Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects and Safety of Non-Pharmacological Therapies of Traditional Chinese Medicine for Coronary Heart Disease: An Overview of Systematic Reviews

Objectives Coronary heart disease (CHD) is currently the leading cause of human death. Non-pharmacological therapy of traditional Chinese medicine (NPTCM) is an important characteristic therapy of traditional Chinese medicine (TCM). Questions concerning the efficacy and safety of NPTCM-related interventions in patients with CHD led us to conduct this overview of systematic reviews (SRs). Methods The Cochrane Library, PubMed, Embase, EBSCO, Epistemonikos, PROSPERO, CNKI, Wanfang Database, and SinoMed were searched without language and publication status restriction from their inception to May 2021, along with grey literature sites and reference lists of included reviews. Systematic reviews comparing NPTCM/a combination of NPTCM and non-TCM interventions with non-TCM interventions/inactive controls for CHD were examined. Two reviewers independently screened titles, abstracts, and full-text articles, and completed data extraction and quality appraisal according to the predefined standards. Results In total, 1494 titles and abstracts and 66 full-text articles were screened, and a total of 12 SRs (11 with meta-analysis) were finally included. According to PRISMA 2020 checklist, more than 50% of reviews conformed to 80% of 54 items. Consistent evidence of effectiveness or harms across multiple outcomes based on more than one moderate quality review with meta-analysis was found for acupuncture and usual care plus acupuncture/Baduanjin/TCM exercise therapies/TCM emotional therapy. These interventions were mostly evaluated less than 6 months. Conclusion Acupuncture or acupuncture plus usual care could improve angina symptoms and ECG, and usual care plus Baduanjin/TCM exercise therapies could ameliorate health-related quality of life. Additionally, Baduanjin plus usual care could also improve psychological condition, and it as well as acupuncture could be safe due to no reports on adverse events related to these interventions. TCM emotional therapy plus usual care could benefit patients with CHD and depression.
Enhancing Network Security through Software Defined Networking (SDN)

The IoT connects many of the home appliances in the world, from intelligent thermostats to intelligent vehicles. By the end of 2015, we had 9 billion connected stuff. The Gartner forecast shows that the number of devices in the network will exceed 50 billion by 2020. Most of the connected devices in the existing network are based on obsolete security infrastructure and encryption, while many do not have provisions for remote updating of these devices. Taking into account the number of IoT devices, from off-shelf motion monitoring to machine tools, it is not possible to check which functions end up with any specific service or product. In short, this is the problem: you can't trust the integrity of the security of the device and determine exactly where the data is processed and stored. The SDN architecture is designed to increase the routing and networking performance of the existing networks by isolating the control plane from the data plane. The basic concept of Software Defined Networking can be applied to IoT Multi networks; however, the standard SDN implementations for wired networks are not directly suitable for distributed and ad-hoc mesh networks, which are common in IoT systems. However, the SDN architecture changes the pattern of communication of the IoT network, leading to a new approach to the manifestation of the Securities IoT network. Centralized data layer control and control layer not only simplifies data package management, but also increases safety. As mentioned above, the amount of data that flows into these systems is significant. Proper management of traffic and load balancing will help to simplify the data flow in some ways. The total system's power consumption may be reduced by the central station, which requires less power than the distributed control. To sum up, introducing SDN into IoT will help IoT and stimulate IoT in people's regular lives.
Algoritma Stemming Nazief & Adriani dengan Metode Cosine Similarity untuk Chatbot Telegram Terintegrasi dengan E-layanan

Abstrak—Sistem Informasi yang berkembang memiliki sejumlah pertanyaan yang sering diajukan kepada customer servicedengan tingkat kesamaan pertanyaan yang tinggi. Untuk membantu hal tersebut dibuat FAQ terkait sistem informasi. FAQmemiliki banyak informasi sehingga pengguna bingung dan memerlukan waktu untuk mencari informasi. Pengguna lebih untuk mengajukan pertanyaan ke customer service. Chatbot merupakan salah cara untuk membantu pengguna dan customer service dalam masalah ini. Customer servicedapat menjawab pertanyaan secara otomatis dan pengguna dapat mengajukan pertanyaan seolah-olah bertanya kepada customer servicesecara langsung. Pada penelitian ini peneliti akan menerapkan algoritma Nazief & Adriani yang digunakan untuk melakukan stemming karena algoritma ini merupakan salah satu algoritma yang efektif dalam stemming bahasa Indonesia. Dan metode cosine similarity untuk mencari tingkat kemiripan dari pertanyaan dengan FAQyang ada dalam database FAQ. Dengan mengimplementasikan algoritma dan metode tersebut dalam chatbot dengan bantuan layanan MessangerTelegrammenghasilkan jawaban yang relative sesuai dengan yang diharapkan pengguna. Cara ini merupakan cara yang efektif untuk menjawab pertanyaan secara otomatis. Dan jika pertanyaan yang diajukan tidak menemukan jawaban atau jawaban tidak sesuai maka pertanyan akan di sampaikan dalam e-Layanan PPTI UNESA. Kata Kunci—algoritma nazief & andriani, cosine similarity, chatbot, bot.
The integration property of heavy forge hydraulic-press and its influence factors

The heavy forge hydraulic-press is built in our country currently. And the prestressed assembled frame is adopted in the new press. The structure conquers the problem that in the tradition press frame the columns are bended with stretching. The stress status of the press is improved effectively. But the new problem is brought into too that is the problem of the integration property. in this paper, the integration property of hydraulic-press is studied, and the influence of upper head stiffness is discussed. It is wished to help the developing of hydraulic-press design theory.
Collaborative Driving: Learning-Aided Joint Topology Formulation and Beamforming

Currently, autonomous vehicles are able to drive more naturally based on the driving policies learned from millions of driving miles in real environments. However, to further improve the automation level of vehicles is a challenging task, especially in the case of multivehicle cooperation. In recent heated discussions of 6G, millimeter-wave (mm-wave and terahertz (THz) bands are deemed to play important roles in new radio communication architectures and algorithms. To enable reliable autonomous driving in 6G, in this article, we envision collaborative autonomous driving, a new framework that jointly controls driving topology and formulate vehicular networks in the mm-wave/THz bands. As a swarm-intelligence system, the collaborative driving scheme goes beyond existing autonomous driving patterns based on single-vehicle intelligence in terms of safety and efficiency. With efficient data sharing, the proposed framework is able to achieve cooperative sensing and load balancing so that improve sensing efficiency with saved computational resources. To deal with the new challenges in the collaborative driving framework, we further illustrate two promising approaches for mm-wave/THz-based vehicle-to-vehicle (V2V) communications. Finally, we discuss several potential open research problems for the proposed collaborative driving scheme.
Identification and Validation of Invasion-Related Molecular Subtypes and Prognostic Features for Cervical Cancer

Background As one of the main causes leading to female cancer deaths, cervical cancer shows malignant features of local infiltration and invasion into adjacent organs and tissues. This study was designed to categorize novel molecular subtypes according to cervical cancer invasion and screen reliable prognostic markers. Methods Invasion-related gene sets and expression profiles of invasion-related genes were collected from the CancerSEA database and The Cancer Genome Atlas (TCGA), respectively. Samples were clustered by nonnegative matrix factorization (NMF) to obtain different molecular subgroups, immune microenvironment characteristics of which were further systematically compared. Limma was employed to screen differentially expressed gene sets in different subtypes, followed by Lasso analysis for dimension reduction. Multivariate and univariate Cox regression analysis was performed to determine prognostic characteristics. The Kaplan-Meier test showed the prognostic differences of patients with different risks. Additionally, receiver operating characteristic (ROC) curves were applied to validate the prognostic model performance. A nomogram model was developed using clinical and prognostic characteristics of cervical cancer, and its prediction accuracy was reflected by calibration curve. Results This study filtered 19 invasion-related genes with prognosis significance in cervical cancer and 2 molecular subtypes (C1, C2). Specifically, the C1 subtype had an unfavorable prognosis, which was associated with the activation of the TGF-beta signaling pathway, focal adhesion, and PI3K-Akt signaling pathway. 875 differentially expressed genes were screened, and 8 key genes were finally retained by the dimension reduction analysis. An 8-gene signature was established as an independent factor predictive of the prognosis of cervical cancer. The signature performance was even stronger when combined with N stage. Conclusion Based on invasion-related genes, the present study categorized two cervical cancer subtypes with distinct TME characteristics and established an 8-gene marker that can accurately and independently predict the prognosis of cervical cancer.
Understanding the Effect of IoT Adoption on the Behavior of Firms: An Agent-based Model

In the context of increasing diffusion of technologies related to Industry 4.0 and the Internet of Things in particular, we have developed an agent-based model to simulate the effect of IoT diffusion in companies and verify potential benefits and risks. The model analyses how firms react to the spread of IoT in the market by analysing its effects on firms' pricing and quality strategies, its impact on variable production costs, and the long-term survival rate of firms. The model shows how IoT diffusion has the potential to influence the market by supporting both quality and cost improvements. The results of the model also confirm the potential for significant benefits for businesses, suggesting the opportunity to support the introduction and application of IoT, and clearly show how the use of IoT can be a key strategic choice in competitive market contexts focused on cost strategies to increase business performance and prospects.
Adaptive Transfer Learning for Multi-Label Emotion Classiﬁcation

In this study, we explore how data annotated 001 with different taxonomies can be used to im-002 prove multi-label emotion classiﬁcation. We 003 propose a novel transfer learning framework 004 to model the interaction between emotion cat-005 egories, and introduce an adaptive aggregation 006 mechanism to fuse the information from differ-007 ent taxonomies. The cross-taxonomy emotion 008 interaction allows the source and target tasks 009 to collaborate effectively, resulting in more ac-010 curate predictions. The experimental results 011 on the SemEval-2018 dataset show that our ap-012 proach can effectively boost the performance 013 gain brought by transfer learning, and signiﬁ-014 cantly outperforms existing methods. 015
Pitch Frequency Based Speech Recognition System for Isolated Hindi Words

:- The concept of Speech Recogntion is to take an utterance of speech signal in the form of input, captured by microphone and convert it into a sequence of text which is as close as possible to the input which was represented by the acoustic data.In India, we have 22 distinct languages and 419 local languages. Majority of population is unaware of English language either in reading or writing but they can take advantage from resources of Information Technology sector if they support native idiom. Therefore, there is huge scope to develop such systems in Hindi language.The national language of OThe literacy rate of India is 74.04% amongst which only 12.18% of Indians are familiar with English language.Speech recognition is the inter-disciplinary sub-field of computational linguistics that develops methodologies and technologies that enables the recognition and translation of spoken language into text by computers. It is also known as "automatic speech recognition"(ASR). The procedure includes creating of database of various speech signals , convert it to computer friendly language and display on a notice board.
Challenges and Opportunities in Low-Resource Natural Language Generation

Many domains and tasks in natural lan-001 guage generation (NLG) are inherently ‘low-002 resource’, where training data and linguistic 003 analyses are scarce. This poses a particular 004 challenge to researchers and system develop-005 ers in the era of machine-learning-driven NLG. 006 Here, we initially discuss the challenges re-007 searchers and developers often encounter when 008 dealing with low-resource settings in NLG. We 009 argue that it is unsustainable to collect large 010 aligned datasets or build large language models 011 from scratch for every possible domain due 012 to cost, labour, and time constraints, so re-013 searching and developing approaches for low-014 resource settings is vital. We then present a 015 survey of current approaches to low-resource 016 NLG, followed by a list of proposed solutions 017 and promising avenues for future work in NLG 018 for low-resource settings. 019
Despondency Analysis by Getting the Hang of Utilizing EEG Flags: An Orderly Survey

Despondency is considered by WHO as the principle supporter of worldwide handicap and it presents hazardous dangers to roughly all parts of human existence, specifically open and private wellbeing. This psychological issue is normally described by impressive changes in sentiments, schedules, or considerations. As for the way that early conclusion of this disease would be of the basic significance in successful treatment, a few advancements have happened in the motivation behind wretchedness recognition. EEG signals mirror the functioning status of the human cerebrum which are viewed as the most legitimate apparatuses for a downturn analysis. Profound learning calculations have the limit of example revelation and removing highlights from the crude information which is taken care of into them. Attributable to this critical trait of profound learning, as of late, these techniques have seriously used in the assorted examination fields, explicitly medication and medical care. Accordingly, in this article, we intended to survey all papers focused on utilizing profound figuring out how to recognize or foresee burdensome subjects with the assistance of EEG signals as information.
Mitochondrial Phenotypes in Genetically Diverse Neurodegenerative Diseases and Their Response to Mitofusin Activation

Mitochondrial fusion is essential to mitochondrial fitness and cellular health. Neurons of patients with genetic neurodegenerative diseases often exhibit mitochondrial fragmentation, reflecting an imbalance in mitochondrial fusion and fission (mitochondrial dysdynamism). Charcot–Marie–Tooth (CMT) disease type 2A is the prototypical disorder of impaired mitochondrial fusion caused by mutations in the fusion protein mitofusin (MFN)2. Yet, cultured CMT2A patient fibroblast mitochondria are often reported as morphologically normal. Metabolic stress might evoke pathological mitochondrial phenotypes in cultured patient fibroblasts, providing a platform for the pre-clinical individualized evaluation of investigational therapeutics. Here, substitution of galactose for glucose in culture media was used to redirect CMT2A patient fibroblasts (MFN2 T105M, R274W, H361Y, R364W) from glycolytic metabolism to mitochondrial oxidative phosphorylation, which provoked characteristic mitochondrial fragmentation and depolarization and induced a distinct transcriptional signature. Pharmacological MFN activation of metabolically reprogrammed fibroblasts partially reversed the mitochondrial abnormalities in CMT2A and CMT1 and a subset of Parkinson’s and Alzheimer’s disease patients, implicating addressable mitochondrial dysdynamism in these illnesses.
Cloze Evaluation for Deeper Understanding of Commonsense Stories in Indonesian

Story comprehension that involves complex causal and temporal relations is a critical task in NLP, but previous studies have focused predominantly on English, leaving open the question of how the findings generalize to other languages, such as Indonesian. In this paper, we follow the Story Cloze Test framework of Mostafazadeh et al. (2016) in evaluating story understanding in Indonesian, by constructing a four-sentence story with one correct ending and one incorrect ending. To investigate commonsense knowledge acquisition in language models, we experimented with: (1) a classification task to predict the correct ending; and (2) a generation task to complete the story with a single sentence. We investigate these tasks in two settings: (i) monolingual training and ii) zero-shot cross-lingual transfer between Indonesian and English.
Extracting Sentiments towards COVID-19 Aspects

In this paper, we introduce a specialized Russian dataset and study approaches for aspect-based sentiment analysis of Russian users’ comments about the COVID-19. We solve two tasks, namely Relevance Determination (RD), which aims to predict whether a sentence is relevant to an aspect of the pandemic, and Sentiment Classification (SC), which classifies the sentiment expressed towards an aspect in a sentence. We applied and tested various methods of machine learning, including finetuning of the pre-trained RuBERT model. The best results in both tasks were obtained by RuBERT model in the Natural Language Inference (NLI) formulation. Copyright © 2021 for this paper by its authors.
A Comprehensive Review of Intrusion Detection System Approach and Technique

: The problem of securing information and data flows has existed from the origin of network communication. Diverse approaches have been developed to protect and transfer such information safely. Conversely, as communication technology advance and information management systems become more powerful and distributed, attack on network system and web application has taken on new and more complex dimensions posing a great challenge to both government and business organization. Security breaches almost occur on daily basis; hence, the need for adequate information security. Presently, security is implemented using firewalls, encryption, intrusion detection systems (IDS), authentication and other software and hardware solutions. This paper provides an up-to-date comprehensive overview of IDS approach and technique through a systematic survey of the major work done in this area to provide researchers with adequate information needed to design robust and efficient IDS.
Knowledge, Attitudes, Perceptions and Vaccination Acceptance/Hesitancy among the Community Pharmacists of Palermo’s Province, Italy: From Influenza to COVID-19

In Italy, following the start of the SARS-CoV-2 vaccination campaign, community pharmacies (CPs) were recruited on a voluntary basis in order to administer COVID-19 vaccines as part of their activities. The aim of the present study was to investigate the knowledge, attitudes, and practices regarding SARS-CoV-2 infection prevention, and vaccine acceptance/hesitancy towards COVID-19 and influenza vaccinations among the community pharmacists operating in the Palermo Province. A cross-sectional study was conducted, with two different questionnaires administered before and after the conduction of the vaccination campaign against SARS-CoV-2 at the COVID-19 vaccination center of the Palermo University Hospital (PUH). The baseline survey showed that 64% of community pharmacists (CPs) declared that they planned to vaccinate against SARS-CoV-2, and 58% were vaccinated against influenza during the 2020/2021 season. Factors significantly associated with willingness to receive the COVID-19 vaccination were confidence in vaccines (adjOR 1.76; CI 1.11–2.80), fear of contracting SARS-CoV-2 infection (adjOR 1.50; CI 1.06–2.11), considering COVID-19 vaccination to be the best strategy to counteract SARS-CoV-2 (adjOR 1.79; CI 1.39–2.29), and adherence to influenza vaccination during the 2020/2021 season (adjOR 3.25; CI 2.23–4.25). The adherence among CPs of the Palermo Province to COVID-19 vaccination was 96.5%. From the post-vaccination survey, the main reasons for changing opinions on vaccination adherence were the introduction of mandatory vaccinations, fear of contracting COVID-19, and limitations on work activities in the case of vaccine refusal. The achievement of very high COVID-19 vaccination coverage rates among healthcare professionals (HCPs) in the present study was mainly due to the mandatory vaccination policies; nevertheless, a willingness for COVID-19 vaccination was relatively high among pharmacists before the beginning of the vaccination campaign. HCPs and CPs should receive training on vaccination, which is recommended in the national immunization plan and is also suggested by the respondents in our study, in order to routinely re-evaluate their own vaccination profiles, as well as those of their patients.
Influence of Marble Slurry Dust on Epidermal Characteristics of Selected Tree Species, in Reference to Their Dust Holding Capacity

Green belts on the embankment of the dumpyard, at Kishangarh, have been developed for mitigating the air pollution caused by the slurry dust, by filtering, intercepting and absorbing the particles in a sustainable manner. The micro-morphological parameters of the phylloplane were undertaken, to evaluate the choice of tree species best suited for plantation. In the present study the dominant tree species of the green belt, viz. Callistemon lanceolata, Albizia lebbeck and Azadirachta indica indicated marked alternation in epidermal traits. Length, breadth and calculated area of stomata exhibited different percentages of inhibition whereas number of stomata, epidermal cells, and stomatal index showed stimulation.
MENOPAUSE Gender-related differences in oxidative stress levels among elderly patients with coronary artery disease

Objective: To evaluate whether gender-related differences exist concerning oxidative stress levels in aged patients with coronary artery disease (CAD). Design: Case-control. Setting: Clinical and research center. Patient(s): Elderly subjects of both genders with or without CAD. Intervention(s): None. Main Outcome Measure(s): Serum hydroperoxides (HP) as index of oxidative stress levels. Result(s): The HP levels were comparable in aged control subjects of both genders (376 20 arbitrary units [AU] in women, 333 19 AU in men) but significantly increased in CAD (456 15 AU) compared with all control subjects (357 14 AU). Moreover, among CAD patients, the HP levels were higher in women than in men (536 33 AU and 428 15 AU, respectively). Multivariate analysis, in which CAD represented the dependent variable, indicated that dyslipidemia was independently associated with CAD in men (odds ratio [OR] 5.8), whereas HP >50th percentile represented the only strong independent risk factor for CAD in elderly women (OR 8.4). Conclusion(s): Differences in oxidative stress levels between elderly males and females might provide a biochemical basis for the epidemiologic differences in CAD, which might help to open new opportunities in the management of patients with cardiovascular disease from a gender point of view. (Fertil Steril 2008;89:608–13. 2008 by American Society for Reproductive Medicine.)