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.

During the COVID pandemic, research has shown an increase in candidemia cases following severe COVID infection and the identification of risk factors associated with candidemia. However, there is a lack of studies that specifically explore clinical outcomes and mortality rates related to candidemia after COVID infection.

Understanding the concepts related to real function is essential in learning mathematics. To determine how students understand these concepts, it is necessary to have an appropriate measurement tool. In this paper, we have created a web application using 32 items from conceptual understanding of real functions (CURF) item bank. We conducted a psychometric analysis using Rasch model on 207 first-year students. The analysis showed that CURF is a dependable and valid instrument for measuring students’ CURF. The test is uni-dimensional; all items are consistent with the construct and have excellent item fit statistics. The results indicate that the items are independent of each other and unbiased towards the gender and high school background of the students.

Simple Summary Innovations in the value chain of traditional meat products, leading to higher quality or healthier products, can support the niche market for local pig breeds and contribute to their more sustainable conservation. In this context, the present study investigated whether the quality traits of smoked dry-cured ham derived from the local Turopolje pig could be improved by including acorns in the animal’s diet or by innovations in processing methods, such as smoke reduction. The results show that feeding acorns to pigs increased the processing yield but had a limited effect on the quality of the dry-cured ham, as only a few differences in the physicochemical, textural or colour parameters and volatile profile were observed. However, some sensory attributes, such as odour typicality, were affected by the acorn diet. Conversely, this innovation in processing led to a significant reduction in smoke-derived volatile compounds and an improved texture to the lightly smoked hams, as shown by both instrumental and sensory analysis. Abstract The Turopolje pig (TP) is a local Croatian pig breed that almost became extinct in the second half of the 20th century. Today, the TP is still endangered, and a new conservation strategy based on products with higher added value is needed to preserve the breed. There is little information on the quality of TP meat products such as smoked and dry-cured ham, including the impact of natural feeds or processing innovations such as smoke reduction. This study, therefore, investigated the effects of the animal’s diet (either conventionally fed or acorn-supplemented) and the processing method (standard or lightly smoked) on the quality traits of dry-cured TP ham. Twenty hams, evenly distributed among the treatments, were processed for 15 months and then analysed for physicochemical and textural traits, volatiles and sensory profile. The hams from acorn-supplemented pigs lost less weight during processing (p ≤ 0.05). Otherwise, the diet had no significant effect on most examined ham traits. The exceptions were protein content and the texture parameter hardness, which decreased (p ≤ 0.05), and the degree of proteolysis and colour parameters, which increased (p ≤ 0.05) as a result of acorn supplementation. However, these effects were generally small and varied between the inner (m. biceps femoris) and outer (m. semimembranosus) muscles. Furthermore, acorn supplementation was associated with less typical ham odour and lower sensory scores for sweetness and colour uniformity (p ≤ 0.05). The smoke reduction had no effect on the physicochemical and colour properties but resulted in a significant reduction (p ≤ 0.05) in the volatile phenolic compounds and an improved texture to the hams. This was reflected both in reduced (p ≤ 0.05) hardness, identified in the instrumental analysis, and in an increased (p ≤ 0.05) softness, solubility and moistness, identified in the sensory evaluation. To summarize, the quality of the TP ham under the conditions studied was only slightly affected by acorn supplementation, whereas reduced smoking had a more significant effect, which was mainly reflected in an improved texture.

Financial performance analysis is of vital importance those involved in a business (e.g., shareholders, creditors, partners, and company managers). An accurate and appropriate performance measurement is critical for decision-makers to achieve efficient results. Integrated performance measurement, by its nature, consists of multiple criteria with different levels of importance. Multiple Criteria Decision Analysis (MCDA) methods have become increasingly popular for solving complex problems, especially over the last two decades. There are different evaluation methodologies in the literature for selecting the most appropriate one among over 200 MCDA methods. This study comprehensively analyzed 41 companies traded on the Borsa Istanbul Corporate Governance Index for 10 quarters using SWARA, CRITIC, and SD integrated with eight different MCDA method algorithms to determine the position of Turkey's most transparent companies in terms of financial performance. In this study, we propose "stock returns" as a benchmark in comparing and evaluating MCDA methods. Moreover, we calculate the "rank reversal performance of MCDA methods". Finally, we performed a "standard deviation" analysis to identify the objective and characteristic trends for each method. Interestingly, all these innovative comparison procedures suggest that PROMETHEE II (preference ranking organization method for enrichment of evaluations II) and FUCA (Faire Un Choix Adéquat) are the most suitable MCDA methods. In other words, these methods produce a higher correlation with share price; they have fewer rank reversal problems, the distribution of scores they produce is wider, and the amount of information is higher. Thus, it can be said that these advantages make them preferable. The results show that this innovative methodological procedure based on 'knowledge discovery' is verifiable, robust and efficient when choosing the MCDA method.

Abstract The impact of logistics performance in the era of sustainable mobility on the overall economic development of a country is inevitable. It can even be said to represent an extremely important component in identifying economic conditions and provides the possibility of defining adequate strategies. In this article, the evaluation of the member countries of the European Union was carried out on the basis of the logistics performance index (LPI) according to the latest report of the World Bank (WB). A unique and original Multiple-Criteria Decision Making (MCDM) approach has been created, and it involves the application of four methods: Criteria Importance Through Intercriteria Correlation, Method based on the Removal Effects of Criteria, and Entropy and Fuzzy ROV (Range of Value). The weighting coefficients of six factors were obtained with the first three methods in crisp form, so they were converted into Triangular Fuzzy Number. The Fuzzy ROV method has been created for the first time in the literature and represents a great contribution from the methodological aspect. The results of the developed model and the applied steps show that there are certain differences in the rankings compared to the World Bank report, with a note that the best-ranked countries have maintained their positions. In addition, verification tests of the originally obtained results were created, with an emphasis on the importance of evaluation parameter values and their impact on the LPI ranking.

Narcissus poeticus L. (Amaryllidaceae), a facultative serpentinophyte, is a highly variable species and particularly important ancestor of cultivated daffodils, but is rarely studied in field populations. This study, based on natural populations in the Balkans, focused on karyotype variability, genome size, ploidy and the presence of B chromosomes. Thirteen native populations from different environmental and soil conditions were collected and analyzed using flow cytometry to estimate nuclear genome size, fluorescence in situ hybridization (FISH) for physical mapping of rDNA, fluorochrome labeling (chromomycin and Hoechst) for heterochromatin organization and silver nitrate staining of nucleoli for determining rRNA gene activity. The organization of rDNA and natural triploids is reported here for the first time. The presence of individuals with B chromosomes (in 9/13 populations) and chromosomal rearrangements was also detected. The observed B chromosome showed three different morphotypes. The most frequent submetacentric type showed four different patterns, mainly with active ribosomal genes. The results obtained show that N. poeticus has a dynamic genome with variable genome size due to the presence of polyploidy, B chromosomes and chromosomal rearrangements. It is hypothesized that the observed changes reflect the response of the genome to different environmental conditions, where individuals with B chromosomes appear to have certain adaptive advantages.