bluuebunny/crossref_metadata_2025 huggingface dataset:
Low CDKN1B Expression Associated with Reduced CD8+ T Lymphocytes Predicts Poor Outcome in Breast Cancer in a Machine Learning Analysis
Authors: Kim Hyung-Suk , Noh Yung-Kyun , Min Kyueng-Whan , Kim Dong-Hoon
Published: December 2023

The cyclin-dependent kinase inhibitor 1B (CDKN1B) gene, which encodes the p27Kip1 protein, is important in regulating the cell cycle process and cell proliferation. Its role in breast cancer prognosis is controversial. We evaluated the significance and predictive role of CDKN1B expression in breast cancer prognosis. We investigated the clinicopathologic factors, survival rates, immune cells, gene sets, and prognostic models according to CDKN1B expression in 3794 breast cancer patients. We performed gene set enrichment analysis (GSEA), in silico cytometry, pathway network analyses, gradient boosting machine (GBM) learning, and in vitro drug screening. High CDKN1B expression levels in breast cancer correlated with high lymphocyte infiltration signature scores and increased CD8+ T cells, both of which were associated with improved prognosis in breast cancer. which were associated with a better prognosis. CDKN1B expression was associated with gene sets for the upregulation of T-cell receptor signaling pathways and downregulation of CD8+ T cells. Pathway network analysis revealed a direct link between CDKN1B and the pathway involved in the positive regulation of the protein catabolic process pathway. In addition, an indirect link was identified between CDKN1B and the T-cell receptor signaling pathway. In in vitro drug screening, BMS-345541 demonstrated efficacy as a therapeutic targeting of CDKN1B, effectively impeding the growth of breast cancer cells characterized by low CDKN1B expression. The inclusion of CDKN1B expression in GBM models increased the accuracy of survival predictions. CDKN1B expression plays a significant role in breast cancer progression, implying that targeting CDKN1B might be a promising strategy for treating breast cancer.
Does FDI Impact the Economic Growth of BRICS Economies? Evidence from Bayesian VAR
Authors: Malik Avisha , Sah Ash Narayan
Published: December 2023

This paper examines the dynamic relationship between foreign direct investment (FDI), economic growth, and trade openness in BRICS countries. Our research aims to address a significant gap in the literature by focusing on this crucial group of emerging nations, given their substantial contribution to the global economy. Annual data for these economies from 1991 to 2020 were collected from various secondary sources. This study employed the Bayesian VAR framework to investigate the panel data. The Pedroni residual cointegration test was used to check the existence of a long-run relationship between FDI and economic growth. The results provided evidence that foreign direct investment (FDI) does exhibit a substantial correlation with economic growth in the short run. However, no long-run relationship was found in the case of BRICS economies. This research contributes to methodological innovation by introducing the Bayesian VAR framework, offering a deeper understanding of the dynamic interactions among these key variables. The incorporation of this framework yields estimates that are both stable and reliable, which is certainly a novelty of this paper. The findings of this study have implications suggesting that policymakers from these emerging economies should establish mechanisms that will monitor the short-term impacts of FDI and adjust policies accordingly to maximize economic gains. The government should tailor policies to the specific circumstances of each country for sustainable economic development.
Preference for Animals: A Comparison of First-Time and Repeat Visitors
Authors: Guo Yulei , Fennell David
Published: December 2023

Wildlife tourism is one of the strongest-performing sectors in the global tourism market. While tourists’ preferences for and affection towards animals are a cornerstone of the industry, a better understanding of how experiences, including animal–tourist encounters and visitation frequency, influence visitors’ animal preferences is required. Through a comparison of preferences among first-time and repeat visitors of four species (giant panda “Ailuropoda melanoleuca”, red panda “Ailurus fulgens”, peafowl “Pavo cristatus”, and swan “Cygnus”), both before and after animal encounters at the Chengdu Research Base of Giant Panda Breeding (Panda Base), the results show that different species elicit varied and, at times, contrasting tourist preferences. As a result, animal preferences in wildlife tourism can vary based on different stages of visitation. Highlighting this dynamic relationship between animal preferences and visitation experiences is further elucidated through consumer learning theory and lively capital. The outcomes of this study contribute to a deeper grasp of human–animal interactions and have broader implications for the development of conservation programs in captive wildlife venues.
Correction: Belchior et al. Repair Kinetics of DSB-Foci Induced by Proton and α-Particle Microbeams of Different Energies. Life 2022, 12, 2040
Authors: Belchior Ana , Canhoto João F. , Giesen Ulrich , Langner Frank , Rabus Hans , Schulte Reinhard
Published: December 2023

In the original publication [...]
What Does Sarcopenia Have to Do with Nonalcoholic Fatty Liver Disease?
Authors: Ferenc Katarzyna , Jarmakiewicz-Czaja Sara , Filip Rafał
Published: December 2023

Nonalcoholic fatty liver disease (NAFLD) is one of the most common causes of chronic liver disease. As the second stage of developing steatosis, nonalcoholic hepatitis (NASH) carries the risk of fibrosis, cirrhosis, and hepatocellular carcinoma. Sarcopenia is defined as a condition characterized by a decrease in muscle mass and functional decline. Both NAFLD and sarcopenia are global problems. The pathophysiological mechanisms that link the two entities of the disease are insulin resistance, inflammation, nutritional deficiencies, impairment of myostatin and adiponectin, or physical inactivity. Furthermore, disorders of the gut-liver axis appear to induce the process of developing NAFLD and sarcopenia. The correlations between NAFLD and sarcopenia appear to be bidirectional, so the main objective of the review was to determine the cause-and-effect relationship between the two diseases.
Comparative Effects on Using Bilberry Leaves in Broiler Diet Reared under Thermoneutral Conditions vs. Heat Stress on Performance, Health Status and Gut Microbiota
Authors: Saracila Mihaela , Untea Arabela Elena , Varzaru Iulia , Panaite Tatiana Dumitra , Vlaicu Petru Alexandru
Published: December 2023

The study aims to investigate the impact of dietary bilberry leaves on the performance, health status, and gut microbiota of broilers reared in both thermoneutral conditions and under heat stress. Sixty Cobb 500 broiler chicks were divided into two groups (C-TN, BL-TN) and reared in thermoneutral conditions for the first trial. For the second trial, two other groups (C-HS and BL-HS) were reared in heat stress (32 °C), with 30 chickens in each group. The experimental diets were supplemented with 1% bilberry leaves compared to the control diets. The broilers fed a diet with bilberry leaves had lower levels of cholesterol compared to the control birds. At the end of the experiment, six broilers per group were slaughtered, and intestinal contents were collected for bacteriological analyses. The results revealed that bilberry leaves increased body weight and average daily feed intake in the BL-TN group compared to the C-HS group. However, the broilers fed a bilberry leaves diet and reared in heat stress had a significantly lower average daily feed intake and average daily weight gain than the C-TN group. Additionally, the number of staphylococci colonies decreased significantly in the group fed with a BL-supplemented diet and reared in TN compared to C-TN, while lactobacilli increased significantly in BL-TN compared to C-TN. In summary, bilberry leaves can be used as a natural supplement in a broiler’s diet to regulate serum cholesterol in heat stress and maintain the health of intestinal microflora in thermoneutral conditions.
Platelet-Rich Plasma in Dermatology: New Insights on the Cellular Mechanism of Skin Repair and Regeneration
Authors: Manole Catalin G. , Soare Cristina , Ceafalan Laura Cristina , Voiculescu Vlad M.
Published: December 2023

The skin’s recognised functions may undergo physiological alterations due to ageing, manifesting as varying degrees of facial wrinkles, diminished tautness, density, and volume. Additionally, these functions can be disrupted (patho)physiologically through various physical and chemical injuries, including surgical trauma, accidents, or chronic conditions like ulcers associated with diabetes mellitus, venous insufficiency, or obesity. Advancements in therapeutic interventions that boost the skin’s innate regenerative abilities could significantly enhance patient care protocols. The application of Platelet-Rich Plasma (PRP) is widely recognized for its aesthetic and functional benefits to the skin. Yet, the endorsement of PRP’s advantages often borders on the dogmatic, with its efficacy commonly ascribed solely to the activation of fibroblasts by the factors contained within platelet granules. PRP therapy is a cornerstone of regenerative medicine which involves the autologous delivery of conditioned plasma enriched by platelets. This is achieved by centrifugation, removing erythrocytes while retaining platelets and their granules. Despite its widespread use, the precise sequences of cellular activation, the specific cellular players, and the molecular machinery that drive PRP-facilitated healing are still enigmatic. There is still a paucity of definitive and robust studies elucidating these mechanisms. In recent years, telocytes (TCs)—a unique dermal cell population—have shown promising potential for tissue regeneration in various organs, including the dermis. TCs’ participation in neo-angiogenesis, akin to that attributed to PRP, and their role in tissue remodelling and repair processes within the interstitia of several organs (including the dermis), offer intriguing insights. Their potential to contribute to, or possibly orchestrate, the skin regeneration process following PRP treatment has elicited considerable interest. Therefore, pursuing a comprehensive understanding of the cellular and molecular mechanisms at work, particularly those involving TCs, their temporal involvement in structural recovery following injury, and the interconnected biological events in skin wound healing and regeneration represents a compelling field of study.
Colloid Chemistry of Fullerene Solutions: Aggregation and Coagulation
Authors: Mchedlov-Petrossyan Nikolay O. , Marfunin Mykyta O. , Kriklya Nika N.
Published: December 2023

This review article is devoted to the colloidal properties of fullerene solutions. According to generally accepted understandings, all solvents in relations to fullerenes are divided into “good”, “poor”, and “reactive”. We have consistently considered the state of fullerenes in these systems. In “good”, predominantly non-polar aromatic solvents and CS2, non-equilibrium dissolution methods lead to the formation of colloidal aggregates, whereas the utilization of equilibrium methods results in the formation of molecular solutions. The latter, however, have some unusual properties; new results considered in this review confirm previously expressed ideas about colloidal properties of these solutions. In “poor” (polar) solvents, lyophobic colloidal systems appear. Both “bottom-up” and “top-down” methods of preparation are well documented in the literature. However, N-methylpyrrolidine-2-one, DMSO, and DMF dissolve fullerenes quite easily and with less energy consumption. These solvents can be considered a subset of “poor” solvents that have some features of being “reactive” at the expense of basic properties. New data confirm that hydrosols of fullerenes are typical hydrophobic colloids that obey the Schulze–Hardy rule and other regularities in the presence of electrolytes. Organosols in acetonitrile and methanol are much less stable with respect to the effects of electrolytes. This allows us to assume a non-DLVO stabilizing factor in the hydrosols. Accordingly, a new estimate of the Hamaker constant of fullerene–fullerene interaction is proposed. In DMSO and DMF, the coagulation of fullerene sols is hindered due to strong solvation with these basic solvents.
Multiple Control Policy in Unreliable Two-Phase Bulk Queueing System with Active Bernoulli Feedback and Vacation
Authors: Niranjan S. P. , Devi Latha S. , Mahdal Miroslav , Karthik Krishnasamy
Published: December 2023

In this paper, a bulk arrival and two-phase bulk service with active Bernoulli feedback, vacation, and breakdown is considered. The server provides service in two phases as mandatory according to the general bulk service rule, with minimum bulk size ′a′ and maximum bulk size ′b′. In the first essential service (FES) completion epoch, if the server fails, with probability ′δ′, then the renewal of the service station is considered. On the other hand, if there is no server failure, with a probability ′1−δ′, then the server switches to a second essential service (SES) in succession. A customer who requires further service as feedback is given priority, and they join the head of the queue with probability β. On the contrary, a customer who does not require feedback leaves the system with a probability ′1−β′. If the queue length is less than ′a′ after SES, the server may leave for a single vacation with probability ′1−β′. When the server finds an inadequate number of customers in the queue after vacation completion, the server becomes dormant. After vacation completion, the server requires some time to start service, which is attained by including setup time. The setup time is initiated only when the queue length is at least ′a′. Even after setup time completion, the service process begins only with a queue length ‘N’ (N > b). The novelty of this paper is that it introduces an essential two-phase bulk service, immediate Bernoulli feedback for customers, and renewal service time of the first essential service for the bulk arrival and bulk service queueing model. We aim to develop a model that investigates the probability-generating function of the queue size at any time. Additionally, we analyzed various performance characteristics using numerical examples to demonstrate the model’s effectiveness. An optimum cost analysis was also carried out to minimize the total average cost with appropriate practical applications in existing data transmission and data processing in LTE-A networks using the DRX mechanism.
Hybrid Deep Learning and Sensitivity Operator-Based Algorithm for Identification of Localized Emission Sources
Authors: Penenko Alexey , Emelyanov Mikhail , Rusin Evgeny , Tsybenova Erjena , Shablyko Vasily
Published: December 2023

Hybrid approaches combining machine learning with traditional inverse problem solution methods represent a promising direction for the further development of inverse modeling algorithms. The paper proposes an approach to emission source identification from measurement data for advection–diffusion–reaction models. The approach combines general-type source identification and post-processing refinement: first, emission source identification by measurement data is carried out by a sensitivity operator-based algorithm, and then refinement is done by incorporating a priori information about unknown sources. A general-type distributed emission source identified at the first stage is transformed into a localized source consisting of multiple point-wise sources. The second, refinement stage consists of two steps: point-wise source localization and emission rate estimation. Emission source localization is carried out using deep learning with convolutional neural networks. Training samples are generated using a sensitivity operator obtained at the source identification stage. The algorithm was tested in regional remote sensing emission source identification scenarios for the Lake Baikal region and was able to refine the emission source reconstruction results. Hence, the aggregates used in traditional inverse problem solution algorithms can be successfully applied within machine learning frameworks to produce hybrid algorithms.
Physical-Unclonable-Function-Based Lightweight Three-Factor Authentication for Multiserver Architectures
Authors: Xie Qi , Zhao Yuanyuan
Published: December 2023

To support more complex and robust online services, enterprise-class applications prefer to interconnect multiple servers as the pedestal to enhance the system’s interoperability. However, the multiserver architecture always struggles to reconcile the trade-off between convenience and security, leaving users exposed to a variety of network attack threats. Existing security authentication schemes based on the Chebyshev Chaotic Map for multiserver architectures cannot provide three-factor (including password, biometric feature, and smart card) security. Therefore, we propose a novel Physical-Unclonable-Function-based Lightweight Three-Factor Authentication (PUF-LTA) scheme, which can achieve three-factor security. The PUF-LTA scheme mainly includes two components: (1) PUF-assisted registration and (2) lightweight mutual authentication with one-time interaction. During the PUF-assisted registration process, to defend against side-channel attacks on smart cards, the login credentials of users are XORed with the unique identifier generated by the PUF so that the adversary cannot obtain these secret login credentials. During the lightweight mutual authentication process, we combine the Chebyshev polynomial map and symmetric encryption/decryption to negotiate the session key between users and servers, which only needs one interaction. The security performance of PUF-LTA is theoretically proved by leveraging the random oracle model. In contrast with relevant multiserver authentication schemes, PUF-LTA is more efficient and suitable for resource-constrained multiserver environments because it can ensure secure three-factor authentication and support flexible biometrics and password updates with less computation cost.
New One-Parameter Over-Dispersed Discrete Distribution and Its Application to the Nonnegative Integer-Valued Autoregressive Model of Order One
Authors: Irshad Muhammed Rasheed , Aswathy Sreedeviamma , Maya Radhakumari , Nadarajah Saralees
Published: December 2023

Count data arise in inference, modeling, prediction, anomaly detection, monitoring, resource allocation, evaluation, and performance measurement. This paper focuses on a one-parameter discrete distribution obtained by compounding the Poisson and new X-Lindley distributions. The probability-generating function, moments, skewness, kurtosis, and other properties are derived in the closed form. The maximum likelihood method, method of moments, least squares method, and weighted least squares method are used for parameter estimation. A simulation study is carried out. The proposed distribution is applied as the innovation in an INAR(1) process. The importance of the proposed model is confirmed through the analysis of two real datasets.
A Novel Approach to Modeling Incommensurate Fractional Order Systems Using Fractional Neural Networks
Authors: Kumar Meshach , Mehta Utkal , Cirrincione Giansalvo
Published: December 2023

This research explores the application of the Riemann–Liouville fractional sigmoid, briefly RLFσ, activation function in modeling the chaotic dynamics of Chua’s circuit through Multilayer Perceptron (MLP) architecture. Grounded in the context of chaotic systems, the study aims to address the limitations of conventional activation functions in capturing complex relationships within datasets. Employing a structured approach, the methods involve training MLP models with various activation functions, including RLFσ, sigmoid, swish, and proportional Caputo derivative PCσ, and subjecting them to rigorous comparative analyses. The main findings reveal that the proposed RLFσ consistently outperforms traditional counterparts, exhibiting superior accuracy, reduced Mean Squared Error, and faster convergence. Notably, the study extends its investigation to scenarios with reduced dataset sizes and network parameter reductions, demonstrating the robustness and adaptability of RLFσ. The results, supported by convergence curves and CPU training times, underscore the efficiency and practical applicability of the proposed activation function. This research contributes a new perspective on enhancing neural network architectures for system modeling, showcasing the potential of RLFσ in real-world applications.
An Out-of-Distribution Generalization Framework Based on Variational Backdoor Adjustment
Authors: Su Hang , Wang Wei
Published: December 2023

In practical applications, learning models that can perform well even when the data distribution is different from the training set are essential and meaningful. Such problems are often referred to as out-of-distribution (OOD) generalization problems. In this paper, we propose a method for OOD generalization based on causal inference. Unlike the prevalent OOD generalization methods, our approach does not require the environment labels associated with the data in the training set. We analyze the causes of distributional shifts in data from a causal modeling perspective and then propose a backdoor adjustment method based on variational inference. Finally, we constructed a unique network structure to simulate the variational inference process. The proposed variational backdoor adjustment (VBA) framework can be combined with any mainstream backbone network. In addition to theoretical derivation, we conduct experiments on different datasets to demonstrate that our method performs well in prediction accuracy and generalization gaps. Furthermore, by comparing the VBA framework with other mainstream OOD methods, we show that VBA performs better than mainstream methods.
Monitored Anesthesia Care in Minimally Invasive Spine Surgery—A Retrospective Case Series Study
Authors: Kim Hyo Jin , Park Seongho , Lim Yunhee , Bang Si Ra
Published: December 2023

Background and Objectives: Minimally invasive spine surgery (MISS) under monitored anesthesia care (MAC) has emerged as a treatment modality for spinal radiculopathy. It is essential to secure the airway and guarantee spontaneous respiration without endotracheal intubation during MISS in a prone position. Materials and Methods: To evaluate the feasibility and safety of MAC with dexmedetomidine during MISS, we retrospectively reviewed clinical cases. A retrospective review of medical records was conducted between September 2015 and June 2016. A total of 17 patients undergoing MISS were included. Vital signs were analyzed every 15 min. The depth of sedation was assessed using the bispectral index (BIS) and the frequency of rescue sedatives. Adverse events during anesthesia, including bradycardia, hypotension, respiratory depression, postoperative nausea, and vomiting, were evaluated. Results: All cases were completed without the occurrence of airway-related complications. None of the patients needed conversion to general anesthesia. The median maintenance dosage of dexmedetomidine for adequate sedation was 0.40 (IQR 0.40–0.60) mcg/kg/hr with a median loading dose of 0.70 (IQR 0.67–0.82) mcg/kg. The mean BIS during the main procedure was 76.46 ± 10.75. Rescue sedatives were administered in four cases (23.6%) with a mean of 1.5 mg intravenous midazolam. After dexmedetomidine administration, hypotension and bradycardia developed in six (35.3%) and three (17.6%) of the seventeen patients, respectively. Conclusions: MAC using dexmedetomidine is a feasible anesthetic method for MISS in a prone position. Hypotension and bradycardia should be monitored carefully during dexmedetomidine administration.
Thin Film Nanocomposite Membranes Based on Zeolitic Imidazolate Framework-8/Halloysite Nanotube Composites
Authors: Wang Yan , Duan Shaofan , Wang Huixian , Wei Can , Qin Lijuan , Dong Guanying , Zhang Yatao
Published: December 2023

Thin film nanocomposite (TFN) membranes have proven their unrivaled value, as they can combine the advantages of different materials and furnish membranes with improved selectivity and permeability. The development of TFN membranes has been severely limited by the poor dispersion of the nanoparticles and the weak adhesion between the nanoparticles and the polymer matrix. In this study, to address the poor dispersion of nanoparticles in TFN membranes, we proposed a new combination of m-ZIF-8 and m-HNTs, wherein the ZIF-8 and HNTs were modified with poly (sodium p-styrenesulfonate) to enhance their dispersion in water. Furthermore, the hydropathic properties of the membranes can be well controlled by adjusting the content of m-ZIF-8 and m-HNTs. A series of modified m-ZIF-8/m-HNT/PAN membranes were prepared to modulate the dye/salt separation performance of TFN membranes. The experimental results showed that our m-ZIF-8/m-HNT/PAN membranes can elevate the water flux significantly up to 42.6 L m−2 h−1 MPa−1, together with a high rejection of Reactive Red 49 (more than 80%). In particular, the optimized NFM-7.5 membrane that contained 7.5 mg of HNTs and 2.5 mg of ZIF-8 showed a 97.1% rejection of Reactive Red 49 and 21.3% retention of NaCl.
Numerical Study of Laser Welding of 270 μm Thick Silicon–Steel Sheets for Electrical Motors
Authors: Jung Dae Gune , Park Ji Young , Ryu Choong Mo , Hwang Jong Jin , Moon Seung Jae
Published: December 2023

In this study, the shape of laser welding parts required to develop a welding automation system was analyzed to improve the production process of thin-plate silicon–steel. During laser welding, a welding defect occurs in the welding area, resulting in beads. This can be measured and analyzed through computational fluid dynamics. When welding thin plates with a laser, precise parameter settings are required to reduce bead height and side effects to improve weld quality. Twelve simulation cases with different laser powers and scan speeds were carried out to compare bead heights. We discussed ways to improve the productivity of electrical steel sheets by applying data collected through simulations of a laser welding automation system.
Review of RF Device Behavior Model: Measurement Techniques, Applications, and Challenges
Authors: Li Haode , Su Jiangtao , Wang Ruijin , Liu Zhenyu , Xu Mengmeng
Published: December 2023

This review presents a concise overview of RF (radio frequency) power transistor behavior models, which is crucial for optimizing RF performance in high-frequency applications like wireless communication, radar, and satellites. The paper highlights the significance of accurate modeling in understanding transistor behavior and traces the evolution of behavior modeling techniques. Different behavior modeling strategies, such as LUT (look-up table) based models, polynomial equation-based models, and machine learning based models, are discussed along with their unique characteristics and modeling challenges. The review explores the difference between behavior models and the conventional empirical or physics-based modeling approaches, addressing the challenges of the accurate characterization of transistors at high frequencies and power levels. This paper concludes with an outlook of emerging trends, such as physical models combined with behavior models, shaping the future of RF power transistor modeling for more efficient communication systems.
A Single Oscillator-Excited Piezoelectric Actuator with Internal Contact Teeth
Authors: Fang Die , Wen Zhiyi , Geng Zhixin , Hu Xiaopin , Kaswango Leon , Cao Jia , Li Xiaoniu , Wu Dawei
Published: December 2023

The tail rotor of a helicopter, a crucial component, traditionally relies on a complex drive mode involving reducers and transmission gears. This conventional setup, with its lengthy transmission chain and numerous components, hinders miniaturization efforts. In response to this challenge, our paper presents a novel piezoelectric drive approach. Our objective was to suggest an innovative design capable of minimizing the components involved in the tail rotor drive. This design can be adjusted in size according to specific requirements and is effective up to a specified speed. Moreover, it facilitates the process of miniaturization and integration. The piezoelectric actuator’s stator comprises an ultrasonic amplitude transformer, a ring, and three drive teeth. Utilizing the rod-like structure of the tail brace, the actuator is simplified by adhering ceramic sheets to it. The rotary piezoelectric actuator combines the first longitudinal mode of a rod with torus bending modes. The drive teeth then amplify the ring’s displacement, facilitating rotor rotation. The resonant frequency and modal shape of the actuator were determined using the finite element method. Furthermore, an investigation was conducted to analyze the influence of the drive teeth positioning on the motion trajectory at the contact point. Theoretically, we infer that the declination angle of the drive tooth is a crucial parameter for achieving high speeds. To test our idea, we built three prototype stators with different drive tooth declination angles. Our actuator stands out for its cost-effectiveness, structural simplicity, compatibility with harmonic signals, and ease of miniaturization. It can be considered for the drive of the tail rotor of a microhelicopter.
Simulating an Integrated Photonic Image Classifier for Diffractive Neural Networks
Authors: Sheng Huayi , Nisar Muhammad Shemyal
Published: December 2023

The slowdown of Moore’s law and the existence of the “von Neumann bottleneck” has led to electronic-based computing systems under von Neumann’s architecture being unable to meet the fast-growing demand for artificial intelligence computing. However, all-optical diffractive neural networks provide a possible solution to this challenge. They can outperform conventional silicon-based electronic neural networks due to the significantly higher speed of the propagation of optical signals (≈108 m.s−1) compared to electrical signals (≈105 m.s−1), their parallelism in nature, and their low power consumption. The integrated diffractive deep neural network (ID2NN) uses an on-chip fully passive photonic approach to achieve the functionality of neural networks (matrix–vector operations) and can be fabricated via the CMOS process, which is technologically more amenable to implementing an artificial intelligence processor. In this paper, we present a detailed design framework for the integrated diffractive deep neural network and corresponding silicon-on-insulator integration implementation through Python-based simulations. The performance of our proposed ID2NN was evaluated by solving image classification problems using the MNIST dataset.
Three-Dimensional Forward Modeling of Transient Electromagnetic Method Considering Induced Polarization Effect Based on Spectral Element Method
Authors: Zhang Xiaonan , Yan Liangjun , Huang Xin , Zhou Lei , Wang Xinyu , Cao Xiaoyue
Published: December 2023

The transient electromagnetic method (TEM) is widely used in the exploration of mineral, petroleum, and geothermal resources due to its sensitivity to low-resistivity bodies, limited site constraints, and strong resistance to interference. In practical applications, the TEM often uses a long wire source instead of an idealized horizontal electric dipole (HED) source as the excitation source. This is due to the complex external conditions and the relatively large distance between the receiving zone and the transmitter source. Compared to the HED, the long wire source can provide a larger excitation current, generating stronger signals to meet the requirements of a higher signal-to-noise ratio or deeper exploration. It also produces longer-duration signals, thereby providing better resolution. Additionally, for the interpretation of TEM data, three-dimensional forward modeling plays a crucial role. However, the mature traditional TEM forward method is based on a simple, sometimes inappropriate model, as it is well established that the induced polarization (IP) effect is widely present in the deep earth, especially in oil and gas reservoirs. The presence of the IP effect results in negative responses in field data that do not conform to the traditional theoretical decay law of TEM, which can significantly impact data processing and inversion results. To address this issue, a TEM forward modeling method considering the IP effect based on the spectral element method (SEM) has been developed in this study. Firstly, starting from the Helmholtz equation satisfied by the time domain electric field, we introduce the Debye model with polarization information into the forward modeling by utilizing the differential form of Ohm’s law. As a result, we derive the boundary value problem for the time domain electric field that considers the induced polarization effect. Using Gauss–Lobatto–Legendre (GLL) polynomials as the basis functions, the SEM is employed to discretize the governing equations at each time step and obtain spectral element discretization equations. Then, temporal discretization equations are derived using the second-order backward Euler formula, and the linear system of equations is solved using the Pardiso direct solver. Finally, the electromagnetic responses at any time channel are obtained via SEM interpolation and numerical integration, thereby achieving three-dimensional TEM forward modeling considering the IP effect. The results indicate that this method can effectively reflect the spatial distribution of polarizable subsurface media. It provides valuable references for studying the polarization parameters of subsurface media and performing a three-dimensional inversion of TEM data considering the induced polarization effect.
Bioleaching of Chalcopyrite by a New Strain Leptospirillum ferrodiazotrophum Ksh-L Isolated from a Dump-Bioleaching System of Kashen Copper-Molybdenum Mine
Authors: Khachatryan Anna , Vardanyan Narine , Willscher Sabine , Sevoyan Garegin , Zhang Ruiyong , Vardanyan Arevik
Published: December 2023

A new strain of Leptospirillum sp. Ksh-L was isolated from a dump-bioleaching system of the Kashen copper-molybdenum mine (South Caucasus). Ksh-L is an obligate chemolithoautotroph, capable of oxidizing ferrous iron (Fe2+). Cells are Gram-negative and vibrio- or spirillum-shaped of a 0.5–3 µm size. The optimal conditions for the growth are 35 °C and pH 1.6–1.8. Cu2+ and Zn2+ have different effects on the oxidizing ability of the Leptospirillum sp. Ksh-L culture depending on the phase of growth and concentration of Fe2+. Under the conditions of gradually increasing the concentration of copper in the medium, during 4–5 successive subculturing experiments, it was possible to obtain an adapted culture of Leptospirillum sp. Ksh-L, capable of growing in the medium in the presence of up to 400 mM Cu2+. A bioleaching experiment indicates that Ksh-L can efficiently oxidize chalcopyrite. However, the bioleaching of copper from chalcopyrite by Leptospirillum ferrodiazotropum Ksh-L increased about 1.8 times in association with At. thiooxidans ATCC 19377. Phylogenetic analysis based on 16S rRNA gene sequences (GenBank ID ON226845) shows that strain Ksh-L forms a single cluster into Group III. The strain possesses 99.59%, 99.52%, and 96.60% sequence similarity with the strains YTW-96-06, YTW-66-06, and Leptospirillum ferrodiazotrophum 5C in Group III, respectively.
Deep Structure of Epithermal Deposits in Youxi Area: Insights from CSAMT and Dual-Frequency IP Data
Authors: He Huanyin , Wang Jinrong , Wen Wu , Tian Rencong , Lin Jiansui , Huang Weiqiang , Li Yabin
Published: December 2023

Epithermal deposits represent a significant category of gold occurrences, with their subsurface structure playing a key role in reserve assessments. Fujian Province, characterized by extensive Mesozoic volcanic activities, stands out as a noteworthy region for shallow hydrothermal mineralization in China. This paper focus on the Youxi area within Fujian Province, employing the dual-frequency induced polarization method (DFIP) and controlled-source audio-frequency magnetotelluric method (CSAMT) to investigate the target ore. The DFIP results revealed predominant northeast-oriented zones with high polarizability and notable apparent resistivity. The CSAMT data were inverted using the SCS2D software. Two-dimensional resistivity profiles reveal a three-layer electrical structure, comprising subsurface banded rhyolites influenced by fault zones, intermediate-low resistivity sandstone layers, and deep-seated high-resistivity conglomerates. The resistivity gradient zones and highly polarizable locations align closely with known local faults. We interpreted these resistivity gradient zones as prospective target areas for mineralization, a hypothesis subsequently validated by drilling results. Combining geochemical analyses of epithermal gold deposits with the electrical resistivity structure, we propose an explanatory model for the mechanism of the formation of epithermal gold–silver deposits in the Youxi area. The magmatic hydrothermal fluids ascended along the fault, underwent convection-driven interaction with meteoric waters, and subsequently metasomatized the host rocks. This integrated approach provides valuable insights into the geological processes governing epithermal gold–silver deposit formation in the Youxi region.
Study on Extraction Valuable Metal Elements by Co-Roasting Coal Gangue with Coal Gasification Coarse Slag
Authors: Zhao Jincheng , Yu Tao , Zhang Huan , Zhang Yu , Ma Lanting , Li Jinling , Qu Chengtun , Wang Te
Published: December 2023

Coal gangue (CG) and coal gasification coarse slag (CGCS) possess both hazardous and resourceful attributes. The present study employed co-roasting followed by H2SO4 leaching to extract Al and Fe from CG and CGCS. The activation behavior and phase transformation mechanism during the co-roasting process were investigated through TG, XRD, FTIR, and XPS characterization analysis as well as Gibbs free energy calculation. The results demonstrate that the leaching rate of total iron (TFe) reached 79.93%, and Al3+ achieved 43.78% under the optimized experimental conditions (co-roasting process: CG/CGCS mass ratio of 8/2, 600 °C, 1 h; H2SO4 leaching process: 30 wt% H2SO4, 90 °C, 5 h, liquid to solid ratio of 5:1 mL/g). Co-roasting induced the conversion of inert kaolinite to active metakaolinite, subsequently leading to the formation of sillimanite (Al2SiO5) and hercynite (FeAl2O4). The iron phases underwent a selective transformation in the following sequence: hematite (Fe2O3) → magnetite (Fe3O4) → wustite (FeO) → ferrosilite (FeSiO3), hercynite (FeAl2O4), and fayalite (Fe2SiO4). Furthermore, we found that acid solution and leached residue both have broad application prospects. This study highlights the significant potential of co-roasting CG and CGCS for high-value utilization.
Hydrogels Based on Natural Polymers Loaded with Bentonite and/or Halloysite: Composition Impact on Spectroscopic, Thermal, and Swelling Properties
Authors: Sabadini Rodrigo César , Fernandes Mariana , Bermudez Verónica de Zea , Pawlicka Agnieszka , Silva Maria Manuela
Published: December 2023

Hydrogels are characterized by their property of absorbing and releasing a high content of water and water-based liquids; thus, they can be applied in agriculture as controlled-release water and fertilizer products. The focus of this research was efficient and low-cost natural polymer-based hydrogels obtained by crosslinking gellan gum (GGLA) and starch (ST) with acetic acid (CA) and loading them with either bentonite (BET) and/or halloysite (HAL). The hydrogels were obtained by mixing 100, 75, 50, 25, and 0 wt.% of GGLA with 0, 25, 50, 75, and 100 wt.% ST water solutions. To obtain the networks, they were crosslinked with 10, 5, and 2 wt.% of CA and loaded with 2, 5, and 10 wt.% of BET and/or HAL. The samples were analyzed by infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), their swelling in water, and the state of bound water properties. The results of these analyses point to the formation of a polymeric network with a decomposition temperature of >250 °C, and tailorable swelling properties that vary between 3 and 77, depending on the hydrogel composition. In summary, GGLA-ST-BET/HAL hydrogels are a good option for eco-friendly agriculture materials.
Gadolinium Effects on Liposome Fluidity and Size Depend on the Headgroup and Side Chain Structure of Key Mammalian Brain Lipids
Authors: Farzi Kianmehr , Issler Travis , Unruh Colin , Prenner Elmar J.
Published: December 2023

The lanthanide metal gadolinium has been used in the healthcare industry as a paramagnetic contrast agent for years. Gadolinium deposition in brain tissue and kidneys has been reported following gadolinium-based contrast agent administration to patients undergoing MRI. This study demonstrates the detrimental effects of gadolinium exposure at the level of the cell membrane. Biophysical analysis using fluorescence spectroscopy and dynamic light scattering illustrates differential interactions of gadolinium ions with key classes of brain membrane lipids, including phosphatidylcholines and sphingomyelins, as well as brain polar extracts and biomimetic brain model membranes. Electrostatic attraction to negatively charged lipids like phosphatidylserine facilitates metal complexation but zwitterionic phosphatidylcholine and sphingomyelin interaction was also significant, leading to membrane rigidification and increases in liposome size. Effects were stronger for fully saturated over monounsaturated acyl chains. The metal targets key lipid classes of brain membranes and these biophysical changes could be very detrimental in biological membranes, suggesting that the potential negative impact of gadolinium contrast agents will require more scientific attention.
Using Magnetic Micelles Combined with Carbon Fiber Ionization Mass Spectrometry for the Screening of Trace Triazine Herbicides from Aqueous Samples
Authors: Chen Chih-Wei , Yang Tzu-Ling , Chen Yu-Chie
Published: December 2023

Triazine herbicides are commonly used in agriculture to eliminate weeds. However, they can persist in the environment. In this study, we explored a new method for detecting triazine herbicides in aqueous samples. We selected two triazine herbicides, namely, prometryn and ametryn, as model herbicides. To generate magnetic probes, we mixed aqueous Gd3+ with aqueous sodium dodecyl sulfate (SDS), which created magnetic probes made of Gd3+-SDS micelles. These probes showed a trapping capacity for the model herbicides. Results indicated that the trapping capacities of our magnetic probes for ametryn and prometryn were approximately 466 and 468 nmol mg−1, respectively. The dissociation constants of our probes toward ametryn and prometryn were 2.92 × 10−5 and 1.27 × 10−5, respectively. This is the first report that the developed magnetic probes can be used to trap triazine herbicides. For detection, we used carbon fiber ionization mass spectrometry (CFI-MS), which can be used to directly detect semi-volatiles from the samples in the condensed phase. Because of the semi-volatility of triazine herbicides, the herbicides trapped by the magnetic probes can be directly analyzed by CFI-MS without any elution steps. In addition, we also demonstrated the feasibility of using our approach for detecting triazine herbicides in lake water and drinking water.
Assessment of Novel Proteins Triggering Celiac Disease via Docking-Based Approach
Authors: Atanasova Mariyana , Dimitrov Ivan , Fernandez Antonio , Moreno Javier , Koning Frits , Doytchinova Irini
Published: December 2023

Human leukocyte antigens (HLAs) are pivotal in antigen processing, presenting to CD4+ T cells, and are linked to autoimmune disease susceptibility. In celiac disease, HLA-DQ2.5 and HLA-DQ8.1 bind gluten peptides on APCs, some recognized by CD4+ T cells, prompting inflammation and tissue damage. While extensively studied experimentally, these alleles lack comprehensive in silico analysis. To explore peptide–HLA preferences, we used molecular docking on peptide libraries, deriving quantitative matrices (QMs) for evaluating amino acids at nine-residue peptide binding cores. Our findings tie specific residue preferences to peptide backbone conformations. Validating QMs on known binders and non-binders showed strong predictive power (89–94% accuracy). These QMs excel in screening protein libraries, even whole proteomes, notably reducing time and costs for celiac disease risk assessment in novel proteins. This computational approach aligns with European Food Safety Authority guidance, promising efficient screening for potential celiac disease triggers.
YTHDF1 in Tumor Cell Metabolism: An Updated Review
Authors: Rong Haichuan , Wang Danyang , Wang Yiran , Dong Chenshuang , Wang Guiling
Published: December 2023

With the advancement of research on m6A-related mechanisms in recent years, the YTHDF protein family within m6A readers has garnered significant attention. Among them, YTHDF1 serves as a pivotal member, playing a crucial role in protein translation, tumor proliferation, metabolic reprogramming of various tumor cells, and immune evasion. In addition, YTHDF1 also exerts regulatory effects on tumors through multiple signaling pathways, and numerous studies have confirmed its ability to assist in the reprogramming of the tumor cell-related metabolic processes. The focus of research on YTHDF1 has shifted in recent years from its m6A-recognition and -modification function to the molecular mechanisms by which it regulates tumor progression, particularly by exploring the regulatory factors that interact with YTHDF1 upstream and downstream. In this review, we elucidate the latest signaling pathway mechanisms of YTHDF1 in various tumor cells, with a special emphasis on its distinctive characteristics in tumor cell metabolic reprogramming. Furthermore, we summarize the latest pathological and physiological processes involving YTHDF1 in tumor cells, and analyze potential therapeutic approaches that utilize YTHDF1. We believe that YTHDF1 represents a highly promising target for future tumor treatments and a novel tumor biomarker.
Extraction of Polysaccharides from Root of Pseudostellaria heterophylla (Miq.) Pax. and the Effects of Ultrasound Treatment on Its Properties and Antioxidant and Immune Activities
Authors: Li Hangyu , Liu Ziwei , Liu Qianqian , Zhang Xinnan , Li Sheng , Tang Feng , Zhang Linzi , Yang Qian , Wang Qiran , Yang Shuyao , Huang Ling , Ba Yuwei , Du Xihui , Yang Falong , Feng Haibo
Published: December 2023

The hydrophilic polysaccharides (PS) were isolated and purified from the tuberous roots of Pseudostellaria heterophylla. The extraction process of PS from Pesudostellariae radix was optimized by single–factor experiments and orthogonal design. The extract was purified by DEAE cellulose column to obtain the pure polysaccharide PHP. Then PHP was treated with different intensities of sonication to study the effect of sonication on PHP’s characteristics and its biological activity in vitro and in vivo. The results of this study revealed that ultrasound treatment did not significantly change the properties of PHP. Further, with the increase of ultrasound intensity, PHP enhanced the proliferation and phagocytosis of macrophage RAW264.7. Meanwhile, it could also significantly improve the body’s antioxidant activity and immune function. The results of this study demonstrated that PHP has the potential as a food additive with enhanced antioxidant and immune functions, and its biological activities could be enhanced by sonication.