bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on geomagnetic perceiving navigation method based on deep reinforcement learning
Authors: Hong Li , yan Xu , yu Liu
Published: October 2024

Path planning and navigation of Autonomous Underwater Vehicles face great challenges in unknown environments without a prior information. In this paper, a deep Q-network-based geomagnetic sensing navigation method is proposed to solve the navigation problem without a prior maps. By constructing a deep Q-network model, the method utilizes the powerful representation capability of deep learning to handle complex geomagnetic sensing data. Meanwhile, an action selection strategy combining heuristic and greedy search is introduced to balance exploration and exploitation and enhance the autonomous navigation capability of underwater vehicles in unknown environments. The strategy dynamically adjusts the exploration probability based on the distance to the target, ensuring effective exploration at an early stage and efficient utilization of the learned knowledge when approaching the target. Moreover, the Autonomous Underwater Vehicle explores the environment using local geomagnetic data and trains a regression model to predict the global geomagnetic map. Simulation results show that the method is significantly effective in reducing path lengths, improving exploration efficiency, and enhancing geomagnetic map accuracy. The results show that the method significantly improves the robot's navigation performance in unknown environments and provides a new way to construct geomagnetic maps.
Structure-based design of a broadly protective influenza hemagglutinin stem immunogen
Authors: Deng Lei , Liu De-Jian , Ru Yan-Xia , Zhao Shi-Long , Yang Guo-Huan , Zheng He-Ping , Liu Cui-Cui , Yi Da-Long , Zhou Wen-Shuo , Jia Wei-Guo , Teng Xiao-Nuo , Cao Wen-Long , Tang Yi-Bo , Song Wen-Wen , Wan Mu-Yang , Ge Xing-Yi , Sui Sen-Fang , Li Xiao-Jun , Zhan Zhi-Fei , Zhong Xiu-Qin , Peng You-Song , Peng Ya-Xuan , Li Yao-Wang
Published: October 2024

The conserved hemagglutinin (HA) stem region is widely regarded as a highly promising target for the development of a universal influenza vaccine. Through structure-based design and iterative mutagenesis screening, we successfully engineered a soluble trimeric H1 stem-only protein, designated #219, which does not contain heterologous trimerization motifs and thus prevents off-target immune responses. As confirmed by a 2.97 Å-resolution cryo-EM structure, the overall conformation of #219 remains intact. Vaccination of mice with #219 protected against lethal heterologous viral challenges. Specific serum antibodies strongly cross-reacted with HAs of diverse influenza A subtypes, cross-neutralized various H1N1 viruses, and exhibited multiple antibody-effector functions mediating infection-permissive protection. We have developed a promising H1 stem immunogen for broad cross-protection against influenza infection and also proposed an efficacious design strategy for soluble homo-oligomeric proteins.
Efficacy of oseltamivir and baloxavir against A(H5N1)-contaminated bovine milk in mice
Authors: Webby Richard , Jones Jeremy , Andreev Konstantin , Fabrizio Thomas , Bowman Andrew , Govorkova Elena
Published: October 2024

Understanding the reliability of FDA-approved antivirals against A(H5N1) influenza viruses circulating in peridomestic species including dairy cows is critical to public health and pre-pandemic planning, but it cannot be modeled clinically due to A(H5N1) disease severity. In mice, we demonstrate baloxavir treatment mediates greater disease outcomes (survival, viral dissemination) than oseltamivir after lethal challenge (orally, intranasally, ocularly) with A(H5N1)-contaminated cow milk.
The blue advantage: a novel blue carotenoprotein pigment in the tropical seastar Linckia laevigata is an antioxidant defence against extreme environmental stress
Authors: Williams Suzanne , Heyworth Stephanie M. , Kano Yasunori , Roberts Nicholas W. , Carter Hugh F. , Cheney Karen L.
Published: October 2024

Some species have evolved innovative solutions that allow them to thrive in extreme environments, including in habitats where temperature and ultraviolet radiation are high. Here we focus on the role of colour, particularly a blue carotenoprotein pigment, for survival in an environmentally stressful habitat. We show that blue Linckia laevigata seastars are common on tropical reef flats throughout the Indo-West Pacific, where at low tide, water temperatures can reach 40º C and water levels frequently drop < 0.5 m, sometimes resulting in animals being fully exposed to the air and ultraviolet radiation. Conversely, non-blue morphs live in water ≥ 1 m, where these stressors are ameliorated. Despite their different depth distribution, blue L. laevigata do not differ significantly from orange morphs in their ability to block ultraviolet radiation, which suggests that the blue carotenoprotein pigment is not a physical sunscreen. However, we show that saline extracts of skin, with intact blue carotenoproteins are antioxidants and demonstrate more than twice as much oxygen radical absorbance capacity as acetone extracts where the carotenoids (mainly astaxanthin) and protein moiety have dissociated. Together with depth data, this suggests that the blue pigment provides protection from environmental stress through an increased capacity to delay, prevent or repair oxidative damage and is a key evolutionary innovation in L. laevigata.
Single-cell imaging reveals efficient nutrient uptake and growth of microalgae that darken the Greenland Ice Sheet
Authors: Halbach Laura , Kitzinger Katharina , Hansen Martin , Benning Liane , Littmann Sten , Bradley James , Whitehouse Martin , Olofsson Malin , Mourot Rey , Tranter Martyn , Kuypers Marcel , Ellegaard-Jensen Lea , Anesio Alexandre
Published: October 2024

Blooms of dark pigmented microalgae accelerate glacier and ice sheet melting by reducing the surface albedo. However, the role of nutrient availability in regulating their growth remains poorly understood. We studied glacier ice algae on the Greenland Ice Sheet, providing the first single-cell based data on their carbon:nitrogen:phosphorus (C:N:P) ratios and assimilation of dissolved inorganic carbon (DIC) and DIN following various nutrient amendments. The single-cell dataset revealed high C:N and C:P atomic ratios in the algal biomass and the presence of intracellular P storage. Assimilation of DIC by the algae was not enhanced by ammonium, nitrate, or phosphate addition. Our combined results demonstrate that glacier ice algae can optimise nutrient uptake, facilitating the potential colonization of ablating ice sheet surfaces without the need for additional nutrient inputs. This adaptive strategy becomes particularly significant as climate warming accelerates the expansion of melt areas on the Greenland Ice Sheet.
Assessing the vulnerability of buildings to long-term sea level rise across the Global South
Authors: Willard-Stepan Maya , Gomez Natalya , Cardille Jeffrey , Galbraith Eric , Bennett Elena
Published: October 2024

Future sea levels are expected to rise, resulting in the progressive inundation of coastal cities. Because the spatio-temporal progression of this inundation is complex, few estimates have been made of how sea level rise will impact specific features of the built environment beyond 2100. Here we provide a first-order assessment of the vulnerability of buildings to sea level rise from satellite observation in Africa, Southeast Asia, and South and Central America. We circumvent factors such as local subsidence and ice sheet dynamics by defining an inundation metric as a function of Local Sea Level Rise (LSLR), rather than time. Of the 840 million buildings in the study region, we find ~ 3.0 million at risk of inundation with 0.5m LSLR, ~ 45 million with 5m LSLR, and ~ 136 million with 20m LSLR. Our results highlight geographic variability in vulnerability and demonstrate the benefits that low-emissions pathways imply for preserving built environments.
Metabolic heterogeneity in DLBCL cells reveals an innovative antimetabolic combination strategy
Authors: Lordello* Leonardo , Nuan-Aliman* Stéphanie , Kielbassa-Elkadi* Karoline , Montagne Aurélie , Kotta Konstantina , Martins Isabelle , Jurado Eva Pinto , Caradeuc Cédric , Lehmann-Che Jaqueline , Martínez-Climent Jose A. , Meignin Véronique , Giraud Nicolas , Kroemer Guido , Bertho Gildas , Thieblemont Catherine , Baud Véronique
Published: October 2024

Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma, characterized by aggressive and heterogeneous tumors originating from B-cells. Especially in patients with relapsed or refractory (R/R) disease, DLBCL remains a challenging cancer to treat. Metabolic reprogramming is a hallmark of malignant cells. Our research focuses on developing strategies to enhance the clinical outcomes for R/R DLBCL patients by targeting metabolic vulnerabilities. Here we report that the combination of metformin and L-asparaginase, two FDA-approved antimetabolic drugs, strongly sensitizes DLBCL cells to apoptosis, independently of their OxPhos or BCR/glycolytic status. The combination of metformin with L-asparaginase strongly impacts various metabolic liabilities, including glutaminolysis, lipid metabolism, TCA cycle and redox responses. In addition, this combination of antimetabolic drugs interferes with two critical pathways involved in cancer survival, namely the mTOR and MAPK oncogenic pathways. Most importantly, we obtained the proof of principle of the beneficial effect of the metformin and L-asparaginase combination in DLBCL patients. Taken together, our findings establish that combining metformin and L-asparaginase affects DLBCL cell survival by targeting multiple metabolic pathways and hence may represent a new approach for the treatment of R/R DLBCL patients.

*Leonardo Lordello, Stéphanie Nuan-Aliman, and Karoline Kielbassa-Elkadi are co-first authors.
fects of early drought-induced phenotypic plasticity on late plant seedling interactions
Authors: Xiali HOU , shu wang , yuanhu huang , qingzhu yang
Published: October 2024

In nature, plants are often exposed to a variety of environments. The study of plant phenotypic plasticity cannot ignore a variety of environmental factors. At present, early exposure to flood or drought conditions will change the response of plants to later conditions, but little research has been done on whether early drought experience affects the interaction between plants in the later period. This paper takes Celtis sinensis and Bidens pilosa L. as the research object, through the second stage of individual growth ( drought, wet ), intraspecific interaction ( dry-dry, drought-wet, wet-wet ), interspecific interaction (dry-dry, drought-wet, wet-dry, wet-wet) biomass and morphological characteristics. The results showed that under the intraspecific interaction, the total biomass and aboveground biomass of Celtis sinensis owed a promoting effect under the treatment of no plasticity in the early flower pot ( no induced DP ) and no plasticity in the early stage and plasticity in the neighbor ( single induced SP- ), while the total biomass and aboveground biomass of Celtis sinensis showed a competitive effect under the treatment of plasticity in the early flower pot ( double induced NP ) and plasticity in the early stage and no plasticity in the neighbor ( single induced SP + ). It shows that early water-induced plasticity affects the strength of plant interaction in the later stage to varying degrees. It experienced early wetting ( no induced DP ). In the later intraspecific interaction, Celtis sinensis showed limited aboveground growth and good underground growth, which was contrary to the result that the aboveground part grew well and the underground part grew limited under single induced SP-. This indicates that the current plastic response of plants is not only dependent on early environmental experience, but also may be related to the cost of plasticity. Therefore, the early plastic response to drought environment may sacrifice the subsequent growth potential of Celtis sinensis and limit the plasticity of Celtis sinensis in the later stage. For Bidens pilosa L. under the intraspecific interaction, the aboveground biomass was increased and the underground biomass was decreased under the treatment of early plasticity and no plasticity of neighbors ( single induced SP + ), while the aboveground growth was limited and the underground growth was good under the treatment of early plasticity and plasticity of neighbors ( single induced SP- ). The influence of different early experiences on the interaction between early and late plants Different Bidens pilosa L. can cope with the influence of late intraspecific interaction through the mutual transformation of aboveground and underground parts.
Hybrid Particle Swarm Optimization and Skewed Variable Neighborhood Search Techniques for the Generalized Max-Mean Dispersion Problem
Authors: Zhao Juntao , Hifi Mhand , Latrem Khadidja
Published: October 2024

When placing facilities such as warehouses, distribution centers, or public services (e.g., hospitals, fire stations), the objective is often to maximize the distance between selected facilities to ensure a wide service area and reduce redundancy. This is particularly important in areas where resource coverage must be spread evenly across a large geographical area. This paper focuses on this challenge by tackling the generalized max-mean dispersion problem with a novel hybrid optimization method. This method combines particle swarm optimization with skewed variable neighborhood search. It merges the global search capabilities of swarm-based optimization with the focused local search strengths of variable neighborhood search. The approach begins with a randomly generated population, refined through a greedy constructive procedure. A variable neighborhood descent strategy, employing diverse neighborhood operators and skewed local search techniques, is then applied to enhance the local search phase. This hybrid approach achieves a balance between global exploration and targeted local refinement, leading to improved solution quality and avoiding local optima. Experimental results illustrate that the proposed method significantly improves both solution quality and computational efficiency compared to existing techniques, achieving new lower bounds and matching the best-known solutions on other benchmark instances.
An Improved Marine Predators Algorithm for Shipment Status Time Estimation and Regression Problems
Authors: Özdemir Resul , Tasyurek Murat , Aslantas Veysel
Published: October 2024

In the realm of machine learning, the optimization of hyperparameters is a pivotal step in creating intelligent models of high efficacy. Configuration of hyperparameters in a smart way contributes to enhanced model generalization and resilience, mitigating the risks associated with overfitting or underfitting. Optimization algorithms play a decisive role in determining the ideal hyperparameters for machine learning algorithms. This study introduces a novel hyperparameter optimization approach based on the Marine Predators Algorithm designed for regression problems. The performance of the proposed algorithm is benchmarked against a spectrum of popular and classical optimization algorithms from the literature. Furthermore, hyperparameter optimization is examined for three widely employed machine learning algorithms which are Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM) and Support Vector Regression (SVR). Regression models are constructed using a actual world dataset for prediction of shipment status time, and the proposed algorithm is further evaluated with public three datasets suitable for regression analysis. A new hyperparameter decoding approach is proposed to turn hyperparameter optimization into a numerical optimization problem regardless of parameter type. Consequently, the experimental results indicate that the proposed optimization algorithm exhibited superior performance than the compared optimizers in hyperparameter optimization for both machine learning algorithms across all regression datasets.
High Throughput VLSI Design for Real-Time JPEG 2000 Embedded Block Coding
Authors: Jin Xin , Jing Peng , Wang Lin , Dai Yuzhou , He Siyuan , Ma Zhao , Zhang Wei
Published: October 2024

The Embedded Block Coding with Optimal Truncation (EBCOT) Tier-1 process is a critical component of the JPEG2000 framework, significantly influencing throughput in hardware encoders. This paper presents an optimized hardware architecture for a high-performance EBCOT Tier-1 encoder, based on parallel code-block processing. The design features simultaneous bit-plane coding via three parallel channels, along with concurrent arithmetic coding enabled by six context-generating units. To overcome the throughput bottleneck of conventional designs, we introduce a novel multiplexing strategy for the MQ coder. Our encoder achieves a throughput of 2782 Mb/s, a 7.3 times improvement over existing implementations, making it well-suited for high-speed JPEG2000 applications. The application of the proposed architecture achieves 1.05 times its throughput rate in the case of FPGA operating at frequencies lower than ASIC. When processing 512 $\times$ 512 size grayscale map, the processing speed can reach more than 160 FPS, which can well meet the real-time requirements of edge device applications.
A Lightweight Transformation Method for Protecting the Privacy of Image Training in Classification.
Authors: Liu Jiahao , Wei Ren , Cai Yifei , Zhang Xianchao , Zhu Tianqing
Published: October 2024

As a rapidly growing research field over the past decade, deep learning technology relies on large amounts of data to achieve better performance. However, privacy concerns arise due to the potential leakage of sensitive information in training data. Recent studies shown that deep learning models are susceptible to various privacy attacks, leading to the exposure of their training data. Such data leakage during model training and usage raises privacy concerns for data providers. While several methods, such as homomorphic encryption and knowledge distillation, can be used to protect training datasets, but they always require significant computational power and time. Given that most data providers lack access to powerful computational resources and ample time, we propose a lightweight and effective transformation-based method in this paper to protect training data privacy. Our experimental results show that deep learning models trained on images processed by the block mutation scrambling algorithm can still achieve acceptable accuracy. Additionally, we explored the reasons for the feasibility of this method and conducted a security and privacy analysis of the proposed approach, demonstrating that attackers cannot recover the images from the transformed training set or obtain usable image information.
An Analysis of Perception Types on HR Analytics by Corporate HR Practitioners: A Q Methodological Approach
Authors:   Human Engagement Institute, Lee Ae-Ree , Ryu Ki-Ung
Published: October 2024

The purpose of this study is to derive the perception types of corporate HR practitioners on HR Analytics and analyze the characteristics of each type. To achieve the purpose of this study, we used the Q methodology, suitable for studying the subjectivity of individuals' perceptions, beliefs, values, and attitudes toward HR analytics. As a result of analyzing 30 corporate HR practitioners, four types of HR analytics perceptions were derived. First, the ‘Balanced Judgment Support Tool Recognizer’ is a type that recognizes HR analytics as a tool that helps people make balanced judgments in consideration of preconceived notions or subjective opinions reflected in HR work. Second, the 'Emphasizer of Contextual Reflection', recognizes that HR analytics does not reflect results that can’t be expressed in numbers and emphasizes that situational context must be reflected. Third, the ‘Reality-Based Observer’ looks at HR analytics from a realistic perspective and expects it to be activated, but recognizes that it is still early. Fourth, the ‘Prioritizer of Objective Data’ prioritizes the importance of data, recognizing that HR analytics provides the most objective and reliable data to guide rational decision-making. Considering the types of HR analytics perceptions, it is necessary to recognize HR analytics as a way of working for HR management. However, it was concluded that it is necessary to establish standards for the direction of utilizing HR analytics that are influenced by the decision-making criteria of HR practitioners, and that it is necessary to organize a data-friendly environment in the HR field.
„Entweder Sein oder Seiendes“ – über ein fundamentales Missverständnis Heideggers Seinsbegriffes
Authors: Kraatz Karl
Published: October 2024

Slavni su filozofi desetljećima kritizirali Heideggerovu filozofiju zbog činjenice da je u njegovoj filozofiji sve podređeno jednom pitanju bivstvovanja. Po njihovu mišljenju, Heideggerov je naglasak na bivstvovanje doveo do sljepoće u pogledu mogućnosti bića. Pretpostavlja se da bivstvovanje nema nikakve veze s bićima. U ovom se radu, s obzirom na ono što Heidegger naziva “konkretnom univerzalnošću” pojma bivstvovanja, pokazuje da je kritika neopravdana. Istražit ću Heideggerovu tvrdnju da se pitanja o bivstvovanju moraju shvatiti kao konkretizacija (Konkretisierung) bića. Da bismo razjasnili i opovrgli kritiku Heideggera, potrebno je adresirati Heideggerovo razumijevanje konkretne općosti pojma bivostvovanja. Pokazuje se da Heidegger, na temelju svojega rada na formalnom označavanju pojmova, pretpostavlja nužno posredovanje između univerzalnosti pojmova i konkretnosti filozofiranja. Za Heideggera, filozofija je konceptualni rad i egzistencijsko opredjeljenje podjednako.
Das Wesen der Sprache und die philosophische Grundlegung der Grammatik bei den Griechen
Authors: Mikecin Igor
Published: October 2024

Mijena filozofijskog shvaćanja λόγος-a od Platona preko Aristotela do Stoika uvjetovala je nastanak filozofijske gramatike. Iz te gramatike razvila se je helenistička gramatika, koja otada određuje ustroj i upotrebu europskih jezika. Ona se oslanja ponajprije na Aristotelovu i stoičku logiku i gramatiku. Udaljavajući se međutim od svojih filozofijskih korijena, ona polaže temelj za daljnji razvoj nefilozofijske gramatike u Rimljana. S pojavom helenističko-rimske gramatike zaborav biti λόγος-a i ujedno biti govora dospijeva do svojeg prvog povijesnog vrhunca. Povijesni spomen na grčko filozofijsko porijeklo gramatike i napose na ranogrčko pred-gramatičko iskustvo λόγος-a, u kojem do riječi dolazi sama bit govora, ima svrhu da pobudi sluh za izvorno govorno kazivanje koje može izmaći vladavini gramatike.
MYOCARDITISREVEALING AN ADULTSTILLONSETDISEASE
Authors:   Cardiology Department, Lucie & Raymand Aubrac Hospital Center, Villeneuve Saint-Georges, France., Jaafari M. , Dahmani H. ,   Cardiology Department, Lucie & Raymand Aubrac Hospital Center, Villeneuve Saint-Georges, France., Krimech A. ,   Cardiology Department, Lucie & Raymand Aubrac Hospital Center, Villeneuve Saint-Georges, France., Ouaouicha H. ,   Cardiology Department, Lucie & Raymand Aubrac Hospital Center, Villeneuve Saint-Georges, France., Salengro E. ,   Cardiology Department, Lucie & Raymand Aubrac Hospital Center, Villeneuve Saint-Georges, France.
Published: October 2024

A 21-year-old male patient presented with a combination of fever, palpitations, a maculopapular rash, and pharyngitis. Laboratory tests revealed an elevated high-sensitivity troponin I concentration of 3000 ng/L, indicating potential cardiac involvement. A transthoracic echocardiogram demonstrated a reduction in global longitudinal strain, suggesting impaired cardiac function. Further investigation with cardiac magnetic resonance imaging confirmed the diagnosis of acute myocarditis. After a thorough clinical evaluation, the patient was diagnosed with adult-onset Stills disease. Treatment was promptly initiated, consisting of intravenous corticosteroids and Kineret (anakinra), aimed at managing the inflammatory response and preventing further complications.
ANALYSIS OF ECG WAVE USING PERCEPTRON NEURAL NETWORK
Authors:   Professor Gandhinagar University, Gandhinagar., Parihar Nilesh
Published: October 2024

Automatic Detection and classification of Cardiac abnormalities and Arrhythmias from a limited number of ECG signals is of considerable importance in critical care or operating room patient monitoring. We propose a method to accurately classify the heartbeat of ECG signals through the Perceptron Neural Networks. Feature sets are based on QRS complex of the ECG signal. The proposed method is capable of distinguishing the normal beat and 6 different arrhythmias. The results of the analysis are found to be more accurate and easily calculated than the other existing methods. Detection and classification of cardiac signals is important for diagnosis of cardiac abnormalities and hence any automated processing of the ECG that assists this process would be of assistance and is the focus of this paper.
Environmental, social, and governance performance: The role of Chinese employee stock ownership plans
Authors: Liu Yasi , McDowell Shaun , Xue Chunxiao , Zhang Jianing
Published: October 2024

The challenges of global warming, resource depletion, and environmental protection require immediate action from corporations, governments, and communities globally. Implementing environmental, social, and governance (ESG) measures represents a key strategy for corporations in addressing sustainability concerns. This study investigates how the ESG performance of publicly listed companies in China is influenced by employee stock ownership plans (ESOPs). Utilizing a dataset covering 4,464 publicly listed Chinese corporations from 2009 to 2022, this analysis employs fixed-effects regressions to reveal the beneficial impact of ESOPs on corporate ESG ratings. A firm’s transition from non-ESOP to ESOP status raises ESG ratings by 1.213, representing 22% of the ESG score’s standard deviation. The findings indicate that greater involvement of the top management team in an ESOP weakens the positive impact of the ESOP on corporate ESG performance. The positive impact of ESOPs on ESG performance is insignificant in the agriculture sector but more pronounced in the manufacturing and service sectors, where the transition to ESOP status results in ESG score increases of 1.122 and 1.500, respectively. The issue of endogeneity is addressed by utilizing a lagged ESOP independent variable and applying two-stage least squares regression with the average ESOP serving as the instrumental variable. The findings confirm that causality runs from ESOP to ESG rather than ESG influencing ESOP.
AcknowledgmentThis study was supported by the Department of Education of Zhejiang Province – General Program (Y202249981, Y202353438), the Wenzhou Association for Science and Technology – Service and Technology Innovation Program (jczc0254), the Wenzhou-Kean University Student Partnering with Faculty Research Program (WKUSPF202404, WKUSPF202411), the Wenzhou-Kean University International Collaborative Research Program (ICRP2023002, ICRP2023004), and the Wenzhou-Kean University Internal Research Support Program (IRSPG202205, IRSPG202206).
La evaluación gubernamental desde la Secretaría de la Función Pública
Authors: Lopez Blanca
Published: October 2024

En México, la Secretaría de la Función Pública coordina el Modelo de Evaluación de la Gestión Gubernamental para examinar el valor público de entidades y dependencias del Poder Ejecutivo federal. El objetivo de este artículo es revisar los resultados de este Modelo mediante el análisis cualitativo de los informes anuales de evaluación 2014-2019. De la revisión destaca que los resultados se presentan como ranking o tablero de control, aunque no son evaluaciones integrales de desempeño basadas en criterios de eficacia, eficiencia y otros, ni incluyen los niveles de la gestión pública. Otros hallazgos son los traslapes y la falta de coordinación con otros sistemas de monitoreo y evaluación, interacción con la ciudadanía y entidades evaluadas, armonización normativa y uso de evaluaciones, así como discrepancias entre evaluaciones del Modelo de Evaluación de la Gestión Gubernamental y auditorias, que obstaculizan su institucionalización. Finalmente, se sugieren acciones para mejorar el diseño del Modelo y fortalecer la evaluación de la gestión pública, pero también se refieren algunas limitaciones del estudio para analizar las capacidades institucionales y efectividad de las evaluaciones.
Entre la creencia y el escepticismo
Authors: Bañuelos Aquino Víctor Manuel
Published: October 2024

El análisis de documentos distintos a los realizados por grandes sistemas religiosos, como las sumas teológicas o la Biblia, puede ayudar a entender la religiosidad practicada por la comunidad menos cercana a la ortodoxia doctrinal desde fuentes diferentes y menos convencionales. Al hacer un cotejo de la cultura tipográfica de la última etapa del porfiriato se aprecian diversas voces activas en torno a temas de interés religioso, como las luchas entre liberales y partidarios de la Iglesia, como institución terrenal; y la disputa entre los que interpretaban los fenómenos naturales como señales divinas y sus detractores. De modo que en este artículo se explora la distinción entre el discurso de los diarios y la prensa numerada y los impresos populares noticiosos, ya que aunque en ocasiones estas formas de cultura tipográfica hablaban de los mismos acontecimientos, no lo hacían desde la misma postura: los primeros solían hacerlo a partir de la creencia pasiva y los segundos a partir de una creencia activa, desde el punto de vista de los creyentes.
Molecular Docking in Drug Discovery: Techniques, Applications, and Advancements
Authors: Aguiar Cinthia , Camps Ihosvany
Published: October 2024

The primary objective of this study is to conduct a comprehensive review of
the significance of molecular docking in the field of drug discovery. This includes an examination
of the various approaches and methods used in molecular docking, as well as
an exploration of the techniques used for interpreting and validating docking results. To
gather relevant data, a systematic search was conducted using Web of Science, PubMed,
and Google Scholar. The search focused on articles related to molecular docking methodologies
and their applications in drug discovery. Additionally, alternative techniques
that can be used for more precise simulations of ligand-protein interactions were also
considered. Molecular docking has proven to be an incredibly rich and valuable process
in the field of drug discovery. Its flexibility allows for the incorporation of advanced
computational techniques, thereby enhancing the reliability and efficiency of drug discovery
processes. The results of the study highlights the significant strides made in the
field of molecular docking, demonstrating its potential to revolutionize drug discovery.
Molecular docking continues to evolve, with new advancements being made regularly.
Despite the challenges faced, these advancements have significantly contributed to the
enhancement of molecular docking, solidifying its position as a crucial tool in the field
of drug discovery.
Improved Therapeutic Efficacy: Liposome-Coated Mesoporous Silica Nanoparticles Delivering Thymoquinone to MCF-7 Cells
Authors: Arvejeh Pooria M. , Chermahini Fatemeh A. , Soltani Amin , Lorigooini Zahra , Rafieian-Kopaei Mahmoud , Mobini Gholam Reza , Khosravian Pegah
Published: October 2024

Background:

Breast cancer remains a significant global health challenge, with thymoquinone
showing promise as a therapeutic agent, but hindered by poor solubility.

Objective:

This study aimed to enhance TQ delivery to MCF-7 breast cancer cells using mesitylene-
mesoporous silica nanoparticles coated with liposomes, designed for controlled drug release.

Methods:

Nanoparticles were synthesized using the sol-gel method and coated with phosphatidylserine-
cholesterol liposomes. Different nanocharacterization techniques and in vitro assays
were employed to assess the drug release kinetics, cellular uptake, cytotoxicity, and apoptosis.

Results:

The nanoparticles exhibited favorable properties, including a large pore size of 3.6 nm, a
surface area of 248.96 m2/g, and a hydrodynamic size of 171.571 ± 8.342 nm with a polydispersity
index of 0.182 ± 0.017, indicating uniformity and stability. The successful lipid bilayer coating
was confirmed by a zeta potential shift from +6.25 mV to -5.65 mV. The coated nanoparticles demonstrated
a slow and sustained drug release profile, with cellular uptake of FITC-formulated
nanoparticles being approximately 5-fold higher than free FITC (P < 0.0001). Cytotoxicity assays
revealed a significant reduction in cell viability (P < 0.0001), reaching an IC50 value of 25 μM at
48 hours. Apoptosis rates were significantly higher in cells treated with the formulated TQ compared
to the free drug and control at both 24 and 48 hours (P < 0.0001).

Conclusion:

This nanoformulation significantly enhanced TQ delivery, offering a promising strategy
for targeted breast cancer therapy. Further preclinical studies are recommended to advance
this approach in cancer treatment.
BBBper: A Machine Learning-based Online Tool for Blood-Brain Barrier (BBB) Permeability Prediction
Authors: Kumar Pawan , Saini Vandana , Gupta Dinesh , Chawla Pooja A. , Kumar Ajit
Published: October 2024

Aims:

Neuronal disorders have affected more than 15% of the world's population, signifying
the importance of continued design and development of drugs that can cross the Blood-Brain
Barrier (BBB).

Background:

BBB limits the permeability of external compounds by 98% to maintain and regulate
brain homeostasis. Hence, BBB permeability prediction is vital to predict the activity of a drug-like
substance.

Objective:

Here, we report about developing BBBper (Blood-Brain Barrier permeability prediction)
using machine learning tool.

Method:

A supervised machine learning-based online tool, based on physicochemical parameters to
predict the BBB permeability of given chemical compounds was developed. The user-end webpage
was developed in HTML and linked with back-end server by a python script to run user queries and
results.

result:

BBBper uses a random forest algorithm at the back end, showing 97

Result:

BBBper uses a random forest algorithm at the back end, showing 97% accuracy on the external
dataset, compared to 70-92% accuracy of currently available web-based BBB permeability
prediction tools.

Conclusion:

The BBBper web tool is freely available at http://bbbper.mdu.ac.in.
Revisiting the COVID-19 Pandemic: A Comparative Analysis between Traditional and Synthetic Modes of Treatment with the Aid of In-silico Methods
Authors: Das Priyam Jyoti , KEMISETTI DURGA PRASAD , Ahmed Shiny , Alam Faruk
Published: October 2024

Introduction/Background:

The COVID-19 pandemic has severely disrupted global health
systems, highlighting the urgent need for effective treatment strategies. This article aims to provide
an assessment of the pandemic's current status and examines the effectiveness of traditional treatments
against innovative synthetic approaches.

Materials and Methods:

The article explores synthetic strategies involving repurposed antiviral
drugs, supportive care, and vaccinations. It emphasizes the role of computational modeling and artificial
intelligence in engineering molecules with potent antiviral properties. In-silico methods were
utilized to accelerate chemical library screenings, predict efficacy, and assess interactions between
viral proteins and potential treatments.

Results:

Studies employing molecular docking analysis have evaluated the efficacy of approved
antiviral drugs and natural compounds. Notably, Azithromycin was found to have a potential inhibitory
effect with a binding energy of -9.69, while natural compounds like Camphor and Curcumin
displayed binding energies of -5.18 and -6.16, respectively.

Discussion:

Synthetic treatments showed effectiveness in inhibiting viral proteins and facilitating
rapid development, while natural products were more effective in preventing virus entry.

Conclusion:

Based on in-silico docking studies, it can be concluded that natural products have more
therapeutic effects than synthetic drugs.
Thrombocytopenia and Other Hematological Features in COVID-19 Patients Referred to Shahid Mostafa Khomeini Hospital
Authors: Nourmohammadi Hassan , Shafiei Elham , Mami Sanaz , Tavan Hamed
Published: October 2024

Introduction:

COVID-19 is a deadly virus, but there is still no appropriate cure for it.
Hence, the target of this study was to estimate the clinical value of thrombocytopenia and other
blood parameters in COVID-19 patients referred to Ilam Shahid Mostafa Khomeini Hospital from
April and September 2020.

Materials and Methods:

In this cross-sectional study, patients with thrombocytopenia, associated
with COVID-19, diagnosed at the Shahid Mostafa Khomeini Hospital in Ilam City during the spring
and summer of 2020 were included. A checklist was used to record the hematological indicators of
the patients. Further, an analysis of data using SPSS V20 software was performed.

Results:

Overall, 66 thrombocytopenic patients were studied. Among patients who succumbed to the
disease complications, 40 (67.8%) were male, and 19 (32.2%) were female. Mortality and survival
rates were 90% and 10%, respectively.

Conclusion:

Due to the high mortality rate of COVID-19 patients with thrombocytopenia, platelet
count can be considered a major risk factor, as well as a prognostic and diagnostic indicator in these
patients.
Illustrations of a Building Design, Foundation System, and Link Bridge
Authors: Cheng Y.M. , Law C.W.
Published: October 2024

This chapter introduces a complete design of the ELS, foundation, and superstructure
in Hong Kong. The constraints and various considerations with respect to the final scheme for
the foundation, ELS, and multi-storey buildings are discussed.
Determinants of growth and measures to prevent professional crime in Russia in 1917 – early 1920s
Authors: Zarubina K A
Published: October 2024

Relevance. Considerable scientific interest is the analysis of the determinants of the development of professional crime in times of crisis, when the political, socio-economic, and cultural spheres of life are particularly unstable in the country. The analysis of these conditions on the example of individual historical periods will make it possible to predict possible changes in the directions of development of domestic professional crime in the present and to determine effective measures against the growth of professional criminal activity in different historical realities.

The purpose of the study is to analyze the causes, factors and conditions of the growth of professional crime in Russia in the 1917 – early 1920s, as well as measures to prevent this dangerous type of criminal activity.

Objectives: to analyze the main determinants of the growth of professional crime in Russia in 1917 – early 1920s; to study individual measures to prevent the development of professional crime in Russia in the chronological period under study; to determine the effectiveness of measures used to counteract professional crime in Russia in 1917 – early 1920s.

Methodology. In the process of working on the study, methods of synthesis, analysis, systematization, generalization, as well as comparative legal and chronological methods were used.

The results. The article examines individual factors, causes and conditions of the growth of professional crime in Russia in 1917 – early 1920s. It was established that against the background of the growing activity of professional criminals in Russia during this period, a targeted policy was implemented to counter the development of this type of crime, but later it was curtailed.

Conclusion. The results of the study allowed us to determine that the development of professional crime in the designated period was influenced by such determinants as the general deterioration of the financial situation of a large part of the country's population, the growth of child homelessness, the lack of effectively functioning law enforcement agencies, as well as some others. The Soviet government made the necessary efforts to combat various manifestations of professional crime, but the "imaginary victory" over this dangerous anti-social phenomenon declared by the Soviet government and the curtailment of certain measures to combat professional crime did not lead to positive results, as a result of which the Soviet criminal world became even more consolidated and monolithic.
The historical evolution of the Russian railway technical operation rules
Authors: Polyakova A. S.
Published: October 2024

Relevance. For almost two centuries, rail transport has been and remains one of the key means of transportation. Due to this, it is necessary to ensure traffic safety, which should be reflected in the basic rules applicable to railway transport. This article is devoted to the analysis of the rules of technical operation of railway transport from the end of the XIX century to the present. The development of railway techniques and technologies reflects not only progress in the engineering and technical fields, but also the vast context of social, economic, political and scientific changes. The study of the evolution of the rules of technical operation allows us to trace these changes and draw conclusions about how scientific and technical innovations were formed and introduced into the practice of railway transport.

Purpose of the study is to study the evolution of the rules of technical operation of Russian railway transport in different periods of time.

Objective is to conduct a comparative analysis of the evolution of the rules of technical operation of railway transport from the end of the XIX century to the present to identify changes in the basic requirements for safety and technical characteristics, to identify the causes of changes and the influence of political, economic and technological factors on the formation of these rules; to assess the role of changes in the context of the development of the railway system.

Methodology. The research is based on the principles of objectivity and historicism. To solve the tasks set, such methods as historical-comparative, historical-genetic, historical-typological were used.

Results. A comparison of the provisions of the rules of technical operation of railways made it possible to objectively assess the impact of scientific and technological progress in the field of railway transport on the formation and strengthening of regulatory and technical traffic safety.

Conclusion. The author came to the conclusion that the rules of technical operation of railways have undergone a number of changes, innovations, exceptions and improvements over their history, but many provisions remain unchanged to this day. The accumulated operational, technical and normative experience is necessary for further improvement of the safety system in Russian railway transport.
INTERFERENCE CANCELLERS FOR SPREAD SPECTRUM MODULATION BASED MULTIPLE ACCESS SYSTEMS
Authors:   Fr. Conceicao Rodrigues College of Engineering, India, Khanore Monica , Unnikrishnan Srija ,   Fr. Conceicao Rodrigues College of Engineering, India
Published: October 2024

Systems based on spread spectrum technique are inherently interference resistant. However, asynchronous transmission and multipath propagation causes manifestation of multiuser interference. Multiuser interference in a multiple access system limits the capacity of the system. Hence, it becomes imperative to mitigate the interference. This work presents the design and mathematical analysis of Hybrid Interference Cancellation (HIC) detector for direct-sequence code division multiple access (DS-CDMA). The detector is analysed for single path as well as multipath propagation over a Rayleigh fading channel. Simulation results are compared with the results of Successive Interference Canceller (SIC). Furthermore, the SIC and HIC detectors are tested for convergence. An HIC detector is proposed for MC-CDMA system. The interference canceller discussed in this paper dispenses with the RAKE receiver for diversity combining and data estimation, which averts the likelihood of errors because of incorrect data estimates.
INTRUSION DETECTION SYSTEM TO AVOID MALICIOUS INTRUDERS IN HIGHER LAYER NETWORK SECURITY
Authors:   Veltech Hightech Dr.Rangarajan Dr.Sakunthala Engineering College, India, E Kamalanaban , S Madhusudhanan ,   Prathyusha Engineering College, India, D Jennifer ,   Panimalar Engineering College, India, M Jayaprakash ,   RMK Engineering College, India
Published: October 2024

Online criminals are focusing their attention more and more on ordinary computer users, seeking to take advantage of them through a variety of social and technological exploitation techniques. Some hackers are getting more skilled and determined. The ability to conceal their identities, keep their communications secret, keep their finances separate from their activities, and make use of private infrastructure are all areas in which cybercriminals have shown a high degree of proficiency. It is of the utmost importance to safeguard computers with surveillance systems that are able to identify complex varieties of malware. In this paper, we utilized machine learning algorithm to validate the samples from different datasets. The machine learning classifier is utilized to find the efficacy of the entire model in validating the class samples. The simulation is conducted in python to test the efficacy of the model against various class of datasets. The results show that the proposed method achieves higher degree of accuracy than the other models.
DETECTION OF CYBER ATTACK ON INTERNET OF VEHICLE COMMUTERS
Authors:   Srinivas University, India, H.A. Dinesh , Rammohan S. Radha ,   Srinivas University, India, A Jayanthiladevi ,   Srinivas University, India, S Kamala ,   Srinivas University, India, Akpakaro Jackson ,   University of Africa, Nigeria
Published: October 2024

The Internet of Vehicles (IoV) is a massive interactive network that can be extended into the realm of smart transportation by utilizing IoV at scale because it is capable of attaining unified management. It is well known that the gathered contents not only contain personal information, but also certain critical data, such as a vehicle running parameter, which is strongly related to traffic safety. This study explains how a network intrusion detection system (IDS) based on artificial intelligence can be deployed over various datasets. The simulation is carried out in an extensive way and the results show that the proposed method achieves a higher rate of accuracy in detecting the instances than the other existing methods.
BLOCKCHAIN-POWERED INTRUDER IDENTIFICATION IN IOT NETWORKS - METHODOLOGY AND IMPLEMENTATION
Authors:   Dhanalakshmi Srinivasan Engineering College, India, Kesavan V. Thiruppathy , D Danalakshmi ,   Dhanalakshmi Srinivasan University, India, R Gopi ,   Dhanalakshmi Srinivasan Engineering College, India
Published: October 2024

The Internet of Things (IoT) is expanding rapidly, raising concerns about network security against attackers. This article explores the use of blockchain technology to enhance intrusion detection and mitigation in IoT networks. By leveraging blockchain’s decentralized and immutable ledger features, the study proposes monitoring and validating device interactions using smart contracts. Devices are assigned unique identities recorded on the blockchain, ensuring a tamper-resistant operation log. Smart contracts trigger alarms and response mechanisms upon detecting suspicious activity. A smart home scenario demonstrates the approach, where various IoT devices are interconnected on the blockchain. The network is equipped with a variety of IoT devices, ranging from smart thermostats to security cameras. Experimental results show high performance across key parameters: Identification Rate, Accuracy, False Positive Rate, True Positive Rate, False Negative Rate, and True Negative Rate, indicating the method’s efficacy in improving IoT security, ensuring device integrity, and maintaining trust in a connected world. This method shows blockchain’s potential to improve IoT security, ensuring device integrity and trust in a connected world.