bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enclosing control for nonholonomic mobile agents with a moving target of unknown velocity
Authors: Ju Shuang , Wang Jing , Dou Li‐Ya 
Published: July 2023

SummaryIn this paper, an enclosing control problem is investigated for nonholonomic mobile agents with a moving target of unknown velocity. An adaptive observer containing two internal variables is first designed for each agent to compensate for the lack of the target velocity information. One variable is designed to estimate the unknown target velocity and further its estimation error is assessed by the other internal variable to subsequently guarantee the control performance. Then using the estimated information from the adaptive observer, a dynamic control law for circular formation of nonholonomic agents around the moving target is designed by a backstepping process. The global asymptotical stability of the closed‐loop system is achieved under the proposed dynamic control law with the adaptive observer. Finally, a simulation is conducted to demonstrate the effectiveness of the proposed approach.
Localized Phase Transformation Triggering Lattice Matching of Metal Oxide and Carbonate Hydroxide for Efficient CO2 Photoreduction
Authors: Yang Bixia , Jiang Xingpeng , Zheng Yanting , Zhou Linxin , Yan Jiawei , Zhuang Zanyong , Yu Yan 
Published: July 2023

AbstractOrderly heterostructured catalysts, which integrate nanomaterials of complementary structures and dimensions into single‐entity structures, have hold great promise for sustainability applications. In this work, it is showcased that air as green reagent can trigger in situ localized phase transformation and transform the metal carbonate hydroxide nanowires into ordered heterostructured catalyst. In single‐crystal nanowire heterostructure, the in situ generated and nanosized Co3O4 will be anchored in single‐crystal Co6(CO3)2(OH)8 nanowires spontaneously, triggered by the lattice matching between the (220) plane of Co3O4 and the (001) plane of Co6(CO3)2(OH)8. The lattice matching allows intimate contact at heterointerface with well‐defined orientation and strong interfacial coupling, and thus significantly expedites the transfer of photogenerated electrons from tiny Co3O4 to catalytically active Co6(CO3)2(OH)8 in single‐crystal nanowire, which elevates the catalytic efficiency of metal carbonate catalyst in the CO2 reduction reaction (VCO = 19.46 mmol g−1 h−1 and VH2 = 11.53 mmol g−1 h−1). The present findings add to the growing body of knowledge on exploiting Earth‐abundant metal‐carbonate catalysts, and demonstrate the utility of localized phase transformation in constructing advanced catalysts for energy and environmental sustainability applications.
The Third Cohomology 2-Group
Authors: Cigoli Alan S. , Mantovani Sandra , Metere Giuseppe 
Published: July 2023

AbstractIn this paper we show that a finite product preserving opfibration can be factorized through an opfibration with the same property, but with groupoidal fibres. If moreover the codomain is additive, one can endow each fibre of the new opfibration with a canonical symmetric 2-group structure. We then apply such factorization to the opfibration that sends a crossed extension of a group C to its corresponding C-module. The symmetric 2-group structure so obtained on the fibres, defines the third cohomology 2-group of C, with coefficients in a C-module. We show that the usual third and second cohomology groups are recovered as its homotopy invariants. Furthermore, even if all results are presented in the category of groups, their proofs are valid in any strongly protomodular semi-abelian category, once one adopts the corresponding internal notions.
Multi-echelon inventory optimization using deep reinforcement learning
Authors: Geevers Kevin , van Hezewijk Lotte , Mes Martijn R. K. 
Published: July 2023

AbstractThis paper studies the applicability of a deep reinforcement learning approach to three different multi-echelon inventory systems, with the objective of minimizing the holding and backorder costs. First, we conduct an extensive literature review to map the current applications of reinforcement learning in multi-echelon inventory systems. Next, we apply our deep reinforcement learning method to three cases with different network structures (linear, divergent, and general structures). The linear and divergent cases are derived from literature, whereas the general case is based on a real-life manufacturer. We apply the proximal policy optimization (PPO) algorithm, with a continuous action space, and show that it consistently outperforms the benchmark solution. It achieves an average improvement of 16.4% for the linear case, 11.3% for the divergent case, and 6.6% for the general case. We explain the limitations of our approach and propose avenues for future research.
Long-Term Impact of Historical Mining on Water Quality at Mount Lyell, Western Tasmania, Australia
Authors: Nascimento Sibele C. , Cooke David R. , Townsend Ashley T. , Davidson Garry , Parbhakar-Fox Anita , Cracknell Matthew J. , Miller Clare B. 
Published: July 2023

AbstractDuring the twentieth century, inadequate management of mine waste at the Mount Lyell Copper Mine affected the ecology of the Queen–King Rivers and Macquarie Harbour, western Tasmania, Australia. Over the past two decades, the water quality of the river system has been measured semi-annually to investigate the long-term hydrochemical and environmental impacts caused by these historical mine practices and the waste associated with the Mount Lyell mine to the Queen–King Rivers. At sample sites below the confluence of Haulage Creek, the water pH was below pH 3.5, remaining below pH 5 across all sites to Macquarie Harbour. Local baseline rivers ranged from pH 4.0 to 8.4. Elemental concentrations of dissolved metals in water samples downstream of Haulage Creek were above the Australian and New Zealand Environment and Conservation Council (ANZECC) water quality guidelines. Copper, Fe, and Zn were not attenuated along the length of the river, with concentrations remaining elevated to the King River Delta. Mineralogical analyses demonstrated secondary minerals in sediments at Haulage Creek and pyrite concentrated at the King River Delta. Static tests on mining-affected sediments indicated risk of AMD and metal(loid) leaching in the river system. Since 2016, after flooding of the Prince Lyell mine, dissolved metal levels in the Queen–King Rivers have decreased; however, concentrations remain above guidelines. Almost three decades after legacy mine waste disposal ended, it still poses a long-term risk to the downstream environment, implying that without effective management of these historical mine wastes, the Queen–King Rivers will continue to be severely impacted.
Graphical Abstract
Growth and carbon sequestration in biomass of Cordia alliodora in Andean agroforestry systems with coffee
Authors: Andrade Hernán J. , Segura Milena A. , Suárez Juan Carlos 
Published: July 2023

AbstractTimber production and carbon sequestration in trees in agroforestry systems (AFS) are key to productivity and climate change mitigation. There are no studies about dynamics of growth and carbon sequestration of Cordia alliodora during all plantation cycle. The objective of this study was to develop models for diametric growth and carbon sequestration in aboveground biomass of C. alliodora in AFS with coffee in Líbano, Tolima, Colombia. Nonlinear models of growth and carbon sequestration in aboveground biomass of C. alliodora in AFS with coffee were developed. A total of 90 trees, ranging in age from 1 to 19 years, were randomly selected in farms and measured (diameter at breast height -dbh- and total height -h) in AFS with a basal area of C. alliodora between 0.22 and 17.8 m2/ha. Timber volume and aboveground biomass were estimated with allometric models, while carbon was estimated by multiplying aboveground biomass by 0.47. The best-fit models were selected according to the coefficient of determination (R2), Akaike's information criterion (AIC), predicted residual error sum of squares (PRESS), biological logic and a residual analysis. The highest growth rate of this species was reached at 4–6 years for dbh and h (3.6 cm/year and 2.9 m/year, respectively) and at 20 years for timber and carbon (0.60 m3/tree/year and 88.9 kg C/tree/year, respectively). In 20 years, a C. alliodora tree would store 1.1 Mg C and a AFS with 60 trees/ha would sequester between 260 Mg CO2/ha in aboveground biomass. The results show that C. alliodora trees could be maintained in the field for more than 20 years, thus increasing the volume per individual and carbon sequestration for a longer time. This demonstrates the importance of this species mainly when timber production and carbon sequestration are priorities for its profitability.
Beta-glucan production of Phaeodactylum tricornutum, Monodopsis subterranea and Cylindrotheca fusiformis during nitrogen depletion
Authors: Frick Konstantin , Ebbing Tobias , Yeh Yen-Cheng , Schmid-Staiger Ulrike , Tovar Günter E. M. 
Published: July 2023

AbstractBeta-glucans are polysaccharides that can be used for different applications, for example as an immunomodulator in food or feed or for managing high cholesterol levels. Certain microalgae species use beta-glucans as energy storage, accumulating them during nutrient depletion. In this study, we examined and compared beta-glucan production during nitrogen depletion in three different algae species, Phaeodactylum tricornutum, Monodopsis subterranea and Cylindrotheca fusiformis, grown in artificially illuminated flat panel airlift reactors, in order to determine the most promising microalgae species for beta-glucan production. Co-products such as fatty acids (especially eicosapentaenoic acid) and the carotenoid fucoxanthin (not produced by M. subterranea) were also considered. Biomass analysis showed that P. tricornutum cultures reached a maximal beta-glucan content of 317 ± 9 mg gDW−1, M. subterranea cultures reached 188 ± 6 mg gDW−1 and C. fusiformis cultures reached 129 ± 13 mg gDW−1. Furthermore, beta-glucan production was faster in P. tricornutum cultures. However, the maximum volumetric beta-glucan concentration reached was higher in M. subterranea cultures compared to P. tricornutum cultures as M. subterranea cultures produced more biomass during nitrogen depletion. In terms of possible co-products, P. tricornutum produced fucoxanthin and EPA, whereas M. subterranea did not produce fucoxanthin. However, M. subterranea exhibited a higher EPA content, which remained above 45 mg g−1 even after several days of nitrogen depletion. Overall, our results suggest that P. tricornutum and M. subterranea are both suitable species for beta-glucan production in flat panel airlift reactors.
Psychosocial well-being in Long-Term Care in the Wake of COVID-19: Findings from a Qualitative Study in New Zealand
Authors: Frey Rosemary , Balmer Deborah 
Published: July 2023

AbstractDrawing on Mason Durie’s (1985) New Zealand Whare Tapa Whā model of health (spiritual, emotional, physical, and family domains), the goal was to link a model of well-being with the lived reality for long-term care residents and bereaved family members during COVID-19. Interviews were conducted with five residents and six family members of previous residents of one long-term care in one urban centre between July and September 2020. The increased demands imposed by the pandemic highlighted the gaps in well-being for residents and families. In particular, the inability to connect with family during COVID-19 restrictions reduced perceptions of well-being for residents. Study findings indicate that the provision of well-being for older adults and families in long-term care extends beyond the narrow bounds of the biomedical model. The Whare Tapa Whā model provides a valuable framework describing the holistic balance needed between the four health domains.
Real-Time Nonlinear Control Allocation Framework for Vehicles with Highly Nonlinear Effectors Subject to Saturation
Authors: Mancinelli Alessandro , Remes Bart D. W. , De Croon Guido C. H. E. , Smeur Ewoud J. J. 
Published: July 2023

AbstractHybrid Unmanned Aerial Vehicles UAV are vehicles capable of take-off and landing vertically like helicopters while maintaining the long-range efficiency of fixed-wing aircraft. Unfortunately, due to their wing area, these vehicles are sensitive to wind gusts when hovering. One way to increase the hovering wind-rejection capabilities of hybrid UAV is through the addition of extra actuators capable of directing the thrust of the rotors. Nevertheless, the ability to control UAVs with many actuators is strictly related to how well the Control Allocation problem is solved. Generally, to reduce the problem complexity, conventional (CA) methods make use of linearized control effectiveness in order to optimize the inputs that achieve a certain control objective. We show that this simplification can lead to oscillations if it is applied to thrust vectoring vehicles, with pronounced non-linear actuator effectiveness. When large control objectives are requested or actuators saturate, the linearized effectiveness based CA methods tend to compute a solution far away from the initial actuator state, invalidating the linearization. A potential solution could be to impose limits on the solution domain of the linearized CA algorithm. However, this solution only reduces the oscillations at the expense of a lag in the vehicle acceleration response. To overcome this limitation, we present a fully nonlinear CA method, which uses an Sequential Quadratic Programming (SQP) algorithm to solve the CA problem. The method is tested and implemented on a single board computer that computes the actuator solution in real time onboard a dual axis tilting rotor quad-plane. Flight test experiments confirm the problem of severe oscillations in the linearized effectiveness CA algorithms and show how the only algorithm able to optimally solve the CA problem is the presented Nonlinear method.
Measuring Moral Injury: Further Validation of the MIES-C and EMIS-C in a Civilian Population
Authors: Morriss Margaux , Berle David 
Published: July 2023

AbstractMoral injury among civilians has garnered increased recognition in recent years. However, most moral injury measures have focused on military experiences, with language being military specific. This study aimed to further validate two self-report measures of civilian moral injury, the Moral Injury Events Scale - Civilian (MIES-C) and Expressions of Moral Injury Scale - Civilian (EMIS-C). Participants were 312 adults (99 males, 212 females, Mage = 37.24) who completed the MIES-C, EMIS-C, and a battery of associated measures on two occasions. For the MIES-C, four Confirmatory Factor Analysis (CFA) models were examined. A three-factor model, with covaried items, provided the best fit to the data. For the EMIS-C, three CFAs were examined. A two-factor model, with covaried items, and the bi-factor model provided the best fit to the data, with the two-factor model being preferred for reasons of parsimony and its absence of weak and negative item loadings. Both measures demonstrated acceptable test-retest reliability and convergent validity with associated measures of psychological distress. This study provides psychometrically sound tools for clinicians and researchers of civilian moral injury.
Reinventing Patient Support and Continuity of Care Using Innovative Physician-staffed Hotline: More than 60,000 Patients Served Across 15 Medical and Surgical Specialties During the First Wave of COVID-19 Lockdown in Qatar
Authors: Arafa Mohamed , El Ansari Walid , Qasem Fadi , Al Ansari Abdulla , Al Dosari Mohammed Al Ateeq , Mukhtar Khalid , Alhabash Mohamed Ali , Awad Khalid , Al Rumaihi Khalid 
Published: July 2023

AbstractRising disease prevalence early during the COVID-19 pandemic in the State of Qatar led to stoppage of all non-emergency health care services. To maintain continuity of care and information exchanges for non-emergency patients, a physician-operated telephone hotline was set up that involved triage followed by immediate consultation with a specialized physician. We describe the initiation and evaluate the operations of the Urgent Consultation Centre (UCC) hotline manned by 150 physicians and aimed at urgent non-life-threatening consultations at Hamad Medical Corporation, the public health provider in Qatar. UCC established a hotline to triage inbound patient calls related to 15 medical and surgical specialties. For calls between April-August 2020, we describe call volume, distribution by specialty, outcomes, performance of UCC team, as well as demographics of callers. During the study period, UCC received 60229 calls (average 394 calls/day) from Qatari nationals (38%) and expatriates (62%). Maximum total daily calls peaked at 1670 calls on June 14, 2020. Call volumes were the highest from 9 AM to 2 PM. Response rate varied from 89% to 100%. After an initial telephone triage, calls were most often related to and thus directed to internal medicine (24.61%) and geriatrics (11.97%), while the least percentage of calls were for pain management and oncology/hematology (around 2% for each). By outcome of consultation, repeat prescriptions were provided for 60% of calls, new prescriptions (15%), while referrals were to outpatient department (17%), emergency department/pediatric emergency center (5%), and primary health care centres (3%). We conclude that during a pandemic, physician-staffed telephone hotline is feasible and can be employed in innovative ways to conserve medical resources, maintain continuity of care, and serve patients requiring urgent care.
High-dimensional order-free multivariate spatial disease mapping
Authors: Vicente Gonzalo , Adin Aritz , Goicoa Tomás , Ugarte María Dolores 
Published: July 2023

AbstractDespite the amount of research on disease mapping in recent years, the use of multivariate models for areal spatial data remains limited due to difficulties in implementation and computational burden. These problems are exacerbated when the number of areas is very large. In this paper, we introduce an order-free multivariate scalable Bayesian modelling approach to smooth mortality (or incidence) risks of several diseases simultaneously. The proposal partitions the spatial domain into smaller subregions, fits multivariate models in each subdivision and obtains the posterior distribution of the relative risks across the entire spatial domain. The approach also provides posterior correlations among the spatial patterns of the diseases in each partition that are combined through a consensus Monte Carlo algorithm to obtain correlations for the whole study region. We implement the proposal using integrated nested Laplace approximations (INLA) in the R package and use it to jointly analyse colorectal, lung, and stomach cancer mortality data in Spanish municipalities. The new proposal allows for the analysis of large datasets and yields superior results compared to fitting a single multivariate model. Additionally, it facilitates statistical inference through local homogeneous models, which may be more appropriate than a global homogeneous model when dealing with a large number of areas.
Efficiently computing alternative paths in game maps
Authors: Li Lingxiao , Cheema Muhammad Aamir , Ali Mohammed Eunus , Lu Hua , Li Huan 
Published: July 2023

AbstractAlternative pathfinding requires finding a set of k alternative paths (including the shortest path) between a given source s and a target t. Intuitively, these paths should be significantly different from each other and meaningful/natural (e.g., must not contain loops or unnecessary detours). While finding alternative paths in road networks has been extensively studied, to the best of our knowledge, we are the first to formally study alternative pathfinding in game maps which are typically represented as Euclidean planes containing polygonal obstacles. First, we adapt the existing techniques designed for road networks to find alternative paths in the game maps. Then, based on our web-based system that visualises alternative paths generated by different approaches, we conduct a user study that shows that the existing road network approaches generate high-quality alternative paths when adapted for the game maps. However, these existing approaches are computationally inefficient especially when compared to the state-of-the-art shortest path algorithms. Motivated by this, we propose novel data structures and exploit these to develop an efficient algorithm to compute high-quality alternative paths. that shows that the existing road network approaches generate high-quality alternative paths in game maps. Our extensive experimental study demonstrates that our proposed algorithm is more than an order of magnitude faster than the existing approaches and returns alternative paths of comparable quality. Furthermore, our algorithm is comparable to a state-of-the-art shortest path algorithm in terms of running time.
New polymeric matrix of polylactic acid/sodium alginate/carbon nanoparticles (PLA/SA/CNP) for efficient removal of methylene blue
Authors: Fathy Reem , Ragab Eman , Ali Korany A. 
Published: July 2023

AbstractFor the adsorption of methylene blue (MB), novel bio-polymeric matrices prepared from polylactic acid/sodium alginate (PLA/SA) and polylactic acid/sodium alginate/carbon nanoparticle (PLA/SA/CNP) as green adsorbates were prepared in the form of beads. The developed adsorbent was analyzed using scanning electron microscopes and Fourier transform infrared spectrometers. The percentage of adsorbed dye increased with increasing CNP content, and the optimum ratio was 5% wt. The efficiency of the beads' removal and adsorption capacity were evaluated concerning with (adsorbent dosage, contact time, initial pH, and concentration of adsorbate). After 120 min using 50 mg of PLA/SA/CNP beads, the adsorptive removal process for MB dye was determined to have the maximum rate at pH 9. The models of Langmuir and Freundlich were used to illustrate the experimental data. Langmuir models determined the highest adsorption capacity to be 304.88 mg/g.
Electroacupuncture Inhibits Pain Memory and Related Anxiety-Like Behaviors by Blockading the GABAB Receptor Function in the Midcingulate Cortex
Authors: Li Xiaoyu , Zhu Yichen , Sun Haiju , Shen Zui , Sun Jing , Xiao Siqi , He Xiaofen , Liu Boyu , Wang Yifang , Hu Yuxin , Liu Boyi , Liang Yi , Jiang Yongliang , Du Junying , Xu Chi , Fang Jianqiao , Shao Xiaomei 
Published: July 2023

AbstractPain memory is commonly considered an underlying cause of chronic pain and is also responsible for a range of anxiety. Electroacupuncture (EA) has been shown to ameliorate pain memories and exert anti-anxiety effects. Previous research has indicated that GABAergic neurons and/or GABA receptors (GABARs) in the midcingulate cortex (MCC) have potential associations with chronic pain and anxiety. However, there is no known empirical research that has specifically studied the effects of EA on the GABAergic system in the MCC. Here, we used cross-injection of carrageenan to establish the pain memory rats model. Immunofluorescence were used to detect the excitability of GABAergic neurons within MCC. Von Frey filament, elevated zero maze, and open field tests were used to measure mechanical allodynia and anxiety-like behaviors, combined with chemogenetic and pharmacologic technologies. Finally, this study provides evidence that pain memories contribute to generalized negative emotions and that downregulating the activity of GABAergic neurons within MCC could block pain memories and reverse anxiety emotion. Specifically, GABABR is involved in pain memory and related anxiety-like behaviors. Activation of GABAergic neurons in the MCC did not reverse the effects of EA on pain memories and related anxiety-like behaviors, whereas these effects could be reversed by a GABABR agonist. These findings highlight the functional significance of GABABR in the EA-mediated attenuation of pain memories and related anxiety-like behaviors in rats.