bluuebunny/crossref_metadata_2025 huggingface dataset:
Hybrid LES/RANS Simulations of Compressible Flow in a Linear Cascade of Flat Blade Profiles
Authors: Příhoda Jaromír , Straka Petr , Šimurda David , Šidlof Petr , Lepicovsky Jan
Published: July 2024

The paper reports on 3D numerical simulations of unsteady compressible airflow in a blade cascade consisting of flat profiles using a hybrid LES/RANS approach including a transition model. As a first step towards simulation of blade flutter in turbomachinery, various incidence angle offsets of the middle blade were modeled. All simulations were run for the flow regime characterized by outlet isentropic Mach number Mis=0.5 and zero incidence. The results of the LES/RANS simulations (pressure and Mach number distributions) were compared to a baseline RANS model, and to experimental data measured in a high-speed wind tunnel. The numerical results show that both methods overpredict flow separation taking place at the leading edge. In this regard, the hybrid LES/RANS method does not provide superior results compared to the traditional RANS simulations. Nevertheless, the LES/RANS results also capture vortex shedding from the blunt trailing edge. The frequency of the trailing edge vortex shedding in CFD simulations matches perfectly the spectral peak recorded during wind tunnel measurements.
Behavior of Different Ultrasonically Bonded Aluminum Heavy Wires in the Shear Test
Authors: Kuttler Simon , Wittler Olaf , Schneider-Ramelow Martin
Published: July 2024

Shear tests are known to be quick tests for heavy wire bonds to evaluate the interconnect quality. The challenge is to interpret the results of such shear tests, in terms of shear strength and the shear code defined by the German Welding Society (DVS). In this study, we aim to get a better understanding of the shear process by studying the material behavior through the shear test of heavy wire bonds. We took two different aluminum wire materials, Al H11 and AlMg0.5, and ultrasonic bonded them on 99.95% copper sheets, resulting in a good bond quality according to the DVS standard. We performed shear tests on these samples, stopping them shortly before final failure. We investigated the resulting deformed state by cross-sections and further instrumental indentation patterns in the middle of the wedge. The indentation hardness patterns revealed that Al H11 and AlMg0.5 behave significantly differently in terms of hardening under deformation. Our experiments show that the different material behavior has an influence on the failure path of the shear tests. We conclude, when comparing different materials by means of shear test results, that the outcome is influenced by the different hardening behavior.
Focusing on foundational Calculus ideas to understand the derivative concept via problem-solving tasks that involve the use of a Dynamic Geometry System
Authors: Santos-Trigo Manuel , Camacho-Machín Matías , Barrera-Mora Fernando
Published: July 2024

The aim of this paper is to review recently calculus curriculum reforms and research studies that document what types of understanding students develop in their precalculus courses. We argue that it is important to characterize what difficulties students experience to solve tasks that include the use of foundational calculus concepts and to look for possible ways for students to develop a way of reasoning to work on problems that involve variational phenomena. Thus, we identified tasks in which calculus students exhibit limited understanding of essential concepts to approach and solve those tasks. The purpose is to illustrate and discuss how the systematic use of a Dynamic Geometry System (DGS) could provide a set of affordances for students to develop ways of thinking to grasp calculus foundational ideas and to study the derivative concept. Here, we relied on Thurston’s seminal work that emphasizes the relevance for learners to identify, connect, and coordinate different dimensions and meanings (intuitive, symbolic, algorithmic, geometric, physical, and formal) to construct, understand, and apply the concept of derivative.
Sex Differences in Outcome of Aneurysmal Subarachnoid Hemorrhage and Its Relation to Postoperative Cerebral Ischemia
Authors: Yang Cheng , Zhao Zenan , Yang Biao , Wang Kaishan , Zhu Gang , Miao Hongping
Published: July 2024

Background

Whether there is a sex difference in the outcome of aneurysmal subarachnoid hemorrhage (aSAH) remains controversial, and clarifying the role of women in postoperative cerebral ischemic events can help us to understand its relationship with poor prognosis. Therefore, the purpose of this study was to elucidate the relationship between the three aspects of sex differences, postoperative cerebral ischemia, and poor prognosis after aSAH.

Methods

A total of 472 patients admitted within 72 h after aSAH between January 2018 and December 2022 were included. We systematically analyzed the characteristics of sex differences in aSAH and explored the relationship between delayed cerebral ischemia (DCI), surgery-related cerebral infarction (SRCI), and poor prognosis (modified Rankin Scale > 2).

Results

Compared with women, men were in worse condition and had more intracerebral hematoma (p = 0.001) on admission, whereas women were older (p < 0.001) and had more multiple aneurysms (p = 0.002). During hospitalization, men were more likely to experience emergency intubation (p = 0.036) and tracheotomy (p = 0.013). Women achieved functional independence at discharge at a similar rate to men (p = 0.394). Among postoperative complications, the incidence of DCI (22% vs. 12%, p = 0.01) and urinary tract infection (p = 0.022) was significantly higher in women. After adjusting for age, multivariable regression analysis showed that hypertension (odds ratio [OR] 2.139, 95% confidence interval [CI] 1.027–4.457), preoperative rerupture (OR 12.240, 95% CI 1.491–100.458), pulmonary infection (OR 2.297, 95% CI 1.070–4.930), external ventricular drainage placement (OR 4.382, 95% CI 1.550–12.390), bacteremia (OR 14.943, 95% CI 1.412–158.117), SRCI (OR 8.588, 95% CI 4.092–18.023), venous thrombosis (OR 5.283, 95% CI 1.859–15.013), higher modified Fisher grades (p = 0.003), and Hunt–Hess grades (p = 0.035) were associated with poor prognosis, whereas DCI (OR 1.394, 95% CI 0.591–3.292) was not an independent risk factor for poor prognosis. The proportion of patients who fully recovered from cerebral ischemia was higher in the DCI group (p < 0.001) compared with the SRCI group, and more patients were discharged with modified Rankin Scale > 2 in the SRCI group (p = 0.005).

Conclusions

Women have a higher incidence of DCI, but there is no sex difference in outcomes after aSAH, and poor prognosis is associated with worse admission condition and perioperative complications. SRCI is a strong independent risk factor for poor prognosis, whereas DCI is not.
Management and treatment of severe immune-related hepatotoxicity based on clinical and pathological characteristics
Authors: Zhang Nan , Li Zhaohui , Liu Yutao , Shi Xiaohua , Shi Di , Li Yue , Si Xiaoyan , Xun Ziyu , Shao Jing , Zhao Haitao , Wang Hanping
Published: July 2024

Background

The management of severe immune-related hepatotoxicity (irH) needs to be further optimized. This study aims to analyze the clinical characteristics of severe irH; improve the therapeutic strategy, especially salvage treatment in steroid-refractory irH; and determine the safety of immune checkpoint inhibitor (ICPi)-rechallenge.

Methods

This multicenter retrospective study included patients who developed severe irH and those without irH after immunotherapy between May 2019 and June 2023. Propensity score matching was used to match these two cohorts with similar baseline characteristics.

Results

Among 5,326 patients receiving ICPis, 51 patients developed severe irH. irH occurred after a median duration of 36 days and a median of two doses after the first ICPi administration. Patients receiving PD-L1 inhibitors faced a lower risk of developing severe irH. A higher dose of glucocorticoids (GCS) was administered to grade 4 irH than grade 3 irH. For steroid-sensitive patients, grade 4 irH individuals received a higher dosage of GCS than those with grade 3 irH, with no difference in time to resolution. Meanwhile, a significantly higher dose of GCS plus immunosuppression was needed in the steroid-refractory group. Liver biopsy of the steroid-refractory patients exhibited heterogeneous histological features. Twelve patients were retreated with ICPi. No irH reoccurred after a median follow-up of 9.3 months.

Conclusion

irH requires multidimensional evaluation. PD-L1 inhibitors correlated with a lower risk of severe irH. Grade 4 irH demands a higher dose of GCS than recommended. Pathology may guide the salvage treatment for steroid-refractory irH. ICPi rechallenge in severe irH is feasible and safe.
Integrated pan-cancer and scRNA-seq analyses identify a prognostic coagulation-related gene signature associated with tumor microenvironment in lower-grade glioma
Authors: Wen Xuehuan , Bai Songjie , Fang Zuochun , Zhu Weiguo
Published: July 2024

Cancer-associated thrombosis is a significant complication in cancer patients, leading to increased morbidity and mortality. The expression of coagulation/fibrinolysis genes, termed the "coagulome", plays a critical role in this process. Using the single-sample gene set enrichment analysis (ssGSEA), we identified seven cancer types with significantly activated coagulation pathways, focusing on lower-grade glioma (LGG) and stomach adenocarcinoma due to their predictive value for overall survival. Through 1000 iterations of the Least Absolute Shrinkage and Selection Operator (LASSO), we selected prognostic genes and constructed effective Cox regression models, particularly for LGG. Incorporating clinical characteristics, we constructed a nomogram for LGG, achieving an impressive area under the curve (AUCs) of 0.79, 0.82, and 0.81 at 1, 3, and 5 years in the test dataset, indicating strong potential for clinical application. Functional enrichment analysis between high-risk and low-risk LGG groups revealed significant enrichment of genes involved in the inflammatory response, interferon-gamma response, and epithelial-mesenchymal transition pathways. Combined with CIBERSORT and single-cell RNA sequencing analysis of LGG, our results demonstrated that the interplay between coagulation and the tumor microenvironment, particularly involving gliomas and myeloid cells, significantly influences tumor progression and patient outcomes.
Mitigation of Greenhouse Gas Emissions by Optimizing Groundwater Level in Boreal Cultivated Peatland
Authors: Heikkinen Jaakko , Lång Kristiina , Honkanen Henri , Myllys Merja
Published: July 2024

Optimizing the level of groundwater presents a viable strategy for mitigating the greenhouse gas (GHG) emissions associated with the cultivation of peatlands. This study investigated the impact of soil hydrological conditions on carbon dioxide (CO2) and methane (CH4) emissions. The CO2 and CH4 emissions from bare soil were continuously measured using an automated chamber system throughout the growing seasons from 2021 to 2023 at a boreal cultivated peat soil site. Annual CO2 emissions from soil respiration averaged to 21,600 kg ha-1 (April-November) corresponding to carbon (C) loss of 5890 kg ha-1. The CO2 emissions were highly temperature dependent. Lowering the groundwater level (GWL) was found to increase the CO2 emissions nearly linearly. The soil functioned as a CH4 sink for the majority of the growing season, and the total sink corresponded to 27 and 20 kg ha-1 yr-1 CO2 equivalent in 2022 and 2023, respectively. The CH4 emissions occurred generally when soil water content (SWC) exceeded 0.6 m3 m-3 and when GWL was at the depth of less than 30 cm from soil surface. For optimal climate efficiency the mitigation measures must be implemented during the mid-growing season, and the water table should be brought close to the soil surface. Potentially, this can hamper the operation of machinery on the field and reduce the harvested yield. Thus, comprehensive cost-benefit analysis is necessary before adopting a raised water table level in large-scale crop production.
A Comprehensive Density Functional Theory Analysis on Structural, Electronic, and Optical Properties of BiOF
Authors: Boran Yakup , Kara Hüsnü
Published: July 2024

Based on density functional theory (DFT), the electronic, structural, and optical properties of bismuth oxyfluoride (BiOF) are investigated by using various exchange–correlation functionals. The local density approximation (LDA), Perdew-Burke-Ernzerhof generalized gradient approximation (PBE-GGA), Perdew-Burke-Ernzerhof generalized gradient approximation for solids (PBEsol), and Wu-Cohen (WC) functionals are implemented in Wien2k software. Modified Becke-Johnson (mBJ) and unmodified Becke-Johnson (umBJ) potentials are also applied to obtain an enhanced band gap. Spin–orbit coupling effect (SOC) is also taken into consideration due to the heavy Bi atom. When employing the PBE+umBJ potential, BiOF exhibits the most enhanced band gap energy, with a direct band gap energy of 3.72 eV. Moreover, optical properties such as dielectric functions, absorption coefficients, and optical conductivities are also calculated for photon energies up to ̴̴ 14 eV. In comparison to other available theoretical and experimental findings, the calculated results are in good agreement.
Relative tilting theory in abelian categories I: Auslander–Buchweitz–Reiten approximations theory in subcategories and cotorsion-like pairs
Authors: Argudín-Monroy Alejandro , Mendoza Hernández Octavio
Published: July 2024

In this paper, we introduce a special kind of relative (co)resolutions associated with a pair of classes of objects in an abelian category $$\mathcal {C}.$$

C
.

We will see that, by studying this relative (co)resolutions, we get a possible generalization of a part of the Auslander–Buchweitz approximation theory that is useful for developing n-$$\mathcal {X}$$
X
-tilting theory in Argudin Monroy and Mendoza Hernández (relative tilting theory in abelian categories II: n-$$\mathcal {X}$$
X
tilting theory. arXiv:2112.14873, 2021). With this goal, new concepts as $$\mathcal {X}$$
X
-complete and $$\mathcal {X}$$
X
-hereditary pairs are introduced as a generalization of complete and hereditary cotorsion pairs. These pairs appear in a natural way in the study of the category of representations of a quiver in an abelian category (Argudin Monroy and Mendoza Hernández in categories of quiver representations and relative cotorsion pairs. arXiv:2311.12774v1, 2023). Our main results will include an existence theorem for relative approximations, among other results related with closure properties of relative (co)resolution classes and relative homological dimensions which are essential in the development of n-$$\mathcal {X}$$
X
-tilting theory in Argudin Monroy and Mendoza Hernández (2021).
Model inductive bias enhanced deep reinforcement learning for robot navigation in crowded environments
Authors: Chen Man , Huang Yongjie , Wang Weiwen , Zhang Yao , Xu Lei , Pan Zhisong
Published: July 2024

Navigating mobile robots in crowded environments poses a significant challenge and is essential for the coexistence of robots and humans in future intelligent societies. As a pragmatic data-driven approach, deep reinforcement learning (DRL) holds promise for addressing this challenge. However, current DRL-based navigation methods have possible improvements in understanding agent interactions, feedback mechanism design, and decision foresight in dynamic environments. This paper introduces the model inductive bias enhanced deep reinforcement learning (MIBE-DRL) method, drawing inspiration from a fusion of data-driven and model-driven techniques. MIBE-DRL extensively incorporates model inductive bias into the deep reinforcement learning framework, enhancing the efficiency and safety of robot navigation. The proposed approach entails a multi-interaction network featuring three modules designed to comprehensively understand potential agent interactions in dynamic environments. The pedestrian interaction module can model interactions among humans, while the temporal and spatial interaction modules consider agent interactions in both temporal and spatial dimensions. Additionally, the paper constructs a reward system that fully accounts for the robot’s direction and position factors. This system's directional and positional reward functions are built based on artificial potential fields (APF) and navigation rules, respectively, which can provide reasoned evaluations for the robot's motion direction and position during training, enabling it to receive comprehensive feedback. Furthermore, the incorporation of Monte-Carlo tree search (MCTS) facilitates the development of a foresighted action strategy, enabling robots to execute actions with long-term planning considerations. Experimental results demonstrate that integrating model inductive bias significantly enhances the navigation performance of MIBE-DRL. Compared to state-of-the-art methods, MIBE-DRL achieves the highest success rate in crowded environments and demonstrates advantages in navigation time and maintaining a safe social distance from humans.
A novel BWM-entropy-COPRAS group decision framework with spherical fuzzy information for digital supply chain partner selection
Authors: Gao Kai , Liu Tingting , Rong Yuan , Simic Vladimir , Garg Harish , Senapati Tapan
Published: July 2024

The transformation and upgrading of traditional supply chain models through digital technology receive widespread attention from the fields of circular economy, manufacturing, and sustainable development. Enterprises need to choose a digital supply chain partner (DSCP) during the process of digital transformation in uncertain and sustainable environments. Thus, the research constructs an innovative decision methodology for selecting the optimal DSCP to achieve digital transformation. The proposed methodology is propounded based upon the entropy measure, generalized Dombi operators, integrated weight-determination model, and complex proportional assessment (COPRAS) method under spherical fuzzy circumstances. Specifically, a novel entropy measure is proposed for measuring the fuzziness of spherical fuzzy (SF) sets, while generalized Dombi operators are presented for fusing SF information. The related worthwhile properties of these operators are discussed. Further, an integrated criteria weight-determination model is presented by incorporating objective weights obtained from the SF entropy-based method and subjective weights from the SF best worst method. Afterward, an improvement of the COPRAS method is proposed based on the presented generalized Dombi operators with SF information. Lastly, the practicability and validity of the proposed methodology are verified by an empirical study that selects an appropriate DSCP for a new energy vehicle enterprise to finish the goal of digital transformation. The sensitivity and comparative analysis are carried out to illustrate the stability, reliability, and superiority of the propounded methodology from multiple perspectives. The results and conclusions indicate that the propounded method affords a synthetic and systematic uncertain decision-making framework for identifying the optimal DSCP with incomplete weight information.
KnowledgeNavigator: leveraging large language models for enhanced reasoning over knowledge graph
Authors: Guo Tiezheng , Yang Qingwen , Wang Chen , Liu Yanyi , Li Pan , Tang Jiawei , Li Dapeng , Wen Yingyou
Published: July 2024

Large language models have achieved outstanding performance on various downstream tasks with their advanced understanding of natural language and zero-shot capability. However, they struggle with knowledge constraints, particularly in tasks requiring complex reasoning or extended logical sequences. These limitations can affect their performance in question answering by leading to inaccuracies and hallucinations. This paper proposes a novel framework called KnowledgeNavigator that leverages large language models on knowledge graphs to achieve accurate and interpretable multi-hop reasoning. Especially with an analysis-retrieval-reasoning process, KnowledgeNavigator searches the optimal path iteratively to retrieve external knowledge and guide the reasoning to reliable answers. KnowledgeNavigator treats knowledge graphs and large language models as flexible components that can be switched between different tasks without additional costs. Experiments on three benchmarks demonstrate that KnowledgeNavigator significantly improves the performance of large language models in question answering and outperforms all large language models-based baselines.
Numerical investigation of laser powder bed fusion of glass
Authors: Datsiou Kyriaki Corinna , Ashcroft Ian
Published: July 2024

Additive manufacturing of glass using laser powder bed fusion has been recently developed, demonstrating its potential to be applied in small scale applications such as flow reactors for the chemical engineering and pharmaceutical manufacturing industries. While previous research demonstrated that complex 3-dimensional shapes can be manufactured, built parts are often brittle, exhibit high porosity and lack transparency. This study employs a transient, heat transfer finite element analysis to shed light on the thermal response of laser—glass powder bed interaction and the impact of processing parameters. Through this understanding, the research seeks to identify practical strategies that can be employed to improve the quality and properties of the built parts. Bulk solid and powder soda lime silica glass properties are used as input in the model, while the laser heat flux and scan strategy, conversion of powder feedstock to bulk solid glass and heat losses from convection and radiation effects are introduced in the model through Fortran coding. The study showed that effective powder consolidation, resulting in well-defined geometrical features, is achieved for temperatures near the glass melting point. Additionally, uniform consolidation depths and widths can be achieved by increasing laser power, elevating substrate temperature and reducing scan speed within certain limits, whilst ensuring hatch spacing is below the corresponding single scan track width for unidirectional adjacent laser trajectories.
„Was hast du damit gemeint?“. Mittels Fragen explanative und argumentative Diskurse im schülergeleiteten Klassenrat ermöglichen
Authors: Kreuz Judith , Müller Lee Ann
Published: July 2024

Der Beitrag beschäftigt sich mit den zentralen Praktiken des Fragens, Erklärens und Argumentierens im schülergeleiteten Klassenrat der Primarschule. Der Klassenrat ist ein schulisches Unterrichtssetting, das darauf abzielt, den Schülerinnen und Schülern (Mit‑)Verantwortung für die Gestaltung ihrer Klassengemeinschaft zu übergeben und sie darüber hinaus in ihren sozialen und sprachlichen Kompetenzen zu fördern. Eine wichtige Instanz stellt die Gesprächsleitung dar, da ihr die Aufgabe zuteil wird, das Gespräch zu steuern, das Rederecht zu verteilen und Partizipationsmöglichkeiten für ihre Mitschülerinnen und Mitschüler zu schaffen. Dabei können Fragen, die einerseits Informationen und andererseits Meinungen der Beteiligten einfordern, eine wichtige Rolle für die Realisierung dieser Aufgabe spielen. Der Beitrag geht anhand zweier Beispiele aus einem videografierten Längsschnitt empirisch den Fragen nach, welche Fragearten und -formen die Gesprächsleitenden verwenden, um die Mitschülerinnen und Mitschüler ko-konstruktiv in die Diskussionsrunden einzubinden (quantitativer Zugang mittels Codierungen) und welche Möglichkeiten die Schülerinnen und Schüler ergreifen, um Sachverhalte zu klären oder eigene Meinungen einzubringen (qualitativer Zugang mittels Gesprächsanalyse). Sowohl für diese explanativen als auch die argumentativen Äußerungen zeigt sich in freien Diskussionen („Kernphase“) eine hohe wechselseitige Orientierung an den Beiträgen anderer, die sich turnübergreifend im ko-konstruierten Erklären und explorativen Argumentieren niederschlägt. In routinisierten Diskussionsphasen hingegen, werden Beiträge eher solistisch hervorgebracht. Das gemeinsame Diskutieren verlangt Diskurskompetenzen auf Kontextualisierungsebene (z. B. Erkennen konditioneller Relevanzen zum Erklären), Vertextungsebene (z. B. Präzisierungen der Erkläraktivitäten anderer) und Markierungsebene (z. B. Verwendung von „weil“-Begründungen), welche das diskurserwerbsförderliche Potenzial von kindergeleiteten Klassenräten in Abhängigkeit verschiedener Rollen (z. B. Gesprächsleitung) und Themen (z. B. Konfliktlösung, Bestimmung eines neuen Klassenziels) unterstreichen.
A Flexural Ultrasonic Transducer for Inducing Acoustic Cavitation on Material Surfaces
Authors: Sugita Naohiro , Yamamoto Shinya , Tomioka Keita , Shinshi Tadahiko
Published: July 2024

Purpose

This paper proposes a flexural ultrasonic transducer specifically designed for surface treatment of materials with delicate surfaces such as skin by acoustic cavitation at low frequencies. The goal of this preliminary study is to assess the resonance frequencies and the output sound pressure of the proposed transducer and confirm generation of acoustic cavitation on the surface of an artificial skin phantom.

Methods

A transducer prototype was designed based on structural-acoustic simulation and fabricated. The proposed design employs a concave-shaped acoustic resonator with a spherical cavity, which is driven by flexural vibration of a piezoelectric ceramic disk actuator. The transducer prototype has compact dimensions of 15 mm in diameter and 8 mm in axial length, working at frequencies around flexural vibration modes of the piezoelectric disk with a thickness of 1 mm.

Results

The maximum sound pressure amplitude reached 125 kPa with an input voltage amplitude of 10 V at the second resonance frequency of 167 kHz, where the third axisymmetric eigenmode was excited. Despite enhancing the maximum pressure, the sound pressure outside the resonator attenuates because the near-field distance of the irradiated sound wave is smaller than the height of the resonator. This implies that the proposed method provides the cavitation effect on material surfaces, possibly minimizing the side effect of ultrasound irradiation on the underlying structure. Cavitation generation on a urethane gel surface was directly observed by using a high-speed video camera.

Conclusion

We confirmed that acoustic cavitation was generated and propelled to the target surface. It concludes that ultrasound irradiation using the proposed ultrasonic transducer could be a promising alternative for effective and safe ultrasound treatment of material surfaces.
Virtual Reality in Education and the Co-construction of Immediacy
Authors: Forsler Ingrid
Published: July 2024

Virtual reality (VR) in educational settings is often promoted by commercial actors as a way to experience environments outside the classroom and a soon-to-be part of everyday teaching and learning. This study follows the development of an educational software package in a Swedish municipality that combines VR technology with 360° live footage from museums and science centers to enable students to visit these spaces from the classroom via their headsets. By focusing on the workarounds and configurations intuitively performed by teachers, students, museum staff, and technicians in this pilot project, different kinds of articulation work performed to make the technology fit with local conditions are identified, from hands-on repair and maintenance to the facilitation of interaction and presence. The collective effort put into making the technology disappear and create a feeling of unmediated experience or immediacy shows how global imaginaries about VR as an immersive technology are enacted by the participants, at the same time as the work put into the project made them challenge the idea of VR as a new everyday technology. This tension between the desire for immediacy and the hands-on work in the physical environment that goes into fulfilling these imaginaries points to the need for local production of educational technologies that recognizes their co-constructive, embodied, and situated nature.
Determination of the levels of selected essential and toxic metals in soil collected from the flower farm in Roshara Roses PLC (Bishoftu) of Ethiopia and assessment of associated human health risks
Authors: Desalegn Elizabeth , Getachew Negash , Tesfaye Gizaw , Tessema Merid
Published: July 2024

The overuse of pesticides and fertilizers to grow high-quality roses unintentionally introduces heavy metals into the soil which is detrimental to the human health. Thus, the aim of the current study is to examine the concentrations of the essential (Ca, Mg, Zn, Fe, Cu, Fe, Mn and Ni) and toxic metals (Cd and Pb) in the soil samples from the flower farm using Flame atomic absorption spectrometry (FAAS) and to assess the risk that heavy metals pose to human health. To obtain an optimum condition for the wet digestion of soil samples, the volume ratio of reagents, reflux time and temperature were optimized. The concentrations of Ca, Fe, Mn, Mg, Zn, Cr, Ni, Cu were found to be 3468, 4926, 450, 255, 74, 70,48.5 and 25 and 2150, 4862,472, 241, 71, 58, 37 and 12.5 mg/kg for the soil samples collected from the flower farm and road side, respectively. Cadmium and lead were not detected in the studied soil samples. Statistical analysis of variance (ANOVA) showed the concentrations of Ca and Cu in the two soil samples are significantly different. Correlation analysis showed there was strong positive association for Fe with Zn, Cr and Ni, Mg with Ca, Cu, Ni and Cr, Zn with Cr and Cu and Ni with (Cu, Zn and Cr). Values of hazard quotient (HQ) and hazard index (HI) for the heavy metals under the study in the all exposure pathways are below 1.0 indicating that none of them could be harmful to human health.
Research on reasonable coal pillar staggered distance in shallow multi-seam mining
Authors: Wang Qingxiong , Huang Qingxiang , He Yanpeng , Fan Dongling , Chen Sushe , Wang Wei
Published: July 2024

In shallow buried closely spaced multi-seam mining in Jurassic Coalfield in western China, due to specific reasons, it is inevitable that the lower and upper coal seam working faces and coal pillars are overlapped, resulting in stress concentration, uneven subsidence of the ground surface, the deformation and damage of the roadway intensified. In order to decrease surface damage and stress concentration, combined with physical simulation, engineering practices and theoretical analyses, reasonable coal pillar staggered distance in shallow multi-seam mining is investigated. The evolution properties of three-field (stress field, displacement field and fracture field) based on coal pillar staggered distance (CPSD) were analyzed, the determination method of rational CPSD was put up. Research findings reveal that concentrated stress results from upper and lower pillar stress superposition, and the lower pillar should be arranged in the low-stress zone. Through rational pillar arrangement, the uneven subsidence of surface is reduced, and the concentrated fractures of overlying strata and surface are decreased. For No. 1–2 and No. 2–2 coal seam mining, as CPSD is increased, subsidence above the upper coal pillar increases and the uneven subsidence of surface decreases, the concentrated stress reduced by 25%, the width of surface fractures reduced 81.1%. Consequently, rational CPSD on the basis of coupling control of three-field can be determined, the reasonable CPSD is 40–55 m. It can provide a method to realize underground safe mining and ground surface green mining in shallow multi-seam mining.
Explainable artificial intelligence and machine learning algorithms for classification of thyroid disease
Authors: Kumari Priyanka , Kaur Baljinder , Rakhra Manik , Deka Aniruddha , Byeon Haewon , Asenso Evans , Rawat Anil Kumar
Published: July 2024

A common endocrine issue affecting millions globally is thyroid illness. For this ailment to be effectively treated and managed, an early and accurate diagnosis is essential. Machine learning algorithms have attracted a lot of attention recently in the healthcare industry and have the potential to improve thyroid disease diagnosis and categorization. The implementation of machine learning methods for the classification of thyroid disease is presented in this study. To create predictive models, the study makes use of a dataset that includes a variety of thyroid-related factors, including age, gender, and hormone levels. To evaluate the effectiveness of several machine learning techniques in classifying thyroid diseases, including random forest, support vector machines, XG-Boost, and ensemble classifier, they are implemented and compared. To ensure robust model performance, the methodology includes data preparation, feature selection, and model training, as well as strategies for hyperparameter adjustment and cross-validation. To assess the algorithms’ efficiency in differentiating between several thyroid illness classifications, such as hyperthyroidism, hypothyroidism, and the study measures the algorithms’ accuracy, precision, recall, F1-score, voting, and area under the ROC curve.
Predictive Assessment of the Interior Quality of Apartments Based on Multimodal Data with Variable Visual Input
Authors: Despotovic Miroslav , Stumpe Eric , Brunauer Wolfgang A. , Lehner Matthias , Zeppelzauer Matthias
Published: July 2024

Multimodal analyses in the context of automated real estate valuation (AVM) offer the possibility of enriching the models with additional information, which benefits the accuracy of the models. However, this variety of data can overwhelm common machine learning models, which generally only process certain data modalities and only a fixed data quantity. This leads to a bottleneck in information processing, as in many cases much more information is available per observation, of which only a single selection or sample is used to train the algorithm and the remaining information is disregarded. We propose a multimodal network architecture that incorporates both textual and visual inputs and fuses their information. Furthermore, we introduce a training strategy that can take advantage of a variable number of input images for each real estate object. In our experiments, we test and compare several unimodal (baseline) models with our multimodal architecture. Our approach shows several advantages in terms of model performance over unimodal approaches. The results show the best performance for the multimodal model with a variable number of visual inputs, as well as improved prediction for the underrepresented classes of indoor quality, mitigating the effects of unbalanced data. With the presented approach, which efficiently combines and merges multiple data modalities, we have shown how such a method can be easily adapted to an AVM for the extraction of supplementary information.
A new approach to the similarity problem
Authors: Papapetros E.
Published: July 2024

We say that a $$C^*$$

C
∗

-algebra $${\mathcal {A}}$$
A
satisfies the similarity property ((SP)) if every bounded homomorphism $$u: {\mathcal {A}}\rightarrow {\mathcal {B}}(H),$$

u
:
A
→
B
(
H
)
,

where H is a Hilbert space, is similar to a $$*$$

∗

-homomorphism and that a von Neumann algebra $${\mathcal {M}}$$
M
satisfies the weak similarity property ((WSP)) if every $$\textrm{w}^*$$

w
∗

-continuous, unital and bounded homomorphism $$\pi : {\mathcal {M}}\rightarrow {\mathcal {B}}(H),$$

π
:
M
→
B
(
H
)
,

where H is a Hilbert space, is similar to a $$*$$

∗

-homomorphism. The similarity problem is known to be equivalent to the question of whether every von Neumann algebra is hyperreflexive. We improve on that by introducing the following hypothesis (EP): Every separably acting von Neumann algebra with a cyclic vector is hyperreflexive. We prove that under (EP), every separably acting von Neumann algebra satisfies (WSP) and we pass from the case of separably acting von Neumann algebras to all $$C^*$$

C
∗

-algebras.
Rigidity of Volterra-type integral operators on Hardy spaces of the unit ball
Authors: Miihkinen Santeri , Pau Jordi , Perälä Antti , Wang Maofa
Published: July 2024

We establish that the Volterra-type integral operator $$J_b$$

J
b

on the Hardy spaces $$H^p$$

H
p

of the unit ball $${\mathbb {B}}^n$$

B

n

exhibits a rather strong rigid behavior. More precisely, we show that the compactness, strict singularity and $$\ell ^p$$

ℓ
p

-singularity of $$J_b$$

J
b

are equivalent on $$H^p$$

H
p

for any $$1 \le p < \infty $$

1
≤
p
<
∞

. Moreover, we show that the operator $$J_b$$

J
b

acting on $$H^p$$

H
p

cannot fix an isomorphic copy of $$\ell ^2$$

ℓ
2

when $$p \ne 2.$$

p
≠
2
.
National assessment of regional sustainability across the United States
Authors: Chapman Eric , Carter Maddison , Harvey Jada , Hatch Ashley , Lucero Clara , Rogers Lauren
Published: July 2024

Industrial agriculture, climate change, biodiversity loss, global conflict, and increasing inequality undermine the life-supporting services provided by our planet. Recently, the global community has started developing frameworks aimed at averting a climate catastrophe. Global agreements are undoubtedly instrumental in providing humanity with a roadmap for sustainable transformation, but policies to affect national and regional change are needed. Here, we argue that regional sustainable transformation is an actionable way to work toward global sustainability. We used the Doughnut Model (DM) and compiled a database of 8 ecological ceiling metrics and 12 social foundation metrics to assess regional sustainability across 32 metro areas and 180 counties in the United States representing roughly 35% of the US population. Using targeted keywords, we reviewed county-level websites to assess to what extent urban and rural counties collaborate on regional sustainable transformation. Finally, we provide two case studies of regional sustainable transformation across urban and rural regions. We found that generally urban areas had lower social foundation deficits (6 of 12 metrics) and higher ecological ceiling overshoot (3 of 8 metrics) compared to rural areas. We also found low levels (16 out of 180 counties) of cross county collaboration between urban and rural counties for sustainability transformation. Disparities across and between urban and rural areas highlight the potential for cross county collaborative programming to increase regional sustainability. We end with a call for increased collaboration between private and public sectors focused on sustainable transformation and increased cross-county collaboration between urban and rural areas.
Extending the shelf-life of refrigerated chicken fillets by using polymeric coating layer composed of ginger Zingiber officinale essential oil loaded-chitosan nanoparticles
Authors: Musalem Safa , Hamdy Mounir Mahmoud , Mashaly Mohamed Mahmoud , Kamoun Elbadawy A. , Malak Nermeen Makram Louis
Published: July 2024

This study aims to evaluate the effect of coating chicken fillets with chitosan nanoparticles (CHN) loaded with ginger (Zingiber officinale) essential oil (GEO) on sensory characteristics, microbiological safety, and deterioration criteria; refrigerated at 4 °C. Furthermore, to determine whether different coatings could increase the storage period of chilled chicken fillets. Consequently, about 6 kg of chicken fillet were equally distributed into six groups. The first group being control (C), the second and third groups being ginger essential oil 0.5% (GEO 0.5%) and 1% (GEO 1%), the fourth group being chitosan nanoparticles alone (NCH 1%), the fifth and sixth groups were chitosan nanoparticles loaded with ginger essential oil 0.5% (NCHGO 0.5%), and 1% (NCHGO 1%). All groups were examined on the initial day of treatment (0-day) and every 4 days until the visible deterioration process appeared in each group. Results revealed that, coating chicken fillet with chitosan nanoparticles and ginger essential oil (NCHGO 1%) produced a powerful synergetic effect during refrigerated storage, as it could significantly inhibit microbial growth, decrease the rate of fat and protein deterioration, and improve sensory attributes. Interestingly, coated chicken fillet in refrigerator could last 28 days instead of 4 days. Ginger loaded-chitosan nanoparticles were employed to produce edible coatings as an efficient natural preservative and flavoring agent in poultry processing.
Regional variation in access to and quality of acute stroke care: results of Germany’s Health System Performance Assessment pilot, 2014–2020
Authors: Hengel P. , Nimptsch U. , Blümel M. , Achstetter K. , Busse R.
Published: July 2024

Background

Health System Performance Assessments (HSPA) and analyses of unwarranted regional variation in health care both aim at identifying strengths and weaknesses of health systems to improve care. Applying HSPA’s conceptual approach of interrelated health system dimensions (e.g., access, quality) to regional levels might help to better understand variation in care to reduce inequity and improve performance.

Methods

We use four indicators identified and analysed in a pilot study for a German HSPA to assess variation in access to and quality of acute stroke care between Germany’s 16 federal states and urban vs. rural regions from 2014 to 2020. Stroke unit (SU) density, share of the population reaching a SU within 30 min by car, share of inpatient stroke cases treated in a hospital with a SU, and inpatient mortality were computed based on hospital quality reports and discharge data covering all acute care hospitals. Inpatient mortality was adjusted for age, sex, stroke type, and comorbidities.

Results

About 500 SU were identified, i.e., 2.0 per 1,000 inpatient stroke cases. Almost 95% of Germans could reach a SU hospital within 30 min (rural: 90%; urban: 99%; > 88% in all states but one). The share of inpatient stroke cases treated in a SU hospital increased to 93% with a decreasing span between rural (92%) and urban (95%) regions and between states (74–98%). Inpatient mortality stagnated around 8.5% and increased to 9.0% in 2020 (rural: 8.7%; urban: 9.2%; states: 7.0–9.7%, one outlier of 13.3%).

Conclusions

The results especially revealed varying performance patterns in access to and quality of acute stroke care between the federal states, indicating different areas for improvement which might be addressed by more targeted policy measures in the future.
Land development and planning laws in ghana: the historical perspective
Authors: Zakaria Yakubu A. , Akolgo-Azupogo Helen , Soale Joseph
Published: July 2024

This article examines Ghana's land development and planning laws from a historical perspective. The methodology involves a documentary study of historical records to explore the evolution of these laws, spanning from the colonial period to the present. Through this approach it sheds light on significant milestones such as the 1988 local government changes, the land use decree's implementation by military juntas, and the identified deficiencies in the decree pertaining to physical planning. The expositions from this study show that Ghana has over the years adopted many land development and planning laws, that there is a visible demand for land among people and a desire by developers to use their land. The topic of planning is thus a significant area for stakeholders in Ghana. The study, therefore, recommends that, given the fact that land development and planning laws are here to stay, and that people are the primary drivers of social change, these laws should respect the culture and norms of the people, and should as well always incorporate active public engagement for stakeholders to feel a sense of ownership and belongingness in the entire process.
A novel experimental method for determination of forming limits with generalized non-planar stress state using hydro-assisted incremental forming
Authors: Fatemi Afshin , Mollaei Dariani Bijan
Published: July 2024

Several studies have explored analytically predicting forming limits in processes like hydroforming and incremental forming, yet there’s a lack of discussion on effective experimental methods. This paper introduces hydro-assisted incremental forming (HAIF) as a hybrid technique combining incremental forming and hydromechanical deep drawing, resulting in improved formability through simultaneous application of normal and through-thickness stresses. A novel test method is devised based on this process, and forming limits are assessed through both experimental and finite element approaches. The authors' earlier analytical forming limit predictions are scrutinized using experimental tests and simulations, revealing a good match. The study reaffirms that the application of normal and through-thickness stresses enhances formability across various strain paths, especially in plane strain mode.
Content annotation in images from outdoor construction jobsites using YOLO V8 and Swin transformer
Authors: Farahat Layan , Rezazadeh Azar Ehsan
Published: July 2024

Digital visual data, such as images and videos, are valuable sources of information for various construction engineering and management purposes. Advances in low-cost image-capturing and storing technologies, along with the emergence of artificial intelligence methods have resulted in a considerable increase in using digital imaging in construction sites. Despite these advances, these rich data sources are not typically used to their full potential because they are processed and documented subjectively, and several valuable contents could be overlooked. Semantic content analysis and annotation of the images could enhance retrieval and application of the relevant instances in large databases. This research proposes an ensemble approach to use deep learning-based object recognition, pixel-level segmentation, and text classification for medium-level (ongoing activities) and high-level (project type) annotation of still images from various outdoor construction scenes. The proposed method can annotate images with and without construction actors, i.e. equipment and workers. The experimental results have shown the potential of this approach in annotating construction activities with an 82% overall recall rate.