Assessing the nonlinear impact of green space exposure on psychological stress perception using machine learning and street view images.

Introduction: Urban green space (GS) exposure is recognized as a nature-based strategy for addressing urban challenges. However, the stress relieving effects and mechanisms of GS exposure are yet to be fully explored. The development of machine learning and street view images offers a method for large-scale measurement and precise empirical analysis. Methods: This study focuses on the central area of Shanghai, examining the complex effects of GS exposure on psychological stress perception. By constructing a multidimensional psychological stress perception scale and integrating machine learning algorithms with extensive street view images data, we successfully developed a framework for measuring urban stress perception. Using the scores from the psychological stress perception scale provided by volunteers as labeled data, we predicted the psychological stress perception in Shanghai's central urban area through the Support Vector Machine (SVM) algorithm. Additionally, this study employed the interpretable machine learning model eXtreme Gradient Boosting (XGBoost) algorithm to reveal the nonlinear relationship between GS exposure and residents' psychological stress. Results: Results indicate that the GS exposure in central Shanghai is generally low, with significant spatial heterogeneity. GS exposure has a positive impact on reducing residents' psychological stress. However, this effect has a threshold; when GS exposure exceeds 0.35, its impact on stress perception gradually diminishes. Discussion: We recommend combining the threshold of stress perception with GS exposure to identify urban spaces, thereby guiding precise strategies for enhancing GS. This research not only demonstrates the complex mitigating effect of GS exposure on psychological stress perception but also emphasizes the importance of considering the "dose-effect" of it in urban planning and construction. Based on open-source data, the framework and methods developed in this study have the potential to be applied in different urban environments, thus providing more comprehensive support for future urban planning.

Insights into climate change dynamics: A tourism climate index-based evaluation of Gilgit-Baltistan, Pakistan.

The tourism industry is a significant contribution to the economy of many countries, including Pakistan. However, its activities often have a negative impact on the environment, particularly related to climate change. Notably, Pakistan ranks fifth among countries most affected by climate change, which requires a targeted analysis of the tourism sector to determine its potential impacts. Despite the critical nature of this issue, there is currently a lack of research that examines how climate change specifically impacts Pakistan's tourism industry. This study aims to address this gap by using the Tourism Climate Index (TCI) to assess the impact of climate change on the suitability of different tourism locations across the country. Our results show that popular tourist destinations such as Gilgit-Baltistan experience their peak season in the warmer third quarter (summer), which corresponds to the highest observed TCI values. This suggests that warmer temperatures could boost tourism activity and spending in these regions. Furthermore, our analysis shows that air temperature plays a crucial role in determining tourist comfort levels and significantly influences tourists' TCI values and sensory experiences. The results of this study show that the TCI methodology can be an effective tool for further research into the geographical impacts of climate change on tourism. By identifying necessary changes due to climatic changes, future studies could provide valuable insights into how the tourism industry can adapt to and reduce its environmental footprint.

Abnormal longitudinal changes of structural covariance networks of cortical thickness in mild traumatic brain injury with posttraumatic headache.

BACKGROUND: It is widely acknowledged that mild traumatic brain injury (MTBI) leads to either functionally or anatomically abnormal brain regions. Structural covariance networks (SCNs) that depict coordinated regional maturation patterns are commonly employed for investigating brain structural abnormalities. However, the dynamic nature of SCNs in individuals with MTBI who suffer from posttraumatic headache (PTH) and their potential as biomarkers have hitherto not been investigated. METHODS: This study included 36 MTBI patients with PTH and 34 well-matched healthy controls (HCs). All participants underwent magnetic resonance imaging scans and were assessed with clinical measures during the acute and subacute phases. Structural covariance matrices of cortical thickness were generated for each group, and global as well as nodal network measures of SCNs were computed. RESULTS: MTBI patients with PTH demonstrated reduced headache impact and improved cognitive function from the acute to subacute phase. In terms of global network metrics, MTBI patients exhibited an abnormal normalized clustering coefficient compared to HCs during the acute phase, although no significant difference in the normalized clustering coefficient was observed between the groups during the subacute phase. Regarding nodal network metrics, MTBI patients displayed alterations in various brain regions from the acute to subacute phase, primarily concentrated in the prefrontal cortex (PFC). CONCLUSIONS: These findings indicate that the cortical thickness topography in the PFC determines the typical structural-covariance topology of the brain and may serve as an important biomarker for MTBI patients with PTH.

Abnormal neuroanatomical patterns as potential diagnostic biomarkers for cocaine use disorder.

Cocaine use disorder (CUD) is a global health problem with serious consequences for both individuals and society. Previous studies on abnormal anatomical patterns in CUD have mainly used voxel-based morphometry to investigate grey matter volume changes, while surface-based morphometry (SBM) has been found to provide detail information on cortical thickness (CT), surface area and cortical meancurve, which can contribute to a better understanding of structural brain changes associated with CUD. In this study, SBM was conducted to investigate abnormal neuroanatomical patterns in CUD and whether these abnormal patterns could be used as potential diagnostic biomarkers for CUD. Sixty-eight CUD individuals and 52 matched healthy controls were enrolled, and all participants performed once MRI scanning and clinical assessments. We found that CUD individuals exhibited altered morphological indicators across widespread brain regions and these abnormal anatomical alterations were significantly predictive of CUD status. Furthermore, the CT reduction of right insula was significantly associated with years of cocaine use in CUD. These findings revealed the association of abnormal anatomical patterns in specific brain regions in CUD, which further improve the understanding of CUD pathophysiology and provide the alternative diagnostic biomarkers for CUD.

Neuroanatomical restoration of salience network links reduced headache impact to cognitive function improvement in mild traumatic brain injury with posttraumatic headache.

BACKGROUND: Neuroanatomical alterations have been associated with cognitive deficits in mild traumatic brain injury (MTBI). However, most studies have focused on the abnormal gray matter volume in widespread brain regions using a cross-sectional design in MTBI. This study investigated the neuroanatomical restoration of key regions in salience network and the outcomes in MTBI. METHODS: Thirty-six MTBI patients with posttraumatic headache (PTH) and 34 matched healthy controls were enrolled in this study. All participants underwent magnetic resonance imaging scans and were assessed with clinical measures during the acute and subacute phases. Surface-based morphometry was conducted to get cortical thickness (CT) and cortical surface area (CSA) of neuroanatomical regions which were defined by the Desikan atlas. Then mixed analysis of variance models were performed to examine CT and CSA restoration in patients from acute to subacute phase related to controls. Finally, mediation effects models were built to explore the relationships between neuroanatomical restoration and symptomatic improvement in patients. RESULTS: MTBI patients with PTH showed reduced headache impact and improved cognitive function from the acute to subacute phase. Moreover, patients experienced restoration of CT of the left caudal anterior cingulate cortex (ACC) and left insula and cortical surface area of the right superior frontal gyrus from acute to subacute phase. Further mediation analysis found that CT restoration of the ACC and insula mediated the relationship between reduced headache impact and improved cognitive function in patients. CONCLUSIONS: These results showed that neuroanatomical restoration of key regions in salience network correlated reduced headache impact with cognitive function improvement in MTBI with PTH, which further substantiated the vital role of salience network and provided an alternative clinical target for cognitive improvement in MTBI patients with PTH.

Fast detection of dam zone boundary based on Otsu thresholding optimized by enhanced harris hawks optimization.

Earth-rock dams are among the most important and expensive infrastructure projects. A key safety issue is dam zone boundary detection to prevent the intrusion of materials from different zones. However, existing detection methods strongly highly depend on human judgement, which is time consuming and labor intensive. To solve this problem, this work proposes a fast boundary detection method based on the Otsu algorithm optimized by enhanced Harris hawks optimization (HHO). Compared with the original Otsu algorithm, the proposed method has a higher computation speed to meet the time requirements of engineering projects. Particle swarm optimization is adopted to enhance the exploration stage of HHO. In addition, a tangent function and chaotic sine map are used to improve the convergence speed and robustness. The application of the proposed method to a real-life project shows that the calculation time can be reduced to 20 s, which is approximately 18.8% of the original calculation time.

The Impact of Urbanization on Urban Heat Island: Predictive Approach Using Google Earth Engine and CA-Markov Modelling (2005-2050) of Tianjin City, China.

Urbanization has adverse environmental effects, such as rising surface temperatures. This study analyzes the relationship between the urban heat island (UHI) intensity and Tianjin city's land cover characteristics. The land use cover change (LUCC) effects on the green areas and the land surface temperature (LST) were also studied. The land cover characteristics were divided into five categories: a built-up area, an agricultural area, a bare area, a forest, and water. The LST was calculated using the thermal bands of spatial images taken from 2005 to 2020. The increase in the built-up area was mainly caused by the agricultural area decreasing by 11.90%. The average land surface temperature of the study area increased from 23.50 to 36.51 °C, and the region moved to a high temperature that the built-up area's temperature increased by 1.5%. Still, the increase in vegetation cover was negative. From 2020 to 2050, the land surface temperature is expected to increase by 9.5 °C. The high-temperature areas moved into an aerial distribution, and the direction of urbanization determined their path. Urban heat island mitigation is best achieved through forests and water, and managers of urban areas should avoid developing bare land since they may suffer from degradation. The increase in the land surface temperature caused by the land cover change proves that the site is becoming more urbanized. The findings of this study provide valuable information on the various aspects of urbanization in Tianjin and other regions. In addition, future research should look into the public health issues associated with rapid urbanization.

Gastronomic Tourism and Tourist Motivation: Exploring Northern Areas of Pakistan.

Gastronomic tourism is becoming an essential consideration among tourists when choosing a tourist destination. One of the main reasons for visiting a specific destination for almost 15% of tourists is "gastronomy". This has led to the development of a new kind of tourism called "Gastronomic Tourism". However, there has been minimal research on gastronomy tourism, specifically in Pakistan. The primary purpose of this study is to measure the level of satisfaction in a tourist destination and furthermore consider gastronomy as a component of visitor motivation. A survey of 307 tourists who had recently visited Pakistan's northern areas was undertaken to conduct the study. This has enabled us to better understand the variables that influence the behaviors and attitudes of tourists toward this popular tourist attraction. Gastronomy motivation impacts tourism location selection, and gastronomic experience influences satisfaction, according to the research. Specifically, tourists show a keen interest in gastronomic experiences after feeling satisfied with the destination and local foods, developing loyalty toward the destination.

Dasatinib self-assembled nanoparticles decorated with hyaluronic acid for targeted treatment of tumors to overcome multidrug resistance.

Multidrug resistance (MDR) and lack of targeting specificity are the main reasons why traditional drug therapies fail and produce toxic side effects in cancer chemotherapy. In order to increase targeting specificity and maximize therapeutic efficacy, new intelligent drug delivery systems are needed. In this study, we prepared the hyaluronic acid (HA) conjugated dasatinib (DAS) and D-α-tocopherol acid polyethylene glycolsuccinate (TPGS) copolymer nanoparticles (THD-NPs). The water solubility of the hydrophobic drug DAS was improved by chemically linking with HA. HA can bind to the over-expressed CD44 protein of tumor cells to increase targeting specificity, TPGS can inhibit the activity of P-glycoprotein (P-gp), and increase the intracellular accumulation of drugs. The prepared drug-loaded nanoparticle has a particle size of 82.23 ± 1.07 nm with good in vitro stability. Our in vitro studies showed that THD-NPs can be released more rapidly in a weakly acidic environment (pH = 5.5) than in a normal physiological environment (pH = 7.4), which can realize the selective release of nanoparticles in tumor cells. Compared to free drugs, THD-NPs showed more efficient cellular uptake, effectively increased the cytotoxic effect of DAS on nasopharyngeal carcinoma HNE1 cells drug resistance HNE1/DDP cells and increased the accumulation of drugs in HNE1/DDP cells, which may be due to the inhibitory effect of TPGS on the efflux function of P-gp. In vivo experiments showed that THD-NPs can effectively inhibit tumor growth without obvious side effects. In conclusion, the targeted and pH-sensitive nanosystem, we designed has great potential to overcome drug resistance and increase therapeutic effects in cancer treatment.

Planar edge Schottky barrier-tunneling transistors using epitaxial graphene/SiC junctions.

A purely planar graphene/SiC field effect transistor is presented here. The horizontal current flow over one-dimensional tunneling barrier between planar graphene contact and coplanar two-dimensional SiC channel exhibits superior on/off ratio compared to conventional transistors employing vertical electron transport. Multilayer epitaxial graphene (MEG) grown on SiC(0001̅) was adopted as the transistor source and drain. The channel is formed by the accumulation layer at the interface of semi-insulating SiC and a surface silicate that forms after high vacuum high temperature annealing. Electronic bands between the graphene edge and SiC accumulation layer form a thin Schottky barrier, which is dominated by tunneling at low temperatures. A thermionic emission prevails over tunneling at high temperatures. We show that neglecting tunneling effectively causes the temperature dependence of the Schottky barrier height. The channel can support current densities up to 35 A/m.

Record maximum oscillation frequency in C-face epitaxial graphene transistors.

The maximum oscillation frequency (fmax) quantifies the practical upper bound for useful circuit operation. We report here an fmax of 70 GHz in transistors using epitaxial graphene grown on the C-face of SiC. This is a significant improvement over Si-face epitaxial graphene used in the prior high-frequency transistor studies, exemplifying the superior electronics potential of C-face epitaxial graphene. Careful transistor design using a high κ dielectric T-gate and self-aligned contacts further contributed to the record-breaking fmax.

Room-temperature metastability of multilayer graphene oxide films.

Graphene oxide potentially has multiple applications. The chemistry of graphene oxide and its response to external stimuli such as temperature and light are not well understood and only approximately controlled. This understanding is crucial to enable future applications of this material. Here, a combined experimental and density functional theory study shows that multilayer graphene oxide produced by oxidizing epitaxial graphene through the Hummers method is a metastable material whose structure and chemistry evolve at room temperature with a characteristic relaxation time of about one month. At the quasi-equilibrium, graphene oxide reaches a nearly stable reduced O/C ratio, and exhibits a structure deprived of epoxide groups and enriched in hydroxyl groups. Our calculations show that the structural and chemical changes are driven by the availability of hydrogen in the oxidized graphitic sheets, which favours the reduction of epoxide groups and the formation of water molecules.

Large area and structured epitaxial graphene produced by confinement controlled sublimation of silicon carbide.

After the pioneering investigations into graphene-based electronics at Georgia Tech, great strides have been made developing epitaxial graphene on silicon carbide (EG) as a new electronic material. EG has not only demonstrated its potential for large scale applications, it also has become an important material for fundamental two-dimensional electron gas physics. It was long known that graphene mono and multilayers grow on SiC crystals at high temperatures in ultrahigh vacuum. At these temperatures, silicon sublimes from the surface and the carbon rich surface layer transforms to graphene. However the quality of the graphene produced in ultrahigh vacuum is poor due to the high sublimation rates at relatively low temperatures. The Georgia Tech team developed growth methods involving encapsulating the SiC crystals in graphite enclosures, thereby sequestering the evaporated silicon and bringing growth process closer to equilibrium. In this confinement controlled sublimation (CCS) process, very high-quality graphene is grown on both polar faces of the SiC crystals. Since 2003, over 50 publications used CCS grown graphene, where it is known as the "furnace grown" graphene. Graphene multilayers grown on the carbon-terminated face of SiC, using the CCS method, were shown to consist of decoupled high mobility graphene layers. The CCS method is now applied on structured silicon carbide surfaces to produce high mobility nano-patterned graphene structures thereby demonstrating that EG is a viable contender for next-generation electronics. Here we present for the first time the CCS method that outperforms other epitaxial graphene production methods.

High-resolution tunnelling spectroscopy of a graphene quartet.

Electrons in a single sheet of graphene behave quite differently from those in traditional two-dimensional electron systems. Like massless relativistic particles, they have linear dispersion and chiral eigenstates. Furthermore, two sets of electrons centred at different points in reciprocal space ('valleys') have this dispersion, giving rise to valley degeneracy. The symmetry between valleys, together with spin symmetry, leads to a fourfold quartet degeneracy of the Landau levels, observed as peaks in the density of states produced by an applied magnetic field. Recent electron transport measurements have observed the lifting of the fourfold degeneracy in very large applied magnetic fields, separating the quartet into integer and, more recently, fractional levels. The exact nature of the broken-symmetry states that form within the Landau levels and lift these degeneracies is unclear at present and is a topic of intense theoretical debate. Here we study the detailed features of the four quantum states that make up a degenerate graphene Landau level. We use high-resolution scanning tunnelling spectroscopy at temperatures as low as 10 mK in an applied magnetic field to study the top layer of multilayer epitaxial graphene. When the Fermi level lies inside the fourfold Landau manifold, significant electron correlation effects result in an enhanced valley splitting for even filling factors, and an enhanced electron spin splitting for odd filling factors. Most unexpectedly, we observe states with Landau level filling factors of 7/2, 9/2 and 11/2, suggestive of new many-body states in graphene.

Nanoscale tunable reduction of graphene oxide for graphene electronics.

The reduced form of graphene oxide (GO) is an attractive alternative to graphene for producing large-scale flexible conductors and for creating devices that require an electronic gap. We report on a means to tune the topographical and electrical properties of reduced GO (rGO) with nanoscopic resolution by local thermal reduction of GO with a heated atomic force microscope tip. The rGO regions are up to four orders of magnitude more conductive than pristine GO. No sign of tip wear or sample tearing was observed. Variably conductive nanoribbons with dimensions down to 12 nanometers could be produced in oxidized epitaxial graphene films in a single step that is clean, rapid, and reliable.