Cobalt’s pivotal role in global development, especially in lithium-ion batteries, entails driving increased demand and strengthening global trading networks. The production of different waste solutions in metallurgical operations requires the development of an environmentally friendly research strategy. The ultrasonic spray pyrolysis and hydrogen reduction method were chosen to produce nanosized magnetic powders from waste solution based on iron and cobalt obtained during the purification process of used polycrystalline diamond blanks. With specific objectives focused on investigating the impact of reaction temperature and residence time on the morphology, chemical composition, and crystal structure of synthesized nanosized cobalt powders, our research involved 15 experimental runs using two reactors with varying residence times (7.19 s and 23 s) and distinct precursors (A, B, and C). Aerosol droplets were reduced at 600 to 900 °C with a flow rate of 3 L/min of argon and hydrogen (1:2). Characterization via scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and X-ray diffraction revealed that higher temperatures influenced the spherical particle morphology. Altering cobalt concentration in the solution impacted the particle size, with higher concentrations yielding larger particles. A short residence time (7.9 s) at 900 °C proved optimal for cobalt submicron synthesis, producing spherical particles ranging from 191.1 nm to 1222 nm. This research addresses the environmental significance of recovering magnetic particles from waste solutions, contributing to sustainable nanomaterial applications.

The reliable and steady operation of the electrical power system relies heavily on the correct operational status and condition of the high voltage air break disconnector switch. If these switches experience any malfunction, it could result in considerable damage, leading to financial consequences and potential hazards for maintenance staff. This paper presents a design for the acquisition and data analysis to evaluate the state of electric motor drives responsible for activating disconnectors. The approach involves capturing relevant time series of the voltage of the motor power supply and current and deriving meaningful indices to assess their condition. The viability of these concepts is showcased through case studies conducted on a real disconnector switch situated within a substation.

The utmost importance of high voltage circuit breakers in the electrical power grid highlights the essential need for their reliability. To ensure this, accurate condition assessment methods for core components like the main contact system are crucial. Dynamic resistance measurement plays a key role as it assesses arcing contacts' condition without contact chamber disassembly. This paper endeavors to meticulously investigate and illuminate the pertinent indices derived from dynamic resistance measurements and motion trajectory waveforms, showcasing their efficacy through two real-world case studies conducted under varied testing scenarios. The analysis underscores the proposed indices' effectiveness, enhancing comprehension of the arcing contact assessment method.

BACKGROUND Cirrus is an automated risk predictor for breast cancer that comprises texture-based mammographic features and is mostly independent of mammographic density. We investigated genetic and environmental variance of variation in Cirrus. METHODS We measured Cirrus for 3195 breast-cancer-free participants, including 527 pairs of monozygotic (MZ) twins, 271 pairs of dizygotic (DZ) twins, and 1599 siblings of twins. Multivariate normal models were used to estimate the variance and familial correlations of age-adjusted Cirrus as a function of age. The classic twin model was expanded to allow the shared environment effects to differ by zygosity. The single-nucleotide polymorphism (SNP)-based heritability was estimated for a subset of 2356 participants. RESULTS There was no evidence that the variance or familial correlations depended on age. The familial correlations were 0.52(standard error[SE]=0.03) for MZ pairs and 0.16(SE=0.03) for DZ and non-twin sister pairs combined. Shared environmental factors specific to MZ pairs accounted for 20% of the variance. Additive genetic factors accounted for 32%(SE=5%) of the variance, consistent with the SNP-based heritability of 36%(SE=16%). CONCLUSIONS Cirrus is substantially familial due to genetic factors and an influence of shared environmental factors that was evident for MZ twin pairs only. The latter could be due to non-genetic factors operating in utero or in early life that are shared by MZ twins. IMPACT Early-life factors shared more by MZ pairs than DZ/non-twin sister pairs, could play a role in the variation in Cirrus, consistent with early life being recognised as a critical window of vulnerability to breast carcinogens.

This study conducted an initial investigation into the association between ACE gene insertion/deletion (I/D) polymorphisms (rs1799752) and hypertension in the Republic of Srpska, Bosnia and Herzegovina. The study featured two distinct groups, each with 100 subjects, systematically categorized based on hypertension status and gender. DNA was extracted, PCR-amplified, and analyzed by gel electrophoresis. Results revealed a higher prevalence of the DD genotype and the D allele in the hypertensive group, although statistical significance was not observed. The II genotype occurred in 18% of the hypertension group and 21% in the control group. A significant difference was found in allele I frequencies between the two groups (p=0.004), with no gender-related variations in ACE alleles. The limited sample size may have constrained the ability to detect statistically significant differences. The odds ratio for the (DD + ID) genotype compared to II was 1.2110 (95% CI: 0.6006 to 2.4418; p=0.5927), indicating no statistical significance. Furthermore, no significant associations were identified between ACE genotypes and alleles and gender. In summary, this preliminary study suggests a potential trend towards a higher prevalence of the ACE gene D allele and DD genotype in hypertensive individuals. However, due to the small sample size, these associations did not achieve statistical significance in this population. Larger-scale investigations are needed for more definitive insights into the relationship between ACE gene polymorphisms and hypertension.

Clear cell renal cell carcinoma (ccRCC) is the most common form of kidney cancer, but a comprehensive description of its genomic landscape is lacking. We report the whole genome sequencing of 778 ccRCC patients enrolled in the 100,000 Genomes Project, providing the most detailed somatic mutational landscape to date. We identify new driver genes, which as well as emphasising the major role of epigenetic regulation in ccRCC highlight additional biological pathways extending opportunities for drug repurposing. Genomic characterisation identified patients with divergent clinical outcome; higher number of structural copy number alterations associated with poorer prognosis, whereas VHL mutations were independently associated with a better prognosis. The twin observations that higher T-cell infiltration is associated with better outcome and that genetically predicted immune evasion is not common supports the rationale for immunotherapy. These findings should inform personalised surveillance and treatment strategies for ccRCC patients.

In the literature, auditory attention is explored through neural speech tracking, primarily entailing modeling and analyzing electroencephalography (EEG) responses to natural speech via linear filtering. Our study takes a novel approach, introducing an enhanced coherence estimation technique that employs multitapers to assess the strength of neural speech tracking. This enables effective discrimination between attended and ignored speech. To mitigate the impact of colored noise in EEG, we address two biases – overall coherence-level bias and spectral peak-shifting bias. In a listening study involving 32 participants with hearing impairment, tasked with attending to competing talkers in background noise, our coherence-based method effectively discerns EEG representations of attended and ignored speech. We comprehensively analyze frequency bands, individual frequencies, and EEG channels. Frequency bands of importance are shown to be delta, theta and alpha, as well as the central EEG channels. Lastly, we showcase coherence differences across different noise reduction settings implemented in hearing aids, underscoring our method’s potential to objectively assess auditory attention and enhance hearing aid efficacy.

This paper is about the parameter identification of an energy based hysteresis model from measurements by employing automatic differentiation and neural networks. We first introduce the energy based hysteresis model and the parameters which are to be identified. Then we show how the model can benefit from automatic differentiation. After that we incorporate a parametrization of the energy based hysteresis model via distribution functions and identify the parameters of the distribution function. Then, the hysteresis model is sampled and the generated datasets are used to train neural networks to predict the hysteresis parameters. The described methods are tested and verified on synthetic as well as measurement data.

Future self-perceptions seem to promote far-sighted decisions in intertemporal choices. Previous work suggested that future self-relatedness, the extent to which we feel similar and connected to our future self, is associated with moral concerns. We aimed to extend these findings to everyday moral judgments and behavior using experience sampling methods. In addition, we assessed how moral foundation concerns mediate the relationship between future self-relatedness and moral behavior. Participants (N = 151) reported their state-levels of future self-relatedness, individualizing, and binding moral foundations and answered whether they performed a moral action five times a day for seven days. Within- and between-participants future self-relatedness predicted daily fluctuations in individualizing and binding moral foundations concerns. On the behavioral level, only within-participants future self-relatedness predicted individualizing moral actions with individualizing moral foundations mediating this effect. Our findings suggest that within- and between-person changes in future self-relatedness might be used to predict everyday moral concerns and behavior.

Background/Aim: Most scoring systems in healthcare take into account the physical condition and pain status of a patient, but the impact of society on the individual is ignored. The aim of our study was to evaluate the social media posts made by patients regarding lumbar discectomy surgery. The objective was to identify and explore concerns and issues that may not be immediately evident during clinical evaluations but are significant to the patients themselves. Methods: Public posts with the hashtags #discectomy, #lumbardisectomy, and #discectomyrecovery were examined on the Instagram application. The tone of the post, return to sports (RTS), rehabilitation or physical therapy (PT), return to work (RTW), incision site (e.g., scarring, sutures, and dressing), pain, activities of daily living (ADL), and X-ray/magnetic resonance imaging (MRI) data were evaluated. The "Instagram likes ratio" was determined by dividing the total number of likes received for each post by the number of followers. Results: 272 posts were assessed, and 77.9% of them exhibited a positive tone. The topic that was most frequently discussed was ADL, which was discussed in 24.6% of the posts. Statistical analysis demonstrated a significant association between positive tone and ADL, as well as positive tone and RTS (P<0.001). A statistically significant correlation was observed between negative tone and neurological deficits, pain, and X-ray/MRI findings (P<0.001). Conclusion: Our study offers a unique perspective on the experience and satisfaction of patients who have undergone lumbar discectomy. Neurologic deficits and pain were notably significant in the negative posts. However, in general, the majority of the posts maintained a positive tone. The results could provide insights into patients' experiences and perspectives that can potentially inform healthcare professionals in providing more comprehensive and patient-centered care.

Traditional dairy products, especially cheeses, represent part of the cultural food heritage of many countries. In addition, these cheeses constitute microbiological “reservoirs”, of which many have been lost due to the introduction of the pasteurization of milk in the dairy industry. Increased awareness of the importance of microorganisms that make up the biodiversity of traditional cheeses, as well as the development of molecular methods in recent decades, have enabled efforts to identify and preserve them. Traditional Livno cheese is a full-fat hard cheese, considered one of the most famous traditional cheeses of Bosnia and Herzegovina and is seasonally produced from a mixture of raw sheep’s milk supplemented with cow’s milk. Often, Livno cheese has variable quality, due to microbial contamination and poor milk quality. In this study, traditional Livno cheese was studied during the ripening of cheeses produced by different producers during two seasons. Culture-dependent analyses were made during ripening using microbiological plating on suitable media. Likewise, culture-independent methods Denaturing Gradient Gel Electrophoresis (DGGE) and Automated Ribosomal Intergenic Spacer Analysis (ARISA) were used to elucidate the cheese microbiota. Results of analysis showed Lactococcus spp., Streptococcus spp., Lactobacillus spp., Pediococcus spp. and Leuconostoc spp. to be dominant species in traditional Livno cheese. However, when comparing the use of culture-dependent and culture-independent methods in the evaluation of Livno cheese microbiota, Enterococcus was not detected by culture-independent DGGE methods. The microbial population of both the milk and the environment determines the fermentation processes during cheese production and ripening, and thereby defines the quality of this cheese. The numbers of bacteria in the cheese were shown to be dependent on the manufacturer, the degree of ripening and the production season.

PAPA syndrome (Pyogenic Arthritis, Pyoderma gangrenosum and Acne) is an autosomal dominant, hereditary autoinflammatory disease resulting from mutations in the PstPiP1/Cd2BP1 gene on chromosome 15q. The disease begins in childhood, most often from the age of 2 to 11, and it is characterised by a triad of symptoms: pyogenic (sterile) arthritis, pyoderma gangrenosum and acne. The disease usually begins with arthritis and is rarely recognised in the initial stage. The appearance of skin symptoms of the disease, either acne or pyoderma gangrenosum, along with the previously existing arthritis, should arouse suspicion of the existence of PAPA syndrome and direct doctors to perform further genetic testing. The triad of symptoms does not always have to be present, but the presence of two of the three symptoms with a confirmed gene mutation is a sufficient criterion for the diagnosis of the disease. Biological drugs have shown the greatest effectiveness in treatment, and il1 inhibitors or tnF alpha inhibitors are most often used medications. in later life, the joint manifestations gradually calm down, but the skin manifestations can last for many years with frequent relapses and remissions even with applied therapy, which makes this syndrome a great challenge for the treatment of this disease. Considering the small number of cases with PAPA syndrome described in the literature, we present to you an interesting case of a twenty-five-year-old patient with this disease and his challenging diagnostic and therapeutic path from childhood to adulthood.

In the last years, Deep learning (DL) has become an active research topic in the field of medical image analysis, in particular for the automatic segmentation of pathological volumes. In order to develop a robust and generalizable system, it is of crucial importance to define the most suitable training set, according to both the model and the aim. Nevertheless, there are still no common guidelines specifying the most appropriate sampling and dimensionality of the set. The aim of the study is to assess how different sampling methods, e.g., stratified and random, and different sizes of the training set affect the performances of DL models for automatic segmentation. All DL algorithms were based on a U-Net structure and were trained using a real-world multi-center and multi-scanner pelvic MRI database. The performances were evaluated and compared using the Dice Similarity Coefficient between manual and automatic masks and the number of false negatives obtained by the different algorithms. Our results suggest that if the size of the training set is sufficiently large, using a stratified approach based on dendrograms does not strongly affect the performances of the nets, otherwise leads to higher results. Further analysis is needed using different stratification methods and sample sizes.

ABSTRACT Introduction Refractory status epilepticus (RSE) is a diagnosis that can be made when tonic-clonic status epilepticus (SE) and focal SE cannot be stopped by at least two anti-seizure medications after 30 and 60 minutes, respectively, from the time of commencement. It could result in mortality, loss of functionality, neurological deficiency, and other serious short- and long-term effects. Areas covered This narrative review covers original clinical studies of any design and case series investigating long-term outcomes of RSE recorded after at least a year from the SE onset. Expert opinion The future of a patient with RSE rests mostly on the long-term effects of this severe pathological condition, which may be accompanied with systemic complications like hyperthermia, hyperkalemia, acidosis, and/or stress cardiomyopathy. Younger patients with less severe RSE of shorter duration, particularly of the convulsive kind, are reported to have better long-term outcomes. Previous studies on the factors influencing the long-term outcomes of RSE, however, did not link the outcomes to treatment options for the condition. Such circumstances currently prevent making any definitive recommendations on the treatment of RSE until future research with adequate statistical power is completed.