nils-herrmann/clean_scirepeval huggingface dataset:
Siderophore-based iron acquisition and pathogen control.

High-affinity iron acquisition is mediated by siderophore-dependent pathways in the majority of pathogenic and nonpathogenic bacteria and fungi. Considerable progress has been made in characterizing and understanding mechanisms of siderophore synthesis, secretion, iron scavenging, and siderophore-delivered iron uptake and its release. The regulation of siderophore pathways reveals multilayer networks at the transcriptional and posttranscriptional levels. Due to the key role of many siderophores during virulence, coevolution led to sophisticated strategies of siderophore neutralization by mammals and (re)utilization by bacterial pathogens. Surprisingly, hosts also developed essential siderophore-based iron delivery and cell conversion pathways, which are of interest for diagnostic and therapeutic studies. In the last decades, natural and synthetic compounds have gained attention as potential therapeutics for iron-dependent treatment of infections and further diseases. Promising results for pathogen inhibition were obtained with various siderophore-antibiotic conjugates acting as "Trojan horse" toxins and siderophore pathway inhibitors. In this article, general aspects of siderophore-mediated iron acquisition, recent findings regarding iron-related pathogen-host interactions, and current strategies for iron-dependent pathogen control will be reviewed. Further concepts including the inhibition of novel siderophore pathway targets are discussed.
Control simulation of an Automatic Turret Gun based on force control method

Automatic Turret Gun (ATG) is a weapon system used in numerous combat platforms and vehicles such as in tanks, aircrafts, or stationary ground platforms. ATG plays a big role in both defensive and offensive scenario. It allows combat engagement while the operator of ATG (soldier) covers himself inside a protected control station. On the other hand, ATGs have significant mass and dimension, therefore susceptible to inertial disturbances that need to be compensated to enable the ATG to reach the targeted position quickly and accurately while undergoing disturbances from weapon fire or platform movement. The paper discusses various conventional control method applied in ATG, namely PID controller, RAC, and RACAFC. A number of experiments have been carried out for various range of angle both in azimuth and elevation axis of turret gun. The results show that for an ATG system working under disturbance, RACAFC exhibits greater performance than both RAC and PID, but in experiments without load, equally satisfactory results are obtained from RAC. The exception is for the PID controller, which cannot reach the entire angle given.
Isolated Developmental Venous Anomaly of the Pons with Transpontine Drainage: Case Report

Initially known as venous angioma, Developmental Venous Anomaly (DVA) is a persistent variant of fetal brain venous drainage [1, 2]. Unlike cerebellar DVA with or without brainstem extension, isolated pontine DVA is a rare condition [3, 4]; and as per our knowledge, its presentation with exclusive transpontine drainage has never been described before. The authors present the case of an isolated pontine DVA with a selective transpontine drainage discovered incidentally; the clinical presentation, the radiological findings, and the management are discussed.
SYMBOLIC REGRESSION OF IMPLICIT EQUATIONS

Traditional Symbolic Regression applications are a form of supervised learning, where a label y is provided for every ~x and an explicit symbolic relationship of the form y = f(~x) is sought. This chapter explores the use of symbolic regression to perform unsupervised learning by searching for implicit relationships of the form f(~x, y) = 0. Implicit relationships are more general and more expressive than explicit equations in that they can also represent closed surfaces, as well as continuous and discontinuous multi-dimensional manifolds. However, searching these types of equations is particularly challenging because an error metric is diff cult to def ne. We studied several direct and indirect techniques, and present a successful method based on implicit derivatives. Our experiments identif ed implicit relationships found in a variety of datasets, such as equations of circles, elliptic curves, spheres, equations of motion, and energy manifolds.
2-year follow-up of trastuzumab after adjuvant chemotherapy in HER2-positive breast cancer: a randomised controlled trial

Trastuzumab--a humanised monoclonal antibody against HER2--has been shown to improve disease-free survival after chemotherapy in women with HER2-positive early breast cancer. We investigated the drug's effect on overall survival after a median follow-up of 2 years in the Herceptin Adjuvant (HERA) study.



HERA is an international multicentre randomised trial that compared 1 or 2 years of trastuzumab treatment with observation alone after standard neoadjuvant or adjuvant chemotherapy in women with HER2-positive node positive or high-risk node negative breast cancer. 5102 women participated in the trial; we analysed data from 1703 women who had been randomised for treatment with trastuzumab for 1 year and 1698 women from the control group, with median follow-up of 23.5 months (range 0-48 months). The primary endpoint of the trial was disease-free survival. Here, we assess overall survival, a secondary endpoint. Analyses were done on an intent-to-treat basis. 
97 (5.7%) patients randomised to observation alone and 58 (3.4%) patients randomised to 1 year of treatment with trastuzumab were lost to follow-up. 172 women stopped trastuzumab prematurely. 59 deaths were reported for trastuzumab and 90 in the control group. The unadjusted hazard ratio (HR) for the risk of death with trastuzumab compared with observation alone was 0.66 (95% CI 0.47-0.91; p=0.0115). 218 disease-free survival events were reported with trastuzumab compared with 321 in the control group. The unadjusted HR for the risk of an event with trastuzumab compared with observation alone was 0.64 (0.54-0.76; p<0.0001).



Our results show that 1 year of treatment with trastuzumab after adjuvant chemotherapy has a significant overall survival benefit after a median follow-up of 2 years. The emergence of this benefit after only 2 years reinforces the importance of trastuzumab in the treatment of women with HER2-positive early breast cancer.
I think therefore I om: cognitive distortions and coping style as mediators for the effects of mindfulness meditation on anxiety, positive and negative affect, and hope.

This study examined cognitive distortions and coping styles as potential mediators for the effects of mindfulness meditation on anxiety, negative affect, positive affect, and hope in college students. Our pre- and postintervention design had four conditions: control, brief meditation focused on attention, brief meditation focused on loving kindness, and longer meditation combining both attentional and loving kindness aspects of mindfulness. Each group met weekly over the course of a semester. Longer combined meditation significantly reduced anxiety and negative affect and increased hope. Changes in cognitive distortions mediated intervention effects for anxiety, negative affect, and hope. Further research is needed to determine differential effects of types of meditation.
Research on computer vision-based for UAV autonomous landing on a ship

In this paper, a novel approach to UAV’s automatic landing on the ship’s deck is proposed. We present the design of the cooperative object, and then begin our basic research on UAV autonomous landing on a ship by using computer vision and affine moment invariants. We analyze the infrared radiation images in our experiments by extracting the target from the background and then recognizing it. Also, we calculate the angle of yaw. We study the basic research concerning automatic UAV navigation and landing on the deck. Based on our experiments, the average recognition time is 17.2 ms which is obtained through the use of affine moment invariants. This type of speed is expected to improve the reliability and real-time performance of autonomous UAV landing.
Channel Feedback Codebook Design for Millimeter-Wave Massive MIMO Systems Relying on Lens Antenna Array

The recently proposed millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) system relying on a lens antenna array (LAA) significantly reduces the number of radio frequency chains using beam selection. A high data rate can be achieved based on the reduced-dimensional equivalent channel after beam selection. In frequency division duplexing systems, the equivalent channel has to be fed back to the base station (BS) via a feedback channel based on a codebook. However, no dedicated codebook has been proposed for LAA-aided mmWave systems. To fill this gap, in this letter, we propose a reduced-dimensional subspace codebook (RDSC) for such systems. Specifically, under the recently proposed concept of angle coherence time, we first generate the large-dimensional vectors in the channel subspace, which is determined by the angles-of-departure of the dominant paths. Then, based on these vectors in the channel subspace, we create the RDSC by considering both the lens and the beam selector. Finally, the equivalent channel is quantized using the proposed RDSC and fed back to the BS. Finally, we carry out mathematical performance analysis of the proposed RDSC and show that its feedback overhead is rendered proportional to the relatively small number of dominant paths per user. The analytical results are verified by our simulations.
Guessing Attacks on User-Generated Gesture Passwords

Touchscreens, the dominant input type for mobile phones, require unique authentication solutions. Gesture passwords have been proposed as an alternative ubiquitous authentication technique. Prior security analysis has relied on inconsistent measurements such as mutual information or shoulder surfing attacks.We present the first approach for measuring the security of gestures with guessing attacks that model real-world attacker behavior. Our major contributions are: 1) a comprehensive analysis of the weak subspace for gesture passwords, 2) a method for enumerating the size of the full theoretical gesture password space, 3) a design of a novel guessing attack against user-chosen gestures using a dictionary, and 4) a brute-force attack used for benchmarking the performance of the guessing attack. Our dictionary attack, tested on newly collected user data, achieves a cracking rate of 47.71% after two weeks of computation using 109 guesses. This is a difference of 35.78 percentage points compared to the 11.93% cracking rate of the brute-force attack. In conclusion, users are not taking full advantage of the large theoretical password space and instead choose their gesture passwords from weak subspaces. We urge for further work on addressing this challenge.
ANO1/TMEM16A interacts with EGFR and correlates with sensitivity to EGFR-targeting therapy in head and neck cancer

The epidermal growth factor receptor (EGFR) contributes to the pathogenesis of head&neck squamous cell carcinoma (HNSCC). However, only a subset of HNSCC patients benefit from anti-EGFR targeted therapy. By performing an unbiased proteomics screen, we found that the calcium-activated chloride channel ANO1 interacts with EGFR and facilitates EGFR-signaling in HNSCC. Using structural mutants of EGFR and ANO1 we identified the trans/juxtamembrane domain of EGFR to be critical for the interaction with ANO1. Our results show that ANO1 and EGFR form a functional complex that jointly regulates HNSCC cell proliferation. Expression of ANO1 affected EGFR stability, while EGFR-signaling elevated ANO1 protein levels, establishing a functional and regulatory link between ANO1 and EGFR. Co-inhibition of EGFR and ANO1 had an additive effect on HNSCC cell proliferation, suggesting that co-targeting of ANO1 and EGFR could enhance the clinical potential of EGFR-targeted therapy in HNSCC and might circumvent the development of resistance to single agent therapy. HNSCC cell lines with amplification and high expression of ANO1 showed enhanced sensitivity to Gefitinib, suggesting ANO1 overexpression as a predictive marker for the response to EGFR-targeting agents in HNSCC therapy. Taken together, our results introduce ANO1 as a promising target and/or biomarker for EGFR-directed therapy in HNSCC.
A Flexible Ultrasound Transducer Array with Micro-Machined Bulk PZT

This paper proposes a novel flexible piezoelectric micro-machined ultrasound transducer, which is based on PZT and a polyimide substrate. The transducer is made on the polyimide substrate and packaged with medical polydimethylsiloxane. Instead of etching the PZT ceramic, this paper proposes a method of putting diced PZT blocks into holes on the polyimide which are pre-etched. The device works in d31 mode and the electromechanical coupling factor is 22.25%. Its flexibility, good conformal contacting with skin surfaces and proper resonant frequency make the device suitable for heart imaging. The flexible packaging ultrasound transducer also has a good waterproof performance after hundreds of ultrasonic electric tests in water. It is a promising ultrasound transducer and will be an effective supplementary ultrasound imaging method in the practical applications.
CLIPS : Customized Levels of IoT Privacy and Security

Internet of Things (IoT) refers to systems that can be attached to the Internet and thus can be accessed and controlled remotely. Such devices are essential for creating ”smart things” like smart homes, smart grids, etc. IoT has achieved unprecedented success. It offers an interconnected network where devices (in the consumer space) can all communicate with each other. However, many IoT devices only add security features as an afterthought. This has been a contributing factor in many of the recently reported attacks and warnings of potential attacks such as those aimed at gaining control of autonomous cars. Many IoT devices are compact and feature limited computing resources, which often limits their ability to perform complex operations such as encryption or other security and privacy checks. With capabilities of devices in IoT varying greatly, a one-size-fits-all approach to security can prove to be inadequate. We firmly believe that safety and privacy should both be easy to use, present little inconvenience for users of non-critical systems, yet be as strong as possible to minimize breaches in critical systems. In this paper, we propose a novel architecture that caters to devicespecific security policies in IoT environments with varying levels of functionalities and criticality of services they offer. This would ensure that the best possible security profiles for IoT are enforced. We use a smart home environment to illustrate the architecture. Internet of Things (IoT); Software Defined Networking (SDN); IoT Security.
Evaluation of machine-learning protocols for technology-assisted review in electronic discovery

Using a novel evaluation toolkit that simulates a human reviewer in the loop, we compare the effectiveness of three machine-learning protocols for technology-assisted review as used in document review for discovery in legal proceedings. Our comparison addresses a central question in the deployment of technology-assisted review: Should training documents be selected at random, or should they be selected using one or more non-random methods, such as keyword search or active learning? On eight review tasks -- four derived from the TREC 2009 Legal Track and four derived from actual legal matters -- recall was measured as a function of human review effort. The results show that entirely non-random training methods, in which the initial training documents are selected using a simple keyword search, and subsequent training documents are selected by active learning, require substantially and significantly less human review effort (P<0.01) to achieve any given level of recall, than passive learning, in which the machine-learning algorithm plays no role in the selection of training documents. Among passive-learning methods, significantly less human review effort (P<0.01) is required when keywords are used instead of random sampling to select the initial training documents. Among active-learning methods, continuous active learning with relevance feedback yields generally superior results to simple active learning with uncertainty sampling, while avoiding the vexing issue of "stabilization" -- determining when training is adequate, and therefore may stop.
Fuzzing: State of the Art

As one of the most popular software testing techniques, fuzzing can find a variety of weaknesses in a program, such as software bugs and vulnerabilities, by generating numerous test inputs. Due to its effectiveness, fuzzing is regarded as a valuable bug hunting method. In this paper, we present an overview of fuzzing that concentrates on its general process, as well as classifications, followed by detailed discussion of the key obstacles and some state-of-the-art technologies which aim to overcome or mitigate these obstacles. We further investigate and classify several widely used fuzzing tools. Our primary goal is to equip the stakeholder with a better understanding of fuzzing and the potential solutions for improving fuzzing methods in the spectrum of software testing and security. To inspire future research, we also predict some future directions with regard to fuzzing.
Isoliquiritigenin, a flavonoid from licorice, plays a dual role in regulating gastrointestinal motility in vitro and in vivo.

Licorice root has been used for years to regulate gastrointestinal function in traditional Chinese medicine. This study reveals the gastrointestinal effects of isoliquiritigenin, a flavonoid isolated from the roots of Glycyrrhiza glabra (a kind of Licorice). In vivo, isoliquiritigenin produced a dual dose-related effect on the charcoal meal travel, inhibitory at the low doses, while prokinetic at the high doses. In vitro, isoliquiritigenin showed an atropine-sensitive concentration-dependent spasmogenic effect in isolated rat stomach fundus. However, a spasmolytic effect was observed in isolated rabbit jejunums, guinea pig ileums and atropinized rat stomach fundus, either as noncompetitive inhibition of agonist concentration-response curves, inhibition of high K(+) (80 mM)-induced contractions, or displacement of Ca(2+) concentration-response curves to the right, indicating a calcium antagonist effect. Pretreatment with N(omega)-nitro-L-arginine methyl ester (L-NAME; 30 microM), indomethacin (10 microM), methylene blue (10 microM), tetraethylammonium chloride (0.5 mM), glibenclamide (1 microM), 4-aminopyridine (0.1 mM), or clotrimazole (1 microM) did not inhibit the spasmolytic effect. These results indicate that isoliquiritigenin plays a dual role in regulating gastrointestinal motility, both spasmogenic and spasmolytic. The spasmogenic effect may involve the activating of muscarinic receptors, while the spasmolytic effect is predominantly due to blockade of the calcium channels.
Reliability and validity of Somali version of the PHQ-9 in primary care practice.

Depression is one of the common mental health problems noticed in immigrants because of the experiences related to their resettlement which is the case for Somali population. Depression increases mortality, morbidity, disability, and costs of health care which can be controlled by screening depression in the primary care setting using a culturally and linguistically congruent screening tool. The aim of the current study is to translate the English PHQ-9 into Somali language using evidence-based translational methodology and establish psychometric properties of the Somali PHQ-9.  The initial validation of the Somali PHQ-9 was studied by comparing the original and back translation versions using the comparability and interpretability tool in a sample of 56 monolingual health care professionals. The reliability and validity of the Somali version were established by psychometric analysis in a sample of 47 bilingual health-care workers. 's alpha was 0.79 for the Somali version with the inter-item correlation mean of 0.33 and item-to-total correlation mean in the range of 0.40-0.80 ( p < 0.01). Pearson correlation for the item-to-item correlation between English and Somali version was between 0.70 and 0.93 ( p < 0.01) with the paired t-test showing no significant difference between the item means.  The Somali PHQ-9 showed a good reliability, homogeneity, and internal consistency. The construct validity for the Somali PHQ-9 was also established showing that the Somali PHQ-9 has similar reliability and validity like the other translated versions of PHQ-9.
Reasoning with Sarcasm by Reading In-Between

Sarcasm is a sophisticated speech act which commonly manifests on social communities such as Twitter and Reddit. The prevalence of sarcasm on the social web is highly disruptive to opinion mining systems due to not only its tendency of polarity flipping but also usage of figurative language. Sarcasm commonly manifests with a contrastive theme either between positive-negative sentiments or between literal-figurative scenarios. In this paper, we revisit the notion of modeling contrast in order to reason with sarcasm. More specifically, we propose an attention-based neural model that looks inbetween instead of across, enabling it to explicitly model contrast and incongruity. We conduct extensive experiments on six benchmark datasets from Twitter, Reddit and the Internet Argument Corpus. Our proposed model not only achieves stateof-the-art performance on all datasets but also enjoys improved interpretability.
On Searching Relevant Studies in Software Engineering

Systematic Literature Review (SLR) has become an important research methodology in software engineering since 2004. One critical step in applying this methodology is to design and execute appropriate and effective search strategy. This is quite time consuming and error-prone step, which needs to be carefully planned and implemented. There is an apparent need of a systematic approach to designing, executing, and evaluating a suitable search strategy for optimally retrieving the target literature from digital libraries.
Decentralized decision support for intelligent manufacturing in Industry 4.0

“Industry 4.0” is recognized as the future of industrial production in which concepts as Smart Factory and Decentralized Decision Making are fundamental. This paper proposes a novel strategy to support decentralized decision, whilst identifying opportunities and challenges of Industry 4.0 contextualizing the potential that represents industrial digitalization and how technological advances can contribute for a new perspective on manufacturing production. It is analysed a set of barriers to the full implementation of Industry 4.0 vision, identifying areas in which decision support is vital. Then, for each of the identified areas, the authors propose a strategy, characterizing it together with the level of complexity that is involved in the different processes. The strategies proposed are derived from the needs of two of Industry 4.0 main characteristics: horizontal integration and vertical integration. For each case, decision approaches are proposed concerning the type of decision required (strategic, tactical, operational and real-time). Validation results are provided together with a discussion on the main challenges that might be an obstacle for a successful decision strategy.