The organizational effectiveness of nonprofit organizations (NPOs) has received considerable attention from the scientific research community and society. Nonprofit scholars call for more empirical research that tests existing theories and develops multidimensional frameworks at the organizational level, with a focus on actual management practices. Previous studies have suggested that a broad set of management practices at the program and organizational levels have positive implications for the perceived effectiveness of NPOs. This study evaluates and refines a conceptual model of the antecedents of organizational effectiveness and validates its applicability in the context of charitable foundations established by corporations. Based on survey data from their executive leaders, this study’s empirical findings suggest that perceived organizational effectiveness is less affected by a broad set of management practices and is driven by a few selected best practices that focus on specific stakeholder groups (i.e., experts). Moreover, the results show that certain organizational characteristics, such as organizational experience, can strengthen the perceived effectiveness of charitable foundations. Overall, the results of this study may help nonprofit executive leaders to better understand that a careful selection and implementation of specific practices might be more beneficial for an organization’s effectiveness than an extensive list of practices. Moreover, this study contributes on a broader theoretical level to the study of multidimensional frameworks as a suitable measure for identifying key antecedents of leader-perceived organizational effectiveness across different types of NPOs. Full article

MEK inhibitors (MEKi) represent innovative and promising treatments for managing manifestations of neurofibromatosis type 1 (NF1). To mitigate potential ophthalmic side effects, such as MEKi-associated retinopathy (MEKAR), patients undergoing MEKi therapy routinely receive ophthalmology evaluations. Our study aims to assess the necessity of this regular screening within a predominantly pediatric NF1 population by examining the occurrence of ocular adverse events (OAE). A retrospective study evaluated 45 NF1 patients receiving MEKi. Inclusion criteria included baseline and follow-up examinations following the initiation of MEKi therapy. At each assessment, a comprehensive eye evaluation was performed, comprising a dilated fundus examination, ocular coherence tomography of the macula and nerve fiber layer, and Humphrey visual field testing. Twenty-six patients, with an average age of 13 years (range 2–23 years) and an average follow-up duration of 413 days were included in the analysis. Three different MEKi were used: selumetinib (77%), trametinib (23%), and mirdametinib (4%). None of the patients experienced retinopathy at any point during the study. Some patients had pre-existing optic neuropathies (27%), but no instances of nerve changes occurred after commencing MEKi therapy. Four patients (15%) exhibited symptoms of dry eye, all of which were effectively managed with topical lubrication. Full article

In the study of English denominal adjectives, scholarly attention has predominantly centred on those with Latinate suffixes (e.g., -al, -ary, and -ic/-ical), which are well-known as relational adjectives (RAdjs) and are extensively scrutinised in the existing literature. Conversely, those with English native suffixes (e.g., -en, -ern, -y, and -ed) have not undergone thorough examination to date. In the present study, I delve specifically into denominal adjectives with the suffix -ed (-ed Adjs), such as bearded, long-tailed, and shirt-sleeved. I present a novel basic picture of these adjectives, setting forth the following two central propositions: (i) -ed Adjs are a type of RAdj and (ii) undergo conversion to qualitative adjectives (QAdjs) (e.g., bearded man vs. bearded rock) akin to the better-known Latinate RAdjs (e.g., grammatical error vs. grammatical sentence). The analysis is conducted by examining suffixal etymology (i.e., Latinate or Germanic), suffixal properties (i.e., all-purpose or dedicated), and the driving factor for QAdj-forming conversion (i.e., the modal attribute true). These propositions and analyses collectively enrich our comprehensive understanding of the semantic and morphosyntactic properties of -ed Adjs within the realm of English morphology. Full article

Background: Additive manufacturing (AM) for patient-specific medical care products offers great opportunities. However, evidence about the supply chain (SC) performance impact based on empirical data is limited. Methods: In this case study, we gathered real-life data about a traditional manufacturing orthopedic shoe SC and developed future scenarios in which AM is introduced at various points and with different degrees of penetration in the SC. Results: Presently, AM can only replace traditional manufacturing of tools and shoe components at a higher total cost. However, with maturing technology, the complete AM production of orthopedic shoes is expected to become feasible. Theoretically, that could disrupt existing SCs, eliminating 70% of the SC steps, improving SC lead time by 90%, and altering SC relations. However, certain thresholds currently prevent disruption. Specifically, the AM of complete orthopedic shoes has to become possible, manufacturing prices have to drop, and traditional craftsmanship has to be integrated into the digital product design. Conclusions: A framework for transition pathways, including directions for future research, is formed. Findings provide valuable insights for scholars and decision makers in the patient-specific products industry, health insurance providers, and healthcare policy makers to be better prepared by adjusting SC designs, relationships, and remuneration programs while AM technology develops towards maturity. Full article

We studied some fibrotic aspects of chronic interstitial pneumonitis in the lungs of dogs infected with Leishmania infantum. The lungs of eleven naturally infected dogs, twelve experimentally infected with two distinct strains of L. infantum (BH401 and BH46), and six uninfected (controls) dogs, were analyzed by histological, parasitological, and immunohistochemical studies. Conventional histology (HE), collagen deposition (Gomori’s silver staining for reticulin collagen fibers), and immunohistochemistry for myofibroblast characterization were carried out based on the cellular expression of alpha-smooth muscle actin, vimentin, cytokeratin, E-cadherin, snail antigen homologue 1 (SNAI1) (Snail), and the cytokine expression of transforming growth factor-beta (TGF-β). Parasitological screening was carried out using conventional polymerase chain reaction (PCR) and the immunohistochemical reaction of streptavidin–peroxidase for visualizing Leishmania amastigotes. Dogs naturally infected with L. infantum and experimentally infected with L. infantum BH401 strains showed intense interstitial pneumonitis characterized by thickening of the alveolar septa as a consequence of an intense diffuse and focal (plaques) chronic exudate of mononuclear cells associated with fibrogenesis. The expression of alpha-actin, vimentin, and TGF-β was higher in the lung interstitium of all infected dogs than in the other two groups (BH46 strain and controls). Moreover, in both the naturally and experimentally infected dog (BH401 strain) groups, the expression of Snail was moderate to intense in contrast to the other groups. Based on these immunohistochemical results, we concluded that mesenchymal cells are active in promoting changes in the extracellular matrix in the lungs of dogs naturally and experimentally infected with L. infantum, but it depends on the virulence of the parasite. Full article

While digital twins (DTs) have recently gained prominence as a viable option for creating reliable asset representations, many existing frameworks and architectures in the literature involve the integration of different technologies and paradigms, including the Internet of Things (IoTs), data modeling, and machine learning (ML). This complexity requires the orchestration of these different technologies, often resulting in subsystems and composition frameworks that are difficult to seamlessly align. In this paper, we present a scalable compositional framework designed for the development of a DT-based production management system (PMS) with advanced production monitoring capabilities. The conducted approach used to design the compositional framework utilizes the Factory Design and Improvement (FDI) methodology. Furthermore, the validation of our proposed framework is illustrated through a case study conducted in a phosphate screening station within the context of the mining industry. Full article

Understanding pedestrian perceptions and attitudes is crucial for promoting walking as a daily transportation mode for sustainable mobility and the effective development of smart cities. Pedestrian preferences, shaped by factors such as age, gender, and urban infrastructure, play a pivotal role in travel behaviors. Based on a survey study, this paper examines the impact of individual and urban factors on pedestrian perceptions and attitudes towards walking in the cities of Bologna and Porto. Results reveal that individuals generally value short, safe, and green walking routes, appreciating walking for physical activity, cost savings, and time efficiency. Disliked aspects include adverse weather conditions and walking on inadequate sidewalks. Through carrying out Chi-square statistical analysis tests, a variety of significant correlations between individual and urban variables have been revealed on what people like or dislike about walking. For instance, males, young individuals, and students were more likely to prefer short pedestrian routes, while adults and seniors favored safe and green routes. These findings can assist urban planners in identifying factors that make walking both convenient and enjoyable and in supporting sustainable urban mobility policies. Full article

Terraces, farmlands built along hillside contours, are common anthropogenically designed landscapes. Terraces control soil and water loss and improve land productivity; therefore, obtaining their spatial distribution is necessary for soil and water conservation and agricultural production. Spatial information of large-scale terraces can be obtained using satellite images and through deep learning. However, when extracting terraces, accurately segmenting the boundaries of terraces and identifying small terraces in diverse scenarios continues to be challenging. To solve this problem, we combined two deep learning modules, ANB-LN and DFB, to produce a new deep learning framework (NLDF-Net) for terrace extraction using remote sensing images. The model first extracted the features of the terraces through the coding area to obtain abstract semantic features, and then gradually recovered the original size through the decoding area using feature fusion. In addition, we constructed a terrace dataset (the HRT-set) for Guangdong Province and conducted a series of comparative experiments on this dataset using the new framework. The experimental results show that our framework had the best extraction effect compared to those of other deep learning methods. This framework provides a method and reference for extracting ground objects using remote sensing images. Full article

We report the case of a 61-year-old woman who was referred to the Oral Surgery and Implantology Unit of the University Hospitals of Geneva to take care of edentulous sites after the dental avulsions of teeth 11 and 21 following traumatic shock due to endotracheal intubation under general anesthesia. The dental history revealed that the patient had a history of generalized chronic periodontitis that had been treated several years earlier. The treatment consisted, for the first time to our knowledge, of the immediate insertion of implants at sites 11 and 21 with simultaneous bone augmentation in a single surgical procedure and immediate restorations. Full article

The determination of illegal drugs and psychoactive substances in wastewater is increasingly being used to monitor the use of both by populations in specific areas. This article describes a method for the simultaneous determination of 78 illegal drugs and psychoactive substances in wastewater using direct-injection ultra-high-performance liquid chromatography–tandem mass spectrometry (UHPLC-MS/MS). This method includes the analysis of stimulants, opioids, antidepressants, antipsychotic drugs, anti-anxiety drugs, and hallucinogens. The method was validated in terms of the selectivity, calibration range, recovery, matrix effects, accuracy, precision, limit of detection (LOD), and limit of quantification (LOQ). The correlation coefficients were higher than 0.99 for all analytes, and the calibration range was from 0.2 to 500 ng/L. The LOD and LOQ of this method were 0.1–1 ng/L and 0.2–5 ng/L, respectively. The intra- and inter-day precisions were <9.3% and 11.4%, respectively, and the recovery ranged from 81.3% to 117.7%. The method was applied to real domestic wastewater collected from wastewater treatment plants, and the results showed that morphine, codeine, and ephedrine were detected in all samples. Some samples also contained other illegal drugs and psychoactive substances (such as etomidate, methamphetamine, ketamine, and tramadol). This indicates that the direct-injection UHPLC-MS/MS method can be used for the rapid determination of illegal drugs and psychoactive substances in wastewater. Full article

To support the bankability of PV projects, PV manufacturers have been offering some of the longest warranties in the world, typically in the range of 25–30 years. During the warranty period, PV manufacturers guarantee that the degradation of PV modules will not exceed 0.4–0.6% each year, or the buyer can at any time make a claim to the manufacturer for replacement or compensation for the shortfall. Due to PV popularity, the performance warranty terms have become more and more competitive each year. However, long-term PV operating data are very limited, and the bankruptcy of PV manufacturers has been quite common. Without a proper methodology to assess the adequacy of the warranty fund (WF) reserves of PV manufacturers, the 25-year performance warranty can reflect an empty promise. To ensure sustainable development of the PV industry, this study develops a probability-weighted expected value method to determine the necessary WF reserve based on benchmark field degradation data and a prevailing degradation cap of 0.55% per year. The simulation results show that, unless the manufacturer’s degradation pattern is significantly better than the benchmark degradation profile, 1.302% of the sales value is required for the WF reserve. To the best of our knowledge, this is the first study that provides WF reserve requirement estimation for 25-year PV performance warranties. The results will provide transparency for PV investors and motivation for PV manufacturers to engage in continuous quality improvement, as all such achievements can now be reflected in the annual report results of manufacturers. Full article

This experimental study investigates the damage effects of nanosecond pulse laser irradiation on silicon solar cells. It encompasses the analysis of transient pulse signal waveform characteristics at the cells’ output and changes in electrical parameters, such as I–V curves before and after laser irradiation under varying laser fluence and background light intensities, and explores the underlying action mechanisms of laser irradiation. The study reveals that as the laser fluence increases up to 4.0 J/cm², the peak value of the transient pulse signal increases by 47.5%, while the pulse width augments by 88.2% compared to the initial transient pulse signal. Furthermore, certain parameters, such as open-circuit voltage, short-circuit current, and peak power obtained, from the measured I–V curve indicate a threshold laser fluence for functional degradation of the solar cell at approximately 1.18 ± 0.42 J/cm². Results obtained from laser irradiation under different background light intensities underscore the significant influence of background light on laser irradiation of silicon cells, with the most severe damage occurring in the absence of light. Moreover, findings from laser irradiation at multiple locations on the silicon cell demonstrate a linear decrease in the output voltage of the silicon cell with an increase in the number of irradiation points. Full article

A series of novel binuclear PNP ligands based on the cyclohexyldiamine scaffold were synthesized for this study. The experimental results showed that positioning the two PNP sites at the para-positions of the cyclohexyl framework led to a significant enhancement in the catalytic activity for selective tri/tetramerization of ethylene. The PNP/Cr(acac)₃/MAO(methylaluminoxane) catalytic system exhibited relatively high catalytic activity (up to 3887.7 kg·g⁻¹·h⁻¹) in selective ethylene oligomerization with a total selectivity of 84.5% for 1-hexene and 1-octene at 40 °C and 50 bar. The relationship between the ligand structure and ethylene oligomerization performance was further explored using density functional theory calculations. Full article

The photoredox-catalyzed decarboxylative cross-coupling reaction of aryl acetic acids and aryl nitriles has been achieved under an argon atmosphere in high yields. This method provides a fast way to obtain prevalent aryl acetic acids from an abundant natural source. A tentative radical mechanism has been proposed. Full article

The global incidence of Type 2 diabetes (T2D) is on the rise, fueled by factors such as obesity, sedentary lifestyles, socio-economic factors, and ethnic backgrounds. T2D is a multifaceted condition often associated with various health complications, including adverse effects on bone health. This study aims to assess key biomarkers linked to bone health and remodeling—Osteoprotegerin (OPG), Receptor Activator of Nuclear Factor Kappa-Β Ligand (RANKL), and Glycoprotein Non-Metastatic Melanoma Protein B (GPNMB)—among individuals with diabetes while exploring the impact of ethnicity on these biomarkers. A cross-sectional analysis was conducted on a cohort of 2083 individuals from diverse ethnic backgrounds residing in Kuwait. The results indicate significantly elevated levels of these markers in individuals with T2D compared to non-diabetic counterparts, with OPG at 826.47 (405.8) pg/mL, RANKL at 9.25 (17.3) pg/mL, and GPNMB at 21.44 (7) ng/mL versus 653.75 (231.7) pg/mL, 0.21 (9.94) pg/mL, and 18.65 (5) ng/mL in non-diabetic individuals, respectively. Notably, this elevation was consistent across Arab and Asian populations, except for lower levels of RANKL observed in Arabs with T2D. Furthermore, a positive and significant correlation between OPG and GPNMB was observed regardless of ethnicity or diabetes status, with the strongest correlation (r = 0.473, p < 0.001) found among Arab individuals with T2D. Similarly, a positive and significant correlation between GPNMB and RANKL was noted among Asian individuals with T2D (r = 0.401, p = 0.001). Interestingly, a significant inverse correlation was detected between OPG and RANKL in non-diabetic Arab individuals. These findings highlight dysregulation in bone remodeling markers among individuals with T2D and emphasize the importance of considering ethnic variations in T2D-related complications. The performance of further studies is warranted to understand the underlying mechanisms and develop interventions based on ethnicity for personalized treatment approaches. Full article

The efficient design of Permanent Magnet Synchronous Motors (PMSMs) is crucial for their operational performance. A key design parameter, cogging torque, is significantly influenced by various structural parameters of the motor, complicating the optimization of motor structures. This paper proposes an optimization method for PMSM structures based on heuristic optimization algorithms, named the Permanent Magnet Synchronous Motor Self-Optimization Lift Algorithm (PMSM-SLA). Initially, a dataset capturing the efficiency of motors under various structural parameter scenarios is created using finite element simulation methods. Building on this dataset, a batch optimization solution aimed at PMSM structure optimization was introduced to identify the set of structural parameters that maximize motor efficiency. The approach presented in this study enhances the efficiency of optimizing PMSM structures, overcoming the limitations of traditional trial-and-error methods and supporting the industrial application of PMSM structural design. Full article

This study explores consumer preferences for brands that emphasize sustainability and inclusivity, and for brands perceived as exclusive and trendy. Consumer data obtained via a large-scale survey involving 24,798 participants across 20 countries and one special administrative region (SAR) are used to understand how willingness to pay (WTP) for these brand types varies globally, accounting for demographic factors like generation, gender, and country. A substantial body of literature highlights growing consumer interest in brands that stand for sustainability and inclusivity, challenging traditional notions that luxury and exclusivity primarily drive brand value. Despite persistent skepticism among some business executives about consumers’ actual versus claimed willingness to spend more for sustainable and inclusive brands, academics and commercial researchers increasingly signal a shift in purchasing behavior that is influenced by socio-ecological factors. This research aims to provide empirical data on consumer WTP across different demographics and countries/regions, thereby contributing to academic discussions and offering insights for managerial decision making. The study frames its investigation around four research questions, to explore how consumers’ WTP for exclusive and inclusive brands varies across generations, genders, and countries/regions. It employs a robust methodological approach, using confirmatory factor analysis (CFA) and structural equation modeling (SEM) to analyze the data. This ensures that the constructs of brand inclusiveness and exclusivity are comparable across diverse cultural contexts. Significant gender, generational, and country/region differences are observed. When comparing generations, the findings indicate that GenZ consumers have a higher WTP for sustainable/inclusive brands (compared to older, GenX, and Baby Boomer generations). Similar patterns are found when considering WTP for exclusive, on-trend brands. In terms of gender, women are observed to have a higher WTP for sustainable/inclusive brands, but a lower WTP for exclusive, on-trend brands compared to men. Finally, compared to consumers originating from certain European countries, we find that consumers living in certain Asian countries/regions have a significantly higher WTP for inclusive and sustainable brands, as well as for exclusive/on-trend brands. The study underscores the complexities of consumer behavior in the global market, highlighting the coexistence of traditional preferences for exclusive, trendy brands and preferences for brands that embrace sustainability and inclusivity. Full article

The paper breaks the general concepts and shows that pore formation is possible in anodic aluminum barrier oxide by anodizing of pure Al, and also presents the results of electrochemical anodizing in boric acid and citrate buffer aqueous solutions of homogeneous binary alloys AlCu (4 wt.%), AlZn (3 wt.%) and AlAg (5.2 wt.% and 16.2 wt.%). Barrier anodizing allowed obtaining Al₂O₃ thin films doped with copper, zinc and silver. The anodizing behavior and the effect of anodic current density on the charge were studied, and scanning electron microscopy, X-ray photoelectron spectroscopy and Auger electron spectroscopy analyses were performed. The doped alumina thin films, which are a mixture of Al₂O₃, Cu₂O, ZnO, Ag₂O, AgO and promising double metal oxides CuAlO₂, AgAlO₂ and ZnAl₂O₄, are promising for use as resistive switching, photoelectron, mechanical, photo-thermoelectric and fluorescence materials; sensors; and transparent conductive and photocatalyst films. Full article

Modern chemotherapies offer a broad approach to cancer treatment but eliminate both cancer and non-cancer cells indiscriminately and, thus, are associated with a host of side effects. Advances in precision oncology have brought about new targeted therapeutics, albeit mostly limited to a subset of patients with an actionable mutation. They too come with side effects and, ultimately, ‘self-resistance’ to the treatment. There is recent interest in the modulation of ion channels, transmembrane proteins that regulate the flow of electrically charged molecules in and out of cells, as an approach to aid treatment of cancer. Phytochemicals have been shown to act on ion channels with high specificity regardless of the tumor’s genetic profile. This paper explores the use of phytochemicals in cancer symptom management and treatment. Full article

With the construction and development of the smart grid, the power business puts higher requirements on the communication capability of the network. In order to improve the energy efficiency of the space–air–ground-integrated power three-dimensional fusion communication network, we establish an optimization problem for joint air platform (AP) flight path selection, ground power facility (GPF) association, and power control. In solving the problem, we decompose the problem into two subproblems, one is the AP flight path selection subproblem and the other is the GPF association and power control subproblem. Firstly, based on the GPF distribution and throughput weights, we model the AP flight path selection subproblem as a Markov Decision Process (MDP) and propose a multi-agent iterative optimization algorithm based on the comprehensive judgment of GPF positions and workload. Secondly, we model the GPF association and power control subproblem as a multi-agent, time-varying K-armed bandit model and propose an algorithm based on multi-agent Temporal Difference (TD) learning. Then, by alternately iterating between the two subproblems, we propose a reinforcement learning (RL)-based joint optimization algorithm. Finally, the simulation results indicate that compared to the three baseline algorithms (random path, average transmit power, and random device association), the proposed algorithm improves an overall energy efficiency of the system of 16.23%, 86.29%, and 5.11% under various conditions (including different noise power levels, GPF bandwidth, and GPF quantities), respectively. Full article

Although research has shown that moral distress harms mental health in diverse populations, information on potential moderators of such associations is scarce. In a sample of sub-Saharan African nurses, we examined the link between moral distress and depressive symptoms. We explored for whom and when such relationships may hold with regard to gender, age, and work experience. Participants consisted of 398 nurses drawn from a tertiary healthcare institution in southeastern Nigeria. Data were collected using the Moral Distress Questionnaire (MDQ) for clinical nurses, and the Center for Epidemiological Studies Depression Scale Revised (CEDS-R). Hayes regression-based macro results for the moderation effects indicated that the association of high moral distress with increased depressive symptoms was robust for women but not significant for men. Although older age and higher years of nursing experience were associated with reduced symptoms of depression, nurses’ age and years of work experience did not moderate the relationship between moral distress and depressive symptoms. To promote mental well-being and preserve the integrity of nurses, gender-based differentials in how morals contribute depressive symptoms should be considered in policy and practice. Full article

Existing research in metasurface design was based on trial-and-error high-intensity iterations and requires deep acoustic expertise from the researcher, which severely hampered the development of the metasurface field. Using deep learning enabled the fast and accurate design of hypersurfaces. Based on this, in this paper, an integrated learning approach was first utilized to construct a model of the forward mapping relationship between the hypersurface physical structure parameters and the acoustic field, which was intended to be used for data enhancement. Then a dual-feature fusion model (DFCNN) based on a convolutional neural network was proposed, in which the first feature was the high-dimensional nonlinear features extracted using a data-driven approach, and the second feature was the physical feature information of the acoustic field mined using the model. A convolutional neural network was used for feature fusion. A genetic algorithm was used for network parameter optimization. Finally, generalization ability verification was performed to prove the validity of the network model. The results showed that 90% of the integrated learning models had an error of less than 3 dB between the real and predicted sound field data, and 93% of the DFCNN models could achieve an error of less than 5 dB in the local sound field intensity. Full article