nils-herrmann/clean_scirepeval huggingface dataset:
Aurantiamide acetate from baphicacanthus cusia root exhibits anti-inflammatory and anti-viral effects via inhibition of the NF-κB signaling pathway in Influenza A virus-infected cells.

ETHNOPHARMACOLOGICAL RELEVANCE
Baphicacanthus cusia root also names "Nan Ban Lan Gen" has been traditionally used to prevent and treat influenza A virus infections. Here, we identified a peptide derivative, aurantiamide acetate (compound E17), as an active compound in extracts of B. cusia root. Although studies have shown that aurantiamide acetate possesses antioxidant and anti-inflammatory properties, the effects and mechanism by which it functions as an anti-viral or as an anti-inflammatory during influenza virus infection are poorly defined. Here we investigated the anti-viral activity and possible mechanism of compound E17 against influenza virus infection.



The anti-viral activity of compound E17 against Influenza A virus (IAV) was determined using the cytopathic effect (CPE) inhibition assay. Viruses were titrated on Madin-Darby canine kidney (MDCK) cells by plaque assays. Ribonucleoprotein (RNP) luciferase reporter assay was further conducted to investigate the effect of compound E17 on the activity of the viral polymerase complex. HEK293T cells with a stably transfected NF-κB luciferase reporter plasmid were employed to examine the activity of compound E17 on NF-κB activation. Activation of the host signaling pathway induced by IAV infection in the absence or presence of compound E17 was assessed by western blotting. The effect of compound E17 on IAV-induced expression of pro-inflammatory cytokines was measured by real-time quantitative PCR and Luminex assays.



Compound E17 exerted an inhibitory effect on IAV replication in MDCK cells but had no effect on avian IAV and influenza B virus. Treatment with compound E17 resulted in a reduction of RNP activity and virus titers. Compound E17 treatment inhibited the transcriptional activity of NF-κB in a NF-κB luciferase reporter stable HEK293 cell after stimulation with TNF-α. Furthermore, compound E17 blocked the activation of the NF-κB signaling pathway and decreased mRNA expression levels of pro-inflammatory genes in infected cells. Compound E17 also suppressed the production of IL-6, TNF-α, IL-8, IP-10 and RANTES from IAV-infected lung epithelial (A549) cells.



These results indicate that compound E17 isolated from B. cusia root has potent anti-viral and anti-inflammatory effects on IAV-infected cells via inhibition of the NF-κB pathway. Therefore, compound E17 could be a potential therapeutic agent for the treatment of influenza.
Force Estimation Method for a Magnetic Lead-Screw-Driven Linear Actuator

Force-controllable actuators are essential for guaranteeing safety in human–robot interactions. Magnetic lead screws (MLSs) transfer force without requiring contact between parts. These devices can drive the parts with high efficiency and no frictional contact, and they are force limited when overloaded. We have developed a novel MLS that does not include spiral permanent magnets and an MLS-driven linear actuator (MLSDLA) that uses this device. This simple structure reduces the overall size of the device and improves productivity because it is constructed by a commonly used machined screw as a screw. The actuator can drive back against an external force and it moves flexibly based on the magnetic spring effect. In this paper, we propose a force estimation method for the MLSDLA that does not require separate sensors. The magnetic phase difference, as measured from the angular and linear displacements of the actuator, is used for this calculation. The estimated force is then compared against measurements recorded with a load sensor in order to verify the effectiveness of the proposed method.
Considering High-Performance Near-Field Reader Antennas: Comparisons of Proposed Antenna Layouts for Ultrahigh-Frequency Near-Field Radio-Frequency Identification

Radio-frequency identification (RFID) is being widely used in supply chain and logistics applications for wireless identification and the tracking and tracing of goods, with excellent performance for the long-range interrogation of tagged pallets and cases (up to 4-6 m, with passive tags). Item-level tagging (ILT) has also received much attention, especially in the pharmaceutical and retail industries. Low-frequency (125-134 KHz) and high-frequency (HF) (13.56 MHz) RFID systems have traditionally been used for ILT applications, where the radio-frequency (RF) power from the reader is delivered to the passive tags by inductive coupling. Recently, ultra-HF (UHF) (840-960 MHz) near-field (NF) RFID systems  have attracted increasing attention because of the merits of the much higher reading speed and capability to detect a larger number of tags (bulk reading). A UHF NF RFID system is a valuable solution to implement a reliable short-range wireless link (up to a few tens of centimeters) for ILT applications. Because the tags can be made smaller, RFID-based applications can be extended to extremely minuscule items (e.g., retail apparel, jewelry, drugs, rented apparel) as well as the successful implementation of RFID-based storage spaces, smart conveyor belts, and shopping carts.
Trajectory tracking for wheeled inverted pendulum robot using tilt angle control

This study investigated to design the trajectory tracking controller for wheeled inverted pendulum robot using tilt angle control. It introduced as follows; 3DOF model of wheeled inverted pendulum robot was derived by Lagrangian multiplier method. The trajectory tracking algorithm was redesigned in order to track the trajectory by forward and backward motions. The update algorithm is used to move the way point, which is desired position for servo controller. The tilt angle control was designed to control the tilt angle and the robot's motion. Initial condition and simulation result, which were described the initial condition for simulating the motion and the result of the trajectory tracking using the tilt angle control. The result exhibited that the robot can performs to track the trajectory well. However, some errors might be occurred when the robot performs the steering motion but the robot has a function able to perform to the goal successfully.
The Impact of Branching Heuristics in Propositional Satisfiability Algorithms

This paper studies the practical impact of the branching heuristics used in Propositional Satisfiability (SAT) algorithms, when applied to solving real-world instances of SAT. In addition, different SAT algorithms are experimentally evaluated. The main conclusion of this study is that even though branching heuristics are crucial for solving SAT, other aspects of the organization of SAT algorithms are also essential. Moreover, we provide empirical evidence that for practical instances of SAT, the search pruning techniques included in the most competitive SAT algorithms may be of more fundamental significance than branching heuristics.
Artistic Movement Recognition by Boosted Fusion of Color Structure and Topographic Description

We address the problem of automatically recognizing artistic movement in digitized paintings. We make the following contributions: Firstly, we introduce a large digitized painting database that contains refined annotations of artistic movement. Secondly, we propose a new system for the automatic categorization that resorts to image descriptions by color structure and novel topographical features as well as to an adapted boosted ensemble of support vector machines. The system manages to isolate initially misclassified images and to correct such errors in further stages of the boosting process. The resulting performance of the system compares favorably with classical solutions in terms of accuracy and even manages to outperform modern deep learning frameworks.
End-to-End Delay Minimization for Scientific Workflows in Clouds under Budget Constraint

Next-generation e-Science features large-scale, compute-intensive workflows of many computing modules that are typically executed in a distributed manner. With the recent emergence of cloud computing and the rapid deployment of cloud infrastructures, an increasing number of scientific workflows have been shifted or are in active transition to cloud environments. As cloud computing makes computing a utility, scientists across different application domains are facing the same challenge of reducing financial cost in addition to meeting the traditional goal of performance optimization. We develop a prototype generic workflow system by leveraging existing technologies for a quick evaluation of scientific workflow optimization strategies. We construct analytical models to quantify the network performance of scientific workflows using cloud-based computing resources, and formulate a task scheduling problem to minimize the workflow end-to-end delay under a user-specified financial constraint. We rigorously prove that the proposed problem is not only NP-complete but also non-approximable. We design a heuristic solution to this problem, and illustrate its performance superiority over existing methods through extensive simulations and real-life workflow experiments based on proof-of-concept implementation and deployment in a local cloud testbed.
Novel Ergonomic Postural Assessment Method (NERPA) Using Product-Process Computer Aided Engineering for Ergonomic Workplace Design

Musculoskeletal disorders (MSDs) that result from poor ergonomic design are one of the occupational disorders of greatest concern in the industrial sector. A key advantage in the primary design phase is to focus on a method of assessment that detects and evaluates the potential risks experienced by the operative when faced with these types of physical injuries. The method of assessment will improve the process design identifying potential ergonomic improvements from various design alternatives or activities undertaken as part of the cycle of continuous improvement throughout the differing phases of the product life cycle.



This paper presents a novel postural assessment method (NERPA) fit for product-process design, which was developed with the help of a digital human model together with a 3D CAD tool, which is widely used in the aeronautic and automotive industries. The power of 3D visualization and the possibility of studying the actual assembly sequence in a virtual environment can allow the functional performance of the parts to be addressed. Such tools can also provide us with an ergonomic workstation design, together with a competitive advantage in the assembly process.



The method developed was used in the design of six production lines, studying 240 manual assembly operations and improving 21 of them. This study demonstrated the proposed method's usefulness and found statistically significant differences in the evaluations of the proposed method and the widely used Rapid Upper Limb Assessment (RULA) method.
Modeling churn using customer lifetime value

0377-2217/$ see front matter 2008 Elsevier B.V. A doi:10.1016/j.ejor.2008.06.027 * Corresponding author.  E-mail address: Nicolas.Glady@econ.kuleuven.ac.b The definition and modeling of customer loyalty have been central issues in customer relationship management since many years. Recent papers propose solutions to detect customers that are becoming less loyal, also called churners. The churner status is then defined as a function of the volume of commercial transactions. In the context of a Belgian retail financial service company, our first contribution is to redefine the notion of customer loyalty by considering it from a customer-centric viewpoint instead of a product-centric one. We hereby use the customer lifetime value (CLV) defined as the discounted value of future marginal earnings, based on the customer’s activity. Hence, a churner is defined as someone whose CLV, thus the related marginal profit, is decreasing. As a second contribution, the loss incurred by the CLV decrease is used to appraise the cost to misclassify a customer by introducing a new loss function. In the empirical study, we compare the accuracy of various classification techniques commonly used in the domain of churn prediction, including two cost-sensitive classifiers. Our final conclusion is that since profit is what really matters in a commercial environment, standard statistical accuracy measures for prediction need to be revised and a more profit oriented focus may be desirable.
The Singular Values of Convolutional Layers

We characterize the singular values of the linear transformation associated with a convolution applied to a two-dimensional feature map with multiple channels. Our characterization enables efficient computation of the singular values of convolutional layers used in popular deep neural network architectures. It also leads to an algorithm for projecting a convolutional layer onto the set of layers obeying a bound on the operator norm of the layer. We show that this is an effective regularizer; periodically applying these projections during training improves the test error of a residual network on CIFAR-10 from 6.2% to 5.3%.
Impact of new traumatic or stressful life events on pre-existing PTSD in traumatized refugees: results of a longitudinal study

A significant proportion of trauma survivors experience an additional critical life event in the aftermath. These renewed experiences of traumatic and stressful life events may lead to an increase in trauma-related mental health symptoms.



In a longitudinal study, the effects of renewed experiences of a trauma or stressful life event were examined. For this purpose, refugees seeking asylum in Germany were assessed for posttraumatic stress symptoms (PTS), Posttraumatic Stress Diagnostic Scale (PDS), anxiety, and depression (Hopkins Symptom Checklist [HSCL-25]) before treatment start as well as after 6 and 12 months during treatment (N=46). Stressful life events and traumatic events were recorded monthly. If a new event happened, PDS and HSCL were additionally assessed directly afterwards. Mann-Whitney U-tests were performed to calculate the differences between the group that experienced an additional critical event (stressful vs. trauma) during treatment (n=23) and the group that did not (n=23), as well as differences within the critical event group between the stressful life event group (n=13) and the trauma group (n=10).



Refugees improved significantly during the 12-month period of our study, but remained severely distressed. In a comparison of refugees with a new stressful life event or trauma, significant increases in PTS, anxiety, and depressive symptoms were found directly after the experience, compared to the group without a renewed event during the 12 months of treatment. With regard to the different critical life events (stressful vs. trauma), no significant differences were found regarding overall PTS, anxiety, and depression symptoms. Only avoidance symptoms increased significantly in the group experiencing a stressful life event.



Although all clinicians should be aware of possible PTS symptom reactivation, especially those working with refugees and asylum seekers, who often experience new critical life events, should understand symptom fluctuation and address it in treatment.
Enabling drone communications with WiMAX Technology

With the popularity of winter tourism, the winter recreation activities have been increased day by day in alpine environments. However, large numbers of people and rescuers are injured and lost in this environment due to the avalanche accidents every year. Drone-based rescue systems are envisioned as a viable solution for saving lives in this hostile environment. To this aim, a European project named “Smart collaboration between Humans and ground-aErial Robots for imProving rescuing activities in Alpine environments (SHERPA)” has been launched with the objective to develop a mixed ground and aerial drone platform to support search and rescue activities in a real-world hostile scenarios. In this paper, we study the challenges of existing wireless technologies for enabling drone wireless communications in alpine environment. We extensively discuss about the positive and negative aspects of the standards according to the SHERPA network requirements. Then based on that, we choose Worldwide interoperability for Microwave Access network (WiMAX) as a suitable technology for drone communications in this environment. Finally, we present a brief discussion about the use of operating band for WiMAX and the implementation issues of SHERPA network. The outcomes of this research assist to achieve the goal of the SHERPA project.
Multi-objective AGV scheduling in an FMS using a hybrid of genetic algorithm and particle swarm optimization

Flexible manufacturing system (FMS) enhances the firm's flexibility and responsiveness to the ever-changing customer demand by providing a fast product diversification capability. Performance of an FMS is highly dependent upon the accuracy of scheduling policy for the components of the system, such as automated guided vehicles (AGVs). An AGV as a mobile robot provides remarkable industrial capabilities for material and goods transportation within a manufacturing facility or a warehouse. Allocating AGVs to tasks, while considering the cost and time of operations, defines the AGV scheduling process. Multi-objective scheduling of AGVs, unlike single objective practices, is a complex and combinatorial process. In the main draw of the research, a mathematical model was developed and integrated with evolutionary algorithms (genetic algorithm (GA), particle swarm optimization (PSO), and hybrid GA-PSO) to optimize the task scheduling of AGVs with the objectives of minimizing makespan and number of AGVs while considering the AGVs' battery charge. Assessment of the numerical examples' scheduling before and after the optimization proved the applicability of all the three algorithms in decreasing the makespan and AGV numbers. The hybrid GA-PSO produced the optimum result and outperformed the other two algorithms, in which the mean of AGVs operation efficiency was found to be 69.4, 74, and 79.8 percent in PSO, GA, and hybrid GA-PSO, respectively. Evaluation and validation of the model was performed by simulation via Flexsim software.
Tuning a PID controller for a digital excitation control system

Some of the modern voltage regulator systems are utilizing the proportional, integral, and derivative (PID) control for stabilization. Two PID tuning approaches, pole placement and pole-zero cancellation, are commonly utilized for commissioning a digital excitation system. Each approach is discussed including its performance with three excitation parameter variations. The parameters considered include system loop gain, uncertain exciter time constants, and forcing limits.
The WDC Gold Standards for Product Feature Extraction and Product Matching

Finding out which e-shops offer a specific product is a central challenge for building integrated product catalogs and comparison shopping portals. Determining whether two offers refer to the same product involves extracting a set of features (product attributes) from the web pages containing the offers and comparing these features using a matching function. The existing gold standards for product matching have two shortcomings: (i) they only contain offers from a small number of e-shops and thus do not properly cover the heterogeneity that is found on the Web. (ii) they only provide a small number of generic product attributes and therefore cannot be used to evaluate whether detailed product attributes have been correctly extracted from textual product descriptions. To overcome these shortcomings, we have created two public gold standards: The WDC Product Feature Extraction Gold Standard consists of over 500 product web pages originating from 32 different websites on which we have annotated all product attributes (338 distinct attributes) which appear in product titles, product descriptions, as well as tables and lists. The WDC Product Matching Gold Standard consists of over 75 000 correspondences between 150 products (mobile phones, TVs, and headphones) in a central catalog and offers for these products on the 32 web sites. To verify that the gold standards are challenging enough, we ran several baseline feature extraction and matching methods, resulting in F-score values in the range 0.39 to 0.67. In addition to the gold standards, we also provide a corpus consisting of 13 million product pages from the same websites which might be useful as background knowledge for training feature extraction and matching methods.
Comparative Analysis of Strengths and Challenges of SACCOS , VICOBA , NGO MFIs and Mobile Money Transactions in Tanzania

The History of financial services in Tanzania shows that there were poor financial services before and soon after the independence. The financial services improved slowly after the liberalization of financial services in the 1990s. This paper uses the empirical literature to compare the current financial services providers serving the middle and lower income groups in Tanzania. The analysis of findings indicates that cooperative financial institutions (VICOBA and SACCOS) and mobile money services serve the majority of Tanzanians both in rural and urban areas. The paper recommends that policymakers should favor the semi-formal MFIs to enable them to serve the majority of Tanzanians and the security of mobile monetary transactions should be strengthened since is the most reliable monetary services used by all categories of Tanzanians throughout the country.
Half-Bridge Integrated ZVS Full-Bridge Converter With Reduced Conduction Loss for Electric Vehicle Battery Chargers

A half-bridge integrated zero-voltage-switching (ZVS) full-bridge converter with reduced conduction loss for battery on-board chargers in electric vehicles (EVs) or plug-in hybrid electric vehicles (PHEVs) is proposed in this paper. The proposed converter features a reduction in primary-conduction loss and a lower secondary-voltage stress. In addition, the proposed converter has the most favorable characteristics as battery chargers as follows: a full ZVS capability and a significantly reduced output filter size due to the improved output waveform. In this paper, the circuit configuration, operation principle, and relevant analysis results of the proposed converter are described, followed by the experimental results on a prototype converter realized with a scale-downed 2-kW battery charger for EVs or PHEVs. The experimental results validate the theoretical analysis and show the effectiveness of the proposed converter as battery on-board chargers for EVs or PHEVs.
Accessing Peer Social Interaction: Using Authorable Virtual Peer Technology as a Component of a Group Social Skills Intervention Program

Autism spectrum and related communication and social disorders can severely affect some children's ability to engage in peer social interaction. In this article, we describe and evaluate an Authorable Virtual Peer (AVP), technology designed to help children access peer interactions by supporting them in developing critical social skills. Children interact with the AVP in three ways: (1) engaging in face-to-face interaction with a life-sized, computer-animated child; (2) creating new social behaviors for the AVP; and (3) controlling the AVP using a graphical user interface to select appropriate responses while the AVP interacts with another person. Our evaluation suggests that when an AVP is used as an activity during a social group intervention, a common intervention approach used with children with social and communication difficulties, that children's use of specific social behaviors critical to successful social interaction increases during role-play of common social situations with another child.