Miracle-dz/UniFAR-FTUs huggingface dataset:
An effective approach for indoor mobile robot SLAM with multi-sensor fusion

With the rapid development of mobile service robot industry, its application scenarios have become more complex and diverse. SLAM (Simultaneous Localization and Mapping) with a single sensor is difficult to meet the application requirements. Multisensor fusion for accurate positioning and mapping navigation has become one of the research hotspots in this field. In order to solve the problem of single sensor simultaneous localization and map construction in indoor small environment, the contour is fuzzy and the effect is not ideal. Based on ORB-SLAM2 fusion and improved Gmapping algorithm, this paper proposes a multi-sensor real-time localization mapping scheme based on laser radar and vision fusion. This algorithm combines the visual information provided by the depth camera and the scanning frame provided by the laser radar to make up for the shortcomings of a single sensor and form a real-time positioning and map building system with higher robustness. The experimental results show that the integrated SLAM scheme can obtain a more comprehensive and accurate map, which meets the expected design requirements.
The role of earning management as a mediator of the effect of the facial width to height ratio CEOs on leverage

Abstract This study aims to prove the consistency of Agency Theory and Behavioral Consistency Theory as a solution to explain the role of Earnings Management in mediating the influence of male CEO masculinity on leverage. This research uses a quantitative approach with the population and research samples using companies on Indonesia’s Stock Exchange in 2014–2018. This study collected facial images identified as male CEOs from data from Indonesia’s Stock Exchange website and company websites and utilized Google searches. The data analysis method in this study uses Structural Equation Modeling (SEM) with Stata Software which connects theories, concepts and data that can be carried out on research variables. The findings explain that the decrease and increase in Earning Management practices has an impact on increasing and decreasing the value of the masculinity face of male CEOs also has an impact on increasing and decreasing the value of corporate leverage.
Quantum cooling by unitary transformations

We study the unitary time evolution of a simple quantum Hamiltonian describing a heat engine coupled to two heat baths. The engine is modeled as a three-level system. Each heat bath consists of a single harmonic oscillator. The engine is operated via time-dependent external fields. The S-matrix of the thermodynamic cycle is obtained in analytic form. We conjecture that the spectrum of this S-matrix contains a continuous part, and that this is a requirement for the operation as a heat engine. Energy currents flow in both directions through the engine. The balance of these currents determines whether the engine performs work or whether its operation requires the application of external forces.
Deposition law of flat fan nozzle for pesticide application in horticultural plants

: Pesticide spraying is to protect the plants with adequate target coverage and a minimum of off-target drift. Understanding the spatial distribution characteristics of spray droplets is essential for regulating pesticide deposition, in order to investigate the relationship between the two at the mechanistic level and provide an accurate basis for nozzle selection, this study compared the characteristics of the atomization field under different pressures, angles, and flow rate types by phase Doppler particle analyzer (PDPA), the unit spatial density of droplet was used as a link to explore the internal mechanism that affects the deposition efficiency by constructing a transport model and conducting actual spraying experiments. The results showed that the cumulative distribution of droplet diameter could be perfectly fitted by the Rosin-Rammler correlation, and the deposition efficiency had a strong correlation with the peak particle size range. For strawberry and chrysanthemum plants, the optimal droplet deposition particle size ranges were 250-270 μ m and 240-260 μ m, respectively. This article explained the deposition efficiency from a single droplet dynamics mechanism and deposition of droplet cloud, which provided a new research idea for the study of precision plant protection.
The spectro-interferometer of the Arcetri solar tower

L'instrument de base est un interferometre de Fabry Perot monte en tandem avec un spectrographe de taille moyenne, ceci permettant la mesure de raies d'absorption solaire entre 5500 et 6500 A avec une forte stabilite de longueur d'onde (0,08 mArms en 12h) et une grande resolution spectrale
Short Tasks for Scaffolding Computational Thinking by the Global Bebras Challenge

The short task methodology enhances the Bebras constructive environment, and provides an emotional context that triggers the convolution of initially biased mental models and corresponding emotional reactions into an unbiased set of conceptual models for informatics education. This provides the motivation of our research–to explore the process of pedagogical design of short informatics concept-based tasks from the standpoint of mindset formation, which allows one to build conceptual models for CT education. The aim of the research is to gain a conceptual understanding of what a short task is in the context of the global Bebras Challenge initiative. We explore the principles which should underlie the pedagogical design of short tasks for informatics education that scaffold CT. Exploration of a number of practical examples of the Bebras short tasks is the background of our research methodology. The results include an analysis of the structure of short tasks, focusing on the interaction of mental models, conceptual models, and heuristics inherent in the task design. The discussion provides a comprehensive insight into the issues of the short tasks in relation to CT and the Bebras environment. We conclude with recommendations for organizing an effective pedagogical design of a short task.
Bounds from multimessenger astronomy on the superheavy dark matter

The purely gravitational evidence supporting the need for dark matter (DM) particles is compelling and based on Galactic to cosmological scale observations. Thus far, the promising weakly interacting massive particles scenarios have eluded detection, motivating alternative models for DM. We consider the scenarios involving the superheavy dark matter (SHDM) that potentially can be emitted by primordial black holes (PBHs) and can decay or annihilate into ultrahigh-energy (UHE) neutrinos and photons. The observation of a population of photons with energies $E\ge 10^{11}$ GeV would imply the existence of completely new physical phenomena, or shed some light on DM models. Only the ultra-high energy cosmic ray observatories have the capabilities to detect such UHE decay products via the measurements of UHE photon induced extensive air showers. Using the upper bound on the flux of UHE cosmic rays beyond $10^{11.3}$ GeV implying $J(>10^{11.3}~{\rm{GeV}})<3.6\times 10^{-5}$ km$^{-2}$sr$^{-1}$y$^{-1}$, at the $90\%$ C.L. reported by the Pierre Auger Observatory, we obtain global limits on the lifetime of the DM particles with masses $10^{15}\le M_{X} \le 10^{17}$ GeV. The constraints derived here are new and cover a region of the parameter space not yet explored. We compare our results with the projected constraints from future POEMMA and JEM-EUSO experiments, in order to quantify the improvement that will be obtained by these missions. Moreover, assuming that an epoch of early PBHs domination introduces a unique spectral break, $f_{\ast}$, in the gravitational wave spectrum, the frequency of which is related to the SHDM mass, we map potential probes and limits of the DM particles masses on the $f_{\ast}-M_{X}$ parameter space.
Optimization of Bifunctional Antisense Oligonucleotides for Regulation of Mutually Exclusive Alternative Splicing of PKM Gene

Oligonucleotide tools, as modulators of alternative splicing, have been extensively studied, giving a rise to new therapeutic approaches. In this article, we report detailed research on the optimization of bifunctional antisense oligonucleotides (BASOs), which are targeted towards interactions with hnRNP A1 protein. We performed a binding screening assay, Kd determination, and UV melting experiments to select sequences that can be used as a high potency binding platform for hnRNP A1. Newly designed BASOs were applied to regulate the mutually exclusive alternative splicing of the PKM gene. Our studies demonstrate that at least three repetitions of regulatory sequence are necessary to increase expression of the PKM1 isoform. On the other hand, PKM2 expression can be inhibited by a lower number of regulatory sequences. Importantly, a novel branched type of BASOs was developed, which significantly increased the efficiency of splicing modulation. Herein, we provide new insights into BASOs design and show, for the first time, the possibility to regulate mutually exclusive alternative splicing via BASOs.
XTCSD: Stata module to test for cross-sectional dependence in panel data models

xtcsd tests for cross-sectional dependence in Fixed Effects or Random Effects models. xtcsd tests the hypothesis of cross-sectional independence in panel data models with small T and large N by implementing two semi-parametric tests proposed by Friedman (1937) and Frees (1995, 2004), as well as the parametric testing procedure proposed by Pesaran (2004). xtcsd with option pesaran can handle balanced as well as unbalanced panels.
Particle-fluid interaction corrections for flow measurements with a laser Doppler flowmeter

A discussion is given of particle lags in mean flows, acoustic oscillations at single frequencies and in turbulent flows. Some simplified cases lead to exact solutions. For turbulent flows linearization of the equation of motion after assuming the fluid and particle streamlines coincide also leads to a solution. The results show that particle lags are a function of particle size and frequency of oscillation. Additional studies are necessary to evaluate the effect of turbulence when a major portion of the energy is concentrated in small eddies.
A sea clutter suppression algorithm based on sparse representation

Sea clutter can affect the detection of sea targets. Traditional clutter suppression methods are difficult to detect slow - moving targets in medium-high sea conditions. Based on sparse representation theory, a novel sea clutter suppression method based on sparse low rank is proposed. It replaces traditional correlative operation with low dimensional projection measurement and signal reconstruction, and transfers a lot of computation to post processing. On the premise that the target range dimension distribution detected by radar satisfies sparsity and the sea clutter satisfies low rank, a solution m-odel is established by using the minimum power sparsity constraint and the low rank constraint of the sea clutter. The co-nvolution matrix is formed by transmitting signals, and then the measurement matrix is constructed by randomly extract-ing rows of the convolution matrix. The iterative contraction threshold algorithm is used to reconstruct the target signal. This paper gives a detailed theoretical derivation of the algorithm and forms a complete implementation framework. Si-mulation results show that the proposed algorithm can effectively reconstruct the target and achieve the sea clutter suppression and target detection under strong sea clutter background.
AN IMAGE RETRIEVAL METHOD BASED ON SPATIAL DISTRIBUTION OF COLOR 1

Color histogram is now widely used in image retrieval. Color histogram-based image retrieval methods are simple and efficient but without considering the spatial distribution information of the color. To overcome the shortcoming of conventional color histogram-based image retrieval methods, an image retrieval method based on Radon Transform (RT) is proposed. In order to reduce the computational complexity, wavelet decomposition is used to compress image data. Firstly, images are decomposed by Mallat algorithm. The low-frequency components are then projected by RT to generate the spatial color feature. Finally the moment feature matrices which are saved along with original images are obtained. Experimental results show that the RT based retrieval is more accurate and efficient than traditional color histogram-based method in case that there are obvious objects in images. Further more, RT based retrieval runs significantly faster than the traditional color histogram methods.
Bio-Inspired Ant Lion Optimizer for a Constrained Petroleum Product Scheduling

Real-world optimization problems demand sophisticated algorithms. Over the years bio-inspired approach, a subset of computational intelligence has demonstrated remarkable success in real-world use cases, especially where exact or deterministic algorithms are ineffective. Petroleum product scheduling is a complex optimization task belonging to the combinatorial problem category. The problem size and the constraints compound the complexity of the petroleum product scheduling problem. However, conventional optimization methods such as the exact or deterministic algorithm produced a poor solution quality to the petroleum products scheduling problem. Therefore, this study leverages the potency of a bio-inspired approach, Ant Lion Optimizer (ALO) in its basic state to enhance the solution quality. This is in line with She-Shin Yang’s proposition, father of bio-inspired algorithms who advocated for the application of existing bio-inspired algorithms to tackle real-world problems rather than developing new algorithms. Bio-inspired is a computational paradigm that models the characteristics of natural biological entities to solve complex problems. We also used the Chaotic Particle Swarm Optimization (CPSO) algorithm for the same problem to unveil the efficacy of the roulette wheel function in ALO. The results show a 24.8% and 23.9% reduction in the original cost of distribution on ALO and CPSO respectively. Also, 99.5% of the constraints are met. Thus, problems of scarcity, minimum allocation and product availability are solved using the penalty constraint handling method. The exact algorithm showed a 14% reduction in the original cost. However, despite the effectiveness, further work on constraint handling methods and other bio-inspired computation approaches such as Genetic algorithms and their variants could be possible in the future scope. Moreover, other real-world problem domains such as power distribution in the power, sector could be a possible application of the ALO.
Effect of magnesium supplementation on pregnancy outcome in gestational diabetes mellitus patients: A meta‐analysis of randomized controlled trials

Abstract Conflicting evidence exists regarding the effectiveness of magnesium supplementation during pregnancy in gestational diabetes mellitus (GDM) patients. This meta‐analysis examines the effect of magnesium on glycemic indices and metabolic status in GDM. We searched databases for randomized controlled trials (RCTs) conducted, and after applying inclusion and exclusion criteria, a total of four RCTs were considered eligible for the analysis. Outcome parameters included markers for glycemic control and metabolic status. A total of four RCTs with 198 participants (control = 99; magnesium supplemented = 99) were selected for the analysis. Magnesium supplementation resulted in a significant reduction in markers of glycemic control—fasting plasma glucose (standard mean difference (μ^) = −0.83; 95% CI: [−1.13, –0.54]; p‐value <. 0001), and insulin levels (μ^ = −0.95; 95% CI: [−1.38, −0.52]; p‐value <.0001). Also, Mg intake resulted in altered oxidative stress markers TAC (μ^ = 1.09; 95% CI: [0.10, 2.07]; p‐value = .03) of the pregnant women. No significant effect on GSH and CRP levels was observed. This study provides evidence of the positive effects of magnesium intervention on insulin sensitivity and oxidative stress in GDM patients.
Exploring LSU and ITS rDNA Sequences for Acanthamoeba Identification and Phylogeny

The identification and classification of strains of Acanthamoeba, a potentially pathogenic ubiquitous free-living amoeba, are largely based on the analysis of 18S rDNA sequences, currently delineating 23 genotypes, T1 to T23. In this study, the sequences of the ITS region, i.e., the 5.8S rDNA and the two internal transcribed spacers (ITS-1 and ITS-2), and those of the large subunit (LSU) rDNA of Acanthamoeba were recovered from amoeba genomes; the sequences are available in GenBank. The complete ITS–LSU sequences could be obtained for 15 strains belonging to 7 distinct lineages (T4A, T4D, T4F, T4G, T2, T5, and T18), and the site of the hidden break producing the 26Sα and 26Sβ was identified. For the other lines, either the LSU is partial (T2/T6, T7) or the ITS is fragmentary (T7, T10, T22). It is noteworthy that a number of sequences assigned to fungi turned out to actually be Acanthamoeba, only some of which could be affiliated with known genotypes. Analysis of the obtained sequences indicates that both ITS and LSU are promising for diagnostic and phylogenetic purposes.
Osteogenic Efficacy of Human Trophoblasts-Derived Conditioned Medium on Mesenchymal Stem Cells

Trophoblasts play an important role in the regulation of the development and function of the placenta. Our recent study demonstrated the skin regeneration capacity of trophoblast-derived extracellular vesicles (EV). Here, we aimed to determine the potential of trophoblast-derived conditioned medium (TB-CM) in enhancing the osteogenic differentiation of bone marrow mesenchymal stem cells (MSCs). We found that TB-CM promoted the osteogenic differentiation of MSCs in a dose-dependent manner. Furthermore, it inhibited adipogenesis of MSCs. We also found that the primary trophoblast-derived conditioned medium (PTB-CM) significantly enhanced the proliferation and osteogenic differentiation of human MSCs. Our study demonstrated the regulatory mechanisms underlying the TB-CM-induced osteogenesis in MSCs. An upregulation of genes associated with cytokines/chemokines was observed. The treatment of MSCs with TB-CM stimulated osteogenesis by activating several biological processes, such as mitogen-activated protein kinase (MAPK) and bone morphogenetic protein 2 (BMP2) signaling. This study demonstrated the proliferative and osteogenic efficacies of the trophoblast-derived secretomes, suggesting their potential for use in clinical interventions for bone regeneration and treatment.
Hierarchical Attributes of Selected Stakeholders Participation in City Planning and Development: A Case Study of Khon Kaen Smart City, Thailand

This paper aims to determine the hierarchical classification of the attributes of participation used by planners and selected stakeholders in a participatory planning approach for smart city development. It also attempts to contribute to the unsolved question raised by Wandersman Giamartino (1980) that “if participation is so rewarding and effective, why doesn’t everyone participate? ” The exploratory sequential mixed method was applied for the data collection procedure. The results of the qualitative approach were used to develop the questionnaires which were conducted with 18 experts/ planners and 111 selected stakeholders. The findings indicated that the interest, influence, and area-based were the key attributes used by planning agency/planners to select the stakeholders to participate in the participatory planning processes. On the other hand, the selected stakeholders relied on the interest, area-based, influence, and urgency to decide to participate in the participatory planning process of Khon Kaen Smart City. Furthermore, the selected stakeholders preferred the on-place-participation rather than e-participation and informal and indirect participation gateways to have an influence on the processes of decision-making.
Prosocial rule breaking, ingroups and social norms: Parental decision‐making about COVID‐19 rule breaking in the UK

Abstract The British public generally adhered to COVID‐19‐related restrictions, but as the pandemic drew on, it became challenging for some populations. Parents with young children were identified as a vulnerable group. We collected rich, mixed‐methods survey data from 99 UK‐based parents (91 mothers) of children under 12, who described their lockdown transgressions. Household mixing was the most prevalent broken rule. Template analysis found that rule breaking was driven by ‘ingroup‐level’ prosocial motivations to protect the mental and social health of family and loved ones, and that parents were ‘engaged’ decision‐makers who underwent careful deliberation when deciding to break rules, making trade‐offs, bending rules, mitigating risks, reaching consensus, and reacting to perceived rule injustices. Cumulative link models found that the perceived reasonableness of rule violations was predicted by social norms. Rules were broken by parents not for antisocial reasons, but for ‘ingroup‐level’ prosocial reasons, linked to supporting loved ones.
Gastrointestinal and Liver Complications in Patients with Diabetes Mellitus—A Review of the Literature

The number of diabetes mellitus patients has increased over the last few years in developing countries, along with obesity and sedentary lifestyle. Besides macroangiopathy and microangiopathy, damage to the nerve fibers of the peripheral nervous system is the most common chronic complication of diabetes. Digestive complications in diabetic patients represent a consequence of diabetic autonomic neuropathy involving the gastrointestinal tract, but unfortunately not always evaluated by diabetologists. Aside from the complications encountered in the digestive tract, patients with diabetes mellitus are prone to developing liver diseases. This review will describe the prevalence of these complications, the modality of diagnosis, and therapeutical solutions in order to reduce the risk of progression of these complications in diabetic subjects.
Transdermal Drug Delivery: Determining Permeation Parameters Using Tape Stripping and Numerical Modeling

The function of transdermal drug delivery (TDD) systems is complex due to the multiple layers necessary for controlling the rate of drug release and the interaction with the patient’s skin. In this work, we study a particular aspect of a TDD system, that is, the parameters that describe the drug permeation through the skin layers. Studies of the diffusion of two compounds were carried out and supported by tape stripping and numerical modeling. The experimental studies are carried out for porcine skin in a Franz diffusion cell and tape stripping is used to quantify the concentration of drug in the stratum corneum. A multi-layered numerical model, based on Fickian diffusion, is used to determine the unknown parameters that define the skin’s permeability, such as the partition between layers and the mass transfer coefficients due to the surface barrier. A significant correlation was found between the numerical modeling and experimental results, indicating that the partition and mass transfer effects at the interlayer boundary are accurately represented in the numerical model. We find that numerical modeling is essential to fully describe the diffusion characteristics.