Miracle-dz/UniFAR-FTUs huggingface dataset:
Wearable Devices for the Assessment of Cognitive Effort for Human–Robot Interaction

This paper is motivated by the need of assessing cognitive effort in affective robotics. In this context, the ultimate goal is that of assessing the mental state while the subject is interacting with a robotic system, by gathering implicit and objective information unobtrusively. To this end, we focus on wearable devices that do not affect the interaction of a human with a robot. In particular, we consider some commercial multi-purpose wearable devices, such as an armband, a smartwatch and a chest strap, and compare them in terms of accuracy in detecting cognitive effort. In an experiment setting, thirty participants were exposed to an increase in their cognitive effort by means of standard cognitive tests. Mental fatigue was estimated by measuring cardiac activity, in terms of heart rate and heart rate variability. The results have shown that the analysis of heart rate variability measured by the chest strap provides the most accurate detection of cognitive effort. Nevertheless, also measurements by the armband are sensitive to cognitive effort.
Influence of organizational culture on firm efficiency: competing values framework in Croatian forestry

For forestry sector in transition economies organizational or corporate culture can be a key link in restructuring processes and business improvements of forest companies. A considerable amount of research about corporate culture influence on firm’s efficiency in various sectors has been conducted, but no one has explored the impact of cultural and managerial components on the development of organizational structure of forest company and improvement of its organizational efficiency. This paper addresses this dearth of research by examining forestry employee’s attitudes, using Competing Value Framework and associated models. The goal is to evaluate forestry firm’s organizational culture, investigate the relationship between culture characteristics and diverse measures of company units’ efficiency (a separate structural and production units). The findings should be used as a potential mediator for the firms restructuring process and business improvement. Results of research, conducted in Croatian forestry sector context, provide evidence that developed approach, i.e. examining and identifying corporate culture, can be used for performance improvements. Results suggest that unbalanced focus of the existing firm culture, with formally directive management style and the lack of reward system, results with a strong resistance to essential improvements in forest company performance. In the discussion this is displayed and argued through a holistic approach to develop (upgrade) forest company (structural, business, and cultural) efficiency.
Utilisation of press mud as soil amendment and organic manure – A review

Pressmud is an unavoidable waste generated from sugar industries. Pressmud is rich in many plant nutrients and it also has properties to ameliorate degraded soils. For this reason pressmud is believed to be of much use in agriculture. Many research works indicate that application of pressmud improves soil fertility, nutrient uptake and yeild of crops. Sulphitation pressmud can be used to amend the alkali soil whereas carbonation pressmud is useful to reclaim acidic soils. This review discusses about the prospects of pressmud utilisation in agriculture, especially with reference to soil conditioning and crop growth.
A preliminary study on the development of colonies of Melipona beecheii in traditional and rational hives

SUMMARYSeventeen colonies of Melipona beecheii were collected from different parts of Yucatan, Mexico, and housed in rational (box) hives or in traditional log hives. Two designs of rational hive were used: the Nogueira-Neto hive (P) and the Instituto Nacional de Pesquisas de Amazonia hive (I). The internal volumes of the P, I and log hives were 14.30, 14.52 and 10.06 litres, respectively. Food stores in the original nests were not transferred to the hives and the colonies were fed on sugar syrup and supplied with cerumen. Brood volumes and numbers of food pots were determined every 15 days for 3 months following the colony transfers. The amount of brood which developed in the log hives (mean 848.21 cm3) was significantly greater than in P (mean 543.64 cm3) and I (mean 413.84 cm3) hives, but there were no significant differences between domiciles in the number of food pots built, indicating that colonies need to build up food stores before producing brood. It is suggested that the volumes of the P and I h.
Deep Learning Based Data Recovery for Localization

In this paper, we study the problem of euclidean distance matrix (EDM) recovery aiming to tackle the problem of received signal strength indicator sparsity and fluctuations in indoor environments for localization purposes. This problem is addressed under the constraints required by the internet of things communications ensuring low energy consumption and reduced online complexity compared to classical completion schemes. We propose EDM completion methods based on neural networks that allow an efficient distance recovery and denoising. A trilateration process is then applied to recovered distances to estimate the target’s position. The performance of different deep neural networks (DNN) and convolutional neural networks schemes proposed for matrix reconstruction are evaluated in a simulated indoor environment, using a realistic propagation model, and compared with traditional completion method based on the adaptative moment estimation algorithm. Obtained results show the superiority of the proposed DNN based completion systems in terms of localization mean error and online complexity compared to the classical completion.
Methacholine-Induced Cough in the Absence of Asthma: Insights From Impulse Oscillometry

Introduction The pathophysiologic differences between methacholine-induced cough but normal airway sensitivity (COUGH) and healthy individuals (CONTROL) are incompletely understood and may be due to differences in the bronchodilating effect of deep inspirations (DIs). The purpose of this study is to compare the bronchodilating effect of DIs in individuals with classic asthma (CA), cough variant asthma (CVA), and COUGH with CONTROL and to assess impulse oscillometry (IOS) measures as predictors of the bronchodilating effect of DIs. Methods A total of 43 adults [18 female; 44.8 ± 12.3 years (mean ± SD); n = 11 CA, n = 10 CVA, n = 7 COUGH, n = 15 CONTROL] underwent modified high-dose methacholine challenge, with IOS and partial/maximal expiratory flow volume (PEFV/MEFV) maneuvers (used to calculate DI Index) to a maximum change (Δ) in FEV1 of 50% from baseline (MAX). Cough count and dyspnea were measured at each dose. The relation between IOS parameters and DI Index was assessed at baseline and MAX using multivariable linear regression analysis. Results Cough frequency, dyspnea intensity, and baseline peripheral resistance (R5–R20) were significantly greater in COUGH compared with CONTROL (p = 0.006, p = 0.029, and p = 0.035, respectively). At MAX, the DI Index was significantly lower in COUGH (0.01 ± 0.36) compared with CA (0.67 ± 0.97, p = 0.008), CVA (0.51 ± 0.73, p = 0.012), and CONTROL (0.68 ± 0.45, p = 0.005). Fres and R5–R20 were independent IOS predictors of the DI Index. Conclusion The bronchodilating effect is impaired in COUGH and preserved in mild CA, CVA, and CONTROL. Increased peripheral airway resistance and decreased resonant frequency are associated with a decreased DI Index. COUGH is a clinical phenotype distinct from healthy normals and asthma.
Postmortem Neuroimaging of Cetacean Brains Using Computed Tomography and Magnetic Resonance Imaging

Postmortem computed tomography (PMCT) and postmortem magnetic resonance (PMMR) imaging (PMMRI) have been applied to provide vital or additional information for conventional necropsy, along the pioneering virtopsy-driven cetacean stranding response program in Hong Kong waters. It is common for stranded carcasses to become badly degraded and susceptible to rapid cerebral autolysis and putrefaction. Necropsy on decomposed brains with limited sample analysis often defy a specific diagnosis. Studies on PMMR neuroimaging have focused on neuroanatomy and brain morphology in freshly deceased or preserved specimens. Moreover, the literature is devoid of any reference on the potential value of PMMRI examination of decomposed cetacean brains. To that end, this project evaluated the benefits of PMMR neuroimaging in situ in decomposed carcasses in comparison to PMCT. A total of 18 cetacean carcasses were studied by PMCT and PMMRI examinations. Anatomical brain structures and visible brain pathologies were evaluated and scored using Likert-scale rating. Intracranial gas accumulation was clearly depicted in all cases by all radiological techniques. Other features were more clearly depictable in PMMRI than in PMCT images. Results of this study indicated that superiority of PMMRI compared to PMCT increased with advanced putrefaction of the brain. The preservation of structural integrity was presented by PMMRI due to its superior capability to evaluate soft tissue. Brain PMMRI should be incorporated in postmortem investigation of decomposed stranded cetaceans.
Online Grocery Shopping Adoption: A Systematic Literature Review

This article presents a Systematic Literature Review or SLR of the emerging ‘e-grocery adoption’ research scope. It proposes grocery application adoption or online grocery shopping adoption that enriches marketing study. This study aims to draft and critically reexamine the article in the features of the grocery application adoption area. The SLR delivered 38 studies presenting jointly to grocery application adoption. Ahead descriptive analytics, outcomes highlight the foremost research issues of grocery application adoption as well as various methodologies that associate researchers and members within several study methods. The article investigates the antecedents of grocery application adoption. The authors highlighted that the topic has been developed over time and identified the promising research streams for the near future. The study presents to subsequent investigations and concurrent state of the art of grocery application adoption references ultimately.
Efficient Attribute-Based Encryption Outsourcing Scheme With User and Attribute Revocation for Fog-Enabled IoT

With the rapid growth of Internet of Things (IoT) applications, fog computing enables the IoT to provide efficient services by extending the cloud computing paradigm to the edge of the network. However, the existing attribute-based encryption schemes rarely focus on user and attribute revocation in fog computing and most of them still impose high computational and storage overhead on resource-limited IoT devices. In this article, we propose an efficient attribute-based encryption outsourcing scheme with user and attribute revocation for fog-enabled IoT. The proposed scheme improves the existing encryption scheme that uses the concept of attribute groups to achieve attribute revocation, making it suitable for fog computing and improving the efficiency of ciphertext update. In addition, it implements a novel method of user revocation in fog computing based on the characteristics of fog computing. In order to reduce the computing and storage burden of IoT devices, the heavy computation operations of encryption and decryption are outsourced to fog nodes and part of secret keys are stored in fog nodes. The security analysis shows that the proposed scheme is secure under the Decisional Bilinear Diffie–Hellman (DBDH) assumption. The performance analysis shows that the proposed scheme has high revocation efficiency and is efficient enough to be deployed in practical fog computing.
A Genetic Algorithm Approach for Sizing Integrated PV-BESS Systems for Prosumers

A procedure for properly sizing integrated configurations of photovoltaic (PV) and battery energy storage systems (BESSs) is presented in this paper. Specifically, an energy management strategy oriented to maximise the electricity self-consumption has been used. In this regard, the energy management of Li-ion BESS is optimised by means of a specific tool based on a Genetic Algorithm (GA). In order to determine the best rated power and capacity of integrated PV-BESS system for residential and commercial users, the optimisation has been performed for different combination of PV and BESS rated powers and capacities, evaluating, for each of them, the annual self-consumption. The analysis of the results permits the proper choice of the PV-BESS system for a specific prosumer end for a given self-consumption target. Moreover, the proposed design approach highlights that the increase of BESS size for a defined electricity demand may lead to weak benefits in terms of increased self-consumption and, thus, to an unsuitable oversizing of the PV-BESS system.
Intention of Tourism Practitioners to Behave Actively Prevent COVID-19 in Zhangjiajie

(1) Background: This study examines the intention to behave actively prevent COVID-19 among local tourism practitioners by adopting an empirically validated norm activation model (NAM) of Schwartz and merging it with the Expectancy theory of Vroom; (2) Methods: The study aims to develops a theoretical framework for understanding the formation and predicting the change of personal protective intention to prevent COVID-19. Based on 514 valid responses from the field surveys; (3) Results: The author develops the refined model including 7 constructs and 26 observational items, and the results showed that the refined model has enjoys a better predictive accuracy of protective intention than the original NAM; and (4) Conclusions: The intention of preventing COVID-19 should needs wider public support and advocacy, and recognizing the change rule of improving behavioral intentions of preventing COVID-19 to maintain the safe tourism image of tourist attractions in Zhangjiajie is also beneﬁts for local tourism practitioners.
Incapability of utilizing galactose by pgs1 mutation occurred on the galactose incorporation step in Saccharomyces cerevisiae

A Saccharomyces cerevisiae pgsl null mutant, which is deficient with phosphatidyl glycerol (PG) and cardiolipin (CL) biosynthesis, grows well on most fermentable carbon sources, but fails to grow on non-fermentable carbon sources such as glycerol, ethanol, and lactate. This mutant also cannot grow on galactose medium as the sole carbon source. We found that the incorporation of [ 14 C]-galactose, which is the first step of the galactose metabolic pathway (Leloir pathway), into the pgsl null mutant cell was extremely repressed. Exogenously expressed PGS1 (YCpPGS1) under indigenous promoter could completely restore the pgsl growth defect on non-fermentable carbon sources, and dramatically recovered [ 14 C]-galactose incorporation into the pgs1 mutant cell. However, PGS1 expression under the GAL1 promoter (YEpP GAL1 -PGS1-myc) could not complement pgs1 null mutation, and the GAL2-lacZ fusion gene (YEpP GAL2 -lacZ) also did not exhibit its β-galactosidase activity in the pgsl mutant. In wild-type yeast, antimycin A (1 μg/ml), which inhibits mitochondrial complex III, severely repressed not only the expression of the GAL2-lacZ fusion gene, but also uptake of [ 14 C]-galactose. However, exogenously expressed PGS1 partially relieved these inhibitory effects of antimycin A in both the pgsl mutant and wild-type yeast, although it could not basically restore the growth defect on galactose by antimycin A. These results suggest that the PGS1 gene product has an important role in utilization of galactose by Gal genes, and that intact mitochondrial function with PGS1 should be required for galactose incorporation into the Leloir pathway. The PGS1 gene might provide a clue to resolve the historic issue about the incapability of galactose with deteriorated mitochondrial function.
The Effect of Family Ownership Concentration, Internet Financial Reporting and Company Sizes on Information Asymmetry

The purpose of this research is to analyze the influence of family ownership concentration, internet financial reporting and firm size toward information asymmetry with volatility of stock yield as the control variable. This research uses manufacture companies listed in Indonesia Stock Exchange on 2018 data and the analysis of multiple regression will be used to analyze the data. The results of the study indicate that family ownership concentration and internet financial reporting does not have significant effect on information asymmetry. Meanwhile the firm size has significant negative effect to information asymmetry.
Cryptocurrencies and Artificial Intelligence: Challenges and Opportunities

Decentralized cryptocurrencies have gained a lot of attention over the last decade. Bitcoin was introduced as the first cryptocurrency to allow direct online payments without relying on centralized financial entities. The use of Bitcoin has vastly grown as a financial asset rather than just a tool for online payments. A lot of cryptocurrencies have been created since 2011 with Bitcoin dominating the cryptocurrencies’ market. With plenty of cryptocurrencies being used as financial assets and with millions of trades being executed through different exchange services, cryptocurrencies are susceptible to trading problems and challenges similar to those traditionally encountered in the financial domain. Price and trend prediction, volatility prediction, portfolio construction and fraud detection are some examples related to trading. In addition, there are other challenges that are specific to the domain of cryptocurrencies such as mining, cybersecurity, anonymity and privacy. In this paper, we survey the application of artificial intelligence techniques to address these challenges for cryptocurrencies with their vast amount of daily transactions, trades and news that are beyond human capabilities to analyze and learn from. This paper discusses the recent research work done in this emerging area and compares them in terms of used techniques and datasets. It also highlights possible research gaps and some potential areas for improvement.
Bearing Fault Detection with Data Augmentation Based on 2-D CNN and 1-D CNN

Bearings are one of the most essential parts of rotary machines. The failure of bearings can lead to significant financial loss as well as personal casualties. Therefore, bearing defect diagnosis is a very important research project. Recently, a lot of bearing defect diagnosis studies using deep learning methods have been conducted. However, there are some challenges to be addressed. In a real working condition, there is always much more normal data than fault data, so a data imbalance problem exists. To address this situation, data augmentation method which generates more training data from the original data, was used. This method was done by applying a geometric transformation so that the class label did not be changed. Therefore, in this paper, we compared the results of using and without data augmentation technique through 1-D CNN and 2-D CNN deep learning algorithm that are effective on time series data analysis and pattern recognition. Finally, we obtained better results when using data augmentation technique.
New finds of Chara oedophylla Feldmann in Tunisia: significance of sejoined gametangia

: Chara oedophylla was established as a new species after examination of specimens collected by L. Gauthier in Tunisia in 1926, which were kept at the herbarium of Paris. Subsequently, several scientists considered it to be a variety of Chara vulgaris. During fieldwork in northern Tunisia, we found the species close to its type locality (Mogods region). Detailed examination of abundant populations of these plants revealed their particular, specific morphology. Chara oedophylla is characterised by a sejoined arrangement of the gametangia (on different nodes), whereas they are conjoined in C. vulgaris . The antheridia are very large, as is usually the case in dioecious species. In contrast to C. vulgaris , where geminate oogonia are side by side, they are vertically geminated in C. oedophylla. The female nodes bear numerous swollen bract cells, hence the etymology of the species name. Here we provide an emended diagnosis that highlights the differences compared to C. vulgaris in order to maintain C. oedophylla as a valid species. The significance of sejoined gametangia with respect to speciation is discussed.
DATA MINING TECHNIQUES FOR INCREASING SMART FARMING IN AGRARIAN SECTOR

: Agriculture become more fruitful when data mining techniques is used, data mining with agronomy boost up the agribusiness and may accomplish the increasing demand of livestock in the world. Agriculture is art of breeding the food plants where all kind of livestock includes, the agrarian, agronomy & cultivation are the another name for agriculture. So by mixing these two fields and applying various data mining techniques in agronomy it gives so many benefits. The aim of this scrutiny is to disclose peculiar extraction approaches in agrarian field, to find those which gives best result and also try to find out the best data mining tool which can be used in agriculture with these techniques. In this paper, various studies proposed the data eradication technique which gives most appropriate result in the field of cultivation for more clear vision. These eradication approaches can be used to find out the solution for real time problems like weather, temperature, soil, rain, pH, Moisture, pesticides & Disease forewarnings which help farmers to achieve their expected crop result.
Wildlife Habitat Relationships in Forested Ecosystems

Originally published in 1992 and welcomed both by professors of forestry and working forest managers, Wildlife Habitat Relationships in Forested Ecosystems has been revised and updated to include new material on adaptive resource management, the eco-regions of the United States, and forest wildlife habitat relationships in Canada and Mexico and on U.S. Indian reservations. It proposes a systems analysis approach to management of habitat relationships, making a convincing case for the importance of using computer-maintained databases and computer models in ecosystem management. The author provides problem-solving techniques for forest managers and decision makers, using an interdisciplinary approach unique to this book. Part of the author's innovation is his development of a specially designed relational data model for microcomputers which helps to organize habitat relationships for decision making by forest managers. He shows the reader how to set up a similar model in a database to store wildlife information for use in evaluating any given local habitat.
Evaluation of INNO dental Implants placed with high insertion torques (Up to 135 Ncm)

Purpose: This study evaluated on the clinical outcome of 42 implants placed with an insertion torque equal or greater than 70 Ncm and evaluated bone levels around these implants. Methods: This prospective study included 48 patients treated with 66 implants of 4.5 mm (INNO® implant Cowellmedi, Pusan, Korea). Maximum insertion torque (MIT) was recorded with an electronic torque measuring device (Tohnichi® STC200CN, Hitachi, Tokyo, Japan). Nine implants (control group) presented MIT between 30 and 50 Ncm (mean = 37.1 Ncm) and 42 implants (experimental group) MIT greater than 70 Ncm (mean = 110.6 Ncm, range: 70.8–176 Ncm). Marginal bone levels were recorded at the time of loading and 1 year later for the two groups. Results: After 2–3 months of sumerged healing, all implants were clinically stable. Mean marginal bone resorption was 1.03 mm (SD = 0.44) for the control group (low torque) and 0.72 mm (SD = 0.56) for the experimental group (high torque) at time of loading, and 1.09 (SD = 0.62) and 1.24 mm (SD = 0.75), respectively, after 1 year. There were no significant differences between the two groups for bone stability and implant success rate. Conclusions: The use of high insertion torques (up to 135 Ncm) did not prevent osseointegration. Marginal bone levels in the control and experimental groups were similar both at the time of loading and 1 year later.