Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling and control of a truck steering-system for active driver support

As a part of the Dutch NWO project ”Truck merging support” (project number 12831), a lane changing assistant is developed to improve safety in commercial freight vehicles. The goal of this assistant is to aid the driver during the safetycritical task of merging on the highway by controlling the vehicle motion and the steering-wheel torque. The contributions of this thesis are two-fold: 1. The modeling and validation of a truck steering-system with hydraulic power-steering. Next to the evaluation on component level, the model is implemented and validated in a multi-body full vehicle model. 2. The design of a steering-wheel torque controller to guide the driver in following a specific course on the road. Based on the physical lay-out, the steering-system of the truck is modeled having three mechanical degrees of freedom. The steering-system is divided in an inertia for the steering-wheel, an inertia for the input shaft and an inertia for the output shaft of the steering-house. The inertias are interconnected via springs, representing the compliance of the physical components in between them. This research shows that friction in the steering-system is a key factor in the prediction of steering torque experienced by the driver. Three separate inertias are required to implement friction at the relevant locations which is different from models found in literature. A hydraulic power-steering model is developed based on a symmetric Wheatstone bridge. A test rig outside the vehicle is used to identify the parameters required for the steering-system model. The steering-system model is parametrized using steady-state tests where the most important parameters are the Wheatstone bridge orifice areas, the friction on the input and output shaft of the steeringhouse and the stiffness of the torsion-bar. Testing with sinusoidal inputs for frequencies above the driver input range (3.5 Hz) enable identification of the damping and inertial parameters of the model. The model is able to reproduce the measurements with an error of less than 10 percent with respect to the
Recommendation for Continuous Ethical Analysis of AI Algorithms

Artificial Intelligence (AI) algorithms and applications have become more prevalent in our information society. Organizations that build AI applications incorporate various ethical evaluation frameworks, policies, and guidelines – and yet the outcome of many AI systems are producing questionable, biased, unfair, opaque, unjustified, and/or unexplained results. In this research project we determine the necessity for not just an initial ethical review of such algorithms, but suggest the ongoing ethical evaluation of AI algorithms as applications are updated and enhanced – a Continuous Ethical Analysis process.
Brief Announcement: (1+ε)-Approximate Shortest Paths in Dynamic Streams.

Computing approximate shortest paths in the dynamic streaming setting is a fundamental challenge that has been intensively studied. Currently existing solutions for this problem either build a sparse multiplicative spanner of the input graph and compute shortest paths in the spanner offline, or compute an exact single source BFS tree. Solutions of the first type are doomed to incur a stretch-space tradeoff of 2k - 1 versus n1+1/k , for an integer parameter k. (In fact, existing solutions also incur an extra factor of 1+ε in the stretch for weighted graphs, and an additional factor of logO(1) n in the space. ) The only existing solution of the second type uses n1/2-O(1/k) passes over the stream (for space O(n1+1/k )), and applies only to unweighted graphs.
Tension analysis of a 6-degree-of-freedom cable-driven parallel robot considering dynamic pulley bearing friction

Recently, cable-driven parallel robots have been used in many industrial fields. Especially, cable-driven parallel robots have been used in specialized industrial fields where dynamical features such as high accuracy in systems requiring quick transitions. In this article, Dahl friction model was proposed to predict the tension during quick transitions in cable-driven parallel robots. And the Dahl friction equation for a combination of pulleys connected in series was derived. From their relationships, a modified kinematic equation was developed for redundant actuation cable-driven parallel robot systems. Because Dahl friction has non-linear characteristics, the actual tension set problem was solved using the Newton–Raphson method combined with the constrained non-linear multivariable optimal method. Finally, the tension profiles were simulated using both Dahl and Coulomb friction models with fast and slow velocities. In conclusion, according to simulation, Dahl friction model expressed dynamic characteristics such as pre-sliding in the transition range. Thus, it was in better agreement with the experiments than the Coulomb friction model. In particular, Dahl friction model was more accurate in the case of slow motion in the pre-sliding range.
Smart Home as a Silent Witness - A Survey

Modern households are equipped with a growing number of smart devices, which aim to support the residents in their everyday life. The raise of the Internet of Things (IoT) supports this shift to an automatized home with different devices like sensors, cameras, remote controlled wall sockets or other actors controlled from a central unit. These devices are always on, to execute the demanded functionality, either if commanded by a user or triggered from external events. This makes a smart home to a silent witness, which monitors, analyzes and stores a huge number of different events inside a modern house. This information might be useful evidence when investigating suspicious activities like burglary, domestic abuse, or homicide. Our research analyzes the need for advanced training for first responders of law enforcement agencies. Derived from surveying officers in the field of crime scenes we propose an improved training with a special focus on the detection of smart home devices.
Increased plasma level of kynurenic acid in drug-free patients with first-episode schizophrenia compared to patients with chronic schizophrenia and healthy controls: preliminary data

Abstract Background Kynurenic acid (KYNA) is a metabolite of tryptophan (TRP). KYNA levels have been reported with controversial findings in patients with schizophrenia. Aim This study aimed to investigate the probable effects of medication and illness chronicity on peripheral KYNA levels in schizophrenia. Methods We assessed peripheral (plasma) TRP metabolite levels in 38 drug-free patients with first-episode schizophrenia (FES), 65 patients with chronic schizophrenia (CHS), and 70 healthy controls by using high-performance liquid chromatography–tandem mass spectrometry (LC-MS/MS). The symptom severity of patients was evaluated by using the Positive and Negative Syndrome Scale (PANSS). Finally, we analyzed the association of TRP metabolites with symptom severity. Results We found significantly higher KYNA levels in FES patients than in both healthy controls (p < 0.01) and CHS patients (p < 0.05). No significant association was observed between plasma TRP metabolite levels and PANSS scores in either FES or CHS patients. Conclusions In conclusion, elevated plasma KYNA levels may be a promising biomarker in FES patients. Medication and illness chronicity may affect peripheral KYNA levels with a currently unknown mechanism.
Coherence and Inelastic Scattering in Electron Microscopy

1. TMF, Lawrence Berkeley National Laboratory, One Cyclotron Rd., Berkeley, CA 94720, USA 2. Department of MSE, University of California Berkeley, Berkeley, CA 94720, USA 3. Thermo Fisher Scientific, Achtseweg Noord 5, 5651 GG Eindhoven, The Netherlands 4. The Dow Chemical Company, Midland, MI 48667, USA 5. EMAT, University of Antwerp, 2020 Antwerp, Belgium * Corresponding author: CFKisielowski@lbl.gov
Wireless Sensor Networks - Applications and Development

Recent technology advances enabled the development of wireless sensor networks (WSN). This paper gives a short overview of WSN, their development and future trends. Further, possible applications of WSN are analysed with reference to some successful examples. Finally, the paper proposes possible applications of WSN in Croatia, focusing on applications in precision agriculture and environmental monitoring applications in Eastern Croatia.
A Spatial-Spectral Interference Model for Dense Finite-Area 5G mmWave Networks

With the overcrowded sub-6 GHz bands, millimeter wave (mmWave) bands offer a promising alternative for the next generation wireless standard, i.e., 5G. However, the susceptibility of mmWave signals to severe pathloss and shadowing requires the use of highly directional antennas to overcome such adverse characteristics. Building a network with directional beams changes the interference behavior, since, narrow beams are vulnerable to blockages. Such sensitivity to blockages causes uncertainty in the active interfering node locations. Configuration uncertainty may also manifest in the spectral domain while applying dynamic channel and frequency assignment to support 5G applications. In this paper, we first propose a blockage model considering mmWave specifications. Subsequently, using the proposed blockage model, we derive a spatial-spectral interference model for dense finite-area 5G mmWave networks. The proposed interference model considers both spatial and spectral randomness in node configuration. Finally, the error performance of the network from an arbitrarily located user perspective is calculated in terms of bit error rate (BER) and outage probability metrics. The analytical results are validated via Monte-Carlo simulations. It is shown that considering mmWave specifications and also randomness in both spectral and spatial node configurations leads to a noticeably different interference profile.
AFM-based force spectroscopy unravels the stepwise-formation of a DNA transposition complex driving multi-drug resistance dissemination

Transposon Tn4430 belongs to a widespread family of bacterial transposons, the Tn3 family, which plays a prevalent role in the dissemination of antibiotic resistance among pathogens. So far, the molecular mechanisms underlying the replicative transposition of these elements are still poorly understood. Here, we use force-distance curve-based atomic force microscopy to probe the binding of the TnpA transposase of Tn4430 to DNA molecules containing one or two transposon ends and to extract the thermodynamic and kinetic parameters of transposition complex assembly. Comparing wild-type TnpA with previously isolated deregulated TnpA mutants supports a stepwise pathway for transposition complex formation and activation during which TnpA first binds to a single transposon end and then undergoes a structural transition that enables it to bind the second end co-operatively and to become activated for transposition catalysis. Our study thus provides an unprecedented approach to probe the dynamic of a complex DNA processing machinery at the single-particle level.
Measuring Dynamics in Energy Materials Using Functional Atomic Force Microscopy

Atomic force microscopy (AFM) is a well-established tool for nanoscale imaging of surfaces for a wide range of materials of interest. In energy materials, such as photovoltaics or battery electrodes, the ability to combine electrical AFM with local optical illumination has enabled a wide range of novel electrical imaging methods that can correlate local structure with device function in realistic conditions. For example, it is possible to use electrical AFM techniques to measure important solar cell properties like local carrier injection barriers or processing effects on short-circuit photocurrent on actual solar cell device stacks
Frem1 activity regulated by Sonic Hedgehog signaling in the cranial neural crest mesenchyme guides midfacial morphogenesis

The Frem/Fras family of extracellular matrix proteins has been linked to human face shape variation and malformation, but little is known about their regulation and biological roles in facial development. During midfacial morphogenesis in mice, we observed Frem1 expression in the embryonic growth centers that form the median upper lip, nose, and palate. Expansive spatial gradients of Frem1 expression in the cranial neural crest cell (cNCC) mesenchyme of these tissues suggested transcriptional regulation by a secreted morphogen. Accordingly, Frem1 expression paralleled that of the conserved Sonic Hedgehog (Shh) target gene Gli1 in the cNCC mesenchyme. Suggesting direct transcriptional regulation by Shh signaling, we found that Frem1 expression is induced by SHH ligand stimulation or downstream pathway activation in cNCCs and observed GLI transcription factor binding at the Frem1 transcriptional start site during midfacial morphogenesis. Shh pathway antagonism reduced Frem1 expression during pathogenesis of midfacial hypoplasia, and FREM1 was sufficient to induce cNCC proliferation in a concentration-dependent manner. These findings provide novel insight into the mechanism by which the Shh pathway drives midfacial morphogenesis and reveal a functional role for Frem1 in cNCC biology that establishes the developmental basis for FREM1-associated face shape variation and malformation.
ZER1 Contributes to the Carcinogenic Activity of High-Risk HPV E7 Proteins

HPV16 is highly carcinogenic and is the most predominant HPV genotype associated with human cancers. The mechanisms that underlie differences between high-risk HPV genotypes are currently unknown, but many of these differences are likely attributable to the activities of the oncogenic HPV proteins, including E7. ABSTRACT Human papillomavirus (HPV) E7 proteins bind to host cell proteins to facilitate virus replication. Interactions between HPV E7 and host cell proteins can also drive cancer progression. We hypothesize that HPV E7-host protein interactions specific for high-risk E7 contribute to the carcinogenic activity of high-risk HPV. The cellular protein ZER1 interacts with the E7 protein from HPV16, the genotype most frequently associated with human cancers. The HPV16 E7-ZER1 interaction is unique among HPV E7 tested to date. Other E7 proteins, even from closely related HPV genotypes, do not bind ZER1, which is a substrate specificity factor for a CUL2-RING ubiquitin ligase. In the present study, we investigated the contribution of ZER1 to the carcinogenic activity of HPV16 E7. First, we mapped the ZER1 binding site to specific residues on the C terminus of HPV16 E7. We showed that the mutant HPV16 E7 that cannot bind ZER1 is impaired in the ability to promote the growth of primary keratinocytes. We found that ZER1 and CUL2 contribute to, but are not required for, HPV16 E7 to degrade RB1. Cancer dependency data show that ZER1 is an essential gene in most HPV-positive, but not HPV-negative, cancer cell lines. Depleting ZER1 impaired the growth of primary keratinocytes expressing HPV16 E7 or HPV18 E7 and of HPV16-and HPV18-positive cervical cancer cell lines. Taken together, our work demonstrates that ZER1 contributes to HPV-mediated carcinogenesis and is essential for the growth of HPV-positive cells. IMPORTANCE HPV16 is highly carcinogenic and is the most predominant HPV genotype associated with human cancers. The mechanisms that underlie differences between high-risk HPV genotypes are currently unknown, but many of these differences are likely attributable to the activities of the oncogenic HPV proteins, including E7. The HPV E7 oncoprotein is essential for HPV-mediated carcinogenesis. A large number of HPV E7 targets have been identified. However, it is unclear which of these many interactions contributes to the carcinogenic activity of HPV E7. Here, we characterized the interaction between HPV16 E7 and the host cell protein ZER1, testing whether this genotype-specific interaction could enable some of the carcinogenic activity of HPV16 E7. We found that ZER1 binding contributes to the growth-promoting activity of HPV16 E7 and to the growth of HPV-positive cervical cancer cells. We propose that ZER1 makes an important contribution to HPV-mediated carcinogenesis.
Fine-Mapping and Comparative Genomic Analysis Reveal the Gene Composition at the S and Z Self-incompatibility Loci in Grasses

Self-incompatibility (SI) is a genetic mechanism of hermaphroditic plants to prevent inbreeding after self-pollination. Allogamous Poaceae species exhibit a unique gametophytic SI system controlled by two multi-allelic and independent loci, S and Z. Despite intense research efforts in the last decades, the genes that determine the initial recognition mechanism are yet to be identified. Here, we report the fine-mapping of the Z-locus in perennial ryegrass (Lolium perenne L.) and provide evidence that the pollen and stigma components are determined by two genes encoding DUF247 domain proteins (ZDUF247-I and ZDUF247-II) and the gene sZ, respectively. The pollen and stigma determinants are located side-by-side and were genetically linked in 10,245 individuals of two independent mapping populations segregating for Z. Moreover, they exhibited high allelic diversity as well as tissue-specific gene expression, matching expected characteristics of SI determinants known from other systems. Revisiting the S-locus using the latest high-quality whole-genome assemblies revealed a similar gene composition and structure as found for Z, supporting the hypothesis of a duplicated origin of the two-locus SI system of grasses. Ultimately, comparative genomic analyses across a wide range of self-compatible and self-incompatible Poaceae species revealed that the absence of a functional copy of at least one of the six putative SI determinants is accompanied by a self-compatible phenotype. Our study provides new insights into the origin and evolution of the unique gametophytic SI system in one of the largest and economically most important plant families.
Corruption of DNA End-Joining in Mammalian Chromosomes by Progerin Expression as Revealed by a Model Cell Culture System

Hutchinson-Gilford Progeria Syndrome (HGPS) is a rare genetic condition characterized by features of accelerated aging and a life expectancy of about 14 years. HGPS is commonly caused by a point mutation in the LMNA gene which codes for lamin A, an essential component of the nuclear lamina. The HGPS mutation alters splicing of the LMNA transcript, leading to a truncated, farnesylated form of lamin A termed “progerin. ” HGPS is associated with accumulation of genomic DNA double-strand breaks (DSBs), suggesting altered DNA repair. DSB repair normally occurs by either homologous recombination (HR), an accurate, templated form of repair, or by non-homologous end joining (NHEJ), an error-prone non-templated rejoining of DNA ends. Some NHEJ events occur via high-fidelity joining of DNA ends and we refer to such events as precise ligation (PL). Previously, we reported that expression of progerin correlated with increased NHEJ relative to HR. We now report on progerin’s impact on the nature of DNA end-joining. We used a model system involving a DNA end-joining reporter substrate integrated into the genome of cultured thymidine kinase-deficient mouse fibroblasts. Some cells were engineered to express progerin. DSBs were induced in the substrate through expression of endonuclease I-SceI, and DSB repair events were recovered through selection for thymidine kinase function. Progerin expression correlated with a significant shift away from PL and toward error-prone NHEJ. Our work suggests that progerin suppresses interactions between complementary sequences at DNA termini, shifting DSB repair toward low-fidelity DNA end-joining and perhaps contributing to aging through compromised genome stability.
Fast and Fair Randomized Wait-Free Locks

We present a randomized approach for wait-free locks with strong bounds on time and fairness in a context in which any process can be arbitrarily delayed. Our approach supports a tryLock operation that is given a set of locks, and code to run when all the locks are acquired. A tryLock operation, or attempt, may fail if there is contention on the locks, in which case the code is not run. Given an upper bound k known to the algorithm on the point contention of any lock, and an upper bound L on the number of locks in a try- Lock's set, a tryLock will succeed in acquiring its locks and running the code with probability at least 1/(kL). It is thus fair. Furthermore, if the maximum step complexity for the code in any lock is T , the attempt will take O(k2L2T ) steps, regardless of whether it succeeds or fails. The attempts are independent, thus if the tryLock is repeatedly retried on failure, it will succeed in O(k3L3T ) expected steps, and with high probability in not much more.
Noise Reconstruction and Removal Network: a New Way to Denoise FIB-SEM Image

1. Micron Technology, Inc, Advanced Computing and Emerging Memory Solutions, Boise, ID, United States. 2. Dept. of Biomedical Engineering, Oregon Health & Science University, Portland, OR, United States. 3. Multiscale Microscopy Core, Oregon Health & Science University, Portland, OR, United States. 4. Knight Cancer Institute, Oregon Health & Science University, Portland, OR, United States. * Corresponding author: thibaulg@ohsu.edu, bdelarosa@micron.com
I Know What You Are Searching for: Code Snippet Recommendation from Stack Overflow Posts

Stack Overflow has been heavily used by software developers to seek programming-related information. More and more developers use Community Question and Answer forums, such as Stack Overflow, to search for code examples of how to accomplish a certain coding task. This is often considered to be more efficient than working from source documentation, tutorials, or full worked examples. However, due to the complexity of these online Question and Answer forums and the very large volume of information they contain, developers can be overwhelmed by the sheer volume of available information. This makes it hard to find and/or even be aware of the most relevant code examples to meet their needs. To alleviate this issue, in this work, we present a query-driven code recommendation tool, named Que2Code, that identifies the best code snippets for a user query from Stack Overflow posts. Our approach has two main stages: (i) semantically equivalent question retrieval and (ii) best code snippet recommendation. During the first stage, for a given query question formulated by a developer, we first generate paraphrase questions for the input query as a way of query boosting and then retrieve the relevant Stack Overflow posted questions based on these generated questions. In the second stage, we collect all of the code snippets within questions retrieved in the first stage and develop a novel scheme to rank code snippet candidates from Stack Overflow posts via pairwise comparisons. To evaluate the performance of our proposed model, we conduct a large-scale experiment to evaluate the effectiveness of the semantically equivalent question retrieval task and best code snippet recommendation task separately on Python and Java datasets in Stack Overflow. We also perform a human study to measure how real-world developers perceive the results generated by our model. Both the automatic and human evaluation results demonstrate the promising performance of our model, and we have released our code and data to assist other researchers.