LLukas22/scidocs huggingface dataset:
Inefficient Hiring in Entry-Level Labor Markets

When a firm hires a novice worker, it obtains both labor services and information about the worker’s productivity. The firm must pay a sunk cost to hire the novice, but the information generated has option value: novices found to have high productivity can be rehired in subsequent periods. If competing firms also observe the novice’s productivity, however, the option value of hiring accrues to the worker, not the employer. Firms will accordingly under-invest in discovering novice talent unless they can claim the benefit, for example, by workers buying their entry-level jobs or signing contracts transferring the option value to the firm. I formalize this intuition in a model of the labor market in which positive hiring costs and publicly observable output lead to ineffi ciently low novice hiring. I test the model’s relevance in an online labor market by hiring 952 workers at random from an applicant pool of 3,767 for a 10-hour data entry job. In this market, worker performance is publicly observable. Consistent with the model’s prediction, novice workers hired at random obtain significantly more employment and have higher earnings than the control group, following the initial hiring spell. A second treatment confirms that this causal effect is likely explained by information revelation rather than skills acquisition. Providing the market with more detailed information about the performance of a subset of the randomly-hired workers raised earnings of high-productivity workers and decreased earnings of low-productivity workers. Due to its scale, the experiment significantly increased the supply of workers recognized as highability in the market. This outward supply shift raised subsequent total employment and decreased average wages in occupations affected by the experiment (relative to non-treated occupations), implying that it also increased the sum of worker and employer surplus. Under plausible assumptions, this additional total surplus exceeds the social cost of the experiment. ∗I would especially like to thank my advisors, David Autor, Esther Duflo, and Daron Acemoglu. I would also like to thank Jason Abaluck, Leila Agha, Josh Angrist, Bob Gibbons, Michael Greenstone, Jon Gruber, Daniel Keniston, Danielle Li, Christopher Palmer, Iuliana Pascu, Jim Poterba, David Powell, Michael Powell, Simone Schaner, Joe Shapiro, Pian Shu, Jean Tirole, Juuso Toikka, Sarah Turner, Heidi Williams and participants at MIT’s labor and applied micro lunches for their many helpful comments and suggestions. I am grateful to Anand Hattiangi, Dmitry Diskin, and the oDesk Corporation for help understanding and accessing the oDesk data. Financial support from the George and Obie Shultz Fund, David Autor, and Esther Duflo is gratefully acknowledged.
Global Multi-armed Bandits with Hölder Continuity

Standard Multi-Armed Bandit (MAB) problems assume that the arms are independent. However, in many application scenarios, the information obtained by playing an arm provides information about the remainder of the arms. Hence, in such applications, this informativeness can and should be exploited to enable faster convergence to the optimal solution. In this paper, formalize a new class of multi-armed bandit methods, Global Multi-armed Bandit (GMAB), in which arms are globally informative through a global parameter, i.e., choosing an arm reveals information about all the arms. We propose a greedy policy for the GMAB which always selects the arm with the highest estimated expected reward, and prove that it achieves bounded parameter-dependent regret. Hence, this policy selects suboptimal arms only finitely many times, and after a finite number of initial time steps, the optimal arm is selected in all of the remaining time steps with probability one. In addition, we also study how the informativeness of the arms about each other’s rewards affects the speed of learning. Specifically, we prove that the parameter-free (worst-case) regret is sublinear in time, and decreases with the informativeness of the arms. We also prove a sublinear in time Bayesian risk bound for the GMAB which reduces to the well-known Bayesian risk bound for linearly parameterized bandits when the arms are fully informative. GMABs have applications ranging from drug dosage control to dynamic pricing. Appearing in Proceedings of the 18 International Conference on Artificial Intelligence and Statistics (AISTATS) 2015, San Diego, CA, USA. JMLR: W&CP volume 38. Copyright 2015 by the authors.
A new rapid landmark-based regional MRI segmentation method of the brain

BACKGROUND
Neurodegenerative and cerebrovascular diseases show a distinct distribution of regional atrophy and subcortical lesions.


OBJECTIVE
To develop an easily applicable landmark-based method for segmentation of the brain into the four cerebral lobes from MRI images.


METHOD
The segmentation method relies on a combination of anatomical landmarks and geometrical definitions. It is applied on the surface reconstruction of the MRI volume. The internal borders between the lobes are defined on the axial slices of the brain. The reliability of this method was determined from MRI scans of 10 subjects. To illustrate the use of the method, it was applied to MRI scans of an independent group of 10 healthy elderly subjects and 10 patients with vascular dementia to determine the regional distribution of white matter hyperintensities (WMH).


RESULTS
The intra-rater relative error (and intra-class correlation coefficient) of the lobe segmentation ranged from 1.6% to 6.9% (from 0.91 to 0.99). The inter-rater relative error (and intra-class correlation coefficient) ranged from 1.4% to 5.2% (from 0.96 to 0.99). Density of WMH was significantly higher in all four lobes in VD patients compared to controls (p<0.05). Within each group, WMH density was significantly higher in frontal and parietal than in temporal and occipital lobes (p<0.05).


CONCLUSION
This landmark based method can accommodate age and disease-related changes in brain morphology. It may be particularly useful for the study of neurodegenerative and cerebrovascular disease and for the validation of template-based automated techniques.
On the algebraic structure of declarative programming languages

We develop an algebraic framework, Logic Programming Doctrines, for the syntax, proof theory, operational semantics and model theory of Horn Clause logic programming based on indexed premonoidal categories. Our aim is to provide a uniform framework for logic programming and its extensions capable of incorporating constraints, abstract data types, features imported from other programming language paradigms and a mathematical description of the state space in a declarative manner. We define a new way to embed information about data into logic programming derivations by building a sketch-like description of data structures directly into an indexed category of proofs. We give an algebraic axiomatization of bottom-up semantics in this general setting, describing categorical models as fixed points of a continuous operator. © 2009 Elsevier B.V. All rights reserved.
Design of anthropomorphic 4-DOF tactile interaction manipulator with passive joints

In this paper, we describe the design method of an anthropomorphic 4-DOF tactile interaction manipulator with mechanically passive joints allowing robots to accomplish high performance force-following and tactile-based contact state recognition despite physical interference and contact with humans occurring at links and at joints. The shape and appearance of this manipulator was based on statistical data on the Japanese male physique to allow for human-like contact interaction recognition. Joint are passively compliant, consisting of a mechanical leaf spring and rotary damper giving the manipulator high passivity. Cylindrical or spherical surfaces of the body including the elbow and wrist are overlaid with distributed tactile sensors acquiring accurate contact information. Evaluation experiments indicate that the manipulator provides high performance of force-following and tactile stimulation measurement during physical interference and contact with humans and confirmed its effectiveness in improving human/robot symbiosis.
The pulse of citizenship: reflections on Griffith Taylor and ‘nation‐planning‘

Abstract This exercise in a type of applied historiography begins by annotating aspects of reform in Western education from the 1880s to the 1930s, an interval which exhibits the responses of ‘new’ subjects to political and social demands for improved civics education, and encompasses the inauguration of a recognisably ‘academic’ geography in Australia. Designedly, since the nominated period also incorporates the early life and career of pioneering geographer Griffith Taylor, the discussion probes beneath the strata of obfuscatory generalisation to relate one individual's engagement with the vortex of change. More specifically, it extracts a few lessons from Taylor's approach to ‘Nation‐Planning’ to suggest an appropriate orientation to current reformism in Australian education. It is argued that, while this trend questions the civic utility of established disciplines, it has been badly served by a disturbing ignorance of the social and intellectual heritage of the subjects under challenge.
Fog-Assisted wIoT: A Smart Fog Gateway for End-to-End Analytics in Wearable Internet of Things

Today, wearable internet-of-things (wIoT) devices continuously flood the cloud data centers at an enormous rate. This increases a demand to deploy an edge infrastructure for computing, intelligence, and storage close to the users. The emerging paradigm of fog computing could play an important role to make wIoT more efficient and affordable. Fog computing is known as the cloud on the ground. This paper presents an end-to-end architecture that performs data conditioning and intelligent filtering for generating smart analytics from wearable data. In wIoT, wearable sensor devices serve on one end while the cloud backend offers services on the other end. We developed a prototype of smart fog gateway (a middle layer) using Intel Edison and Raspberry Pi. We discussed the role of the smart fog gateway in orchestrating the process of data conditioning, intelligent filtering, smart analytics, and selective transfer to the cloud for long-term storage and temporal variability monitoring. We benchmarked the performance of developed prototypes on real-world data from smart e-textile gloves. Results demonstrated the usability and potential of proposed architecture for converting the real-world data into useful analytics while making use of knowledge-based models. In this way, the smart fog gateway enhances the end-to-end interaction between wearables (sensor devices) and the cloud.
Development of a dynamic traffic assignment system for short-term planning applications

Evaluation of Intelligent Transportation Systems (ITS) at the planning level, as well as various short-term planning projects, require the use of appropriate tools that can capture the dynamic and stochastic interactions between demand and supply. The objective of this thesis is to develop a methodological framework for such applications and implement it in the context of an existing dynamic traffic assignment system, DynaMIT. The methodological framework captures the day-to-day evolution of traffic. Furthermore, it models traveler behavior and network performance, in response to special events and situations such as incidents, weather emergencies, sport events etc. The new planning tool DynaMIT-P, consists of a supply (network performance) simulator, a demand simulator and algorithms that capture their interactions. The supply simulator captures traffic dynamics in terms of evolution and dissipation of queues, spill-backs etc. The demand simulator estimates OD flows that best match current measurements of them in the network, and models travel behavior in terms of route choice, departure time choice and response to information. DynaMIT-P is particularly suited to evaluate Advanced Traffic Management Systems (ATMS) and Advanced Traveler Information Systems (ATIS) at various levels of sophistication. The results of a case study, focusing on the evaluation of alternative designs of Variable Message Signs (VMS) using a network in Irvine, California, illustrate the functionality and potential of the system. Thesis Supervisor: Moshe Ben-Akiva Title: Edmund K. Turner Professor of Civil and Environmental Engineering Thesis Supervisor: Haris N. Koutsopoulos Title: Volpe National Transportation Center
GANerated Hands for Real-Time 3 D Hand Tracking from Monocular RGB – Supplementary Document –

Network Design: The architecture of GeoConGAN is based on the CycleGAN [13], i.e. we train two conditional generator and two discriminator networks for synthetic and real images, respectively. Recently, also methods using only one generator and discriminator for enrichment of synthetic images from unpaired data have been proposed. Shrivastava et al. [9] and Liu et al. [5] both employ an L1 loss between the conditional synthetic input and the generated output (in addition to the common discriminator loss) due to the lack of image pairs. This loss forces the generated image to be similar to the synthetic image in all aspects, i.e. it might hinder the generator in producing realistic outputs if the synthetic data is not already close. Instead, we decided to use the combination of cycle-consistency and geometric consistency loss to enable the generator networks to move farther from the synthetic data thus approaching the distribution of real world data more closely while preserving the pose of the hand. Our GeoConGAN contains ResNet generator and Least Squares PatchGAN discriminator networks. Training Details: We train GeoConGAN in Tensorflow [1] for 20,000 iterations with a batch size of 8. We initialize the Adam optimizer [4] with a learning rate of 0.0002, β1 = 0.5, and β2 = 0.999.
Validation of the spanish version of the multiple sclerosis international quality of life (musiqol) questionnaire

BACKGROUND
The Multiple Sclerosis International Quality Of Life (MusiQoL) questionnaire, a 31-item, multidimensional, self-administrated questionnaire that is available in 14 languages including Spanish, has been validated using a large international sample. We investigated the validity and reliability of the Spanish version of MusiQoL in Spain.


METHODS
Consecutive patients with different types and severities of multiple sclerosis (MS) were recruited from 22 centres across Spain. All patients completed the MusiQoL questionnaire, the 36-Item Short Form (SF-36) health survey, and a symptoms checklist at baseline and 21 days later. External validity, internal consistency, reliability and reproducibility were tested.


RESULTS
A total of 224 Spanish patients were evaluated. Dimensions of MusiQoL generally demonstrated a high internal consistency (Cronbach's alpha: 0.70-0.92 for all but two MusiQoL domain scores). External validity testing revealed that the MusiQoL index score correlated significantly with all SF-36 dimension scores (Pearson's correlation: 0.46-0.76), reproducibility was satisfactory (intraclass correlation coefficient: 0.60-0.91), acceptability was high, and the time taken to complete the 31-item questionnaire was reasonable (mean [standard deviation]: 9.8 [11.8] minutes).


CONCLUSIONS
The Spanish version of the MusiQoL questionnaire appears to be a valid and reliable instrument for measuring quality of life in patients with MS in Spain and constitutes a useful instrument to measure health-related quality of life in the clinical setting.
Fast Boundary Detection: A Generalization and a New Algorithm

We study class of fast algorithms that extract object boundaries from digitized images. A set of orthogonal functions related to distinctive image features is presented, which allows efficient extraction of such boundary elements. The properties of these functions are. used to define new criteria for edge detection and a sequential algorithm is presented. Results indicate considerable improvements over, existing techniques, with a very moderate increase of computational cost.
Cannabis for dyskinesia in Parkinson disease: a randomized double-blind crossover study.

BACKGROUND
The long-term treatment of Parkinson disease (PD) may be complicated by the development of levodopa-induced dyskinesia. Clinical and animal model data support the view that modulation of cannabinoid function may exert an antidyskinetic effect. The authors conducted a randomized, double-blind, placebo-controlled crossover trial to examine the hypothesis that cannabis may have a beneficial effect on dyskinesia in PD.


METHODS
A 4-week dose escalation study was performed to assess the safety and tolerability of cannabis in six PD patients with levodopa-induced dyskinesia. Then a randomized placebo-controlled crossover study (RCT) was performed, in which 19 PD patients were randomized to receive oral cannabis extract followed by placebo or vice versa. Each treatment phase lasted for 4 weeks with an intervening 2-week washout phase. The primary outcome measure was a change in Unified Parkinson's Disease Rating Scale (UPDRS) (items 32 to 34) dyskinesia score. Secondary outcome measures included the Rush scale, Bain scale, tablet arm drawing task, and total UPDRS score following a levodopa challenge, as well as patient-completed measures of a dyskinesia activities of daily living (ADL) scale, the PDQ-39, on-off diaries, and a range of category rating scales.


RESULTS
Seventeen patients completed the RCT. Cannabis was well tolerated, and had no pro- or antiparkinsonian action. There was no evidence for a treatment effect on levodopa-induced dyskinesia as assessed by the UPDRS, or any of the secondary outcome measures.


CONCLUSIONS
Orally administered cannabis extract resulted in no objective or subjective improvement in dyskinesias or parkinsonism.
Creating a low-cost autonomous vehicle

Autonomous vehicles are equipped with a variety of instrumentation and controls depending upon the mission of the target vehicle. One of the biggest challenges in developing low risk autonomous vehicles is keeping the cost down. Leveraging from low cost instrumentation developed for high volume consumer applications, inexpensive microcontrollers, ultrasonic sensors and a global positioning systems result in a low-cost autonomous vehicle that will navigate to a desired location with obstacle avoidance. This paper describes the design of a low budget autonomous vehicle using a modified radio control car chassis equipped with a GPS and ultrasonic sensors to navigate to a predetermined geographical location with obstacle avoidance. The focus of the project was to determine how much capability could be achieved on a minimal budget. A budget shows that high performance can be readily achieved using low cost processors and commercially available instrumentation. Since the system is battery operated, attention is given to power consumption.
Waiting times in polling systems with various service disciplines

We consider a polling system of N queues Q1, . . . , QN , cyclically visited by a single server. Customers arrive at these queues according to independent Poisson processes, requiring generally distributed service times. When the server visits Qi, i = 1, . . . , N , it serves a number of customers according to a certain visit discipline. This discipline is assumed to belong to the class of branching-type disciplines, which includes gated and exhaustive service. The special feature of our study is that, within each queue, we do not restrict ourselves to service in order of arrival (FCFS); we are interested in the effect of different service disciplines, like Last-ComeFirst-Served, Processor Sharing, Random Order of Service, and Shortest Job First. After a discussion of the joint distribution of the numbers of customers at each queue at visit epochs of the server to a particular queue, we determine the Laplace-Stieltjes transform of the cycle-time distribution, viz., the time between two successive visits of the server to, say, Q1. This yields the transform of the joint distribution of past and residual cycle time, w.r.t. the arrival of a tagged customer at Q1. Subsequently concentrating on the case of gated service at Q1, we use that cycle-time result to determine the (Laplace-Stieltjes transform of the) waiting-time distribution at Q1. Next to locally gated visit disciplines, we also consider the globally gated discipline. Again, we consider various non-FCFS service disciplines at the queues, and we determine the (LaplaceStieltjes transform of the) waiting-time distribution at an arbitrary queue.
Content-aware adaptation scheme for QoE optimized dash applications

The paper presents novel content-aware adaptation schemes for QoE optimized HTTP-based adaptive video streaming services. In recent years, content type has been investigated and proofed to have a deep influence on user's acceptable quality of experience (QoE). However, most of the existing HTTP-based adaptive video strategies only conduct bitrate switching according to network resources without a consideration of video content types. This may cause a non-optimal network resource allocation which may not achieve the optimized QoE for delivered video streaming services. In this paper, we proposed two content-aware adaptation schemes, named as Content-aware Probe and Adapt (C-PANDA) and Content-aware Dynamic Programming (C-DP), which are able to decide the video bitrate for the next video segment, based on not only the available bandwidth, the existing buffer capacity, but also the video content type. We implemented both content-aware adaptation algorithms in player prototypes based on libdash 3.0 library. Preliminary results show that content-aware adaptation schemes achieve better QoE when compared with conventional PANDA scheme. The proposed schemes are able to optimize QoE according to contents. They can achieve higher than acceptable QoE for most attractive contents such as those with high motion intensity to improve user experience for the most interesting scenes; select same video representations for segments belonging to a scene to avoid quality oscillation; and reserve buffer resource during low motion scenes to avoid stalling for the following high motion scenes. The work will be helpful in designing QoE-aware DASH schemes in the future.