Miracle-dz/UniFAR-FTUs huggingface dataset:
Affective Politics and Algorithms in the Neoliberal Social Media Landscape

Does social media threaten democracy? Is social media killing democracy? Are social media algorithms bad for democracy? Such questions have appeared in the titles and headlines of many journalistic and scholarly essays. In the last several years, social media, and their algorithms in particular, have indeed been blamed for weakening democracy, including facilitating the victory of Trump in the United States (Grassegger & Krogerus, 2017; Rosenberg, Confessore, & Cadwalladr, 2018) and the Brexit campaign in the United Kingdom (Scott, 2018). Some media observers believe that by their exploitation of access to big personal data and manipulation of the algorithms (Dalli, 2018; Saunders, 2018; Summers, 2018), social media platforms have created “a global crisis of democracy” (Ferguson, 2018, para. 14). Undeniably, social media platforms have become embedded in everyday practices of communication, community making, and information sharing in various topics; politics is not an exception. Social media algorithms, as the engine of sorting and filtering information, are indeed central to these practices. However, social media algorithms (and algorithms in general) should not be depicted as a modern myth—powerful entities that “rule the world” (Hickman, 2013) by sorting, governing, shaping, and even controlling our everyday lives. Certainly, scholarly debates on the role of social media algorithms in politics paint more shades than this oversimplified depiction; most accept that within the social media landscape there is an ongoing pull-and-push dynamic between technological constraints and individual choices and decisions. Recent studies on the relationship between politics and social media reflect an algorithmic turn, namely a paradigm shift that occurred in the early 2010s as social science and humanities scholars turned their attention to (roles and implications of) algorithms as a means to understand social processes. These studies largely revolve cited as: Lim, M. (2020). Algorithmic enclaves: Affective politics and algorithms in the neoliberal social media landscape. In M. Boler & E. Davis (eds.), Affective Politics of Digital Media: Propaganda by Other Means (pp. 186-203). New York & London: Routledge.
Analysis and design of a three-level PWM converter system for railway-traction applications

The paper analyses the merits and demerits of three-level PWM converters through the comparison with two-level PWM converters. A general method for analysing the switching modes of PWM converters is described and an analysis of the three-level PWM converter is presented as an example. A neutral-point voltage-balance-control algorithm together with its hardware and software implementation is presented. A three-step methodology of rapid prototyping by using CAD for the system design, using a real-time simulator for checking the implementation and using high-power testing for validating the system, is described.
Chronic Venous Leg Ulcer in Klinefelter Syndrome Treated with Platelet-Rich Fibrin: A Case Report

Abstract Venous leg ulcers (VLUs) are the most common causes of leg ulcers due to venous insufficiency. Most cases persist for more than 6 weeks, referred to as chronic VLUs. These chronic ulcers have been described as a manifestation of Klinefelter syndrome (KS). Platelet-rich fibrin (PRF) is a second-generation platelet concentrate, which contains growth factors required for chronic wound healing. The use of PRF in the management of VLUs in KS has not been reported, to the best of our knowledge. We report a case of chronic VLU associated with KS in a 41-year-old man treated with PRF. Dermatological examination showed a tender, shallow, irregular ulcer partly covered with hard, yellow necrotic tissue on the anterior side of the lower-left leg and hyperpigmented indurated skin on both lower legs. The diagnosis of venous ulcer was established based on clinical manifestation and supported by the result of Doppler ultrasound showed chronic venous insufficiency. Histopathological examination, which showed epidermal acanthosis, dermal fibrosis, and thickening with hemosiderin deposits consistent with the diagnosis of venous ulcer. The patient presented with eunuchoid features characterized by long extremities, gynecomastia, increased fat distribution around the hips, scanty pubic hairs, and small testes. Laboratory tests found decreased levels of testosterone, increased levels of follicle-stimulating and luteinizing hormone, and bilateral testicular atrophy was found from testicular ultrasound. These physical examinations and laboratory findings supported the diagnosis of KS. The patient was treated with PRF dressing once a week. After 7 weeks of treatment with PRF, the ulcer almost reached complete closure. PRF gives a good result in a chronic VLU with KS.
Design of Electric Vehicle Energy Regenerative Braking System Based on Super Capacitor

The necessity of the electric vehicle using energy regenerative braking system is described in this paper. Then the design process of the braking system with the super capacitor was discussed and the determination method and the control mode of the main technical parameters was analyzed. Using the system the electric automobile can realize regenerative braking in any common condition especially when the conventional regenerative braking can not be achieved. Under these circumstances the electric energy which is generated by braking process and stored in the super capacitor can output to the traction inverter DC link when the automobile is in the traction mode . So it is a good way to significantly reduce the electric vehicle energy consumption.
Element placement in thinned arrays using genetic algorithms

Optimization techniques based on natural evolutionary processes, known as genetic algorithms, are applied to the problem of element placement in a discrete linear lattice, which is combinatorial in nature and cannot be analytically optimized. Representation of potential array occupancy patterns as binary vectors allows iterative utilization of numerical models of differential reproduction, crossover and mutation to converge on near-optimal solutions. Results are presented for the placement of 31 elements within a linear lattice of 63 locations under the design constraints of center and end position occupancy and bilateral symmetry. "Fitness" of the configuration is given in terms of mainlobe width and sidelobe levels of the corresponding response pattern. When results of multiple optimization runs are compared with expectations of random search, genetic algorithms show greater efficiency, especially when increasingly rarer solutions are sought. <<ETX>>
The miR-200 Family of microRNAs: Fine Tuners of Epithelial-Mesenchymal Transition and Circulating Cancer Biomarkers

Simple Summary MicroRNAs (miRNAs) are small RNA molecules that regulate gene expression by blocking translation or inducing degradation of specific gene transcripts. The miR-200 family controls the expression of many genes that play important roles in cancer cells. One of the main pathways controlled by these miRNAs, termed epithelial-mesenchymal transition (EMT), is an essential component of the invasive growth program of solid tumors. The miR-200 family has thus been the focus of many studies aimed at discovering strategies to block cancer cell growth and disease progression. In addition, the miR-200 family miRNAs have been investigated as possible circulating cancer biomarkers. Here we provide an overview of factors that influence miR-200 family expression and target genes relevant to tumor development, followed by a summary of their potential utility as noninvasive biomarkers for selected cancers. Abstract The miR-200 family of microRNAs (miRNAs) includes miR-200a, miR-200b, miR-200c, miR-141 and miR-429, five evolutionarily conserved miRNAs that are encoded in two clusters of hairpin precursors located on human chromosome 1 (miR-200b, miR-200a and miR-429) and chromosome 12 (miR-200c and miR-141). The mature -3p products of the precursors are abundantly expressed in epithelial cells, where they contribute to maintaining the epithelial phenotype by repressing expression of factors that favor the process of epithelial-to-mesenchymal transition (EMT), a key hallmark of oncogenic transformation. Extensive studies of the expression and interactions of these miRNAs with cell signaling pathways indicate that they can exert both tumor suppressor- and pro-metastatic functions, and may serve as biomarkers of epithelial cancers. This review provides a summary of the role of miR-200 family members in EMT, factors that regulate their expression, and important targets for miR-200-mediated repression that are involved in EMT. The second part of the review discusses the potential utility of circulating miR-200 family members as diagnostic/prognostic biomarkers for breast, colorectal, lung, ovarian, prostate and bladder cancers.
Dopamine, Cognitive Flexibility, and IQ: Epistatic Catechol-O-MethylTransferase:DRD2 Gene–Gene Interactions Modulate Mental Rigidity

Abstract Cognitive flexibility has been hypothesized to be neurochemically rooted in dopamine neurotransmission. Nonetheless, underpowered sample sizes and contradictory meta-analytic findings have obscured the role of dopamine genes in cognitive flexibility and neglected potential gene–gene interactions. In this largest neurocognitive-genetic study to date (n = 1400), single nucleotide polymorphisms associated with elevated prefrontal dopamine levels (catechol-O-methyltransferase; rs4680) and diminished striatal dopamine (C957T; rs6277) were both implicated in Wisconsin Card Sorting Test performance. Crucially, however, these genetic effects were only evident in low-IQ participants, suggesting high intelligence compensates for, and eliminates, the effect of dispositional dopamine functioning on flexibility. This interaction between cognitive systems may explain and resolve previous empirical inconsistencies in highly educated participant samples. Moreover, compensatory gene–gene interactions were discovered between catechol-O-methyltransferase and DRD2, such that genotypes conferring either elevated prefrontal dopamine or diminished striatal dopamine—via heightened striatally concentrated D2 dopamine receptor availability—are sufficient for cognitive flexibility, but neither is necessary. The study has therefore revealed a form of epistatic redundancy or substitutability among dopamine systems in shaping adaptable thought and action, thus defining boundary conditions for dopaminergic effects on flexible behavior. These results inform theories of clinical disorders and psychopharmacological interventions and uncover complex fronto-striatal synergies in human flexible cognition.
Internal inductance and conductor loss associated with the ground plane of a microstrip line

In previous work, a closed-form expression for the current density on the ground plane of a microstrip line was presented. In this paper, we show how this formula for the current density is used to derive an expression for the internal inductance associated with the ground plane. Results are presented for different geometries that illustrate when the internal inductance of the ground becomes comparable to the external inductance of the microstrip line. We also illustrate that the integrals needed for the internal inductance calculation can be used to develop an expression for the conductor loss associated with the ground plane.
Heat sink design of high power converter

In this paper, heat sink design for a high power converter is presented. There are many ways of designing heat sinks, but air cooling is by far the most used and much more practical than any of the other methods. In this paper, the practical methods of cooling which include a method to reduce noise and vibration due to a fan, and the method to design a gap resistance and contact resistance due to mounting force between thyristor and heat sink, are proposed. Finally, simulation and experimental results are describe to verify validity of the proposed method.
Dynamics of inter‐organizational knowledge creation and information technology use across object worlds: the case of an innovative construction project

Organizational research argues that under relational forms of governance a high degree of both information pooling and physical interaction are necessary for inter‐organizational knowledge creation. Yet, recent studies of information and communication technologies (ICTs) suggest that both practices at the same time are sometimes unnecessary. We address this discrepancy by developing a framework whereby the intensity and proportion of these inter‐organizational practices are affected by the object world congruence between designers within and across partnering firms, and the level to which a common information technology platform is embedded in their activity. Through a multi‐level case study of a Frank Gehry construction project we illustrate how designers with highly congruent object worlds, due to a strongly embedded common information technology platform, could jointly create knowledge despite decreased physical interaction. Conversely, designers from firms with incongruent object worlds or with congruent object worlds lacking a strongly embedded common ICT platform demanded a higher degree of physical interaction for effective knowledge creation. Our research suggests a dynamic, evolutionary model of inter‐organizational knowledge creation influenced by variation in object world congruence and the levels of embedding a common ICT platform.
Spatio-Temporal Reconstruction and Visualization of Plant Growth for Phenotyping

Recently, there has been increasing interest in applying spatio-temporal registration for phenotyping of both individual and groups of plants in large agricultural fields. However, 3D non-rigid methods for registration are still a research topic and present numerous particular challenges in plant phenotyping due to: overlaps and self-occlusions in dense phyllotaxies; deformations caused by plant growth over time; changes in outdoor environmental settings, etc. In this paper, we address the problem of registering spatio-temporal 3D models of plants by proposing a bundle registration approach that can handle transformations with up to three additional Degrees of Freedom (DoF) to capture the growth of the plant. Besides, we offer to the research community a new multi-view stereo dataset consisting of 2D images and 3D point clouds of an African violet plant observed over a period of ten days. We evaluate the proposed algorithm on the new African violet dataset using the usual 6 DoF (three rotations and three translations) and compared it with 7 DoF (three rotations, three translations, and one scale) and 9 (three rotations, three translations, and three scales). We also performed the comparison between the proposed approach and two other registration approaches: pairwise and incremental. We show that the proposed algorithm achieves an average registration error of less than 2 mm on the African violet dataset. Also, we used VisND, an N-dimensional spatio-temporal visualization tool, to perform a visual assessment of the aligned time-varying 3D models of the plants.
Salt and Water Stress Responses in Plants

Climate change-driven ecological disturbances have a great impact on freshwater availability which hampers agricultural production. Currently, drought and salinity are the two major abiotic stress factors responsible for the reduction of crop yields worldwide. Increasing soil salt concentration decreases plant water uptake leading to an apparent water limitation and later to the accumulation of toxic ions in various plant organs which negatively affect plant growth. Plants are autotrophic organisms that function with simple inorganic molecules, but the underlying pathways of defense mechanisms are much more complex and harder to unravel. However, the most promising strategy to achieve sustainable agriculture and to meet the future global food demand, is the enhancement of crop stress tolerance through traditional breeding techniques and genetic engineering. Therefore, it is very important to better understand the tolerance mechanisms of the plants, including signaling pathways, biochemical and physiological responses. Although, these mechanisms are based on a well-defined set of basic responses, they can vary among different plant species.
Control performance of autonomous underwater vehicle "AQUA EXPLORER 1000" for inspection of underwater cables

The paper deals with analysis of control performance of an autonomous underwater vehicle named AQUA EXPLORER 1000 (AE1000) for inspection of underwater telecommunication cables up to 1000 m depth, reviewing results of sea trials in autonomous tracking. The control performance of the cable tracking at 40 m water depth, consisting of descent from the surface, cable searching, cable tracking and ascent to the surface, is discussed based on the measured data. Next, the performance of spiral motion control in a limited area from the mother ship, which is an important operation for the AE1000 not to be lost during descent and ascent, is discussed by showing test results. Finally, the performance of the fuzzy controller for cable tracking control in tidal currents is discussed by use of numerical simulation. <<ETX>>
Focusing As Commitment

The paper analyzes the decisions of a β − δ consumer who has the ability, through effort invested in focusing on the future, to set the exponential discount factor δ that will apply to her self in the next period. She has access to no other commitment technology. Because the model interprets dynamic inconsistency in a way that gives rise to the demand for costly self-control, it disambiguates the welfare benefit of formal commitment devices that limit future options. The model explains why cognitive loading is associated with impulsivity and why U.S. savings rates have exhibited increased income stratification since the 1980s. The model additionally offers a unifying theory of visionary leadership, managerial training, motivational speakers, and role models.
Technical Demand Analysis of Judicial Big Data Application under Risky Driving Behavior of Drivers

According to the rapid development of the global economy and the continuous improvement of people's living standards, more and more people have a car driving license. We must pay attention to standardize the driving behavior of drivers, which is important to ensure personal safety. The survey also found that more than half of traffic accidents are related to dangerous driving behavior. However, in judicial judgment, there are many problems in judicial application which can not be solved because of the abstract provisions of laws in various countries. If the method of big data can be used as a reference for determining risky driving behaviors of drivers, it can provide evidence for identification, improve the accuracy of judicial judgment, and timely avoid some accidents. This paper aims to explore what application technical support is needed by judicial big data in determining risky driving behaviors of drivers.
Guided-wave tomographic imaging of defects in pipe using a probabilistic reconstruction algorithm

There has been much interest recently in monitoring the structural integrity of predetermined critical zones in pipeline using leave-in-place sensors. Ultrasonic guided waves have significant advantages over vibration and impedance methods for structural health monitoring. With guided waves it is possible to locate and size defect regions. The work presented here introduces a Reconstruction Algorithm for the Probabilistic Inspection of Damage (RAPID), which is used to construct tomographic images of multiple defects in a 16"-diameter schedule 30 steel pipe. Imaging is completed using an array of 16 low-cost transducers. It is shown that defect location and severity are accurately predicted by employing the RAPID algorithm with multifrequency data sets. A sparse array study is completed in which images are reconstructed using only eight of the 16 available transducers. It is found that damage can still be detected using the sparse array, though defect sizing and location accuracy suffer. It is shown that multiple defects can still be resolved using 13 of the original 16 transducers chosen at random.
-doped CsPbI3 Nanocrystals

α-CsPbI3 nanocrystals (NCs) with poor stability prevent their wide applications in optoelectronic fields. Ca 2+ (1.00 Å) as a new B-site doping ion can successfully boost CsPbI3 NCs performance with both improved phase stability and optoelectronic properties. With a Ca 2+ /Pb 2+ ratio of 0.40%, both phase and photoluminescence (PL) stability could be greatly enhanced. Facilitated by increased tolerance factor, the cubic phase of its solid film could be maintained after 58 days in ambient condition or 4-h accelerated aging process at 120 o C. The PL stability of its solution could be preserved to 83% after 147 days in ambient condition. Even using UV light to accelerate aging, the T50 of PL could boost 1.8 fold as compared to CsPbI3 NCs. Because Ca 2+ doping can dramatically decrease defect densities of films and reduce hole injection barriers, the red light-emitting diodes (LED) exhibited about triple 2 enhancement for maximum the external quantum efficiency (EQE) up to 7.8%, and 2.2 times enhancement for half-lifetime of LED up to 85 min. We believe it is promising to further explore high-quality CsPbI3 NCs LED via Ca 2+ doping strategy.
SIMULASI PENGENALAN KARAKTER MENGGUNAKAN NEURAL NETWORK

At present almost all aspects of life have been done by computerization. One of them is how a computer system can recognize or read certain characters from a digital image. For example, how a computer can recognize someone's face or determine someone's handwriting, diagnose a disease and others. Pattern recognition is one of the branches of computer science which can be interpreted as collecting raw data to be classified with specific intentions. This pattern recognition is conceptually driven processing which means that the process starts from the formation of concepts on objects encountered (information from memory)
Recent Developments on Social Robots and Imitation Learning for Robotic Therapy

The development of social robots has been notably increasing and gaining popularity in recent times. These are also being integrated into healthcare systems, as a means to accompany patients, provide mental health therapy, and entertainment in place of direct human intervention. This paper discusses the recent developments on imitation learning for robot therapy in the field of social robotics to gain knowledge about the importance of this approach as an alternative solution to mental health therapy. The integration of robots to the mental healthcare system is known as robot therapy, which is used as a substitute for animal assisted therapy. Therapy that makes use of animals has been proven to be effective in dealing with mental disorders. However, there are risks such as allergic reactions, bites, and scratches that come with animal assisted therapy, but not robot therapy. The goal for developing robots for this is to make them seem almost life-like--has a way of thinking and emotions. For this to happen, humanoids are being programmed to appear human-like. A solution for this is imitation learning, which is a way for machines to learn, not only tasks, but responses in certain situations, only by observing and imitating humans in an environment.