Modulation of starch digestibility using non-thermal processing techniques:A review

Obesity and type 2 diabetes are widespread throughout the world, especially in developed countries. Starch is an important part of human staple food, the modulating of starch digestibility is conducive to reducing postprandial blood glucose levels and alleviating the chronic disease caused by high caloric intake. The digestion properties of starch are correlated with its structural features, including crystallization, amylose/amylopectin ratio, non-starch components, etc. Among the modified methods applied to regulate starch digestibility, non-thermal processing techniques(NTPT) receive extensive attention due to the characteristics of safety, environmental friendliness and high efficiency. The influence and mechanism of NTPT on the digestion properties of starch are discussed in this review, including ultrasounds, high pressure, γ-irradiation, etc. NTPT induces the alternation of morphological and structural characteristics of native starch, changing their sensitivity to enzymes. The effects of NTPT on the digestibility of starch are highly related to the processing parameters and structure characteristics of native starch. The review shows that NTPT is an effective way to modulate the digestion properties of starch and prevent people from suffering from chronic diseases such as obesity and type 2 diabetes.

Constraints on Characteristics and Distribution of Gas Hydrate and Free Gas Using Broad-Band Processing of Three-Dimensional Seismic Data

Gas hydrate drilling expeditions in the Pearl River Mouth Basin,South China Sea,have identified concentrated gas hydrates with variable thickness.Moreover,free gas and the coexistence of gas hydrate and free gas have been confirmed by logging,coring,and production tests in the foraminifera-rich silty sediments with complex bottom-simulating reflectors(BSRs).The broad-band processing is conducted on conventional three-dimensional(3D)seismic data to improve the image and detection accuracy of gas hydratebearing layers and delineate the saturation and thickness of gas hydrate-and free gas-bearing sediments.Several geophysical attributes extracted along the base of the gas hydrate stability zone are used to demonstrate the variable distribution and the controlling factors for the differential enrichment of gas hydrate.The inverted gas hydrate saturation at the production zone is over 40% with a thickness of 90 m,showing the interbedded distribution with different boundaries between gas hydrate-and free gas-bearing layers.However,the gas hydrate saturation value at the adjacent canyon is 70%,with 30-m-thick patches and linear features.The lithological and fault controls on gas hydrate and free gas distributions are demonstrated by tracing each gas hydrate-bearing layer.Moreover,the BSR depths based on broad-band reprocessed 3D seismic data not only exhibit variations due to small-scale topographic changes caused by seafloor sedimentation and erosion but also show the upward shift of BSR and the blocky distribution of the coexistence of gas hydrate and free gas in the Pearl River Mouth Basin.

Investigation on taste characteristics and sensory perception of soft-boiled chicken during oral processing based on electronic tongue and electronic nose

The sensory perception of food is a dynamic process,which is closely related to the release of flavor substances during oral processing.It’s not only affected by the food material,but also subjected to the individual oral environment.To explore the oral processing characteristics of soft-boiled chicken,the sensory properties,texture,particle size,viscosity,characteristic values of electronic nose and tongue of different chicken samples were investigated.The correlation analysis showed that the physical characteristics especially the cohesiveness,springiness,resilience of the sample determined oral processing behavior.The addition of chicken skin played a role in lubrication during oral processing.The particle size of the bolus was heightened at the early stage,and the fluidity was enhanced in the end,which reduced the chewing time to the swallowing point and raised the aromatic compounds signal of electronic nose.But the effect of chicken skin on chicken thigh with relatively high fat content,was opposite in electronic nose,which had a certain masking effect on the perception of umami and sweet taste.In conclusion,fat played a critical role in chicken oral processing and chicken thigh had obvious advantages in comprehensive evaluation of soft-boiled chicken,which was more popular among people.

The State-of-the-Art Review on Applications of Intrusive Sensing,Image Processing Techniques,and Machine Learning Methods in Pavement Monitoring and Analysis

In modern transportation,pavement is one of the most important civil infrastructures for the movement of vehicles and pedestrians.Pavement service quality and service life are of great importance for civil engineers as they directly affect the regular service for the users.Therefore,monitoring the health status of pavement before irreversible damage occurs is essential for timely maintenance,which in turn ensures public transportation safety.Many pavement damages can be detected and analyzed by monitoring the structure dynamic responses and evaluating road surface conditions.Advanced technologies can be employed for the collection and analysis of such data,including various intrusive sensing techniques,image processing techniques,and machine learning methods.This review summarizes the state-ofthe-art of these three technologies in pavement engineering in recent years and suggests possible developments for future pavement monitoring and analysis based on these approaches.

Effects of friction stir processing and nano-hydroxyapatite on the microstructure,hardness,degradation rate and in-vitro bioactivity of WE43 alloy for biomedical applications

Nowadays,magnesium alloys are emerging in biomedical implants for their similar properties to natural bones.However,the rapid degradation of magnesium alloys in biological media hinders successful implantation.Refinement of microstructure,as well as reinforcement particles can significantly improve the degradation rate.In this work,multi-pass friction stir processing(FSP)was proposed to synthesize WE43/nano-hydroxyapatite(n HA)surface composite,the microstructure,reinforced particle distribution,micro-hardness,corrosion behavior and in-vitro bioactivity were studied.The subsequent FSP passes of WE43 alloy and WE43/n HA composite refined the grain size which was reduced by 94.29%and 95.92%(2.63 and 1.88μm,respectively)compared to base metal after three passes.This resulted in increasing the microhardness by 120%(90.86 HV0.1)and 135%(105.59 HV0.1)for the WE43 and WE43-n HA,respectively.It is found that increasing FSP passes improved the uniform distribution of n HA particles within the composite matrix which led to improved corrosion resistance and less degradation rate.The corrosion rate of the FSPed WE43/n HA composite after three passes was reduced by 38.2%(4.13 mm/year)and the degradation rate was reduced by 69.7%(2.87 mm/y).This is attributed to secondary phase(Mg24Y5and Mg41Nd5)particle fragmentation and redistribution,as well as a homogeneous distribution of n HA.Additionally,the growing Ca-P and Mg(OH)2layer formed on the surface represented a protective layer that reduced the degradation rate.The wettability test revealed a relatively hydrophilic surface with water contact angle of 49.1±2.2°compared to 71.2±2.1°for base metal.Also,biomineralization test showed that apatite layer grew after immersion 7d in simulated body fluid with atomic ratio of Ca/P 1.60 approaching the stoichiometric ratio(1.67)indicating superior bioactivity of FSPed WE43/n HA composite after three passes.These results raise that the grain refinement by FSP and introduction of n HA particles significantly improved the degradation rate and in-vitro bioactivity of WE43 alloy for biomedical applications.

A new insight into LPSO phase transformation and mechanical properties uniformity of large-scale Mg-Gd-Y-Zn-Zr alloy prepared by multi-pass friction stir processing

A large-scale fine-grained Mg-Gd-Y-Zn-Zr alloy plate with high strength and ductility was successfully prepared by multi-pass friction stir processing(MFSP)technology in this work.The structure of grains and long period stacking ordered(LPSO)phase were characterized,and the mechanical properties uniformity was investigated.Moreover,a quantitative relationship between the microstructure and tensile yield strength was established.The results showed that the grains in the processed zone(PZ)and interfacial zone(IZ)were refined from 50μm to 3μm and 4μm,respectively,and numerous original LPSO phases were broken.In IZ,some block-shaped 18R LPSO phases were transformed into needle-like 14H LPSO phases due to stacking faults and the short-range diffusion of solute atoms.The severe shear deformation in the form of kinetic energy caused profuse stacking fault to be generated and move rapidly,greatly increasing the transformation rate of LPSO phase.After MFSP,the ultimate tensile strength,yield strength and elongation to failure of the large-scale plate were 367 MPa,305 MPa and 18.0% respectively.Grain refinement and LPSO phase strengthening were the major strengthening mechanisms for the MFSP sample.In particularly,the strength of IZ was comparable to that of PZ because the strength contribution of the 14H LPSO phase offsets the lack of grain refinement strengthening in IZ.This result opposes the widely accepted notion that IZ is a weak region in MFSP-prepared large-scale fine-grained plate.

Machine Learning-based Identification of Contaminated Images in Light Curve Data Preprocessing

Attitude is one of the crucial parameters for space objects and plays a vital role in collision prediction and debris removal.Analyzing light curves to determine attitude is the most commonly used method.In photometric observations,outliers may exist in the obtained light curves due to various reasons.Therefore,preprocessing is required to remove these outliers to obtain high quality light curves.Through statistical analysis,the reasons leading to outliers can be categorized into two main types:first,the brightness of the object significantly increases due to the passage of a star nearby,referred to as“stellar contamination,”and second,the brightness markedly decreases due to cloudy cover,referred to as“cloudy contamination.”The traditional approach of manually inspecting images for contamination is time-consuming and labor-intensive.However,we propose the utilization of machine learning methods as a substitute.Convolutional Neural Networks and SVMs are employed to identify cases of stellar contamination and cloudy contamination,achieving F1 scores of 1.00 and 0.98 on a test set,respectively.We also explore other machine learning methods such as ResNet-18 and Light Gradient Boosting Machine,then conduct comparative analyses of the results.

A Systematic Review of Computer Vision Techniques for Quality Control in End-of-Line Visual Inspection of Antenna Parts

The rapid evolution of wireless communication technologies has underscored the critical role of antennas in ensuring seamless connectivity.Antenna defects,ranging from manufacturing imperfections to environmental wear,pose significant challenges to the reliability and performance of communication systems.This review paper navigates the landscape of antenna defect detection,emphasizing the need for a nuanced understanding of various defect types and the associated challenges in visual detection.This review paper serves as a valuable resource for researchers,engineers,and practitioners engaged in the design and maintenance of communication systems.The insights presented here pave the way for enhanced reliability in antenna systems through targeted defect detection measures.In this study,a comprehensive literature analysis on computer vision algorithms that are employed in end-of-line visual inspection of antenna parts is presented.The PRISMA principles will be followed throughout the review,and its goals are to provide a summary of recent research,identify relevant computer vision techniques,and evaluate how effective these techniques are in discovering defects during inspections.It contains articles from scholarly journals as well as papers presented at conferences up until June 2023.This research utilized search phrases that were relevant,and papers were chosen based on whether or not they met certain inclusion and exclusion criteria.In this study,several different computer vision approaches,such as feature extraction and defect classification,are broken down and analyzed.Additionally,their applicability and performance are discussed.The review highlights the significance of utilizing a wide variety of datasets and measurement criteria.The findings of this study add to the existing body of knowledge and point researchers in the direction of promising new areas of investigation,such as real-time inspection systems and multispectral imaging.This review,on its whole,offers a complete study of computer vision approaches for quality control in antenna parts.It does so by providing helpful insights and drawing attention to areas that require additional exploration.

Optimized protocol of multiple post-processing techniques improves diagnostic accuracy of multidetector computed tomography in assessment of small bowel obstruction compared with conventional axial and coronal reformations

BACKGROUND Axial and coronal reformations have been a widely used image post-processing protocol for the ordinary multidetector computed tomography(MDCT)examination of patients with small bowel obstruction(SBO) or other abdominal diseases. The diagnostic accuracy of MDCT for assessing SBO is expected to be further improved through the use of multiple post-processing techniques.AIM To systemically evaluate the diagnostic accuracy and efficiency of an optimized protocol using multiple post-processing techniques for MDCT assessment of SBO and secondary bowel ischemia.METHODS This retrospective cross-sectional study included 106 patients with clinically suspected SBO. Two readers applied three protocols to image post-processing and interpretation of patients' MDCT volume data. We compared the three protocols based on time spent, number of images, diagnostic self-confidence,agreement, detection rate, and accuracy of detection of SBO and secondary bowel ischemia.RESULTS Protocol 2 resulted in more time spent and number of images than protocols 1 and 3(P < 0.01), but the results of the two readers using the same protocol were not different(P > 0.05). Using protocol 3, both readers added multiple postprocessing techniques at frequencies of 29.2% and 34.9%, respectively, for obstruction cause, and 32.1% and 30.2%, respectively, for secondary bowel ischemia. Protocols 2 and 3 had higher total detection rates of obstruction cause and secondary bowel ischemia than protocol 1(P < 0.01), but no difference was detected between protocols 2 and 3(P > 0.05). The accuracy, sensitivity,specificity, positive predictive value and negative predictive value of protocols 2 and 3 were superior to those of protocol 1 for evaluating obstruction cause and secondary bowel ischemia.CONCLUSION Our optimized protocol of multiple post-processing techniques can both guarantee efficiency and improve diagnostic accuracy of MDCT for assessing SBO and secondary bowel ischemia.

Mechanical Properties,Purifying Techniques and Processing Methods of Metal Yttrium

The mechanical properties of metal yttrium such as strength, plasticity, hardness and elasticity were introduced . The purifying techniques of yttrium were discussed in detail. The processing methods for metal yttrium including extruding, forging, rolling, wiredrawing and welding were also introduced. Finally, the potential use of yttrium and its alloys were prospected.

The Application of Analytical Techniques to Alpha-Synuclein in Parkinson’s Disease

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by motor symptoms such as tremors, rigidity, and bradykinesia, as well as non-motor symptoms including cognitive impairment and mood disorders. A hallmark of PD is the accumulation of alpha-synuclein, a presynaptic neuronal protein that aggregates to form Lewy bodies, leading to neuronal dysfunction and cell death. The study of alpha-synuclein and its pathological forms is crucial for understanding the etiology of PD and developing effective diagnostic and therapeutic strategies. Analytical techniques play a pivotal role in elucidating the structure, function, and aggregation mechanisms of alpha-synuclein. Biochemical methods such as Western blotting and enzyme-linked immunosorbent assay (ELISA) are employed to detect and quantify alpha-synuclein in biological samples, offering insights into its expression levels and post-translational modifications. Imaging techniques like immunohistochemistry and positron emission tomography (PET) allow for the visualization of alpha-synuclein aggregates in tissue samples and in vivo, respectively, facilitating the study of its spatial distribution and progression in PD Spectroscopic methods, including nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry, provide detailed structural information on alpha-synuclein and its isoforms, aiding in the identification of conformational changes associated with aggregation. Emerging techniques such as cryo-electron microscopy (Cryo-EM) and single-molecule fluorescence enable high-resolution structural analysis and real-time monitoring of alpha-synuclein aggregation dynamics, respectively. The application of these analytical techniques has significantly advanced our understanding of the pathophysiological role of alpha-synuclein in PD. They have contributed to the identification of potential biomarkers for early diagnosis and the evaluation of therapeutic interventions targeting alpha-synuclein aggregation. Despite technical limitations and challenges in clinical translation, ongoing advancements in analytical methodologies hold promise for improving the diagnosis, monitoring, and treatment of Parkinson’s disease through a deeper understanding of alpha-synuclein pathology.

THE CALCULATION OF THE DENSITY FIELD FROM AXISYMMETRIC SCHLIEREN INTERFEROGRAMS BY THE IMAGE PROCESSING TECHNIQUES

The schlieren interferograms used to be analyzed in a qualitative way. In this paper, by means of the powerful computational ability and the large memory of computer; the image processing method is investigated for the digitalization of an axisymmetric schlieren interferogram and the determination of the density field. This method includes the 2-D low-pass filtering, the thinning of interferometric fringes, the extraction of physical information and the numerical integration of the density field. The image processing results show that the accuracy of the quantitative analysis of the schlieren interferogram can be improved and a lot of time can be saved in dealing with optical experimental results. Therefore, the algorithm used here is useful and efficient.

Review on the effect of different processing techniques on the microstructure and mechanical behaviour of AZ31 Magnesium alloy

Magnesium(Mg)alloys despite being the ideal candidate for structural applications,owing to their high specific strength and low density,are not widely used due to lack of active slip systems at room temperature in their hexagonal close-packed crystal structure,eliciting poor ductility and formability.Amongst the various series of Mg alloys,the AZ and ZK series alloys have been standouts,as they inherit better room temperature strength and flow characteristics through their solute elements.Grain refinement,as well as eliminating casting defects through metal processing techniques are vital for the commercial viability of these alloys since they play a key role in controlling the mechanical behaviour.As such,this review highlights the effect of different Bulk-deformation and Severe Plastic Deformation techniques on the crystal orientation and the corresponding mechanical behaviours of the AZ31 alloy.However,every process parameter surrounding these techniques must be well thought of,as they require specially designed tools.With the advent of finite element analysis,these processes could be computationally realized for different parameters and optimized in an economically viable manner.Hence,this article also covers the developments made in finite element methods towards these techniques.

Review of artificial intelligence applications in astronomical data processing

Artificial Intelligence(AI)is an interdisciplinary research field with widespread applications.It aims at developing theoretical,methodological,technological,and applied systems that simulate,enhance,and assist human intelligence.Recently,notable accomplishments of artificial intelligence technology have been achieved in astronomical data processing,establishing this technology as central to numerous astronomical research areas such as radio astronomy,stellar and galactic(Milky Way)studies,exoplanets surveys,cosmology,and solar physics.This article systematically reviews representative applications of artificial intelligence technology to astronomical data processing,with comprehensive description of specific cases:pulsar candidate identification,fast radio burst detection,gravitational wave detection,spectral classification,and radio frequency interference mitigation.Furthermore,it discusses possible future applications to provide perspectives for astronomical research in the artificial intelligence era.

Development and Validation of Integrated Nutrient Management Practices of Industrial Processing Varieties: Asterix and Courage in Bangladesh

An experiment was meticulously conducted at the research field of Bangabandhu Sheikh Mujibur Rahman Agricultural University (BSMRAU), Gazipur, Bangladesh, during the 2011-2012 potato growing season to develop integrated crop management practices for the potato seed production of industrial processing varieties Asterix and Courage. Significantly, higher growth and yield parameters were found in the BADC-recommended practice. Later, another experiment was conducted to validate the BADC practice during the 2013-2014 potato growing season in two locations in Bangladesh. Results showed that the production of tuber per hill, tuber weight per hill as well as gross tuber yield per plot, higher proportion of storable seed tubers, and more quality seed potatoes (A-grade and B-grade) seed tubers were found significantly higher in the “BADC developed practice” compared to other treatments. Viral diseases (PLRV and PVY) prevalence was lower in “BADC developed practice”. Moreover, “BADC developed practice” contributed more economic yield by minimizing input cost compared to “Munshiganj advanced farmers’ practice”. Therefore, the “BADC developed practice” was found “superior” regarding yield, quality, and profitability in seed potato production of industrial varieties—Asterix and Courage in Bangladesh.

Pretreatment and analysis techniques development of TKIs in biological samples for pharmacokinetic studies and therapeutic drug monitoring

Tyrosine kinase inhibitors(TKIs)have emerged as the first-line small molecule drugs in many cancer therapies,exerting their effects by impeding aberrant cell growth and proliferation through the modulation of tyrosine kinase-mediated signaling pathways.However,there exists a substantial inter-individual variability in the concentrations of certain TKIs and their metabolites,which may render patients with compromised immune function susceptible to diverse infections despite receiving theoretically efficacious anticancer treatments,alongside other potential side effects or adverse reactions.Therefore,an urgent need exists for an up-to-date review concerning the biological matrices relevant to bioanalysis and the sampling methods,clinical pharmacokinetics,and therapeutic drug monitoring of different TKIs.This paper provides a comprehensive overview of the advancements in pretreatment methods,such as protein precipitation(PPT),liquid-liquid extraction(LLE),solid-phase extraction(SPE),micro-SPE(μ-SPE),magnetic SPE(MSPE),and vortex-assisted dispersive SPE(VA-DSPE)achieved since 2017.It also highlights the latest analysis techniques such as newly developed high performance liquid chromatography(HPLC)and high-resolution mass spectrometry(HRMS)methods,capillary electrophoresis(CE),gas chromatography(GC),supercritical fluid chromatography(SFC)procedures,surface plasmon resonance(SPR)assays as well as novel nanoprobes-based biosensing techniques.In addition,a comparison is made between the advantages and disadvantages of different approaches while presenting critical challenges and prospects in pharmacokinetic studies and therapeutic drug monitoring.

Isothermal hydrogen absorption process of Pd-capped Mg films traced by ion beam techniques and optical methods

Pd-capped nanocrystalline Mg films were prepared by electron beam evaporation and hydrogenated under isothermal conditions to inves-tigate the hydrogen absorption process via ion beam techniques and in situ optical methods.Films were characterized by different techniques such as X-ray diffraction(XRD)and scanning electron microscopy(SEM).Rutherford backscattering spectrometry(RBS)and elastic recoil detection analysis(ERDA)provided a detailed compositional depth profile of the films during hydrogenation.Gas-solid reaction kinetics theory applied to ERDA data revealed a H absorption mechanism controlled by H diffusion.This rate-limiting step was also confirmed by XRD measurements.The diffusion coefficient(D)was also determined via RBS and ERDA,with a value of(1.1±0.1)·10^(−13)cm^(2)/s at 140℃.Results confirm the validity of IBA to monitor the hydrogenation process and to extract the control mechanism of the process.The H kinetic information given by optical methods is strongly influenced by the optical absorption of the magnesium layer,revealing that thinner films are needed to extract further and reliable information from that technique.

Software Defect Prediction Using Hybrid Machine Learning Techniques: A Comparative Study

When a customer uses the software, then it is possible to occur defects that can be removed in the updated versions of the software. Hence, in the present work, a robust examination of cross-project software defect prediction is elaborated through an innovative hybrid machine learning framework. The proposed technique combines an advanced deep neural network architecture with ensemble models such as Support Vector Machine (SVM), Random Forest (RF), and XGBoost. The study evaluates the performance by considering multiple software projects like CM1, JM1, KC1, and PC1 using datasets from the PROMISE Software Engineering Repository. The three hybrid models that are compared are Hybrid Model-1 (SVM, RandomForest, XGBoost, Neural Network), Hybrid Model-2 (GradientBoosting, DecisionTree, LogisticRegression, Neural Network), and Hybrid Model-3 (KNeighbors, GaussianNB, Support Vector Classification (SVC), Neural Network), and the Hybrid Model 3 surpasses the others in terms of recall, F1-score, accuracy, ROC AUC, and precision. The presented work offers valuable insights into the effectiveness of hybrid techniques for cross-project defect prediction, providing a comparative perspective on early defect identification and mitigation strategies. .

Advances in the application of auxiliary imaging techniques in parathyroid diseases

Hypoparathyroidism is one of the main complications after total thyroidectomy,severely affecting patients’quality of life.How to effectively protect parathyroid function after surgery and reduce the incidence of hypoparathyroidism has always been a key research area in thyroid surgery.Therefore,precise localization of parathyroid glands during surgery,effective imaging,and accurate surgical resection have become hot topics of concern for thyroid surgeons.In response to this clinical phenomenon,this study compared several different imaging methods for parathyroid surgery,including nanocarbon,indocyanine green,near-infrared imaging techniques,and technetium-99m methoxyisobutylisonitrile combined with gamma probe imaging technology.The advantages and disadvantages of each method were analyzed,providing scientific recommendations for future parathyroid imaging.In recent years,some related basic and clinical research has also been conducted in thyroid surgery.This article reviewed relevant literature and provided an overview of the practical application progress of various imaging techniques in parathyroid surgery.

High Accuracy Time of Flight Measurement Using Digital Signal Processing Techniques for Subsea Applications

The techniques widely used in ultrasonic measurements are based on the determination of the time of flight (T.o.F). A short train of waves is transmitted and same transducer is used for reception of the reflected signal for the pulse-echo measurement applications. The amplitude of the received waveform is an envelope which starts from zero reaches to a peak and then dies out. The echoes are mostly detected by simple threshold crossing technique, which is also cause of error. In this paper digital signal processing is used to calculate the time delay in reception i.e. T.o.F, for which a maximum similarity between the reference and the delayed echo signals is obtained. To observe the effect of phase uncertainties and frequency shifts (Doppler), this processing is carried out, both directly on the actual wave shape and after extracting the envelopes of the reference and delayed echo signals. Several digital signal processing algorithms are considered and the effects of different factors such as sampling rate, resolution of digitization and S/N ratio are analyzed. Result show accuracy, computing time and cost for different techniques.