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Meningiomas are the most common primary intracranial tumors and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists, and radiation oncologists rely on brain MRI for diagnosis, treatment planning, and longitudinal treatment monitoring. However, automated, objective, and quantitative tools for non-invasive assessment of meningiomas on multi-sequence MR images are not available. Here we present the BraTS Pre-operative Meningioma Dataset, as the largest multi-institutional expert annotated multilabel meningioma multi-sequence MR image dataset to date. This dataset includes 1,141 multi-sequence MR images from six sites, each with four structural MRI sequences (T2-, T2/FLAIR-, pre-contrast T1-, and post-contrast T1-weighted) accompanied by expert manually refined segmentations of three distinct meningioma sub-compartments: enhancing tumor, non-enhancing tumor, and surrounding non-enhancing T2/FLAIR hyperintensity. Basic demographic data are provided including age at time of initial imaging, sex, and CNS WHO grade. The goal of releasing this dataset is to facilitate the development of automated computational methods for meningioma segmentation and expedite their incorporation into clinical practice, ultimately targeting improvement in the care of meningioma patients.

Meningiomas are the most common primary intracranial tumors and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists, and radiation oncologists rely on brain MRI for diagnosis, treatment planning, and longitudinal treatment monitoring. However, automated, objective, and quantitative tools for non-invasive assessment of meningiomas on multi-sequence MR images are not available. Here we present the BraTS Pre-operative Meningioma Dataset, as the largest multi-institutional expert annotated multilabel meningioma multi-sequence MR image dataset to date. This dataset includes 1,141 multi-sequence MR images from six sites, each with four structural MRI sequences (T2-, T2/FLAIR-, pre-contrast T1-, and post-contrast T1-weighted) accompanied by expert manually refined segmentations of three distinct meningioma sub-compartments: enhancing tumor, non-enhancing tumor, and surrounding non-enhancing T2/FLAIR hyperintensity. Basic demographic data are provided including age at time of initial imaging, sex, and CNS WHO grade. The goal of releasing this dataset is to facilitate the development of automated computational methods for meningioma segmentation and expedite their incorporation into clinical practice, ultimately targeting improvement in the care of meningioma patients.

PET technology has immense potential for furthering understanding of the brain and associated disorders, including advancements in high-resolution tomographs and hybrid imaging modalities. Novel radiotracers targeting specific neurotransmitter systems and molecular markers provide opportunities to unveil intricate mechanisms underlying neurologic and psychiatric conditions. As PET imaging techniques and analysis methods continue to be refined, the field is poised to make significant contributions to personalized medicine for more targeted and effective interventions. PET instrumentation has advanced the fields of neurology and psychiatry, providing insights into pathophysiology and development of effective treatments., PET technology has immense potential for furthering understanding of the brain and associated disorders, including advancements in high-resolution tomographs and hybrid imaging modalities. Novel radiotracers targeting specific neurotransmitter systems and molecular markers provide opportunities to unveil intricate mechanisms underlying neurologic and psychiatric conditions. As PET imaging techniques and analysis methods continue to be refined, the field is poised to make significant contributions to personalized medicine for more targeted and effective interventions. PET instrumentation has advanced the fields of neurology and psychiatry, providing insights into pathophysiology and development of effective treatments.

We describe the design and results from the BraTS 2023 Intracranial Meningioma Segmentation Challenge. The BraTS Meningioma Challenge differed from prior BraTS Glioma challenges in that it focused on meningiomas, which are typically benign extra-axial tumors with diverse radiologic and anatomical presentation and a propensity for multiplicity. Nine participating teams each developed deep-learning automated segmentation models using image data from the largest multi-institutional systematically expert annotated multilabel multi-sequence meningioma MRI dataset to date, which included 1000 training set cases, 141 validation set cases, and 283 hidden test set cases. Each case included T2, T2/FLAIR, T1, and T1Gd brain MRI sequences with associated tumor compartment labels delineating enhancing tumor, non-enhancing tumor, and surrounding non-enhancing T2/FLAIR hyperintensity. Participant automated segmentation models were evaluated and ranked based on a scoring system evaluating lesion-wise metrics including dice similarity coefficient (DSC) and 95% Hausdorff Distance. The top ranked team had a lesion-wise median dice similarity coefficient (DSC) of 0.976, 0.976, and 0.964 for enhancing tumor, tumor core, and whole tumor, respectively and a corresponding average DSC of 0.899, 0.904, and 0.871, respectively. These results serve as state-of-the-art benchmarks for future pre-operative meningioma automated segmentation algorithms. Additionally, we found that 1286 of 1424 cases (90.3%) had at least 1 compartment voxel abutting the edge of the skull-stripped image edge, which requires further investigation into optimal pre-processing face anonymization steps., Comment: 16 pages, 11 tables, 10 figures, MICCAI

Threat analysis (TA) is a process to identify, detect, and evaluate security vulnerabilities systematically. Specifically, the TA, which focuses on threats that can potentially violate the customer's data ownership requirements of security and performance, is named Requirement Based Threat Analysis (RBTA). Despite the importance of RBTA, the current manual RBTA process is both time intensive and makes no assurance of completeness of the analysis. Thus, we develop a systematic analytic technique that enumerates customers' requirements and then determines all possible direct/indirect dependencies across them to conduct a generalized threat analysis from their requirements. The approach is validated for its effectiveness on actual Cloud customer requirements and can be generalized to apply to other requirements.

Threat analysis (TA) is a process to identify, detect, and evaluate security vulnerabilities systematically. Specifically, the TA, which focuses on threats that can potentially violate the customer's data ownership requirements of security and performance, is named Requirement Based Threat Analysis (RBTA). Despite the importance of RBTA, the current manual RBTA process is both time intensive and makes no assurance of completeness of the analysis. Thus, we develop a systematic analytic technique that enumerates customers' requirements and then determines all possible direct/indirect dependencies across them to conduct a generalized threat analysis from their requirements. The approach is validated for its effectiveness on actual Cloud customer requirements and can be generalized to apply to other requirements.

Background Lance–Adams syndrome (LAS), also known as chronic post-hypoxic myoclonus manifests as myoclonic movements of the face, limbs, or trunk following hypoxic brain injury, which may occur during respiratory failure or cardiac arrest. Case presentation We present a case and provide a video of a patient who developed LAS 3 years after experiencing cardiac arrest, presenting with action-induced generalized myoclonus upon standing. The patient exhibited a significant response to levetiracetam. To the best of our knowledge, this is the first reported case of LAS with such a delayed onset following the initial hypoxic event. Conclusion It is crucial for clinicians to be aware of this treatable condition and recognize that its onset may be delayed, occurring years after a hypoxic brain insult. This improved understanding will facilitate prompt diagnosis and effective management of LAS, ultimately enhancing patient outcomes.

Background: Assessment of a patient’s renal function may be used for two different purposes. One is to diagnose impaired renal function, and the other is to detect the presence of a progressive loss of renal function over time 1. In Sudan according to our knowledge there is lack of information regarding the impact of prolong type 2 diabetes mellitus on the renal function. Objective: This study aims to assess renal function described as serum creatinine, urea and some urine parameters in type 2 diabetics after more than ten years onset. To detect impact of patient age and the duration on renal function. Materials and methods: This study was designed as case control study, carried out in Northern State, Al Dabbah, during the period from Februarys to June 2014. Include 100 samples (57 males and 43 females), 50 samples collected from patient with more than ten years type 2 diabetic (27 males and 23 females) and 50 samples collected from healthy volunteers as pre described by physical examination and medical history (30 males and 20 females).  Results: The results showed statistically significant increase in the serum levels of creatinine and urea in diabetic compared to their copartner with p.value 0.000 and mean ± SD (3.29±2.25, 1.28±0.35) mg/dl and (63.88±3.38, 21.28±5.48) mg/dl for diabetic and non-diabetic respectively. urine parameters showed elevation and presence of albumin 35% in diabetic and 1% in non-diabetic, sugar 99% for diabetic and 0% in non-diabetic, acetone 60% for diabetic and 0% for non-diabetic, pus 55% for diabetic and 5% for non-diabetic, calcium oxalate 66% for diabetic and 1% for non-diabetic, RBCs 5% for diabetic and 2% for non-diabetic, yeast cells 2% for diabetic and 1% for non-diabetic, epithelial cells 11% for diabetic and 1% for non-diabetic.  Conclusion: There were significant increase in serum levels of creatinine and urea. And urine albumin, sugar, acetone, pus and calcium oxalate. Positive correlation between duration and urea

This work reveals undiscovered challenges in the performance and generalizability of deep learning models. We (1) identify spurious shortcuts and evaluation issues that can inflate performance and (2) propose training and analysis methods to address them. We trained an AI model to classify cancer on a retrospective dataset of 120,112 US exams (3,467 cancers) acquired from 2008 to 2017 and 16,693 UK exams (5,655 cancers) acquired from 2011 to 2015. We evaluated on a screening mammography test set of 11,593 US exams (102 cancers; 7,594 women; age 57.1 \pm 11.0) and 1,880 UK exams (590 cancers; 1,745 women; age 63.3 \pm 7.2). A model trained on images of only view markers (no breast) achieved a 0.691 AUC. The original model trained on both datasets achieved a 0.945 AUC on the combined US+UK dataset but paradoxically only 0.838 and 0.892 on the US and UK datasets, respectively. Sampling cancers equally from both datasets during training mitigated this shortcut. A similar AUC paradox (0.903) occurred when evaluating diagnostic exams vs screening exams (0.862 vs 0.861, respectively). Removing diagnostic exams during training alleviated this bias. Finally, the model did not exhibit the AUC paradox over scanner models but still exhibited a bias toward Selenia Dimension (SD) over Hologic Selenia (HS) exams. Analysis showed that this AUC paradox occurred when a dataset attribute had values with a higher cancer prevalence (dataset bias) and the model consequently assigned a higher probability to these attribute values (model bias). Stratification and balancing cancer prevalence can mitigate shortcuts during evaluation. Dataset and model bias can introduce shortcuts and the AUC paradox, potentially pervasive issues within the healthcare AI space. Our methods can verify and mitigate shortcuts while providing a clear understanding of performance.

Background: Assessment of a patient’s renal function may be used for two different purposes. One is to diagnose impaired renal function, and the other is to detect the presence of a progressive loss of renal function over time 1. In Sudan according to our knowledge there is lack of information regarding the impact of prolong type 2 diabetes mellitus on the renal function. Objective: This study aims to assess renal function described as serum creatinine, urea and some urine parameters in type 2 diabetics after more than ten years onset. To detect impact of patient age and the duration on renal function. Materials and methods: This study was designed as case control study, carried out in Northern State, Al Dabbah, during the period from Februarys to June 2014. Include 100 samples (57 males and 43 females), 50 samples collected from patient with more than ten years type 2 diabetic (27 males and 23 females) and 50 samples collected from healthy volunteers as pre described by physical examination and medical history (30 males and 20 females).  Results: The results showed statistically significant increase in the serum levels of creatinine and urea in diabetic compared to their copartner with p.value 0.000 and mean ± SD (3.29±2.25, 1.28±0.35) mg/dl and (63.88±3.38, 21.28±5.48) mg/dl for diabetic and non-diabetic respectively. urine parameters showed elevation and presence of albumin 35% in diabetic and 1% in non-diabetic, sugar 99% for diabetic and 0% in non-diabetic, acetone 60% for diabetic and 0% for non-diabetic, pus 55% for diabetic and 5% for non-diabetic, calcium oxalate 66% for diabetic and 1% for non-diabetic, RBCs 5% for diabetic and 2% for non-diabetic, yeast cells 2% for diabetic and 1% for non-diabetic, epithelial cells 11% for diabetic and 1% for non-diabetic.  Conclusion: There were significant increase in serum levels of creatinine and urea. And urine albumin, sugar, acetone, pus and calcium oxalate. Positive correlation between duration and urea

This work presents a methodology to evaluate the bioenergetic feasibility of alternative metabolic pathways for a given microbial conversion, optimising their energy yield and driving forces as a function of the concentration of metabolic intermediates. The tool, based on thermodynamic principles and multi-objective optimisation, accounts for pathway variants in terms of different electron carriers, as well as energy conservation (proton translocating) reactions within the pathway. The method also accommodates other constraints, some of them non-linear, such as the balance of conserved moieties. The approach involves the transformation of the maximum energy yield problem into a multi-objective mixed-integer linear optimisation problem which is then subsequently solved using the epsilon-constraint method, highlighting the trade-off between yield and rate in metabolic reactions. The methodology is applied to analyse several pathway alternatives occurring during propionate oxidation in anaerobic fermentation processes, as well as to the reverse TCA cycle pathway occurring during autotrophic microbial CO fixation. The results obtained using the developed methodology match previously reported literature and bring about insights into the studied pathways.

Deep-learning-based object detection methods show promise for improving screening mammography, but high rates of false positives can hinder their effectiveness in clinical practice. To reduce false positives, we identify three challenges: (1) unlike natural images, a malignant mammogram typically contains only one malignant finding; (2) mammography exams contain two views of each breast, and both views ought to be considered to make a correct assessment; (3) most mammograms are negative and do not contain any findings. In this work, we tackle the three aforementioned challenges by: (1) leveraging Sparse R-CNN and showing that sparse detectors are more appropriate than dense detectors for mammography; (2) including a multi-view cross-attention module to synthesize information from different views; (3) incorporating multi-instance learning (MIL) to train with unannotated images and perform breast-level classification. The resulting model, M&M, is a Multi-view and Multi-instance learning system that can both localize malignant findings and provide breast-level predictions. We validate M&M's detection and classification performance using five mammography datasets. In addition, we demonstrate the effectiveness of each proposed component through comprehensive ablation studies., Comment: MICCAI 2023 with supplementary materials

BACKGROUND: This study aimed to determine whether paromomycin plus miltefosine (PM/MF) is noninferior to sodium stibogluconate plus paromomycin (SSG/PM) for treatment of primary visceral leishmaniasis in eastern Africa. METHODS: An open-label, phase 3, randomized, controlled trial was conducted in adult and pediatric patients at 7 sites in eastern Africa. Patients were randomly assigned to either 20 mg/kg paromomycin plus allometric dose of miltefosine (14 days), or 20 mg/kg sodium stibogluconate plus 15 mg/kg paromomycin (17 days). The primary endpoint was definitive cure after 6 months. RESULTS: Of 439 randomized patients, 424 completed the trial. Definitive cure at 6 months was 91.2% (155 of 170) and 91.8% (156 of 170) in the PM/MF and SSG/PM arms in primary efficacy modified intention-to-treat analysis (difference, 0.6%; 97.5% confidence interval [CI], -6.2 to 7.4), narrowly missing the noninferiority margin of 7%. In the per-protocol analysis, efficacy was 92% (149 of 162) and 91.7% (155 of 169) in the PM/MF and SSG/PM arms (difference, -0.3%; 97.5% CI, -7.0 to 6.5), demonstrating noninferiority. Treatments were well tolerated. Four of 18 serious adverse events were study drug-related, and 1 death was SSG-related. Allometric dosing ensured similar MF exposure in children (<12 years) and adults. CONCLUSIONS: PM/MF and SSG/PM efficacies were similar, and adverse drug reactions were as expected given the drugs safety profiles. With 1 less injection each day, reduced treatment duration, and no risk of SSG-associated life-threatening cardiotoxicity, PM/MF is a more patient-friendly alternative for children and adults with primary visceral leishmaniasis in eastern Africa. Clinical Trials Registration. NCT03129646.

In this work, the effects of using natural lignocellulosic-based adsorbents from sugarcane bagasse (SC), cornstalk piths (CP), and corn cob (CC) on the physicochemical properties and quality of fried oils were studied. The properties of lignocellulosic biomasses were examined using X-ray diffraction (XRD), scanning electron microscope (SEM), and Fourier transform infrared spectroscopy (FTIR). Moreover, the changes in the physicochemical properties of fresh, fried oils (for 4, 8, 12, 16 and 20 h) and adsorbents-treated oils were examined. The XRD results revealed that SC and CP biomasses have more amorphous regions than CC biomass, which had the highest crystallinity percentage. The results also showed that lignocellulosic biomasses enhanced the quality of the used oils. SC was the most effective biomass to enhance the properties of the used sunflower oil. For instance, the acid value of oil samples fried for 20 h reduced from 0.63 ± 0.02 to 0.51 ± 0.02 mg KOH/g oil after SC biomass treatment. For the peroxide value, the SC biomass treatment reduced it from 9.45 ± 0.56 (fried oil for 20 h) to 6.91 ± 0.12 meq O2/kg. Similarly, SC biomass adsorbent reduced the p-Anisidine Value (p-AV) of the used oil (20 h) from 98.45 ± 6.31 to 77.92 ± 3.65. Moreover, SC adsorbents slightly improved the lightness of the used oils (20 h). In conclusion, natural lignocellulosic biomasses, particularly SC, could be utilized as natural adsorbents to improve the oil quality. The results obtained from this study could help in developing sustainable methods to regenerate used oils using natural and cheap adsorbents.

Medical images come in high resolutions. A high resolution is vital for finding malignant tissues at an early stage. Yet, this resolution presents a challenge in terms of modeling long range dependencies. Shallow transformers eliminate this problem, but they suffer from quadratic complexity. In this paper, we tackle this complexity by leveraging a linear self-attention approximation. Through this approximation, we propose an efficient vision model called HCT that stands for High resolution Convolutional Transformer. HCT brings transformers' merits to high resolution images at a significantly lower cost. We evaluate HCT using a high resolution mammography dataset. HCT is significantly superior to its CNN counterpart. Furthermore, we demonstrate HCT's fitness for medical images by evaluating its effective receptive field.Code available at https://bit.ly/3ykBhhf, Comment: MICCAI 2022 + Extra Experiments

Climate change is expected to affect agricultural production in direct and indirect pathways. The increase in mean temperatures directly accelerates crop development, the change in seasonal precipitation amounts together with increasing evaporative demand can indirectly lead to more drought stress for crops. In Egypt, the agricultural sector is highly vulnerable to climate change due to its dependence on the Nile River for irrigation, increasing soil salinity by sea water intrusion and soil deterioration as a result of decomposition of its organic contents. In this article, previous research carried out in Egypt on climate change assessments on water resources (the Nile River and rainfall on the north coast of Egypt), crop evapotranspiration, crop water requirements, crop yield, agricultural soils and national cultivated area are reviewed. Furthermore, the implemented actions to increase crop resilience to climate change were discussed. Additionally, the procedures used to reduce greenhouse gases emission were also reviewed. Keywords: Water resources, soil resources, climate-resilient crops, greenhouse gases emissions, carbon sequestration, biogas production

A two-year study was carried out at Giza Agricultural Experiments Station, Agricultural Research Center, Egypt during 2020 and 2021 to study the effect of three irrigation treatments (120, 100 and 80% ETo) on yields, amounts of applied irrigation water (AIW), water equivalent ratio (WER), of intercropped maize-cowpea, sole maize and cowpea cultivations. Water use efficiency (WUE) and water productivity (WP) were evaluated for sole cultivation of maize and cowpea. Results indicated that the AIW depths under 120, 100 and 80% ETo were respectively 1081, 926 and 772 mm in the 1st season and 1036, 889 and 742 mm in 2nd. There were no significant differences between yields of intercropped maize and cowpea irrigated with 120 and 100% ETo. Adopting the 100% ETo treatment will save 14% of irrigation water, however the highest WER values were obtained from 80% ETo treatment, namely 1.21 and 1.26 respectively in the 1st and 2ndseasons. For sole cultivation of maize and cowpea, the highest WUE and WP were obtained under 100% ETo. The two-season average local Kc values for maize and cowpea under 120% ETo were 0.73 and 0.70, respectively.  It could be concluded that irrigating cowpea intercropped with maize with 100% ETo irrigation treatment resulted in insignificantly less yield than that obtained under 120% ETo treatment, but with 14% less applied irrigation water. Keywords: Maize, cowpea, intercropping, Irrigation water amounts, Water equivalent ratio, Water productivity, Water use efficiency, Crop coefficients

A field experiment was conducted on drip irrigated date palm trees (Barhi var.) in a private farm during the 2020 and 2021 seasons to evaluate the effect of five irrigation treatments (120, 100, 80, and 60% ETo and farmer practice) on amounts of applied irrigation water (AIW), consumptive use (CU), date yield and its components, fruit quality, water use efficiency (WUE), water productivity (WP), consumed electric energy, net income, a local date crop coefficient (Kc) and yield response factor (Ky). Results revealed that, average ETo values varied between 1.26 mm/day in December and 9.85 mm/day in July. The 2–year average AIW values were 17 377, 14 546, 11 715, 8 885 and 24 680 m3/ha for the 120, 100, 80 and 60% ETo treatments and farmer practice, respectively. Highest and lowest fruit yields of 39.2 and 15.2 t/ha were recorded for the 120% and 60% ETo treatments, respectively. The WP values of the same treatments were 2.27 and 1.23 kg fruits/m3. Seasonal average Kc value of 0.74 is obtained for the 120% ETo treatment. The Ky value of 1.187 is obtained for the Barhi variety. The lowest consumed energy (64.7%) and highest net income (31.8%) were recorded for 60% and 120% ETo treatments compared with farmer practice.  Keywords: Applied water, water consumption, water use efficiency, water productivity, crop coefficient, yield response factor, energy saving, net income

Climate change is expected to affect agricultural production in direct and indirect pathways. The increase in mean temperatures directly accelerates crop development, the change in seasonal precipitation amounts together with increasing evaporative demand can indirectly lead to more drought stress for crops. In Egypt, the agricultural sector is highly vulnerable to climate change due to its dependence on the Nile River for irrigation, increasing soil salinity by sea water intrusion and soil deterioration as a result of decomposition of its organic contents. In this article, previous research carried out in Egypt on climate change assessments on water resources (the Nile River and rainfall on the north coast of Egypt), crop evapotranspiration, crop water requirements, crop yield, agricultural soils and national cultivated area are reviewed. Furthermore, the implemented actions to increase crop resilience to climate change were discussed. Additionally, the procedures used to reduce greenhouse gases emission were also reviewed. Keywords: Water resources, soil resources, climate-resilient crops, greenhouse gases emissions, carbon sequestration, biogas production

A field experiment was conducted on drip irrigated date palm trees (Barhi var.) in a private farm during the 2020 and 2021 seasons to evaluate the effect of five irrigation treatments (120, 100, 80, and 60% ETo and farmer practice) on amounts of applied irrigation water (AIW), consumptive use (CU), date yield and its components, fruit quality, water use efficiency (WUE), water productivity (WP), consumed electric energy, net income, a local date crop coefficient (Kc) and yield response factor (Ky). Results revealed that, average ETo values varied between 1.26 mm/day in December and 9.85 mm/day in July. The 2–year average AIW values were 17 377, 14 546, 11 715, 8 885 and 24 680 m3/ha for the 120, 100, 80 and 60% ETo treatments and farmer practice, respectively. Highest and lowest fruit yields of 39.2 and 15.2 t/ha were recorded for the 120% and 60% ETo treatments, respectively. The WP values of the same treatments were 2.27 and 1.23 kg fruits/m3. Seasonal average Kc value of 0.74 is obtained for the 120% ETo treatment. The Ky value of 1.187 is obtained for the Barhi variety. The lowest consumed energy (64.7%) and highest net income (31.8%) were recorded for 60% and 120% ETo treatments compared with farmer practice.  Keywords: Applied water, water consumption, water use efficiency, water productivity, crop coefficient, yield response factor, energy saving, net income

A two-year study was carried out at Giza Agricultural Experiments Station, Agricultural Research Center, Egypt during 2020 and 2021 to study the effect of three irrigation treatments (120, 100 and 80% ETo) on yields, amounts of applied irrigation water (AIW), water equivalent ratio (WER), of intercropped maize-cowpea, sole maize and cowpea cultivations. Water use efficiency (WUE) and water productivity (WP) were evaluated for sole cultivation of maize and cowpea. Results indicated that the AIW depths under 120, 100 and 80% ETo were respectively 1081, 926 and 772 mm in the 1st season and 1036, 889 and 742 mm in 2nd. There were no significant differences between yields of intercropped maize and cowpea irrigated with 120 and 100% ETo. Adopting the 100% ETo treatment will save 14% of irrigation water, however the highest WER values were obtained from 80% ETo treatment, namely 1.21 and 1.26 respectively in the 1st and 2ndseasons. For sole cultivation of maize and cowpea, the highest WUE and WP were obtained under 100% ETo. The two-season average local Kc values for maize and cowpea under 120% ETo were 0.73 and 0.70, respectively.  It could be concluded that irrigating cowpea intercropped with maize with 100% ETo irrigation treatment resulted in insignificantly less yield than that obtained under 120% ETo treatment, but with 14% less applied irrigation water. Keywords: Maize, cowpea, intercropping, Irrigation water amounts, Water equivalent ratio, Water productivity, Water use efficiency, Crop coefficients

Dairy and plant-based proteins are widely utilized in various food applications. Several techniques have been employed to improve the techno-functional properties of these proteins. Among them, pulsed electric field (PEF) technology has recently attracted considerable attention as a green technology to enhance the functional properties of food proteins. In this review, we briefly explain the fundamentals of PEF devices, their components, and pulse generation and discuss the impacts of PEF treatment on the structure of dairy and plant proteins. In addition, we cover the PEF-induced changes in the techno-functional properties of proteins (including solubility, gelling, emulsifying, and foaming properties). In this work, we also discuss the main challenges and the possible future trends of PEF applications in the food proteins industry. PEF treatments at high strengths could change the structure of proteins. The PEF treatment conditions markedly affect the treatment results with respect to proteins’ structure and techno-functional properties. Moreover, increasing the electric field strength could enhance the emulsifying properties of proteins and protein-polysaccharide complexes. However, more research and academia–industry collaboration are recommended to build highly effective PEF devices with controlled processing conditions.

Diabetes Miletus (DM) is a global epidemic disease. It is estimated that there are already 415 million adults aged 20–79 years diabetics worldwide. Sildenafil citrate is a phosphodiesterase type 5 (PDE5) inhibitor, which increases cyclic guanosine monophosphate (cGMP) and metformin (MET) is a biguanide used for the treatment of type 2 diabetes which increases peripheral insulin sensitivity. Aim: This study aims to assess the effect of sildenafil citrate and metformin on lipid profile and glycemic control in diabetic and prediabetic albino rats. Materials and methods: Adult male albino rats are used and divided into nine groups each group consists of 10 rats, diabetes is induced by feeding a high-fat diet (HFD) for an initial period of 2 weeks followed by a single intraperitoneal injection of (35 mg/kg) Streptozotocin. Prediabetes is induced by feeding (HFD) and glucose in water for a period of 2 weeks. Sildenafil was given in a dose of (5 &10 mg/kg/day orally for 4 weeks), metformin was given in a dose of (50 &100 mg/kg/day orally for 4 weeks) using oral gavages to normal healthy rats, diabetic and prediabetic rats. Blood samples were collected after 4 weeks of treatment in all experimental groups. Results: Combined administration of sildenafil and metformin on diabetic rats improving hyperglycemia, oxidative stress, and hyperlipidemia induced by streptozotocin than the administration of metformin or sildenafil alone. Conclusion: Sildenafil has beneficial effects against some diabetic complications. The present study showed that sildenafil with metformin has beneficial effects against diabetic complications.

Diabetes Miletus (DM) is a global epidemic disease. It is estimated that there are already 415 million adults aged 20–79 years diabetics worldwide. Sildenafil citrate is a phosphodiesterase type 5 (PDE5) inhibitor, which increases cyclic guanosine monophosphate (cGMP) and metformin (MET) is a biguanide used for the treatment of type 2 diabetes which increases peripheral insulin sensitivity. Aim: This study aims to assess the effect of sildenafil citrate and metformin on lipid profile and glycemic control in diabetic and prediabetic albino rats. Materials and methods: Adult male albino rats are used and divided into nine groups each group consists of 10 rats, diabetes is induced by feeding a high-fat diet (HFD) for an initial period of 2 weeks followed by a single intraperitoneal injection of (35 mg/kg) Streptozotocin. Prediabetes is induced by feeding (HFD) and glucose in water for a period of 2 weeks. Sildenafil was given in a dose of (5 &10 mg/kg/day orally for 4 weeks), metformin was given in a dose of (50 &100 mg/kg/day orally for 4 weeks) using oral gavages to normal healthy rats, diabetic and prediabetic rats. Blood samples were collected after 4 weeks of treatment in all experimental groups. Results: Combined administration of sildenafil and metformin on diabetic rats improving hyperglycemia, oxidative stress, and hyperlipidemia induced by streptozotocin than the administration of metformin or sildenafil alone. Conclusion: Sildenafil has beneficial effects against some diabetic complications. The present study showed that sildenafil with metformin has beneficial effects against diabetic complications.

A field experiment was conducted in a private farm (30o40' N latitude, 32o15' E longitude, and 10.0 m above mean sea level), Ismailia Governorate, Egypt, during the 2020 and 2021 summer growing seasons. The aim was to study the effect of four irrigation treatments (125, 100, 75% ETo, and farmer practice) on pearl millet forage yield. Average amounts of applied irrigation water under 125, 100, 75% ETo and farmer practice were 4637, 3710, 2782, and 5950 m3/ha, respectively with respective average water consumption values of 4130, 3308, 2482, and 5302 m3/ha. Compared to the farmer practice, the saved water was 22, 38, and 53 % for the 125, 100, and 75% ETo treatments. Average water use efficiency values were 7.91, 7.55, 6.96 and 4.59 kg/m3, and average water productivity values were 7.04, 6.73, 6.21, and 4.08 kg/m3 for 125, 100, 75% ETo and farmer treatments, respectively. The Ky factor was 1.17 indicating that the pearl millet crop is moderately sensitive to water stress. Irrigating pearl millet in sandy soils with 100% ETo will save 38% of applied irrigation water, achieve water use efficiency of 7.55 green yield/m3 of water consumed, and water productivity of 6.73 kg green yield/m3 of water applied. Keywords: Pearl millet, BIS model, sprinkler system, sandy soil, water use efficiency and water productivity

A field experiment was conducted in a private farm (30o40' N latitude, 32o15' E longitude, and 10.0 m above mean sea level), Ismailia Governorate, Egypt, during the 2020 and 2021 summer growing seasons. The aim was to study the effect of four irrigation treatments (125, 100, 75% ETo, and farmer practice) on pearl millet forage yield. Average amounts of applied irrigation water under 125, 100, 75% ETo and farmer practice were 4637, 3710, 2782, and 5950 m3/ha, respectively with respective average water consumption values of 4130, 3308, 2482, and 5302 m3/ha. Compared to the farmer practice, the saved water was 22, 38, and 53 % for the 125, 100, and 75% ETo treatments. Average water use efficiency values were 7.91, 7.55, 6.96 and 4.59 kg/m3, and average water productivity values were 7.04, 6.73, 6.21, and 4.08 kg/m3 for 125, 100, 75% ETo and farmer treatments, respectively. The Ky factor was 1.17 indicating that the pearl millet crop is moderately sensitive to water stress. Irrigating pearl millet in sandy soils with 100% ETo will save 38% of applied irrigation water, achieve water use efficiency of 7.55 green yield/m3 of water consumed, and water productivity of 6.73 kg green yield/m3 of water applied. Keywords: Pearl millet, BIS model, sprinkler system, sandy soil, water use efficiency and water productivity

Diabetes Miletus (DM) is a global epidemic disease. It is estimated that there are already 415 million adults aged 20–79 years diabetics worldwide. Sildenafil citrate is a phosphodiesterase type 5 (PDE5) inhibitor, which increases cyclic guanosine monophosphate (cGMP) and metformin (MET) is a biguanide used for the treatment of type 2 diabetes which increases peripheral insulin sensitivity. Aim: This study aims to assess the effect of sildenafil citrate and metformin on lipid profile and glycemic control in diabetic and prediabetic albino rats. Materials and methods: Adult male albino rats are used and divided into nine groups each group consists of 10 rats, diabetes is induced by feeding a high-fat diet (HFD) for an initial period of 2 weeks followed by a single intraperitoneal injection of (35 mg/kg) Streptozotocin. Prediabetes is induced by feeding (HFD) and glucose in water for a period of 2 weeks. Sildenafil was given in a dose of (5 &10 mg/kg/day orally for 4 weeks), metformin was given in a dose of (50 &100 mg/kg/day orally for 4 weeks) using oral gavages to normal healthy rats, diabetic and prediabetic rats. Blood samples were collected after 4 weeks of treatment in all experimental groups. Results: Combined administration of sildenafil and metformin on diabetic rats improving hyperglycemia, oxidative stress, and hyperlipidemia induced by streptozotocin than the administration of metformin or sildenafil alone. Conclusion: Sildenafil has beneficial effects against some diabetic complications. The present study showed that sildenafil with metformin has beneficial effects against diabetic complications.

Diabetes Miletus (DM) is a global epidemic disease. It is estimated that there are already 415 million adults aged 20–79 years diabetics worldwide. Sildenafil citrate is a phosphodiesterase type 5 (PDE5) inhibitor, which increases cyclic guanosine monophosphate (cGMP) and metformin (MET) is a biguanide used for the treatment of type 2 diabetes which increases peripheral insulin sensitivity. Aim: This study aims to assess the effect of sildenafil citrate and metformin on lipid profile and glycemic control in diabetic and prediabetic albino rats. Materials and methods: Adult male albino rats are used and divided into nine groups each group consists of 10 rats, diabetes is induced by feeding a high-fat diet (HFD) for an initial period of 2 weeks followed by a single intraperitoneal injection of (35 mg/kg) Streptozotocin. Prediabetes is induced by feeding (HFD) and glucose in water for a period of 2 weeks. Sildenafil was given in a dose of (5 &10 mg/kg/day orally for 4 weeks), metformin was given in a dose of (50 &100 mg/kg/day orally for 4 weeks) using oral gavages to normal healthy rats, diabetic and prediabetic rats. Blood samples were collected after 4 weeks of treatment in all experimental groups. Results: Combined administration of sildenafil and metformin on diabetic rats improving hyperglycemia, oxidative stress, and hyperlipidemia induced by streptozotocin than the administration of metformin or sildenafil alone. Conclusion: Sildenafil has beneficial effects against some diabetic complications. The present study showed that sildenafil with metformin has beneficial effects against diabetic complications.

Yasmine Samir Galal,1 Walaa Ahmed Khairy,1 Ahmed Ali Taha,2 Tarek Tawfik Amin1 1Public Health and Community Medicine Department, Faculty of Medicine, Cairo University, Cairo, Egypt; 2Vascular Surgery Consultant, National Institute of Diabetes and Endocrinology, Cairo, EgyptCorrespondence: Walaa Ahmed KhairyPublic Health and Community Medicine Department, Faculty of Medicine, Cairo University, Kasr Alainy Street, Cairo, 11562, EgyptTel +20-1223682081Email Walaa.khairy@kasralainy.edu.egBackground and Purpose: Diabetic foot ulcers (DFUs) markedly contribute to morbidity and mortality of diabetic patients. Hence, this study was conducted to investigate the predictors of foot ulcers among Egyptian diabetic patients.Methods: A case-control study was conducted among 488 diabetic patients attending the inpatient departments and outpatient clinics at the National Diabetes Institute in Egypt. A pretested data collection sheet was designed to collect and record the following: socio-demographic data, diabetic history and lifestyle characteristics, recorded comorbidities, and the results of foot examination.Results: Significant positive predictors of DFUs on multivariate logistic regression analysis included presence of three or more comorbidities; two or more diabetic complications; callus; and flatfoot. Significant protective (negative) predictors were management of diabetes by diet, oral hypoglycemic drugs (OHGs), and insulin; and intact vibration sense.Conclusion: Significant positive predictors of DFUs on multivariate analysis were presence of three or more comorbidities, two or more diabetic complications, callus and flatfoot, while protective predictors were management of diabetes by diet, OHGs, and insulin; and intact vibration sense. Hence, close monitoring should be provided to diabetic patients with comorbidities and complications to reduce the risk of DFUs.Keywords: diabetic foot ulcers, comorbidities, peripheral vascular disease, foot deformities

Deep learning relies on the availability of a large corpus of data (labeled or unlabeled). Thus, one challenging unsettled question is: how to train a deep network on a relatively small dataset? To tackle this question, we propose an evolution-inspired training approach to boost performance on relatively small datasets. The knowledge evolution (KE) approach splits a deep network into two hypotheses: the fit-hypothesis and the reset-hypothesis. We iteratively evolve the knowledge inside the fit-hypothesis by perturbing the reset-hypothesis for multiple generations. This approach not only boosts performance, but also learns a slim network with a smaller inference cost. KE integrates seamlessly with both vanilla and residual convolutional networks. KE reduces both overfitting and the burden for data collection. We evaluate KE on various network architectures and loss functions. We evaluate KE using relatively small datasets (e.g., CUB-200) and randomly initialized deep networks. KE achieves an absolute 21% improvement margin on a state-of-the-art baseline. This performance improvement is accompanied by a relative 73% reduction in inference cost. KE achieves state-of-the-art results on classification and metric learning benchmarks. Code available at http://bit.ly/3uLgwYb, Comment: CVPR Oral 2021

A neural network regularizer (e.g., weight decay) boosts performance by explicitly penalizing the complexity of a network. In this paper, we penalize inferior network activations -- feature embeddings -- which in turn regularize the network's weights implicitly. We propose singular value maximization (SVMax) to learn a more uniform feature embedding. The SVMax regularizer supports both supervised and unsupervised learning. Our formulation mitigates model collapse and enables larger learning rates. We evaluate the SVMax regularizer using both retrieval and generative adversarial networks. We leverage a synthetic mixture of Gaussians dataset to evaluate SVMax in an unsupervised setting. For retrieval networks, SVMax achieves significant improvement margins across various ranking losses. Code available at https://bit.ly/3jNkgDt

Retrieval networks learn a feature embedding where similar samples are close together, and different samples are far apart. This feature embedding is essential for computer vision applications such as face/person recognition, zero-shot learn- ing, and image retrieval. Despite these important applications, retrieval networks are less popular compared to classification networks due to multiple reasons: (1) The cross-entropy loss – used with classification networks – is stabler and converges faster compared to metric learning losses – used with retrieval networks. (2) The cross-entropy loss has a huge toolbox of utilities and extensions. For instance, both AdaCos and self-knowledge distillation have been proposed to tackle low sample complexity in classification networks; also, both CAM and Grad-CAM have been proposed to visualize attention in classification networks. To promote retrieval networks, it is important to equip them with an equally powerful toolbox. Accordingly, we propose an evolution-inspired approach to tackle low sample complexity in feature embedding. Then, we propose SVMax to regularize the feature embedding and avoid model collapse. Furthermore, we propose L2-CAF to visualize attention in retrieval networks. To tackle low sample complexity, we propose an evolution-inspired training approach to boost performance on relatively small datasets. The knowledge evolution (KE) approach splits a deep network into two hypotheses: the fit-hypothesis and the reset-hypothesis. We iteratively evolve the knowledge inside the fit-hypothesis by perturbing the reset-hypothesis for multiple generations. This approach not only boosts performance but also learns a slim (pruned) network with a smaller inference cost. KE reduces both overfitting and the burden for data collection. To regularize the feature embedding and avoid model collapse, We propose singular value maximization (SVMax) to promote a uniform feature embedding. Our formulation mitigates model collapse and e

Cloud computing offers a model where resources (storage, applications, etc.) are abstracted and provided “as-aservice” in a remotely accessible manner. Although there are numerous claimed benefits of the Cloud to ensure confidentiality, integrity, and availability of the stored data, the number of security breaches is still on the rise. The lack of security assurance and transparency prevented customers/enterprises from trusting the Cloud Service Providers (CSPs). Unless the customer's security requirements are identified and documented by the CSPs, customers can not be assured that the CSPs will satisfy their requirements. Furthermore, the customer's compensation upon a violation is a manual time intensive process.In this paper we address the aforementioned challenges by proposing a decentralized customer-based monitoring approach running over Ethereum blockchain. The proposed approach allows the customer(s) to validate the compliance of CSP(s) to the contracted services in the Service Level Agreements (SLAs) and “autonomsly” compensate customers in case of security breaches. At the same time, the proposed approach prevents customers from misreporting for financial gain. The approach builds upon the Ethereum blockchain infrastructure in order to securely store monitoring logs and incorporate SLAs as smart contracts. The compliance validation framework is implemented and its functionality is evaluated on Amazon EC2 and Ethereum Blockchain.

Recently, modern wireless communication applications are extended to call high frequency bands including millimeter waves for 5G systems. Therefore, the propagation properties of such waves in different media have attracted many researchers. In this work, the results of the S-parameters measurements of mortar with four thicknesses are obtained using a nondestructive free space measurement technique for the frequency bands from 8 GHz up to 32 GHz. The obtained results of the dielectric properties and loss factors for the prepared mortar samples are realized. The variation in both the reflection and transmission coefficients and the dielectric properties with curing time conditions of mortar structure is examined. The dielectric properties of water are realized using the proposed method to subtract the effects of water contents from the prepared mortar samples. The effects of the sample thickness and relaxation frequency are considered. The obtained measurements are compared to the simulated results based on a full wave simulation software package of CSTMWS algorithms. Finally, excellent agreements are achieved between the simulated and measured results.

Recently, modern wireless communication applications are extended to call high frequency bands including millimeter waves for 5G systems. Therefore, the propagation properties of such waves in different media have attracted many researchers. In this work, the results of the S-parameters measurements of mortar with four thicknesses are obtained using a nondestructive free space measurement technique for the frequency bands from 8 GHz up to 32 GHz. The obtained results of the dielectric properties and loss factors for the prepared mortar samples are realized. The variation in both the reflection and transmission coefficients and the dielectric properties with curing time conditions of mortar structure is examined. The dielectric properties of water are realized using the proposed method to subtract the effects of water contents from the prepared mortar samples. The effects of the sample thickness and relaxation frequency are considered. The obtained measurements are compared to the simulated results based on a full wave simulation software package of CSTMWS algorithms. Finally, excellent agreements are achieved between the simulated and measured results.

Cloud computing offers a model where resources (storage, applications, etc.) are abstracted and provided “as-aservice” in a remotely accessible manner. Although there are numerous claimed benefits of the Cloud to ensure confidentiality, integrity, and availability of the stored data, the number of security breaches is still on the rise. The lack of security assurance and transparency prevented customers/enterprises from trusting the Cloud Service Providers (CSPs). Unless the customer's security requirements are identified and documented by the CSPs, customers can not be assured that the CSPs will satisfy their requirements. Furthermore, the customer's compensation upon a violation is a manual time intensive process.In this paper we address the aforementioned challenges by proposing a decentralized customer-based monitoring approach running over Ethereum blockchain. The proposed approach allows the customer(s) to validate the compliance of CSP(s) to the contracted services in the Service Level Agreements (SLAs) and “autonomsly” compensate customers in case of security breaches. At the same time, the proposed approach prevents customers from misreporting for financial gain. The approach builds upon the Ethereum blockchain infrastructure in order to securely store monitoring logs and incorporate SLAs as smart contracts. The compliance validation framework is implemented and its functionality is evaluated on Amazon EC2 and Ethereum Blockchain.

Two field experiments were conducted during 2015/16 and 2016/17 seasons at Kafr El-Hamam Agricultural Research Station, Sharkia Governorate to study the effect of two methods of nitrogen application on yield and quality of three flax cultivars. In the 1st method, all N was applied prior to the first irrigation and in the 2nd method half N was applied prior to the first irrigation + ½ N dose prior to the second one. Application of 2nd method and delaying harvest from 135 to 150 up to 165 days after sowing (DAS) were associated with the highest values of yield and quality. Giza 10 variety ranked first and significantly surpassed the two other cultivars (Belnika and Sakha 5) in terms of straw yield. However, Sakha 5 outyielded significantly the two tested flax cultivars regarding seed yield. For highest values of yield and quality, we recommend planting Giza 10 and Sakha 5 flax cultivars with a split application of nitrogen and delaying harvest to up to 150 DAS. Key words: Flax, cultivars, splitting nitrogen, harvest date

Two field experiments were conducted during 2015/16 and 2016/17 seasons at Kafr El-Hamam Agricultural Research Station, Sharkia Governorate to study the effect of two methods of nitrogen application on yield and quality of three flax cultivars. In the 1st method, all N was applied prior to the first irrigation and in the 2nd method half N was applied prior to the first irrigation + ½ N dose prior to the second one. Application of 2nd method and delaying harvest from 135 to 150 up to 165 days after sowing (DAS) were associated with the highest values of yield and quality. Giza 10 variety ranked first and significantly surpassed the two other cultivars (Belnika and Sakha 5) in terms of straw yield. However, Sakha 5 outyielded significantly the two tested flax cultivars regarding seed yield. For highest values of yield and quality, we recommend planting Giza 10 and Sakha 5 flax cultivars with a split application of nitrogen and delaying harvest to up to 150 DAS. Key words: Flax, cultivars, splitting nitrogen, harvest date

Retrieval networks are essential for searching and indexing. Compared to classification networks, attention visualization for retrieval networks is hardly studied. We formulate attention visualization as a constrained optimization problem. We leverage the unit L2-Norm constraint as an attention filter (L2-CAF) to localize attention in both classification and retrieval networks. Unlike recent literature, our approach requires neither architectural changes nor fine-tuning. Thus, a pre-trained network's performance is never undermined L2-CAF is quantitatively evaluated using weakly supervised object localization. State-of-the-art results are achieved on classification networks. For retrieval networks, significant improvement margins are achieved over a Grad-CAM baseline. Qualitative evaluation demonstrates how the L2-CAF visualizes attention per frame for a recurrent retrieval network. Further ablation studies highlight the computational cost of our approach and compare L2-CAF with other feasible alternatives. Code available at https://bit.ly/3iDBLFv, Comment: ECCV'2020

Background: Bacterial vaginosis (BV) is the most common cause of unpleasant vaginal odor and discharge in women of reproductive age. It is induced by an imbalance in naturally occurring microflora. Any change in the resident flora including reduction of lactobacilli allows for different anaerobic bacteria to gain a foothold and multiply. Nevertheless the process is multifactorial and the initial mechanism of replacement of normal lactobacillary flora by opportunistic pathogens. In pregnancy, certain complications such as preterm delivery, premature rupture of the membranes, and so on could ensue from Bacterial vaginosis. Objective: This study aimed to determine the frequency of Gardnerella vaginalis among pregnant women at Khartoum state hospitals, and to find out risk factors predisposing to the infection. Material and methods: A total of 140 of high vaginal swab were collected and examined by using wet preparation, Amsel criteria and culture method for detection of Gardnerella vaginalis from 70 pregnant women attended to Khartoum hospitals. Results: The overall prevalence of the studied Gardnerella vaginalis among pregnant women at Khartoum hospitals was as follows: Gardnerella vaginalis was isolated from 20 pregnant women (28.5%). The most frequent age group was 21-30 years (71.4%) and the most frequent group was second trimester (61.5%). Conclusion: The highest rate with Gardnerella was detected from pregnant women that came from Khartoum, followed by Omdurman. The most infections were detected in second trimester of pregnancy. The rate of Gardenerlla was found to be higher within age group 21-30 years. Keywords: Pregnant Women, vaginosis, Gardnerella vaginalis, Sudanese

The kidney is complex vital organs, and has many functions. The main function it‘s removal of toxic and excess  substancesfrom the plasma, if there is any defect in the kidney like renal failure can disrupt  this function. The aim of this study was to determine the level of Zinc and Copper in Sudanese patient with chronic renal failure. This study was designed as case control, which includes 100 blood samples, a 60 from these sample were collected from patient with chronic renal failure and 40 samples were collected from health individual as control group and the sample is collected by using sterile disposable syringes and separated by centrifuge. Carried out in Ribat University Hospital in Khartoum state, during period from March to June 2018. And the plasma levels of zinc and copper determined by the use of atomic absorption spectrophotometer (OPERATOR’S MANUAL January 2003 VER 3.94 C), and the obtained results were analyzed by SPSS. The result of this study showed that there was significant decrease (p<0.05) in the plasma levels of zinc and copper in patient with chronic renal failure compared to the control subjects. The mean of plasma Zn was 0.3mg/l in test group and 0.7mg/l in control group with p. value of 0.002 and the mean of plasma Copper was 0.5mg/l in test group and 0.7mg/l in control group with p. value of 0.019. Also the study showed the gender and age of the patient, also the duration of the disease have no effect on the plasma level of zinc and copper (p 0.05). The study concludes that the plasma level of zinc and copper are low in patient with chronic renal failure. And the gender and age of the patient also the duration of disease have no significant effect on the plasma level of zinc and copper. Keywords: Chronic Renal Failure, Zinc, Copper, Sudanese

Background: The thyroid gland is responsible for the production of two hormones. Those are regulating body metabolism, neurologic development, and numerous other body functions. So this study aimed to determine the level of serum Zinc and Manganese in Sudanese patient with non-cancerous thyroid disorders in Khartoum state. Material and Methods: This study was designed as case control, which includes 100 blood samples, a 60 from these samples were collected from patient with non-cancerous thyroid disorders and 40 samples were collected from health individual as control group. A total of 60 blood samples from the patients the males is 32 sample 53% and females is 28 sample 47%. Carried out in different Hospital in Khartoum state and the sample is collected by using sterile disposable syringes and separated by centrifuge, during period from March to June 2018. And the serum levels of zinc and manganese determined by atomic absorption spectrophotometer (OPERATOR’S MANUAL January 2003 VER 3.94 C), and the obtained results were analyzed by SPSS. Results: The study showed that there was significant different because the mean of serum Zn was 0.285 in test group and 0.720 in control group with p.value of 0.001 in serum level of Zn and Mn in patient compared to control subject, significant decrease in the serum levels of Zn and increase in Mn. Mean of Mn in test group was 0.428 and 0.406 control group with p.value of 0.006. Also the study showed the age, gender of the patient and duration of the disease have no effect on the serum level of Zn and Mn. Conclusion: This study conclude that the serum level of Zn is decrease and Mn is increase in patients with non-cancerous thyroid disorders and the age, gender of the patient and duration of the disease have no effect on the serum level of Zn and Mn. Keywords: Thyroid disorders, Zinc, Manganese, Sudanese

We introduce an unsupervised formulation to estimate heteroscedastic uncertainty in retrieval systems. We propose an extension to triplet loss that models data uncertainty for each input. Besides improving performance, our formulation models local noise in the embedding space. It quantifies input uncertainty and thus enhances interpretability of the system. This helps identify noisy observations in query and search databases. Evaluation on both image and video retrieval applications highlight the utility of our approach. We highlight our efficiency in modeling local noise using two real-world datasets: Clothing1M and Honda Driving datasets. Qualitative results illustrate our ability in identifying confusing scenarios in various domains. Uncertainty learning also enables data cleaning by detecting noisy training labels.

We cast visual retrieval as a regression problem by posing triplet loss as a regression loss. This enables epistemic uncertainty estimation using dropout as a Bayesian approximation framework in retrieval. Accordingly, Monte Carlo (MC) sampling is leveraged to boost retrieval performance. Our approach is evaluated on two applications: person re-identification and autonomous car driving. Comparable state-of-the-art results are achieved on multiple datasets for the former application. We leverage the Honda driving dataset (HDD) for autonomous car driving application. It provides multiple modalities and similarity notions for ego-motion action understanding. Hence, we present a multi-modal conditional retrieval network. It disentangles embeddings into separate representations to encode different similarities. This form of joint learning eliminates the need to train multiple independent networks without any performance degradation. Quantitative evaluation highlights our approach competence, achieving 6% improvement in a highly uncertain environment.

We employ triplet loss as a feature embedding regularizer to boost classification performance. Standard architectures, like ResNet and Inception, are extended to support both losses with minimal hyper-parameter tuning. This promotes generality while fine-tuning pretrained networks. Triplet loss is a powerful surrogate for recently proposed embedding regularizers. Yet, it is avoided due to large batch-size requirement and high computational cost. Through our experiments, we re-assess these assumptions. During inference, our network supports both classification and embedding tasks without any computational overhead. Quantitative evaluation highlights a steady improvement on five fine-grained recognition datasets. Further evaluation on an imbalanced video dataset achieves significant improvement. Triplet loss brings feature embedding characteristics like nearest neighbor to classification models. Code available at \url{http://bit.ly/2LNYEqL}., Comment: WACV 2020 Camera ready + supplementary material

Background: Skin tags (acrochordons) are the common small benign connective tissue tumor of the dermis that occurs in old subjects usually located on the neck and the major flexors .and the aim of this study to estimate the prevalence of Diabetes Mellitus and dyslipidemia among patients with Skin Tags in Khartoum state. Material and Methods: This is descriptive case control study and was conducted during the period from March to July 2018. In this study 50 [28 (56%) male and 22 (54%) female] patients with skin tags and 20 [11 (55%) male and 9 (45%) female] healthy individual are randomly selected, blood samples were collected after fulfillment of questionnaire, fasting venous blood collected in fluoride oxalate container for fasting glucose, cholesterol and triglycerides and 2.5ml venous blood in EDTA for HbA1c,  and were analysis by spectrophotometer for glucose cholesterol and triglycerides and  ichroma for HbA1c,obtained results were analyzed statistically by using SPSS. Results: The mean of fasting blood glucose, HbA1c, cholesterol and triglycerides of case is (111mg.dl, 5.6 %, 205mg.dl, 160mg.dl) respectively. And the mean of fasting blood glucose, HbA1c, cholesterol and triglycerides of healthy individual is (86mg.dl, 5.0%, 149mg.dl, 170mg.dl) respectively. 62.2% of male has (1-10 ST), 38.5% of male has (11-20 ST) and 37.8% of female has (1-10 ST) ,61.5% has 11-20 ST. case aged 20-40 years (48.6% has 1-10 ST and 15.4% has 11-20 ST ), case aged 41-80 years (51.4% has 1-10 ST and 84.6% has 11-20 ST). Conclusion: There was significant correlation between number of skin tags and mean levels of fasting blood glucose, HbA1c, and fasting serum cholesterol levels, no significant correlation between gender and number of ST, significant correlation between age and number of ST. Keywords: Skin Tags, Fasting Blood Glucose, Hba1c, Cholesterol, Triglycerides, Sudanese

Background: The thyroid gland is responsible for the production of two hormones. Those are regulating body metabolism, neurologic development, and numerous other body functions. So this study aimed to determine the level of serum Zinc and Manganese in Sudanese patient with non-cancerous thyroid disorders in Khartoum state. Material and Methods: This study was designed as case control, which includes 100 blood samples, a 60 from these samples were collected from patient with non-cancerous thyroid disorders and 40 samples were collected from health individual as control group. A total of 60 blood samples from the patients the males is 32 sample 53% and females is 28 sample 47%. Carried out in different Hospital in Khartoum state and the sample is collected by using sterile disposable syringes and separated by centrifuge, during period from March to June 2018. And the serum levels of zinc and manganese determined by atomic absorption spectrophotometer (OPERATOR’S MANUAL January 2003 VER 3.94 C), and the obtained results were analyzed by SPSS. Results: The study showed that there was significant different because the mean of serum Zn was 0.285 in test group and 0.720 in control group with p.value of 0.001 in serum level of Zn and Mn in patient compared to control subject, significant decrease in the serum levels of Zn and increase in Mn. Mean of Mn in test group was 0.428 and 0.406 control group with p.value of 0.006. Also the study showed the age, gender of the patient and duration of the disease have no effect on the serum level of Zn and Mn. Conclusion: This study conclude that the serum level of Zn is decrease and Mn is increase in patients with non-cancerous thyroid disorders and the age, gender of the patient and duration of the disease have no effect on the serum level of Zn and Mn. Keywords: Thyroid disorders, Zinc, Manganese, Sudanese

The kidney is complex vital organs, and has many functions. The main function it‘s removal of toxic and excess  substancesfrom the plasma, if there is any defect in the kidney like renal failure can disrupt  this function. The aim of this study was to determine the level of Zinc and Copper in Sudanese patient with chronic renal failure. This study was designed as case control, which includes 100 blood samples, a 60 from these sample were collected from patient with chronic renal failure and 40 samples were collected from health individual as control group and the sample is collected by using sterile disposable syringes and separated by centrifuge. Carried out in Ribat University Hospital in Khartoum state, during period from March to June 2018. And the plasma levels of zinc and copper determined by the use of atomic absorption spectrophotometer (OPERATOR’S MANUAL January 2003 VER 3.94 C), and the obtained results were analyzed by SPSS. The result of this study showed that there was significant decrease (p<0.05) in the plasma levels of zinc and copper in patient with chronic renal failure compared to the control subjects. The mean of plasma Zn was 0.3mg/l in test group and 0.7mg/l in control group with p. value of 0.002 and the mean of plasma Copper was 0.5mg/l in test group and 0.7mg/l in control group with p. value of 0.019. Also the study showed the gender and age of the patient, also the duration of the disease have no effect on the plasma level of zinc and copper (p 0.05). The study concludes that the plasma level of zinc and copper are low in patient with chronic renal failure. And the gender and age of the patient also the duration of disease have no significant effect on the plasma level of zinc and copper. Keywords: Chronic Renal Failure, Zinc, Copper, Sudanese

Background: Bacterial vaginosis (BV) is the most common cause of unpleasant vaginal odor and discharge in women of reproductive age. It is induced by an imbalance in naturally occurring microflora. Any change in the resident flora including reduction of lactobacilli allows for different anaerobic bacteria to gain a foothold and multiply. Nevertheless the process is multifactorial and the initial mechanism of replacement of normal lactobacillary flora by opportunistic pathogens. In pregnancy, certain complications such as preterm delivery, premature rupture of the membranes, and so on could ensue from Bacterial vaginosis. Objective: This study aimed to determine the frequency of Gardnerella vaginalis among pregnant women at Khartoum state hospitals, and to find out risk factors predisposing to the infection. Material and methods: A total of 140 of high vaginal swab were collected and examined by using wet preparation, Amsel criteria and culture method for detection of Gardnerella vaginalis from 70 pregnant women attended to Khartoum hospitals. Results: The overall prevalence of the studied Gardnerella vaginalis among pregnant women at Khartoum hospitals was as follows: Gardnerella vaginalis was isolated from 20 pregnant women (28.5%). The most frequent age group was 21-30 years (71.4%) and the most frequent group was second trimester (61.5%). Conclusion: The highest rate with Gardnerella was detected from pregnant women that came from Khartoum, followed by Omdurman. The most infections were detected in second trimester of pregnancy. The rate of Gardenerlla was found to be higher within age group 21-30 years. Keywords: Pregnant Women, vaginosis, Gardnerella vaginalis, Sudanese

Cloud computing offers a model where resources (storage, applications, etc.) are abstracted and provided "as-a-service" in a remotely accessible manner. In such a service-based environment, the Cloud provisioning relies on stipulated Service Level Agreements (SLAs). Such an agreement is a contract between the Cloud Service Provider (CSP) and the Cloud Service Customer (CSC) regarding the offered services. These SLAs specify the Cloud services requested by the customers and are required to be achieved by the CSPs. A variety of parameters for different aspects of a service can be included in the SLA, such as but not limited to: availability, performance, downtime and location of the data. Although there are numerous claimed benefits of the Cloud to ensure confidentiality, integrity, and availability of the stored data, the number of security breaches is still on the rise. The lack of security assurance and transparency prevented customers/enterprises from trusting the CSPs, and hence not using their services. Unless the customer's security requirements are identified and documented by the CSPs, customers can not be assured that the CSPs will satisfy their requirements. Although the recent efforts on specification of security services using SLAs, also known as security SLAs or secSLAs, is a positive development, multiple technical and usability issues limit the adoption of Cloud secSLAs in practice. For example, multiple CSPs offer similar security services (e.g., "encryption key management") albeit with different capabilities and prices. The customers need to comparatively assess the offered security services in order to select the best CSP matching their security requirements. However, the presence of both explicit and implicit dependencies across security related services add further challenges for Cloud customers to: (i) specify their security requirements taking service dependencies into consideration, (ii) determine which CSP can satisfy these requirements in a q