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Introduction/purpose: The Collatz conjecture has been considered and the stopping time needed for the recursive transformation to end has been investigated. Methods: A statistical analysis on the stopping time has been used. Results: The statistical approach shows that the probability of finding an infinite stopping time, that is a violation of the Collatz conjecture, is extremely low. Conclusion: Picking precisely one particular atom in the Universe is still more favorable, by more than 61 orders of magnitude, than encountering an infinite total stopping time.

In this article, the authors present a study on artificial intelligence (AI) integration in transportation and storage SMEs, focusing on research questions, literature reviews, hypotheses, sample selection, and data analysis. They explored current AI support and perceptions and plans of SMEs in this sector. The authors addressed the lack of literature on AI use in transport SMEs and investigated factors, such as AI adoption, benefits perception, company size correlation, and investment willingness. Data was collected from 163 SMEs in Serbia and Slovakia, revealing challenges in participant identification due to low AI use. Declining AI adoption rates authors attributed to financial, technological, regulatory, and awareness issues. The research aims to enhance the AI adoption in transportation and storage SMEs and give some directions for future work.

Values for diagnostic reference levels are proposed for intraoral dental radiography in the Republic of Serbia. Proposed numbers for diagnostic reference levels were based on measurements on 119 intraoral units in clinical settings for an adult posterior bitewing X-ray. Values of 3.17 mGy, 3.11 mGy, and 1.58 mGy incident air kerma were found for image receptors film E class, charge-coupled device, and photostimulable phosphor plate, respectively. Similarly, 89.6 mGycm2, 88 mGycm2, and 44.6 mGycm2 air kerma-area products were found for the same detectors. All values are greater than those published in several other similar studies. This is especially true for charge-coupled device image receptors since this technology enables lower patient doses as reported before. This calls for urgent action to optimize intraoral dental imaging, so we present the radiographic techniques used and equipment description to help guide optimization actions.

This study aimed to validate the automated temporal analysis of countermovement vertical jump (CMJ) using MMPose, a markerless pose estimation framework, by comparing it with the gold-standard 3D marker-based motion capture system. Twelve participants performed five CMJ trials, which were simultaneously recorded using the marker-based system and two smartphone cameras capturing both sides of the body. Key kinematic points, including center of mass (CoM) and toe trajectories, were analyzed to determine jump phases and temporal variables. The agreement between methods was assessed using Bland–Altman analysis, root mean square error (RMSE), and Pearson’s correlation coefficient (r), while consistency was evaluated via intraclass correlation coefficient (ICC 3,1) and two-way repeated-measures ANOVA. Cohen’s effect size (d) quantified the practical significance of differences. Results showed strong agreement (r > 0.98) with minimal bias and narrow limits of agreement for most variables. The markerless system slightly overestimated jump height and CoM vertical velocity, but ICC values (ICC > 0.91) confirmed strong reliability. Cohen’s d values were near zero, indicating trivial differences, and no variability due to recording side was observed. Overall, MMPose proved to be a reliable alternative for in-field CMJ analysis, supporting its broader application in sports and rehabilitation settings.

Given the complex nature of the handball as a game, players are required to possess a distinct set of physical and physiological attributes to attain peak performance. With the countermovement vertical jump (CVJ) being widely implemented as a non-invasive and time-efficient testing modality in sports settings, the purpose of the present study was twofold: (a) to establish a CVJ profile of professional female handball players and (b) to examine differences in force-time metrics between starters and non-starters. Forty-two professional female handball players (e.g., SuperLeague) volunteered to participate in this study. Each athlete performed three maximum-effort CVJs with no arm swing while standing on a uni-axial force plate system sampling at 1,000 Hz. Independent t-tests were used to examine differences in each variable between starters and non-starters. The results revealed that starters attained superior performance within the eccentric phase of the CVJ when compared to non-starters, particularly in terms of eccentric peak velocity (−0.957 ± 0.242 vs. −0.794 ± 0.177 m·s−1), eccentric mean power (320.0 ± 77.7 vs. 267.1 ± 75.2 W), and eccentric peak power (929.0 ± 388.1 vs. 684.4 ± 214.2 W). While not reaching the level of statistical significance, moderate-to-large effect sizes were observed for concentric impulse, peak velocity, and mean and peak force and power, all in favor of players included in the starting lineup (g = 0.439–0.655). Overall, these findings suggest that at the top-tier level of handball competition, the ability to secure a spot in a starting lineup may be possibly influenced by the athlete's eccentric performance capabilities. Thus, the development of lower-body eccentric strength and power may positively impact on-court athlete performance and ultimately help the team secure the desired game outcome.

Flexible manufacturing systems are becoming increasingly popular in modern industry, providing flexibility in producing different products and quick adaptability to changes in the production program. Didactic FMC (DFMC) are small manufacturing systems used for educational purposes, providing students with practical experience in production. DFMC systems are the basic element in learning new concepts of Industry 4.0. This paper explores the flexibility of routing components in DFMC systems using the Dempster-Shafer theory of belief functions and evidence networks developed based on this theory. By using the Dempster-Shafer theory, we evaluate the flexibility of routing in the system for producing different products, i.e., the system's ability to adapt to changes in the production program according to the concepts of Industry 4.0. The analysis of routing flexibility allows for identifying critical points of the system and suggestions for improving system efficiency. The results show that routing flexibility is a key factor for the efficiency of the DFMC system. The Dempster-Shafer theory provides a precise analysis of beliefs based on various input parameters, which contributes to the precision and reliability of the analysis of routing flexibility of DFMC system components. This paper contributes to the understanding of routing flexibility and provides guidelines for further research in this area.

Student motivation is one of the affective components that plays a key role in learning science. Research shows that in developed countries there is a trend of declining students’ interest in science and technology. In this paper, the relationships between intrinsic motivation, self-concept, and the achievement of the fourth-grade elementary school students in mathematics and sciences were investigated. The authors also present the results of the secondary data analyses obtained in Serbia by means of student questionnaires and knowledge tests in the last two cycles of the TIMSS research in 2015 and 2019. The questionnaire contains two scales in which motivational variables are operationalized: students’ attitudes towards mathematics/sciences and mathematical/ scientific self-confidence. Students’ attitude is an indicator of an intrinsic motivation, and self-confidence is an indicator of self-concept. The results show that students express a high motivation for learning mathematics and sciences and a high level of self-concept. A higher level of self-concept is accompanied by a higher level of motivation for learning mathematics and sciences. Individual characteristics of students have a greater influence on achievement than the influence of schools and teachers. Students who express a more positive attitude towards mathematics and science and a higher level of self-concept in these areas also have a higher level of achievement. The influence of mathematical self-concept on achievement is particularly significant. The obtained results are in accordance with the findings of the earlier research that indicate complex and controversial relationships between intrinsic motivation, self-concept, and mathematical achievement, as well as that other constructs, including self-concept, can mediate the links between motivation and achievement. The authors point out the possibilities of encouraging students’ motivation for learning. If students are trained in the teaching process to organize their own activities, this will contribute to their experience of autonomy and the development of confidence in their own competence, which positively impacts their motivation for learning.

Spinal osteoarthritis, a degenerative condition of the spine, significantly impairs quality of life, causing pain, stiffness, and limited mobility. Treatment primarily aims to improve functionality and quality of life. This study investigated the effects of lower back surgery (e.g., spinal decompression with vertebra stabilization) on upper-limb maximum strength, lower limb functionality, and quality of life in osteoarthritis patients. A total of 16 patients (♀ = 10 and ♂ = 6) patients from the orthopedic clinic who were diagnosed with osteoarthritis based on MRI and clinical symptoms underwent the surgery. Their handgrip strength, lower limb functionality (6 min walk test), and quality of life (Flanagan quality of life scale) were assessed before and after the surgery. A repeated measures ANOVA was conducted to assess differences in these metrics pre- and post-surgery across the entire patient cohort, as well as within gender-specific subgroups. A large positive effect was seen in the 6 min walk (p = 0.02, d = −0.83) test but not in the handgrip test or quality of life. However, female patients showed a trend towards better quality of life. The results of this study provide evidence for the effectiveness of surgery in the treatment of spinal osteoarthritis and underscore the need for personalized treatment approaches in the treatment of spinal osteoarthritis.

This study explored the changes in the rate of torque development scaling factor (RTD-SF) and maximum voluntary isometric contraction (MVC) variables following six weeks of unilateral isometric electromyostimulation (EMS) and voluntary (VOL) exercises. Twenty-six physically active participants were randomly assigned to EMS (n = 13) or a VOL group. MVC and RTD-SF of the quadriceps femoris of both legs were assessed before and after training. EMS and VOL exercises had identical frequency (three sessions/week), intensity (60% MVC), volume (40 contractions), and work-to-rest ratio (18 min: 6.25 s of work/20 s of rest). There were no between-group differences for the trained leg with overall increases in maximal torque (Tmax) of ~29% (d = 2.11–2.12), ~13% for RTDmax (d = 0.92–1.10); ~23% for Intercept (d = 0.72–0.78), and reduction in RTD-SF by ~15% (d = 1.01–1.10). In the non-trained leg, significant moderate change was only observed after EMS for RTD-SF which decreased by 12.5% (d = 0.76). Both EMS and VOL training applied at equivalent workloads positively impact on Tmax, RTDmax, and Intercept, but they negatively affect the quickness with which muscle contracts across a wide range of submaximal forces. Using a moderate training intensity in regularly physically active participants could explain the absence of cross-education in the VOL group.

Given the multidirectional nature of the sport, handball athletes must frequently perform high-intensity decelerations to avoid defenders, generate space, or perform directional changes. The aim of the present study was twofold: (i) to investigate different kinematic measures of horizontal deceleration performance by comparing the acceleration-deceleration assessment (ADA) with the 5-0-5 test and (ii) to investigate relationships between force-time characteristics derived from the countermovement vertical jump (CVJ) and measures of horizontal deceleration performance. Eleven female handball players competing in the first-tier professional league in Europe performed three CVJs while standing on a uni-axial force plate system sampling at 1000 Hz, followed by two ADAs (i.e., maximal-effort acceleration over a 10 m distance, followed by rapid deceleration) and 5-0-5 test trials. Tripod-mounted radar sampling at 47 Hz, placed 5 m behind the start line, was used to record horizontal velocity data. Each test was separated by a 5–7 min rest interval to minimize the influence of fatigue. No statistically significant differences were found in horizontal deceleration performance parameters between ADA and the 5-0-5 test. However, athletes with a higher CVJ height and reactive strength index-modified showed better performance in terms of horizontal deceleration measures such as maximal approach velocity and average and maximal deceleration. Overall, these results may be of interest to practitioners working with multidirectional sport athletes such as handball players as they provide critical insight for the selection of assessments and training strategies targeted toward optimizing on-court athlete performance.

This paper aims to correct recent results on a generalized class of ϝ-contractions in the context of b-metric spaces. The significant work consists of repairing some novel results involving ϝ-contraction within the structure of b-metric spaces. Our objective is to take advantage of the property (F1) instead of the four properties viz. (F1), (F2), (F3) and (F4) applied in the results of Nazam et al. ["Coincidence and common fixed point theorems for four mappings satisfying ϝ-contraction", Nonlinear Anal: Model. Control., vol. 23, no. 5, pp. 664--690, 2018]. Our approach of proving the results utilizing only the condition (F1) enriches, improves, and condenses the proofs of a multitude of results in the existing state-of-art.

ABSTRACT The aim of study was to determine the relationship between metabolic parameters, body weight and body growth of piglets at birth and weaning. The experiment included 80 piglets obtained from F1 generation sows. Body weight was measured at birth (BW0), 24h (BW1) after birth and on day 25 (at weaning, BW2). Blood sampling was performed at the beginning of life (3rd day after birth) and at weaning (21st day after birth). BW0 and BW1 positively correlated with cholesterol and negatively with urea values at the beginning of life and RBC values at weaning. BW2 positively correlates with albumin and cortisol values at the beginning of life, total proteins, and globulins at weaning, and negatively correlates with erythrocyte values at weaning. Piglet growth from birth to weaning (BWG2-0) correlates positively with total proteins, albumin, and cortisol at the beginning of life and total proteins at weaning. ROC analysis shows that MCHC, TPROT, GLOB, CHOL and AST at the beginning of life can distinguish fast-growing from slow-growing piglets from birth to weaning period. The use of blood parameters enables early recognition of growth rate in piglets, which can help to optimize all further steps to achieve the best possible growth.

Metastases largely rely on hematogenous dissemination of tumor cells via the vascular system and significantly limit prognosis of patients with solid tumors. To colonize distant sites, circulating tumor cells must destabilize the endothelial barrier and transmigrate across the vessel wall. Here we performed a high-content screen to identify drugs that block tumor cell extravasation by testing 3,520 compounds on a transendothelial invasion coculture assay. Hits were further characterized and validated using a series of in vitro assays, a zebrafish model enabling three-dimensional (3D) visualization of tumor cell extravasation, and mouse models of lung metastasis. The initial screen advanced 38 compounds as potential hits, of which, four compounds enhanced endothelial barrier stability while concurrently suppressing tumor cell motility. Two compounds niclosamide and forskolin significantly reduced tumor cell extravasation in zebrafish, and niclosamide drastically impaired metastasis in mice. Because niclosamide had not previously been linked with effects on barrier function, single-cell RNA sequencing uncovered mechanistic effects of the drug on both tumor and endothelial cells. Importantly, niclosamide affected homotypic and heterotypic signaling critical to intercellular junctions, cell-matrix interactions, and cytoskeletal regulation. Proteomic analysis indicated that niclosamide-treated mice also showed reduced levels of kininogen, the precursor to the permeability mediator bradykinin. Our findings designate niclosamide as an effective drug that restricts tumor cell extravasation through modulation of signaling pathways, chemokines, and tumor-endothelial cell interactions. SIGNIFICANCE: A high-content screen identified niclosamide as an effective drug that restricts tumor cell extravasation by enhancing endothelial barrier stability through modulation of molecular signaling, chemokines, and tumor-endothelial cell interactions. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/81/3/619/F1.large.jpg.

In this study, the idea of using a fully symmetric U-Net deep learning model for forecasting a segmented image of high global aerosol concentrations is implemented. As the forecast relies on historical data, the model used a sequence of the last eight segmented images to make the prediction. For this, the classic U-Net model was modified to use ConvLSTM2D layers with MaxPooling3D and UpSampling3D layers. In order to achieve complete symmetry, the output data are given in the form of a series of eight segmented images shifted by one image in the time sequence so that the last image actually represents the forecast of the next image of high aerosol concentrations. The proposed model structure was tuned by the new FOX metaheuristic algorithm. Based on our analysis, we found that this algorithm is suitable for tuning deep learning models considering their stochastic nature. It was also found that this algorithm spends the most time in areas close to the optimal value where there is a weaker linear correlation with the required metric and vice versa. Taking into account the characteristics of the used database, we concluded that the model is capable of generating adequate data and finding patterns in the time domain based on the ddc and dtc criteria. By comparing the achieved results of this model using the AUC-PR metric with the previous results of the ResNet3D-101 model with transfer learning, we concluded that the proposed symmetric U-Net model generates data better and is more capable of finding patterns in the time domain.

ABSTRACT While the effect of gut microbiota and/or inflammation on a distant body site, including the lungs (gut–lung axis), has been well characterized, data about the influence of lung microbiota and lung inflammation on gut homeostasis (lung–gut axis) are scarce. Using a well-characterized model of pulmonary infection with the fungus Aspergillus fumigatus, we investigated alterations in the lung and gut microbiota by next-generation sequencing of the V3–V4 regions of total bacterial DNA. Pulmonary inflammation due to the fungus A. fumigatus caused bacterial dysbiosis in both lungs and gut, but with different characteristics. While increased alpha diversity and unchanged bacterial composition were noted in the lungs, dysbiosis in the gut was characterized by decreased alpha diversity indices and modified bacterial composition. The altered homeostasis in the lungs allows the immigration of new bacterial species of which 41.8% were found in the feces, indicating that some degree of bacterial migration from the gut to the lungs occurs. On the contrary, the dysbiosis occurring in the gut during pulmonary infection was a consequence of the local activity of the immune system. In addition, the alteration of gut microbiota in response to pulmonary infection depends on the bacterial composition before infection, as no changes in gut bacterial microbiota were detected in a rat strain with diverse gut bacteria. The data presented support the existence of the lung–gut axis and provide additional insight into this mechanism. IMPORTANCE Data regarding the impact of lung inflammation and lung microbiota on GIT are scarce, and the mechanisms of this interaction are still unknown. Using a well-characterized model of pulmonary infection caused by the opportunistic fungus Aspergillus fumigatus, we observed bacterial dysbiosis in both the lungs and gut that supports the existence of the lung–gut axis.

Bacterial microbiota of the gastrointestinal tract is known to prevent the invasion of pathogenic microorganisms and regulate intestinal permeability, digestion, metabolism, and immune response. It affects function, homeostasis, and disease outcomes in the gastrointestinal tract and extra-intestinal sites such as the lungs. This review summarizes the currently available knowledge regarding the gut-lung axis. The association of bacterial composition and/or dysbiosis in the gut with asthma, chronic obstructive lung disease, cystic fibrosis, recurrent respiratory tract infections, and lung cancer in humans is highlighted, as well as data obtained from animal models of pulmonary inflammation, which indicated that modulation of immune system activity lies at the base of this interaction. Additionally, the potential use of prebiotics, probiotics, and postbiotics in the treatment of lung inflammation is presented.

The paper will analyze two speeches of historical importance for international relations and oratory of the 21st century. The first one is the speech of the President of the Russian Federation, Vladimir Putin, of 21 February 2022, which is considered the most significant official announcement of Russia about the events in Ukraine, and the second one is the speech of 24 February 2022 as its logical, meaningful and contextual continuation. Those two speeches, broadcast on multiple channels and media, last for an hour and a half and contain a multitude of material facts exposed through special rhetorical procedures, most often rhetorical examples of misunderstandings. The perspective of the Russian side which could not be seen in the pro-Western media is also given here. It sets up a euphemistic reinterpretation of the events eristically presented in the foreign media as an invasion, an aggression, a war conflict and an attack.

Introduction/purpose: The paper presents a new state-of-the-art method that involves NASA satellite imagery with the latest deep learning model for a spatiotemporal sequence forecasting problem. Satellite-retrieved aerosol information is very useful in many fields such as PM prediction or COVID-19 transmission. The input data set was MODAL2_E_AER_OD which presents global AOT for every 8 days from Terra/MODIS. The implemented machine learning algorithm was built with ConvLSTM2D layers in Keras. The obtained results were compared with the new CNN LSTM model. Methods: Computational methods of Machine Learning, Artificial Neural Networks, Deep Learning. Results: The results show global AOT prediction obtained using satellite digital imagery as an input. Conclusion: The results show that the ConvLSTM developed model could be used for global AOT prediction, as well as for PM and COVID-19 transmission.

In order to better predict the high aerosol concentrations associated with air pollution and climate change, a machine learning model was developed using transfer learning and the segmentation process of global satellite images. The main concept of transfer learning lies on convolutional neural networks and works by initializing the already trained model weights to better adapt the weights when the network is trained on a different dataset. The transfer learning technique was tested with the ResNet3D-101 model pre-trained from a 2D ImageNet dataset. This model has performed well for contrail detection to assess climate impact. Aerosol distributions can be monitored via satellite remote sensing. Satellites can monitor some aerosol optical properties like aerosol optical thickness. Aerosol optical thickness snapshots were the input dataset for the model and were obtained from NASA’s Terra-Modis satellite; the output images were segmented by comparing the pixel values with a threshold value of 0.8 for aerosol optical thickness. Hyperparameter optimization finds a tuple of hyperparameters that yields an optimal model that minimizes a predefined loss function on given independent data. The model structure was adjusted in order to improve the performance of the model by applying methods and hyperparameter optimization techniques such as grid search, batch size, threshold, and input length. According to the criteria defined by the authors, the distance domain criterion and time domain criterion, the developed model is capable of generating adequate data and finding patterns in the time domain. As observed from the comparison of relative coefficients for the criteria metrics proposed by the authors, ddc and dtc, the deep learning model based on ConvLSTM layers developed in our previous studies has better performance than the model developed in this study with transfer learning.

In this paper, various tensorial inequalities of trapezoid type were obtained. Identity from classical analysis is utilized to obtain the tensorial version of the said identity which in turn allowed us to obtain tensorial inequalities in Hilbert space. The continuous functions of self-adjoint operators in Hilbert spaces have several tensorial norm inequalities discovered in this study. The convexity features of the mapping f lead to the variation in several inequalities of the trapezoid type.

Introduction/purpose: Saddle point approximation has been considered in the paper Methods: The saddle point method is used in several different fields of mathematics and physics. Several terms of the expansion for the factorial function have been explicitely computed. Results: The integrals estimated in this way have values close to the exact one. Conclusions: Higher order corrections are not negligible even when requiring moderate levels of precision.

In this study, the understanding of self-regulated learning as one of the key competences in contemporary education was based on Pintrich’s model of self-regulated learning. The goal was to examine the links between different motivational orientations and learning strategies among university students in Serbia and explore the relations between these variables on the one hand and academic achievement, gender, field of study, and year of study on the other. A total of 520 students enrolled in art, science, and social science studies at universities in Belgrade, Novi Sad, Niš, and Kragujevac filled out the Motivated Strategies for Learning Questionnaire (MSLQ). The obtained data were processed via a factor analysis, correlations, and non-parametric tests. We isolated six factors, including Self-Confidence and Orientation Towards Understanding, Elaboration and Metacognitive Self-Regulation Strategies, Critical Thinking and Orientation Towards Expanding Knowledge, Orientation Towards External Criteria Accompanied by Self- Discipline, Anxiety, and High Learning Motivation and Dedication to Achieving the Set Goals. The application of metacognitive self-regulation strategies could be linked to both intrinsic and extrinsic motivation. Students oriented towards external criteria exhibited higher levels of academic achievement. We identified gender differences in the application of elaboration and metacognitive self-regulation strategies in terms of learning motivation and anxiety levels. Art students were more prone to the use of the critical thinking strategy compared to science and social science students. In this paper, we highlight practical implications related to designing self-regulated learning courses for university teachers and students, along with recommendations for future research.

Understanding motivation for learning as a complex construct allows for education to be tailored to students’ individual characteristics and needs. Although different combinations of motivational factors lead to different outcomes, there is still a remarkable scarcity of research on students’ motivational profiles in science. To identify groups of fourth-graders characterized by different levels of intrinsic motivation and self-efficacy in science, we applied the person-centered approach. By conducting secondary analyses of data obtained via student questionnaires and science knowledge tests in TIMSS 2019 in Serbia, we examined motivational profiles’ structure and relations to achievement as well as the membership of students of different genders and profile stability across two research cycles. The cluster analysis revealed four profiles characterized by different levels of intrinsic motivation, self-efficacy, and achievement. Students who reported higher levels of motivation and self-efficacy were more successful than students with lower scores on these variables. Students who reported the highest levels of self-efficacy and moderate levels of motivation demonstrated the highest achievement levels. This finding indicates that teachers need to use strategies for improving competencies and enhancing students’ self-efficacy. It is necessary to examine contextual factors that might have contributed to the increase in the number of students who demonstrated low levels of intrinsic motivation and self-efficacy, and the lowest levels of achievement.

In the age of digital content, information does not reach people only through standard and established linguistic and genre forms. In addition to hybrids, it is possible to experience many other genres in public, in accordance with the context of current reality. The first journalistic genre singled out from the world of literature -the column -today is not just small-scale literature. There are currents in it that we can observe from the angle of literary and journalistic studies because it retains the standardized genre properties, giving new dimensions of meaning. There is little genealogical research in the field of media. Preserving the features of traditional genres is as difficult as shaping new genres that can be labeled as alternatives. The column in public discourse today is not neglected, but, on the contrary, it attracts the attention of young generations (weeklies, portals, new media platforms such as YouTube or Ted talk). The column as a counter-genre is a proven "habit" of the text to take shape against expectations. The columnist himself determines his genre boundaries. The ironic-parodic, negative, nihilistic side of the column stems from the uncertainty of journalistic discourse. The constant meandering of the form affects its perception. The anti-genre features of the column make it critically oriented towards genealogical conventions. The column has no strict conventions, other than conventions breaking conventions and trying to be "unconventional." The column pushes the boundaries and meanings of genres and contributes to the decentralization of contemporary media discourse. It is becoming the new structural dominant of contemporary journalism.

Research in medical imaging focuses on methods useful in computer-aided diagnosis systems. In modern times, these systems often have automatic detection of regions of interest, and imaging technologies offer numerous advantages, like the possibility of developing reliable assisting algorithms. Magnetic Resonance Imaging (MRI) provides compelling features for brain tumor detection due to good soft tissue contrast and has important clinical value. To help clinicians in making diagnoses, current algorithms for processing and medical image classification may depend on intricate deep learning designs that demand large hardware resources and lengthy execution times. This is with no doubt helpful in understanding disease mechanisms and in labeling difficult instances for brain tumor identification. On the other hand, statistical low-dimension feature sets including co-occurrence-based ones could be useful in dealing with tumor detection avoiding possible complexity. In this paper, statistical approaches for feature extraction and reduction are analyzed for MRI brain tumor classification, and the evaluation of the results is presented on one of the publicly available brain tumor detection database commonly used for machine learning tasks. Bayes and kNN classifiers are applied for the analysis, as well as four distance metrics, and two methods for feature reduction. The results seem promising in developing a simple and less hardware-demanding procedure.

The objective of this study was to investigate the hydrodynamics and the gas-liquid mass transfer coefficient of an external-loop airlift reactor (ELAR). The ELAR was operated in three cases: different inlet velocities of fluids, different alcohols solutions (water, 0.5% methanol, 0.5% ethanol, 0.5% propanol and 0.5% butanol) and different concentration of methanol in solutions (0%, 0.5%, 1%, 2% and 5%). The influence of superficial gas velocity and various diluted alcohol solutions on hydrodynamics and the gas-liquid mass transfer coefficient of the ELAR was studied. Experimentally, the gas hold-up, liquid velocities and volumetric mass transfer coefficient values in the riser and the downcomer were obtained from the literature source. A computational fluid dynamics (CFD) model was developed, based on two-phase flow, investigating different liquids regarding surface tension, assuming the ideal gas flow, applying the finite volume method and Eulerian-Eulerian model. The volumetric mass transfer coefficient was determined using the CFD and artificial neural network model. The effects of liquid parameters and gas velocity on the characteristics of the gas-liquid mass transfer were simulated. These models were compared with the appropriate experimental results. The CFD model successfully simulates the influence of different alcohols regarding the number of C-atoms on hydrodynamics and mass transfer.

The research presents an experiment with a model of an electronic generator for energy injection into the plasma of a fusion reactor. By recording a non-ionizing field in the vicinity of a fusion reactor, it was determined that this field has an extremely high growth rate. At the site of the maximum intensity of the field of non-ionizing radiation, commercial surge arresters with a flexible model of surge arresters were used for experimentation. It has been found that the commercial surge arresters have an efficiency of about 20%. For the efficiency of the flexible model, it was found to be slightly less than 40% (and to be achieved by the application of alpha particle radiation). Since neither of these efficiencies guarantee reliable operation of the gas-filled surge arrester, it was concluded that essential electronics in the vicinity of the fusion generator must be protected. However, since this protection can only be implemented in a fusion reactor, the fact remains that the environment of such a reactor is extremely contaminated with non-ionizing radiation. Commercial surge voltages are isolated for testing since the protection of electronic circuits from fast overvoltages is a critical point for the functioning of modern electronics.

Using the approach of so-called c-sequences introduced by the fifth author in his recent work, we give much simpler and shorter proofs of multivalued Perov's type results with respect to the ones presented in the recently published paper by M. Abbas et al. Our proofs improve, complement, unify and enrich the ones from the recent papers. Further, in the last section of this paper, we correct and generalize the well-known Perov's fixed point result. We show that this result is in fact equivalent to Banach's contraction principle.

Introduction/purpose: The aim of this paper is to present the concept of b(αn,βn) -hypermetric spaces. Methods: Conventional theoretical methods of functional analysis. Results: This study presents the initial results on the topic of b(αn,βn) - hypermetric spaces. In the first part, we generalize an n-dimensional (n ≥ 2) hypermetric distance over an arbitrary non-empty set X. The b(αn,βn) -hyperdistance function is defined in any way we like, the only constraint being the simultaneous satisfaction of the three properties, viz, non-negativity and positive-definiteness, symmetry and (αn, βn)-triangle inequality. In the second part, we discuss the concept of (αn, βn)- completeness, with respect to this b(αn,βn) -hypermetric, and the fixed point theorem which plays an important role in applied mathematics in a variety of fields. Conclusion: With proper generalisations, it is possible to formulate well-known results of classical metric spaces to the case of b(αn,βn) - hypermetric spaces.

ABSTRACT Reducing the mortality rate is of a great economic importance for pig farming. Therefore, it is necessary to define the conditions in the farrowing unit based on the performance of the piglets, and specific hematological and biochemical parameters. Therefore, the aim of this paper is to examine the importance of using skin moisture absorbent and its influence in preventing hypothermia, which causes great economic losses in pig production. The experiment was set up on a commercial farm in Serbia and included 92 pigs divided into the experimental and control group. Body temperature values, body weight and blood parameters were monitored. The obtained values indicate that there is a significantly positive correlation of body temperature change and body weight values, and body temperature showed a significantly higher increase in the experimental group compared to the control group. The results obtained from hematological and biochemical parameters provide a clearer picture of the metabolic processes in piglets in the farrowing unit and can be used to further improve pig production and as a complement to genetic enhancement.

The rate of force development scaling factor (RFD-SF) has been used to assess neuromuscular quickness. However, the common protocols are lengthy. This study evaluated the validity and reliability of the reduced protocol to assess the RFD-SF and its validity in detecting inter-limb asymmetries. Eighteen participants (five females and thirteen males; mean age = 20.8 ± 0.6 years) performed the common and reduced RFD-SF protocols (five isometric pulse knee extensions at 30 and 70% of maximal voluntary contraction). A repeat measure design was employed including one test session of the common protocol and two test sessions of the reduced protocol. Correlation analysis was conducted to investigate the association between the two protocols, while a paired-sample t-test and a Bland–Altman plot assessed whether the reduced protocol provided valid results. The between-day reliability was assessed using an intra-class correlation coefficient, coefficient of variation, typical error of measurement, and paired-sample t-test. The validity to detect asymmetries was checked with the paired-sample t-test. The correlation between RFD-SF obtained using two protocols was significant (p < 0.001) and very large for the dominant (r = 0.71) and non-dominant (r = 0.80) legs. No significant difference occurred between protocols in the RFD-SF for the dominant (p = 0.480, d = 0.17) and non-dominant legs (p = 0.213, d = 0.31). The reliability was acceptable for both legs, with no between-day difference for the dominant (p = 0.393) and non-dominant legs (p = 0.436). No significant difference between the two protocols (p = 0.415, d = 0.19) was found in the detection of inter-limb asymmetries. The results of this study suggest that the reduced protocol could be used as a valid and reliable alternative to the common protocol, as well as to identify interlimb asymmetries.

Introduction/purpose: The aim of this paper is to present the concept of a universal hypermetric space. An n-dimensional (n ≥ 2) hypermetric distance over an arbitrary non-empty set X is generalized. This hypermetric distance measures how separated all n points of the space are. The paper discusses the concept of completeness, with respect to this hypermetric as well as the fixed point theorem which play an important role in applied mathematics in a variety of fields. Methods: Standard proof based theoretical methods of the functional analysis are employed. Results: The concept of a universal hypermetric space is presented. The universal properties of hypermetric spaces are described. Conclusion: This new version of the results for Un-hypermetric spaces may have applications in various disciplines where the degree of clustering is sought for.

The purpose of this research is to investigate the occurrence of two heavy metals (namely cadmium (Cd) and lead (Pb)) in the liver of hogs bred in different locations in Vojvodina. A total of 30 liver samples were collected from ten pig farms in Vojvodina for experimental purposes in the period from December 2017 to January 2018. The samples collected were analysed for the presence of lead and cadmium. The average concentration of lead in all the samples was 0.39 mg/kg wet weight, whereas the samples from only one farm of the ten considered were found to contain a slightly higher average lead concentration than permitted by the Serbian standard. A lead concentration of 0.86 mg/kg wet weight was detected in one liver sample from this farm. The maximum permitted lead concentration was exceeded in the liver samples obtained from three farms. However, all the liver samples analysed were found to contain the permitted levels of cadmium, with an average cadmium concentration of 0.12 mg/kg wet weight and a maximum cadmium concentration of 0.48 mg/kg wet weight. The occurrence of heavy metals and their origin in the pig’s offals should be examined in greater detail in future research, especially because pig’s offals are used in the meat processing industry.

Piglets are an important category in pig farming which should, alongside sows, be considered essential production heads. Over the past decades, the intensive selection in pig production has given priority to economically important traits resulting in greater feed utilization and obtaining more piglets from fewer sows. However, such selection practices have failed to improve the overall vitality of piglets and their ability to survive immediately after birth or during their stay in the farrowing unit. Body weight is of great importance in pig production, especially the piglet body weight at birth. A number of parameters can be predicted according to the piglet birth weight: mortality and growth rate, the physiological status of the heard, sensitivity to external influences, vitality and etc. The purpose of this paper is to determine the piglet body weight variation from birth to weaning (measured at birth, 3 hours after birth, 24 hours after birth and at weaning) and to examine the relationship between the birth weight of piglets and their body weight during the transition into nursing. A total of 105 piglets were enrolled in this study from the F1 generation sows followed through eight consecutive parities. The paper presents the results obtained using descriptive statistics, as well as variance and correlation analysis. The relationship between the piglet body weight at different stages of their life and overall production parameters was found to emphasize the centrality of housing conditions as the piglet weight at birth exerts a great impact on the body weight of older piglets, especially in the first days of the piglet life. Therefore, the proper care of piglets in farrowing units is of paramount importance to pig production, especially because piglets have lower body weight at birth nowadays than before.

The aim of this work is in situ anodization/anaphoretic deposition of a nano amorphous calcium phosphate (ACP)/chitosan oligosaccharide lactate (ChOL) multifunctional hybrid coating decorated with selenium (Se) on a titanium substrate and in vivo investigation of its immunomodulatory and anti-inflammatory effect. Investigating phenomena at the implant–tissue interface of interest for controlled inflammation and immunomodulation was also the aim of the research. In our earlier research, we designed coatings based on ACP and ChOL on titanium with anticorrosive, antibacterial and biocompatible properties, while in the presented results we show that selenium addition makes this coating an immunomodulator. The immunomodulatory effect of the novel hybrid coating is characterized by the examination of the functional aspects in the tissue around the implant (in vivo): proinflammatory cytokines’ gene expression, M1 (iNOS) and M2 (Arg1) macrophages, fibrous capsule formation (TGF-β) and vascularization (VEGF). The EDS, FTIR and XRD analyses prove the formation of a ACP/ChOL/Se multifunctional hybrid coating on Ti and the presence of Se. A higher M2/M1 macrophage ratio in the ACP/ChOL/Se-coated implants compared to pure titanium implants (a higher level of Arg1 expression) is noted at all time points examined (after 7, 14 and 28 days). Lower inflammation measured by gene expression of proinflammatory cytokines IL-1β and TNF, lower expression of TGF-β in the surrounding tissue and higher IL-6 expression (solely at day 7 post-implantation) is noted in presence of the ACP/ChOL/Se-coated implants.

The attention mechanism in natural language processing and self-attention mechanism in vision transformers improved many deep learning models. An implementation of the self-attention mechanism with the previously developed ConvLSTM sequence-to-one model was done in order to make a comparative evaluation with statistical testing. First, the new ConvLSTM sequence-to-one model with a self-attention mechanism was developed and then the self-attention layer was removed in order to make comparison. The hyperparameters optimization process was conducted by grid search for integer and string type parameters, and with particle swarm optimization for float type parameters. A cross validation technique was used for better evaluating models with a predefined ratio of train-validation-test subsets. Both models with and without a self-attention layer passed defined evaluation criteria that means that models are able to generate the image of the global aerosol thickness and able to find patterns for changes in the time domain. The model obtained by an ablation study on the self-attention layer achieved better outcomes for Root Mean Square Error and Euclidean Distance in regards to developed ConvLSTM-SA model. As part of the statistical test, a Kruskal–Wallis H Test was done since it was determined that the data did not belong to the normal distribution and the obtained results showed that both models, with and without the SA layer, predict similar images with patterns at the pixel level to the original dataset. However, the model without the SA layer was more similar to the original dataset especially in the time domain at the pixel level. Based on the comparative evaluation with statistical testing, it was concluded that the developed ConvLSTM-SA model better predicts without an SA layer.

Background: Provision of a Medication Action Plan (MAP) on admission and a Discharge Medication Record (DMR) are associated with reduced medication‐related harm. Aim: To report factors associated with the provision of MAPs and DMRs in rural and regional hospitals in Queensland, Australia. Method: A literature search, environmental scan and department consultations were conducted to develop Clinical Pharmacy Key Performance Indicators (cpKPIs) and design a cpKPI dashboard. Two of the five KPIs included in the dashboard, relating to medication action plans on admission and medication records on discharge, were reported for all the hospitals and were included in the study. A retrospective, period‐prevalence study was conducted to evaluate the coverage and equity of clinical pharmacy service provision for patients admitted for longer than 24 h. The proportions of patients who received MAPs and DMRs were stratified by age, gender, Indigeneity and hospital type. Statistical analysis used chi‐squared tests and logistic regression in R. This project was exempt due to the local policy requirements that constitute research by the Far North Queensland Human Research Ethics Committee (Reference no: EX/2023/QCH/94383‐1684QA). The justification for this exemption is as follows: the project was determined to be negligible risk research and involved the use of existing collection of data or records that contain only non‐identifiable data about human beings. Results: In total, 13 818 patients (37.9% of admissions) received a MAP and 11 631 patients (32.7% of discharges) received a DMR. The proportion of MAPs and DMRs was significantly higher in rural hospitals than in regional hospitals (MAP 50.6% vs 34.6%, DMR 33.1% vs 31.3%) and for male patients than female patients (MAP 42.2% vs 33.7%, DMR 36.4% vs 29.2%). When stratified by age, First Nations patients received a higher proportion of MAPs and DMRs in each age group, except for age 85 years and over. The proportion of First Nations patients aged 50 years and over who received MAP was lower compared to that for non‐Indigenous patients aged 65 years and over (56.3% vs 59.8%), whilst the proportion for DMRs was similar (50.4% vs 49.3%). Conclusion: The study defined the clinical pharmacy key performance indicators for measuring equity of clinical pharmacy service provision in Australia. When adjusted for a difference in life expectancy, the proportion of MAPs for First Nations patients was lower compared to the proportion of MAPs for non‐Indigenous patients. Further improvements are required to achieve equity of service provision for First Nations patients and female patients. [ABSTRACT FROM AUTHOR]

This paper presents two Machine Learning models that classify time series data given from smartwatch accelerometer of observed subjects. For the purpose of classification we use Deep Neural Network and Random Forest classifier algorithms. The comparison of both models shows that they have similar performance with regard to recognition of subject's activities that are used in the test group of the dataset. Training accuracy reaches approximately 95% and 100% for Deep Learning and Random Forest model respectively. Since the validation and recognition, reached about 81% and 75% respectively, a tendency for improving accuracy as a function of number of participants is considered. The influence of data sample precision to the accuracy of the models is examined since the input data could be given from various wearable devices.

This study examines how students’ absenteeism moderates the relationship of math self-concept and motivation to learn math on one side and the achievement in the TIMSS 2015 math test on the other. The stratified random sample consists of 4036 fourth grade pupils from 160 primary schools in Serbia. Separate regression models were made for four levels of frequency of students’ absenteeism. The results show that self-concept makes a positive contribution to the prediction of achievement, and motivation a negative one. Additionally, with the increase of absenteeism the importance of self-concept drops and that of motivation grows. The analysis of variance confirmed that along with the increase of absenteeism, students express lower levels of self-concept, while the level of motivation does not change. The most important conclusion is that regular class attendance contributes to the students’ math self-concept and consequential achievement by developing their experiences of success in math. The usefulness of the motivation scale for predicting math test performance is discussed.

The paper deals with the measures for the preparation and planning of the hearing of the defendant, taken by representatives of the police or prosecutor's office. In the introduction, the author provides general observations on the hearing of the defendant and his testimony in the criminal procedure. The paper then proceeds to outline the views of theoreticians regarding the significance of the preparation and planning of the defendant's hearing, as well as specific measures that need to be taken when carrying out this activity. These measures consist of the following: 1) determining the person who will conduct the hearing; 2) determining the location and time of the hearing; 3) analysis of the situation in the case files before the first hearing and identification of all facts and circumstances concerning the criminal offence; 4) obtaining information on the defendant's personality, and 5) preparation of the hearing strategy. The author considers these measures necessary assumptions for obtaining not only a lawful testimony - in line with the provisions of the law on criminal procedure, but also a complete testimony, which is able to shed light on the facts surrounding the criminal offence.

Over the past decade, force-velocity (F-v) profiling has emerged as a promising tool for assessing neuromuscular capacity to design individually tailored interventions in diverse populations. To date, a limited number of studies have addressed the optimization of the linear method for measuring F-v profiles of single-joint isokinetic movements. We aimed to simplify the measurement of knee extension (KE) and knee flexion (KF) isokinetic tasks by evaluating the most appropriate combination of two velocities (i.e., the 2-point method). Twenty-two healthy participants (11 males and 11 females) were included in the study. Isokinetic peak torque was measured at nine angular velocities (30-60-90-120-150-180-210-240-300°/s) and under isometric conditions (at 150° and 120° of KF for KE, and KF, respectively). Maximal theoretical force (F0), maximal theoretical velocity (v0), slope of the relationship (Sfv) and maximal theoretical power (Pmax) were derived from the linear F-v profiles of KE and KF and compared between the 9-point method and all possible combinations (36 in total) of the 2-point methods. The F-v profiles obtained from nine points were linear for KE (R2 = 0.95; 95% CI = 0.94–0.96) and KF (R2 = 0.93; 95% CI = 0.90–0.95), with F0 underestimating isometric force. Further analyses revealed great to excellent validity (range: ICCs = 0.89–0.99; CV = 2.54%–4.34%) and trivial systematic error (range: ES = −0.11–0.24) of the KE 2-point method when force from distant velocities (30°/s, 60°/s or 90°/s combined with 210°/s, 240°/s or 300°/s) was used. Similarly, great to excellent validity and trivial systematic error of the KF 2-point method for F0 and Pmax (range: ICC = 0.90–0.96; CV = 2.94%–6.38%; ES = −0.07–0.14) were observed when using the previously described combinations of velocities. These results suggest that practitioners should consider using more distant velocities when performing simplified isokinetic 2-point single-joint F-v profiling. Furthermore, the F-v profile has the potential to differentiate between the mechanical properties of knee extensors and flexors and could therefore serve as a potential descriptor of performance.

The main objective of present study was to evaluate inter-rater reliability and concurrent validity of Side Hop Test stopwatch vs. force plates timing, and to determine the number of sessions and trials required to minimize the effects of learning on Side Hop Test total time and limb symmetry index. Fifteen healthy male physical education students (mean ± SD: age, 23 ± 3 years; height, 181 ± 9 cm; and weight 72 ± 6 kg) participated. Side Hop Test total time (stopwatch and force plates) of left and right leg, and limb symmetry index (force plates) were obtained over seven sessions conducted 5–7 days apart. Time recordings of two raters were similar (t = −0.56, p > 0.05) with high reliability (all ICC >0.99 and CV% 0.05; for rater 1 and 2, respectively). Total time improved across the Sessions (F = 25.87, p < 0.01, ω2 = 0.18) and Trials (F = 68.15, p < 0.01, ω2 = 0.10), with no significant interaction between factors. No between-leg differences were detected (F = 0.52, p > 0.05, ω2 = 0.001). Limb symmetry index ranged from 0.999 to 1.055 across all sessions and trials (all p > 0.05 and ω2 < 0.00). Due to low coefficient of correlation, high interclass correlation coefficient, and the lack in heteroscedasticity, stopwatch measurements are valid to measure total time in the Side Hop Test. Moreover, stopwatch measurements could be reliably used to measure total time in the Side Hop Test, while the test could be administrated with only one experienced rater. Unlike total times, findings on limb symmetry index suggest it could be reliably assessed after seven familiarization sessions.

The purpose of this paper is to determine the reference ranges for hematological, biochemical and endocrinological parameters in the blood of the commercial F1 Landrace x Yorkshire and Yorkshire x Landrace piglets aged 1 and 21 days. A total of 72 animals were enrolled in this study. The following reference ranges were determined for the blood parameters considered (day 1 vs. day 21): WBC 10.0-12.4 vs. 11.5-13.7 × 109/L; RBC 3.72-4.06 vs. 5.25-5.73 × 1012/L; HGB 71.4-79.0 vs. 100-110 g/L; HCT 24.4-26.5 vs. 35.7-39.1 %; MCV 64.4-66.0 vs. 72.7-74.8 fL; MCH 20.9-21.7 vs. 24.7-25.6 pg; MCHC 321-329 vs. 367-378 g/L; AST 78.5-98.9 vs. 51.8-66 U/L; ALT 72.5-84.5 vs. 65.9-76.5 U/L; CHOL 2.41-2.71 vs. 3.81-4.27 mmol/L; TGC 1.55-1.93 vs. 1.85-2.25 mmol/L; GLU 5.58-6.24 vs. 5.97-6.67 mmol/L; TPROT 55.2-59.4 vs. 65-69.9 g/L; ALB 13.4-15.1 vs. 27.8-30.9 g/L, GLOB 41.3-44.8 vs. 35.3-40.9 g/L; UREA mmol/L; TBIL 36.6-44.5 vs. 29.4-40.8 μmol/L; ALFAAMYLASE 897-998 vs. 851-949 U/L; LIPASE 74.1-79.7 vs. 88.3-98.1 U/L; CORT 140-196 vs. 41.4-63.8 ng/mL; INSUL 4.04-5.68 vs. 1.71-2.41 μU/L. The RBC, HGB, HCT, MCV, MCH, and MCHC values recorded were found to be higher in the piglets aged 21 days than those in the piglets aged 1 day. The total leukocyte count did not differ between the experimental groups. Lower AST, ALT, globulin, cortisol and insulin values were detected in the piglets aged 21 days than those in the piglets aged 1 day. However, the values of triglycerides, cholesterol, total protein, albumin and lipase were found to be higher in the piglets aged 21 days than those in the piglets aged 1 day. The glucose, alpha amylase and total bilirubin (TBIL) values did not differ significantly between the experimental groups. The Kolmogorov-Smirnov test conducted shows that there are significant differences in the frequency distribution of most of the blood parameters tested in the pigs aged 1 and 21 days, which confirms that a separate reference interval must be determined and applied to the respective piglet ages considered. The establishment of reference values for different age categories can facilitate the assessment of health status and productive performance of farm piglets.

ABSTRACT Recent studies have focused on the use of seminal plasma to increase sow fertility after classical intracervical artificial insemination (AI). The aim of the present study was to investigate the influence of seminal plasma infusion, prior to the application of conventional AI dose, on the fertility rate in sows. A total of 114 sows were treated with intrauterine infusion of 30ml seminal plasma (SP), while 114 control sows were infused by physiological solution (PS), immediately before the application of conventional AI dose. The experiment was conducted at one commercial pig farm in Serbia, which is comprised of 1,500 sows in the breeding herd. Intrauterine infusion of seminal plasma produced significantly (P

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The purpose of the present study was (i) to explore the reliability of the most commonly used countermovement jump (CMJ) metrics, and (ii) to reduce a large pool of metrics with acceptable levels of reliability via principal component analysis to the significant factors capable of providing distinctive aspects of CMJ performance. Seventy-nine physically active participants (thirty-seven females and forty-two males) performed three maximal CMJs while standing on a force platform. Each participant visited the laboratory on two occasions, separated by 24–48 h. The most reliable variables were performance variables (CV = 4.2–11.1%), followed by kinetic variables (CV = 1.6–93.4%), and finally kinematic variables (CV = 1.9–37.4%). From the 45 CMJ computed metrics, only 24 demonstrated acceptable levels of reliability (CV ≤ 10%). These variables were included in the principal component analysis and loaded a total of four factors, explaining 91% of the CMJ variance: performance component (variables responsible for overall jump performance), eccentric component (variables related to the breaking phase), concentric component (variables related to the upward phase), and jump strategy component (variables influencing the jumping style). Overall, the findings revealed important implications for sports scientists and practitioners regarding the CMJ-derived metrics that should be considered to gain a comprehensive insight into the biomechanical parameters related to CMJ performance.

The aim of this study was to investigate the resistance-specific gains in muscle power and strength (1RM) following the training of maximum bench-press throws (BPT) against constant, inertial, and combined resistance. Forty-eight male participants (age 20.5 ± 2.0 years) were randomly assigned to the constant, inertial, combined resistance, or control group. Participants underwent 8 weeks of training of BPT against the loads that corresponded to the different effects of mass of 40 kg (∼50% of 1RM). The gains in average and maximum power, and 1RM were significant in all experimental groups (P < 0.01), but not in the control group (P > 0.1). Relative gains in the average (26.3 ± 9.8%) and maximum power (25.2 ± 9.8%) were larger than that in the 1RM (mean 7.2 ± 6.9%; both P < 0.001). The gains in the average (F4, 66 = 6.0; P < 0.01) and maximum power (F4, 66 = 4.7; P < 0.01) were higher when tested against the training-specific resistance than when tested against the remaining two resistance types. Differences in 1RM among experimental groups were not significant (P = 0.092). The most important and rather novel finding of the study is that the training against the weight and inertial resistance, and their combination results in resistance-specific gains in muscle power, although the overall gains muscle strength and power remain comparable across the training protocols.