bluuebunny/crossref_metadata_2025 huggingface dataset:
Keeping it simple: simplified frameworks for long-lived particles at neutrino facilities
Authors: Batell Brian , Huang Wenjie , Kelly Kevin J.
Published: August 2023

Abstract

Modern-day accelerator neutrino facilities are excellent venues for searches for new-physics particles. Many distinct new-physics models predict overlapping signatures and phenomenology in these experiments. In this work, we advocate for the adoption of simplified frameworks when studying these types of new-physics signatures, which are characterized by a small number of primary variables, including particle masses, lifetimes, and production and decay modes/rates that most directly control signal event rates and kinematics. In particular, taking the example of long-lived particles that decay inside a neutrino detector as a test case, we study formulate and study simplified frameworks in the context of light scalars/fermions produced in kaon decays which then decay into final states containing an electron-positron pair. We show that using these simplified frameworks can allow for individual experimental analyses to be applicable to a wide variety of specific model scenarios. As a side benefit, we demonstrate that using this approach can allow for the T2K collaboration, by reinterpreting its search for Heavy Neutral Leptons, to be capable of setting world-leading limits on the Higgs-Portal Scalar model. Furthermore, we argue the simplified framework interpretation can serve as a bridge to model identification in the hopeful detection of a new-physics signal. As an illustration, we perform a first determination of the likelihood that, in the presence of a new-physics signal in a detector like the DUNE ND-GAr, multiple different new-physics hypotheses (such as the Higgs-Portal Scalar and Heavy Neutral Lepton ones) can be disentangled. We demonstrate that this model discrimination is favorable for some portions of detectable new-physics parameter space but for others, it is more challenging.
Metric fluctuations in higher-dimensional black holes
Authors: Han Hyewon , Gwak Bogeun
Published: August 2023

Abstract

We investigated the impact of metric fluctuations on the higher-dimensional black hole geometry. We generalized the four-dimensional model to higher dimensions to treat quantum vacuum fluctuations by the classical approach. A fluctuating black hole is portrayed by a higher-dimensional Vaidya metric with a spherically oscillating mass. Assuming a small fluctuation amplitude, we employed a perturbation method to obtain a radially outgoing null geodesic equation up to the second order in the fluctuation. Furthermore, the fluctuation of the event horizon up to the second order depends on the number of spacetime dimensions. Therefore, the time-averaged values of the thermodynamic variables defined at the horizon also feature dimension-dependent correction terms. A general solution was obtained for rays propagating near the horizon within a fluctuating geometry. Upon examining this in a large D limit, we found that a complete solution can be obtained in a compact form.
Geometric quantum discord signals non-factorization
Authors: Banerjee Souvik , Basteiro Pablo , Das Rathindra Nath , Dorband Moritz
Published: August 2023

Abstract

We propose the information-theoretic quantity of geometric quantum discord (GQD) as an indicator of the factorization properties of a given quantum system. In particular, we show how non-vanishing discord implies that the corresponding partition function does not factorize, both for generic pure states and the thermofield double state as a state with a known geometric dual in light of the AdS/CFT correspondence. Via this analysis, we give a novel interpretation to the thermomixed double state as the best purely classical approximation of the Einstein-Rosen bridge. We connect the non-vanishing of GQD with the existence of wormhole microstates.
Identification of representative sampling sites for the investigation of aerial longer distances transport of pesticides in Germany
Authors: Kubiak Roland , Peters Anna , Gathmann Achim , Hohgardt Karsten , Kula Christine , Marutzky Daniela , Streib Lucas , Thomas Kai , Trapp Matthias
Published: August 2023

Aerial transport of pesticides during and after their application both over medium range distances and long distance may lead to residues on plants and soil far away from agricultural treatments. Therefore, the Federal Office of Consumer Protection and Food Safety carried out a Germany-wide geographical analysis to identify monitoring sites which could be used for a representative German-wide monitoring. The identified sites reflect climate areas with different meteorological conditions, land coverage and pesticide use. By using a geographical information system, five different areas were identified representing the climatic and agricultural conditions of pesticide use in Germany. Since the required measuring technique needed a certain infrastructure, using already existing measuring sides was considered to be most efficient in order to use them for a German-wide monitoring. In a second step, agro-meteorological weather stations with distances of < 100 m, 100–1000 m and > 1 km in the main wind direction from treated fields were identified within these areas. The identified areas reflect the main different conditions for aerial pesticide transport along with suitable weather stations to monitor pesticide residues in the air and its deposition on plants and soil all over Germany.
Sex influences elemental variation in the mineralized vertebrae cartilage of round stingray (Urobatis halleri)
Authors: Brodbeck Bethany E. , Lyons Kady , Miller Nathan R. , Mohan John A.
Published: August 2023

The elemental composition of mineralized vertebral cartilage has proven useful for reconstructing the movement and environmental history of elasmobranchs. However, the effects of intrinsic and extrinsic factors on vertebral chemistry have not been well explored, making meaningful interpretations of results difficult. This study quantified trace element incorporation along the corpus calcareum of 116 Round Stingray (Urobatis halleri) vertebrae and explored the influence of intrinsic (i.e., sex) and extrinsic (i.e., location and year) factors on vertebral edge chemical variations. We quantified eight element/Ca ratios (Li/Ca, Mg/Ca, Mn/Ca, Co/Ca, Cu/Ca, Zn/Ca, Sr/Ca, Ba/Ca) by laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). Behavioral sexual segregation by Round Stingrays explained differences found in Mn/Ca, Zn/Ca, Sr/Ca, and Ba/Ca ratios. Higher vertebral Mn/Ca and Zn/Ca in females likely originate from the use of salt marsh habitats as a refuge as well as higher reproductive hormone concentrations during gestation, respectively. Female and male Round Stingrays were also found to have an inverse relationship between Sr/Ca and Ba/Ca, likely due to environmental differences (e.g., temperature) between their sexually segregated habitats. This study demonstrates how multielement signatures in vertebral cartilage may improve understanding of habitat use and migration throughout life and advances the development of biomineral usage as an environmental proxy in elasmobranchs.
Neural mechanism of circadian clock-based photoperiodism in insects and snails
Authors: Hamanaka Yoshitaka , Hasebe Masaharu , Shiga Sakiko
Published: August 2023

The photoperiodic mechanism distinguishes between long and short days, and the circadian clock system is involved in this process. Although the necessity of circadian clock genes for photoperiodic responses has been demonstrated in many species, how the clock system contributes to photoperiodic mechanisms remains unclear. A comprehensive study, including the functional analysis of relevant genes and physiology of their expressing cells, is necessary to understand the molecular and cellular mechanisms. Since Drosophila melanogaster exhibits a shallow photoperiodism, photoperiodic mechanisms have been studied in non-model species, starting with brain microsurgery and neuroanatomy, followed by genetic manipulation in some insects. Here, we review and discuss the involvement of the circadian clock in photoperiodic mechanisms in terms of neural networks in insects. We also review recent advances in the neural mechanisms underlying photoperiodic responses in insects and snails, and additionally circadian clock systems in snails, whose involvement in photoperiodism has hardly been addressed yet. Brain neurosecretory cells, insulin-like peptide/diuretic hormone44-expressing pars intercerebralis neurones in the bean bug Riptortus pedestris and caudo-dorsal cell hormone-expressing caudo-dorsal cells in the snail Lymnaea stagnalis, both promote egg laying under long days, and their electrical excitability is attenuated under short and medium days, which reduces oviposition. The photoperiodic responses of the pars intercerebralis neurones are mediated by glutamate under the control of the clock gene period. Thus, we are now able to assess the photoperiodic response by neurosecretory cell activity to investigate the upstream mechanisms, that is, the photoperiodic clock and counter.
Comparative analysis of surgical management approaches for hydatid liver cysts: conventional vs. minimally invasive techniques
Authors: Elmoghazy Walid , Alqahtani Jowhara , Kim Seon Woo , Sulieman Ibnouf , Elaffandi Ahmed , Khalaf Hatem
Published: August 2023

Introduction

Hydatid liver disease is a prevalent condition in endemic areas, particularly in the Middle East and North Africa. The use of laparoscopy as a treatment option has gained popularity. However, there is still ongoing debate regarding the optimal approach for surgical management. In this study, we present our experience with the surgical treatment of hydatid liver disease comparing conventional and minimally invasive approaches, including laparoscopic and robotic options.

Methods

We conducted a retrospective review of patients who underwent surgery for hydatid liver disease at our institution. Data was collected on the patients’ clinical presentations, cyst characteristics, surgical procedures performed, intraoperative findings, and postoperative complications.

Results

A total of 98 hydatid liver cysts were surgically managed in 57 patients. The mean age of the patients was 37.2 ± 10.2 years, with 38 (66.7%) being male. Among the patients, 14 (24.6%) underwent conventional surgery (6 partial pericystectomy, 4 total pericystectomy, and 4 liver resection), 37 (64.9%) underwent laparoscopic surgery (31 partial pericystectomy, 4 total pericystectomy, and 2 liver resection), and 6 (10.5%) underwent robotic surgery (6 partial pericystectomy). There were no significant differences between the conventional surgery and minimally invasive groups in terms of patient age, gender, cyst size, or number. However, laparotomy was associated with a higher number of total pericystectomy and liver resection procedures compared to the minimally invasive approach (P = 0.010). Nonetheless, the operation time and blood loss were comparable between both groups. Perioperative complications occurred in 19 (33.3%) patients, with 16 (84%) experiencing minor issues. Bile leak occurred in 8 (14%) patients, resolving spontaneously in 5 patients. There was no significant difference (P = 0.314) in the incidence of complications between the two groups. Conventional surgery, however, was associated with a significantly longer hospital stay (P = 0.034). During follow-up, there were no cases of mortality or cyst recurrence in our cohort.

Conclusion

Minimally invasive approaches for hydatid liver cysts offer advantages such as shorter hospitalization and potentially quicker recovery, making them valuable treatment options when accompanied by careful patient selection and adherence to proper surgical techniques.
Swin-LBP: a competitive feature engineering model for urine sediment classification
Authors: Erten Mehmet , Barua Prabal Datta , Tuncer Ilknur , Dogan Sengul , Baygin Mehmet , Tuncer Turker , Tan Ru-San , Acharya U. Rajendra
Published: August 2023

Automated urine sediment analysis has become an essential part of diagnosing, monitoring, and treating various diseases that affect the urinary tract and kidneys. However, manual analysis of urine sediment is time-consuming and prone to human bias, and hence there is a need for an automated urine sediment analysis systems using machine learning algorithms. In this work, we propose Swin-LBP, a handcrafted urine sediment classification model using the Swin transformer architecture and local binary pattern (LBP) technique to achieve high classification performance. The Swin-LBP model comprises five phases: preprocessing of input images using shifted windows-based patch division, six-layered LBP-based feature extraction, neighborhood component analysis-based feature selection, support vector machine-based calculation of six predicted vectors, and mode function-based majority voting of the six predicted vectors to generate four additional voted vectors. Our newly reconstructed urine sediment image dataset, consisting of 7 distinct classes, was utilized for training and testing our model. Our proposed model has several advantages over existing automated urinalysis systems. Firstly, we used a feature engineering model that enables high classification performance with linear complexity. This means that it can provide accurate results quickly and efficiently, making it an attractive alternative to time-consuming and biased manual urine sediment analysis. Additionally, our model outperformed existing deep learning models developed on the same source urine sediment image dataset, indicating its superiority in urine sediment classification. Our model achieved 92.60% accuracy for 7-class urine sediment classification, with an average precision of 92.05%. These results demonstrate that the proposed Swin-LBP model can provide a reliable and efficient solution for the diagnosis, surveillance, and therapeutic monitoring of various diseases affecting the kidneys and urinary tract. The proposed model's accuracy, speed, and efficiency make it an attractive option for clinical laboratories and healthcare facilities. In conclusion, the Swin-LBP model has the potential to revolutionize urine sediment analysis and improve patient outcomes in the diagnosis and treatment of urinary tract and kidney diseases.
Effect of inorganic fillers on the light transmission through traditional or flowable resin-matrix composites for restorative dentistry
Authors: Fidalgo-Pereira Rita , Carvalho Óscar , Catarino Susana O. , Henriques Bruno , Torres Orlanda , Braem Annabel , Souza Júlio C. M.
Published: August 2023

Objectives

The aim of this in vitro study was to evaluate the light transmission through five different resin-matrix composites regarding the inorganic filler content.

Methods

Resin-matrix composite disc-shaped specimens were prepared on glass molds. Three traditional resin-matrix composites contained inorganic fillers at 74, 80, and 89 wt. % while two flowable composites revealed 60 and 62.5 wt. % inorganic fillers. Light transmission through the resin-matrix composites was assessed using a spectrophotometer with an integrated monochromator before and after light curing for 10, 20, or 40s. Elastic modulus and nanohardness were evaluated through nanoindentation’s tests, while Vicker’s hardness was measured by micro-hardness assessment. Chemical analyses were performed by FTIR and EDS, while microstructural analysis was conducted by optical microscopy and scanning electron microscopy. Data were evaluated using two-way ANOVA and Tukey’s test (p < 0.05).

Results

After polymerization, optical transmittance increased for all specimens above 650-nm wavelength irradiation since higher light exposure time leads to increased light transmittance. At 20- or 40-s irradiation, similar light transmittance was recorded for resin composites with 60, 62, 74, or 78–80 wt. % inorganic fillers. The lowest light transmittance was recorded for a resin-matrix composite reinforced with 89 wt. % inorganic fillers. Thus, the size of inorganic fillers ranged from nano- up to micro-scale dimensions and the high content of micro-scale inorganic particles can change the light pathway and decrease the light transmittance through the materials. At 850-nm wavelength, the average ratio between polymerized and non-polymerized specimens increased by 1.6 times for the resin composite with 89 wt. % fillers, while the composites with 60 wt. % fillers revealed an increased ratio by 3.5 times higher than that recorded at 600-nm wavelength. High mean values of elastic modulus, nano-hardness, and micro-hardness were recorded for the resin-matrix composites with the highest inorganic content.

Conclusions

A high content of inorganic fillers at 89 wt.% decreased the light transmission through resin-matrix composites. However, certain types of fillers do not interfere on the light transmission, maintaining an optimal polymerization and the physical properties of the resin-matrix composites.

Clinical significance

The type and content of inorganic fillers in the chemical composition of resin-matrix composites do affect their polymerization mode. As a consequence, the clinical performance of resin-matrix composites can be compromised, leading to variable physical properties and degradation.

Graphical Abstract
Insights on the internal dynamics of bi-disperse granular flows from machine learning
Authors: Laudari Sudip , Marks Benjy , Rognon Pierre
Published: August 2023

In granular flows, grains exhibit heterogeneous dynamics featuring large distributions of forces and velocities. Conventional statistical methods have previously revealed how these dynamical properties scale with the grain size in monodisperse flows. We explore here whether they differ between small and large grains in bi-disperse flows. In simulated silo flows comprised of dense and collisional zones, we use a machine learning classifier to attempt to distinguish small from large grains based on features such as velocity, acceleration and force. Results show that a classification based on grain velocity is not possible, which suggests that large and small grains feature statistically similar velocities. In the dense zones, classification based on force only fails too, indicating that small and large grains are subjected to similar forces. However, classification based on force and acceleration succeeds. This indicates that the classifier is sensitive to the correlation between forces and acceleration, i.e. Newton’s second law, and can thus detect differences in grain size via their mass. These results highlight the potential for machine learning to assist with better understanding the behaviour of granular flows and similar disordered fluids.
Use of major ion chemistry and trace and rare earth elements to characterize hydraulic relations, mixing processes and water–rock interaction in the Dong Van karst aquifer system, Northern Vietnam
Authors: Tran Diep Anh , Goeppert Nadine , Goldscheider Nico
Published: August 2023

The effectiveness of using a groundwater geochemistry approach in karst hydrogeologic research is highlighted. In particular, this approach is useful for preliminary investigations, such as for the study described here on the Dong Van karst aquifer system in Northern Vietnam. Analyses of different groundwater chemistry parameters complement each other, to clarify hydrochemical processes that are occurring in the karst system. The results of this study show that major ion composition can be used to clarify water chemistry signatures, as well as to identify the mixing processes and water–rock interactions in aquifers. Meanwhile, trace element concentrations and rare earth element patterns can be used as potential natural tracers when some processes are not revealed through conventional hydrochemical methods. These natural tracers can also be used to identify contaminant sources and/or contaminant transport pathways in karst aquifers. Viewed holistically, the groundwater geochemistry approach provides scientific information to establish a basic hydrogeological conceptual model and to estimate the water balance, which has implications for water resources protection and management in karstic systems.
Fractional CO2 laser versus 1064-nm long-pulsed Nd:YAG laser for inflammatory acne vulgaris treatment: a randomized clinical trial
Authors: Hammoda Tasneem Muhammad , Ahmed Naglaa Abdallah , Hamdino Mervat
Published: August 2023

Acne vulgaris is challenging to treat for several individuals. Laser therapy may be a desirable alternative to traditional therapies with limited success. This study aimed to assess efficacy of fractional CO2 laser versus Nd:YAG laser for acne vulgaris therapy. Thirty cases with acne vulgaris underwent both fractional CO2 laser and Nd: YAG laser treatments in a randomized split face design at a 14-day interval for four sessions. The clinical efficacy was evaluated by counting acne lesions and utilizing the Global Acne Severity Scale (GEA Scale). GEAs decreased significantly after both fractional CO2 and Nd:YAG modalities after treatment and at a 3-month follow-up; fractional CO2 demonstrated significant more decrease in GEAs with (P = 0.006, 0.00 (respectively. Moreover, fractional CO2 showed a significantly higher satisfaction level (P = 0.004) and a better clinical improvement percentage regarding inflammatory and noninflammatory acne lesions (P = 0.007 and 0.000, respectively) after 3 months of follow-up. Apart from transient erythema, there were insignificant adverse effects concerning both treated sides. Fractional CO2 and Nd:YAG lasers are efficient physical modalities of acne treatment. However, fractional CO2 laser was more effective and more satisfying to the patients.
A Drinfeld-Type Presentation of the Orthosymplectic Yangians
Authors: Molev A. I.
Published: August 2023

We use the Gauss decomposition of the generator matrix in the R-matrix presentation of the Yangian for the orthosymplectic Lie superalgebra $$\mathfrak {osp}_{N|2m}$$

osp

N
|
2
m

to produce its Drinfeld-type presentation. The results rely on a super-version of the embedding theorem which allows one to identify a subalgebra in the R-matrix presentation which is isomorphic to the Yangian associated with $$\mathfrak {osp}_{N|2m-2}$$

osp

N
|
2
m
-
2

.
Drug Death-Bereaved Parents’ Perspectives on Family Interactions and Help Needs: A Qualitative Study
Authors: Kalsås Øyvind R. , Dyregrov Kari , Fadnes Lars Thore , Lindeman Sari Kaarina , Titlestad Kristine B.
Published: August 2023

Family relations are essential for the bereaved in terms of healing and adjusting to life, especially after experiencing a traumatic death. Although 500 000 people die in drug-related deaths each year, few works focus on family interactions and the help needs of those bereaved by such losses. In this qualitative study, we interviewed 14 parents who had lost their child through a drug-related death. Through a reflexive thematic analysis, we generated three themes: (I) considerable needs in the family become our responsibility, capturing how parents try to mend the disrupted family system and provide adequate care for those who struggle after death, (II) conversations that are important for family connections are obstructed, encompassing how family members sometimes seem afraid of grief emotions and try to protect each other by not talking, and (III) as parents, we can strengthen family connections, encapsulating how parents create space to talk and listen to each other in the family and navigate relational challenges in maintaining relationships. The findings are discussed through the Dual Process Model of Coping with Bereavement as well as family resilience theory. Based on the results, we propose that professional family-oriented help efforts for drug death-bereaved families in two main domains should be considered. The first includes those related to the family’s need and ability to adapt roles and relationships to the new reality, and the second involves those connected to creating a space and environment for emotional sharing and joint meaning-making processes in the family.
Detail Feature Inpainting of Art Images in Online Educational Videos based on Double Discrimination Network
Authors: Xue Feng , Połap Dawid
Published: August 2023

In order to improve the image detail restoration effect of online education videos and improve the quality of online education images, a method for image detail restoration of online education videos based on dual discriminant networks is proposed. Utilize the grayscale changes in the selected spatial domain to enhance the detailed features of the original video art image, and construct a dual discriminant generative adversarial network model to repair the enhanced image details. Using a U-Net structured generation network to generate images similar to detail regions, and using image detail features as input, the initial image restoration is completed by training the generation network. Improve the authenticity and consistency of output image details through global and local discriminant networks. The experimental results show that this method has a good image enhancement effect in restoring image detail features in online education video art, improving the dynamic range and grayscale contrast of the image, and has a significant effect on image detail repair. The average peak signal-to-noise ratio of this method is 30.108, and the average structural similarity is 0.961, proving that the repair effect of this method is good. The average PSNR of this method under Gaussian noise interference is 29.68, which proves the robustness of this method.
Detection of preexisting quantum entanglements between dipole–photon discrete observables
Authors: Porcelli Elio B. , Alves Omar R. , Filho Victo S.
Published: August 2023

We performed measurements of laser beam power polarized in different angles as 0$$^\circ $$

∘

, 45$$^\circ $$

∘

and 90$$^\circ $$

∘

passing close to a symmetric shielded capacitor with parallel plates and through a polaroid filter configured with angles as 0$$^\circ $$

∘

, 45$$^\circ $$

∘

and 90$$^\circ $$

∘

. An unusual light power variation was detected during the charging and discharging of the high voltage capacitor even considering the suppression of known electromagnetic interaction between laser beam and capacitor. The light power variation curves also indicated a typical pattern of charge and discharge of capacitors. The combination of the angles of the laser beam polarization and polaroid filter surprisingly indicated the measurement of correlations between the polarizations of photons and electric dipoles of the capacitor dielectric. These novel results can only be explained supposing the preexisting condition of quantum entanglements between discrete observables of electric dipoles and photons.
Is the One-Compartment Model with First Order Absorption a Useful Approximation?
Authors: Weiss Michael
Published: August 2023

Purpose

The one-compartment model with first order absorption (ka1C) has been extensively used to fit oral data. But when the disposition parameters of the drug are not available, the bias in the parameter estimates remains unclear. In this paper, the effect of potential misspecification of the area under the curve (AUC) and the mean absorption time (MAT) was evaluated for three relatively slowly absorbed drugs/formulations.

Methods

Assuming a three-compartment disposition model with an input (absorption) rate described as a sum of two inverse Gaussian functions (2IG3C) as the true model, the deviations of AUC and MAT estimated with simpler models were analyzed. Simpler models, as the ka1C model (Bateman function), the one-compartment model with IG input function (IG1C) and the gamma density function were fitted to the oral data alone, and compared to the fits obtained with the 2IG3C model which also uses the 3C disposition parameters of the drug. Data from pharmacokinetic studies of trospium, propiverine and ketamine in healthy volunteers were analyzed using a population approach.

Results

The Bateman function (ka1C) allowed a robust estimation of the population mean AUC, but the individual estimates were highly biased. It failed in evaluating MAT. The simple alternative models did not improve the situation.

Conclusions

The Bateman function appears to be useful for estimating the population mean value of AUC after oral administration. The results reemphasize the fact that insight into the absorption process can be only gained when also intravenous reference data are available.
Defamiliarization in advancing a decolonial approach to global citizenship education
Authors: Waghid Zayd , Meda Lawrence
Published: August 2023

The purpose of this article is to investigate whether defamiliarization used in schools by some preservice teachers during their teaching practice can be considered an appropriate decolonizing pedagogical practice for advancing global citizenship education (GCE). The research used a case study design, with data collected in the form of reflection essays from 11 preservice teachers during their teaching practice period. The findings indicate that the specific defamiliarization practice used by these teachers aided both them and their students, through a reflective and collaborative process, in recognizing and critiquing the hierarchical knowledge paradigm in the current school curriculum and consciously resisting epistemic violence. The defamiliarization practice increased participants’ self-reflexivity and served as a pedagogy of dissensus. This is a novel study in that it accounts for the perceived benefits of defamiliarization in advancing certain aspects of critical GCE from the Global South.
Reviewing and improving spatiotemporal modeling approaches for mackerel’s total annual egg production
Authors: Núñez-Riboni Ismael , Costas Gersom , Diekmann Rabea , Ulleweit Jens , Kloppmann Matthias
Published: August 2023

Since the late 1970s the international ICES mackerel egg survey takes place in the Northeast Atlantic to obtain an estimate of total annual egg production (TAEP), to assess the spawning stock biomass and to support the sustainable management of the mackerel stock. However, its standard calculation of TAEP has some shortcomings: egg production is estimated from arithmetic averages of individual observations regardless whether they are extreme, rarely observed values, and has shown difficulties coping with the spatial expansion of mackerel spawning observed since 2007 (increasing the number of interpolated estimates). Various previous modeling efforts attempted to map the habitat of spawning mackerel to obtain more accurate egg production estimates by using generalized additive models (GAMs). In this study, we review and improve these models by introducing new features: We model both the western and southern components of the mackerel stock with a Tweedie distribution and test more than 400 model forms, including new predictors (like population size) and complex covariate interactions. We select the best model with various metrics, including the score of a tenfold cross validation. Our results show that environmental variables should be included in the model as simple functional, unimodal terms. This leads to a model that is more similar to a generalized linear mixed model than the typical GAM with smoothers. Models including only smoothers performed worse as they have a poor skill to extrapolate beyond the sampled region. Additionally, accounting for the effect of population size on the spatial distribution of eggs was shown to be fundamental to better model performance.

Graphical abstract
Paradoxes and paradigms: elements and compounds: similar names, very different energetics. Part 5, selected examples of exotic species and isotopes (H, He, C, F, U)
Authors: Ponikvar‑Svet Maja , Edwards Kathleen Frances , Liebman Joel Fredric
Published: August 2023

In this paper we continue to review the phonetic similarity of trivial names of chemical substances, in the particular, the names of isotopes of selected elements (H, He, C, F, U) of the periodic table. Thermochemical properties are explicitly considered.
Methane and CO2 production in the wetland Lake Podpeč (Slovenia)
Authors: Ogrinc Nives , Šegedin Urban , Faganeli Jadran
Published: August 2023

Purpose

This study deals with the identification of CH4 and CO2 sources in the high-carbonate wetland Lake Podpeč in the Ljubljana Marshes, Slovenia.

Materials and methods

Lake Podpeč is situated on the periphery of the Ljubljana Marshes in central Slovenia. A combination of chemical analysis and natural abundance analysis of stable carbon and hydrogen isotopes of CH4, along with analysis of dissolved inorganic carbon (DIC), was employed in an incubation experiment.

Results and discussion

The isotopic composition of dissolved inorganic carbon (δ13CDIC) suggests three main processes occurring during incubation: oxic degradation of organic matter (OM), anoxic OM degradation, and methanogenesis. During oxic degradation of OM, the δ13CDIC values slightly decrease from − 13.2 to − 14.5‰. However, after 50 days, the δ13CDIC values started to increase, reaching − 12.2‰ by the end of the experiment. 13C enrichment coincided with the formation of CH4, which began to increase simultaneously. The CH4 produced had an average δ13CCH4 value of − 67 ± 1‰ and δ2HCH4 value of − 389 ± 3‰, suggesting that CH4 is formed through acetate fermentation. The contribution of calcite dissolution to DIC increased during the degradation of OM by 53%. However, during methanogenesis, there was no significant change in the concentrations of Ca, and the estimated contribution to DIC was only 3%.

Conclusions

This study enhances our understanding of methane production in wetland Lake Podpeč and its relevance in the context of other high-carbonate lakes. The findings offer insights into the complex interactions between OM degradation, methane production pathways, and carbonate dissolution, which has implications for the global carbon cycle and greenhouse gas emissions.
The Role of Affective Empathy in Eliminating Discrimination Against Women: a Conceptual Proposition
Authors: Guthridge Michaela , Penovic Tania , Kirkman Maggie , Giummarra Melita J.
Published: August 2023

Due to its wide-ranging reservations and lack of effective enforcement mechanisms the Convention on the Elimination of All Forms of Discrimination Against Women (CEDAW) has failed to dismantle widespread and systemic discrimination. The present paper proposes a broad, theoretical, preventive and relational approach to creating and enhancing the effectiveness of novel interventions to accelerate gender equality. We describe the main elements of affective empathy (i.e. intersubjectivity, multisensory engagement and empathic embodiment) and identify potential interventions that build on those elements to advance gender equality. We ultimately argue that increased empathy towards women, transwomen and girls is required to disrupt the beliefs and behaviours that lead to discrimination, and that these changes must be enacted alongside legislative reforms and community education that construct equality environments. Our affective empathy framework could have the capacity to operationalise the normative fight against gender stereotypes and inequality in line with article 5(a) of CEDAW.
Nasopharyngeal carcinoma
Authors: Fuereder Thorsten
Published: August 2023

The incidence of nasopharyngeal carcinoma (NPC) shows geographically differences between certain parts of Asia and the rest of the world. While NPC is an orphan disease in Western Europe/United States of America, it is endemic to southern China, southeast Asia and northern Africa. NPC is a radio- and chemotherapy sensitive malignancy. Although it is essential to follow the evidence-based treatment recommendations outlined in the international guidelines, it has to be emphasized that the field is rapidly involving and relevant data gaps such as the optimal treatment strategy for stage II disease, non-Epstein Barr Virus associated NPC or the role of immunotherapy in low incidence areas exist. These topics will be addressed in this article. Most importantly, interdisciplinary management of NPC patients is key for the optimal management at all disease stages.
Neutrophil-Enriched Biomarkers and Long-Term Prognosis in Acute Coronary Syndrome: a Systematic Review and Meta-analysis
Authors: Yiu Jaquelina Y. T. , Hally Kathryn E. , Larsen Peter D. , Holley Ana S.
Published: August 2023

Activated neutrophils release a range of inflammatory products that represent potential biomarkers, and there is interest in the prognostic value of these in acute coronary syndrome (ACS) patients. We conducted a systematic review to examine neutrophil-enriched biomarkers and the occurrence of major adverse cardiovascular events (MACE) in patients with ACS. We identified twenty-seven studies including 17,831 patients with ACS. The most studied biomarkers were neutrophil gelatinase-associated lipocalin (NGAL) and myeloperoxidase (MPO). Meta-analyses showed that elevated NGAL was associated with higher MACE rates (unadjusted risk ratio (RR) 1.52, 95% CI 1.12–2.06, p = 0.006) as were elevated MPO levels (unadjusted RR 1.61, 95% CI 1.22–2.13, p = 0.01). There was limited data suggesting that increased levels of calprotectin, proteinase-3 and double-stranded DNA were also associated with MACE. These results suggest that higher levels of neutrophil-enriched biomarkers may be predictive of MACE in patients with ACS, although higher-quality studies are needed to confirm these observations.

Graphical abstract
Impact of stenosis resistance and coronary flow capacity on fractional flow reserve and instantaneous wave-free ratio discordance: a combined analysis of DEFINE-FLOW and IDEAL
Authors: Stegehuis Valérie , Boerhout Coen , Kikuta Yuetsu , Cambero-Madera Maribel , van Royen Niels , Matsuo Hitoshi , Nakayama Masafumi , de Waard Guus , Knaapen Paul , Nijjer Sukhjinder , Petraco Ricardo , Siebes Maria , Davies Justin , Escaned Javier , van de Hoef Tim , Piek Jan
Published: August 2023

Background

The pressure-derived parameters fractional flow reserve (FFR) and the emerging instantaneous wave-free ratio (iFR) are the most widely applied invasive coronary physiology indices to guide revascularisation. However, approximately 15–20% of intermediate stenoses show discordant FFR and iFR, and therapeutical consensus is lacking.

Aims

We sought to associate hyperaemic stenosis resistance index, coronary flow reserve (CFR) and coronary flow capacity (CFC) to FFR/iFR discordance.

Methods

We assessed pressure and flow measurements of 647 intermediate lesions (593 patients) of two multi-centre international studies.

Results

FFR and iFR were discordant in 15% of all lesions (97 out of 647). FFR+/iFR− lesions had similar hyperaemic average peak velocity (hAPV), CFR and CFC as FFR−/iFR− lesions, whereas FFR−/iFR+ lesions had similar hAPV, CFR and CFC as FFR+/iFR+ lesions (p > 0.05 for all). FFR+/iFR− lesions were associated with lower baseline stenosis resistance, but not hyperaemic stenosis resistance, compared with FFR−/iFR+ lesions (p < 0.001).

Conclusions

Discordance with FFR+/iFR− is characterised by maximal flow values, CFR, and CFC patterns similar to FFR−/iFR− concordance that justifies conservative therapy. Discordance with FFR−/iFR+ on the other hand, is characterised by low flow values, CFR, and CFC patterns similar to iFR+/FFR+ concordance that may benefit from percutaneous coronary intervention.
Role of Regulatory Sandboxes and MLOps for AI-Enabled Public Sector Services
Authors: Gonzalez Torres Ana Paula , Sawhney Nitin
Published: August 2023

This paper discusses how innovations in public sector AI-based services must comply with the Artificial Intelligence Act (AI Act) regulatory frameworks while enabling experimentation and participation of diverse stakeholders throughout the Artificial Intelligence (AI) lifecycle. The paper examines the implications of the emerging regulation, AI regulatory sandboxes and Machine Learning Operations (MLOps) as tools that facilitate compliance while enabling co-learning and active participation of multiple stakeholders. We propose a framework that fosters experimentation with automation pipelines and continuous monitoring for the deployment of future public sector AI-based services in a regulatory-compliant and technically innovative manner. AI regulatory sandboxes can be beneficial as a space for contained experimentation that goes beyond regulatory considerations to specific experimentation with the implementation of ML frameworks. While the paper presents a framework based on emerging regulations, tools and practices pertaining to the responsible use of AI, this must be validated through pilot experimentation with public and private stakeholders and regulators in different areas of high-risk AI-based services.
The ISAC Paradigm to Tame Oral Cancer in Saudi Arabia: A Quasi-experimental Study
Authors: Jafer Mohammed , Moafa Ibtisam , Hoving Ciska , Candel Math , Kaabi Abdulrahman A. , Van Den Borne Bart
Published: August 2023

Late detection of oral cancer (OC) cases in Saudi Arabia is concerning. It reduces survival rate and complicates treatment. The ISAC intervention was developed to bridge the gaps observed in dentists’ practice of OC examination and patient education. The ISAC stands for I, informing patients of OC screenings; S, screening for OC; A, advising high-risk patients to quit risk factors; and C, connecting patients to advanced services. This study tested the potential effect of the ISAC in influencing dentists’ cognitive and behavioral skills, to enhance early detection and prevention of OC. A quasi-experimental study was conducted among dental interns (DIs) at dental setting to test the effect on comprehensive oral cancer examination score (COCE), awareness, self-efficacy, descriptive-norms, and self-reported behavior. Data were collected through triangulation of methods pre and post the intervention at two-months. Multiple linear mixed effects regression models were utilized for data analysis. Between October 2020 and April 2021, 47 DIs participated in the study. The final model showed the significant effects of time (ISAC) on COCE (95% CI = 25.12–29.42, P < .001). DIs had a significant improvement in awareness, self-efficacy, descriptive norms, and self-reported behavior. The findings showed promising effects of the intervention toward the early detection and prevention of OC. Dentists, dental organizations, and policymakers in areas with a high risk of OC could benefit from the current intervention which contributes to capacity building and improved community health. A pragmatic study with a robust design is needed to test the effectiveness of the intervention on a wider scale.
Differentiation of Chemical Components in Basaltic Melts During Eruptions: An Example from Tolbachik–Hawaiian Fissure Zones and Etna Vent
Authors: Gembitskaya Irina Mikhailovna , Pharoe Benedict Kinshasa
Published: August 2023

The study on differentiation of chemical components in quenched volcanics from the Etna, Tolbachik and Hawaiian fissure zones was carried out under simulated temperature/pressure (T/P) conditions reflecting real-time conditions in the early stages of magmatic eruptions. The simulation was performed under high-pressure chamber apparatus, and the rocks were then subjected to high T/P conditions resulting in basaltic melts. Various temperature and pressure conditions were adjusted from the apparatus to allow for different rates of magmatic cooling and crystallization. The scanning electron microscopy (SEM) coupled with energy-dispersive spectroscopy (EDS-microanalysis) was then used to study the quenched glasses with the aim of identifying major element partitioning based on micro-heterogeneity of melts structures. The microscopic study of the experimental melts and their comparisons with natural melts under the electron microscopes indicate the existence of two distinct liquids which fractionated during cooling on the basis of their chemical composition (compositional melts): Fe, Mg liquids concentrated in the poorly polymerized and mobile parts of the melt and K, Na and Al liquids were concentrated in more highly polymerized parts of the melts. Partitioning of Ca and Si appears to be changeable and more dependent on bulk melt composition. Fractionation of non-crystalline melts was evident under post-explosion sharp quenching and high-pressure conditions.
A Systematic and Quality Review of Augmentative and Alternative Communication Interventions that use Core Vocabulary
Authors: Carnett Amarie , Devine Bailey , Ingvarsson Einar , Esch Barbara
Published: August 2023

Core vocabulary is defined as “lexical items that are accepted as being central and indispensable to language use” (Bell, 2012, p. 1). Use of core vocabulary is common amongst professionals who teach augmentative and alternative communication (AAC) to individuals with disabilities. Although the use of AAC is often classified as an evidence-based practice (EBP) (Steinbrenner et al., 2020; Wong et al., Journal of Autism and Developmental Disorders, 45(7), 1951–1966, 2015) an analysis of the relevant intervention procedures as well as the vocabulary used is often missing from syntheses of the literature. Therefore, a systematic review was conducted to determine the quality and strength of the evidence for AAC interventions that use core vocabulary. A systematic database search and a subsequent screening process resulted in a total of 10 peer-reviewed studies that involved an AAC intervention that used core vocabulary. Each study’s outcomes were then categorized as positive, mixed, or negative and a quality review was performed using the Council for Exceptional Children’s (CEC) standards for evidence-based practices (Cook et al., Teaching Exceptional Children, 46(6), 206-212, 2015a; Remedial and Special Education, 36, 220-234, 2015b). Overall, the results suggest a lack of strong evidence in favor of AAC interventions that use core vocabulary. The results are discussed in the context of general suggestions for vocabulary selection and teaching practices for AAC systems.
Quantitative Analysis of Group for Epidemiology Architectural Approach
Authors: Mathebula Dephney
Published: August 2023

Epidemiology, the aspect of research focusing on disease modelling is date intensive. Research epidemiologists in different research groups played a key role in developing different data driven model for COVID-19 and monkeypox. The requirement of accessing highly accurate data useful for disease modelling is beneficial but not without having challenges. Currently, the task of data acquisition is executed by select individuals in different research groups. This approach experiences the drawbacks associated with getting permission to access the desired data and inflexibility to change data acquisition goals due to dynamic epidemiological research objectives. The presented research addresses these challenges and proposes the design and use of dynamic intelligent crawlers for acquiring epidemiological data related to a given goal. In addition, the research aims to quantify how the use of computing entities enhances the process of data acquisition in epidemiological related studies. This is done by formulating and investigating the metrics of the data acquisition efficiency and the data analytics efficiency. The use of human assisted crawlers in the global information networks is found to enhance data acquisition efficiency (DAqE) and data analytics efficiency (DAnE). The use of human assisted crawlers in a hybrid configuration outperforms the case where manual research group member efforts are expended enhancing the DAqE and DAnE by up to 35% and 99% on average, respectively.