Miracle-dz/UniFAR-FTUs huggingface dataset:
Incidence of tuberculosis in Babylon Province -Iraq

Tuberculosis (TB) remains a leading cause of mortality in the world ,WHO(2012) reports more than two billion people about one-third of the world population were estimated to be infected with Mycobacterium tuberculosis . Screening for TB (to diagnose latent TB infection) and prophylactic therapy remain the most important tools to reduce the risk of progression to TB disease among high risk individuals (close contacts, HIV infected individuals, health care workers, etc.) and be considered in endemic countries to reduce the progression from infection to disease (Padmanesan et al., 2013).
Performance Evaluation of DSR, AODV, DSDV, Multipath AOMDV Routing Protocols in MANETS

A Mobile ad hoc network is a collection of various number of mobile nodes connected through wireless links forming a temporary network without any type of fixed topology, centralized access point and infrastructure. In such a network, each node acts as a router and host simultaneously, it can move out or join in the network freely as and when required. Various routing protocols have been discussed so far but in this paper a brief comparison of two reactive protocols DSR, AOMDV and AODV along with proactive protocol DSDV is done. AOMDV was designed primarily for highly dynamic ad hoc networks where link failures and route breaks occur frequently. It maintains routes for destinations in active communication and uses sequence numbers to determine the freshness of routing information to prevent routing loops. It is a timer-based protocol and provides a way for mobile nodes to respond to link breaks and topology changes. As the node performance gets affected due to mobility and position error, the variation in performance are analyzed by use of varying simulation time and it is carried out using NS-2 simulator. The results presented specify the importance in evaluation and implementation of routing protocols in an ad hoc environment.
Lipidomic diversity and proxy implications of archaea from cold seep sediments of the South China Sea

Cold seeps on the continental margins are characterized by intense microbial activities that consume a large portion of methane by anaerobic methanotrophic archaea (ANME) through anaerobic oxidation of methane (AOM). Although ANMEs are known to contain unique ether lipids that may have an important function in marine carbon cycling, their full lipidomic profiles and functional distribution in particular cold-seep settings are still poorly characterized. Here, we combined the 16S rRNA gene sequencing and lipidomic approaches to analyze archaeal communities and their lipids in cold seep sediments with distinct methane supplies from the South China Sea. The archaeal community was dominated by ANME-1 in the moderate seepage area with strong methane emission. Low seepage area presented higher archaeal diversity covering Lokiarchaeia, Bathyarchaeia, and Thermoplasmata. A total of 55 core lipids (CLs) and intact polar lipids (IPLs) of archaea were identified, which included glycerol dialkyl glycerol tetraethers (GDGTs), hydroxy-GDGTs (OH-GDGTs), archaeol (AR), hydroxyarchaeol (OH-AR), and dihydroxyarchaeol (2OH-AR). Diverse polar headgroups constituted the archaeal IPLs. High concentrations of dissolved inorganic carbon (DIC) with depleted δ13CDIC and high methane index (MI) values based on both CLs (MICL) and IPLs (MIIPL) indicate that ANMEs were active in the moderate seepage area. The ANME-2 and ANME-3 clades were characterized by enhanced glycosidic and phosphoric diether lipids production, indicating their potential role in coupling carbon and phosphurus cycling in cold seep ecosystems. ANME-1, though representing a smaller proportion of total archaea than ANME-2 and ANME-3 in the low seepage area, showed a positive correlation with MIIPL, indicating a different mechanism contributing to the IPL-GDGT pool. This also suggests that MIIPL could be a sensitive index to trace AOM activities performed by ANME-1. Overall, our study expands the understanding of the archaeal lipid composition in the cold seep and improves the application of MI using intact polar lipids that potentially link to extent ANME activities.
Deep-Learning-Based Automated Rotator Cuff Tear Screening in Three Planes of Shoulder MRI

This study aimed to develop a screening model for rotator cuff tear detection in all three planes of routine shoulder MRI using a deep neural network. A total of 794 shoulder MRI scans (374 men and 420 women; aged 59 ± 11 years) were utilized. Three musculoskeletal radiologists labeled the rotator cuff tear. The YOLO v8 rotator cuff tear detection model was then trained; training was performed with all imaging planes simultaneously and with axial, coronal, and sagittal images separately. The performances of the models were evaluated and compared using receiver operating curves and the area under the curve (AUC). The AUC was the highest when using all imaging planes (0.94; p < 0.05). Among a single imaging plane, the axial plane showed the best performance (AUC: 0.71), followed by the sagittal (AUC: 0.70) and coronal (AUC: 0.68) imaging planes. The sensitivity and accuracy were also the highest in the model with all-plane training (0.98 and 0.96, respectively). Thus, deep-learning-based automatic rotator cuff tear detection can be useful for detecting torn areas in various regions of the rotator cuff in all three imaging planes.
Unsupervised Tensor Based Feature Extraction From Multivariate Time Series

Clustering and outlier detection for multivariate time series are essential tasks in data mining fields and many algorithms have been developed for this purpose. However, these tasks remain challenging because both time-wise and variable-wise associations should be taken into account to treat multivariate time series appropriately. We propose a tensor based feature extraction method called UFEKT, which focuses on subsequences to account for the time-wise association and constructs a feature vector for each subsequence by applying tensor decomposition to account for the variable-wise association. This method is simple and can be used as an effective means of preprocessing for clustering and outlier detection algorithms. We show empirically that UFEKT leads to superior performance on various popularly used clustering algorithms such as <inline-formula> <tex-math notation="LaTeX">${K}$ </tex-math></inline-formula>-means and DBSCAN and outlier detection algorithm such as the <inline-formula> <tex-math notation="LaTeX">$\kappa $ </tex-math></inline-formula>-nearest neighbor and LOF.
Spatial resolution enhancement of hyperspectral images from miniaturized sensors

Here we describe and mitigate issues of optical aberrations related to wavelength-dependent blur caused by miniaturization in hyperspectral pushbroom image sensors, which degrade spatial resolution and limit their usefulness. Panchromatic sharpening algorithms are modified to enhance the spatial resolution of acquired hyperspectral image cubes, explicitly focusing on optical aberrations associated with pushbroom scanners. The study explores algorithms for component substitution and multi-resolution analysis, such as modulation and Laplacian pyramids, adapting them for single image cubes while considering the characteristics of miniaturized hyperspectral imagers. Simulations demonstrate the method’s effectiveness in improving the spatial quality of images obtained from miniaturized hyperspectral imagers, expanding their potential applicability. The study evaluates the method using metrics like the BRISQUE score and utilizes data from the HYPSO-1 CubeSat platform.
GIRDLING OF HASS AVOCADO TREES TO INCREASE FRUIT YIELD AND INCOME IN "OFF" YEARS IN A CALIFORNIA COASTAL VALLEY

Sixteen trees each of mature Hass avocado trees were treated with three 2 cm (.5 in) girdling treatments prior to two light bloom springs resulting in “off” year crops: 1. A December girdle, 2. A February girdle, 3. An ungirdled control. One-third of the limbs were girdled on each tree, changing limbs each treatment year. December girdles were performed in 1995 and 1997. February girdles were performed in 1996 and 1998. Fruit number data was taken for three seasons, two “off” years (1997 and 1999) after girdling and one “on” year (1998) without girdling. The December girdling time averaged 111 more fruit per tree than the control trees for the three years of the study. The February girdling time averaged 80 more fruit per tree than the control trees for the three years. Fruit size was slightly smaller for both December and February girdled trees for the 1999 crop. INTRODUCTION The avocado industry is a large economic factor for many nations. Unsatisfactory bearing habits of the avocado tree have always been a major problem for the avocado grower. Avocado trees are alternate bearers, so 1-3 poor crops (lag crops) may follow a heavy crop. As production costs increase (especially water) there is a growing need to maximize production in these lag crops. Girdling has been practiced to increase productivity in many fruit trees, including the avocado. It is a simple process of cutting through and removing the bark in a two cm diameter circular pattern around one third of the limbs per year. This is usually recommended in November or December in California (McNeil, 2001). The removal of the bark prevents carbohydrates from going down the tree to the roots. These carbohydrates are then used by the upper portion of the tree to increase fruit set. 263 Proceedings V World Avocado Congress (Actas V Congreso Mundial del Aguacate) 2003. pp. 263-265.
Phenotyping and predicting wheat spike characteristics using image analysis and machine learning

Improvements in trait phenotyping are needed to increase the quantity and quality of data available for genetic improvement of crops. In this study, we used moderate throughput image analysis and machine learning as a pipeline for phenotyping a key wheat spike characteristic: spikelet number per spike. A population of 594 soft red winter wheat inbred lines was evaluated in the field for 2 years and images of wheat spikes were taken and used to train deep‐learning algorithms to predict spikelet number. A total of 12,717 images were used to train, test, and validate a basic regression convolutional neural network (CNN), a visual geometry group application regression model, VGG16, the ResNet152V2 model, and the EfficientNetV2L model. The EfficientNetV2L model was the most accurate, having the lowest mean absolute error, second lowest root mean square error, and highest coefficient of determination (mean absolute error [MAE] = 0.60, root mean square error [RMSE] = 0.79, and R2 = 0.90). The ResNet152V2 model was slightly less accurate with a slightly better fit (MAE = 0.61,m RMSE = 0.78, and R2 = 0.87), followed by the basic CNN (MAE = 0.75, RMSE = 1.00, and R2 = 0.74) and finally by the VGG16 (MAE = 1.51, RMSE = 1.29, and R2 = 0.076). With an average error of just above one half of a spikelet, utilizing image analysis and machine learning counting methods could be used for multiple breeding applications, including direct selection of spikelet number, to provide data to identify quantitative trait loci, or for training whole genome selection models.
Exploring Verbal Fluency Strategies among Individuals with Normal Cognition, Amnestic and Non-Amnestic Mild Cognitive Impairment, and Alzheimer’s Disease

Background and Objectives: The present study explored the utilization of verbal fluency (VF) cognitive strategies, including clustering, switching, intrusions, and perseverations, within both semantic (SVF) and phonemic (PVF) conditions, across a continuum of neurocognitive decline, spanning from normal cognitive ageing (NC) to mild cognitive impairment (MCI) and its subtypes, amnestic (aMCI) and non-amnestic (naMCI), as well as AD. Materials and Methods: The study sample was derived from the Hellenic Longitudinal Investigation of Aging and Diet (HELIAD) cohort. The sample included 1607 NC individuals, 146 with aMCI (46 single-domain and 100 multi-domain), 92 with naMCI (41 single-domain and 51 multi-domain), and 79 with AD. Statistical analyses, adjusting for sex, age, and education, employed multivariate general linear models to probe differences among these groups. Results: Results showed that AD patients exhibited poorer performance in switching in both VF tasks and SVF clustering compared to NC. Similarly, the aMCI group performed worse than the NC in switching and clustering in both tasks, with aMCI performing similarly to AD, except for SVF switching. In contrast, the naMCI subgroup performed similarly to those with NC across most strategies, surpassing AD patients. Notably, the aMCI subgroup’s poor performance in SVF switching was mainly due to the subpar performance of the multi-domain aMCI subgroup. This subgroup was outperformed in switching in both VF tasks by the single-domain naMCI, who also performed better than the multi-domain naMCI in SVF switching. No significant differences emerged in terms of perseverations and intrusions. Conclusions: Overall, these findings suggest a continuum of declining switching ability in the SVF task, with NC surpassing both aMCI and AD, and aMCI outperforming those with AD. The challenges in SVF switching suggest executive function impairment associated with multi-domain MCI, particularly driven by the multi-domain aMCI.
Land-Cover Legacy Effects on Arbuscular Mycorrhizal Abundance in Human and Wildlife Dominated Systems in Tropical Savanna

Arbuscular mycorrhizal fungi (AMF) can be important mutualists to plant hosts in acquiring soil nutrients. Past work has not explored whether previous land-cover history influences current AMF abundance in croplands and whether different land-cover histories in grazed but not cultivated areas influence AMF. This study was conducted to assess the effects of land-cover history in and near Serengeti National Park on AMF abundance in areas with three different land uses. The results showed that land-cover history influenced a number of soil physicochemical properties following conversion of grassland to cropland or woodland to cropland during the past 27 years. Different original land cover generally did not significantly influence current AMF abundance in croplands or livestock-grazed soils. However, livestock-grazed current grasslands that were formerly woodlands had lower AMF abundance than sites that had been grasslands since 1984. These results suggest that lower AMF abundance in livestock-grazed and cropland areas as compared to protected wildlife-grazed areas may reflect reduced total carbon inputs and higher disturbance and are not strongly influenced by the legacy of previous land cover. Given that recent studies have detected legacy effects on AMF, such effects may reflect more the impact on the taxonomic composition of AMF rather than their total abundance.
Geomorphological investigations of Bor River Basin (Tributary of Pedi River) Amravati District, Maharashtra using Remote Sensing and GIS techniques

Detailed morphometric analysis of the Bor River basin in Amravati district has been attempted to delineate the various groundwater potential zones based on hydrogeomorphological investigations Morphometric analysis is the measurement and mathematical analysis of the configuration of the earth's surface, shape and dimension of its landforms (Clarke, 1966). This analysis can be achieved through measurement of linear, aerial and relief aspects of the basin and slope contribution (Nag and Chakraborty, 2003). The present study area of Bor River basin is a tributary of Pedi River lying in the Amravati district. For the Morphometric analysis Geographic information system techniques has been used and Strahler (1964) stream order method used for stream ordering. The drainage density (D) of study area is 1.9674 km indicating low to moderate drainage density. In this study an attempt has been made to understand the morpho-tectonic analysis of the Bor river basin by utilizing the remote sensing and GIS techniques for delineating groundwater potential zones for the sustainable development of the region. By utilizing the remote sensing and GIS techniques, various maps have been prepared to delineate the groundwater potential zones for the sustainable development of the Bor River basin.
Substation Personnel Fall Detection Based on Improved YOLOX

With the continuous promotion of smart substations, staff fall detection has become a key issue in automatic detection of substations. The injuries and safety hazards caused by falls among substation personnel are numerous. If a timely response can be made in the event of a fall, the injuries caused by falls can be reduced. In order to address the issues of low accuracy and poor real-time performance in detecting human falls in complex substation scenarios, this paper proposes an improved algorithm based on YOLOX. A customized feature extraction module is introduced to the YOLOX feature fusion network to extract diverse multiscale features. A recursive gated convolutional module is added to the head to enhance the expressive power of the features. Meanwhile, the SIoU(Soft Intersection over Union) loss function is utilized to provide more accurate position information for bounding boxes, thereby improving the model accuracy. Experimental results show that the improved algorithm achieves an mAP value of 78.45%, which is a 1.31% improvement over the original YOLOX. Compared to other similar algorithms, the proposed algorithm achieves high accuracy prediction of human falls with fewer parameters, demonstrating its effectiveness.
Common Mode Current Effect Reduction Method for NEMP Current Sensors Calibration Techniques

Current sensors used in nuclear electromagnetic pulse experiments are generally shielded current transformers. Despite this shielding, calibration measurements are disturbed by common mode current interference. This letter uses a mathematical approach to limit this effect. The proposed method was applied to a test case and compared with two other techniques, including a conventional technique. The method was shown to have two benefits: to limit the influence of common mode currents and to consider the impedance mismatch effect.
Analyzing Driver Strategy for Scheduled Takeovers Under the Effect of Multi-stage Takeover Request Design

For scheduled takeover events in conditional driving automation, a longer lead time of takeover request (ToR) up to 60 seconds was recommended for drivers’ better situation awareness and subjective evaluations. However, the long ToR lead time could impair drivers’ estimation of the urgency of situation, which potentially results in risky takeover behavior. Four multi-stage ToR designs varying in warning modality that communicate the urgency within a long lead time were thus proposed to mitigate the negative effects. The present study involved a driving simulator experiment with 32 participants performing 12 takeover tasks for exiting a freeway with the aim to analyze driver strategy for scheduled takeover events and evaluate the multi-stage ToR designs. Eight driver strategies for attention management and takeover were identified. Using multi-stage ToR designs advanced drivers’ takeover actions by decreasing the likelihood of alternating attention between non-driving activities and road and reducing the duration of takeover preparation.
Effect of SrCO3 and MgCl2 Addition on Synthesis of Aragonite in Ca(OH)2-CO2-H2O System at Low Temperature

ABSTRACT The main purpose of the present investigation is to save energy in carbonation process by the addition of Sr CO3 and MgCl2·6H2O for the synthesis of aragonite at low temperature like 30°C. In this process, MgCl2 · 6H2O and SrCO3 seed was added together to Ca(OH)2. The yield of aragonite was increased with the increase of SrCO3 seed at 0.2 mole of MgCl2·6H2O. We employed an experimental approach to study the effect of above mentioned materials on aragonite formation in Ca(OH)2-CO2-H2O system at low temperature.
ECONOMIC CONVERGENCE: EVIDENCE FROM COUNTIES IN THE CAROLINAS

This paper applies a common empirical methodology in testing for convergence of per capita incomes across the counties in North and South Carolina. Decennial census data on per capita income for the 46 counties of South Carolina and the 100 counties of North Carolina are used to test for two types of income convergence over the 1959-2010 time span. The results indicate that both beta and sigma convergence occurred across the counties for the full period, but there were sub-periods (the 1980s, and the 2000s) over which neither measure of convergence was evident. In fact, measured by the beta method, there was statistically significant divergence of per capita incomes across both North and South Carolina counties in the decade of the 1980s. In general, there was great similarity in convergence measured by either method across the counties in these two states.
Physicochemical Properties and Bacterial Diversity of Sediment in Sea Cucumber Culture Ponds under High Summer Temperatures

This study examined the effect of aquaculture management parameters on sea cucumbers in culture ponds during high summer temperatures. The physicochemical properties of 18 sediment samples from six sea cucumber culture ponds were assessed at a high temperature (HT) and the end of the high temperature (EHT) stages of summer. High-throughput sequencing was used to analyze the bacterial community composition and diversity of the sediment in the culture pond. The results showed that total nitrogen (TN), total carbon (TC), total organic carbon (TOC), ammonia nitrogen (NH4+), total sulfur (TS), sulfate (SO42−), and sulfide (S2−) contents were the lowest in the Geziling sediments at both stages, indicating a favorable sediment environment. The TN, TC, TOC, and NH4+ contents decreased significantly in the Wulei Island sediments during the EHT stage, indicating strong self-purification capacity. The TN, TC, TOC, NH4+, TS, SO42−, and S2− were higher in the Rushankou and Xiaohongcun sediments during both stages, indicating a worse sediment environment. Alpha diversity analysis revealed increased bacterial diversity in the sediments during the HT stage when compared to that during the EHT stage. Correlation analysis between bacterial diversity and the physicochemical properties of the TN sediments had the greatest impact on bacterial diversity, followed by TOC, TC, NH4+, TS, S2−, SO42−, and NO2− (in order). Our results suggest that the physicochemical properties (TC, TOC, TN, and NH4+) of the culture pond sediment can significantly influence bacterial community composition and diversity. Management measures for aquaculture, including desilting and monthly water change, could positively affect these physicochemical properties and the bacterial community structure of the sediment. These findings will provide a reference for healthier aquaculture practices of Apostichopus japonicus under high summer temperatures.