Miracle-dz/UniFAR-FTUs huggingface dataset:
Endorsement of TNBC Biomarkers in Precision Therapy by Nanotechnology

Simple Summary Triple-negative breast cancer (TNBC), the most aggressive and heterogenous type of cancer, lacks the expression of hormones like estrogen, progesterone, and human epidermal growth receptor-2, making chemotherapy the only treatment regimen against TNBC. It was further observed that chemotherapy leads to off-site toxicity and chemoresistance, decreasing anticancer activity. Therefore, to overcome the problem faced during chemotherapy, and to address the heterogeneity of TNBC, targeted therapy emerged based on the molecular profiling of TNBC. Such a scenario further encouraged the acceptance of biomarkers as some of the targeting moieties for effective and precise TNBC therapy. Several biomarkers are used as targets for the precision therapy in TNBC, including EGFR, VGFR, TP53, interleukins, insulin-like growth factor binding proteins, c-MET, androgen receptor, BRCA1, glucocorticoid, PTEN, ALDH1, etc. Additionally, nanoparticles were employed as parts of a multifunctional platform to deliver the therapeutics to the target site with increased precision. Abstract Breast cancer is a heterogeneous disease which accounts globally for approximately 1 million new cases annually, wherein more than 200,000 of these cases turn out to be cases of triple-negative breast cancer (TNBC). TNBC is an aggressive and rare breast cancer subtype that accounts for 10–15% of all breast cancer cases. Chemotherapy remains the only therapy regimen against TNBC. However, the emergence of innate or acquired chemoresistance has hindered the chemotherapy used to treat TNBC. The data obtained from molecular technologies have recognized TNBC with various gene profiling and mutation settings that have helped establish and develop targeted therapies. New therapeutic strategies based on the targeted delivery of therapeutics have relied on the application of biomarkers derived from the molecular profiling of TNBC patients. Several biomarkers have been found that are targets for the precision therapy in TNBC, such as EGFR, VGFR, TP53, interleukins, insulin-like growth factor binding proteins, c-MET, androgen receptor, BRCA1, glucocorticoid, PTEN, ALDH1, etc. This review discusses the various candidate biomarkers identified in the treatment of TNBC along with the evidence supporting their use. It was established that nanoparticles had been considered a multifunctional system for delivering therapeutics to target sites with increased precision. Here, we also discuss the role of biomarkers in nanotechnology translation in TNBC therapy and management.
Obesity, Preserved Ejection Fraction Heart Failure, and Left Ventricular Remodeling

Owing to the overwhelming obesity epidemic, preserved ejection fraction heart failure commonly ensues in patients with severe obesity and the obese phenotype of preserved ejection fraction heart failure is now commonplace in clinical practice. Severe obesity and preserved ejection fraction heart failure share congruent cardiovascular, immune, and renal derangements that make it difficult to ascertain whether the obese phenotype of preserved ejection fraction heart failure is the convergence of two highly prevalent conditions or severe obesity enables the development and progression of the syndrome of preserved ejection fraction heart failure. Nevertheless, the obese phenotype of preserved ejection fraction heart failure provides a unique opportunity to assess whether sustained and sizeable loss of excess body weight via metabolic bariatric surgery reverses the concentric left ventricular remodeling that patients with preserved ejection fraction heart failure commonly display.
Emerging and Recycling of Li-Ion Batteries to Aid in Energy Storage, A Review

The global population has increased over time, therefore the need for sufficient energy has risen. However, many countries depend on nonrenewable resources for daily usage. Nonrenewable resources take years to produce and sources are limited for generations to come. Apart from that, storing and energy distribution from nonrenewable energy production has caused environmental degradation over the years. Hence, many researchers have been actively participating in the development of energy storage devices for renewable resources using batteries. For this purpose, the lithium-ion battery is one of the best known storage devices due to its properties such as high power and high energy density in comparison with other conventional batteries. In addition, for the fabrication of Li-ion batteries, there are different types of cell designs including cylindrical, prismatic, and pouch cells. The development of Li-ion battery technology, the different widely used cathode and anode materials, and the benefits and drawbacks of each in relation to the most appropriate application were all thoroughly studied in this work. The electrochemical processes that underlie battery technologies were presented in detail and substantiated by current safety concerns regarding batteries. Furthermore, this review collected the most recent and current LIB recycling technologies and covered the three main LIB recycling technologies. The three recycling techniques—pyrometallurgical, hydrometallurgical, and direct recycling—have been the subject of intense research and development. The recovery of valuable metals is the primary goal of most recycling processes. The growth in the number of used LIBs creates a business opportunity to recover and recycle different battery parts as daily LIB consumption rises dramatically.
Windstorms along the Western Side of the Washington Cascade Mountains. Part I: A High-Resolution Observational and Modeling Study of the 12 February 1995 Event

Abstract This paper describes the leeside wind event of 12 February 1995 in which a swath of strong low-level easterly flow, with gusts to 35–40 m s−1, extended downwind of a major gap in the Cascade Mountains. Over the Puget Sound lowlands, low-level easterly flow approaching the Olympics was decelerated to less than 5 m s−1, resulting in enhanced (over 30 cm) snowfall along the windward side of the barrier. In addition to conventional synoptic observations, high-resolution data sources were utilized: profilers on both sides of the Cascades, a WSR-88D Doppler radar located in northern Puget Sound, and nonhydrostatic model simulations down to 1-km resolution. With the exception of underpredicting heavy snowfall to the east of the Olympics, many of the mesoscale features of this event were realistically simulated, including cold-air damming over eastern Washington, strong winds downwind of the gaps, a mountain wake downstream of Mount Rainier, and flow splitting around the Olympics. A major objective of th.
Formulations of Viscoelastic Constitutive Laws for Beams in Flexible Multibody Dynamics

It is often necessary to consider material dissipation effects in structural dynamics analysis. A novel three-dimensional viscoelastic beam formulation is proposed. A systematic procedure is proposed to incorporate existing viscoelastic material models into beam theories. The generalized Maxwell model is used to demonstrate the procedure. Starting from a three-dimensional beam theory, classical material viscoelastic constitutive laws are used to develop viscoelastic beam models for flexible multibody dynamics. In contrast with classical beam theories, the proposed beam formulation captures three-dimensional stress and strains distributions based on a novel dimensional reduction method, and models dissipative phenomena at the same time. All cross-sectional deformation modes are considered in the formulation. With the generalized Maxwell model, the formulation is valid for a broad range of frequencies. Because it is based on a three-dimensional formulation, the proposed approach uses a decomposition of the strain tensor into bulk and deviatoric components, thereby eliminating Poisson locking effects. This is particularly important because many highly dissipative materials are also nearly incompressible. Numerical examples are presented to illustrate these characteristics. Because the formulation developed is a beam model, it is computationally efficient and can be used for the simulation of flexible multibody dynamics systems.Copyright © 2015 by ASME
تاجتنملا تامييقت باسح يف يعانطصلاا ءاكذلا فيظوت ءلامعلل ةيصنلا تاعجارملا ىلع ًءانب AI Model to Calculate Products’ Rates Based on Customer's Reviews

Customer reviews and user-generated content about the products have become one of the most crucial factors in determining whether to make a new purchase or otherwise, as e-commerce has grown substantially over the past years and has become increasingly important in our daily life, especially recently under the influence of COVID-19 (Hasanat et al., 2020). A survey conducted by Zhong-Gang et al., (2015) revealed that nearly 60% of consumers browse online product reviews at least once a week, and 93% of them believe that these online reviews help them improve the accuracy of purchase decisions. Therefore, this paper seeks to develop an AI model that calculates the product rating based on the likelihood of negative feedback in the written review and apply this model to a dataset downloaded from the Kaggle website ( the dataset includes 23,486 records and 10 variables) , customer reviews of women's clothing products, to compare the results from the model with the actual costumers' rates in the dataset. The premise of this paper is that reviews are more accurate than rates because reviews give consumers a chance to elaborate on their feedback and specifically point out the positive and negative aspects of a product. On the other hand, rates may be emotionally influenced by customers' feedback, as they may be very irate, which could affect how accurately they specify a value through rates. Consumers often have complaints about a particular aspect of a product, such as the packaging, the delivery date, or other issues that may not be related to the product itself as a commodity, nonetheless, they still rate the product very low, which is unfair and does not reflect the real evaluation of the product. In order to assist new clients in making better decisions, the outcome model developed in the paper should assist in providing a more precise, equitable, and reliable evaluation.
Sur la diagonalisation conjointe approchée par un critère des moindres carrés

A new algorithm for approximate joint diagonalization of a set of matrices is presented. Using the mean square criterium, without the ortogonality constraint, it is compared with an analogous algorithm for sources separation. The criterium of our algorithm is on the separating matrix while the other is on the mixing matrix. This improves significantely the rate of convergence with better performances.
Artificial Intelligence-Aided Grade Crossing Safety Violation Detection Methodology and a Case Study in New Jersey

Fatalities at grade crossings accounted for an average of 33% of all railroad industry fatalities occurring in the past 10 years. As road traffic increases and high-speed rail deployments become more common in the United States, the number of fatalities is expected to remain a concern. Railroads have tackled this challenge through a combination of engineering, education, and enforcement campaigns. One of these efforts has been the increased deployment of security cameras throughout railroad networks. These video sources allow for the collection of big data to better understand grade crossing violation behaviors. However, monitoring these video feeds and extracting useful information requires prohibitive amounts of manual labor. This research utilizes state-of-the-art vision-based artificial intelligence (AI) techniques to record, recognize, and understand railroad video data in real time. This system’s understanding of active grade crossing violations helps to develop precise long-term grade crossing violation prevention strategies. This study explains how this AI-aided algorithm is used to monitor 1 year’s worth of violations at an active grade crossing in New Jersey and provides an overview of the observed trends. These data can be used to develop better engineering enforcement and education strategies for the mitigation of active grade crossing violations.
A Serosurvey of Japanese Encephalitis Virus in Monkeys and Humans Living in Proximity in Thailand

Japanese encephalitis virus (JEV) is a member of the Flaviviridae family and one of Asia’s most common causes of encephalitis. JEV is a zoonotic virus that is transmitted to humans through the bite of infected mosquitoes of the Culex species. While humans are dead-end hosts for the virus, domestic animals such as pigs and birds are amplification hosts. Although JEV naturally infected monkeys have been reported in Asia, the role of non-human primates (NHPs) in the JEV transmission cycle has not been intensively investigated. In this study, we demonstrated neutralizing antibodies against JEV in NHPs (Macaca fascicularis) and humans living in proximity in two provinces located in western and eastern Thailand by using Plaque Reduction Neutralization Test (PRNT). We found a 14.7% and 5.6% seropositive rate in monkeys and 43.7% and 45.2% seropositive rate in humans living in west and east Thailand, respectively. This study observed a higher seropositivity rate in the older age group in humans. The presence of JEV neutralizing antibodies in NHPs that live in proximity to humans shows the occurrence of natural JEV infection, suggesting the endemic transmission of this virus in NHPs. According to the One Health concept, regular serological studies should be conducted especially at the animal–human interface.
Risk Assessment of a Coastal Ecosystem from SW Spain Exposed to CO2 Enrichment Conditions

The Weight-of-Evidence (WOE) approach uses multiple lines of evidence to analyze the adverse effects associated with CO2 enrichment in two stations from the Gulf of Cádiz (Spain) with different contamination degrees. Sediment contamination and metal (loid) mobility, toxicity, ecological integrity, and bioaccumulation from the samples exposed to different acidification scenarios (pH gradient from 8.0 to 6.0) were used in the WOE. The experiments were conducted under laboratory conditions using a CO2-bubbling system. Different integration approaches such as multivariate analyses were used to evaluate the results. The results indicated that the adverse biological effects under pH 6.5 were related to the mobility of dissolved elements (As, Fe, Cu, Ni, and Zn). Furthermore, the pH reduction was correlated to the increase of bioaccumulation of As, Cr, Cu, Fe, and Ni in the tissues of mussels at pH 7.0. The noncontaminated sediment showed environmental degradation related to the acidification at pH values of 7.0; whereas the sediment moderately contaminated showed both environmental risks, caused by acidification and the presence and the increase of the bioavailability of contaminants. The WOE approach supposes an effective tool to identify and distinguish the causes of adverse effects related to the enrichment of CO2 in marine environments.
LIE SYMMETRIES OF NONLINEAR DIFFUSION EQUATIONS WITH CONVECTION TERM

In the present paper, we consider nonlinear diffusion equations with convection term of the form u t = (k(u)u x ) x + q(u), q(u) ≠ 0 (1) where u = u(x, t) is the unknown function and k(u), q(u) are arbitrary smooth functions. Equation (1) generalizes a great number of the well-known nonlinear second-order evolution equations, describing various processes in physics, chemistry, biology. Apart from their intrinsic theoretical interest, the equations of the type (1) are used to model a wide variety of phenomena in physics, engineering, chemistry, biology etc.
Commensuration Bias in Peer Review

To arrive at their final evaluation of a manuscript or grant proposal, reviewers must convert a submission’s strengths and weaknesses for heterogeneous peer review criteria into a single metric of quality or merit. I identify this process of commensuration as the locus for a new kind of peer review bias. Commensuration bias illuminates how the systematic prioritization of some peer review criteria over others permits and facilitates problematic patterns of publication and funding in science. Commensuration bias also foregrounds a range of structural strategies for realigning peer review practices and institutions with the aims of science.
A dynamic graph Hawkes process based on linear complexity self-attention for dynamic recommender systems

The dynamic recommender system realizes the real-time recommendation for users by learning the dynamic interest characteristics, which is especially suitable for the scenarios of rapid transfer of user interests, such as e-commerce and social media. The dynamic recommendation model mainly depends on the user-item history interaction sequence with timestamp, which contains historical records that reflect changes in the true interests of users and the popularity of items. Previous methods usually model interaction sequences to learn the dynamic embedding of users and items. However, these methods can not directly capture the excitation effects of different historical information on the evolution process of both sides of the interaction, i.e., the ability of events to influence the occurrence of another event. In this work, we propose a Dynamic Graph Hawkes Process based on Linear complexity Self-Attention (DGHP-LISA) for dynamic recommender systems, which is a new framework for modeling the dynamic relationship between users and items at the same time. Specifically, DGHP-LISA is built on dynamic graph and uses Hawkes process to capture the excitation effects between events. In addition, we propose a new self-attention with linear complexity to model the time correlation of different historical events and the dynamic correlation between different update mechanisms, which drives more accurate modeling of the evolution process of both sides of the interaction. Extensive experiments on three real-world datasets show that our model achieves consistent improvements over state-of-the-art baselines.
CONVERGENCE OF SOLUTIONS OF CERTAIN NON-HOMOGENEOUS THIRD ORDER ORDINARY DIFFERENTIAL EQUATIONS

This paper is concerned with differential equations of the form . x +aẍ+ g(ẋ) + h(x) = p(t, x, ẋ, ẍ) where a is a positive constant and g,h and p are continuous in their respective arguments, with functions g and h not necessarily differentiable. By introducing a complete Lyapunov function, as well as restricting the incrementary ratio η−1{h(ξ+ η)− h(ξ)}, (η 6= 0), of h to a closed sub-interval of the Routh-Hurwitz interval, we prove the convergence of solutions for this equation. This generalizes earlier results. Research supported by Universidad de Antioquia grant from SUI No. IN10095CE
Local structure analysis of magnetic transparent conducting films by x-ray spectroscopy

We prepared Mn-doped indium-tin oxide (ITO) films on glass substrates by radio-frequency magnetron sputtering and investigated local structures surrounding Mn ions in the films by x-ray absorption spectroscopy. The Fourier transform of the extended x-ray absorption fine structure (EXAFS) spectrum indicated that the Mn ions preferably substitute the In ions at the b sites of the In2O3 lattice. According to the threshold energy obtained from the inflection point of the edge in the x-ray absorption near edge structure (XANES) spectrum, the valence of the Mn ions was evaluated to range from +2 to +3. These x-ray absorption spectroscopic data are useful for revealing the origin of the magnetism of the Mn-doped ITO films.
A Case of Dulaglutide-Induced Vaginal Bleed

Type 2 diabetes mellitus (T2DM) is a growing challenge across the globe. The disease process is amendable to lifestyle modifications in the early stages. If those changes fail to correct endocrine dysfunction, medical therapy is initiated. Initially, therapy for type 2 diabetes consisted of biguanides and sulfonylureas. With modern medicine, we have developed dipeptidyl peptidase-4 inhibitors, sodium-glucose cotransporter-2 inhibitors, and glucagon-like peptide 1 (GLP-1) receptor agonists. Dulaglutide is a GLP-1 receptor agonist that is sold under the brand name Trulicity. The most common side effect associated with Dulaglutide is gastrointestinal discomfort. We present a case of severe vaginal bleeding due to a rare side effect of Dulaglutide. A 44-year-old perimenopausal female with a past medical history of type 2 diabetes mellitus presented to the clinic after experiencing significant vaginal bleeding. The patient was unable to tolerate Metformin and Semaglutide in the past. The abnormal vaginal hemorrhage started one week after receiving the second dose of Dulaglutide. Her hemoglobin concentration fell significantly. Dulaglutide was immediately discontinued, and her vaginal bleeding stopped. This case documents the necessity of post-market surveillance to oversee the safety of recently approved medications by the Food and Drug Administration (FDA). Rare side effects can emerge in the general population that were not seen during clinical trials. Physicians should consider the possibility of adverse medication reactions when determining whether to start a new medication or a conventional one.
Recognition Problems for Connectivity Functions

A connectivity function is a symmetric, submodular set function. Connectivity functions arise naturally from graphs, matroids and other structures. This thesis focuses mainly on recognition problems for connectivity functions, that is when a connectivity function comes from a particular type of structure. In particular we give a method for identifying when a connectivity function comes from a graph, which uses no more than a polynomial number of evaluations of the connectivity function. We also give a proof that no such method can exist for matroids.
Do TripAdvisor Valences are Trustworthy on South Asian Destinations?

Travellers prefer to rely on peers’ recommendations and review websites to look for reliable and unbiased information. Trustworthy communicators are more influential than the untrustworthy one. Trustworthy content is need of the hour in specific to post COVID19 travel. This research is analysing what propels a traveller towards destinations and empirically verify the valences of trustworthiness on TripAdvisor reviews. Content analysis of TripAdvisor reviews (153799 numbers) on South Asian destinations are captured, modelled, and analysed using Descriptive statistics, Regression Analysis and Structural Equation Modelling. Positive reviews are more trustworthy than the negative reviews and are helpful to potential tourist who seeks ‘real’ or ‘genuine’ reviews. There is no moderating effect of negative sentiments on Trustworthiness. Our research results find that valences of TripAdvisor review are useful to potential tourists for their travel planning and actions. Practitioners should listen to TripAdvisor review valences and keep up with the value chain, make the destinations more tourist friendly and evolve new themes. Tourism ecosystem should use modicum of digital opportunities emanating from sentiments and apply appropriate strategies to develop their destinations. This way, tourists will develop brand equity. This study contributes to the growing body of literature on polarity analysis in TripAdvisor reviews and investigated the relationship between positive and negative valences with trustworthiness.
Sistema básico de monitorización para la regulación de la contaminación atmosférica en la Ciudad de Esmeraldas: caso IOT para redes sensoriales

El internet de las cosas implica un modelo de gestión para aumentar la eficiencia de los procesos productivos, inclusive cuando se trata de aplicaciones que no pertenecen al proceso de manufactura, pero necesitan de datos relevantes para tomar decisiones técnicas a nivel de control y ejercer acción sobre una salida. Se presenta una red sensorial que permite determinar los niveles de contaminación sobre la norma aplicada al Ecuador, y en base a ella se determina la ubicación técnica más conveniente para poder instalar una red de comunicación que permita la visualización de los datos recolectados.