Search Results (17)

This work presents the results of a research study focused on the development and evaluation of an algorithmic optimal control framework for energy-efficient operation of screw compressors in smart power systems. The proposed approach is based on the Pontryagin maximum principle (PMP), which enables the synthesis of a mathematically grounded regulator that minimizes the total energy consumption of a nonlinear electromechanical system composed of a screw compressor and a variable-frequency induction motor. Unlike conventional PID controllers, the developed algorithm explicitly incorporates system constraints, nonlinear dynamics, and performance trade-offs into the control law, allowing for improved adaptability and energy-aware operation. Simulation results obtained using MATLAB/Simulink confirm that the PMP-based regulator outperforms classical PID solutions in both transient and steady-state regimes. Experimental tests conducted in accordance with standard energy consumption evaluation methods showed that the proposed PMP-based controller provides a reduction in specific energy consumption of up to 18% under dynamic load conditions compared to a well-tuned basic PID controller, while maintaining high control accuracy, faster settling, and complete suppression of overshoot under external disturbances. The control system demonstrates robustness to parametric uncertainty and load variability, maintaining a statistical pressure error below 0.2%. The regulator’s structure is compatible with real-time execution on industrial programmable logic controllers (PLCs), supporting integration into intelligent automation systems and smart grid infrastructures. The discrete-time PLC implementation of the regulator requires only 10³ arithmetic operations per cycle and less than 10² kB of RAM for state, buffers, and logging, making it suitable for mid-range industrial controllers under 2–10 ms task cycles. Fault-tolerance is ensured via range and rate-of-change checks, residual-based plausibility tests, and safe fallbacks (baseline PID or torque-limited speed hold) in case of sensor faults. Furthermore, the proposed approach lays the groundwork for hybrid extensions combining model-based control with AI-driven optimization and learning mechanisms, including reinforcement learning, surrogate modeling, and digital twins. These enhancements open pathways toward predictive, self-adaptive compressor control with embedded energy optimization. The research outcomes contribute to the broader field of algorithmic control in power electronics, offering a scalable and analytically justified alternative to heuristic and empirical tuning approaches commonly used in industry. The results highlight the potential of advanced control algorithms to enhance the efficiency, stability, and intelligence of energy-intensive components within the context of Industry 4.0 and sustainable energy systems. Full article

Background/Objectives: Prenatal psychology studies show that stress, depression, and psychological stress during pregnancy can have a significant impact on maternal and fetal health and are highly prevalent. The aim of the study was to compare maternal and neonatal short-term outcomes in pregnant women* (the asterisk (*) is used at the appropriate places in this text to indicate that all genders are included) with a history of prenatal maternal psychological stress (PMPS) with those of pregnant women* not exposed to PMPS to determine differences and identify risk factors. Methods: Statistical tests for differences and relative risks between the groups were carried out with the perinatal data of University Hospital Tübingen from 2022 using IBM SPSS. Results: The study shows that PMPS has significant negative effects on various parameters, including the rate of premature births, preeclampsia, induction of birth, birth duration, and fetal asphyxia, as well as the birth weight of the children and their Apgar values (an assessment of newborn health scored shortly after birth). In addition, the risk of PMPS increases in women* with stillbirths and two or more previous miscarriages. However, the practical relevance must be critically scrutinized and confirmed by bigger studies. Conclusions: PMPS has a significant impact on the maternal and neonatal birth outcomes and must be identified as a risk factor in pregnancy. There is still a need for further research with larger samples, more balanced groups, and multivariate regression models to generate detailed, more transferable results and a deeper insight into the significant effects of PMPS and the role midwives can play in helping it. Full article

A combination of bromelain and acetylcysteine, BromAc^®, is an efficient intraperitoneal mucolytic for thick mucus secreted in pseudomyxoma peritonei (PMP). Patients with PMP quite often undergo colon anastomosis. Hence, we investigated the effect of the intraperitoneal delivery of BromAc^® on colon-anastomosis healing in a rat model. Sixteen Wistar rats were divided into two groups (N = 8). The controls received intraperitoneal saline after anastomosis, whilst the other group received BromAc^®. They were monitored for body-weight and general health parameters. Half the rats in each group (N = 4) were culled at 4 or 13 days post-surgery for assessment. The healing process of the tissues was assessed by burst pressure and collagen density with histology to assess the integrity of the internal organs. The results indicated that there was a similar pattern of weight fluctuation during the experiment, although the rats treated with the BromAc^® showed slightly greater weight loss during the first 4 days. Although the burst pressure was similar in both groups, the BromAc^® group at day 13 showed a slightly higher burst pressure, which was complemented by a higher collagen density (albeit not statistically significant). The histology of the internal organs was comparable to those of the controls. This study indicates that the intraperitoneal delivery of BromAc^® in a rat model does not interfere with the healing process of colonic anastomosis. Full article

Extreme rainfall and floods have increased in frequency and severity in recent years, due to climate change and urbanization. Consequently, interest in estimating the probable maximum precipitation (PMP) has been burgeoning. The World Meteorological Organization (WMO) recommends two types of methods for calculating the PMP: hydrometeorological and statistical methods. This study proposes a modified Hershfield’s nomograph method and assesses the changes in PMP values based on the two representative concentration pathway (RCP4.5 and RCP8.5) scenarios in South Korea. To achieve the intended objective, five techniques were employed to compute statistical PMPs (SPMPs). Moreover, the most suitable statistical method was selected by comparing the calculated SPMP with the hydrometeorological PMP (HPMP), by applying statistical criteria. Accordingly, SPMPs from the five methods were compared with the HPMPs for the historical period of 2020 and the future period of 2100 for RCP 4.5 and 8.5 scenarios, respectively. The results confirmed that the SPMPs from the modified Hershfield’s nomograph showed the smallest MAE (mean absolute error), MAPE (mean absolute percentage error), and RMSE (root mean square error), which are the best results compared with the HPMP with an average SPMP/HPMP ratio of 0.988 for the 2020 historical period. In addition, Hershfield’s method with varying $K_M$ exhibits the worst results for both RCP scenarios, with SPMP/HPMP ratios of 0.377 for RCP4.5 and 0.304 for RCP8.5, respectively. On the contrary, the modified Hershfield’s nomograph was the most appropriate method for estimating the future SPMPs: the average ratios were 0.878 and 0.726 for the 2100 future period under the RCP 4.5 and 8.5 scenarios, respectively, in South Korea. Full article

Positive mathematical programming (PMP) has a substantial number of applications in the field of agricultural and resource economics. Their focus has often been placed on the simulation analysis of farmers’ response to drastic changes in exogenous factors especially brought about by policy changes. In the present study, an exploration was made to widen the application area of the PMP approach, targeting farmers’ expectation toward the farm-gate price of rice in comparison with that of wheat under the policy to suppress overproduction. When domestic consumption is mature and the regulation of production by the government is present, farmers’ expectation toward the farm-gate price of a crop can be assumed to fall in response to an increased allocation of land area to produce the crop. The degree of the fall is defined as the expectation fall index (EFI) in the present study. A proposition was made as to the procedure for quantifying EFI using the PMP approach with statistical datasets of multiple years retrieved from the Ministry of Agriculture, Forestry, and Fisheries. The present study is considered to have provided a basis to discuss the formation processes of farmers’ attitudes toward policy measures. Full article

Extensive hydrological analysis is carried out to estimate floods for the Batu Dam, a hydropower dam located in the urban area upstream of Kuala Lumpur, Malaysia. The study demonstrates the operational state and reliability of the dam structure based on hydrologic assessment of the dam. The surrounding area is affected by heavy rainfall and climate change every year, which increases the probability of flooding and threatens a dense population downstream of the dam. This study evaluates the adequacy of dam spillways by considering the latest Probable Maximum Precipitation (PMP) and Probable Maximum Flood (PMF) values of the concerned dams. In this study, the PMP estimations are applied using comparison of both statistical method by Hershfield and National Hydraulic Research Institute of Malaysia (NAHRIM) Envelope Curve as input for PMF establishments. Since the PMF is derived from the PMP values, the highest design flood standard can be applied to any dam, ensuring inflow into the reservoirs and limiting the risk of dam structural failure. Hydrologic modeling using HEC-HMS provides PMF values for the Batu dam. Based on the results, Batu Dam is found to have 200.6 m³/s spillway discharge capacities. Under PMF conditions, the Batu dam will not face overtopping since the peak outflow of the reservoir level is still below the crest level of the dam. Full article

The coronavirus disease 2019 (COVID-19) pandemic has posed a severe threat to public health and economic activity. Governments all around the world have taken positive measures to, on the one hand, contain the epidemic spread and, on the other hand, stimulate the economy. Without question, tightened anti-epidemic policy measures restrain people’s mobility and deteriorate the levels of social and economic activity. Meanwhile, loose policy measures bring little harm to the economy temporarily but could accelerate the transmission of the virus and ultimately wreck social and economic development. Therefore, these two kinds of governmental decision-making behaviors usually conflict with each other. With the purpose of realizing optimal socio-economic benefit over the full duration of the epidemic and to provide a helpful suggestion for the government, a trade-off is explored in this paper between the prevention and control of the epidemic, and economic stimulus. First, the susceptible–infectious–recovered (SIR) model is introduced to simulate the epidemic dynamics. Second, a state equation is constructed to describe the system state variable—the level of socio-economic activity dominated by two control variables. Specifically, these two variables are the strengths of the measures taken for pandemic prevention and control, and economic stimulus. Then, the objective function used to maximize the total socio-economic benefit over the epidemic’s duration is defined, and an optimal control problem is developed. The statistical data of the COVID-19 epidemic in Wuhan are used to validate the SIR model, and a COVID-19 epidemic scenario is used to evaluate the proposed method. The solution is discussed in both static and dynamic strategies, according to the knowledge of the epidemic’s duration. In the static strategy, two scenarios with different strengths (in terms of anti-epidemic and economic stimulus measures) are analyzed and compared. In the dynamic strategy, two global optimization algorithms, including the dynamic programming (DP) and Pontryagin’s minimum principle (PMP), respectively, are used to acquire the solutions. Moreover, a sensitivity analysis of model parameters is conducted. The results demonstrate that the static strategy, which is independent of the epidemic’s duration and can be easily solved, is capable of finding the optimal strengths of both policy measures. Meanwhile, the dynamic strategy, which generates global optimal trajectories of the control variables, can provide the path that leads to attaining the optimal total socio-economic benefit. The results reveal that the optimal total socio-economic benefit of the dynamic strategy is slightly higher than that of the static strategy. Full article

With the development of rail transit in terms of speed and carrying capacity, train safety problems caused by wheel tread defects and wear have become more prominent. The wheel is an important part of the train, and the wear and defects of the wheel tread are directly related to the safety of the train; therefore, wheel tread testing is a key element of train testing. In phase measuring profilometry (PMP), the virtual sine grating generated by the computer is projected onto the measured wheel tread by a digital projector, and then a camera is used to obtain the modulated deformed grating on the surface of the wheel tread. Next, the wrapped phase is obtained by the improved Stoilov algorithm, and the unwrapped phase is obtained by the phase unwrapped algorithm. Finally, the three-dimensional (3D) profile of the wheel tread is reconstructed. This paper presents an improved Stoilov algorithm based on probability and statistics. Supposing that the probability of real data was the highest, we chose the cosine square matrix value of the phase shift for processing. After ruling out the singular points of large error, we obtained the closest value to the true phase shift using the method of probability and statistics. The experimental results show that this method can effectively restrain the singular phenomenon, and the 3D profile of wheel tread can be reconstructed successfully. Full article

In this study, we compare and analyze the scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), morphometry and cyclic fatigue resistance of Endogal, PathMax, and Smarttrack novel brands of nickel–titanium (NiTi) alloy endodontic files. Material and Methods: Thirty sterile NiTi endodontic rotary files were randomly selected and assigned to one of the following study groups: A: 25.08 F2 Endogal (EDG) (n = 10); B: 25.08 F2 Path Max Pro (PMP) (n = 10); and C: 25.06 Smarttrack (ST) (n = 10). Dynamic cyclic fatigue tests were conducted using a cyclic fatigue device in stainless steel artificial root canal systems with an apical diameter of 250 µm, curvature angle of 60°, radius of curvature of 3 mm, and taper of 6%. Additionally, we analyzed the NiTi endodontic rotary files using EDX, SEM, and morphometry after micro-CT scanning. The results were analyzed using Weibull statistical analysis and ANOVA testing. Results: SEM, EDX, and morphometric analyses showed differences between the three novel brands of NiTi endodontic rotary files. Moreover, statistically significant differences were observed between the number of cycles to failure and time to failure of the three novel brands of NiTi endodontic rotary files (p < 0.001). Conclusions: Smarttrack NiTi alloy endodontic reciprocating files display greater resistance to cyclic fatigue than Endogal and Path Max Pro NiTi alloy endodontic rotary files, due to the reciprocating movement and metallurgical composition. Full article

Chlamydia pecorum is a common gastrointestinal inhabitant of livestock but infections can manifest in a broad array of clinical presentations and in a range of host species. While C. pecorum is a known cause of ovine abortion, clinical cases have only recently been described in detail. Here, the prevalence and sequence types (STs) of C. pecorum in ewes from a property experiencing high levels of perinatal mortality (PNM) in New South Wales (NSW), Australia, were investigated using serological and molecular methods. Ewes that were PNM+ were statistically more likely to test seropositive compared to PNM− ewes and displayed higher antibody titres; however, an increase in chlamydial shedding from either the rectum, vagina or conjunctiva of PNM+ ewes was not observed. Multilocus sequence typing (MLST) indicated that C. pecorum ST23 was the major ST shed by ewes in the flock, was the only ST identified from the vaginal site, and was the same ST detected within aborted foetal tissues. Whole genome sequencing of C. pecorum isolated from one abortion case revealed that the C. pecorum plasmid (pCpec) contained a unique deletion in coding sequence 1 (CDS1) that was also present in C. pecorum ST23 shed from the ewes. A further unique deletion was noted in a polymorphic membrane protein gene (pmpG) of the C. pecorum chromosome, which warrants further investigation given the role of PmpG in host cell adherence and tissue tropism.This study describes novel infection parameters in a sheep flock experiencing C. pecorum-associated perinatal mortality, provides the first genomic data from an abortigenic C. pecorum strain, and raises questions about possible links between unique genetic features of this strain and C. pecorum abortion. Full article

The focus of this research is to develop a general method for estimation of rain intensity for application in various geographical regions. In a world with a changing climate, a high importance is attributed to the potential threats caused by increased temperature and rainfall intensity levels. The rainfall intensity climate is here interpreted by a combination of cloud physical factors affecting rain intensity and further developed by the use of climate data and rain intensity statistics. A formula was developed that estimates extreme rainfall and the frequency of these extremes with durations in the intervals of 5 min to 24 h. The obtained estimates are compared in this article with results from statistical methods for the extreme value analysis of measurements. The comparison shows about 90% of the explained variance. The coefficients in the formula are connected with climatological predictors based on the climatological norms of temperature and rainfall. Rain intensity maps over Sweden were produced using the developed formula. Examples of the function of the formula are also given for six European countries. The application of the formula in connection with the probable maximum precipitation (PMP) is presented, where the return period of extreme rainfall is a key factor. The formula is tested with an assumed increased warming of the atmosphere of 1 to 5 °C, and the result indicates an increase of 5.9% of the rainfall amount per each warming degree in intense rainfall. Full article

Background: An abnormal faecal microbiota could be a causal factor for disease. This study evaluated a new method for faecal microbiota analysis in subjects with obesity and irritable bowel syndrome. Methods: The study had a matched case-control design. Forty-six subjects with morbid obesity (defined as BMI > 40 or >35 kg/m² with obesity-related complications) of whom 23 had irritable bowel syndrome (IBS), were compared with 46 healthy volunteers. The faecal microbiota was analysed with Precision Microbiome Profiling (PMP™) which quantified 104 bacteria species. The primary aim was comparisons between the cases and controls. Results: Two men and 44 women with a mean age of 43.6 years were included in each of the groups; BMI in the groups was (mean and SD) 41.9 (3.5) and 22.5 (1.5) kg/m², respectively. Seventeen bacterial species showed statistically significant differences between the groups after adjusting for multiple testing. In a post hoc analysis, the sensitivity and specificity were 78%. Alpha diversity was lower in the group with obesity. In subjects with morbid obesity, no clinically significant differences were seen between subjects with and without IBS or from before to six months after bariatric surgery. Conclusions: The results encourage further evaluation of the new microbiome profiling tool. Full article

The relative contribution of brake emissions to traffic-induced ambient Particulate Matter (PM) concentrations has increased over the last decade. Nowadays, vehicles’ brakes are recognised as an important source of non-exhaust emissions. Up to now, no standardised method for measuring brake particle emissions exists. For that reason, the Particle Measurement Programme (PMP) group has been working on the development of a commonly accepted method for sampling and measuring brake particle emissions. The applied braking cycle is an integral part of the overall methodology. In this article, we present the results of an interlaboratory study exploring the capacity of existing dynamometer setups to accurately execute the novel Worldwide Harmonised Light-Duty Vehicles Test Procedure (WLTP)–brake cycle. The measurements took place at eight locations in Europe and the United States. Having several dynamometers available enabled the coordination and execution of the intended exercise, to determine the sources of variability and provide recommendations for the correct application of the WLTP–brake cycle on the dyno. A systematic testing schedule was applied, followed by a thorough statistical analysis of the essential parameters according to the ISO 5725 standards series. The application of different control programmes influenced the correct replication of the cycle. Speed control turned out to be more accurate and precise than deceleration control. A crucial output of this interlaboratory study was the quantification of standard deviations for repeatability (between repeats), sample effect (between tests), laboratory effect (between facilities), and total reproducibility. Three critical aspects of the statistical analysis were: (i) The use of methods for heterogeneous materials; (ii) robust algorithms to reduce the artificial increase in variability from values with significant deviation from the normal distribution; and (iii) the reliance on the graphical representation of results for ease of understanding. Even if the study of brake emissions remained out of the scope of the current exercise, useful conclusions are drawn from the analysis of the temperature profile of the WLTP–brake cycle. Urban braking events are generally correlated to lower disc temperature. Other parameters affecting the brake temperature profile include the correct application of soak times, the temperature measurement method, the proper conditioning of incoming cooling air and the adjustment of the cooling airspeed. Full article

The 5-year survival rate in the early and late stages of ovarian cancer differs by 63%. In addition, a liquid biopsy is necessary because there are no symptoms in the early stage and tissue collection is difficult without using invasive methods. Therefore, there is a need for biomarkers to achieve this goal. In this study, we found blood-based metabolite or protein biomarker candidates for the diagnosis of ovarian cancer in the 20 clinical samples (10 ovarian cancer patients and 10 healthy control subjects). Plasma metabolites and proteins were measured and quantified using mass spectrometry in ovarian cancer patients and control groups. We identified the differential abundant biomolecules (34 metabolites and 197 proteins) and statistically integrated molecules of different dimensions to better understand ovarian cancer signal transduction and to identify novel biological mechanisms. In addition, the biomarker reliability was verified through comparison with existing research results. Integrated analysis of metabolome and proteome identified emerging properties difficult to grasp with the single omics approach, more reliably interpreted the cancer signaling pathway, and explored new drug targets. Especially, through this analysis, proteins (PPCS, PMP2, and TUBB) and metabolites (L-carnitine and PC-O (30:0)) related to the carnitine system involved in cancer plasticity were identified. Full article

Global climate change is a challenge for dairy farming. In this regard, identifying reliable correlations between environmental parameters and animals’ physiological responses is a starting point for the mathematical modeling of their effects on the future welfare and milk production of cows. The aim of the study was to examine the relationship between environmental parameters and the milk production of cows in hot period. Archival data from the Ukrainian Hydrometeorological Center were used to study the state of insolation conditions (IC), wind direction (WD), wind strength (WS), air temperature (AT), and relative humidity (RH). The temperature–humidity index (THI) (Kibler, 1964) and temperature–humidity index in the hangar-type cowshed (THI_CHT) (Mylostyvyi et al., 2019) served as integral indicators of the state of the cowshed’s microclimate. The daily milk yield (DMY), yield of milk fat (MF) and milk protein (MP), and percentage of milk fat (PMF) and protein (PMP) were taken into account by the DairyComp 305 herd management system (VAS, USA). Statistical data processing was performed using the mathematical functions of Microsoft Excel (Microsoft Inc.) and Statistica 10 (StatSoft Inc.). There was a weak correlation between IC and DMY at r = −0.2, between RH and DMY at r = +0.4, and between RH and MF at r = +0.2. Between DMY, MF, MP, and WS made up r = –0.2 to 0.4. Between DMY, MF, MP, and AT made up r = −0.2 to 0.5 (p < 0.05). The effects of weather factors on animal productivity will be the subject of further research. Full article