Next-generation Techniques Research Articles

Modeling different strategies towards control of lung cancer: leveraging early detection and anti-cancer cell measures

The global population has encountered significant challenges throughout history due to infectious diseases. To comprehensively study these dynamics, a novel deterministic mathematical model, TCD I L 2 Z, is developed for the early detection and treatment of lung cancer. This model incorporates I L 2 cytokine and anti-PD-L1 inhibitors, enhancing the immune system’s anticancer response within five epidemiological compartments. The TCD I L 2 Z model is analyzed qualitatively and quantitatively, emphasizing local stability given the limited data-a critical component of epidemic modeling. The model is systematically validated by examining essential elements such as equilibrium points, the reproduction number ( R 0 ), stability, and sensitivity analysis. Next-generation techniques based on R 0 that track disease transmission rates across the sub-compartments are fed into the system. At the same time, sensitivity analysis helps model how a particular parameter affects the dynamics of the system. The stability on the global level of such therapy agents retrogrades individuals with immunosuppression or treated with I L 2 and anti-PD-L1 inhibitors admiring the Lyapunov functions’ applications. NSFD scheme based on the implicit method is used to find the exact value and is compared with Euler’s method and RK4, which guarantees accuracy. Thus, the simulations were conducted in the MATLAB environment. These simulations present the general symptomatic and asymptomatic consequences of lung cancer globally when detected in the middle and early stages, and measures of anticancer cells are implemented including boosting the immune system for low immune individuals. In addition, such a result provides knowledge about real-world control dynamics with I L 2 and anti-PD-L1 inhibitors. The studies will contribute to the understanding of disease spread patterns and will provide the basis for evidence-based intervention development that will be geared toward actual outcomes.

Next-Generation Frozen Elephant Trunk Technique in the Era of Precision Medicine.

The frozen elephant trunk (FET) technique can be applied to extensive aortic pathology, including lesions in the aortic arch and proximal descending thoracic aorta. FET is useful for tear-oriented surgery in dissections, managing malperfusion syndrome, and promoting positive aortic remodeling. Despite these benefits, complications such as distal stent-induced new entry and spinal cord ischemia can pose serious problems with the FET technique. To prevent these complications, careful sizing and planning of the FET are crucial. Additionally, since the FET technique involves total arch replacement, meticulous surgical skills are essential, particularly for young surgeons. In this article, we propose several techniques to simplify surgical procedures, which may lead to better outcomes for patients with extensive aortic pathology. In the era of precision medicine, the next-generation FET device could facilitate the treatment of complex aortic diseases through a patient-tailored approach.

Digital Epidemiology of Prescription Drug References on X (Formerly Twitter): Neural Network Topic Modeling and Sentiment Analysis.

Data from the social media platform X (formerly Twitter) can provide insights into the types of language that are used when discussing drug use. In past research using latent Dirichlet allocation (LDA), we found that tweets containing "street names" of prescription drugs were difficult to classify due to the similarity to other colloquialisms and lack of clarity over how the terms were used. Conversely, "brand name" references were more amenable to machine-driven categorization. This study sought to use next-generation techniques (beyond LDA) from natural language processing to reprocess X data and automatically cluster groups of tweets into topics to differentiate between street- and brand-name data sets. We also aimed to analyze the differences in emotional valence between the 2 data sets to study the relationship between engagement on social media and sentiment. We used the Twitter application programming interface to collect tweets that contained the street and brand name of a prescription drug within the tweet. Using BERTopic in combination with Uniform Manifold Approximation and Projection and k-means, we generated topics for the street-name corpus (n=170,618) and brand-name corpus (n=245,145). Valence Aware Dictionary and Sentiment Reasoner (VADER) scores were used to classify whether tweets within the topics had positive, negative, or neutral sentiments. Two different logistic regression classifiers were used to predict the sentiment label within each corpus. The first model used a tweet's engagement metrics and topic ID to predict the label, while the second model used those features in addition to the top 5000 tweets with the largest term-frequency-inverse document frequency score. Using BERTopic, we identified 40 topics for the street-name data set and 5 topics for the brand-name data set, which we generalized into 8 and 5 topics of discussion, respectively. Four of the general themes of discussion in the brand-name corpus referenced drug use, while 2 themes of discussion in the street-name corpus referenced drug use. From the VADER scores, we found that both corpora were inclined toward positive sentiment. Adding the vectorized tweet text increased the accuracy of our models by around 40% compared with the models that did not incorporate the tweet text in both corpora. BERTopic was able to classify tweets well. As with LDA, the discussion using brand names was more similar between tweets than the discussion using street names. VADER scores could only be logically applied to the brand-name corpus because of the high prevalence of non-drug-related topics in the street-name data. Brand-name tweets either discussed drugs positively or negatively, with few posts having a neutral emotionality. From our machine learning models, engagement alone was not enough to predict the sentiment label; the added context from the tweets was needed to understand the emotionality of a tweet.

Analytical analysis and bifurcation of pine wilt dynamical transmission with host vector and nonlinear incidence using sustainable fractional approach

To study the dynamical system, it is necessary to formulate a mathematical model to comprehend the dynamics of the diseases that are prevalent around the world by using fractional calculus. A mathematical model is developed with the hypothesis created by adding control and asymptomatic variables to observe the rate of change of pine wilt and the ABC operator is used to turn the model into a fractional ordered model for continuous monitoring. The Boundedness and uniqueness of the developed model are investigated for bounded findings by using Banach space, which are the key properties of such an epidemic model. A newly developed system is examined both qualitatively and quantitatively to determine its stable position, and the verification of flip bifurcation has been made for developed systems. Derived reproductive numbers using the next-generation technique as well as the sensitivity of each involved parameter are verified. The Atangana–Toufik scheme is employed to find the solution for the developed system using different fractional values, which are advanced tools for reliable bounded solutions. Simulations have been made to see the real behavior and effects of pine wilt disease with control and asymptomatic battels in the community. Also, identify the real situation of the spread as well as the control of pine wilt after employing control and asymptomatic battels due to treatment. Such a type of investigation will be useful in investigating the spread of disease as well as helpful in developing control strategies based on our justified outcomes.

Nanowatt all-optical 3D perception for mobile robotics.

Three-dimensional (3D) perception is vital to drive mobile robotics' progress toward intelligence. However, state-of-the-art 3D perception solutions require complicated postprocessing or point-by-point scanning, suffering computational burden, latency of tens of milliseconds, and additional power consumption. Here, we propose a parallel all-optical computational chipset 3D perception architecture (Aop3D) with nanowatt power and light speed. The 3D perception is executed during the light propagation over the passive chipset, and the captured light intensity distribution provides a direct reflection of the depth map, eliminating the need for extensive postprocessing. The prototype system of Aop3D is tested in various scenarios and deployed to a mobile robot, demonstrating unprecedented performance in distance detection and obstacle avoidance. Moreover, Aop3D works at a frame rate of 600 hertz and a power consumption of 33.3 nanowatts per meta-pixel experimentally. Our work is promising toward next-generation direct 3D perception techniques with light speed and high energy efficiency.

A retrospective study of the yield of next-generation sequencing in the diagnosis of developmental and epileptic encephalopathies and epileptic encephalopathies in 0-12 years aged children at a single tertiary care hospital in South India.

Studies on the genetic yield of developmental and epileptic encephalopathy and Epileptic encephalopathies using next-generation sequencing techniques are sparse from the Indian subcontinent. Hence, the study was conducted to assess the yield of genetic testing and the proportion of children where a positive genetic yield influenced treatment decisions. In this retrospective observational study, electronic medical records of children (0-12 years) with suspected genetic epilepsy who underwent genetic testing using whole exome sequencing, focused exome sequencing and epilepsy gene panels were retrieved. Genetic yield was ascertained based on the detection of pathogenic and likely pathogenic variants. A total of 100 patients with epilepsy underwent genetic testing. A yield of 53.8% (42/78) was obtained. Pathogenic variants were identified in 18 (42.8%) cases and likely pathogenic variants in 24 (57.1%) cases. Yield was 66.6% each through whole exome sequencing, focused exome sequencing and 40% through Epilepsy gene panels (p = .07). Yield was not statistically significant across different age groups (p = .2). It was however found to significantly vary across different epilepsy syndromes with maximum yield in Epilepsy in infancy with migrating focal seizures in 2 (100%), followed by developmental and epileptic encephalopathy unspecified in 14 (77.7%), Dravet syndrome in 14 (60.8%), early infantile developmental and epileptic encephalopathy in 3 (60%), infantile epileptic spasm syndrome in 5 (35.7%), and other epileptic encephalopathies in 4 (30.7%) cases (p = .04). After genetic diagnosis and drug optimization, drug-refractory proportion reduced from 73.8% to 45.3%. About half of the cases achieved seizure control. A reasonably high yield of 53.8% was obtained irrespective of the choice of panel or exome or age group using next-generation sequencing-based techniques. Yield was however higher in certain epilepsy syndromes and low in Infantile epileptic spasms syndrome. A specific genetic diagnosis facilitated tailored treatment leading to seizure freedom in 28.6% and marked seizure reduction in 54.7% cases.

The microbial composition of pancreatic ductal adenocarcinoma: A systematic review of 16S rRNA gene sequencing.

Pancreatic cancer, specifically pancreatic ductal adenocarcinoma (PDAC), continues to pose a significant clinical and scientific challenge. The most significant finding of recent years is that PDAC tumours harbour their specific microbiome, which differs amongst tumour entities and is distinct from healthy tissue. This review aims to evaluate and summarise all PDAC studies that have used the next-generation technique, 16S rRNA gene amplicon sequencing within each bodily compartment. As well as establishing a causal relationship between PDAC and the microbiome. This systematic review was carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. A comprehensive search strategy was designed, and 1727 studies were analysed. In total, 38 studies were selected for qualitative analysis and summarised significant PDAC bacterial signatures. Despite the growing amount of data provided, we are not able to state a universal 16S rRNA gene microbial signature that can be used for PDAC screening. This is most certainly due to the heterogeneity of the presentation of results, lack of available datasets and the intrinsic selection bias between studies. Several key studies have begun to shed light on causality and the influence the microbiome constituents and their produced metabolites could play in tumorigenesis and influencing outcomes. The challenge in this field is to shape the available microbial data into targetable signatures. Making sequenced data readily available is critical, coupled with the coordinated standardisation of data and the need for consensus guidelines in studies investigating the microbiome in PDAC.

Low-cost scalable high-power-density solar thermochemical energy storage via accelerating ion diffusion in Calcium-based solid wastes

Calcium-based solar thermochemical energy storage (TCES) has a great potential for next-generation concentrated solar power (CSP) systems due to its unique advantages of high operation temperature from 750 ℃ to 900 ℃ and high energy storage density, while current Calcium-based pellets suffer from poor cyclic stability and slow reaction kinetics. The mainstream solution relies on expensive inert stabilizers and complicated fabrication processes, which severely limited their affordability and scalability. Herein, we propose a strategy for recycling different Ca-based solid wastes, achieving low-cost and scalable high-power-density solar TCES simultaneously via the synergistic effect of multiple solid wastes and MgCl2. The power density of proposed pellets is 2 times than that of the conventional CaCO3, as the promoted solid-state diffusion of Ca2+ accelerates the decomposition of CaCO3. The energy storage density is as high as 1191 kJ/kg after 50 cycles, along with energy storage economy higher than 70 MJ/$ and friction loss less than 0.3 %, far exceeding that of the state-of-the-art Calcium-based TCES pellets. The feasibility of high-performance solar-driven TCES is further demonstrated on a pilot-scale system, providing a promising high-temperature thermal energy storage solution for next-generation CSP techniques.

Predicting the shear strength of rectangular RC beams strengthened with externally-bonded FRP composites using constrained monotonic neural networks

Fiber-reinforced polymer (FRP) composites bonded externally to reinforced concrete beams have shown promise for increasing shear load-carrying capacity. However, accurately predicting the shear strength contribution of FRP remains challenging due to the complexity of the shear failure mechanisms and interactions between the contributing components. Existing design provisions have limitations in modeling this behavior. Recently, machine learning has shown promise for addressing such complex problems but lacks transparency. Therefore, this study developed a data-driven Constrained Monotonic Neural Network (CMNN) approach implemented using Python libraries Keras and Tensorflow, which integrates domain knowledge to provide reliable FRP shear-strength predictions. This framework directly encodes expected monotonic input-output relationships through constraints, harnessing both predictive power and monotonicity guarantees. A comprehensive database of 273 beam tests was used to train and evaluate the model. Bayesian optimization through the Optuna framework and 4-fold cross-validation were used to tune the hyperparameters of the CMNN model. Extensive evaluation demonstrated the CMNN model's superior accuracy, yielding an R² value over 0.9, a CI above 0.93 and a low MAE under 16 kN on both training and unseen test data. The model also outperformed existing design code provisions, achieving significantly optimal performance metrics across various strengthening configurations. The analysis of the predictions revealed logical sensitivity trends aligned with the principles of shear mechanics. Such physics-informed machine learning presents a next-generation technique for performance-based structural design, contributing an effective and interpretable tool to advance knowledge on quantifying the shear capacity contribution of externally bonded FRP reinforcement in concrete beams.

Next-Generation Exoscopic Surgery Featuring a Head-Mounted 3-Dimensional Display for Carotid Endarterectomy: 2-Dimensional Operative Video.

Recent advancements in medical equipment have led to the use of exoscopes in neurosurgery, thereby replacing conventional operating microscopes.1,2 These devices enable surgeons to work comfortably, even in situations requiring a tilted visual axis, and their effectiveness in carotid endarterectomy (CEA) for carotid artery stenosis has been reported.3,4 However, the placement of 3-dimensional (3D) monitoring devices is challenging.3,4 To address this issue, we present a case in which CEA was performed using ORBEYE with a 3D head-mounted display. This device allows continuous 3D observation of the surgical field on the preocular screen. Case: A 79-year-old man who had undergone chemoradiotherapy for left maxillary cancer 5 years earlier was referred to our department to undergo treatment for left internal carotid artery stenosis. Computed tomography angiography revealed severe left internal carotid artery stenosis with hypoechoic vulnerable plaques on carotid ultrasound. Carotid artery stenting was considered to be a better option than CEA. However, CEA yields better outcomes, especially in patients with vulnerable soft plaques.5 Left CEA was performed using ORBEYE with a 3D head-mounted display (HOGY Medical Co., Ltd.). The procedure was successfully performed under the observation of the head-mounted display, from skin incision to closure. Postoperatively, the patient had no neurological deficits but experienced transient hoarseness. Using an exoscope under the guidance of a head-mounted display represents a next-generation surgical technique that overcomes the limitations of traditional exoscopic surgery. The patient consented to the procedure, and the participants and any identifiable individuals consented to publication of his/her image. Our institutional review board approved this publication (#B230184).

Current Diagnostic Approaches in the Genetic Diagnosis of Disorders of Sex Development.

Disorders of sex development (DSD) are a clinically and genetically highly heterogeneous group of congenital disorders. The most accurate and rapid diagnosis may be possible with a complementary multidisciplinary diagnostic approach, including comprehensive clinical, hormonal, and genetic investigations. Rapid and accurate diagnosis of DSD requires urgency in terms of gender selection and management of the case. Despite the genetic tests performed in current daily practice, the genetic cause is still not elucidated in a significant proportion of cases. Karyotype analysis can be used as a standard for sex chromosome identification. In addition, quantitative fluorescent polymerase chain reaction (QF-PCR) or fluorescence in situ hybridization (FISH) analysis can be used for faster and more cost-effective detection of the sex chromosome and SRY gene. Multiplex ligation-dependent probe amplification (MLPA), single-gene sequence analysis, next-generation sequence analysis (NGSA), targeted NGSA, whole-exome sequencing (WES), and whole-genome sequencing (WGS) analyses can be performed according to preliminary diagnoses. Microarray analysis (array comparative genomic hybridization (aCGH) and single nucleotide polymorphism array (SNPa)) should be performed in cases with syndromic findings and if no pathology is detected with other tests. In DSD cases, the use of optical genome mapping and techniques, which will probably be in daily practice in near future, may be considered. In conclusion, the clinical and genetic diagnosis of DSD is difficult, and molecular genetic diagnosis is often not available. This has psychosocial and health implications for patients and their families. New genetic techniques, especially those targeting the whole genome, may provide a better understanding of DSD through the identification of little-known genetic causes. This review focuses on conventional genetic and next-generation genetic techniques used in the genetic diagnosis of DSD, as well as possible genetic diagnostic techniques and approaches that may be used in routine practice in near future.

A review on drainage of dredged marine soils: Advances and prospects

Drainage is a common practice in geotechnical engineering concerning dredged marine soils. Current drainage techniques, including surcharge preloading, vacuum preloading, and combined vacuum-surcharge preloading, have been proven to be effective in soft soil treatment, but are also criticized for their high energy consumption. This paper made a brief review on existing drainage techniques and proposed some prospects for the next-generation techniques in response to the public concern of sustainability. It is found that all conventional preloading techniques have been well studied from tests to modeling, and improved vacuum preloading tends to be used in combination with other techniques. Drainage techniques with lower energy consumption can be realized either by using renewable energy or designing biomimetic devices. The paper is expected to provide a comprehensive while concise report on recent advances in drainage techniques for dredged marine soils and in the meanwhile give an insight into the further development towards a more sustainable future.

Habitat shapes the gut microbiome diversity of Malayan tigers (Panthera tigris jacksoni) as revealed through metabarcoding 16S rRNA profiling.

The gut microbiome refers to the microorganism community living within the digestive tract. The environment plays a crucial role in shaping the gut microbiome composition of animals. The gut microbiome influences the health and behavior of animals, including the critically endangered Malayan tiger(Panthera tigris jacksoni). However, the gut microbiome composition of Malayan tigers, especially those living in their natural habitats, remains poorly understood. To address this knowledge gap, we used next-generation sequencing DNA metabarcoding techniques to analyze the gut microbiome of wild Malayan tigers using fecal samples collected from their natural habitats and in captivity. Our aim was to determine the gut microbiota composition of the Malayan tiger, considering the different types of habitat environments. The results revealed a diverse microbial community within the gut microbiome of Malayan tigers. The prominent phyla that were observed included Firmicutes, Proteobacteria, Actinobacteriota, Fusobacteriota and Bacteroidota. Beta diversity analysis revealed significant differences in gut microbiome composition of Malayan tigers that inhabited oil palm plantations, in villages and protected areas. Diversity analysis also revealed significant difference in the gut microbiome between wild and captive Malayan tigers. However, the distinctions of gut microbiome between wild and captive alpha diversity did not yield significant differences. The differences in microbiome diversity resulted from the interplay of dietary intake and environmental factors. This information will facilitate the establishment of focused conservation approaches and enhance our understanding of the effect of microbiome composition on Malayan tiger health.

Effect of different forms of tobacco on the oral microbiome in healthy adults: a systematic review.

The study aimed to evaluate the impact of tobacco use on the composition and functions of the oral microbiome in healthy adult humans. We conducted a systematic search on PubMed, Web of Science, and Cinhal databases for literature published until 15 December 2023, to identify studies that have evaluated the oral microbiome with culture-independent next-generation techniques comparing the oral microbiome of tobacco users and non-users. The search followed the PECO format. The outcomes included changes in microbial diversity and abundance of microbial taxa. The quality assessment was performed using the Newcastle-Ottawa Scale (NOS) (PROSPERO ID CRD42022340151). Out of 2,435 articles screened, 36 articles satisfied the eligibility criteria and were selected for full-text review. Despite differences in design, quality, and population characteristics, most studies reported an increase in bacterial diversity and richness in tobacco users. The most notable bacterial taxa enriched in users were Fusobacteria and Actinobacteria at the phylum level and Streptococcus, Prevotella, and Veillonella at the genus level. At the functional level, more similarities could be noted; amino acid metabolism and xenobiotic biodegradation pathways were increased in tobacco users compared to non-users. Most of the studies were of good quality on the NOS scale. Tobacco smoking influences oral microbial community harmony, and it shows a definitive shift towards a proinflammatory milieu. Heterogeneities were detected due to sampling and other methodological differences, emphasizing the need for greater quality research using standardized methods and reporting. CRD42022340151.

Next-generation therapeutics for rare genetic disorders.

The therapeutic potential of the human genome has been explored through the development of next-generation therapeutics, which have had a high impact on treating genetic disorders. Classical treatments have traditionally focused on common diseases that require repeated treatments. However, with the recent advancements in the development of nucleic acids, utilizing DNA and RNA to modify or correct gene expression in genetic disorders, there has been a paradigm shift in the treatment of rare diseases, offering more potential one-time cure options. Advanced technologies that use CRISPR-Cas 9, antisense oligonucleotides, siRNA, miRNA, and aptamers are promising tools that have achieved successful breakthroughs in the treatment of various genetic disorders. The advancement in the chemistry of these molecules has improved their efficacy, reduced toxicity, and expanded their clinical use across a wide range of tissues in various categories of human disorders. However, challenges persist regarding the safety and efficacy of these advanced technologies in translating into clinical practice. This review mainly focuses on the potential therapies for rare genetic diseases and considers how next-generation techniques enable drug development to achieve long-lasting curative effects through gene inhibition, replacement, and editing.

Fabrication Technology of Self-Dissolving Sodium Hyaluronate Gels Ultrafine Microneedles for Medical Applications with UV-Curing Gas-Permeable Mold.

Microneedles are of great interest in diverse fields, including cosmetics, drug delivery systems, chromatography, and biological sensing for disease diagnosis. Self-dissolving ultrafine microneedles of pure sodium hyaluronate hydrogels were fabricated using a UV-curing TiO2-SiO2 gas-permeable mold polymerized by sol-gel hydrolysis reactions in nanoimprint lithography processes under refrigeration at 5 °C, where thermal decomposition of microneedle components can be avoided. The moldability, strength, and dissolution behavior of sodium hyaluronate hydrogels with different molecular weights were compared to evaluate the suitability of ultrafine microneedles with a bottom diameter of 40 μm and a height of 80 μm. The appropriate molecular weight range and formulation of pure sodium hyaluronate hydrogels were found to control the dissolution behavior of self-dissolving ultrafine microneedles while maintaining the moldability and strength of the microneedles. This fabrication technology of ultrafine microneedles expands their possibilities as a next-generation technique for bioactive gels for controlling the blood levels of drugs and avoiding pain during administration.

Mathematical analysis and numerical simulations of the piecewise dynamics model of Malaria transmission: A case study in Yemen

<abstract><p>This study presents a mathematical model capturing Malaria transmission dynamics in Yemen, incorporating a social hierarchy structure. Piecewise Caputo-Fabrizio derivatives are utilized to effectively capture intricate dynamics, discontinuities, and different behaviors. Statistical data from 2000 to 2021 is collected and analyzed, providing predictions for Malaria cases in Yemen from 2022 to 2024 using Eviews and Autoregressive Integrated Moving Average models. The model investigates the crossover effect by dividing the study interval into two subintervals, establishing existence, uniqueness, positivity, and boundedness of solutions through fixed-point techniques and fractional-order properties of the Laplace transformation. The basic reproduction number is computed using a next-generation technique, and numerical solutions are obtained using the Adams-Bashforth method. The results are comprehensively discussed through graphs. The obtained results can help us to better control and predict the spread of the disease.</p></abstract>

Aicardi-Goutières Syndrome Type 1: A Novel Missense Variant and Review of the Mutational Spectrum.

Mutations in the TREX1 gene cause Aicardi-Goutières syndrome (AGS) 1, associated with a spectrum of autoimmune and neurodegenerative manifestations. AGS 1, the most severe neonatal type of AGS, is characterized by abnormal neurologic findings, visual inattention, hepatosplenomegaly, thrombocytopenia, skin rash, restlessness, and fever. The present study described two affected siblings from an Iranian family whose phenotypes overlap with intrauterine infections. They had almost similar presentations, including developmental delay, microcephaly, no fix and follow epileptic seizures and the same pattern of brain CT scan involvements. Following clinical and paraclinical assessments, whole-exome sequencing was employed to determine the disease-causing variant, and subsequently, PCR-Sanger sequencing was performed to indicate the segregation pattern of the candidate variant in family members. Genetic analysis revealed a novel homozygous missense variant (c.461A>C; p.D154A) in the TREX1 gene in affected family members. Sanger sequencing of other family members showed the expected zygosities. This study identifies a novel mutation in the TREX1 gene in this family and highlights the efficiency of next-generation sequencing-based techniques for obtaining a definite diagnosis in patients with early-onset encephalopathy.

Exploring the interplay between climate change and schistosomiasis transmission dynamics

Schistosomiasis, a neglected tropical disease caused by parasitic worms, poses a major public health challenge in economically disadvantaged regions, especially in Sub-Saharan Africa. Climate factors, such as temperature and rainfall patterns, play a crucial role in the transmission dynamics of the disease. This study presents a deterministic model that aims to evaluate the temporal and seasonal transmission dynamics of schistosomiasis by examining the influence of temperature and rainfall over time. Equilibrium states are examined to ascertain their existence and stability employing the center manifold theory, while the basic reproduction number is calculated using the next-generation technique. To validate the model's applicability, demographic and climatological data from Uganda, Kenya, and Tanzania, which are endemic East African countries situated in the tropical region, are utilized as a case study region. The findings of this study provide evidence that the transmission of schistosomiasis in human populations is significantly influenced by seasonal and monthly variations, with incidence rates varying across countries depending on the frequency of temperature and rainfall. Consequently, the region is marked by both schistosomiasis emergencies and re-emergences. Specifically, it is observed that monthly mean temperatures within the range of 22–27 °C create favorable conditions for the development of schistosomiasis and have a positive impact on the reproduction numbers. On the other hand, monthly maximum temperatures ranging from 27 to 33 °C have an adverse effect on transmission. Furthermore, through sensitivity analysis, it is projected that by the year 2050, factors such as the recruitment rate of snails, the presence of parasite egg-containing stools, and the rate of miracidia shedding per parasite egg will contribute significantly to the occurrence and control of schistosomiasis infections. This study highlights the significant influence of seasonal and monthly variations, driven by temperature and rainfall patterns, on the transmission dynamics of schistosomiasis. These findings underscore the importance of considering climate factors in the control and prevention strategies of schistosomiasis. Additionally, the projected impact of various factors on schistosomiasis infections by 2050 emphasizes the need for proactive measures to mitigate the disease's impact on vulnerable populations. Overall, this research provides valuable insights to anticipate future challenges and devise adaptive measures to address schistosomiasis transmission patterns.

In-situ repairing quantum-dot-monolayer-film defects for laminated light-emitting diodes

Quantum dot (QD) light-emitting diodes (QLEDs) have become one of the primary development directions for next-generation display techniques due to their excellent optoelectronic and solution-processing properties. High-performance QLEDs rely on high-quality light-emitting layers that are mainly stacked QD films deposited by spin-coating (SC). However, preparing large-area and defect-free monolayer films, which is crucial for high-quality displays, is the inherent drawback of the SC technique and is still challenging. Herein, we propose an in-situ defect-repairing strategy to create defect-passivating monolayer QD films at a liquid/air interface by a simple injection assembly (IA) technique. The monolayer QD film was assembled and passivated by a simple n-butylamine injection into ethylene glycol (EG), prompting the IA-QLEDs to exhibit excellent electrical performance. The as-fabricated IA-QLEDs outperform conventional SC-QLEDs with EQEs exceeding 24 % and significantly extended lifetimes. Furthermore, our method demonstrated its scalability (a defect-free 7×5 cm2 monolayer is fabricated), enabling the fabrication of large-area QD films with uniform morphology through a straightforward expansion of the film-forming container. This work proposes a general strategy for interfacial film formation and defect repair of QD film and holds significant promise for the practical application of high-performance QLEDs.