In recent years, music education in Ibero-America has been losing ground within the school environment in favor of the development of curricular systems that benefit academic results in standardized tests. Despite this, several studies in the field of cognitive neurosciences have found evidence of great relevance and in which it can be observed how music education can favor cognitive development and performance in practically all stages of human development, with important results in language tasks, attention, and executive functions such as planning, inhibition, cognitive flexibility and working memory.

Cerebrospinal fluid (CSF)-contacting neurons (CSF-N) located in the surface of both brain ventricles and the central canal (cc) in the spinal cord. The cc and CSF maintain a proliferative niche for neural progenitor cells and play a vital role in development of the brain. The CSF circulates in the ventricles and the subarachnoid spaces with the CSF rhythmic flow: cardiac pulsation and respiratory fluctuation. A new concept of CSF motion may be contrary to the classical one that the direction of CSF motion may vary in direction and may be dynamic in its location. The CSF pressure may also depend on the body position. Moderate music-making has been considered a potential approach for rehabilitative and restorative therapy of brain dysfunctions. Recently, we find that the CSF-Ns are present in both the interior CFS in the cc and also exterior CSF around the surface of the spinal cord. We hypothesize that CSF-N as mechanical sensors in the spinal cord could sense motion of the spinal cord. The myodural bridge is a ligament connecting a pair of deep, upper-neck muscles to the dura mater, which envelops the arachnoid mater and contains the CSF surrounding the brain and the spinal cord. We figure out the term “CSF-static compartment” and classify CSF storage location as rostral pool and caudal pool to demonstrate our hypothesis. We presume that the somatic body movement with music-making and rehabilitation-based interventions would orchestrate the CSF motion with head movement, myodural bridge stretching and puling as well as spinal bending.

This article aims to analyze music from a philosophical and theological perspective, using the principles of multi- and transdisciplinary methodology. After a brief introduction, which presents the main moments in the history of the musical phenomenon, a first chapter addresses the metaphysical dimension of music in classical composers. The second chapter shows the position of philosophers towards music, starting with Pythagoras and ending with Schopenhauer. The third chapter focuses on music theology in general, but also on the theology and metaphysics of music to the French philosopher of Romanian origin, Emil Cioran, who, after Augustin and Schopenhauer, wrote probably the deepest pages on the ontology of music. The last chapter refers to to the archetypal character of music.

In music, the role of the interpreter is to play her/his part manipulating the performance parameters in order to offer a sonic rendition of the piece capable of conveying specific expressive intentions. Since the 1980s there has been a growing interest in computational expressive music performance (EMP). This research field has two fundamental objectives: the understanding of the phenomenon of human musical interpretation and the automatic generation of expressive performances. Rule based, statistical, machine and deep learning approaches have been proposed, most of them devoted to the classical repertoire, in particular to piano pieces. On the contrary, we present an introduction to the role of expressive performance within popular music and to the contemporary ecology of pop music production, based on the use of Digital Audio Workstations (DAWs) and virtual instruments. After an analysis of the tools related to expressiveness commonly available to modern producers we propose a detailed survey of research into the computational EMP field, highlighting the potential and limits of what is present in literature with respect to the context of popular music, which by its nature cannot be completely superimposed on the classical one. In the concluding discussion we suggest possible lines of future research in the field of computational expressiveness applied to pop music.

Music is capable of conveying many emotions. The level and type of emotion of the music perceived by a listener, however, is highly subjective. In this study, we present the Music Emotion Recognition with Profile information dataset (MERP). This database was collected through Amazon Mechanical Turk (MTurk) and features dynamical valence and arousal ratings of 54 selected full-length songs. The dataset contains music features, as well as user profile information of the annotators. The songs were selected from the Free Music Archive using an innovative method (a Triple Neural Network with the OpenSmile toolkit) to identify 50 songs with the most distinctive emotions. Specifically, the songs were chosen to fully cover the four quadrants of the valence arousal space. Four additional songs were selected from DEAM to act as a benchmark in this study and filter out low quality ratings. A total of 277 participants participated in annotating the dataset, and their demographic information, listening preferences, and musical background were recorded. We offer an extensive analysis of the resulting dataset, together with a baseline emotion prediction model based on a fully connected model and an LSTM model, for our newly proposed MERP dataset.

The present study examined music-induced dopamine release, as measured by a proxy measure of spontaneous eye blinks. Specifically, we explored the effects of uplifting and sombre tones in different sections of Vivaldi's Four Seasons to investigate the affective content of musical pieces within one composition. Seventeen participants listened to four concertos (Major modes: Spring, Autumn, Minor modes: Summer and Winter) and a silence condition while completing the 3-Stimulus Odd-ball attention task. Electrooculograms were recorded from electrodes placed above and under the left eye. Self-reported arousal and music preference measures were also gathered during the testing session. In addition, the P3a Event-Related Potential (ERP) component was analysed as another potential index of dopamine function. Results revealed significant differences in the blink rates during music listening and silence, with the largest effect observed for the sad, melancholic Winter concerto. However, no significant correlation was found between blink rate and music preference or arousal. Furthermore, no reliable association was found between blink rate and the P3a ERP component, suggesting that these measures tap into different aspects of dopamine function. These findings contribute to understanding the link between dopamine and blink rate, particularly in response to classical music. Crucially, the study's discovery that the Winter concerto, with its sorrowful tone, significantly increased the blink rate highlights the significance of sad music and perhaps the programmatic qualities of this concerto to induce a strong emotional response.

Music acoustics is an interdisciplinary field and mathematics is the basis in the music art form. Music and mathematics correlation exist since the inception of music. Various philosophers, scientists, mathematicians and musicians have expressed their views about this relationship. This paper attempts to explore this association with focus on melodic pattern identification. Mathematics in Indian Classical music with raga as the basis and just intonation tuning system is discussed. Indian vocal music clips are used for different pitch estimation algorithms in the experimentation. Harmonic product spectrum and auto-correlation algorithms are tested for accurate pitch estimation. Enhanced auto-correlation function using audio segmentation is compared with other approaches for effective pitch extraction. Results indicate pitch extraction with enhanced auto-correlation function provides accurate results as compared with other approaches tested.

In the present work we present a methodology for teaching the basis of the genetic code through music composition, with the aim to combine science and arts learning. The project was carried out by 155 students, the so-called MARGA Consortium, with ages comprised between 10 and 17 years from different public schools located in the Principality of Asturias, Spain. The different groups generated 8 different music works using a short genetic sequence obtained from the human notch1 gene, receptor of mutations leading to chronic lymphocytic leukemia.

Music therapy has served as complementary and alternative medicine for various neurological disorders. Five Phases Music Therapy (FPMT) employs the theory of five phases and five music scales or tones (宫Gong (do), 商Shang (ri), 角Jue (mi), 徵Zhi (so) and 羽Yu (la)) to analyze and treat mind-body illness. In Chinese Medicine (CM), the five music scales are used to connect the human body and the universe, interpret personalities and constitution and analyze the influences of climatic changes on health. FPMT has a self-contained theory and routine of practice application. Large amounts of clinical and fundamental reports have been available and clinical benefits have been obtained. However more systemic clinic research esp. evidence-based and random controlled trials must be performed to validate and optimize its routines and biological and neurological mechanism must be further explored. It’s reasonable to believe that the effective music therapy will attract more attention from the world outside China with the introduction of FPMT.

The adaptation stress experienced by overseas dispatched employees has serious implications for their physical and mental health and work performance. This study aimed to investigate the impact of resource-oriented music listening on work stress among overseas dispatched employees. The study recruited 10 participants of different ages and occupations who had worked abroad for at least 3 years. Five sessions of personalized resource-oriented music listening, and interviews were conducted. The Global Assessment of Recent Stress Scale (GARS) and Job Stress Scale (JSS) were used to measure stress before and after the intervention. Results showed that participants' work stress and perceived stress were significantly reduced after the music therapy intervention. The study also found that 'awareness' and 'self-acceptance' were factors that reduced regulatory stress among overseas dispatched employees. This study highlights the potential of resource-oriented music listening as a useful tool to address workplace stress and promote the well-being of expatriate employees.

Background: Music evokes positive emotions and reduces stress and anxiety. Operating Room (OR) staff face various challenges which can lead to high levels of stress. The aim of the study is to assess whether listening to music during intraoperative phases improves the work environment by reducing anxiety and stress in the entire surgical team. Methods. A prospective observational study was conducted from February to September 2023, involving medical personnel, nursing staff, and nursing students. They were divided into two groups: Group 1 with music during surgical procedures, and Group 2 without music. Participants were administered two validated instruments: the Zung Anxiety Self-Assessment Scale (SAS) to measure anxiety, and the Positive and Negative Affect Schedule to assess emotions generating stress. Additional items were included for demographics, job satisfaction, and the organization method. Results. Music did not impact anxiety but increased positive emotions while reducing negative ones. Music had an ancillary effect, highlighting the need for significant organizational interventions aimed at increasing operator satisfaction, including voluntary rather than mandatory assignments for nursing staff. Conclusions. Music appears to reduce stress in the intraoperative team when supported by a positive work environment in which assigned operators have chosen to work in the OR.

Self-efficacy and perfectionism play an important role in high-performance activities. This cross-sectional study analyses the relationship between these constructs and resilience in a sample of 145 music students (57.9% female) with a mean age of 27.77 years. Perfectionism was assessed using the Multidimensional Inventory of Perfectionism in Sport, resilience using the Resilience Scale, and self-efficacy using the General Self-Efficacy Scale. Compared to those with low resilience, students with high resilience score higher on self-efficacy and lower on dysfunctional perfectionism. No differences were observed in the total perfectionism score or adaptive perfectionism. Self-efficacy shows significant predictive power for resilience (β = .525, p < .001). Although functional perfectionism did not significantly predict resilience, a marginal negative relationship was found between dysfunctional perfectionism and resilience (β = - .156, p = .063). The results are discussed concerning their implications for music pedagogy and teacher intervention.

In this study, the effects of music therapy on anxiety for patients undergoing regional anaesthesia in an operating room was succinctly investigated. This investigation was largely based on the adapted Hospital Anxiety and Depression Score (HADS) and Spielberger State-Trait Anxiety Inventory (STAI-S), of patients undergoing regional anaesthesia in an operating room. A randomized control trial was performed on 90 patients due for surgery. The selected patients for regional anaesthesia were allocated to either the music therapy group who listened to music using headphones for the entire surgery or the no-treatment control group. Based on the findings, it has been conclusively demonstrated that music can decrease the patient's anxiety level. According to the socio-demographic evaluation, elderly patients have the highest stress hormones levels when compared to young patients. Although elderly patients are more likely to choose religious songs to help them relax, cortisol analysis revealed an increase in cortisol levels among the elderly compared with younger patients. As a result, music is especially important to be delivered to elderly patients. Nonetheless, there is no restriction against administering music to elderly patients because evidence from the Hospital Anxiety and Depression Score (HADS) and State-Trait Anxiety Inventory (STAI-S) has shown that music helps to shift their attention away from pain and complications and makes them feel tranquil. Similarly, the HADS and modified Spielberger STAI (STAI-S) analyses demonstrate a substantial outcome for both groups, with respondents responding positively. The study found that listening to music during regional anaesthesia might help people feel less worried.

The Needleman-Wunsch process is a classic tool in bioinformatics, being a dynamic programming algorithm that performs a pairwise alignment of two input biological sequences, either protein or nucleic acid. A distance matrix between the tokens used in the sequences is also required as input. The distance matrix is used to generate a positional pairwise similarity matrix between the input sequences, which is in turn used to generate a dynamic programming matrix. The best path through the dynamic programming matrix is navigated using a traceback procedure that maximises similarity, inserting gaps as necessary. Needleman-Wunsch can align both nucleic acids or proteins, which use alphabets of size 4 and 20 tokens respectively. It can also be applied to any other kind of sequence where distance matrices can be specified. Here, we apply it to chains of Pousseur’s Scambi electronic music fragments, of which there are 32, and which Pousseur categorised by their sonic properties, thus permitting the consecutive construction of distance, similarity and dynamic programming matrices. Traceback through the dynamic programming matrix thus produces contrapuntal duet compositions in which two Scambi chains are played in the maximally euphonious manner, providing also an illustration of the principles of biological sequence alignment in sound.

Mental wellness can be related to healthier living, the learning process and working environments for people in the university community. A wide range of mental wellness programmes have been explored to provide students with pleasant and satisfying experiences. The purpose of this study is to explore the effects of integrating Zen meditation(禪)and music listening on the mindfulness and happiness levels of university music therapy students. Qualitative methodology was used, and data were collected through surveys and semi-structured interviews. To investigate various aspects of data regarding the role of meditation and music (MM) programme for mindfulness and happiness, this study used thematic analysis within a qualitative research design. The results of this study indicate that the 8-week MM programme is effective in enhancing mindfulness and happiness and has positive responses to daily life stress (e.g., exam anxiety, financial difficulties, and emotional distress during the COVID-19 pandemic). The role of meditation and music in promoting mental health and well-being has long been discussed and the combination of the two has been recognised as a beneficial intervention. This paper could contribute to the support of mental health resources and coping strategies in higher education, as well as expand the potential range of integrating practices involving music and meditation.

Teaching and learning a new language is a complex process that requires more than just memorizing vocabulary and grammar rules. Immersing oneself in the target language's culture and history is essential for achieving fluency and accuracy. In recent years, researchers have explored the potential of music as a tool for language learning. This paper discusses the benefits of using music in language learning, including improved listening comprehension, pronunciation and fluency, and cultural understanding. The theoretical framework of sociocultural theory, cognitive load theory, and task-based language learning is presented to support the use of music in language learning. This paper also provides practical recommendations for learners to incorporate music into their language learning routine, as well as resources for finding music in the target language, such as online music platforms and language learning apps. The article concludes by encouraging language learners to incorporate music into their language learning routine and providing resources for finding music in the target language, such as online music platforms and language learning apps. Overall, this paper demonstrates that music can be a powerful and enjoyable tool for enhancing language learning outcomes.

The purpose of the current study was the level of the self-confidence among with high musical abilities Student? The randomly selected sample consisted of students (n= 130, M= 65, F= 65) . The analytical descriptive approach was applied in the study and self-confidence Scale developed by the author was administered to participants. Results indicated that: - The self-confidence among the high musical abilities Student students was rated high. There were no statistically significant differences at (α=≤0.05) attributed to effect of sex on the self-confidence overall degree. There were statistically no significant differences at (α≤0.05) attributed to effect of achievement on the self-confidence overall degree,

Background: Music therapy (MT) is a non-pharmacological treatment increasingly used to reduce stress and anxiety in hospitalized children affected by cancers. The aim of this study was to eval-uate the impact of MT on quality of life of children with cancer. Methods: We have conducted a quasi-experimental study between April 1 and August 31, 2021 at Bechir Hamza children's Hos-pital in Tunis, including children treated for cancer. The child or the parent completed PedsQL Module Cancer french version 3.0 questionnaires before and after four weekly music therapy ses-sions. Child's respiratory and heart rate were measured before and after each session. Results: We included 20 children whose mean age was 7 ± 4.5 years [2-14]. The median value of the total questionnaire score increased from 57 [46; 70] to 72 [67; 85] (p < 10-3) with a significant reduction in pain (p = 0.02), nausea (p = 0.009), anxiety related to medical procedures (p = 0.009) and worry about the future (p = 0.005). We highlighted a significant decrease in respiratory and heart rate after MT (p<0,05). Conclusions: MT has positive impact of on quality of life of children with cancer.

Better auditory processing of musicians is observed in previous research. As musicians differentiate their practice method and performance environment, we aimed to assess auditory perception in Greek musicians with respect to their musical specialization. If there are differences, this may provide a basis for better shaping auditory training in individuals with auditory processing disorder. The auditory tests administered were speech in noise (Speech in Babble), with and without rhythmic advantage (Word Recognition—Rhythm Component), short-term and working memory (Digit Span - Forward and Backwards), temporal resolution (Gaps In Noise) and detection of frequency discrimination threshold (DFL). Groups consisted of classical musicians, Byzantine chanters, percussionists, and non-musicians (12 participants/group). Statistical analysis revealed significant difference in: (i) word recognition in noise with precursor synchronized pulse between classical musicians compared to Byzantine musicians, (ii) better frequency discrimination of Byzantine musicians compared to non-musicians for the 2000Hz region and (iii) working memory, an advantage detected in musicians. Considering all the above, we conclude that musicians have a superior auditory perception, regardless of musical specialization. Musical training enhances elements of auditory processing and may be used as an additional rehabilitation during auditory training, focusing on specific types of music for specific auditory processing deficits.

This article presents an overview of the first AI-human collaborated album, Hello World, by SKYGGE, which utilizes Sony’s Flow Machines technologies. This case study is situated within an overview of current and emerging uses of AI in popular music production, and connects those uses with myths and fears that have circulated in discourses concerning the use of AI in general, but also in music specifically. By proposing the concept of an audio uncanny valley in relation to AIPM (artificial intelligence popular music), this article offers a lens through which to examine the more novel and unusual melodies and harmonisations made possible through AI music generation, and questions how this content relates to wider speculations about posthumanism, sincerity, and authenticity in both popular music, and more wider assumptions of anthropocentric creativity. In its documentation of the emergence of a new era of popular music, the AI era, this article surveys: (1) the current landscape of artificial intelligence popular music focusing on the use of Markov models for generative purposes; (2) posthumanist creativity and the potential for an audio uncanny valley; and (3) issues of perceived authenticity in the technologically mediated “voice”.

This paper introduces an ecological approach to quantifying diversity in musical compositions. The approach considers notations with distinct pitches and duration as equivalents of species in ecosystems, measures within a composition as equivalents of ecosystems, and the sum of measures (i.e., the entire composition) as a landscape in which ecosystems are embedded. Structural diversity can be calculated at the level of measures (“alpha diversity”) and the entire composition (“gamma diversity”). An additional metric can be derived that quantifies the structural differentiation between measures in a composition (“beta diversity”). We demonstrate the suitability of the approach in music using specifically composed examples and real songs that vary in complexity. We discuss the potential of the approach with selected examples from a potentially ample spectrum of applications within musicology research. The method seems particularly suitability for hypothesis testing to objectively identify many of the intricate phenomena in music. Because the approach extracts information present in the compositions – it lets the songs tell their structure – it can complement more complex modeling approaches used by music scholars. Combined such approaches provide opportunities for interdisciplinary research. They can help to fill knowledge gaps, stimulate further research and increase our understanding of music.

Music cultural heritage, as an important component of cultural heritage, possesses significant cultural value and inheritance significance. With the development of society and the passage of time, these precious traditional music cultural heritages inevitably face the dilemma of gradual depletion or even disappearance. In the digital age, effectively protecting and inheriting these music cultural heritages has become an urgent problem to be addressed. Therefore, this paper proposes an application method based on digital twin technology, exploring how to protect and inherit music cultural heritages through digital twin technology. By leveraging digital twin technology, a virtual museum dedicated to showcasing the richness and historical connotations of music cultures is created, preserving and simulating the soundscapes of historical music eras. Through the integration of audio archives, 3D modeling, and interactive displays, users can immerse themselves in the experience of historical music in the digital space. This paper evaluates the feasibility and cultural preservation value of this digital music history museum through the creation of music digital twin technology instances and user survey feedback, and discusses the prospects of digital twins in the field of music cultural heritage.

There is a deep link existing between symmetry and nature that may be best apprehended by using group theory. In physics, giving a symmetry group is entirely equivalent to fix natural laws (Noether’s theorem). Within such a framework, it follows that all fundamental mechanical laws may be given by defining a group of symmetry operations belonging to the Gal(3,1) symmetry group having ten generators (3 + 3 + 3 + 1 = 10). The move to special relativity amounts simply to substitute another group ISO(3,1) to Gal(3,1) and having the same number of generators. In both cases, one immediately perceives that we live in universe with 3 dimensions of space and 1 dimension of time. A further progress could be made by looking for the symmetry group that leaves Maxwell’s equations invariant. The answer to this fundamental question is the group ISO(4,2)⊗U(2)⊗U(2) characterized by 23 generators : 15 = 10 + 5 for the conformal group ISO(4,2), 4 for U(2) and hence 8 = 4 + 4 for the compact part U(2)⊗U(2) that could be related to the existence of quantum physics besides relativity. As ISO(3,1) is a sub-group of ISO(4,2), the two numbers 4 and 2 suggests that, taking into account the existence of light besides matter, we live in an universe having 4 spacelike dimensions and 2 time-like dimensions. Here, it is proposed that, as music is characterized by a scale-invariant symmetry operation (transposition by octaves) and that as time may be perceived differently in shamanic trance for instance, the two “new” dimensions of our universe may be related to music and consciousness. Related to the fifth dimension of music, the notion of diapason linking physical frequencies to a musical note is revisited. It is thus proposed to adopt a new A4 = 429.62 Hz value based on universal physical constants of our universe and on the mass of the water molecule H₂O, the most abundant molecule in the universe. Demonstration is done that this new diapason is superior to other diapasons based on frequencies of 440 Hz or even 432 Hz

Incarceration negatively affects well-being and can shift an individual’s identity through labeling theory and prisonization. Seven incarcerated girls at a juvenile residential facility were administered self-esteem and life satisfaction questionnaires, and interviews were conducted to assess the impacts of incarceration on happiness and well-being. Afterwards, an eight-week music program was implemented. Results indicated that life satisfaction was significantly lower than self-esteem (p = .037), yet all participants expressed an optimistic outlook on their future in their interviews, sharing a desire to pursue further education. Participant feedback following the music program suggests positive impacts on their emotional state and well-being.

The term Bio-Art has entered common usage to describe the interaction between the arts and the biological sciences. Although Bio-Art implies that Bio-Music would be one of its obvious sub-disciplines, the latter term has been much less frequently used. Nevertheless, there has been no shortage of projects that have brought together music and the biological sciences. Most of these projects have allowed the biological data to dictate to a large extent the sound produced, for instance the translation of genome or protein sequences into musical phrases, and therefore may be regarded as process compositions. Here I describe a Bio-Music process composition that derives its biological input from a visual representation of the expression pattern of the gene fushi tarazu in the Drosophila embryo. An equivalent pattern is constructed from the Scambi portfolio of short electronic music fragments created by Henri Pousseur in the 1950s. This general form of the resulting electronic composition follows that of the fushi tarazu pattern, while satisfying the rules of the Scambi compositional framework devised by Pousseur. The range and flexibility of Scambi make it ideally suited to other Bio-Music projects wherever there is a requirement, or desire, to build larger sonic structures from small units.

Music and language are hypothesized to share neural resources, particularly at the level of syntax processing. Recent reports suggest that attention modulates this sharing of neural resources, but the time-course of the effects of attention, and the degree to which attention operates similarly on music and language, are yet unclear. In this EEG study we manipulate the syntactic structure of simultaneously presented musical chord progressions and garden-path sentences in a modified rapid serial visual presentation paradigm, while varying top-down attentional demands to the two modalities. The Early Right Anterior Negativity (ERAN) was observed in response to both attended and unattended musical syntax violations. In contrast, an N400 was only observed in response to attended linguistic syntax violations, and a P3 only in response to attended musical syntax violations. Results show that top-down allocation of attention indeed affects the processing of syntax in both music and language, with different neural resources acting upon the two modalities particularly at later stages of cognitive processing. However, the processing of musical syntax at an earlier stage of the perceptual-cognitive pathway, as indexed by the ERAN, is partially automatic, and is strongly indicative of separate neural resources for music and language.

Indian classical music is entirely based on the “Raga” structures. In Indian classical music, a “Gharana” or school refers to the adherence of a group of musicians to a particular musical style of performing a raga. The objective of this work was to find out if any characteristic acoustic cues exist which discriminates a particular gharana from the other. Another intriguing fact is if the artists of the same gharana keep their singing style unchanged over generations or evolution of music takes place like everything else in nature. In this work, we chose to study the similarities and differences in singing style of some artists from at least four consecutive generations representing four different gharanas using robust non-linear methods. For this, alap parts of a particular raga sung by all the artists were analyzed with the help of non linear multifractal analysis (MFDFA and MFDXA) technique. The spectral width obtained from the MFDFA method gives an estimate of the complexity of the signal whereas the cross correlation coefficient obtained from the MFDXA technique gives the degree of correlation between two nonlinear time series. The observations give a cue in the direction to the scientific recognition of “Guru-Shisya Parampara” (teacher-student tradition)—a hitherto much-heard philosophical term. Moreover the variation in the complexity patterns among various gharanas will give a hint of the characteristic feature of that particular gharana as well as the effect of globalization in the field of classical music happening through past few decades.

This paper formulates the performance evaluation of cloud services as a multicriteria group decision making problem, and presents a fuzzy multicriteria group decision making method for evaluating the performance of cloud services. Interval-valued intuitionistic fuzzy numbers are used to model the inherent subjectiveness and imprecision of the performance evaluation process. An effective algorithm is developed based on the technique for order preference by similarity to ideal solution method and the Choquet integral operator for adequately solving the performance evaluation problem. An example is presented to demonstrate the applicability of the proposed fuzzy multicriteria group decision making method for solving the multicriteria group decision making problem in real world situations.

(1) Background: The elderly who have chewing difficulty (CD) are prone to malnutrition, frail-ty, and sarcopenia, and those with insufficient physical activity (IPA) are also prone to frailty, overweight, and high blood cholesterol. There is an urgent need to prepare functional foods and to promote healthy physical activity for the elderly over 70 years of age to prevent poor nutri-tion and frailty. (2) Methods: This study prepared functional foods (FF) with softened chicken moose and milkfish without fin for the elderly and compared the different effects of FF from those of music aerobic exercise (MAE) on the complete blood counts, blood biochemistry, in-cluding nutrition index of albumin, and cholesterol levels, and frailty scores before and after in-stitution of FF and MAE among residents of long-term care institutes. (3) Results: The FF signif-icantly increased the high-density lipoprotein cholesterol and albumin levels. In contrast, MAE significantly increased red blood cells (RBC), and decreased the rates of frailty items on fatigue feeling and low physical activity. In comparison between FF and MAE groups, we found that the FF for 5 weeks significantly improved better on HDL-C and MCV while the MAE for 10 weeks improved significantly better on hematopoiesis as increases in red blood cells and platelets. (4) Conclusions: Results from this study suggest that FF and MAE for the elderly have different ef-fects on nutrition status, blood biochemistry and frailty. A combination of both FF and MAE might provide better benefits of nutrition status, physical function, and frailty for the elderly.

Symbolic semantic understanding of staff images is an important part in music information retrieval. Due to the complex composition of staff symbols and the strong semantic correlation between symbol spaces, it is difficult to understand the pitch and duration of each note during performances. In this paper, we design a semantic understanding system for optical staff symbols. The system uses the YOLOv5 to implement optical staff’s low-level semantic understanding stage, which understands the pitch and duration in natural scales and other symbols that affect the pitch and duration. The proposed note encoding reconstruction algorithm is used to implement high-level semantic understanding stage. Such algorithm understands the logical, spatial, and temporal relationships between natural scales and other symbols based on music theory, and outputs digital codes for the pitch and duration of main notes during performances. The model is trained with a self-constructed SUSN dataset. Experimental results of YOLOv5 show that the precision is 0.989 and the recall is 0.972. For the system, the error rate is 0.031 and the omission rate is 0.021. The paper concludes by analysing the causes of semantic understanding errors and offers recommendations for further research. The results of this paper provide a method for multimodal music artificial intelligence applications such as notation recognition through listening, intelligent score flipping and automatic performance.

Opera and oratorio overtures exist in an indeterminate state between purely symphonic and dramatic music. While they can be and often are extracted for symphonic programs, they are ultimately tied to the story to which they grant the audience a preview of the story and music yet to come. Those that are easily extracted are so independent due to their structure, one well known to the symphony: the sonata form. In studying overtures from the 19^th century, however, one can trace a decline of the sonata form overture for one that is more subservient to the dramatic story soon to follow it. In this paper, three representatives of the early, mid and late period of the highlight this steady shift away from sonata form. Using Hepokoski and Darcy’s Elements of Sonata Theory: Norms, Types, and Deformations in the Late-Eighteenth-Century Sonata, I will categorize these overtures into one of the five sonata types listed therein. The increasing number of deformations as one moves through the overtures chronologically will illustrate the deliberate decline of use of the sonata form for the overture in favor of a clearer reflection of the upcoming story.

Music has the ability to evoke a wide variety of emotions in human listeners. Research has shown that treatment for depression and mental health disorders is significantly more effective when it is complemented by music therapy. However, because each human experiences music-induced emotions differently, there is no systematic way to accurately predict how people will respond to different types of music at an individual level. In this experiment, a model is created to predict humans’ emotional responses to music from both their electroencephalographic data (EEG) and the acoustic features of the music. By using recursive feature elimination (RFE) to extract the most relevant and performing features from the EEG and music, a regression model is fit and accurately correlates the patient’s actual music-induced emotional responses and model’s predicted responses. By reaching a mean correlation of r = 0.788, this model is significantly more accurate than previous works attempting to predict music-induced emotions (e.g. a 370% increase in accuracy as compared to Daly et al. (2015)). The results of this regression fit suggest that accurately predicting how people respond to music from brain activity is possible. Furthermore, by testing this model on specific features extracted from any musical clip, music that is most likely to evoke a happier and pleasant emotional state in an individual can be determined. This may allow music therapy practitioners, as well as music-listeners more broadly, to select music that will improve mood and mental health.

Background: Consciousness is usually interpreted as a state of being aware of one’s environment as well as self. According to the trilogy paradigm of consciousness (or simply “trilogy”), it is primarily guided by two new mental functions—awareness-based choice selection (ABCS) and discretionary selection of information for awareness (DSIA) or intentional attention—which may play a role in the choice selection during decision making. Method: To test whether ABCS and DSIA could improve the choice selection efficiency, 204 subjects were recruited using social media platforms to complete an anonymous online survey. The survey was designed to examine the role of subtle hints and cues in guiding participants’ attention toward a particular subject of awareness and this in return would increase the likelihood of selecting a correct choice among the proposed options, thereby enhancing the decision-making efficacy. Results: The participants’ attention could be successfully swayed to a particular subject matter (DSIA) in 59−73% of occasions. In addition, using ABCS increased the efficiency of selecting a correct choice among presented options. The analyses further revealed a gap between the selecting a choice during decision-making process and its execution, which is indicative of an appropriation process. Conclusion: The present study shows that sheer knowledge of facts may not be sufficient for selecting a correct choice among presented options effectively. However, as ABCS improves the choice selection efficiency, it plays an instrumental role in determining the subject of awareness, indirectly supporting the notion of DSIA.

Nowadays the freedom to make choices is considered of vital importance for decision-makers. Researchers investigating the psychological effects of choice provided empirical evidence about the many advantages of choice (i.e., increased intrinsic motivation, greater perception of self-determination, better performance, and greater life satisfaction). However, more recent studies demonstrated the downsides of choice. When the decision task difficulty exceeds the natural cognitive resources of human mind, the possibility to choose becomes more a source of unhappiness and dissatisfaction than an opportunity for a greater well-being. We here discuss in a detailed fashion the main findings of research in psychology and consumer behavior showing the bright sides and the downsides of choice.

Recently, historians have discussed the relevance of the nineteenth-century mathematical discipline of projective geometry for early modern classical logic in relation to possible solutions to semantic problems facing it. In this paper I consider Hegel’s Science of Logic as an attempt to provide a projective geometrical alternative to the implicit Euclidean underpinnings of Aristotle’s syllogistic logic. While this proceeds via Hegel’s acceptance of the role of the three means of Pythagorean music theory in Plato’s cosmology, the relevance of this can be separated from any fanciful “music of the spheres” approach by the fact that common mathematical structures underpin both music theory and projective geometry, as suggested in the name of projective geometry’s principal invariant, the “harmonic cross-ratio”. Here I demonstrate this common structure in terms of the phenomenon of “inverse foreshortening”. As with recent suggestions concerning the relevance of projective geometry for logic, Hegel’s modifications of Aristotle respond to semantic problems of his logic.

Background: In the midst of a worldwide COVID-19 pandemic music therapists previously not involved in telehealth had to develop effective remote forms of music therapy. The objective of this review was to systematically explore how music therapists previously working in-person adapted to the transfer to remote forms of therapy in the context of the coronavirus outbreak. Methods: We searched Scopus, Web of Science Core Collection, CINAHL, Medline, ProQuest Central, PubMed, EMBASE, PsycINFO and PsyARTICLES, grey literature (October 2020), and websites of professional organizations. We followed the JBI methodology for scoping reviews. Results: Out of the 194 screened texts, we included ten very heterogenous articles with an overall very low quality. Most texts described remote therapy in the form of synchronous video calls using the Internet, one paper described a concert in a patio of a residential home. We report the authors´ experience with the adaptation and activities, challenges and benefits of remote forms of therapy, recommendations of organizations, and examples and tips for online therapies. Conclusions: Music therapists have adapted the musical instruments, the hours, the technology used, the therapeutic goals, the way they prepared their clients for sessions, and other aspects. They needed to be more flexible, consult with colleagues more, and mind the client-therapist relationship's boundaries. It seems, when taken as a necessary short-term measure, online music therapy works sufficiently well. The majority of papers stated that benefits outweighed the challenges, although many benefits were directly linked with the pandemic context.

The article is devoted to applications of 2-dimensional hyperbolic numbers and their algebraic 2ⁿ-dimensional extensions in modeling some genetic and cultural phenomena. Mathematical properties of hyperbolic numbers and their bisymmetric matrix representations are described in a connection with their application to analyze the following structures: alphabets of DNA nucleobases; inherited phyllotaxis phenomena; Punnett squares in Mendelian genetics; the psychophysical Weber-Fechner law; long literary Russian texts (in their special binary representations). New methods of algebraic analysis of the harmony of musical works are proposed, taking into account the innate predisposition of people to music. The hypothesis is put forward that sets of eigenvectors of matrix representations of basis units of 2ⁿ-dimensional hyperbolic numbers play an important role in transmitting biological information. A general hyperbolic rule regarding the oligomer cooperative organization of different genomes is described jointly with its quantum-information model. Besides, the hypothesis about some analog of the Weber-Fechner law for sequences of spikes in single nerve fibers is formulated. The proposed algebraic approach is connected with the theme of the grammar of biology and applications of bisymmetric doubly stochastic matrices. Applications of hyperbolic numbers reveal hidden interrelations between structures of different biological and physical phenomena. They lead to new approaches in mathematical modeling genetic phenomena and innate biological structures.

1) Background: Bipolar or manic-depressive disorder is a malign mental disease that frequently faces social stigma. Educational and thinking models are needed to increase people’s awareness and understanding of the disorder. The arts have potential to achieve this goal. 2) Methods: This paper builds on the recent use of heavy metal music as a thinking and education model. It emphasizes the artistic component of heavy metal and its potential to characterize the symptomatology during the episodes of (hypo)mania and depression and the recurrence of these episodes. Heavy metal music has diversified into subgenres that become allegorical to both the symptoms of episodes and the recurrence of bipolar cycles. 3) Results: Examples of songs are given that mirror distinct facets of the disorder. 4) Conclusion: Although the links drawn between art (music) and science (psychiatry) are inherently subjective, such connections might be used to trigger a learning process, facilitate judgment and decision-making, and induce affective reactions and memory formation in the listener. The approach may facilitate collaborative efforts and serve healthcare professionals and educators as a communication tool to aid the public’s comprehension of the disease and an associated social paradox: On one hand, bipolar disorder incurs substantial costs to society. On the other hand, it benefits from the creative artistic and scientific endeavors of bipolar individuals from which cultural and political gains may ensue.

Rare diseases are characterized by a wide diversity of signs and symptoms and vary not only from disease to disease, but also from person to person, and living with a disease leads patients to peculiar experiences and treatments, without limits of time and space, as they extend to various environments and relationships of their lives. The objective of this study is the theoretical interaction between Value Co-creation (VC) and the Stakeholder Theory (ST) with the Shared Decision Making (SDM) health care theory. It is configured as a multiparadigmatic proposal by enabling the analysis of multiple perspectives of different stakeholders in health care. Thus, Co-created Decision Making (CDM) emerges in a logic dominated by service, with emphasis on intangible aspects and the interactivity of the relationships. It goes beyond the clinical office and the doctor-patient relationships, as studied in SDM, extending to all environments and interactions that add value to the patient's treatment. It was concluded that the essence of this new theory proposed here is neither in patient-centered care nor in patient self-care, but in co-created relationships with and between stakeholders in both directions, including non-health care environments that are important to the patient, such as relationships with friends, family, other patients with the same disease, social media, public policies, and the practice of pleasurable activities.

Digital music is one of the most important things in market due to the music royalties’ distribution in Korea. As the music market is transformed to the digital music market such as download the music and streaming, the distribution of music royalties starting from online service provider (OSP) has come to be a highly important part for music rights holders. One of the most important issues in current music royalties’ distribution in Korea is the unfair way of music royalties due to indiscriminative repeat streaming of digital music. To prevent this, music log usage data from several OSPs was collected in day-based system, however, there was a limit to identify detailed information on the use of music in current state. This paper analyzed the structural problems and limitations of settlement of music royalties, and provides a structure in which there can be transparent settlement and distribution between users and rights holders as one of the institutional measures. We’ll also propose various AI-based applications using music log usage data. The proposed system will hopefully be used for public purposes.

This study addresses the problem of accurately predicting azimuth and elevation angles of signals impinging on an antenna array employing Machine Learning (ML). Using the information obtained at a receiving system when a transmitter’s signal hits it, a Decision Tree (DT) model is trained to estimate azimuth and elevation angles simultaneously. Simulation results demonstrate the robustness of the proposed DT-based method, showcasing its ability to predict the Direction of Arrival (DOA) in diverse conditions beyond the ones present in the training dataset, i.e., the results display the model’s generalization capability. Additionally, the comparative analysis reveals that DT-based DOA estimation outperforms the state-of-the-art MUltiple SIgnal Classification (MUSIC) algorithm, establishing DTs as competitive alternatives for DOA estimation in signal reception systems.

Power law relationships, which describe scaling relationships of data, are powerful information theoretic descriptive tools in many empirical contexts, including that of music. Zipf’s law (pink noise) describes the optimum case of a power law relation where observations are exactly inversely proportional to their rank. Descriptions that approximate a pink noise signature can be said to maximize the amount of information in a signal, and is thus suggestive of a richness of an understanding. This information density of pink noise signatures is not, however, necessarily a desirable quality for explanations in general, which, by definition, “flattens out” some data while highlighting others, ideally those most relevant to an interpretation. The privileging of data most relevant to comprehension corresponds to a red noise relationship, as opposed to the pink noise of Zipf’s law or the white noise of a description that highlights nothing in particular. Here, I explore and evaluate this concept of red noise explanations in the form of analyses of three comparable short piano works: Robert Schumann’s “Von fremden Ländern und Menschen” (no.1 from Kinderszenen op. 15, 1838), Frédéric Chopin’s Prelude op. 28 no. 20 (1838-9), and Felix Mendelssohn’s “Venetianisches Gondellied” (no. 6 from Lieder ohne Worte op. 19b, 1829-30).

The onset of coronavirus disease 2019 (COVID-19), an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has sparked unprecedented change. Due to the public health guidelines imposed during the COVID-19 pandemic, there is no longer sufficient street traffic for remaining buskers to generate sufficient revenue, leading a majority of street musicians to pursue remote music production. However, real-time music production is notoriously difficult due to the excessively high latencies that current video call platforms such as Zoom and Google Meet harbor. In this paper, we propose an architecture for a platform with end-to-end, near-lossless audio transmission tailored specifically to online joint music production, called Latent Space. We discuss the usage of a recurrent autoencoder with sequence-aware encoding (RAES) and a 1D convolutional layer for audio compression, which we dub ClefNet, as well as propose a new evaluation metric for naive autoencoders (AEs), MSE-DTW loss, which combines the traditional mean square error (MSE) loss function with dynamic time warping (DTW) to prevent an increase in loss when the target sequence predicted by the AE is strictly a temporal variation of the source sequence. Moreover, we detail the logistics of a live system implementation which uses the Web Audio API to extract raw audio samples in real-time to feed into our client-side model before relaying the traffic using peer-to-peer WebRTC technology. The Latent Space platform can be accessed at https://latent-space.tech, and the code and data can be found under the MIT License at https://github.com/rvignav/ClefNet.

Purpose: The study is aimed to quantify the effects of social noise (personal music players (PMP), high-intensity noise exposure events) and road traffic noise exposures in the sample of Slovak university students living and studying in Bratislava. Methods: There were 1,003 university students (306 males and 697 females, average age 23.13±2) enrolled in the study; 347 lived in the student housing facility exposed to road traffic noise (LAeq =67.6 dB) and 656 in the control one (LAeq =53.4 dB). Respondents completed a validated ICBEN 5-grade scale “Noise annoyance questionnaire”. The exposure to PMP was objectified by the conversion of the subjective evaluation of the volume setting and duration. With the cooperation of the ENT specialist, we arranged audiometric examinations on the pilot sample of 41 volunteers. Results: From the total sample of 1,003 students, 794 (79.16 %) of them reported the use of PMP in the course of the last week; average time of 285 minutes. There was a significant difference in PMP use between the exposed (85.59 %) and the control group (75.76 %) (p=0.01). Among PMP users 30.7 % exceeded the LAV (lower action value for industry LAeq,8h = 80 dB). On a pilot sample of volunteers (n=41) audiometry testing was performed indicating a hearing threshold shift at higher frequencies in 22% of subjects. Conclusions: The results of the study on a sample of young healthy individuals showed the importance of exposure to environmental noise from different sources (transportation, neighborhood, construction, entertainment facilities, etc.) as well as social noise and the need for prevention and intervention.

Speech/music classification that facilitates optimized signal processing from classification results has been extensively adapted as an essential part of various electronics applications, such as multi-rate audio codecs, automatic speech recognition, and multimedia document indexing. In this paper, a new technique to improve the robustness of speech/music classifier for 3GPP enhanced voice service (EVS) using long short-term memory (LSTM) is proposed. For effective speech/music classification, feature vectors implemented with the LSTM are chosen from the features of the EVS. Experiments show that LSTM-based speech/music classification produces better results than conventional EVS under a variety of conditions and types of speech/music data.

This article offers a pragmatic ‘epistemology of wargaming’ which views wargames as immersive ‘thought experiments’ in which the human players involved use their experiential, empirical, and theoretical knowledge – together with whatever cognitive models they are able to deploy, or develop anew – to generate a conceptual, operational understanding of the adversarial scenario in which they are immersed; and exploit this understanding to craft tactical decisions designed to optimise the likelihood they will achieve their strategic objectives. From this perspective, contemporary interest in the use of ‘AI’-enabled tools to augment the validity of wargaming outputs – where these outputs constitute the decisions players make and the insights such decisions reveal – might most purposefully focus on: the design and implementation of wargames (to strengthen the architecture these provide to support immersive decision-making); and the analysis of players’ decisions (to better understand the cognitive models these involve and reflect). While the focus we suggest might disappoint those keen to replace human players with (semi-) autonomous decision-making machines, as long as the principal objectives of wargaming are to assess and enhance the decision-making capabilities of human players and human personnel, ‘AI’-enabled applications can only ever play a supporting role (albeit a potentially invaluable one) in the design, presentation, implementation, and analysis of wargames. As Irving Berlin might have it: ‘AI’ might soon be able to do most things better than us, but it can never replace humans when only a human will do.

Safety is very important in aviation since a loss of safety frequently results in both fatalities and financially damaging situations that are typically unrecoverable. Thus, achieving safety as much as possible is the primary goal of practically all aviation technology work. In this study, an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based classifier is created to estimate the fault risk factor of airplanes. Five categories of real fleet data belonging to structure, electrical, avionic, motor systems, and incident statistics of the planes have been used for classifier development. A risk factor determination for each plane is the output of the developed intelligent classifier, and it can be used to identify general overhaul candidate planes and stop defects and crashes before they happen. The obtained results show that using ANFIS provides a great capability in processing many inputs and outputs depending on different types and classes in the aviation industry and thus predicting the failure risk of the airplane efficiently.

This thesis presents findings from an online experiment aimed at evaluating individuals' attitudes towards their own cognitive biases that lead to objective mistakes. In a number of incentivized decision problems, a participant in the experiment might make a mistake and choose a dominated lottery (FOSD lottery), which is likely to result from a particular heuristic or cognitive bias. In this case, she is then confronted with her error under one of two treatments: a confrontation with an explanation only regarding the mistake or one with the addition of the supposed mechanism (bias). Following this explanation, her comfort level with her choice is measured. A bias that acted as a mechanism for the observed error could be considered advantageous (i.e., useful given alternative costs) or disadvantageous (i.e., mostly harmful) in other decision-making scenarios encountered during one's lifetime. Consequently, the perception of cognitive biases is subjective and may vary among decision makers, who may emphasize either the positive or negative aspects of such biases. The proposed methodology allows to determine whether these biases are perceived as useful rules of thumb, despite leading to a dominated lottery choice in that particular context, or unfavorable.Results revealed significant differences between the two treatments and across five different decision problems. Interestingly, the results showed that in only 60% of the cases, the participants felt uneasy about their mistakes. In the remaining instances, the participants demonstrated either indifference or a sense of comfort with their choice of a dominated lottery. The net effect of providing information on the cognitive biases that presumably lead to the mistakes, measured as the difference between treatments, revealed a negative perception of the mechanism behind the error in one problem, contentment with the mechanism for another, and no significant effect for the remaining biases.

Little is known about fertility preservation within the TGD community. Few receive adequate counseling placing them at risk for decision regret. The goal of this project was to develop, and pilot test the Transgender Fertility Preservation Knowledge Scale (TFPKS) to support the development and evaluation of health education resources. A community engaged; cross sectional retrospective design was used. Participants (n=189) provided information describing demographics, healthcare decision-making preferences, experiences/knowledge of fertility preservation, and treatment decision regret. The sample included 189 TGD adults. Most were white and aged 26-35 (33.3%) and not offered a consultation (73.0%). Many (41.2%) report they would have participated if offered. Knowledge regarding fertility preservation to support this desire was low. Most participants identified a patient-centered (69.4%) decision making preference. Much remains to address the healthcare inequities within the TGD population regarding fertility preservation. Overall participants had low levels of knowledge to support decision making. Further, healthcare system and individual barriers to fertility preservation remain prevalent. A foundational step towards addressing these disparities, is the identification of a valid and reliable instrument to measure TGD knowledge of fertility preservation.

Re-creation of the past of historical buildings sits at the intersection of the spatio-temporal manifestation of cultural memories, socio-cultural meanings, values and identity re-moulds and refines the existing understanding and sense of place. Digital technologies have become a popular tool in re-creation of the past by creating a new body of knowledge and historical discourse based on identifying the gaps within our written histories. Designers and policymakers around the world have been exploring various tools and technologies such as diachronic modelling yet there is a gap in evidence-based understanding regarding the actual functioning and success of application for place making. This paper, therefore, sets out to scrutinise the role of digital technologies in facilitating digital place making. To do so, it investigates the potential of a new “digital heritage” narrative in the revival of the lost architectural narrative of the Dennys Lascelles Wool Store, Geelong. The proposed paper aims to investigate the potential of a new “digital heritage” narrative and story-telling as a means towards digital place making framework. While exploring the new and unique capabilities provided by the digital narrative in capturing, simulating and disseminating ‘lost’ heritage it will further imbue a sense of place by connecting the everyday city dweller.

Machine safety is not only a prerequisite for successful production, but also the foundation for sustainability and growth of any manufacturing organisation. The latest approaches in this rapidly developing field are the integration of effective risk management tools and strategies into occupational health and safety (OHS) systems. In this article, using a specific example from practice, we will show how using multi-criteria decision making (AHP) support Machinery Safety Decision Making (MSDM) from the point of reducing losses. Using Classification and Regression Tree Analysis (CART), we estimated the efficiency, cost-effectiveness and thus the sustainability level of the relevant safety measures. These were proposed risk reduction measures that typically raised uncertainty among managers regarding the estimation of cost-effectiveness. The advantage of application decision trees approach is possibility to identify and establish relatively homogeneous groups of undesirable events and their impact on the organisation's objectives. A comprehensive model has been developed to support management decision making in manufacturing organizations in implementing and improving safety measures in line with manufacturing sustainability goals.

Investment management is a common process and practice used for achieving a desirable investment goal or outcome. Investment assessment should be carried out at various stages of project realization in accordance with capital investment volume. Investment risk management implies the effective control of all procedures and monitoring of risks in all phases of the investment project. Because of the reason that a single indicator in probability calculation of achieving optimal return from the investment does not exist, performing sufficiently reliable estimates of the quality of investments becomes a tedious task. There are many indicators, factors, and criteria required for consideration to reach the effective solution of the investment problem. Unfortunately, the systematic variation of economic situations in the marketplace stipulates the continuous and frequent changes of investment conditions and environment in which the investor should act and operate. Hence, the rules required for providing a reasonable quality of investment projects can be based only on investor’s management strategy and rely on investor’s intuition and practice. The importance of classification in investment management and decision making process is undeniable. The objects to be classified are described using assessments in accordance with various criteria which can be both quantitative and qualitative. With a competent formulation of the investment process, both methods are used in parallel. There exist various decision making approaches for the investment management, and simple additive weighting (SAW) is one of the well-known multi-criteria decision making (MCDM) methods aiming to provide an optimal decision for decision maker when solving various real-life problems, and particularly, investment problem. In this paper, fuzzy simple additive weighting (FSAW) method in group decision making is applied to undertake the capital investment expenditure for purchasing cars with the purpose of renting them to the public. The development of existing FSAW method is accomplished and this process involves the sensibility of outcomes to changes in the rate of fuzziness represented with decisions taken. Eventually, the degree of fuzziness involved in an analysis that directly attempts to model the immanent vagueness and imperfectness in particular precedency judgments made, is determined. A numerical example illustrates the importance and effectiveness of the suggested approach with the aim of ranking alternatives and hence, determining the most preferred alternative in MCDM problem.

Electric stimulation via a Cochlear Implant (CI) enables people with severe to profound sensorineural hearing loss to regain speech understanding and music appreciation and thus allowing them to actively engage in social life. Three main manufacturers (Cochlear, MED-EL and Advanced Bionics “AB”) have been offering CI systems, thus challenging CI recipients and Otolaryngologists with a difficult decision, as currently no comprehensive overview or meta-analyses on performance outcome following CI implantation is available. The main goal of this scoping review is to provide evidence that data and standardized speech and music performance tests are available for performing such comparisons. To this end, a literature search was conducted to find studies that address speech and music outcomes in CI recipients. From a total of 1592 papers, 188 paper abstracts were analyzed and 147 articles were found suitable for examination of full text. From which, 42 studies were included for synthesis. A total of 16 studies used the consonant-nucleus-consonant (CNC) word recognition test in quiet at 60db SPL. We found that aside from technical comparisons, only very few publications compare speech outcomes across manufacturers of CI systems. Evidence suggests though, that these data are available in large CI centers in Germany and US. Future studies should therefore leverage large data cohorts to perform such comparisons that could provide critical evaluation criteria and assist both CI recipients and Otolaryngologists to make informed performance-based decisions.

Music perception in foetuses has been explored under different theoretical paradigms such as habituation, categorical perception, sound preferences and recall. This study investigated the temporal dimension of music perception through the habituation and sensitization paradigm. Foetuses of 41 pregnant women, mean gestational age of 34.7 weeks (±2.4), were observed during ultrasound exams. Foetuses’ reaction to two different tempos (Allegro vs Adagio) and sources (internal vs external) of music stimuli was registered by heart rate variability (HR) and motor response according to the Assessment of Preterm Infants Behaviour scale (APIB) by its factors of movement (MOV) and organization (ORG). A folkloric lullaby, sung and played live with a stringed instrument by a musician, was presented in three stages that were compared to baseline: 1) slow tempo (Adagio), 2) fast tempo (Allegro); and 3) now sung by mother at slow tempo (Adagio). Exploratory analyses showed that all factors increased from baseline to first stage. HR and ORG varied significantly among stages, with HR being the strongest factor. MOV merely detected change from baseline to first stage. ORG decreased for Allegro but increased for maternal Adagio, while HR decreased to near baseline values. ANOVA-repeated measures with gestational age as covariate showed that all measures were sensitive to first music presentation (Adagio), although only HR and ORG differed among stages. Considering estimated marginal means, adjusted for gestational age, HR presented a sensitization pattern throughout stages, but ORG kept habituating to external source and increased to maternal Adagio, suggesting foetal discrimination by sound source. We conclude that foetuses showed different behavioural and physiological responses to external versus internal sound source and musical tempo. The combined use of a behavioural scale (APIB) and HR in foetuses proved to be a valid multidimensional instrument.

The automatic recognition of scanned Medieval manuscripts still represents a challenge due to degradation, non standard layouts, or notations. This paper focuses on the Medieval square notation developed around the 11th century which is composed of staff lines, clefs, accidentals, and neumes which are basically connected single notes. We present a novel approach to tackle the automatic transcription by applying CNN/LSTM networks that are trained using the segmentation-free CTC-loss-function which considerably facilitates the GT-production. For evaluation, we use three different manuscripts and achieve a dSAR of 86.0% on the most difficult book and 92.2% on the cleanest one. To further improve the results, we apply a neume dictionary during decoding which yields a relative improvement of about 5%.

Background: Fertility is a crucial component of population maintenance and growth. A declin-ing fertility trend has been observed over the past two decades, and it continues. Objective: The aim of this research was to examine the level of fertility knowledge, factors in-fluencing fertility knowledge, and the relationship between fertility knowledge and the decision to have a child. Methods: A cross-sectional study was conducted on a sample of mothers in five hospitals on the Adriatic coast of the Republic of Croatia, involving 1541 mothers from September 2021 to De-cember 2023. The Cardiff Fertility Knowledge Scale was used for the research. Results: The participants were divided into two groups based on fertility status in women, spe-cifically the period of declining fertility in women. Group 1 included participants aged 18-31 with sustained fertility, and Group 2 included participants aged 32 and older experiencing de-clining fertility. Fertility knowledge was 58.9%. Women with higher educational status showed better results (62.3%). The most common sources of fertility knowledge were the healthcare sys-tem and the internet. Factors associated with the level of fertility knowledge included higher education, marital status, and higher economic status. Conclusion: The research results reveal a lack of fertility knowledge among participants, as well as an intention to have a child in later stages of life. The lack of formal education on this topic leads to information gathering from unreliable sources.

Preconception or prenatal carrier screening for hereditary deafness is an effective early intervention strategy to reduce the incidence of newborn deafness, but current research is limited. This study aimed to investigate the carrier frequencies of common deafness genes in the Chinese population and to follow up on pregnancy outcomes in high-risk couples. Carrier screening for common deafness genes in the Chinese population, including the GJB2 and SLC26A4 genes, was performed using next-generation sequencing technology. Of the 9,993 subjects screened, the carrier rate was 2.86% for the GJB2 gene and 2.63% for the SLC26A4 gene. Of the six high-risk couples, four made alternative reproductive decisions (three with prenatal diagnosis and one with preimplantation genetic testing), with consequent successful termination of the birth of two affected fetuses. The frequencies of preconception or prenatal carrier screening for the deafness genes GJB2 and SLC26A4 in 9,993 subjects from China in this study were 2.86% and 2.63%, respectively. In addition, four out of six high-risk couples made alternative reproductive decisions, followed by the successful prevention of the birth of two affected fetuses. These findings confirmed the clinical utility of preconception or prenatal carrier screening for hereditary deafness.

The goal of this study is to categorize stakeholders in Internet of Things (IoT) security based on their roles in order to address the challenges associated with managing the large amount of data generated by IoT devices. With the increasing number of connected devices, the security risks also escalate, necessitating skilled stakeholders to mitigate these risks and prevent potential attacks. This study proposes a two-part approach that involves clustering stakeholders according to their responsibilities and determining relevant features to enhance decision-making. By grouping stakeholders into shared categories, the study aims to provide a more efficient and effective method for managing IoT security. The insights gained from this research will not only benefit stakeholders involved in IoT security but also assist policymakers and regulators in developing effective strategies.

Finding a suitable support is a key process in the life history of climbing plants. Climbers that find a suitable support have greater performance and fitness than those that remain prostrate. Numerous studies on climbing plant behavior have elucidated the mechanistic details of support searching and attachment. Far fewer studies have addressed the ecological significance of support-searching behavior and the factors that affect it. Among these, the diameter of supports influences their suitability for twining plants. When support diameter increases beyond some point climbing plants are unable to maintain tensional forces and therefore lose attachment to the trellis. Here we further investigate this issue by putting pea plants in the situation to choose between supports of different diameters while their movement was recorded by means of a three-dimensional motion analysis system. The results indicate that the way climbing plants move can vary depending on whether they are presented with one or two potential supports. Furthermore, when presented with a choice between a thin and a thick support, the plants showed a distinct preference for the former than the latter. The present findings shed further light on how climbers make decisions as far as support search is concerned, and provide evidence that plants adopt one of several alternative plastic responses in a way that optimally corresponds to environmental scenarios.

Transformation studies have been leaning towards the more practical aspects of change processes and have not yet dealt sufficiently with their personal and political dimensions. They are arguably constrained in doing so if they are either overly focussed on systems and how to control them or on individualistic values and behaviours. In this study we show how the actually-occurring societal transformations that people face can be usefully approached through the lenses of dialogical sense-making and critical phenomenology. While distinct, these approaches share a concern with aspects missed when transformation is abstracted and alienated from people’s lives; namely people’s lived experiences during times of change, and the conditions of possibility for these experiences. Dialogical sense-making explores how people create meaning around transformations, through interactions with other people, with different lines of arguments, and as part of broader public discourse. Critical phenomenology engages with subjectivity and lived experience, and with the role of foundational as well as socio-culturally dominant yet contingent structures in shaping our ways of perceiving, experiencing and knowing the world. Through a discussion of insights from these approaches, we show how they offer tools that enable new questions about transformative change as it is experienced and made sense of. Situating analyses of tranformation from within a focus on experience brings us closer to understanding the significance of change processes in people’s lives, and allows for an inquiry into the conditions of experience, including transformative experiences.

Decision making is a complex process involving various parts of the brain which are active during different times. It is challenging to measure externally the exact instance when any given region becomes active during the decision-making process. Here we try to extract and visualize the dynamic functional brain activation information from the observed fMRI data. We propose the use of a regularized deconvolution model to simultaneously map various activation regions within the brain and track how different activation regions changes with time. Thus, providing both spatial and temporal brain activation information. The activation information can then be further analyzed as per need and requirements. The proposed technique was validated using simulated data and then applied to a simple decision-making task for identification of various brain regions involved in different stages of decision making. The visualization aspect of the algorithm allows us to actually see the flow of activation (and deactivation) in form of a motion picture. The dynamic estimate may aid in understanding the causality of activation between various brain regions in a better way.

Multi-objective optimization (MOO) is an optimization involving minimization or maximization of several objective functions more than the conventional one objective optimization, which is useful in many fields. Many of the current methodologies addresses challenges and solutions that attempt to solve simultaneously several Objectives with multiple constraints subjoined to each. Often MOO are generally subjected to linear inequality, equality and or bounded constraint that prevent all objectives from being optimized at once. This paper reviews some recent articles in area of MOO and presents deep analysis of Random and Uniform Entry-Exit time of objectives. It further break down process into sub-process and then provide some new concepts for solving problems in MOO, which comes due to periodical objectives that do not stay for the entire duration of process lifetime, unlike permanent objectives which are optimized once for the entire process duration. A methodology based on partial optimization that optimizes each objective iteratively and weight convergence method that optimizes sub-group of objectives are given. Furthermore, another method is introduced which involve objective classification, ranking, estimation and prediction where objectives are classified based on their properties, and ranked using a given criteria and in addition estimated for an optimal weight point (pareto optimal point) if it certifies a coveted optimal weight point. Then finally predicted to find how far it deviates from the estimated optimal weight point. A Sample Mathematical Tri-Objectives and Real world Optimization was analyzed using partial method, ranking and classification method, the result showed that an objective can be added or removed without affecting previous or existing optimal solutions. Therefore suitable for handling time governed MOO. Although this paper presents concepts work only, it’s practical application are beyond the scope of this paper, however base on analysis and examples presented, the concept is worthy of igniting further research and application.

SIGNIFICANCE Putting worth on research and selection of studies by importance are crucial in medical innovation. Practical applications include choosing personal study topics, publication review, study grant selection, and decisions of spending or misspending billions in public health. Multiple studies raised alarm that current methods perform poorly in reproducibility, prediction of best research and objectivity. I propose using the metrics how much disease burden is reduced and calculating objective, numerical research value. The concept is that worth of medical research is not subjective but can be reproducible and numerically quantified. The method increases transparency by giving decision makers an externally accountable proof, and frees peer reviewers to check scientific integrity. Its numerical form can capture small differences important in competition between studies. ABSTRACT Finding value and selecting knowledge by importance are crucial in medical innovation. Applications include individuals designing research, funding organizations selecting grants, journals – publications, institutions – priorities in public health and health policy, and decision makers spending or misspending billions of research funds. Currently finding value of knowledge is done by peer review together with checking scientific integrity. Multiple studies raised alarm that it performs poorly in prediction of highest citations, bias, transparency and quality. The resulting problems include perception of slow medical progress and wasting funds and time. I introduce a standard, objective and numerical method for finding value of medical research. It measures disease burden prevented by new knowledge contained in a study or a publication. In its simple form, it is calculated by multiplying disease prevalence, disease burden, and efficacy of the therapy. It can be modified for risk of failure, multi-disease effect and for ethical considerations. The process is described step-by-step in terms common in medical practice. A quick estimate is often sufficient. The advantage is objectivity, since it is calculated from real world data. This gives transparency and externally accountability of decision making. The second advantage is a numerical form. This can measure small differences in research value which, in sharp competition, determine which studies are selected. A researcher can calculate the value of own future effort. Institutions might ask to provide it at submission. The method is also applicable to broad policy analysis, objective evaluation of scientific achievement and bibliometric studies.

The rapid and extensive loss of biodiversity globally has resulted in an increased urgency to capture and conserve the diversity which is present, including genetic diversity within species. However, for many species there is currently no detailed genetic data available to inform the collection and use of material held in ex situ collections and this can hamper the consideration of genetic issues and reduce the likelihood collection represent the diversity present. Even in the absence of direct genetic data, however, it is possible to consider genetic issues using the existing theoretical and empirical evidence-based and biological, ecological and demographic data for a given species. Here a framework to facilitate the consideration of genetic diversity and genetic issues, even where genetic data is lacking, is presented.

The current discussion about a “risk culture” in financial services was triggered by the recent series of crisis (from the US subprime mortgage crisis to the lock-in trap of central banks in the aftermath of the sovereign debt crisis). The last decade saw a long list of hybris, misconduct and criminal activities by human beings on a single or even a collective basis in banks, in the industry or in the whole economy. As a counter-reaction, financial authorities called for a guidance by a “new” risk culture in financial institutions based on a set of abstract, formal and normative governance processes. In the humanities, culture is a paraphrase for the behaviour in collectives and dynamics of organization found in human societies. Therefore, a “risk culture” should be a link between those normative guidelines and the positive “real-world” decision-making in financial services. This paper will focus on “risk culture” from the perspective of human beings interacting in dynamical and intertemporal commercial relations. In this context, “risk” is perceived by economic agents ex-ante as the consequence of the time-lag between the present and the uncertain future development (compared to a probability distribution calculated by observers ex-post). For all those individual decisions – to be made under uncertainty – future “risk” includes the so-called “normal accidents”, i.e. failures that will happen at some uncertain point in time but inevitable, and it is only the questions, when failure will happen and how to maintain function in the first line of defence. Finally, the sum of all decisions with individual responsibility for things to come is the positive economical context of a “risk culture” in the sense of the (rational) behaviour of an honourable merchant in long-term and repeated commercial relations in a merchant community, as this is a heritage of European business culture.

Aaron Copland’s only full-length opera, The Tender Land has had a difficult production history. Critics of the 1954 New York City Opera Premiere bemoaned the atypical storyline, the music declared too dry, and the singing too sparse. The opera’s failure to dazzle initial audiences is likely because it was originally written for television. Copland was commissioned to write this opera for television in 1952, but was rejected by NBC in 1953, with no official explanation given as to why. The New York City Opera premiere, therefore, was not an accurate representation of Aaron Copland's vision. The opera eventually did find receptive audiences, each success marked by a smaller, more intimate venue, not unlike the intimacy afforded on a sound stage. Perhaps most notable of these was the touring 1993 University of Minnesota production that performed in barns and farmhouses throughout the Midwest. Through this tour, the opera reached a rural community mirrored in the story, providing much more opportunity for the audience to connect to the characters. However, the question remains what caused NBC to initially reject the opera. This paper exposes the likely political obstacles that prevented Copland’s opera from premiering in its intended medium, and the subsequent consequences of displacing The Tender Land from its television premiere.

The lymphatic system of the brain meninges and head plays a crucial role in the clearance of amyloid-β protein (Aβ), a peptide thought to be pathogenic in Alzheimer’s disease (AD), from the brain. The development of methods to modulate lymphatic clearance of Aβ from the brain coild be a revolutionary step in the therapy of AD. The opening of the blood-brain barrier (OBBB) by focused ultrasound is considered as a possible tool for stimulation of clearance of Aβ from the brain of humans and animals. Here, we propose an alternative method of non-invasive music-induced OBBB that is accompanied by the activation of clearance of fluorescent Aβ (Fαβ) from the mouse brain. Using confocal imaging, fluorescence microscopy and magnetic resonance tomography, we clearly demonstrate that OBBB by music stimulates the movement of Fαβ and Omniscan in the cerebrospinal fluid and lymphatic clearance of Fαβ from the brain. We propose the extended detrended fluctuation analysis (EDFA) as a promising method for the identification of OBBB markers in the electroencephalographic (EEG) patterns. These pilot results suggest that music-induced OBBB and the EDFA analysis of EEG can be a non-invasive, low cost, labelling free, clinical perspective and completely new approach for the treatment and monitoring of AD.

Even today, the automatic digitisation of scanned documents in general but especially the automatic optical music recognition (OMR) of historical manuscripts still remain an enormous challenge, since both handwritten musical symbols and text have to be identified. This paper focuses on the Medieval so-called square notation developed in the 11th-12th century, which is already composed of staff lines, staves, clefs, accidentals, and neumes, that are roughly spoken connected single notes. The aim is to develop an algorithm that captures both the neume and pitch, that is melody information that can be used to reconstruct the original writing. Our pipeline is similar to the standard OMR approach and comprises a novel staff line and symbol detection algorithm, based on deep Fully Convolutional Networks (FCN), which perform pixel-based predictions for either staff lines or symbols and their respective types. Then, the staff line detection combines the extracted lines to staves and yields an F1-score of over 99% for both detecting lines and complete staves. For the music symbol detection we choose a novel approach that skips the step to identify neumes and instead directly predicts note components (NCs) and their respective affiliation to a neume. Furthermore, the algorithm detects clefs and accidentals. Our algorithm recognises these symbols with an F1-score of over 96% if the type is ignored and predicts the true symbol sequence of a staff with a diplomatic symbol accuracy rate (dSAR) of about 87%. If only the NCs without their respective connection to a neume, all clefs, and accidentals are of interest the algorithm reaches an harmonic symbol accuracy rate (hSAR) of approximately 90%.

The emergence of Distributed Ledger Technology (DLT) in the past decade has challenged our imagination to discover new, innovative and disruptive solutions to problems in domains ranging from finance and healthcare to supply chain and smart cities. However, the enormous energy consumption that has been observed in some of the most successful DLT applications raises the question of their long term sustainability. This article reviews the standardization efforts of the International Telecommunications Union (ITU) to provide guidelines to regulators and policy makers for making informed decisions on the applicability and sustainability of DLT architectures from the point of view of energy consumption.

Oxytocin is well known for its role in relationships and social cognition and has more recently been implicated in pain relief and pain perception. Connections between prosocial feelings and pain relief are also well documented, however, effects of exogenous oxytocin on social cognition and pain have not been explored. The current study tested whether intranasally-delivered oxytocin affects pain perception through prosocial behaviors. Additionally, moderation of the effects of oxytocin by life history or genetic polymorphisms are examined. Young adults (n=43; 65% female) were administered intranasal oxytocin (24 IU) or placebo in a crossover design on two visits separated by a one-week washout period. Pain was delivered via cold-pressor. Baseline measures for decision-making and social cognition were collected, as well as pain sensitivity and medication history. Saliva samples were collected for analysis of genetic markers, and urine samples were collected to assess oxytocin saturation. Following oxytocin administration, participants reported increased prosocial cognition and decision-making. Pain perception appeared to be adaptive, with procedural order and expectation affecting perception. Finally, behavioral trust and cooperation responses were significantly predicted by genetic markers. Oxytocin may increase a patient’s trust and cooperation and reduce pain sensitivity while having fewer physiological side effects than current pharmaceutical options.

Smartphone Addiction is a social issue caused by excessive smartphone use, affecting decision-making processes. Current research on the risky decision-making abilities of smartphone addicts is limited. This study used the fNIRS brain imaging technique and a Sequential Risk-Taking Task experimental paradigm to investigate the decision-making behavior and brain activity of smartphone addicts under varying risk levels. Using a mixed experimental design, the research assessed decision-making ability and brain activation levels as dependent variables across two groups (addiction and control), two risk amounts (high and low), and two outcomes (gain and loss). The study included 42 participants, with 25 in the addiction group and 17 in the control group. Results indicated that risk level significantly impacted the decision-making ability of smartphone addicts, with high-risk levels leading to weaker decision-making ability and increased risk-taking. However, at low risk levels, decision-making abilities between addicts and healthy individuals showed no significant difference. Furthermore, brain imaging results using fNIRS revealed stronger brain activation in the dlPFC region for smartphone addicts under loss outcome conditions, with no significant differences between the two groups in terms of brain activation at varying risk volumes. These findings are critical in promoting healthy smartphone use, guiding clinical treatment, and advancing brain mechanism research.

Type I contextuality or inconsistent connectedness is a fundamental feature of both the classical as well as the quantum realms. Type II contextuality (true contextuality or CHSH type contextuality) is frequently asserted to be specific to the quantum realm. Nevertheless, evidence for Type II contextuality in classical settings is slowly emerging (at least in the psychological realm). An example is given here of Type II contextuality involving a simple cooperative game. This arises due to the cooperative nature of the game which results in sign intransitivity for expectation values while individual random variables remain consistently connected. This shows that the conditions attributed uniquely to quantum systems may occur in classical settings as well. Sign intransitivity can be observed in preference relations in the setting of decision making and so intransitivity in decision making may also yield examples of Type II contextuality. Previously it was suggested that a fruitful setting in which to search for such contextuality is that of decision making by collective intelligence systems. An experiment was conducted using a detailed simulation of nest emigration by workers of the ant Temnothorax albipennis. In spite of intransitivity, these simulated colonies came close to but failed to violate Dzhafarov’s inequality for a 4-cyclic system. Further research using more sophisticated simulations and experimental paradigms is required

When following a prescribed route, we need to decide at each intersection which way to proceed. The present work addressed several factors that might influence the difficulty of this decision making process. Participants repeatedly followed a route through a virtual maze with twelve or eighteen intersections, and with two or three choices per intersection. One group performed task S, which promoted decision making by the serial order strategy since all intersections looked alike. Another group performed task SA, which allowed the use of the serial order and the associative cue strategy since unique visual cues were presented at each intersection. We found that in both tasks, participants were more accurate in making decisions on routes with twelve rather than eighteen intersections, and more accurate by a similar amount on routes with two rather than three choices. Reaction time in task SA was reciprocal to accuracy; reaction time in task S was generally lower and route-independent. Accuracy in task SA was similar for participants who experienced smooth transport across intersections and those who experienced abrupt transport, while accuracy in task S was lower for participants who experienced smooth rather than abrupt transport across intersections. We conclude that the number of intersections and the number of choices were equivalent determinants of route following difficulty. We further conclude that optic flow during turns at intersections interfered with anticipatory decision making in task S; hence natural (smooth) transport across intersections did not enhance route following performance.

The pace of implementation of renewable electricity storage in Europe is disappointingly slow. Several factors influence it, but there is a need to speed up the rate and increase the volumes in order to promote a 100% transition to renewable energy resources, expand the practice of using renewable energy, and contribute to the improvement of the user's quality of life. Also, an important factor is significantly reducing the global impact on the environment and climate change. Electricity from renewable energy sources such as solar and wind has a seasonal nature that cannot provide the necessary electricity consumption and cover peak loads. Also, the so-called "energy resource crisis" is a very topical problem at the moment, which reinforces the global need to increase the share of renewable energy resources in the overall balance of primary energy resources. It is precisely the wider integration of renewable electricity storage in practice that can help stimulate this. The availability of renewable electricity is constantly increasing and the level of technological innovation is rapidly developing, therefore it is valuable to analyze, look for connections and at the same time the main differences in the ways of accumulation in order to promote its availability from a private house to the national and European scale as a whole. Therefore, this article analyses and compares the different options for renewable electricity storage, from small batteries to large storage systems, arriving at the best solution according to needs, using analysis methods such as multicriteria decision analysis (MCDA) and TOPSIS. After comparing nine criteria, such as the amount of investment required, existing power density, efficiency, duration of operation and others, in both groups, it was concluded that lithium-ion batteries are currently the best solution among batteries, while in the group of large accumulation systems – pumped hydro storage.

This article is a theoretical contribution to mental model research, which currently has different threads. Whereas some researchers focus on the perceived causal structure, others also include decision policies and decisions. We focus on the link between recognized causal structure (“mental models of dynamic systems”) and policies, proposing Johnson-Laird’s theory of mental models as the link. The resulting framework hypothesizes two types of systematic mental model errors: (1) misrepresentation of the system’s structure and (2) failure to deploy relevant mental models of possibilities. Examination of three experiments through this lens reveals errors of both types. Therefore, we propose that the cognitive theory of mental models opens a path to better understand how people construct their decision policies and develop interventions to reduce such mental model errors. The article closes by raising several questions for empirical studies of the reasoning process leading from mental models of dynamic systems to decision policies.

Petrochemicals, which convert oil and gas into products such as plastics, are fundamental to modern societies. Chemists recognize their role in the design of materials and the adverse effects that these may have on the environment, preventing sustainable development. Several methodological frameworks and sustainability assessment approaches have been developed to evaluate the resources used in the petrochemical sector in terms of environmental costs. A combination of Life Cycle Assessment and Emergy Accounting - to assess the environmental support for resource use - is applied in this study of the PET production chain in Europe. The Unit Emergy Values of several intermediates are calculated or updated to facilitate discernment of the quality of energy used and the processes' efficiency. Several routes for synthesizing renewable para-xylene and ethylene glycol from biomass are discussed and confronted with the efforts focused on recycling and recovering the final product providing concurrently a procedure and a valuable data set for future CP actions. The results show that understanding the efficiencies changing across the production chain may help stakeholders make wise choices as to where and when interventions to promote a circular economy are most effective along a petrochemical production chain.

We are of the opinion that during the design of a binary classifier one ought to consider adding an “I don’t know” answer. We provide the case for the introduction of this third category when a human needs to make a decision based on the answer from a binary classifier. We discuss the costs and potential benefits of its introduction. Colloquially, we have used the term “I don’t know”, but formally we refer to it as NotAvailable. A procedure to define NotAvailable predictions in binary classifiers, called all leave-one-out models (ALOOM), is presented as proof of the concept. Furthermore, we discuss the potential benefits of applying ALOOM in real life applications.

Multi-criteria decision-making (MCDM) methods and techniques have been applied to many real-world problems in different fields of engineering science and technology. The evaluation based on distance from average solution (EDAS) method is a new and efficient MCDM method. The aim of this study is to propose a modification to address two exceptional cases in which the EDAS method fails to solve an MCDM problem.

This research article presents the integration of participatory modeling and system dynamics as a novel methodology for the consolidation of social dynamic models for the subsequent evaluation and prioritization of green projects in Colombian post-conflict communities. In the first instance, through participatory work carried out along with the community, it was possible to identify, evaluate and systematize citizen factors in relation to the problems and needs of the region. Second, based on the results obtained, to calibrate a simulation model based on system dynamics that facilitates decision making with regard to the evaluation of green projects. The proposed methodology leads to the conclusion that, with the participation of the community and with a model based on the dynamics of variables such as supply and demand for natural resources of water and land, it is possible to warn decision makers about the variables that can lead to the maximization of investments and thus prioritize and select the most appropriate environmental, social or economic initiatives, that certainly meet the needs or expectations of the involved community. In the future, the model could be used to facilitate the management, administration and control of water and land resources by creating alerts called reserve margins.

The performance of choice-reaction tasks during athletic movement has been demonstrated to evoke unfavorable lower limb biomechanics. However, the mechanism of this observation is unknown. We conducted a systematic review examining the association between 1) the biomechanical and functional safety of unplanned sports-related movements (e.g. jumps/runs with spontaneously indicated landing leg/cutting direction) and 2) markers of perceptual-cognitive function (PGF). A literature search in three databases (Pubmed, ScienceDirect, Google Scholar) identified five relevant articles. Study quality, rated by means of a modified Downs & Black checklist, was moderate to high (average: 13.5/16 points). Four of five papers, in at least one parameter, found either an association of lower PGF and reduced task safety or significantly reduced task safety in low vs. high PGF performers. Yet, as a) the outcomes, populations and statistical methods of the included trials were highly heterogeneous and b) only two out of five studies had an adequate control condition (pre-planned movement task), evidence was classified as conflicting. In sum, PGF may represent a factor increasing injury risk during unplanned sports-related movements but future research strengthening the evidence of this association is warranted.

Uncertainty is the main source of risk of geological hazards in tunnel engineering. Uncertainty information not only affects the accuracy of evaluation results, but also affects the reliability of decision-making schemes. Therefore, it is necessary to evaluate and control the impact of uncertainty on risk. In this study, the problems in existing entropy-hazard model such as inefficient decision-making and failure of decision-making are analysed, and an improved uncertainty evaluation and control process are proposed. Then the tolerance cost, the key factor in the decision-making model, is also discussed. It is considered that the amount of change in risk value (R1) can better reflect the psychological behaviour of decision-makers. Thirdly, common attribute decision models, such as the expected utility-entropy model, are analysed, and then the viewpoint of different types of decision-making issues that require different decision methods is proposed. The well-known Allais paradox is explained by the proposed methods. Finally, the engineering application results show that the uncertainty control idea proposed here is accurate and effective. This research indicates a direction for further research into uncertainty, and risk control, issues affecting underground engineering works.

Recent findings show that preferences for food items can be modified without external-reinforcements using the cue-approach task. In the task, the mere association of food item images with a neutral auditory cue and a speeded button press, resulted in enhanced preferences for the associated stimuli. Here, in a series of 10 independent samples with a total of 255 participants, we show we can enhance preferences using this non-reinforced method for faces, fractals and affective images as well as snack foods, using auditory, visual and even aversive cues. This change was highly durable in follow-up sessions performed one to six months after training. Preferences were successfully enhanced for all conditions, except for negative valence items. These findings promote our understanding of non-reinforced change, suggest a boundary condition for the effect and lay the foundation for development of novel applications.

The purposes of this study were to identify clinician’s characteristics associated with higher prescription rates of long-acting injectable (LAI) antipsychotics, as well as the information sources influencing medical decision-making about treatment of schizophrenia. We surveyed 202 psychiatrists during 6 regional French conferences (Bordeaux, Lyon, Marseille, Nice, Paris, Strasbourg). Data on the characteristics of practice, prescription rates of antipsychotic and information sources about their clinical decisions were collected. Most of psychiatrists used second-generation antipsychotic (SGA), and preferentially an oral formulation, in the treatment of schizophrenia. SGA LAI was prescribed to 30.4% of schizophrenic patients. The duration and the type of practice did not influence the class or formulation of antipsychotics used. The clinicians following the higher percentage of schizophrenic patients were associated with the higher use of LAI antipsychotics and the lower use of oral SGA. Personal experience, government regulatory approval and guidelines for the treatment of schizophrenia were the 3 main contributing factors guiding the clinical decision-making of clinicians about treatment of schizophrenia. The more clinicians follow schizophrenic patients, the more they use LAI antipsychotic. The development of specialised programmes with top specialists should lead to better use of LAI in the treatment of schizophrenia.

Several review articles about megachurch studies have been published recently concentrating their work on USA, Europe, and other parts of the world, with just a few references about Latin American megachurches. For that reason, this article aims to identify some of the characteristics of Latin American Evangelical megachurches by looking at relevant literature, especially that produced in the region, in Spanish and Portuguese, which is usually overlooked by researchers in Global North. Since this research field is still limited in Latin America, areas, where further work is necessary, are identified. Three general catalysts for the emergence of megachurches in the region, church growth methodologies, Pentecostalization, and theologies of growth, serve as guides to organize the review process. The discussion shows several potential areas of research in a variety of fields such as theology, ecclesiology, organizational theory, leadership, gender studies, and ethics, are proposed from the review.

In our recent works we reported that physical and chemical characteristics of serum can vary in relation to the psychic activity of an individual depending on whether it is oriented to stress or relaxation. We wandered if these observations could be accompanied by an appreciable modification of the Ph, electric conductivity and Delayed Luminescence of the same serum samples. Our preliminary data may suggest that the serum pH could significantly increase during a Relaxation Response intervention while electric conductivity seems to decrease. Moreover, Delayed Luminescense could vary in the same subject according to the Relaxation Response practice. According to our proof of concept study, we postulate the appearance of a coherent system within the blood samples analyzed after the Relaxation Response. Further researches and some technical development are needed to support our preliminary findings.

The new Post Accelerating Data and Knowledge Online Society, or ‘Padkos’ requires a new model of decision making. This introductory paper proposes a model where decision making and learning are a single symbiotic process, incorporating man and machine, as well as the AADD (ánthrōpos, apparatus, decider, doctrina) diamond model of individual and organizational decision-making and learning processes. The learning is incorporated by using a newly proposed quadruple loop learning model. This model allows for controlled changes of identity, the process of creating and the sense making of new mental models and assumption, and reflections. The model also incorporates the recently proposed model of quantum decision-making, where time collapse of the opted past and the anticipated future (explicitly including its time horizon) into the present play a key role in the process, leveraging decision-making and learning by human as well as Artificial Intelligence (AI) and Machine Learning (ML) algorithms. The paper closes with conclusions.

Although child-centred care is increasingly referred to within the nursing literature, a clear definition of child-centred care and clarity around the concept is yet to be achieved. The objectives of this review were to examine: 1) What constitutes the concept of child-centred care in healthcare? 2) How has the concept of child-centred care developed? 3) What is the applicability of child-centred care and what are its limitations? and 4) How does the concept of child-centred care benefit and inform children’s healthcare? In total, 2984 papers were imported for screening, following removal of duplicates and screening, 21 papers were included in the scoping review.The findings suggest that child-centred care is an emerging, ambiguous, poorly defined concept; no clear consensus exists about what constitutes child-centred care. Although it seems antithetical to argue against child-centred care, little robust evidence was identified that demonstrates the impact of, and benefit from, child-centred care. If child-centred care is to be a sustainable, convincing model to guide practice and compete with other models of care it needs to establish robust evidence of its effectiveness, impact on children and their families as well as the wider impacts on the healthcare system.

The wastewater circular economy (WW-CE) promises a solution to improve water and sanitation management worldwide. However, the transition from conventional to circular wastewater treatment plants (WWTPs) requires facilitation to aid in decision makers understanding of integral sustainability impacts of alternative WW-CE configurations. This research implemented Life Cycle Sustainability Assessment (LCSA), combining Life Cycle Assessment, Social Life Cycle Assessment and Life Cycle Costing with a Multi-criteria Decision Making (MCDM) model to quantify environmental, socio-cultural, and economic impacts of conventional WWTPs with the WW-CE. Two real WWTPs in Chile have embraced the WW-CEs and adopting the title of Biofactories. These were considered as case studies, compared under three scenarios to demonstrate the sustainability trade-offs of the transition from no sanitation to conventional WWTPs and Biofactory WW-CE configurations. Results demonstrated that the transition to WW-CEs improved integral sustainability according to the LCSA model implemented in both WWPTs. This study highlights the urgent need to adopt sustainable decision-making models to not only improve sanitation coverage, but also improve sustainability performance of the sanitation industry across the globe.

This study addresses the motivations behind Generation Z's attendance at conferences and aims to contribute to a better understanding of their conference participation behavior. The study identified six latent factors that influence conference attendance motivation: Green and Digital Conference Experience, Educational and professional opportunities, Conference costs, Destination and conference stimuli, Stimulating factors, and Conference accessibility. These factors align with Generation Z's unique characteristics and preferences, such as their environmental consciousness, reliance on digital technologies, desire for continuous learning, career advancement, and experiences. The study also found that destination characteristics and educational and professional opportunities are significant motivators for Generation Z's conference attendance across different cultural contexts. Additionally, Generation Z's strong interest in sustainability and financial challenges highlights the need for eco-friendly practices and affordable registration fees to make conferences more appealing and accessible. The study further explores the impact of socio-demographic characteristics, revealing the gender and past conference attendance differences in motivation. Finally, the study discusses the implications for the conference industry and suggests areas for future research to enhance the understanding of conference attendance motivation among Generation Z.

Purpose: To clarify the mechanism of state anxiety on intertemporal decision-making, two studies were conducted to investigate the role of trait anxiety and inhibitory control. Study 1 examined the moderating effect of trait anxiety. Study 2 continued to investigate the mediating effect of inhibition control on the basis of study 1. Methods: A total of 266 Chinese college students participated. Participants’ state anxiety, trait anxiety and intertemporal decision-making were measured by questionnaires (scales) respectively. And inhibition control was evaluated by two-choice oddball paradigm. Results: The results of Study 1 indicated that state anxiety could predict intertemporal decision-making and that the moderating effect of trait anxiety on this relationship was significant. Study 2 found that inhibitory control could completely moderate the relationship between state anxiety and intertemporal decision-making and that this indirect effect was affected by trait anxiety. Conclusion: 1)Individuals with higher trait anxiety are more inclined to make more impulsive and intertemporal decisions when they have a high level of state anxiety; 2)state anxiety allows inhibitory control ability to have a further effect on intertemporal decision-making; and 3)the higher trait anxiety in individuals, the stronger mediating effect of inhibitory control on the relationship between state anxiety and intertemporal decision-making.

This research aimed to determine salient factors affecting the decision to become a beginning organic farmer. New and beginning organic farmers have unique characteristics, showcasing their dedication to environmental justice and social justice at the expense of their own businesses. This research employed a multiple-case case study design. We conducted semi-structured interviews with 40 first-generation farmers who operate organic farms in Arkansas, Florida, or Georgia. We analyzed interview transcripts using the qualitative analysis approach of coding. Our results revealed the reasons that people with little practical knowledge start farms. They are inspired by those around them who succeed and encouraged by influential characters in the field who assure them they can do something they love and be profitable. This research showed that first-generation farmers find inspiration and develop values rooted in food justice. Our findings have implications for developing and implementing current and future programmatic activities that aim to enhance beginning farmer training and workforce development. Identifying sources of inspiration will help researchers and service providers target newer and beginning farmers to support a vibrant food system, including a burgeoning market opportunity, developing strong communities around food, and building grassroots solutions.

Background: Chikungunya virus (CHIKV) diagnosis have become a challenge for primary care physicians in areas where zika virus and/or dengue virus are present. Case definitions for the three arboviral infections are overlapping. Methods: A cross-sectional analysis was carried out. A bivariate analysis was made using confirmed CHIKV infection as the outcome. Variables with significant statistical association were included in an agreement consensus. Agreed variables were analyzed in multiple regression model. The area under the receiver operating characteristic (ROC) curve was calculated to determine a cut-off value and performance. Results: 295 patients with confirmed CHIKV infection were included. A screening tool was made using symmetric arthritis (4 points), fatigue (3 points), rash (2 points) and ankle joint pain (1 point). The ROC curve identified a cut-off value and a score ≥ 5.5 was considered positive to identify CHIKV patients with a sensibility of 64.4% and a specificity of 87.4%, positive predictive value of 85.5%, negative predictive value of 67.7%, area under the curve of 0.72, and an accuracy of 75%. Conclusion: We developed a screening tool for CHIKV diagnosis using only clinical symptoms as well as proposed an algorithm to aid the primary care physician.

Land degradation and climate change are among the main threats to the sustainability of ecosystems worldwide. Therefore, the restoration of degraded landscapes is essential to maintain the functionality of ecosystems, especially those with greater social, economic and environmental vulnerability. Nevertheless, policy-makers are frequently challenged by deciding on where to prioritize restoration actions, which usually includes to deal with multiple and complex needs under an always short budget. If these decisions are not taken based on proper data and processes, restoration implementation can easily fail. To help decision-makers taking informed decisions on where to implement restoration activities, we have developed a semiautomatic geospatial platform to prioritize areas for restoration activities based on ecological, social and economic variables. This platform takes advantage of the potential to integrate R coding, Google Earth Engine cloud computing and GIS visualization services to generate an interactive geospatial decision-maker tool for restoration. Here, we present a prototype version called "RePlant alpha" which was tested with data from the Central Zone of Chile. This exercise proved that integrating R and GEE was feasible, and that the analysis, with at least six indicators and for a specific region was also feasible to implement even from a personal computer. Therefore, the use of a virtual machine in the cloud with a large number of indicators over large areas is both possible and practical.

The notion of free will seems so intuitive to us that it would be hard, even impossible, to imagine that we live in a world without ever exerting any willpower. This view of reality is not only hindrance to inspiration, it poses a serious threat to our moral and social responsibilities. Nonetheless, many scientific and philosophical schools of thought such as determinism purport free will as a mere illusion. As an attempt to rescue free will put forward by libertarianism, compatibilism or physical indeterminism that either exempts our mind from the universal rules of cause and effect by offering our minds a metaphysical status or substitute free will with random will rooted in the laws of quantum mechanics. This manuscript offers an alternative perspective under a new paradigm of consciousness called physical libertarianism that explicates true free will through the unwavering laws of cause and effect. Based on this paradigm, consciousness is the result of interaction of awareness and decision-making process. By applying awareness to the process of decision-making awareness-based choice selection or true free will is conceived. In return, by assigning the power of decision making to the process of awareness discretionary selection of information for attention or intentional attention is emerged. Through integration of these two mental functions, an independent entity called “I” is formed that differentiates natural intelligence from artificial intelligence. While determinism can aptly describe the world of inanimate objects and artificial intelligence, because of “I,” determinism has no jurisdiction over the realm of natural intelligence.

Urban flood risk mapping is an important tool for the mitigation of flooding in view of human activities and climate change. Many developing countries, however, lack sufficiently detailed data to produce reliable risk maps with existing methods. Thus, improved methods are needed that can improve urban flood risk management in regions with scarce hydrological data. Given this, we estimated the flood risk map for Rasht City (Iran), applying a composition of decision-making and machine learning methods. Flood hazard maps were produced applying six state-of-the-art machine learning methods such as classification and regression trees (CART), random forest (RF), boosted regression trees (BRT), multivariate adaptive regression splines (MARS), multivariate discriminant analysis (MDA), and support vector machine (SVM). Flood conditioning parameters applied in modeling were elevation, slope angle, aspect, rainfall, distance to river (DTR), distance to streets (DTS), soil hydrological group (SHG), curve number (CN), distance to urban drainage (DTUD), urban drainage density (UDD), and land use. In total, 93 flood location points were collected from the regional water company of Gilan province combined with field surveys. We used the Analytic Hierarchy Process (AHP) decision-making tool for creating an urban flood vulnerability map, which is according to population density (PD), dwelling quality (DQ), household income (HI), distance to cultural heritage (DTCH), distance to medical centers and hospitals (DTMCH), and land use. Then, the urban flood risk map was derived according to flood vulnerability and flood hazard maps. Evaluation of models was performed using receiver-operator characteristic curve (ROC), accuracy, probability of detection (POD), false alarm ratio (FAR), and precision. The findings showed that the CART method is most accurate method (AUC = 0.947, accuracy = 0.892, POD = 0.867, FAR = 0.071, and precision = 0.929). The results also demonstrated that DTR, UDD, and DTUD played important roles in flood hazard modeling; whereas, the population density was the most significant parameter in vulnerability mapping. These findings indicated that machine learning methods can improve urban flood risk management significantly in regions with limited hydrological data.

The introduction of social commerce ushered in a new era in business-consumer interaction. As a result, more power has passed from the vendor to the buyer, primarily fueling e-commerce acceptance. As a result, understanding consumer behaviour in the context of social commerce adoption has become essential for businesses looking to persuade customers by using the power of social ties and support.Furthermore, such social ties will facilitate trust as the most promising benefit while reducing perceived risk, which has always been a critical problem with online commerce. This study proposes a paradigm for understanding the impact of social commerce on the stages of the consumer decision-making process: need recognition, information search, alternative evaluation, purchase decision, and post-purchase behaviour, with a focus on social support. In this respect, relevant literature in the subject of social commerce either (1) lacks an adequate explanatory model, (2) has a solid theoretical base, or (3) contains practically complex theories with insufficient empirical data. The research model applies the Social Commerce Constructs (SCC): recommendations and referrals, forums and communities, and ratings and reviews to study the respective influence on the consumer decision-making process phases. This paper aims to understand the influence of social commerce on an integrative model that incorporates all customer choice phases while expecting new knowledge. Furthermore, it is advised that this conceptual model be empirically verified to evaluate the practical consequences.

With the revolution of computing and biology technology, data sets containing information could be huge and complex that sometimes are difficult to handle. Dynamic computing is an efficient approach to solve some of the problems. Since neighborhood multigranulation rough sets(NMGRS) were proposed, few papers focused on how to calculate approximations in NMGRS and how to update them dynamically. Here we propose approaches for computing approximations in NMGRS and updating them dynamically. First, static approaches for computing approximations in NMGRS are proposed. Second, search region in data set for updating approximations in NMGRS is shrunk. Third, matrix-based approaches for updating approximations in NMGRS while decreasing or increasing neighborhood classes are proposed. Fourth, incremental algorithms for updating approximations in NMGRS while decreasing or increasing neighborhood classes are designed. Finally, the efficiency and validity of the designed algorithms are verified by experiments.

The use of machine learning (ML) approaches to target clinical problems is called to revolutionize clinical decision-making. The success of these tools is subjected to the understanding of the intrinsic processes being used during the classical pathway by which clinicians make decisions. In a parallelism with this pathway, ML can have an impact at four levels: for data acquisition, predominantly by extracting standardized, high-quality information with the smallest possible learning curve; for feature extraction, by discharging healthcare practitioners from performing tedious measurements on raw data; for interpretation, by digesting complex, heterogeneous data in order to augment the understanding of the patient status; and for decision support, by leveraging the previous step to predict clinical outcomes, response to treatment or to recommend a specific intervention. This paper discusses the state-of-the-art, as well as the current clinical status and challenges associated with each of these tasks, together with the challenges related to the learning process, the auditability/traceability, the system infrastructure and the integration within clinical processes.

In considering the question of machine as artist, the art object can be analytically separated from its making, and its making can be dualistically conceptualized as process on one hand and experience on the other. One of the reasons we value art is that there was an experience of its making. To better understand what is meant by the experience of art-making, this paper presents results from a qualitative, phenomenological study of a group of artists. These results appear in three groups: feeling, intention and lifeworld. Machines cannot experience art-making, at least not in the same way as humans, and thus they cannot create art but only art-like objects. Even so, in the present century, we should not be asking whether machines can be artists, but rather how machines can help more people experience art-making for themselves.

Background: Parents of preterm infants face major mental health challenges in the Neonatal Intensive Care Unit (NICU). Family-centered music therapy actively integrates and empowers parents in their infant’s care. With the aim to better understand and address parental needs separately from their babies’, a music therapy (MT) self-care group was implemented as part of clinical practice at the hospital Clínica de la Mujer in Bogotá, Colombia. Methods: The group is provided for both parents twice a week in the NICU. Music guided relaxations, breathing techniques, and self-expression are at the center of the MT group sessions. Parents complete a pre/post self-administered Numeric Rating Scale (NRS) including anxiety levels, stress levels, mood and motivation. Results: Parents highly value the MT self-care group at the NICU. On average there is a 37% improvement in anxiety levels, 28% in stress levels, and 12% in mood, restfulness and motivation. Being able to relax, to distract themselves from their worries and having time for themselves are amongst the most frequently mentioned benefits. Conclusions: Addressing parents’ needs separately form their babies’ treatment with culturally sensitive interventions aimed to improve parental mental health, is essential for continuing the development of family-centered music therapy interventions in the NICU.