nils-herrmann/clean_scirepeval huggingface dataset:
A SPATIAL CHOICE MODEL FOR PRODUCT RECOMMENDATIONS

Product recommendation models are key tools in customer relationship management (CRM). This study develops a product recommendation model based upon the principle that customer preference similarity stemming from prior response behavior is a key element in predicting current product purchase. The proposed recommendation model is dependent upon two complementary methodologies: joint space mapping (placing customers and products on the same psychological map) and spatial choice modeling (allowing observed choices to be correlated across customers). Using a joint space map based upon past purchase behavior, a predictive model is calibrated in which the probability of product purchase depends upon the customer's relative distance to other customers on the map. An empirical study demonstrates that the proposed approach provides excellent forecasts relative to benchmark models for a customer database provided by an insurance firm. Product recommendation models are key tools in customer relationship management (CRM). An effective recommendation model contributes to the CRM goal of customer expansion by offering high-valued products to regular customers. When regular customers purchase more products from the same company, long-term customer retention is likely to be improved because of increased customers benefits and higher switching costs. This research develops a product recommendation system based upon the principle that customer preference similarity stemming from prior response behavior is a key element in predicting product purchase. Our study brings together two complementary research methodologies: joint space mapping methodology (placing customers and products on the same psychometric map) and spatial choice modeling (allowing observed choices to be correlated across customers). The current research, however, differs from existing research in two respects. First, marketing science models based upon psychometric maps typically examine distances between products and customers in order to infer the attractiveness of each product to each customer (e.g., Moore and Winer 1987). In contrast, this research infers product preferences from the relative similarity of other customers based on inter-customer distances (Kapteyn et al. Because this approach only relies upon customer positions on a psychometric map, it is less susceptible to measurement error and does not require that the researcher accurately locate a new product on an existing product map. Second, contrary to previous work, this research uses a choice model adapted assume that entities (such as customers) can be located in a space. Responses by entities are assumed to be correlated in such a manner that entities near one another in the space generate similar outcomes. The methodology can …
A Permanent-Magnet Linear Motion Driven Kinetic Energy Harvester

This manuscript presents a double-sided flat-type permanent magnetic linear energy harvester to scavenge kinetic power from linear motions. The dynamic system model of the linear generator is analytically driven and analyzed by an innovative state-based approach. The analytical equations on maximum power generation specific for non-resonant applications such as human foot motion are derived. Both magnetic circuit analysis and the finite-element analysis simulation are carried out on the linear machine to investigate its performance. Under the typical horizontal foot motion velocity of 4.5 m/s, the proposed energy harvester generates 674 mW electric power with the power density as high as 3.4 mW/cm3. A macro-scale proof-of-concept machine is prototyped to verify the performance of the linear machine and validate the analysis, simulation, and the proposed modeling approach.
A Loop Antenna with Coupling Strip and Tuner for All-Metal-Shell Handset Application

A dual-band frame antenna with coupling strip and tuner is proposed in this work for all-metal-shell mobile telephone application with all the metal devices being considered The metal-shell handsets are getting more and more popular nowadays due to the robustness and its fascinating appearance. The metal-shell associated with surrounding electronic components would occupy the metal clearance, which will absorb the energy radiated by the antenna. This work provides an optional solution to design the antenna with all the metal components like front-and-back facing cameras, telephone receiver and steel sheet taken into consideration, where the metal shell of the handset and a coupling strip are utilized as part of the antenna. The metal shell of the handset has a symmetric C-shaped gap with a width of 2mm and no other breakpoints to decrease the robustness of the structure. The proposed antenna is able to generate radiation covering the bandwidth of 824–960 MHz (GSM) and 1710–2690 MHz (DCS/PCS/UMTS/L TE) for mobile communication. With the application of the tuner, the antenna can get a broadband characteristic and the coupling strip may add the capacitance of the structure, making the antenna resonate at the lower band as 0.25λ resonant mode and as 0.5λ resonant mode at the higher band. The principle of the tuner has also been discussed in the paper, helping locate the proper situation to induce the switchable inductor. A prototype has been fabricated to verify the radiation performance in a practical handset test environment.
Beyond objects: a software design paradigm based on process control

A standard demonstration problem in object-oriented programming is the design of an automobile cruise control. This design exercise demonstrates object-oriented techniques well, but it does not ask whether the object-oriented paradigm is the best one for the task. Here we examine the alternative view that cruise control is essentially a control problem. We present a new software organization paradigm motivated by process control loops. The control view leads us to an architecture that is dominated by analysis of a classical feedback loop rather than by the identification of discrete stateful components to treat as objects. The change in architectural model calls attention to important questions about the cruise control task that aren't addressed in an object-oriented design.
See the Difference: Direct Pre-Image Reconstruction and Pose Estimation by Differentiating HOG

The Histogram of Oriented Gradient (HOG) descriptor has led to many advances in computer vision over the last decade and is still part of many state of the art approaches. We realize that the associated feature computation is piecewise differentiable and therefore many pipelines which build on HOG can be made differentiable. This lends to advanced introspection as well as opportunities for end-to-end optimization. We present our implementation of ΔHOG based on the auto-differentiation toolbox Chumpy [18] and show applications to pre-image visualization and pose estimation which extends the existing differentiable renderer OpenDR [19] pipeline. Both applications improve on the respective state-of-the-art HOG approaches.
PLM (Product Lifecycle Management) Model for Supply Chain Optimization

Product Lifecycle Management (PLM) is an integrated business approach to the collaborative creation, management and dissemination of engineering information throughout the extended enterprise. Concretely, PLM enables a supply chain to become much more competitive by an effective collaboration among customers, developers, suppliers and manufacturers at various lifecycle stages of a product. Our objective is to propose a PLM model for a supply chain in order to increase its overall performance through better control of products at all stages of their lives. Thus, we will track product’s information on a supply chain composed, as a first step, by five actors (supplier, enterprise, warehouse, transporter and customer). Indeed, by integrating the logistics constraints in the early stages of product development, this will avoid additional costs and time waste caused by a product unsuitable for its supply chain.
Can we make an early 'do not resuscitate' decision in severe burn patients?

The present study was conducted to examine topic of issuing early do-not-resuscitate (DNR) order at first diagnosis of patients with severe burn injuries in light of current law in Turkey and the medical literature. DNR requires withholding cardiopulmonary resuscitation in event of respiratory or cardiac arrest and allowing natural death to occur. It is frequently enacted for terminal cancer patients and elderly patients with irreversible neurological disorders.



Between January 2009 and December 2014, 29 patients (3.44%) with very severe burns were admitted to burn unit. Average total burn surface area (TBSA) was 94.24% (range: 85-100%), and in 10 patients, TBSA was 100%. Additional inhalation burns were present in 26 of the patients (89.65%). All of the patients died, despite every medical intervention. Mean survival was 4.75 days (range: 1-24 days). Total of 17 patients died within 72 hours. Lethal dose 50 (% TBSA at which certain group has 50% chance of survival) rate of our burn center is 62%. Baux indices were used for prognostic evaluation of the patients; mean total Baux score of the patients was 154.13 (range: 117-183).



It is well known that numerous problems may be encountered during triage of severely burned patients in Turkey. These patients are referred to burn centers and are frequently transferred via air ambulance between cities, and even countries. They are intubated and mechanical ventilation is initiated at burn center. Many interventions are performed to treat these patients, such as escharotomy, fasciotomy, tangential or fascial excision, central venous catheterization and tracheostomy, or hemodialysis. Yet despite such interventions, these patients die, typically within 48 to 96 hours. Integrity of the body is often lost as result of aggressive intervention with no real benefit, and there are also economic costs to hospital related to use of materials, bed occupancy, and distribution of workforce. For these reasons, as well as patient comfort, early do-not-resuscitate or do-not-intubate protocol for these patients is suggested. Resources could then be directed to other patients with high expectancy of life and patients with burns that are beyond treatment can experience more comfortable end of life.



At present in Turkey, it is not possible to give DNR order for patient with severe burns that are incompatible with survival due to legal interdiction. This subject should be discussed at high-level meetings with participation of doctors, legal experts, economists, and theologians.
Towards versatile legged robots through active impedance control

Robots with legs and arms have the potential to support human s in dangerous, dull or dirty tasks. A major motivation behind research on such robots is their potentialversatility. However, these robots come at a high price in mechanical and control complexity. Hence, until they can demonstrate a cle r advantage over their simpler counterparts, robots with arms and legs will not ful fill their true potential. In this paper, we discuss the opportunities for versatile ro bots that arise by actively controlling the mechanical impedance of joints and particu larly legs. In contrast to passive elements like springs, active impedance is achieve d by torque-controlled joints allowing real-time adjustment of stiffness and damp ing. Adjustable stiffness and damping in realtime is a fundamental building block towa rds versatility. Experiments with our 80 kg hydraulic quadruped robot HyQ demon strate that active impedance alone (i.e. no springs in the structure) can succe sfully emulate passively compliant elements during highly-dynamic locomotion task s (running, jumping and hopping); and, that no springs are needed to protect the actu ation system. Here we present results of a flying trot, also referred to as running t rot. To the authors’ best knowledge this is the first time a flying trot has been successf ully implemented on a robot without passive elements such as springs. A critical discussion on the pros and cons of active impedance concludes the paper. This artic le is an extension of our previous work (Semini et al. (2013)) presented at the Int rnational Symposium on Robotics Research (ISRR) 2013.
Tune: A Research Platform for Distributed Model Selection and Training

Modern machine learning algorithms are increasingly computationally demanding, requiring specialized hardware and distributed computation to achieve high performance in a reasonable time frame. Many hyperparameter search algorithms have been proposed for improving the efficiency of model selection, however their adaptation to the distributed compute environment is often ad-hoc. We propose Tune, a unified framework for model selection and training that provides a narrow-waist interface between training scripts and search algorithms. We show that this interface meets the requirements for a broad range of hyperparameter search algorithms, allows straightforward scaling of search to large clusters, and simplifies algorithm implementation. We demonstrate the implementation of several state-of-the-art hyperparameter search algorithms in Tune. Tune is available at http://ray.readthedocs.io/en/latest/tune.html.
Object Detection based on LIDAR Temporal Pulses using Spiking Neural Networks

Neural networks has been successfully used in the processing of Lidar data, especially in the scenario of autonomous driving. However, existing methods heavily rely on pre-processing of the pulse signals derived from Lidar sensors and therefore result in high computational overhead and considerable latency. In this paper, we proposed an approach utilizing Spiking Neural Network (SNN) to address the object recognition problem directly with raw temporal pulses. To help with the evaluation and benchmarking, a comprehensive temporal pulses data-set was created to simulate Lidar reflection in different road scenarios. Being tested with regard to recognition accuracy and time efficiency under different noise conditions, our proposed method shows remarkable performance with the inference accuracy up to 99.83% (with 10% noise) and the average recognition delay as low as 265 ns. It highlights the potential of SNN in autonomous driving and some related applications. In particular, to our best knowledge, this is the first attempt to use SNN to directly perform object recognition on raw Lidar temporal pulses.
Early sex differences in spatial skill.

This study investigated sex differences in young children's spatial skill. The authors developed a spatial transformation task, which showed a substantial male advantage by age 4 years 6 months. The size of this advantage was no more robust for rotation items than for translation items. This finding contrasts with studies of older children and adults, which report that sex differences are largest on mental rotation tasks. Comparable performance of boys and girls on a vocabulary task indicated that the male advantage on the spatial task was not attributable to an overall intellectual advantage of boys in the sample.
Medical Therapy of Malignant Bowel Obstruction With Octreotide, Dexamethasone, and Metoclopramide.

Malignant bowel obstruction is a highly symptomatic, often recurrent, and sometimes refractory condition in patients with intra-abdominal tumor burden. Gastro-intestinal symptoms and function may improve with anti-inflammatory, anti-secretory, and prokinetic/anti-nausea combination medical therapy.



To describe the effect of octreotide, metoclopramide, and dexamethasone in combination on symptom burden and bowel function in patients with malignant bowel obstruction and dysfunction.



A retrospective case series of patients with malignant bowel obstruction (MBO) and malignant bowel dysfunction (MBD) treated by a palliative care consultation service with octreotide, metoclopramide, and dexamethasone. Outcomes measures were nausea, pain, and time to resumption of oral intake.



12 cases with MBO, 11 had moderate/severe nausea on presentation. 100% of these had improvement in nausea by treatment day #1. 100% of patients with moderate/severe pain improved to tolerable level by treatment day #1. The median time to resumption of oral intake was 2 days (range 1-6 days) in the 8 cases with evaluable data. Of 7 cases with MBD, 6 had For patients with malignant bowel dysfunction, of those with moderate/severe nausea. 5 of 6 had subjective improvement by day#1. Moderate/severe pain improved to tolerable levels in 5/6 by day #1. Of the 4 cases with evaluable data on resumption of PO intake, time to resume PO ranged from 1-4 days.



Combination medical therapy may provide rapid improvement in symptoms associated with malignant bowel obstruction and dysfunction.
Price Prediction : Hedonic Price Model vs . Artificial Neural Network

The objective of this study is to empirically compare the predictive power of the hedonic model with an artificial neural network model for house price prediction. A sample of 200 houses in Christchurch, New Zealand is randomly selected from the Harcourt website. Factors including house size, house age, house type, number of bedrooms, number of bathrooms, number of garages, amenities around the house and geographical location are considered. Empirical results support the potential of artificial neural network on house price prediction, although previous studies have commented on its black box nature and achieved different conclusions.
Cellulosomes: bacterial nanomachines for dismantling plant polysaccharides

Cellulosomes are multienzyme complexes that are produced by anaerobic cellulolytic bacteria for the degradation of lignocellulosic biomass. They comprise a complex of scaffoldin, which is the structural subunit, and various enzymatic subunits. The intersubunit interactions in these multienzyme complexes are mediated by cohesin and dockerin modules. Cellulosome-producing bacteria have been isolated from a large variety of environments, which reflects their prevalence and the importance of this microbial enzymatic strategy. In a given species, cellulosomes exhibit intrinsic heterogeneity, and between species there is a broad diversity in the composition and configuration of cellulosomes. With the development of modern technologies, such as genomics and proteomics, the full protein content of cellulosomes and their expression levels can now be assessed and the regulatory mechanisms identified. Owing to their highly efficient organization and hydrolytic activity, cellulosomes hold immense potential for application in the degradation of biomass and are the focus of much effort to engineer an ideal microorganism for the conversion of lignocellulose to valuable products, such as biofuels.
A literature review and classification of electronic commerce research

In this paper, we present a literature review and classification scheme for electronic commerce (EC) research. The former consists of 275 journal articles published between 1993 and 1999 in nine journals that are appropriate outlets for EC research. The results show that an increasing volume of EC research has been conducted for a diverse range of areas. The articles are classified and results of these are presented, based on a scheme that consists of four main categories: application areas, technological issues, support and implementation, and others. A comprehensive list of references is presented. Hopefully, this review will provide a source for anyone interested in EC research and help simulate further interest.
The value of contrast-enhanced color Doppler ultrasound in the detection of vascularization of finger joints in patients with rheumatoid arthritis.

A prospective study was performed to assess the usefulness of contrast-enhanced color Doppler ultrasound (CDUS) in the evaluation of intraarticular vascularization of finger joints in patients with rheumatoid arthritis (RA).



We investigated 198 finger joints in 46 patients with RA, and 80 finger joints in 10 healthy volunteers. Joints with varying levels of clinical activity of inflammation were classified as being active, moderately active, or inactive. CDUS was performed with a high-frequency multi-D linear array transducer. A microbubble-based ultrasound (US) contrast agent (Levovist; Schering, Berlin, Germany) was intravenously infused. Doppler findings were rated on the basis of both unenhanced and contrast-enhanced CDUS images.



Healthy joints showed no intraarticular vascularization on either unenhanced or contrast-enhanced CDUS. Unenhanced CDUS detected intraarticular vascularization in 7 (8%) of 83 inactive joints, in 31 (52%) of 60 moderately active joints, and in 32 (58%) of 55 active joints. Contrast-enhanced CDUS detected intraarticular vascularization in 41 (49%) of 83 joints with inactive RA, in 59 (98%) of 60 joints with moderately active RA, and in all 55 joints with active RA. Detection of intraarticular vascularization was improved by administration of the microbubble-based US contrast agent (P < 0.001). Contrast-enhanced CDUS demonstrated differences in intraarticular vascularization between joints with inactive RA and those with active RA (P < 0.001), between joints with inactive RA and those with moderately active RA (P < 0.001), and between joints with moderately active RA and those with active RA (P < 0.001).



The use of a microbubble-based US contrast agent significantly improved the detection of intraarticular vascularization in the finger joints of patients with RA. This technique seems to be a useful adjunct in the assessment of disease activity.
Complete Algorithms

This chapter is concerned with sound and complete algorithms for testing satisfiability, i.e., algorithms that are guaranteed to terminate with a correct decision on the satisfiability/unsatisfiability of the given CNF. One can distinguish between a few approaches on which complete satisfiability algorithms have been based. The first approach is based on existential quantification, where one successively eliminates variables from the CNF without changing the status of its satisfiability. When all variables have been eliminated, the satisfiability test is then reduced into a simple test on a trivial CNF. The second approach appeals to sound and complete inference rules, applying them successively until either a contradiction is found (unsatisfiable CNF) or until the CNF is closed under these rules without finding a contradiction (satisfiable CNF). The third approach is based on systematic search in the space of truth assignments, and is marked by its modest space requirements. The last approach we will discuss is based on combining search and inference, leading to algorithms that currently underly most modern complete SAT solvers. We start in the next section by establishing some technical preliminaries that will be used throughout the chapter. We will follow by a treatment of algorithms that are based on existential quantification in Section 3.3 and then algorithms based on inference rules in Section 3.4. Algorithms based on search are treated in Section 3.5, while those based on the combination of search and inference are treated in Section 3.6. Note that some of the algorithms presented here could fall into more than one class, depending on the viewpoint used. Hence, the classification presented in Sections 3.3-3.6 is only one of the many possibilities.