bluuebunny/crossref_metadata_2025 huggingface dataset:
The Proper Landau–Ginzburg Potential, Intrinsic Mirror Symmetry and the Relative Mirror Map
Authors: You Fenglong
Published: March 2024

Given a smooth log Calabi–Yau pair (X, D), we use the intrinsic mirror symmetry construction to define the mirror proper Landau–Ginzburg potential and show that it is a generating function of two-point relative Gromov–Witten invariants of (X, D). We compute certain relative invariants with several negative contact orders, and then apply the relative mirror theorem of Fan et al. (Sel Math (NS) 25(4): Art. 54, 25, 2019. https://doi.org/10.1007/s00029-019-0501-z) to compute two-point relative invariants. When D is nef, we compute the proper Landau–Ginzburg potential and show that it is the inverse of the relative mirror map. Specializing to the case of a toric variety X, this implies the conjecture of m Gräfnitz et al. (2022) that the proper Landau–Ginzburg potential is the open mirror map. When X is a Fano variety, the proper potential is related to the anti-derivative of the regularized quantum period.
Random Quantum Circuits Transform Local Noise into Global White Noise
Authors: Dalzell Alexander M. , Hunter-Jones Nicholas , Brandão Fernando G. S. L.
Published: March 2024

We study the distribution over measurement outcomes of noisy random quantum circuits in the regime of low fidelity, which corresponds to the setting where the computation experiences at least one gate-level error with probability close to one. We model noise by adding a pair of weak, unital, single-qubit noise channels after each two-qubit gate, and we show that for typical random circuit instances, correlations between the noisy output distribution $$p_{\text {noisy}}$$

p
noisy

and the corresponding noiseless output distribution $$p_{\text {ideal}}$$

p
ideal

shrink exponentially with the expected number of gate-level errors. Specifically, the linear cross-entropy benchmark F that measures this correlation behaves as $$F=\text {exp}(-2s\epsilon \pm O(s\epsilon ^2))$$

F
=
exp
(
-
2
s
ϵ
±
O

(
s

ϵ
2

)

)

, where $$\epsilon $$
ϵ
is the probability of error per circuit location and s is the number of two-qubit gates. Furthermore, if the noise is incoherent—for example, depolarizing or dephasing noise—the total variation distance between the noisy output distribution $$p_{\text {noisy}}$$

p
noisy

and the uniform distribution $$p_{\text {unif}}$$

p
unif

decays at precisely the same rate. Consequently, the noisy output distribution can be approximated as $$p_{\text {noisy}}\approx Fp_{\text {ideal}}+ (1-F)p_{\text {unif}}$$

p
noisy

≈
F

p
ideal

+

(
1
-
F
)

p
unif

. In other words, although at least one local error occurs with probability $$1-F$$

1
-
F

, the errors are scrambled by the random quantum circuit and can be treated as global white noise, contributing completely uniform output. Importantly, we upper bound the average total variation error in this approximation by $$O(F\epsilon \sqrt{s})$$

O
(
F
ϵ

s

)

. Thus, the “white-noise approximation” is meaningful when $$\epsilon \sqrt{s} \ll 1$$

ϵ

s

≪
1

, a quadratically weaker condition than the $$\epsilon s\ll 1$$

ϵ
s
≪
1

requirement to maintain high fidelity. The bound applies if the circuit size satisfies $$s \ge \Omega (n\log (n))$$

s
≥
Ω
(
n
log
(
n
)
)

, which corresponds to only logarithmic depth circuits, and if, additionally, the inverse error rate satisfies $$\epsilon ^{-1} \ge {\tilde{\Omega }}(n)$$

ϵ

-
1

≥

Ω
~

(
n
)

, which is needed to ensure errors are scrambled faster than F decays. The white-noise approximation is useful for salvaging the signal from a noisy quantum computation; for example, it was an underlying assumption in complexity-theoretic arguments that noisy random quantum circuits cannot be efficiently sampled classically, even when the fidelity is low. Our method is based on a map from second-moment quantities in random quantum circuits to expectation values of certain stochastic processes for which we compute upper and lower bounds.
Frustration can Limit the Adaptation of Promiscuous Enzymes Through Gene Duplication and Specialisation
Authors: Schmutzer Michael , Dasmeh Pouria , Wagner Andreas
Published: March 2024

Virtually all enzymes catalyse more than one reaction, a phenomenon known as enzyme promiscuity. It is unclear whether promiscuous enzymes are more often generalists that catalyse multiple reactions at similar rates or specialists that catalyse one reaction much more efficiently than other reactions. In addition, the factors that shape whether an enzyme evolves to be a generalist or a specialist are poorly understood. To address these questions, we follow a three-pronged approach. First, we examine the distribution of promiscuity in empirical enzymes reported in the BRENDA database. We find that the promiscuity distribution of empirical enzymes is bimodal. In other words, a large fraction of promiscuous enzymes are either generalists or specialists, with few intermediates. Second, we demonstrate that enzyme biophysics is not sufficient to explain this bimodal distribution. Third, we devise a constraint-based model of promiscuous enzymes undergoing duplication and facing selection pressures favouring subfunctionalization. The model posits the existence of constraints between the catalytic efficiencies of an enzyme for different reactions and is inspired by empirical case studies. The promiscuity distribution predicted by our constraint-based model is consistent with the empirical bimodal distribution. Our results suggest that subfunctionalization is possible and beneficial only in certain enzymes. Furthermore, the model predicts that conflicting constraints and selection pressures can cause promiscuous enzymes to enter a ‘frustrated’ state, in which competing interactions limit the specialisation of enzymes. We find that frustration can be both a driver and an inhibitor of enzyme evolution by duplication and subfunctionalization. In addition, our model predicts that frustration becomes more likely as enzymes catalyse more reactions, implying that natural selection may prefer catalytically simple enzymes. In sum, our results suggest that frustration may play an important role in enzyme evolution.
A new incubation system to simultaneously measure N2 as well as N2O and CO2 fluxes from plant-soil mesocosms
Authors: Yankelzon Irina , Willibald Georg , Dannenmann Michael , Malique Francois , Ostler Ulrike , Scheer Clemens , Butterbach-Bahl Klaus
Published: March 2024

This study presents a novel plant-soil mesocosm system designed for cultivating plants over periods ranging from days to weeks while continuously measuring fluxes of N2, N2O and CO2. For proof of concept, we conducted a 33-day incubation experiment using six soil mesocosms, with three containing germinated wheat plants and three left plant-free. To validate the magnitude of N2 and N2O fluxes, we used 15N-enriched fertilizer and a 15N mass balance approach. The system inherent leakage rate was about 55 µg N m− 2 h− 1 for N2, while N2O leakage rates were below the detection limit (< 1 µg N m− 2 h− 1). In our experiment, we found higher cumulative gaseous N2 + N2O losses in sown soil (0.34 ± 0.02 g N m− 2) as compared to bare soil (0.23 ± 0.01 g N m− 2). N2 fluxes accounted for approximately 94–96% of total gaseous N losses in both planted and unplanted mesocosms. N losses, as determined by the 15N mass balance approach, were found to be 1.7 ± 0.5 g N m− 2 for the sown soil and 1.7 ± 0.6 g N m− 2 for the bare soil, indicating an inconsistency between the two assessment methods. Soil respiration rates were also higher in sown mesocosms, with cumulative soil and aboveground biomass CO2 respiration reaching 4.8 ± 0.1 and 4.0 ± 0.1 g C m− 2 over the 33-day incubation period, in sown and bare soil, respectively. Overall, this study measured the effect of wheat growth on soil denitrification, highlighting the sensitivity and utility of this advanced incubation system for such studies.
Stroke frequency, associated factors, and clinical features in primary systemic vasculitis: a multicentric observational study
Authors: Geraldes Ruth , Santos Monica , Ponte Cristina , Craven Anthea , Barra Lillian , Robson Joanna C. , Hammam Nevin , Springer Jason , Henes Jöerg , Hocevar Alojzija , Putaala Jukka , Santos Ernestina , Rajasekhar Liza , Daikeler Thomas , Karadag Omer , Costa Andreia , Khalidi Nader , Pagnoux Christian , Canhão Patrícia , Melo Teresa Pinho e , Fonseca Ana Catarina , Ferro José M. , Fonseca João Eurico , Suppiah Ravi , Watts Richard A. , Grayson Peter , Merkel Peter A. , Luqmani Raashid A. ,   the DCVAS Study Group
Published: March 2024

Objectives

The cerebral vessels may be affected in primary systemic vasculitis (PSV), but little is known about cerebrovascular events (CVEs) in this population. This study aimed to determine the frequency of CVEs at the time of diagnosis of PSV, to identify factors associated with CVEs in PSV, and to explore features and outcomes of stroke in patients with PSV.

Methods

Data from adults newly diagnosed with PSV within the Diagnostic and Classification Criteria in VASculitis (DCVAS) study were analysed. Demographics, risk factors for vascular disease, and clinical features were compared between patients with PSV with and without CVE. Stroke subtypes and cumulative incidence of recurrent CVE during a prospective 6-month follow-up were also assessed.

Results

The analysis included 4828 PSV patients, and a CVE was reported in 169 (3.50%, 95% CI 3.00–4.06): 102 (2.13% 95% CI 1.73–2.56) with stroke and 81 (1.68% 95% CI 1.33–2.08) with transient ischemic attack (TIA). The frequency of CVE was highest in Behçet’s disease (9.5%, 95% CI 5.79–14.37), polyarteritis nodosa (6.2%, 95% CI 3.25–10.61), and Takayasu’s arteritis (6.0%, 95% CI 4.30–8.19), and lowest in microscopic polyangiitis (2.2%, 95% CI 1.09–3.86), granulomatosis with polyangiitis (2.0%, 95% CI 1.20–3.01), cryoglobulinaemic vasculitis (1.9%, 95% CI 0.05–9.89), and IgA-vasculitis (Henoch-Schönlein) (0.4%, 95% CI 0.01–2.05). PSV patients had a 11.9% cumulative incidence of recurrent CVE during a 6-month follow-up period.

Conclusion

CVEs affect a significant proportion of patients at time of PSV diagnosis, and the frequency varies widely among different vasculitis, being higher in Behçet’s. Overall, CVE in PSV is not explained by traditional vascular risk factors and has a high risk of CVE recurrence.
Clinicopathological analysis of thyroid carcinomas with the RET and NTRK fusion genes: characterization for genetic analysis
Authors: Okubo Yoichiro , Toda Soji , Kadoya Mei , Sato Shinya , Yoshioka Emi , Hasegawa Chie , Ono Kyoko , Washimi Kota , Yokose Tomoyuki , Miyagi Yohei , Masudo Katsuhiko , Iwasaki Hiroyuki , Hayashi Hiroyuki
Published: March 2024

Thyroid carcinomas exhibit various genetic alterations, including the RET and NTRK fusion genes that are targets for molecular therapies. Thus, detecting fusion genes is crucial for devising effective treatment plans. This study characterized the pathological findings associated with these genes to identify the specimens suitable for genetic analysis. Thyroid carcinoma cases positive for the fusion genes were analyzed using the Oncomine Dx Target Test. Clinicopathological data were collected and assessed. Among the 74 patients tested, 8 had RET and 1 had NTRK3 fusion gene. Specifically, of the RET fusion gene cases, 6 exhibited “BRAF-like” atypia and 2 showed “RAS-like” atypia, while the single case with an NTRK3 fusion gene presented “RAS-like” atypia. Apart from one poorly differentiated thyroid carcinoma, most cases involved papillary thyroid carcinomas (PTCs). Primary tumors showed varied structural patterns and exhibited a high proportion of non-papillary structures. Dysmorphic clear cells were frequently observed. BRAF V600E immunoreactivity was negative in all cases. Interestingly, some cases exhibited similarities to diffuse sclerosing variant of PTC characteristics. While calcification in lymph node metastases was mild, primary tumors typically required hydrochloric acid-based decalcification for tissue preparation. This study highlights the benefits of combining morphological and immunohistochemical analyses for gene detection and posits that lymph node metastases are more suitable for genetic analysis owing to their mild calcification. Our results emphasize the importance of accurate sample processing in diagnosing and treating thyroid carcinomas.
Pyodermatitis-pyostomatitis vegetans: a case report and systematic review focusing on oral involvement
Authors: Chrcanovic Bruno Ramos , Martins-Chaves Roberta Rayra , Pontes Flávia Sirotheau Correa , Fonseca Felipe Paiva , Pontes Hélder Antônio Rebelo , Gomez Ricardo Santiago
Published: March 2024

Background

Pyodermatitis-pyostomatitis vegetans (PPV) is a rare mucocutaneous disease characterized by multiple pustules and it is considered a marker for inflammatory bowel disease (IBD). The oral manifestations of this condition are referred to as pyostomatitis vegetans (PSV).

Purpose

To investigate which features could help in establishing the diagnosis of PSV, with or without cutaneous lesions, based on information retrieved from all cases of PSV described in the literature. A case of PV from the authors was also included in the analysis.

Methods

An electronic search was undertaken, last updated in August 2022. Inclusion criteria included publications reporting cases of PSV, with the diagnosis confirmed by the pathological examination of oral or skin lesions, and presence of IBD.

Results/Conclusions

Sixty-two publications with 77 cases of PSV and an associated IBD were included. Features that are helpful in establishing the diagnosis of PSV are snail track appearance of oral lesions, an associated IBD (which is not always symptomatic), evidence of intraepithelial clefting on microscopic examination of oral lesions, and peripheral blood eosinophilia. A gold standard for the management of PSV does not exist and high-level evidence is limited. There is no established therapeutic protocol for PSV and management primarily consists of topical and/or systemic corticosteroids, antirheumatic drugs (sulfasalazine, mesalazine), monoclonal antibody (infliximab, adalimumab) immunosuppressives (azathioprine, methotrexate), antibiotics (dapsone), or a combination of these. The risk of recurrence of oral lesions is considerable when the medication dose is decreased or fully interrupted.
Structured interpolation for multivariate transfer functions of quadratic-bilinear systems
Authors: Benner Peter , Gugercin Serkan , Werner Steffen W. R.
Published: March 2024

High-dimensional/high-fidelity nonlinear dynamical systems appear naturally when the goal is to accurately model real-world phenomena. Many physical properties are thereby encoded in the internal differential structure of these resulting large-scale nonlinear systems. The high dimensionality of the dynamics causes computational bottlenecks, especially when these large-scale systems need to be simulated for a variety of situations such as different forcing terms. This motivates model reduction where the goal is to replace the full-order dynamics with accurate reduced-order surrogates. Interpolation-based model reduction has been proven to be an effective tool for the construction of cheap-to-evaluate surrogate models that preserve the internal structure in the case of weak nonlinearities. In this paper, we consider the construction of multivariate interpolants in frequency domain for structured quadratic-bilinear systems. We propose definitions for structured variants of the symmetric subsystem and generalized transfer functions of quadratic-bilinear systems and provide conditions for structure-preserving interpolation by projection. The theoretical results are illustrated using two numerical examples including the simulation of molecular dynamics in crystal structures.
A chaotic based image encryption scheme using elliptic curve cryptography and genetic algorithm
Authors: Kumar Sanjay , Sharma Deepmala
Published: March 2024

In the era of digital communication and data security, image encryption plays a crucial role in safeguarding sensitive information. Protecting sensitive visual data from unauthorized access drives the pursuit of advanced image encryption methods. This paper proposes a novel approach to enhance image encryption by combining the power of a chaotic map, elliptic curve cryptography, and genetic algorithm. The chaotic map, specifically Arnold’s cat map, is employed to introduce chaos and randomness into the encryption process. The proposed image encryption process involves applying Arnold’s cat map for shuffling the pixel positions, followed by elliptic curve cryptography for encrypting the pixel values using public and private keys. Additionally, a genetic algorithm is employed to optimize the key generation process, enhancing the security of the encryption scheme. The combined utilization of these techniques aims to achieve a high level of confidentiality and robustness in image encryption. The algorithm underwent thorough analysis. It achieved a maximum entropy score of 7.99, indicating a high level of randomness and unpredictability in the encrypted data. Additionally, it exhibited near-zero correlation, which suggests strong resistance against statistical attacks. Moreover, the cryptographic range of possible keys was found to be $$2^{511}$$

2
511

. This extensive key space makes the algorithm highly resilient against brute force attacks. It took only 0.5634 s to encrypt a moderately sized $$512\times 512$$

512
×
512

pixel image with an 8-bit image on a standard desktop computer with a 2.3 GHz processor and 16 GB of RAM. The experimental findings confirm that the proposed approach is highly effective and efficient in safeguarding sensitive image data from unauthorized access and potential attacks. This scheme has the benefit of allowing us to protect our private image data while it’s being transmitted.
Toxicological insight of magnetite nanogel: neuro-ethological, hepato-renal, antioxidant, and histopathological traits in Clarias gariepinus
Authors: Kamel Samar , Ahmed Shaimaa A. A. , Elsayyad Asmaa , Abdelwarith Abdelwahab A. , Younis Elsayed M. , Shaalan Mohamed , Gaballa Mohamed M. S. , Mahboub Heba H. , Khamis Tarek , Ismail Sameh H. , Davies Simon J. , Hassan Zeinab
Published: March 2024

Assessment of acute toxicity of magnetic nanogel (MNG) is crucial to conclude the safe applicable dose and to warrant its application in aquaculture. Therefore, the current study is a novel step to assess behavior, neuro-stress response, hepato-renal, oxidative, and histopathological variations produced by MNG’ acute toxicity in Clarias gariepinus. Two experiments were conducted: the first was a determination of the 96-h lethal concentration 50 (LC50) of MNG in C. gariepinus. Meanwhile, the second was an assessment of the toxicological impacts of three different concentrations of MNG in C. gariepinus following a 10-day exposure period and a subsequent 10-day depuration trial. One hundred and eighty fish were allotted to four groups exposed to 0, 1/10, 1/8, or 1/5 96-h LC50 of MNG. The outcomes exhibited that 96-h LC50 of MNG for C. gariepinus was 44 mg/L. The subjected group to MNG induced a concentration-dependent elevation in the serum values of cortisol, alanine transaminase, aspartate transaminase, urea, and creatinine following MNG exposure. Marked elevation in the oxidative stress indicators (catalase (CAT), glutathione S-transferase activity (GST), and superoxide dismutase (SOD)) was also evident. Meanwhile, the value of the neurological biomarker, acetylcholinesterase (AChE), was markedly reduced in a concentration-dependent way. These biochemical changes were complemented by pathological alterations in the hepato-renal architecture. Interestingly, in response to the 10-day depuration period, most of the tested parameters were eliminated in C. gariepinus exposed to 1/10 of LC50. Conclusively, MNG can induce numerous adverse effects only at higher doses (1/5 and 1/8 of LC50). Meanwhile, the lowest tested concentration of MNG (1/10 of LC50) was safe for application in aquaculture practices with only mild disruptions in the bio-indices. In addition, a retrieval period of 10 days was sufficient to renovate these alterations only in fish exposed to the same concentration.
Effectiveness of Vasopressin Against Cardiac Arrest: A Systematic Review of Systematic Reviews
Authors: Ho Jonathan Ka-Ming , Tam Hon-Lon , Leung Leona Yuen-Ling
Published: March 2024

Purpose

This systematic review (SR) of SRs evaluates the effectiveness of vasopressin alone or in combination with other drugs in improving the outcomes of cardiac arrest (CA).

Methods

Using a three-step approach, we searched five databases to identify all relevant SRs. Two reviewers independently selected suitable studies, assessed study quality, and extracted relevant data. If an outcome was reported by multiple SRs, a re-meta-analysis was conducted as needed; otherwise, a narrative analysis was performed.

Results

Twelve SRs covering 16 original studies were included in this review. The meta-analysis results revealed a significant increase in survival to hospital admission for patients with in-hospital CA (IHCA) or out-of-hospital CA (OHCA) receiving vasopressin alone compared with that for those receiving epinephrine alone. Furthermore, the return of spontaneous circulation (ROSC) was significantly increased in patients with OHCA receiving vasopressin with epinephrine compared with that in those receiving epinephrine alone. Compared with patients with IHCA receiving epinephrine with placebo, those receiving vasopressin, steroids, and epinephrine (VSE) exhibited significant increases in ROSC, survival to hospital discharge, favorable neurological outcomes, mean arterial pressure, renal failure–free days, coagulation failure–free days, and insulin requirement.

Conclusion

VSE is the most effective drug combination for improving the short- and long-term outcomes of IHCA. It is recommended to use VSE in patients with IHCA. Future studies should investigate the effectiveness of VSE against OHCA and CA of various etiologies, the types and standard dosages of steroids for cardiac resuscitation, and the effectiveness of vasopressin–steroid in improving CA outcomes.
Decision making in complex land systems: outline of a holistic theory of agency
Authors: Christensen Andreas Aagaard , Van Eetvelde Veerle
Published: March 2024

Context

Models of human agency within research on land systems and landscapes do not fully account for social and cultural factors in decision making. Conversely, within social theory, parallel concepts of agency do not fully take biophysical and spatial factors into account. This calls for a synthesis of conceptual models addressing human decision making in land systems.

Objectives

The review identifies parallels between social and ecological perspectives on humans as co-constituent parts of complex land systems. On this basis selected models of agency combining insights from social theory and land systems research are outlined and compared, and improved concepts are outlined.

Methods

Elements of agency in modern agricultural land systems are reviewed. A case study illustrating the application of agency concepts in an analysis of decision making among farmers on the Canterbury Plains (New Zealand) is presented. On this basis it is discussed how to improve understandings of human agency in land systems.

Results

The review identifies and compares parallel conceptions of agency, practice and holism in landscape ecology and social theory. Taking the agency of farmers in contemporary agricultural landscapes as an example, theories currently used to characterise and interpret the agency of farmers are discussed and improvements considered. Potentials for improvement of current conceptual models are indicated and discussed, and an improved model of agency is suggested.

Conclusions

Based on the review, the article presents an improved conceptual model of agency in land systems emphasizing the position of agents in social-ecological contexts of action.
Multi-back-propagation Algorithm for Signal Neural Network Decomposition
Authors: Salgado Paulo , Perdicoúlis T.-P. Azevedo
Published: March 2024

In this paper, a novel back-propagation error technique is presented. This neural network structure allows for two fundamental basic modes: (1) To decompose the neurones by transforming their variables, weights, and scalar functions into vectors. This conveys for the decomposition of the transfer function of every neurone (where the output variables are the components of the decomposition) and, consequently, to be written as the invariant sum of orthogonal functions, with the safeguard of preserving information This orthogonality is proven using Fourier theory. (2) In a second mode, a tuned neural network that occupies one of the channels of the neural network can see the weights of its supplementary channels adjusted to retain additional information. Only the decomposition algorithm of the network is presented here—Multi-back-propagation algorithm. The adopted methodology is validated step-by-step with some representative examples. Namely, to assess the performance of the splitting method, two different examples have been constructed from scratch: (1) a 2D classification problem and (2) a 3D surface. In both problems, the signal and transfer functions of the neural network are successfully decomposed without information losses. Therefore, since the main contribution of this work is to allow for the organisation of the information stored in neural network structure, through a split process, this promising method shows potential use in various areas—e.g. classification and/or pattern recognition problems, data analysis, modelling and so on. In the future, we expect to work further in the method computational aspects to render it more efficient, versatile and robust.
Predictive machine learning for gully susceptibility modeling with geo-environmental covariates: main drivers, model performance, and computational efficiency
Authors: Phinzi Kwanele , Szabó Szilárd
Published: March 2024

Currently, machine learning (ML) based gully susceptibility prediction is a rapidly expanding research area. However, when assessing the predictive performance of ML models, previous research frequently overlooked the critical component of computational efficiency in favor of accuracy. This study aimed to evaluate and compare the predictive performance of six commonly used algorithms in gully susceptibility modeling. Artificial neural networks (ANN), partial least squares, regularized discriminant analysis, random forest (RF), stochastic gradient boosting, and support vector machine (SVM) were applied. The comparison was conducted under three scenarios of input feature set sizes: small (six features), medium (twelve features), and large (sixteen features). Results indicated that SVM was the most efficient algorithm with a medium-sized feature set, outperforming other algorithms across all overall accuracy (OA) metrics (OA = 0.898, F1-score = 0.897) and required a relatively short computation time (< 1 min). Conversely, ensemble-based algorithms, mainly RF, required a larger feature set to reach optimal accuracy and were computationally demanding, taking about 15 min to compute. ANN also showed sensitivity to the number of input features, but unlike RF, its accuracy consistently decreased with larger feature sets. Among geo-environmental covariates, NDVI, followed by elevation, TWI, population density, SPI, and LULC, were critical for gully susceptibility modeling. Therefore, using SVM and involving these covariates in gully susceptibility modeling in similar environmental settings is strongly suggested to ensure higher accuracy and minimal computation time.
Bank intervention and firms’ earnings management: evidence from debt covenant violations
Authors: Huang Yichu , Chen Lei , Liu Frank Hong
Published: March 2024

Earnings management has long been one of the main concerns in accounting and management literature, and the extent to which corporate governance mechanisms can discipline management behaviour and prevent earnings management has attracted increasing interest among policy makers and academic researchers. Differing from previous corporate governance literature that focuses mainly on the board and auditors, we explore the role of creditors in corporate governance. In particular, we examine the effect of bank intervention on earnings management via the lens of debt covenant violations, where control rights are transferred to creditors (banks). Using a Difference-in-Difference approach, we find that firms reduce both their accruals-based and real earnings management following debt covenant violations. The negative effect on earnings management is more prominent when banks possess greater bargaining and monitoring power and when firms are more financially constrained. By identifying a specific channel through which debt providers influence corporate financial reporting, our findings suggest that creditors can play an important role in governing organisations and disciplining management behaviour.
Impact of bee bread supplementation on Japanese quails: laying performance, eggshell chemical composition and serum biochemistry
Authors: Simonova Nikoleta , Kalafova Anna , Dupak Rudolf , Schneidgenova Monika , Hanusova Emília , Hrncar Cyril , Hascik Peter , Gren Agnieszka , Goc Zofia , Kapusta Edyta , Capcarova Marcela
Published: March 2024

Bee bread is exceptional product of the beehive by its composition and a unique production by honeybees. Since the legislation prohibits the use of growth stimulants in animal husbandry, there is a growing interest in improving the yield of meat and eggs, and its quality parameters after applying various natural products. The impacts of bee bread supplementation on laying performance, eggshell chemical composition, serum biochemical parameters of Japanese quails were studied. Antioxidant activity, polyphenols, flavonoids, phenolic acids from bee bread, feeding mixture and combination was determined. A total of 45 female quails were involved in the experiment. The quails were divided into three groups as follows: group with 0.2% addition of bee bread into feeding mixture (E1, n = 15), group with 0.6% addition of bee bread into feeding mixture (E2, n = 15), and the control without additives (C, n = 15). The groups were kept under the standard conditions. After 180 days the animals were slaughtered, blood samples were collected. Addition of 0.6% bee bread in group E2 significantly decreased TAG level compared to group E1, without affecting laying performance. We noticed significant increase in Cd, Pb levels in eggshell in group E1 compared to control group. On the other side, 0.6% addition of bee bread caused significant reduction in Pb, Cd levels in eggshell compared to group with 0.2% addition of bee bread. The incorporation of bee bread into feeding mixture added improved antioxidant activity along with polyphenols and flavonoids. The results indicate that the effect of bee bread was dose dependent. The effective dosage estimation of additives used in feed for Japanese quails plays important role.
Osteopontin Rejuvenates Senescent Adipose-Derived Stem Cells and Restores their Bone Tissue Regenerative Function
Authors: Zhang Yiran , Zhang Junni , Lesani Pooria , Lu Zufu , Zreiqat Hala
Published: March 2024

The regenerative function of stem cells is compromised when the proportion of senescent stem cells increases with ageing advance. Therefore, combating stem cell senescence is of great importance for stem cell-based tissue engineering in the elderly, but remains largely unexplored. Osteopontin (OPN), a glycosylated phosphoprotein, is one of the key extracellular matrix molecules in bone tissue. OPN activates various signalling pathways and modulates cellular activities, including cell senescence. However, the role of OPN in stem cell senescence remains largely unknown. This study aims to investigate if OPN modulates cell senescence and bone regenerative function in human adipose-derived mesenchymal stem cells (ASCs), and to determine the underlying mechanisms. We first developed a senescent ASC model using serial passaging until passage 10 (P10), in which senescent cells were characterised by reduced proliferation and osteogenic differentiation capacity compared to P4 ASCs. The conditioned medium from P10 ASCs exhibited a diminished trophic effect on human osteoblasts (HOBs), compared to that from P4 ASCs. P10 ASCs on OPN-coated surface showed rejuvenated phenotype and enhanced osteogenic differentiation. The conditioned medium from P10 ASCs on OPN-coating improved trophic effects on HOBs. OPN regulated the morphology of senescent ASCs, transforming them from a more rounded and flattened cell shape to an elongated shape with a smaller area. These findings demonstrated the effects of OPN in restoring senescent ASCs functions, possibly through a mechanism that involves the modulation of cell morphology, indicating that OPN might hold a great potential for rejuvenating senescent stem cells and could potentially open a new venue for regenerating bone tissue in age-related diseases.

Graphical Abstract
Quantitative needs assessment tools for people with mental health problems: a systematic scoping review
Authors: Makivić Irena , Kragelj Anja , Lasalvia Antonio
Published: March 2024

Needs assessment in mental health is a complex and multifaceted process that involves different steps, from assessing mental health needs at the population or individual level to assessing the different needs of individuals or groups of people. This review focuses on quantitative needs assessment tools for people with mental health problems. Our aim was to find all possible tools that can be used to assess different needs within different populations, according to their diverse uses. A comprehensive literature search with the Boolean operators “Mental health” AND “Needs assessment” was conducted in the PubMed and PsychINFO electronic databases. The search was performed with the inclusion of all results without time or other limits. Only papers addressing quantitative studies on needs assessment in people with mental health problems were included. Additional articles were added through a review of previous review articles that focused on a narrower range of such needs and their assessment. Twenty-nine different need-assessment tools specifically designed for people with mental health problems were found. Some tools can only be used by professionals, some by patients, some even by caregivers, or a combination of all three. Within each recognized tool, there are different fields of needs, so they can be used for different purposes within the needs assessment process, according to the final research or clinical aims. The added value of this review is that the retrieved tools can be used for assessment at the individual level, research purposes or evaluation at the outcome level. Therefore, best needs assessment tool can be chosen based on the specific goals or focus of the related needs assessment.
TIDAL: exploring the potential of data physicalization-based interactive environment on runners' motivation
Authors: Guo Mengyan , Hu Jun , Vos Steven
Published: March 2024

Representing fitness-related data physically can better help people gain awareness and reflect on their physical activity behavior. However, there has been limited research conducted on the impact of physicalizing personal data in a public context, particularly regarding its effect on motivations for physical activity. Augmenting the physical environment with interactive technology holds great promise in facilitating outdoor physical activity. To explore the design space of data physicalization-based interactive environments, we created TIDAL, a design concept that provides physical rewards in the form of tiles on the road to acknowledge runners’ goal achievements. We created a video prototype as a probe to gather insights through semi-structured interviews with six recreational runners to evaluate TIDAL. The co-constructing stories method, a participatory design technique, was employed during these interviews to facilitate qualitative evaluation. The results of our study showed that TIDAL has the potential to increase runners’ motivation. We reported the key insights derived from participants’ feedback and co-constructed stories and discussed the broader implications of our work.
Classification of geotechnical units and their associated slope movements for application to civil engineering in volcanic territories
Authors: Hernández-Gutiérrez Luis. E. , Rodríguez-Losada José A. , Cruz-Pérez Noelia , Rodríguez-Martín Jesica , Santamarta Juan C.
Published: March 2024

Slope movements are one of the natural hazards that most affect volcanic islands and often cause alarm to society, as they produce considerable material losses, affect communications and basic community services and, on occasion, involve the loss of human lives. Based on the classification of geotechnical units of the Canary Islands and the characteristic slope movements observed in each of them, the main goal of this article has been to elaborate a classification of movements versus units, as a tool for the management landslides hazards in volcanic environments. The applied methodology was based on the types of slope movements defined by the USGS, and on the research team three decades of experience of the study of geotechnical characterisation and slope instability of volcanic formations. A graphical classification of the possible movements affecting the volcanic geotechnical units has been prepared to make a preliminary estimate of the types of movements that will affect a slope or hillside.
Status quo of fertilization strategies and nutrient farm gate budgets on stockless organic vegetable farms in Germany
Authors: Stein Sophie , Hartung Jens , Zikeli Sabine , Möller Kurt , Reents Hans Jürgen
Published: March 2024

Fertilizer management in stockless organic vegetable production is strongly affected by external nutrient purchases due to the high nitrogen (N) and potassium (K) requirements of vegetables. However, the database on nutrient flows and budgets in organic vegetable farming in Europe is very limited. Therefore, a survey based on semi-structured interviews was carried out comprising 12 organic horticultural farms in Germany. The results show that three different main fertilizer categories are used as inputs in different ratios by the inventoried farms: (1) base fertilizers (e.g., composts, solid farmyard manures), (2) commercial organic N fertilizers (e.g., keratins or plant products from food production or fermentation processes), and (3) commercial mineral fertilizers (e.g., potassium sulfate), all of which are approved for organic production. Ninety percent of the total nutrient inputs to the farms came from these fertilizers and biological N2 fixation, with the remaining 10% coming from other inputs, such as seeds or growing media. The estimated yearly average total farm budgets were nearly balanced across all farms with moderate surpluses (67.5 kg N ha−1, 2.06 kg P ha−1, and 0.26 kg K ha−1). However, large imbalances were found for most of the individual farms. These imbalances indicate the risk of nutrient accumulation or nutrient depletion in the soil, depending on the fertilization strategy and productivity of the farm. More specifically, increasing N share from base fertilizers led to increased P and K budgets, while strategies based on the use of large amounts of keratins led to the opposite—K and P depletion. We concluded that balanced nutrient management in organic vegetable production systems requires a thorough calculation and should combine the use of base fertilizers, commercial fertilizers with low P content, and increased N supply via BNF.
In Memory of Steffen Hölldobler: From Logic to Formal and Cognitive Reasoning
Authors: Bhadra Meghna , Furbach Ulrich
Published: March 2024

With this article, the two authors would like to pay tribute to the memory of their dear friend and colleague Steffen Hölldobler, who left us far too early in 2023. Ulrich (UF), in his time as a postdoc at the University of the Bundeswehr Munich, mentored Steffen as a student in his first logic lectures. Meghna (MB) is Steffen’s last PhD student. Although there is so much more to the wonderful man Steffen was, this article strives to briefly touch upon some of the various hats he donned during his lifetime—as a student, a researcher, a professor and a friend.
Rotorcraft stability analysis using Lyapunov characteristic exponents estimated from multibody dynamics
Authors: Cassoni Gianni , Cocco Alessandro , Tamer Aykut , Zanoni Andrea , Masarati Pierangelo
Published: March 2024

Stability analysis of complex, nonlinear dynamical systems is a challenge. The use of Lyapunov Characteristic Exponents through a Jacobian-less method is proposed as a means to identify the Maximum Lyapunov Characteristic Exponent, namely the fundamental stability indicator of a generic problem, solely from time series obtained through general-purpose multibody dynamics simulations of complex rotorcraft aeromechanics models. The method is first applied to a relatively simple scenario concerning the identification of ground resonance. Then, its application to more complex models is addressed by studying the aeroelastic stability and identifying the whirl flutter of the XV-15 tiltrotor using a comprehensive aeroelastic model.
Artificial intelligence in the diagnosis and treatment of acute appendicitis: a narrative review
Authors: Bianchi Valentina , Giambusso Mauro , De Iacob Alessandra , Chiarello Maria Michela , Brisinda Giuseppe
Published: March 2024

Artificial intelligence is transforming healthcare. Artificial intelligence can improve patient care by analyzing large amounts of data to help make more informed decisions regarding treatments and enhance medical research through analyzing and interpreting data from clinical trials and research projects to identify subtle but meaningful trends beyond ordinary perception. Artificial intelligence refers to the simulation of human intelligence in computers, where systems of artificial intelligence can perform tasks that require human-like intelligence like speech recognition, visual perception, pattern-recognition, decision-making, and language processing. Artificial intelligence has several subdivisions, including machine learning, natural language processing, computer vision, and robotics. By automating specific routine tasks, artificial intelligence can improve healthcare efficiency. By leveraging machine learning algorithms, the systems of artificial intelligence can offer new opportunities for enhancing both the efficiency and effectiveness of surgical procedures, particularly regarding training of minimally invasive surgery. As artificial intelligence continues to advance, it is likely to play an increasingly significant role in the field of surgical learning. Physicians have assisted to a spreading role of artificial intelligence in the last decade. This involved different medical specialties such as ophthalmology, cardiology, urology, but also abdominal surgery. In addition to improvements in diagnosis, ascertainment of efficacy of treatment and autonomous actions, artificial intelligence has the potential to improve surgeons’ ability to better decide if acute surgery is indicated or not. The role of artificial intelligence in the emergency departments has also been investigated. We considered one of the most common condition the emergency surgeons have to face, acute appendicitis, to assess the state of the art of artificial intelligence in this frequent acute disease. The role of artificial intelligence in diagnosis and treatment of acute appendicitis will be discussed in this narrative review.
Research on Fiber Optic Surface Plasmon Resonance Biosensors: A Review
Authors: Wang Qi , Zhang Dianyun , Qian Yizhuo , Yin Xiangyu , Wang Lei , Zhang Shushuai , Wang Yuyang
Published: March 2024

Due to the benefits of the high sensitivity, real-time response, no labeling requirement, and good selectivity, fiber optic sensors based on surface plasmon resonance (SPR) have gained popularity in biochemical sensing in recent years. The current research on such sensors is hot in enhancing sensitivity, improving detection accuracy, and achieving the detection of biochemical molecules. The goal of this work is to present a thorough overview of recent developments in the optical fiber SPR biosensor research. Firstly, it explores the basic principles and sensing structures of optical fiber SPR biosensors, focusing on four aspects. Subsequently, this paper introduces three fiber optic surface plasmon biosensors: SPR, localized surface plasmon resonance (LSPR), and long-range surface plasmon resonance (LRSPR). Each concept is explained from the perspective of the basic principles of fiber optic SPR biosensors. Furthermore, a classification of fiber optic SPR biosensors in health monitoring, food safety, environmental monitoring, marine detection, and other applications is introduced and analyzed. Eventually, this paper summarizes the current research directions of SPR biosensors. Meanwhile, it provides a prospective outlook on how fiber optic SPR sensors will develop in the future.
Parent-Mediated Naturalistic Developmental Behavioral Interventions for Young Autistic Children: A Systematic Literature Review of Single-Case Research
Authors: van Noorden Lauren , Gardiner Siobhan , Waddington Hannah
Published: March 2024

Naturalistic developmental behavioral interventions (NDBIs) are a class of supports that may lend themselves to a parent-mediated approach. This systematic literature review synthesizes single-case research evaluations of parent-mediated NDBIs for young autistic children. Of the 353 articles screened, 17 were eligible for inclusion. Child outcome measures included engagement, joint attention, language/communication, imitation, and ‘compliance’/avoidance. Most studies found positive effects for at least some children on at least one measure. However, there were no consistently positive effects across studies. Most parents increased their NDBI fidelity, but many did not reach specified fidelity criteria. Only three studies met all Council of Exceptional Children quality indicators. These results suggest that parent-mediated NDBIs are a promising approach to supporting young autistic children, but more high-quality research is needed.