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Abstract Drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome is a rising morbidity amongst hospitalized patients. Whilst clinical protocols for the management of individual DRESS cases have been well established, determination of potential prevention of these cases by utilizing novel “avoidability” tools has remained unexplored. This retrospective study reviewed records of patients who presented to the emergency department of Weill Cornell Medicine-affiliated Hamad General Hospital, Doha Qatar with suspected DRESS syndrome. These cases were independently adjudicated (utilizing the RegiSCAR, and JSCAR tools) as DRESS-drug pairs by a team of two clinical pharmacists and two General Physicians. They were then rated for potential avoidability with the Liverpool adverse drug reactions avoidability tool (LAAT) by the same team of raters. A total of 16 patients satisfied RegiSCAR criteria for DRESS syndrome. The mean age of the study population was 41.5 years (SD ± 13.3). The study population was predominantly male (n = 12; [75%]). The median latent period from drug ingestion to clinical presentation was 14 days (interquartile range [IQR] 6.5, 29). The median RegiSCAR and J-SCAR scores were 6 (IQR 5, 6.8), 5 (IQR 4, 5.8) respectively. Utilizing the LAAT, about 60% of the DRESS syndrome-drug pairs were rated as “avoidable” (“probable” or “definite”). The overall Krippendorf’s alpha with the LAAT was 0.81 (SE 0.10, CI 0.59–1.00); with an intraclass correlation coefficient (ICC) of 0.90 (CI 0.77, 0.96.). In a randomly selected cohort of DRESS syndrome-drug pairs, a significant proportion was potentially avoidable (“possibly” and “definitely”) utilizing the LAAT. This will need validation by larger sample-sized prospective studies utilizing the updated LAAT proposed by this study.

Introduction The benefits of antibiotics are under threat by self-medication, which culminated in economic burdening of developing countries, treatment failures, the emergence of antibiotic-resistant strains of bacteria and an increased probability of exposure and infection of the general population by antibiotic-resistant bacterial strains. Objectives This study aimed to evaluate the knowledge and attitude of medical students in Sudan towards the use of antibiotics, the prevalence of self-medication with antibiotics among medical students in Sudan and to identify risk factors which promote self-medication with antibiotics. Materials and methods This was a cross-sectional, descriptive and institution-based study, between November 2020 and May 2021. 1,110 medical students were selected by multistage cluster sampling. Logistic regression was used to identify risk factors of self-medication with antibiotics among the study participants. Results The median knowledge score was 7 out of a maximum of 10 (IQR: 5–8). A moderately positive attitude was observed among the participants (Median: 7/10; IQR: 6–8). Knowledge and attitude scores were significantly associated with academic year and monthly allowance (p < 0.05). 675 (60.8%) self-medicated with antibiotics within the previous 12 months, mostly from community pharmacies (321/675; 47.5%). Antibiotics were most commonly used to treat respiratory tract infections (38.1%) and cough (30.4%). Chi-square analysis demonstrated that self-medication with antibiotics was significantly associated with gender, year of study and monthly income. Conclusions Undergraduate medical students had moderate knowledge and attitude towards antibiotic use and antibiotic resistance, and an alarmingly high prevalence of self-medication with antibiotics. This highlights the urgent need for tighter legislation regarding the sales of antibiotics in community pharmacies by the state and federal health ministries.

Against the backdrop of global warming and increased rainfall, the hazards and potential risks of landslides are increasing. The rapid generation of a landslide inventory is of great significance for landslide disaster prevention and reduction. Deep learning has been widely applied in landslide identification due to its advantages in terms of its deeper model structure, high efficiency, and high accuracy. This article first provides an overview of deep learning technology and its basic principles, as well as the current status of landslide remote sensing databases. Then, classic landslide deep learning recognition models such as AlexNet, ResNet, YOLO, Mask R-CNN, U-Net, Transformer, EfficientNet, DeeplabV3+ and PSPNet were introduced, and the advantages and limitations of each model were extensively analyzed. Finally, the current constraints of deep learning in landslide identification were summarized, and the development direction of deep learning in landslide identification was analyzed. The purpose of this article is to promote the in-depth development of landslide identification research in order to provide academic references for the prevention and mitigation of landslide disasters and post-disaster rescue work. The research results indicate that deep learning methods have the characteristics of high efficiency and accuracy in automatic landslide recognition, and more attention should be paid to the development of emerging deep learning models in landslide recognition in the future. [ABSTRACT FROM AUTHOR]

The conventional methods of supplying feed to tilapia tanks are ineffective. It is better to find new a automatic feeder saving pellets from crushing and cohesion without hitting pellets during feeding at a predetermined interval of time and an accurate amount of food with a larger surface area covered by pellets. Developing-country fish farmers use manual feeding to be more cost-effective than with costly mechanized feeding, so this research aimed to design and construct an automatic fish feeder prototype to feed tilapia in a recirculation aquaculture system’s tank. The performance of the prototype was studied after it was designed and installed. The dispensed feed operated by a DC motor located underneath the pellet hopper and the feed material was discharged into the tank through a gate in the bottom of the feeder. Three pellet sizes, three rotation speeds, and three feeder heights from the water’s surface were used to test the automatic feeder’s efficiency. The results showed that the optimal speed for the automatic feeder was 14 rpm with a height of 70 cm, resulting in a distribution width of 26.6 cm and a high automatic feeder efficiency of 99.9%. Furthermore, the feeder used very little electricity and saved time, cost, labor, energy, and pellets.

Economic thought is defined as research, theory and economic troubleshooting methods for ideas and efforts from Islamic scholars based on the benefits and syara’. The flourish of the Islamic economic thought discussion began since the early period of Prophet Muhammad SAW because one of the aspects in the al-Quran and al-Sunnah is about economy. With the expansion of Islamic civilization, the discussion regarding economy was flourish as well, especially with the emergence of the fiqh scholars and the sects of fiqh. Fiqh scholars were one of the people who played vital roles in expressing ideas based on naqli and aqli propositions, in addition of arranging discussions in regard to economics. Conservative scholars in the Malay Archipelago such as Syeikh Daud al-Fatani had also played the same role in the Malay World. Thus, this study aims at analyzing the economic thought regarding the concept of gharar in one of his work (the text of Sullam al-Mubtadi) using content analysis method. The focus of the research is on the Mua’wadah contract.

A diversity of Devonian-Carboniferous volcanic arcs and granitoid intrusions are exposed in the Gurvansaykhan arc terrane of southern Mongolia. Several giant porphyry Cu-Au-Mo deposits are associated with intrusions within these arcs. The Bronze Fox deposit located in the central part of the Gurvansaykhan arc terrane is an example of a potentially economic deposit with affinity of adakite-like granitoid porphyry (i.e. 428 Mt grading 0.26% to 0.30% Cu for up to 2,437 Mlb of copper and 0.84 Moz gold). The genesis and magmatic evolution of the causative rocks of the Bronze Fox porphyry Cu-Au hosting rocks are poorly understood, and different models are still under debate. In the current study, we present new field observations and petrographic, geochemical, and geochronological data to describe the magmatic evolution and geodynamic settings. In addition, the mineral chemical data are reported from some selected rock-forming minerals to identify crystallization conditions of the studied rock suites by employing geothermobarometric methods. Zircon chronological data reveal the emplaced age at 331 ± 3.4 Ma for the volcanic lava, followed by mineralized granodiorite and monzodiorite with intruded ages of 326.5 ± 3.4 Ma and 326.5 ± 2.7 Ma, respectively. The studied intrusive and extrusive rocks are high-K-alkaline and metaluminous, characterized by high Mg#. They are enriched in large ion lithophile elements (Sr and Ba) and light rare earth elements (LREEs) and depleted in high field strength elements (Nb, Ta, and Ti) and heavy rare earth elements (HREEs). The highly mineralized granodiorite intrusion yields zircon crystallization temperatures ranging from 631.8 to 779.4°C, and the monzodiorite intrusion, which contains relatively low-grade mineralization, has a wider range (599.0 to 803.4°C). The formation pressures of the former range from 0.5 to 0.2 kbar, which is equivalent to a depth of 1.38 km based on amphibole geochemical calculations. The results of mineral chemistry indicate that the unmineralized diorite unit was formed under medium pressure (~50 MPa) and high temperature (~750°C) at depths of 6.8 to 7.5 km. Similarities in geochemistry and petrographic features suggest that the igneous rocks probably originated from a similar magma source (i.e. from the melting of ancient oceanic crust and sediments) but experienced different degrees of partial melting or mixing with lower juvenile crust melts. The estimated fO2 values obtained by amphibole chemistry in the granodiorite and quartz diorite of the Bronze Fox copper-gold mineralization range from −13.0 to −11.8 and −13.2 to −10.8, respectively, confirming that these igneous rocks probably crystallized under relatively oxidized conditions above the nickel-nickel oxide (NNO) buffer. Such results yield an overall range between NNO +2.6 and NNO +1.4, which are characterized by high oxygen fugacities and high Ce4+/Ce3+ ratios that reflect oxidizing magma, thus indicating quite promising potential for porphyry Cu-Au mineralization in the region. Based on the findings of this work, we suggest a new tectonic model of arc magmatism that is a response to the subduction of the Paleo-Asian Ocean in the early Carboniferous period. [ABSTRACT FROM AUTHOR]