bluuebunny/crossref_metadata_2025 huggingface dataset:
An investigation on 45S5 nanobioactive glass using FTIR and Raman spectroscopy
Authors: Sanjay Sharda Sundaram , Yadav Pratibha , Asthana Nidhi , Dwivedi Mrigank Mauli , Pandey Kamlesh
Published: February 2024

Bioactive materials are those that cause a number of interactions at the biomaterial-living tissue inter-face that result in the evolution of a mechanically strong association between them. For this reason, an implantable material’s bioactive behavior is highly advantageous. Silicate glasses are encouraged to be used as bioactive glasses due to their great biocompatibility and beneficial biological effects. The sol-gel method is the most effective for preparing silicate glasses because it increases the material’s bioactivity by creating pores. Glass densities are altered by the internal network connectivity between network formers and network modifiers. The increase in the composition of alkali or alkaline oxides reduces the number of bridging oxygens and increases the number of non-bridging oxygens by retaining the overall charge neutrality between the alkali or alkaline cation and oxygen anion. Higher drying temperatures increase pore densities, while the melt-quenching approach encourages the creation of higher density glasses. Band assignments for the BAG structure can be explained in detail using Fourier Transform Infrared (FTIR) and Raman spectroscopic investigations. Raman spectroscopy makes it simple to measure the concentration of the non-bridging oxygens in the silica matrix.
Stator-rotor fault diagnosis of induction motor based on time-frequency domain feature extraction
Authors: Yi Lingzhi , Long Jiao , Wang Yahui , Sun Tao , Huang Jianxiong , Huang Yi
Published: February 2024

Since the induction motor operates in a complex environment, making the stator and rotor of the motor susceptible to damage, which would have significant impact on the whole system, efficient diagnostic methods are necessary to minimize the risk of failure. However, traditional fault diagnosis methods have limited applicability and accuracy in diagnosing various types of stator and rotor faults. To address this issue, this paper proposes a stator-rotor fault diagnosis model based on time-frequency domain feature extraction and Extreme Learning Machine (ELM) optimized with Golden Jackal Optimization (GJO) to achieve highprecision diagnosis of motor faults. The proposed method first establishes a platform for acquiring induction motor stator-rotor fault data. Next, wavelet threshold denoising is used to pre-process the fault current signal data, followed by feature extraction to perform time-frequency domain eigenvalue analysis. By comparison, the impulse factor is finally adopted as the feature vector of the diagnostic model. Finally, an induction motor fault diagnosis model is constructed by using the GJO to optimize the ELM. The resulting simulations are carried out by comparing with neural networks, and the results show that the proposed GJO-ELM model has the highest diagnostic accuracy of 94.5%. This finding indicates that the proposed method outperforms traditional methods in feature learning and classification of induction motor fault diagnosis, and has certain engineering application value.
The development of a meta-learning calibration network for low-cost sensors across domains
Authors: Tianliang Feng , Xingchuang Xiong , Shangzhong Jin
Published: February 2024

Low-cost sensor arrays are an economical and efficient solution for large-scale networked monitoring of atmospheric pollutants. These sensors need to be calibrated in situ before use, and existing data-driven calibration models have been widely used, but require large amounts of co-location data with reference stations for training, while performing poorly across domains. To address this problem, a meta-learningbased calibration network for air sensors is proposed, which has been tested on ozone datasets. The tests have proved that it outperforms five other conventional methods in important metrics such as mean absolute error, root mean square error and correlation coefficient. Taking Manlleu and Tona as the source domain and Vic as the target domain, the proposed method reduces MAE and RMSE by 17.06% and 6.71% on average, and improves R2 by an average of 4.21%, compared with the suboptimal pre-trained multi-source transfer calibration. The method can provide a new idea and direction to solve the problem of cross-domain and reliance on a large amount of co-location data in the calibration of sensors.
A new approach to water cooling of photovoltaic panels with a tracking system
Authors: Płachta Kamil , Mroczka Janusz , Ostrowski Mariusz
Published: February 2024

The article presents a water-cooling system for photovoltaic (PV) modules using a two-axis tracking system that tracks the apparent position of the Sun on the celestial sphere. The cooling system consists of 150 adjustable spray nozzles that cool the bottom layer of PV modules. The refrigerant is water taken from a tank with a capacity of 7 m 3. A water recovery system reduces its consumption with efficiency of approximately 90%. The experimental setup consists of a full-size photovoltaic installation made of 10 modules with an output power of 3.5 kWp combined with a tracking system. The article presents an analysis of the cooling system efficiency in various meteorological conditions. Measurements of energy production were performed in the annual cycle using three different types of photovoltaic installations: stationary, two-axis tracking system and two-axis tracking system combined with the cooling system.
A hybrid denoising method for gyroscopes based on multiple screening
Authors: Rong Hailong , Jin Tianlei , Wang Hao , Wu Xiaohui , Zou Ling
Published: February 2024

To reduce the random error of microelectromechanical system (MEMS) gyroscope, a hybrid method combining improved empirical mode decomposition (EMD) and least squares algorithm (LS) is proposed. Firstly, based on the multiple screening mechanism, intrinsic mode functions (IMFs) from the first decomposition are divided into noise IMFs, strong noise mixed IMFs, weak noise mixed IMFs and signal IMFs. Secondly, according to their characteristics, they are processed again. IMFs from the second decomposition are divided into noise IMFs and signal IMFs. Finally, useful signal is gathered to obtain the final denoising signal. Compared with some other denoising methods proposed in recent years, the experimental results show that the proposed method has obvious advantages in suppressing random error, greatly improving the signal quality and improving the accuracy of inertial navigation.
Comparison of the neutronic properties of the (Th-233U)O2, (Th-233U)C, and (Th-233U)N fuels in small long-life PWR cores with 300, 400, and 500 MWth of power
Authors: Lapanporo Boni Pahlanop , Su’ud Zaki , Mustari Asril Pramutadi Andi
Published: February 2024

The neutronic characteristics of (Th-233U)O2, (Th-233U)C, and (Th-233U)N have been compared in small long-life pressurized water reactors (PWRs). Neutronic calculations were carried out at 300 MWth, 400 MWth, and 500 MWth with two cladding types: zircaloy-4 and ZIRLO (Zr low oxygen). They were performed using the Standard Reactor Analysis Code (SRAC) and JENDL-4.0 nuclide data, dividing the reactor core into three fuel zones with varying 233U enrichment levels, ranging from 3% to 9% and fluctuating by 1%, employing the PIJ module at the fuel cell level and the CITATION module at the reactor core level. In addition, 231Pa was added as burnable poison (BP). The (Th-233U)N fuel demonstrated superior criticality compared to the other fuel types, as it consistently achieves critical conditions throughout the reactor’s operating cycle with excess reactivity <1.00% dk/k for several fuel configurations at the 300 MWth and 400 MWth power levels. Moreover, the (Th-233U)N and (Th-233U)C fuels exhibited similar and flatter power density distribution patterns compared to the (Th-233U)O2 fuel. The power peaking factor (PPF) value was relatively higher for (Th-233U)O2 fuel than the other two fuels. The (Th-233U)N fuel exhibited the most negative Doppler coefficient, followed by (Th-233U)C and (Th-233U)O2 fuels. Analysis of burnup levels revealed that the (Th-233U)O2 fuel achieved significantly higher burnup than the other two fuels.
Readiness to discharge patients after radical prostatectomy with the assistance of the da Vinci robot
Authors: Hreńczuk Marta Katarzyna , Maziarz Milena , Małkowski Piotr
Published: February 2024

Aim. The study aimed to assess the readiness for discharge of patients after da Vinci robot-assisted radical prostatectomy.

Material and methods. The study included 100 patients on the day of discharge, treated in one of Warsaw’s hospitals at the turn of 2022 and 2023. The study was conducted by means of a diagnostic survey, the tool was the C-HOBIC questionnaire. The SPSS programme was used in the statistical analysis. A statistical signifi cance of p<0.05 was assumed.

Results. Patients demonstrated good readiness for discharge, especially in terms of knowledge about taking medications. They showed the lowest readiness when it came to observing disturbing health-related symptoms. Education level had an impact on patients’ ability to take medications.

Conclusions. Patients show good readiness to leave the hospital. Their knowledge of how to take medications is particularly good, although being able to notice symptoms or changes in health requires a little more attention. Pre-discharge education is a key element in preparing patients for self-care at home.
What the relationship of religion and culture means for the role of the State in society: Parliamentary debates on education during the “Kulturkampf” in Prussia, France and the Netherlands
Authors: van der Eyk Lise
Published: February 2024

Die Ära der Kulturkämpfe kann als ein Schlüsselmoment in der westeuropäischen Geschichte gesehen werden, in dem die Beziehung zwischen Kultur und Religion ein zentrales Thema und Gegenstand unterschiedlicher Interpretationen war, je nach politischem Standpunkt und Land. Diese unterschiedlichen Auffassungen und Definitionen liegen den Argumenten über die Rolle des Staates bei der Erziehung der Nation in diesen Debatten zugrunde. Am Beispiel Preußens, Frankreichs und der Niederlande in den 1870/80er Jahren analysiere ich, welche Rolle dem Staat als „Ersatz“ für die Kirche in der Schule zugeschrieben wurde und welche Rolle die unterschiedlichen und oft gegensätzlichen Definitionen von Religion in der Argumentation hatten.

L’ère du Kulturkampf apparaît comme un moment historique privilégié dans l’Europe occidentale où l’articulation entre culture et religion est centrale et sujette à des interprétations très divergentes selon les forces politiques et les pays. Ces différentes conceptions et définitions constituent en même temps un enjeu majeur des débats parlementaires autour du rôle de l’Etat dans l’éducation de la nation à cette époque. A partir de l’exemple de la Prusse, de la France et des Pays Bas dans les années 1870/80, l’objet de cette contribution est d’analyser le discours de « remplacement » de l’Eglise par l’Etat dans le domaine de l’école ainsi que les enjeux qui y sont liés pour les définitions de la religion.

The Kulturkampf era can be seen as a key moment in western European history in which the relationship between culture and religion is a central theme and subject to different interpretations depending on the political actors and the country. These different representations of religion and its role in culture function as premises in arguments regarding the role of the State in national education. Using parliamentary debates in the 1870s/80s in Prussia, France and the Netherlands as case studies, I analyze the discourse on the role of the State as “replacement” for the Church in the school and the role that often contradictory definitions of religion had in the legitimation of or opposition to legislation on this topic.
ANÁLISE DO CIDADÃO COMO PROTAGONISTA NA CONSTRUÇÃO DA CIDADE INTELIGENTE: UMA REVISÃO SISTEMÁTICA DA LITERATURA
Authors: Yaya Miguel Lucas dos Santos , Rosa Eduarda , Oliveira Guilherme , Brito Paola da Silva , Moraes Cristine Frare
Published: February 2024

Esta revisão sistemática da literatura aborda a relevância dos cidadãos no contexto do desenvolvimento de cidades inteligentes. Seu objetivo é conduzir uma análise abrangente da literatura sobre o conceito de Cidadãos Inteligentes, buscando elucidar as tendências e direções que essa área de pesquisa tem seguido. A metodologia adotada envolve uma abordagem qualitativa que combina revisão sistemática da literatura e análise de conteúdo categorial indutiva. A pesquisa utilizou as bases de dados Scopus e Scielo para realizar consultas, resultando na identificação de 535 artigos. Após uma avaliação criteriosa, 92 desses artigos foram considerados pertinentes para a investigação. A análise dos dados revela que fatores como educação, infraestrutura, tecnologia e a dinâmica entre governo e sociedade desempenham papéis cruciais não apenas na promoção de Cidades Inteligentes, mas, sobretudo, no desenvolvimento dos cidadãos que residem nesse contexto. Ainda, a análise das características desejáveis nos cidadãos inteligentes destaca a importância da disposição para adotar tecnologias, engajamento social e a incorporação de um estilo de vida sustentável. O estudo enfatiza que a transição para uma cidade inteligente demanda não apenas a implementação de tecnologias inovadoras, mas também a adoção de um modelo educacional que capacite e promova a alfabetização digital dos cidadãos, permitindo-lhes explorar e co-criar valor a partir dessas inovações tecnológicas.
Eschatologie Pana Cogito
Authors: Michalski Przemysław
Published: February 2024

Artykuł jest próbą analizy wierszy Zbigniewa Herberta o tematyce eschatologicznej. Autor proponuje podział tych utworów na wiersze eschatologiczne we właściwym znaczeniu tego słowa, czyli takie, które zmagają się z tajemnicą śmierci i życia pozagrobowego oraz proponują poetyckie wizje zaświatów, i wiersze określone jako quasi-eschatologiczne, to znaczy utwory wykorzystujące eschatologiczne obrazowanie do omawiania problemów doczesnych.
Stunting dan Malnutrisi Penyebab Kelainan Email Gigi Anak dan Early Childhood Caries (ECC): Komprehensif Review
Authors: Prihastari Lisa , Prasonto Djuned , Rintoko Bimo , Jos Erry Hesti Witasari
Published: February 2024

Background: Childhood dental health is a vital component of overall well-being, with Early Childhood Caries (ECC) and defect enamel being major concerns. This article explores the intricate connection between stunting, malnutrition, and the development of defect enamel and ECC in children. Methods: Narrative review use Pubmed and Google Scholar databases with article inclusion criteria, namely research articles and reviews that discuss the relationship between enamel defects and malnutrition and ECC with malnutrition Results: Childhood malnutrition, characterized by inadequate intake of essential nutrients, poses a significant global health challenge. Stunting, a manifestation of chronic malnutrition, adversely affects physical growth and cognitive development in children. However, the link between malnutrition and dental health has not received adequate attention. This article examines the mechanisms through which malnutrition, specifically stunting, can contribute to the development of defective enamel in children. Nutritional deficiencies, particularly in calcium, vitamin D, and fluoride, are identified as key culprits in compromising enamel formation and strength. Weakening of the enamel leaves teeth vulnerable to dental caries, including ECC, which can lead to pain and long-term oral health problems. The complex relationship between malnutrition, stunting, defect enamel, and ECC calls for multifaceted solutions. Conclusion: This article highlights the importance of holistic public health initiatives, which encompass nutritional education for caregivers and improved access to dental care services for at-risk children. Interdisciplinary collaboration among healthcare professionals is emphasized to address the synergistic nature of these interconnected health challenges.
Unit Cost Perawatan Gigi di Klinik Fanisa Kota Pariaman dengan Metode Activity Based Costing
Authors: Hidayati Hidayati , Febrian Febrian , Lendrawati Lendrawati , Suprianto Kosno
Published: February 2024

Objective: To find out unit cost of dental health service in Pariaman City Fanisa Clinic using the Activity Based Costing method in era of national health insurance. Method : This research was a quantitative descriptive study that used was Activity Based Costing (ABC) used mathematical calculations. Results : The results of this study indicated there was 8 dental health service in Fanisa Clinic in Pariaman City in 2018 and the unit cost for each service was consultation Rp.55.945, permanent tooth extraction Rp.127.825, extraction of deciduous teeth Rp.79.311, composit resin patching Rp.156.384, GIC patching Rp.145.843, scalling Rp.131.358, premedication Rp.61.291 and pulp capping Rp.107.729. Conclusion: The highest unit cost for dental health services at the Fanisa Clinic in Pariaman City was composite resin patching service and the lowest was consulting services. The average unit cost of dental health services at the Fanisa Clinic in Pariaman City was Rp.108.211. The biggest cost in the production unit was the cost of employee salary.
Potensi Kader Posyandu sebagai Tenaga Skrining Early Childhood Caries (ECC) Tidak Terawat
Authors: Pujiastuty Arymbi
Published: February 2024

Background: Early Childhood Caries (ECC) is a significant health problem. Untreated ECC can have substantial impacts on individuals and communities, causing pain, disrupting functions, hindering the child's growth process, affecting the child's weight, and influencing the child's developmental progress, ultimately reducing the quality of life for the child. Preventive efforts for untreated ECC include activities such as ECC screening, allowing for prompt intervention in cases of untreated ECC. Non-dental health personnel, such as community health workers, are alternative resources that can be empowered to participate in screening for untreated ECC using pufa Index. Purpose: to analyze the level of validity and reliability of community health workers in conducting screening for untreated ECC using the pufa index. Methods: The research design involves diagnostic testing with a cross-sectional approach, and samples are taken from children in community health posts using simple random sampling. The study is conducted in the working area of the Sijunjung Health Center, Sijunjung District, West Sumatra. Results: The reliability of cumulative PUFA examinations by Community health workers with a Kappa value of 0.88 is considered a very strong level of agreement. The sensitivity and specificity values of cumulative PUFA are 96% and 94%, respectively, which indicate excellent diagnostic values. This means that Community health workers demonstrate a very strong level of agreement and excellent accuracy in diagnosing untreated ECC using the PUFA index in young children. Conclusion: Community health workers have great potential to be empowered as personnel for screening untreated ECC using pufa index.
Behavior of Reinforced Concrete Corbels Strengthened with CFRP Strips Subjected to Monotonic and Repeated Loading
Authors: Ibrahim Enas S. , Abdulrahman Mazin B. , Yahia Yasser I. , Alsubari Belal , Abdulaali Hayder S. , Alqawzai Shagea
Published: February 2024

Concrete corbels are short cantilevers subjected to monotonic and repeated loads. Repeated loads generally negatively affect the concrete structural members' strength as they decrease the resistance to external loads. To increase these loads, strengthening with carbon fiber reinforced polymer (CFRP) strips as an externally bounded technique is used. This paper studies the behavior and strength of strengthened corbels subjected to monotonic and repeated (constant and incremental) loads. The experimental program included the casting and testing of twelve double-concrete corbels. All specimens have been kept constant for corbel dimensions and main and secondary reinforcement. Nine were strengthened with CFRP strips using different patterns, while the others were left un-strengthened as control corbels. The results showed that both repeated loads' types, i.e., constant and incremental, affected the ultimate load capacity of corbels. Compared to monotonic loading, a reduction occurred in ultimate load and ultimate deflection for corbels subjected to five repeated loading cycles. For corbels strengthened by externally bounded CFRP strips under any applied loads, the ultimate load significantly increased, while the ultimate deflection decreased compared to un-strengthened at the same applied load. All corbels failed by de-bonding the CFRP strips.
Anti-Crisis Industrial Policy of the Constituent Entities of the Russian Federation during the COVID-19 Pandemic
Authors: Koshkin Andrey Vyacheslavovich , Shcheglov Maksim Yur'evich , Bit-Zaya George Aleksandrovich , Kalinichenko Anastasia Sergeevna , Mikhaleva Diana Maksimovna
Published: February 2024

The COVID-19 pandemic was one of the first “black swan” for the global economy. Regional authorities in Russia were faced to support their regional economies but they were faced with uncharacteristic independence. The issue of assessing the effectiveness of regional anti-crisis industrial policy measures in Russia during the COVID-19 crisis is becoming urgent. The purpose of this study is to search for the most successful measures of regional support in Russia during the designated period. The study is based on the conceptual framework of the St. Petersburg School of Industrial Policy. Descriptive statistics, cluster analysis, and correlation analysis are used as statistical methods of analysis. 1196 anti-crisis industrial policy measures were classified in all 85 regions of the Russian Federation. A scatter diagram of regions was constructed with indicators of the scale for assessing the intensity of the anti-crisis industrial policy and the scale of the impact of the crisis on socio-economic indicators. Four clusters were identified: (1) regions that practically did not implement an anti-crisis industrial policy and suffered during the crisis; (2) regions that have significant economic stability and are less likely to resort to active anti-crisis policies; (3) regions, the values of indicators of the dynamics of socio-economic indicators of which are at an average and below level, but are pursuing, on average, a more intensive anti-crisis policy; (4) regions that pursued an active anti-crisis industrial policy and achieved good socio-economic indicators. Correlation analysis did not reveal a stable connection between the intensity of the anti-crisis policy and the crisis dynamics of socio-economic indicators. The study also presents leading regions and outsider regions in terms of anti-crisis industrial policy measures for each of the 4 clusters.
Advances in Space Launch System Booster Separation Computational Fluid Dynamics
Authors: Meeroff Jamie G. , Dalle Derek J. , Rogers Stuart E. , Burkhead Aaron C. , Schauerhamer Daniel G. , Diaz Joshua F.
Published: February 2024

The Space Launch System (SLS) employs two Space Shuttle–derived solid rocket boosters, which separate from the SLS core while still experiencing appreciable aerodynamic loads. Creating an aerodynamic database for this phase of flight can be challenging due to the large number of independent variables needed to fully constrain the problem and the complex flow induced by exhaust plumes of the booster separation motors and core main engines impinging on other parts of the vehicle. This paper details recent efforts in generating aerodynamic data used to create databases for the SLS during the booster separation event using viscous computational fluid dynamics (CFD) simulations obtained using NASA’s FUN3D solver. Particular challenges faced when modeling a complex problem, such as booster separation, are presented. Reductions in interpolation error estimates were observed through the introduction of a physics-based covariance approach to building the CFD run matrix, eliminating infeasible booster location permutations that could potentially skew final response surfaces. Interpolation error control is shown using test cases outside of the main database. Code-to-code comparisons between the FUN3D and OVERFLOW solvers are also presented to further verify the results.
Fluidic Flow Control Devices for Gust Load Alleviation
Authors: Khalil Khalid , Bauknecht André
Published: February 2024

A reduction in the structural weight and climate-relevant emissions of future transport aircraft can be realized through active gust load alleviation, limiting the peak aerodynamic loads experienced in flight. Two fluidic concepts, surface and Coandă jets, offer promising solutions. The surface jet induces a separated flow region on the wing’s suction side near the trailing edge, while the Coandă jet utilizes tangential blowing over a rounded trailing edge to make use of the Coandă effect for direct circulation control. This study investigates these fluidic actuation concepts using two-dimensional unsteady Reynolds-averaged Navier–Stokes simulations on a supercritical airfoil to alleviate gust-induced lift increases. Results reveal that fluidic concepts can surpass the load reduction capability of a trailing edge flap. Notably, the Coandă-type design, while more efficient, exhibits limited control authority compared to surface jet, achieving maximum gust load reductions of 40% versus 70% for surface jet. Optimizing the temporal deployment of the surface jet leads to increased peak lift reduction. Even under challenging conditions with reduced gust anticipation time and actuator placement near the wing tip with a reduced chord length, the surface jet maintains consistent performance and therefore offers a promising solution for active gust load alleviation on future aircraft.
Aircraft Simulations Using the New CFD Software from ONERA, DLR, and Airbus
Authors: Stefanin Volpiani Pedro , Chapelier Jean-Baptiste , Schwöppe Axel , Jägersküpper Jens , Champagneux Steeve
Published: February 2024

This paper presents a thorough comparison between RANS simulations performed with the computational fluid dynamics by ONERA, DLR, and Airbus (CODA) new-generation flow solver and reference legacy codes TAU (DLR) and elsA (ONERA) for high-speed cruising NASA Common Research Model (CRM) configurations that were considered in the context of the 5th, 6th, and 7th Drag Prediction Workshops. The solver’s accuracy is assessed with several meshing strategies, including block-structured, hybrid-structured/unstructured, and fully unstructured tetrahedral meshes. This solver features both a cell-centered finite-volume (FV) scheme suited to arbitrary meshes as well as a modern high-order discontinuous Galerkin (DG) scheme. We show that for all cases considered, the FV component recovers an equivalent accuracy compared to elsA (cell-centered FV) on block-structured meshes and TAU (node-centered FV) on hybrid and unstructured meshes. The high-order DG scheme (third-order accurate) is found to significantly enhance the drag prediction on coarse meshes compared to legacy FV methods, both for structured and unstructured meshes.
Generative Adversarial Networks for Inverse Design of Two-Dimensional Spinodoid Metamaterials
Authors: Liu Sheng , Acar Pınar
Published: February 2024

The geometrical arrangement of metamaterials controls their mechanical properties, such as Young’s modulus and the shear modulus. However, optimizing the geometrical arrangement for user-defined performance criteria leads to an inverse problem that is intractable when considering numerous combinations of properties and underlying geometries. Machine-learning techniques have been proven to be effective and practical to accomplish such nonintuitive design tasks. This paper proposes an inverse design framework using conditional generative adversarial networks (CGANs) to explore and optimize two-dimensional metamaterial designs consisting of spinodal topologies, called spinodoids. CGANs are capable of solving the many-to-many inverse problem, which requires generating a group of geometric patterns of representative volume elements with target combinations of mechanical properties. The performance of the networks was validated by numerical simulations with the finite element method. The proposed inverse design framework vastly improves the efficiency of design exploration and optimization of spinodoid metamaterials.
A Comparative Study on the Cognitive Functions and Psychological Factors Associated with Google Effect among College Students
Authors: Ms. Shruti Mohan  , Dr. Pangajam Ponnusamy
Published: February 2024

The usage of digital gadgets for academic purposes has increased significantly after the Covid-19 pandemic lockdown. Google Effect is also known as Digital Amnesia which can be stated as the tendency to forget what is being read on a digital gadget believing that they can refer to it whenever they are in need of it. College students were recruited through purposive sampling and screened based on checklist was developed for the study which was validated by experts in the field of psychiatry, neurology and clinical psychology. Cognitive functions were assessed using subtests of Weschler’s Memory Scale-lll. The DASS-21 was used to measure features of depression, anxiety and stress and EIS was also used to find the difference in emotional intelligence, t-test was used to analyze the significant difference between the two groups. Findings indicates that the students who had Google Effect had shown significant impairment in the cognitive tests of memory and learning compared to the group without Google Effect along with higher scores in depression, anxiety and stress and lower scores in emotional intelligence. This implies the need to bring awareness and interventions in limiting dependence on digital devices.
Postoperative discal pseudocyst: Report of A case with an unusual complication after microlumbar discectomy and successful treatment by transforaminal endoscopic lumbar decompression
Authors: Patgaonkar Prasad R. , Kokate Sagar Kishor , Subith S. , Borole Pushkar S.
Published: February 2024

Background:

Lumbar discal pseudocysts are uncommon complications that can arise following lumbar spine surgery. It manifests as a fluid-filled sac near the intervertebral disc, causing pain and discomfort. Understanding its causes, symptoms, and management is crucial for patients and healthcare professionals involved in postoperative spinal care.

Case Description: A

35-year-old female developed a discal pseudocyst after undergoing laminectomy and discectomy for lumbar disc herniation. The patient presented with recurrent lower back pain, radiculopathy, and neurological deficit two months post-surgery. Imaging revealed a discal pseudo cyst causing compression of the traversing right L5 nerve root. Given the refractory nature of her symptoms, an endoscopic procedure was offered. Using the transforaminal endoscopic technique, the pseudo cyst was identified and removed, leading to immediate symptomatic relief.

Conclusion:

This article reports the rare occurrence of discal pseudocyst and highlights the use of endoscopic techniques in its surgical management. Surgeons should be aware of the minimally invasive techniques, as they can offer less morbidity, shorter recovery times, and reduced healthcare costs compared to traditional open surgery.
Bio produced nanoparticles load into extracellular vesicles and support horizontal transfer of therapeutic antimiR
Authors: Pourali Parastoo , Svoboda Milan , Benson Veronika
Published: February 2024

The extracellular vesicles (EVs) serve for cell-to-cell communication and delivery of signaling molecules and they represent interesting approach in targeted therapy. This study focuses on an EV-mediated transfer of functionalized nanoparticles into recipient tumor cells. We used biologically produced gold nanoparticles (AuNPs) with known physical-chemical properties and decorated them with an inhibitory RNA targeting oncogenic microRNA-135b (AuNPs-antimiR 135 b) and transferrin (AuNPs-antimiR 135 b-Tf). The AuNPs were added to the breast cancer 4T1 cell line at a non-toxic dose 0.03 µg/µL. The 4T1-autologous EVs (with or without the AuNPs) were extracted and analyzed. The amount of endocytosed and excreted AuNPs was determined by graphite furnace atomic absorption spectrometry. The protein content was analyzed using sodium dodecyl-sulfate polyacrylamide gel electrophoresis and liquid chromatography with mass spectrometry (LC–MS). The fate of EVs and/or AuNPs was characterized using a Transmission Electron Microscopy and Zetasizer. The target-specific silencing effect of the antimir-135b was analyzed with a quantitative real-time PCR (qPCR). The AuNPs produced by Fusarium oxysporum possessed round shape, size of 5 nm and a zeta potential of -33 mV. We observed two types of EV populations: 60 nm and 250 nm. Out of the initial 58.7 µg of AuNPs added to the cells, 52.68 ± 0.65 µg were internalized and 38.64 ± 0.29 µg were found inside the EVs. The protein content in EV-AuNPs was higher compared to control EVs. LC-MS analysis showed that the AuNPs could alter the protein expression profile of the cancer cell. qPCR results revealed both EV-AuNPs-antimiR 135 b and EV-AuNPs-antimiR 135 b-Tf silenced target microRNA-135b, but higher efficacy was observed in the EV-AuNPs-antimiR 135 b-Tf group. Obtained data proved EV-mediated transportation of biological AuNPs bearing effector RNA among tumor cells. We also found the efficacy of loaded EVs is higher using AuNPs decorated with a tumor-specific ligand such as transferrin.
Proximity Graph Networks: Predicting Ligand Affinity with Message Passing Neural Networks
Authors: Gale-Day Zachary J. , Shub Laura , Chuang Kangway V. , Keiser Michael J.
Published: February 2024

Message-passing neural networks (MPNNs) on molecular graphs generate continuous and differentiable encodings of small molecules with state-of-the-art performance on protein-ligand complex scoring tasks. Here, we describe the Protein-Graph Network (PGN) package, an open-source toolkit that constructs ligand-receptor graphs based on atom proximity and allows users to rapidly apply and evaluate MPNN architectures for a broad range of tasks. We demonstrate the utility of PGN by introducing benchmarks for affinity and docking score prediction tasks. Graph networks generalize better than fingerprint-based models and perform strongly for the docking score prediction task. Overall, MPNNs with Proximity Graph data structures augment the prediction of ligand-receptor complex properties when ligand-receptor data are available.
Modeling Exciton Transport in Organic Semi-conductors Using Machine Learned Hamiltonian and its Gradients
Authors: Ghalami Farhad , Dohmen Philipp M. , Krämer Mila , Elstner Marcus , Xie Weiwei
Published: February 2024

In this study, we present a multiscale method to simulate the propagation of Frenkel singlet excitons in Organic Semi-conductors(OSCs). The approach uses advanced neural network models to train Frenkel-type Hamiltonian and its gradient, obtained by the Long-Range Correction version of Density Functional Tight-Binding with Self-Consistent Charges (LC-DFTB2). Our models accurately predict site energies, excitonic couplings, and corresponding gradients, essential for the non-adiabatic molecular dynamics simulations. Combined with Fewest Switches Surface Hopping (FSSH) algorithm, the method was applied to four representative OSCs: Anthracene (ANT), Pentacene (PEN), Perylenediimide (PDI), and Diindenoperylene (DIP). The simulated exciton diffusion constants align well with experimental and reported theoretical values, and offer valuable insights into exciton dynamics in OSCs.
Cationic Nanoparticle Interactions with Catabolic Cartilage Modify Macrophage Cytokine Production
Authors: von Mentzer Ula , Havemeister Fritjof , Råberg Loise , Erensoy Gizem , Esbjörner Elin K , Stubelius Alexandra
Published: February 2024

Cationic nanoparticles (NPs) have emerged as promising candidates for intra-articular drug delivery, showcasing their potential as efficient carriers. However, despite their evident utility, many studies neglect to investigate their interactions with the extracellular matrix (ECM). This oversight represents a significant gap in our understanding, particularly in the context of osteoarthritis (OA) treatment, where viable therapeutic options are limited. The clinical translation of functionalize drug carriers for OA has been hindered, in part, by our incomplete comprehension of how these materials interact with and respond to the pathological environment. This study aims to address this gap by examining how cationic NPs interact with ECM components in an ex vivo OA cartilage explant model. By comparing the behavior of smaller (<10nm) and larger (~270 nm) cationic NPs and subjecting them to explants preconditioned with OA-specific catabolic enzymes, we observed multifaceted effects on ECM integrity and biomolecule conformation. All NP-biomolecule complexes induced differential cytokine production from stimulated macrophages. Smaller polyamidoamine (PAMAM) nanocarriers reduced glycosaminoglycan (GAG) release from explants but increased proinflammatory cytokine stimulation under pathological conditions, while larger poly lactic(co-glycolic)acid(PLGA)/polyethylenimine(PEI)-based nanocarriers maintained GAG release but induced a significantly lower proinflammatory cytokine response. Collagenase-induced OA-mimicking preconditioning produced distinct profiles across the NP panel in GAG interactions and cytokine production. The findings from these studies underscore the significance of tailored nanocarrier approaches to achieve optimal therapeutic efficacy for OA and other complex diseases.
Water-Assisted Diffusional Phase Transitions in Inorganic Metal Halide Perovskites
Authors: Liu Jialin , Hao Xiangming , van Huis Marijn , Fan Zhaochuan
Published: February 2024

In experiments, water is observed to accelerate the black-yellow phase transition in inorganic metal halide perovskites (MHPs). However, the underlying microscopic mechanisms for this phenomenon remain unclear. In this study, we employ classical molecular dynamics simulations to examine the role of water molecules in the yellow-black phase transition in the typical inorganic MHP CsPbI3. Our simulation results demonstrate that the black-yellow phase transitions in CsPbI3 follow a crystal-amorphous-crystal two-step mechanism and that water molecules in the air can enter the amorphous interface between the black and yellow regions. The rate of the yellow-black phase transition markedly increases with the influx of interfacial water molecules, which enhance ion diffusivity by reducing the diffusion barrier, thereby expediting the yellow-black phase transition in CsPbI3. We discuss implications for the reverse black-yellow phase transition, which is known to degrade the photovoltaic properties of perovskites, and we present a general mechanism through which solvent molecules can greatly facilitate phase transitions that otherwise have prohibitively high transition energies.
Nanoscale analysis of plastic contaminants migration in packaging materials and potential leaching into model food systems
Authors: M. Mileo Paulo G. , Krauter Caroline M. , Sanders Jeffrey M. , Coscia Benjamin , Browning Andrea R. , Halls Matthew D.
Published: February 2024

Polymers are the most common packaging materials used for food, beverages, cosmetics, and other consumer products. The ever-growing concern over pollution generated from single-use packaging materials, and the ensuing potential environment contamination resulting from their use has raised safety questions. Polymers used in these materials are often not spared from the presence of impurities, including unreacted monomers and small oligomers. The characterization of transport properties, including diffusion and leaching of these penetrant molecules is largely hampered by the long timescales involved in shelf-life experiments. In this work, we employ molecular simulation techniques to explore the main mechanisms involved in the bulk and interfacial transport of monomer molecules from three polymers commonly employed as packaging materials: polyamide-6, polycarbonate, and poly(methyl-methacrylate). Our simulations shed light on the main diffusion mechanisms for in- and outbound penetrant diffusion and provide rationalization for monomer leaching in model food formulations as well as bulky industry-relevant molecules. With these molecular-scale characterization we provide base insights to aid the design of polymer/consumer product interfaces with reduced risk of contamination and longer shelf-life.
PREDICTING CARDIAC ISSUES FROM ECHOCARDIOGRAMS: A LITERATURE REVIEW USING DEEP LEARNING AND MACHINE LEARNING TECHNIQUES
Authors:   Research Scholar, Department of Computer Science, Vellalar College for Women,  Thindal, Tamilnadu, India, Valanrani B.Arockia
Published: February 2024

Cardiovascular disease (CVD) has a substantial impact on overall health, well-being, and life-expectancy. Echocardiography is a widely used imaging technique in cardiovascular medicine, utilizing various medical imaging technology to visualize heart chambers and valve’s motion activity. In order to diagnose and treat complicated cardiovascular problems, it takes high-resolution images of the heart and its surroundings. However, it has limitations such as long procedure times, multiple measurement values, complex analyses, individualized assessments, operator subjectivity, and wide observation ranges. This makes it challenging for sonographers to accurately detect and diagnose heart diseases. In recent days, Deep Learning (DL) is increasingly used in clinical computer-assisted systems for disease detection, feature segmentation, functional evaluation, and diagnosis. It is an alternate technique for accurate detection and treatment of cardiovascular disorders; it improves the diagnostic capacities of echocardiography by identifying pathological conditions, extracting anatomically significant data, measuring cardio-motion, and calculating echo image quality. This paper presents a detailed review of various DL frameworks developed to analyse different cardiac views using echocardiography for improving the prediction and diagnosis of CVD. At the outset, a variety of echocardiography systems linked with DL-based segmentation and classification are reviewed briefly. Afterwards, a comparison research is carried out to gain insight into the shortcomings of those algorithms and provide a fresh approach to improve the accuracy of cardiac view categorization in echocardiography systems.
Medical Sensors and their Integration in Wireless Body area Networking for Pervasive Healthcare Delivery
Authors:   PG Scholar, Dept of Medical Electronics, Sengunthar Engineering College (Autonomous), Tiruchengode. Tamil Nadu, INDIA, S Raffi , sathik Raja Prof.Muhammadu ,   Professor, Dept of Medical Electronics, Sengunthar Engineering College (Autonomous), Tiruchengode. Tamil Nadu, INDIA, K. Prof.Jamuna ,   Professor, Dept of Medical Electronics, Sengunthar Engineering College (Autonomous), Tiruchengode, Tamil Nadu, INDIA
Published: February 2024

Wireless Body Area Networks (WBANs) integrate diverse sensors like heart rate monitors, electrocardiograms, pulse oximeters, respiration rate sensors, gyroscopes, and skin conductance sensors into a network for pervasive healthcare delivery. This interconnected system enables real-time monitoring and data fusion, ensuring accurate and comprehensive health assessments. Efficient communication protocols, cloud integration, and power management enhance the reliability and longevity of wearable devices. Security measures and user-friendly interfaces prioritize the protection of sensitive health data and ease of access. Machine learning algorithms contribute to predictive analytics for early detection of health issues. WBANs offer a holistic approach to personalized healthcare, allowing for continuous and remote monitoring of physiological parameters. The seamless integration of these sensors establishes a foundation for timely intervention and improved patient outcomes.
Multikulturalisme dan Kebijakan Publik: Rekognisi dan Perlindungan Hak Asasi Masyarakat Adat di Indonesia dalam Perspektif Universalisme Interaktif Seyla Benhabib
Authors: Sentana Fajar Yudha , Manalu Abby Gina Boang
Published: February 2024

This article discusses the issue of recognition and protection of community rights in Indonesia in the light of Seyla Benhabib's interactive universalism. The research aims to analyse the challenges and opportunities in pursuing recognition and protection of indigenous peoples within the framework of interactive universalism, by emphasising cultural diversity and the importance of the local context. Interactive universalism concerns about the importance of dialogue, public participation, and the adaptation of democratic principles in preserving indigenous peoples' rights. Here interactive universalism is used to review the state of indigenous peoples' rights in Indonesia. Various public policies have caused conflicts, ranging from land take over to human rights violation, that are detrimental to the existence of indigenous peoples. Public policy as a representation of the state should protect their rights. In this article public policies are reviewed from the perspective of interactive universalism. The review process will consider cultural diversity in order to prevent future problems and to recommend adequate and assured protection of the rights of indigenous peoples. This research is a qualitative research using a philosophical approach and literature review to analyse actual problems.
Book & Film Reviews
Authors: Bawono Haryo Tejo
Published: February 2024

Book & Film Reviews is a column in "MELINTAS" containing reviews of books and films published recently that bring different interpretation and inspiration to the fields of philosophy and religion.