bluuebunny/crossref_metadata_2025_split huggingface dataset:
Avena sterilis ssp. ludoviciana (Durieu) Control in Wheat Through Integration of Tillage, Seeding Rate, and Herbicide Application
Authors: Mahajan Gulshan , Chauhan Bhagirath Singh 
Published: July 2023

AbstractAvena sterilis ssp. ludoviciana (Durieu) is a problematic weed in the wheat crop of Australia. Pinoxaden is an effective herbicide for the control of this weed. However, late cohorts of A. ludoviciana escape from the early application of pinoxaden and produce seeds. This research investigated the integrated effect of tillage systems (no-tillage and conventional tillage), seeding rates (100 and 200 seeds m−2), and weed control treatments (nontreated control and pinoxaden application at Z12 and Z33 stages of wheat) on Avena ludoviciana control and wheat yield. The wheat yield remained similar in no-tillage and conventional tillage systems; however, the no-tillage system helped in reducing A. ludoviciana seed production by 28% compared with the conventional tillage system. In the nontreated control, the increased seeding rate of wheat reduced A. ludoviciana biomass and seed production by 33 and 66%, respectively, compared with the low seeding rate. These results suggest that a high seeding rate could be useful in the organic production of wheat. Application of pinoxaden at Z12 and Z33 stages of wheat resulted in an improvement in grain yield by 170 and 150%, respectively, compared with the nontreated control. At both seeding rates, the application of pinoxaden at the Z33 stage of wheat reduced weed seed production by 99% compared with the nontreated control. These results implied that the delayed application of pinoxaden at the Z33 stage of wheat effectively reduced weed biomass and seed production of A. ludoviciana without compromising grain yield as the yield in this treatment was similar to the pinoxaden application at the Z12 stage.
The trade-off frontier for ESG and Sharpe ratio: a bootstrapped double-frontier data envelopment analysis
Authors: Boubaker Sabri , Le Tu D. Q. , Manita Riadh , Ngo Thanh 
Published: July 2023

AbstractThe trade-off between the returns and the risks associated with the stocks (i.e., the Sharpe ratio, SR) is an important measure of portfolio optimization. In recent years, the environmental, social, and governance (ESG) has increasingly proven its influence on stocks’ returns, resulting in the evolvement from a two-dimensional (i.e., risks versus returns) into a multi-dimensional setting (e.g., risks versus returns versus ESG). This study is the first to examine this setting in the global energy sector using a (slacks-based measures, SBM) ESG-SR double-frontier double-bootstrap (ESG-SR DFDB) by studying the determinants of the overall ESG-SR efficiency for 334 energy firms from 45 countries in 2019. We show that only around 11% of our sampled firms perform well in the multi-dimensional ESG-SR efficient frontier. The 2019 average (in)efficiency of the global energy sector was 2.273, given an efficient level of 1.000. Besides the differences in the firm’s input/output utilization (regarding their E, S, G, and SR values), we found that the firm- (e.g., market capitalization and board characteristics) and country-level characteristics (e.g., the rule of law) have positive impacts on their ESG-SR performance. Such findings, therefore, are essential not only to the (responsible) investors but also to managers and policymakers in those firms/countries.
Interventions for Young Children’s Mental Health: A Review of Reviews
Authors: Hudson Jennifer L. , Minihan Savannah , Chen Wenting , Carl Talia , Fu Michele , Tully Lucy , Kangas Maria , Rosewell Linda , McDermott Emma A. , Wang Yiwen , Stubbs Thomas , Martiniuk Alexandra 
Published: July 2023

AbstractTo determine the efficacy of intervention programs for young children (4–9 years) with emerging mental health needs, we conducted a review of meta-analytic and systematic reviews of the intervention literature. Of 41,061 abstracts identified and 15,076 screened, 152 review articles met the inclusion criteria. We reviewed interventions across multiple disciplines targeting: (1) general mental health concerns; (2) internalizing symptoms; (3) externalizing symptoms; (4) anxiety; (5) depression; (6) trauma; (7) symptoms of attention-deficit/hyperactivity disorder; and (8) mental health concerns associated with autism spectrum disorder. Substantial evidence was found for the efficacy of behavioral and cognitive behavioral interventions for general mental health concerns, externalizing symptoms (generally, as well as ADHD, conduct, and other behavioral symptoms) and internalizing symptoms (generally, as well as anxiety) aged 4–9 years. Emerging evidence was identified for interventions targeting trauma symptoms, depression symptoms, and social, emotional and behavioral symptoms in autism spectrum disorder in children aged 4–9 years. Currently there is only limited emerging evidence regarding non-behavioral or non-cognitive behavioral interventions for programs targeting children ages 4–9 years where the aim is to deliver an evidence-based program to improve child social, emotional and/or behavioral functioning. Given the recent rises in mental health needs reported in children, targeted behavioral-and/or cognitive behavior therapy-based interventions should be made widely available to children (and their families) who experience elevated symptoms.
AI, Behavioural Science, and Consumer Welfare
Authors: Mills S. , Costa S. , Sunstein C. R. 
Published: July 2023

AbstractThis article discusses the opportunities and costs of AI in behavioural science, with particular reference to consumer welfare. We argue that because of pattern detection capabilities, modern AI will be able to identify (1) new biases in consumer behaviour and (2) known biases in novel situations in which consumers find themselves. AI will also allow behavioural interventions to be personalised and contextualised and thus produce significant benefits for consumers. Finally, AI can help behavioural scientists to “see the system,” by enabling the creation of more complex and dynamic models of consumer behaviour. While these opportunities will significantly advance behavioural science and offer great promise to improve consumer outcomes, we highlight several costs of using AI. We focus on some important environmental, social, and economic costs that are relevant to behavioural science and its application. For consumers, some of those costs involve privacy; others involve manipulation of choices.
Smart nesting: estimating geometrical compatibility in the nesting problem using graph neural networks
Authors: Abdou Kirolos , Mohammed Osama , Eskandar George , Ibrahim Amgad , Matt Paul-Amaury , Huber Marco F. 
Published: July 2023

AbstractReducing material waste and computation time are primary objectives in cutting and packing problems (C &P). A solution to the C &P problem consists of many steps, including the grouping of items to be nested and the arrangement of the grouped items on a large object. Current algorithms use meta-heuristics to solve the arrangement problem directly without explicitly addressing the grouping problem. In this paper, we propose a new pipeline for the nesting problem that starts with grouping the items to be nested and then arranging them on large objects. To this end, we introduce and motivate a new concept, namely the Geometrical Compatibility Index (GCI). Items with higher GCI should be clustered together. Since no labels exist for GCIs, we propose to model GCIs as bidirectional weighted edges of a graph that we call geometrical relationship graph (GRG). We propose a novel reinforcement-learning-based framework, which consists of two graph neural networks trained in an actor-critic-like fashion to learn GCIs. Then, to group the items into clusters, we model the GRG as a capacitated vehicle routing problem graph and solve it using meta-heuristics. Experiments conducted on a private dataset with regularly and irregularly shaped items show that the proposed algorithm can achieve a significant reduction in computation time (30% to 48%) compared to an open-source nesting software while attaining similar trim loss on regular items and a threefold improvement in trim loss on irregular items.
Beta-TCP scaffolds with rationally designed macro-micro hierarchical structure improved angio/osteo-genesis capability for bone regeneration
Authors: Feng Jianlang , Liu Junjie , Wang Yingqu , Diao Jingjing , Kuang Yudi , Zhao Naru 
Published: July 2023

AbstractThe design of hierarchical porous structure in scaffolds is crucial for bone defect regenerative repair. However, bioceramic materials present a challenge in precisely constructing designed micropores owing to the limitation of forming process. To investigate micropore shape influences bone regeneration in bioceramic scaffolds with macropores, hierarchical porous scaffolds with interconnective macropores (~400 μm) and two types of micropores (spherical and fibrous) were prepared using a combination of direct ink writing (DIW) and template sacrifice methods. Compared to the scaffold with spherical micropores, the scaffold with highly interconnected fibrous micropores significantly improved cell adhesion and upregulated osteogenic and angiogenetic-related gene expression in mBMSCs and HUVECs, respectively. Furthermore, in vivo implantation experiments showed that hierarchical scaffolds with fibrous micropores accelerated the bone repair process significantly. This result can be attributed to the high interconnectivity of fibrous micropores, which promotes the transportation of nutrients and waste during bone regeneration. Our work demonstrates that hierarchical porous scaffold design, especially one with a fibrous micropore structure, is a promising strategy for improving the bone regeneration performance of bioceramic scaffolds.
Graphical Abstract
A tri-layer decellularized, dehydrated human amniotic membrane scaffold supports the cellular functions of human tenocytes in vitro
Authors: Mao Yong , John Nikita , Protzman Nicole M. , Long Desiree , Sivalenka Raja , Azimi Shamshad , Mirabile Brandon , Pouliot Robert , Gosiewska Anna , Hariri Robert J. , Brigido Stephen A. 
Published: July 2023

AbstractDifferences in scaffold design have the potential to influence cell-scaffold interactions. This study sought to determine whether a tri-layer design influences the cellular function of human tenocytes in vitro. The single-layer decellularized, dehydrated human amniotic membrane (DDHAM) and the tri-layer DDHAM (DDHAM-3L) similarly supported tenocyte function as evidenced by improved cell growth and migration, reduced dedifferentiation, and an attenuated inflammatory response. The tri-layer design provides a mechanically more robust scaffold without altering biological activity.
Graphical Abstract
Improving exploration strategies in large dimensions and rate of convergence of global random search algorithms
Authors: Noonan Jack , Zhigljavsky Anatoly 
Published: July 2023

AbstractWe consider global optimization problems, where the feasible region $${\mathcal {X}}$$
X
is a compact subset of $$\mathbb {R}^d$$

R

d

with $$d \ge 10$$

d
≥
10

. For these problems, we demonstrate that the actual convergence of global random search algorithms is much slower than that given by the classical estimates, based on the asymptotic properties of random points, and that the usually recommended space exploration schemes are inefficient in the non-asymptotic regime. Moreover, we show that uniform sampling on entire $${\mathcal {X}}$$
X
is much less efficient than uniform sampling on a suitable subset of $${\mathcal {X}}$$
X
, and that the effect of replacement of random points by low-discrepancy sequences can be felt in small dimensions only.
EpiGeostats: An R Package to Facilitate Visualization of Geostatistical Disease Risk Maps
Authors: Ribeiro Manuel , Azevedo Leonardo , Pereira Maria João 
Published: July 2023

AbstractWith the emergence of the coronavirus disease 2019 (COVID-19) pandemic in Portugal, a geostatistical tool was developed to model the spatial distribution of COVID-19 risk to support decision-making and policymakers. Based on a block direct sequential simulation algorithm, the model provides detailed disease risk estimates and associated spatial uncertainty. However, uncertainty is difficult to visualize with the estimated risk, and is usually overlooked as a tool to support decision-making. Ignoring uncertainty can be misleading in evaluating risk, since the amount of uncertainty varies throughout the spatial domain. The EpiGeostats R package was developed to solve this problem, since it integrates the geostatistical model and visualization tools to deliver a single map summarizing disease risk and spatial uncertainty. This paper briefly describes the methodology and package functions implemented for interfacing with the tools in question. The use of EpiGeostats is illustrated by applying it to real data from COVID-19 incidence rates on mainland Portugal. EpiGeostats is a powerful tool for supporting decision-making in the context of epidemics, since it combines a well-established geostatistical model for disease risk mapping with simple and intuitive ways of visualizing results, which prevent fine-scale inference in regions with high-risk uncertainty. The package may be used for similar problems such as mortality risk, or applied to other fields such as ecology or environmental epidemiology.
Integration of state machine graphical animation and Maude to facilitate characteristic conjecture: an approach to lemma discovery in theorem proving
Authors: Bui Dang Duy , Tran Duong Dinh , Ogata Kazuhiro , Riesco Adrian 
Published: July 2023

AbstractState Machine Graphical Animation (called SMGA) is a visualization tool that assists formal methods experts in conjecturing characteristics of a protocol/system. The characteristics guessed by using the tool can be used as lemma candidates to theorem prove that the protocol/system satisfies its desired properties. Because previous work has shown that interaction in SMGA is one promising factor to foster assistance, in this paper, we revise SMGA equipping it with various interactive features in order to help human users in conjecturing lemmas. Moreover, we integrate SMGA and Maude, a declarative language and high-performance tool, so that the revised version of SMGA (called r-SMGA) can use some powerful features of Maude, such as parsing associative-commutative binary operators as well as context-free grammars, reachability analysis, and model checking. We conduct a case study with the Suzuki-Kasami protocol to demonstrate the usefulness of these new features. In the case study, some characteristics are conjectured and confirmed with these features. Based on the guessed characteristics and assistance of r-SMGA, we successfully prove that the protocol enjoys the mutual exclusion property. Finally, we propose guidelines that can help users to conjecture characteristics using r-SMGA. Our result shows that the graphical animation approach is useful for lemma conjecture in theorem proving. The formal verification is a part of the case study.
Asymptotics, Trace, and Density Results for Weighted Dirichlet Spaces Defined on the Half-line
Authors: Capone Claudia , Kałamajska Agnieszka 
Published: July 2023

AbstractWe give an analytic description for the completion of $$C_0^\infty (\mathbb {R}_+)$$

C
0
∞

(

R
+

)

, where $$\mathbb {R}_+= (0,\infty )$$

R
+

=

(
0
,
∞
)

, in Dirichlet space $$D^{1,p}(\mathbb {R}_+, \omega ):= \{ u \, :\mathbb {R}_+\rightarrow {{\mathbb {R}}}: u\ $$

D

1
,
p

(

R
+

,
ω
)

:
=
{
u

:

R
+

→
R
:
u

is locally absolutely continuous on $$\mathbb {R}_+\, and \, \Vert u^{'}\Vert _{L^p(\mathbb {R}_+, \omega )}<\infty \}$$

R
+

a
n
d

‖

u

′

‖

L
p

(

R
+

,
ω
)

<
∞
}

, for given continuous positive weight $$\omega $$
ω
defined on $$\mathbb {R}_+$$

R
+

, where $$1<p<\infty $$

1
<
p
<
∞

. The conditions are described in terms of the modified variants of the $$B_p$$

B
p

conditions due to Kufner and Opic from 1984, which in our approach are focusing on the integrability of $$\omega ^{-p/(p-1)}$$

ω

-
p
/
(
p
-
1
)

near zero or near infinity. Moreover, we propose applications of our results to: obtaining new variants of Hardy inequality, interpretation of boundary value problems in ODE’s defined on the half-line with solutions in $$D^{1,p}(\mathbb {R}_+, \omega )$$

D

1
,
p

(

R
+

,
ω
)

, new results from complex interpolation theory dealing with interpolation spaces between weighted Dirichlet spaces, and for deriving new Morrey type embedding theorems for our Dirichlet space.
Economic effects of litigation risk on corporate disclosure and innovation
Authors: Schantl Stefan F. , Wagenhofer Alfred 
Published: July 2023

AbstractEmpirical studies on the relationship between shareholder litigation and corporate disclosure obtain mixed results. We develop an economic model to capture the endogeneity between disclosure and litigation. Equilibrium disclosure is determined by two countervailing effects of litigation, a deterrence effect and an insurance effect. We derive four key results. (i) Decreasing litigation risk leads to less disclosure of very bad news, due to a weakening of the deterrence effect, but to more disclosure of weakly bad news, due to a weakening of the insurance effect. (ii) Given a sufficiently large information asymmetry, litigation risk dampens (boosts) overall disclosure of bad news for low (high) litigation risk firms. (iii) Capital markets respond more to the disclosure of bad news than of good news if the deterrence effect is strong, which arises if both insiders’ penalties and litigation risk are high. (iv) In an extension, we highlight real effects of litigation on corporate innovation and establish that innovation first decreases and then increases (strictly decreases) with litigation risk if insiders’ penalties are small (large). We reconcile our findings with results from a large set of U.S.-based empirical studies and make several novel predictions.
Phase angle as a marker of outcome in hospitalized pediatric patients. A systematic review of the evidence (GRADE) with meta-analysis
Authors: Fernández-Jiménez Rocío , Martín-Masot Rafael , Cornejo-Pareja Isabel , Vegas-Aguilar Isabel M. , Herrador-López Marta , Tinahones Francisco J. , Navas-López Víctor Manuel , Bellido-Guerrero Diego , García-Almeida José Manuel 
Published: July 2023

AbstractPhase angle (PhA) is a valuable tool for evaluating the nutritional and inflammatory status, which can accompany acute and severe disorders. PhA is a cellular health biomarker, whose value is particularly substantial due to the negative consequences of these situations in the pediatric population. Relevant literature was collected with the aim of comprehensively analysing the evidence on the association between an altered PhA can serve as a predictive-marker for mortality and poor-outcomes in at-risk-pediatric patients. Understanding this relationship could have significant implications for identifying high-risk individuals and implementing timely interventions. A systematic review with meta-analysis was conducted in the primary electronic databases from inception until January 2023. Overall, four studies with a total of 740 patients were eligible for our analysis. Evidence demonstrates that PhA is associated with nutritional status, reflecting undernutrition and changes in body composition related to illness. This review suggests that PhA can indeed be used as an indicator of nutritional status and a tool for predicting prognosis, including mortality and poor-outcomes, in hospitalized pediatric patients. A low PhA was associated with a significant mortality risk [RR:1.51;95%CI (1.22–1.88),p = 0.0002;I2 = 0%,(p = 0.99)] and an increased complications risk [OR:8.17;95%CI (2.44–27.4),p = 0.0007;I2 = 44%,(p = 0.18)]. These findings highlight the importance of taking a comprehensive approach to clinical nutrition, integrating multiple evaluation aspects to establish an accurate diagnosis and personalized therapeutic plans. While PhA emerges as a valuable tool for assessing the risk of malnutrition and as a prognostic-indicator for poor-outcomes in pediatric patients. Further future studies are needed to focus on investigating this relationship in larger and diverse population to strengthen the evidence base.
Graphical Abstract
Differential effects of arsenite and arsenate on rice (Oryza sativa) plants differing in glutathione S-transferase gene expression
Authors: Pandey Ambika , Wu Lin-Bo , Murugaiyan Varunseelan , Schaaf Gabriel , Ali Jauhar , Frei Michael 
Published: July 2023

AbstractContamination of paddy soils with arsenic (As) can cause phytotoxicity in rice and increase the accumulation of arsenic in grains. The uptake and accumulation of As in rice depends on the different As species present in the soil. Plants detoxify As by conjugating and sequestering xenobiotic compounds into vacuoles using various enzymes. However, the severity of damage induced by arsenite (As(III)) and arsenate (As(V)), as well as the roles of glutathione S-transferase in detoxifying these As species in rice, are not fully understood. In this study, we developed plant materials overexpressing a glutathione S-transferase gene OsGSTU40 under the control of the maize UBIL promoter. Through systematic investigations of both wild-type Nipponbare (Oryza sativa L., ssp. japonica) and OsGSTU40 overexpression lines under chronic or acute stress of As, we aimed to understand the toxic effects of both As(III) and As(V) on rice plants at the vegetative growth stage. We hypothesized that (i) As(III) and As(V) have different toxic effects on rice plants and (ii) OsGSTU40 played positive roles in As toxicity tolerance. Our results showed that As(III) was more detrimental to plant growth than As(V) in terms of plant growth, biomass, and lipid peroxidation in both chronic and acute exposure. Furthermore, overexpression of OsGSTU40 led to better plant growth even though uptake of As(V), but not As(III), into shoots was enhanced in transgenic plants. In acute As(III) stress, transgenic plants exhibited a lower level of lipid peroxidation than wild-type plants. The element composition of plants was dominated by the different As stress treatments rather than by the genotype, while the As concentration was negatively correlated with phosphorus and silicon. Overall, our findings suggest that As(III) is more toxic to plants than As(V) and that glutathione S-transferase OsGSTU40 differentially affects plant reactions and tolerance to different species of arsenic.