gebhart/patrepeval huggingface dataset:
Searching for New Physics in Resonant and Non-Resonant Dilepton Final States With the ATLAS Detector at the LHC (2022)

The Standard Model, the mathematical description of the interactions of elementary particles, has proven to be a successful framework. Since its finalisation in the 1970s, no significant deviations have been measured from its predictions. However, some phenomena are not currently explained by the Standard Model: What is the nature of dark matter? Can a quantum theory of gravity be constructed? Numerous extensions to the Standard Model have been put forth over the years, trying to answer these, and other, questions about nature. Theoretical extensions of the Standard Model may yield different predictions about nature than the Standard Model itself. Physicists look for evidence of new physics by finding discrepancies from predictions, for example in particle collision experiments.\nWe search for discrepancies to the Standard Model predictions by analysing proton-proton collision data collected by the ATLAS detector at the Large Hadron Collider, located at the CERN particle physics laboratory in Switzerland. Specifically, we select particle collision events for analysis where the final state of the collisions are two electrons or muons. We perform two separate searches for new physics on this dataset. The first is a search for so-called resonant phenomena, manifesting as localised deviations from the Standard Model prediction, in the reconstructed mass of the selected lepton pairs. The second search is for non-resonant phenomena, where the new physics is expected to appear as broad deviations to the Standard Model predictions in the high mass region of the data. In both searches, the Standard Model background prediction is estimated by fitting a functional form to the data.\nNo significant deviation from the background estimate is observed in either search. We set upper limits on the cross-section of a generic dilepton resonance and lower limits on the mass of a potential new heavy neutral boson. We also set lower limits on the so-called string scale parameter of the Arkani-Hamed, Dimopoulos, and Dvali model of large extra dimensions. This model may explain the discrepancy in strength between the particle interactions of the Standard Model, and gravity.
RF sputter etch as a surface cleaning process for CdTe solar cells (2005)

Thin film CdTe/CdS solar cells benefit from the use of a wet chemistry step prior to the application of the back contact electrode. A nitric-phosphoric acid mixture and a bromine solution are the most commonly used etchants. Following the CdCI/sub 2/ heat treatment the CdTe/CdS structures are briefly etched in one of the above solutions in order to remove native oxides and leave the CdTe surface Te-rich. A higher carrier concentration at the surface of CdTe is believed to be a key factor in facilitating the formation of an effective back contact. The primary objective of this work is to investigate the potential of an alternative dry, vacuum-based process, as a surface modification step for CdTe prior to the application of the back contact electrode. RF-sputter etch has been used as an alternative surface cleaning process. The process was optimized for the type of etchant gas, pressure, time, and sputter power. Solar cells exhibited V/sub OC/'s greater than 830 mV and FF's in the high 60's. This performance demonstrates the potential of this process for the development of an all-dry vacuum based CdTe technology.
Research on Adaptive Control Strategy of Intelligent Spray System (2017)

By looking back the research status both at home and abroad, the overall plan of the target spray control system of self-propelled target sprayer is formulated. Based on the speed to dynamically adjust the sampling frequency by single chip microcomputer controller to realize three consecutive sampling methods for identifying targets and the algorithm of interference signal filtering, solenoid valve is used to control the spray opening and closing, combining with technology of target based on laser sensor. In this paper, main components of the hydraulic circuit are selected and STCI2CSA60S2 is set as the core to design the connection of single chip processor module, signal detection module, matrix key module, liquid crystal display module, alarm indicator module and serial interface communication module. Based on the C language, the handler and target discrimination algorithm is written, including the processing of the main program, the target sampling, detection, alarm indication and matrix button subroutine.
Do Deep Generative Models Know What They Don't Know? (2018)

A neural network deployed in the wild may be asked to make predictions for inputs that were drawn from a different distribution than that of the training data. A plethora of work has demonstrated that it is easy to find or synthesize inputs for which a neural network is highly confident yet wrong. Generative models are widely viewed to be robust to such mistaken confidence as modeling the density of the input features can be used to detect novel, out-of-distribution inputs. In this paper we challenge this assumption. We find that the density learned by flow-based models, VAEs, and PixelCNNs cannot distinguish images of common objects such as dogs, trucks, and horses (i.e. CIFAR-10) from those of house numbers (i.e. SVHN), assigning a higher likelihood to the latter when the model is trained on the former. Moreover, we find evidence of this phenomenon when pairing several popular image data sets: FashionMNIST vs MNIST, CelebA vs SVHN, ImageNet vs CIFAR-10 / CIFAR-100 / SVHN. To investigate this curious behavior, we focus analysis on flow-based generative models in particular since they are trained and evaluated via the exact marginal likelihood. We find such behavior persists even when we restrict the flows to constant-volume transformations. These transformations admit some theoretical analysis, and we show that the difference in likelihoods can be explained by the location and variances of the data and the model curvature. Our results caution against using the density estimates from deep generative models to identify inputs similar to the training distribution until their behavior for out-of-distribution inputs is better understood.
Edge Machine Learning for AI-Enabled IoT Devices: A Review (2020)

In a few years, the world will be populated by billions of connected devices that will be placed in our homes, cities, vehicles, and industries. Devices with limited resources will interact with the surrounding environment and users. Many of these devices will be based on machine learning models to decode meaning and behavior behind sensors' data, to implement accurate predictions and make decisions. The bottleneck will be the high level of connected things that could congest the network. Hence, the need to incorporate intelligence on end devices using machine learning algorithms. Deploying machine learning on such edge devices improves the network congestion by allowing computations to be performed close to the data sources. The aim of this work is to provide a review of the main techniques that guarantee the execution of machine learning models on hardware with low performances in the Internet of Things paradigm, paving the way to the Internet of Conscious Things. In this work, a detailed review on models, architecture, and requirements on solutions that implement edge machine learning on Internet of Things devices is presented, with the main goal to define the state of the art and envisioning development requirements. Furthermore, an example of edge machine learning implementation on a microcontroller will be provided, commonly regarded as the machine learning "Hello World".
Adaptive mode tuning for vibrational gyroscopes (2003)

We present an adaptive controller for tuning the natural frequency of the drive axis of a vibrational gyroscope. This is an attractive alternative to a phase-locked loop, since it introduces feedback, which can reduce the effects of imprecise fabrication. We also operate the gyroscope at a fixed frequency, chosen by the designer, which can simplify signal processing.
Is sympathectomy of benefit in critical leg ischaemia not amenable to revascularisation? (2005)

A best evidence topic in vascular surgery was written according to a structured protocol. The question addressed was whether the use of sympathectomy was of benefit in non-revascularisable critical leg ischaemia. Altogether 387 papers were found using the reported search, of which 13 represented the best evidence to answer the clinical question. The author, journal, date and country of publication, patient group studied, study type, relevant outcomes, results, and study weaknesses were tabulated. We conclude that lumbar sympathectomy is a minimally invasive procedure with a low complication rate. Randomized controlled trials have failed to identify any objective benefits for lumbar sympathectomy, but subjective improvements in symptoms for patients with highly symptomatic critical leg ischaemia have been consistently demonstrated in multiple cohort studies with sustained symptom improvements in approximately 60% of patients. Lumbar sympathectomy should be considered for symptomatic patients with critical leg ischaemia as an alternative to amputation in patients with otherwise viable limbs.
Cooperation between Active Material, Polymeric Binder and Conductive Carbon Additive in Lithium Ion Battery Cathode (2012)

A lithium ion battery electrode is a composite of active material, polymeric binder, and conductive carbon additive(s). Cooperation among the different components plays a subtle and important role in determining the physical and electrochemical properties of the electrode. In this study, the physical and electrochemical properties of a LiNi0.8Co0.15Al0.05O2 cathode were investigated as a function of the electrode compositions. The electrode conductivity, porosity, specific capacity, first Coulombic efficiency, and rate capability were found significantly affected by the polyvinylidene difluoride (PVDF)-to-acetylene black (AB) ratio and the total inactive material amount. The electronic conductivity of the laminate does not so much decide the rate performance of the electrode as it is generally believed. The rate capability of the electrode is enhanced by an increase in the total inactive material content at a PVDF/AB ratio of 5:4, whereas it is deteriorated by increasing the total inactive material content at PVDF/AB ratios of 5:1 and 5:2. At a PVDF/AB ratio of 5:3, the rate performance is not considerably affected by the inactive material content. The result is explained by the competition between the ion-blocking effect of PVDF binder and the electronic conducting effect of the AB additive. A long-term cycling experiment shows the mechanical integrity of the laminate is important for the durability of the composite electrode.
A model for studying human articular cartilage integration <i>in vitro</i> (2010)

One of the major obstacles hindering cartilage repair is the integration of the reparative cartilage with the recipient cartilage. The purpose of this study was to develop an in vitro model that can be conveniently applied to simulate and improve the integration of tissue engineered cartilage with native articular cartilage. This model, a cartilage integration construct, consists of a cartilage explant and isolated chondrocytes. The explant was anchored to agarose gel on a culture plate as agarose gelation at 4 degrees C to seal the gap between the bottom of the explant and culture plate surface. Isolated chondrocytes were added and confined in the defect created in the center of the explant. After 4 weeks of culture, neocartilage containing proteoglycans and type II collagen was formed. Minimal integration occurred between the neocartilage and the cartilage explant, resembling the failure of cartilage integration manifested in experimental and clinical cartilage repair. In this model, agarose gel anchors the explant onto culture plate by altering temperatures and effectively prevents "leakage" of the isolated chondrocytes from the defect of the explant. This model provides a convenient simulation of the cartilage integration process in vitro and has applications in studies of cartilage integration and cartilage tissue engineering.
Development and Characterization of a Subtilin-Regulated Expression System in <i>Bacillus subtilis</i> : Strict Control of Gene Expression by Addition of Subtilin (2005)

A system for subtilin-regulated gene expression (SURE) in Bacillus subtilis that is based on the regulatory module involved in cell-density-dependent control of the production of subtilin is described. An integration vector for introduction of the essential sensor-regulator couple spaRK into the amyE locus of the B. subtilis chromosome and a B. subtilis 168-derived production host in which the spaRK genes were functionally introduced were constructed. Furthermore, several expression plasmids harboring the subtilin-inducible wild-type spaS promoter or a mutated derivative of this promoter were constructed, which facilitated both transcriptional and translational promoter-gene fusions. Functional characterization of both spaS promoters and the cognate expression host could be performed by controlled overproduction of the beta-glucuronidase (GusA) and green fluorescent protein (GFP) reporters. Both spaS promoters exhibited very low levels of basal expression, while extremely high levels of expression were observed upon induction with subtilin. Moreover, the level of expression depended directly on the amount of inducer (subtilin) used. The wild-type spaS promoter appeared to be more strictly controlled by the addition of subtilin, while the highest levels of expression were obtained when the mutated spaS promoter was used. Induction by subtilin led to 110- and 80-fold increases in GusA activity for the spaS promoter and its mutant derivative, respectively. Since the SURE system has attractive functional characteristics, including promoter silence under noninducing conditions and a controlled and high level of expression upon induction, and since it is not subject to catabolite control, we anticipate that it can provide a suitable expression system for various scientific and industrial applications.
Design and Implementation of Indoor Environmental Quality Monitoring System based on ZigBee (2015)

This paper designs a indoor environmental quality monitoring system, in which indoor environment parameters, such as temperature, humidity and PM2.5 density can be gathered, transmitted and displayed. Arduino, a open-source hardware and software platforms, is used to access sensors. With the help of ZigBee, which is a new wireless communication protocol characterized by low-power, devices composed of Arduino and sensors are placed in different rooms so that the energy consumption can be effectively reduced. In addition, an specific transmission protocol is also be defined for this system. Finally sensor data are transmitted to the internal server and then a cloud platform via WiFi. The result shows that this system is stable and easy to build and change network.
Best basis segmentation of ECG signals using novel optimality criteria (2002)

Automatic segmentation of the electrocardiogram (ECG) is important in both clinical and research settings. Past algorithms have relied on incorporation of detailed heuristics. We avoid heuristics by employing a best-basis algorithm. As large variability of the local SNR causes the standard entropy criterion to produce an overly-fine segmentation, we introduce a novel optimality criterion which is based on a linear combination of the entropy measure and a function of a smoothness measure, and is quite general in form. We tested the algorithm on the MIT-BIH arrythmia database and body surface potential maps.
Leveraging Product Characteristics for Online Collusive Detection in Big Data Transactions (2019)

Online fraud transaction has been a big concern for e-business platform. As the development of big data technology, e-commerce users always evaluate the sellers according to the reputation scores supplied by the platform. The reason why the sellers prefer chasing high reputation scores is that high reputations always bring high profit to sellers. By collusion, fraudsters can acquire high reputation scores and it will attract more potential buyers. It has been a crucial task for the e-commerce website to recognizing the fake reputation information. E-commerce platforms try to solve this continued and growing problem by adopting data mining techniques. With the high development of the Internet of Things, big data plays a crucial role in economic society. Big data brings economic growth in different domains. It supplies support to the management and decision-making ability in e-business through analyzing operational data. In online commerce, the big data technology also helps in providing users with a fair and healthy reputation system, which improves the shopping experience. This paper aims to put forward a conceptual framework to extract the characteristics of fraud transaction, including individual- and transaction-related indicators. It also contains two product features: product type and product nature. The two features obviously enhance the accuracy of fraud detection. A real-world dataset is used to verify the effectiveness of the indicators in the detection model, which is put forward to recognize the fraud transactions from the legitimate ones.
Functionality of Sortase A in <i>Lactococcus lactis</i> (2010)

Lactococcus lactis IL1403 harbors a putative sortase A (SrtA) and 11 putative sortase substrates that carry the canonical LPXTG signature of such substrates. We report here on the functionality of SrtA to anchor five LPXTG substrates to the cell wall, thus suggesting that SrtA is the housekeeping sortase in L. lactis IL1403.
Computational Prediction of Viral miRNAs (2011)

While cloning and/or massive parallel sequencing of small RNAs represent powerful tools for the discovery of novel miRNAs, computational miRNA prediction represents a valuable alternative which can be performed with comparably little technical effort. This is especially true for viruses, as the number of predicted candidates generally remains low and thus within a range that may be readily confirmed by experimental means. Here, we provide a detailed protocol for the prediction of putative miRNA genes using VMir, an ab initio prediction program which we have recently designed specifically to identify pre-miRNAs in viral genomes.
High critical current densities in YBa2Cu3O7−<i>x</i> films on polycrystalline zirconia (1990)

We report the growth on polycrystalline yttria-stabilized zirconia substrates of YBa2Cu3O7−x films with Jc (77 K)=11 000 A/cm2 and Jc (4.2 K)=122 000 A/cm2 by pulsed laser ablation. These Jc values are among the highest reported for YBa2Cu3O7−x on any polycrystalline substrate and approach the intrinsic upper limit for films with large-angle grain boundaries, as indicated by recent bicrystal experiments. We find that the substrate temperature during film growth is most important in obtaining high Jc polycrystalline films. Although the magnetic field dependence of Jc indicates the presence of weak links, the behavior of Jc (4.2 K, H) suggests that a percolative path consisting of low-angle grain boundaries exists in the films, resulting in Jc (4.2 K, 60 kOe)=4100 A/cm2.
LANDING SITE PREDILEKSI LALAT SUMBA (Hippobosca sp.) PADA SAPI BALI (2017)

The development of cattle farming in East Nusa Tenggara is one of the potential contributors to support local demands. In order to achive this goal, cattle have to be free from the disease and parasites. One of the most common ecto- parasites that also serve as disease vector is bitting flies. Hippobosca sp. is bitting flies that commonly breed in the semi-arid  tropics  area  with  low  rate  of rainfall and high temperature such as East Nusa Tenggara Province. The aims of this research are to observe and determine the landing site of Hippobosca sp. in certain area of the cattle and to identify the predilection of Hippobosca sp. in Bali cattle. This research conducted in two different Bali cattle farms, Agricultural High School of Kupang in Kupang District and Neotnana Farmers Group in Kupang City. The observation was conducted to measure flies landing activity on five cows of each farm. The activity of the flies were observed in 5 major body regio, head area, neck area, thoraco-abdominal area, extremity area and perineal area. Landing flies was collected every 2 hours from 06:00 till 18:00 local time, and pooled based on body area they collected from. This procedure repeated 8 times in 4 weeks in each farm. The result showed that neck area is as the major landing site predilection of Hippobosca sp. in Bali Cattle. Neck area showed the highest density of landing flies, with total 3313 flies observed, followed by thoraco-abdominal, perineal, extremity and head area, with total amount of 2811, 1689, 1037, and 172 flies, respectively.
Neuro-ophthalmological complications of coronary artery bypass graft surgery (1987)

In a prospective study of neurological complications of coronary bypass surgery, detailed pre- and post-operative bedside ophthalmological evaluation was undertaken in 312 patients. Post-operative neuro-ophthalmological complications developed in 80/312 (25.6%) patients and included: areas of retinal infarction (17.3%); retinal emboli (2.6%); visual field defects (2.6%); reduction of visual acuity (4.5%) and Horner's syndrome (1.3%). Neuro-ophthalmological complications were not observed in a control group of 50 patients undergoing major peripheral vascular surgery. Ten of 75 patients reviewed at 6 months still had detectable neuro-ophthalmological abnormalities, but functional disability occurred only in those with persistent visual field defects. Multivariate analysis revealed that extra-coronary vascular disease, severe and prolonged duration of heart disease prior to operation, and large drop in haemoglobin level during surgery may predispose to neuro-ophthalmological complications.
ICFAX, an integrated circuit failure analysis expert system (2002)

An expert system to aid in the analysis of failed integrated circuits has been developed. The integrated circuit failure analysis expert system (ICFAX) captures a substantial portion of the procedural knowledge necessary to successfully analyze CMOS integrated circuit failures. ICFAX is designed to apply generically to all types of CMOS ICs. ICFAX also contains general information on how to analyze components as well as product specific information, including schematics, layout plots, product specifications, and fabrication data. The expert system centralizes textual and graphical knowledge about failure analysis, increasing the analyst's productivity and ability to determine the failure.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>