Purpose There have been several studies into medical student career decision making in occidental countries (eg US, UK), but medical career selection in a Middle Eastern context has not been as well studied. This study aims to explore determinants underpinning medical students’ residency choice in Qatar. Patients and methods During the Fall semester of the 2022–2023 academic year, all (n=358) medical students from the College of Medicine at Qatar University were invited to participate in an online explorative questionnaire about students’ career choices and the factors determining their selection. Results Of the 358 students, 184 responded (51%). Respondents had a mean age of 20 years; the majority were female (73.9%), Qatari (54.3%), unmarried (97.3%), and enrolled in a pre-clerkship year (55.0%). The most important career determinant was specialty-specific factors. The relative importance of other determinants differed by gender and stage of training. Among our respondents, male students were more likely to rate role models and influencers as being important to their choice, while female students and Qatari students overall were more likely to cite societal obligation. Medical students in Qatar seemed to have career preferences in mind upon entry into medical education. Later-year students were more likely to identify the importance of work-life balance and place of practice, but were less likely to rank prestige and income as an important determinant. Conclusion The results of this baseline study suggest that socioeconomic and cultural context influence medical student career decisions.

Uterine leiomyosarcoma (uLMS) is a rare but aggressive cancer with a high metastatic potential and an unfavorable prognosis. A 54-year-old woman with a history of uterine fibroids clinically presented with a painless, palpable left breast mass measuring 20 mm. A core biopsy of the breast mass demonstrated a cellular spindle cell neoplasm (a potentially malignant smooth muscle neoplasm; B4). A wide local breast-mass excision was performed, revealing grade-2 leiomyosarcoma. A re-review of the uterine fibroids revealed that the largest one (200 × 130 mm), initially diagnosed as symplastic leiomyoma, was morphologically identical to the breast lesion. Additional diagnostic work-up revealed multiple liver and pulmonary metastases with a suspected metastatic sclerotic lesion in the L3 projection. The patient was subsequently treated with chemotherapy protocol for metastatic uLMS. The latest follow-up in September 2023 confirmed stable disease. This case highlights the importance of considering unusual metastatic patterns when evaluating breast masses, particularly in patients with a history of non-specific uterine conditions. Comprehensive diagnostic work-up, including imaging and histopathologic examinations, is crucial for an accurate diagnosis of uLMS and appropriate treatment selection. Further studies are needed to better understand the underlying mechanisms and optimal management strategies for metastatic uLMS.

We report on the development of a novel pixel charge readout system, Grid Activated Multi-scale pixel readout (GAMPix), which is under development for use in the GammaTPC gamma ray instrument concept. GammaTPC is being developed to optimize the use of liquid argon time projection chamber technology for gamma ray astrophysics, for which a fine grained low power charge readout is essential. GAMPix uses a new architecture with coarse and fine scale instrumented electrodes to solve the twin problems of loss of measured charge after diffusion, and high readout power. Fundamentally, it enables low noise and ultra low power charge readout at the spatial scale limited by diffusion in a time projection chamber, and has other possibly applications, including future DUNE modules.

The Sustainable Development Goals (SDGs) of the United Nations provide a blueprint of a better future by 'leaving no one behind', and, to achieve the SDGs by 2030, poor countries require immense volumes of development aid. In this paper, we develop a causal machine learning framework for predicting heterogeneous treatment effects of aid disbursements to inform effective aid allocation. Specifically, our framework comprises three components: (i) a balancing autoencoder that uses representation learning to embed high-dimensional country characteristics while addressing treatment selection bias; (ii) a counterfactual generator to compute counterfactual outcomes for varying aid volumes to address small sample-size settings; and (iii) an inference model that is used to predict heterogeneous treatment-response curves. We demonstrate the effectiveness of our framework using data with official development aid earmarked to end HIV/AIDS in 105 countries, amounting to more than USD 5.2 billion. For this, we first show that our framework successfully computes heterogeneous treatment-response curves using semi-synthetic data. Then, we demonstrate our framework using real-world HIV data. Our framework points to large opportunities for a more effective aid allocation, suggesting that the total number of new HIV infections could be reduced by up to 3.3% (~50,000 cases) compared to the current allocation practice.

We assess proton decay signatures in the simplest viable $SU(5)$ model with regard to constraints on parameters governing the Standard Model fermion mass spectrum. Experimental signals for all eight two-body proton decay processes result from exchange of two gauge bosons, a single scalar leptoquark, or their combination. Consequently, it enables us to delve into an in-depth anatomy of proton decay modes and anticipate future signatures. Our findings dictate that observing a proton decay into $p\to\pi^0e^+$ indicates gauge boson mediation, with the potential for observation of $p\to\eta^0e^+$ mode. Alternatively, if decay is through $p\to K^+\overline\nu$ process, it is mediated by a scalar leptoquark, possibly allowing the observation of $p\to\pi^0\mu^+$. Detection of both $p\to\pi^0 e^+$ and $p\to K^+\overline\nu$ could enhance $p\to\pi^0\mu^+$ through constructive interference. The model predicts inaccessibility of $p\to\pi^+\overline\nu$, $p\to\eta^0\mu^+$, $p\to K^0e^+$, and $p\to K^0\mu^+$, regardless of the dominant mediation type, in the coming decades. In summary, through a comprehensive analysis of proton decay signals, gauge coupling unification, and fermion masses and mixing, we precisely constrain the parameter space of the $SU(5)$ model in question.

Frontal polymerization (FP) is a self-sustaining curing process that enables rapid and energy-efficient manufacturing of thermoset polymers and composites. Computational methods conventionally used to simulate the FP process are time-consuming, and repeating simulations are required for sensitivity analysis, uncertainty quantification, or optimization of the manufacturing process. In this work, we develop an adaptive surrogate deep-learning model for FP of dicyclopentadiene (DCPD), which predicts the evolution of temperature and degree of cure orders of magnitude faster than the finite-element method (FEM). The adaptive algorithm provides a strategy to select training samples efficiently and save computational costs by reducing the redundancy of FEM-based training samples. The adaptive algorithm calculates the residual error of the FP governing equations using automatic differentiation of the deep neural network. A probability density function expressed in terms of the residual error is used to select training samples from the Sobol sequence space. The temperature and degree of cure evolution of each training sample are obtained by a 2D FEM simulation. The adaptive method is more efficient and has a better prediction accuracy than the random sampling method. With the well-trained surrogate neural network, the FP characteristics (front speed, shape, and temperature) can be extracted quickly from the predicted temperature and degree-of-cure fields.

Background: Difficult cholecystectomy, often associated with a heightened risk of complications, poses a significant surgical dilemma. Risk factors, such as patient age, increased body weight, the presence of gallstones, acute cholecystitis, and prior abdominal surgeries, can complicate laparoscopic cholecystectomy and necessitate conver- sion to an open procedure for safety. The aim of our study was to assess the applicability of the Nassar scale in predicting the need for conversion from laparoscopic to open cholecystectomy.Material and methods: In our prospective cohort study, we included 85 patients who underwent either emergency or elective laparoscopic cholecystectomy between December 2021 and October 2023. The Nassar scale was used to assess the complexity of laparoscopic cholecystectomy, incorporating parameters such as ‘Gallbladder,’ ‘Cystic pedicle,’and ‘Adhesions’ to determine a final score ranging from 1 to 5. Statistical analysis involved descriptive and analytical methods, with the significance threshold set at p < 0.05.Results: ANOVA analysis revealed a statistically significant difference in the duration of operative procedures with different Nassar grades (p < 0.001). An increase in the Nassar grade by 1 was associated with a statistically significant6.23-fold increase in the odds of conversion to an open procedure (p < 0.001). Receiver Operating Characteristic (ROC) analysis demonstrated a highly significant association (p < 0.001) between the Nassar grade and the conversion event, with an Area Under the Curve (AUC) of 0.881 (95% CI 0.79,0.96). The optimal cutoff value, identified as >2.5, struck a balance between sensitivity (0.86) and 1-specificity (0.23). Conclusion: Our study underscores the utility of the Nassar scale in surgical practice. It provides valuable insights into assessing the severity of operations, facilitating informed decision-making, and optimizing treatment outcomes for patients undergoing laparoscopic cholecystectomy at our institution.

Abstract. Agricultural headwater streams are important pathways for diffuse sediment and nutrient losses, requiring mitigation strategies beyond in-field measures to intercept the transport of pollutants to downstream freshwater resources. As such, floodplains can be constructed along existing agricultural streams and ditches to improve fluvial stability and promote deposition of sediments and particulate phosphorus. In this study, we evaluated 10 remediated agricultural streams in Sweden for their capacity to reduce sediment and particulate phosphorus export and investigated the interplay between fluvial processes and phosphorus dynamics. Remediated streams with different floodplain designs (either on one side or both sides of the channel, with different width and elevation) were paired with upstream trapezoidal channels as controls. We used sedimentation plates to determine seasonal patterns in sediment deposition on channel beds and floodplains and monthly water quality monitoring. This was combined with continuous flow discharge measurements to examine suspended sediment and particulate phosphorus dynamics and reduction along reaches. Remediated streams with floodplains on both sides of the channel reduced particulate phosphorus concentrations and loads (−54 µg L−1, −0.21 kg ha−1 yr−1) along reaches, whereas increases occurred along streams with one-sided floodplains (27 µg L−1, 0.09 kg ha−1 yr−1) and control streams (46.6 µg L−1). Sediment deposition in remediated streams was five times higher on channel beds than on floodplains and there was no evident lateral distribution of sediments from channel to floodplains. There was no effect from sediment deposition on particulate phosphorus reduction, suggesting that bank stabilization was the key determinant for phosphorus mitigation in remediated streams, which can be realized with two-sided but not one-sided floodplains. Further, the overall narrow floodplain widths likely restricted reach-scale sediment deposition and its impact on P reductions. To fully understand remediated streams' potential for reductions in both nitrogen and different phosphorus species and to avoid pollution swapping effects, there is a need to further investigate how floodplain design can be optimized to achieve a holistic solution towards improved stream water quality.

Accurate identification of the QRS complex is critical to analyse heart rate variability (HRV), which is linked to various adverse outcomes in premature infants. Reliable and accurate extraction of HRV characteristics at a large scale in the neonatal context remains a challenge. In this paper, we investigate the capabilities of 15 state-of-the-art QRS complex detection implementations using two real-world preterm neonatal datasets. As an attempt to improve the accuracy and reliability, we introduce a weighted ensemble-based method as an alternative. Obtained results indicate the superiority of the proposed method over the state of the art on both datasets with an F1-score of 0.966 (95% CI 0.962-0.97) and 0.893 (95% CI 0.892-0.894). This motivates the deployment of ensemble-based methods for any HRV-based analysis to ensure robust and accurate QRS complex detection.

Women were more affected than men during the COVID-19 pandemic. This study aimed to investigate COVID-19-related stress response in adult women and its association with the relevant socioeconomic, lifestyle and COVID-19-related factors. This research was carried out in eight randomly chosen cities from September 2020 to October 2021. To examine stress, we distributed the COVID Stress Scales (CSS) and the Perceived Stress Scale (PSS). Women also fulfilled a general socio-epidemiologic questionnaire. The study included 1,264 women. Most women were healthy, highly educated, employed, married, nonsmokers who consumed alcohol. The average total CSS score suggested a relatively low COVID-19 related stress), while 1.7% of women had CSS ≥ 100. The mean PSS was around the mid-point value of the scale. Older women, who were not in a relationship, didn't smoke, didn't drink alcohol, but used immune boosters, had chronic illnesses and reported losing money during the pandemic had higher CSS scores. A higher level of stress was also experienced by women exposed to the intense reporting about COVID-19, had contact with COVID-19 positive people or took care of COVID-19 positive family members. In this sample of predominantly highly educated women few women experienced very high stress level, probably due to the study timing (after the initial wave) when the pandemic saw attenuated stress levels. To relieve women from stress, structural organization and planning in terms of health care delivery, offsetting economic losses, controlled information dissemination and psychological support for women are needed.

ABSTRACT The paper deals with the population decline in Balkan countries in the last three decades, since 1990. It researches the scale of depopulation in the Balkans and analyses the causes and possible consequences of the population decline. It argues that the failure of imposed neoliberal economic policies in the Balkan countries in the 1990s caused deindustrialization, GDP stagnation and high unemployment rates, especially of young people. Together with the shift in values from traditional to neo-liberal ones which promote materialism, hedonism, consumerism and liberal middle-class feminism, it caused dramatic reduction in fertility (live births per woman) as well as a significant brain drain and economic emigration from the Balkan countries in the last 30 years. Depopulation is becoming a limiting factor for sustainability of Balkan societies. It imposes a long-term danger for demographic survival of these societies, and generates an array of other negative economic, social and political consequences.

BACKGROUND Computational research plays an important role in predicting the chemical and physical properties of biologically active compounds important in future structural modifications to improve or modify biological activity. OBJECTIVE This research focuses on quantum chemical and spectroscopic investigations properties of synthesized 4-hydroxycoumarin derivatives. METHODS Quantum chemical calculations were obtained using B3LYP, HF, and M06-2x level methods with the 6-31++G (d,p) basis set. Afterward, IR, 1H, 13C, UV-Visible experimentally parameters were compared with the results obtained using the B3LYP/6-31+G*(d) basis set of the molecules to be able to characterize the structures. RESULTS Based on the quantum chemical calculations compound with acetamido group on the phenyl ring is the most reactive, and compound with nitro substituent is the least reactive and the the strongest electrophile among tested compounds. With the exception of compounds with dimethylamino group, all other compounds have a pronounced tautomer between between OH and C = O group. The calculated and experimental values are in agreement with each other. CONCLUSION The molecular structure in the ground state of six 3-cinnamoyl 4-hydroxycoumarin derivatives was optimized using density functional theory. The observed and computed values were compared and it can be concluded that the theoretical results were in good linear agreement with the experimental data.

ABSTRACT The purpose of this article is to analyse the state and the dynamics of developmental and other aspects of investments in research and development (R&D) in the group of countries in Southeast Europe. The analysis is performed for several countries in Southeast Europe together and by individual countries. The period from 1996 to 2020 is observed in the analysis. In most countries of Southeast Europe, the allocation for R&D is relatively small. Applied research is the most represented. Significant differences can be noticed regarding the sources of financing and to the implementation of allocations for R&D. A particularly important part of this work is devoted to the analysis of the impact of the gross expenditures on R&D on economic growth. This analysis was performed on the basis of regression analysis. Several regression models were formed in which the dependent variable was gross domestic product per capita It can be concluded that the parameters of the financial condition of the observed economy have the greatest influence on the economic growth of the observed group of countries. Allocations for research and development still do not have a significant enough impact on economic growth in observed countries in Southeast Europe.