Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of the mechanical properties of microcapsules using diffuse approximation

A novel inverse analysis procedure based on diffuse approximation is presented to characterize the mechanical behavior of microcapsules. The method consists in flowing a dilute suspension of capsules through a prismatic microfluidic channel with a cross-section size comparable to the capsule diameter. For each capsule, we record its deformed profile and deduce from it a series of geometrical quantities and the capsule velocity. The unknowns are the membrane mechanical properties and the exact mean velocity of the background flow when the capsule is captured. A full mechanical model of the motion and deformation of a capsule is used to generate an exhaustive database of simulated profiles for different values of the input parameters: the capillary number and the size ratio. From the set of quantities obtained experimentally as well as the precomputed database, diffuse approximation efficiently estimates the unknown values of the input parameters of the flowing capsule. The shear modulus can then be determined with high precision provided that the capsule is sufficiently deformed to exhibit a parachute shape at the rear.
Privacy-Preserving and Lightweight Key Agreement Protocol for V2G in the Social Internet of Things

The concept of the Social Internet of Things (SIoT) can be viewed as the integration of prevailing social networking and the Internet of Things, which is making inroads into the daily operation of many industries. Smart grids, which are cost-effective and environmentally friendly applications, are a promising field of the SIoT. However, security and privacy concerns are the dark aspects of smart grids. The goal of this paper is to address the security and privacy issues in the vehicle-to-grid (V2G) networks with the intention of promoting a more extensive deployment of V2G networks for smart grids. Driven by this motivation, in this paper, we propose a robust key agreement protocol that can achieve mutual authentication without exposing the real identities of users. Efficiency is also a major concern in resource-constrained environments. By leveraging only hash functions and bitwise exclusive-OR operations, the proposed protocol is highly efficient compared with pairing-based protocols. In addition, we define a formal security model for our privacy-preserving key agreement protocol for V2G networks. Using this model, a formal security analysis shows that the proposed protocol is secure. Moreover, an informal security analysis demonstrates that our protocol can withstand different types of attacks.
Ultraviolet Irradiation of Skin Alters the Faecal Microbiome Independently of Vitamin D in Mice

Reduced sunlight exposure has been associated with an increased incidence of Crohn’s disease and ulcerative colitis. The effect of ultraviolet radiation (UVR) on the faecal microbiome and susceptibility to colitis has not been explored. C57Bl/6 female mice were fed three different vitamin D-containing diets for 24 days before half of the mice in each group were UV-irradiated (1 kJ/m2) for each of four days, followed by twice-weekly irradiation of shaved dorsal skin for 35 days. Faecal DNA was extracted and high-throughput sequencing of the 16S RNA gene performed. UV irradiation of skin was associated with a significant change in the beta-diversity of faeces compared to nonirradiated mice, independently of vitamin D. Specifically, members of phylum Firmicutes, including Coprococcus, were enriched, whereas members of phylum Bacteroidetes, such as Bacteroidales, were depleted. Expression of colonic CYP27B1 increased by four-fold and IL1β decreased by five-fold, suggesting a UVR-induced anti-inflammatory effect. UV-irradiated mice, however, were not protected against colitis induced by dextran sodium sulfate (DSS), although distinct faecal microbiome differences were documented post-DSS between UV-irradiated and nonirradiated mice. Thus, skin exposure to UVR alters the faecal microbiome, and further investigations to explore the implications of this in health and disease are warranted.
C5aR1 regulates migration of suppressive myeloid cells required for costimulatory blockade‐induced murine allograft survival

Costimulatory blockade‐induced murine cardiac allograft survival requires intragraft accumulation of CD11b+Ly6CloLy6G− regulatory myeloid cells (Mregs) that expand regulatory T cells (Tregs) and suppress effector T cells (Teffs). We previously showed that C5a receptor (C5aR1) signaling on T cells activates Teffs and inhibits Tregs, but whether and/or how C5aR1 affects Mregs required for transplant survival is unknown. Although BALB/c hearts survived >60 days in anti‐CD154 (MR1)‐treated or cytotoxic T‐lymphocyte associated protein 4 (CTLA4)‐Ig–treated wild‐type (WT) recipients, they were rejected at ~30 days in MR1‐treated or CTLA4‐Ig–treated recipients selectively deficient in C5aR1 restricted to myeloid cells (C5ar1fl/flxLysM‐Cre). This accelerated rejection was associated with ~2‐fold more donor‐reactive T cells and ~40% less expansion of donor‐reactive Tregs. Analysis of graft‐infiltrating mononuclear cells on posttransplant day 6 revealed fewer Ly6Clo monocytes in C5ar1fl/flxLysM‐Cre recipients. Expression profiling of intragraft Ly6Clo monocytes showed that C5aR1 deficiency downregulated genes related to migration/locomotion without changes in genes associated with suppressive function. Cotransfer of C5ar1fl/fl and C5ar1fl/flxLysM‐Cre myeloid cells into MR1‐treated allograft recipients resulted in less accumulation of C5ar1−/− cells within the allografts, and in vitro assays confirmed that Ly6Chi myeloid cells migrate to C5a/C5aR1‐initiated signals. Together, our results newly link myeloid cell–expressed C5aR1 to intragraft accumulation of myeloid cells required for prolongation of heart transplant survival induced by costimulatory blockade.
The effect of acute caffeine ingestion on upper body anaerobic exercise and cognitive performance

Abstract The current study examined the effect of acute caffeine ingestion on mean and peak power production during upper body Wingate test (WANT) performance, rating of perceived exertion, readiness to invest effort and cognitive performance. Using a double-blind design, 12 males undertook upper body WANTs, following ingestion of caffeine (5 mg*kg−1) or placebo. Pre-substance ingestion, 60 mins post substance ingestion and post exercise participants completed measures of readiness to invest physical and mental effort and cognitive performance. Peak power was significantly higher (P = .026), fatigue index greater (P = .02) and rating of perceived exertion lower (P = .025) in the presence of caffeine. Readiness to invest physical effort was also higher (P = .016) in the caffeine condition irrespective of time point (pre, 60 mins post ingestion and post exercise). Response accuracy for incongruent trials on the Flanker task was superior in the presence of caffeine (P = .006). There was a significant substance × time interaction for response speed in both congruent and incongruent conditions (both P = .001) whereby response speeds were faster at 60 mins post ingestion and post exercise in the caffeine condition, compared to placebo. This is the first study to examine the effects of caffeine ingestion on this modality of exercise and suggests that caffeine ingestion significantly enhances peak power, readiness to invest physical effort, and cognitive performance during WANT performance.
Green Communication for Tracking Heart Rate with Smartbands

The trend of using wearables for healthcare is steeply increasing nowadays, and, consequently, in the market, there are several gadgets that measure several body features. In addition, the mixed use between smartphones and wearables has motivated research like the current one. The main goal of this work is to reduce the amount of times that a certain smartband (SB) measures the heart rate (HR) in order to save energy in communications without significantly reducing the utility of the application. This work has used an SB Sony 2 for measuring heart rate, Fit API for storing data and Android for managing data. The current approach has been assessed with data from HR sensors collected for more than three months. Once all HR measures were collected, then the current approach detected hourly ranges whose heart rate were higher than normal. The hourly ranges allowed for estimating the time periods of weeks that the user could be at potential risk for measuring frequently in these (60 times per hour) ranges. Out of these ranges, the measurement frequency was lower (six times per hour). If SB measures an unusual heart rate, the app warns the user so they are aware of the risk and can act accordingly. We analyzed two cases and we conclude that energy consumption was reduced in 83.57% in communications when using training of several weeks. In addition, a prediction per day was made using data of 20 users. On average, tests obtained 63.04% of accuracy in this experimentation using the training over the data of one day for each user.
Diamond-free Degree Sequences

While attempting to classify partial linear spaces produced during the execution of an extension of Stinson's hill-climbing algorithm a new problem arises, that of generating all graphical degree sequences that are diamond-free (i.e. have no diamond as subgraph) and satisfy ad- ditional constraints. We formalize this new problem, propose a constraint programming solution and list all satisfying degree sequences of length 8 to 16 inclusive.
Learning to Segment Generic Handheld Objects Using Class-Agnostic Deep Comparison and Segmentation Network

Learning unknown objects in the environment is important for detection and manipulation tasks. Prior to learning the unknown objects the ground-truth labels have to be provided. The data annotation or labeling can be achieved in a number of ways but the most widely used method is still manual annotation. Although manual annotation has shown superior performance, it limits robots’ capabilities to known object instances and is also a time consuming task. This letter considers the aforementioned limitations and presents a method that allows robots to autonomously annotate objects from observations of human–object interactions. Specifically, we present a novel method that segments handheld objects in real-time using the class-agnostic deep comparison and segmentation network. The inputs to the network are the RGB-D data of known object template and a search space, and it outputs a pixel-wise label of the object and an objectness score. The score indicates the likelihood that the same object is present in both the inputs. The object template is manually initialized in the first frame and thereafter, the object is segmented and the template is updated online. The template is strategically updated using the likelihood score. The segmented object regions are accumulated as pseudo-ground-truth labels, which are used for object learning. The approach efficiently handles both rigid and highly deformable objects.
Mid-IR Supercontinuum Generation in Ultrafast Laser Inscribed Waveguides

Supercontinuum from 2.5 to 6.5 μm has been generated in ULI waveguides pumped with femtosecond pulses centered at 4.6 μm. Dispersion measurements show the zero dispersion wavelength for the waveguides to be around 5.3 μm.
3-D Measurement of Rollable Fiber Ribbons in 1000-Fiber Cable and Calculated Fiber Reliability

We propose a technique for the 3-D measurement of fiber position to allow the experimental evaluation of the fiber reliability of 1000-fiber high-density cables. We acquire the fiber positions from the position of peaks in a cross-sectional X-ray computed tomography image. We can evaluate the cable reliability by calculating the fiber strain imposed by bending and twisting from the fiber positions. To calculate the fiber strain, we also propose the models of the deformation of rollable optical fiber ribbon in a cable. The measured fiber positions coincide well with the deformation models that we proposed and revealed in which the calculated cable strains are almost the same as or lower than those that we estimated theoretically. Consequently, the equivalent strain is less than the allowable value needed for maintaining reliability when the other strain factors are the same as those of the conventional high-density cable.
High-quality, cost-effective facial motion capture pipeline with 3D regression

We present our improved marker-based facial motion capture pipeline that leverages on 3D regression from head-mounted camera (HMC) images to speed up and reduce the cost of high quality 3D marker tracking. We use machine learning to boost productivity by training regressors on traditionally tracked performances and applying those models to the remaining performances. Our specialized regressor for HMC marker-based tracking shows improvements in quality and robustness for marker tracks. The regressor results are automatically refined by a simple blob detection tool and then imported back into the tracking tool such that manual correction can be applied as needed and subsequently included as additional training data. This iterative approach reduces 70% the amount of artist time required for traditional tracking methods and does not add much setup time nor planning as alternative techniques.
Which BSSRDF model is better for heterogeneous materials?

We present an improved method for rendering heterogeneous translucent materials with existing BSSRDF models. In the general BSSRDF models, the optical properties of the target object are constant. Sone et al. have proposed a method to combine with existing BSSRDF models for rendering heterogeneous materials. However, the method generates more bright and blurred images compared with correctly simulated images. We have experimented with various BSSRDF models by the method and rendered heterogeneous materials. As a result, the rendered image with the better dipole model is the closest to the result of Monte carlo simulation. If incorporating the better dipole model into the method proposed by Sone et al., we can render more realistic images of heterogeneous materials.
Reduce the Wafer Warpage Introduced by Cu in RDL Through Adjusting the Cooling Temperatures

Wafer level chip scale package (WL-CSP) which is low cost and small size is becoming the mainstream of package form for the chip used in mobile devices. The processes are done on wafers, and the wafer warpage is severe after the redistribution layer (RDL). It is proved that the plastic deformation of copper during the thermal processes causes almost 1/3 of wafer warpage in RDL. In order to reduce the warpage caused by Cu, copper films deposited on the silicon wafers are cooled to extremely low temperatures such as -196°C after the thermal process. The wafer warpage of blank Cu film and Cu film passivated with SiNx is reduced by 65% and 93.5% after the cooling process, respectively. Besides, the stress in Cu film transforms from tensile to compressive, indicating an obvious plastic deformation occurred during cooling in liquid nitrogen. When changing the cooling temperature, the final wafer warpage at ambient temperature varies. The decreased wafer warpage is almost recovered after another thermal process. The stress-temperature curve coincides with the curve before cooling for the sample without passivation. As for the Cu film passivated with SiNx, the stress-temperature curve parallel moves downwards and roughly 10% of initial wafer warpage is reduced and unrecoverable.
Numerical Evaluation of Sensitivity of Microwave Metamaterial and Microstrip TL Sensors to Blood Glucose Concentration

In our previous paper, a metamaterial and microstrip transmission line sensors were designed for non-invasive blood glucose level monitoring. In this paper two different models of dielectric properties of blood glucose solutions are used to evaluate sensitivity of microwave metamaterial and microstrip TL sensors to blood glucose concentration by means of numerical simulations. Model A is adopted from literature and the model B was created by our group using information about dielectric properties of blood plasma-glucose solutions, recently published dielectric properties of red blood cell cytoplasm-glucose solutions and an electromagnetic mixing formula. Both sensors show smaller sensitivity for model B than for model A. Due to non-linear dependency of dielectric properties on glucose concentration predicted by model B a lower sensitivity for high glucose concentrations was observed. The metamaterial sensor shows more than to-times higher sensitivity than the microstrip sensor.
Momentum-based Balance Control for Torque-controlled Humanoids

In this contribution we propose a reformulation of a momentum-based balance controller originally proposed by Lee and Goswami. The advantage of our formulation is that we can guarantee that the control will satisfy any constraint in contact forces, joint accelerations and torque commands. Moreover, the formulation leads to an interesting insight into how equations of motion can be decoupled to significantly simplify the design of controllers based on the full robot dynamics. Finally, we present balancing experiments on a torque controlled humanoid robot. To the best of our knowledge, it is the first time that this momentum-based balance controller is implemented on a real robot, using a pure torque control approach.
Analgesic effect of AG490, a Janus kinase inhibitor, on oxaliplatin-induced acute neuropathic pain

Neuropathic pain often occurs during chemotherapy with oxaliplatin. AG490 has been shown to exert an antagonistic effect on inflammatory pain, but its effect on oxaliplatin-induced neuropathic pain remains poorly understood. This study sought to observe the analgesic effect of AG490 on acute neuropathic pain induced by a single oxaliplatin treatment and to address the possible mechanism. In this study, we established a model of oxaliplatin-induced acute neuropathic pain by intraperitoneal injection of 6 mg/kg oxaliplatin. On day 2 after injection, models were intraperitoneally injected with 1, 5, or 10 mg/kg AG490. Paw withdrawal threshold to mechanical stimuli and tail withdrawal latency to cold stimuli were determined. Western blot assay was performed to detect the expression of spinal phosphorylated signal transducer and activator of transcription 3 (p-STAT3). Immunohistochemistry was used to determine the immunoreactivity of p-STAT3 and interleukin-6. Results demonstrated that paw withdrawal threshold and tail withdrawal latency were significantly increased by the treatment of AG490 in rats. There was no significant difference in the effect among the different doses of AG490. AG490 10 mg/kg decreased the expression of p-STAT3, the immunoreactivity of p-STAT3 and interleukin-6 in spinal cord of acute neuropathic pain rats. These findings confirm that AG490 can attenuate oxaliplatin-induced acute neuropathic pain and is associated with the inhibition in the JAK/STAT3 signaling pathway.
Interpreting Recurrent and Attention-Based Neural Models: a Case Study on Natural Language Inference

Deep learning models have achieved remarkable success in natural language inference (NLI) tasks. While these models are widely explored, they are hard to interpret and it is often unclear how and why they actually work. In this paper, we take a step toward explaining such deep learning based models through a case study on a popular neural model for NLI. In particular, we propose to interpret the intermediate layers of NLI models by visualizing the saliency of attention and LSTM gating signals. We present several examples for which our methods are able to reveal interesting insights and identify the critical information contributing to the model decisions.
Transcriptome sequencing identifies key pathways and genes involved in gastric adenocarcinoma

The present study aimed to investigate the key pathways and genes associated with gastric adenocarcinoma via transcriptome sequencing. Five pairs of gastric adenocarcinoma tissue and normal tumor-adjacent tissue were harvested. After sequencing, raw data were processed and differentially expressed genes (DEGs) between tumor and control groups were screened, followed by functional enrichment analysis and gene clustering analysis. The effect of DEGs on patient prognosis was analyzed on the basis of the survival data from gastric adenocarcinoma patients in The Cancer Genome Atlas database. Several genes were validated through reverse transcription-quantitative polymerase chain reaction. In total, 1,477 upregulated and 282 downregulated DEGs were screened in tumor groups. These genes were segregated into four clusters. Genes in cluster 1 were significantly involved in metabolism of xenobiotics by cytochrome P450, genes in cluster 2 were majorly involved in apoptosis, tight junction formation, and platelet activation, genes in cluster 3 were primarily enriched in the p53 signaling pathway and genes in cluster 4 were significantly enriched in the insulin resistance pathway. Furthermore, 15 DEGs significantly influenced prognosis, including F2R, CTHRC1, and RASGRP3. The expression levels of CYP2B6, MAPK13, CTHRC, RASGRP3 and PYGM were consistent with our analysis results. In conclusion, pathways for metabolism of xenobiotics via cytochrome P450, apoptosis, tight junction formation, platelet activation, and insulin resistance may serve important roles in the progression of gastric adenocarcinoma. Notably, CTHRC1 and RASGRP3 may serve as key prognostic markers.
A hybrid approach for aspect‐oriented business process modeling

Separation of concerns has long been an important strategy to deal with complexity when developing a system. Some concerns (like security) are scattered through the whole system, and different modules are tangled to such concerns. These concerns are known as cross‐cutting concerns. When the system in question is a business process, cross‐cutting concerns are aimed at being encapsulated by Aspect‐Oriented Business Process Modeling. However, the state‐of‐the‐art techniques in this field lack efficient mechanisms that (1) support composition of cross‐cutting concerns that can be defined in parallel to (a part of) a process model and (2) enable specifying both mandatory and optional cross‐cutting concerns. To address these limitations, this paper proposes a new Aspect‐Oriented Business Process Modeling approach. The approach is hybrid since it is based on declarative rules to relate imperative cross‐cutting concerns and imperative business process models. The approach is explained, formally grounded with precise semantics, and used accordingly to implement the artifacts that support modeling and enactment of business processes in the proposed fashion as a proof of concept. In addition, the approach is evaluated on the basis of the Technology Acceptance Model during a workshop session. The result shows that participants perceived the approach usable and easy to use.