LLukas22/scidocs huggingface dataset:
Quantum nature of a strongly coupled single quantum dot–cavity system

Cavity quantum electrodynamics (QED) studies the interaction between a quantum emitter and a single radiation-field mode. When an atom is strongly coupled to a cavity mode, it is possible to realize important quantum information processing tasks, such as controlled coherent coupling and entanglement of distinguishable quantum systems. Realizing these tasks in the solid state is clearly desirable, and coupling semiconductor self-assembled quantum dots to monolithic optical cavities is a promising route to this end. However, validating the efficacy of quantum dots in quantum information applications requires confirmation of the quantum nature of the quantum-dot–cavity system in the strong-coupling regime. Here we find such confirmation by observing quantum correlations in photoluminescence from a photonic crystal nanocavity interacting with one, and only one, quantum dot located precisely at the cavity electric field maximum. When off-resonance, photon emission from the cavity mode and quantum-dot excitons is anticorrelated at the level of single quanta, proving that the mode is driven solely by the quantum dot despite an energy mismatch between cavity and excitons. When tuned to resonance, the exciton and cavity enter the strong-coupling regime of cavity QED and the quantum-dot exciton lifetime reduces by a factor of 145. The generated photon stream becomes antibunched, proving that the strongly coupled exciton/photon system is in the quantum regime. Our observations unequivocally show that quantum information tasks are achievable in solid-state cavity QED.
Design of a Packet-Based Control Framework for Networked Control Systems

A packet-based control framework is proposed for networked control systems (NCSs). This framework takes advantage of the characteristic of the packet-based transmission in a networked control environment, which enables a sequence of control signals to be sent over the network simultaneously, thus making it possible to actively compensate for the communication constraints in NCSs. Under this control framework and a deriving delay-dependent feedback gain scheme, a novel model for NCSs is proposed which can deal with network-induced delay, data packet dropout and data packet disorder in NCSs simultaneously and a receding horizon controller is also designed to implement the packet-based control approach. This approach is then verified by a numerical example and furthermore an Internet-based test rig which illustrates the effectiveness of the proposed approach.
Acceleration of cheese ripening

The characteristic aroma, flavour and texture of cheese develop during ripening of the cheese curd through the action of numerous enzymes derived from the cheese milk, the coagulant, starter and non-starter bacteria. Ripening is a slow and consequently an expensive process that is not fully predictable or controllable. Consequently, there are economic and possibly technological incentives to accelerate ripening. The principal methods by which this may be achieved are: an elevated ripening temperature, modified starters, exogenous enzymes and cheese slurries. The advantages, limitations, technical feasibility and commercial potential of these methods are discussed and compared.
Rethinking Permissioned Blockchains

Current blockchain platforms, especially the recent permissioned systems, have architectural limitations: smart contracts run sequentially, all node executes all smart contracts, consensus protocols are hard-coded, the trust model is static and not flexible, and non-determinism in smart-contract execution poses serious problems. Overcoming these limitations is critical for improving both functional properties of blockchains, such as confidentiality and consistency, as well as their non-functional properties, such as performance and scalability. We discuss these limitations in the context of permissioned blockchains, including an early version of the Hyperledger Fabric blockchain platform, and how a re-design of Hyperledger Fabric's architecture addresses them.
Robotics in the Small, Part I: Microbotics

This article provided an overview of the field of microrobotics, including the distinct but related topics of micromanipulation and microrobots. While many interesting results have been shown to date, the greatest results in this field are yet to come.
Malacosporean-like spores in urine of rainbow trout react with antibody and DNA probes to Tetracapsuloides bryosalmonae

Tetracapsuloides bryosalmonae is the myxozoan parasite causing proliferative kidney disease (PKD) of salmonid fishes in Europe and North America. The complete life cycle of the parasite remains unknown despite recent discoveries that the stages infectious for fish develop in freshwater bryozoans. During the course of examinations of the urine of rainbow trout (Oncorhynchus mykiss) with or recovering from PKD we identified spores with features similar to those of T. bryosalmonae found in the bryozoan host. Spores found in the urine were subspherical, with a width of 16 µm and height of 14 µm, and possessed two soft valves surrounding two spherical polar capsules (2 µm in diameter) and a single sporoplasm. The absence of hardened valves is a distinguishing characteristic of the newly established class Malacosporea that includes T. bryosalmonae as found in the bryozoan host. The parasite in the urine of rainbow trout possessed only two polar capsules and two valve cells compared to the four polar capsules and four valves observed in the spherical spores of 19 µm in diameter from T. bryosalmonae from the bryozoan host. Despite morphological differences, a relationship between the spores in the urine of rainbow trout and T. bryosalmonae was demonstrated by binding of monoclonal and polyclonal antibodies and DNA probes specific to T. bryosalmonae.
Capsule Deep Neural Network for Recognition of Historical Graffiti Handwriting

Automatic recognition of the historical letters (XI-XVIII centuries) carved on the stoned walls of St.Sophia cathedral in Kyiv (Ukraine) was demonstrated by means of capsule deep learning neural network. It was applied to the image dataset of the carved Glagolitic and Cyrillic letters (CGCL), which was assembled and pre-processed recently for recognition and prediction by machine learning methods. CGCL dataset contains >4000 images for glyphs of 34 letters which are hardly recognized by experts even in contrast to notMNIST dataset with the better images of 10 letters taken from different fonts. The capsule network was applied for both datasets in three regimes: without data augmentation, with lossless data augmentation, and lossy data augmentation. Despite the much worse quality of CGCL dataset and extremely low number of samples (in comparison to notMNIST dataset) the capsule network model demonstrated much better results than the previously used convolutional neural network (CNN). The training rate for capsule network model was 5-6 times higher than for CNN. The validation accuracy (and validation loss) was higher (lower) for capsule network model than for CNN without data augmentation even. The area under curve (AUC) values for receiver operating characteristic (ROC) were also higher for the capsule network model than for CNN model: 0.88-0.93 (capsule network) and 0.50 (CNN) without data augmentation, 0.91-0.95 (capsule network) and 0.51 (CNN) with lossless data augmentation, and similar results of 0.91-0.93 (capsule network) and 0.9 (CNN) in the regime of lossless data augmentation only. The confusion matrixes were much better for capsule network than for CNN model and gave the much lower type I (false positive) and type II (false negative) values in all three regimes of data augmentation. These results supports the previous claims that capsule-like networks allow to reduce error rates not only on MNIST digit dataset, but on the other notMNIST letter dataset and the more complex CGCL handwriting graffiti letter dataset also. Moreover, capsule-like networks allow to reduce training set sizes to 180 images even like in this work, and they are considerably better than CNNs on the highly distorted and incomplete letters even like CGCL handwriting graffiti. Keywords— machine learning, deep learning, capsule neural network, stone carving dataset, notMNIST, data augmentation
Prediction of Surface Topomorphy and Roughness in Ball-End Milling

Milling is today the most effective, productive and flexiblemanufacturing method for machining complicated or sculptured surfaces. Ball-end tools are used for machining 3D freeform surfaces for dies, moulds, and various parts, such as aerospace components, etc. Milling data, such as surface topomorphy, surface roughness, non-deformed chip dimensions, cutting force components and dynamic cutting behaviour, are very helpful, especially if they can be accurately produced by means of a simulation program. This paper presents a novel simulation model, the so-called MSN-Milling Software Needle program, which is able to determine the surface produced and the resulting surface roughness, for ball-end milling. The model simulates precisely the tool kinematics and considers the effect of the cutting geometry on the resulting roughness. The accuracy of the simulation model has been thoroughly verified, with the aid of a wide variety of cutting experiments. Many roughness measurements were carried out on workpieces, which were cut using a 5-axis machining centre. The calculated roughness levels were found to be in agreement with the experimental ones. The proposed model has proved to be suitable for determining optimal cutting conditions, when finishing complex surfaces. The software can be easily integrated into various CAD-CAM systems.
Improving synoptic and intraseasonal variability in CFSv2 via stochastic representation of organized convection

1Department of Mathematics and Statistics, University of Victoria, Victoria, BC, Canada. 2Indian Institute of Tropical Meteorology, Pune, India. 3Department of Mathematics and Center for Atmosphere and Ocean Sciences, Courant Institute for Mathematical Sciences, New York University, New York, NY, USA and Center for Prototype Climate Models, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
Structure response and damage produced by ground vibration from surface mine blasting

The Bureau of Mines studied blast-produced ground vibration 1 :·om surface mining to assess its damage and annoyance potential, and to de1 ~rmine safe levels and appropriate measurement techniques. Direct measurements were made of ground-vibration-produced structure responses and <'amage in 76 homes for 219 production blasts. These results were combined with damage data from nine other blasting studies, including the three analyz ~d previously for Bureau of Mines Bulletin 656. ~~~C ~levels of ground vibration from blasting range from 0.5 to 2.0 in/sec peak p,article velocity for residential-type structures. The damage threshold values are functions of the frequencies of the vibration transmitted into the residences and the types of construction. Particularly serious are the low-frequency vibrations that exist in soft foμndation materials and/or result from long blast-to-residence distances. These vibrations produce not only structure res6nances (4 to 12 Hz for whole structures and lO to 25 Hz for midwalls) but also excessive levels of displacement and strain. Threshold damage was defined as the occurrence of cosmetic damage; that is, the most superficial interior cracking of the type that develops in all homes independent of blasting. Homes with plastered interior walls are more susceptible to blast-produced cracking then modern gypsum wallboard; the latter are adequately protected by a minimum particle velocity of approximately 0. 75 in/ sec for frequencies below 40 Hz. Structure response amplification factors were measured; typical values were l.5 for structures as a whole (racking) and 4 for midwalls, at their respective resonance frequencies. For blast vibrations above 40 Hz, all amplification factors for frame residential structures were less than unity. The human response and annoyance problem from ground vibration is aggravated by wall rattling, secondary noises, and the presence of airblast. Approximately 5 to 10 pct of the neighbors will judge peak particle velocity levels of 0.5 to 0.75 in/sec as "less than acceptable" (i.e., unacceptable) based·on direct reactions to the vibration. Even lower levels cause psychological response problems, and thus social, economic, and public relations factors beC:ome critical for continued blasting. I Geophylicist, Twin Cities Research C.cnter. Bureau of Mines. Twin Cities. Minn. t Civil mgincer, Twin Cities Resean:h Cmter, Bureau of Mines. Twin Cities. Minn. s Mining mgineer, Twin Cities Research Cmter, Bu.,,.•u of Mines. Twin Cities. Minn. 'Civil engineer: Professor of Civil Engineerin11. Nonhwntern Unn·enity. E•-anston, Ill. ,io.\;~:;ill-..-'/·~.~ ,,.. '-~,".'.::....''!·-~ ••·•• -~. ·~1-~,..· .,. . ' -'· . v..'', .• ~ • . ' -.:" ·" ~··-' .,, ••••. ,.. ... •
The Birds of Michigan

th , Science Duration: One class period to build birdhouses, one day field trip to Belle Isle Nature Center Lesson Overview: After making birdhouses, students will visit Belle Isle Nature Center to observe and hang houses in wooded area around the site. This trip will help prepare the students for our overnight camping trip. They will be able to listen and recognize bird sounds and attributes.  What are some ways other than migration that birds meet the challenges of winter?  How do feathers heal birds? Activities Focus on Feathers Give each child a feather or two to examine. If possible, include flight, contour, and down feathers. a) As the children describe the parts of a feather, the leader draws them on the blackboard to illustrate a typical feather. Make sure to note the hollow shaft. What differences do the children notice between their feathers? What functions do feathers perform? b) Have the children gently pull apart the web of the feather. Use a hand lens to see the tiny barbules that project from the barbs. What function might these serve? Have the children try to zip feathers together by pinching and drawing their fingers along the separated barbs from the shaft to the outer edge. Discuss how birds oil and groom themselves. Mix and Match Give each pair of children a picture of a bird. Ask them to look at the shape of the bird's beak, feet, legs, and with a partner talk about how the bird might use these to obtain food and eat it. Spread out the pictures of possible bird foods. Ask the children to place their bird picture next to an appropriate food. More than one bird may eat the same
Technische Grundlagen und datenschutzrechtliche Fragen der Blockchain-Technologie

Die Blockchain-Technologie beflügelt derzeit wie kaum eine andere Phantasien von einer transparenteren Informationsgesellschaft. Ihr Verhältnis zum Datenschutz ist allerdings kompliziert. Der Beitrag skizziert die Grundzüge der Problematik.
Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations

How can we learn a classier that is “fair” for a protected or sensitive group, when we do not know if the input to the classier belongs to the protected group? How can we train such a classier when data on the protected group is dicult to aain? In many settings, nding out the sensitive input aribute can be prohibitively expensive even during model training, and sometimes impossible during model serving. For example, in recommender systems, if we want to predict if a user will click on a given recommendation, we oen do not know many aributes of the user, e.g., race or age, and many aributes of the content are hard to determine, e.g., the language or topic. us, it is not feasible to use a dierent classier calibrated based on knowledge of the sensitive aribute. Here, we use an adversarial training procedure to remove information about the sensitive aribute from the latent representation learned by a neural network. In particular, we study how the choice of data for the adversarial training eects the resulting fairness properties. We nd two interesting results: a small amount of data is needed to train these adversarial models, and the data distribution empirically drives the adversary’s notion of fairness. ACM Reference format: Alex Beutel, Jilin Chen, Zhe Zhao, Ed H. Chi. 2017. Data Decisions and eoretical Implications when Adversarially Learning Fair Representations. In Proceedings of 2017Workshop on Fairness, Accountability, and Transparency in Machine Learning, Halifax, Canada, August 2017 (FAT/ML ’17), 5 pages.
Fabrication of Graphene/Epoxy Resin Composites with Much Enhanced Thermal Conductivity via Ball Milling Technique

Ball milling is selected to prepare composites of graphene nanoplatelets (GNPs) and epoxy. Much enhanced thermal conductivity was recorded with higher GNP loading, which varied between 5 and 25 wt %. A maximum thermal conductivity of 2.67 W/m·K was found. The prepared composites were characterized by scanning electron microscopy, transmission electron microscopy, and Raman. It was found that KNG180, a commercially available kind of natural graphite, with a thickness of 30 ∼ 80 nm were mainly exfoliated into GNPs (<10 layers) with high quality, which were in turn uniformly dispersed in the composites. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014, 131, 40565.
Spanish Influenza in Japanese Armed Forces, 1918–1920

With the recent outbreaks of avian influenza A (H5N1), the risk for the next influenza pandemic has increased. For effective countermeasures against the next pandemic, investigation of past pandemics is necessary. We selected cases diagnosed as influenza from medical records and hospitalization registries of Japanese army hospitals during 1918-1920, the Spanish influenza era, and investigated clinical features and circumstances of outbreaks. Admission lists showed a sudden increase in the number of inpatients with influenza in November 1918 and showed the effect of the first wave of this pandemic in Tokyo. The death rate was high (6%-8%) even though patients were otherwise healthy male adults.
Age-dependent prognostic value of exercise capacity and derivation of fitness-associated biologic age.

OBJECTIVE
Given the aging population and prevalence of sedentary behaviour in the USA, we investigated the impact of differences in exercise capacity associated with age on long-term outcomes. We derived fitness-associated 'biologic age' as a tool to encourage positive lifestyle changes.


METHODS
This retrospective cohort study included 57085 patients without established coronary artery disease or heart failure (median age 53 years, 49% women, 29% black) who underwent clinically-referred treadmill stress testing at the Henry Ford Health System from 1991 to 2009. Patients were followed for 10.4±5 and 5.4±4 years for all-cause mortality and myocardial infarction (MI), respectively. We calculated hazard ratios associated with exercise capacity by age deciles using Cox regression models, adjusting for demographic and haemodynamic data, medical history, and medication use. Fitness-associated 'biologic age' was derived as the chronologic age with equivalent mortality or MI risk.


RESULTS
There were 6356 deaths and 1646 MIs during follow-up. Exercise capacity declined with increasing age. Higher exercise capacity was strongly associated with greater survival, with per-MET HR ranging from 0.82 (95% CI 0.78 to 0.86) in patients under 40 years of age, to 0.88 (95% CI 0.87 to 0.90) in those over 70 years of age. Biologic age varied markedly-up to three decades-within each age decile, and was a stronger predictor of mortality (C-statistic 0.81 vs 0.77) and MI (C-statistic 0.72 vs 0.68) than chronologic age.


CONCLUSIONS
Higher exercise capacity remained a powerful predictor of survival despite lower average exercise capacity at older ages, reinforcing its importance in patients of all ages. Fitness-associated biologic age was a stronger predictor of survival than chronologic age, and may be a useful clinical tool for facilitating patient discussions regarding the impact of exercise capacity on long-term risk.
The Effect of Mulligan Mobilization Technique in Older Adults with Neck Pain: A Randomized Controlled, Double-Blind Study

Background
The purpose of this study was to examine the effect of Mulligan mobilization technique (MMT) on pain, range of motion (ROM), functional level, kinesiophobia, depression, and quality of life (QoL) in older adults with neck pain (NP).


Methods
Forty-two older adults with NP were included in the study, and they were randomly divided into two groups: traditional physiotherapy (TP) group and traditional physiotherapy-Mulligan mobilization (TPMM) group. Treatment program was scheduled for 10 sessions. Participants were assessed in terms of pain, ROM, functional level, kinesiophobia, depression, and QoL both pre- and posttreatment.


Results
Pain, ROM, functional level, kinesiophobia, depression, and QoL improved in both groups following treatment (p < 0.05). When comparing effects of these two treatment programs, it was observed that the TPMM group had a better outcome (p < 0.05) in terms of ROM, kinesiophobia, depression, and QoL.


Conclusion
In older adults with NP, MMT has been found to have significant effects on pain, ROM, functional level, kinesiophobia, depression, and QoL as long as it is performed by a specialist. "This trial is registered with NCT03507907".