Fundamental Types Research Articles

An Overview of the most Common Vehicle Suspension Problems

The design of the suspension system, which transmits force between the vehicle and the ground, is principally responsible for the driving comfort of a vehicle. Importantly, a vehicle's suspension system contributes to the reliability and precision of steering and control, as well as to the friction between the vehicle and the road. The suspension system is also responsible for absorbing and dampening road stress, so that we do not feel every bump on the road when driving. Linkages, springs, and shock absorbers are the three fundamental types of suspension components. This paper introduced the most common suspension problems and the symptoms that may indicate you need a suspension system repair, where it turns out that there is a set of problems common to all vehicle suspension systems, such as poor wheel alignment, faulty shocks or struts, damaged springs, failing ball joints, and faulty control arms. Now as a conclusion of this paper, the reader can know the most common suspension system problems in vehicles and thus how to deal with these problems.

IRFNet: Skin Lesion Detection and Classification Using Unified Intuitive and Object Classifier with Iterative Random Forest Algorithm

Skin cancer is one of the critical diseases that occurs in different age groups of the population. Early detection and prevention can save many lives. Melanoma is one of the fundamental skin cancer types. The traditional approaches for skin lesion detection and classification (SLDC) failed to distinguish between melanoma and non-melanoma skin malignancies, resulting in low classification accuracy. Thus, this article is focused on the implementation of computer aided detection method for SLDC using iterative random forest (IRF) algorithm, hereafter named as IRFNet. The proposed IRFNet acts as a decision-making tool for the dermatologists. Initially, the first level consists of five intuitive classifiers (ICs) named as perceptron coupled with color local binary patterns (PC-CLBP), histograms of oriented gradients (HOGs), the generative adversarial network coupled with ABCD rule (GAN-ABCD), ResNet, and AlexNet are used to extract the texture, shape, color, size, and convolutional pixel connections-based features from given skin lesion images. Then, IRF algorithm is used to select the optimal features and finally the object classifier called deep learning convolutional neural network (DLCNN) is employed to classify the type of lesion as either melanoma or non-melanoma based on back-propagation perceptron that provides the final decision. The extensive simulation outcome performed on ISIC-2019 and PH2 datasets discloses the superiority of the proposed IRFNet in terms of precision, recall, sensitivity, specificity, and f1-score. In addition, it also achieved the trade-off between classification accuracy and execution time as compared to the existing SLDC approaches.

Quantifying the anion effect of gas solubility within ionic liquids using the solvation affinity index

The solubility of gas molecules within ionic liquids (ILs) is strongly dictated by the anion effect and the free volume effect, and of these two influences, the anion effect can be challenging to predict. We evaluate a wide range of different gas solutes (O2, NH3, CH4, H2S, SO2, Ar, H2, N2, CO2) in different ILs, and we find that the solubility is strongly correlated to one of three different IL properties, which can be directly calculated from the anion electrostatic potential (ESP) surfaces. Thus, the solutes can be grouped into three fundamental types, leading to a general descriptor, the solvation affinity index (SAI), which can identify the affinity between a wide range of gas solutes and IL solvents. The SAI of nine common industrial gases with 47 common anions are generated. This can provide a fast approach for pre-screening IL solvents or even for ILs embedded within porous supports.

Analyzing data with systematic bias

In many data analysis problems, we only have access to biased data due to some systematic bias of the data collection procedure. In this letter, we present a general formulation of systematic bias in data as well as our recent results on how to handle two very fundamental types of systematic bias that arise frequently in econometric studies: truncation bias and self-selection bias.

Spatiotemporal Organization of Electromechanical Phase Singularities during High-Frequency Cardiac Arrhythmias

Ventricular fibrillation (VF) is a lifethreatening electromechanical dysfunction of the heart associated with complex spatiotemporal dynamics of electrical excitation and mechanical contraction of the heart muscle. It has been hypothesized that VF is driven by three-dimensional (3D) rotating electrical scroll waves, which can be characterized by filament-like electrical phase singularities (EPS). Recently, it was shown that rotating excitation waves during VF are associated with rotating waves of mechanical deformation. 3D mechanical scroll waves and mechanical filaments describing their rotational core were observed in the ventricles by using high-resolution ultrasound. The findings suggest that the spatiotemporal organization of cardiac fibrillation may be assessed from waves of mechanical deformation. However, the complex relationship between excitation and mechanical waves during VF is currently not understood. Here, we study the fundamental nature of mechanical phase singularities (MPS), their spatiotemporal organization and relation with EPS. We demonstrate the existence of two fundamental types of MPS: "paired singularities", which are co-localized with EPS, and "unpaired singularities", which can form independently. We show that the unpaired singularities emerge due to the anisotropy of the active force field, generated by fiber anisotropy in cardiac tissue, and the non-locality of elastic interactions, which jointly induce strong spatiotemporal inhomogeneities in the strain fields. The inhomogeneities lead to the breakup of deformation waves and create MPS, even in the absence of EPS, which are typically associated with excitation wave break. We exploit these insights to develop an approach to discriminate paired and unpaired MPS. Our findings provide a fundamental understanding of the complex spatiotemporal organization of electromechanical waves in the heart.

Typology and Progression of Death in the Work of J.R.R. Tolkien «The Children of Hurin»

The article discusses the study of the phenomenon of death in the book "The Children of Hurin" by the famous English writer and thinker John Ronald Reuel Tolkien. Tolkien views "death" as a philosophical category. Two aspects of the category of death in Tolkien's work are revealed: 1) death as a gift, 2) death as a curse. The analysis of the typology of death in the work «The Children of Hurin» is carried out in accordance with the ethical content of each type. As a result, ten main types of death and ethical violations are distinguished according to Tolkien's thought, thereby reconstructing the system of his ethical views. The full progression of death devised by J.R.R. Tolkien is reconstructed according to the text of «The Children of Hurin». Each type of death is corresponded with a certain vice which helps us see the consecutive links of the writer’s ethical conception. The author developed a sophisticated philosophy of death and singled out its two fundamental types: «death as a gift» and «death as a curse».

Transcriptome and TCR Repertoire Measurements of CXCR3+ T Follicular Helper Cells Within HIV-Infected Human Lymph Nodes.

Follicular-helper T cells (TFH) are an essential arm of the adaptive immune system. Although TFH were first discovered through their ability to contribute to antibody affinity maturation through co-stimulatory interactions with B cells, new light has been shed on their ability to remain a complex and functionally plastic cell type. Due to a lack sample availability, however, many studies have been limited to characterizing TFH in mice or non-canonical tissue types, such as peripheral blood. Such constraints have resulted in a limited, and sometimes contradictory, understanding of this fundamental cell type. One subset of TFH receiving attention in chronic infection are CXCR3-expressing TFH cells (CXCR3+TFH) due to their abnormal accumulation in secondary lymphoid tissues. Their function and clonal relationship with other TFH subsets in lymphoid tissues during infection, however, remains largely unclear. We thus systematically investigated this and other subsets of TFH within untreated HIV-infected human lymph nodes using Mass CyTOF and a combination of RNA and TCR repertoire sequencing. We show an inflation of the CXCR3+TFH compartment during HIV infection that correlates with a lower HIV burden. Deeper analysis into this population revealed a functional shift of CXCR3+TFH away from germinal center TFH (GC-TFH), including the altered expression of several important transcription factors and cytokines. CXCR3+TFH also upregulated cell migration transcriptional programs and were clonally related to peripheral TFH populations. In combination, these data suggest that CXCR3+TFH have a greater tendency to enter circulation than their CXCR3- counterparts, potentially functioning through distinct modalities that may lead to enhanced defense.

Multi-meron interactions and statistics in two-dimensional materials

As a fundamental type of topological spin textures in two-dimensional (2D) magnets, a magnetic meron carries half-integer topological charge and forms a pair with its antithesis to keep the stability in materials. However, it is challenging to quantitatively calculate merons and their dynamics by using the widely used continuum model because of the characteristic highly inhomogeneous spin textures. In this work, we develop a discrete method to address the concentrated spin structures around the core of merons. We reveal a logarithmic-scale interaction between merons when their distance is larger than twice their core size and obtain subsequent statistics of meron gas. The model also predicts how these properties of single and paired merons evolve with magnetic exchange interactions, and the results are in excellent agreement with the Monte Carlo simulations using the parameters of real 2D van der Waals magnetic materials. This discrete approach not only shows equilibrium static statistics of meron systems but also is useful to further explore the dynamic properties of merons through the quantified pairing interactions.

Recent developments and applications of simultaneous localization and mapping in agriculture

AbstractSimultaneous Localization and Mapping (SLAM) is a process to use multiple sensors to position an unmanned mobile vehicle without previous knowledge of the environment, and meanwhile construct a map of this environment for the further applications. Over the past three decades, SLAM has been intensively researched and widely applied in mobile robot control and unmanned vehicle navigation. SLAM technology has demonstrated a great potential in autonomously navigating the mobile robot and simultaneously reconstructing the three‐dimensional (3D) information of surrounding environment. With the vigorous driving of sensor technology and 3D reconstruction algorithms, many attempts have been conducted to propose novel systems and algorithms combined with different sensors to solve the SLAM problem. Notably, SLAM has been extended to various aspects of agriculture involved with autonomous navigation, 3D mapping, field monitoring, and intelligent spraying. This paper focuses on the recent developments and applications of SLAM, particularly in complex and unstructured agricultural environment. A detailed summary of the developments of SLAM is given from three main fundamental types: light detection and ranging SLAM, Visual SLAM, and Sensor Fusion SLAM, and we also discuss the applications and prospects of SLAM technology in agricultural mapping, agricultural navigation, and precise automatic agriculture. Particular attention has been paid to the SLAM sensors, systems, and algorithms applied in agricultural tasks. Additionally, the challenges and future trends of SLAM are reported.

An Analytic Hierarchy Process (AHP) Framework for Selecting Flexible Manufacturing System

The main objective of this paper is to propose a structured model for evaluating different Flexible Manufacturing System (FMS) using the Analytic Hierarchy Process (AHP). The paper aims to demonstrate how the model can help in taking correct decisions regarding the type of manufacturing flexibility needed for best FMS. This is because huge amount of money is invested to implement FMS in the industry. Hence, managers need to take judicious decision regarding the type and level of manufacturing flexibility. There are a number of manufacturing flexibility being reported in the literature. In this paper the most fundamental types i.e., machine, routing and product flexibility are examined. The AHP is aimed at integrating different measures into a single overall score for ranking decision alternatives. Its main characteristic is that it is base on pairwise comparison judgment. A usability evaluation of the AHP based model of FMS along with structure of the hierarchy is developed. The framework that is used in this example could serve as one of the tools for making a strategic decision. The effectiveness of our model is demonstrated through numerical examples.

Religiosity, Religious Fundamentalism, Heterosexism, and Support for Lesbian and Gay Civil Rights: A Moderated Mediation Approach

Support for lesbian and gay (LG) civil rights has increased in recent decades, but heterosexism is still prevalent, particularly among highly religious populations. Evidence suggests, however, that it may not be affiliation, but rather conviction in one’s beliefs that relates to prejudicial attitudes. The aims of this study were to examine the relationships among religiosity, heterosexism, and level of support for LG civil rights, as well as potential moderating effects by religious fundamentalism. This study used Amazon’s Mechanical Turk (Mturk) to recruit a U.S. national sample (n = 407) to participate in an online survey. A mediation model was constructed with religiosity leading to heterosexism, which diminished support for LG civil rights. This mediation model was expanded into moderated mediations with three types of religious fundamentalism as moderators. Heterosexism fully mediated the relationship between religiosity and support for LG civil rights. A moderated mediation was observed for aspects of religious fundamentalism reflecting external authority and worldly rejection (but not fixed religion) such that the mediation was present only when participants had high levels of these types of religious fundamentalism. Despite the belief that religious people endorse higher levels of heterosexism and that this influences their support for LG civil rights, this is only true when religiosity is also coupled with fundamentalist belief systems reflecting external authority and worldly rejection.

ПАРАДИГМА ЕКОНОМІЧНОЇ НАУКИ І ПОТЕНЦІАЛ ЇЇ ЗМІН У XXI ст.

Зміни в парадигмі економічної науки розглядаються як відповідь на системні трансформації економіки початку XXI ст. Під потенціалом зміни парадигми розуміється рівень готовності й схильності сучасної економічної науки до парадигмальних зрушень. При цьому зміна наукової парадигми визначається як внутрішнім потенціалом самої науки, так і потенціальним впливом зовнішнього соціально-економічного середовища. Репрезентовано авторське розуміння сутності й структурних компонентів парадигми економічної науки XXI ст. У контексті проблеми моно-/поліпарадигмальності економічної науки виокремлено зміст парадигмального комплексу на основі критеріального застосування трьох фундаментальних категоріальних типів: онтологічного, епістемологічного і аксіологічного. Розкрито основні нормативні положення домінуючої нині неокласичної парадигми як мейнстриму економічної науки з позицій критичного ставлення до них. Центральною аномалією неокласичної парадигми є фактичне заперечення категорії «вартість». Архітектоніка системи сучасних фінансів, де переважають віртуальні фінансові активи, які «відірвані» від їх реальної вартісної оцінки, успішно «функціонує», на думку неокласиків, без категорії «вартість». Доведено, що наукове економічне дослідження у своїй реальності не може не спиратися на кількісні наукометричні моделі, в основу яких має бути покладено категорію “вартість”. Вартість є первинним онтологічним фундаментом економічної науки. Запропоновано інтерпретацію потенційних можливостей парадигмального оновлення сучасної економічної науки з урахуванням відповідних об’єктивних змін глобального соціально-економічного розвитку. Обґрунтовується необхідність парадигмального подолання відособлення мікро- і макроекономіки, розширення застосування емпіричних аналітичних методів та їх формалізованої інтерпретації на основі використання штучного інтелекту в процесі наукових досліджень, поліпшення механізмів управління складними соціально-економічними системами на підставі прогнозування їх розвитку.

AN EVALUATION OF ENVIRONMENTAL IMPACTS OF REAL ESTATE PROJECTS

The negative environmental implications of real estate projects are one of the industry’s largest challenges. During construction, environmental consequences occur. Many threats to the ecosystem are human made, such as the ones occurring due to construction projects. That’s why this study’s purpose is to determine the country’s biggest environmental impacts. An examination of the literature discovered 28 environmental consequences of real estate construction which are subdivided into three fundamental types of repercussions was cross-sectional surveyed. A total of 48 building specialists were picked at random for questioning. Based on these experts response, the most serious environmental concerns were ranked. The relative importance index was used for ranking the discovered impacts (RII).The study concluded that real estate projects causes dust, social disruption, noise pollution, and energy usage. Construction workers were more prone to lung and organ cancer, hypertension, irritability, and insomnia, as well as other heart-related concerns. Some of the remedial measures to overcome these issues might include requiring institutions to complete environmental impact assessments (EIA). Results of the study can assist decision-makers in identifying significant environmental implications of construction and developing environmentally friendly building plans early on. KEYWORDS: Environment, Construction, Ecosystem, Pollution, Public Impact

Scanning Disk Rings and Winds in CO at 0.01–10 au: A High-resolution M-band Spectroscopy Survey with IRTF-iSHELL

Abstract We present an overview and first results from a M-band spectroscopic survey of planet-forming disks performed with iSHELL on the Infrared Telescope Facility, using two slits that provide resolving power R ≈ 60,000–92,000 (5–3.3 km s−1). iSHELL provides a nearly complete coverage at 4.52–5.24 μm in one shot, covering >50 lines from the R and P branches of 12CO and 13CO for each of multiple vibrational levels, and providing unprecedented information on the excitation of multiple emission and absorption components. Some of the most notable new findings of this survey are: (1) the detection of two CO Keplerian rings at <2 au (in HD 259431), (2) the detection of H2O rovibrational lines at 5 μm (in AS 205 N), and (3) the common kinematic variability of CO lines over timescales of 1–14 yr. By homogeneously analyzing this survey together with a previous survey of cooler stars, we discuss a unified view of CO spectra where emission and absorption components scan the disk surface across radii from a dust-free region within dust sublimation out to ≈10 au. We classify two fundamental types of CO line shapes interpreted as emission from Keplerian rings (double-peak lines) and a disk surface plus a low-velocity part of a wind (triangular lines), where CO excitation reflects different emitting regions (and their gas-to-dust ratio) rather than just the irradiation spectrum. A disk+wind interpretation for the triangular lines naturally explains several properties observed in CO spectra, including the line blueshifts, line shapes that turn into narrow absorption at high inclinations, and the frequency of disk winds as a function of the stellar type.

I Hear You Feel Confident

AbstractHere I explore a new line of evidence for belief–credence dualism, the thesis that beliefs and credences are distinct and equally fundamental types of mental states. Despite considerable recent disagreement over this thesis, little attention has been paid in philosophy to differences in how our mindreading systems represent the beliefs and credences of others. Fascinatingly, the systems we rely on to accurately and efficiently track others’ mental states appear to function like belief–credence dualists: Credence is tracked like an emotional state, composed of both representational and affective content, whereas belief is tracked like a bare representational state with no affective component. I argue on a preliminary basis that, in this particular case, the mechanics of mentalizing likely pick out a genuine affective dimension to credence that is absent for belief, further strengthening the converging case for belief–credence dualism.

A novel approach for high-quality drainage network extraction in flat terrains by using a priori knowledge of hydrogeomorphic features to extend DEMs: A case study in the Hoh Xil region of the Qinghai-Tibetan Plateau

Being a fundamental type of hydrogeomorphic parameter, drainage networks have been widely applied in the fields of geographic cartography, hydrologic and hydraulic modeling, water resource management, flood risk analysis, and so on. The rapid developments of modern remote sensing technologies have greatly improved the resolution and precision of spatial data providing a plenty of microtopographic information that could have significant impacts on the surface runoff, but most of the drainage network extraction methods have paid less attention to it especially for flat terrains. In order to deal with this problem, we propose a novel approach for high-quality drainage network extraction in flat terrains, in which the hydrogeomorphic features with the function of obstruction, guidance or collection to the runoff are considered as a priori knowledge used to extend digital elevation models (DEMs). Firstly, the hydrogeomorphic features that have obvious influences on surface runoff are classified, and used as a priori knowledge to extract drainage networks. After mathematically described by reorganizing their data into raster form and semanticizing their responses to runoff, this prior knowledge is then incorporated into a DEM to construct a Digital elevation-eXtended Model (DXM). Secondly, in order to solve the problem of erroneous or indeterminate flow directions in drainage network extraction based on the DEM alone, a method of drainage network extraction based on DXM is thereby developed. Finally, the proposed approach is applied and validated in a case study in Yanhu Lake area of Hoh Xil in the Qinghai–Tibet Plateau. The DEMs and digital orthophoto maps (DOMs) with sub-meter resolution were collected by employing unmanned aerial vehicle-based (UAV-based) structure-from-motion (SFM) photogrammetry. The hydrogeomorphic features with runoff responses were extracted from the DOMs and used as a priori knowledge. Various DXMs are constructed based on the extracted hydrogeomorphic features and DEMs to extract the drainage networks of the study area. The extraction results are qualitatively and quantitatively evaluated by visual comparisons and statistical analysis to validate the proposed approach. Additionally, the effects of DEM resolution and the presence of a priori knowledge on the quality of drainage network extraction were investigated. It is found that the DXM can clearly determine the flow directions by adding useful auxiliary information into the conventional D8 algorithm. This approach provides a new high-efficient way to extract the drainage networks in flat terrains.

Emergent strings, duality and weak coupling limits for two-form fields

We systematically analyse weak coupling limits for 2-form tensor fields in the presence of gravity. Such limits are significant for testing various versions of the Weak Gravity and Swampland Distance Conjectures, and more broadly, the phenomenon of emergence. The weak coupling limits for 2-forms correspond to certain infinite-distance limits in the moduli space of string compactifications, where asymptotically tensionless, solitonic strings arise. These strings are identified as weakly coupled fundamental strings in a dual frame, which makes the idea of emergence manifest. Concretely we first consider weakly coupled tensor fields in six-dimensional compactifications of F-theory, where the arising tensionless strings play the role of dual weakly coupled heterotic strings. As the main part of this work, we consider certain infinite distance limits of Type IIB strings on K3 surfaces, for which we show that the asymptotically tensionless strings describe dual fundamental Type IIB strings, again on K3 surfaces. By contrast the analogous weak coupling limits of M-theory compactifications are found to correspond to an F-theory limit where an extra dimension emerges rather than tensionless strings. We comment on extensions of our findings to four-dimensional compactifications.

Ants Colony Optimization Algorithm in the Hopfield Neural Network for Agricultural Soil Fertility Reverse Analysis

The Boolean Satisfiability Problem (BSAT) is one of the most important decision problems in mathematical logic and computational sciences for determining whether or not a solution to a Boolean formula.. Hopfield neural network (HNN) is one of the major type artificial neural network (NN) popularly known for it used in solving various optimization and decision problems based on its energy minimization machinism. The existing models that incorporate standalone network projected non-versatile framework as fundamental Hopfield type of neural network (HNN) employs random search in its training stages and sometimes get trapped at local optimal solution. In this study, Ants Colony Optimzation Algorithm (ACO) as a novel variant of probabilistic metaheuristic algorithm (MA) inspired by the behavior of real Ants, has been incorporated in the training phase of Hopfield types of the neural network (HNN) to accelerate the training process for Random Boolean kSatisfiability reverse analysis (RANkSATRA) based for logic mining. The proposed hybrid model has been evaluated according to robustness and accuracy of the induced logic obtained based on the agricultural soil fertility data set (ASFDS). Based on the experimental simulation results, it reveals that the ACO can effectively work with the Hopfield type of neural network (HNN) for Random 3 Satisfiability Reverse Analysis with 87.5 % classification accuracy

Determinants of Malaysian Real Estate Investment Trusts (M-REITs) Risk-Adjusted Performance during the Period of Property Oversupply

After the remarkable property surge in the first half of 2010s decade (2010-2014), the Malaysian property market has then moved into a period of oversupply and price overhang, which pose more challenges for REIT managers. Unlike most previous research that mainly compared various risk-adjusted performance measures among REITs, this research looks into whether size of portfolio, fundamental performance measures (net property income and dividend yield) and types of property managed by REITs influence their risk-adjusted performance measure of Jensen alpha. Based on a sample of 16 Malaysian REITs over the period 2015-2017, regression results generally show that there is no significant relationship between any of these determinants and Jensen alpha. Furthermore, only one out of the 16 M-REITs has a positive Jensen alpha and outperforms the benchmark FTSE Bursa Malaysia Kuala Lumpur Composite Index. Investors who prefer a high and certain dividend yield can consider to invest in M-REITs that mainly focused in the hospitality sector. Based on the rankings of Jensen alpha, M-REIT fund managers can consider to diversify their property portfolios to include more retail and hospitality properties during the period of property oversupply.

Deriving Ranges of Optimal Estimated Transcript Expression due to Nonidentifiability.

Current expression quantification methods suffer from a fundamental but undercharacterized type of error: the most likely estimates for transcript abundances are not unique. This means multiple estimates of transcript abundances generate the observed RNA-seq reads with equal likelihood, and the underlying true expression cannot be determined. This is called nonidentifiability in probabilistic modeling. It is further exacerbated by incomplete reference transcriptomes where reads may be sequenced from unannotated transcripts. Graph quantification is a generalization to transcript quantification, accounting for the reference incompleteness by allowing exponentially many unannotated transcripts to express reads. We propose methods to calculate a “confidence range of expression” for each transcript, representing its possible abundance across equally optimal estimates for both quantification models. This range informs both whether a transcript has potential estimation error due to nonidentifiability and the extent of the error. Applying our methods to the Human Body Map data, we observe that 35%–50% of transcripts potentially suffer from inaccurate quantification caused by nonidentifiability. When comparing the expression between isoforms in one sample, we find that the degree of inaccuracy of 20%–47% transcripts can be so large that the ranking of expression between the transcript and other isoforms from the same gene cannot be determined. When comparing the expression of a transcript between two groups of RNA-seq samples in differential expression analysis, we observe that the majority of detected differentially expressed transcripts are reliable with a few exceptions after considering the ranges of the optimal expression estimates.