The National Contact Center (NCC) in the Kingdom of Bahrain serves as a pivotal platform for government clients to voice inquiries, requests, suggestions, and complaints regarding various government services. This paper introduces a secure platform for an Intelligent Agent (IA) named “Ali”. It is driven by Artificial Intelligence, engages in conversational interactions with e-Government customers. The platform incorporates Natural Language Processing (NLP) and Deep Learning (DL) to train the IA in understanding queries and formulating responses through Natural Language Generation (NLG). Ali is tasked with addressing incoming calls and executing various functions such as answering questions, executing actions, integrating with call center systems like Client Relationship Management (CRM), directing inquiries to appropriate government departments, completing forms, and scheduling appointments. The platform is tailored for a Bahraini IA proficient in Arabic and English, equipped with intelligent capabilities. To ensure customer privacy and security and to comply with Bahrain’s laws and regulations, the platform boasts a comprehensive security framework covering all aspects of security layers, network security, storage security, operating system security, system software and application security, data security, identity and access management, and service level agreements. This research delves into the architecture of conversational AI and the Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Natural Language Understanding (NLU), and Natural Language Generation (NLG) components that collaborate to enable the IA’s functionality. The proposed project entails the development of an Intelligent Agent Framework in partnership with the Information and eGovernment Authority (iGA). The initiative involves initiating the IA project, delineating its scope, planning its phases, designing the solution architecture and requirements, and establishing security requirements for the chosen cloud model.

An increasing number of AI-based gender-swap applications have become a popular trend in our social media platforms and communities, rising controversial issues beyond their apparently playful intent. The primary ludic function informing the use/consumption of such apps opens to further signification and valorization of the produced images. In many cases, the portrait pictures, modified through a system of filters, assume an existential and utopic value for (transgender and nonbinary) users who have the possibility to reimagining and reperforming their gender identity. At the same time, the social availability and disposability of such images risk to trivialize the subjective and highly complex process of sexual and gender transition undergone by many people on their own material body in the real life. The aim of this paper is to point out the ambivalences and the possibilities opened by gender-swap apps for what concerns the issue of gender identity. Through the analysis of a corpus of promotional messages and users’ responses to the gender-swap apps, it is argued that these trans-faces, far from operating a flawless passing from a gender to the other, constantly dis-play the social construction and deconstruction of sexual and gender binary identities.

Wildfires and heatwaves have recently affected the hydrological system in unprecedented ways due to climate change. In cold regions, these extremes cause rapid reductions in snow and ice albedo due to soot deposition and unseasonal melt. Snow and ice albedo dynamics control net shortwave radiation and the available energy for melt and runoff generation. Many albedo algorithms in hydrological models cannot accurately simulate albedo dynamics because they were developed or parameterised based on historical observations. Remotely sensed albedo data assimilation (DA) can potentially improve model performance by updating modelled albedo with observations. This study seeks to diagnose the effects of remotely sensed snow and ice albedo DA on the prediction of streamflow from glacierized basins during wildfires and heatwaves. Sentinel-2 20-m albedo estimates were assimilated into a glacio-hydrological model created using the Cold Regions Hydrological Modelling Platform (CRHM) in two Canadian Rockies glacierized basins, Athabasca Glacier Research Basin (AGRB) and Peyto Glacier Research Basin (PGRB). The study was conducted in 2018 (wildfires), 2019 (soot/algae), 2020 (normal), and 2021 (heatwaves). DA was employed to assimilate albedo into CRHM to simulate streamflow and was compared to a control run (CTRL) using off-the-shelf albedo parameters. Albedo DA benefited streamflow predictions during wildfires for both basins, with a KGE coefficient improvement of 0.18 and 0.20 in AGRB and PGRB, respectively. Four-year DA streamflow predictions were superior to CTRL in PGRB, but DA was slightly better in AGRB. DA was not beneficial to streamflow predictions during heatwaves. These results show that albedo DA can reveal otherwise unknown albedo and snowpack dynamics occurring in remote glacier accumulation zones that are not well simulated by model predictions alone. These findings corroborate the power of observational tools to incorporate near real-time information into hydrological models to better inform water managers of the streamflow response to wildfires and heatwaves.

Environmental gradients can influence morpho-physiological and life-history differences in natural populations. It is unclear, however, to what extent such gradients can also modulate phenotypic differences in other organismal characteristics such as the structure and function of host-associated microbial communities. In this work, we addressed this question by assessing intra-specific variation in the diversity, structure and function of environmental-associated (sediment and water) and animal-associated (skin and gut) microbiota along an environmental gradient of pollution in one of the most urbanized coastal areas in the world. Using the tropical sea cucumber Holothuria leucospilota, we tested the interplay between deterministic (e.g., environmental/host filtering) and stochastic (e.g., random microbial dispersal) processes underpinning host-microbiome interactions and microbial assemblages. Overall, our results indicate that microbial communities are complex and vary in structure and function between the environment and the animal hosts. However, these differences are modulated by the level of pollution across the gradient with marked clines in alpha and beta diversity. Yet, such clines and overall differences showed opposite directions when comparing environmental- and animal-associated microbial communities. In the sea cucumbers, intrinsic characteristics (e.g., body compartments, biochemistry composition, immune systems), may underpin the observed intra-individual differences in the associated microbiomes, and their divergence from the environmental source. Such regulation favours specific microbial functional pathways that may play an important role in the survival and physiology of the animal host, particularly in high polluted areas. These findings suggest that the interplay between both, environmental and host filtering underpins microbial community assembly in H. leucospilota along the pollution gradient in Hong Kong.

Robust Semantic segmentation based on visual images is an effective method for intelligent vehicles to perceive road scenes. It can help intelligent vehicles quickly obtain the positions and occupancy information of various entities. However, when intelligent vehicles are driving, they face continuous changes in imaging quality, such as variations decreased visibility (from sunny to rainy, foggy or snowy). Among them, the blurring of images caused by fog increases the difficulty of recognition and makes annotation of foggy scene images more expensive, resulting poor performance when recognizing entities in the fog. Currently, many methods use domain adaptation to transfer segmentation knowledge from clear scenes to foggy ones. But these method are often ineffective due to the large domain gap between different cities' styles and the quality degradation of images caused by fog. The latest research has attempted to introduce an intermediate domain to decouple the domain gap and gradually complete the semantic segmentation of foggy scenes, but the exploration of how the intermediate domain works is often insufficient. To solve these problems, we first analyze the self-training in domain adaptation and propose the concept of "label reference value". We prove that the higher the total label reference value, the easier the self-training performance gets improved. With this precondition, we can reasonably split the original problem into two-stage domain adaptation. In each stage, the "label reference value" can be controlled and maximized. Specifically, the first stage only process the style gap between source domain and the intermediate domain, and the second stage process the fog gap. The fog gap includes: (1) real fog gap between the intermediate domain and target domain; (2) the synthetic fog gap between clear source domain and synthetic foggy source domain. This allows the model to make full use of "label reference value" and gradually develop good semantic segmentation skills for foggy scenes. Our approach significantly outperforms the baseline algorithm on all the mainstream SFSS benchmarks, with good generalization ability demonstrated in other adverse scenes such as rain and snow. We also compare our method with latest large segmentation models, which shows that our method has more robust performance in the foggy scenes.

Improving the accuracy of photovoltaic power prediction is crucial for grid scheduling planning and is essential for the safe, stable, and economic operation of power systems. Based on the statistical characterization of the data, a two-stage PV power prediction model with error correction is developed. First, an Elman neural network model optimized by a small habitat genetic algorithm is introduced; subsequently, a more accurate model for the preliminary prediction error probability distribution is established, based on its distribution characteristics. This model aims to achieve error correction of the preliminary prediction results. The empirical results, derived from actual PV power curves and meteorological data, demonstrate the effectiveness of the proposed method.

Guyon’s canal syndorme resulting from an ulnar aretery aneurysm :

The balaenid whale, comprising three species of right whales and the bowhead whale, represents an ancient and highly endangered lineage of marine mammals. To unravel the evolutionary history of balaenid whales with respect to gene flow, a comprehensive analysis based on whole-genome data was conducted for all species within this group. Employing population genomic methodologies, we revealed the polytomic nature of extant right whales, identified passage of historical trans-equatorial migration, and provided estimates to the age of the group. Furthermore, we investigated the impact of glacial cycles on the connectivity of bowhead whale populations. By employing multiple complementary approaches to detect gene flow, we identified and characterized gene flow events from bowhead whales to North Atlantic right whales, offering detailed insights into the process. Lastly, we assessed the phenotypic consequences of interspecies gene flow. The outcomes of our study shed light on the intricate evolutionary history of modern balaenid whales, which have been profoundly shaped by ancient climate events.

Forest litter decomposition is considered as an essential ecosystem process affecting carbon and nutrient cycling in mountains. However, there exists high uncertainty in accurately estimating the contribution of litter decomposition to terrestrial ecosystems, largely due to the incomparability of different studies and the data limitation in microclimate and non-climatic factors at spatially matched scales. Here we used the tea bag index (TBI) as a standardized protocol to evaluate spatial variations in forest litter decomposition rate (k) and stabilization factor (S) across 10 mountains spanning a wide range of subtropical and tropical forests. Based on the coordinated experiment of 6,864 teabags in 568 sampling sites along elevations, we evaluated the importance of 10 environmental factors covering soil microclimate, edaphic properties, plant diversity, and topography on k and S by using model averaging and linear-mixed effects models. Of the 10 mountains, we found a consistently decreasing pattern of k and an increasing pattern for S along elevations. And the significant effect of k with elevation was mainly found in the western and northmost mountains, while the effect of S occurred in the western and southernmost mountains. For microclimate, there was a general importance of soil temperature (coef. = 0.48) and temperature variation in the growing season (coef. = 0.36) in k, and soil temperature (coef. = -0.46) and moisture variation on S (coef. = -0.36). The dominant role of soil microclimate was mainly found in western mountains with relatively cold environments. For non-climatic drivers, a significant effect of tree diversity on k and a negative correlation of edaphic and topography with S in the western and southern mountains were detected. These findings provide a general understanding of spatial variations of driving factors in forest litter decomposition and highlight a dominant control of soil microclimate in cold forests in high elevations and latitudes.

Sodium-glucose cotransporter 2 inhibitors (SGLT2i), a new class of glucose-lowering drugs traditionally used to control blood glucose levels in patients with type 2 diabetes mellitus, have been proven to reduce major adverse cardiovascular events, including cardiovascular death, in patients with heart failure irrespective of ejection fraction and independently of the hypoglycemic effect. Because of their favorable effects on the kidney and cardiovascular outcomes, their use has been expanded in all patients with any combination of diabetes mellitus type 2, chronic kidney disease and heart failure. Although mechanisms explaining the effects of these drugs on the cardiovascular system are not well understood, their effectiveness in all these conditions suggests that they act at the intersection of the metabolic, renal and cardiac axes, thus disrupting maladaptive vicious cycles while contrasting direct organ damage. In this systematic review we provide a state of the art of the randomized controlled trials investigating the effect of SGLT2i on cardiovascular outcomes in patients with chronic kidney disease and/or heart failure irrespective of ejection fraction and diabetes. We also discuss the molecular targets and signaling pathways potentially explaining the cardiac effects of these pharmacological agents, from a clinical and experimental perspective.

Breast cancer has distinct causes and molecular characteristics at premenopausal and postmenopausal ages. The age-standardized incidence rate for postmenopausal breast cancer is more than 10 times higher than in premenopausal breast cancer. Here, I showed that the expression of 10 out of 20 most frequently mutated genes in breast cancer (namely, PIK3CA, CDH1, MUC16, PTEN, FAT3, FAT1, SPEN, ARID1A, LRP1B and RUNX1) is higher in premenopausal women with breast cancer than in postmenopausal women with breast cancer. The most significant differences in the expression in terms of menopause status were observed for RUNX1 and FAT1. Furthermore, I found that the majority of these 10 genes also show ER (estrogen receptor) or PR (progesterone receptor) status-dependent expression in both premenopausal and postmenopausal breast cancer patients. Unlike what I observed in the case of ER or PR status, the expression of most of these genes does not change depending on HER2 (human epidermal growth factor receptor 2) status in both premenopausal and postmenopausal breast cancer patients. Combined, our analysis suggests that menopause status might influence the expression of most frequently mutated genes in breast cancer, and that the most of these genes whose expression differ between pre- and post-menopausal women with breast cancer also show ER or PR status-dependent expression in women with breast cancer.

2,3-Butanediol (2,3-BD), known for its various applications and potential microbial production, faces challenges in commercial viability due to the high energy intensity nature of the conventional purification method. This study focuses on recovering and purifying 2,3-BD from glucose-based fermentation broth (FB) using aqueous two-phase extraction-assisted distillation (HATPED). The selected isobutanol/NaCl system studies were optimized with the parameter effect of salt, solvent, and extraction temperature on extraction efficiency of 2,3-BD through central composite design (CCD) and response surface methodology (RSM). Under Optimal conditions (30% (w/v) NaCl, 35% (v/v) isobutanol, and 40°C extraction temperature) yielded the highest partition coefficient ( KD) (6.8) and extraction efficiency (87%) of 2,3-BD exceeding the theoretical value of 86.93%, by 0.080%. The extract phase further proceeds in a distillation column to recover the 2,3-BD. In the scale-up study, the extraction and purification were conducted in two cycles, resulting in an overall 2,3-BD extraction and recovery of 97.63% and 95.88% (>99% purity), respectively. NaCl recovery from the aqueous phase reached 86.66% through evaporation. This cost-effective and scalable method provides valuable insights for developing an organic solvent/ inorganic salt ATPS-assisted distillation for 2,3-BD separation and recovery from complex fermentation broth.

Phase 1 clinical drug trials critically depend on the participation of healthy volunteers to evaluate the safety and pharmacokinetics of new medicinal products. Current selection criteria and health definitions often overlook the unique health profiles of transgender and nonbinary individuals, potentially excluding them from participating in these essential early-stage studies. This review aims to identify and discuss current knowledge gaps and considerations regarding the inclusion of transgender and nonbinary participants in Phase 1 clinical drug trials. We highlight the need for research on how gender-affirming hormone therapy may affect drug pharmacokinetics and call for the development of inclusive biological reference ranges that account for the physiological effects of hormone therapies.

Translocations, a conservation tool used to conserve and restore dwindling species, are often associated with high failure rates. Inadequate long-term monitoring of both populations and their introduction sites beyond the initial years post-translocation creates a gap in our understanding of the factors that determine translocation success or failure, resulting in less informed projects in the future. This lack of long-term monitoring is partly caused by the absence of a well-defined framework by which the success of the translocation can be measured, leading to premature and sometimes inaccurate assessments of their outcome. We investigated the long-term outcome of a red squirrel translocation in the west of Ireland, specifically assessing the habitat changes in the translocation site since the introduction in 2005, and their impact on carrying capacity. Using digitised historical map data, we showed that the translocation site experienced a 53% reduction in suitable habitat. Additionally, there was a 41-81% reduction in the red squirrel carrying capacity of the forest, according to feeding survey data. Clear-felling, a forest fire and a shift in tree species composition collectively contributed to this decline in site suitability. This investigation underscores the complexity of translocation projects and emphasises the pivotal role of habitat quality in their outcomes. We advocate for detailed habitat assessments during the planning phase, avoidance of unstable habitats as translocation sites, and the implementation of long-term monitoring practices.

A document by Maryam Javid. Click on the document to view its contents.

Why the countries within the Middle East are unstable despite sharing a common Arabic Language among them, which has been based on Phoenician text? There are different theories explaining the insecurity condition in the countries within the Middle East region including poverty, inequality, domestic violence and etc. These theories does provide an understanding about the insecurity as a factor of failure to achieve economic growth or stable social and economic status but these theories failed to provide an understanding that the type of insecurity resulting from the failure of a language to be creative enough based on the international organizations desire or choice. A part of the answer for this failure maybe the possibility of the Arabic language text which had failed to contribute to creativity based on the international organization desire because the Arabic language consisted of symbolic foundation of cuneiform after conversion to the text forms, through the Phoenicians which had close relations to the Latin and Greek languages, the Arabic language could not ensure creativity while the Latin and Greek languages contributed to the creativity while the Arabic language consist of different creativity based on cuneiform. Therefore, the Arabic language in the region is facing the pressure from the Latin and Greek languages or the influence of the different languages in the region, which has creativity foundation, which is not consistent with the type of creativity from the traditional Arabic language but consistent with the type of creativity from the non-traditional Arabic language. As a result, following the non traditional Arabic language and leaving aside the traditional Arabic language causing insecurity difficulty in the countries within the Middle East region. It is important for the international organization to engage in promoting creative activities in the countries within the Middle East based on the traditional Arabic language and non-traditional Arabic language in order to ensure security in the countries within the Middle East region.

Mitochondrial DNA analyses were carried out in order to determine the haplogroups of 6 individuals obtained from the cemetery of Resuloğlu and dated to the Early Bronze Age (EBA III). The individuals to be included in the bioinformatics analysis were evaluated according to their sequence quality and it was decided that 3 individuals could be used in further analysis. Using bioinformatics tools, it was determined that three individuals belonged to the T2e+152, H32 and JT haplogroups. These results support a link between the origins of the present-day European population and the farmers of the Anatolian Neolithic period. Furthermore, a detailed analysis of single nucleotide polymorphisms revealed T16189C and C150T mutations in the two of three individuals, which are associated with the risk of melanoma and cervical cancer - HPV infection. These molecular findings are consistent with the health profiles of the excavated skeletons, which indicate that the community struggled with infectious and metabolic diseases. The entire study was carried out in the Ancient DNA and Metagenomics Research Laboratory of the Department of Molecular Biology and Genetics, Istanbul University. Keywords: Ancient DNA, Mitochondrial DNA, Single Nucleotide Polymorphism, Haplogroup

This study presents a comprehensive multidisciplinary review of autonomous monitoring and analysis of large-scale photovoltaic (PV) power plants using enabling technologies, namely artificial intelligence, machine learning, deep learning, internet of things, unmanned aerial vehicle, and big data analytics, aiming to automate the entire condition monitoring procedures of PV systems. Autonomous monitoring and analysis is a novel concept for integrating various techniques, devices, systems, and platforms to further enhance the accuracy of PV monitoring, thereby improving the performance, reliability, and service life of PV systems. This review article covers current trends, recent research paths and developments and future perspectives of autonomous monitoring and analysis for PV power plants. Additionally, this study identifies the main barriers and research routes for the autonomous and smart condition monitoring of PV systems, to address the current and future challenges of enabling the PV terawatt transition. The holistic review of the literature shows that the field of autonomous monitoring and analysis of PV plants is rapidly growing and is capable to significantly improve the efficiency and reliability of PV systems. It can also have significant benefits for PV plant operators and maintenance staff, such as reducing the downtime and the need for human operators in maintenance tasks, as well as increasing the generated energy.

Plants are an intrinsic part of the soil community and the “one health concept” considers that human health is intimately connected to the health of animals, plants, and microbial environments. Plant-microbe interactions are a cornerstone of one health, the soil microbiome being comprised of a diverse range of organisms, interacts in the rhizosphere through continuous molecular communications. Soils are a source and reservoir of pathogens, as well as beneficial microorganisms. Hence, the molecular dialogue at the rhizosphere interface is crucial not only for successful plant-microbe interactions but also for crop resilience and stress tolerance. The plant-microbe continuum forms a network of underground “nutrient highways” that benefit both plant and microbial communities. It also serves as a significant sink for atmospheric CO 2. While microbial diversity is generally positively associated with one health, the host range of beneficial microbes currently limits their successful exploitation with a wide range of microbial communities. We consider the possibility of increasing the host range of beneficial microbes, including arbuscular mycorrhiza fungi (AMF) and rhizobia, and how current genetic incompatibility and/or activation of robust plant defenses, can be overcome while accepting that significant challenges exist in translating laboratory findings into the field. We consider why AMF inoculants and plant growth-promoting microbes are not always beneficial under field conditions and suggest possible approaches for tailoring plant-microbe interactions to assist plant breeding efforts in crop resilience.

In this parper we consider an Alpazur oscillator which consists of a Rayleigh-type oscillator and a DC power supply controlled by a switch that modifies the operating mode. The oscillator denotes some special phenomena in some parameter settings and are called chaos or bifurcation. In addition, we observe the behavior of this oscillator over a wide rage of parameter variation. Chaos theory tools such as, bifurcation, phase portrait, poincaré section and Matching Energy (ME) was examined in the analysis of dynamic of the system. Simulations were carried out using the 4th-order Runge-Kutta algoritm in Matlab. The results shows that Alpazur oscillator is sensitive to parameter variation and exhibts a wide range dynamics from fundamental periodicty to chaos.

We have proposed a Generalized Descent Symmetrical Hestenes-Stiefel algorithm [12] , GDSHS for short, which can generate sufficient descent directions for the objective function. Using the Wolfe line search conditions, the global convergence property of the method is also obtained based on the spectral analysis of the conjugate gradient iteration matrix and the Zoutendijk condition for steepest descent methods. I propose in this paper a theoretical choice to improve the performance of the GDSHS algorithm, by the use of an optimal parameter. Based on this, some descent algorithms are developed. 86 numerical experiments are presented to verify their performance and the numerical results show that the new conjugate gradient method GDSHS with the parameter c=1 , denoted GDSHS1, is competitive with GDSHS algorithms that have a parameter c chosen in the interval ] 0 , + ∞ [ .

IntroductionBleeding due to renal artery pseudoaneurysm is a rare but important complication that can occur after renal trauma, renal biopsy, percutaneous nephrostomy, percutaneous nephrolithotomy (PCNL), and partial nephrectomy. The incidence of this potentially life-threatening complication is less than 1% but is likely to increase with the increasing popularity of endoscopic renal procedures [1]. However, the risk of RAP is higher in the case of PCNL done in a solitary kidney because of the hypertrophy of the renal parenchyma [2]. Renal angiography can be used for diagnosing RAP of an interlobar artery.  Ultrasound guidance is a unique alternative to fluoroscopy for percutaneous renal access. Besides being free of ionizing radiation exposure to the patient and intraoperative personnel, it offers several advantages, including easier identification of the posterior renal calix and surrounding visceral structures [1, 3]. We present a 41-year-old male with a solitary right kidney presented with hematuria and a renal artery pseudoaneurysm post-PCNL and its comprehensive management.

Abstract In the present study, the in vitro and in vivo anti-acne activation by flavonoid combination therapy were investigated, and the role and relationship between flavonoid and FOXO3 signaling pathway were discussed. Three natural flavonoid such as quercetin, kaempferol, luteolin had certain anti-inflammation activity. Meanwhile, the combination therapy significantly outperforming using these flavonoids alone, which might be attributed to the synergistic bactericidal effect on the cells. Besides, it was also found that the FOXO3 pathway play an important role in P acnes induced skin inflammation. It’s promoted the decreasing of FOXO3 signaling pathway activation and induced an increasing in sebum secretion. During the acne inflammatory response, the expression of pro-inflammatory cytokine was increased significantly. After flavonoid combination therapy, the pro-inflammatory cytokines expression levels such as TNF-α (19.36 ± 2.44 pg/ml), IL-8 (1392.52 ± 131.75 pg/ml), IL-1β (13.42 ± 4.54 pg/ml) and IL-6 (109.64±13.34 pg/ml) were significantly reduced. Flavonoid combination therapy effectively decreased the expression of pro-inflammatory cytokines and increased the secretion of the anti-inflammatory cytokines. In addition, the activation of the FOXO3 pathway was found to be inversely proportional to the expression of pro-inflammatory cytokines. In this study, the flavonoid combination therapy demonstrated a “synergistic effect” inhibiting the inflammatory process via the activation of the FOXO3 pathway. The enhanced synergy observed surpassed their individual effects when used in combination. Consequently, the “synergistic effect” of three flavonoid ingredients suggested a new approach for the development of anti-acne reagents as FOXO3 enhancers.

Background: Viral wheeze is an important risk factor for asthma, which comprises several respiratory phenotypes. We sought to understand if the etiology of early life wheezing illnesses relates to childhood respiratory and asthma phenotypes. Methods: Data were collected prospectively on 429 children in the Urban Environment and Childhood Asthma (URECA) birth cohort study through age 10 years. We identified wheezing illnesses and the corresponding viral etiology (PCR testing of nasal mucus) during the first three years of life. Six phenotypes of respiratory health were identified at 10 years of age based on trajectories of wheezing, allergic sensitization, and lung function. We compared etiology of early wheezing illnesses on these respiratory phenotypes and the development of asthma. Results: In the first three years of life, at least one virus was detected in 324 (67%) of the 483 wheezing episodes documented in the study cohort. Using hierarchical partitioning we found that non-viral wheezing episodes accounted for the greatest variance on asthma diagnosed at both 7 and 10 years of age (8.0% and 5.8% respectively). Rhinovirus wheezing illnesses explained the most variance on respiratory phenotype outcome followed by non-viral wheezing episodes (4.9% and 3.9% respectively) at 10 years of age. Conclusion and Relevance: Within this high-risk urban-residing cohort early life, non-viral wheezing episodes were frequently identified and associated with asthma development. Though rhinovirus wheezing illnesses had the greatest association with phenotype outcome, the specific etiology of wheezing episode in early life provided limited information about subsequent wheezing phenotypes.