Miracle-dz/UniFAR-FTUs huggingface dataset:
Gaps in Live Inter-Observer Reliability Testing of Animal Behavior: A Retrospective Analysis and Path Forward

Observational behavior research is an important activity for zoos and aquariums, often being conducted to provide insights into welfare and guide management decisions. This research relies on standardized protocols to ensure consistent data collection. Inter-observer reliability, where untrained observers are tested against the behavior identifications of an expert observer, represent a critical internal validation process. Recent software advances have made reliability testing easier and more accessible, but there is limited guidance on what constitutes a strong reliability test. In this study, we reviewed historic reliability test data from Lincoln Park Zoo’s on-going behavior monitoring program. Six representative species were chosen that included 645 live pairwise reliability tests conducted across 163 total project observers. We identified that observers were being tested on only approximately 25% of the behaviors listed and defined in the species ethograms. Observers did encounter a greater percent of the ethogram with successive reliability tests, but this gap remained large. While inactive behaviors were well-represented during reliability tests, social and other non-maintenance solitary behaviors (e.g., exploratory, scent marking, play, etc.) did not frequently occur during tests. While the ultimate implications of these gaps in testing are unclear, these results highlight the risks of live reliability testing as an inherently non-standardized process. We suggest several approaches to help address these limitations, including refining ethograms, reconsidering criteria, and supplementing live training with video. We hope this self-critique encourages others to critically examine their methods, enhance the quality of their behavioral data, and ultimately, strengthen conclusions drawn about animal behavior and welfare.
Mode-locking features in a sub-200-fs erbium-doped all-fiber laser based on high-density well-aligned single-walled carbon nanotubes

In this paper, we have studied ML features in a sub-200-fs erbium-doped all-fiber laser based on a saturable absorber obtained by high-pressure-high-temperature treatment of commercially available single-walled carbon nanotubes. We have shown that there is a significant effect on the ultrafast optical properties of saturable absorber due to the high-density well-aligned structure of newly-developed single-walled carbon nanotubes and related it to the mode-locked laser performance. We have obtained a low-intensity-noise ultra-short stretched pulse generation with a repetition rate of 42.22 MHz, a spectral pulse width of 30 nm, and average output power of 11.3 mW with long-term stability of ~ 0.06% during 3 h measurement time
ILBPSDNet: Based on improved local binary pattern shallow deep convolutional neural network for character recognition

This paper proposes an architecture based on the improved local binary pattern (LBP) shallow deep convolution neural network, which integrates hand-crafted feature pre-processing and the advantage of character learning in the supervised high-level function of CNN, in order to enhance its performance. This study introduced the information of scale space into the LBP to reduce the sensitivity to noise, and applied feature maps with two features, the maximum selection feature map (MLBP) and the ﬁrst selection feature map (FLBP). The former selected the edge with the strongest intensity to reduce the inﬂuence of noise points, while the latter measured local binary features through the scale detection of an effective edge. In the network architecture design, according to the differences of input features, networks of different depths were used for learning, and the features learned by the two networks were adopted for classiﬁcation. The experimental results show that, the ILBPSDNet proposed had certain recognition abilities in many character data sets, and the network parameters and computation were also reduced. Therefore, it has a signiﬁcant effect in realizing the application of real-time character recognition. Finally, compared with other latest networks, its network performance could be maintained at a certain level.
Examining Hispanic Preservice Teachers’ Perceptions of Scientists in a Science Methods Course

International Journal on Studies in Education (IJonSE) is a peer-reviewed scholarly online journal. This article may be used for research, teaching, and private study purposes. Authors alone are responsible for the contents of their articles. The journal owns the copyright of the articles. The publisher shall not be liable for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of the research material. All authors are requested to disclose any actual or potential conflict of interest including any financial, personal or other relationships with other people or organizations regarding the submitted work.
Dropout management in online learning systems

ABSTRACT We examine the role of communication from users on dropout from digital learning systems to answer the following questions: (1) how does the sentiment within qualitative signals (user comments) affect dropout rates? (2) does the variance in the proportion of positive and negative sentiments affect dropout rates? (3) how do quantitative signals (e.g. likes) moderate the effect of the qualitative signals? and (4) how does the effect of qualitative signals on dropout rates change across early and late stages of learning? Our hypotheses draws from learning theory and self-regulation theory, and were tested using data of 447 learning videos across 32 series of online tutorials, spanning 12 different fields of learning. The findings indicate a main effect of negative sentiment on dropout rates but no effect of positive sentiment on preventing dropout behaviour. This main effect is stronger in the early stages of learning and weakens at later stages. We also observe an effect of the extent of variance of positive and negative sentiments on dropout behaviour. The effects are negatively moderated by quantitative signals. Overall, making commenting more broad-based rather than polarised can be a useful strategy in managing learning, transferring knowledge, and building consensus.
The Nephroprotective Effects of Moringa Oleifera Extract against Contrast Induced Nephrotoxicity

Objectives: The present research has been conducted to assess the Nephroprotective effects of the Moringa Oleifera Extract against contrast -induced nephrotoxicity in male rabbits. Study Design: Experimental design Place and Duration of Study: it was carried out in the Faculty of Pharmacy/University of Kufa, Iraq/Al-Najaf Town . The study began at October 2020 and end at March 2021. Methodology: Twenty one adult (male rabbits) weighing range(1.2-1.5kg). Rabbits are divided in a random manner into three equal groups each group including seven rabbits. Group1:control group administered DW, Group2:has been treated with Iodide contrast(2.5mg/kg) of (370mg/ml),group 3: dosed alcoholic extracts of Moringa 250 mg/kg and contrast (2.5mg/kg). By accounting data on the MDA levels ,Glutathione level and features of kidney histopathology. All efforts have been made to reduce the suffering of a animals prior to and throughout the experiment and sampling. Results: The alcoholic Moringa extract at 250mg/kg body weight doses orally considerably protected contrast induced toxicity of the kidneys in the rabbits through the increment of the level of GSH and reduces the level of MDA. In the Histological data, the extract activities also protect the damage of the kidney, which is induced by the contrast that has been represented by the de-generation of some tubules and atrophy of glomerular, glomerular tuft congestion and expanded Bowman’s Space. Conclusions: This study proposed that Moringa’s alcoholic extract results in the enhancement of the defense status of the oxidative stress against the renal toxicity. (Moringa Oleifera have Nephroprotective effect against contrast induce Nephrotoxicity).
A Study on Influence of Psychological Capital of Chinese University Teachers Upon Job Thriving: Based on Motivational Work Behavior as an Intermediary Variable

With the continuous development of the information process, a series of revolutionary changes are occurring in universities such as knowledge acquisition methods, teaching methods, as well as the relation between teaching and learning, which lead to new and higher requirements for teaching staff. Combining the development requirements of China’s new era, starting from the perspective of capital development in universities, we should discuss the influence of universities teachers’ psychological capital on job thriving. Through the literature, we found that the psychological capital of universities teachers cannot affect the job thriving directly. Therefore, we would try to find an intermediary variable-motivational work behavior and establish an intermediary model to study the relationship between variables. Through the establishment of models, the use of empirical analysis methods, analysis the data from electronic questionnaires, use software analysis, and we reveal the role of university teachers’ psychological capital on the job thriving, and how to improve teachers’ job thriving, the organization brings greater benefits to provide countermeasures and suggestions and provides more new enlightenment for the management of universities.
Research on Noise Reduction of 3.6 MW Evaporative Cooling Wind Motor Induced by Electromagnetic and Two-Phase Flow Resonance Based on Stator Optimization

In this paper, the vibration frequency of the stator of 3.6 MW fully immersed evaporative cooling permanent magnet semi-direct drive generators (ECPMSDDGs) was analyzed based on the fluid-structure coupling theory and solved by finite element analysis (FEA) simulation. The resonance noise reduction research under the typical working condition induced by two-phase flow and electromagnetic force was studied based on the method of structural optimization. In this paper, a structural optimal design method for the stator of the 3.6 MW ECPMSDDGs was presented. First of all, the frequency and characteristics of electromagnetic force of 3.6 MW ECPMSDDGs under the rated power were analyzed. Secondly, the frequency and characteristics of two-phase flow boiling vibration were analyzed based on the bubble oscillation theory of the two-phase flow and the experiment. Thirdly, the wet modal natural frequency of the stator core cooling structure was analyzed based on the fluid-structure coupling theory and FEA. Finally, the natural wet mode vibration frequency of the stator cooling structure of the 3.6 MW ECPMSDDGs was improved based on the structure optimization. This optimization method could reduce the resonance noise of evaporative cooling motor induced by electromagnetic and two-phase flow. The optimization results showed that the natural wet mode frequency of the stator could be improved by optimizing the radial flow groove and supporting beam under the condition that the effective length of the stator core remained unchanged during the optimization. The noise simulation result showed that the resonance noise of 3.6 MW ECPMSDDGs induced by electromagnetic and two-phase flow could be reduced after the structural optimization.
Design of wideband/dual‐band bandpass filter using a vias and slots loaded sector circular patch resonator

In this paper, a novel patch resonator is proposed to realize wideband and dual‐band bandpass filter (BPF) with small frequency ratio. The introduction of metallic vias and slots on the patch enables the flexible control of the resonant frequencies of TM01, two degenerated modes of TM11, and TM21. Two stubs loaded on the patch and coupled with I/O feeding line can introduce two additional resonant modes, and facilitate the control of input/output coupling strength. Owing to the different coupling relationships between the stub modes and two degenerated modes of TM11, the transmission zeros (TZs) located at the center of passband can be eliminated or generated by altering their resonant order, thus realizing wideband or dual‐band operation. For demonstration, two prototypes are simulated, fabricated and measured. Good agreement can be observed between simulation and measurement. The implemented wideband BPF has a passband from 1.85 GHz to 3.03 GHz with six transmission poles (TPs). While the implemented dual‐band BPF operates at 1.8/2.45 GHz with three TPs within each band and two TZs between two bands. Small frequency ratio of 1.33 is achieved. Wide upper stopband and low insertion loss can be observed for both prototypes.
Application of A Scaled, Three-Dimensional High-Pressure Physical Model to Steamflooding

Abstract This paper presents the results of steamflooding experiments using a three-dimensional scaled, physical model. Twenty-four experiments were performed to study the effects of production completion intervals, low quality steam injection, stepwise decrease of heat input, and addition of nitrogen on oil recovery. Completing the production well in the lower half of the formation produced more oil than that produced by completing the well in the full interval of the formation. At constant water throughput, a decrease in steam quality resulted in a decrease in oil recovery. A 4.5% decrease of heat input and a 10% increase in water throughput maintained oil production at about the same level. A stepwise decrease of either steam quality or steam injection rate did not improve oil recovery. After steam breakthrough, the addition of a small amount of nitrogen to the injected steam increased oil recovery.
L-RTAM: Logarithm based reliable trust assessment model for WBSNs

Abstract In has been considered that the sensor network’s safety measures have been built upon a non-realistic, trusted environment. After analyzing the trust models for wireless body sensor networks (WBSNs), it has been found that trust models should be distributed, lightweight, and robust against various vulnerabilities. They are also facing issues regarding computation overhead. Moreover, there is a threat of internal attacks over WBSNs. These attacks may be an on-off attack, data modification, message disclosure, collusion attack, bad-mouthing, brute force, and denial of service attack. Thus, this research paper considers three issues: network internal security, resource management, and spiteful node detection. The Proposed dynamic and trustworthy lightweight trust assessment scheme (RTAM) for WBSNs would play a significant role in the appropriate usage of resources and minimize the computational overhead. RTAM is a scalable trust model that incorporates logarithm based direct trust, indirect trust, and success ratio based data trust. It would be safe from a different type of attacks. To check the malicious activities that have been performed in nodes, some malicious nodes from the total nodes have been managed by the proposed network.
Clustering Moving Object Trajectories: Integration in CROSS-CPP Analytic Toolbox

Mobile devices equipped with sensors are generating an amount of geo-spatial related data that, properly analyzed can be used for future applications. In particular, being able to establish similar trajectories is crucial to analyze events on common points in the trajectories. CROSS-CPP is a European project whose main aim is to provide tools to store data in a data market and to have a toolbox to analyze the data. As part of these analytic tools, a set of functionalities has been developed to cluster trajectories. Based on previous work on clustering algorithms we present in this paper a Quickbundels algorithm adaptation to trajectory clustering . Experiments using different distance measures show that Quickbundles outperforms spectral clustering, with the WS84 geodesic distance being the one that provides the best results.
DNA mixture interpretation using linear regression and neural networks on massively parallel sequencing data of single nucleotide polymorphisms

ABSTRACT Massively parallel sequencing (MPS) enables concurrent analysis of multiple single nucleotide polymorphisms (SNPs) and detection of alleles from minor contributors to extremely imbalanced DNA mixtures. To interpret the complex MPS data obtained from DNA mixtures, EuroForMix, linear regression, and neural network models were employed. Data of 960 autosomal SNPs sequenced through MPS of 10 single-source DNA samples, 26 nondegraded DNA mixtures from nonrelative (mixture ratio 1:29–1:99), 16 nondegraded DNA mixtures from relatives (1:29–1:99), 8 degraded DNA mixtures from nonrelatives (1:29–1:99), and 16 degraded DNA mixtures of relatives (1:29–1:99) were analysed. In total, 89.4% (59/66), 93.9% (62/66), and 93.9% (62/66) of the minor contributors to DNA mixtures could be correctly inferred using EuroForMix, linear regression, and a neural network, respectively. In conclusion, the linear regression and neural network models outperformed EuroForMix in determining the minor contributor to DNA mixtures from MPS data.
Implosion in the Challenger Deep: Echo Sounding with the Shock Wave

Since HMS Challenger made the first sounding in the Mariana Trench in 1875, scientists and explorers have been seeking to establish the exact location and depth of the deepest part of the ocean. The scientific consensus is that the deepest depth is situated in the Challenger Deep, an abyss in the Mariana Trench with depths greater than 10,000 m. Since1952, when HMS Challenger II, following its namesake, returned to the Mariana Trench, 20 estimates (including the one from this study) of the depth of the Challenger Deep have been made. The location and depth estimates are as diverse as the methods used to obtain them; they range from early measurements with explosives and stop watches, to single- and multi-beam sonars, to submersibles, both crewed and remotely operated. In December 2014, we participated in an expedition to the Challenger Deep onboard Schmidt Ocean Institute’s R/V Falkor and deployed two free-falling, passive-acoustic instrument platforms, each with a glass-sphere pressure housing containing system electronics. At a nominal depth of 9,000 m, one of these housings imploded, creating a highly energetic shock wave that, as recorded by the other instrument, reflected multiple times from the sea surface and seafloor. From the arrival times of these multi-path pulses at the surviving instrument, in conjunction with a concurrent measurement of the sound speed profile in the water column, we obtained a highly constrained acoustic estimate of the Challenger Deep: 10,983 ± 6 m.
Generation of terahertz signal by photomixing Kelly sidebands of mode-locking fiber laser

We investigate the photomixing Kelly sidebands of soliton mode-locking fiber laser to generate the Terahertz (THz) signal. A simulation model about soliton fiber laser with obvious ±1 order Kelly sidebands is built up to design the sidebands with strong intensity, narrow bandwidth and adjustable spacing. It is found that the parameters of mode-locking fiber laser such as the total dispersion, filtering bandwidths, pump power of the laser play significant roles in determining the features of the ±1 order Kelly sidebands and the relationships between them are investigated. By photomixing the ±1 order sidebands, the experimental result shows that the desired THz signals with high optical-to-THz conversion are generated at frequencies of 0.187THz from the lab-made Yb-doped mode-locking fiber lasers. Well-designed Er-doped ring-cavity soliton fiber laser is used for obtaining THz signal of narrow linewidth with 1.35THz frequency tunable range.
A Bayesian Optimization Approach for Multi-Function Estimation for Environmental Monitoring Using an Autonomous Surface Vehicle: Ypacarai Lake Case Study

Bayesian optimization is a sequential method that can optimize a single and costly objective function based on a surrogate model. In this work, we propose a Bayesian optimization system dedicated to monitoring and estimating multiple water quality parameters simultaneously using a single autonomous surface vehicle. The proposed work combines different strategies and methods for this monitoring task, evaluating two approaches for acquisition function fusion: the coupled and the decoupled techniques. We also consider dynamic parametrization of the maximum measurement distance traveled by the ASV so that the monitoring system balances the total number of measurements and the total distance, which is related to the energy required. To evaluate the proposed approach, the Ypacarai Lake (Paraguay) serves as the test scenario, where multiple maps of water quality parameters, such as pH and dissolved oxygen, need to be obtained efficiently. The proposed system is compared with the predictive entropy search for multi-objective optimization with constraints (PESMOC) algorithm and the genetic algorithm (GA) path planning for the Ypacarai Lake scenario. The obtained results show that the proposed approach is 10.82% better than other optimization methods in terms of R2 score with noiseless measurements and up to 17.23% better when the data are noisy. Additionally, the proposed approach achieves a good average computational time for the whole mission when compared with other methods, 3% better than the GA technique and 46.5% better than the PESMOC approach.
Visual and Scent as Sensory Marketing Tools in the Dental Care Services: An Experimental Research Design Approach

The objective of this research is to examine the effect of visual and scent on perceived intimacy of a service provider and consumers’ dental anxiety, in the context of the healthcare industry, specifically dental clinic service. Further, this study also examined the possibility of interaction effect of visual and scent on both variables. A 2x2, full factorial, an experimental research design was conducted throughout a four-day experiment in a marketing lab of a large private university in Indonesia. The tools needed to analyse the data are SPSS data processing devices. Sampling method used in this study is nonprobability sampling purposive sampling by making criteria to have visited a dental clinic. This research managed to collect a total of 144 samples. Findings show that visuals only have a significant effect on store intimacy and dental anxiety. Scent has no significant effect on any of the variables we study. Additionally, we found no interaction effect between visual and scent in this context.
Co‒ordination studies of polyarene and halocarbon functionalised tertiary phosphines for explosives detection

Schiff base condensation of Polyaromatic Hydrocarbon (PAH) functionalised aldehydes and a range of alkyl functionalised primary amines was successfully undertaken. Subsequent reduction yielded new PAH‒substituted amines and the Mannich‒based condensation chemistry of these new amines was explored using HOCH2PR2 precursors to yield (9‒anth)CH2N(R)CH2X (X = PAd or PR’2) ligands. The co‒ordination of these new monophosphines to a readily available dichloroplatinum(II) metal centre was explored to form cis complexes cis–PtCl2{9– (anth)CH2N(iPr)CH2PAd}2 (2.1d), cis–PtCl2{9–(anth)CH2N(Bz)CH2PAd}2 (2.2d),cis–PtCl2{9–(anth)CH2N(nPr)CH2PAd}2 (2.3d), cis–PtCl2{9– (anth)CH2N(iPr)CH2PPh2} (2.1g) and cis–PtCl2{9–(anth)CH2N(iPr)CH2P(C6H4 o–OCH3)2} (2.1h). Further studies involving synthesis of the chelating bisphosphines [(2‒anth)CH2N(CH2PR2)2 and (1‒pyr)CH2N(CH2PR2)2] were undertaken. This was achieved using Mannich‒based condensation of PAH‒functionalised primary amines with HOCH2P(C6H4–o–OCH3)2 and gave rise to interesting behaviour upon co-ordination to a Pt(II) metal centre, with significant broadening observed in both the 1H and 31P{1H} NMR (ω1/2 ca. 73 Hz) spectra of these compounds.