bluuebunny/crossref_metadata_2025 huggingface dataset:
Something in Our Ears Is Oscillating, but What? A Modeller’s View of Efforts to Model Spontaneous Emissions
Authors: Wit Hero P. , Bell Andrew
Published: May 2024

When David Kemp discovered “spontaneous ear noise” in 1978, it opened up a whole new perspective on how the cochlea works. The continuous tonal sound emerging from most healthy human ears, now called spontaneous otoacoustic emissions or SOAEs, was an unmistakable sign that our hearing organ must be considered an active detector, not just a passive microphone, just as Thomas Gold had speculated some 30 years earlier. Clearly, something is oscillating as a byproduct of that sensitive inbuilt detector, but what exactly is it? Here, we give a chronological account of efforts to model SOAEs as some form of oscillator, and at intervals, we illustrate key concepts with numerical simulations. We find that after many decades there is still no consensus, and the debate extends to whether the oscillator is local, confined to discrete local sources on the basilar membrane, or global, in which an assembly of micro-mechanical elements and basilar membrane sections, coupled by inner ear fluid, interact over a wide region. It is also undecided whether the cochlear oscillator is best described in terms of the well-known Van der Pol oscillator or the less familiar Duffing or Hopf oscillators. We find that irregularities play a key role in generating the emissions. This paper is not a systematic review of SOAEs and their properties but more a historical survey of the way in which various oscillator configurations have been applied to modelling human ears. The conclusion is that the difference between the local and global approaches is not clear-cut, and they are probably not mutually exclusive concepts. Nevertheless, when one sees how closely human SOAEs can be matched to certain arrangements of oscillators, Gold would no doubt say we are on the right track.
Habitat segregation by sympatric juvenile Arctic charr and brown trout in shallow lake areas: a consequence of interspecific differences in predator avoidance?
Authors: Svenning Martin-A. , Stien Audun , Borgstrøm Reidar
Published: May 2024

In sympatry, juvenile brown trout (Salmo trutta) usually occupy the shallow and most productive areas (littoral zone) of lakes, while juveniles of Arctic charr (Salvelinus alpinus) are found in deeper, less productive parts. In contrast, when Arctic charr juveniles occur in allopatry, they often occupy shallow littoral areas as well. Habitat segregation has traditionally been interpreted as a trade-off between predation risk and energy gain, while the segregation of these two species has been explained by brown trout being more aggressive and competitively superior to Arctic charr. We hypothesize, however, that the marked habitat segregation between the two species may also be due to differences in predator avoidance. Accordingly, we conducted several laboratory tests, using Arctic charr and brown trout as potential predators. Live fish of the same species were offered as prey, either as small charr only, small trout only, or both small charr and small trout together. Artificial shelters were then introduced to examine the avoidance ability of prey fish against predatory fish. Our results showed that under these circumstances, access to shelters strongly decreased mortality in juvenile brown trout, but had no effect on juvenile Arctic charr mortality. Thus, the habitat segregation shown by sympatric juvenile Arctic charr and brown trout in lakes may be a consequence of interspecific differences in predator avoidance.
A Novel Data Augmentation Method for Radiomics Analysis Using Image Perturbations
Authors: Lo Iacono F , Maragna R. , Pontone G. , Corino V. D. A.
Published: May 2024

Radiomics extracts hundreds of features from medical images to quantitively characterize a region of interest (ROI). When applying radiomics, imbalanced or small dataset issues are commonly addressed using under or over-sampling, the latter being applied directly to the extracted features. Aim of this study is to propose a novel balancing and data augmentation technique by applying perturbations (erosion, dilation, contour randomization) to the ROI in cardiac computed tomography images. From the perturbed ROIs, radiomic features are extracted, thus creating additional samples. This approach was tested addressing the clinical problem of distinguishing cardiac amyloidosis (CA) from aortic stenosis (AS) and hypertrophic cardiomyopathy (HCM). Twenty-one CA, thirty-two AS and twenty-one HCM patients were included in the study. From each original and perturbed ROI, 107 radiomic features were extracted. The CA-AS dataset was balanced using the perturbation-based method along with random over-sampling, adaptive synthetic (ADASYN) and the synthetic minority oversampling technique (SMOTE). The same methods were tested to perform data augmentation dealing with CA and HCM. Features were submitted to robustness, redundancy, and relevance analysis testing five feature selection methods (p-value, least absolute shrinkage and selection operator (LASSO), semi-supervised LASSO, principal component analysis (PCA), semi-supervised PCA). Support vector machine performed the classification tasks, and its performance were evaluated by means of a 10-fold cross-validation. The perturbation-based approach provided the best performances in terms of f1 score and balanced accuracy in both CA-AS (f1 score: 80%, AUC: 0.91) and CA-HCM (f1 score: 86%, AUC: 0.92) classifications. These results suggest that ROI perturbations represent a powerful approach to address both data balancing and augmentation issues.
Can the phase of SNR oscillations in GNSS-IR be used to estimate sea-level height?
Authors: Wei Zhenkui , Ren Chao , Liang Yueji , Liu Yintao , Liang Jieyu , Yin Anchao , Yue Weiting , Zhang Xudong , Lin Xiaoqi
Published: May 2024

In existing global navigation satellite system-interference reflectometry (GNSS-IR) research, only the frequency of signal-to-noise ratio (SNR) oscillations has been used to estimate sea-level height. However, the characteristic parameters of SNR oscillations are not isolated from each other, and a single feature cannot accurately and comprehensively capture the environmental changes of reflecting surface. Our simulation results show that for the nonlinear least squares (NLS), when there is a certain difference between the fitting frequency and the actual frequency of SNR oscillations, the deviation of the phase solution obtained is approximately linear with the frequency difference. Consequently, a linear phase correction GNSS-IR sea-level estimation method is constructed in this study. This method integrates the Lomb–Scargle periodogram (LSP) and NLS to process SNR oscillations, using the phase obtained from NLS to correct the retrieval error of LSP. Through processing SNR data from four sites for nearly half a year, we verified the stability of the relationship between phase and frequency-based retrieval error at different sites in continuous monitoring, and established the relationship model between the two. Then, utilizing the relationship model acquired at different sites, we estimated the sea-level variations for the next 6 months at each site through joint frequency and phase versus reflector height relationships. Experimental results show that the phases acquired from NLS can effectively correct the retrieval error of LSP. Compared with the traditional method using only frequency, the root mean square error and mean absolute error of the retrieval results obtained from the linear phase correction GNSS-IR sea-level estimation method based on LSP-NLS are both reduced by about 60%. This multi-feature fusion technique introduces a new perspective and technical approach for GNSS-IR sea-level estimations.
Fill-ins with scalar curvature lower bounds and applications to positive mass theorems
Authors: McCormick Stephen
Published: May 2024

Given a constantCand a smooth closed$$(n-1)$$(n-1)-dimensional Riemannian manifold$$(\Sigma , g)$$(Σ,g)equipped with a positive functionH, a natural question to ask is whether this manifold can be realised as the boundary of a smoothn-dimensional Riemannian manifold with scalar curvature bounded below byCand boundary mean curvatureH. That is, does there exist afill-inof$$(\Sigma ,g,H)$$(Σ,g,H)with scalar curvature bounded below byC? We use variations of an argument due to Miao and the author (Int Math Res Not 7:2019, 2019) to explicitly construct fill-ins with different scalar curvature lower bounds, where we permit the fill-in to contain another boundary component provided it is a minimal surface. Our main focus is to illustrate the applications of such fill-ins to geometric inequalities in the context of general relativity. By filling in a manifold beyond a boundary, one is able to obtain lower bounds on the mass in terms of the boundary geometry through positive mass theorems and Penrose inequalities. We consider fill-ins with both positive and negative scalar curvature lower bounds, which from the perspective of general relativity corresponds to the sign of the cosmological constant, as well as a fill-in suitable for the inclusion of electric charge.
A semi-parametric claims reserving model with monotone splines
Authors: Chang Le , Gao Guangyuan , Shi Yanlin
Published: May 2024

Stochastic reserving models used in the insurance industry are usually based on an assumed distribution of claim amounts. Despite their popularity, such models may unavoidably be affected by the misspecification issue given that it is likely that the underlying distribution will be different from that assumed. In this paper, we incorporate monotone splines to ensure the expected monotonically increasing pattern of cumulative development factors (CDFs) to develop a new semi-parametric reserving model that does not require a density assumption. To allow the maximum utilization of available information, we also propose an enhanced sampling approach that greatly increases the size of unbiased CDFs, particularly in later development periods. Based on the enhanced samples, a bootstrap technique is employed in the estimation of monotone splines, from which incurred-but-not-reported (IBNR) reserves and prediction errors can be obtained. Associated technical features, such as the consistency of estimator, are discussed and demonstrated. Our simulation studies suggest that the new model improves the accuracy of IBNR reserving, compared with a range of classic competing models. A real data analysis produces many consistent findings, thus supporting the usefulness of the monotone spline model in actuarial and insurance practice.
Effects of supplementary and mainstream education on the secondary–tertiary transitional challenges in English medium higher education
Authors: Yau Alice Hoi Ying , Fung D. , Tsang A.
Published: May 2024

Despite the rapid growth of English medium instruction (EMI) in higher education, little research has been conducted to pinpoint the challenges faced by students. This quantitative study explored the challenges posed by the secondary–tertiary transition to first-year students with different English proficiency levels in EMI higher education institutions. In addition, we also investigated students’ perception of the usefulness of supplementary and mainstream education in preparing them for those challenges. 91 participants studying at two tertiary institutions in Hong Kong completed a 52-item questionnaire. The questionnaire included items in relation to three major aspects of challenges: ‘academic studies and skills’, ‘socialization’, and ‘college/university life adaptation’. It was found that students with low proficiency regarded all three aspects as significantly more challenging than the high proficiency ones in their first-year studies. However, despite the different proficiency levels, students similarly perceived mainstream education to be significantly more useful than supplementary education in preparing them for those transitional challenges. The findings together suggest that more English support is needed for low-proficiency students at the tertiary level and argue that mainstream education plays an essential role in assisting students in this secondary–tertiary transition. Implications are discussed in terms of the benefits of having a general English course as perquisite for low English proficiency students before they enroll in English for Academic Purposes courses, and the development of a variety of tasks with more emphasis on communication and collaboration at the secondary level to support them in this transition.
Temporal validity reassessment: commonsense reasoning about information obsoleteness
Authors: Hosokawa Taishi , Jatowt Adam , Sugiyama Kazunari
Published: May 2024

It is useful for machines to know whether text information remains valid or not for various applications including text comprehension, story understanding, temporal information retrieval, and user state tracking on microblogs as well as via chatbot conversations. This kind of inference is still difficult for current models, including also large language models, as it requires temporal commonsense knowledge and reasoning. We approach in this paper the task of Temporal Validity Reassessment, inspired by traditional natural language reasoning to determine the updates of the temporal validity of text content. The task requires judgment whether actions expressed in a sentence are still ongoing or rather completed, hence, whether the sentence still remains valid or has become obsolete, given the presence of context in the form of a supplementary content such as a follow-up sentence. We first construct our own dataset for this task and train several machine learning models. Then we propose an effective method for learning information from an external knowledge base that gives information regarding temporal commonsense knowledge. Using our prepared dataset, we introduce a machine learning model that incorporates the information from the knowledge base and demonstrate that incorporating external knowledge generally improves the results. We also experiment with different embedding types to represent temporal commonsense knowledge as well as with data augmentation methods to increase the size of our dataset.
Non-linear Time Series Prediction using Improved CEEMDAN, SVD and LSTM
Authors: Poongadan Sameer , Lineesh M. C.
Published: May 2024

This study recommends a new time series forecasting model, namely ICEEMDAN - SVD - LSTM model, which coalesces Improved Complete Ensemble EMD with Adaptive Noise, Singular Value Decomposition and Long Short Term Memory network. It can be applied to analyse Non-linear and non-stationary data. The framework of this model is comprised of three levels, namely ICEEMDAN level, SVD level and LSTM level. The first level utilized ICEEMDAN to break up the series into some IMF components along with a residue. The SVD in the second level accounts for de-noising of every IMF component and residue. LSTM forecasts all the resultant IMF components and residue in third level. To obtain the forecasted values of the original data, the predictions of all IMF components and residue are added. The proposed model is contrasted with other extant ones, namely LSTM model, EMD - LSTM model, EEMD - LSTM model, CEEMDAN - LSTM model, EEMD - SVD - LSTM model, ICEEMDAN - LSTM model and CEEMDAN - SVD - LSTM model. The comparison bears witness to the potential of the recommended model over the traditional models.
Dimensions of teachers’ data literacy: A systematic review of literature from 1990 to 2021
Authors: Lee Jihyun , Alonzo Dennis , Beswick Kim , Abril Jan Michael Vincent , Chew Adrian W. , Oo Cherry Zin
Published: May 2024

The current study presents a systematic review of teachers’ data literacy, arising from a synthesis of 83 empirical studies published between 1990 to 2021. Our review identified 95 distinct indicators across five dimensions: (a) knowledge about data, (b) skills in using data, (c) dispositions towards data use, (d) data application for various purposes, and (e) data-related behaviors. Our findings indicate that teachers' data literacy goes beyond addressing the needs of supporting student learning and includes elements such as teacher reflection, collaboration, communication, and participation in professional development. Considering these findings, future policies should acknowledge the significance of teacher dispositions and behaviors in relation to data, recognizing that they are as important as knowledge and skills acquisition. Additionally, prioritizing the provision of system-level support to foster teacher collaboration within in-school professional development programs may prove useful in enhancing teachers’ data literacy.
Framing the predictive mind: why we should think again about Dreyfus
Authors: Reynolds Jack
Published: May 2024

In this paper I return to Hubert Dreyfus’ old but influential critique of artificial intelligence, redirecting it towards contemporary predictive processing models of the mind (PP). I focus on Dreyfus’ arguments about the “frame problem” for artificial cognitive systems, and his contrasting account of embodied human skills and expertise. The frame problem presents as a prima facie problem for practical work in AI and robotics, but also for computational views of the mind in general, including for PP. Indeed, some of the issues it presents seem more acute for PP, insofar as it seeks to unify all cognition and intelligence, and aims to do so without admitting any cognitive processes or mechanisms outside of the scope of the theory. I contend, however, that there is an unresolved problem for PP concerning whether it can both explain all cognition and intelligent behavior as minimizing prediction error with just the core formal elements of the PP toolbox, and also adequately comprehend (or explain away) some of the apparent cognitive differences between biological and prediction-based artificial intelligence, notably in regard to establishing relevance and flexible context-switching, precisely the features of interest to Dreyfus’ work on embodied indexicality, habits/skills, and abductive inference. I address several influential philosophical versions of PP, including the work of Jakob Hohwy and Andy Clark, as well as more enactive-oriented interpretations of active inference coming from a broadly Fristonian perspective.
Unfulfilled habits: on the affective consequences of turning down affordances for social interaction
Authors: Vara Sánchez Carlos
Published: May 2024

Many pragmatist and non-representational approaches to cognition, such as the enactivist, have focused on the relations between actions, affectivity, and habits from an intersubjective perspective. For those adopting such approaches, all these aspects are inextricably connected; however, many questions remain open regarding the dynamics by which they unfold and shape each other over time. This paper addresses a specific topic that has not received much attention: the impact on future behavior of not fulfilling possibilities for social interaction even though their fulfillment is desirable within a given context. Inspired by Gibson’s theory of affordances and Dewey’s account of habits, these situations will be characterized as events where an agent does not act upon an inviting affordance for social interaction due to a conflict which he or she experiences between given concerns, needs, and social norms. This conflict leads to a sense of unfulfillment that may eventually bring about a crisis and revision of habits. Through specific examples, this work presents the potential impact of the connection between affordances, habits, and affectivity on everyday situations. It therefore represents an exploration of the common ground between pragmatism and enactivism and an attempt to contribute to a process-based approach to social interaction.
Advanced high-resolution chromatographic strategies for efficient isolation of natural products from complex biological matrices: from metabolite profiling to pure chemical entities
Authors: Queiroz Emerson Ferreira , Guillarme Davy , Wolfender Jean-Luc
Published: May 2024

The isolation of pure compounds from extracts represents a key step common to all investigations of natural product (NP) research. Isolation methods have gone through a remarkable evolution. Current approaches combine powerful metabolite profiling methods for compounds annotation with omics mining results and/or bioassay for bioactive NPs/biomarkers priorisation. Targeted isolation of prioritized NPs is performed using high-resolution chromatographic methods that closely match those used for analytical profiling. Considerable progress has been made by the introduction of innovative stationary phases providing remarkable selectivity for efficient NPs isolation. Today, efficient separation conditions determined at the analytical scale using high- or ultra-high-performance liquid chromatography can be optimized via HPLC modelling software and efficiently transferred to the semi-preparative scale by chromatographic calculation. This ensures similar selectivity at both the analytical and preparative scales and provides a precise separation prediction. High-resolution conditions at the preparative scale can notably be granted using optimized sample preparation and dry load sample introduction. Monitoring by ultraviolet, mass spectrometry, and or universal systems such as evaporative light scattering detectors and nuclear magnetic resonance allows to precisely guide the isolation or trigger the collection of specific NPs with different structural scaffolds. Such approaches can be applied at different scales depending on the amounts of NPs to be isolated. This review will showcase recent research to highlight both the potential and constraints of using these cutting-edge technologies for the isolation of plant and microorganism metabolites. Several strategies involving their application will be examined and critically discussed.

Graphical abstract
Reduced belowground allocation of freshly assimilated C contributes to negative plant-soil feedback in successive winter wheat rotations
Authors: Kaloterakis Nikolaos , Kummer Sirgit , Le Gall Samuel , Rothfuss Youri , Reichel Rüdiger , Brüggemann Nicolas
Published: May 2024

Aims

Successive winter wheat (WW) rotations are associated with yield reduction, often attributed to the unfavorable soil microbes that persist in the soil through plant residues. How rotational positions of WW affect the allocation of freshly assimilated carbon (C), an energy source for soil microbes, above and belowground remains largely unknown.

Methods

A 13CO2 pulse labeling rhizotron experiment was conducted in the greenhouse to study freshly fixed C allocation patterns. WW was grown in soil after oilseed rape (W1), after one season of WW (W2), and after three successive seasons of WW (W4). We used an automatic manifold system to measure excess 13C of soil respiration at six depths and five different dates. Excess 13C was also measured in dissolved organic C (DOC), microbial and plant biomass pools.

Results

There was a strong yield decline in successive WW rotations accompanied by distinct changes in root growth. Higher excess 13C of soil respiration was measured in W1 compared to W4, especially in the topsoil during at later growth stages. Higher excess 13C of the DOC and the microbial biomass was also traced in W1 and W4 compared to W2. Less 13C was taken up by successive WW rotations.

Conclusions

Our study demonstrates a mechanism through which the rotational position of WW affects the allocation of freshly assimilated C above and belowground. WW after oilseed rape sustains belowground allocation of freshly assimilated C for a longer time than successively grown WW and incorporates more of this C to its biomass.
On Fundamental Solutions and Gaussian Bounds for Degenerate Parabolic Equations with Time-dependent Coefficients
Authors: Ataei Alireza , Nyström Kaj
Published: May 2024

We consider second order degenerate parabolic equations with real, measurable, and time-dependent coefficients. We allow for degenerate ellipticity dictated by a spatial $$A_2$$

A
2

-weight. We prove the existence of a fundamental solution and derive Gaussian bounds. Our construction is based on the original work of Kato (Nagoya Math. J. 19, 93–125 1961).
Characterization and Quantification of the Major Bioactive Compounds in Mexican Purple Tomatoes
Authors: Torres Andrea , Pérez-Flores Laura J. , Lobato-Ortíz Ricardo , Navarro-Ocana Arturo
Published: May 2024

The present work carries out a quantitative analysis of the major bioactive compounds found in the native Mexican purple tomatoes. Total phenolic content ranged from 7.54 to 57.79 mg TPC/g DM, total flavonoid content ranged from 1.89 to 16.93 mg TFC/g DM, total anthocyanin content ranged from 0.29 to 2.56 mg TAC/g DM, and total carotenoid content ranged from 0.11 to 0.75 mg TCC/ g DM. In addition, 14 phenolic acids were identified, among which caffeoylquinic acid derivatives were the most abundant compounds with chlorogenic acid concentration up to 9.680 mg/g DM, together with flavonoids, such as rutin and quercetin-hexoxide. The qualitative analysis also showed the presence of 9 acylated anthocyanins and 2 carotenoids with significant functional features. As for anthocyanins, their chemical structures disclosed special structural features: glycosylated anthocyanins exhibited cis-trans hydroxycinnamic moieties and petunidin-3-(trans-p-coumaroyl)-rutinoside-5-glucoside was reported to be the main anthocyanin, whitin the range of concentrations between 0.160 and 1.143 mg/g DM.

Graphical Abstract
Crithmum maritimum Extract Restores Lipid Homeostasis and Metabolic Profile of Liver Cancer Cells to a Normal Phenotype
Authors: Gnocchi Davide , Nikolic Dragana , Paparella Rosa Rita , Sabbà Carlo , Mazzocca Antonio
Published: May 2024

Hepatocellular carcinoma (HCC) is an alarming epidemiological clinical problem worldwide. Pharmacological approaches currently available do not provide adequate responses due to poor effectiveness, high toxicity, and serious side effects. Our previous studies have shown that the wild edible plant Crithmum maritimum L. inhibits the growth of liver cancer cells and promotes liver cell differentiation by reducing lactic acid fermentation (Warburg effect). Here, we aimed to further characterise the effects of C. maritimum on lipid metabolism and markers of cellular metabolic health, such as AMP-activated protein kinase (AMPK), Sirtuin 1 (SIRT1), and Sirtuin 3 (SIRT3), as well as the insulin signalling pathway. To better mimic the biological spectrum of HCC, we employed four HCC cell lines with different degrees of tumorigenicity and lactic acid fermentation/Warburg phenotype. Lipid accumulation was assessed by Oil Red O (ORO) staining, while gene expression was measured by real-time quantitative PCR (RT-qPCR). The activation of AMPK and insulin signalling pathways was determined by Western blotting. Results indicate that C. maritimum prevents lipid accumulation, downregulates lipid and cholesterol biosynthesis, and modulates markers of metabolic health, such as AMPK, SIRT1 and SIRT3. This modulation is different amongst HCC cell lines, revealing an important functional versatility of C. maritimum. Taken together, our findings corroborate the importance of C. maritimum as a valuable nutraceutical, reinforcing its role for the improvement of metabolic health.
The Effect of the Countercyclical Capital Buffer on the Stability of the Housing Market
Authors: Braun Julia , Burghof Hans-Peter , Sommervoll Dag Einar
Published: May 2024

After the great turmoil of the latest financial crisis, the criticism of the regulatory frameworks became increasingly stronger. The rules that banks needed to comply with are presumed to be procyclical and unable to prevent and mitigate the extent of strong financial and economic cycles. As a result, Basel III introduced a set of macroprudential tools to overcome these regulatory shortfalls. One tool that strives to counteract the issue of procyclicality is the countercyclical capital buffer ($$CCyB$$

CCyB

). This paper introduces a heterogeneous agent-based model that investigates the implication of the new regulatory measure. We develop a housing and a financial market where economic agents trade residential property that is financed by financial institutions. To examine the macroeconomic performance of the $$CCyB$$

CCyB

, we evaluate the dynamics of key stability indicators of the housing and the financial market under four different market conditions: in an undisturbed market and in times of three different structural shocks. Computational experiments reveal that the $$CCyB$$

CCyB

is effective in stabilizing the housing and the financial market in all market settings. The new macroprudential tool helps to mitigate economic fluctuations and to stabilize market conditions, especially in the aftermath of a crisis. It is not able to prevent any of the crises tested. However, the extent of the stabilizing effect varies according to market conditions. In the shock scenarios, the $$CCyB$$

CCyB

performs better in dampening market fluctuations and increasing banking soundness than in the base scenario.
The Effect of Lubricity of Calcium Sulfonate on ZnDTP and MoDTC
Authors: Hayashi Yumi , Sato Kaisei , Sasaki Shinya
Published: May 2024

Reduction of friction and wear by lubrication is necessary to improve the efficiency and prolong the lifespan of industrial machinery. However, several aspects regarding the lubrication effects in additive-combined oil are still unresolved. This study focuses on the effects of combining zinc dialkyldithiophosphate (ZnDTP), molybdenum dithiocarbamate (MoDTC), and Ca sulfonate on the frictional behavior of poly-α-olefin 4 (PAO4) lubricant oils. Ball-on-disk friction tests demonstrated that the exclusive addition of high-base Ca sulfonate solution reduced friction and wear of the lubricating oil. When combined with ZnDTP and MoDTC, the friction coefficients of PAO with high-base and low-base Ca sulfonate are affected by competitive reactions on the sliding surface. Quartz crystal microbalance with dissipation monitoring measurements suggests that high-base Ca sulfonate forms a stronger adsorption film than low-base Ca sulfonate. Atomic force microscope observations confirmed that the addition of low-base Ca sulfonate reduced friction and wear, whereas high-base Ca sulfonate induced competitive reactions with ZnDTP and MoDTC. This study provides valuable insights into the effects of the combination of additives on the lubricity of PAO and their impact on friction and wear characteristics, which are valuable for the design of suitable lubricants for industrial machinery.
Earnouts in mergers and acquisitions: a systematic literature review of a contingent payment mechanism
Authors: Dahlen Niklas
Published: May 2024

Defining the deal value in mergers and acquisitions is inherently complex and often constitutes an inflection point for the parties involved. By paying part of the deal value at a later stage according to predefined goals, earnouts are intended to alleviate information asymmetries and help bridge valuation differences. Despite their wide application in practice, research on earnouts remains fragmented. This study presents the first systematic literature review of earnouts, mapping the scattered research landscape by analyzing 64 papers published between 1970 and 2023. The review categorizes the body of earnout research into three distinct streams: the motives for employing earnouts, their implications, and the nuances of their contractual arrangements. Based on this synthesis, research gaps are identified that present a comprehensive road map for future research. This study enables investors to employ earnouts more successfully and guides scholars to pursue further earnout research based on its holistic overview.
Potential effects of the discharge of wastewater treatment plant (WWTP) effluents in benthic communities: evidence from three distinct WWTP systems
Authors: Silva Carlos , Santos Joana Isabel , Vidal Tânia , Silva Susana , Almeida Salomé Fernandes Pinheiro , Gonçalves Fernando José Mendes , Abrantes Nelson , Pereira Joana Luísa
Published: May 2024

Wastewater treatment plant (WWTP) effluents can be sources of environmental contamination. In this study, we aimed to understand whether effluents of three different WWTPs may have ecological effects in riverine recipient ecosystems. To achieve this, we assessed benthic phytobenthos and macroinvertebrate communities at three different locations relative to the effluent discharge: immediately upstream, immediately downstream and 500-m downstream the effluent discharge. Two approaches were employed: the ecological status classification as defined in the Water Framework Directive (WFD) based on biological indicators; constrained multivariate analysis to disentangle the environmental drivers (physicochemical variables and contaminants, namely metals, polycyclic aromatic hydrocarbons, pharmaceuticals, and personal care products) of ecological changes across the study sites. The results showed inconsistencies between the WFD approach and the multivariate approach, as well as between the responses of macroinvertebrates and diatoms. The WWTP effluents impacted benthic communities in a single case: macroinvertebrates were negatively affected by one of the WWTP effluents, likely by the transported pharmaceuticals (other stressors are essentially homogeneous among sites). Given the findings and the scarcity of consistent evidence on ecological impacts that WWTP effluents may have in recipient ecosystems, further research is needed towards more sustainable regulation and linked environmental protection measures.
Investigation of 200 anthropogenic activities in a representative alpine peatland in the Altay Mountains, northwestern China
Authors: Luo Nana , Yu Rui , Wen Bolong , Li Xiaoyu , Zhang Qilin , Li Xiujun
Published: May 2024

Peatlands records can be used to reconstruct and understand the history of environmental evolution, as well as a more accurate reflection of human activities. The black carbon (BC) and polycyclic aromatic hydrocarbons (PAHs) are ideal natural archives of anthropogenic activities. To identify the information of anthropogenic activities recorded by peatlands in the middle and high latitudes of the alpine mountains in the arid and semi-arid regions of China. this study analyzed the concentrations of BC, δ13C ratios of BC, PAHs, and molecular diagnostic ratios of PHAs (including Benzo(a) anthracene (BaA), Chrysene (Chr), fluoranthene (Flt), anthracene (Ant), phenanthrene (Phe), Benzo(a) pyrene (BaP), and pyrene (Pyr) in a 30-cm peat profile from the Altay Mountain, northwestern China. Our results revealed concentrations of BC from 11.71 to 67.5 mg·g−1, and PAHs from 168.09 to 263.53 ng·g−1. The δ13CBC value ranged from − 31.37 to − 26.27‰, with an average of − 29.54‰, indicating that the BC mainly comes from biomass combustion. The ratios of BaA/(BaA + Chr), Flt/(Flt + Pyr), and Ant/(Ant + Phe) exceeded 0.35, 0.5, and 0.1, respectively, revealing that the PAHs pollutants mainly originated from the combustion of biomass and fossil fuel burning. Furthermore, based on these findings and our knowledge of social development in Altay, industrial transport and tourism have influenced the emission, transport, and deposition of BC and PAH in peatlands in the Altay mountains since the 1980s. After 1980, pollutant concentrations decreased with the implementation of environmental policies. The results not only reveal the influence of anthropogenic activities on the sedimentary characteristics of peatlands in the Altay Mountains, but also provide an important theoretical basis for the conservation of fragile mountain peatlands.
Data augmentation for generating synthetic electrogastrogram time series
Authors: Miljković Nadica , Milenić Nikola , Popović Nenad B. , Sodnik Jaka
Published: May 2024

To address an emerging need for large number of diverse datasets for rigor evaluation of signal processing techniques, we developed and evaluated a new method for generating synthetic electrogastrogram time series. We used electrogastrography (EGG) data from an open database to set model parameters and statistical tests to evaluate synthesized data. Additionally, we illustrated method customization for generating artificial EGG time series alterations caused by the simulator sickness. Proposed data augmentation method generates synthetic EGG data with specified duration, sampling frequency, recording state (postprandial or fasting state), overall noise and breathing artifact injection, and pauses in the gastric rhythm (arrhythmia occurrence) with statistically significant difference between postprandial and fasting states in > 70% cases while not accounting for individual differences. Features obtained from the synthetic EGG signal resembling simulator sickness occurrence displayed expected trends. The code for generation of synthetic EGG time series is not only freely available and can be further customized to assess signal processing algorithms but also may be used to increase data diversity for training artificial intelligence (AI) algorithms. The proposed approach is customized for EGG data synthesis but can be easily utilized for other biosignals with similar nature such as electroencephalogram.

Graphical abstract
CT findings as predictive factors for treatment failure in Mycobacterium abscessus complex lung disease: a retrospective cohort study
Authors: Chiang Pin-Yi , Huang Yu-Sen , Huang Yu-Cheng , Lee Ming-Yann , Kang Victor Jing-Wei , Shu Chin-Chung , Chang Yeun-Chung
Published: May 2024

Purpose

Mycobacterium abscessus complex (MABC) commonly causes lung disease (LD) and has a high treatment failure rate of around 50%. In this study, our objective is to investigate specific CT patterns for predicting treatment prognosis and monitoring treatment response, thus providing valuable insights for clinical physicians in the management of MABC-LD treatment.

Methods

We retrospectively assessed 34 patients with MABC-LD treated between January 2015 and December 2020. CT scores for bronchiectasis, cellular bronchiolitis, consolidation, cavities, and nodules were measured at initiation and after treatment. The ability of the CT scores to predict treatment outcomes was analyzed in logistic regression analyses.

Results

The CT scoring system had excellent inter-reader agreement (all intraclass correlation coefficients, > 0.82). The treatment failure (TF) group (17/34; 50%) had higher cavitation diameter (p = 0.049) and extension (p = 0.041) at initial CT and higher cavitation diameter (p = 0.049) and extension (p =0 .045), consolidation (p = 0.022), and total (p = 0.013) scores at follow-up CT than the treatment success (TS) group. The changes of total score and consolidation score (p = 0.049 and 0.024, respectively) increased in the TF group more than the TS group between the initial and follow-up CT. Multivariable logistic regression analysis showed initial cavitation extension, follow-up consolidation extension, and change in consolidation extension (adjusted odds ratio: 2.512, 2.495, and 9.094, respectively, per 1-point increase; all p < 0.05) were significant predictors of treatment failure.

Conclusions

A high pre-treatment cavitation extension score and an increase in the consolidation extension score during treatment on CT could be alarm signs of treatment failure requiring tailor the treatment of MABC-LD carefully.
Emotion regulation of sustainability professionals facing adversity
Authors: Johannessen Vilde , Giæver Fay , Efstathiou Sophia , Russell Sally
Published: May 2024

In this Group. Interaction. Organizations. (GIO) article, we view Norwegian regenerative farmers as sustainability professionals and explore their emotions and emotion regulation strategies as they face adversity at work. Working with sustainability is intense work as it implies addressing economic, sustainability, and social needs. Regenerative farmers experience heightened stress and strains due to limited resources in farming. We did a qualitative study based on participant observation and interviews and found that regenerative farmers reported emotions such as guilt, pride, frustration, joy, sadness, and loneliness in their work. They regulated their emotions by a) redefining and accepting problems as challenges; b) creating meaning from their work; c) seeking community through exchange of knowledge and care; and d) protecting their philosophy and practice. This study identifies how sustainability professionals might regulate their emotions over transitions to more sustainable practices. We found that it is essential to facilitate social connections between sustainability professionals for their wellbeing, and mental health.
(Selbst‑)Coachingprogramm für Long Covid-Betroffene
Authors: Nüßlein Stefanie
Published: May 2024

Das von der Autorin entwickelte (Selbst‑)Coachingprogramm richtet sich speziell an Personen, die unter den anhaltenden Symptomen von Long Covid leiden. Basierend auf aktuellen Leitlinienempfehlungen und wissenschaftlichen Erkenntnissen zur Krankheitsbewältigung, begleitet das 8‑Schritte-Programm Betroffene durch verschiedene Phasen ihrer Erkrankung. Das übergeordnete Ziel ist die Förderung des Selbstmanagements im Umgang mit der Erkrankung sowie die Verbesserung der Lebensqualität der Betroffenen. Angesichts der Herausforderungen in der Versorgung von Long Covid-Patient:innen stellt das Programm sowohl für Betroffene als auch für professionelle Coaches im Rahmen von Gesundheitscoachings einen niederschwelligen Zugang zu evidenzbasierten Interventionen dar. Positive Erfahrungsberichte unterstreichen den Nutzen des vorliegenden (Selbst-﻿)Coachingprogramms.
Degrowth scenarios for biodiversity? Key methodological steps and a call for collaboration
Authors: Otero Iago , Rigal Stanislas , Pereira Laura , Kim HyeJin , Gamboa Gonzalo , Tello Enric , Grêt-Regamey Adrienne
Published: May 2024

Studies show that economic growth contributes to biodiversity loss and that, after a certain threshold, it does not contribute to wellbeing. Thus, when developing biodiversity scenarios, considering societal futures where economic growth is not a pre-condition deserves special attention. However, to date, degrowth scenarios have not been explored for biodiversity conservation and human wellbeing. In this paper, we explain how the Nature Futures Framework (NFF) and other approaches could be used to generate degrowth scenarios for biodiversity, nature’s contributions to people (NCP) and good quality of life (GQL) based on multiple societal values. We present key methodological steps of such an endeavour, including: (i) producing degrowth visions for high-income countries; (ii) identifying leverage points and imagining degrowth pathways; (iii) identifying key social–ecological interactions; and (iv) modelling biodiversity, NCP, and GQL along degrowth scenarios. Our proposal is framed within current theoretical, empirical, and modelling work as well as within efforts to improve scenario development across the biodiversity and climate communities. To develop degrowth scenarios for biodiversity, NCP, and GQL, we call for collaboration across natural and social sciences, quantitative and qualitative approaches, and northern and southern perspectives. This collaboration could lead to a community of practice that tests and improves the degrowth scenarios in national and international science–policy interfaces as they set out to achieve the Convention on Biological Diversity’s 2050 vision of living in harmony with nature.
Memory retrieval effects as a function of differences in phenomenal experience
Authors: Schmidt Austin H. , Kirwan C. Brock
Published: May 2024

Conscious experience and perception are restricted to a single perspective. Although evidence to suggest differences in phenomenal experience can produce observable differences in behavior, it is not well understood how these differences might influence memory. We used fMRI to scan n = 49 participants while they encoded and performed a recognition memory test for faces and words. We calculated a cognitive bias score reflecting individual participants’ propensity toward either Visual Imagery or Internal Verbalization based on their responses to the Internal Representations Questionnaire (IRQ). Neither visual imagery nor internal verbalization scores were significantly correlated with memory performance. In the fMRI data, there were typical patterns of activation differences between words and faces during both encoding and retrieval. There was no effect of internal representation bias on fMRI activation during encoding. At retrieval, however, a bias toward visualization was positively correlated with memory-related activation for both words and faces in inferior occipital gyri. Further, there was a crossover interaction in a network of brain regions such that visualization bias was associated with greater activation for words and verbalization bias was associated with greater activation for faces, consistent with increased effort for non-preferred stimulus retrieval. These findings suggest that individual differences in cognitive representations affect neural activation across different types of stimuli, potentially affecting memory retrieval performance.
Radical innovation breakthroughs of biodegradation of plastics by insects: history, present and future perspectives
Authors: Yang Shan-Shan , Wu Wei-Min , Bertocchini Federica , Benbow Mark Eric , Devipriya Suja P. , Cha Hyung Joon , Peng Bo-Yu , Ding Meng-Qi , He Lei , Li Mei-Xi , Cui Chen-Hao , Shi Shao-Nan , Sun Han-Jun , Pang Ji-Wei , He Defu , Zhang Yalei , Yang Jun , Hou Deyi , Xing De-Feng , Ren Nan-Qi , Ding Jie , Criddle Craig S.
Published: May 2024

Insects damaging and penetrating plastic packaged materials has been reported since the 1950s. Radical innovation breakthroughs of plastic biodegradation have been initiated since the discovery of biodegradation of plastics by Tenebrio molitor larvae in 2015 followed by Galleria mellonella in 2017. Here we review updated studies on the insect-mediated biodegradation of plastics. Plastic biodegradation by insect larvae, mainly by some species of darkling beetles (Tenebrionidae) and pyralid moths (Pyralidae) is currently a highly active and potentially transformative area of research. Over the past eight years, publications have increased explosively, including discoveries of the ability of different insect species to biodegrade plastics, biodegradation performance, and the contribution of host and microbiomes, impacts of polymer types and their physic-chemical properties, and responsible enzymes secreted by the host and gut microbes. To date, almost all major plastics including polyethylene (PE), polypropylene (PP), polyvinyl chloride (PVC), polyethylene terephthalate (PET), polyurethane (PUR), and polystyrene (PS) can be biodegraded by T. molitor and ten other insect species representing the Tenebrionidae and Pyralidae families. The biodegradation processes are symbiotic reactions or performed by synergistic efforts of both host and gut-microbes to rapidly depolymerize and biodegrade plastics with hourly half-lives. The digestive ezymens and bioreagents screted by the insects play an essential role in plasatic biodegradation in certain species of Tenebrionidae and Pyralidae families. New research on the insect itself, gut microbiomes, transcriptomes, proteomes and metabolomes has evaluated the mechanisms of plastic biodegradation in insects. We conclude this review by discussing future research perspectives on insect-mediated biodegradation of plastics.