bluuebunny/crossref_metadata_2025 huggingface dataset:
Curative Properties of Kencur (Kaempferia galanga L.) Extract on Mice (Mus musculus) Kidney Histopathology Exposed to Cigarette Smoke
Authors: Arianto Intan Diah Safitri , Lastoaji Firman , Sudjarwo Sri Agus , Valentinus Thomas Widiyatno , Hestiana Eka Pramyrtha , Hamid Iwan Sahrial , Herupradoto Eduardus Bimo Aksono , Lovela Aprinda Ratna
Published: January 2025

The aim of this research was to investigate the therapeutic effects of Kencur (Kaempferia galanga L.) extract on kidney histopathological damage in male mice exposed to cigarette smoke. Twenty 8-week-old male mice were randomly divided into five treatment groups (n=5). The negative control group (C-) consisted of mice not given kencur extract or exposed to cigarette smoke, while the positive control group (C+) comprised mice exposed to cigarette smoke without kencur extract. Treatment groups included Treatment 1 (T1) administered 150 mg/kg BW of kencur extract, Treatment 2 (T2) administered 300 mg/kg BW, and Treatment 3 (T3) administered 600 mg/kg BW. Mice were exposed to cigarette smoke for 14 days. The data were analyzed using the Kruskal-Wallis test to evaluate overall differences among the treatment groups. Where significant differences were found (p<0.05), further pairwise comparisons were conducted using the Mann-Whitney test, confirming statistically significant differences between specific treatment groups.  Treatment 3 (T3) was found to be the most effective in reducing histopathological damage in the kidneys of male mice. This study demonstrates that kencur extract effectively reduces histopathological damage in the kidneys of mice exposed to cigarette smoke, highlighting its potential as a protective agent against smoke-induced tissue injury.
Ovariohysterectomy in Cat as An Alternative Handling of Fetus Mummification Cases
Authors: Ercha Aulia Putri Cindy , Safitri Erma , Syafitri Winda
Published: January 2025

Fetal mummification is a rare and challenging condition in cats that requires immediate intervention to mitigate potential risks to the mother and future pregnancies. This case study presents the diagnosis, treatment, and outcomes of Pawpaw, a cat diagnosed with fetal mummification. Ovariohysterectomy was performed as an alternative treatment method to address the critical condition of the cat. The diagnosis was established based on various factors, including indications, anamnesis, clinical symptoms, clinical examination, clinical findings, and investigative results. Diagnostic confirmation was achieved through blood haematology tests and ultrasound examinations. The therapeutic approach consisted of administering a combination of normal saline fluid therapy, glycerin, ondansetron, ceftriaxone, intramox, doxycycline, acetylcysteine, sakatonic liver, vitamins, ventolin, Tripura, meloxicam, impacting, and furosemide. Anesthesia during the ovariohysterectomy procedure involved the use of atropine sulfate, xylazine, and ketamine. Despite the extensive medical intervention, the cat, Bimbim, succumbed to its critical condition during the surgery. This case study highlights the importance of early diagnosis and prompt intervention in cases of feline fetal mummification. Ovariohysterectomy proved to be a viable alternative treatment option, although the critical condition of the cat posed significant challenges to its successful outcome. Further research and enhanced understanding of fetal mummification in cats are essential to improve the management and prognosis of this condition.
Elimination of Large Bladder Stone-Obstructing Pelvic Canal in African Spurred Tortoise (Centrochelys sulcata) with Per-Cloacal Bladder Stone Removal Method without Utilizing an Endoscope
Authors: Rickyawan, drh., M.Sc. Nofan , Vivi Oktavia  , Dodik Prasetyo
Published: January 2025

Bladder stone formation in reptiles arises from the accumulation and subsequent solidification of uric acid in the urinary bladder. The bladder stones vary in size and can migrate from the bladder to the pelvic canal. In cases where larger bladder stones enter the pelvic canal, they pose a risk of obstructing the digestive and urinary tracts of the tortoise. This study discusses managing bladder stone elimination in sulcata tortoises (Centrochelys sulcata) located in the pelvic canal without utilizing an endoscope. In 2023, four sulcata tortoises were presented at the Teaching Veterinary Hospital Universitas Brawijaya with diagnoses of large bladder stone-blocking pelvic canals that had been causing digestive and urinary tract obstruction. All of the tortoises have similar clinical signs, such as lethargy, anorexia, inability to defecate, and anuria. Physical examinations and radiography revealed the presence of bladder stones in the pelvic canal, exceeding the dimensions of the pelvic outlet and hindering passage through the cloaca. Treatment involved per-cloacal bladder stone removal. This procedure begins by anesthetizing the sulcata tortoise using ketamine and medetomidine combination, followed by fragmentation and extraction of the bladder stones from the pelvic canal through the cloaca. All procedures were performed without utilizing an endoscope. The success of the treatment was evidenced by radiographic examination, confirming the absence of bladder stones in the pelvic canal, and the recovery of normal defecation, urination, appetite, and activity levels.
Prevalence and Potential Risk Factors of Rift Valley Fever in Sheep in East Nile Locality-Khartoum State, Sudan
Authors: El nour Manal Ali , Ibrahim Hano Suleiman Adam , Fangama M. I. M. , Abdalla M. A.
Published: January 2025

Rift Valley Fever is an acute, mosquito-borne viral disease that causes a significant global threat to humans and livestock. This disease holds great importance in terms of its impact on agriculture and public health in African and Middle Eastern countries. RVF primarily affects domestic and wild ruminants such as cattle, sheep, goats, and camels. RVF closely linked to heavy rainfall, floods, and the presence of mosquito species. Recently, the RVF has become endemic in African continent including Sudan. A Cross-section study was conducted during June 2022 to June 2024. A total of 150 of samples were examined using competitive EALISA test to demonstrate the sera-prevalence of RVFIgG immunoglobulins in sheep’s serum, in eastern Nile locality - Khartoum State, Sudan. RVFV seropositivity was recorded in 3 out of 150 samples. In addition, the overall prevalence was found 0.02%. Surprisingly, body condition was the only associated risk factor with Rift Valley Fever in the Study area using Univariate analysis (P-value =.009) and (X2: 6.921). Other factors Such as animals site, Age, Sex, Breed, Presence of mosquito, grassing system, herd size, mortality in kids, and abortion in sheep were not found significantly associated with Rift Valley Fever. Finally, Rift Valley Fever needs an epidemiological study to understand this disease incidence, prevalence and the effective control methods and the best prevention measures that should be implemented including one heath approach.
Enhancing the Yield of Lentils (Lens culinaris) in Greater Noida (U.P.) by Improving Irrigation Frequency, Nutrient Management Techniques, and Soil Conservation Techniques (Mulching) at Greater Noida (U.P.), India
Authors: Tripathi Varun , Chisi Nyaken
Published: January 2025

The study aimed to Optimizing Lentil (Lens culinaris) Yield Through Irrigation Frequency at the Experimental Fields of Sharda University, Greater Noida, Uttar Pradesh, during the rabi season of 2023-2024. A split-plot Design with nine Treatments and three replications was employed, which includes T1: M1S1; T2: M1S2; T3: M1S3; T4: M2S1; T5: M2S2; T6: M2S3; T7: M3S1; T8: M3S2; T9: M3S3. Measurements were taken for plant parameters, yield analyses and soil analyses. Results indicated that integration of second irrigation and 50% Organic manure+ 50% R.D.F. (T6) demonstrated significantly higher growth and productivity in lentil compared to other treatments. This combination led to increased plant height, dry matter accumulation and higher yields, including the number of pods and grains per plant. Moreover, soil analyses revealed improvements in soil pH, organic carbon, and nutrient levels with this integrated approach. Additionally, effective crop management practices, such as timely irrigation, weed management, and disease control, contributed to the overall success of lentil cultivation. These findings underscore the significance of optimizations in integrating fertilization strategies, incorporating both organic and inorganic amendments along with rhizobium culture, for maximizing lentil productivity while ensuring soil health and sustainability.
Design and Optimization of Combustion Chamber for Gas Turbine Engine
Authors: Kumar Jha Nandan , Malve Bhakti Sachin , Gawde Rohit Vinod , Chand Dharmahinder Singh , Malhi Gurmail Singh
Published: January 2025

Gas turbine engines are widely used in aviation, power generation, and marine propulsion due to their efficiency and reliability. The combustion chamber, crucial to engine performance, involves various components such as fuel injection, ignition, and cooling systems. This study presents the design and optimization of a cost-effective combustion chamber model aimed at improving efficiency and power-to-fuel ratio. Numerical simulations were conducted to analyze the swirler design, enhancing combustion efficiency, air-fuel mixing, and emission reduction. The research compares different combustion chamber types based on cost, availability, and fabrication time. The fabrication process and materials used, along with safety and environmental measures, are discussed. Future work will focus on experimental validation and further development of low-emission designs to address challenges in fuel consumption and emissions.
Valorization of Spend Coffee Grounds Using Koh and Concentrated Leachate as Activating Agents in Slow Pyrolysis at 600ºC – a Comparative Analysis of Char Properties
Authors: Almeida Ronei de , Vianna Marcelo Mendes , Lanero Francesco , Lavagnolo Maria Cristina , Sgarbossa Paolo , Bertani Roberta , Quintaes Bianca Ramalho , Bila Daniele Maia , Campos Juacyara Carbonelli
Published: January 2025

The coffee industry and landfill leachate treatment generate residual waste streams, known as spent coffee grounds (SCG) and landfill leachate membrane concentrate (LLMC). Current practices for managing these residues, including open burning, incineration, and landfilling as a final disposal method, represent a waste of resources and pose a challenge to sustainability. Due to the high pollution potential of solid waste SCG and LLMC, cost-effective management solutions are urgently needed. The present research investigates the slow pyrolysis of SCG using potassium hydroxide (KOH) (weight ratio of 1:1) and LLMC residue (weight ratio of 1:1) as activating agents. The high content of alkali and alkaline earth metals in LLMC could promote the activation of the resulting char and improve the quality of the carbon-based material produced in pyrolysis. The use of LLMC as an activating agent could be a sustainable alternative for valorizing SCG and landfill wastes, potentially replacing ingredients such as steam, CO2, and chemical additives used on an industrial scale. The SCG had a low specific surface area (4.5 m2 g-1), contrasting with the notable surface areas observed in both activated chars. In particular, the KOH-activated char exhibited a higher surface area than the LLMC-activated char, measuring 1,960 m2 g-1 compared to 1,138 m2 g-1 – a difference of about 72%. On the other hand, the combustion enthalpy of the LLMC-activated material was estimated at 22.04 MJ kg-1. The combustion enthalpy of LLMC-activated char was about 21.7% and 19.8% higher than that of SCG and KOH-activated chars, which had values of 18.11 and 18.40 MJ kg-1, respectively. Our findings confirm that pyrolysis of SCG with KOH produces a microporous material with a high specific surface area. In contrast, the resulting LLMC-activated char demonstrates a higher value of combustion enthalpy. This work showed that both activated chars had superior energetic and morphological properties compared to the non-activated char made from SCG biomass. Among the activating agents, KOH led to better performance in terms of char yield and morphological properties. Meanwhile, utilizing LLMC residue as an activating agent highlights its potential for converting landfill waste into high-value material.
Interpretation of Gravity by Entropy
Authors: Fujino Seiji
Published: January 2025

In this paper, we introduce generalized entropy, acceleration of its entropy and its partial entropy. We assume that generalized entropy can represent as a second-order polynomial by applying the idea of logistics function to its entropy. Besides, we show that the inverse of partial entropy can represent Newton's gravity, which is an inverse square law. By applying these concepts, we attempt to explain that 1) gravity becomes constant within small distance with some conditions. It is possible that gravity has 5-states within small enough distance. There exists possible anti-force, which is the opposite of Newton's gravity among 5-states. Furthermore, within small distance, we show the possibility that gravitational potential and Coulomb potential can be treated in the same way, that 2) the rotation speed of the galaxy does not depend on its radius if the radius is within the size level of the universe. (The galaxy rotation curve problem), and that 3) gravitational acceleration toward the center may change at long distance compared to Newton's gravity. We show that it becomes an expansion of Newton's gravity, and that the possibility of the existence of some constants which controls gravity and the speed of galaxies, and that gravity may relate on entropy. It also describes the relationship between Yukawa-type potential and generalized negative partial entropy. Using equations proposed in this paper, it attempts to propose 11-types of forces (accelerations) including $g$ and compare the ratios of size of the fundamental 4-forces in nature (strong force, electromagnetic force, weak force and gravity). Furthermore, it suggests that there may exists new forces, and that gravitational constant $G$ can fluctuate if entropy changes. Thermodynamics, quantum, gravity, electromagnetic and ecology may be unified through entropy.
Assembly Theory - Formalizing Assembly Spaces and Discovering Patterns and Bounds
Authors: Bieniawski Wawrzyniec , Masierak Piotr , Tomski Andrzej , Łukaszyk Szymon
Published: January 2025

Assembly theory bridges the gap between evolutionary biology and physics by providing a framework to quantify the generation and selection of novelty in biological systems. We formalize the assembly space as an acyclic digraph of strings with 2-in-regular assembly steps vertices and provide a novel definition of the assembly index. In particular, we show that the upper bound of the assembly index depends quantitatively on the number b of unit-length strings, and the longest length N of a string that has the assembly index of N − k is given by N(N−1) = b2 + b + 1 and by N(N−k) = b2 + b + 2k for 2 ≤ k ≤ 9. We also provide particular forms of such maximum assembly index strings. For k = 1, such odd-length strings are nearly balanced, and there are four such different strings if b = 2 and seventy-two if b = 3. We also show that each k copies of an n-plet contained in a string decrease its assembly index at least by k(n − 1) − a, where a is the assembly index of this n-plet. We show that the minimum assembly depth satisfies d(N) min = ⌈log2(N)⌉, for all b, and is the assembly depth of a maximum assembly index string. We also provide the general formula for the lengths of the minimum assembly index strings having only one independent assembly step in their assembly spaces. Since these results are also valid for b = 1, assembly theory subsumes information theory.
Introducing the Effective Gravitational Constant 4πε0G
Authors: Christodoulou Dimitris M. , Kazanas Demosthenes
Published: January 2025

The gravitational and electrostatic fields are both conservative fields, thus their forces exhibit similar forms. But there are also differences best seen in Gauss's law, where the sources of these fields are leveraged by the vacuum differently: the source of gravity is enhanced by a modest factor of $4\pi$, whereas the Coulomb source is strongly amplified by a factor of $\sim\!\! 10^{11}$. Discontented by such vexing disparities, we cast Newton's gravitational law and Coulomb's law in the same form that allows for categorical comparisons. The conformity of these force laws suggests that the effective universal gravitational constant is $4\pi\varepsilon_0 G$, where $\varepsilon_0$ is the vacuum permittivity and $G$ is the Newtonian gravitational constant. Furthermore, there is no need for adopting an equivalence principle. The numerical value of $4\pi\varepsilon_0 G$ appears also in the deep limit of MOND and of varying-$G$ gravity, where it specifies (apart from units) the magnitude of the mysterious constant $\mathcal{A}_0$, the only constant in such theories besides their gravitationally interacting masses. The same methodology also offers self-consistent definitions and insightful clarifications concerning dimensionless constants in general and some particular fundamental constants of cosmology and particle physics.
Deep Learning-Based Gain Estimation for Multi-User Software Defined Radios in Aircraft Communications
Authors: Gajjar Viraj K. , Kosbar Kurt L.
Published: January 2025

It may be helpful to integrate multiple aircraft communication and navigation functions into a single software defined radio (SDR) platform. To transmit these multiple signals, the SDR would first sum the baseband version of the signals. This outgoing composite signal would be passed through a digital-to-analog converter (DAC), before being up-converted and passed through a radio frequency (RF) amplifier. To prevent non-linear distortion in the RF amplifier, it is important to know the peak voltage of the composite. While this is reasonably straightforward when a single modulation is used, it is more challenging when working with composite signals. This paper describes a machine learning solution to this problem. We demonstrate that a generalized gamma distribution (GGD) is a good fit for the distribution of the instantaneous voltage of the composite waveform. A deep neural network was trained to estimate the GGD parameters, based on the parameters of the modulators. This allows the SDR to accurately estimate the peak of the composite voltage, and set the gain of the DAC and RF amplifier, without having to generate or directly observe the composite signal.
Origin of the Gravitational Force
Authors: Liu Shangqing
Published: January 2025

The gravitational force is extremely important because it dominates the formation and evolution of the universe. However, its physical origin and intrinsic nature have not been clearly comprehended for a long time. Certain observed phenomena, along with the newly discovered by the Hubble and James Webb telescopes, cannot be explained well by current theories. Furthermore, general relativity and quantum mechanics, which are mainstream theories explaining the gravitational force, are incompatible. This situation strongly points to the need for a better or novel theory of the gravitational force. Here, based on classical space-time view, a different but solid understanding of the gravitational force is introduced. The author has realized that the gravitational force originates from none other than the electric force and is the synthetic electric force produced by a large number of electric charges. Generally speaking, in most objects, there are a large number of free and potentially induced electric charges. Due to various reasons, including unavoidable fluctuations of microscopic particles, non-uniform charge distribution in the object is normal. Earth is typically such an example. The non-uniform charge distribution within an object will almost certainly turn that object into an electric dipole. Thus, almost any object can be regarded as an electric dipole, resulting in any two objects attracting each other. This is the true origin of the gravitational force. This understanding can solve or explain confusing problems or phenomena simply and effectively, such as dark matter, dark energy, flat galaxy and filamentary nebula. This understanding also naturally unifies the gravitational and electromagnetic forces.
Why Does Earth Rotate?
Authors: Rueda José A. , Sánchez Miguel A. , Ramirez Sergio , Rueda B. Sandra
Published: January 2025

The equation of time (EoT) tracks daily deviations in length between the solar day and the mean day. Since the length of the mean day remains constant throughout the year, the EoT must mirror daily fluctuations in the length of the solar day. Furthermore, if the Sun meridian declination (SMD) is dynamically linked to Earth’s rotational speed (ERS) the EoT must obey to oscillations in ERS. This document examines the position, velocity, acceleration, and net drive of the mean-time Sun within a solar sundial noon analemma considering both its vertical and horizontal dimensions: the SMD and the EoT. Evidence supports that ERS decreases monotonically along two trans-equinoctial analemmatic phases in which the net drives of the EoT and SMD become coordi-nated (either both accelerating or both decelerating) within the SMD interval of −16 to +19 arcdeg, centered at +3. Conversely, ERS increases monotonically along two trans-solstitial analemmatic phases in which the net drives of the EoT and SMD become opposed, outside the specified interval of SMD. The ERS reaches its minima and maxima at the troughs and crests of the EoT; whereas it varies respectively.
Vitamin D, Calcium to Magnesium, and the Gut Microbiome
Authors: Chambers Patrick
Published: January 2025

The gut microbiome has been the subject of increasing interest as integral to our health. Few realize that the enormous benefits of vitamin D (VD) and magnesium (Mg) are highly dependent on a healthy gut microbiome. Short chain fatty acids, especially butyrate, reflect not only a healthy gut microbiome but also VD status. Suboptimal VD, Mg, or butyrate translates to some degree of gut dysbiosis and vice versa. Mg dependent secondary bile acids, indoles, and tryptophan, all microbial metabolites and longevity agents, are also discussed. Mg is indispensable to not only the synthesis of the active form of VD but also that of 7-dehydrocholesterol (7-DHC) from acetate. 7-DHC is the substrate for solar conversion to D3. The steadily increasing Ca:Mg in the Western diet and its troubling impact on parathormone (PTH) is discussed. Gut dysbiosis further complicates this. A model addressing the seemingly contradictory reports regarding calcium, magnesium, and VD efficacy among disparate groups is presented. Biochemical and physiologic interlinkages are legion and most remain hidden. This limited mini review exposes insight into the tight linkage between 25(OH)D3 and Ca:Mg, facilitated by the gut microbiome. A model incorporating the physiologically discordant but reinforcing effects on this linkage based on genes, culture, socioeconomic status, and diet is proposed.
Association Between Pets and Mental Health in University Students with Borderline Personality Disorder Symptoms
Authors: Khattiya Kanyarat , Wongpakaran Tinakon , Wongpakaran Nahathai
Published: January 2025

Approximately 9.7% of university students exhibit symptoms of borderline personality disorder (BPD), characterized by poor self-identity, low self-esteem, and emotional dysregulation. Caring for a pet may enhance self-esteem and provide a sense of purpose, potentially benefiting those with BPD. This study aimed to explore the relationship between pet ownership and mental health in 346 university students with BPD symp-toms. Participants were divided into pet owners and non-pet owners, and self-report questionnaires assessed their mental health. Results showed no significant differences in negative mental health outcomes between the two groups. However, pet owners demonstrated higher levels of inner strength, including wisdom (p = 0.034) and precepts (p = 0.011). Notably, dog owners reported lower anxiety (p = 0.008), depression (p = 0.036), and somatization (p = 0.011), while scoring higher in self-esteem (p = 0.025) and various measures of mental well-being. These findings suggest that pet ownership, especially of dogs, may positively impact mental health among university students with BPD symptoms. Future research should explore intervention-based approaches to validate these results.
Stopping Power of Iron for Protons, Theoretical Calculations from Very Low to High Energies
Authors: Peralta Jesica , Mendez Alejandra , Mitnik Darío , Montanari Claudia
Published: January 2025

The energy loss in iron is valuable knowledge due to its extended use, technological applications and open topics in fundamental physics. The electronic structure of solid Fe is challenging, being the first of the groups of transition metals with some of the d-electrons promoted to the conduction band while others remain bound. The low energy description, the deviation from velocity proportionality at low impact energies, and the contribution of the loosely bound d-electrons to the energy loss are active featured fields about the stopping in Fe. Very recent TDDFT calculations have been compared with the first stopping measurements in steel, showing surprisingly good agreement. In the present work, we applied a recent model based on the momentum distribution function of the d-electrons to the case of Fe. The comparison with other models is discussed, as well as with the experimental data. We also highlight discrepancies among data sets regarding the stopping maximum and the need for new experimental efforts.
Recent Advances in Biofilm Cycle by Bibliography Analysis
Authors: Ding Yuanzhao
Published: January 2025

Biofilms are communities of microorganisms attached to surfaces, embedded within self-produced extracellular polymeric substances (EPS). They play a dual role in human and environmental contexts. Beneficial biofilms are widely utilized in bioreactors for applications such as energy production and pollutant immobilization, while harmful biofilms are associated with severe infections, including lung infections and urinary tract infections. Understanding the biofilm cycle, encompassing attachment, maturation, and dispersal phases, is critical for optimizing beneficial biofilms and mitigating harmful ones. For example, identifying the optimal late exponential or early maturation phases can enhance biofilm utility, while predicting dispersal timing can inform strategies for disrupting harmful biofilms, safeguarding human health. This study employs a bibliometric approach to analyze the biofilm cycle, extracting core keywords, leading organizations, and active countries/regions. By synthesizing data from the Web of Science, this analysis highlights key trends and knowledge gaps in the field, providing a comprehensive overview of biofilm cycle dynamics. The study also identifies future opportunities for integrating big data and machine learning, which have the potential to revolutionize biofilm research. These technologies could enable precise predictions of biofilm behavior, fostering advancements in healthcare, environmental protection, and industrial processes, and ensuring more effective biofilm management strategies.
Towards Green Transportation: Predictive Modeling of Intersection Congestion Using Machine Learning for Sustainable Urban Traffic Management
Authors: Muktar Bappa , Fono Vincent , Nouboukpo Adama
Published: January 2025

One of the main consequences of urban pollution is intersection congestion, which occurs due to frequent vehicle stops. These interruptions lead to increased fuel consumption and greenhouse gas emissions (CO₂), along with other pollutants such as nitrogen oxides (NOx) and fine particulates. These pollutants can adversely affect the respiratory, cardiac, and neurological health of city residents. To address the growing demand for smart and sustainable transportation systems in large cities, predicting intersection congestion using artificial intelligence offers a promising solution. In this study, we present a predictive modeling approach to classify congestion levels at intersections controlled by traffic lights. Using the CN+ dataset collected in Bremen, Germany, our methodology incorporates vehicle and environmental features to predict congestion levels, optimize traffic flow, and reduce pollutant emissions. We employ data preprocessing, feature engineering, and machine learning techniques, including an innovative feature selection method called Dual Importance Intersection Feature Selection (DIFS), which combines Random Forest (RF) and Chi-square analysis. We tested various classifiers, including RF, XGBoost, LightGBM, CatBoost, and Artificial Neural Network (ANN), utilizing SMOTE balancing to address the class imbalance. Performance metrics such as precision, recall, F1 score, overall accuracy, and Quadratic Weighted Kappa (QWK) demonstrate promising results, with F1 and QWK scores reaching 100%. This makes our approach a robust tool for managing traffic sustainably and efficiently.
Dynamic Selection Debiasing Recommendations Based On Sentiment Analysis
Authors: Zhang Fan , Luo Wenjie , Yang Xiudan
Published: January 2025

Debiased recommendation has received significant attention from the academic community in recent years. Currently, our research on selection bias indicates that the existing literature ignores the effect of sentiment factors on selection bias. In the recommendation task, the existence of sentiment bias due to sentiment factors may lead to the recommendation of low-quality products to important users and unfair recommendation to niche(products designed for specific target markets and purposes) items. Eliminating sentiment bias and improving the quality of recommendations to important users can help balance research on selection bias. Sentiment bias is hidden in user ratings and reviews. Consequently, an effective approach to mitigate this bias is to analyze user ratings and comments in order to ascertain their genuine opinions. We have developed a sentiment analysis module with the objective of eliminating the bias between reviews and ratings, providing accurate sentiment ratings, mining users' real sentiment opinions, and eliminating the sentiment bias. Currently, a combinatorial function is constructed that performs the corresponding computations based on three different scenarios. Furthermore, the concept of dynamic debiasing is introduced, where the modeling time is dynamic. A selection debiasing recommendation method based on time-dynamic scenarios is also proposed. This paper demonstrates how the three aforementioned approaches can effectively mitigate selection bias by addressing data sparsity (sentiment analysis), optimizing data at the level of the data set (combinatorial functions), and considering dynamic scenarios and applying inverse propensity weighting methods (time-dynamic modeling). Our experiments on several real datasets demonstrate that our model can effectively improve the performance of recommendations.
How Consumer Feedback Shapes Supply Chain Adaptability: A Marketing Perspective
Authors: Bennett Lydia
Published: January 2025

This research explores the significant role of consumer feedback in shaping the adaptability of supply chains from a marketing perspective. With the growing emphasis on consumer-centric strategies, companies have increasingly recognized the value of feedback in driving operational and strategic decisions within the supply chain. This study examines how consumer insights influence various stages of the supply chain, including inventory management, product development, logistics, and distribution, and how organizations respond to these insights to enhance operational efficiency and customer satisfaction. The findings reveal that consumer feedback is a critical driver of innovation, with businesses using it to inform demand forecasting, product modifications, and real-time adjustments in production schedules. Furthermore, consumer feedback has been pivotal in fostering greater collaboration across supply chain partners, improving transparency, and encouraging the adoption of sustainable practices. Despite these benefits, the study also identifies challenges, such as the overwhelming volume of feedback, variations in its quality, and delays in implementing feedback-driven changes. However, the research suggests that companies that successfully integrate consumer feedback into their supply chain operations are more agile, responsive, and resilient, which ultimately leads to improved customer loyalty and market competitiveness. This research highlights the growing importance of consumer feedback in supply chain management and provides insights into how organizations can better leverage consumer insights to adapt and thrive in an increasingly dynamic and competitive market environment.
The Acute Effects of Fast Food Versus Mediterranean Meal on Autonomic Nervous System, Lung Function, and Airway Inflammation: A Randomized Crossover Trial
Authors: Silva Diana , Mendes Francisca Castro , Stanzani Vânia , Moreira Rita , Pinto Mariana , Beltrão Marília , Sokhatska Oksana , Severo Milton , Padrão Patrícia , Garcia-Larsen Vanessa , Delgado Luís , Moreira André , Moreira Pedro
Published: January 2025

This study aimed to assess the acute effects of two isoenergetic but micronutrient-diverse meals—a Mediterranean-like meal (MdM) and a fast food-like meal (FFM)—on the autonomic nervous system (ANS), lung function, and airway inflammation response. Forty-six participants were enrolled in a randomized cross-over clinical trial, consuming two isoenergetic meals: FFM (burger, fries, and sugar-sweetened drink) and MdM (vegetable soup, whole wheat pasta, salad, olive oil, sardines, fruit, and water). Pupillometry assessed parasympathetic (MaxD, MinD, Con, ACV, MCV) and sympathetic (ADV, T75) nervous system outcomes. Lung function and airway inflammation were measured before and after each meal through spirometry and fractional exhaled nitric oxide (FeNO), respectively. Mixed-effects model analysis showed that MdM was associated with a hegemony of parasympathetic response, with a significant increase of MaxD associated with a faster constriction velocity (ACV and MCV); on the other side, the FFM associated with changes in the sympathetic response, showing a quicker redilation velocity (decreased of T75). After adjusting for confounders, mixed-effects models revealed that the FFM significantly decreased T75. Regarding lung function, a meal negatively impacted FVC (ae= -0.079, p<0.001) and FEV1 (ae= -0.04, p= 0.017); however, FeNO increased, although after adjusting, no difference between meals was seen. In conclusion, our study showed that FFM counteracted the parasympathetic activity of a meal, while a meal, irrespective of the type, decreased lung function and increased airway inflammation.
Circadian Rhythms, Regular Exercise and Cognitive Performance in Morning-Trained Dancers
Authors: Marchesano Mariana , Carboni Román María Alejandra , Tassino Bettina , Silva Ana
Published: January 2025

Time-of-day and individual circadian variability influence cognitive performance, with later chronotypes being most compromised earlier in the day. On the other hand, moderate-intensity exercise has been shown to enhance cognitive function. We sought to evaluate the interplay between circadian rhythms, exercise, and cognitive performance in 22 students from the Uruguayan National Dance School, a population previously characterized as late chronotypes, attending a demanding morning schedule. We assessed sleep habits and physical activity patterns using self-report questionnaires and actigraphy. Before and after morning training, participants completed a psychomotor vigilance task (PVT) and a visual Stroop task (congruent and incongruent). The reaction speeds were lower early in the morning than at noon for all these tasks. We also found 1) a positive correlation between weekend sleep duration and PVT performance before training but not after; 2) a negative correlation between individual circadian phase and Stroop performance for both congruent and incongruent conditions after training but not before; and 3) a better Stroop performance after training for both congruent and incongruent conditions in dancers who engaged longer moderate-intensity exercise during training. Our findings suggest that regular morning training might help mitigate cognitive impairments experienced by dancers with later chronotypes in challenging morning scenarios.
General Stochastic Vector Integration - Three Approaches
Authors: Sohns Moritz
Published: January 2025

The development of stochastic integration theory throughout the 20th century has led to several definitions and approaches of the stochastic integral, particularly for predictable integrands and semimartingale integrators. This survey provides an overview of the two prominent approaches in defining the stochastic integral: the classical approach attributed to Itô, Meyer and Jacod, and the more contemporary functional analytical approach mainly developed by Bichteler and Protter. It also delves into the historical milestones and achievements in this area and analyzes them from a modern perspective. Drawing inspiration from the similarities of existing approaches, this survey introduces a new topology-based approach to the general vector-valued stochastic integral for predictable integrands and semimartingale integrators. This new approach provides a faster, simpler way to define the general integral and offers a self-contained derivation of its key properties without depending on semimartingale decomposition theorems.
Multi-Modal Wound Classification Using Wound Image and Location by Xception and Gaussian Mixture Recurrent Neural Network (GMRNN)
Authors: Mousa Ramin , Matbooe Ehsan , Khojasteh Hakimeh
Published: January 2025

The effective diagnosis of acute and hard-to-heal wounds is crucial for wound care practitioners to provide effective patient care. Poor clinical outcomes are often linked to infection, peripheral vascular disease, and increasing wound depth, which collectively exacerbate these comorbidities. However, diagnostic tools based on Artificial Intelligence (AI) speed up the interpretation of medical images and improve early detection of disease. In this article, we propose a multi-modal AI model based on transfer learning (TL), which combines two state-of-the-art architectures, Xception and GMRNN, for wound classification. The multi-modal network is developed by concatenating the features extracted by a transfer learning algorithm and location features to classify the wound types of diabetic, pressure, surgical, and venous ulcers. The proposed method is comprehensively compared with deep neural networks (DNN) for medical image analysis. The experimental results demonstrate a notable wound class classifications (containing only diabetic, pressure, surgical, and venous) vary from 78.77 to 100% in various experiments. The results presented in this study showcase the exceptional accuracy of the proposed methodology in accurately classifying the most commonly occurring wound types using wound images and their corresponding locations.
Sustainable European Mountain Entrepreneurship Through Statistical, Neural Network, and Fractal Analyzes—A Review
Authors: Covaci Brindusa , Covaci Mihai
Published: January 2025

The article explores the key dimensions of European mountain entrepreneurship, emphasizing the economic roles of the Industry (secondary sector) and Services (tertiary sector). The analysis aims to provide a comprehensive understanding of entrepreneurial support sectors in mountain regions, including commerce, automotive, transport, storage, finance, and real estate. These sectors collectively represent a substantial share of mountain-based economic activity, comprising over one-third of all enterprises in these areas, with a steady rise in their numbers. Across EU countries, the level of entropy in mountain entrepreneurship within these supporting sectors underscores the need for better structural coherence at the community level. Fractal simulations offer innovative perspectives on the organizational dynamics of mountain entrepreneurship in Europe. Furthermore, neural network models reveal patterns highlighting weak links within these supporting sectors compared to the broader secondary and tertiary sectors, while also identifying robust interconnections between these two sectors. The authors propose actionable strategies to strengthen interconnectivity among European countries based on these findings.
Significance of Influent C/N Ratios in Mainstream Anammox Process: Nitrogen Removal and Microbial Dynamics
Authors: Yang Yandong , Liu Shichong , Liu Lei , Long Yanan , Wang Chao , Liu Changqing
Published: January 2025

Achieving simultaneous anammox and denitrification is a promising strategy to enhance nitrogen removal in mainstream anammox processes. However, the optimal influent C/N ratio and the microbial dynamics driving this process are still not fully understood. In this study, three mainstream anammox reactors were operated with varying influent C/N ratios. The results demonstrated a remarkable nitrogen removal efficiency of 92.6% achieved by combining partial denitrification and anammox, with the C/N ratio set at 1.0. Whereas, the nitrogen removal efficiency decreased when the C/N ratio was either 0.5 or 2.0, causing the accumulation of nitrate and ammonium in the effluent, respectively. These results suggest a narrow optimal range of the influent C/N ratio for mainstream anammox processes. Additionally, a transition in the predominant denitrifier population from Denitratisoma to Thauera was noted with the rise of the C/N ratio. The denitrifying phenotype of Thauera greatly depended on the C/N ratio. Only at a suitable C/N ratio, Thauera can effectively collaborate with anammox bacteria, partially reducing the nitrate generated in the anammox reaction. When the C/N ratio was high, Thauera primarily performed nitrite reduction, notably inhibiting anammox activity. The results of this study are valuable for the optimal design of the mainstream anammox process. In this study, the effects of carbon/nitrogen (C/N) ratio on mainstream anammox reactor were investigated.
Hot Modification of Silicomanganese Slag in Its Crystallization and Viscosity Properties for Preparation of Cast Stone
Authors: Huang Yi , Li Yu , Cheng Zhaoyang , Feng Wei
Published: January 2025

The direct hot modification and then preparation of qualified building materials from molten slag have gained significant attention at present due to its characteristics to save energy and reduce CO2 emissions. Molten silicomanganese slag discharged at 1500-1600 ℃ with high content of SiO2 and Al2O3 (above 50 mass%) is suitable for preparation of casting stone. For ensuring a qualified casting stone, the study focused on the improvement of crystallization properties and fluidity of molten silicomanganese slag by modification of its composition, crystallization, structure, viscosity of raw slag and two modified slags, and physical properties of their final cast stone was compared and discussed. The results showed that after modified by addition of 10 mass% chromite and serpentine or 20 mass% ferrochrome slag into silicomanganese slag, both crystallization ability and fluidity of the molten slag were improved simultaneously. Augite and spinel precipitated in the modified slag compared with glass phase in the raw slag. The precipitation of spinel on the one hand acted as a nucleation agent, dynamically promoting the formation of augite, and on the other hand, increased the proportion of SiO2 and its polymerization of [SiO4] structural units in the residual liquid slag, further promoting the generation of augite in composition and structure. The gradual precipitation of crystals effectively mitigates sudden viscosity fluctuations resulting from crystallization, contributing to a smooth casting process for molten slag. Both cast stone from the modified slag exhibited qualified physical properties, compared with the broken glass from the raw slag. It indicates a feasibility for a simple and low-cost modification during discharging process of molten silicomanganese slag by blending 10 mass% cold modifiers or 20 mass% molten ferrochrome slag into it.
Newtonian Theory of Orbit Perturbation and Revalued Mass of Sgr A*
Authors: Zhu Yin
Published: January 2025

It is a famous old problem: Why the orbit of the Moon around the Earth is stable under the condition that, calculated with F=GMm/R2, the force of the Sun on the orbit is almost 2.2 times that of the Earth? We find, the calculated force of the Sgr A* on the orbit of the Oort cloud around the Sun is larger than that of the Sun; and, the force of the Sgr A* on the orbits on the edge of the ω Centauri is larger than that of the black hole at the center of the ω Centauri. It is known that the old problem about the Moon around the Earth can be understood with the Newtonian theory of orbit perturbation. Here, we find, the problem about the Oort cloud and the ω Centauri also can be understood with the Newtonian theory of orbit perturbation. And, we conclude that the mass of the Sgr A* should be MSgrA*∼1.8×1011MSun ; and, at the center of every stellar cluster there should be a black hole or other massive body which can be easily measured with any one of the orbits in the cluster or with the Hill sphere.
Sustainable Strategies for Improving Humanitarian Construction through BIM and Climate analysis
Authors: Gladdys Mwikilwa Mukamba , Gentil Bigirimana , Cao Ping
Published: January 2025

The growing need for effective and sustainable solutions in humanitarian construction has prompted scholars and practitioners to explore technical approaches that address the challenges of natural disasters, health emergencies, armed conflicts and migratory flows. These solutions often encompass temporary shelters, durable shelters and multifunctional buildings designed to balance rapid deployment, cultural sensitivity and environmental sustainability. However, the assessment of sustainability in humanitarian construction remains insufficiently defined due to the complexities of crises, the variability of local materials and the impact of local climatic conditions. This study aims to bridge this gap by integrating Building Information Modeling (BIM) and simulation tools such as COMSOL Multiphysics to study sustainable strategies for humanitarian housing. Using case studies aligned with IFRC, UNHCR and CRL (red-cross of Luxembourg) family shelter standards, the research assessed a Climate and Local Skill-Centered Design (CLCD) by examining the performance of key design elements, including wall material emissivity and reflectance, natural lighting and energy efficiency within the indoor thermal comfort. Simulation results revealed that wall finishing material reflectance significantly influences average daylight factors (D), with variations of 2% to 5% linked to lower reflectance values and changes in the window-to-floor ratio (WFR). Conversely, thermal comfort metrics indicated minimal variations in heat discomfort hours, maintaining indoor temperatures between 19°C and 25°C, consistent with ASHRAE Standard 55 thermal comfort criteria. This paper underscores the importance of integrating advanced IT tools and green Local technic and materials to optimize humanitarian housing for health, comfort and environmental performance, offering actionable insights for future Humanitarian sustainable designs.