This study deals with the selection of a sustainable supplier on the example of the agribusiness company Mamex from Bosnia and Herzegovina. The main problem of this research is the selection of a sustainable supplier as a part of the sustainable strategy of the Mamex company. One of the prerequisites is that suppliers must present sustainability principles in business by having an appropriate certificate. The results of the selection of sustainable suppliers are completed using a new hybrid fuzzy approach with the methods IMF SWARA (Improved Fuzzy Stepwise Weight Assessment Ratio Analysis) and fuzzy TRUST (multi-normalization multi-distance assessment) CRADIS (compromise ranking of alternatives from distance to ideal solution) methods. The innovative approach is reflected in the use of a combination of these methods, especially by combining the TRUST and CRADIS methods into one method. The IMF SWARA method shows that the most important main criterion is the economic criterion, while the least important is the social criterion. By applying the fuzzy TRUST CRADIS method, it is found that out of the observed six suppliers, the second supplier has the best indicators. These results are confirmed by other fuzzy methods: MABAC (multi-attributive border approximation area comparison), WASPAS (weighted aggregated sum product assessment), fuzzy SAW (simple additive weighting), MARCOS (measurement of alternatives and ranking according to compromise solution), ARAS (a new additive ratio assessment), and TOPSIS (technique for order preference by similarity to an ideal solution). This research shows that applying more normalization when ranking alternatives reduces the influence of individual normalizations, and this approach should be used in future research.

Dry eye syndrome and allergic conjunctivitis are the most common inflammatory disorders of the eye surface. Although eye drops are the most usual prescribed dosage form, they are characterized by low ocular availability due to numerous barrier mechanisms of the eye. The use of biopolymers in liquid ophthalmic preparations has numerous advantages, such as increasing the viscosity of the tear film, exhibiting bioadhesive properties, and resisting the drainage system, leading to prolonged retention of the preparation at the site of application, and improvement of the therapeutic effect. Some mucoadhesive polymers are multifunctional excipients, so they act by different mechanisms on increasing the permeability of the cornea. Additionally, many hydrophilic biopolymers can also represent the active substances in artificial tear preparations, due to their lubrication and moisturizing effect. With the modification of conventional ophthalmic preparations, there is a need for development of new methods for their characterization. Numerous methods for the assessment of mucoadhesiveness have been suggested by the literature. This review gives an overview related to the development of mucoadhesive liquid ophthalmic formulations for the treatment of dry eye and allergic conditions.

The selection of the most appropriate underground mining technology is not a simple process because it involves handling of a large amount of information about several potential methods. Multicriteria optimization approaches are proven useful tools for ranking alternatives, especially in cases where multiple complex criteria have to be considered simultaneously. An ore deposit is a complex system because of its geology, physical and mechanical properties, and hydrogeological conditions. As such, problem solving requires a heuristic approach and includes tasks involving expert judgement, intuition, estimation, and experience. Using a heuristic strategy to state a problem means that the analyst is placed in a position to apply past experience to a future situation and existing knowledge to new circumstances, as well as discover new avenues to creative problem solving. A complex algorithm was developed to pave the way to quality management of mining, by using the VIKOR method to rank various mining technologies relative to a set of criteria and select the optimum mining method that will primarily ensure profitable and safe mining.

Two-dimensional van der Waals (vdW) materials exhibit a broad palette of unique and superlative properties, including high electrical and thermal conductivities, paired with the ability to exfoliate or grow and transfer single layers onto a variety of substrates thanks to the relatively weak vdW interlayer bonding. However, the same vdW bonds also lead to relatively low thermal boundary conductance (TBC) between the 2D layer and its 3D substrate, which is the main pathway for heat removal and thermal management in devices, leading to a potential thermal bottleneck and dissipation-driven performance degradation. Here, we use first-principles phonon dispersion with our 2D–3D Boltzmann phonon transport model to compute the TBC of 156 unique 2D/3D interface pairs, many of which are not available in the literature. We then employ machine learning to develop streamlined predictive models, of which a neural network and a Gaussian process display the highest predictive accuracy (RMSE [Formula: see text] 5 MW m−2 K−1 and [Formula: see text] 0.99) on the complete descriptor set. Then we perform sensitivity analysis to identify the most impactful descriptors, consisting of the vdW spring coupling constant, 2D thermal conductivity, ZA phonon bandwidth, the ZA phonon resonance gap, and the frequency of the first van Hove singularity or Boson peak. On that reduced set, we find that a decision-tree algorithm can make accurate predictions (RMSE [Formula: see text] 20 MW m−2 K−1 and [Formula: see text] 0.9) on materials it has not been trained on by performing a transferability analysis. Our model allows optimal selection of 2D-substrate pairings to maximize heat transfer and will improve thermal management in future 2D nanoelectronics.

Patients with occlusion myocardial infarction (OMI) and no ST-elevation on presenting ECG are increasing in numbers. These patients have a poor prognosis and would benefit from immediate reperfusion therapy, but we currently have no accurate tools to identify them during initial triage. Herein, we report the first observational cohort study to develop machine learning models for the ECG diagnosis of OMI. Using 7,313 consecutive patients from multiple clinical sites, we derived and externally validated an intelligent model that outperformed practicing clinicians and other widely used commercial interpretation systems, significantly boosting both precision and sensitivity. Our derived OMI risk score provided superior rule-in and rule-out accuracy compared to routine care, and when combined with the clinical judgment of trained emergency personnel, this score helped correctly reclassify one in three patients with chest pain. ECG features driving our models were validated by clinical experts, providing plausible mechanistic links to myocardial injury.

Immunomodulators and biologicals are essential in current IBD management, but are associated with increased risk of infections. Considering the growing number of treatment options, the benefit-risk balance of drugs is becoming increasingly important in clinical decision making. To date, post-marketing surveillance studies mainly focus on severe infections. As a result, data on mild and moderate infections are scarce. These infections take longer to clear in immunosuppressed patients and can substantially impact quality of life. We aimed to assess the incidence of all infections and identify risk factors for the development of infections in IBD patients. We previously developed and validated a Patient-Reported Infections Questionnaire (PRIQ), with excellent diagnostic accuracy, covering 15 infection categories with a 3-month recall period. The current prospective, multicentre, observational cohort study was performed between Jun, 1 2020 and Jul, 1 2021, enrolling consecutive IBD patients using the PRIQ implemented in myIBDcoach, an established telemedicine platform. Infection severity was defined as mild (self-limiting or topical treatment), moderate (oral antibiotics, antivirals or antifungals) or severe (hospitalization or IV treatment). Incidence rates (IR) were calculated for all infections, stratified for severity and subtype. Risk factors for infections were identified using multivariable logistic regression. In total, 629 IBD patients were included which completed 2391 PRIQs during 572 person-years (PY) of follow-up, resulting in 990 reported infections, corresponding to IRs of 17.3, 11.8, 5.1, and 0.4 per 10PY for all, mild, moderate, and severe infections, respectively (Tables 1-2). Upper respiratory tract (IR 26.9/100PY) and urinary tract infections (IR 14.8/100PY) were the most commonly reported mild and moderate infections (Table 3). Compared to patients without treatment, patients on immunosuppressives more frequently experienced infections of any severity (mild: IR ratio (IRR) 1.57 [95%CI 1.21-2.06] p<0.001, moderate: IRR 1.42 [95%CI 1.20-1.69] p<0.001). On multivariable logistic regression, female sex (mild aOR 1.96; moderate aOR 1.71), smoking status (mild aOR 1.66; moderate aOR 1.86), higher BMI (moderate aOR 1.05), and more comorbidities (mild aOR 2.41; moderate aOR 1.82) were all significantly associated with the development of mild and moderate infections (Table 4). In this real-world prospective study, immune suppressive therapy was associated with mild and moderate infections of any kind in IBD patients. These infections particularly occur in females, smokers, patients with higher BMI and more comorbidities. This information should be considered in personalised treatment selection.

Background Clear cell sarcomas (CCSs) are translocated aggressive malignancies, most commonly affecting young adults with a high incidence of metastases and a poor prognosis. Research into the disease is more feasible when adequate models are available. By establishing CCS cell lines from a primary and metastatic lesion and isolating healthy fibroblasts from the same patient, the in vivo process is accurately reflected and aspects of clinical multistep carcinogenesis recapitulated. Methods Isolated tumor cells and normal healthy skin fibroblasts from the same patient were compared in terms of growth behavior and morphological characteristics using light and electron microscopy. Tumorigenicity potential was determined by soft agar colony formation assay and in vivo xenograft applications. While genetic differences between the two lineages were examined by copy number alternation profiles, nuclear magnetic resonance spectroscopy determined arginine methylation as epigenetic features. Potential anti-tumor effects of a protein arginine n -methyltransferase type I (PRMT1) inhibitor were elicited in 2D and 3D cell culture experiments using cell viability and apoptosis assays. Statistical significance was calculated by one-way ANOVA and unpaired t-test. Results The two established CCS cell lines named MUG Lucifer prim and MUG Lucifer met showed differences in morphology, genetic and epigenetic data, reflecting the respective original tissue. The detailed cell line characterization especially in regards to the epigenetic domain allows investigation of new innovative therapies. Based on the epigenetic data, a PRMT1 inhibitor was used to demonstrate the targeted antitumor effect; normal tissue cells isolated and immortalized from the same patient were not affected with the IC_50 used. Conclusions MUG Lucifer prim, MUG Lucifer met and isolated and immortalized fibroblasts from the same patient represent an ideal in vitro model to explore the biology of CCS. Based on this cell culture model, novel therapies could be tested in the form of PRMT1 inhibitors, which drive tumor cells into apoptosis, but show no effect on fibroblasts, further supporting their potential as promising treatment options in the combat against CCS. The data substantiate the importance of tailored therapies in the advanced metastatic stage of CCS.

The content of bioactive compounds in four brown and one red algae from the Adriatic Sea (Dictyota dichotoma, Gongolaria barbata, Ericaria amentacea, Sargassum hornschuchii and Ellisolandia elongata) is explored. The efficiency of two different extraction methods viz. ultrasound-assisted extraction (UAE) and matrix solid-phase dispersion (MSPD) to obtain the extracts rich in phenolic compounds was compared. The effect of the extraction solvent to modulate the phenolic profile was assessed. In general, the mixture ethanol/water in an isovolumetric proportion showed the best results. The total phenolic content (TPC) and antioxidant activity (AA), as well as the individual polyphenolic profile, were evaluated for five target algae. TPC values ranged between 0.2 mg GAE/g (for E. elongata) and 38 mg GAE/g (for S. hornschuchii). Regarding the quantification of individual polyphenols by liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis, the presence of a high number of hydroxybenzoic acid derivatives (mainly of 3- and 4-hydroxybenzoic acids) in all species was noted. In G. barbata their concentrations reached up to 500 mg/kg. IC50 values (ABTS assay) ranged between 44 mg/L (for S. hornschuchii) and 11,040 mg/L (for E. elongata). This work contributes to the in-depth characterization of these little-explored algae, showing their potential as a natural source of phenolic compounds.

OBJECTIVE Despite an increased interest in research of theory of mind (ToM) in recent years - both related to psychopathology (depression and anxiety spectrum disorders) and within the typical adults, the existing literature is scarce and presents some conflicting results. Present study aimed to explore sex differences in ToM, alongside its associations with current anxiety and depression symptoms, in a large sample of typical adults collected online. METHOD Participants completed the 15-minutes survey obtaining socio-demographic data, current self-reported depression and anxiety symptom severity, and ToM ability (the Reading the Mind in the Eyes Task). The sample comprised 605 participants -mostly younger adults, women, and high school graduate/student population. RESULTS The majority of participants reported minimal/mild depressive and anxiety symptoms that were significantly more severe in women. Women also displayed significantly better overall ToM ability than men. Significant negative correlation between the severity of current depressive and anxiety symptoms and ToM ability was also observed, but only in individuals expressing the symptoms requiring clinical attention (such association was absent in those exhibiting minimal/mild symptoms). CONCLUSIONS Present research adds to the existing knowledge on the association between ToM ability, anxiety, and depressive symptoms in typical adults as well as on the sex-differences in this important social cognitive domain. Exploring the factors representing indicators of vulnerability for depression-anxiety spectrum disorders is important for their timely detection and treatment.

Detecting new and enlarged lesions in multiple sclerosis (MS) patients is needed to determine their disease activity. LeMan‐PV is a software embedded in the scanner reconstruction system of one vendor, which automatically assesses new and enlarged white matter lesions (NELs) in the follow‐up of MS patients; however, multicenter validation studies are lacking.

The selection and prioritization of suitable strategies to address the challenges to the successful operation and implementation of the bus rapid transit (BRT) system is a common problem faced by practitioners and decision-makers. Recent research has widely discussed the issue, but such assessments have remained limited in the city of Dar es Salaam, Tanzania context, where there are mobility difficulties. The present study addresses this research gap and identifies the most critical challenges to BRT implementation and operation, and recommends the most appropriate strategy for overcoming them. Seven strategies are defined. To prioritize these strategies, five criteria are determined. An integrated multi-criteria decision-making model is introduced. Improved Fuzzy Step-Wise Weight Assessment Ratio Analysis based on the Bonferroni operator was used to determine the importance of the criteria. Measurement of alternatives and ranking according to compromise solution was applied to assess and rank the strategies. The results indicate that “frequent flooding at the Jangwani bridge bus terminal” and “long waiting time at bus stops” are the most critical challenges while the fourth alternative “strengthening the operation and management” is the appropriate strategy to be implemented for successful operation and implementation of the BRT system. After that, a five-phase sensitivity analysis is performed to observe the robustness of the proposed approach. The results indicate the flexibility and applicability of the proposed approach can address real-life problems. The proposed methodology in this work can be instrumental in assisting mass transit operators with the successful implementation and operation of the BRT system.

Background: In vivo diffuse reflectance spectroscopy provides additional contrast in discriminating nerves embedded in adipose tissue during surgery. However, large datasets are required to achieve clinically acceptable classification levels. This study assesses the spectral similarity between ex vivo porcine and in vivo human spectral data of nerve and adipose tissue, as porcine tissue could contribute to generate large datasets. Methods: Porcine diffuse reflectance spectra were measured at 124 nerve and 151 adipose locations. A previously recorded dataset of 32 in vivo human nerve and 23 adipose tissue locations was used for comparison. In total, 36 features were extracted from the raw porcine to generate binary logistic regression models for all combinations of two, three, four and five features. Feature selection was performed by assessing similar means between normalized features of nerve and of adipose tissue (Kruskal–Wallis test, p < 0.05) and for models performing best on the porcine cross validation set. The human test set was used to assess classification performance. Results: The binary logistic regression models with selected features showed an accuracy of 60% on the test set. Conclusions: Spectral similarity between ex vivo porcine and in vivo human adipose and nerve tissue was present, but further research is required.

Ćupter is Herzegovinian candy made of must and flour/semolina. Much research about the incorporation of brewers’ spent grains into the human diet has been published. The purpose of this study was to partially replace semolina (Samples 1 and 2) and flour (Samples 3 and 4) with brewers’ spent grains originating from industrial (Samples 1 and 4) and craft breweries (Samples 2 and 3) and study nutritive, chemical, and preference properties of the product. In this research, the authors aimed to find application of this already proven functional ingredient in ćupter production. Values for pH were higher for all samples compared to the traditional recipe. Samples produced with flour had higher values of water activity (0.86 ± 0.01) and moisture (41.82 ± 1.68 and 41.11 ± 1.41). Ash content increased with BSG addition, but between samples, there were no significant differences. Collected data showed significant differences in fat levels. Higher protein content was measured for Samples 4 (6.60 ± 0.17) and 1 (6.13 ± 0.07). The highest total sugar content was measured for Sample 1. The general appearance for all samples was “moderately like”. Nutritive value was improved with the addition of BSG, but recipes and drying should be modified to improve consumer acceptance.

A search for flavor-changing neutral-current couplings between a top quark, an up or charm quark and a $Z$ boson is presented, using proton-proton collision data at $\sqrt{s} = 13$ TeV collected by the ATLAS detector at the Large Hadron Collider. The analyzed dataset corresponds to an integrated luminosity of 139 fb$^{-1}$. The search targets both single-top-quark events produced as $gq\rightarrow tZ$ (with $q = u, c$) and top-quark-pair events, with one top quark decaying through the $t \rightarrow Zq$ channel. The analysis considers events with three leptons (electrons or muons), a $b$-tagged jet, possible additional jets, and missing transverse momentum. The data are found to be consistent with the background-only hypothesis and 95% confidence-level limits on the $t \rightarrow Zq$ branching ratios are set, assuming only tensor operators of the Standard Model effective field theory framework contribute to the $tZq$ vertices. These are $6.2 \times 10^{-5}$ ($13\times 10^{-5}$) for $t\rightarrow Zu$ ($t\rightarrow Zc$) for a left-handed $tZq$ coupling, and $6.6 \times 10^{-5}$ ($12\times 10^{-5}$) in the case of a right-handed coupling. These results are interpreted as 95% CL upper limits on the strength of corresponding couplings, yielding limits for $|C_{uW}^{(13)*}|$ and $|C_{uB}^{(13)*}|$ ($|C_{uW}^{(31)}|$ and $|C_{uB}^{(31)}|$) of 0.15 (0.16), and limits for $|C_{uW}^{(23)*}|$ and $|C_{uB}^{(23)*}|$ ($|C_{uW}^{(32)}|$ and $|C_{uB}^{(32)}|$) of 0.22 (0.21), assuming a new-physics energy scale $\Lambda_\text{NP}$ of 1 TeV.

The aim of this research was to examine characteristics and predictors of auto stimulatory behavior in children with autism spectrum disorders (ASD), as well as to determine the presence of auto stimulatory behavior exhibited by children with ASD. The sample included 43 participants diagnosed with ASD. The instrument used was Behavior Problems Inventory (BPI-01, Rojahn et al., 2002), subscale for stereotyped behavior. Our results show that children with ASD from our sample have lower rates of auto stimulatory behavior, with the most common ones being repetitive body movements, arm shaking, bouncing around, running and pacing. The school type has not proven to be a predictor of auto stimulatory behaviors. However, male participants and those with low functioning ASD exhibit more auto stimulatory behaviors than females and those with high functioning ASD. The presence of auto stimulatory behaviors persists through age. Auto-stimulatory behaviors exhibited by children with ASD can be reduced or eliminated, however it is important to use evidence-based interventions with proven benefits for the child. Since stereotypy is usually automatically maintained and therefore is one of the behaviors that is often difficult to reduce, it is recommended that parents are taught on how to implement interventions in their home environment.