Miracle-dz/UniFAR-FTUs huggingface dataset:
Model-free and model-based time-optimal control of a badminton robot

In this research, time optimal control is considered for the hit motion of a badminton robot during a serve operation. For this task the racket always starts at rest in a given position and has to move to a target state, defined by a target position and a non-zero target velocity. The goal is to complete this motion in as little time as possible, yet without violating bounds on the actuator. To find controllers satisfying these requirements, a reinforcement learning approach is implemented, using a Natural Actor-Critic (NAC) reinforcement learning algorithm. This approach is experimentally shown to yield the desired robot motions after about 200 trials. Next to this model-free learning approach, the control signals obtained with a model-based optimization are also applied to the robot. The results achieved with both approaches are compared, and a thorough analysis is presented, highlighting the properties of each approach, as well as their advantages and drawbacks.
Central energy-to-peak filter design for uncertain linear systems

This paper presents the central finite-dimensional energy-to-peak filter for linear systems that is optimal with respect to a modified Bolza-Meyer quadratic criterion including the first degree state-dependent term and the attenuation control term with the opposite sign. The obtained solution is based on reducing the original energy-to-peak filtering problem to the corresponding mean-module filtering problem, using the technique proposed in [1]. The paper first presents the central energy-to-peak filter for linear systems, based on the optimal mean-module filter from [2], assuming the standard filtering conditions of stabilizability, detectability, and noise orthonormality. Finally, to relax the standard conditions, the paper presents the generalized version of the designed energy-to-peak filter in the absence of the noise orthonormality. Numerical simulations are conducted to verify performance of the designed energy-to-peak filter for linear systems against the central suboptimal H∞ filter [3]. The simulation results show a definite advantage in the values of the noise-output energy-to-peak norm in favor of the designed filter.
Applying Formal Methods to Design of Migrator Component of Data Masking Software

Developing defect free design of software systems is an important problem. This is because of high cost incurred due to failure of incorrectly designed software. In this paper, we demonstrate development of software design by applying correct by construction semantics. We combine Symbolic Execution technique with Hoare Logic to develop defect free design of migrator component created for Data Masking Software of TCS. The basic functionality of migrator component is to migrate settings from the old DataMasker product to new DataPlus product. This requires development of correct mapping and processing of Intermediate Representations of these products. After migrating settings, we also validate the functionality of migrator component with minimal testing to ensure correctness of design. Thus, our work shows effectiveness of formal methods to develop high quality design of industry strength software.1
Restricted Isometry Property of Gaussian Random Projection for Finite Set of Subspaces

Dimension reduction plays an essential role when decreasing the complexity of solving large-scale problems. The well-known Johnson–Lindenstrauss (JL) lemma and restricted isometry property (RIP) admit the use of random projection to reduce the dimension while keeping the Euclidean distance, which leads to the boom of compressed sensing and the field of sparsity related signal processing. Recently, successful applications of sparse models in computer vision and machine learning have increasingly hinted that the underlying structure of high dimensional data looks more like a union of subspaces. In this paper, motivated by JL lemma and an emerging field of compressed subspace clustering, we study for the first time the RIP of Gaussian random matrices for the compression of two subspaces based on the generalized projection $F$-norm distance. We theoretically prove that with high probability the affinity or distance between two projected subspaces are concentrated around their estimates. When the ambient dimension after projection is sufficiently large, the affinity and distance between two subspaces almost remain unchanged after random projection. Numerical experiments verify the theoretical work.
Gastrointestinal Symptoms in Diabetes: Prevalence, Assessment, Pathogenesis, and Management

If you haven’t measured something, you really don’t know much about it. —Karl Pearson (attributed) Gastrointestinal (GI) symptoms represent an important and often unappreciated cause of morbidity in diabetes, although the significance of this burden across the spectrum of patients and the underlying pathophysiology, including the relationship of symptoms with glycemic control, remain poorly defined. The relevance of GI symptoms and the necessity for their accurate assessment have increased with the greater focus on the gut as a therapeutic target for glucose lowering. This review addresses the prevalence, assessment, pathogenesis, and management of GI symptoms in diabetes, beginning with broad principles and then focusing on specific segments of the GI tract. We initially performed a literature search of PubMed by using synonyms and combinations of the following search terms: “gastrointestinal symptoms”, “diabetes”, “prevalence”, “pathogenesis”, “diagnosis”, and “management”. We restricted the search results to English only. Review papers and meta-analyses are presented as the highest level of evidence where possible followed by randomized controlled trials, uncontrolled trials, retrospective and observational data, and expert opinion.
User assignment for MU-MIMO downlink system based on Munkres algorithm

This paper investigates user assignment algorithms for the downlink multiuser multiple-input multiple-output system with strong correlation at the transmitter side. In maximizing the ergodic achievable sum rate per group (EASRPG), the Munkres user assignment algorithm (MUAA) efficiently finds the optimal solution for the problem but some user groups of the optimal solution severely degrade the EASRPG due to excessive inter-user interference (IUI) in the multiuser statistical eigen-mode transmission (MU-SET) mode. To overcome this, MUAA with mode switching (MUAA-MS) is proposed to build partial optimal paired groups with the MU-SET mode while the other unpaired users perform the single-user SET mode. Results show a higher EASRPG for MUAA-MS.
Can the Critical Power Model Explain the Increased Peak Velocity/Power During Incremental Test After Concurrent Strength and Endurance Training?

Abstract Denadai, BS and Greco, CC. Can the critical power model explain the increased peak velocity/power during incremental test after concurrent strength and endurance training? J Strength Cond Res 31(8): 2319–2323, 2017—The highest exercise intensity that can be maintained at the end of a ramp or step incremental test (i.e., velocity or work rate at V[Combining Dot Above]O2max − Vpeak/Wpeak) can be used for endurance performance prediction and individualization of aerobic training. The interindividual variability in Vpeak/Wpeak has been attributed to exercise economy, anaerobic capacity, and neuromuscular capability, alongside the major determinant of aerobic capacity. Interestingly, findings after concurrent strength and endurance training performed by endurance athletes have challenged the actual contribution of these variables. The critical power model usually derived from the performance of constant-work rate exercise can also explain tolerance to a ramp incremental exercise so that, Vpeak/Wpeak can be predicted accurately. However, there is not yet discussion of possible concomitant improvements in the parameters of the critical power model and Vpeak/Wpeak after concurrent training and whether they can be associated with and therefore depend on different neuromuscular adaptations. Therefore, this brief review presents some evidence that the critical power model could explain the improvement of Vpeak/Wpeak and should be used to monitor aerobic performance enhancement after different concurrent strength- and endurance-training designs.
Towards universal kinect interface for fighting games

This paper presents an approach towards developing a universal Kinect interface supporting game-playing. The proposed interface is designed to be used with existing fighting games of any sort. Players can define their own postures and map them to keystrokes for sending input to a targeted game without the need of accessing game source code. We describe the overview of the interface system; including motion segmentation, posture feature extraction, and posture-to-key mapping.
The human Dcn1-like protein DCNL3 promotes Cul3 neddylation at membranes

Cullin (Cul)-based E3 ubiquitin ligases are activated through the attachment of Nedd8 to the Cul protein. In yeast, Dcn1 (defective in Cul neddylation 1 protein) functions as a scaffold-like Nedd8 E3-ligase by interacting with its Cul substrates and the Nedd8 E2 Ubc12. Human cells express 5 Dcn1-like (DCNL) proteins each containing a C-terminal potentiating neddylation domain but distinct amino-terminal extensions. Although the UBA-containing DCNL1 and DCNL2 are likely functional homologues of yeast Dcn1, DCNL3 also interacts with human Culs and is able to complement the neddylation defect of yeast dcn1Δ cells. DCNL3 down-regulation by RNAi decreases Cul neddylation, and overexpression of a Cul3 mutant deficient in DCNL3 binding interferes with Cul3 function in vivo. Interestingly, DCNL3 accumulates at the plasma membrane through a conserved, lipid-modified motif at the N terminus. Membrane-bound DCNL3 is able to recruit Cul3 to membranes and is functionally important for Cul3 neddylation in vivo. We conclude that DCNL proteins function as nonredundant Cul Nedd8-E3 ligases. Moreover, the diversification of the N termini in mammalian Dcn1 homologues may contribute to substrate specificity by regulating their subcellular localization.
Development of simulator for pressure controlled cooling pumps

This paper proposes a simulation model of pressure control of cooling pumps used for air-conditioners. To ensure proper working of cooling pumps for air-conditioning, proper control on pump activation and speed needs to be enforced. Control can be applied by various means. One way is to use input water flow quantity to determine the number of activated pumps. But due to the relatively high cost of sensors, output pressure signal can be used instead via a much cheaper pressure sensor. This work will concentrate on building a simulator to model pressure controlled pumps. It acts as a preliminary work to simulate the actual physical system such that further analysis on pressure-controlled pumps can be performed much easily. We conduct preliminary experiments to compare the similarity between the simulation model and the actual physical system. Preliminary experimental results show that the simulation model can produce signals quite similar to those produced by the actual system.
Model predictive steering control for independent driving and steering vehicles considering coaxial steering mechanism — Implementation to an embedded CPU

Omnidirectional vehicles with independent driving and steering wheels are useful since they can move with arbitrary attitude and change the moving direction rapidly. However, excessively rapid steering and unacceptable load may damage mechanisms. To prevent rapid steering and overloads, low-pass filter (LPF) is applied to the steering signals. Since the angular velocity should be limited on account of the motor constraint, even if the time constant is set small, the convergence of the steering is slow, and the error between the target angle and the real steering angle may occur. In this study, we propose the model predictive steering control for independent four-wheel driving and steering vehicles with coaxial steering mechanisms. The proposed method can consider physical constraints of actuators and achieve smooth and quick convergence of the steering to the target angle. We verify the efficiency of the proposed method by experiments using the vehicle which is equipped with an embedded CPU.
Effect of droplet diameter on liquid impingement erosion

One of the parameters influencing the liquid impingement erosion remarkably is droplet size. The effect of droplet size has been studied since 1927. Some researchers found a strong increase in erosion with droplet size and the others found a weak dependence. In this study, the effect of droplet size on liquid impingement erosion was studied for pure aluminum and low-carbon steel S15C. We found that the volume loss per droplet increases with the 4.67th power of droplet diameter, and proposed a new predict formulation of volume loss per droplet in terms of impact velocity and droplet diameter.
Systemic Hypoxia Increases the Expression of DPP4 in Preadipocytes of Healthy Human Participants

Abstract Dipeptidyl peptidase 4 (DPP4) is a transmembrane glycoprotein involved in protein degradation. Due to its action on incretins, which increase insulin secretion, DPP4 is considered a therapeutic target for type 2 diabetes. Here we have studied the role of single and combined effects of hypoxia and inactivity on the expression of DPP4 in human adipose tissue of 12 adult normal-weight males. Fat biopsies were obtained at baseline and after each of three experimental campaigns. The results revealed that in isolated human preadipocytes the expression of DPP4 was significantly increased by exposure of participants to hypoxia. Physical inactivity per se had no apparent effect on the DPP4 expression. It is concluded that DPP4 may be a marker to monitor indirectly tissue hypoxia, as occurs in obese subjects.
A Pipeline for Drug Target Identification and Validation

Rapid and affordable tumor profiling has led to an explosion of genomic data that is facilitating the development of new cancer therapies. The potential of therapeutic strategies aimed at inactivating the oncogenic lesions that contribute to the aberrant survival and proliferation of tumor cells has yielded remarkable success in some malignancies such as BRAF-mutant melanoma and BCR-ABL expressing chronic myeloid leukemia. However, the direct inhibition of several well-established oncoproteins in some of these cancers is not possible or produces only transient benefits. Functional genomics represents a powerful approach for the identification of vulnerabilities linked to specific genetic alterations and has provided substantial insights into cancer signaling networks. Still, as inhibition of gene function can have diverse effects on both tumor and normal tissues, information on the potency of target inhibition on tumor growth as well as the toxic side effects of target inhibition are also needed. Here, we discuss our RNA interference (RNAi) pipeline for cancer target discovery based on our optimized short-hairpin RNA (shRNA) tools for negative selection screens and inducible RNAi platform that, in combination with embryonic stem cell (ESC)-based genetically engineered mouse models (GEMMs), enable deep in vivo target validation.
Modeling of Lithium-Ion Battery Degradation for Cell Life Assessment

Rechargeable lithium-ion batteries are promising candidates for building grid-level storage systems because of their high energy and power density, low discharge rate, and decreasing cost. A vital aspect in energy storage planning and operations is to accurately model the aging cost of battery cells, especially in irregular cycling operations. This paper proposes a semi-empirical lithium-ion battery degradation model that assesses battery cell life loss from operating profiles. We formulate the model by combining fundamental theories of battery degradation and our observations in battery aging test results. The model is adaptable to different types of lithium-ion batteries, and methods for tuning the model coefficients based on manufacturer’s data are presented. A cycle-counting method is incorporated to identify stress cycles from irregular operations, allowing the degradation model to be applied to any battery energy storage (BES) applications. The usefulness of this model is demonstrated through an assessment of the degradation that a BES would incur by providing frequency control in the PJM regulation market.
Sum-Product-Quotient Networks

We present a novel tractable generative model that extends Sum-Product Networks (SPNs) and significantly boost their power. We call it Sum-Product-Quotient Networks (SPQNs), whose core concept is to incorporate conditional distributions into the model by direct computation using quotient nodes, e.g. $P(A|B){=}\frac{P(A,B)}{P(B)}$. We provide sufficient conditions for the tractability of SPQNs that generalize and relax the decomposable and complete tractability conditions of SPNs. These relaxed conditions give rise to an exponential boost to the expressive efficiency of our model, i.e. we prove that there are distributions which SPQNs can compute efficiently but require SPNs to be of exponential size. Thus, we narrow the gap in expressivity between tractable graphical models and other Neural Network-based generative models.
Blended-Learning Strategy in the Altay State Medical University

New educational technologies prove to be capable of solving many problems in the medical training. Students do not see e-Learning as replacing traditional instructor-led training but as a complement to it, forming part of a blended-learning strategy. Innovations in e-Learning technologies point toward a revolution in education, allowing learning to be individualized (adaptive learning), enhancing learners' interactions with others (collaborative learning), and transforming the role of the teacher. The integration of e-Learning into medical education can catalyze the shift towards applying adult learning theory, where educators will no longer serve mainly as the distributors of content, but will become more involved as facilitators of learning and assessors of competency. This survey analyzes possibilities to effectively use e-Learning in medical education, and what steps are to be made in that direction.
Dual-Energy CT Imaging of Tumor Liposome Delivery After Gold Nanoparticle-Augmented Radiation Therapy

Gold nanoparticles (AuNPs) are emerging as promising agents for both cancer therapy and computed tomography (CT) imaging. AuNPs absorb x-rays and subsequently release low-energy, short-range photoelectrons during external beam radiation therapy (RT), increasing the local radiation dose. When AuNPs are near tumor vasculature, the additional radiation dose can lead to increased vascular permeability. This work focuses on understanding how tumor vascular permeability is influenced by AuNP-augmented RT, and how this effect can be used to improve the delivery of nanoparticle chemotherapeutics. Methods: Dual-energy CT was used to quantify the accumulation of both liposomal iodine and AuNPs in tumors following AuNP-augmented RT in a mouse model of primary soft tissue sarcoma. Mice were injected with non-targeted AuNPs, RGD-functionalized AuNPs (vascular targeting), or no AuNPs, after which they were treated with varying doses of RT. The mice were injected with either liposomal iodine (for the imaging study) or liposomal doxorubicin (for the treatment study) 24 hours after RT. Increased tumor liposome accumulation was assessed by dual-energy CT (iodine) or by tracking tumor treatment response (doxorubicin). Results: A significant increase in vascular permeability was observed for all groups after 20 Gy RT, for the targeted and non-targeted AuNP groups after 10 Gy RT, and for the vascular-targeted AuNP group after 5 Gy RT. Combining targeted AuNPs with 5 Gy RT and liposomal doxorubicin led to a significant tumor growth delay (tumor doubling time ~ 8 days) compared to AuNP-augmented RT or chemotherapy alone (tumor doubling time ~3-4 days). Conclusions: The addition of vascular-targeted AuNPs significantly improved the treatment effect of liposomal doxorubicin after RT, consistent with the increased liposome accumulation observed in tumors in the imaging study. Using this approach with a liposomal drug delivery system can increase specific tumor delivery of chemotherapeutics, which has the potential to significantly improve tumor response and reduce the side effects of both RT and chemotherapy.
Low-loss polymer optical waveguides using fluorinated poly(arylene ether sulfides and sulfones)

We synthesized novel cross-linkable fluorinated co-poly(arylene ether sulfide)s and co-poly(arylene ether sulfone)s for optical waveguide applications, having high thermal stability, high optical transparency in the infrared communication region, and small birefringence. The refractive index of the materials can be easily controlled in the range of 1.50~1.58 by changing the copolymer composition in the materials. The birefringence of the polymer films was 0.0015~0.0039 at the wavelength of 1.55 μm. These are much lower than those of fluorinated polyimides for optical waveguides. The optical loss after storing at 300 °C for 1 h remains almost constant, demonstrating the thermal stability. The propagation losses of the fluorinated polymers were 0.1~0.3 dB/cm and 0.2~0.5 dB/cm at the wavelength of 1.3 and 1.55 μm, respectively. These excellent optical properties have allowed us to fabricate a variety of optical devices such as straight channel waveguides, directional coupler, and polymeric wavelength filter.
CD5L is upregulated in hepatocellular carcinoma and promotes liver cancer cell proliferation and antiapoptotic responses by binding to HSPA5 (GRP78)

CD5‐like (CD5L) is a soluble scavenger cysteine‐rich protein that modulates inflammatory responses. We studied the involvement of CD5L in liver cancer. Immunohistochemistry (IHC) of CD5L in 60 hepatocellular carcinomas and 34 adjacent nontumor livers, showed that CD5L staining was higher in tumor than in nontumor tissue (Mann‐Whitney test; P = 0.0039). High CD5L correlated with elevated proliferation (Ki67, linear regression; P < 0.0001) and lower patient event‐free survival (log‐rank; P = 0.0185). Accordingly, CD5L expression was detected in the liver cancer cell lines Huh7, HepG2, and SNU‐398. In vitro technologies using these cell lines, including small interfering RNA (siRNA) and cDNA transfection, showed that CD5L promoted colony formation and cell proliferation and protected against cisplatin‐induced apoptosis. To find a molecular explanation for these roles, novel CD5L‐interacting protein ligands in liver cancer cells were identified by immunoprecipitation followed by mass spectrometry. Among these, the molecular chaperone of the unfolded protein response (UPR), heat shock protein (HSP)‐A5, was selected for validation. The interaction was confirmed by confocal microscopy in the Huh7 and HepG2 cell lines. Furthermore, functional experiments revealed that CD5L activates the UPR and autophagy mechanisms in Huh7 cells, thereby providing a novel molecular link between the UPR and autophagy in liver cancer. —Aran, G. , Sanjurjo, L. , Barcena, C. , Simon‐Coma, M. , Tellez, E. , Vazquez‐Vitali, M. , Garrido, M. , Guerra, L. , Díaz, E. , Ojanguren, I. , Elortza, F. , Planas, R. , Sala, M. , Armengol, C. , Sarrias, M. ‐R. CD5L is upregulated in hepatocellular carcinoma and promotes liver cancer cell proliferation and antiapoptotic responses by binding to HSPA5 (GRP78). FASEB J. 32, 3878–3891 (2018). www.fasebj. org