bluuebunny/crossref_metadata_2025 huggingface dataset:
Litchi chinensis: nutritional, functional, and nutraceutical properties
Authors: Castillo-Olvera Guillermo , Sandoval-Cortes José , Ascacio-Valdes Juan A. , Wong-Paz Jorge E. , Álvarez-Pérez Olga B. , FloresLópez María L. , Aguilar Cristóbal N.
Published: January 2025

Litchi chinensis is a tree in the Sapindaceae family. It is originally from China but grows in countries with tropical or subtropical climates. It has great commercial value because of its juiciness and fresh pulp. It is a rich source of nutrients and bioactive compounds (procyanidin type A and B, epicatechin, rutin, and quercetin). The compounds present in litchi have been reported to confer functional properties, such as antioxidant, anticancer, antimicrobial, and nutraceutical properties, and are believed to have the potential to develop new functional foods or products. This review summarizes the botanical characteristics and cultivation methods of litchis. Its nutritional composition has also been described, which includes a macronutrient and micronutrient profile; its functional properties, such as antioxidant, anti-inflammatory, and anticancer potential; and the relationship between bioactive compounds and their medicinal potential. Despite their beneficial qualities, litchi fruits face significant challenges in terms of conservation. Rapid browning of the pericarp is a major problem resulting in considerable product loss. Therefore, producers must develop sustainable strategies for the conservation and valorization of fruits and their byproducts. Therefore, it is necessary to look for innovative solutions that take advantage of the bioactive properties of litchi, which can be used to develop innovative pharmaceutical, food, or cosmetic products.

Graphical Abstract
The unbearable lightness of restricted Boltzmann machines: Theoretical insights and biological applications
Authors: di Sarra Giovanni , Bravi Barbara , Roudi Yasser
Published: January 2025

Restricted Boltzmann machines are simple yet powerful neural networks. They can be used for learning structure in data, and are used as a building block of more complex neural architectures. At the same time, their simplicity makes them easy to use, amenable to theoretical analysis, yielding interpretable models in applications. Here, we focus on reviewing the role that the activation functions, describing the input-output relationship of single neurons in RBM, play in the functionality of these models. We discuss recent theoretical results on the benefits and limitations of different activation functions. We also review applications to biological data analysis, namely neural data analysis, where RBM units are mostly taken to have sigmoid activation functions and binary units, to protein data analysis and immunology where non-binary units and non-sigmoid activation functions have recently been shown to yield important insights into the data. Finally, we discuss open problems addressing which can shed light on broader issues in neural network research.
IFN-α Neutralizing Antibodies Distinguish LADA From Early-onset Type 1 Diabetes
Authors: Amendolara Rocco , D’Onofrio Luca , Sessa Rosario Luigi , Di Giulio Stefano , Mignogna Carmen , Coraggio Lucia , Schirano Roberto , Zampetti Simona , Malandrucco Ilaria , Pozzilli Paolo , Giannini Giuseppe , Maddaloni Ernesto , Buzzetti Raffaella
Published: January 2025

Context

Autoantibodies against interferon-α (AAb-IFN-α) might be associated with the less aggressive autoimmunity in latent autoimmune diabetes in adults (LADA) compared to early-onset type 1 diabetes (T1D).

Objective

To investigate the presence and clinical relevance of the positivity to AAb-IFN-α in people with LADA compared to T1D.

Research Design and Methods

Serum levels of AAb-IFN-α isoforms were measured using a cell-based approach in 41 subjects with LADA and 90 subjects with T1D.

Outcomes

The primary and secondary outcomes were the difference between LADA and T1D in the proportion of participants testing positive for autoantibodies (AAb) against ≥2 and against 3 interferon-α (IFN-α) isoforms, respectively. The presence and levels of AAb-IFN-α were related to clinical and biochemical features of participants with LADA.

Results

Seven (17.1%) and 5 (12.2%) participants with LADA and 3 (3.3%) and 0 participants with T1D showed positivity for AAb against ≥2 and 3 IFN-α isoforms (P = .011 and P = .0025, respectively). Fasting blood glucose and hemoglobin A1c levels were numerically lower among people with LADA testing positive for AAb against ≥2 IFN-α isoforms than among those who were either negative or positive for AAb against 1 IFN-α isoform. Among LADA-positive individuals, levels of AAb-IFN-α2 isoform were inversely correlated with glutamic acid decarboxylase antibodies levels (rho = −0.513; P = .025).

Conclusion

Autoimmunity against IFN-α is peculiar to autoimmune diabetes and appears to be distinctive to its slowly progressive forms. Understanding the underlying molecular mechanisms and clinical significance of this novel autoimmunity could lead to the development of new therapeutic strategies in autoimmune diseases, advancing personalized medicine.
An Assessment of Professional Burnout within Hospital Pharmacists: A Case Study of Abu Dhabi
Authors: Mohammed Wadha , Fylan Beth , Breen Liz
Published: January 2025

Introduction Burnout is a syndrome resulting from unsuccessful stress management in the workplace, and is characterized by three dimensions: energy depletion, reduced professional efficacy, and feelings of negativism. Background Studies have confirmed that burnout causes deterioration in teamwork and job satisfaction and negatively impacts and compromises services. Many studies have examined the impact of burnout on health. Aim This cross-sectional study aimed to assess the rate of burnout among hospital pharmacists working in Sheikh Khalifa Medical City. Method The Maslach Burnout Inventory-Human Services Survey for Medical Professionals was used to assess burnout. The survey measured three subscales: emotional exhaustion, depersonalization, and personal achievement. In addition, pharmacists were asked questions regarding their demographic years of practice and qualifications. The surveys were distributed to inpatients, discharge/emergency, outpatients, and clinical pharmacies. The data were collected over two weeks and analyzed. Results Sixty-eight of the 90 pharmacists participated in this study. The response rate was 75.5%. Seventeen pharmacists were considered to have high burnout as they had both high emotional exhaustion and high depersonalization scores. Two pharmacists were considered to have moderate burnout, as they had moderate emotional exhaustion, depersonalization, and personal achievement. Only 17 pharmacists reported a low level of burnout. Conclusion The study revealed that 25% of the pharmacists had high burnout rates. Although statistically insignificant (P > 0.05), all pharmacists with high burnout were female and working in different pharmacy settings. Moreover, an additional 25% experienced low burnout, and 3% had moderate burnout levels. The remaining items were difficult to classify because they did not fit the Maslach definition of high, moderate, or low burnout. Further investigation is needed to identify the levels and causes of burnout among Sheikh Khalifa Medical City pharmacists.
Research on Vehicle Routing Problem with Time Window based on Improved Genetic Algorithm
Authors: Li Xu , Liu Zhengyan , Zhang Yan
Published: January 2025

This article conducts a detailed study on the vehicle routing problem with time window constraints. We constructed an objective function for the vehicle routing problem with time windows, established a mathematical model, and proposed an improved genetic algorithm to solve the problem. The algorithm first constructs a chromosome encoding method, designs a heuristic initialization algorithm to generate a better initial population, and determines the fitness function. During the operation of the algorithm, selection, crossover, and mutation operations are designed to generate offspring populations, enhancing the diversity of the population and avoiding premature convergence of the algorithm. Meanwhile, in order to improve the optimization and local search capabilities of genetic algorithms, this paper constructs a local search operation. Finally, the algorithm implements an elite retention strategy on the parent population and reconstructs a new population. We conducted simulation experiments on the algorithm using MATLAB and selected examples from the Solomon dataset for testing. The simulation experiment results have verified that the improved genetic algorithm is feasible and effective in solving vehicle routing problems with time windows.
Analyzing Histopathological Images for Cancer Prediction using Human Centric Learning Approaches
Authors: Babu N Hari , Enireddy Vamsidharr
Published: January 2025

Examining Histopathological images are a substantial approach for earlier cancer prediction in clinical analysis. However, the examination encounters some inefficiency; therefore, the cancer prediction process is depicted as a significant issue in medical imaging analysis. To simulate the prediction accuracy and to diminish the expert's decision-making complexity, this work proposes a novel feature extraction and selection of histopathological images by integrating deep learning and machine learning approaches. Initially, the provided input samples are pre-processed via dimensionality reduction, RGB colour analysis, and image transformation. Then, the features are extracted with the pre-trained network model like AlexNet, GoogleNet, Inception V3, and ResNet 50. Next, feature selection is done with Recursive Feature Elimination (RFE) to enhance and boost the system performance and eliminate over-fitting or under-fitting issues. The proposed model is evaluated with the key evaluation parameters like accuracy, precision and recall. At last, a non-linear Support Vector Machine ($nl-SVM$) is trained to fuse the related features and to enhance the performance outcomes. Here, an online available dataset for histology image-based cancer analysis is adopted. The observation proves that the anticipated model gives promising outcomes and better results than various prevailing approaches.
New Path Scheduling Approach for Multipath Transmission Control Protocol
Authors: Kushwah Deepika Singh , Kumar Mahesh
Published: January 2025

A popular transport layer protocol that makes extensive use of multi-path communication technology is called Multi-Path Transmission Control Protocol (MPTCP). Making use of the end-host’s multi-interface capabilities is MPTCP’s primary goal. However, the protocol’s main weakness is lower channel usage suffers from a sharp decline in throughput due to its sudden congestion window (cwnd) growth policy. Furthermore, the performance of MPTCP is significantly reduced when there are many possible channels for transmission because different wireless path parameters such as bandwidth, loss rate (due to congestion or unreliability of the wireless channel), and delay necessitate higher re-ordering at the receiver end. As a result, it causes a significant increase in buffer-blocking and needless retransmissions. Nonetheless, a few strategies that efficiently schedule and distribute the load over accessible, qualifying channels have been proposed. However, our proposed policy takes all these parameters into consideration and the performance has been improved significantly can be seen be the graphs presented in the later section of the paper.
Research on the Optimization of English-speaking Teaching Strategies based on Genetic Algorithm
Authors: Jing Yan
Published: January 2025

This exploration examines the optimization of English-speaking showing techniques through the use of genetic algorithms (GAs), particle swarm optimization (PSO), ant colony optimization (ACO), and simulated annealing (SA). By blending bits of knowledge from related work and directing analyses, it exhibits the adequacy of these optimization algorithms in upgrading language learning results. Our examinations uncover that genetic algorithms and ant colony optimization reliably outflank different algorithms concerning arrangement quality and viability in working on English-speaking capability. In particular, genetic algorithms and ant colony optimization show higher assembly velocities and produce better arrangements contrasted with particle swarm optimization and simulated annealing. Also, these algorithms show more prominent adequacy in upgrading English-speaking capability, as confirmed by significant enhancements in student execution measurements and language capability evaluations. In general, this exploration adds to propelling the talk on optimization procedures in language schooling and features the capability of computational optimization algorithms in fitting educational strategies to meet the different necessities of language students.
A Novel Deep Learning-based Classification Approach for the Detection of Heart Arrhythmias from the Electrocardiography Signal
Authors: Razzak Khan Qureshi Abdul , Patil Govinda , Bhatt Ruby , Moghe Chhaya , Pal Hemant , Tatawat Chandresh
Published: January 2025

Cardiovascular disease causes more deaths than any other cause in the globe. The present method of illness identification involves electrocardiogram (ECG) analysis, a medical monitoring gadget that captures heart activity. Regrettably, a great deal of medical resources is required to locate specialists in ECG data. Consequently, ML feature detection in ECG is rapidly gaining popularity. Human intervention is required for ”feature recognition, complex models, and lengthy training timeframes” - limitations that are inherent to these traditional approaches. Using the ”MIT-BIH Arrhythmia” database, this study presents five distinct categories of heartbeats and the efficient and effective deep-learning (DL) classification algorithms that go along with them. The five types of pulse features are classified experimentally using the wavelet self-adaptive threshold denoising method. Models such as AlexNet and CNN are employed in this dataset. For model evaluation use some performance metrics, like recall, accuracy, precision, and f1-score. The suggested Alex Net model achieves an overall classification accuracy of 99.68%, while the recommended CNN model achieves an accuracy of 99.89%. The end findings demonstrate that the suggested models outperform the current model on several performance criteria and are more efficient overall. With its accurate categorization, important medical resources are better preserved, which has a positive effect on the practice of medicine.
A Study on the Effect of Deep Reinforcement Learning in Cultivating Athlete Decision Behavior and Psychological Resilience
Authors: Song ShuYing , Qian Kun
Published: January 2025

In order to explore the relationship between the psychological resilience level and risk decision-making behavior of volleyball players, the author proposes a study on the effect of deep reinforcement learning in the cultivation of athlete decision-making behavior and psychological resilience. A survey and analysis were conducted on the psychological resilience level and risk decision-making behavior of 64 volleyball club athletes (29 males and 35 females) using the Psychological Resilience Inventory (PPI-A) and Sports Scenario Risk Decision Questionnaire. Construct a random forest regression model based on questionnaire data. The results indicate that there is a significant difference in risk decision-making behavior between athletes with high and low levels of psychological resilience in terms of benefits and losses =4.700,P=0.017,=22.065,P=0.000; There is a significant difference in risk decision-making behavior between athletes with high and low levels of psychological resilience when risk preference loss occurs =4.351,P=0.024, and in the context of positive and negative framing effects, the level of psychological resilience has no significant impact on decision-making behavior. The risk decision-making behavior of volleyball players is influenced by the framing effect, with negative framing and preference loss resulting in more risky behavior and a preference reversal; The level of psychological resilience affects the risk decision-making behavior of athletes in stressful situations, and athletes with high levels of psychological resilience have more adventurous behaviors.
IoT Enabled Smart Agriculture System for Detection and Classification of Tomato and Brinjal Plant Leaves Disease
Authors: Kasera Rohit Kumar , Swarnali Nath  , Das Bikash , Aniket Kumar  , Acharjee Tapodhir
Published: January 2025

Internet of Things (IoT) assisted smart farming techniques are gradually being used efficiently for identification and classification of vegetable plant diseases. Detection and classification of diseases in these plant families like Solanaceae are still problematic using DCNN due to variations in environmental conditions, genome variation, type of disease, etc. In this paper, two methods for spotting and diagnosing diseases of brinjal and tomato plants leaves named as Optimal Environmental Traversing Alert (OETA) and Optimum diagnosis of Solanaceae leaf diseases (ODSLD) respectively have been proposed. The OETA machine learning (ML) based method is used first to detect the disease, and then the ODSLD deep convolutional neural networks (DCNN) method is used to classify it. An analysis of the proposed method experiments showed that OETA disease detection for brinjal plant (eggplants) was 97.81 percent and for tomato plants was 99.03 percent. For disease classification by ODSLD method, the VGG-16 for brinjal plant and ResNet-50 for tomato plants outperformed other existing DCNN computer vision methods.
Research on the Analysis of students’ English Learning Behavior and Personalized Recommendation Algorithm based on Machine learning
Authors: Yang Qiujuan , Zhang Jiaxiao
Published: January 2025

The goal of this study is to create a personalized recommendation system for English learning resources by analysing students’ English learning behaviors using a Generalized Regression Neural Network (GRNN). For efficient language acquisition, tailored educational support is essential due to the diversity of students’ linguistic backgrounds and learning demands. Performance ratings, personal preferences, and the amount of time students spent on various content categories were among the data gathered for this study on how students interacted with English language learning materials. Our initial analysis of the patterns and discrepancies in the learning behaviors of the pupils involved the use of the GRNN model. Strong insights into the correlations between various aspects and learning results were obtained by the neural network, which was especially well-suited for this investigation due to its affinity for handling non-linear interactions and its low need for preprocessing data. These observations led us to create an individual recommendation engine that recommends educational resources and activities based on each user’s learning preferences and skill level. Using a varied set of students, a controlled study was conducted to assess the efficacy of the individual suggestions. Comparing the preliminary findings to conventional, non-personalized methods of learning, efficiency in learning and student engagement have significantly improved. In addition to showcasing GRNN’s potential for educational applications, this work offers an adaptable framework for adaptive learning systems across a range of academic fields.
Liquid biopsy - a review
Authors: Rutkowska-Kawalec Weronika , Michalczuk Karolina , Fabian Dariusz , Kurowski Marek , Leszczyńska-Knaga Elżbieta , Jakubczyk Natalia , Moczydłowski Paweł , Ryglewicz Monika , Gliwa Anna , Kuczapska Karolina
Published: January 2025

Introduction and objective:Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide. Early detection is crucial for better outcomes. Traditional diagnostic methods, such as imaging and biopsies, often fail to detect HCC in early stages. Liquid biopsy, based on circulating free DNA (cfDNA) analysis, offers a promising, non-invasive approach, allowing frequent testing, addressing tumor heterogeneity, and reducing costs.
Review methods:This article's databases were accessed through the WHO website, PubMed, and Google Scholar.
A brief description of the state of knowledge:Early detection of HCC significantly improves survival. Biomarkers from cfDNA, including DNA fragment patterns, methylation markers (e.g., USP44), 5-hydroxymethylcytosine (5hmC), and digital PCR analysis, have shown potential in early-stage detection. Advanced cfDNA fragmentomics identifies tumor-specific DNA fragmentation patterns. Techniques like DELFI demonstrate high sensitivity (94%) and specificity (98%). Machine learning enhances cfDNA analysis by integrating multiple markers, improving accuracy in distinguishing cancerous from precancerous states. Combining methylation analysis with machine learning further addresses challenges of tumor heterogeneity.
Summary:Studies highlight the high sensitivity and specificity of cfDNA biomarkers for HCC diagnosis, especially in high-risk groups like individuals with cirrhosis. Integrating technologies like 5hmC analysis and machine learning enables early diagnosis and treatment monitoring. These advancements represent a transformative step in cancer diagnostics, offering effective tools to improve patient outcomes.
Building on Bibbesworth: Language, Estates Management, and the Domestic Economy of London, British Library, Ms Harley 4971
Authors: Mills Edward
Published: January 2025

Abstract: This article offers the first complete critical edition and study of the text known as Domestic Economy , a late fourteenth-century Anglo-French vocabulary and guide to household accounting found in London, British Library, MS Harley 4971, much of the content of which is ‘grafted’ from Walter de Bibbesworth’s thirteenth-century rhymed vocabulary, the Tretiz . The Domestic Economy demonstrates that the Tretiz enjoyed currency within the professional domains of later medieval England, and in the process challenges straightforward typologies of French-language didacticism in medieval England as either linguistic or practical.
Effects of tactile feedback in post-stroke hand rehabilitation on functional connectivity and cortical activation: an fNIRS study
Authors: Chen Lingling , Meng Fanyao , Huo Congcong , Shao Guangjian , Pan Guoxin , Zhang Xuemin , Zhang Simin , Li Zengyong
Published: January 2025

Stroke-induced hand motor impairments have a significant impact on the daily lives of patients. Motor rehabilitation with tactile feedback (TF) shows promise as an effective rehabilitation intervention; however, its neural mechanisms are still not fully understood. The main objective of this study was to examine the effect of tactile feedback on brain functional responses during a single hand movement session in post-stroke patients, using functional near-infrared spectroscopy (fNIRS). The changes in oxy- and deoxy-hemoglobin concentrations were recorded from the bilateral prefrontal, motor, and occipital areas in 13 post-stroke patients in the subacute recovery phase and 15 healthy controls during a hand-grasping task with TF and no-TF. The cortical activation responses, functional connectivity, and brain functional network properties were calculated to explore the specific cortical response in post-stroke patients and healthy controls during the two grasping tasks. The results showed that post-stroke patients exhibited increased hemodynamic responses in the motor cortex during grasping tasks with TF. However, brain activation in the prefrontal cortex, left sensorimotor cortex, and right premotor area was significantly lower in post-stroke patients compared to healthy controls (p < 0.05). Additionally, post-stroke patients exhibited poorer overall brain network function, with significant reductions in both clustering coefficient (p = 0.0016), reflecting local information transfer efficiency, and transitivity (p = 0.0053), representing global network integration. A significant positive correlation was observed between the clustering coefficient and grip strength metrics (r = 0.592, p = 0.033), as well as between transitivity and grip strength (r = 0.590, p = 0.034) in post-stroke patients, indicating that greater impairments were associated with reduced overall brain functional network transmission efficiency. These findings indicated that TF can modulate brain activity in areas associated with motor learning and sensorimotor integration, providing evidence for its potential as a valuable tool in stroke rehabilitation.
Access point selection based on beacon signals in optical satellite networks
Authors: Zhang Yuanjian , Zhao Yongli , Zhang Dedong , Yan Xiaodan , Wang Wei , Jing Yinji , Hua Nan , Zhang Jie
Published: January 2025

Megasatellite constellations (MSCs) represent the forefront of satellite network development, encompassing a vast network of interconnected low-Earth orbit (LEO) satellites. The satellites in MSCs will be interconnected with laser links, capitalizing on the laser’s impressive bandwidth and robust security features. This interconnectivity enables the provision of high-bandwidth and low-latency Internet services on a global scale. However, LEO satellite networks exhibit high dynamics, especially between satellite nodes and ground nodes. This poses challenges to the high-bandwidth communication capabilities and quality of service in satellite networks. In such cases, the selection of different satellite access points will significantly affect the performance of the communication. This paper proposes an access point selection algorithm that chooses access satellites based on information from the satellite’s beacon signals, achieving lower service latency and handover times. The algorithm innovatively leverages the regularity of the inter-satellite topology in large-scale satellite networks to evaluate access points, resulting in the selection of preferred access points. Simulation results show that the algorithm achieves access satellite service performance that reduces service latency by 13% and handover frequencies by 40% compared to random access satellite selection.
Optimization of digital back-propagation for coherent optical fiber communication systems using fourth-order Runge-Kutta in the interaction picture method
Authors: Xu Tianjia , Yang Aiying , Guo Peng , Yang Meng , Zhao Zhe , Wan Wenkai
Published: January 2025

The digital back-propagation (DBP) is an algorithm that can equalize the chromatic dispersion and nonlinearity in the coherent optical fiber communication system. However, the nonlinear equalization effect of traditional split-step Fourier method (SSFM)-based DBP is limited. This paper replaces the SSFM in DBP algorithm with the fourth-order Runge-Kutta in the interaction picture (RK4IP) method, and employs the Bayesian optimization algorithm (BOA) to optimize the coefficients in RK4IP-based DBP algorithm, then compares it with SSFM-based DBP algorithm, which is also optimized using BOA. The experimental results of 9×100 km standard single-mode fiber (SSMF) 20 Gbaud 16QAM transmission system demonstrate that the coefficient-optimized RK4IP (CO-RK4IP)-based DBP algorithm can achieve the maximum improvement of 0.89 dB in the Q-factor compared to the coefficient-optimized SSFM (CO-SSFM)-based DBP algorithm at equivalent complexity, proving that CO-RK4IP is an effective recursive method for DBP algorithm.
Infrared surface plasmon and hot carrier properties of topological nodal line semimetal ZrSiS
Authors: Fan Haojiang , Ma Xiangchao , Wei LinFang , Wu Xin , Liu Delian
Published: January 2025

Recently, a new plasmon mode, the nodal-line plasmon, was discovered in ZrSiS, which provides promising possibilities for plasmonics or optics. However, there remains a lack of research on the surface plasmon (SP) properties and carrier transport characteristics of ZrSiS. In this paper, we conduct an in-depth study of these properties and compare them with the traditional SP material Au. The interband contribution of the dielectric function of ZrSiS is much greater than the intraband contribution, which is opposite to the properties of traditional SP materials such as Au. In addition, it’s found that ZrSiS can generate SP in the infrared range, with the imaginary part of the dispersion relation larger than that of Au and a much shorter propagation length. This implies that ZrSiS has significant potential for generating hot carriers in the infrared range. Notably, the initial energy distribution and hot carrier transport properties indicate that the hot carriers generated by ZrSiS are concentrated in the high-energy region and exhibit good separation. Furthermore, ZrSiS can simultaneously produce long-lived hot electrons and holes with lifetimes comparable to those of Au, which is crucial for the collection and application of hot carriers. Our results not only provide theoretical analysis for understanding the surface plasmonic properties of ZrSiS but also offer important guidance for the collection and application of the carriers in ZrSiS.
Flexible multi-access scheme for indoor VLC using multiband N-dimensional CAP and a wide field-of-view white laser transmitter
Authors: Lin Xianhao , Wang ZhiChong , Zhou Yingjun , Zhang Junwen , Shen Chao , Chi Nan
Published: January 2025

Visible light communication (VLC) has emerged as a crucial technology for next-generation (6 G) communication, integrating illumination and data transmission. However, the modulation bandwidths of light-emitting diodes (LEDs) are relatively limited, which restricts communication capacity. In contrast, laser diodes (LDs) offer distinct advantages, including high luminous flux, compact size, and large modulation bandwidth. Notably, white LDs with a wide field-of-view (FOV) are particularly suitable for indoor VLC applications, as they can cover a broad range. To meet the diverse requirements of indoor access devices, we propose a multiband N-dimensional carrierless amplitude and phase (multiband N-D CAP) modulation technique. In multiband N-D CAP, N users are distributed across multiple sub-bands, where frequency division multiplexing is applied between sub-bands and code division multiplexing is adopted within each sub-band. This structure enables adaptable configurations of sub-band numbers, user counts, and data rates, providing superior flexibility and compatibility compared to traditional multiband CAP or N-D CAP techniques. In our VLC system with a wide FOV white laser transmitter, we tested four configurations for 12 users with different user distributions or data rates. Results show total data rates ranging from 3.45 Gbps to 2.75 Gbps at 1.0 m, and from 1.35 Gbps to 1.00 Gbps at 2.5 m, with an effective FOV angle of approximately 25°. These results underscore the potential of multiband N-D CAP modulation for flexible and efficient indoor VLC access.
Multi-band reconfigurable microwave photonic transceiver towards high-performance integrated radar
Authors: Shao Shuai , Wu Yilin , Xue Qiyin , Wang Hui , Yang Sigang , Chen Hongwei , Chen Minghua
Published: January 2025

As an effective approach to overcome the electronic bottlenecks of conventional electrical radars, microwave photonic radars have demonstrated significant superiority in their perception and recognition capabilities. However, trade-offs exist among the reconfigurability, signal time-bandwidth product (TBWP), linearity, and phase coherence of current photonic radars, which ultimately weaken the overall performance. To address these challenges, a photonic transceiver based on electrically assisted synchronized lasers is proposed and demonstrated, which combines high resolution and multi-band reconfigurability. Optical coherent heterodyne linear frequency-modulated (LFM) radar signal generation and photonic dechirping reception are implemented through the synchronized lasers at the transmitter and receiver, respectively. In a proof-of-concept experiment, reconfigurable LFM signals covering the L- to Ka-band with improved linearity and phase coherence are generated. Furthermore, the proposed photonic transceiver operates in the Ka-band with an ultra-large signal TBWP of 4 × 106, enabling high-resolution ranging and inverse synthetic aperture radar (ISAR) imaging. A range resolution of 1.92 cm and an imaging resolution of 1.92 cm × 1.89 cm are obtained, which require a receiver sampling rate of only 5 MSa/s. Featuring a simple structure, flexible reconfiguration, and integration compatibility, the demonstrated photonic transceiver opens new opportunities for next-generation miniaturized radar application scenarios.
Dual-function terahertz metamaterial absorber based on microfluidic structures
Authors: Ge Hongyi , Jia Keke , Jiang Yuying , Bu Yuwei , Zhang Yujie , Zhang Yuan , Sun Qingcheng
Published: January 2025

In recent years, terahertz metamaterial sensors have shown great potential in label-free biosensing; yet, the detection of high-absorption liquid samples that are sensitive to terahertz waves remains a significant challenge. In this study, a dual-function absorber capable of dynamically switching between broadband absorption and high-sensitivity sensing is proposed based on the microfluidic technology and phase change characteristics of vanadium dioxide (VO2). Compared with traditional terahertz microfluidic sensors, this structure differs in that it incorporates a VO2 film as a separation layer in the sensor cover plate and a VO2 square resonator on top. This configuration not only exhibits high-sensitivity sensing but can also function as an absorber for broadband absorption. When VO2 is in the metallic state, the structure acts as a broadband absorber with an absorption rate exceeding 90% across the 1.09–3.02 THz range. When VO2 is in the insulating state, the structure functions as a microfluidic sensor, achieving an absorption rate above 99.9% at 1.438 and 2.068 THz, with nearly perfect absorption and refractive index sensitivities of 532 and 785 GHz/RIU, respectively; the quality factor is 17.6 and 23.5, respectively, indicating excellent sensing performance. Moreover, due to the symmetry of the metal micro-structured layer and the VO2 square resonator, the device exhibits polarization insensitivity and stability at large incident angles. In summary, this structure significantly broadens the applications of traditional absorbers and sensors and holds promise for future applications in electromagnetic cloaking, energy harvesting, and biomedical detection.
Depth-gated Fourier transform to accelerate spectral recovery in visible light optical coherence tomography retinal oximetry
Authors: Nolen Stephanie L. , Wang Jingyu , Yi Ji
Published: January 2025

Visible light optical coherence tomography (VIS-OCT) provides retinal oximetry at micro-level vessels by performing spatiospectral analysis. Typical methodology involves the short-time Fourier transform (STFT), which requires computationally intensive repetitive transforms. Here we report a depth-gated Fourier transform (DGFT) method to reduce the number of transforms (and time) for spectral extraction by windowing the depth domain. The number of transforms was decreased from 13 to 3 by DGFT, nearly 6× faster in computation time than STFT. We validated DGFT for retinal oximetry in a human eye. Oxygen saturation (sO2) values matched well between STFT and DGFT (percent difference of 0.63% ± 1.10%), while the DGFT extracted spectra significantly faster than the STFT (0.15 ± 0.11 s vs 0.89 ± 0.48 s). The reported method shows potential for real-time oximetry calculation in the future.
Bidirectional synapse based on anti-resonance modulation of a photonic microring
Authors: Hao Xinmeng , Zhang Hengyu , Song Bing , Liao Cen , Tian Yuan , Li Qingjiang , Sun Zhenyuan
Published: January 2025

A synaptic device is fundamental for memory and learning functions of neural networks. In this work, we demonstrated a GST (Ge2Sb2Te5)-based microring synapse with nonvolatile reconfigurable characteristics. The device shows bidirectional weight modulation during unidirectional crystallization or amorphization of GST, simulating long-term depression (LTD) and long-term potentiation (LTP). In addition, we adopted an anti-resonance pump scheme to reduce the fluctuations in pump energy coupled into the device to less than 12%. This scheme significantly enhances the programming precision of the microring synapse, achieving 24 resolvable states over 15 cycles. This work holds promise for laying the foundation for novel, to the best of our knowledge, photonic computing architectures and provides possibilities for the implementation of vision and adaptive optical neural networks that rely on bidirectional plasticity.
Blind aberration correction for light field photography: publisher’s note
Authors: Cheng Kai , Pan Long , Lai Zhitong , Jiang Min , Xu Ya , Qi Ji , Feng Xiaohua
Published: January 2025

This publisher’s note contains a correction to Opt. Lett. 50, 209 (2025)10.1364/OL.542480.
Effectiveness of carbon dioxide cryotherapy for the treatment of cutaneous leishmaniasis: Systematic review and meta-analysis
Authors: Tilahun Zewdu Feleke , Misganaw Geremew Bisrat , Gadisa Belachew Endalamaw , Alemu Gelay Kassahun
Published: January 2025

Background

Cutaneous leishmaniasis is one of the neglected tropical diseases which is hard to treat. Carbon dioxide-based cryotherapy is a novel therapeutic option for cutaneous leishmaniasis in both developed and developing nations. This study aims to summarize the pooled evidence on the effectiveness of carbon dioxide-based cryotherapy for the treatment of cutaneous leishmaniasis.

Methods

Searches of grey literature using Google Scholar and databases including PubMed, Scopus, EMBASE, Web of Science, and Google Scholar were conducted to find studies that reported the cure rate of cryotherapy. The search, screening, data extraction, and critical evaluation were carried out by two authors, with a third acting as a tiebreaker. To locate papers, we used Medical Subject Headings (MeSH) phrases and keywords. Between May 10 and May 13, 2023, the review protocol was developed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 checklist. For the meta-analysis, STATA 17 was the statistical software used. The random effects model was employed to compile the effect estimates. Lastly, we used the funnel plot and Egger’s test to evaluate publication bias, heterogeneity, sensitivity, and subgroup analyses.

Result

Out of the 16 researches included in the review, seven papers with a total of 1,357 cases were chosen for the meta-analysis. For the treatment of cutaneous leishmaniasis, the pooled cure rate with carbon dioxide-based cryotherapy was 87.84% (95% CI: 65.92–109.77). Randomized controlled trials made up the majority of the studies that were used. The highest cure rate was seen when there were two lesions, 94.34% (95% CI:68.21–119.48), and when the size of the lesion was less than or equal to 4, 93.83% (95% CI:68.92–118.75). There was no indication of a significant publishing bias.

Conclusion

Carbon dioxide-based cryotherapy revealed a high pooled efficacy. The efficacy of the CL instances was mostly dependent on the extent of the lesion and the frequency of therapy administration. To determine if this therapy is beneficial in a routine care context, a large-scale study with a sound design is necessary.
Malian field isolates provide insight into Plasmodium malariae intra-erythrocytic development and invasion
Authors: Dao Francois , Niangaly Amadou , Sogore Fanta , Wague Mamadou , Dabitao Djeneba , Goita Siaka , Hadara Aboubacrin S. , Diakite Ousmaila , Maiga Mohamed , Maiga Fatoumata O. , Cazevieille Chantal , Cassan Cecile , Talman Arthur M. , Djimde Abdoulaye A. , Marin-Menendez Alejandro , Dembélé Laurent
Published: January 2025

Plasmodium malariae is the third most prevalent human malaria parasite species and contributes significantly to morbidity. Nevertheless, our comprehension of this parasite’s biology remains limited, primarily due to its frequent co-infections with other species and the lack of a continuous in vitro culture system. To effectively combat and eliminate this overlooked parasite, it is imperative to acquire a better understanding of this species. In this study, we embarked on an investigation of P. malariae, including exploring its clinical disease characteristics, molecular aspects of red blood cell (RBC) invasion, and host-cell preferences. We conducted our research using parasites collected from infected individuals in Mali. Our findings revealed anaemia in most of P. malariae infected participants presented, in both symptomatic and asymptomatic cases. Regarding RBC invasion, quantified by an adapted flow cytometry based method, our study indicated that none of the seven antibodies tested, against receptors known for their role in P. falciparum invasion, had any impact on the ability of P. malariae to penetrate the host cells. However, when RBCs were pre-treated with various enzymes (neuraminidase, trypsin, and chymotrypsin), we observed a significant reduction in P. malariae invasion, albeit not a complete blockade. Furthermore, in a subset of P. malariae samples, we observed the parasite’s capability to invade reticulocytes. These results suggest that P. malariae employs alternative pathways to enter RBCs of different maturities, which may differ from those used by P. falciparum.
Safety and security of journalists in Ghana: Policies and journalists’ perception of stakeholders, issues and practices
Authors: Serwornoo Michael Yao Wodui
Published: January 2025

This study examines the safety and security of journalists in Ghana, assessing their satisfaction with key media stakeholders and the state of press freedom through the United Nations Educational, Scientific and Cultural Organization’s (UNESCO) journalists’ safety indicators. Using a predominantly quantitative, integrative mixed-method approach, it surveyed 80 journalists from broadcast, print and online outlets, conducted ten in-depth interviews and analysed two policy documents. The findings reveal widespread dissatisfaction with stakeholders such as law enforcement, politicians, regulatory bodies and journalists’ associations. The independent t-test shows that the editors and reporters did not differ significantly in their assessment of their satisfaction with stakeholders in the media landscape. Only the online media journalists reported satisfaction with their management’s efforts to ensure safety. The absence of formal safety policies and the frequent closure of broadcast outlets signal a decline in press freedom. This study highlights a concerning gap between Ghana’s democratic credentials and the unsafe working conditions for journalists. Recent press freedom rankings align with these challenges, affirming UNESCO’s indicator as a predictive tool.
BIM CONTROL METHOD FOR HIDDEN QUALITY COST OF PREFABRICATED BUILDING CONSTRUCTION PROJECT
Authors: Heng Zhao , Ningning Zhana
Published: January 2025

At present, the hidden quality cost in the construction process of prefabricated building projects in China is too high. If it is not controlled, there will inevitably be a "benefit funnel". Based on the construction of cost BIM control model, the information integration platform of prefabricated construction project is designed. Utilizing the details provided regarding the model and platform, the technique of constrained machine learning is employed for managing the concealed expenses related to quality in prefabricated construction ventures. By optimizing cost control, the ultimate objective of managing expenses is achieved. The outcomes of experiments illustrate that this approach has the capability to proficiently govern the covert quality expenses linked with prefabricated construction projects. It significantly enhances the focused and efficient management of comprehensive and evolving oversight of quality-related expenses throughout the construction process.
PREVENTION AND DRAINAGE TECHNOLOGY FOR ANTI-STUCK AND DISCHARGING DURING SHIELD TUNNELING IN COMPLEX RED ROCK STRATA WITH ULTRA-LARGE DIAMETER UNDER NORMAL AND PRESSURIZED CONDITIONS
Authors: Zhang Kexin , Dong Xin , Zeng Qingcheng , Ouyang Jian , Hu Dawei , Xue Xingwei
Published: January 2025

During the construction process of shield tunneling with ultra-large diameter under normal and pressurized conditions, problems such as mud cake formation on the cutterhead, stagnation of mud in the chamber, blockage of slurry discharge chute, high cutterhead torque, and slow excavation speed are prone to occur. In severe cases, these issues can impact construction progress and pose a threat to construction safety. Taking the Guangzhou Haizhu Bay Tunnel project as a case study, this paper proposes prevention and drainage technology for anti-stuck and discharging during shield tunneling in complex red rock strata with ultra-large diameter under normal and pressurized conditions, focusing on mud slurry control, optimization of cutterhead flushing system, excavation parameter control, and cutter tool optimization.
DUST DISTRIBUTION PATTERN AND OPTIMIZATION OF TUNNEL VENTILATION SYSTEM
Authors: Zhang Xuhui , Lai Hanwen , Peng Zeren , Zhong Hengxing , Liao Yashi , Liao Jingping
Published: January 2025

This paper focuses on examining the effectiveness of a long-pressure and short-pumping ventilation system in a highway tunnel construction project in China. Utilizing computational fluid dynamics theory and ventilation system design principles, the study involves numerical simulations through finite element method to analyze dust distribution within the tunnel. The research investigates the effect of the distance of the duct from the working face and pumping ratio on dust concentration. The results indicate that optimal ventilation and dust removal occur when Lpressure set at 20m, Lpumping set at 3m, and pumping ratio is 0.7, resulting in an average dust concentration of 250mg/m3. These findings offer valuable insights for designing effective ventilation systems in tunnel construction projects, thereby enhancing dust control measures to ensure a safer working environment.
Healthy Homes for All – Designing and testing a healthy prototype for social housing
Authors: Fraser Murray , Raine Rosalind , Jewell Nicholas , Pizzo Elena , Kim Ye Ha
Published: January 2025

The project sought to answer a key research question: i.e. how can we ensure that the new housing we are providing for those on lower incomes will be safe and healthy to live in? Using a design prototype which had been initiated in previously funded research investigations, for a site in Upton Gardens in East Ham, the purpose of this Grand Challenges project was to showcase a method for how to easily and quickly model and test any proposed housing scheme using a range of readily available proprietary software. As well as testing our own design prototype and demonstrating its health and well-being benefits compared to the typical new dwellings being built currently in the UK, our project also proposes a methodological approach which could be used by all architects who are designing social/affordable housing schemes.
Access to and experiences of parental and associated leaves for university employees
Authors: Uzunalioglu Merve , Twamley Katherine
Published: January 2025

The project aimed to identify factors impacting the uptake and experiences of parental and associated leave among colleagues and to develop recommendations for improvement and future strategies.
Some Preliminary Theses on the Concept of Eco-Civilization
Authors: Foster John Bellamy
Published: January 2025

In this talk given at Peking University in October 2024, John Bellamy Foster shares ten theses describing both the roots and contemporary manifestations of the idea of ecological civilization. Relating the concept's origins in the writings of Marx and Engels to its expression today in Chinese society, Foster reveals the inherently socialist nature of eco-civilization and the necessity of a worldwide ecological revolution to shift toward sustainable human development.