CORPORATE INCOME TAX BURDEN FOR SMES - THE CASE OF BOSNIA AND HERZEGOVINA

Small and medium entreprises (SMEs) play a significant role in economic development of both advanced and developing countries. Some earlier research showed that taxation and compliance costs have a significant effect on economic growth, development and performance of the business sector. For this reason, our research focuses on tax compliance costs imposed on the SMEs in Bosnia and Herzegovina (B&H), which is a transition and post-conflict country with a complex tax system structure. This complexity is particularly highlighted in the direct taxation system, hence the focus of this research is on corporate income tax (CIT) compliance costs. Our methodology is based on simulation of tax complience costs between different entities in BiH – Federation of B&H (FB&H) and the Republika Srpska (RS). Our simulation of the CIT return of a company „X“ in line with the entity law suggests that the effective tax burden is higher in RS than in FB&H entity. This result has an important policy implication for the fiscal authorities in B&H, as very often public discourse goes in the oposite direction to our finding

Differentiating Radiation Necrosis and Metastatic Progression in Brain Tumors Using Radiomics and Machine Learning

Objectives: Distinguishing between radiation necrosis(RN) and metastatic progression is extremely challenging due to their similarity in conventional imaging. This is crucial from a therapeutic point of view as this determines the outcome of the treatment. This study aims to establish an automated technique to differentiate RN from brain metastasis progression using radiomics with machine learning. Methods: 86 patients with brain metastasis after they underwent stereotactic radiosurgery as primary treatment were selected. Discrete wavelets transform, Laplacian-of-Gaussian, Gradient, and Square were applied to magnetic resonance post-contrast T1-weighted images to extract radiomics features. After feature selection, dataset was randomly split into train/test (80%/20%) datasets. Random forest classification(RFC), logistic regression, and support vector classification(SVC) were trained and subsequently validated using test set. The classification performance was measured by area under the curve(AUC) value of receiver operating characteristic curve, accuracy, sensitivity, and specificity. Results: The best performance was achieved using RFC with a Gradient filter (AUC=0.910, std=0.047), (accuracy 0.8, std=0.071), (sensitivity=0.796 std=0.055), (specificity =0.922, std=0.059). For SVC the best result obtains using wavelet_HHH with a high AUC of 0.890 with std=0.89, accuracy of 0.777 with std=0.062, sensitivity=0.701, std=0.084, and specificity=0.85 with std=0.112. Logistic regression using wavelet_HHH provides a poor result with AUC=0.882 & std=0.051, accuracy of 0.753 & std=0.08, sensitivity=0.717 & std=0.208, and specificity=0.816 with std=0.123. Conclusion: This type of machine-learning approach can help accurately distinguish RN from recurrence in magnetic resonance imaging, without the need for biopsy. This has the potential to improve the therapeutic outcome.Comment: 10 pages, 4 Figures, 2 Tables. American Journal of Clinical Oncology, August 202

Improving Education through Linking Personality to Organisational Citizenship Behaviour in Balkans Universities

Personality can explain people’s adjustment to the environment, prestige, esteem and respect by society, friends, family, co-workers, and supervisors. The five-factor personality model describes a common understanding of personality formation in the five major profiles, commonly referred to as Extroversion, Conscientiousness, Neuroticism, Agreeableness, and Openness to Experience. This research explored the effect of Big five personality profiles on Organizational Citizenship Behaviour to determine whether a personality can be a predictor of the existence of Organizational Citizenship Behaviour particularly toward university personnel. Baseline data for this research was collected from public and private universities in Bosnia and Herzegovina, Serbia, and Montenegro. A total of 560 surveys were collected from 26 private and public universities. Findings show that Extraversion has an impact on Organizational Citizenship Behaviour. On the other side, Neuroticism has a negative impact on Organizational Citizenship Behaviour, while Openness to experience has no impact on Organizational Citizenship Behaviour

A Deep-Learning Algorithm to Predict Short-Term Progression to Geographic Atrophy on Spectral-Domain Optical Coherence Tomography

IMPORTANCE: The identification of patients at risk of progressing from intermediate age-related macular degeneration (iAMD) to geographic atrophy (GA) is essential for clinical trials aimed at preventing disease progression. DeepGAze is a fully automated and accurate convolutional neural network-based deep learning algorithm for predicting progression from iAMD to GA within 1 year from spectral-domain optical coherence tomography (SD-OCT) scans. OBJECTIVE: To develop a deep-learning algorithm based on volumetric SD-OCT scans to predict the progression from iAMD to GA during the year following the scan. DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study included participants with iAMD at baseline and who either progressed or did not progress to GA within the subsequent 13 months. Participants were included from centers in 4 US states. Data set 1 included patients from the Age-Related Eye Disease Study 2 AREDS2 (Ancillary Spectral-Domain Optical Coherence Tomography) A2A study (July 2008 to August 2015). Data sets 2 and 3 included patients with imaging taken in routine clinical care at a tertiary referral center and associated satellites between January 2013 and January 2023. The stored imaging data were retrieved for the purpose of this study from July 1, 2022, to February 1, 2023. Data were analyzed from May 2021 to July 2023. EXPOSURE: A position-aware convolutional neural network with proactive pseudointervention was trained and cross-validated on Bioptigen SD-OCT volumes (data set 1) and validated on 2 external data sets comprising Heidelberg Spectralis SD-OCT scans (data sets 2 and 3). MAIN OUTCOMES AND MEASURES: Prediction of progression to GA within 13 months was evaluated with area under the receiver-operator characteristic curves (AUROC) as well as area under the precision-recall curve (AUPRC), sensitivity, specificity, positive predictive value, negative predictive value, and accuracy. RESULTS: The study included a total of 417 patients: 316 in data set 1 (mean [SD] age, 74 [8]; 185 [59%] female), 53 in data set 2, (mean [SD] age, 83 [8]; 32 [60%] female), and 48 in data set 3 (mean [SD] age, 81 [8]; 32 [67%] female). The AUROC for prediction of progression from iAMD to GA within 1 year was 0.94 (95% CI, 0.92-0.95; AUPRC, 0.90 [95% CI, 0.85-0.95]; sensitivity, 0.88 [95% CI, 0.84-0.92]; specificity, 0.90 [95% CI, 0.87-0.92]) for data set 1. The addition of expert-annotated SD-OCT features to the model resulted in no improvement compared to the fully autonomous model (AUROC, 0.95; 95% CI, 0.92-0.95; P = .19). On an independent validation data set (data set 2), the model predicted progression to GA with an AUROC of 0.94 (95% CI, 0.91-0.96; AUPRC, 0.92 [0.89-0.94]; sensitivity, 0.91 [95% CI, 0.74-0.98]; specificity, 0.80 [95% CI, 0.63-0.91]). At a high-specificity operating point, simulated clinical trial recruitment was enriched for patients progressing to GA within 1 year by 8.3- to 20.7-fold (data sets 2 and 3). CONCLUSIONS AND RELEVANCE: The fully automated, position-aware deep-learning algorithm assessed in this study successfully predicted progression from iAMD to GA over a clinically meaningful time frame. The ability to predict imminent GA progression could facilitate clinical trials aimed at preventing the condition and could guide clinical decision-making regarding screening frequency or treatment initiation

Growth aspirations and social capital:young firms in a post-conflict environment

This article explores the growth aspirations of owners and managers of young firms in a post-conflict economy by focusing on social capital. It treats social capital as a multidimensional, multilevel phenomenon, studying the effects of discussion network characteristics, trust in institutions, generalised trust in people and local ethnic pluralism. We argue that in a post-conflict country, ethnic pluralism is indicative of local norms of tolerance towards experimentation and risk taking which support growth aspirations. It also distinguishes between the aspirations of hired managers and owners-managers. The empirical counterpart and hypotheses testing rely on survey evidence drawn from young businesses in Bosnia and Herzegovina

Dietary Lactoferrin Alleviates Age-Related Lacrimal Gland Dysfunction in Mice

BACKGROUND: Decrease in lacrimal gland secretory function is related to age-induced dry eye disease. Lactoferrin, the main glycoprotein component of tears, has multiple functions, including anti-inflammatory effects and the promotion of cell growth. We investigated how oral administration of lactoferrin affects age-related lacrimal dysfunction. METHODS AND FINDINGS: Twelve-month-old male C57BL/6Cr Slc mice were randomly divided into a control fed group and an oral lactoferrin treatment group. Tear function was measured at a 6-month time-point. After euthanasia, the lacrimal glands were subjected to histological examination with 8-hydroxy-2'-deoxyguanosine (8-OHdG) antibodies, and serum concentrations of 8-OHdG and hexanoyl-lysine adduct (HEL) were evaluated. Additionally, monocyte chemotactic protein-1(MCP-1) and tumor necrosis factor-α (TNF-α) gene expression levels were determined by real-time PCR. The volume of tear secretion was significantly larger in the treated group than in the control. Lactoferrin administration reduced inflammatory cell infiltration and the MCP-1 and TNF-α expression levels. Serum concentrations of 8-OHdG and HEL in the lactoferrin group were lower than those in the control group and were associated with attenuated 8-OHdG immunostaining of the lacrimal glands. CONCLUSION: Oral lactoferrin administration preserves lacrimal gland function in aged mice by attenuating oxidative damage and suppressing subsequent gland inflammation

Orally Active Multi-Functional Antioxidants Are Neuroprotective in a Rat Model of Light-Induced Retinal Damage

Progression of age-related macular degeneration has been linked to iron dysregulation and oxidative stress that induce apoptosis of neural retinal cells. Since both antioxidants and chelating agents have been reported to reduce the progression of retinal lesions associated with AMD in experimental animals, the present study evaluates the ability of multi-functional antioxidants containing functional groups that can independently chelate redox metals and quench free radicals to protect the retina against light-induced retinal degeneration, a rat model of dry atrophic AMD.Proof of concept studies were conducted to evaluate the ability of 4-(5-hydroxypyrimidin-2-yl)-N,N-dimethyl-3,5-dioxopiperazine-1-sulfonamide (compound 4) and 4-(5-hydroxy-4,6-dimethoxypyrimidin-2-yl)-N,N-dimethyl-3,5-dioxopiperazine-1-sulfonamide (compound 8) to reduce retinal damage in 2-week dark adapted Wistar rats exposed to 1000 lx of light for 3 hours. Assessment of the oxidative stress markers 4- hydroxynonenal and nitrotyrosine modified proteins and Thioredoxin by ELISA and Western blots indicated that these compounds reduced the oxidative insult caused by light exposure. The beneficial antioxidant effects of these compounds in providing significant functional and structural protection were confirmed by electroretinography and quantitative histology of the retina.The present study suggests that multi-functional compounds may be effective candidates for preventive therapy of AMD

Human Capital and Economic Development Review of What was Studied and Where was Researched

The main aim of this study is to define the most researched topics and geographical locations and the most active authors and institutions in Human Capital and Economic Development research area. 317 articles that published between 2007 and 2014 from 5 different journals with Social Scientific Citation Index (SSCI) were examined. This study also explores relation between research topics and researched countries and why some topics attracted more attention than others. It is found that some topics and geographic locations were researched more than others. Authors identified topics that were researched less or not researched as well as geographic locations. Proposal for future study is discussed according to results of analysis