bluuebunny/crossref_metadata_2025 huggingface dataset:
Association of Albumin and Globulin with Mortality Risk in Incident Peritoneal Dialysis Patients
Authors: Lai Kuan-Ju , Hsieh Yao-Peng , Chiu Ping-Fang , Lin Pei-Ru
Published: July 2022

Background: Nutrition and inflammation have been implicated in predicting mortality in patients on peritoneal dialysis (PD). Serum albumin and globulin can be regarded for the nutritional and inflammatory status. However, there is lack of data to evaluate the synergistic effect of albumin and globulin on mortality prediction. Methods: In 554 patients initiating PD from January 2001 to July 2016, we divided them into four groups by the combination of two categories of low vs. high albumin and low vs. high globulin. The median values for albumin and globulin were chosen to classify them into low or high groups. Their associations with all-cause and cardiovascular (CV) mortality were examined in Cox regression models adjusted for confounding clinical and laboratory data. Results: Patients, 52.91 ± 15.2 years old and 47.8% men, had a median (interquartile range) value of 3.3 (2.9–3.8) g/dL for albumin and 2.8 (2.5–3.2) g/dL for globulin, respectively. Patients with low albumin and high globulin had the highest all-cause mortality and CV mortality, with adjusted hazard ratios of 3.87 (95% CI 1.83–8.20, p < 0.001) and 5.65 (95% CI 2.23–14.34, p < 0.001), respectively, compared with those with a high albumin and low globulin having the lowest mortality rate. Sensitivity analyses further confirmed this relationship. Conclusions: A patient profile of either low albumin or high globulin is linked to a higher risk for mortality, particularly for a profile of both low albumin and high globulin compared with one without either of them. Further studies are needed to explore the mechanisms underlying this phenomenon and how to improve clinical outcomes in those high-risk patients.
Translation and Modification of a Mindful Eating Questionnaire for Children Assisted by Item Response Theory in Chinese Children and Adolescents
Authors: Wang Dan , Hu Yuzheng , Zhou Hui , Ye Zhihong , Fu Junfen
Published: July 2022

Mindful eating has gained attention in studies on healthy eating. However, measurement of it is scarce, particularly in pediatrics. This study aimed to translate and modify the 12-item Mindful Eating Questionnaire for Children (MEQ-C) using techniques based on both classical test theory (ICC) and item response theory (IRT) in Chinese children and adolescents. Of the 426 participants enrolled and randomly grouped, the test (n = 223) and validation (n = 203) subsamples were well-matched in age, gender, body mass index z score (BMIz), and waist to height ratio (WHtR) (p > 0.556). Three items were eliminated due to deviating from the mindful eating concept (content validity index < 0.71) and presenting as an independent dimension in parallel analysis, or yielding a poor distribution (−4.331 < b < −0.111). The final 5-item Mindless Eating and 4-item Awareness subscales were identified with sound Cronbach’s α of 0.802 and 0.779, respectively. The remaining items functioned well (a > 1, −3 < b < 3), and the Mindless Eating subscale was accurate for the low-to-medium range (−2 to 0) of the mindful eating measure. The Awareness one was reliable for the relatively high range (0 to 2). Participants’ mindful eating characteristics should be taken into consideration in practice.
Primary Antibiotic Resistance of Helicobacter pylori in Different Regions of China: A Systematic Review and Meta-Analysis
Authors: Chen Jinnan , Li Puheng , Huang Yu , Guo Yixian , Ding Zhaohui , Lu Hong
Published: July 2022

Aim: Understanding the prevalence of antibiotic resistance can provide reliable information for selecting treatment options. The goal of this meta-analysis was to observe the primary antibiotic resistance of Helicobacter pylori (H. pylori) in different regions and time periods of China. Method: We searched PubMed, EMBASE, Chinese Biomedical databases and the China National Knowledge Infrastructure from inception to 20 February 2022. Data on the prevalence of H. pylori primary resistance at various time points were included. A random-effect model was established to calculate the pooled antibiotic resistance. Results: In total, 2150 articles were searched, with 70 meeting the inclusion criteria. The resistance to clarithromycin, metronidazole, levofloxacin amoxicillin, tetracycline and furazolidone in 2016–2020 were 34% (95% CI: 30–39%), 78% (95% CI: 73–84%), 35% (95% CI: 30–40%), 3% (95% CI: 1–5%), 2% (95%CI: 1–4%) and 1% (95% CI: 0–4%), respectively. Clarithromycin showed regional difference, as the resistance was higher in northern (37%, 95% CI: 32–41%) and western China (35%, 95% CI: 17–54%) than that in southern (24%, 95% CI: 17–32%) and eastern China (24%, 95% CI: 20–28%). Conclusion: The resistance of H. pylori to clarithromycin and metronidazole was high and increased over time, whereas resistance to levofloxacin, amoxicillin, tetracycline and furazolidone remained stable.
A New Approach for the Development of Multiple Cardiovascular Risk Factors in Two Rat Models of Hypertension
Authors: Moreno Karyne Garcia Tafarelo , Marques Aline Aparecida Macedo , da Silva Gabriela Pereira , Lourençone Bethânia Rosa , Fortini Clara Soligo , Leite Patrícia Regina Terço , dos Santos Ariany Carvalho , Souza Roosevelt Isaías Carvalho , da Siva Leila Isabel , Gasparotto Junior Arquimedes
Published: July 2022

Cardiovascular disease (CVD) is the leading cause of death among non-communicable diseases. There is a lack of valid animal models that mimic associations among multiple cardiovascular risk factors in humans. The present study developed an animal model that uses multiple cardiovascular risk factors—namely, hypertension, hypothyroidism, and a high-fat diet (HFD). Two models of hypertension were used: renovascular hypertension (two-kidney, one clip [2K1C]) and spontaneously hypertensive rats (SHRs). The naive group was composed of normotensive rats. Twelve weeks after surgery to induce renovascular hypertension, rats in the 2K1C and SHR groups underwent thyroidectomy. The HFD was then implemented for 6 weeks. Renal function, serum redox status, biochemical CVD markers, electrocardiographic profile, blood pressure, mesenteric vascular bed reactivity, histopathology, and morphometry were investigated. Both experimental models induced dyslipidemia, renal function impairment, and hepatic steatosis, accompanied by higher levels of different inflammatory markers and serum oxidative stress. These alterations contributed to end-organ damage in all hypertensive rats. Our findings corroborate a viable alternative model that involves multiple cardiovascular risk factors and resembles conditions that are seen in humans. Both models mimicked CVD, but our data show that SHRs exhibit more significant pathophysiological changes.
Just Rules for Innovative Pharmaceuticals
Authors: Pogge Thomas
Published: July 2022

Globalized in 1995 through the TRIPs Agreement, humanity’s dominant mechanism for encouraging innovations involves 20-year product patents, whose monopoly features enable innovators to reap large markups or licensing fees from early users. Exclusive reliance on this reward mechanism in the pharmaceutical sector is morally problematic for two main reasons. First, it imposes a great burden on poor people who cannot afford to buy patented treatments at monopoly prices and whose specific health problems are therefore neglected by pharmacological research. Second, it discourages pharmaceutical firms from fighting diseases at the population level with the aim of slashing their incidence. These problems can be alleviated by establishing a supplementary alternative reward mechanism that would enable pharmaceutical innovators to exchange their monopoly privileges on a patented product for impact rewards based on the actual health gains achieved with this product. As such, an international Health Impact Fund (HIF) would create powerful new incentives to rapidly develop remedies against diseases concentrated among the poor, provide such remedies with ample care at very low prices, and deploy them strategically to contain, suppress, and ideally eradicate the target disease. By promoting innovations and their diffusion together, the HIF would greatly enlarge the benefits, and thereby also the cost-effectiveness, of the pharmaceutical sector, especially in favor of the world’s poor.
Partial-Failure Segregated Spectrum Assignment for Multicast Traffic in Flex-Grid Optical Networks
Authors: Qiu Yang
Published: July 2022

In this paper, we propose a new algorithm called the partial-failure segregated multicasting routing and spectrum assignment (PFS MRSA) algorithm to improve the service blocking performance of the multicast transmission in flex-grid optical networks (FGONs). By segregating one failure destination leaf-node from a blocked multicast request and accommodating the failure destination leaf-node and the remaining multicast request independently, the success probability of accommodating the originally blocked multicast request can be greatly increased. In this way, the proposed PFS MRSA algorithm can effectively reduce the service blocking probability for the multicast services in FGONs. Simulation results show that the proposed PFS MRSA algorithm achieves significant reduction in service blocking probability when compared with the conventional MRSA algorithms, and such reduction can even reach 100% in some scenarios with low traffic load.
Research on Tunable SPR Sensors Based on WS2 and Graphene Hybrid Nanosheets
Authors: Wang Di , Liu Jin , Yang Haima , Huang Bo , Zeng Guohui
Published: July 2022

A prismatic excitation-based affinity biosensor consisting of the prism (BK7), WS2/graphene hybrid nanosheets, and silver (Ag) as the active metal for the surface plasmon resonance is proposed in this present research. The introduction of the transition metal WS2/graphene layer protected the silver substrate and enhanced the adsorption of biomolecules, which facilitated the quality and performance of detection. Here, we improved the detection structure by focusing on the metallic materials, graphene and WS2 film layers, and the thickness of the measured medium on the sensing effect. The results show that the silver film had a more desirable resonance effect, and the design of the symmetric detection structure produced a double resonance peak, and it provides a reference for distributed sensing. Changing the thickness of the detection medium can dynamically adjust the wave vector matching conditions, which gives the sensor a certain tunability. In the bilayer WS2 and monolayer graphene (W = 2, G = 1) configuration, the sensitivity was up to 224 deg/RIU with a quality factor of 96.97 RIU−1, which has potential for clinical analytic and biochemical detecting applications.
Parameters Influencing Moisture Diffusion in Epoxy-Based Materials during Hygrothermal Ageing—A Review by Statistical Analysis
Authors: Gillet Camille , Tamssaouet Ferhat , Hassoune-Rhabbour Bouchra , Tchalla Tatiana , Nassiet Valérie
Published: July 2022

The hygrothermal ageing of epoxy resins and epoxy matrix composite materials has been studied many times in the literature. Models have been developed to represent the diffusion behaviour of the materials. For reversible diffusions, Fick, Dual–Fick and Carter and Kibler models are widely used. Many parameters, correlated or not, have been identified. The objectives of this review by statistical analysis are to confirm or infirm these correlations, to highlight other correlations if they exist, and to establish which are the most important to study. This study focuses on the parameters of the Fick, Dual–Fick and Carter and Kibler models. For this purpose, statistical analyses are performed on data extracted and calculated from individuals described in the literature. Box plot and PCA analyses were chosen. Differences are then noticeable according to the different qualitative parameters chosen in the study. Moreover, correlations, already observed in the literature for quantitative variables, are confirmed. On the other hand, differences appear which may suggest that the models used are inappropriate for certain materials.
Prediction and Optimization of Process Parameters for Composite Thermoforming Using a Machine Learning Approach
Authors: Tan Long Bin , Nhat Nguyen Dang Phuc
Published: July 2022

Thermoforming is a process where the laminated sheet is pre-heated to the desired forming temperature before being pressed and cooled between the molds to give the final formed part. Defects such as wrinkles, matrix-smear or ply-splitting could occur if the process is not optimized. Traditionally, for thermoforming of fiber-reinforced composites, engineers would either have to perform numerous physical trial and error experiments or to run a large number of high-fidelity simulations in order to determine satisfactory combinations of process parameters that would yield a defect-free part. Such methods are expensive in terms of equipment and raw material usage, mold fabrication cost and man-hours. In the last decade, there has been an ongoing trend of applying machine learning methods to engineering problems, but none for woven composite thermoforming. In this paper, two applications of artificial neural networks (ANN) are presented. The first is the use of ANN to analyze full-field contour results from simulation so as to predict the process parameters resulting in the quality of the formed product. Results show that the developed ANN can predict some input parameters reasonably well from just inspecting the images of the thermoformed laminate. The second application is to optimize the process parameters that would result in a quality part through the objectives of minimizing the maximum slip-path length and maximizing the regions of the laminate with a predesignated shear angle range. Our results show that the ANN can provide reasonable optimization of the process parameters to yield improved product quality. Overall, the results from the ANNs are encouraging when compared against experimental data. The image analysis method proposed here for machine learning is novel for composite manufacturing as it can potentially be combined with machine vision in the actual manufacturing operation to provide active feedback to ensure quality products.
Synthesis and Characterization Bimetallic Organic Framework CoxFex(BDC) and Adsorption Cationic and Anionic Dyes
Authors: Tran Thi Kim Ngan , Phan Cao Phuong Khanh , Ngo Thi Cam Quyen , Hoang Ngoc Bich , Truong Le Dang , Nguyen Thi Kim Oanh
Published: July 2022

Co-doped Fe-MOF bimetallic organic framework materials at different ratios were synthesized based on the solvothermal method, and we evaluated their morphological characteristics by modern analytical methods such as SEM, XRD, FT-IR, and isotherm of nitrogen adsorption-desorption (BET). The specific surface area of the 0.3 CoFe-MOF sample (280.9 m2/g) is much larger than the Fe-MOF and samples at other ratios. The post-synthesized materials were evaluated for their ability to absorb various dyes, including Methylene Blue (MB), Methyl orange (MO), Congo red (CR), and Rhodamine (RhB), and evaluated for the effects of pH, the initial concentration of the dye solution, time, and dose of adsorbent. The results show that the 0.3 CoFe-MOF material has a high adsorption capacity that is superior to both the original Fe-MOF and the CoFe-MOFs at other ratios. The highest adsorption capacity of MB dye by 0.3 CoFe-MOF reaches up to 562.1 mg/g at pH 10, the initial concentration of MB of 200 mg/L, after 90 min. The charged properties of the dyes and the charged nature of the bimetallic organic frameworks are best demonstrated through the adsorption of dye mixtures. The adsorption efficiency on the mixed system of cationic (MB) and anionic (MO) dyes yielded the highest removal efficiency of 70% and 81%, respectively, after 30 min. Therefore, the research has opened up the potential application of M/Fe-MOF modified materials and CoFe-MOF in organic dyes adsorption in wastewater treatment for environmental protection.
One-Step Synthesis of High-Performance N/S Co-Doped Porous Carbon Material for Environmental Remediation
Authors: Huo Xiaoyu , Jia Chao , Shi Shanshan , Teng Tao , Zhou Shaojie , Hua Mingda , Zhu Xiangdong , Zhang Shicheng , Xu Qunjie
Published: July 2022

Potassium thiocyanate (KSCN), a highly efficient “three birds with one stone” activator, might work with inorganic activators to produce excellent N/S co-doped porous carbon (NSC) materials for environmental remediation. However, the effects of inorganic activators on cooperative activation are unclear. As a result, the influence of inorganic activators on the synthesis of NSC materials was investigated further. This study shows that the surface areas of the NSC materials acquired through cooperative activation by potassium salts (KOH or K2CO3) were considerably higher than those acquired through KSCN activation alone (1403 m2/g). Furthermore, KSCN could cooperate with K2CO3 to prepare samples with excellent specific surface area (2900 m2/g) or N/S content. The as-prepared NSC materials demonstrated higher adsorption capability for chloramphenicol (833 mg/g) and Pb2+ (303 mg/g) (pore fitting, complexation). The research provides critical insights into the one-step synthesis of NSC materials with a vast application potential.
On the Macroeconomic Conditions of West African Economies to External Uncertainty Shocks
Authors: Frimpong Siaw
Published: July 2022

This study provides a detailed investigation of the time–frequency and frequency-domain analysis of the interconnectedness of country-level macroeconomic variables. Hence, the wavelet techniques—vector wavelet and wavelet multiple—employed with TVP-VAR are utilised as a robustness check. The macroeconomic variables considered are consumer price index (CPI), real exchange rate (EXR) and nominal effective exchange rate (NEER) for four selected West African economies—Côte d’Ivoire, Gambia, Ghana and Nigeria. The findings of the study reveal that there are significant comovements between the macroeconomic dynamics in a time–frequency domain for the selected economies. From the wavelet multiple technique, the study finds three interesting outcomes. First, there are traces of high comovements between the macroeconomic conditions of some countries in the long term. In addition, NEER has a strong exposure to external shocks due to the presence of periodic swings such as inflation, which makes it largely susceptible to shocks. Second, a high integration of macroeconomic variables, in the long term is found. Third, Global Economic Policy Uncertainty (GEPU) lags in the long term within the interdependencies of CPI as well as NEER but not EXR. This suggests that the presence of inflation most likely exposes these economies to external shocks. However, when this happens, external shocks act as a follower to influence economic activities within this region. The study advocates that governments and policymakers should deploy efficient inflation-targeting monetary policies to enhance price stability and minimise the adverse impact of GEPU for future monetary convergence.
Financing Cooperative Supply Chain Members—The Bank’s Perspective
Authors: Juhász Péter , Felföldi-Szűcs Nóra
Published: July 2022

This paper contributes to the supply chain finance literature with an agent-based Monte Carlo simulation model focusing on the bank’s point of view. Our theoretical model assesses how a bank should screen a supply chain (SC) member and whether that requires different considerations and monitoring systems compared with traditional corporate loans. In the model, the SC members may cooperate, reducing their bankruptcy risk considerably; thus, the chance for and extent of inter-entity financial aid are critical to consider when assessing bankruptcy risk. A cooperative SC member cannot just be financed from debt taken by other members, but it may also offer protection to other SC members using its operating cash flow. Thus, based on our results, bankruptcy risk is SC-specific, rather than a characteristic of an individual firm. Therefore, to finance an SC member is a quasi-joint decision of its peers, so particular care should be paid to estimating and monitoring the correlations between the operational cash flows of cooperative SC members. One of the key results is that of edge default exposure of the bank; it might be optimal to limit the amount of the loan made available to a given collaborative SC member instead of charging higher rates or financing the most attractive SC member only. Another SC member offering an additional guarantee with its assets will provide the remaining need for financing. As this solution also reduces the total bankruptcy risk of the SC, the SC itself should prefer this financing structure.
Marriage and Individual Equity Release Contracts with Dread Disease Insurance as a Tool for Managing the Pensioners’ Budget
Authors: Marciniuk Agnieszka , Zmyślona Beata
Published: July 2022

In many countries around the world, demographic and civilization changes have brought about the phenomenon of aging societies. This phenomenon affects the economy, especially the pension and health care systems, causing difficulties in their financing. The implementation of a policy that would effectively manage the problem of the longevity risk is thus required. Using housing resources and private health insurance to improve retirees’ living standards may serve this purpose. The instruments we propose comprise two variants of contracts: the first for a marriage, the second for an individual client. We analysed the cash flow in both the cases. The results suggest that the amount of cash flows related to reverse equity and dread disease insurance benefits depends on the spouse’s economic status, age, and health conditions. The benefits of the two variants of the contract vary. This paper examines numerous strategies for selecting the type of the contract, taking into consideration the abovementioned factors.
On Fast Jerk-Continuous Motion Functions with Higher-Order Kinematic Restrictions for Online Trajectory Generation
Authors: Alpers Burkhard
Published: July 2022

In robotics and automated manufacturing, motion functions for parts of machines need to be designed. Many proposals for the shape of such functions can be found in the literature. Very often, time efficiency is a major criterion for evaluating the suitability for a given task. If there are higher precision requirements, the reduction in vibration also plays a major role. In this case, motion functions should have a continuous jerk function but still be as fast as possible within the limits of kinematic restrictions. The currently available motion designs all include assumptions that facilitate the computation but are unnecessary and lead to slower functions. In this contribution, we drop these assumptions and provide an algorithm for computing a jerk-continuous fifteen segment profile with arbitrary initial and final velocities where given kinematic restrictions are met. We proceed by going systematically through the design space using the concept of a varying intermediate velocity and identify critical velocities and jerks where one has to switch models. The systematic approach guarantees that all possible situations are covered. We implemented and validated the model using a huge number of random configurations in Matlab, and we show that the algorithm is fast enough for online trajectory generation. Examples illustrate the improvement in time efficiency compared to existing approaches for a wide range of configurations where the maximum velocity is not held over a period of time. We conclude that faster motion functions are possible at the price of an increase in complexity, yet which is still manageable.
Extensive Evaluation of Four Satellite Precipitation Products and Their Hydrologic Applications over the Yarlung Zangbo River
Authors: Ye Xiangyu , Guo Yuhan , Wang Zhonggen , Liang Liaofeng , Tian Jiayu
Published: July 2022

Satellite remote sensing precipitation products with high temporal–spatial resolution and large area coverage have great potential in hydrometeorological research. This paper analyzes the performance of four satellite products from 2000 to 2008 in the Yarlung Zangbo River Basin, namely the Tropical Rainfall Measuring Mission (TRMM), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN), Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), and Climate Prediction Center morphing method (CMORPH). The four products are evaluated from three aspects: spatial distribution, temporal characteristics, and hydrological simulation. The results show that: (1) the four products exhibit similar annual and daily precipitation patterns, with the highest daily precipitation accuracy concentrated in the center, followed by the east and west; (2) TRMM, CHIRPS, and CMORPH exhibit the largest positive bias for monthly precipitation estimation in December, while PERSIANN shows the largest positive bias in July. All products overestimate the precipitation of 0.1–5 mm/d, and underestimate the precipitation above 5 mm/d, especially for PERSIANN; (3) certain Products tend to perform better than others at elevations of 3000–4000 m and in relatively humid zones. TRMM shows relatively stable performance for various elevation and climate zones; (4) for hydrological model validation, TRMM has the best performance during the calibration period, although it is inferior to CHIRPS during the validation period. Overall, TRMM has the highest applicability in the Yarlung Zangbo River Basin; however, its impact on the uncertainty of hydrological modeling needs to be further studied.
Mapping the Spatial Distribution of Fern Thickets and Vine-Laden Forests in the Landscape of Bornean Logged-Over Tropical Secondary Rainforests
Authors: Takeshige Ryuichi , Onishi Masanori , Aoyagi Ryota , Sawada Yoshimi , Imai Nobuo , Ong Robert , Kitayama Kanehiro
Published: July 2022

Forest degradation has been most frequently defined as an anthropogenic reduction in biomass compared with reference biomass in extant forests. However, so-defined “degraded forests” may widely vary in terms of recoverability. A prolonged loss of recoverability, commonly described as a loss of resilience, poses a true threat to global environments. In Bornean logged-over forests, dense thickets of ferns and vines have been observed to cause arrested secondary succession, and their area may indicate the extent of slow biomass recovery. Therefore, we aimed to discriminate the fern thickets and vine-laden forests from those logged-over forests without dense ferns and vines, as well as mapping their distributions, with the aid of Landsat-8 satellite imagery and machine learning modeling. During the process, we tested whether the gray-level co-occurrence matrix (GLCM) textures of Landsat data and Sentinel-1 C-band SAR data were helpful for this classification. Our study sites were Deramakot and Tangkulap Forest Reserves—commercial production forests in Sabah, Malaysian Borneo. First, we flew drones and obtained aerial images that were used as ground truth for the supervised classification. Subsequently, a machine-learning model with a gradient-boosting decision tree was iteratively tested in order to derive the best model for the classification of the vegetation. Finally, the best model was extrapolated to the entire forest reserve and used to map three classes of vegetation (fern thickets, vine-laden forests, and logged-over forests without ferns and vines) and two non-vegetation classes (bare soil and open water). The overall classification accuracy of the best model was 86.6%; however, by combining the fern and vine classes into the same category, the accuracy was improved to 91.5%. The GLCM texture variables were especially effective at separating fern/vine vegetation from the non-degraded forest, but the SAR data showed a limited effect. Our final vegetation map showed that 30.7% of the reserves were occupied by ferns or vines, which may lead to arrested succession. Considering that our study site was once certified as a well-managed forest, the area of degraded forests with a high risk of loss of resilience is expected to be much broader in other Bornean production forests.
Toward a Comprehensive Domestic Dirt Dataset Curation for Cleaning Auditing Applications
Authors: Pathmakumar Thejus , Elara Mohan Rajesh , Soundararajan Shreenhithy V , Ramalingam Balakrishnan
Published: July 2022

Cleaning is an important task that is practiced in every domain and has prime importance. The significance of cleaning has led to several newfangled technologies in the domestic and professional cleaning domain. However, strategies for auditing the cleanliness delivered by the various cleaning methods remain manual and often ignored. This work presents a novel domestic dirt image dataset for cleaning auditing application including AI-based dirt analysis and robot-assisted cleaning inspection. One of the significant challenges in an AI-based robot-aided cleaning auditing is the absence of a comprehensive dataset for dirt analysis. We bridge this gap by identifying nine classes of commonly occurring domestic dirt and a labeled dataset consisting of 3000 microscope dirt images curated from a semi-indoor environment. The dirt dataset gathered using the adhesive dirt lifting method can enhance the current dirt sensing and dirt composition estimation for cleaning auditing. The dataset’s quality is analyzed by AI-based dirt analysis and a robot-aided cleaning auditing task using six standard classification models. The models trained with the dirt dataset were capable of yielding a classification accuracy above 90% in the offline dirt analysis experiment and 82% in real-time test results.
Foggy Lane Dataset Synthesized from Monocular Images for Lane Detection Algorithms
Authors: Nie Xiangyu , Xu Zhejun , Zhang Wei , Dong Xue , Liu Ning , Chen Yuanfeng
Published: July 2022

Accurate lane detection is an essential function of dynamic traffic perception. Though deep learning (DL) based methods have been widely applied to lane detection tasks, such models rarely achieve sufficient accuracy in low-light weather conditions. To improve the model accuracy in foggy conditions, a new approach was proposed based on monocular depth prediction and an atmospheric scattering model to generate fog artificially. We applied our method to the existing CULane dataset collected in clear weather and generated 107,451 labeled foggy lane images under three different fog densities. The original and generated datasets were then used to train state-of-the-art (SOTA) lane detection networks. The experiments demonstrate that the synthetic dataset can significantly increase the lane detection accuracy of DL-based models in both artificially generated foggy lane images and real foggy scenes. Specifically, the lane detection model performance (F1-measure) was increased from 11.09 to 70.41 under the heaviest foggy conditions. Additionally, this data augmentation method was further applied to another dataset, VIL-100, to test the adaptability of this approach. Similarly, it was found that even when the camera position or level of brightness was changed from one dataset to another, the foggy data augmentation approach is still valid to improve model performance under foggy conditions without degrading accuracy on other weather conditions. Finally, this approach also sheds light on practical applications for other complex scenes such as nighttime and rainy days.
Temperature Fluctuations Compensation with Multi-Frequency Synchronous Manipulation for a NV Magnetometer in Fiber-Optic Scheme
Authors: Zhang Ning , Guo Qiang , Ye Wen , Feng Rui , Yuan Heng
Published: July 2022

Nitrogen-vacancy (NV) centers in diamonds play a large role in advanced quantum sensing with solid-state spins for potential miniaturized and portable application scenarios. With the temperature sensitivity of NV centers, the temperature fluctuations caused by the unknown environment and the system itself will mix with the magnetic field measurement. In this research, the temperature-sensitive characteristics of different diamonds, alongside the temperature noise generated by a measurement system, were tested and analyzed with a homemade NV magnetometer in a fiber-optic scheme. In this work, a multi-frequency synchronous manipulation method for resonating with the NV centers in all axial directions was proposed to compensate for the temperature fluctuations in a fibered NV magnetic field sensing scheme. The symmetrical features of the resonance lines of the NV centers, the common-mode fluctuations including temperature fluctuations, underwent effective compensation and elimination. The fluorescence change was reduced to 1.0% by multi-frequency synchronous manipulation from 5.5% of the single-frequency manipulation within a ±2 °C temperature range. Additionally, the multi-frequency synchronous manipulation improved the fluorescence contrast and the magnetic field measurement SNR through an omnidirectional manipulation scheme. It was very important to compensate for the temperature fluctuations, caused by both internal and external factors, to make use of the NV magnetometer in fiber-optic schemes’ practicality. This work will promote the rapid development and widespread applications of quantum sensing based on various systems and principles.
Transformer Feature Enhancement Network with Template Update for Object Tracking
Authors: Hu Xiuhua , Liu Huan , Hui Yan , Wu Xi , Zhao Jing
Published: July 2022

This paper proposes a tracking method combining feature enhancement and template update, aiming to solve the problems of existing trackers lacking global information attention, weak feature characterization ability, and not being well adapted to the changing appearance of the target. Pre-extracted features are enhanced in context and on channels through a feature enhancement network consisting of channel attention and transformer architectures. The enhanced feature information is input into classification and regression networks to achieve the final target state estimation. At the same time, the template update strategy is introduced to update the sample template judiciously. Experimental results show that the proposed tracking method exhibits good tracking performance on the OTB100, LaSOT, and GOT-10k benchmark datasets.
Green Lights and Red Flags: The (Im)Possibilities of Contextual Safeguarding Responses to Extra-Familial Harm in the UK
Authors: Firmin Carlene , Lloyd Jenny
Published: July 2022

Young people experience significant harm in a range of social contexts and from adults and peers unconnected to their caregivers. The recognition of this by policymakers in England, Scotland, and Wales has resulted in child protection policy frameworks increasingly requiring social work responses to the extra-familial contexts where such harm occurs, as well as to the young people affected. This paper presents results from an embedded research project in which five local children’s social care departments used a Contextual Safeguarding framework to respond to this shifting policy direction. The data collected via ethnographic methods over three years included meeting and practice observations (n = 65), meeting participation (n = 334), reviews of young people’s case files (n = 122), interviews (n = 27) and focus groups (n = 33) with professionals, focus groups (n = 6), interviews (n = 2) and surveys (n = 78) with parents and young people, and analysis of local policies and procedures (n = 101). At two stages in the project, the researchers used this dataset to review the progress in each participant site against the Contextual Safeguarding framework. Reporting on the progress made across the five sites, this paper identifies elements of the system change that appeared most feasible or challenging. The results demonstrate four ways in which current policy reforms fall short in creating national contexts that are conducive to the implementation of Contextual Safeguarding, despite local progress towards this goal. The implications for the policy and practices are outlined, with fundamental questions asked of the statutory systems which need to protect, but all too often criminalise, young people abused beyond their front doors.
Using Maps to Boost the Urban Proximity: Analysis of the Location of Public Facilities According to the Criteria of the Spanish Urban Agenda
Authors: Torinos-Aguado Beatriz , Rabanaque Isabel , López-Escolano Carlos
Published: July 2022

Developing analysis models that promote the sustainability, compactness and social balance of cities is particularly important in addressing post-pandemic urban planning. In this context, the population’s proximity to public facilities is essential for achieving these objectives. Based on this framework, this paper analyses the city of Valladolid (Spain) under the criteria of distance between the population and public facilities proposed by the Spanish Urban Agenda. Specifically, the focus is on calculating the coverage of population with access to the facilities within the recommended distance thresholds using GIS techniques. The methods used relate the facilities with the distance to the population in the census sections, a highly detailed statistical unit. The results have been mapped as a decision making support tool for the city, and show how general coverage of access to facilities for the urban area as a whole is adequate, especially in terms of public transport services, and meets the recommendations of the Spanish Urban Agenda. Maps also reveal how some areas of the city are not covered by most public facilities.
Decision Support Concept for Improvement of Sustainability-Related Competences
Authors: Abina Andreja , Batkovič Tanja , Cestnik Bojan , Kikaj Adem , Kovačič Lukman Rebeka , Kurbus Maja , Zidanšek Aleksander
Published: July 2022

In this paper, we derived competences from previously developed competence models, ensuring the effective use of advanced technologies in future factories to improve the sustainability of their business models and strategies. Based on the analysis of the Hogan competence model and competence models for sustainability and leadership, we compiled a selection of competences for digitalisation, automation, robotics, artificial intelligence, and soft competences such as emotional intelligence and cultural literacy. We also included competences required for sustainability, corporate social responsibility, and circular economy. The selected competences formed the core for the conceptual development of a decision support tool for the individualised selection of training for employees. The concept was tested in customised training to improve employees’ skills and motivation for lifelong learning at the selected industrial partner. The developed assessment algorithm was used to monitor the progress of individual employees’ skills development before and after their training participation. The results of the assessment help human resource departments make decisions for selecting the most effective and optimal training for employees to improve their sustainability-related competences. Such a systematic approach can improve and evaluate competences that companies need to transition to a circular economy.
Exploring Customers’ Experiences with P2P Accommodations: Measurement Scale Development and Validation in the Chinese Market
Authors: Lyu Jing , Fang Sha
Published: July 2022

This study explored key dimensions of customers’ experiences with peer-to-peer (P2P) accommodations through Airbnb in China and developed a corresponding measurement scale. Thirty-four in-depth interviews were conducted with Airbnb customers. A pilot study and main survey were implemented to collect data. Exploratory factor analysis was performed, and five factors related to the customer experience were extracted: tangible and sensory experiences, host, cultural experience, interaction with peer guests, and location. Confirmatory factor analysis was performed using data gathered from the main survey. This study contributes to the literature by capturing customers’ holistic experiences in the Chinese market via empirical testing. Theoretical and practical implications are also discussed.
A Note on Varying G and Λ in Chern–Simons Modified Gravity
Authors: Ali Sarfraz , Saif Maryam , Khan Khuram Ali , Shah Nehad Ali , Weera Wajaree
Published: July 2022

We have considered the holographic dark energy and modified holographic Ricci dark energy models to analyze the time-dependent gravitational constant G(t) and cosmological constant Λ(t) in the context of Chern–Simons modified gravity theory. The FRW metric is used to examine the physical and kinematical properties of these models, which predicted the accelerated expansion phase of universe. Further, the Λ(t) showed increasing trends while G(t) showed decreasing trends for both cases. Finally, the range −1.99×10−10yr−1≤G˙G≤0 was estimated mathematically, which is similar to the results obtained from observational data.
Damage-Induced Mutation Clustering in Gram-Positive Bacteria: Preliminary Data
Authors: Nugmanova Raushan , Ramankulov Yerlan , Tarlykov Pavel
Published: July 2022

The phenomenon of a nonrandom distribution of mutations in a genome has been observed for many years. In fact, recent findings have indicated the presence of mutation clusters in different biological systems, including chemically treated yeast, transgenic mice, and human cancer cells. Until now, an asymmetrical distribution of mutations was only described in a single bacterial species. Here, we used ethyl methanesulfonate mutagenesis and a whole-genome sequencing approach to determine if this phenomenon is universal and not confined to Gram-negative bacteria. The Gram-positive bacterium Bacillus subtilis was selected for ethyl methanesulfonate treatment, followed by the next-generation sequencing of several mutagenized B. subtilis genomes. A nonrandom distribution of mutations was observed. This pilot study with a limited number of sequenced clones may indicate not only the universality of the phenomenon of mutation clusters but also the effectiveness of the use of a whole-genome sequencing approach in studying this phenomenon.
Indoor Air Quality Considerations for Laboratory Animals in Wildfire-Impacted Regions—A Pilot Study
Authors: Schuller Adam , Walker Ethan S. , Goodrich Jaclyn M. , Lundgren Matthew , Montrose Luke
Published: July 2022

Wildfire events are increasing across the globe. The smoke generated as a result of this changing fire landscape is potentially more toxic than air pollution from other ambient sources, according to recent studies. This is especially concerning for populations of humans or animals that live downwind of areas that burn frequently, given that ambient exposure to wildfire smoke cannot be easily eliminated. We hypothesized that a significant indoor air pollution risk existed for laboratory animal facilities located proximal to fire-prone areas. Here, we measured real time continuous outdoor and indoor air quality for 28 days at a laboratory animal facility located in the Rocky Mountain region. We demonstrated that during a wildfire event, the indoor air quality of this animal facility is influenced by ambient smoke events. The daily average indoor fine particulate matter value in an animal room exceeded the Environmental Protection Agency’s ambient annual standard 14% of the time and exceeded the World Health Organization’s ambient annual guideline 71% of the time. We further show that specialized cage filtration systems are capable of mitigating air pollution penetrance and could improve an animal’s microenvironment. The potential effects for laboratory animal physiology that occur in response to the exposure levels and durations measured in this study remain to be determined; yet, even acute wildfire exposure events have been previously correlated with significant differences in gene regulatory and metabolic processes in vivo. We believe these findings warrant consideration for indoor laboratory animal facility air quality monitoring and development of smoke exposure prevention and response protocols, especially among facilities located downwind of fire-prone landscapes.
Investigation of the effect of small iron and molybdenum additives on the phase composition of a titanium and nickel-based powder alloy
Authors:   Southwest State University, Kursk, Gadalov V. N. , Gubanov O. M. ,   Novolipetsk Metallurgical Combine (NLMK), Lipetsk, Filonovich A. V. ,   Southwest State University, Kursk, Vornacheva I. V. ,   Southwest State University, Kursk, Shirobokov P. V. ,   Southwest State University, Kursk
Published: July 2022

The article presents information on the study of the effect of small iron and molybdenum additives on the phase composition of a powder alloy based on titanium and nickel. The authors found that the presence of unreacted pure components (titanium and nickel) indicates the incompleteness of the diffusion interaction process and the need to adjust the sintering mode of porous samples. Additives of 2.5% and 4.0% iron, as well as 2% molybdenum act as an inhibitor on the sintering process of porous samples.
Tax monitoring in the construction organization
Authors:   Moscow State University of Civil Engineering, Akimova E. М.
Published: July 2022

The contents and functions of tax monitoring are considered in the article. The possible ways of statement of tax monitoring in the organizations, their advantages and disadvantages are investigated. The authors drew the conclusion, that the transition to the so-called tax showcase is the most perspective of them. The stages of expansion of a tax showcase in the organizations are presented, the conditions necessary for its successful formation in the organization are formulated.
On the ban of application of budget standards during the execution of government contracts
Authors:   ", Vasilyeva E. Yu. ,   Budget-and-contracted work in construction",   Journal
Published: July 2022

The article is devoted to the amendments, adopted in May, 2022 for the development of the legislation in the sphere of purchases of construction works. A ban on the application of budget standards and prices of construction resources during the execution of some works has been imposed since 01.05.2022. This innovation can have both positive influence on the performance of contracts in the sphere of construction, and some negative consequences. The analysis of the matter proves, that the imposed ban, as well as the new order of formation of the estimated cost of construction in general, need completion.
A METHOD FOR ASSESSING THE TECHNICAL CAPABILITY OF A VEHICLE DRIVER TO AVOID AN ACCIDENT USING MODERN INFORMATION AND TELEMATICS TECHNOLOGIES
Authors:   Saint-Petersburg State University of Architecture and Civil Engineering, EVTYUKOV S.A. , LUKASHOV B.V. ,   Saint-Petersburg State University of Architecture and Civil Engineering
Published: July 2022

Promising areas of research of the subsystem for detecting incidents of the intelligent transport system (ITS) have been identified. A method for assessing the technical capability of a vehicle driv-er to avoid an accident using modern information and telematics technologies is presented.
ASSESSMENT OF THE LEVEL OF INTELLECTUALIZATION OF THE ROAD TRANSPORT SYSTEM
Authors:   Saratov State Technical University, BASKOV V.N. , ISAEVA E.I. ,   Saratov State Technical University
Published: July 2022

The intellectualization of the road transport system of the city allows solving transport problems in the field of traffic management, and the creation of a Unified Intelligent Transport System at the country level will allow monitoring the traffic situation at the road network in real time, making the necessary management decisions, and will also enable participants in the transport process to use ITS services anywhere in the country. An analysis of the dynamics of changes in the accident rate in the city of Saratov and the Saratov region was carried out. The structure of development and interaction of ITS components is considered. The process of phased introduction of a single platform for managing the transport system, which contributes to an increase in the level of intel-lectualization of the road transport system, is considered.