The quality of output or decision-making depends on high-quality input data, their adequate evaluation, the application of adequate approaches, and accurate calculation. In this paper, an objective criticism of applying the fuzzy SWARA (step-wise weight assessment ratio analysis) method based on the Chang TFN (triangular fuzzy number) scale is performed. Through research, it has been noticed that a large number of studies use this approach and, as an epilogue, there are wrong decisions based on inconsistent values in relation to the initial assessment of decision-makers (DMs). Seven representative studies (logistics, construction industry, financial performance management, and supply chain) with different parameter structures and decision matrix sizes have been singled out. The main hypothesis has been set, which implies that the application of this approach leads to wrong decisions because the weight values of the criteria are incorrect. A comparative analysis with the improved fuzzy SWARA (IMF SWARA) method has been created and a number of negative conclusions has been reached on using the fuzzy SWARA method and the Chang scale: Primarily, that using such an approach is impossible for two or more criteria to have equal value, that allocating TFN (1,1,1) leads to criteria values that are inconsistent with expert evaluation, that the last-ranked criteria in the fuzzy SWARA method have no influential value on the ranking of alternatives, that there is a great gap between the most significant and last-ranked criteria, and that the most significant criterion has a huge impact on the evaluation of alternative solutions and decision making. As a general conclusion, it is given that this approach is not adequate for application in problems of multi-criteria decision making because it produces inadequate management of processes and activities in various spheres.

This paper demonstrates how recursive least squares (RLS) can be used to estimate the parameters of remote environment contact force which can be used to render a virtual environment on the operator side in a bilateral teleoperation system. Proper and fast estimation of the remote environment impedance plays a crucial role in the realization of local force controllers for time delayed teleoperation systems. Addressing that challenge, in this paper, three variants of RLS estimators are implemented and compared against three different impedance models. The algorithms are tested in the simulation environment making use of a recorded real experiment data set. The force reconstruction performances are compared to evaluate the implemented models and estimators. Based on the simulation results, one of the estimators and one of the models are selected for experimental validation on a single degree of freedom motion control system. The results obtained from the experiments confirm how the estimated forces match with that of the actual force responses and provide promising potential for further application in local force controllers of the teleoperation systems.

This paper proposes a navigation algorithm for indoor mobile robots in unknown and unstructured environments using a modified Artificial Potential Fields (APF) approach. The proposed algorithm takes into consideration the well-known drawbacks of the APF such as local minima, U-Shaped traps, box canyon and the goal non-reachable with obstacles nearby (GNRON) and implies certain modifications to address those problems. The proposed method is tested in a series of simulations performed on actual lidar measurement data and taking into consideration the problems mentioned above. The results of the simulations confirm the performance of the proposed method yielding a robust and fast algorithm for indoor localization and navigation of mobile robots.

BACKGROUND The 4S-AF scheme includes: stroke risk, symptoms, severity of burden, and substrate severity domain. AIM Our aim was to assess the adherence to 4S-AF scheme in patients classified according to stroke risk in post-hoc analysis of the BALKAN-AF dataset. METHODS A 14-week prospective enrolment of consecutive patients with electrocardiographically documented atrial fibrillation (AF) was performed in seven Balkan countries from 2014 to 2015. RESULTS Low stroke risk (CHA₂DS₂-VASc score, 0 in males or 1 in females) was present in 162 (6.0%) of the patients. 2,099 (77.4%) of patients had CHA₂DS₂-VASc score ≥3 in females or ≥2 in males (high stroke risk) and 613 (22.6%) had CHA₂DS₂-VASc score <3 in females or <2 in males. 75 (46.3%) of patients with low stroke risk and 1555 (74.1%) of patients with high stroke risk were prescribed oral anticoagulants (OAC). 2677 (98.6%) had data on European Heart Rhythm Association (EHRA) class. Among 2099 patients with high stroke risk, 703 (33.4%) had EHRA class ≥3. 207 (29.4%) of patients with EHRA class ≥3 and high stroke risk were offered rhythm control; 620 (55.2%) of individuals with first-diagnosed or paroxysmal AF with high stroke risk were offered rhythm control. Two or more comorbidities occurred in 1927 (91.8%) of patients with high stroke risk. CONCLUSIONS OAC overuse was observed in patients with low stroke risk, whilst OAC underuse was evident in those with high risk of stroke. The percentage of highly symptomatic patients with high risk of stroke who were offered rhythm control strategy was low.

Hurricane Ida ferociously affected many south-eastern and eastern parts of the United States, making it one of the strongest hurricanes in recent years. Advanced forecast and warning tool has been used to track the path of the ex-Hurricane, Ida, as it left New Orleans on its way towards the northeast, accurately predicting significant supercell development above New York City on September 01, 2021. This advanced method accurately detected the area with the highest possible level of convective instability with 24-h lead time and even Level 5, devised in the categorical outlooks legend of the system. Therefore, an extreme level implied a very high probability of the local-scale hazard occurring above the NYC. Cloud model output fields (updrafts and downdrafts, wind shear, near-surface convergence, the vertical component of relative vorticity) show the rapid development of a strong supercell storm with rotating updrafts and a mesocyclone. The characteristic hook-shaped echo signature visible in the reflectivity patterns indicates a signal for a highly precipitable (HP) supercell with the possibility of tornado initiation. Open boundary conditions represent a good basis for simulating a tornado that evolved from a supercell storm, initialized with initial data obtained from a real-time simulation in the period when the bow echo and tornado-like signature occurred. Тhe modeled results agree well with the observations.

Apoptosis induction is a promising approach in targeting tumor cells. As halogenated boroxine (HB) shows antitumor activity, but its mechanism of action in hematological tumors remains unclear, in this study, we aimed to analyze apoptosis triggering in normal and UT‐7 leukemia cells by HB. Methods for assessing cell viability and cytotoxicity, apoptosis detection, relative expression of 84 apoptosis‐associated genes and BCL‐2, and functional analysis were applied. Pronounced HB activities in inhibition of cell viability, cytotoxicity, and apoptosis induction with measurable differences between tumor and normal cells were found. HB modulated the expression of 21 genes, predominantly downregulated the antiapoptotic genes in leukemia. The functional association revealed HB's impact on inhibition of NF‐κB signaling pathway. BCL‐2 expression decreasing was found only in UT‐7 leukemia. This study identified HB as an apoptosis inducer affecting leukemia but not normal cells considering mechanisms of selective activity that may be a great advantage of HB applications.

During the execution of construction projects, uncertain events, such as delays, prolongations and disruptions of project activities, have the potential to cause a significant deviation between the planned and realized state of a project. As a result, progress on important project objectives can decrease and this leads to critical delays as well as heavy profit loss. For this reason, we propose the implementation of the customized evolutionary algorithm to generate resilient baseline schedules which include a sufficient number of time floats to absorb the negative impact of uncertainty. This way, the baseline solution is searched as a trade-off between project duration, its final profit and the overall baseline stability. The proposed algorithm is applied to real construction project data and the results of the analysis suggest improved stability for resilient baseline schedules. Application of the genetic algorithm to solve the existing multi-objective problem enables practical implementation of new technologies and methods in construction management. Resilient baseline schedules can be used in an uncertain environment to achieve more accurate predictions and support decision making in the areas of construction scheduling and costing.

Background: The dorsal root ganglion (DRG) is structurally complex and pivotal to systems processing nociception. Whole mount analysis allows examination of intricate microarchitectural and cellular relationships of the DRG in three-dimensional (3D) space. New method: We present DRGquant a set of tools and techniques optimized as a pipeline for automated image analysis and reconstruction of cells/structures within the DRG. We have developed an open source software pipeline that utilizes machine learning to identify substructures within the DRG and reliably classify and quantify them. Results: Our methods were sufficiently sensitive to isolate, analyze, and classify individual DRG substructures including macrophages. The activation of macrophages was visualized and quantified in the DRG following intrathecal injection of lipopolysaccharide, and in a model of chemotherapy induced peripheral neuropathy. The percent volume of infiltrating macrophages was similar to a commercial source in quantification. Circulating fluorescent dextran was visualized within DRG macrophages using whole mount preparations, which enabled 3D reconstruction of the DRG and DRGquant demonstrated subcellular spatial resolution within individual macrophages. Comparison with existing method(s): Here we describe a reliable and efficient methodologic pipeline to prepare cleared and whole mount DRG tissue. DRGquant allows automated image analysis without tedious manual gating to reduce bias. The quantitation of DRG macrophages was superior to commercial solutions. Conclusions: Using machine learning to separate signal from noise and identify individual cells, DRGquant enabled us to isolate individual structures or areas of interest within the DRG for a more granular and fine-tuned analysis. Using these 3D techniques, we are better able to appreciate the biology of the DRG under experimental inflammatory conditions.

Drying of textiles in industrial facilities represents an energy-intensive process where a large number of measures for energy and production cost savings can be introduced. Typical measures include the introduction of energy management, waste-heat recovery, process optimization and so on. Drying is a complex process with coupled heat and mass transfer between the heated air and humid textile, where parameters such as the air flow rate, air velocity and its flow regime and textile velocity and water content represent significant influential factors. The distribution of air temperature and density inside the drying section of an industrial stenter frame is analyzed in detail using three-dimensional numerical simulation, where the textile is modeled as a porous medium to analyze moisture diffusion within the textile. Heated air is introduced into a chamber by inlet nozzles and removed by exit nozzles, the distribution of which is based on actual machine configuration. A humid textile is introduced into a section, where temperature and density distribution within the textile are calculated for selected time periods. During the simulation in the Fluent program, models of specific component transport, multiphase air flow, turbulent flow, porosity and evaporation were used. The results represent a valuable data set that provides an in-depth insight into the drying process in the industrial stenter machine.