Miracle-dz/UniFAR-FTUs huggingface dataset:
A System for Rapidly Yet Rigorously Evaluating the Quality of Randomized Controlled Trials

Abstract This tutorial describes a system for rapidly yet rigorously assessing the quality of randomized controlled trials (RCTs). The system has 7 criteria, represented by the acronym “BIS FOES. ” The BIS FOES system directs readers to assess RCTs based on the following 7 criteria: the RCT's use (or not) of effective (1) Blinding; the RCT's use (or not) of (2) Intent-to-Treat Analysis; the RCT's (3) Size and other information reflecting the effectiveness of randomization; the amount of sample lost during (4) Follow-up; the (5) Outcomes examined by the RCT (specifically, the outcome measures used by the RCT), the (6) Efects reported (ie, the statistical and clinical significance of the RCT's primary, secondary, and safety findings), and any (7) Special Considerations (ie, additional strengths, limitations, or notable features of the RCT). The first 6 criteria are of basic importance to the assessment of every RCT, whereas the Special Considerations criteria allows the system to be expanded to include virtually any other important aspect of the RCT. This tutorial explains the importance of these criteria and how to assess them. This tutorial also describes how many BIS FOES criteria can be initially assessed from the RCT Abstract while also directing readers to specific locations in the RCT article where additional important information can be found. We hope that the BIS FOES system will help healthcare trainees, but also potentially clinicians, researchers, and the general public, rapidly and thoroughly assess RCTs.
SerBERTus: A SMART Three-Headed BERT Ensemble

We examine different architectures, learning methods, and hyperparameter choices for fine-tuning the 110 million parameter BERT BASE model on three different tasks: five class sentiment analysis on Stanford Sentiment Treebank (SST) (Socher et al., 2013); binary paraphrase detection on Quora Question Pairs (QQP) 1 , and regression on Semantic Text Similarity (Agirre et al., 2013). We find that a strong SMART (Jiang et al., 2020) loss combined with a novel architecture replicating only the BERT layers closest to the task-specific heads brings the greatest improvement to performance on the three tasks without too severe an increase in model size and resource consumption. Our best model is an ensemble achieving mean performance of 78.61% on the test set.
ALPHA-STABLE P-ADIC TIME SIGNALS

The estimation of the spectral density of stable p-adic signals is already done. Such estimation is based on smoothing the periodogram by using a spectral window. The convergence rate of this estimator depends on bandwidth of spectral window (called the smoothing parameter). The aim of this work is to give a technique for selecting the optimal parameter, i.e. the parameter that achieves the estimation with the best convergence rate. For that purpose, we were inspired by the cross-validation method of finding the optimal parameter. This method minimizes the integrated square error estimate.
Impact of BERT Extensions on Cross-Domain Text Classification

In the era of Deep Learning, there is a plethora of neural language models that deal with the text classification problem reasonably well but these are almost always expensive to train from scratch. Reducing this expense is one of the many primary motivations to employ pre-trained models like BERT which essentially provide a springboard to near State-of-The-Art (SoTA) results at a fraction of the required computational costs. By leveraging the power of pre-trained language models coupled with a collection of curated fine-tuning techniques like additional cross-domain pre-training based on masked language modelling objective coupled with regularization, we extend the base-bert model to perform well on multiple downstream text classification tasks. We draw on the fine-tuning techniques discussed in Sun et al. (2019) coupled with Joshi et al. (2019) and Jiang et al. (2020) to analyze and report what works for and what hurts the performance.
CAMBRIDGE WORKING PAPERS IN ECONOMICS JANEWAY INSTITUTE WORKING PAPERS On the Origin and Persistence of Identity- Driven Choice Behavior

Recent literature shows how a priori identical individuals belonging to different social groups make different choices. This paper proposes a novel explanation for this identity-driven choice behavior. Agents choose whether to undertake a task with a probability of success driven by an ability. They have a noisy perception of this ability and observe social cues that stem from the prevalence of their subgroup among the successful individuals. Although the noise in their perception is unbiased, it has an asymmetric effect on expected utility. This makes it optimal for certain agents to bias their noisy perception with social cues, even when these cues are irrelevant in a Bayesian sense. I show the existence of a stable population equilibrium in which both task allocation and the use of social cues differ between a priori identical subgroups. Reference Details 2274 Cambridge Working Papers in Economics 2232 Janeway Institute Working Paper Series Published 15 December 2022 Revised 4 January 2023 JEL codes D81, D91, I240, Z13 Websites www.econ.cam.ac.uk/cwpe www.janeway. econ.cam.ac.uk/working-papers On the Origin and Persistence of Identity-Driven Choice
Patenting with the Stars: Where are Technology Leaders Leading the Labor Market?∗

This paper considers the potential labor market consequences of the innovative activity of the largest U.S. firms (‘superstars’) over eight decades. Superstars generate a large share of innovations, and their innovations are technologically distinct and differentially impactful relative to those of other firms. Leveraging a novel patent-level measure of innovations’ labor-augmenting and labor-automating potential, we show that superstar innovations are more likely to augment labor compared to innovations pioneered by other firms, especially in recent decades. Workers of different skill types do not benefit equally, however: top firms’ differential labor augmentation is largely limited to highpaid occupations. This suggests modern-day superstar firms’ innovations contribute to the diverging labor market fortunes of highand low-skilled workers. We highlight that the social value of augmenting innovations as measured by novelty and intellectual impact has risen while their market value has fallen—particularly for innovations which augment middle-skilled workers—suggesting that labor-augmenting innovations may be under-supplied by the market.
LAN Based GIS Optimization for Coverage in Wireless Networks

Machine learning is a branch of artificial intelligence based on the idea that systems can learn to identify patterns and make decisions with a minimum of human intervention. In this Paper, demonstration learning will be used, using neural networks in a prototype of a drone built to perform trajectories in controlled environments. To accelerate the training convergence process, a new training data selection approach has been introduced, which picks data from the experience pool based on priority instead of randomness. An autonomous maneuver strategy for dual-UAV olive formation air warfare is provided, which makes use of UAV capabilities such as obstacle avoidance, formation, and confrontation to maximize the effectiveness of the attack.
The Viscoplastic Behavior of Natural Hydrate‐Bearing Sandy‐Silts Under Uniaxial Strain Compression (K0 Loading)

The in‐situ stress state and geomechanical properties of hydrate‐bearing sediments impact hydrate formation and gas production strategies. We explore the uniaxial strain compression and stress evolution of natural hydrate‐bearing sandy‐silts from Green Canyon Block 955 in the deep‐water Gulf of Mexico. We performed constant rate of strain uniaxial strain experiments, interrupted by periods where we held the axial stress constant, to explore the vertical deformation and the evolution of the ratio of lateral to axial effective stress (K0) with time. The hydrate‐bearing sandy‐silt is stiffer and has a larger K0 than the equivalent hydrate‐free sediment upon loading. During stress holds, the void ratio decreases sigmoidally with the log of time, and K0 converges to isotropic conditions. We interpret that during loading, the hydrate bears the load and deforms. With time, the hydrate redistributes the load and K0 increases. We used a viscoelastic model to describe the behavior. The model accurately captures deformation and K0 trends but does not reproduce all the complex interactions of the hydrate with the porous skeleton. We anticipate that viscous effects within hydrate sediments will impact reservoir compression and stresses during production (hours to days), result in isotropic stress state over geological timescales, and explain the creeping movement in submarine landslides.
Tree-dependent extreme values: the exponential case

The length of the main channel in a river network is viewed as an extreme value statistic L on a randomly weighted binary rooted tree having M sources. Questions of concern for hydrologic applications are formulated as the construction of an extreme value theory for a dependence which poses an interesting contrast to the classical independent theory. Equivalently, the distribution of the extinction time for a binary branching process given a large number of progeny is sought. Our main result is that in the case of exponentially weighted trees, the conditional distribution of n–1/2 L given M = n is asymptotically distributed as the maximum of a Brownian excursion. When taken with an earlier result of Kolchin (1978), this makes the maximum of the Brownian excursion a tree-dependent extreme value distribution whose domain of attraction includes both the exponentially distributed and almost surely constant weights. Moment computations are given for the Brownian excursion which are of independent interest.
Latency and Reliability Analysis of a 5G-Enabled Internet of Musical Things System

The availability of high-performance embedded audio systems, along with high-bandwidth and low-latency connectivity options provided by 5G networks, is enabling the Internet of Musical Things (IoMusT) paradigm. A central component of this paradigm is represented by networked music performances (NMPs), where geographically displaced musicians play together over the network in real time. However, to date, IoMusT deployments over 5G networks remain scarce, and very limited statistical results are available on the actual latency and reliability of 5G networks for IoMusT and NMP scenarios. In this article, we present a private 5G IoMusT deployment and analyze its performance when supporting NMPs. Our IoMusT system is composed of up to four nodes and includes different background traffic conditions. We focused on the assessment of the sole wireless link, as the measurements can be easily transferred to a realistic NMP architecture involving a wide area network (WAN) by compounding them with those of the WAN. Our results show that latency increases with the number of nodes and with the presence of background traffic, whereas the reliability did not vary with the complexity of the conditions. For all tested scenarios, the average measured latency was below 24 ms (including a jitter buffer of 10.66 ms), whereas packet losses occurred with a probability of less than 0.01. However, irregular spikes were found for all latency and reliability metrics, which can significantly reduce the quality of service perceived by the users of NMP applications. Finally, packet loss and latency resulted to be uncorrelated, which suggests that they have different root causes.
COVID-19 and Psychiatric Admissions: A Comparative Study of Pre-pandemic and Post-pandemic Psychosis Admissions in a South Florida Emergency Department

We noticed a subjective increase in psychosis admissions within our emergency department (ED) with the onset of the coronavirus disease 2019 (COVID-19) pandemic. This study aimed to identify trends concerning admissions due to psychosis in the ED before and after the beginning of the COVID-19 pandemic. We analyzed 508 psychiatric admissions through the ED from October 2019 to October 2020, of which 367 cases of psychosis were identified. Statistical analysis was performed using T-tests and Pearson's correlation coefficient. T-testing showed mean psychosis admissions during the pandemic (March 2020 to July 2020) to be greater than admissions occurring during the pre-pandemic period (October 2019 to February 2020) (p = 0.04). Pearson's correlation coefficient identified the relationships between COVID-19 admissions and psychosis admissions during this time as positive (r = 0.5) but did not reach statistical significance (p = 0.06). Therefore, within our time frame, we did see a noted increase in psychosis by 22.9% during the pandemic compared to pre-pandemic times. Current research remains conflicted concerning psychiatric ED admissions during COVID-19, with some stating an increase and others finding a decrease. Our data showed a significant statistical increase in the mean number of psychosis cases when comparing pre-pandemic and pandemic admissions. These findings help add pertinent data to understand how psychosis admissions trended before and during the beginning of the COVID-19 pandemic, specifically in South Miami, Florida. It also provides a foundation for future studies by providing data points concerning mental illness within the vulnerable population of patients served in our community.
The Distribution of Points on Hyperelliptic Curves Over F_q of Genus g in Finite Extensions of F_q

For a fixed q and any n ≥ 1, the number of F_{q^n} -points on a hyperelliptic curve over F_q of genus g can be written as a q^n +1+S, where S is a certain character sum. We show that S behaves as a sum of q^n + 1 independent random variables as g → ∞, with values depending on the parity of n. We get our result by generalizing the result of Kurlberg and Rudnick [1] for the distribution of the affine F_q-points to any finite extension F_{q^n} of F_q, and using the techniques of Bucur, David, Feigon, and Lalin [2] to also consider the points at infinity over the full space of of hyperelliptic curves of genus g.
The Role of Teachers in Values Education in Pakistan: A Case of Early Childhood Education and Development from Pakistan.

The teachers in early childhood education and preschool have a significant influence on curriculum and daily practices in the class, therefore, have a dominant influence on the implementation of values education. Deeming values as a social construct, this small-scale qualitative case study was carried out to explore the priority values of early childhood education teachers and their ways of teaching values in a school in northern Pakistan. Interviews and classroom observations were conducted to gather in-depth data from the school leadership and the teachers. Teachers were found primarily focused on the inculcation of societal values, behaviors and life skills needed for children to successfully adjust to society. In this school, teachers are playing a dominant role in the values education of the young children through role modeling, daily practices and routines and interactions with the parents. School leadership is focused on values education. While doing so, they are aspiring for other stakeholders to accept the upper hand of the school values and expect them to facilitate the inculcation of these values in young children. The school and teachers are facing the problem of the reluctance of parents to take full responsibility for the values education of their children. Introduction Values are the commonly recognized and approved principles, convections, and standards of society that are transcending specific situations. Therefore, “values appear to be an allembracing element of human life; that is, values are connected both to the human mind and action, and they emerge at the levels of individuals, cultural groups, and societies” (Johansson, Emilson, & Puroila, 2017, p.14). These principles are the foundation of the social structure (Dasari, 2017) to cultivate and ensure harmony, peace, and prosperity in the social order. Hence, values are the “determiners of how people will live in harmony and peace without hurting one another and become virtuous individuals within the community” (Khathi, Govender, & Ajani, 2021, p.404). Human societies are steadily transferring these principles, convections, and standards to the next generations to ensure a constructive, peaceful, and prosperous society. This transformation of values to the young generation is taking place at multiple stages of the family, school, and broader society. School is considered a value-laden context where implicit and explicit values education is imparted to young children (Ulavere & Tammik (2017). The schools which are explicitly teaching values education have structured a concrete plan, and overtly included it into their school curriculum whereas, the schools which are following the implicit route, are embedding values education in their daily practices and ethos but it is not included in their formal curriculum (Thornberg, 2016). In ABIDA BEGUM
U-UV Coding for Bit-Interleaved Coded Modulation

U-UV codes were recently proposed as a competent short-to-medium length coding scheme. With well designed component codes, U-UV codes can outperform similar rate cyclic redundancy check (CRC)-polar codes with the successive cancellation (SC) and the SC list (SCL) decoding. In order to improve the coded transmission spectral efficiency, this paper proposes the bit-interleaved coded modulation (BICM) scheme with U-UV codes as the channel codes. A bit interleaver structure is proposed to facilitate the component code rate allocation based on the polarized subchannel capacities. Under the BICM paradigm, the component code rates can be allocated by first estimating the modulation subchannel capacities, then adjusting based on the finite length rates and the equal error probability rule. Theoretical performance bounds and their approximations on decoding error rates are further analyzed. It provides the theoretical benchmarks for our simulations and guides the optimized design of the coded modulation scheme. Finally, simulation results of the U-UV coded BICM scheme are provided to demonstrate its error-correction competency. It can outperform the relevant bit-interleaved polar coded modulation (BIPCM) scheme.
A Dissection of the Inter‐Model Spread of the Aerosol Direct Radiative Effect in CMIP6 Models

The all‐sky Aerosol Direct Radiative Effect (ADRE) varies considerably among global climate models (GCMs), which results from differences in aerosol and atmospheric states and ADRE sensitivity to aerosol‐related radiative processes. This study uses a regression method to analyze the inter‐model spread of ADRE among the GCMs of the Sixth Coupled Model Intercomparison Projects (CMIP6). The key state variables examined include scattering and absorbing aerosol optical depth, surface albedo, and shortwave cloud radiative effect. We find that differences in state variables and radiative sensitivity explain 67% and 17%, respectively, of the global ADRE anomaly. The ADRE anomaly in different models is dominated by different factors, which sometimes leads to compensating effects. For the global mean ADRE anomaly, aerosol optical depth differences dominate in CNRM‐ESM2‐1 and GFDL‐ESM4 models, while ADRE sensitivity variations to aerosol‐only scattering effect dominate in HadGEM3‐GC31‐LL, MPI‐ESM‐1‐2‐HAM, and MRI‐ESM2‐0 models.
Bank Risk-Taking, Credit Allocation, and Monetary Policy Transmission: Evidence from China

Loan-level evidence shows that China’s implementation of Basel III in 2013 has reduced bank risk-taking both on average and conditional on monetary policy easing. However, banks reduce risk-taking by increasing lending to ostensibly lowrisk but inefficient state-owned enterprises (SOEs), leading to credit misallocation. We establish these empirical results using a difference-in-difference identification, exploiting cross-sectional differences in lending behaviors between high-risk and low-risk bank branches before and after the new regulations. To understand how changes in capital regulations may affect monetary policy transmission, we construct a two-sector general equilibrium model featuring bank portfolio choices and capital adequacy ratio (CAR) constraints. The model highlights a risk-weighting channel, through which expansionary monetary policy shifts bank lending toward inefficient SOEs, consistent with empirical evidence. Under government guarantees of SOE loans, such a shift in lending reduces the portfolio risks for individual lenders, but it also reduces aggregate productivity and raises the average risk of bank insolvency. Date: May 19, 2022.
Estimation of Regression Discontinuity and Kink Designs with Multiple Running Variables

In regression discontinuity and regression kink designs with multiple running variables (respectively, MRD and MRK), units are assigned different treatments based on whether their values on several observed running variables exceed known thresholds. In such designs, applied work commonly analyzes each running variable separately: for example, when financial aid eligibility depends on GPA and family income, researchers separately consider the sample of students with low enough family income to estimate the effect at the GPA threshold, and the sample of students with high enough GPA to estimate the effect at the income threshold. In this paper, I propose a new estimator for MRD and MRK designs using thin plate splines that improves upon the applied practice in two ways. First, the estimator provides efficiency gains by using the entire sample, and second, it may be used to estimate the conditional average treatment effect at every point on the boundary separating treated and untreated units. I show consistency of my estimator and construct asymptotically valid confidence intervals (CIs), before presenting simulations results showing that the estimator and its CIs perform well in finite samples. Finally, I demonstrate the performance of my estimator with two empirical applications: Londoño-Vélez, Rodríguez, and Sánchez (2020) on the effect of financial aid on college enrollment, and Keele and Titiunik (2015) on the effect of political ads on election turnout. R code for estimation and inference will soon be available. I thank Alberto Abadie, Josh Angrist, David Autor, David Card, Dave Donaldson, Ismaël Castillo, Matias Cattaneo, EunYi Chung, Jonathan Cohen, Amy Finkelstein, Florian Gunsilius, Jetson Leder-Luis, Juliana Londoño-Vélez, Richard Nickl, Parag Pathak, Rahul Singh, and all participants of MIT’s labor lunch for their comments and suggestions. Titles of previous versions of this paper include "Regression Discontinuity Designs with Multiple Assignment Variables", and "Regression Discontinuity Designs with Multiple Assignment Variables". All mistakes are my own.
Global stabilization of a coupled system of two generalized Korteweg-de Vries type equations posed on a finite domain

The purpose of this work is to study the internal stabilization of a coupled system of two generalized Korteweg-de Vries equations under the effect of a localized damping term. The exponential stability, as well as, the global existence of weak solutions are investigated when the exponent in the nonlinear term ranges over the interval $[1, 4)$. To obtain the decay we use multiplier techniques combined with compactness arguments and reduce the problem to prove a unique continuation property for weak solutions. Here, the unique continuation is obtained via the usual Carleman estimate.