bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of different crop model-based approaches for variable rate nitrogen fertilization in winter wheat
Authors: Gobbo S. , De Antoni Migliorati M. , Ferrise R. , Morari F. , Furlan L. , Sartori L. 
Published: September 2022

AbstractSeveral remote sensing-based methods have been developed to apply site-specific nitrogen (N) fertilization in crops. They consider spatial and temporal variability in the soil-plant-atmosphere continuum to modulate N applications to the actual crop nutrient status and requirements. However, deriving fertilizer N recommendations exclusively from remote proximal and remote sensing data can lead to substantial inaccuracies and new, more complex approaches are needed.Therefore, this study presents an improved approach that integrates crop modelling, proximal sensing and forecasts weather data to manage site-specific N fertilization in winter wheat. This improved approach is based on four successive steps: (1) optimal N supply is estimated through the DSSAT crop model informed with a combination of observed and forecast weather data; (2) actual crop N uptake is estimated using proximal sensing; (3) N prescription maps are created merging crop model and proximal sensing information, considering also the contribution of the soil N mineralisation; (4) N-Variable Rate Application (N-VRA) is implemented in the field. A VRA method based on DSSAT fed with historical weather data and a business-as- usual uniform fertilization were also compared.The methods were implemented in a 23.4 ha field in Northern Italy, cropped to wheat and characterized by large soil variability in texture and organic matter content. Results indicated that the model-based approaches consistently led to higher yields, agronomic efficiencies and gross margins than the uniform N application rate. Furthermore, the proximal sensing-based approach allowed capturing of the spatial variability in crop N uptake and led to a substantial reduction of the spatial variability in yield and protein content. This study grounds the development of web-based software as a friendly tool to optimize the N variable rate application in winter cereals.
Additive functions in short intervals, gaps and a conjecture of Erdős
Authors: Mangerel Alexander P. 
Published: September 2022

AbstractWith the aim of treating the local behaviour of additive functions, we develop analogues of the Matomäki–Radziwiłł theorem that allow us to approximate the average of a general additive function over a typical short interval in terms of a corresponding long average. As part of this treatment, we use a variant of the Matomäki–Radziwiłł theorem for divisor-bounded multiplicative functions recently proven in Mangerel (Divisor-bounded multiplicative functions in short intervals. arXiv: 2108.11401). We consider two sets of applications of these methods. Our first application shows that for an additive function $${\varvec{g:}} \mathbb {N} \rightarrow \mathbb {C}$$

g
:

N
→
C

any non-trivial savings in the size of the average gap $$|{\varvec{g}}{} {\textbf {(}}{\varvec{n}}{} {\textbf {)}}-{\varvec{g}}{} {\textbf {(}}{\varvec{n}}-{\textbf {1}}{} {\textbf {)}} |$$

|

g

(

n

)
-

g

(

n

-
1

)
|

implies that $${\varvec{g}}$$

g

must have a small first centred moment i.e. the discrepancy of $${\varvec{g}}{} {\textbf {(}}{\varvec{n}}{} {\textbf {)}}$$

g

(

n

)

from its mean is small on average. We also obtain a variant of such a result for the second moment of the gaps. This complements results of Elliott and of Hildebrand. As a second application, we make partial progress on an old question of Erdős relating to characterizing constant multiples of $${{\textbf {log}}} \,{\varvec{n}}$$

log

n

as the only almost everywhere increasing additive functions. We show that if an additive function is almost everywhere non-decreasing then it is almost everywhere well approximated by a constant times a logarithm. We also show that if the set $$\{{\varvec{n}} \in \mathbb {N} : {\varvec{g}}{} {\textbf {(}}{\varvec{n}}{} {\textbf {)}} < {\varvec{g}}{} {\textbf {(}}{\varvec{n}}-{\textbf {1}}{} {\textbf {)}}\}$$

{

n

∈
N
:

g

(

n

)
<

g

(

n

-
1

)
}

is sufficiently sparse, and if $${\varvec{g}}$$

g

is not extremely large too often on the primes (in a precise sense), then $${\varvec{g}}$$

g

is identically equal to a constant times a logarithm.
Spatial variations in financial constraints of SMEs—evidence from firm-level estimates of investment-cash flow sensitivities in Sweden
Authors: Andersson Martin , Eklund Johan E. , Tsvetkova Alexandra 
Published: September 2022

AbstractIt is well established that there is uneven availability of credit across space, in particular for SMEs. The evidence on whether this translates into differences in actual business investments remains scarce. We assess this question by using firm-level data for Swedish firms and estimate the extent to which the average investment-cash flow sensitivities of firms vary across the urban–rural hierarchy. We find that the world of financing is not yet flat for the majority of Swedish SMEs. Companies located in non-metro regions are most dependent on own cash flow in their investments. The results hold for all firms, firms of different sizes, firms operating in low-end services, unaffiliated firms and those belonging to domestic corporations. In contrast, investment-cash flow sensitivity of firms operating in high-tech services and those belonging to a multinational enterprise does not differ geographically. On average, regional investment-cash flow sensitivity is lower in bigger, denser and more educated local labour market regions; it is higher in regions with greater concentration of SMEs.
The G-NORM Scale: Development and Validation of a Theory-Based Gender Norms Scale
Authors: Sedlander Erica , Bingenheimer Jeffrey B. , Long Michael W. , Swain Minati , Rimal Rajiv N. 
Published: September 2022

AbstractGender norms are increasingly recognized as important modifiers of health. Despite growing awareness of how gender norms affect health behavior, current gender norms scales are often missing two important theoretical components: differentiating between descriptive and injunctive norms and adding a referent group. We used a mixed-methods approach to develop and validate a novel gender norms scale that includes both theoretical components. Based on qualitative data, the theory of normative social behavior, and the theory of gender and power, we generated a pool of 28 items. We included the items in a baseline questionnaire among 3,110 women in Odisha, India as part of a cluster randomized controlled trial. We then ran exploratory factor analysis which resulted in 18 items. Using a second wave of data with the same sample, we evaluated psychometric properties using confirmatory factor analysis and structural equation modeling. The analysis resulted in two subscales with nine items each, “descriptive gender norms” and “injunctive gender norms.” Both subscales represent high internal validity with Cronbach’s alpha values of 0.81 and 0.84 and the combined scale has an alpha of 0.87. The G-NORM, gender norms scale, improves on existing measures by providing distinct descriptive and injunctive norms subscales and moving beyond individual attitudes by assessing women’s perceptions of community-level gender norms.
Comparing Teachers’ and Students’ Perspectives on the Treatment of Student Misbehavior
Authors: Twardawski Mathias , Hilbig Benjamin E. 
Published: September 2022

AbstractThe treatment of student misbehavior is both a major challenge for teachers and a potential source of students’ perceptions of injustice in school. By implication, it is vital to understand teachers’ treatment of student misbehavior vis-à-vis students’ perceptions. One key dimension of punishment behavior reflects the underlying motives and goals of the punishment. In the present research, we investigated the perspectives of both teachers and students concerning the purposes of punishment. Specifically, we were interested in the extent to which teachers and students show preferences for either retribution (i.e., evening out the harm caused), special prevention (i.e., preventing recidivism of the offender), or general prevention (i.e., preventing imitation of others) as punishment goals. Therefore, teachers (N = 260) and school students around the age of 10 (N = 238) were provided with a scenario depicting a specific student misbehavior. Participants were asked to indicate their endorsement of the three goals as well as to evaluate different punishment practices that were perceived (in pretests) to primarily achieve one specific goal but not the other two. Results show that teachers largely prefer general prevention, whereas students rather prefer special prevention and retribution. This discrepancy was particularly large in participants’ evaluation of specific punishment practices, whereas differences between teachers’ and students’ direct endorsement of punishment goals were relatively small. Overall, the present research may contribute to the development of classroom intervention strategies that reduce conflicts in student–teacher-interactions.
Edge-Aware Graph Matching Network for Part-Based Semantic Segmentation
Authors: Michieli Umberto , Zanuttigh Pietro 
Published: September 2022

AbstractSemantic segmentation of parts of objects is a marginally explored and challenging task in which multiple instances of objects and multiple parts within those objects must be recognized in an image. We introduce a novel approach (GMENet) for this task combining object-level context conditioning, part-level spatial relationships, and shape contour information. The first target is achieved by introducing a class-conditioning module that enforces class-level semantics when learning the part-level ones. Thus, intermediate-level features carry object-level prior to the decoding stage. To tackle part-level ambiguity and spatial relationships among parts we exploit an adjacency graph-based module that aims at matching the spatial relationships between parts in the ground truth and predicted maps. Last, we introduce an additional module to further leverage edges localization. Besides testing our framework on the already used Pascal-Part-58 and Pascal-Person-Part benchmarks, we further introduce two novel benchmarks for large-scale part parsing, i.e., a more challenging version of Pascal-Part with 108 classes and the ADE20K-Part benchmark with 544 parts. GMENet achieves state-of-the-art results in all the considered tasks and furthermore allows to improve object-level segmentation accuracy.
Nocturnal nasal high-flow oxygen therapy in elderly patients with concomitant chronic obstructive pulmonary disease and obstructive sleep apnea
Authors: Spicuzza Lucia , Sambataro Gianluca , Schisano Matteo , Ielo Giuseppe , Mancuso Salvatore , Vancheri Carlo 
Published: September 2022

Abstract
Purpose
The coexistence of obstructive sleep apnea (OSA) and chronic obstructive pulmonary disease (COPD) is known as “overlap syndrome” (OS). Patients with OS are usually older than patients with OSA alone, suffer from more profound oxygen desaturation during the obstructive events often accompanied by sustained nocturnal hypoventilation. Although oxygen-enriched positive airway pressure (PAP) is the treatment of choice in these patients, this therapy is often poorly tolerated particularly by the elderly. The aim of this study was to assess the usefulness of nocturnal oxygen therapy via nasal high flow (NHF-OT) as a possible alternative to PAP in patients with OS.

Methods
Patients > 65 years old with OS and nocturnal respiratory failure (time spent below SaO2 90% (T90) > 30%) had cardio-respiratory monitoring performed at baseline, during NHF-OT, or during conventional oxygen therapy (COT).

Results
A total of 40 patients were enrolled in the study. NHF-OT significantly reduced the apnea–hypopnea index (AHI) in all patients compared to baseline and COT. The mean basal AHI was 25.4 ± 8.6. During COT and NHF-OT, the AHI was 19.4 ± 7 and 5.4 ± 4.6, respectively (P < 0.001) and 19 patients reached an AHI < 5 during NHF-OT. The mean nocturnal SaO2% was 86.2 ± 2.6 at baseline and at equivalent FiO2 it significantly increased to 91.8 ± 2.4 during COT and to 93.9 ± 2.5 during NHF-OT (P < 0.001). The T90% was 48.7 ± 20.1 at baseline, 16.8 ± 11.7 during COT, and 8.8 ± 8.0 during NHF-OT (P < 0.001).

Conclusions
In elderly patients with OS, nocturnal treatment with NHF-OT significantly reduces obstructive episodes and improves oxygenation. As the treatment is generally well tolerated compared to PAP, NHF-OT may be a possible alternative therapy in this subgroup of patients.
Accuracy assessment of inverse distance weighting interpolation of groundwater nitrate concentrations in Bavaria (Germany)
Authors: Ohlert Paul L. , Bach Martin , Breuer Lutz 
Published: September 2022

AbstractFor the designation of nitrate vulnerable zones under the EU Nitrate Directive, some German federal states use inverse distance weighting (IDW) as interpolation method. Our study quantifies the accuracy of IDW with respect to the designation of areas with a groundwater nitrate concentration above the threshold of 50 mg NO3/l using a dataset of 5790 groundwater monitoring sites in Bavaria. The results show that the absolute differences of nitrate concentrations between the monitoring sites are only weakly correlated within a range of no more than 0.4 km. The IDW cross-validated nitrate concentration of measurement sites shows a mean absolute error of 7.0 mg NO3/l and the number of measurement sites above 50 mg NO3/l is 44% too low by interpolation for all sites as a whole. The corresponding values for interpolation separately for the 18 hydrogeological regions in Bavaria are 7.1 mg NO3/l and 38%. The sensitivity and the accuracy of nitrate concentration maps due to the variation of IDW parameters and the position of sampling points are analysed by Monte Carlo IDW interpolations using a Random Forest modelled map as reference spatial distribution. Compared to this reference map, the area with a concentration above 50 mg NO3/l in groundwater is estimated by IDW to be 46% too low for the best IDW parametrization. Overall, IDW interpolation systematically underrates the occurrence of higher range nitrate concentrations. In view of these underestimations, IDW does not appear to be a suitable regionalization method for the designation of nitrate vulnerable zones, neither when applied for a federal state as a whole nor when interpolated separately for hydrogeological regions.
Analysing the influence of foreign direct investment and urbanization on the development of private financial system and its ecological footprint
Authors: Ponce Pablo , Álvarez-García José , Álvarez Viviana , Irfan Muhammad 
Published: September 2022

Abstract
In this research, the objective is to examine how private financial development, urbanization and foreign direct investment and economic growth affects the environment using the ecological footprint as an indicator. Panel data was used for 100 countries from 1980 to 2019, classified according to their income level. Several econometric steps were used to estimate the results, such as cointegration and causality techniques. The results show that the private financial system and environmental degradation have a long-term equilibrium relationship, and the incidence is positive, but not significant at the level of the 100 countries. In high-income countries, the private financial system reduces environmental degradation; however, in upper middle-income, lower middle-income and low-income countries, it increases in the long run. Likewise, urbanization plays a predominant role on the ecological footprint in the long term. Meanwhile, the role of foreign direct investment is not stable over time. The causality test shows bidirectional causality between environmental degradation and the private financial system at the global level in high- and upper middle-income countries. However, low-income countries have a unidirectional relationship of environmental degradation to the private financial system. With regard to foreign direct investment, there is a unidirectional causal relationship between environmental degradation and foreign direct investment at the global level and from foreign direct investment to environmental degradation in high-income countries.
Factors controlling 137Cs distribution in bottom sediments of Koronowo Reservoir (Poland)
Authors: Sekudewicz Ilona , Matoušková Šárka , Ciesielska Zuzanna , Mulczyk Anna , Gąsiorowski Michał 
Published: September 2022

Abstract
Purpose
The main aim of this study was to investigate factors influencing the long-term distribution of 137Cs activity concentrations in the bottom sediments of the dam lake, Koronowo Reservoir, 32 years after the Chernobyl nuclear power plant accident. For this purpose, selected properties of the collected sediment samples, such as grain size, mineralogical composition, and organic matter (OM) content, were investigated.

Materials and methods
The samples of lake sediments were collected with a Kayak-type gravity corer. The spatial and vertical distributions of 137Cs and 40K activity concentrations in the bottom sediments were investigated based on gamma spectrometry measurements. The particle size distribution of surface lake sediments was determined using a laser particle size analyzer. SEM and XRD were used for the mineralogical analysis of the collected sediment samples. Additionally, the content of organic matter was examined in all samples using an elemental analyzer.

Results
The 137Cs content was significantly elevated in the case of fine-grained (< 63 µm) surface lake sediments (classified as silts, which are deposited in the profundal zone of Koronowo Lake) and ranged from 12.5 ± 4.1 to 29.2 ± 4.0 Bq kg−1. It was found that the increased concentration of 137Cs activity is more closely related to the content of the silt fraction (2–63 µm) than to the clay fraction (< 2 µm) in the collected surface lake sediments. The content of clay minerals also showed a significant positive correlation with 137Cs activity concentration in the surface lake sediments of Koronowo Lake. A similar relationship was noticed for the OM content, but it may be suspected that it is the result of radiocesium-bearing particle accumulation in OM-rich sediments.

Conclusion
The most important factor influencing the spatial distribution of 137Cs activity concentrations in the surface lake sediments of Koronowo Lake, apart from the bottom morphology and grain size of sediments, is the content of clay minerals. Moreover, the increased detrital inflow to the lake after the construction of the dam could have probably affected the vertical distribution of 137Cs activity concentrations in the bottom sediments, as evidenced by, e.g., the measurements of 40K activity concentration.
Differences in functional network between focal onset nonconvulsive status epilepticus and toxic metabolic encephalopathy: application to machine learning models for differential diagnosis
Authors: Kim Seong Hwan , Kim Hayom , Kim Jung Bin 
Published: September 2022

AbstractWe aimed to compare network properties between focal-onset nonconvulsive status epilepticus (NCSE) and toxic/metabolic encephalopathy (TME) during periods of periodic discharge using graph theoretical analysis, and to evaluate the applicability of graph measures as markers for the differential diagnosis between focal-onset NCSE and TME, using machine learning algorithms. Electroencephalography (EEG) data from 50 focal-onset NCSE and 44 TMEs were analyzed. Epochs with nonictal periodic discharges were selected, and the coherence in each frequency band was analyzed. Graph theoretical analysis was performed to compare brain network properties between the groups. Eight different traditional machine learning methods were implemented to evaluate the utility of graph theoretical measures as input features to discriminate between the two conditions. The average degree (in delta, alpha, beta, and gamma bands), strength (in delta band), global efficiency (in delta and alpha bands), local efficiency (in delta band), clustering coefficient (in delta band), and transitivity (in delta band) were higher in TME than in NCSE. TME showed lower modularity (in delta band) and assortativity (in alpha, beta, and gamma bands) than NCSE. Machine learning algorithms based on EEG global graph measures classified NCSE and TME with high accuracy, and gradient boosting was the most accurate classification model with an area under the receiver operating characteristics curve of 0.904. Our findings on differences in network properties may provide novel insights that graph measures reflecting the network properties could be quantitative markers for the differential diagnosis between focal-onset NCSE and TME.
Sarmanov bivariate distribution: dependence structure—Fisher information in order statistics and their concomitants
Authors: Barakat H. M. , Alawady M. A. , Mansour G. M. , Husseiny I. A. 
Published: September 2022

AbstractThe Sarmanov family of bivariate distributions is considered as the most flexible and efficient extended families of the traditional Farlie–Gumbel–Morgenstern family. The goal of this work is twofold. The first part focuses on revealing some novel aspects of the Sarmanov family’s dependency structure. In the second part, we study the Fisher information (FI) related to order statistics (OSs) and their concomitants about the shape-parameter of the Sarmanov family. The FI helps finding information contained in singly or multiply censored bivariate samples from the Sarmanov family. In addition, the FI about the mean and shape parameter of exponential and power distributions in concomitants of OSs is evaluated, respectively. Finally, the cumulative residual FI in the concomitants of OSs based on the Sarmanov family is derived.
Differences in pigment circadian rhythmicity in green- and red-leafed tree species in the sun and shade
Authors: Lo Piccolo Ermes , Lauria Giulia , Bongi Giulia , Guidi Lucia , Brestic Marian , Remorini Damiano , Massai Rossano , Landi Marco 
Published: September 2022

AbstractLight flux and quality are crucial factor for setting endogenous plant circadian rhythms. Evaluating the daily rhythmicity of leaf chlorophyll content is an effective method to monitor the plant physiological endogenous clock in response to environmental signals such as light availability/quality. Here, we used a leaf-clip sensor to monitor diurnal rhythms in the content of chlorophyll and flavonoids such as flavonols and anthocyanins in three green- (Ailanthus altissima, Tilia platyphyllos and Platanus × acerifolia) and two red-leafed (Acer platanoides cv. Crimson King and Prunus cerasifera var. pissardii) tree species, adapted to sun (L) or shade (S). Significant differences in chlorophyll content (Chl) and its variations during the day were observed among treatments in all the analyzed species. S-plants had more Chl than L-plants irrespective of leaf color, and Chl variations were more distinct during the day than in L-plants. In particular, contents were lowest in the morning (9:00) and in the middle of the day (at 12:00 and 15:00), and the highest at dusk (21:00). The less evident trends in Chl variation in L-plants were attributed to a decrease in Chl content in high light, which likely masked any increases in the shaded counterparts during the afternoon. Daily flavonol levels did not vary no notably during the day. In sun-exposed red leaves, anthocyanins partially screened mesophyll cells from incident light, and its levels were similar to the Chl dynamics in the shaded counterparts. This study provides new bases for further work on endogenous rhythms of plant pigments and improves our understanding of plant physiology in the context of day/night rhythmicity.