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.

Pored oblika i ukrasa, natpisi predstavljaju najkarakterističniji i najznačajniji faktor naučne i umjetničke vrijednosti stećaka. Kada je poznato vrijeme nastanka natpisa, onda istraživači imaju bolja polazišta za svestranije proučavanje stećaka. Prije svega, datacija natpisa značajno pomaže u praćenju razvoja jezika i pisma. Svaki datirani stećak predstavlja značajnu i stabilnu stepenicu na slabije poznatom putu u razvoju srednjovjekovnog pisma. Na ovom mjestu dajemo prilog dataciji natpisa na stećku Vukašina Dobrašinovića iz Vrsinja u naselju Konjsko u blizini Trebinja. Ranije ponude datiranja ukazuju na odstupanjameđu vrsnim epigrafičarima i prave dodatne nejasnoće na polju epigrafike. Novim arhivskim pokazateljima historijat Dobrašinovića iz Vrsinja dobija svoje konture. Egzaktno utvrđena životnost Vukašina Dobrašinovića (1421-1428) je relevantna polazna osnova za datiranje natpisa na njegovom nadgrobnom spomeniku pa time i jasnija osnova za daljnje proučavanje jezika i pisma. 

U antičko doba bile su prisutne predstave zmija u mnogim mitovima i kultovima. Zmija je često bila simbol života i smrti. Kao kultna životinja javlja se u Mitraizmu, a kao simbol zla javlja se u hrišćanskoj tradiciji. Na području velikog rudarskog nalazišta Japra pronađena su dva ulomka keramike sa predstavama zmija koje su bile omotane oko drške. Prema analogijom sa sličnim slučajevima može se reći da su ove posude povezane sa kultom Mitre i korišteni u vjerske svrhe.  

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.

Introduction: Covert brain infarcts (CBI) are frequent incidental findings on MRI and associated with future stroke risk in patients without a history of clinically evident cerebrovascular events. However, the prognostic value of CBI in first-ever ischemic stroke patients is unclear and previous studies did not report on different etiological stroke subtypes. We aimed to test CBI phenotypes and their association with stroke recurrence in first-ever ischemic stroke patients according to stroke etiology. Patients and methods: This study is a pooled data analysis of two prospectively collected cohorts of consecutive first-ever ischemic stroke patients admitted to the comprehensive stroke centers of Bern (Switzerland) and Graz (Austria). CBI phenotypes were identified on brain MRI within 72 h after admission. All patients underwent a routine follow-up (median: 12 months) to identify stroke recurrence. Results: Of 1577 consecutive ischemic stroke patients (median age: 71 years), 691 patients showed CBI on brain MRI (44%) and 88 patients had a recurrent ischemic stroke (6%). Baseline CBI were associated with stroke recurrence in multivariable analysis (HR 1.9, 95% CI 1.1–3.3). CBI phenotypes with the highest risk for stroke recurrence were cavitatory CBI in small vessel disease (SVD)-related stroke (HR 7.1, 95% CI 1.6–12.6) and cortical CBI in patients with atrial fibrillation (HR 3.0, 95% CI 1.1–8.1). Discussion and conclusion: This study reports a ≈ 2-fold increased risk for stroke recurrence in first-ever ischemic stroke patients with CBI. The risk of recurrent stroke was highest in patients with cavitatory CBI in SVD-related stroke and cortical CBI in patients with atrial fibrillation. Subject terms: Covert brain infarcts, stroke Graphical abstract

Ljubomir Maksimović: Vizantijski svet i Srbi, Beograd: Istorijski institut, 2008,Studia historica collecta, knjiga 6, 535 str. (Dženan Dautović)   Spomenica akademika Marka Šunjića (1927-1998), ur. Dubravko Lovrenović,Filozofski fakultet u Sarajevu, Sarajevo 2010, 366 str. (Nedim Rabić)

In the past years the interest in Solute Carrier Transporters (SLC) has increased due to their potential as drug targets. At the same time, macrocycles demonstrated promising activities as therapeutic agents. However, the overall macrocycle/SLC‐transporter interaction landscape has not been fully revealed yet. In this study, we present a statistical analysis of macrocycles with measured activity against SLC‐transporter. Using a data mining pipeline based on KNIME retrieved in total 825 bioactivity data points of macrocycles interacting with SLC‐transporter. For further analysis of the SLC inhibitor profiles we developed an interactive KNIME workflow as well as an interactive map of the chemical space coverage utilizing parametric t‐SNE models. The parametric t‐SNE models provide a good discrimination ability among several corresponding SLC subfamilies’ targets. The KNIME workflow, the dataset, and the visualization tool are freely available to the community.

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.

Abstract 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 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.

Glioblastoma multiforme (GBM) is a highly invasive brain malignancy originating from astrocytes, accounting for approximately 30% of central nervous system malignancies. Despite advancements in therapeutic strategies including surgery, chemotherapy, and radiopharmaceutical drugs, the prognosis for GBM patients remains dismal. The aggressive nature of GBM necessitates the identification of molecular targets and the exploration of effective treatments to inhibit its proliferation. The Notch signaling pathway, which plays a critical role in cellular homeostasis, becomes deregulated in GBM, leading to increased expression of pathway target genes such as MYC, Hes1, and Hey1, thereby promoting cellular proliferation and differentiation. Recent research has highlighted the regulatory role of non-coding RNAs (ncRNAs) in modulating Notch signaling by targeting critical mRNA expression at the post-transcriptional or transcriptional levels. Specifically, various types of ncRNAs, including long non-coding RNAs (lncRNAs) and microRNAs (miRNAs), have been shown to control multiple target genes and significantly contribute to the carcinogenesis of GBM. Furthermore, these ncRNAs hold promise as prognostic and predictive markers for GBM. This review aims to summarize the latest studies investigating the regulatory effects of ncRNAs on the Notch signaling pathway in GBM.