Miracle-dz/UniFAR-FTUs huggingface dataset:
Archaeology of Death

List of contributors Preface 1. Approaches to the archaeology of death Robert Chapman and Klavs Randsborg 2. The search for rank in prehistoric burials James A. Brown 3. Social configurations and the archaeological study of mortuary practices: a case study John O'Shea 4. One-dimensional archaeology and multi-dimensional people: spatial organisation and mortuary analysis Lynne Goldstein 5. The emergence of formal disposal areas and the 'problem' of megalithic tombs in prehistoric Europe Robert Chapman 6. Dialogues with death Ian Kinnes 7. 'Various styles of urn' - cemeteries and settlement in southern England Richard Bradley 8. Burial, succession and early state formation in Denmark Klavs Randsborg 9. Mortuary practices, palaeodemography and palaeopathology: a case study from the Koster site (Illinois) Jane E. Buikstra 10. Mortality, age structure and status in the interpretation of stress indicators in prehistoric skeletons Della C. Cook Bibliography Index.
The permafrost

Permafrost is present on the Earth's surface, particularly in the Northern Hemisphere. Its thickness and continuity depend on latitude and altitude. There are two main categories of permafrost: a thick, continuous permafrost that occupies the large areas of the continental shelves of Alaska, Canada and Siberia; and a thinner, often discontinuous or even sporadic permafrost, which concerns mountain ranges, particularly the alpine ranges. In these, rocky glaciers constitute a remarkable form, whose genesis and behaviour are the subject of special studies, different from those traditionally carried out on "real" glaciers. This article also discusses the risks associated with mountain permafrost in the context of climate change.
Standardised Uptake Value in Organ Confined Prostate Cancer in 68-Ga- Prostate-Specific Membrane Antigen Positron Emission Tomography-Computed Tomography Scan and its Correlation with Prostate Specific Antigen Level and Gleason Score

Introduction: A positron emission tomography (PET) scan and a computed tomography (CT) scan are an integral part of oncological imaging and other modalities such as magnetic resonance imaging, CT or bone scintigraphy have some limitations in staging the workup of prostate carcinoma. Combined with tissue-specific markers like prostate-specific membrane antigen (PSMA), positron emitter-based functional imaging results have improved. Our study aimed to determine the Standardised Uptake Value (SUVmax) in prostate adenocarcinoma that is confined to the organ in Ga-68-PSMA PET-CT scans and how it correlates with prostate-specific antigen (PSA) levels and Gleason score (GS). Materials and Methods: This cross-sectional study was conducted at Sindh Institute of Urology and Transplantation (SIUT), Karachi, and includes subjects referred for a Ga68-PSMA PET-CT scan from September 2017 to January 2022. Histopathologic-proven adenocarcinoma prostate patients with organ-confined disease and PSA levels obtained within 6 weeks before the PSMA-PET-CT scan were included in the study. PET-CT images were semi-quantitatively analysed by measuring SUVmax and the result was interpreted using statistical software SPSS version 22.0. Results: A total of 154 patients were analysed. The mean age of patients was 66.57 ± 8.86 years. The GS of all patients ranges from 6 to 10. The mean and median PSA levels were 32.33 ng/mL (range: 0.004–306.00) and 14.20 ng/mL, respectively. The mean SUVmax of all prostatic lesions was 14.67 ± 12.58 and the median value was 10.76. SUVmax was higher in patients with a PSA level of more than ten than those with a <10. The correlation of SUVmax with PSA and GS showed a significant correlation. Conclusion: The SUVmax of organ-confined prostate cancer correlates well with PSA level and GS Median SUVmax and PSA directly relate to GS.
Revisiting Machine Learning Approaches for Short- and Longwave Radiation Inference in Weather and Climate Models, Part I: Offline Performance

As climate modellers prepare their code for kilometre-scale global simulations, the computationally demanding radiative transfer parameterization is a prime candidate for machine learning (ML) emulation. Because of the computational demands, many weather centres use a reduced spatial grid and reduced temporal frequency for radiative transfer calculations in their forecast models. This strategy is known to affect forecast quality, which further motivates the use of ML-based radiative transfer parameterizations. This paper contributes to the discussion on how to incorporate physical constraints into an ML-based radiative parameterization, and how different neural network (NN) designs and output normalisation affect prediction performance. A random forest (RF) is used as a baseline method, with the European Centre for Medium-Range Weather Forecasts (ECMWF) model ecRad, the operational radiation scheme in the Icosahedral Nonhydrostatic Weather and Climate Model (ICON), used for training. Surprisingly, the RF is not affected by the top-of-atmosphere (TOA) bias found in all NNs tested (e.g., MLP, CNN, UNet, RNN) in this and previously published studies. At lower atmospheric levels, the RF is able to compete with all NNs tested, but its memory requirements quickly become prohibitive. For a fixed memory size, most NNs outperform the RF except at TOA. For the best emulator, we use a recurrent neural network architecture which closely imitates the physical process it emulates. We additionally normalize the shortwave and longwave fluxes to reduce their dependence from the solar angle and surface temperature respectively. Finally, we train the model with an additional heating rates penalty in the loss function.
Listening With Lasers: A Novel Interferometer Microphone

Interferometry is a technique which uses the interference of superimposed waves, such as the electromagnetic waves of light, to extract information from the paths that the waves have traversed. In a Michelson interferometer, this technique is achieved with a laser source split into two equal parts which are then reflected off of two mirrors and recombined to measure the relative difference between the two respective path-lengths. Building off of this standard design, I present a novel laser interferometer setup to be used specifically in measuring acoustic vibrations. The goal of the interferometry microphone design is to accurately record surrounding sound waves via a specialized mirror mount that acts as an acoustic diaphragm. To achieve this goal, a feedback loop is utilized to suppress unwanted noise and signal loss.
Community-based benchmarking improves spike rate inference from two-photon calcium imaging data

In recent years, two-photon calcium imaging has become a standard tool to probe the function of neural circuits and to study computations in neuronal populations. However, the acquired signal is only an indirect measurement of neural activity due to the comparatively slow dynamics of fluorescent calcium indicators. Different algorithms for estimating spike rates from noisy calcium measurements have been proposed in the past, but it is an open question how far performance can be improved. Here, we report the results of the spikefinder challenge, launched to catalyze the development of new spike rate inference algorithms through crowd-sourcing. We present ten of the submitted algorithms which show improved performance compared to previously evaluated methods. Interestingly, the top-performing algorithms are based on a wide range of principles from deep neural networks to generative models, yet provide highly correlated estimates of the neural activity. The competition shows that benchmark challenges can drive algorithmic developments in neuroscience.
Chemotaxonomy of domesticated grasses: a pathway to understanding the origins of agriculture

Abstract. The grass family (Poaceae) is one of the most economically important plant groups in the world today. In particular many major food crops, including rice, wheat, maize, rye, barley, oats and millet, are grasses that were domesticated from wild progenitors during the Holocene. Archaeological evidence has provided key information on domestication pathways of different grass lineages through time and space. However, the most abundant empirical archive of floral change – the pollen record – has been underused for reconstructing grass domestication patterns because of the challenges of classifying grass pollen grains based on their morphology alone. Here, we test the potential of a novel approach for pollen classification based on the chemical signature of the pollen grains measured using Fourier transform infrared (FTIR) microspectroscopy. We use a dataset of eight domesticated and wild grass species, classified using k-nearest neighbour classification coupled with leave-one-out cross validation. We demonstrate a 95 % classification success rate on training data and an 82 % classification success rate on validation data. This result shows that FTIR spectroscopy can provide enhanced taxonomic resolution enabling species level assignment from pollen. This will enable the full testing of the timing and drivers of domestication and agriculture through the Holocene.
Achieving urban food and nutrition security in the developing world

CONTENTS: Brief 1. Overview / James L. Garrett Brief 2. An urbanizing world / Martin Brockerhoff Brief 3. Rural-urban interdependence / Ceclia Tacoli Brief 4. Urban livelihoods and labor markets / Arjan de Haan Brief 5. Feeding the cities: food supply and distribution / Olivio Argenti Brief 6. The hidden significance of urban agriculture / Luc J.A. Mougeot Brief 7. Urbanization and the nutrition transition / Barry M. Popkin Brief 8. Urban women: balancing work and childcare / Patrice L. Engle Brief 9. Threats to urban health / Carolyn Stephens Brief 10. Programming for urban food and nutrition security / Timothy R. Frankenberger, James L. Garrett, and Jeanne Downen.
Predefined-time stabilisation of a class of nonholonomic systems

ABSTRACT This paper deals with the predefined-time stabilisation problem for a class of uncertain chained-form nonholonomic systems. Based on a novel generalised Lyapunov-like characterisation of predefined-time stability, new predefined-time controllers are introduced for a class of first and second order systems with matched perturbations. Contrary to existing finite-time and fixed-time schemes, an upper bound of the settling time is an easily tuneable control parameter. Then, these results for first and second order systems are used to design a switching strategy, which guarantees the predefined-time stability of the closed-loop system. The switching time and the settling-time can be easily tuned according to the control parameters. A benchmark example is presented to show the effectiveness of the proposed method.
Diabetes-specific variables associated with quality of life changes in young diabetic people: the type 1 diabetes Registry of Turin (Italy)

Background and aims: Type 1 diabetes (T1DM) affects young people during the most active years of their life. Our aim was to assess quality of life (QoL) and associated variables in a large cohort of adults with childhood-onset and adult-onset T1DM. Methods: A cohort of adult patients (18 years and older) from the T1DM Registry of Turin, Italy, was recruited. Clinical characteristics and Diabetes QoL (DQOL) questionnaire were assessed by standardized procedures. Results: 310 adults completed the questionnaire. Age and diabetes duration at assessment (mean ± SD) were 32.8±7.3 years and 17.3±6.3 years, respectively. DQOL and its subscores were in the lower quartiles of their distributions, indicating a good level of QoL. However, scores were significantly higher in females than in males, particularly for the subscale of diabetes-related worries. In multivariate analysis, lower QoL was independently associated with female sex (β=1.07, 95% CI 1.03-1.11, p=0.003), higher age at onset (β=1.03, 1.00-1.05, p=0.009), lower schooling (β=1.05, 1.00-1.09, p=0.02), higher fasting plasma glucose (β=1.03, 1.01-1.05, p=0.008), daily SMBG >4 (β=1.06, 1.01-1.10, p=0.01), severe hypoglycemia over the last year (β=1.06, 1.01-1.11, p=0.02), lower numbers of diabetologic visits (β=1.07, 1.01-1.13, p=0.02) and hypertension (β=1.06, 1.02-1.10, p=0.005). Autonomic neuropathy was associated with diabetes impact. Female sex (β=4.36, 2.43-7.83) and daily SMBG >4 (β=3.77, 1.72-8.30) were independently associated with worst level and CSII
5nW-Power DC-Coupled Digital Acquisition Front-End Based on Time-Multiplexed Digital Differential Amplification

—A reconﬁgurable, high-impedance, DC-coupled low-frequency digital acquisition front-end (DAFE) suitable to operate under a power supply voltage ranging from 0.2 to 1V down to 600pW power is presented in this paper. Matching-indifferent DC accuracy over a rail-to-rail input range is uniquely achieved by the new time-multiplexed digital differential am-pliﬁcation technique at ultra-low area and without chopping and auto-zeroing. A 180nm testchip of the proposed DAFE occupies 0.00945 mm 2 and draws 4.5nW at a 0.4V supply, has a 120 Hz gain-bandwidth product, with an in-band input noise of 11 . 3 µ V rms , a 137 µ V input offset voltage standard deviation, 65.7dB CMRR, 63.8dB PSRR, and provides a 46.5dB-SFDR, 6.9bit-ENOB digitized output at -12dBFS.
Explorer A systematic review on the effect of ICT on social support measures in healthcare

Background: With increased popularity in the use of ICT in healthcare to provide support to individuals, it is imperative to investigate the impact of ICT on social support measures in health and social care. Objective: This study aims to review literature on the effectiveness of ICT-based tools and intervention on social support measures with reference to health and illness. Methods: Relevant databases (PubMed\MEDLINE, clinicaltrials.gov and Cochrane Library) were systematically searched using a combination of key search terms. To be included in the review, studies had to be published in English language, involve human subjects, be published between 2000 and 2017, apply ICT intervention on a health-related condition and report the effect of ICT on social support measures. Results: The database search returned 4020 articles. After screening, 30 eligible papers were selected for the review. The studies were quite heterogeneous in terms of study design, age of participants, reported outcome, outcome measuring tool and health condition of participants. 20% of included studies were rated as low quality evidence, with a high risk of research bias. Over 75% of reviewed studies reported positive impact of ICT on social support measures. The results show that ICT interventions have a statistically significant positive impact on social support measures. Social network was found to be the ICT intervention with the most impact on social support measures. Conclusion: There is need for more high quality research on the effect of ICT on social support measures. The results of this systematic review suggest that ICT could effectively provide social support to individuals, although the degree of its effect could depend on the nature of ICT tool used and the well-being status of individuals. Further work in the use of ICT to provide social support for preventive healthcare is recommended. Also, more research investigating the effect of using Smartphone-based instant messaging applications (such as WhatsApp and Snapchat) and virtual reality technology on social support is encouraged.
Modélisation bayésienne des changements aux niches écologiques causés par le réchauffement climatique

This thesis presents some estimation methods and algorithms to analyse count data in particular and discrete data in general. It is also part of an NSERC strategic project, named CC-Bio, which aims to assess the impact of climate change on the distribution of plant and animal species in Québec. After a brief introduction to the concepts and definitions of biogeography and those relative to the generalized linear mixed models in chapters 1 and 2 respectively, my thesis will focus on three major and new ideas. First, we introduce in chapter 3 a new form of distribution whose components have marginal distribution Poisson or Skellam. This new specification allows to incorporate relevant information about the nature of the correlations between all the components. In addition, we present some properties of this probability distribution function. Unlike the multivariate Poisson distribution initially introduced, this generalization enables to handle both positive and negative correlations. A simulation study illustrates the estimation in the two-dimensional case. The results obtained by Bayesian methods via Monte Carlo Markov chain (MCMC) suggest a fairly low relative bias of less than 5% for the regression coefficients of the mean. However, those of the covariance term seem a bit more volatile. Later, the chapter 4 presents an extension of the multivariate Poisson regression with random effects having a gamma density. Indeed, aware that the abundance data of species have a high dispersion, which would make misleading estimators and standard deviations, we introduce an approach based on integration by Monte Carlo sampling. The approach remains the same as in the previous chapter. Indeed, the objective is to simulate independent latent variables to transform the multivariate problem estimation in many generalized linear mixed models (GLMM) with conventional gamma random effects density. While the assumption of knowledge a priori dispersion parameters seems too strong and not realistic, a sensitivity analysis based on a measure of goodness of fit is used to demonstrate
On the Spatial Scales to be Resolved by the Surface Water and Ocean Topography Ka-Band Radar Interferometer

The Surface Water and Ocean Topography (SWOT) mission aims to measure the sea surface height (SSH) at a high spatial resolution using a Ka-band radar interferometer (KaRIn). The primary oceanographic objective is to characterize the ocean eddies at a spatial resolution of 15 km for 68% of the ocean surface. This resolution is derived from the ratio between the wavenumber spectrum of the conventional altimeter (projected to submesoscale) and the SWOT SSH errors. While the 15-km threshold is useful as a global approximation of the spatial scales resolved by SWOT (SWOT scale), it can be misleading for regional studies. Here we revisit the problem using a high-resolution (~2-km horizontal grid spacing) tide-resolving global ocean simulation and map the SWOT scale as a function of location and season. The results show that the SWOT scale increases, in general, from about 15 km at low latitudes to ~30–45 km at mid- and high latitudes but with a large geographical dependence. A SWOT scale smaller than 30 km is expected in the high-latitude energetic regions. The SWOT scale varies seasonally as a result of the seasonality in both the noise and ocean signals. The seasonality also has a geographical dependence. Both eddies and internal gravity waves/tides contribute significantly to the SWOT scale variation. Our analysis provides model predictions for interpreting the anticipated observations from SWOT and guidance for the development of analysis methodologies.
A Robust Test for the Stationarity Assumption in Sequential Decision Making

Reinforcement learning (RL) is a powerful technique that allows an autonomous agent to learn an optimal policy to maximize the expected return. The optimality of various RL algorithms relies on the stationarity assumption, which requires time-invariant state transition and reward functions. However, deviations from stationarity over extended periods often occur in real-world applications like robotics control, health care and digital marketing, resulting in suboptimal policies learned under stationary assumptions. In this paper, we propose a model-based doubly robust procedure for testing the stationarity assumption and detecting change points in offline RL settings with certain degree of homogeneity. Our proposed testing procedure is robust to model misspecifi-cations and can effectively control type-I error while achieving high statistical power, especially in high-dimensional settings. Extensive comparative simulations and a real-world interventional mobile health example illustrate the advantages of our method in detecting change points and optimizing long-term rewards in high-dimensional, non-stationary environments.
Warunki meteorologiczne i biometeorologiczne południowo-zachodniego Svalbardu w 2010 roku

Zarys treści. Opracowanie nawiązuje do prezentowanych w latach ubiegłych artykułów, których celem jest przedstawienie warunków meteorologicznych i biometeorologicznych jakie występowały w południowej części Ziemi Wedela Jarlsberga, SW Svalbard. Dane, na podstawie których tego dokonano, zostały zgromadzone w roku 2010 w następujących punktach: na terasie morskiej (PSP), pobliskim szczycie górskim (FUG) i na Lodowcu Hansa: w strefie akumulacji (HT9) i poniżej linii równowagi (HT4). Zgromadzone dane meteorologiczne są w pełni oryginalne i nigdzie dotychczas niepublikowane. Na ich podstawie przeprowadzono analizę warunków meteorologicznych i biometeorologicznych jakie występowały w 2010 roku. Po raz pierwszy autorzy zastosowali wskaźnik UTCI (Universal Thermal Climate Index) do oceny warunków klimatu odczuwalnego tego obszaru. Słowa kluczowe: warunki meteorologiczne, bioklimat, Spitsbergen, automatyczne stacje meteorologiczne, UTCI.
Tea Leaves : How Humans Interpret Topic Models

Probabilistic topic models are a popular tool for the unsupervised analysis of text, providing both a predictive model of future text and a latent topic representation of the corpus. Practitioners typically assume that the latent space is semantically meaningful. It is used to check models, summarize the corpus, and guide exploration of its contents. However, whether the latent space is interpretable is in need of quantitative evaluation. In this paper, we present new quantitative methods for measuring semantic meaning in inferred topics. We back these measures with large-scale user studies, showing that they capture aspects of the model that are undetected by previous measures of model quality based on held-out likelihood. Surprisingly, topic models which perform better on held-out likelihood may infer less semantically meaningful topics.
Random Classification Noise does not defeat All Convex Potential Boosters Irrespective of Model Choice

A landmark negative result of Long and Serve-dio has had a considerable impact on research and development in boosting algorithms, around the now famous tagline that ”noise defeats all convex boosters”. In this paper, we appeal to the half-century+ founding theory of losses for class probability estimation, an extension of Long and Servedio’s results and a new general convex booster to demonstrate that the source of their negative result is in fact the model class , linear separators. Losses or algorithms are neither to blame. This leads us to a discussion on an otherwise praised aspect of ML, parameterisation .
USING MULTUvIEDIA TO SUPPORT COOPERATIVE SOFTWARE DEVELOPMENT

The aim of this paper is to propose a global solution to support Coopera.tive Soft ware Development (CSD) through a multimedia environment. CSD systems have as main goal to enable several users connected over a network to work together in order to develop software products. They have to solve problems such as: coherence main tenance of the software project through the distributed system by managing possible confücts between local versions of each group member and, above all, promote the necessary mechanisms for the inter-group awareness and integrity. We introduce here the strategies of our own CSD prototype: a computer supported cooperative work architecture for software development. It enables a group of developers ( 2 to 4), possibly located at remate places and connected over network, to develop software together. A cooperative multimedia editing envi ronment is available for the whole Development Cycle, enclosing mechanisms of computer-conferencing (text, audio and video communications).