Applied Science Private University

An updated comprehensive review to help researchers understand nanozymes better and in turn to advance the field.

This paper presents a technique for motion detection that incorporates several innovative mechanisms. For example, our proposed technique stores, for each pixel, a set of values taken in the past at the same location or in the neighborhood. It then compares this set to the current pixel value in order to determine whether that pixel belongs to the background, and adapts the model by choosing randomly which values to substitute from the background model. This approach differs from those based upon the classical belief that the oldest values should be replaced first. Finally, when the pixel is found to be part of the background, its value is propagated into the background model of a neighboring pixel. We describe our method in full details (including pseudo-code and the parameter values used) and compare it to other background subtraction techniques. Efficiency figures show that our method outperforms recent and proven state-of-the-art methods in terms of both computation speed and detection rate. We also analyze the performance of a downscaled version of our algorithm to the absolute minimum of one comparison and one byte of memory per pixel. It appears that even such a simplified version of our algorithm performs better than mainstream techniques.

Cancer immune evasion is a major stumbling block in designing effective anticancer therapeutic strategies. Although considerable progress has been made in understanding how cancers evade destructive immunity, measures to counteract tumor escape have not kept pace. There are a number of factors that contribute to tumor persistence despite having a normal host immune system. Immune editing is one of the key aspects why tumors evade surveillance causing the tumors to lie dormant in patients for years through "equilibrium" and "senescence" before re-emerging. In addition, tumors exploit several immunological processes such as targeting the regulatory T cell function or their secretions, antigen presentation, modifying the production of immune suppressive mediators, tolerance and immune deviation. Besides these, tumor heterogeneity and metastasis also play a critical role in tumor growth. A number of potential targets like promoting Th1, NK cell, γδ T cell responses, inhibiting Treg functionality, induction of IL-12, use of drugs including phytochemicals have been designed to counter tumor progression with much success. Some natural agents and phytochemicals merit further study. For example, use of certain key polysaccharide components from mushrooms and plants have shown to possess therapeutic impact on tumor-imposed genetic instability, anti-growth signaling, replicative immortality, dysregulated metabolism etc. In this review, we will discuss the advances made toward understanding the basis of cancer immune evasion and summarize the efficacy of various therapeutic measures and targets that have been developed or are being investigated to enhance tumor rejection.

Liposomes are now considered the most commonly used nanocarriers for various potentially active hydrophobic and hydrophilic molecules due to their high biocompatibility, biodegradability, and low immunogenicity. Liposomes also proved to enhance drug solubility and controlled distribution, as well as their capacity for surface modifications for targeted, prolonged, and sustained release. Based on the composition, liposomes can be considered to have evolved from conventional, long-circulating, targeted, and immune-liposomes to stimuli-responsive and actively targeted liposomes. Many liposomal-based drug delivery systems are currently clinically approved to treat several diseases, such as cancer, fungal and viral infections; more liposomes have reached advanced phases in clinical trials. This review describes liposomes structure, composition, preparation methods, and clinical applications.

Over the past decades, a tremendous amount of research has been done on the use of machine learning for speech processing applications, especially speech recognition. However, in the past few years, research has focused on utilizing deep learning for speech-related applications. This new area of machine learning has yielded far better results when compared to others in a variety of applications including speech, and thus became a very attractive area of research. This paper provides a thorough examination of the different studies that have been conducted since 2006, when deep learning first arose as a new area of machine learning, for speech applications. A thorough statistical analysis is provided in this review which was conducted by extracting specific information from 174 papers published between the years 2006 and 2018. The results provided in this paper shed light on the trends of research in this area as well as bring focus to new research topics.

Due to the advent of computer technology image-processing techniques have become increasingly important in a wide variety of applications. Image segmentation is a classic subject in the field of image processing and also is a hotspot and focus of image processing techniques. Several general-purpose algorithms and techniques have been developed for image segmentation. Since there is no general solution to the image segmentation problem, these techniques often have to be combined with domain knowledge in order to effectively solve an image segmentation problem for a problem domain. This paper presents a comparative study of the basic Block-Based image segmentation techniques.

COVID-19 pandemic has disrupted teaching in a vriety of institutions. It has tested the readiness of academic institutions to deal with such abrupt crisis. Online learning has become the main method of instruction during the pandemic in Jordan. After 4 months of online education, two online surveys were distributed to investigate faculty’s and Students’ perception of the learning process that took place over that period of time with no face to face education. In this regard, the study aimed to identify both faculty’s and students’ perceptions of online learning, utilizing two surveys one distributed to 50 faculty members and another 280 students were selected randomly to explore the effectiveness, challenges, and advantages of online education in Jordan. The analysis showed that the common online platforms in Jordan were Zoom, Microsoft Teams offering online interactive classes, and WhatsApp in communication with students outside the class. The study found that both faculty and students agreed that online education is useful during the current pandemic. At the same time, its efficacy is less effective than face-to-face learning and teaching. Faculty and students indicated that online learning challenges lie in adapting to online education, especially for deaf and hard of hearing students, lack of interaction and motivation, technical and Internet issues, data privacy, and security. They also agreed on the advantages of online learning. The benefits were mainly self-learning, low costs, convenience, and flexibility. Even though online learning works as a temporary alternative due to COVID-19, it could not substitute face-to-face learning. The study recommends that blended learning would help in providing a rigorous learning environment.

Abstract The two‐dimensional scattering and diffraction of plane SH waves by a semi‐cylindrical canyon is analysed for a general angle of wave incidence. The closed‐form solution of the problem shows that the surface topography can have prominent effects on incident waves only when the wavelengths of incident motion are short compared to the radius of a canyon. The surface amplification of displacement amplitudes around and in the canyon changes rapidly from one point to another, but the amplification is always less than 2. The over‐all trends of amplification pattern are determined by two principal parameters: (1) γ, the angle of incidence of plane SH waves, and (2) η, the ratio of radius of the canyon to one‐half wave length of incident waves. The higher η leads to greater complexity of the pattern of surface displacement amplitudes characterized by more abrupt changes of amplification from one point to another, while γ mainly determines the over‐all trends of displacement amplitudes. For grazing and nearly grazing incidences, for example, a strong shadow zone is developed behind the canyon. The qualitative analysis of the topographic effects on the Pacoima Dam accelerogram, 1 based on the semi‐cylindrical canyon, suggests that this strong‐motion record was not seriously affected by surface topography of the recording site.

Paramagnetic ultrasmall gadolinium oxide (Gd(2)O(3)) nanoparticles with particle diameters (d) of approximately 1 nm were synthesized by using three kinds of Gd(III) ion precursors and by refluxing each of them in tripropylene glycol under an O(2) flow. A large longitudinal relaxivity (r(1)) of water proton of 9.9 s(-1) mM(-1) was estimated. As a result, high contrast in vivo T(1) MR images of the brain tumor of a rat were observed. This large r(1) is discussed in terms of the huge surface to volume ratio (S/V) of the ultrasmall gadolinium oxide nanoparticles coupled with the cooperative induction of surface Gd(III) ions for the longitudinal relaxation of a water proton. It is found from the d dependence of r(1) that the optimal range of d for the maximal r(1), which may be used as an advanced T(1) MRI contrast agent, is 1-2.5 nm.

Complex three-dimensional biophotonic nanostructures produce the vivid structural colors of many butterfly wing scales, but their exact nanoscale organization is uncertain. We used small angle X-ray scattering (SAXS) on single scales to characterize the 3D photonic nanostructures of five butterfly species from two families (Papilionidae, Lycaenidae). We identify these chitin and air nanostructures as single network gyroid (I4(1)32) photonic crystals. We describe their optical function from SAXS data and photonic band-gap modeling. Butterflies apparently grow these gyroid nanostructures by exploiting the self-organizing physical dynamics of biological lipid-bilayer membranes. These butterfly photonic nanostructures initially develop within scale cells as a core-shell double gyroid (Ia3d), as seen in block-copolymer systems, with a pentacontinuous volume comprised of extracellular space, cell plasma membrane, cellular cytoplasm, smooth endoplasmic reticulum (SER) membrane, and intra-SER lumen. This double gyroid nanostructure is subsequently transformed into a single gyroid network through the deposition of chitin in the extracellular space and the degeneration of the rest of the cell. The butterflies develop the thermodynamically favored double gyroid precursors as a route to the optically more efficient single gyroid nanostructures. Current approaches to photonic crystal engineering also aim to produce single gyroid motifs. The biologically derived photonic nanostructures characterized here may offer a convenient template for producing optical devices based on biomimicry or direct dielectric infiltration.

Abstract The Sabatier principle is widely explored in heterogeneous catalysis, graphically depicted in volcano plots. The most desirable activity is located at the peak of the volcano, and further advances in activity past this optimum are possible by designing a catalyst that circumvents the limitation entailed by the Sabatier principle. Herein, by density functional theory calculations, we discovered an unusual Sabatier principle on high entropy alloy (HEA) surface, distinguishing the “just right” (Δ G H* = 0 eV) in the Sabatier principle of hydrogen evolution reaction (HER). A new descriptor was proposed to design HEA catalysts for HER. As a proof-of-concept, the synthesized PtFeCoNiCu HEA catalyst endows a high catalytic performance for HER with an overpotential of 10.8 mV at −10 mA cm −2 and 4.6 times higher intrinsic activity over the state-of-the-art Pt/C. Moreover, the unusual Sabatier principle on HEA catalysts can be extended to other catalytic reactions.

Cancer arises in the context of an in vivo tumor microenvironment. This microenvironment is both a cause and consequence of tumorigenesis. Tumor and host cells co-evolve dynamically through indirect and direct cellular interactions, eliciting multiscale effects on many biological programs, including cellular proliferation, growth, and metabolism, as well as angiogenesis and hypoxia and innate and adaptive immunity. Here we highlight specific biological processes that could be exploited as targets for the prevention and therapy of cancer. Specifically, we describe how inhibition of targets such as cholesterol synthesis and metabolites, reactive oxygen species and hypoxia, macrophage activation and conversion, indoleamine 2,3-dioxygenase regulation of dendritic cells, vascular endothelial growth factor regulation of angiogenesis, fibrosis inhibition, endoglin, and Janus kinase signaling emerge as examples of important potential nexuses in the regulation of tumorigenesis and the tumor microenvironment that can be targeted. We have also identified therapeutic agents as approaches, in particular natural products such as berberine, resveratrol, onionin A, epigallocatechin gallate, genistein, curcumin, naringenin, desoxyrhapontigenin, piperine, and zerumbone, that may warrant further investigation to target the tumor microenvironment for the treatment and/or prevention of cancer.

BACKGROUND: For more than three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has provided a framework to quantify health loss due to diseases, injuries, and associated risk factors. This paper presents GBD 2023 findings on disease and injury burden and risk-attributable health loss, offering a global audit of the state of world health to inform public health priorities. This work captures the evolving landscape of health metrics across age groups, sexes, and locations, while reflecting on the remaining post-COVID-19 challenges to achieving our collective global health ambitions. METHODS: The GBD 2023 combined analysis estimated years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) for 375 diseases and injuries, and risk-attributable burden associated with 88 modifiable risk factors. Of the more than 310 000 total data sources used for all GBD 2023 (about 30% of which were new to this estimation round), more than 120 000 sources were used for estimation of disease and injury burden and 59 000 for risk factor estimation, and included vital registration systems, surveys, disease registries, and published scientific literature. Data were analysed using previously established modelling approaches, such as disease modelling meta-regression version 2.1 (DisMod-MR 2.1) and comparative risk assessment methods. Diseases and injuries were categorised into four levels on the basis of the established GBD cause hierarchy, as were risk factors using the GBD risk hierarchy. Estimates stratified by age, sex, location, and year from 1990 to 2023 were focused on disease-specific time trends over the 2010-23 period and presented as counts (to three significant figures) and age-standardised rates per 100 000 person-years (to one decimal place). For each measure, 95% uncertainty intervals [UIs] were calculated with the 2·5th and 97·5th percentile ordered values from a 250-draw distribution. FINDINGS: Total numbers of global DALYs grew 6·1% (95% UI 4·0-8·1), from 2·64 billion (2·46-2·86) in 2010 to 2·80 billion (2·57-3·08) in 2023, but age-standardised DALY rates, which account for population growth and ageing, decreased by 12·6% (11·0-14·1), revealing large long-term health improvements. Non-communicable diseases (NCDs) contributed 1·45 billion (1·31-1·61) global DALYs in 2010, increasing to 1·80 billion (1·63-2·03) in 2023, alongside a concurrent 4·1% (1·9-6·3) reduction in age-standardised rates. Based on DALY counts, the leading level 3 NCDs in 2023 were ischaemic heart disease (193 million [176-209] DALYs), stroke (157 million [141-172]), and diabetes (90·2 million [75·2-107]), with the largest increases in age-standardised rates since 2010 occurring for anxiety disorders (62·8% [34·0-107·5]), depressive disorders (26·3% [11·6-42·9]), and diabetes (14·9% [7·5-25·6]). Remarkable health gains were made for communicable, maternal, neonatal, and nutritional (CMNN) diseases, with DALYs falling from 874 million (837-917) in 2010 to 681 million (642-736) in 2023, and a 25·8% (22·6-28·7) reduction in age-standardised DALY rates. During the COVID-19 pandemic, DALYs due to CMNN diseases rose but returned to pre-pandemic levels by 2023. From 2010 to 2023, decreases in age-standardised rates for CMNN diseases were led by rate decreases of 49·1% (32·7-61·0) for diarrhoeal diseases, 42·9% (38·0-48·0) for HIV/AIDS, and 42·2% (23·6-56·6) for tuberculosis. Neonatal disorders and lower respiratory infections remained the leading level 3 CMNN causes globally in 2023, although both showed notable rate decreases from 2010, declining by 16·5% (10·6-22·0) and 24·8% (7·4-36·7), respectively. Injury-related age-standardised DALY rates decreased by 15·6% (10·7-19·8) over the same period. Differences in burden due to NCDs, CMNN diseases, and injuries persisted across age, sex, time, and location. Based on our risk analysis, nearly 50% (1·27 billion [1·18-1·38]) of the roughly 2·80 billion total global DALYs in 2023 were attributable to the 88 risk factors analysed in GBD. Globally, the five level 3 risk factors contributing the highest proportion of risk-attributable DALYs were high systolic blood pressure (SBP), particulate matter pollution, high fasting plasma glucose (FPG), smoking, and low birthweight and short gestation-with high SBP accounting for 8·4% (6·9-10·0) of total DALYs. Of the three overarching level 1 GBD risk factor categories-behavioural, metabolic, and environmental and occupational-risk-attributable DALYs rose between 2010 and 2023 only for metabolic risks, increasing by 30·7% (24·8-37·3); however, age-standardised DALY rates attributable to metabolic risks decreased by 6·7% (2·0-11·0) over the same period. For all but three of the 25 leading level 3 risk factors, age-standardised rates dropped between 2010 and 2023-eg, declining by 54·4% (38·7-65·3) for unsafe sanitation, 50·5% (33·3-63·1) for unsafe water source, and 45·2% (25·6-72·0) for no access to handwashing facility, and by 44·9% (37·3-53·5) for child growth failure. The three leading level 3 risk factors for which age-standardised attributable DALY rates rose were high BMI (10·5% [0·1 to 20·9]), drug use (8·4% [2·6 to 15·3]), and high FPG (6·2% [-2·7 to 15·6]; non-significant). INTERPRETATION: Our findings underscore the complex and dynamic nature of global health challenges. Since 2010, there have been large decreases in burden due to CMNN diseases and many environmental and behavioural risk factors, juxtaposed with sizeable increases in DALYs attributable to metabolic risk factors and NCDs in growing and ageing populations. This long-observed consequence of the global epidemiological transition was only temporarily interrupted by the COVID-19 pandemic. The substantially decreasing CMNN disease burden, despite the 2008 global financial crisis and pandemic-related disruptions, is one of the greatest collective public health successes known. However, these achievements are at risk of being reversed due to major cuts to development assistance for health globally, the effects of which will hit low-income countries with high burden the hardest. Without sustained investment in evidence-based interventions and policies, progress could stall or reverse, leading to widespread human costs and geopolitical instability. Moreover, the rising NCD burden necessitates intensified efforts to mitigate exposure to leading risk factors-eg, air pollution, smoking, and metabolic risks, such as high SBP, BMI, and FPG-including policies that promote food security, healthier diets, physical activity, and equitable and expanded access to potential treatments, such as GLP-1 receptor agonists. Decisive, coordinated action is needed to address long-standing yet growing health challenges, including depressive and anxiety disorders. Yet this can be only part of the solution. Our response to the NCD syndemic-the complex interaction of multiple health risks, social determinants, and systemic challenges-will define the future landscape of global health. To ensure human wellbeing, economic stability, and social equity, global action to sustain and advance health gains must prioritise reducing disparities by addressing socioeconomic and demographic determinants, ensuring equitable health-care access, tackling malnutrition, strengthening health systems, and improving vaccination coverage. We live in times of great opportunity. FUNDING: Gates Foundation and Bloomberg Philanthropies.

John Giorgi, Osvald Nitski, Bo Wang, Gary Bader. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). 2021.

Intelligent Transportation Systems are rapidly expanding to meet the growing demand for safer, more efficient, and sustainable transportation solutions. These systems encompass various applications, from traffic management and control to autonomous vehicles, aiming to enhance mobility experiences while addressing urbanization challenges. This paper examines key components of Intelligent Transportation Systems, including Vehicular Ad-hoc Networks, Intelligent Traffic Lights, Virtual Traffic Lights, and Mobility Prediction, emphasizing their role in improving transportation efficiency, safety, and sustainability. It explores recent advancements in communication systems that enable real-time Intelligent Transportation Systems operations, contributing to the realization of environmentally friendly smart cities.Moreover, the paper addresses security challenges associated with Intelligent Transportation Systems deployment, particularly concerning public transit privacy, and presents case studies illustrating the benefits of Intelligent Transportation Systems integration in specific urban areas, emphasizing its role in fostering Sustainable Smart Cities. Additionally, it examines proactive initiatives by automotive manufacturers in adhering to Intelligent Transportation Systems standards, ensuring mutual benefits for drivers and urban centers.

Preface 1. Cellular disorder 2. Topographical disorder 3. Continuum disorder 4. The observation of disorder 5. Statistical mechanics of substitutional disorder 6. Thermodynamics of topological disorder 7. Macromolecular disorder 8. Excitations on a disordered linear chain 9. Excitations on a disordered lattice 10. Electrons in disordered metals 11. Excitations of a toplogically disordered network 12. Dilute and amorphous magnets 13. Electrons in 'gases' References Index.

Companies seek to adopt competitive strategies that achieve sustainability standards, not only in achieving economic success but also in serving society and preserving the environment at the same time. Pharmaceutical companies and their supply chains are facing increasing pressure to preserve the environment because of the problems caused by medical waste, and it is necessary to show their role through their strategies in preserving the environment and serving society as well. This study aims to investigate the relationship between sustainable supply chain strategies and supply chain collaboration and its effect on competitive priorities. The study investigates whether Jordanian Pharmaceutical companies incorporate the sustainability strategy into supply chain strategy, and whether that may impact its competitive priorities. The study population consists of (23) Jordanian Pharmaceutical companies. A structured questionnaire is designed and distributed among top managers in the surveyed companies. A Structural Equation Modeling technique is used to analysis the data and provide the results. Analysis proves the relationship between sustainable supply chain strategies and supply chain collaboration, where companies are interested in attaining some achievements in the area of social and environmental to gain some collaborative strategies with their partners in the supply chain. The study suggests that organizations may adopt the Triple Bottom Line (TBL) framework to evaluate their performance in a broader perspective and extend the collaboration with suppliers and customers through information sharing along the supply chain partners.

Abstract A criterion for the transition in fracture mode from ductile to cleavage is calculated for fracture at a notch. It is concluded that the temperature-dependence of this transition probably arises more from that of the Peierls-Nabarro stress required to move a free dislocation in α-iron than from the temperature-dependence of the locking of e dislocation source. The transition temperature is found to be a function of grain size, the friction on a free dislocation, the strength of the dislocation locking, the degree of triaxiality of the applied stress and the elastic constants.

Since its public release in November 2022, ChatGPT has gained a widespread attention and received mixed responses in the academia. Promising applications of ChatGPT in university education has been suggested; however, several concerns were raised. The aim of this descriptive study was to investigate the pros and cons of ChatGPT use in medical, dental, pharmacy, and public health education. Based on expert panel discussion and review of the existing literature, specific and concise ChatGPT prompts were constructed and the responses were generated on 25 February 2023. Out data suggested that in medical education, ChatGPT benefits included the possibility of improving personalized learning, clinical reasoning and understanding of complex medical concepts. The benefits listed in the context of dental education included improved skills through step- by-step instructions and interactive content, with instant feedback on student techniques. In pharmacy education, the advantages included possible explanations of complex subjects and the deployment of interactive tools aiding to develop skills for patient counselling. In public health education, the listed benefits included providing explanations and case scenarios, besides improved skills in data analysis and literature review. The limitations listed based on ChatGPT-generated content were common across all of the investigated healthcare disciplines and included data privacy issues, risk of generating biased and inaccurate content, and the risk of deterioration of critical thinking and communication skills among healthcare students. The ChatGPT-generated content in the context of healthcare education was deemed partially helpful by the expert panel. However, several important points regarding the pros and cons of ChatGPT use in medical, dental, pharmacy and public health education were missed by ChatGPT- generated content including: the risk of plagiarism, copyright issues, the risk of academic dishonesty, and the lack of personal and emotional interactions necessary for developing proper communication skills in healthcare education. In conclusion, despite the promising prospects of ChatGPT in healthcare education, several drawbacks should be addressed with implementation of guidelines for proper use to ensure exploiting the benefits of this innovative technology.

Targeted therapies and the consequent adoption of "personalized" oncology have achieved notable successes in some cancers; however, significant problems remain with this approach. Many targeted therapies are highly toxic, costs are extremely high, and most patients experience relapse after a few disease-free months. Relapses arise from genetic heterogeneity in tumors, which harbor therapy-resistant immortalized cells that have adopted alternate and compensatory pathways (i.e., pathways that are not reliant upon the same mechanisms as those which have been targeted). To address these limitations, an international task force of 180 scientists was assembled to explore the concept of a low-toxicity "broad-spectrum" therapeutic approach that could simultaneously target many key pathways and mechanisms. Using cancer hallmark phenotypes and the tumor microenvironment to account for the various aspects of relevant cancer biology, interdisciplinary teams reviewed each hallmark area and nominated a wide range of high-priority targets (74 in total) that could be modified to improve patient outcomes. For these targets, corresponding low-toxicity therapeutic approaches were then suggested, many of which were phytochemicals. Proposed actions on each target and all of the approaches were further reviewed for known effects on other hallmark areas and the tumor microenvironment. Potential contrary or procarcinogenic effects were found for 3.9% of the relationships between targets and hallmarks, and mixed evidence of complementary and contrary relationships was found for 7.1%. Approximately 67% of the relationships revealed potentially complementary effects, and the remainder had no known relationship. Among the approaches, 1.1% had contrary, 2.8% had mixed and 62.1% had complementary relationships. These results suggest that a broad-spectrum approach should be feasible from a safety standpoint. This novel approach has potential to be relatively inexpensive, it should help us address stages and types of cancer that lack conventional treatment, and it may reduce relapse risks. A proposed agenda for future research is offered.