Reusing the tactile knowledge of some previously explored objects helps us to easily recognize the tactual properties of new objects. In this paper, we enable a robotic arm equipped with multi-modal artificial skin, like humans, to actively transfer the prior tactile exploratory action experiences when it learns the detailed physical properties of new objects. These experiences, or prior tactile knowledge, are built by the feature observations that the robot perceives from multiple sensory modalities, when it applies the pressing, sliding, and static contact movements on objects with different action parameters. We call our method Active Prior Tactile Knowledge Transfer (APTKT), and systematically evaluated its performance by several experiments. Results show that the robot improved the discrimination accuracy by around 10% when it used only one training sample plus the feature observations of prior objects. By incorporating the auxiliary features, the transfer learning improved the discrimination accuracy by over 20%. The results also show that the proposed method is robust against transferring irrelevant prior tactile knowledge (negative knowledge transfer).

Recycling information can be complex and often confusing which may subsequently reduce the participations in any waste recycling schemes. As a result, this research explored the roles as well as the importance of a holistic approach in designing recycling information using 15 expert-based in-depth interviews. The rationale was to offer a better understanding of what constitutes waste, recycling, and how recycling information should be designed and presented to make recycling more attractive/convenient. Based on the research participants’ perceptions with supports from the existing studies, this research sub-categorised recycling information into three different themes, termed the “WWW” of recycling information components. As a result, these components (or attributes) were extensively described (using findings of semi-structured interviews) to elicit pragmatic guidance for practitioners, policy-makers, and other stakeholders in designing structured communication or information strategies that may simplify and subsequently increase waste-recycling practices. The policy implications of holistic information in enhancing recycling are further discussed.

Non-invasive, electroencephalography (EEG)-based brain-computer interfaces (BCIs) on motor imagery movements translate the subject’s motor intention into control signals through classifying the EEG patterns caused by different imagination tasks, e.g. hand movements. This type of BCI has been widely studied and used as an alternative mode of communication and environmental control for disabled patients, such as those suffering from a brainstem stroke or a spinal cord injury (SCI). Notwithstanding the success of traditional machine learning methods in classifying EEG signals, these methods still rely on hand-crafted features. The extraction of such features is a difficult task due to the high non-stationarity of EEG signals, which is a major cause for the stagnating progress in classification performance. Remarkable advances in deep learning methods allow end-to-end learning without any feature engineering, which could benefit BCI motor imagery applications. We developed three deep learning models: 1) a long short-term memory (LSTM); 2) a proposed spectrogram-based convolutional neural network model (pCNN); and 3) a recurrent convolutional neural network (RCNN), for decoding motor imagery movements directly from raw EEG signals without (manual) feature engineering. Results were evaluated on our own, publicly available, EEG data collected from 20 subjects and on an existing dataset known as 2b EEG dataset from "BCI Competition IV". Overall, better classification performance was achieved with deep learning models compared to state-of-the art machine learning techniques, which could chart a route ahead for developing new robust techniques for EEG signal decoding. We underpin this point by demonstrating the successful real-time control of a robotic arm using our CNN based BCI.

Intersectional experiences, socio-cultural meanings, ethnic traditions and morals compound stigma-related stress (Jackson et al., 2020; Schmitz 2019). Sex workers are subject to various stigmatizing forces which can lead to secrecy, isolation and lack of social and cultural support (Koken 2012). Stigmatizing forces include structural humanitarian governance and aid interventions that conflate migration and sex work with insidious constraints and coercion. This study explored how migrant female sex workers from distinctive ethnic cultures manage their identity on a day to day basis in relation to the separation of work and home life. Methods: The perspectives of female sex workers were collected via a series of in-depth semi-structured interviews. The inclusion criteria were that the women had worked in sex work for over 18months, defined their involvement in sex work as voluntary, and were over 18yrs of age. The perspectives of seven women from South Asian (Pakistani), Brazilian, and British backgrounds were analyzed using Grounded Theory (Glaser and Strauss, 1967). Ethnicity was considered to explore how the women experienced stigma, how it impacted on the management of their identity, and how the process of change occurred. Results: The women used a variety of methods to maintain work and home life boundaries, processes they used switch into a role and all experienced stigma and tried to deal with it in ways such as concealment from friends and family. Two core categories and properties emerged from the data as participants felt guilt and/or shame but only the South Asian participants spoke of this with reference to their culture and religion. Conclusion: It was not migration per se but rather the relationship of migration to culture that was key to identity management. Participants reflected that as their country was considered collectivist country with interdependent thought, that any negativity felt could not only be reflected on the individual, but also the entire family. For these reasons Pakistani sex workers were subject to more complex stigmatizing forces, shame and guilt as regards risk and exposure. Discussion focusses on the processes and management strategies used to extend social and cultural support.

The first group to build artificial general intelligence or AGI stands to gain a significant strategic and market advantage over competitors, so companies, universities, militaries, and other actors have strong incentives to race to build AGI first. An AGI race would be dangerous, though, because it would prioritize capabilities over safety and increase the risk of existential catastrophe. A self-regulatory organization (SRO) for AGI may be able to change incentives to favor safety over capabilities and encourage cooperation rather than racing.

Using two infectious DNA clones originating from isolates obtained in Kenya, a genetic investigation of maize streak virus (MSV) pathogenicity was carried out. The susceptible Pioneer hybrid 3379 was used to investigate the virulence of kernels administered through vascular puncture inoculation. Mild [pMSV-KL (mild)] and severe [pMSV-Km(severe)] parental infectious MSV DNA clones were linked with considerable changes in the severity of chlorotic streaks and stunting of seedlings. Using restriction endonuclease fragments, chimeric clones were created from parental clones in order to investigate the genetic elements influencing these changes. Restrictions mapping was used to validate clone identities. For genomic portions encoding the replication initiator (Rep and RepA), movement (MP), and coat (CP) protein ORFs as well as for those containing non-coding long (LIR) and short intergenic regions (SIR), putative virulence determinants were discovered. Recombinant clones with intermediate symptoms included LIRs together with the first 189 nt of the Rep/RepA ORFs from the pMSV-Km (Severe) and pMSV-KL (Mild) ORFs. Symptoms identical to those of parental clones were produced by complementary substitution of the Rep/RepA ORF. When compared to pMSV-Km (Severe), the recombinant clone having MP, CP, and SIR genome sequences from pMSV-KL(Mild) and LIR, Rep, and RepA genome sequences from pMSV-Km (Severe) displayed much more severe symptoms and accumulated greater concentrations. The reciprocal clone, in contrast, displayed much milder signs and virus titers than pMSV-KL(Mild). The level of leaf chlorosis and plant stunting were linked with viral accumulation. These findings are consistent with the idea that MSV virulence is a polymorphic feature involving complementary sense genes (LIR and SIR) and the virion.

This paper presents a novel sensor for the detection and characterization of regions of air turbulence that would be of use to improve UAV stability in bad weather. It consists of a combined Schlieren imager and a Radar Acoustic Sounding System (RASS) to produce dual modality “images” of air movement within the measurement volume. The ultrasound modulated Schlieren imager consists of a strobed point light source, parabolic mirror, light-block and camera which are controlled by two laptops. It provides a fine scale projection of the acoustic pulse modulated air turbulence through the measurement volume. The narrow beam 40 kHz/ 17 GHz RASS produces spectra based on Bragg enhanced Doppler radar reflections from the acoustic pulse as it travels. Tests using artificially generated air vortices showed some disruption of the Schlieren image and of the RASS spectrogram. This should allow the higher resolution Schlieren images to identify the turbulence mechanisms that are disrupting the RASS spectra.

This paper presents the perturbation theory for the double–sine–Gordon equation. We obtain a system of differential equations that shows the amplitude and phase modulation of the approximate solution.. In the particular case λ = 0 we get the well-known perturbation theory for the sine–Gordon equation. For a special value λ=-1/8, we derive a phase-locked solution with the same frequency of the linear case. In general we obtain both coherent (solitary waves, lumps and so on) solutions as well as fractal solutions. We can demonstrate the existence of envelope wobbling solitary waves, because of the phase modulation depending on the solution amplitude and on the position. The main conclusion is that it is too reductive focus only on coherent solutions for the double sine-Gordon equation, because of the very rich behavior for the DSG nonlinear equation, including wobbling chaotic and fractal solutions.

Dimethylformamide (DMF), a polar solvent, is commonly used for preparing graphene/epoxy nanocomposites. While commonly previous research has predominantly highlighted the improvement in physio-mechanical properties of these nanocomposites, the effect of DMF on processing and its direct influence on the final characteristics of MXene/epoxy nanocomposites have not been investigated.This unexplored link between DMF dosage, MXene concentrations, and the final composite properties presents an exciting direction for future research. In this study, a fixed dosage of DMF was used with varying MXene concentrations to fabricate the nanocomposites. To assess the reliability of DMF dosage on the characteristics of the fabricated nanocomposites, various evaluation techniques were employed, including dispersion evaluation, mechanical tests, thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), scanning electron microscopy (SEM), electromagnetic interference (EMI) shielding, and surface roughness measurements. The research outcomes revealed that as MXene concentration increased, the characteristics of the MXene/epoxy nanocomposites, improved across the board, indicating their potential for use in energy storage applications.

Injured peripheral nerves regenerate their axons in contrast to those in the central nervous system. However, functional recovery after surgical repair is often disappointing. The basis for the poor recovery is the progressive deterioration with time and distance, of the growth capacity of the neurons that lose their contact with targets (chronic axotomy) and the growth support of the chronically denervated Schwann cells (SC) in the distal nerve stumps. This is despite the retained capacity of chronically denervated and atrophic muscle to accept reinnervation. Progressive decline in regeneration associated genes in both axotomized neurons and denervated SCs accounts for the decline in regenerative success in association with silencing of neural activity in sensory neurons due to their disconnection from their sense organs and, in motoneurons due to loss of their synaptic contacts in the spinal cord. Whilst exogenous neurotrophic factors promote nerve regeneration, the profuse axonal outgrowth and difficulties in delivery are avoided by promoting their endogenous expression with brief (1 hour) low frequency (20Hz) electrical stimulation (ES) proximal to the injury site. ES accelerates axon outgrowth and in turn, target reinnervation in both animals and human subjects. Applying ES to intact nerve days prior to nerve injury, conditional ES (CES) increases axonal outgrowth and regeneration rate with the potential for application in nerve transfer surgeries and end-to-side neurorrhaphies. However, the additional surgery for applying CES electrodes may be a hurdle. ES is applicable in all surgeries with excellent outcomes.

Physicists have employed various approaches to solve the “paradox” and offered a consistent conclusion that the traveller twin is younger than the homebody twin. However, some authors attribute the cause of differential aging to acceleration, while others believe that acceleration should not be regarded as the source of differential aging, but frame switch is. So far there is no agreement on this issue. Actually, acceleration and frame switch should not be regarded as the source of differential aging. The author will introduce a thought experiment in which two very long spacecraft are moving in opposite directions at a speed close to the speed of light to discuss the real cause of differential aging. The author found that the real cause of differential aging in the twin “paradox” is because of the asymmetry of destination choice. People always choose their destinations in the universe rather than in spacecraft. The destinations are always stationary relative to the homebody twin and moving relative to the traveller twin. Once we choose a destination in a reference frame, the distance is the proper length in this reference frame, but the distance will contract in another moving reference frame, thus the recording time will be shorter.

Burn injury serves as an example of a condition with a robust inflammatory response. The elevation of circulating interleukins (IL)- 1 beta and -6 in children with severe burn injury up-regulate the parathyroid calcium sensing receptor (CaSR) resulting in hypocalcemic hypoparathyroidism with urinary calcium wasting. This effect protects the body from the hypercalcemia resulting from bone resorption liberating calcium into the circulation. Extracellular calcium can exacerbate and prolong the inflammatory response by stimulating mononuclear cell chemokine production as well as the NLRP3 inflammasome of the innate immune system, resulting in increased IL-1 production by monocytes and macrophages. Interestingly, the CaSR response to inflammatory cytokines disappears with age, potentially trapping calcium from bone resorption in the circulation and allowing it to contribute to increased inflammation and possibly increased calcium deposition in small arteries, , such as the coronaries, as conditions with increased chronic inflammation, such as spinal cord injury, osteoarthritis and rheumatoid arthritis have an incidence of cardiovascular disease and coronary artery calcium deposition significantly higher than the unaffected age-matched population.

The article presents the results of tests related to failure analysis and finding ways to diagnose used semiconductor elements, among other, in power electronics converter systems on vessels and offshore facilities (drilling and production rigs, wind turbines). Diagnostic relationships were found between the temperature change in the above systems and the signals generated in form of elastic waves of acoustic emission.

The concept of a ‘just transition’ encompasses political and policy imperatives to minimise the harmful impacts of industrial and economic transitions on workers, communities and society more generally, and to maximise their potential benefits. This imperative has gained heightened importance as governments commit to reducing greenhouse gas emissions. A wide range of policies strategies and initiatives have been adopted by national and regional governments to facilitate and help manage a just transition. It is a concept that is increasingly being put into practice. This scoping study identifies and compares strategies, policies and practices that are presently being implemented in order to manage a just transition across 25 countries and 74 regions alongside European Union-level policies. This work develops a typology of policy instruments to manage just transitions and identifies implementation gaps and leading practices.

Aluminum wire is a common material for wire bonding due to its resistance to oxidation and low price. It does not melt when becoming a free air ball (FAB) during the electronic flame-off (EFO) process with wettability, and is applied by wedge bonding. This study used 20μm Zn-Coated Al-0.5wt.%Si (ZAS) wires to improve the FAB shape after the EFO process, while maintaining stability of the mechanical properties, including the interface bonding strength and hardness. In order to test circuit stability after ball bonding, the current-tensile test was performed. During the experiment, it was found that 80nm ZAS with wire bonding has lower resistance and higher fusing current. For the bias tensile test, the thicker Zn film diffused into the Al-Si matrix easily, after which the strength was reduced. The ball-bond interfaces had no change in their condition before and after the bias. Accordingly, ZAS could be a promising candidate for ball bonding in the future.

Head and neck squamous cell carcinoma (HNSCC) takes the sixth place among the most common cancers in the world. Abnormal methylation can be one of the reasons for this cancer. The aim of this study was to investigate the DNA promotor methylation status of cancer-associated genes (ATM, APC, CDO1, RB1, TP53, WIF1) in patients with HNSCC. Bisulfite Conversion and Methylation-Sensitive High-Resolution Melting was used for analysis of the DNA methylation level of normal and tumor tissues in 44 patients. There were significant differences in DNA methylation level between patient’s tumor and normal tissues for CDO1 and WIF1 genes in all subjects and subgroups (p<0.05). In T3 subgroup there was significant correlation between CDO1 gene methylation and age in the normal tissue. The same correlation was detected also for the WIF1 gene methylation in tumor tissue samples in the subgroup with T3 and in normal tissue samples in the subgroup with T4 (p<0,05). In all genes no significant differences were found between the subgroups (T2, T3, T4 stage, primary/recurrent lesion, non-keratinizing/keratinizing SCC, age before/ after 50, smokers/non-smokers) of the patients. Thus, changes in the expression of the CDO1 and WIF1 genes can affect mechanisms of the occurrence and development of HNSCC.

The purpose of this study is to assess the concentration-response relations between conjunctivitis and exposure to ambient ozone. This retrospective study includes emergency department (ED) visits for conjunctivitis in Edmonton, Canada, for the period April 1992–March 2002. Daily average levels of ozone (range: 1.2–50.9, ppb), of temperature, and of relative humidity were estimated and used for the period of the study. For each of the considered exposure lags, (from 0 to 9 days), six different models were fitted to estimate the concentration-response function. The goodness of fit was assessed using the Akaike information criterion. During the period of the study, 17,211 ED visits for conjunctivitis were recorded and used. For all subjects together, a positive statistically significant association was obtained for the exposure lagged by 5 days. For female subjects, lags 1, 3, and 9 had positive statistically significant associations (lag 2 had negative associations). For male subjects, only lag 5 had a positive statistically significant association. The estimated non-linear concentration-response functions for the considered groups (all, males, females) and lags, revealed the associations along the exposure levels. The fitted shapes are described by algebraic functions and may have various forms. The estimated functions are useful to determine the risk associated with exposure to ground-level ozone.

Autonomous image recognition has numerous potential applications in the field of planetary science and geology. For instance, having the ability to classify images of rocks would allow geologists to have immediate feedback without having to bring back samples to the laboratory. Also, planetary rovers could classify rocks in remote places and even in other planets without needing human intervention. Shu et al. classified 9 different types of rock images using a Support Vector Machine (SVM) with the image features extracted autonomously. Through this method, the authors achieved a test accuracy of 96.71%. In this research, Convolutional Neural Networks(CNN) have been used to classify the same set of rock images. Results show that a 3-layer network obtains an average accuracy of 99.60% across 10 trials on the test set. A version of Self-taught Learning was also implemented to prove the generalizability of the features extracted by the CNN. Finally, one model has been chosen to be deployed on a mobile device to demonstrate practicality and portability. The deployed model achieves a perfect classification accuracy on the test set, while taking only 0.068 seconds to make a prediction, equivalent to about 14 frames per second.

Protected areas, such as natural World Heritage sites, RAMSAR wetlands, and Biosphere reserves are ecosystems within landscapes. Each site meets certain criteria that allow it to qualify as heritage or protected. Both climate change and human influence (e.g., incursion, increased tourist visitation) are altering biophysical conditions at many such sites. As a result, conditions at many sites are falling outside the criteria for their original designation. The alternatives are to change the criteria, remove protection from the site, change site boundaries such that the larger or smaller landscape meets the criteria, or manage the existing landscape in some way that reduces the threat. This paper argues for adaptive heritage, an approach that explicitly recognizes changing conditions. We discuss the need to view heritage areas as parts of a larger landscape, and to take an adaptive approach to management of that landscape. We offer five themes of adaptive heritage: 1) treat sites as living heritage, 2) employ innovative governance, 3) embrace transparency and accountability, 4) invest in monitoring and evaluation, and 5) manage adaptively. We offer the Australian Wet Tropics as an example where aspects of adaptive heritage currently are practiced, highlighting the tools being used. This paper offers guidance supporting decisions about natural heritage in the face of climate change and non-climatic pressures. Rather than delisting or lowering standards, we argue for adaptive approaches.

An effective empirical statistical method is developed to improve the process of mineral resource estimation of seabed polymetallic nodules and is applied to analyse the abundance of seabed polymetallic nodules in the Clarion Clipperton Zone (CCZ). The newly proposed method is based on three hypotheses as the foundation for a model of “Idealized Nodules”, which was validated by analysing nodule samples collected from the seabed within the Tonga Offshore Mining Limited (TOML) exploration contract. Once validated, the “Idealized Nodule” model was used to deduce a set of empirical formulae for predicting the nodule resources, in terms of Percentage Coverage and Abundance. The formulae were then applied to analysing a total of 188 sets of nodule samples collected across the TOML areas, comprising box-core samples and towed camera images collected by one of the authors and detailed in [4]. The analysis also relies upon detailed box-core sample measurements from other areas reported by [7]. Numerical results for resource prediction were compared with field measurements, and reasonable agreement has been achieved. The new method has the potential to achieve more accurate mineral resource estimation with reduced sample numbers and sizes. They may also have application in improving the efficiency of design and configuration of mining equipment.

In this work, we investigate the behaviour of relativistic quantum oscillator under the effects of Lorentz symmetry violation determined by a tensor $(K_F)_{\mu\nu\alpha\beta}$ out of the Standard Model Extension. We analyze this relativistic system under an inverse radial electric field and a constant magnetic field induced by Lorentz symmetry violation. We see that the presence of Lorentz symmetry breaking terms modified the energy spectrum of the system, and a quantum effect arise due to the dependence of the linear charge density on the quantum numbers of the system

In order to make full use of the complementarity of existing navigation systems to improve the navigation and positioning accuracy, this paper investigates the visual/INS integrated navigation system based on the factor graph optimization (FGO) algorithm. In the traditional visual/INS integrated navigation system, there is often the problem of image blurring due to the rapid change of light and shadow captured by the vision sensor and the attitude change of the carrier, which leads to the decrease of the positioning accuracy of the combined navigation system. Therefore, this paper firstly introduces Retinex algorithm and BID algorithm to carry out the design of image de-blurring method; then implements the visual/INS integrated navigation algorithm based on the factor graph optimization method; finally, the experimental scheme is designed, comparative experiments are carried out, and the researched method is verified by using the public dataset. The experimental results show that the combined navigation algorithm realized in this paper has high accuracy, and its positioning accuracy is improved by 40% compared with visual positioning.

Taiwan developing offshore wind power to promote green energy and self-electricity production. In this study, a Light Detection and Ranging (Lidar) was set up at Chang-Hua development zone one on the sea and 10km away from the seashore. At Lidar location, WRF (3.33km & 2km grid lengths) model and WAsP were used to simulate the wind speed at various elevations. Three days mean wind speed of simulated results were compared with Lidar data. From the four wind data sets, developed five different comparisons to find an error% and R-Squared values. Comparison between WAsP and Floating Lidar was shown good consistency. Lukang meteorological station 10 years wind observations at 5m height were used for wind farm energy predictions. The yearly variation of energy predictions of traditional and TGC wind farm layouts are compared under purely neutral and stable condition. The one-year cycle average surface heat flux over the Taiwan Strait is negative (-72.5 (W/m2) and 157.13 STD), which represents stable condition. At stable condition TGC (92.39%) and 600(92.44%), wind farms were shown higher efficiency. The Fuhai met mast wind data was used to estimate roughness length and power law exponent. The average roughness lengths are very small and unstable atmosphere.

Phylogenomic analyses have revolutionized the study of biodiversity, but they have revealed that estimated tree topologies can depend, at least in part, on the subset of the genome that is analyzed. For example, estimates of trees for avian orders differ if protein coding or non-coding data are analyzed. The bird tree is a good study system because the historical signal for relationships among orders is very weak, which should permit subtle non-historical signals to be identified, while monophyly of orders is strongly corroborated, allowing identification of strong non-historical signals. Hydrophobic amino acids in mitochondrially-encoded proteins, which are expected to be found in transmembrane helices, have been hypothesized to be associated with non-historical signals. We tested this hypothesis by comparing the evolution of transmembrane helices and extramembrane segments of mitochondrial proteins from 420 bird species, sampled from most avian orders. We estimated amino acids exchangeabilities for both structural environments and assessed the performance of phylogenetic analysis using each data type. We compared those relative exchangeabilities with values calculated using a substitution dataset for transmembrane helices from a variety of sampled set of nuclear- and mitochondrially-encoded proteins, allowing us to compare the bird-specific mitochondrial models with a general model of transmembrane protein evolution. To complement our amino acid analyses, we examined the impact of protein structure on patterns of nucleotide evolution. Models of transmembrane and extramembrane sequence evolution for amino acids and nucleotides exhibited striking differences, but there was no evidence for strong topological data type effects. However, incorporating protein structure into analyses of mitochondrially-encoded proteins improved model fit. Thus, we believe that considering protein structure will improve analyses of mitogenomic data, both in birds and in other taxa.

Given the opportunities offered by foreign investment in energy infrastructure mostly by Chinese firms, the Government of Cambodia is giving high priority to developing hydropower resources for reducing energy poverty and powering economic growth. Using a “Political ecology of the Asian drivers” framework, this paper assesses China’s involvement in the development of large dams’ in Cambodia and its impacts on the access of natural resources such as water and energy by dam builders, local communities and the government. This analysis is based on 61 interviews and 10 focus group discussions with affected communities, institutional actors, Chinese dam builders and financiers in relation to the first large Chinese dam built in Cambodia, the Kamchay dam. Based on the results of the analysis this paper makes recommendations on how to improve the planning, implementation and governance of large dams to ensure that the dams’ benefits are shared more equally.

In the present study, we derive a new B-spline technique namely trigonometric B-spline collocation algorithm to solve some initial boundary value problems for the nonlinear Klein-Gordon equation. In order to carry out the time integration with Crank-Nicolson implicit method, the order of the equation is reduced to give a coupled system of nonlinear partial differential equations. The collocation approximation based on trigonometric cubic B-splines for spatial discretization is followed by the linearization of the nonlinear term. The efficiency and accuracy of the present method are validated by measuring the error between the numerical and analytical solutions when exist. The conservation laws representing momentum and energy are also computed for all problems.

Population based studies have associated poor living conditions with the persistent disparity in the health of Aboriginal and non-Aboriginal Australians. This project assesses the applicability of the Health Community Assessment Tool and its role in improving the environment of a small community in the Midwest of WA. The action research cycles started with the initial reflection on the suitability of the HCAT version 2 for the local community context and whether it was fit-for-purpose. The researcher provided ‘critical companionship’, while the participants of the study were invited to be co-researchers (the Assessors) who critically examined the HCAT and assess the community. The relevant domains to the serviced town (an outer regional community) were pest control and animal management; healthy housing; food supply; community vibrancy, pride and safety; reducing environmental tobacco smoke; and promoting physical activity. The Assessors found the HCAT descriptors mostly aligned with their community context but found some of the items difficult to apply. Based on participant’s suggestions, some of the original scoring scales were reformatted. School attendance and illicit drug use were identified as a key outcome indicator for youth but were missing from the HCAT. The HCAT domains applied helped streamlining core business of agencies in the local community. The face validity of HCAT items were confirmed in this research with minor adjustments to reflect local context. Youth engagement to education is of high community concern and the development of an item would create similar interagency collaborative dialogues.

On 17 October 1947, Niels Bohr was made a knight of the Order of the Elephant by the King of Denmark in view of his outstanding achievements and contributions to science. Bohr designed his own coat of arms that featured a pattern of Yin and Yang (Tai Chi symbol) to symbolize the wave-particle complementarity. However, Bohr’s Yin-Yang diagram (YYD) was neither drawn based on the principles of quantum mechanics, nor did it originate from the traditional Taoist YYD. Scientists still have doubts about the legitimacy of using YYD as the icon of the wave-particle complementarity, because the YYD belonging to quantum mechanics itself is unknown so far. This article reports the YYDs existing in quantum mechanics and justifies the role of YYD in the wave-particle duality by showing that any system, whether classical or quantum, has an ideal YYD as long as it satisfies Bohr’s principle of complementarity (BPC). The deviation of a deformed YYD from the ideal YYD indicates the extent to which a real system satisfies BPC. This article constructs the quantum YYD by the complex quantum trajectory of a particle tunneling via a step barrier, which displays the continuous transition between the wave behavior and the particle behavior. It appears that the YYD designed by Bohr in his coat of arms resembles the YYD generated by tunneling motion, not only in appearance but also in the governing equation.

The black hole (BH) phenomenon is an intraluminal restenotic lesion. It was identified by intravascular ultrasound (IVUS) and optical coherence tomography (OCT) after intracoronary brachytherapy and drug-eluting stent implantation. Despite the similarity in the mode of action of brachytherapy and drug-eluting stent implantation, the BH phenomenon appears to be uncommon after drug-eluting stent implantation. Specifically, the BH phenomenon is better identified by OCT than by IVUS. Herein, we present a case of in-stent restenosis with suspected BH phenomenon on IVUS confirmed by OCT.

Focal cartilage defects are a prevalent knee problem affecting people of all ages. Due to its avascular nature, cartilage has limited self-repair capacity, and osteochondral defects can lead to pain and long-term complications such as osteoarthritis. Autologous chondrocyte implantation (ACI) has been a successful surgical approach for repairing osteochondral defects over the past two decades. However, a major drawback of ACI is the de-differentiation of chondrocytes during their in vitro expansion. In this study, we isolated ovine chondrocytes and cultured them in a two-dimensional environment as for ACI procedures. We hypothesised that the 3D scaffolds would support the cells re-differentiation without the need for growth factors and so we encapsulated them into soft collagen and alginate (col/alg) hydrogels. Chondrocytes embedded into hydrogels were viable and proliferated. After 7 days they acquired a rounded morphology and started to aggregate. Gene expression studies showed that the genes associated with chondrogenesis started to be up regulated as early as day one. At 21 days chondrocytes had extensively colonized the hydrogel, forming large cell clusters and started to deposit collagen II and aggrecan with limited collagen type I deposition. These findings highlight the potential of soft col/alg hydrogels to enhance ACI outcomes by creating a favourable microenvironment for chondrocyte reprogramming and re-differentiation, eliminating the dependency on growth factors.

The environmental legacy of post-closure mine sites poses a significant risk to the sustainability of mining operations and natural resource development. This study aims to advance the understanding of sustainable mine site reclamation behavior in Canada by using multi-temporal Landsat satellite images to examine the long-term land cover changes at post-closure mine sites. Six representative post-closure mine sites were selected for the evaluation and comparison. The Normalized Difference Vegetation Index (NDVI) analysis, Landsat image classification, post-classification change detection, and Regrowth Index (RI) analysis were conducted to assess the speed and extent of landscape and vegetation recovery at the target mine sites. A significant vegetation recovery was quantified for the mine sites that have experienced active reclamation activities. In contrast, the post-closure mine area undergoing only the passive revegetation typically demonstrated a slow and minor increase in vegetation over time. The actively revegetated mine sites can typically be restored to a level that equals or better than the pre-mining situation. This work confirms that active reclamation and revegetation at post-closure mine sites is critically important in sustainable mining. The quantified mine site reclamation behavior and the relevant sustainable practices would be useful for evidence-based sustainable resource management in Canada.

Estimating plume cloud height is essential for various applications, such as global climate models. Smokestack plume rise is the constant height at which the plume cloud is carried downwind as its momentum dissipates and the plume cloud and the ambient temperatures equalize. Although different parameterizations are used in most air-quality models to predict the plume rise, they have been unable to estimate it properly. This paper proposes a novel framework to monitor smokestack plume clouds and make long-term, real-time measurements of the plume rise. For this purpose, a three-stage framework is developed based on Deep Convolutional Neural Networks (DCNNs). In the first stage, an improved Mask R-CNN, called Deep Plume Rise Network (DPRNet), is applied to recognize the plume cloud. Then, image processing analysis and least squares theory are respectively used to detect the plume cloud’s boundaries and fit an asymptotic model into their centerlines. The y-component coordinate of this model’s critical point is considered the plume rise. In the last stage, a geometric transformation phase converts image measurements into real-life ones. A wide range of images with different atmospheric conditions, including day, night, and cloudy/foggy, have been selected for the DPRNet training algorithm. Obtained results show that the proposed method outperforms widely-used networks in smoke border detection and recognition.

Electroencephalography (EEG) is a crucial tool in cognitive neuroscience, enabling the study of neurophysiological function by measuring the brain's electrical activity. Its applications are included perception, learning, memory, language, decision-making and neural network mapping. Recently, interest has surged in extending EEG measurements to domestic environments. However, the high costs associated with traditional laboratory EEG systems have hindered accessibility for many individuals and researchers in education, research, and medicine. To tackle this, a mobile-EEG device named "DreamMachine” was developed. A more affordable alternative to both lab-based EEG systems and existing mobile-EEG devices. This system boasts 24-channels, 24-bit resolution, up to 6 hours of battery life, portability and a low price. Our open-source and open-hardware approach empowers cognitive neuroscience, especially in education, learning, and research, opening doors to more accessibility. This paper introduces the DreamMachine's design and compares it with the lab-based EEG system "asalabTM" in an eyes-open and eyes-closed experiment. The Alpha band exhibited higher power in the power spectrum during eyes-closed conditions, whereas the eyes-open condition showed increased power specifically within the Delta frequency range. Our analysis confirms that the DreamMachine accurately records brain activity, meeting the necessary standards when compared to the asalabTM system.

In Taiwan, mountainous areas account for approximately two-thirds of the total area. The steep terrain and concentrated rainfall during typhoons cause landslides, which pose a considerable threat to mountain settlements. Therefore, models for analyzing rainfall-induced landslide hazards are urgently required to ensure adequate land use in mountainous areas. In this study, focusing on Pingtung County in southern Taiwan, we developed a landslide hazard index (IRL) to land use. Using FORMOSA-2 and SPOT-5 satellite images, data were collected before and after four typhoons (one in 2009 and three in 2013). The ArcGIS random tree classifier was used for interpreting satellite images to explore surface changes and disasters, which were used to analyze slope disturbances. The product of the maximum 3-h rolling rainfall intensity and effective accumulated rainfall was used as a rainfall trigger index (IRT). Considering environmental and slope disturbance factors, an index of slope environmental strength potential (ISESP) was developed through logistic regression (LR). Landslide hazard to land use was estimated using IRT and ISESP. The average coefficient of agreement (Kappa) was approximately 0.71 (medium to high accuracy); the overall accuracy of slope environmental strength potential analysis was approximately 80.4%. At a constant ISESP, IRT increased with the increasing hazard potential of rainfall-induced landslides. Furthermore, IRT and ISESP were positively correlated with landslide occurrence. When large ISESP values occur (e.g., fragile environment and high land development intensity), small IRT values may induce landslides.

Climate change impacts threaten sustainable development efforts. The magnitude of the impacts, however, varies with socio-ecological characteristics of locations. This is the reason there is con-sensus on the necessity for climate change adaptive capacity building that is country driven, based on and responsive to local needs. However, information on context specific capacity building needs in developing countries is not readily available. The objective of this study was to establish location specific awareness, training, educational, research and technology capacity building needs for climate change adaptation among small-holder farmers in Uganda. Structured interviews were undertaken with 465 households from five agro-ecological zones selected based on the level of vulnerability of agricultural systems to the main climate variation and change hazards. Results reveal substantial capacity building needs in all the zones. Majority of the farmers needed capacity building for interventions on soil water conservation practices for adapting to drought and un-predictable rainfall. For all zones, education, research, and technology were perceived as key needs. However, the needs varied among zones. These results demonstrate the importance of context specificity in adaptation efforts. The study provides agro-ecological and social system specific in-formation for climate change adaptation planning and policy interventions for effective capacity building

The 2030 Agenda for Sustainable Development, the SDGs, are high on the agenda for most countries of the world. In its publication of the SDGs, the UN has provided the goals and target descriptions that, if implemented at a country level, would lead towards a sustainable future. The IAEG (InterAgency Expert Group of the SDGs) was tasked with disseminating indicators and methods to countries that can be used to gather data describing the global progress towards sustainability. However 2030 Agenda leaves it to countries to adopt the targets with each government setting its own national targets guided by the global level of ambition but taking into account national circumstances. At present, guidance on how to go about this is scant, but it is clear that the responsibility is with countries to implement and that it is actions at a country level that will determine the success of the SDGs. SDG reporting by countries takes on two forms 1) global reporting using prescribed indicator methods and data; 2) National Voluntary Reviews where a country reports on its own progress in more detail but is also able to present data that are more appropriate for the country. For the latter, countries need to be able to adapt the global indicators to fit national priorities and context, thus the global description of an indicator could be reduced to describe only what is relevant to the country. Countries may also, for the National Voluntary Review, use indicators that are unique to the country but nevertheless contribute to measurement of progress towards the global SDG target. Importantly, for those indicators that relate to the security of natural resources security (e.g. water) indicators, there are no prescribed numerical targets/standards or benchmarks. Rather countries will need to set their own benchmarks or standards against which performance can be evaluated. This paper presents a procedure that would enable a country to describe national targets with associated benchmarks that are appropriate for the country. The procedure focusses on those SDG targets that are natural resource-security focussed e.g. extent of water-related ecosystems (6.6), desertification (15.3) etc., because the selection of indicator methods and benchmarks is based on the location of natural resources, their use and present state and how they fit into national strategies.

The Range–Doppler (R-D) model is extensively employed for the geometric processing of Synthetic Aperture Radar (SAR) images. Refining the sensor motion state and imaging parameters is the most common method for achieving high-precision geometric processing using the R-D model, comprising a process that involves numerous parameters and complex computations. In this study, we introduce a novel approach to improve the positioning accuracy of the R-D model, implementing a low-order polynomial to compensate for the original imaging errors without altering the initial positioning parameters. We also design low-order polynomial compensation models with different parameters. The models are evaluated on various SAR images from different platforms and bands, including spaceborne TerraSAR-X and GF3-C images, manned airborne SAR-X images, and unmanned aerial vehicle-mounted miniSAR-Ku images. Furthermore, image positioning experiments involving the use of different polynomial compensation models and various numbers and distributions of Ground Control Points (GCPs) are conducted. The experimental results demonstrate that geometric processing accuracy comparable to that of the classical rigorous positioning method can be achieved even when applying only an affine transformation model to the images. Compared to classical refinement models, however, the proposed image-compensated R-D model is much simpler and easy to implement. Thus, this study provides a convenient, robust, and widely applicable method for the geometric positioning processing of SAR images, offering a potential approach for the joint-positioning processing of multi-source SAR images.

An expansion method based on time fractional Sine-Gordon equation is implemented to construct some real and complex valued exact solutions to the Korteweg-de Vries and modified Korteweg-de Vries equation in time fractional forms. Compatible fractional traveling wave transform plays a key role to be able to apply homogeneous balance technique to set the predicted solution. The relation between trigonometric and hyperbolic functions based on fractional Sine-Gordon equation allows to form the exact solutions with multiplication of powers of hyperbolic functions.

In this paper, the functional variable method is used to establish solitary wave solutions and periodic wave solutions of the loaded quadratic non-linear Klein-Gordon equation, the loaded cubic non-linear Klein-Gordon equation and the loaded coupled non-linear Klein-Gordon equation. All solutions of these equations have been examined and three dimensional graphics of the obtained solutions have been drawn by using the Matlab software. The main advantage of the proposed functional variable method over other methods is that it provides more new exact traveling wave solutions along with additional free parameters. The graphical representations of the soliton solutions and the periodic wave solutions by using distinct values of random parameter are demonstrated to better understand their physical features. The exact solutions have its great importance to reveal the internal mechanism of the physical phenomena.

The Sine-Gordon expansion method is implemented to construct exact solutions some conformable time fractional equations in Regularized Long Wave(RLW)-class. Compatible wave transform reduces the governing equation to classical ordinary differential equation. The homogeneous balance procedure gives the order of the predicted polynomial-type solution that is inspired from well-known Sine-Gordon equation. The substitution of this solution follows the previous step. Equating the coefficients of the powers of predicted solution leads a system of algebraic equations. The solution of resultant system for coefficients gives the necessary relations among the parameters and the coefficients to be able construct the solutions. Some solutions are simulated for some particular choices of parameters.

Geopolitical situations, such as the Ukraine–Russia war, the Israel–Hamas war, and pandemics, can disrupt supply chains, such as the rerouting of oil tankers via South Africa to avoid the impact of the Israel–Hamas conflict. These events will probably occur again, but they are black swan events and difficult to predict. How can firms manage these events to minimise disruption to their supply chains? This paper proposes that a blockchain architecture has the potential to build resilience in supply chains and give them the flexibility to withstand the challenges of black swan events. The decentralisation ability of blockchain technology enables separation of the discrete elements of a sustainable supply chain so contagion does not impact the overall sustainable supply chain. To achieve flexibility in a sustainable supply chain ecosystem requires governance, leadership, and management. Also, artificial intelligence (AI), in conjunction with blockchain, is a technology that can enhance the flexibility and resilience of the supply chain. Thus, AI can act as a controller, co-ordinator, and an integrator in sustainable supply chain systems.

High-density polyethylene (HDPE) waste poses a significant environmental challenge due to its non-biodegradable nature and the vast quantities generated annually. However, conventional recycling methods are energy-intensive and often yield low-quality products. Herein, HDPE waste is upcycled into anti-aging superhydrophobic thin films suitable for outdoor applications. A two-layer spin-casting method combined with heating-induced crosslinking is utilized to produce an exceptionally rough superhydrophobic surface, featuring a root mean square (RMS) roughness of 50 nm, an average crest height of 222 nm, an average trough depth of –264 nm, and a contact angle (CA) of 148°. To assess durability, weathering tests were conducted, revealing the films' susceptibility to degradation under harsh conditions. The films' resistance to environmental factors is improved by incorporating a UV absorber, maintaining their hydrophobic properties and mechanical strength. Our research demonstrates a sustainable method for upcycling waste into high-performance, weather-resistant superhydrophobic films.

The Dirac and Klein-Gordon equations have proven to be some of the most accurate theories for describing particle behaviour and have laid the foundations of Relatavistic Quantum Mechanics. We extend the formulations to consider a 5 Dimensional spacetime with two time dimensions (as first conceptualised by Sajjad Zahir) and extend the notions to Quantum Field Theory to arrive at the behaviour of particles through the Dirac and Klein-Gordon counterparts of the 5 Dimensional spacetime. The implications of this to anti-matter are discussed.

To contain and mitigate the coronavirus (COVID-19) pandemic, African governments have implemented non-pharmacological interventions (NPIs), such as imposing travel bans, confining people to their homes and closing schools, shops and workplaces. These NPIs are likely to be less effective in circumstances where people need to leave their homes to work, collect food, water and cooking fuel or where people cannot maintain distancing due to overcrowded living environments. Using data from the nationally representative South African General Household Survey 2019, we examined individuals’ vulnerability to the risk of COVID-19 infection due to their health, socioeconomic and living circumstances. We explored socioeconomic-related inequalities in COVID-19 using concentration curve and concentration index methods. Our results showed that vulnerability to COVID-19 was disproportionately concentrated among those with low socioeconomic status. Using the Recentered Influence Function decomposition approach, we found that higher income and education had a significant and positive impact on reducing socioeconomic-related COVID-19 vulnerability. Conversely, people with lower socioeconomic status were more likely to live in circumstances that made compliance with NPI requirements almost impossible, and they were also more likely to have pre-existing health conditions that made them more vulnerable to COVID-19.

The fluorine-less noble-gas containing anions OBONgO- and OCNNgO-have been studied by correlated electronic structure calculation and density functional theory. The obtained energetics indicates that for Ng = Kr and Xe, these anions should be kinetically stable at low temperature. The molecular structures and electron density distribution suggests that these anions are stabilized by ion-induced dipole interactions with charges concentrated on the electronegative OBO and OCN groups. The current study shows that in additional to the fluoride ion, polyatomic groups with strong electronic affinities can also form stable noble-gas containing anions of the type X-...NgO.

Introduction: Treating elbow fracture-dislocation is a challenge, especially in the situation of basal-coronoid trans-ulnar fracture. The study ams to explain whether or not the minimal invasive surgery (MIS) would be feasible in elbow dislocation with coronoid fracture. Materials & Methods: At Taipei Veterans General Hospital, patients who had elbow dislocations with coronoid process fractures underwent single one surgeon’s MIS techniques which included the fluoroscopy-guided ulnar anteromedial (FGUAM) approach in the stage of reducing coronoid process. When there is a proximal ulnar fracture, the posterior incision should be necessary, followed by the incision over the lateral or medial elbow in treating radial fractures or ligament injuries. Results: The Flow Diagram about approach recommendation was established in base of defining MIS as not to do cross-plane dissection. Anteriorly rigid fixation for the coronoid process was also emphasized. Conclusions: MIS can be achieved by multiple limited surgical incisions. However, if there is an unstable ulnar metaphysis or ligament avulsion fracture, the posterior approach has to be extended and the so-called MIS fails to be established.

Desalination accounts for 1% of the total global water consumption and is an energy-intensive process, with the majority of operational expenses attributed to energy consumption. Moreover, at present, a significant portion of the power comes from traditional fossil fuel-fired power plants and the greenhouse gas emissions associated with power production along with concentrated brine discharge from the process, pose a severe threat to the environment. Due to the dramatic impact of climate change, there is a major opportunity to develop sustainable desalination processes to combat the issues of brine discharge, greenhouse gas emissions along with a reduction in energy consumption per unit of freshwater produced. Nanotechnology can play a vital role to achieve specific energy consumption reduction as nanofluids application increases the overall heat transfer coefficient enabling the production of more water for the same size desalination plant. Furthermore, concentrated brine discharge harms the marine ecosystems, and hence, this problem must also be solved to support the objective of sustainable desalination. Several studies have been carried out in the past several years in the field of nanotechnology applications for desalination, brine treatment and the role of renewable energy in desalination. This paper aims to review the major advances in this field of nanotechnology for desalination. Furthermore, a hypothesis for developing an integrated solar thermal and nanofluid sustainable desalination system, based on the cyclic economy model is proposed.

Contaminants of Emerging Concern (CECs), a new category of contaminants in limelight, is a major issue of global concern. The pervasive nature of CECs and its harmful effects, such as cancer, reproductive disorders, neurotoxicity etc., make the situation alarming. The perilous nature of CECs lies in the fact that even very small concentration of CECs can cause great impacts on living beings. It also has a nature of bioaccumulation. Thus, it is the ultimate need to have efficient sensors for detection of CECs to ensure safe living environment. Electrochemical sensors are an efficient platform for CEC detection as they are highly selective, sensitive, stable, reproducible, and prompt, and can detect very low concentrations of analyte. Major classes of CECs are pharmaceuticals, illicit drugs, personal care products, endocrine disruptors, newly registered pesticides, and disinfection by-products. This review focusses on CECs, including their sources and pathways, health effects caused by them, and electrochemical sensors as reported in literatures under each category for the detection of major CECs.

Scaffoldings play a critical role as temporary structures in supporting construction processes. Accidents at construction sites frequently stem from issues related to scaffoldings, including insufficient support caused by deviations from the construction design, insecure rod connections, or absence of cross bracing, which result in uneven loading and potential collapse, leading to casualties. In this study, we introduce a deep-learning-based, augmented reality (AR)-enabled system called scaffolding assembly deficiency detection system (SADDS) to assist field inspectors in identifying deficiencies in scaffolding assemblies. Inspectors have the flexibility to utilize SADDS through various devices, such as video cameras, mobile phones, or AR goggles (i.e., Microsoft HoloLens 2), for automated detection of deficiencies in scaffolding assemblies. The training test yielded satisfactory results, with a mean average precision of 0.89 and individual precision values of 0.96, 0.82, 0.90, and 0.89 for “qualified” frames and frames with the “missing cross-tie rod,” “missing lower-tie rod,” and “missing footboard” deficiencies, respectively. Field tests conducted at two construction sites demonstrated improved system performance compared to that in the training test. However, these field tests also revealed certain limitations of the SADDS system.

GaN ultraviolet photodetector with metal-semiconductor-metal structure is achieved by growing on a periodic trapezoid column-shape patterned sapphire substrate using metalorganic chemical vapor deposition. Under 5-V reverse bias, the photodetector fabricated on such patterned sapphire substrate exhibits a lower dark current, a higher photocurrent, and a 476 % enhancement in the maximum responsivity as compare with those of the photodetector fabricated on conventional flat sapphire substrate. It is also found that the much larger UV-to-visible rejection ratio and the fact that responsivity drops in a smaller cut-off region are observed from photodetector fabricated by using a periodic trapezoid column-shape patterned sapphire substrate. These phenomena may all be attributed to the reduction of threading dislocation density and the improved quality of GaN film, as well as the internal reflection and/or scattering effect on the interface between GaN film and the periodic trapezoid column-shape pattern of the substrate.

Understanding surface water evaporation in tropical catchments is pivotal for effective water management, but limited research exists on stable isotopic (δ2H and δ18O) assessment of water evaporation losses. Our study bridges that gap, examining stable isotopes in meteoric water and surface waters across tropical regions, both humid and semi-arid. Using the Craig-Gordon model, we calibrated evaporation-to-inflow (E/I) ratios, identifying distinct E/I variations between seasons and regions. Notably, the semi-arid region consistently exhibited higher E/I ratios due to climatic characteristics. By integrating the Hamiltonian Monte Carlo and the No-U-Turn Sampler, we were able to quantify uncertainties in isotopic and meteorological parameters, resulting in E/I estimates within 68% and 95% confidence intervals. Our Bayesian model insights are critical for freshwater resource optimization and hydrological modeling in tropical regions.

New exact solutions to conformable time fractional EW and modified EW equations are constructed by using Sine-Gordon expansion approach. The fractional traveling wave transform and homogeneous balance have significant roles in the solution procedure. The predicted solution is of the form of some finite series of multiplication of powers of cos and sin functions. The relation among trigonometric and hyperbolic functions in sense of Sine-Gordon expansion gives opportunity to construct the solutions in terms of hyperbolic functions.

Applied talent is not only a builder of human civilization but also a promoter of economic development. They not only need systematic and solid engineering theoretical knowledge but also rich engineering practical experience. Applied undergraduate colleges are the cradle for cultivating applied talent and shoulder the important mission of cultivating various types of applied talent for society. With the rapid development of higher education, the number of applied undergraduate institutions has sharply increased, but the quality of applied talent cultivated by them has shown a significant decline, which greatly restricts the pace of industrial development in the world. This article proposes a new concept of promoting the "three certificates" (graduation certificate, degree certificate, and skill certificate) education model in applied undergraduate colleges, which is of great significance for the country to cultivate composite talents with the ability of "product design, production management, and product processing" at the same time.

Heavy metals contamination in groundwater often occurs in various industrial processes. Stud-ies have confirmed that polysulfide could reduce hexavalent chromium to trivalent chromium, achieving the effect of in-situ stabilization. For other heavy metals contamination in groundwa-ter, whether polysulfide also had a stabilizing ability to achieve in-situ remediation. This re-search focused on heavy metals except for chromium that often contaminated in groundwater, including lead, nickel, zinc, copper, and cadmium to explore the feasibility of using calcium polysulfide (CaSx) as an in-situ stabilization technology for these heavy metals contamination groundwater. Results showed that CaSx had a great removal efficiency for heavy metals lead, nickel, zinc, copper, and cadmium. However, for nickel, zinc, copper and cadmium, when CaSx was added excessively, complexes would be formed, causing the result of re-dissolve and this would also reduce the removal efficiency. Since it is difficult to accurately control the dosage of agents for in-situ groundwater remediation, the concentration of re-dissolved nickel, zinc, cop-per, and cadmium may not be able to meet the groundwater control standards. CaSx had high lead removal efficiency, and it would not cause re-dissolution due to excessive CaSx dosing. CaSx can be used as an in-situ stabilization technique for lead contaminated groundwater.

The sustainable development of resource-based cities has long been a focal point for both governmental policies and academic research. A wealth of academic literature identifies the 'resource curse' as a critical barrier to sustainable development in these urban areas. Despite extensive studies, a consensus on effective strategies to circumvent or resolve this challenge remains elusive. Recent empirical data reveals a noticeable pattern of economic growth differentiation in China's resource-based cities. Why do some resource-based cities experience economic decline while others achieve sustainable economic growth? Therefore, this paper analyzes the reasons for the divergence of economic growth in resource cities from the perspective of heterogeneity. The results of the study show that the phenomenon of the resource curse is conditional, and the heterogeneity of demo-graphic changes, geographic location and institutional environment has a significant impact on the economic growth of resource cities. These factors are investigated to elucidate the observed diversification and heterogeneity in the economic growth of resource-based cities. Building upon this analysis, the paper proposes a framework for differentiated sustainable development pathways tailored to the unique contexts of these cities. This approach not only contributes to the current understanding of the 'resource curse' but also offers novel insights for future research aiming to adopt a more nuanced and context-specific perspective in examining sustainable urban development.

There always exist steel cuttings, holes and cracks at the interfaces in the explosive composite plate. Multi-pass friction stir processing (M-FSP) is proposed in this research to optimize the interface microstructure and the interface connection for 1060Al/Q235 explosive composite plate. Results show that the microstructures of 1060Al after M-FSP are fine and uniform owing to the strong stirring effect and recrystallization. Micro-defects formed by the explosive welding can be repaired by the M-FSP. However, M-FSP can also form tunnel defects in the aluminum, especially when the passes are one and two. The melting block and the melting lump in the composite plates are easy to become source of crack. The shear strengths and the bending properties for the 1060Al/Q235 explosive composite plate after M-FSP are the best when the passes are three, with the tool rotation speed of 1200rpm and the forward speed of 60mm/min. The optimized interfaces for the explosive composite plate after M-FSP are mainly by the metallurgical bondings, with a certain thickness and are discontinuous. Therefore, the crack extension stress is the largest and the mechanical properties are the best.

In the rapidly evolving landscape of genetic engineering, the advent of CRISPR-Cas technologies has catalyzed a paradigm shift, empowering scientists to manipulate the genetic code with unprece-dented accuracy and efficiency. Despite the remarkable capabilities inherent to CRISPR-Cas sys-tems, recent advancements have witnessed the integration of small molecule to augment their functionality, introducing new dimensions to the precision and versatility of gene editing applica-tions. This review delves into the synergy between CRISPR-Cas technologies and small molecule drugs, elucidating the pivotal role of chemicals in optimizing target specificity and editing efficiency. By examining a diverse array of applications, ranging from therapeutic interventions to agricultural advancements, we explore how the judicious use of chemicals enhances the precision of CRISPR-Cas-mediated genetic modifications. In this review we emphasize the significance of small molecule drugs in fine-tuning the CRISPR-Cas machinery, which allows researchers to exert meticulous con-trol over the editing process. We delve into the mechanisms through which these chemicals bolster target specificity, mitigate off-target effects, and contribute to the overall refinement of gene edit-ing outcomes. Additionally, we discuss the potential of chemical integration in expanding the scope of CRISPR-Cas technologies, enabling tailored solutions for diverse genetic manipulation challenges. As CRISPR-Cas technologies continue to evolve, the integration of small molecule drugs emerges as a crucial avenue for advancing the precision and applicability of gene editing techniques. This re-view not only synthesizes current knowledge but also highlights future prospects, paving the way for a deeper understanding of the synergistic interplay between CRISPR-Cas systems and chemical modulators in the pursuit of more controlled and efficient genetic modifications.

AI advances integrate generative design tools in architecture, providing architects with sophisticated design options. It enables the creation of intricate, high-performing projects by exploring diverse design possibilities with AI and algorithms. Generative AI and generative design empower architects to create better-performing, sustainable, and efficient design solutions and explore diverse design possibilities. This paper leverages multimodal generative AI to enhance design creativity by combining textual and visual inputs. Blockchain technology converts design metadata into NFTs, ensuring secure, authentic, and traceable data storage. The framework addresses data ownership, legal adherence, and client-architect collaboration and is entirely scalable for digital design authentication. This research exemplifies the pragmatic fusion of Generative AI and blockchain technology applied in architectural design for more transparent, secure, and effective results. This study provides a strategy that uses generative AI technologies to achieve an efficient and creative workflow in the early stages of architectural design.

In the TANGO study, the long-term noninferior efficacy of switching to dolutegravir/lamivudine (DTG/3TC) compared to continuing tenofovir alafenamide–based regimens was demonstrated in treatment-experienced adults with HIV. However, there is limited real-world data comparing the effectiveness and safety of bictegravir/emtricitabine/tenofovir alafenamide fumarate (BIC/FTC/TAF) and DTG/3TC in Asia. This retrospective observational study, conducted at a designated HIV-care hospital from March 2019 to January 2023, aimed to address this gap. Demographic, clinical, and laboratory data, including HIV viral loads and lipid profiles, were collected and analyzed. The primary outcome was the proportion of patients with HIV RNA <50 copies/mL at week 48 in both groups, utilizing a snapshot, per-protocol–exposed population. A total of 1086 patients were included, with 511 in the DTG/3TC group and 575 in the BIC/FTC/TAF group. At week 48, 98% of patients in the DTG/3TC group and 94% in the BIC/FTC/TAF group achieved HIV RNA <50 copies/mL (p <0.01). Logistic regression analysis identified risk factors for detectable viral loads at week 48, including HIV RNA >100,000 copies/mL (AOR 5.13, 95% CI 1.42–18.53), low-level viremia (AOR 3.91, 95% CI 1.07–14.25), and record of virologic failure ≥2 times (AOR 4.21, 95% CI 1.64–10.85) before the switch. Furthermore, no significant difference was found between the DTG/3TC and BIC/FTC/TAF regimens (AOR: 1.51, 95% CI 0.70–3.24). In conclusion, the study demonstrates that the effectiveness and safety profiles of DTG/3TC and BIC/FTC/TAF were comparable in treatment-experienced adults with HIV, particularly among those with undetectable viral loads at baseline.

In this work, we study a Klein-Gordon oscillator subject to Cornelltype potential in the background of the Lorentz symmetry violation determined by a tensor out of the Standard Model Extension. We introduce a Cornell-type potential S(r) = (η_L\,r + \frac{η_c}{r} ) by modifying the mass term via transformation $M → M + S(r)$ and then coupled oscillator with scalar particle by replacing the momentum operator $\vec{p}→ (\vec{p}+ i\,M\,ω\,\vec{r})$ in the relativistic wave equation. We see that the analytical solution to the Klein-Gordon oscillator equation can be achieved, and a quantum effect characterized by the dependence of the angular frequency of the oscillator on the quantum numbers of the relativistic system is observed

The negative energy solutions of the Klein-Gordon and Dirac equations have been used to define the antiparticle with the positive energy from the Feynman - Stueckelberg interpretation in the standard model based on the 4-D Minkowski space with the relative time. The negative energy solutions of the Klein-Gordon and Dirac equations are used to define the antiparticles with the negative energy in the present 3-D quantized space model. Note that all the present results are based on the 4-D Euclidean space with the absolute time (t) and relative time (t_l). Then the particle with the positive energy and antiparticle with the negative energy have the 4-D P₄ = TCP = T_cP symmetry. The continuity equations are derived from the Klein-Gordon, Dirac and Schrodinger equations. The Klein-Gordon and Schrodinger equations with the potential barriers are solved. The Klein paradox is explained by using the pair production of the electron with the positive energy and positron with the negative energy under the P₄ = _TcP symmetry, The effective velocity ( c_eff=√2 " c " ) and effective energy ("Etl =" √2 E ) along the relative time axis (ctl) give the relative time momentum of "p_tl"=E_tl/c_eff =(√2 E)/(√2 c)=E/c=p_t=p_x. This indicates that the photons with the energy of E have the constant photon velocity of c and the constant photon momentum of "ptl"=E_tl/c_eff =(√2 E)/(√2 c)=E/c=p_t=p_x. For the negative energy particles, the space momentum directions are opposite to the particle velocity directions because the energy is negative. And the matter collapse to the photons at the very high particle velocity is discussed from the length expansion. It is, for the first time, proposed that the gamma ray burst is originated from the matter collapse to the photons near the black hole. Also, the wave function collapse is explained from the length expansion. The wave function collapse takes place when the measurement makes the particle velocity to be zero. It is concluded that the negative energy solutions of the Klein-Gordon and Dirac equations support the existence of the partner antimatter universe with the negative energy and negative time direction. Our matter universe has the positive energy and the positive time direction.

Session-based recommendations which aim to predict subsequent user-item interaction based on historical user behavior during anonymous sessions can be challenging tasks. Two main challenges need to be addressed and improved: (1) How to analyze these sessions to accurately and completely capture users’ preferences, and (2) how to identify and eliminate any interference caused by noisy behavior. Existing methods have not adequately addressed these issues since they either neglected the valuable insight that can be gained from analyzing consecutive groups of items or failed to take these noisy data in sessions seriously and handled them properly, which can jointly impede recommendation systems from capturing users’ real intentions. To address these two problems, we designed a multi-order semantic denoising (MSD) model for session-based recommendations. Specifically, we grouped items of different lengths as varying multi-order semantic units to mine the user’s primary intention from multiple dimensions. Meanwhile, a novel denoising network was designed to alleviate the interference of noisy behavior and provide a more precise session representation. The result of extensive experiments on three real-world datasets demonstrated that the proposed MSD model exhibited improved performance compared with existing state-of-the-art methods in session-based recommendation.

This paper presents a comprehensive study on the application and optimization of automotive thermoelectric generators (ATEGs), focusing on the crucial role of heat exchangers in enhancing energy conversion efficiency. Recognizing the substantial waste of thermal energy in internal combustion engines, our research delves into the potential of TEGs to convert engine waste heat into electrical energy, thereby improving fuel efficiency and reducing environmental impact. We meticulously analyze various heat exchanger designs, assessing their influence on the TEG's output power under different exhaust gas flow rates and temperatures. Furthermore, we explore the impact of TEG material properties on the overall energy conversion effectiveness. Our findings reveal that specific heat exchanger designs significantly enhance the efficiency of waste gas heat exchange, leading to an improved performance of the TEG system. We also highlight the importance of thermal insulation in maximizing TEG output. This study not only contributes to the ongoing efforts to develop more sustainable and efficient vehicles but also provides valuable insights into the practical application of thermoelectric technology in automotive engineering. Through this research, we aim to pave the way for more environmentally friendly transportation solutions, aligning with global efforts to reduce fossil fuel dependence and mitigate environmental pollution.

Ganoderic Acid (GA), a major bioactive compound isolated from an oriental medicinal mushroom, i.e. Ganoderma tsugae, has traditionally been found to have significant medicinal properties. As a result of GA's poor solubility in water, formulation poses several challenges. Additionally, the traditional method of administering it via alcohol always results in unfavorable patient side effects. In order to overcome these problems, Ganoderma Tsugae extracts obtained by ethanol extraction were encapsulated in nanodispersions by ultrasonic cavitation and solvent evaporation to maximise bioavailability. Resultant nanodispersions contained Ganoderic acid in a hydrophobic core with a mean particle size of no more than 200 nm and a very narrow particle distribution. An analysis of the interactions between the control variables and the process optimisation was conducted using the Response Surface Methodology (RSM). Based on the results of the experiment, it was found that the particle size of nanodispersions was influenced by the Hydrophilic-Lipophilic Balance (HLB) number and the evaporation temperature. Moreover, the physical stability of micellar systems is generally determined by the organic phase within them. Regarding formulation stability, the zeta average of the nanodispersions remained virtually unchanged in solutions with different pH levels and short-term storage (14 days) at room temperature. Overall, it has been demonstrated that Ganoderic acid nanodispersions can be efficiently generated by combining ultrasound cavitation and solvent evaporation.

During planetary exploration mission operations, one of the key responsibilities of the instrument teams to determine data viability for subsequent analysis. During the 2019 CanMoon Lunar Sample Return Analogue Mission, the Lead Raman Specialist manually examined each spectra to provide quality assurance/validation. This non-trivial process requires years of experience to complete accurately. With the proven efficacy of Convolutional Neural Networks (CNNs) in classification tasks, and the increased use of automation and control loops on planetary space platforms for navigation and science targeting, an opportunity presents itself to approach this validation problem utilising CNNs. We present the Generalised Raman Validation Network (GRaVN), an neural network focused specifically on extracting the generalised structure of Raman spectra for quality assurance/validation. This work demonstrates the viability of utilising a CNN network in validation activities for Raman spectroscopy. Utilising only two hidden layers, a configuration was developed that provided good levels of accuracy on a manually curated dataset. This indicates that such a system could be useful as part of an autonomous control loop during planetary exploration activities.

Due to the fact that abrasive media can deform flexibly in abrasive flow machining (AFM) making this method easily to polish the complex holes and the curved surface of the hard machining shapes. Although abrasive media dominate the polishing behavior in AFM process, the mechanism of the abrasive media are not easy to understand because of the high viscous gels, therefore, many finishing works need lots of time to design AFM process. Power laws of the abrasive gels is studied here to evaluate the non-Newtonian flow of abrasive gels in complex holes polishing firstly, at the mean time different abrasive gels are utilized to finish the complex holes to follow the results by non-Newtonian flow calculation. Moreover, traditional AFM has difficulty to achieve a uniform roughness of radial distribution in the complex holes polishing because of the non-uniform abrasive forces. So a helical passageway is proposed to create a multiple motion of abrasive medium and to obtain the even surface of the complex holes in AFM process.

The integration of robotic devices into healthcare settings for rehabilitation purposes represents a rapidly advancing field with significant benefits for both therapists and patients. However, standalone robot systems face limitations such as inefficient processing of patient data and logistical challenges for patients, such as travel time to rehabilitation centers. To address these shortcomings, this paper proposes the integration of cyber-physical systems into rehabilitation robotics. Cyber-physical systems leverage network connectivity and real-time data processing to enhance the efficiency and convenience of robot-based rehabilitation. By seamlessly integrating sensors, actuators, and computational algorithms, cyber-physical rehabilitation systems empower therapists to more effectively treat patients by providing actionable insights derived from comprehensive data analysis. This enables therapists to tailor treatment plans precisely to each patient’s unique needs, ultimately leading to improved outcomes. Additionally, cyber-physical rehabilitation systems facilitate remote monitoring and intervention, allowing therapists to oversee patient progress and make timely adjustments to treatment protocols without the need for in-person visits. This not only saves patients valuable time and resources but also ensures continuity of care, particularly for individuals residing in remote or underserved areas. Furthermore, cyber-physical rehabilitation systems enable collaborative decision-making by facilitating communication and information sharing among healthcare professionals, further enhancing the quality and efficacy of rehabilitation services. In summary, integrating cyber-physical systems into rehabilitation robotics represents a significant advancement in leveraging technology to optimize patient care and outcomes, promising to revolutionize rehabilitation therapy.

The rapid retreat of coastal cliffs poses a profound risk to property, transport infrastructure and public safety both in Ireland and globally. This study combines historical data (maps and orthophotos, 1842 to 2000) with contemporary UAV surveys (2019 to 2023) to quantify cliff top and cliff face retreat along a 250 m wide coastal drumlin at Silverstrand in Galway Bay, Ireland. Retreat rates for the cliff top and cliff face were calculated using 2D mapping and 3D modelling, respectively. Critically, the choice of method appears to have a major impact on apparent rates of cliff top retreat, with output from the 2D mapping approach (0.14 +/- 0.02 m yr-1) being double that of the 3D modelling approach (0.08 +/- 0.02 m year-1). The aperiodic development of a talus cone, which offers temporary protection to the cliff from storm waves, also influences the estimation of cliff retreat. The repeat cycles of talus slope formation and removal in this high wave energy climate suggest that the drumlin transitions between a periodically transport-limited system and supply limited system over short- and long-time periods, respectively, on the continuum of cliff types. These results warrant further research to identify and quantify the rates, patterns, drivers (marine and subaerial processes), and timing of cliff retreat rates in response to climate change.

Alveolar Rhabdomyosarcoma (ARMS), an invasive subtype of Rhabdomyosarcoma (RMS), is associated with chromosomal translocation events resulting in one of two oncogenic fusion genes PAX3-FOXO1 or PAX7-FOXO1. ARMS patients exhibit an overexpression of the pleiotropic cytokine Transforming growth factor beta (TGF-β). This overexpression of TGF-β1 causes an increased expression of a downstream transcription factor called SNAIL, which promotes Epithelial to Mesenchymal Transition (EMT). Overexpression of TGF-β also inhibits myogenic differentiation, making ARMS patients highly resistant to chemotherapy. In this review, we first describe different types of RMS and then focus on ARMS and the impact of TGF-β in this tumor type. We next highlight current chemotherapy strategies including a combination of FDA approved drugs vincristine, actinomycin D, and cyclophosphamide (VAC), Cabozantinib, Bortezomib, Vinorelbine, AZD 1775 and cisplatin. Lastly, we discuss chemotherapy agents that target the differentiation of tumor cells in ARMS which include all trans retinoic acid (ATRA) and 5-Azacytidine. Improving our understanding of the role of signaling pathways, such as TGF-β1, in the development of ARMS tumor cells differentiation will help inform more tailored drug administration in the future.

Questions：SAP in mountainous cities of China serve as crucial carriers for species and wild food, constituting potential green infrastructure. These patches should be recognized as locally specific resources. This study investigates the transformation characteristics of the landscape patterns of SAP, along with their elements, across urban-rural gradients, providing foundational support for the planning of conservation and utilization strategies. Location: Yongchuan area of Chongqing in southwest China. Methods: The study investigated urban-rural gradient-based transformation of SAP. A four-direction transect space was selected and divided into uniform sample squares. Fragstats 4.3 calculated the landscape index of SAP, and Spearman correlation coefficients in SPSS were used to evaluate the influence of landform and artificial factors on agroforestry patch transformation. Results: 1) Patch area (PA), Plaque density (PD), and CLUMPY of SAP systematically transform, showing increased SAP areas and higher connectivity with greater distance from the city, resulting in reduced patch fragmentation. However, Edge density (ED) and Largest plaque index (LPI) exhibit irregular transformation patterns. 2) With increased distance from the city, woodland patch area and connectivity increase, leading to decreased fragmentation, dispersal, and lower fractal dimensions. Conversely, Cultivated land follows the opposite trend. garden land patch area, fractal dimension, fragmentation, and dispersal all increase, while connectivity decreases. 3) Landscape pattern transformations of SPA are significantly influenced by artificial factors. Woodland patches are influenced similarly by landform and artificial factors. In contrast, cultivated land and garden land patches are more significantly impacted by artificial factors. Conclusions: SAP exhibit differentiated conservation and utilization measures across urban-rural gradients. Small patches located far from urban centers may benefit from systematic conservation measures to prevent further fragmentation and erosion in peri-urban areas.

To decrease privacy risks, consumers may choose to misrepresent when they are asked to offer personal information. This paper examines the impact of consumer misrepresentation on a monopolistic firm and consumers with an economic model. The results show that consumer misrepresentation may benefit the firm but hurt consumers. In addition, consumers misrepresentation may encourage the firm to provide higher personalized service level in certain scenarios, such as, when the unit cost of personalized service is low. Thirdly, when consumers misrepresent, and the firm only covers part of the market, a greater unit value of consumer’s privacy information will reduce the firm’s profit, but a greater unit cost of personalized service increases the firm’s profit.

Oil-Gan, also known as emblica, is the fruit of the genus Phyllanthus emblica L. The fruits of these trees are high in nutrients and have excellent effects on health care and development values. There are many methods for the management of diabetic nephropathy (DN). However, there is a lack of effective drugs for treating DN from throughout the disease course. The primary aim of this study was to examine the protective effects (including urine analyses, the measurement of inflammatory cytokine levels, and histological examination) and mechanisms of action of an ethyl acetate extract of P. emblica (EPE) on db/db mice, an animal model of diabetic nephropathy, as well as a secondary aim of examining the expression levels of protein kinase Cα (PKCα) in the kidney and its downregulation of vascular endothelial growth factor (VEGF) and fibrosis gene transforming growth factor-β1 (TGF-β1) by Western blot analyses. Eight db/m C57BLKS/J mice were used as the control group. Forty db/db mice were randomly divided into five groups. Treatments included vehicle, EPE1, EPE2, EPE3 (at doses of 100, 200, or 400 mg/kg EPE), or the comparative drug aminoguanidine for 8 weeks. After 8 weeks of treatment, blood samples were collected for analyses of blood glucose, insulin, and HbA1c levels, and pancreatic and kidney tissues were dissected for histological analyses. The present study indicated that the administration of EPE to db/db mice effectively controlled hyperglycemia and hyperinsulinemia by markedly lowering blood glucose, insulin, and glycosylated HbA1c levels. Administration of EPE to db/db mice decreased the levels of BUN and creatinine both in blood and urine and reduced urinary albumin excretion and the albumin creatine ratio (UACR) in urine. Moreover, EPE treatment decreased the blood levels of inflammatory cytokines, including kidney injury molecule-1 (KIM-1), C-reactive protein (CRP), and NLR family pyrin domain containing (NLRP3). Our findings showed that EPE not only had antihyperglycemic effects but also improved renal function in db/db mice. Histological examination of the kidney by immunohistochemistry indicated that EPE can improve kidney function by ameliorating glomerular morphological damage following glomerular injury; alleviating proteinuria by upregulating the expression of nephrin, a biomarker of early glomerular damage; and inhibiting glomerular expansion and tubular fibrosis. Moreover, the administration of EPE to db/db mice increased the expression levels of p- PKCα/t-PKCα but decreased the expression levels of VEGF and renal fibrosis biomarkers (TGF-β1, collagen IV, p-Smad2, p-Smad3, and Smad4), as shown by Western blot analyses. These results implied that EPE as a supplement has a protective effect against renal dysfunction through the amelioration of insulin resistance as well as the suppression of nephritis and fibrosis in a DN model.

Multimodal remote sensing data classification can enhance the model’s ability to distinguish land features through multimodal data fusion. In this context, how to help models understand the relationship between multimodal data and target tasks is the focus of researchers. Inspired by human feedback learning mechanisms, causal reasoning mechanisms, and knowledge induction mechanisms, this paper integrates causal learning, reinforcement learning, and meta learning into a unified remote sensing data classification framework and proposed the causal meta-reinforcement learning (CMRL). First, based on feedback learning mechanisms, we have overcome the limitations of traditional implicit optimization of fusion features and customized a reinforcement learning environment for multimodal remote sensing data classification tasks. Through feedback interactive learning between agents and the environment, we help them understand the complex relationships between multimodal data and labels, thereby achieving full mining of multimodal complementary information. Second, based on the causal inference mechanism we designed causal distribution prediction action, classification reward, and causal intervention reward, capturing pure causal factors in multimodal data and cutting off false statistical associations between non-causal factors and class labels. Finally, based on the knowledge induction mechanism, we designed a bi-layer optimization mechanism based on meta-learning. By constructing a meta training task and meta validation task simulation model in the generalization scenario of unseen data, we helped the model induce cross-task shared knowledge, thereby improving its generalization ability for unseen multimodal data. The experimental results on multiple sets of multimodal datasets show that the proposed method achieved state-of-the-art performance in multimodal remote sensing data classification tasks.

As part of a comprehensive research on eco-friendly processing techniques, the influence of heat treatment environment on the case-hardening of AISI 1018 steel using pulverized cassava leaf was studied. The process was carried out at two different temperatures (850˚C and 950˚C) and under three environmental conditions: (Process 1) the control experiment, was carried out in air only, (Process 2) the medium comprised of pulverized cassava leaves, and (Process 3) the combination of pulverized cassava leaves plus barium carbonate (BaCO3) as an energizer (CBC mixture). Vickers microhardness testing and scanning electron microscopy were used to evaluate the effect of processing environment on case hardening of the steel. As expected, regardless of the processing temperature, Process 1 resulted in little or no hardening of the steel surface. However, notable case hardening occurred when steel specimens were subjected to either Process 2 or Process 3. Furthermore, the inclusion of barium carbonate in Process 3 significantly enhanced the case hardening effectiveness of the cassava leaf as it pertains to rate and maximum hardness achieved. Maximum enhancement was observed at 950oC. After 1 hour, the increase in hardness were 160% and 280%, for Process 2 and Process 3, respectively. Upon increasing the processing time to 5 hours, the increase in hardness due to Process 2 was raised to 254%, while that of Process 3 remained at approximately 280%. Diffusivity of AISI 1018 was calculated using the microhardness data. Diffusivity was highest in Process 2 samples with values of 1.568 x 10-9 m2/s at 850°C and 1.893 x 10-9 m2/s at 950 °C.

At the Rio Conference in 1992, the sustainable development agenda promised a new era for natural resource management, where the well-being of human society would be enhanced through the sustainable use of natural capital. Several decades on, economic growth continues unabated at the expense of natural capital, as evidenced by biodiversity loss, climate change and further environmental issues. Why is this happening and what can be done about it? In this research, we present three Agent-Based Models that explore the social, economic and governance factors driving (un)sustainability in complex social-ecological systems. Our modelling results reinforce the idea that the current economic system does not protect the natural capital on which it depends. This is due to a disjunction between the economic and environmental elements upon which the sustainable development paradigm is founded. Additionally, various factors appear to enhance social-ecological system unsustainability: the role of financial entities and monetary debt; economic speculation; technological development and efficiency; lack of long-term views and late government interventions; inefficient tipping point management; and the absence of strong top-down and bottom-up conservation forces. Interestingly, alternative scenarios showed that these same factors could be redirected to enhance sustainable development. The current economic system may, therefore, not be inherently unsustainable, but rather specific economic mechanisms, agents’ decision-making, and the kinds of links between economic and natural systems could be at the root of the problem. We argue that short- and medium-term sustainability can be enhanced by implementing mechanisms that shift capitalist forces to support environmental conservation. Long-term sustainability, however, requires further paradigm change: where the economy integrates, and fully accounts for, externalities and recognises the actual value of natural capital.

Excretory-secretory products (ESPs) are the main research targets for investigating the hosts and helminths interaction. Parasitic worms can migrate to parasitic sites and avoid the host immune response by secreting this product. Angiostrongylus cantonensisis an important food-borne zoonotic parasite that causes severe neuropathological damage and symptoms, including eosinophilic meningitis or meningoencephalitis in humans. Benzaldehydes are organic compounds composed of a benzene ring and formyl substituents. This compound has anti-inflammatory and antioxidation properties. Previous studies showed that 3-hydroxybenzaldehyde (3-HBA) and 4-hydroxybenzaldehyde (4-HBA) can reduce apoptosis in A. cantonensis ESPs treated astrocytes. These results on the protective effect underlying benzaldehyde have primarily focused on cell survival. The study was designed to investigate the molecular mechanisms of endoplasmic reticulum stress (ER stress) and oxidative stress in astrocytes in A. cantonensis ESPs treated astrocytes and to evaluate the therapeutic consequent of 3-HBA and 4-HBA. First, we initially established the RNA-seq dataset in each group, including Normal, ESPs, ESPs+3-HBA, and ESPs+4-HBA. We also found that benzaldehyde (3-HBA and 4-HBA) can stimulate astrocytes to express ER stress-related molecules after ESP treatment. The level of oxidative stress could also be decreased in astrocytes by elevating antioxidant activity and reducing ROS generation. These results suggested that benzaldehyde may be a potential therapeutic compound for human angiostrongyliasis to support brain cell survival by inducing the expression levels of ER stress- and oxidative stress-related pathway.

The International Roughness Index (IRI) is the standard scale for evaluating road roughness in many countries in the world. The Taipei City government actively promotes a Road Smoothing Project and plans to complete the rehabilitation of the main and minor roads within its jurisdiction. This study aims to detect the road surface roughness in Taipei City and recommend appropriate IRI thresholds for road rehabilitation. A total of 171 asphalt concrete pavement sections in Taipei City with a total length of 803.49 km were analyzed and compared by IRI. The longitudinal profile of the detected road sections was measured using an inertial profiler. The statistical analysis showed that the IRI value prior to road leveling was mainly distributed between 5 and 8 m/km, while the IRI value after road leveling was mainly distributed between 3 and 4.5 m/km. This confirms that the implementation of the Road Smoothing Project has a significant effect on improving road smoothness. Moreover, based on the analysis results, it is recommended that the IRI threshold value for road rehabilitation in Taipei City be set at 4.50 m/km.

In this work, optimal consumption and investment strategies are derived for risk-averse investors under the 4/2 stochastic volatility class of models. We work under an expected utility (EUT) framework and consider a Constant Relative Risk Aversion (CRRA) investor, who might also be ambiguity-averse. The corresponding Hamilton-Jacobi-Bellman (HJB) and HJB-Isaacs (HJBI) equations are solved in closed-form for a subset of the parametric space and under some restrictions on the portfolio setting, for complete markets. Conditions for proper changes of measure and well defined solutions are provided. These are the first analytical solutions for the 4/2 stochastic volatility model and the embedded 3/2 model for the type of excess returns established in .

This paper reviews the requirements for the production, quality, and quality assurance of solid recovered fuels (SRF) that are increasingly used for the substitution of fossil fuels in the indus-trial utilities. The economical, technological and environmental aspects should be considered before using SRF as an alternative fuel. In general, the most important factors determining the commercial production of SRF referred to the calorific values and their available amounts adopted in the starting materials. Furthermore, the low-melting impurities and undesired constituents/elements, including chlorine, sulfur, potassium and sodium, may pose negative impacts on air pollutant emission and slagging & fouling in the process utilities. In this regard, the vent emitted from the industrial utilities must comply with the effluent standards of station-ary sources like particulate, sulfur oxides, nitrogen oxides, heavy metals (e.g., lead, cadmium, and mercury) and dioxins. For these reasons, this work will summarize the legal or regulatory requirements under development in Asian countries (i.e., Japan, South Korea, and Taiwan) and European Union (EU). Finally, the outlook of solid recovered fuel (SRF) in the waste manage-ment and industrial sectors will be addressed to echo the sustainable development goals (SDGs).

A typhoon-induced storm surge is considered one of the most severe coastal disasters in Taiwan. However, the combination of the storm surge and the astronomical tide called the storm tide can actually cause extreme flooding in coastal areas. This study implemented a two-dimensional hydrodynamic model to account for the interaction between tides and storm surges on the coast of Taiwan. The model was validated with observed water levels at Sauo Fish Port, Hualien Port, and Chenggong Fish Port under different historical typhoon events. The model results are in reasonable agreement with the measured data. The validated model was then used to evaluate the effects of the typhoon's intensity, bathymetric change, and the combination of the typhoon’s intensity and bathymetric change on the maximum storm tide and its distribution along the east coast of Taiwan. The results indicated that the maximum storm tide rises to 1.92 m under a typhoon with an intensity of a 100-year return period. The maximum storm tide increased from a baseline of 1.26 m to 2.63 m for a 90% bathymetric rise at Sauo Fish Port under the conditions of Typhoon Jangmi (2008). The combination of the intensity of a typhoon with a 100-year return period and a 90% bathymetric rise will result in a maximum storm tide exceeding 4 m, 2 m, and 3 m at Sauo Fish Port, Hualien Port, and Chenggong Fish Port, respectively. We also found that the distribution of the maximum storm tide on the east coast of Taiwan can expand significantly subject to the bathymetric rise.

In the human organism various carotenoids are present of which, some are retinoid precursors. The bioactive derivatives of these retinoids are the retinoic acids, which can potently activate nuclear hormone receptors like the retinoic acid receptor and the retinoid X receptor. In our study using an HPLC analytical approach we aimed to assess how plasma carotenoid and retinoid concentrations along with the ratio of their isomers are altered in atopic dermatitis (AD) patients (n=20) compared to healthy volunteers (HV, n=20). We found that plasma levels of the carotenoids lutein (HV 198 ± 68 ng/ml, AD 158 ± 57 ng/ml), zeaxanthin (HV 350 ± 142 ng/ml, AD 236 ± 85) as well as the retinoids retinol (HV 216 ± 89 ng/ml, AD 167 ± 76 ng/ml) and all-trans-retinoic acid (HV 1.1 ± 0.6 ng/ml, AD 0.7 ± 0.5 ng/ml) were significantly lower in AD-patients, while lycopene, α-carotene and β-carotene levels were comparable. In addition the ratios of 13-cis vs. all-trans lycopene as well as 13-cis vs. all-trans retinoic acid were increased in the plasma of AD-patients indicating an AD-specific 13C-isomerisation. A positive correlation with SCORRAD was calculated with 13-cis vs. all-trans lycopene ratio, while a negative correlation was observed with zeaxanthin plasma levels. Based on our results we conclude that in the plasma of AD-patients various carotenoids and retinoids are at lower levels, while the ratio of lycopene isomers was also altered. The higher rate of lycopene and retinoic acid isomerisation products might be a consequence of AD or might result in an altered activation of nuclear hormone receptor signaling pathways and thus maybe partly be responsible for the AD-phenotype and additionally may represent a good plasma marker for AD.

The morphological and compositional complexities of keratinized components make feathers ingenious skin appendages adapted to diverse ecological needs. Frizzling feathers, characterized by their distinct curling phenotypes, offer a unique model to explore the intricate morphogenesis in developing a keratin-based bioarchitecture over a wide range of morphospace. Here, we investigated the heterogeneous allocation of α- and β-keratins in flight feather shafts of homozygous and heterozygous frizzle chickens by analyzing the medulla-cortex integrations using quantitative morphology characterizations across scales. Our results reveal intriguing construction of frizzling feather shaft through modified medulla development, leading to a perturbed balance of the internal biomechanics and, therefore, introducing the inherent natural frizzling compared to those from wild-type chickens. We elucidate how the localized developmental suppression of the α-keratin in the medulla interferes with the growth of the hierarchical keratin organization by changing the internal stress in the frizzling feather shaft. This research not only offers insights into the morphogenetic origin of the inherent bending of frizzling feathers but also facilitates our in-depth understanding of the developmental strategies toward the diverse integuments adapted for ecological needs.

Background: Metastatic cancer is associated with an invariably fatal outcome. However, DeltaRex-G, a tumor- targeted retrovector encoding a CCNG1 inhibitor gene, has induced long term (>10 years) survival of patients with chemo-resistant metastatic pancreatic adenocarcinoma, MPNST, osteosarcoma, B-cell lymphoma, and breast carcinoma. Objective: To evaluate the level of CCNG1 expression in tumors as a potential biomarker for CCNG1 inhibitor therapy. Methods: CCNG1 RNA expression levels were measured in tumors (TCGA, N=9161), adjacent “tissues” (TCGA, N=678) and GTEx normal tissues (N=7187) across 22 organ sites. Differential expression of CCNG1 and Ki-67 in primary (N= 9161) vs metastatic (N= 393) tumors were also compared and particularly in primary (N=103) vs. metastatic (N=367) skin cancer (i.e., melanoma). Results: Enhanced CCNG1 RNA and protein expression were noted in tumors compared to normal analogous counterparts, and CCNG1 expression correlated significantly with that of Ki-67. Further, CCNG1 expression tended to be higher than that of Ki-67 in metastatic vs primary tumors, particularly in skin cancer (melanoma). Conclusions: Taken together, these data indicate that (1) CCNG1 expression is frequently enhanced in tumors when compared to their normal analogous counterparts, (2) CCNG1 and Ki-67 expressions are higher in metastatic vs primary tumors, (3) CCNG1 expression is significantly correlated with that of Ki-67, and (4) CCNG1 may be a stronger marker of metastasis than Ki-67. Phase 2 studies are planned to identify patients who are likely to respond favorably to CCNG1 inhibitor therapy by correlating treatment outcome parameters with CCNG1 expression levels in various cancer types.

Influenza is a disease that poses a significant health burden worldwide. Vaccination is the best way to prevent influenza virus infections. However, conventional vaccines are only effective for a short period of time due to the propensity of influenza viruses to undergo antigenic drift and antigenic shift. The efficacy of these vaccines is uncertain from year-to-year due to potential mismatching between the circulating viruses and vaccine strains, mutations arising due to egg adaptation, and potential contamination of the vaccine virus stock. Subsequently, the inability to store these vaccines long-term and vaccine shortages are challenges that need to be overcome. Conventional vaccines are also less effective for certain populations, including the young, old, and immunocompromised. This warrants for diverse efficacious vaccine developmental approaches, involving both active and passive immunization. As opposed to active immunization platforms (requiring the use of whole or portions of pathogens as vaccines), the rapidly developing passive immunization involves administration of either pathogen-specific or broadly acting antibodies against a kind or class of pathogens as a prophylactic treatment to corresponding acute infection. Several antibodies with broadly acting capacities have been discovered that may serve as means to suppress influenza viral infection and allow the process of natural immunity to engage opsonized pathogens whilst boosting immune system by antibody-dependent mechanisms that bridge the innate and adaptive arms. By that, passive immunotherapeutics approach assumes a robust tool that could aid control of influenza viruses. In this review, we comment on some improvements in influenza management and promising vaccine development platforms, with emphasis on the capacity of passive immunotherapeutics especially when coupled with the use of antivirals in the management of influenza infection.

There is a current worldwide outbreak of a new type of coronavirus (2019-nCoV), which originated from China and has now spread to 17 other countries. Governments are under increase pressure to stop the outbreak spiraling into a global health emergency. At this stage, preparedness, transparency and sharing of information are crucial to risk assessments and beginning outbreak control activities. This information should include reports from outbreak sites, and from laboratories supporting the investigation. This paper aggregates and consolidates the virology, epidemiology, clinical management strategies from both English and Chinese literature, official news channels and other official government documents. In addition, by fitting the number of infections with a single-term exponential model, we report that the infection is spreading at an exponential rate, with a doubling period of 1.8 days.

Isokinetic testing of the knee joint is the “gold standard” in strength assessment in sport especially in soccer, where it is part of pre-season screening to establish norms in case of injuries. There are many devices on the market that make it difficult to use of normative data. Isokinetics literature in females’ soccer players is scarce in comparison to males. Furthermore, evaluation protocols strongly differ from each other, using different ranges of speeds, movement patterns and output data. Thus, it is difficult for the researcher and the clinician to choose a correct protocol for isokinetic evaluation in female soccer players. The indexes of isokinetic performance that are widely accepted are the hamstring/quadriceps (H/Q) ratio and dominant/non-dominant (D/ND) ratio as reference. In this review are highlighted some common features of isokinetic testing in female soccer players of different levels of qualification. From this study, it emerges that, for a reliable test, 3 reps at the speed of 60°/sec in knee flexion/extension is preferable due to the high reliability and that an optimal H/Q ratio in healthy female soccer players of different level of qualification and age is 50%, while the interlimb differences (D/ND) should be below 10%.

[Introduction]: In the contemporary international financial environment, marked by intricate complexities and increasing uncertainties, the impact of exchange rate fluctuations on national economies has become increasingly significant. In this context, this study uses the Chinese economy as a case study to delve deeply into the interaction effects between macroprudential and monetary policies, analyzing how these policies jointly address economic instability. The aim is to offer new perspectives and strategies for stabilizing the global economic and financial landscape. [Methods]: This paper constructs an open-economy Dynamic Stochastic General Equilibrium (DSGE) model specifically tailored for China, incorporating Bayesian estimation and numerical simulation techniques. The study meticulously examines how macroprudential and monetary policies can be coordinated to achieve economic stability in response to exchange rate shocks. [Results]: The research finds that (1) targeted coordination of macroprudential and monetary policies towards asset prices and price levels can maintain stability under exchange rate shocks; (2) the effective implementation of such coordinated policies not only mitigates the fluctuations in asset prices due to exchange rate shocks but also enhances the level of societal welfare; (3) in terms of choosing an exchange rate regime, a managed floating rate system can prevent policy overlaps and conflicts that might occur in a floating rate system during the coordination of macroprudential and monetary policies, thus offering comparative advantages. [Discussion]: The findings underscore the importance of policy integration in a dynamic and complex global economic environment. They provide policy recommendations for China and other emerging market countries on how to effectively maintain economic stability through the synergistic interplay of macroprudential and monetary policies amid fluctuations in exchange rates and asset prices.

Vitamin D, unlike the micronutrients, vitamins A, E and K, is largely obtained, not from food, but by the action of solar UV light on its precursor, 7-dehydrocholesterol, in skin. With the decline in UV light intensity in winter, most skin production of vitamin D occurs in summer. Because no defined storage organ or tissue has been found for vitamin D, it has been assumed that adequate vitamin D status in winter can only be maintained by oral supplementation. Skeletal muscle cells have now been shown to incorporate the vitamin D-binding protein (DBP) from blood into the cell cytoplasm where it binds to cytoplasmic actin. This intracellular DBP provides an array of specific binding sites for 25-hydroxyvitamin D (25(OH)D) which diffuses into the cell from the extracellular fluid. When intracellular DBP undergoes proteolytic breakdown, the bound 25(OH)D is then released and diffuses back into blood. This uptake and release of 25(OH)D by muscle, accounts for the very long half-life of this metabolite in the circulation. As 25(OH)D concentration in blood declines in winter, its cycling in and out of muscle cells appears to be upregulated. Parathyroid hormone is the most likely factor enhancing the repeated cycling of 25(OH)D between skeletal muscle and blood. This mechanism appears to have evolved to maintain adequate vitamin D status in winter.

Vitamin D, unlike the micronutrients, vitamins A, E and K, is largely obtained, not from food, but by the action of solar UV light on its precursor, 7-dehydrocholesterol, in skin. With the decline in UV light intensity in winter, most skin production of vitamin D occurs in summer. Because no defined storage organ or tissue has been found for vitamin D, it has been assumed that adequate vitamin D status in winter can only be maintained by oral supplementation. Skeletal muscle cells have now been shown to incorporate the vitamin D-binding protein (DBP) from blood into the cell cytoplasm where it binds to cytoplasmic actin. This intracellular DBP provides an array of specific binding sites for 25-hydroxyvitamin D (25(OH)D) which diffuses into the cell from the extracellular fluid. When intracellular DBP undergoes proteolytic breakdown, the bound 25(OH)D is then released and diffuses back into blood. This uptake and release of 25(OH)D by muscle, accounts for the very long half-life of this metabolite in the circulation. As 25(OH)D concentration in blood declines in winter, its cycling in and out of muscle cells appears to be upregulated. Parathyroid hormone is the most likely factor enhancing the repeated cycling of 25(OH)D between skeletal muscle and blood. This mechanism appears to have evolved to maintain adequate vitamin D status in winter.

The utilization of optical antennas for active control of far-field radiation at the subwavelength scale is crucial in various scientific and technological applications. We propose a thermally tunable disk design of indium tin oxide (ITO) and aluminum gallium nitride (Al0.18Ga0.82As), enabling a switch between absorption and scattering. Furthermore, the control of far-field radiation pattern can be easily realized by combining ITO and Al0.18Ga0.82As to enhance or suppress emission. Our results demonstrate that hybrid structure can be dynamically tuned with temperature variations. In the proposed design, a frequency is achieved at the epsilon-near-zero wavelength of 1240 nm. The thermal tunability of hybrid structure introduces new multifunctional possibilities for light manipulation, thereby enhancing the potential applications of new devices in the near-infrared range.

In this paper we overview all analytical engineering solutions for corrosion problems in pressure vessels delivered over the past 60 years. We briefly detail strengths and weaknesses of existing approaches, thus demonstrating the need for novel uniform corrosion analysis methods for both current and new applications. To complement the review, we also present a new analytical model allowing to estimate the lifetime of pressured elastic vessels with mechanically assisted corrosion. Both internal/external pressure and internal/external corrosion are captured and dissolution driven corrosion is also considered. The readily implemented method improves existing analytical approaches and is shown to be effective for thin and thick shells, as well as various loading and corrosion intensity and geometrical conditions.

Microvascular self-healing composite materials have significant potential for application and their mechanical properties need in-depth investigation. In this paper, tensile and compressive properties of woven fabric carbon fiber reinforced polymers (CFRP) laminates containing three-dimensional microvascular channels were investigated experimentally. Several detailed finite element (FE) models were established to simulate the mechanical behavior of the laminate and the effectiveness of different models were examined. The damage propagation process of the microvascular laminates and the influence of microvascular parameters were studied by the validated models. The results show that microvascular channels arranged along the thickness direction (z-direction) of the laminates are critical locations under the loads. The channels have minimal effect on the stiffness of the laminates but causing a certain reduction in strength, which varies approximately linearly with the z-direction channel diameter within its common design range of 0.1~1mm. It is necessary to consider the resin-rich region formed around microvascular channels in the warp and weft fiber yarns of the woven fabric composite when establishing the FE model. And the layers in model should be assigned with equivalent unidirectional ply material in order to calculate the mechanical properties of laminates correctly.

We present three reduced integrable hierarchies of nonlocal integrable NLS type equations from a vector integrable hierarchy associated with a matrix Lie algebra, not being A type. Three similarity transformations are taken to keep the invariance of the transformed zero curvature equations. The key step is to formulate a solution to a reduced stationary zero curvature equation so that the zero curvature formulation works for a reduced case.

Predicting the outcome of a future game between two National Basketball Association (NBA) teams poses a challenging problem of interest to statistical scientists as well as the general public. In this article, we formalize the problem of predicting the game results as a classification problem and apply the principle of maximum entropy to construct NBA maximum entropy (NBAME) model that fits to discrete statistics for NBA games, and then predict the outcomes of NBA playoffs by the NBAME model. The best NBAME model is able to correctly predict the winning team 74.4 percent of the time as compared to some other machine learning algorithms which is correct 69.3 percent of the time.

We employed the Riemannian Face Manifold (RFM) as an alternative approach to the conventional linear Euclidean space for explaining the atypicality bias in face likeliness judgments. The RFM posits that the mental representation of faces is better captured as a manifold of stable states, accounting for the nonlinearity in the physical properties of faces. To examine the relationship between physical and psychological distance of morph and typical/atypical faces, we manipulated the parameter k and incorporated a weight function in the Riemannian metric. Our results indicate that the psychological distance between the morph and typical face was longer than that between the morph and atypical face, consistent with prior research on the atypicality bias in perceptual similarity. The RFM approach provides mathematical support and is a powerful tool for studying face perception and recognition, offering potential implications for explaining the other-race effect. Future research can utilize the RFM to investigate individual differences in face recognition abilities and expertise, and how they impact psychological distance and face processing.

In this paper we present the exploration of indoor positioning technologies for UAVs, and navigation techniques for path planning and obstacle avoidance. The objective is to perform warehouse inventory tasks using a drone to search for barcodes or markers to identify the objects. For the indoor positioning techniques, we employ Visual-Inertial Odometry (VIO), Ultra-Wideband (UWB), AprilTag fiducial markers, and Simultaneous Localization and Mapping (SLAM). These algorithms encompass global positioning, local positioning, and pre-mapping positioning, comparing the merits and drawbacks of various techniques and trajectories. In UAV navigation, we combine SLAM-based RTAB-Map indoor mapping and navigation path planning of the ROS for indoor environments. This system enables precise drone positioning indoors and utilizes global and local path planners to generate flight paths that avoid dynamic, static, unknown, and known obstacles, demonstrating high practicality and feasibility. To achieve the warehouse inventory inspection, a reinforcement learning approach is proposed to recognize the markers by adjusting the UAV's viewpoint. We address several main problems in inventory management, including efficiently planning paths while ensuring a certain level of detection rate. Two reinforcement learning techniques, AC (Actor-Critic) and PPO (Proximal Policy Optimization), are implemented based on AprilTag identification. Testing is performed in both simulated and real-world environments, and the effectiveness of the proposed method is validated.Code is available at https://github.com/kellen080/Navigation and https://github.com/kellen080/Indoor\_Positioning.

Nanomedicine holds great potential to devise better drug delivery systems (DDSs). However, many reported nanomedicines still fall short of commercial requirements including specific targetability, scale-up manufacturing and safety. Cell/tissue based carriers, including cell membrane vehicle and exosome, are biocompatible and targeting platforms but usually suffered from low yields and unstable reproducibility. Here in this study, we proposed the concept and preparation of reconstituted lipid nanoparticles (rLNPs) to develop highly reproducible cell/tissue based lipid nanoparticles (LNPs) for drug delivery, which holds the potential as a versatile drug delivery platform. The whole lipids of cell or tissue were firstly extracted and then prepared into rLNPs using solvent diffusion method. In this way, the preparation of ultra-small (~20 nm) rLNPs can be easily applied to both cell (mouse breast cancer cell line, 4T1) and tissue (mouse liver tissue). Our results demonstrated that mouse liver tissue derived rLNPs can be further labeled/modified with imaging, targeting or other functional moieties. Furthermore, rLNPs were highly biocompatible and capable of loading different drugs including doxorubicin hydrochloride (Dox) and curcumin (Cur). Most importantly, Dox loaded rLNPs (rLNPs/Dox) showed preferable in vitro and in vivo anticancer performance. Therefore, rLNPs might be a versatile drug delivery platform for future application in the treatment of a variety of diseases.

This article analyzes in detail the influence of Jupiter on the measurement of the gravitational constant. Including a specific estimate of the change in the gravitational constant caused by the change of the earth's orbital position every half month. The influence of Jupiter's perihelion and aphelion on the gravitational constant is also estimated. On this basis, this article analyzes the data with specific time records such as BIPM-01, BIPM-14, JILA-10, UCI-14, HUST-09. The analysis results show that after considering the influence of Jupiter, the experimental results have been significantly improved.

Restricted Boltzmann machines (RBMs) are the building blocks of some deep learning networks. However, despite their importance, it is our perception that some very important derivations about the RBM are missing in the literature, and a beginner may feel RBM very hard to understand. We provide here these missing derivations. We cover the classic Bernoulli-Bernoulli RBM and the Gaussian-Bernoulli RBM, but leave out the ``continuous'' RBM as it is believed not as mature as the former two. This tutorial can be used as a companion or complement to the famous RBM paper ``Training restricted Boltzmann machines: An introduction'' by Fisher and Igel.

A portable Fourier Transform Spectrometer (B3M-IR) is built and used to measure atmospheric trace gases in the city of Beijing during Olympic Games in 2008. A short description of the instrument is first provided in this paper. A detailed spectral analysis is then presented. The total columns of ozone (O3), carbon monoxide (CO), methane (CH4) and nitrous oxide (N2O) are retrieved from the ground-based solar absorption spectra recorded by the B3M-IR during the Olympic Games. Lacking validation data, only the retrieved total column of O3 is compared with that retrieved by MAX-DOAS, which is deployed at the same station. The mean difference between the two methods of measurement is 6.5%, demonstrating the performance and reliability of B3M-IR.