Lynch syndrome (LS) is an inherited cancer predisposition disorder associated with an elevated risk of various epithelial cancers. Despite sharing the same pathogenic variant (PV), Lynch syn-drome variant heterozygotes (LSVH) exhibit considerable phenotypic variability in cancer risk. The role of Human Leukocyte Antigen (HLA) in modifying cancer risk prompted our investiga-tion into whether HLA variations act as genetic modifiers influencing age at cancer diagnosis in a unique cohort of LSVH carrying a PV in the hMLH1 gene in South Africa. Within our extensive LS cohort, 426 individuals carried the same hMLH1 PV (MLH1:c.1528C>T). We selected 100 indi-viduals with the greatest diversity in age at cancer diagnosis and the oldest unaffected individu-als for high-throughput HLA genotyping of 12 HLA class I and II loci using next-generation se-quencing. Statistical analyses employed Kaplan-Meier survival analyses with Logrank tests and Cox proportional hazards. Following the robust application of statistical correction methods, six HLA alleles (3.2%) were significantly associated with a young age at cancer diagnosis. Notably, HLA-B*15:17 and HLA-DPB1*55:01 correlated significantly with very young colorectal cancer (CRC) diagnosis (Mean age: 21y [17-25]; HR = 71.59; q

The African continent has the highest prevalence of hypertension globally, with South Africa reporting the highest prevalence in Southern Africa. While the influence of genetic variability in the pathogenesis of hypertension is well described internationally, limited reports are available for African populations. This study aimed to assess the association of genetic variants and essential hypertension in a cohort of two ethnic South African population groups. Two hundred and seventy-seven hypertensive and one hundred and seventy-six normotensive individuals were genotyped for 79 variants. Genotyping was performed using the Illumina GoldenGate Assay and allele-specific polymerase chain reaction. The association of variants was assessed using the Fisher Exact test under the additive and allelic genetic models, while multivariate logistic regression was used to predict the development of hypertension. Five variants (CYP11B2 rs179998, AGT rs5051 and rs699, AGTR1 rs5186 and ACE rs4646994) were significantly associated with essential hypertension in the cohort under study. Furthermore, AGTR1 rs5186 and AGT rs699 were identified as risk factors for the development of hypertension in both ethnic groups. In two ethnic South African populations an association was observed between Renin-Angiotensin-Aldosterone System (RAAS) related genes and the development of hypertension.

Postpartum haemorrhage (PPH) is a significant cause of maternal morbidity and mortality worldwide, particularly in low-resource settings. This study aimed to develop a predictive model for PPH using early risk factors and rank their importance in terms of predictive ability. The dataset was obtained from an observational case-control study in Northern Rwanda. Various statistical models and machine learning techniques were evaluated, including logistic regression, logistic re-gression with elastic-net regularisation, Random Forest, Extremely Randomized Trees, and gradient boosted trees with XGBoost. Random Forest emerged as the best predictive model for PPH across three different train-test data partitions. The important predictors identified in the study were haemoglobin level during labour and maternal age. However, there were differences in PPH risk factor importance in different data partitions, highlighting the need for further investigation. These findings contribute to understanding PPH risk factors, highlight the importance of considering different data partitions and implementing cross-validation in predictive modelling, and emphasise the value of identifying the appropriate prediction model for the application. Effective PPH pre-diction models are essential for improving maternal health outcomes on a global scale. This study provides valuable insights for healthcare providers to develop predictive models for PPH to identify high-risk women and implement targeted interventions

Pancreatic cancer is an intractable disease with the worst prognosis of all cancers. The currently used treatment regimens do not significantly impact patient survival, and therefore, effective treatment strategies are urgently needed. Drug repurposing, which identifies new indications for existing and approved drugs, has proven to be a promising approach to anti-cancer drug discovery. Indeed the antihelmintic drug, pyrvinium pamoate has shown promise as an anti-pancreatic cancer drug, but to date, the inhibition of mitochondrial function is the only mechanism of action described in pancreatic cancer. This study showed, using pancreatic cancer 2D cell cultures and 3D spheroids, that pyrvinium pamoate exhibited short- and long-term cytotoxicity, inhibited epithelial-to-mesenchymal transition and cell invasion and migration. Mechanistically, pyrvinium pamoate induced DNA damage, inhibited the PI3K/AKT cell survival pathway, and triggered cell cycle arrests, as well as apoptotic and autophagic cell death. Importantly, pyrvinium pamoate acted synergistically with the first-line drug, gemcitabine in 2D and 3D pancreatic cancer cell culture models. This study provided evidence that pyrvinium pamoate is effective as a single agent and in combination with gemcitabine for the treatment of pancreatic cancer.

Managing a portfolio whose value closely tracks an index by trading only in a subset of the index constituents involves an NP-hard optimisation problem. In the prior literature, it has been suggested to solve this problem using sequential Monte Carlo (SMC, a.k.a. particle filter) methods. However, this literature does not take transaction costs into account, although transaction costs are the primary motivation for attempting to replicate the index by trading in a subset, rather than the full set of index constituents. This paper extends the SMC approach to index tracking to allow for proportional transaction costs and implements this extended method on empirical data for a variety stock indices. In addition to providing a more practically useful tracking strategy by allowing for transaction costs, we find that including a penalty for transaction costs in the optimisation objective can actually lead to better tracking performance.

Wetlands play a crucial role not only in providing ecological services but also in enriching the cultural and spiritual life of human society. Despite this, their cultural values have often been overlooked. The formal recognition of cultural values began with the Ramsar Convention in the 1970s, which acknowledged wetlands as resources of great economic, cultural, scientific, and recreational value. The wetlands of Majuli are of profound cultural and socio-cultural importance, particularly in terms of religious and spiritual significance, as well as recreational value. This study examines the cultural services provided by the wetland ecosystem of Majuli, focusing on its significance in the local human-environment nexus. Utilizing a qualitative approach with quantitative aspects, data was collected from primary sources through observation, interviews, and group discussions, along with secondary sources such as books, journals, and web portals.

In this paper, the integrated performance of a modular biomass boiler with an existing industrial Rankine steam heat and power cycle and a supplementary supercritical-CO2 (sCO2) Brayton cycle is analyzed. The aim is to leverage the high efficiency supplementary sCO2 cycle to increase net generation and energy efficiency from the existing biomass boiler. Two sCO2 heater configurations situated within the flue gas flow path are investigated, namely a single convective-dominant heater, and a dual heater configuration with a radiative and a convective heater. A quasi-steady-state 1D model was developed to simulate the integrated cycle, including detailed component characteristics for the Rankine and Brayton cycles. The model solves the mass, energy, momentum, and species balance equations. The system is analyzed for three cases: (i) the existing Rankine cycle without the sCO2 integration, (ii) with the single convective-dominant sCO2 heater configuration, and (iii) the dual sCO2 heater configuration. The results show the required rate of overfiring for the sCO2 configurations, with a 15.3% increase in fuel flowrate resulting in an additional 21.2% in net power output. The model quantifies the impact of the sCO2 heaters, with reduced heat uptakes for downstream boiler heat exchangers. Furnace water wall heat uptake increased due to overfiring, offsetting the reduced heat uptakes at downstream evaporative heat exchangers. The dual configuration has more impact on Rankine cycle operation due to the radiative sCO2 heater placement in front of the second superheater, absorbing some of the direct radiation from the furnace.

Historic expeditions are events that are flavored by exploratory, scientific, military or geographic characteristics. Such events are often documented in literature, journey notes or personal diaries. A typical historic expedition involves multiple site visits and their descriptions contain spatiotemporal and attributive contexts. Expeditions involve movements in space that can be represented by triplet features (location, time and description). However, such features are implicit and innate parts of textual documents. Extracting the geospatial information from these documents requires understanding the contextualized entities in the text. To this end, we developed a semi-automated framework that has multiple Information Retrieval and Natural Language Processing components to extract the spatiotemporal information from a two-volumes historic expedition gazetteer. Our framework has three basic components, namely, the Text Preprocessor, the Gazetteer Processing Machine and the JAPE (Java Annotation Pattern Engine) Transducer. We used the Brazilian Ornithological Gazetteer as an experimental dataset and extracted the spatial and temporal entities from entries that refer to three expeditioners’ site visits and mapped the trajectory of each expedition using the extracted information. Finally, one of the mapped trajectories was manually compared with a historical reference map of that expedition to assess the reliability of our framework. The reference map was manually prepared in previous research work by others.

The electric vehicle (EV) industry is experiencing rapid growth, accompanied by continuous advancements in charging infrastructure to satisfy the rising need for fast and reliable charging. Particularly, the focus has shifted towards EV fast charging (EVFC) and its impact on the power grid. This paper presents a comprehensive analysis and survey of scholarly literature and projects conducted in this field over the past decade. The findings highlight the rising demand for EVFC and the need to address its potential adverse effects on the power grid. However, there is a noticeable lack of clear research guidance regarding charging time. To tackle these challenges and pave the way for future solutions, extensive research on DC fast charging, ultra-fast charging, and the integration of vehicle-to-grid (V2G) systems is required. This review paper thoroughly investigates the development of fast charging technology for electric vehicles (EVs), including its advantages and comparative analyses from various perspectives. Furthermore, it delves into the advancements in DC fast charging infrastructure, emphasizing charging standards and control modes. The study also investigates different categories of battery chargers for both on-board and off-board charging. Additionally, it explores the classification of DC-DC converters in the context of DC fast charging stations, discusses control strategies for EV systems, identifies existing challenges, and outlines future trends in EV fast charging.

The information on the land use and soil conservation practice based on year 2006, 2010 and 2014, hence offering an opportunity to model the impacts of land use change on erosion, deposition and surface water runoff. Limitation in the use of hydrological models had been their inability to handle the large amount of input data that describe the heterogeneity of the natural system. In this study, a procedure that takes into account soil conservation practice based on the land use change, the response of soil erosion and sediment export from the George Town Conurbation catchment area, and average annual sediment yields were estimated for each grid cell of the watershed to identify the critical erosion areas of rural and urban planning proposes. Average annual sediment yield and data on a grid basis estimated using Universal Soil Loss Equation (USLE) and an emerging technology represented by Geographic Information System (GIS) used as a tool to produce a map for erosion rate. The changing of the land use from forest to agriculture and then to an urban area is a challenging task to research on land use demand for population, and environmental impact assessment is important for the planning of natural resources management, allowing research the modification of land use properly and implement more sustainable for long term management strategies. The challenge is to formulate strategies that would promote an integrated approach to the land use planning at an appropriate level as to address the issues that arose. Modelling for creating urban growth boundary for the George Town Conurbation must have to be controlled surface runoff and soil loss and sediment export from land use of the George Town Conurbation catchment.

Droughts have negative impacts on agricultural productivity and economic growth. Effective monitoring and accurate forecasting of drought occurrences and trends are crucial for minimizing drought losses and mitigating their spatial and temporal effects. In this study, trend dynamics in monthly total rainfall time series measured at Cape Town International Airport were analyzed using Mann-Kendall (MK) test, Modified Mann-Kendall (MMK) and innovative trend analysis (ITA) were examined. Additionally, we utilized hybrid prediction method that combined the model with the complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN) technique, the autoregressive integrated moving average (ARIMA) model, the long short-term memory (LSTM) network (i.e. CEEMDAN-ARIMA-LSTM) to forecast SPI values of 6-, 9-, and 12-months using rainfall data between 1995 and 2020 from Cape Town International Airport meteorological rainfall stations. The results demonstrate the following essential points: (1) The trend analysis results of the total monthly rainfall values indicate a significant decreasing trend with the negative z-score (MK= -3.7541 and MMK= - 4.0773). ITA also indicated a significant downwards trend of rainfall in the study area. (2) As the forecasting horizon increases, the prediction accuracy of the models and CEEMDAN-combined models gradually improves, reaching their optimum performance at the 12-month horizon. (3) CEEMDAN efficiently stabilizes time-series data, resulting in greater prediction accuracy in the hybrid model compared to individual models at all timescales. (4) The RMSE and R2 values for the hybrid CEEMDAN-ARIMA-LSTM model at a 12-month forecasting horizon are 0.042 and 0.995, demonstrating the applicability of this hybrid approach for drought forecasting.

This research paper examines the effects, advantages, challenges, and economic aspects of a research town. The study concludes that inclusion and diversity not only constitute fundamental values but also serve as crucial drivers of business success and sustained competitiveness. Universities play a central role in shaping the prosperity of the research town by functioning as knowledge hubs, fostering collaboration, nurturing talent, and contributing to the broader innovation ecosystem. The symbiotic relationship between universities and industries within the cluster establishes a dynamic and resilient environment for research and development. The presence of startups within the research cluster introduces novel ideas, enhancing the overall vibrancy and competitiveness of the local economy. In an era where social media algorithms increasingly influence people's choices, the potential for foreign interference emerges as a significant threat.

Although mammography has been the gold standard for early detection of breast cancer, if a woman has dense breast tissue, a false negative diagnosis may occur. Breast ultrasound, whether hand-held or automated, is a useful adjunct to mammography but adds extra time and cost. The primary aim was to demonstrate that our second-generation Aceso system, which combines full-field digital mammography (FFDM) and automated breast ultrasound (ABUS) in a single platform, is able to produce improved quality images that provide clinically meaningful results. Aceso was first tested using two industry standards: a CDMAM phantom to assess the FFDM images; and the CIRS 054GS phantom to evaluate the ABUS images. In addition, 25 women participated in a clinical trial: 14 were healthy volunteers while 11 were patients referred by the breast clinic at Groote Schuur Hospital. The CDMAM phantom results showed the FFDM results were better than EUREF’s standard of “acceptable” and were approaching “achievable”. The ABUS results showed lateral and axial spatial resolution of 0.5 mm and adequate depth penetration of 80 mm. Our second-generation Aceso system, with its improved quality of clinical FFDM and ABUS images, has demonstrated its potential for early detection of breast cancer in a busy clinic.

Empowering women and promoting gender equality is crucial for accelerating sustainable development in fragile countries, including the Democratic Republic of Congo (DRC). However, there is scarce existing knowledge or understanding of the factors determining women’s empowerment in these contexts. We aimed to assess women's empowerment and determine its associated factors in Kinshasa, DRC. We analyzed data from the 2021 Performance Monitoring Assessment (PMA) survey. A sample of 1,365 women of childbearing age was retained for this study. Twenty empowerment items related to household decision-making, contraception use, and husband/partner influence were considered. We calculated the average women’s empowerment index (aWEI), identified the women empowerment variables using principal component analysis (PCA), and determined the associated factors for the first three principal components through the performance of multivariate binary logistic regression. In Kinshasa, the overall aWEI was estimated at 0.65. It was low for household decision-making (0.34) and high for husband/partner influence domains (0.93), respectively. Three principal components were identified and named, including the absence of threats, control of sexuality, and participation in decision-making. The factors associated with these components were having internet access, being in free union with a partner, being aged 40-49 years, and residing in a non-slum area. Increasing access to information would enable women in Kinshasa to make strategic decisions about their lives, benefiting themselves and others.

The use of new assistive technologies in general, and Socially Assistive Robots (SAR) in particular is becoming increasingly common for supporting people’s health and well-being. However, it still faces many issues regarding long-term adherence, acceptability and utility. Most of these issues are due to design processes that insufficiently take into account the needs, preferences and values of intended users. Other issues are related to the currently very limited amount of long-term evaluations, performed in real world settings, for SAR. This study presents the results of two regional projects that consider as a starting hypothesis that the assessment in controlled environments and/or with short exposures may not be enough in the design of a SAR deployed in a retirement home and the necessity of designing for and with users. Thus, the proposed methodology has focused in use cases definitions that follow a human-centred and participatory design approach. The main goals have been facilitating system acceptance and attachment by involving stakeholders in the robots design and evaluation, overcoming usage barriers and considering user’s needs integration. The implementation of the first use case deployed and the two-phase pilot test performed in the retirement home are presented. In particular, a detailed description of the interface re-design process based on improving a basic prototype with users’ feedback and recommendations is presented together with main results of a formal evaluation that has highlighted the impact of changes and improvements addressed in the first redesign loop of the system.

This paper presents a novel approach to designing beam codebooks for downlink multiuser hybrid multiple input multiple output (MIMO) wireless communication systems, leveraging multi-agent reinforcement learning (MARL). The primary objective is to develop an environment-specific beam codebook composed of non-interfering beams, learned by cooperative agents within the MARL framework. Machine learning (ML) based beam codebook design for downlink communications have been based on channel state information (CSI) feedback or only reference signal received power (RSRP) consisting of an offline training and user clustering phase. In massive MIMO, the full CSI feedback data is of large size and is resource-intensive to process, making it challenging to implement efficiently. RSRP alone for a stand-alone base station is not a good marker of the position of a receiver. Hence, in this work, uplink CSI estimated at the base station along with feedback of RSRP and binary acknowledgment of the accuracy of received data is utilized to design the beamforming codebook at the base station. Simulations using sub-array antenna and ray-tracing channel demonstrate the proposed system’s ability to learn topography-aware beam codebook for arbitrary beams serving multiple user groups simultaneously. The proposed method extends beyond mono-lobe and fixed beam architectures by dynamically adapting arbitrary shaped beams to avoid inter-beam interference, enhancing overall system performance. This work leverages MARL’s potential in creating efficient beam codebooks for hybrid MIMO systems, paving the way for enhanced multiuser communication in future wireless networks.

Background Neisseria gonorrhoeae can acquire antimicrobial resistance (AMR) through horizontal gene transfer (HGT) from other Neisseria spp. such as commensals like Neisseria subflava. The prevalence of Neisseria subflava in the oropharynx is close to 100%. Low doses of antimicrobials in food could select for AMR in N. subflava, which could then be transferred to N. gonorrhoeae. In this study, we aimed to determine the lowest concentration of ciprofloxacin that can induce ciprofloxacin resistance (minimum selection concentration – MSC) in N. subflava. Methods Neisseria subflava Co000790/2 was serially passaged on GC agar plates containing ciprofloxacin concentrations ranging from 1:100- to 1:10,000-below its ciprofloxacin MIC (0.006 µg/ml) for six days. Results After 6 days of serial passaging at ciprofloxacin concentrations 1/100th of the MIC, 24 colonies emerged on the 0.06 µg/ml ciprofloxacin plate. Their ciprofloxacin MICs were between 0.19 to 0.25 µg/ml, and whole genome sequencing revealed a missense mutation T91I in the gyrA gene, which has previously been found to cause reduced susceptibility to fluoroquinolones. Conclusion The N. subflava MSCde novo was determined to be 0.06 ng/mL or 1:100 below the MIC. The implications of this finding are that the low concentrations of antibiotics found in certain environmental samples and even the food we eat may be able to select for ciprofloxacin resistance in N. subflava.

Australian regional areas are now receiving significant numbers of migrants from the African continent. Predominantly Anglo-Saxon communities perceive these ‘newcomers’ as physically and culturally different. Asking, however, how African migrants themselves construct relationships with local communities and build a sense of belonging in regional and rural areas is a very different question. This paper explores South Sudanese migrants’experiences conceptualising their sense of belonging in a small county town: Castlemaine, Victoria. Focus group discussions show that even with the welcoming atmosphere and support from the local community, South Sudanese migrants are still attracted to metropolitan environments that have greater diversity, feeling more at home in such settings. Using the theoretical background of a stranger, this paper argues the cities allow strangers be un-noticed letting them feel at ‘home’. Findings from the study show settings with greater diversity encourage negotiating difference openly and easing power imbalances among different groups.Finally, the locality of Castlemaine, within easy commuting distance to metropolitan Melbourne and suburbs, is considered in relation to hypermobility reducing the capacity to construct ‘bridging capital’ within such local communities.

The purpose of this study is to assess the solid waste management status and practice in Sendafa town, Oromia regional state residents. In order to achieve this goal, the researcher intends to employ both primary and secondary data from the Sendafa town municipality. With the aid of multi-cluster sampling and a purposive sampling method, the researchers chose a sample size of 398 people and 10 interview responders. To utilize a systematic sampling technique at intervals of residences, individual samples were chosen. Quantitative data was cleaned and analysed using STATA software. A multiple linear regression model and logistic regression other descriptive statistics methods were then used to change the results. The qualitative data were imported, coded, and thematised using ATLAS.ti.9 in order to prepare respondents' interviews for analysis. The findings indicate that residents' poor solid waste management practices are a result of a lack of awareness, low family income transportation issues, issues with waste collectors, a lack of a sense of responsibility and belonging, and a failure to enforce current solid waste management laws. Solid waste accumulates near roads, bridges, and residential areas that are close to landfills, contaminating the area and leading to diseases like TB and Asthma (and other related health issues in children and adults who live there). Thus, researcher recommends that to have sustainable solid waste management the town administrators should have plan to develop awareness creation symposium or panel of discussion, resolve transportation issues, monitor and guide the routine activities of waste collectors, develop sense of belongingness for themselves and for the community, develop integrated solid waste land fill projects and working with all stakeholders like NGO and health institution will minimize the adverse effect of improper solid waste management. Keywords: Solid Waste, Status of Solid Waste Management, Land fill site suitability

Vaccination attitudes among healthcare workers (HCWs) is a vital factor for measuring their level of vaccination uptake and intention to recommend vaccinations to their patients. To our knowledge, no study has been conducted in South Africa to assess hesitancy to influenza vaccines among HCWs. We used questionnaire adapted from Betsch and colleagues to conduct an online and face-to-face cross-sectional study among HCWs at the start of COVID-19 vaccine roll-out prior to the flu season. Main outcome was influenza vaccine hesitancy. We used multivariate logistic regression to assess predictors of influenza vaccine hesitancy. Of 401 participants, 64.5% were women, 49.2% nurses, and 12.5% physicians. A total of 54.9% were willing to accept vaccination, 20.4% were undecided, and 24.7% intended to refuse. Older participants above 17-25 years and physicians were likely to receive the vaccine. Key predictors of vaccine acceptance were confidence in the effectiveness, consideration of benefits and risks, and willingness to be vaccinated to protect others. Influenza vaccine hesitancy was highest in those who did not trust that influenza vaccines are safe. For future flu seasons, tailored education programs targeting younger HCWs and more information about the composition of flu vaccines would be vital to improve vaccine uptake.

The stormwater drainage problem is one of the major challenges facing in Shire Endaslasse town, Ethiopia. In a town, Street flooding and overtopping drainage system problems are occurring during the rainy season. This causes ponding which poses difficulties in ease of transportation and it hinders the day-to-day activity of the people. So, the study focuses on the performance of the stormwater drainage system in Shire Endaslasse town using Arc GIS and SWMM5.1. For this study, the primary data were collected by field surveys and interviews with the council body. Simulation results for storm events show that in some of the drainage systems in different regions of Shire Endaslasse town have flooded. During the field observation, the drainage structures are filled with solid wastes, inadequate inlet and outlet structures and some of the top element of the manhole have been broken this may cause a problem of aesthetic and healthy at large it may increase flood risk. The flooding risk in the drainage systems is very high due to the drainage system is undersized to cope with the current rainfall rates, but also is very limited to face the upcoming predicted rainfall.

Background: Bacteria can survive antibiotic exposure by mechanisms like tolerance without a shift in antimicrobial susceptibility. In this study, we investigated the presence of tolerance to three antimicrobials, ceftriaxone (CRO), azithromycin (AZM), and ciprofloxacin (CIP), in clinical isolates and WHO reference panel of N. gonorrhoeae and explored the prevalence between urogenital and anorectal infection sites. Methods: We examined 66 N. gonorrhoeae clinical isolates, evenly divided between anorectal and urogenital infection sites, using a modified tolerance disk (TD test) for three antibiotics. The isolates underwent a three-step incubation process wherein the isolates were exposed to an antibiotic disc for 20 hours of incubation (Step I), followed by the replacement of the antibiotic disc with a nutrient disc for overnight incubation (Step II) and additional overnight incubation with extra nutrients (Step III). Results: Four isolates were lost due to contamination. Of 62 clinical isolates, 7 exhibited tolerance to AZM, with 6 from anorectal and 1 from urogenital sites (p = 0.0496). Tolerance to CRO was observed in 11 isolates, which was significantly associated with the infection site, with 9 from the anorectum, and 2 from the urogenital site being tolerant (p = 0.02). Tolerance to CIP was found in 11 isolates, but was not significantly associated with the infection site. Tolerance was also detected in 8 (K, M, N, O, P, U, V, W) out of the 14 WHO (World Health Organization) reference strains, with varying patterns of tolerance to CRO (n=8), CIP (n=2) and AZM (n=1). Conclusion: This study identified CRO, AZM, and CIP tolerance in clinical Neisseria gonorrhoeae isolates. Significant variations in tolerance proportions between anorectal and urogenital infection sites, particularly for CRO, were observed. Additionally, tolerance was detected in WHO reference strains.

The quality of the environment affects human behavior, the micro-communities of human beings need creative thinking and ideas. Social environments have a significant impact on collective behaviors and social interactions. Nowadays achieving social indicators in housing with a sustainable approach is one of the goals that have been considered. The most important issue in the field of research is recognizing and examining the value of spaces in residential environments to achieve social life, in which it leads human to be social in public residential spaces. Paying attention to social relations with neighbors and people to create Social relationships are proportionate to the presence of individuals in their realm of life. The concept of neighborhood is being responsible for creating social relationships, influencing people living in the complex and community-based life. In this research, by satisfying the human need to communicate and interact with others, creating collective spaces in different scales such as commercial and recreational spaces in residential complexes, the presence of people in these spaces leads to the socialization of collective space and the factor in which the space achieves success. By explaining and identifying the components of socialization in the collective spaces of residential complexes, such spaces can be prepared for the presence of people in the space.

In recent years, technical processes for the sequestration of CO2 through industrial waste mineral carbonation have been explored and developed. There is a large portfolio of Carbon Capture, Uti-lisation and Storage (CCUS) techniques that have been employed on a laboratory and at pilot scale. These include geological storage, ocean storage and mineralisation by carbonate ores. In view of this, the main purpose of this research was to investigate and explore chemical variables, particularly ammonium salts as lixiviants for calcium mineral extraction from iron making slag. The slag in use was acquired from a Steel Mill in the Vaal Triangle Region in Gauteng, South Af-rica. The experimental test work was conducted using different ammonium lixiviants, namely, NH4NO3, NH4Cl and CH3COONH4 to understand the influence of anion type as well as possible differences in mechanisms of interactions. Lixiviant concentration as well as the reaction time were varied in this research study. The three selected ammonium based lixiviants showed different extents of calcium extraction owing to differences in the anion groups. NH4NO3, NH4Cl and CH3COONH4 were found capable of dissolving 50% to 80% of calcium from the selected slag for different molar concentrations. Anion type and leaching time also had significant influences on the leaching of calcium from the slag. Rapid pH degradation resulted in better calcium extraction ca-pabilities. This work has shown that the selected ammonium salts have a potential as lixiviants for calcium dissolution from iron making blast furnace slags. These lixiviants would therefore be important to consider during calcium mineral carbonation for CO2 sequestration.

A novel compressible real gas 1D finite volume thermofluid network modelling methodology is proposed that can be applied in the analysis of supercritical CO₂ (sCO2) power cycles. It is applied to simulate centrifugal compressor performance via a mean line approach that directly solves the mass, energy, and momentum balance equations for the discretized flow channels within the machine along with the associated loss models, component characteristics, and applicable compressible real gas equation of state. This can be integrated seamlessly with the rest of the power cycle components like pipes, valves, heat exchangers, etc., thereby eliminating the need for static performance maps and the associated difficulties to ensure similarity over the whole range of operation. This direct simulation of the internal flows also makes it possible to do integrated cycle design optimization that includes the geometry of the compressors, and to simulate fast transients for dynamic analysis. The methodology was applied to simulate well-documented air and sCO2 centrifugal compressors and compared the generated results with that of conventional thermofluid network incompressible and compressible ideal gas approaches. The results indicate that the proposed compressible real gas approach can capture the stagnation pressure changes and isentropic efficiencies with good accuracy for both cases over the whole range of mass flow rates and shaft rotational speeds. In contrast, the conventional thermofluid network incompressible and compressible ideal gas approaches are only applicable in selected regions of the fluid property regime and suffer from discretization errors and inappropriate treatment of the relationship between stagnation and static pressures. Furthermore, comparative analyses between the newly proposed approach and the traditional mechanical energy balance method are performed, showing that the latter approach needs to be discretized more finely through the compression process to correctly capture the polytropic compression path shape, whereas the former more accurately captures the stagnation pressure changes through the analyzed compressors with only a single increment per compressor component.

Everyone should therefore consistently get access to enough and safe water. The operation of the existing distribution network as well as the proper optimization and implementation of the new distribution systems are required for a sufficient and safe water supply. In Sekota town sufficient amount of water was not reached to the beneficiaries due to shortage of water at the source. The primary goal of this study was to evaluate the performance and optimize the existing Sekota water supply distribution system using Bentley Water GEMS.The system's hydraulic modeling is carried out by considering as a continuous supply system, and the evaluation procedure used the extended period simulation approach after calibration was done. Calibration is used to ensure the performance of the model using the observed pressure values. The output of the existing system shows pressure is very high means above the maximum pressure and velocity is very low at peak hour demand. The results of velocity and pressure before optimization have negative effect on the performance of the system. The number of pipes and junctions their velocities and pressures which were in admissible ranges are 15 and 42 pipes for velocities and zero and 59 junctions for pressure before and after optimization were evaluated respectively.

Improperly prepared fresh fruit and vegetable juices are recognized as an emerging cause of food borne illnesses. Therefore, this study was aimed at evaluating the microbiological safety of fresh fruit juices marketed in Debre-Markos town and their hygienic conditions of preparations. Thirty six fruit juices samples were collected from 6 cafés and restaurants of Debre-Markos town and analyzed for total aerobic viable bacterial count (TAVBC), total staphylococcal count (TSC), aerobic spore forming bacterial count (ASFBC), total coliform count (TCC), fecal coliform count (FCC), yeast and mould count (YMC). The spread plate method was used for the isolation of microorganisms on appropriate selective media. All isolates were characterized following standard methods. Bacterial and fungal species were isolated following standard methods. Questionnaires were distributed for 30 juice makers to obtain preliminary information on hygienic and safety practices of fruit juice makers. Results show that the mean TAVBC, ASFBC, TSC, yeast and mold, TCC and FCC of mango were 2.2±0.48x10⁶,0.13±0.04x10⁵ ,0.004x10⁵ ,1.1±0.2x10⁶ ,0.15±0.05x10⁵,5.7±3.73x10⁴ and 0.06±0.04x10⁴ cfu/ml respectively. The mean of TAVBC, ASFBC, TSC, YMC, TCC, and FCC of avocado juice were 3.6±0.6x10⁶, 0.08±0.02x10⁵, 0.27±0.07x10⁵, 1.2±0.4x10⁶, 0.02±0.01x10⁵, 6.46±3.7x10^4, and 0.2±0.1x10⁴ cfu/ml respectively. The bacterial isolates were identified as Staphylococcus aureus, Escherichia coli, Klebsiella spp. Bacillus cereus, Enterobacter spp., Enterococcous spp., Streptococcus spp., and Serratia spp. while the identities of the fungal isolates were Fusarium spp., Mucor spp. and Saccharomyces cerevisiae. The results also showed that the microbial loads of most of the fruit juices were higher than the specifications set for fruit juices sold in the Gulf region and other parts of the world. Most venders obtained fruit from the open market and all juice makers lacked special training in food hygiene and safety. Therefore, regular training and health education on food hygiene and safety is recommended for juice handlers to improve the quality of fresh fruit juices in the study area.

Encouraged by the administration the gentrification process has been useful in economic terms for the reactivation of socio-cultural fabrics of historic urban spaces in decline. What was initially considered an advantage has led to the touristification of historic centres, and in turn to the alter-ation of their original use. In these settings, the demographic void caused by increasingly shunning local identity has combined with pressure from excessive tourism and the obsolescence of heritage protection bodies in charge of conservation. Given the crisis affecting the definitions of the current system, this study aims to review the envi-ronmental agents of heritage value in relation to the processes of touristification and gentrification. Data obtained from different methodologies are analysed using a multidisciplinary database, a model which enables the analysis of the relevant information from the different interacting fields. The case study focuses on the historic town centre of Seville specifically between 2015 and 2020. Elements are defined as indicators for these processes and the analysis of the case study will com-prise the main results of this research.

Towns emerged as dynamic economic and political centers during the Middle Ages, giving rise to the emergence of new social classes. As a result of these functions, a new relationship began to be forged with the rural world, which supplied towns with foodstuffs that satisfied new social demands. Archaeobotanical analysis (carpology) allows us to understand the flow of cash crops by tracing seeds and fruits produced in the countryside that were consumed in and redistributed from the towns. The study of waterlogged contexts from medieval archaeological sites in the Kingdom of Galicia (Santiago de Compostela, Padrón, and Pontevedra) has provided a set of species that played a crucial role in the economy of the urban dwellers and that possibly were related to differential access or food preferences. Evidence for fruits (grapes, chestnuts, figs, apples, and cherries, among others), garden crops (melon), and cereals (foxtail millet, rye, naked wheat, and oat) has been documented. Broomcorn millet is particularly abundant, demonstrating that it was important for subsistence. Some of the species found (medlar and turnip/grelo) are novel in the archaeobotanical literature of the medieval period in the Iberian Peninsula.

There are many modern and traditional methods in valuing the performance of the company among them EVA, CVA are modern methods where as EPS, ROI, ROE etc. are some of the traditional methods. modern and traditional methods are not only used to check the performance of a company but it also used in investment decisions by the investors. Stern Stewart, managing partner of M/s Stern Stewart & Co. introduced a modified concept of economic profit in 1990 in the name of Economic Value Added (EVA) as measure of business performance and CVA is only a cash consideration in EVA. In this paper an attempt is made to study which method is used by the investors while taking the investment decisions i.e. traditional methods are modern methods. 100 respondents (Investors) are questioned and collected their views, we are assuming that there is no impact of traditional or modern methods while taking investment decisions by the investors.

Sustainable Development Goal (SDG) 6.2 sets an ambitious target of leaving no one without adequate sanitation by 2030. The key concern is the lack of local human and financial capital to fund the collection of reliable information to monitor progress towards the goal. As a result, national and local records may be telling a different story of the proportion of safely managed sanitation that counts towards achieving the SDGs. This paper unveils such inconsistency in sanitation data generated by urban authorities and proposes a simple approach for collecting reliable and verifiable information on access to safely managed sanitation. The paper is based on a study conducted in Babati Town Council in Tanzania. Using a smartphone-based survey tool, city health officers were trained to map 17,383 housing units in the town. A housing unit may comprise of two or more households. The findings show that 5% practice open defecation, while 82% of the housing units have some forms of sanitation. Despite the extensive coverage, only 31% of the faecal sludge generated is safely contained, while 64% is not. This study demonstrates the possibility of using simple survey tools to collect reliable data for monitoring progress towards safely managed sanitation in the towns of global south.

Objective: To evaluate the variables influencing the length of stay (LoS) for COVID-19 ICU patients at Tygerberg Hospital (Cape Town) and to identify the covariates that significantly influenced it and any potential risk factors associated with LoS. Methods and Results: Poisson, negative binomial (NB), Hurdle–Poisson, and Hurdle–NB regression models were used to model the LoS in this prospective cohort study. The fitted models were compared using the Akaike information criterion (AIC), Vuong’s test criteria, and Rootograms. Based on the chosen performance criteria, the NB model provided the best fit outperforming other candidate models. The baseline LoS count was 8 days. On average, antibiotics reduced LoS by 0.74-fold (95% CI 0.62-0.89) compared to not taking antibiotics. The second wave had a significant effect on the average LoS, which decreased by 0.36-fold (95% CI 0.14-0.93) compared to the first wave. Average LoS increased by 1.01-fold (95% CI 1.01-1.02) for every one-year increase in the age of the patient and by 1.02-fold (95% CI 1.01-1.03) for every 1 unit increase in neutrophils. A 1 ng/L increase in log (TropT) levels decreased the average LoS by 0.87-fold (95% CI 0.81-0.93) similarly, a unit increase in the PF ratio decreased the average LoS by 0.998-fold (95% CI 0.997-0.999) respectively. Conclusion: The study identified common clinical characteristics associated with length of stay in ICU for COVID-19 patients, including age at admission, PF ratio, neutrophils, TropT, Wave, and antibiotic use. These results can aid in identifying risk factors for increased length of stay, assist in healthcare systems planning, and aid in evaluating different models for analysing this type of data.

Histone deacetylases inhibitors (HDACi) have shown promising therapeutic outcomes in haematological malignancies such as leu-kaemia, multiple myeloma and lymphoma, with dis-appointing results in solid tumours when used as monotherapy. As a result, combination therapies either with radiation or other deoxyribonucleic acid (DNA) damaging agents have been suggested as ideal strategy to improve their efficacy in solid tumours. Numerous in vitro and in vivo studies have demonstrated that HDACi can sensitise malignant cells to both electromagnetic and particle types of radiation by inhibiting DNA damage repair. Although the radiosensitising ability of HDACi has been reported as early as 1990s, the mechanisms of radiosensitisation are yet to be fully understood. This review brings forth the various protocols used to sequence the administration of radiation and HDACi treatments in the different studies. The possible contribution of these various protocols on the ambiguity that surrounds the mechanisms of radiosensitisation is also highlighted.

Background: The COVID-19 pandemic is the global public health emergency concern and had an impact on the day to day life of individuals. Its effect on an individual’s mental health is significant to the extent of suicide. Objective: This study aimed to assess the magnitude of psychological problems and their associated factor among communities living in Dilla town in response to the pandemic. Methods: From Apr 1- Apr 15, 2020, a community-based cross-sectional study was conducted using multi-stage sampling techniques. Self-administered the questioner, Depression, Anxiety and Stress Scale (DASS-21), and logistic regression analysis (95% CI, p-value <0.05) was used. Results: This study included 445 respondents with a 94% non- response rate who was living in Dilla town. In total, 34.4% of respondents had a psychological problem (11.4 % mild and 23% moderate level of the psychological problem). Female, Greater secondary level of education, monthly income below 500 ETB, more than three family size, and wearing face mask were variables associated with the outcome variable (p < 0.05). Conclusions: Nearly one-third of the respondents had mild to moderate psychological among communities living in Dilla town. There is a need for mental health support on those identified groups of peoples to enhance their resilience in response to the pandemic.

Folk residence in the cold region of Northeast China is an important part of China's traditional folk residence, with significant geographical representation. In this paper, we take the residential compounds of villages and towns in the cold region of Northeast China as the research object, summarize four typical layout forms of residential compounds of villages and towns in the cold region of Northeast China, simulate the wind environment of compounds of different layout forms in winter by using the computer numerical simulation software Fluent, and then analyze and evaluate the wind environment of compounds by combining with the evaluation standard of wind speed ratio and considering the area of wind shadows, number of vortices and other factors.

Estimating the economic risks of climate shocks and climate stressors on spatially heterogeneous cities over time remain highly challenging. The purpose of this paper is to present a practical methodology to assess the economic risks of climate change in developing cities to inform spatially sensitive municipal climate response strategies. Building on a capital-based framework (CBF), spatially disaggregated baseline and future scenario scores for economic wealth and its exposure to climate change are developed for six different classes of capital and across 77 major suburbs in Cape Town, South Africa. Capital-at-risk was calculated by combining relative exposure and capital scores across different scenarios and with population impacted plotted against the major suburbs and the city’s 8 main planning districts. The economic risk assessment presented here provides a generic approach to assist investment planning and the implementation of adaptation options through an enhanced understanding of relative levels of capital endowment vis-à-vis relative levels of exposure to climate-related hazards over time. An informed climate response strategy in spatially heterogeneous cities need to include spatially sensitive estimates on capital-at-risk and populations disproportionally impacted by climate exposure over time. The economic risk assessment approach presented here helps in advancing to such a goal.

Infant mortality remains a major global concern. Sudden unexpected death in infancy (SUDI) is reported globally and in the Western Cape of South Africa it accounted for 40% of all infant deaths between 2012 and 2016. Research highlighting molecular typing of respiratory viruses in SUDI cases is lacking. A total of 116 PCR-positive human rhinovirus (HRV) and respiratory syncytial virus (RSV) swab samples collected from the lungs and trachea of SUDI cases admitted to Tygerberg Medico-legal Mortuary in Cape Town between 2015 and 2019 were included and underwent sequencing and phylogenetic analysis. Three distinct HRV species were identified; HRV-A (n=28), HRV-C (n=11), and HRV-B (n=4), including eight HRV-A, seven HRV-C and one HRV-B genotypes. For RSV, both RSV-A (n=5) and -B (n=5) were detected, but no RSV-A. After amino acid alignment indicating 20 amino acid duplication and nine substitutions, two BA9 genotypes were confirmed. This study describes the first molecular and phylogenetic characterisation of respiratory viruses in SUDI cases in South Africa. The rapid decline in viral viability in post-mortem samples and the retrospective study design employed for the current study did not allow for any correlations between viral genotypes and cause of death and future prospective studies should investigate temporality and specific viral strains associated with clinical disease severity.

South Africa’s internationally celebrated water legislation placed the responsibility for investing in water services at the door of the government. In recent years South Africa has struggled to invest adequately to keep up with growing demand for these services. The result is a suite of social, economic and environmental risks that are destabilising to the fiscus and the financial sector. This paper explored both operating and capital costs, and applied the ‘Beyond the Gap’ analysis to show that an additional 55% investment (R91 billion annually) is necessary to ensure South Africa meets its water policy goals. The analysis explores the factors that influence the investment amount and shows that a combination of policy choices and exogenous factors such as climate change could render the investment gap anywhere between 30% and 90% of the estimated current allocation to the water sector. The most significant savings are attributed to reducing the extent of “non-revenue water”, an energy transition away from coal, sharing of some water taps between (up to) five houses, reduced water allocations to agriculture, investments in invasive alien plant (IAP) clearing in water catchments above dams, and water demand management, capacity building and more efficient integration of different bulk water schemes. The study revealed important dependencies between capital and operating costs; where operating costs are ignored, the decay of water infrastructure is accelerated. Showing the contingency of investment needs on policy choices, places responsibility for attaining water policy goals and SDG 6 in the hands of a diverse set of actors. Quantifying the investment need also raises the critical question of how to raise the required investment. Recognising the need to balance risks to financiers with the widespread risks to households, companies and government when investment in water services is inadequate, South Africa is exploring a Monetary Architecture approach of inter-balance sheet relationships in an attempt to mobilise investment from new sources.

The present study took into account the influence of local cuisine in the restaurants awarded Michelin stars in Phuket Old Town, influenced by Chinese cultural diffusion to other cultures contributing to a unique culture in the Malay Peninsula. It sought to investigate components of local gastronomic tourism and perceived value towards the Michelin Guide’s assessment criteria of local cuisine in Phuket Old Town, delving into the relationship between these two factors. In particular, a structural equation model (SEM) was adopted to explore such a relationship, with an exploratory factor analysis (EFA) and a confirmatory factory analysis (CFA) to assess a measurement model of latent variables and accuracy and reliability of the structure. The study was conducted in the context of Phuket Old Town, Phuket Province, Thailand, renowned as a City of Gastronomy. The results demonstrated that the phenomenon of local cuisine in Phuket Old Town embodied the perceived value of local cuisine, origins, history, traditions, rituals, and unique lifestyles; particularly, the components of local gastronomic tourism reflected the significance of food products in the food industry, together with the organization of local cuisine activities and festivals. This finding contributed to an understanding of the reasons behind the perceived value among consumers traveling to this town to gain experiences of local cuisine in the restaurants awarded with Michelin stars. It could serve as a policy for improving food establishments’ quality and standards based on the specified criteria to foster sustainable gastronomic tourism in Thailand.

The aim of this study, therefore, provides information about Aflatoxin levels in raw cow’s milk in Injibara Town of Awi Administrative zone by using HPLC-FLD. A good linearity of standard calibration was found for AFM1 at a range of 0.5–7 µg/L. Regression coefficient (R2) values were 0.9999, whereas slope and intercept were 2.5278 and 0.1012, respectively. The average recoveries for the spiked samples were range from76.62– 90.98 % and the RSD values ranged between 2.55–7.36 %. The results showed that 15 % of samples (3 out of 20) were contaminated with AFM1 in the range of 0.046–0.22 µg/L. The average contamination level was 0.121 µg/L. The determined mean values of AFM1 in the collected milk samples were above the standard limit of the European Commission and lower than the level established by United States regulations. Further monitoring of Aflatoxin in milk samples from different regions of the country is justified to conclusively determine the actual safe/risks and possibly low Aflatoxins-risk milk production areas.

1) Background: Intellectual disability is more common in low- and middle-income countries than in high-income countries. Stigma and discrimination have contributed to barriers to people with intellectual disability accessing healthcare. As part of a larger study on caregiving of children with intellectual disability in urban Cape Town, South Africa, we interviewed a sub-group of families who had never used the intellectual disability services available to them, or who had stopped using them; 2) Methods: We employed a qualitative research design and conducted semi-structured interviews to explore the views and perspectives of parents and caregivers of children with intellectual disability who are not using specialised hospital services. We developed an interview guide to help explore caregivers’ and parents’ views; 3) Results: Results revealed that caregivers and parents of children with intellectual disability did not use the service due to financial difficulties, fragile care networks and opportunity costs, community stigma and lack of safety, lack of faith in services and powerlessness at effecting changes, and self-stigmatisation; 4) Conclusion: Current findings highlight a need for increased intervention at community level and collaboration with community-based projects to facilitate access to services, and engagement with broader issues of social exclusion.

Persistent post market quality evaluation helps produce clear information on the current quality status of the different brands of a given drug and hence introduces biopharmaceutically and therapeutically equivalent list of the products to the prescribers and users of it. This in turn facilitates access to essential medicines by breaking the high cost barrier imposed by few expensive brands of the product. This study was aimed at determining the quality and evaluating equivalence of doxycycline hyclate capsules and tablets in Jimma, Ethiopia. Ten brands of doxycycline hyclate capsules and tablets were tested for physic-chemical parameters. All investigated brands of doxycycline complied with the USP for dosage unifor¬mity, assay of active ingredient and single-point dissolution tests. One brand, D09 failed both hardness and friabilty tests. Comparisons of dissolution profiles applying fit factors confirmed that only brands D04, D06 and D07 had similarity with innovator. Ratio test approaches also showed significant variability existence between test products and comparators. This may question the product’s being categorized as a <biowaiver> to mean in-vitro dissolution evaluation suffices its market approval. This work, however, found equivalence problems between ‘comparators’ and interchangeability issues among doxycycline different brands already distributed in the market.

Background: Immunization prevents over 4-6 million deaths each year worldwide. Ensuring mother satisfaction is an important means of preventing the death of children caused by communicable diseases. However, in Ethiopia, there is paucity of evidence on maternal satisfaction with immunization services. Thus, this study is aimed at assessing the level of maternal satisfaction with childhood immunization services and associated factors among children’s caregivers. Methods: A facility-based cross-sectional study was conducted among 556 systematically selected children’s caregivers in public health facilities at Gondar Town from May through June, 2022. Data were collected using a pretested structured questionnaire. P≤ 0.25 during the bivariate binary logistic regression analysis was included in the multivariate analysis. From the multivariable analysis, variables with p ≤ 0.05 were declared statistically significant. Results: The prevalence of maternal satisfaction towards childhood immunization services was 69.3%(95%CI: 65.5, 73.1%). Of mothers, 45.3% had adequate knowledge, while 43.9% had favorable attitude. Mothers 19-24 years old [AOR = 5.29; 95%CI:2.58,10.86], mothers who waited less than one hour [AOR = 3.03; 95%CI: 1.92,4.77], mothers less than thirty minutes waiting in health facility[AOR=1.98;95%CI:1.24,3.15], mother feel happy during service[ AOR=4.00; 95%CI: 2.53,6.34], mothers adequate knowledge [AOR=2.91; 95%CI: 1.79, 4.73] and had favorable attitude [AOR=3.64; 95%CI: 2.25, 5.91] were significantly associated with maternal satisfaction during childhood immunization services.Conclusions: The overall level of mothers’ satisfaction with childhood immunization services was considerably lower as compared with other studies. Thus, the town health office and concerned stakeholders need more efforts to improve mothers’ satisfaction with childhood immunization services.

The concept of "Eco-authoritarianism", although appeared in the 1970s, through the writings of Robert Heilbroner, William Ophuls etc., but Eco-authoritarianism as a theory has emerged very recently [1]. In this era of global environmental degradation and rampant defacement of green space in the rapidly expanding cities of developing countries especially in India, historical sites of green belts, or eco-space developed by royal dynasties or colonial rulers are still preserved by eco-authoritarianism and cultural praxis. A lot of such heritage sites and built-up eco-spaces have faded out over time but at the same time, huge numbers are still present due to the imposition of restrictions by the state or national government or statutory organizations. Built up eco-space under Burdwan Raj Dynasty during the 18th and 19th centuries is still preserved almost in its original form due to the eco-authoritarianism outlook of the present stakeholder (The University authority mainly and the Forest Department). People of this urban unit not only feel proud of such built up eco-space; they also give credit to the university authority for maintaining the legacy of the Raj Dynasty. This investigation attempts to capture not only the role of authoritarian legacy for the preservation and conservation of eco-space in the urban context but also clarify the benefits of this eco-space regarding the cultural ecosystem services and outlook of urbanites towards nature. To portray this, both the qualitative and quantitative methods have been applied to glean the whole perspective.

Background: Streptococcus agalactiae or Group B Streptococcal colonization of the gastrointestinal and genital tracts of pregnant women usually remains asymptomatic; even if it is the critical determinant of infection in neonates and young infants. It causes early and late onset of invasive Group B Streptococcus (GBS) disease manifesting as septicemia, meningitis and pneumonia. Now it is recognized as an important cause of maternal and neonatal morbidity and mortality in many parts of the world including Ethiopia where the magnitude of the problem has been little studied. The aim of this study was to assess the prevalence of GBS colonization, to identify associated risk factors and antimicrobial susceptibility pattern among pregnant women at selected health facilities of Wolaita Sodo Town, Southern Ethiopia. Methodology: A health facility based cross-sectional study design was conducted at WSUCSH & Wolaita Sodo Health Center from June to August, 2022. A total of 279 pregnant women who were in ANC follow up with at 35-37 weeks of gestation were included. For GBS isolation, recto-vaginal swabs were inoculated in 1ml Todd-Hewitt broth medium supplemented with 10μg/ml colistin and 15μg/ml nalidixic acid and followed by identification of isolates based on colonial morphology, gram stains, catalase reaction and CAMP tests. Antimicrobial susceptibility testing was performed using modified Kirby–Bauer disk diffusion method. All collected data were organized in Epi info 4.6.0.2, then transfer tabulated using SPSS version 20. Logistic regression analysis was used to see the association between variables. Finally, the p-value < 0.05 were considered statistically significant. Results: In present study, 279 pregnant mothers included and their age was between 15 to 38 years with a mean of 26.5 ± 4.5 years. Of all participants, the highest 120 (43.01%) were housewives. The overall carriage rate of GBS was 67(24.0%). GBS colonization showed a statistically significant association with college and above levels of maternal education [AOR= 6.610, 95% CI (1.724 - 25.349), P=0.01]. High susceptibility of GBS isolate was seen to Penicillin G & Chloramphenicol (92.5%) for each, Ampicillin, and Ceftriaxone (89.6%) each, following Vancomycin (74.62%), and Erythromycin (77%). Relatively, GBS showed high resistance to Tetracycline (88 %). Conclusion: In this study, the overall prevalence of GBS colonization was 24.0%. College and above educational level was statistically significant with GBS colonization. This study used to give attention to the management of pregnant women by making GBS culture one of the routine diagnoses during ANC follow-up and to prevent infection by early detection.

Rainwater harvesting could be an optional water source to fulfil the emergency water demand in different setups. The aim was to assess if the rainwater harvesting potential for households and selected institutions were sufficient to satisfy the emergency water demand for the prevention of COVID-19 in Dilla town, Southern, Ethiopia. Rain water harvesting potential for households and selected institutions were quantified using 17 years’ worth of rainfall data from Ethiopian Metrology Agency. With an average annual rainfall of 1464 mm, households with 40 and 100 m2 roof sizes have a potential to harvest between 15.71-31.15 m3 and 41.73-82.73 m3 of water using Maximum Error Estimate. Meanwhile 7.2-39.7 m3 and 19.11-105.35 m3 of water can be harvested from the same roof sizes using Coefficient of Variation for calculation. Considering mean monthly rainfall, the health centres and Dilla University can attain 45.7% and 77% of their emergency water demand, while the rest of the selected institutions in Dilla Town can attain more than 100 % of their demand using only rainwater. Rain water can be an alternative water source for the town in the fight against COVID-19.

COVID-19 vaccine hesitancy and its enablers would shape community uptake of non-covid vaccines such as oral cholera vaccine (OCV) in the post-COVID-19 era. This study assessed the impact of COVID-19 vaccine hesitancy and its drivers on OCV hesitancy in a cholera endemic region of the Democratic Republic of Congo. We conducted a community-based survey in Bukavu. The survey included characteristics, intention to take OCV and COVID-19, reasons for COVID-19 hesitancy, and thinking and feeling about COVID-19 vaccines. Poisson regression analyses were performed. Of the 1708 respondents, 84.66% and 77.57% were hesitant to OCV alone and to both OCV and COVID-19, respectively. Hesitancy to COVID-19 vaccines rose OCV hesitancy by 12% (crude Prevalence Ratio, [cPR]=1.12, 95%CI[1.03-1.21]). Independent predictors of OCV hesitancy were living in semi-urban area (adjusted Prevalence Ratio [aPR]=1.10, 95%CI[1.03-1.12]), religious refusal of vaccines (aPR=1.06, 95%CI[1.02-1.12]), concerns about vaccine safety (aPR=1.05, 95%CI[1.01-1.11]) and adverse effects (aPR=1.06, 95%CI[1.01-1.12]), as well as poor knowledge (aPR=1.07, 95%CI[1.01-1.14]). Conversely, the belief about COVID-19 vaccine effectiveness reduced OCV hesitancy (aPR=0.76, 95%CI[0.62-0.93]). COVID-19 vaccine hesitancy and its drivers exhibiting a significant domino effect on OCV uptake. Addressing vaccine hesitancy through community-based health literacy interventions would likely improve the introduction of novel non-COVID-19 vaccines in post-COVID-19 era.

Prochlorococcus, a cyanobacteria genus of the smallest and most abundant oceanic phototrophs, encompasses ecotype strains adapted to high-light (HL) and low-light (LL) niches. To elucidate the adaptive evolution of this genus, we analyzed 40 Prochlorococcus marinus ORFeomes, including two cornerstone strains, MED4 and NATL1A. Employing deep learning with robust statistical methods, we detected new protein family distributions in the strains and identified key genes differentiating HL and LL strains. HL strains harbor genes (ABC-2 transporters) related to stress resistance, such as DNA repair and RNA processing, while LL strains exhibit unique chlorophyll adaptations (ion transport proteins, HEAT repeats). We report variable, depth-dependent endogenous viral elements in the 40 strains. We constructed the ORFeomes of MED4 and NATL1A covering 99 % of the annotated protein-coding sequences of the two species, totaling 3976 cloned, sequence-verified ORFs. These comparative genomics analyses, paired with MED4 and NATL1A ORFeomes, will facilitate future genotype-to-phenotype mappings and systems biology exploration of Prochlorococcus ecology.

This research aimed to develop a causal relationship model of the behavior of a Thai rural community in disposing of used batteries. The variables studied were 1) the household latent variable (three observable variables); 2) the social latent variable (six observable variables); 3) the intention latent variable (three observable variable); and 4) the behavior latent variable (three observable variables). Six hundred households were surveyed using a questionnaire. The questionnaire developed was validated by seven experts and its reliability was established by testing it with a sample group. Results showed that the modified model do present a good overall level of fit. The House and social positively and directly influenced intention. Intention positively and directly influenced behavior. The theoretical and practical implications relating specifically to intention to the behavior in disposing of used dry batteries by households are emphasized. The modified model indicated eighty-nine percent of the variance in the behavior in disposing of used dry batteries by households was explained by the intention factors. The most direct effect on behavior was the intention factors with 0.89 of effect size. The factors with indirect effects on behavior were household and social factors with an effect size of 0.52 and 0.35.

The Ebola virus disease (EVD) is an extremely contagious and fatal illness caused by the Ebola virus. Recently, Uganda witnessed an outbreak of EVD, which generated a lot of attention on various social media platforms. To ensure effective communication and implementation of targeted health interventions, it is crucial for stakeholders to comprehend the sentiments expressed in the posts and discussions on these online platforms. In this study, we used deep learning techniques to analyze the sentiments expressed in Ebola-related tweets during the outbreak. We explored the application of three deep learning techniques to classify the sentiments in 8,395 tweets as positive, neutral, or negative. The techniques examined included a 6-layer convolutional neural network (CNN), a 6-layer long-short-term memory model (LSTM), and an 8-layer Bidirectional Encoder Representations from Transformers (BERT) model. The study found that the BERT model outperformed both the CNN and LSTM-based models across all the evaluation metrics, achieving a remarkable classification accuracy of 95\%. These findings confirm the reported effectiveness of transformer-based architectures in tasks related to natural language processing, such as sentiment analysis.

Abstract Introduction: Antimicrobial resistance (AMR) is a recognised public health threat today globally. Though many active and passive stewardship strategies are employed to counter AMR clinically, educating school going children on AMR could be a futuristic cost-effective measure to minimize AMR development. We hypothesised NICE’s e-bug module to class VII school students on AMR determinants. Methodology: A prospective non-randomized intervention study on 327 students belonging to 9 schools of class VII around Manipal town, Udupi district, Karnataka state, India were included for the study. 10 questions on AMR determinants extracted from NICE’s e-bug program were quizzed in written as pre-test followed by an education intervention on the same questions followed by a post-test to end the session. Descriptive statistics to estimate epidemiological characteristics, Wilcoxon Signed Ranks and Kruskal-Wallis tests were applied to analyse statistical significance of pre/post-test performance scores for the 10 questions and between schools respectively Results: Students had inadequate knowledge on 7 AMR determinants (antimicrobial indication, its course, hand hygiene, fermentation, spread of infection, microbial multiplication and characteristics of microbe) when analysed for post-test performance (p<0.05). Comparison of post-test performance of 9 participating schools revealed statistical significance (p<0.05) for 3 questions (definition on antimicrobial, cover while cough/sneezing and microbial characteristics) Conclusion: Although students exhibited sub-optimal knowledge on few AMR determinants, they showed keenness to learn exhibited by their performance. Our findings and previous similar studies from Europe are suggestive of early pedagogic interventions on AMR through inclusion of such education modules in the curriculum could be potential tool for AMR prevention for future generations.

Chronic kidney disease (CKD) is a growing public health issue with significant morbidity and mortality rates. Traditional diagnostics, with about 70% accuracy, often delay CKD detection, highlighting the need for more efficient methods. Recent studies indicate a potential link between CKD and auditory health, yet this relationship remains underexplored due to methodological challenges and the complexity of establishing causality. Our research utilizes data spanning from 2000 to 2020 from the National Health and Nutrition Examination Survey (NHANES), covering 12,392 participants, including 2,060 diagnosed with CKD. Through meticulous analysis employing logistic regression and Mendelian randomization, we have unearthed novel insights into the bi-directional associations between hearing impairment and CKD. Furthermore, we developed and validated a machine learning model that surpasses traditional diagnostic approaches in terms of accuracy and predictive power. These findings highlight the innovative integration of auditory examinations with demographic data to enhance CKD detection. Our approach demonstrates the potential of machine learning in transforming diagnostic methodologies, thus offering a significant advancement in the field of nephrology and public health.

Background: Early diagnosis of postoperative complications is an urgent task, allowing timely prescribing of appropriate therapy and reducing the cost of patient treatment. Prognostic models based on various data could help in the early diagnosis of postoperative complications after cardiac surgery. Objectives: The purpose of the study was to determine whether an integrated approach based on clinical data along with metabolites and biomarkers had greater predictive value than the models built on less data. Methods: The study included patients (n=62) admitted for planned cardiac surgery (coronary artery bypass grafting with cardiopulmonary bypass), who were retrospectively divided into two groups depending on the presence (n=26) or absence (n=36) of postoperative complications of all types. Clinical and laboratory data on the first day after surgery were analyzed. Additionally, patients' blood samples were collected before and on the first day after surgery to determine biomarkers (interleukin-6, procalcitonin, NT-proBNP, high-sensitivity troponin T) and metabolites (8 aromatic and 2 dicarboxylic acids were detected using gas chromatography-mass spectrometry). Results: Patients before surgery, compared with healthy donors, differed in the concentration of metabolites (p &lt; 0.05), and had concentrations of a number of biomarkers exceeding the corresponding reference values. Multivariate PLS-DA models, predicting the presence or absence of postoperative complications, were built using clinical data (ROC-AUC=0.71), concentrations of metabolites and biomarkers (ROC-AUC=0.60), and the entire data set (ROC-AUC=0.75). For comparison we built univariate models using the EuroScore2 (ROC-AUC=0.59) and SOFA (ROC-AUC=0.76) scales; concentrations of lactate (ROC-AUC=0.71), the dynamic changes of 4-hydroxyphenyllactic acid (ROC-AUC=0.69), and the sum of three sepsis-associated metabolites (ROC-AUC=0.70). The proposed complex model using entire data set was comparable to the SOFA scale, which confirms the expediency of searching for new predictive models based on a variety of factors.

Milk serves as a crucial source of natural bioactive compounds essential for human nutrition and health. The gastrointestinal digestion of milk proteins releases various biologically active peptides that positively impact human health and enhance physiological performance. With the growing production of cheese, Greek yogurt, and other dairy products, the volume of unutilized acid whey is significantly increasing. Acid whey, containing almost all whey proteins and approximately one-quarter of casein, presents a valuable raw material for generating peptides with potential health benefits. These peptides exhibit properties such as antioxidant, antimicrobial, anti-inflammatory, anticarcinogenic, antihypertensive, antithrombotic, opioid, mineral-binding, and growth-stimulating activities, contributing to improved human immunity and the treatment of chronic diseases. Enzymatic hydrolysis of milk proteins has been developed as a method to produce these peptides, facilitating their use in food fortification. To incorporate whey into functional beverages, it undergoes fermentation by lactic acid bacteria with proteolytic activity. To specifically enrich these beverages with peptides exhibiting targeted bioactivities, it is essential to select lactic acid bacteria strains possessing the requisite protease profiles. Additionally, the sensory properties of the final product can be enhanced using starter cultures with diverse metabolic capabilities, even in the absence of added flavoring agents. Given the imperative to develop waste-free technologies and enhance the profitability of the dairy industry, there is a growing need to efficiently utilize and transform acid whey into a broad spectrum of valuable products and food additives. This approach is justified not only by the nutritional benefits of the bioactive components in whey but also by the commercial potential of safe and health-enhancing products.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.

In order to shorten the detection time and improve the average precision on embedded devices, A lightweight and high accuracy model is proposed for passion fruit in complex environments (backlight, occlusion, overlap, sunny, cloudy, rainy). Firstly, replacing the backbone network of YOLOv5 with a lightweight GhostNet model reduces the number of parameters and computation while improving detection speed. Secondly, a new feature branch is added to the GhostNet network, and the feature fusion layer in the neck network is reconstructed to effectively combine the lower-level and higher-level features, which not only improves the accuracy of the model but also maintains its lightweight. Finally, the knowledge distillation methods are used to transfer the knowledge from the more capable teacher model to the less capable student model, which significantly improving the detection accuracy. The improved model is denoted as G-YOLO-NK. The average accuracy of the G-YOLO-NK network is 96.00%, which is 1.00% higher than the original YOLOv5s model. Furthermore, the improved model size is 7.14MB, reduced to half of the original model, and the real-time detection frame rate is 11.25 FPS on the Jetson Nano. Compared to the state-of-the-art model, the proposed model outperforms them in terms of average precision and detection performance. The present work provides an effective model for real-time detection of passion fruits in complex orchard scenes, which can provide valuable technical support for the development of orchard picking robots and greatly improve the intelligence level of orchards.

The impact of interaction SS with MJO on rainfall along Java Island to East Nusa Tenggara has been studied using daily rainfall observation data from 2140 weather observation stations, which are also equipped with GSMaP, OLR, and ERA5 data. There were 61 SS events found, 17 during active MJO and 44 in inactive MJO. Rainfall increases more in the western study area when the active MJO and more in the eastern study area when the inactive MJO is due to SS. SS reduces rainfall in the Jakarta region, regardless of the activity or inactivity of the MJO. SS causes extreme rainfall to only occur in a small part of certain areas, so it tends to significantly reduce the possibility of extreme rainfall. In the southern part of the IMC, SS predominates over MJO in supporting increased water vapor transport. Large-scale synoptic circulations like the monsoon, SS, and MJO can interact with local land-sea wind circulation to produce spatiotemporal variability in rainfall on Java Island. Rainfall mostly increases in the afternoon and decreases in the morning when SS occurs, whether there is MJO or not. Convective instability analysis indicates that SS increases precipitation, most likely by lowering CIN and raising VIMFC.

The Simultaneous Localization And Mapping (SLAM) scanner is an easy and portable Light Detection And Ranging (LiDAR) data acquisition device. Its main output is a 3D point cloud covering the scanned scene. Regarding the importance of accuracy in the survey domain, this paper aims to assess the accuracy of two SLAM scanners: the NavVis VLX and the BLK2GO Scanner. This assessment is conducted for both outdoor and indoor environments. In this context, two types of reference data are used: the Total Station (TS) and the static scanner Z+F Imager 5016. To carry out the assessment, four comparisons are tested: cloud to cloud, cloud to mesh, mesh to mesh, and edge detection board assessment. However, the results of the assessments confirm that the accuracy of indoor SLAM scanner measurements (5 mm) is greater than that of outdoor ones (between 10 mm and 60 mm). Moreover, the comparison of cloud to cloud provides the best accuracy regarding direct accuracy measurement without manipulations. Finally, based on the high accuracy, scanning speed, flexibility, and the accuracy differences between tested cases, it is confirmed that SLAM scanners are effective tools for data acquisition.

In recent years, electroencephalogram (EEG) emotion recognition has emerged as a research hotspot in the field of artificial intelligence (AI). Despite advancements in EEG-based emotion recognition, room for enhancing performance persists due to EEG signal redundancy and limitations in feature extraction, leading to inefficient models and emotional information loss. To fully utilize EEG's emotional information and improve recognition accuracy while reducing computational costs, this paper proposes a Convolutional-Recurrent Hybrid Network with a dual-stream adaptive approach and an attention mechanism (CSA-SA-CRTNN). Firstly, the model utilizes a CSAM module to assign corresponding weights to EEG channels. Then, an adaptive dual-stream convolutional-recurrent network (SA-CRNN and MHSA-CRNN) is applied to extract local spatial-temporal features. After that, the extracted local features are concatenated and fed into a temporal convolutional network with a multi-head self-attention mechanism (MHSA-TCN) to capture global information. Finally, the extracted EEG information is used for emotion classification. We conducted binary and ternary classification experiments on the DEAP dataset, achieving 99.26% and 99.15% accuracy for arousal and valence in binary classification, and 97.69% and 98.05% in ternary classification, surpassing relevant algorithms. Additionally, the model's efficiency is significantly higher than other models, achieving better accuracy with lower resource consumption.

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

Background: Educating college students about the importance of good sleep habits could lead to the adoption of healthier sleep routines, including sufficient sleep duration and sleep quality. The current pre-post study examines the impact of completing a sleep education program called “Sleep 101” on (1) sleep hygiene practices, (2) sleep quality, and (3) weekday and weekend sleep behaviors among college students. “Sleep 101” is an interactive online course developed to educate college students about the importance of sleep by addressing basic sleep physiology, the impact of sleep on mood, academic and physical performance, the interactions between sleep and various substances, and common sleep disorders. Methods: 338 college students were recruited from a midsized public university in the US and invited to participate in “Sleep 101”, of which 25 participants completed the baseline and post-intervention questionnaire. The Sleep Hygiene Index (SHI) was utilized to evaluate sleep hygiene practices, while standard questions were employed to assess weekday and weekend sleep behaviors and overall sleep quality. Results: Those who completed the study demonstrated a significant increase in weekday sleep duration and were less likely to engage in negative prior bedtime activities. In addition, 40% of those who completed baseline and post-intervention assessments noticed improvements in their sleep quality. Conclusion: These findings suggest that a brief online program is beneficial in improving sleep behaviors among college and could be a scalable approach to addressing current sleep issues and preventing future sleep problems in college students.

The profile of secondary metabolites occurring in apple cuticular layer is not only characteristic for particular apple cultivar, but also dynamically reflects various external factors in growing environment. In this study, the possibility to authenticate apple samples based on analysis of their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. In total, 274 authentic apple samples, four cultivars harvested within the seasons 2020 to 2022 in the Czech Republic and Poland were analysed. The generated complex data processed by univariate and multivariate statistical methods enabled to build classification models for discrimination of apple cultivars as well as their geographical origin. The models showed very good performance in differentiation of Czech and Polish samples for three of four cultivars: ‘Gala’, ‘Golden Delicious’ and ‘Idared’, moreover, the validity of the models was verified over harvest seasons. The diagnostic markers, besides metabolites of triterpene biosynthetic pathway, mainly represented wax esters. ‘Jonagold’, which is known to be susceptible to mutations, was the only cultivar for which the unambiguous classification of geographical origin was not possible.

Superior fiber quality is one of the most important objectives in cotton breeding. To detect the genetic basis underlying fiber quality, an F2 population containing 413 plants was constructed by crossing Jifeng 914 and Jifeng 173, both of which have superior fiber quality, with Jifeng 173 being better. Five fiber quality traits were investigated in the F2, F2:3, F2:4, and F2:5 populations. Quantitative trait loci (QTL) mapping was conducted based on a high-density genetic map containing 11,488 single nucleotide polymorphisms (SNPs) and spanning 4,202.12 cM in length. Transgressive segregation patterns and complex correlations in the five tested traits were observed. A total of 108 QTLs were found, including 27 for fiber length (FL), 16 for fiber strength (FS), 24 for micronaire (MC), 17 for fiber uniformity (FU), and 24 for fiber elongation rate (FE). Chromosome A7 contained 12 QTL, ranking the first. No QTL was found on chromosome D1 and D11. Each QTL contributed 1.98%–21.45% to the phenotypic variation (PV), including 13 major effect QTLs that contributed more than 10% toward PV. Two QTLs could be repeatedly detected in three populations, including qFL-D3-2 in F2, F2:4, and F2:5 with 9.18%–21.45% of PV, qFS-A11-1 in F2:3, F2:4 and F2:5 with 6.05%–10.41% of PV. Another seven stable QTLs could be detected in two populations, including four major effect QTLs: qFL-A12-3, qFS-D10-2, qMC-D6-2, and qMC-D8-1. Fourteen QTL-overlapping regions were found, which might explain the complex correlations among the five phenotypic traits. Four regions on chromosome A11, D3, D6, and D10 covered by both stable and major effect QTLs are promising for further fine mapping. The genomic regions of the two QTLs detected in three populations and the four major effect QTLs contain 810 genes. Gene functional analysis revealed that the annotated genes are mainly involved in protein binding and metabolic pathways. Fifteen candidate genes in the qFL-D3-2 region are highly expressed in fiber or ovules during fiber initiation, elongation, secondary cell wall thickening, or maturation stages. qRT-PCR revealed that Ghir_D03G005440.1 and Ghir_D03G011310.1 may play a role in promoting fiber initiation, Ghir_D03G006470.1 may be beneficial for promoting fiber elongation. This study provides more information for revealing the molecular genetic basis underlying cotton fiber quality.

Currently there are fewer depth models applied to pepper picking detection, while the existing generalized neural networks have problems such as large model parameters, long training time, and low model accuracy.In order to solve the above problems, this paper proposes a Yolo-chili target detection algorithm for chili pepper detection. First, the classical target detection algorithm yolov5 is used as a benchmark model, and an adaptive spatial feature pyramid structure combining the attention mechanism and the idea of multi-scale prediction is introduced to improve the model's detection effect on occluded peppers and small target peppers. Secondly, a three-channel attention mechanism module is introduced to improve the algorithm's long-distance recognition ability and reduce the interference of redundant testers. Finally, the quantized pruning method is used to reduce the model parameters and realize the lightweight processing of the model. Applying the method to the homemade chili pepper dataset, the AP value of chili pepper reaches 93.11%; the accuracy rate is 93.51% and the recall rate is 92.55%.The experimental results show that yolo-chili is able to achieve accurate and real-time pepper detection under complex orchards.

The temporary immersion system bioreactor named GreenTray®[2], [3]presents advantages over the existing ones. Firstly, there is no need to use forceps to move the shoots or plantlets in or out of the recipient, neither the use of scalpel to divide them. Secondly, the basis of the shoot can remain in the GreenTray® and can sprout again in several cycles of growth. These two characteristics reduce the costs in the process of micropropagation. Besides, shoots or plantlets development is enhanced by the aeration of the recipient, thus enriching with CO2 the recipient atmosphere. The chapter describes and provides images and values of interest in (1) the micropropagation process of some commercial Prunus or Pyrus rootstocks; (2) the plantlet growth under autotrophic conditions; and (2) the inoculation of plants with pathogens that reproduce in vitro the symptoms observed in vivo, using the GreenTray® bioreactor.

Aiming at the problems of inaccurate segmentation of long object and information loss of small object in real-time semantic segmentation algorithm, this paper proposes a lightweight multi-branch real-time semantic segmentation network based on BiseNetV2. The new auxiliary branch makes full use of spatial details and context information to cover the long object in the field of view. Meanwhile, in order to ensure the inference speed of the model, the asymmetric convolution is used in each stage of the auxiliary branch to design a structure with low computational complexity. In the multi-branch fusion stage, the alignment and fusion module is designed to provide guidance information for deep and shallow feature mapping, so as to make up for the problem of feature misalignment in the fusion of information at different scales, and thus reduce the loss of small target information. In order to further improve the model’s awareness of key information, a global context module is designed to capture the most important features in the input data. The proposed network uses NVIDIA GeForce RTX 3080 Laptop GPU experiment, on the road street view data set Cityscapes and CamVid average occurring simultaneously ratio reached 77.1% and 78.4% respectively, with running speed of 127 frames/s respectively and 112 frames/s. The experimental results show that the proposed algorithm can achieve real-time segmentation and improve the accuracy significantly, showing good semantic segmentation performance

Strawberry root rot caused by Neopestalotiopsis clavispora is one of the main diseases of strawberry and significantly impacts the yield and quality of strawberry fruit. There are now no effective control techniques available except for fungicide sprays, which may directly impact consumers. Biological control is becoming an alternative method for the control of plant diseases to replace or decrease the application of traditional synthetic chemical fungicides. Trichoderma is widely used as a biological agent for controlling strawberry root rot. In order to provide resources for screening the highly effective biocontrol fungus for controlling strawberry root rot caused by Neopestalotiopsis clavispora, the biocontrol mechanism,the control effects of Trichoderma asperellum CMT10 against strawberry root rot and growth-promoting effects on strawberry seedlings were investigated by plate culture, microscopy observation and root drenching methods.The results showed that CMT10 had obvious competitive, antibiotic and hyperparasitism effects on Neopestalotiopsis clavispora CMGF3. The CMT10 could quickly occupy nutritional space, and the inhibition rates of CMT10 against CMGF3 in confrontation culture on 7 d was 65.49%. The inhibition rates of volatile metabolite and fermentation metabolite produced by CMT10 against CMGF3 were 79.67% and 69.84%, respectively. The mycelium of strain CMT10 can act as hyperparasites by making contacting, winding and penetrating hyphae of CMGF3. Pot experiment showed that the biocontrol efficacy of CMT10 on strawberry root rot caused by Neopestalotiopsis clavispora was 63.00%. CMT10 had obvious promotion effect on strawberry growth, the plant height, root length, total fresh weight, root fresh weight, stem fresh weight and root dry weight, with the promotion rates were 20.09%, 22.39%, 87.11%, 101.58%, 79.82% and 72.33%, respectively. Overall, this study showed the ability of Trichoderma asperellum CMT10 to control strawberry root rot and their potential to develop as novel biocontrol agents to replace chemical fungicides for eco-friendly, sustainable agriculture.

In this paper we study a class of impulsive delayed neural networks with parameter uncertainties and reaction-diffusion terms. Using the properties of M-matrices and some inequality techniques, some sufficient conditions are derived to guarantee the global exponential stability of the given system. The results obtained are presented by simple algebraic inequalities, which are certainly more concise than previous methods. Finally, the validity and usefulness of our results are illustrated by arithmetic examples.

Pyrops candelaria is one of the common pests of fruit trees, but the research on the pathogenic microorganisms it may carry is very limited. Therefore, it is essential to reveal the pathogenic microbes it carries and their potential hazards. This study found a new virus from the transcriptome of P. candelaria, which was first reported in P. candelaria and named as PyCaV (Pyrops candelaria associated virus). RACE and bioinformatics assay revealed that the full-length of PyCaV is 10855 bp with the polyA tail, containing a single open reading frame (ORF) encoding a polyprotein consisting of 3171 amino acid (aa). The virus has a typical Iflavirus structure, including two rhv domains, a RNA helicase domain (HEL), a 3C cysteine protease domain (Pro), and a RNA-dependent RNA polymerase domain (RdRp). Further phylogenetic analysis revealed that this virus belongs to family Iflaviridae and sequence alignements analysis suggedted PyCaV is new member in unassigned genus of family Iflaviridae. Further in-depth analysis of virus-infection-part showed that PyCaV is distributing in the whole longan lanternfly, including its head, chest, and abdomen, but more PyCaV was identified in the chest. The distribution of PyCaV in different parts of P. candelaria was further explored, which showed that more PyCaV were detected in its piercing-sucking mouthparts and chest viscera. Statistical analysis showed that the PyCaV infection was affected by time and locations.

Apis mellifera, especially weak ones, are highly vulnerable to Carpoglyphus lactis mites, which can rapidly infest and consume stored pollen, leading to weakened colonies and potentially colony collapse. This study aimed to ascertain and investigate the prevalence of this mite in honeybee colonies across 9 provinces in the Republic of Korea (ROK). A total of 615 honeybee colonies were collected, from 66 apiaries during the spring and 58 apiaries during the summer of 2023. A 1,242 bp segment of the the Cytochrome c oxidase subunit 1 (COI) gene was amplified using the polymerase chain reaction method. The detection levels of C. lactis in the honeybees were compared between winter and summer. Based on the COI sequence analysis, the nucleotide sequence similarity of C. lactis mites isolated in the ROK with those from China (NC048990.1) was found to be 99.5%, and with those from the United Kingdom (KY922482.1) was 99.3%. This study is the first report of C. lactis in Korean apiaries. The findings in this study demonstrate a significantly higher detection rate in winter, which is 4.1 times greater than that in summer (p &lt; 0.001). Furthermore, the results underscore the usefulness of molecular diagnostic techniques for detecting C. lactis mites.

With the burgeoning growth of online retail, the issue of counterfeit products has become a significant threat to both consumer trust and brand integrity, posing challenges to sustainable market practices. Online retail platforms are promoted to redesign their channel structures and enhance brand traceability to tackle counterfeits using blockchain technology. To investigate the interactions between blockchain technology and the channel structures of online retail platforms, we design a game theory model incorporating a manufacturer with(out) blockchain participation selling products via an online retail platform that operates an agency channel and/or a reselling channel. We show that the critical trade-off of blockchain participation comprises the brand assurance effect of the blockchain, the channel competition intensification effect, and the blockchain adoption cost. The platform is capable of strategically designing the channel structure to encourage (while discouraging) blockchain participation by the manufacturer. Our analysis highlights the complementarity between blockchain participation and the channel structure. Furthermore, the effect of the consumer’s belief in the reselling channel, the commission fee in the agency channel, and the substitutability between channels are investigated in depth. The research provides valuable insights for online retail platforms and policymakers seeking to foster a sustainable and trustworthy e-commerce ecosystem.

In this paper, we extend the KdVSKR equations in (1+1)-dimension and (2+1)-dimension to fractional KdVSKR equations with modified Riemann-Liouville derivative. The (2+1)-dimensional KdVSKR equation, which is a recent extension of (1+1)-dimensional KdVSKR equation, can model the resonances of solitons in shallow water. By means of the Hirota bilinear method, finite symmetry group method and consistent Riccati expansion method, many new interaction solutions have been derived. Soliton-cnoidal interaction solution of the (1+1)-dimensional fractional KdVSKR equation has been derived for the first time. For the (2+1)-dimensional frac-tional KdVSKR equation, two-wave interaction solutions and three-wave interaction solutions, including dark-soliton-sine interaction solution, bright-soliton-elliptic interaction solution, and lump-hyperbolic-sine interaction solution, have been derived. Impact of the fractional order on the shapes of these solutions has been illustrated by figures. Three-wave interaction solutions of fractional systems have not been reported in the existing references. The research idea in this paper can be applied to other fractional differential equations.

COX II containing a dual core CuA active site is one of the three core subunits of mitochondrial Cco, which plays a significant role in the physiological process. In this report, the full-length cDNA of COXⅡ gene was cloned from Sitophilus zeamais, which had an ORF of 684 bp encoding 227 amino acids residues. The predicted COXⅡ protein had a molecular mass of 26.2 kDa with pI value of 6.37, and multiple sequence alignment and phylogenetic analysis indicated that Sitophilus zeamais COXⅡ had high sequence identity 78.51% with the COXⅡ of other insect species, especially similarity to sitophilus oryzae. This gene was subcloned into the prokaryotic expression vector pET-32a, and induced by IPTG in E.coli Transetta (DE3) expression system. Finally the COXⅡ with 6-His tag was purified using affinity chromatography with Ni²⁺-NTA agarose. WB showed the recombinant COXⅡ was about 44 kD, and the concentration of fusion protein was 50μg/mL. UV-spectrophotometer and infrared spectrometer analysis showed that recombinant COXⅡ could catalyze the oxidation of substrate Cytc, and influenced by AITC. It was found that AITC could form a hydrophobic region with COXⅡ protein via molecular docking, besides, a sulfur atom of AITC structure could form a length of 2.9 Å hydrogen bond with Leu-31. These results will provide valuable information for elucidating the role of COXⅡ in Sitophilus zeamais responses to AITC, meanwhile, it will helpful to carry out a point mutation in AITC binding sites for the future research.

The properties of the annual, semiannual and triennial oscillations (AO, SAO and TO) in the middle atmosphere have been investigated using the TIMED/SABER temperature data. The Lomb-Scargle and wavelet spectra were used to determine the dominant oscillations in the background temperature field. The AO is prominent at the mid-latitudes. The AO amplitudes present an asymmetry between the two Hemispheres, being larger in the mesosphere than in the stratosphere. The SAO dominates the tropical regions, with three amplitude maxima at altitudes of 45, 75, and 85 km. The SAOs in the upper mesosphere (75 km) are out of phase with those in the mesopause (85 km) in the tropical regions, which can generate an enhancement of 11 K at each equinox, contributing to the lower mesospheric inversion layer. The TO is significant in the tropical region, with amplitude being maximum at 35, 45 and 85 km. Result shows that there may be potential interaction by the TO with SAO at 85km at the equator. The relation between ENSO and TO has also been discussed. The ENSO signal may modulate the amplitude of the TO, mainly in the lower stratosphere. The real origin of the TO may lie in the wave-mean-flow interaction.

As the world population grows, fulfilling the need for biomaterials in the healthcare system becomes increasingly important. Biomaterials, which include metals, polymers, ceramics, and composites, play an important role in the creation of medical devices that improve people's lives. The European Society for Biomaterials described biomaterials as non-biological materials used in medical devices to interact with biological systems. This definition has developed to encompass materials that treat, assess, or replace tissues or bodily functions. Biocompatibility, as defined by the FDA, is a key feature of biomaterials, as is the requirement to fulfil design requirements such as mechanical performance, geometry, and electrical control. Over the last decade, advances in regenerative medicine and tissue engineering have boosted biomaterials' usage in medical applications dramatically. Despite its promise, scientists, engineers, and physicians continue to face significant challenges due to the complexity of biomaterials. Biomaterials have various benefits, including biodegradability, non-toxicity, and biocompatibility, making them extremely useful for replacing, sustaining, or improving biological activities in damaged tissues. They are used in a wide range of applications, including tissue engineering implants, human tissue healing and regeneration, medication delivery systems, and biosensors. This study gives insights into the fundamental characteristics, case studies, and ethical issues associated with the usage and use of biomaterials, further examining their potential and significance in healthcare and medicine.

The paper describes the new method for image compression based on coordinated group signal transformation. The algorithm is a type of difference coding. Coordinated processing significantly simplifies the difference signal conversion scheme using a single group codec for all signals. The described method considers color channels as correlated signals of a multi-channel communication system. The specifics of the processed data required modification of the coordinated group processing algorithm. First, we changed how to calculate the difference signals to prevent data loss. Secondly, the group codec was supplemented with a neural network to improve the quality of reconstructed images. We considered the following types of neural networks: fully connected, recurrent, convolution, and convolution in the Fourier space. Based on the simulation results, it is best to use fully connected neural networks if the goal is to minimize processing delay time. These networks have a response time of 13 ms. On the other hand, if the priority is to improve quality in cases where delays are not critical, then convolution neural networks in the Fourier space should be used. These networks have a response time of 140 ms and are of significant interest.

In electromagnetic ultrasonic testing, it is difficult to recognize small-size bottom cracks by time of flight (ToF), and the lift-off fluctuation of the probe affects the accuracy and consistency of the inspection results. In order to overcome the difficulty, a novel EMAT (electromagnetic acoustic transducer)-PEC (pulse eddy current) composite sensor is designed. We use amplitude of bottom echo recorded by EMAT to identify the tiny bottom crack as well as the amplitude of PEC signals picked up by the integrated symmetric coils to measure the average lift-off of the probe in real time. Firstly, the effects of lift-off and bottom cracks on amplitude of bottom echo are distinguished combining the theoretical analysis and finite element method (FEM). And then an amplitude correction method based on the fusion of EMAT and PEC signals is proposed to reduce the impact of lift-off on the defect signal. The experimental results demonstrate that the designed composite sensor can effectively detect the bottom crack as small as 0.1mm* 0.3mm. The signal fusion method can accurately correct the amplitude of defect signal and the relative error is less than ±8%.

The studied solar pot is a recent invention, which gained a utility model protection in 2021 from the Hungarian Intellectual Property Office under patent number 5489. The device is made for environmentally friendly cooking or heating (by utilizing solar energy) of foods and liquids. Its structure is similar to a double pipe heat exchanger, it has an outer mantle and an inner cooking tank. The goals of the paper are proposing a new physically-based mathematical model describing the solar pot and carrying out computer experiments with it, assembling an experimental system of the pot connected with a solar collector and performing measurements on it. Based on the results, the solar pot can successfully be used for cooking or sterilizing foods or liquids during the studied time period, in Hungary.

The research reported on this paper was aimed at improving the overall efficiency of a PDO certified artisanal cheese production process. Being a PDO certified foodstuff by the EU, it is considered to have properties and qualities determined by the geographical environment in which is made, with its production taking place in a specific and determined geographical location, in this case the Serra da Estrela region. In that sense, the authors conducted a mapping according to a systemic perspective of the processes involved in the context of manufacturing and distribution of certified Serra da Estrela cheese. Numerous methods were used throughout the process, such as a systemic design analysis, and techniques derived from ethnographic methods, which led to the collection of data in the field and consequently provided the immersion of the researcher in genuine work situations. Critical points were identified and emphasized in the systemic map with the purpose of encouraging initiatives to address and overcome the gaps and inefficiencies detected. The systemic design analysis triggered the development of design work. Observations following an ethnographic approach identified ergonomic risks in cheese making during the process of cutting excess chips, fostering the emergence of musculoskeletal disorders at the wrist. A tool that fits best to the task at hand was developed. A prototype of the new tool enabled collecting feedback from use in the work context, in order to inform product development. The domains of agricultural production and microbiology, considering the specific microorganisms developed trough the ripening process of the cheese, turned out to be aspects of high importance for the issue under focus, contributing to a broader understanding of the ripening process and its risks, simultaneously improving the efficiency and success of cheese production. If it were not for the systemic analysis, which served as a link between the boundaries of distinct domains such as the risk of microorganism contamination, ergonomics, energy efficiency, legislation and regulation policies, transportation challenges and economic viability, approached throughout the research. Simultaneously creating bridges between them, the various problems might not have been detected in the first place, as they are usually addressed in specialized disciplines, predetermined by the restrictions of each specific area of knowledge. As a consequence of the development of this research, which was based on an analysis that sought to establish possible connections between various disciplines and tried to constantly maintain a holistic perspective, making new connections and observing the issues from a new angle, apart from the already established methodologies. All this allowed to lay out the seeds for the development of a plan to tackle the critical points identified by the systemic analysis reported in this paper.

Abstract: Transcription factors are crucial pre-transcriptional regulatory mechanisms that can modulate the expression of downstream genes by binding to their promoter regions. DOF (DNA binding with One Finger) proteins are a unique class of transcription factors with extensive roles in plant growth and development. Our previous research indicated a decrease in iron content in chlorotic bamboo leaves. However, to our knowledge, genes related to iron metabolism pathways in bamboo species have not yet been studied. Therefore, in the current study, we identified iron metabolism-related (IMR) genes in bamboo and determined the transcription factors that significantly influence them. Among these, DOFs were found to have widespread effects and potentially significant impacts on their expression. We identified specific DOF members in Dendrocalamus latiflorus with binding abilities through homology with Arabidopsis DOF proteins, and established connections between some of these members and IMR genes using RNA-seq data. Additionally, molecular docking confirmed the binding interactions between these DlDOFs and the DOF binding sites in the promoter regions of IMR genes. The co-expression relationship between the two gene sets was further validated using q-PCR experiments. This study paves the way for research into iron metabolism pathways in bamboo and lays the foundation for understanding the role of DOF transcription factors in D. latiflorus.

This paper is focused on typical rural settlements in the Stara Planina Mountain area in Serbia. They are distinguished by their authenticity, identity and character, and they have still not been destroyed by inappropriate development as is the case in some other mountain areas in Serbia, where the effects of urbanization, globalization and homogenization are obvious. Consequently, there is a need to prevent these effects in mountain areas where there is a threat of disbalance between development and the inherited natural and cultural values. The paper starts from several important concepts that relate contemporary approaches to cultural heritage preservation, place morphology and planning future development. The concept definitions from recent documents from related fields are used. These concepts are then applied to the area of Stara Planina Mountain and its rural settlements. The necessity for an integrative approach to planning this area with significant natural and anthropogenic potential is pointed out, including its integration into international programs of sustainable development.

The wetlands in northeastern Bangladesh are home to some of the most prolific and valuable ecosystems on the planet, offering a wide range of benefits to both the local and wider communities. A limited number of research on this topic have been carried out in various wetlands in coastal hilsa, but none have been located in the northeastern region of Bangladesh. Thus, the goal of this study was to better understand the most commercially relevant species (anadromous hilsa) in northeastern Bangladesh as well as to assess the wetland ecosystem services more thoroughly with the contribution of their fish genetic resources. In addition to laboratory studies, fieldwork was done in the fishing settlements along the Surma River, Hakaluki Haor, and Tanguar Haor. The study classified 77 fish species into 21 subcategories of ecosystem services, of which 56% were not threatened, 17% were vulnerable, and 10% were highly endangered. The species Hilsa was found to be the most economically significant, accounting for 1% of the GDP overall. The study determined if the hilsa stock of the examined wetlands maintains a single or several subpopulations in comparison to other parts of the country when they migrate from saline water to northeastern Bangladesh (freshwater). But when compared to other groups, the FST score was between 0.000 to 0.017, indicating that the populations are identical and that there is genetic material sharing between them. Additionally, these statistics imply that the Sylhet haor and adjacent river systems contain a single stock of Hilsa fish. Nevertheless, a number of stresses and risks, including overexploitation, illicit and destructive fishing, siltation, and natural disasters like flash floods, have been linked to changes in the supply of hilsa and other ecosystem services. This study also emphasizes the necessity of policy attention and research to address the concerns.

Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) continues to be a global threat due to its ability to evolve and generate new subvariants, leading to new waves of infection. Additionally, other coronaviruses like Middle East respiratory syndrome coronavirus (MERS-CoV, formerly known as hCoV-EMC) which first emerged in 2012, persists and continues to present a threat of severe illness to humans. The continued identification of novel coronaviruses, coupled with the potential for genetic recombination between different strains, raises the possibility of new coronavirus clades of global concern emerging. As a result, there is a pressing need for pan-CoV therapeutic drugs and vaccines. After extensive optimization of an HCV protease inhibitor screening hit, a novel 3CLPro inhibitor (MK-7845) was discovered and subsequently profiled. MK-7845 exhibited nanomolar in vitro potency with broad spectrum activity against a panel of clinical SARS-CoV-2 subvariants and MERS-CoV. Furthermore, when administered orally, MK-7845 demonstrated a notable reduction of viral burdens by &gt;6 log orders in the lungs of transgenic mice infected with SARS-CoV-2 (K18-hACE2 mice) and MERS-CoV (K18-hDDP4 mice).

The continuous casting process of helical fiber reinforced metal matrix composites was proposed, and the experimental equipment was designed and manufactured. The relationship model be-tween the process parameters and the helical shape of the fibers in the metal matrix is analyzed by differential geometry. Helical carbon fiber reinforced lead matrix composites were prepared under different conditions. When the melting temperature and cooling intensity were increased, the helical radius of helical carbon fiber in lead matrix was increased. When the fiber rotation speed was increased, the helical radius was decreased, and the helical pitch was de-creased proportionally. The experimental results are consistent with the process model. Carbon fiber rein-forced aluminum composites were prepared. Scanning electron microscopy showed that the infiltration between the aluminum matrix and the carbon fiber was not complete. As the volume fraction of carbon fiber which was added in composites is too small, the mechanical properties of the composites have not been significantly improved.

This article presents an innovative approach to the design of a safe adaptive backstepping control system. Tailored specifically for underactuated marine robots, the system utilizes simple sensors for enhanced practicality and efficiency. Given their operation in diverse oceanic environments fraught with various sources of uncertainties, ensuring the system's safe and robust behavior holds paramount importance in the control literature. To address this concern, this paper introduces a control strategy designed to ensure robustness at both the kinematic and dynamic levels. By emphasizing the compensation for the system uncertainties, the design integrates a straightforward fuzzy system structure. To further ensure the system's safety, a funnel surface is defined, followed by the design of a suitable nonlinear sliding surface as a function of the funnel and tracking error. Specifically leveraging the Lyapunov function, the study formally establishes the Semi-globally Practically Finite-time Stability of the closed-loop system, validated through simulations conducted on underactuated marine robots.

Several types of guided bone regeneration materials are available with various properties and clinical indications. Among them, dentin-derived matrix from extracted teeth is an excellent alternative to traditional graft materials, such as allografts and xenografts. Different clinical preparation protocols exist: block form versus powder form, demineralized versus non-demineralized form. Out of these methods, demineralization protocols for dentin-derived matrix from extracted teeth have been noted for a wide range of successful clinical outcomes. The purpose of this animal study was to find out the most effective method of demineralizing dentin-derived matrix to result in the highest regenerative ability in the bone graft material in rabbit calvaria. The study conducted a comparative histomorphometric analysis of four groups in distinguished matrix conditions: a control group without graft placement, a non-demineralized dentin-derived matrix graft placement group, a 15-minute demineralized dentin-derived matrix graft placement group, and a 30-minute demineralized dentin-derived matrix graft placement group. Regenerative processes were evaluated three times at 2, 4, and 8 weeks post-graft placement. These groups of rabbits were evaluated randomly in a blinded setting to prevent bias. Among the four groups compared, the group with a 15-minute demineralized dentin-derived matrix graft showed the most efficient bone regeneration in the histomorphometric analysis. Based on this animal study, it was apparent that a 15-minute demineralization of dentin-derived matrix is the preferred preparation protocol to maximize the regenerative potential in the matrix.

Promoting green development has become an important way to optimize the ecological and economic structure and promote sustainable development. The Yangtze River Economic Belt is an important economic corridor in China, and it remains to be examined whether the implementation of environmental regulations has enhanced the green total factor productivity (GTFP) of cities. This paper calculates the green total factor productivity of 107 cities within the Yangtze River Economic Belt by using the super-efficient SBM model and the GML index with Chinese city panel data from 2007-2019 and measures the intensity of environmental regulations through textual analysis. The bidirectional fixed-effects model constructed in this paper suggests an inverted U-shaped relationship between environmental regulation and GTFP, which is confirmed by a series of robustness tests. Green technology innovation and advanced industrial structure play a mechanism role in this. In regions with lower levels of green technology and industrial structure, the inverted U-shaped relationship between environmental regulation and green total factor productivity is more significant. In addition, the phenomenon of GTFP rising and then falling because of environmental regulation is more obvious in cities in the middle and upper reaches of the Yangtze River and outside the urban agglomerations. Therefore, when formulating environmental regulation policies, it is necessary to balance the relationship between economic development and environmental protection and harmonize the environment and economic development of the entire Yangtze River Basin.

The main purpose of this study is the determination of the optimal data acquisition and processing parameters of electric and seismic tomographic techniques, for the investigation of complex geological environments. Two different study areas, in central-east Peloponnese and SW Attica were selected, where a detailed geological mapping and surface geophysical survey were carried out. The applied geophysical survey included the application of electrical resistivity tomography (ERT) and seismic refraction tomography (SRT). The geoelectrical measurements were acquired with different arrays and electrode configurations. Moreover, various types of seismic sources were used at seventeen shot locations along the seismic arrays. For the processing of geoelectrical data, clustered datasets were created increasing the depth of investigation and the discriminatory capability. The seismic data processing included: (a) creation of synthetic models and seismic records to determine the effectiveness and capabilities of the technique, (b) spectral analysis of the seismic records to determine the optimal seismic source type and (c) inversion of the field data to create representative subsurface velocity models. The results of the two techniques successfully delineated the complex subsurface structure that characterizes these two geological environments. The application of the ERT combined with the SRT, are the two dominant, high-resolution techniques for the elucidation of complex subsurface structures.

Cocoa (Theobroma Cacao, L.) represents an important market that gained relevance and became an esteemed commodity thanks to cocoa powder, chocolate, and other related products. This work has analyzed 59 cocoa powder samples from the European market. Three distinct subgroups were identified: organic or conventional, alkalized or not alkalized, and raw or roasted processing. The impact of the technological process was evaluated on the pH, color, and compositional traits, as content of biogenic amines and salsolinol. The phenolic fraction was also investigated trough both common and emerging methods. Results depict that the influence of the agronomical practices (organic/conventional) did not affect significatively (p&lt;0.05) the composition of cocoa powders; similarly, the roasting process was not discriminative for the compounds traced. On the other hand, the alkalinization process greatly impacted on color, and pH, no matter of cocoa provenience, obtention, or other processes, also resulting reducing the phenolic fraction of treated samples. Principal components analysis confirmed that the alkali process acts on pH, color, and phenolic composition, but not on other bioactives molecules (BAs and salsolinol). All samples resulted safe while alkalized powders have a great reduction in beneficial biocompounds. A novel strategy could be to emphasize non-alkalized powders in the label, to meet the demand for more beneficial products.

Oral squamous cell carcinoma (OSCC) is a highly prevalent and aggressive malignancy, with mortality rates that reach 60%, mainly due to an excessive diagnostic delay. MiRNAs, a class of crucial epigenetic gene-expression regulators, have emerged as potential diagnostic biomarkers, with >200 molecules reported to be dysregulated in OSCC. We had previously established an in silico methodology for the identification of the most disease-specific molecules by bridging genetics and epigenetics. Here, we identified the stage-specific miRNAs that govern the asymptomatic early stages of oral tumorigenesis by exploiting the reverse interplay between miRNA-levels and their target-genes’ expression. Incorporating gene expression data from our group’s experimental hamster model of sequential oral oncogenesis, we bioinformatically detected the miRNAs that simultaneously target/regulate >75% of the genes that are characteristically upregulated or downregulated in the consecutive stages of hyperplasia, dysplasia and early-invasion OSCC, while exhibiting the opposite expressional dysregulation in OSCC-derived tissue and/or saliva specimens. We found that all stages share the downregulation of miR-34a-5p, miR124-3p, and miR-125b-5p, while miR-1-3p is underexpressed in dysplasia and early-invasion. Malignant early-invasion stage is distinguished by the downregulation of miR-147a and the overexpression of miR-155-5p, miR-423-3p and miR-34a-5p. The identification of stage-specific miRNA molecules may facilitate their utilization as biomarkers for presymptomatic OSCC diagnosis.

Hydrogen sulfide is present in active or extinct volcanic areas (mofettas). The habitable premises in these areas are affected by the presence of hydrogen sulfide, which, even in low concentrations, gives off a bad to unbearable smell. If the living spaces considered are closed enclosures, then a system can be designed to reduce the concentration of hydrogen sulfide. This paper presents a membrane way to reduce the hydrogen sulfide concentration to acceptable limits using a cellulosic derivative-propylene hollow fiber based composite membrane module. The cellulosic derivatives considered were carboxymethyl–cellulose (NaCMC), cellulose acetate (CA), methyl 2–hydroxyethyl–cellulose (MHEC), and 2–hydroxyethyl–cellulose (HEC). In the permeation module, hydrogen sulfide is captured with a solution of cadmium that forms cadmium sulfide, usable as a luminescent substance. The composite membranes were characterized by SEM, EDAX, FTIR, FTIR 2D maps, thermal analysis (TG and DSC) and from the perspective of hydrogen sulfide air removal performance. To determine the process performances, the variables were: the nature of the cellulosic derivative–polypropylene hollow fiber composite membrane, the concentration of hydrogen sulfide in the polluted air, the flow rate of polluted air, and the pH of the cadmium nitrate solution. Pertraction efficiency was maximum for the sodium carboxymethyl–cellulose (NaCMC)-polypropylene hollow fiber membrane, a hydrogen sulfide concentration in the polluted air of 20 ppm, polluted air flow rate of 50 L/min, and a pH of 2 and 4.

Estimating the ocean’s subsurface thermohaline information from satellite measurements is essential for understanding ocean dynamics and El Niño phenomenon. This paper proposes an improved double-output Residual Neural Network (DO-ResNet) model to concurrently estimate the ocean subsurface temperature (OST) and ocean subsurface salinity (OSS) in the tropical Western Pacific using multi-source remote sensing data, including sea surface temperature (SST), sea surface salinity (SSS), sea surface height anomaly(SSHA), sea surface wind (SSW), and geographical information (including longitude (LON) and latitude (LAT)). In the model experiment, Argo data were used to train and validate the model, and the root mean square error (RMSE), normalized root mean square error (NRMSE) and coefficient of determination (R²) were employed to evaluate the model's performance. The results showed that the sea surface parameters selected in this study have a positive effect on the estimation process, and the average RMSE and R² values for estimating OST (OSS) by the proposed model are 0.34 °C (0.05 psu) and 0.91 (0.95), respectively. Under the data conditions considered in this study, DO-ResNet demonstrates superior performance relative to the extreme gradient boosting model, random forest model, and artificial neural network model. Additionally, this study evaluates the model’s accuracy by comparing its estimations of OST and OSS across different depths with Argo-derived data, demonstrating the model's ability to effectively capture the most spatial features, and by comparing NRMSE across different depths and seasons, the model displays strong seasonal adaptability. In conclusion, this research introduces a novel artificial intelligence technique for estimating OST and OSS in the tropical Western Pacific Ocean.

The normal growth and development of skeletal muscle is essential for the health of the body. The regulation of skeletal muscle by intestinal microorganisms and their metabolites has been continuously revealed. Acetate is the predominant short-chain fatty acid synthesized by gut microbiota through the fermentation of dietary fiber, however, the underlying molecular mechanisms governing the interaction between acetate and skeletal muscle during rapid growth stage remain to be further elucidated; Here, specific pathogen-free (SPF) mice, germ-free (GF) mice, and germ-free mice supplemented with sodium acetate (GS) were used to evaluate the effects of acetate on skeletal muscle growth and development of young mice with gut microbiota deficiency; We found the concentration of serum acetate, body mass gain, succinate dehydrogenase activity and expression of myogenesis maker gene of skeletal muscle in the GS group was higher than GF group following sodium acetate supplement. Furthermore, the transcriptome analysis revealed that acetate activated biological processes regulating skeletal muscle growth and development in GF group that are inhibited due to gut microbiota deficiency. In vitro experiment, we proved that acetate up-regulated Gm16062 to promote skeletal muscle cell differentiation; Overall, our findings proved that acetate promote skeletal muscle growth and development in young mice via increase Gm16062 expression.

Phased injection of natural gas into internal combustion marine engines is a promising solution for optimizing performance and reducing harmful emissions, particularly unburned methane, a potent greenhouse gas. This innovative practice distinguishes itself from continuous injection because it allows for more precise control of the combustion process with only a slight increase in system complexity. By synchronizing the injection of natural gas with the intake and exhaust valve opening and closing times while also considering the gas path in the manifolds, methane release into the atmosphere is significantly reduced, making a substantial contribution to efforts to address climate change. Moreover, phased injection improves the efficiency of marine engines, resulting in reduced overall fuel consumption, lower fuel costs, and increased ship autonomy. This technology has been tested on a single-cylinder, large-bore, four-stroke research engine designed for marine applications, operating in dual-fuel mode with diesel and natural gas. Performance was compared with that of the conventional continuous feeding method. Evaluation of the effect on equivalent CO2 emissions indicates a potential reduction of up to approximately 20%. This reduction effectively brings greenhouse gas emissions below those of the diesel baseline case, especially when injection control is combined with supercharging control to optimize the air-fuel ratio.

In numerical simulations, achieving high accuracy without significantly increasing computational costs is often challenging. To address this, this paper presents an improved finite volume weighted essentially non-oscillatory (WENO) scheme tailored for applicability in computational fluid dynamics (CFD) and implemented in the flow solver NUAA-Turbo for simulating turbomachinery flows using both RANS and RANS/LES coupling. Firstly, the new WENO scheme is validated against classic numerical test cases to assess its stability and reliability in handling discontinuities, the Double problem, and Raleigh-Taylor (RT) instability issues. Compared to the original format, this enhanced finite volume WENO scheme demonstrates superior stability near discontinuities and resolves flow features with the same grid resolution more effectively. Next, for engineering applications related to turbomachinery, such as compressor and turbine characteristics, computations are performed using RANS, and the results obtained using WENO-ZQ3 and WENO-JS3 are compared. Finally, the new fifth-order WENO scheme is applied to RANS/LES coupled simulations of turbine wakes and film cooling. The results show that the enhanced finite volume WENO scheme offers improved stability and accuracy in engineering applications, allowing for high-precision calculations with fewer grid points to capture more detailed flow physics, thereby reducing computational costs in aerodynamic applications.

To conduct high-precision and high-resolution numerical simulation of complex flow structures in turbomachinery, a high-order finite volume weighted essentially non-oscillatory (WENO) scheme for the large eddy simulation (LES) is improved and embedded into the three-dimensional viscous unsteady CFD solver NUAA-Turbo. Firstly, the spectral characteristics and unsteady convergence of the improved WENO scheme are studied. Compared with the classical WENO scheme, the improved WENO scheme has better dissipation and dispersion characteristics and faster convergence speed. Then, the coefficient CW of the Wall-Adapting Local Eddy-viscosity (WALE) model is calibrated by decaying homogeneous isotropic turbulence (DHIT) test case. Finally, the scheme is applied to conduct high-precision LES calculations of turbulent boundary layer flow, supersonic compression corner flow, and low-pressure turbine cascade separation flow. The numerical simulation results show that this WENO scheme has excellent shock wave capture ability and turbulence resolution and can capture more flow field details with less mesh size, greatly reducing the computational cost and laying a foundation for large-scale engineering application of LES.

To secure logic circuits against the illegal copying the insertion of the so-called key bit inputs using XOR/XNOR gates has been proposed in . The inserted gates modify (lock) the behavior of the original circuit and only the correct choice of the secret key bits guarantees the equivalent behaviour of the locked circuit to the original circuit. To break this kind of security, i.e. to find the secret key bits, there was a SAT solver based attack proposed in . The aim of this work is to experimentally verify this attack on several locked circuits with various number of primary inputs and outputs and with various number of gates. Except for the random placement of the key gates we evaluate also the positioning with chaining elimination. The obtained and presented results show that we were able to unlock 10 of 11 circuits within few minutes on a common PC.

Intermetallic compounds are increasingly being expected to utilize in tribological environments, but to date the works are hindered by insufficient ductility at low and medium temperature. This paper presents a novel multiphase intermetallic alloy with the chemical composition of Mo-40Ni-13Si (at.%). Microstructure characterization reveals that a certain amount of ductile Mo phases formed during the solidification process of ternary Mo-Ni-Si alloy melt, which is undoubtedly beneficial to the ductility improvement of intermetallic alloy. Tribological properties of the designed alloy, including wear resistance, friction coefficient and metallic tribological compatibility, were evaluated under dry sliding wear test conditions at room temperature. Results suggested that the multiphase alloy possesses an excellent property for room-temperature wear applications, which is attributed to the unique microstructural features and thereby good combination in hardness and ductility. The corresponding wear mechanism is also reported by observing the worn surface, subsurface and wear debris of alloy, which to be found is soft abrasive wear.

With the integrated development of the Internet, wireless sensor technology, cloud computing, and mobile Internet, there has been a lot of attention given to research about and applications of the Internet of Things. A Wireless Sensor Network (WSN) is one of the important information technologies in the Internet of Things; it integrates multi-technology to detect and gather information in a network environment by mutual cooperation, using a variety of methods to process and analyze data, implement awareness, and perform tests. This paper mainly researches the localization algorithm of sensor nodes in a wireless sensor network. Firstly, a multi-granularity region partition is proposed to divide the location region. In the range-based method, the RSSI (Received Signal Strength indicator, RSSI) is used to estimate distance. The optimal RSSI value is computed by the Gaussian fitting method. Furthermore, a Voronoi diagram is characterized by the use of dividing region. Rach anchor node is regarded as the center of each region; the whole position region is divided into several regions and the sub-region of neighboring nodes is combined into triangles while the unknown node is locked in the ultimate area. Secondly, the multi-granularity regional division and Lagrange multiplier method are used to calculate the final coordinates. Because nodes are influenced by many factors in the practical application, two kinds of positioning methods are designed: the unknown node is in the positioning unit or not. When the unknown node is on the side of the positioning unit, we use the method of vector similarity. Moreover, we use the centroid algorithm to calculate the ultimate coordinates of unknown node. When the unknown node is not on the side of the positioning unit, we establish a Lagrange equation containing the constraint condition to calculate the first coordinates. Furthermore, we use the Taylor expansion formula to correct the coordinates of the unknown node. In addition, this localization method has been validated by establishing the real environment.

The electroencephalogram (EEG) is a record of brain activity. Brain Computer Interface (BCI) technology formed by the EEG signal has become one of the hotspots at present. How to extract the feature signal of EEG is the most basic research of BCI technology. In this paper, A new method of recognizing fatigue, conscious, concentrated state of human brain is proposed by the combination of discrete wavelet transform and the neural network based on EEG signal. First of all, the law signal is preprocessed by the wavelet denoising method because the law EEG signal contains a large number of high frequency noise, which is decomposed into multi-layer high frequency signal and low frequency signal. thus, δ wave, θ wave, α wave, β wave are obtained by the wavelet transform. And then, frequency band energy of the different wave is regards as the feature signal of EEG. In the experiment, the feature signal is classified by radial basic function (RBF) and annealed chaotic competitive learning network (ACCLN). RBF and ACCLN networks are trained with 500 sets of sample data and are tested by 100 sets of samples in different mental states. The experimental results show that the average accuracy of RBF network under three conditions are 88.75%, 88.25%, 88.5%, respectively, and the correct rate of ACCLN network is 97%, 98%, 98%, respectively.