Books in Arabic Script

The chapter approaches the book in Arabic script as the indispensable means for the transmission of knowledge across Eurasia and Africa, within cultures and across cultural boundaries, since the seventh century ad. The state of research can be divided into manuscript and print studies, but there is not yet a history of the book in Arabic script that captures its plurilinear development for over fourteen hundred years. The chapter explores the conceptual and practical challenges that impede the integration of the book in Arabic script into book history at large and includes an extensive reference list that reflects its diversity. The final published version was slightly updated, and includes seven illustrations of six Qurans from the holdings of Columbia University Libraries, four manuscripts and two printed versions. Moreover, the illustrations are images of historical artifacts which are in the public domain - despite Wiley's copyright claim

Islam, science, and the challenge of history

New Heavenxii, 239 hlm.: index; 20 c

Lung disease recognition methods using audio-based analysis with machine learning

The use of computer-based automated approaches and improvements in lung sound recording techniques have made lung sound-based diagnostics even better and devoid of subjectivity errors. Using a computer to evaluate lung sound features more thoroughly with the use of analyzing changes in lung sound behavior, recording measurements, suppressing the presence of noise contaminations, and graphical representations are all made possible by computer-based lung sound analysis. This paper starts with a discussion of the need for this research area, providing an overview of the field and the motivations behind it. Following that, it details the survey methodology used in this work. It presents a discussion on the elements of sound-based lung disease classification using machine learning algorithms. This includes commonly prior considered datasets, feature extraction techniques, pre-processing methods, artifact removal methods, lung-heart sound separation, deep learning algorithms, and wavelet transform of lung audio signals. The study introduces studies that review lung screening including a summary table of these references and discusses the literature gaps in the existing studies. It is concluded that the use of sound-based machine learning in the classification of respiratory diseases has promising results. While we believe this material will prove valuable to physicians and researchers exploring sound-signal-based machine learning, large-scale investigations remain essential to solidify the findings and foster wider adoption within the medical community

Розробка виявлення об'єктів з хмар точок тривимірного набору даних за допомогою нейронної мережі Point-Pillars

Deep learning algorithms are able to automatically handle point clouds over a broad range of 3D imaging implementations. They have applications in advanced driver assistance systems, perception and robot navigation, scene classification, surveillance, stereo vision, and depth estimation. According to prior studies, the detection of objects from point clouds of a 3D dataset with acceptable accuracy is still a challenging task. The Point-Pillars technique is used in this work to detect a 3D object employing 2D convolutional neural network (CNN) layers. Point-Pillars architecture includes a learnable encoder to use Point-Nets for learning a demonstration of point clouds structured with vertical columns (pillars). The Point-Pillars architecture operates a 2D CNN to decode the predictions, create network estimations, and create 3D envelop boxes for various object labels like pedestrians, trucks, and cars. This study aims to detect objects from point clouds of a 3D dataset by Point-Pillars neural network architecture that makes it possible to detect a 3D object by means of 2D convolutional neural network (CNN) layers. The method includes producing a sparse pseudo-image from a point cloud using a feature encoder, using a 2D convolution backbone to process the pseudo-image into high-level, and using detection heads to regress and detect 3D bounding boxes. This work utilizes an augmentation for ground truth data as well as additional augmentations of global data methods to include further diversity in the data training and associating packs. The obtained results demonstrated that the average orientation similarity (AOS) and average precision (AP) were 0.60989, 0.61157 for trucks, and 0.74377, 0.75569 for cars.Алгоритми глибокого навчання дозволяють автоматично обробляти хмари точок у широкому діапазоні реалізацій тривимірної візуалізації. Вони застосовуються в сучасних системах допомоги водієві, в області сприйняття та навігації роботів, класифікації сцен, спостереження, стереобачення та оцінки глибини. Згідно з попередніми дослідженнями, виявлення об'єктів з хмар точок тривимірного набору даних з прийнятною точністю все ще є складним завданням. У роботі використовується метод Point-Pillars для виявлення тривимірного об'єкта з використанням шарів двовимірної згорткової нейронної мережі (CNN). Архітектура Point-Pillars включає навчальний кодувальник для використання Point-Nets для навчання демонстрації хмар точок, структурованих вертикальними стовпцями (pillars). Архітектура Point-Pillars використовує двовимірну CNN для декодування прогнозів, створення оцінок мережі та тривимірних оболонок для позначення різних об'єктів, таких як пішоходи, вантажівки та легкові автомобілі. Метою даного дослідження є виявлення об'єктів із хмар точок тривимірного набору даних за допомогою архітектури нейронної мережі Point-Pillars, що дозволяє виявляти тривимірний об'єкт за допомогою шарів двовимірної згорткової нейронної мережі (CNN). Даний метод включає в себе отримання розрідженого псевдозображення з хмари точок за допомогою кодувальника ознак, використання магістралі двовимірної згортки для обробки псевдозображення у високорівневе та використання детекторних головок для регресії і виявлення тривимірних обмежуючих рамок. У роботі використовується доповнення до даних підсупутникових спостережень, а також додаткові доповнення до глобальних методів збору даних для включення подальшої різноманітності в пакети даних навчання та ідентифікації. Отримані результати показали, що середня подібність орієнтації (AOS) та середня точність (AP) склали 0,60989, 0,61157 для вантажних автомобілів та 0,74377, 0,75569 для легкових автомобілів

Baseline Susceptibility of Different Geographical Strains of Anopheles stephensi (Diptera: Culicidae) to Temephos in Malarious Areas of Iran

Background: Malaria still remains a public health problem in Iran. There are different vector control interventions such as insecticide spraying. The present study was carried out to determine the susceptibility status of Anopheles stephensi larvae to temephos as a national plan for monitoring and mapping of insecticide resistanceMethods: Eight different localities in two main malarious provinces were determined as field collecting sites. Mos­quitoes were collected from the field and reared in an insectray. Susceptibility assays were carried out according to the WHO method. The laboratory reared susceptible Beech-Lab strain was used for comparison. Data were analyzed using Probit analysis to determine LC50 and LC90 values.Results: Susceptibility of An. stephensi to temephos indicated that the LC50 ranged from 0.0022 mg/l to 0.0141 mg/l. Although all field strains were susceptible to temephos, considerable variations in temephos resistance ratios of field strains were noticed from all the localities studied in comparison with the susceptible strain. A low level of resistance ratio was noticed in An. stephensi populations except for the Chabahar strain (RR= 4.27 fold). All field-collected An. stephensi populations exhibited homogeneity to the larvicide except for Bandar Abbas and Hormoodar village strains (P> 0.05%).Conclusion: Due to intensive use of temephos in the neighboring countries and occurrence of resistant to this insec­ticide in the main malaria vector in the region, insecticide resistance gene may evolve in the populations of An. stephensi. If temephos be applied as a larvicide it should be used judiciously for resistance management, as rotation strateg

Use of anti-viral therapies in hospitalised COVID-19 patients in the United Arab Emirates: a cost-effectiveness and health-care resource use analysis

Abstract Background This study attempts to estimate the cost-effectiveness of the antiviral remdesivir, as recommended in the 2021 COVID treatment guidelines for the United Arab Emirates, compared to standard of care (SOC), but also favipiravir (FAVI), which was also recommended for the treatment of hospitalized COVID patients. Methods A cost-effectiveness model was built using published efficacy data for RDV, FAVI and SOC as well as local epidemiology data. The outcomes measured included hospital bed days averted, mortality, costs and cost per outcome over one year. One-way, probabilistic and scenario analyses were undertaken to reflect uncertainty in the estimates. Results When modelled over one year, the results indicated that treatment of adults in need of supplemental oxygen with RDV + SOC could result in 11,338 fewer general ward bed days, 7,003 fewer ICU days and 5,451 fewer ICU + MIV bed days compared to SOC alone and similar results when compared with FAVI + SOC. The model results also showed that there were 374 fewer deaths associated with the use of RDV + SOC compared to SOC alone. The model also estimates substantial potential cost-savings associated with RDV + SOC treatment compared with SOC alone (USD 3,454 per patient). The results of the one-way sensitivity analysis showed that the model was sensitive to estimates of length of stay and the cost of hospitalization. Despite this, the model predicted cost-savings in all scenarios versus all comparators. Conclusions The model estimated that using RDV + SOC could result in substantial reductions in HCRU and cost savings regardless of the comparator. However, it should be noted that reliable clinical information on FAVI was limited therefore it is challenging to interpret these results. All the potential benefits modelled here for RDV + SOC can have implications not only for the health of the UAE population but for improving hospital capacity to deal with other conditions

McKittrick–Wheelock syndrome presenting with presumed paraneoplastic syndrome extra-ocular muscle enlargement masquerading as thyroid eye disease

Paraneoplastic syndromes (PS) are uncommon and are known to mimic other clinical entities, often carrying significant morbidity and mortality. The commonest cause of extra-ocular muscle enlargement (EOME) is thyroid eye disease (TED). Rarely, PS can cause EOME and masquerade as TED. We describe a 52-year-old female who presented with diarrhoea, acute kidney injury and electrolyte imbalance. An ophthalmic review identified right upper lid retraction. MRI orbits showed increased thickness of the inferior and medial recti bilaterally, presumed as TED. Whilst investigating her diarrhoea, imaging revealed a large rectosigmoid tumour which required surgical excision. In the context of electrolyte disturbance and acute kidney injury, a diagnosis of McKittrick–Wheelock syndrome (MWS) was made. Following successful surgery, electrolyte imbalance, diarrhoea and eyelid retraction improved. Repeat MRI orbits displayed complete resolution of EOME. To our knowledge, this is the first case of MWS presenting with PS-EOME masquerading as TED

Effect of Amniotic Membrane Combined with Ciprofloxacin in Curing the Primary Stages of Pseudomonal Keratitis

Background: Keratitis caused by Pseudomonas aeruginosa is often resulted in severe corneal ulcers and perforation, which leads to losses of vision. Human amniotic membrane (HAM) forms the inner wall of the membranous sac which surrounds and protects the embryo during gestation. The purpose of this study was to evaluate the effectiveness of the amniotic membrane's healing in rabbits with pseudomonas keratitis.Methods: In total 14 rabbits divided in 2 groups of: 1 as Control and 2 as experimental amniotic membrane combined with ciprofloxacin. A 0.05 ml suspension of Pseudomonas aeruginosa ATCC 27853 was injected into rabbit’s corneal stroma, with no interference in control group. In the second group, the amniotic membrane in pieces of 1.5 × 1.5 cm transplanted to the entire corneal surface by eight interrupted 10.0 nylon sutures. In the first day ciprofloxacin drop was injected to the second group every 30 minutes and through second to seventh days every 2 hours. The results of perforation in cornea and the amount of infiltration were registered.Results: The results showed that amniotic membrane transplantation (AMT) + ciprofloxacin group had 0% perforation and the control group 85.6%. Average infiltrations were 5 mm in AMT + ciprofloxacin groups and 23.75 mm in control.Conclusion: The use of amniotic membrane with ciprofloxacin was effective in prevention of cornea perforation and controlling the process of pseudomonal keratitis remission. The improvement of inflammation rapidly happened in ciprofloxacin + AMT group