bluuebunny/crossref_metadata_2025 huggingface dataset:
A Hybrid Forecasting Structure Based On Arima And Artificial Neural Network Models
Authors: Atesongun Adil , Gulsen Mehmet
Published: July 2024

This study involves the development of a hybrid forecasting framework that integrates two different models in a framework to improve prediction capability. Although the concept of hybridization is not a new issue in forecasting, our approach presents a new structure that combines two standard simple forecasting models uniquely for superior performance. Hybridization is significant for complex data sets with multiple patterns. Such data sets do not respond well to simple models, and hybrid models based on the integration of various forecasting tools often lead to better forecasting performance. The proposed architecture includes serially connected ARIMA and ANN models. The original data set is first processed by ARIMA. The error (i.e., residuals) of the ARIMA is sent to the ANN for secondary processing. Between these two models, there is a classification mechanism where the raw output of the ARIMA is categorized into three groups before they are sent to the secondary model. The algorithm is tested on well-known forecasting cases from the literature. The proposed model performs better than existing methods in most cases.
Recent Advances in Phthalocyanine-Based Hybrid Composites for Electrochemical Biosensors
Authors: Puttaningaiah Keshavananda Prabhu Channabasavana Hundi , Hur Jaehyun , Gaddimath Shivalingayya
Published: July 2024

Biosensors are smart devices that convert biochemical responses to electrical signals. Designing biosensor devices with high sensitivity and selectivity is of great interest because of their wide range of functional operations. However, the major obstacles in the practical application of biosensors are their binding affinity toward biomolecules and the conversion and amplification of the interaction to various signals such as electrical, optical, gravimetric, and electrochemical signals. Additionally, enhancement of sensitivity, limit of detection, time of response, reproducibility, and stability are considerable challenges when designing an efficient biosensor. In this regard, hybrid composites have high sensitivity, selectivity, thermal stability, and tunable electrical conductivities. The integration of phthalocyanines (Pcs) with conductive materials such as carbon nanomaterials or metal nanoparticles (MNPs) improves the electrochemical response, signal amplification, and stability of biosensors. This review explores recent advancements in hybrid Pcs for biomolecule detection. Herein, we discuss the synthetic strategies, material properties, working mechanisms, and integration methods for designing electrochemical biosensors. Finally, the challenges and future directions of hybrid Pc composites for biosensor applications are discussed.
The Relationship of Cup Inclination and Anteversion in the Coronal Plane with Ante-Inclination in the Sagittal Plane
Authors: Innmann Moritz M. , Merle Christian , Ratra Akaash , Speirs Andrew , Adamczyk Andrew , Murray David , Gill Harinderjit S. , Grammatopoulos George
Published: July 2024

Background:

This study aimed to establish an equation for calculating cup ante-inclination (AI) from radiographic cup inclination and anteversion, to validate this equation in a total hip arthroplasty (THA) cohort, and to test whether achieving previously described radiographic cup inclination and anteversion targets would also satisfy sagittal cup AI targets.

Methods:

A mathematical equation linking cup AI, radiographic inclination (RI), and anteversion (RA) was determined: tan(AI) = tan(RA)/cos(RI). Supine and standing anteroposterior and lateral radiographs of 440 consecutive THAs were assessed to measure cup RI and RA and spinopelvic parameters, including cup AI, using a validated software tool. Whether orientation within previously defined RI and RA targets was associated with achieving the AI target and satisfying the sagittal component orientation (combined sagittal index, 205° to 245°) was tested.

Results:

The cups in the THA cohort had a measured mean inclination (and standard deviation) of 43° ± 7°, anteversion of 26° ± 9°, and AI of 34° ± 10°. The calculated cup AI was 34° ± 12°. A strong correlation existed between measured and calculated AI (r = 0.75; p < 0.001), with a mean error of 0° ± 8°. The inclination and anteversion targets were both satisfied in 194 (44.1%) to 330 (75.0%) of the cases, depending on the safe zone targets that were used, and 311 cases (70.7%) satisfied the AI target. Only 125 (28.4%) to 233 (53.0%) of the cases satisfied the AI target as well as the inclination and anteversion targets. Satisfying inclination and anteversion targets was not associated with increased chances of satisfying the AI target.

Conclusions:

Achieving optimal cup inclination and anteversion does not ensure optimal orientation in the sagittal plane. The equation and nomograms provided can be used to determine and visualize how the 2 planes used for evaluating the cup orientation and the pertinent angles relate, potentially aiding in preoperative planning.
Metaverse as a Macroshift of Modern Culture
Authors: Leshkevich Tatiana ,   Southern Federal University
Published: July 2024

The article examines the macro shift of modern culture associated with the emer­gence of a metaverse, creating a new audiovisual landscape and overcoming the line between the virtual and the real. The author identifies the characteristics of the metaverse, its supra-temporal and supra-territorial dimensions, which en­sure the storage, distribution and location of digital cultural artifacts. The most important properties of the metaverse are analyzed, these include its emotional persuasiveness and expansion of the boundaries of the possible. The focus is on the process of digitization of cultural heritage, the problem of the authenticity of a digital art object and the longevity of the created metaverses. Three groups of problems are considered. Firstly, this is an analysis of the metaverse as a digi­tal environment for the interaction of avatars, which transfer individuals into a different ontology with existing prospects for multiple identities without any biomedical restrictions. Secondly, the pros and cons of the simulated effects of the metaverse are analyzed in their dependence on the software. Thirdly, dif­ficulties are revealed on the way from data scientists – big data integrators to understanding Foresight perspectives. The author concludes that “digital hu­manism” is associated with the expansion of the metaverse and appropriates the future for itself.
Culture, civilization and the “new barbarism”: the historiosophical insights of Nikolai Berdyaev
Authors: Kara-Murza Alexei ,   Institute of Philosophy, Russian Academy of Sciences
Published: July 2024

The article examines the evolution of the philosophical and historical views of N.A. Ber­dyaev (1874–1948) in the first months of the First World War (“Second Patriotic War”). According to the general concept of the author of the article, philosophical journalism (in particular, in Russia) is not a translation, a “simplification” of a ready-made philo­sophy, but, on the contrary, a way of ascending to philosophy – due to the increasingly distinct crystallization of philosophical meanings born in journalism. In this context, the author of the article, using the method of analytical condensation of some frag­ments of Berdyaev’s intellectual work, examines his texts of 1914–1915 from the point of view of their “elevation” from the actual patriotic journalism (built on the princi­ples of Russophile cultural self-apology) to the heights of historiosophical and philo­sophical-cultural thinking based on the methods of analytical criticism and civilizational self-criticism.
The Content Analysis of Reception of Hegel’s Philosophy in Dialectical Materialism (the Late 19th – the First Half of the 20th Century)
Authors: Vladimirov Pavel ,   Russian State University for the Humanities
Published: July 2024

The article presents the results of a study devoted to the attitudes towards Hegel’s philosophy in Russian and Soviet Marxist philosophy (Dialectical materialism) of the late 19th and first half of the 20th century. The research is based on the collection of nearly 200 works, in which 1,766 interpretative theses were identified by the method of content analysis. On the basis of quantitative parameters, the paper demonstrates the development of attitudes towards Hegel’s philosophy in pre-Soviet and Soviet Marxism. The main directions of interpretation of Hegel’s philosophy are also described and the internal inconsistency as well as the diversity of the interpretations, are presented. The main influences on Hegelian themes in the USSR are mentioned in the article and the problem of Stalinist repressions among Soviet philosophers working on Hegelian issues is also touched upon.
RETRACTED: Improved dissolution and pharmacokinetics of insufficiently water-soluble canagliflozin in solid dispersions with gelucire 50/13 as a drug carrier
Authors: Deshmukh Rutuja , Deshmane Subhash Vishwanath , Sawant Atish , Deshmane Snehal , Jain Shirish
Published: July 2024

The authors have requested that this preprint be removed from Research Square.
Generalisable functional imaging classifiers of schizophrenia have multifunctionality as trait, state, and staging biomarkers
Authors: Kawashima Takahiko , Yamashita Ayumu , Yoshihara Yujiro , Kobayashi Yuko , Okada Naohiro , Kasai Kiyoto , Huang Ming-Chyi , Sawa Akira , Yoshimoto Junichiro , Yamashita Okito , Murai Toshiya , Miyata Jun , Kawato Mitsuo , Takahashi Hidehiko
Published: July 2024

Schizophrenia spectrum disorder (SSD) is one of the top causes of disease burden; similar to other psychiatric disorders, SSD lacks widely applicable and objective biomarkers. This study aimed to introduce a novel resting-state functional connectivity (rs-FC) magnetic resonance imaging (MRI) biomarker for diagnosing SSD. It was developed using customised machine learning on an anterogradely and retrogradely harmonised dataset from multiple sites, including 617 healthy controls and 116 patients with SSD. Unlike previous rs-FC MRI biomarkers, this new biomarker demonstrated a notable accuracy rate of 77.3% in an independent validation cohort, including 404 healthy controls and 198 patients with SSD from seven different sites, effectively mitigating across-scan variability. Importantly, our biomarker specifically identified SSD, differentiating it from other psychiatric disorders. Our analysis identified 47 important FCs significant in SSD classification, several of which are involved in SSD pathophysiology. Beyond their potential as trait markers, we explored the utility of these FCs as both state and staging markers. First, based on aggregated FCs, we built prediction models for clinical scales of trait and/or state. Thus, we successfully predicted delusional inventory scores (r = 0.331,P = 0.0177), but not the overall symptom severity (r = 0.128,P = 0.178). Second, through comprehensive analysis, we uncovered associations between individual FCs and symptom scale scores or disease stages, presenting promising candidate FCs for state or staging markers. This study underscores the potential of rs-FC as a clinically applicable neural phenotype marker for SSD and provides actionable targets to neuromodulation therapies.
Management of metabolic and reproductive disturbances in letrozole induced polycystic ovarian syndrome by Asparagus racemosus roots
Authors: Ghosh Angshita , Sil Sananda , Kar Tarun Kumar , Barman Ananya , Chattopadhyay Sandip
Published: July 2024

Background: Polycystic Ovary Syndrome (PCOS) has emerged as a widespread endocrine health challenge for women in the childbearing phase by imposing an adverse influence on fertility. Unfortunately, the existing treatment-strategies are inadequate and largely focused on symptom-based relief. Therefore, the demand for safer herbal alternatives is more pressing than ever.Asparagus racemosus Willd. has a longstanding history as a traditional herb for addressing diverse hormonal and fertility complications. The present study explored the in-depth mechanism by which A. racemosus ethanolic extract (ARE) ameliorates PCOS in female adult rats.
Methods: ARE at different doses (100, 150, 250 mg/kg-bw) were concurrently supplemented in the letrozole-induced PCOS group (1 mg/kg-bw) for a continuous period of 21 days. LC/ESI-MS was employed for determination of active phytotherapeutics within the ARE. Biochemical assay, ELISA, native PAGE expression, Real-time PCR, immunostaining and histological study were implemented for the experimental analysis.
Results: ARE regularized the disrupted estrous pattern, improved metabolic status and balanced endocrine activity by reducing excess androgen production. ARE restored intraovarian antioxidant enzyme expression and markedly reduced the mRNA expression of inflammatory (NFkB/TNFα) and proapoptotic markers (Bax/P53) along with elevated expression of anti-apoptotic factor (BCL2). The downregulation of androgen receptor (AR) in ovarian tissue accompanied by a decreased in the angiogenic factor VEGF-B were also observed. ARE improved gonadal weights and histomorphology by limiting the formation of cystic follicles and promoting folliculogenesis. The presence of essential secondary metabolites, specifically steroidal sapogenin, isoflavones and polyphenols, is primarily responsible for these advantageous effects.
Conclusion: The observed findings suggested that A. racemosus could be a highly effective safer alternative therapeutic intervention for managing the complexities of PCOS.
Variability of Silicon with Basic Soil Properties using Machine Learning
Authors: Pooniyan Seema Pooniyan Seema , Tushar Tushar Kumar , Kour Sarabdeep Kour Sarabdeep , Yadav K.K. Yadav K.K.
Published: July 2024

Random geo-referenced soil surface (0–15 cm) samples were used to study the geographical variability of soil properties and plant-accessible silicon (Si) in rice growing soils of three districts of Jammu plains. The represent study was conducted descriptive statistics along with graphs for spatial distribution of soil data. The region had an interquartile range (IQR) of sand (%), silt (%), clay (%), pH, electrical conductivity (dSm− 1), soil organic carbon (g kg− 1), and cation exchange capacity (cmol (p+) kg− 1), 8.14, 5.80, 6.76, 1.10, 0.11, 2.70 and 1.88, respectively. The interquartile range (IQR) of available nitrogen (kg ha− 1), phosphorus (kg ha− 1), potassium (kg ha− 1), and sulfur (ppm) was noted to be 94.45, 16.93, 74.35, and 8.98, respectively. Positive skewness distribution was found in all physico-chemical properties, except sand content. Positive kurtosis distribution was found in all available nutrients except available nitrogen. Out of 10, 4 principal components exhibited greater than 1.00 eigen value and explained 89.00% cumulative variability among the parameters studied. The Dim 1 displayed 55.9% while Dim 2, Dim 3 and Dim 4 exhibited 16.9%, 10.3% and 5.9% variability, respectively amongthe parameters under study. This study will be helpful in identifying the variability contributing parameter and selection of suitable parameters in Jammu plains.
How common are Medico-legal issues among Obstetricians and Gynecologists in Ethiopia: a descriptive cross-sectional study
Authors: Teklu Alula M. , Bekelle Delayehu , Surur Feiruz , Kassa Munir , Yirdaw Kesetebirhan D , Taddesse Daniel , Lamaro Tafesse , Solomon Ananya , Legese Tegene , Kebede Birhanu
Published: July 2024

Background: One of the common challenges encountered by the Obstetrics and Gynecology (ObGyn) specialists is medico-legal issues including litigations for medical malpractice, lawsuits for medical errors and others. The magnitude of the challenges, perceptions and concerns are not well known. This study looked at these factors.
Methods: a cross-sectional assessment of current encounters, experiences and perceptions of practicing ObGyn physicians who attended the Ethiopian Society of Obstetricians and Gynecologists conference in February 2016. A self-administered semi-structured questionnaire was used to collect the data. Descriptive statistics were done to determine the magnitude of the different issues in relation to medico-legal issues.
Results: A total of 112 obstetricians and gynecologists (OBGYNs) were interviewed, median age of the participants was 40 years and only 8.9% were women. Close to half of them worked in Addis Ababa and the same proportion worked in the public sector.
Nearly a third (34.8%) admitted making at least one error, 21.4% have been accused of malpractice, 21.4% were questioned by police/attorney and 6.3% were imprisoned. 83.3% of those who were questioned were declared free. 83% claimed to know someone who was accused of malpractice unfairly. Only 55.4% were aware of the role of the federal ethics committee.
Conclusions: Many ObGyns are neither knowledgeable nor ready for management of medical error. There is a huge concern about the fairness of the treatment they receive for medical error lawsuits. Fear of litigation is enormous. Improving awareness about medical errors and their management paired with creating clarity on the roles of the federal ethics committee is highly needed. Bridging the gap between the judiciary system and the ObGyn society and addressing the disparity between the perceived susceptibility and the reality are crucial.
Generation of Tooth Replicas by Virtual Segmentation Using Artificial Intelligence
Authors: Pedrinaci Ignacio , Nasseri Anita , Calatrava Javier , Couso-Queiruga Emilio , Giannobile William V. , Gallucci German O. , Sanz Mariano
Published: July 2024

Objectives: The primary aim of this investigation was to validate a method for generating 3D replicas through virtual segmentation, utilizing artificial intelligence (AI) or manual-driven methods, assessing accuracy in terms of volumetric and linear discrepancies. The secondary aims were the assessment of time efficiency with both segmentation methods and the effect of post-processing 3D replicas.
Methods: Thirty teeth were scanned through Cone Beam Computed Tomography (CBCT), capturing the region of interest from human subjects. DICOM files underwent segmentation through both AI and manual-driven methods. Replicas were fabricated with a stereolithography 3D printer. After surface scanning of pre-processed replicas and extracted teeth, STL files were superimposed to evaluate linear and volumetric differences using the extracted teeth as the reference. Post-processed replicas were scanned to assess the effect of post-processing on linear and volumetric changes.
Results: AI-driven segmentation resulted in statistically significant mean linear and volumetric differences of -0.709mm and -4.70%, respectively. Manual segmentation showed no statistically significant differences in mean linear (-0.463mm) and volumetric (-1.20%) measures. Comparing manual and AI-driven segmentations, showed that AI-driven segmentation displayed mean linear and volumetric differences of -0.329mm and -2.23%, respectively. Additionally, AI segmentation reduced mean time by 21.8 minutes. When comparing post-processed to pre-processed replicas, there was a volumetric reduction of -4.53% and a mean linear difference of -0.151mm.
Conclusion: Both segmentation methods achieved acceptable accuracy, with manual segmentation slightly more accurate and AI-driven segmentation more time-efficient. Continuous improvement in AI offers the potential for increased accuracy, efficiency, and broader application in the future.
Clinical Significance: Tooth replica generation in the context of tooth autotransplantation therapy may contribute to enhanced success and survival rates. Accurate CBCT-based virtual segmentation and 3D printing technologies are particularly important in the fabrication of 3D replicas. Therefore, it is crucial to assess the accuracy of available techniques and alternatives to demonstrate their reliability and accuracy in the fabrication of tooth replicas.
The Impact of COVID-19 Anxiety affected the Academic Motivation, Life-Orientation, and Meaning in Life of University Students
Authors: Cayubit Ryan Francis O.
Published: July 2024

Despite the declaration of the end of the global health emergency related to COVID-19, the disease remains a significant concern worldwide. However, little is known about how COVID-19 anxiety influences the presence and search for meaning, optimism-pessimism, and academic motivation of university students. This research addresses this gap by determining whether COVID-19 anxiety is a significant predictor of meaning in life, life orientation, and academic motivation. A cross-sectional predictive study was conducted involving 557 samples and the results showed that COVID-19 anxiety negatively impacted amotivation, presence of meaning and life orientation. On the other hand, result also showed that searching for meaning was positively influenced by COVID-19 anxiety. These key findings contribute to the existing body of knowledge on how COVID-19 anxiety affected the general well-being of university students.
Phosphopeptide-bridged NH2-TiO2-mediated carbon dots self-enhancing and electrochemiluminescence microsensors for label-free protein kinase A detection
Authors: Guo Jianping , Yue Lele , Ning Lingya , Han Ailing , Wang Junping
Published: July 2024

A novel electrochemiluminescence (ECL) method was developed for analyzing protein kinase A (PKA) ultra-sensitively based on amidated nano-titanium (NH2-TiO2) embellished carbon dots (Mg@N-CDs) fluorescent probe, which integrated the target recognition and ECL-signal enhancement. The Cys-labeled kemptides were employed to build a serine-rich synthetic substrate-heptapeptide (Cys-kemptide) on the Au-electrode surface. Then, the PKA-induced biosensor was triggered as a signal switch to introduce the large amounts of TiO2 decorated Mg@N-CDs nanohybrid (Ti@NMg-CDs) into AuE/Cys-phosphopeptides for signal output. In particular, the presence of PKA could induce the formation of Cys-phosphopeptides by the catalytic reaction between specific substrate (kemptide) and PKA, which could act as an initiator to link the Ti@NMg-CDs according to the bridge interactions Ti-O-P. By this way, multiple Cys-phosphopeptides were adsorbed onto a single Ti@NMg-CDs and the Ti@NMg-CDs not only provided the high specific selectivity but also large surface area, as well as unprecedented high ECL efficiency. Using this PKA-induced enhanced sensor, the limit-of-detection of the PKA was 4.89 × 10− 4 U/mL (S/N = 3). The proposed ECL biosensor was also universally applicable for the screening of PKA inhibitors and the determining of other kinases activity. Our sensing-system has excellent performance of specificity and the screening of kinase inhibitors, as well as it will inspire future effort on clinical diagnostics and new drugs discovery.
Preparation and Characterization of Fluorine and Magnesium co-doping LiNi0.8Fe0.1Al0.1O2 Cathode Materials for Lithium-Ion Batteries
Authors: Wu Huacheng , Huang Xinping , Li Jun
Published: July 2024

With the vigorous development of new energy vehicles, cobalt in the traditional lithium-ion(Li-ion) battery industry chain is obviously in short supply. To manage this challenge, a new cobalt free cathode material Li[Ni0.8Fe0.1Al0.1]1-xMgxO2-yFy (x=0.01, y=0.01, 0.02, 0.03) with different f-doping contents (labeled Mg-1, Mg-F-1, Mg-F-2, Mg-F-3) was prepared by sol-gel method. XRD results show that the co-doping of Mg2+ and F− reduces the mixing degree of cations and increases the lattice parameters. A small amount of Mg2+ and F− co-doping does not affect the layered structure of NFA materials. The results of SEM, EDS and elemental spectrum showed that Mg and F elements were evenly dispersed on the surface of the material and successfully doped into the crystal structure of the material. The co-doping of Mg2+ and F− did not damage the surface of NFA primary particles. XPS results further confirmed that Mg2+ and F− were introuduced successfully into NFA materials. Compared with the original NFA material, the co-doping of Mg2+ and F- significantly improved the electrochemical performance of the pirstine material. Electrochemical results show that co-doping has the best first discharge specific capacity, first coulomb efficiency and cycle life. The first discharge specific capacity and coulomb efficiency at 0.1C were 171.8 mAh g-1 and 88.1%, respectively. After 150 cycles at 0.1C, the capacity retention rate was 88.1%. This study emphasizes the broad prospects of this new material in the future cobalt free market.
Practical runtime verification of cross-organizational smart contracts
Authors: Kangogo Damaris Jepkurui , Péter Bertalan Zoltán , Klenik Attila , Kocsis Imre
Published: July 2024

Smart contracts in blockchains often implement critical functionality; consequently, their development time software fault detection, removal, and avoidance have been the target of intensive research. However, the applicability of runtime dependability mechanisms to smart contracts has not been explored systematically, mainly due to the transaction pricing models of public blockchains. In this paper, we propose a novel and practical runtime verification approach for Hyperledger Fabric, the leading cross-organizational blockchain platform, as an error detection facility for fault tolerance mechanisms; building on the proposition that, in contrast to the public setting, cross-organizational blockchains have ample computational headroom for their systematic use. We introduce a smart contract entity framework architecture with reusable domain models and encapsulated runtime verification. We describe Hypernate, our open-source implementation of the approach for Java smart contracts, which uses the Java Modelling Language for requirement specification and integrates the OpenJML verification tool. We demonstrate and evaluate the approach on a Fabric implementation of the TPC-C benchmark.
Analysis of the Matching Degree between Professional Needs and Professional Training Plans for Big Data Engineers
Authors: Rui Fang , Jingbai Tian
Published: July 2024

Aiming at the mismatch between the current college talent training model and the job market demand, this paper proposes a model based on big data analysis and natural language processing, taking big data engineers as an example. By collecting and analyzing the recruitment market data of enterprises, combining with NLP, entropy and weight normalization, this paper provides scientific basis for universities to formulate and adjust professional training programs. The model proposed in this paper can help colleges and universities to understand the market demand more accurately according to the current job market demand, and adjust and optimize the professional curriculum, so as to cultivate graduates who are more in line with the market demand. Through comparative analysis of recruitment information and professional training programs of colleges and universities, this study confirms this contradiction and proposes improvement strategies to improve the employment rate and career development success rate of graduates.
Traceability and dispersion of highly toxic soluble phases from historical mine tailings
Authors: Rio-Salas Rafael Del , Moreno-Rodríguez Verónica , Loredo-Portales René , Salgado-Souto Sergio Adrián , Valencia-Moreno Martín , Ochoa-Landín Lucas , Romo-Morales Diana
Published: July 2024

Dispersion of highly toxic elements associated with efflorescent crusts and mine tailings materials from historical mine sites threaten the environment and human health. Limited research has been done on traceability from historical mining sites in arid and semi-arid regions. Pb isotope systematics was applied to decipher the importance of identifying the mixing of lead sources involved in forming efflorescent salts and the repercussions on traceability. This research assessed mine waste (sulfide-rich and oxide-rich tailings material and efflorescent salts) and street dust from surrounding settlements at a historical mining site in northwestern Mexico, focusing on Pb isotope composition. The isotope data of tailings materials defined a trending line (R2 = 0.9); the sulfide-rich tailings materials and respective efflorescent salts yielded less radiogenic Pb composition, whereas the oxide-rich tailings and respective efflorescent salts yielded relatively more radiogenic compositions, similar to the geogenic component. The isotope composition of street dust suggests the dispersion of tailings materials into the surroundings. This investigation found that the variability of Pb isotope composition in tailings materials because of the geochemical heterogeneity, ranging from less radiogenic to more radiogenic, can add complexity during environmental assessments because the composition of oxidized materials and efflorescent salts can mask the geogenic component, potentially underestimating the influence on the environmental media.
Explanation of the Characteristics of Thermo diffusion and Buoyant Force in MHD Flow of Copper and Titanium Dioxide Nanoparticles Suspended in Water between infinite vertical Plates
Authors: Nazia S , Seshaiah B
Published: July 2024

This study explores the heat and mass transfer characteristics of an inconsistent, MHD condensed nanoliquid flow over a stretched sheet under a transverse magnetic field and thermal impacts. The theoretical framework examines two types of nanofluids, Ag-water-based and TiO2- water -based. By converting the governing differential equations into nonlinear ODE’s and subsequently employing a standard perturbation approach with appropriate boundary conditions, the solutions are obtained for various physical parameters. The graphical representation and comprehensive analysis of the consequences of these characteristics on dimensionless momentum, energy, and concentration outlines are presented. Comparisons with existing literature demonstrate favourable agreement. Tabulated numerical implications of material abundances, such as the local skin conflict, the local Nusselt numeral, and the local Sherwood numeral, are also furnished. The study reveals that increasing thermal radiation reduces velocity and temperature while enhanced chemical process efficiency decreases concentration levels. Moreover, an increased Soret parameter results in higher velocity and concentration measurements. Notably, TiO2 nanofluids exhibit significantly higher velocities compared to Ag nanofluids when based on water.
The effect of persistent acaricide residues on Varroa destructor population dynamics within honey bee colonies
Authors: Murcia-Morales María , Benito-Murcia María , Martín-Hernández Raquel , Fernández-Alba Amadeo , Higes Mariano
Published: July 2024

Continuous exposure of honey bee colonies to acaricides can affect Varroa destructor populations and their susceptibility to veterinary treatments. In this study, two groups of colonies were established using decontaminated wax or commercial wax (containing more pesticide residues). Both groups received two amitraz treatments and Varroa levels were monitored four times. Colonies containing contaminated wax exhibited consistently higher Varroa populations and the amitraz treatments had limited efficacy in reducing infestation, compared to colonies containing decontaminated wax. The findings suggest a connection between acaricide persistence and Varroa evolution, emphasizing the importance of indirect effects on honey bee behavior and colony dynamics.
Investigating Thermal Dynamic Behavior of Cryogenic Cooling for Low-Energy Impact Fracturing on ISO EN 1.0577 (S355J2) Mild Carbon Steel Grade Offshore Monopile Structures
Authors: Christensen Kenneth Bisgaard , Maheri Alireza , Siddiq M. Amir
Published: July 2024

This study delves into the significant area of low-energy impact fracturing within ISO EN 1.0577 (S355J2) mild carbon steel grade, exploring its cooling time depending on diverse temperature gradients across varying wall thicknesses. The cooling behavior is analyzed systematically to comprehend the material's structural dynamics under different thermal conditions. The findings, which are of utmost importance, offer insights into the nuanced interplay between temperature gradients and wall thickness, crucial for determining the cooling time needed to reach the desired temperature on the Ductile to Brittle Transition Temperature (DBTT) of the ISO EN 1.0577 (S355J2) mild carbon steel grade for the low-impact energy fracturing of the offshore structure depending on its wall thickness. The research not only delves into the mechanical aspects of low-energy impact fracturing but also unravels the thermal implications on cooling time depending on the desired temperature and the wall thickness of the mild ISO EN 1.0577 (S355J2) mild carbon steel structure, guiding engineering decisions for applications for low-energy impact fracturing added by cryogenic cooling of ISO EN 1.0577 (S355J2) mild carbon steel structure decommissioning.
3D path planning of unmanned ground vehicles based on improved DDQN
Authors: Tang Can , Peng Tao , Xie Xingxing , Peng Junhu
Published: July 2024

For safe and efficient path planning of unmanned ground vehicles in complex 3D environment, this paper proposes an improved deep reinforcement learning algorithm (Dual Experience Dynamic Target DDQN, DEDT DDQN) to solve the problems of sparse reward convergence and over-estimation that are difficulties for traditional DDQN algorithms in complex maps. The algorithm improves the performance of the DDQN algorithm in dealing with complex environments by dividing the input quality experience and dynamically fusing the a priori knowledge of DDQN and average DDQN for network parameter training. For unstructured 3D environments, this paper adopts a path planning strategy based on the digital elevation model (DEM) considering environmental characteristics and time cost. Simulation experiments of the DEDT DDQN algorithm in 3D maps modeled on realistic environments show that the DEDT DDQN algorithm reduces the number of inflection points and the average slope change by 40% and 16.7%, respectively, and improves the performance of optimization searching as well as the convergence speed by 5.34% and 60%, respectively. The proposed improved algorithm and adopted strategy can be applied in two different types of maps, which verifies the effectiveness and robustness of the algorithm and strategy.
Synthesis, characterization and impact of different carbon-based nanomaterials on gram (Cicer arietinum) plant growth and soil sustainability
Authors: Srivast Rajani , Awasthi Kalpana
Published: July 2024

The long-term use of chemical fertilizers negatively affects the environment and public health. Among many alternatives, applying carbon-based nanomaterials is a better option for maximizing plant growth acceleration while minimizing environmental damage. The objective of the present study is to evaluate carbon nanotubes (CNTs), functionalized carbon nanotubes (FCNTs), and graphene oxides (GO) on soil nutrient content and plant growth. We have synthesized and applied CNTs, FCNTs, and GO in the present study on gram plant growth and soil properties. Compared with the control (no nanomaterials), a 41% increase in crop height was noted in GO-treated crops, whereas this increase was 33% and 40% in FCNT and CNT-treated crops, respectively, after 90 days of seed sowing. Among treatments, the GO-treated plants showed a twofold increase in root length compared to the control whereas, this increase was 60% and 25% in FCNTs and CNTs-treated plants. GO-treated plants showed a maximum increase in plant biomass, soil organic matter, total nitrogen, microbial biomass, and enzymatic activity. Compared with the control, a 52% higher SDA was noted in GO-treated soil, whereas this, increase was 32% and 19% in FCNT and CNT-treated soils, respectively. Carbon-based nanomaterial is an organic substance that can regulate the soil microenvironment and has a certain activating effect on soil enzyme activity. The findings confirmed that adding carbon-based nanomaterials especially GO, to the soil may improve gram plant growth and soil sustainability.
Extracting subleading corrections in entanglement entropy at quantum phase transitions
Authors: Song Menghan , Zhao Jiarui , Meng Zi Yang , Xu Cenke , Cheng Meng
Published: July 2024

We systematically investigate the finite size scaling behavior of the Rényi entanglement entropy (EE) of several representative 2d quantum many-body systems between a subregion and its complement, with smooth boundaries as well as boundaries with corners. In order to reveal the subleading correction, we investigate the quantity “subtracted EE” S^s(l) = S(2l) - 2S(l)Ss(l)=S(2l)−2S(l) for each model, which is designed to cancel out the leading perimeter law. We find that (1) for a spin-1/2 model on a 2d square lattice whose ground state is the Neel order, the coefficient of the logarithmic correction to the perimeter law is consistent with the prediction based on the Goldstone modes; (2) for the (2+1)d(2+1)d O(3) Wilson-Fisher quantum critical point (QCP), realized with the bilayer antiferromagnetic Heisenberg model, a logarithmic subleading correction exists when there is sharp corner of the subregion, but for subregion with a smooth boundary our data suggests the absence of the logarithmic correction to the best of our efforts; (3) for the (2+1)d(2+1)d SU(2) J-Q_22 and J-Q_33 model for the deconfined quantum critical point (DQCP), we find a logarithmic correction for the EE even with smooth boundary.
“Gosto de ser livre, fazer as coisas no tempo que quero” Depoimentos de mulheres que optaram pela não maternidade
Authors: Almeida Jhenyfer Caroliny de , Moreno Lucca Gherardi , Gherardi Sandra Regina Marcolino , Marafon Alan de Almeida
Published: July 2024

Este trabalho teve como objetivo abrir um espaço de escuta para as mulheres que optaram pela não maternidade e refletir sobre os motivos de sua decisão. A pesquisa, de caráter qualitativo, foi realizada entre os meses de fevereiro e abril de 2023. Foram aplicados questionários online (socioeconômicos e perguntas com respostas objetivas e discursivas), divulgado em redes sociais (instagram e facebook) com grupos que se baseavam nesse perfil (temas “child free” ou “não maternidade”). O grupo amostral consistiu em 247 participantes, com idades entre 18 e 50 anos. Os dados socioeconômicos indicaram que a maior parte das participantes apresentavam elevado índice de escolarização e renda, corroborando com a literatura que indica que mulheres com maior vulnerabilidade social e baixa escolaridade tendem a ter menos opção em ser ou não mãe. Este grupo alega que a decisão pela não maternidade se baseia na existência de outras prioridades, tais como a liberdade, o trabalho e o desejo em manter o seu estilo de vida. Diante dos resultados é possível refletir que a identidade da mulher brasileira do século 21 está cada vez mais distante daquela visão tradicionalista e tem ganhado espaço e destaque nos contextos sociais, profissionais e públicos. Assim, este estudo indicou que a maternidade é apenas mais um dos possíveis caminhos da mulher e não somente um destino único e inevitável.
Impacto del modelo docencia servicio en un consultorio psicológico universitario en los años 2020-2021
Authors: Lotero Osorio Hernán Darío , Navarro Arboleda Luis Felipe , Marín Marín Margarita María
Published: July 2024

En Colombia, en el decreto 2376 de 2010 se exige a las instituciones de formación superior formar el talento humano en salud a través de la relación docencia-servicio, cumpliendo con los principios estipulados en la Constitución Política, las normas de salud y de educación. El objetivo de la actual investigación es describir la percepción del impacto generado por la prestación de servicios de atención psicológica brindados por un Consultorio Psicológico de una institución universitaria bajo el modelo docencia-servicio durante los años 2020-2021. El estudio presenta un diseño mixto de carácter exploratorio, con una muestra de 367 participantes, divididos entre miembros del comité docencia servicio, supervisores, practicantes profesionales y usuarios. Los resultados mostraron una percepción adecuada del impacto en los procesos formativos, de adquisición de competencias clínicas y de efectividad de los procesos terapéuticos empleados. Se discute acerca de la implementación de la relación docencia-servicio según las políticas legales vigentes y su ejecución en el proceso de prácticas profesionales. Se concluye que el acompañamiento a través del modelo de docencia-servicio permite garantizar un adecuado proceso formativo y de prestación de servicios de salud mental.
Validez y confiabilidad de las Escalas de siluetas de fatiga, caras de dolor revisada y catastrofización del dolor en adultos mayores
Authors: Tapias Soto María Fernanda , Mancera Pérez Natalia , Márquez Mercado Gabriela , Albarracín Rodríguez Angela Pilar
Published: July 2024

Durante el proceso de envejecimiento aparece el dolor como uno de los síntomas más comunes y al que menos se le presta atención, este puede generar un impacto negativo en la calidad de vida de las personas mayores. También, la fatiga se manifiesta frecuentemente, pero no se suele evaluar o exteriorizar en consulta. Por esto, la presente investigación tuvo como propósito estudiar la validez y fiabilidad de las escalas Siluetas de Fatiga, Caras de Dolor Revisada y Catastrofización del Dolor en una muestra de adultos mayores del área metropolitana de Bucaramanga. La muestra estuvo conformada por 131 adultos mayores tanto institucionalizados como no institucionalizados. Los resultados evidenciaron altos valores de fiabilidad en las tres escalas y se revisan las evidencias de validez con el análisis factorial exploratorio. En conclusión, las escalas contribuyen a la medición del dolor en adultos mayores colombianos, brindando a los profesionales de la salud instrumentos confiables. Se sugiere ampliar la muestra con estudios en otras regiones del país.
A Highly Efficient Preconcentration/Clean-Up Method for Insecticides, Fungicides, and Herbicides Determination in Water Samples and Flour Samples by HPLC-DAD Using Water-Induced and Restricted-Access Supramolecular Microextraction
Authors: Effting Luciane , Effting Letícia , Tarley César
Published: July 2024

A green supramolecular vortex-assisted microextraction employing a mixture of 1-decanol and tetrahydrofuran (THF) was developed for the simultaneous extraction of pesticides from different classes (insecticides, fungicides, and herbicides) from water and flour samples, followed by their determination in high-performance liquid chromatography with diode array detector (HPLC-DAD). The most favorable results were achieved at pH 6.0 in the presence of 4% (m/v) NaCl, utilizing a low volume of 1-decanol and THF (75 and 400 µL, respectively), a short vortex-assisted extraction time (120 s), and centrifugation time (120 s). These conditions yielded high preconcentration factors ranging from 50.1 to 90.3 and low limits of quantification (LOQs) ranging from 1.3 to 27.3 µg L-1. The intraday (n = 10) and interday (n =1 0) precision, assessed as the percentage of relative standard deviation (RSD), varied from 4.4 to 12.4%. The optimized method was successfully applied to determine the pesticides in water and flour samples, with recoveries ranging from 81 to 111%.
Artificial Intelligence Predictions of Biomass Power of an Installed Waste Water Treatment Plant
Authors: İlhan Akın
Published: July 2024

In the current study, the power generations obtained from gas turbines of an installed waste water treatment plant were predicted, utilizing artificial intelligence method consisting of artificial neural network (ANN). In this regards, a cumulative of 445 data, found in the power generation data cluster and found in the physical and chemical data clusters has been used in the predictions based on the artificial intelligence association method. Each instant data of these total 445 data corresponds to daily average power generation (P) obtained from gas turbines of the facility and corresponds to physical and chemical parameters including the temperature (T), degree of acidity (pH), conductivity (σ), as well as the daily total volumetric flow of the waste gas to be burned at the gas generator (Q). Accordingly, the best prediction obtained by ANN approach was concluded to generate the statistical accuracy results corresponding to 6.1279% mean absolute percentage error (MAPE), 2.1540 MWh/day root mean square error (RMSE), and 0.9730 correlation coefficient (R) for power generation parameter.
Toprak Mikrobiyoloji Laboratuvarlarında Güvenlik Önlemlerine göre Tehlikelerin Sıralanması
Authors: Işık Melek
Published: July 2024

Laboratuvar faaliyetleri gerçekleştiren kurum ve kuruluşlarda güvenlik önlemleri önemli hale gelmektedir. Güvenlik önlemleri için fiziksel, kimyasal ve biyolojik tehlikelerin sıralanması tedbirler açısından önemlidir. Bu çalışmada, toprak mikrobiyoloji laboratuvarı için güvenlik önlemlerinin Analitik Hiyerarşi Prosesi (AHP) yöntemiyle ağırlıklandırılması yapılmıştır. Güvenlik önlemleri biyogüvenlik kabini, çıkışa yakın el yıkama için lavabo, otoklav, laboratuvar güvenlik personeli, kendiliğinden kapanan kapı ve korumalı penceredir. Sonrasında, bu güvenlik önlemleri için fiziksel, kimyasal ve biyolojik tehlikeler Gerçekliği Yansıtan Eleme ve Seçim (ELECTRE-Elimination and Choice Translating Reality) yöntemiyle sıralanmıştır. Sonuç olarak, fiziksel tehlikelerin en çok dikkat edilmesi gerektiği sonucuna ulaşılmıştır.
Kar Erime Optimizasyonu Algoritması ile Çok Katmanlı Yapay Sinir Ağının Eğitimi
Authors: Özdemir Feyza Nur , Özkış Ahmet
Published: July 2024

Kar erime optimizasyonu (snow ablation optimizer, SAO) algoritması, karın erimesinden ilham alınarak 2023 yılında önerilen yeni bir metasezgisel algoritmadır. Bu çalışmada, yapay sinir ağının ağırlıklarının güncellenmesi amacıyla SAO algoritması ile hibrit bir model geliştirilmiştir. Geliştirilen hibrit model aggregation, balance, liver, pathbased ve wine adlı beş farklı veri seti üzerinde gri kurt, sürüngen arama, guguk kuşu ve sinüs kosinüs algoritmaları ile oluşturulan hibrit modeller ile karşılaştırılmıştır. Modellerin başarısını ölçmek için duyarlılık, özgüllük, kesinlik ve f1-puanı adı verilen dört farklı metrik kullanılmıştır. Modellerin her veri seti için başarı sıralaması ve tüm veri setleri için ortalama başarı sıralaması verilmiştir. Sonuçlar incelendiğinde, SAO modelinin tüm metrikler için wine veri setinde 2., diğer tüm veri setlerinde 1. olduğu görülmektedir. Ortalama başarı sırası açısından ise SAO modeli tüm metriklerde 1.2 değeri ile en iyi sonucu elde etmiştir. Ayrıca hibrit modellerin, eğitim aşamasındaki ortalama karesel hata değerlerinin yakınsama grafikleri çizdirilmiş ve SAO hibrit modelinin wine hariç diğer tüm veri setlerinde karşılaştırılan modellerden daha hızlı bir yakınsama performansına sahip olduğu gözlenmiştir. Son olarak popülasyondaki parçacık sayısının hibrit SAO modelinin başarısına etkisi analiz edilmiş ve birey sayısının 100 olması durumunda başarının arttığı gözlenmiştir.