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The excessive growth of carbon emissions (CO2E) from industrial energy use not only exacerbates global warming and severely curbs the sustainable development of the economy and society. As a high energy-consuming sector second only to the fossil energy division, the power and heavy division, China's chemical industry should have received more attention for its CO2E. However, there are limited literatures on energy CO2E in China's chemical sector at present. Based on this fact, this current paper uses the energy utilization approach, the input–output analysis approach, and the extended structural decomposition method to evaluate the energy-related CO2E of China's chemical sector from 2007 to 2017. (1) China's chemical sector energy-related CO2E showed a trend of first growth and then a slow decline, demonstrating that the rapid growth of China's chemical sector energy-related CO2E has been effectively controlled; However, it should be noted that the chemical industry is still dominated by high-CO2E energy-related CO2E at the current stage. (2) Input structure and energy intensity effects have a reduced influence on the growth of energy-related CO2E in China's chemical sector. This is due to upgrading energy use technology and optimizing the generalized technology progress rate in the chemical sector. (3) Energy structure and final demand effects have encouraged the growth of the chemical sector's energy-related CO2E. It shows that the industrial system's demand for chemical products is constantly expanding, and the chemical products still have the characteristics of high carbonization. Also, the chemical sector's supply-side energy utilization structure has not been significantly enhanced. [ABSTRACT FROM AUTHOR]

The ocean is the largest carbon sink on Earth and an important pathway to China achieving carbon neutrality. From a consumption perspective, studying the capacity of marine carbon sink in each of China's provinces and its interregional transfer is of great significance in harnessing the increase in ocean carbon sink driven by final demand. This article first calculates the productionside carbon sink in coastal provinces. Then, based on the 2007, 2012, 2015, and 2017 Chinese inter-regional input-output tables, each province's consumptionside marine carbon sink is calculated. The article further examines the influencing factors and key transfer paths for the growth of marine carbon sink through Structural Decomposition Analysis (SDA) and Structural Path Analysis (SPA) methods. The results show that each province's total consumption-side carbon sink continues to rise, with significant regional disparities, demonstrating a trend of higher carbon sink in coastal provinces than inland provinces. Among the nine coastal provinces, Hainan and Guangdong are in a net input state regarding carbon sink transfer, while the other seven are in a net output state. SDA results indicate that the carbon sink intensity effect and the consumption demand effect are important factors inhibiting and promoting carbon sink growth, respectively, while the influence of the input-output technical effect is weak and variable. SPA analysis reveals that carbon sink outputs are primarily transferred to the food and tobacco sector, the agricultural and forestry products and services sector, and the wood processing and furniture industry. The key transfer paths mostly occur within a province, with a relatively small proportion of interprovincial transfer paths. Based on the research findings, this article suggests steadily increasing the proportion of marine product consumption, actively expanding the value chain of shellfish and seaweed industries, continuously strengthening coordination between land and marine industries, and further promoting the domestic circulation of marine carbon sinks. [ABSTRACT FROM AUTHOR]

Introduction: Pythons are a well-studied model of postprandial physiological plasticity. Consuming a meal evokes a suite of physiological changes in pythons including one of the largest documented increases in post-feeding metabolic rates relative to resting values. However, little is known about how this plasticity manifests in the brain. Previous work has shown that cell proliferation in the python brain increases 6 days following meal consumption. This study aimed to confirm these findings and build on them in the long term by tracking the survival and maturation of these newly created cells across a 2-month period. Methods: We investigated differences in neural cell proliferation in ball pythons 6 days after a meal with immunofluorescence using the cell-birth marker 5-bromo-12′-deoxyuridine (BrdU). We investigated differences in neural cell maturation in ball pythons 2 months after a meal using double immunofluorescence for BrdU and a reptilian ortholog of the neuronal marker Fox3. Results: We did not find significantly greater rates of cell proliferation in snakes 6 days after feeding, but we did observe more new cells in neurogenic regions in fed snakes 2 months after the meal. Feeding was not associated with higher rates of neurogenesis, but snakes that received a meal had higher numbers of newly created nonneuronal cells than fasted controls. We documented particularly high cell survival rates in the olfactory bulbs and lateral cortex. Conclusion: Consuming a meal stimulates cell proliferation in the brains of ball pythons after digestion is complete, although this effect emerged at a later time point in this study than expected. Higher rates of proliferation partially account for greater numbers of newly created non-neuronal cells in the brains of fed snakes 2 months after the meal, but our results also suggest that feeding may have a mild neuroprotective effect. We captured a slight trend toward higher cell survival rates in fed snakes, and survival rates were particularly high in brain regions associated with olfactory perception and processing. These findings shed light on the relationship between energy balance and the creation of new neural cells in the brains of ball pythons. [ABSTRACT FROM AUTHOR]

Esta revisión se centra en describir nuevos sistemas de diagnóstico molecular de tipo POC disponibles en el mercado que pueden implementarse fácilmente en farmacias comunitarias y tienen el potencial de ampliar la cartera de servicios farmacéuticos y hacer una contribución significativa a la mejora de la salud pública. El conocimiento de nuevas técnicas de diagnóstico molecular distintas de la PCR es relativamente desconocido. Sin embargo, las opciones disponibles son diversas y han alcanzado suficiente madurez tecnológica para su uso a gran escala. La pandemia de SARS-CoV-2 ha sacado al mercado pruebas de diagnóstico que, en algunos casos, se han utilizado exclusivamente en investigación durante décadas. La tecnología isotérmica de amplificación de ácidos nucleicos sigue evolucionando y es probable que en los próximos años seamos testigos de un aumento exponencial de su uso, así como del desarrollo de nuevas mejoras que simplifiquen y reduzcan aún más el coste de cada ensayo. Igualmente, no podemos obviar el hecho de que durante la pandemia de COVID-19, el público se ha habituado a autodiagnosticarse a través de canales de distribución masiva como las farmacias comunitarias, lo que puede abrir el sector a otras enfermedades —como las de transmisión sexual o salud animal—, el control de alimentos, la contaminación del agua y del aire (hongos) o la presencia de alérgenos. El conocimiento de estas nuevas tecnologías es esencial estrategia de vigilancia tecnológica e inteligencia competitiva del sector farmacéutico.

ABSTRACTDietary omega-3 polyunsaturated fatty acids (n-3 PUFAs) and the gut microbiome affect each other. We investigated the impact of supplementation with Buglossoides arvensis oil (BO), rich in stearidonic acid (SDA), on the human gut microbiome. Employing the Mucosal Simulator of the Human Intestinal Microbial Ecosystem (M-SHIME), we simulated the ileal and ascending colon microbiomes of four donors. Our results reveal two distinct microbiota clusters influenced by BO, exhibiting shared and contrasting shifts. Notably, Bacteroides and Clostridia abundance underwent similar changes in both clusters, accompanied by increased propionate production in the colon. However, in the ileum, cluster 2 displayed a higher metabolic activity in terms of BO-induced propionate levels. Accordingly, a triad of bacterial members involved in propionate production through the succinate pathway, namely Bacteroides, Parabacteroides, and Phascolarctobacterium, was identified particularly in this cluster, which also showed a surge of second-generation probiotics, such as Akkermansia, in the colon. Finally, we describe for the first time the capability of gut bacteria to produce N-acyl-ethanolamines, and particularly the SDA-derived N-stearidonoyl-ethanolamine, following BO supplementation, which also stimulated the production of another bioactive endocannabinoid-like molecule, commendamide, in both cases with variations across individuals. Spearman correlations enabled the identification of bacterial genera potentially involved in endocannabinoid-like molecule production, such as, in agreement with previous reports, Bacteroides in the case of commendamide. This study suggests that the potential health benefits on the human microbiome of certain dietary oils may be amenable to stratified nutrition strategies and extend beyond n-3 PUFAs to include microbiota-derived endocannabinoid-like mediators.

This review focuses on describing new commercially available POC-type molecular diagnostic systems that can be easily implemented in community pharmacies and have the potential to expand the portfolio of pharmaceutical services and make a significant contribution to the improvement of public health. Knowledge of new molecular diagnostic techniques other than PCR is relatively unexplored. However, the available options are diverse and have reached sufficient technological maturity for large-scale use. The SARS-CoV-2 pandemic has brought diagnostic tests to market that, in some cases, have been used exclusively in research for decades. Isothermal nucleic acid amplification technology continues to evolve and it is likely that in the coming years we will witness an exponential increase in its use, as well as the development of new improvements that further simplify and reduce the cost of each assay. Furthermore, we cannot ignore the fact that during the COVID-19 pandemic, the public has become accustomed to self-diagnosing through mass distribution channels such as community pharmacies. Which can open the sector to other diseases - such as sexually transmitted diseases or animal health -, food control, water and air contamination (fungi) or the presence of allergens. Knowledge of them is an essential technological surveillance strategy for the pharmaceutical sector. [ABSTRACT FROM AUTHOR]

For several decades, no satisfactory solutions have been provided to the problem of offline handwriting recognition. In the field of online recognition, researchers have had more successful performance, but the ability to extract dynamic information from static images has not been well explored yet. In this paper, we introduce a novel multi-lingual word handwriting recovery framework based on a convolutional denoising autoencoder with an attention model for pen up/down, velocity and temporal order recovery. The proposed framework consists of extracting robust features from a handwriting image using a stacked denoising autoencoder and an encoder Bidirectional Gated Recurrent Unit (BGRU) model. Then, the obtained vectors are decoded to produce an online script with dynamic characteristics using a BGRU with temporal attention. Evaluation is done on a Latin and Arabic Online and offline handwriting character / word databases and the proposed framework achieves high competitive results. [ABSTRACT FROM AUTHOR]

In order to improve the recognition precision and accuracy of tool wear monitoring, an unsupervised deep neural network (DNN) based on stack denoising autoencoder (SDA) is proposed. After feature extraction and selection, the stack denoising automatic coding network reduces the dimensionality of the feature vector. On this basis, principal component analysis (PCA) and T-distributed random neighbor embedding (t-SNE) are used to reduce the dimensionality of the features twice, and finally a simple two-dimensional feature matrix is obtained. Finally, the deep neural network model of SDA is established by adding SoftMax regression layer, and the tool wear monitoring results are taken as new labeled data, and the deep neural network parameters are fine-tuned by secondary backpropagation. The experimental results show that the proposed method can learn adaptively and obtain effective feature expression, and the tool wear state recognition results are highly accurate. The proposed method can effectively identify the tool wear state. [ABSTRACT FROM AUTHOR]

Death is something inevitable and common to all human beings. However, cultures vary in how they define and manage living with the inevitability of death and what happens when a person dies. Among the possible responses to this inescapable reality, there is death anxiety. Several instruments have proliferated in the literature to assess death anxiety. Among them, stands out the Scale of Death Anxiety (SDA) which contemplates somatic, cognitive, emotional and behavioural reactions from a symptomatic perspective. Thus, the objective of this study is the validation and measurement invariance of the SDA in Portuguese and Arab samples (N = 216 and N = 377, respectively). Confirmatory factor analyses, multi-group confirmatory factor analyses measurement invariance and latent mean differences were performed across cultures and gender groups. Our results provided important preliminary evidence for the validity of the scale in both samples. The structure of the SDA remained unchanged in both cultures and genders. The SDA showed partial scalar invariance across cultural groups, and full scalar invariance across gender groups. As expected, the Arab participants showed higher levels of anxiety than the Portuguese sample. The analyses also showed that females in both cultural groups obtained higher scores than males on dysphoria and fear of death. However, the two genders did not differ significantly on avoidance of death. The results show that the SDA is a reliable and valid measure for the study of death anxiety, showing to be invariant between cultures and between genders. [ABSTRACT FROM AUTHOR]

praktik ijon politik dalam perhelatan politik elektoral menjadi ancaman demokrasi yang sampai hari ini masih sangat relatif terbatas dikaji. Hal ini menjadikan minimnya celah bagaimana melihat fenomena pembiayaan politik elektoral yang tinggi dari sudut pandang politik SDA. Selama ini SDA selalu dipandang sebagai objek mati. Namun dalam studi politik SDA, objek tersebut merupakan objek yang tidak netral. Hadirnya sistem ijon politik yang menjadi bagian kecil dari bentuk politik transaksional di dalam ruang demokrasi informal sesungguhnya telah menjadi identitas dan ciri khas politik elektoral di Indonesia. Pada konteks ijon politik inilah kemudian pertukaran peran antara patron menjadi klien dan sebaliknya klien menjadi patron akan terus berulang. Penelitian ini menggunakan pendekatan kualitatif dengan metodologi library research. Peneliti mengumpulkan data melalui data sekunder yakni berbagai literatur relevan, mulai dari media, buku, jurnal, pemberitaan, data lembaga formal, dan data-data lainnya yang dipilah sesuai dengan kebutuhan penelitian. Hasil menunjukkan bahwa praktik ijon politik masih sarat dan selalu di mewarnai politik elektoral di Indonesia. Praktik demokrasi informal ini berujung pada tingginya pembiayaan politik elektoral. Menariknya keterlibatan korporasi dalam pendanaan pemilihan umum di luar dana partai politik turut berimbas pada balas budi atas pengelolaan SDA. Terbangunnya praktik politik transaksional dalam ruang informal akan menciptakan tantangan bagi kualitas demokrasi. Lahirnya perilaku koruptif, lemeanya tatanan pemerintahan, politik dinasti-oligarkis, sampai pada melonjaknya pembiayaan politik elektoral. Kesimpulannya ialah praktik ijon politik akan selalu tumbuh dalam ruang demokrasi informal. Perkelindanan sektor publik, elit, dengan swasta akan selalu bertukar peran sebagai patron dan klien sesuai dengan kondisi dan peta politik elektoral di lapangan.

Introduction: The fossil energy sector is an important part of international trade, and the flow of products between sectors will bring about the flow of embodied carbon. There are relatively few studies on embodied carbon in the fossil energy sector, which are mostly concentrated in other sectors and are not well integrated with GVC. Combining embodied carbon with GVC provides a better view of the allocation of environmental responsibility in trade. At the same time, it can also help different countries to improve the environment with the help of GVC.Methods: This research is based on the World Input–Output Database. First, by using multi-regional input–output, this paper measures fossil energy trade embodied carbon (FEE) data of 39 countries from 2000 to 2014; second, using structural decomposition analysis, we find what factors affect FEE. Finally, we analyze theimpact of global value chain (GVC) on the FEE.Results: This study obtained the following conclusions: 1) different GVCs have different effects on the embodied carbon in trade. Simple forward, complex forward, and simple backward to embedded play a positive role. The complex backward GVC has a negative impact; 2) high-income countries can get greater positive environmental effects through GVC, and middle-income countries cannot obtain or obtain less environmental effects; and 3) the backward GVC affects the FEE by affecting the proportion of fossil energy consumption.Discussion: The results show that the FEE shall be jointly responsible for the world’s countries, and different countries should make different contributions to the world’s environmental protection comprehensively considering factors such as the economic development level of various countries. This proposes relevant policy suggestions in China.

Este trabalho apresenta um estudo estatístico das capturas de meteoros da chuva Southern Delta-Aquariids (SDA). Os registros foram feitos pelas câmeras das estações de monitoramento de meteoros UVP1 e UVP2, da rede EXOSS, instaladas em São José dos Campos SP, no Observatório de Astronomia e Física Espacial da Universidade do Vale do Paraíba (UNIVAP), em cooperação com o Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP). A chuva SDA ocorre anualmente no período de julho a agosto. Foram analisados registros dos anos 2017, 2018, 2019 e 2020. Em 2017, 27 registros foram obtidos entre 12 de julho e 24 de agosto, com pico de atividade em 27-28 de julho; em 2018, foram 12 registros entre 18 de julho e 20 de agosto, com pico na noite de 29-30 de julho; para 2019, foram 45 meteoros registrados entre 11 de julho e 13 de agosto, com pico em 27-28 de julho; e em 2020, foram 22 registros entre 25 de julho e 07 de agosto, com pico em 28 de julho, com cerca de um terço dos meteoros SDA registrados nesse ano. Nos quatro anos consecutivos, os meteoros SDA apresentaram duração média de 0,18 s, 0,23 s, 0,23 s, e 0,21 s; magnitude aparente média de -1,1, -1,2, -0,8 e -1,1 e velocidade linear média de 47,1 km/s, 51,4 km/s, 49,0 km/s, e 45,7 km/s, respectivamente

This article investigates the possibilities of frequency tuning of a Self-diplexing antenna (SDA) using different liquid dielectrics. Tuning analysis is carried out using the fluidic pockets introduced into the substrate by drilling blind vias starting at the bottom layer. To examine the frequency tuning, the pockets can be filled with either air, olive oil, transformer oil, acetone, or distilled water and sealed with copper tape. The experimental results demonstrate that the proposed antenna can be configured to operate in the 3.25 to 3.52 GHz and 4.5 to 5.04 GHz bands. The proposed SDA is designed and fabricated on a substrate of 1.575 mm thick Rogers 5880 ( ϵ r = 2.2 and tan δ = 0.0009). It is observed that frequency shift is more when using higher permittivity fluids. The proposed antenna model has competitive features such as simple design, compact size ( 0.34 λ g 2 ), better isolation (>30 dB), and fine-tuning, which makes it suitable for modern multiband and multifunctional gadgets. The simulated and measured circuit responses are in good agreement. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSN) have been implemented in nearly every field of use because they offer a solution to practical problems that can also be affordably implemented. The sensor nodes have limited computing resources, weak batteries, and limited storage space. The environmental or physical data collected by these nodes is transmitted straight to the BS. The data transfer cost is raised due to the direct data transmission. In addition, the lifetime of sensor networks is shortened because of the rise in energy required for data exchange. As a result, data aggregation is utilized in WSN to lessen the burden of transmission costs and lengthen the useful life of the sensor networks. Each sensor node's transmission is encrypted with cipher text generated by the Paillier homomorphic cryptosystem. In addition, the Bilinear aggregate signature method is used to create a digital signature at each sensor node. The cluster head / BS is where the aggregation takes place once the cipher text and signature have been combined. Before deciding whether to accept or reject the message, the BS checks the aggregate signature. The homomorphic cryptosystem saves power because it does not perform intermediate-level or cluster-head decryption. Data integrity, authenticity, and confidentiality are all maintained while using less power with this technology. The Intel laboratory dataset is used in the implementation. When compared to current systems, the proposed SDA method requires less time and energy to calculate. [ABSTRACT FROM AUTHOR]

Based on the latest China-Russia input-output data sets over the period from 2007 to 2015, this study quantified the flow of embodied carbon emissions in China-Russia trade using the emission embodied in bilateral trade (EEBT) approach. In addition, the structural decomposition analysis (SDA) was employed to identify the potential driving factors that affect embodied carbon in imports and exports. The results showed as follow. 1) China was a net exporter of carbon emissions in bilateral trade between China and Russia during 2007–2015. Despite that the bilateral trade scale had expanded considerably, the net export volume of CO2 from China to Russia decreased from 13.21 Mt in 2007 to 4.45 Mt in 2015. 2) From the perspective of different sectors, the metal manufacturing and the chemical sectors of China and Russia were the main sources of CO2 emissions. 3) In terms of driving factors, it was found that the carbon emission coefficient was the main reason for contributing to embodied emission reduction. Moreover, the contribution rate of carbon emission coefficient to reduce the carbon emissions in imports reached to 95.26%, as well as 108.22% in exports. The bilateral trade scale was the main driver for the increase in embodied carbon emissions, and the contribution rate to embodied carbon emissions in imports and exports were 14.80% and 65.17%, respectively. 4) This study argued that China and Russia should further optimize the energy structure and improve the energy efficiency and intermediate technology in the future. [ABSTRACT FROM AUTHOR]

Thirty years after the passage of the Americans with Disabilities Act, people with disabilities still face significant barriers to transportation access. Nearly one-third of disabled people describe inadequate transportation as a problem in their lives, and many major transportation systems have large accessibility gaps. In the San Francisco Bay Area, home to Silicon Valley and the 2010s tech boom, new mobility services are particularly widespread. TNCs, for example, make up approximately 25% of peak-hour traffic in Downtown San Francisco. San Francisco also has a well-established bike-share system and was among the first cities in the country to see hundreds of scooters on its streets and sidewalks. In light of the prevalence of these services and the significant transportation needs of the disability community, this project examines perceptions of new mobility among disabled people in San Francisco and makes recommendations for improving transportation access for people with disabilities.

Electrical conductivity is an important characteristic for safe and economic handling of aviation turbine fuels which have the potential to accumulate static charges. Jet fuels are highly refined product with very low conductivity. To ensure safe fuel storage and distribution, Jet fuel specifications have been established specifying permissible levels of fuel conductivity. Static Dissipater Additive (SDA) or conductivity improver, is often added to fuel to achieve specification requirements. Controlling of SDA concentration via conductivity measurement is essential for commercial practice due to its surface active nature and anti-electrostatic properties All possible factors affecting the conductivity of jet fuel has been taken into account and described in this research article. The effect of 0.5 to 3.5 mg/l SDA on water separation characteristic (MSED) are also studied and presented. [ABSTRACT FROM AUTHOR]

• Carbon emission transfers show a significant trend from the North to the South in 2017. • Electricity and heat power, metal and non-metal industries in less developed northern regions are the important "suppliers" of embodied carbon emissions. • Construction and service industries in richer southern regions are the main "consumers". • New carbon transfer patterns are mainly due to changes in consumption and export. The carbon transfer changes triggered by transformation of economic development patterns are less concerned. This study seeks to estimate the carbon implications caused by regional development gaps between the North and South in China. We utilize Multiregional Input-Output (MRIO) model to reveal the new features of embodied carbon emission, and apply structural decomposition analysis (SDA) to reflect the main driving forces behind the changes in implied emissions patterns. The results demonstrate that carbon transfers show a significant trend from the North to the South in 2017. Moreover, electricity and heat power, metal and non-metal industries in poorer northern regions are the important "suppliers" of implied emissions, while construction and service industries in developed southern regions are the main "consumers". Carbon transfers from the North to the South mainly due to changes in consumption and export. The key industries and driving forces should receive more attention when making carbon reduction policies. [ABSTRACT FROM AUTHOR]

AIMS:To provide quantitative conversions between commonly used scales for the assessment of negative symptoms in schizophrenia. METHOD:Linear regression analyses generated conversion equations between symptom scores from the Scale for the Assessment of Negative Symptoms (SANS), the Schedule for the Deficit Syndrome (SDS), the Positive and Negative Syndrome Scale (PANSS), or the Negative Symptoms Assessment (NSA) based on a cross sectional sample of 176 individuals with schizophrenia. Intraclass correlations assessed the rating conversion accuracy based on a separate sub-sample of 29 patients who took part in the initial study as well as an independent sample of 28 additional subjects with schizophrenia. RESULTS:Between-scale negative symptom ratings were moderately to highly correlated (r = 0.73-0.91). Intraclass correlations between the original negative symptom rating scores and those obtained via using the conversion equations were in the range of 0.61-0.79. CONCLUSIONS:While there is a degree of non-overlap, several negative symptoms scores reflect measures of similar constructs and may be reliably converted between some scales. The conversion equations are provided at http://www.converteasy.org and may be used for meta- and mega-analyses that examine negative symptoms.

ABSTRACT Although the pour plate method is widely employed in microbiological quality control, it has certain drawbacks, including having to melt the culture medium before seeding. In this study, the preparation of the culture medium was modified by using a lower concentration of agar (10 g/L), which was separated from the nutrients during sterilization. The new protocol was assessed in media frequently used in microbiological quality control of food, cosmetics, and pharmaceutical products, with tryptic soy agar (TSA), Sabouraud 4% dextrose agar (SDA), and violet red bile glucose agar (VRBG). In comparison with the conventionally produced media, the modifications significantly improved the growth of Saccharomyces cerevisiae in SDA, Staphylococcus aureus, Salmonella enterica subsp. enterica serovar Typhimurium, and Candida albicans in TSA and Escherichia coli ATCC 8739 and ATCC 25922 and S. Typhimurium in VRBG. The modified VRBG was also more selective for Pseudomonas aeruginosa. Regarding physicochemical properties, a significantly lower pH was observed in TSA and VRBG and lower strength values in TSA. Sterilizing agar separately from the other components of the medium and reducing the agar concentration to 10 g/L can improve microorganism growth and enhance the selectivity of differential media in the pour plate method. These modifications could facilitate the automation of this culture technique. IMPORTANCE In the era of rapid microbiological methods, there is a need to improve long-established culture techniques. Drawbacks of the pour plate method include having to melt each medium separately before seeding. For this technique, we demonstrate that separating the agar from the other components of commonly used media during sterilization and reducing the agar concentration to 10 g/L can enhance microbial growth. The new protocol could have advantages in routine laboratory practice because less agar is required and the same molten agar suspension can be used to prepare different media. Moreover, these modifications could facilitate the automation of the pour plate method.

Background: In patients with comorbid illnesses, COVID 19 disease is a severe acute respiratory syndrome that is linked to a variety of opportunistic bacterial and fungal infections. Finding the cause of fungal infections among post-covid patients in tertiary care hospitals is the aim of the study. Objectives: To study the etiology of post-covid fungal infections among various age groups Methods: Out of 578 samples (pus/tissue/biopsy) collected from patients attending Koti ENT hospital with complaints of pain in eye, cheek swelling, headache. All samples were subjected to direct KOH mount and inoculated on SDA, incubated for 1 week at 25°C. Result: Out of 578 samples 214 are KOH positive and 291 are culture positive with fungi isolated – Mucor species, Aspergillus species and Candida species. Conclusion: As post covid fungal infections are rapidly progressive and devascularised disease, timely diagnosis helps in effective management and treatment of patients. [ABSTRACT FROM AUTHOR]

Due to higher thermal and hydrothermal stability, suitable acidity properties, Beta zeolite is considered as promising catalyst for naphtha catalytic cracking process. However, high cost and environmental pollution issue limit its industrial application by using high content of N-containing organic structural directing agent (SDA). In this paper, different SiO 2 /Al 2 O 3 ratios of Beta zeolites were prepared assisting by seeds induced method with low SDA and cheap industrial silica sol as the silicon source. Physical and chemical properties of as-prepared Beta zeolites were characterized by XRD, N 2 adsorption-desorption, NH 3 -TPD, Py-FTIR and SEM. N-Heptane was used as model compound for catalytic cracking performance evaluation. The results showed that Beta zeolite with high SAR was successfully synthesized, which had well defined crystallinity, proper specific surface area and pore structure, high B/L ratio and strong acid site. n-Heptane catalytic cracking performance showed high yield of low-carbon olefins with relative low activity on hydrogen transfer reaction and coke formation. [Display omitted] • High SAR Beta zeolite was synthesized with low SDA assisted by seeds induced method. • As-prepared Beta zeolite showed high crystallinity, high B/L and strong acid site. • n-Heptane catalytic cracking performance showed high yield of low-carbon olefins. [ABSTRACT FROM AUTHOR]

Pakistan, being an agricultural country, highly depends on its natural water resources which originate from the upper regions of Hindu Kush-Karakoram-Himalaya Mountains and nourish one of the world's largest Indus Basin irrigation systems. This paper presents streamflow modelling and forecasting using signal difference average (SDA) based variational mode decomposition (VMD) combined with machine learning (ML) methods at Chitral and Tarbela stations on the Indus River network. For this purpose, VMD based random forest (VMD-RF), gradient boosting machine (VMD-GBM) and Bayesian regularized neural network (VMD-BRNN) have been chosen. Moreover, traditional time series flow models, that is seasonal autoregressive integrated moving average (SARIMA) and classical decomposition approach with particle swarm optimization-based support vector regression (PSO-SVR), are considered as benchmark models for comparison. The results show that overall, VMD-BRNN performed best, followed by VMD-GBM and VMD-RF, whereas SARIMA and PSO-SVR ranked last. Overall, SARIMA and PSO-SVR are failing to capture most of the peaks even during the training period whereas hybridization of VMD and ML methods has shown increased robustness of the models. The results show that the influential role of the high dimensional components and robustness on the river flow may be explored by most optimum SDA based VMD signals hybrid with BRNN method. HIGHLIGHTS SDA based VMD combined with machine learning model is developed for streamflow modelling and forecasting at Chitral and Tarbela stations.; Modelling and forecasting capability are enhanced via SDA based VMD combined with Machine Learning methods.; VMD-BRNN is more capable of capturing and forecasting streamflow pattern, especially peaks as compared to VMD-RF and VMD-GBM methods.;

In this contribution, novel design is presented for a very compact shielded quarter-mode substrate-integrated waveguide (S-QMSIW) based self-diplexing antenna (SDA) for WiMAX/WLAN applications. In order to achieve dual-band features, a slot is etched onto the top of the metal. Two orthogonal microstrip feed lines in the full-wave EM-simulator (HFSS) simulate the S-QMSIW resonator at two different frequencies (3.45 and 5.45 GHz). The proposed antenna pattern is extremely adaptable, allowing for simple frequency adjustments for each resonant frequency. A lumped circuit model is expected to be used to assess the antenna structure. A self-diplexing antenna based on S-QMSIW was designed, fabricated and tested to claim the proposed concept. At 3.45 and 5.45 GHz, the proposed antenna peak gains are 4.7 and 5.6 dBi, respectively. It offered port isolation better than 38 dB. The antenna front-to-back ratio was greater than 19.5 dB in each band. The proposed antenna circuit size was very compact ( 0.08 λ g 2 ). [ABSTRACT FROM AUTHOR]

This paper presents a new framework for investigating regional CO2 emissions from the perspective of the domestic supply chain, with a combination of linkage analysis and structural decomposition analysis (SDA), which allows for a better understanding of spatial emission distributions and cross-boundary potential for CO2 mitigation. Based on the multi-regional input–output (MRIO) tables of 2007 and 2012, Chinese provinces (cities) are categorised into three groups according to linkage characteristics, among which, Group I is suggested to be given priority in formulating mitigation policies due to their stronger regional CO2 influence characteristics. Moreover, regions in Group I have been more affected by inter-regional trade than other groups with regard to their local CO2 emissions. Therefore, turning Group I into a low-carbon production pattern could help construct greener domestic supply chains. The results emphasise that regional analysis on CO2 emissions should go beyond the local factors, and that regional mitigation polices should consider the position and participation degree of different regions in domestic supply chains. [ABSTRACT FROM AUTHOR]

China and G7 countries contribute 70% global GDP and 55% global carbon emissions. The carbon leakage between China and G7 is a crucial issue in achieving the synergetic emission abatement globally. The motivation of this study is to evaluate the embodied carbon transfer between China and G7 in the trade between 2000 and 2014, and investigate the driving factors that impact the embodied carbon trend. A multiregional input–output (MRIO) model based on the WIOD database is constructed, and a structural decomposition analysis (SDA) is employed. The results indicate that China plays the role of net exporter of embodied carbon in trade with G7, which mainly flows to the US (5825.67 Mt), Japan (3170.36 Mt) and Germany (1409.93 Mt). However, China's embodied carbon exports to the G7 show an inverted U-shaped trend with a turning point after financial crisis, while the G7's embodied carbon exports to China continue to rise. The conclusion is that to achieve the climate goal of carbon neutrality, it is not enough to rely solely on the low-carbon transition on the production side, the demand side should also be adjusted. [ABSTRACT FROM AUTHOR]

To develop effective strategies to reduce CO2 emissions from electricity systems, this study accounted for carbon emissions from power systems (production, transmission, consumption) in Gansu Province based on life cycle theory. We used LMDI and SDA decomposition methods to analyze the driving force of carbon emissions and quantified the influence effect and action intensity of various factors on carbon emissions in corresponding links. Several results were found: (1) Direct carbon emissions during the stage of electricity production had the largest share of the entire electricity life cycle. (2) From the perspective of the cumulative contribution rate, electricity consumption and the electricity trade promoted carbon emissions in the stage of electricity production; the power structure, electricity efficiency, and fuel structure had opposite effects. (3) In the stage of electricity transmission, the higher the voltage level, the lower the net loss rate; high-voltage-level transmission lines effectively reduced the growth of implied carbon emissions. (4) Industrial restructuring and technological advances effectively offset the growth in carbon emissions due to population, economy, and electricity consumption. The results can provide a scientific basis for energy-saving and emission reduction policies in provincial government departments and the electric industry. [ABSTRACT FROM AUTHOR]

Providing sufficient daylight and view access to the outdoors is crucial to creating a productive work environment and ensuring employees' wellbeing and mental health in offices. To these aims, determining an optimum shading form can be challenging for designers. This study applied an 'external shading form-finding' and a novel 'dynamic view access assessment' method to find the optimum shading devices from 723 shading systems. Each system contains a typical louvre blade with two equidistant shading devices. These were externally fixed in front of a south-facing window with a dynamic interior blind, and were tested across three window-to-wall ratios. Optimum forms were selected according to LEED v4 daylight needs and unobstructed views. The results indicate that these proposed methods have the potential to support decision-making related to shading design, helping designers and architects to study the view quantitatively and combine its results with daylight assessment leading to improved building performance, employee mental health and wellbeing. [ABSTRACT FROM AUTHOR]

SDA (Space Domain Awareness) and SSA (Space Situational Awareness – SSA) have been defined as comprehensive knowledge of space objects and the ability to track, understand, and predict their future location. The purpose of the article is to present SSA initiatives to protect space systems, which are now recognized as fundamental assets of the sustainable development of each country. The destruction of even a part of the space infrastructure can have severe consequences for the security of citizens and economic activity. These systems assume the combination of all data obtained by various entities operating in space and Earth to create a common database. The SSA system was created based on the US military programme SDA (Space Domain Awareness); SSA and SDA are almost similar, but SDA is a new term replacing SSA, which existed previously. SDA is a better and improved SSA. Increasingly, the SSA programme is part of national and EU space strategies, but it is not yet possible to include it in international space law.

According to the characteristics of DNA programming, the cascaded nucleic acid amplification technology with larger output can overcome the problem of insufficient sensitivity of single nucleic acid amplification technology, and it combines the advantages of two or even multiple nucleic acid amplification technologies at the same time. In this work, a novel cascade signal amplification strategy with strand displacement amplification (SDA) and cascade hybridization chain reaction (HCR) was proposed for trace detection of hAAG and VEGF165. HAAG-induced SDA produced a large amount of S2 to open H2 on Polystyrene (PS) nanospheres, thereby triggering cascade HCR to form DNA dendritic nanostructures with rich fluorescence (FL) signal probes (565 nm). It could realize the amplification of FL signals for the detection of hAAG. Moreover, many doxorubicin (Dox) were loaded into the GC bases of DNA dendritic nanostructures, and its FL signal was effectively shielded. VEGF165 specifically bound to its aptamer to form G-quadruplex structures, which released Dox to produce a high FL signal (590 nm) for detection of VEGF165. This work developed a unique multifunctional DNA dendritic nanostructure fluorescence probe, and cleverly designed a new "On-off" switch strategy for sensitive trace detection of cancer markers. [Display omitted] • A multifunctional fluorescence probe of DNA dendritic nanostructure was developed. • A novel cascade signal amplification strategy with SDA and HCR was proposed for double targets. • A signal "On-off" switch is cleverly designed to detect dual targets by using aptamer and G-quadruplex structure. • This work shows a great contribution to simultaneous sensitive detection of cancer markers. [ABSTRACT FROM AUTHOR]

Large-scale education data are collected via complex sampling designs that incorporate clustering and unequal probability of selection. Multilevel models are often utilized to account for clustering effects. The probability weighted approach (PWA) has been frequently used to deal with the unequal probability of selection. In this study, we examine the performance of an intuitive, easy to implement approach named the sample distribution approach (SDA) that utilizes Markov Chain Monte Carlo (MCMC) methods and Bayesian inference. Our simulation design focused on clustering effects, represented by the Intraclass Correlation (ICC) and on the sample size of the cluster. We analyzed a large-scale educational assessment dataset (Early Childhood Longitudinal Study - Kindergarten 2011) to compute estimates for the simulation. Findings reveal that the SDA overall generated reliable posterior distributions of parameters and had small error variances. In addition, although design informativeness is important, the ICC and cluster sample size factors had little impact on the performance of this model-based approach. [ABSTRACT FROM AUTHOR]

Sda, produced by the B4GALNT2 enzyme, has been recognized as an important xenoantigen for pig-to-nonhuman primate xenotransplantation. However, little is known about Sda expression in pigs and its immunogenicity in xenotransplantation. In this study, peripheral blood mononuclear cells (PBMCs) were isolated from wildtype, GTKO (with high, moderate, and low Sda expression), GTKO/β4GalNT2KO, GTKO/CMAHKO, or GTKO/CMAHKO/β4GalNT2KO pigs. Anti-pig IgM/IgG binding and complement-dependent cytotoxicity (CDC) to pig PBMCs was measured by flow cytometry using pooled rhesus monkey sera (n=20) or human sera (n=20). As compared to wild-type pigs (n=12), GTKO pigs (n=17) had a significantly higher mean level of Sda expression on PBMCs and showed a greater individual difference in expression. Both the overall binding of monkey serum IgM/IgG antibody to GTKO pig PBMCs and CDC against these PBMCs decreased significantly with a progressive reduction in Sda expression, showing a clear dose-effect relationship. Both the monkey serum antibody binding and CDC decreased significantly after the additional deletion of Sda, whereas the binding of human serum antibody and CDC against the GTKO pig PBMCs were markedly reduced after the deletion of Neu5Gc in the pigs. In addition, anti-Sda antibody accounted for > 50% of the induced anti-non-Gal antibody at the time of rejection in two rhesus monkeys that received GTKO/hCD55 pig kidney xenotransplantation, and the anti-Sda antibody showed significant cytotoxic activity against GTKO pig cells. We conclude that both natural and induced anti-Sda antibodies play important roles in GTKO pig-to-rhesus monkey xenotransplantation, thus providing further evidence for GTKO/β4GalNT2KO pigs as the preferred organ source for rhesus monkeys as a preclinical model of xenotransplantation. [ABSTRACT FROM AUTHOR]

Most deep learning-based compressed sensing (DCS) algorithms adopt a single neural network for signal reconstruction and fail to jointly consider the influences of the sampling operation for reconstruction. In this paper, we propose a unified framework, which jointly considers the sampling and reconstruction process for image compressive sensing based on well-designed cascade neural networks. Two sub-networks, which are the sampling sub-network and the reconstruction sub-network, are included in the proposed framework. In the sampling sub-network, an adaptive fully connected layer instead of the traditional random matrix is used to mimic the sampling operator. In the reconstruction sub-network, a cascade network combining stacked denoising autoencoder (SDA) and convolutional neural network (CNN) is designed to reconstruct signals. The SDA is used to solve the signal mapping problem, and the signals are initially reconstructed. Furthermore, CNN is used to fully recover the structure and texture features of the image to obtain better reconstruction performance. Extensive experiments show that this framework outperforms many other state-of-the-art methods, especially at low sampling rates. [ABSTRACT FROM AUTHOR]

Nucleic acid tests (NATs) are considered as gold standard in molecular diagnosis. To meet the demand for onsite, point-of-care, specific and sensitive, trace and genotype detection of pathogens and pathogenic variants, various types of NATs have been developed since the discovery of PCR. As alternatives to traditional NATs (e.g., PCR), isothermal nucleic acid amplification techniques (INAATs) such as LAMP, RPA, SDA, HDR, NASBA, and HCA were invented gradually. PCR and most of these techniques highly depend on efficient and optimal primer and probe design to deliver accurate and specific results. This chapter starts with a discussion of traditional NATs and INAATs in concert with the description of computational tools available to aid the process of primer/probe design for NATs and INAATs. Besides briefly covering nanoparticles-assisted NATs, a more comprehensive presentation is given on the role CRISPR-based technologies have played in molecular diagnosis. Here we provide examples of a few groundbreaking CRISPR assays that have been developed to counter epidemics and pandemics and outline CRISPR biology, highlighting the role of CRISPR guide RNA and its design in any successful CRISPR-based application. In this respect, we tabularize computational tools that are available to aid the design of guide RNAs in CRISPR-based applications. In the second part of our chapter, we discuss machine learning (ML)- and deep learning (DL)-based computational approaches that facilitate the design of efficient primer and probe for NATs/INAATs and guide RNAs for CRISPR-based applications. Given the role of microRNA (miRNAs) as potential future biomarkers of disease diagnosis, we have also discussed ML/DL-based computational approaches for miRNA-target predictions. Our chapter presents the evolution of nucleic acid-based diagnosis techniques from PCR and INAATs to more advanced CRISPR/Cas-based methodologies in concert with the evolution of deep learning (DL)- and machine learning (ml)-based computational tools in the most relevant application domains., (© 2025. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Sda, produced by the B4GALNT2 enzyme, has been recognized as an important xenoantigen for pig-to-nonhuman primate xenotransplantation. However, little is known about Sda expression in pigs and its immunogenicity in xenotransplantation. In this study, peripheral blood mononuclear cells (PBMCs) were isolated from wildtype, GTKO (with high, moderate, and low Sda expression), GTKO/β4GalNT2KO, GTKO/CMAHKO, or GTKO/CMAHKO/β4GalNT2KO pigs. Anti-pig IgM/IgG binding and complement-dependent cytotoxicity (CDC) to pig PBMCs was measured by flow cytometry using pooled rhesus monkey sera (n=20) or human sera (n=20). As compared to wild-type pigs (n=12), GTKO pigs (n=17) had a significantly higher mean level of Sda expression on PBMCs and showed a greater individual difference in expression. Both the overall binding of monkey serum IgM/IgG antibody to GTKO pig PBMCs and CDC against these PBMCs decreased significantly with a progressive reduction in Sda expression, showing a clear dose-effect relationship. Both the monkey serum antibody binding and CDC decreased significantly after the additional deletion of Sda, whereas the binding of human serum antibody and CDC against the GTKO pig PBMCs were markedly reduced after the deletion of Neu5Gc in the pigs. In addition, anti-Sda antibody accounted for > 50% of the induced anti-non-Gal antibody at the time of rejection in two rhesus monkeys that received GTKO/hCD55 pig kidney xenotransplantation, and the anti-Sda antibody showed significant cytotoxic activity against GTKO pig cells. We conclude that both natural and induced anti-Sda antibodies play important roles in GTKO pig-to-rhesus monkey xenotransplantation, thus providing further evidence for GTKO/β4GalNT2KO pigs as the preferred organ source for rhesus monkeys as a preclinical model of xenotransplantation.

The System of Environmental-Economic Accounting - Ecosystem Accounting (SEEA-EA) is a spatially-based, integrated statistical framework for organizing biophysical information about ecosystems, measuring ecosystem services (ES). Water flow regulation ES and biophysical modeling are among the main topics in the individual ES part of the SEEA-EA framework and flood regulation ES is one of the important services. Characterizing and assessing flood regulation is a challenging task as both assessment and accounts of this ES need various data which are usually not available through direct or indirect measurements, therefore modeling approaches of water regulation are much needed. Despite growing attention and studies using hydrologic models to assess and/or map flood regulation ES, the accounting of this service is still not well developed. In this paper, we present an approach for accounting flood regulation at a local scale using ArcSWAT modeling. It is based on the results of flood regulation ES assessment, where modeling results are used to quantify the ES indicators and delineate the service providing areas (SPA) and service demand areas (SDA). The actual flow of flood regulation is calculated as a ratio between ES demand and ES potential and it represents the area of SPA which corresponds to the demand for flood regulation represented by SDA. The results show that predominant flood regulations ES supply is provided by the forest ecosystem as well as the actual flow. The accounting of flood regulation is strongly determined by ecosystem extent mapping. The CORINE Land Cover (CLC) provides the most appropriate and available data for mapping ecosystem extent at smaller scales. However, at a larger scale, it is too coarse and the combination of Mapping and Assessment of Ecosystems and their Services (MAES) national ecosystem mapping gives better results. [ABSTRACT FROM AUTHOR]

China is committed to achieving the goals of "peak carbon and carbon neutrality," and the carbon dioxide emissions generated in the energy utilization process mainly come from industrial and energy systems. This paper used structural decomposition analysis (SDA) and input-output analysis to study the structural emission reductions in China's industrial and energy systems in 2007–2015. The results revealed that the final demand effect was the main factor promoting the growth of energy-related CO2 emissions and that the energy intensity effect played a weak role in promoting the growth of energy-related CO2 emissions. However, the energy structure effect and input structure effect reduced energy-related carbon emission growth. We found that for energy systems, the emission reduction effects of blast furnace gas, raw coal, refinery dry gas, and natural gas were obvious, while those of crude oil, gasoline, fuel oil, and kerosene were not obvious. For industrial systems, the tertiary industry played a major role in the final demand effect, followed by the secondary industry, and the primary industry in turn. This paper provides a theoretical basis and practical guidance for the carbon peak and carbon neutrality goals of China's energy systems and industrial systems. [ABSTRACT FROM AUTHOR]

The approximate greatest common divisor problem (ACD) and its variants have been used to construct many cryptographic primitives. In particular, the variants of the ACD problem based on Chinese remainder theorem (CRT) are being used in the constructions of a batch fully homomorphic encryption to encrypt multiple messages in one ciphertext. Despite the utility of the CRT-variant scheme, the algorithms that secures its security foundation have not been probed well enough.

Klinefelter syndrome (KS), also known as 47, XXY, is characterized by a distinct set of physiological abnormalities, commonly including infertility. The molecular basis for Klinefelter-related infertility is still unclear, largely because of the cellular complexity of the testis and the intricate endocrine and paracrine signaling that regulates spermatogenesis. Here, we demonstrate an analysis framework for dissecting human testis pathology that uses comparative analysis of single-cell RNA-sequencing data from the biopsies of 12 human donors. By comparing donors from a range of ages and forms of infertility, we generate gene expression signatures that characterize normal testicular function and distinguish clinically distinct forms of male infertility. Unexpectedly, we identified a subpopulation of Sertoli cells within multiple individuals with KS that lack transcription from the XIST locus, and the consequence of this is increased X-linked gene expression compared to all other KS cell populations. By systematic assessment of known cell signaling pathways, we identify 72 pathways potentially active in testis, dozens of which appear upregulated in KS. Altogether our data support a model of pathogenic changes in interstitial cells cascading from loss of X inactivation in pubertal Sertoli cells and nominate dosage-sensitive factors secreted by Sertoli cells that may contribute to the process. Our findings demonstrate the value of comparative patient analysis in mapping genetic mechanisms of disease and identify an epigenetic phenomenon in KS Sertoli cells that may prove important for understanding causes of infertility and sex chromosome evolution. [ABSTRACT FROM AUTHOR]

Snakes are characterized by distinct foraging strategies, from ambush to active hunting, which can be predicted to substantially affect the energy budget as a result of differential activity rates and feeding frequencies. Intense foraging activity and continuously upregulated viscera as a result of frequent feeding leads to a higher standard metabolic rate (SMR) in active than in ambush predators. Conversely, the costs of digestion (Specific Dynamic Action—SDA) are expected to be higher in ambush predators following the substantial remodelling of the gut upon ingestion of a meal after a long fasting period. This prediction was tested on an interspecific scale using a large multispecies dataset (> 40 species) obtained from published sources. I found that the metabolic scope and duration of SDA tended to reach higher values in ambush than in active predators, which probably reflects the greater magnitude of postprandial physiological upregulation in the former. In contrast, the SDA energy expenditure appeared to be unrelated to the foraging mode. The costs of visceral activation conceivably are not negligible, but represent a minor part of the total costs of digestion, possibly not large enough to elicit a foraging-mode driven variation in SDA energy expenditure. Non-mutually exclusive is that the higher costs of structural upregulation in ambush predators are balanced by the improved, thus potentially less expensive, functional performance of the more efficient intestines. I finally suggest that ambush predators may be less susceptible than active predators to the metabolic 'meltdown effect' driven by climate change. [ABSTRACT FROM AUTHOR]