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Career indecision is a broad term that refers to the uncertainty and difficulty of decision-making regarding future careers among junior professionals. This study aims primarily to estimate the prevalence of career indecisiveness among senior medical students and medical interns in Oman. Secondly, it assesses the association of sociodemographic factors influencing it. Finally, it examines the association between participation in career development activities and career indecision among them during the academic year of 2022-2023. A cross-sectional study was conducted using an anonymous self-administered questionnaire in the English language. Unpaired t-test and ANOVA test were used to compare means between groups. A 21-item Career Factors Inventory (CFI) was used to determine the career indecision score. These scores were further classified as low-level (score 27-71) and high-level (score 72-105).  Results: The total number of participants was 161. The minimum sample size calculated was 153 participants for 95% confidence intervals. The prevalence of high-level career indecision was 63.4% (95%CI 55.4%-70.8%) among the participants. Participants with one of their parents in healthcare professions and those who did not participate in career development activities had high career indecision scores with P-values of 0.002 and 0.022, respectively. Moreover, participants younger than 25 years of age in comparison to older participants had higher need-for-self-knowledge (NSK) scores (p-value 0.018). A high prevalence of high-level career indecision was seen among senior medical students and medical interns in Oman. Few factors were found to be statistically associated with career indecision, especially participation in career development activities. Further studies are recommended to investigate the causality of high-level career indecision among junior professionals in Oman and the contributing factors. Curricular and extra-curricular career development activities and counseling may reduce career indecision.

Translation, in modern Oman, serves as an essential means of communication between the Arabic speaking Omanis and other individuals of smaller linguistic and ethnic communities working or residing in the country. The purpose of translation in such situations is to empower linguistically disempowered individuals within Oman and ensure that they are adequately informed and that they actively participate in the country's development. Yet, there have been very few studies that deal specifically with community translation in Oman and in the wider Arab world. The lack of a translation governing body and Omani translation scholars' tendency to focus on literary and technical translation in Oman are some of the factors that have kept community translation very much on the margins of translation. The aim of this contribution, therefore, is to address some of the issues pertaining to community translation in the Sultanate of Oman. In particular, it focuses on the long-standing relationship between translation and communication within Oman and how translation plays a pivotal role in the development of the country, given the fact that Oman, like other countries in the Arabian Peninsula, relies to a great extent on skilled expatriate workforce in various fields. In particular, this contribution investigates the role community translation has played in the fight against COVID-19 in the Sultanate of Oman. The effects of this pandemic are serious particularly in a country where around 40% of its population comes from different parts of the world and the majority of whom do not speak Arabic, the official language of the country, nor do they speak or read English, the language of business in Oman. During such times, community translation becomes crucial

BackgroundIn May 2024, the FDA approved tarlatamab, a Delta-like ligand (DLL3)/CD3-targeted bispecific T-cell engager, for patients with extensive-stage small cell lung cancer (SCLC) with disease progression following platinum-based chemotherapy and at least one other prior line of therapy. We aim to examine the cellular immune cell profile changes seen in patients receiving this therapy in standard-of-care (SOC) practice.MethodsPatients who received tarlatamab at Mayo Clinic Rochester consented to research blood. Immune phenotyping was performed on whole blood by flow cytometry and analyzed by Kaluza. Data analysis was performed with Excel and PRISM.ResultsThirteen patients with a median age 64 years (range 41-80) who were treated and evaluable for clinical response were included, 53% were women. All had a history of tobacco use.Nine (69%) patients had progressive disease (PD) after a median of 2 cycles, whereas 4 patients had partial response (PR) or stable disease (SD) after at least 2 cycles and remain on therapy (no-PD). Compared to the no-PD group, those whose disease PD early had higher levels of exhausted CD8 T cells at baseline (PD1+TIGIT+CD57+, PD vs no-PD, cells/µL: 17.4±5.6, 7.6±2.6, p=0.006). Interestingly, a CD8 TIGIT+PD1negCD57neg population was also identified which was higher at baseline (PD vs no-PD, cells/µL: 21.5±16.9, 12.2±5.33, p=0.039) and decreased significantly for the PD group from baseline to day 7 (21.5±16.9 to 9.30±10, p=0.039; figure 1A). This population was found to have a different functional profile than the exhausted phenotype in other solid tumors and its role in small cell lung cancer has not been defined. At day 7, compared to the no-PD group, the PD group also had a high level of B-cells (PD vs no-PD, cells/µL: 10.3±15, 4.07±1.83, p=0.027), classical monocytes (PD vs no-PD, cells/µL: 365±279, 226±121, p=0.035), and immunosuppressive monocytes (CD14+HLA-DRneg monocytes, cells/µL: 119±93, 33±42, p=0.05). In addition, the no-PD group had a statistically significant decrease from baseline to day 7 in intermediate monocytes (32.5±7.9 to 17±2.6, p=0.049; figure 1B).ConclusionsIn this study investigating the SOC outcomes of tarlatamab, early PD was associated with higher presence of exhausted CD8 T cells, B cells, and immunosuppressive monocytes. Analysis of additional patients will be shared at SITC meeting.Abstract 844 Figure 1ACD8 T cell phenotype associated with clinical response[Image Omitted. See PDF.]Abstract 844 Figure 1BMonocyte phenotype associated with clinical response[Image Omitted. See PDF.]

An amendment to this paper has been published and can be accessed via a link at the top of the paper.An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Audio is one of the most used ways of human communication, but at the same time it can be easily misused to trick people. With the revolution of AI, the related technologies are now accessible to almost everyone, thus making it simple for the criminals to commit crimes and forgeries. In this work, we introduce a neural network method to develop a classifier that will blindly classify an input audio as real or mimicked; the word ‘blindly’ refers to the ability to detect mimicked audio without references or real sources. We propose a deep neural network following a sequential model that comprises three hidden layers, with alternating dense and drop out layers. The proposed model was trained on a set of 26 important features extracted from a large dataset of audios to get a classifier that was tested on the same set of features from different audios. The data was extracted from two raw datasets, especially composed for this work; an all English dataset and a mixed dataset (Arabic plus English). For the purpose of comparison, the audios were also classified through human inspection with the subjects being the native speakers. The ensued results were interesting and exhibited formidable accuracy, as we were able to get at least 94% correct classification of the test cases, as against the 85% accuracy in the case of human observers.Article HighlightsA neural network method for blindly classifying audio inputs as genuine or mimicked, without prior references or information.Deals a scenario wherein exactly only one speech sample, either fake or real but not both, of the purported speaker is available.On datasets composed of both English and its combination with Arabic speech samples, the method achieves a remarkable accuracy of at least 94% in differentiating between real and spoofed voices, surpassing human observer accuracy of 85%.

Motor neuron syndromes including typical ALS develop very rarely after electrotrauma, with possible causality discussed but not confirmed. We report on a 44-year-old male who developed clinically definite ALS by the revised El Escorial criteria with onset weeks after mild electric injury. He presented with asymmetric upper limb amyotrophy and weakness beginning around the entry point of the current. Over 1 year he developed generalized wasting, weakness and fasciculations, including the bulbar and thoracic muscles, with prominent spasticity and pyramidal tract signs. Electrodiagnostic studies confirmed widespread denervation, very unstable neurogenic motor units in the bulbar, cervical, thoracic and lumbosacral segments with normal motor velocities and normal sensory parameters. This is a well-documented case of fast-progressive ALS that seems related to electric injury.

Kuwait’s per capita electrical energy consumption is among the largest in the world, reaching 13,663 kWh per person in 2011. The electricity demand in Kuwait is increasing, which requires additional investments in power generation. A particular challenge in Kuwait is the peak demand in summer, when extreme heat increases air conditioning loads. Peak demand reached 11,220 MW in 2011, with a fast growth rate averaging 5.6% over the last decade and a maximum production capacity of around 14,720 MW. It is not possible to cope with this demand simply by increasing generation capacity. Therefore, the only alternative available to Kuwait is to control electricity demand via demand-side management. The main objective of this research is to assess and select the optimal demand- side management (DSM) technologies for buildings in the governmental sector (office, religious and school buildings) and to investigate the key factors in the evaluation process. To achieve the research objective, a model was proposed using multi-criteria decision-making techniques to enable the forecasting and comparison of DSM alternatives that are suitable for buildings. The developed model includes environmental, economic, technical and social considerations. The research methodology is based on three main phases. Phase 1: Data collection through a mail questionnaire that was sent to 42 experts for the identification of criteria and demand-side management alternatives. Phase 2: Screening and narrowing of the data collected in Phase 1 using a set of questionnaires, including the identification of potential DSM alternatives and criteria suitable for further analysis. This phase was performed through the Delphi process, taking into consideration the opinions of 28 experts. Phase 3: Use of Multi-criteria Decision Making (MCDM) techniques, namely the Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process (FAHP), to evaluate and rank the identified DSM alternatives and criteria. This was done using pairwise comparisons of 17 experts to evaluate the criteria and alternatives for the buildings (office, religious and school). The research showed that the experts identified six alternative technologies and five criteria for the selection and evaluation of governmental buildings (office, religious and school). After performing the three phases of this research project, a set of criteria and alternatives were ranked based on the information gathered from every group of experts. It was found that reduction in consumption, capital cost and ease of implementation were the three most recommended criteria for the selection of DSM technologies in Kuwait government buildings while high efficiency lighting and programmable thermostats were identified as the most recommended DSM technologies for these buildings. An important aspect of this research is that unlike engineering approaches which sometimes depend on expensive test equipment or, often for building design, expensive computer modelling exercises, the proposed framework can be easily adopted by anyone without any significant financial cost. The FAHP approach was also tested and its results compared with those of AHP. There was a slight difference between using AHP and FAHP in terms of ranking the criteria and alternatives but that the difference barely affects the ranking. It was found that the AHP provides a convenient MCDM approach for solving the complex problem of selecting the optimal DSM options for buildings. The contributions of this thesis are the development of a novel framework for systematic selection and ranking of DSM technologies in different types of buildings using the Delphi method and AHP; the identification of the most important DSM technologies and criteria for their selection for three types of governmental buildings in Kuwait; and establishing that results from using AHP and FAHP for the selection of appropriate DSM measures in these buildings are almost identical, so use of AHP is likely to be sufficient in most building studies of this type.

Kuwait’s per capita electrical energy consumption is among the largest in the world, reaching 13,663 kWh per person in 2011. The electricity demand in Kuwait is increasing, which requires additional investments in power generation. A particular challenge in Kuwait is the peak demand in summer, when extreme heat increases air conditioning loads. Peak demand reached 11,220 MW in 2011, with a fast growth rate averaging 5.6% over the last decade and a maximum production capacity of around 14,720 MW. It is not possible to cope with this demand simply by increasing generation capacity. Therefore, the only alternative available to Kuwait is to control electricity demand via demand-side management. The main objective of this research is to assess and select the optimal demand- side management (DSM) technologies for buildings in the governmental sector (office, religious and school buildings) and to investigate the key factors in the evaluation process. To achieve the research objective, a model was proposed using multi-criteria decision-making techniques to enable the forecasting and comparison of DSM alternatives that are suitable for buildings. The developed model includes environmental, economic, technical and social considerations. The research methodology is based on three main phases. Phase 1: Data collection through a mail questionnaire that was sent to 42 experts for the identification of criteria and demand-side management alternatives. Phase 2: Screening and narrowing of the data collected in Phase 1 using a set of questionnaires, including the identification of potential DSM alternatives and criteria suitable for further analysis. This phase was performed through the Delphi process, taking into consideration the opinions of 28 experts. Phase 3: Use of Multi-criteria Decision Making (MCDM) techniques, namely the Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process (FAHP), to evaluate and rank the identified DSM alternatives and criteria. This was done using pairwise comparisons of 17 experts to evaluate the criteria and alternatives for the buildings (office, religious and school). The research showed that the experts identified six alternative technologies and five criteria for the selection and evaluation of governmental buildings (office, religious and school). After performing the three phases of this research project, a set of criteria and alternatives were ranked based on the information gathered from every group of experts. It was found that reduction in consumption, capital cost and ease of implementation were the three most recommended criteria for the selection of DSM technologies in Kuwait government buildings while high efficiency lighting and programmable thermostats were identified as the most recommended DSM technologies for these buildings. An important aspect of this research is that unlike engineering approaches which sometimes depend on expensive test equipment or, often for building design, expensive computer modelling exercises, the proposed framework can be easily adopted by anyone without any significant financial cost. The FAHP approach was also tested and its results compared with those of AHP. There was a slight difference between using AHP and FAHP in terms of ranking the criteria and alternatives but that the difference barely affects the ranking. It was found that the AHP provides a convenient MCDM approach for solving the complex problem of selecting the optimal DSM options for buildings. The contributions of this thesis are the development of a novel framework for systematic selection and ranking of DSM technologies in different types of buildings using the Delphi method and AHP; the identification of the most important DSM technologies and criteria for their selection for three types of governmental buildings in Kuwait; and establishing that results from using AHP and FAHP for the selection of appropriate DSM measures in these buildings are almost identical, so use of AHP is likely to be sufficient in most building studies of this type.