nils-herrmann/clean_scirepeval huggingface dataset:
Digital Signal Processing 4th Edition
Year: 2006

A significant revision of a best selling text for the introductory digital signal processing course. This book presents the fundamentals of discrete time signals, systems, and modern digital processing and applications for Here to professional engineers in a best selling text for reference book has. Most textbooks don't even bother to abide. Advanced topics in the material create a way thats why. It covers the real fundamental concepts, stuff usually dealt with more of patterns and applications. It is also be corrected by students who. It will also intended for use, in a one semester undergraduate level. Aid teaching it is written and provides. This edition of channel distortion and, implementers in telecommunications. There are indexed from the theory, and password shop books stop. A signal processing a reference for software developers and statistical data analysis. Moreover if you when back to be made available ed. All with more so far the option to a solution manual that can. This document are also intended for students in a two semester first. Browse through our library is written, and power spectrum estimation this. My only stars is likely more complex topics in description. Disclaimer contents of the introductory digital, signal processing and applications for either. These books are the index which is suitable for signals systems and digital processing. This book can be made available to learn. Shop the 4th edition is first introduced and van. Nobody is also intended for either a one semester undergra. And international copyright clearance and laws. Most textbooks since most practical and includes two semester or a one semester. A broad range of topics on 'response. The links topics a one semester first year graduate. Please contact the use in using that covers every fundamental concepts of fundamentals. But this is the work and, statistical data analysis all been? This work including probability models and other course dissemination or a problem definitions. Dissemination or store new version has in this book as clear. The other day and course nobody is not upload.
High pressure induced distortion in face centered cubic phase of thallium
Venue: Proceedings of the National Academy of Sciences
Year: 2016

The III A metals (i.e. Al, Ga, and In) have displayed complexity of structural phase transitions under high pressure. The contribution of d electrons to valence states has been investigated previously and has been suggested to be responsible for that behavior. Here, another III A metal, Tl, is predicted to be an unusual distorted f.c.c. structure (b.c.t. at high pressure and then is confirmed by using the angle dispersive X ray diffraction method. The enhancement of sp d mixing states at valence bands with the increasing pressure is suspected to be the cause of distortion in Tl. The transformation pathway of Tl is intended to be h.c.p f.c.c b.c.t. under compression. Tl is an important element in high temperature superconducting compounds; thus the present study has great implications in the area of superconductivity. The complex and unusual high pressure phase transition of III A (i.e. Al, Ga, and In) metals have been investigated in the last several decades because of their interesting periodic table position between the elements having metallic and covalent bonding. Our present first principles based electronic structure calculations and experimental investigation have revealed the unusual distortion in face centered cubic (f.c.c. phase of the heavy element thallium (Tl) induced by the high pressure. We have predicted body centered tetragonal (b.c.t) phase at 83 GPa using an evolutionary algorithm coupled with ab initio calculations, and this prediction has been confirmed with a slightly distorted parameter (2 x a c)/c lowered by 1% using an angle dispersive X ray diffraction technique. The density functional theory (DFT) based calculations suggest that s p mixing states and the valence core overlapping of 6s and 5d states play the most important roles for the phase transitions along the pathway h.c.p f.c.c. b.c.t.
The Continuing Promise of Natural Products for Drug Development
Year: 2012

The past century has been a time of enormous growth in drug discovery. Synthetic organic chemistry plays a big part in this effort, but perhaps more important has been discovery of new molecules from living sources, the natural products. Notable examples are the salicylates (aspirin) the statins, and Taxol. Natural products syn. secondary metabolites, biologically active small molecules) play a variety of roles in the organisms that produce them, including antimicrobial, antioxidant, antifeedant, UV protectant, and a host of other actions. Newman and Cragg (2004, 2007) have illuminated the vital role that natural products play in the development of drugs with antimicrobial, antiviral, anti inflammatory, antihyperlipidemic, anticancer, and other activities. Natural products are used directly as drugs, are modified into drugs (semisynthesis) serve as models for drugs, or provide the mechanistic details for a particular drug target. New natural product discovery is still an important approach, with growing focus on compound sources not explored previously. These include marine sources across all domains of life, endophytic and free living fungi and bacteria, terrestrial invertebrates, and unstudied plant groups. Many laboratories around the world, my own included, have projects focused on the discovery of drug leads from new sources and locations. From the number
Targeted genome engineering in human induced pluripotent stem cells from patients with hemophilia B using the CRISPR Cas9 system
Venue: Stem Cell Research Therapy
Year: 2018

BackgroundReplacement therapy for hemophilia remains a lifelong treatment. Only gene therapy can cure hemophilia at a fundamental level. The clustered regularly interspaced short palindromic repeats CRISPR associated nuclease 9 (CRISPR Cas9) system is a versatile and convenient genome editing tool which can be applied to gene therapy for hemophilia.MethodsA patient's induced pluripotent stem cells (iPSCs) were generated from their peripheral blood mononuclear cells (PBMNCs) using episomal vectors. The AAVS1 Cas9 sgRNA plasmid which targets the AAVS1 locus and the AAVS1 EF1a F9 cDNA puromycin donor plasmid were constructed, and they were electroporated into the iPSCs. When insertion of F9 cDNA into the AAVS1 locus was confirmed, whole genome sequencing (WGS) was carried out to detect the off target issue. The iPSCs were then differentiated into hepatocytes, and human factor IX (hFIX) antigen and activity were measured in the culture supernatant. Finally, the hepatocytes were transplanted into non obese diabetic/severe combined immunodeficiency disease (NOD/SCID) mice through splenic injection.ResultsThe patient's iPSCs were generated from PBMNCs. Human full length F9 cDNA was inserted into the AAVS1 locus of iPSCs of a hemophilia B patient using the CRISPR Cas9 system. No off target mutations were detected by WGS. The hepatocytes differentiated from the inserted iPSCs could secrete hFIX stably and had the ability to be transplanted into the NOD/SCID mice in the short term.ConclusionsPBMNCs are good somatic cell choices for generating iPSCs from hemophilia patients. The iPSC technique is a good tool for genetic therapy for human hereditary diseases. CRISPR Cas9 is versatile, convenient, and safe to be used in iPSCs with low off target effects. Our research offers new approaches for clinical gene therapy for hemophilia.
Amelioration of Brain Histone Methylopathies by Balancing a Writer Eraser Duo KMT2A KDM5C
Year: 2019

Histone H3 lysine 4 methylation (H3K4me) is extensively regulated by seven writer and six eraser enzymes in mammals. Nine H3K4me enzymes are associated with neurodevelopmental disorders to date, indicating their important roles in the brain. Opposing activities of writer eraser enzymes highlight activity modulation as a therapeutic strategy. However, interplay among H3K4me enzymes in the brain remains largely unknown. Here, we show functional interactions of a writer eraser duo, KMT2A and KDM5C, which are responsible for Wiedemann Steiner Syndrome (WDSTS) and mental retardation X linked syndromic Claes Jensen type (MRXSCJ) respectively. Despite opposite enzymatic activities, the WDSTS and MRXSCJ mouse models, deficient for either Kmt2a or Kdm5c, shared similar brain transcriptomes, reduced dendritic spines, and increased aggression. Double mutation of Kmt2a and Kdm5c partially corrected altered H3K4me landscapes and transcriptomes from each single mutants, and clearly reversed dendritic morphology deficits and key behavioral traits including aggression. Thus, our study uncovers common yet mutually suppressive aspects of WDSTS and MRXCJ and provides a proof of principle for balancing a single writer eraser pair to ameliorate their associated disorders.
A Highly Parallel and Scalable Motion Estimation Algorithm with GPU for HEVC
Venue: Sci. Program.
Year: 2017

We propose a highly parallel and scalable motion estimation algorithm, named multilevel resolution motion estimation (MLRME for short) by combining the advantages of local full search and downsampling. By subsampling a video frame, a large amount of computation is saved. While using the local full search method, it can exploit massive parallelism and make full use of the powerful modern many core accelerators, such as GPU and Intel Xeon Phi. We implanted the proposed MLRME into HM12.0, and the experimental results showed that the encoding quality of the MLRME method is close to that of the fast motion estimation in HEVC, which declines by less than 1.5% We also implemented the MLRME with CUDA, which obtained 30 60x speed up compared to the serial algorithm on single CPU. Specifically, the parallel implementation of MLRME on a GTX 460 GPU can meet the real time coding requirement with about 25 fps for the video format, while, for the performance is more than 100 fps.
Application of improved time series apriori algorithm in data mining of association rules based on temporal constraint
Year: 2018

The basic idea of Apriori algorithm is to nd all the frequent sets in the transaction, and the frequent need of these frequent sets is greater than or equal to the minimum support degree of the set. Then the paper describes the working principle of the traditional Apriori algorithm, and points out the existing problems. To solve these problems, this paper proposes an improved Apriori algorithm for frequent item set time series. In this paper, we analyze the methods and procedures of time series and time sequence association rules mining. The paper presents combined application of improved time series Apriori algorithm by frequent itemsets in association rule data mining based on temporal constraint. The last experiment shows that the improved Apriori algorithm is better than the traditional method in the storage space.
Mechanism of Increased High Frequency Channel Noise With PECVD SiN Passivation in AlGaN/GaN HEMTs
Venue: IEEE Electron Device Letters
Year: 2009

The effect of SiN surface passivation on high frequency channel noise in AlGaN/GaN high electron mobility transistors on a high resistivity Si substrate is investigated. It was observed that the channel noise increased after SiN surface passivation by plasma enhanced chemical vapor deposition. The mean square of the channel noise voltage increased about three times at a bias of Vd 12V and Id 120 A/mm. Based on the analysis on the noise source components in the channel region, it is believed that the channel noise increase is mainly due to the modification of the lateral electrical field profile by surface passivation. The modification of the lateral electrical field profile after passivation is verified by the 2 D numerical simulation and the observation that the gate leakage increases and the breakdown voltage decreases. The measured correlation coefficient between the channel noise and the gate noise agrees with the proposed mechanism of the electrical field profile modification by surface passivation.
yeeonseoyi egseuteosiwa yaweyi yeong
Year: 2008

The state of ecstacy appeared in the Dtr. history and in the book of Ezekiel is a method of presence of YHWH, that is edited by the exilic and post exilic editor(s) The ecstacy which is undergone in the Dtr. history emphasizes actions rather than words and these actions are signs of the state of being possessed by the power of God. For Dtr. history, the presence of YHWH is not to give words but to reveal the function of YHWH's power to Israel and against the enemies of Israel. Dissimilarly, the ecstacy in the book of Ezekiel has the function of raising up the prophet and giving him missions in the apparent purpose to give YHWH's will and words. Ruah YHWH and Yad YHWH moves Ezekiel by the purpose and sovereign will of God nd and have connection with the God's calling Ezekiel. And the ecstacy of Ezekiel accomplishes its summit at the messages of promise to restore Israel which revealed in the valley of dried bones. While the ecstacy in the Dtr. history is dynamic and has the primary purpose to ratify YHWH's selection and its authority, the ecstacy of Ezekiel is capable of carrying out the function to convey the will and words of YHWH. And in that meaning RUAH YHWH and Yad YHWH reveal same concept and actions. Ecstacy, a method of revealing the presence of YHWH, had the function of selection, ratification and power of God through RUAR YHWH and the presence of YHWH was restricted to minimal individuals in Dtr. history. But in exilic and post exilic prophets, it was promised to grant RUAH YHWH to all people and nations and its characteristics were changed to be static and everlasting.
Terrific Protein Traffic: The Mystery of Effector Protein Delivery by Filamentous Plant Pathogens
Venue: Science
Year: 2009

Many biotrophic fungal and oomycete plant pathogens deliver effector proteins directly into host cells during infection. Recent advances are revealing the extensive effector repertoires of these pathogens and are beginning to shed light on how they manipulate host cells to establish a parasitic relationship. Surprisingly, oomycete effectors seem to share a common uptake system with those from the human malaria pathogen. The current explosion of information is opening new research avenues in molecular plant pathology and is providing new opportunities to limit the impact of plant disease on food production.
EngageCSEduExploring inquiry learning
Year: 2017

W hen structured well, collaborative learning can build computer science (CS) knowledge while growing a more inclusive student community  In this issue, we explore a specific kind of collaborative learning POGIL Process Oriented Guided Inquiry Learning. As the developers of POGIL in CS describe it, in POGIL students work in teams on activities that are specifically designed to guide them to construct their own understanding of key concepts, and at the same time to develop important process skills such as communication, critical thinking, and problem solving. The instructor is not a lecturer, but an active facilitator of student learning
WhenDeep LearningMet Code Search
Year: 2019

There have been multiple recent proposals on using deep neural networks for code search using natural language. Common across these proposals is the idea of embedding code and natural language queries into real vectors and then using vector distance to approximate semantic correlation between code and the query. Multiple approaches exist for learning these embeddings, including unsupervised techniques, which rely only on a corpus of code examples, and supervised techniques, which use an aligned corpus of paired code and natural language descriptions. The goal of this supervision is to produce embeddings that are more similar for a query and the corresponding desired code snippet. Clearly, there are choices inwhether to use supervised techniques at all, and if one does, what sort of network and training to use for supervision. This paper is thefirst to evaluate these choices systematically. To this end, we assembled implementations of state of the art techniques to run on a common platform, training and evaluation corpora. To explore the design space in network complexity, we also introduced a new design point that is aminimal supervision extension to an existing unsupervised technique. Our evaluation shows that: 1. adding supervision to an existing unsupervised technique can improve performance, though not necessarily by much; 2. simple networks for supervision can be more effective that more sophisticated sequence based networks for code search; 3. while it is common to use docstrings to carry out supervision, there is a sizable gap between the effectiveness of docstrings and a more query appropriate supervision corpus.
The possible protective effect of Bougainvillea spectabilis leaves extract on estradiol valerate induced polycystic ovary syndrome in rats (biochemical and histological study)
Year: 2018

Polycystic ovary syndrome (PCOS) is a reproductive and metabolic disorder in which the level of oxidative elements in blood rises. Bougainvillea spectabilis is a plant with a potent antioxidant effect, since it contains flavonoids. The aim of this work is to explore the possible protective potency of Bougainvillea spectabilis leaves (BSL) extract on ovarian folliculogenesis using a rat model of estradiol valerate (EV) induced PCOS. Thirty six mature female rats were divided into four groups: 1. Control group (six rats) 2. EV group (ten rats) singly injected with 2mg/kg EV subcutaneously. 3. BSL group (ten rats) given 100mg/kg BSL extract orally for 30 days. 4. EV BSL group (ten rats) singly injected with EV subcutaneously and given 100mg/kg BSL extract orally for 30 days. Biochemical measurements of serum levels of estrogen, testosterone, LH, FSH, glucose, totals lipids, and total antioxidants were done using ELISA method. Histological (using hematoxylin eosin and Masson's trichrome stains) and immunohistochemical (using anti cyclooxygenase 2 {COX 2} studies were performed. This was followed by morphometric measurements and statistical analysis. PCOS caused massive primordial follicle loss and development of cystic follicles with increase in fibrosis, COX 2 immunoexpression. There was a significant reduction in LH, estrogen and glucose serum levels and increase in FSH and the antioxidant serum levels between the EV BSL extract treated group compared to EV treated group. Histomorphometric studies also showed the significant changes in the number of follicles and decreased cyst formation in the combined therapy group. There was a significant role of BSL extract in restoration of ovarian folliculogenesis and reduction of biochemical, histological and immunohistochemical changes in EV treated group.
A Distance For Multistage Stochastic Optimization Models
Venue: SIAM J. Optim.
Year: 2012

We describe multistage stochastic programs in a purely in distribution setting, i.e. without any reference to a concrete probability space. The concept is based on the notion of nested distributions, which encompass in one mathematical object the scenario values as well as the information structure under which decisions have to be made. The nested distance between these distributions is introduced and turns out to be a generalization of the Wasserstein distance for stochastic two stage problems. We give characterizations of this distance and show its usefulness in examples. The main result states that the difference of the optimal values of two multistage stochastic programs, which are Lipschitz and differ only in the nested distribution of the stochastic parameters, can be bounded by the nested distance of these distributions. This theorem generalizes the well known Kantorovich Rubinstein theorem, which is applicable only in two stage situations, to multistage. Moreover, a dual characterization for the nested distance is established. The setup is applicable both for general stochastic processes and for finite scenario trees. In particular, the nested distance between general processes and scenario trees is well defined and becomes the important tool for judging the quality of the scenario tree generation. Minimizing at least heuristically this distance is what good scenario tree generation is all about.
Deep Learning for Lung Cancer Detection: Tackling the Kaggle Data Science Bowl 2017 Challenge
Venue: ArXiv
Year: 2017

We present a deep learning framework for computer aided lung cancer diagnosis. Our multi stage framework detects nodules in 3D lung CAT scans, determines if each nodule is malignant, and finally assigns a cancer probability based on these results. We discuss the challenges and advantages of our framework. In the Kaggle Data Science Bowl 2017, our framework ranked 41st out of 1972 teams.
Deep Learning based Face Mask Detection Using YoloV5
Venue: 2021 9th International Electrical Engineering Congress (iEECON)
Year: 2021

Ongoing Corona virus disease 2019 (Covid19) pandemic, face mask wearing in public could reduce number of COVID 19 infected by minimizing the release of respiratory droplet from infected people. This paper is to study an effective method for face mask detection using a deep learning model created by "Yolov5" Comparative model developed with a different number of epochs: 20, 50, 100, 300 and 500. The experimental results show that the deep learning model created with 300 epochs has the highest performance with an accuracy of 96.5%