Miracle-dz/UniFAR-FTUs huggingface dataset:
Expert Systems With Applications

This article introduces a novel collaborative optimal motion planning framework for parallel aerial 3D printing. The proposed novel framework is efficiently capable of handling conflicts between the utilized Unmanned Aerial Vehicles (UAVs), as they follow predefined paths, allowing for a seamless enhancement of aerial 3D printing capabilities by employing multiple UAVs to collaborate in a parallel printing process. The established approach ingeniously formulates UAVs’ motion planning as a multi-constraint optimization problem, ensuring minimal adjustments to their velocities within specified limits. This guarantees smooth and uninterrupted printing while preventing collisions and adhering to the requirements of aerial printing. To substantiate the effectiveness of our proposed motion planning algorithm, an extensive array of simulation studies have been undertaken, encompassing scenarios where multiple UAVs engage in the fabrication of diverse construction shapes. The overall novel concept is being extensively validated in simulations, while the obtained results promise for enhancing the viability and advancing the landscape of aerial additive manufacturing.
Sparklinglight Transactions on Artificial Intelligence and Quantum Computing

Prediction of vehicle breakdowns in commercial vehicles is of utmost importance to ensure the safety, reliability, and cost-effectiveness of road transport. In today's fast-paced and competitive business landscape, the smooth operation of commercial vehicles is crucial for ensuring efficient logistics and supply chain management. Unplanned breakdowns of commercial vehicles can lead to significant financial losses, delays in delivery schedules, and potential damage to the reputation of the transportation companies. Commercial vehicle breakdowns pose significant challenges to both fleet operators and the broader transportation industry. The unexpected failure of a commercial vehicle can result in substantial costs, operational disruptions, and safety hazards. In light of these considerations, the development of effective breakdown prediction models has become an essential endeavor. Predicting when and why a breakdown might occur not only allows for proactive maintenance but also minimizes the economic and safety risks associated with breakdowns.
JURNAL TEKNOLOGI

The production of biodiesel has become a crucial part of the global effort to replace fossil fuels with renewable energy sources. However, one of the challenges faced in biodiesel production is the increased production of glycerol as a by-product. Glycerol, or crude glycerol (CG), is generally produced in significant quantities and needs to be managed wisely. This article discusses the potential utilization of glycerol from biodiesel production as a raw material for bioethanol production. Bioethanol is one of the environmentally friendly renewable fuels. This research explores the transformative potential of glycerol from biodiesel production as a raw material for bioethanol. Progress in separation technology to purify CG, such as distillation, chemical treatment
Improving Performance of Spatial Database Based on Hybrid Machine Learning and Hilbert Curve Data Structure

This work introduces and analyzes a novel approach to multi-dimensional indexing. It is based on the concepts of the hybrid learnt spatial indexing by using Hilbert space filling curve algorithm with machine learning. Using Hilbert algorithm to obtain indexing for each spatial objects )point, line, polygon(, then ex - ecuting nearest neighbor queries in traditional technique. Taking benefits of machine learning method to learn indices of spatial objects, in learnt method we also used Hilbert curve to indexing spatial objects as in
Justi ﬁ cative conformity in ontologically ring-fenced ﬁ elds: Problematizing the scholarly nomenclature in qualitative studies

Ontology is implicitly or explicitly the impetus of any study. However, what are the implications of a scholarly ﬁ eld whose prevailing ontological assumptions and resultant epistemological commitments impede more nuanced theorizing? In this paper, we caution against theorizing norms in ﬁ elds characterized by a non-diverse and non-inclusive set of ontological assumptions. We contend that editorial practices therein create a certain kind of methodological conformity and conduct, that is, an undue justi ﬁ cation and explanatory overtones related to methods that are set against the predominant grain. Through a thematic review of qualitative papers in international marketing as a case in point, we argue against narrow onto-epistemological arsenals, we discuss the value of critical theorizing and put forward two modest proposals to address this kind of scholarly conformity in the future.
School Psychology Refugee School Consultation Effects on Teacher Self-Efficacy, Self-Care, and Peer Consultation Skills

Guided by a participatory culture-speci ﬁ c consultation model, this study contributes to an understanding of the effectiveness of school consultation with teachers of refugee students. The goal of the present study was to determine the impact of an individual consultation intervention with refugee teachers on their self-ef ﬁ cacy and self-care, in addition to their peer consultation skills. The participants were 109 teachers at refugee schools in Malaysia, most of whom were refugees (91% refugees; 73% female). Of the 109 participants, 84 teachers were coconsultants with psychology graduate students; all 109 were individual consultees. The study used a two-timepoint design with the outcomes of self-reported teacher self-care; teacher self-ef ﬁ cacy in the management of refugee student emotion regulation and emotional engagement; and consultation skills. Additionally, consultee-reported goal attainment, consultation effectiveness, and satisfactionwerecollected.The ﬁ ndingssuggestedsigni ﬁ cantlatentgrowthfrombaselinetopost-intervention in refugee teacher self-care and self-ef ﬁ cacy in the management of student emotion regulation and emotional engagement in addition to the growth of their consultation skills. The effect sizes were large for latent growth of teacher self-ef ﬁ cacy in promoting student emotion regulation, behavior, and emotional engagement ( d = 1.19, 1.01, 1.02); the effect size for self-care was medium ( d = .62). Growth was not dependent on dosage, age, gender, or consultee education, with the exception of teacher self-ef ﬁ cacy in management of emotional engagement which was dependent on dosage. After the intervention, the consultees reported that they completed their consultation goals at a higher level than expected, were satis ﬁ ed with the consultation, and found the consultants to be helpful. The discussion situates the ﬁ ndings in relevant theory, research, and the culture-speci ﬁ c context
Introducing Social Robots to Assess Frailty in Older Adults

Frailty is a crucial indicator in determining the well-being of older adults in terms of their health. With the growing number of elderly people, the demand for geriatricians is increasing, which means that they have less time to spend with each patient. The current meth-ods for frailty assessment use simple tests that are time-consuming and do not require specific medical expertise. To address this issue, this paper proposes the use of social robots to assess frailty autonomously. It presents a practical proposal that defines the robot’s behavior and explains the design and implementation concepts. Finally, it discusses some of the challenges that may arise from introducing social robots as frailty evaluators.
AI facilitated ﬂ uoro-electrochemical phytoplankton classi ﬁ cation †

* a Marine phytoplankton is extremely diverse. Counting and characterising phytoplankton is essential for understanding climate change and ocean health not least since phytoplankton extensively biomineralize carbon dioxide whilst generating 50% of the planet's oxygen. We report the use of ﬂ uoro-electrochemical microscopy to distinguish di ﬀ erent taxonomies of phytoplankton by the quenching of their chlorophyll-a ﬂ uorescence using chemical species oxidatively electrogenerated in situ in seawater. The rate of chlorophyll-a quenching of each cell is characteristic of the species-speci ﬁ c structural composition and cellular content. But with increasing diversity and extent of phytoplankton species under study, human interpretation and distinction of the resulting ﬂ uorescence transients becomes increasingly and prohibitively di ﬃ cult. Thus, we further report a neural network to analyse these ﬂ uorescence transients, with an accuracy >95% classifying 29 phytoplankton strains to their taxonomic orders. This method transcends the state-of-the-art. The success of the ﬂ uoro-electrochemical microscopy combined with AI provides a novel, ﬂ exible and highly granular solution to phytoplankton classi ﬁ cation and is adaptable for autonomous ocean monitoring.
Methane Sulphonic Acid in East Antarctic Coastal Firn and Ice Cores and Its Relationship with Chlorophyll-a and Sea Ice Extent

Sea ice is important for both regional and global climate, but comprehensive sea ice records are lacking pre-1978, when global-scale spaceborne observations began. Attempts to reconstruct sea ice conditions in different regions of Antarctica with the help of methane sulphonic acid (MSA) records from ice cores have had varying success, highlighting the often-regional relationship between ice core MSA and sea ice. This study uses MSA records from three firn cores and one ice core drilled on Fimbul Ice Shelf in Dronning Maud Land, East Antarctica, to investigate the relationship to satellite-20 derived sea ice extent (SIE) in the Southern Ocean. Chlorophyll-a concentrations, serving as a measure of phytoplankton biomass, are correlated to the MSA records to further test the MSA – SIE relationship. The relationship to both SIE and chlorophyll-a differs largely between the different firn and ice core MSA records. We find significant correlations for the MSA records from the two higher accumulation core sites to SIE and chlorophyll-a in the Weddell Sea, Western Pacific Ocean, and Ross Sea Sectors. Furthermore, the use of stacked MSA records introduced significant correlations between 25 MSA from the lower accumulation core sites and SIE. The absence of coherent correlation patterns between the MSA records across the four investigated cores and SIE or chlorophyll-a in the Southern Ocean suggests that the Fimbul Ice Shelf MSA records are not consistent proxies for regional SIE.
Modelling autonomic dataspaces using answer sets

This paper presents an approach for managing an autonomic data space, able to automatically define views that fulfill the requirements of a set of users, and adjust them as the data space evolves. An autonomic data space deals with incomplete knowledge to manage itself because of the heterogeneity and the lack of metadata related to the resources it integrates. Our approach exploits the expressiveness of stable models and the K action language for expressing the data space management functions. It is based on a model for specifying an autonomic dataspace expressed using answer set programming (ASP). ASP is a type of declarative logic programming particularly useful in knowledge-intensive applications. It is based on the stable semantics (answer sets), which allows negation as failure and applies the ideas of auto-epistemic logic to distinguish between what is true and what is believed.
Parallelism in a Region Inference Context

Region inference is a type-based program analysis that takes a non-annotated program as input and constructs a program that explicitly manages memory allocation and deallocation by dividing the heap into a stack of regions, each of which can grow and shrink independently from other regions, using constant-time operations. Whereas region-based memory management has shown useful in the contexts of explicit region-based memory management, and in particular, in combination with parallel execution of code, combining region inference with techniques for higher-order parallel programming has not been investigated. In this paper, we present an implementation of a fork-join parallel construct suitable for a compiler based on region inference. We present a minimal higher-order language incorporating the parallel construct, including typing rules and a dynamic semantics for the language, and demonstrate type soundness. We present a novel eﬀect-based region-protection inference algorithm and discuss beneﬁts and shortcomings of the approach. We also describe an eﬃcient implementation embedded in the MLKit Standard ML compiler. Finally, we evaluate the approach and the implementation based on a number of parallel benchmarks, and thereby demonstrate that the technique eﬀectively utilises multi-core architectures in a higher-order functional setting.
Analytic Hierarchy Process by Least Square Method Revisit

We study the paper of Saaty and Vargas to discuss the solutions for a comparison matrix derived by eigenvector method, least square method, and logarithmic least square method, respectively. We prove that the prediction of Saaty and Vargas is valid. Our result will provide a patch work for the theoretic foundation for Analytic Hierarchy Process.
Goal-Oriented End-User Programming of Robots

End-user programming (EUP) tools must balance user control with the robot's ability to plan and act autonomously. Many existing task-oriented EUP tools enforce a specific level of control, e.g., by requiring that users hand-craft detailed sequences of actions, rather than offering users the flexibility to choose the level of task detail they wish to express. We thereby created a novel EUP system, Polaris, that in contrast to most existing EUP tools, uses goal predicates as the fundamental building block of programs. Users can thereby express high-level robot objectives or lower-level checkpoints at their choosing, while an off-the-shelf task planner fills in any remaining program detail. To ensure that goal-specified programs adhere to user expectations of robot behavior, Polaris is equipped with a Plan Visualizer that exposes the planner's output to the user before runtime. In what follows, we describe our design of Polaris and its evaluation with 32 human participants. Our results support the Plan Visualizer's ability to help users craft higher-quality programs. Furthermore, there are strong associations between user perception of the robot and Plan Visualizer usage, and evidence that robot familiarity has a key role in shaping user experience.
Smith ScholarWorks Smith ScholarWorks

The surface mucus layer of reef-building corals supports feeding, sediment clearing, and protection from pathogenic invaders. As much as half of the fixed carbon supplied by the corals’ photosynthetic symbionts is incorporated into expelled mucus. It is therefore reasonable to expect that coral bleaching (disruption of the coral–algal symbiosis) would affect mucus production. Since coral mucus serves as an important nutrient source for the entire reef community, this could have substantial ecosystem-wide consequences. In this study, we examined the effects of heat stress-induced coral bleaching on the composition and antibacterial properties of coral mucus. In a controlled laboratory thermal challenge, stressed corals produced mucus with higher protein ( β = 2 . 1, p < 0 . 001) and lipid content ( β = 15 . 7, p = 0 . 02) and increased antibacterial activity (likelihood ratio = 100, p < 0 . 001) relative to clonal controls. These results are likely explained by the expelled symbionts in the mucus of bleached individuals. Our study suggests that coral bleaching could immediately impact the nutrient flux in the coral reef ecosystem via its effect on coral mucus.
Investigating the Interaction Effect of Democracy and Economic Investigating the Interaction Effect of Democracy and Economic Freedom on Corruption: A Cross-Country Quantile Regression Freedom on Corruption: A Cross-Country Quantile Regression Analysis Analysis

: This paper explores the interaction effects of economic freedom and democracy in controlling corruption for 100 countries by using quantile regression technique. The main contribution is to explore the interaction effects throughout conditional distribution of corruption across nations. Our results reinforce some findings in the literature, but also provide new conclusions. The findings suggest a stronger and significant interaction effect in reducing corruption, especially in the most-corrupt countries. However, democratic and economic freedoms alone may not cure corruption effectively in the most-corrupt nations, a sound democratic reform can eliminate corruption substantially only after achieving a threshold level of economic freedom.
Influence of Parthenium hysterophorus on Weed Community and Species Diversity in Zhangzhou

Using the intercept method,this paper investigated Parthenium hysterophorus distritution area's weed species and distribution with different habitats in Zhangzhou.The important value of weed and diversity index were caculated.The aim were to study influence of Parthenium hysterophorus on community of weed and species diversity and estimation of invation of Parthenium hysterophorus.The results showed there were 26 families and 91 speciese weed in habitats with Parthenium hysterophorus in Zhangzhou.The levels of human disturbance,the soil humidity and illumination were main factors affecting the occurrence and distribution of weed species.The Shannon-Wiener index and Pielou evenness indexes in construction waste and frontier land where Parthenium hysterophorus was dominant species were lower than those in farmland where Parthenium hysterophorus was not dominant species.Zhangzhou Parthenium hysterophorus lied in the later estabish stage which powerful soil weed bank was farmen.If effective measures were not taken,the invasion of Parthenium hysterophorus would cause the local ecological and economic great loss.
Azoramide ameliorates cadmium-induced cytotoxicity by inhibiting endoplasmic reticulum stress and suppressing oxidative stress

Background Cadmium (Cd) is hazardous to human health because of its cytotoxicity and long biological half-life. Azoramide is a small molecular agent that targets the endoplasmic reticulum (ER) and moderates the unfolded protein response. However, its role in Cd-induced cytotoxicity remains unclear. This study was performed to investigate the protective effect of azoramide against Cd-induced cytotoxicity and elucidate its underlying mechanisms. Methods Inductively coupled plasma‒mass spectrometry was used to measure Cd concentrations in each tissue of ICR male mice. The human proximal tubule epithelial cell line HK-2 and the human retinal pigment epithelial cell line ARPE-19 were used in the in vitro study. Cell apoptosis was determined by DAPI staining, JC-1 staining, and annexin V/propidium iodide double staining. Intracellular oxidative stress was detected by MitoSOX red staining, western blot, and quantitative real-time PCR. Moreover, ER stress signaling, MAPK cascades, and autophagy signaling were analyzed by western blot. Results The present data showed that Cd accumulated in various organs of ICR mice, and the concentrations of Cd in the studied organs, from high to low, were as follows: liver > kidney > testis > lung > spleen > eye. Our study demonstrated that azoramide inhibited ER stress by promoting BiP expression and suppressing the PERK-eIF2α-CHOP pathway. Additionally, we also found that azoramide significantly decreased ER stress-associated radical oxidative species production, attenuated p38 MAPK and JNK signaling, and inhibited autophagy, thus suppressing apoptosis in HK-2 and ARPE-19 cells. Conclusion Our study investigated the effect of azoramide on Cd-induced cytotoxicity and revealed that azoramide may be a therapeutic drug for Cd poisoning.
Impact of systemic hypoxia and blood flow restriction on mechanical, cardiorespiratory, and neuromuscular responses to a multiple-set repeated sprint exercise

Introduction: Repeated sprint cycling exercises (RSE) performed under systemic normobaric hypoxia (HYP) or with blood flow restriction (BFR) are of growing interest. To the best of our knowledge, there is no stringent consensus on the cardiorespiratory and neuromuscular responses between systemic HYP and BFR during RSE. Thus, this study assessed cardiorespiratory and neuromuscular responses to multiple sets of RSE under HYP or with BFR. Methods: According to a crossover design, fifteen men completed RSE (three sets of five 10-s sprints with 20 s of recovery) in normoxia (NOR), HYP, and with bilaterally-cuffed BFR at 45% of resting arterial occlusive pressure during sets in NOR. Power output, cardiorespiratory and neuromuscular responses were assessed. Results: Average peak and mean powers were lower in BFR (dz = 0.87 and dz = 1.23, respectively) and HYP (dz = 0.65 and dz = 1.21, respectively) compared to NOR (p < 0.001). The percentage decrement of power output was greater in BFR (dz = 0.94) and HYP (dz = 0.64) compared to NOR (p < 0.001), as well as in BFR compared to NOR (p = 0.037, dz = 0.30). The percentage decrease of maximal voluntary contraction of the knee extensors after the session was greater in BFR compared to NOR and HYP (p = 0.011, dz = 0.78 and p = 0.027, dz = 0.75, respectively). Accumulated ventilation during exercise was higher in HYP and lower in BFR (p = 0.002, dz = 0.51, and p < 0.001, dz = 0.71, respectively). Peak oxygen consumption was reduced in HYP (p < 0.001, dz = 1.47). Heart rate was lower in BFR during exercise and recovery (p < 0.001, dz = 0.82 and p = 0.012, dz = 0.43, respectively). Finally, aerobic contribution was reduced in HYP compared to NOR (p = 0.002, dz = 0.46) and BFR (p = 0.005, dz = 0.33). Discussion: Thus, this study indicates that power output during RSE is impaired in HYP and BFR and that BFR amplifies neuromuscular fatigue. In contrast, HYP did not impair neuromuscular function but enhanced the ventilatory response along with reduced oxygen consumption.
Natural phenolic compounds from Satureja L. as inhibitors of COVID-19 protease (Mpro): Computational investigations

Coronavirus (SARS-CoV-2) causes a new type of severe acute respiratory syndrome that first appeared in Wuhan in December 2019; it is a very fast-spreading and deadly virus. Therefore, urgent discovery or development of “lead compounds” against this virus is crucial. Natural compounds have always served as a great source, especially the use of traditional medicinal plants, in modern drug discovery. This study aimed to investigate the SARS-CoV-2 protease inhibition potential of the phenolic compounds in the genus Satureja L. The affinities of the chosen natural products were understood using molecular docking simulation against the SARS-CoV-2 protease enzyme. The study proved that three different phenolic compounds namely 5,6-dihydroxy-2-(4-hydroxy-3-methoxyphenyl)-7,8-dimethoxy-4H-chromen-4-one, 2-(3,4-dimethoxyphenyl)-5,6-dihydroxy-7,8-dimethoxy-4H-chromen-4-one, and 5,6-dihydroxy-2-(3-hydroxy-4-methoxyphenyl)-7,8-dimethoxy-4H-chromen-4-one obtained from Satureja L. taxa were found as promising against SARS-CoV-2 main protease.