bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reflectance spectroscopy as a promising tool for ‘sensing’ metals in hyperaccumulator plants
Authors: Purwadi Imam , Erskine Peter D. , van der Ent Antony 
Published: July 2023

Abstract
Main conclusion
The VNIR reflectance spectra of nickel hyperaccumulator plant leaves have spectral variations due to high nickel concentrations and this property could potentially be used for discovery of these plants.

Abstract
Hyperaccumulator plants accumulate high concentrations of certain metals, including manganese, cobalt, or nickel. Of these metals, the divalent ions of nickel have three absorption bands in the visible to near-infrared region which may cause variations in the spectral reflectance of nickel hyperaccumulator plant leaves, but this has not been investigated previously. In this shortproof-of-concept study, the spectral reflectance of eight different nickel hyperaccumulator plant species leaves were subjected to visible and near-infrared and shortwave infrared (VNIR-SWIR) reflectance spectrum measurements in dehydrated state, and for one species, it was also assessed in hydrated state. Nickel concentrations in the plant leaves were determined with other methods and then correlated to the spectral reflectance data. Spectral variations centred at 1000 ± 150 nm were observed and had R-values varying from 0.46 to 0.96 with nickel concentrations. The extremely high nickel concentrations in nickel hyperaccumulator leaves reshape their spectral reflectance features, and the electronic transition of nickel-ions directly contributes to absorption at ~ 1000 nm. Given that spectral variations are correlated with nickel concentrations it make VNIR-SWIR reflectance spectrometry a potential promising technique for discovery of hyperaccumulator plants, not only in the laboratory or herbarium, but also in the field using drone-based platforms. This is a preliminary study which we hope will instigate further detailed research on this topic to validate the findings and to explore possible applications.
Learning a covert sequence of effector movements: limits to its acquisition
Authors: Johannsen Leif , Koch Iring 
Published: July 2023

AbstractSequence learning in serial reaction time (SRT) tasks is an established, lab-based experimental paradigm to study acquisition and transfer of skills based on the detection of predictable regularities in stimulus and motor response sequences. Participants learn a sequence of targets and responses to these targets by associating the responses with subsequently presented targets. In the traditional paradigm, however, actions and response targets are directly related. In contrast, the present study asked whether participants would demonstrate acquisition of a sequence of effector movements of the left vs. right hand (e.g., hand sequence learning), whilst the actual targets and associated finger responses are unpredictable. Twenty-seven young adults performed a SRT task to visually presented characters with the index or middle fingers of both hands. While the specific fingers to respond with were randomly selected for each target presentation, both hands followed a covert sequence. We asked whether participants would learn the underlying hand sequence as demonstrated by shortened response latencies and increased accuracy compared to a fully randomized hand sequence. The results show sequence-specific learning effects. However, categorization of hand responses depending on the previous response suggested that learning occurred predominantly for subsequent finger responses of the same hand, which added to general hand-based priming. Nevertheless, a marginally significant effect was observed even for predictable shifts between hands when homologous fingers were involved. Our results thus suggest that humans are able to benefit from predictable within-hand finger shifts but less so for predicted shifts between hands.
Reducing Graph Parameters by Contractions and Deletions
Authors: Lucke Felicia , Mann Felix 
Published: July 2023

AbstractWe consider the following problem: for a given graph G and two integers k and d, can we apply a fixed graph operation at most k times in order to reduce a given graph parameter $$\pi $$
π
by at least d? We show that this problem is NP-hard when the parameter is the independence number and the graph operation is vertex deletion or edge contraction, even for fixed $$d=1$$

d
=
1

and when restricted to chordal graphs. We give a polynomial time algorithm for bipartite graphs when the operation is edge contraction, the parameter is the independence number and d is fixed. Further, we complete the complexity dichotomy for H-free graphs when the parameter is the clique number and the operation is edge contraction by showing that this problem is NP-hard in $$(C_3+P_1)$$

(

C
3

+

P
1

)

-free graphs even for fixed $$d=1$$

d
=
1

. When the operation is edge deletion and the parameter is the chromatic number, we determine the computational complexity of the associated problem for cographs and complete multipartite graphs. Our results answer several open questions stated in Diner et al. (Theor Comput Sci 746:49–72, 2012, https://doi.org/10.1016/j.tcs.2018.06.023).
Non-structural carbohydrate concentrations in contrasting dry and wet years in early- and late-successional boreal forest trees
Authors: Dulamsuren Choimaa , Byamba-Yondon Gurbazar , Oyungerel Shagjjav , Nitschke Renate , Gebauer Tobias 
Published: July 2023

AbstractKey messagePatterns of non-structural carbohydrate allocation in dry and wet differ between birch and larch in southern boreal forest.AbstractAn increasing area of boreal forests is currently switching from temperature to drought limitation. It is not sufficiently known how the trees’ non-structural carbohydrate (NSC) pools are affected by alternating dry and wet phases in drought-prone boreal forests and how NSC concentrations are related to growth responses. In the southern boreal forests of Mongolia, NSC concentrations (including soluble sugars and starch) were determined enzymatically in the stemwood of two tree species during a drought year (2017) that was preceded by another drought in 2015 and two subsequent wet years (2018/19).Betula platyphyllaas a broadleaved pioneer tree showed reduced radial stem increment in the drought year and rapidly increasing growth in the following wet years. It had low concentrations of NSC and of soluble sugars in particular, suggesting that most assimilate were invested into growth in this early successional tree.Larix sibiricaas a late-successional conifer also showed reduced growth in the drought year, but lagged reductions in NSC concentrations and less pronounced growth releases than birch in 2018/19, suggesting a longer aftereffect of the drought than in birch. Larch maintained much higher NSC concentrations throughout the three studied growing seasons, including the drought episode in 2017. The NSC pool in larch was primarily formed by soluble sugars in sapwood and heartwood. In contrast to birch, larch showed a high allocation priority for assimilates in soluble sugars before investment in biomass, which explains the aftereffect of the drought on both growth and NSC. We conclude that the high soluble sugar concentrations in larch are a key determinant of the extreme drought and cold tolerance ofL. sibiricaand, therefore, growth has lower allocation priority for carbon compared to birch.
Minimally invasive fusion surgery for patients with degenerative spondylolisthesis and severe lumbar spinal stenosis: a comparative study between MIDLIF and TLIF
Authors: Silva Pedro Santos , Jardim Ana , Pereira Joana , Sousa Rita , Vaz Rui , Pereira Paulo 
Published: July 2023

Abstract
Purpose
This study aims to compare midline lumbar interbody fusion (MIDLIF) and minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF) for treatment of patients with severe stenosis and lumbar degenerative spondylolisthesis (DS), focusing on dural tears rates, other complications, clinical and radiological outcomes.

Methods
This cohort study included patients with severe lumbar spinal stenosis (Shizas C or D) and lumbar DS who underwent MIDLIF or MIS-TLIF. Propensity score matching was done and the groups were compared regarding surgery time, length of stay, perioperative complications, clinical results and radiological outcomes, at 1 year of follow-up.

Results
The study included initially 80 patients, and 72 patients after matching, 36 in each group. Six patients had dural tears, four in the MIDLIF group and two in the MIS-TLIF group (p = 0.67). General complication rates and reoperations were not significantly different between the groups. Good or excellent clinical was achieved in 75% of the MIDLIF patients and 72% of the MIS-TLIF patients (p = 0.91). Radiological parameters showed small but statistically significant (p < 0.01) improvements after surgery, particularly in segmental lordosis and lumbar lordosis (2.0° and 1.7°), while pelvic tilt and global tilt decreased (1.6° and 2.6°). These findings were similar for both groups.

Conclusion
Our study confirms that MIDLIF is a safe and reliable minimally invasive alternative for lumbar interbody fusion in DS, even in patients with severe stenosis and previous spine surgery. It seems to offer similar results to MIS-TLIF regarding clinical results, radiological outcomes and complications.
The effect of GLP-1 receptor agonist lixisenatide on experimental diabetic retinopathy
Authors: Oezer Kuebra , Kolibabka Matthias , Gassenhuber Johann , Dietrich Nadine , Fleming Thomas , Schlotterer Andrea , Morcos Michael , Wohlfart Paulus , Hammes Hans-Peter 
Published: July 2023

Abstract
Aims
Glucagon-like peptide-1 receptor agonists are effective treatments for type 2 diabetes, effectively lowering glucose without weight gain and with low risk for hypoglycemia. However, their influence on the retinal neurovascular unit remains unclear. In this study, we analyzed the effects of the GLP-1 RA lixisenatide on diabetic retinopathy.

Methods
Vasculo- and neuroprotective effects were assessed in experimental diabetic retinopathy and high glucose-cultivated C. elegans, respectively. In STZ-diabetic Wistar rats, acellular capillaries and pericytes (quantitative retinal morphometry), neuroretinal function (mfERG), macroglia (GFAP western blot) and microglia (immunohistochemistry) quantification, methylglyoxal (LC–MS/MS) and retinal gene expressions (RNA-sequencing) were determined. The antioxidant properties of lixisenatide were tested in C. elegans.

Results
Lixisenatide had no effect on glucose metabolism. Lixisenatide preserved the retinal vasculature and neuroretinal function. The macro- and microglial activation was mitigated. Lixisenatide normalized some gene expression changes in diabetic animals to control levels. Ets2 was identified as a regulator of inflammatory genes. In C. elegans, lixisenatide showed the antioxidative property.

Conclusions
Our data suggest that lixisenatide has a protective effect on the diabetic retina, most likely due to a combination of neuroprotective, anti-inflammatory and antioxidative effects of lixisenatide on the neurovascular unit.
Highlighting the potential of multilevel statistical models for analysis of individual agroforestry systems
Authors: Golicz Karolina , Piepho Hans-Peter , Minarsch Eva-Maria L. , Niether Wiebke , Große-Stoltenberg André , Oldeland Jens , Breuer Lutz , Gattinger Andreas , Jacobs Suzanne 
Published: July 2023

AbstractAgroforestry is a land-use system that combines arable and/or livestock management with tree cultivation, which has been shown to provide a wide range of socio-economic and ecological benefits. It is considered a promising strategy for enhancing resilience of agricultural systems that must remain productive despite increasing environmental and societal pressures. However, agroforestry systems pose a number of challenges for experimental research and scientific hypothesis testing because of their inherent spatiotemporal complexity. We reviewed current approaches to data analysis and sampling strategies of bio-physico-chemical indicators, including crop yield, in European temperate agroforestry systems to examine the existing statistical methods used in agroforestry experiments. We found multilevel models, which are commonly employed in ecology, to be underused and under-described in agroforestry system analysis. This Short Communication together with a companion R script are designed to act as an introduction to multilevel models and to promote their use in agroforestry research.
On the exact mid-band gain of the CMOS OTA with low-voltage-cascode-current-mirror
Authors: Singhal Naina , Hasan S. M. Rezaul 
Published: July 2023

AbstractThis article presents an exact mid-band gain-expression for the CMOS operational-transconductance-amplifier (OTA) with low-voltage-cascode-current-mirror (LVCCM) load. Its small-signal analysis is not available in any CMOS text-book or other published sources/articles. A simplified and innovative technique is employed in performing this analysis with an in depth tutorial flavor. It shows that the derived mid-band gain of the CMOS OTA with LVCCM load is significantly more accurate than that obtained using the highly approximate classical gain-expression of the OTA employing a standard cascode-current-mirror equivalence which may be used in textbooks and other articles. Circuit simulations employing the 180-nm and 65-nm TSMC CMOS process technologies has been performed to indicate the progressively higher accuracy of the derived exact gain-expression for the LVCCM loaded OTA with technology scaling. This new analysis indicates an additional degree of freedom in tuning the gain of the OTA with LVCCM load using an additional transconductance parameter, gm5,6 of (M5, M6). A simplified expression is also deduced which provides an improvement over the classical approximate expression, due to the additional design insight and accuracy provided by this additional parameter while still being amenable to first order gain evaluation in a simplified way. The presented analysis is new and has not been reported before in open literature in any form.
Fluid nature constrains Horndeski gravity
Authors: Miranda Marcello , Vernieri Daniele , Capozziello Salvatore , Faraoni Valerio 
Published: July 2023

AbstractThe elusive physical nature of Horndeski gravity is elucidated in a new approach depicting this class of theories as a dissipative effective fluid. Requiring the constitutive equations of the latter to be those of a Newtonian fluid restricts the theory to only two disconnected subclasses of “viable” Horndeski gravity. Therefore, a stress-energy tensor of the Horndeski effective fluid, linear in the first derivatives of the fluid’s 4-velocity, is a sufficient condition for gravitational waves to propagate at light speed. All other Horndeski theories correspond to exotic non-Newtonian effective fluids. The two linear Horndeski classes are studied in the framework of first-order thermodynamics of viscous fluids, which further constrains the functional form of the theory.
Electronic transport computation in thermoelectric materials: from ab initio scattering rates to nanostructures
Authors: Neophytou Neophytos , Priyadarshi Pankaj , Li Zhen , Graziosi Patrizio 
Published: July 2023

AbstractOver the last two decades a plethora of new thermoelectric materials, their alloys, and their nanostructures were synfthesized. The ZT figure of merit, which quantifies the thermoelectric efficiency of these materials increased from values of unity to values consistently beyond two across material families. At the same time, the ability to identify and optimize such materials, has stressed the need for advanced numerical tools for computing electronic transport in materials with arbitrary bandstructure complexity, multiple scattering mechanisms, and a large degree of nanostructuring. Many computational methods have been developed, the majority of which utilize the Boltzmann transport equation (BTE) formalism, spanning from fully ab initio to empirical treatment, with varying degree of computational expense and accuracy. In this paper we describe a suitable computational process that we have recently developed specifically for thermoelectric materials. The method consists of three independent software packages that we have developed and: (1) begins from ab initio calculation of the electron–phonon scattering rates, (2) to then be used within a Boltzmann transport simulator, and (3) calculated quantities from the BTE are then passed on to a Monte Carlo simulator to examine electronic transport in highly nanostructured material configurations. The method we describe is computationally significantly advantageous compared to current fully ab initio and existing Monte Carlo methods, but with a similar degree of accuracy, thus making it truly enabling in understanding and assessing thermoelectric transport in complex band, nanostructured materials.
A two-stages global sensitivity analysis by using the δ sensitivity index in presence of correlated inputs: application on a tumor growth inhibition model based on the dynamic energy budget theory
Authors: De Carlo Alessandro , Tosca Elena Maria , Melillo Nicola , Magni Paolo 
Published: July 2023

AbstractGlobal sensitivity analysis (GSA) evaluates the impact of variability and/or uncertainty of the model parameters on given model outputs. GSA is useful for assessing the quality of Pharmacometric model inference. Indeed, model parameters can be affected by high (estimation) uncertainty due to the sparsity of data. Independence between model parameters is a common assumption of GSA methods. However, ignoring (known) correlations between parameters may alter model predictions and, then, GSA results. To address this issue, a novel two-stages GSA technique based on the δ index, which is well-defined also in presence of correlated parameters, is here proposed. In the first step, statistical dependencies are neglected to identify parameters exerting causal effects. Correlations are introduced in the second step to consider the real distribution of the model output and investigate also the ‘indirect’ effects due to the correlation structure. The proposed two-stages GSA strategy was applied, as case study, to a preclinical tumor-in-host-growth inhibition model based on the Dynamic Energy Budget theory. The aim is to evaluate the impact of the model parameter estimate uncertainty (including correlations) on key model-derived metrics: the drug threshold concentration for tumor eradication, the tumor volume doubling time and a new index evaluating the drug efficacy-toxicity trade-off. This approach allowed to rank parameters according to their impact on the output, discerning whether a parameter mainly exerts a causal or ‘indirect’ effect. Thus, it was possible to identify uncertainties that should be necessarily reduced to obtain robust predictions for the outputs of interest.
The Role of Religion, Spirituality and Social Media in the Journey of Eating Disorders: A Qualitative Exploration of Participants in the “TastelifeUK” Eating Disorder Recovery Programme
Authors: Mitra Barbara , Archer Diana , Hurst Joanne , Lycett Deborah 
Published: July 2023

AbstractThis study explores the religious and spiritual aspects of eating disorder recovery and the role of social media in the context of a third sector community-based recovery group in the UK. Four online focus groups explored participant perspectives (17 participants in total) using thematic analysis. The qualitative findings highlight that relational support from God is important in eating disorder recovery and coping, although this can be challenged by spiritual struggles and tensions. Relational support from people is also relevant where it offers a place to share different experiences together giving a sense of community belonging. Social media was also found to be important in relation to eating disorders, either providing a community of support or exacerbating existing issues. This study suggests that the role of religion and social media should be acknowledged where it is important for that individual in relation to eating disorder recovery.
Error Bounds for Discrete-Continuous Free Flight Trajectory Optimization
Authors: Borndörfer Ralf , Danecker Fabian , Weiser Martin 
Published: July 2023

AbstractTwo-stage methods addressing continuous shortest path problems start local minimization from discrete shortest paths in a spatial graph. The convergence of such hybrid methods to global minimizers hinges on the discretization error induced by restricting the discrete global optimization to the graph, with corresponding implications on choosing an appropriate graph density. A prime example is flight planning, i.e., the computation of optimal routes in view of flight time and fuel consumption under given weather conditions. Highly efficient discrete shortest path algorithms exist and can be used directly for computing starting points for locally convergent optimal control methods. We derive a priori and localized error bounds for the flight time of discrete paths relative to the optimal continuous trajectory, in terms of the graph density and the given wind field. These bounds allow designing graphs with an optimal local connectivity structure. The properties of the bounds are illustrated on a set of benchmark problems. It turns out that localization improves the error bound by four orders of magnitude, but still leaves ample opportunities for tighter error bounds by a posteriori estimators.
Evolutionary feature selection approaches for insolvency business prediction with genetic programming
Authors: Beade Ángel , Rodríguez Manuel , Santos José 
Published: July 2023

AbstractThis study uses different feature selection methods in the field of business failure prediction and tests the capability of Genetic Programming (GP) as an appropriate classifier in this field. The prediction models categorize the insolvency/non-insolvency of a firm one year in advance from a large set of financial ratios. Different selection strategies based on two evolutionary algorithms were used to reduce the dimensionality of the financial features considered. The first method considers the combination between the global search provided by an evolutionary algorithm (differential evolution) with a simple classifier, together with the possible use of classical filters in a first step of feature selection. Secondly, genetic programming is used as a feature selector. In addition, these selection approaches will be compared when GP is used exclusively as a classifier. The results show that, when using GP as a classifier method, the proposed selection method with GP stands out from the rest. Moreover, the use of GP as a classifier improves the results with respect to other classifier methods. This shows an added value to the use of GP in this field, in addition to the interpretability of GP prediction models.
Rational QZ steps with perfect shifts
Authors: Mastronardi Nicola , Van Barel Marc , Vandebril Raf , Van Dooren Paul 
Published: July 2023

AbstractIn this paper we analyze the stability of the problem of performing a rational QZ step with a shift that is an eigenvalue of a given regular pencil $$H-\lambda K$$

H
-
λ
K

in unreduced Hessenberg–Hessenberg form. In exact arithmetic, the backward rational QZ step moves the eigenvalue to the top of the pencil, while the rest of the pencil is maintained in Hessenberg–Hessenberg form, which then yields a deflation of the given shift. But in finite-precision the rational QZ step gets “blurred” and precludes the deflation of the given shift at the top of the pencil. In this paper we show that when we first compute the corresponding eigenvector to sufficient accuracy, then the rational QZ step can be constructed using this eigenvector, so that the exact deflation is also obtained in finite-precision.