bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design and Implementation of Full Adder Using Negative Differential Resistance Circuits Based on CMOS Process
Authors: Gan Kwang-Jow , Zhang Li-Cheng 
Published: August 2024

Abstract

We demonstrate a full adder design based on several MOS-NDR circuits connected in series and in parallel. A basic MOS-NDR circuit is made of thee standard Si-based metal-oxide-semiconductor field-effect-transistor (MOSFET) devices. By adjusting the appropriate parameters of the gate width of the MOSFET, the Λ-type negative differential resistance (NDR) characteristic can be presented in its combined current-voltage (I-V) curve. The operating principle of this 1-bit full adder is based on the theory of monostable-bistable transmission logic gate (MOBILE). The bias voltage of this circuit is a clock signal, and its output voltage is a low or high logic level determined by the relative current peak conditions of the load and driver components of the MOBILE circuit. Most of the NDR-based applications designed in the general literature use resonant tunnel diode (RTD) devices as the main components. Compared with RTD device, our MOS-NDR circuit can be designed with standard CMOS process and simulated with HSPICE. We implement this full adder using 0.18 µm standard CMOS process.
Ambiguity in Business Process Reengineering: A Comprehensive Review of Trends, Challenges and Future Prospects.
Authors: Alam Md Mahbub 
Published: August 2024

Abstract

This document presents a comprehensive Systematic Literature Review (SLR) on the critical topic of Ambiguity In Business Process Reengineering (BPR). The review meticulously analyzes a range of methodologies, identifies prevalent challenges, and outlines potential avenues for future research in this domain. Through a thorough examination of 60 papers published between 2000 and 2023, this SLR illuminates evolving trends in Ambiguity Techniques, emphasizing the paramount importance of clear Business Process Reengineering in software development. By exploring the synergies between human expertise and computational methods, the review evaluates the strengths and weaknesses of various approaches, particularly their implications for collaborative efforts between Business Process Reengineering (BPR) engineers and testers. Notably, the study explores novel approaches aimed at problem-solving and preventing future challenges. Furthermore, it explores the promising integration of Artificial Intelligence and Machine learning with contextual awareness and adaptive learning models as a strategic means to address current limitations in unclear meaning. This research serves as a foundational contribution to advancing the field of BPR, with a specific focus on optimizing software development and delivery efficiency and effectiveness.
A Structural Equation Model of the Factors Affecting the Belt and Road Initiative (BRI) on the Perceived Benefits and Intention of Thai People to Use the China-Laos High-Speed Rail Service
Authors: Theerathitichaipa Kestsirin , Wisutwattanasak Panuwat , Se Chamroeun , Seefong Manlika , Jomnonkwao Sajjakaj , Champahom Thanapong , Ratanavaraha Vatanavongs , Kasemsri Rattanaporn 
Published: August 2024

Abstract

The Belt and Road Initiative (BRI) policy, with the China-Laos high-speed railway being a part of the BRI project. As it is well known, Thailand shares a border with Laos and has significant cross-border trade with China. In terms of tourism, Thailand is a globally popular destination, with Chinese tourists being the largest group of visitors. This study takes place in Thailand, a developing country, to examine the opportunities that may arise if Thailand prepares to handle the China-Laos high-speed railway. The objective of this research is to study the relationship between factors affecting BRI and Thai people's perceived benefits and their intention to use the China-Laos high-speed railway. Data was collected through a survey conducted in key trade gateway areas along the Thailand-Laos border, using Stratified Random Sampling of 1,540 Thai residents living in border provinces along the BRI route. The research findings indicate that Perceived Emotional is the most important factor in explaining Thai people's perception. Additionally, foreign direct investment, tourism, employment, living standards and society, economy, and logistics transportation positively influence the perceived benefits of BRI. Furthermore, the perceived benefits of BRI have a positive relationship with the attitudes of Thai people. The results also reveal that perceived benefits, attitudes, and subjective norms positively correlate with the intention to use the China-Laos high-speed railway. These findings can be utilized to provide in-depth insights to relevant agencies and assist in formulating policies and measures that align with the BRI policy. This alignment will enhance development to sustainable changes.
Lightweight Monocular Depth Estimation Using a Fusion- Improved Transformer
Authors: Sui Xin , Gao Song , Xu Aigong , Zhang Cong , Wang Changqiang , Shi Zhengxu 
Published: August 2024

Abstract

The existing deep estimation networks often overlook the issue of computational efficiency while pursuing high accuracy. This paper proposes a lightweight self-supervised network that combines convolutional neural networks (CNN) and Transformers as the feature extraction and encoding layers for images, enabling the network to capture both local geometric and global semantic features for depth estimation. First, depth-separable convolution is used to construct a dilated convolution residual module based on a shallow network to improve the shallow CNN feature extraction receptive field. In the transformer, a multidepth separable convolution head transposed attention module is proposed to reduce the computational burden of spatial self-attention. In the feedforward network, a two-step gating mechanism is proposed to improve the nonlinear representation ability of the feedforward network. Finally, the CNN and transformer are integrated to implement a depth estimation network with a local-global context interaction function. Compared with other lightweight models, this model has fewer model parameters and higher estimation accuracy. It also has better generalizability for different outdoor datasets. Additionally, the inference speed can reach 87 FPS, achieving better real-time performance and accounting for both inference speed and estimation accuracy.
Segmentation of Breast Cancer Masses in Mammography Images Using Deep Convolutional Neural Network (DCNN)
Authors: Hoseini Farnaz , Mirzaei Abbas 
Published: August 2024

Abstract

Mammography is one of the most important and effective ways to detect breast cancer, especially in the early stages of the disease. However, due to the complexity of breast tissue, the similarity between cancerous masses and natural tissues, the different sizes and shapes of masses, and the use of low-density X-ray radiation, mammogram images often have poor quality. Therefore, detecting lesions, especially in the early stages, is a challenging task. In this study, we address the improvement of breast cancer mass segmentation in mammography images. Accurate mass segmentation on mammograms is an important step in computer-aided diagnosis systems, which is also a challenging task because some mass lesions are embedded in natural tissues and have weak or ambiguous margins. The proposed method in this study presents an improved algorithm for segmenting cancerous masses in mammography images using a Deep Convolutional Neural Network (DCNN), which ultimately leads to mass classification into benign and malignant classes. Deep convolutional neural networks extract high-level concepts from low-level features, and are appropriate for handling large volumes of data. In fact, in deep learning, high-level concepts are defined by low-level features. Segmentation based on the proposed method with preprocessed images achieves more accurate delineation in high-resolution images, and ultimately improves the accuracy and sensitivity of mass tissue separation in the breast. In this study, we used three different architectures for deep convolutional neural networks. The proposed DCNNs were validated on mammography images of INbreast dataset. The reliability of the system's performance is ensured by applying 5-fold cross-validation. The proposed method has been evaluated based on accuracy, precision, sensitivity, and ROC criteria. The results obtained with an accuracy of 97.76% for the third proposed deep model indicate an improvement in the accuracy of the diagnosis as well as a reduction in the cost of the diagnostic process. Results showed that our proposed algorithm is significantly more accurate than other methods due to its deep and hierarchical extraction.
Abandoned croplands show higher insectivorous bat species and functional diversity than forest fragments in a communal land area of the Eastern Cape, South Africa
Authors: Meulen Khia R. van der , Richards Leigh R. , Shackleton Ross T , Cherry Michael I. 
Published: August 2024

Abstract

Deagrarianisation (cropland, field abandonment) is a widespread global phenomenon with high potential for carbon sequestration and for reversing biodiversity extinction debt thus promoting environmental sustainability and conservation. To date, much work on this topic has focused on plant succession and associated plant diversity, but few studies have considered faunal communities, particularly in Africa. Here we used passive acoustic monitoring to record insectivorous bat communities within forest fragments and former fields under communal land tenure in the Transkei region (Eastern Cape) of South Africa. Insectivorous bat diversity of fields, abandoned in the 1960s to 1980s, resembling late stages of succession, were compared to fragments of Transkei Coastal Scarp forest embedded within the landscape. We found that former fields hosted 14 species from 11 genera, comprising greater species richness, activity, Shannon-Weiner diversity, and functional diversity, irrespective of age, as compared to the forest fragments. Furthermore, the former fields exhibited comparable species richness to, and higher functional diversity than, three large neighbouring intact Transkei Scarp forests. Interestingly, the time since cultivation had ceased (35—64 years ago) had no measurable effect on species and functional diversity. Former fields are dominated by the invasive alien shrub Lantana camara and the indigenous pioneer tree Vachellia karoo, but nonetheless in terms of insectivorous bats, these landscapes have a conservation value as they are diverse both in terms of species and function. Mutual mechanisms to enhance both biodiversity conservation and the utility of the land to local communities should be further considered.
Structure and magnetic properties of epitaxial Sr-LaMnO3 thin films obtained by polymer assisted deposition
Authors: Vukmirović Jelena , Piper Danica , Šenjug Pavla , Pajić Damir , Miljević Bojan , Milanović Marija , Joksović Sara , Novaković Mirjana , S Vladimir V. 
Published: August 2024

Abstract

Epitaxial La1 − xSrxMnO3 (LSMO, where x = 0, 0.1, 0.3 and 0.5) films on single crystal SrTiO3 (001) substrate were obtained by water-based chemical solution deposition method, so-called polymer assisted deposition. The as-prepared films (heated at 750°C for 1 h) have thickness of ~ 30 nm, high uniformity, clear and well-defined interface and crack free surfaces. In addition, they are characterized by the formation of an imperfect crystal structure with some disoriented areas, small amount of non-stoichiometric phase and defects created just to support the epitaxial film growth. During multiple annealing at different temperatures up to 900°C epitaxial nature was preserved in all LSMO films and the structure rearrangement through elimination of defects and formation of unit cell closer to the corresponding bulk stoichiometric phase was observed. The magnetic properties of the LSMO thin film were measured using SQUID magnetometer in the temperature range of 5–400 K with the field applied parallel (in-plane) and perpendicular (out-of-plane) to the film surface. The angle dependence of the magnetic moment in the LSMO thin films at the room temperature was also measured by a vibrating sample magnetometer.
Dendrimer of aminoethylene carbonate as a potential retanning agent of hare skin
Authors: Maksimov Aleksei , Yarullin Bulat , Maksimova Ksenia , Latfullin Ilfat , Ostrovskaya Alla , Kharlampidi Kharlampii , Kutyrev Gennadii 
Published: August 2024

Abstract

The hare skin has weak leather tissue, which requires filling and tanning in order to prolong the period of use of products. To strengthen hare skin it was proposed to use aminoethylene carbonate dendrimer, which was first synthesized by the reaction of triethanolamine with dimethyl carbonate. The dendrimer was characterized by 1H NMR and IR spectroscopy, elemental analysis, TGA, SEM and dynamic light scattering. The aminoethylene carbonate molecule contains 6 terminal hydroxyl groups and has a number-average molecular weight of 674 g∙mol-1. The hare skins treated with chrome tanning agent, with and without dendrimer, have close shrinkage temperatures. However, the experimental samples filled with dendrimer show better physical and mechanical properties, higher degree of thickening and ordered dermis structure compared to the control samples. This study shows the effectiveness of using aminoethylene carbonate dendrimer as a retanning agent for hare skin.
A shady business in Legumes: Lutein epoxidase enables α-xanthophyll cycling
Authors: Leonelli Laurie , Attri Komal , Harris Jake , Brooks Matthew 
Published: August 2024

Abstract

Leaves rapidly adjust their xanthophyll pool in response to changes in light to funnel absorbed excitation energy toward either photochemistry or photoprotective energy dissipation. In roughly 60% of species surveyed, α-xanthophylls are interconverted between photoprotective lutein (L) and shade-enriched lutein epoxide (Lx), forming the lutein epoxide cycle (LxL cycle). Despite its prevalence, the enzyme involved in the epoxidation reaction of the LxL cycle is unknown. Using pigment profiling and canopy-specific RNAseq, we detect Lx throughout the middle and lower canopy of soybean and link its accumulation to the expression of a mono-oxygenase we call lutein epoxidase (LEP). We confirm LEP activity in a transient assay in Nicotiana benthamiana. LEPs are distinct from zeaxanthin epoxidases (ZEPs) and are conserved across many legumes. The discovery of an enzyme involved in α-xanthophyll cycling in an agriculturally important crop presents us with a new target for optimizing plant productivity in the shade.
Characterization of Unconventional Sources of Starch: Physicochemical and Thermal Properties
Authors: Pérez-Pacheco E. , Ortiz-Fernández A. , Ríos-Soberanis C. R. , Estrada-León R. J. , Moo-Huchín V. M. , Pérez-Padilla Y. , Canto-Pinto Jorge Carlos , Dzul-Cervantes Mario Adrian 
Published: August 2024

Abstract

This study aims to explore and characterize unconventional sources of starch, specifically Brosimum alicastrum (Ramón), Enterolobium cyclocarpum (Parota), Melicoccus bijugatus (Huaya), and Talisia floresii Standl (Colok), collected in the Yucatán Peninsula in México. Various analytical techniques, including scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA), were employed to evaluate the physicochemical and morphological properties of these starches. The results indicate that Ramón starch exhibits the highest crystallinity (38%), followed by Parota starch (37%), Colok (33%), and Huaya (22%). These structural differences significantly impact their thermal and mechanical properties. Parota and Colok starches demonstrated high thermal stability, making them suitable for applications in bioplastics and biodegradable packaging materials. Huaya starch, possessing lower thermal stability, is more appropriate for moderate-temperature applications in the food and pharmaceutical industries. DSC studies revealed that Colok starch exhibits the highest gelatinization enthalpy, representing a highly organized structure. These unconventional starches show promising characteristics for various industrial applications, offering sustainable and biodegradable alternatives to traditional polymeric materials.
The associations of long-term temperature and precipitation with chronic respiratory symptoms: Projections for the changing climate
Authors: Koskela Heikki O , Kaulamo Johanna T , Lätti Anne M 
Published: August 2024

Abstract

Purpose
To clarify the associations of climatic indices with chronic respiratory symptoms, with a final aim to approximate the effects of climate change on them.
Methods
An e-mail survey was directed to the members of the Finnish Pensioners` Federation. The mean 20-years’ precipitation and temperature in each subjects’ home municipality were obtained from the Finnish Meteorological Institute, separately for summer and winter. Adjusted multivariate models were utilized to investigate the associations of the climatic indices with chronic rhinosinusitis, chronic cough, wheezing with dyspnea, and sleep apnea.
Results
There were 6189 responders from 283 municipalities. Chronic rhinosinusitis and chronic cough were most prevalent in the southeastern regions of the country, where the precipitation counts were highest. In the multivariate models, winter precipitation in the home municipality increased the risks of chronic rhinosinusitis and chronic cough (adjusted OR 1.79 (1.29-2.49) per 100 mm, p < 0.001, and 1.57 (1.19 to 2.07), p = 0.001, respectively). Wheezing with dyspnea and sleep apnea were not associated with the climatic indices.
Conclusion
Chronic rhinosinusitis and chronic cough were associated with long-term winter precipitation. Given the anticipated increase in winter precipitation in Northern America and Northern Europe, the prevalences of chronic rhinosinusitis and chronic cough may increase there.
Spatiotemporal cerebral blood flow dynamics underlies emergence of the limbic-sensorimotor-association cortical gradient in human infancy
Authors: Huang Hao , Detre John , Hyland Jessica , Sindabizera Kay , Kuschner Emily , Edgar J , Peng Yun , Ouyang Minhui 
Published: August 2024

Abstract

Infant cerebral blood flow (CBF) delivers nutrients and oxygen to fulfill brain energy consumption requirements for the fastest period of postnatal brain development across the lifespan. However, organizing principle of whole-brain CBF dynamics during infancy remains obscure. Leveraging a unique cohort of 100 + infants with high-resolution arterial spin labeled MRI, we found the emergence of the cortical hierarchy revealed by the highest-resolution infant CBF maps available to date. Infant CBF across cortical regions increased in a biphasic pattern with initial rapid and sequentially slower rate, with break-point ages increasing along the limbic-sensorimotor-association cortical gradient. Increases in CBF in sensorimotor cortices were associated with enhanced language and motor skills, and frontoparietal association cortices for cognitive skills. The study discovered emergence of the hierarchical limbic-sensorimotor-association cortical gradient in infancy, and offers standardized reference of infant brain CBF and insight into the physiological basis of cortical specialization and real-world infant developmental functioning.
Blockchain-Enabled Security Model for VANETs: A Novel Approach to Authentication and Position
Authors: Faisal Syed Mohd 
Published: August 2024

Abstract

Vehicular Ad-hoc Networks (VANET) is infrastructure-less networks that does not rely on a preexisting infrastructure and are inherently vulnerable to cyber-attacks due to their intrinsic openness. We proposed a new blockchain-based security model that is meant to make VANET safer by adding methods for authentication and position verification. The proposed model uses Road Side Units (RSUs) to verify the identification of vehicles and an iterative method to verify the vehicle’s geographical location by calculating the Time Difference of Arrival (TDOA). Blockchain technology is a key part of keeping track of safety event messages, location badges, and trust levels, which ensures compliance with local regulations. The proposed model was simulated under the OMNeT + + Veins, and SUMO simulators. In situations where there are no malicious nodes, the model has a better Packet Delivery Ratio (PDR) than common protocols like ASC, LAKAP, and HEPPA. The proposed method constantly has a big advantage in PDR, even when there are malicious nodes present. This shows how reliable the proposed method is. We also examined End-to-End Delay, Transmission overhead, and Packet Loss Ratio, which shows that the model can make networks more efficient. The simulation results proved that the proposed model is a strong way to improve the safety and performance of communication networks, especially when it comes to self-driving and connected vehicles. These encouraging results pave the way for more study to improve how useful and effective blockchain implementation is in VANETs, which is in line with the dynamic landscape of connected vehicles.
Assessing Allura Red Concentration in Commercial Tropical Punch Kool-Aid: A Study
Authors: Rao Idhant 
Published: August 2024

Abstract

This study investigates the concentration of Allura Red dye in commercial Kool-Aid to determine whether its levels are within safe limits as specified by regulatory bodies such as the FDA. FD & C Red 40, also known as Allura Red, has been linked to adolescent hyperactivity [1] and symptoms of attention-deficit/hyperactivity disorder [2], raising concerns about its safety. In a randomized study using spectrophotometry and stoichiometry conducted in a high school laboratory, we measured and analyzed the concentration of Allura Red in various dilution levels of Kool-Aid. Our results indicate that the concentration of Allura Red in the prepared Kool-Aid solution from one Kool-Aid container exceeds the determined calculated, acceptable limit suggesting potential health risks associated with consumption.
Dynamic X-ray Microtomography vs. Laser-Doppler Vibrometry: A Comparative Study
Authors: Ivanovic Aleksandra , Cheng Jeffrey Tao , Schmeltz Margaux , Schlepütz Christian M. , Bonnin Anne , Anschuetz Lukas 
Published: August 2024

Abstract

Purpose: There are challenges in understanding the biomechanics of the human middle ear, and established methods for studying this system show significant limitations. In this study, we evaluate a novel dynamic imaging technique based on synchrotron X-ray microtomography designed to assess the biomechanical properties of the human middle ear by comparing it to laser-Doppler vibrometry (LDV).
Methods: We examined three fresh-frozen temporal bones (TB) using dynamic synchrotron-based X-ray microtomography for 256 Hz and 512 Hz, stimulated at 110 dB and 120 dB SPL. In addition, we performed measurements on these TBs using 1D LDV, a well-established method.
Results: The normalized displacement values (µm/Pa) at the umbo and the posterior crus of the stapes are consistent or within 5-10 dB differences between all LDV and dynamic microtomography measurements and previously reported literature references. In general, the overall behavior is similar between the two measurement techniques. Conclusion: In conclusion, our results demonstrate the suitability of dynamic synchrotron-based X-ray microtomography in studying the middle ear’s biomechanics. However, this study shows that better standardization regarding acoustic stimulation and measurement points is needed to better compare the two measurement techniques.