bluuebunny/crossref_metadata_2025 huggingface dataset:
Synthesis of dual-responsive, highly fluorescent, non-conjugated polymer dots for Fe 3+ detection
Authors: Vahedi Forough , Arsalani Nasser , Amjadi Mohammad
Published: June 2024

Highly fluorescent non-conjugated polymer dots (PDs) were synthesized by an aqueous synthetic route using a hydrothermal method from polyester prepared with PEG and di-anhydride EDTA (DA-EDTA). The synthesized PDs display strong blue fluorescence with a high quantum yield (QY) of 45% in water and more than 45% in ethanol, dimethyl sulfoxide, N, N-dimethyl formamid, and acetone. The optical and structural properties of the PDs were investigated by UV–Vis, fluorescence spectrophotometry, EDX, FTIR, SEM, TEM, AFM, and DLS. The PDs were used as a sensitive fluorescence probe for Fe3+ ions detection, with a low detection limit of 1.28 µM. The linear range in which fluorescent intensity decreases with increasing Fe3+ is 0-120 µM. Besides, in the range of 20℃ to 70 ℃, fluorescent intensity declines with increasing temperature. Therefore, it can also be used as a thermometer. The spike recovery test confirmed the practicality of the method for the analysis of Fe3+ ions in tap water samples.
Application of Discrete Random Forest Algorithm in Multi-Person Asynchronous Parallel Disassembly Sequence Planning for Hydropower Station Equipment Maintenance
Authors: Li Bailin , Chen Ao , Wu Panqi , Zhang Chao , Fu Wenlong
Published: June 2024

Working procedures is the key link of equipment maintenance in hydropower stations. Excellent working procedures is beneffcial to improve maintenance quality and efffciency. However, for the complex hydropower station equipment with multiple parts, it is difffcult to obtain the multi-person collaborative working procedures of maintenance tasks. To overcome this problem, this paper establishes a multi-person asynchronous parallel disassembly sequence planning (DSP) model and solves it using a discrete random forest algorithm (DRFA). Firstly, based on the actual operation environment of the hydropower station, a disassembly model is constructed by considering the disassembly tools, disassembly direction, part distance, and working space. Secondly, DRFA is proposed. Meanwhile, a sub-tree fftting strategy and a sub-tree iteration mechanism are introduced to increase the probability of ffnding the optimal sequence. Thirdly, taking hydropower station equipment as example, higher quality disassembly sequencecan be obtained by DRFA compared with simpliffed discrete gravitational searchalgorithm (SDGSA), genetic algorithm (GA), and simpliffed swarm optimization(SSO), which reffects the applicability of the method.
Views and experience of non-hospitalised individuals with Long COVID of using pacing interventions: a mixed methods study
Authors: McMullan Christel , Haroon Shamil , Turner Grace , Aiyegbusi Olalekan , Hughes Sarah , Flanagan Sarah , Subramanian Anuradhaa , Nirantharakumar Krish , Davies Elin , Frost Chris , Jackson Louise , Guan Naijie , Alder Yvonne , Chong Amy , Buckland Lewis , Jeyes Felicity , Stanton David , Calvert Melanie
Published: June 2024

Background
Long COVID is highly prevalent and debilitating, with key symptoms including fatigue, breathlessness, and brain fog. Pacing is an approach to energy conservation used to help people with chronic conditions like ME/CFS manage the impact of their condition, and could be a useful strategy for people with Long COVID. The aim of this study was to explore the views and experiences of non-hospitalised adults with Long COVID of pacing as an intervention.
Methods
This mixed methods study is part of the Therapies for Long COVID (TLC) Feasibility trial. A feasibility questionnaire was developed for participants. In addition, a sub-sample of participants were interviewed at the end of the study.
Results
28 participants completed the feasibility questionnaire and 19 participants took part in a qualitative interview. Participants found that pacing helped improve motivation and activity planning. Concerns included challenges due to time constraints, complexity of the intervention, and limited instructions.
Conclusion
Pacing for Long COVID may offer potential benefits and is feasible but further research is required to demonstrate its benefits. Overall, research on pacing in the context of Long COVID has the potential to enhance our understanding of symptom management and rehabilitation strategies for this emerging population.
Graphene-Modified Concrete: Understanding Mechanical Behaviour with Varied Coarse Aggregates
Authors: Kaushik Pooja , Hassan Owais Ul , Mehmood Gauhar
Published: June 2024

Concrete, a widely used construction material, faces challenges such as resource depletion, noise, and dust pollution. Conventional concrete has a reduced lifespan and increased maintenance, with brittleness issues. To address these issues, graphene oxide, an admixture, has been proposed as an alternative binder in cement coarse aggregations. The study uses three types of coarse aggregations which employ coarse aggregates from different sites in Delhi: granite from Vasant Kunj (Phase-2), sandstone from Sarai Madhavpur, and quartzite from Delhi Metro Mall. The study aims to understand the synergistic effects of graphene oxide and aggregates on the mechanical properties of the composite, including compressive, tensile, and flexural strength. Graphene insertion in concrete results in ultra-high performance, with slump values decreasing as the percentage of graphene increases. Sandstone, quartzite, and granite exhibit the slump decrease, with sandstone showing the maximum decrease. Graphene incorporation positively influences compressive strength, with granite showing the most significant improvement. Split tensile strength also shows a notable increase, with granite demonstrating the most significant increase, even at moderate graphene percentages. Flexural strength also shows a substantial increase. This is due to enhanced bonding between aggregate particles and graphene oxide sheets, resulting in heightened tensile strength and improved crack resistance.
Global-scale multidecadal variability in climate models and observations. Part II: The stadium wave
Authors: Kravtsov Sergey , Westgate Andrew , Gavrilov Andrei
Published: June 2024

A significant fraction of multidecadal fluctuations in the reanalysis-based gridded estimates of the observed climate variability over the past century and a half lie outside of the envelope generated by ensembles of climate-model historical simulations. Several pattern-recognition methods have been previously used to map out a truly global reach of the observed vs. simulated climate-data differences; in our own work we dubbed these global discrepancies the stadium wave to highlight their most striking spatiotemporal characteristic. Here we used a novel combination of such methods in conjunction with a large multi-model ensemble and two popular twentieth-century reanalysis products to: (i) succinctly describe the geographical evolution of the observed stadium wave in the annually sampled near-surface atmospheric temperature and mean sea-level pressure fields in terms of three basic patterns; (ii) show the robustness of this identification with respect to methodological details, including the demonstration of the truly global character of the stadium wave; and (iii) provide essential clues to its dynamical origin. Part I of this study decomposed all input time series into the forced signal and the residual internal variability; multi-model forced-signal estimates were also decomposed into their common-evolution part and the individual-model residuals. Analysis of the latter residuals suggests a contribution to the stadium-wave dynamics from a delayed climate response to variable external forcing despite the observed stadium-wave patterns’ exhibiting the magnitudes and the level of global teleconnectivity unmatched by the forced-signal residuals. Part III of this paper will compare the observed stadium wave with the model simulated internal patterns.
Isolation and Identification of Endophytic Fungi from the Roots of two epiphytic orchids: Rhynchostylis retusa (L.) Bl. and Vanda tessellata (L.) Bl
Authors: Sayem M Abu , Miah M Shahin , Hossain Mohammad Musharof
Published: June 2024

Two fungal endophytes were isolated and identified from two indigenous orchids of Bangladesh namely, Rhynchostylis retusa (L.) Bl. and Vanda tessellata (L.) Bl. Nature of fungal colonization, seasonal variations of colonization in root cortex cells were also studied. The fungal endophytes isolated from two different orchids differed in their cultural morphology and microscopic features such as colony morphology, colour of the colony, presence/absence of monilioid cells or spores and diameter of vegetative hyphae. The microscopic features i.e., hyphal structure, right-angle branching of hyphae, slight constriction at the branching point, shape and diameter of monilioid cells of the endophytic fungus isolated from R. retusa showed resemblance with the anamorphic Rhizoctonia-like fungi Ceratobasidium sp. On the other hand, the fungal endophytes isolated from the roots of V. tessellata produced huge number of spores. The cultural characteristics and spore morphology of this fungi corroborated resemblance with pathogenic fungi, Fusarium sp. The identity of the fungi was further reconfirmed through sequencing of the internal transcribed spacer (ITS) of the nuclear ribosomal DNA (nrDNA). The BLASTn search of ITS region sequences of the endophytic fungi isolated from R. retusa exhibited maximum similarity (97%) with an orchid mycorrhizal fungi (OMF), Ceratobasidium papillatum (GeneBank Accession No. OQ073691), while the fungal endophyte isolated from V. tessellata showed maximum similarity (99%) with Fusarium ambrosium (GeneBank Accession No. OP752102). The phylogenetic tree constructed using ITS region sequences of the isolated fungal endophytes and their closely linked species from genebank data developed two distinct groups. The conventional and molecular approaches applied for identification of these OMF can be followed for easy and accurate identification of other OMF.
ZTA: A Novel Zero Trust Framework for Detection and Prevention of Malicious Android Applications
Authors: Nazir Aleena , Iqbal Zafar , Muhammad Zia
Published: June 2024

The proliferation of preloaded apps and third-party applications has raised significant concerns regarding user security and privacy. This study introduces the Zero Trust Architecture (ZTA), a novel approach to addressing the issues caused by poorly designed vulnerable mobile applications. ZTA employs a comprehensive strategy to safeguard user privacy, incorporating thorough app permission analysis alongside dynamic behavior assessment. The proposed framework closely monitors real-time app behavior and leverages the MITRE ATT&CK framework to identify security threats, vulnerabilities, and essential Tactics, Techniques, and Procedures (TTPs). The ZTA empowers users to make informed choices about app usage, promote data security, and cultivate a safer environment. Through this framework, users can confidently decide on app usage, ensuring the safeguarding of their data and fostering a more secure mobile app ecosystem. This research presents a proactive approach to privacy-conscious app utilization, bolstering user trust in the continually evolving realm of Android applications.
Modulation of Neural Correlates of Model-based Performance with Impulsivity and Compulsivity
Authors: Dück Kerstin , Wüllhorst Raoul , Overmeyer Rebecca , Endrass Tanja
Published: June 2024

Impaired goal-directed behavior is associated with a range of mental disorders, implicating underlying transdiagnostic factors. While compulsivity has been linked to reduced model-based (MB) control, impulsivity has rarely been studied in the context of reinforcement learning despite its links to reward processing and cognitive control. This study investigated the neural mechanisms underlying MB control and the influence of impulsivity and compulsivity. We analyzed EEG data from 238 individuals during a two-step decision making task. Single-trial analyses revealed that while feedback-related negativity (FRN) amplitudes were higher after common transitions and negative/neutral reward prediction error (RPE), the P3a and P3b were enhanced after rare transitions and both positive and negative RPE. In a second step, we regressed the mean b values of the effect of RPE on the EEG signals onto self-reported impulsivity and compulsivity and weighting parameter w (representing behavioral MB control). The effect of RPE on FRN-related activity was mainly associated with higher wscores. The interaction of impulsivity and w influenced both FRN- and P3a-related activity. The modulation of P3a by RPE was also negatively associated with compulsivity, pointing to a deficient mental model in highly compulsive individuals. Further research is needed to understand these alterations in decision-making processes.
Identification of soluble biomarkers that associate with distinct manifestations of long COVID
Authors: Buggert Marcus , Gao Yu , Cai Curtis , Adamo Sarah , Biteus Elsa , Kamal Habiba , Dager Lena , Miners Kelly , Llewellyn-Lacey Sian , Ladell Kristin , Sabberwal Pragati , Bentley Kirsten , Wu Jinghua , Akhirunnesa Mily , Jones Samantha , Julin Per , Lidman Christer , Stanton Richard , Davies Helen , Aleman Soo , Price David , Goepfert Paul , Deeks Steven , Peluso Michael
Published: June 2024

Long COVID is a heterogeneous clinical syndrome of uncertain etiology triggered by infection with SARS-CoV-2. We employed ultrasensitive approaches to profile the immune system and plasma proteome in healthy convalescent individuals and patients with long COVID. Symptomatic disease was not consistently associated with quantitative differences in immune cell lineage composition or antiviral T cell immunity. Healthy convalescent individuals nonetheless exhibited higher titers of neutralizing antibodies against SARS-CoV-2 than patients with long COVID, and extensive phenotypic analyses revealed a subtle increase in the expression of some coinhibitory receptors, most notably PD-1 and TIM-3, among SARS-CoV-2 nonspike-specific CD8+ T cells in patients with long COVID. We further identified a plasma biomarker signature of disease linking breathlessness with apoptotic inflammatory networks centered on the hub protein TRAF2 and dysregulated pathways associated with lung injury, cell cycle progression, and platelet activation, which could potentially inform the diagnosis and treatment of long COVID.
Multi-Modality Deep Infarct: Non-invasive identification of infarcted myocardium using composite in-silico-human data learning
Authors: Mehdi Rana Raza , Kadivar Nikhil , Mukherjee Tanmay , Mendiola Emilio A. , Shah Dipan J. , Karniadakis George , Avazmohammadi Reza
Published: June 2024

Myocardial infarction (MI) continues to be a leading cause of death worldwide. The precise quantification of infarcted tissue is crucial to diagnosis, therapeutic management, and post-MI care. Late gadolinium enhancement-cardiac magnetic resonance imaging (LGE-CMR) is regarded as the gold standard for precise infarct tissue localization in MI patients. A fundamental limitation of LGE-CMR is the invasive intravenous introduction of gadolinium-based contrast agents that present potential high-risk toxicity, particularly for individuals with underlying chronic kidney diseases. Herein, we develop a completely non-invasive methodology that identifies the location and extent of an infarct region in the left ventricle via a machine learning (ML) model using only cardiac strains as inputs. In this transformative approach, we demonstrate the remarkable performance of a multi-fidelity ML model that combines rodent-based in-silico-generated training data (low-fidelity) with very limited patient-specific human data (high-fidelity) in predicting LGE ground truth. Our results offer a new paradigm for developing feasible prognostic tools by augmenting synthetic simulation-based data with very small amounts of in-vivo human data. More broadly, the proposed approach can significantly assist with addressing biomedical challenges in healthcare where human data are limited.
Electron Density Distribution using Maximum Entropy Method and Conductivity Studies of Highly Dense BaZr0.85Ho0.10Y0.025Nd0.025O3-δ Electrolyte Ceramic for Intermediate Temperature Solid Oxide Fuel Cells
Authors: Singh Bijendra , Kumar Sandeep , Singh Sunder , Kumar Upendra , Kumar Manindra , Kumar Anil , Saini Deepash Shekhar
Published: June 2024

In this research work, highly dense BaZr0.85Ho0.10Y0.025Nd0.025O3-δ electrolyte ceramic was synthesized through a cost-effective flash pyrolysis route followed by conventional sintering for intermediate-temperature solid oxide fuel cells. The calcined powder and sintered pellet were characterized through various techniques like HRXRD, HRTEM, FESEM, EDS, and Raman spectroscopy. The XRD pattern of calcined and sintered pellet shows the pure cubic phase with space group symmetry through the Rietveld refinement. The study of the electron density distribution of calcined powder and sintered pellet calculated by the maximum entropy method reveals the presence of oxygen vacancies at the octahedral site in the sintered sample. The microstructure of the fracture surface of the sintered sample indicates highly dense with a relative density of 97.4% through FESEM. The Raman analysis confirms the distortion along the c-axis and oxygen vacancies in the octahedral site of BaZr0.85Ho0.10Y0.025Nd0.025O3-δ. Impedance spectroscopy measurements was conduct in the temperature range of 50 to 700 ℃ and frequency range of 1 Hz to 1 MHz. The Nyquist plots in the temperature range of 350 to 700 ℃ provide information of three types of relaxations corresponding to grain and grain boundary, and electrode effect. The temperature-dependent exponent (n) associated with grain and grain boundary decreases with the increase in temperature, indicating that large polaron hopping is involved in the electrical conduction mechanism.
High-Altitude Parabolic Detection: An Innovative Algorithm That Combines MOG-CNN and Enhanced SORT
Authors: Zhu QiGuang , Liu Meng , Wu WenLong , Chen WeiDong
Published: June 2024

Addressing the challenges of complex backgrounds, small parabolic targets, indistinct appearance features of parabolas, and easy loss of parabolic tracking in high-altitude parabolic object detection, this paper proposes a hybrid approach integrating the Mixture of Gaussians Background Modeling (MOG) algorithm with neural networks and an improved Simple Online and Realtime Tracking (SORT) algorithm for parabolic tracking. Firstly, to mitigate the issues of small target parabolas and complex backgrounds, a region-specific conditional filtering is introduced to reduce non-parabolic foreground in foreground detection while preserving parabolic foreground. Secondly, to tackle the problem of indistinct appearance features of parabolas, a multi-frame channel fusion technique is employed to enhance motion features, and a lightweight classification network is designed to differentiate parabolic objects. Finally, to address the challenge of easy loss of parabolic tracking, the state space and matching metrics of SORT are improved to better match parabolic trajectories. Experimental results demonstrate that the improved parabolic detection method reduces detection quantity by 97\% compared to the original MOG algorithm while exhibiting a 7\% decrease in recall rate. Additionally, compared to the original SORT algorithm, the improved parabolic tracking method reduces the number of ID switches by 50%, increases the MOTA metric by 8%, and increases the TIOU metric by 7%.
Code: https://figshare.com/articles/dataset/High-Altitude Object Detection algorithm/25778430. Dataset:https://figshare.com/articles/dataset/High-Altitude Object Detection Dataset/25778289.
Laser-Activated Lightweight Porous Linear Actuation Micro Mechanisms through Multiscale Topology Optimization with Considering Radiation
Authors: Ali Musaddiq Al , Shimoda Masatoshi
Published: June 2024

This study applies multi-physics concurrent multiscale topology optimization to develop a lightweight porous linear actuation mechanism activated by laser energy. It meticulously explores thermal dissipation mechanisms, incorporating conduction, convection, and radiation dynamics. By examining various numerical cases, the study reveals a substantial 45% performance improvement in porous designs compared to solid actuators. The investigation extends to simultaneous optimization of multiscale porous displacement actuators, achieving a remarkable 75% weight reduction and demonstrating significant performance enhancements over single-scale designs. The increased freedom in micro-scale design allows more efficient material distribution, optimizing both macro and overall layouts. Sequential optimization of macro and micro-scale actuators is contrasted with concurrent multiscale optimization, showing inferior performance for separate optimizations. The study also delves into topology optimization under energy dissipation, focusing on multiple-rate thermal convection and revealing adaptive design behaviors in response to thermal stresses. Macro-scale designs influenced by convection exhibit perpendicular links and adaptive microstructures to enhance resilience and elasticity. The investigation also includes thermal radiation and convection, highlighting intricate design considerations for effective thermal dissipation. Ultimately, this study advances the understanding of multiscale effects in topology optimization, paving the way for more efficient and lightweight laser-activated porous actuators.
Improved global estimation of seasonal variations in C3 photosynthetic capacity based on eco-evolutionary optimality hypotheses and remote sensing
Authors: Liu Yihong , Chen Jing M. , Xu Mingzhu , Wang Rong , Fan Weiliang , Li Wenyu , Kammer Lucas , Prentice Colin , Keenan Trevor F. , Smith Nicholas G.
Published: June 2024

The maximum carboxylation rate of plant leaves (Vcmax) at 25°C (Vcmax25) is a fundamental parameter in terrestrial biosphere models (TBMs) to estimate carbon assimilation of C3 biomes. It has been reported that ignoring the seasonal variations inVcmax25induces considerable uncertainties in TBMs. Recently, a model was developed to estimateVcmax25of C3 biomes mechanistically from climate data based on eco-evolutionary optimality hypotheses, which hypothesized that plants acclimate to the environment to achieve maximum carbon assimilation with minimum related costs. However, uncertainties of this optimality-based model (EEO model) have been found to correlate to leaf nitrogen content, partly due to the lack of parameterization on how the acclimation ofVcmax25is constrained by photosynthetic nitrogen other than that in RuBisCO. This constraint could be parametrized by remote sensing methods globally. In this study, we developed remote sensing methods to estimate leaf absorptance of radiation based on MODIS LCC (leaf chlorophyll content) data and the ratio of the maximum electron transport rate of plant leaves (Jmax) toVcmaxat 25°C (rJV25) based on TROPOMI SIF (solar-induced chlorophyll fluorescence) data (RS-rJV25). These two parameters contain photosynthetic nitrogen information related to light harvesting, electron transport, and carboxylation, and they were then incorporated into the EEO model to constrain howVcmax25acclimates to the environment. The simulatedVcmax25constrained by MODIS LCC and RS-rJV25agreed well with seasonal variations in field-measuredVcmax25at 18 sites (R2 = 0.76, RMSE = 13.40 µmol·m− 2·s− 1), showing better accuracy than the simulation without incorporating leaf absorptance andrJV25(R2 = 0.63, RMSE = 31.59 µmol·m− 2·s− 1). Our results indicated that variations in leaf absorptance andrJV25constrained the acclimation ofVcmax25to the environment and contributed to the variation inVcmax25that cannot be fully captured by environmental factors alone in the EEO model. The remote-sensing-based leaf absorptance andrJV25captured the sensitivity of these two parameters to environmental conditions on the global scale. The influence of leaf absorptance onVcmax25was primarily affected by the irradiance level, whilerJV25was determined by the growing season mean temperature. The simulatedVcmax25had large spatiotemporal variations on the global scale, and the environment drove the variation pattern more greatly than the biome distribution. With reasonably accurate seasonal variations inVcmax25, this study can help improve the global carbon cycle and leaf trait modelling.
Water Reuse in the Hill Country: Lessons from Existing Reuse Facilities in Texas and Opportunities to Advance Reuse in Comal County
Authors: Hanes Rachel
Published: June 2024

The Greater Edwards Aquifer Alliance outlines the opportunities present in the Texas Hill Country to use recycled water to alleviate the burdens placed on the Edwards and Trinity aquifers by focusing on the present state of recycled water use in Comal County, Texas. The impacts of population growth, prolonged drought, and wastewater disposal on water sources in Comal County are analyzed along with current sources of water reuse to show where recycled water can be utilized effectively. Reclaimed water systems in seven municipalities across Texas are analyzed as case studies to provide examples for further implementation. Water reuse is integral to protecting water supplies and ensuring counties in the Hill Country can adequately protect the health, safety, and quality of life of current and future residents. Water reuse is a vastly underutilized tool in the effort to manage water supplies in the Hill Country, and there are a variety of authorization, financing, and implementation opportunities present in the region to take better advantage of this resource.
Wegner's Ising gauge spins versus Kitaev's Majorana partons: Mapping and application to anisotropic confinement in spin-orbital liquids
Authors: Seifert Urban F. P. , Moroz Sergej
Published: June 2024

Emergent gauge theories take a prominent role in the description of quantum matter, supporting deconfined phases with topological order and fractionalized excitations. A common construction of \mathbb{Z}_2ℤ2 lattice gauge theories, first introduced by Wegner, involves Ising gauge spins placed on links and subject to a discrete \mathbb{Z}_2ℤ2 Gauss law constraint. As shown by Kitaev, \mathbb{Z}_2ℤ2 lattice gauge theories also emerge in the exact solution of certain spin systems with bond-dependent interactions. In this context, the \mathbb{Z}_2ℤ2 gauge field is constructed from Majorana fermions, with gauge constraints given by the parity of Majorana fermions on each site. In this work, we provide an explicit Jordan-Wigner transformation that maps between these two formulations on the square lattice, where the Kitaev-type gauge theory emerges as the exact solution of a spin-orbital (Kugel-Khomskii) Hamiltonian. We then apply our mapping to study local perturbations to the spin-orbital Hamiltonian, which correspond to anisotropic interactions between electric-field variables in the \mathbb{Z}_2ℤ2 gauge theory. These are shown to induce anisotropic confinement that is characterized by emergence of weakly-coupled one-dimensional spin chains. We study the nature of these phases and corresponding confinement transitions in both absence and presence of itinerant fermionic matter degrees of freedom. Finally, we discuss how our mapping can be applied to the Kitaev spin-1/2 model on the honeycomb lattice.
Object Detection Model for Web-Based Physical Distancing Detector Using Deep Learning
Authors: Chowanda Andry , Sariputra Ananda Kevin Refaldo , Prananto Ricardo Gunawan
Published: June 2024

The pandemic has changed the way people interact with each other in the public setting. As a result, social distancing has been implemented in public society to reduce the virus’s spread. Automatically detecting social distancing is paramount in reducing menial manual tasks. There are several methods to detect social distance in public, and one is through a surveillance camera. However, detecting social distance through a camera is not an easy task. Problems, such as lighting, occlusion, and camera resolution, can occur during detection. The research aims to develop a physical distancing detector system that is adjusted to work with Indonesian rules and conditions, especially in Jakarta, using deep learning (i.e., YOLOv4 architecture with the Darknet framework) and the CrowdHuman dataset. The detection is done by reading the source video, detecting the distance between individuals, and determining the crowd of individuals close to each other. In order to accomplish the detection, the training is done with CSPDarknet53 and VGG16 backbone in YOLOv4 and YOLOv4 Tiny architecture using various hyperparameters in the training process. Several explorations are made in the research to find the best combination of architectures and fine-tune them. The research successfully detects crowds at the 16th training, with mAP50 of 71.59% (74.04% AP50) and 16.2 Frame per Second (FPS) displayed on the web. The input size is essential for determining the model’s accuracy and speed. The model can be implemented in a web-based application.
Classification Taxonomies Genus of 90 Animals Using Transfer Learning Resnet-152
Authors: Saputro Satria Nur , Adhinata Faisal Dharma , Athiyah Ummi
Published: June 2024

The process of learning theory and the limited ability to remember anything, especially a foreign language, often cause students to have difficulty understanding lessons, especially in determining the type and taxonomy of the animal. With the assistance of computer vision technology, students can more effectively face various challenges, enhance their understanding, and improve their ability to apply the concept of animal classification. The research classifies the taxonomy of 90 animals using Transfer Learning ResNet 152. It aims to analyze the performance of Transfer Learning ResNet 152 on the 90-animal dataset. The results show that in Model A with an architecture with frozen layers in 6 ResNet blocks, the highest evaluation value obtained is 0.9222 on Batch size 4 with Dropout 6, 0.9241 on Batch size 8 with Dropout 7, 0.9259 on Batch size 16 with Dropout 8, and 0.9296 on Batch size 32 with Dropout 4 and Dropout 7. Meanwhile, in model B with an architecture with frozen layers in 5 ResNet blocks and one non-frozen block, the highest evaluation value obtained is 0.7611 on Batch size 4 with Dropout 8, 0.8713 on Batch size 8 with Dropout 2, 0.8852 on Batch size 16 with Dropout 1, and 0.9204 on Batch size 32 with Dropout 3.
Resimli Çocuk Kitaplarında Toplumsal Cinsiyet Eşitliği Konusu Üzerine Bir İnceleme
Authors: Derdiyok Rukiye
Published: June 2024

Toplumsal cinsiyet eşitliği, kadın ve erkeklerin eşit sorumluluk, hak ve fırsatlara sahip olmalarını ifade etmektedir. Bu makalenin amacı cinsiyet eşitliği konusunun resimli çocuk kitaplarında nasıl ele alındığını incelemektir. Kategori olarak okul öncesi resimli çocuk kitapları seçilmiştir. Bunun sebebi 3-6 yaş aralığındaki çocukların kendilerini ve sosyal çevrelerini tanıyabilmeleri ve davranış kalıplarının oluşmaya başlamasıdır. Yapılan literatür taraması sonucunda konu ile bağlantılı 10 adet kitap incelenmiştir. Kitaplar tasarım ilkeler, iç yapı ve dış yapı özellikleri açısından irdelenmiştir. Kitapların stereotip düşünce içermeyen ve toplumsal cinsiyet eşitliğini destekleyen kitaplar olmasına özen gösterilmiştir. İnceleme sonucunda örnek kitapların teknik özelliklerinin çoğunlukla uygun olduğu gözlenmiştir. Kitaplara içerik açısından bakıldığında toplumsal cinsiyet eşitliğinin önemsendiği, kız ile erkek çocuklar için eşitlikçi yaklaşımların olduğu gözlenmiştir. İnceleme sonucunda yerli yapımların azlığı dikkat çekmiştir. Yerli yayınlar artırılabilir ve tasarım açısından daha nitelikli ve özgün örnekler oluşturulabilir. Bu bağlamda uzmanların işbirliği büyük önem taşımaktadır.
Avaliação da expansão do gás natural como ponte para a transição energética no Brasil
Authors: Barbosa Luciana Pereira , Moura Lyzette Gonçalves Moraes de , Barros Filho Allan Kardec Duailibe
Published: June 2024

O objetivo desse artigo consiste em realizar uma avaliação da expansão do gás natural enquanto ponte para a transição energética de baixo carbono em termos de infraestrutura, disponibilidade, consumo e produção. Os resultados alcançados durante o estudo, puderam dar o enfoque necessário na questão da interiorização do gás, mesmo sabendo que as malhas de gasoduto estão localizadas, em sua maioria nas proximidades do litoral do país, haja visto tratar-se da região que tem mais indústria. Por outro lado, isso dificulta o acesso a este recurso em regiões centrais do país por este modal, sendo necessário viabilizar outras formas logísticas que possam contribuir com o desenvolvimento econômico dos estados, em especial o Estado do Maranhão, pois o mesmo apresenta grande quantidade de bloco exploratório, e isso agregaria significativamente quanto ao seu desenvolvimento econômico no estado. Logo, é necessário estratégias para que elevem o acesso a estes recursos do gás natural.
Avaliação dos mecanismos de previsão energética com fontes renováveis para maximização da matriz energética brasileira utilizando machine learning
Authors: Gomes Barreto Abreu Laís , Mauricio Yepes Maya Diego , Rafael Melian Cobas Vladimir , José Garcia Pabón Juan , Proenza Perez Nestor
Published: June 2024

O presente estudo concentra-se no cenário energético brasileiro e destaca o aumento progressivo do uso de fontes renováveis na matriz de energia elétrica do país. O principal objetivo deste trabalho é contribuir para a busca de soluções e impulsionar debates e reflexões sobre as ações futuras necessárias para o planejamento energético. Para isso, a pesquisa emprega ferramentas computacionais baseadas em machine learning e mineração de dados, utilizando fontes de dados governamentais e de mercado de energia. A metodologia abrange a utilização de ferramentas computacionais para projetar a previsão do mercado de energia elétrica no país, inclui a execução de modelos de previsão, destacando o comportamento do mercado energético ao longo do tempo, a partir dos métodos Redes Neurais Multilayer Perceptron (MLP), Regressão do Processo Gaussiano (GPR) e Regressão Linear para projetar a geração elétrica por fonte no Brasil. Os resultados indicam um crescimento considerável das fontes renováveis no mercado energético nacional até o ano de 2030, aproximando-se do objetivo do Plano Decenal de Expansão de Energia de atingir 90% de renovabilidade, abrangendo fontes como hidrelétrica, biomassa, eólica e solar. O método de Regressão Linear alcançou 86% de renovabilidade, enquanto o método de GPR atingiu 90%, e o método das MLP chegou a 88%. A projeção da previsão do mercado de energia elétrica, possibilitou a identificação dos padrões de comportamento mercadológico, permitindo antecipar as tendências e mudanças no mercado. Essas previsões têm o propósito de fornecer informações para apoiar o desenvolvimento de ações no processo de planejamento energético, contribuindo para a transição para fontes mais sustentáveis e renováveis de energia no Brasil.
Estimativa de parâmetros de modelos não-lineares usando o EMSO, um programa de código aberto para modelagem, simulação, controle e otimização de processos
Authors: Rodrigues Pinheiro Thaís , Marina Pinotti Laura , Cordeiro Mancini Maurício , Barroso Soares Vinícius
Published: June 2024

Simuladores são ferramentas valiosas para aplicações que vão desde a validação de projetos, operabilidade de plantas, até aumento de produção e redução de custos. Essas características, e outras, fizeram crescer o interesse industrial por softwares para modelagem, simulação, controle e otimização de processos. Todavia, ainda existe uma grande insatisfação dos usuários, principalmente com relação ao uso/aprendizado e custo elevado. No presente trabalho, rotinas de estimativa não-linear de parâmetros foram desenvolvidas na plataforma EMSO (Environment for Modelling, Simulation and Optimization), um programa livre e de código aberto, visando a simulação e a discriminação dos modelos mais adequados à descrição da cinética de crescimento celular da levedura Saccharomyces cerevisiae em biorreator batelada para a produção de álcool. Os dados experimentais aqui utilizados foram adotados de trabalhos disponíveis na literatura. Os modelos cinéticos de Monod, Moser, Contois e Andrews foram avaliados. Os critérios usados para a discriminação dos modelos foram o desvio médio absoluto, o erro percentual absoluto médio e o quadrado do coeficiente de correlação entre valores preditos e observados. Com base nos resultados obtidos, foi possível concluir que o modelo de Contois apresentou os melhores resultados com desvio médio absoluto de 4,1683 g/L e 0,2451 g/L para a curva de substrato e de crescimento celular, respectivamente e ainda erro percentual absoluto médio de 9,82% e 17,67% para a curva de substrato e de crescimento celular, respectivamente. Além disso, apresentou valores de coeficiente de correlação acima de 0,98 para ambas as curvas.
Aproveitamento de dejeto bovino para a produção de biogás
Authors: Salvador Belchior Dinis Martins Francisco João , Mesquita Bruel Gabriela , Correia Souza Taís Rosângela , Esposito Marcelo
Published: June 2024

No presente trabalho, como atividade experimental foi desenvolvido um protótipo de biodigestor do tipo batelada, usando um barril de cerveja descartável, de plástico PET (Polietileno tereftalato). Os dejetos foram coletados na exploração leiteira da Universidade de Évora (UÉ - Polo da Mitra/Portugal). Como parte da análise foram empregadas duas metodologias para estimar o potencial de biogás e biometano a partir de plantéis bovinos no Brasil. Pela divergência de valores na produção diária percebeu-se uma lacuna científica que poderia ser investigada em termos globais. O título de um novo trabalho poderia ser: modelo para a produção de biogás a partir de dejetos de bovinos leiteiros. A composição do biogás foi analisada por GC (cromatografia gasosa). A desvantagem é que por GC não foram analisadas as quantidades de amônia e gás sulfídrico. Detectou-se uma quantidade de 46%mol de N2 o que é extremamente alta. O nitrogênio faz parte da estrutura molecular das proteínas e pode variar de acordo com o tipo de ração, pastagem ou silagem adicionada à alimentação do animal. Contudo o aproveitamento dos dejetos animais para a produção de biogás na UÉ não é suficiente para manter a exploração autossustentável (energia elétrica, aquecimento de água e do ambiente).
Implantação de serviço multidisciplinar em estomatologia e patologia oral
Authors: Thalía Rissa Silva  , Vinícius Gonçalves de Souza  , Amaro José Alves Júnior  , Luís Henrique da Silva Lima  , Damilys Joelly Souza Santos  , Tatiana Santos Araújo  , Ludimila Paula Vaz Cardoso  , Carla Silva Siqueira Miranda
Published: June 2024

A maioria das doenças bucais pode ser prevenida por medidas individuais, comunitárias e profissionais, mas a acessibilidade é dificultada por recursos limitados e mal distribuídos. Para reduzir o risco desses agravos, os sistemas de saúde bucal precisam ser orientados no sentido do fortalecimento da atenção e prevenção primária à saúde. Objetivo: Avaliar a implantação de serviço de estomatologia e patologia oral vinculado ao SUS e o perfil clínico-epidemiológico dos pacientes atendidos. Material e métodos: Avaliaram-se as ações de educação permanente em saúde, a qualidade do serviço prestado aos pacientes e o perfil de pacientes atendidos no período de novembro de 2017 a fevereiro de 2020. Resultados: A média de avaliação da educação permanente foi igual ou superior a 8,5 em todos os critérios avaliados. O tempo entre a percepção do paciente e a procura do atendimento, entre a triagem e o atendimento no serviço especializado e entre o atendimento do serviço e a emissão do laudo anatomopatológico foram de, respectivamente, 688,9, 22,7 e 7,9 dias. Observou-se concordância entre o diagnóstico clínico e o diagnóstico anatomopatológico em 78,8% dos casos. Lesões bucais foram detectadas em 35,3% dos pacientes; destes, 75,2% realizaram biópsia. No grupo com lesões bucais, a mediana de idade foi de 54 anos, sendo 55,2% do sexo feminino, 33,3% se declaram brancos, 49,5% são tabagistas/ex-tabagistas e 31,4% eram hipertensos. Conclusão: Este estudo reforça a importância e necessidade de serviços multiprofissionais com foco na atenção primária à saúde para prevenção, diagnóstico precoce e tratamento de lesões bucais.
Protocolo para cimentação de pinos de fibra de vidro imediatamente após a obturação do canal radicular: revisão da literatura
Authors: Alana Akemi Okamura  , Julia Daniel
Published: June 2024

Os pinos de fibra de vidro são indicados na reconstrução de dentes com extensa fratura coronária e que necessitam de tratamento endodôntico. A sequência clínica ainda hoje é um grande desafio, principalmente quando a cimentação do pino é feita imediatamente após o término do tratamento endodôntico, em que vários fatores podem influenciar na adesividade do pino de fibra de vidro ao canal radicular, como a interferência da solução irrigadora, o resíduo do cimento endodôntico usado na obturação do canal e a escolha do cimento resinoso. A previsibilidade do sucesso depende de um planejamento adequado tanto para evitar a contaminação do canal radicular como para conseguir uma adequada adesão entre as interfaces envolvidas. Objetivo: Elaborar um protocolo para cimentação de pinos de fibra de vidro, imediatamente após a obturação do canal radicular, por meio de uma revisão de literatura, a fim de ser de grande valia para o uso na clínica odontológica. Resultados: O protocolo elaborado aqui em questão se baseia no uso do cimento resinoso dual convencional e autoadesivo. Conclusão: Embora a cimentação do pino de fibra de vidro imediatamente após a obturação do canal radicular requeira cuidado em virtude da cura do cimento endodôntico, seguindo os critérios pré-cimentação e a escolha do cimento obturador, a chance de insucesso diminui potencialmente.
Withdrawn: CircRNA_0008668 Sponges miR-1301-3p to Promote the Inflammatory Response in Allergic Rhinitis by Upregulating GATA6 Expression
Authors: Xiao Xiyan , Zhai Feng , Yang Yue , Chen Jie
Published: June 2024

The article has been withdrawn at the request of the author.

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Discovery of an EP300 Inhibitor using Structure-based Virtual Screening and
Bioactivity Evaluation
Authors: Pan Dabo , Huang Yaxuan , Jiang Dewen , Zhang Yonghao , Wu Mingkai , Han Minzhen , Jin Xiaojie
Published: June 2024

Background:

EP300 (E1A binding protein p300) played a significant role in serial diseases such as
cancer, neurodegenerative disease. Therefore, it became a significant target.

Methods:

Targeting EP300 discovery of a novel drug to alleviate these diseases. In this paper, 17 candidate
compounds were obtained using a structure-based virtual screening approach, 4449-0460, with an IC50 of 5.89
± 2.08 uM, which was identified by the EP300 bioactivity test. 4449-0460 consisted of three rings. The middle
benzene ring connected the 5-ethylideneimidazolidine-2,4-dione group and the 3-F-Phenylmethoxy group.

Results:

Furthermore, the interaction mechanism between 4449-0460 and EP300 was explored by combining
molecular dynamics (MD) simulations and binding free energy calculation methods.

Conclusion:

The binding free energy of EP300 with 4449-0460 was -10.93 kcal/mol, and mainly came from
the nonpolar energy term (ΔGnonpolar). Pro1074, Phe1075, Val1079, Leu1084, and Val1138 were the key residues
in EP300/4449-0460 binding with more -1 kcal/mol energy contribution. 4449-0460 was a promising inhibitor
targeting EP300, which had implications for the development of drugs for EP300-related diseases.
Long Non-coding RNA DANCR Regulates the Proliferation and Migration of Human Adipose-derived Mesenchymal Stromal Cells in Inflammation
Conditions
Authors: Yan Ran , Dong Ping , Yang Zhigang , Cao Rui , Xiao Ran , Liu Xia
Published: June 2024

Background:

Mesenchymal stromal cells (MSCs) and Dexamethasone (Dex) are both
effective methods to treat inflammatory diseases. However, the interaction between inflammatory
factors, Dex, and MSCs in repair is not fully understood. The purpose of this study is to clarify
the effects and mechanisms of glucocorticoids on the tissue repair characteristics of MSCs in an
inflammatory environment.

Methods:

This is an experimental study. Human adipose-derived mesenchymal stromal cells
(hASCs) were cultured, and Long non-coding RNA (lncRNA) differentiation antagonizing nonprotein
coding RNA (DANCR) expression was detected after treatment with Dex and inflammation
factors. Additionally, DANCR was knockdown or overexpressed before Dex or tumor necrosis
factor-alpha (TNF-α) treatments, respectively. hASC proliferation, cell cycle, and migration
ability were analyzed to evaluate the effects of DANCR in hASCs treated with Dex or TNF-α. Nuclear
factor-kB (NF-κB) pathway inhibitors were used to clarify the signal pathway that DANCR
involved. All data are presented as the mean ± standard deviation. The two-tailed Student's t-test
or one-way analysis of variance (ANOVA) was used to determine the statistical differences between
groups.

Results:

Dex decreased the proliferation and migration of hASCs and upregulated DANCR expression
in a dosage-dependent relationship. The knockdown of DANCR reversed Dex's repression
of hASC proliferation. Moreover, DANCR was decreased by inflammatory cytokines, and
overexpressing DANCR alleviated the promotion effects of TNF-α on hASC proliferation and migration.
Furthermore, mechanistic investigation validated that DANCR was involved in the NF-
κB signaling pathway.

Conclusions:

We identified a lncRNA, DANCR, that was involved in Dex and inflammation-affected
hASC proliferation and migration. Dex reduced the proliferation and migration of hASCs
through DANCR while exerting its anti-inflammatory effects. Thus, it is suggested to avoid the simultaneous
application of hASCs and steroids in clinical practice. These results enrich our understanding
of the versatile function of lncRNAs in the crosstalk of inflammation conditions and
MSCs.