Miracle-dz/UniFAR-FTUs huggingface dataset:
Circulating Tumor Cell Separation of Blood Cells and Sorting in novel Microfluidic approaches: a review

Separation and interpretation of rebellious Circulating Tumor Cells (CTCs) originating from the primary tumor or cancer tissue plays a significant role in diagnostics, cancer progression analyses, suitable medicine exploration, and treatment proficiency examination. Cancer metastasis occurs when CTCs spread throughout the body and invade healthy tissues, leading to new tumors in that area. Although a dramatic rate of deaths begins from spreading CTCs around the body, valuable measures have been made to control their development. However, the first step is separating these harmful cells from the bloodstream and investigating their features. Having examined the characteristics of CTCs as cancer’s main strength, researchers can introduce complementary treatments that can affect cancerous cells without damaging the healthy cells. Therefore, according to their unique characteristics, numerous techniques have been established for continuous and fast separation and sorting of CTCs. Nevertheless, few separators enjoy the efficient performance and appropriate accuracy and can be produced in mass numbers due to the available fabrication equipment. Microfabrication advancements enable separators to combine the advantages of active and passive methods in a small-scale platform for probing individual cells and separation purposes. Reduction in reagents, sample volume, analysis time, and less harmfulness to patients are some of the motivations that encourage researchers to employ microfluidic instruments for CTCs separation from other blood cells over the last two decades. However, microfabrication limitations mean effective separators, and the diagnostic option they provide, are not readily available. Addressing these limitations requires optimizing the design and fabrication of separators such that they are reduced in their size and fabrication cost, while also maintaining high-throughput separating capability. The emergence of the Lab-On-a-Chip (LOC) and then Lab-On-a-CD (LOCD) technologies, having more inherent benefits than conventional microfluidic devices, has created new opportunities and become increasingly widespread in recent years. Evidence suggests that employing single methodologies or integrating approaches without sufficient understanding of potential outcomes is unlikely to result in successful diagnostic results. This paper contributes an extensive review of several separation systems, including fundamental theories and experimental details, and describes detailed operating principles and device performance.
Internet addiction and educational attitude

The investigator aimed to find out the impact of internet addiction on educational attitude of adolescent students. Through non-probability random sampling 200 adolescent students of higher secondary class were selected from Muzaffarpur District of Bihar. Internet addiction test developed by Kimberly young and adapted and standardized in Hindi language by researcher himself was used while educational attitude was measured through educational attitude scale developed by Dr. C Bhasin. For data analysis descriptive analysis and Pearson’s Coefficient of Correlation ‘r’ were employed to achieve the objective of this study. Results revealed that internet addiction had negative effect on the educational attitude of adolescents having r-values -. 249significat at . 05 (two tailed). The negative two tailed r – value indicated that internet addiction not only impact educational attitude of internet addicted samples but also reveal the fact that the two variables affected negatively one another. The r calculated between internet non-addicted group and their educational attitude scores is – . 615 significant at . 01(two tailed) level of confidence. The two variables, internet addiction and educational attitude negatively affecting each other simultaneously.
Contextual Identification of Windows Malware through Semantic Interpretation of API Call Sequence

The proper interpretation of the malware API call sequence plays a crucial role in identifying its malicious intent. Moreover, there is a necessity to characterize smart malware mimicry activities that resemble goodware programs. Those types of malware imply further challenges in recognizing their malicious activities. In this paper, we propose a standard and straightforward contextual behavioral models that characterize Windows malware and goodware. We relied on the word embedding to realize the contextual association that may occur between API functions in malware sequences. Our empirical results proved that there is a considerable distinction between malware and goodware call sequences. Based on that distinction, we propose a new method to detect malware that relies on the Markov chain. We also propose a heuristic method that identifies malware’s mimicry activities by tracking the likelihood behavior of a given API call sequence. Experimental results showed that our proposed model outperforms other peer models that rely on API call sequences. Our model returns an average malware detection accuracy of 0.990, with a false positive rate of 0.010. Regarding malware mimicry, our model shows an average noteworthy accuracy of 0.993 in detecting false positives.
Enantiocontrolled Construction of Functionalized Tetrahydrofurans: Total Synthesis of (6S,7S,9R,10R)-6,9-Epoxynonadec-18-ene-7,10-diol, a Marine Natural Product

An efficient strategy has been developed for the construction of highly functionalized tetrahydrofurans. The key feature involves the use of Sharpless asymmetric dihydroxylation and the choice of a new bis-C3 building block 5 as the starting material which increased the efficiency. On the basis of this methodology, a marine natural product, (6S,7S,9R,10R)-6,9-epoxynonadec-18-ene-7,10-diol (1), was successfully synthesized in high enantioselectivity.
Artificial intelligence in radiology: does it impact medical students preference for radiology as their future career?

Objective: To test medical students’ perceptions of the impact of artificial intelligence (AI) on radiology and the influence of these perceptions on their choice of radiology as a lifetime career. Methods: A cross-sectional multicenter survey of medical students in Saudi Arabia was conducted in April 2019. Results: Of the 476 respondents, 34 considered radiology their first specialty choice, 26 considered it their second choice, and 65 considered it their third choice. Only 31% believed that AI would replace radiologists in their lifetime, while 44.8% believed that AI would minimize the number of radiologists needed in the future. Approximately 50% believed they had a good understanding of AI; however, when knowledge of AI was tested using five questions, on average, only 22% of the questions were answered correctly. Among the respondents who ranked radiology as their first choice, 58.8% were anxious about the uncertain impact of AI on radiology. The number of respondents who ranked radiology as one of their top three choices increased by 14 when AI was not a consideration. Radiology conferences and the opinions of radiologists had the most influence on the respondents’ preferences for radiology. Conclusion: The worry that AI might displace radiologists in the future had a negative influence on medical students’ consideration of radiology as a career. Academic radiologists are encouraged to educate their students about AI and its potential impact when students are considering radiology as a lifetime career choice. Advances in knowledge: Rapid advances of AI in radiology will certainly impact the specialty, the concern of AI impact on radiology had negative influence in our participants and investing in AI education and is highly recommended.
Research on the teaching practice itself in physical education classes: implications and challenges perceived by a teacher-researcher

ABSTRACT It is through the daily construction of teaching supported by research strategies that the teachers constantly learn and promote their professional development. As they teach, they learn about themselves, their students and the social context. By taking on the task of investigating their own practice, the teacher also learns the art and challenges of being a researcher. Self-study of Teacher Education Practice methodology was used to identify and analyse the challenges and obstacles perceived by a physical education teacher when acting as a researcher of her own teaching. The instruments for producing information were records created by the teacher-researcher: videos, photographs, observation recorded in field notes, interviews with the collaborating teacher and with the children, audio recording and transcription of the collaborative processes understood in the self-study as critical friends, and the teacher’s reflective narrative about the research process. The information produced was analysed in a thematic form, identifying units of meaning according to the purpose of the study. The analysis of the results indicates that the teacher-researcher perceived barriers and methodological difficulties to act simultaneously in the management of the class and in the production and analysis of the information about her teaching, constantly dealing with the complexity of the school’s everyday activities. The perceived challenges emerged in three moments: in the research planning, in the production of information and records, and in the information analysis. The study allowed us to understand that the teachers’ research on their teaching practice is a challenging process of learning, and that their improvement as researchers is a major factor also to the improvement of teaching.
Improving the Environmental Impact Classification for Alien Taxa (EICAT): a summary of revisions to the framework and guidelines

The Environmental Impact Classification for Alien Taxa (EICAT) classifies the impacts caused by alien species in their introduced range in standardised terms across taxa and recipient environments. Impacts are classified into one of five levels of severity, from Minimal Concern to Massive, via one of 12 impact mechanisms. Here, we explain revisions based on an IUCN-wide consultation process to the previously-published EICAT framework and guidelines, to clarify why these changes were necessary. These changes mainly concern: the distinction between the two highest levels of impact severity (Major and Massive impacts), the scenarios of the five levels of severity for the hybridisation and disease transmission mechanisms, the broadening of existing impact mechanisms to capture overlooked mechanisms, the Current (Maximum) Impact, and the way uncertainty of individual impact assessments is evaluated. Our aim in explaining this revision process is to ensure consistency of EICAT assessments, by improving the understanding of the framework.
Error Analysis and Uncertainty in the Determination of Aerosol Optical Properties Using Cavity Ring-Down Spectroscopy, Integrating Nephelometry, and the Extinction-Minus-Scattering Method

Despite the substantial improvements in the measurements of aerosol physical and chemical properties and in the direct and indirect radiative effects of aerosols, there is still a need for studying the properties of aerosols under controlled laboratory conditions to develop a mechanistic and quantitative understanding of aerosol formation, chemistry, and dynamics. In this work, we present the factors that affect measurement accuracy and the resulting uncertainties of the extinction-minus-scattering method using a combination of cavity ring-down spectroscopy (CRDS) and integrating nephelometry at a wider range of optical wavelengths than previously attempted. Purely scattering polystyrene latex (PSL) spheres with diameters from 107–303 nm and absorbing polystyrene spheres (APSL) with 390 nm diameter were used to determine the consistency and agreement, within experimental uncertainties, of CRDS and nephelometer values with theoretical calculations derived from Mie theory for non-absorbing spheres. Overall uncertainties for extinction cross-section were largely 10%–11% and dominated by condensation particle counter (CPC) measurement error. Two methods for determining σext error are described, and they were found to produce equivalent results. Systematic uncertainties due to particle losses, RD cell geometry (RL), CPC counting efficiency, ring-down regression fitting, blank drift, optical tweezing, and recapturing of forward scattered light are also investigated. The random error observed in this work for absorbing spheres is comparable to previous reported measurements. For both absorbing and non-absorbing spheres, a statistical framework is developed for including the contributions to random error due to CPC measurement uncertainty, RL, statistical fluctuations in particle counts, fluctuations in the blank, and mass flow controller flow error. Copyright 2014 American Association for Aerosol Research
¿Qué fue de la unión bancaria europea?

El impulso para la creación de la unión bancaria constituyó una respuesta política de gran calado y una solución técnica e institucional a la crisis financiera de 2008 sin precedentes en este ámbito. Ocho años después del acuerdo político que impulsó el proyecto, la unión bancaria es una realidad en lo que a su pilar de supervisión y resolución se refiere, a pesar de los importantes retos que ambos marcos enfrentan a futuro. La ausencia de avances, sin embargo, en el pilar correspondiente a la cobertura de depósitos y las otras piezas hoy identificadas como relevantes obliga a hablar de una unión bancaria incompleta.
Smart E-Textile Materials

Smart textiles are one of the areas that provides added value to textile materials. It is a sector that has been developed with new technologies, new fibers, and textile materials. The production of smart or intelligent textiles cooperate with other branches of science like nanotechnology, materials science, design, electronics, and computer engineering, etc. Smart textiles are classified into three groups as passive smart textiles, active smart textiles and ultra smart textiles according to their performance characteristics. Passive smart textiles are the first generation of smart textiles and sense the external conditions; for instance, UV protecting clothing, conductive fibers, etc. As active smart textiles respond to external conditions, ultra smart textiles sense, react, and adopt themselves to conditions. Shape memory materials, chromic materials, heat storage, and thermo-regulated fabrics are the typical applications of active smart textiles.
Individual differences in negotiation: A relational process model

Intuition suggests that individual differences should play an important role in negotiation performance, and yet empirical results have been relatively weak. Because negotiations are inherently dyadic, the dyad needs to feature prominently in theorizing. In expanding the traditional treatment of individual differences to two systematically interconnected parties, a relational process model (RPM) emerges. The RPM illustrates how the individual differences of both negotiators spark complex behavioral dynamics through five distinct theoretical mechanisms. Individuals (a) select each other, (b) set expectancies for each other, (c) serve as behavioral triggers and affordances for each other, (d) reciprocate and complement each other’s behaviors, and (e) vary in their responses to identical behaviors. It also directs attention to new classes and dimensions of individual difference factors. The RPM helps explain why past research has been highly conservative. A more complete picture needs to incorporate the complex interplay starting with parties’ individual differences.
Enrichment of Organic Manure with Plant Growth Promoting Rhizobacteria Improved the Root and Shoot Growth of Okra (Abelmoschus esculentus L. Moench.)

A well-structured root system is essential to ensure optimal plant growth and yield. Two experiments were conducted to determine the effects of plant growth promoting rhizobacteria (PGPR) on the root system of okra plant. These experiments were arranged with a completely randomized design. The first experiment was conducted in the growth chamber with 8 different bacterial isolates consisting of Methylobacterium sp. , Bacillus sp. , Bacillus methylotrophicus, Flavobacterium tirrenicum, Providencia stuartii, Azotobacter vinelandii, Methylocystis parvus and PGPR consortium. The second experiment was conducted in the greenhouse and examined the effects of four poultry manure rates, i.e. 0, 6, 12 and 18 ton.ha-1, or equivalent to 0, 75, 150 and 225% of recommended rates and how these are altered with the presence or absence of PGPR. The results of the experiments showed that, PGPR significantly improved root architecture; the number and length of lateral roots was increased by 242.86% and 777.79% respectively, as well as the dry weight of the roots and shoots of okra plant by 236.36% and 333.33%, respectively. Moreover applying 150% (12 t.ha-1) of the recommended rate of poultry manure enriched with PGPR was found to be most effective in terms of improving the growth and root attributes of okra plants.
Blockchain Technology in the Food Industry: A Review of Potentials, Challenges and Future Research Directions

Blockchain technology has emerged as a promising technology with far-reaching implications for the food industry. The combination of immutability, enhanced visibility, transparency and data integrity provides numerous benefits that improve trust in extended food supply chains (FSCs). Blockchain can enhance traceability, enable more efficient recall and aids in risk reduction of counterfeits and other forms of illicit trade. Moreover, blockchain can enhance the integrity of credence claims such as sustainably sourced, organic or faith-based claims such as kosher or halal by integrating the authoritative source of the claim (e.g., the certification body or certification owner) into the blockchain to verify the claim integrity and reassure business customers and end consumers. Despite the promises and market hype, a comprehensive overview of the potential benefits and challenges of blockchain in FSCs is still missing. To bridge this knowledge gap, we present the findings from a systematic review and bibliometric analysis of sixty-one (61) journal articles and synthesize existing research. The main benefits of blockchain technology in FCSs are improved food traceability, enhanced collaboration, operational efficiencies and streamlined food trading processes. Potential challenges include technical, organizational and regulatory issues. We discuss the theoretical and practical implications of our research and present several ideas for future research.
Improved Oscillation Results for Functional Nonlinear Dynamic Equations of Second Order

In this paper, the functional dynamic equation of second order is studied on an arbitrary time scale under milder restrictions without the assumed conditions in the recent literature. The Nehari, Hille, and Ohriska type oscillation criteria of the equation are investigated. The presented results confirm that the study of the equation in this formula is superior to other previous studies. Some examples are addressed to demonstrate the finding.
Beliren Yetişkinlerde Yalnızlık ile Yaşam Yönelimi Arasındaki Doğrudan ve Dolaylı İlişkiler: Sürekli Kaygının Aracılık Rolü

Bu araştırmanın amacı, beliren yetişkinlerde sürekli kaygının yaşam yönelimi ile yalnızlık arasındaki ilişkide aracılık rolü üstlenip üstlenmediğini ortaya koymaktır. Bu amaçla 385 üniversite öğrencisinden (133 erkek ve 252 kadın, yaş ort: 20.56, ss. 2.11) veri toplanmıştır. Veri toplama araçları olarak Yaşam Yönelimi Ölçeği, UCLA Yalnızlık Ölçeği ve Sürekli Kaygı Ölçeği kullanılmıştır. Araştırmadan elde edilen bulgulara göre, beliren yetişkinlerde yalnızlık ile yaşam yönelimi arasında negatif yönde anlamlı ilişki bulunmaktadır. Benzer bir biçimde, yaşam yönelimi ile sürekli kaygı arasında negatif yönde anlamlı bir ilişki vardır. Buna karşın, yalnızlık ile sürekli kaygı arasında pozitif yönde anlamlı ilişki elde edilmiştir. Beliren yetişkinlerde sürekli kaygı puanlarının, yalnızlık ile yaşam yönelimi arasındaki ilişkide aracılık rolü üstlenip üstlenmediğine ilişkin bulgulara göre, yalnızlığın yaşam yönelimi üzerindeki doğrudan etkisinin anlamsız olduğu görülmektedir. Diğer taraftan, yalnızlığın yaşam yönelimi üzerindeki dolaylı etkisinin anlamlı olduğu görülmüştür. Bu bulguya dayanarak, sürekli kaygının yalnızlık ile yaşam yönelimi arasındaki ilişkide tam aracılık rolü üstlendiği söylenebilir. Elde edilen bulgular alanyazını ışığında tartışılmış ve yorumlanmıştır.
Sensory evaluation and acceptance of food made of edible insects

This paper discusses the sensory analysis of food enriched with selected edible insect species which are labelled as a novel food – house cricket (Acheta domesticus) and mealworm (Tenebrio molitor). Energy bars of two different compositions with the addition of cricket flour and puff pastry bars sprinkled with the whole roasted mealworm larvae were evaluated by consumer tests performed via a questionnaire survey. Respondents represented both men and women in equal numbers and included consumers with the experience of the sensory analysis and edible insects to ensure accurate results. Sensory analyses revealed that respondents associated their tastes with already known flavors (salty, sweet, bitter, fish, French fries, chicken, and mushrooms). The most common answer from respondents was a salty taste, followed by a sweet taste. There were also unusual comparisons such as pine seeds. Consumers’ positive attitude to these energy bars has been registered which shows that the Czech consumer accepts edible insects in a suitable form as a novel food and possible part of the food basket.
Internet-scale Insecurity of Consumer Internet of Things

The number of Internet-of-Things (IoT) devices actively communicating across the Internet is continually increasing, as these devices are deployed across a variety of sectors, constantly transferring private data across the Internet. Due to the extensive deployment of such devices, the continuous discovery and persistence of IoT-centric vulnerabilities in protocols, applications, hardware, and the improper management of such IoT devices has resulted in the rampant, uncontrolled spread of malware threatening consumer IoT devices. To this end, this work adopts a novel, macroscopic methodology for fingerprinting Internet-scale compromised IoT devices, revealing crucial cyber threat intelligence on the insecurity of consumer IoT devices. By developing data-driven techniques rooted in machine learning methods and analyzing 3.6 TB of network traffic data, we discover 855,916 compromised IP addresses, with 310,164 fingerprinted as IoT. Further analysis reveals China and Brazil to be hosting the most significant population of compromised IoT devices (100,000 and 55,000, respectively). Additionally, we provide a longitudinal analysis on data from one year ago against this work, revealing the evolving trends of IoT exploitation, such as the increased number of vendors targeted by malware, rising from 50 to 131. Moreover, countries such as China (420% increased infected IoT count) and Indonesia (177% increased infected IoT count) have seen notably high increases in infection rates. Last, we compare our geographic results against Global Cybersecurity Index (GCI) ratings, verifying that countries with high GCI ratings, such as the Netherlands and Germany, had relatively low infection rates. However, upon further inspection, we find that the GCI rate does not accurately represent the consumer IoT market, with countries such as China and Russia being rated with “high” CGI scores, yet hosting a large population of infected consumer IoT devices.