Miracle-dz/UniFAR-FTUs huggingface dataset:
Bioarchaeological Analysis of Isolated Crania from the Elizabeth Site in the Lower Illinois River Valley

This thesis explores the life history of six isolated skulls interred in Mound 3 of the Elizabeth site, a Middle Woodland site in the lower Illinois valley. This study employs analyses of osteological features, stable and radiogenic isotopes, and biodistance for a cross-section of the Mound 3 population (n=15), including the isolated crania. Isotopic results reveal significant variation in lead isotope ratios in enamel, and interpretively meaningful variation in strontium values. However, bone carbonate oxygen values are not significantly different. Carbon isotope values from bone carbonate revealed only sex-based dietary differences. Biodistance data indicate relatively genetic homogeneity at the site, although significant variation was present in two of the isolated crania. Ultimately, data indicate that two of the six isolated skulls likely originated from elsewhere in the valley, but that the population likely resided in the Elizabeth site vicinity in the decade preceding death, and were not outsiders. INDEX WORDS: Middle Woodland, Lower Illinois River Valley, Multi-isotope analysis, Carbon, Lead, Strontium, Oxygen, Elizabeth Mound, Trophy heads, Isolated crania
A Silver Nanoparticle Modified Etched Fiber Bragg Grating Sensor for Arsenic Detection

The global data on arsenic (As) contamination in drinking water and the severity of As exposure emphasize the utmost need for early and efficient detection of As in water. In this work, we report a quantitative optical detection of As in drinking water using silver nanoparticle (AgNP) functionalized etched-fiber Bragg grating (e-FBG) sensor. The selective attachment of As (III) to AgNP is applied here for the sensitive detection of As, which is exemplified as a Bragg wavelength shift (<inline-formula> <tex-math notation="LaTeX">$\Delta \lambda _{B}{)}$ </tex-math></inline-formula> in the functionalized e-FBG sensor. The detection limit is found to be 10 femtomolar (fM) with dynamic range up to 100 nanomolar (nm), which is less than the World Health Organization (WHO) standards for drinking water (not over 50.5 nm). The e-FBG sensor shows a good reproducibility (standard error < 10 pm), specificity, and sensitivity (86.13 pm/<inline-formula> <tex-math notation="LaTeX">$10^{-{1}}\cdot \text{M}$ </tex-math></inline-formula>) to As in real time at ambient conditions. The quantitative As value, with a 94% recovery in tap water sample, makes the e-FBG sensor better than the other methods.
At-Home Blood Pressure Measurements Provide Better Assessments of Orthostatic Hypotension in Parkinson’s Disease

Orthostatic hypotension (OH) is common in Parkinson’s Disease (PD). It is intermittent, exacerbated by stressors including meals, medications, and dehydration, and frequently is unrecognized. Although intermittent, assessment is usually by a single “in clinic” BP measurement. This study examines whether 10 home measurements are more sensitive in detecting OH than a single “in clinic” measurement. Participants (44 people with PD and 16 controls) were instructed to measure lying and standing BP at home. BP was measured on five consecutive days upon waking and before bedtime. Symptoms were also assessed using the Movement Disorder Society United Parkinson’s Disease Rating Scale and the Non-Motor Questionnaire. While a postural drop in systolic BP (≥20 mmHg) was recorded “in clinic” in thirteen of the forty-four PD participants, a postural drop was found in at least one of the ten home measurements in twenty-eight of the forty-four participants. Morning hypertension and variability in lying systolic BP was more common in these subjects than in those without a postural drop or the controls. A greater number of measurements of lying and standing BP are more likely to reveal orthostatic hypotension, variation in systolic BP, and hypertension than a single office measurement in people with PD.
FCS-Model Predictive Control of a Quadratic Buck Converter for more Efficient Data Centers

The energy consumption in Data Centers is increasing faster in the last few years, due to the IoT and big data world market impact. This research applies the finite control set model predictive control (FCS-MPC) to a single-switch quadratic buck converter (QBC) for future data centers. The FCS-MPC can solve the stability problem of QBC without any need for linearization. Designing a stable controller is a challenge, especially in the case when a constant power load is fed. Two control objectives of the proposed controller are voltage and current regulation. Both objectives are satisfied by the proposed method. Fast dynamic response and performance in a wide range of operating points are achieved by this method. The proposed method is verified by PSIM simulations.
Fusion of ViT Technique and Image Filtering in Deep Learning for Plant Pests and Diseases Recognition

Over a decade, deep learning methods using convolutional neural network (CNN) architecture have achieved breakthroughs in the precision criterion, which compared to the traditional machine learning methods. However, those approaches still faced some limitations of processing time and precision when they are applied to large samples and hard datasets. Recently, some new methods based on the transformer learning approach have been applied to image processing. This direction approach has illustrated the promising results in the terms of accuracy and computational time. This paper presents a new approach, which combines a pre-processing technique of image filtering and vision transformer (ViT) learning for the problem of plant insect pests and diseases recognition. The proposed solution involves some stages: neural network-based image filtering, then passes results through a ViT module to extract feature map, and then fed to multiple head network for classification. The proposed method applies image filtering pre-processing to highlight features before passing results to the ViT processing stage instead of using ViT from raw input images. Furthermore, element-wise multiplication in the frequency domain reduces processing time instead of using convolutional processing in the spatial domain. Experimental results demonstrate that applying filtering preprocessing does not significantly increase the number of learning parameters and training time compared to using ViT directly and it leverages to improve accuracy to compare to well-known models based on deep CNN. The research results also illustrated that the ViT solution and the proposed method are reached more accurate than CNN-based deep learning methods.
Bioaccumulation and sub-lethal effects of intermittent and continuous exposure to metals on the marine mussel, Mytilus galloprovincialis

79 4.0. Introduction . 80 4.1. Methodology . 83 4.1. 1. Test Organism and Acclimation . 83 4.1. 2. Experimental Design . 83 4.1. 3. Heamolymph Extraction and Tissue Collection . 84 4.1. 4. Trace Metal Analysis . 84 4.1. 5. TBARS and Total Glutathione Analysis . 85 4.1. 6. Neutral Red Retention and Total Haemocyte Count. 88 4.1. 7. Plasma Ion, Osmotic Pressure and Glucose Assay . 88 4.1. 8. Histological Examinations . 88 4.1. 9. Calculations and Statistical Analysis . 88 4.2. Results . 89 4.2. 1. Aqueous Exposure to Mercury and Tissue Accumulation . 89 4.2. 2. Tissue Hg Accumulation . 91 4.2. 3. Effects of Hg Exposure on Haemolymph Chemistry and Ionic Regulation. 94 4.2. 4. Effects of Hg exposure on TBARS . 102
The contributions of teacher intercultural competence to academic satisfaction and engagement among international students in China and Thailand

Purpose: The contributions of teacher intercultural competence to educational outcomes, including student self-efficacy, engagement, and academic satisfaction, were investigated in this study. Design/Methodology/Approach: The study applies the quantitative method using primary data from the survey collected from 400 international undergraduate students in China and Thailand. The partial least squares structural equation modeling is used to analyze the relationships of variables between conceptual constructions. Findings: The results indicate that teacher intercultural competence has positive and significant effects on international student self-efficacy and engagement but has no significant effect on international student academic satisfaction. Conclusion: This study provides new insight into international student self-efficacy, engagement, and academic satisfaction from the perspective of teacher intercultural competence. Research Limitations/Implications: In this study, undergraduate international students were selected only from China and Thailand, which is considered a research limitation. Thus, increasing the generalizability of the whole population by collecting data from more universities is suggested for future research. Practical Implications: Educational policymakers or university administrators should improve international student educational outcomes from the perspective of teacher education and professional development. Teacher intercultural competence should be considered a significant part of teacher education and professional development. If the teachers understand the cultural or behavioral differences from the perspective of students, they can construct a more inclusive and effective academic environment. Contribution to Literature: This study proposed and confirmed the mediating role of international student self-efficacy, which brings clarification to the formational mechanism of how teacher intercultural competence affects international student engagement and academic satisfaction.
Impact of Vitamin D Deficiency on Tumor Aggressiveness in Neuroendocrine Neoplasms

Abstract: Background: The role of vitamin D (25(OH)D) in the pathogenesis and outcome of several conditions, including autoimmune diseases, diabetes and cancers is largely described in the literature. The aims of this study were to evaluate the prevalence of 25(OH)D deficit in a cohort of patients with neuroendocrine neoplasms (NENs) in comparison to a matched healthy control group and to analyze the possible role of 25(OH)D as a prognostic factor for NENs in terms of biological aggressiveness, tumor progression and survival. Methods: From 2009 to 2023, 172 patients with NENs (99 females; median age, 63 years) were included in the study. Serum 25(OH)D levels were defined as deficient if ≤20 ng/mL. The possible associations between 25(OH)D levels and disease grading, staging, ki67%, overall survival (OS), and progression-free survival (PFS) were considered. Results: NEN patients had significantly lower 25(OH)D levels compared to controls (p < 0.001) regardless of the primary origin. Patients with 25(OH)D < 20 ng/mL had a significantly higher ki67 index (p = 0.02) compared to the ones with 25(OH)D levels above 20 ng/mL. Patients with disease progression were found to have a significantly lower 25(OH)D at baseline (p = 0.02), whereas PFS and OS were not significantly influenced by 25(OH)D. Conclusions: Vitamin D deficiency is highly prevalent among NENs and is associated with higher ki67 and disease progression. Our study highlights the importance of monitoring 25(OH)D levels in patients with NENs, as its deficiency appeared to be linked to the worst biological tumor aggressiveness.
Biosensors and Wearable Sensors Based on Graphene Composites for Lab-on-Skin

A highly-sensitive wearable sensor based on Graphene (G) - Hexagonal boron nitride (h-BN) composite with various organic additives ((poly (3,4-ethylenedioxythiophene): polystyrene sulfonate composite (PEDOT:PSS), glucose oxidase enzyme (GOx or GOD), ethylene glycol (EG)) has been developed. The effect of the substrate on the sensitive abilities of sensors of various compositions has been studied. It has been shown that when the G+PEDOT:PSS composite is exposed to glucose solutions of various concentrations, a different change in the electrical resistance of the samples on the PET substrate is observed. The addition of h-BN to the composite creates a mesa-porous structure, due to which there is an increase in the sensor response on the PET substrate by an order of magnitude. On a paper substrate, there is an increase in the current response of the sensor by (4–5) orders, depending on the active material. Preliminary modification of the sensor with GOD can further increase the response of the sensor to exposure to glucose solutions. This is true for both PET and paper substrates. In vivo experiments have shown that there is a relationship between the electrical current through the sample and the concentration of glucose in the blood when wearing samples on the wrist. With an increase in the number of layers during printing, the current response increases. The mechanism of conductivity of composite films was investigated. It turned out to be the Schottky emission mechanism. The mechanism of conductivity does not depend on the addition of organics.
Digital Twin-Enabled Service Satisfaction Enhancement in Edge Computing

The emerging digital twin technique enhances the network management efficiency and provides comprehensive insights, through mapping physical objects to their digital twins. The user satisfaction on digital twin-enabled query services relies on the freshness of digital twin data, which is measured by the Age of Information (AoI). Because the remote cloud faces challenges in providing data for users due to long service delays, Mobile Edge Computing (MEC), as a promising technology, offers real-time data communication between physical objects and their digital twins at the edge of the core network. However, the mobility of physical objects and dynamic query arrivals make efficient service provisioning in MEC become challenging. In this paper, we investigate the dynamic digital twin placement for improving user service satisfaction in MEC environments. We focus on two user service satisfaction augmentation problems under both static and dynamic digital twin placement schemes: the static and dynamic utility maximization problems. We first formulate an Integer Linear Programming (ILP) solution to the static utility maximization problem when the problem size is small; otherwise, we propose a performance- guaranteed approximation algorithm for it. We then devise an online algorithm for the dynamic utility maximization problem with a provable competitive ratio. Finally, we evaluate the performance of the proposed algorithms through experimental simulations. Simulation results demonstrate that the proposed algorithms outperform the comparison baseline algorithms, and the performance improvement is no less than 11.6%, compared with the baseline algorithms.
Advances and Opportunities in Nanoparticle Drug Delivery for Central Nervous System Disorders: A Review of Current Advances

This narrative review provides an overview of the current advances, challenges, and opportunities in nanoparticle drug delivery for central nervous system (CNS) disorders. The treatment of central nervous system disorders is challenging due to the blood-brain barrier (BBB), which limits the delivery of therapeutic agents to the brain. Promising approaches to address these issues and improve the efficacy of CNS disease therapies are provided by nanoparticle-based drug delivery systems. Nanoparticles, such as liposomes, polymeric nanoparticles, dendrimers, and solid lipid nanoparticles, can be modified to enhance targeting, stability, and drug-release patterns. They allow for the encapsulation of a variety of therapeutic compounds and can be functionalized with ligands or antibodies for active targeting, minimizing off-target effects. Additionally, nanoparticles can circumvent drug resistance processes and provide versatile platforms for applications that combine therapeutic and diagnostic functions. Although the delivery of CNS medications using nanoparticles has advanced significantly, there are still challenges to be resolved. These include understanding the BBB interactions, doing long-term safety studies, and scaling up the production. However, improvements in nanotechnology and a deeper comprehension of CNS disorders provide opportunities to enhance treatment results and address unmet medical requirements. Future research and ongoing clinical trials are required to further explore the potential of nanoparticle drug delivery for CNS disorders.
Performance Evaluation of Variable Pulse Density Modulation Algorithm in SWISS Rectifier for Induction Heating

Induction heating (IH) converts electrical energy into heat at a high efficiency, allowing fast, and localized heating which is desirable in forging and hardening applications. With power quality standards getting stricter and stricter, the power supply used for induction heating system would need to improve input power factor and input current total harmonics distortion. There have been many topologies and modulation methods proposed to solve this problem. Single-stage and power factor correction (PFC) front-end topologies are attractive due to their low cost, and high performance. Supporting the PFC front-end solution, this paper proposes the use of an active SWISS rectifier and a novel variable pulse density modulation for three-phase input currents shaping, as the first stage of a two-stage IH system, achieving high input power factor, wide power control range, and good efficiency. Simulation and experimental results confirmed the feasibility of the proposed topology and modulation algorithm.
An Investigation of Structure–Activity Relationships and Cell Death Mechanisms of the Marine Alkaloids Discorhabdins in Merkel Cell Carcinoma Cells

A library of naturally occurring and semi-synthetic discorhabdins was assessed for their effects on Merkel cell carcinoma (MCC) cell viability. The set included five new natural products and semi-synthetic compounds whose structures were elucidated with NMR, HRMS, and ECD techniques. Several discorhabdins averaged sub-micromolar potency against the MCC cell lines tested and most of the active compounds showed selectivity towards virus-positive MCC cell lines. An investigation of structure–activity relationships resulted in an expanded understanding of the crucial structural features of the discorhabdin scaffold. Mechanistic cell death assays suggested that discorhabdins, unlike many other MCC-active small molecules, do not induce apoptosis, as shown by the lack of caspase activation, annexin V staining, and response to caspase inhibition. Similarly, discorhabdin treatment failed to increase MCC intracellular calcium and ROS levels. In contrast, the rapid loss of cellular reducing potential and mitochondrial membrane potential suggested that discorhabdins induce mitochondrial dysfunction leading to non-apoptotic cell death.
A high speed and power efficient multiplier based on counter-based stacking

High speed and competent addition of various operands is an essential operation in the design any computational unit. The swiftness and power competence of multiplier circuits plays vital role in enlightening the overall performance of microprocessors. Multipliers play crucial role in the design of arithmetic logic unit (ALU) or any digital signal processor (DSP) that are effectively employed for filtering and convolution operations. The process of multiplication either binary numbers or fixed-point numbers yields in enormous partial products that are to be added to get final product. These partial products in number and the process of summing up partial products dictate the latency and power consumption of the multiplier design. Here, we present a novel binary counter design that hires stacking circuits, that groups all logic “1” bits as one, followed by a novel symmetric method to merge pairs of 3-bit stacks into 6-bit stacks and then changes them to binary counts. This results in drastic improvements in power and area utilization of the multiplier. Additionally, this paper also focuses on implementation of novel approximate compressor and exploits the same for the design of approximate multipliers that can be effectively employed in any electronic systems that are characterized by power and speed constraints.
Glia Cells Control Olfactory Neurogenesis by Fine-Tuning CXCL12

Olfaction depends on lifelong production of sensory neurons from CXCR4 expressing neurogenic stem cells. Signaling by CXCR4 depends on the concentration of CXCL12, CXCR4’s principal ligand. Here, we use several genetic models to investigate how regulation of CXCL12 in the olfactory stem cell niche adjusts neurogenesis. We identify subepithelial tissue and sustentacular cells, the olfactory glia, as main CXCL12 sources. Lamina propria-derived CXCL12 accumulates on quiescent gliogenic stem cells via heparan sulfate. Additionally, CXCL12 is secreted within the olfactory epithelium by sustentacular cells. Both sustentacular-cell-derived and lamina propria-derived CXCL12 are required for CXCR4 activation. ACKR3, a high-affinity CXCL12 scavenger, is expressed by mature glial cells and titrates CXCL12. The accurate adjustment of CXCL12 by ACKR3 is critical for CXCR4-dependent proliferation of neuronal stem cells and for proper lineage progression. Overall, these findings establish precise regulation of CXCL12 by glia cells as a prerequisite for CXCR4-dependent neurogenesis and identify ACKR3 as a scavenger influencing tissue homeostasis beyond embryonic development.
Modified Super-Twisting Algorithm-Based Model Reference Adaptive Observer for Sensorless Control of the Interior Permanent-Magnet Synchronous Motor in Electric Vehicles

In this paper, the model reference adaptive system (MRAS) method has been employed to observe speed in sensorless field-oriented control (FOC) with flux weakening (FW) and maximum torque per ampere (MTPA) operations for the interior permanent-magnet synchronous motor (IPMSM). This paper focuses on the modified MRAS observer, which is based on the sigmoid function as a switching function and also the adaptive sliding mode coefficient. The sliding mode strategies are employed for the adaptation mechanism instead of the PI controller. The conventional PI-MRAS causes oscillations in rotor speed. To solve this problem, the modified adaptive super-twisting algorithm (STA)-based MRAS method is proposed by utilizing the sigmoid function. The proposed modified MRAS is compared to conventional methods. Additionally, it is examined for performance against the fast terminal sliding mode (FTSM), which is applied to the MRAS as an adaptation mechanism in terms of sliding mode strategies. The modified STA-MRAS is explored under the ECE and EUDC (Extra Urban Driving Cycle) drive cycles for electric vehicle applications. Finally, the obtained results show the validity and capability of the proposed adaptive STA-MRAS in terms of speed tracking.
A Secure RPL Rank Computation and Distribution Mechanism for Preventing Sinkhole Attack in IoT-based Systems

The sinkhole attack detection mechanisms that have been reported till date are distributed in nature. Defending a sinkhole attack requires protecting the act of forging the rank computation task. This paper propose a secure centralized mechanism to ensure protection of rank computation process against sinkhole nodes in the IoT-Based Systems. The expectation maximization algorithm is used to optimally cluster the nodes into a group bearing the same rank. The distribution of ranks to the nodes is protected by the signature of the sink. The experimental results show that the optimal rank computation is secure against sinkhole nodes, however requires additional network communication between nodes and the sink node.