Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of 3D Printable Calcium Phosphate Cement Scaffolds with Cockle Shell Powders

Three-dimensional (3D) printed calcium phosphate cement (CPC) scaffolds are increasingly being used for bone tissue repair. Traditional materials used for CPC scaffolds, such as bovine and porcine bone, generally contain low amounts of calcium phosphate compounds, resulting in reduced production rates of CPC scaffolds. On the other hand, cockle shells contain more than 99% CaCO3 in the form of amorphous aragonite with excellent biocompatibility, which is expected to increase the CPC production rate. In this study, 3D-printed cockle shell powder-based CPC (CSP-CPC) scaffolds were developed by the material extrusion method. Lactic acid and hyaluronic acid were used to promote the printability. The characterization of CSP-CPC scaffolds was performed using Fourier transform infrared spectra, X-ray diffraction patterns, and scanning electron microscopy. The biocompatibility of CSP-CPC scaffolds was evaluated using cell viability, Live/Dead, and alkaline phosphatase assays. In addition, CSP-CPC scaffolds were implanted into the mouse calvarial defect model to confirm bone regeneration. This study provides an opportunity to create high value added in fishing villages by recycling natural products from marine waste.
Fusing Local Shallow Features and Global Deep Features to Identify Beaks

Simple Summary Cephalopods are not only important economic products in fisheries, but also located in the middle pyramid of the marine ecosystem, playing a role of carrying the top and bottom. Cephalopods are the meals of large marine mammals, and their soft tissues are mostly digested in the stomach, and the beaks can be retained as hard tissues of cephalopods, which are structurally stable and resistant to corrosion. Therefore, the biodiversity of cephalopods can be analyzed by studying the beaks. However, there are many difficulties in the identification of beaks, such as the high level of similarity between different species of beaks and the variability arising from the growth process. The local shallow features, namely texture features and morphological features, and the global deep features were used, and the two types of features were fused for identification. This study verifies the complementarity between the two types of features and further contributes to the progress of beak recognition, providing a new approach to analyzing the biodiversity of cephalopods. Abstract Cephalopods are an essential component of marine ecosystems, which are of great significance for the development of marine resources, ecological balance, and human food supply. At the same time, the preservation of cephalopod resources and the promotion of sustainable utilization also require attention. Many studies on the classification of cephalopods focus on the analysis of their beaks. In this study, we propose a feature fusion-based method for the identification of beaks, which uses the convolutional neural network (CNN) model as its basic architecture and a multi-class support vector machine (SVM) for classification. First, two local shallow features are extracted, namely the histogram of the orientation gradient (HOG) and the local binary pattern (LBP), and classified using SVM. Second, multiple CNN models were used for end-to-end learning to identify the beaks, and model performance was compared. Finally, the global deep features of beaks were extracted from the Resnet50 model, fused with the two local shallow features, and classified using SVM. The experimental results demonstrate that the feature fusion model can effectively fuse multiple features to recognize beaks and improve classification accuracy. Among them, the HOG+Resnet50 method has the highest accuracy in recognizing the upper and lower beaks, with 91.88% and 93.63%, respectively. Therefore, this new approach facilitated identification studies of cephalopod beaks.
Application of Single Particle ICP-MS for the Determination of Inorganic Nanoparticles in Food Additives and Food: A Short Review

Due to enhanced properties at the nanoscale, nanomaterials (NMs) have been incorporated into foods, food additives, and food packaging materials. Knowledge gaps related to (but not limited to) fate, transport, bioaccumulation, and toxicity of nanomaterials have led to an expedient need to expand research efforts in the food research field. While classical techniques can provide information on dilute suspensions, these techniques sample a low throughput of nanoparticles (NPs) in the suspension and are limited in the range of the measurement metrics so orthogonal techniques must be used in tandem to fill in measurement gaps. New and innovative characterization techniques have been developed and optimized for employment in food nano-characterization. Single particle inductively coupled plasma mass spectrometry, a high-throughput nanoparticle characterization technique capable of providing vital measurands of NP-containing samples such as size distribution, number concentration, and NP evolution has been employed as a characterization technique in food research since its inception. Here, we offer a short, critical review highlighting existing studies that employ spICP-MS in food research with a particular focus on method validation and trends in sample preparation and spICP-MS methodology. Importantly, we identify and address areas in research as well as offer insights into yet to be addressed knowledge gaps in methodology.
Stratégies de coopération dans les réseaux radio cognitif

Les reseaux radio actuelles utilisent le spectre inefficacement, car une bande de frequence est allouee de facon permanente a une technologie specifique. Vu que le spectre est une ressource limitee, cette attribution statique ne pourra bientot plus combler les besoins des systemes de transmission qui ne cessent de croitre. On peut toutefois optimiser l'utilisation du spectre en permettant des transmissions secondaires (SU) dans les espaces libres du primaire (PU). Cette vision constitue l'objectif principal de la radio cognitive. Nous proposons d'evaluer les strategies de transmission pour la coexistence des systemes primaires (PU) et SU dans les memes reseaux. Plus concretement, nous nous focalisons sur un scenario spatial interweave en emettant les signaux SU dans les espaces vides du PU a l'aide d'un precodeur lineaire. Neanmoins, ce precodage necessite une connaissance a priori des canaux interferents. L'echange d'informations entre le PU et le SU etant proscrit, nous exploitons l'hypothese de la reciprocite du canal. Cette hypothese compense l'absence de cooperation, mais elle n'est pas si evidente a exploiter en pratique a cause des perturbations des circuits radio frequence. Nous suggerons de compenser ces perturbations par des methodes de calibration relative. Nous proposons ensuite une implementation temps-reel des solutions sur une plateforme LTE. Pour finir, nous generalisons l'approche RC a un systeme de transmission multi-utilisateurs, a travers une combinaison des techniques RC et massive MIMO, cette approche constitue s’etablit comme une solution a la progression exponentielle du trafic.
DSG-PL: ROI Extraction Based on Dual Saliency Guided Progressive Learning for Weakly Labeled Remote Sensing Images

Region of Interest (ROI) extraction from weakly annotated remote sensing images (RSIs) can save the huge labor cost of labelling accurate pixel-level annotations. However, weakly supervised approaches with sparseness and incompleteness inevitably result in a performance gap compared with fully supervised counterparts. To tackle this issue, a dual saliency guided progressive learning (DSG-PL) framework is developed, which focuses on progressively enhancing the quality of supervision from the image level to the precise pixel level. To begin, a dual saliency constraint mechanism is created to guide the training of a classification network in both an explicit and implicit manner for generating integral pixel-wise pseudo labels (PLs). Then, to gradually refine the initial PLs, an adaptive label self-correction module is presented, in which the updated labels are used to iteratively train a context-enhanced segmentation network, therefore constantly boosting model performance. Finally, a confidence-aware denoising loss is intended to alleviate the impacts of training with noisy PLs by adaptively reweighting the pixel-wise loss with confidence scores. Comprehensive evaluations and ablation studies verify the superiority of the proposed DSG-PL.
A COMPARISON OF STATE-OF-THE-ART ALGORITHMS FOR LEARNING BAYESIAN NETWORK STRUCTURE FROM CONTINUOUS DATA

A digital data receiving arrangement, which adapts itself to channel variations of a transmission system, comprises an adaptive receiver stage (11), having an adaptive equalizer and at least one sampler, and producing, at a certain rate, complex samples yk from the input signal x(t), a decision circuit (14) supplying detected complex samples ak and an adaptive timing recovery circuit (12) determining the optimal sampling instant by minimizing a quadratic function J which represents the difference between yk and ak. The adaptive timing recovery circuit comprises a device (121) for shaping a primary clock signal in accordance with a secondary clock signal, whose period is twice the period of the primary clock and whose consecutive ascending edges are spaced in time by T1 and T2, said secondary clock producing alternately two sampling instants tau and tau + DELTA tau . By minimizing the function J, on the basis of the difference determined for two instants tau k and tau k+ DELTA tau , the control of the timing recovery is defined for the consecutive sampling instants tau k and tau k+1.
Al-based intrusion detection systems for in-vehicle networks: a survey.

The Controller Area Network (CAN) is the most widely used in-vehicle communication protocol, which still lacks the implementation of suitable security mechanisms such as message authentication and encryption. This makes the CAN bus vulnerable to numerous cyber attacks. Various Intrusion Detection Systems (IDSs) have been developed to detect these attacks. However, the high generalization capabilities of Artificial Intelligence (AI) make AI-based IDS an excellent countermeasure against automotive cyber attacks. This article surveys AI-based in-vehicle IDS from 2016 to 2022 (August) with a novel taxonomy. It reviews the detection techniques, attack types, features, and benchmark datasets. Furthermore, the article discusses the security of AI models, necessary steps to develop AI-based IDSs in the CAN bus, identifies the limitations of existing proposals, and gives recommendations for future research directions.
A robust interface finite element formulation for modeling brittle material failure problems

Failure of many brittle materials and structures can be modeled using interface‐oriented finite elements combined with intrinsic cohesive zone models. The discontinuous Galerkin (DG) finite element method provides an innovative framework for modeling brittle crack propagation with zero‐thickness interface elements, which can accommodate extrinsic cohesive laws to avoid the artificial compliance required in intrinsic cohesive models. However, robust formulations and implementations of DG methods are critical in alleviating the well‐known convergence issues for both crack nucleation and propagation with reduced instability. This paper presents a robust interface element formulation by modifying the incomplete interior penalty Galerkin (IIPG) method, which successfully avoids the initial element interface penetration across elements that occurs prior to crack nucleation, and thereby greatly reduces the instability issue as cracks open. We further verified and validated our implementation by using a bar tension test and a beam fracturing benchmark. The robustness of our proposed interface element method was demonstrated by a micromechanics fiber/matrix debonding problem with 64 fibers embedded in a bulk matrix.
Features and Comparative Research on Ecological Civilization Vocabularies in the Five-Year Plan of China: An Analysis Based on Semantic Phrases

The Five-Year Plan (FYP) in China guides the social and economic development. The features of ecology-related vocabularies in national and regional FYPs help to study China's emphasis and focus on ecological civilization. In this paper, a multi-phrase dictionary with syntactic and semantic features is constructed to analyze the features and trends of ecology-related vocabularies through social network and phrase topic model. Then, based on studies on the 13th and 14th FYPs of China and 31 provinces and cities, it is found that remarkable different stage definitions and tasks of ecological civilization construction are proposed according to different description vocabularies, with more pragmatic measures to fulfill its “carbon” target in 2030 as a duty-bound responsibility and mission to cope with climate change. The research ideas and methods in this paper can provide references for similar policy text analysis, and the conclusions from empirical studies are helpful to grasp the focus and trends of ecological civilization-related policies in China and various provinces and cities.
Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Methods This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation.
8 Bare-Foot Activists: Transformations In The Haratine Movement In Mauritania

This chapter analyzes the transformations undergone by the Haratine movement since its first actions in 1980. It describes the trajectory of the collective action as it developed at the interface between society, politics and the struggle for civil and human rights. The chapter focuses on the movement? s origins and the successive changes in its form of organization, types of actions and the outcome of its activism. Located between the Western Sahara to the north and the Senegal River to the south, the Islamic Republic of Mauritania has a population of about three million. Questioning the legitimacy of slavery has often been considered going against the national religion. El-Hor? s charter was circulated clandestinely, like many other political tracts at that time. The development of the activism characteristic of SOS Esclaves represents one of the most important transformations undergone by the Haratine movement. Keywords: activism; El-Hor? s charter; Haratine movement; human rights; Mauritania; slavery; SOS Esclaves
Probabilistic approaches for investigating species co-occurrence from presence-absence maps

Background In this research, we propose probabilistic approaches to identify pairwise patterns of species co-occurrence by using presence-absence maps only. In particular, the two-by-two contingency table constructed from a presence-absence map of two species would be sufficient to compute the test statistics and perform the statistical tests proposed in this article. Some previous studies have investigated species co-occurrence through incidence data of different survey sites. We focus on using presence-absence maps for a specific study plot instead. The proposed methods are assessed by a thorough simulation study. Methods A Chi-squared test is used to determine whether the distributions of two species are independent. If the null hypothesis of independence is rejected, the Chi-squared method can not distinguish positive or negative association between two species. We propose six different approaches based on either the binomial or Poisson distribution to obtain p-values for testing the positive (or negative) association between two species. When we test to investigate a positive (or negative) association, if the p-value is below the predetermined level of significance, then we have enough evidence to support that the two species are positively (or negatively) associated. Results A simulation study is conducted to demonstrate the type-I errors and the testing powers of our approaches. The probabilistic approach proposed by Veech (2013) is served as a benchmark for comparison. The results show that the type-I error of the Chi-squared test is close to the significance level when the presence rate is between 40% and 80%. For extremely low or high presence rate data, one of our approaches outperforms Veech (2013)’s in terms of the testing power and type-I error rate. The proposed methods are applied to a tree data of Barro Colorado Island in Panama and a tree data of Lansing Woods in USA. Both positive and negative associations are found among some species in these two real data.
Improving Worst-case TSN Communication Times of Large Sensor Data Samples by Exploiting Synchronization

Higher levels of automated driving also require a more sophisticated environmental perception. Therefore, an increasing number of sensors transmit their data samples as frame bursts to other applications for further processing. As a vehicle has to react to its environment in time, such data is subject to safety-critical latency constraints. To keep up with the resulting data rates, there is an ongoing transition to a Time-Sensitive Networking (TSN)-based communication backbone. However, the use of TSN-related industry standards does not match the automotive requirements of large timely sensor data transmission, nor it offers benefits on time-critical transmissions of single control data packets. By using the full data rate of prioritized IEEE 802.1Q Ethernet, giving time guarantees on large data samples is possible, but with strongly degraded results due to data collision. Resolving such collisions with time-aware shaping comes with significant overhead. Hence, rather than optimizing the parameters of the existing protocol, we propose a system design that synchronizes the transmission times of sensor data samples. This limits network protocol complexity and hardware requirements by avoiding tight time synchronization and time-aware shaping. We demonstrate that individual sensor data samples are transmitted without significant interference, exclusively at full Ethernet data rate. We provide a synchronous event model together with a straightforward response time analysis for synchronous multi-frame sample transmissions. The results show that worst-case latencies of such sample communication, in contrast to non-synchronized approaches, are close to their theoretical minimum as well as to simulative results while keeping the overall network utilization high.
Development of a 6 GHz RF-EMF Exposure System for Investigating Human Skin Temperature Responses: Characterization, Integration, and Pilot Testing

We developed a radiofrequency electromagnetic field (RF-EMF) exposure system to investigate human skin temperature responses to localized exposures. The system was designed to project a 6 GHz RF-EMF beam with enough energy to rapidly increase peak local skin temperature on the human forearm from a baseline of 30–32°C to $\sim $ 38°C within 6 min. First, the RF-EMF exposure conditions were characterized using computer simulations to confirm that the antenna produced the desired spot size (4 cm) and resultant temperature rise in the skin. ANSYS-HFSS and Sim4Life electromagnetic and thermal simulations were performed to fully characterize the relation between electromagnetic physics and the bioheat thermal conduction problem. Next, an open-ended waveguide antenna was integrated with other hardware peripherals to comprise the full RF-EMF exposure system. Finally, human pilot testing was conducted while participants were seated comfortably with the antenna 5 cm above the skin surface on the volar (i.e. palm side) forearm. Local skin temperatures were monitored continuously with a thermal camera, which automatically identified and continuously tracked the peak skin temperature under the projected beam. Both electromagnetic and thermal data plots are presented to illustrate the bioelectromagnetic response for the exposure system. Future experimental studies using this system will examine individual and environmental factors that may influence local human skin temperature responses to RF-EMF exposures on the forearm and other body regions.
Chapter 9 ZnO Thin Films: Fabrication Routes, and Applications

Thin films have become a hot topic in the field of nanotechnology. Due to their optical and electrical characteristics, thin-film semiconductor oxides are among the semiconductor oxides with the greatest range of applications. The most popular semiconductor component is zinc oxide (ZnO). ZnO, a wide bandgap semiconductor (Eg = 3.37 eV at room temperature), have been widely used in electronic, optoelectronic, and information technology device platforms. Nano-ZnO thin films have a wide range of applications due to their remarkable properties. There are several
Optimization of cultural and nutritional conditions for selection of the most promising microalgae intended for wastewater treatment and biodiesel production by direct transesterification method

Recently, algae have become the latest feasible source being targeted for biofuel production since they exhibit several attractive features. An investigation concerning the treatment of wastewater and the production of biodiesel by different cyanobacteria and micro-algae has been undertaken. Twelve soil and water samples were collected from different localities in Egypt. Eleven microalgae were isolated from collected soil and water samples and subjected to different purification methods. The isolated microalgae were used in the treatment of wastewater samples, and physical and chemical properties of wastewater samples were evaluated before and after treatment. The results evoked the superior activity of the isolated microalgal strains in the treatment of wastewater. Determination of lipid content of all isolated microalgae was carried out and showed 2.10 up to 5.13% of lipid. Factors affecting the lipid content productivities by selected promising microalgae were investigated viz. pH, incubation periods, and nitrogen sources. Three isolates were selected for cultivation on large scale, Oscillatoria chalybea (2) with dry weight 1028.4 mg and lipid yield 0.72%, O. chalybea (3) with dry weight 480.4 mg and lipid yield 0.9%, and O. chalybea (5) with dry weight 524.4 mg and lipid yield 1.01%. Extraction of oil from microbial biomass was done by Bligh and Dyer method. The lipid composition was determined as fatty acid methyl esters (FAMEs) through the direct transesterification method. The conversion of the extracted oil into biodiesel was analyzed by standard gas chromatographic technique.
Marginal regression of recurrent gap times based on semiparametric transformation cure model

Abstract Recurrent event data frequently arise in longitudinal studies. In this article, we consider a marginal semiparametric transformation cure model for gap times between recurrent events. We assume that each individual has the possibility of being cured after each event. We proposed generalized estimating equations for parameter estimation of the regression parameters in this model. The asymptotic properties of the proposed estimators are established under independent censoring. A simulation study is conducted to investigate finite sample properties of the proposed estimators. The proposed method is illustrated using an example of the tumor recurrent data for bladder cancer patients.