour return will forecast the last half-hour return of the S&P500, but during the pandemic shock, the last half-hour of both stock markets will not have a significant impact on intraday momentum. Additionally, market timing strategy analysis is a significant factor in the stock market because it shows the perfect trading time, decides investment opportunities and which stocks will perform well on this day. Besides, we also found that when the volatility and volume of the S&P500 are both at a high level, the first half-hour has been a positive impact, while at the low level, the CSI300 has a negative impact on the last half-hour. In addition, this shows that the optimistic effect and positive outlook of the stockholders for the S&P500 is in the first half-hours after weekend on Monday morning because market open during the weekend holiday, and the mentality of every stockholder’s indicate the positive impression of the stock market.