Real Samples Research Articles

Novel optical optode for selective detection and removal of ultra-trace level of mercury ions in different environmental real samples

Owing to the high cost and unavailability of different analytical techniques, there is an urgent need to develop new techniques not only for detecting but also removing mercury ions in real samples. Thus, an optical chemical sensor based on the anchoring of phenanthraquinone monophenylthiosemicarbazone in a plasticized cellulose triacetate membrane was fabricated and applied to the recognition and removal of mercury ions from aqueous solutions. The synthesized optode was characterized by FT-IR, SEM, AFM, and thermal analysis. Several parameters, including the pH, temperature, contact time, washing solvent, and washing time, were optimized. Under optimal conditions, a promising optode film platform was utilized for sensing mercury ions, and the concentrations were calculated based on colorimetric analysis (Histogram, RGB) of digital images, visualization, and spectrophotometry. Also, an optical optode was used for complete adsorption of mercury ions from aqueous solutions. In addition, the regeneration of the synthesized optode was evaluated using 0.1 mol L− 1 nitric acid, which effectively removed all adsorbed mercury ions. The obtained data indicated good linearity in the sensing and adsorption of Hg2+ over a concentration range of 0.005–5000 µgL− 1 with a low limit of detection (LOD = 0.066 µgL− 1) and limit of quantification (LOQ, 0.22 µgL− 1). Furthermore, it showed good distinctions in the presence of coexisting ions, high stability (five months), good applicability, and reproducibility (RSD = 1.31%), making it a promising sensor for Hg2+ detection. On the other hand, the kinetic studies revealed that the pseudo-second-order was the best model for describing the adsorption behavior of mercury ions on the optode surface. Also, the thermodynamic parameters indicate spontaneous (ΔG0 < 0) and endothermic (ΔH0 < 0) reactions. Also, the maximum adsorption capacity was found to be 73.2 mg g− 1. Thus, the optodes were successfully applied for the detection and/or removal of Hg2+ in different real samples, including cucumber, fish, soil, and water samples, with excellent recoveries of 98.1–99.5%.

A New Modified Carbon Paste Electrode for Selective Determination of Chromium(III) in Pharmaceutical Drugs and Food Samples

Background and Objective: This study presents a novel potentiometric method for the precise, accurate, selective, and rapid determination of Cr(III) ion concentration in different samples. Methods: A new ionophore, namely macrocyclic tetramide ionophore (MCTA), was synthesized through an inexpensive and straightforward approach, yielding a high-quality product. The (MCTA) ionophore was utilized as the active center in the preparation of modified carbon paste electrodes (MCPEs) to quantify the Cr(III) ion. The paste was made by adding graphite, MCTA, and plasticizer and mixing them in varying weight percent ratios. Results: The proposed electrodes, I and II, exhibited a trivalent Nernstian response of 20.029 ±0.57 and 20.3±0.56 mV decade-1 , respectively, with linearity of 1.0x10-7 – 1.0x10-2 and 1.0x10-5 – 1.0x10- 2 mol L-1 . Electrodes I and II were examined for their pH, response time, and thermal stability. In comparison to other mono-, bi-, and trivalent cations, starch, and sugars, the electrodes demonstrated a high degree of selectivity for Cr(III). The modified electrodes were used to determine the concentration of Cr(III) in various real samples, including drug tablets, juice extractions, and tap water, with acceptable recovery values. Conclusion: The results were compared with those obtained using the previously reported method, with no significant difference observed between them, as indicated by the F and t-test values. The data showed good accuracy and precision, as well as a high percentage of recovery. The adsorption capacity of the MCTA ionophore towards Cr(III) ions was also examined.

Comprehensive review of sample preparation strategies for phthalate ester analysis in various real samples

Comprehensive review of sample preparation strategies for phthalate ester analysis in various real samples

A novel dual-function fluorescence sensor Eu/CDs@MOF-808 for the sensitive detection of adenosine triphosphate and uric acid

Designing and developing a reliable method for the detection of potential biomarker molecules are crucial for the early prevention and diagnosis of diseases. In this study, we present a novel functionalized metal–organic framework material (MOF-808) that is developed to construct ratiometric fluorescence sensing platforms (Eu/CDs@MOF-808) for the detection of adenosine triphosphate (ATP) and uric acid (UA). The fluorescent probe Eu/CDs@MOF-808 prepared through the in-situ encapsulation of fluorescent carbon dots (CDs) within the structure of MOF-808 exhibits excellent optical properties. Additionally, rare earth ions (Eu3+) are incorporated into the CDs@MOF-808 using a post-synthetic modification strategy. The presence of ATP significantly enhances the characteristic peak of carbon dots (CDs) at 440 nm, while the peak of Eu3+ at 614 nm remains relatively unchanged. Furthermore, the concentration of ATP exhibits a strong linear relationship with the ratiometric fluorescence intensity (F440/F614) in the concentration range of 0.5–450 μM, with a detection limit of 0.22 μM. Notably, the addition of uric acid (UA) to this fluorescence sensing platform leads to a marked reduction in the characteristic peak intensity of Eu3+, which results in a satisfactory linear relationship between the ratiometric fluorescence intensity and UA concentration in the concentration ranges of 0.04–300 μM and 300–650 μM, with a detection limit of 0.04 μM. Additionally, the fluorescent sensor has been successfully applied for the detection of ATP and UA in real serum and urine samples.

Removal of phosphate from wastewater using zirconium/iron embedded chitosan/alginate hydrogel beads: An experimental and computational perspective

Adsorptive removal of phosphate plays a crucial role in mitigating eutrophication. Herein, the Zr/Fe embedded chitosan/alginate hydrogel bead (Zr/Fe/CS/Alg) is reported as an effective phosphate adsorbent. This polymer nanocomposite is synthesized by the in-situ reduction of the metals on the polymer matrix. The synthesized adsorbent was characterized by the FTIR, SEM-EDX, TGA, BET, and XPS. The adsorbent showed a maximum phosphate adsorption capacity of 221.72 mg/g at pH 3. The experimental data fit well with the Freundlich isotherm and pseudo-second-order kinetics model, indicating a heterogeneous multilayer surface formation and a chemisorption-dominated adsorption process. Density Functional Theory (DFT) and Monte Carlo (MC) calculations revealed high negative adsorption energy due to the chemisorption of phosphate on the adsorbent. Hence, the major interactions such as electrostatic attraction, hydrogen bonding, and inner-sphere complexation of phosphate adsorption and Zr/Fe/CS/Alg hydrogel beads were investigated from the experimental and computational analysis. The negative values of thermodynamic parameters indicated a spontaneous, exothermic, and less random adsorption process. The synthesized adsorbent exhibited excellent selectivity toward phosphate and maintained 73 % efficiency after six adsorption/desorption cycles. The Zr/Fe/CS/Alg hydrogel beads reduced the phosphate concentration in real wastewater samples from 19.02 mg/L to 0.985 mg/L, suggesting that these nanocomposite hydrogel beads could be a promising adsorbent for real-world applications.

A PET based colorimetric/fluorescent dual-signal probe for selective detection of hypochlorite in real water samples

A PET based colorimetric/fluorescent dual-signal probe for selective detection of hypochlorite in real water samples

Electrochemical activation of periodate with graphite electrodes for degradation of high concentrations of thiocyanogen (SCN−) in mineral processing tail liquid

Cyanide has been widely used in gold extraction due to its cost-effectiveness, high selectivity and recovery. Regrettably, its wide application also leads to the presence of a large amount of thiocyanogen (SCN−) in the tail liquid of mineral processing plants, which affects the quality of the effluent water, and thus poses a threat to the ecological environment and human health. This paper investigates the degradation of high concentration of SCN− in water using electrochemical oxidation/periodate (E-GP/PI) system. A degradation rate of 90.25 % of SCN− was achieved by optimising various operating parameters. The effects of organic matter and typical heavy metal ion concentrations on the degradation of SCN− were investigated, and it was found that Cu2+ was able to promote the degradation of SCN− through the formation of stable complexes with SCN−, which enhanced the degradation rate to 96.48 %. However, the presence of Octadecyltrimethylammonium bromide (OTAB) and butylxanthin hindered the degradation process, where 500 mg/L of OTAB reduced the degradation rate of SCN− to 80.88 %, while 100 mg/L of butylxanthin reduced the degradation rate to 78.66 %. On this basis, experiments were carried out using real wastewater samples and SCN− degradation efficiencies of about 90 % were obtained. Afterwards, through electron paramagnetic resonance analysis, free radical burst, ion chromatograph and other research techniques, IO3 and O2– were obtained as the main drivers of SCN− degradation and SCN− degradation pathways were elucidated. Finally, the E-GP/PI system was shown to be effective in reducing the ecotoxicity of SCN− by increasing the 24-h LC50 from 12.5 % to 48.5 % in a toxicity test with daphnia. This study provides a new idea for the green and efficient treatment of SCN− rich beneficiation tail liquid.

ONLINE RESTRICTED ACCESS MOLECULARLY IMPRINTED SOLID PHASE EXTRACTION COUPLED WITH ELECTROSPRAY IONIZATION-TANDEM MASS SPECTROMETRY FOR DETERMINATION OF MEBENDAZOLE AND ALBENDAZOLE IN MILK SAMPLES

Multifunctional materials, such as restricted access molecularly imprinted polymers covered with bovine serum albumin (RAMIP-BSA), are effective alternatives for sample preparation techniques. This material selectively adsorbs analytes while excluding macromolecules, enhancing the analysis's efficiency. Among analytical techniques, ESI-MS/MS (Electrospray Ionization-Tandem Mass Spectrometry) has successfully identified and quantified various molecules, including trace-level drugs. Therefore, we proposed, for the first time, an integrated online extraction/analysis system that combines the benefits of RAMIP-BSA and ESI-MS/MS for analyzing mebendazole (MBZ) and albendazole (ABZ) in milk samples without the need for chromatographic separation. Initially, a RAMIP selective for MBZ was synthesized using the bulk method with methacrylic acid and glycidyl methacrylate. Then, the polymer was covered with bovine serum albumin. Subsequently, this adsorbent was packed in a small column and coupled with an ESI-MS/MS instrument in an online configuration. Milli-Q water was used as the loading and reconditioning mobile phases, and a solution of formic acid in methanol (1:100 v/v) was employed as the elution phase. The system enabled simultaneous extraction and determination of MBZ and ABZ in milk samples. The method exhibited linearity between 15.0 and 125.0 μg L-1 for MBZ and 10.0 and 125.0 μg L-1 for ABZ (with a correlation coefficient exceeding 0.99). The limits of quantification were 15.0 and 10.0 μg L-1 for MBZ and ABZ, respectively. Good precision and accuracy were achieved. The developed method was used to analyze MBZ and ABZ in real milk samples and proved to be a viable alternative to conventional sample preparation and chromatographic techniques.

Ultralow magnetic susceptibility in pure and Fe(Bi)-doped Au-Pt alloys improved by structural strain regulation

Designing and manufacturing multi-component alloy samples with ultralow magnetic susceptibilityχ(<10-6cm3mol-1) is crucial for producing high-quality test masses to successfully detect gravitational wave in the LISA and TianQin projects. Previous research has idenfified AuPt alloys as a potential candidate for test masses, capable of achieving ultralow magnetic susceptibility that meets the requirements from both theoretical and experimental perspectives. In this study, we discover that the structural strain regulation (i.e. tensile and stress) can effectively optimize and further reduce the ultralow magnetic susceptibility of AuPt allpys, while fully understanding their underlying physical mechanisms. More importantly, even when doped with trace elements such as Fe or Bi impurity, strain regulation can still effectively reduce the magnetic susceptibility of the doped AuPt alloy to the desired range. Our theoretical calculations also reveal that, when the strain ratioηis controlled within in a relatively small range (<2.0%), the regulaton effect on the ultralow magnetic susceptibilities of pure or doped-AuPt alloys remains significant. This property is beneficial for achieving ultralow or even near-zero magnetic susceptibility in real AuPt alloy samples.

Adversarial attacks in signature verification: a deep learning approach

Handwritten signature recognition in forensic science is crucial for identity and document authentication. While serving as a legal representation of a person’s agreement or consent to the contents of a document, handwritten signatures de termine the authenticity of a document, identify forgeries, pinpoint the suspects and support other pieces of evidence like ink or document analysis. This work focuses on developing and evaluating a handwritten signature verification sys tem using a convolutional neural network (CNN) and emphasising the model’s efficacy using hand-crafted adversarial attacks. Initially, handwritten signatures have been collected from sixteen volunteers, each contributing ten samples, fol lowed by image normalization and augmentation to boost synthetic data samples and overcome the data scarcity. The proposed model achieved a testing accu racy of 91.35% using an 80:20 train-test split. Additionally, using the five-fold cross-validation, the model achieved a robust validation accuracy of nearly 98%. Finally, the introduction of manually constructed adversarial assaults on the sig nature images undermines the model’s accuracy, bringing the accuracy down to nearly 80%. This highlights the need to consider adversarial resilience while designing deep learning models for classification tasks. Exposing the model to real look-alike fake samples is critical while testing its robustness and refining the model using trial and error methods.

Novel 3D plate-like g-C3N4/BiOCl heterojunction as a highly efficient photocatalyst for the degradation of carbofuran in wastewater under visible light irradiation

The g-C3N4/BiOCl (gCN-BCl) heterojunction photocatalyst was synthesized using a low-temperature precipitation method for effective photocatalytic degradation of carbofuran (CBF). All gCN-BCl composites demonstrate greater efficacy in removing CBF compared to its individual constituents. The synergistic effect of incorporating the 0D structured BiOCl onto the 2D structured g-C3N4 was comprehensively examined using various microscopic, X-ray, and spectroscopic analytical techniques. Additionally, optical and photoelectrochemical analyses were conducted. The findings validated that the interaction between the two semiconductors at the heterointerfaces enhanced remarkable physical and structural stability, promoted high charge separation and transfer properties, and improved photocatalytic degradation. Under optimal conditions, 5-gCN-BCl (0.25 g/L) achieved a CBF (5 mg/L) removal efficiency of 95.7 % under visible light irradiation of 120 min, achieving 3.1- and 5.9-times higher degradation rate than the pure BiOCl and g-C3N4, respectively. The radical trapping experiments indicated that the h+ and •O2− were the primary reactive species involved in the CBF degradation. Furthermore, the potential toxicity of CBF and its intermediates was assessed, revealing that the photocatalytic degradation process significantly lowered the ecotoxicity of pesticide wastewater. The potency of 5-gCN-BCl was also evaluated in tap water and real wastewater samples, with CBF degradation efficiencies of 85.8 %, 47.6 %, and 38.7 % in tap water, municipal, and pesticide industry wastewater, respectively. Additionally, artificial neural network (ANN) modeling was employed to predict and optimize the photocatalytic degradation process, providing further insights into the system’s performance. The outcomes of this work offer valuable insights into the development of heterojunction photocatalysts with superior stability and efficacy for eliminating pesticides from water bodies.

Multi-core–shell nanoboxes comprising polydopamine-derived C coated NiCo@C and FeCo@C nanohybrid for enhanced electrochemical quantification of nitrofurantoin

The development of a high-performance electrochemical sensing platform for monitoring nitrofurantoin (NFT) levels in various real samples plays an important role in the research community worldwide. To accomplish this objective, the crucial challenge is to construct sensing interfaces with outstanding electrocatalytic capabilities. In the present work, a highly efficient metal@carbon electrocatalyst with porous and multi-core–shell nanobox structure comprising polydopamine (PDA)-derived C coated NiCo@C and FeCo@C nanohybrid (named as NiCo@C/FeCo@C@C) was fabricated by simply pyrolyzing NiCo@FeCo Prussian blue analogues (PBA)@PDA. The carbonization of PDA into carbon shells protected the framework from collapsing during high-temperature pyrolysis process, thus enlarging the specific surface areas and porosity. The NiCo@C/FeCo@C@C composite attained an enhanced electrochemical capability, such as an outstanding electronic conductivity from the double carbon shell with porous structure, a large number of active sites and a high electrocatalytic activity from the metallic alloy nanoparticles, which exhibited a highly sensitive response to NFT. Under optimized experimental conditions, the established NiCo@C/FeCo@C@C electrochemical sensor displayed a wide linear range of 0.05–100 μM for NFT determination, coupled with a low detection limit of 14 nM. The practical feasibility of this sensor was also confirmed by the analysis of NFT in tablet and lake water samples with outstanding recovery rates. Moreover, the sustainability of the sensor was demonstrated through its prominent performance in high reproducibility, selectivity and long-term stability. This study thus introduces an innovative approach for the advance of highly efficient electrocatalysts in the area of electrochemical sensing.

Dicarboxylate cellulose nanofibrils-supported silver nanoparticles as a novel, green, efficient and recyclable catalyst for 4-nitrophenol and dyes reduction

This study reports dicarboxylate cellulose nanofibrils (DCNF) as a novel reducing and supporting agent for producing silver nanoparticles (AgNPs) with high efficiency (63.82 % reduction) and loading (6.88 %) using UV light. Unlike previous research, AgNPs formation with DCNF doesn't involve cellulose oxidation. Instead, it appears to involve a loss of carboxyl groups from DCNF. In comparative studies, pristine CNF (PCNF) and TEMPO-oxidized CNF (TOCNF) were also examined for AgNPs production. The resulting AgNPs from DCNF exhibited a significantly smaller average size (3.9 ± 0.7 nm) compared to those from PCNF (26.9 ± 10.9 nm) and TOCNF (13.5 ± 4.5 nm). Catalytic activity evaluation by the 4-nitrophenol (4-NP) reduction reaction revealed a high rate constant of 8.47× 10−3 s−1 by AgNPs/DCNF, which surpassed AgNPs/TOCNF (1.79 × 10−3 s−1) and AgNPs/PCNF (0.63 × 10−3 s−1) by 4.7 and 13.4 times, respectively. Besides 4-NP, AgNPs/DCNF aerogels were also applied for methyl orange and Rhodamine B dyes reduction. The aerogels showed excellent reusability, maintaining over 95 % conversion even after five cycles and also effective in treating real samples and mixed dye solutions. This study opens the door for future research exploring DCNF as a support material for various metal, metal oxide, and carbon nanoparticles.

Determination of trace analytes in nuclear grade Calcium Metal Samples by Axially Viewed Inductively Coupled Plasma – Atomic Emission Spectrometric technique

An Inductively Coupled Plasma – Atomic Emission Spectrometric (ICP-AES) method has been developed for the direct determination of 19 analytes namely, Al, B, Be, Cd, Co, Cr, Cu, Fe, Li, Mg, Mo, Mn, Ni, Pb, Pd, Si, Ta, V and W at trace concentration levels in calcium matrix. In nuclear industry, quality control and assurance of nuclear fuels and associated materials for trace metallic impurity contents form an integral part of the system for the smooth functioning of the reactor for the stipulated time span. In this context, it was required to determine trace analytes in nuclear grade Calcium which is used as a reducing agent for the production of U, Th, Pu, etc. in nuclear industry. Using axial ICP-AES, initially calibration curve for Ca with 396.847nm analytical line was obtained. Systematic studies were carried out to identify various analytical wavelengths of the analyte elements which are almost free from Ca, being the main matrix and calibration curves were obtained. For all analytes and Ca, detection limits and sensitivity values were calculated. To validate the method, three synthetic samples with analyte contents in the range of 0.1 - 5 g/mL and Ca at 1 mg/mL were analyzed, the % recovery being in the range of 80-120% with precision better than 5% RSD. The method was found to be useful for the direct determination of the elements of interest in calcium matrix and was applied for the analysis of two nuclear grade real life calcium metal samples.

Wireless Data Transmission through Concrete Structures

Chloride ion presence in the concrete pore solution is an important factor in the initiation of rebar corrosion. Therefore, elevated chloride concentration in the pore solution needs to be detected as early as possible. For this early detection to be achieved, it is ideal to deploy sensors inside the concrete structure itself. This allows real time sampling of the pore solution which is closest to the rebar. To achieve this one needs to have a system based on wireless communication which allow the sensors to communicate within the structure. This would avoid wired communications methods, which impart fragility and implementation difficulties. This literature review paper endeavours to look at the various types of radiation which can be harnessed to penetrate through the opaque concrete structure. Potential data transmission methods utilising Radio Frequency Radiation, Ultrasonic Radiation, X-Ray Radiation and Neutron Beam Radiation physics were reviewed and evaluated against a set of parameters. The paper scores each radiation type against System Size, Power Supply Requirements, Transmission Range, Complexity of Circuits and Safety issues. Through these scores, each transmission technology was graded on its potential to act as the basis on which to build a micrometre sized intra-concrete data transmission system. The paper shows that ultrasonic radiation is the most promising radiation technology for use in this application.

Label-free detection and simultaneous viability determination of CTCs by lens-free imaging cytometry.

The detection of extremely rare circulating tumor cells (CTCs) in peripheral blood and simultaneously identifying their viabilities are significant for cancer diagnosis and prognosis as well as monitoring the efficacy of personalized treatment. A lens-free imaging system features high-resolution images taken over a large field of view (FOV), which has great potential for CTC detection and viability determination. But current still lens-free systems restrict the application for CTC detection in real samples due to the inherent limitations of lens-free technology: (1) the location of cells in the FOV will affect the imaging; (2) the extremely rare CTCs probably did not exist in one observation. In this paper, we realized the detection of CTCs in whole blood and the simultaneous determination of their viabilities by lens-free imaging cytometry. Our in-flow system plus a large FOV range of lens-free imaging highly increased the detection rate of rare CTCs with a high throughput of 150,000 cells per minute and improved the recognition efficiency for blood cells, living/dead CTCs by using a cell tracing-assisted deep learning algorithm. With this method, the average precision of blood cells, living/dead lung cancer cells A549, and living/dead colon cancer cells SW620 reached 98.80%, 97.88%, 97.93%, 97.72%, and 98.60%, respectively. Our system got a highly consistent result with the manual counting method using fluorescent staining (Pearson's r 99.93% for SW620) and can easily detect as few as 10 dead or living CTCs from 100,000 white blood cells (WBCs). Finally, real clinical samples were detected in our system. Both dead and living CTCs were found in all six advanced-stage cancer patients, and the number of living CTCs per million WBCs ranged from 13 to 39, more than that of the dead CTCs (5 to 25), while none of the CTCs were detected in six healthy control subjects. Moreover, we also found that CTCs died very quickly after leaving the human body, indicating that CTCs should be studied as soon as possible after sampling. Although this method is implemented for CTCs, it can also be used for the detection of other rare cells.

Electrochemical Sensing of Paracetamol Using Functionalized MWCNTs: Integrating Computational and Experimental Methods

An electrochemical sensing platform for the detection of paracetamol is proposed in this work. The sensor (Asp‐MWCNTs/IL/ITO) is based on Indium Tin Oxide (ITO) electrode loaded with asparagine functionalised Multi Walled Carbon Nanotubes (MWCNTs) and Ionic Liquid (IL). Initially, in‐silico studies were performed to check the favourable interaction of the drug with the nanocomposite. The potential energy surface of Asp‐MWCNTs and paracetamol complexes were explored using density functional theory and single‐point energy coupled cluster calculations. The analysis of non‐covalent interactions showed hydrogen bonding interactions predominantly stabilising the complex. The interaction process between Asp‐MWCNTs and paracetamol is spontaneous due to negative value of binding energy (‐0.75 eV). The functionalised MWCNTs were characterised through different techniques. Asp‐MWCNTs/IL/ITO electrode showed good sensitivity with a linear range from 20 – 300 μgL−1 and limit of detection of 0.0194 μM for paracetamol in phosphate buffer as supporting electrolyte. The sensor showed excellent repeatability and reproducibility with a relative standard deviation of 1.45% at 60 μgL−1 concentration. The chemical functionalization resulted in providing extra stability as it retained 95% of its signal response even after 45 days. The sensor’s applicability was tested in real water samples with the help of spiking study which showed good recovery &gt;95%.”

ВЛИЯНИЕ ЭКОНОМИЧЕСКИХ ФАКТОРОВ (ДЕТЕРМИНАНТ) НА СУБЪЕКТИВНЫЕ ОЦЕНКИ УРОВНЯ ФИЗИЧЕСКОЙ АКТИВНОСТИ НАСЕЛЕНИЯ ТРУДОСПОСОБНОГО ВОЗРАСТА

Despite the importance of physical activity indicators and their decisive influence on public health indicators, no studies have been conducted on the impact of health determinants, including economic ones, on physical activity indicators. The purpose of the study is to analyze the fact and degree of influence of economic factors as a component of lifestyle on physical activity indicators. Materials and methods of research. The individual economic characteristics of patients were considered as the object of the study. Since the normality of the distribution for quantitative features, as a rule, was not observed, a nonparametric criterion was used to assess the differences 2 and the nonparametric analogue of the correlation coefficient is the association coefficient. Approaches to the identification and measurement of the economic determinant of public health were described in detail earlier [24, 25]. The size of the real random sample was 1400 respondents. The average age of respondents of working age in the general sample was 39.7 years. As criteria of physical activity, subjective characteristics of physical activity given by the respondents themselves, the fact of performing physical exercises, and attitude to active recreation were used. Results. The use of complex (composite) features characterizing a person's financial situation and economic well-being makes it possible to identify differences in behavioral patterns regarding subjective perceptions of the level of physical activity among the working-age population. The influence of economic factors (determinants) is manifested in a decrease in the level of physical activity and a greater proportion of those who have low and very low levels of physical activity according to their own ideas, a more frequent negative attitude towards physical exercise among respondents with a low level of material security. However, the subjective attitude towards active recreation was positive for the majority of respondents, regardless of their level of material well-being.

Denoising diffusion probabilistic model enhanced tool condition monitoring method under imbalanced conditions

Abstract In recent years, tool condition monitoring (TCM) based on deep learning has been widely considered and achieved remarkable success. However, these methods typically require relatively large training samples to produce significant results, which are both imbalanced and rather troublesome to obtain in the practical application of TCM. To address this issue, a novel TCM method combined with multiscale permutation entropy (MPE), denoising diffusion probabilistic model (DDPM) and a residual network (ResNet) is proposed under conditions of sample imbalance. First, the one-dimensional sensing signal data is converted to a grayscale recurrence plot (RP) by minimizing the MPE of the signals in each channel. Second, combine and splice these grayscale RPs from different channels in each sample into color RPs. After that, the generated RP images using DDPM are added to the imbalanced dataset to augment the data to achieve a balanced state of the dataset. Finally, the balanced mixed data set of real and fake samples is input into a ResNet for recognition and monitoring tool conditions. TCM experiments are conducted to verify the performance of the proposed method with imbalanced dataset, and the results of experimental investigation demonstrate that the accuracy of the proposed method improved by 2%–18.8% compared to that of the other four sample augmentation methods using ResNet18 when the imbalance rate is 1:200.

Wireless Data Transmission through Concrete Structures

Chloride ion presence in the concrete pore solution is an important factor in the initiation of rebar corrosion. Therefore, elevated chloride concentration in the pore solution needs to be detected as early as possible. For this early detection to be achieved, it is ideal to deploy sensors inside the concrete structure itself. This allows real time sampling of the pore solution which is closest to the rebar. To achieve this one needs to have a system based on wireless communication which allow the sensors to communicate within the structure. This would avoid wired communications methods, which impart fragility and implementation difficulties. This literature review paper endeavours to look at the various types of radiation which can be harnessed to penetrate through the opaque concrete structure. Potential data transmission methods utilising Radio Frequency Radiation, Ultrasonic Radiation, X-Ray Radiation and Neutron Beam Radiation physics were reviewed and evaluated against a set of parameters. The paper scores each radiation type against System Size, Power Supply Requirements, Transmission Range, Complexity of Circuits and Safety issues. Through these scores, each transmission technology was graded on its potential to act as the basis on which to build a micrometre sized intra-concrete data transmission system. The paper shows that ultrasonic radiation is the most promising radiation technology for use in this application.