Additional Value Research Articles

Tumor Budding, Poorly Differentiated Clusters, and Stroma Percentage in Uterine Endometrioid Carcinomas Are Morphologic Findings Associated With Adverse Clinical Outcomes

Uterine endometrioid carcinoma (UEC) has well-defined morphologic features that carry prognostic significance and guide treatment. In addition to the well-known features, tumor budding (TB), poorly differentiated clusters (PDCs), and amount of stroma within the invasive front are associated with a poor prognostic outcome in many carcinomas. Here, we evaluate TB, PDCs, and the stroma percentage in UEC and correlate these findings with morphologic features known to be associated with a poor clinical outcome and with recurrence-free survival (RFS). We performed a retrospective search of our institution’s EMR for cases of hysterectomy for UEC. We collected clinical data including disease recurrence, death, and data associated with poor patient outcomes. Cases were evaluated for TB, PDCs, and percent stroma by 2 pathologists. Ten 20× fields were examined, and the one with the most PDCs and TB was evaluated. Percent stroma was evaluated in a ×10 field of tumor at the area of deepest invasion. Less than 10% stroma was defined as stroma poor, and >10% stroma was defined as stroma rich. Statistical testing and analysis were conducted, and P-value was set at 0.05. One hundred thirteen cases were evaluated. Decreased RFS was seen with TB (P=0.03), at least 5 PDCs (P=0.01), and stroma-rich tumors (P=0.043). This study shows a statistically significant association between TB presence, at least 5 PDCs, stroma-rich tumors, and decreased RFS in UEC. We conclude that TB, PDCs and stromal evaluation are strong independent prognostic indicators in UEC and provide additional value to the currently used morphologic assessment of UEC.

Assessing carbon storage and sequestration benefits of urban greening in Nador City, Morocco, utilizing GIS and the InVEST model

In the 21st century, tackling climate change is an important challenge, and the absorption of CO2 via urban greening employing photosynthesis offers a potential answer to the climate issue. Within this work, the city of Nador is chosen as a case study. The initiative in question proposes an enhanced technique focused on estimating the advantages of urban greening in terms of carbon storage and sequestration. This technique combines the use of Geographic Information Systems (GIS) tools and the InVEST model, enabling the study of land use and land cover (LULC) scenarios within the location. These scenarios contain numerous alternatives, ranging from the adoption of intense and extensive green roofs to the establishment of gardens and woodland areas. The carbon storage modeling technique depends on the exploitation of land use maps, reinforced by a bibliographic examination of the key carbon reservoirs. The analysis of results from biophysical modeling indicates a considerable increase of over 45.36 % compared to the existing condition when the option of extensive green roofs is chosen. In the setting of extensive green roofs, this rise reaches a rate of 64.20 %. Furthermore, the restoration of the Gourougou forest north of the city leads to an increase of 70.30 %. The adoption of diverse combinations, such as the integration of green roofs with urban vegetation, greatly helps to further enhancing carbon storage. From a financial perspective, the additional value can range from $2,012,825.16 to $3,601,025.53, depending on the chosen scenario. This financial assessment highlights the possible advantages that might be converted into carbon credits in return for emission reduction, partially offsetting the expenses associated with the adoption of each greening solution. Ultimately, these findings give a chance for urban planners and green architecture professionals to perform in-depth planning analyses.

Determinants of Operations Management Faculty Salary: Is Publishing in “A” Journals the “Bottom Line”?

This study investigates the determinants of salary for operations management scholars. Is it as some opine that the only thing that matters is the publication count in “A” journals? How do the full range of activities: research, teaching, service, and administration, affect salary? The present research seeks to shed light on these questions and is predicated on a data set that consists of the research, teaching, and service outcomes, along with salary, for a full census of operations management faculty at 22 public universities (227 faculty) for base, 9-month salary and a subset of 15 universities (150 faculty) for total annual compensation. The results demonstrate partial support for the hypotheses that only “A” publications are financially rewarded, with publications in Production and Operations Management having the highest correlation with salary. The salary reward for publishing in “A” journals is unaffected by number of coauthors. Publications in other academic journals, top-tier practitioner journals, and top journals in sister-fields, and measures of impact, such as citations, H-index, and research awards provide no additional explanatory value of salary. Likewise, service and teaching awards do not add explanatory value. Female Full Professors are paid roughly $23,000 less in base salary than their male counterparts. Non-publishing factors that significantly contribute to salary include changing university affiliations (only for Associate and Full Professors), taking on administrative duties, as well as certain qualitative measures such as achieving Fellow status at the Production and Operations Management Society.

Exploring novel heat transfer correlations: Machine learning insights for molten salt heat exchangers

The utilization of molten salts in heat transfer applications, specifically within shell-and-tube heat exchangers, has garnered significant attention for its potential in sustainable energy solutions. this study employs advanced machine learning algorithms, including decision tree regressor, support vector regressor, extreme gradient boosting, and random forest, to not only predict the heat transfer behavior of molten salts but also unravel the complex mechanisms underlying this process. Achieving a remarkable accuracy score of 0.985, the Support Vector Regressor leads the predictive models, closely followed by random forest (0.982), Decision Tree Regressor (0.974), and Extreme Gradient Boosting (0.965). The incorporation of Shapley Additive exPlanations values accentuates the Reynolds number’s pivotal role, elucidating a robust correlation with the Nusselt value. These insights transcend mere prediction, offering a profound understanding that can significantly impact the design and optimization of molten salt heat exchangers. The applications of molten salts extend across various sectors, including concentrated solar energy and thermal storage, solidifying their position as a versatile and effective solution in the pursuit of sustainable and efficient energy systems.

Dynamics of Wetland Conversion and Its Implications for Socio-Cultural Aspects of Communities in Banjar District, Indonesia

The massive conversion of wetlands has implications not only for social aspects but also for cultural aspects of society. This research aims to analyze the dynamics of wetland conversion and its implications for the socio-cultural aspects of society in Banjar Regency. The research method is a qualitative method with data collection methods through observation, literature studies, and in-depth interviews. The research results show that the process of changing the function of wetlands in Banjar Regency is carried out through hierarchy 1 which occurs in the first stage of wetland conversion, with characteristics that are still passive and social changes that emerge to the surface or are manifest only in the individual realm (not collective), and is closely related to the direct impact of spatial changes. Hierarchy 2 occurs when hierarchy 1 experiences a value addition process, namely the infiltration of capitalistic values into the socio-cultural values that exist in society. This process occurred when the private sector (companies the warehousing industry and housing developers) emerged as actors driving the conversion of wetland functions who made concrete efforts to encourage change. In hierarchical dynamics 2, a transformation process occurs in socio-cultural society, which is characterized by a process of internalizing a "new perspective" regarding employment status, or economic accumulation, and tends to ignore and even erase the "old perspective" namely the community's traditional life as farmers in a wetland environment.

Chikki: Food from De-oiled Peanut Cake

A “Tel-Ghani” (Indian traditional oil-expression unit) of about 150 kg/day of peanuts, yields about 5% less oil from peanuts than mechanical oil expeller, and is an important entrepreneurial activity in villages. De-oiled cake fetch low price as animal feed. Use of peanut cake in snack food as chikki was attempted for value addition to improve the economics of the Tel-Ghani. Preparation of the snack, technical specifications of processes involved, characterization of the snack in terms of colour, texture, and sorption isotherms to predict keeping quality and economic analysis are reported. Chikki made from ground deolied cakepowder containing 16.3 % residual oil and having added 20% jaggery, 12% sugar, 8% liquid glucose and 4% vanaspati ghee scored best in sensory evaluation. The product - chikki not only provides a protein-rich food, but also improves the economics of Tel-Ghani.

Metabolic profiling of highland barley (Hordeum vulgare var. nudum) genotypes

Highland barley (HB), a valuable crop thriving in challenging conditions on the Qinghai-Tibet Plateau, possesses rich nutrient contents. This study aims to investigate the nutrient profile of HB genotypes and compare the metabolic profiles of three representative genotypes exhibiting high, medium, and low quality. The screening of HB genotypes reveals significant genotype-dependent differences in starch content, protein content, amino acid content, flavonoid content, antioxidant capacity, β-glucan, and γ-aminobutyric acid. The selected genotypes, namely KKDM2021005, ZJDM012, and DCDM2020017, exemplify high, average, and low quality, respectively. Utilizing LC–MS/MS for metabolic profiling, 617 metabolites from 12 major classes, with flavonoids being the most abundant, are identified. Distinct metabolic profiles are observed among the three genotypes, with 262 DAMs for KKDM2021005 versus DCDM2020017, 261 DAMs for KKDM2021005 versus ZJDM012, and 298 DAMs for ZJDM012 versus DCDM2020017. Enrichment analysis of DAMs highlights pathways associated with anthocyanin, phenylpropanoid, flavone and flavonol, and isoflavonoid biosynthesis. Specific DAMs such as l-valine, l-isoleucine, l-leucine, trifolin, spiraeoside, ferulic acid, betanin, cyanidin-3-O-galactoside, and cyanidin-3-O-glucoside, along with others, contribute to the observed quality differences among the genotypes. These findings provide a foundation for further exploration of genotype-specific metabolic profiles to manipulate the quality aspects of HB utilizing the existing gene pool. By enhancing its nutritional value, functional properties, and potential health benefits, HB can receive significant value addition.

Value Addition of Crude Glycerol – A Co-product from Biodiesel Production Process

The crude glycerol obtained as a co-product from biodiesel production process had soap, alcohol, water and catalyst. It contained 8.9% soap, 4.6% ash, 3.7% free fatty acid and had pH of 11.8. More than 21% methanol was recovered from the neutralized glycerol at 65°C. The glycerol, after alcohol recovery, was distilled at 100°C to remove moisture. The moisture-free glycerol was distilled under vacuum at 0.4 mbar for 140°C. The recovery of distilled glycerol was 40.5% of the crude glycerol, and 19% residue was obtained. The distilled glycerol was further purified by filtration using Whatman No.22 filter paper and activated carbon to remove odour and color, respectively. The purified glycerol had 0.77% soap, 0.03% ash and pH of 3.5.

Water Harvesting Based Integrated Vertical Farming

Water shortage at critical times is a dominant constraint in most rain fed areas. Small Farm Reservoir (SFR) could play an important role in alleviating the problem by mitigating drought situation and/or submergence in these areas. It has multiple uses such as reducing drainage congestion, irrigation and aquaculture, improved cropping systems, increasing productivity and income, harnessing idle farm labour and improving family nutrition, although the utilization of full potential of SFR depends on innovativeness of the owner. To address the main issue of the farmers who do not wish to loose 5 to 20% land forever, it is imperative to consider integrated vertical farming to have multifarious uses of the same land/water. The multi-storeyed farming and animal rearing on the bunds of SFR is one of the options. The stored water of SFR can be used for fish (below water surface) and duck rearing (on the water surface) and space above it for poultry and rabbit farming. This system has great potential to boost the economy of farmers. The excreta of rabbits and poultry birds served as a part of the fish-food as well as add value to the stored water. Besides the animal rearing practiced on peripheral bunds would produce good amount of dung and urine, which was sloped down to SFR water which further helped to provide feed and value addition to the water. This organic water through drip irrigation system was used to irrigate orchards grown in the vicinity of SFR. The B:C ratio of such a system varied from 5.08 to 6.17 depending upon the intensity of remunerative activities. This paper reviews some of the systems installed at various places in the country to bring out the practical applications. It is concluded that in view of the decreasing trend in the average land holdings, innovative forms of this technology could be used by adding suitable components to enhance the farmer’s income.

A modified CEUS risk stratification model for adnexal masses with solid components: prospective multicenter study and risk adjustment.

To evaluate the additional advantages of integrating contrast-enhanced ultrasound (CEUS) into the Ovarian-Adnexal Reporting and Data System (O-RADS) ultrasound (US) for the characterization of adnexal lesions with solid components. This prospective multicenter study recruited women suspected of having adnexal lesions with solid components between September 2021 and December 2022. All patients scheduled for surgery underwent preoperative CEUS and US examinations. The lesions were categorized according to the O-RADS US system, and quantitative CEUS indexes were recorded. Pathological results served as the reference standard. Univariable and multivariable analyses were performed to identify risk factors for malignancy in adnexal lesions with solid components. Receiver operating characteristic (ROC) curve analysis was employed to assess diagnostic performance. A total of 180 lesions in 175 women were included in the study. Among these masses, 80 were malignant and 100 were benign. Multivariable analysis revealed that serum CA-125, the presence of acoustic shadowing, and peak intensity (PI) ratio (PImass/PIuterus) of solid components on CEUS were independently associated with adnexal malignancy. The modified CEUS risk stratification model demonstrated superior diagnostic value in assessing adnexal lesions with solid components compared to O-RADS US (AUC: 0.91 vs 0.78, p < 0.001) and exhibited comparable performance to the Assessment of Different NEoplasias in the adnexa (ADNEX) model (AUC 0.91 vs 0.86, p = 0.07). Our findings underscore the potential value of CEUS as an adjunctive tool for enhancing the precision of diagnostic evaluations of O-RADS US. The promising performance of the modified CEUS risk stratification model suggests its potential to mitigate unnecessary surgeries in the characterization of adnexal lesions with solid components. • The additional value of CEUS to O-RADS US in distinguishing between benign and malignant adnexal lesions with solid components requires further evaluation. • The modified CEUS risk stratification model displayed superior diagnostic value and specificity in characterizing adnexal lesions with solid components when compared to O-RADS US. • The inclusion of CEUS demonstrated potential in reducing the need for unnecessary surgeries in the characterization of adnexal lesions with solid components.

Application of Explainable Artificial Intelligence technique to model the predictors of South African SMMEs resilient performance during the Covid-19 pandemic

Various studies have been carried out to establish the key drivers impacting small enterprise sustainable performance in developing countries. Despite many policy-oriented studies to uncover the factors influencing SME resilience in emerging markets, these firms continue to register high failure rate, which has been further exacerbated by the Covid-19 pandemic. Guided by a history of linear- and log-linear econometric model estimation that ignores potential network effects, our study extends the literature by implicating SMME resilience as a production network. Utilising data from both incubated and non-incubated SMMEs, marking a departure from traditional linear econometric models, radial basis function artificial neural network algorithm was invoked to establish the drivers of SMME resilience during Covid-19 regime. The study extends the literature by implicating eXplainable Artificial Intelligence (XAI) methods. Specifically, optimal SHapley Additive Explanations values (SHAP values) were computed to enhance the prediction output from the machine learning algorithm. The XAI analytics provide insightful findings on the key drivers which influenced the resilience of SMMEs during the Covid-19 pandemic. The importance of innovation through introduction of new products, company age and higher number of marketing mediums is confirmed however total assets, analytics, educational level and number of workers surfaced as a threat to these enterprises’ sustainable performance. The study recommends that both the government and SMEs should leverage XAI to identify their heterogeneous attributes and inform intelligent decision-making which necessities their resilient performance.

Incorporating media news to predict financial distress: Case study on Chinese listed companies

AbstractFinancial distress prediction has been a prominent research field for several decades. Accurate prediction of financial distress not only helps to safeguard the interests of investors but also improves the ability of managers to manage financial risks. Prior studies predominantly rely on accounting metrics derived from financial statements to predict financial distress. Our research takes a step further by incorporating media news to enhance the accuracy of financial distress prediction. Based on the data from Chinese listed companies, seven classifiers are established to verify the additional value of media news in improving the financial distress prediction performance of models. Experimental results demonstrate that the inclusion of media news in predictive models is effective as it contributes to better performance compared with models that solely rely on accounting features. Moreover, random forest model is a reliable tool in financial distress prediction due to its superior ability to capture complex feature relationships. Evaluation indicators, statistical tests, and Bayesian A/B tests further confirm that the inclusion of media news can significantly improve the identification of financially distressed companies.

Progress of Multiparameter Magnetic Resonance Imaging in Bladder Cancer: A Comprehensive Literature Review.

Magnetic resonance imaging (MRI) has been proven to be an indispensable imaging method in bladder cancer, and it can accurately identify muscular invasion of bladder cancer. Multiparameter MRI is a promising tool widely used for preoperative staging evaluation of bladder cancer. Vesical Imaging-Reporting and Data System (VI-RADS) scoring has proven to be a reliable tool for local staging of bladder cancer with high accuracy in preoperative staging, but VI-RADS still faces challenges and needs further improvement. Artificial intelligence (AI) holds great promise in improving the accuracy of diagnosis and predicting the prognosis of bladder cancer. Automated machine learning techniques based on radiomics features derived from MRI have been utilized in bladder cancer diagnosis and have demonstrated promising potential for practical implementation. Future work should focus on conducting more prospective, multicenter studies to validate the additional value of quantitative studies and optimize prediction models by combining other biomarkers, such as urine and serum biomarkers. This review assesses the value of multiparameter MRI in the accurate evaluation of muscular invasion of bladder cancer, as well as the current status and progress of its application in the evaluation of efficacy and prognosis.

[C-reactive protein, cardiovascular issues of an acute-phase protein: an update for theclinician].

Inflammation is an important pathogenic factor for the development of atherosclerotic cardiovascular disease. Currently, the most frequently used biomarker reflecting systemic inflammation is C-reactive protein (CRP), an acute-phase protein produced primarily by hepatocytes under the influence of interleukin-6, interleukin-1 beta, and tumor necrosis factor. Growing evidence from epidemiological studies has shown a robust association between elevated serum or plasma CRP concentrations and the incidence of a first cardiovascular adverse event (including acute myocardial infarction, ischemic stroke, and sudden cardiac death) in the general population, as well as recurrence of major adverse cardiovascular events among patients with established disease. The additive value that CRP measurement gives to traditional risk factors is reflected in novel cardiovascular risk calculators and in current intervention regimens, which already consider CRP as a target therapeutic. However, the variations in CRP levels, that depend on sex, ethnicity, hormonal status, and some peculiarities of the measurement assays, must be taken into consideration when deciding to implement CRP as a useful biomarker in the study and treatment of atherosclerotic cardiovascular disease. This review aims to offer an updated vision of the importance of measuring CRP levels as a biomarker of cardiovascular risk beyond the traditional factors that estimate the risk of atherosclerotic disease.

Influence of chitin nanofibers and gallic acid on physical-chemical and biological performances of chitosan-based films

In this work, chitosan films loaded with gallic acid and different content of chitin nanofibers were prepared and subjected to different characterization techniques. The results showed that the inclusion of gallic acid to chitosan films caused moderate decrease in water vapor permeability (by 29 %) and increased tensile strength of films (by 169 %) in comparison to the neat chitosan films. Furthermore, it was found that the addition of chitin nanofibers up to 30 % into chitosan/gallic acid films additionally improved tensile strength (by 474 %) and reduced plasticity of films (by 171 %), when compared to the chitosan/gallic acid films. Increased concentration of chitin nanofibers in films reduced the overall water vapor permeability of films by 51 %. In addition, gallic acid and chitin nanofibers had synergic effect on high chitosan film's antioxidant and antifungal activity toward Botrytis cinerea (both above 95 %). Finally, chitosan/gallic acid/chitin nanofibers films reduced decay incidence of strawberries, increased total soluble solid content, and promoted high production of some polyphenols during cold storage, in comparison to the control chitosan films and uncoated strawberry samples. Hence, these results suggest that chitosan/gallic acid/chitin nanofibers can present eco-sustainable approach for preservation of strawberries, giving them additional nutritional value.

Identifying biologically implausible values in big longitudinal data: an example applied to child growth data from the Brazilian food and nutrition surveillance system

BackgroundSeveral strategies for identifying biologically implausible values in longitudinal anthropometric data have recently been proposed, but the suitability of these strategies for large population datasets needs to be better understood. This study evaluated the impact of removing population outliers and the additional value of identifying and removing longitudinal outliers on the trajectories of length/height and weight and on the prevalence of child growth indicators in a large longitudinal dataset of child growth data.MethodsLength/height and weight measurements of children aged 0 to 59 months from the Brazilian Food and Nutrition Surveillance System were analyzed. Population outliers were identified using z-scores from the World Health Organization (WHO) growth charts. After identifying and removing population outliers, residuals from linear mixed-effects models were used to flag longitudinal outliers. The following cutoffs for residuals were tested to flag those: -3/+3, -4/+4, -5/+5, -6/+6. The selected child growth indicators included length/height-for-age z-scores and weight-for-age z-scores, classified according to the WHO charts.ResultsThe dataset included 50,154,738 records from 10,775,496 children. Boys and girls had 5.74% and 5.31% of length/height and 5.19% and 4.74% of weight values flagged as population outliers, respectively. After removing those, the percentage of longitudinal outliers varied from 0.02% (<-6/>+6) to 1.47% (<-3/>+3) for length/height and from 0.07 to 1.44% for weight in boys. In girls, the percentage of longitudinal outliers varied from 0.01 to 1.50% for length/height and from 0.08 to 1.45% for weight. The initial removal of population outliers played the most substantial role in the growth trajectories as it was the first step in the cleaning process, while the additional removal of longitudinal outliers had lower influence on those, regardless of the cutoff adopted. The prevalence of the selected indicators were also affected by both population and longitudinal (to a lesser extent) outliers.ConclusionsAlthough both population and longitudinal outliers can detect biologically implausible values in child growth data, removing population outliers seemed more relevant in this large administrative dataset, especially in calculating summary statistics. However, both types of outliers need to be identified and removed for the proper evaluation of trajectories.

Enhancing Bromelain Recovery from Pineapple By-Products: A Sustainable Approach for Value Addition and Waste Reduction.

Pineapple by-products are good sources of bromelain, a complex enzyme with commercial applications. This study evaluated the feasibility of producing bromelain powders from pineapple waste using an organic solvent-free approach. Pineapple by-products (from var. MD2), including cores, peels, crowns, stems, and basal stems, were homogenized with deionized water, and the pH of the mixture was adjusted to 4.5 and 9 (isoelectric points of fruit bromelain and stem bromelain), clarified, ultra-filtered, and freeze-dried to produce bromelain powders. The enzymatic activity of the bromelain powders was measured using the gelatin and casein digestion methods. The bromelain powders from the crowns did not show significant enzymatic activity (p < 0.05). Meanwhile, bromelain powders produced from the cores and peels had an enzymatic activity of 694 gelatin digesting units (GDU)/g and 124 casein digesting units (CDU)/mg, and 1179 GDU/g and 217 CDU/mg, respectively. Bromelain powders from the basal stems showed the highest enzymatic activity (2909 GDU/g and 717 CDU/mg). Increasing the pH of the liquid mixture before the purification and freeze drying significantly (p < 0.05) reduced the enzymatic activity of the bromelain powders. Using a practical and organic solvent-free approach, this study demonstrates the feasibility of producing bromelain powders with high enzymatic activity from pineapple waste.

Solvent-Free Organic Liquids: An Efficient Fluid Matrix for Unexplored Functional Hybrid Materials.

ConspectusThe invention of solvent-free organic liquids (SOLs) was serendipitous. However, the curiosity-driven research in the later stage delivered new soft materials with exciting optical, and optoelectronic properties along with appealing physical characteristics suitable for the futuristic applications. A slight change in the molecular design resulted in a drastic change in the physical state of molecules demonstrating monomer-like features in the bulk. The basic idea of core isolation has been successful in delivering new SOLs with attractive functional properties. The unique fluid matrix associated with SOLs offers a tremendous opportunity for making hybrid materials by simple mixing. The chance to study the fundamentally important electron transfer, energy transfer, charge transfer interactions, triplet-state emissions, and even detailed NMR experiments in the solvent-free neat state is the major attraction of SOLs. Usually, solvents and their polarity control such molecular properties, and in the case of SOLs, it avoids the use of solvents to study such fundamentally important properties. Besides, SOLs protect the triplet emitters and excited state processes involving triplet states from quenchers and make the analysis possible under ambient conditions.Our effort in this direction was focused on tuning the ground and excited state properties by transforming conventional organic molecules to SOLs and further value addition by preparing the hybrid SOLs. We developed a series of hybrid SOLs, exploring room-temperature phosphorescence, thermally activated delayed fluorescence, charge or energy transfer between donor and acceptor SOLs, selective explosive sensing, etc. A slight variation in the chemical structure or optoelectronic properties of the individual components imparted exciting optical features for the hybrid SOLs. It includes nonemissive charge transfer, tunable emission exciplex, room temperature phosphorescence, and thermally activated delayed fluorescence SOLs. The liquid matrix of donor SOLs accommodated varying amounts of acceptor SOLs to tune the ground and excited state features. In all examples of donor-acceptor-based hybrid SOLs, even a low amount of acceptor, such as a donor-acceptor ratio of 1000:1, can cause pronounced optical properties. Hence, the evaluation of the optical properties of SOLs, especially, in the absence of solvents is so special that it avoids the interference of solvent molecules. Still, the major drawback of SOLs remains unsolved until we report polymerizable SOLs. Although a large variety of SOLs have been reported in the literature, the long-lasting problem of surface stickiness of SOLs was resolved by polymerizable SOLs. It enabled the development of flexible, foldable, and stretchable large-area luminescent films suitable for lighting and display devices. In this Account, we summarize our work on SOLs, hybrid SOLs, polymerizable SOLs, and the application of SOLs in selective sensing of explosives. Finally, an outlook on the feasibility of luminescent polymerizable SOLs in futuristic applications is provided.

The effects of shaping employee work engagement and job satisfaction on company performance results: the mediating role of HRM outcomes in Central European MNCs

PurposeThe main goal of the article is to determine the mediating role of human resources management (HRM) outcomes in the relationships between shaping employee work engagement and job satisfaction (SEWE&amp;JS) and company performance results and to establish whether there are any identifiable regularities in this scope in the pre-pandemic and pandemic period in the headquarters (HQs) and foreign subsidiaries of multinational companies (MNCs).Design/methodology/approachThe empirical research included 200 MNCs headquartered in Central Europe. The raw data in the variables were adjusted with the efficiency index (EI) to capture the actual relations between the variables under study. The partial least squares structural equation modeling (PLS-SEM) was used to verify the research hypotheses and assess the mediating effects.FindingsThe research findings show that the HRM outcomes positively mediate the relationships between SEWE&amp;JS and the company performance results. HRM outcomes turned out to be a stronger mediator between SEWE&amp;JS and company performance results in finance and quality in the HQs during the pandemic. By contrast, in the local subsidiaries, they were a stronger mediator of the relationships between the results in innovativeness and quality during the pandemic.Originality/valueIn addition to confirming the results of some other researchers, the research findings also provide new knowledge. They determine the mediating role of HRM outcomes in the relationship between SEWE&amp;JS and the three categories of company performance results, namely finance, innovativeness and quality. In addition, they identify certain regularities in the four studied contexts, which is a novelty in this type of research. A novelty is also the use of employee key performance indicators (KPIs) in the data analysis as the efficiency index in analyzing the effect of the variables under study. The value of the research is also the fact that it covers HRM in MNCs established in Central Europe, which, compared to MNCs from the Western world, is not a frequent subject of research.

COMPASS: Double-ended saddle point search as a constrained optimization problem.

We present an algorithm to find first order saddle points on the potential energy surface (PES). The algorithm is formulated as a constrained optimization problem that involves two sets of atomic coordinates (images), a time-varying distance constraint and a constraint on the energy difference. Both images start in different valleys of the PES and are pulled toward each other by gradually reducing the distance. The search space is restricted to the pairs of configurations that share the same potential energy. By minimizing the energy while the distance shrinks, a minimum of the constrained search space is tracked. In simple cases, the two images are confined to their respective sides of the barrier until they finally converge near the saddle point. If one image accidentally crosses the barrier, the path is split at suitable locations and the algorithm is repeated recursively. The optimization is implemented as a combination of a quasi-Newton optimization and a linear constraint. The method was tested on a set of Lennard-Jones-38 cluster transitions and a set of 121 molecular reactions using density functional theory calculations. The efficiency in terms of energy and force evaluation is better than with competing methods as long as they do not switch to single-ended methods. The construction of a continuous search path with small steps and the ability to focus on arbitrary subsegments of the path provide an additional value in terms of robustness and flexibility.