Weed Detection by Faster RCNN Model: An Enhanced Anchor Box Approach

(c) The Author/sTo apply weed control treatments effectively, the weeds must be accurately detected. Deep learning (DL) has been quite successful in performing the weed identification task. However, various aspects of the DL have not been explored in previous studies. This research aimed to achieve a high average precision (AP) of eight classes of weeds and a negative (non-weed) class, using the DeepWeeds dataset. In this regard, a DL-based two-step methodology has been proposed. This article is the second stage of the research, while the first stage has already been published. The former phase presented a weed detection pipeline and consisted of the evaluation of various neural networks, image resizers, and weight optimization techniques. Although a significant improvement in the mean average precision (mAP) was attained. However, the Chinee apple weed did not reach a high average precision. This result provided a solid ground for the next stage of the study. Hence, this paper presents an in-depth analysis of the Faster Region-based Convolutional Neural Network (RCNN) with ResNet-101, the best-obtained model in the past step. The architectural details of the Faster RCNN model have been thoroughly studied to investigate each class of weeds. It was empirically found that the generation of anchor boxes affects the training and testing performance of the Faster RCNN model. An enhancement to the anchor box scales and aspect ratios has been attempted by various combinations. The final results, with the addition of 64 × 64 scale size, and aspect ratio of 1:3 and 3:1, produced the best classification and localization of all classes of weeds and a negative class. An enhancement of 24.95% AP was obtained in Chinee apple weed. Furthermore, the mAP was improved by 2.58%. The robustness of the approach has been shown by the stratified k-fold cross-validation technique and testing on an external dataset.fals

A weight optimization-based transfer learning approach for plant disease detection of New Zealand vegetables.

Deep learning (DL) is an effective approach to identifying plant diseases. Among several DL-based techniques, transfer learning (TL) produces significant results in terms of improved accuracy. However, the usefulness of TL has not yet been explored using weights optimized from agricultural datasets. Furthermore, the detection of plant diseases in different organs of various vegetables has not yet been performed using a trained/optimized DL model. Moreover, the presence/detection of multiple diseases in vegetable organs has not yet been investigated. To address these research gaps, a new dataset named NZDLPlantDisease-v2 has been collected for New Zealand vegetables. The dataset includes 28 healthy and defective organs of beans, broccoli, cabbage, cauliflower, kumara, peas, potato, and tomato. This paper presents a transfer learning method that optimizes weights obtained through agricultural datasets for better outcomes in plant disease identification. First, several DL architectures are compared to obtain the best-suited model, and then, data augmentation techniques are applied. The Faster Region-based Convolutional Neural Network (RCNN) Inception ResNet-v2 attained the highest mean average precision (mAP) compared to the other DL models including different versions of Faster RCNN, Single-Shot Multibox Detector (SSD), Region-based Fully Convolutional Networks (RFCN), RetinaNet, and EfficientDet. Next, weight optimization is performed on datasets including PlantVillage, NZDLPlantDisease-v1, and DeepWeeds using image resizers, interpolators, initializers, batch normalization, and DL optimizers. Updated/optimized weights are then used to retrain the Faster RCNN Inception ResNet-v2 model on the proposed dataset. Finally, the results are compared with the model trained/optimized using a large dataset, such as Common Objects in Context (COCO). The final mAP improves by 9.25% and is found to be 91.33%. Moreover, the robustness of the methodology is demonstrated by testing the final model on an external dataset and using the stratified k-fold cross-validation method.Published onlin

Weed Identification by Single-Stage and Two-Stage Neural Networks: A Study on the Impact of Image Resizers and Weights Optimization Algorithms.

The accurate identification of weeds is an essential step for a site-specific weed management system. In recent years, deep learning (DL) has got rapid advancements to perform complex agricultural tasks. The previous studies emphasized the evaluation of advanced training techniques or modifying the well-known DL models to improve the overall accuracy. In contrast, this research attempted to improve the mean average precision (mAP) for the detection and classification of eight classes of weeds by proposing a novel DL-based methodology. First, a comprehensive analysis of single-stage and two-stage neural networks including Single-shot MultiBox Detector (SSD), You look only Once (YOLO-v4), EfficientDet, CenterNet, RetinaNet, Faster Region-based Convolutional Neural Network (RCNN), and Region-based Fully Convolutional Network (RFCN), has been performed. Next, the effects of image resizing techniques along with four image interpolation methods have been studied. It led to the final stage of the research through optimization of the weights of the best-acquired model by initialization techniques, batch normalization, and DL optimization algorithms. The effectiveness of the proposed work is proven due to a high mAP of 93.44% and validated by the stratified k-fold cross-validation technique. It was 5.8% improved as compared to the results obtained by the default settings of the best-suited DL architecture (Faster RCNN ResNet-101). The presented pipeline would be a baseline study for the research community to explore several tasks such as real-time detection and reducing the computation/training time. All the relevant data including the annotated dataset, configuration files, and inference graph of the final model are provided with this article. Furthermore, the selection of the DeepWeeds dataset shows the robustness/practicality of the study because it contains images collected in a real/complex agricultural environment. Therefore, this research would be a considerable step toward an efficient and automatic weed control system.Published onlin

Clinical, anthropometric, radiological and molecular characteristics of Egyptian achondroplasia patients

Background: Achondroplasia is the most common form of non lethal skeletal dysplasia. It is a fully penetrant autosomal dominant disorder and the majority of cases are sporadic resulting from de novo mutations associated with advanced paternal age. The phenotype of achondroplasia is related to disturbance in endochondral bone formation due to mutations in the fi broblast growth factor receptor-3 (FGFR3) gene. Aim of the Work: Evaluation of the cardinal phenotypic features in achondroplasia, the body physique using anthropometric measurements, the characteristic radiological signs in the patients as a main tool for diagnosis and detection of the most common mutations in achondroplasia patients in the studied sample.Subjects and Methods: From 42 cases referred to us as achondroplasia, we selected 20 cases where clinical manifestations were consistent with achondroplasia. Cases were subjected to full clinical examination, detailed anthropometric measurements, whole body skeletal survey and molecular studies of the most common mutations of the FGFR3 gene using PCR amplifi cation technique. Results: Nineteen cases were sporadic (95%) and one case had an affected father (5%). A paternal age above 35 years at the time of child’s birth was present in 7 cases (35%). Paternal exposure to occupational heat was noted in 6 cases (30%) and parental exposure to chemicals in 3 cases (15%). All cases showed typical clinical and radiological manifestations of achondroplasia. Anthropometricmeasurements quantitatively confi rmed the body physique in thestudied cases. G380R common mutations of the FGFR3 gene were detected in 15/18 cases (83%) with the G to A transition at nucleotide 1138 in 14 cases (77%). Agenesis of corpus callosum, not previously reported in association with achondroplasia, was present in the only case with the G-C transversio nmutation at nucleotide 1138 (5%).Conclusions: Awareness of the cardinal features of achondroplasia, properanthropometric measurements and detailed skeletal survey are the key foraccurate diagnosis, genetic counseling and avoidance of over diagnosis. The majority of studied Egyptian achondroplasia patients have the same common mutation that has been most often defi ned in patients with achondroplasia from other countries.Keywords: Achondroplasia, fi broblast growth factor receptor3,skeletal dysplasia, paternal heat exposure

Amoebic liver abscess – a cause of acute respiratory distress in an infant: a case report

<p>Abstract</p> <p>Introduction</p> <p>The usual presentation of amebic liver abscess in children is extremely variable and unpredictable. It presents with a picture of common pediatric illness that is fever, lethargy, and abdominal pain, and can go on to develop into a rare complication of rupture into the pleura to cause acute respiratory distress, which is another common pediatric illness. In our patient, diagnosis was not made or suspected in these two stages.</p> <p>Case presentation</p> <p>This is the report of a 2-year-old male infant who presented with a 2-week history of anorexia, fever, and abdominal pain. A few hours after admission, he suddenly developed acute respiratory distress; chest X-ray demonstrated massive right pleural effusion that failed to response to tube thoracostomy. Limited thoracotomy revealed a ruptured amebic liver abscess through the right cupola of the diaphragm. The content of the abscess was evacuated from the pleural cavity, which was drained with two large chest tubes. Serological examination confirmed the diagnosis of ruptured amebic liver abscess. Postoperative treatment with antibiotics including metronidazole continued until full recovery.</p> <p>Conclusion</p> <p>Diagnosis of such a rare disease requires a high degree of suspicion. In this patient, the diagnosis was only made postoperatively. The delay in presentation and the sudden onset of respiratory distress must be emphasized for all those physicians who care for children.</p

Quantitative determination of the effects of He–Ne laser irradiation on seed thermodynamics, germination attributes and metabolites of Safflower (Carthamus tinctorius L) in relation with the activities of germination enzymes

The present investigation was undertaken to assess the effects of different doses (100, 300, and 500 mJ) of low power He–Ne laser (632.8 nm) irradiation on seed germination and thermodynamics attributes and activities of potential germinating enzymes in relation with changes in seed metabolites. He–Ne laser seed irradiation increased the amylase (Amy), protease (Pro) and glucosidase (Gluco) activities, with a significant improvement in seed thermodynamics and seed germination attributes. A fast increase was found in free fatty acids (FFA), free amino acids (FAA), chlorophyll (Chl), carotenoids (Car), total soluble sugars (TSS) and reducing sugars (RS) in laser treated seeds in parallel with fast decline in seed oil contents and total soluble proteins (TSP). Significant positive correlations were recorded in laser-induced enhanced seed energy levels, germination, activities of germination enzymes with levels of FAA, FFA, Chl, TSS and RS, but a negative correlation with the levels of TSP and oil. In conclusion, the seed treatment with 100 and 300 mJ He–Ne laser was more effective to improve the seed germination potential associated with an improvement in seed energy levels due to increased activities of germination enzymes due to the speedy breakdown of seed reserves to simple metabolites as building blocks

Thymoquinone Lowers Blood Glucose and Reduces Oxidative Stress in a Rat Model of Diabetes

The aim of the present study was to assess the short-term effects of Thymoquinone (TQ) on oxidative stress, glycaemic control, and renal functions in diabetic rats. DM was induced in groups II and III with a single dose of streptozotocin (STZ), while group I received no medication (control). The rats in groups I and II were then given distilled water, while the rats in group III were given TQ at a dose of 50 mg/kg body weight/day for 4 weeks. Lipid peroxidase, nitric oxide (NO), total antioxidant capacity (TAC), glycated haemoglobin (HbA1c), lipid profiles, and renal function were assessed. Moreover, the renal tissues were used for histopathological examination. STZ increased the levels of HbA1c, lipid peroxidase, NO, and creatinine in STZ-induced diabetic rats in comparison to control rats. TAC was lower in STZ-induced diabetic rats than in the control group. Furthermore, rats treated with TQ exhibited significantly lower levels of HbA1c, lipid peroxidase, and NO than did untreated diabetic rats. TAC was higher in diabetic rats treated with TQ than in untreated diabetic rats. The histopathological results showed that treatment with TQ greatly attenuated the effect of STZ-induced diabetic nephropathy. TQ effectively adjusts glycaemic control and reduces oxidative stress in STZ-induced diabetic rats without significant damaging effects on the renal function

Biochar optimizes wheat quality, yield, and nitrogen acquisition in low fertile calcareous soil treated with organic and mineral nitrogen fertilizers

Crop quality and nutrient uptake are considerably influenced by fertilizers inputs and their application rate. Biochar (BC) improves nitrogen uptake and crop productivity. However, its interaction with synthetic and organic fertilizers in calcareous soil is not fully recognized. Therefore, we inspected the role of biochar (0, 10, 20, and 30 t ha–1) in improving N uptake and quality of wheat in a calcareous soil under integrated N management (90, 120, and 150 kg N ha–1) applied each from urea, farmyard manure (FYM) and poultry manure (PM) along with control) in 2 years field experiments. Application of 20 t BC along with 150 kg N ha–1 as poultry manure considerably improved wheat grain protein content (14.57%), grain (62.9%), straw (28.7%), and biological (38.4%) yield, grain, straw, and total N concentration by 14.6, 19.2, and 15.6% and their uptake by 84.6, 48.8, and 72.1%, respectively, over absolute control when averaged across the years. However, their impact was more pronounced in the 2nd year (2016–2017) after application compared to the 1st year (2015–2016). Therefore, for immediate crop benefits, it is recommended to use 20 t BC ha–1 once in 50 years for enhancing the nitrogen use efficiency of fertilizers and crop yield

Correlation of Circulating Omentin-1 with Bone Mineral Density in Multiple Sclerosis: The Crosstalk between Bone and Adipose Tissue

BACKGROUND: Patients with multiple sclerosis (MS) are at increased risk of osteoporosis and fractures. Adipose tissue-derived adipokines may play important roles in the osteoimmunology of MS. In order to determine whether omentin-1 and vaspin may be related to bone health in MS patients, we compared circulating levels of these recently identified adipokines, between MS patients and healthy controls. METHODS: A total of 35 ambulatory MS patients with relapsing-remitting courses were compared with 38 age- and sex-matched healthy controls. Bone mineral density (BMD) was determined for the lumbar spine (L2-L4) and the proximal femur using dual-energy x-ray absorptiometry. Circulating omentin-1, vaspin, osteocalcin, osteopontin, osteoprotegerin, the receptor activator of nuclear factor-κB ligand, matrix metalloproteinase 9, C-reactive protein and 25-hydroxy vitamin D levels were evaluated by highly specific enzyme-linked immunosorbent assay methods. RESULTS: There was no significant difference between the two groups regarding bone-related cytokines, adipocytokines, and the BMD measurements of patients with MS and the healthy controls. However, in multiple regression analysis, serum omentin-1 levels were positively correlated with BMD at the femoral neck (β = 0.49, p = 0.016), total hip (β = 0.42, p = 0.035), osteopontin (β = 0.42, p = 0.030) and osteocalcin (β = 0.53, p = 0.004) in MS patients. No correlations were found between vaspin, biochemical, and BMD measures in both groups. CONCLUSIONS: Elevated omentin-1 serum levels are correlated with BMD at the femoral neck and the serum levels of osteocalcin and osteopontin in MS patients. Therefore, there is crosstalk between adipose tissue and bone in MS

Clinical experience in T cell deficient patients

T cell disorders have been poorly understood until recently. Lack of knowledge of underlying molecular mechanisms together with incomplete data on long term outcome have made it difficult to assess prognosis and give the most effective treatment. Rapid progress in defining molecular defects, improved supportive care and much improved results from hematopoietic stem cell transplantation (HSCT) now mean that curative treatment is possible for many patients. However, this depends on prompt recognition, accurate diagnosis and careful treatment planning