Abstract Lipofibromatosis (LF) is a rare benign fibrofatty tumor of infancy and childhood with a predilection for distal extremities, poor margination, and a high local recurrence rate. We report a toddler who presented with an LF involving her right labiocrural fold. Imaging showed a soft tissue mass extending through the right labiocrural fold with possible infiltration into the underlying muscles. The mass was excised entirely, preserving adjacent structures. The histopathologic report revealed the mass to be LF. A 3-year follow-up revealed no disease recurrence. No other cases of LF in this localization have been presented in the literature. Despite its rarity, LF should be considered in diagnosing soft tissue neoplasms in children. Accurate diagnosis and proper surgical management with complete resection are essential to reduce the postoperative recurrence risk.

The COVID-19 pandemic negatively influenced individuals’ physical activity levels (PALs) and particularly the PAL of the elderly. However, few studies have examined the correlates of PALs in this population during the pandemic. This study aimed to evaluate the residence-specific correlates of PALs in elderly people from Croatia and Bosnia and Herzegovina during the COVID-19 pandemic. The participants were 211 persons older than 65 years (101 females), of whom 111 were community-dwelling residents, and 110 were nursing home residents (71.11 ± 3.11 and 72.22 ± 4.01 years of age, respectively; t-test = 0.91, p < 0.05). The variables included health status, residential status sociodemographic factors, anthropometrics (body mass, height, and body mass index), and PAL. PAL was evaluated using a translated version of the Physical Activity Scale for the Elderly (PASE), and was validated in this study. PASE showed good test–retest reliability (51% of the common variance) and validity (57% of the common variance, with the step count measured using pedometers). Apart from participants’ health status and age, PAL was positively correlated with (i) community-dwelling residence (OR = 1.93, 95% CI: 1.60–2.23), and (ii) a lower BMI (OR = 0.85, 95% CI = 0.71–0.98). The pre-pandemic physical activity was positively correlated with the PAL of the nursing home residents (OR = 1.2, 95% CI: 1.02–1.45). A higher education level was positively correlated with the PAL of community-dwelling residents (OR = 1.31, 95% CI: 1.04–1.66). This study evidenced the residence-specific correlates of PALs, and enabled the identification of specific groups that are at risk of having low PALs during the pandemic. Future studies examining this problem during a non-pandemic period are warranted.

In this study, we propose an eco-friendly method for synthesizing cerium tungstate nanoparticles using hydrothermal techniques. We used scanning, transmission electron microscopy, and X-ray diffraction to analyze the morphology of the synthesized nanoparticles. The results showed that the synthesized nanoparticles were uniform and highly crystalline, with a particle size of about 50 nm. The electrocatalytic properties of the nanoparticles were then investigated using cyclic voltammetry and electrochemical impedance spectroscopy. We further used the synthesized nanoparticles to develop an electrochemical sensor based on a carbon paste electrode that can detect hydroquinone. By optimizing the differential pulse voltammetric method, a wide linearity range of 0.4 to 45 µM and a low detection limit of 0.06 µM were obtained. The developed sensor also expressed excellent repeatability (RSD up to 3.8%) and reproducibility (RSD below 5%). Interferences had an insignificant impact on the determination of analytes, making it possible to use this method for monitoring hydroquinone concentrations in tap water. This study introduces a new approach to the chemistry of materials and the environment and demonstrates that a careful selection of components can lead to new horizons in analytical chemistry.

Education and employment stakeholders worldwide have increasingly acknowledged the need to teach students soft skills to improve their academic performance and long-term prospects. Soft skills are transferable across jobs and industries and related to personal and social competencies. Their development aims to empower and increase personal growth and learning participation and improve job opportunities. Given their central role in shaping students’ educational experiences, teachers must be well-versed in the value of cultivating soft skills and awareness of the necessity to incorporate their study into various curricular frameworks. As a result, this article investigates whether business schools adequately prepare their students for the soft skills demanded by today’s labor market. Business teachers in Bosnia and Herzegovina were the subjects of the survey. The findings indicate that teachers recognize the value of teaching students soft skills but that current curricula may be strengthened in this area.

While clear cell renal cell carcinoma (ccRCC) is curable, advanced metastatic (mRCC) remains a clinical challenge. We analyzed clinical, pathohistological, and molecular data (Receptor Interacting Protein 5—RIP5 and Vestigial Like Family Member 4—VGLL4 expression) of 55 mRCC patients treated with first-line treatment with sunitinib. The trend of linear increase in the protein expression of RIP5 was observed with the progression of tumor grade. Overall, 80% of RIP5-positive cells were in the control kidneys and high-grade mRCC. On the contrary, RIP5 displayed low expression in grade 2 mRCC (5.63%). The trend of linear decrease in the expression of VGLL4 was observed with the progression of tumor grade. The highest protein expression of VGLL4 was observed in grade 2 (87.82%) in comparison to grade 3 and 4 and control. High expression of RIP5 mRNA was associated with longer first-line overall survival and longer progression-free survival in mRCC. In addition, a high VGLL4 mRNA expression showed better overall survival in patients with ccRCC. In conclusion, high mRNA expression of RIP5 and VGLL4 are important markers of better survival rates in mRCC patients.

Abstract Chenopodium ambrosioides, a member of the Chenopodiaceae family, is renowned for its toxic properties. Despite its toxicity, it has been traditionally utilized in various communities, particularly in pediatric contexts, for its vermifuge, antispasmodic, and antipyretic attributes. This study aims to unravel the phytochemical composition present in organic fractions and aqueous extracts obtained from the aerial components of C. ambrosioides. Furthermore, our objective is to evaluate the antioxidant activity of these extracts and fractions, coupled with a comprehensive examination of their toxicological effects. Polyphenols were quantified using the Folin–Ciocalteu reagent, flavonoids via the aluminum trichloride reagent AlCl3, and tannins using the vanillin method. Identification of bioactive compounds within the plant specimen was accomplished through GC-MS spectrophotometric analysis. The assessment of antioxidant activity employed DPPH, ferric (Fe3+) ion antioxidant reducing power (FRAP), ABTS, and TAC methods, with quercetin, catechin, and ascorbic acid serving as standards. Dermoprotective activity was studied using the ultraviolet absorption test. The GC-MS analysis conducted on the aqueous extracts (EAI and EAM) and assorted fractions (FCH, FE, FB, and FA) revealed the presence of diverse chemical families encompassing alcohols, acids, terpenes, steroids, and phenolic compounds. The components identified in the investigated samples, including trans-ascaridol glycol, palmitic acid, phenol, octadecadienoic acid, isoascaridol, eicosanoic acid, 2-methoxy-4-vinyl phenol, mexiletine, and thymol, are postulated as potential contributors to the observed antioxidant activity inherent in the plant extracts and fractions. Our findings highlight the remarkable antioxidant potential of Chenopodium ambrosioides, with the ethyl acetate fraction exhibiting the highest activity (IC50 = 0.54 mg/ml) in the DPPH test. In the FRAP and ABTS tests, the n-butanolic and ethyl acetate fractions demonstrated superior activity (IC50 = 4.43 mg/ml, 12.9 mg/ml and IC50 = 1.6 mg/ml, 4.54 mg/ml, respectively). Conversely, the TAC test revealed that the macerated aqueous extract displayed the highest activity (316.33 mg Eq AG/g), followed closely by the n-butanolic fraction (250.67 mg Eq AG/g). These outcomes can be attributed to the abundant presence of phenolic compounds in the n-butanolic and ethyl acetate fractions, as well as the macerated aqueous extract, playing a pivotal role in the observed antioxidant activity. Additionally, our investigation of the dermoprotective activity demonstrated robust efficacy in the ethyl acetate fraction (FE) and the n-butanolic fraction (FB) compared to the standard agents employed (ZnO and methyl salicylate). Overall, our comprehensive studies affirm that the extracts and fractions derived from C. ambrosioides manifest moderate antioxidant activities alongside significant dermoprotective potential, elucidated by the presence of phenolic compounds in moderate quantities within the plant.

Does climate change influence if societies will be better or worse equipped to reduce climatic risks in the future? A society’s adaptive capacity determines whether the potential of adaptation to reduce risks will be realized. Assumptions about the level of adaptive capacity are inherently made when the potential for adaptation to reduce risks in the future and resultant levels of risk are estimated. In this review, we look at the literature on human impacts of climate change through the lens of adaptive capacity. Building on evidence of impacts on financial resources as presented in the Working Group 2 (WG2) report of the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6), we here present the methodology behind this review and complement it with an analysis of climatic risks to human resources. Based on our review, we argue that climate change itself adds to adaptation constraints and limits. We show that for more realistic assessments of sectoral climate risks, assumed levels of future adaptive capacity should — and can — be usefully constrained in assessments that rely on expert judgment, and propose avenues for doing so.

This article proposes a new framework of aerial reconfigurable intelligent surface (ARIS) enhancing the nonorthogonal multiple access (NOMA) system. The base station (BS) transmits superimposed signals to multiple users with different channel gains through ARIS which can flexibly change channel conditions and perform intelligent NOMA operations. It ensures that our system can perform well in providing services to multiple users simultaneously. In this system, the placement of the unmanned aerial vehicle (UAV) is jointly optimized along with the AIRS passive beam and the multiuser power allocation in order to maximize the communication sum rate. Since the joint optimization problem is nonconvex and coupled, it is hence disintegrated into three subproblems and it is solved alternately through the successive convex approximation (SCA). Moreover, semi definite programming (SDP) is used to deal with the rank one constraint of RIS reflection matrix and comparisons are made using particle swarm optimization (PSO). The numerical results show that the proposed ARIS-NOMA framework can achieve better sum rate performance than traditional NOMA with fixed RIS and OMA-ARIS.

The cryptocurrency market has attracted considerable attention from investors and researchers alike. This paper examines the volatility patterns of two major cryptocurrencies utilizing GARCH modeling: Bitcoin, based on a proof-of-work mechanism, and Cardano, operating on a proof-of-stake mechanism. Our findings reveal differences in the volatility structures of the two cryptocurrencies, with Cardano demonstrating a reduced long-term volatility compared to Bitcoin. This study suggests that transitioning from proof-of-work to proof-of-stake mechanisms might lead to a decrease in market volatility.

Abstract The olive trituration activity is one of the most important industrial activities in Fez, Morocco. These effluents are highly loaded with organic, inorganic, and phenolic compounds without any preliminary treatment that affects water quality. In this sense, the waters of Oued Fez are deteriorating due to the discharge of wastewater from oil mills and the excessive proliferation of Pistia stratiotes L., an invasive macrophyte that represents a significant stress to the aquatic ecosystem, eutrophication, and a reduction in biodiversity. This ecological situation has prompted us to carry out phytotoxicity bioassays based on the detection of the lethal concentration of P. stratiotes in the wastewater from the olive oil mill to evaluate the sensitivity and tolerance of macrophytes to the different concentrations of total polyphenols (TPP) present in the olive mill wastewater. To estimate their impact on the environment. Fresh whole plants of P. stratiotes were exposed to varying concentrations of olive oil mill wastewater with a series of TPP concentrations (0–30 mg/l) for 1 week in the natural environment. The results also show that P. stratiotes is able to grow rapidly in culture with 20 mg/l of TPP; the highest growth of wet weight of P. stratiotes occurred at 20 mg/l treatment with an average of 13 g wet weight increase. At 0 mg/l, treatment is known to cause very slow growth with an average of 2 g. Olive oil mill wastewater was toxic to the plant at concentrations higher than 30 mg/l, and the phytotoxic effect was manifested by retardation of growth, detachment of roots, wilting, and chlorosis of leaves. This indicates that polyphenols have great potential to inhibit the proliferation of P. stratiotes in aquatic environments.

Introduction: There is considerable concern with rising rates of antimicrobial resistance (AMR) with its subsequent impact on morbidity, mortality and costs. In low- and middle-income countries, a key driver of AMR is the appreciable misuse of antibiotics in ambulatory care, which can account for up to 95% of human utilisation. A principal area is the selling of antibiotics without a prescription. There is conflicting evidence in South Africa regarding this practice alongside rising AMR rates. Consequently, there is a need to explore this further, especially in more rural areas of South Africa. A pilot study was undertaken to address this. Materials and Methods: A two-step descriptive approach involving a self-administered questionnaire amongst pharmacists and their assistants followed by cognitive interviews with some of the participants. Results: Twenty-one responses were obtained from nine of the 11 community pharmacies invited to participate. Participating pharmacies were all independently owned. Ten of the 21 participants admitted dispensing antibiotics without a prescription, including both adults and children, representing five of the nine participating pharmacies. A minority dispensed antibiotics before recommending suitable over-the-counter medicines. These high rates were exacerbated by patient pressure. There were issues with the length of the questionnaire and some of the phraseology, which will be addressed in the main study. Conclusion: There were concerns with the extent of purchasing antibiotics without a prescription in this pilot in South Africa study. Key issues will be explored further in the main study.

The increasing prevalence of colon and lung cancer presents a considerable challenge to healthcare systems worldwide, emphasizing the critical necessity for early and accurate diagnosis to enhance patient outcomes. The precision of diagnosis heavily relies on the expertise of histopathologists, constituting a demanding task. The health and well‐being of patients are jeopardized in the absence of adequately trained histopathologists, potentially leading to misdiagnoses, unnecessary treatments, and tests, resulting in the inefficient utilization of healthcare resources. However, with substantial technological advancements, deep learning (DL) has emerged as a potent tool in clinical settings, particularly in the realm of medical imaging. This study leveraged the LC25000 dataset, encompassing 25,000 images of lung and colon tissue, introducing an innovative approach by employing a self‐organized operational neural network (Self‐ONN) to accurately detect lung and colon cancer in histopathology images. Subsequently, our novel model underwent comparison with five pretrained convolutional neural network (CNN) models: MobileNetV2‐SelfMLP, Resnet18‐SelfMLP, DenseNet201‐SelfMLP, InceptionV3‐SelfMLP, and MobileViTv2_200‐SelfMLP, where each multilayer perceptron (MLP) was replaced with Self‐MLP. The models’ performance was meticulously assessed using key metrics such as precision, recall, F1 score, accuracy, and area under the receiver operating characteristic (ROC) curve. The proposed model demonstrated exceptional overall accuracy, precision, sensitivity, F1 score, and specificity, achieving 99.74%, 99.74%, 99.74%, 99.74%, and 99.94%, respectively. This underscores the potential of artificial intelligence (AI) to significantly enhance diagnostic precision within clinical settings, portraying a promising avenue for improving patient care and outcomes. The synopsis of the literature provides a thorough examination of several DL and digital image processing methods used in the identification of cancer, with a primary emphasis on lung and colon cancer. The experiments use the LC25000 dataset, which consists of 25,000 photos, for the purposes of training and testing. Various techniques, such as CNNs, transfer learning, ensemble models, and lightweight DL architectures, have been used to accomplish accurate categorization of cancer tissue. Various investigations regularly show exceptional performance, with accuracy rates ranging from 96.19% to 99.97%. DL models such as EfficientNetV2, DHS‐CapsNet, and CNN‐based architectures such as VGG16 and GoogleNet variations have shown remarkable performance in obtaining high levels of accuracy. In addition, methods such as SSL and lightweight DL models provide encouraging outcomes in effectively managing large datasets. In general, the research emphasizes the efficacy of DL methods in successfully diagnosing cancer from histopathological pictures. It therefore indicates that DL has the potential to greatly improve medical diagnostic techniques.