Successful Development Research Articles

Fruit Disease Detection using Image Processing

These days within the agrarian assiduity we've a good reference in fruit field. As we know that India’s frugality is truly dependent upon the agrarian assiduity, so an advanced field is must necessary and important. That is why growers want the homemade process of covering the fruits from crop till its growing phase. Purely homemade observing will not give reasonable results and also consumes a lot of your time, hence proposing an resourceful smart husbandry approach. That helps growers to descry conditions in crops. The proposed work uses image processing ways like preprocessing to enhance the quality of an image and segmentation to partition the images also feature birth to prize some useful information and type to classify the diseases. Fruit conditions are a major problem in profitable losses and product in the agrarian assiduity worldwide. In this paper, an image processing approach is proposed for relating fruit conditions. conditions in fruit cause ruinous problem in profitable losses and producting agricultural assiduity worldwide. According to the Sri Lankan terrain, treatment details are taken by the growers from the field officers. But it can take a multitudinous days. So, this proposed system can be used to identify fruit conditions snappily and automatically. This proposed approach is composed of the following main way; Preprocessing, point birth, Bracket, Training &Testing. Our experimental results express that the proposed result can significantly support accurate discovery and automatic type of fruit diseases. Paper demonstrates the system for discovery of fruit complaint. Present days as there's restrictive interest for husbandry assiduity, successful development and enhanced product of fruit is abecedarian and imperative. For this reason agronomists bear homemade observing of fruits. But all the time primer observing will not give satisfactory results and they generally bear guidance from master. So there's demand for proposing an effective cultivating system which helps for better product and advancement with truly lower mortal trouble, Image processing strategies are employed for performance of proposed system. For image segmentation Four point vectors are used in the proposed system those are colour, morphology, texture and structure of hole on the fruit. The system utilizes two image databases, one for training of formerly stored complaint images and one further for performance of query images. For matching of patterns and identification of fruit conditions GLCM or CNN generality is used.

Characterization of sperm quality in captive-bred barramundi (Lates calcarifer): Effect on spawning performance and paternal contribution in mass-spawning events

Barramundi (Asian sea bass, Lates calcarifer) is a species with a mass-spawning reproductive strategy whereby adults synchronously release their gametes into the water column. In captivity, this reproductive strategy usually results in uneven paternal contributions to each cohort of progeny, creating skews in family size that hinder the effectiveness of selective breeding programs. As sperm quality influences fertilization success and early larval development, we investigated the relationship between sperm quality and spawning performance. Accordingly, we assessed three established breeding cohorts. Sperm samples (n = 22) were collected by cannulation. Sperm motility was assessed using CASA, and sperm viability and DNA integrity were evaluated using dual-fluorescence stains by flow cytometry. Broodstock were induced to spawn across two consecutive nights, and offspring were collected at 2.5 h and 12 h post-fertilization (hpf) and 24 h and 48 h post-hatching (hph). Offspring were assessed for morphological abnormalities, and key morphological parameters were recorded. Offspring collected at 2.5 hpf and 24 hph were genotyped to determine their parentage and examine the relationship between sperm quality of individual males and offspring survival. Results highlighted that male condition factor (K) and sperm quality were highly variable within each breeding cohort. Males with a lower condition factor showed lower sperm motility and velocity. In contrast, males with a higher condition factor showed higher sperm motility and velocity but also higher levels of sperm DNA damage. While all males were capable of fertilization, males with a lower condition factor had greater paternal contribution. In this study, a reduction in skewed paternity was also found on Night 2 of spawning compared to Night 1. Moreover, males from Tank B, which had the lowest level of sperm DNA damage, had the most even paternal contribution. Conversely, highly skewed maternal contributions were reported across all spawning events. The results of this study suggest that additional complex dynamics and further unmeasured variables, such as spawning behavior, social hierarchy, and the spawning induction procedure, may also skew family sizes. Therefore, further development of artificial reproductive technology is recommended to gain greater control over individual contribution and overcome current breeding bottlenecks.

The role of design engineers: Evidence from intra-firm knowledge and collaboration networks.

Successful new product development requires the integration of design and engineering, bridging the gap between technological feasibility and user-centric considerations. However, direct collaboration between designers and engineers with heterogeneous knowledge presents challenges. In this context, the role of design engineers-professionals skilled in both design and engineering-becomes pivotal. This study categorizes inventors into three primary groups: engineers, designers, and design engineers based on the type of patent applications they hold and investigates their differences in knowledge portfolios and collaboration patterns. The study relies on patent data for 4,665 US publicly-traded firms from 1980 to 2015 from the PATSTAT database, and constructs two networks for each firm period: a social network of inventors and a knowledge network of knowledge elements. Findings show that design engineers are highly connected within the social network but have disconnected knowledge in the knowledge network in comparison to engineers. While design engineers may not be the primary drivers of firms' technological innovations, they facilitate interdisciplinary communication and decision-making, fostering a design-technology integrated new product development environment. This research has practical implications for firms seeking to optimize their innovation processes by creating interdisciplinary teams that harness the complementary strengths of engineers and design engineers.

Application of 3D printing technology for the development of dose adjustable geriatric and pediatric formulation of celecoxib

Developing safe and effective formulations for the geriatric and pediatric population is a challenging task due to issues of swallowability and palatability. The lack of standardized procedures for pediatric formulations further complicates the process. Manipulating adult formulations for children can lead to suboptimal efficacy and safety concerns. To overcome these challenges, minitablets or spinklets are preferred for the geriatric and pediatric population due to their smaller size and flexible dose adjustment. The aim of this study is the development of a 3D printed spinklets formulation of celecoxib, a nonsteroidal anti-inflammatory drug, using hot melt extrusion to address the limitations of traditional manufacturing methods. Three different formulations of celecoxib were prepared using Poly-2-ethyl-tetra-oxazoline (Aquazol) with and without surfactant. Subsequently, the mechanical properties and solubility of the drug-loaded filaments were evaluated. Solid state characterization confirmed the drug conversion into an amorphous form during the extrusion process, Computer-aided design software facilitate sprinklets design for fused deposition modeling and scanning electron microscopy assess the surface morphology. Sophorolipids plasticize better than TPGS, resulting in lowering processing temperatures during melt extrusion. In vitro drug release showed successful enhancements in the dissolution of oral medications for pediatric patients, considering their distinctive physiological characteristics. Overall, this study demonstrates the successful development of PEtOx-based 3D printed celecoxib sprinklets by coupling hot-melt extrusion and 3D printing technology. Future exploration holds the potential to revolutionize pharmaceutical production and advance personalized medication formulations.

Current Strategies on the Enantioselective Synthesis of Modified Nucleosides

AbstractThe isolation of two carbocyclic nucleosides, viz., neplanocin A and aristeromycin, from natural sources, triggered a revolution in the scientific community, leading to the development of more versatile and therapeutically useful compounds. For this purpose, many new methods for the synthesis of the carbocyclic framework of nucleosides have been developed. These efforts resulted in the successful development of many marketable drugs. The inherent benefits associated with carbocyclic nucleosides, such as higher lipophilicity and metabolic stability, resistance against glycosidic hydrolysis and the ability to modify aromatic bases by cellular phosphorylases, make them popular for the development of drugs against cancer and different viruses. Classically, carbocyclic nucleosides of various ring sizes and configurations have been synthesized starting from chiral pool substrates, such as ribose, glucose, etc., but recently, many other new asymmetric versions have been developed. Herein, we present recent developments on the catalytic enantioselective synthesis of nucleoside analogues, including carbocyclic and other varieties. This account provides new insights into the future development of modified nucleosides.1 Introduction2 Cyclic Nucleosides3 Acyclic Nucleosides4 Conclusion

Trace polymer coated clarithromycin spherulites: Formation mechanism, improvement in pharmaceutical properties and development of high-drug-loading direct compression tablets

Clarithromycin (CLA) is a high dose antibiotic drug exhibiting poor flowability and tabletability, making the tablet development challenging. This study aims to develop spherulitic CLA by introducing trace amount of polymer in crystallization solution. Its formation mechanism, physicochemical properties and potential for the direct compression (DC) tablets development were also investigated. Morphological analyses and the in situ observation on crystallization process revealed that the CLA spherulites are formed by fractal branching growth from both sides of the threadlike precursor fibers. 1H NMR analysis and nucleation time monitoring indicated that the existence of hydroxypropyl cellulose in solution slowed down the crystal nucleation and growth rate by forming hydrogen bonding interactions with CLA molecules, making the system maintain high supersaturation, providing high driving forces for CLA spherulitic growth. In comparison to commercial CLA, the CLA spherulites exhibit profoundly improved flowability, tabletability and dissolution behaviors. XPS, contact angle and Raman mapping analysis confirmed the presence of a thin HPC layer on the surfaces and interior of CLA spherulitic particles, resulting in increasing powder plasticity, interparticulate bonding strength and powder wettability, thus better tabletability and dissolution performances. The improved flowability and tabletability of CLA spherulites also enabled the successful development of DC tablet formulation with a high CLA loading (82.8 wt%) and similar dissolution profiles to reference listed drug. This study provides a novel solid form of CLA with superior manufacturability for further development.

Best Practices and Strategies for Talent Acquisition, Retention and Development in Egypt

Purpose: The aim of the study was to investigate best practices and strategies for talent acquisition, retention, and development.
 Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries.
 Findings: In talent management, key strategies include assessing both skills and cultural fit in recruitment, providing continuous learning opportunities, promoting diversity and inclusion, offering competitive compensation, and fostering a supportive work environment through regular feedback and opportunities for advancement. These practices contribute to successful talent acquisition, retention, and development.
 Unique Contribution to Theory, Practice and Policy: Human capital theory, psychological contract theory & resource-based view (RBV) may be used to anchor future studies on best practices and strategies for talent acquisition, retention, and development. Organizations should adopt a comprehensive talent management approach that strategically integrates these practices, ensuring consistency across HR functions.HR policies and guidelines should promote the alignment of talent management practices, emphasizing the synergy between acquisition, retention, and development to optimize human capital.

Development of the tangent linear and adjoint models of the global online chemical transport model MPAS-CO2 v7.3

Abstract. We describe the development of the tangent linear (TL) and adjoint models of the Model for Prediction Across Scales (MPAS)-CO2 transport model, which is a global online chemical transport model developed upon the non-hydrostatic Model for Prediction Across Scales – Atmosphere (MPAS-A). The primary goal is to make the model system a valuable research tool for investigating atmospheric carbon transport and inverse modeling. First, we develop the TL code, encompassing all CO2 transport processes within the MPAS-CO2 forward model. Then, we construct the adjoint model using a combined strategy involving re-calculation and storage of the essential meteorological variables needed for CO2 transport. This strategy allows the adjoint model to undertake a long-period integration with moderate memory demands. To ensure accuracy, the TL and adjoint models undergo vigorous verifications through a series of standard tests. The adjoint model, through backward-in-time integration, calculates the sensitivity of atmospheric CO2 observations to surface CO2 fluxes and the initial atmospheric CO2 mixing ratio. To demonstrate the utility of the newly developed adjoint model, we conduct simulations for two types of atmospheric CO2 observations, namely the tower-based in situ CO2 mixing ratio and satellite-derived column-averaged CO2 mixing ratio (XCO2). A comparison between the sensitivity to surface flux calculated by the MPAS-CO2 adjoint model with its counterpart from CarbonTracker–Lagrange (CT-L) reveals a spatial agreement but notable magnitude differences. These differences, particularly evident for XCO2, might be attributed to the two model systems' differences in the simulation configuration, spatial resolution, and treatment of vertical mixing processes. Moreover, this comparison highlights the substantial loss of information in the atmospheric CO2 observations due to CT-L's spatial domain limitation. Furthermore, the adjoint sensitivity analysis demonstrates that the sensitivities to both surface flux and initial CO2 conditions spread out throughout the entire Northern Hemisphere within a month. MPAS-CO2 forward, TL, and adjoint models stand out for their calculation efficiency and variable-resolution capability, making them competitive in computational cost. In conclusion, the successful development of the MPAS-CO2 TL and adjoint models, and their integration into the MPAS-CO2 system, establish the possibility of using MPAS's unique features in atmospheric CO2 transport sensitivity studies and in inverse modeling with advanced methods such as variational data assimilation.

Development Challenges in Egypt: Constraints, Practices, and Opportunities

This paper analyzes the constraints, practices, and opportunities of Egypt’s development. Egypt experienced economic stagnation under the regime of President Hosni Mubarak which was exacerbated by the political situation that resulted from its end. Egypt’s economic efforts stalled and it was not until the end of the power struggle between the Muslim Brotherhood and the Egyptian Army, during the counterrevolutionary period, that political normalcy returned to the extent needed to focus on improvements of the domestic economic situation. This phase resulted in the election of President Abdel Fatah El-Sisi whose policies fought back against terrorism and initiated successful developmental efforts to address developmental constraints. These initiatives range from diplomatic efforts to solve the Nile River dispute between Egypt and Ethiopia, building roads and bridges, encouraging foreign investment, and increasing the supply of electricity. There is still a long way to go in terms of building various industries, increasing exports, lowering unemployment rates, and encouraging tourism as an important source of income and also a vital means of obtaining foreign currency. Successful development efforts in Egypt will allow for increased levels of self-sufficiency regarding agriculture and water as well as broader levels of prosperity across other sectors of production.

A smartphone-based crowd-sourced real-time surveillance platform (apple snail inspector) for the invasive snails: a design and development study

BackgroundThe large amphibious freshwater apple snail is an important invasive species in China, but there is currently no method available for their surveillance. The development and popularization of smartphones provide a new platform for research on surveillance technologies for the early detection and effective control of invasive species.MethodsThe ASI surveillance system was developed based on the infrastructure of the WeChat platform and Amap. The user can directly enter the game interface through the WeChat port on their mobile phone, and the system automatically obtains their location. The user can then report the location of apple snails. The administrator can audit the reported information, and all information can be exported to Microsoft Excel version 2016 for analysis. The map was generated by ArcGIS 10.2 and was used to characterize the spatial and temporal distribution of apple snails in Jiangsu Province.ResultsThe architecture of ASI consists of three parts: a mobile terminal, a server terminal and a desktop terminal. We published more than 10 tweets on the official WeChat account of the system to announce it to the public, and a total of 207 users in 2020 and 2021 correctly reported sightings of apple snails. We identified 550 apple snails breeding sites in 2020 and 2021, featuring ponds (81%), parks (17%) and farmland (2%). In addition, most of the locations contained snail eggs, and the reporting times mainly occurred between May and September.ConclusionsThe ASI is an effective surveillance system that can be used to identify the breeding locations of apple snails and provides the basis of prevention and control for its dispersal. Its successful development and operation provide new potential avenues for surveillance of other public health issues.Graphical

Kesiapan Elemen Support, Capacity Dan Value Untuk Pengembangan E-Government Pada Aplikasi “Miton” Bagian Administrasi Pembangunan Sekretariat Daerah Timor Tengah Utara Provinsi Nusa Tenggara Timur

This article aims to determine the extent of readiness for e-government development through the Online Integrated Information Management Application (Miton) in the Development Administration Section of the North Central Timor Regional Secretariat, East Nusa Tenggara Province. The problem focuses on 3 (three) important elements of e-Government Development, namely Support Elements, Capacity Elements, and Value Elements based on). To approach this problem, a theoretical reference from Indrajit, and an opinion from Indrajit (Indrajit 2016) was used. Data was collected through questionnaires and analyzed quantitatively. This study concluded that the average level of readiness of 3 (three) elements of successful e-government development in the Miton application it is 75.5% with the details of each element being as follows: (1) Support Elements are ready at 78.59%, (2) Capacity Elements are ready at 70.75%, (3) Value Elements are ready at 70.75% 77.14 %

Towards co-design of rehabilitation technologies: a collaborative approach to prioritize usability issues.

Early stakeholder engagement is critical to the successful development and translation of rehabilitation technologies, a pivotal step of which is usability testing with intended end-users. To this end, several methods employ end-user feedback to identify usability and implementation issues. However, the process of prioritizing identified issues seldom leverages the knowledge and expertise of the range of stakeholders who will ultimately affect the demand and supply of a device. This paper describes a novel method to prioritize end-user feedback using transdisciplinary stakeholder consultation and address it in subsequent product development. The proposed approach was demonstrated using a case study relating to the development of a novel technology for neural recovery after spinal cord injury. Feedback from five individuals with chronic spinal cord injury was collected during two-hour usability evaluation sessions with a fully functional high-fidelity system prototype. A think-aloud and semi-structured interview protocol was used with each participant to identify usability and acceptability issues relating to the system in a 3-phase approach. Phase 1 involved extracting usability issues from think-aloud and semi-structured interview data. Phase 2 involved rating the usability issues based on their significance, technical feasibility, and implementation priority by relevant internal and external stakeholders. Finally, Phase 3 involved aggregating the usability issues according to design and implementation elements to facilitate solution generation, and these solutions were then raised as action tasks for future design iterations. Sixty usability issues representing nine facets of usability were rated. Eighty percent of issues were rated to be of moderate to high significance, 83% were rated as being feasible to address, and 75% were rated as addressable using existing project resources. Fifty percent of the issues were rated to be a high priority for implementation. Evaluation of the grouped issues identified 21 tasks which were mapped to the product roadmap for integration into future design iterations. This paper presents a method for meaningful transdisciplinary stakeholder engagement in rehabilitation technology development that can extended to other projects. Alongside a worked example, we offer practical considerations for others seeking to co-develop rehabilitation technologies.

ARIMA Modeling and Forecasting of National Consumer Price Index in Nepal

This research aims to determine an Auto-Regressive Integrated Moving Average (ARIMA) model and forecasting the National Consumer Price Index (NCPI) in Nepal, using annual data from the fiscal year 1972/73 to 2022/23. The research utilized secondary data collected from the online bulletin published by Nepal Rastra Bank, aiming to enhance understanding of NCPI patterns and contribute to predictive modelling techniques for economic indicators. Adopting the Box-Jenkins technique and using E-Views statistical software, this study identifies ARIMA (1, 2, 8) as the most suitable model for NCPI forecasting. This selection is validated through meticulous diagnostic tests, affirming the appropriateness of the model, as evidenced by residuals exhibiting white noise characteristics. The research findings suggest a rapid increase in the National Consumer Price Index for the coming years. Implications of this research extend to both academic and policy-oriented audiences. A successful ARIMA model development holds significant potential for providing accurate predictions of future price trends in Nepal. This, in turn, can assist policymakers in making informed decisions regarding economic strategies, monetary policies, and inflation control measures. Moreover, the study's outcomes offer a foundational framework for future research endeavours in the domain of economic forecasting and modelling, contributing to the broader field of economic analysis and policy formulation.

Accelerating AI Innovation in Healthcare Through Mentorship.

The adoption of Artificial Intelligence (AI) in the Canadian healthcare system falls behind that of other countries. Socio-technological considerations such as organizational readiness and a limited understanding of the technology are a few barriers impeding its adoption. To address this need, this study implemented a five-month AI mentorship program with the primary objective of developing participants' AI toolset. The analysis of our program's effectiveness resulted in recommendations for a successful mentorship and AI development and implementation program. 12 innovators and 11 experts from diverse backgrounds were formally matched and two symposiums were integrated into the program design. 8 interviewed participants revealed positive perceptions of the program underscoring its contribution to their professional development. Recommendations for future programs include: (1) obtaining organizational commitment for each participant; (2) incorporating structural supports throughout the program; and (3) adopting a team-based mentorship approach. The findings of this study offer a foundation rooted in evidence for the formulation of policies necessary to promote the integration of AI in Canada.

PathoSense: a rapid electroanalyticaldevice platform for screening Salmonella in water samples.

Salmonella contamination is a major global health challenge, causing significant foodborne illness. However, current detection methods face limitations in sensitivity and time, which mostly rely on the culture-based detection techniques. Hence, there is an immediate and critical need to enhance early detection, reduce the incidence and impact of Salmonella contamination resulting in outbreaks. In this work, we demonstrate a portable non-faradaic, electrochemical sensing platform capable of detecting Salmonella in potable water with an assay turnaround time of ~ 9min. We evaluated the effectiveness of this sensing platform by studying two sensor configurations: one utilizing pure gold (Au) and the other incorporating a semiconductor namely a zinc oxide thin film coated on the surface of the gold (Au/ZnO). The inclusion of zinc oxide was intended to enhance the sensing capabilities of the system. Through comprehensive experimentation and analysis, the LoD (limit of detection) values for the Au sensor and Au/ZnO sensor were 0.9 and 0.6CFU/mL, respectively. In addition to sensitivity, we examined the sensing platform's precision and reproducibility. Both the Au sensor and Au/ZnO sensor exhibited remarkable consistency, with inter-study percentage coefficient of variation (%CV) and intra-study %CV consistently below 10%. The proposed sensing platform exhibits high sensitivity in detecting low concentrations of Salmonella in potable water. Its successful development demonstrates its potential as a rapid and on-site detection tool, offering portability and ease of use. This research opens new avenues for electrochemical-based sensors in food safety and public health, mitigating Salmonella outbreaks and improving water quality monitoring.

How stakeholders influence MaaS implementation? An analysis based on evolutionary game theory

Mobility as a service (MaaS) is an emerging mobility service that has received high expectations from the transportation sector in recent years. MaaS integrates multiple transportation services into a single platform, enhancing the accessibility of various transportation resources. However, the complex integration involved in MaaS leads to uncertainty in stakeholder interaction and system implementation. For the successful deployment and development of MaaS, this study aims to identify stakeholder enablers and barriers as well as to solve the uncertainty in MaaS implementation. We construct a tripartite evolutionary game model among government, transportation service providers (TSPs) and travelers. By synthesizing the evolutionary stability of each participant through simulation, we explored the impact of factors on stakeholder strategy choices and further analyzed the stability of equilibrium points in the system. The results show that: 1) Government subsidies and penalties, TSPs' costs and revenues, travelers' utility and expenses all impact the strategy choices of stakeholders. 2) The costs of government policy-making and TSPs will influence the evolution of MaaS system into two different development modes: free-market model and policy-supported model. 3) Travelers’ utilities play a crucial role in promoting the stability of travelers' adoption of MaaS. This study provides new insights into identifying stakeholder demands. The findings contribute to formulating specific policy recommendations and incentive measurements to help in the strengthen and forward movement of MaaS development in the future.

Anti-dengue potential and mosquitocidal effect of marine green algae-stabilized Mn-doped superparamagnetic iron oxide nanoparticles (Mn-SPIONs): an eco-friendly approach.

Vector-borne diseases pose a significant public health challenge in economically disadvantaged nations. Malaria, dengue fever, chikungunya, Zika, yellow fever, Japanese encephalitis, and lymphatic filariasis are spread by mosquitoes. Consequently, the most effective method of preventing these diseases is to eliminate the mosquito population. Historically, the majority of control programs have depended on chemical pesticides, including organochlorines, organophosphates, carbamates, and pyrethroids. Synthetic insecticides used to eradicate pests have the potential to contaminate groundwater, surface water, beneficial soil organisms, and non-target species. Nanotechnology is an innovative technology that has the potential to be used in insect control with great precision. The goal of this study was to test the in vitro anti-dengue potential and mosquitocidal activity of Chaetomorpha aerea and C. aerea-synthesized Mn-doped superparamagnetic iron oxide nanoparticles (CA-Mn-SPIONs). The synthesis of CA-Mn-SPIONs using C. aerea extract was verified by the observable alteration in the colour of the reaction mixture, transitioning from a pale green colour to a brown. The study of UV-Vis spectra revealed absorbance peaks at approximately 290nm, which can be attributed to the surface Plasmon resonance of the CA-Mn-SPIONs. The SEM, TEM, EDX, FTIR, vibrating sample magnetometry, and XRD analyses provided evidence that confirmed the presence of CA-Mn-SPIONs. In the present study, results revealed that C. aerea aqueous extract LC50 values against Ae. aegypti ranged from 222.942 (first instar larvae) to 349.877ppm in bioassays (pupae). CA-Mn-SPIONs had LC50 ranging from 20.199 (first instar larvae) to 26.918ppm (pupae). After treatment with 40ppm CA-Mn-SPIONs and 500ppm C. aerea extract in ovicidal tests, egg hatchability was lowered by 100%. Oviposition deterrence experiments showed that in Ae. aegypti, oviposition rates were lowered by more than 66% by 100ppm of green algal extract and by more than 71% by 10ppm of CA-Mn-SPIONs (oviposition activity index values were 0.50 and 0.55, respectively). Moreover, in vitro anti-dengue activity of CA-Mn-SPIONs has good anti-viral property against dengue viral cell lines. In addition, GC-MS analysis showed that 21 intriguing chemicals were discovered. Two significant phytoconstituents in the methanol extract of C. aerea include butanoic acid and palmitic acid. These two substances were examined using an in silico methodology against the NS5 methyltransferase protein and demonstrated good glide scores and binding affinities. Finally, we looked into the morphological damage and fluorescent emission of third instar Ae. aegypti larvae treated with CA-Mn-SPIONs. Fluorescent emission is consistent with ROS formation of CA-Mn-SPIONs against Ae. aegypti larvae. The present study determines that the key variables for the successful development of new insecticidal agents are rooted in the eco-compatibility and the provision of alternative tool for the pesticide manufacturing sector.

Paternal heat exposure affects progeny larval development in green-lipped mussels Perna canaliculus

The green-lipped mussel Perna canaliculus is critically important to the New Zealand aquaculture industry. However, the rise in marine heatwave (MHW) events poses an emerging threat to this industry through summer mortality events. This study investigated the potential for paternally mediated transgenerational plasticity to improve offspring performance under heat stress. We simulated a week-long MHW event, exposing male P. canaliculus broodstock to elevated (22°C) or ambient (17.5°C) temperatures immediately prior to spawning, and evaluated the effects of paternal heat exposure on successful development, size and acute thermal tolerance of their larvae that were also reared under ambient or elevated (20°C) temperatures through to completion of the lecithotrophic trochophore stage. Elevated paternal and larval temperatures both increased incidence of abnormal development, reducing larval yield, while initial D-veliger shell length was predominantly influenced by developmental temperature, with longer shells formed at 20°C. Veligers from heat-exposed fathers raised under 20°C showed a small, but significant, elevation in lethal tolerance 50 (LT50), the temperature at which 50% of the larvae are predicted to die, when exposed to an additional 1 h heat-shock. These results indicate that paternal heat exposure over a relatively short period can influence offspring performance in this species. The paternal exposure investigated showed limited positive effects on offspring thermal tolerance, which may be outweighed by the negative impact on larval development. As MHWs are forecasted to continue accelerating, understanding transgenerational effects of heat stress will be critical for maintaining high-quality hatchery yields through broodstock selection and may inform wild population forecasting models.

Machine learning algorithm for predict the in-hospital mortality in critically ill patients with congestive heart failure combined with chronic kidney disease

Background The objective of this study was to develop and validate a machine learning (ML) model for predict in-hospital mortality among critically ill patients with congestive heart failure (CHF) combined with chronic kidney disease (CKD). Methods After employing least absolute shrinkage and selection operator regression for feature selection, six distinct methodologies were employed in the construction of the model. The selection of the optimal model was based on the area under the curve (AUC). Furthermore, the interpretation of the chosen model was facilitated through the utilization of SHapley Additive exPlanation (SHAP) values and the Local Interpretable Model-Agnostic Explanations (LIME) algorithm. Results This study collected data and enrolled 5041 patients on CHF combined with CKD from 2008 to 2019, utilizing the Medical Information Mart for Intensive Care Unit. After selection, 22 of the 47 variables collected post-intensive care unit admission were identified as mortality-associated and subsequently utilized in the development of ML models. Among the six models generated, the eXtreme Gradient Boosting (XGBoost) model demonstrated the highest AUC at 0.837. Notably, the SHAP values highlighted the sequential organ failure assessment score, age, simplified acute physiology score II, and urine output as the four most influential variables in the XGBoost model. In addition, the LIME algorithm explains the individualized predictions. Conclusions In conclusion, our study accomplished the successful development and validation of ML models for predicting in-hospital mortality in critically ill patients with CHF combined with CKD. Notably, the XGBoost model emerged as the most efficacious among all the ML models employed.

Resilience to economic shrinking: reinterpreting the Asian economic miracle in a comparative perspective, 1964–2018

ABSTRACT The successful economic performance of Pacific Asia is often held as a source of inspiration for aspiring catching-up countries. Notwithstanding, recent literature suggests that a key to the understanding of successful long-term economic performance lies not only in the ability to generate economic growth, but in limiting incidences of economic shrinking. Such analyses to explain the Asian economic miracle are however in short supply. This study highlights the significance of economic shrinking in Asia in a comparative perspective to demonstrate how and why resilience to economic shrinking was a significant aspect of the successful development of the region. To approach the question of why some countries became more resilient than others we propose a social capability framework and apply it to a sample of 26 developing countries between 1964 and 2018. We construct a social capability index on which we develop a set of simple OLS regressions to estimate the impact of social capabilities on shrinking patterns. We demonstrate that poorly endowed countries do not lack the ability to generate growth, but their limited resilience prevents them from catching up.