Inspiring best business practices / Dr. Basil Mustafa

The people of Turkey ought to be congratulated for their hard work in achieving a sustained record of economic stability with growth over the last decade or more. Unemployment rate, particularly given the continuous growth of workforce, and inflation, remain the significant challenges. Nevertheless, Turkey maintained its Gross Domestic Product (purchasing power parity) share of the world’s total and improved its GDP’s percentage on exports of goods and services. Turkey’s exports to the UK have been growing steadily from about $2billion in 2001 to about$8billion in 2010 with the exception of 2009. Turkish industries in various sectors have been producing quality goods. In view of the growing popularity of the oriental drink Turkish “coffee” and that of coffee houses in England, one of the most innovative products of Turkey is the coffeemaker. Ironically, a few centuries ago Turkish coffee was perceived as a challenge to the religious culture of England. Writers in Britain’s 17th century denounced coffee as conducive to sin, a drink that “could not have originated in paradise,…but in hell”.1 Now we all must wait with great expectation to see the British people discovering the influence of Turkish dessert kazandibi

CLIPPO: Image-and-Language Understanding from Pixels Only

Multimodal models are becoming increasingly effective, in part due to unified components, such as the Transformer architecture. However, multimodal models still often consist of many task- and modality-specific pieces and training procedures. For example, CLIP (Radford et al., 2021) trains independent text and image towers via a contrastive loss. We explore an additional unification: the use of a pure pixel-based model to perform image, text, and multimodal tasks. Our model is trained with contrastive loss alone, so we call it CLIP-Pixels Only (CLIPPO). CLIPPO uses a single encoder that processes both regular images and text rendered as images. CLIPPO performs image-based tasks such as retrieval and zero-shot image classification almost as well as CLIP-style models, with half the number of parameters and no text-specific tower or embedding. When trained jointly via image-text contrastive learning and next-sentence contrastive learning, CLIPPO can perform well on natural language understanding tasks, without any word-level loss (language modelling or masked language modelling), outperforming pixel-based prior work. Surprisingly, CLIPPO can obtain good accuracy in visual question answering, simply by rendering the question and image together. Finally, we exploit the fact that CLIPPO does not require a tokenizer to show that it can achieve strong performance on multilingual multimodal retrieval without modifications.Comment: CVPR 2023. Code and pretrained models are available at https://github.com/google-research/big_vision/blob/main/big_vision/configs/proj/clippo/README.m

Hydrological Study and Analysis of Two Farm Dams in Erbil Governorate

This research presents hydrological study and analysis for two proposed farm dams (Chaluk and Zurgazraw) located in Erbil Governorate - Iraqi Kurdistan Region. Many site visits were made to the Chaluk and Zurgazraw areas to select the most suitable site for the farm dams. The area and properties of the catchment area for both farm dams were measured by arc GIS software and were equal to 1.99, and 3.97 km2 for Chaluk and Zurgazraw farm dams, respectively. The topographic study and surveying of the selected sites aimed to construct the contour maps of the sites, determine the capacity of the reservoir for different heights of the farm dam embankment, and locate the centerline of the dam and spillway. In the hydrological analysis, as the proposed farm dam’s streams are ungauged streams with no runoff data records, the U.S. Soil Conservation Service (SCS) method was used to find the annual runoff yield. This method depends on physical parameters of the catchment area and daily rainfall depth data taken from Erbil Meteorological station; the calculated minimum, maximum, and average runoff yield were equal to 16556, 233407, and 103957 m3 for Chaluk, and 33030, 456641, and, 207393 m3 , Zurgazraw farm dam. The Australian (ARR) organization method was used to determine the 50 year return period peak discharge for the farm dams catchment area, which were equal to 14.71, and 24.07 m3 /sec for Chaluk, and Zurgazraw farm dams, respectively. Based on the calculated average annual inflow and calculated annual sediment inflow into farm dams by Universal Soil Loss Equation, the dead, and live storages elevations, and volumes were fixed to be equal to 411, and 418 m.a.s.l. (meters above sea level) and 7741, and 103425 m3 for Chaluk, and 404, and 412 m.a.s.l 20863, and 293822m3 for Zurgazraw farm dam

From Sparse to Soft Mixtures of Experts

Sparse mixture of expert architectures (MoEs) scale model capacity without large increases in training or inference costs. Despite their success, MoEs suffer from a number of issues: training instability, token dropping, inability to scale the number of experts, or ineffective finetuning. In this work, we proposeSoft MoE, a fully-differentiable sparse Transformer that addresses these challenges, while maintaining the benefits of MoEs. Soft MoE performs an implicit soft assignment by passing different weighted combinations of all input tokens to each expert. As in other MoE works, experts in Soft MoE only process a subset of the (combined) tokens, enabling larger model capacity at lower inference cost. In the context of visual recognition, Soft MoE greatly outperforms standard Transformers (ViTs) and popular MoE variants (Tokens Choice and Experts Choice). For example, Soft MoE-Base/16 requires 10.5x lower inference cost (5.7x lower wall-clock time) than ViT-Huge/14 while matching its performance after similar training. Soft MoE also scales well: Soft MoE Huge/14 with 128 experts in 16 MoE layers has over 40x more parameters than ViT Huge/14, while inference time cost grows by only 2%, and it performs substantially better

Non-Histaminergic Angioedema Following Infection with COVID-19

Non-respiratory manifestations of COVID-19, including dermatological manifestations, have been reported, and although urticaria associated with COVID-19 has been reported, there have been no reports of non-histaminergic angioedema following infection with mild COVID-19. Non-histaminergic angioedema has a gradual onset and is characterized by submucosal swelling without accompanying urticaria or pruritus, and poor response to antihistamines and corticosteroids. We report a case of non-histaminergic angioedema in a 29-year-old woman with a history of mild COVID-19 infection. Our case highlights the fact that early diagnosis of non-histaminergic angioedema in mild COVID-19 patients is crucial for effective treatment and requires a high level of suspicion from both general and emergency physicians

Serum leptin and 25 Hydroxyvitamin D levels in patients with type II diabetes mellitus

Background: Vitamin D and Leptin appears to play a range of roles in beta cell growth and insulin secretion and most importantly interaction with other hormonal mediators and regulators of energy and metabolism. Objective: The aim of this study was to measure serum leptin and vitamin D levels and to investigate their relationships with vitamin D and other clinical laboratory parameters in patients with type II diabetes. Subjects and Methods: Blood samples were taken from 80 patients with type II diabetes mellitus encountered during their attending the Internal Medicine clinic consultancy in Ramadi Teaching Hospital and the National Diabetes Center for Treatment and Research at Al-Mustansiriya University and 60 healthy subject. From December 2014 to November 2015. Investigations included serum Leptin, 25OHD, Insulin, HbA1c using ELISA and biochemical test. Results: The median concentration of serum 25 OH vitamin D of patients (15.70 ng/ ml) was significantly lower than healthy controls (20.27 ng/ ml). The rate of vitamin D deficiency (VDD) was significantly higher in patients (82.5%) than healthy controls (48.3%). The serum insulin and HOMA- IR were significant increase in patients had vitamin D < 20 ng/ml when compared with an insufficient/normal group. There were no significant differences in leptin levels between type II DM and healthy control. Conclusion: These results strongly support the role of vitamin D deficiency and serum leptin in pathogenesis of type II diabetes