bluuebunny/crossref_metadata_2025 huggingface dataset:
In vitro growth (IVG) of human ovarian follicles in frozen thawed ovarian cortex tissue culture supplemented with follicular fluid under hypoxic conditions
Authors: Schallmoser Andreas , Einenkel Rebekka , Färber Cara , Sänger Nicole
Published: July 2022

Background

Despite its clinical success rates, transplantation after ovarian tissue cryopreservation (OTC) remains a matter of concern. Certain cancer subtypes may lead to the transfer of malignant cells when transplantation of affected ovarian tissue is conducted. IVG and subsequent isolation of vital follicles obtained from frozen thawed ovarian tissue for further in vitro maturation (IVM) would expand current fertility protection techniques while reducing the risk of retransplanting malignant cells.

Methods

A total of 216 cortical biopsies from 3 patients were included in this study in 4 treatment groups. After freezing, thawing and 8 days of hypoxic tissue culture supplemented with different concentrations of human follicular fluid (HuFF) and follicle-stimulating hormone (FSH), follicles were isolated enzymatically and stained with calcein to determine follicular viability. Numbers and size of vital follicles were assessed by fluorescence microscopy (Ti2, Nikon) and specified by computer assisted, semi-automated measurement (NIS software, Nikon). To estimate the effect of in vitro culture on apoptosis, tissue sections were stained for nicked DNA (TUNEL) prior and after tissue culture.

Results

Analysing 3025 vital follicles, we observed significant differences [P < 0.01] regarding follicle size when hypoxic tissue culture was supplemented with HuFF compared with the control group on day 1, individual follicles reached sizes > 100 µm.

Conclusions

The results implicate that HuFF contains valuable factors contributing to significant IVG of follicles in human ovarian tissue and could be regarded as an additional tool in personalized fertility restoration prior to retransplantation of ovarian tissue.
Chorda tympani injury during endoscopic versus microscopic stapes surgery: a randomized controlled clinical trial
Authors: Moneir Waleed , Eladl Hesham Mohamed , El-Okda Moataz Mohammed , Ebada Hisham Atef
Published: July 2022

Objectives

The aim of this study was to compare the incidence of chorda tympani nerve (CTN) injury between endoscopic and microscopic stapes surgery.

Methods

This randomized controlled clinical trial included 88 patients who were randomly divided into two groups: endoscopic stapedotomy group (n = 44) and microscopic stapedotomy group (n = 44). The incidence of chorda tympani nerve (CTN) injury after surgery was determined by both subjective taste testing and chemical taste tests, before and after surgery. The results were compared between the two groups.

Results

The total number of patients who were identified as having CTN affection (based on the chemical testing) was 16 out of 88 (18.2%). The incidence was significantly lower in the endoscopic group (n = 2) than the microscopic group (n = 14) (p = 0.019).

Conclusion

Altered taste as a result of iatrogenic CTN injury can affect the patients’ quality of life. Endoscopic ear surgery offers better visualization, less need for extensive manipulation of the chorda tympani, and consequently decreased incidence of CTN injury.
Factors Affecting Domiciliary Non-Invasive Ventilation Compliance
Authors: Shah Amar J. , Florman Katia , Kaushal Nitika , Kwong Hiu Fung , Karoshi Akul , White Laura , Walker Ryan , Lin Yan-Pin , Ko Ho Juen , Saigal Anita , Devani Nikesh , Mansell Stephanie K. , Mandal Swapna
Published: July 2022

Few international studies have investigated factors affecting domiciliary non-invasive ventilation (D-NIV) compliance, and data from the UK are limited. We assessed compliance (defined as ≥ 4 h/night for at least 70% of the time) in a retrospective UK population study, at three time points (0–1 month, 3–4 months and 11–12 months), for all patients commenced on D-NIV over a 5-year period. A total of 359 patients were included. Non-compliant vs. compliant patients were significantly younger (median age 64 (IQR 52–72) vs. 67 (58–75) years, p = 0.032) and more likely to have schizophrenia, consistent at both 3–4 months (5% vs. 1%, p = 0.033) and 11–12 months (5% vs. 2%, p = 0.049). Repeated measures ANOVA demonstrated that the minutes [median (IQR)] of D-NIV used significantly increased at the three time points (0–1 month, 3–4 months and 11–12 months) for patients with hypertension [310 (147.5–431) vs. 341 (89–450) vs. 378 (224.5–477.5), p = 0.003]; diabetes [296.5 (132.5–417.5) vs. 342.5 (94.5–438.5) vs. 382 (247.5–476.25), p = 0.002] and heart failure [293 (177–403) vs. 326 (123–398) vs. 365 (212–493), p = 0.04]. In conclusion, younger and comorbid schizophrenic patients have lower D-NIV compliance rates, and our data suggest that persistence with D-NIV over a year may improve overall use.
The network of the subjective experience in embodiment phenomena
Authors: Tosi Giorgia , Romano Daniele
Published: July 2022

Introduction

Body illusions are designed to temporarily alter body representation by embodying fake bodies or part of them. Despite their large use, the embodiment questionnaires have been validated only for the embodiment of fake hands in the rubber hand illusion (RHI).

Methods

With the current study, we aimed at (1) extending the validation of embodiment questionnaires to a different illusory situation e.g., the full-body illusion (FBI); (2) comparing two methods to explore the questionnaires structures: a classic exploratory factor analysis (EFA) and a modern exploratory graph analysis (EGA). 118 healthy participants completed an FBI procedure where the subjective experience of embodiment was measured with a standard questionnaire.

Results

The EFA results in two-factor structures. However, the confirmatory factor analysis (CFA) fit indices do not show a good fit with the data. Conversely, the EGA identified four communities: ownership, agency, co-location and disembodiment; the solution was confirmed by a CFA.

Conlcusions

Overall, the EGA seems to be the best fitting method for the present data. Our results confirm the EGA as a suitable substitute for a more classical EFA. Moreover, the emerged structure suggests that the FBI induces similar effects to the RHI, implying that the embodiment sensations are common to different illusory methods.
Early mortality factors in immune checkpoint inhibitor monotherapy for advanced or metastatic non-small cell lung cancer
Authors: Takeuchi Eiji , Kondo Kensuke , Okano Yoshio , Kunishige Michihiro , Kondo Yoshihiro , Kadota Naoki , Machida Hisanori , Hatakeyama Nobuo , Naruse Keishi , Ogino Hirokazu , Nokihara Hiroshi , Shinohara Tsutomu , Nishioka Yasuhiko
Published: July 2022

Purpose

Immune checkpoint inhibitors (ICI) are a promising treatment, but may cause hyperprogressive disease and early death. The present study investigated early mortality factors in ICI monotherapy for lung cancer.

Patients and methods

We retrospectively reviewed all patients diagnosed with advanced or metastatic non-small cell lung cancer (NSCLC) and treated with ICI monotherapy (nivolumab, pembrolizumab, and atezolizumab) between March 2016 and August 2021 at National Hospital Organization Kochi Hospital and Tokushima University. Early death was defined as patients who died within 60 days of ICI treatment.

Results

A total of 166 patients were included. The majority of patients (87%) had an Eastern cooperative oncology group (ECOG) Performance status (PS) of 0/1. There were 21 early deaths. Significant differences were observed in ECOG PS, the histological type, liver metastasis, tumor size, the white blood cell count, neutrophils (%), lymphocytes (%), the neutrophil-to-lymphocyte ratio in serum (sNLR), C-reactive protein (CRP), and albumin between the groups with or without early death. Univariate logistic regression analyses identified ECOG PS score ≥ 2, liver metastasis, tumor size ≥ 5 cm, neutrophils ≥ 69%, lymphocytes < 22%, sNLR ≥ 4, CRP ≥ 1 mg/dl, and albumin < 3.58 g/dl as significant risk factors for early death. A multivariate logistic regression analysis revealed that liver metastasis (Odds ratio [OR], 10.3; p = 0.008), ECOG PS score ≥ 2 (OR, 8.0; p = 0.007), and a smoking history (OR, 0.1; p = 0.03) were significant risk factors for early death.

Conclusion

Liver metastases, ECOG PS score ≥ 2, and a non-smoking history are early mortality factors in ICI monotherapy for advanced or metastatic NSCLC.
Reliable detection of compressed and encrypted data
Authors: De Gaspari Fabio , Hitaj Dorjan , Pagnotta Giulio , De Carli Lorenzo , Mancini Luigi V.
Published: July 2022

Several cybersecurity domains, such as ransomware detection, forensics and data analysis, require methods to reliably identify encrypted data fragments. Typically, current approaches employ statistics derived from byte-level distribution, such as entropy estimation, to identify encrypted fragments. However, modern content types use compression techniques which alter data distribution pushing it closer to the uniform distribution. The result is that current approaches exhibit unreliable encryption detection performance when compressed data appear in the dataset. Furthermore, proposed approaches are typically evaluated over few data types and fragment sizes, making it hard to assess their practical applicability. This paper compares existing statistical tests on a large, standardized dataset and shows that current approaches consistently fail to distinguish encrypted and compressed data on both small and large fragment sizes. We address these shortcomings and design EnCoD, a learning-based classifier which can reliably distinguish compressed and encrypted data. We evaluate EnCoD on a dataset of 16 different file types and fragment sizes ranging from 512B to 8KB. Our results highlight that EnCoD outperforms current approaches by a wide margin, with accuracy ranging from $$\sim 82\%$$

∼
82
%

for 512B fragments up to $$\sim 92\%$$

∼
92
%

for 8KB data fragments. Moreover, EnCoD can pinpoint the exact format of a given data fragment, rather than performing only binary classification like previous approaches.
Transport and mechanical behavior in PEO-LLZO composite electrolytes
Authors: Kim Hong-Keun , Barai Pallab , Chavan Kanchan , Srinivasan Venkat
Published: July 2022

Composite solid electrolytes (CEs), wherein ion-conducting polymer and ceramic/glass is mixed, are promising candidates for all-solid-state batteries due to their promise of acceptable ionic conductivity and mechanical properties compared to their individual constituents. While numerous studies have focused on improving the performance of CEs, it is still unclear what the material targets are that can result in improved macroscopic performance especially in light of the coupled needs for high transport and high mechanical strength in these materials. In this study, a two-dimensional (2D) mathematical model is developed to investigate electrochemical and mechanical characteristics of CEs. The model is compared to CEs consisting of poly-ethylene-oxide (PEO) polymer and lithium lanthanum zirconium oxide (LLZO) ceramic material with examination of the impact of varying LLZO volume fractions. The potential drop at the PEO-LLZO interface is evaluated using the junction potential theory. Using experimental data from the literature, the model estimates the ionic conductivity, effective transference number, and mechanical stiffness of the CEs. While the mechanical stiffness improves with increasing volume fraction of LLZO, the impact on conductivity and transference number depends on interfacial resistance at the interface. Finally, the study reports CE’s potential to enhance Li-ion transport and mechanical properties to inhibit lithium (Li) dendrite growth.
Estimating loss in capability wellbeing in the first year of the COVID-19 pandemic: a cross-sectional study of the general adult population in the UK, Australia and the Netherlands
Authors: Mitchell Paul Mark , Morton Rachael L. , Hiligsmann Mickaël , Husbands Samantha , Coast Joanna
Published: July 2022

Objectives

To estimate capability wellbeing lost from the general adult populations in the UK, Australia and the Netherlands in the first year of the COVID-19 pandemic and the associated social restrictions, including lockdowns.

Design

Cross-sectional with recalled timepoints.

Setting

Online panels in the UK, Australia and the Netherlands conducted in February 2021 (data collected 26 January–2 March 2021).

Participants

Representative general adult (≥ 18 years old) population samples in the UK (n = 1,017), Australia (n = 1,011) and the Netherlands (n = 1,017)

Main outcome measure

Participants completed the ICECAP-A capability wellbeing measure in February 2021, and for two recalled timepoints during the initial lockdowns in April 2020 and in February 2020 (prior to COVID-19 restrictions in all three countries). ICECAP-A scores on a 0–1 no capability–full capability scale were calculated for each timepoint. Societal willingness to pay estimates for a year of full capability (YFC) was used to place a monetary value associated with change in capability per person and per country. Paired t tests were used to compare changes in ICECAP-A and YFC from pre- to post-COVID-19-related restrictions in each country.

Results

Mean (standard deviation) loss of capability wellbeing during the initial lockdown was 0.100 (0.17) in the UK, 0.074 (0.17) in Australia and 0.049 (0.12) in the Netherlands. In February 2021, losses compared to pre-lockdown were 0.043 (0.14) in the UK, 0.022 (0.13) in Australia and 0.006 (0.11) in the Netherlands. In monetary terms, these losses were equivalent to £14.8 billion, AUD$8.6 billion and €2.1 billion lost per month in April 2020 and £6.4 billion, A$2.6 billion and €260 million per month in February 2021 for the UK, Australia and the Netherlands, respectively.

Conclusions

There were substantial losses in capability wellbeing in the first year of the COVID-19 pandemic. Future research is required to understand the specific impact of particular COVID-19 restrictions on people’s capabilities.
Papillary thyroid cancer with Hashimoto’s thyroiditis attenuates the tumour aggressiveness through the up-regulation of E-cadherin and TGF-β expression
Authors: Kim Su Jin , Lee Seung-Eun , Kim Young Il , Nam-Goong Il Sung , Jung Hyo Won , Kim Eun Sook
Published: July 2022

Human papillary thyroid cancer (PTC) is often associated with Hashimoto’s thyroiditis (HT), and their coexistence improves the prognosis of PTC.Aim of the study. The objective of our study is to investigate the expression of cadherins and TGF-β which are regulators in the tumour aggressiveness with metastatic spread in PTC patients and its relationship with HT. The expression of E-cadherin and N-cadherin was measured in thyroid tissues of healthy volunteers and PTC patients with HT (PTC/HT) or without. The E-cadherin expression was also determined in thyroid cancer cells (TPC1, SNU373, SNU790, 8505C, CAL62, and FTC133). Cell migration was measured by wound healing assay. The expression of N-cadherin, ICAM1, and TGF-β was measured in thyroid tissues and plasma. The E-cadherin expression was significantly increased in PTC/HT patients compared with PTC alone. Meanwhile, the N-cadherin expression was significantly decreased in PTC/HT patients. The E-cadherin expression was only observed in FTC cells, and the overexpression of E-cadherin inhibited cancer cell migration. The TGF-β expression was significantly increased in PTC/HT patients, and the plasma levels were higher in PTC/HT patients than in PTC alone. The expression of N-cadherin and ICAM-1 was significantly decreased in PTC/HT patients. Our results indicate that the expression of E-cadherin and TGF-β was higher in PTC/HT patients than in PTC alone. This suggests that the presence of PTC with HT may attenuate the tumour aggressiveness and metastasis through the up-regulation of E-cadherin and TGF-β expression.
Exploring interoperability of distributed Ledger and Decentralized Technology adoption in virtual enterprises
Authors: Bokolo Anthony Jnr.
Published: July 2022

The breakthrough of Distributed Ledger Technologies (DLT) has enabled the emergence and implementation of a wide range of digital platforms in Virtual Enterprises (VE) which collaborate to provide digital services. DLT has the potential to revolutionize VE by offering transparent, decentralized, trustworthy, data provenance, reliable, and auditable features. Yet, the full deployment of DLT systems and digital platforms is still limited since some systems are operating in isolation. Hence, DLT interoperability is one of the challenges inhibiting widespread adoption of DLT platforms. DLT interoperability represents the ability for one distributed ledger platform to interact and share data with other legacy digital applications. It is inevitable to orchestrate these digital platforms fragments by introducing a cross-DLT platform integration to govern data usage within VE. Presently, already proposed approaches for DLT interoperability such as naive relay, sidechain, oracle solutions notary scheme, or relay chain are mostly not employed as they are either resource-intensive or too expensive to operate. Therefore, this paper presents a layered architecture that aids interoperability of DLT, and digital platforms based on IOTA Tangle. Design science method is adopted, and case demonstration is carried out to show how IOTA Tangle enable VE to provide an innovative virtual asset payment platform for seamless electric mobility as a service to clients. IOTA was employed as the DLT platform due to its data traceability, immutability, and tamper-proof features which allow for verification of integrity of data. IOTA offers flexibility and performance to support a reliable digital solution. Findings from this study presents a layered architecture that aids IOTA Tangle to make requests, inter-communicate, and share data via RESTful application programming interface as gateway with other external digital platforms deployed by VE to achieve an interoperable eco-system.
Enhanced biocontrol services in artificially selected strains of Orius laevigatus
Authors: Mendoza José Enrique , Balanza Virginia , Rodríguez-Gómez Amador , Cifuentes Dina , Bielza Pablo
Published: July 2022

Augmentative biological control in protected crops relies mainly on omnivorous predators. Their performance as biological control agents (BCA) depends on several characteristics of the species, which in turn may differ among strains within a species. We have recently reported the achievement of twoOrius laevigatus(Hemiptera: Anthocoridae) strains showing a significant larger body size or better fitness when feeding on pollen, two characteristics having a key impact on field performance. However, selection towards a specific trait might result in trade-offs, such as reduced predation capacity, which may impair control efficiency. Therefore, the predation capacity of these selected populations was tested in laboratory as a first step prior to its field use. Functional response to different densities ofFrankliniella occidentalis(Thysanoptera: Thripidae) (adults and larvae) andMyzus persicae(Hemiptera: Aphididae) (nymphs) were studied in the large-sized and pollen-tolerantO. laevigatusstrains in comparison with commercial and wild populations. A type-II functional response was observed regardless of the population. Body size was significantly related to thrips but not to aphid predation. The large-sized strain showed a superior predation capacity, both on thrips larvae and especially on adult thrips, although not on aphids. Therefore, the larger body size of the selected strain may increase its effectiveness as BCA of thrips. Regarding the pollen-tolerant strain, no trade-offs were observed in predation rates on adults or larvae of thrips, but it showed higher predation capacity on aphid nymphs, suggesting an expanded prey range. Implications of such enhanced biocontrol services on crop protection are also discussed.
(Re)Conceptualizing decision-making tools in a risk governance framework for emerging technologies—the case of nanomaterials
Authors: Mullins Martin , Himly Martin , Llopis Isabel Rodríguez , Furxhi Irini , Hofer Sabine , Hofstätter Norbert , Wick Peter , Romeo Daina , Küehnel Dana , Siivola Kirsi , Catalán Julia , Hund-Rinke Kerstin , Xiarchos Ioannis , Linehan Shona , Schuurbiers Daan , Bilbao Amaia García , Barruetabeña Leire , Drobne Damjana
Published: July 2022

The utility of decision-making tools for the risk governance of nanotechnology is at the core of this paper. Those working in nanotechnology risk management have been prolific in creating such tools, many derived from European FP7 and H2020-funded projects. What is less clear is how such tools might assist the overarching ambition of creating a fair system of risk governance. In this paper, we reflect upon the role that tools might and should play in any system of risk governance. With many tools designed for the risk governance of this emerging technology falling into disuse, this paper provides an overview of extant tools and addresses their potential shortcomings. We also posit the need for a data readiness tool. With the EUs NMP13 family of research consortia about to report to the Commission on ways forward in terms of risk governance of this domain, this is a timely intervention on an important element of any risk governance system.
Optimal droplet transfer mode maintenance for wire + arc additive manufacturing (WAAM) based on deep learning
Authors: Qin Jian , Wang Yipeng , Ding Jialuo , Williams Stewart
Published: July 2022

In the last decade, wire + arc additive manufacturing (WAAM), which is one of the most promising metal additive manufacturing technologies, has been attracting high interest from both academia and industry. WAAM systems are increasingly employed in the industry and academia, but there are still several challenges and barriers to process stability control. The process stability is highly dependent on how the molten feed wire is added into the melt pool, which is known as the droplet transfer mode. To ensure a stable WAAM deposition process, it is essential to maintain the transfer mode in a suitable stable status. Without an effective transfer mode control method, the operators need to determine and control the transfer mode based on their experience using manual adjustment, which is difficult to achieve in a long period of production process. In this paper, a deep learning-based technology was proposed for the control of the droplet transfer mode based on the data collected from the WAAM process. A long short term memory neural network was applied as the core transfer mode classification model. A time-series data, arc voltage, was collected and statistical and frequency features were extracted, which included 11 relevant features, as the inputs of the classification model. Then, the distance between the melted wire and the melt pool was adjusted based on the determined transfer mode to keep a suitable stability of the process. A case study was used to evaluate the proposed approach and to show its merit. The proposed approach was compared to three commonly used machine learning algorithms,k-nearest neighbours, support vector machine, and decision tree. The proposed method obtained the highest accuracy in determining the transfer mode, which was over 91%. The performance of the proposed approach was also evaluated by the single-pass and oscillated wall building. The proposed deep learning based approach improved the process stability in real-time, which resulted in better deposition qualities, in terms of geometry size and processing cleanliness compared to without control. Furthermore, this data-driven method could be applied to other WAAM processes and materials.
Computing the sequence of k-cardinality assignments
Authors: Rosenmann Amnon
Published: July 2022

The k-cardinality assignment (k-assignment, for short) problem asks for finding a minimal (maximal) weight of a matching of cardinality k in a weighted bipartite graph $$K_{n,n}$$

K

n
,
n

, $$k \le n$$

k
≤
n

. Here we are interested in computing the sequence of all k-assignments, $$k=1,\ldots ,n$$

k
=
1
,
…
,
n

. By applying the algorithm of Gassner and Klinz (2010) for the parametric assignment problem one can compute in time $${\mathcal {O}}(n^3)$$

O
(

n
3

)

the set of k-assignments for those integers $$k \le n$$

k
≤
n

which refer to essential terms of the full characteristic maxpolynomial $${\bar{\chi }}_{W}(x)$$

χ

¯

W

(
x
)

of the corresponding max-plus weight matrix W. We show that $${\bar{\chi }}_{W}(x)$$

χ

¯

W

(
x
)

is in full canonical form, which implies that the remaining k-assignments refer to semi-essential terms of $${\bar{\chi }}_{W}(x)$$

χ

¯

W

(
x
)

. This property enables us to efficiently compute in time $${\mathcal {O}}(n^2)$$

O
(

n
2

)

all the remaining k-assignments out of the already computed essential k-assignments. It follows that time complexity for computing the sequence of all k-cardinality assignments is $${\mathcal {O}}(n^3)$$

O
(

n
3

)

, which is the best known time for this problem.
Shock waves in gas flows with nanoparticles
Authors: Avramenko Andriy A. , Shevchuk Igor V. , Dmitrenko Nataliia P. , Skitsko Ivan F.
Published: July 2022

The paper focuses on the analytical analysis of the propagation of a normal shock wave in an adiabatic gas flow with nanoparticles. A modified Rankine–Hugoniot model was used for this purpose. A solution is obtained for the Rankine–Hugoniot conditions in a gas flow with different nanoparticle concentrations, which makes it possible to analyze the dynamics of variation of the parameters of this type of flow under a shock wave. The variation of velocity, pressure and entropy production of the adiabatic gas flow during a direct shock wave depending on the concentration of nanoparticles in the gas was depicted graphically. It was revealed that increasing the nanoparticle concentration to φ ~ 0.1 weakens the effect of the shock wave, and then, after passing the zone of minimum parameters, the intensity of the shock wave increases.
Towards a systematic evaluation of moral bioenhancement
Authors: Kudlek Karolina
Published: July 2022

The ongoing debate about moral bioenhancement (MBE) has been exceptionally stimulating, but it is defined by extreme polarization and lack of consensus about any relevant aspect of MBE. This article reviews the discussion on MBE, showing that a lack of consensus about enhancements’ desirable features and the constant development of the debate calls for a more rigorous ethical analysis. I identify a list of factors that may be of crucial importance for illuminating the matters of moral permissibility in the MBE debate and which could help us move beyond the current lack of consensus. More precisely, I propose three important theoretical and normative standards that MBE should satisfy if we wish to mitigate the concerns about its utter impermissibility. Systematically assessing MBE interventions across the presented categories should provide valuable conclusions about its theoretical soundness and feasibility, its compatibility with fundamental moral norms, and its compatibility with or facilitation of socio-political goals of equality and justice.
Cyclic Gate Recurrent Neural Networks for Time Series Data with Missing Values
Authors: Weerakody Philip B. , Wong Kok Wai , Wang Guanjin
Published: July 2022

Gated Recurrent Neural Networks (RNNs) such as LSTM and GRU have been highly effective in handling sequential time series data in recent years. Although Gated RNNs have an inherent ability to learn complex temporal dynamics, there is potential for further enhancement by enabling these deep learning networks to directly use time information to recognise time-dependent patterns in data and identify important segments of time. Synonymous with time series data in real-world applications are missing values, which often reduce a model’s ability to perform predictive tasks. Historically, missing values have been handled by simple or complex imputation techniques as well as machine learning models, which manage the missing values in the prediction layers. However, these methods do not attempt to identify the significance of data segments and therefore are susceptible to poor imputation values or model degradation from high missing value rates. This paper develops Cyclic Gate enhanced recurrent neural networks with learnt waveform parameters to automatically identify important data segments within a time series and neglect unimportant segments. By using the proposed networks, the negative impact of missing data on model performance is mitigated through the addition of customised cyclic opening and closing gate operations. Cyclic Gate Recurrent Neural Networks are tested on several sequential time series datasets for classification performance. For long sequence datasets with high rates of missing values, Cyclic Gate enhanced RNN models achieve higher performance metrics than standard gated recurrent neural network models, conventional non-neural network machine learning algorithms and current state of the art RNN cell variants.
Prediction with expert advice applied to the problem of prediction with expert advice
Authors: Herrmann Daniel A.
Published: July 2022

We often need to have beliefs about things on which we are not experts. Luckily, we often have access to expert judgements on such topics. But how should we form our beliefs on the basis of expert opinion when experts conflict in their judgments? This is the core of the novice/2-expert problem in social epistemology. A closely related question is important in the context of policy making: how should a policy maker use expert judgments when making policy in domains in which she is not herself an expert? This question is more complex, given the messy and strategic nature of politics. In this paper we argue that the prediction with expert advice (PWEA) framework from machine learning provides helpful tools for addressing these problems. We outline conditions under which we should expert PWEA to be helpful and those under which we should not expect these methods to perform well.
CuCe-Ferrite/TiO2 Nanocomposite as an Efficient Magnetically Separable Photocatalyst for Dye Pollutants Decolorization
Authors: Helmy Elsayed T. , Soliman Usama A. , Elbasiony A. M. , Nguyen Ba-Son
Published: July 2022

In this work, a magnetically separated photocatalyst with great efficiency CuCe-Ferrite/TiO2composite was prepared and characterized by X-ray diffraction (XRD), UV–Vis spectrophotometry, Fourier transformer infra-red spectroscopy (FTIR), field emission scanning electron microscopy (FE-SEM), high resolution transmission electron microscopy (HR-TEM), energy dispersive X-ray spectroscopy (EDX) and vibrating sample magnetometer (VSM). Single-phase cubic spinel was formed by calcining the prepared sample at a temperature of 550 °C, according to the results. Different concentrations of reactive red 250 (RR250) dye photodegradation was evaluated using different doses of CuCe-ferrite/ TiO2and TiO2NPs. Higher efficiency of RR250 photodegradation up to 100% was obtained using CuCe-ferrite/ TiO2. The photodegradation efficiency was confirmed using chemical oxygen demand (COD) test of both treated and untreated samples. The oxidation process was mostly mediated by photogenerated.O2−according to scavenger test results. The catalyst possess higher photodegradation efficiency even after regeneration for ten times.

Graphical Abstract
A framework for supporting systems thinking and computational thinking through constructing models
Authors: Shin Namsoo , Bowers Jonathan , Roderick Steve , McIntyre Cynthia , Stephens A. Lynn , Eidin Emil , Krajcik Joseph , Damelin Daniel
Published: July 2022

We face complex global issues such as climate change that challenge our ability as humans to manage them. Models have been used as a pivotal science and engineering tool to investigate, represent, explain, and predict phenomena or solve problems that involve multi-faceted systems across many fields. To fully explain complex phenomena or solve problems using models requires both systems thinking (ST) and computational thinking (CT). This study proposes a theoretical framework that uses modeling as a way to integrate ST and CT. We developed a framework to guide the complex process of developing curriculum, learning tools, support strategies, and assessments for engaging learners in ST and CT in the context of modeling. The framework includes essential aspects of ST and CT based on selected literature, and illustrates how each modeling practice draws upon aspects of both ST and CT to support explaining phenomena and solving problems. We use computational models to show how these ST and CT aspects are manifested in modeling.
The impact of particle radiotherapy on the functioning of cardiac implantable electronic devices: a systematic review of in vitro and in vivo studies according to PICO criteria
Authors: Barcellini Amelia , Dusi Veronica , Mirandola Alfredo , Ronchi Sara , Riva Giulia , Dal Mas Francesca , Massaro Maurizio , Vitolo Viviana , Ciocca Mario , Rordorf Roberto , Orlandi Ester
Published: July 2022

The number of oncological patients who may benefit from proton beam radiotherapy (PBT) or carbon ion radiotherapy (CIRT), overall referred to as particle radiotherapy (RT), is expected to strongly increase in the next future, as well as the number of cardiological patients requiring cardiac implantable electronic devices (CIEDs). The management of patients with a CIED requiring particle RT deserves peculiar attention compared to those undergoing conventional photon beam RT, mostly due to the potential generation of secondary neutrons by particle beams interactions. Current consensus documents recommend managing these patients as being at intermediate/high risk of RT-induced device malfunctioning regardless of the dose on the CIED and the beam delivery method used, despite the last one significantly affects secondary neutrons generation (very limited neutrons production with active scanning as opposed to the passive scattering technique). The key issues for the current review were expressed in four questions according to the Population, Intervention, Control, Outcome criteria. Three in vitro and five in vivo studies were included. Based on the available data, PBT and CIRT with active scanning have a limited potential to interfere with CIED that has only emerged from in vitro study so far, while a significant potential for neutron-related, not severe, CIED malfunctions (resets) was consistently reported in both clinical and in vitro studies with passive scattering.
The hypertrophic amygdala shape associated with anxiety in patients with primary dysmenorrhea during pain-free phase: insight from surface-based shape analysis
Authors: Yu Siyi , Wei Wei , Liu Liying , Guo Xiaoli , Shen Zhifu , Tian Jin , Zeng Fang , Liang Fanrong , Yang Jie
Published: July 2022

Background

Primary dysmenorrhea (PDM) is highly associated with mood symptoms. However, the neuropathology of these comorbidities is unclear. In the present study, we aimed to investigate the structural changes in the amygdala of patients with PDM during the pain-free phase using a surface-based shape analysis.

Methods

Forty-three PDM patients and forty healthy controls were recruited in the study, and all participants underwent structural magnetic resonance imaging scans during their periovulatory phase. FMRIB’s Integrated Registration and Segmentation Tool (FIRST) was employed to assess the subcortical volumetric and surface alterations in patients with PDM. Moreover, correlation and mediation analyses were used to detect the clinical significance of the subcortical morphometry alteration.

Results

PDM patients showed hypertrophic alteration of the amygdala in the left superficial nuclei and right basolateral and superficial nuclei but not for the whole amygdala volume. The hypertrophic amygdala was associated with disease duration, pain severity and anxiety symptoms during the menstrual period. Furthermore, the hypertrophic left amygdala could mediate the association between disease duration and anxiety severity.

Conclusions

The results of the current study demonstrated that the localized amygdala shape hypertrophy was present in PDM patients even in the pain-free phase. In addition, the mediator role of the hypertrophic amygdala indicates the potential target of amygdala for anxiety treatment in PDM treatment in the pain-free phase.
The Infinite-Dimensional Standard and Strict Bounded Real Lemmas in Continuous Time: The Storage Function Approach
Authors: Ball J. A. , ter Horst S. , Kurula M.
Published: July 2022

The bounded real lemma (BRL) is a classical result in systems theory, which provides a linear matrix inequality criterium for dissipativity, via the Kalman-Yakubovich-Popov (KYP) inequality. The BRL has many applications, among others in $$H^\infty $$

H
∞

control. Extensions to infinite dimensional systems, although already present in the work of Yakubovich, have only been studied systematically in the last few decades. In this context various notions of stability, observability and controllability exist, and depending on the hypothesis one may have to allow the KYP-inequality to have unbounded solutions which forces one to consider the KYP-inequality in a spatial form. In the present paper we consider the BRL for continuous time, infinite dimensional, linear well-posed systems. Via an adaptation of Willems’ storage function approach we present a unified way to address both the standard and strict forms of the BRL. We avoid making use of the Cayley transform and work only in continuous time. While for the standard bounded real lemma, we obtain analogous results as there exist for the discrete time case, when treating the strict case additional conditions are required, at least at this stage. This might be caused by the fact that the Cayley transform does not preserve exponential stability, an important property in the strict case, when transferring a continuous-time system to a discrete-time system.
An imaginary refined count for some real rational curves
Authors: Blomme Thomas
Published: July 2022

In 2015, Mikhalkin introduced a refined count for the real rational curves in a toric surface which pass through a set consisting of real points and pairs of complex conjugated points chosen generically on the toric boundary of the surface. He then proved that the result of this refined count depends only on the number of pairs of complex conjugated points on each toric divisor. Using the tropical geometry approach and the correspondence theorem, we address the computation of the refined count when the pairs of complex conjugated points are chosen purely imaginary and belonging to the same component of the toric boundary. Despite the non-genericity, we relate this refined count for purely imaginary values to the refined invariant of Mikhalkin for generic values. That allows us to extend the relation between these classical refined invariants and the tropical refined invariants from Block–Göttsche.
A quantitative evaluation of the biochar’s influence on plant disease suppress: a global meta-analysis
Authors: Yang Yuheng , Chen Tongtong , Xiao Ran , Chen Xinping , Zhang Tong
Published: July 2022

Numerous studies have demonstrated that soil applications of biochar contribute to plant disease suppression and growth promotion. Here, we quantitatively evaluated the performance of biochars on plant disease suppression and production using meta-analysis of literature data. The results indicated that biochar amendment dramatically reduced disease severity (DS) by 47.46% while increasing plant biomass by 44.05%. The highest disease suppression was achieved with soil application of straw-derived biochar compared to biochar from other feedstocks, while no significant increase in yield was found with straw-derived biochar. Biochars pyrolyzed at medium temperatures (350–600 °C) facilitate both disease controlling and growth promotion. Soil application of biochars between 3 and 5% significantly decreased plant DS by 59.11%, and inverted U-shaped biochar dose/DS suppression curve and biochar dose/growth curve were observed. In cash crop fields, the DS of plants amended with biochar was reduced over 50%, which was  significantly higher than that of grain crops and perennial trees. Furthermore, biochar performance on plant disease suppression was higher for airborne pathogens than for soilborne pathogens, possibly due to the systemic activation of plant defences by biochar amendment. Additionally, a reduction of DS by biochar was observed on plants grown in agricultural soils. Our work contributes to the standardization of biochar production and provides a reference for improving the function of biochar in disease control.

Graphical Abstract
A nanoscale observation to explain the discrepancy of electron exchange capacities between biochar containing comparable surface redox-active moieties
Authors: Li Shasha , Shao Liming , Zhang Hua , Lu Xuemin , Lü Fan , He Pinjing
Published: July 2022

Biochar, possessing electron exchange capacities (EEC), is generally involved in environmental redox reactions due to the presence of redox-active moieties (RAMs). The phenomenon that chars containing comparable RAMs possess differential EEC revealed that the accessibility of RAMs is important to the redox properties. However, many studies have focused on the type of RAMs, whereas the distribution has been insufficiently investigated. Herein, we achieved nanoscale observation of electroactive moieties on the surface of six chars using a conductive atomic force microscope. For the two specific kinds of chars with submicron particles and opposite current distributions, the submicron particles took up only 1–4‰wt of biochar accounting for approximately 30–50% of electron-donating capacity (EDC), and electron-accepting capacity (EAC) became 87% and 1.40 times as before after removing submicron particles, respectively. Meanwhile, the combined impact of RAMs and surface topography (that uneven distribution of RAMs resulted in outstanding EEC by enhancing accessibility) was clarified. Furthermore, direct evidence of the link between char structure and EEC (that condensed aromatic structures were indispensable to EAC while both heteroatoms and amorphous aromatics contributed to EDC) was established. These findings can aid in understanding the functions of biochar in biotic and abiotic redox processes.

Graphical Abstract
Biochar amendment alters the partitioning of nitrate reduction by significantly enhancing DNRA in a paddy field
Authors: Wei Zhijun , Senbayram Mehmet , Zhao Xu , Li Chenglin , Jin Ke , Wu Min , Rahman M. Mizanur , Shan Jun , Yan Xiaoyuan
Published: July 2022

Using 15N tracer technique, we investigated the potential rates of denitrification, anaerobic ammonium oxidation, dissimilatory nitrate reduction to ammonium (DNRA), and their partitioning among nitrate reduction, as well as the N2O emission rates in a paddy soil receiving various biochar (0%, 0.03%, 0.1%, 0.5%, and 1.0%; w/w) and straw (0.1%) over six consecutive years. Results showed that except for the 1.0% amendment treatment, biochar significantly (P < 0.05) increased denitrification rates by 10.19‒75.96% compared with non-biochar amended treatment, and that  biochar significantly (P < 0.05) increased DNRA rates by 1.63‒6.84 folds relative to non-biochar amended treatment. Consequently, biochar shifted more NO3– partitioning toward DNRA process, as suggested by the increased DNRA/(denitrification + DNRA) ratios from 1.60 to 13.18%. On the other hand, biochar significantly (P < 0.05) reduced N2O emission rates by 61.86–97.65% accompanied by a significant decrease in N2O/(N2O + N2) ratios (65.29–98.39%), indicating biochar amendment facilitated the reduction of N2O to N2. The promoting effects of biochar on DNRA rates and DNRA/(denitrification + DNRA) ratios were attributed to the increased carbon availability and the altered nitrate reducer communities. Collectively, our study suggests that biochar amendment in the paddy soil is helpful for N conservation by favoring nitrate partitioning toward DNRA process, which deepens our understanding of how biochar mediates N cycling in the paddy field.

Graphical Abstract
Weak-acid biochar catalyst prepared from mechanochemically-activated biomass and humic acid for production of 5-hydroxymethylfurfural
Authors: Guo Haixin , Ogawa Sohei , Isoda Yukiya , Shen Feng , Smith Richard Lee
Published: July 2022

Many types of sustainably-prepared functional biochar catalysts are needed to transform biomass substrates into platform chemicals. In this work, weak-acid biochar catalysts were prepared by mix ball-milled (10 min, isothermal, room temperature) cherry blossom tree leaf biomass (BM) with humic acid (H) prior to carbonization of samples for 1 h under nitrogen gas. Characterization of the as-prepared materials (HBM-carbonization temperature in °C) showed that humic acid activated the biochars and increased their number of oxygen-containing functional (–COOH, OH) groups. The weak-acid biochars were applied as heterogeneous catalysts for dehydration of fructose to 5-hydroxymethylfurfural (5-HMF), where it was found that biochar catalyst, HBM-400, gave 100% fructose conversion and 77.5% 5-HMF yields in an ionic liquid (1-butyl-3-methylimidazolium chloride) reaction system (140 °C, 60 min reaction time). As-prepared HBM-400 biochars exhibited constant catalytic activity for fructose dehydration with repeated use without any type of reactivation treatment and were stable for 5 cycles. Humic acid is an effective additive for preparing weak-acid catalytic materials from waste biomass.

Graphical Abstract
Preparation and characterization of MgO hybrid biochar and its mechanism for high efficient recovery of phosphorus from aqueous media
Authors: Fang Yueru , Ali Amjad , Gao Yuxi , Zhao Peng , Li Ronghua , Li Xianxian , Liu Junxi , Luo Yuan , Peng Yaru , Wang Hailong , Liu Hongbin , Zhang Zengqiang , Pan Junting
Published: July 2022

Conversion of organic waste into engineered metal-biochar composite is an effective way of enhancing biochar’s efficiency for adsorptive capture of phosphorus (P) from aqueous media. Thus, various strategies have been created for the production of metal-biochar composites; however, the complex preparation steps, high-cost metal salt reagent application, or extreme process equipment requirements involved in those strategies limited the large-scale production of metal-biochar composites. In this study, a novel biochar composite rich in magnesium oxides (MFBC) was directly produced through co-pyrolysis of magnesite with food waste; the product, MFBC was used to adsorptively capture P from solution and bio-liquid wastewater. The results showed that compared to the pristine food waste biochar, MFBC was a uniformly hybrid MgO biochar composite with a P capture capacity of 523.91 mg/g. The capture of P by MFBC was fitted using the Langmuir and pseudo-first-order kinetic models. The P adsorptive capture was controlled by MgHPO4 formation and electrostatic attraction, which was affected by the coexisting F− and CO32− ions. MFBC could recover more than 98% of P from the solution and bio-liquid wastewater. Although the P-adsorbed MFBC showed very limited reusability but it can be substituted for phosphate fertiliser in agricultural practices. This study provided an innovative technology for preparing MgO-biochar composite against P recovery from aqueous media, and also highlighted high-value-added approaches for resource utilization of bio-liquid wastewater and food waste.

Graphical Abstract