bluuebunny/crossref_metadata_2025 huggingface dataset:
A Practitioner’s View on Process Mining Adoption, Event Log Engineering and Data Challenges
Authors: Accorsi Rafael , Lebherz Julian
Published: June 2022

Process mining is, today, an essential analytical instrument for data-driven process improvement and steering. While practical literature on how to derive value from process mining exists, less attention haas been paid to how it is being used in different industries, the effort involved in creating an event log and what are the best practices in doing so. Taking a practitioner’s view on process mining, we report on process mining adoption and illustrate the challenges of log contruction by means of the order to cash (i.e. sales) process in an SAP system. By doing so, we collect a set of best practices regarding the data selection, extraction, transformation and data model engineering, which proved themselves handy in large-scale process mining projects.
Process Mining over Multiple Behavioral Dimensions with Event Knowledge Graphs
Authors: Fahland Dirk
Published: June 2022

Classical process mining relies on the notion of a unique case identifier, which is used to partition event data into independent sequences of events. In this chapter, we study the shortcomings of this approach for event data over multiple entities. We introduce event knowledge graphs as data structure that allows to naturally model behavior over multiple entities as a network of events. We explore how to construct, query, and aggregate event knowledge graphs to get insights into complex behaviors. We will ultimately show that event knowledge graphs are a very versatile tool that opens the door to process mining analyses in multiple behavioral dimensions at once.
Alternating complexity of counting first-order logic for the subword order
Authors: Kuske Dietrich , Schwarz Christian
Published: June 2022

This paper considers the structure consisting of the set of all words over a given alphabet together with the subword relation, regular predicates, and constants for every word. We are interested in the counting extension of first-order logic by threshold counting quantifiers. The main result shows that the two-variable fragment of this logic can be decided in twofold exponential alternating time with linearly many alternations (and therefore in particular in twofold exponential space as announced in the conference version (Kuske and Schwarz, in: MFCS’20, Leibniz International Proceedings in Informatics (LIPIcs) vol. 170, pp 56:1–56:13. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020) of this paper) provided the regular predicates are restricted to piecewise testable ones. This result improves prior insights by Karandikar and Schnoebelen by extending the logic and saving one exponent in the space bound. Its proof consists of two main parts: First, we provide a quantifier elimination procedure that results in a formula with constants of bounded length (this generalises the procedure by Karandikar and Schnoebelen for first-order logic). From this, it follows that quantification in formulas can be restricted to words of bounded length, i.e., the second part of the proof is an adaptation of the method by Ferrante and Rackoff to counting logic and deviates significantly from the path of reasoning by Karandikar and Schnoebelen.
Reallocation of Hospital Resources During COVID‐19 Pandemic and Effect on Trauma Outcomes in a Resource‐Limited Setting
Authors: Gallaher Jared R. , Yohann Avital , Kajombo Chifundo , Schneider Andrew , Purcell Laura , Charles Anthony
Published: June 2022

Background

The COVID‐19 pandemic has caused unprecedented disruptions to surgical care worldwide, particularly in low‐resource countries. We sought to characterize the association between pre‐and intra‐pandemic trauma clinical outcomes at a busy tertiary hospital in Malawi.

Methods

We analyzed trauma patients that presented to Kamuzu Central Hospital in Lilongwe, Malawi, from 2011 through July 2021. Burn patients were excluded. We compared patients based on whether they presented before or during the pandemic (defined as starting March 11, 2020, the date of the official WHO designation). We used logistic regression modeling to estimate the adjusted odds ratio of death based on presentation.

Results

A total of 137,867 patients presented during the study period, with 13,526 patients during the pandemic. During the pandemic, patients were more likely to be older (mean 28 vs. 25 years, p < 0.001), male (79 vs. 74%, p < 0.001), and suffer a traumatic brain injury (TBI) as their primary injury (9.7 vs. 4.9%, p < 0.001). Crude trauma‐associated mortality was higher during the pandemic at 3.7% vs. 2.1% (p < 0.001). The odds ratio of mortality during the pandemic compared to pre‐pandemic presentation was 1.28 (95% CI 1.06, 1.53) adjusted for age, sex, initial AVPU score, transfer status, injury type, and mechanism.

Conclusions

During the pandemic, adjusted trauma‐associated mortality significantly increased at a tertiary trauma center in a low‐resource setting despite decreasing patient volume. Further research is urgently needed to prepare for future pandemics. Potential targets for improvement include improving pre‐hospital care and transportation, planning for intensive care utilization, and addressing nursing shortages.
Roles of climate feedback and ocean vertical mixing in modulating global warming rate
Authors: Yang Haijun , Zhou Xiangying , Yang Qianzi , Li Yang
Published: June 2022

Despite the rapid increase of greenhouse gases (GHGs) in the atmosphere during the past 50 years, observed global mean surface temperature (GMST) showed a pause in the warming trend during the first decade of the twenty-first century. This is referred to as the global warming “hiatus”. A dominant hypothesis emphasizes that the superimposition of the cold phase of the Pacific decadal variability and the global warming trend can lead to the hiatus. Using simply energy balance models, we explore two potential mechanisms that may supress the GMST warming trend: enhanced negative climate feedback and downward heat mixing. Forced by linearly increasing heating, a stronger negative climate feedback can reduce the GMST warming rate, but cannot result in a warming hiatus. Downward mixing of heat can cause a short-lived hiatus of surface warming rate due to enhanced nonlinear ocean heat uptake by the lower ocean, but the surface warming would be accelerated in the long run due to the decline of downward heat mixing rate. This study provides further evidence, both theoretically and numerically, that in the long run, the only route to contain the global warming effectively is to reduce GHG emissions.
On the Influence of Sampling Scale on the In Situ Block Size Distribution
Authors: Bernardini Maurizio , Paredes Carlos , Sanchidrián José A. , Segarra Pablo , Gómez Santiago
Published: June 2022

The modelling of discontinuities in rock mass is undertaken with different measurement techniques and used to determine the in situ block size distribution (IBSD). Two monitoring techniques are employed: televiewer logging of boreholes and photogrammetry of highwall faces in a quarry bench; televiewer performs at the borehole diameter scale, while photogrammetry surveys at the entire bench scale. Ground sampling distances were, respectively, about 1 and 8.5 mm. The discontinuities are modelled as a stochastic discrete fracture network (DFN), with the number of discontinuities used in the simulation calibrated by the intensity per unit length (P10) on the televiewer data, or by the fracture density (P21) on the photogrammetry data, leading to different fracture networks. From the discontinuity network models, the IBSDs are calculated and discussed as function of the sampling scale (i.e. televiewer or photogrammetry data source) and of the fracture density. The goal is to compare the results from both techniques for rock mass structural characterization, to assess their limitations and shortcomings, and to show their potential complementarity at different sampling scales. The televiewer data provides smaller block sizes than the photogrammetry, following the higher number of fractures observed in the former. All volumetric distributions obtained are extremely well represented by Gamma with a power law tail distribution. Despite different location parameters, it is particularly remarkable that all distributions present very similar Gamma shape parameters. The constant log–log slopes of the tails provide evidence of multi-scale validity and a scaling invariant structure (more than two orders of magnitude) of discontinuities of the rock mass. The IBSDs and the scale effect are discussed in the light of the fragment size distributions from blasts carried out in the area characterized.
A short- and long-term follow-up study of intersphincteric NASHA Dx implants for fecal incontinence
Authors: Ezra E. , Danielsson J. M. , Graf W.
Published: June 2022

Background

The bulking agent NASHA Dx injected into the submucosal layer is effective in the treatment of fecal incontinence (FI) at short-and medium-term follow-up but efficacy after injection in the intersphincteric location is unknown. The aim of this study was to determine the short- and long-term efficacy and safety of NASHA Dx injected into the intersphincteric location for FI.

Methods

Patients were recruited from referrals to our Department for treatment of FI in November 2008–January 2010. Eligible patients were injected with 8 ml of NASHA Dx. Patients with a subtotal treatment effect were retreated after 2–4 weeks. The change in number of fecal incontinence episodes, the proportion of responders defined as at least 50% decrease in number of FI episodes and side effects were the main outcome measures.

Results

Sixteen patients, 15 women and 1 man with a median age of 68, 5 (range 44–80) years and a median CCFIS of 15 (range 10–19) were included in the study. The median number of incontinence episodes decreased from 21.5 (range 8–61) at baseline to 10 (range 0–30) at 6 months (p = 0.003) and 6 (range 0–44) at 12 months (p = 0.05). The median number of incontinence episodes in the 11 patients completing the 10-year follow-up was 26.5 (range 0–68). The percentage of responders at 12 months and 10 years were 56% and 27%, respectively. Mild to moderate pain at the injection site was described by 69%. There was one case of mild infection, successfully treated with antibiotics and one implant had to be removed due to dislocation.

Conclusions

NASHA Dx as an intersphincteric implant improves incontinence symptoms in the short term with moderate side effects and can be used alone or as an adjunct to other treatment modalities. Long-term efficacy was observed in 27%.
Site- and Zone-Dependent Changes in Proteoglycan Content and Biomechanical Properties of Bluntly and Sharply Grooved Equine Articular Cartilage
Authors: Mohammadi Ali , te Moller Nikae C. R. , Ebrahimi Mohammadhossein , Plomp Saskia , Brommer Harold , van Weeren P. René , Mäkelä Janne T. A. , Töyräs Juha , Korhonen Rami K.
Published: June 2022

In this study, we mapped and quantified changes of proteoglycan (PG) content and biomechanical properties in articular cartilage in which either blunt or sharp grooves had been made, both close to the groove and more remote of it, and at the opposing joint surface (kissing site) in equine carpal joints. In nine adult Shetland ponies, standardized blunt and sharp grooves were surgically made in the radiocarpal and middle carpal joints of a randomly chosen front limb. The contralateral control limb was sham-operated. At 39 weeks after surgery, ponies were euthanized. In 10 regions of interest (ROIs) (six remote from the grooves and four directly around the grooves), PG content as a function of tissue-depth and distance-to-groove was estimated using digital densitometry. Biomechanical properties of the cartilage were evaluated in the six ROIs remote from the grooves. Compared to control joints, whole tissue depth PG loss was found in sites adjacent to sharp and, to a larger extent, blunt grooves. Also, superficial PG loss of the surgically untouched kissing cartilage layers was observed. Significant PG loss was observed up to 300 µm (sharp) and at 500 µm (blunt) from the groove into the surrounding tissue. Equilibrium modulus was lower in grooved cartilage than in controls. Grooves, in particular blunt grooves, gave rise to severe PG loss close to the grooved sites and to mild degeneration more remote from the grooves in both sharply and bluntly grooved cartilage and at the kissing sites, resulting in loss of mechanical strength over the 9-month period.
Relationships between preadmission variables and academic outcomes for postbaccalaureate students in medical school
Authors: Schneid Stephen D. , Kelly Carolyn J. , Brandl Katharina
Published: June 2022

There is currently little guidance for medical school admissions committees regarding how to weigh postbaccalaureate program grades relative to undergraduate grades. This study was designed to address this issue. Admissions data, preclerkship course performance and United States Medical Licensing Exam (USMLE) Step 1 results were analyzed over three years for University of California, San Diego (UCSD) postbaccalaureate premedical (PBPM) students (n = 25), students who participated in other postbaccalaureate programs (n = 34), and for the remainder of the medical students who did not participate in any postbaccalaureate programs (n = 329). UCSD PBPM program alumni did not significantly differ in their cumulative academic performance on exams in preclerkship courses and USMLE Step 1 pass rates compared to the rest of the class despite their significantly lower GPA, lower Biology, Chemistry, Physics and Math (BCPM) GPA, and Medical College Admissions Test (MCAT) percentiles. For students who participated in the PBPM programs, PBPM program GPA was a significant predictor of preclerkship academic performance and USMLE Step 1 performance. When assessing academic readiness of applicants who have completed postbaccalaureate programs, admissions committees might closely consider the postbaccalaureate program GPA in addition to other academic metrices such as BCPM GPA and MCAT score.
An architecture-level analysis on deep learning models for low-impact computations
Authors: Li Hengyi , Wang Zhichen , Yue Xuebin , Wang Wenwen , Tomiyama Hiroyuki , Meng Lin
Published: June 2022

Deep neural networks (DNNs) have made significant achievements in a wide variety of domains. For the deep learning tasks, multiple excellent hardware platforms provide efficient solutions, including graphics processing units (GPUs), central processing units (CPUs), field programmable gate arrays (FPGAs), and application-specific integrated circuit (ASIC). Nonetheless, CPUs outperform other solutions including GPUs in many cases for the inference workload of DNNs with the support of various techniques, such as the high-performance libraries being the basic building blocks for DNNs. Thus, CPUs have been a preferred choice for DNN inference applications, particularly in the low-latency demand scenarios. However, the DNN inference efficiency remains a critical issue, especially when low latency is required under conditions with limited hardware resources, such as embedded systems. At the same time, the hardware features have not been fully exploited for DNNs and there is much room for improvement. To this end, this paper conducts a series of experiments to make a thorough study for the inference workload of prominent state-of-the-art DNN architectures on a single-instruction-multiple-data (SIMD) CPU platform, as well as with widely applicable scopes for multiple hardware platforms. The study goes into depth in DNNs: the CPU kernel-instruction level performance characteristics of DNNs including branches, branch prediction misses, cache misses, etc, and the underlying convolutional computing mechanism at the SIMD level; The thorough layer-wise time consumption details with potential time-cost bottlenecks; And the exhaustive dynamic activation sparsity with exact details on the redundancy of DNNs. The research provides researchers with comprehensive and insightful details, as well as crucial target areas for optimising and improving the efficiency of DNNs at both the hardware and software levels.
In Defence of the Normative Account of Ignorance
Authors: Meylan Anne
Published: June 2022

The standard view of ignorance is that it consists in the mere lack of knowledge or true belief. Duncan Pritchard has recently argued, against the standard view, that ignorance is the lack of knowledge/true belief that is due to an improper inquiry. I shall call, Pritchard’s alternative account the Normative Account. The purpose of this article is to strengthen the Normative Account by providing an independent vargument supporting it.
In-process monitoring and prediction of droplet quality in droplet-on-demand liquid metal jetting additive manufacturing using machine learning
Authors: Gaikwad Aniruddha , Chang Tammy , Giera Brian , Watkins Nicholas , Mukherjee Saptarshi , Pascall Andrew , Stobbe David , Rao Prahalada
Published: June 2022

In droplet-on-demand liquid metal jetting (DoD-LMJ) additive manufacturing, complex physical interactions govern the droplet characteristics, such as size, velocity, and shape. These droplet characteristics, in turn, determine the functional quality of the printed parts. Hence, to ensure repeatable and reliable part quality it is necessary to monitor and control the droplet characteristics. Existing approaches for in-situ monitoring of droplet behavior in DoD-LMJ rely on high-speed imaging sensors. The resulting high volume of droplet images acquired is computationally demanding to analyze and hinders real-time control of the process. To overcome this challenge, the objective of this work is to use time series data acquired from an in-process millimeter-wave sensor for predicting the size, velocity, and shape characteristics of droplets in DoD-LMJ process. As opposed to high-speed imaging, this sensor produces data-efficient time series signatures that allows rapid, real-time process monitoring. We devise machine learning models that use the millimeter-wave sensor data to predict the droplet characteristics. Specifically, we developed multilayer perceptron-based non-linear autoregressive models to predict the size and velocity of droplets. Likewise, a supervised machine learning model was trained to classify the droplet shape using the frequency spectrum information contained in the millimeter-wave sensor signatures. High-speed imaging data served as ground truth for model training and validation. These models captured the droplet characteristics with a statistical fidelity exceeding 90%, and vastly outperformed conventional statistical modeling approaches. Thus, this work achieves a practically viable sensing approach for real-time quality monitoring of the DoD-LMJ process, in lieu of the existing data-intensive image-based techniques.
More Continuous Mass-Lumped Triangular Finite Elements
Authors: Mulder Wim A.
Published: June 2022

When solving the wave equation with finite elements, mass lumping allows for explicit time stepping, avoiding the cost of a lower-upper decomposition of the large sparse mass matrix. Mass lumping on the reference element amounts to numerical quadrature. The weights should be positive for stable time stepping and preserve numerical accuracy. The standard triangular polynomial elements, except for the linear element, do not have these properties. Accuracy can be preserved by augmenting them with higher-degree polynomials in the interior. This leaves the search for elements with positive weights, which were found up to degree 9 by various authors. The classic accuracy condition, however, is too restrictive. A sharper, less restrictive condition recently led to new mass-lumped tetrahedral elements up to degree 4. Compared to the known ones up to degree 3, they have less nodes and are computationally more efficient. The same criterion is applied here to the construction of triangular elements. For degrees 2 to 4, these turn out to be identical to the known ones. For degree 5, the number of nodes is the same as for the known element, but now there are infinitely many solutions. Some of these have a considerably larger stability limit for time stepping. For degree 6, two elements are found with less nodes than the known ones. For degree 7, one element with less nodes was found but with a negative weight, making it useless for time stepping with the wave equation. If the number of nodes is the same as for the classic element, there are now infinitely many solutions. Numerical tests for a homogeneous wave-propagation problem with a point source confirm the expected accuracy of the new elements. Some of them require less compute time than those obtained with the more restrictive accuracy criterion.
Longitudinal-transverse soliton chains analog to heisenberg ferromagnetic spin chains in (2+1) dimensional with biquadrant interactions
Authors: Abel-Gawad H. I.
Published: June 2022

In quantum spin systems, lower energy state for a nuclear spin in an external field is spin ($$+1/2$$

+
1
/
2

) while the higher energy state is spin ($$-1/2$$

-
1
/
2

). A continuum analog to the discrete model led to nonlinear Schrodinger equation (NLSE) with higher order dispersion. Recently, a model equation with bilinear and biquadratic interactions in the (2 + 1) dimensional Heisenberg ferromagnetic spin chain (HFSC), was derived in the literature. This model equation is a NLSE with quartic dispersion and fifth degree nonlinearity, and it was rarely considered in the literature. The, only, work done has shown solitons solutions. This motivated us to consider this problem for inspecting the multiple characteristics of the HFSC in space-time. Here, the exact solutions of the HFSC biquadratic model equation are obtained by using the unified method (UM). In applications, it is found the UM is of low time cost in symbolic computations. So, we think that it prevails the known methods. The solutions obtained are evaluated numerically and shown in figures.These figures reveal that the solutions exhibit longitudinal-transverse (L-T) solitons chains (SCs) with presence (or absence) of tunneling, depending on the values of the parameters of high dispersivity and high nonlinearity. Also, L-T zig-zag SCs are observed, where pulses with higher amplitudes (or gaps) occur along a characteristic line. Furthermore, L-TSCs modulation along the space axes is shown. It is remarked that the contour plots show complex lattice waves, which is relevant to the spin chain system. So, the present work reveals new solitons structures induced by bilinear-biquadratic interactions of HFSC.
The political economy of Solon’s law against neutrality in civil wars
Authors: Schwuchow Soeren C. , Tridimas George
Published: June 2022

In 594 BCE, the Athenian lawgiver Solon, called upon to resolve a deepening social crisis, introduced a new constitution and mandated that in civil conflicts, no citizen is to remain apathetic and must take sides. Because the law seemed to support strife, it presents a puzzle. The paper offers a political economy rationale for Solon’s law against neutrality, modeling social conflict as a rent-seeking competition. We divide society into three groups, a hereditary aristocracy, which monopolized power before the Solonian constitution, a rival wealth-based commercial elite, called the new Solonian elite, and the poor, who are enfranchised only partly. We then identify the conditions under which the third group is better off by allying with one of the other groups, protecting the Solonian constitution. In our framework, Solon’s ban on neutrality is an attempt to change the payoffs from violent redistributions of rents, so that conflict is avoided. Accordingly, the ban should not only impede excessive rent seeking, but also prevent the exclusion of any social group.
An efficient DBSCAN optimized by arithmetic optimization algorithm with opposition-based learning
Authors: Yang Yang , Qian Chen , Li Haomiao , Gao Yuchao , Wu Jinran , Liu Chan-Juan , Zhao Shangrui
Published: June 2022

As unsupervised learning algorithm, clustering algorithm is widely used in data processing field. Density-based spatial clustering of applications with noise algorithm (DBSCAN), as a common unsupervised learning algorithm, can achieve clusters via finding high-density areas separated by low-density areas based on cluster density. Different from other clustering methods, DBSCAN can work well for any shape clusters in the spatial database and can effectively cluster exceptional data. However, in the employment of DBSCAN, the parameters, EPS and MinPts, need to be preset for different clustering object, which greatly influences the performance of the DBSCAN. To achieve automatic optimization of parameters and improve the performance of DBSCAN, we proposed an improved DBSCAN optimized by arithmetic optimization algorithm (AOA) with opposition-based learning (OBL) named OBLAOA-DBSCAN. In details, the reverse search capability of OBL is added to AOA for obtaining proper parameters for DBSCAN, to achieve adaptive parameter optimization. In addition, our proposed OBLAOA optimizer is compared with standard AOA and several latest meta heuristic algorithms based on 8 benchmark functions from CEC2021, which validates the exploration improvement of OBL. To validate the clustering performance of the OBLAOA-DBSCAN, 5 classical clustering methods with 10 real datasets are chosen as the compare models according to the computational cost and accuracy. Based on the experimental results, we can obtain two conclusions: (1) the proposed OBLAOA-DBSCAN can provide highly accurately clusters more efficiently; and (2) the OBLAOA can significantly improve the exploration ability, which can provide better optimal parameters.
Usefulness of fibrosis-4 (FIB-4) score and metabolic alterations in the prediction of SARS-CoV-2 severity
Authors: Lombardi Rosa , Mura Vincenzo La , Cespiati Annalisa , Iuculano Federica , Sigon Giordano , Pallini Giada , Proietti Marco , Motta Irene , Montinaro Beatrice , Fiorelli Elisa , Cesari Matteo , Bandera Alessandra , Valenti Luca , Peyvandi Flora , Montano Nicola , Baldini Marina , Fracanzani Anna Ludovica
Published: June 2022

Despite vaccination programs, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection remains a public health problem. Identifying key prognostic determinants of severity of the disease may help better focus health resources. The negative prognostic role for metabolic and hepatic alterations is established; however, the interplay among different metabolic comorbidities and their interconnections with the liver have never been explored.

The objective of this study is to evaluate the impact of liver alterations in addition to metabolic comorbidities as a predictor of SARS-CoV-2 severity. 382 SARS-CoV-2 patients were enrolled. Severe SARS-CoV-2 was diagnosed according to international consensus. Transaminases > 2 times the upper limit of normality (2ULN), hepatic steatosis (by ultrasound and/or computed tomography in 133 patients), and FIB-4 defined liver alterations. All data were collected on admission. The results are severe SARS-CoV-2 infection in 156 (41%) patients (mean age 65 ± 17; 60%males). Prevalence of obesity was 25%; diabetes, 17%; hypertension, 44%; dyslipidaemia, 29%; with 13% of the cohort with ≥ 3 metabolic alterations. Seventy patients (18%) had transaminases > 2ULN, 82 (62%) steatosis; 199 (54%) had FIB-4 < 1.45 and 45 (12%) > 3.25. At multivariable analysis, ≥ 3 metabolic comorbidities (OR 4.1, CI 95% 1.8–9.1) and transaminases > 2ULN (OR 2.6, CI 95% 1.3–6.7) were independently associated with severe SARS-CoV-2. FIB-4 < 1.45 was a protective factor (OR 0.42, CI 95% 0.23–0.76). Hepatic steatosis had no impact on disease course. The presence of metabolic alterations is associated with severe SARS-CoV-2 infection, and the higher the number of coexisting comorbidities, the higher the risk of severe disease. Normal FIB-4 values are inversely associated with advanced SARS-CoV-2 regardless of metabolic comorbidities, speculating on use of these values to stratify the risk of severe infection.
Flavor release and stability comparison between nano and conventional emulsion as influenced by saliva
Authors: Sanni Oluwatofunmi , Lakemond Catriona M. , Benjamin Ofir
Published: June 2022

Flavour release and emulsion stability depend on volatile organic compounds' environmental conditions, food microstructure, and physicochemical properties. The effect of pH (3.5 vs 7.0) and saliva addition on stability and flavour release from nano and conventional emulsions was investigated using particle size, charge and Lumisizer measurments. Larger particle sizes were observed at lower pressures and in saliva-containing emulsions. At 1700 bar, nano-emulsions (below 150 nm) were created at pH 3.5 and 7.0 including saliva-containing emulsions. As was clear from the creaming velocity measurements, saliva addition decreased the emulsion stability by reducing particle charges and increased viscosity by more than 50%, especially when prepared at pH 3.5 closer to the isoelectric point of the used emulsifier β-lactoglobulin (pH 5.2). (5.2). Flavour release from emulsions was measured at equilibrium using a phase ratio variation to determine partition coefficients and dynamically using an electronic nose. Partition coefficients of the flavour compounds for most conditions were two to four times lower in emulsions prepared at pH 7.0 than at pH 3.5 and in emulsions without saliva. Emulsions prepared with higher pressures showed stronger flavor release rates, while additional salvia dropped the release rate for ethyl acetate at pH 3.5. The physicochemical properties of flavour compounds, saliva addition and pH of emulsions influenced flavour release more than homogenization pressures. The potential in using nano-emulsions in food applications an be attributed higher stability and enhanced flavor release.
Risk factors associated with early mortality after recovery from severe listeriosis: a multicentre 17-year longitudinal study
Authors: Rivera-Izquierdo Mario , Galicia-García María Dolores , Láinez-Ramos-Bossini Antonio Jesús , Redruello-Guerrero Pablo , Fernández-Martínez Nicolás Francisco
Published: June 2022

Background

Listeriosis presents high rates of mortality but prognostic factors for early prevention are not well established. The aim of this study was to analyse factors associated with in-hospital and early mortality of adults after recovery from severe infection caused by Listeria monocytogenes.

Methods

All cases of listeriosis notified in the province of Granada from January 2005 to December 2021, including 9 centres, were included. Only laboratory confirmed non-neonatal cases were considered. Follow-up was conducted by accessing medical records and epidemiological data. Bivariate and multivariate analyses were conducted to detect potential risk factors associated to in-hospital mortality, 1-year, and 5-year early death after recovery. Multivariate Cox regression models were performed. A total of 206 patients were identified.

Results

The mean age was 62.6 years (sd, 18.8). A high frequency of comorbidities (88.3%) was observed, and 42 patients (20.4%) died during hospitalisation. Of the patients who recovered from acute infection, 26 (15.9%) died during the following year and 47 (28.7%) died during the following 5 years. The main factors associated with early mortality after recovery were age (HR: 1.03; 95% CI 1.02–1.07), diabetes mellitus (HR 1.86, 95% CI 1.01–3.44), chronic kidney disease (HR 3.96, 95% CI 1.87–8.38), liver disease (HR 3.62, 95% CI 1.64–8.51), and cancer (HR 3.76, 95% CI 1.90–7.46).

Conclusion

Listeriosis is associated with high early post-recovery mortality. Our study describes the main prognostic factors, which may help to improve preventive follow-up strategies of adults with severe listeriosis.
Ternary Egyptian fractions with prime denominator
Authors: Mond Adva , Portier Julien
Published: June 2022

For a prime number p, let $$A_3(p)= | \{ m \in \mathbb {N}: \exists m_1,m_2,m_3 \in \mathbb {N}, \frac{m}{p}=\frac{1}{m_1}+\frac{1}{m_2}+\frac{1}{m_3} \} |$$

A
3

(
p
)

=

|

{
m
∈
N
:
∃

m
1

,

m
2

,

m
3

∈
N
,

m
p

=

1

m
1

+

1

m
2

+

1

m
3

}

|

. In 2019 Luca and Pappalardi proved that $$x (\log x)^3 \ll \sum _{p \le x} A_{3}(p) \ll x (\log x)^5$$

x

(
log
x
)

3

≪

∑

p
≤
x

A
3

(
p
)

≪
x

(
log
x
)

5

. We improve the upper bound, showing $$\sum _{p \le x} A_{3}(p) \ll x (\log x)^3 (\log \log x)^2$$

∑

p
≤
x

A
3

(
p
)

≪
x

(
log
x
)

3

(
log
log
x
)

2

.
Risk Management in Drug-Device Combination Product Development
Authors: Kumoluyi Robin , Khanolkar Amit
Published: June 2022

Breakthrough innovations in drug and biologic based therapies as well as technological developments in design and development of medical devices have led to the rapid rise in the use of combination products in the last few decades. The resulting maturity of combination products as a global market category has led to 3 key trends: expanding adoption of medical devices for drug delivery, increasing complexity, and growing awareness of product experience and risk. Adoption of integrated combination product risk management enables robust product development and manufacturing strategies as well as facilitates alignment with regulators for efficient regulatory pathways and predictable outcomes.
Modeling of Ventilation’s Influence on Energy Consumption in Multi-cylinder Dryer Section Part 2: Simulations and Applications
Authors: Yin Yongjun , Yang Jingjing , Jia Yanlong , Lan Shuang , Liao Zhaoli
Published: June 2022

Ventilation system affects the water evaporation rate, energy consumption and the paper quality, which is considered as the largest optimization potential part of multi-cylinder dryer section. In this paper, energy consumption models of multi-cylinder dryer section are constructed by combining energy modules of moisture evaporation, heat recovery system, air heaters, supply air and exhaust air. Taking a corrugated paper machine as an example, ventilation system influence on the energy consumption of drying system is analyzed systematically. It is concluded that reducing the temperature of supply air and increasing exhaust humidity as much as possible to save energy consumption on the premise of meeting the safety production. The increase of supply air humidity will lead to the increase of steam consumption for heating supply air, power consumption of fans, and the total steam consumption in the drying process, so the intake point of supply air should be chosen at the point with low absolute humidity. The models can predict the energy consumption of ventilation system adjustment and optimization, and provide a method for energy-saving evaluation of ventilation system technical transformation in drying process.
Melincourt
Authors: Peacock Thomas Love
Published: June 2022

Melincourt (1817), Thomas Love Peacock's only three-volume novel, is also his most comprehensive work. In it, he explores a broad range of controversies: the dangers of 'paper money'; British consumers' complicity in slavery; the inequities of the current system of parliamentary representation; the problem of differentiating between human beings and other animals; and, most centrally, the question of whether and how the human condition might be improved. Peacock's brilliant synthesis of courtship novel and quest romance can only be fully appreciated against its colourful and fraught historical background, and Gary Dyer expertly equips readers with the historical and literary awareness required to recognise it as one of Peacock's most stimulating works. Vividly illuminating its remarkable plot – from the suitors' courtship of Anthelia Melincourt to the rescue party comprised of Sylvan Forester, Mr Fax and the chivalrous 'oran outang' Sir Oran Haut-ton – this edition makes Melincourt more accessible than ever before.
Role of Frictional Processes in Mesoscale Eddy Available Potential Energy Budget in the Global Ocean
Authors: Yang Peiran , Jing Zhao , Wang Hong , Wu Lixin , Chen Yuhu , Zhou Shenghui
Published: June 2022

Mesoscale eddies in the global ocean are thought to be powered primarily through transfer from available potential energy stored in mean flows to eddy available potential energy (EAPE). Part of the EAPE is further converted to eddy kinetic energy (EKE) with the residue dissipated through diabatic processes. Currently, the effect of frictional processes on the EAPE budget has not been thoroughly analyzed. Using an eddy‐resolving (1/10°) global climate simulation, we demonstrate that frictionally driven mesoscale eddy flow plays an important role in the EAPE budget, accounting for more than 30% of the EAPE‐to‐EKE conversion in the global ocean and dominating its seasonal cycle. This role can be understood based on the turbulent thermal wind balance under which the frictional force induces an ageostrophic secondary circulation producing a prominent EAPE‐to‐EKE conversion in the winter surface boundary layer.
Enhanced Ventilation in Energetic Regions of the Antarctic Circumpolar Current
Authors: Dove Lilian A. , Balwada Dhruv , Thompson Andrew F. , Gray Alison R.
Published: June 2022

Flow‐topography interactions along the path of the Antarctic Circumpolar Current generate standing meanders, create regions of enhanced eddy kinetic energy (EKE), and modify frontal structure. We consider the impact of standing meanders on ventilation based on oxygen measurements from Argo floats and the patterns of apparent oxygen utilization (AOU). Regions of high‐EKE have relatively reduced AOU values at depths 200–700 m below the base of the mixed layer and larger AOU variance, suggesting enhanced ventilation due to both along‐isopycnal stirring and enhanced exchange across the base of the mixed layer. Vertical exchange is inferred from finite‐size Lyapunov exponents, a proxy for the magnitude of surface lateral density gradients, which suggest that submesoscale vertical velocities may contribute to ventilation. The shaping of ventilation by standing meanders has implications for the temporal and spatial variability of air‒sea exchange.
Gravity‐Wave‐Driven Seasonal Variability of Temperature Differences Between ECMWF IFS and Rayleigh Lidar Measurements in the Lee of the Southern Andes
Authors: Gisinger Sonja , Polichtchouk Inna , Dörnbrack Andreas , Reichert Robert , Kaifler Bernd , Kaifler Natalie , Rapp Markus , Sandu Irina
Published: June 2022

Long‐term high‐resolution temperature data of the Compact Rayleigh Autonomous Lidar (CORAL) is used to evaluate temperature and gravity wave (GW) activity in ECMWF Integrated Forecasting System (IFS) over Río Grande (53.79°S, 67.75°W), which is a hot spot of stratospheric GWs in winter. Seasonal and altitudinal variations of the temperature differences between the IFS and lidar are studied for 2018 with a uniform IFS version. Moreover, interannual variations are considered taking into account updated IFS versions. We find monthly mean temperature differences <2 K at 20–40 km altitude. At 45–55 km, the differences are smaller than 4 K during summer. The largest differences are found during winter (4 K in May 2018 and −10 K in August 2018, July 2019 and 2020). The width of the difference distribution (15th/85th percentiles), the root mean square error, and maximum differences between instantaneous individual profiles are also larger during winter (>±10 K) and increase with altitude. We relate this seasonal variability to middle atmosphere GW activity. In the upper stratosphere and lower mesosphere, the observed temperature differences result from both GW amplitude and phase differences. The IFS captures the seasonal cycle of GW potential energy (Ep) well, but underestimates Ep in the middle atmosphere. Experimental IFS simulations without damping by the model sponge for May and August 2018 show an increase in the monthly mean Ep above 45 km from only ≈10% of the Ep derived from the lidar measurements to 26% and 42%, respectively. GWs not resolved in the IFS are likely explaining the remaining underestimation of the Ep.
Surface Ocean Biogeochemistry Regulates the Impact of Anthropogenic Aerosol Fe Deposition on the Cycling of Iron and Iron Isotopes in the North Pacific
Authors: König D. , Conway T. M. , Hamilton D. S. , Tagliabue A.
Published: June 2022

Distinctively‐light isotopic signatures associated with Fe released from anthropogenic activity have been used to trace basin‐scale impacts. However, this approach is complicated by the way Fe cycle processes modulate oceanic dissolved Fe (dFe) signatures (δ56Fediss) post deposition. Here we include dust, wildfire, and anthropogenic aerosol Fe deposition in a global ocean biogeochemical model with active Fe isotope cycling, to quantify how anthropogenic Fe impacts surface ocean dFe and δ56Fediss. Using the North Pacific as a natural laboratory, the response of dFe, δ56Fediss, and primary productivity are spatially and seasonally variable and do not simply follow the footprint of atmospheric deposition. Instead, the effect of anthropogenic Fe is regulated by the biogeochemical regime, specifically the degree of Fe limitation and rates of primary production. Overall, we find that while δ56Fediss does trace anthropogenic input, the response is muted by fractionation during phytoplankton uptake, but amplified by other isotopically‐light Fe sources.
A Century of Observed Temperature Change in the Indian Ocean
Authors: Wenegrat J. O. , Bonanno E. , Rack U. , Gebbie G.
Published: June 2022

The Indian Ocean is warming rapidly, with widespread effects on regional weather and global climate. Sea‐surface temperature records indicate this warming trend extends back to the beginning of the 20th century, however the lack of a similarly long instrumental record of interior ocean temperatures leaves uncertainty around the subsurface trends. Here we utilize unique temperature observations from three historical German oceanographic expeditions of the late 19th and early 20th centuries: SMS Gazelle (1874–1876), Valdivia (1898–1899), and SMS Planet (1906–1907). These observations reveal a mean 20th century ocean warming that extends over the upper 750 m, and a spatial pattern of subsurface warming and cooling consistent with a 1°–2° southward shift of the southern subtropical gyre. These interior changes occurred largely over the last half of the 20th century, providing observational evidence for the acceleration of a multidecadal trend in subsurface Indian Ocean temperature.
A Filtered Model for the Tropical Intraseasonal Moisture Mode
Authors: Wang Shuguang , Sobel Adam H.
Published: June 2022

The authors propose a new analytic approximation to aid understanding of the “moisture modes” that arise in idealized models of tropical intraseasonal oscillations. The approximation makes use of the separation between the time scale of the large scale flow and that of convective adjustment, but does not neglect the moisture tendency. The approximation filters out equatorial Kelvin waves, so that the only remaining mode is the intraseasonal moisture mode. Some physical insights are more transparent under the approximation: (a) vertical advection of moisture or temperature lead to a diffusion‐type operator that damps short waves, and instability is strongest at planetary scale. (b) A positive effective gross moist stability appears in a wave operator, while a negative effective gross moist stability leads to instabilities whose growth rates increase with zonal wavenumber. (c) Zonal moisture advection and surface flux feedbacks are crucial for both planetary instability and eastward propagation.
Combination of Decadal Predictions and Climate Projections in Time: Challenges and Potential Solutions
Authors: Befort D. J. , Brunner L. , Borchert L. F. , O’Reilly C. H. , Mignot J. , Ballinger A. P. , Hegerl G. C. , Murphy J. M. , Weisheimer A.
Published: June 2022

This study presents an approach to provide seamless climate information by concatenating decadal climate predictions and climate projections in time. Results for near‐surface air temperature over 29 regions indicate that such an approach has potential to provide meaningful information but can also introduce significant inconsistencies. Inconsistencies are often most pronounced for relatively extreme quantiles of the CMIP6 multi‐model ensemble distribution, whereas they are generally smaller and mostly insignificant for quantiles close to the median. The regions most affected are the North Atlantic, Greenland and Northern Europe. Two potential ways to reduce inconsistencies are discussed, including a simple calibration method and a weighting approach based on model performance. Calibration generally reduces inconsistencies but does not eliminate all of them. The impact of model weighting is minor, which is found to be linked to the small size of the decadal climate prediction ensemble, which in turn limits the applicability of that method.
Snow Nitrate Isotopes in Central Antarctica Record the Prolonged Period of Stratospheric Ozone Depletion From ∼1960 to 2000
Authors: Shi Guitao , Hu Ye , Ma Hongmei , Jiang Su , Chen Zhenlou , Hu Zhengyi , An Chunlei , Sun Bo , Hastings Meredith G.
Published: June 2022

Interpretation of NO3− variability recorded in ice cores remains challenging as it can be lost from snow. Here, we present 60‐year records of NO3− and its isotopic composition (δ15N, δ18O, and Δ17O) in snow in central Antarctica, Dome A. In the upper ∼90 cm snowpack, variations in concentration and isotopic composition of NO3− are dominated by photolytic loss, and δ18O and Δ17O of NO3− are associated with the recycling of NOx to NO3− in the condensed phase driven by photolysis. In the deeper snowpack (∼1960–2000), we observe prolonged trends in concentration and isotopic composition of NO3−, which are best explained as enhanced snow NO3− photolysis due to long‐term decreasing total column ozone (TCO). That is, the prolonged period of trends in NO3− and its isotopes in extremely low snow accumulation sites such as Dome A relay information on variations in TCO and consequently surface solar ultraviolet radiation over time.
Annual Mean Arctic Amplification 1970–2020: Observed and Simulated by CMIP6 Climate Models
Authors: Chylek Petr , Folland Chris , Klett James D. , Wang Muyin , Hengartner Nick , Lesins Glen , Dubey Manvendra K.
Published: June 2022

While the annual mean Arctic Amplification (AA) index varied between two and three during the 1970–2000 period, it reached values exceeding four during the first two decades of the 21st century. The AA did not change in a continuous fashion but rather in two sharp increases around 1986 and 1999. During those steps the mean global surface air temperature trend remained almost constant, while the Arctic trend increased. Although the “best” CMIP6 models reproduce the increasing trend of the AA in 1980s they do not capture the sharply increasing trend of the AA after 1999 including its rapid step‐like increase. We propose that the first sharp AA increase around 1986 is due to external forcing, while the second step close to 1999 is due to internal climate variability, which models cannot reproduce in the observed time.