bluuebunny/crossref_metadata_2025_split huggingface dataset:
Metabolomics targets tissue-specific responses in alleviating the negative effects of salinity in tef (Eragrostis tef) during germination
Authors: Haddadi Bahareh Sadat , Fang Rui , Girija Aiswarya , Kattupalli Divya , Widdowson Emma , Beckmann Manfred , Yadav Rattan , Mur Luis A. J. 
Published: August 2023

Abstract
Main conclusion
Salinity induced metabolite responses resulted in differential accumulation of flavonoids and antioxidant metabolites in shoots and roots suggesting improved antioxidant capacity in providing salt-adaptive phenotype of tef seedling.

Abstract
Tef [(Eragrostis tef) (Zucc.) Trotter] is an important ‘cash crop’ of Ethiopia grown mainly for human food, and development of elite tef cultivars with better performance is vital to Ethiopian farmers and breeders. Soil salinity is one of the key constraints that affects tef yield in the Ethiopian lowlands and Rift valley where cultivation of tef is limited. Being a minor crop, the responses of tef towards salinity is unknown. Salinity involves physiological and metabolite reprogramming that can have major impact on germination and seedling establishment. Here we evaluate the in vitro effect of NaCl on tef germination and associate this with metabolomic approaches to suggest salt tolerance mechanisms. In this study, 19 tef varieties were screened for NaCl tolerance and were investigated using untargeted metabolomics. Screened tef varieties showed differential germination rates with NaCl treatment varying from < 20 to 100%. Viable seedlings exposed to NaCl exhibited purple-red pigment accumulation in the roots except for Beten and Tullu nasy varieties. Metabolite comparisons between shoots and roots showed significant differences and, in particular, roots of salt tolerant tef varieties accumulated flavonoid derivatives as well as sugars and cell wall associated metabolites. These metabolic changes were correlated with patterns of antioxidant capacities and total flavonoid content in shoots and roots and suggested a mitigating response by tef to salinity. Our study highlights the role of flavonoid accumulation following salt stress on tef seedlings and further these findings could be used as targets for selective tef breeding.
The role of environmental contextual cues in sequence learning: evidence from a virtual maze context
Authors: Koch Iring , Bock Otmar 
Published: August 2023

AbstractStudies on sequence learning usually focus on single, isolated stimuli that are presented sequentially. For example, in the serial reaction time (RT) task, stimuli are either presented in a predictable sequence or in a random sequence, and better performance with the predictable sequence is taken as evidence for sequence-specific learning. Yet, little is known about the role of environmental context cues in sequence learning. If the target stimuli are embedded in a meaningful context, would this facilitate learning by providing helpful contextual associations or would it hinder learning by adding distracting stimuli? This question was examined in two studies. A pilot study compared sequence learning in a virtual maze with a horizontal vs. vertical maze context, in which arrow stimuli guide spatial lever movement responses that resulted in a corresponding virtual transport on the screen. The results showed only overall somewhat better performance with the vertical maze compared to the horizontal maze, but general practice effects and sequence-specific learning effects were the same for both contexts. The main study compared sequence learning with a maze context to sequence learning of arrows without a maze context. The results showed significantly better learning with maze context than without context. These data suggest that the maze context facilitated sequence learning by inducing a meaningful spatial representation (“mental map”) similar to that formed in wayfinding.
Kawasaki disease, multisystem inflammatory syndrome in children, and adenoviral infection: a scoring system to guide differential diagnosis
Authors: Fabi Marianna , Dondi Arianna , Andreozzi Laura , Frazzoni Leonardo , Biserni Giovanni Battista , Ghiazza Francesco , Dajti Elton , Zagari Rocco Maurizio , Lanari Marcello 
Published: August 2023

AbstractChildren with Kawasaki disease (KD), Multisystem Inflammatory Syndrome in Children (MIS-C), and Adenovirus infections (AI) of the upper respiratory tract show overlapping features. This study aims to develop a scoring system based on clinical or laboratory parameters to differentiate KD or MIS-C from AI patients. Ninety pediatric patients diagnosed with KD (n = 30), MIS-C (n = 26), and AI (n = 34) admitted to the Pediatric Emergency Unit of S.Orsola University Hospital in Bologna, Italy, from April 2018 to December 2021 were enrolled. Demographic, clinical, and laboratory data were recorded. A multivariable logistic regression analysis was performed, and a scoring system was subsequently developed. A simple model (clinical score), including five clinical parameters, and a complex model (clinic-lab score), resulting from the addition of one laboratory parameter, were developed and yielded 100% sensitivity and 80% specificity with a score ≥2 and 98.3% sensitivity and 83.3% specificity with a score ≥3, respectively, for MIS-C and KD diagnosis, as compared to AI. Conclusion: This scoring system, intended for both outpatients and inpatients, might limit overtesting, contribute to a more effective use of resources, and help the clinician not underestimate the true risk of KD or MIS-C among patients with an incidental Adenovirus detection.

What is Known:• Kawasaki Disease (KD), Multisystem Inflammatory Syndrome in Children (MIS-C) and adenoviral infections share overlapping clinical presentation in persistently febrile children, making differential diagnosis challenging.• Scoring systems have been developed to identify high-risk KD patients and discriminate KD from MIS-C patients.

What is New:• This is the first scoring model based on clinical criteria to distinguish adenoviral infection from KD and MIS-C.• The score might be used by general pediatricians before referring febrile children to the emergency department.
Braced Triangulations and Rigidity
Authors: Cruickshank James , Kastis Eleftherios , Kitson Derek , Schulze Bernd 
Published: August 2023

AbstractWe consider the problem of finding an inductive construction, based on vertex splitting, of triangulated spheres with a fixed number of additional edges (braces). We show that for any positive integer b there is such an inductive construction of triangulations with b braces, having finitely many base graphs. In particular we establish a bound for the maximum size of a base graph with b braces that is linear in b. In the case that $$b=1$$

b
=
1

or 2 we determine the list of base graphs explicitly. Using these results we show that doubly braced triangulations are (generically) minimally rigid in two distinct geometric contexts arising from a hypercylinder in $$\mathbb {R}^4$$

R

4

and a class of mixed norms on $$\mathbb {R}^3$$

R

3

.
Concerns and coping mechanisms of breast cancer survivor women from Asia: a scoping review
Authors: Sarang Bhakti , Bhandarkar Prashant , Parsekar Shradha S. , Patil Priti , Venghateri Jubina Balan , Ghoshal Rakhi , Veetil Deepa Kizhakke , Shah Priyansh , Gadgil Anita , Roy Nobhojit 
Published: August 2023

Abstract
Purpose
The incidence of breast cancer has increased significantly in Asia due to epidemiological transition and changes in human development indices. Advancement in medical technology has improved prognosis with a resultant increase in survivorship issues. The effects of breast cancer diagnosis and treatment are influenced by the patient’s cultural beliefs and social systems. This scoping review aims to summarise concerns and coping mechanisms of women with breast cancer in Asia and understand gaps in the existing literature.

Methods
We performed a scoping review using the population-concept-context strategy. A systematic search of MEDLINE (PubMed, Web of Science), CINAHL, SCOPUS, and Embase was conducted for studies conducted in Asia on women diagnosed with breast cancer, identifying their concerns and coping mechanisms, published between January 2011 and January 2021. Data from included studies were reported using frequencies and percentages.

Results
We included 163 studies, of which most (81%) were conducted in hospital settings. Emotional and psychological concerns were reported in 80% of studies, followed by physical appearance and body-image concerns in 46%. Social support (59%), emotion-based coping (46%), spirituality, and problem-based coping (37%) were the major coping systems documented.

Conclusion
The mapped literature documented that anxiety, depression, and fear of cancer recurrence dominated women’s emotional concerns. Women coped with the help of social support, positive reappraisal, and faith in God and religion. Sensitization of caregivers, including healthcare professionals and family members, to context-specific concerns and inquiry into the patients’ available support systems is essential in strengthening breast cancer women’s recovery and coping.
A novel uncertainty-aware deep learning technique with an application on skin cancer diagnosis
Authors: Shamsi Afshar , Asgharnezhad Hamzeh , Bouchani Ziba , Jahanian Khadijeh , Saberi Morteza , Wang Xianzhi , Razzak Imran , Alizadehsani Roohallah , Mohammadi Arash , Alinejad-Rokny Hamid 
Published: August 2023

AbstractSkin cancer, primarily resulting from the abnormal growth of skin cells, is among the most common cancer types. In recent decades, the incidence of skin cancer cases worldwide has risen significantly (one in every three newly diagnosed cancer cases is a skin cancer). Such an increase can be attributed to changes in our social and lifestyle habits coupled with devastating man-made alterations to the global ecosystem. Despite such a notable increase, diagnosis of skin cancer is still challenging, which becomes critical as its early detection is crucial for increasing the overall survival rate. This calls for advancements of innovative computer-aided systems to assist medical experts with their decision making. In this context, there has been a recent surge of interest in machine learning (ML), in particular, deep neural networks (DNNs), to provide complementary assistance to expert physicians. While DNNs have a high processing capacity far beyond that of human experts, their outputs are deterministic, i.e., providing estimates without prediction confidence. Therefore, it is of paramount importance to develop DNNs with uncertainty-awareness to provide confidence in their predictions. Monte Carlo dropout (MCD) is vastly used for uncertainty quantification; however, MCD suffers from overconfidence and being miss calibrated. In this paper, we use MCD algorithm to develop an uncertainty-aware DNN that assigns high predictive entropy to erroneous predictions and enable the model to optimize the hyper-parameters during training, which leads to more accurate uncertainty quantification. We use two synthetic (two moons and blobs) and a real dataset (skin cancer) to validate our algorithm. Our experiments on these datasets prove effectiveness of our approach in quantifying reliable uncertainty. Our method achieved 85.65 ± 0.18 prediction accuracy, 83.03 ± 0.25 uncertainty accuracy, and 1.93 ± 0.3 expected calibration error outperforming vanilla MCD and MCD with loss enhanced based on predicted entropy.
The evolution Navier–Stokes equations in a cube under Navier boundary conditions: rarefaction and uniqueness of global solutions
Authors: Falocchi Alessio , Gazzola Filippo 
Published: August 2023

AbstractWe study the evolution Navier–Stokes equations in a cube under Navier boundary conditions. For the related stationary Stokes problem, we determine explicitly all the eigenvectors, eigenvalues and the corresponding Weyl asymptotic. We introduce the notion of rarefaction, namely families of eigenvectors that weakly interact with each other through the nonlinearity. By combining the spectral analysis with rarefaction, we expand the solutions in Fourier series, making explicit some of their properties. We then suggest several new points of view in order to explain the striking difference in uniqueness results between 2D and 3D. First, we construct examples of solutions for which the nonlinearity plays a minor role, both in 2D and 3D. Second, we show that, if a solution is rarefied, then its energy is decreasing: hence, rarefaction may be seen as an almost two dimensional assumption. Finally, by exploiting the explicit form of the eigenvectors we provide a numerical explanation of the difficulty in using energy methods for general solutions of the 3D equations.
A novel cognitive neurosurgery approach for supramaximal resection of non-dominant precuneal gliomas: a case report
Authors: Bermúdez Garazi , Quiñones Ileana , Carrasco Alejandro , Gil-Robles Santiago , Amoruso Lucia , Mandonnet Emmanel , Carreiras Manuel , Catalán Gregorio , Pomposo Iñigo 
Published: August 2023

AbstractDespite mounting evidence pointing to the contrary, classical neurosurgery presumes many cerebral regions are non-eloquent, and therefore, their excision is possible and safe. This is the case of the precuneus and posterior cingulate, two interacting hubs engaged during various cognitive functions, including reflective self-awareness; visuospatial and sensorimotor processing; and processing social cues. This inseparable duo ensures the cortico-subcortical connectivity that underlies these processes. An adult presenting a right precuneal low-grade glioma invading the posterior cingulum underwent awake craniotomy with direct electrical stimulation (DES). A supramaximal resection was achieved after locating the superior longitudinal fasciculus II. During surgery, we found sites of positive stimulation for line bisection and mentalizing tests that enabled the identification of surgical corridors and boundaries for lesion resection. When post-processing the intraoperative recordings, we further identified areas that positively responded to DES during the trail-making and mentalizing tests. In addition, a clear worsening of the patient’s self-assessment ability was observed throughout the surgery. An awake cognitive neurosurgery approach allowed supramaximal resection by reaching the cortico-subcortical functional limits. The mapping of complex functions such as social cognition and self-awareness is key to preserving patients’ postoperative cognitive health by maximizing the ability to resect the lesion and surrounding areas.
Voltammetric analysis of biological fluids: quantification of species in urine accounting for non-linear concentration effects
Authors: Doménech-Carbó Antonio , Doménech-Casasús Clara , Ramos David 
Published: August 2023

AbstractVoltammetric sensing of analytes in biological fluids is frequently accompanied by non-linear effects due to the analyte/matrix interactions. A theoretical approach is developed to describe such effects when standard addition methods are applied. Several asymptotic models are described considering equilibrium-like and kinetic-like interaction models and possible co-diffusion effects. Experimental data for non-linear features which appear in voltammetric sensing of serotonin and noradrenalin in urine are in satisfactory agreement with theoretical predictions.
Drivers of shoreline change on Pacific coral reef islands: linking island change to processes
Authors: Sengupta Meghna , Ford Murray R. , Kench Paul S. , Perry George L. W. 
Published: August 2023

AbstractReef islands are considered highly vulnerable to the impacts of anthropogenic climate change. While existing studies provide evidence of high dynamism and predominant stability over recent periods of sea-level rise, efforts to statistically link recorded morphological changes to processes are limited. We analyse shoreline changes across an expansive region of diverse oceanographic and climatic conditions and assess those observations relative to the processes potentially driving change. This record comprises 568 islands from 42 atolls spanning the western to the central Pacific Ocean from the Federated States of Micronesia, Marshall Islands, Kiribati and Tuvalu, and is one of the first robust attempts to statistically attribute the drivers of observed island changes within the past half-century. Our analyses demonstrate that island change and a range of its potential controls, including oceanographic, climatic and local-scale morphometric characteristics of reefs and islands, are not correlated, underscoring that no single variable could predict a uniform response across the study islands. The lack of association between sea-level rise and shoreline change on this large sample of islands addresses the common notion of a linear relationship between rising sea levels and magnitude of erosion in reef island systems. We emphasise the critical need to move from simplistic assessments of island change, highlight the importance of incorporating multiple predictors and the need for more computationally robust models.
Enhancing the prediction for shunt-dependent hydrocephalus after aneurysmal subarachnoid hemorrhage using a machine learning approach
Authors: Frey Dietmar , Hilbert Adam , Früh Anton , Madai Vince Istvan , Kossen Tabea , Kiewitz Julia , Sommerfeld Jenny , Vajkoczy Peter , Unteroberdörster Meike , Zihni Esra , Brune Sophie Charlotte , Wolf Stefan , Dengler Nora Franziska 
Published: August 2023

AbstractEarly and reliable prediction of shunt-dependent hydrocephalus (SDHC) after aneurysmal subarachnoid hemorrhage (aSAH) may decrease the duration of in-hospital stay and reduce the risk of catheter-associated meningitis. Machine learning (ML) may improve predictions of SDHC in comparison to traditional non-ML methods. ML models were trained for CHESS and SDASH and two combined individual feature sets with clinical, radiographic, and laboratory variables. Seven different algorithms were used including three types of generalized linear models (GLM) as well as a tree boosting (CatBoost) algorithm, a Naive Bayes (NB) classifier, and a multilayer perceptron (MLP) artificial neural net. The discrimination of the area under the curve (AUC) was classified (0.7 ≤ AUC < 0.8, acceptable; 0.8 ≤ AUC < 0.9, excellent; AUC ≥ 0.9, outstanding). Of the 292 patients included with aSAH, 28.8% (n = 84) developed SDHC. Non-ML-based prediction of SDHC produced an acceptable performance with AUC values of 0.77 (CHESS) and 0.78 (SDASH). Using combined feature sets with more complex variables included than those incorporated in the scores, the ML models NB and MLP reached excellent performances, with an AUC of 0.80, respectively. After adding the amount of CSF drained within the first 14 days as a late feature to ML-based prediction, excellent performances were reached in the MLP (AUC 0.81), NB (AUC 0.80), and tree boosting model (AUC 0.81). ML models may enable clinicians to reliably predict the risk of SDHC after aSAH based exclusively on admission data. Future ML models may help optimize the management of SDHC in aSAH by avoiding delays in clinical decision-making.
Instrumentation of Sealing Layers Made of Two Different Amendments (Green Liquor Dregs and Bentonite) to Till for Reclamation of Sulfidic Mine Waste
Authors: Nigéus Susanne , Maurice Christian , Lindblom Jenny 
Published: August 2023

AbstractIn Sweden, a dry cover solution is commonly used to stop sulfide oxidation and the production of acid rock drainage from unattended sulfidic mine waste. Recycling a non-hazardous industrial residue, such as green liquor dregs (GLD) generated during pulp production, in this cover solution is beneficial for both the mining industry where there is a great need for cover materials and the pulp production industry. The objectives of this field study were to install and evaluate the instrumentation of sealing layers made of GLD- and bentonite-amended till, and to evaluate the practical aspects of two different methods of installation: monitoring wells and pits. This practical field study demonstrated that it is difficult to properly seal the drill holes after installing the probes in observation wells and suggests that a better (easier and less costly) alternative for future instrument installation in a sealing layer might be to excavate a pit in the protective layer after installation of the soil cover and then drill the probes into the sealing layer from that pit.
Wearable Neuromuscular Electrical Stimulation on Quadriceps Muscle Can Increase Venous Flow
Authors: Flodin Johanna , Wallenius Philip , Guo Li , Persson Nils-Krister , Ackermann Paul 
Published: August 2023

AbstractNeuromuscular electrical stimulation (NMES) of the quadriceps (Q) may increase venous blood flow to reduce the risk of venous thromboembolism. This study assessed whether Q-NMES pants could increase peak venous velocity (PVV) in the femoral vein using Doppler ultrasound and minimize discomfort. On 15 healthy subjects, Q-NMES using textile electrodes integrated in pants was applied with increasing intensity (mA) until the first visible muscle contraction [measurement level (ML)-I] and with an additional increase of six NMES levels (ML II). Discomfort using a numeric rating scale (NRS, 0–10) and PVV were used to assess different NMES parameters: frequency (1, 36, 66 Hz), ramp-up/-down time (RUD) (0, 1 s), plateau time (1.5, 4, and 6 s), and on:off duty cycle (1:1, 1:2, 1:3, 1:4). Q-NMES pants significantly increased PVV from baseline with 93% at ML I and 173% at ML II. Frequencies 36 Hz and 66 Hz and no RUD resulted in significantly higher PVV at both MLs compared to 1 Hz and 1 s RUD, respectively. Plateau time, and duty cycle did not significantly change PVV. Discomfort was only significantly higher with increasing intensity and frequency. Q-NMES pants produces intensity-dependent 2−3-fold increases of venous blood flow with minimal discomfort. The superior NMES parameters were a frequency of 36 Hz, 0 s RUD, and intensity at ML II. Textile-based NMES wearables are promising for non-episodic venous thromboembolism prevention.
Social-Symbolic Work in the Construction of Social Problems: Constructing Gender Inequality in Turkish Social Partnerships
Authors: Karakulak Özgü , Lawrence Thomas B. 
Published: August 2023

AbstractHow social problems are constructed within social partnerships has significant effects on the management, impact, and survival of those partnerships. To explore how social problems are constructed, we adopt a social-symbolic work perspective, which highlights the variety of forms of work involved in this process, how they interact, and the impact of context on that process. Empirically, we focus on two social partnerships in Turkey that both addressed gender inequality but constructed that problem in very different terms. Our study suggests that the differences in how they came to construct the problem of gender inequality in Turkey was tied to the qualities of two forms of social-symbolic work—relational work and practice work—in which they engaged: the partnership that constructed gender inequality as an embedded problem engaged in extensive relational work and deep practice work; in contrast, the partnership that constructed the problem as disembedded engaged in efficient relational work and shallow practice work. Further, we observed that the construction of the problem of gender inequality was tied to different outcomes: an embedded social construction of the problem was associated with holistic outcomes on a more limited scale; a disembedded construction of the problem was associated with simpler outcomes on a greater scale. The paper contributes to the literature on social partnerships by showing how social problems are constructed through partners' work and how this affects their impact and sustainability. It also extends the literature on social-symbolic work by highlighting the interplay of different forms of work in constructing social problems. Finally, it contributes to research on gender inequality and organizations by showing how the work of social partnerships can shape conceptions of gender inequality at the meso level.