Miracle-dz/UniFAR-FTUs huggingface dataset:
Mini-Symposium : Esophageal Atresia and Tracheo-esophageal Fistula Surgical Treatment of Tracheobronchomalacia : A novel approach

Describe the constellation of conditions associated with tracheobronchomalacia (TBM) and excessive dynamic airway collapse (EDAC) Identify the differences seen in upper airway obstruction versus lower airway obstruction Describe the adjunctive modalities utilized to determine the best surgical approach in a particular patient Describe the various surgical therapies for tracheobronchomalacia with their associated advantages and disadvantages
Dual-functionalised shellac nanocarriers give a super-boost of the antimicrobial action of berberine

We have developed highly efficient antimicrobial nanocarriers for berberine (BRB) based on shellac nanoparticles (NPs) which were surface-functionalised with a surface active polymer, Poloxamer 407 (P407), and the cationic surfactant octadecyltrimethylammonium bromide (ODTAB). These shellac nanocarriers were produced in a two-step process which involves: (i) a pH change from aqueous ammonium shellac solution using P407 as a steric stabilizer in the presence of berberine chloride, and (ii) addition of ODTAB to yield shellac nanocarriers of cationic surface. We determined the BRB encapsulation efficiency and release profiles from such nanocarriers. We explored the antimicrobial action of these nanocarriers at different stages of their preparation which allowed us gain better understanding how they work, fine tune their design and reveal the impact of the nanoparticle coatings on to its antimicrobial effect. The antimicrobial action of BRB loaded within such shellac NPs with cationic surface functionality was examined on three different microorganisms, C. reinhardtii, S. cerevisiae and E. coli and compared with the effect of free BRB as well as non-coated BRB-loaded nanocarriers at the same BRB concentrations. We found that the cationic surface coating of the shellac NPs strongly amplified the efficiency of the encapsulated BRB across all tested microorganisms. The effect was attributed to the increased attraction between the ODTAB-coated BRB-loaded NPs and the anionic surface of the cell walls which delivers locally high BRB concentration. This nanotechnological approach could lead to more effective antimicrobial and disinfecting agents, dental formulations for plaque control, wound dressings, antialgal/antibiofouling formulations and antifungal agents.
Equivalent Continuous Medium Model for Fractured Extra-low Permeability Sand Stone Reservoir

Considering the development characteristics of extra-low permeability fractured sandstone reservoir,an equivalent continuous medium model was developed based on tensor theory and the law of equivalent seepage resistance.It provided the basis for evaluating the impact of natural fracture on extra-low permeability sandstone reservoir and the research on the seepage theory in this kind of reservoir.Influence factors were analyzed using the established model,and the results showed that natural fracture significantly increased the reservoir permeability parallel to fracture direction,improved the percolation ability of the reservoir,and aggravated the reservoir anisotropy.
Factors influencing the implementation of severe acute malnutrition guidelines within the healthcare referral systems of rural subdistricts in North West Province, South Africa

Severe acute malnutrition (SAM) is associated with 30.9% of South Africa’s audited under-five children deaths regardless of available guidelines to reduce SAM at each level of a three tyre referral system. Existing research has explored and offered solutions for SAM guidelines implementation at each referral system level, but their connectedness in continuation of care is under-explored. Therefore, I examined implementation of SAM guidelines and factors influencing implementation within subdistrict referral systems. An explanatory qualitative case study design was used. The study was conducted in two subdistricts involving two district hospitals; three community health centres, four clinics, and two emergency service stations. Between February to July 2016 and 2018, data were collected using 39 in-depth interviews with clinical, emergency service and administrative personnel; 40 reviews of records of children younger than five years; appraisals of nine facilities involved in referrals and observations. Thematic content analysis was used to analyse all data except records which were aggregated to elicit whether required SAM guidelines’ steps were administered per case reviewed. Record reviews revealed SAM diagnosis discrepancies demonstrated by incomplete anthropometric assessments; non-compliance to SAM management guidelines was noted through skipping some critical steps including therapeutic feeding at clinic level. Record reviews further revealed variations of referral mechanisms across subdistricts, contradictory documentation within records, and restricted continuation of care. Interviews, observations and facility appraisals revealed that factors influencing these practices included inadequate clinical skills; inconsistent supervision and monitoring; unavailability of subdistrict specific referral policies and operational structures; and suboptimal national policies on therapeutic food. SAM diagnosis, management, and referrals within subdistrict health systems need to be strengthened to curb preventable child deaths. Implementation of SAM guidelines needs to be accompanied by job aids and supervision with standardised tools; subdistrict-specific referral policies and suboptimal national policies to ensure availability and accessibility of therapeutic foods.
Effects of South Asian dust storm on air quality over the capital city of India

In the present study, an intense unseasonal dust storm has been analyzed during third week of March 2012 from multi satellite datasets and from surface measurements over National Capital Region (NCR), Delhi. The intrusion of dust over study region has increased the MODIS Aerosol Optical Depth at 550 nm more than 1.0 whereas significant decrease in Angstrom Exponent (α) has been observed . Very high UV aerosol Index (> 2) over study location indicates the presence of UV absorbing aerosols . Fire activities are found to be negligible over the source region confirming the effect of dust storm. Strong southwesterly winds prevailed over northern Arabian Sea which trans ported the dust plume across the oceanic region towards Indian capital region. In-situ measurements of PM 2.5 and PM10, obtained from CPCB observational site over the IGI airport, NCR Delhi, showed abrupt increase on 20, 21 March. Eight hourly average concentration of the particulate matters less than 10 μm (PM10) is found to be ~990 μg/m3 and particulate matters less than 2.5 μm (PM2.5) is found to be ~900 μg/m3 over IGI Airport, NCR Delhi. These values are remarkably higher as compared to the daily National Ambient Air Quality Standards (NAAQS) i.e. 100 μg/m3 and 60 μg/m3 for PM10 and PM2.5 respectively. In addition, Vertical distribution of dust has been examined using CALIPSO observation. The layer of dust is found to be trapped within lower 3 km in altitude. The Potential Source Contribution Function (PSCF) modeling has been carried out to identify the specific source locations.
From conservative to reactive transport under diffusion‐controlled conditions

We assess the possibility to use conservative transport information, such as that contained in transit time distributions, breakthrough curves and tracer tests, to predict nonlinear fluid‐rock interactions in fracture/matrix or mobile/immobile conditions. Reference simulated data are given by conservative and reactive transport simulations in several diffusive porosity structures differing by their topological organization. Reactions includes nonlinear kinetically controlled dissolution and desorption. Effective Multi‐Rate Mass Transfer models (MRMT) are calibrated solely on conservative transport information without pore topology information and provide concentration distributions on which effective reaction rates are estimated. Reference simulated reaction rates and effective reaction rates evaluated by MRMT are compared, as well as characteristic desorption and dissolution times. Although not exactly equal, these indicators remain very close whatever the porous structure, differing at most by 0.6% and 10% for desorption and dissolution. At early times, this close agreement arises from the fine characterization of the diffusive porosity close to the mobile zone that controls fast mobile‐diffusive exchanges. At intermediate to late times, concentration gradients are strongly reduced by diffusion, and reactivity can be captured by a very limited number of rates. We conclude that effective models calibrated solely on conservative transport information like MRMT can accurately estimate monocomponent kinetically controlled nonlinear fluid‐rock interactions. Their relevance might extend to more advanced biogeochemical reactions because of the good characterization of conservative concentration distributions, even by parsimonious models (e.g., MRMT with 3–5 rates). We propose a methodology to estimate reactive transport from conservative transport in mobile‐immobile conditions.
Mitigation of N2O emissions from surface-irrigated cropping systems using water management and the nitrification inhibitor DMPP

Soils under irrigated agriculture are a significant source of nitrous oxide (N2O) owing to high inputs of nitrogen (N) fertiliser and water. This study investigated the potential for N2O mitigation by manipulating the soil moisture deficit through irrigation scheduling in combination with, and in comparison to, using the nitrification inhibitor, 3,4-dimethylpyrazole phosphate (DMPP). Lysimeter cores planted with wheat were fitted with automated chambers for continuous measurements of N2O fluxes. Treatments included conventional irrigation (CONV), reduced deficit irrigation (RED), CONV-DMPP and RED-DMPP. The total seasonal volume of irrigation water applied was constant for all treatments but the timing and quantity in individual irrigation applications varied among treatments. 15N-labelled urea was used to track the source of N2O emissions and plant N uptake. The majority of N2O emissions occurred immediately after irrigations began on 1 September 2014. Applying RED and DMPP individually slightly decreased N2O emissions but when applied in combination (RED-DMPP) the greatest reductions in N2O emissions were observed. There was no effect of treatments on plant N uptake, 15N recovery or yield possibly because the system was not N limited. Half of the plant N and 53% to 87% of N2O was derived from non-fertiliser sources in soil, highlighting the opportunity to further exploit this valuable N pool.
Isolation and Characterization of Cellulase-Producing Myxobacterial Strain from the Unique Niche of Mirgund Wetland from the North-Western Himalayas

Microbes are stated to be an excellent source of novel enzymes and secondary metabolites having potential industrial applications. Many attempts have been made around the globe to unravel novel bioactive molecules from microbes inhabiting different unexplored ecological niches. Myxobacteria, a member of δ -proteobacteria belonging to the order Myxococcales, is a gram-negative rod-shaped bacterium well-known for coordinated movement, fruiting body formation during starvation, gliding mobility, and a well-developed communication system. They have emerged as valuable producers of various natural products belonging to diverse chemical classes with wide-spectrum and unique bioactive molecules that have attracted academicians and researchers for their exploration. The bioactive molecules obtained from myxobacteria have been proclaimed to have the ability to break down macromolecules of biological origin by secreting a large number of extra-cellular enzymes. The current study reports the isolation of myxobacteria from the Mirgund Wetland in the North-Western Himalayas through the dung-baiting method. The isolated myxobacteria showed characteristic morphological features of myxobacteria, like the formation of fruiting bodies and swarming patterns on the solid Casitone-enriched media. 16S ribosomal RNA gene sequencing of the strain showed 100% similarity with Myxococcus spp. The isolated strain produced an active cellulase with an optimum activity at 40°C and pH 7.0 using the 3,5-dinitro salicylic acid method when cultured on minimal broth containing carboxymethyl cellulose. This is the first report of a myxobacterial strain and enzyme from the Mirgund Wetland of the Union Territory of Jammu and Kashmir and highlights the immense potential of the hidden wealth of enzymes in the area.
THE INFLUENCE OF DEFORESTATION ON SOIL WATER CONSERVATION IN A PINE FOREST IN TENERIFE (CANARY ISLANDS, SPAIN)

The present work studies the effect of deforestation on soil water conservation in a pine forest in Tenerife (Canary Islands, Spain). We compare two adjoining plots, with originally similar environmental characteristics but now differentiated by the presence or absence of canarian pines (Pinus canariensis) following the removal from one of the plots of trees for use as timber. In both areas soil moisture was monitored monthly every 10 cm to a depth of 1 metre over a period of three years. Also analysed were the spatial variability of the soil water in the pine forest and the influence of the type of vegetation thereon. The results obtained show differences in the soil moisture content distribution throughout the year. The importance of water uptake from condensation is also apparent. The increase in seasonal contrasts and the prolongation of the dry period caused by deforestation influence the soil moisture regime, which changes from udic under the pine trees to xeric in the deforested zone. Additional Keywords: Land use, soil moisture regime, Soil Taxonomy, condensation
Butterfly diversity in tropical moist deciduous sal (Shorea robusta) forests of Dehra Dun Valley: The lower Western Himalayas

During a three year survey (July , 2000 - August , 2003) , 183 species of butterflies (representing 128 genera , 9 sub-families and 5 families) were recorded from 10 sites (4 km 2 each) in Dehra Dun valley which represents the tropical moist deciduous Sal , Shorea robusta forest (TMDSF) zone of the lower Western Himalayas. Amongst these 46 species recorded are new records for Dehra Dun valley. Twenty-six species found here have geographical distribution restricted to the Himalayas and mountains of North-East India and Myanmar in the Indian Sub-Continent. Twenty-five butterfly species of Dehra Dun valley are 'protected' under the Indian Wildlife (Protection) Act of 1972. The species diversity of butterflies (July , 2000 - July , 2001) peaked in the valley during late April (spring) - early May (summer) which was a few weeks earlier than known to be in the hills (2000 m) of the Western Himalayas. This was followed by a slightly greater second peak during late October (post-monsoon) - early November (autumn) which was a few weeks later as known from the adjoining hills. Specific threats to butterfly habitats in TMDSF are discussed. A complete annotated list of 211 species recorded from the valley is also given.
Yankee Fork Salmon River Chinook Salmon Run Report

VI ACKNOWLEDGEMENTS V INTRODUCTION 1 PROJECT BACKGROUND 2 PROGRAM PHASES, GOALS, AND OBJECTIVES 4 STUDY AREA 5 SMOLT RELEASE AND ACCLIMATION STUDY 6 JUVENILE TRAPPING 8 ADULT TRAPPING 18 POLE FLAT WEIR 18 ADULT TRAPPING 21 RUN-TIMING 24 AGE STRUCTURE 25 FIVE MILE WEIR 28 HATCHERY ADULT OUTPLANTS 29 POLE FLAT WEIR HATCHERY OUTPLANTS 29 SAWTOOTH HATCHERY OUTPLANTS 29 HARVEST MONITORING 32 SPAWNING GROUND SURVEYS 32 REDD COUNTS 32 CARCASS SURVEYS 35 MARK-RECAPTURE EVALUATION 35 FISH PER REDD ESTIMATION 36 POLE FLAT TO FIVE MILE WEIR 36 ABOVE FIVE MILE WEIR 37 TOTAL ESCAPEMENT 38 DISCUSSION AND RECOMMENDATIONS 39 CITATIONS 40 APPENDIX A: REGIONAL PARTICIPATION 43
Going the Distance: Memory and Control Processes in Active Dependency Construction

Filler–gap dependencies make strong demands on working memory in language comprehension because they cannot always be immediately resolved. In a series of three reading-time studies, we test the idea that these demands can be decomposed into active maintenance processes and retrieval events. Results indicate that the fact that a displaced phrase exists and the identity of its basic syntactic category both immediately impact comprehension at potential gap sites. In contrast, specific lexical details of the displaced phrase show an immediate effect only for short dependencies and a much later effect for longer dependencies. We argue that coarse-grained information about the filler is actively maintained and is used to make phrase structure parsing decisions, whereas finer grained information is more quickly released from active maintenance and consequently has to be retrieved at the gap site.
A 3D U-Net Based on a Vision Transformer for Radar Semantic Segmentation

Radar data can be presented in various forms, unlike visible data. In the field of radar target recognition, most current work involves point cloud data due to computing limitations, but this form of data lacks useful information. This paper proposes a semantic segmentation network to process high-dimensional data and enable automatic radar target recognition. Rather than relying on point cloud data, which is common in current radar automatic target recognition algorithms, the paper suggests using a radar heat map of high-dimensional data to increase the efficiency of radar data use. The radar heat map provides more complete information than point cloud data, leading to more accurate classification results. Additionally, this paper proposes a dimension collapse module based on a vision transformer for feature extraction between two modules with dimension differences during dimension changes in high-dimensional data. This module is easily extendable to other networks with high-dimensional data collapse requirements. The network’s performance is verified using a real radar dataset, showing that the radar semantic segmentation network based on a vision transformer has better performance and fewer parameters compared to segmentation networks that use other dimensional collapse methods.
Machine Learning for Indoor Localization Without Ground-truth Locations

Wi-Fi Received Signal Strength Indicator (RSSI) has been considered as one of most important resources for indoor localization. However, the conventional RSSI fingerprint method needs recording many ground-truth locations. In this paper, we propose an unsupervised Wi-Fi RSSI learning without true location. Pseudo-labels are made by another machine learning model, which uses inertial measurement unit (IMU) as training input. From the experiments in an office building, the proposed algorithm validates to learn an unsupervised Wi-Fi RSSI positioning model by resulting in 0.8 CDF at 2 meter distance.
A prospective guide for clinical implementation of selected OGTT-derived surrogate indices for the evaluation of β-cell function and insulin sensitivity in patients with transfusion-dependent β-thalassaemia

The gold standard for the measurement of insulin secretion is the hyperglycemic clamp and for insulin sensitivity the hyperinsulinemic euglycemic clamp, respectively. Their disadvantages are the non-physiological route, the complexity of protocols requiring an experienced operator and the high costs; thus, they are mainly used for research purposes. A number of surrogate indices, derived from plasma glucose and insulin levels at a fasting state or after oral glucose load, have been proposed to estimate β-cell response, and the ability of β-cells to compensate for changes of insulin sensitivity by modulating insulin secretion (disposition index). Starting from the current recommendations for the annual screening of glucose dysregulation in patients with transfusion dependent β-thalassemia (β-TDT), this article summarizes the most frequently used indirect indices of insulin secretion and resistance derived from the oral glucose tolerance test (OGTT) and discusses the strengths and weaknesses of selected indices and the basic concepts underlying each method for the appropriate evaluation of glucose regulation. Basal indices for β-cell function and insulin sensitivity, albeit simple and cheap, have limited usefulness due to a high coefficient variation and the lack of data about response to glucose load. Therefore, measurement of indices during an OGTT, despite being costly and time-consuming, is suggested since it can detect, even subtle, dynamic changes in insulin secretion and glucose handling. In patients with β-TDT, the indices derived from OGTT may offer an additional factor to evaluate the efficiency of iron chelation therapy and detect patients who may need intensification of iron chelation therapy and/or pharmacological intervention. (www.actabiomedica.it)
Drowsiness Detection System

Driver drowsiness is a critical factor contributing to road accidents worldwide. The increasing occurrence of road accidents due to driver drowsiness has prompted significant research and development efforts towards creating effective Driver Drowsiness Detection Systems. The after-effects of drivers being drowsy while driving can have far-reaching consequences, affecting not only the driver’s immediate performance but also contributing to potential accidents and impacting overall road safety. To mitigate these risks, we propose a driver drowsiness detection system that detects drowsiness patterns using facial images of the driver. The system utilizes computer vision and machine learning techniques to monitor the driver’s state in real-time and issue timely alerts if signs of drowsiness are detected. The proposed system employs a camera-based approach to capture and analyze facial features and driver behavior, extracting key indicators of drowsiness such as eye closure, head pose, and yawning. These visual cues are processed using state-of-the-art deep learning algorithms, enabling accurate and efficient detection of drowsiness patterns. Furthermore, our system integrates with a user-friendly dashboard that provides visualizations and real-time alerts to the driver and relevant stakeholders, including fleet managers or vehicle owners. Our driver drowsiness detection system offers a practical and reliable solution for enhancing road safety. By leveraging computer vision and machine learning technologies, it enables timely detection of drowsiness indicators, empowering drivers and stakeholders with critical information to prevent accidents and save lives. The findings from our work serves as a foundation for further research and potential integration into existing driver assistance systems and automotive safety frameworks.