Miracle-dz/UniFAR-FTUs huggingface dataset:
Fish Consumption Improved Head Circumference and Mid-Upper Arm Circumference among Infants in Zambia: A Randomised Controlled Trial

Fish is a good source of Animal Source Proteins (ASP). Families from low-income countries with limited access to other animal source proteins can utilize it to improve the nutrition status of infants and young children. The objective of the study was to assess if fish fed during the early complementary feeding period had an effect on improved head circumference (HC) and mid-upper arm circumference (MUAC) among infants aged 6–7 months. A randomised controlled trial was conducted from April 2019 to January 2020 in the Samfya district, Luapula Province, Zambia. The infants (238) were randomised to either the fish group (intervention) or the sorghum group (control). Every week for a period of 6 months, infants received seven sachets of fish powder and sorghum powder, respectively. Compliance was also monitored during the fish powder distribution. The head circumference measurements were conducted at baseline and once each follow-up month for a period of six months while the MUAC measurements were conducted twice (at baseline and endline). Using statistical software for data science (STATA) (version 16), a linear mixed effect model was used to analyse the data. The results showed that fish improved head circumference for age z score (HCZ) by 0.53 (95% CI: 0.23–0.82), p-value < 0.001, and MUAC by 0.36 (95% CI: 0.13–0.59) p-value < 0.002. Therefore, fish can be used as the main source of protein in complementary foods for infants and young children in low-income communities with limited access to meat.
Multiclass Segmentation of Breast Tissue and Suspicious Findings: A Simulation-Based Study for the Development of Self-Steering Tomosynthesis

In breast tomosynthesis, multiple low-dose projections are acquired in a single scanning direction over a limited angular range to produce cross-sectional planes through the breast for three-dimensional imaging interpretation. We built a next-generation tomosynthesis system capable of multidirectional source motion with the intent to customize scanning motions around “suspicious findings”. Customized acquisitions can improve the image quality in areas that require increased scrutiny, such as breast cancers, architectural distortions, and dense clusters. In this paper, virtual clinical trial techniques were used to analyze whether a finding or area at high risk of masking cancers can be detected in a single low-dose projection and thus be used for motion planning. This represents a step towards customizing the subsequent low-dose projection acquisitions autonomously, guided by the first low-dose projection; we call this technique “self-steering tomosynthesis. ” A U-Net was used to classify the low-dose projections into “risk classes” in simulated breasts with soft-tissue lesions; class probabilities were modified using post hoc Dirichlet calibration (DC). DC improved the multiclass segmentation (Dice = 0.43 vs. 0.28 before DC) and significantly reduced false positives (FPs) from the class of the highest risk of masking (sensitivity = 81.3% at 2 FPs per image vs. 76.0%). This simulation-based study demonstrated the feasibility of identifying suspicious areas using a single low-dose projection for self-steering tomosynthesis.
Design and Implementation of a Hierarchical Digital Twin for Power Systems Using Real-Time Simulation

This paper presents a hierarchical Digital Twin architecture and implementation that uses real-time simulation to emulate the physical grid and support grid planning and operation. With the demand for detailed grid information for automated grid operations and the ongoing transformation of energy systems, the Digital Twin can extend data acquisition by establishing a reliable real-time simulation. The system uses observer algorithms to process model information about the voltage dependencies of grid nodes, providing information about the dynamic behavior of the grid. The architecture implements multiple layers of data monitoring, processing, and simulation to create node-specific Digital Twins that are integrated into a real-time Hardware-in-the-Loop setup. The paper includes a simulation study that validates the accuracy of the Digital Twin, in terms of steady-state conditions, dynamic behavior, and required processing time. The results show that the proposed architecture can replicate the physical grid with high accuracy and corresponding dynamic behavior.
Capitalization versus expensing of R&D costs under IAS 38: An empirical investigation using machine learning

: We study whether financial ratios or raw accounting data can achieve better out of sample predictions of R&D accounting treatment. We show that when the traditional logistic regression is used, financial ratios outperform raw accounting data. However, if machine learning algorithms are used, we provide evidence that raw accounting data may convey more information about future R&D accounting treatment. Finally, we introduce a Hybrid model, consisted of both ratios and raw data, which has achieved the best out of sample performance compared to all the examined models.
Sequence Stratigraphy, Sedimentology, and Reservoir Characteristics of the Middle Cretaceous Mishrif Formation, South Iraq

The Cenomanian–Early Turonian Mishrif Formation is a great contributor to oil production in Iraq. Integrating petrographic, mineralogical, and wireline logging data from 52 wells, this study provides an improved understanding of the sequence stratigraphy, depositional evolution, and reservoir characteristics of the Mishrif Formation in the Mesopotamian Basin, south Iraq. Five types of facies associations are classified: lagoon, shoal, rudist bioherm, shallow marine, and deep marine. Such a classification allows convenient differentiation and interpretation of wireline logs. A sequence stratigraphic framework including five third-order sequences (Mhf 1 to Mhf 5) for the Mishrif Formation is established mainly using wireline logging data of close-distance wells, with the aid of cores and thin sections. Two end-member depositional evolution stages are recognized, from clinoform-like progradational shoal complexes in Mhf 1 within a shallow marine environment, to tidal channels in Mhf 2–3 within a lagoon environment. For Mhf 4–5, abrupt changes in facies associations from north to south indicate the development of an intra-shelf basin where organic-rich mudstones directly overlie the shallow marine grainstone shoals and lagoonal wackestones. Reservoir characteristics and compartmentalization are directly controlled by the sequence stratigraphic framework. Sequence boundaries are featured by wackestones and mudstones overprinted by cementation; they are regionally correlatable and work as regional barriers. Shoal complexes in Mhf 1 and tidal channels in Mhf 2–3 are the main reservoir units. Mudstones and wackestones are intra-reservoir baffles and become more frequently developed towards the south, reflecting the increasing water depth towards south. The characterization of the tidal channels, clinoform-like shoals, and intrashelf basinal deposits in the current study could benefit later development of the Mishrif Formation.
Anisotropy-Based Estimation for Sensor Network with Non-Centered Disturbance

: This paper concerns the anisotropy-based estimation design for sensor networks with coloured external disturbance. The boundedness criterion of anisotropic norm for estimation problems in network systems relies on the analysis of multiplicative noise systems in the framework of anisotropy-based theory. The solution of the considered problem is reduced to a convex optimization problem.
An Ultrathin Low-Profile Tightly Coupled Dipole Array Fed by Compact Zigzagging Baluns

In this paper, we propose for the first time a novel feed approach to a tightly coupled dipole array (TCDA). Firstly, compact zigzagging microstrip feedlines are utilized as baluns to feed our array elements to obtain wideband impedance-matching characteristics. Secondly, this array is designed on ultrathin substrates aiming at obtaining ultra-tight coupling between the dipole arms of two neighboring elements. Some irreplaceable parasitic pads are developed and added to the radiating arms to improve both the impedance and radiation characteristics of the TCDA. With these technologies, a 12 × 12 TCDA prototype is designed, fabricated and measured for verification. The array achieves an impressive impedance bandwidth spanning of 4–18 GHz for S11<−10 dB. Its radiation patterns and realized gain are measured to verify its stable electromagnetic characteristics. Its realized gain is from 15 dB to 25 dB within the operating frequency band. Its efficiency is around 91%. Its measured results show good agreement with simulations.
Developing an Interferogram-Based Module with Machine Learning for Maintaining Leveling of Glass Substrates

In this research, we propose a method that utilizes machine learning to maintain the parallelism of the resonant cavity in a Fabry–Perot interferometer designed specifically for glass substrates. Based on the optical principle and theory, we establish a proportional relationship between interference fringes and the inclination angle of the mirrors. This enables an accurate determination of the inclination angle using supervised learning, specifically classification. By training a machine learning model with labeled data, interference fringe patterns are categorized into three levels, with approximately 100 training data available for each level in each location. The experimental results of Level 2 and Level 3 classification indicate an average number of corrections of 2.55 and 3.55 times, respectively, in achieving the target position with a correction error of less than 30 arc seconds. These findings demonstrate the essential nature of this parallelism maintenance technology for the semiconductor industry and precision mechanical engineering.
Cybersecurity for Blockchain-Based IoT Systems: A Review

The Internet of Things (IoT) has become a pervasive technology with various applications ranging from smart homes and cities to industrial automation and healthcare. However, the increasing adoption of IoT devices has also raised significant concerns about cybersecurity and privacy. Blockchain, as a distributed and immutable ledger technology, has been proposed as a potential solution to enhance the security and privacy of IoT systems. Blockchain-based IoT systems offer several benefits, such as decentralization, transparency, and data integrity. However, they also pose unique cybersecurity challenges that need to be addressed for their secure and reliable deployment. In this paper, we review the existing literature and highlight the key challenges in cybersecurity for blockchain-based IoT systems. We categorize these challenges into three main areas: (i) IoT device security, (ii) blockchain security, and (iii) integration of IoT devices with blockchain (network security). Through an in-depth analysis, we present the current state of research and discuss potential solutions for each challenge. Additionally, we contribute by identifying future research directions to address these challenges and enhance the cybersecurity of blockchain-based IoT systems.
Cell-Penetrating Peptides as Valuable Tools for Nose-to-Brain Delivery of Biological Drugs

Due to their high specificity toward the target and their low toxicity, biological drugs have been successfully employed in a wide range of therapeutic areas. It is yet to be mentioned that biologics exhibit unfavorable pharmacokinetic properties, are susceptible to degradation by endogenous enzymes, and cannot penetrate biological barriers such as the blood–brain barrier (i.e., the major impediment to reaching the central nervous system (CNS)). Attempts to overcome these issues have been made by exploiting the intracerebroventricular and intrathecal routes of administration. The invasiveness and impracticality of these procedures has, however, prompted the development of novel drug delivery strategies including the intranasal route of administration. This represents a non-invasive way to achieve the CNS, reducing systemic exposure. Nonetheless, biotherapeutics strive to penetrate the nasal epithelium, raising the possibility that direct delivery to the nervous system may not be straightforward. To maximize the advantages of the intranasal route, new approaches have been proposed including the use of cell-penetrating peptides (CPPs) and CPP-functionalized nanosystems. This review aims at describing the most impactful attempts in using CPPs as carriers for the nose-to-brain delivery of biologics by analyzing their positive and negative aspects.
Numerical Investigation on Pairing Solutions of Non-Positive Displacement Pumps and Internal Gear Pump for High-Speed Design

Raising the working speed of hydraulic pumps to maximize the efficient matching range of electric motors is one of the possible ways to achieve energy efficiency in electric machinery. By means of a simulation method verified with subsequent experiments in terms of filling efficiency, this paper first analyzed the suction capacity of crescent-type internal gear pumps with different geometric parameters at high speed, and the gear pair that is more suitable for high-speed operation was obtained. Subsequently, as the more significant contributions, two pairing solutions of a non-positive displacement pump and an internal gear pump were proposed to pressurize the inlet of the gear pump to keep it from cavitating. In the compact design solution, the inclined-holes type and axial-flow blade pumps share the same speed as the hydraulic pump, while the decentralized layout solution allows for flexible adjustment of the centrifugal impeller-type pump speed to maximize the filling capability. The final simulation results show that, with the help of inclined-holes type and centrifugal impeller type pumps, the filling efficiency of the internal gear pump at 6000 rpm can be improved by 3.59% and 5.84%, respectively, while the axial-flow blades pump fails to eliminate cavitation regardless of speed. Moreover, when the hydraulic pump works at 6000 rpm, the centrifugal impeller speed needs to be set above 2500 rpm to make sense.
Quasi-static analysis of a compliant tripod stage with plane compliant lever mechanism

In nanopositioning system, the compliant tripod stages have proved to have enormous advantages for out-of-plane (z/tip/tilt) positioning in turns of compactness, simplicity in structure, and economic cost. However, most of the present-day compliant tripod stage undergo manufacturing problems due to a complicate structure, and little study has been carried out to formulate the tri-inputs and tri-outputs relationship, which is essential for precise positioning. Accordingly, this paper presents the quasi-static analysis of a novel compliant tripod stage with an equivalent plane model to achieve precise position analysis for nanopositioning. Three-plane compliant lever mechanisms and cylindrical flexure hinges with high length–diameter ratio are employed, which mitigate couple influence and enable easy fabrication via planar manufacturing processes. The spatial output motions of the compliant tripod stage are first split among inputs of the three-plane compliant lever mechanisms, where the lateral translations of the compliant tripod stage are included. Then the displacement equations of the plane compliant lever mechanism are formulated through Castigliano’s second theorem. The model is further verified by finite element analysis. Finally, an experimental test system is set up and the test results validate the proposed approach.
Cytotoxic Properties of Polyurethane Foams for Biomedical Applications as a Function of Isocyanate Index

Polyurethane foams are widely used in biomedical applications due to their desirable mechanical properties and biocompatibility. However, the cytotoxicity of its raw materials can limit their use in certain applications. In this study, a group of open-cell polyurethane foams were investigated for their cytotoxic properties as a function of the isocyanate index, a critical parameter in the synthesis of polyurethanes. The foams were synthesized using a variety of isocyanate indices and characterized for their chemical structure and cytotoxicity. This study indicates that the isocyanate index highly influences the chemical structure of polyurethane foams, also causing changes in cytotoxicity. These findings have important implications for designing and using polyurethane foams as composite matrices in biomedical applications, as careful consideration of the isocyanate index is necessary to ensure biocompatibility.
Deep Neural Networks for Joint Source-Channel Coding

Digital communication systems typically entail separate steps for source coding and channel coding. In source coding, the source signal, e.g., text, image, or video, is mapped to a sequence of symbols that compresses the data for efficient transmission while guaranteeing a certain reconstruction quality. This involves stripping the original source signal of any redundancies. In channel coding, redundant symbols are systematically added to the compressed source sequence prior to transmission. These redundant symbols enable the receiver to detect or correct any errors that may be introduced during the transmission of data over the channel. Surprisingly, Shannon showed that this two-step approach to data communication is optimal for ergodic sources and channels when infinite blocklength codes are allowed [1]. Known as Shannon’s separation theorem, this has been extended to a larger class of source, channel, and network scenarios [2–4]. Optimality of separation in Shannon’s theorem assumes no constraint on the complexity of the source and channel code design. However, in practice, having large blocklengths may not be possible due to computational complexity as well as delay constraints. Thus, in challenging communication scenarios with more stringent power or latency constraints, or in the presence of multiple users or rapidly changing channels, the limitations of this separation-based approach become more apparent, significantly limiting the performance with respect to its fundamental information theoretic limit [5–7]. The alternative is to design the mapping from the source signal directly to the channel input, which is called joint source-channel coding (JSCC). There have been significant research efforts on JSCC over the years; however, these have focused either on the theoretical analysis under some idealistic source and channel distributions, e.g., [8–13], or on the joint optimization of the component parameters (vector quantizer, index assignment, channel code, and modulator) of an inherently separate design, e.g., [14–21]. Nonetheless, despite the suboptimality of separate source and channel coding in many practical settings, the lack of powerful JSCC techniques with reasonable coding and decoding complexities has prevented the emergence of alternatives to the modular separation-based approach. In this chapter, we show that deep neural networks (DNNs) can be used to design JSCC solutions with impressive results. We illustrate the potential of DNNbased JSCC through concrete examples for various source and channel distributions.
Enhancement of Medical Ultrasonic Image Based on Gray-level Histogram Equalization

The enhancement on the detail of local issue and endocardium boundary were obtained by using full frame histogram equalization (FFHE), local area histogram equalization (LAHE) and adaptive neighborhood histogram equalization (ANHE). The characteristics of the methods have been compared. To enhance the detail of local issue, it is better to use ANHE method. To enhance the edge of full image, which the full information must been taken into account, it is better to use FFHE method.
LINK-BASED MODELS FOR SURVIVAL DATA WITH INTERVAL AND CONTINUOUS TIME CENSORING

We present a flexible family of link-based regression models with time-independent (baseline) covariates. Particular choices of the link function yield a proportional hazard or a proportional odds model, among others. The background hazard function in the model is estimated using B-splines. This yields a full likelihood under both continuous time and random interval censoring. Residuals for influence and goodness-of-fit are described. Two examples are shown, one in continuous time and the other under interval censoring.
Low-light image enhancement based on Retinex theory for beam-splitting prism system

The existing color image enhancement methods are utilized for the most part to directly improve the color image that is obtained through the use of a Bayer array camera, whereas the color image that is obtained through the use of a prism camera is the result of the fusion of three primary color images that have been collected independently. As a result, a method for enhancing color photographs based on three images of primary colors that have a low level of light has been proposed. In this paper, we first transfer RGB to HSV space for image enhancement. In the V channel, we use guided filtering combined with improved SSR method to better preserve edge information. Then the S channel is adjusted adaptively to make the image look more natural. Finally, the image is transferred from HSV space back to RGB space. Compared with other traditional methods, our method achieves better results in PSNR, SSIM and NIQE, and has less computational complexity.
A Reproducible Approach of Preparing High-Quality Overdoped Bi 2 Sr 2 CaCu 2 O 8+ δ Single Crystals by Oxygen Annealing and Quenching Method

We report a reproducible approach in preparing high-quality overdoped Bi2Sr2 CaCu2 O8+δ (Bi2212) single crystals by annealing Bi2212 crystals in high oxygen pressure followed by a fast quenching. In this way, high-quality overdoped and heavily overdoped Bi2212 single crystals are obtained by controlling the annealing oxygen pressure. We find that, beyond a limit of oxygen pressure that can achieve most heavily overdoped Bi2212 with a Tc ~63 K, the annealed Bi2212 begins to decompose. This accounts for the existence of the hole-doping limit and thus the Tc limit in the heavily overdoped region of Bi2212 by the oxygen annealing process. These results provide a reliable way in preparing high-quality overdoped and heavily overdoped Bi2212 crystals that are important for studies of the physical properties, electronic structure and superconductivity mechanism of the cuprate superconductors.
Equalization technology of special vehicle power battery pack

In special vehicles, single cells or battery packs often provide energy for the vehicle after being connected in series and parallel. However, due to the influence of the single battery production process and the use environment, inconsistencies may occur in the battery pack, resulting in a decline in the performance of the battery pack. Therefore, the battery balance management system has increasingly become an indispensable module in the battery management system. It can perform real-time balanced management of the battery pack according to the battery pack status information, thereby avoiding the expansion of inconsistency, improving the capacity utilization rate of the battery pack, slowing down the aging speed of the battery pack, and increasing the driving mileage of the vehicle. To sort out and summarize the current development of battery pack balancing system, based on a large number of references, this paper studies and analyzes the mechanism of inconsistency, the commonly used equalization topology and control strategy of lithium power battery pack. And finally, the development trend of battery pack equalization technology for special vehicles is prospected.