bluuebunny/crossref_metadata_2025 huggingface dataset:
Pharmacokinetics and tissue distribution of LN002, a new compound alternative oxidase inhibitor against Cryptosporidium in rats
Authors: Ma Minglang , Zhang Yongxiang , Fang Yanjun , Lu Yixing , Huang Huiguo , Zeng Zhenling , Zeng Dongping
Published: July 2024

Cryptosporidiosis is considered a crucial zoonotic disease caused by widely distributing parasitic protozoa called Cryptosporidium spp. Nitazoxanide is the only FDA-approved drug but is only effective with a good immune response of the host. In addressing this unmet medical need, we previously identified a compound, namely, LN002, as a potent alternative oxidase inhibitor against cryptosporidiosis. To illustrate the pharmacokinetics, absolute bioavailability, and tissue distribution of LN002 in rats, rapid and sensitive high-performance liquid chromatography was developed and validated for the separation and detection of LN002 in plasma, tissue samples, and intestinal contents. In this study, a single dose of oral administration and intravenous injection of LN002 was used to determine the levels of LN002 in plasma, tissue samples, and intestinal contents by UHLC. Results of the study indicated that after intravenous administration of 1 mg/kg LN002, the AUC0–24 h, T1/2,Vd, and Cl were 7024.86 h·ng/mL, 10.91 h, 1.69 L/kg, and 0.11 L/h/kg, respectively. After oral administration of a single dosage of 100, 200, and 400 mg/kg LN002, the Tmax, Cmax, AUC0–24 h, T1/2, F, Vd, and Cl/F in plasma of rats were 1 h, 849.88–4033.21 ng/mL, 2280.41–7498.10 h·ng/mL, 17.96–18.83 h, 0.27%–0.32%, 581.54–869.21 L/kg, and 25.97–39.00 L/h/kg, respectively. After oral administration of 200 mg/kg, LN002 was extensively distributed in the main tissues of rats, and massive amounts of LN002 were distributed in the intestine and intestinal contents, indicating its potential as an effective anti-Cryptosporidium compound. After oral administration of a single dosage of 200 mg/kg, LN002 has a low bioavailability and high levels in the intestine, which is crucial for the safe and effective treatment of cryptosporidiosis. Overall, the results of this study provide valuable data support for the future study of LN002.
Naringin and temozolomide combination suppressed the growth of glioblastoma cells by promoting cell apoptosis: network pharmacology, in-vitro assays and metabolomics based study
Authors: Bisht Priya , Prasad Surendra Rajit , Choudhary Khushboo , Pandey Ruchi , Aishwarya Dande , Aravind Vulli , Ramalingam Peraman , Velayutham Ravichandiran , Kumar Nitesh
Published: July 2024

Introduction: Glioblastoma, which affects a large number of patients every year and has an average overall lifespan of around 14.6 months following diagnosis stands out as the most lethal primary invasive brain tumor. Currently, surgery, radiation, and chemotherapy with temozolomide (TMZ) are the three major clinical treatment approaches. However, the ability to treat patients effectively is usually limited by TMZ resistance. Naringin, a bioflavonoid with anti-cancer, antioxidant, metal-chelating, and lipid-lowering effects, has emerged as a promising therapeutic option.

Methods: To explore the targets and pathways of naringin and TMZ in glioblastoma network pharmacology, cell line-based ELISA, flow cytometry, immunocytochemistry, western blotting, and LC-HRMS based metabolomics study were used.

Results: The findings through the network pharmacology suggested that the key targets of naringin in the chemosensitization of glioblastoma would be Poly [ADP-ribose] polymerase 1 (PARP-1), O-6-Methylguanine-DNA Methyltransferase (MGMT), and caspases. The functional enrichment analysis revealed that these targets were significantly enriched in important pathways such as p53 signaling, apoptosis, and DNA sensing. Further, the results of the in-vitro study in U87-MG and T98-G glioblastoma cells demonstrated that TMZ and naringin together significantly reduced the percentage of viability and inhibited the DNA repair enzymes PARP-1 and MGMT, and PI3K/AKT which led to chemosensitization and, in turn, induced apoptosis, which was indicated by increased p53, caspase-3 expression and decreased Bcl2 expression. Additionally, a metabolomics study in T98-G glioblastoma cells using liquid chromatography high-resolution mass spectrometry (LC-HRMS) revealed downregulation of C8-Carnitine (−2.79), L-Hexanoylcarnitine (−4.46), DL-Carnitine (−2.46), Acetyl-L-carnitine (−3.12), Adenine (−1.3), Choline (−2.07), Propionylcarnitine (−1.69), Creatine (−1.33), Adenosine (−0.84), Spermine (−1.42), and upregulation of Palmitic Acid (+1.03) and Sphingosine (+0.89) in the naringin and TMZ treatment groups.

Discussion: In conclusion, it can be said that naringin in combination with TMZ chemosensitized TMZ antiglioma response and induced apoptosis in tumor cells.
The impact of population influx on infectious diseases – from the mediating effect of polluted air transmission
Authors: Fu Haifeng , Zhu Chaoping
Published: July 2024

The global population influx during the COVID-19 pandemic poses significant challenges to public health, making the prevention and control of infectious diseases a pressing concern. This paper aims to examine the impact of population influx on the spread of infectious diseases, with a specific emphasis on the mediating role of air pollution in this process. A theoretical analysis is conducted to explore the relationship between population influx, air pollution, and infectious diseases. Additionally, we establish a series of econometric models and employ various empirical tests and analytical techniques, including mediation effect test, threshold effect test, and systematic GMM test, to evaluate our hypotheses. The results indicate that: (1) Population influx directly and indirectly impacts infectious diseases. Specifically, population influx not only directly elevates the risk of infectious diseases, but also indirectly increases the incidence rate of infectious diseases by intensifying air pollution. (2) The impact of population inflow on infectious diseases exhibits regional heterogeneity. Compared to central and western China, the eastern regions exhibit a significantly higher risk of infectious diseases, exceeding the national average. (3) External factors influence the relationship between population influx and infectious diseases differently. Personal income and medical resources both help mitigate the risk of infectious diseases due to population influx, with medical resources having a more substantial effect. Contrary to expectations, abundant educational resources have not reduced the risk, instead, they have exacerbated the risk associated with population influx. This paper provides a scientific basis for formulating effective strategies for the prevention and control of infectious diseases.
Ballistic Limit Equation Derivation for Thin Tape Tethers
Authors: Olivieri Lorenzo , Giacomuzzo Cinzia , Francesconi Alessandro
Published: July 2024

Electromagnetic tethers of hundreds or thousands of meters have been proposed for maneuvring spacecraft in Low Earth Orbit, and in particular, for post-mission disposals. The debate on tether survivability to debris impact is still influencing further advances in the implementation of such technology because of the large area they expose to the debris environment; thin tape geometries have been proposed instead of round ones to increase the survivability to hypervelocity impacts. In this context, this paper introduces a new Ballistic Limit Equation (BLE) for thin tape tethers, derived from experimental results, numerical simulations, and literature data. The resulting equation is non-monotonic with respect to impact angle, presenting a minimum depending on the debris velocity and size; for high obliquities, the debris fragmentation triggered by shock waves propagating into the material reduces the damage. This feature allows to set a minimum particle diameter for risk assessment, excluding a significant part of the debris flux. The proposed BLE confirms the performance of thin tape tethers, with respect to round wires, due to their better ballistic response as well as their reduced cross-section at high-obliquity impacts.
Risk Factor Analysis for Occurrence of Linezolid-Resistant Bacteria in the Digestive and Respiratory Tract of Food-Producing Animals in Belgium: A Pilot Study
Authors: Driesen Michèle , Timmermans Michaël , Cargnel Mickaël , Simons Xavier , Filippitzi Maria-Eleni , Catry Boudewijn , Dal Pozzo Fabiana , Vanderhaeghen Wannes , Callens Bénédicte , Dispas Marc , Boland Cécile
Published: July 2024

Linezolid is a critically important antimicrobial used in human medicine. While linezolid is not licensed for food-producing animals, the veterinary use of other antimicrobials, such as phenicols (e.g., florfenicol), could cross/co-select for linezolid-resistant (LR) bacteria. Such LR strains pose a great concern for public health due to their potential transfer between animals and humans. This study explored possible associations between epidemiological risk factors, including phenicol use, and the occurrence of LR bacteria, such as enterococci and staphylococci, in poultry, pigs, and veal calves in Belgium. Florfenicol use significantly increased the likelihood of harboring LR bacteria in veal calves, sows, and fattening pigs, particularly for the digestive tract (odds ratio (OR): [3.19–5.29]) and the respiratory tract (OR: [6.11–9.09]). LR strains from feces from fattening pigs were significantly associated with production type (OR: [3.31–44.14]) and the presence of other animal species (OR: 0.41). The occurrence of LR strains in the respiratory tract from sows was also significantly associated with using antimicrobials other than florfenicol (OR: 10.07) and purchasing animals (OR: 7.28). Our study highlights the potential risks of using certain veterinary antimicrobials, such as florfenicol, in food-producing animals and emphasizes the need for responsible antimicrobial use to safeguard both animal and public health.
On-Site Inactivation for Disinfection of Antibiotic-Resistant Bacteria in Hospital Effluent by UV and UV-LED
Authors: Azuma Takashi , Usui Masaru , Hasei Tomohiro , Hayashi Tetsuya
Published: July 2024

The problem of antimicrobial resistance (AMR) is not limited to the medical field but is also becoming prevalent on a global scale in the environmental field. Environmental water pollution caused by the discharge of wastewater into aquatic environments has caused concern in the context of the sustainable development of modern society. However, there have been few studies focused on the treatment of hospital wastewater, and the potential consequences of this remain unknown. This study evaluated the efficacy of the inactivation of antimicrobial-resistant bacteria (AMRB) and antimicrobial resistance genes (AMRGs) in model wastewater treatment plant (WWTP) wastewater and hospital effluent based on direct ultraviolet (UV) light irradiation provided by a conventional mercury lamp with a peak wavelength of 254 nm and an ultraviolet light-emitting diode (UV-LED) with a peak emission of 280 nm under test conditions in which the irradiance of both was adjusted to the same intensity. The overall results indicated that both UV- and UV-LED-mediated disinfection effectively inactivated the AMRB in both wastewater types (>99.9% after 1–3 min of UV and 3 min of UV-LED treatment). Additionally, AMRGs were also removed (0.2–1.4 log10 for UV 254 nm and 0.1–1.3 log10 for UV 280 nm), and notably, there was no statistically significant decrease (p < 0.05) in the AMRGs between the UV and UV-LED treatments. The results of this study highlight the importance of utilizing a local inactivation treatment directly for wastewater generated by a hospital prior to its flow into a WWTP as sewage. Although additional disinfection treatment at the WWTP is likely necessary to remove the entire quantity of AMRB and AMRGs, the present study contributes to a significant reduction in the loads of WWTP and urgent prevention of the spread of infectious diseases, thus alleviating the potential threat to the environment and human health risks associated with AMR problems.
Optimization of the Operating Voltage of Cobalt-Free Nickel-in-Medium Cathodes for High-Performance Lithium-Ion Batteries
Authors: Qi Yuchuan , Hou Shuheng , Qin Ningbo , Huang Ting , Guo Jiawen , Hou Xianghua , Huang Ning , Liu Yifan , Liu Xijun
Published: July 2024

Medium-nickel cobalt-free cathode materials have attracted much attention in recent years for their low cost and high energy density. However, the structural stability of nickel-based cathode materials becomes compromised when accompanied by the increasing of voltage, leading to poor cycling performance and, thus, hindering their widespread industrial application. In this work, we investigated the optimal charge cut-off voltage for the nickel-based cathode material LiNi0.6Mn0.4O2 (NM64). Within the voltage range of 3.0 to 4.5 V, the electrode energy density reached 784.08 Wh/kg, with an initial Coulombic efficiency of 84.49%. The reversible specific capacity at 0.1 C reached 197.84 mAh/g, and it still maintained a high reversible specific capacity of nearly 150 mAh/g, with a capacity retention rate of 86% after 150 cycles at 1 C. Furthermore, NM64 exhibited an intact morphological structure without noticeable cracking after 150 cycles, indicating excellent structural stability. This study emphasizes the relationship between the stability of NM64 cathodes and different operating voltage ranges, thereby promoting the development of high-voltage layered nickel-based cathode materials.
Improving Machine Learning Predictive Capacity for Supply Chain Optimization through Domain Adversarial Neural Networks
Authors: Sayyad Javed , Attarde Khush , Yilmaz Bulent
Published: July 2024

In today’s dynamic business environment, the accurate prediction of sales orders plays a critical role in optimizing Supply Chain Management (SCM) and enhancing operational efficiency. In a rapidly changing, Fast-Moving Consumer Goods (FMCG) business, it is essential to analyze the sales of the products and accordingly plan the supply. Due to low data volume and complexity, traditional forecasting methods struggle to capture intricate patterns. Domain Adversarial Neural Networks (DANNs) offer a promising solution by integrating transfer learning techniques to improve prediction accuracy across diverse datasets. This study presents a new sales order prediction framework that combines DANN-based feature extraction and various machine learning models. The DANN method generalizes the data, maintaining the data behavior’s originality. The approach addresses challenges like limited data availability and high variability in sales behavior. Using the transfer learning approach, the DANN model is trained on the training data, and this pre-trained DANN model extracts relevant features from unknown products. In contrast, Machine Learning (ML) algorithms are used to build predictive models based on it. The hyperparameter tuning of ensemble models such as Decision Tree (DT) and Random Forest (RF) is also performed. Models like the DT and RF Regressor perform better than Linear Regression and Support Vector Regressor. Notably, even without hyperparameter tuning, the Extreme Gradient Boost (XGBoost) Regressor model outperforms all the other models. This comprehensive analysis highlights the comparative benefits of various models and establishes the superiority of XGBoost in predicting sales orders effectively.
A Systematic Review and Meta-Analysis of MicroRNA as Predictive Biomarkers of Acute Kidney Injury
Authors: Brown Naomi , Roman Marius , Miller Douglas , Murphy Gavin , Woźniak Marcin J.
Published: July 2024

Acute kidney injury (AKI) affects 10–15% of hospitalised patients and arises after severe infections, major surgeries, or exposure to nephrotoxic drugs. AKI diagnosis based on creatinine level changes lacks specificity and may be delayed. MicroRNAs are short non-coding RNA secreted by all cells. This review of studies measuring miRNAs in AKI aimed to verify miRNAs as diagnostic markers. The study included data from patients diagnosed with AKI due to sepsis, ischaemia, nephrotoxins, radiocontrast, shock, trauma, and cardiopulmonary bypass. Out of 71 studies, the majority focused on AKI in sepsis patients, followed by cardiac surgery patients, ICU patients, and individuals receiving nephrotoxic agents or experiencing ischaemia. Studies that used untargeted assays found 856 differentially regulated miRNAs, although none of these were confirmed by more than one study. Moreover, 68 studies measured miRNAs by qRT-PCR, and 2 studies reported downregulation of miR-495-3p and miR-370-3p in AKI patients with sepsis after the AKI diagnosis. In three studies, upregulation of miR-21 was reported at the time of the AKI diagnosis with a significant pooled effect of 0.56. MiR-21 was also measured 19–24 h after cardiac surgery in three studies. However, the pooled effect was not significant. Despite the considerable research into miRNA in AKI, there is a knowledge gap in their applicability as diagnostic markers of AKI in humans.
Local Therapy and Reconstruction in Penile Cancer: A Review
Authors: Zekan David , Praetzel Rebecca , Luchey Adam , Hajiran Ali
Published: July 2024

Local therapy for penile cancer provides robust survival and can preserve the penis functionally and cosmetically. Interventions must target the appropriate clinical stage. We reviewed studies regarding the primary therapy in penile cancer, from topical therapy to radical penectomy, and reconstructive techniques. Topical therapy (5-FU or Imiquimod) provides a robust oncologic response in patients with Ta or Tis disease. Multiple laser therapies are available for localized patients and those with low-grade T1 disease. There is a non-trivial risk of progression and nodal metastases in poorly selected patients. Wide local excision provides an oncologically sound option in patient with up to T1 disease; less evidence exists for Mohs microsurgery in the setting of penile cancer. Increasingly aggressive approaches include glansectomy and partial/radical penectomy, which provide 5- and 10-year cancer-specific survival rates of over 80%. Meticulous reconstruction is necessary for the durable function of the remaining penis. Preservation of voiding and sexual function occurs via penile skin grafting, glans resurfacing, creation of a functional penile stump, and phalloplasty with a penile implant. Perineal urethrostomy provides an alternative in pathology demanding extensive partial or radical penectomy, and a durable option for seated voiding. Clinical suspicion and timely diagnosis are paramount in terms of management as less-invasive options for earlier-stage disease develop.
An Injury-like Signature of the Extracellular Glioma Metabolome
Authors: Ha Yooree , Rajani Karishma , Riviere-Cazaux Cecile , Rahman Masum , Olson Ian E. , Gharibi Loron Ali , Schroeder Mark A. , Rodriguez Moses , Warrington Arthur E. , Burns Terry C.
Published: July 2024

Aberrant metabolism is a hallmark of malignancies including gliomas. Intracranial microdialysis enables the longitudinal collection of extracellular metabolites within CNS tissues including gliomas and can be leveraged to evaluate changes in the CNS microenvironment over a period of days. However, delayed metabolic impacts of CNS injury from catheter placement could represent an important covariate for interpreting the pharmacodynamic impacts of candidate therapies. Intracranial microdialysis was performed in patient-derived glioma xenografts of glioma before and 72 h after systemic treatment with either temozolomide (TMZ) or a vehicle. Microdialysate from GBM164, an IDH-mutant glioma patient-derived xenograft, revealed a distinct metabolic signature relative to the brain that recapitulated the metabolic features observed in human glioma microdialysate. Unexpectedly, catheter insertion into the brains of non-tumor-bearing animals triggered metabolic changes that were significantly enriched for the extracellular metabolome of glioma itself. TMZ administration attenuated this resemblance. The human glioma microdialysate was significantly enriched for both the PDX versus brain signature in mice and the induced metabolome of catheter placement within the murine control brain. These data illustrate the feasibility of microdialysis to identify and monitor the extracellular metabolome of diseased versus relatively normal brains while highlighting the similarity between the extracellular metabolome of human gliomas and that of CNS injury.
Prospective Study of Non-Contrast, Abbreviated MRI for Hepatocellular Carcinoma Surveillance in Patients with Suboptimal Hepatic Visualisation on Ultrasound
Authors: Vithayathil Mathew , Qurashi Maria , Vicente Pedro Rente , Alsafi Ali , Naik Mitesh , Graham Alison , Khan Shahid , Lewis Heather , Dhar Ameet , Smith Belinda , Selvapatt Nowlan , Manousou Pinelopi , Possamai Lucia , Izadi Hooshang , Lim Adrian , Tait Paul , Sharma Rohini
Published: July 2024

Background: Biannual ultrasound (US) is recommended for hepatocellular carcinoma (HCC) surveillance in patients with cirrhosis. However, US has limited sensitivity for early-stage HCC, particularly in overweight cohorts, where hepatic visualisation is often inadequate. Currently there are no robust imaging surveillance strategies in patients with inadequate US visualisation. We investigated the ability of non-contrast, abbreviated magnetic resonance imaging (aMRI) to adequately visualise the liver for HCC surveillance in patients with previously inadequate US. Methods: Patients undergoing US surveillance, where liver visualisation was inadequate (LI-RADS VIS-B and VIS-C), were prospectively recruited. Patients underwent non-contrast T2-weighted and diffusion-weighted aMRI. The images were reviewed and reported by an expert liver radiologist. Three independent, blinded radiologists assessed the aMRI visualisation quality using a binary score assessing five parameters (parenchymal definition, vascular definition, coverage of the liver, uniformity of liver appearance and signal-to-noise ratio). Results: Thirty patients completed the aMRI protocol. The majority (90%) had underlying cirrhosis and were overweight (93.3%), with 50% obese and 20% severely obese. A total of 93.3% of the aMRI scans were of satisfactory quality. Six patients (20%) had hepatic abnormalities detected with aMRI that were not seen on their US: one HCC, one haemangioma and three clinically insignificant lesions. For the aMRI visualisation quality assessment, the coverage of the liver, vascular definition and parenchymal definition were consistently rated to be of sufficient quality by all three radiologists. Conclusions: Non-contrast aMRI provided good visualisation of the liver and detection of abnormalities in patients with inadequate US. aMRI should be further explored in a larger, prospective study as an alternative surveillance strategy in patients with inadequate US.
Synergistic Efficacy of CDK4/6 Inhibitor Abemaciclib and HDAC Inhibitor Panobinostat in Pancreatic Cancer Cells
Authors: Bhutkar Shraddha , Yadav Anjali , Patel Himaxi , Barot Shrikant , Patel Ketan , Dukhande Vikas V.
Published: July 2024

The current 5-year survival rate of pancreatic cancer is about 12%, making it one of the deadliest malignancies. The rapid metastasis, acquired drug resistance, and poor patient prognosis necessitate better therapeutic strategies for pancreatic ductal adenocarcinoma (PDAC). Multiple studies show that combining chemotherapeutics for solid tumors has been successful. Targeting two distinct emerging hallmarks, such as non-mutational epigenetic changes by panobinostat (Pan) and delayed cell cycle progression by abemaciclib (Abe), inhibits pancreatic cancer growth. HDAC and CDK4/6 inhibitors are effective but are prone to drug resistance and failure as single agents. Therefore, we hypothesized that combining Abe and Pan could synergistically and lethally affect PDAC survival and proliferation. Multiple cell-based assays, enzymatic activity experiments, and flow cytometry experiments were performed to determine the effects of Abe, Pan, and their combination on PDAC cells and human dermal fibroblasts. Western blotting was used to determine the expression of cell cycle, epigenetic, and apoptosis markers. The Abe-Pan combination exhibited excellent efficacy and produced synergistic effects, altering the expression of cell cycle proteins and epigenetic markers. Pan, alone and in combination with Abe, caused apoptosis in pancreatic cancer cells. Abe-Pan co-treatment showed relative safety in normal human dermal fibroblasts. Our novel combination treatment of Abe and Pan shows synergistic effects on PDAC cells. The combination induces apoptosis, shows relative safety, and merits further investigation due to its therapeutic potential in the treatment of PDAC.
An Adoption of the Fractional Maxwell Model for Characterizing the Interfacial Dilational Viscoelasticity of Complex Surfactant Systems
Authors: Loglio Giuseppe , Czakaj Agnieszka , Jarek Ewelina , Kovalchuk Volodymyr I. , Krzan Marcel , Liggieri Libero , Miller Reinhard , Warszynski Piotr
Published: July 2024

In this communication, the single-element version of the fractional Maxwell model (single FMM) is adopted to quantify the observed behaviour of the interfacial dilational viscoelasticity. This mathematical tool is applied to the results obtained by the oscillating drop method for aqueous solutions of ethyl lauroyl arginate (LAE). The single FMM adequately fits the experimental results, fairly well characterizing the frequency dependence of the modulus and the inherent phase-shift angle of the complex physical quantity, i.e., the interfacial dilational viscoelasticity. Further speculations are envisaged to apply the FMM to step perturbations in the time domain, allowing for the same parameter set as in the frequency domain.
Enhancing Mission Planning of Large-Scale UAV Swarms with Ensemble Predictive Model
Authors: Meng Guanglei , Zhou Mingzhe , Meng Tiankuo , Wang Biao
Published: July 2024

Target assignment and trajectory planning are two crucial components of mission planning for unmanned aerial vehicle (UAV) swarms. In large-scale missions, the significance of planning efficiency becomes more pronounced. However, existing planning algorithms based on evolutionary computation and swarm intelligence face formidable challenges in terms of both efficiency and effectiveness. Additionally, the extensive trajectory planning involved is a significant factor affecting efficiency. Therefore, this paper proposes a dedicated method for large-scale mission planning. Firstly, to avoid extensive trajectory planning operations, this paper suggests utilizing a machine learning algorithm to establish a predictive model of trajectory length. To ensure predictive accuracy, an ensemble algorithm based on Gaussian process regression (GPR) is proposed. Secondly, to ensure the efficiency and effectiveness of target assignments in large-scale missions, this paper draws inspiration from a greedy search and proposes a simple yet effective target assignment algorithm. This algorithm can effectively handle a large number of decision variables and constraints involved in large-scale missions. Finally, we validated the effectiveness of the proposed method through 15 simulated missions of different scales. Among the 10 medium- to large-scale missions, our method achieved the best results in 9 of them, demonstrating the competitive advantage of our method in large-scale missions. Comparative results demonstrate the advantage of the proposed methods from both prediction and mission planning perspectives.
Quantum Physics-Informed Neural Networks
Authors: Trahan Corey , Loveland Mark , Dent Samuel
Published: July 2024

In this study, the PennyLane quantum device simulator was used to investigate quantum and hybrid, quantum/classical physics-informed neural networks (PINNs) for solutions to both transient and steady-state, 1D and 2D partial differential equations. The comparative expressibility of the purely quantum, hybrid and classical neural networks is discussed, and hybrid configurations are explored. The results show that (1) for some applications, quantum PINNs can obtain comparable accuracy with less neural network parameters than classical PINNs, and (2) adding quantum nodes in classical PINNs can increase model accuracy with less total network parameters for noiseless models.
A Thermodynamic Study on Information Power in Communication Systems
Authors: Yan Litao , Ge Xiaohu
Published: July 2024

Modern information theory pioneered by Shannon provides the mathematical foundation of information transmission and compression. However, the physical (and especially the energetic) nature of the information has been elusive. While the processing of information incurs inevitable energy dissipation, it is possible for communication systems to harness information to perform useful work. In this article, we prove that the thermodynamic cost (that is, the entropy production of the communication system) is at least equal to the information transmitted. Based on this result, a model of a communication heat engine is proposed, which can extract work from the heat bath by utilizing the transmission of information. The communication heat engine integrates the manipulation of both energy and information so that both information and power may be transmitted in parallel. The information transmission rate and the information power of the communication heat engine are derived from a pure thermodynamics argument. We find that the information power of the communication heat engine can be increased by increasing the number of communication channels, but the absolute energy efficiency of the heat engine first increases and then decreases after the number of channels of the system exceeds a threshold. The proposed model and definitions provide a new way to think of a classical communication system from a thermodynamic perspective.
Statistics as a Social Activity: Attitudes toward Amalgamating Evidence
Authors: Gelman Andrew , O’Rourke Keith
Published: July 2024

Amalgamation of evidence in statistics is conducted in several ways. Within a study, multiple observations are combined by averaging, or as factors in a likelihood or prediction algorithm. In multilevel modeling or Bayesian analysis, population or prior information is combined with data using the weighted averaging derived from probability modeling. In a scientific research project, inferences from data analysis are interpreted in light of mechanistic models and substantive theories. Within a scholarly or applied research community, data and conclusions from separate laboratories are amalgamated through a series of steps, including peer review, meta-analysis, review articles, and replication studies. These issues have been discussed for many years in the philosophy of science and statistics, gaining attention in recent decades first with the renewed popularity of Bayesian inference and then with concerns about the replication crisis in science. In this article, we review the amalgamation of statistical evidence from different perspectives, connecting the foundations of statistics to the social processes of validation, criticism, and consensus building.
Probabilistic Estimation and Control of Dynamical Systems Using Particle Filter with Adaptive Backward Sampling
Authors: Omi Taketo , Omori Toshiaki
Published: July 2024

Estimating and controlling dynamical systems from observable time-series data are essential for understanding and manipulating nonlinear dynamics. This paper proposes a probabilistic framework for simultaneously estimating and controlling nonlinear dynamics under noisy observation conditions. Our proposed method utilizes the particle filter not only as a state estimator and a prior estimator for the dynamics but also as a controller. This approach allows us to handle the nonlinearity of the dynamics and uncertainty of the latent state. We apply two distinct dynamics to verify the effectiveness of our proposed framework: a chaotic system defined by the Lorenz equation and a nonlinear neuronal system defined by the Morris–Lecar neuron model. The results indicate that our proposed framework can simultaneously estimate and control complex nonlinear dynamical systems.
A Networked Meta-Population Epidemic Model with Population Flow and Its Application to the Prediction of the COVID-19 Pandemic
Authors: Xue Dong , Liu Naichao , Chen Xinyi , Liu Fangzhou
Published: July 2024

This article addresses the crucial issues of how asymptomatic individuals and population movements influence the spread of epidemics. Specifically, a discrete-time networked Susceptible-Asymptomatic-Infected-Recovered (SAIR) model that integrates population flow is introduced to investigate the dynamics of epidemic transmission among individuals. In contrast to existing data-driven system identification approaches that identify the network structure or system parameters separately, a joint estimation framework is developed in this study. The joint framework incorporates historical measurements and enables the simultaneous estimation of transmission topology and epidemic factors. The use of the joint estimation scheme reduces the estimation error. The stability of equilibria and convergence behaviors of proposed dynamics are then analyzed. Furthermore, the sensitivity of the proposed model to population movements is evaluated in terms of the basic reproduction number. This article also rigorously investigates the effectiveness of non-pharmaceutical interventions via distributively controlling population flow in curbing virus transmission. It is found that the population flow control strategy reduces the number of infections during the epidemic.
On the Interplay between Deadline-Constrained Traffic and the Number of Allowed Retransmissions in Random Access Networks
Authors: Nomikos Nikolaos , Charalambous Themistoklis , Wichman Risto , Pignolet Yvonne-Anne , Pappas Nikolaos
Published: July 2024

In this paper, a network comprising wireless devices equipped with buffers transmitting deadline-constrained data packets over a slotted-ALOHA random-access channel is studied. Although communication protocols facilitating retransmissions increase reliability, a packet awaiting transmission from the queue experiences delays. Thus, packets with time constraints might be dropped before being successfully transmitted, while at the same time causing the queue size of the buffer to increase. To understand the trade-off between reliability and delays that might lead to packet drops due to deadline-constrained bursty traffic with retransmissions, the scenario of a wireless network utilizing a slotted-ALOHA random-access channel is investigated. The main focus is to reveal the trade-off between the number of retransmissions and the packet deadline as a function of the arrival rate. Towards this end, analysis of the system is performed by means of discrete-time Markov chains. Two scenarios are studied: (i) the collision channel model (in which a receiver can decode only when a single packet is transmitted), and (ii) the case for which receivers have multi-packet reception capabilities. A performance evaluation for a user with different transmit probabilities and number of retransmissions is conducted. We are able to determine numerically the optimal probability of transmissions and the number of retransmissions, given the packet arrival rate and the packet deadline. Furthermore, we highlight the impact of transmit probability and the number of retransmissions on the average drop rate and throughput.
The Threefold Role of the University in Fostering the Energy Transition: The Case of Bologna and Its Cesena Campus
Authors: Boeri Andrea , Turillazzi Beatrice , Sabatini Francesca , Sassenou Louise-Nour , Manella Gabriele
Published: July 2024

As acceleration toward the transition to a carbon-neutral energy production becomes an urgent imperative, universities are called to play a multifaceted role: to produce knowledge and cutting-edge research for the pursuit of energy transition; to transform infrastructures to promote circular economy practices and a more sustainable use of their building stock; and to promote energy citizenship through formal and informal education. The authors aim to move from these considerations to critically present some actions and programs in education, research, and campus operations in which the University of Bologna is engaged. The first part presents an overview of the role of universities in this transition, with a focus on the UI GreenMetric international standard for assessing the different dimensions of sustainability. In the core section, an empirical focus is provided on Bologna and its Cesena campus through three directions: the University’s multicampus sustainable strategy (campus operations), the relevant research–action projects on energy justice and the energy transition (research), and the EN-ACTION project to foster energy citizenship and behavioral change in students and citizens (education). This study concludes that the comprehensive approach of the University of Bologna in integrating sustainability into its operations, education, and research while fostering student engagement in energy citizenship, provides a replicable model for other institutions. It highlights the need for consistent and ongoing support to ensure the long-term impact and effectiveness of sustainability initiatives. The integration of social components and engagement with civil society is crucial for fostering a collective behavioral shift toward low-carbon systems, which can be further supported by interdisciplinary and transdisciplinary research approaches.
Development of Energy Poverty and Its Solutions through the Use of Renewables: The EU Case with a Focus on Slovakia
Authors: Taušová Marcela , Domaracká Lucia , Čulková Katarína , Tauš Peter , Kaňuch Pavol
Published: July 2024

The problem of energy poverty (EP), when energy becomes unaffordable for some population groups, is not only a problem for developing countries, but this phenomenon is appearing more and more often in European countries. In Europe, it is estimated that 50 to 125 million people are living in energy poverty. We hear more and more about energy poverty in connection with the current energy crisis and rising energy prices, but also because of insufficient renewable use. Due to increasing energy prices, we are increasingly hearing about the deepening energy poverty in Slovakia. This study aims to evaluate the development of energy poverty in Slovakia compared to other EU countries. The situation is studied from the view of the number of heating and cooling days, the percentage of the population that cannot maintain adequate heat at home, the percentage of the population that lacks heat, and the percentage of residents without enough heat. During the research, we used distribution analysis, trend analysis, analysis of variance, and one-way analysis. The main results show that the heating degree days (HDD) index recorded a decrease, the cooling degree days (CDD) index recorded an increase, and energy poverty is most obvious in a low-income group of inhabitants, having shortage of heat, when renewable energy sources (RES) use contributes to the mitigation of energy poverty. Solving the unfavorable situation of energy poverty is possible by increasing the share of renewables used in the gross final energy consumption for heating and cooling, primarily in residential buildings. The results provide information for policymakers regarding the triple bottom line approach (people, planet, and profit).
Performance Assessment of an Integrated Low-Approach Low-Temperature Open Cooling Tower with Radiant Cooling and Displacement Ventilation for Space Conditioning in Temperate Climates
Authors: Nasrabadi Mehdi , Finn Donal
Published: July 2024

Cooling towers, by producing chilled water and by integration with radiant and displacement cooling systems, offer a possible alternative method for space conditioning of office buildings in temperate climates. This present study examines the operational feasibility of a cooling tower in conjunction with a radiant and displacement ventilation cooling system for office conditioning in four temperate climates. The climates are: cool and semi-humid (Birmingham, UK), cool and dry (Helsinki, FI), warm and humid (Paris, FR) and warm and dry (Prague, CZ). The system is capable of producing chilled water between 14 and 20 °C, with low approach tower temperatures (1–3 K). A mathematical model of the cooling tower system was developed and integrated with an office building energy simulation model. Using the integrated simulation model, assessment was carried out based on ASHRAE design day specifications, as well as a complete cooling seasonal analysis. Moreover, the performance of the system is benchmarked against a variable-air-volume cooling system. Energy savings for the system when benchmarked against a variable-air-volume air conditioning system, where the chiller COP (coefficient of performance) varies from 2.75 to 6.5, were 62% to 37% in Paris, 56% to 30% in Prague, 52% to 28% in Helsinki and 45% to 13% in Birmingham, respectively.
A Comparative Analysis of Data Source’s Impact on Renewable Energy Scenario Assessment—The Example of Ground-Mounted Photovoltaics in Germany
Authors: Fakharizadehshirazi Elham , Rösch Christine
Published: July 2024

The German government aims to convert its energy system to renewable energy by 2045. This requires a comprehensive understanding of land eligibility for renewables, particularly land-intensive ground-mounted photovoltaics (GM-PV). Federal states must set aside at least 2% of their land for renewable energy. This target value was derived using a top-down energy demand approach. Georeferenced land use data can be used to make bottom-up estimates. This study investigates how the choice of data source influences the bottom-up evaluation of land eligibility for GM-PV installations in Germany. This study evaluates the quality of data sources and their applicability for GM-PV scenario assessment by comparing the official data source Basis-DLM as the reference with the open-access data sources OpenStreetMap (OSM), Corine Land Cover (CLC), and Copernicus Emergency Management Service (CEMS). The intersection over union (IoU) and Matthews correlation coefficient (MCC) methods were used to analyse the differences in land use and eligibility due to the quality of the data sources and to compare their accuracy. The study’s results show the crucial role of data source selection in estimating the potential for GM-PV in Germany. The results indicate that open-access data overestimate land eligibility by 4.0% to 4.5% compared to the official Basis-DLM data. Spatial similarities and discrepancies between the OSM, CEMS CLC, and Basis-DLM land uses were identified. The CLC data exhibit higher consistency with Basis-DLM. These findings emphasise the importance of selecting the appropriate data source depending on the purpose and the use of official data sources for accurate and spatially differentiated decision-making and project planning at different scales. Open-access data sources can be applied for initial orientation and large-scale rough assessment as they balance data accuracy and accessibility.
Bioluminescence Inhibition Bioassay for Estimation of Snow Cover in Urbanised Areas within Boreal Forests of Krasnoyarsk City
Authors: Rimashevskaya Anastasia A. , Muchkina Elena Y. , Sutormin Oleg S. , Chuyashenko Dmitry E. , Gareev Arsen R. , Tikhnenko Svetlana A. , Rimatskaya Nadezhda V. , Kratasyuk Valentina A.
Published: July 2024

It has been proposed that the level of air pollution in a city should be estimated based on the accumulation of pollutants in the snow cover of urban forests. This study presents a bioluminescence method for estimating the extent of snow cover pollution in the urbanised areas of boreal forests in Krasnoyarsk city. A bioluminescent assay involving NAD(P)H:FMN oxidoreductase (Red) and luciferase with luminous bacteria (BLuc) was employed to measure the concentrations of six heavy metals (As, Cd, Zn, Co, Hg, and Pb) in the snow cover. The tested snow samples demonstrated a correlation between the reduced activity of the enzyme system and variations in Cd concentration. Furthermore, the research indicated that the period of unfavourable meteorological conditions in Krasnoyarsk city resulted in a notable decline in the activity of the BLuc–Red enzyme system, which may be associated with elevated air pollution levels. This study underscores the potential of the bioluminescence method for monitoring environmental pollution in urban forested areas.
Comparison of Algorithms and Optimal Feature Combinations for Identifying Forest Type in Subtropical Forests Using GF-2 and UAV Multispectral Images
Authors: He Guowei , Li Shun , Huang Chao , Xu Shi , Li Yang , Jiang Zijun , Xu Jiashuang , Yang Funian , Wan Wei , Zou Qin , Zhang Mi , Feng Yan , He Guoqing
Published: July 2024

The composition and spatial distribution of tree species are pivotal for biodiversity conservation, ecosystem productivity, and carbon sequestration. However, the accurate classification of tree species in subtropical forests remains a formidable challenge due to their complex canopy structures and dense vegetation. This study addresses these challenges within the Jiangxi Lushan National Nature Reserve by leveraging high-resolution GF-2 remote sensing imagery and UAV multispectral images collected in 2018 and 2022. We extracted spectral, texture, vegetation indices, geometric, and topographic features to devise 12 classification schemes. Utilizing an object-oriented approach, we employed three machine learning algorithms—Random Forest (RF), k-Nearest Neighbor (KNN), and Classification and Regression Tree (CART)—to identify 12 forest types in these regions. Our findings indicate that all three algorithms were effective in identifying forest type in subtropical forests, and the optimal overall accuracy (OA) was more than 72%; RF outperformed KNN and CART; S12 based on feature selection was the optimal feature combination scheme; and the combination of RF and Scheme S12 (S12) yielded the highest classification accuracy, with OA and Kappa coefficients for 2018-RF-S12 of 90.33% and 0.82 and OA and Kappa coefficients for 2022-RF-S12 of 89.59% and 0.81. This study underscores the utility of combining multiple feature types and feature selection for enhanced forest type recognition, noting that topographic features significantly improved accuracy, whereas geometric features detracted from it. Altitude emerged as the most influential characteristic, alongside significant variables such as the Normalized Difference Greenness Index (NDVI) and the mean value of reflectance in the blue band of the GF-2 image (Mean_B). Species such as Masson pine, shrub, and moso bamboo were accurately classified, with the optimal F1-Scores surpassing 89.50%. Notably, a shift from single-species to mixed-species stands was observed over the study period, enhancing ecological diversity and stability. These results highlight the effectiveness of GF-2 imagery for refined, large-scale forest-type identification and dynamic diversity monitoring in complex subtropical forests.