nils-herrmann/clean_scirepeval huggingface dataset:
Efficacy and Safety of Echinacoside in a Rat Osteopenia Model
Venue: Evidence based complementary and alternative medicine eCAM
Year: 2013

This study aimed to investigate the efficacy and safety of echinacoside (ECH) using an osteopenia rat model. Forty eight 6 month old female Sprague Dawley rats were randomly divided into one sham operated group (SHAM) and five OVX (ovariectomized) subgroups: SHAM with vehicle 0.5% carboxymethylcellulose sodium (0.5% CMC Na) and OVX with vehicle (OVX) OVX with 17b estradiol (E2) and OVX with ECH of graded doses (ECH L, ECH M, and ECH H) The effects of ECH and E2 on serum biochemical parameters, bone mineral density (BMD) bone biomechanical properties, bone microarchitecture, and immunohistochemistry were examined, and safety assessments were also evaluated. The results showed that ECH treatments improved total femur BMD, bone microarchitecture, and biomechanical properties and decreased serum marker levels in comparison to OVX group. Moreover, ECH administration significantly increased osteoprotegerin (OPG) level, and decreased receptor activator of nuclear factor kB ligand (RANKL) level in serum, as well as in proximal femur. Importantly, ECH treatment ameliorated the lipid parameters without the overall incidences of adverse events of uterus and mammary gland compared to OVX and SHAM groups. This study demonstrated that administration of ECH for 12 weeks can effectively and safely prevent OVX induced osteoporosis in rats via increasing the OPG/RANKL ratio.
Applications of Blockchain Technology in Medicine and Healthcare: Challenges and Future Perspectives
Venue: Cryptogr.
Year: 2019

Blockchain technology has gained considerable attention, with an escalating interest in a plethora of numerous applications, ranging from data management, financial services, cyber security, IoT, and food science to healthcare industry and brain research. There has been a remarkable interest witnessed in utilizing applications of blockchain for the delivery of safe and secure healthcare data management. Also, blockchain is reforming the traditional healthcare practices to a more reliable means, in terms of effective diagnosis and treatment through safe and secure data sharing. In the future, blockchain could be a technology that may potentially help in personalized, authentic, and secure healthcare by merging the entire real time clinical data of a patient's health and presenting it in an up to date secure healthcare setup. In this paper, we review both the existing and latest developments in the field of healthcare by implementing blockchain as a model. We also discuss the applications of blockchain, along with the challenges faced and future perspectives.
A DLT based Smart Contract Architecture for Atomic and Scalable Trading
Venue: ArXiv
Year: 2021

Distributed Ledger Technology (DLT) has an enormous potential but also downsides. One downside of many DLT systems, such as blockchain, is their limited transaction throughput that hinders their adoption in many use cases (e.g. real time payments) State channels have emerged as a potential solution to enhance throughput by allowing transactions to process off chain. While current proposals can increase scalability, they require high collateral and lack support for dynamic systems that require asynchronous state transitions. Additionally, the latency of channel initialisations can cause issues especially if fast interactions are required. In this paper, we propose an atomic, scalable and privacy preserving protocol that enables secure and dynamic updates. We develop a smart contract based Credit Note System (CNS) that allows participants to lock funds before a state channel initialisation, which enhances flexibility and efficiency. We formalise our model using the Universal Composability (UC) framework and demonstrate that it achieves the stated design goals of privacy, scalability, and atomicity. Moreover, we implement a dispute process in the state channel to counter availability attacks. Finally, we analyse the protocol in the context of an asynchronous smart grid based marketplace.
Named Entity Recognition with Homophones Noisy Data
Venue: PRICAI
Year: 2019

General named entity recognition systems exclusively focus on higher accuracy regardless of dirty data. However, raw source data face serious challenges specially that are originated from automated speech recognition systems' results. In this paper, we propose Pinyin (Pinyin is the official romanization system for Standard Chinese, each Chinese character has its own pinyin sequence which is composed of Latin alphabet) Hierarchical Attention Encoder Decoder network and Character Alternate Network to overcome Chinese homophones' problems which frequently frustrate researchers in consecutive Natural Language Understanding (NLU) Our models present a none word segmentation structure to effectively avoid secondary data corruption and adequately extract words' internal features. Besides, corrupted sequences can be revised by character level network. Evaluation demonstrates that our proposed method achieves 93.73% F1 scores which are higher than 90.97% F1 scores using baseline models in homophone noisy dataset. Additional experiments are conducted to show equivalent results in the universal dataset.
Energy Internet: Concept and practice exploration
Venue: 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2)
Year: 2017

Under the situations of energy crisis around the world, Energy Internet has become the focus of international academic and industrial areas. In this paper, comprehensive reviews and prospects were made based on the background and current research status of Energy Internet. Moreover, the core concept, basic structure, and operation mode of Energy Internet were introduced and discussed. Finally, constructive solutions to the current problems were proposed with the demonstration project of Energy Internet that is the Beijing New Aerotropolis, which draws the future of the Energy Internet.
The Design and Implementation of Trade Finance Application based on Hyperledger Fabric Permissioned Blockchain Platform
Venue: 2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)
Year: 2019

Blockchain has grown beyond cryptocurrency. It has found a sweet spot in applications that required increased trust and transparency among multi party transactions. This paper describes our experience in the design, implementation and architecture of blockchain based trade finance application. The implementation is based on permissioned blockchain Hyperledger Fabric. Recently, the number of projects embarked on blockchain application have grown significantly over the year. However, the current level of understanding of blockchain application is insufficient and the architectural aspects of the system has remained largely unexplored. This paper attempts to solve this problem. It applies the concept of software connectors as a medium to explore fundamental building blocks of software interaction and how they are composed into a more complex interaction
Severe Post Herpetic Lumbar Plexopathy Responds to Pulse Intravenous Methylprednisolone: A Case Report With a Side Note on its Parallel Semiology to Diabetic Radiculoplexopathy and the Vascular Invasiveness of the Varicella Zoster Virus
Venue: Cureus
Year: 2020

Post herpetic lumbar plexopathy (post herpetic segmental paresis) immune mediated lumbar plexopathy and diabetic radiculoplexopathy (diabetic amyotrophy) have similar and seemingly parallel semiologies. The latter two conditions have an underlying microvasculitic pathological substrate that has shown potential (yet unproven) amelioration with immunodulatory therapy. These observations gave us the motivation to treat our patient with intravenous methylprednisolone for a profound proximal left leg weakness due to post herpetic segmental paresis. In this case report, we outline in detail the clinical and electophysiolgical phenotype of this disease and we demonstrate the spectacular improvement of left leg power that had previously remained static for three months. In the discussion section, we review the vascular invasiveness of the varicella zoster virus.
PolderCast: Fast, Robust, and Scalable Architecture for P2P Topic Based Pub/Sub
Venue: Middleware
Year: 2012

We propose PolderCast, a P2P topic based Pub/Sub system that is (a) fault tolerant and robust, (b) scalable w.r.t the number of nodes interested in a topic and number of topics that nodes are interested in, and (c) fast in terms of dissemination latency while (d) attaining a low communication overhead. This combination of properties is provided by an implementation that blends deterministic propagation over maintained rings with probabilistic dissemination following a limited number of random shortcuts. The rings are constructed and maintained using gossiping techniques. The random shortcuts are provided by two distinct peer sampling services: Cyclon generates purely random links while Vicinity produces interest induced random links. We analyze PolderCast and survey it in the context of existing approaches. We evaluate PolderCast experimentally using real world workloads from Twitter and Facebook traces. We use widely renowned Scribe  as a baseline in a number of experiments. Robustness with respect to node churn is evaluated through traces from the Skype superpeer network. We show that the experimental results corroborate all of the above properties in settings of up to 10K nodes, 10K topics, and 5K topics per node.
PAX 8 expression in non neoplastic tissues, primary tumors, and metastatic tumors: a comprehensive immunohistochemical study
Venue: Modern Pathology
Year: 2011

PAX 8 is a transcription factor that is essential for embryonic development of the kidney, Mullerian organs, and thyroid. It may also have a role in tumor development in these organs. The diagnostic utility of PAX 8 has not been comprehensively studied. Formalin fixed, paraffin embedded tissue samples for non neoplastic tissues (n=1601) primary neoplasms (n=933) and metastatic neoplasms (n=496) were subjected to PAX 8 immunostain. In non neoplastic tissues, PAX 8 was consistently noted in glomerular parietal epithelial cells, renal collecting ductal cells, atrophic renal tubular epithelial cells regardless of nephronic segments, and epithelial cells of the endocervix, endometrium, fallopian tube, seminal vesicle, epidydimis, thyroid, pancreatic islet cells, and lymphoid cells. PAX 8 was not seen in the rest of the tissue samples. In primary neoplasms, PAX 8 was expressed by 194 of 240 (89% renal cell neoplasms, by 238 of 267 (89% Mullerian type neoplasms, by 65 of 65 (100% thyroid follicular cell neoplasms, by 8 of 8 (100% nephrogenic adenomas, and by 17 of 17 (100% lymphomas. Weak focal staining was noted in 5 of 12 (42% cases of parathyroid hyperplasia/adenoma and in 6 of 17 (35% well differentiated neuroendocrine tumors of the pancreas. PAX 8 was not seen in other neoplasms. In metastatic neoplasms, PAX 8 was expressed by 90 of 102 (88% metastatic renal cell carcinomas, by 57 of 63 metastatic Mullerian tumors (90% and by 6 of 6 metastatic papillary thyroid carcinomas (100% There was also weak focal staining for 1 of 15 metastatic small cell carcinomas and for 1 of 9 metastatic well differentiated neuroendocrine carcinomas. PAX 8 was not seen in other metastatic neoplasms. It can be successfully identified in routinely processed tissue samples, and its expression is mostly nuclear. PAX 8 expression in non neoplastic mature tissues is limited to the organs, the embryonic development of which depends on this transcription factor. This tissue/cell specific expression is maintained during both neoplastic transformation and metastasis. PAX 8 is a sensitive and specific marker for tumors of renal, Mullerian, or thyroid origin in both primary and metastatic sites.
Achieve ultrahigh energy storage performance in BaTiO3 Bi(Mg1/2Ti1/2)O3 relaxor ferroelectric ceramics via nano scale polarization mismatch and reconstruction
Year: 2020

Development of lead free dielectric ceramics with large recoverable energy storage density (Wrec) high energy storage efficiency (e) and wide usage temperature range is of great significance to improve the overall performance of power electronic devices. Despite the numerous research efforts, performance of existing lead free dielectric ceramics is barely satisfactory. Herein, an effective strategy to achieve ultrahigh energy storage performance via nano scale polarization mismatch and reconstruction is proposed. By developing solid solutions of A site coupling and B site coupling ferroelectrics, polarization mismatch and ultrahigh energy storage performance can be realized in intermediated compositions. It is demonstrated that ultrahigh energy storage performance with a e of 93% and a Wrec of 4.49 J/cm3 is achieved in the 0.6BaTiO3 0.4Bi(Mg1/2Ti1/2)O3 (0.6BT 0.4BMT) ceramic, which is a record high energy storage property in lead free relaxor ferroelectric bulk ceramics. Excellent temperature stability with a variation of Wrec and e less than 5% is also realized in a wide temperature range from 30 degC to 170 degC. Such an ultrahigh energy storage performance not only verifies our strategy, but also makes the 0.6BT 0.4BMT ceramic a promising candidate material for energy storage. Moreover, of particular significance is that this work provides an effective method to design novel high performance dielectric ceramics for future energy storage devices.
ANALISIS RASIO KEUANGAN UNTUK MEMPREDIKSI KONDISIFINANCIAL DISTRESS PADA PERUSAHAAN MANUFAKTUR YANGTERDAFTAR DI BURSA EFEK INDONESIA:ANALISIS MODEL ATLMAN Z SCORE
Year: 2013

ABSTRAK ANALISIS RASIO KEUANGAN UNTUK MEMPREDIKSI KONDISI FINANCIAL DISTRESS PADA PERUSAHAAN MANUFAKTUR YANG TERDAFTAR DI BURSA EFEK INDONESIA: ANALISIS MODEL ATLMAN Z SCORE Aditya Firmansyah F0309003 ABSTRAK Penelitian ini bertujuan untuk mengetahui apakah rasio keuangan dapat digunakan dalam memprediksi kondisi financial distress dan pengaruh rasio keuangan tersebut terhadap kondisi financial distress pada perusahaan manufaktur yang terdaftar di Bursa Efek Indonesia (BEI) Pada penelitian ini rasio keuangan yang digunakan untuk memprediksi kondisi financial distress adalah rasio lancar, rasio profit margin, rasio utang dan return on equity (ROE) Kondisi financial distress ditentukan dengan formula Atlman Z Score. Penelitian ini menggunakan data sekunder, yaitu pelaporan keuangan perusahaan manufaktur yang di lihat dari Indonesian Capital Market Directory (ICMD) seluruh perusahaan manufaktur pada tahun 2008 2011 dengan perusahaan sampel sebanyak 56 perusahaan manufaktur. Metode analisis yang digunakan adalah analisis binary regresi logistik. Hasil penelitian ini menunjukkan bahwa rasio lancar, rasio profit margin dan ROE berpengaruh negatif terhadap kondisi financial distress dan signifikan dalam memprediksi kondisi financial distress pada perusahaan manufaktur di Indonesia. Sedangkan rasio utang berpengaruh positif terhadap kondisi financial distress dan tidak signifikan dalam memprediksi kondisi financial distress pada perusahaan manufaktur di Indonesia. Kata kunci: rasio keuangan, financial distress ABSTRACT ANALYSIS FINANCIAL RATIO TO PREDICT FINANCIAL DISTRESS CONDITION IN MANUFACTURING COMPANIES LISTED IN INDONESIA STOCK EXCHANGE: ANALYSIS ATLMAN Z SCORE MODEL Aditya Firmansyah F0309003  This study aimed to determine whether financial ratios can be used to predict financial distress and the impact of financial ratios to financial distress in companies listed on the Indonesia Stock Exchange (IDX) In this study, the use of financial ratios to predict financial distress is the current ratio, profit margin ratio, debt ratio and return on equity (ROE) Financial distress is determined by the Atlman's Z Score formula. This study uses secondary data, the manufacturing company's financial reporting in view of the Indonesian Capital Market Directory (ICMD) all manufacturing companies in the year 2008 to 2011 with a sample of 56 companies manufacturing company. The analytical method used was a binary logistic regression analysis. Results of this study indicate that the current ratio, profit margin ratio and ROE negatively affect financial distress and significant in predicting financial distress in manufacturing companies in Indonesia. While the debt ratio has a positive effect on financial distress and not significant in predict financial distress in manufacturing companies in Indonesia.  financial ratios, financial distress
Revisiting fundamental welding concepts to improve additive manufacturing: From theory to practice
Year: 2020

Additive manufacturing technologies based on melting and solidification have considerable similarities with fusion based welding technologies, either by electric arc or high power beams. However, several concepts are being introduced in additive manufacturing which have been extensively used in multipass arc welding with filler material. Therefore, clarification of fundamental definitions is important to establish a common background between welding and additive manufacturing research communities. This paper aims to review these concepts, highlighting the distinctive characteristics of fusion welding that can be embraced by additive manufacturing, namely the nature of rapid thermal cycles associated to small size and localized heat sources, the non equilibrium nature of rapid solidification and its effects on: internal defects formation, phase transformations, residual stresses and distortions. Concerning process optimization, distinct criteria are proposed based on geometric, energetic and thermal considerations, allowing to determine an upper bound limit for the optimum hatch distance during additive manufacturing. Finally, a unified equation to compute the energy density is proposed. This equation enables to compare works performed with distinct equipment and experimental conditions, covering the major process parameters: power, travel speed, heat source dimension, hatch distance, deposited layer thickness and material grain size.
Multi Scale Visual Semantics Aggregation with Self Attention for End to End Image Text Matching
Venue: ACML
Year: 2019

For both datasets, input images are resized to 224 x 224 with a random crop, and we use the 152 layer ResNet He et al. (2016) pre trained on ImageNet Jia et al. (2009) to extract visual features. Different scales of feature maps (28 x 28, 14 x 14, 7 x 7) are captured by the last residual blocks in different stages (conv3_x, conv4_x, conv5_x) of ResNet. For the adaptive self attention (ASA) we follow Wang et al. (2018) to initialize the weight layers. Note that BatchNorm Ioffe and Szegedy (2015) is crucial to the convergence of ASA. We set the dimensionality of instance candidates and instance level features as C 2048 and D 1024 respectively. For sentences, the dimensionality of word embeddings is set as d 300, and the pre trained GloVe Jeffrey et al. (2014) is taken to initialize the word embedding matrix Wx. We set the number of hidden units in the bi directional GRU and the dimensionality of joint embedding space to 1024. We follow [Lee et al. (2018) Faghri et al. (2018) to set the margin m of triplet loss to 0.2 and threshold of maximum gradient norm to 2.0 for gradient clipping. The Adam optimizer Kingma and Ba (2015) is leveraged to train all models with a mini batch size of 128. Besides, two training stages are applied to each model, where we freeze ResNet in the first 20 epochs with an initial learning rate of 5e 4, and the whole network is fine tuned in the next 15 epochs with an initial learning rate of 2e 5. We follow Lee et al. (2018) to set the hyper parameters.
Abstractive Text Summarization based on Improved Semantic Graph Approach
Venue: International Journal of Parallel Programming
Year: 2018

The goal of abstractive summarization of multi documents is to automatically produce a condensed version of the document text and maintain the significant information. Most of the graph based extractive methods represent sentence as bag of words and utilize content similarity measure, which might fail to detect semantically equivalent redundant sentences. On other hand, graph based abstractive method depends on domain expert to build a semantic graph from manually created ontology, which requires time and effort. This work presents a semantic graph approach with improved ranking algorithm for abstractive summarization of multi documents. The semantic graph is built from the source documents in a manner that the graph nodes denote the predicate argument structures (PASs) the semantic structure of sentence, which is automatically identified by using semantic role labeling; while graph edges represent similarity weight, which is computed from PASs semantic similarity. In order to reflect the impact of both document and document set on PASs, the edge of semantic graph is further augmented with PAS to document and PAS to document set relationships. The important graph nodes (PASs) are ranked using the improved graph ranking algorithm. The redundant PASs are reduced by using maximal marginal relevance for re ranking the PASs and finally summary sentences are generated from the top ranked PASs using language generation. Experiment of this research is accomplished using DUC 2002, a standard dataset for document summarization. Experimental findings signify that the proposed approach shows superior performance than other summarization approaches.
Quantum Annealing Machine based on Floating Gate Array
Year: 2017

Quantum annealing machines based on superconducting qubits, which have the potential to solve optimization problems faster than digital computers, are of great interest not only to researchers but also to the general public. Here, we propose a quantum annealing machine based on a semiconductor floating gate (FG) array. We use the same device structure as that of the commercial FG NAND flash memory except for small differences such as thinner tunneling barrier. We theoretically derive an Ising Hamiltonian from the FG system in its single electron region. Recent high density NAND flash memories are subject to several problems that originate from their small FG cells. In order to store information reliably, the number of electrons in each FG cell should be sufficiently large. However, the number of electrons stored in each FG cell becomes smaller and can be countable. So we utilize the countable electron region to operate single electron effects of FG cells. Second, in the conventional NAND flash memory, the high density of FG cells induces the problem of cell to cell interference through their mutual capacitive couplings. This interference problem is usually solved by various methods using a software of error correcting codes. We derive the Ising interaction from this natural capacitive coupling. Considering the size of the cell, 10 nm, the operation temperature is expected to be approximately that of a liquid nitrogen. If a commercial 64 Gbit NAND flash memory is used, ideally we expect it to be possible to construct 2 megabytes (MB) entangled qubits by using the conventional fabrication processes in the same factory as is used for manufacture of NAND flash memory. A qubit system of highest density will be obtained as a natural extension of the miniaturization of commonly used memories in this society.
Measurement Error Impact on Node Localization of Large Scale Underwater Sensor Networks
Venue: 2015 IEEE 82nd Vehicular Technology Conference (VTC2015 Fall)
Year: 2015

This paper studies the impact of distance measurement error on node localization in large scale Underwater Wireless Sensor Networks (UWSNs) where only a small percent of nodes are anchor nodes with accurate location information and a large percent of ordinary nodes are to be localized. The recursive localization algorithm is re evaluated under realistic assumptions that low cost underwater sensor node may experience large system errors and random errors of distance measurement. Our results show that the errors indeed cause severe performance degradation in localization coverage and normalized localization errors. The sources of distance measurement errors are also identified and their remedies are suggested.