Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Slicing with Curvature Considerations

In this paper, first order slice height calculation in Laminated Object Manufacturing (LOM) of free form surfaces is done with two different considerations: that a) the cutter trajectory is oriented in the direction of local absolute maximum curvature of the surface or b) in the direction of local maximum flatness of the surface. For the former, the slices would be more in number when compared to the case where the cutter trajectory is contained in the normal vertical section (NVS). However, it would help in achieving higher form accuracy of the final part because it would be a form of worst-case check. For the second proposed strategy, least number of slices results, thereby reducing overall build time drastically.
Osteomyelitis prevention in rabbits using antimicrobial peptide hLF1-11- or gentamicin-containing calcium phosphate cement.

OBJECTIVES The efficacy of prophylactic treatment with human lactoferrin 1-11 (hLF1-11), a broad-spectrum antimicrobial peptide, was studied in a rabbit model of femur infection. METHODS Calcium phosphate cement with 50 mg/g hLF1-11 or gentamicin was injected into the femoral canal, after inoculation with Staphylococcus aureus. Three weeks later, slices of the proximal femora were sawn for quantitative bacterial culture and histology. RESULTS Treatment with hLF1-11 (P<0.038) or gentamicin (P<0.008) caused a reduction of cfu compared with the untreated control rabbits. The number of sterile cultures was higher in hLF1-11- (3/7) and gentamicin- (5/6) treated animals than in controls (1/7). Radiological and histological analysis showed early bone ingrowth into the cement cracks, and only moderate pathological changes in rabbits with positive cultures. CONCLUSIONS Local prophylaxis with hLF1-11 effectively reduced development of osteomyelitis in a rabbit model, but gentamicin resulted in a larger number of sterile femora.
A large project for demonstrating knowledge engineering techniques including applications of neural networks

One of the difficulties in introducing students to the variety of approaches used in knowledge engineering and neural networks in particular, is getting them to appreciate the strengths and weaknesses of each approach. Toy problems can be helpful but they often have little transfer to the real world problems encountered in the field. They tend to gloss over the very real limitations of existing tools and do little to challenge students to discover improved techniques. To this end we suggest the use of a single substantial problem from the published literature throughout a course as different approaches are presented.
Effect of antipsychotic medication alone vs combined with psychosocial intervention on outcomes of early-stage schizophrenia: A randomized, 1-year study.

CONTEXT Antipsychotic drugs are limited in their ability to improve the overall outcome of schizophrenia. Adding psychosocial treatment may produce greater improvement in functional outcome than does medication treatment alone. OBJECTIVE To evaluate the effectiveness of antipsychotic medication alone vs combined with psychosocial intervention on outcomes of early-stage schizophrenia. DESIGN Randomized controlled trial. SETTING Ten clinical sites in China. PARTICIPANTS Clinical sample of 1268 patients with early-stage schizophrenia treated from January 1, 2005, through October 31, 2007. Intervention Patients were randomly assigned to receive antipsychotic medication treatment only or antipsychotic medication plus 12 months of psychosocial intervention consisting of psychoeducation, family intervention, skills training, and cognitive behavior therapy administered during 48 group sessions. MAIN OUTCOME MEASURES The rate of treatment discontinuation or change due to any cause, relapse or remission, and assessments of insight, treatment adherence, quality of life, and social functioning. RESULTS The rates of treatment discontinuation or change due to any cause were 32.8% in the combined treatment group and 46.8% in the medication-alone group. Comparisons with medication treatment alone showed lower risk of any-cause discontinuation with combined treatment (hazard ratio, 0.62; 95% confidence interval, 0.52-0.74; P < .001) and lower risk of relapse with combined treatment (0.57; 0.44-0.74; P < .001). The combined treatment group exhibited greater improvement in insight (P < .001), social functioning (P = .002), activities of daily living (P < .001), and 4 domains of quality of life as measured by the Medical Outcomes Study 36-Item Short Form Health Survey (all P < or = .02). Furthermore, a significantly higher proportion of patients receiving combined treatment obtained employment or accessed education (P = .001). CONCLUSION Compared with those receiving medication only, patients with early-stage schizophrenia receiving medication and psychosocial intervention have a lower rate of treatment discontinuation or change, a lower risk of relapse, and improved insight, quality of life, and social functioning. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00654576.
Optimal retirement bene fi t systems in the presence of moral hazard

Several countries that switched to funded private account retirement systems opted to complement such systems with explicit guarantees to retirees and agents saving for retirement. The motivation was that a social insurance system should provide a minimum standard of living in retirement. This paper studies the optimal design of a social insurance system that aims to provide retirees with a minimum standard of living in retirement. Particular attention is paid to moral hazard, i.e. the incentive to take more risk once the guarantees are in place. Surprisingly, the simple policy of giving agents a fixed annuity in retirement is shown to be an optimal policy in the baseline model. ∗Contact: panageas@wharton.upenn. edu. I would like to thank Andrew Abel, Patrick Kehoe, Naryana Kocherlakota, Nicholas Souleles and participants of seminars at Wharton, the Minneapolis FED, the Philadelphia FED, and the University of Lausanne for helpful comments and discussions. Any errors are mine.
What Has Become of the "Stability-through-Inflation" Argument?

In this article, James B. Bullard and Alvin L. Marty begin by summarizing some popular arguments for positive steady-state rates of inflation based on the idea that a certain amount of inflation stabilizes economic performance. Then, synthesizing a number of disparate results in a single framework and using a general class of money-demand functions, they find that the stability-through-inflation arguments have either been completely replaced (by potent but unsettling results based on rational expectations) or called into question (by more sophisticated treatments of the adaptive expectations hypothesis).
An Overview of Internet Measurements: Fundamentals, Techniques, and Trends

The Internet presents great challenges to the characterization of its structure and behavior. Different reasons contribute to this situation, including a huge user community, a large range of applications, equipment heterogeneity, distributed administration, vast geographic coverage, and the dynamism that are typical of the current Internet. In order to deal with these challenges, several measurement-based approaches have been recently proposed to estimate and better understand the behavior, dynamics, and properties of the Internet. The set of these measurement-based techniques composes the Internet Measurements area of research. This overview paper covers the Internet Measurements area by presenting measurement-based tools and methods that directly influence other conventional areas, such as network design and planning, traffic engineering, quality of service, and network management.
Medical diagnostic image fusion based on feature mapping wavelet neural networks

In recent years, many solutions to medical diagnostic image fusion have been proposed; however, it is difficult to simulate the surgical ability of image fusion when algorithms of image processing are merely piled up. On the basis of the review of researches on psychophysics and physiology of human vision, this paper presents an effective multi-resolution image fusion methodology, which is self-organizing feature mapping wavelet neural network (SOFMWNN), to simulate the processes of images recognition and understanding implemented in the human vision system. As an example, the fusion process is applied in the clinical case: the study of some particular disease by MR/SPECT fusion. Results are presented and evaluated, and a preliminary clinical validation is achieved. The effectiveness of the proposed model is demonstrated via results comparison with several other image fusion methods.
Mathematical modelling of differential permeability of carbon nanotubes

We study permeability of a porous element in a carbon filter - the carbon nanotube, as well as the possibility of applying this structure in the process of natural gas components separation. The filtering effect is based on intermolecular interaction between the carbon nanotube elements and molecules and atoms of various substances in a gaseous state. With respect to these graphene structures we study the internal dynamics of hydrogen, oxygen, helium, and methane molecules. The geometrical dimensions of the tubes providing differential gas permeability of components are found.
Two dimensional dynamic stability for reconfigurable robots designed to traverse rough terrain

Robots must be designed with consideration for reconfiguring body pose during operation if they are to address more challenging environments. Researchers have mostly relied on static stability methods to monitor the possibility of rollover in stationary or slow moving vehicles. However, little research in dynamic stability is being conducted for robots capable of reconfiguring their pose to overcome obstacles encountered in challenging terrains. A multi-degree-of-freedom robot with the capability to vary its center of gravity is discussed in this paper. It is designed to improve mobility over rough terrain and is used in this paper as an example to address one aspect of dynamic stability. A complete understanding of the dynamic behaviour of a multiple degree of freedom robot in unstructured terrain is a difficult problem to solve. It is too complex to solve completely and therefore a reduced aspect of the problem is addressed. The robot will only have the ability to vary its center of gravity in the plane parallel to its direction of forward motion. In addition the robot will only move on flat terrain and encounter an immovable linear step feature. The result of the research is that once the center of gravity is specified by selection of robot body pose, and a maximum obstacle considered, platform stability can be ensured with a maximum allowable velocity. In other words, a maximum allowable velocity of the robot is governed by the position of the center of gravity relative to the wheel in contact with the linear step feature. If the robot is traveling below the predetermined maximum velocity then the robot is guaranteed to remain upright.
A single supply level shifter for multi-voltage systems

This paper presents design and application of a level shifter circuit which works with a single power supply. Unlike the conventional level shifter circuits, the proposed level shifter can shift any voltage level signal to a desired higher level without any leakage current. Use of single supply level shifter greatly reduces the supply routing and layout congestion within the chip when level shifting is required between different voltage domains. It also reduces pin count if level shifting is required between two or more chips operating at different supply voltages in a multi-voltage system. The proposed circuit is generic in nature and the voltage range at which level shifting can be done is limited by the technology only. The circuits was designed in 90nm CMOS technology and simulated in SPICE. The simulation results show that the proposed level shifter circuit is able to shift the input signal from 1.2V to 2.5V at maximum frequency of 500MHz.
Running head : REACTIVE AND PROACTIVE AGGRESSION 1 Joint Trajectories of Reactive and Proactive Aggression from Mid-childhood to Early Adolescence : Relations to Sensation Seeking , Risk Taking , and Moral Reasoning

We examined the roles of sensation seeking, risk taking, and moral reasoning in the development of reactive and proactive aggression. Data were drawn from a multiethnic, longitudinal study of children from Switzerland (N = 1,571; assessed annually over 6 years; 7-years-old at Time 1). At all six time points, teachers reported children’s reactive and proactive aggression via questionnaire. Children’s sensation seeking (at Time 1) and risk taking (at Time 2) were assessed with two interactive computer tasks and their moral reasoning was assessed at Time 2 in response to four hypothetical vignettes depicting moral transgressions. Latent Class Growth Modeling revealed four developmental trajectories of reactive aggression and three of proactive aggression. Six joint trajectories of reactive and proactive aggression were then identified. Children with high sensation seeking and risk taking were very likely to develop both types of aggression during childhood. Children with high moral reasoning skills were very likely to develop reactive aggression during adolescence, whereas those with low moral reasoning were likely to show proactive aggression during childhood. These findings highlight the shared and differential roles of sensation seeking, risk taking, and moral reasoning in the development of reactive and proactive aggression from mid-childhood to early adolescence. We discuss implications for common and tailored strategies to combat these aggression subtypes.
Evolving Graph Compression using Similarity Measures for Bioinformatics Applications

Many real-world graphs, including those storing various forms of biological data, are of such large size that storing and processing their information has too high a cost. As a result, one possible solution is to compress the graphs by merging nodes into supernodes. This study introduces a genetic algorithm for graph compression that is based on the similarity of nodes, where two nodes are considered similar if a high proportion of their neighbours are in common. The methodology was applied to three real-world graphs storing widely varying data, as well as the gene regulatory network of E. coli. This study used a fixed compression rate of 25 % as a target for the graphs. Results for a parameter study of variation operators exhibit a strong preference for crossover, in comparison to mutation which was found to be disruptive to graph structure.
Provable Storage Medium for Data Storage Outsourcing

In remote storage services, delays in the time to retrieve data can cause economic losses to the data owners. In this paper, we address the problem of properly establishing specific clauses in the service level agreement (SLA), intended to guarantee a short and predictable retrieval time. Based on the rationale that the retrieval time mainly depends on the storage media used at the server side, we introduce the concept of Provable Storage Medium (PSM), to denote the ability of a user to efficiently verify that the provider is complying to this aspect of the SLA. We propose PSM as an extension of Provable Data Possession (PDP): embedding challenge-response PDP schemes with measurements of the response time, both properties can be enforced without any need for the user to locally store nor download her data. We describe a realistic implementation of PSM in a scenario where data should be stored both in RAM and HDD. A thorough analysis shows that, even for relatively small challenges, the total time to compute and deliver the response is sensibly affected by the remarkable difference in the access time of the two supports. An extensive simulation campaign confirms the quality and viability of our proposal.
Finite-Element Model Predicts Current Density Distribution for Clinical Applications of tDCS and tACS

Transcranial direct current stimulation (tDCS) has been applied in numerous scientific studies over the past decade. However, the possibility to apply tDCS in therapy of neuropsychiatric disorders is still debated. While transcranial magnetic stimulation (TMS) has been approved for treatment of major depression in the United States by the Food and Drug Administration (FDA), tDCS is not as widely accepted. One of the criticisms against tDCS is the lack of spatial specificity. Focality is limited by the electrode size (35 cm2 are commonly used) and the bipolar arrangement. However, a current flow through the head directly from anode to cathode is an outdated view. Finite-element (FE) models have recently been used to predict the exact current flow during tDCS. These simulations have demonstrated that the current flow depends on tissue shape and conductivity. To face the challenge to predict the location, magnitude, and direction of the current flow induced by tDCS and transcranial alternating current stimulation (tACS), we used a refined realistic FE modeling approach. With respect to the literature on clinical tDCS and tACS, we analyzed two common setups for the location of the stimulation electrodes which target the frontal lobe and the occipital lobe, respectively. We compared lateral and medial electrode configuration with regard to their usability. We were able to demonstrate that the lateral configurations yielded more focused stimulation areas as well as higher current intensities in the target areas. The high resolution of our simulation allows one to combine the modeled current flow with the knowledge of neuronal orientation to predict the consequences of tDCS and tACS. Our results not only offer a basis for a deeper understanding of the stimulation sites currently in use for clinical applications but also offer a better interpretation of observed effects.
Interactive maps for visual data exploration

Descartes (formerly called IRIS) is a software system designed to support visual exploration of spatially referenced data, e.g. demographic, economical, or cultural information about geographical objects or locations such as countries, districts, or cities. Descartes offers two integrated services: automated presentation of data on maps, and facilities to interactively manipulate these maps. Automated mapping is enabled by incorporating generic knowledge on map design into the system. Descartes selects suitable presentation methods according to characteristics of the variables to be analysed and relationships among those variables if more than one were selected simultaneously. The cartographic knowledge of Descartes allows non-cartographers to receive proper presentations of their data, and the automation of map construction helps the users to save valuable time that can better be used for data analysis and problem-solving. Exploratory data analysis requires highly interactive, dynamic data displays. We s.
Partial Purification and Characterization of a Hepatocyte Growth Factor Produced by Rat Hepatocellular Carcinoma Cells 1

Serum-free medium conditioned by confluent cultures of JM1 or JM2 rat hepatocellular carcinoma cells stimulated DMA syn thesis in primary cultures of adult rat hepatocytes in a dosedependent, saturable manner and in the absence of epidermal growth factor. The hepatotrophic activity was nondialyzable in Mr 50,000 cutoff membranes, heat (60Â°C)and acid stable, and sensitive to trypsin and dithiothreitol treatment. Gel filtration of concentrated JM1 or JM2 conditioned medium on Sephadex G100 separated the activity into two regions, the major broad peak migrating with apparent M, 25,000. Chromatography frac tions active in the hepatocyte proliferation bioassay also inhibited specific binding of iodinated epidermal growth factor to cultures of A431 carcinoma cells and rat hepatocytes. These results suggest that neoplastic liver cells synthesize and secrete polypeptide growth factors which can bind to epidermal growth factor receptors and stimulate proliferation of normal adult rat hepato cytes in primary culture.
Statin Inhibition of Fc Receptor–Mediated Phagocytosis by Macrophages Is Modulated by Cell Activation and Cholesterol

Objectives—An inflammatory response to altered lipoproteins that accumulate in the arterial wall is a major component of the pathogenesis of atherosclerosis. Statins reduce plasma levels of low-density lipoprotein (LDL) and are effective treatments for atherosclerosis. It is hypothesized that they also modulate inflammation. The aim of this study was to examine whether lovastatin inhibits macrophage inflammatory processes and clarify its mechanism of action. Methods and Results—We examined the effects of statins on phagocytosis of antibody-coated red blood cells by cultured human monocytes and mouse peritoneal macrophages. Lovastatin, simvastatin, and zaragozic acid, a squalene synthase inhibitor, blocked Fc receptor–mediated phagocytosis by cultured human monocytes and mouse peritoneal macrophages. The inhibitory effect of lovastatin on Fc receptor–mediated phagocytosis was prevented completely by addition of mevalonate, farnesyl pyrophosphate, LDL, or cholesterol to the culture medium. The inhibitory effect of zaragozic acid was reversed by addition of LDL, but not by the addition of geranylgeranyl pyrophosphate, to the medium. In addition, the effect of lovastatin on phagocytosis is a function of cell activation because treatment of cells with tumor necrosis factor-&agr; or lipopolysaccharide prevented inhibition of phagocytosis by lovastatin. Conclusions—The inhibition of Fc receptor–mediated phagocytosis of lovastatin is related to its effect on cholesterol biosynthesis rather than its effect on the formation of isoprenoids.
Introspective classification for pedestrian detection

State-of-the-art pedestrian detectors are capable of finding humans in images with reasonable accuracy. However, accurate object detectors such as Integral Channel Features (ICF) do not provide good reliability; they are unable to identify detections which they are less confident (or more uncertain) about. We apply existing methods for generating probabilistic measures from classifier scores (such as Piatt exponential scaling and Isotonic Regression) and compare these to Gaussian Process classifiers (GPCs), which can provide more informative predictive variance. GPCs are less accurate than ICF classifiers, but GPCs and Adaboost with Piatt scaling both provide improved reliability over existing methods.
CONSORTS-S: A mobile sensing platform for context-aware services

This paper proposes a mobile sensing platform that provides context-aware services for mobile users by accessing surrounding wireless sensor networks. The platform provides the following facilities: 1) communicating to wireless sensor networks via a mobile sensor router attached to a userpsilas mobile phone, 2) analyzing the sensed data derived from networks by cooperating with sensor middleware on a remote server to capture onepsilas contexts, and 3) providing context-aware services for mobile users of cellular telephones. The platform is designed to process the sensed data effectively through cooperation between a mobile phone, a mobile sensor router, and a sensor middleware on a remote server. In this paper, we describe the concept of a mobile sensing platform: CONSORTS-S and its architecture, and show a healthcare service as a prototype application of CONSORTS-S. The healthcare service is aware of userspsila conditions such as heartbeat, posture, and movement through monitors of physiological signals (e.g., electrocardiograph, thermometer, and 3-axis accelerometer) and environmental conditions (e.g. room temperatures) by communication with environmental sensors.