Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Gait Events Detection with Inertial Measurement Units: Healthy Subjects and Moderate to Severe Impaired Patients

Background: Recently, the use of inertial measurement units (IMUs) in quantitative gait analysis has been widely developed in clinical practice. Numerous methods have been developed for the automatic detection of gait events (GEs). While many of them have achieved high levels of eﬃciency in healthy subjects, detecting GEs in highly degraded gait from moderate to severely impaired patients remains a challenge. In this paper, we aim to present a method for improving GE detection from IMU recordings in such cases. Methods: We recorded 10-meter gait IMU signals from 13 healthy subjects, 29 patients with multiple sclerosis, and 21 patients with post-stroke equino varus foot. An instrumented mat was used as the gold standard. Our method detects GEs from ﬁltered free acceleration and gyration signals. Firstly, we use autocorrelation and pattern detection techniques to identify a reference stride pattern. Next, we apply multiparametric Dynamic Time Warping to annotate this pattern from a model stride, in order to detect all GEs in the signal. Results: We analyzed 16,819 GEs recorded from healthy subjects and achieved an F1-score of 100%, with a median absolute error of 8 ms (IQR [3-13] ms). In multiple sclerosis and equino varus foot cohorts, we analyzed 6067 and 8951 GEs, respectively, with F1-scores of 99.4% and 96.3%, and median absolute errors of 18 ms (IQR [8-39] ms) and 26 ms (IQR [12-50] ms). Conclusions: Our results are consistent with the state of the art for healthy subjects and demonstrate a good accuracy in GEs detection for pathological patients. Therefore, our proposed method provides an eﬃcient way to detect GEs from IMU signals, even in degraded gaits. However, it should be evaluated in each cohort before being used to ensure its reliability.
~1400-nm continuous-wave diamond Raman laser intracavity-pumped by an InGaAs semiconductor disk laser

We present a ~1400nm-emitting diamond Raman laser intracavity-pumped by an ~1180nm semiconductor disk laser. We measured a maximum output power of 2.3 W at ~1400nm with an output coupling of 3.5%. The Raman laser was tunable from 1373 to 1415nm using a 4-mm-thick birefringent filter.
Risk Influence of Some Environmental and Behavioral Factors on Air Contamination in the Operating Room: An Experimental Study

Air contamination in operating rooms (ORs) depends on the conditions of the room and on activities therein performed. Methodologies of air quality assessment in ORs are often inadequately described in the scientific literature, and the time required for a change in status in air quality is never taken into account. The purpose of this study was to determine the influence of the state and the presence of human operators on air quality by implementing a precise measurement protocol that also took into account the time required for changes in the room to affect air pollution. As the main indicators of air pollution, bacterial load and concentration of airborne dust were measured. The results showed that: the use of surgical masks by operators in the OR did not significantly affect bacterial load within a distance of 2 m; keeping OR doors open did not induce a significant increase in bacterial load and of 5 μm particles while 10 μm particles concentration was positively affected; and air pollution measured with open doors was not significantly different from that due to the presence of two staff members, whether or not they were wearing masks. The results clarified the role of some factors on air pollution in ORs.
Integrated Campaigns: Evidence on pro-equity interventions to improve immunization coverage for zero-dose children and missed communities

What are the main barriers and facilitators to implementation? ● Major facilitators during planning and implementation include working closely with communities and key stakeholders, using existing tools and digital platforms, and ensuring a clear coordination plan. ● Major barriers include operational and logistical considerations relevant to ensuring the simultaneous delivery of multiple health services and cost.
UvA-DARE (

Funded social security programs are particularly vulnerable to economic and ﬁnancial market shocks. As a consequence of the recent crisis, a large fraction of the Dutch pension funds had to submit restoration plans for the recovery of their buffers. Such plans will have to rely primarily on a mix of reduced beneﬁt indexation and increased pension contributions. Hence, a discussion has emerged whether index-ation should be differentiated across the various groups of participants in a pension fund. We investigate this issue numerically, developing an applied many-generation small open-economy OLG model with heterogeneous agents. The pension system consists of a ﬁrst-pillar PAYG component and a second pillar with a pension fund. In our stochastic simulations, we hit the economy with a variety of unexpected demographic, economic and ﬁnancial shocks. We compare uniform indexation of pension
Syddansk Universitet Cost-effectiveness of blended vs . face-to-face cognitive behavioural therapy for severe anxiety disorders study protocol of a randomized controlled trial

Background: Anxiety disorders are among the most prevalent psychiatric conditions, and are associated with poor quality of life and substantial economic burden. Cognitive behavioural therapy is an effective treatment to reduce anxiety symptoms, but is also costly and labour intensive. Cost-effectiveness could possibly be improved by delivering cognitive behavioural therapy in a blended format, where face-to-face sessions are partially replaced by online sessions. The aim of this trial is to determine the cost-effectiveness of blended cognitive behavioural therapy for adults with anxiety disorders, i.e. panic disorder, social phobia or generalized anxiety disorder, in specialized mental health care settings compared to face-to-face cognitive behavioural therapy. In this paper, we present the study protocol. It is hypothesized that blended cognitive behavioural therapy for anxiety disorders is clinically as effective as face-to-face cognitive behavioural therapy, but that intervention costs may be reduced. We thus hypothesize that blended cognitive behavioural therapy is more cost-effective than face-to-face cognitive behavioural therapy. Methods/design: In a randomised controlled equivalence trial 156 patients will be included (n = 78 in blended cognitive behavioural therapy, n = 78 in face-to-face cognitive behavioural therapy) based on a power of 0.80, calculated by using a formula to estimate the power of a cost-effectiveness analysis: n 1⁄4 2 zaþzβ ð Þ 2 sdþ W2sd ð Þ− 2Wρsdcsdq ð Þ ð Þ WE−C ð Þ . Measurements will take place at baseline, midway treatment (7 weeks), immediately after treatment (15 weeks) and 12-month follow-up. At baseline a diagnostic interview will be administered. Primary clinical outcomes are changes in anxiety symptom severity as measured with the Beck Anxiety Inventory. An incremental costeffectiveness ratio will be calculated to obtain the costs per quality-adjusted life years (QALYs) measured by the EQ-5D (5-level version). Health-economic outcomes will be explored from a societal and health care perspective. Discussion: This trial will be one of the first to provide information on the cost-effectiveness of blended cognitive behavioural therapy for anxiety disorders in routine specialized mental health care settings, both from a societal and a health care perspective. Trial registration: Netherlands Trial Register NTR4912. Registered 13 November 2014.
Decision Layer: Enhancing Multi-model, Multi Timescale Decisions on the Fly with Online Feedback

Rogue actors employ sophisticated automation techniques to mimic human browsing/click patterns and generate invalid (i.e., fraudulent or robotic) traffic on retail marketplaces to artificially inflate their key performance metrics at the expense of their legitimate competitors. To maintain a clean and fair advertising system, it is essential to identify and mitigate ad traffic that is invalid, i.e., fraudulent or coerced or unintended, driven by bad actors and ensure that advertisers do not get charged for invalid traffic (IVT). One major challenge for advertising systems is the absence of complete ground truth fraud labels, even in limited amounts, which makes it challenging to build one single overarching model for comprehensive IVT detection. This generally results in a suite of models, each trying to identify some specific bot modus operandi. While this approach has been beneficial to offer more robust protection to advertisers by catching a variety of bots, it also piled up potentially millions of dollars of lost revenue opportunities, with each algorithm contributing incrementally to false positive detection (i.e., incorrect removal of valid traffic). Hence, we propose to build a “model over models” that learns to maintain true IVT coverage of ad fraud detection system while simultaneously lowering the cost of false positives. In this paper, we present a few variations for the new system, trained with incomplete labels that are either high quality but delayed in availability or low quality but available faster. Our proposed online algorithm combines the best of both worlds. It continuously adapts to not only reduce false positive cost by a massive 37% (owing to strong delayed labels), but also to rapidly mitigate revenue loss spikes (owing to weak fast labels) associated with occasional IVT detection system failure scenarios. To this end, we show that the online algorithm has sub-linear regret.
Acta Botanica Brasilica

The Atlantic Forest of southeastern Brazil has been considered to have the highest number of tree species per hectare in the world. Assessing the influence of climate on tropical tree species is a priority in the face of ongoing climate change, and for which dendrochronological studies have been important. We address the dendrochronological potential of Licaria bahiana Kurz (Lauraceae), an endemic species of the Atlantic forests. We studied growth ring anatomy of L. bahiana and applied dendrochronological methods to investigate how short-term variation in climate affect its radial growth. Distinct growth rings were observed in all individuals and demarcated by darker tangential fiber zones in latewood. Trees showed high climatic sensitivity (0.48) and growth synchrony (intercorrelation r = 0.69; rbar = 0.38). Radial growth was negatively influenced by high temperatures at the beginning of the current growing season (r = -0.46) and by excessive rainfall at the end of the current growing season (r = -0.29), which are periods that correspond to the phenological reproductive phases of the species. Climate anomalies during this period may alter the tradeoff between growth and reproduction, in favor of the latter.
Acta Botanica Brasilica

We experimentally evaluated how different temperatures affect germination of individual seedlings of Dipteryx alata, and estimated the impact of climate change on the species using ecological niche modeling. A total of 240 seeds were randomly distributed among three different temperature treatments (32 oC, 36 oC, and 40 oC), and monitored for 35 days. We measured seven seed traits and estimated the ecological niche of D. alata using a consensus of four methods. The treatment with the highest temperature produced smaller and lighter seedlings. The consensus of ecological niche modeling indicated that are expected to reduce the areas with climates favorable for D. alata in future scenarios. Thus, our two results (experiment and ecological niche modeling) are concordant, and both indicate the impact of global warming on germination (initial stage of the plant) and potential geographic distribution. Moreover, in geographic context, our experiment and ecological niche modeling indicated that north, northwest and central regions of the “Cerrado” are predicted to have lower morphological traits of germination and loss climate favorable area, since these regions are predicted to have higher temperatures (nearly 40 oC) in future climatic scenarios.
FORMULATION AND EVALUATION OF CURCUMIN LOADED SOLID LIPID NANOPARTICLES BY EMPLOYING CUTINA ® HR AND TWEEN 80

The aim of the present study is to formulate and evaluate solid lipid nanoparticles of Curcumin. Curcumin has many potential pharmacological effects including anti-inflammatory, antibacterial, antioxidant and anticancer activities. Curcumin has poor water solubility and oral bioavailability. Therefore, the delivery of drug molecules through the carrier systems avoid unwanted effects because of controlled biodistribution. Development of efficient drug delivery system for curcumin would be a potential approach to improve its bioavailability and clinical efficacy. To overcome these problems an attempt was made to prepare Curcumin into Solid lipid nanoparticles which has ability to improve the solubility and enhance the oral bioavailability. In the present study Curcumin loaded SLNs was prepared by Hot Homogenization method. The Cutina® HR was used as the Lipid, Soya lecithin as lipophilic surfactant, and Tween 80 as Hydrophilic surfactant in the preparation. The four prepared formulations were evaluated for various parameters like Drug content, entrapment efficiency, In Vitro drug release and the best formulation was further analysed by instrumental methods such as particle size determination, zeta potential and also for SEM analysis. Among all the Preparations, T3 formulation was best in terms of Entrapment efficiency with 85.2%, Drug release of 75.7%, in-vitro drug release of 82.6% for 24hrs, particle size of 155.9nm of and with a stability of -30.9mV. The present study conclusively demonstrated that the solubility of drug was improved by entrapment of drug into solid lipid carrier which led to prolongation of drug release.
The Economics of Faith : Using an Apocalyptic Prophecy to Elicit Religious Beliefs in the Field

We model religious faith as a “demand for beliefs,” following the logic of the Pascalian wager. We show how standard experimental interventions linking financial consequences to falsifiable religious statements can elicit and characterize beliefs. We implemented this approach with members of a group that expected the “End of the World”to occur on May 21, 2011 by varying monetary prizes payable before and after May 21st. To our knowledge, this is the first incentivized elicitation of religious beliefs ever conducted. The results suggest the existence of a demand for extreme, sincere beliefs that was unresponsive to experimental manipulations in price. JEL codes: D84, D81, Z12, N30
A Lattice-based Publish-Subscribe Communication Protocol using Accelerated Homomorphic Encryption Primitives

Key-policy attribute-based encryption scheme (KP-ABE) uses a set of attributes as public keys for encryption. It allows homomorphic evaluation of ciphertext into another ciphertext of the same message, which can be decrypted if a certain access policy based on the attributes is satisfied. A lattice-based KP-ABE scheme is reported in several works in the literature, and its software implementation is available in an open-source library called PALISADE. However, as the cryptographic primitives in KP-ABE are overly involved, non-trivial hardware acceleration is needed for its adoption in practical applications. In this work, we provide GPU-based algorithms for accelerating KP-ABE encryption and homomorphic evaluation functions seamlessly integrated into the open-source library with minor additional build changes needed to run the GPU kernels. Using GPU algorithms, we perform both homomorphic encryption and homomorphic evaluation operations 2 . 1 × and 13 . 2 × faster than the CPU implementations reported in the literature on an Intel i9, respectively. Furthermore, our implementation supports up to 128 attributes for encryption and homomorphic evaluation with fixed and changing access policies. Unlike the reported GPU-based homomorphic operations in the literature, which support only up to 32 attributes and give estimations for a higher number of attributes. We also propose a GPU-based KP-ABE scheme for publish/subscribe messaging applications, in which end-to-end security of the messages is guaranteed. Here, while the exchanged messages are encrypted with as many as 128 attributes by publishers, fewer attributes are needed for homomorphic evaluation. Our fast and memory-efficient GPU implementations of KP-ABE encryption and homomorphic evaluation operations demonstrate that the KP-ABE scheme can be used for practicable publish/subscribe messaging applications.
Q UANTIFYING VARIABLE IMPORTANCE IN CLUSTER ANALYSIS

A BSTRACT : We propose to measure the importance of variables when running a cluster analysis by measuring the similarity of a clustering using all variables with a clustering applying the same method leaving out one variable. If the resulting clustering is very similar, the left out variable does not have much impact. An alternative is to replace the variable by randomly permuted values. Beyond variable selection (on which we will not focus), variable importance measurement is useful for interpreting and understanding a clustering. Also we will use variable importance measurement to discuss whether clustering methods appropriately balance the impact of different variables in mixed type variables clustering
Solving the swing-up and balance task for the Acrobot and Pendubot with SAC

We present a solution of the swing-up and balance task for the pendubot and acrobot for the participation in the AI Olympics competition at IJCAI 2023. Our solution is based on the Soft Actor Crtic (SAC) reinforcement learning (RL) algorithm for training a policy for the swing-up and entering the region of attraction of a linear quadratic regulator(LQR) controller for stabilizing the double pendulum at the top position. Our controller achieves competitive scores in performance and robustness for both, pendubot and acrobot, problem scenarios.
Has COVID changed consumer payment behavior?

: The COVID-19 pandemic has caused large changes in consumer spending, including how people make their payments. We use data from a nationally representative survey of U.S. consumers collected before COVID in 2018 and 2019 and during COVID in 2020 to analyze changes in consumer payment behavior during the pandemic. We find that compared with their payment behavior in 2019, consumers had shifted some of their purchases from in person to online by fall 2020, significantly lowered their use of cash for purchases, and shifted their person-to-person (P2P) payments away from paper (cash and checks). Those changes are consistent with what we might expect, as many people were less able or willing to shop in person. The adoption of electronic P2P increased, especially the use of payment apps such as PayPal, Venmo, and Zelle. Consumers who worked exclusively from home during COVID made significantly higher shares of their payments online or through mobile devices and were less likely to use cash at all compared with those who worked at least partly in person, even after we control for income and education levels. In contrast, payment-behavior changes that took place from 2018 to 2019 were smaller in magnitude and largely insignificant, suggesting that COVID likely accelerated any longer-term trends. Although it is too soon to determine whether these changes will persist for the longer term, we observed them several months after the onset of the pandemic, so they certainly were not just temporary shifts.
A Robust Algebraic Phase Unwrapping Based on Spline Approximation (VLSI設計技術)

The phase unwrapping is a problem to ﬁnd, at any speciﬁed point, the value of the continuous phase function which contains valuable information in many applications. If a given data sequence of 2 -D real vectors is modeled as samples of a complex polynomial, the exact unwrapped phase can be computed through algorithms named the algebraic phase unwrapping. In this paper, to promote the understanding and extend the practicability of the algebraic phase unwrapping, we propose a widely applicable phase unwrapping technique, by combining the spline smoothing and the algebraic phase unwrapping, for a given data sequence of 2 -D noisy vectors. The spline smoothing works as an optimal preprocessing in the sense that it is the unique solution to a variational problem for minimizing the sum of “ﬁdelity” to the data and “roughness” of the curve. Fortunately, since the standard spline smoothing and its various generalizations produce always low-order piecewise real polynomials, we can compute the exact unwrapped phase for the pair of piecewise polynomials without suffering from a certain numerical instability observed typically in applications of the algebraic phase unwrapping to a complex polynomial of large degree.
Spitzer IRAC Colors of Nebulae Associated with Star-Forming Regions

Star-forming regions are often associated with nebulosity. In this study, we investigated infrared diffuse emission in Spitzer IRAC images. The infrared nebula L1527 traces outflows emanating from a low-mass protostar. The nebular color is consistent with the color of a stellar photosphere with large extinction. Nebulae around the HII region W5-East are bright in the infrared. These colors are consistent with the model color of dust containing polycyclic aromatic hydrocarbon (PAH). The strength of ultraviolet irradiation of the nebulae and the small dust fraction were deduced from the infrared colors of the nebulae. We found that the edges of the nebulae are irradiated by strong ultraviolet radiation and have abundant small dust. Dust at the surface of the molecular cloud is thought to be destroyed by ultraviolet radiation from an early-type star.
Adversaries or Cross-Organization Co-workers? Exploring the Relationship between Gig Workers and Conventional Employees

This article explores how gig workers interact with more conventional employees. Drawing on original qualitative and quantitative data from Instacart shoppers and grocery store staff, this article shows how Instacart’s algorithmic management system pushes shoppers to mistreat in-store staff. Yet for shoppers who frequently interact with staff, the author finds they develop cooperative, cross-organization co-worker relationships. These relationships grant shoppers access to resources typically reserved for staff, allowing them to navigate the algorithmic constraints that Instacart places on them. Findings show that platform companies’ use of algorithmic management tools can spill over to negatively affect the working conditions of conventional workers; but also, that gig workers can improve their own conditions by building relationships with their conventional peers.
Remote Detection of Oil Slicks at the Ocean Surface

The 2010 Deepwater Horizon (DWH) oil slick caused by the explosion of the Macondo well was the worst man-made disaster in the history of the Gulf of Mexico, and the largest marine spill in the history of the petroleum industry. We provide an overview of our efforts to monitor the extent of these slicks using automated algorithms for the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Synthetic Aperture Radar (SAR). We discuss the advantages and limitations of each of the methods in detection of oil from space, and suggest that the NIR bands may be the best option to monitor emulsified oil when using passive sensors. Additionally, we discuss current laboratory-based efforts to measure oil thickness via holographic interferometry, and propose this as an ideal technique for future remote sensing of oil.