bluuebunny/crossref_metadata_2025 huggingface dataset:
Barriers and Challenges in the Implementation of Decentralized Solar Water Disinfection Treatment Systems – a Case of Ghana
Authors: Afitiri Abdul-Rahaman , Afrifa Ernest Kofi Amankwa
Published: February 2025

Decentralized solar water disinfection systems (DSODIS) in continuous flow systems are alternatives for large-scale improved water access in rural contexts. However, DSODIS in rural Ghana are limited. Exploratory sequential mixed-methods design (QUAL→QUAN) was used to explore the enablers and barriers as well as reported barrier perceptions to effective implementation of DSODIS in the Sawla-Tuna-Kalba district (STK) of Ghana. The qualitative data (26 respondents) were analyzed thematically, and the quantitative data (1155 household heads) were subjected to a Poisson regression analysis. Enablers were categorized into themes as willingness to pay for DSODIS, household and community participation, and willingness to use water from DSODIS. Similarly, the barriers include environmental barriers, technological barriers, economic barriers, and political and legal barriers. Household characteristics such as main water source and income, age group, education, marital status, household size, born in community, and lived in the community are statistically associated with reported barrier perceptions. Households with unimproved water sources and high income (IRR=1.432, P=0.000) and improved water sources and high income (IRR=1.295, P=0.000) are, respectively, 43% and 30% more likely to report more barrier perceptions compared with households with unimproved water sources and low income. Females (IRR=1.070, P=0.032) are marginally more likely to report more barrier perceptions compared with males. The model output also indicates that household heads with higher educational attainment (IRR=1.152, P=0.001) are 15% more likely to report more barrier perceptions compared with those with no formal education. The findings provide valuable information to policymakers and stakeholders aimed at providing quality water in rural Ghana, where centralized systems cannot be installed.
A Simple Rigorous Proof of Riemann’s Hypothesis
Authors: Tang Jau
Published: February 2025

We present a simple rigorous proof of Riemann’s hypothesis. This hypothesis has remained unsolved since Riemann’s original formulation in 1859, although numerous zeros have been found along the critical line with the assistance of computer calculations. Our analytic proof is based on the analysis of the reflection symmetry between |Γ(s⁄2))〖(ζ(s))⁄π^(s⁄2) |〗^2 and |Γ(((1-s))⁄2)) 〖ζ(1-s)⁄π^(((1-s))⁄2) |〗^2, although the zeta and Gamma functions are asymmetric. We show their global minimum along the x-direction throughout the critical strip, their zeros, and the non-trivial zeros of the zeta function must occur at s=1/2+iy. If the zeros were not along the critical line, we show contradictions to the properties of the symmetric functional pair would arise. Thus, we prove rigorously the validity of Riemann’s conjecture.
Harnessing the Power of Improved Deep Learning for Precise Building Material Price Predictions
Authors: Guo Zhilong , Luo Yayong , Yi Tongqiang , Jing Xiangnan , Ma Jing
Published: February 2025

Accurate forecasting of construction material prices is essential for effective cost control and risk management in construction projects. However, due to the influence of various complex factors, building material prices exhibit high nonlinearity and instability, making traditional prediction methods often inadequate for achieving optimal results. This study introduces an innovative prediction model, CEEMDAN-VMD-GRU-ARIMA, specifically designed for forecasting the price of prestressed steel bars. This model uniquely combines CEEMDAN and VMD to address nonlinear characteristics, and it innovatively incorporates sample entropy for the adaptive selection of either GRU or ARIMA for prediction. Additionally, a VMD decomposition mode number K value optimization method based on a sparse index is proposed. Experimental results demonstrate that the model performs exceptionally well, achieving an Adjusted R-squared value of 0.81, with various error indicators significantly surpassing those of the baseline model. This approach offers new insights for short-term price prediction of building materials and contributes to enhancing the economic benefits and management efficiency of construction projects.
Women Empowerment Through Globalization
Authors: Aprajita Km. , Singh Balbeer
Published: February 2025

Women empowerment, a central focus in the pursuit of gender equality, has been significantly influenced by globalization in recent decades. This abstract explores how globalization has facilitated the advancement of women's rights and opportunities across various sectors. Through increased access to education, employment, and technology, globalization has opened new avenues for women to participate in the global economy and public life. However, this process is not without challenges, as the benefits of globalization are often unevenly distributed, with marginalized groups facing additional barriers. The paper examines how globalization, while offering opportunities for economic independence and social mobility, also exposes women to new forms of exploitation and inequality. It highlights key case studies of women in developing regions, illustrating both the empowering and disempowering aspects of globalization. The study suggests that to achieve true women’s empowerment, it is crucial to address the systemic issues that persist globally, ensuring that the benefits of globalization are inclusive and equitable.
From Parts to Whole: A Systems Approach to Decoding Milk Fever
Authors: Ametaj Burim N.
Published: February 2025

Milk fever, or periparturient hypocalcemia, in dairy cows has traditionally been ad-dressed as an acute calcium deficiency, leading to interventions like supplementation and adjustments in dietary cation-anion balance. Although these measures have im-proved clinical outcomes, milk fever remains a widespread and economically signifi-cant issue for the dairy industry. Emerging findings demonstrate that a narrow empha-sis on blood calcium concentration overlooks the complex interactioins of immune, en-docrine, and metabolic pathways. Inflammatory mediators and bacterial endotoxins can compromise hormone-driven calcium regulation and induce compensatory calcium se-questration, thereby worsening both clinical and subclinical hypocalcemia. Recent in-sights from systems biology illustrate that milk fever arises from non-linear interactions among various physiological networks, rather than a single deficiency. Consequently, this review contends that a holistic strategy, integrating nutrition, immunology, micro-biology, genetics, and endocrinology, is vital for comprehensive management and prevention of milk fever. By embracing a multidisciplinary perspective, producers and veterinarians can develop more robust, customized solutions that not only safeguard animal well-being but also bolster profitability. Such an approach promises to meet the evolving demands of modern dairy operations by reducing disease prevalence and enhancing overall productivity. Tackling milk fever through integrated methods may unlock possibilities for improved herd health and sustainable dairy farming.
UAV Based Hyperspectral Imaging for PVY Detection: Machine Learning Insights
Authors: Nesar Siddat , Nugent Paul , Zidack Nina , Whitaker Bradley M
Published: February 2025

Potato is the third major crop in the world and more than 375 million metric tonnes of potatoes are produced globally on an annual basis. Potato Virus Y (PVY) poses a significant threat to the production of seed potatoes thus resulting in a substantial economic loss and a threat to food security. The traditional approach uses serological assays to detect PVY in potato leaves and PCR is used to detect PVY in tubers, however, the processes are sophisticated, labor-intensive, and time-consuming. We propose to use Unmanned Aerial Vehicles (UAVs) integrated with hyperspectral cameras included with a downwelling irradiance spectrometer, to detect the PVY virus in commercial growers’ fields. We have used a 400-1000 nm visible and near-infrared (Vis-NIR) hyperspectral camera. We have trained several machine learning and deep learning models with optimized hyperparameters on the curated dataset. The performance of the models are very promising, and we found the convolutional neural network (CNN) is reliable in identifying the healthy plants (precision 0.980), and the feedforward neural neural network (FNN) is reliable in identifying the PVY-infected plants (recall 0.988). The hyperspectral camera provides a wide spectrum and most of them are redundant in identifying PVY. According to our analysis, five spectra regions are impactful in identifying the PVY. Two of them are in the visible spectrum, two in the near-infrared spectrum, and one in the red-edge spectrum. This research shows that PVY detection is possible in the early growing season minimizing the economic and yield losses, and identifies the most relevant spectra carrying the signatures of PVY.
Preparation of TiO2/α-Fe2O3 Nanorod Heterostructures and Their Applications for Efficient Photodegradation of Methylene Blue
Authors: Jeong Yujeong , Lee Kyubeom , Kim Gaeun , Jang Eun-Hye , Choe Youngson , Kim Seok , Chung Sungwook
Published: February 2025

A facile solvo-hydrothermal method was developed to synthesize sub-100 nm diameter TiO2/α-Fe2O3@SiO2 nanorods (TiO2/HNRs@SiO2). Thermal annealing of TiO2/HNRs@SiO2 activated the photosensitizing crystalline TiO2 domains containing mixed anatase and rutile phases. Photocatalytic decomposition of methylene blue (MB) was performed using thermally the annealed TiO2/HNRs@SiO2 photocatalysts was successfully demonstrated with ~95% MB removal efficiency achieved under mild conditions of pH = ~7 and room temperature using ~150 min of solar irradiation. The enhanced removal efficiency was attributed to the rapid adsorption of MB onto the TiO2/HNRs@SiO2 surface via favorable electrostatic interactions and the synergistic integration of α-Fe2O3 and TiO2 into nanorod heterostructures with bandgaps of 1.99–2.03 eV, allowing them to absorb visible light for efficient photocatalytic degradation reactions. This study provides insights into designing photocatalysts with improved selectivity for sustainable water treatment and environmental remediation.
Seismic Images of Pressurized Sources and Fluid Migration Driving Uplift at Campi Flegrei Caldera During 2020–2024
Authors: Patanè Domenico , Barberi Graziella , Martino Claudio
Published: February 2025

After the 1982–1984 subsidence phase, ground uplift at Campi Flegrei Caldera resumed in 2005, while volcanic-tectonic earthquakes have steadily increased in frequency and intensity since 2020, with a significant intensification observed since 2023. This rise in seismic activity enabled us to conduct a new tomography using data collected from 2020 to June 2024. In this work, we used 4,161 local earthquakes (41,272 P-phases and 14,683 S-phases) processed with the tomoDDPS code, considering 388,166 P and 107,281 S differential times to improve earthquake locations and velocity models. Compared to previous tomographic studies, our 3D velocity models provide higher-resolution images of the central caldera's structure down to ~4 km depth. Additionally, we separately inverted datasets for 2020–2022 (moderate seismicity) and 2023–2024 (intense seismicity), identifying velocity variations (ranging from 5% to 10%) between these periods. These changes observed in 2023–2024 support the existence of two pressurized sources at different depths. One, located at 3–4 km depth beneath Pozzuoli and offshore, could represent either a magma intrusion enriched in supercritical fluids or an accumulation of pressurized, high-density fluids—a finding that aligns with recent ground deformation studies and modeled source depths. Furthermore, the upward migration of magmatic fluids interacting with the geothermal system generated a secondary, shallower pressurized source at approximately 2 km depth (beneath the Solfatara-Piscirelli area). Overall, these processes are responsible for the recent acceleration in uplift, increased seismicity and gases from the fumarolic field, and changes in crustal elastic properties through stress variations and fluid/gas migration.
Deep Learning Based 6D Pose Estimation of Unknown Objects
Authors: Hensel Stefan , Marinov Marin B. , Fischer Jeremy
Published: February 2025

6D pose estimation of unknown objects is an unsolved research problem in computer vision. This contribution proposes a novel method for estimating an object's pose using a monocular camera and an artificially created point cloud from the geometric object data. Point cloud generation and pose estimation are done with deep learning methods, combining several neural network-based approaches in one system. This paper describes the architecture and methods and compares and evaluates several ideas.
Multi Energy Static Modelling Approaches: A Critical Overview
Authors: Migliavacca Gianluigi
Published: February 2025

In Europe and elsewhere in the world, the current ambitious decarbonization targets push in the direction of a gradual decommissioning of all fossil-fuel-based dispatchable electrical generation and, at the same time, a gradual increase of the penetration of the Renewable Energy Sources (RES). Moreover, considerations tied to decarbonization as well as to security of supply, following the recent geo-political events, call for a gradual replacement of gas appliances with electricity-based ones. As RES generation is characterized by a variable generation pattern and as the electric carrier is characterized by scarce intrinsic flexibility (load and generation must coincide instant by instant and storage capabilities through electrochemical batteries as well as demand-side flexibility provision stay rather limited), it is quite natural to think of other energy carriers as possible service providers towards the electricity system. Gas networks are characterized by high compressibility (the so-called linepack phenomenon). Hydrogen stays very promising for providing not only daily but also seasonal storage. Heat networks are also intrinsically flexible because characterized by high thermal inertia and able to ensure comfort while varying water temperatures within a wide range of temperatures. All these carriers could, thus, provide storage services for the electricity system and this could allow, in turn, to increase the amount of RES penetration to be managed safely by the system, without incurring in risks of blackouts and without, on the other side, wasting RES generation peaks (or carrying out expensive reinforcements of electric transmission and distribution networks for hosting flows that would materialize only in a very limited number of hours in one year). All this calls for a new approach, both in electricity network dispatch simulations and in grid planning studies, which extends the simulation domain to other carriers (gas, heat, hydrogen…) so that a global optimal solution is sought for. This simulation approach, called multi-energy or multi-carrier, is gaining momentum in the last years and many approaches have been proposed, both in modelling the single carrier components and in joining them together for creating an overall model. The present paper aims at describing the most important of these approaches and comparing pros and cons of all of them. The style is that of a tutorial aimed at providing some guidance and a few bibliographic references to those who are interested to approach this issue in the next years.
Synthesis of Low-Defect Iron-Based Prussian Blue with Low Water Content for High-Stability Sodium-Ion Batteries
Authors: Li Zhaoyue , Zhong Shenglin , Zhou Bingcheng , Chen Denglian , Qiu Zehai , Zhang Rui , Zheng Ruijuan , Zhao Chenhao , Zhou Jiangcong
Published: February 2025

This study proposes an innovative two-step synthesis strategy to significantly enhance the performance of sodium-ion batteries by developing low-defect, low-water-content iron-based Prussian blue (PB) materials. Addressing the limitations of traditional co-precipitation methods—such as rapid reaction rates leading to excessive crystal defects and interstitial water content—the research team introduced a synergistic approach combining non-aqueous phase precursor synthesis and controlled water-concentration secondary crystallization. The process involves preparing a PB precursor in a glycerol system, followed by secondary crystallization in a water/ethanol mixed solvent with precisely regulated water content, achieving dual objectives of water-content reduction and crystal morphology optimization. Systematic characterization revealed that water concentration during secondary synthesis critically influences the materials crystal structure, morphological features, and water content. The optimized PB50-24 material exhibited a highly regular cubic morphology with a sodium content of 9.2% and a remarkably low interstitial water content of 2.1%. Electrochemical tests demonstrated outstanding performance: an initial charge-discharge capacity of 120 mAh g⁻¹ at 1C rate, retention of 105 mAh g⁻¹ after 100 cycles, and a high-rate capability of 86 mAh g⁻¹ at 10C, representing significant improvements in cycling stability and rate performance over conventional methods. This work not only establishes a cost-effective, scalable synthesis pathway for Prussian blue materials but also provides theoretical guidance for developing other metal-based Prussian blue analogs, offering substantial value for advancing the industrial application of sodium-ion batteries in next-generation energy storage systems.
A Survey on Edge Computing (Ec) Security Challenges: Classification, Threats, and Mitigation Strategies
Authors: Sheikh Abdul Manan , Islam Md. Rafiqul , Habaebi Mohamed Hadi , Zabidi Suriza Ahmad , Bin Najeeb Athaur Rahman , Kabani Adnan
Published: February 2025

Edge computing (EC) is a distributed computing approach to processing data at the network edge, either by the device or a local server, instead of centralized data centers or the cloud. EC proximity to the data source can provide faster insights, response time, and bandwidth utilization. However, the distributed architecture of EC, makes them vulnerable to data security breaches and diverse attack vectors. The edge paradigm has limited availability of resources like memory and battery power. Also, the heterogeneous nature of the hardware, diverse communication protocols, and difficulty in timely updating security patches exist. A significant number of researchers have presented countermeasures for the detection and mitigation of data security threats in an EC paradigm. However, an approach that differs from traditional data security and privacy-preserving mechanisms already used in cloud computing is required. Artificial Intelligence (AI) greatly improves EC security through advanced threat detection, automated responses, and optimized resource management. When combined with Physical Unclonable Functions (PUFs), AI further strengthens data security by leveraging PUFs’ unique and unclonable attributes alongside AI’s adaptive and efficient management features. This paper investigates various edge security strategies and cutting-edge solutions. It presents a comparison between existing strategies, highlighting their benefits and limitations. Additionally, the paper offers a detailed discussion of EC security threats, including their characteristics and the classification of different attack types. The paper also provides an overview of the security and privacy needs of the EC, detailing the technological methods employed to address threats. Its goal is to assist future researchers in pinpointing potential research opportunities.
Understanding the Unmet Needs of People Living with Type 2 Diabetes in Self-Managing Their Condition
Authors: Sarapis Katerina , Cao Yingting , Abou Chakra Melissa , Nunn Jack , Weber Mark , Albuquerque Carlyle , Chapman Maryse , Barr Richard , Gilfillan Christopher P. , Skouteris Helen , Oldenburg Brian , Brukner Peter , Beauchamp Alison , Moschonis George
Published: February 2025

Background/Objectives: Type 2 diabetes (T2D) prevalence is rising worldwide. Despite numerous efforts to tackle T2D, many initiatives fail due to poor engagement. Consumer involvement in healthcare design is increasingly recognized as an effective strategy for managing diabetes. Aim: To understand the unmet needs of people with T2D in self-managing their condition through the development of a Consumer Reference Group (CRG). Methods: The CRG was established using a standardized approach advised by Monash Partners, with specific terms of reference for consumer engagement. A face-to-face training workshop was conducted to develop consumers' skills in co-designing T2D interventions. Two focus groups were also conducted to identify consumers’ unmet needs and proposed solutions for effective T2D management. Inductive thematic analysis was used to extract themes. Results: Ten adults (3 females/7 males; 58-78 years old) with T2D participated. The thematic analysis highlighted four main themes: (1) misinformation; (2) limited guidance; (3) self-management; (4) prevention and screening. Consumers reported unmet needs in maintaining motivation, managing T2D alongside other commitments, and addressing mental health issues. They felt misinformed about self-management and lacked guidance from healthcare professionals and organizations, often relying on conflicting information. Those from culturally and linguistically diverse (CALD) backgrounds noted a lack of tailored dietary information. Proposed solutions included training primary care providers, reinforcing the role of diabetes nurse educators, providing targeted mental health support, and collaborating with CALD communities for culturally appropriate dietary information. Conclusions: These findings are crucial for informing consumer-driven intervention programs for T2D management, developed by and for people living with T2D.
The Unification of Intelligence Across Systems: A Noesiological Framework for Understanding Cognition, Technology, and Society
Authors: Moleka Pitshou
Published: February 2025

This article presents a groundbreaking exploration of Noesiology as a scientific discipline that unifies multiple forms of intelligence—human, artificial, and collective—into a coherent framework. Noesiology integrates concepts from cognitive science, artificial intelligence, evolutionary biology, and complex systems theory to understand how intelligence emerges and interacts across various systems. By drawing on theoretical insights and empirical evidence, this work introduces a novel model for studying intelligence across human, machine, and collective systems, which has profound implications for future research in artificial intelligence, human-machine collaboration, and social governance. Through the integration of interdisciplinary perspectives, the paper aims to lay the foundation for Noesiology as a central field of study in cognitive science and beyond.
Lean, Agile and Six Sigma: Efficiency and the Challenges of Today's World, Is It Time for Change?
Authors: Milewska Beata , Milewski Dariusz
Published: February 2025

The article presents the results of the authors' research on the resilience of management concepts such as Lean Management, Agile, SixSigma to phenomena in the business environment. The crises of recent years - the Covid-19 pandemic, the increase in energy prices, the war in Ukraine - have posed great challenges for companies, including those that have applied management concepts such as Lean Management. Just-In-Time may involve more frequent deliveries, which has an impact on fuel consumption costs. On the other hand, however, improving processes by eliminating waste leads to a reduction in the consumption of production resources, including energy. The relationship is therefore not clear-cut. The authors used three research methods. Firstly, they analysed the literature - scientific publications, studies and expert reports. Secondly, they analysed the financial results from recent years of Polish companies, multinationals and companies that apply Lean Management, Agile and Six Sigma strategies and their combination. Thirdly, they surveyed companies that apply the Lean Management concept. The research sought to establish how crises, especially energy crises, have affected the effectiveness of companies using these management strategies and to determine whether the solutions used so far are sufficient or whether they need to be modified or new methods or tools need to be developed. The results of this research show that the crises of recent years, if they even caused a deterioration in the financial situation, were short-lived, as companies were able to adapt to the new conditions. The situation of companies that have implemented Lean is no better than that of other companies - it is not apparent that any of the management concepts studied help more in increasing process efficiency. The best results come from companies that combine different concepts (Lean, Agile, SixSigma), as well as digital technologies Industry 4.0). The crises, although they have forced companies to take certain measures (e.g. the use of renewable energy sources), have (contrary to predictions) not resulted in radical changes, i.e. moving from one concept to another or abandoning Just-In-Time. The issue of energy efficiency is gaining more and more attention in companies and is included in management concepts, e.g. Lean management. Lean management has a positive effect on energy efficiency (indirect effect) through the elimination of waste, but in order to effectively increase energy efficiency, solutions must be applied that are aimed directly at increasing energy efficiency.
Adapting RIACT for Ice Storm Resilience of the Hydro-Québec Grid: A City-Level Approach
Authors: Rezvani Seyed MHS , Morissette Marc , Komljenovic Dragan , Falcão Silva Maria João , de Almeida Nuno Marques
Published: February 2025

This paper presents an adaptation and application of the Risk-Informed Asset-Centric (RIACT) process to analyze the resilience of a portion of Hydro-Québec's electric power grid against extreme ice storm risks, when supplying the densely populated Greater Montreal area, one of the power system’s major load centers. The key aspect consists in avoiding widespread or major blackouts and maintaining the functional performance of the area’s critical and essential services. The study identifies critical risks and asset exposures, analyzes potential solutions. The evaluation is aimed at deploying, on an urban grid, measures based on the PERA resilience stages: i) Preparation; ii) Endurance (Absorption); iii) Recovery; and iv) Adaptation. The proposed PERA plan aims to provide insights in implementing effective preventive measures while emphasizing the importance of monitoring, communication, and reporting throughout the process. By integrating resilience and asset management practices, this approach provides a simplified framework for managing risks associated with extreme weather events, ensuring the continuity of essential services.
Compressive Strength of Geopolymer Mortar Produced from Fire Brick and Ceramic Waste
Authors: Raoof Saad Mahmood , Hameed Anfal M.
Published: February 2025

The production of Ordinary Portland Cement (OPC) generates about 7% of global CO2 emissions. Geopolymer concrete could be a successful alternative to the ordinary Portland concrete. Construction and Demolishing Wastes (CDWs) have the potential of containing of alkaline activation binders due to their rich nature of aluminosilicate. This study investigates the possibility of producing geopolymer concrete using Fire brick (FB) and Ceramic Waste (CW) CDWs based materials as binders. This was achieved through evaluating the compressive strength of the produced geopolymer mortar. The main tested parameters were; the type of binders (FB and CW), the activator molarity (10, 12, and 15) M, the activator (Sodium Silicate to Sodium Hydroxide) ratio (1, 1.5, 2, 1 and 2.5), curing conditions (ambient and heating) and curing period (age) (7, 14 and 28) days. It was mainly found that both binders could be a successful potential to produce geopolymer concrete. The FB-based mortar showed higher compressive strength than the counterpart CW-based mortar for all considered parameters. Overall, it seems that the chemical composition of the binder was the main factor affecting the compressive strength of the resulted geopolymer.
Compression Loading Behaviour of A. squamosa Seeds for Sustainable Biodiesel Synthesis
Authors: Oloyede Christopher Tunji , Jekayinfa Simeon Olatayo , Enweremadu Christopher C. , Oluborode Iyanuoluwa
Published: February 2025

Due to the increasing demand for sustainable energy, non-edible oilseed crops are being explored as alternatives to traditional edible oils. The A. squamosa seeds are rich in oil content (24%/100g), and often discarded as agricultural waste. Determination of mechanical properties of the seeds under compression loading is significant for designing machinery for its handling and processing. Thus, the present study assessed the effect of loading speeds, LS, (5.0-25 mm/min) and moisture contents, ms, (8.0-32.5%, db) on rupture force and energy, bioyield force and energy, deformation, and hardness at the seed’s horizontal and vertical orientations using Testometric Universal Testing Machine. The results indicate that both LS, and mc significantly (p< 0.05) affect the mechanical properties of the seeds. Particularly, horizontal loading orientations consistently exhibited higher values for the selected compressive properties than vertical orientations, except for deformation at varying LS. The correlations between LS, mc, and the compressive parameters of the seed were mostly linear, at both orientations, with increasing mc from 8.0-32.5%, (db). High correlation coefficients (R²) were obtained for the relationship between the studied parameters, LS, and mc. The data obtained would provide crucial insights into optimizing oil extraction processes by enabling the design of efficient machinery that accommodates the unique characteristics of the seeds.
Histone Phosphorylation in DNA Damage Response
Authors: Gong Ping , Guo Zhaohui , Wang Shengping , Gao Shufeng , Cao Qinhong
Published: February 2025

DNA damage response (DDR) is crucial for maintaining genomic stability and preventing the accumulation of mutations that can lead to various diseases, including cancer. DDR is a complex cellular regulatory network that involves DNA damage sensing, signal transduction, repair, and cell cycle arrest. Modifications in histone phosphorylation play important roles in these processes, facilitating DNA repair factor recruitment, damage signal transduction, chromatin remodeling, and cell cycle regulation. The precise regulation of histone phosphorylation is critical for the effective repair of DNA damage, genomic integrity maintenance, and prevention of diseases such as cancer, where DNA repair mechanisms are often compromised. Thus, understanding histone phosphorylation in DDR provides insights into DDR mechanisms and offers potential therapeutic targets for diseases associated with genomic instability, including cancers.
Self-Sustaining Double Stage Circularity Through Utilization of Sunflower Agriculture’s Waste into Bio-Fertilizers: Commissioning of Full-Scale Facility
Authors: Zgureva-Filipova Denitza , Nikolova Viktoria , Krasteva Lyudmila , Filipov Kalin
Published: February 2025

The conception of circular economy is one of the crucial approaches that could accelerate the processes of achieving the sustainable development goals that challenged all industries and societies. This study aims to develop a full-scale technology for self-sustaining double stage circularity through utilization of sunflower agriculture’s waste into bio-fertilizers. The investigation is performed in Bulgaria as available sunflower hush ashes (SHA) are subjected to analyses regarding their applicability for bio-fertilizer production. The design of technology and full-scale equipment commissioning process are described. The conditions and results from adjustment tests are presented and based on them the optimal operating parameters are defined. The successful granulation of different samples of SHA at these conditions is performed as the final granular bio-fertilizers are characterized with content of 30 wt. % K2O and 5 % wt. P2O. The moisture of prepared granules is approx.. 5 wt. % and they pass the crushing tests at 2.5 kgf. The bio-toxicity of bio-fertilizer is also analyzed and the results show their applicability in agriculture. The proposed approach allows the initial sources of K2O and P2O from soil feeding the sunflowers to circulate in different industrial technologies and to enter again in the soil through bio-fertilizers.
Temporal-spatial Evolution and Driving Mechanism for Ecosystem Health Service Based on GD-MGWR-XGBOOT-SEM model: A Case Study in Guangxi Region
Authors: Wei Zhenfeng , Chen Dong , Huang Qunying , Chen Qifeng , Wei Chunxia
Published: February 2025

With the expansion of urbanization in China, ecological environment are becoming more and more prominent. To explore the driving factors and regulation ways of ecosystem health has become a hot issue in realizing regional sustainable development. This paper adopted the improved vigor-organization-resilience-service (VORS) model to diagnose the regional ecosystem health status from 2000 to 2020 in Guangxi and find out the main factors affecting the ecosystem health. Considering the influence factors (including vegetation, terrain, climate and human activities), the mechanism of driving factors on regional ecosystem health was analyzed by using geographic detector (GD), multiscale geographically weighted regression model (MGWR), XGBOOTS-SHAP model. The results found that the spatial distribution of ecosystem health was characterized by low values in the central region, and high values in the northern and eastern regions with higher elevations from 2000 to 2020. The spatial agglomeration evolution changed from agglomeration to dispersion, and the regional urbanization distribution and evolution were consistent. The interaction of driving factors on ecosystem health and vegetation was enhanced significantly, while the interaction of climate factors was relatively weak. And most of the impacts of human activities on ecological environment are negative. Vegetation factor has a dominant positive effect on ecosystem health, while human activity elements have a weak negative effect on ecosystem health. Meanwhile, climate factors are complex and changeable, and their impacts on ecosystem health are changeable, which leads to corresponding changes in other factors. This study provides scientific reference for the harmonious and sustainable development of man and nature in southern China.
Establishing Reference Data for Electromyographic Activity in Gait: Age and Gender Variations
Authors: Davoudi Mehrdad , Salami Firooz , Putz Cornelia , Wolf Sebastian I.
Published: February 2025

Instrumented gait analysis provides objective data for clinical assessment, with surface electromyography (EMG) serving as a key tool in identifying abnormal muscle activation. However, reliable reference data considering both age and gender remain limited. This study examines age- and gender-related differences in lower-limb EMG during gait in typically developing individuals using statistical parametric mapping (SPM). We also determine the minimum sample size required for robust clinical reference data. Our findings reveal significant differences in muscle activation patterns across age and gender. Children exhibited increased rectus femoris activation in initial swing and greater hamstring activation in mid-stance, whereas adults demonstrated higher semimembranosus activity at initial contact, increased soleus activation at push-off, and greater rectus femoris activity in late swing. Gender-based differences included higher tibialis anterior activation in females during terminal stance and increased vastus lateralis activity during swing, whereas males showed greater vastus lateralis and biceps femoris activation during terminal swing. Additionally, significant age-gender interaction effects were observed in the biceps femoris and semimembranosus, with gender-related differences becoming more pronounced in adulthood. Power analysis indicates that at least 47 participants, with a minimum of 12 per subgroup (male children, female children, male adults, female adults), are required to detect age-gender interactions reliably. Since our study included 97 subjects, our results are robust. We strongly recommend incorporating both age and gender in clinical norm bands to enhance the accuracy of gait assessments and improve clinical and research comparisons.
Impacts of Urban Heat Island and Future Climate on Urban Buildings Energy Use in a U.S. Midwest Neighborhood
Authors: Hashemi Farzad , Najafian Parisa , Salahi Negar , Ghiasi Sedigheh , Passe Ulrike
Published: February 2025

Urban Heat Island (UHI) effects and future climate change significantly impact building energy use but are often overlooked in widely used meteorological datasets like Typical Meteorological Years (TMYs). These datasets are collected at rural stations, such as airports, over long historical periods, failing to capture localized microclimates and climate shifts. This study integrates Urban Weather Generator (UWG)-based UHI simulation, future climate modeling, and neighborhood-scale data within an Urban Building Energy Modeling (UBEM) framework to assess residential energy demand in Des Moines, Iowa. Results show that UHI intensity rises from an annual average of 0.55 °C under current conditions to 0.60 °C by 2050 and 0.63 °C by 2080, with peak intensities in summer. UHI elevates cooling Energy Use Intensity (EUI) by 7% today, with projections indicating a sharp increase: 91% by 2050 and 154% by 2080. UHI further amplifies cooling demand by 2.3% and 6.2% in 2050 and 2080, respectively. Conversely, heating EUI declines by 20.0% by 2050 and 40.1% by 2080, with UHI slightly reducing heating demand. Insulation mitigates cooling loads but becomes less effective for heating demand over time. These findings underscore the need for climate-adaptive energy policies, prioritizing retrofits, and passive design to manage future cooling burdens.
Development of PP-Compound Recipes Using Genetic Algorithms and Analytical Models
Authors: Seifert Lukas , Leuchtenberger-Engel Lisa , Hopmann Christian
Published: February 2025

This study explores the development of polypropylene (PP) compound recipes using analytical models (AM) combined with genetic algorithms (GA). A talcum-filled PP compound, commonly utilised in injection moulding for packaging applications, served as a reference material, with shear viscosity, tensile modulus, and impact strength selected as target properties for replication. The AM were adapted and fitted to a dataset of 52 compounds, achieving high predictive accuracy for shear viscosity and tensile modulus, while impact strength proved more challenging due to its inherent variability. Three recipes were generated using GA under predefined material constraints. Recipe 1 aimed to replicate all three target properties, achieving a balanced compromise with maximum deviations of 13.14% for tensile modulus and 12.37% for impact strength while closely matching shear viscosity (maximum 9.8% deviation). Recipes 2 and 3, focused solely on matching shear viscosity and impact strength, demonstrated exceptional accuracy for shear viscosity, with Recipe 2 achieving near-perfect alignment (2.5% deviation). However, neither recipe approached the tensile modulus target due to material limitations. The findings demonstrate the effectiveness of combining AM with GA for designing alternative formulations, emphasising the importance of realistic targets and material constraints. This methodology is highly adaptable, allowing for the inclusion of additional optimisation criteria such as cost or sustainability. Future work will explore broader material sets and properties, extending the framework’s applicability to technical polymers and diverse industrial applications.
Investigation of Mechanical Properties and Microstructural Development in Cement-Based Materials Incorporating Zinc Oxide Nanoparticles
Authors: Al-Kasassbeh Salam , Assolie Amani Abdallah , El-Sayed SALAMA Ahmad hamed , Alobeidyeen Ala Alobeidyeen , Khliefat Ibrahim , Al-Zu'bi Mohammad Ibrahim Awad
Published: February 2025

This study investigates the impact of Zinc Oxide nanoparticles (ZnO NPs) on the mechanical properties and microstructural development of cement-based composites. Characterization using Scanning Electron Microscopy (SEM) and Dynamic Light Scattering (DLS) revealed uniformly distributed, spherical ZnO NPs with an average size of approximately 72 nm. X-ray Diffraction (XRD) and SEM analyses were performed on cement paste and mortar specimens with varying ZnO NP contents (1.0%, 1.5%, 2.0%, 2.5%, and 3.0% by weight). The results indicate that lower ZnO NP contents (1.0% and 1.5%) accelerate initial setting times, while higher contents (2.0%, 2.5%, and 3.0%) delay them due to the formation of clinohedrite (CaZn(SiO)₄•H₂O), which increases porosity and reduces matrix compaction. Calorimetric analysis showed decreased hydration heat with rising ZnO NP content, negatively affecting workability. This study highlights the dual effect of ZnO NPs in cement-based materials: low concentrations improve early-age mechanical performance, while higher amounts hinder hydration and microstructural integrity. These findings provide insights into optimizing ZnO NP dosage for the development of high-performance, nano-enhanced construction materials.
Generation of Murine Carcinoma Models with Functional Heterologous HER1 and/or HER2 Receptors for In Vivo Study of Specific Therapies
Authors: Fundora-Barrios Talia , Hechavarría-Bajuelo Amanda R. , García Lisset Chao , Gonzalez-Cruz Miguel Angel , Gonzalez-Suarez Najara , Bergado-Baez Gretchen , Sánchez-Ramírez Belinda
Published: February 2025

HER1 and HER2 (human epidermal growth factor receptors 1-2) are essential proteins for cellular physiology. Dysregulation of these receptors plays a key role in tumorigenesis. This turns both oncogenic receptors into targets for antitumor therapies, which currently include passive and active immunotherapy strategies, such as monoclonal antibodies and therapeutic vaccines. In this context, preclinical studies in immunocompetent mice provide insight into these therapies' complex tumor-host interaction and mechanisms of action. However, most therapeutic antibodies and vaccine candidates targeting HER1 and/or HER2 are not cross-reactive for their murine counterparts, which limits the characterization of their effector mechanisms in vivo. Murine models with induced, heterologous expression of human variants of HER1 and HER2 are, hence, needed and scarcely available to date. Herein, we generated and characterized nine tumor models derived from prostate (RM1), lung (Lewis variant 3LL-D122) and breast (4T1) carcinomas expressing HER1 and/or HER2, obtained by lentiviral transduction. Protein expression of the desired antigen and proper folding and insertion in the plasma membrane were confirmed. The functionality of these heterologous targets was demonstrated, in terms of appropriate ligand-induced activation and enhancement of tumor cells proliferation, suggesting that the receptors could engage into the signaling machinery of the modified tumor cells. In addition, incubation of cells from the generated tumor models with specific therapies decreased their viability targeting therapies, indicating the susceptibility of the modified cells to receptors’ inhibition, which advises the utility of the generated models in the characterization of targeted therapies, and their combinations. Overall, generated models are proposed as suitable tools for studying the regulatory roles of HER1 and/or HER2 in the biology of high-incidence carcinomas, as well as to gain deeper insights into the connection of therapies targeting these receptors with the immune system.
Icy Balls That May Be A New Kind of Star Connect the Maths and Quanta of this Universe to the Dark Universe
Authors: Bartlett Rodney
Published: February 2025

This article began when icy balls that may be a new kind of star were observed in space. They seem to have the contradictory characteristic of being cold enough to have abundant ice, but also possess infrared emission like a hot star. The contradiction could be resolved using a mathematics called vector-tensor-scalar geometry which is based on a paper published by Albert Einstein. This geometry presents new ways of looking at formation of planets, stars, and black holes as well as the Higgs boson/field and every other subatomic particle. A Cosmological Entanglement that’s based on the Holographic Principle and is not dependent on temperatures near absolute zero or any experiments in laboratories is introduced. Spacetime-exploring “topological propulsion” and totally emission-free “topological manufacturing / transportation” are proposed, as is the alternative of describing certain phenomena with either advanced / retarded waves or Complex (Real+Imaginary) numbers. Chaos theory states there is hidden order in randomness and apparent disorder. This has implications for the way Brownian motion and quantum mechanics are viewed - possibly giving rise to the concept of quantum certainty or the principle of determinacy. Finally, the article looks at a) dark matter and dark energy as intimately related processes divorced from the concept of universal expansion (or contraction), b) space-time travel and planet Mercury’s precession in the light of the Riemann hypothesis, and c) coding waves.
A Novel Strong Pairing Mechanism in High-TC Cuprates
Authors: Buot Felix A.
Published: February 2025

In high-TC cuprates, the presence of parallel superconducting stripes or rivers of charge is well established experimentally. These also act as domain walls for the antiferromagnetic order. To readily explain the pattern of superconducting stripes near and at optimal doping levels, we propose
a novel strong pairing mechanism, devoid of Coulomb repulsion, for high-TC cuprates. This new mechanism is based on the quantum entanglement and connement or degree of entanglement. Some quantum entanglement experiments with antiferromagnetic-chain links directly support our proposed entanglement pairing mechanism. Depending on doping levels, the triplet and singlet pairing can either exist independently, as a "lattice" of Bell basis states with unpolarized rivers of charge for underdoped regime, or as a mixed triplet-singlet or interacting Bell basis states with spatially alternating spin-polarized superconducting stripes of charge for overdoped range. Several spin resolved (SR)-ARPES experiments on the complex spin texture of cuprates are qualitatively interpreted in the light of our novel "lattice" of coupled triplet-singlet pairing leading to polarized rivers of charge in line with experimentally-found doping-level dependence. The resulting simple intuitive model suggests that entanglement is indeed a new strong pairing mechanism, devoid of Coulomb repulsion, leading to high-TC superconductivity and strange metal behavior above TC. Moreover, our model can possibly accommodate the Meissner effect, probably as superconducting plaquettes formed by "spokes" of antiferromagnetic-chain entanglement link.
Extensive Unreported Non-Plantation Oil Palm in Africa
Authors: Descals Adrià , Sheil Douglas , Wich Serge , Ozigis Mohammed , Meijaard Erik
Published: February 2025

The extent of oil palm in non-plantation settings in Africa remains unknown despite its considerable socio-economic, nutritional, and cultural importance. Based on a sampling approach and sub-meter satellite data, we estimated 6.53 ± 0.99 Mha of non-plantation oil palm, unreported in official statistics, but widespread near West and Central African villages. These results indicate a capacity to meet local nutritional needs that were previously unrecognized by official statistics. Our findings are therefore of significance for policies and practices related to African food security.