Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of whey of Mozzarella di Bufala Campana fermented by lactic acid bacteria as a bread biopreservative agent

Summary A total of nine isolated lactic acid bacteria (LAB) from tomato and sourdough with antifungal activity were employed to revaluate the whey of Mozzarella di Bufala through the fermentation process for 72 h at 37 ° C. Then, the fermented whey (BWF) was characterised and used as biopreservative in bread formu-lation. L . plantarum TR7 and L . plantarum TR2 strains showed average lactic acid concentration in BWF of 13.8 g L (cid:1) 1 . Also, the bread volatile organic compounds (VOC) analysis showed an increase in hexanal, benzeneacetaldehyde, benzaldehyde and pyrazine tetramethyl when using BWF as ingredient. Moreover, the DPPH-inhibitory activity of bread with BWF extract also reﬂected a 33% rise in comparison with control bread. The application of BWF as a biopreservation agent in bread showed an increase in shelf life compared with bread with 0.3% calcium propionate and bread control for 2 and 15 days, respectively. BWF can be used as an interesting biopreservation strategy of bread.
Prevalence and Characteristics of Insomnia Problems Among Adults in Central Istria

Aim: We sought to examine the frequency and characteristics of insomnia among adults in central Istria, as well as to analyse sociodemographic characteristics and explore whether there is an association between symptoms of insomnia and sociodemographic parameters. Methods: This research included 685 participants that visited family medicine offices (FMOs) in Central Istria from September till December 2016. Mean age of the sample was 52.73 ± 17.93 years. Participants were randomly selected and interviewed and all gave their informed consent. Participants with sleep disturbances and insomnia lasting one year prior to study enrolment were assessed using the questionnaire designed for the study; along with gathering of sociodemographic data. Results: More than half of the participants had insomnia, 30% of them each night or several times a week, mostly older participants and women. Regardless of the frequency of insomnia symptoms, all participants reported great impairment in all areas of daytime functioning. The most frequent incidence of insomnia was associated with more frequent sleep apnoea and less frequent bruxism. Frequent night awakenings and restless legs syndrome were not related to a greater incidence of insomnia. Conclusion: Insomnia is a common problem among patients treated in primary care. Family physicians are therefore in an ideal position to identify, evaluate and treat insomnia. The high prevalence of insomnia highlights the need for a more adequate recognition and treatment of this psychiatric illness.
Deep Transfer Learning Method Based on 1D-CNN for Bearing Fault Diagnosis

In mechanical fault diagnosis, it is impossible to collect massive labeled samples with the same distribution in real industry. Transfer learning, a promising method, is usually used to address the critical problem. However, as the number of samples increases, the interdomain distribution discrepancy measurement of the existing method has a higher computational complexity, which may make the generalization ability of the method worse. To solve the problem, we propose a deep transfer learning method based on 1D-CNN for rolling bearing fault diagnosis. First, 1-dimension convolutional neural network (1D-CNN), as the basic framework, is used to extract features from vibration signal. The CORrelation ALignment (CORAL) is employed to minimize marginal distribution discrepancy between the source domain and target domain. Then, the cross-entropy loss function and Adam optimizer are used to minimize the classification errors and the second-order statistics of feature distance between the source domain and target domain, respectively. Finally, based on the bearing datasets of Case Western Reserve University and Jiangnan University, seven transfer fault diagnosis comparison experiments are carried out. The results show that our method has better performance.
The impact of the image on personal life: is current law out of focus?

ABSTRACT Drawing upon empirical research carried out by the author, this paper demonstrates that the current law in England and Wales on privacy fails to provide appropriate recourse for a person who feels aggrieved at their photograph being taken and shared, particularly where this evokes emotions of embarrassment or humiliation. Whilst some improvements to the current law are discussed to improve protection for the photographed's privacy rights, the main conclusion suggests that a greater focus on education and guidance would be a pragmatic and cost-effective solution, with this shift in emphasis concentrating efforts on the actions of the photographer. In turn, this would protect the interests of the photographed as a form of preventative measure, rather than reactionary move.
Combined Pretreatment as an Effective Technology in Breaking of Phenolic Polymer Lignin from Sustainable Biomass: Bambusa balcooa

Bamboo biomass is a potential source for the production of monomeric sugars containing high cellulose content with low amount of lignin. However, for efficient hydrolysis, the biomass treatment by effective pretreatment technique is required to minimize lignin content and other barrier components. During present study, the bamboo biomass was treated with different physical, chemical, biological and combined treatments to reduce the lignin content. Among all the pretreatments, the maximum lignin removal (14.5%) was obtained with the combined chemical and biological treatment under 2% NaOH+1% H2O2 +WDP2 fungal culture (5 plugs) conditions. In addition, lignolytic fungus and NaOH pretreatment was mainly effective in removing lignin, whereas the H2O2 pretreatment efficiently minimize cellulose crystallinity. To analyze structural changes of raw and treated biomass, we used scanning electron microscopy and fourier transform infrared spectroscopy. The structural analysis indicated that all treatments causes disruption in the biomass structure and loses the compactness of the biomass which facilitates the biomass conversion during hydrolysis process. The findings of the present study indicate effective pretreatment methods in breaching the recalcitrancy of the potential lignocellulosic biomass for maximum hydrolysis.
Temporal Dynamics of Event-Related Potentials during Inhibitory Control Characterize Age-Related Neural Compensation

Aging is accompanied by frontal lobe and non-dominant hemisphere recruitment that supports executive functioning, such as inhibitory control, which is crucial to all cognitive functions. However, the spatio-temporal sequence of processing underlying successful inhibition and how it changes with age is understudied. Thus, we capitalized on the temporal precision of event-related potentials (ERPs) to assess the functional lateralization of N200 (conflict monitoring) and P300 (inhibitory performance evaluation) in young and healthy older adults during comparably performed successful stop-signal inhibition. We additionally used temporal principal components analysis (PCA) to further interrogate the continuous spatio-temporal dynamics underlying N200 and P300 activation for each group. Young adults demonstrated left hemisphere-dominant N200, while older adults demonstrated overall larger amplitudes and right hemisphere dominance. N200 activation was explained by a single PCA factor in both age groups, but with a more anterior scalp distribution in older adults. The P300 amplitudes were larger in the right hemisphere in young, but bilateral in old, with old larger than young in the left hemisphere. P300 was also explained by a single factor in young adults but by two factors in older adults, including distinct parieto-occipital and anterior activation. These findings highlight the differential functional asymmetries of conflict monitoring (N200) and inhibitory evaluation and adaptation (P300) processes and further illuminate unique age-related spatio-temporal recruitment patterns. Older adults demonstrated lateralized recruitment during conflict processing and bilateral recruitment during evaluation and adaptation, with anterior recruitment common to both processes. These fine-grained analyses are critically important for more precise understanding of age-related compensatory activation.
Developing and Assessing Learning Progression for Botanical Literacy by Using Rasch Analysis

This study aimed to develop a learning progression (LP) for botanical literacy and assess the impact of a garden-based education course on Thai pre-service science teachers (n = 49). The inquiry- and community-based education course was taught over a 15-week period. To measure botanical literacy, a 50-item multiple-choice test was employed. A hypothetical model of the construct was proposed and validated using a dichotomous Rasch model. Results indicated that the model fits the data well. Thus, the hypothetical model was confirmed. The validated botanical literacy comprised conceptual and procedural domains. Each domain had several core ideas and subordinate concepts located on a linear construct and arranged by increasing difficulty. For example, in the conceptual domain, the core ideas arranged from the easiest to most difficult were plant diversity, plant morphology, and plant eco-physiology. The botanical literacy of the pre-service teachers was measured before and after the instruction. To measure the learning gain, we fixed the pre- and post-item difficulty and estimated the post-instruction person ability. The means of pre- and post-instruction person ability were compared using the Welch t-test. We found that learning gain was statistically significant (p < 0.01). This study discusses implications of LP for botanical literacy in biology education.
Dynamics and Drivers of Grasslands in the Eurasian Steppe during 2000–2014

The Eurasian steppe (EAS) is the largest contiguous grassland worldwide. Quantitative evaluations of the relative impacts of climate change and human activities on grasslands are significant for understanding grassland degradation mechanisms and controlling degraded grasslands. In this study, we analyzed the grassland productivity based on multiple forms of net primary productivity (NPP), including climate NPP (CNPP), actual NPP (ANPP), and human-caused NPP (HNPP) during 2000–2014. The results demonstrate that the average value of annual ANPP in the EAS was 47.36 gC/(m2·year), with a weak decrease (−0.02 gC/(m2·year)) during the study period. The area of grassland degradation account for 48.52% of the total grassland area in EAS, while the area of grassland recovery account for 51.48%. Restorative grassland was mainly distributed in Mongolia and China, while worse grassland was mainly distributed in the Kazakh steppe regions. Grassland degradation in China was mainly caused by climate change, whereas it was mainly caused by human activities in Mongolia. Grassland recovery in Kazakh steppe regions was mainly caused by human activities, but in Mongolia, it was mainly caused by climate change. Compared with temperature, precipitation played a more significant role on grassland productivity.
Identification and modelling of race driving styles

A good understanding and modelling of the human driver is essential for modern vehicle development, particularly in motorsports, where the race car should fit its driver perfectly. At the same time, an objective assessment and especially imitation of professional race drivers is difficult due to individual driving styles, complex and non-deterministic decision making processes, and small stability margins. In this paper, we present a holistic approach to identify and model individual race driving styles in a robust way. We develop the Driver Identification and Metric Ranking Algorithm (DIMRA) as a data-based method for an in-depth objective analysis and assessment of professional race drivers. Supported by this knowledge, we extend and adapt the imitation learning framework Probabilistic Modeling of Driver Behavior (ProMoD) in order to model race drivers in a complex simulation environment. An evaluation with data from professional race drivers shows the capability of DIMRA to derive metrics which describe human race driving styles, as well as ProMoD to robustly generate competitive laps with human-like controls in a professional motorsport driving simulator. The ability to identify and imitate individual driving styles does not only support the performance optimisation of race cars but could also aid the development of road cars and driver assistance systems in future work.
Sahelian Heat Wave Characterization From Observational Data Sets

This paper makes use of spaceborne observational data sets in order to characterize radiative processes involved in spring time heat waves in the Sahel. Spring corresponds to the hottest period of the year, with a high aerosol load, a gradual moistening, and the presence of clouds contributing to greenhouse effect. Heat waves are defined as synoptic events that have a large spatial extent and a duration longer than 3 days. Two types of heat waves are studied: daytime heat waves, detected with the daily maximum temperature and nighttime heat waves, detected with the daily minimum temperature. Daytime heat waves correspond to situations where cloud optical thickness is lower than the climatology and a large number of these situations are also associated with a lower aerosol load and a drier atmosphere. Nighttime heat waves correspond to a moister atmosphere compared to the climatology. In a large fraction of them, an increase in aerosol loading is also observed. This study, only based on observational data sets, highlights the subtle but different radiative balance at play in both types of events.
Explaining different types of undeclared work: lessons from a 2019 Eurobarometer survey

PurposeUntil now, most scholars have used one of four competing theories to explain undeclared work. Political economy theories explain undeclared work as resulting from the exclusion of workers from formal work and welfare, neo-liberal theories explain such work as a voluntarily chosen rational economic decision and neo-institutionalist and post-structuralist theories explain those engaging as social actors who disagree with the formal rules or seek to help others out respectively. Recognising that each theory focuses upon different employment relationships, this paper evaluates the proposition that these different theories are more explanations of different types of undeclared work.Design/methodology/approachTo evaluate this, data reported is collected in 2019 across 28 European countries (the 27 member states of the European Union and the United Kingdom) in special Eurobarometer survey 92.1 involving 27,565 interviews.FindingsOf the 3.6% of citizens participating in undeclared work, 10% engage in undeclared waged employment, 42% in undeclared self-employment and 48% in undeclared paid favours. Reporting their rationales, 7% state purely political economy exclusion-driven reasons, 19% solely neo-liberal rational economic actor reasons, 20% purely social actor reasons and 54% mixed motives. A logistic regression analysis finds those engaging in undeclared waged employment significantly more likely to state purely exclusion-driven rationales, those engaging in undeclared self-employment significantly more likely to state neo-liberal rational economic actor and neo-institutionalist social actor rationales and those engaging in undeclared paid favours post-structuralist social actor motives.Practical implicationsThis finding suggests that the policy initiatives required to tackle undeclared work will vary according to the type of undeclared work addressed. These are outlined.Originality/valueEvidence is provided that a different weighting needs to be given to different theories when explaining each type of undeclared work.
Chemical Weather and Chemical Climate

Progress in fundamental understanding of atmospheric chemistry in the past decades has enabled the development of advanced environmental predictive capability. Accurate chemical weather forecasts and source attribution information can play a decisive role in mitigating the short‐term exposure of the public to acute air pollution episodes. Chemical climate projections will allow investigation of the long‐term consequences of human choices and their impact on the future evolution of the Earth system. This commentary stresses the importance of integrating atmospheric chemistry in operational environmental prediction and projection systems.
Diagnostic Support System for the Detection of Attention Deficit Hyperactivity Disorder Using EOG Signals

Although Attention Deficit Hyperactivity Disorder (ADHD) is a common childhood disease, objective diagnostic methods are insufficient still. Current diagnostic methods include the subjective influence of the evaluator. In this context, in our study, we aimed to minimize the subjective effect of the evaluator with the objective diagnosis support system for ADHD.In our study, a visual stimulus follow-up test developed by us was applied to the patient with ADHD and healthy individuals, and electrooculogram (EOG) signals were recorded simultaneously. With the features extracted from EOG signals, Artificial Neural Networks (ANN) were used for the classification study of patients and healthy individuals, and it was determined that the classification of ADHD and healthy group could be distinguished by 81.76% performance. Thus, the outcomes that will contribute to the objective diagnosis of ADHD have been presented. The results are remarkable and important findings have been obtained that will contribute to the literature.
Spatial distribution of participation in boycott calls: a study of tourism destination boycotts associated with animal abuse

ABSTRACT Boycott is a form of protest that has been employed worldwide to challenge policies and alter behaviour that is perceived to be unacceptable. However, few studies have addressed tourism boycotts, particularly factors that influence participation from a spatial perspective. Utilizing tweets that were posted calling for the tourism boycott of China, Kerala, South Africa, and Spain, this paper analyses the spatial distribution of boycott calls. Proximity associated with awareness, local politics, changing ideologies, access to the boycott space, and concern about the boycott trigger is observed to contribute to the spatial distribution of participation in the boycott calls.
Antecedents to green apparel purchase behavior of Indian consumers

ABSTRACT The current study examines the influence of innovativeness theory-based consumer independent judgment making (CIJM), novelty-seeking behavior (CNS), green apparel knowledge (GAK) and green apparel perceived effectiveness (GAPE) on green apparel purchase behavior (GAPB) in an emerging economy, i.e., India. The covariance-based structural equation modeling (CB-SEM) and a fuzzy-set qualitative comparative analysis (fsQCA) were employed. A mall intercept method was used for data collection across 10 cities in India. A total of 450 responses were obtained through a structured questionnaire. Results indicated that green apparel perceived effectiveness (GAPE) and green apparel knowledge (GAK) had a positive influence on Indian consumers’ green apparel purchase behavior (GAPB). Consumer innovativeness construct of consumer independent judgment making (CIJM) and novelty-seeking behavior (CNS) had no positive impact on green apparel purchase behavior (GAPB). The findings can help green apparel manufacturers, environmentalists, and marketers to focus on prominently communicating the environment-related benefits of green apparels. Green clothing benefits may be improved by incorporating new fashion, designs, fabrics, and trendy styles.
Herzrhythmusstörungen im Kindesalter und bei angeborenen Herzfehlern

Alter 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0 H ä u fi g k e it ABKÜRZUNGEN ARVC arrhythmogene rechtsventrikuläre Kardiomyopathie AV-Block atrioventrikulärer Block ICD implantierbarer KardioverterDefibrillator LQTS langes QT-Syndrom SA-Block sinuatrialer Block SM Schrittmacher SVES supraventrikuläre Extrasystolen SVT supraventrikuläre Tachykardie VES ventrikuläre Extrasystole VF Kammerflimmern (ventricular fibrillation) VT ventrikuläre Tachykardie WPW Wolff-Parkinson-White
The Relationship between Complications, Common Knowledge Details and Self-handicapping Strategies and Veracity: A Meta-analysis

Practitioners frequently inform us that variable ‘total details’ is not suitable for lie detection purposes in real life interviews. Practitioners cannot count the number of details in real time and the threshold of details required to classify someone as a truth teller or a lie teller is unknown. The authors started to address these issues by examining three new verbal veracity cues: complications, common knowledge details, and self-handicapping strategies. We present a meta-analysis regarding these three variables and compared the results with ‘total details’. Truth tellers reported more details (d = 0.28 to d = 0.45) and more complications (d = 0.51 to d = 0.62) and fewer common knowledge details (d = -0.40 to d = -0.46) and self-handicapping strategies (d = -0.37 to d = -0.50) than lie tellers. Complications was the best diagnostic veracity cue. The findings were similar for the initial free recall and the second recall in which only new information was examined. Four moderators (scenario, motivation, modality, and interview technique) did not affect the results. As a conclusion, complications in particular appear to be a good veracity indicator but more research is required. We included suggestions for such research.
Inhibition of the fungus Colletotrichum lindemuthianum in the presence of different potassium sorbate concentrations

One of the major problems of in vitro plant cultivation is caused by contaminations such as fungal, which represent great losses for plant cultivation laboratories. In view of the problem about contamination and gaps in efficient disinfection protocols, the present study aimed to evaluate the inhibition of the fungus Colletotrichum. lindemuthianum in the presence of the potassium sorbate food preservative at different concentrations (0 g L-1; 0.076 g. L-1; 0.15 g. L-1; 0.30 g. L-1; 0.45 g. L-1; 0.60 g. L-1 and 0.75 g. L-1). The analyses of the Percentage of Micelal Growth Inhibition (ICP) and the growth at 24 and 72 hours at different concentrations were quantified. It was observed that Potassium Sorbate was effective in the analysis of ICP at different concentrations in relation to control, with greater effectiveness for T4 to T7. The highest percentages of inhibition (T5 to T7) presenting an inhibition rate of mean mycelial growth of 17.5 % in relation to the control for the 72h period, indicating, therefore, that with further studies this preservative can be used to combat fungal microorganisms in vitro culture.