Miracle-dz/UniFAR-FTUs huggingface dataset:
Biomarkers as Biomedical Bioindicators: Approaches and Techniques for the Detection, Analysis, and Validation of Novel Biomarkers of Diseases

A biomarker is any measurable biological moiety that can be assessed and measured as a potential index of either normal or abnormal pathophysiology or pharmacological responses to some treatment regimen. Every tissue in the body has a distinct biomolecular make-up, which is known as its biomarkers, which possess particular features, viz., the levels or activities (the ability of a gene or protein to carry out a particular body function) of a gene, protein, or other biomolecules. A biomarker refers to some feature that can be objectively quantified by various biochemical samples and evaluates the exposure of an organism to normal or pathological procedures or their response to some drug interventions. An in-depth and comprehensive realization of the significance of these biomarkers becomes quite important for the efficient diagnosis of diseases and for providing the appropriate directions in case of multiple drug choices being presently available, which can benefit any patient. Presently, advancements in omics technologies have opened up new possibilities to obtain novel biomarkers of different types, employing genomic strategies, epigenetics, metabolomics, transcriptomics, lipid-based analysis, protein studies, etc. Particular biomarkers for specific diseases, their prognostic capabilities, and responses to therapeutic paradigms have been applied for screening of various normal healthy, as well as diseased, tissue or serum samples, and act as appreciable tools in pharmacology and therapeutics, etc. In this review, we have summarized various biomarker types, their classification, and monitoring and detection methods and strategies. Various analytical techniques and approaches of biomarkers have also been described along with various clinically applicable biomarker sensing techniques which have been developed in the recent past. A section has also been dedicated to the latest trends in the formulation and designing of nanotechnology-based biomarker sensing and detection developments in this field.
Laser Cavitation Peening: A Review

During submerged laser peening using a pulsed laser, a bubble that behaves like cavitation is generated after laser ablation (LA). The bubble is referred to as laser cavitation (LC). The amplitude of the shockwave in water generated by LA is larger than that of LC; however, the impact passing through the target metal during LC is larger than that of LA. LC impact can be utilized for peening at optimized conditions. Thus, submerged laser peening is referred to as “laser cavitation peening”, as the peening method using the cavitation impact is known as “cavitation peening”. The impact induced by a hemispherical bubble is more aggressive than that of a spherical bubble with a microjet. Laser cavitation peening can improve the fatigue strength of metallic materials by producing work-hardening and introducing compressive residual stress. Three-dimensional additively manufactured metals (3D metals) such as titanium alloy are attractive materials for aviation components and medical implants; however, the fatigue strength of as-built components is nearly half of that of bulk metals, and this is an obstacle for the applications of 3D metals. In the present study, published research papers are reviewed to identify the key factors of laser cavitation peening, with additional visualization of LC and data. Then, improvements in the fatigue strength of metallic materials, including 3D metals treated by laser cavitation peening, are summarized.
Simulating Nonlinear Neutrino Oscillations on Next-Generation Many-Core Architectures

In this work an astrophysical simulation code, XFLAT, is developed to study neutrino oscillations in supernovae. XFLAT is designed to utilize multiple levels of parallelism through MPI, OpenMP, and SIMD instructions (vectorization). It can run on both the CPU and the Xeon Phi co-processor, the latter of which is based on the Intel Many Integrated Core Architecture (MIC). The performance of XFLAT on configurations and scenarios has been analyzed. In addition, the impact of I/O and the multi-node configuration on the Xeon Phi-equipped heterogeneous supercomputers such as Stampede at the Texas Advanced Computing Center (TACC) was investigated.
Mathematical Model of Information Exchange in the Autonomous Underwater Vehicle Network

: Nowadays, a lot of attention is given to autonomous underwater exploration. To reduce the time of such explorations groups of networked underwater vehicles are used. The implementation of such communication is rather problematic because of low message transfer speed and other factors related to the underwater environment. In such networks, messages often pass through a chain of relay nodes to reach their destination point. Moreover, vehicles can form queues of messages to be transmitted. The order of messages in the queue can inﬂuence the total transmission time. In complex information exchange scenarios, it is crucial to order the messages that should be delivered to ensure optimal management of the process. The proposed article discusses an optimization of messaging in a network of autonomous underwater vehicles. The authors propose algorithms for scheduling information exchanges in an underwater network. These algorithms are suboptimal. Algorithms that satisfy the criteria of the minimum upper bounds for either the total or average delivery time have been proposed. The authors considered situations when messages are unordered, as well as when messages are partially pre-ordered.
Evaluation of Wild Almond Genotypes Grown as a Rain-fed Crop in Sulaimani Governorate using RAPD and ISSR Markers

Almond is considered the most common and essential nut grown in the rainfed area. It has many species wildly distributed in the Iraqi Kurdistan region, which are called Chaqala by local people. To understand and improve the characteristics of the cultivated almonds, a comprehensive study of wild almonds in terms of population structure and genetic diversity is needed to transfer new traits into the domesticated almonds. So, twelve different genotypes were collected and analyzed using random amplified polymorphic DNA (RAPD) and inter-simple sequence repeat (ISSR) markers. The results revealed polymorphic bands for both markers, the mean value of 5.8 for the RAPD marker and 7.8 for the ISSR marker was also documented. The polymorphic information content (PIC) values were obtained for RAPD primes that range between (0.64-0.85) and ISSR primers were also verified between (0.53-0.91), which shows the discriminatory power of these markers. “Jaccard similarity coefficients” were obtained between 0.34 (G11 vs. G12) to 0.77 (G1 vs. G10), and clustered into four groups with a mean similarity (0.65) for ten RADP markers. For ten ISSR markers, 0.35 (G8, G10) to 0.79 (G6 vs. G11) were also observed, which is clustered into a mean similarity (0.65). Structure analysis of RAPD and ISSR showed two major groups. Overall, these outcomes showed the diversity between the studied genotypes and among groups which are highly important for future almond breeding and conservation programs.
A Benchmark for the UEQ+ Framework: Construction of a Simple Tool to Quickly Interpret UEQ+ KPIs

Questionnaires are a highly efficient method to compare the user experience (UX) of different interactive products or versions of a single product. Concretely, they allow us to evaluate the UX easily and to compare different products with a numeric UX score. However, often only one UX score from a single evaluated product is available. Without a comparison to other measurements, it is difficult to interpret an individual score, e.g. to decide whether a product’s UX is good enough to compete in the market. Many questionnaires offer benchmarks to support researchers in these cases. A benchmark is the result of a larger set of product evaluations performed with the same questionnaire. The score obtained from a single product evaluation can be compared to the scores from this benchmark data set to quickly interpret the results. In this paper, the first benchmark for the UEQ+ (User Experience Questionnaire +) is presented, which was created using 3.290 UEQ+ responses for 26 successful software products. The UEQ+ is a modular framework that contains a high number of validated user experience scales that can be combined to form a UX questionnaire. Currently, no benchmark is available for this framework, making the benchmark constructed in this paper a valuable interpretation tool for UEQ+ questionnaires.
Trusting Behavior, Risk Preference and Loss Aversion

—This paper uses experimental methods to study if individual’s risk preference or loss aversion will affect people’s trusting behavior. The results of the experiment show that individuals’ risk preference significantly impacts people’s trusting behavior. Compared with other subjects, people who are relatively less risk-averse show a higher degree of trust in others. Moreover, individuals’ loss aversion also affects people’s trusting behavior, subjects with relatively lower levels of loss aversion exhibit a higher degree of trust in others.
Jak2 and Jaw Muscles Are Required for Buccopharyngeal Membrane Perforation during Mouth Development

The mouth is a central feature of our face, without which we could not eat, breathe, or communicate. A critical and early event in mouth formation is the creation of a “hole” which connects the digestive system and the external environment. This hole, which has also been called the primary or embryonic mouth in vertebrates, is initially covered by a 1–2 cell layer thick structure called the buccopharyngeal membrane. When the buccopharyngeal membrane does not rupture, it impairs early mouth functions and may also lead to further craniofacial malformations. Using a chemical screen in an animal model (Xenopus laevis) and genetic data from humans, we determined that Janus kinase 2 (Jak2) has a role in buccopharyngeal membrane rupture. We have determined that decreased Jak2 function, using antisense morpholinos or a pharmacological antagonist, caused a persistent buccopharyngeal membrane as well as the loss of jaw muscles. Surprisingly, we observed that the jaw muscle compartments were connected to the oral epithelium that is continuous with the buccopharyngeal membrane. Severing such connections resulted in buccopharyngeal membrane buckling and persistence. We also noted puncta accumulation of F-actin, an indicator of tension, in the buccopharyngeal membrane during perforation. Taken together, the data has led us to a hypothesis that muscles are required to exert tension across the buccopharyngeal membrane, and such tension is necessary for its perforation.
From flowers to far-right extremists: A genealogy of ecology in terrorism and extremism studies

ABSTRACT The idea that violent extremists inhabit an “ecosystem” of interrelated online spaces has been popularised by both scholars and practitioners in recent years. Drawing from the natural sciences, terrorism and extremism studies has sought to capitalise on the conceptual potential of ecology to understand otherwise perplexing natural and artificial environments. Yet, despite its popularisation, there remain fundamental gaps in understanding the benefits and limits of using ecology to analyse extremist communities dwelling in cyberspace. To be applied in a rigorous manner, it is essential that the intellectual tradition and tenets that underpin ecology in the natural and social sciences be explained. Since its conception in biology, this article presents a historical and conceptual exploration of ecology to explain the lessons, opportunities, and limits it presents scholars and practitioners in terrorism and extremism studies today. This article provides the first systematic, genealogical overview of how ecology has evolved from the study of plant communities to become relevant in far-right extremism studies. This article provides foundational knowledge and lessons for moving disciplinary research and policy work forward, and offers guidance on how future studies can use ecology in a more rigorous and consistent manner.
Ordering and surface segregation in Co1−cPtc nanoparticles: A theoretical study from surface alloys to nanoalloys

Monte Carlo simulations within a tight-binding Ising model (TBIM) have been performed on bulk, surfaces, and nanoclusters of Co 1-c -Pt c alloys in order to describe and understand the competition or synergy between surface segregation and chemical ordering phenomena in nanoalloys. Considering effective pair interactions (EPIs) up to the third neighbors, we put in evidence new ordered phases at low temperature in the Co-Pt bulk phase diagram. On the inﬁnite (100) and (111) surfaces, the Pt surface segregation leads to select the Pt-rich plan at the surface without modiﬁcation of the bulk ordering in the (100) orientation but with an extension of the ordering on a larger composition range in the (111) orientation as compared to the bulk. The truncated octahedron clusters of 405 and 1289 atoms are studied. Their chemical structure is compared in their core with the bulk phase diagram and in their facets with the (111) and (100) inﬁnite surfaces segregation isotherms. The cluster core presents an asymmetry as compared to the bulk phase diagram. The (111) facets are similar to the (111) surface, whereas the (100) facets present geometrical frustrations for the segregation versus core ordering.
Application of improved graph theory image segmentation algorithm in tongue image segmentation

For the special characters of human's tongue,when directly segmenting the tongue's image,over-segmentation and over-merging always exist.Based on the characters of the tongue's image,this paper combines one of the Graph theory image segmentation methods and multi-resolution image segmentation together to segment the image on two different resolutions.Based on the two results'situation,"AND"or"OR"operation is used to deal with them and the tongue body is exacted from the image.In practice,this method can effectively avoid the above problems.
Reverse Attention Dual-Stream Network for Extracting Laver Aquaculture Areas From GF-1 Remote Sensing Images

Extracting laver aquaculture areas from remote sensing images is very important for laver aquaculture monitoring and scientific management. However, due to the large differences in spectral features of laver aquaculture areas caused by factors such as different growth stages and harvesting conditions, traditional machine learning and deep learning methods face great challenges in achieving accurate and complete extraction of raft laver aquaculture areas. In this article, a reverse attention dual-stream network (RADNet) is proposed for the extraction of laver aquaculture areas with weak spectral responses by comprehensively considering both the aquaculture boundary and surrounding sea background information. RADNet consists of a boundary stream and a segmentation stream. Considering the weaker spectral responses of certain laver aquaculture areas, we introduce a reverse attention module in the segmentation stream to amplify the weaker responses of inapparent laver aquaculture areas. To suppress the response of nonboundary details in the boundary stream, we design a boundary attention module, which is guided by high-level semantics from the segmentation stream. The structural information of the laver aquaculture area learned from the boundary stream will be fed back to the segmentation stream through a specially designed boundary guidance module. The study is conducted in Haizhou Bay, China, and is verified using a self-labeled GF-1 multispectral dataset. The experimental results show that RADNet model performs better in extracting inapparent laver aquaculture areas compared to SOTA models.
INVERSE MODELING AND UNCERTAINTY QUANTIFICATION OF NONLINEAR FLOW IN POROUS MEDIA MODELS

When using computer models to predict flow in porous media, it is necessary to set parameter values that correctly characterize the geological properties like permeability and porosity. Besides direct measurements of these geological properties, which may be expensive and difficult, parameter values could be obtained from inverse modeling which calibrates the model to any available observations on flow behaviors such as pressure, saturation and well production rates. A typical inverse problem has non-unique solutions because the information contained in the observations is usually insufficient to identify all uncertain parameters. Finding a single solution to the inverse problem that well matches all observations does not guarantee the correct representation of the real geological system. In order to capture multiple solutions and quantify remaining uncertainty we solve an inverse problem from a probabilistic point of view: seek the posterior distribution of parameters given the observations using Bayes’ theorem. In the situation where the model is nonlinear, which is often the case of subsurface flow problems, the posterior distribution cannot be analytically derived. Instead we implement numerical algorithms to find approximate results. The key to running an inversion algorithm is to understand how the
Geodynamics of the South Balkan and Northern Aegean Regions Driven by the Westward Escape of Anatolia

The Plio-Quaternary deformation pattern of the northern Aegean and south Balkan regions is interpreted as an effect of the interaction between the Anatolian-Aegean-Pelagonian system (Tethyan belt), undergoing westward extrusion and strong deformation, and the surrounding plates (Nubia, Europe and Adriatic). Since the middle-late Miocene, the collision of the Tethyan belt with the continental Adriatic domain has caused strong E-W shortening in the outer Hellenides and Albanides, also involving the southward extrusion of the Peloponnesus wedge, at the expense of the Ionian oceanic domain. The roughly E-W extension recognized in the western South Balkan zones (Ma-cedonia and eastern Albania) is related to the divergence between the Pelagonian belt (Albanides and Hellenides) and the Rhodope-Moesia domain. Stressed by the westward displacement of the central Anatolian plateau and by the southward bowing of the Cycladic Arc, the northern Aegean zone has con-temporaneously undergone E-W compression and N-S extension, which has generated a series of dextral shear faults, delimiting a number of slats. The westward displacement and deformation of such slats can explain the morphological features of the northern Aegean
RNA-Seq Analysis of Aboveground and Underground Parts of Biomass Sorghum Was Performed to Evaluate Its Suitability for Environmental Remediation

“Alto2” is a new biomass sorghum variety, which has the characteristics of fast growth, high growth, and strong cadmium (Cd) resistance, so it has the application prospect of soil remediation plants. In order to reveal the Cd resistance mechanism of this plant and pave the way for genetic breeding and cultivation of efficient remediation plants in the future, in this research, through the determination of Cd content in various tissues of sorghum under Cd stress and the physicochemical response combined with RNA-Seq analysis, the mechanism of Cd resistance of “Alto2” was initially revealed. The results show biomass sorghum “Alto2” was mainly connected with aboveground and underground parts through the MAPK signaling pathway and plant hormone signaling pathway, and transmit stress signal in response to Cd stress. Chelase and metal-binding proteins may be the functional genes mainly responsible for Cd enrichment and transport and regulated by stress signals. However, the expression of aboveground transporters was not significant. This may be because Cd in biomass sorghum is mainly concentrated in the underground part and is enriched by the chelation of secondary metabolites from plant roots by the cell wall leading to inhibition of aboveground transporter expression. The results of this study indicate that the biomass sorghum “Alto2” on Cd has high resistance, but the lack of the aboveground enrichment of transportability requires further research to improve the Cd transportability of this plant.
The Regulated Secretion and Models of Intracellular Transport: The Goblet Cell as an Example

Transport models are extremely important to map thousands of proteins and their interactions inside a cell. The transport pathways of luminal and at least initially soluble secretory proteins synthesized in the endoplasmic reticulum can be divided into two groups: the so-called constitutive secretory pathway and regulated secretion (RS) pathway, in which the RS proteins pass through the Golgi complex and are accumulated into storage/secretion granules (SGs). Their contents are released when stimuli trigger the fusion of SGs with the plasma membrane (PM). In specialized exocrine, endocrine, and nerve cells, the RS proteins pass through the baso-lateral plasmalemma. In polarized cells, the RS proteins secrete through the apical PM. This exocytosis of the RS proteins increases in response to external stimuli. Here, we analyze RS in goblet cells to try to understand the transport model that can be used for the explanation of the literature data related to the intracellular transport of their mucins.
A finite element solution of unsteady two-dimensional flow in cascades

SUMMARY A theory is presented for unsteady two-dimensional potential transonic flow in cascades of compressor and turbine blades using a mesh of triangular finite elements. The theory leads to a computer program, FINSUP, which is fast and has moderate storage requirements, so that it can be run on a personal computer. Comparisons with other theories in special cases show that the program is accurate in subsonic flow, and that in supersonic flow, although the wave effects are smeared by the numerical process, the results for overall blade force and moment have acceptable accuracy. The program is useful for engineering assessment of unstalled flutter of actual compressor and turbine blades.
Lower Limb Exoskeleton for Rehabilitation with Flexible Joints and Movement Routines Commanded by Electromyography and Baropodometry Sensors

This paper presents the development of an instrumented exoskeleton with baropodometry, electromyography, and torque sensors. The six degrees of freedom (Dof) exoskeleton has a human intention detection system based on a classifier of electromyographic signals coming from four sensors placed in the muscles of the lower extremity together with baropodometric signals from four resistive load sensors placed at the front and rear parts of both feet. In addition, the exoskeleton is instrumented with four flexible actuators coupled with torque sensors. The main objective of the paper was the development of a lower limb therapy exoskeleton, articulated at hip and knees to allow the performance of three types of motion depending on the detected user’s intention: sitting to standing, standing to sitting, and standing to walking. In addition, the paper presents the development of a dynamical model and the implementation of a feedback control in the exoskeleton.