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Objectives This study was conducted to assess the relationship between adventitial vasa vasorum neovascularization (VVn) in femoral artery of type 2 diabetic patients with macroangiopathy and the recruitment of macrophages and lymphocytes, and to relate the density of VVn to the occurrence of cardiovascular events. Materials Femoral artery samples were obtained from amputation cases. A total of 55 type 2 diabetic patients with macroangiopathy, 15 autopsy cases with type 2 diabetes without atherosclerosis. Methods Hematoxylin and eosin (H&E) staining to observe the histopathological features; Victoria blue staining to analyze the histological features; immunohistochemistry (CD34, CD68, CD20, and CD3) to determine the VVn density and the expression of macrophages, B lymphocytes, and T lymphocytes. Results Type 2 diabetic patients with macroangiopathy showed a higher mean adventitial VVn density in femoral artery (48.40 ± 9.39 no./mm2) than patients with type 2 diabetes without atherosclerosis (19.75 ± 6.28 no./mm2) (p Conclusion VVn density in type 2 diabetic patients with macroangiopathy is positively correlated with the adventitial immune-inflammatory cell numbers and the development of atherosclerotic lesions. Furthermore, VVn density is associated with adverse cardiovascular events.

Understanding the drivers of community assembly process is of great importance for better conservation outcomes; and the main mechanisms include competitive exclusion, environmental filtering and neutral assembly. While mechanisms of assembly processes for vertebrates living in natural habitats have been well studied, their urban counterparts encountering highly human modified environments are still largely understudied. As a result, there are knowledge gaps for urban planners to better protect urban biodiversity and develop eco-friendly cities. University campuses are important components of cities, harboring the majority of urban biodiversity. In this study, based on monthly bird surveys data covering 12 university campuses located either downtown or in the newly developed areas in Nanjing, China, in 2019, we studied the assembly processes of campus’s birds, and their main drivers, by modeling a set of ecological and landscape determinants. Our results showed that bird diversity in the newly developed areas were significantly higher than those downtown. The phylogeny of bird communities in all universities followed a pattern of aggregation, indicating that environmental filtering played a major role in the community assembly. Specifically, grass, water and building were the main factors affecting campus’s bird functional and phylogenetic diversity, with the area of grass and water habitats having a significant positive correlation with phylogenetic diversity while the building areas was negatively correlated. Our results emphasize that habitat features play a decisive role in determining urban bird community assembly processes. We suggest that increasing landscape diversity and improving the landscape connectivity could be a powerful way to maintain and promote urban bird diversity.

Epidural spinal cord stimulation has been reported to partially restore volitional movement and autonomic functions after motor and sensory-complete spinal cord injury (SCI). Modern spinal cord stimulation platforms offer significant flexibility in spatial and temporal parameters of stimulation delivered. Heterogeneity in SCI and injury-related symptoms necessitate stimulation personalization to maximally restore functions. However, the large multi-dimensional stimulation space makes exhaustive tests impossible. In this paper, we present a Bayesian optimization strategy for identifying personalized optimal stimulation patterns based on the participant's expressed preference for stimulation settings. We present companion validation protocols for investigating the credibility of learned preference models. The results obtained for five participants in the E-STAND spinal cord stimulation clinical trial are reported. Personalized preference models produced by the proposed learning and optimization algorithm show that there is more similarity in optimal frequency than in pulse width across participants. Across five participants, the average model prediction accuracy is 71.5% in internal cross-validation and 65.6% in prospective validation. Statistical tests of both validation studies show that the ability of the preference models to correctly predict unseen preference data is significantly greater than chance. The personalized preference models are also shown to be significantly correlated with motor task performance across participants. We show that several aspects in participants' quality of life has been improved over the course of the trial. Overall, the results indicate that the Bayesian preference optimization algorithm could assist clinicians in the systematic programming of individualized therapeutic stimulation settings and improve the therapeutic outcomes.

Previous studies showed that the COVID-19 outbreak increased the levels of depression and anxiety in heterogeneous populations. This study examines the prevalence of depression and anxiety among Chinese international students enrolled in US universities during the COVID-19 pandemic and identifies the associated factors, including habits, social and psychological support, sleep quality, and remote learning. Participants were recruited with snowball sampling through 21 Chinese international student associations in US universities. The survey consisted of demographic questions, the Social Support Rating Scale (SSRS), the Insomnia Severity Index (ISI), the Patient Health Questionnaire-9 (PHQ-9), the General Anxiety Disorder-7 (GAD-7), and self-constructed questions on academic performance, financial concerns, use of social media, physical exercise, and psychological support. Cut-off scores of 10 were used for both PHQ-9 and GAD-7 to determine the binary outcomes of depression and anxiety, respectively. Bivariant analyses and multivariable logistic regression analyses were performed to identify the associated factors. Among 1881 participants, we found a prevalence of depression at 24.5% and that of anxiety at 20.7%. Multiple correlates—including recent exposure to traumatic event(s), pandemic-related financial concerns, workload, social support, remote learning, willingness to seek professional help, and sleep quality—were identified. It is critical for future studies to further investigate this student population and for universities to provide more flexible learning options and more access to psychological services.

Strobilurin fungicides are a class of persistent fungicides frequently detected in the environment. Microbes can effectively degrade strobilurins, but the mechanisms are complex and diverse. Compared with isolated strains, bacterial consortia are more robust in terms of the degradation of multiple pollutants. The enrichment culture XS19 is a group of bacterial strains enriched from soil and degrades six strobilurins at 50 mg/L within 8 d, including azoxystrobin, picoxystrobin, trifloxystrobin, kresoxim-methyl, pyraclostrobin and enestroburin. LC-Q-TOF-MS analysis confirmed that XS19 can demethylate these strobilurins via hydrolysis of the methyl ester group. Analysis of the bacterial communities suggested that Pseudomonas (69.8%), Sphingobacterium (21.2%), Delftia (6.3%), and Achromobacter (1.6%) spp. were highly associated with the removal of strobilurins in the system. Metagenomics-based comprehensive analysis of XS19 suggested that carboxylesterases in Pseudomonas and Sphingobacterium play a central role in the catabolism of strobilurins. Moreover, the carboxylesterase inhibitor bis-p-nitrophenyl phosphate inhibited the degradation activity of strobilurins in XS19. This work proved that XS19 or carboxylesterases can effectively hydrolyze strobilurins, providing a reliable bioremediation paradigm.

BACKGROUND Previous studies have shown that COVID-19 increased the prevalence of depression and anxiety among various populations. However, few have explored the mental health issues of Chinese international students in the US and the risk factors involved. OBJECTIVE his study examines the prevalence of anxiety and depression among Chinese international students enrolled in US universities during the COVID-19 pandemic and identifies the risk factors pertaining to changes in lifestyle, social support, sleep quality, and the virtual instruction mode to this student population. METHODS This study was conducted via an online cross-sectional questionnaire distributed through snowball sampling. The questions of the survey included demographic information, self-constructed questions on academic performance, financial concerns, use of social media, exercise, and psychological support, the Social Support Rating Scale (SSRS), the Insomnia Severity Index (ISI), the Patient Health Questionnaire-9 for depression (PHQ-9), and the General Anxiety Disorder-7 (GAD-7) for anxiety. Univariate analyses and multivariate logistic regression analysis were performed to identify the associated risk factors. RESULTS From the 1881 participants, this study found a general prevalence of depression (PHQ-9 score⩾ 5) at 48.6% and that of anxiety (GAD-7⩾ 5) at 43.0% among Chinese international students in the US during the late COVID pandemic period. Multivariate logistic regression analysis showed that recent traumatic event(s), having friend(s) as tuition source(s), agreeing with and strongly agreeing with the pandemic’s impacts on financial status, a little workload, medium workload, a lot of workload, and higher ISI scores to be a associated with an increased risk of depression, while being a PhD student, more sources of emotional support, and higher SSRI scores were associated a lower risk of depression. Additionally, having friend(s) as tuition source(s), a little workload, often staying up for online courses, strongly agreeing with remote learning’s negative impacts on personal relationships, and higher ISI scores were associated with an increased risk of anxiety, while higher SSRI scores and older ages were associated with a lower risk of anxiety. CONCLUSIONS This study showed a high prevalence of depression and anxiety among Chinese international students in the US. Multiple risk factors pertaining to financial concerns, workload, social support, and sleep quality were identified. It is important for future studies to further investigate this student population and for schools to make adjustments to better accommodate their psychological needs.

The pathophysiology of primary osteoarthritis (OA) remains unclear. However, a specific subclassification of OA in relatively younger age groups is likely correlated with a history of articular cartilage damage and ligament avulsion. Surgical animal models of OA of the knee play an important role in understanding the onset and progression of post-traumatic OA and aid in the development of novel therapies for this disease. However, non-surgical models have been recently considered to avoid traumatic inflammation that could affect the evaluation of the intervention. In this study, an intra-articular cartilage lesion rat model induced by in vivo cyclic compressive loading was developed, which allowed researchers to (1) determine the optimal magnitude, speed, and duration of load that could cause focal cartilage damage; (2) assess post-traumatic spatiotemporal pathological changes in chondrocyte vitality; and (3) evaluate the histological expression of destructive or protective molecules that are involved in the adaptation and repair mechanisms against joint compressive loads. This report describes the experimental protocol for this novel cartilage lesion in a rat model.

Based on the statistical data of COVID-19 from January 22, 2020 to June 7, 2020 in Hubei, China, the states are divided according to the standard deviation, and based on the Markov chain theory, the mathematical analysis model of daily confirmed, dead and cured number of COVID-19 in Hubei, China was established, and the probability of steady distribution of each state and the average return time were used to analyze the prevention and control of COVID-19 epidemic situation in Hubei, China. The analysis shows that by June 2020, the daily confirmed number of COVID-19 in Hubei, China is basically in state Ⅰ, the number of daily deaths is basically in state Ⅰ-Ⅱ, and the number of people cured per day is basically in state Ⅰ-Ⅱ.

The prevalence of inflammatory bowel disease (IBD), which includes ulcerative colitis (UC) and Crohn’s disease (CD), increases gradually worldwide in the past decades. IBD is generally associated with the change of the immune system and gut microbiota, and the conventional treatments usually result in some side effects. Bifidobacterium longum, as colonizing bacteria in the intestine, has been demonstrated to be capable of relieving colitis in mice and can be employed as an alternative or auxiliary way for treating IBD. Here, the mechanisms of the Bifidobacterium longum in the treatment of IBD were summarized based on previous cell and animal studies and clinical trials testing bacterial therapies. This review will be served as a basis for future research on IBD treatment.

Utilization of glycerol, a biodiesel byproduct, has not been well explored. In the present study, glycerol and the other carbon sources were studied for cometabolism of dibenzothiophene (DBT), a model chemical commonly used in bioremediation studies, by Paraburkholderia sp. C3. This study showed a direct association between rhamnolipids (RLs) biosynthesis and DBT biodegradation induced by different carbon sources in a Paraburkholderia specie. Glycerol can induce the strain C3 produce at least four RLs. The RL precursor is mainly derived from the fatty acid synthesis (FAS II) and β-oxidation pathway. The genome contained two (fabF and fabG) and four (fadA, fadE, fadB and echA) genes involved in FAS II and β-oxidation, respectively. The genome also carried the rhlA and rhlB genes involved in rhamnosyltransferase for RL biosynthesis and two DBT dioxygenase genes (nahAc and catA). The findings suggest a viable approach of using the biodiesel byproduct glycerol to remediate contaminated environments.

The fungicides epoxiconazole and pyraclostrobin have been widely used to control wheat fusarium head blight. This study was designed to investigate the dissipation behaviors in different climate regions and provide data for the modification of maximum residue limits of the two fungicides. Wheat samples were collected from field sites in twelve different regions, China and analyzed with an HPLC-MS/MS method for simultaneous detection of epoxiconazole and pyraclostrobin in wheat. The average recoveries of epoxiconazole and pyraclostrobin in wheat matrix were 87–112% and 85–102%, respectively, with the relative standard deviations ≤8.1%. The limits of quantification of epoxiconazole and pyraclostrobin in grain and straw were both 0.01 mg/kg. The dissipations of epoxiconazole and pyraclostrobin followed first-order kinetics, with the half-lives of 10.3 days and 7.6 days, respectively. The terminal residues of epoxiconazole and pyraclostrobin in grain were below 0.034 and 0.028 mg/kg, separately, both lower than the maximum residue limits recommended by China. Based on Chinese dietary pattern and terminal residue distributions, the risk quotients of epoxiconazole and pyraclostrobin were 13.9% and 65.9%, respectively, revealing the evaluated wheat exhibited an acceptably low dietary risk to consumers.

A passivity-based input observer is proposed. The problem is motivated by reaction rate and heat estimation in control of chemical reaction systems. The input observer assumes measurement of the output, and its first order time derivative. The observer gives asymptotically converging estimation when both are accurately available, the so-called ideal case. In the nonideal case, where the derivative is not available, differentiators can be used to reconstruct the derivative with some error. Simulation results show performance results using a deadbeat differentiator for derivative reconstruction.

With the continuous advancement of the new curriculum reform, the cultivation of primary and secondary school students’ thinking ability has gradually become the focus of education, and the strength of thinking ability will have a profound impact on students’ problem analysis and judgment ability. Thinking visualization theory provides important guidance for the cultivation and orderly development of students’ thinking ability. The application of thinking visualization theory in primary school mathematics teaching can realize the effective combination of graphics and text, and then present mathematics knowledge and conceptual content to students concretely and vividly, and help students effectively sort out knowledge, To achieve high quality and efficient learning, reduce the primary school students in the process of mathematics problems and difficulties. This research focuses on the reconstruction of primary school mathematics classroom under the theory of “thinking visualization”，and provides ideas and methods from multiple perspectives.

This paper shows that we can use the backstepping method for semi-batch reactor temperature control. The system studied has relative degree higher than one. We show that the feedback system can be written in its error dynamic model form, which is shown to be passive. Input strictly passive feedback controllers render the origins of the passive error dynamics to be globally asymptotically stable. A simulation study shows the application to a semi-batch reactor. Industrial trials are in progress.

This work shows that kinetic information is not needed to estimate states (compositions) and control continuous stirred tank reactors (CSTRs). An asymptotic observer is developed using reaction invariants to provide on-line estimates of unmeasured compositions. The estimates are used in a feedback controller, based on inventory control theory, to control compositions and reactor temperature. The dynamics of the reaction system are reduced using reaction variants and invariants. The reaction rates are estimated through differentiation of reaction variants, such that no kinetic information is required. An example of a serial reaction in a CSTR illustrates the theoretical results and the performance of the proposed adaptive control approach.

A novel method for determination of inorganic arsenic in natural water, based on nano ferric hydroxides (FeOOH) preconcentration and electrochemistry detection has been developed. As the nano α-FeOOH could successfully act as the adsorbent and electrode matrix modifier, the method presents great potential in practical routine analysis of inorganic arsenic. With optimization of the experimental conditions, nano α-FeOOH modified carbon paste electrode (α-FeOOH@CPE) was obtained by mixing 0.03 g of nano α-FeOOH and 0.02 g graphite powder in n-eicosane as an adhesive and then embedding them in a Teflon tube. Cyclic voltammetry, chronoamperometry and high resolution transmission electron microscopy were used to check and confirm the presence of nano α-FeOOH on the carbon paste electrodes. According to the results, α-FeOOH@CPE showed a considerably higher response to As(III) in comparison with the bare CPE, indicating the α-FeOOH has well selective enrichment for As(III). The developed modified electrode showed a linear range of 1.0 × 10-8 ~ 2.0 × 10-5 mol·L-1 and detection limit of 5.0 nmol·L-1 (S/N = 3). The newly prepared carbon paste electrode was successfully applied for As(III) determination in Yangzonghai Lake water with RSD of less than 3.6 % (n = 3) and recovery in the range of 100.7 ~ 115.0 %. DOI: http://dx.doi.org/10.5755/j01.ms.24.4.18499

In this thesis, we develop a passivity-based adaptive control framework for controlling nonlinear processes with uncertainty. The development of the method is motivated by the question whether we can control reaction systems without the knowledge of reaction kinetics. The proposed adaptive control framework incorporates the measurements’derivative information in order to estimate the uncertainty involved in output dynamics. The output dynamics is assumed to take a special control-affine structure, and by using the output’s derivative information we can avoid using internal state dynamics, which is not usually available. Passivity theory is applied for control and estimation designs and overall closed-loop stability is achieved. By extending the passivity-based control to systems with relative degree higher than one throughbackstepping, we can obtain cascade feedback schemes with PID controllers that overall control convergence is guaranteed. The proposed framework allows us to control reaction systems without knowing the reaction kinetics, and estimate unmeasured compositions by utilizing theavailable partially linear structure of internal dynamics. A reactor temperature control problem that usually has high relative degree is used to illustrate the applicationof passivity-based backstepping control, and results from industrial trials are presented.

In this work, we first report the application of fluorescent polymer brushes film as a device for ultrasensitive and selective detection of TNT. As positively charged fluorescent molecules of quaternary ammonium tetraphenylethylene derivatives (d-TPE) were self-assembled on the brushes of poly(acrylic acid) (PAA) by coulomb forces, we obtained a novel fluorescent polymer brushes film with excellent photoluminescent properties, and the emission could be quantitatively and sensitively responsive to 2,4,6-trinitrotoluene (TNT) due to the electron transfer between d-TPE and TNT. The limit of detection of TNT was established to be 0.1 ppb in water. The fluorescent device could also be used repeatedly for TNT detection, which indicated a promising application in trace explosive detection.

Colloidal particles (CPs) have been the subject of intensive studies and have attracted increasing attention from the scientific community. In this contribution, we present the design and synthesis of luminescent colloidal crystal films. Rare earth complexes as the photoluminescent source is introduced into the polymeric nanospheres system, the diameter can be controlled by changing the polymeric reaction condition, which can act as building blocks to prepare diverse functional materials. Further, three-dimensional (3-D) colloidal crystal films with excellent fluorescent properties are fabricated by self-organization of the monodispersed polymeric nanospheres. The colloidal crystal film indicates a photonic band gap, which depends on the diameter and size-dispersing of the nanospheres building blocks. It shows potential applications in fabricating optical devices, data storage, chemical and biological sensors, and color displays.