A Bayesian network approach to county-level corn yield prediction using historical data and expert knowledge

Machine learning has become a popular technology that has not only turbo-charged the existing problems in the AI but it has also emerged as the powerful toolkit to solve some of the interesting problems across the various interdisciplinary domains. The availability of food is the biggest problem of the 21st century and many experts have raised their concerns as we continue to see a rise in the global human population. There have been many efforts in this direction which include but not limited to improvement in the seeds quality, good management practices, prior knowledge about the expected yield, etc. In this work, we propose a data-driven approach that is ‘gray box’ i.e. that seamlessly utilizes expert knowledge in constructing a statistical network model for corn yield forecasting. Our multivariate gray box model is developed on Bayesian network analysis to build a Directed Acyclic Graph (DAG) between predictors and yield. Starting from a complete graph connecting various carefully chosen variables and yield, expert knowledge is used to prune or strengthen edges connecting variables. Subsequently, the structure (connectivity and edge weights) of the DAG that maximizes the likelihood of observing the training data is identified via optimization. We curated an extensive set of historical data (1948 − 2012) for each of the 99 counties in Iowa as data to train the model. We discuss preliminary results, and specifically focus on (a) the structure of the learned network and how it corroborates with known trends, and (b) how partial information still produces reasonable predictions (predictions with gappy data), and show that incorporating the missing information improves predictions

Influence of process parameters on torsional strength, impact toughness and hardness of dissimilar AISI 304 and AISI 1021 friction welded steels

In this present study an attempt was made to join austenitic stainless steel (AISI 304) with low alloy steel (AISI 1021) at different rotational speeds and at different axial pressures and then determining the strength of the joint by means of mechanical properties such as torsional strength, impact strength and micro hardness. The experimental results indicate that the rotational speed and the axial pressure have a significant effect on the mechanical properties of the joint and it is possible to improve the quality of the joint by selecting the optimum parameters

EVALUATION OF WEAR BEHAVIOR OF Al-Si ALLOY USING SiC AS THE REINFORCEMENT

The current study investigates the wear behavior of the SiC particles reinforced Al-Si alloy composites developed using the stir casting process. The results were obtained from the wear tests of the cast Al-Si alloy and prepared SiC reinforcement composites containing 3 % wt and 9 % wt using fine and coarse size SiC particles. The wear test of all the developed composites were done at different testing conditions with varying loads. The analysis of wear traces, as well as the wear debris, was done at every composition but at higher loads. It was observed that the wear resistance was improved with increasing the amount as well as decreasing the size of the SiC particles. However, the wear rate of the composites increases with increasing the applied load. From the microstructural study of specimen after the wear test one can conclude that both adhesive and abrasive wear mechanisms contribute for wear of SiC particle composites

Combating Wear of ASTM A36 Steel by Surface Modification Using Thermally Sprayed Cermet Coatings

Thermal spray coatings can be applied economically on machine parts to enhance their requisite surface properties like wear, corrosion, erosion resistance, and so forth. Detonation gun (D-Gun) thermal spray coatings can be applied on the surface of carbon steels to improve their wear resistance. In the present study, alloy powder cermet coatings WC-12% Co and Cr3C2-25% NiCr have been deposited on ASTM A36 steel with D-Gun thermal spray technique. Sliding wear behavior of uncoated ASTM A36 steel and D-Gun sprayed WC-12% Co and Cr3C2-25% NiCr coatings on base material is observed on a Pin-On-Disc Wear Tester. Sliding wear performance of WC-12% Co coating is found to be better than the Cr3C2-25% NiCr coating. Wear performance of both these cermet coatings is found to be better than uncoated ASTM A36 steel. Thermally sprayed WC-12% Co and Cr3C2-25% NiCr cermet coatings using D-Gun thermal spray technique is found to be very useful in improving the sliding wear resistance of ASTM A36 steel

EVALUATION OF WEAR BEHAVIOR OF Al-Si ALLOY USING SiC AS THE REINFORCEMENT

The current study investigates the wear behavior of the SiC particles reinforced Al-Si alloy composites developed using the stir casting process. The results were obtained from the wear tests of the cast Al-Si alloy and prepared SiC reinforcement composites containing 3 % wt and 9 % wt using fine and coarse size SiC particles. The wear test of all the developed composites were done at different testing conditions with varying loads. The analysis of wear traces, as well as the wear debris, was done at every composition but at higher loads. It was observed that the wear resistance was improved with increasing the amount as well as decreasing the size of the SiC particles. However, the wear rate of the composites increases with increasing the applied load. From the microstructural study of specimen after the wear test one can conclude that both adhesive and abrasive wear mechanisms contribute for wear of SiC particle composites

Study of hematological profile of systemic lupus erythematosus

Background: Hematological abnormalities are prevalent in systemic lupus erythematosus (SLE), with approximately 72% of patients experiencing anemia, primarily in the form of autoimmune hemolytic anemia. Other manifestations include leukopenia (32%), lymphopenia (54%), and thrombocytopenia (23%). This study aimed to further investigate these hematological manifestations, which may serve as presentations of SLE and might be overlooked if suspicion levels are low. Methods: A descriptive observational study was conducted over 18 months at a Sir Ganga Ram hospital, a tertiary care centre. One hundred thirteen SLE cases, comprising newly diagnosed patients and previously diagnosed patients’ records, were reviewed, with 13 cases excluded based on exclusion criteria. One hundred patients with hematological abnormalities and fulfilling ≥4 SLICC criteria for SLE diagnosis were included in the study. Results: One hundred cases of SLE with hematological abnormalities (88 women, 12 men) were analyzed. At presentation, 83% (n=84) of patients displayed hematological manifestations. The most prevalent abnormality was anemia, present in 72% of the study group, with a mean hemoglobin level of 10.073 gm/dl. Additionally, leukopenia, lymphopenia, thrombocytopenia, and pancytopenia were observed in 32%, 54%, 23%, and 14% of cases, respectively. Neutropenia was detected in only 5% of cases. Conclusions: Hematological manifestations are the most common presenting signs of SLE in North India. Anemia, with a multifactorial basis, is the most frequent hematological abnormality throughout the disease course. A high index of suspicion is crucial when evaluating cases of anemia in daily clinical practice

An end-to-end convolutional selective autoencoder approach to Soybean Cyst Nematode eggs detection

This paper proposes a novel selective autoencoder approach within the framework of deep convolutional networks. The crux of the idea is to train a deep convolutional autoencoder to suppress undesired parts of an image frame while allowing the desired parts resulting in efficient object detection. The efficacy of the framework is demonstrated on a critical plant science problem. In the United States, approximately $1 billion is lost per annum due to a nematode infection on soybean plants. Currently, plant-pathologists rely on labor-intensive and time-consuming identification of Soybean Cyst Nematode (SCN) eggs in soil samples via manual microscopy. The proposed framework attempts to significantly expedite the process by using a series of manually labeled microscopic images for training followed by automated high-throughput egg detection. The problem is particularly difficult due to the presence of a large population of non-egg particles (disturbances) in the image frames that are very similar to SCN eggs in shape, pose and illumination. Therefore, the selective autoencoder is trained to learn unique features related to the invariant shapes and sizes of the SCN eggs without handcrafting. After that, a composite non-maximum suppression and differencing is applied at the post-processing stage.Comment: A 10 pages, 8 figures International Conference on Machine Leaning(ICML) Submissio

Ultrasound-Guided Transversus Abdominis Plane Block Versus Intraperitoneal Instillation of Bupivacaine after Laparoscopic Cholecystectomy – A Randomized Control Trial

Background: Postoperative pain prolongs hospital stay after laparoscopic cholecystectomy and remains a major challenge during the postoperative period. Effective pain control encourages early ambulation, which significantly reduces postoperative complications. In recent years, multimodal analgesia has been recommended with fewer adverse effects and more effective analgesia. The primary objective of this study was to compare the efficacy of analgesia between Transversus Abdominis Plane Block (TAP) Block and intraperitoneal instillation of bupivacaine by comparing the meantime of the first dose of rescue analgesia in either group and the total supplementary analgesia required. Methods: This retrospective observational study was conducted on 150 patients who underwent laparoscopic cholecystectomy Group 1 comprised of patients who had received Intraperitoneal Bupivacaine for analgesia and Group 2 received TAP Block for pain relief. Results: Time of the first dose of analgesia after surgery was observed earlier in Group 1 as compared to Group 2 (Time – hours: 9.2 ± 2 vs. 12.3 ± 1.6; p = 0.0001. The Total dose of analgesic was higher in the Intra Peritoneal Bupivacaine Group as compared to the TAP group. Conclusion: AP block provided for a better quality of analgesia as assessed by the reduced requirement of intravenous supplementary analgesia which was less in patients who were given TAP Block as compared to local instillation of Bupivacaine. Keywords: Cholecystectomy, Bupivacaine, Transversus abdominis plane bloc

Global Retinoblastoma Presentation and Analysis by National Income Level.

Importance: Early diagnosis of retinoblastoma, the most common intraocular cancer, can save both a child's life and vision. However, anecdotal evidence suggests that many children across the world are diagnosed late. To our knowledge, the clinical presentation of retinoblastoma has never been assessed on a global scale. Objectives: To report the retinoblastoma stage at diagnosis in patients across the world during a single year, to investigate associations between clinical variables and national income level, and to investigate risk factors for advanced disease at diagnosis. Design, Setting, and Participants: A total of 278 retinoblastoma treatment centers were recruited from June 2017 through December 2018 to participate in a cross-sectional analysis of treatment-naive patients with retinoblastoma who were diagnosed in 2017. Main Outcomes and Measures: Age at presentation, proportion of familial history of retinoblastoma, and tumor stage and metastasis. Results: The cohort included 4351 new patients from 153 countries; the median age at diagnosis was 30.5 (interquartile range, 18.3-45.9) months, and 1976 patients (45.4%) were female. Most patients (n = 3685 [84.7%]) were from low- and middle-income countries (LMICs). Globally, the most common indication for referral was leukocoria (n = 2638 [62.8%]), followed by strabismus (n = 429 [10.2%]) and proptosis (n = 309 [7.4%]). Patients from high-income countries (HICs) were diagnosed at a median age of 14.1 months, with 656 of 666 (98.5%) patients having intraocular retinoblastoma and 2 (0.3%) having metastasis. Patients from low-income countries were diagnosed at a median age of 30.5 months, with 256 of 521 (49.1%) having extraocular retinoblastoma and 94 of 498 (18.9%) having metastasis. Lower national income level was associated with older presentation age, higher proportion of locally advanced disease and distant metastasis, and smaller proportion of familial history of retinoblastoma. Advanced disease at diagnosis was more common in LMICs even after adjusting for age (odds ratio for low-income countries vs upper-middle-income countries and HICs, 17.92 [95% CI, 12.94-24.80], and for lower-middle-income countries vs upper-middle-income countries and HICs, 5.74 [95% CI, 4.30-7.68]). Conclusions and Relevance: This study is estimated to have included more than half of all new retinoblastoma cases worldwide in 2017. Children from LMICs, where the main global retinoblastoma burden lies, presented at an older age with more advanced disease and demonstrated a smaller proportion of familial history of retinoblastoma, likely because many do not reach a childbearing age. Given that retinoblastoma is curable, these data are concerning and mandate intervention at national and international levels. Further studies are needed to investigate factors, other than age at presentation, that may be associated with advanced disease in LMICs