Miracle-dz/UniFAR-FTUs huggingface dataset:
Organ Transplantation Policy Evaluation

This paper on the UNOS Liver Allocation Model (uLAM) describes the building of a simulation model that supports policy evaluation for a national medical problem. The modeling and simulation techniques used in building ULAM include: fitting donor and patient arrival processes having trend and cyclic rate components using non-homogeneous Poisson processes (NEIPPs) having exponential rate fimctions which may include both a polynomial and some trigonometric components; fitting distributions to data on transition times between states of medical urgen~, application of variance reduction techniques using common random-number streams and prior information, organizing data structures for efficient file searching and ranking capabilities; the use of bootstrapping techniques for attribute sampling; the building of submodels employing biostatistical procedures such as ISaplan-Meier and logistic regression; and the characterization of performance measures within a complex political, economic and social environment. ULAM provides a means for producing quantitative information to support the selection of a liver allocation policy. 1 DESCRIPTION OF THE MEDICAL PROBLEM Organs for transplantation are a scarce resource. The number of people who donate organs has not kept pace with increasing demand. Thousands of people wait for organs every year, with many dying while they wait. The list of waiting patients continues to grow at a faster rate than the number of donors. How to allocate such a scarce and valuable resource is indeed complex. Much is at stake among doctors, Organ Procurement Organizations (OPOS), transplant centers, and, without question, the potential recipients. Issues revolve around what is an equitable, efficient and effective means of organ distribution, that is, the trade-off between medical utility and justice among patients. 2 SYSTEM ENVIRONMENT In 1987, the United Network for Organ Sharing (UNOS) was formed to develop and operate a nationwide system to allocate human organs to potential recipients. To this day, UNOS has maintained a leadership position in helping to establish and execute organ allocation policies in the United States. The national system for collecting data on patients and organs, called the Organ Procurement Transplantation Network (OPTN), is operated by 1314 Organ Transplantation Policy Evaluation 1315 UNos. Organ allocation policies are constantly reviewed and changed to reflect the accelerated advances being made in science, medicine and communications. These changes are regularly reviewed and modified to ensure equity among those in the transplantation community and to instill cotildence in the community at large. Many issues arise with organ allocation. What may maximize medical benefit for one …
Fast and accurate computation of surface normals from range images

The fast and accurate computation of surface normals from a point cloud is a critical step for many 3D robotics and automotive problems, including terrain estimation, mapping, navigation, object segmentation, and object recognition. To obtain the tangent plane to the surface at a point, the traditional approach applies total least squares to its small neighborhood. However, least squares becomes computationally very expensive when applied to the millions of measurements per second that current range sensors can generate. We reformulate the traditional least squares solution to allow the fast computation of surface normals, and propose a new approach that obtains the normals by calculating the derivatives of the surface from a spherical range image. Furthermore, we show that the traditional least squares problem is very sensitive to range noise and must be normalized to obtain accurate results. Experimental results with synthetic and real data demonstrate that our proposed method is not only more efficient by up to two orders of magnitude, but provides better accuracy than the traditional least squares for practical neighborhood sizes.
New Partition Factor Calculations for Evaluating the Damage of Low Energy Ions in Silicon

The analysis of Lindhard's calculations of the partition factor Q and the corresponding factor obtained from the SRIM calculations shows that both significantly underestimate the energy losses to damage for ions below 100 keV. This is the result of their overestimation of the electronic losses of such ions in matter. New partition factor for low energy (<500 keV) ions in silicon is calculated by a specially developed Monte Carlo code. The new Q-values are significantly larger than previous results. This brings them to a good agreement with the experimental data including recently published precise ionization measurements using silicon based photodiodes. We used the new partition factor for calculating the non-ionizing energy losses (NIEL) for electrons and protons. The resulted NIEL values are larger by 15% on the average compared to the published calculated data
New trends in aptamer-based electrochemical biosensors

Summary The analytical characteristics of aptamers are comparable with those of antibodies for the development of biosensor technology. However, aptamers offer some crucial advantages over antibodies such as selection capability for a variety of targets, easy synthesis, improved reproducibility and stability, simple modification for immobilization to solid supports and enhanced selectivity. This article reviews aptamer technology as well as aptamer-based assay configurations and goes on to explore reported applications in electrochemical aptasensors.
Viral vector-based reversible neuronal inactivation and behavioral manipulation in the macaque monkey

Viral vectors are promising tools for the dissection of neural circuits. In principle, they can manipulate neurons at a level of specificity not otherwise achievable. While many studies have used viral vector-based approaches in the rodent brain, only a few have employed this technique in the non-human primate, despite the importance of this animal model for neuroscience research. Here, we report evidence that a viral vector-based approach can be used to manipulate a monkey's behavior in a task. For this purpose, we used the allatostatin receptor/allatostatin (AlstR/AL) system, which has previously been shown to allow inactivation of neurons in vivo. The AlstR was expressed in neurons in monkey V1 by injection of an adeno-associated virus 1 (AAV1) vector. Two monkeys were trained in a detection task, in which they had to make a saccade to a faint peripheral target. Injection of AL caused a retinotopic deficit in the detection task in one monkey. Specifically, the monkey showed marked impairment for detection targets placed at the visual field location represented at the virus injection site, but not for targets shown elsewhere. We confirmed that these deficits indeed were due to the interaction of AlstR and AL by injecting saline, or AL at a V1 location without AlstR expression. Post-mortem histology confirmed AlstR expression in this monkey. We failed to replicate the behavioral results in a second monkey, as AL injection did not impair the second monkey's performance in the detection task. However, post-mortem histology revealed a very low level of AlstR expression in this monkey. Our results demonstrate that viral vector-based approaches can produce effects strong enough to influence a monkey's performance in a behavioral task, supporting the further development of this approach for studying how neuronal circuits control complex behaviors in non-human primates.
Bone marrow transplantation reproduces the tristetraprolin-deficiency syndrome in recombination activating gene-2 (-/-) mice. Evidence that monocyte/macrophage progenitors may be responsible for TNFalpha overproduction.

Tristetraprolin-deficient [TTP (-/-)] mice exhibit a complex syndrome of myeloid hyperplasia, cachexia, dermatitis, autoimmunity, and erosive arthritis. Virtually the entire syndrome can be prevented by the repeated injection of anti-TNFalpha antibodies (Taylor, G.A., E. Carballo, D.M. Lee, W.S. Lai, M.J. Thompson, D.D. Patel, D.I. Schenkman, G.S. Gilkeson, H.E. Broxmeyer, B.F. Haynes, and P.J. Blackshear. 1996. Immunity. 4:445-454). In the present study, we transplanted bone marrow from TTP (-/-) and (+/+) mice into recombination activating gene-2 (-/-) mice. After a lag period of several months, marrow transplantation from the (-/-) but not the (+/+) mice resulted in the full syndrome associated with TTP deficiency, suggesting that hematopoietic progenitors are responsible for the development of the syndrome. Western blot analysis of supernatants from cultured TTP-deficient macrophages derived from the peritoneal cavity or bone marrow of adult TTP (-/-) mice, or from fetal liver, demonstrated an increased accumulation of TNFalpha after stimulation with LPS compared to control cells, and also increased accumulation of TNFalpha mRNA. This difference was not observed with cultured fibroblasts or T and B lymphocytes. These data suggest that macrophages are among the cells responsible for the effective excess of TNFalpha that leads to the pathology reported in TTP (-/-) animals, and that macrophage progenitors may be involved in the transplantability of this syndrome.
Facultative Nectar-Feeding Behavior in a Gleaning Insectivorous Bat (Antrozous pallidus)

Abstract Foraging plasticity that includes facultative nectarivory is extremely rare in temperate insectivorous bats. We investigated flower-visiting behavior of pallid bats (Antrozous pallidus, Vespertilionidae) to bat-adapted flowers of cardon cacti (Pachycereus pringlei) to determine whether pallid bats consume floral nectar or visit flowers to opportunistically glean insects attracted to flowers. In 2007 and 2008, we recorded flower-visiting behavior of bats using infrared videography on 143 cactus-nights across 14 sites in Baja California, Mexico. Pallid bats were regular visitors to cardon flowers and consumed floral nectar by plunging their faces into the corolla to lap pooled nectar. We recorded 1,198 flower visits by A. pallidus, which accounted for 10% of visits to flowers by all bats. Pallid bats visited flowers on 57% of cactus-night observations (n = 81/143) and 52% (n = 28/54) of captured bats had visible pollen loads. Flower-visiting activity by A. pallidus was concentrated early in the evening where nectarivorous Mexican lesser long-nosed bats (Leptonycteris yerbabuenae [ = curasoae], Phyllostomidae) were present, but more evenly distributed throughout the night at sites without L. yerbabuenae, suggesting potential competitive exclusion among these nocturnal chiropteran pollinators.
Formation of TiO2 based nanoribbons and the effect of post-annealing on its photocatalytic activity

The formation of TiO2 based nanoribbons via alkaline hydrothermal methods and the post-annealing effect on its photocatalytic activity were investigated. The structure features and physical properties were characterized using X-ray diffraction (XRD), Scanning Electron Microscope (SEM) and Fourier-transform infrared (FTIR). The result shows that the morphology evolution of starting material (TiO2 nanopowder) into TiO2 based nanoribbons is initiated at low temperature (100°C), while the structure transformation occurred at higher temperatures (150-180°C). The process includes formation of layered titanate and dissolution-crystallisation with the ion exchange. The post-annealing process applied to the TiO2 based nanoribbons improves its photocatalytic activity as it provides more active sites. The nanoribbon annealed at 500°C possesses high photocatalytic activity with kinetics constant of 0.082/min.
Speech Compression Using LPC-10 and VELPC Based on DCT Technique Compression

: In this paper, we have presented the speech compression techniques i.e. Linear Predictive Coding and its modified version Voice Excited Linear Predictive Coding. Output of LPC-10 is compared with output of VELPC. Here instead of using plain VELPC we are using modified VELPC or we can say that VELPC based on Discrete Cosine Transform technique. The result shown here was obvious since VELPC is modified version of LPC and so its output quality is better as compared to output quality of LPC. LPC is one of the most powerful speech coding techniques and it is widely used for encoding speech signal at a very low bit rate. Pitch period estimation is the weakest link in the LPC method so this drawback is eliminated in VELPC technique. Thus, the bit rate however is somewhat increased in VELPC technique. Therefore Discrete Cosine Transform is used to compress the innovation signal in case of VELPC in order to reduce bit rate to some extent.
Dual band power divider for wlan applications

This paper proposes a dual band power divider for WLAN applications. The design is modified to improve the performance characteristics. The output ports of the divider are designed by taking extended lines. The modified version gives an improvement in return loss and thus exhibits enhanced transmission. The impedance of the extended lines is obtained from the average value of bi-section impedance transformers using the Cheng design. Proposed circuit exhibits equal power division at WLAN frequencies 2.45 GHz and 5GHz. An improved return loss is obtained at WLAN frequency.
Scalable Matching of Industry Models - a Case Study

A recent approach to the problem of ontology matching has been to convert the problem of ontology matching to information retrieval. We explore the utility of this approach in matching model elements of real UML, ER, EMF and XML-Schema models, where the semantics of the models are less precisely defined. We validate this approach with domain experts for industry models drawn from very different domains (healthcare, insurance, and banking). We also observe that in the field, manually constructed mappings for such large industry models are prone to serious errors. We describe a novel tool we developed to detect suspicious mappings to quickly isolate these errors.
High-rate vector quantization for the Neyman-Pearson detection of some stationary mixing processes

This paper investigates the decentralized detection of spatially correlated processes using the Neyman-Pearson test. We consider a network formed by a large number of sensors, each of them observing a random data vector. Sensors' observations are non-independent, but form a stationary process verifying mixing conditions. Each vector-valued observation is quantized before being transmitted to a fusion center which makes the final decision. For any false alarm level, it is shown that the miss probability of the Neyman-Pearson test converges to zero exponentially as the number of sensors tends to infinity. A compact closed-form expression of the error exponent is provided in the high-rate regime i.e., when fine quantization is applied. As an application, our results allow to determine relevant quantization strategies which lead to large error exponents.
Efficacy of bronchoscopic lung volume reduction: a meta-analysis

Background Over the last several years, the morbidity, mortality, and high costs associated with lung volume reduction (LVR) surgery has fuelled the development of different methods for bronchoscopic LVR (BLVR) in patients with emphysema. In this meta-analysis, we sought to study and compare the efficacy of most of these methods. Methods Eligible studies were retrieved from PubMed and Embase for the following BLVR methods: one-way valves, sealants (BioLVR), LVR coils, airway bypass stents, and bronchial thermal vapor ablation. Primary study outcomes included the mean change post-intervention in the lung function tests, the 6-minute walk distance, and the St George’s Respiratory Questionnaire. Secondary outcomes included treatment-related complications. Results Except for the airway bypass stents, all other methods of BLVR showed efficacy in primary outcomes. However, in comparison, the BioLVR method showed the most significant findings and was the least associated with major treatment-related complications. For the BioLVR method, the mean change in forced expiratory volume (in first second) was 0.18 L (95% confidence interval [CI]: 0.09 to 0.26; P<0.001); in 6-minute walk distance was 23.98 m (95% CI: 12.08 to 35.88; P<0.01); and in St George’s Respiratory Questionnaire was -8.88 points (95% CI: −12.12 to −5.64; P<0.001). Conclusion The preliminary findings of our meta-analysis signify the importance of most methods of BLVR. The magnitude of the effect on selected primary outcomes shows noninfe-riority, if not equivalence, when compared to what is known for surgical LVR.
International Journal of Advanced Robotic Systems Safety Supervisory Strategy for an Upper-limb Rehabilitation Robot Based on Impedance Control

which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract User security is an important consideration for robots that interact with humans, especially for upper‐limb rehabilitation robots, during the use of which stroke patients are often more susceptible to injury. In this paper, a novel safety supervisory control method incorporating fuzzy logic is proposed so as to guarantee the impaired limb's safety should an emergency situation occur and the robustness of the upper‐limb rehabilitation robot control system. Firstly, a safety supervisory fuzzy controller (SSFC) was designed based on the impaired‐limb's real‐time physical state by extracting and recognizing the impaired‐limb's tracking movement features. Then, the proposed SSFC was used to automatically regulate the desired force either to account for reasonable disturbance resulting from pose or position changes or to respond in adequate time to an emergency based on an evaluation of the impaired‐limb's physical condition. Finally, a position‐based impedance controller was implemented to achieve compliance between the robotic end‐effector and the impaired limb during the robot‐ assisted rehabilitation training. The experimental results show the effectiveness and potential of the proposed method for achieving safety and robustness for the rehabilitation robot.
Scalable Mammogram Retrieval Using Composite Anchor Graph Hashing With Iterative Quantization

Content-based image retrieval (CBIR) shows great significance in clinical decision-making, which explores the visual content of medical images rather than keywords, tags, or descriptions. It provides doctors an image-guided approach to explore relevant cases that could offer doctors instructive reference. Mammogram screening has been known to be widely used in the early stage diagnosis of breast cancer and could reduce its morbidity and mortality. In this paper, we aim to develop a scalable CBIR method for a large repository of mammogram. To this end, we extend the original Anchor Graph Hashing (AGH) and propose a new unsupervised hashing algorithm, named as composite AGH with iterative quantization (C-AGH-ITQ), which compresses mammographic regions of interest (ROIs) into compact binary codes and enables real-time searching in Hamming space. Multimodal features and different distance metrics are integrated, performing upon a composite Anchor Graph. To improve the effectiveness of the hash code, quantization error is further iteratively minimized by introducing an orthogonal rotation matrix. We evaluate the presented C-AGH-ITQ algorithm on a data set of 11 533 mammographic ROIs obtained from the Digital Database for Screening Mammography. Our method obtains more than 84% retrieval precision and 93% classification accuracy (using $k$ NN prediction), which demonstrates that hash codes produced by C-AGH-ITQ well capture the visual similarities between mammographic images. In addition, since C-AGH-ITQ ensures linear complexity of the training procedure and constant time for query, our system is readily applicable to large-scale mammogram databases and has the potential to provide abundant clinical cases as reference.
Constrained Parametric Proposals and Pooling Methods for Semantic Segmentation in RGB-D Images

We focus on the problem of semantic segmentation based on RGB-D data, with emphasis on analyzing cluttered indoor scenes containing many instances from many visual categories. Our approach is based on a parametric figure-ground intensity and depth-constrained proposal process that generates spatial layout hypotheses at multiple locations and scales in the image followed by a sequential inference algorithm that integrates the proposals into a complete scene estimate. Our contributions can be summarized as proposing the following: (1) a generalization of parametric max flow figure-ground proposal methodology to take advantage of intensity and depth information, in order to systematically and efficiently generate the breakpoints of an underlying spatial model in polynomial time, (2) new region description methods based on second-order pooling over multiple features constructed using both intensity and depth channels, (3) an inference procedure that can resolve conflicts in overlapping spatial partitions, and handles scenes with a large number of objects category instances, of very different scales, (4) extensive evaluation of the impact of depth, as well as the effectiveness of a large number of descriptors, both pre-designed and automatically obtained using deep learning, in a difficult RGB-D semantic segmentation problem with 92 classes. We report state of the art results in the challenging NYU Depth v2 dataset, extended for RMRC 2013 Indoor Segmentation Challenge, where currently the proposed model ranks first, with an average score of 24.61% and a number of 39 classes won. Moreover, we show that by combining second-order and deep learning features, over 15% relative accuracy improvements can be additionally achieved. In a scene classification benchmark, our methodology further improves the state of the art by 24%.
Simple Surfactant Concentration-Dependent Shape Control of Polyhedral Fe3 O4 Nanoparticles and Their Magnetic Properties.

The shape and size of monodisperse Fe3 O4 nanoparticles (NPs) are controlled using a chemical solution synthesis in the presence of the surfactant cetylpyridinium chloride (CPC). Cubic Fe3 O4 NPs surrounded by six {100} planes are obtained in the absence of CPC. Increasing the CPC content during synthesis causes the shape of the resulting Fe3 O4 NPs to change from cubic to truncated cubic, cuboctahedral, truncated octahedral, and finally octahedral. During this evolution, the predominantly exposed planes of the Fe3 O4 NPs vary from {100} to {111}. The shape control results from the synergistic effect of the pyridinium cations, chloride anions, and long-chain alkyl groups of CPC, which is confirmed by comparison with NPs synthesized in the presence of various related cationic surfactants. The size of the cubic Fe3 O4 NPs can be tuned from 50 to 200 nm, by changing the concentration of oleic acid in the reaction solution. The Fe3 O4 NPs exhibit shape-dependent saturation magnetization, remanent magnetization, and coercivity.
Designer modeling for Sentient Sketchbook

This paper documents the challenges in creating a computer-aided level design tool which incorporates computergenerated suggestions which appeal to the human user. Several steps are suggested in order to make the suggestions more appropriate to a specific user's overall style, current focus, and end-goals. Designer style is modeled via choice-based interactive evolution which adapts the impact of different dimensions of quality based on the designer's choice of certain suggestions over others. Modeling process is carried out similarly to style, but adapting to the current focus of the designer's actions. Goals are modeled by estimating the visual patterns of the designer's final artifact and changing the parameters of the algorithm to enforce such patterns on generated suggestions.