Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of Structural Parsers and Neural Language Models as Surprisal Estimators

Expectation-based theories of sentence processing posit that processing difficulty is determined by predictability in context. While predictability quantified via surprisal has gained empirical support, this representation-agnostic measure leaves open the question of how to best approximate the human comprehender's latent probability model. This article first describes an incremental left-corner parser that incorporates information about common linguistic abstractions such as syntactic categories, predicate-argument structure, and morphological rules as a computational-level model of sentence processing. The article then evaluates a variety of structural parsers and deep neural language models as cognitive models of sentence processing by comparing the predictive power of their surprisal estimates on self-paced reading, eye-tracking, and fMRI data collected during real-time language processing. The results show that surprisal estimates from the proposed left-corner processing model deliver comparable and often superior fits to self-paced reading and eye-tracking data when compared to those from neural language models trained on much more data. This may suggest that the strong linguistic generalizations made by the proposed processing model may help predict humanlike processing costs that manifest in latency-based measures, even when the amount of training data is limited. Additionally, experiments using Transformer-based language models sharing the same primary architecture and training data show a surprising negative correlation between parameter count and fit to self-paced reading and eye-tracking data. These findings suggest that large-scale neural language models are making weaker generalizations based on patterns of lexical items rather than stronger, more humanlike generalizations based on linguistic structure.
Transcriptome Analysis Revealed a Cold Stress-Responsive Transcription Factor, PaDREB1A, in Plumbago auriculata That Can Confer Cold Tolerance in Transgenic Arabidopsis thaliana

The tropical plant Plumbago auriculata can tolerate subzero temperatures without induction of apoptosis after cold acclimation in autumn, making it more cold tolerant than conventional tropical plants. In this study, we found that low temperatures significantly affected the photosynthetic system of P. auriculata. Using transcriptome sequencing, PaDREB1A was identified as a key transcription factor involved in the response to cold stress in P. auriculata. This transcription factor may be regulated by upstream JA signaling and regulates downstream ERD4 and ERD7 expression to resist cold stress. Overexpression of PaDREB1A significantly enhanced freezing resistance, protected the photosynthetic system, and enhanced the ROS scavenging mechanism under cold stress in Arabidopsis thaliana. Additionally, PaDREB1A significantly enhanced the expression of CORs and CAT1 in A. thaliana, which further activated the downstream pathway to enhance plant cold tolerance. This study explored the possible different regulatory modes of CBFs in tropical plants and can serve as an important reference for the introduction of tropical plants to low-temperature regions.
Laparoscopic Gastrectomy for Cancer: Cut Down Complications to Unveil Positive Results of Minimally Invasive Approach

Several randomized controlled trials and meta-analyses have confirmed the advantages of laparoscopic surgery in early gastric cancer, and there are indications that this may also apply in advanced distal gastric cancer. The study objective was to evaluate the safety and effectiveness of laparoscopic gastrectomy (LG), in comparison to open gastrectomy (OG), in the management of locally advanced gastric cancer. The single-center, case–control study included 204 patients, in conveyance sampling, who underwent radical gastrectomy for locally advanced gastric cancer. Out of 204 patients, 102 underwent LG, and 102 patients underwent OG. The primary endpoints were safety endpoints, i.e., complication rates, reoperation rates, and 30-day mortality rates. The secondary endpoints were efficacy endpoints, including perioperative characteristics and oncological outcomes. Even though the overall complication rate was higher in the OG group compared to the LG group (30.4% and 19.6%, respectively), the difference between groups did not reach statistical significance (p = 0.075). No significant difference was identified in reoperation rates and 30-day mortality rates. Time spent in the intensive care unit (ICU) and overall hospital stay were shorter in the LG group compared to the OG group (p < 0.001). Although the number of retrieved lymph nodes is oncologically adequate in both groups, the median number is higher in the OG group (35 vs. 29; p = 0.024). Resection margins came out to be negative in 92% of patients in the LG group and 73.1% in the OG group (p < 0.001). The study demonstrated statistically longer survival rates for the patients in the laparoscopic group, which particularly applies to patients in the most prevalent, third stage of the disease. When patients with the Clavien–Dindo grade ≥II were excluded from the survival analysis, further divergence of survival curves was observed. In conclusion, LG can be safely performed in patients with locally advanced gastric cancer and accomplish the oncological standard with short ICU and overall hospital stay. Since postoperative complications could affect overall treatment results and diminish and blur the positive effect of the minimally invasive approach, further clinical investigations should be focused on the patients with no surgical complications and on clinical practice to cut down the prevalence of complications.
Investigating the Relationship Between Entity Financialization, Managers’ Incentives, and Enterprise’s Innovation: Fresh Evidence From China

The current study examines the relationship between financialization, managers’ incentives, and the enterprise’s innovation. Based on the principal-agent and incentive theories, this study proposes a research model with two management incentives as moderating variables between financialization and the enterprise’s innovation. First, we analyze the direct relationship between financialization and the enterprise’s innovation. Second, we examine the moderating effect of managers’ equity incentive and compensation incentives on the relationship between entity financialization and the enterprise’s innovation in high-tech/non-high-tech enterprises and state-owned and non-state-owned enterprises. This study covers the most recent updated data from both A-share listed companies in the Shenzhen and Shanghai stock exchange in China from 2009 to 2019. This study’s finding indicates a significant negative impact of entity financialization and the enterprise’s innovation. It means that the entity financial has a significant “crowding-out” effect on the enterprise’s innovation. This study also confirms that management incentives cannot effectively suppress a “crowding-out” impact of entity financialization on firm innovation because of the principal-agent severe problem in financialization. Finally, considering the heterogeneities of property rights and degrees of dependence on the enterprise’s innovation, a “crowding-out” effect of entity financialization on the enterprise’s innovation is more significant in high-tech and state-owned enterprises. Managers’ equity incentive significantly affects the enterprise’s innovation in high-tech enterprises, while the managers’ compensation incentive affects the enterprise’s innovation in state-owned enterprises. Our study could help the enterprise to improve the company manager’s incentive and provide the optimal assets allocation to improve the enterprise’s innovation ability. Lastly, this study provides significant policies and recommendations for the public sector high-tech enterprise and private sector high-tech enterprises. Moreover, policies and recommendations are fruitful for the public sector non-high-tech enterprise and private sector non-high-tech enterprise.
Delayed Senescence and Marketability Index Preservation of Blackberry Fruit by Preharvest Application of Chitosan and Salicylic Acid

Blackberry fruits are appreciated as a source of nutrients and compounds related to benefit human health. However, they are highly perishable and very susceptible to decay factors. Current methods to improve and maintain blackberry quality are limited in use because of the fruit's fragile physical properties. Regarding these properties, it has been reported that the activities of certain enzymes are linked to senescence and fruit softening processes. This study was aimed to assess the effect of salicylic acid (SA) and chitosan (COS) as preharvest treatments on the physiology related to improving fruit conservation and preserving the marketability index of blackberry fruit. The preharvest treatments were foliar sprayed on blackberry plants at different concentrations. The activities of enzymes superoxide dismutase (SOD), catalase (CAT), phenylalanine ammonia-lyase (PAL), and polygalacturonase (PG) were measured. Total soluble solids (TSS), titratable acidity (TA), TSS/TA ratio, and marketability index (MI) were analyzed after 144 h of storage. The application of 3 mM of SA and 0.25% of COS treatments preserved the MI of blackberries by reducing leakage, red drupelet reversion (RDR), and mycelium presence in the fruit. SA application increased SOD, CAT, and PAL activities. Our results also showed that SA and COS preharvest treatments modified the activity of the cell wall degrading enzyme PG, which might play a role in improving the shelf life and resistance to decay factors of blackberry fruit without any significant effects on physicochemical properties like TSS, TA, and the TSS/TA ratio.
Memory Modulation Via Non-invasive Brain Stimulation: Status, Perspectives, and Ethical Issues

While research to improve memory or counter decay caused by neurodegenerative diseases has a fairly long history, scientific attempts to erase memories are very recent. The use of non-invasive brain stimulation for memory modulation represents a new and promising application for the treatment of certain disorders [such as Post-Traumatic Stress Disorder (PTSD)]. However, numerous ethical issues are related to memory intervention. In particular, the possibility of using forms of non-invasive brain stimulation requires to distinguish treatment interventions from the enhancement of the healthy. Furthermore, a range of important societal and legal concerns arise when manipulating memories. In this short contribution, we address some of the most significant ethical, social, and legal implications surrounding the application of memory-modulation techniques and offer a series of reflections and considerations, which we hope can be of use to guide -and perhaps regulate- their potential, future implementation in society.
The Relationship Between Self-Care Behavior and Concerns About Body Image in Patients Undergoing Hemodialysis in Iran

Background and Aim Hemodialysis treatment saves the life of people with end-stage renal disease (ERDS), but does not prevent the suffering of the disease, anxiety, hopelessness, and so on. Many studies have been performed on self-care behaviors as well as body image in different patients, but so far, no research has been done to investigate the relationship between self-care behavior and body image concerns in hemodialysis patients. Therefore, the aims of this study are to determine the relationship between self-care behavior and body image concern in patients undergoing hemodialysis. Materials and Methods A cross-sectional design was used to evaluate Self-care Behavior and Concerns about Body Image in a convenience sample of 280 patients with ERDS. Measures included demographic factors, health characteristics, and validated instruments of the study constructs Body Image Concern Questionnaire (BICI) and Assessment of self-care behaviors with arteriovenous fistula (ASBHD-AVF). Results This study showed that self-care behaviors have the ability to predict body image concerns. There was a negative and significant relationship between self-care behavior and body image concern (B = −0.162, β = −0.140, p = 0.020). These variables explain 7.5% of predictors. Conclusion Although the findings of the present study showed that increasing age and improving the level of self-care behaviors in patients undergoing hemodialysis reduces body image anxiety, but women were the strongest predictor of body image anxiety.
The Emerging Role of PRMT6 in Cancer

Protein arginine methyltransferase 6 (PRMT6) is a type I PRMT that is involved in epigenetic regulation of gene expression through methylating histone or non-histone proteins, and other processes such as alternative splicing, DNA repair, cell proliferation and senescence, and cell signaling. In addition, PRMT6 also plays different roles in various cancers via influencing cell growth, migration, invasion, apoptosis, and drug resistant, which make PRMT6 an anti-tumor therapeutic target for a variety of cancers. As a result, many PRMT6 inhibitors are being utilized to explore their efficacy as potential drugs for various cancers. In this review, we summarize the current knowledge on the function and structure of PRMT6. At the same time, we highlight the role of PRMT6 in different cancers, including the differentiation of its promotive or inhibitory effects and the underlying mechanisms. Apart from the above, current research progress and the potential mechanisms of PRMT6 behind them were also summarized.
Cyberintrusion Detection in Critical Infrastructure

Sophisticated cyberterrorists have sufficient knowledge to devise an attack through the Internet which could compromise critical resource delivery. As the threat of such cybercrime escalates, defending critical infrastructure is a primary focus of the United States government, industry executives, and the research community. Current research and development primarily focuses on preventing the cyberterrorist from accomplishing his mission of disruption. This research focuses not on prevention, but on detection. Its main objective is the development of an algorithm that can be used to detect data anomalies which may be the result of security breaches. Grounded in multivariate statistical process control, the algorithm uses principal component analysis to separate data variability into common-cause and assignable-cause subspaces. Analysis using the common-cause subspace determines whether the data has been compromised. Successful results will add a dimension of protection for critical infrastructure systems that has not previously been addressed in the literature. Implementation of the algorithm in a process control system could significantly improve the security of operational and planning practices today and in the future. In process control operations, wireless transmission of measurements could be interrupted or data storage in databases on the TCP/IP network could be corrupted or compromised through malware or other human interference. Data errors resulting from any of these occurrences could disrupt physical processes in critical infrastructure. This innovative algorithm provides a solution to this problem.
The Peak to Average Power Reduction (PAPR) Technique of OFDM Signal by using Clipping and Filtering Method

Orthogonal Frequency Division Multiplexing (OFDM) has several attributes which make it a preferred modulation scheme for high speed wireless communication. Orthogonal Frequency Division Multiplexing (OFDM) has been currently under intense research for broadband wireless transmission due to its robustness against multipath fading. However OFDM signals have a problem with high Peak-to- Average power ratio (PAPR) and thus, a power amplifier must be carefully manufactured to have a linear input-output characteristic or to have a large input power back-off. In recent years, many peak-to-average power ratio (PAPR) reduction techniques have been proposed for orthogonal frequency division multiplexing (OFDM) signals. Among various techniques, the clipping and filtering technique has been considered as a practical scheme, and widely used owing to its non-expansion of bandwidth, low computational complexity, and simplicity in implementation without receiverside cooperation.
Nonlinear Behaviour And Digital Phase Predistortion Of Outphasing Power Amplifiers

The nonlinear behaviour of an outphasing 24W power amplifier (PA) for WCDMA basestation applications at 2.14GHz is investigated. For this purpose the nonlinear transfer characteristics are determined by measurements. Afterwards a digital phase-only predistortion is used to investigate the capability of a digital linearization approach. Two different test signals are applied to study the linearization performance. Firstly for a two-tone signal as a classical test signal an overall distortion level of -43dBc and secondly for an UMTS application utilizing a pseudo-noise (PN) modulated QPSK signal an adjacent channel power ratio (ACPR) of about -43dBc are achieved.
P o S ( E P SH E P 2 0 2 1 ) 6 0 2 Searches for Higgs invisible

A summary of searches for Higgs bosons decaying to invisible particles using the data collected by the CMS experiment is presented. This report focuses on three stages of these analyses. First, the combination of results using data collected during the Run 1 ( √ s = 7 and 8 TeV, with 24.6 fb−1 of total integrated luminosity) and early Run 2 ( √ s = 13 TeV, with 38.2 fb−1) data taking periods is presented. This combination places a limit on the B(H → inv) at 0.20 (0.19) in terms of the observed (expected) 95 % Confidence Level (CL) upper limit. It is followed by a look into the currently available results focusing on the entire Run 2 phase of data collection (137 fb−1), namely the analyses targeting the VH production mode of the Higgs boson. Lastly, a summary of future prospects is presented in terms of the most sensitive channel of this search, indicating the possibility of further constraining the B(H→ inv) to 0.038 during the High Luminosity (HL) phase of operation of the Large Hadron Collider (LHC).
Modeling of ultrashort optical pulses in nonlinear fibers

This work deals with theoretical aspects of pulse propagation. The core focus is on extreme, few-cycle pulses in optical fibers, pulses that are strongly affected by both dispersion and nonlinearity. Using Hamiltonian methods, we discuss how the meaning of pulse envelope changes, as pulses become shorter and shorter, and why an envelope equation can still be used. We also discuss how the standard set of dispersion coefficients yields useful rational approximations for the chromatic dispersion in optical fibers. Three more specific problems are addressed thereafter. First, we present an alternative framework for ultrashort pulses in which non-envelope propagation models are used. The approach yields the limiting, shortest solitons and reveals their universal features. Second, we describe how one can manipulate an ultrashort pulse, i.e., to change its amplitude and duration in a predictable manner. Quantitative theory of the manipulation is presented based on perturbation theory for solitons and analogy between classical fiber optics and quantum mechanics. Last but not least, we consider a recently found alternative to the standard split-step approach for numerical solutions of the pulse propagation equations. DOI 10.20347/WIAS.PREPRINT. 2918 Berlin 2022
Determining the Relationship between Non- HDL Cholesterol and Syntax Score in Patients with Acute Coronary Syndrome Under 45 Years of Age

Cardiovascular diseases (CVDs) remains to be the most common cause of death in the world despite the growing medical knowledge, many emerging cardiovascular drugs, and the development of the medical device industry in the 21st century. According to the data of the World Health Organization, 17.9 million deaths were reported in the world due to CVDs in 2019, representing 32% of all global deaths. [1] In the TEKHARF study conducted in our country, coronary mortality in the age range of 45-74 years was found to be 7.3 per 1000 population in men and 3.8 years in women. [2]
The Affordances of Quality

The phrase “build quality in” has become ubiquitous in the software industry. Many books, articles and papers propose specific examples of building in quality, but what is the common thread that ties these approaches together? How should someone looking to “build quality in” approach the problem at a high level? This paper explores the idea of affordances, from the field of Human Centered Design, and how they can be used to identify places where quality can be built into the process.
Rancangan Pengembangan Sediaan Nanospraygel in situ Mengandung

Cinnamon bark oil is known to have antifungal activity so it can be used for oral candidiasis treatment. Thick and impenetrable oral mucosa needs to be treated with modification. Development of in situ nanospraygel can increase the effectiveness and reduce the risk of contamination of the preparation. This study tries to investigate the antifungal activity of cinnamon bark oil, determine suitable formula for the cinnamon bark oil nanoemulsion, and determine the type of gelling agent that can be used to develop in situ nanospraygel. The design of in situ nanospraygel formula containing cinnamon bark oil was carried out by Systematic Literature Review. The study was conducted on articles from reputable databases that matched the inclusion and exclusion criteria. The results of study showed that cinnamon bark oil of Cinnamomum burmannii has antifungal activity against Candida albicans with a minimum inhibitory concentration of 0.039%. Cinnamon bark oil 1% can be formulated into a good nanoemulsion preparation, using Tween 80 as a surfactant with a ratio of oil and surfactant 1:3.The combination of carbopol 934P & gellan gum with a concentration of 0.2% each can be used as an in situ gelling agent to produce cinnamon bark oil Nanospraygel in situ.
Artificial intelligence empowered threat detection in the Internet of Things: A systematic review

Internet of Things (IoT) is a new phenomenon that proposes novel business opportunities. IoT allows the world to be programmable and might provide several benefits for organizations. Based on the IoT survey, cyber‐security issues are among the most extensive and complicated challenges faced by IoT devices. Threat detection is considered a preventive measure against malware threats, ransomware, and attacks, which become more serious each year because of the dramatic rise in malware attacks. This article investigates threat detection techniques that fall into three categories: malware detection, attack detection, and ransomware detection, published from 2017 to August 2021. We examine solutions, techniques, features, classifiers, and tools proposed by IoT researchers. Some questions are proposed, and answering the questions may help the researchers suggest a more efficient solution in future works. Furthermore, the achievement and disadvantages of each study are discussed. Finally, based on the reviewed studies, some open challenges and practical measures to future directions are suggested, worth further studying and researching threat detection techniques in the IoT.
The travel dream experience in pandemic times

ABSTRACT This study was developed to understand how tourists feel after dreamed travel experiences ended up cancelled. The orchestra model that considers experiences as an intermingled process was applied to analyse the negative feelings experienced by tourists during these pandemic times. Through web scraping, over 40 thousand comments from 600 threads discussing the pandemic impact on tourists’ inability to concretize their dreams were extracted from the TripAdvisor forum. Those comments were subjected to data mining techniques, including the generation of topic modelling and analysis of sentiment scores across continents vis-à-vis reported cases and fatalities. Results suggested that despite the disillusion for not being able to travel, tourists were understanding and mostly concerned with the health of their peers.