Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of non-invasive vagus nerve stimulation on clinical symptoms and molecular biomarkers in Parkinson’s disease

Non-invasive vagus nerve stimulation (nVNS) is an established neurostimulation therapy used in the treatment of epilepsy, migraine and cluster headache. In this randomized, double-blind, sham-controlled trial we explored the role of nVNS in the treatment of gait and other motor symptoms in Parkinson’s disease (PD) patients. In a subgroup of patients, we measured selected neurotrophins, inflammatory markers and markers of oxidative stress in serum. Thirty-three PD patients with freezing of gait (FOG) were randomized to either active nVNS or sham nVNS. After baseline assessments, patients were instructed to deliver six 2 min stimulations (12 min/day) of the active nVNS/sham nVNS device for 1 month at home. Patients were then re-assessed. After a one-month washout period, they were allocated to the alternate treatment arm and the same process was followed. Significant improvements in key gait parameters (speed, stance time and step length) were observed with active nVNS. While serum tumor necrosis factor- α decreased, glutathione and brain-derived neurotrophic factor levels increased significantly (p < 0.05) after active nVNS treatment. Here we present the first evidence of the efficacy and safety of nVNS in the treatment of gait in PD patients, and propose that nVNS can be used as an adjunctive therapy in the management of PD patients, especially those suffering from FOG. Clinical trial registration: identifier ISRCTN14797144.
IFGAN - A Novel Image Fusion Model to Fuse 3D Point Cloud Sensory Data

To enhance the level of autonomy in driving, it is crucial to ensure optimal execution of critical maneuvers in all situations. However, numerous accidents involving autonomous vehicles (AVs) developed by major automobile manufacturers in recent years have been attributed to poor decision making caused by insufficient perception of environmental information. AVs employ diverse sensors in today’s technology-driven settings to gather this information. However, due to technical and natural factors, the data collected by these sensors may be incomplete or ambiguous, leading to misinterpretation by AVs and resulting in fatal accidents. Furthermore, environmental information obtained from multiple sources in the vehicular environment often exhibits multimodal characteristics. To address this limitation, effective preprocessing of raw sensory data becomes essential, involving two crucial tasks: data cleaning and data fusion. In this context, we propose a comprehensive data fusion engine that categorizes various sensory data formats and appropriately merges them to enhance accuracy. Specifically, we suggest a general framework to combine audio, visual, and textual data, building upon our previous research on an innovative hybrid image fusion model that fused multispectral image data. However, this previous model faced challenges when fusing 3D point cloud data and handling large volumes of sensory data. To overcome these challenges, our study introduces a novel image fusion model called Image Fusion Generative Adversarial Network (IFGAN), which incorporates a multi-scale attention mechanism into both the generator and discriminator of a Generative Adversarial Network (GAN). The primary objective of image fusion is to merge complementary data from various perspectives of the same scene to enhance the clarity and detail of the final image. The multi-scale attention mechanism serves two purposes: the first, capturing comprehensive spatial information to enable the generator to focus on foreground and background target information in the sensory data, and the second, constraining the discriminator to concentrate on attention regions rather than the entire input image. Furthermore, the proposed model integrates the color information retention concept from the previously proposed image fusion model. Furthermore, we propose simple and efficient models for extracting salient image features. We evaluate the proposed models using various standard metrics and compare them with existing popular models. The results demonstrate that our proposed image fusion model outperforms the other models in terms of performance.
Morphological variability and age structure in a population of Bufo verrucosissimus (Anura: Bufonidae) from Artvin, Turkey

We investigated morphological diversity (external body traits, coloration patterns and skin structure) and age structure in a population of Caucasian toad (Bufo verrucosissimus) from Lake Borçka Karagöl, situated in the vicinity of Artvin on the northeastern border of Turkey and Georgia. Age was determined using phalangeal skeletochronology. The external morphological variability was assessed using the linear measurement of 27 body-related characters and the photographs of each specimen. According to the results, the means of head length and head width were found significantly lower in Karagöl population as opposed to Caucasian populations, but average body size did not differ among all populations. Coloration and pattern features of the specimens from Karagöl were identical to those of Caucasia. Most of the females have brown tones and males are usually olive green and brown. The indiscrete elongated dark bands on parotoids did not extend behind the gland. PCA analysis confirmed a clear separation between the sexes and a high degree of female-biased sexual size dimorphism was determined based on the body size (SDI index: +0.41). The constructed Von Bertalanffy growth curve models yielded similar profiles in both sexes. Body size and age were significantly correlated in both models, but growth coefficient value was higher in males. Accordingly, the mean age of the Karagöl population is greater in both sexes, but the lifespan and maximum age are greater in Caucasus populations.
Optimal time alignment of tide‐gauge tsunami waveforms in nonlinear inversions: Application to the 2015 Illapel (Chile) earthquake

Tsunami waveform inversion is often used to retrieve information about the causative seismic tsunami source. Tide gauges record tsunamis routinely; however, compared to deep‐ocean sensor data, tide‐gauge waveform modeling is more difficult due to coarse/inaccurate local bathymetric models resulting in a time mismatch between observed and predicted waveforms. This can affect the retrieved tsunami source model, thus limiting the use of tide‐gauge data. A method for nonlinear inversion with an automatic optimal time alignment (OTA), calculated by including a time shift parameter in the cost function, is presented. The effectiveness of the method is demonstrated through a series of synthetic tests and is applied as part of a joint inversion with interferometric synthetic aperture radar data for the slip distribution of the 2015 Mw 8.3 Illapel earthquake. The results show that without OTA, the resolution on the slip model degrades significantly and that using this method for a real case strongly affects the retrieved slip pattern.
Breaking Dynamic Behavior in 3D Covalent Organic Framework with Pre-Locked Linker Strategy

Due to their large surface area and pore volume, three-dimensional covalent organic frameworks (3D COFs) have emerged as competitive porous materials. However, structural dynamic behavior, often observed in imine-linked 3D COFs, could potentially unlock their potential application in gas storage. Herein, we showed how a pre-locked linker strategy introduces breaking dynamic behavior in 3D COFs. A predesigned planar linker-based 3,8-diamino-6-phenylphenanthridine (DPP) was prepared to produce non-dynamic 3D JUC-595, as the benzylideneamine moiety in DPP locked the linker flexibility and restricted the molecular bond rotation of the imine linkages. Upon solvent inclusion and release, the PXRD profile of JUC-595 remained intake, while JUC-594 with a flexible benzidine linker experienced crystal transformation due to framework contraction–expansion. As a result, the activated JUC-595 achieved higher surface areas (754 m2 g−1) than that of JUC-594 (548 m2 g−1). Furthermore, improved CO2 and CH4 storages were also seen in JUC-595 compared with JUC-594. Impressively, JUC-595 recorded a high normalized H2 storage capacity that surpassed other reported high-surface area 3D COFs. This works shows important insights on manipulating the structural properties of 3D COF to tune gas storage performance.
Development of a Data Science Curriculum for an Engineering Technology Program

Data science has gained the attention of various industries, educators, parents, and students thinking about their future careers. Statistics departments have traditionally offered data science courses for a long time. The main objective of these courses is to examine the fundamental concepts and theories. However, teaching data science courses has also expanded to other disciplines due to the vast amount of data being collected by numerous modern applications. Also, someone needs to learn how to collect and process data, especially from industrial devices, because of the recent development of Internet of Things (IoT) technologies. Hence, integrating data science into the curricula of different engineering branches becomes a matter of relating the statistics background to the specific discipline. There are several reasons for this transition. Firstly, as the increased computational power and massive availability of the data make the use of statistical theories possible in more engineering applications, there is a growing need for engineering students to build knowledge in data science concepts. Secondly, the wide availability of libraries and models allows for the implementation of diverse solutions to engineering problems. This paper will discuss introducing a new data science curriculum in an Engineering Technology (ET) program with a focus on Electrical Engineering Technology (EET) program.
Application of Near-Infrared Spectroscopy to Rapidly Classify the Chinese Quince Fruits from Different Habitats

The ecological habitats of Chinese quince (Chaenomeles speciosa Nakai) fruits affect their phenotype. Currently, limited or no rapid method exists for classifying Chinese quince fruit from different ecosystems. This study developed a partial least squares discriminant analysis (PLS-DA) classification model to effectively and nondestructively classify 663 Chinese quince fruit samples from six environments in 2020. PLS-DA models and other variable selection approaches were used in this study. The near-infrared spectroscopy (NIRs) absorption spectra of raw Chinese quince fruit samples from six habitats showed a similar shape. The spectra of each environment showed little variance. The raw fruit spectra varied significantly among habitat categories after the first derivative preprocessing phase. The uninformative variable elimination (UVE) variable selection approach had greater calibration and validation set specificity of 0.93 and 0.98. This study found the best classification specificity using the UVE variable selection approach compared to other methods including the PLS-DA model without variable selection. The UVE approach improved Yunnan habitat categorization specificity from 86% to 88% when integrated with PLS-DA. Additionally, the validation set for quinces originating from Anhui, Chongqing, Hubei, Shandong, and Zhejiang achieved an ideal classification score of 100%. The findings of the study indicated that PLS-DA can serve as an alternative approach for classifying the habitats of Chinese quince fruits. When used in conjunction with other methods, this technique can assist researchers, scientists, and industry professionals in identifying the main factors responsible for significant variations in the habitats, composition, and quality of Chinese quince fruits.
Comparative transcriptome analysis of T lymphocyte subpopulations and identification of critical regulators defining porcine thymocyte identity

Introduction The development and migration of T cells in the thymus and peripheral tissues are crucial for maintaining adaptive immunity in mammals. However, the regulatory mechanisms underlying T cell development and thymocyte identity formation in pigs remain largely underexplored. Method Here, by integrating bulk and single-cell RNA-sequencing data, we investigated regulatory signatures of porcine thymus and lymph node T cells. Results The comparison of T cell subpopulations derived from porcine thymus and lymph nodes revealed that their transcriptomic differences were influenced more by tissue origin than by T cell phenotypes, and that lymph node cells exhibited greater transcriptional diversity than thymocytes. Through weighted gene co-expression network analysis (WGCNA), we identified the key modules and candidate hub genes regulating the heterogeneity of T cell subpopulations. Further, we integrated the porcine thymocyte dataset with peripheral blood mononuclear cell (PBMC) dataset to systematically compare transcriptomic differences between T cell types from different tissues. Based on single-cell datasets, we further identified the key transcription factors (TFs) responsible for maintaining porcine thymocyte identity and unveiled that these TFs coordinately regulated the entire T cell development process. Finally, we performed GWAS of cell type-specific differentially expressed genes (DEGs) and 30 complex traits, and found that the DEGs in thymus-related and peripheral blood-related cell types, especially CD4_SP cluster and CD8-related cluster, were significantly associated with pig productive and reproductive traits. Discussion Our findings provide an insight into T cell development and lay a foundation for further exploring the porcine immune system and genetic mechanisms underlying complex traits in pigs.
Effectiveness of Psychosocial care interventions in improving the Quality of Life for Adult Patients with Cancer in low-and middle-income countries (LMICs): A Systematic Review and Meta-Analysis Protocol

Background Psychosocial care interventions are part and parcel of cancer care and are known for their significant contribution to the improvement of the quality of life (QoL) for cancer patients and their families. Assessment of the QoL of patients with cancer and their families has become critical in cancer care nowadays since it guides health care providers in making informed decisions during the care process. The aim of this meta-analysis is to synthesise the online literature of primary studies from LMICs in order to understand the effectiveness of psychosocial care interventions towards the improvement of the QoL of adult patients with cancer. Methods This study will be done in tandem with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards. Primary studies that would have investigated the effectiveness of psychosocial care interventions on quality of life of adult cancer patients will be identified through searches in the various electronic databases that are known to produce optimal and efficient searches for systematic reviews and meta-analyses include: Ovid MEDLINE(R), PubMed, EMBASE, APA PsychINFO, Web of Science, PubMed, and Google Scholar. Studies published between 1st January 2002 and 31st December 2023 in any LMIC, will be searched. After developing the meta-analysis question, we have developed a search string from the PICOST (population, intervention, comparison, outcome, study design, setting and Time-frame) model with a limitation on study design. Discussion This systematic review and meta-analysis will gather evidence from primary studies on the effectiveness of psychosocial care interventions in improving the QoL for adult patients with cancer in LMICs. Protocol registration: This protocol was registered on 5th June 2023 and its registration number is CRD42023421561.
IMPACTS OF LANDUSE CHANGES ON RUNOFF GENERATION IN SIMLY WATERSHED

Landuse change has significant impacts on hydrologic processes in a watershed. Assessment of the impacts of landuse changes is essential for watershed management and sustainable development. In this study, a soil and water assessment tool (SWAT) model was used to assess the landuse changes impacts on runoff generation in Simly dam watershed located 30 km east of Islamabad, Pakistan with a catchment area of 156 km 2 . The simulation was performed for three time periods 1991-92, 2000-01, 2009-10 on a monthly time step. The model was calibrated using the auto-calibration tool SWAT- CUP. Model predicted surface runoff volumes with Nash Sutcliffe Efficiency (NSE) ranges from 0.81 to 0.83. The results of the scenarios revealed that expansion of urban areas from 5% to 10% indicated 1.2% and 0.2% increase in the surface runoff and water yield respectively, expansion of forests areas from 46% to 66% indicated 9.3% and 2.5% decrease in the surface runoff and water yield respectively and deforestation of the catchment from 46% to 36% indicated 6.7% and 2.2% increase in the surface runoff and water yield respectively. The study has presented that the Soil and Water Assessment Tool (SWAT) model can be a suitable tool for evaluating the impacts of landuse changes in Simly watershed.
Comparable dynamic cerebral autoregulation and neurovascular coupling of the posterior cerebral artery between healthy men and women

Abstract Aims Most studies focus on dynamic cerebral autoregulation (dCA) in the middle cerebral artery (MCA), and few studies investigated neurovascular coupling (NVC) and dCA in the posterior cerebral artery (PCA). We investigated NVC and dCA of the PCA in healthy volunteers to identify sex differences. Methods Thirty men and 30 age‐matched women completed dCA and NCV assessments. The cerebral blood flow velocity (CBFV) and mean arterial pressure were evaluated using transcranial Doppler ultrasound and a servo‐controlled plethysmograph, respectively. The dCA parameters were analyzed using transfer function analysis. The NCV was evaluated by eyes‐open and eyes‐closed (24 s each) periodically based on voice prompts. The eyes‐open visual stimulation comprised silent reading of Beijing‐related tourist information. Results The PCA gain was lower than that of the MCA in all frequency ranges (all p < 0.05). Phase was consistent across the cerebrovascular territories. The cerebrovascular conductance index (CVCi) and mean CBFV (MV) of the PCA were significantly higher during the eyes‐open than eyes‐closed period (CVCi: 0.50 ± 0.12 vs. 0.38 ± 0.10; MV: 42.89 ± 8.49 vs. 32.98 ± 7.25, both p < 0.001). The PCA dCA and NVC were similar between the sexes. Conclusion We assessed two major mechanisms that maintain cerebral hemodynamic stability in healthy men and women. The visual stimulation‐evoked CBFV of the PCA was significantly increased compared to that during rest, confirming the activation of NVC. Men and women have similar functions in PCA dCA and NCV.
Theoretical Framework of Radiation Force in Surface Acoustic Waves for Modulated Particle Sorting

Sorting specific target entities from sample mixtures is commonly used in many macroscale laboratory processing, such as disease diagnosis or treatment. Downscaling of sorting systems enables less laboratory space and fewer quantities of sample and reagent. Such lab-on-a-chip devices can perform separation functions using passive or active sorting methods. Such a method, acoustic sorting, when used in microfluidics, offers contactless, label-free, non-invasive manipulation of target cells or particles and is therefore the topic of active current research. Our phase-modulated sorting technique complements traditional time-of-flight techniques and offers higher sensitivity separation using a periodic signal. By cycling of this periodic signal, the target entities are gradually displaced compared to the background debris, thereby achieving sorting. In this paper, we extend the knowledge on phase-modulated sorting techniques. Firstly, using numerical simulations, we confirm the sorting role of our proposed primary acoustic radiation force within surface wave devices. Secondly, a threefold agreement between analytical, numerical and experimental sorting trajectories is presented.
Neonatal stress disrupts the glymphatic system development and increases the susceptibility to Parkinson's disease in later life

Abstract Introduction Neonatal stress disrupts brain development and increases the risk of neurological disorders later in life. However, the impact of neonatal stress on the development of the glymphatic system and susceptibility to Parkinson's disease (PD) remains largely unknown. Methods Neonatal maternal deprivation (NMD) was performed on mice for 14 consecutive days to model chronic neonatal stress. Adeno‐associated virus expressing A53T‐α‐synuclein (α‐syn) was injected into the substantia nigra to establish PD model mice. Glymphatic activity was determined using in vivo magnetic resonance imaging, ex vivo fluorescence imaging and microplate assay. The transcription and expression of aquaporin‐4 (AQP4) and other molecules were evaluated by qPCR, western blotting, and immunofluorescence. Animal's responses to NMD and α‐syn overexpression were observed using behavioral tests. Results Glymphatic activity was impaired in adult NMD mice. AQP4 polarization and platelet‐derived growth factor B (PDGF‐B) signaling were reduced in the frontal cortex and hippocampus of both young and adult NMD mice. Furthermore, exogenous α‐syn accumulation was increased and PD‐like symptoms were aggravated in adult NMD mice. Conclusion The results demonstrated that NMD could disrupt the development of the glymphatic system through PDGF‐B signaling and increase the risk of PD later in life, indicating that alleviating neonatal stress could be beneficial in protecting the glymphatic system and reducing susceptibility to neurodegeneration.
Getting everyone to agree on gene signatures for murine macrophage polarization in vitro

Macrophages, key players in the innate immune system, showcase remarkable adaptability. Derived from monocytes, these phagocytic cells excel in engulfing and digesting pathogens and foreign substances as well as contributing to antigen presentation, initiating and regulating adaptive immunity. Macrophages are highly plastic, and the microenvironment can shaper their phenotype leading to numerous distinct polarized subsets, exemplified by the two ends of the spectrum: M1 (classical activation, inflammatory) and M2 (alternative activation, anti-inflammatory). RNA sequencing (RNA-Seq) has revolutionized molecular biology, offering a comprehensive view of transcriptomes. Unlike microarrays, RNA-Seq detects known and novel transcripts, alternative splicing, and rare transcripts, providing a deeper understanding of genome complexity. Despite the decreasing costs of RNA-Seq, data consolidation remains limited, hindering noise reduction and the identification of authentic signatures. Macrophages polarization is routinely ascertained by qPCR to evaluate those genes known to be characteristic of M1 or M2 skewing. Yet, the choice of these genes is literature- and experience-based, lacking therefore a systematic approach. This manuscript builds on the significant increase in deposited RNA-Seq datasets to determine an unbiased and robust murine M1 and M2 polarization profile. We now provide a consolidated list of global M1 differentially expressed genes (i.e. robustly modulated by IFN-γ, LPS, and LPS+ IFN-γ) as well as consolidated lists of genes modulated by each stimulus (IFN-γ, LPS, LPS+ IFN-γ, and IL-4).