bluuebunny/crossref_metadata_2025 huggingface dataset:
Pioneering Experimental Exploration of an in-situ Characterization of the Shearing Stress-Strain Mechanism of Human Plantar Soft Tissue
Authors: Wu Longyan , Tang Lisheng , Zhu Jun , Geng Xiang , Jiang Xilin , Ma Xin , Huang Ran
Published: May 2023

Aiming to characterize the material mechanism of biological soft tissue, which is intensively studied in biomechanics, however the in-situ method is very difficult whereas the sample preparation from living body for classical tests is almost impossible, we have designed and manufactured a dynamic mechanical analysis (DMA)-like device to achieve the in-situ and in-vivo stress-strain test for living plantar tissue. A series of pioneering tests of horizontal shearing on the heel of five volunteers are reported, with the reference of tests on mimic foot model made by silicon rubber, standard silicon rubber brick sample, and finite elementary analysis. Beside certifying the device and method are practical, interesting phenomena are observed implying great potentials of the invention in future research.
Constraining the parent magma composition of the mineralized deep Flatreef at Turfspruit, northern lobe, Bushveld Complex: insights from silicate mineral compositions
Authors: Chaumba Jeff B. , Prevec Stephen A. , Dyan Siyasanga
Published: May 2023

Unlike platinum-group elements (PGEs) deposits from the western and eastern lobes of the Bushveld Complex which are generally thought to have been largely formed as a consequence of primary magmatic processes, PGEs from the northern lobe are generally thought to have originated by processes involving contamination of parental magmas by crustal sources. We investigated mineral compositions from the deep Flatreef at the Turfspruit farm where dolomitic calc-silicate rocks form part of the country rocks to determine the role of crustal sources in the formation of PGE mineralization. Orthopyroxene compositions vary widely from En77.9 to En91.7, and compositions of clinopyroxene display wider variations (Ca38.8−67.0Mg24.7−51.6Fe6.4−19.6). Plagioclase similarly varies widely in composition (An1.3−73.7) whereas compositions of olivine (Fo85.9−87.6) are very restricted. Temperatures ranging from ~ 500 to 1300 oC were obtained from two pyroxene geothermometers similarly likely indicating crystallization from contaminated magma and/or hydrothermal alteration. The wide compositional ranges of calcium-bearing phases such as clinopyroxene and feldspars suggest that the Platreef crystallized from parental magmas that were contaminated by dolomitic calc-silicate floor rocks. The very restricted and highly magnesian forsterite contents in olivines are inconsistent with expected primary magmatic compositions. Simple mixing models utilizing existing sulfur isotope data suggest that, in the Turfspruit area, contamination of Bushveld Complex parental magmas with 2–10% contamination by floor rock dolomitic calc-silicates with δ34S values of 32‰ would account for the observed data in the Turfspruit area.
A Parallel Design of Frequent Item-sets Mining on CPU-MIC Heterogeneous Systems
Authors: Zhang Bin , Dong Wenyong , Zhao Chao , Luo Meizhen , Wu Liangshun , Yang Shujun , Hu Juan , Peng Ling , Yan Shankai
Published: May 2023

With the rapid growth of the text mining technology, knowledge discovery in text is appealing more and more to researchers. Furthermore, association rule mining (ARM), an essential issue in data mining, is widely used in the field of text information. However, due to the exploding amount of information in different fields, the serial ARM algorithm has left much to be desired. In this paper, we propose a new parallel ARM algorithm on corpus, using MPI programming interface. The algorithm mainly makes use of distributed inverted hash index, a communication pattern based on chessboard decomposition and a multi-thread candidate item-set filtering method running on MIC platform to accelerate the generation of frequent item sets. We implemented the algorithm and run some test on the supercomputer cluster. The performance evaluations show that the speedup rate can reach 34 when using 7 nodes.
An Empirical Study to Trace the Impact of Macro- Economic Variables and Information Asymmetry on the Aum of Indian Mutual Funds- a Vecm and E- Garch Model Approach
Authors: kulshreshtha Priyank
Published: May 2023

Early theories of finance discarded the role of human behaviour in decision making, but over a period it is realised that human emotions play pivotal role in investors’ choice. Investors’ behaviour gets affected by so many factors namely personal factors, demographic factors, geographic factors, regulatory factors, macro- economic factors etc. Amongst these factors, macro- economic factors play a direct and important role in investment decision making because these factors impact entire system. In this study the impact of macro- economic variables is tracked on the investors’ behaviour towards mutual funds by taking Assets Under Management (AUM) as a proxy of for investor behaviour. Further, this study attempts to trace the impact of bad news on the investor behaviour. For accomplishing the objectives Vector Error Correction Model and E- GARCH model is used. It is found that 6 identified macro- economic variables explain 48% variation in the AUM and the error correction term is not statistically significant and it is also found that leverage effect exists in AUM which means that bad news impacts the volatility of AUM more than good news.
A lightweight high-resolution Human pose estimation method with an integrated attention mechanism
Authors: Liu Fuchen , Zhou Sijia , Wang Xiaocui , Zhang Dezhou
Published: May 2023

Deep learning has significant advantages in the field of human posture estimation. However, traditional methods often increase the parameter size and complexity of posture estimation networks by widening and deepening them to improve performance. To address this issue, this paper proposes a lightweight human posture estimation network, ADNet, based on the high-resolution network(HRNet). ADNet replaces Basic Blocks and downsampling in the high-resolution network with GABlocks and GDBlocks that incorporate lightweight convolution and attention mechanisms to reduce the number of parameters and computational complexity in the network. Additionally, ADNet solves the problem of feature redundancy by fusing relationships between different channels to make effective feature channels fully utilized. Experimental results show that ADNet achieves high-precision detection of human keypoint information even with fewer parameters and less computational complexity than commonly used human posture estimation networks, such as Cascaded Pyramid Network (CPN), Stacked Hourglass Network(Hourglass), and HRNet. Results also indicate that, compared to HRNet, ADNet reduces the model parameter size by 69.1% and computational complexity by 58.9% under the same image resolution and environment configuration. Furthermore, in the visualization of feature maps, the network using ADNet exhibits stronger feature extraction performance and less feature redundancy.
Floral resources, energetic value and pesticide residues in larval provisions collected by Osmia bicornis in oilseed rape dominated landscape
Authors: Misiewicz Anna , Mikołajczyk Łukasz , Bednarska Agnieszka J.
Published: May 2023

Pollinators in agricultural landscapes are facing global decline and the main pressures include food scarcity and pesticide usage. Although intensive agricultural landscapes are poor habitats for wild pollinators, the mass flowering crops may provide important food resources, albeit monofloral and short-term, which in addition may contain pesticide residues. We explored how the landscape composition with a different proportion of oilseed rape (6%-65%) around Osmia bicornis nests affects floral diversity, contamination with pesticides, and energetic value of provisions collected by bees as food for their offspring. The bees collected pollen from 28 floral taxa (6-15 per nest) and provisions were dominated by Brassica napus (6.0-54.2%), Quercus (1.2-19.4%) and Ranunculus (0.4-42.7%) found in all 12 nests, but also by Poaceae (1.2-59.9%, 11 nests) and Acer (0.6-42%, 8 nests). Residues of 12 pesticides were found in provisions, with acetamiprid, azoxystrobine, boscalid, and dimethoate being the most frequently detected at concentrations up to 1.2, 198.4, 16.9 and 17.8 ng/g, respectively. Floral diversity and energetic value of provisions, but not the Pesticide Risk Index depended on landscape structure. Moreover, pollen diversity decreased, and energetic value increased with landscape diversity. Thus, even a structurally simple landscape may provide diverse food for O. bicornis if the nest is located close to a single but resource-diverse patch. Both B. napus and non-crop pollen were correlated with pesticide concentrations.
Volume of the proximal half of the thoracic aorta is the most comprehensive FDG-PET/CT indicator of arterial aging throughout adulthood
Authors: HURSTEL Moira , JOLY Laure , IMBERT Laetitia , ZIMMERMANN Gaetan , ROCH Véronique , SCHOEPFER Pauline , LAMIRAL Zohra , SALVI Paolo , BENETOS Athanase , VERGER Antoine , Marie Pierre Yves
Published: May 2023

Introduction
18F-fluorodeoxyglucose positron emission tomography (FDG-PET) and computed tomography (CT) features of the proximal and more elastic half of the thoracic aorta are known to correlate with aorta stiffness in older populations. This prospective study aimed to analyze the changes in these FDG-PET/CT features between young, middle-aged, and older adults, and investigate associations with arterial stiffness and blood pressure (BP).
Methods
Young (< 40 years), middle-aged (40-to-60 years), and older (> 60 years) adults, who underwent an FDG-PET/CT, were prospectively recruited. FDG-PET/CT features of the proximal half of the thoracic aorta were analyzed relative to the age categories, BP and carotid-femoral pulse wave velocity (PWV), a reference indicator of aorta stiffness.
Results
We included 79 patients (38 women; 22 young, 19 middle-aged, and 38 older adults). An increase in age category was associated with increases in mean standardized uptake values (SUVs) of blood and aorta and most significantly in aorta SUV heterogeneity, represented by SUV standard deviation (SUV-SD), aorta calcification volume, and the aorta volume indexed to body surface area. However, this indexed aorta volume was the sole variable: (i) exhibiting a stepwise increase from young (median: 25 cm3/m2 [interquartile range: 20–28 cm3/m2]), to middle-aged (41 [30–48] cm3/m2, p < 0.001 vs. Young), and older (62 [44–70] cm3/m2, p < 0.001 vs. middle-age) adults, and (ii) selected in the multivariate predictions of systolic, diastolic, and pulse BP. Indexed aorta volume was also a multivariate predictor of PWV but in association with SUV-SD and hypertension.
Conclusion
In a population of patients referred to an FDG-PET/CT investigation, the indexed volume of the proximal and more elastic half of the thoracic aorta is the most comprehensive indicator of arterial aging. This imaging parameter exhibits a stepwise increase from young to middle-aged and older adults, is strongly linked to inter-individual changes in both arterial stiffness and BP, and thus, could help assess the early phases of arterial aging.
Trial registration
ClinicalTrial.gov, NCT03345290. Registered 17 November 2017, https://clinicaltrials.gov/ct2/show/NCT03345290?term=NCT03345290&draw=2&rank=1
Habitat Preference and Local Climate Influencing Mantella Baroni Activity and Abundance
Authors: Rasoarimanana Tantely , Edmonds Devin , Marquis Olivier
Published: May 2023

Amphibian habitat preferences have ecological, evolutionary, and conservation implications, but for most species we have no information about habitat use, especially at the microhabitat level. Relatedly, considering ongoing widespread amphibian population declines, baseline estimates of abundance are increasingly important for informing conservation, yet for most species we have no knowledge of their population sizes. We explored the habitat preferences and estimated abundance for the poison frog Mantella baroni in Vohimana Reserve, eastern Madagascar. We recorded microhabitat and environmental variables in 155 quadrats in forest valleys, on slopes, and on ridgelines, surveying both during the rainy season and at the onset of winter. Using occupancy models, we identified leaf litter depth and the number of small trees in a quadrat as the most important habitat features. Deeper litter and fewer small trees increased the probability of quadrat use. Mean 24-hr temperature influenced activity, with higher detection at warmer temperatures. Capture-recapture models estimated the two M. baroni populations in the reserve at 27 (95% CI: 22–49) and 197 (95% CI: 168–246) adult individuals. Our results provide the first information about habitat use for M. baroni, showing frogs select relatively open areas with deep litter near valley streams, likely due to the species eco-physiological requirements and reproductive behavior. Considering M. baroni is harvested commercially for the international pet trade, we note current export numbers could impact local populations if collection is not spread across multiple sites and we point to how our results can inform ex situ conservation efforts.
Visible-light photocatalysed Synthesis of Bioactive Benzo[b]thiophenes via Intramolecular C−S Bond Formation
Authors: Mishra Mangla , Srivast Vishal , Tivari Shraddha , Singh Praveen P.
Published: May 2023

Visible light driven synthesis of substituted benzo[b]thiophenes from phenylethenethiol under an air atmosphere at room temperature is reported, using eosin Y as an organophotoredox catalyst by intramolecular C−S bond formation. This process accepts a wide range of functional groups tolerance and generates benzo[b]thiophenes under highly environmentally benign conditions via transition-metal-free organic photoredox catalysis.
Nuclear structure, periodicity, and reactions of stable nuclei through 36Ar from average quark positions
Authors: Walsh Ray
Published: May 2023

Exact quark positions are indiscernible per the uncertainty principle. The hypothesis that quarks occupy average positions, however, leads to a variety of accurate predictions. Proposed average quark model (AQM) radius predictions correlate near-perfectly with accepted charge radii of stable nuclides through 36Ar. Per the model, alternating up- and down-quarks occupy average positions within linear and polygonal chains, and the distance between sequential quarks equals the proton’s radius. Best-fit solutions form anisotropic cylindrical lattices of stacked 6-nucleon (18-quark) rings. Evolving structures contain unique sub-structures that recur periodically every 12 nuclides, as presented within a periodic table of nuclear structures. Structural periodicity begins at 6Li and has led to the discovery of corresponding periodicities in nuclear magnetic moments and nucleosynthesis. The 12-nuclide periodicity of each is superior when analyzed against hypothetical 6,8,10,14, and 16-nuclide periodicities. Proposed quark structures are consistent with theoretical prolate hadron shapes, and open ring and cylindrical structures are consistent with electron scattering experiments demonstrating central depressions in the nuclide charge densities. A novel criterion of nuclear stability is presented: Nuclides containing contiguous alternating quark sequences tend to be stable, and tend to produce alternating nucleon sequences that contain stable equal ratios of neutrons to protons. Nuclides having disrupted quark sequences tend to be unstable, and tend to have unstable neutron/proton ratios. Model-consistent structures of 5He, 8Be, 18F, and 30P illuminate why they are unstable. The list of stable nuclides through 36Ar evolves one nucleon at a time. During nucleosynthesis, the AQM nuclide structure acts as a substrate that sterically selects whether a proton or neutron will be the next added nucleon, analogous to base pair selection in DNA replication. This method correctly predicts the most abundant isotope of every stable nuclide through 36Ar. The proposed model of nucleosynthesis exhibits important similarities to linear step-growth polymerization (SGP). Implications for the European Muon Collaboration effect are discussed.
Nonlinear optimal control of the parallel double inverted pendulum
Authors: Rigatos Gerasimos , Pomares Jorge , Abbaszadeh Masoud , Mhmood Ali , ALI HAZEM
Published: May 2023

The article proposes a nonlinear optimal control method for the dynamic model of the parallel double inverted pendulum. Three different forms of this system are considered: (i) two poles mounted on the same cart resulting into a model with four state variables and one control input, (ii) two poles mounted on the same cart resulting into a model with six state variables and one control input, (iii) two different cart-pole systems connected through an elastic link, resulting into a model with eight state variables and two control inputs. To implement the proposed nonlinear optimal control method the dynamic model of the parallel double pendulum undergoes approximate linearization around a temporary operating point which is updated at each sampling instance. This operating point is defined within each sampling period by the present value of the state vector of the parallel double inverted pendulum and by the last sampled value of the control inputs vector. The linearization process is based on first-order Taylor series expansion and on the computation of the associated Jacobian matrices. For the approximately linearized model of the parallel double inverted pendulum a stabilizing H-infinity feedback controller is designed. To compute the feedback gains of this controller an algebraic Riccati equation is also being solved at each time-step of the control algorithm. The global stability properties of the control scheme are proven through Lyapunov analysis. First it is demonstrated that the H-infinity tracking performance criterion holds, which signifies robustness of the control method under model uncertainty and external perturbations. Moreover, under moderate conditions it is proven that the control loop of the parallel double inverted pendulum is globally asymptotically stable. To implement state estimation-based control the H-infinity Kalman Filter is used as a robust observer. The nonlinear optimal control scheme for the parallel double inverted pendulum achieves fast and accurate tracking of reference setpoints under moderate variations of the control inputs.
Predicted configuration and stability of the ALKBH5/USP36 complex
Authors: Lehrer Steven , Rheinstein Peter
Published: May 2023

Background

Alpha-ketoglutarate dependent dioxygenase-5 (ALKBH5), a de-ubiquinating enzyme, is abnormally activated and plays important functions in glioblastoma formation. Ubiquitin-specific peptidase 36 (USP36) is crucial for maintaining ALKBH5 stability and controlling ALKBH5-mediated gene expression in glioblastoma stem cells. Reduced cell proliferation, worsened self-renewal, and increased sensitivity to temozolomide (TMZ) therapy were all effects of USP36 depletion. Elucidation of the ADAT2/USP36 complex structure may therefore facilitate the development of drugs that can block complex formation.

Methods

We have used the ClusPro web server for protein-protein docking to visualize and analyze the complex and GROMACS to perform molecular dynamics simulation.

Results

ClusPro protein docking analysis demonstrates the loose peripheral position of ADAT2 in the ADAT2/USP36 complex. Molecular dynamics simulation of ALKBH5 docked to USP36 suggests that ALKBH5/USP36 is not a stable structure.

Conclusion

The results of protein-protein docking and molecular dynamics simulation imply that the ADAT2/USP36 complex is not stable and might be disrupted by a therapeutic molecule or molecules, improving the prognosis of glioblastoma. Knowledge of the ADAT2/USP36 complex structure may facilitate the development of drugs that can block or disrupt complex formation.
Le tre Grazie e la danza dello splendore. Con un approfondimento sulle Grazie di Cirene e una nuova lettura degli affreschi di Sandro Botticelli conservati al Louvre.
Authors: Ferrauti Simona
Published: May 2023

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Soziale Medien als fünfte Gewalt: Strategische Organisation deutscher und finnischer Gegenredekampagnen auf Facebook
Authors: Ylönen Sabine
Published: May 2023

Social media, as the fifth estate, increasingly influence public dis­courses and play a major role in shaping public opinion. Undoubt­edly, they have the potential to promote participation and democra­cy. On the other side, they also constitute a risk for democratic soci­eties, as the spread of hate speech and fake news has shown. As a response, forms of counterspeech organised by civil society have emerged in social media to counter the normalisation of hate speech and democracy-threatening discourses. In order to influence dis­course in social media in terms of the fifth estate, counterspeech campaigns must be visible also quantitatively. In this ethnographic contrastive study, I analysed the activities of the German and Finn­ish Facebook groups of the network #iamhere international. The in­tensity and continuity of their activities is obviously influenced by their strategic organisation: conventionalised rules support them whereas lacking or inconsequent rules seemed to be counterpro­ductive.
Green Experience: The Effect of Horticultural Activities on Children’s Physical and Mental Health and Dietary Behavior
Authors: Tseng Tzuhui Angie , Chang Jui-Jung , Chang Yun-Chen
Published: May 2023

Child obesity is a major global public health issue. This study sought to identify means to improve children’s dietary behaviors through horticultural activities and effectively enhance their health and quality of life. The 129 participants were children in third grade through sixth grade in Hsinchu City, Taiwan. A quasi-experimental design was adopted as an intervention for school horticultural activities. The 68 students in the intervention group engaged in 40-minute horticultural sessions for 6 weeks. The pretest and post-test scores of both groups were measured using the Physical Questionnaire for older Children, the Connection to Nature Index, the Willingness to Taste Fruits and Vegetable Scale, and the Children’s Quality of Life Scale, as well as questionnaire items. The qualitative and quantitative data were analyzed through a parallel mixed-method approach. The findings showed that the intervention group’s physical activity levels, nature connectedness, and overall health were higher than those of the control groups. There were no significant differences in willingness to taste fruits and vegetables. This study demonstrates that engaging in natural school spaces and participating in horticultural activities improved the physical and mental health of children. Natural elements should be incorporated into the campus design, and children should be encouraged to participate in school horticultural activities.
Fabrication and Thermal Analysis of Hybrid A356 Aluminium Metal
Matrix Composites Prepared by Stir Casting Process
Authors: Naik J. Murali , Jagadeesh S. K. , Babu P. Sekhar , Naidu S C V Ramana Murty , Muruganandhan P. , Beneston S. Lionel
Published: May 2023

Background:

Electronic packaging makes use of hybrid A356 aluminium alloy MMCs (matrix metal composites). Enhanced endurance limit, increased production and energy, low maintenance cost, and benefits to the environment, such as reduced noise and airborne pollutants, are among the features that are recommended to be evaluated.

Objective:

This study aimed to analyze the thermal properties of A356 aluminium alloy with graphite (Gr) and boron carbide (B4C) hybrid metal matrix composites. For this purpose, the A356 hybrid composite was primed by the stir casting process with the addition of 5 wt % and 10 wt % of Gr and B4C reinforcements. In general, A356 hybrid composite material thermal analysis is crucial for electrical equipment.

Methods:

The liquid-in-filtration method was used to create the hybrid composites, which were then tested thermally for parameters, like melting point, thermal diffusivity, and thermal coefficient of expansion. The thermocouple sensor of a calorimeter was used to examine the disparity in the composites. A thermal analysis tool called TGA was used to visually represent the relationship between a material's weight and temperature.

Results:

The temperature was found to be 300oC at the 0.411 W/g maximum heat flow rate. Thermal conductivity is the ratio of the temperature difference divided by the area of the heat transfer from one substance to another. The thermal coefficient of expansion illustrates how a material's dimensions and weight change as temperature increases.

Conclusion:

The proportion of the weight of the hybrid composites was found to fall with a rise in the temperature. The melting point curve of the composites demonstrated a little increase in temperature to be accompanied by a sharp increase in heat flow.
Family Functioning Dynamics in Post-Drug Rehabilitation Recovery (Case Study in Banjarbaru City)
Authors: Sa'diyah Siti Halimatus
Published: May 2023

This study discusses the dynamics of family functioning in optimizing support for the child's recovery process after undergoing drug rehabilitation. The research location was in Banjarbaru, Landasan Ulin Sub-District. This study used a qualitative approach with case study methods and analysis using the Structural-Functional theory of Robert K. Merton. The results show that the external aspect of the family has a positive impact because they work together in maximizing post-rehabilitation recovery even though it does not directly impact the level of family functioning. While on the internal aspect, post-rehabilitation recovery is not optimal because both parents do not play an active role in both post-rehabilitation treatments nor maintain the family system's resilience. Therefore, it can be concluded that the balance of structure and function is the main component in maintaining the functioning of the family because the family environment is an essential factor in achieving and maintaining healing.
Representation Learning and Spectral Clustering for the Development and External Validation of Dynamic Sepsis Phenotypes: Observational Cohort Study
Authors: Boussina Aaron , Wardi Gabriel , Shashikumar Supreeth Prajwal , Malhotra Atul , Zheng Kai , Nemati Shamim
Published: May 2023

Background

Recent attempts at clinical phenotyping for sepsis have shown promise in identifying groups of patients with distinct treatment responses. Nonetheless, the replicability and actionability of these phenotypes remain an issue because the patient trajectory is a function of both the patient’s physiological state and the interventions they receive.

Objective

We aimed to develop a novel approach for deriving clinical phenotypes using unsupervised learning and transition modeling.

Methods

Forty commonly used clinical variables from the electronic health record were used as inputs to a feed-forward neural network trained to predict the onset of sepsis. Using spectral clustering on the representations from this network, we derived and validated consistent phenotypes across a diverse cohort of patients with sepsis. We modeled phenotype dynamics as a Markov decision process with transitions as a function of the patient’s current state and the interventions they received.

Results

Four consistent and distinct phenotypes were derived from over 11,500 adult patients who were admitted from the University of California, San Diego emergency department (ED) with sepsis between January 1, 2016, and January 31, 2020. Over 2000 adult patients admitted from the University of California, Irvine ED with sepsis between November 4, 2017, and August 4, 2022, were involved in the external validation. We demonstrate that sepsis phenotypes are not static and evolve in response to physiological factors and based on interventions. We show that roughly 45% of patients change phenotype membership within the first 6 hours of ED arrival. We observed consistent trends in patient dynamics as a function of interventions including early administration of antibiotics.

Conclusions

We derived and describe 4 sepsis phenotypes present within 6 hours of triage in the ED. We observe that the administration of a 30 mL/kg fluid bolus may be associated with worse outcomes in certain phenotypes, whereas prompt antimicrobial therapy is associated with improved outcomes.
Global research of artificial intelligence in lung Cancer: A bibliometric and visualized study (Preprint)
Authors: Yang Qiwei , Wang Ziyi , Fu Qiang , Hu Xiaohai , Chen Liang , Chen Weiyang , Lv Ling , Liu Zhenghua , Men Wanfu , Li Wenya
Published: May 2023

BACKGROUND

In recent years, the rapid development of artificial intelligence (AI) has created new opportunities for lung cancer research, and a large number of academic research results have been published.

OBJECTIVE

We used a bibliometric approach to visualize and analyze the scientific research results related to AI in lung cancer in the 21st century, and summarize the current status and research hotspots in this field.

METHODS

Published scientific literature related to AI in lung cancer was searched in The Web of Science Core Collection (WoSCC). R software, Citespace, VOSviewer, Microsoft Excel 2019 and Tableau were used for bibliometric analysis and scientific mapping visualization.

RESULTS

The number of publications increased annually from 2000 to 2022, and the United States and Stanford University were the most influential countries and research institutions, respectively. The most prominent researcher is Philippe Lambin from Maastricht University Medical Centre in the Netherlands. Journal of Clinical Oncology is the most cited journal, and Frontiers in Oncology is the most productive journal. Machine learning (ML), deep learning (DL), pulmonary nodules, radiomics, and prognosis are the most frequently occurring keywords and trending topics in the field.

CONCLUSIONS

AI has a wide range of promising applications in lung cancer, and more and more researchers are devoted to this field of study. The results of our bibliometric analysis provide researchers with a more intuitive understanding of the current status and trends of research in this field. Quantitative and visual analysis can guide scholars worldwide in their research and exploration.
Prevalensi Strain Avian Pathogenik Escherichia coli (APEC) Penyebab Kolibasilosis pada Burung Puyuh
Authors: Sarwohadi Wahyu Prihtiyantoro
Published: May 2023

PREVALENCE OF AVIAN PATHOGENIC Escherichia coli (APEC) STRAINS ON COLIBACILLOSIS IN QUAIL Wahyu Prihtiyantoro1), Khusnan1), Mitra Slipranata2)†  dan Imron Rosyidi2)  1 Akademi Peternakan Brahmaputra, Jl. Ki Ageng Pemanahan, Nitikan, Sorosutan Umbulharjo Yogyakarta,Tlp. 0274-384370, E-mail: wahyumatra@gmail.com 2 Fakultas Kedokteran Hewan, Universitas Gadjah Mada, Jl. Fauna 2, Karangmalang, Yogyakarta 55281            ABSTRACTAvian Pathogenic Escherichia coli (APEC) is a pathogen that causes colibacillosis in poultry, including salpingitis, omphalitis, cellulitis, swollen head syndrome, coligranuloma yolk sac inflammation, and air sacs inflammation. APEC is a zoonotic strain which spread through raw meat and processed meat products of animals and birds. In this research, the isolation and the identification of Escherichia coli were done by using selective media MacConkey, Kligger Iron Agar, and Gram staining. To analyse genetopically, polymerase chain reaction (PCR) was used to detect 16SrRNA genes, vt1 genes, and vt2 genes. Thirty one (55,36%)  isolates of 56 specimens collected from quail were detected as Escherichia coli. The detection of APEC strains towards 31 Escherichia coli isolates were done by using polymerase chain reaction (PCR) with vt1 and vt2 specific primer. From the results showed that 32,26% (10/31) was APEC strains and 67.74% was non-APEC strains. From 10 isolates, 90% had vt1 gene and 10% had vt2 gene. Escherichia coli isolates were found in eyes (32,26%), infraorbital sinus fluid (32,26%), nasal fluid (16,20%), also in lungs, air sacs, ascites, and heart for 3,2% each. The isolates could not be found in the specimens from the skull. These isolates are zoonotic and have an impact on human health.Keywords: APEC, colibacillosis, quail, vt1 and vt2
Aktivitas Ekstrak Rimpang Kunyit (Curcuma longa L) pada Mencit Parkinson yang Diinduksi Haloperidol
Authors: Yuliani Sapto , Bachri Mochammad Saiful , Sofia Vivi , Widyaningsih Wahyu , Muttaqien Dandy Annas , Putri Galuh Rista , Selvia Nadia , Rahmadita Sofina , Rahmita Intan Dwi
Published: May 2023

Penyakit Parkinson merupakan penyakit neurodegeneratif dengan gangguan motorik seperti bradikinesia, rigiditas, dan tremor yang dapat mempengaruhi keseimbangan tubuh.  Hal ini terjadi karena penurunan kadar dopamin yang dapat dipicu oleh adanya stres oksidatif. Kunyit (Curcuma longa) mengandung kurkumin yang mempunyai aktivitas antioksidatif dan neuroprotektif yang potensial sehingga dapat mencegah gangguan neurodegeneratif karena stres oksidatif. Tujuan penelitian ini adalah untuk mengetahui aktivitas ekstrak rimpang kunyit pada mencit model Parkinson yang diinduksi haloperidol. Ekstraksi rimpang kunyit dilakukan secara maserasi dengan pelarut etanol 96%. Sebanyak 60 ekor mencit dibagi menjadi 6 kelompok, masing-masing mendapat perlakukan sebagai berikut : Kelompok normal diberi CMC-Na per oral (p.o) dan NaCl fisiologis intraperitoneal (i.p), kelompok haloperidol diberi CMC -Na (p.o) dan larutan haloperidol i.p (1 mg/kg BB), kelompok levodopa diberi levodopa (p.o) dan larutan haloperidol i.p, Kelompok ekstrak 100 diberi ekstrak kunyit dosis 100 mg/kg BB dan larutan haloperidol i.p , Kelompok ekstrak 200 diberi ekstrak kunyit dosis 200 mg/kg BB dan larutan haloperidol i.p, Kelompok ekstrak 400 diberi ekstrak kunyit dosis 400 mg/kg BB dan larutan haloperidol i.p. Pemberian CMC-Na, levodopa dan ekstrak kunyit diberikan selama 21 hari. Lima belas menit setelah pemberian perlakuan hari terakhir, semua hewan uji kecuali kelompok 1 diinjeksi haloperidol dosis 1 mg/kg BB secara i.p. Kemudian dilakukan uji batang, uji roda berputar, uji refleks geotaksis, uji refleks menghindari jurang dan uji kemampuan penciuman pada menit ke 5, 60, 120 dan 180. Data yang diperoleh dianalisis menggunakan uji anova satu jalur dilanjutkan dengan uji post hoc LSD. Hasil analisis data menunjukkan bahwa pemberian haloperidol dapat meningkatkan waktu katalepsi, meningkatkan jumlah jatuh dan mempercepat waktu jatuh pertama kali, menurunkan refleks geotaksis, meningkatkan waktu refleks menghindari jurang serta menurunkan kemampuan indera penciuman. Sedangkan pemberian ekstrak kunyit dosis 200 dan 400 mg/kgBB dapat menurunkan waktu katalepsi, menurunkan jumlah jatuh dan memperlama waktu jatuh pertama kali, menurunkan refleks geotaksis, menurunkan lama waktu pada uji refleks menghindari jurang serta meningkatkan kemampuan indera penciuman jika dibandingkan dengan Haloperidol (P<0.05). Pemberian ekstrak 200 dan 400 mg/kg tidak berbeda bermakna (P>0,05) dengan pemberian levodopa. Berdasarkan hasil dapat disimpulkan bahwa ekstrak rimpang kunyit dosis 200 dan 400 mg/kgBB memiliki aktivitas untuk mencegah terjadinya Parkinson pada mencit yang diberi haloperidol.
Pendeteksian secara Otomatis Telur Cacing Haemonchus contortus menggunakan Algoritma YOLOv3
Authors: Arif Ridi , Retnani Elok Budi , Satrija Fadjar , Purnama Rizky Diyu
Published: May 2023

Infeksi Haemonchus contortus atau haemonchosis umumnya terjadi pada ruminansia kecil seperti domba. Haemonchus contortus adalah spesies yang paling patogenik pada ruminansia kecil dan berhabitat di abomasum. Hewan yang terinfeksi Haemonchus contortus  secara berangsur-angsur akan mengalami anemia karena aktivitas cacing yang menghisap darah. Selain menimbulkan anemia, domba akan mengalami penurunan bobot badan akibat penurunan daya cerna. Infeksi tersebut dapat berjalan secara akut maupun kronis dan dalam kondisi tertentu dapat juga mengakibatkan kematian pada hewan. Oleh karena itu dibutuhkan perangkat yang efektif dan efisien untuk mengindentifikasi keberadaan telur cacing Haemonchus contortus sebagai alat deteksi cepat telur cacing. Tujuan dari penelitian ini adalah membuat perangkat cerdas berbasis Algoritma YOLOv3 yang mampu mendeteksi dan mengidentifikasi telur cacing Haemonchus contortus secara cepat.  Penelitian ini menggunakan Algoritma You Only Look Once (YOLO) versi 3 yang merupakan algoritma yang dikembangkan untuk membantu mendeteksi objek secara realtime. Algoritma YOLO dijalankan dalam framework aplikasi anaconda dengan menggunakan pycharm dan aplikasi OPENCV. Identifikasi telur Haemonchus contortus secara otomatis berhasil dilakukan dengan proses tagging pada dataset dan membuat file weight training bagi YOLO. Hasil uji coba menggunakan mikroskop cahaya dan smartphone menunjukan bahwa bahwa Algoritma YOLO mampu mengidentifikasi telur Haemonchus contortus dengan nilai confidence lebih dari 90%. Penggunaan perangkat Dino-Lite yang terhubung pada mikroskop cahaya menunjukan algoritma YOLO tidak dapat berjalan karena adanya enkripsi pada perangkat tersebut. Otomatisasi pendeteksian telur Haemonchus contortus dapat dilakukan dengan memanfaatkan Algoritma YOLOv3 yang dibantu dengan hardware berupa laptop dan smartphone android serta memiliki kemampuan identifikasi dengan tingkat akurasi yang tinggi.
Profil Leukosit Tikus Jantan (Rattus novergicus L.) Galur Sprague Dawley Setelah Paparan Nanopartikel Kitosan Ekstrak Etanol Daun Mimba (Azadirachta indica A. Juss.)
Authors: Putri Fauziah Mustika , Sitasiwi Agung Janika , Isdadiyanto Sri , Mardati Siti Muflichatun
Published: May 2023

Ekstrak daun mimba memiliki aktivitas antioksidan yang memberikan efek terapeutik luas. Penelitian in vivo berbasis bio-nanomaterial banyak digunakan sebagai drug delivery untuk meningkatkan ketersediaan hayati pada obat selama berada di sirkulasi sistemik. Kombinasi antara nanopartikel dan ekstrak daun mimba perlu diketahui kadar keamananya bagi tubuh. Tujuan dari penelitian ini untuk mengetahui pengaruh nanopartikel kitosan ekstrak etanol daun mimba terhadap profil leukosit tikus jantan galur Sprague Dawley jantan yang ditunjukkan dengan jumlah total dan diferensial leukosit. Penelitian ini menggunakan desain RAL dengan 4 ekor tikus jantan dari 4 kelompok perlakuan terdiri dari P0 (akuades), P1 (larutan nanopartikel kitosan), P2 (NEEDM 50%), P3 (NEEDM 100%). Pemberian perlakuan diberikan secara oral selama 28 hari. Semua prosedur penelitian telah disetujui oleh komisi etik KEPK FK UNDIP, Semarang dengan nomor sertifikat 29/EC/H/FK-UNDIP/III/2021. Sintesis nanopartikel kitosan menggunakan metode gelasi ionik dan berhasil mendapatkan ukuran nano sebesar 232,3 nm, 700,1 nm, dan 297,3 nm. Uji fitokimia pada ekstrak etanol daun mimba positif mengandung senyawa fenolik, alkaloid, flavonoid, terpenoid, tanin, dan saponin. Variabel yang diamati yaitu jumlah total dan diferensial leukosit. Data dianalisis dengan Statistical Product and Service Solution (SPSS). Hasil penelitian menunjukkan tidak ada perbedaan secara nyata antar kelompok perlakuan (P>0,05). Jumlah total leukosit, dan jumlah rataan limfosit, monosit, dan neutrofil segmen masih dalam kisaran normal. Berdasarkan hasil penelitian disimpulkan bahwa pemberian sediaan nanopartikel kitosan ekstrak etanol daun mimba memberikan efek protektif terhadap sistem imun dan tidak bersifat toksik.
How Does Social Media Affect Traditional Culture
Authors: Wang Ruizhe
Published: May 2023

In the 21st century, with the changes in mass media, new forms of social media have emerged. Social media has become an indispensable part of human society, thoroughly integrated into various aspects of people’s lives. Social media plays an important role in the dissemination and promotion of traditional culture. However, in recent years, many new forms of social media have inappropriately used or showcased traditional culture and cultural heritage for the sake of entertainment, neglecting the respect for traditional culture and the understanding of its cultural essence, or directly engaging in cultural appropriation. This paper explores how to better use social media to promote and disseminate traditional culture through collecting and comparing the impact of social media on the dissemination of traditional culture, how to use social media in a correct manner.
New Research Direction and Overview of the Crescent School in the Twenty-first Century
Authors: Zhou Jing , Chen Maolong
Published: May 2023

The Crescent School was a significant liberal intellectual organization in modern China during the 1920s and 1930s, greatly impacting the development of new Chinese literature and modern thought. This paper reviews the research conducted on the Crescent School in the twenty-first century, identifying an evident shortcoming of one-sided, superficial, and repetitive research due to disciplinary boundaries and a lack of theoretical framework. To address these limitations, this paper argues for the adoption of a new integrated perspective that combines literature, intellectual history, and histology, aimed at establishing the Crescent School’s complete subjectivity. Furthermore, this paper explores the potential value of such an approach, which not only enriches the morphological samples of organizational studies but also expands the research view of organizations. In summary, this paper calls for a fresh look at the Crescent School and its impact on modern Chinese intellectual history, advocating for a more holistic approach to studying this organization and its contributions.
Biosíntesis de nanopartículas de plata con actividad antimicrobiana por Pseudomonas aeruginosa ambiental
Authors: Jiménez Mejía Rafael , Ramírez Herrera Ángel Daniel , Orozco Ceja Jesús Alejandro , González Domínguez Martha Isabel
Published: May 2023

Las nanopartículas de plata (NPs-Ag) son de gran interés debido a las aplicaciones potenciales en diferentes áreas. En busca de metodologías que no presenten riesgos a la salud y sean amigables con el ambiente, la biosíntesis de nanopartículas ha sido una opción viable. Se sabe que diversas biomoléculas presentes en los microrganismos pueden tener las funciones de agente oxidante, reductor y estabilizador, favoreciendo la formación de nanopartículas. En el presente trabajo se tuvo como objetivo la biosíntesis, caracterización y evaluación de la actividad antibacteriana de NPs-Ag. La biosíntesis se realizó a partir de sobrenadante de un cultivo de Pseudomonas aeruginosa, las nanopartículas se caracterizaron mediante espectroscopía UV-VIS, microscopía electrónica de barrido y difracción de rayos X, y la actividad antibacteriana se evaluó con ensayos de dilución en caldo Mueller Hinton, se determinó la concentración mínima inhibitoria (CMI) y concentración mínima bactericida (CMB) sobre bacterias Gram positivas y negativas. Se encontró que la mejor síntesis fue con una mezcla de 20% de sobrenadante conteniendo 3 mM de AgNO3, observando nanoestructuras con morfologías mixtas. Presentaron actividad contra bacterias Gram positivas y negativas con CMI de 1 a 2 µg/ml y CMB de 2 a 4 µg/ml. En conclusión, el sobrenadante de cultivos de P. aeruginosa es una alternativa viable para la síntesis de NPs-Ag con actividad antibacteriana.
Real Time Drowsiness Detection System Using CNN
Authors: Pushkar Piyush , Khandare Rohan , Prasad Yasharth , Kumar Vishal , Kadam Dr. Megha
Published: May 2023

Abstract: Driver fatigue and rash driving are the leading causes of road accidents, which result in the loss of valued life and decrease road traffic safety. Driver drowsiness solutions that are reliable and precise are essential to prevent accidents and increase road traffic safety. Various driver drowsiness detection systems have been developed using various technologies that are geared at the specific parameter of detecting the driver's tiredness. This research offers a unique multi-level distribution model for detecting driver drowsiness utilising Convolution Neural Networks (CNN) and. To detect the driver's behaviour and emotion, the driver's face pattern is handled with a 2D Convolution Neural Network (CNN). The suggested model is built with OpenCV, and the experimental findings show that it recognises the driver's emotion and tiredness more efficiently than existing technologies
Smart Bin Using IoT
Authors: Diware Anirudh
Published: May 2023

Abstract: The study presents a design and development of a smart garbage bin that can detect dry and wet waste using moisture sensors and ultrasonic sensors and has Bluetooth connectivity for remote monitoring and management. The aim of this study is to evaluate the accuracy, reliability, and potential environmental impact of the smart garbage bin in waste management practices. The smart garbage bin prototype was developed using Arduino technology and integrated with moisture sensors and ultrasonic sensors to accurately detect and classify dry and wet waste. The Bluetooth connectivity allows for real-time monitoring of fill levels and waste composition, optimizing waste collection schedules and routes and reducing costs. The prototype was tested for accuracy and reliability in detecting different types of waste, including paper, plastic, food waste, and liquids, and was found to be highly reliable in detecting and segregating waste accurately.
A Review on Age and Gender Recognition Using Various Datasets and Deep Learning Models
Authors: Shettigar Suraj Kumar , CK Prof. Lokesh
Published: May 2023

Abstract: Age and Gender are two facial potentials play a principalrole in the society. An instinctive age and gender appreciation have a massive numeral of real-world uses that comprises a consumer facility, the priority voting system, medical diagnosis, the human computer communication. Deep learning methods are usually used in utmost researches and attained to progress the performance too. Relating dissimilar deep education models and evaluating the enhancement in exactness leads to complementary studies. The chief aim of this paper is to achieve detailed examination of age and gender credentials through numerous datasets and deep learning prototypes. In this paper, the growth made by, deep learning prototypes are highlighting the assistances addressed; the prototypes and dataset used are estimating the acclaimed method with the concerns attained.
Channelizing Machine Learning Towards Early Threat Detection and Prevention Against Women Using Surveillance Cameras
Authors: Gupta Chirag , Vinchurkar Tejas , Chavan Sarthak , Waware Prof. P. G.
Published: May 2023

Abstract: Closed Circuit Television Systems (CCTV) are being used in a growing number of office buildings, housing developments, and public locations. Many towns now have CCTV surveillance systems in place. Such monitoring systems create a tremendous load for the CCTV operators because the number of cameras views a single CCTV operator can process is constrained by human considerations. Surveillance automation of public places assumes an important role in proactively detection of possible threat to public and in maintaining law and order. Based on a review of the existing approaches followed in monitoring of crowd behaviours and the techniques applied, especially in public places like bus stands, railway stations and airports, the paper proposes surveillance automation i.e., automating the process of detecting, recognizing the suspects and suspicious behaviour of the people in the crowd. Here, in this project called channelizing machine learning towards early threat detection and prevention against women using surveillance cameras, we propose algorithms that are capable of alerting the human operator when: (1) Presence of a inhuman act, after setting zones of interest and danger zones within those zones of interest, the danger is detected when someone follows a women on streets, roads or any other public places, which can reduce the number of sexual harassment and other forms of sexual Algorithms violence in public spaces; (2) An abnormal behaviour of a person such as handling some objects abnormally; (3) In this project, our main aim is towards women safety and also we concentrate on reducing the amount of false alerts and to enable a real-life use of the system.