Miracle-dz/UniFAR-FTUs huggingface dataset:
Professionals, purpose-seekers, and passers-through: How microworkers reconcile alienation and platform commitment through identity work

Digital microwork consists of remote and highly decontextualized labor that is increasingly governed by algorithms. The anonymity and granularity of such work is likely to cause alienation among workers. To date, we know little about how workers reconcile such potential feelings of alienation with their simultaneous commitment to the platform. Based on a longitudinal survey of 460 workers on a large microworking platform and a combination of quantitative and qualitative analyses, we show that (1) alienation is present in digital microwork. However, our study also finds that (2) workers’ commitment to the platform over time may alter their subjective perceptions of alienation. Drawing from qualitative statements, we show (3) how workers perform identity work that might help reconcile feelings of alienation with simultaneous platform commitment. Our findings contribute to solving the paradox of worker commitment to precarious platform labor, which is an issue frequently raised in the digital labor literature.
A Comparative Study on Abstractive and Extractive Approaches in Summarization of European Legislation Documents

Extracting the most important part of legislation documents has great business value because the texts are usually very long and hard to understand. The aim of this article is to evaluate different algorithms for text summarization on EU legislation documents. The content contains domain-specific words. We collected a text summarization dataset of EU legal documents consisting of 1563 documents, in which the mean length of summaries is 424 words. Experiments were conducted with different algorithms using the new dataset. A simple extractive algorithm was selected as a baseline. Advanced extractive algorithms, which use encoders show better results than baseline. The best result measured by ROUGE scores was achieved by a fine-tuned abstractive T5 model, which was adapted to work with long texts.
The impact of semiconductor devices on electrical power engineering

The differences in approach between power engineering and electronic engineering are briefly outlined and the role of semiconductor devices in place of those based on the mercury-arc is discussed. Applications of the diode and thyristor to d.c. and a.c. machines are described together with the use of thyristors in high voltage d.c. power transmission. The importance of careful integration of semiconductor devices with the associated machines in any proposed scheme is emphasised.
Efficiency improved sensorless control scheme for electric vehicle induction motors

This study presents an energy efficient and speed-sensorless control scheme for electric vehicle induction motors (IMs). The IM drive is designed to feature characteristics such as fast dynamic response, high efficiency and low cost. Hybrid field orientation control (FOC) and direct torque control (DTC) is employed as the main control method of IM drive. This method enjoys the advantages of both FOC and DTC and eliminates certain disadvantages. A field weakening algorithm is developed and utilised within the control strategy to ensure robust operation at high speeds. The cost is lowered by eliminating the speed encoder and estimating the speed using an extended Kalman filter observer. Furthermore, a loss minimisation algorithm is associated with the main control strategy to ensure high IM drive efficiency. The effectiveness of the proposed method is verified through simulation and experimental results.
Clinically Relevant Genes and Proteins Modulated by Tocotrienols in Human Colon Cancer Cell Lines: Systematic Scoping Review

The last decade has witnessed tremendous growth in tocotrienols (T3s) research, especially in the field of oncology, owing to potent anticancer property. Among the many types of cancers, colorectal cancer (CRC) is growing to become a serious global health threat to humans. Chemoprevention strategies in recent days are open to exploring alternative interventions to inhibit or delay carcinogenesis, especially with the use of bioactive natural compounds, such as tocotrienols. This scoping review aims to distil the large bodies of literature from various databases to identify the genes and their encoded modulations by tocotrienols and to explicate important mechanisms via which T3s combat CRC. For this scoping review, research papers published from 2010 to early 2021 related to T3s and human CRC cells were reviewed in compliance with the PRISMA guidelines. The study included research articles published in English, searchable on four literature databases (Ovid MEDLINE, PubMed, Scopus, and Embase) that reported differential expression of genes and proteins in human CRC cell lines following exposure to T3s. A total of 12 articles that fulfilled the inclusion and exclusion criteria of the study were short-listed for data extraction and analysis. The results from the analysis of these 12 articles showed that T3s, especially its γ and δ analogues, modulated the expression of 16 genes and their encoded proteins that are associated with several important CRC pathways (apoptosis, transcriptional dysregulation in cancer, and cancer progression). Further studies and validation work are required to scrutinize the specific role of T3s on these genes and proteins and to propose the use of T3s to develop adjuvant or multi-targeted therapy for CRC.
The Effects of Implementing Clinical Supervision Model on Supervisors’ Teaching Perspectives and Qualifications: A Case Study in an EFL Context

This study set out to determine the possible impacts of implementing the Clinical Supervision Model (CSM) on supervisors’ philosophy of teaching, in both theory and practice. In order to gather the required data, two highly experienced supervisors were recruited according to the degree of homogeneity of the educational context in which they were working. By applying qualitative case study design, the required data were collected by conducting two distinct phases of classroom observations, accompanied by semistructured interviews. Considering the nature of the investigation, it was decided to employ the Transcendental Phenomenology (TPh) approach to analyze the data in order to determine the supervisors’ accurate perceptions and lived experiences regarding the nature of taking on a supervisory role and the effects of implementing CSM on their teaching career. The empirical findings in this investigation provided a new understanding of the probable effects of implementing CSM on supervisors’ general attitudes towards both teaching and supervisory careers. The results of the study indicated that CSM can be potentially effective in encouraging critical thinking, providing more constructive feedback in postobservation meetings, and improving the teaching quality of both teachers and supervisors.
Large-scale algorithmic search identifies stiff and sloppy dimensions in synaptic architectures consistent with murine neocortical wiring

Complex systems can be defined by “sloppy” dimensions, meaning that their behavior is unmodified by large changes to specific parameter combinations, and “stiff” dimensions whose change results in considerable behavioral modification. In the neocortex, sloppiness in synaptic architectures would be crucial to allow for the maintenance of asynchronous irregular spiking dynamics with low firing rates despite a diversity of inputs, states, and both short- and long-term plasticity. Using simulations on neural networks with first-order spiking statistics matched to firing in murine visual cortex while varying connectivity parameters, we determined the stiff and sloppy parameters of synaptic architectures across three classes of input (brief, continuous, and cyclical). Algorithmically-generated connectivity parameter values drawn from a large portion of the parameter space reveal that specific combinations of excitatory and inhibitory connectivity are stiff and that all other architectural details are sloppy. Stiff dimensions are consistent across input classes with self-sustaining synaptic architectures following brief input occupying a smaller subspace as compared to the other input classes. Experimentally estimated connectivity probabilities from mouse visual cortex are consistent with the connectivity correlations found and fall in the same region of the parameter space as architectures identified algorithmically. This suggests that simple statistical descriptions of spiking dynamics are a sufficient and parsimonious description of neocortical activity when examining structure-function relationships at the mesoscopic scale. Additionally, coarse graining cell types does not prevent the generation of accurate, informative, and interpretable models underlying simple spiking activity. This unbiased investigation provides further evidence of the importance of the interrelationship of excitatory and inhibitory connectivity to establish and maintain stable spiking dynamical regimes in the neocortex. Author Summary Connections between neurons are continuously changing to allow learning and adaptation to new stimuli. However, the ability of neural networks to vary these connections while avoiding excessively high- or low-activity states is still not well understood. We tackled this question by studying how changes in the parameters of connectivity within and between different neuronal populations impacted network activity in computational models. We identified specific combinations of parameters, deemed “stiff”, that must be maintained to observe activity consistent with recordings from murine visual cortex, while the rest of the parameters can be varied freely with minimal effects on activity. Our results agree with experimentally measured connectivity statistics demonstrating the importance of balancing opposing forces to maintain activity in a natural regime.
On Turing Machines Deciding According to the Shortest Computations

In this paper we propose and analyse from the computational complexity point of view several new variants of nondeterministic Turing machines. In the first such variant, a machine accepts a given input word if and only if one of its shortest possible computations on that word is accepting; on the other hand, the machine rejects the input word when all the shortest computations performed by the machine on that word are rejecting. We are able to show that the class of languages decided in polynomial time by such machines is PNP[log]. When we consider machines that decide a word according to the decision taken by the lexicographically first shortest computation, we obtain a new characterization of PNP. A series of other ways of deciding a language with respect to the shortest computations of a Turing machine are also discussed.
Left‐handed metamaterial structure incorporated with microstrip antenna

This article presents the design, simulation, and fabrication of a new planar left‐handed metamaterial (LHM), which consist of a combination of a modified square rectangular split ring resonator and strip wire. Both structures are on the same plane. The structure is simulated and measured with the microstrip antenna operating at frequency 5.8 GHz. The LHM has been analyzed using Nicolson–Ross–Weir approach to obtain the negative permeability and permittivity at 5.8 GHz. The fabrication of the LHM is on FR‐4 board substrate. From the simulation and measurement results, the gain of the microstrip antenna with LHM has increased by 4.0 dB. The return loss of the antenna with LHM is improved to 15.7 dB compare without LHM structure. © 2012 Wiley Periodicals, Inc. Microwave Opt Technol Lett 54:2828–2832, 2012; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.27186
Building Global Societies on Collective Intelligence: Challenges and Opportunities

Digital disruptions caused by the use of technologies like social media arguably present a formidable challenge to democratic values and in turn to collective intelligence. Challenges such as misinformation, partisan bias, polarization, and rising mistrust in institutions (including mainstream media) present a new constant threat to collectives both online and offline—amplifying the risk of turning ‘wise’ crowds ‘mad’ and rendering their actions counterproductive. Considering the increasingly important role crowds play in solving today’s socio-political, technological, and economical issues, and in shaping our future, it is vital to protect crowd-oriented systems against such disruptions. In this commentary, we identify time-critical challenges and potential solutions from emerging work on diversity, transparency, collective dynamics, and machine behavior that require urgent attention if future collective intelligence systems are to sustain their indispensable role as global deliberation instruments.
A programmable bispecific nano-immuno-engager promotes T cell homing and reprograms tumour microenvironment

Immune checkpoint blockade (ICB) therapy has revolutionized clinical oncology. However, the efficacy of ICB therapy is limited by the ineffective homing of T effector (Teff) cells to tumours and the immunosuppressive tumour microenvironment (TME). Here, we report a programmable tumour cells/Teff cells bispecific nano-immuno-engager (NIE) that can circumvent these limitations to improve ICB therapy. We have developed 28 nm non-toxic peptidic micellar nanoparticles (NIE-NPs) that bind α3β1 integrin on tumour cells membrane and undergo in situ transformation on surface of tumour cells into nanofibrillar network (NIE-NFs). The nanofibrillar network persistently facilitates cytotoxic T cells’ homing to the proximity of tumour cells via activatable α4β1 integrin ligands, and also allows sustained release of resiquimod to reprogram the TME. This bispecific NIE eliminates syngeneic 4T1 breast cancer and Lewis lung cancer models in mice, when given together with anti-PD-1 antibody. The in vivo structural transformation-based supramolecular bispecific NIE represents an innovative class of programmable receptor-mediated targeted immunotherapeutics to greatly enhance ICB therapy against cancers.
The Effects of Logo Shape, Logo Color, Typography and Service Quality Towards Brand Image on PT. Gojek Indonesia

This research aims to explain the influences of logo shape, logo color, typography and service quality towards brand image on PT. Gojek Indonesia. There are four independent variables, those are logo shape. Logo color, typography and service quality that researcher wanted to know how much those variables influence on the image of Gojek as a dependent variable. This research used a non-probability sampling technique with a purposive sampling method. The population of the research as a media. The samples in this research were 115 respondents. This research examines the hypothesis by using Statistical Package for Social Sciences (SPSS). The results of this study indicate that typography and service quality have a positive and significant effect on brand image. Meanwhile, logo shape and logo color does not have a significant effect on brand image. Service quality as a dominant variables that influence the brand image.
Uncertain Bayesian Networks: Learning from Incomplete Data

When the historical data are limited, the conditional probabilities associated with the nodes of Bayesian networks are uncertain and can be empirically estimated. Second order estimation methods provide a framework for both estimating the probabilities and quantifying the uncertainty in these estimates. We refer to these cases as uncertain or second-order Bayesian networks. When such data are complete, i.e., all variable values are observed for each instantiation, the conditional probabilities are known to be Dirichlet-distributed. This paper improves the current state-of-the-art approaches for handling uncertain Bayesian networks by enabling them to learn distributions for their parameters, i.e., conditional probabilities, with incomplete data. We extensively evaluate various methods to learn the posterior of the parameters through the desired and empirically derived strength of confidence bounds for various queries.
E7-Targeted Nanotherapeutics for Key HPV Afflicted Cervical Lesions by Employing CRISPR/Cas9 and Poly (Beta-Amino Ester)

Introduction Persistent HR-HPV (high-risk human papillomavirus) infection is the main cause of cervical cancer. The HPV oncogene E7 plays a key role in HPV tumorigenesis. At present, HPV preventive vaccines are not effective for patients who already have a cervical disease, and implementation of the recommended regular cervical screening is difficult in countries and regions lacking medical resources. Therefore, patients need medications to treat existing HPV infections and thus block the progression of cervical disease. Methods In this study, we developed nanoparticles (NPs) composed of the non-viral vector PBAE546 and a CRISPR/Cas9 recombinant plasmid targeting HPV16 E7 as a vaginal treatment for HPV infection and related cervical malignancies. Results Our NPs showed low toxicity and high biological safety both in vitro (cell line viability) and in vivo (various important organs of mice). Our NPs significantly inhibited the growth of xenograft tumors derived from cervical cancer cell lines in nude mice and significantly reversed the cervical epithelial malignant phenotype of HPV16 transgenic mice. Conclusion Our NPs have great potential to be developed as a drug for the treatment of HPV-related cervical cancer and precancerous lesions.
Voltage-mode multifunction biquadratic filter employing single DVCC

A new voltage-mode single-input and four-output multifunction biquadratic filter using single differential voltage current conveyor, three capacitors and two resistors is presented. According to the values of the passive components used, the highpass, bandpass, lowpass and notch filters can be simultaneously obtained from the first circuit configuration. Moreover, the allpass, highpass and bandpass filters can be simultaneously obtained from the second circuit configuration. H-Simulation program with integrated circuit emphasis (HSPICE) simulations using Taiwan Semiconductor Manufacturing Company, Ltd. (TSMC) 0.18 µm level 49 complementary metal oxide semiconductor (CMOS) technology process parameters are given to validate theoretical predictions.
Series elastic actuators for high fidelity force control

Series elastic actuators provide many benefits in force control of robots in unconstrained environments. These benefits include high force fidelity, extremely low impedance, low friction, and good force control bandwidth. Series elastic actuators employ a novel mechanical design architecture which goes against the common machine design principal of “stiffer is better”. A compliant element is placed between the gear train and driven load to intentionally reduce the stiffness of the actuator. A position sensor measures the deflection, and the force output is accurately calculated using Hooke’s Law (F = Kx). A control loop then servos the actuator to the desired output force. The resulting actuator has inherent shock tolerance, high force fidelity and extremely low impedance. These characteristics are desirable in many applications including legged robots, exoskeletons for human performance amplification, robotic arms, haptic interfaces, and adaptive suspensions.
Evaluation of GaN technology in power amplifier design

In this contribution the features of GaN technology for power applications will be explored from the designer point of view. Therefore, the active device will be studied as a black box using its simplified model and putting in evidence the role of its key parameters such as the knee voltage, the breakdown voltage, etc. At the end, the experimental results of several power amplifiers designed using different strategies will be presented to highlight both, the capabilities and/or drawbacks of such material. © 2008 Wiley Periodicals, Inc. Microwave Opt Technol Lett 51: 42–44, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.23958
Chronic Autoimmune Gastritis: Modern Diagnostic Principles

This article summarizes and systematizes the available data from the literature on chronic autoimmune gastritis (CAG) in order to increase the awareness of specialists about the modern possibilities for diagnosing the disease, including its early stages. The clinical manifestation of the disease includes possible variants such as gastrointestinal, hematological (first of all, the formation of iron deficiency and B12-deficiency anemia), and neurological variants. Patients with chronic autoimmune gastritis are characterized by comorbidity with other autoimmune diseases. In this paper, data on the most informative serological markers for the diagnosis of CAG, as well as laboratory tests to detect micronutrient deficiencies, information on the characteristic changes in the gastric mucosa, and the prognosis of the disease, are presented. The diagnosis of CAG should be based on a multidisciplinary approach that combines a thorough analysis of a patient’s complaints with a mandatory assessment of nutritional status, as well as the results of serological, endoscopic, and histological research methods.
Divorce after breast cancer diagnosis and its impact on quality of life

Abstract Objective This study aims to identify factors associated with divorce following breast cancer diagnosis and measures the impact of divorce on the quality of life (QoL) of patients. Methods We used cross-sectional survey data collected at breast cancer outpatient clinics in South Korea from November 2018 to April 2019. Adult breast cancer survivors who completed active treatment without any cancer recurrence at the time of the survey (N = 4,366) were included. The participants were classified into two groups: “maintaining marriage” and “being divorced,” between at the survey and at the cancer diagnosis. We performed logistic regression and linear regression to identify the factors associated with divorce after cancer diagnosis and to compare the QoL of divorced and nondivorced survivors. Results Approximately 11.1/1,000 of married breast cancer survivors experienced divorce after cancer diagnosis. Younger age, lower education, and being employed at diagnosis were associated with divorce. Being divorced survivors had significantly lower QoL (Coefficient [Coef] = −7.50; 95% CI = −13.63, −1.36), social functioning (Coef = −9.47; 95% CI = −16.36, −2.57), and body image (Coef = −8.34; 95% CI = −6.29, −0.39) than survivors who remained married. They also experienced more symptoms including pain, insomnia, financial difficulties, and distress due to hair loss. Conclusion Identifying risk factors of divorce will ultimately help ascertain the resources necessary for early intervention.