Miracle-dz/UniFAR-FTUs huggingface dataset:
CSR disclosure and investor social preferences: heterogenous investor responses to media reports on corporate greenwashing

Purpose There is emerging evidence in the accounting literature that investors react negatively to corporate greenwashing. But does that hold for all investors, or do different types of investors react differently? This paper aims to study retail investors’ responses to media reports on corporate greenwashing and how these responses depend upon the investors’ social value orientation. The authors argue that media reporting on corporate greenwashing negatively affects the rationale for allocating funds to firms engaging in greenwashing. The authors also expect this reaction to be stronger for prosocial investors compared to proself investors. Design/methodology/approach The authors conduct an online experiment with 229 participants representing retail investors in the German-speaking countries. Findings The results show that retail investors who received media reports on deceptive disclosure invest more funds in the company that does not engage in greenwashing (and less in the firm that engages in greenwashing) than investors who did not receive these reports. The authors’ results provide novel evidence that this effect primarily holds for investors with a prosocial value orientation. Finally, the authors’ data show that lower trust in the firm that engages in greenwashing partially mediates the effect of media reports on investor choices. Originality/value The authors provide unique evidence how different types of investors react to media reports on greenwashing. The authors find that moral motives, rather than risk-return considerations, drive investor responses to greenwashing. Overall, these findings support the important function of the media as an intermediary in stock market participation and highlight the pivotal role of individual traits in investors’ responses to greenwashing.
Application of Multivariate Principal Component Analysis for Characterization of Leaf Litters in Northern Nigeria

This study was to objectively describe the interrelationship between mass loss and leaf chemical parameters of litter species: Khaya senegalensis, Mangifera indica, Gmelina arborea, and Eucalyptus camaldulensis using principal component analysis. Leaf litters were analyzed for chemical compositions. Mass loss and ten litter chemical parameters such as organic carbon, total nitrogen, total phosphorus, potassium, magnesium, calcium, sodium, total soluble polyphenol, total sulphur and carbon to nitrogen ratio were investigated. Principal Component Analysis (PCA) was used to identify the variation of litter chemical properties. The results showed significant relationships between mass loss and litter chemical parameters in PC1 and PC2 axes. Khaya senegalensis has the highest loadings 84% followed by Gmelina arborea 77%, Eucalyptus camaldulensis 75.3% and Mangifera indica 64.5%. In conclusion, Khaya senegalensis showed a propensity to have a faster response in driving biogeochemical cycling during decomposition.
Evaluation of P5CS and ProDH activity in Paulownia tomentosa (Steud.) as an indicator of oxidative changes induced by drought stress

The aim of the study was to investigate changes in proline metabolism in seedlings of tree species during drought stress. One month old Paulownia tomentosa seedlings were exposed to moisture conditions at various levels (irrigation at 100, 75, 50 and 25% of field capacity), and then the material (leaves and roots) was collected three times at 10-day intervals. The activity of enzymes involved in proline metabolism was closely related to drought severity; however, proline content was not directly impacted. The activity of pyrroline-5-carboxylate synthetase (P5CS), which catalyzes proline biosynthesis, increased in response to hydrogen peroxide accumulation, which was correlated with soil moisture. In contrast, the activity of proline dehydrogenase (ProDH), which catalyzes proline catabolism, decreased. Compared to proline, the activity of these enzymes may be a more reliable biochemical marker of stress-induced oxidative changes. The content of proline is dependent on numerous additional factors, i.e., its degradation is an important alternative energy source. Moreover, we noted tissue-specific differences in this species, in which roots appeared to be proline biosynthesis sites and leaves appeared to be proline catabolism sites. Further research is needed to examine a broader view of proline metabolism as a cycle regulated by multiple mechanisms and differences between species.
Remote Heart Rate Estimation Based on Transformer with Multi-Skip Connection Decoder: Method and Evaluation in the Wild

Heart rate is an essential vital sign to evaluate human health. Remote heart monitoring using cheaply available devices has become a necessity in the twenty-first century to prevent any unfortunate situation caused by the hectic pace of life. In this paper, we propose a new method based on the transformer architecture with a multi-skip connection biLSTM decoder to estimate heart rate remotely from videos. Our method is based on the skin color variation caused by the change in blood volume in its surface. The presented heart rate estimation framework consists of three main steps: (1) the segmentation of the facial region of interest (ROI) based on the landmarks obtained by 3DDFA; (2) the extraction of the spatial and global features; and (3) the estimation of the heart rate value from the obtained features based on the proposed method. This paper investigates which feature extractor performs better by captioning the change in skin color related to the heart rate as well as the optimal number of frames needed to achieve better accuracy. Experiments were conducted using two publicly available datasets (LGI-PPGI and Vision for Vitals) and our own in-the-wild dataset (12 videos collected by four drivers). The experiments showed that our approach achieved better results than the previously published methods, making it the new state of the art on these datasets.
Spatial redistribution of organic phosphorus in hay and grass pastures of eastern West Virginia following longterm animal manure applications

Spatial Redistribution of Organic Phosphorus in Hay and Grass Pastures of Eastern West Virginia Following Long-term Animal Manure Applications Michael B. Harman This study was conceived to investigate the fate of organic P (Po) in typical hay and grass pasture of eastern West Virginia. It is not uncommon in this region of West Virginia for hay and grass pastures to receive annual applications of animal manure, often on a nitrogen basis. As P management has evolved, many farms in the region have begun to use management tools such as a P index to continue use of animal manure as N fertilizer. However, many hay and grass pastures in the region already have a high degree of P saturation. There are reasonable expectations that in time the P saturation at these sites may reach thresholds whereby actions to lower P saturation become necessary. At such time it may become necessary to develop interception strategies to prevent movement of P into surface and ground water from there extremely saturated locations. While most P research focuses on P loss via surface erosion, or on tile drained land, and rarely is Po considered. To fully evaluate the risks of P loss and develop remediation and interception strategies, data specific to Po movement at field scales across complex landscapes is needed to increase assurances that existing research is compatible with or applicable to West Virginia pastures. To develop this data, sequentially extracted P fractions were measured in samples from both spatially-explicit locations across typical hay and grass pastures and from bench top experiments to evaluate the applicability of existing research. I examined patterns in Po distributions to determine if Po levels significantly exceeded what could be explained by changes in soil properties. Results support the presence of spatial structure in the variability of the NaHCO3 and HCl extractable Po fractions in some locations, but no purely spatial component is present in the variability of the NaOH and H2O extractable fractions. Various topographic parameters were evaluated to determine their efficacy in explaining Po variability and soil-landscape modeling techniques were successfully used to develop relatively simple models based on soil test P results and topographic data to predict the distributions of the sequential extracted Po fractions across these landscapes. The bench top experiment indicated no significant effects from actively growing plants or P sources on the disposition of Po. As such, the bench top results support the acceptance of existing data in decision making processes, and the field scale data supports development of soil landscape models to afford future environment professional a higher degree of understanding relative to the spatial distribution of sequentially extracted Po fractions at a landscape scale.
Assessing the Suitability of Fractal Dimension for Measuring Graphic Complexity Change in Schematic Metro Networks

Schematization is a process of generating schematic network maps (e.g., metro network maps), where the graphic complexity of networks is usually reduced. In the past two decades, various automated schematization methods have been developed. A quantitative and accurate description of the complexity variation in the schematization is critical to evaluate the usability of schematization methods. It is noticed that fractal dimension (F) has been widely used to analyze the complexity of geographic objects, and this indicator may be appropriate for this purpose. In some existing studies, although F has been employed to describe the complexity variation, the theoretical and experimental basis for adopting this approach is inadequate. In this study, experiments based on 26 Chinese cities’ metro networks showed that the F of all these metro networks have decreased in schematization, and a significant positive correlation exists between the F of original networks and the reduction of F after schematization. The above results were verified to have similar trends with the subjective opinions of participants in a psychological questionnaire. Therefore, it can be concluded that F can quantitatively measure the complexity change of networks in schematization. These discoveries provide the basis for using F to evaluate the usability of schematization methods.
Distinguishing Polymorphs of Ethenzamide-Saccharin Cocrystal Based on Terahertz and Raman Vibrational Spectroscopic Techniques

In this article, two kinds of pharmaceutical crystallized polymorphs of ethenzamide (ETZ) and saccharin (SAC) cocrystal were synthesized by both solution crystallization and solid-state grinding methods. Crystal structure analysis revealed that the primary hydrogen-bonding heterosynthon of amide–imide in the form I and form II of ETZ-SAC cocrystal was the same, but the secondary interactions in the extended hydrogen-bonding network were different. In addition, ETZ, SAC, their physical mixture, the form I and form II of ETZ-SAC cocrystal were characterized using terahertz (THz) and Raman spectroscopy. The experimental spectra of THz and Raman showed that ETZ, SAC, and two kinds of polymorphs of ETZ-SAC cocrystal exhibited different characteristic peaks, and THz spectroscopy could distinguish the form I and form II of ETZ-SAC cocrystal, but could not be identified by Raman spectroscopy. Solvent phase transition analysis showed that the result polymorphism of ETZ-SAC cocrystal was not dependent on the polarity of the solvent in the solvent drop grinding experiments, neat grinding and most of solvent drop grinding experiments formed the metastable form II of ETZ-SAC cocrystal. These results indicate that with the in-depth study of pharmaceutical polymorphs of cocrystal, it can be reasonably predicted that polymorphs of cocrystal will have great significance in the development of pharmaceutical cocrystals in the future.
Verse-Based Emotion Analysis of Bengali Music from Lyrics
Using Machine Learning and Neural Network Classifiers

: Throughout the decades, music has been involved with human emotions and inner imaginations. Along with the overgrowing demands for the overhead reduction of human-aided processes, the urge for automation in the linguistic domain has become a preponderance. Research related to Natural Language Processing (NLP) has been flourished well enough in the case of English and other contemporary modern languages. Although Bengali is an enriched multipurpose language with so wide varieties and precious dialects, very few researches have been conducted on emotion recognition in Bengali music. Besides, the Bengali music archive is blessed with pioneering works of some world-class writers, and in addition to that, modern music enthusiasts’ versatile music predilection has made the task of automation in sentiment analysis quite interesting and challenging. In this study, we introduce a verse-based emotion analysis system for Bengali songs that is able to identify certain emotions from textual data. To appraise the relevant results of our resorted approach, we used several Machine Learning (ML) and Neural Network (NN) models. Eventually, we were able to achieve the best accuracy of 80% and 65% using the Bidirectional Encoder Representations from Transformers (BERT) model for both three and two emotion classes.
The Impact of the Employee’s Personal Characteristics on the Abuse of Sickness Absence: Empirical Evidence From Poland

The tendency to abuse sickness absence is a complex problem conditioned by many factors, that can be divided, depending on the level of impact, into three groups: micro (related to personal characteristics), meso (related to the work environment), and macro (related to the broader environment). The subject of interest in the article is the first level (micro). The aim is to evaluate the impact of various personal factors on the declared abuse of sickness leave in Poland. The data was gathered using the CAWI survey. The research sample consisted of 1067 respondents (full-time employees). Statistical analysis incorporated multivariable linear regression and structural equation modelling. Some personal characteristics have a significant impact on the declared abuse of sick leave. These factors are: gender, age, number of children, place of living, marital status, and subjective health. We found no impact of education and financial status. Although abusing sick leave is a serious economic and organisational problem, its causes still remain relatively poorly recognised. Personal characteristics determine the propensity to abuse sick leave, and they need to be taken into account under the process of managing absence behaviours. The added value of the study is drawing attention to the new personal factors which were not previously identified as a determinant of abuse of sick leave. These are: the number of children, place of living, and marital status.
Edge Detection For Eye States Using Color Image Sequence

In this work, an automatic and real time method for detecting eye states is proposed. The method is based on the fact that the regions of iris and white regions of an eyeball can be detected when it is open. In this case, color images contain more information helpful for detecting irises than intensity images. The saturation of color is used to detect whether the eye is open or closed, then the edge map of the eye image is used to detect the irises. Using the color information to detect the locations of irises is more accurate than using only the edge image.
Ultrafast Resource Allocation by Parallel Bandit Architecture Using Chaotic Lasers for Downlink NOMA Systems

The effectiveness of laser chaos decision-makers in facilitating ultrafast decision-making makes it possible for a real-time process of channel allocation scheme for the non-orthogonal multiple access (NOMA) technology in the next generation of wireless communications. However, managing the increasing number of users is challenging as the complexity of channel allocation increases significantly. To resolve this challenge, this paper proposes a novel approach to address scalability problems by introducing a parallel bandit architecture using an array of laser chaos decision-makers. In the proposed method, each user is allocated a specific channel by a dedicated laser chaos decision-maker, thereby reducing the number of available options compared with the conventional approach. This parallel bandit architecture enables the system to efficiently manage increasing users while maintaining scalability and ultrafast channel allocation in NOMA. Additionally, fairness is considered by incorporating a logarithmic utility function for design compensation. Numerical simulation results demonstrate that the proposed method achieves higher data rate and enhanced fairness than conventional NOMA approaches such as minimum distance-NOMA (MD-NOMA), conventional-NOMA (C-NOMA), and uniformed channel gain difference-NOMA (UCGD-NOMA). Moreover, the system performance is evaluated on a larger scale, accommodating a significant number of users, with the study considering up to 64 users, surpassing the limitations of the conventional approach of one laser chaos decision-maker, which is constrained to 10 users.
Ship Rescue Optimization: A New Metaheuristic Algorithm for Solving Engineering Problems

In recent years, more and more problems in the industry have started to be solved using metaheuristics. In this paper, inspired by the ship maneuvering motion function and the rescue process, we propose ship rescue optimization (SRO) to solve the challenging optimization problem. The ship rescue process can be divided into two types of delayed rescue (large area rescue) and immediate rescue (small rescue) according to the searched person, and we can correspond these two types of rescue behaviors to the search space exploration and exploitation processes, respectively. In this process, SRO simulates the motion process of ship rescue according to the ship maneuvering equation of motion and finally comes up with an optimal position update algorithm. We verified the performance of the proposed algorithm on different dimensions of 57 test functions consisting of CEC2013 and CEC2017 and on three real engineering problems, and compared it with eight current mainstream algorithms. The algorithm proposed in this paper is shown to be robustly applicable in solving challenging optimization problems.
Analisis Persepsi Pelanggan terhadap Kualitas Jasa dengan Metode Importance Performance Analysis dan Potential Gain Customer Value

Purpose: The objectives of the study are first, to know how customers perceive the service quality of Hotel Santika Gresik with an Importance Performance Analysis (IPA) method and second to determine the priority of service quality improvement at Hotel Santika Gresik with the Potential Gain Customer Value (PGCV) method. Methodology: The population in this study is who have used the services at Hotel Santika Gresik and the sample in this study are customers who have used the services at Hotel Santika Gresik in the period November 2020 – April 2022. Determination of the number of samples will be determined with a 95% level of confidence and a margin of error of 10%, the number of samples obtained is 96 respondents. The researcher's decision to increase the sample to 98 respondents so that the sample is better at representing the population and the results are better generalized. The sampling technique used in this study is based on the Non Probabilistic Sampling method using a purposive sampling. Results: The results show that (1) the level of conformity between the interests (importance) of customers and the company's performance on the quality of services provided by Hotel Santika Gresik has an average level of conformity below 100%, which is 95.41%, which means Hotel Santika Gresik still lacking or not fulfilling what is considered important by customers and the service is not fully satisfactory; (2) the priority of improvement on the service quality of Hotel Santika Gresik according to the Importance Performance Analysis (IPA) method is that Hotel Santika Gresik employees serve customers quickly, the behavior of Hotel Santika Gresik employees is able to grow customer trust in them, Hotel Santika Gresik always strives to store proprietary data the customer properly and without error, the equipment owned by Hotel Santika Gresik is complete; (3) the priority of improvement on the service quality of Hotel Santika Gresik with the Potential Gain Customer Value (PGCV) method is that Hotel Santika Gresik employees give individual attention to customers with the highest number of 3.86 and the lobby room at Hotel Santika Gresik is clean and comfortable to get the lowest value is 2.77.
Depression and Anxiety in Chronic Kidney Disease Patients Undergoing Hemodialysis Therapy at Hemodialysis Installations General Hospital Dr. Moewardi Surakarta

This study is an analytical descriptive study with a cross-sectional design that aims to determine the proportion and level of depression and anxiety of patients, as well as the relationship between the length of hemodialysis therapy with depression and anxiety of patients with Chronic Kidney Disease undergoing hemodialysis therapy at the Hemodialysis Installation of Dr. Moewardi Surakarta Regional General Hospital. Samples in this study were taken by purposive sampling. The sample in this study amounted to 31 research subjects. The specified data analysis is a Chi-square test analysis to test the relationship between variables. The percentage of anxiety among Chronic Kidney Disease patients receiving hemodialysis treatment at Dr. Moewardi Surakarta Regional General Hospital's Hemodialysis Facility is 29%, while the percentage of depressed patients with Chronic Kidney Disease undergoing hemodialysis therapy at the same facility is 41.9%. It has been determined that there is no discernible correlation between the duration of hemodialysis therapy and the emergence of anxiety and depression in patients with Chronic Kidney Disease at this specific healthcare center. To gain a more comprehensive understanding, additional research is warranted to investigate other factors linked to anxiety and depression in patients with chronic kidney disease undergoing hemodialysis therapy. Furthermore, there is a pressing need for the implementation of a screening program for Chronic Kidney Disease patients undergoing hemodialysis therapy at hospitals, with a potential referral to the Department of Psychiatry for the assessment and management of any mental symptoms that may arise. Keyword: Anxiety, Chronic kidney disease, Depression