Miracle-dz/UniFAR-FTUs huggingface dataset:
First Attempt to Infer Sound Hearing and Its Paleoenvironmental Implications in the Extinct Insular Canid Cynotherium sardous Studiati, 1857 (Sardinia, Italy)

Simple Summary The microtomographic approach allows nondestructive acquisition of anatomical details of the bone labyrinth that houses the inner ear. The petrosal bone can be a gold mine of information for a variety of questions in different research fields, including taxonomic, behavioral, and genetic studies. The semicircular canals provide information on head posture and locomotor ability, whereas the cochlea provides data on hearing ability. The petrosal bone is the hardest structure in the skeleton and could be well preserved in fossil specimens. As a result, it is becoming more and more popular in current archaeological and paleontological studies. In this study, petrosal microtomographic analysis was applied for the first time to Cynotherium sardous, a highly modified endemic canid that inhabited Sardinia during the Middle to Late Pleistocene. Indications about its hearing ability may provide interesting insights to better understand the new lifestyle and behavior this canid acquired during the long evolutionary process it underwent in the peculiar insular ecosystem with a depleted fauna. The poor hearing and echolocalization capabilities of Cynotherium sardous would have been the outcome of reduced competition pressure due to the absence of predators and the abundance of prey, such as the large ochotonid Prolagus sardus, while the high-frequency hearing could be interpreted as an adaptation to detect sounds emitted by its preferred prey. Abstract This is the first study on the bony labyrinth of Cynotherium sardous, an intriguing extinct canid that inhabited Sardinia in the late Middle and Late Pleistocene. The morphological features of the cochlea indicate that C. sardous had a lower number of cochlear turns (2.25) than all extant canids. This feature, as well as the reduced length of the spiral canal, the cochlear curvature rate, and the narrow basal membrane, indicates that C. sardous had poor hearing abilities limited to high-frequency sounds with a low limit of 250 Hz and poor echolocalization skills. From the data available, it is not possible to infer whether C. sardous was unable to echolocalize its prey and relied on other senses (e.g., smell and sight) to locate them or whether the acoustic range of C. sardous was specialized for identifying the sounds produced by its most common prey to transmit signals for predator warnings or group communication. All things considered, the results obtained confirm the utility of cochlea morphological studies in reconstructing the hearing abilities of this species and in providing some suggestions about its ethology, but they fall short of providing any new sound evidence regarding the ecological role of C. sardous in the Late Pleistocene Sardinian ecosystem.
Development and Evaluation of a Saturated Zone Module in an Integrated Urban Hydrological Model

Shallow urban groundwater interacts with surface water and underground infrastructures. Low-impact development in urban water management by at-source infiltration should consider shallow urban groundwater in a holistic manner. Traditional hydrological models, however, rarely detail groundwater flows and their interaction with urban runoff and the water budget. In the present study, a new approach is proposed, using the integration of a flow module WTI for the saturated zone in a distributed urban hydrological model URBS-MO. This integration is carried out by paying attention to retaining the initial waterflow subsurface parameterization. The performance of the integrated model is evaluated by piezometric and runoff data in an experimental urban catchment, through a sensitivity analysis and a manual calibration of the main model parameters, as well as a validation step. The new module shows its capacity to improve groundwater flow simulation by assessing more realistic water table variation, along with a very small improvement of flowrate simulation. The bias on the average groundwater level was reduced from +14 to +7% for the one-year validation period. The modelling results show the importance of parameter calibration for distributed physically-based hydrological models. Difficulties in the calibration of parameter values due to spatial heterogeneities are also revealed, as the use of piezometric data for the calibration of a hydrological model is rather innovative.
Melissa officinalis: Composition, Pharmacological Effects and Derived Release Systems—A Review

Melissa officinalis is a medicinal plant rich in biologically active compounds which is used worldwide for its therapeutic effects. Chemical studies on its composition have shown that it contains mainly flavonoids, terpenoids, phenolic acids, tannins, and essential oil. The main active constituents of Melissa officinalis are volatile compounds (geranial, neral, citronellal and geraniol), triterpenes (ursolic acid and oleanolic acid), phenolic acids (rosmarinic acid, caffeic acid and chlorogenic acid), and flavonoids (quercetin, rhamnocitrin, and luteolin). According to the biological studies, the essential oil and extracts of Melissa officinalis have active compounds that determine many pharmacological effects with potential medical uses. A new field of research has led to the development of controlled release systems with active substances from plants. Therefore, the essential oil or extract of Melissa officinalis has become a major target to be incorporated into various controlled release systems which allow a sustained delivery.
TEACHING TECHNOLOGY FORESIGHT TO BUSINESS AND MANAGEMENT STUDENTS

Predicting the future is an important, yet highly difficult management task. Disruptive technologies create new ways of working, shopping, and consuming, offering both risk and opportunity. Leading experts struggle to make accurate predictions about which technology will become ubiquitous, and which will face obscurity. However, 82% of jobs require digital skills, and while the current skillset is known, future requirements are unknown. Therefore, developing the ability of students to understand and capitalise on technology change is a problematic, but worthwhile endeavour. Technology foresight, sometimes called road-mapping is the process of looking at current trends and identifying how a new technology might impact a country, industry, market, or firm, should the future application and posited benefits be realised. This is problematic because – contrary to other forms of forecasting in which ex post forecasts can be compared to events – the dynamic nature of technology means that comparison is extremely difficult. This paper reports on the design and delivery of a module called Trends in Technology, to third year undergraduate Marketing students at a UK University. Hitherto, there would appear not to be an academic model to support teaching technology foresight. Therefore, through synthesis of literature of technology foresight and pedagogy with regard to design thinking, a process was developed that could be taught. Design thinking was selected because it is particularly useful when a solution cannot be judged in absolute terms and where user or customer perceptions of the same solution may differ based on a wide range of heuristics, which may be unknown to the designer. Students reported that a design thinking approach to technology application enabled them to relate to it and how it may impact their everyday lives. This fostered engagement. Furthermore, the potential career impact was recognised, with, for example, assessment artefacts being used as evidence to support job applications and interviews. Contributions include presentation of a process for teaching technology foresight and a theoretical model that explains how technology foresight can be applied to marketing theory to create both firm and consumer value.
Conceptual Model of Conflict Resolution for Personal Assistants of Nigerian National Assembly Members

The paper investigated the major conflicts of interests existing between the assembly members and the people they are representing and suggested possible ways in which the personal assistants of the national assembly members could help them to resolve such conflicts and foster good relationship. It was shown that the people and the assembly members may differ in opinions because of the varying levels of sensitivity of the assembly members to certain issues, however, the personal assistants of the assembly members could help by adopting conflict resolution and management techniques and take some definite steps in addressing such issues. The steps to be taken have been well enumerated and a model was suggested.
Cybersecurity Deep: Approaches, Attacks Dataset, and Comparative Study

ABSTRACT Cyber attacks are increasing rapidly due to advanced digital technologies used by hackers. In addition, cybercriminals are conducting cyber attacks, making cyber security a rapidly growing field. Although machine learning techniques worked well in solving large-scale cybersecurity problems, an emerging concept of deep learning (DL) that caught on during this period caused information security specialists to improvise the result. The deep learning techniques analyzed in this study are convolution neural networks, recurrent neural networks, and deep neural networks in the context of cybersecurity.A framework is proposed, and a real-time laboratory setup is performed to capture network packets and examine this captured data using various DL techniques. A comparable interpretation is presented under the DL techniques with essential parameters, particularly accuracy, false alarm rate, precision, and detection rate. The DL techniques experimental output projects improvise the performance of various real-time cybersecurity applications on a real-time dataset. CNN model provides the highest accuracy of 98.64% with a precision of 98% with binary class. The RNN model offers the second-highest accuracy of 97.75%. CNN model provides the highest accuracy of 98.42 with multiclass class. The study shows that DL techniques can be effectively used in cybersecurity applications. Future research areas are being elaborated, including the potential research topics to improve several DL methodologies for cybersecurity applications.
Fragmentation inside proton-transfer-reaction-based mass spectrometers limits the detection of ROOR and ROOH peroxides

Abstract. Proton transfer reaction (PTR) is a commonly applied ionization technique for mass spectrometers, in which hydronium ions (H3O+) transfer a proton to analytes with higher proton affinities than the water molecule. This method has most commonly been used to quantify volatile hydrocarbons, but later-generation PTR instruments have been designed for better throughput of less volatile species, allowing detection of more functionalized molecules as well. For example, the recently developed Vocus PTR time-of-flight mass spectrometer (PTR-TOF) has been shown to agree well with an iodide-adduct-based chemical ionization mass spectrometer (CIMS) for products with 3–5 O atoms from oxidation of monoterpenes (C10H16). However, while several different types of CIMS instruments (including those using iodide) detect abundant signals also at “dimeric” species, believed to be primarily ROOR peroxides, no such signals have been observed in the Vocus PTR even though these compounds fulfil the condition of having higher proton affinity than water. More traditional PTR instruments have been limited to volatile molecules as the inlets have not been designed for transmission of easily condensable species. Some newer instruments, like the Vocus PTR, have overcome this limitation but are still not able to detect the full range of functionalized products, suggesting that other limitations need to be considered. One such limitation, well-documented in PTR literature, is the tendency of protonation to lead to fragmentation of some analytes. In this work, we evaluate the potential for PTR to detect dimers and the most oxygenated compounds as these have been shown to be crucial for forming atmospheric aerosol particles. We studied the detection of dimers using a Vocus PTR-TOF in laboratory experiments, as well as through quantum chemical calculations. Only noisy signals of potential dimers were observed during experiments on the ozonolysis of the monoterpene α-pinene, while a few small signals of dimeric compounds were detected during the ozonolysis of cyclohexene. During the latter experiments, we also tested varying the pressures and electric fields in the ionization region of the Vocus PTR-TOF, finding that only small improvements were possible in the relative dimer contributions. Calculations for model ROOR and ROOH systems showed that most of these peroxides should fragment partially following protonation. With the inclusion of additional energy from the ion–molecule collisions driven by the electric fields in the ionization source, computational results suggest substantial or nearly complete fragmentation of dimers. Our study thus suggests that while the improved versions of PTR-based mass spectrometers are very powerful tools for measuring hydrocarbons and their moderately oxidized products, other types of CIMS are likely more suitable for the detection of ROOR and ROOH species.
The Effect of Plant Density and Supplementary Irrigation on Nutritional Value of Two Safflower (Carthamustincturius L.) Forage Crops

ABSTRACT Safflower (Carthamustinctorius L.) is an important forage. An experiment was carried out to investigate the effects of planting density and supplementary irrigation on quantitative and qualitative forage yield of two safflower cultivars as a split-factorial at the research farm of the Agricultural Faculty of Ilam University, Iran during 2015–2017. The main factor was irrigation at two levels (supplementary irrigation and dry-land) and sub–factors included density levels (20, 30, 40, 50, and 60 kgseed/ha) and cultivars (Goldasht and Faraman) in three replications. In both growing seasons, supplementary irrigation (SI) increased Ash, neutral detergent fiber (NDF), Phosphorus (P) and fresh forage yield (FFY), while rain-fed (RF) increased crude protein (CP), ethereal extract (EE) and potassium (K). Faraman had better FFY, Ash, EE and K in terms of these traits, while Goldasht was better than Faraman. Improving FFY through increasing in plant density per unit area was considered appropriate, so that the densities of 50 and 60 (kg/ha−1) in SI treatment in both cultivars were concluded as more effective, while in RF treatment for having better nutritional value (in terms of protein and fat content) lower density was observed as more appropriate and in order to have less NDF higher density was more suitable. Due to the two-year data of nutritional values and yields, it was concluded that the crop had the ability to adapt to and tolerate drought condition and increase yield in semi-arid regions. Also, it is suitable in terms of nutritional value and forage production in dry-land areas of experiment.
The Role of Circulating Tumor Cells in the Prognosis of Metastatic Triple-Negative Breast Cancers: A Systematic Review of the Literature

Breast cancer is one of the leading causes of death in women worldwide. One subtype of breast cancer is the triple-negative, which accounts for 15% of total breast cancer cases and is known for its poor prognosis. The main cause of death is due to metastasis. Circulating tumor cells (CTCs) play a key role in the metastatic process. CTCs arise either by detaching from the primary tumor or from cancer stem cells undergoing an epithelial-to-mesenchymal transition (EMT). This review aims to present up-to-date data concerning the role of CTC numbers in relation to the prognostic and treatment response in metastatic triple-negative breast cancer (mTNBC) patients, and also to discuss the methods used for CTCs’ identification. A search in the MEDLINE database was performed. A total of 234 articles were identified. The results of the 24 eligible studies showed that positive CTC status is associated with shorter overall survival (OS) and progression-free survival (PFS) in mTNBC patients. Furthermore, a decrease in number of CTCs during therapy seems to be a favorable prognostic factor, making CTCs’ detection an important prognostic tool before and during therapy in mTNBC patients. The methods used for CTC detection are still developing and need further improvement.
A Comparative Analysis for Optical Character Recognition for Text Extraction from Images Using Artificial Neural Network Fuzzy Inference System

Artificial neural networks (ANN) has the capability to analyze raw data from processing input-output relationships. This function considers them important in areas of industry with such information is unusual. Researchers have tried to extract the information embedded within ANNs as set of rules used with inference systems to resolve the black-box function of ANNs. When ANN applied within a fuzzy inference system, the extracted rules yield high classification accuracy. In this paper a Multi-Layer Neural Feed-Forward Network using Artificial Neural Network Fuzzy Inference System (MLNFFN-ANNFIS) is proposed for accurate character recognition from images. The technique targets areas of business that have less complicated issues about which there is no simpler approach is desired to a complex one. This paper proposed an Optical Character Recognition model for Text Extraction from Images using Artificial Neural Network Fuzzy Inference System for accurate text detection from images. The technique proposed is more effective and simple than most of the techniques previously proposed. The proposed model is compared with various traditional models and the results indicate that the proposed model accuracy is more and performance is also improved.
Does Objectively Measured Social-Media or Smartphone Use Predict Depression, Anxiety, or Social Isolation Among Young Adults?

Despite a plethora of research, the link between digital-technology use and psychological distress among young adults remains inconclusive. Findings in this area are typically undermined by methodological limitations related to measurement, study design, and statistical analysis. Addressing these limitations, we examined the prospective, within-persons associations between three aspects of objectively measured digital-technology use (duration and frequency of smartphone use, duration of social-media use) and three aspects of psychological distress (depression, anxiety, and social isolation) among a sample of young adults (N = 384). Across 81 different model specifications, we found that most within-persons prospective effects between digital-technology use and psychological distress were statistically nonsignificant, and all were very small—even the largest effects were unlikely to register a meaningful impact on a person’s psychological distress. In post hoc subgroup analyses, we found scant evidence for the claim that digital-technology use is more harmful for women and/or younger people.
Knowledge Management in Practice: Using Wikis to Facilitate Project-Based Learning

Knowledge is created when individuals come together to solve a problem. Project-based learning focuses on solving problems. One aspect of the work of a 21 st century design engineer is the requirement to work remotely on design projects. Engineers coming together to design a product face the problem of working remotely, collaborating, creating, and sharing knowledge. This chapter explores the use of wikis in a product design and development class at an Irish university. This chapter begins by giving an introduction to wikis and their use in education. The design project exercise and assessment process is described. The results of a study are provided that indicate that the vast majority of students found wikis to be a good tool for project collaboration. Wikis were found to be an excellent knowledge management tool that facilitates project-based learning. © 2013, IGI Global.
Contesting globalization and internationalization of higher education: discourse and responses in the Asia Pacific Region

Shaopeng Li is a lecturer in EFL at Shanghai International Studies University in China. He has studied in the Department of Theoretical and Applied Linguistics, University of Cambridge before earning his PhD. His research interests are in second language acquisition and EFL education. He has published in these fields, including a monograph, a book chapter in New Perspectives on Transfer in Second Language Learning (Multilingual Matters), along with several reviews and journal articles in international journals. His publications appear in such journals as English Today, Studies in Second Language Learning and Teaching, International Journal of Applied Linguistics and Southern African Linguistics and Applied Language Studies.
Multidimensional attitudes: Homonationalist and selective tolerance toward homosexuality and Muslim migration across 21 Countries

Attitudinal studies illustrate high levels of support toward homosexuality across European countries. Although these patterns suggest that European societies are becoming more progressive and tolerant, they do not extend to Muslim migration. As Western conceptions of liberalism are increasingly defined in terms of tolerance of sexual minorities as a marker of societal progress, persistent anti-Muslim sentiment presents a liberalism paradox. Existing research often explores these two social topics independently, with limited attention to their intersection. Moving beyond this unidimensional lens, we draw on the frameworks of homonationalism and illiberal liberalism to provide insights into how seemingly incompatible perspectives are mutually constitutive and operate in the service of individuals’ self-interest. We use latent class analysis to examine attitudinal configurations related to homosexuality and Muslim exclusion from the 7th wave (2014) of the European Social Survey (ESS). Our analysis identifies three dominant attitudinal clusters. We find that most respondents held multidimensional views—supporting homosexuality while simultaneously rejecting Muslim migration—consistent with selective tolerance and homonationalist perspectives. The remaining two clusters held unified viewpoints, either rejecting both homosexuality and Muslim migration or favoring both. Predicting these attitudinal configurations with socio-demographic characteristics and attitudes towards immigration, we find that those with selective tolerance-homonationalist perspectives occupy a precarious middle-class position characterized by low levels of educational attainment and lower-status white-collar occupations. We find evidence that individuals in this tenuous social class position express both economic and cultural threat by reappropriating tolerant views toward homosexuality for the purpose of justifying Muslim exclusion.
Labor Substitutability among Schooling Groups

Knowing the degree of substitutability between schooling groups is essential to understanding the role of human capital in income dierences and to assessing the economic impact of such policies as schooling subsidies, immigration systems, or redistributive taxes. We derive a lower bound for the substitutability required for worldwide growth in real GDP from 1960 to 2010 to be consistent with a stable wage premium for schooling despite the rapid growth in schooling, assuming no exogenous worldwide regress in the technology frontier for workers with only primary schooling. at lower bound for the long-run elasticity of substitution is about 4, which is far higher than values commonly used in the literature. Given our bound, we reexamine the importance of human capital in cross-country income dierences and the roles of school quality versus the skill bias of technology in greater eciency gains from schooling in richer countries. JEL Codes: E24, J24, O15, O47