Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhanced kinematic model for dexterous manipulation with an underactuated hand

Recent studies on underactuated manipulation usually describe the system with a Kinematic Model (KM), which is built by adding external constraints to the standard manipulation analysis method. However, such external constraints are easily violated in a real-world dexterous manipulation task which results in significant control errors. In this work, the Enhanced Kinematic Model (E-KM), an integrated model of the KM and the Sparse Online Gaussian Process (SOGP) is proposed. The E-KM can compensate the shortfalls of the KM by on-the-fly training the SOGP on the residual between the prediction of the KM and the ground truth data. Based on the E-KM, we further contribute an optimal controller for underactuated manipulations. This optimal E-KM controller is implemented and tested on the iCub, a humanoid robot with two anthropomorphic underactuated hands. Two sets of real-world experiments are carried out to verify our method. The results demonstrate that the controller using E-KM statistically can achieve higher control accuracy than using solely using the KM for a wide range of objects.
αVβ3-Integrin Relocalizes nectin1 and Routes Herpes Simplex Virus to Lipid Rafts

ABSTRACT Herpes simplex virus (HSV) enters cells by fusion at plasma membranes or endosomes. Cellular factors route the virus to different pathways. αVβ3-integrin directs HSV to a lipid raft and acidic endosome pathway. We report that infection mediated by nectin1 plus αVβ3-integrin exhibits the same characteristics as entry mediated by raft-located forms of nectin. αVβ3-integrin relocalizes nectin1 to lipid rafts, independently of virus. Thus, HSV routing to the lipid raft-dependent pathway is consequent to the integrin-induced relocalization of nectin1. Inhibition by the Na+/H+ exchanger 5-(N-ethyl-N-isopropyl)amirolide suggests that αVβ3-integrin overexpression favors HSV macropinocytic uptake in some cells but not in others.
Resolution of anti-neutrophil cytoplasmic antibody-associated vasculitis after resection of gastric cancer

We report a case of anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis in a 62-year-old patient with gastric cancer. The myeloperoxidase–anti-neutrophil cytoplasmic antibody (MPO–ANCA) level was threefold above normal preoperatively. Vasculitis was seen on renal biopsy. Gastric resection revealed well-differentiated adenocarcinoma and vasculitis. The MPO–ANCA level returned to normal post-operatively. Although ANCA-associated vasculitis occasionally accompanies malignant tumors, this is the first documented case of concurrent gastric cancer-associated and ANCA-associated vasculitis, with post-operative resolution of the vasculitis.
Automatic lung segmentation in the presence of alveolar collapse

Abstract Lung ventilation and perfusion analyses using chest imaging methods require a correct segmentation of the lung to offer anatomical landmarks for the physiological data. An automatic segmentation approach simplifies and accelerates the analysis. However, the segmentation of the lungs has shown to be difficult if collapsed areas are present that tend to share similar gray values with surrounding non-pulmonary tissue. Our goal was to develop an automatic segmentation algorithm that is able to approximate dorsal lung boundaries even if alveolar collapse is present in the dependent lung areas adjacent to the pleura. Computed tomography data acquired in five supine pigs with injured lungs were used for this purpose. First, healthy lung tissue was segmented using a standard 3D region growing algorithm. Further, the bones in the chest wall surrounding the lungs were segmented to find the contact points of ribs and pleura. Artificial boundaries of the dorsal lung were set by spline interpolation through these contact points. Segmentation masks of the entire lung including the collapsed regions were created by combining the splines with the segmentation masks of the healthy lung tissue through multiple morphological operations. The automatically segmented images were then evaluated by comparing them to manual segmentations and determining the Dice similarity coefficients (DSC) as a similarity measure. The developed method was able to accurately segment the lungs including the collapsed regions (DSCs over 0.96).
Combining Optimizations , Combining Theories

We consider the problem of how best to combine optimizations in imperative compilers. It is known that combined optimizations (or \super-analyses") can be strictly better than iterating separate improvement passes. We propose an explanation of why this is so by drawing connections between program analysis and the algebraic and coalgebraic views of programs and processes. We argue that \optimistic" analyses decide coinductively-de ned relations and are based on bisimilarity. We relate combining program improvements to the problem of deciding combinations of theories. Iterating program improvements is similar to the Nelson-Oppen method of deciding combined theories: in Nelson-Oppen decision procedures communicate equalities, and iterated improvement passes implicitly communicate equalities via term replacements. To decide combined theories of bisimilarity, some \co-NelsonOppen" procedure is needed that propagates inequalities amongst decision procedures. Hence, iterating optimistic analyses fails to be e ective because inequalities cannot be communicated by semantics-preserving rewrites. Superanalysis is conjectured to overcome this failing by behaving like a \co-Nelson-Oppen" decision procedure.
Efficient Online and Batch Learning Using Forward Backward Splitting

We describe, analyze, and experiment with a framework for empirical loss minimization with regularization. Our algorithmic framework alternates between two phases. On each iteration we first perform an unconstrained gradient descent step. We then cast and solve an instantaneous optimization problem that trades off minimization of a regularization term while keeping close proximity to the result of the first phase. This view yields a simple yet effective algorithm that can be used for batch penalized risk minimization and online learning. Furthermore, the two phase approach enables sparse solutions when used in conjunction with regularization functions that promote sparsity, such as l1. We derive concrete and very simple algorithms for minimization of loss functions with l1, l2, l22, and l∞ regularization. We also show how to construct efficient algorithms for mixed-norm l1/lq regularization. We further extend the algorithms and give efficient implementations for very high-dimensional data with sparsity. We demonstrate the potential of the proposed framework in a series of experiments with synthetic and natural data sets.
Clonal analysis reveals nerve-dependent and independent roles on mammalian hind limb tissue maintenance and regeneration

Significance In Urodeles, surgical denervation before limb amputation results in regeneration failure. Here we explored the dependency of the peripheral nervous system on tissue replacement in mammalian appendages by performing a comprehensive clonal analysis of hind limb tissues devoid of nerve supply. Our experiments uncover conserved phenotypes, which mimic clinical observations of patients with nerve damage resulting from spinal cord injury. Our system could be used to better understand both pathophysiology and treatment of patients with spinal cord injury. The requirement and influence of the peripheral nervous system on tissue replacement in mammalian appendages remain largely undefined. To explore this question, we have performed genetic lineage tracing and clonal analysis of individual cells of mouse hind limb tissues devoid of nerve supply during regeneration of the digit tip, normal maintenance, and cutaneous wound healing. We show that cellular turnover, replacement, and cellular differentiation from presumed tissue stem/progenitor cells within hind limb tissues remain largely intact independent of nerve and nerve-derived factors. However, regenerated digit tips in the absence of nerves displayed patterning defects in bone and nail matrix. These nerve-dependent phenotypes mimic clinical observations of patients with nerve damage resulting from spinal cord injury and are of significant interest for translational medicine aimed at understanding the effects of nerves on etiologies of human injury.
Dietary Intake of Heterocyclic Amines and Benzo(a)Pyrene: Associations with Pancreatic Cancer

Objective: Heterocyclic amines (HCA) and polycyclic aromatic hydrocarbons, formed in temperature- and time-dependent manners during the cooking of meat, are mutagens and carcinogens. We sought to assess the association between dietary intake of HCA and benzo(a)pyrene [B(a)P] and exocrine pancreatic cancer in a population-based case-control study. Methods: Subjects (193 cases and 674 controls) provided information on their usual meat intake and preparation method, e.g., stewed, fried, or grilled/barbecued, etc. Meat doneness preferences were measured using photographs that showed internal doneness and external brownness. We used a meat-derived HCA, B(a)P, and mutagen database with a questionnaire to estimate intake of PhIP, DiMeIQx, MeIQx, B(a)P, and mutagenic activity (revertants/g of daily meat intake). Data were analyzed with unconditional logistic regression. Results: In analyses adjusted for age, sex, smoking, education, race, and diabetes, the odds ratio and 95% confidence interval for the highest compared with the lowest quintile were as follows: PhIP, 1.8 (1.0-3.1); DiMeIQx, 2.0 (1.2-3.5); MeIQx, 1.5 (0.9-2.7); B(a)P, 2.2 (1.2-4.0); and mutagenic activity, 2.4 (1.3-4.3). Conclusions: HCAs and B(a)P from well-done barbecued and pan-fried meats may be associated with increased risk for pancreatic cancer.
Allocation of Returned Products among Different Recovery Options through an Opportunity Cost-Based Dynamic Approach

In a make-to-order product recovery environment, we consider the allocation decision for returned products decision under stochastic demand of a firm with three options: refurbishing to resell, parts harvesting, and recycling. We formulate the problem as a multiperiod Markov decision process (MDP) and present a linear programming (LP) approximation that provides an upper bound on the optimal objective function value of the MDP model. We then present two solution approaches to the MDP using the LP solution: a static approach that uses the LP solution directly and a dynamic approach that adopts a revenue management perspective and employs bid-price controls technique where the LP is resolved after each demand arrival. We calculate the bid prices based on the shadow price interpretation of the dual variables for the inventory constraints and accept a demand if the marginal value is higher than the bid price. Since the need for solving the LP at each demand arrival requires a very efficient solution procedure, we present a transportation problem formulation of the LP via variable redefinitions and develop a one-pass optimal solution procedure for it. We carry out an extensive numerical analysis to compare the two approaches and find that the dynamic approach provides better performance in all of the tested scenarios. Furthermore, the solutions obtained are within 2% of the upper bound on the optimal objective function value of the MDP model.
Self-Organization in Overlay Networks

Overlay networks are an important kind of P2P infrastructures. The range of applications and requirements is broad. Consequently, our research objective are overlay networks which organize and adapt themselves at runtime. This article describes the current state of our project and gives an overview of the steps envisioned. We briefly show the necessity for self-organization in overlay networks. Based on our experience, we then provide a list of overlay network system parameters relevant for dynamic adjustment. When designing mechanisms for self-adaptation for overlay networks, we have observed implementationlevel interference and semantic-level interference. To deal with these phenomena, the overlay network architecture envisioned (1) must separate functionality for self-organization and system core functionality and (2) should preserve system integrity. To achieve this, we propose to use self-tuning mechanisms with explicit preand postconditions and conflict resolution as well as reflection. We discuss alternative implementation techniques and present one concrete approach based on AspectOriented Programming and Mixin Layers. We conclude with first insights into organic overlay networks and emergent behavior.
Subtyping patterns for active objects

Subtyping relations for object-oriented formalisms describe relationships between superand subclasses which satisfy the substitutability requirement imposed on types and their subtypes. For active objects with an associated behaviour description subtyping relations also have to guarantee substitutability with respect to the dynamic behaviour of classes. In this paper, we give subtyping patterns for integrated object-oriented formalisms, that is, with a description of a static as well as a dynamic part. The patterns can be used to obtain subtypes by construction without computing the semantics of classes at all.
Patterned Array of Poly(ethylene glycol) Silane Monolayer for Label-Free Detection of Dengue

In the present study, the construction of arrays on silicon for naked-eye detection of DNA dengue was demonstrated. The array was created by exposing a polyethylene glycol (PEG) silane monolayer to 254 nm ultraviolet (UV) light through a photomask. Formation of the PEG silane monolayer and photomodifed surface properties was thoroughly characterized by using atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS), and contact angle measurements. The results of XPS confirmed that irradiation of ultraviolet (UV) light generates an aldehyde functional group that offers conjugation sites of amino DNA probe for detection of a specific dengue virus target DNA. Employing a gold enhancement process after inducing the electrostatic interaction between positively charged gold nanoparticles and the negatively charged target DNA hybridized to the DNA capture probe allowed to visualize the array with naked eye. The developed arrays demonstrated excellent performance in diagnosis of dengue with a detection limit as low as 10 pM. The selectivity of DNA arrays was also examined using a single base mismatch and noncomplementary target DNA.
Automated Chinese Essay Scoring using Vector Space Models

This paper presents experiments using several vector space models in Automated Essay Scoring (AES). Firstly, we compare four different Vector Space Models (VSM) which are the Word-based Vector Space Model (W-VSM), the Weight Adapted Word-based Vector Space Model (WAW-VSM), the Latent Semantic-based Vector Space Model (LS-VSM) and the Sequence Latent Semantic-based Vector Space Model (SLS-VSM). The results show that the WAW-VSM with the addition of word relation information is better than the W-VSM, while the SLS-VSM is also better than the LS-VSM by considering the sequence information in document representation. After that, we add some statistical surface features in the experiments. With the application of Support Vector Regression (SVR), the final machine score is generated. The correlation between the machine score and the human score reaches that between two human scores in average.
View makes a difference: Presenting human figures from the back or front affects mental spatial transformations of children and adults

Previous research suggested that performance in spatial judgments involving rotated human figures is poorer if these figures are presented from the front than from the back. We further investigated this effect, controlling for visible facial information in front and back view by presenting figures' faces as profile. Children's and adults' judgments were still faster and less error prone if figures were presented from the back. Moreover, reaction times indicated that participants did not mentally rotate figures in front view. Children performed overall more poorly than adults, but there were also qualitative differences suggesting that children are more susceptible to embodiment effects than adults. This study underlines that embodiment may have differential effects in spatial transformation tasks, enhancing or impairing performance.
Sooty Mould Disease Caused by Leptoxyphium kurandae on Kenaf

Abstract In September 2013, we discovered sooty mould growing on kenaf with the extrafloral nectaries in Iksan, Korea and identified the causative fungus as Leptoxyphium kurandae based on morphological characteristics and phylogenetic analyses. This is the first report of sooty mould caused by L. kurandae on kenaf in Korea and globally.
Modeling Litz-wire winding losses in high-frequency power inductors

The parasitic effects in stranded, twisted, and Litz wire windings operating at high frequencies are studied. The skin and proximity effects that cause the winding parasitic resistance of an inductor to increase with the operating frequency are considered. An expression for the AC resistance as a function of the operating frequency is given. The measured and calculated values of the inductor AC resistance and quality factor are plotted versus frequency and compared. The theoretical results were in good agreement with those experimentally measured.
Detection of fastener loosening in simple lap joint based on ultrasonic wavefield imaging

Joints in aero-mechanical structures are critical elements that ensure the structural integrity but they are prone to damages. Inspection of such joints that have no prior baseline data is really challenging but it can be possibly done using the Ultrasonic Propagation Imager (UPI). The feasibility of applying UPI for detection of loosened fastener is investigated in this study. A simple lap joint specimen made by connecting two pieces of 2.5mm thick SAE304 stainless steel plates using five M6 screws and nuts has been used in this study. All fasteners are tightened to 10Nm but one of them is completely loosened to simulate the damage. The wavefield data is processed into ultrasonic wavefield propagation video and a series of spectral amplitude images. The spectral images showed noticeable amplitude difference at the loosened fastener, hence confirmed the feasibility of using UPI for structural joints inspection. A simple contrast maximization method is also introduced to improve the result.
Role of the Primary Motor and Dorsal Premotor Cortices in the Anticipation of Forces during Object Lifting

When lifting small objects, people apply forces that match the expected weight of the object. This expectation relies in part on information acquired during a previous lift and on associating a certain weight with a particular object. Our study examined the role of the primary motor and dorsal premotor cortices in predicting weight based either on information acquired during a previous lift (no-cue experiment) or on arbitrary color cues associated with a particular weight (cue experiment). In the two experiments, subjects used precision grip to lift two different weights in a series of trials both before and after we applied low-frequency repetitive transcranial magnetic stimulation over the primary motor and dorsal premotor cortices. In the no-cue experiment, subjects did not receive any previous information about which of two weights they would have to lift. In the cue experiment, a color cue provided information about which of the two weights subjects would have to lift. Our results demonstrate a double dissociation in the effects induced by repetitive stimulation. When applied over the primary motor cortex, repetitive stimulation disrupted the scaling of forces based on information acquired during a previous lift. In contrast, when applied over the dorsal premotor cortex, repetitive stimulation disrupted the scaling of forces based on arbitrary color cues. We conclude that the primary motor and dorsal premotor cortices have unique roles during the anticipatory scaling of forces associated with the lifting of different weights.
Stabilized Dye–Pigment Formulations with Platy and Tubular Nanoclays

Alumosilicate materials of different morphologies, such as platy and tubule nanoclays, may serve as an efficient, protective encasing for colored organic substances and nanoparticles. The adsorption of dyes onto the nanoclays increases their stability against thermal, oxidative, and acid–base‐induced decomposition. Natural organic dyes form stable composites with clays, thus allowing for “green” technology in production of industrial nanopigments. In the presence of high‐surface‐area alumosilicate materials, semiconductor nanoparticles known as quantum dots are stabilized against agglomeration during their colloid synthesis, resulting in safe colors. The highly dispersed nanoclays such as tubule halloysite can be employed as biocompatible carriers of quantum dots for the dual labeling of living human cells—both for dark‐field and fluorescence imaging. Therefore, complexation of dyes with nanoclays allows for new, stable, and inexpensive color formulations.
Focusing Extreme Programming on Usability

Agile methods such as extreme programming are becoming increasingly important for the rapid development of software applications. They proofed to be applicable and beneficial for a variety of domains. Nevertheless, due to the iterative nature of these approaches, software developers focus on functional aspects and tend to neglect nonfunctional characteristics, like usability. This paper addresses this issue by providing an extension suggestion for extreme programming that helps the on-site customer and development team to take into account usability. Usability criteria are attached to user stories, and a new type of user stories, called usability stories are introduced. This also influences the way on-site customers perform the acceptance test. We present first results of a case study where small changes to extreme programming have been introduced. The benefits were an increased perception of usability due to the integration into the user stories and an early evaluation of usability criteria in the acceptance test. Eventually, these measures lead to a high usability of the software system.
Industrial Strength Software Development Environments

‘‘Industrial strength’’ software development environments (SDEs) must provide facilities to address three essential properties of multi-developer software systems: evolution, complexity and scale. It is my contention that in order to be an industrial strength SDE, an environment must support at least a city model environment. Moreover, SDEs must include such high level policies as supporting cooperation and communication, supporting a unified process and product, providing multiple means of expression, supporting interand intraconnections, managing the change process and managing the multiplicity of versions. Underlying the implementation of these policies are three themes: developer-machine symbiosis in which the machine becomes an active partner in system development and evolution; formalization of the development/evolution process so that we can reason about the process and automate its support; and finally, formalization of the software product so that we can reason about it and automate its support. Invited Keynote Presentation for the Software Engineering Track 11th World Computer Congress IFIP ’89 August 28 September 1, 1989 San Francisco CA