bluuebunny/crossref_metadata_2025 huggingface dataset:
Identification of novel therapeutic targets for jaranol alleviating cognitive impairment in db/db mice
Authors: Qian Ye , Xu Yue , Zhang Qiuyu , Huang Chengyu , Li Hui , Gao Lin , Wu Shidi , Qi Chengyu , Zhou Xiaoyan , Wen Xiangru , Ying Changjiang
Published: May 2024

The widely used Radix Astragali (RA) has significant therapeutic effects on cognitive impairment (CI) caused by type 2 diabetes (T2DM). However, the effective active ingredients and the precise mechanism underly RA alleviation of T2DM-induced CI still require further study. In this study, we aim to elucidate whether and how jaranol, a key effective active ingredient in RA, influences CI in db/db mice. We used various online databases and Cytoscape to screen jaranol as the most active ingredient of RA in the treatment of T2DM-induced CI. The fear conditioning experiment, new object recognition (NOR) test, and Morris water maze (MWM) test were conducted to assess the improvement effect of jaranol on CI in diabetic mice. The protein-protein interaction (PPI) network, Cytoscape, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to identify key genes. The levels of AKT and caspase-3 were determined by Western blotting. The number of surviving hippocampal neurons was verified through Nissl staining. AutoDock was utilized for predicting potential binding sites between jaranol and key genes.As a result, jaranol attenuated CI in db/db mice probably through activation of PI3K-AKT signaling pathway by inhibiting cell apoptosis in hippocampus. Furthermore, A329 near the active site of AKT1 had hydrogen bond with jaranol. In conclusion, we suggest that jaranol may have therapeutic applications in T2DM-induced CI by targeting the PI3K-AKT signaling pathway directly via key sites. Our study provides alternative drugs and potential therapeutic targets for the prevention and treatment of T2DM-induced CI.
Revolutionizing Geriatric Care: Radar and Digital Twin Technology for Fall Severity Detection
Authors: Elbadrawy Abdelrahman , Abedi Hajar , Sligar Arien , Ramahi Omar M , Shaker George
Published: May 2024

In this study, we present a novel approach for fall detection, leveraging radar-based sensing systems and advanced digital twin simulations. The choice of radar technology is rooted in its capability for high-resolution detection of micro-movements and its inherent respect for individual privacy, as it does not require visual imaging. The integration of digital twins, replicating a diverse array of human physiology and fall dynamics, allows for extensive, varied, and ethical training of sophisticated machine learning algorithms without the constraints and ethical concerns of using human subjects. Our proposed methodology has led to significant advancements in the accuracy and sensitivity of detecting and assessing fall severity, especially in diverse populations and scenarios. We observed notable improvements in the system’s ability to discern subtle variations in falls, a critical factor in elderly care where such incidents can have serious health implications. Our approach not only sets a new benchmark in fall detection technology, but also demonstrates the vast potential of combining radar technology with digital simulations in medical research. This research paves the way for innovative patient monitoring solutions, offering a beacon of hope in improving seniors care and proactive health management. In this study, diverse fall scenarios were simulated under varied conditions. The correlation between the simulation and measurement results is presented. Employing convolution neural networks, we obtained an accuracy of 99.45% using simulated data and 81.25% using measured data, in detecting severity of falls. The analysis addressed various parameters distinguishing different scenarios, including fall speed and the participant’s body size.
A landscape analysis of Digital Health Technology in medical schools: preparing students for the future of health care
Authors: Boillat Thomas , Otaki Farah , Baghestani Ameneh , Zarnegar Laila , Kellett Catherine
Published: May 2024

Although Digital Health Technology is increasingly implemented in hospitals and clinics, physicians are not sufficiently equipped with the competencies needed to optimize technology utilization. Medical schools seem to be the most appropriate channel to better prepare future physicians for this development. The purpose of this research study is to investigate the extent to which top-ranked medical schools equip future physicians with the competencies necessary for them to leverage Digital Health Technology in the provision of care. This research work relied on a descriptive landscape analysis, and was composed of two phases: Phase I aimed at investigating the articulation of the direction of the selected universities and medical schools to identify any expressed inclination towards teaching innovation or Digital Health Technology. In phase II, medical schools’ websites were thoroughly analyzed to discover how innovation and Digital Health Technology are integrated in their curricula. Among the 60 medical schools that were analyzed, none mentioned any type of Digital Health Technology in their mission statements (that of the universities, in general, and medical schools, specifically). When investigating the medical schools’ curricula to figure-out how universities nurture their learners in relation to Digital Health Technology, four universities covering different Digital Health Technology areas were identified. The results of the current study shed light on the untapped potential of working towards better equipping medical students with competencies that will enable them to leverage Digital Health Technology in their future practice and in turn enhance the quality of care.
Intraligamentary anaesthesia: a possible alternative for perineural blocks in equine dentistry
Authors: Teysen Stijn
Published: May 2024

Background The injection of a local anaesthetic into the periodontal ligament (PDL) to achieve desensitisation of the pulp, periodontium and adjacent tissues, is a well-established technique in humans, especially in paediatric dentistry. The technique is commonly referred to as intraligamental or intraligamentary anaesthesia (ILA). The aims of the present publication were: (1) to provide a review of the literature, (2) to describe an ILA technique used by the authors in the field of equine dentistry, and (3) to evaluate ILA in a cadaver study in horses. Results In the clinic, we used a 27G x 35mm disposable dental needle in combination with a long-handled syringe. According to authors’ experience, high pressure is not necessary. 1.8 ml of anaesthetic solution was used. With the help of a crocodile forceps or a needle holder, the needle is directed into the PDL. The needle is inserted into the periodontal ligament until resistance is met (in general after 25–35 mm). The procedure was repeated on the mesiobuccal, mesiolingual (or -palatal), distobuccal and distolingual (or -palatal) side of the teeth. Four frozen equine cadaver heads and two fresh horse heads were used to evaluate the distribution of a local anaesthetic after an intraligamentary injection. Four cheek teeth were chosen at random on each skull. At each site of the tooth, one cartridge (1.8 ml) of black ink was manually injected. Conclusion The ILA technique is simple to use in equine dentistry to achieve desensitisation of the pulp, periodontium and adjacent tissues. The supplementary cadaver study showed spreading of the solution around apex of the root. We conclude that ILA may be an interesting alternative for perineural blocks in equine dentistry.
Physiological changes in stomata and regulation of genes involved in CAM metabolism in polyploid Agave L.
Authors: Gutierrez Benjamín Abraham Ayil , Teyer Felipe Lorenzo Sanchez , Zapata Luis Carlos Rodriguez , Pool Felipe Barredo , Garcia Victor Hugo Ramos , Ordoñez Francisco Alberto Tamayo , Ordoñez Yahaira de Jesus Tamayo , Ordoñez Maria Concepcion Tamayo
Published: May 2024

In recent years there has been growing interest in increasing plant water use efficiency (WUE) through the introduction of crassulacean acid metabolism (CAM) into C3 crops. However, this task has been hampered because the scaling of CAM to other C3 plants requires knowledge of the enzymatic and regulatory pathways underpinning this temporal CO2 pump.
Agave presents CAM metabolism, to date research aimed at knowing the physiological and morphological adaptations related to CAM metabolism, only includes a small group of species analyzed. With the aim of knowing basic aspects related to the physiological response of polyploid (2n=2x=60 to 2n=6x=180) Agave accessions, we carried out genetic and physiological studies in A. tequilana Weber, A. fourcroydes Lem., and A. angustifolia Haw. Using AFLP markers, differences in genetic variability between the polyploid accessions and their diploid counterparts were found. Analysis of expression by real-time PCR showed that the regulation of CAM in Agave is accompanied by the transcription of RbcL, PEPC and PEPCK. Monitoring of the stomatal opening during the night showed differences according to the level of ploidy of the accessions.
The genetic and physiological data obtained suggest that agave species present adaptations and flexibility in the transcriptional regulation of genes related to CAM metabolism, suggesting that some polyploid accessions of Agave L. could be more tolerant to drought and heat, adapting their CO2 exchange mechanisms according to the metabolic needs of each species of agave.
Convective turbulent mixing drives rapid upwelling along the ocean’s bottom boundary
Authors: Garabato Alberto Naveira , Spingys Carl , Castro Bieito Fernández , Couto Nicole , Drake Henri , Forryan Alexander , Ma Yuchen , Mercier Herle , Messias Marie-Jose , Ruan Xiaozhou , van Haren Hans , Voet Gunnar , Wynne-Cattanach Bethan , Ferrari Raffaele , Alford Matthew , Polzin Kurt
Published: May 2024

Deep-ocean upwelling, driven by small-scale turbulent mixing1,2, plays a central role in Earth’s climate by regulating the ocean’s capacity to sequester heat and carbon for decades to millennia3,4. Recent theoretical studies5-8 have hypothesized that this upwelling may primarily occur within a thin bottom boundary layer (BBL) adjacent to the sloping seafloor. However, little is known about the mixing processes that might drive such along-bottom upwelling, and the problem remains the subject of an enduring and vigorous debate8-11. Here, we elucidate the processes governing BBL-focussed upwelling in a typical continental-slope canyon, in which very rapid upwelling is observed12. We show that upwelling along the canyon stems from episodic cells of convective turbulent mixing up to 250 m in height, generated by tidal currents sweeping up- and down-canyon. Once per tidal cycle, these currents develop a vertical shear that conveys dense waters over slower-flowing lighter waters below, causing the dense waters to convectively mix, lighten and upwell. We argue that this upwelling mechanism is likely to be of wider representativeness, substantiating the view that deep-ocean upwelling can predominantly occur along the ocean’s sloping boundaries.
Environment-friendly Hanji cellulose paper-based humidity sensor for multifunctional applications
Authors: Amjad Mufarah , Kim Junyoung , Shin Subin , Joo Yongho , Son Jangyup
Published: May 2024

Recent advancements in sensor technology have led to the development of humidity sensors with applications in multiple fields such as agriculture, medical, food storage, and processing industries. Recently, the focus in humidity sensor research has moved towards creating sensors that are not only flexible and low-cost but also harmless to humans and eco-friendly. However, it requires clean rooms, nonbiodegradable substrates like silicon elastomers, and intricately synthetic highly toxic metallic sensing materials (based on Ti, Ru, Ni, etc.). These factors result in high costs, negative skin and environmental effects, and a substantial increase in the need for landfill space. Here, we propose Hanji cellulose paper-based humidity sensor with having rich hydrophilic and porous surface. Our Hanji humidity sensor has stable humidity sensing response close to 106 and demonstrates a linearity of R2 = 0.9912 across a relative humidity range from 7.6 to 91.8% by using just 0.3 V. In addition to its performance, Hanji humidity sensor is environment-friendly, cost-effective, naturally decomposable, and flexible, requiring only two simple fabrication steps. It shows potential applications like fingertip moisture detection and breath intensity monitoring. Further engineering and surface modifications will not only enhance its performance but also expand its potential for additional applications in the field of humidity sensing.
Metagenomic analysis reveals gut phage diversity across three mammalian models
Authors: Ma Yingfei , Yu Menghao , Chu Yunmeng , Wang Yongming , Mo Luofei , TAN Xin , Guo Shun , Yuan Shengjian
Published: May 2024

The gut virome plays a pivotal role in shaping the host’s microbiota. However, gut viruses across different mammalian models, and their connections with the human gut microbiota remain largely unknown. Here, we identified 977 high-confidence species-level viral operational taxonomic units (vOTUs) in mice (hcMGV), 12896 in pigs (hcPGV), and 1480 in cynomolgus macaques (hcCMGV) from metagenomes, respectively. Clustering these vOTUs at approximately genus level uncovered novel clades with high prevalence across animal guts (>=30%). In particular, crAss-like phages and cas-harboring jumbo phages were characterized. Comparative analysis revealed that hcCMGV had a closer relationship with hcPGV than hcMGV, despite the animal-specific characteristics, and that 55.88% hcCMGV had connections with the human microbiota. Viral functional analysis indicated a low risk in disseminating antibiotic and virulent genes. In summary, our findings shed light on the diversity of gut viruses across these three animals, contributing to future gut microbial studies using model animals.
DEM-based study on mechanical behavior and strength criterion in layered slate under triaxial compression
Authors: Yang Xiuzhu , Li Xilai , Zhang Yongguan , Lei Jinshan , Huang Xinyue , Li Jiahua , Hong Jiamin
Published: May 2024

The study utilizes discrete element method simulations of triaxial compression to explore the effects of bedding plane inclination and confining pressure on layered slate's mechanical properties, crack evolution, and anisotropy. Additionally, the results were analyzed using the Hoek-Brown, Ramamurthy, and Saeidi strength criteria. The findings indicate that higher confining pressures enhance the slate's compressive strength and elastic modulus, displaying a distinct ‘U’-shape because of the joint inclination angle. Furthermore, as the bedding plane inclination angle increases, the damage mode has a progressive transition from shear damage to a combination of tensile-shear damage. At lower confining pressures, the crack count in the Parallel Bond Model exhibits ‘U’-shaped behavior, while the Smooth-Joint Contact Model follows an inverted ‘U’-shaped trajectory. With increasing confining pressure, the crack distribution stabilizes, suggesting that elevated confining pressures mitigate the influence of bedding plane inclination on compressive strength. Moreover, the compressive strength anisotropy ratios decrease with higher confining pressure, whereas the elastic modulus anisotropy ratios become more prominent. The Hoek-Brown criterion was superior upon comprehensively evaluating both model fitting accuracy and generalization capabilities. The modified Hoek-Brown criterion can accurately predict the failure strength of the slate at all inclination angles with a few experimental data.
Observer Design for Networked Control Systems with Game Theory Achitecture Under Cyber Attacks
Authors: Fattahi Maryam
Published: May 2024

The object of this article is to propose observer-based controller design for Networked Control Systems (NCS) with resilient architecture under cyber-attacks. In first step, by game theory approach, an attack tolerant NCS using deceptive sensor and actuator in both cyber and physical space is designed. Then, assuming attacker injects unknown false data to simultaneously sensor and actuator, a novel resilient observer-based controller is proposed. Applying Lyapunov–Krasovskii functional method, delay dependent resilient criterion is established to show the exponential behavior of NCS. Finally, for evaluating results, practical example will be discussed.
IM3HRL: Model-assisted Intrinsically Motivated Modular Hierarchical Reinforcement Learning
Authors: Liu Wei , Wang Jiaxiang , Liu Guangwei , Wang Haonan
Published: May 2024

Goal-conditioned reinforceµent learning (GCRL) excels in tackling intricate decision-µaking tasks by µanaging µultiple goals siµultaneously. To enhance the agent’s exploration and learning capabilities within coµplex tasks, µodular goal representation is first coµbined with a hierarchical structure. Additionally, we introduce the CLP task priority µetric and intrinsic µotivation reward function to guide the agent, facilitating cross-µodule and cross-goal learning for efficient exploration. Furtherµore, we iµpleµent a Future Goal Relabeling Strategy (FGRS) to diversify goals. Leveraging a learned dynaµics µodel, the short-rollout is perforµed froµ the current policy to generate predictive goals, thus iµproving the efficiency of the policy optiµization process. Finally, by integrating the above iµproveµents, µodel-assisted intrinsically µotivated µodular hierarchical reinforceµent learning (IM3HRL) is proposed. Experiµental results in the Modular Goal Fetch Arµ test environµent deµonstrate that IM3HRL outperforµs other baseline µethods, achieving a µiniµuµ 15% iµproveµent in learning speed and exhibiting robustness against forgetting and sensor perturbations. Our research results prove the excellent µodel perforµance of IM3HRL and hold significant practical value for GCRL to solve the probleµ of exploratory learning in coµplex tasks.
Effects of FMS Functional Movement Training on Body Posture Control in College Female Aerobics Athletes
Authors: Li Lan , Chen Yanke , Wang Qinghe , PAN Deng , Jiang Chuan
Published: May 2024

Purpose
To investigate the effects of FMS functional movement training on aerobics gymnasts' body posture control ability, and to explore the application of FMS functional movement training on aerobics gymnasts' physical ability promotion.
Method
Forty female collegiate aerobic athletes aged 18 to 23 were randomly assigned to one of two groups: Control, Traditional Physical Training Group (T, N = 20), FMS Functional Movement Training Group (Intervention, Functional Training Group, F, N = 20). The control group used traditional physical training methods and the experimental group used FMS-based functional movement training methods. A 12-week functional movement training program was developed, and the experimental group received the intervention training 4 times a week for 40 minutes each time, and FMS scores, body autonomic control and sports performance were tested before and after the intervention.
Results
Compared with the pre-training, the five locomotor movements of deep squat, hurdle step, shoulder flexibility, trunk stability push-up and rotational stability in the FMS test of the subjects were significantly improved after the intervention of the traditional physical training group and the FMS functional movement training group (P<0.05), and there was no significant difference in the Inline lunge test and the Active straight leg raise test (P>0.05); aerobic dynamic movement and static lower body postural control were significantly improved in the FMS functional movement training group (P<0.05); the FMS functional movement training group showed significant differences before and after the experiment in the competitive performance test.
Conclusion
FMS functional training can better promote aerobic athletes' body posture control and competitive performance during exercise, which is suitable for further application and promotion in the physical training of female aerobic collegiate athletes.
Novel rapid control prototyping for permanent-magnet synchronous motor via model-based design and STM32 chip
Authors: Hu Mingyuan , Ahn Hyeongki , Kang Hyein , You Kwanho
Published: May 2024

As control algorithms become increasingly sophisticated, delivering improved performance at the expense of greater complexity, practical experiments are often unfeasible. To address this issue, this study devised a novel rapid control prototyping (NRCP) based on model-based design (MBD) by MAT LAB/Simulink, STM32CubeMX software, and field-oriented control (FOC) strategies for permanent-magnet synchronous motors (PMSMs). The NRCP avoids complex toolboxes and utilizes only MATLAB/Simulink’s model-to-C language tool, facilitating code portability and development. By using the NRCP, users can quickly experiment with FOC strategies, reducing their reliance on complex automatic code generation tools typically associated with toolboxes. This study focused on the PMSM model, employing only the basic modules of MATLAB/Simulink to generate the application-layer code and the STM32CubeMX software to do low-level code generations, significantly simplifying user experience. To demonstrate the feasibility and efficiency of the protocol, sensor-based and sensorless control models were developed using the MBD method. Finally, the practicality of the NRCP was successfully validated via sensor-based and sensorless experiments using an ARM Cortex-M4-based STM32 microcontroller.
Emergence of the B.1.214.2 SARS-CoV-2 lineage with an Omicron-like spike insertion and a unique upper airway immune signature
Authors: Holtz Andrew , Weyenbergh Johan , Hong Samuel L. , Cuypers Lize , O’Toole Áine , Dudas Gytis , Gerdol Marco , Potter Barney I. , Ntoumi Francine , Mapanguy Claujens Chastel Mfoutou , Vanmechelen Bert , Wawina-Bokalanga Tony , Bram Van Holm , Menezes Soraya Maria , Katja Soubotko , Pottelbergh Gijs Van , Wollants Elke , Vermeersch Pieter , Jacob Ann-Sophie , Maes Brigitte , Obbels Dagmar , Matheeussen Veerle , Martens Geert , Gras Jérémie , Verhasselt Bruno , Laffut Wim , Vael Carl , Goegebuer Truus , Kant Rob van der , Rousseau Frederic , Schymkotwitz Joost , Serrano Luis , Delgado Javier , Wenseleers Tom , Bours Vincent , André Emmanuel , Suchard Marc A. , Rambaut Andrew , Dellicour Simon , Maes Piet , Durkin Keith , Baele Guy
Published: May 2024

We investigate the emergence, mutation profile, and dissemination of SARS-CoV-2 lineage B.1.214.2, first identified in Belgium in January 2021. This variant, featuring a 3-amino acid insertion in the spike protein similar to the Omicron variant, was speculated to enhance transmissibility or immune evasion. Initially detected in international travelers, it substantially transmitted in Central Africa, Belgium, Switzerland, and France, peaking in April 2021. Our travel-aware phylogeographic analysis, incorporating travel history, estimated the origin to the Republic of the Congo, with primary European entry through France and Belgium, and multiple smaller introductions during the epidemic. We correlate its spread with human travel patterns and air passenger data. Further, upon reviewing national reports of SARS-CoV-2 outbreaks in Belgian nursing homes, we found this strain caused moderately severe outcomes (8.7% case fatality ratio). A distinct nasopharyngeal immune response was observed in elderly patients, characterized by 80% unique signatures, higher B- and T-cell activation, increased type I IFN signaling, and reduced NK, Th17, and complement system activation, compared to similar outbreaks. This unique immune response may explain the variant's epidemiological behavior and underscores the need for nasal vaccine strategies against emerging variants.
The association of pre-operative biomarkers of endothelial dysfunction with the risk of post- operative neurocognitive disorders: Results from BioCog study
Authors: Moazzen Sara , Janke Jürgen , Slooter Arjen , Winterer Georg , Spies Claudia , Pischon Tobias , Feinkohl Insa
Published: May 2024

Introduction: Endothelial dysfunction (ED) promotes atherosclerosis development, and studies suggest an association with age-related neurocognitive disorders. Nonetheless, it is unclear whether ED is associated with the risk of neurocognitive disorders.
Method: We included 788 participants aged ≥65 years in the BioCog study. Blood was collected before surgery for measurement of 5 biomarkers of ED including asymmetric and symmetric dimethylarginine (ADMA; SDMA), intercellular and vascular adhesion molecule (ICAM-1, VCAM-1), and von Willebrand factor (vWF). Patients were examined for the occurrence of postoperative delirium (POD) daily until the 7th postoperative day. 537 (68.1%) patients returned for a 3-month follow-up. Post-operative cognitive dysfunction (POCD) was defined from the change in results on 6 neuropsychological tests between baseline and 3 months, compared to the change in results of a control group during a 3-month interval. The associations of each of the 5 ED biomarkers with POD and POCD respectively were determined using multiple logistic regression analyses with adjustment for age, sex, surgery type, pre-morbid IQ, body mass index, hypertension, diabetes, HbA1C, triglyceride, total and HDL cholesterol.
Results: 19.8% of 788 patients developed POD; 10.1% of 537 patients developed POCD. Concentrations of ED biomarkers were not significantly associated with a POD (all p>0.05). A higher VCAM-1 concentration was associated with a reduced POCD risk (odds ratio 0.64; 95% CI: 0.43-0.95). No further statistically significant results were found.
Conclusion: Pre-operative concentrations of ED biomarkers are not associated with POD risk. We unexpectedly found higher VCAM-1 to be associated with a reduced POCD risk. Further studies are needed to confirm or refute these findings.
An improved deep convolutional neural network fororal cancer detection using pretrained models
Authors: C Kavyashree , S Vimala H , J Shreyas
Published: May 2024

Purpose:
Oral cancer is a type of cancer that arises from Oral Squamous Cell Carcinoma (OSCC) that develops in the mouth. Oral cancer is a major global public health issue, which emphasizes the urgent need in the research domain for targeted and effective approaches that enable timely identification. The current diagnostic approaches has a limitation of delay and inefficiency. Artificial Intelligence (AI) is nowadays extensively used the cancer diagnosis and prognosis can provide a fast results that helps in early detection of cancer and improves the survival rate of the cancer patients. Deep learning techniques offers several pretrained models in automating the cancer detection. The research focus on developing a light weight architecture with improved results and low computational costs based on DenseNet architecture of the Convolutional Neural Network (CNN).
Methods:
The number of dense blocks are reduced without compromising the classification of histopathology images as benign and malignant. The histopathology images are preprocessed in a way that is suitable to fed to a neural network. The hyper parameters of the model is fine tuned to obtained the better results.
Results:
The proposed model is evaluated with the standard performance metrics and compared with the other pretrained models. The proposed model provides 98.96% of classification accuracy in training and 82.49% in validation. The loss also has been reduced with a good precision of 0.98, recall of 0.76 and F1 score of 0.82.
Conclusion:
The proposed model also takes care of overfitting and vanishing gradient problem that could hamper the models performance. This will also help a medical practitioner can utilize these findings to formulate initial decisions and plan treatment for oral cancer.
When in doubt average your priors: a latent cause model of risk and ambiguity aversion
Authors: Lannou Erwann Le , Dolan Raymond , Story Giles
Published: May 2024

In decision-making, the likelihood of outcomes is often partly unknown, a form of uncertainty known as ambiguity. Previous studies report that people tend to be averse to ambiguity. However, existing models of decision making under uncertainty fail to explain why people will sometimes show an actual preference for ambiguity, particularly in contexts where reward appears unlikely. Likewise, models of ambiguity do not provide predictions regarding decisions under risk, wherein reward probabilities are explicit. Here we apply a model wherein ambiguity attitudes hinge on a Bayesian average over prior beliefs about reward probabilities, where priors correspond to alternative latent causes governing the distribution of reward. By postulating that all gambles inherently embody a degree of ambiguity, our approach can seamlessly integrate decisions made under both risk and ambiguity. We provide empirical support for predictions of this model in two behavioural experiments. Firstly, as predicted by our model, we show that ambiguity attitude seamlessly transitions from ambiguity seeking at low reward probabilities to ambiguity aversion at higher reward probabilities. Secondly, the model accounts for an empirical observation of non-linear probability weighting for both risky and ambiguous choices. Our approach highlights a continuum between risk and ambiguity, providing an integrated framework for interpreting decision-making under uncertainty.
Enhancing Practicality and Efficiency of Deepfake Detection.
Authors: Balafrej Ismael , Dahmane Mohamed
Published: May 2024

The proliferation of deepfake generation has become increasingly widespread. Current solutions for automatically detecting and classifying generated content require substantial computational resources, making them impractical for use by the average non-expert individual particularly from edge computing applications. In this paper, we propose a series of techniques to accelerate the inference speed of deepfake detection on video data. We also draw inspiration from steganalysis approaches to expose deepfakes as any secret payloads encoded in the image. Furthermore, some key considerations were identified to significantly reduce the size of the core convolutional neural network. The experiment yielded competitive results when evaluated on two second-generation deepfake datasets, namely Celeb-DFv2 and DFDC, while requiring only a fraction of the typical computational cost and resources.
Tensile strength and deformation properties of fiber-reinforced loess: Laboratory and numerical investigation
Authors: Wu Zhipeng , Xu Jian , Ji Yuyang , Fan Henghui , Li Liang , Meng Minqiang
Published: May 2024

The lower tensile strength of loess is an important cause of geohazards such as landslides and ground fissures in loess areas. In this study, the uniaxial tensile tests were conducted on basalt fiber-reinforced loess based on the digital image correlation method (DIC). Moreover, the discrete element method (DEM) was used to investigate the local microscopic mechanism of fiber-particle interaction. Results show that both the peak stress and the peak strain of loess were enhanced after fiber reinforcement. Brittle fracture was observed in unreinforced samples while ductile failure in fiber-reinforced ones with certain residual strength. The uniaxial tensile strength (UTS) of fiber-reinforced samples shows inverted U-shape changes with fiber content and fiber length, with the optimal reinforcement effect at fiber content of 0.6% and fiber length of 12 mm. The failure strain of loess increases after fiber reinforcement, which varies consistently with that of UTS. The maximum axial strain in the surface strain field declines first and then grows with the increase of fiber content and fiber length. More uniform deformation and pronounced plasticity were noted under the optimal fiber condition. The UTS of fiber-reinforced soil is about 1/5 of the uniaxial compressive strength (UCS). A UCS-based prediction model for fiber-reinforced loess was proposed and verified to estimate the UTS effectively. DEM simulation's force chain and displacement field results demonstrate the strength and deformation mechanism of reinforced loess with fiber content and fiber length.
The Feasibility of Switching IVF to IVM in PCOS Patients with Unexpected Poor Ovarian Response Who Underwent Prolonged Protocol
Authors: Wu Yanhong , Su Weijue , Fu Yanghua , Zhao Junzhao , Chen Haoying
Published: May 2024

Background
With the expanding utilization of prolonged protocol, switching from in vitro fertilization to in vitro maturation (IVF/M) was a choice to prevent ovarian hyperstimulation syndrome and to avoid cycle cancellation. Our aim was to explore the feasibility of IVF/M in polycystic ovarian syndrome (PCOS) patients with unexpected poor ovarian response (UPOR) underwent prolonged protocol by comparing with IVF.
Methods
A retrospective analysis was performed on PCOS patients who were treated with prolonged protocol from June 2016 to December 2022. A total of 444 patients were diagnosed with unexpected poor ovarian response during ovarian stimulation. 156 patients performed IVF/M and 288 patients were treated with IVF. Laboratorial and clinical outcomes were analyzed and compared in two Groups.
Results
The Positive β-hCG rate (57.9%), clinical pregnancy rate (52.6%), live birth rate (38.9%) in fresh embryo transfer and cumulative live birth rate (35.3%) in IVF/M Group were lower than those in IVF Group (76.1%,66.8%,53.3%, 67.7%, respectively;all P < 0.05). The number of oocytes retrieved, mature oocytes, 2 pronuclear zygotes, embryos on day3, available blastocysts and high-quality blastocysts in IVF/M Group were less than those in IVF Group (P < 0.001). IVF/M Group gained no case of ovarian hyperstimulation syndrome (OHSS) while 59 (20.5%) patients cancelled fresh embryo transfer for OHSS and 23 (8.0%) of them were moderate to severe OHSS in IVF Group (P < 0.05). The pregnancy and neonatal complications were comparable between two groups. No dominant risk factor was found for non-live birth in fresh embryo transfer cycle. The only independent risk factor for non-live birth in cumulative cycles was IVF/M protocol. (4.58, 95%CI:2.94–7.13, P < 0.001).
Conclusion
IVF/M was a complement feasible choice for PCOS with UPOR who underwent prolonged protocol. Though with a lower live birth rate compared with IVF, almost one third couples still could achieve live birth and avoid neither cycle cancellation nor OHSS.
The digital twin of the human brain: Simulation and assimilation
Authors: Feng Jianfeng , Lu Wenlian , Zeng Longbin , Wang Jiexiang , Ye Leijun , Du Xin , Xiang Shitong , Zheng Qibao , Zhang Jie , Xu Ningsheng , Consortium DTB
Published: May 2024

The Digital Twin Brain (DTB) is a simulation of the human brain at the large scale, with up to 86 billion neurons and 47.8 trillion neural synapses. The DTB mimics both the resting state and aspects of the action of its biological counterpart. A novel architectural assignment of neurons to 14,012 GPUs (with 57.39 million cores) and a two-level routing scheme between GPUs was implemented in the simulations. This was combined with development of a hierarchical mesoscale data assimilation method, that is capable of constructing trillions of parameters from estimated hyper-parameters. The constructed DTB reproduces blood-oxygen-level-dependent (BOLD) signals of the resting-state of its living biological counterpart with high correlation (> 0.9). We enabled the DTB to interact with its environment, as demonstrated in a visual task. The result indicates the feasibility of implementing a digital twin of the human brain, by overcoming key computational, mathematical and biological challenges, and opens the door to a broad range of applications.
Assessing hydro-chemical evolution of groundwater in Balkh Center (Mazar-e-Sharif), northern Afghanistan using an integrated approach
Authors: Farahmand Asadullah , Zaryab Abdulhalim , Ameri Nasrullah , Ali Shakir , Eqrar Mohammad Naim
Published: May 2024

Groundwater in Afghanistan stands as the predominant water source employed for potable consumption, household utilization, agricultural irrigation, and industrial applications. Major cities of Afghanistan are largely dependent on groundwater resources. However, the groundwater quality of major cities in Afghanistan was not investigated in detail. In this study, we investigated Mazar-e-Sharif city of northern Afghanistan intending to identify the major hydrogeochemical processes controlling groundwater chemistry and evaluate the groundwater quality of Mazar-e-Sharif using an integrated approach. We found that 1) The prevailing groundwater within the study area are predominantly characterized by Na-(Ca)-HCO3 and Ca-(Mg)-SO4 water types. 2) Physicochemical variables such as NO3¯, F¯, TDS, and SO42− exceeded the World Health Organization (WHO) safe limits in many wells. 3) Weathering of silicates and cation exchange are the main hydrogeochemical processes controlling hydro-geochemistry in the aquifer. 4) The high salinity observed in the groundwater of Mazar-e-Sharif is likely attributed to a combination of geogenic and natural factors and the Cl/Br ratios suggest that salinity may originate from evaporitic lacustrine and evaporite deposits. The findings of this study hold value for decision-makers in formulating a proficient strategy for the management of groundwater resources in Mazar-e-Sharif City in achieving the UN sustainable goal (SDG) of providing sustainable water for all.
Incidence and risk factors for blood transfusion after abdominal radical hysterectomy for cervical cancer: A 10-year retrospective study of the US nationwide inpatient sample
Authors: 陈 川 , Zhu BenLi , Wang YouFeng , Zhao YangYang , Chen Gang , Peng Ying , Wang XinYu , Xie Hao , Zhou Yin , Chen KeYuan ,   Ying2 Peng
Published: May 2024

Purpose
With the increasing prevalence of abdominal radical hysterectomy, the need for perioperative blood transfusion has emerged as a significant clinical challenge. The independent risk factors for blood transfusion during abdominal radical hysterectomy remain limited, and identifying these factors is needed.
Methods
The Kolmogorov‒Smirnov test was used to assess the normality of continuous variables. Continuous variables with normal distributions were evaluated using Student’s t test, and noncontinuous variables were evaluated using the Mann‒Whitney U test. Categorical variables were evaluated using the χ2 test. Multivariate logistic regression analyses were implemented to identify potential predictors.
Results
Blood transfusions occurred in 14.84% of patients between 2010 and 2019, with a decreasing trend over time. Receiving a transfusion was associated with several negative outcomes, including a longer length of stay, higher total charges, and an increased risk of complications such as thrombocytopenia, acute myocardial infarction, and pneumonia. Additionally, patients who received transfusions were more likely to experience postoperative delirium, deep vein thrombosis, and wound infection. Independent risk factors for blood transfusion included age greater than 60 years, black race, Asian or Pacific Islander race, nonelective surgery, hospitalization in a rural setting, and preexisting medical conditions such as coagulopathy, chronic blood loss anemia, and deficiency anemia. Conversely, patients with private insurance residing in the West or Midwest/North Central Regions were less likely to require a blood transfusion.
Conclusion
Stratifying analyses by race, geographic region, and comorbidity profile among cervical cancer patients is important for enabling the implementation of targeted interventions and improving patient care.
Temporal and spatial characteristics of ecological drought in the Inland River Basin and its driving factors
Authors: Zhang Zezhong , Liu Jian , Feng Kai , Wang Fei , Guo Hengzhi , Zhang Weijie , Wang Sinan
Published: May 2024

Most of the previous studies only used the index of vegetation growth to characterize ecological drought. This study built a Standardized Ecological Water Deficit Index (SEWDI), analysed its space-time evolution characteristics from the perspectives of time, space and spatio-temporal coupling, extractes feature variables by three-dimensional spatio-temporal clustering, analysed typical ecological drought events, the effect of teleconnection factors on ecological drought was investigated using cross wavelet analysis. The reliability of SEWDI was quantitatively evaluated by comparing the r values of Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Soil Moisture Index(SSMI), self-calibrating Palmer Drought Severity Index (scPDSI), and SEWDI with Standardized Solar-induced Fluorescence (SSIF) at various scales in time.The results demonstrated that: (1) Ecological drought in the Inland River Basin showed a weakening trend from 1982 to 2015. Seasonal drought showed a wetting trend in the west and a drought trend in the east, and the wetting trend is most evident in spring. (2) Three-dimensional recognition method could extract more detailed characteristic variables of ecological drought events. A total of 133 ecological drought events occurred in the Inland River Basin during 1982–2015, and ecological drought events had a longer duration and intensity after the 21st century. (3) June 2005 to February 2007 was the most severe ecological drought event on record, which lasted for 21 months. The drought intensity was 44.65×105month·km2, and the drought area was 23.79×104km2. The event occurred in June 2005, intensified in September 2005, attenuated in June 2006, re-intensified in August 2006 and re-attenuated (extinction) in February 2007. The trend of drought migration spread to northeast (4) Among the teleconnecting factors, Among the teleconnection factors, ENSO has the most complex and greatest influence on ecological drought in the Inland River Basin. (5) In addition to having a high correlation with other drought indexs, the SEWDI can also more accurately reflect the effects of drought on vegetation.
First 1000 days - a potential explanatory factor for Risk of hypertension in undernourished populations: Pune Rural Cohort
Authors: Rao Shobha
Published: May 2024

Background
Scientific evidence is lacking whether stunting during first 1000 days of life confers risk of hypertension in adulthood in the event of rising obesity.
Method
449 Rural adult males who were measured in their preschool, pre-pubertal and adolescent ages every six months were revisited for anthropometry and blood pressure measurements using standard techniques.
Results
Proportion of subjects with body mass index (BMI) < 18.5 kg/m2 was high (29%) while only 6.5% were overweight or 5.7% adipose and obesity was hardly present. Prevalence of hypertension (HTN) was high (16.3%). Difference in the prevalence of HTN among not stunted and stunted was high obese (24.1% Vs 50%; p = 0.09) as well as non-obese (16.2–28.1%; p = 0.003) subjects. Subjects who were not stunted at 3 + but were obese, did not have significant risk of HTN but those were stunted at 3 + and were not obese, had risk of HTN (OR 2.5, CI: 1 -5.9). Significant risk seen for stunting as the cofactor indicated its independent influence. Stunting at 3 + affected adult size as also adult sitting and leg height. The ratio of sitting /leg height showed inverse association with HTN prevalence and appeared to be a proxy for early life stunting.
Conclusion
Stunting at 3 + is a major explanatory factor for risk of adult HTN in populations exposed to chronic malnutrition. Our observations highlight need for administering nutrition interventions both during pregnancy and post-natal period and would be a promising alternative for improving birth length and preventing childhood stunting and thereby CVD risks.
StrawSnake: A Real-time strawberry instance segmentation network based on the contour learning approach
Authors: Guo Zhiyang , Hu Xing , Zhao Baigan , Wang HuaiWei , Ma XueYing
Published: May 2024

Fruit recognition is critical for automated harvesting systems. This paper aims to explore a high-precision, real-time method for strawberry recognition. Existing methods for strawberry recognition are mostly pixel-level and box-based. However, these methods cannot accurately or in real-time determine the position of strawberries. Therefore, this paper proposes a new contour-based real-time detection and segmentation network for strawberries, called "StrawSnake." A strawberry-specific octagonal contour is designed based on the shape of strawberries for initial strawberry contour extraction. Deep snake convolution is used for boundary feature extraction and a contour feature aggregation module is proposed, prioritizing important boundary feature channels and enhancing the global context understanding capability of strawberries by aggregating multi-level strawberry contour features. This study obtained a new high-resolution dataset of 3100 strawberry images and the corresponding manually segmented ground truth images (StrawDI_Db1 database). Edge detection was used to label the ground truth images of strawberry contours in the dataset to build strawberry contour labels. Results obtained from testing 200 images in the dataset show that our StrawSnake can achieve real-time strawberry contour recognition at a speed of 39.2 frames per second, with an average accuracy of 59.23%. On another TongStraw_DB built by us, compared with other methods,, our StrawSnake algorithm has also a competitive advantage in terms of segmentation speed and accuracy. Finally, through ablation experiments, we demonstrate the performance improvement brought by DSConv and MFRB. Since our method can be integrated into strawberry automated harvesting systems, it is considered the most promising approach.