Miracle-dz/UniFAR-FTUs huggingface dataset:
It's Out of Our Hands Now! Effects of Non-Driving Related Tasks During Highly Automated Driving on Drivers' Fatigue

With introduction of conditional automation in vehicles the driver can engage in non-driving related tasks (NDRTs) and only has to intervene in case of take-over requests (TOR). Therefore, active fatigue, which is the most frequent form of fatigue in manual driving, is assumed to be replaced by passive fatigue, intensified through monotony and monitoring tasks in conditional automated driving (CAD), SAE Level 3. To investigate effects of NDRTs on drivers’ fatigue and take over capability a driving simulator study was conducted. In total, 56 participants experienced two rides on a highway with CAD. During the two rides, participants had to fulfill both a monotonous monitoring task and an activating task. As in CAD the system is executing longitudinal and lateral control, drowsiness detection referring to driving performance becomes inoperative. Noninvasive methods for drowsiness detection that are not related to driving performance have to be investigated. Therefore, fatigue was measured with percentage of eye-lid closure (PERCLOS), blink related eye-tracking parameters, and the self-report Karolinska Sleepiness Scale (KSS). Results suggest that fatigue can be caused through a monitoring task in highly automated driving. PERCLOS could be confirmed as a valid parameter for detecting fatigue in CAD. Further, passive task related fatigue caused by a 25 min monotonous monitoring task does not affect the drivers’ take over capability negatively.
Data-Efficient Learning of Feedback Policies from Image Pixels using Deep Dynamical Models

Data-efficient reinforcement learning (RL) in continuous state-action spaces using very high-dimensional observations remains a key challenge in developing fully autonomous systems. We consider a particularly important instance of this challenge, the pixels-to-torques problem, where an RL agent learns a closed-loop control policy ("torques") from pixel information only. We introduce a data-efficient, model-based reinforcement learning algorithm that learns such a closed-loop policy directly from pixel information. The key ingredient is a deep dynamical model for learning a low-dimensional feature embedding of images jointly with a predictive model in this low-dimensional feature space. Joint learning is crucial for long-term predictions, which lie at the core of the adaptive nonlinear model predictive control strategy that we use for closed-loop control. Compared to state-of-the-art RL methods for continuous states and actions, our approach learns quickly, scales to high-dimensional state spaces, is lightweight and an important step toward fully autonomous end-to-end learning from pixels to torques.
Neuro-fuzzy classifier for fault detection and classification in photovoltaic module

The reliability increase of a photovoltaic (PV) module, thus PV systems, passes through an efficient diagnosis process. This can be achieved by the use of two main techniques such as fault detection and fault classification. Identifying faults by using classification algorithms gives us a better knowledge about a fault nature. However, faults may have the same numeric signature by using conventional methods that consider only a presence or absence of symptoms or residues. This paper proposes a fault detection and classification algorithm using a neuro-fuzzy classifier. The faults being in concerns are relating to series losses, defect by-pass diode and blocking diode faults. The fault diagnosis based parameters are maximum power and, opencircuit voltage deviations, that are used as defect PV system symptoms. The method has been found proficient for fault detection and shows good discrimination for the most frequently occurring PV module faults.
[The impact of socioeconomic and sociodemographic factors on the criminal behavior of patients with a psychotic disorder].

INTRODUCTION The impact of socioeconomic and demographic factors on the criminal behavior of patients with a psychotic disorder was evaluated. METHOD The study included 70 psychotic men hospitalized in the forensic psychiatry unit of the Bakirköy State Hospital for Psychiatric and Neurological Diseases for compulsory treatment who were compared to 70 psychotic disorder cases with no criminal history hospitalized in the acute wards in the same hospital. Socioeconomic and sociodemographic data were collected and statistical evaluations were made. RESULTS The vast majority of all the patients (90.7%) in both groups were diagnosed with schizophrenia. The forensic group was significantly less educated than the control group (7.99+/-3.81 years vs. 9.37+/-3.62 years, P<0.05). More than 50% of the cases in both groups were never married ; when considering divorced and widowed patients together with these unmarried patients, the percentage rose to 83%. Fewer forensic cases lived in urban areas than did control cases (50% vs. 84.3%). Logistic regression analysis highlighted a relationship between unemployment and the lack of social insurance to the criminal behaviour of the forensic group. Of those in the forensic group, 48.6% had no social insurance, whereas only 15.7% of the control group had none. CONCLUSION The data suggested that unemployment and the lack of social insurance are 2 independent variables that may contribute to the probability that patients with a psychotic disorder will engage in criminal behavior.
Using Ion Electron Emission Microscopy to Study Current Spikes in NAND Flash Memories

Today Flash memories are attractive for space applications, due to their non-volatility, large capacity, low cost, and small power consumption [1]. Ionizing radiation effects should be carefully addressed before using them in space [1]. Although a huge amount of work has been performed in the past, there are still open issues concerning single events and total dose response of these devices. Single event effects are becoming more and more widespread and complex, due to charge reduction in the floating gate and the increasing complexity of the control circuitry. Anomalous spikes in the supply current during heavy-ion exposure and seemingly correlated destructive events have been recently observed [2,3]. In this work, we investigate supply current spikes using first heavy-ion beams and then the ion electron emission microscopy technique [4]. By correlating the spike events with the ion impact locations, reconstructed with micrometer accuracy, this technique allows us to pinpoint positional information on the device response.
The Science of Psychology

The is the first English publication of Vygotsky's work of 1926-27 that was composed at the time of, or, more likely, immediately after the completion of his work on the unfinished manuscript "The Historical Meaning of the Crisis in Psychology. " Unlike the latter manuscript, this work was finalized, prepared for publication by its author, and published in 1928. In a certain sense, this publication can be regarded as a shortened and yet comprehensive exposition of the main points of his unpublished manuscript on the crisis in psychology.
Two modes of polyamine block regulating the cardiac inward rectifier K+ current IK1 as revealed by a study of the Kir2.1 channel expressed in a human cell line

The strong inward rectifier K+ current, IK1, shows significant outward current amplitude in the voltage range near the reversal potential and thereby causes rapid repolarization at the final phase of cardiac action potentials. However, the mechanism that generates the outward IK1 is not well understood. We recorded currents from the inside‐out patches of HEK 293T cells that express the strong inward rectifier K+ channel Kir2.1 and studied the blockage of the currents caused by cytoplasmic polyamines, namely, spermine and spermidine. The outward current–voltage (I–V) relationships of Kir2.1, obtained with 5–10μm spermine or 10–100μm spermidine, were similar to the steady‐state outward I–V relationship of IK1, showing a peak at a level that is ∼20mV more positive than the reversal potential, with a negative slope at more positive voltages. The relationships exhibited a plateau or a double‐hump shape with 1μm spermine/spermidine or 0.1μm spermine, respectively. In the chord conductance–voltage relationships, there were extra conductances in the positive voltage range, which could not be described by the Boltzmann relations fitting the major part of the relationships. The extra conductances, which generated most of the outward currents in the presence of 5–10μm spermine or 10–100μm spermidine, were quantitatively explained by a model that considered two populations of Kir2.1 channels, which were blocked by polyamines in either a high‐affinity mode (Mode 1 channel) or a low‐affinity mode (Mode 2 channel). Analysis of the inward tail currents following test pulses indicated that the relief from the spermine block of Kir2.1 consisted of an exponential component and a virtually instantaneous component. The fractions of the two components nearly agreed with the fractions of the blockages in Mode 1 and Mode 2 calculated by the model. The estimated proportion of Mode 1 channels to total channels was 0.9 with 0.1–10μm spermine, 0.75 with 1–100μm spermidine, and between 0.75 and 0.9 when spermine and spermidine coexisted. An interaction of spermine/spermidine with the channel at an intracellular site appeared to modify the equilibrium of the two conformational channel states that allow different modes of blockage. Our results suggest that the outward IK1 is primarily generated by channels with lower affinities for polyamines. Polyamines may regulate the amplitude of the outward IK1, not only by blocking the channels but also by modifying the proportion of channels that show different sensitivities to the polyamine block.
Simulation of Social Behaviors in Virtual Crowd

This paper presents a novel communication model to simulate various crowd behaviors such as riot. Our communication model is heavily based on the results from sociology research. Collective behaviors can emerge out of social processes such as emotion contagion and conformity effect among individual agents. The communication model has been implemented in our crowd simulation system, IMCrowd, in which each agent has a local perception and autonomous abilities to improvise their actions. Simulations on riot formation and riot control are demonstrated as an application example of IMCrowd.
Automatic collimation in peripheral X-ray imaging

A method has been developed using which the foreground (body) in a fluoroscopy image of the peripherals can be segmented from the background (existing collimation and direct exposure). The extracted information about where the body is in an image is used to suggest settings for the collimator hardware during image acquisition. Segmentation is achieved through global feature extraction and supervised classification.
Raindrop Size Distributions and Rain Characteristics in California Coastal Rainfall for Periods with and without a Radar Bright Band

Abstract Recent studies using vertically pointing S-band profiling radars showed that coastal winter storms in California and Oregon frequently do not display a melting-layer radar bright band and inferred that these nonbrightband (NBB) periods are characterized by raindrop size spectra that differ markedly from those of brightband (BB) periods. Two coastal sites in northern California were revisited in the winter of 2003/04 in this study, which extends the earlier work by augmenting the profiling radar observations with collocated raindrop disdrometers to measure drop size distributions (DSD) at the surface. The disdrometer observations are analyzed for more than 320 h of nonconvective rainfall. The new measurements confirm the earlier inferences that NBB rainfall periods are characterized by greater concentrations of small drops and smaller concentrations of large drops than BB periods. Compared with their BB counterparts, NBB periods had mean values that were 40% smaller for mean-volume diameter, 32% s.
Race and Sex Differences in the Receipt of Timely and Appropriate Lung Cancer Treatment

Background:Previous research suggests that disparities in non–small-cell lung cancer (NSCLC) survival can be explained in part by disparities in the receipt of cancer treatment. Few studies, however, have considered race and sex disparities in the timing and appropriateness of treatment across stages of diagnosis. Objective:To evaluate the relationship of sex and race with the receipt of timely and clinically appropriate NSCLC treatment for each stage of diagnosis. Method:Surveillance Epidemiology and End Result data linked to Medicare claims for beneficiaries diagnosed with NSCLC between 1995 and 1999 were used to evaluate the relationship between race and sex with timely and appropriate NSCLC treatment while controlling for other demographic characteristics, comorbidities, socioeconomic status, and provider supply (N = 22,145). Results:Overall adjusted rates of timely and appropriate treatment are 37.2%, 58.1%, and 29.2% for Medicare beneficiaries diagnosed with stage I or II, III, and IV NSCLC, respectively. Among stage I or II patients, women were 25% less likely to receive timely surgical resection relative to men, and blacks were 66% less likely to receive timely and appropriate treatment than whites. Black men were least likely to receive resection (22.2% compared with 43.7% for white men). Blacks were 34% less likely to receive timely surgery, chemotherapy, or radiation for stage III disease and were 51% less likely to receive chemotherapy in a timely fashion for stage IV disease relative to whites. Conclusion:Significant variations in appropriate timely treatment were found within and across stages of diagnosis, confirming that sex and race differences in NSCLC treatment exist.
Combinatorial optimization in DNA mapping - a computational thread of the Simplified Partial Digest Problem

In the paper, the problem of the genome mapping of DNA molecules, is presented. In particular, the new approach — the Simplified Partial Digest Problem (SPDP), is analyzed. This approach, although easy in laboratory implementation and robust with respect to measurement errors, when formulated in terms of a combinatorial search problem, is proved to be strongly NP-hard for the general error-free case. For a subproblem of the SPDP, a simple O(n logn )-time algorithm is given, where n is a number of restriction sites.
The impact of diabetes on the association between epicardial fat thickness and extent and complexity of coronary artery disease in patients with non-ST elevation myocardial infarction.

BACKGROUND Epicardial fat thickness (EFT) is associated with increased cardio metabolic risk. Recent studies have suggested that there is a strong relationship between diabetes and EFT. Although the relationship between EFT and coronary artery disease (CAD) is well known, the possible impact of diabetes on the relationship between EFT and extent and complexity of CAD was not fully investigated. AIM We aimed to investigate the relationship between EFT and extent and complexity of CAD in patients with non-ST elevation myocardial infarction (NSTEMI) with and without diabetes. METHODS We prospectively included 454 patients with NSTEMI (mean age: 61.8 ± 10.4 years) in the present study. Patients were classified into two groups according to their diabetes status (diabetic group and non-diabetic group). EFT was measured by transthoracic echocardiography on the right ventricle in individuals having the left lateral decubitus position. SYNTAX score was used to define the extent and complexity of CAD. High-sensitivity C-reactive protein (hs-CRP) and other biochemical markers were measured in all participants. RESULTS Diabetic patients had higher EFT values compared with non-diabetics (p < 0.05). EFT is independently associated with diabetes, SYNTAX score, and hs-CRP in all patients (p < 0.05, for all). When patients were divided into two groups, as diabetic and non-diabetic, the association between EFT and SYNTAX score was stronger in diabetic patients compared with non-diabetics (r = 0.635; p < 0.001 vs. r = 0.179; p = 0.003). CONCLUSIONS Epicardial fat thickness is associated with SYNTAX score in both diabetic and non-diabetic patients. Furthermore, there is a stricter relationship between EFT and SYNTAX score in diabetic patients.
The influence of the organisational context on training motivation

The study examines the infl uence of individual and organisational factors on motivation and training. In particular, personality factors such as innovativeness, proactivity and dominance, work-related factors such as job involvement, and organisational support for training. These have all been found to infl uence training motivation viewed as a multidimensional construct. The aspects observed include motivation to learn and to obtain professional skills, the motivation to put new knowledge acquired in training into the workplace and the motivation to undergo training for the purpose of increasing status and social and company standing. The study was carried out on a sample of 382 adult employees in public and private organisational contexts and has confi rmed that a number of individual, work and organisational factors act together to influence training motivation.
Examining teacher effectiveness within differentially effective primary schools in the People's Republic of China

The objective of this study was to advance our understanding of educational effectiveness processes within contexts where they have seldom been studied before: rural and urban areas in China. Utilizing a “contextually sensitive” school effectiveness research design, we collected classroom observation data to address our research hypotheses and question. The research design called for crossing 2 levels of effectiveness status (more effective, less effective) and 2 levels of community type (urban, rural). Multivariate analyses of variance with traditional teacher effectiveness variables as the dependent indices yielded significant differences between more effective and less effective schools and between urban and rural schools. Qualitative results complemented the classroom observations by identifying unique characteristics of classroom teaching in the People's Republic of China.
NOVA: Towards on-demand equivalent network view abstraction for network optimization

As many applications today migrate to distributed computing and cloud platforms, their user experience depends heavily on network performance. Software Defined Networking (SDN) makes it possible to obtain a global view of the network, introducing the new paradigm of developing adaptive applications with network views. A naive approach of realizing the paradigm, such as distributing the whole network view to applications, is not practical due to scalability and privacy concerns. Existing approaches providing network abstractions are limited to special cases, such as bottlenecks exist only at networks edges, resulting in potentially suboptimal or infeasible decisions. In this paper, we introduce a novel, on-demand network abstraction service that provides an abstract network view supporting not only accurate end-to-end QoS metrics, which satisfy the requirements of many peer-to-peer applications, but also multi-flow correlation, which is essential for bandwidth-sensitive applications containing many flows to conduct global network optimization. We prove that our abstract view is equivalent to the original network view, in the sense that applications can make the same optimal decision as with the complete information. Our evaluations demonstrate that the abstraction guarantees feasibility and optimality for network optimizations and protects the network service providers' privacy. Our evaluations also show that the service can be implemented efficiently; for example, for an extreme large network with 30,000 links and abstraction requests containing 3,000 flows, an abstract network view can be computed in less than one second.
BRIP1 overexpression is correlated with clinical features and survival outcome of luminal breast cancer subtypes

In Oman, breast cancer is most common, representing approximately more than 25% of all cancers in women. Relatively younger populations of patients (25–40 years) present surprisingly with an aggressive phenotype and advanced tumor stages. In this study, we investigated differential gene expressions in Luminal A, Luminal B, triple-negative and Her2+ breast cancer subtypes and compared data to benign tumor samples. We identified a potential candidate gene BRIP1, showing differential expression in the four breast cancer subtypes examined, suggesting that BRIP1 has the profile of a useful diagnostic marker, suitable for targeted therapeutic intervention. RT-qPCR and Western blotting analysis showed higher BRIP1 expression in luminal samples as compared to triple-negative subtype patient’s samples. We further screened BRIP1 for eventual mutations/SNPs/deletions by sequencing the entire coding region. Four previously identified polymorphisms were detected, one within the 5′-UTR region (c.141-64G > A) and three in the BRCA-binding domain (c.2755T > C, c.2647G > A and c.3411T > C). Kaplan–Meier analysis revealed that patients with overexpression of BRIP1 displayed a poor survival rate (P < 0.05). BRIP1 has a dual function of an oncogene and a tumor suppressor gene in addition to its role as a potential biomarker to predict survival and prognosis. Data obtained in this study suggest that BRIP1 can plausibly have an oncogenic role in sporadic cancers.
Optimal fiscal policy, limited commitment and learning

Esta tesis trata sobre como la autoridad fiscal debe fijar los impuestos distorsivos de manera optima. El Capitulo 1 analiza el problema de la politica fiscal cuando el gobierno tiene un incentivo a hacer default a su deuda externa. El Capitulo 2 trata sobre el problema de la politica fiscal cuando los agentes no conocen como el gobierno fija las tasas impositivas. La principal conclusion que obtengo es que, en ambos contextos, el resultado de suavidad de las tasas, que es estandar en la literatura de imposicion optima, se rompe. Cuando los gobiernos no tienen una tecnologia de compromiso, los impuestos responden a los incentivos de default; cuando los agentes poseen informacion parcial sobre el modelo subyacente de la economia, los impuestos dependen de sus expectativas sobre los mismos.