Miracle-dz/UniFAR-FTUs huggingface dataset:
Do the Locally Advanced Rectal Cancer Patients Enjoy Long-term Survival Benefit From the Radiation-based Neoadjuvant Treatments in the Total Mesorectal Excision Era: a Population-based Analysis

Background: Radiation-based neoadjuvant therapy followed by radical surgery is the standard treatment for locally advanced rectal cancer (LARC), but things might have changed with the advent of total mesorectal excision (TME). This study re-evaluated the clinical efficacy of preoperative radiotherapy for LARC patients in the TME era by population-based analysis to identify any long-term survival benefits. Methods: LARC patients receiving preoperative radiotherapy or not followed by surgery between 2011 and 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Overall survival (OS) was analyzed by Kaplan-Meier curves, and potential candidates for preoperative radiotherapy were identified by nomogram. Results: There were 7582 eligible patients; 6066 received preoperative radiotherapy, and 1516 received non-preoperative radiotherapy. The initial result showed that the pooled hazard ratio (HR) for OS was in favor of preoperative radiotherapy compared with non-preoperative radiotherapy group (HR = 0.86, 95% confidence interval (CI) = 0.75-0.98, P <0.05). The cases were randomly divided into training and validation datasets, and multivariate Cox regression analysis of the training set determined that age, sex, carcinoembryonic antigen level, tumor stage, node stage, tumor differentiation, perineural invasion, and the number of dissected lymph nodes were independent risk factors for OS in the training set (all P <0.05). A nomogram was established based on the risk factors to predict the OS (concordance index, training set: 0.70, validation set: 0.67). Further analysis showed that the long-term survival of high-risk patients was better with preoperative radiotherapy (HR = 0.71, 95% CI = 0.56-0.91, P <0.05). Conclusions: Preoperative radiotherapy has long-term survival benefits for LARC patients, especially those with high risk.
A novel focal-loss and class-weight-aware convolutional neural network for the classification of in-text citations

We argue that citations, as they have different reasons and functions, should not all be treated in the same way. Using the large, annotated dataset of about 10K citation contexts annotated by human experts, extracted from the Association for Computational Linguistics repository, we present a deep learning–based citation context classification architecture. Unlike all existing state-of-the-art feature-based citation classification models, our proposed convolutional neural network (CNN) with fastText-based pre-trained embedding vectors uses only the citation context as its input to outperform them in both binary- (important and non-important) and multi-class (Use, Extends, CompareOrContrast, Motivation, Background, Other) citation classification tasks. Furthermore, we propose using focal-loss and class-weight functions in the CNN model to overcome the inherited class imbalance issues in citation classification datasets. We show that using the focal-loss function with CNN adds a factor of ( 1 − p t ) γ to the cross-entropy function. Our model improves on the baseline results by achieving an encouraging 90.6 F1 score with 90.7% accuracy and a 72.3 F1 score with a 72.1% accuracy score, respectively, for binary- and multi-class citation classification tasks.
Do Credit Supply Shocks Affect Employment in Middle-Income Countries?

This paper studies the effect of bank credit supply shocks on formal employment in Mexico using a proprietary dataset containing information on all loans extended to firms by commercial banks during 2010–2015. We find large impacts on the formal employment of small and medium firms: a positive credit shock of 1 standard deviation increases yearly employment by 1.4 percentage points. The shares of uncollateralized credit and credit received by family firms, younger firms, and firms with no previous bank relationships also increase, suggesting that credit shocks may play a more prominent role for employment creation in credit-constrained settings. (JEL D22, G21, G32, J23, L25, M51, O16)
How do network attributes impact information virality in social networks?

Purpose Social media platforms play a key role in information propagation and there is a need to study the same. This study aims to explore the impact of the number of close communities (represented by cliques), the size of these close communities and its impact on information virality. Design/methodology/approach This study identified 6,786 users from over 11 million tweets for analysis using sentiment mining and network science methods. Inferential analysis has also been established by introducing multiple regression analysis and path analysis. Findings Sentiments of content did not have a significant impact on the information virality. However, there exists a stagewise development relationship between communities of close friends, user reputation and information propagation through virality. Research limitations/implications This paper contributes to the theory by introducing a stagewise progression model for influencers to manage and develop their social networks. Originality/value There is a gap in the existing literature on the role of the number and size of cliques on information propagation and virality. This study attempts to address this gap.
Syrius: Synthesis of Rules for Intrusion Detectors

Network intrusion detection systems (NIDS) are popular tools to defend local networks against attacks. These systems monitor the network traffic and flag suspicious behavior. Rule-based NIDS do that by checking the network traffic against a set of rules, which become obsolete as attackers learn new strategies to circumvent existing defenses. This article proposes synthesis of suricata rules (Syrius), a novel approach to synthesize rules for rule-based NIDS. Syrius leverages malicious (positive) and benign (negative) traffic to create rules for new attacks. Syrius is organized as a pipeline of three components to 1) create an overspecified seed rule, 2) derive plausible rules from the seed, and 3) rank plausible rules. We evaluated Syrius against a set of 21 network attacks with various characteristics. Syrius was capable of generating the correct rule among the top-3 and top-1 rules of the ranking, respectively, in 80.1% and 47.6% of the cases.
Rating model of logistic attractiveness on the example of the Russian Federation

Anastasia A. Kuznetsova , Tatiana A. Burtseva , Tatiana A. Osipova, Pavel Yu. Grankov 3 1 Obninsk Institute for Nuclear Power Engineering 1 Studgorodok, 249040, Kaluga Region, Obninsk, Russian Federation e-mail: anastkuznetsova@rambler.ru; tatiana_osipova@yahoo.com MIREA–Russian Technological University 78 Vernadsky Avenue, 119454, Moscow, Russian Federation e-mail: tbur69@mail.ru; tatiana_osipova@yahoo.com JSC “Kaluga Region Agency for Innovation Development” 2 Tsvetkova str. , 249038, Kaluga region, Obninsk, Russian Federation e-mail: grankov@airko.org
A deep biometric hash learning framework for three advanced hand-based biometrics

Hand ‐ based biometrics has undergone extensive research in recent decades. Besides fingerprint, which is commonly used in personal authentication, there are other three advanced hand ‐ based biometrics that are further researched worldwide, such as palm-print, palm vein, and dorsal hand vein. However, the academics mainly focus on their unimodal or multimodal recognitions, and few researchers conduct comprehensive comparisons for them to guide practical applications, that is, to assess which one is the suitable biometric modality. Inspired by deep hashing network (DHN) and transfer learning, we propose a deep biometric hash learning (DBHL) framework to uniformly analyse and deal with these three biometrics. An end ‐ to ‐ end network is involved to convert images into binary codes. Pre ‐ trained network is employed for fine ‐ tuning, and the hamming distance is adopted to measure the similarity between the codes of query and registration images. Through experiments on benchmarks, equal error rate (EER) and the maximum or minimum distance of genuines or imposters are obtained as performance
Three-Level Optical Stark Effect of Excitons in GaAs Cylindrical Quantum Wires

This study looks at the three-level optical Stark effect of excitons in GaAs cylindrical quantum wires, utilizing the renormalized wave function theory. By applying the three-level model consisting of the first two electron levels connected via a powerful pump laser and the first hole level, we observe the appearance of the excitonic optical Stark effect through the appearance of two separated peaks in the exciton absorption spectra. In addition, the strong impact of the pump laser detuning and the wire radius on the optical Stark effect are also put under thorough examination. Finally, a brief guidance for experimental verification is also suggested.
Ghosting and orbiting: An analysis of victims’ experiences

Ghosting is the practice of ending a relationship without explaining to the partner and avoiding any communication attempts. Orbiting is identical to ghosting, but the disengager still visibly follows the former partner on social media. Despite the increasing attention that ghosting and orbiting have gained in the popular press, they remain largely unexplored phenomena in scientific inquiry. In this work, we explored the psychological and behavioral reactions to ghosting and orbiting from the victim’s perspective, comparing them to the experience of being rejected through direct communication. Participants were randomly assigned to recall one of three conditions (ghosting, orbiting, and rejection), and the reports of 208 young adults were analyzed through qualitative thematic content analysis. The results described different stages of reactions that follow event detection and that are respectively characterized by 1) surprise and confusion, 2) anger, sadness, and guilt, 3) attempts of relational repair, 4) acceptance. The specificities of being a victim of ghosting and orbiting are presented, comparing them with social rejection. The results are discussed in the light of the existing literature on social exclusion, suggesting that ghosting and orbiting can be considered forms of ostracism. Connections between the proposed stage model and traditional relationship dissolution theories are highlighted, and relevant implications for future research and interventions are presented.
Life cycle assessment of CO2-based C1-chemicals

Carbon dioxide (CO2) and hydrogen are promising feedstocks for a sustainable chemical industry. Currently, the conversions of CO2 and hydrogen are most advanced for chemicals with 1 carbon atom, the so-called C1-chemicals, with the first pilot plants in operation. For formic acid, carbon monoxide, methanol, and methane, CO2-based C1-chemicals can reduce the impacts of fossil depletion and global warming through the substitution of fossil-based processes. Existing life cycle assessment (LCA) studies for carbon monoxide, methanol, and methane show that a reduction in environmental impacts is achieved if hydrogen is supplied by water electrolysis with renewable electricity. However, in the foreseeable future, renewable electricity will be limited. Thus, from an environmental point of view, renewable electricity should be employed for chemical processes in the order of highest environmental impact reductions. Environmental impact reductions are the difference in environmental impacts of fossil-based processes and CO2-based processes. In this study, we compared the CO2-based production of formic acid, carbon monoxide, methanol, and methane. We determined the reduction of global warming and fossil depletion impacts using 1 kg of hydrogen. Our results show that the CO2-based production of formic acid achieves the highest environmental impact reductions, followed by carbon monoxide and methanol. The lowest environmental impact reductions are achieved for CO2-based methane production. Our analysis reveals that the CO2-based production of formic acid can reduce environmental impacts, compared to the fossil-based process, even if hydrogen is supplied by fossil-based steam-methane-reforming.
Optimizing a vehicle’s route in an on-demand ridesharing system in which users might walk

Abstract Within the context of a shared on-demand transport system, we study the problem of selecting the stopping points from which passengers should walk to their exact destinations (or from their exact origins). We focus on the single-vehicle case that must follow a predefined order of requests, posing the mathematical program, showing that it can be solved in polynomial time and proposing a heuristic that runs faster. We compare the optimal algorithm, the heuristic, and the routes that visit the exact request points, and we show that avoiding detours can reduce total costs by almost one fifth and vehicle costs by more than one third. The heuristic yields competitive results. Simulations over the real street network from Manhattan show that the time reduction achieved by the heuristic might be crucial to enable the system to operate in real-time.
Modification of raindrop size distribution due to seeder–feeder interactions between stratiform precipitation and shallow convection observed by X‐band polarimetric radar and optical disdrometer

The seeder–feeder interactions (SFIs), where raindrops from upper clouds grow by accreting cloud droplets in the lower clouds, have been extensively studied. However, there are few studies on the modification of raindrop size distribution (DSD) through this process. In the present study, rainfall from the landfalling rainbands of a typhoon was observed using an optical disdrometer and an X‐band polarimetric radar. Rainfall was classified into the following three types based on the DSD characteristics at the surface and the existence of a ρHV minimum in the upper layer: convective rainfall accompanied by a melting layer (type SF), convective rainfall without a melting layer (type C), and stratiform rainfall with a melting layer (type S). Type SF rainfall was regarded as having undergone SFIs between stratiform precipitation and shallow convection. The DSD for SF type rainfall was characterized by more small‐ to medium‐sized raindrops and a larger normalized intercept parameter than rainfall types C and S. An analysis using vertical profiles of radar‐derived DSD parameters for type SF rainfall suggested that the median‐volume diameter of raindrops increased by accreting cloud droplets in the lower clouds, and that small‐ to medium‐sized raindrops were produced by a warm rain process and breakup of raindrops.
Bottom‐up vs reactive sintering of Al2O3–YAG–YSZ composites via one or three‐phase nanoparticles (NPs). Bottom‐up processing wins this time

The bottom-up approach describes the synthesis of bulk materials from the finest possible length scales to obtain the best global properties. This approach was adapted to the synthesis of multi-phase ceramic composites produced from metal oxides produced by liquid-feed flame spray pyrolysis (LF-FSP). The effect of length scale of mixing was tested through two processing schemes, mixed single metal-oxide nanopowders (NPs) and nanocomposite NPs having the desired composition within single particles. For the Al2O3–Y2O3–ZrO2 ternary system, composites prepared from nanostructured nanoparticles sinter to finer grain sizes (<410 nm) at equivalent densities of 95%TD than those prepared from mixed nanoparticle processing. These contrast with our previous studies in this area where mixed NP processing gave the best or equivalent results. The nanocomposite NPs produced in this study exhibit novel nanostructures with three phases contained within single particles <26 nm average particle size (APS). This nanostructure may directly explain the enhanced sintering of the nanocomposite NPs and may provide an impetus for future synthesis of similarly structured NPs.
Molecular design and performance improvement in organic solar cells guided by high‐throughput screening and machine learning

Over past two decades, organic photovoltaics (OPVs) with unique advantages of low cost and flexibility meet significant development opportunities and the official world record for the power conversion efficiency (PCE) of organic solar cells (OSCs) has reached to 17.3%. Traditionally, efficiency breakthrough need the constant input of intensive labor and time. The artificial intelligence, as a rising interdisciplinary, brings certainly a revolution in research methods. In this review, we introduce a state-of-art theoretical methodology of the synergy of high-throughput screening and machine learning (ML) in accelerating the discovery of high-efficient OSC materials. We present key details, rules and experience in database construction, selection of molecular features, fast-screening calculations, models training and their predication capabilities. Meanwhile, three typical ML frameworks are concluded to reveal the structure-property-efficiency relationship, suggesting that this theoretical methodology can train powerful models with just molecular configurations and theoretical calculations for molecular design and efficiency improvements.
Pediatric Functional Constipation and Whey Protein: A Randomized Clinical Trial

Background: Functional constipation is a chronic gastrointestinal disease in children. Pharmacological treatment of constipation is mostly based on the prescription of laxatives. In addition to this treatment, complementary therapies were also proposed to treat constipation. In this study, the effect of whey protein in the treatment of constipation was investigated. Method and Materials: A total of 56 children with functional constipation within the age range of 1 to 16 years were included in the study. Patients were randomly divided into the intervention (n=28) and control (n=28) groups. The intervention group received 15 g whey protein and the control group received 15 g placebo. Both groups received 0.4 0.8 gr/kg PEG powder. The amount of PEG was adjusted every four days based on having soft stools. Demographic information were collected and recorded. Furthermore, fecal consistency, stool frequency, symptoms of stool retention, fecal Original Research Article Motavasselian et al.; JPRI, 33(15): 45-55, 2021; Article no.JPRI. 66211 46 incontinence, and abdominal pain were recorded prior to the intervention and at the second and fourth weeks of the intervention. Results: All patients had soft daily stools at the end of the intervention. At the end of the fourth week, the mean required amounts of PEG powder were respectively 0.62 and 0.28 g/kg in the control and intervention groups, which showed a significant difference (p value ≤0.001). Conclusion: Based on these findings, whey protein is safe and can improve constipation. However, more studies with larger sample size and longer follow-up period are needed to confirm the results of this study.
The Forces of Decline and Regeneration : A Discussion of Jane Jacobs and Gentrification

This chapter takes the form of a discussion about the urbanist Jane Jacobs and the legacy of her work in the era of gentrification. Zipp introduces, Storring surveys Jacobs’ contributions to our thinking about gentrification, and Hock analyzes Jacobs’ “reticence” on the problem of racism in urban history. Then all three discuss the ways that Jacobs’ signature ideas – the “sidewalk ballet,” organized complexity, the “self-destruction of diversity,” and others – appear now, in a time when cities are beset by problems she predicted but only glancingly addressed.
PERIODS OF HIGHEST OCCURRENCE OF FOREST FIRES IN BRAZIL

Forest fires affect ecosystems and cause damage that can be minimized by fire prevention programs. The objective was to determine the periods with the highest probability of occurrence of forest fires in Brazil. Heat source records detected by satellites between 1999 and 2014, and the frequency of occurrences of fire and burnt area sizes from 2006 to 2014, were evaluated. A statistical analysis of averages grouping allowed to separate the months with the highest number of heat sources into homogeneous groups, being possible to validate them with the months with the highest record of fires in the Conservation Units, thus defining the normal fire season. The number of heat sources records in Brazil was higher in winter and spring, dry seasons with lower rainfall and higher temperatures, with normal fire season from August to November. The fire occurrences were higher between August and October, with the higher burnt area in September. The periods of highest fire occurrence in Brazil varied between regions according to the climatological characteristics, and therefore strategies for fire prevention and control in vegetation must be intensified during the normal fire season. The period from August to November needs the greatest attention from the public authorities regarding the implementation of prevention and control fire programs. The months September and October make up the normal fire season from all regions of the Brazil.
Uptake of Water‐soluble Gas‐phase Oxidation Products Drives Organic Particulate Pollution in Beijing

Despite the recent decrease in pollution events in Chinese urban areas, the World Health Organization air quality guideline values are still exceeded. Observations from monitoring networks show a stronger decrease of organic aerosol directly emitted to the atmosphere relative to secondary organic aerosol (SOA) generated from oxidation processes. Here, the uptake of water‐soluble gas‐phase oxidation products is reported as a major SOA contribution to particulate pollution in Beijing, triggered by the increase of aerosol liquid water. In pollution episodes, this pathway is enough to explain the increase in SOA mass, with formaldehyde, acetaldehyde, glycolaldehyde, formic acid, and acetic acid alone explaining 15%–25% of the SOA increase. Future mitigation strategies to reduce non‐methane volatile organic compound emissions should be considered to reduce organic particulate pollution in China.
Electrochemical borylation of carboxylic acids

Significance Boronic acids are one of the most useful functional groups in organic chemistry and can be used as intermediates in synthesis or as key motifs in medicines. This work describes an extremely simple and economical way to use electrochemistry to convert carboxylic acids, through the intermediacy of redox-active esters, to boronic acids. The scope of this reaction is broad, the mechanism has been thoroughly studied, and it can be easily scaled up. Finally, application to the synthesis of a complex polycyclopropane natural product is demonstrated. A simple electrochemically mediated method for the conversion of alkyl carboxylic acids to their borylated congeners is presented. This protocol features an undivided cell setup with inexpensive carbon-based electrodes and exhibits a broad substrate scope and scalability in both flow and batch reactors. The use of this method in challenging contexts is exemplified with a modular formal synthesis of jawsamycin, a natural product harboring five cyclopropane rings.